Here - Air Quality 2016

Proceedings of Abstracts
9th International Conference on
Air Quality
Science and Application
Garmisch-Partenkirchen, 24-28 March 2014
Editors
Tonio Mitto, Joachim Fallmann, Urszula Mikolajczyk,
Peter Suppan, Vikas Singh and Ranjeet S. Sokhi
Proceedings of Abstracts
9th International Conference on
Air Quality
Science and Application
Garmisch-Partenkirchen, 24-28 March 2014
Editors
Tonio Mitto1, Joachim Fallmann1, Urszula Mikolajczyk1,
Peter Suppan1, Vikas Singh2 and Ranjeet S. Sokhi2
1
Institute of Meteorology and Climate Research (IMK-IFU) at the
Karlsruhe of Technology (KIT) in Garmisch-Partenkirchen
2
Centre for Atmospheric and Instrumentation Research (CAIR),
University of Hertfordshire, UK
Organised by
Karlsruhe Institute of Technology, Germany
University of Hertfordshire, UK
Published by the University of Hertfordshire
College Lane
Hatfield
AL10 9AB
United Kingdom
and
Institute of Meteorology and Climate Research (IMK-IFU)
at the Karlsruhe Institute of Technology (KIT)
Kreuzeckbahnstr. 19
82467 Garmisch-Partenkirchen
Germany
ISBN: 978-1-909291-20-1
Cover picture:
Dr. Jörg Bodenbender
Print:
Cityprint
Stephan Spindler
Amselstrasse 9
82467 Garmisch-Partenkirchen
Germany
Phone:
++49 8821 52 7 53
e-mail:
info@cityprint-gap.de
All inquiries to:
Professor Ranjeet S Sokhi
Centre for Atmospheric Science and Instrumentation Research (CAIR)
University of Hertfordshire
College Lane, Hatfield, AL0 9AB, UK
Tel: +44(0) 1707 284520 Fax: +44(0) 1707 284208
Email: r.s.sokhi@herts.ac.uk
Acknowledgement of Supporting Organisations
The support of the following organisations is gratefully acknowledged:
Karlsruhe Institute of Technology (KIT), Germany
University of Hertfordshire, UK
COST 728 Action on Enhancing Meso-Scale Meteorological Modelling Capabilities for Air
Pollution and Dispersion Applications
COST ES0602 Towards a European Network on Chemical Weather Forecasting and
Information Systems
The Aerosol Society, UK
American Meteorological Society (AMS)
Air & Waste Management Association (A&WMA)
European Meteorological Society (EMS)
World Meteorological Organisation (WMO) and the GAW Urban Research Meteorology and
Environment (GURME) programme
We are grateful for the attendance and support of the exhibitors:
Europa Environmental/ENVILYSE, www.europaenvironmental.com, www.envilyse.de
KISTERS AG, www.kisters.eu/air-quality
MLU Messtechnik für Luft und Umwelt GmbH, www.mlu.eu
Supporting U, www.WeCare4Air.co.uk
TSI GmbH, www.tsi.com
Conference Organising Committee
Ranjeet S Sokhi (Chair), University of Hertfordshire, UK
Peter Suppan (Chair of the Local Organising Committee), Karlsruhe Institute of Technology
(KIT/IMK-IFU), Germany
Vikas Singh, University of Hertfordshire, UK
Joachim Fallmann (KIT/IMK-IFU)
Matthias Lindauer (KIT/IMK-IFU)
Urszula Mikolajczyk (KIT/IMK-IFU)
Rongrong Shen (KIT/IMK-IFU)
Stefan Emeis (KIT/IMK-IFU)
Renate Forkel (KIT/IMK-IFU)
Klaus Schäfer (KIT/IMK-IFU)
Conference Secretariat, University of Hertfordshire
Dr Vikas Singh
Dr Aidan Farrow
Dr Kevin Douglas
Dr Charles Chemel
Dr Xavier Francis
Dr Xin Kong
Dr Heather Price (University of Southampton)
International Scientific and Advisory Committee
Professor Ranjeet S Sokhi (Chair), University of Hertfordshire, UK
Dr Peter Suppan, Karlsruhe Institute of Technology (KIT), Germany
Professor Bernard Fisher (University of Hertfordshire, UK)
Professor Nicolas Moussiopoulos, Aristotle University Thessaloniki, Greece
Professor Zissis Samaras, Aristotle University of Thessaloniki, Greece
Professor Alexander Baklanov, Danish Meteorological Institute, Denmark
Professor John Bartzis, University of West Macedonia, Greece
Dr Matthias Ketzel, NERI, Denmark
Professor Carlos Borrego, University of Aveiro, Portugal
Dr Trond Bohler, NILU, Norway
Professor Rainer Friedrich, IER University of Stuttgart, Germany
Professor Eugene Genikhovich, Main Geophysical Observatory, Russia
Professor Sue Grimmond, Kings College London, UK
Dr S T Rao, North Carolina State University, USA
Professor Greg Carmichael, University of Iowa, USA
Dr Liisa Jalkanen, World Meteorological Organisation
Professor Judy Chow, Desert Research Institute, USA
Professor Jaakko Kukkonen, Finnish Meteorological Institute, Finland
Professor Millán Millán, CEAM, Spain
Professor Roberto San Jose, Technical University of Madrid, Spain
Professor Michael Schatzmann, University of Hamburg, Germany
Dr Andreas Skouloudis, JRC, ISPRA
Dr Jacek Kaminski, York University, Canada
Professor James Sloan, University of Waterloo, Canada
Professor Selahattin Incecik, Technical University of Istanbul, Turkey
Dr R.K.M.Jayanty, RTI International, USA
Professor Hyo Choi, Gangneung-Wonju National University, Korea
Welcome address by the Lord Mayor
Ladies and Gentlemen,
I would like to welcome you cordially to the “Air Quality Conference“, which will be held at
our Congress Center in the heart of the climatic health resort Garmisch-Partenkirchen.
European Guidelines do also have a great impact on the municipal level like in determining
the judgment and control of the air quality within the scope of environmental compatibility.
The excellent Garmisch-Partenkirchen mountain air has made our town internationally
renowned besides our positive image as a winter sports resort. For this reason, I feel strongly
attached to the concept of your conference, as it is also our aim to preserve the high air
quality. We will therefore keep on our fight for bypass roads around our city. The enormous
heavy transit traffic - with over 3.000 trucks daily - endangers our healthy air.
I am glad that you have chosen Garmisch-Partenkirchen as site of your important event.
So I would like to thank the local Institute of Meteorology and Climate Research which is in
charge to organize the conference accompanied by the University of Hertfordshire in England.
Finally I would like to wish all attendees the desired success in realizing their goals as well as
pleasant and relaxing days within the Garmisch-Partenkirchen vacation area.
Thomas Schmid
1. Bürgermeister
Preface
This 9th International Conference in Air Quality - Science and Application is being held in
the beautiful town of Garmisch-Partenkirchen, Germany and is hosted by the Campus Alpine,
Institute of Meteorology and Climate Research (IMK-IFU) of the Karlsruhe Institute of
Technology (KIT). The meeting builds upon the series that began at the University of
Hertfordshire, UK in July 1996. Subsequent meetings have been held at the Technical
University of Madrid (1999), Loutraki, Greece (2001), Charles University, Prague (2003),
Valencia, Spain (2005), Cyprus (2007), Istanbul, Turkey (2009) and Athens, Greece (2012).
Despite increased control of air pollution, the quality of air that we breathe remains a key
issue to reduce health impacts and for achieving sustainable development. The growth in
urban areas is continuing in terms of population, transport, energy consumption and utilities.
Science has shown that impact from air pollution is not restricted to local scales but occurs
also on regional and global scales including interactions with climate change. Despite
improvements in technology, users still demand robust management and assessment tools to
formulate effective control policies and strategies for reducing the health impact of air
pollution.
The topics of papers presented at the conference reflect the diversity of scales, processes and
interactions affecting air pollution and its impact on health and the environment. As usual, the
conference is stimulating cross-fertilisation of ideas and cooperation between the different air
pollution science and user communities. In particular, there is greater involvement of city,
regional and global air pollution, climate change, policy and health communities at the
meeting.
Air Quality 2014 brings together scientists, users and policy makers from across the globe to
discuss the latest scientific advances in our understanding of air pollution and its impacts on
our health and environment. In addition to the scientific papers, the conference will also seek
to highlight applications and developments in management strategies and assessment tools for
policy and decision makers. This volume presents a collection of abstracts of papers presented
at the Conference. The main themes covered in the Conference include:
Air quality and impact on regional to global scales
Air quality management and policy
Emission models/inventories
Environmental and health impact resulting from air pollution
Environmental Meteorology - Processes and interactions
Measurement of air pollutants and source apportionment
Model development, evaluation and application studies
Wind tunnel/physical modelling
Use of remote sensing and satellite data for air quality research
Special session - Air quality and climate/meteorology interactions and feedbacks
Special session - Air quality forecasting and early warning systems
Special session - Air pollution in cities
Special session - Local and regional air quality services
Special session - Transport related air pollution - science and impacts
Ranjeet S Sokhi, University of Hertfordshire, UK
Peter Suppan, Karlsruhe Institute of Technology (KIT/IMK-IFU), Germany
March 2014
PART ONE: ORAL SESSIONS .............................................. 1 KEY NOTE SPEAKERS ...................................................................................... 2 WITHIN- AND BETWEEN-CITY CONTRASTS IN NITROGEN DIOXIDE AND MORTALITY IN 10 CANADIAN
CITIES ....................................................................................................................................................................................... 3 D. L. Crouse (1), P. A. Peters (2, 3), P. J. Villeneuve (4), M.-O. Proux (2), H. H. Shin (1), M. S. Goldberg (5), M.
Johnson (6), A. J. Wheeler (6), R. W. Allen (7), D. O. Atari (8), M. Jerrett (9), M. Brauer (10), J. R. Brook (11, 12), R. T.
Burnett (1) ESTABLISHING NEW AMBIENT AIR QUALITY STANDARDS FOR PM2.5: THE CHINESE EXPERIENCE ............... 4 J. C. Chow (1,2), J. G. Watson (1,2), J. J. Cao(2) AN OBSERVATIONAL PERSPECTIVE OF THE IMPACT OF ATMOSPHERIC WEATHER STATES ON CARBON
MONOXIDE LEVELS IN THE FREE TROPOSPHERE OVER THE NORDIC COUNTRIES.............................................. 5 M. A. Thomas (1) and A. Devasthale (1) INTEGRATED ASSESSMENT OF POLICIES FOR REDUCING HEALTH IMPACTS OF AIR POLLUTION
CAUSED BY TRANSPORT IN EUROPE ................................................................................................................................ 6 R. Friedrich, J. Roos, C. Schieberle DEVELOPMENTS IN REGIONAL AND LOCAL AIR QUALITY MONITORING AND FORECASTING –
RESULTS OF PASODOBLE .................................................................................................................................................... 7 T. Erbertseder (1), D. Balis (2), C. Bergemann (1), L. Blyth (3), D. Carruthers (4), S. Choudrie (5), A. De Rudder (6),
W. Di Nicolantonio (7), H. Elbern (8), H. Eskes (9), E. Friese (8), K. Ganev (10), T. Holzer-Popp (1), J. Kukkonen
(11), O. Lesne (12), D. Melas (2), J. Meyer-Arnek (1), F. Prata (13), P. Sicard (12), N. Smeets (3), M. Sofiev (11), A.
Stidworthy (4), R. Timmermans (14), N. Veldeman (3), H. Zelle (15) and the PASODOBLE consortium AIR QUALITY MANAGEMENT IN CITIES – A NEVER ENDING STORY? ..................................................................... 8 U. Reuter (1), R. Kapp (1) THE REVIEW OF AIR POLICY – WHAT IS IN FOR THE MEASUREMENT COMMUNITY ........................................... 9 A. Borowiak (1) and D. Buzica-Widlowski (2) ENVIRO-HIRLAM ONLINE INTEGRATED METEOROLOGY-CHEMISTRY MODELLING SYSTEM:
STRATEGY, METHODOLOGY, DEVELOPMENTS AND APPLICATIONS .................................................................... 10 A. Baklanov (1), U. Korsholm (1), R. Nuterman (2), K. P. Nielsen (1), B. H. Sass(1), A. Mahura (1), A. Rasmussen(1),
B. Sørensen (2), E. Kaas (2), I. González-Aparicio (3), A. Mažeikis (4), A. Kurganskiy (5), E. Morozova (5), S. Ivanov
(6), Y. Palamarchuk (6), A. Zakey (1), J. Chenevez (1), A. Gross (1), K. Lindberg (1) EMEP MODEL SIMULATIONS OF PM LEVELS IN EUROPE UNDER THE GOTHENBURG PROTOCOLL AND
MEASURES TO REDUCE FURTHER AMMONIA EMISSIONS FROM AGRICULTURE ............................................... 11 C. Guerreiro (1), M. Beauchamp, B. Bessagnet (2), S. Tsyro (3) USING REGIONAL AIR QUALITY MODELS FOR ASSESSING THE EFFICACY OF EMISSION CONTROL
STRATEGIES IN MEETING THE RELEVANT AMBIENT AIR QUALITY STANDARDS ............................................. 12 P. S. Porter (1), S. T. Rao (2), C. Hogrefe (3), and R. Mathur (3) AIRBORNE PARTICULATE MATTER AND ASSOCIATED HEALTH IMPACTS: NEW DEVELOPMENTS AND
IMPLICATIONS FOR EUROPE............................................................................................................................................. 13 R. S. Sokhi and TRANSPHORM Partners AIR QUALITY AND IMPACT ON LOCAL TO GLOBAL SCALES ............ 14 GLOBAL MODEL SIMULATIONS OF THE IMPACT OF TRANSPORT SECTOR EMISSIONS ON
ATMOSPHERIC AEROSOL AND CLIMATE ...................................................................................................................... 15 M. Righi (1), J. Hendricks (1), R. Sausen (1) ATMOSPHERIC NITROGEN DEPOSITION TO THE BALTIC SEA – NORMALISATION APPROACH ....................... 16 J. Bartnicki ASSESSMENT OF CONTRIBUTION TO PM10 CONCENTRATIONS FROM LONG RANGE TRANSPORT OF
POLLUTANTS USING WRF/CHEM OVER A SUBTROPICAL URBAN AIRSHED ........................................................ 17 M. Gupta and M. Mohan MODELING HIGH AEROSOL LOADS IN CHINA IN JANUARY 2013 ............................................................................ 18 V. Matthias (1), A. Aulinger (1), J. Bieser (1), B. Geyer (1), M. Quante (1) AIR QUALITY AT THE STREET LEVEL IN CYPRUS ....................................................................................................... 19 I. Douros (1), L. Kalognomou (1), E. Chourdakis (1), N. Moussiopoulos(1) and S. Kleanthous (2) INTEGRATED ASSESSMENT USING OBSERVATIONS AND MODELLING FOR AIR QUALITY MANAGING IN
SANTA CRUZ DE TENERIFE (CANARY ISLANDS) ......................................................................................................... 20 J. M. Baldasano (1,2) A. Soret (1), M. Guevara (1), F. Martínez (1), S. Gassó(1,2) i
A STUDY OF OZONE CONCENTRATIONS AND TRENDS ACROSS EUROPE: 1996-2010.......................................... 21 T. Chatterton (1), E. Hayes (1), J. Barnes (1), J. Longhurst (1), D. Laxen (1) J. Irwin (1), H. Bach (2), J. Brandt (2), J.
H. Christensen (2), T. Ellermann (2), C. Geels (2), O. Hertel (2), A. Massling (2), H. Ø. Nielsen (2), O. K. Nielsen (2),
C. Nordstrøm (2), J. K. Nøjgaard (2), H. Skov (2), F. Pelsy (3) and T. Zamparutti (3) A MODELLISTIC STUDY OF THE INFLUENCE OF AN HARBOUR SHIP EMISSIONS ON REGIONAL AIR
QUALITY IN A MEDITERRANEAN AREA ........................................................................................................................ 22 R. Cesari (1), A.Maurizi (2), F. Tampieri (2) MODELING TRENDS IN AIR POLLUTANT CONCENTRATIONS AND THEIR OPTICAL AND RADIATIVE
PROPERTIES OVER THE NORTHERN HEMISPHERE USING THE COUPLED WRF-CMAQ MODEL ....................... 23 R. Mathur, J. Xing, G. Sarwar, J. Pleim AIR QUALITY MANAGEMENT AND POLICY ............................................ 24 STRENGTHS AND WEAKNESSES OF THE EU AIR QUALITY STANDARDS FOR PARTICULATE MATTER ........ 25 K. D. van den Hout (1), C. Nagl (2), W. Spangl (2) and B. Conlan (3) CAN A STRINGENT REDUCTION IN EUROPEAN EMISSIONS HELP SWEDEN REACH NATIONAL
ENVIRONMENTAL QUALITY OBJECTIVES FOR ACIDIFICATION AND EUTROPHICATION? ............................... 26 S. Åström and M. Lindblad MODELLING REAL WORLD ROAD DUST ABATEMENT MEASURES: AN APPLICATION OF THE NORTRIP
MODEL ................................................................................................................................................................................... 27 I. Sundvor (1) and B. R. Denby (1) THE IMPACT OF LOW EMISSION ZONE AND HEAVY TRAFFIC BAN IN MUNICH ON THE REDUCTION OF
PM10 IN AMBIENT AIR ......................................................................................................................................................... 28 J. Cyrys (1,2), V. Fensterer (3), H. Küchenhoff (3), B. Bauer (3), H.-E. Wichmann (4), S. Breitner (1), A. Schneider (1),
A. Peters (1) ATMO-IDEE: RHINE TRANSBOUNDARY ATMOSPHERIC PREVENTION IN THE EURODISTRICT
STRASBOURG-ORTENAU AND IN THE UPPER RHINE ................................................................................................. 29 R. Deprost (1), H. Scheu-Hachtel (2), J. Kleinpeter (1), E. Herber (1), S. Mazurais (1), C. Schillinger (1), T. Leiber (2),
F. Brocheton (3), C. Pesin (3), J. Galineau (3), L. Zilliox (4), G. Najjar (5) INVENTORY AND EFFECTIVENESS OF MEASURES TO IMPROVE AIR QUALITY IN GERMANY ........................ 30 F. Pfäfflin, V. Diegmann, H. Wursthorn AMMONIA AND NITROGEN OXIDES EMISSIONS REDUCTION INFLUENCE ON AIR QUALITY OVER THE
PO VALLEY............................................................................................................................................................................ 31 E. Angelino (1), M. P. Costa (2), A. D’Allura (2), S. Finardi (2), G. Fossati (1), G. Lanzani (1), E. Peroni (1), P.
Radice (2), C. Silibello (2) ASSESSMENT OF CO-BENEFITS FROM CLIMATE AND AIR QUALITY POLICIES WITH THE TM5-FASST
TOOL ....................................................................................................................................................................................... 32 J. Leitao (1), R. Van Dingenen (1), F. Dentener (1), S. Rao (2) THE COMPARISON OF COSTS OF POLICIES AIMED AT REDUDING AIR QUALITY INDUCED HEALH RISKS,
HEALTH BENEFITS AND PERCEIVED VALUES IN FINLAND ...................................................................................... 33 J. Kutvonen (1,2), A. Asikainen (1), P. Pasanen (2) and O. Hänninen (1) DEVELOPMENT AND APPLICATION OF AIR QUALITY AND
RELATED MODELS ......................................................................................... 34 PLSR AND ANN APPROACHES TO ESTIMATE HEAVY METAL LEVELS IN AIRBORNE PM10.............................. 35 G. Santos, I. Fernández-Olmo and A. Irabien APPLICATION AND DEVELOPMENT OF THE OPERATIONAL STREET POLLUTION MODEL (OSPM) TO
COMPLEX GEOMETRIES AND DRY CLIMATES ............................................................................................................. 36 T.-B. Ottosen (1,2) K. Kakosimos (1), M. Ketzel (2), O. Hertel (2) and R. Berkowicz (2) MULTIPHASE CHEMISTRY OF AMINES RELEASED FROM CCS TECHNIQUES: REACTIVITY EXPERIMENTS
AND NUMERICAL MODELING .......................................................................................................................................... 37 C. J. Nielsen (1), C. Weller (2), A. Tilgner (2), R. Schrödner (2) R. Wolke (2) and H. Herrmann (2) IMPACT OF MERCURY CHEMISTRY ON REGIONAL CONCENTRATION AND DEPOSITION PATTERNS ........... 38 J. Bieser (1), V. Matthias (1), A. Aulinger (1), B. Geyer (1), I. Hedgecock (2), F. DeSimone (2), C. Gencarelli (2), O.
Travnikov (3) MODELLING BLACK CARBON CONCENTRATIONS IN TWO BUSY CANYON STREETS IN BRUSSELS
USING OSPMBC .................................................................................................................................................................... 39 O. Brasseur (1a), P. Declerck (1b), B. Heene (2) and P. Vanderstraeten (1a) REGIONAL MODELLING OF THE TROPOSPHERIC MULTIPHASE SYSTEM USING COSMO-MUSCAT:
SENSITIVITY ON DETAIL OF CLOUD MICROPHYSICS AND CHEMICAL MECHANISM ........................................ 40 R. Schrödner, A. Tilgner and R. Wolke ii
USE OF ARTIFICIAL NEURAL NETWORKS FOR PM10 RE-ANALYSIS OVER NORTHERN ITALY ........................ 41 C. Carnevale (1), G. Finzi (1), E. Pisoni (2), A. Pederzoli (1), E. Turrini (1), M. Volta (1) USING WRF-CHEM WITH HIGH RESOLUTION EMISSION DATA TO MODEL THE EFFECT OF URBAN HEAT
ISLAND MITIGATION STRATEGIES ON URBAN AIR QUALITY .................................................................................. 42 J. Fallmann (1), S. Emeis (1), P. Suppan (1), R. Forkel (1), G. Grell (2), S. McKeen (2) PM AIR QUALITY ASSESSMENT IN PMINTER – BRIDGING THE GAPS – A NEW INTEGRAL APPROACH ......... 43 U. Uhrner (1), R. Reifeltshammer (1), M. Steiner (1), B. Lackner (1), P. J. Sturm(1) and R. Forkel (2) CAN A SIMPLE INTERPOLATION MODEL PERFORM BETTER FOR AIR QUALITY ASSESSMENT THAN
DATA ASSIMILATED DETERMINISTIC MODELS? ......................................................................................................... 44 S. Janssen (1), B. Maiheu (1), N. Veldeman (1), P. Viaene (1), K. De Ridder (1), D. Lauwaet (1), F. Deutsch (1), F.
Fierens (2), E. Trimpeneers (2), L. Vancraeynest (3) and C. Mensink (1) EMISSION MODELS / INVENTORIES ........................................................... 45 REAL-WORLD VERSUS COMPLIANCE SOURCE TESTING: GETTING MORE INFORMATION FOR LESS
MONEY ................................................................................................................................................................................... 46 J. G. Watson (1), J. C. Chow (1) A COMPREHENSIVE INVENTORY OF EMISSIONS FROM SHIP TRAFFIC IN EUROPE IN 2011 .............................. 47 J.-P. Jalkanen, L. Johansson and J. Kukkonen A MODEL FOR FEEDBACKS BETWEEN BIOGENIC EMISSIONS AND URBAN AIR QUALITY ............................... 48 R. Grote (2), G. Churkina (1), T. Butler (1), C. Morfopoulos (3) PREPARATION OF MODELLING EMISSIONS BASED ON RECENT RECOMMENDATIONS FROM UK
NATIONAL ATMOSPHERERIC EMISSIONS INVENTORY STUDIES. ........................................................................... 49 A. Fraser (1), S. Beevers (2), X. Francis (3), N. Kitwiroon (2), T. P. Murrells (1), R. A. Rose (1), R. S. Sokhi (3) OPEN CHALLENGES IN LOCAL ATMOSPHERIC EMISSION INVENTORIES ............................................................. 50 E. Angelino, A. Marongiu, G. Fossati, M. Moretti THE SHIPPING EMISSIONS AND THE COSTS OF EMISSION REGULATIONS IN THE NORTHERN EUROPEAN
EMISSION CONTROL AREA ............................................................................................................................................... 51 L. O. Johansson (1), J.-P. Jalkanen (1), J. Kalli (2) and J. Kukkonen (1) ENVIRONMENTAL AND HEALTH IMPACT RESULTING FROM AIR
POLLUTION....................................................................................................... 52 AN INTEGRATED BAP (PAHS) APPROACH TO ESTIMATE CHILDREN AND ELDERLY EXPOSURE IN THE
CITY OF ROME, ITALY ........................................................................................................................................................ 53 C. Gariazzo (1), M. Lamberti (1), C. Silibello (2), S. Finardi (2), P. Radice (2), A. D’Allura (2), M. Gherardi (1), A.
Cecinato (3), D. Porta (4), F. Sacco (5), O. Hänninen (6), A. Pelliccioni (1) CARDIOVASCULAR HOSPITAL ADMISSIONS DUE TO MULTIPLE AIRBORNE EXPOSURES UNDER THE
CONDITIONS OF SANTIAGO DE CHILE ........................................................................................................................... 54 U. Franck (1), A. M. Leitte (1), P. Suppan (2) ENHANCING PM EPIDEMIOLOGICAL CONCENTRATION-RESPONSE FUNCTIONS BY INCORPORATING
LUNG DEPOSITION AND OXIDATIVE STRESS ............................................................................................................... 55 D. A. Sarigiannis, S. Karakitsios, M. Kermenidou HIGH-RESOLUTION MODELLING OF HEALTH IMPACTS FROM AIR POLLUTION USING THE INTEGRATED
MODEL SYSTEM EVA .......................................................................................................................................................... 56 J. Brandt (1), M. S. Andersen (1), J. Bønløkke (2), J. H. Christensen (1), C. Geels (1), K. M. Hansen (1), S. S. Jensen
(1), M. Ketzel (1), M. S. Plejdrup (1), T. Sigsgaard (2), J. D. Silver (1) SHORT-TERM EFFECTS OF AIR TEMPERATURE ON MORTALITY AND EFFECT MODIFICATION BY AIR
POLLUTION IN THREE CITIES OF BAVARIA, GERMANY ............................................................................................ 57 S. Breitner (1), K. Wolf (1), R. B. Devlin (2), D. Diaz-Sanchez (2), A. Peters (1), A. Schneider (1) DETERMINANTS OF PERCEIVED AIR POLLUTION ANNOYANCE AND EXPOSURE-RESPONSE
RELATIONSHIP FOR ANNOYANCE AND PARTICULATE MATTER ............................................................................ 58 M. Machado (1), J. M. Santos (2), N. C. Reis Jr.(2), V. A. Reisen (2) CARCINOGENIC RISK OF PAHS IN PARTICULATE MATTER FROM BIOMASS COMBUSTION ............................ 59 D. A. Sarigiannis (1,2), D. Zikopoulos (1), M. Kermenidou (1), S. Nikolaki (1,2), S. Karakitsios (1,2) EVALUATION OF AIR QUALITY IMPACTS WITH AN INTEGRATED ASSESSMENT MODEL FOR SPAIN ........... 60 M. Vedrenne, R. Borge, J. Lumbreras and M. E. Rodríguez POWER PLANTS AND THE INDUSTRIAL EMISSIONS DIRECTIVE: AIR QUALITY-RELATED IMPACTS
UNDER VARIABLE ENVIRONMENTAL AND TECHNICAL SETTINGS ....................................................................... 61 T. M. Bachmann, J. van der Kamp iii
LAND USE REGRESSION MODELLING FOR AIR QUALITY EXPOSURE: A STEP IN THE WRONG DIRECTION . 62 B. R. Denby OUTDOOR AIR DOMINATES BURDEN OF DISEASE FROM INDOOR EXPOSURES.................................................. 63 O. Hänninen (1), A. Asikainen (1), P. Carrer (2), S. Kephalopoulos (3), E. de Oliveira Fernandes (4), P. Wargocki (5) PM ATTRIBUTED MORTALITY AND MORBIDITY DUE TO BIOMASS USE IN THESSALONIKI –
ESTIMATION OF SOCIOECONOMIC COST ...................................................................................................................... 64 D.A. Sarigiannis (1,2), S. Karakitsios (1,2), M. Kermenidou (1) WAVELET ANALYSIS OF HEALTH EFFECT OUTCOMES ATTRIBUTRABLE TO AIR QUALITY AND
ASSOCIATED VARIABLES .................................................................................................................................................. 65 V. Garcia (1), P. S. Porter (2), E. Gégo (2), S. T. Rao (3) and S. Lin (4) IMPROVED HEALTHCARE THROUGH NEW AIR POLLUTION RISK TOOL ............................................................... 66 P. Sicard (1), C. Talbot (1), O. Lesne (1), A. Mangin (1), R. Collomp (2), N. Alexandre (2), H. Zelle (3), A. Mika (3), D.
Melas (4), D. Balis (4), A. Poupkou (4), Th. Giannaros (4), V. Costigliola (5) and D. Chloros (5) ASSESSING INDIVIDUAL EXPOSURE TO BLACK CARBON IN THE EUROPEAN DISTRICT IN BRUSSELS
USING OSPMBC MODELLING AND MOBILE MEASUREMENTS ................................................................................... 67 P. Declerck (1a), O. Brasseur (1b), B. Heene (2) and P. Vanderstraeten (1b) ENVIRONMENTAL METEOROLOGY – PROCESSES AND
INTERACTIONS ................................................................................................ 68 IMAGING OF NITROGEN DIOXIDE DURING AND AFTER AN ACTIVE LIGHTNING STORM................................. 69 R. R Graves1, R. J. Leigh1, E. Arnone2, J. P. Lawrence1, K. Faloon3 and P. S. Monks3 INLET AND OUTLET SHAPE DESIGN OF NATURAL CIRCULATION BUILDING VENTILATION SYSTEMS ....... 70 J. J. Swiegers, R. T. Dobson INFLUENCE OF SURFACE AND SUBSIDENCE THERMAL INVERSION ON PM2.5 AND BLACK CARBON
CONCENTRATION ................................................................................................................................................................ 71 E. Gramsch (1), D. Cáceres (1), P. Oyola (2), F. Reyes (2), Y. Vasquez (2), M. A. Rubio (3) PERFORMANCE OF EUROPEAN CHEMISTRY-TRANSPORT MODELS AS FUNCTION OF HORIZONTAL
SPATIAL RESOLUTION ....................................................................................................................................................... 72 C. Cuvelier (1), P. Thunis (1), D. Karam (1), M. Schaap (2), C. Hendriks (2), R. Kranenburg (2), H. Fagerli (3), A.
Nyiri (3), D. Simpson (3), P. Wind (3), M. Schultz (3), B. Bessagnet (4), A. Colette (4), E. Terrenoire (4), L. Rouil (4),
R. Stern (5), A. Graff (6), J. M. Baldasano (7), M. T. Pay (7) INTENSIVE RESEARCH-GRADE NETWORK FOR TURBULENCE OBSERVATIONS OVER HELSINKI .................. 73 C.R. Wood (1), R.D. Kouznetsov (1,2), A. Nordbo (3), S. Joffre (1), A. Hirsikko (1,4), A. Karppinen (1), L. Järvi (3), P.
Ukkonen (1,3), T. Vesala (3), V. Vakkari (1), E.J. O'Connor (1,5), J. Kukkonen (1) MEASUREMENT OF AIR POLLUTANTS AND SOURCE
APPORTIONMENT ........................................................................................... 74 PLUMES WITH ELEVATED MERCURY CONCENTRATIONS OBSERVED DURING CARIBIC FLIGHTS IN 2005
- 2013 ....................................................................................................................................................................................... 75 F. Slemr (1), A. Weigelt (2), R. Ebinghaus (2), C. A. M. Brenninkmeijer (1), T. Schuck (1), A. Rauthe-Schöch (1), M.
Hermann (3), P. van Velthoven (4), D. Oram (5), A. Zahn (6) and H. Ziereis (7) A SYNERGIC APPROACH FOR PM2.5 SOURCE APPORTIONMENT THROUGH RECEPTOR MODELLING AND
CHEMICAL TRANSPORT MODEL SIMULATIONS .......................................................................................................... 76 P. Brotto (1)(3), M. C. Bove (1)(3), F. Cassola (1)(3), E. Cuccia (1)(3), D. Massabò (1)(3), A. Mazzino (2)(3) and P.
Prati (1)(3) SOURCE IDENTIFICATION OF TRACE METALS IN URBAN/INDUSTRIAL MIXED SITES OF THE
CANTABRIA REGION (NORTHERN SPAIN) ..................................................................................................................... 77 I. Fernández-Olmo (1), C. Andecochea (1), S. Ruiz (1) and A. Irabien (1) BUILDING AND CONSTRUCTION ACTIVITIES: A SOURCE OF ULTRAFINE PARTICLES? .................................... 78 P. Kumar (1, 2), M. Mulheron (1) HIGHLY TIME- AND SIZE-RESOLVED MEASUREMENTS OF TRACE ELEMENTS DURING CLEARFLO,
LONDON ................................................................................................................................................................................. 79 S. Visser (1), M. Furger (1), U. Flechsig (2), K. Appel (3*), R. Dressler (4), P. Zotter (1), J. G. Slowik (1), A. S. H.
Prevot (1), U. Baltensperger (1) POLYCYCLIC AROMATIC HYDROCARBONS IN PM1: SEASONAL CHANGES AND SOURCES
IDENTIFICATION USING DIAGNOSTIC RATIOS ............................................................................................................ 80 D. M. Agudelo-Castañeda (1). E. C. Teixeira (1,2), and H. Silveira (2) MOBILE MONITORING OF AIR QUALITY IN THE CITY OF ROTTERDAM ................................................................ 81 M. H. Voogt (1), P. J. van der Mark (1), A. R. A. Eijk (1), P. van Breugel (2) iv
NEAR-ROAD PARTICLE NUMBER CONCENTRATIONS IN KUWAIT DURING SUMMERTIME.............................. 82 A. N. Al-Dabbous (1), P. Kumar (1) (2) MULTIPLE CH4 SOURCE IDENTIFICATION FOR A BIOGAS PLANT .......................................................................... 83 M. Piringer (1), M. Hrad (2) and M. Huber-Humer (2) MONITORING OUTDOOR AIR PARTICLE CONCENTRATIONS WITH THE PPS-M SENSOR ................................... 84 A. Järvinen (1), H. Kuuluvainen (1), A. Rostedt (1), J. V. Niemi (2), L. Pirjola (3), R. Hillamo (4), J. Keskinen (1) and
T. Rönkkö (1) REAL-TIME MEASUREMENTS OF BIOAEROSOLS IN URBAN ENVIRONMENT ....................................................... 85 S. Saari (1), J. V. Niemi (2), T. Rönkkö (1), H. Kuuluvainen (1), A. Järvinen (1), L. Pirjola (3), R. Hillamo (4), J.
Keskinen (1) QUANTIFICATION OF ORGANIC, ELEMENTAL AND BLACK CARBON IN THE RUHR AREA, GERMANY ........ 86 M. Küpper (1), U. Quass (1), H. Kaminski (1), A. John (1), T. A. J. Kuhlbusch (1), S. Leinert (2), J. Geiger (2), L.
Breuer (2), D. Gladtke (2), A. Olschewski (2), T. J. Schuck and U. Pfeffer (2) CHARACTERIZATION OF SOURCES AND PROCESSES OF ORGANIC AEROSOLS SAMPLED AT REVIN,
FRANCE, DURING THE EMEP 2012 SUMMER CAMPAIGN ........................................................................................... 87 A. Setyan (1,2), V. Crenn (1,2,3), V. Riffault (1,2), J.-L. Jaffrezo (4), A. Waked (4), S. Sauvage (1,2), J.-L. Besombes
(5), J.-E. Petit (3,6), O. Favez (6), T. Leonardis (1,2), J. Sciare (3), N. Locoge (1,2) SOURCE IDENTIFICATION OF FINE PARTICLE EMISSIONS IN URBAN AIR BY MOBILE MEASUREMENTS .... 88 L. Pirjola (1), J. V. Niemi (2), A. Kousa (2), S. Saarikoski (3), S. Carbone (3), H. Kuuluvainen (4), A. Järvinen (4), T.
Rönkkö (4), J. Keskinen (4), R. Hillamo (3) VOLATILE ORGANIC COMPOUNDS SOURCE APPORTIONMENT IN PARIS: FOCUS ON THE TRAFIC AND
WOOD BURNING SOURCES ............................................................................................................................................... 89 V. Gros(1), A. Baudic(1), R. Sarda-Esteve (1), H. Petetin (2), O. Sanchez (2), A. Rosso (2), O. Perrusel (2), T. le Priol
(3), J. F. Petit (3), J.-E. Petit (1), O. Favez (4) C. Kalogridis (1), N. Bonnaire (1), B. Bonsang (1), I. Xueref-Rémy (1),
L. Ammoura (1), and J. Sciare (1) OBSERVATION OF TRACE GAS DISTRIBUTIONS WITH AN AIRBORNE IMAGING DOAS INSTRUMENT .......... 90 D. Pöhler (1), S. General (1), J. Zielcke (1), U. Frieß (1), P. Shepson (2), B. Stirm (2), W. Simpson (3), H. Sihler (1,4),
K. P. Heue (1,4), D. Walter (1,4), K. Weber (5), C. Fischer (5) and U. Platt (1) SECONDARY POLLUTANTS IN THE LAKE TAHOE BASIN, USA................................................................................. 91 B. Zielinska (1), A. Bytnerowicz (2), A. Gertler (1), M. McDaniel (1) and J. Burley (3) EFFECTS OF WOOD COMBUSTION EMISSIONS ON THE AIR QUALITY IN RESIDENTIAL AREAS MEASUREMENTS AND MODELLING ............................................................................................................................... 92 G. Baumbach (1), M. A. Bari, (1), W. Juschka (1), M. Struschka (1), G. Scheffknecht (1), B. Kuch (2), W. Baechlin (3) SOURCE APPORTIONMENT OF URBAN FINE PARTICLE NUMBER CONCENTRATION DURING
SUMMERTIME IN BEIJING.................................................................................................................................................. 93 Z. R. Liu (1), B. Hu (1), Q. Liu (1,2), Y. Sun (1) and Y. S. Wang (1) 5 YEAR MEASUREMENTS OF LUNG DEPOSITED SURFACE AREA CONCENTRATIONS AND PARTICLE
NUMBER SIZE DISTRIBUTIONS AT AN URBAN BACKGROUND STATION IN GERMANY .................................... 94 J. Meyer (1), H. Kaminski (1), U. Quass (1), C. Nickel (1), M. Küpper (1), and T. A. J. Kuhlbusch (1) A NOVEL METHODOLOGY FOR ASSESSING THE SPATIAL REPRESENTATIVENESS OF AIR QUALITY
MONITORING STATIONS IN EUROPE .............................................................................................................................. 95 E. Solazzo (1), O. Kracht (1), D. Carruthers (2), M. Gerboles (1), J. Stocker (2), S. Galmarini (1) CHEMICAL COMPOSITION OF PM2.5 AND PM10: IMPLICATIONS FOR SOURCE APPORTIONMENT
STUDIES OVER EUROPE ..................................................................................................................................................... 96 H. Price (1), K. Douglas (1), R. S. Sokhi (1), M. Keuken (2), M. Kermenidou (3), D. A. Sarigiannis (3) ANALYSIS OF AN EPISODE OF HIGH PM POLLUTION IN THE PO VALLEY, ITALY OBSERVED IN THE
FRAMEWORK OF THE SUPERSITO PROJECT ................................................................................................................. 97 V. Poluzzi1, D. Bacco2, G. Bonafè1, P. Ugolini1, C. Maccone1, S. Ferrari1, and I. Ricciardelli1 ANALYSIS OF ATMOSPHERIC AEROSOL (PM2.5) IN RIO DE JANEIRO CITY, BRAZIL........................................... 98 L. H. M. dos Santos (1), A. A. F. S. Kerr (1), T. G. Veríssimo (1), M. de Fatima Andrade (2), R. M. de Miranda (3), A.
Fornaro (2), and P. Saldiva (4) COMPOSITION AND SOURCE APPORTIONMENT OF NON-METHANE VOLATILE ORGANIC COMPOUNDS
(NMVOCS) IN BEIRUT, LEBANON ..................................................................................................................................... 99 T. Salameh (1,2,3), S. Sauvage (1,2), C. Afif (3), A. Borbon (4), N. Locoge (1,2) PARTICULATE MATTER SOURCE APPORTIONMENT IN THE AREA OF THESSALONIKI, GREECE. ................. 100 D.E. Saraga (1, 2), E. Tolis (1), E.M. Kougioumtzidis (1) and J.G. Bartzis (1) v
MODEL EVALUATION STUDIES ................................................................ 101 EVALUATION OF THE ON-LINE NMMB/BSC-CTM MODEL GAS-PHASE RESULTS ON THE EUROPEAN
DOMAIN FOR 2010 IN THE FRAMEWORK OF THE AQMEII-PHASE2 INITIATIVE ................................................. 102 A. Badia (1),O. Jorba (1) CAN WE EXPLAIN THE OBSERVED DECREASE IN SECONDARY INORGANIC AEROSOL AND ITS
PRECURSORS BETWEEN 1990 AND 2009 OVER EUROPE USING LOTOS-EUROS? ................................................ 103 S. Banzhaf (1), M. Schaap (2), R. Kranenburg (2), A. Manders (2), A. Segers (2), A. Visschedijk (2), H. Denier van der
Gon (2), J. Kuenen (2), C. Hendriks (2), E. van Meijgaard (3), L. van Ulft (3) and P. Builtjes (1/2) MODELLING THE SPATIAL AND TEMPORAL PATTERN OF AMMONIA OVER THE PO VALLEY...................... 104 V. Capiaghi (1,2), G. Pirovano (2), C. Colombi (3), G. Lonati (1), G. M. Riva (2), A. Toppetti (2), V. Gianelle (3), A.
Balzarini (2) COMPARISON OF MEASURED DATA AND MODEL-RESULTS DURING PEGASOS-CAMPAIGN 2012 ................ 105 C. Ehlers, D. Klemp, A. Wahner, H. Elbern INVESTIGATING RELATIONSHIPS BETWEEN MODEL PERFORMANCE AND MODELING OUTCOMES .......... 106 N. Kumar (1), B. Koo (2), O. Nopmongcol (2), T. Odman (3), A. G. Russell (3), E. M. Knipping (1), G. Yarwood (2) AIR QUALITY OVER ASIA, A MODELLING STUDY WITH WRF-CHEM ................................................................... 107 A. K. Petersen (1), G. P. Brasseur (1), R. Kumar (2) LOCAL-SCALE MODELLING OF ACCIDENTAL RELEASES IN BUILT ENVIRONMENTS – SELECTED
RESULTS OF THE ‘MICHELSTADT’ MODEL EVALUATION EXERCISE IN COST ACTION ES1006 ..................... 108 K. Baumann-Stanzer (1), B. Leitl (2), S. Trini Castelli (3), M. Milliez (4), G. Rau (1) and all COST ES1006 Members TRANSNATIONAL MODEL INTERCOMPARISON AND VALIDATION EXCERSICE (JOAQUIN) .......................... 109 S. Adriaenssens (1), F. Fierens (1), E. Trimpeneers (1), E. Van der Swaluw (2), F. Deutsch (3) and H. Denier Van der
Gon (4) APPLICATION OF NINFA/AODEM OVER NORTHERN ITALY: MODEL EVALUATION IN THE FRAMEWORK
OF SUPERSITO PROJECT ................................................................................................................................................... 110 T. C. Landi (1,2), M. Stortini (2), G. Bonafè (2), P. Cristofanelli (1) and P. Bonasoni (1) EVALUATION OF THE MACC OPERATIONAL FORECAST SYSTEM WITH RESPECT TO GLOBAL REACTIVE
GASES ................................................................................................................................................................................... 111 Annette Wagner (1), Harald Flentje (1), Werner Thomas (1) and the MACC Team SPECIAL SESSION - AIR POLLUTION IN CITIES ..................................... 112 SEASONAL VARIATION OF PAHS CONCENTRATION IN ROME METROPOLITAN AREA AND SOURCE
ATTRIBUTION THROUGH DIAGNOSTIC RATIOS ANALYSIS .................................................................................... 113 S. Finardi (1), A. Cecinato (2), C. Gariazzo (3), M. Gherardi (3), P. Radice (1), P. Romagnoli (2) A FEASIBILITY STUDY OF MAPPING LIGHT ABSORBING CARBON USING A TAXI FLEET AS A MOBILE
PLATFORM .......................................................................................................................................................................... 114 P. Krecl (1), C. Johansson (2,3), J. Ström (2), J.-C. Gallet (4) and B. Lövenheim (3) INDOOR PSYCHOTROPIC SUBSTANCES IN ROME, ITALY ........................................................................................ 115 A. Cecinato, P. Romagnoli, M. Perilli, C. Patriarca, C. Balducci ON THE EFFECT OF A PARK ON FLOW AND POLLUTANT DISPERSION IN THE BUILT ENVIRONMENT CFD STUDY FOR AN IDEALZED URBAN NEIGHBOURHOOD - ................................................................................. 116 C. Gromke (1), B. Blocken (1,2) PARTICLE SURFACE AREA SIZE DISTRIBUTIONS IN DIFFERENT URBAN AEREAS ........................................... 117 H. Kuuluvainen (1), A. Järvinen (1), L. Pirjola (2), J. V. Niemi (3), R. Hillamo (4), J. Keskinen (1) and T. Rönkkö (1) SYNCHRONOUS MOBILE MEASUREMENTS WITHIN A DENSE URBAN VALLEY ................................................ 118 E. R. Somervell (1), J. Salmond (2), I. D. Longley (1), K. Dirks (2), G. Olivares (1), S. Grange (2) MODELLED URBAN ACETALDEHYDE CONCENTRATION ASSOCIATED WITH BIOETHANOL FUELLED
TRANSPORT ........................................................................................................................................................................ 119 S. López-Aparicio and I. Sundvor DEVELOPMENT AND ASSESSMENT OF TRAFFIC-RELATED EMISSION ABATEMENT MEASURES FOR THE
MADRID CITY (SPAIN) THROUGH THE WRF-SMOKE-CMAQ MODELLING SYSTEM .......................................... 120 R. Borge, J. Lumbreras, D. de la Paz, J. Pérez, M. E. Rodríguez THE VERTICAL PROFILES OF PM2.5 AND O3 MEASURED IN AUTUMN AND WINTER FROM A 325-METERMETEOROLOGICAL TOWER IN URBAN BEIJING, CHINA .......................................................................................... 121 D. S. Ji, Y. S. Wang, Y. Sun MULTI-YEAR CHARACTERISATION OF METALS CONCENTRATIONS IN AEROSOL COLLECTED IN
DIFFERENT SITES OF THE VENICE LAGOON ............................................................................................................... 122 E. Morabito (1), D. Cesari (2), D. Contini (2), A. Gambaro (3), P. Campostrini (4), C. Dabalà (4), F. Belosi (5) vi
VALIDATION OF NEW PARAMETERISATIONS FOR THE OPERATIONAL STREET POLLUTION MODEL
(OSPM) .................................................................................................................................................................................. 123 M. Ketzel (1), O. Hertel (1), T.-B. Ottosen (1,2), K. Kakosimos (2) and R. Berkowicz (1) HIGH RESOLUTION MAPPING OF ATMOSPHERIC POLLUTANTS IN URBAN ENVIRONMENTS UTILISING
DATA FROM SENSOR NETWORKS ................................................................................................................................. 124 M. D. Mueller (1), C. Hueglin (1), D. Hasenfratz (2), O. Saukh (2), V. B. Bright (3), O. A. M. Popoola (3), R. Jones (3) IMPACT OF THE ECONOMIC CRISIS ON WINTERTIME AIR QUALITY IN THESSALONIKI, GREECE................ 125 Arian Saffari (1), Nancy Daher (1), Constantini Samara (2), Dimitra Voutsa (2), Athanasios Kouras (2), Evangelia
Manoli (2), Olga Karagkiozidou (2), Christos Vlachokostas (3), Nicolas Moussiopoulos (3), Martin M. Shafer (4),
James J. Schauer (4), Constantinos Sioutas (1) ASSESMENT OF ORGANIC COMPOUNDS AS VEHICULAR EMISSION TRACERS IN THE ABURRA VALLEY
REGION OF COLOMBIA .................................................................................................................................................... 126 M. Gómez (1), E. Posada (2), V. Monsalve (2) OVERVIEW OF ANTHROPOGENIC EMISSIONS OF VOC IN NORTHERN MID-LATITUDE CITIES INFERRED
FROM INTENSIVE AND LONG TERM OBSERVATIONS .............................................................................................. 127 A.Borbon (1), A. Boynard (2), V. Gros (3), N. Locoge (4), J. de Gouw (5) ATMOSPHERIC POLLUTION IN NORTH AFRICA. FACTS AND LESSONS IN THE SPANISH CITY OF CEUTA .. 128 S. García Dos Santos (1), R. Benarroch Benarroch (2), R. Fernández Patier (1), M.A. Sintes Puertas (1), A. Aguirre
Alfaro (1), J.M. Cantón Gálvez (2), J. Alonso Herreros (1) and S. Guevara Hernández (1) CHEMICAL CHARACTERISTICS OF PM2.5 IN HAZE EPISODES IN BEIJING ............................................................. 129 R. R. Shen (1), K. Schäfer (1), P. Suppan (1), Y. S. Wang (2), J. Schnelle-Kreis (3), L. Y. Shao (4) SPECIAL SESSION - AIR QUALITY AND CLIMATE METEOROLOGY
INTERACTIONS AND FEEDBACKS ............................................................ 130 DOWNSCALING OF MONTHLY PM10 CONCENTRATIONS IN BAVARIA BASED ON CIRCULATION TYPE
CLASSIFICATIONS ............................................................................................................................................................. 131 C. Beck (1), C. Weitnauer (1) and J. Jacobeit (1) CHANGES TO THE EUROPEAN PARTICLE COMPOSITION DURING THE 21ST CENTURY ................................... 132 C. Andersson (1), M. Engardt (1) and C. Geels (2) AIR QUALITY PROJECTIONS OVER EUROPE UNDER CLIMATE CHANGE AND EMISSION MITIGATION
SCENARIOS: HORIZONS 1971-2060 ................................................................................................................................. 133 P. Navarro (1), J. P. Montávez (1) and P. Jiménez-Guerrero (1) INVESTIGATING AEROSOL OPTICAL PROPERTIES USING WRF/CHEM ................................................................. 134 A. Balzarini (1), G. Pirovano (1), G. M. Riva (1) AIRBORNE SOURCE APPORTIONMENT FOR ULTRAFINE ATMOSPHERIC PARTICLES AND THE
DEPENDENCE OF LOCAL SURFACE CONCENTRATIONS ON REGIONAL SCALE METEOROLOGY.................. 135 W. Junkermann WRF-CHEM SIMULATIONS ON THE EFFECT OF AEROSOL-METEOROLOGY FEEDBACK ON REGIONAL
POLLUTANT DISTRIBUTIONS OVER EUROPE ............................................................................................................. 136 R. Forkel (1), A. Balzarini (2), R. Baró (3), G. Curci (4), P. Jiménez-Guerrero (3), M. Hirtl (5), L. Honzak (6), J. L.
Pérez (7); G. Pirovano (2), R. San José (7); P. Tuccella (4), J. Werhahn (1), R Žabkar (6) REPRESENTATION OF COUPLING PROCESSES IN ONLINE COUPLED METEOROLOGY AND CHEMISTRY
MODELS – AN EXPERT POLL SURVEY RESULTS ........................................................................................................ 137 X. Kong (1), M. Gauss (2), G. Tsegas (3), A. Baklanov (4), R. Forkel (5), P. Suppan (5), D. Brunner (6), R. S. Sokhi
(1), K. H. Schlünzen (7) and the COST ES1004 EuMetChem team QUANTIFYING THE RESPONSES OF FUTURE AIR QUALITY OF EUROPE TO CHANGES IN CLIMATE AND
EMISSIONS WITH WRF-CMAQ AND HADGEM ............................................................................................................. 138 X. Kong (1), R. S. Sokhi (1), X. Francis (1), C. Chemel (1), G. Folberth (2) and B. Collins (3) AIR QUALITY AND CLIMATE CHANGE IMPACT ON URBAN HEAT ISLAND IN CENTRAL EUROPE................ 139 T. Halenka (1), P. Huszar (1), M. Belda (1), K. Zemankova (2) INFLUENCES OF METEOROLOGICAL PARAMETERS AND MIXING LAYER HEIGHT UPON AIR
POLLUTANT CONCENTRATIONS IN URBAN AREA .................................................................................................... 140 K. Schäfer (1), P. Wagner (2), H. Ling (1, 3), C. Münkel (4), S. Emeis (1), P. Suppan (1) DEVELOPING A NEW DATABASE FOR SOURCE FINGERPRINTS IN THE ASIAN REGION – AN OVERVIEW
OF THE IAEA/RCA PROGRAMME ON AIR PARTICULKATE MATTER POLLUTION RAS0723.............................. 141 A. Markwitz (1), D. D. Cohen (2), B. A. Begum (3), B. F. Ni (4), G. G. Pandit (5), M. Santoso (6) , Y. S. Chung (7), S.
Abd Rahman (8), D. Shagjjamba (9), S. Waheed (10), P. C. B. Pabroa (11), M. C. S. Seneviratne (12), T. B. Vuong
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SPECIAL SESSION - AIR QUALITY FORECASTING AND EARLY
WARNING SYSTEMS..................................................................................... 142 DO AIR QUALITY INFORMATION, FORECASTING AND EARLY WARNING SYSTEMS REACH
VULNERABLE TARGET GROUPS? .................................................................................................................................. 143 M. Capellaro (1), D. Sturm (2), U. Reis (3) and H.-G. Mücke (4) IMPROVING AIR QUALITY MODELING FORECASTING SYSTEMS BY USING ON-LINE WILD LAND FIRE
FORECASTING TOOLS: AN APPLICATION OF WRF/CHEM/FIRE MODEL OVER EUROPE ................................... 144 R. San José (1), J. L. Pérez (1), R. M. González (2) , J. Pecci (3) and M. Palacios (3) LOTOS-EUROS CONTRIBUTION TO MACC-II-REANALYSIS-2011 TO ASSESS THE AIR QUALITY OF
EUROPE ................................................................................................................................................................................ 145 U. Kumar1, A. Segers2, R. L. Curier2, R. Timmermans2, H. Eskes1 AIR QUALITY FORECASTING AND INFORMATION TOWARDS PUBLIC DEMONSTRATED IN WUHAN,
HUBEI PROVINCE, CHINA ................................................................................................................................................ 146 L. Liu (1), C. Hak (1), N. Chen (2) SPECIAL SESSION - LOCAL AND REGIONAL AIR QUALITY
SERVICES ........................................................................................................ 147 THE PASODOBLE AIRSHEDS - BRIDGING THE GAP BETWEEN THE COPERNICUS ATMOSPHERIC
SERVICE AND LOCAL FORECASTING SERVICES........................................................................................................ 148 R. Timmermans (1), D. Balis (2), H. Elbern (3), T. Erbertseder (4), H. Eskes (5), E. Friese (3), C. Hendriks (1), E.
Katagrou (2), R. Kouznetsov (6),U. Kumar (5), O. Lesne (7), A. Poupkou (2), M. de Ruyter de Wildt (5), M. Schaap (1),
A. Segers (1), M. Sofiev (6), and C. Talbot (7) SATELLITE BASED MAPPING OF PARTICULATE MATTER ....................................................................................... 149 M. Kosmale, D. Martynenko, T. Holzer-Popp AN INTEGRATED PLUME RISE MODEL FOR WILD-LAND FIRES ............................................................................. 150 J. Kukkonen (1), J. Nikmo (1), M. Sofiev (1), K. Riikonen (1), T. Petäjä (2), A. Virkkula (1,2), J. Levula (3), S.
Schobesberger (2) and D. M. Webber (4) ON THE IMPACT OF AIR QUALITY ON HUMAN HEALTH: APPLICATION OF AN AIR QUALITY INDEX FOR
THESSALONIKI, GREECE.................................................................................................................................................. 151 Th. Giannaros (1), P. Siropoulou (1), A. Poupkou (1), S. Dimopoulos (1), D. Melas (1) and D. Balis (1) AIR QUALITY FORECASTS FOR THE BLACK FOREST REGION ............................................................................... 152 C. C. Bergemann (1), T. Erbertseder (1) AIRINFORM: DEVELOPMENT OF AIR QUALITY INFORMATION AND AWARENESS TOOLS FOR CHINESE
CITIES ................................................................................................................................................................................... 153 N. Veldeman (1), L. Blyth (1), P. Viaene (1), B. Maiheu (1), S. van den Elshout (2), J. Hui (3), W. Shuying (3) SILAM OERATIONAL FORECASTS AT THREDDS SERVER ........................................................................................ 154 R. D. Kouznetsov, M. A. Sofiev, J. Vira, M. Prank, J. Soares, C. T. M. Silam INTERACTIVE WEBSITE FOR AIR QUALITY AT ADDRESS LEVEL IN DENMARK ............................................... 155 S. S. Jensen (1), M. Fuglsang (1), T. Becker (1), M. Ketzel (1), J. Brandt (1), M. Plejdrup (1), M. Winther (1), T.
Ellermann (1), O. Hertel (1) THE COMBINED USE OF MEASUREMENT DATA AND MODEL RESULTS - THE DATA FUSION OF THE
PESCADO PROJECT ............................................................................................................................................................ 156 A. Karppinen (1), L. Johansson (1), J. Kukkonen (1), K. Karatzas (2), L. Wanner (3) SPECIAL SESSION - TRANSPORT RELATED AIR POLLUTION SCIENCE AND IMPACTS .............................................................................. 157 IMPACT OF EMISSIONS FROM INLANDS SHIPPING ON AIR QUALITY AND HEALTH IN THE
NETHERLANDS ................................................................................................................................................................... 158 M. P. Keuken (1), M. Moerman (1), S. Jonkers (1), J. Hulskotte (1) and G. Hoek (2) AN IMPROVED MODEL FOR EVALUATING THE URBAN POPULATION EXPOSURE ........................................... 159 J. Soares (1), A. Kousa (1), J. Kukkonen (1), L. Matilainen (1), L. Kangas (1), M. Aarnio (1), M. Kauhaniemi (1), K.
Riikonen (1), J.-P. Jalkanen (1), T. Rasila (1), O. Hänninen (3), T. Koskentalo (2) and A. Karppinen (1) CAN THE PREDICTIONS OF ROAD DUST EMISSION MODELS BE DIRECTLY COMPARED WITH ON-SITE
MOBILE MEASUREMENTS? ............................................................................................................................................. 160 M. Kauhaniemi (1), A. Stojiljkovic (2), L. Pirjola (3), A. Karppinen (1), J. Härkönen (1), K. Kupiainen (2), L. Kangas
(1), M. A. Aarnio (1), G. Omstedt (4), B. R. Denby (5), J. Kukkonen (1) viii
EVALUATION OF THE PRESENT AND FUTURE AIR QUALITY IN EUROPE BASED ON TRANSPHORM
MULTI-MODEL ENSEMBLE .............................................................................................................................................. 161 M. Prank (1), M. Sofiev (1), B. Amstrup (2), A. Baklanov (2), H. Denier van der Gon (3), C. Hendriks (3), X. Kong (4),
A. Mažeikis (2), R. Nuterman (2), S. Tsyro (5), S. Valiyaveetil (5), X. Vazhappilly Francis (4), J. Kukkonen (1), R. S.
Sokhi (4) TRAFFIC-RELATED AIR POLLUTION AND THE ONSET OF MYOCARDIAL INFARCTION: DISCLOSING
BENZENE AS A TRIGGER? A SMALL-AREA CASE-CROSSOVER STUDY ................................................................ 162 D. Bard (1), W. Kihal (1), C. Schillinger (2), C. Fermanian (1), C. Ségala (3), S. Glorion (1), D. Arveiler (4), C. Weber
(5) HEALTH IMPACT ASSESSMENT OF LONG-TERM EXPOSURE TO PARTICULATE AIR POLLUTION WITHIN
TRANSPHORM. (FOR SPECIAL SESSION ON TRANSPHORM PROJECT) .................................................................. 163 B. G. Miller (1), J. F. Hurley (1), R. S. Sokhi (2), M. Keuken (3) and B. Brunekreef (4) EUROPEAN PARTICLE NUMBER EMISSIONS FOR 2005, 2020 AND 2030 WITH SPECIAL EMPHASIS ON THE
TRANSPORT SECTOR. ....................................................................................................................................................... 164 H. A. C. Denier van der Gon (1), A. J. H. Visschedijk (1), J. Kuenen (1), C. Schieberle (2), I. Vouitsis (3), Z. Samaras
(3), J. Moldanova (4), A. Petzold (5) AIR QUALITY IMPACTS OF ELECTRIC VEHICLES IN BARCELONA ........................................................................ 165 A. Soret (1), M. Guevara (1), and J. M. Baldasano (1,2) CALCULATIONS OF PRESENT AND FUTURE EFFECTS OF DIFFERENT TRANSPORT MODES ON AIR
QUALITY AND HUMAN HEALTH IN EUROPE .............................................................................................................. 166 J. E. Jonson(1), R. Friedrich (2), S. Tsyro (1), J. Roos (2) and V. S. Semeena (1) MODELLING OF PARTICULATE MATTER CONCENTRATIONS IN THE HELSINKI METROPOLITAN AREA
IN 2008 AND 2010 ................................................................................................................................................................ 167 M. A. Aarnio (1), L. Kangas (1), M. Kauhaniemi (1), A. Karppinen (1), A. Kousa (2), T. Petäjä (3), C. Hendriks (4), J.
Kukkonen (1) EMISSIONS FROM THE PORT OF RIJEKA (CROATIA) AND THEIR IMPACT ON AIR QUALITY .......................... 168 A. Alebic-Juretic (1), A. van Hyfte (2), K. Devoldere (2), I. Hladki (3) and V. Jelavic (3) REFINEMENT AND EVALUATION OF A STATISTICAL APPROACH FOR DETERMINING CONCENTRATION
INCREMENTS IN URBAN AREAS .................................................................................................................................... 169 N. Moussiopoulos (1), S. Torras Ortiz (2), I. Douros (1), E. Chourdakis (1), R. Friedrich (2) MONITORING OF AIR POLLUTION BY TRANSPORT RELATED NITROGEN OXIDES ON ROADS AND
HIGHWAYS OF ST. PETERSBURG ................................................................................................................................... 170 O. V. Lozhkina, V. S. Marchenko, V. N. Lozhkin ASSESSING THE HEALTH BENEFITS OF DECREASED POPULATION EXPOSURES VERSUS DISBENEFITS
OF INCREASED DRIVER EXPOSURES IN AN 18 KM LONG HIGH-WAY ROAD TUNNEL BY-PASS IN
STOCKHOLM ....................................................................................................................................................................... 171 H. Orru (1, 2), B. Lövenheim (3), C. Johansson (3, 4), B. Forsberg (1) INTERCOMPARISON OF URBAN SCALE AIR QUALITY MODELS ............................................................................ 172 S. Jonkers (1), E .W. Meijer (1), P. Y. J. Zandveld (1), B. R. Denby (2), I. Douros, (3), N. Moussiopoulos (3), V. Singh
(4), R. S. Sokhi (4), A. Karppinen (5), L. Kangas (5) and J. Kukkonen (5) CONTRIBUTION OF EMISSION SOURCES TO CONCENTRATIONS OF FINE PARTICULATE MATTER (PM2.5)
IN EUROPE ........................................................................................................................................................................... 173 X. Francis (1), R. S. Sokhi (1), C. Chemel (1) H. Denier van der Gon (2) URBAN AND TRAFFIC CONTRIBUTIONS TO PM2.5 IN LONDON ............................................................................... 174 V. Singh (1), R. S. Sokhi (1) and J. Kukkonen (2) ROADSIDE AND URBAN BACKGROUND MEASUREMENTS OF ULTRAFINE PARTICLES IN
THESSALONIKI, GREECE – 7 YEARS LATER ................................................................................................................ 175 Ι. Vouitsis, S. Amanatidis, L. Ntziachristos and Z. Samaras USE OF REMOTE SENSING AND SATELLITE DATA FOR AIR
QUALITY RESEARCH ................................................................................... 176 A REGIONAL SCALE NOX EMISSION INVERSION USING OMI OBSERVATIONS ................................................... 177 J. Vira (1), M. Sofiev (1) AIRBORNE MAPPING OF NITROGEN DIOXIDE CONCENTRATIONS IN URBAN ENVIRONMENTS ................... 178 R. J. Leigh (1), J. P. Lawrence (1), J. Vande Hey(1), R. R. Graves (1),and P. S. Monks (2) OBTAINING PM2.5 IN THE STOCKHOLM REGION FROM SPACEBORNE MEASUREMENTS............................... 179 M. Tesche (1), P. Glantz (1), and C. Johansson (1, 2) ix
ON POSSIBILITY OF REMOTE-SENSING COMPLIANCE MONITORING OF SHIP-FUEL SULPHUR CONTENT:
A MODELLING STUDY IN GULF OF FINLAND ............................................................................................................. 180 M. Sofiev (1), M.Prank (1), L.Johansson (1), J.-P.Jalkanen (1), T.Stipa (1) BOUNDARY LAYER AEROSOL INVESTIGATION WITH LASER CEILOMETER...................................................... 181 C. Münkel (1), K. Schäfer (2), S. Emeis (2) and P. Suppan (2) WIND TUNNEL - PHYSICAL MODELLING ............................................... 182 A COMPARISON OF NUMERICAL AND EXPERIMENTAL STUDIES OF THE WIND FLOW IN URBAN STREET
CANYONS ............................................................................................................................................................................ 183 F. C. Cezana (1), E. V. Goulart (1), R. R. C. de Paula (2), J. C. F. Queiroz (2), L. B. Föeger (1) and D. Z. Matta (2) IMPACT OF URBAN-AREA GEOMETRY ON POLLUTION VENTILATION ............................................................... 184 L. Kukačka (1,2), V. Fuka (1), Š. Nosek (2), Z. Jaňour (2) EVAPORATION AND SORPTION OF TOXIC SUBSTANCES IN ATMOSPHERIC BOUNDARY LAYER FLOW..... 185 K. Jurčáková (1), T. Dropa and M. Weisheitelová (2) DEVELOPMENT AND VALIDATION OF THE HYBRID WIND TUNNEL/NUMERICAL MODEL HYWINMOD..... 186 A. Beyer-Lout (1), R. L. Petersen (1) COMPARISON OF PIV EXPERIMENT AND LES ON STREET CANYON DYNAMICS ............................................... 187 R. Kellnerová (1,2), L. Kukačka (1,2), V. Fuka (2), V. Uruba (1), Z. Jaňour (1), Š. Nosek (1) PART TWO: POSTER SESSIONS ..................................... 188 AIR QUALITY AND IMPACT ON LOCAL TO GLOBAL SCALES .......... 189 MODELLING AND ANALYSIS OF THE ROLE OF MESOMETEOROLOGICAL PROCESSES ON TRANSPORT
AND ACCUMULATION OF POLLUTANTS IN THE WESTERN MEDITERRANEAN AND THEIR INFLUENCE
ON CHEMICAL DEGRADATION MECHANISMS ........................................................................................................... 190 J. L. Palau (1), M. Vázquez (1), F. Rovira (2), M. J. Sales (2), A. Muñoz (1), E. Borrás (1) T. Vera (1), F. Santa-Cruz
(1), J. I. Roselló (1) and P. Sánchez (1) ROLE OF THE LONG-RANGE TRANSPORT IN THE AEROSOL CONCENTRATION FORMATION IN
HUNGARY ............................................................................................................................................................................ 191 Z. Ferenczi LONG RANGE TRANSPORT OF PM10 TO MARMARA REGION................................................................................... 192 E. Oksuz (1), M. Kafadar (1) MEASUREMENT AND MODELING ACTIVITIES IN NEPAL IN FRAMEWORK OF THE SUSKAT PROJECT ........ 193 A. Mues (1), A. Lauer (1), M. Rupakheti (1), A. Panday (2,3) DETECTION OF FUKUSHIMA ORIGIN CEASIUM ISOTOPES AT POLISH POLAR STATION IN HORSUND
(SPITSBERGEN) AND ITS EFFECTS TO ATMOSPERIC ELECTRICITY PARAMETERS ........................................... 194 B. Mysłek-Laurikainen (1), M. Matul (1), S. Mikołajewski (1), H. Trzaskowska (1), M. Kubicki (2), P. Baranski (2), A.
Ozimek (2), S. Michnowski (2) ATTEMPT TO IDENTIFY OF EPISODES THE CONTRIBUTION OF STRATOSPHERIC OZONE IN THE
GROUND LAYER OF THE ATMOSPHERE ...................................................................................................................... 195 E. Krajny (1), L. Osrodka (1), M. Wojtylak (1) and M. Pajek (2) REGIONAL EMISSION FACTORS OF CARBON DIOXIDE FROM AGRICULTURAL WASTE RESIDUES
BURNING IN NORTHEASTERN REGION THAILAND ................................................................................................... 196 N. Khosavithitkul (1), N. Chuersuwan (2), and T. Wannasook (3) AIR QUALITY MANAGEMENT AND POLICY .......................................... 197 UFIREG PROJECT: ULTRAFINE PARTICLES - AN EVIDENCE BASED CONTRIBUTION TO THE
DEVELOPMENT OF REGIONAL AND EUROPEAN ENVIRONMENTAL AND HEALTH POLICY ........................... 198 S. Lanzinger (1), A. Schneider (1), S. Breitner (1), R. Rückerl (1), A. Peters (1), S. Bastian (2), A. Zscheppang (3), J.
Cyrys (1) (4) TEN YEARS OF WOODBURNER RESEARCH IN NEW ZEALAND: LESSONS LEARNED AND FUTURE
DIRECTIONS ........................................................................................................................................................................ 199 G. Coulson (1), E. Wilton (2), E. R. Somervell (1), R. Bian (1) A DYNAMIC PROGRAMMING APPROACH FOR AIR QUALITY PLANNING AT REGIONAL SCALE................... 200 C. Carnevale (1), G. Finzi (1), F. Padula (1), E. Turrini (1) and M. Volta (1) A MULTI-STRESSOR, MULTI-MODAL APPROACH TO BRIDGE THE GAP BETWEEN CHEMICAL AND
PHYSICAL HEALTH STRESSORS IN URBAN AREAS ................................................................................................... 201 Ch. Vlachokostas (1), G. Banias (2), A. Athanasiadis (1), V. Akylas (1), Ch. Achillas (2) and N. Moussiopoulos (1) x
HEALTH BENEFITS FROM TRANSPORT RELATED GREENHOUSE GAS EMISSION POLICIES ........................... 202 D. A. Sarigiannis, P. Kontoroupis, S. Karakitsios, D. Chapizanis DEVELOPMENT - APPLICATION OF AIR QUALITY AND RELATED
MODELS........................................................................................................... 203 SENSITIVITY OF THE SEMI-EMPIRICAL URBAN STREET (SEUS) MODEL TO VARIATIONS IN NO2/NOX
EMISSIONS RATIOS ........................................................................................................................................................... 204 S. Vardoulakis (1), N. A. Mazzeo (2) and L. E. Venegas (2) DOWNSCALING MESOSCALE WIND FIELDS THROUGH A MASS-CONSISTENT MODEL TO DRIVE
DISPERSION SIMULATIONS WITH ADMS ..................................................................................................................... 205 P. Brotto (1)(3), F. Cassola (1)(3), A. Mazzino (2)(3) and P. Prati (1)(3) TIME EVOLUTION OF OZONE PRODUCTION FROM VOCS ....................................................................................... 206 K. A. Mar (1), J. Coates (1), S. Zhu (1), T. M. Butler (1) MATCH-SALSA - MULTI-SCALE ATMOSPHERIC TRANSPORT AND CHEMISTRY MODEL COUPLED TO
THE SALSA AEROSOL MICROPHYSCIS MODEL .......................................................................................................... 207 C. Andersson (1), R. Bergström, (1,2), H. Kokkola (3), C. Bennet (1), M. Thomas (1), H. Korhonen (3), K. Lehtinen (3)
and L. Robertson(1) MEASUREMENTS AND MODELLING OF BLACK CARBON IN TWO CITIES IN SOUTH-WEST SPAIN ............... 208 C. Milford (1,2), R. Fernández-Camacho (1), A. Sánchez de la Campa (1), S. Rodríguez (2), N. Castell (3), C. Marrero
(2), J. De la Rosa (1) and A. F. Stein (4) A METHODOLOGY TO ESTIMATE PM10 OUTDOOR URBAN CONCENTRATIONS USING GLM .......................... 209 J. M. Garcia (1), F. Teodoro (1), R. Cerdeira (1), L. M. R. Coelho (1), M. G. Carvalho (2)(3) IMPLEMENTATION OF THE ON LINE COUPLED MODEL WRF/CHEM OVER THE PO VALLEY ......................... 210 C. Carnevale (1), G. Finzi (1), E. Pisoni (2), A. Pederzoli (1), E. Turrini (1), M. Volta (1) IMPACT OF SHIPPING EMISSIONS FROM A MEDITERRANEAN PORT CITY BY COUPLING OF THE MESOSCALE MODEL BOLCHEM WITH THE MICRO-SCALE MODEL ADMS-URBAN ..................................................... 211 R. Cesari (1), R. Buccolieri (2), A. Maurizi (3), R. Quarta (2) and S. Di Sabatino (2) ADVANCED ODOUR DISPERSION MODELLING IN A NEW ENVIRONMENTAL INFORMATION SYSTEM ....... 212 U. Uhrner (1), G. Grosso (1), D. Öttl (2) MAKING AIR QUALITY INDICES COMPARABLE – ASSESSMENT OF TEN YEARS OF AIR POLLUTANT
LEVELS IN WESTERN EUROPE ........................................................................................................................................ 213 H. Lokys (1, 2), J. Junk (1), A. Krein (1) EMISSION MODELS - INVENTORIES ......................................................... 214 RESIDENTIAL HEATING EMISSIONS OF PM2.5 AND NOX IN ESTONIA .................................................................. 215 M. Kaasik (1), M. Maasikmets (2;3), E. Teinemaa (2) CALORIFIC VALUES AND PARTICULATE EMISSION ESTIMATES OF DISTRIBUTED BIOMASS FUELS
OVER RURAL WESTERN INDIA....................................................................................................................................... 216 Rohtash, A. Sen, T. K. Mandal, M. Saxena, S. K. Sharma USING TRACERS FOR ESTIMATION OF CO2 SOURCE IN THE URBAN ENVIRONMENT ..................................... 217 J. M. Necki, D. Jelen, M. Zimnoch MICRO AND MACRO MODELLING OF COLD START EMISSIONS FROM ROAD TRAFFIC: A CASE STUDY IN
ATHENS ................................................................................................................................................................................ 218 C. Samara (1), E. Mitsakis (2), I. Stamos (2), J. M. Salanova-Grau (2), G. Aifadopoulou (2), L. Ntziachristos (1) and Z.
Samaras (1) ENVIRONMENTAL AND HEALTH IMPACT RESULTING FROM AIR
POLLUTION..................................................................................................... 219 AIR QUALITY MEASUREMENTS IN INDOOR ENVIRONMENT OF MODERN OFFICES IN ATHENS, GREECE
(OFFICAIR PROJECT) ......................................................................................................................................................... 220 I.A. Sakellaris (1), D.E. Saraga (1,2), K.K. Kalimeri (1), E.M. Kougioumtzidis (1), V.G. Mihucz (3), R. Mabilia (4) and
J.G. Bartzis (1) ANALYSING THE BIOLOGICAL INTERVENTION OF FINE PARTICULATE FRACTIONS IN HUMAN BODY ..... 221 I. Mukherjee (1), T. Chakraborty (2) CHEMICAL MECHANISM OF CU-TIO2/GF PHOTOCATALYST FOR DISINFECTION OF E. COLI IN AEROSOL
UNDER VISIBLE LIGHT ..................................................................................................................................................... 222 T. D. Pham, B. K. Lee, C. H. Lee xi
EXTERNAL COSTS OF AIR POLLUTION FROM ENERGY SUPPLY: REVIEWING METHODOLOGIES FROM
EXTERNE TO NEEDS.......................................................................................................................................................... 223 J. van der Kamp, T. M. Bachmann A STUDY OF OZONE EXPOSURE ACROSS EUROPE: 2004-2010 ................................................................................. 224 T. Chatterton (1), E. Hayes (1), J. Barnes (1), J. Longhurst (1), D. Laxen (1) J. Irwin (1), H. Bach (2), J. Brandt (2), J.
H. Christensen (2), T. Ellermann (2), C. Geels (2), O. Hertel (2), A. Massling (2), H. Ø. Nielsen (2), O. K. Nielsen (2),
C. Nordstrøm (2), J. K. Nøjgaard (2), H. Skov, (2), F. Pelsy (3) and T. Zamparutti (3) MODELLING EXPOSURE AND LUNG DEPOSITION OF PARTICLE-BOUND POLYCYCLIC AROMATIC
HYDROCARBONS (PAHS) ................................................................................................................................................. 225 O. Hänninen (1), P. Lipponen (1), R. Sorjamaa (1), M. Lamberti (2), C. Gariazzo (2) GREEN-AGRICHAINS PROJECT: INTERACTIONS BETWEEN AIR QUALITY, CLIMATE CHANGE AND
AGRICULTURE.................................................................................................................................................................... 226 N. Moussiopoulos (1), K. Schäfer (2), E. Iakovou (3), E. Fragkou (1), E.-A. Kalognomou (1), G. Tsegas (1) and Ch.
Achillas (4) AIR POLLUTION MODELING ON AN URBAN SCALE: CASE STUDIES FOR THE FUTURE HEALTH IMPACT
ASSESSMENT UNDER DIFFERENT CLIMATE CHANGE SCENARIOS ...................................................................... 227 U. Mikolajczyk (1), P. Suppan (1), S. Emeis (1), R. Forkel (1), A. Schneider (2) SIMULATED AIRWAY PARTICLE DEPOSITION IN AN URBAN ENVIRONMENT IMPACTED BY BIOMASS
SMOKE .................................................................................................................................................................................. 228 A. C. Targino (1), P. Krecl (2), C. Johansson (3) ENVIRONMENTAL METEOROLOGY - PROCESSES AND
INTERACTIONS .............................................................................................. 229 ASSESSMENT OF URBAN PARAMETERIZATIONS IN THE WRF MODEL FOR AIR QUALITY MODELLING
PURPOSES IN MADRID (SPAIN) ....................................................................................................................................... 230 D. de la Paz, R. Borge, J. Lumbreras, M. E. Rodríguez MODIFIED MELLOR-YAMADA-JANJIC PLANETARY BOUNDARY LAYER SCHEME USED TO SIMULATE
BOUNDARY LAYER HEIGHTS AND AEROSOL CONCENTRATION IN AUGSBURG, SOUTHERN GERMANY .. 231 R. J. Foreman (1), R. Forkel (1), S. Emeis (1) CLIMATE CHANGE EFFECTS ON URBAN AIR QUALITY ........................................................................................... 232 M. Piljek (1), V. Džaja Grgičin (1), A. Jeričević (1,2), S. Vidič (1), M. Patarčić (1), L. Srnec (1), I. Guettler (1) and Č.
Branković (1) MEASUREMENT OF AIR POLLUTANTS AND SOURCE
APPORTIONMENT ......................................................................................... 233 GIORDAN LIGHTHOUSE - A GAW STATION ON THE ISLAND OF GOZO IN THE CENTRAL
MEDITERRANEAN; SUMMARY OF RESULTS OBTAINED CONCERNING SHIPPING EMISSIONS, VOLCANIC
PLUMES AND OTHER ANTHROPOGENIC EMISSIONS ................................................................................................ 234 F. Azzopardi1, A. Smyth1, M. Saliba1, M. Azzopardi1, J. Azzopardi2, J. Sciare3, F. DuLac3, S. Scollo4, M. Prestifilippo4,
J.-P. Jalkanen5, L. Johansson5 , P. Pribylova6 and R. Ellul1 MESUREMENTS OF TRACE GASES (NH3, NO, NO2 & SO2), PARTICULATES (PM2.5 & TSP) AND BLACK
CARBON OVER THE WESTERN HIMALAYAN REGION, INDIA................................................................................. 235 T. K. Mandal (1), S. K. Sharma (1), C. Sharma (1), J. C. Kuniyal (2), Rohtash (1), A. Sen (1), H. Ghayas (3), N. C.
Gupta (3), M. Saxena (1) and A. Sharma (1) NANOPARTICLES NUMBER CONCENTRATION AND SIZE DISTRIBUTION NEAR A HIGHWAY IN SOUTH
BRAZIL ................................................................................................................................................................................. 236 I. L. Schneider (1), E. C. Teixeira (1,2), F. P. Norte (2), D. M. Agudelo-Castañeda (1), and L. F. S. Oliveira (1,3) AIR QUALITY SENSORS IN SCHOOLS: OPEN DATA FOR PUBLIC ENGAGEMENT ............................................... 237 R. R. Graves (1), R. J. Leigh (1) and J. J. Remedios (1) SECONDARY ORGANIC AEROSOL FORMATION IN THE OZONOLYSIS OF LIMONENE PERFORMED IN A
LAMINAR FLOW REACTOR ............................................................................................................................................. 238 T. Braure (1,2), V. Riffault (1,2), A. Tomas (1,2), Y. Bedjanian (3) and P. Coddeville (1,2) ATMOSPHERIC CHEMISTRY OF 3-METHYL-3-HYDROXY-2-BUTANONE: PHOTOLYSIS AND REACTION
WITH OH RADICALS .......................................................................................................................................................... 239 H. Bouzidi (1,2), A. Tomas (1,2), P. Coddeville (1,2), C. Fittschen (3), C. Sleiman (4), G. El Dib (4), A. Canosa (4), E.
Roth (5), A. Chakir (5) xii
INFLUENCE OF WINTER AND SUMMER METEOROLOGICAL CONDITIONS ON FORMATION OF OZONE
FROM A RURAL AND URBAN TYPICAL VOCS/NOX RATIO: SIMULATIONS AT THE EUPHORE SMOG
CHAMBER ............................................................................................................................................................................ 240 M. Vázquez (1), F. Alacreu (1), E. Borrás (1), E. García (1), T. Gómez (1), A. Muñoz (1), M. Ródenas (1), J. I. Roselló
(1), P. Sánchez (1), T. Vera (1), J. L. Palau (1). METHANE HOT SPOT IN CENTRAL EUROPE – IDENTIFICATION OF CH4 SOURCES IN SILESIA, POLAND ..... 241 A. Jasek1, M. Zimnoch1, L. Chmura1,2, J. M. Necki1, R. Fisher3 and D. Lowry3 MODELLING THE SOURCE CONTRIBUTION OF PARTICULATE MATTER IN OSLO: COMPARISON
BETWEEN MODELS AND OBSERVATIONS ................................................................................................................... 242 B. R. Denby and C. Hak NEW ADVANCES IN ENVIRONMENTAL AIR MONITORING ..................................................................................... 243 N. M. Watson (1), S. Koschinski (2), L. Pollack (2). SEASONAL VARIATION OF PB IN PM10 AEROSOLS AND BACKWARD TRAJECTORY ANALYSIS AT AN
URBAN SITE IN NORTH INDIA ........................................................................................................................................ 244 S. Chandra, R. Singh & M. J. Kulshrestha SOURCE APPOIRTIONMENT OF PM10 ELICIT REACTIVE OXYGEN SPECIES AT AN URBAN BACKGROUND
STATION............................................................................................................................................................................... 245 B. Hellack (1), M. Küpper (1), U. Quass (1), R. P. F. Schins (2) and T. A. J. Kuhlbusch (1) EMISSIONS FROM THE COMBUSTION OF COAL AND MIXTURE OF COAL AND WOOD PELLETS INDIVIDUAL PARTICLE ANALYSIS BY TEM/EDX ELECTRON MICROSCOPY ...................................................... 246 J. V. Niemi (1), A. Frey (2), K. Saarnio (3), L. Pirjola (4) A. Häyrinen (5), F. Mylläri (6), T. Rönkkö (6) and R. Hillamo
(3) ESTIMATING THE ORIGIN OF BACKGROUND AEROSOL POLLUTION IN ESTONIA ............................................ 247 B. Laan, K. Komsaare, M. Kaasik, U. Hõrrak TRENDS OF ATMOSPHERIC PERSISTENT ORGANIC POLLUTANTS IN EUROPEAN SAMPLING STATIONS ... 248 I. García (1), P. Jiménez-Guerrero (1), N. Ratola (1) ANALYSES AND SOURCE IDENTIFICATION OF PM10 CONCENTRATIONS DURING EPISODES OF AIR
POLLUTION IN CENTRAL AND SOUTHEASTERN EUROPEAN AREA ...................................................................... 249 V. Dz. Grgicin (1), A. Jeričević (1,4) M. T. Prtenjak (2), S. Vidič (1), H. Bloemen (3) Α MODELLING APPROACH TO ASSESS THE CONTRIBUTION OF DOMESTIC WOOD BURNING ON
AMBIENT PM2.5 LEVELS IN THE GREATER THESSALONIKI AREA, GREECE....................................................... 250 N. Moussiopoulos (1), C. Samara (2), G. Tsegas (1), Ch. Vlachokostas (1), D. Voutsa (2), G. Argyropoulos (2), A.
Kouras (2), E. Manoli (2), I. Douros (1), A. Michailidou (1) HETEROGENEOUS ATMOSPHERIC PHOTODEGRADATION OF CHLORPYRIFOS ................................................. 251 A. El Masri (1), E. Roth (1) , A. Chakir (1) MEASURING REMOTELY THE SULPHUR CONTENT OF SHIP FUEL ........................................................................ 252 J. Balzani, B. Alfoldy, F. Lagler, J. Hjorth and A. Borowiak MODEL EVALUATION STUDIES ................................................................ 253 SOURCE APPORTIONMENT OF PM10 AND PM2.5 BY USING POSITIVE MATRIX FACTORIZATION.................... 254 S. K. Sharma (1), R. Masiwal (1,2), N. C. Gupta (2), T. K. Mandal (1), M. Saxena (1) and Rohtash (1) EVALUATION OF THE SEMI-EMPIRICAL URBAN STREET (SEUS) MODEL USING AIR QUALITY DATA
FROM TWO STREET CANYONS IN THE UK .................................................................................................................. 255 L. E. Venegas (1), N. A. Mazzeo (1) and S. Vardoulakis (2) COMPARISON WIND-TUNNEL EXPERIMENT WITH LES MODELLING OF ATMOSPHERIC DISPERSION
OVER COMPLEX TERRAIN ............................................................................................................................................... 256 Š. Nosek (1), Z. Jaňour (1), V. Fuka (2), L. Kukačka (1,2), K. Jurčáková (1), R. Kellnerová (1,2), E. Gulikova (3) MEASUREMENT AND MODELLING OF CANADIAN FOREST FIRE EMISSIONS IN SUMMER 2013 WITH THE
MACC OPERATIONAL FORECAST SYSTEM ................................................................................................................. 257 H. Flentje (1), A. Wagner (1), I. Mattis (1), W. Thomas (1), A. Benedetti (2), J. Kaiser (3) PERSONAL EXPOSURE................................................................................. 258 INDOOR AIR AT A SUBURBAN NURSERY: FINE PARTICLES ASSESSMENT ......................................................... 259 P. T. B. S. Branco, M. C. M. Alvim-Ferraz, F. G. Martins, S. I. V. Sousa INDOOR AIR AT A SUBURBAN NURSERY: GASEOUS COMPOUNDS ASSESSMENT ............................................ 260 P. T. B. S. Branco, M. C. M. Alvim-Ferraz, F. G. Martins, S. I. V. Sousa VARIABILITY OF PM LEVELS IN THE BARCELONA METRO SYSTEM ................................................................... 261 V. Martins (1), T. Moreno (1), M. C. Minguillón (1) and X. Querol (1) xiii
SPECIAL SESSION - AIR POLLUTION IN CITIES .................................... 262 PSYCHOTROPIC SUBSTANCES IN LONDON, UK ......................................................................................................... 263 A. Cecinato (1), P. Romagnoli (1), M. Perilli (1), C. Balducci (1), D. Green (2) EFFECTS OF URBANIZED MODELLING IN FINE RESOLUTION EULERIAN AIR QUALITY SIMULATIONS ..... 264 J. Resler (1,2), J. Liczki (2), M. Belda (2,3), K. Eben (1,2), P. Jurus (1,2), J. Karel (4), R. Jares (4), O. Vlcek (5) and
M. Kazmukova (6) SEASONAL VARIATIONS OF VOLATILE HYDROCARBONS IN THE METROPOLITAN AREA OF SÃO PAULO 265 P. A. Dominutti (1), T. Nogueira (1), A. Fornaro (1) and M. F. Andrade (1) STUDY OF THE SOURCES OF FINE PARTICLE MATTER IN SANTIAGO DE CHILE AND ITS CORRELATION
WITH SOLAR RADIATION ................................................................................................................................................ 266 E. Gramsch (1), P. Oyola (2), F. Reyes (2), Y. Vasquez (2), M. A. Rubio (3) PM2.5 AND CARBONACEOUS SPECIES IN THESSALONIKI, GREECE DURING THE ECONOMIC RECESSION
PERIOD ................................................................................................................................................................................. 267 C. Samara (1), D. Voutsa (1), A. Kouras (1), M. Petrakakis (2), A. Kelessis (2), and P. Tzoumaka (2) ASSESSING AIR QUALITY IN A MEDITERRANEAN COASTAL CITY: AN APPROACH FROM THE URBAN
SUSTAINABILITY PERSPECTIVE .................................................................................................................................... 268 A. I. Domenech (1) and P. Jiménez-Guerrero (2) PORT-AU-PRINCE AIR POLLUTION FIRST CONCENTRATION MEASURES COMPARE TO EMISSION
INVENTORY DATA ............................................................................................................................................................ 269 A. Antoine (1), F. Bade (1), P. Nuiro (2), J. Molinie (1) USING WRF/CHEM AND EULAG CFD MODELS TO PRODUCE VERY HIGH SPATIAL AIR POLLUTION
SIMULATIONS OVER AN URBAN ENVIRONMENT: MADRID CASE STUDY .......................................................... 270 R. San José (1), J. L. Pérez (1) and R. M. González (2) SURFACE HCHO VARIATION IN URBAN AREA ........................................................................................................... 271 H. Ling (1, 2), Y. S. Wang (1) HOW IMPORTANT IS THE PM2,5 CARBONACEOUS FRACTION IN AMBIENT AIR IN MADRID (SPAIN)? ........ 272 P. Díez Hernández (1), C. Andrés Escrivá (1), M. A. Cristóbal López (2), S. García Dos Santos (1), R. Fernández
Patier (1) ENHANCEMENT OF THE SECONDARY FRACTION OF PM2.5 IN THE UPPER PART OF SANTIAGO DE CHILE 273 F. Reyes (1),(2), Y. Vásquez (1)(2), J. P. Moraga (1), R. Donoso (1), M. A. Rubio (2), E. Gramsch (2), P. Oyola (1) INFLUENCE OF TRANSPORT ON SIZE DISTRIBUTION AND PARTICLE NUMBER IN SANTIAGO DE CHILE .. 274 Y. Vásquez (1,3), F. Reyes (1,3), R. Donoso (2), J. Moraga (3), P. Oyola (1), E. Gramsch (2), M. A. Rubio (3) LONG-TERM DYNAMICS OF THE AIR POLLUTION IN MOSCOW............................................................................. 275 M. A. Lokoshchenko (1), A. V. Trifanova (2) AEROSOL PROPERTIES IN BUENOS AIRES: LOCAL AND REGIONAL CONTRIBUTIONS .................................... 276 A. G. Ulke (1,3), B. M. Torres (1), G. Raga (2), D. Baumgardner (4) and B. Kucienska (2) COVENANT OF MAYORS INITIATIVE: REDUCING GHG EMISSIONS AT LOCAL LEVEL BEYOND THE 20%
TARGET IN 2020 - AN EMPIRICAL STUDY .................................................................................................................... 277 S. Rivas et al. SPECIAL SESSION - AIR QUALITY AND CLIMATE METEOROLOGY INTERACTIONS AND FEEDBACKS ............................ 278 THE IMPACT OF CENTRAL EUROPEAN CITIES ON CLIMATE AND AIR QUALITY: PRELIMINARY RESULTS 279 P. Huszar (1), T. Halenka (1), M. Belda (1) CHANGES IN SURFACE AIR TEMPERATURE AND TRENDS IN INDICES OF TEMPERATURE IN BURGOS
(SPAIN) FOR THE PERIOD 1997-2012 ............................................................................................................................... 280 R. Viloria, V. Tricio SPECIAL SESSION - AIR QUALITY FORECASTING AND EARLY
WARNING SYSTEMS..................................................................................... 281 A WRF-EMEP FORECAST SYSTEM FOR THE HUBEI PROVINCE, CHINA ................................................................ 282 T. Svendby, S. Solberg, P. Schneider, L. Liu NEW DATA ASSIMILATION OF PM OBSERVATIONS APPROACH FOR IMPROVED PM FORECASTS ............... 283 A. Segers (1), A. Manders (1), R. Timmermans (1), and M. Schaap (1) FORECASTING THE INFLUENCE OF CLIMATE CHANGE ON EXTREME GROUND-LEVEL OZONE EVENTS
IN THE TORONTO AREA, CANADA ................................................................................................................................ 284 K. H. Y. Leung (1) and W. A. Gough (2) xiv
MODELLING OF DAILY AIR POLLUTANT CONCENTRATION PROFILES USING ASSOCIATION RULES ......... 285 R. Jasinski SPECIAL SESSION - LOCAL AND REGIONAL AIR QUALITY
SERVICES ........................................................................................................ 286 WEAK SIGNALS AND AIR QUALITY: NETWORK OF SENTINEL PHARMACISTS .................................................. 287 R. Collomp (1, 2), T. Collomp (1, 2), C. Durand (2), C. Debail (1), A. Mangin (3), O. Lesne (3), P. Sicard (3), C.
Talbot (3), A. Anziani (1), N. Alexandre (1) TOTUS – TOWARDS SUSTAINABLE URBAN FORMS .................................................................................................. 288 G. Olivares (1), E. R. Somervell (1) ATMOSYS, A GENERIC WEB PLATFORM FOR AIR POLLUTION HOT SPOTS IN EUROPE ................................... 289 N. Veldeman (1), D. Roet (2), P. Viaene (1), D. Lauwaet (1), W. Lefebvre (1), S. Vranckx (1), P. Vos (1), K. Decoene
(2), E. Trimpeneers (3), B. Maiheu (1), G. Driesen (1), N. Smeets (1), W. Peelaerts (1), T. Op ’t Eyndt (1), K. De
Ridder (1), L. Blyth (1), S. Janssen (1), E. Roekens (2) AIRDART – AIR QUALITY DATA ANALYSIS AND RETRIEVAL TOOL .................................................................... 290 A. Fraser, D. Brookes SPECIAL SESSION - TRANSPORT RELATED AIR POLLUTION SCIENCE AND IMPACTS .............................................................................. 291 EFFECT OF TRANSPORT POLICIES ON AIR QUALITY IN BIG CITIES OF THE RUSSIAN FEDERATION:
PAST, PRESENT, FUTURE ................................................................................................................................................. 292 O. V. Lozhkina, V. N. Lozhkin IMPACTS OF HARBOUR ACTIVITIES AND SHIPPING EMISSIONS IN THE AIR QUALITY OF A
MEDITERRANEAN COASTAL CITY ................................................................................................................................ 293 R. García-Cabañero (1) and P. Jiménez-Guerrero (1) UNCERTAINTIES IN HEALTH IMPACT ESTIMATES DUE TO EXPOSURE AND RESPIRATORY TRACT
DEPOSITION PROCESSES ................................................................................................................................................. 294 O. Hänninen (1), J. Roos (2), S. Karakitsios (3), P. Kontoroupis (3), D. A. Sarigiannis (3), B. Miller (4) RESIDENTIAL LONG-TERM EXPOSURE TO PARTICULATE MATTER COMPONENTS AND
CARDIOVASCULAR DISEASE ENDPOINTS IN ADULTS ............................................................................................. 295 A. Peters (1), K. Wolf (1), R. Hampel (1), R. Beelen (2), F. Forastiere (3), I. Kooter (4), A. Jedynska (4), M. Keuken
(4), B. Hoffmann (5), N. Künzli (6), T. Lanki (7), on behalf of the members of the ESCAPE work package 5 and
TRANSPHORM AIR QUALITY IN COTONOU : PARTICULATE MATTER CHARACTERIZATION AND BIOLOGICAL EFFECTS
ON HUMAN HEALTH ......................................................................................................................................................... 296 F. B. Cachon (1,2), A. Verdin (1,2), L. Ayi Fanou (3), S. Firmin (1,2), F. Cazier (1,4), S. Billet (1,2), P. J. Martin (1,2),
F. Aïssi (1), D. Courcot (1,2), P. Shirali (1,2) and A. Sanni (3) TRANSPORT RELATED EMISSION ASSESSMENT FOR PRAGUE .............................................................................. 297 N. Benesova (1), M. Kazmukova (2), H. Kazmarova (3) MESMART – MEASUREMENTS OF SHIPPING EMISSIONS IN THE MARINE TROPOSPHERE .............................. 298 F. Wittrock (1), L. Kattner (1,2), B. Mathieu-Üffing (1,2), M. Chirkov (1), A. Meier (1), A. Richter (1), A. Schönhardt
(1), V. Matthias (3), S. Schmolke (2), S. Weigelt-Krenz (2), N. Theobald (2), J. P. Burrows (1) USE OF REMOTE SENSING AND SATELLITE DATA FOR AIR
QUALITY RESEARCH ................................................................................... 299 INTERANNUAL VARIABILITY OF TROPOSPHERIC OZONE DERIVED FROM SCIAMACHY LIMB-NADIR
MATCHING OBSERVATIONS ........................................................................................................................................... 300 F. Ebojie, C. von Savigny, A. Ladstätter-Weissenmayer, A. Rozanov, M. Weber, K. Eichmann, S. Bötel, N. Rahpoe, H.
Bovensmann, J. Burrows WIND TUNNEL -PHYSICAL MODELLING ................................................ 301 EFFECT OF ATMOSPHERIC CONDITION ON POLLUTANT DISPERSION OF BUILDING STACK EMISSIONS ... 302 M. F. Yassin (1,2) M. Abu-Kassem (2) WIND TUNNEL INVESTIGATIONS OF FLOW FIELD AROUND AN ISOLATED OBSTACLE .................................. 303 E. V. Goulart (1), F. C. Cezana (1), R. R. C. de Paula (2), J. F. Stocco (2), A. Burgo (2) and S. C. Zucoloto (2) xv
xvi
PART ONE:
ORAL SESSIONS
1
KEY NOTE SPEAKERS
2
WITHIN- AND BETWEEN-CITY CONTRASTS IN NITROGEN DIOXIDE AND MORTALITY IN 10 CANADIAN
CITIES
D. L. Crouse (1), P. A. Peters (2, 3), P. J. Villeneuve (4), M.-O. Proux (2), H. H. Shin (1), M. S. Goldberg (5), M. Johnson
(6), A. J. Wheeler (6), R. W. Allen (7), D. O. Atari (8), M. Jerrett (9), M. Brauer (10), J. R. Brook (11, 12), R. T. Burnett (1)
(1) Environmental Health Science and Research Bureau, Health Canada, Ottawa, Canada; (2) Health Analysis Division,
Statistics Canada, Ottawa, Canada; (3) Department of Sociology, University of New Brunswick, Fredericton, Canada; (4)
Institute of Health: Science, Technology and Policy, Carleton University, Ottawa, Canada; (5) Department of Medicine,
McGill University, Montreal, Canada; (6) Air Health Science Division, Health Canada, Ottawa, Canada; (7) Faculty of
Health Sciences, Simon Fraser University, Burnaby, Canada; (8) Faculty of Arts & Science, Nipissing University, North Bay,
Canada; (9) School of Public Health, University of California, Berkeley, USA; (10) School of Population and Public Health,
University of British Columbia, Vancouver, Canada; (11) Air Quality Research Division, Environment Canada, Downsview,
Canada; (12) Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
Presenting author email: dlcrouse@gmail.com
Summary
This study investigated the effects of within- and between-city contrasts in exposure to ambient nitrogen dioxide (NO2) on
mortality among subjects living in 10 of the largest cities in Canada. We assigned estimates of residential-level (i.e. withincity) and citywide mean (i.e., between-city) contrasts in exposure to NO2 for each year from 1984 to 2006 to a cohort of
approximately 576,000 adults. We used historical fixed-site monitoring data to scale the exposure estimates, and residential
histories allowed us to follow subjects annually during the study period. We found positive associations between the withincity exposure contrasts and mortality from non-accidental causes, cardiovascular, ischemic heart, and respiratory diseases,
but not from cerebrovascular diseases. We also found positive associations with mortality and between-city exposure
contrasts, but they were weaker, less consistent, and more sensitive to covariate adjustment.
Introduction
Previous cohort studies in Canada, the United States, and Europe have reported positive associations between long-term
exposure to ambient air pollution and mortality rates from non-accidental causes and cardiovascular diseases. The
independent and joint effects of within- and between-city contrasts in air pollution on mortality, however, have not been
investigated adequately. Our primary objective, therefore, was to investigate associations between selected causes of
mortality and exposure to NO2 from highly spatially resolved land use regression models in 10 Canadian cities. We compared
the strength of associations between mortality and NO2 among subjects using both: a) within-city contrasts of exposure (i.e.,
residential exposures); and, b) between city contrasts in exposure (i.e., citywide mean exposures).
Methodology
Our cohort is a subset of the Canadian Census Health and Environmental Cohort (Crouse et al., 2012). We used city-specific
land use regression models developed at different times between 2002 and 2010 to assign residential and city-wide mean
exposure estimates of NO2 to cohort members for each year from 1984 to 2006. We used historical fixed-site monitoring data
to temporally scale the exposure estimates, and used residential histories to track subjects annually during the study period.
We used these data to calculate a seven-year moving window of exposure with a single year lag (e.g., for 1991, subjects were
assigned the mean of their scaled exposures – both residential and citywide mean – during the years 1984 to 1990). We then
calculated hazard ratios (HRs) per 5 parts per billion (ppb) adjusted for personal and contextual variables. Additionally we
investigated different exposure windows, and tested for effect modification by selected personal characteristics (e.g., age, sex,
income), which is of particular interest in the Canadian context where mean concentrations of pollution are relatively low.
Results and Conclusions
We found positive associations between within-city exposure contrasts and mortality from non-accidental causes,
cardiovascular, ischemic heart, and respiratory diseases, but not from cerebrovascular diseases. We found the strongest
associations among subjects who were less than 75 years of age during follow-up, and with death from ischemic heart disease
(e.g., HR per 5 ppb in models adjusted for personal and contextual covariates: 1.06, 95% confidence interval (CI): 1.03-1.08)
and respiratory diseases (HR: 1.05, 95% CI: 1.00-1.10). We were less able to demonstrate consistent and robust associations
with mortality and between-city exposure contrasts. Among subjects less than 75 years of age during follow-up, however, in
models adjusted only for personal covariates, we found HR: 1.06, 95% CI: 1.02-1.11 for death from ischemic heart disease
and HR: 1.01, 95% CI: 0.93-1.09 for death from respiratory diseases. Overall, in this large cohort we found that exposure to
long-term, within-city contrasts in NO2 was positively associated with several important causes of mortality.
References
Crouse D.L., Peters P.A., van Donkelaar A., Goldberg M.S., Villeneuve P.J., Brion O., Khan S., Atari D.O., Jerrett M., Pope
C.A., Brauer M., Brook J.R., Martin R.V., Stieb D., Burnett R.T., 2012. Risk of nonaccidental and cardiovascular mortality
in relation to long-term exposure to low concentrations of fine particulate matter: a Canadian national-level cohort study.
Environmental Health Perspectives 120(5), 708-714.
3
ESTABLISHING NEW AMBIENT AIR QUALITY STANDARDS FOR PM2.5: THE CHINESE EXPERIENCE
J. C. Chow (1,2), J. G. Watson (1,2), J. J. Cao(2)
(1) Desert Research Institute, Nevada System of Higher Education, Reno, Nevada USA 89512
(2) Key Laboratory of Aerosol Science and Technology, SKLLQG, Institute of Earth Environment, Chinese Academy of
Sciences, Xi’an, China
Presenting author email: judith.chow@dri.edu
Summary
Many countries have established ambient air quality standards, but they have often followed the lead of North America and
Europe rather than customizing these to their specific situations. Following recommendations of a joint panel of National
Academies (NRC, 2008), China has completed a process and adopted short-term and long-term limits for PM2.5 (Cao et al.,
2013; Chow et al., 2012), particles in the size range that contain the most toxic species and can penetrate into the human
respiratory system.
Introduction
Ambient Air Quality Standards (AAQS) were first established in the United States to protect public health and welfare, and
the concept has been adopted in China and many other countries. For particulate matter (PM), the NAAQS indicator evolved
from total particle mass concentration (TSP), to PM10 and PM2.5 mass concentrations as defined by the PM size-selective
properties of the monitoring instrument and human inhalation characteristics. Several options for PM2.5 measurement and
assessment are available to China and other developing countries as they implement new PM2.5 AAQS.
Methodology and Results
Table 1. Evolution of China’s AAQS for suspended particulate matter.
Table 1 summarizes the
Daily Averageb (μg/m3)
Maximum Not to Exceedc (μg/m3)
EPOa 1982
d
e
f
evolution
of
China’s
AAQS
Class I
Class II
Class III Class Id
Class IIe
Class IIIf
AAQS for PM which were
TSP
150
300
500
300
1000
1500
first established in 1982.
Airborne Particlesg 50
150
250
150
500
700
The approach was, and still
SEPAa 1996
Daily Average (μg/m3)
Annual Arithmetic Mean (μg/m3)
is, to set different limits for
AAQS
Class Id Class IIe Class IIIf Class Id
Class IIe
Class IIIf
different
environments.
TSP
120
300
500
80
200
300
Class
I
areas
were
Airborne Particlesg 50
150
250
40
100
150
designated
by
the
a 2012
3)
MEP
24
hr
Average
(μg/m
Annual
Arithmetic
Mean
(μg/m3)
particles”, which were
d
h
d
h
AAQS
Class
I
Class
II
Class
I
Class
II
renamed “inhalable PM”
TSP
120
300
80
200
(PM10) in 1996. The 1982
PM10
50
150
40
70
AAQS regulated daily
PM2.5
35
75
15
35
average and maximum notaEPO: Environmental Protection Office; SEPA: State Environmental Protection
to-exceed concentrations
Administration; MEP: Ministry of Environmental Protection. bThe daily average for 1982
of TSP and PM10. A
and
1996 was redefined as a 24-hr average in 2012. cReplaced by annual standards as of
minimum sampling time of
1996. dApplies to national parks, conservation areas, and designated historical sites.
one hour was required to
eApplies to residential and commercial areas. fApplies to industrial and heavy traffic areas.
determine
the
not-togDefined as airborne particles with d < 10 μm; redefined as inhalable particulate matter
p
exceed concentration. To
(PM10) in 2011. hApplies to residential, commercial, cultural, industrial, and heavily
compute a daily average, at
trafficked areas. Previous Class III areas are included in Class II.
least two intervals with total
sample durations >6 hr
were needed for TSP), and at least four intervals with each sample duration > 1 hr required for airborne particles. The 1996
AAQS replaced the 1982 approach with daily and annual arithmetic average limits for TSP and airborne particles. A sample
duration of 12 to 24 hrs was required to compute a daily average. For the annual average, each month was represented by five
or more daily averages, and these 12 monthly averages were averaged for the year, with the provision of at least 60 daily
samples distributed throughout the year. The 2012 AAQS add PM2.5 as an indicator, requiring 20 to 24 valid hourly
concentrations for the daily average and at least 324 daily averages with ≥27 per month each month (≥ 25 for February) to
compute annual average.
Conclusions
Although much can be learned from the experience of the U.S. and Europe, China can leapfrog ahead in terms of PM2.5
monitoring and emission reduction technology. China-specific guidance documents should be created for network design,
equipment selection and operation, quality control and quality assurance, database management, and interpretation.
References
Cao, J.J.; Chow, J.C.; Lee, S.C.; Watson, J.G. (2013). Evolution of PM2.5 measurements and standards in the U.S. and future
perspectives for China. AAQR, 13(4):1197-1121. http://aaqr.org/VOL13_No4_August2013/5_AAQR-12-11-OA0302_1197-1211.pdf.
Chow, J.C.; Cao, J.J.; Lee, S.C.; Wang, X.L.; Watson, J.G. (2012). A brief history of PM2.5 and its adverse effects (in
Chinese).
Journal
of
Earth
Environment,
3(5):1019-1029.
doi:10.7515/JEE201205001.
http://dqhjxb.paperopen.com/Upload/PaperUpLoad/c7436a2c-4ca3-4487-8580-67e1169973bb.pdf.
NRC (2008). Energy Futures and Urban Air Pollution Challenges for China and the United States. National Academies
Press: Washington, DC.
4
AN OBSERVATIONAL PERSPECTIVE OF THE IMPACT OF ATMOSPHERIC WEATHER STATES ON
CARBON MONOXIDE LEVELS IN THE FREE TROPOSPHERE OVER THE NORDIC COUNTRIES
M. A. Thomas (1) and A. Devasthale (1)
(1) Research department, Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden
Presenting author email: Manu.Thomas@smhi.se
Summary
One of the major pathways of the inter-continental transport of pollution to the Arctic passes over the Nordic countries,
wherein pollution is often carried from the continental European region. The pollution transport from the North American
and Asian regions also reaches in the free troposphere (FT) of the Nordic countries. The transport component in the FT can
sometimes amount to a significant fraction of the total column values. The short-term variability of the pollutant levels in the
FT is very sensitive to the atmospheric weather state, which would eventually determine the fate of the pollutants. Therefore,
it is of great importance that we understand and quantify the sensitivity of pollutants to the large-scale atmospheric
circulation. Here, using a decade of satellite retrievals of carbon monoxide (CO), we examined this sensitivity over the
Nordic countries. We focused major atmospheric states that occur over the Nordic countries and investigated variability in
CO levels during different persistency periods of these weather states.
Introduction
Although atmospheric weather states and large-scale circulation have first order impact on the spatio-temporal and vertical
distribution of pollutants locally, a little is known regarding sensitivity of pollutants to these weather states from an
observational perspective. With the availability of data sets from advanced satellite sensors since nearly a decade, it is now
possible to gain insights into these aspects. This is attempted in the present study.
Methodology and results
We first analysed mean sea level pressure (MSLP) and 850
hPa winds averaged over southern Sweden [55N-65N, 10E20E] to classify atmospheric weather states and large-scale
circulation patterns. We then used retrievals from two
completely independent satellite sensors, MOPITT and
AIRS-Aqua, for the 10-yr period of 2003 till 2012 to
compute CO mean concentrations during these different
weather states. The data at three vertical levels, namely at
850, 500 and 300 hPa are analysed. The figure here shows
CO from AIRS at 500 hPa under different atmospheric
states. The top (bottom) row shows CO levels when MSLP
over southern Sweden was greater (lower) than one standard
deviation and this atmospheric state persisted for at least 3,
5 and 7 days. The elevated levels of CO are observed when
stable conditions persist. An interesting feature is that when
MSLPs is high, CO levels continue to increase as the high
persists, while in the case of lower MSLPs atmosphere
becomes cleaner. The latter is mainly due to advection of
cleaner air and wet deposition.
Conclusions
Using satellite observations, we show that the CO levels in the FT over the Nordic countries are sensitive to atmospheric
weather states and their persistency. Strong differences in CO levels are observed when MSLPs are high versus when they
are low. More detailed investigations will be presented later considering wind directions and their persistency as well. These
results are also useful to carry out process oriented evaluation of chemistry transport models.
References
Devasthale, A., and Thomas, M. A., An investigation of statistical link between inversion strength and carbon monoxide over
Scandinavia in winter using AIRS data, Atmos. Environ, doi:10.1016/j.atmosenv.2012.03.042, 2012.
5
INTEGRATED ASSESSMENT OF POLICIES FOR REDUCING HEALTH IMPACTS OF AIR POLLUTION
CAUSED BY TRANSPORT IN EUROPE
R. Friedrich, J. Roos, C. Schieberle
Institute of Energy Economics and the Rational Use of Energy (IER), University of Stuttgart, Germany
Presenting author email: rf@ier.uni-stuttgart.de
Summary
This paper describes a new methodology to assess polices for reducing environmental pressures of transport, that lead to
health impacts and climate change. The assessment is Europe-wide, but nonetheless capable of dealing with polices for cities.
The methodology is applied to assess 26 urban and non-urban transport policies and rank them according to their
effectiveness and efficiency.
Introduction
Transport contributes considerably to emissions of air pollutants and greenhouse gases and thus to environmental health
impacts in Europe. Further reduction of these pressures is necessary; a number of policies for reducing emissions is
discussed. To be able to support decision making by finding the most effective and efficient policies, an assessment of the
policies has to be made by estimating for each policy the avoided health impacts, the avoided greenhouse gas emissions and
the costs.
Methodology and Results
The methodology for estimating health impacts
follows the ‘impact pathway approach’ as presented
in Fig. 1. First, the most promising policies for
reducing health impacts and climate change caused
by transport (all modes) are identified, this includes
13 measures to be implemented for road transport in
cities (from a certain defined size on), 8 measures for
all road transport, three policies for ship transport
and two for air transport. Then Europe-wide
reference scenarios are generated for the years 2005,
2020 and 2030, using updated emission factors
provided by Samaras (2012) and updated transport
activity data provided by Ypermann et al. (2012).
Results show, that in 2005, road transport is the
dominating source for emissions of air pollutants,
however due to EU regulations (e.g. EURO 4, 5 and
6 standards), these emissions are largely reduced –
with the exception of emissions from abrasion processes (tyre, break, road wear). Thus in 2030 maritime transport is the
transport mode with the highest emissions. Then, for the identified policies, policy scenarios are prepared. A new
methodology was developed to estimate the effects of the urban policies on the emissions in each of the relevant cities in the
EU28+2. The next step is the estimation of concentrations of pollutants. The challenge here is, that on the one hand the
calculation has to be done for the whole European domain, on the other hand it has to be detailed enough to take account of
the specific situation in each of the major cities in Europe. In addition the large number of scenarios makes it unfeasible to
use full runs of Eulerian models. We use here a two step approach. For regional modelling, we use a parameterized version
of a European-wide Eulerian model, the Unified EMEP Model 2003. The parameterized version uses “Source-ReceptorMatrices” provided by the EMEP team, which describe the change in concentrations of an atmospheric pollutant in each of
ca. 14 600 grid cells (with a size of 50km*50km), if the emission of a substance changes by one unit in one of 65 European
regions. Releases from high stacks are treated differently from low releases. For the city modelling, a new approach for
estimating urban increments described in Torras et al. 2013 is used. Using updated concentration-response functions prepared
in TRANSPHORM, health impacts are estimated. The difference in health impacts and greenhouse gas emissions between
the reference scenario and the policy scenario is then allocated to the policy. Results show, that especially improved tyres and
brake pads, that are more durable, and tighter emissions limits for ships are the most effective of the analysed measures.
Conclusions
A new methodology for assessing the health impacts of policies for reducing transport related health effects has been
developed. The methodology allows to rank policies according to their effectiveness and efficiency and thus contributes to
achieving a more sustainable transport.
Acknowledgement
This work was supported by the EU 7'th framework project TRANSPHORM.
References
Samaras, Z. (2012), Aristotle University of Thessaloniki, personal commumication within TRANSPHORM
Torras et al. 2013: Torras Ortiz, S., Friedrich, R.: A modelling approach for estimating background pollutant concentrations
in urban areas, Atmospheric Pollution Research 4 (2013) 147‐156
Unified EMEP Model 2003: Unified EMEP Model Description, http://www.emep.int/index_model.html
Yperman, I., de Ceuster, G. (2012), Transport & Mobility Leuven, personal commumication within TRANSPHORM
6
DEVELOPMENTS IN REGIONAL AND LOCAL AIR QUALITY MONITORING AND FORECASTING –
RESULTS OF PASODOBLE
T. Erbertseder (1), D. Balis (2), C. Bergemann (1), L. Blyth (3), D. Carruthers (4), S. Choudrie (5), A. De Rudder (6), W. Di
Nicolantonio (7), H. Elbern (8), H. Eskes (9), E. Friese (8), K. Ganev (10), T. Holzer-Popp (1), J. Kukkonen (11), O. Lesne
(12), D. Melas (2), J. Meyer-Arnek (1), F. Prata (13), P. Sicard (12), N. Smeets (3), M. Sofiev (11), A. Stidworthy (4), R.
Timmermans (14), N. Veldeman (3), H. Zelle (15) and the PASODOBLE consortium
(1) Deutsches Zentrum für Luft- und Raumfahrt (DLR), Germany; (2) Aristotle University Thessaloniki, Greece; (3) Flemish
Institute for Technological Research (VITO), Belgium; (4) Cambridge Environmental Research Consultants, UK; (5)
Ricardo-AEA, UK; (6) Belgian Institute for Space Aeronomy (BIRA), Belgium; (7) Compagnia Generale per lo Spazio
(CGS-OHB), Italy; (8) Rheinisches Institut für Umweltforschung (RIU), Germany; (9) Royal Netherlands Meteorological
Institute (KNMI), Netherlands; (10) National Institute for Geophysics, Geography and Geodesy, Bulgaria; (11) Finnish
Meteorological Institute (FMI), Finland; (12) ACRI-ST, France; (13) Norwegian Institute for Air Research (NILU), Norway;
(14) Netherlands Organisation for Applied Scientific Research (TNO), Netherlands; (15) BMT-ARGOSS, Netherlands
Presenting author email: thilo.erbertseder@dlr.de
Summary
Within the framework of the European Earth Observation Programme Copernicus/GMES, PASODOBLE has developed
information services and tools on air quality in more than 30 regions and cities throughout Europe. In close collaboration
with local stakeholders and agencies existing user requirements were analysed to develop improved air quality monitoring,
assessment and forecasting services (www.myair.eu). Innovative approaches were followed by combining space-based
observations, in-situ measurements, chemical-transport modelling and information technology. This paper will present an
overview of the PASODOBLE results that were achieved from 2010 to 2013. The results comprise new developments on
health community support services, air quality modelling and forecasting including data assimilation, air quality model
evaluation, compliance monitoring and assessment support as well as improved and harmonized web services and interfaces.
Introduction
Considering the adverse health effects of air pollution, monitoring, assessing and forecasting of air quality are fundamental to
increase the quality of life particularly in air pollution hot spots. Air quality services play an important role in raising public
awareness, advising people at risk, and in providing information to stakeholders and policy makers e.g. to comply with
legislation and implement mitigation management plans. However, it has become evident that information gaps between
existing data, methods and the requirements of different user communities need to be bridged. Recent research has clearly
demonstrated the necessity for air quality information at regional and local scales. PASODOBLE sought to improve air
quality information, introduce innovative services and develop a harmonized technical infrastructure.
Methodology and Results
Satellite-based observations, in-situ measurement networks, chemical-transport modelling and information technology have
been combined to improve air quality monitoring, assessment and forecasting services in response to requirements of local
and regional stakeholders. In collaboration with the health community, services have been developed to provide appropriate
and timely information to hospitals, pharmacies and doctors to mitigate the potentially harmful effects of air pollution among
vulnerable groups. Short-term exposure to a mixture of pollutants as well as different pathologies and age classes have been
accounted for. Improved forecasting services further comprise a combination of chemical, physical and biological
components. They were used for events like the Olympic Games in London in 2012 to provide health advice to the athletes.
The regional and local scale models were subject to nesting into global and European scale forecasts of the Copernicus
Atmosphere Service (MACC-II). Improvements in forecast skill and chemical analyses were obtained by additional
assimilation of in-situ measurements at traffic sites at high spatial model resolution (1x1km) and by considering orographic
effects in mountainous terrain. To enable a harmonized evaluation of the forecasting models, a comprehensive evaluation
toolkit has been developed, which is now available to the community. Concerning air quality assessments, highly resolved
traffic scenario services for cities have been developed. PASODOBLE introduced satellite-based information as
complementary source for supporting compliance monitoring of particulate matter. New retrieval techniques enable the
differentiation of natural and anthropogenic particulate matter contributions. All these developments where embedded in a
technical framework aiming at a harmonized European infrastructure for air quality services.
Conclusions
Through its developments PASODOBLE has bridged gaps between existing data, methods and end user needs, by supporting
key players with customized solutions. Building upon the Copernicus Atmosphere Service (MACC), PASODOBLE has
linked satellite data, in-situ networks and air quality modelling to complementary downstream applications. By developing a
generic technical infrastructure, interoperability and implementation efficiency have been significantly increased.
Acknowledgement
PASODOBLE was funded by the European Commission within the 7th Framework Programme for Research.
References
Erbertseder, T. and the PASODOBLE consortium: Take a deep breath with Myair Services - Window on Copernicus, p.4451, 2012, available from: http://copernicus4regions.eu/publications/window-on-copernicus-en/at_download/file
7
AIR QUALITY MANAGEMENT IN CITIES – A NEVER ENDING STORY?
U. Reuter (1), R. Kapp (1)
(1) City of Stuttgart, Office for Environmental Protection, Department of Urban Climatology, Gaisburgstraße 4,
70182 Stuttgart, Germany
Presenting author email: ulrich.reuter@stuttgart.de
Summary
The EU limit values for air pollution are exceeded in many cities near streets with much traffic. This concerns nitrogendioxid
(NO2) and small particles (PM10). Main source for the pollution is the traffic. So measures have to be concentrated mainly in
the field of traffic. The consequence is, that air quality management has a lot of impacts on the traffic. Effective measures are
traffic bans for heavy vehicles and the implementation of environmantal zones, where only cars with little emissions are
allowed to drive. Speed reductions are especially effective, if they are combined with a better traffic flow (see Fig. 1). Also
special street constructions with photokatalytic effects can reduce air pollution. All these measures are effective in reducing
the air pollution. This is shown with a focus on the city of Stuttgart, where in the last years the highest air pollution
concentrations in Germany have been registrated. Up to now the limit values are exceeded despite the measures, so other
measures are necessary. It is discussed, what can be done. But is all this enough to reach the limit values?
Introduction
The air quality guidelines of the EU define limit values
for different air pollutants. Especially for PM10 and NO2
the limit values are exceeded near streets with a lot of
traffic. For both components there is an annual mean
value of 40 µg/m3. Concerning PM10 a daily mean of
50 µg/m3 may be exceeded not more than 35 days a year.
Concerning NO2 an hourly value of 200 µg/m3 may be
exceeded not more than 18 times a year. If the limit
values are exceeded, air quality action plans have to be
implemented to reduce the pollution.
Air Quality Measures and Results
In many cities air quality strategies were implemented.
Very effective measures are traffic bans for heavy
Fig. 1 Dynamic speed limit (40 km/h) in Stuttgart reducing
vehicles and environmental zones. For example in
number of stops
Stuttgart heavy traffic is only allowed if goods are
delivered or picked up.in the city. In the whole city of Suttgart only cars with low emissions are accepted. They have to be
identified by a green label which is defind by national law. Meanwhile also speed reductions to 40 km/h have been
introduced in Stuttgart. According to scientific studies this measure is especially effective on uphill streets.
Further measures concern the improvement of public traffic, a special management of car parking and efforts in the field of emobility. In Stuttgart a “Recharging infrastructure” for electricity was implemented and electric cars don’t have to pay
parking fees. 450 small cars are available in a carsharing system (e-car2go). With a special mobile pass the mobility systems
of public traffic, carsharing, bycicles and other public offers have been combined. By all these measures effective reductions
of air pollution could be reached (see Fig. 2). For example at a hot
spot measurement point in Stuttgart the NO2 hourly limit value was
exceeded more than 800 times per year some years ago. In 2012 there
were only 69 hours with concentrations above 200 µg/m3. Finally
despite all thes effective measures the limit values for the air
pollutants are still exceeded.
Conclusions
As with the measures up to now it is not possible to hit the limit
values, new measures are necessary. But these have to be more
restrictive than the ones up to now, perhaps an environmental zone
Fig. 2 Exceeding of NO2 limit value
without diesel vehicles or for cars only with low fuel consumption, in
(one hour, not to be exceeded more than 18 times a
order also to reduce the CO2 emissions? We have to suppose that the
calendar year) at two sampling points in Stuttgart
(near the street)
development of e-mobility will advance too slowly to be an effective
measure in the coming years. The question arises, wether or not the EU
regulations concerning the car emissions and the air pollution immission regulations are a good match.
References
Council Directive 2008/50/EC on ambient air quality and cleaner air for Europe
Council Directive 96/62/EC on ambient air quality assessment and management
Luftreinhalte- und Aktionsplan für den Regierungsbezirk Stuttgart, Fortschreibung, Februar 2010
WHO Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide; global update 2005;
Summary of risk assessment World Health Organization. Occupational and Environmental Health Team, 2006
8
THE REVIEW OF AIR POLICY – WHAT IS IN FOR THE MEASUREMENT COMMUNITY?
A. Borowiak (1) and D. Buzica-Widlowski (2)
(1) Joint Research Centre, European Commission, Institute for Environment and Sustainability, Air & Climate Unit, TP 441,
21027 Ispra, Italy
(2) Environment Directorate-General, European Commission, Air & Industrial Emissions Unit, 1049 Brussels, Belgium
Presenting author email: annette.borowiak@jrc.ec.europa.eu
Summary
Commissioner Potočnik has announced 2013 as the Year of Air. The European Commission is therefore carrying out a
thorough review of European air policy to shape a new strategy to improve air quality in the EU. Major issues tackled are
compliance and implementation of current regulations, protection of human health and the environment, promotion of cleaner
products and processes and creating better coherence with other international initiatives and policies.
Introduction
The European Commission estimates that air pollution caused 420.00 people to die prematurely in the EU in 2010. The air
pollutants of biggest concern are fine particles, ground level ozone and nitrogen dioxide. Latest studies from the World
Health Organisations (WHO) show that long term exposure to fine particles is linked with cardiovascular and respiratory
deaths and increased sickness. Further bad air quality causes significant damage to environment and ecosystems, by
acidification, eutrophication or reducing plant growth rate. As air pollution ignores national borders it needs to be tackled
through co-operation at European and international level.
Methodology and outlook
The basis for the starting of the review process are the international (UNECE convention and protocols) and the European
policy frameworks (as ambient air quality directive, national emission ceiling and source regulations). Emission trends are
not matched by air quality improvements. Air quality limit values are still exceeded and a significant percentage of European
citizens is living in zones that are not complying with limit and target values for the protection of human health. The review
of the Thematic Strategy on Air Pollution is comprising many elements: Reduction scenarios and sectoral analysis take place,
synergies with other policies (e.g. climate) are explored, two public consultations have been arranged and evaluated, Member
States and stakeholders meet and discuss regularly with the Commission, the WHO is advising on latest health evidence of
air pollution, the scientific communities of European Research projects under FP 7 provided a review on important scientific
results, as well as the networks AQUILA (National Air Quality Reference Laboratories) and Fairmode (Air Quality
Modelling).
The AQUILA Network comprises 37 institutes or laboratories that are responsible for the quality of air pollution
measurements in their Member States. The Network was founded more than 10 years ago and is discussing and advising on
issues related to measurements in European air policy. Meetings are dedicated to topics of special interest, as equivalence of
methods, type approval of instrumentation, or accreditation requirements. The latest meetings have been dedicated to the
recommendations that AQUILA has given to the review of air policy. Details of the recommendations and an outlook on the
review process and its outcome will be given.
9
ENVIRO-HIRLAM ONLINE INTEGRATED METEOROLOGY-CHEMISTRY MODELLING SYSTEM:
STRATEGY, METHODOLOGY, DEVELOPMENTS AND APPLICATIONS
A. Baklanov (1), U. Korsholm (1), R. Nuterman (2), K. P. Nielsen (1), B. H. Sass(1), A. Mahura (1), A. Rasmussen(1), B.
Sørensen (2), E. Kaas (2), I. González-Aparicio (3), A. Mažeikis (4), A. Kurganskiy (5), E. Morozova (5), S. Ivanov (6), Y.
Palamarchuk (6), A. Zakey (1), J. Chenevez (1), A. Gross (1), K. Lindberg (1)
(1) Danish Meteorological Institute (DMI), Copenhagen, Denmark; (2) University of Copenhagen, Denmark; (3)
Vilnius University, Lithuania; (4) TECNALIA Research and Innovation, Derio, Spain; (5) Russian State
Hydrometeorological University, St.-Petersburg, Russia; (6) Odessa State Environmental University, Ukraine
Presenting author email: alb@dmi.dk
Enviro-HIRLAM is developed as a fully online coupled numerical weather prediction (NWP) and Chemical Transport model
for research and forecasting of joint meteorological, chemical and biological weather. The integrated modelling system is
developed by DMI and other collaborators (Chenevez et al., 2004; Baklanov et al., 2008a, 2011b; Korsholm et al., 2008,
2009; Korsholm, 2009). It is the baseline system in the HIRLAM Chemical Branch and used in several countries. The
development was initiated at DMI about 15 years ago. The first version was based on the DMI-HIRLAM NWP model with
online integrated pollutant transport and dispersion (Chenevez et al., 2004), chemistry, deposition and indirect effects
(Korsholm, 2009) and aerosol dynamics (Gross and Baklanov, 2004). To make the model suitable for chemical weather
forecasting in urban areas the meteorological part was improved by implementation of urban parameterizations (Baklanov et
al., 2008b; Mahura et al., 2008; González-Aparicio et al., 2012). The dynamic core was improved by adding a locally mass
conserving semi-Lagrangian numerical advection scheme (Kaas, 2008; Sørensen, 2012; Sørensen et al., 2013), which
improves forecast accuracy and speed of simulations. The latest developing version (Nuterman et al., 2013) is based on
HIRLAM reference version 7.2 with a more sophisticated and effective chemistry scheme, multi-compound modal approach
aerosol dynamics modules, aerosol feedbacks on radiation (direct and semi-direct effects) and on cloud microphysics (first
and second indirect effects).
Since 2004 the modelling system is used for different research studies, including since 2009 operational pollen forecasting
for Denmark. Following main development strategy (Baklanov, 2008; Baklanov et al., 2011a) for the HIRLAM community,
the Enviro-HIRLAM further developments will be moving towards the new HARMONIE NWP platform by incorporation of
the developed chemistry modules and aerosol–radiation–cloud interactions into the future Enviro-HARMONIE integrated
system. Different aspects of the online coupling methodology, research strategy and possible applications of the modelling
system, and ‘fit-for-purpose’ model configurations for the meteorological, air quality and climate research communities are
discussed.
References
Baklanov, A.: Integrated meteorological and atmospheric chemical transport modeling: perspectives and strategy for
HIRLAM/HARMONIE, HIRLAM Newsletter, 53, 68–78, 2008.
Baklanov, A., Korsholm, U., Mahura, A., Petersen, C., and Gross, A.: ENVIRO-HIRLAM: on- line coupled modelling of urban
meteorology and air pollution, Adv. Sci. Res., 2, 41–46, doi:10.5194/asr-2-41-2008, 2008a.
Baklanov, A., Mestayer, P. G., Clappier, A., Zilitinkevich, S., Joffre, S., Mahura, A., and Nielsen, N. W.: Towards improving the
simulation of meteorological fields in urban areas through updated/advanced surface fluxes description, Atmos. Chem. Phys., 8, 523–
543, doi:10.5194/acp-8-523-2008, 2008b.
Baklanov, A., Mahura, A., and Sokhi, R. (Eds.): Integrated Systems of Meso-Meteorological and Chemical Transport Models, Springer,
242 pp., doi:10.1007/978-3-642-13980-2, 2011a.
Baklanov, A. A., Korsholm, U. S., Mahura, A. G., Nuterman, R. B., Sass, B. H., and Zakey, A. S.: Physical and chemical weather
forecasting as a joint problem: two-way interacting integrated modelling, in: American Meteorological Society 91st Annual Meeting,
23–27 January 2011, Seattle, WA, USA, Paper 7.1 (Invited Speaker), AMS2011 paper 7-1 fv.pdf, 2011b.
Chenevez, J., Baklanov, A., and Sørensen, J. H.: Pollutant transport schemes integrated in a numerical weather prediction model: model
description and verification results, Meteorol. Appl., 11, 265–275, 2004.
González-Aparicio, I., J. Hidalgo, A. Baklanov, U. Korsholm, R. Nuterman, A. Mahura, O. Santa-Coloma: Urban boundary layer analysis
in the complex coastal terrain of Bilbao using Enviro-HIRLAM. Theoretical and Applied Climatology. 01/2012; 110(4), 2012.
Gross, A. and Baklanov, A.: Modelling the influence of dimethyl sulphid on the aerosol production in the marine boundary layer, Int. J.
Environ. Pollut., 22, 51–71, 2004.
Korsholm, U. S.: Integrated modeling of aerosol indirect effects – development and application of a chemical weather model, PhD thesis
University of Copenhagen, Niels Bohr Institute and Danish Meteorological Institute, Research department, available at:
http://www.dmi.dk/dmi/ sr09-01.pdf, last access: 28 April 2013, 2009.
Korsholm, U. S., Baklanov, A., Gross, A., Mahura, A., Hansen Sass, B., and Kaas, E.: Online coupled chemical weather forecasting based
on HIRLAM – overview and prospective of Enviro-HIRLAM, HIRLAM Newsletter, 54, 151–168, 2008.
Korsholm, U. S., Baklanov, A., Gross, A., and Sørensen, J. H.: On the importance of the meteorological coupling interval in dispersion
modeling during ETEX-1, Atmos. Environ., 43, 4805–4810, 2009.
Kaas, E.: A simple and efficient locally mass conserving semi-Lagrangian transport scheme, Tellus A, 60A, 305–320, 2008.
Mahura A., C. Petersen, A. Baklanov, B. Amstrup, U. S. Korsholm, K. Sattler, "Verification of Longterm DMI-HIRLAM NWP Model
Runs Using Urbanisation and Builing Effect Parameterization Modules". HIRLAM Newsletter, vol. no.53, no. 11pp, 2008.
Nuterman, R., Korsholm, U., Zakey, A., Nielsen, K. P., Sørensen, B., Mahura, A., Rasmussen, A., Mazeikis, A., Gonzalez-Aparicio, I.,
Morozova, E., Sass, B. H., Kaas, E., and Baklanov, A.: New developments in Enviro-HIRLAM online integrated modeling system,
Geophysical Research Abstracts, vol. 15, EGU2013-12520-1, 2013.
Sørensen, B.: New mass conserving multi-tracer efficient transport schemes focusing on semi- Lagrangian and Lagrangian methods for
online integration with chemistry, PhD Thesis, University of Copenhagen, Danish Meteorological Institute, Copenhagen, Denmark,
2012.
Sørensen, B., Kaas, E., Korsholm, U.S.: A mass conserving and multi-tracer efficient transport scheme in the online integrated EnviroHIRLAM model. Geosci. Model Dev., 6,1029-1042, doi:10.5194/gmd-6-1029-2013, 2013.
10
EMEP MODEL SIMULATIONS OF PM LEVELS IN EUROPE UNDER THE GOTHENBURG PROTOCOLL
AND MEASURES TO REDUCE FURTHER AMMONIA EMISSIONS FROM AGRICULTURE
C. Guerreiro (1), M. Beauchamp, B. Bessagnet (2), S. Tsyro (3)
(1) Norwegian Institute for Air Research (NILU) 2027 Kjeller, Norway; (2) National Institute for Industrial Environment and
Risks (INERIS), 60550 Verneuil-en-Halatte, France; (3) Norwegian Meteorological Institute (Met.no) 0313 Oslo, Norway
Presenting author email: cbg@nilu.no
Summary
Particulate matter (PM) prevails as the main air quality problem in Europe, as it continues to pose the greatest risk to human
health. Exceedances of the European PM standards are widespread and the development in annual mean concentrations from
2002 to 2011 indicates a slow decrease in PM10 averaged across Europe, but a small increase in PM2.5 levels measured at
regional and especially urban background stations (EEA, 2013). Simulations using the EMEP model combined with
measurement data show that the emission reductions agreed under the revised Gothenburg protocol (GP) will contribute to
reduce considerably PM levels across Europe, but will still be far from sufficient to achieve compliance. About one third of
PM10 and half of PM2.5 in Europe is composed by secondary inorganic aerosols (SIA). Emissions of the SIA precursor gases
NOx and SOx have decreased considerably over the last decade (27% and 50%, respectively), while NH3 emissions have
only decreased by 7%. Agriculture was responsible for 93% of the ammonia (NH3) emissions in 2011 (EU27) and there are
proven and feasible methods to control and mitigate ammonia emissions from agriculture which could cut ammonia
emissions by about 30% on top of current legislation. Simulations of PM concentrations in 2020, with a reduction of 30% of
NH3 emissions from agriculture beyond the GP, show that considerable reductions can be achieved in PM10 and specially
PM2,5 concentrations, leading to further reductions in exceedances of PM standards in Europe.
Introduction
PM levels across Europe continue to cause significant negative impacts on human health. Although ammonium constitutes
only a small fraction of the PM mass, it plays a decisive role in the formation of SIA, determining the amounts of ammonium
sulphate ((NH4)2SO4)) and ammonium nitrate (NH4NO3) as PM constituents. Several studies point out the importance of
agricultural NH3 emissions to PM concentrations in different European regions, highlighting the need to investigate the
potential of NH3 emission reductions to reduce PM levels over Europe. We have therefore used the EMEP model to quantify
the reductions in PM2.5 and PM10 concentrations due to reductions of agricultural NH3 emissions beyond the GP.
Methodology and Results
Simulations of PM2.5 and PM10 concentrations using the EMEP
MSC--W model, with a resolution of 0.25° x 0.25° and 2009
meteorology, were undertaken for 5 scenarios: 2009 emissions, GP
emissions in 2020, and further 10%, 20% and 30% NH3 agriculture
emission reductions in EU27 beyond the GP. Results show that the
GP alone will contribute to a 21, 28 and 30% reduction of the PM10
daily limit value (LV), PM10 annual LV and PM2.5 LV in 2020,
respectively. Hence further measures are needed to achieve
compliance. A further reduction of 30% of NH3 agriculture
emissions may contribute to reduce the exceedances of the PM10
daily LV, PM10 annual LV and PM2.5 LV further by respectively 8, 5
and 11% in 2020, compared to the GP. Annual mean PM2.5
concentrations across Europe may also be considerably reduced,
especially in Central and Central-Eastern Europe, reaching a 10%
reduction in Belgium, Germany, the Czech Republic and Poland
(figure 1).
Conclusions
The emissions reductions imposed by the revised GP for 2020 will
not suffice to achieve compliance with PM standards in Europe;
hence further European measures should be considered. NH3
emissions from agriculture can be further reduced, in order to reduce
PM levels and their impacts on human health across Europe.
Fig.1 Reduction of PM2.5 annual mean (%) due to 30%
reduction in NH3 agriculture emissions, compared to GP
Acknowledgement
This work was founded by the European Environmental Agency and co-founded by the French Ministry in charge of Ecology
for INERIS. All results are presented in Beauchamp et al (2013).
References
Beauchamp, M., Bessagnet, B., Guerreiro, C., Leeuw, F., Tsyro, S., Ruyssenaars, P., Sauter, P. et al, 2013, Sensitivity
analysis of ammonia emission reductions on exceedances of PM air quality standards, ETC/ACM Technical Paper 2013/12.
EEA (2013) Air quality in Europe — 2013 report, EEA Report No 9/2013, Office for Official Publications of the European
Union, ISBN 978-92-9213-406-8.
11
USING REGIONAL AIR QUALITY MODELS FOR ASSESSING THE EFFICACY OF EMISSION CONTROL
STRATEGIES IN MEETING THE RELEVANT AMBIENT AIR QUALITY STANDARDS
P. S. Porter (1), S. T. Rao (2), C. Hogrefe (3), and R. Mathur (3)
(1) Porter-Gego, Idaho Falls, ID, USA, 83401; (2) NCSU, Raleigh, NC 27695, USA;
(3) USEPA, ORD, RTP, NC, USA, 27711
Presenting author email: strao@ncsu.edu
Summary
In the United States, regional-scale photochemical models are being used to design emission control strategies needed to
meet and maintain the relevant air quality standards as part of the attainment demonstration process. Four methods for
assessing the efficacy of emission perturbation scenarios using modeled ozone concentrations were compared, including: the
commonly-used relative reduction factor (RRF) approach, spectral decomposition adjustment of model estimates on daily
time scales, spectral decomposition adjustments on hourly time scales, and Cumulative Distribution Function (CDF)
mapping. Ozone concentrations were simulated by the Community Multiscale Air Quality (CMAQ) model for the
northeastern US domain for the year 2002. Factors for adjusting 2002 modeled ozone concentrations so that relevant
statistical characteristics match those observed in 2002 were calculated and applied to 2005 model estimates. The adjusted
2005 model estimates were then compared to 2005 observations. Results reveal that it is important to not only reduce the
bias in the model results but also reproduce other statistical properties (i.e., variability and extreme values) seen in the
observations.
Introduction
In this paper, we present innovative approaches to correct for the model bias and error in order to provide greater confidence
in the use of models for designing emission control strategies needed to meet the relevant air quality standards. Previous
studies have shown that current models have large biases and errors in simulating the absolute levels of pollutant
concentrations; nonetheless, it is thought that models might be useful for examining various "what if" scenarios on a relative
basis (RRF approach). However, recent research has revealed that it is difficult to assess the credibility of models in
reproducing even relative changes in air quality stemming from past changes in emissions because of uncertain emission
inventories, boundary conditions, and inadequate representation of physics and chemistry in models. Even if the model input
data and air quality models were perfect, there is an inherent uncertainty in the model results: because the state of the
atmosphere is not known completely, its future state cannot be predicted perfectly. These issues suggest that model outputs
constrained by the observations could yield more robust methods for using regional air quality models for policy analysis.
Methodology and Results
Temporal components representing intra-day, diurnal, synoptic and seasonal forcings were extracted from time series of
observed and modeled ozone. Model components for the year 2002 were rescaled so that the mean and variance matched
those observed. The same scaling was then applied to 2005 model outputs. Using simulated and observed ozone
concentrations over the modeling domain for the years 1993-2005, the robustness of the proposed methodologies was
evaluated.
Conclusions
This paper illustrates several methodologies for applying regional photochemical models in demonstrating the attainment of
the ozone air quality standard from the regulatory perspective. Specifically, we introduce spectral decomposition and CDFmapping techniques to adjust for the bias and variance in the simulated ozone concentrations. When the model is replicating
what is seen in observations, we can then test whether a given emission reduction scenario would lead to compliance with the
ozone standard in the model domain. Subsequently, deterministic model results can be expressed in probabilistic form so that
the chances of compliance with the relevant air quality standard associated with a given emission control case can be
determined.
Acknowledgement
This research is supported by the Coordinating Research Council, Inc. contract A-89.
12
AIRBORNE PARTICULATE MATTER AND ASSOCIATED HEALTH IMPACTS: NEW DEVELOPMENTS AND
IMPLICATIONS FOR EUROPE
R. S. Sokhi and TRANSPHORM Partners
Centre for Atmospheric and Instrumentation Research (CAIR)
University of Hertfordshire, Hatfield, Hertfordshire, AL10 9AB, UK
Presenting author email: r.s.sokhi@herts.ac.uk
Summary
As part of an extensive European collaboration, developments are reported of improved measurements, modelling and
assessment approaches for quantifying the health impact of airborne particulate matter (PM) on city and continental scales. In
addition to developing improved emissions, measurements of PM in European cities have been undertaken and analysed to
determine contributions to PM2.5 from transport and other source sectors. An integrated approach for estimating population
exposure and health impacts resulting from PM has been demonstrated for European applications. The presentation will
highlight major outcomes from the TRANSPHORM project with particular emphasis on European air quality and
implications for policy makers.
Introduction
Exposure to particulate matter (PM) is a key contributor to adverse health impacts. Quantification of health impacts resulting
from air pollutants such as PM relies on a number of factors including reliable emissions, knowledge of their characteristics
and composition and prediction of concentrations and exposure levels. Through the use of concentration response functions,
estimates of health impacts can be made for different end points. TRANSPHORM (FP7 large scale project,
www.transphorm.eu) has focussed on PM10, PM2.5 and other species such as EC and BaP. This presentation will provide new
results of PM related health impacts in European cities and on regional scales. The importance of improved emission factors,
reliable source apportionment and application of advanced city and regional scale models are discussed along with
implications for European policy development.
Methodology and Results
Measurements of PM2.5 and PM10 for a number of European cities have been used for source apportionment to derive
quantitative information on contributions from transport and other source sectors. Emission factors for shipping and road
traffic have been updated and European wide emission inventories have been developed. Concentrations of PM species have
been predicted for 2005 and 2020 with five regional scale models (WRF/CMAQ, SILAM, LOTUS-EURO, ENVIROHIRLAM and EMEP). Figure 1 shows the avoided Disability Adjusted Life Years (DALY) based on WRF/CMAQ
predictions of PM2.5 over Europe. City scale models (e.g. OSCAR and URBIS) have used to predict 2008 and 2020
population weighted concentrations for Rotterdam, Helsinki, Oslo, Athens and London. Health impacts in terms of DALYs
and attributable deaths have been calculated for PM10, PM2.5 and EC for selected cities and for Europe.
Figure 1 Avoided DALYs over Europe for 2020 relative
to 2005 using PM2.5 annual mean concentrations
predicted with WRF/CMAQ.
Figure 2 Urban increment due to traffic and other
sources and regional contributions to PM2.5 at different
location types over London for 2008 using OSCAR.
Results indicate that for certain scenarios, attributable deaths in 2020 may be reduced by more than 30% across Europe
compared to 2005 levels. Within cities, PM levels are sensitive to regional contributions and to local measures which affect
near road and urban background concentrations. Figure 2 shows results from the OSCAR air quality assessment system for
urban increments arising from road traffic and other sources compared to regional background affecting PM2.5 levels at
different location types in London for 2008.
Conclusions
New results on measured and modelled PM concentrations and associated health impacts have been generated by the
TRANSPHORM project for Europe and selected cities focussing on recent and future years. Contributions to PM levels
across Europe from different source sectors have been quantified on city and regional scales. Predictions in PM related
concentrations have resulted from improvements to models as demonstrated by detailed evaluation studies. The presentation
will highlight key developments and new results as well as important implications for policy formulation.
Acknowledgement: Funding from the European Community's Seventh Framework Programme for TRANSPHORM under
the grant agreement no. 243406 is gratefully acknowledged.
13
AIR QUALITY AND
IMPACT ON LOCAL TO
GLOBAL SCALES
14
GLOBAL MODEL SIMULATIONS OF THE IMPACT OF TRANSPORT SECTOR EMISSIONS ON
ATMOSPHERIC AEROSOL AND CLIMATE
M. Righi (1), J. Hendricks (1), R. Sausen (1)
(1) Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Presenting author email: mattia.righi@dlr.de
Summary
In this work, we quantify the impact of emissions from the transport sectors (land-based transport, shipping, aviation) on
global atmospheric aerosol and climate. We use a global aerosol model to characterize impacts on aerosol mass, number and
size distributions, and the related aerosol radiative effects. We additionally perform sensitivity experiments to quantify the
uncertainties resulting from the assumptions on the size of the emitted particles and to investigate the non-linearities in the
aerosol response to emission perturbations.
Introduction
Emissions from the transport sectors are among the major sources of tropospheric aerosol. Aerosol particles can have a
significant impact on climate and can affect air quality, particularly in urban, densely populated areas, resulting in adverse
health effects. The emissions from the transport sectors are expected to grow in the near future, especially in the developing
countries. At the same time, various mitigation strategies are being applied in order to reduce air pollution and climate
impacts. In the present study, we investigate the global distribution of transport-induced particulate matter for present-day
and possible future conditions.
Methodology
We use the EMAC general circulation model (Jöckel et al., 2006) coupled to the aerosol sub-model MADE (Lauer et al.,
2007). We consider a present-day (2000) scenario and four future (2030) scenarios from the emission dataset developed in
support of IPCC assessment report 5 (Lamarque et al., 2010). Number emissions are also included in the model and derived
from mass emissions under different assumptions on the size distribution of particles emitted by the three transport sectors.
Additional sensitivity experiments are performed to quantify the effects of the uncertainties related to such assumptions. The
simulations are run over a 10-year period. Atmospheric dynamics is
nudged to the ECMWF operational analysis data.
Results
The model simulations show that the impact of the transport sectors
closely matches the emission patterns. Land transport is the most
important source of black carbon pollution in the USA, Europe and the
Arabian Peninsula (Fig. 1). Shipping strongly contributes to aerosol
sulphate concentrations along the most-travelled routes of the northern
Atlantic and northern Pacific oceans, with a significant effect also along
the coastlines. The impact of aviation is mostly confined to the uppertroposphere (7-12 km), in the northern mid-latitudes, although
significant effects are also simulated at the ground, due to the emissions
from landing and take-off cycles. The simulations further reveal that
transport-induced perturbations of particle number concentrations are
Fig.1 Absolute impact of land transport on BC
surface-level concentration for year 2000
very sensitive to the assumptions on the size distribution of emitted
emissions.
particles, with the largest uncertainties simulated for the land transport
sector. The climate impacts, due to aerosol direct and indirect radiative effects, are strongest for the shipping sector, as a
consequence of large effects of sulphate aerosol on low marine clouds. Significant non-linearities in the response of aerosol
effects to emission perturbations are found, especially for the secondary aerosol compounds .
Conclusions
The transport sectors are among the major sources of pollution close to the surface, in the vicinity of major emission sources
and in the upper troposphere (aviation). They have a large potential for affecting climate, mostly via aerosol-cloud
interactions and modification of cloud reflectivity, which is projected to decrease in the future (2030), with the except of
aviation. The non-linearities in the simulated effects for specific aerosol compounds might limit the applicability of the
results to the evaluation of mitigation strategies.
Acknowledgement
This study has been conducted in the framework of the DLR project VEU and of the EU project TRANSPHORM.
References
Jöckel, P. et al., 2006. The atmospheric chemistry general circulation model ECHAM5/MESSy1: consistent simulation of
ozone from the surface to the mesosphere. Atmospheric Chemistry and Physics 6, 5067-5104.
Lamarque, J.-F. et al., 2010. Historical (1850-200) gridded anthropogenic and biomass burning emissions of reactive gases
and aerosols: methodology and application. Atmospheric Chemistry and Physics 10, 7017-7039.
Lauer, A. et al., 2007. Global model simulations of the impact of ocean-going ships on aerosols, clouds, and the radiation
budget. Atmospheric Chemistry and Physics 7, 5061-5079.
15
ATMOSPHERIC NITROGEN DEPOSITION TO THE BALTIC SEA – NORMALISATION APPROACH
J. Bartnicki
Norwegian Meteorological Institute, P.O. Box 43, Blindern, NO0313 Oslo
Presenting author email: jerzy.bartnicki@met.no
Summary
An approach to normalisation of atmospheric nitrogen deposition to the Baltic Sea basin is the aim of this study. The time
series of normalised annual values of nitrogen deposition to the Baltic Sea basin were calculated for the period 1995-2011.
The method for calculating normalised depositions, which involves annual source-receptor matrices from the EMEP MSC-W
model, is presented. This method can be used, not only for estimating depositions from all sources, but also for estimating
normalised individual contributions from the emission sources to nitrogen deposition. The normalised depositions will be
used as a standard indicator by HELCOM.
Introduction
Eutrophication is one of the main environmental problems of the Baltic Sea. It is caused by the excessive input of mainly
nitrogen and phosphorus both from riverine input and via atmospheric deposition. Nitrogen deposition from the air can
account for 25-45% of the total annual deposition (Bartnicki et al., 2011), depending on the year, whereas atmospheric
deposition of phosphorus in not larger than 4% of annual total deposition. Within the long-term cooperation between
European Monitoring and Evaluation Program (EMEP) and Helsinki Commission (HELCOM), nitrogen depositions to the
Baltic Sea and its sub-basins are computed every year using the EMEP MSC-W model and reported to HELCOM (Bartnicki
et al., 2012). The results of these computations are used by HELCOM, mainly for the purpose of the Baltic Sea Action Plan
(BSAP). The computed nitrogen deposition depend, first of all on emissions, but also on meteorological conditions and
especially precipitation, which can be responsible for large variations in calculated annual depositions (Bartnicki et al., 2011).
From the decision making point of view, it is very important to filter out the influence of meteorology on the computed
depositions, so that nitrogen emission reductions are better reflected in the computed depositions. It is done by using the so
called “normalised deposition” concept.
Methodology and Results
For calculating normalised nitrogen depositions, the source-receptor matrices from the EMEP MSC-W model are used for all
years of the considered period. Then, for the year of interest, emissions from this year are multiplied by every source-receptor
matrix and 17 different depositions are calculated representing 17 meteorological years. The median value from these
depositions is defined as normalised deposition. These calculations are performed both for oxidised and reduced nitrogen
deposition. The results for total (osidised+reduced) normalised nitrogen deposition are shown in Fig. 1. In addition, the minimum and maximum depositions for each year are shown,
representing the best and the worst meteorological
conditions. The actual annual values, calculated with the
real meteorological conditions for each year are also
shown in Fig. 1. They are oscillating between minimum
and maximum values. The actual annual values show
large variations from one year to another and no clear
trend in the entire period. Contrary, the normalised
depositions are more smooth and monotonic and indicate
a decreasing trend in the considered period, which
follows more closely nitrogen emission trends. It should
be stressed here that normalised depositions are not
replacing the actual depositions, but they are part of
Fig.1 Normalised and annual depositions to the Baltic Sea
important additional information for the decision makers,
basin in the period 1995-2011.
especially concerning uncertainty.
Conclusion
The concept of normalised deposition was shown for nitrogen and Baltic Sea basin as an example. This concept can be also
used for other receptors and for calculating normalised contributions from individual emissions sources. It was decided by
HELCOM that normalised depositions will be one of the standard annual indicators for the status of the Baltic Sea.
Acknowledgement
This work was initiated and supported by the Helsinki Commission.
References
Bartnicki J., Valiyaveetil S. and H. Fagerli (2011) Atmospheric deposition of nitrogen to the Baltic Sea in the period 1995 –
2006. Atmos. Chem. Phys., 11, 10057-10069, www.atmos-chem-phys.net/11/10057/2011/ doi:10.5194/acp-11-10057-2011.
Bartnicki J., Gusev A., Aas W. and Valiyaveetil S. (2012) Atmospheric Supply of Nitrogen, Lead, Cadmium, Mercury and
Dioxins/Furans to the Baltic Sea in 2010. EMEP Centres Joint Report for HELCOM. EEMEP/MSC-W Technical Report
2/2012. Norwegian Meteorological Institute, Oslo, Norway.
16
ASSESSMENT OF CONTRIBUTION TO PM10 CONCENTRATIONS FROM LONG RANGE TRANSPORT OF
POLLUTANTS USING WRF/CHEM OVER A SUBTROPICAL URBAN AIRSHED
M. Gupta and M. Mohan
Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi-110016, India
Presenting author email:guptamedhavi@hotmail.com
Summary
This study simulates the PM10 concentration in order to study the impact of long range transport (LRT) over megacity Delhi
with due consideration to different geographical domains extending upto entire Asia. A regional chemical transport model
namely WRF/Chem version 3.2 is implemented. A highly satisfactory model performance is interpreted based on the several
statistical parameters as per the current state of the science and their recommended values. Model simulations representing
different geographical domains encompassing Asia, India, North India and Delhi and their corresponding emissions, it is
clearly reflected that contributions due to emissions of the megacity Delhi alone is 11 % - 41 % and thus remaining (59%89%) proportion is expected to be contributed from the sources outside of the Delhi which is significant. This can serve as an
important tool towards planning and implementing the regulatory policies for air pollution control for more effective
outcome.
Introduction
PM10 can be transported in the atmosphere for hundreds or even thousands of kilometers, implies that pollutants emitted in
one country can affect PM10 concentrations in neighboring countries and even countries far distant from the source (WHO,
2006). Intercontinental transport of Asian aerosols is considered as an important issue for air quality and climate concerns
(Wuebbles et al., 2007). Considering this, contributions to PM10 due to LRT over megacity Delhi is studied using
WRF/Chem model. This abstract is based on the study published by the authors Gupta and Mohan, 2013 recently.
Methodology and Results
Table 1 shows the statistical evaluation of model for Delhi at 4 locations Shadipur, Dilshad Garden, Dwarka and ITO which
is highly satisfactory and promising to be implemented for LRT assessment.
Simulations were carried out from 1-7 June 2010 when maximum
Table 1: Statistical evaluation for PM10 concentration over
values of PM10 of about 1000 μg/m3 were monitored. The
Delhi (Gupta and Mohan, 2013)
simulations consisted of a parent domain and three nested
Statistical
Dilshad
domains with resolutions of 90 km, 30 km, 10 km and 3.3 km
Shadipur
Dwarka ITO
Parameter
Garden
respectively. It was observed that when low concentrations were
NMSE
0.11
0.28
0.03
0.19
simulated the % distribution due to Delhi was 41.5 %, 34.7 % due
FB
0.32
0.57
0.14
0.41
to India and North India region together and remaining 23.8 %
FAC2
0.72
0.29
0.72
0.72
was contributed from outside India. Whereas for days when high
IOA
0.92
0.9
0.98
0.94
PM10 were simulated the contribution from Delhi changed to 11.2
MNGE
0.33
0.54
0.24
0.38
%, 69.2 % was due to India and North India combined; and 19.6
MNB
-0.33
-0.54
-0.17
-0.38
% PM10 resulted from outside India. Thus contribution due to
R
0.94
0.94
0.98
0.9
Delhi region ranged from about 11% to 41% and the remaining
approximately 59% to 89% was estimated to be from outside the
urban airshed depending upon the PM10 concentrations. However, sources contribution from outside India was assessed
approximately in the range of 20% to 24%. It is interesting to note that % contribution due to Delhi decreases when high
concentrations are observed and vice-versa indicating that there is greater degree of LRT from outside Delhi region during
high concentrations and vice-versa.
Conclusions

Performance of model is good but there is marked underestimation in the simulated concentration which can be
improved perhaps with better emission inventories.

Further, it is stated that overcoming under-prediction may change these contributions; however relative percentage
distributions may still be significant and may not vary substantially. Moreover, the model evaluation discussed above
indicate by and large a reasonable model performance such that improving further model performance may not
drastically undermine the importance of long range transport from outside the urban airshed and its usefulness to
contribute towards planning and implementing air pollution control strategies.

In megacity Delhi, particulate matter levels remain persistently high. It is therefore recommended that regulatory
measures should duly incorporate regional and long range transport in policy formulations.
References

Gupta, M., Mohan, M., 2013. Assessment of contribution to PM10 concentrations from long range transport of pollutants
using WRF/Chem over a subtropical urban airshed. Atmospheric Pollution Research, article in press, doi:
10.5094/APR.2013.046

W.H.O. (World Health Organisation), 2006. Health risks of particulate matter from long-range transboundary air
pollution, European Centre for Environment and Health, Copenhagen, 113 pages.

Wuebbles, D.J., Lei, H., Lin, J., 2007. Intercontinental transport of aerosols and photochemical oxidants from asia and
its consequences. Environmental Pollution 150, 65-84.
17
MODELING HIGH AEROSOL LOADS IN CHINA IN JANUARY 2013
V. Matthias (1), A. Aulinger (1), J. Bieser (1), B. Geyer (1), M. Quante (1)
(1) Helmholtz-Zentrum Geesthacht, Institute of Coastal Research, Max-Planck-Strasse 1, 21502 Geesthacht, Germany
Presenting author email: volker.matthias@hzg.de
Summary
In January 2013 exceptionally high levels of particulate matter (PM) concentrations were reported for the area around Beijing
(40 N, 116 E) with maximum concentrations exceeding 500 µg/m³ and aerosol optical depth (AOD) values of more than 2 on
several days. In order to analyze this high pollution episode PM concentrations in China were simulated with the Community
Multiscale Air Quality (CMAQ) model for the period from 10 December 2012 to 31 January 2013. Emissions were taken
from the EDGAR data base. The results were compared to ground based PM2.5 measurements taken at the US embassy in
Beijing and to Aeronet sun-photometer observations. The model was generally able to reproduce the high PM levels
measured in situ close to ground, however the largest peak on 12 January was not captured, because of an exceptionally
strong temperature inversion close to ground that was not reproduced in the meteorological fields.
Introduction
In January 2013 exceptionally high levels of particulate matter (PM) concentrations were reported for the area around Beijing
coinciding with low temperatures and calm winds in entire North East China. A model study has been set up at HelmholtzZentrum Geesthacht which aimed at answering the following questions related to this exceptional situation: Which emission
sectors contribute most to the high aerosol concentrations? What is the impact of the meteorological situation on the high
pollution level? How accurately can state of the art air quality models simulate extreme pollution events?
Methodology and Results
The regional atmospheric chemistry transport model CMAQ (Community Multiscale Air Quality) was set up on a 72 x 72
km2 grid for South East Asia with a nested 24 x 24 km2 grid covering mainly North East China. 30 vertical layers up to 20
hPa were implemented on the coarse grid, the finer grid contained 40 vertical layers. CMAQ was driven with meteorological
fields from the mesoscale meteorological model COSMO-CLM (CCLM). The model was run for the period from 10
December 2012 until 31 January 2013.
The most recent freely available emission data set is the EDGAR emission data from 2008 on 0.1 x 0.1 degrees. They were
adapted for the current situation by extrapolating the emission increase between 2004 and 2008 until the year 2012. This was
done on a grid cell basis in order to apply different growth factors in different areas. The emissions were then distributed in
time according to temporal profiles determined in the SMOKE for Europe emission model (Bieser et al., 2012).
The average PM2.5 concentration for the second week in January (7 – 13 January) was higher than 85 µg/m³ in large areas of
North East China. The time series of the modelled PM2.5 concentration showed up to 500 µg/m³. No officially measured
PM2.5 concentrations were available to the authors, however observations made at the US embassy in Beijing were reported
in the internet. The corresponding PM2.5 concentrations were even higher than the modelled values. In particular on 12
January PM2.5 concentrations of more than 800 µg/m³ were reported . These values were not reproduced by the model.
During the other periods, the model captured the pollution levels and their variability quite well.
The model results were were also compared against aerosol optical depth (AOD) observations of gathered within the Aeronet
sun-photometer network (Holben et al., 1998). The model typically underestimates the highest observations. There are two
important reasons for this which are closely related to the meteorological situation. One is that extreme temperature
inversions and very shallow boundary layers are not well simulated by the model. The second reason is that AOD depends
critically on relative humidity (RH) at values above 80%. Such high values were frequently observed in Beijing, as was seen
in data from radiosoundings. The model typically showed much lower RH in the boundary layer.
An analysis of the modelled chemical species of the fine aerosol at Beijing (Figure 4) reveals that the aerosol is to a large
extent composed of primary and secondary organics. These species have a particularly high share of 60 -70 % in the total
emissions in the residential heating sector. Traffic emissions were found to be of minor importance for the aerosol formation.
Conclusions
The exceptionally high air pollution in China in January 2013 was simulated with the CMAQ model system using
extrapolated EDGAR emission data from 2008 and COSMO-CLM meteorological fields. In general, the level of PM2.5 was
matched well according to the few available observations. However, the highest PM2.5 concentrations were not adequately
reproduced because the very shallow boundary layer could not be captured by the meteorological model. According to the
CMAQ model, primary and secondary organics are the largest fractions in the chemical composition of the aerosol in Beijing.
Emissions from residential heating contributed more than on average to the aerosol concentrations on those days with the
highest aerosol load.
Acknowledgement
The authors thank US EPA for the development and distribution of CMAQ and the EDGAR community for the provision of
emission data. We would like to thank the AERONET sun-photometer network and their PIs for their important observations.
Special thanks to David Black and Ajay Pillarisetti for collecting the PM2.5 observations at the US embassy in Beijing.
References
Bieser, J.; et al. (2011), 'SMOKE for Europe - adaptation, modification and evaluation of a comprehensive emission model
for Europe', Geoscientific Model Development 4(1), 47--68.
Holben, B. N. et al. (1998), 'AERONET- A Federated Instrument Network and Data Archive for Aerosol Characterization',
Remote Sens. Environment 66, 1-16.
18
AIR QUALITY AT THE STREET LEVEL IN CYPRUS
I. Douros (1), L. Kalognomou (1), E. Chourdakis (1), N. Moussiopoulos(1) and S. Kleanthous (2)
(1) Laboratory of Heat Transfer and Environmental Engineering, Aristotle University, Greece – University Campus, P.O.
Box 483, 54124 Thessaloniki; (2) Department of Labour Inspection, Ministry of Labour and Social Insurance,
Apelli 12, 1480 Nicosia Cyprus
Presenting author email: jdouros@aix.meng.auth.gr
Summary
The main goal of the present study was the quantification of local anthropogenic contributions to the hotspot PM
concentrations with a focus on the urban areas. For this purpose, the street scale air quality model OSPM (Berkowicz, 2000),
was applied in order to describe the particulate pollution levels at street scale, as well as to describe the processes that govern
the distribution of the pollutants inside typical Cypriot street canyons.
Introduction
This study provides an estimate of the street scale increment for PM, i.e. the contribution of local scale (mainly traffic)
emissions and PM resuspension to the levels of PM concentrations at urban hotspots. Although only a few cases of Cypriot
streets could strictly be classified as street canyons, it is important to investigate the upper levels of the street scale
contribution for certain cases of streets where street geometry is clearly unfavourable for the dispersion of pollutants.
Besides, a factor which decisively affects dispersion characteristics inside street canyons and thus dictates the levels of the
street scale increment is meteorology, most importantly wind speed and direction. For this reason this report also explores the
impact of different meteorological conditions during recent years, on the PM street scale increments.
Methodology and Results
In order to make accurate choice with respect to the representativity of the locations where the street scale application would
take place, as a first step a preselection of areas was conducted. In this direction, existing transport and geometric data were
used to select a first set of possible locations for the street scale model application in each one of the four major cities of
Cyprus. These hotspots were chosen according to the availability of traffic measurements and the street geometry in the
specific area. All areas are characterized by high activity levels, as they are located close to or within the economic centres of
each city. As a result of a second stage of this process, two particular road segments, one in Makariou Ave. (Nicosia) and one
in Afxediou Ave. (Larnaca), were chosen for the long term street scale application, as the geometric and traffic characteristics
of these sites lead to the conclusion that they constitute typical Cypriot street canyons and, therefore, form the worst case
scenarios in the framework of this study. Based on street scale model applications, we have been able to estimate an upper
limit for the street scale increment regarding PM and NO2. These estimates reveal that for Makariou Avenue in Nicosia the
street scale increment for PM10 can reach 18.5 μg/m3, while for PM2.5 it can reach 6.3 μg/m3. For Grigoriou Afxediou Avenue
in Larnaca, the street scale increment for PM10 can reach 26.9 μg/m3, while for PM2.5 it can reach 9.9 μg/m3. For NO2, higher
concentrations at the street level can reach 26.3 μg/m3 for Makariou Ave and 38.4 μg/m3 for Afxediou Ave. For all pollutants
higher street scale increments are estimated for Afxediou Ave. due to the increased number of vehicles circulating in the
specific street. Unfavourable wind conditions inhibit dispersion of air pollutants and lead to increased concentrations at street
level. The increase depends on the number of vehicles circulating inside the street and for NO2 the increase is estimated to be
6.5 μg/m3 in Nicosia and 12.5 μg/m3 in Larnaca, for PM10 5.9 μg/m3 in Nicosia and 9 μg/m3 in Larnaca and for PM2.5
1.9 μg/m3 in Nicosia and 3.3 μg/m3 in Larnaca.
Conclusions
Due to the fact that both Makariou and Afxediou avenues cannot be strictly characterized as street canyons along the whole
length of the streets, these are the upper limits for street level concentrations where multi storey buildings are present on both
sides of the road. Nevertheless, it is clearly evident that pollutant levels inside street canyons can be significantly higher than
the urban background, thus presenting more challenges as regards the attainment of the Air Quality Directive limit values.
References
Berkowicz R. (2000), OSPM - A parameterised street pollution model, Environmental Monitoring and Assessment 65(1-2):
323-331.
19
INTEGRATED ASSESSMENT USING OBSERVATIONS AND MODELLING FOR AIR QUALITY MANAGING
IN SANTA CRUZ DE TENERIFE (CANARY ISLANDS)
J. M. Baldasano (1,2) A. Soret (1), M. Guevara (1), F. Martínez (1), S. Gassó(1,2)
(1) Barcelona Supercomputing Center – Centro Nacional de Supercomputación (BSC-CNS). Earth Sciences Department.
Jordi Girona 29, Edificio Nexus II, 08034 Barcelona, Spain; (2) Technical University of Catalonia (UPC). Avda. Diagonal
647, Edificio H, Oficina 10.23, 08028 Barcelona, Spain
Presenting author email: jose.baldasano@bsc.es
Summary
This study aims to analyse the atmospheric dynamics of the Santa Cruz de Tenerife region (Canary Islands). The area is
characterized by the presence of anthropogenic emission sources (refinery, port and road traffic) and by very specific
meteorological and orographic conditions. These factors lead to specific atmospheric pollution episodes, particularly in
relation to SO2 and PM10. We applied a methodology to study these dynamics based on two complementary approaches: 1)
the analysis of observations and 2) model simulations. The results show that the refinery plume plays an important role in the
maximum SO2 observed levels. The area of maximum impact of the refinery is confined to a radius of 3 km around this
installation. In the case of particulate matter, Saharan dust intrusions result in episodes with high levels of PM10.
Introduction
The interaction between the synoptic and local dynamics in areas of complex topography has a significant effect on air
pollution. The Tenerife Island is characterized by very specific meteorological and orographic conditions. It is a coastal area
with a complex topography in which there is an interaction of regional atmospheric dynamics and a low thermal inversion
layer. In the case of Santa Cruz de Tenerife, the combination of anthropogenic emission sources: refinery, port and road
traffic, and the Islands’ singular meteorological and orographic characteristics lead to specific pollution episodes. This study
aims to analyse the atmospheric dynamics of the area affecting the city of Santa Cruz de Tenerife to determine the impact of
emissions on air quality. These results have helped air quality managers to identify main emission sources and the
meteorological situations with limited dispersive conditions to plan future air quality strategies.
Methodology and Results
The analysis is conducted for the whole year 2011. A cluster analysis is performed to objectively identify dominant synoptic
patterns affecting Tenerife Island. Six days of studio are selected, each one representing one of these synoptic patterns. The
singular meteorological-emissions interactions are analysed combining two complementary approaches: 1) the analysis of the
observations from the air quality network stations and 2) simulation of atmospheric dynamics using the WRFARW/HERMESv2/CMAQ/BSC-DREAM8b and WRF-ARW/HYSPLIT modelling systems with a high spatial resolution
(1×1 km2). Detailed information of traffic, refinery and port activity has been collected as input information for the emission
inventory. This methodology has allowed linking poor air quality levels with emission sources in an area of complex terrain.
Fig. 1. Wind streams and SO2 levels caused by refinery emissions (µg m-3) for: January 24, 2011 (Western advection). From
left to right: wind streams (U10) over Tenerife Island at 2UTC; detail of wind streams (U10) at Northeast Tenerife at 10
UTC; SO2 increases at 10 UTC (WRF-ARW/HERMESv2/CMAQ); SO2 increases at 10 UTC (WRF-ARW/HYSPLIT).
Results show that SO2 air pollution episodes occur mainly in those situations with more limited dispersive conditions, such as
the northeastern recirculation, the northwestern recirculation and the western advection (Fig.1), which represent 33.70%,
11.23% and 18.63% of the meteorological situations affecting Tenerife in 2011, respectively. Refinery emissions play an
important role in the exceedances of the legal limits of SO2 levels. The oil refinery plume has a local effect in the vicinity of
the installation (maximum influence located in a radius of 3 km). Air quality levels of NO2 do not exceed maximum legal
levels; the main emission source is road traffic and is complemented by the refinery emissions. In the case of particulate
matter, Saharan dust intrusions result in episodes with high levels of PM10; these episodes are favored when the synoptic
situation is from the east (3.29% of the situations during 2011).
Conclusions
This study has analysed and evaluated the air quality in the area of Santa Cruz de Tenerife in 2011 to determine the impact of
emissions in the area. This analysis has identified the main factors that lead to exceedances of air quality levels. These factors
are very specific; meteorological and orographic conditions that hinder dispersive conditions in the area, and the presence of
significant emission sources in the area. The results show an important role for refinery emissions in the exceedances of the
legal limits of SO2 levels. With respect to particulate matter levels, the episodes of high concentration are related to episodes
of Saharan dust intrusion.
20
A STUDY OF OZONE CONCENTRATIONS AND TRENDS ACROSS EUROPE: 1996-2010
T. Chatterton (1), E. Hayes (1), J. Barnes (1), J. Longhurst (1), D. Laxen (1) J. Irwin (1), H. Bach (2), J. Brandt (2), J. H.
Christensen (2), T. Ellermann (2), C. Geels (2), O. Hertel (2), A. Massling (2), H. Ø. Nielsen (2), O. K. Nielsen (2), C.
Nordstrøm (2), J. K. Nøjgaard (2), H. Skov (2), F. Pelsy (3) and T. Zamparutti (3)
(1) Air Quality Management Resource Centre, University of the West of England, Bristol, BS16 1QY, UK; (2) DCE - Danish
Centre for Environment and Energy, Aarhus University, Denmark; (3) Milieu, 15 rue Blanche, Brussels 1050, Belgium
Presenting author email: tim.chatterton@uwe.ac.uk
Summary
This study reviews ozone concentrations from rural monitoring stations across Europe between 1996 and 2010 across a range
of statistics with regard to the various objectives, target values and thresholds established by the 2008 Ambient Air Quality
Directive 2008/50/EC. The findings reveal that whilst there have been complex and varied changes in patterns of ozone
concentrations during the last 15 years, there are still extensive exceedences of the various regulatory standards and that
while peak concentrations may have been decreasing, background concentrations are on the rise.
Introduction
The Air Quality Directive 2008/50/EC established two target values for ozone, one based on the protection of human health
(120 µg/m3 as maximum daily 8-hour mean, not to be exceeded more than 25 days per year averaged over three years) and
another for protection of vegetation (AOT40 (Accumulated Ozone over a Threshold of 40 ppb) 18,000 µg/m3-h averaged
over five years. The directive also established a long-term objective of 120 µg/m3 as maximum daily 8-hour mean (no
exceedences) and an AOT40 of 6,000 µg/m3-h (no achievement date defined). The 2008 Directive also set an information
threshold of 180 µg/m3 and an alert threshold of 240 µg/m3 (both hourly averages).
Methodology and Results
Data were collected from the European Airbase database (v6) and
following screening of the data, 286 rural background stations were
selected for analysis over a 10-year period from 2001-2010, and 186
stations for a fifteen year period from 1996-2001. The analysis
covered both absolute concentrations, as well as long-term trends in
concentrations calculated using Theil Sen slope estimates, following a
methodology established by Wilson et al. (2012).
The findings of the analysis are that that there is no clear single trend
in ozone concentrations. However, the following points can be noted:
1. Mean concentrations tended to increase over the period 19962005, whilst decreasing 2001-2010;
2. During this latter period, mean and 5th percentile (background)
concentrations tended to reduce, but this pattern was less obvious
for 95th percentile (peak) concentrations;
3. Monitoring stations recording the highest mean ozone
concentrations (>60 µg.m-3) tended to show the greatest
downward trends over the whole 15 year period;
4. Different spatial regimes exist for mean concentrations and
trends, on the one hand and maximum 1-hour or 8-hour mean
concentrations, on the other.
5. Any discernible downward trend in some of the exceedence
statistics is relatively insignificant in the context of year-to-year
variations due to changing meteorological conditions.
6. The extent to which trends are evident is highly dependent on the
chosen measure, e.g. average concentrations or exceedences of
particular thresholds.
Fig.1 Mean ozone concentrations 2001-10
Fig.2 Trends in mean ozone concentration
2001-10
Conclusions
Patterns of ozone pollution over Europe are complex, and the EU monitoring network is only coming to the stage where
widespread spatial trends can be evaluated. What becomes clear from the analyses undertaken is that it is unlikely that a ‘one
size fits all’ policy will be suitable for all Member States, and therefore better information on the nature of any region’s
problem will be vital for effective management strategies.
Acknowledgement
This work was undertaken as part of a service contract for DG ENV, European Commission. The work as presented is from a
report that has not yet been approved or published by the Commission.
References
Wilson, R. C., et al. (2012) Have primary emission reduction measures reduced ozone across Europe? An analysis of
European rural background ozone trends 1996–2005, Atmos. Chem. Phys., 12, 437-454, doi:10.5194/acp-12-437-2012.
21
A MODELLISTIC STUDY OF THE INFLUENCE OF AN HARBOUR SHIP EMISSIONS ON REGIONAL AIR
QUALITY IN A MEDITERRANEAN AREA
R. Cesari (1), A.Maurizi (2), F. Tampieri (2)
(1) National Research Council, Institute of Atmospheric Sciences and Climate, S. P. Lecce-Monteroni km 1.2, 73100, Lecce,
Italy; (2) National Research Council, Institute of Atmospheric Sciences and Climate, via Gobetti 101, 40100, Bologna, Italy
Presenting author email:r.cesari@isac.cnr.it
Summary
In this study we are interested in studying the effect of ship emissions from a port city located in a Mediterranean area on air
quality level, over a regional domain. The on-line meso-scale atmospheric composition model BOLCHEM (Mircea et al.,
2006) is used to simulate transport and dispersion of both gaseous and aerosols pollutants in a summer period (July 2010).
Numerical results shows that over the simulation domain, monthly average ground concentration of both primary pollutants
NOx and PM10, and secondary pollutant O3 are influenced by ship emissions, with an higher impact in the area that surrounds
the harbor.
Introduction
Ship emissions represent an important and growing contribution to the total emissions from the transportation sector (Eyring
et al., 2010) and they significantly influence air pollution level of both primary and secondary pollutants. This is confirmed
by different studies that evaluate the contribution of shipping emissions on air quality in the Mediterranean Area (Marmer et
Langmar, 2005). Environmental impact from ship emission has become a “hot” issue for air pollution and climate policy, and
a large number of European projects are devoted to this topic. Among those, the European Territorial Cooperation
Programme Grece-Italy 2007-2013 CESAPO (Contribution of Emission Sources on the Air Quality of the Port-cities in
Greece and Italy - www.cesapo.upatras.gr) project has the general objective to study the contribution of emission from
maritime transport and activity within the ports of Patras (Greece) and Brindisi (Italy) to the air quality and to propose actions
for sustainable development in the Mediterranean Region. In this frame, we are interested in evaluate the impact of port of
Brindisi on ground pollutants concentration levels over Apulia region, where Brindisi is located.
Methodology and Results
The model BOLCHEM comprises the meteorological model BOLAM (Buzzi et al., 1994), an algorithm for airborne
transport and diffusion of pollutants, the photochemical mechanisms SAPRAC90 (Carter, 1990) and the aerosol dynamic
model AERO3 (Binkowski et al. , 2003). In this study we use the model in a one-way nested grid configuration. The inner
domain, with horizontal resolution of 0.06o x 0.06o (60 x 86 grid points) covers the spatial domain (14.50o E-18.975o E, 38o
N-42.98o N) and includes the Apulia Region. The vertical grid has 40 σ layers for meteorology and 20 for the chemistry. The
first vertical level is at about 20 m. The mother run is driven by initial and boundary conditions from ECMWF for
meteorology. Simulations have been performed for the summer period July 2010. To investigate the impact of ship emissions
on ground concentration pollutants level, the BOLCHEM simulations have been run with the inclusion of anthropogenic
emissions from all the sources (base run) and then switching off the ship emissions. The difference between the two run
output constitute the contribution of ship emissions on pollutant concentration.
Conclusions
Numerical results shows that monthly average ground concentration of primary pollutant NOx increases up to 5%, while O3
ground concentration decreases of about 2%. An higher impact is found in the area that surrounds the harbor, where NOx
ground concentration increases up to 40% and O3 ground concentration decreases up to 20%. PM10 monthly average ground
concentration increases of about 2% over the region, and about 15% very close to the port.
Acknowledgement
The authors thank the European Territorial Cooperation Programme Greece-Italy 2007-2013 CESAPO project for the
financial support.
References
Binkowski F.S., Roselle S.J., 2003. Models-3 Community Multiscale Air Quality (CMAQ) model aerosol component 1.
Model description. Journal of Geophysical Research, 108 D6, 4183.
Buzzi, A., Fantini, M., Malaguzzi, P., Nerozzi, P. 1994. Validation of a limited area model in cases of Mediterranean
cyclogenesis: surface fields and precipitation scores. Meteor. Atmos. Phys, 53, 37153.
Carter W., 1990. A detailed mechanism for the gas-phase atmospheric reactions of organic compounds. Atmospheric
Environment 27A, 481-518.
Eyring, V., Isaksen, I.S.A., Berntsen, T., Collins, W.J., Corbett, J.J., Endresen, O., Grainger, R.G., Moldanova, J., Schlager,
H., Stevenson, D.S., 2010. Transport impacts on atmosphere and climate: Shipping. Atmospheric Environment 44, 47354771.
Marmer E. and Langman B., 2005, Impact of ship emissions on the Mediterranean summertime pollution and climate: A
regional model study, Atmospheric Environment, 39, 4659-4669
Mircea, M., D’Isidoro, M., Maurizi, A., Vitali, L., Conforti, F., Zanini, G., Tampieri, F. 2006. A comprehensive performance
evaluation of the air quality model BOLCHEM to reproduce the ozone concentrations over Italy. Atmospheric Environment
42, 6, 1169-1185
22
MODELING TRENDS IN AIR POLLUTANT CONCENTRATIONS AND THEIR OPTICAL AND RADIATIVE
PROPERTIES OVER THE NORTHERN HEMISPHERE USING THE COUPLED WRF-CMAQ MODEL
R. Mathur, J. Xing, G. Sarwar, J. Pleim
Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, U.S. Environmental Protection
Agency, Research Triangle Park, NC 27711
Presenting author email: mathur.rohit@epa.gov
Summary
Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range
transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate
and influence regional calculations and often confound interpretation of model results. Since transport is efficient in the freetroposphere and since simulations over Continental scales and annual cycles provide sufficient opportunity for “atmospheric
turn-over”, i.e., exchange between the free-troposphere and the boundary-layer, a conceptual framework is needed wherein
interactions between processes occurring at various spatial and temporal scales can be consistently examined. The coupled
WRF-CMAQ model is expanded to hemispheric scales and model simulations over period spanning 1990-current are
analyzed to examine changes in hemispheric air pollution resulting from changes in emissions over this period.
Introduction
Both observational and modeling studies have demonstrated that pollutants near the Earth’s surface can be convectively
lofted to higher altitudes where strong winds can efficiently transport them from one continent to another, thereby impacting
air quality on intercontinental to global scales. Thus, strategies for reduction of pollution levels of surface air over a region
are complicated not only by the interplay of local emissions sources and several complex physical, chemical, dynamical
processes in the atmosphere, but also hemispheric background levels of pollutants. To assist with the design of emission
control strategies that yield compliance with more stringent air quality standards, models must possess the fidelity to
accurately simulate ambient pollutant levels across the entire spectrum ranging from background to extreme concentrations.
Consistent modeling frameworks that can represent the interactions between various physical and chemical atmospheric
processes at the disparate space and time scales are thus needed.
Methodology and Results
Expansion of the coupled WRF-CMAQ modeling system to hemispheric scales is pursued to enable the development of a
robust modeling framework in which the interactions between atmospheric processes occurring at various spatial and
temporal scales can be examined in a consistent manner. The CMAQ modeling system was applied over a domain
encompassing the northern hemisphere. The horizontal domain, set on a polar stereographic projection, was discretized using
grid cells with a 108 km resolution, while the vertical extent ranging from the surface to 50 mb was discretized with 44 layers
of variable thickness with a 20 m deep lowest layer. 3-D meteorological fields were derived from the Weather Research and
Forecasting (WRF) modeling system operating on the exact same projection and grid configuration as CMAQ. Observations
from NCAR’s global upper air observation data set combined with the GFS 1-degree analysis provided the reanalysis fields
for data assimilation in the WRF simulations. Emissions of NOx, SO2, CO, volatile organic compounds, and particulate
matter from anthropogenic, biomass burning, and biogenic sources were derived from existing global inventories. Annual
CMAQ simulations for multiple years spanning the 1990-2010 period and numerous associated sensitivity simulations
(examining impacts of vertical layer structure, stratospheric O3 influences, representation of NOx recycling through organic
nitrates, halogen chemistry in marine environments) have been conducted to establish the capability to exercise CMAQ over
the Northern hemisphere. The ability of the model to represent long-range transport of pollutants is analyzed through
comparisons with aircraft measurements from the 2006 INTEX-B field campaign, ozonesonde profiles, and remotely sensed
observations of aerosol optical depth.
Significance and Implications
Changes in emission patterns over different regions of the world are likely to exacerbate the impacts of long-range pollutant
transport on background pollutant levels in the U.S., which may then impact the attainment of local air quality standards. The
successful expansion of coupled WRF-CMAQ to the hemispheric scales now provides a robust framework to examine
interactions between atmospheric processes occurring at various spatial and temporal scales in a consistent manner and to
characterize changes in regional background pollutant levels as well as the spatial heterogeneity in aerosol loading and
associated radiative impacts over the Northern hemisphere.
23
AIR QUALITY
MANAGEMENT AND
POLICY
24
STRENGTHS AND WEAKNESSES OF THE EU AIR QUALITY STANDARDS FOR PARTICULATE MATTER
K. D. van den Hout (1), C. Nagl (2), W. Spangl (2) and B. Conlan (3)
(1) TNO, Utrecht, Netherlands; (2) Umweltbundesamt, Vienna, Austria; (3) Ricardo-AEA, London.
Presenting author email: dick.vandenhout@tno.nl
Summary
An evaluation of the strengths and weaknesses of the EU air quality standards for particulate matter is presented. It is based
on a consultation of EU member states and stakeholder associations and a subsequent analysis of the properties of the various
PM standards. Possibilities for addressing weaknesses, by refinement of existing standards or by adding or withdrawing
standards, were identified and assessed.
Introduction
The EU directive on ambient air quality and cleaner air for Europe 2008/50/EC has set air quality standards for PM and
requires the Commission to review the PM2.5 standards by 2013. In support of the review, WHO has re-evaluated the health
impacts of PM; its recent report emphasised the importance of all current PM air quality standards (WHO, 2013). The review
activities also included an evaluation of the experiences of member states and other stakeholders with the air quality
standards and an investigation of possibilities to improve the PM standards.
Methodology and Results
Using a questionnaire, an inquiry of views of EU member states and stakeholder associations was conducted. About half the
member states and stakeholders that were invited responded. There was broad agreement with the overall approach of the
directive, including the concepts of the air quality standards. The introduction of the new standards for the average exposure
indicator, as instruments for driving down the average exposure of the general urban population in large cities, was
welcomed. Many respondents emphasised, in view of the wide-spread exceedances of the PM standards, that the air quality
standards need to be consistent with emission reductions under EU legislation. Another priority mentioned was the need to
identify and address the most harmful PM fractions. Views on the flexibility arrangements (derogations, time extensions) and
on the ambition level to be aimed at in a possible revision of the standards were divided. There was concern about the
complexity of the set of PM standards.
An analysis of the strengths and weaknesses of the PM standards and options for improvement was subsequently carried out.
To do this systematically, a set of evaluation criteria was drawn up, such as health protection, attainability, scientific
robustness, regulatory stability, redundancy, complexity. The properties of the PM standards were investigated: the fraction
regulated (e.g. PM2.5), the binding nature (e.g. to be achieved as far as possible), the attainment date (e.g. 1-1-2020), other
temporal aspects (e.g. averaging time; statistical definition such as 90th percentile of 24-hour means) and spatial aspects (e.g.
where does the standard apply; averaging area; relation to exposure). In view of parallel scenario calculations for PM in
Europe, led by IIASA, the numerical level of the standards was excluded from the analysis.
Pros and cons of strengthening the binding nature of the standards were identified; for the national exposure reduction target
strengthening was considered important to make it effective. For limit values – which have to be attained everywhere – a
degree of flexibility was deemed necessary to make reduction of their levels to be attained feasible. It is questionable whether
the added value of an additional 24-hour PM2.5 standard as proposed by WHO or a new standard for black carbon or ultrafine
particulates as proposed by others would counterbalance the increase of complexity of the set of standards. Possibilities for
withdrawal of one or several of the partially overlapping standards were investigated; this is however not possible without
changing the spatial distribution of the protection provided by the set of standards. Many refinement options were considered,
such as setting a long-term timeline for standards, differentiation of standards by area type, reduction of compliance
fluctuations by three-year averaging for limit values.
Conclusions
Reduction of PM is likely to be effective for reducing the health impact at all concentration levels in the EU. To avoid that a
fully binding level to be attained everywhere will only drive down levels at the most unfavourable locations, lower, more
ambitious levels in combination with flexibility provisions for locations where the standard cannot be met should be
considered. Several options for optimising the set of PM standards were identified, the expected improvement of which
should be balanced against the merits of regulatory stability.
Acknowledgement
The presentation is based on work carried out in service contracts to DG Environment of the European Commission.
References
WHO, 2013. Review of evidence on health aspects of air pollution – REVIHAAP project. World Health Organization,
Regional Office for Europe, Copenhagen.
25
CAN A STRINGENT REDUCTION IN EUROPEAN EMISSIONS HELP SWEDEN REACH NATIONAL
ENVIRONMENTAL QUALITY OBJECTIVES FOR ACIDIFICATION AND EUTROPHICATION?
S. Åström and M. Lindblad
IVL Swedish Environmental Research Institute Ltd., P.O. Box 53021, SE-400 14 Göteborg, Sweden
Presenting author email: Stefan.Astrom@ivl.se
Summary
In this study, scenario analysis was performed to determine if it is possible for Sweden to reach its environmental quality
objectives for acidification and eutrophication by emission reductions in Europe by 2020 and 2030. The environmental
impacts from emission reductions in 15 countries and three sectors were analysed in separate Ambition Scenarios. The results
showed that given an already full implementation of all emissions control technologies, the countries will have low potential
for further emission reduction of sulphur dioxide and nitrogen oxides, while the potential to reduce ammonia emissions
would be larger. As a consequence, reduction in ammonia emissions becomes the most important way to improve the
acidification problem in 2020. In the Ambition Scenarios, there was no significant improvement in acidification status in
Sweden. For Eutrophication, the affected areas were reduced from 13% to 5% in the Ambition Scenarios. Based on the data
and methods used in this study, the conclusions are that the Swedish environmental quality objective for acidification will be
difficult to achieve even by implementing extremely stringent European emission reductions, but that achievement of the
Swedish environmental quality objective for eutrophication will be aided by the corresponding emission reductions.
Introduction
The Swedish environmental quality objectives (SEQO) for acidification and eutrophication are currently not achieved, and
are not expected to be achieved by 20201. Sulphur dioxide (SO2), nitrogen oxides (NOx), and ammonia (NH3) are acidifying
compounds, while NOx and NH3 also are eutrophying. They are all transboundary pollutants, and Swedish problems with
acidification and eutrophication are therefore caused by emissions in several other countries. Since 2020 is the target year for
the SEQO:s, emission reductions are likely to be necessary. The purpose of this study was to analyse to what extent European
emission reductions would contribute to the achievement of the SEQO:s for acidification and eutrophication by 2020 and
2030.
Methodology
Achievement of the SEQO:s was in this study defined as a zero exceedance of modelled critical loads for acidification and
eutrophication. Analysis of the future European emissions that would enable Sweden to reach the SEQO:s was performed by
comparing different emission scenarios and the resulting environmental impacts. The scenarios were based on scenarios used
in the current EU policy process of revising the National Emissions Ceilings (NEC) directive2,3, and analysed using the
GAINS model4. Given the high exceedance previously reported, the emissions in this study’s Base Scenario included a full
implementation of available emission control technologies. The Ambition Scenarios represented additional sector-specific
emission reductions for each of the countries of highest importance for acidification and eutrophication in Sweden. In these
scenarios, emission reductions following a reduction of the emission precursor activities by 50% was assumed for the most
important sectors: power plants; transport; and agriculture. A Combined Scenario was also analysed.
Results
Despite very sharp reductions in the emission precursor activities, the corresponding emissions would only be 16% / 12%
(SO2), and 22% / 17% (NOx) lower in the Combined Scenario than in the Base Scenario emissions in 2020 and 2030,
respectively. Emissions of NH3 would be 34% lower by 2020 and 2030. The acidification problem in Sweden improved most
in the scenarios were NH3 emission were reduced. The model results showed that the improvement in the Combined Scenario
corresponded to <1% of the acidified areas in Sweden by 2020 and 2030, a non-significant improvement. For Eutrophication,
exceedance was reduced from 13% to 5% of the total ecosystem area considered in 2020 (from 11% to 4% in 2030). A
sensitivity analysis for acidification 2020 showed that Swedish and shipping emissions alone would cause exceedance of
critical loads for acidification on 17% of the areas considered.
Conclusions & discussion
The main conclusions are that by 2020 and 2030, given that all available emission control technologies are implemented,
further reduction in impact on acidification in Sweden will be difficult to achieve by emission reductions in nearby countries.
It will however be more feasible to reduce the impact on eutrophication by reduction of emissions from European countries.
However, one should contemplate whether the current methods used for calculating critical loads for acidification and
eutrophication needs further development and adaptation to the projected emission levels in 2020 and 2030.
Acknowledgement
This study was performed as a part of the CLEO programme, financed by the Swedish EPA. We would also like to thank the
GAINS model experts at IIASA for support with the analysis.
References
1. Swedish Environmental Protection Agency. 2012. Report 6500.
2. Amann M, et al. 2012. TSAP report #1.
3. Amann M, et al. 2013. TSAP report #10 - version 1.2.
4. Amann M. 2012. The GAINS Integrated Assessment Model.
26
MODELLING REAL WORLD ROAD DUST ABATEMENT MEASURES: AN APPLICATION OF THE NORTRIP
MODEL
I. Sundvor (1) and B. R. Denby (1)
(1) The Norwegian Institute for Air Research (NILU). PO BOX 100, 2027 Kjeller, Norway.
Presenting author email: is@nilu.no
Summary
In this paper we present an application of the NORTRIP road dust emission model. The model is used to simulate actual road
dust emission abatement measures implemented in Oslo including speed reduction, studded tyre reduction, dust binding and
cleaning. The model successfully reproduces changes in concentrations observed over a three year period for a particular road
in Oslo where a real world road dust mitigation experiment was carried out. Sensitivity analysis of the model to both
meteorological and traffic conditions indicate that meteorology and the related road maintenance activities have as significant
an impact on emissions as do changes in traffic speed and studded tyre share. The study provides confirmation that the model
can be used to predict the impact of a range of road dust mitigation strategies.
Introduction
Non-exhaust traffic emissions are a dominant contributor to PM10 concentrations in many Nordic countries. A range of
measures have been introduced to reduce these emissions but their impact needs to be better quantified if they are to be
efficiently implemented. The NORTRIP road dust emission model is a process based model developed as a tool to quantify
non-exhaust emissions and their dependency on meteorology, vehicle type, tyre types, studded tyre share, vehicle speed, road
salting, dust binding and cleaning. The model is described and validated in detail in Denby et al. (2013a, 2013b). In this paper
the model is applied to reproduce real world road dust emission abatement in Oslo.
Methodology and results
NORTRIP is applied over a three year period (2004-2006) in Oslo to one particular road (RV4). During this period an
experiment was carried out where speed limit signage was reduced from 80km/hr, in 2004, to 60 km/hr in 2005 and 2006. In
addition dust binding, using MgCl2, and road cleaning were only carried out in the year 2006. During this period studded tyre
share decreased from 27% to 20% and meteorological conditions varied considerably. Using observed meteorological data,
traffic counts and records of road maintenance activity for salting and cleaning, the model is applied to the three year period
and compared to observations. In addition a range of sensitivity tests is carried out to assess the impact of meteorology and
traffic on the emissions.
The model correctly simulates the changes in observed concentrations resulting from changes in traffic conditions and
meteorology over the three year period (Fig 1). It is found that meteorology, and associated road salting activities, affects
concentrations as significantly as changes in traffic and studded tyre share during this period (Fig 2). Additional sensitivity
tests with the model show that a reduction by half of cars and trucks using studded tyres on RV4 would lead to a reduction in
net mean PM10 concentrations of 23% - 31% and a reduction in the number of exceedance days by 5 to 12 days.
Fig.1 Comparison of modelled and observed net mean PM10
concentrations at the traffic station at RV4.
Fig.2 Model sensitivity matrix for meteorology and traffic conditions.
The diagonal represents the actual conditions, as in Fig 1.
References
Denby, B.R., Sundvor, I., Johansson, C., Pirjola, L., Ketzel, M., Norman, M., Kupiainen, K. , Gustafsson, M., Blomqvist, G.
and Omstedt, G., 2013a. A coupled road dust and surface moisture model to predict non-exhaust road traffic induced particle
emissions (NORTRIP). Part 1: road dust loading and suspension modelling. Atmospheric Environment, 77, 283-300, DOI:
10.1016/j.atmosenv.2013.04.069.
Denby, B.R., Sundvor, I., Johansson, C., Pirjola, L., Ketzel, M., Norman, M., Kupiainen, K. , Gustafsson, M., Blomqvist, G.,
Omstedt, G., M., Kauhaniemi 2013b. A coupled road dust and surface moisture model to predict non-exhaust road traffic
induced particle emissions (NORTRIP). Part 2: surface moisture and salt impact modelling. In press: Atmospheric
Environment 2013.
27
THE IMPACT OF LOW EMISSION ZONE AND HEAVY TRAFFIC BAN IN MUNICH ON THE REDUCTION
OF PM10 IN AMBIENT AIR
J. Cyrys (1,2), V. Fensterer (3), H. Küchenhoff (3), B. Bauer (3), H.-E. Wichmann (4), S. Breitner (1), A. Schneider (1), A.
Peters (1)
(1) Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology II, 85764
Neuherberg, Germany; 2) Environment Science Center, Universität Augsburg, 86159 Augsburg, Germany; (3) Statistical
Consulting Unit, Department of Statistics, Ludwig-Maximilians-Universität, 80799 Munich, Germany; (4) Helmholtz
Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology I, 85764 Neuherberg,
Germany;
Presenting author email: cyrys@helmholtz-muenchen.de
Summary
In our study we evaluate the effectiveness of a truck transit ban through the city area and implementation of Low Emission
Zones (LEZ) on the reduction of PM10 mass concentrations in the ambient air in Munich, Germany. The analysis of the PM10
levels by a semiparametric regression model showed statistically significant reduction of PM10 levels both at an urban
background site and a traffic site. The magnitude of the effect depends on the day of the week, time of day and location of the
monitoring site.
Introduction
In the framework of the new EU-Project ACCEPTED (Assessment of Changing Conditions, Environmental Policies, Timeactivities, Exposure and Disease) the impact of the implementation of LEZs on traffic-related air pollutant levels will be
estimated for three German cities (Berlin, Munich and Augsburg) applying advanced statistical method. We present here the
preliminary results of the analysis for Munich. The analysis for Berlin and Augsburg are still ongoing.
In Munich, a transit ban for heavy-duty vehicles larger than 3.5 tons was introduced on February 1, 2008. As a second
measure, the first stage of the LEZ became operative on October 1, 2008, and the second stage was introduced on October 1,
2010 (Bayerisches Staatsministerium für Umwelt und Gesundheit, 2010).
Methodology and Results
A semiparametric regression model with a first-order autocorrelated error term was applied for modeling the hourly PM10
mass concentration, adjusted for the time of day, day of the week, measures taken, and further confounder variables, such as
background pollution, public holidays and wind direction. The changes in PM10 were observed in relation to a reference
station representing regional background concentrations.
In the analysis we compared PM10 mass concentrations measured prior to the implementation of any air quality measures
(January 2006 – January 2008) with those recorded after introducing them (October 2008 – September 2010 (LEZ I) and
October 2010 – September 2012 (LEZ II)). In general, a reduction of mean PM10 mass concentration in ambient air was
observed after air quality measures had been introduced in Munich (Table 1).
Table.1 Changes of PM10 concentrations at an urban background (UB) and traffic (T) site in Munich (adjusted for exposure
at the reference site, wind direction, day of the week, time of day and public holidays)
Measurement site
Summer
Winter
Effect
Confidence interval
p-value
Effect
Confidence interval
p-value
UB (LEZ I)
-7.68%
(-8.70%, -6.64%)
<0.001
-6.27%
(-7.48%, -5.04%)
<0.001
UB (LEZ II)
-18.08%
(-18.90%, -17.26%)
<0.001
-7.62%
(-8.81%, -6.41%)
<0.001
T (LEZ I)
-7.13%
(-8.02%, -6.23%)
<0.001
-3.94%
(-5.12%, -2.75%)
<0.001
T (LEZ II)
-18.94%
(-18.23%, -19.64%)
<0.001
-6.10%
(-7.12%, -5.06%)
<0.001
A significant reduction of PM10 concentrations was observed in the time period from October 2008 until September 2010
(compared to the years 2006 – 2007) when the traffic ban and first stage of LEZ had become effective. After implementing
the second stage of the LEZ in Munich in October 2010, a further reduction of PM10 levels was achieved (October 2010 –
September 2012). In general, the effects were stronger during summer than in winter. The magnitude of the effect depends on
the time of day and the day of the week (data not shown).
Conclusions
The introduction of two measures for improvement of the ambient air quality in Munich resulted in a decrease of ambient
PM10 concentrations. However, the evaluation of such measures by means of PM10 data remains difficult due to strong
influence of meteorological conditions on PM10 levels. We recommend further particulate variables, such as PM2.5, Black
Smoke, or particulate organic compounds to obtain more precise evaluations of LEZ effects.
References
Bayerisches Staatsministerium für Umwelt und Gesundheit, 2010. Luftreinhalteplan für die Stadt München. 4.
Fortschreibung. http://www.muenchen.de/rathaus/Stadtverwaltung/Referat-fuer-Gesundheit-und-Umwelt/Luft und Strahlung
/Luftreinhalteplan.html [last access September 2013]
28
ATMO-IDEE: RHINE TRANSBOUNDARY ATMOSPHERIC PREVENTION IN THE EURODISTRICT
STRASBOURG-ORTENAU AND IN THE UPPER RHINE
R. Deprost (1), H. Scheu-Hachtel (2), J. Kleinpeter (1), E. Herber (1), S. Mazurais (1), C. Schillinger (1), T. Leiber (2), F.
Brocheton (3), C. Pesin (3), J. Galineau (3), L. Zilliox (4), G. Najjar (5)
(1) ASPA Association pour la Surveillance et l’étude de la Pollution atmosphérique en Alsace, Schiltigheim, France; (2)
LUBW Landesanstalt für Umwelt, Messungen und Naturschutz Baden-Württemberg, Karlsruhe, Germany; (3) NUMTECH,
Aubière, France; (4) SPPPI Strasbourg-Kehl, Permanent Office for Industrial Pollution Prevention, Strasbourg, France ; (5)
ICUBE, University of Strasbourg, UMR 7357, France.
Presenting author email: rdeprost@atmo-alsace.net
Summary
How to deal with public consultation and with the
environmental impact assessment (EIA) of an
authorization procedure in a transboundary context?
The governance and technical proposals of the AtmoIDEE project should improve answers to this question,
since it develops a local transboundary procedure and
all necessary air quality databases for the Eurodistrict
Strasbourg-Ortenau. Concerning consultation, the
project aims at identifying schedules and instances for
common transboundary debates and opinions.
Concerning data, the project has already released a
detailed emission inventory based on homogenised
calculation methods between Alsace (ASPA) and
Baden-Württemberg (LUBW). Then it produced
homogenised fine scale air quality maps for the
Eurodistrict using the urban model ADMS Urban
(distributed in France by NUMTECH). The model was
calibrated with air pollution and meteorology data
from fixed measurement networks and from several
fine scale measurement campaigns. Until its end in
2014, the project will still work on governance and on
several modelling exercises like a sector apportionment
study.
Fig.1 NO2 annual averages for 2012, simulated and calibrated with
homogeneous data and methods across the French/German border
Introduction
The question was initially raised by citizen associations for environmental defence that worried about the installation of new
industrial sites or traffic infrastructures in the already polluted transboundary urban area of Strasbourg and Kehl. Even if the
official way to proceed between French and German administrations is described in the “Guide for transboundary
consultations” of the French-German-Swiss Upper Rhine Conference, the local SPPPI wanted to add a real transboundary
governance of air quality in such cases, and furthermore, the ASPA demonstrated the need of homogeneous air quality data at
fine scale to be integrated EIAs. Hence, the Atmo-IDEE INTERREG IV Upper Rhine project started in 2012.
Methodology and Results
Finding common primary data and calculation methodologies for each significant third level activity (SNAP code), a fine
scale emission inventory was computed for SO2, NOX, CO, PMtot, PM10, PM2.5, NMVOC, CH4, N2O, NH3, HCl, C6H6,
BaP and CO2. The road traffic sector, representing finally 56% of NOX, 46% of C6H6 and 38% of PM10 emissions of the
Eurodistrict, was particularly highly investigated. The model ADMS Urban was set on an intelligent grid and calibrated with
air pollution and meteorology data of fixed networks (ASPA, LUBW, METEO FRANCE, DWD), of 4 urban measurement
campaigns during the summer 2012 and the winter 2012/2013 and of a specific urban climatology campaign of ICUBE. The
NO2 (see Fig.1), PM10, PM2.5, C6H6 and SO2 annual concentration means were respectively in the ranges [16;140], [17;60],
[14;46], [0.5;2.6] and [0.1;3.7] μg/m3, showing a good consistence with available measurements.
Conclusions
The Atmo-IDEE project has already delivered harmonized fine scale databases on emissions and concentrations for the
Eurodistrict Strasbourg-Ortenau and is now developing the local procedure allowing a total compliance to the wished
governance. The transferability of all developments to other Eurodistricts of the Upper Rhine will be investigated in 2014.
Acknowledgement
This work was co-financed by FEDER funds in the frame of the INTERREG IV Upper Rhine program, as well as the Urban
Community of Strasbourg, the City of Kehl and the Eurodistrict Strasbourg-Ortenau. We also acknowledge other partners:
SPPPI Strasbourg-Kehl, Lufhygieneamt Beider Basel (LHA), Regierungspräsidium Freiburg, DREAL Alsace, Landratsamt
Ortenaukreis, Eurodistrict Trinational de Bâle, Eurodistrict Regio PAMINA, Eurodistrict Freiburg, Centre et Sud Alsace.
References
All technical reports are available under www.atmo-idee.eu and on Facebook.
29
INVENTORY AND EFFECTIVENESS OF MEASURES TO IMPROVE AIR QUALITY IN GERMANY
F. Pfäfflin, V. Diegmann, H. Wursthorn
IVU Umwelt GmbH; Emmy-Noether-Str. 2; 79110 Freiburg
Presenting author email: fp@ivu-umwelt.de
Summary
The status of air quality plans published in Germany is described by a thorough analysis. These plans offer an extensive
overview of the current situation in Germany regarding air quality, different methodologies of assessment and proposed
measures to improve the respective situations. Due to the long period in which plans and measures have been developed and
put into action in Germany, there is the possibility to assess the effectiveness of measures after their respective
implementation using comparative studies. Reduction potentials for three examples of measures concerning road traffic were
analysed and the theoretical reduction potentials of Low-Emission-Zones (LEZs) were compared with published evaluations.
Introduction
Many cities in Germany still have problems to meet the limit values for NO2 and PM10 defined in Directive 2008/50/EC of
the European Parliament and of the Council, especially at locations influenced by road traffic. Most likely, these problems
will persist in the following years. Therefore, responsible authorities continue to publish or update air quality plans in
Germany, in particular accompanying notifications of time extensions (postponements of attainment deadlines) based on Art.
22 of Directive 2008/50/EC. The study provides an overview and a detailed inventory of the plans and identifies and
classifies measures in order to meet air quality limit values. In order to optimize further planning, a second part of the study
analyses the effectiveness of selected measures.
Methodology and Results
A total of 242 air quality plans published in Germany up to 30.11.2012 were compiled, registered and analysed. Plans are
expected to include source apportionments with respect to both spatial origin and different source groups and were, e. g.
analysed with this respect. For NO2, pollution due to local road traffic at the respective sites causes, on average, 50 % of the
total concentration and, on average, 64 % of the total concentration are caused by road traffic in the city. For PM10, local
sources contribute 26 % to the total concentration and 54 % are attributed to regional background. The fraction of road traffic
in the cities is, on average, 30 %. Some of the data of the plans were presented as thematic maps, showing, e. g., regional
differences.
A detailed scheme for classifying the measures (e. g. with respect to source groups or fields of action) was compiled as an
analysis tool, currently containing 2588 measures. To ensure comparability of the measures, a compilation of standardized
measures (currently 130) was developed. A statistical analysis shows that, in accordance with the results of the source
apportionment, 80 % of the measures are aiming at road traffic. Industrial processes are targeted by 16 % of these measures.
Due to the long period in which plans and measures have been developed and put into action in Germany, there is a
possibility to assess the effectiveness of measures after their respective implementation using comparative studies and, thus,
found the assessment of the effectiveness of measures on more information than the expected effects noted in the plans which
are normally based on estimations and scenario calculations. To do so, reports of evaluations of measure that were carried out
after the adoption of the plans and the implementation of the measures were compiled, analysed and documented. This
research shows that there are relatively few such studies. A comparatively wide spectrum of evaluations does exist for LEZs
however about half of these studies do not note a specific potential for the reduction of concentrations. The remaining studies
give reduction potentials for the single measure LEZ of up to 10 % for NO2 7 % for PM10 and 10 % for PM2.5. Additionally,
results for evaluations of the measures 'environmental traffic management', 'ban on transit of trucks' and 'speed limits of 30 or
40 km/h on major roads' have been compiled.
Theoretical reduction potentials for three examples of measures concerning road traffic were assessed based on the
'Handbook of emission factors for road transport' (HBEFA, 2010) and studies for the air quality plans of Berlin and Kassel.
These assessments predict, e. g., for an extension of the German vehicle classification regulation to include gasoline vehicles
a significant increase of the NO2 reduction potential of a LEZ to up to 7 % in 2015. Higher reduction potentials can only be
reached by intensified insertion of Euro-6/VI vehicles in the fleet. A comparison of the theoretical reduction potentials with
published evaluations shows good agreement with most publications.
Conclusions
The study provides an extensive overview and analysis of German air quality plans and measures to improve air quality
together with a tool to classify and analyse the measures. Reduction potentials of single measures are in general low and not
all air quality problems in Germany will be solved by the measures planned. E. g., for NO2 in more than 60 % of the cases a
local measure has to reduce the additional concentration by more than 50 % to allow for the possibility to comply with the air
quality limit value. In three of the 80 cases analysed, a complete reduction of the additional concentration doesn't suffice for
complying with the air quality limit value.
Acknowledgement
This work was funded by the Federal Environment Agency (Umweltbundesamt) of Germany (FKZ 3712 43 255).
References
HBEFA, 2010: Handbook Emission Factors For Road Transport 3.1. Quick Reference. INFRAS, Bern.
30
AMMONIA AND NITROGEN OXIDES EMISSIONS REDUCTION INFLUENCE ON AIR QUALITY OVER THE
PO VALLEY
E. Angelino (1), M. P. Costa (2), A. D’Allura (2), S. Finardi (2), G. Fossati (1), G. Lanzani (1), E. Peroni (1), P. Radice (2),
C. Silibello (2)
(1) ARPA Lombardia, via I. Rosellini, 17 - 20124 Milano, Italy; (2) ARIANET S.r.l., via Gilino 9, 20128 Milano, Italy
Presenting author email: e.angelino@arpalombardia.it
Summary
Fourteen different combinations of ammonia and nitrogen oxides emission reduction scenarios have been investigated
through the application of a chemical transport model on two monthly periods characterised by significant measured levels of
ammonia and particulate matter, respectively during spring and autumn 2011. The simulation domain covers the whole Po
Valley (hereafter P-V) in Northern Italy. Results obtained considering the actual emissions simulation (base case) have been
compared with observed levels of PM2.5, PM10, NH3, NOX and O3 at different monitoring stations located in P-V. The amount
and combination of emissions reduction needed to effectively reduce secondary PM levels has been also estimated from the
analysis of considered scenarios. The role of NOX and NH3 on PM2.5 mass and composition is confirmed, claiming for the
implementation of proper emission control strategies.
Introduction
P-V is one of the air pollution hot spots of major concern in Europe where the EC air quality standards are presently not
attained. It is characterised by peculiar topographic features, being surrounded on three sides by the Alps/Apennines chain,
and by one of the most densely populated area in Europe, with a global population of about 20 million inhabitants. This area
is characterised by very high emissions and concentrations of ammonia, whose role as aerosol precursor, together with NOX
and SO2, is well known. Since PM composition analysis showed that: 1) a large fraction of aerosol has secondary origin; 2)
SO2 emissions have significantly decreased during the last decades, leading to year-round low concentrations recordings; it is
of major interest to understand the potential PM2.5 concentration reduction reachable through NOX and ammonia emission
limitation policies. According to the Lombardia regional emission inventory, 96% of NH3 year emissions in the region
comes from agriculture activities while the remaining portion (about 4%) is given, particularly in urban areas, by road traffic,
from vehicles equipped with three-way catalytic converters.
16/9/2011-16/10/2011
80
70
-3
g m ]
60
50
40
30
20
10
0
7/10
5/4
7/4
9/4
15/10
5/10
3/4
13/10
3/10
1/4
11/10
1/10
9/10
29/9
27/9
25/9
23/9
21/9
19/9
17/9
15/9
17/3/2011-19/4/2011
80
70
-3
g m ]
60
50
40
30
20
10
0
17/4
15/4
13/4
11/4
30/3
28/3
26/3
24/3
22/3
Fig.1
20/3
18/3
Methodology and Results
The atmospheric modelling system (AMS) used to simulate the chemical and
physical processes involving the pollutants in the atmosphere is based on
Flexible Air quality Regional Model (FARM). A description of FARM model
and the modules that constitute the AMS can be found in Silibello et al.
(2012). Following inventories have been used to apportion emissions to grid
cells:
Regional
(www.inemar.eu),
National
(www.sinanet.apat.it/it/sinanet/serie_storiche_emissioni) and International
(www.ceip.at). Simulations were performed on two one-month periods during
2011, lasting respectively from March 17th to April 19th and from September
16th to October 16th. Figure 1 shows an example of the performance of the
AMS, at an urban background station located in Milano urban area, confirming
its reliability for further emission scenarios studies. The fourteen scenarios
have been selected to study the influence on PM2.5 levels of possible ammonia
and nitrogen oxides emission reduction strategies over Lombardia Region and
over the whole P-V domain. The impact of the two main ammonia emissions
sources (manure/agriculture and traffic) has been also investigated. As an
example in the following Figure 2 the evaluation of a 50% reduction of NH3
emissions from agriculture for the Spring period is given, evidencing an
average reduction of about 1 g m-3 over a large portion of Lombardia region.
Comparison between observed
(black) and base-case (grey)
PM2.5 concentrations
Conclusions
Results obtained allowed to derive a first estimation of the more effective
strategies to reduce particulate matter levels over Lombardia region. Combined
reductions appear to be more effective than higher reductions of individual
species. Moreover, a careful analysis of emissions from surrounding areas is
needed to set up proper emission control strategies at local administrative
level.
References
Silibello, C., Calori, G., Costa, M.P., Dirodi, M.G., Mircea, M., Radice, P.,
Vitali, L., Zanini, G., 2012. Benzo[a]pyrene modelling over Italy: comparison
with experimental data and source apportionment. Atmospheric Pollution
Research, 3, 399-407.
31
Fig.2 Average reduction of PM2.5 levels
during spring period due to a
50% reduction of NH3 emissions
from agriculture
ASSESSMENT OF CO-BENEFITS FROM CLIMATE AND AIR QUALITY POLICIES WITH THE TM5-FASST
TOOL
J. Leitao (1), R. Van Dingenen (1), F. Dentener (1), S. Rao (2)
(1) European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi 2749, I-21027
Ispra (VA) , Italy (2) IIASA Schlossplatz 1, A-2361 Laxenburg Austria
Presenting author email: joana.leitao@jrc.ec.europa.eu
Summary
This study provides an assessment of co-benefits of combined climate and air pollution strategies in long-term integrated
assessment scenarios. A set of air pollutant emission scenarios, delivered by 5 different integrated assessment models for a
selection of combined climate and air quality policies within the LIMITS project, were used as input of the TM5-FASST
global source-receptor model and impacts on human health, vegetation and radiative forcing were determined . The obtained
results allowed for an identification of possible synergies and trade-offs of combined national policy that focus both on
climate change and air pollution.
Introduction
National policies do not usually deal with air pollution control and climate mitigation as one single problem to be tackled.
Nevertheless, the link between the two issues is becoming more evident even if their impacts and scales (time and spatial) are
quite diverse. Some sectors, such as fossil fuel combustion, are sources of both pollutants (NOx and PM) and greenhouse
gases (CO2). Additionally, the implementation of measures such as wood burning as biofuel to reduce climate impact may in
fact deteriorate air quality. This linkage should not be disregarded in policy making and design of emission control strategies.
A better understanding of these co-benefits and trade-offs is a prerequisite for a more efficient development of cross-policy
schemes and supports as stimulation for the effective implementation of mitigation measures.
Methodology
Within the LIMITS FP7 project (http://www.feem-project.net/limits/index.html), five integrated assessment models (IAMs)
provided greenhouse gas and pollutant emission scenarios within predefined constraints on climate change, socio-economic
development, technological scenarios, accounting also for current and future climate and air quality policies. Three air
quality scenarios based on the stringency and implementation of future global air pollution legislation were combined with 2
climate policy scenarios (no climate policy and 2.8 W/m2 target). Emission factors for relevant air pollutants by sector and
region were harmonized between the IAMs.
In the framework of this project the impact evaluation of the resulting emissions is done with a global air quality sourcereceptor model TM5-FASST that calculates in a first stage the pollutant concentrations. TM5-FASST is a linearized version
derived from the full chemical transport model TM5-CTM (Krol et al., 2005). The model takes as input pollutants emissions
from 56 source regions with global coverage, and calculates resulting pollutant concentrations and their associated impacts
on human health and ecosystems, besides it also provides some climate metrics such as CO2eq of emitted short lived climate
pollutants. The validity of the TM5-FASST tool has been demonstrated in several studies, such as the UNEP synthesis report
addressing the control of short-lived climate forcers and co-benefits from climate policy (UNEP, 2011).
Results and Conclusions
The results show that stringent climate policies provide a significant air quality benefit compared to current legislation air
quality policy, both in terms of reduced premature mortalities and improved crop yields. The air quality co-benefit of climate
policies is more pronounced in polluted developing regions (Asia). These regional and near-term benefits provide a strong
incentive for the implementation of climate policies.
Acknowledgement
The research leading to these results has received funding from the European Union Seventh Framework Programme
FP7/2007-2013 under grant agreement n° 282846 (LIMITS).
References
Krol, M., Houweling, S., Bregman, B., Van Den Broek, M., Segers, A., Van Velthoven, P., Peters, W., Dentener, F. and
Bergamaschi, P., 2005. The two-way nested global chemistry-transport zoom model TM5: Algorithm and applications.
Atmospheric Chemistry and Physics, 5(2), 417-432.
UNEP, 2011. Near-term Climate Protection and Clean Air Benefits: Actions for Controlling Short-Lived Climate Forcers,
United Nations Environment Programme (UNEP), Nairobi, Kenya, 78pp.
32
THE COMPARISON OF COSTS OF POLICIES AIMED AT REDUDING AIR QUALITY INDUCED HEALH
RISKS, HEALTH BENEFITS AND PERCEIVED VALUES IN FINLAND
J. Kutvonen (1,2), A. Asikainen (1), P. Pasanen (2) and O. Hänninen (1)
(1) National Institute on Welfare and Health of Finland
(2) University of Eastern Finland
Presenting author email: juho.kutvonen@thl.fi
Summary
Particulate matter is a serious threat to public health. This work evaluates the benefits achievable by restricting residential
wood combustion and traffic speed limits in urban areas in Finland. The estimated costs and health benefits were compared
with perceived values assessed by a questionnaire. Costs of policy implementation, gained health benefits and their monetary
values and people´s values were estimated by an econometric model. The model showed that based on cost-benefit analysis,
reduction of small-scale wood combustion to half by increasing the price of wood to € 140 per cubic meter and 35 kmh-1
speed limits in urban areas would be profitable policies. When people´s values were considered in cost-benefit analysis,
reduction of small-scale wood combustion to half remained a profitable policy but 35 kmh-1 speed limits in urban areas did
not.
Introduction
Outdoor PM2.5 is the most dangerous environmental agent in Finland causing annually nearly 2 000 deaths (Pekkanen 2010).
Burden of disease caused by outdoor PM2.5 can be reduced by political decisions but implementation of policies causes
expenses. Cost-benefit analysis can be applied in decision making to find out whether a political decision is profitable or not.
Cost-benefit analysis, however, doesn´t consider people´s attitudes or values regarding political decisions. The aim of this
work is to compare results of traditional cost-benefit analyses with perceived values of subjects affected by the policies.
Methodology
An econometric model was developed to quantify policy costs, health benefits and perceived values. Hypothetical scenario
for PM2.5 emission reductions from small scale wood combustion and urban road traffic were developed including (i) total
ban of small-scale wood combustion in urban areas, (ii): reduction of small-scale wood combustion to half by the price raise
and (iii) 35 kmh-1 speed limits in urban area. People´s attitudes were measured from university students in Kuopio and
Helsinki and employees of the Finnish National Institute on Health and Welfare in Kuopio and Helsinki (n =1946, 468
responses) with a value questionnaire based on willingness to pay technique (Le Gall-Ely 2009).
Results
Cumulative costs of policies observed for 50 years for small-scale wood combustion, reduction of small-scale wood
combustion to half and 35 kmh-1 speed limits in urban area were €9.5 billion, €0.6 billion and €0.1 (0.05-1.3) billion,
respectively. Reductions in burden of disease were 570 DALY, 285 DALY and 462 DALY per year. DALY was given a
monetary value (€ 150 000, € 165 000 and € 180 000). Discounted (interest 3 %) monetary values observed for 50 years for
these reductions were € 2.5 (2.3-2.7) billion, € 1.2 (1.1-1.3) billion and € 2.0 (1.8-2.2) billion, respectively. People´s attitudes
were either positive or negative, i.e. positive value is found as a benefit and negative value if found as a disadvantage. 35
kmh-1 speed limits in urban areas were found very disadvantageous since the value measured in money was €-200 (-350– 359 billion). Surprisingly, people found policies aimed to reduce PM2.5 emissions from small-scale wood combustion
advantageous. Values to total ban of small-scale wood combustion in urban areas and to reduction of small-scale wood
combustion to half by increasing the price of wood to €140 per cubic meter were € 0.6 (-0.2-+1.4) billion and € 0.3 billion (0.1-+0.7), respectively. Based on the traditional cost-benefit analysis in which only costs and benefits are considered,
reduction of small-scale wood combustion to half and 35 kmh-1 speed limits in urban areas are profitable since they yield a
positive net sum of € 0.6 (0.5-0.7) and 1.2 (0.03-1.3) billion, respectively. When supplemented with the perceived values,
reduction of small-scale wood combustion to half by increasing the price of wood to € 140 per cubic meter yields a positive
net sum of € 0.4 (0.3-1.2) but 35 kmh-1 speed limits in urban areas yields a negative net sum of € -211 (-28–-350) billion.
Conclusions
It seems that when people´s attitudes are considered, reduction of small-scale wood combustion to half and 35 kmh-1 speed
limits in urban area seem to be profitable policies. However, national actions (ban of small-scale wood combustion in urban
areas and 35 km/h speed limits in urban areas) aimed to reduce outdoor PM2.5 exposure are not efficient enough since
majority of the burden of disease of outdoor PM2.5 is caused by long-range transport that can only be reduced by international
agreements.
Acknowledgement
This work was supported by Ministry of Social Affairs and Health of Finland.
References
Pekkanen J. 2010. Elin- ja työympäristön riskit Suomessa Ympäristö ja Terveys-lehti 3:2010, 41 vsk. p.4-5
Le Gall-Ely M. 2009. Definition, Measurement and Determinants of the Consumer’s Willingness to Pay: a Critical Synthesis
and Avenues for Further Research. Recherche et Applications en Marketing 24(2): 91-112
Gynther L., Tervonen J., Hippinen I., Lovén K., Salmi J., Soares J., Torkkeli S. and Tikka T. 2012. Liikenteen
päästökustannukset. Liikenneviraston tutkimuksia ja selvityksia 23/2012. p.152
33
DEVELOPMENT AND
APPLICATION OF AIR
QUALITY AND RELATED
MODELS
34
PLSR AND ANN APPROACHES TO ESTIMATE HEAVY METAL LEVELS IN AIRBORNE PM10
G. Santos, I. Fernández-Olmo and A. Irabien
Dpto. Ingeniería Química y Química Inorgánica, Universidad de Cantabria, Avda. Los Castros s/n 39005 Santander,
Cantabria, Spain
Presenting author email: santosg@unican.es
Summary
According to the European Union (EU) Air Quality Framework Directive, ambient air quality in zones and agglomerations
where the level of pollutants is below the lower assessment threshold can be assessed by means of objective estimation
techniques. This is the case of some metals in some urban areas in Cantabria (Northern Spain). This work aims to estimate
the annual mean levels of the EU regulated metals i.e. arsenic, cadmium, nickel and lead, in airborne PM10 by means of
objective estimation techniques in two urban areas in Cantabria: Castro Urdiales and Reinosa. Partial Least Square
Regression (PLSR) and Artificial Neural Networks (ANN) were used to develop the estimation models. The results show that
the estimations developed in this work, based on PLSR and ANN, fulfill the EU uncertainty requirements for objective
estimations techniques and, consequently, can be used for the air quality assessment.
Introduction
Detrimental effects of Particulate Matter (PM), which still remains one the most concerning air pollutants responsible for
causing human health damages in urban areas, are due to its physical attributes as well as to its chemical composition. In this
regard, the European Union (EU) has not only included limits for PM10 and PM2.5 in the air quality directive, 2008/50/EC, but
also it has established a set of air quality targets for some trace metals in PM10: As, Cd, Ni (Directive 2004/107/EC) and Pb
(Directive 2008/50/EC).
The annual mean concentration of these metals is well below the lower assessment threshold in two urban areas of Cantabria
(Northern Spain): Castro Urdiales and Reinosa (Arruti et al., 2011). Therefore, according to the EU regulation, objective
estimation techniques are sufficient to assess the air quality in relation to heavy metals at these locations, which would allow
to avoid making experimental measurements saving time, effort and resources. In the present work, the fairly broad term
“objective estimation techniques” is understood as empirical modelling.
Methodology and Results
Empirical modelling techniques require measurements of the properties of the system output and of those variables believed
to be representative of the process behaviour. Therefore, the input data set used in this study is divided into response
variables and predictor variables. The former consist of PM10-bound regulated metal concentrations in Castro Urdiales and
Reinosa. The latter are constituted by: qualitative or nominal variables taking into account the seasonal, the Saharan dust
intrusion and the weekend effects; and quantitative or continuous variables, namely, meteorological data and major
atmospheric pollutants concentration, which are measured automatically on real time at the Castro Urdiales and Reinosa
monitoring stations of the Cantabria Regional Air Quality Monitoring Network.
A previous work by Arruti et al. (2011) demonstrated the feasibility to apply multivariate regression techniques such as
Multiple Linear Regression (MLR) and Principal Components Regression (PCR) to estimate the ambient air heavy metal
levels. Nevertheless, there are other promising techniques which could lead to an improvement of the estimations. In this
study, Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) models have been developed.
The models performance has been evaluated using some statistics including the correlation coefficient (r). In addition, two
indexes of uncertainty have been used to validate the objective estimation techniques in the context of the Air Quality
Directives: the relative maximum error without timing (RME) and the relative directive error (RDE).
The results obtained at the two different sites show that PLSR models estimate the annual mean concentrations precisely. The
r values are within the range of 0.5-0.8. On the contrary, ANN models provide less accuracy when it comes to estimate the
annual mean values. Regarding the uncertainty indexes, both techniques provide a RME and a RDE below 100%, which is
the maximum uncertainty allowed by the EU for objective estimation techniques. Hence, since the main objective of this
work is to obtain a proper estimation of the annual mean concentrations of the EU regulated heavy metals fulfilling the EU
uncertainty requirements, PLSR and ANN models can be considered valid approaches for this purpose.
Conclusions
Partial least squares regression (PLSR) and Artificial Neural Network (ANN) techniques were employed to develop
empirical models to estimate the ambient air levels of the EU regulated metals i.e. arsenic, cadmium nickel and lead, from the
airborne PM10 in two urban areas in Cantabria (Northern Spain): Castro Urdiales and Reinosa. Based on the results obtained,
PLSR-based and ANN-based estimation models could be employed as an alternative to experimental measurements for the
air quality assessment in relation to heavy metals in the studied areas with the consequent saving of time and resources.
Acknowledgement
This work was supported the Spanish Ministry of Economy and Competitiveness (MINECO) through the Project CTM201016068. Germán Santos also thanks MINECO for an FPI fellowship.
References
Arruti A., Fernández-Olmo I., Irabien A., 2011. Assessment of regional metal levels in ambient air by statistical regression
models. J. Environ. Monit. 13(7), 1991-2000.
35
APPLICATION AND DEVELOPMENT OF THE OPERATIONAL STREET POLLUTION MODEL (OSPM) TO
COMPLEX GEOMETRIES AND DRY CLIMATES
T.-B. Ottosen (1,2) K. Kakosimos (1), M. Ketzel (2), O. Hertel (2) and R. Berkowicz (2)
(1) Department of Chemical Engineering, Texas A&M University at Qatar, Doha, Qatar; (2) Department of Environmental
Science, Aarhus University, Roskilde, Denmark
Presenting author email: thor-bjorn.ottosen@qatar.tamu.edu
Summary
One of the most widely applied models for predicting air pollution concentrations in street canyons is the Operational Street
Pollution Model (OSPM). Recent findings have however suggested that the model underperforms in certain situations. It is
the aim of the research to analyze the causes of the slightly poorer performance and suggest improved parameterizations.
Results of the analyses of the model performance will be presented, and validation of new parameterizations against existing
measurements and numerical models is performed.
Background
Due to the toxic nature of the compounds in car exhaust, emissions from vehicles is increasingly becoming a health concern
in cities around the world. The Operational Street Pollution Model (OSPM, Berkowicz et al. 2000) is one of the most widely
applied models in this area (Vardoulakis et. al., 2003).
OSPM was developed in the early 1990’s and has since then successfully been applied to model air pollution concentrations
in different types of street canyons around the world. However, recently a number of shortcomings in the model have been
revealed. The shortcomings mainly relate to application of the model to street canyons characterized by either aspect ratio
significantly different from one, tropical-dry climates and the thereof following atmospheric stability, or inhomogeneously
distributed emissions (Kakosimos et. al., 2010).
Methodology
The model was originally developed for streets with aspect ratio (height to width ratio) of approximately one. Validation
studies have shown that the model tends to underperform when applied to streets with either very high or very low aspect
ratio plus streets with only buildings on one side of the street (Kakosimos et. al., 2010, Ketzel et. al., 2012). The model thus
has to be adapted to more adequately describe the flows in these types of “irregular” street canyons. The adaptation will be
based on existing measurements and wind tunnel data plus CFD-modeling of the flow in this type of street canyon.
The model contains a simplified chemical scheme to describe the conversion of NOx to nitrogen dioxide. This scheme has
shown to perform adequately for temperature and solar radiation conditions as found in Northern Europe, but underperforms
for warmer climates, and new parameterizations for this chemical conversion thus have to be developed.
In the original model the emission is evenly distributed from wall to wall in the street canyon as an approximation for the
actual inhomogeneously distributed emission. A new modeling approach, where the emission is distributed into a number of
uneven sized segments along the length of the street canyon, has been developed. A suggestion for a new parameterization of
horizontal dispersion is also presented.
Results
The results of the new model will be compared to measurements and CFD modeling of a street canyon in Stockholm,
Sweden. Moreover, the new model will be validated against long time series measurements from street canyons in Denmark.
Preliminary results from application of the model to the conditions found in Doha, Qatar also highlight some of these
problems.
References
Berkowicz, R., OSPM – a parameterised street pollution model. Environ. Monitor. Assess., 2000, 65, 259-267.
Kakosimos K., Hertel O., Ketzel M., Berkowicz R., 2010. Operational Street Pollution Model (OSPM) – a review of
performed application and validation studies, and future prospects. Environ. Chem. 7, 285-503.
Ketzel M, Jensen SS, Brandt J, Ellermann T, Olesen HR, 2012. Evaluation of the Street Pollution Model OSPM for
Measurements at 12 Streets Stations Using a Newly Developed and Freely Available Evaluation Tool. J. Civil. Environ. Eng.
S1:004. doi:10.4172/2165-784X. S1-004
Vardoulakis S, Fisher B. E. A., Koulis P., Gonzalez-Flesca N., 2003. Modelling air quality in street canyons: a review.
Atmos. Environ. 37, 155-182.
36
MULTIPHASE CHEMISTRY OF AMINES RELEASED FROM CCS TECHNIQUES:
REACTIVITY EXPERIMENTS AND NUMERICAL MODELING
C. J. Nielsen (1), C. Weller (2), A. Tilgner (2), R. Schrödner (2) R. Wolke (2) and H. Herrmann (2)
(1) University of Oslo, Department of Chemistry, University of Oslo, 0315 Oslo, Norway
(2) Leibniz-Institute for Tropospheric Research (TROPOS), Permoserstraße 15, 04318 Leipzig (Germany)
Presenting author email: c.j.nielsen@kjemi.uio.no
Summary
The present study investigated the chemical fate and removal (deposition) of amines and other emitted or secondarily
produced compounds related to amine-based solvent CCS technology. The dispersion model studies have revealed that the
expected emissions from the use of a MEA-based solvent at CO2 Technology Centre Mongstad will result in nitrosamine and
nitramine amounts well below the guidelines for drinking water and long-term exposure in air set by the Norwegian Institute
for Public Health.
Introduction
The CO2 Technology Centre Mongstad (TCM) is the world’s largest facility for testing and improving technologies for CO2
capture. The knowledge gained will prepare the ground for full scale CO2 capture initiatives to combat climate change. TCM
is a joint venture between the Norwegian state, Statoil, Shell and Sasol. It is located at the West coast of Norway, north of the
city Bergen. The centre presently consists of two post-combustion CO2 capture demonstration plants and utility systems. One
plant uses amine based technology, the other uses chilled ammonia technology. The main emitted component is NH3 from
both plants. The amine plant additionally emits amines and various degradation products of which nitrosamines and
nitramines are of particular concern. These compounds can also form in the atmosphere post-emission of amines.
Methodology and Results
To investigate the tropospheric chemical fate of emitted amines, the impact
of the gas and aqueous phase needs to be considered (Nielsen et al., 2012).
Thus, both reactivity laboratory experiments and chamber studies focusing
on the gas and aqueous phase chemistry of amines and its oxidation products
were performed. In detail, gas phase reactivity experiments focusing on
nitrosamine photolysis as well as the NO3 and Cl radical chemistry of
amines, nitramines and nitrosamines were conducted. Moreover, the
aqueous phase reactivity of NO3 radicals and ozone with relevant amines
and their corresponding nitrosamines as well as the aqueous phase
nitrosamine formation and nitrosamine photolysis were investigated during
lab experiments. These experiments implicate e.g. that aqueous phase
photolysis can be an effective sink for nitrosamines and that ozone is
unreactive towards amines and nitrosamines. Based on the performed lab
and chamber studies, up-to-date tropospheric oxidation schemes were
developed describing the gas and aqueous phase chemistry of amines and its
oxidation products. The developed multiphase phase oxidation schemes were
Fig.1 Monthly mean nitramine concentrations
coupled to the existing multiphase chemistry mechanism and built into the
for June 2007 for the explicit MEA mechanism
scheme, modelled with COSMO-MUSCAT
parcel model SPACCIM for detailed process model studies and the
dispersion model (“expected” case).
subsequent development of an reduced multiphase MEA mechanism. The
modelling work was specifically designed to resemble characteristic
conditions present at a planned CCS power plant site (Mongstad, Norway). Additonally, a simplified gas phase chemistry
mechanism scheme for MEA and other emitted or secondarily produced compounds (amines, nitramines and nitrosamines)
was developed. Both reduced gas phase mechanism schemes were used for regional scale dispersion modelling studies with
the COSMO-MUSCAT model. Model simulations were performed for two different emission scenarios (“expected” and
“worst” case). The dispersion studies have revealed that secondarily formed nitramines (from MEA) are in the same order of
magnitude of their concentrations as the primarily emitted nitrosamines.
Conclusions
The studies have shown that both gas phase and aqueous phase processes are important for the atmospheric processing of
amines. Amines are readily oxidized by OH radicals in the gas and cloud phase under summer conditions; amine oxidation is
limited during winter conditions at Mongstad. The importance of the gas and aqueous phase depends strongly on the
partitioning of the different amines. Model simulations showed that the aqueous formation of nitrosamines is not a relevant
process under tropospheric conditions. The aqueous phase reduces substantially the formation of harmful compounds in the
gas phase. The performed dispersion model studies revealed that both dry and wet deposition processes are equally important
for the investigated compounds, and that the proposed guidelines for nitrosamines and nitramines in drinking water and for
long-term exposure in air will not be exceeded from the use of a MEA-based solvent at TCM.
Acknowledgement
This work was financed by Gassnova and the CO2 Technology Centre Mongstad (TCM, http://www.tcmda.com).
References
Nielsen C. J., Herrmann H., Weller C., 2012. Atmospheric chemistry and environmental impact of the use of amines in
carbon capture and storage (CCS). Chemical Society Reviews. 41(19), 6684- 6704
37
IMPACT OF MERCURY CHEMISTRY ON REGIONAL CONCENTRATION AND DEPOSITION PATTERNS
J. Bieser (1), V. Matthias (1), A. Aulinger (1), B. Geyer (1), I. Hedgecock (2), F. DeSimone (2), C. Gencarelli (2), O.
Travnikov (3)
(1) Helmholtz-Zentrum Geesthacht, , Institute of Coastal Research, Max-Planck-Strasse 1, 21502 Geesthacht, Germany
(2) CNR – Institut Inquinamento Atmosferico, U.O.S. Di Rende, UNICAL-Polifunzionale, 87036 Rende, Italia
(3) Meteorological Synthesizing Center-East of EMEP, 2nd Roshchinsky proezd., 8/5 Moscow 115419, Russia
Presenting author email: johannes.bieser@hzg.de
Summary
Mercury is a toxic substance that is ubiquitous in the environment. In the atmosphere mercury exists in three forms: Gaseous
Elemental Mercury (GEM), Gaseous Oxidized Mercury (GOM), and Particle Bound Mercury (PBM). GOM and PBM make
up only 1 percent of the total. But deposition, which is the only sink for atmospheric mercury, is dominated by these two
species. Therefore, oxidation processes are key to understand the behaviour of mercury in the atmosphere. However, in the
scientific community a consensus on the importance of oxidizing reactants, namely ozone, hydroxy radicals, and halogens,
has not been reached yet. This model study about the influence of chemical reactants on the regional transport of mercury is
part of the European Union FP7 Research Project GMOS (Global Mercury Observation System). GMOS focuses on the
improvement and validation of mercury models to assist establishing a global monitoring network and to support political
decisions. In the course of this study the Chemistry Transport Model CMAQ was used to simulate the transport and
deposition of mercury using different chemical oxidation mechanisms. The different chemical mechanisms were evaluated by
comparison to a long term dataset of high resolution speciated mercury measurements (Weigelt et al., 2013).
Introduction
Mercury is a global pollutant that is known to have adverse effects on human health (UNEP 2013). Because of anthropogenic
emissions from fossil fuel burning the amount of mercury available in the environment is steadily increasing. Recent studies
have shown that the atmospheric mercury burden has increased by a factor of 7.5 since pre-industrial times (Amos et al.
2012).
Methodology and Results
The CMAQ model was set up on a 72x72km² domain over Europe with a 24x24km² nested domain over the North- and
Baltic Sea region. To account for the uncertainty in input datasets the model was run with meteorological fields from
COSMO-CLM and WRF. The outer domain was forced with 6 hourly boundary conditions from the global Hg CTMs
ECHMERIT and GLEMOS. Hourly anthropogenic and biogenic emissions were created with the SMOKE-EU emissions
model. Annual total mercury emissions were obtained from the AMAP 0.5x0.5° global emission inventory for 2005.
Modelled concentrations of PBM and GOM, as well as wet deposition of mercury were compared with observations at the
German measurement station Waldhof. At Waldhof for the years 2009 to 2012 hourly observations of GEM and three-hourly
observations of PBM and GOM are available. The detection limit of the applied method is 0.4 pg/m³. Additionally, daily
precipitation and weekly wet deposition measurements are available. Based on this dataset the capability of CMAQ to
reproduce atmospheric concentrations of oxidized mercury and the removal of mercury out of the atmosphere was
investigated. For this purpose several CMAQ scenarios were calculated, where the different sources of PBM and GOM (i.e.:
atmospheric oxidation, inflow from the Atlantic boundary, and primary emissions) were removed from the input fields.
Finally, the chemical reactions for mercury oxidation were evaluated. In the heavy metal version of CMAQ GEM can be
oxidized by ozone, OH, H2O2, and chlorine. Bromine reactions are not implemented into the model. To evaluate the influence
of the different reactions additional CMAQ runs were performed for each reactant and each product.
Conclusions
A comparison of high resolution speciated mercury and wet deposition measurements revealed that the reaction rates
currently used in atmospheric CTMs overestimate the production of PBM and GOM. For PBM, the primary emissions lead to
an annual cycle and PBM concentrations that were in accordance with observations, while the oxidation reactions resulted in
an overestimation of PBM concentrations during summer. For GOM the model overestimated concentrations by a factor of 5.
The modelled concentrations were inside a factor of 2 of observations if primary GOM emissions were completely neglected.
In this case the model was also able to reproduce the strong annual and diurnal cycle of GOM.
This leads to the assumption that the reaction rates for mercury oxidation need to be revised and that the current split of
products overestimates the production of PBM. The best agreement between the model and observations at Waldhof was
found for the ozone reaction. Moreover, the speciation of emissions in current inventories appears to overestimate the amount
of GOM emitted by combustion processes. This could be explained by in-plume reduction of GOM. The results of this study
are based on a single measurement station. With additional high resolution long-term speciated mercury measurements
becoming available through the GMOS project, during the next years the presented findings will be evaluated for further
observations in Europe and other regions.
Acknowledgement
This work was supported by European Commission under the FP7 project GMOS (Global Mercury Observation System).
References
Amos, H.M., Jacob, D.J., Holmes, C.D., Fisher, J.A., Wang, Q., Yantosca, R.M., Corbitt, E.S., Galarneau, E., Rutter, A.P., Gustion, M.S.,
Steffen, A., Schauer, J.J., Graydon, J.A., St. Louis, V.L., Talbot, R.W., Edgerton, E.S., Sunderland, E.M., (2011). Gas-particle
partitioning of atmospheric Hg(II) and its effect on global mercury deposition Atmos. Chem. Phys. Discuss., 11, 29441-29477.
UNEP (United Nations Environment Programme), (2013). Global Mercury Report, UNEP, Geneva, Switzerland, 2013.
Weigelt, A., Temme, C., Bieber, E., Schwerin, A., Schuetz, M., Ebinghaus, R., Kock, H.H., (2013). Measurements of atmospheric mercury
species at a German rural background site from 2009 to 2011 – methods and results. Environ. Chem., 10 (2) 102-110.
38
MODELLING BLACK CARBON CONCENTRATIONS IN TWO BUSY CANYON STREETS IN BRUSSELS
USING OSPMBC
O. Brasseur (1a), P. Declerck (1b), B. Heene (2) and P. Vanderstraeten (1a)
(1a) Dept. Telemetric Network & IRCEL-CELINE; Brussels Environment, Gulledelle 100, 1200 Brussels, Belgium;
(1b) Dept. Health, Chemistry Lab. & Indoor; Brussels Environment, Gulledelle 100, 1200 Brussels, Belgium;
(2) Earth & Life Institute, Université Catholique de Louvain, Place de l’Université 1, 1348 Louvain-la-Neuve, Belgium
Presenting author e-mail: brasseur@irceline.be
Summary
This study aimed to simulate Black Carbon (BC) concentrations in two selected canyon streets in Brussels. The Danish
Operational Street Pollution Model (OSPM) model, specifically adapted to BC and noted as OPSMBC, was used. OPSMBC
validations were performed using temporal data from the fixed measurement network in Brussels. The model simulated very
well the diurnal, daily (weekdays and weekends) and monthly evolutions of BC, meaning that it handles correctly the
variation of traffic emissions as well as the meteorological conditions. Considering the dispersion, it should be noted that BC
concentrations were better simulated under stable than under unstable conditions. OPSMBC appeared to accurately simulate
BC concentrations in canyon streets provided that accurate input data related to traffic are available.
Introduction
High BC concentrations can be found in urban environments where the topography and microclimate create poor air dispersal
conditions, resulting in pollutant hotspots. A well know example of this can be found in canyon streets where dilution of car
exhaust is significantly limited by the presence of buildings at both sides of the road. In this framework, the aim of this paper
was to model traffic related BC emissions in canyon streets. In order to do so, the Danish Operational Street Pollution Model
(Berkowicz, 2000) was specifically adapted to BC and validated for two busy canyon streets in Brussels.
Black Carbon concentration (µg/m³)
6
Observation
(a)
5
Simulation (OSPM-BC)
4
3
2
1
0
6
Black Carbon concentration (µg/m³)
Methodology and Results
OPSMBC was validated using half-hourly data from the stations
41R002 (Crown Street) and 41B008 (Belliard Street) of the fixed
measurement network in Brussels. Direct validations were
performed for the Crown street, while model calculations for the
Belliard street were validated indirectly using the linear
relationship between BC and NOx.
Concerning the Crown street, simulated and observed BC
concentrations correlated in an excellent way for the period from 1
July 2011 till 30 June 2013. In particular, OPSMBC performed very
well to simulate the diurnal and monthly evolutions of BC (Fig.1).
The daily variation between weekdays and weekends was also
very well reproduced. This means that the model correctly handled
the variation in traffic emissions as well as the meteorological
conditions. The correlation coefficient computed on the whole
time series of half-hourly concentrations was 0.74, and ranged
between 0.56 and 0.82, depending on the time of the day.
Considering the dispersion, it should however be noted that BC
emissions were better simulated under stable than under unstable
conditions. This can be explained by the background contribution
that is proportionally more important than local traffic under weak
dispersion conditions.
The same conclusions were obtained for the Belliard street, even if
the correlation on half-hourly NOx concentrations was slightly
less. This was due to an accuracy loss in using the relationship
between BC and NOx.
(b)
5
4
3
Observation (41R002)
Simulation (OSPM-BC)
2
1
0
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour (UT)
Fig.1 Comparison between simulated (dashed curve)
and observed (solid curve) BC concentrations at the
station of Ixelles (41R002) in Brussels. (a): monthlyaveraged data and (b): diurnal data. The period
considered: 1 July 2011- 30 June 2013.
Conclusions
Based on our results, we can state that OPSMBC is suitable to
accurately simulate BC concentrations in canyon streets of Brussels, under the following conditions: (i) accurate vehicle
counting data is available to correctly estimate traffic emissions, and (ii) vehicle speeds are measured in order to better take
into account the impact of the turbulence generated by vehicles on the local dispersion of BC.
Acknowledgement
This work was financed by the ExpAIR project (Assessment of the Individual Exposure of the Brussels Population to Urban
Air Pollution), financed by the Brussels Region.
References
Berkowicz R., 2000. OSPM - A parameterised street pollution model. Environmental Monitoring and Assessment, 65, 323331.
39
REGIONAL MODELLING OF THE TROPOSPHERIC MULTIPHASE SYSTEM USING COSMO-MUSCAT:
SENSITIVITY ON DETAIL OF CLOUD MICROPHYSICS AND CHEMICAL MECHANISM
R. Schrödner, A. Tilgner and R. Wolke
Institute for Tropospheric Research, Leipzig, 04318, Germany
Presenting author email: roland.schroedner@tropos.de
Summary
The 3D-chemistry transport model COSMO-MUSCAT consisting of MUSCAT (Wolke et al., 2004a) and the forecast model
of the German Weather Service (DWD) COSMO (Schättler et al., 2008) was extended to consider size-resolved cloudchemical processes (chemical aqueous phase reactions and phase transfer processes). With the advanced model system,
sensitivity-studies have been conducted for urban and remote cases and for different resolutions of the aerosol and cloud
droplet size distribution. Also, the complexity of the used aqueous phase chemical mechanism was varied. For analysis,
reaction fluxes were investigated.
Introduction
Clouds play a major role in the atmosphere due to their influence on the Earth’s radiative budget, on the hydrologic cycle and
on the tropospheric chemical composition. Cloud lifetime is driven by the dynamics of the atmosphere at the synoptic scale
and, in close interaction, by microphysical processes on the small scale.
These processes depend on the chemical composition of particles and cloud droplets. In addition, microphysical processes
redistribute chemicals among the various reservoirs: gaseous, particulate, liquid and ice phases. Clouds favor the
development of “multiphase chemistry” since they are an ideal reaction medium for this: (1) clouds support very efficient
photochemical processes inside droplets; (2) certain homogeneous chemical reactions within clouds can be usually faster than
the equivalent reactions in the gas phase, and reactions such as those involving ionic species, can be important; (3) finally,
interactions between the aqueous and solid phase can contribute additionally to chemical processes in clouds (for example
dissolution of soluble particulate species). The evaluation of multiphase chemistry versus overall tropospheric chemistry and
its role in the Earth’s radiative budget is challenging since microphysical and chemical processes occurring at different time
scales within clouds are still poorly known.
Methodology and Results
Based on the increasing kinetic and mechanistic
knowledge on chemical aqueous phase reactions in the last
two decades, advanced aqueous phase chemical
mechanisms such as the Chemical Aqueous Phase Radical
Mechanism (CAPRAM) are continuously developed
(Tilgner and Herrmann, 2010). CAPRAM is an almost
explicit mechanism which describes relevant chemical
aqueous-phase conversions of both inorganic and organic
compounds. A reduced version of the mechanism,
applicable for 3D chemistry transport models was created
(Deguillaume et al., 2009). This mechanism was compared
to a simple inorganic mechanism.
A simple size-resolved microphysical scheme was
introduced which shows the chemical partitioning in the
different droplet-bins.
Conclusions
Fig. 1: Height profile in x-direction of the simulated mass of S(VI)
The comparison of different chemical mechanisms have simulated with CAPRAM compared to the run with simple inorganic
revealed agreements but also interesting differences for chemistry. The cloud is located left of the mountain (red and yellow
important chemical subsystems e.g. in the modeled area). Species stream in from the left-hand side.
multiphase HOx budget and pH whereas more simple
mechanism (without organics) lead to less acidic cloud droplets than CAPRAM. Investigation of reaction fluxes show that
this is mostly due to organic acidification in CAPRAM. The difference in pH leads consequently to different regimes for e.g.
the S(IV)-oxidation and organic partitioning in the droplet bins.
Acknowledgement
This work was funded by the scholarship program of the German Federal Environmental Foundation (DBU). Furthermore,
we thank the JSC Jülich for providing computing time.
References
Deguillaume, L., et al. (2010), Journal of Atmospheric Chemistry, 64(1), 1-35.
Schättler, U., et al. (2008): A Description of the Nonhydrostatic Regional COSMO-Model Part VII: User's Guide.
Tilgner, A. and Herrmann, H. (2010) Atmospheric Environment, 44(40), 5415-5422
Wolke, R., et al. (2004a) Parallel computing: Software technology, algorithms, architectures and applications, 363-370
40
USE OF ARTIFICIAL NEURAL NETWORKS FOR PM10 RE-ANALYSIS OVER NORTHERN ITALY
C. Carnevale (1), G. Finzi (1), E. Pisoni (2), A. Pederzoli (1), E. Turrini (1), M. Volta (1)
(1) Department of Industrial and Mechanical Engineering (DIMI), University of Brescia, Via Branze 38, 25123 Brescia, Italy
(2) European Commission – Joint Research Centre (JRC), Via Fermi, 2749 - 21027 Ispra (VA) - Italy
Presenting author email: carneval@ing.unibs.it
Summary
Artificial Neural Networks (ANNs) are used to link PM10 concentration from a deterministic air quality model and precursor
scenario emissions to the PM10 concentration of a base case re-analyzed using PM10 surface observations. A case study over
Northern Italy is presented. The goal is to show that ANNs are capable to model the nonlinear relationship between precursor
emissions and PM10 re-analyzed concentrations, so they can be used for reducing the under-prediction of this pollutant by
deterministic air quality models in scenario simulations.
Introduction
A high number of studies highlight how current deterministic air quality models are not capable to simulate the spatial and
temporal distribution of PM10 surface concentration properly. In particular, most of air quality models tend to underestimate
PM10, especially during winter time. This underestimation makes difficult the use of these models to define efficient emission
control strategies on a certain area.
A possible way for correcting the underestimation in PM10 modelled concentration is the use of off-line data assimilation
techniques (i.e. optimal interpolation) which integrate model output and observations. Unfortunately, re-analysis techniques
can only be applied when PM10 concentration measures are available, thus they become unhelpful for the evaluation of
emission reduction impacts. In this work, the application of ANNs for linking emissions, deterministic simulation results
(PM10 surface concentrations) and re-analyzed PM10 concentrations over Northern Italy is investigated.
Methodology and Results
ANNs are identified by processing the long-term simulation (1-year) output of a 3D deterministic Chemical Transport Model
(TCAM) (Carnevale et al., 2008) on a set of emission reduction scenarios. This procedure is named Design of Experiments.
The model domain is a 128x82 cells grid at 5x5 km2 resolution over Northern Italy. 22 emission scenarios have been
considered (emissions values varying between the base case CLE 2010 and the Maximum Feasible Reduction scenario
MFR), for 6 precursors. Emissions are from the POMI inter-comparison exercise (http://aqm.jrc.ec.europa.eu/POMI/).
TCAM concentrations for the base case, re-analysed through optimal interpolation, are also used.
Several tests have been carried out by varying number of epochs and number of hidden neurons. The optimal configuration
(the one which minimize the Root Mean Square Error) is achieved with a number of neurons=20 and a number of training
epochs=300. On a yearly basis, the correlation between ANNs output (corrected PM10) and TCAM PM10 concentrations for
the validation dataset is 0.87. The Root Mean Square Error (rmse) is 0.041.
Conclusions
The present work aims to show that ANNs can potentially be used for describing the spatial distribution of PM10
concentration in scenario simulations, helping to reduce the underestimation of deterministic air quality models.
Acknowledgments
This study is carried out in the frame of the OPERA (Operational Procedure for Emission Reduction Assessment) LIFE+
project (www.operatool.eu).
References
C. Carnevale, Decanini, E., Volta, M. (2008) Design and validation of a multiphase 3D model to simulate tropospheric
pollution. Science of the Total Environment, vol. 390, p. 166‐176.
41
USING WRF-CHEM WITH HIGH RESOLUTION EMISSION DATA TO MODEL THE EFFECT OF URBAN
HEAT ISLAND MITIGATION STRATEGIES ON URBAN AIR QUALITY
J. Fallmann (1), S. Emeis (1), P. Suppan (1), R. Forkel (1), G. Grell (2), S. McKeen (2)
(1) Karlsruhe Institute of Technology (KIT) – Institute for Meteorology and Climate Research,
Kreuzeckbahnstr. 19, 82467 Garmisch-Partenkirchen
(2) NOAA Earth System Research Laboratory (ESRL), 325 Broadway, Boulder, CO 80305-3328, USA
Presenting author email: joachim.fallmann@kit.edu
Summary
In 2050 the global fraction of urban population will increase to over 69%, which means that around 6.3 billion people are
expected to live in urban areas. Cities are the predominant places for human beings to settle down, thus becoming more
vulnerable to extreme weather events aggravating phenomena like heat stress and decreasing air quality. Finding mitigation
strategies to counteract future air quality related problems and ways to sustain development is of great importance. In this
study, the mesoscale numerical model WRF-Chem is used on regional scale to investigate the effect and the potential of
urban planning strategies to mitigate air quality problems caused by the Urban Heat Island (UHI).
Introduction
UHI describes the tendency for an urbanized area, because of its radiative and geometrical features, to remain warmer than its
rural surroundings and thus generating its own microclimate (Oke 1982). Additional heat generated by fuel combustion, air
conditioning or other human activities as well as roughness effects caused by building structures, help to ‘design’ specific
atmospheric dynamics resulting in modified urban rural circulation patterns (Arnfield 2003). UHI’s raise demands of energy
for air conditioning during summer periods and with power plants relying on fossil fuels, air pollutants and greenhouse gas
emissions are increasing. Primary pollutants include SO2, NOx, PM or CO, which contribute to complex air quality problems
such as ground level ozone (SMOG), fine PM or acid rain.
Methodology and Results
Tab.1 Urban Heat Island Intensity expressed as difference between
Time period August 11-08 2003 is used for the modelling.
average 2m temperature of urban area (Aug 13th 2003 6pm UTC)
To account for 3 dimensional structures in WRF, different
Scenario
Albedo
Density Many
Big
Real
urban parameterization schemes are coupled to a land surface
Parks
Park
Case
model (Noah LSM) and results compared with observation
Ɵ urban [°C]
31.5
32.4
32.5
32.3
33.1
data. A sensitivity study reveals the highest R^2 = 0.72 (2m
Ɵ
max
[°C]
31.9
33
33.5
33.3
34.3
Tpot) for the multi-layer BEP approach, in turn used for
Std dev. [°C]
0.32
0.48
0.5
0.43
0.6
further proceedings. By changing the land use
UHI; delta Ɵ
0.84
1.32
1.47
1.19
2.52
characteristics, different scenario runs can be executed
implying certain mitigation strategies. 4 case studies are presented: increasing of the albedo
(Albedo; 0.7), decreasing of building density (Density; 20%) and replacing of urban land use
by natural vegetation (Big Park/ Many Parks). Each scenario has an impact on UHI intensity,
thus affecting the local surface- atmosphere exchange processes, as well as air quality. The
albedo case offers the greatest potential with a decrease of urban-rural temperature difference
of 1.7 °C (Tab. 1). Same scenario runs are executed with WRF-Chem, using 7km resolution
emission inventory as chemical input data for a 3km resolution WRF-simulation. Correlation
of modelling data (O3) with average of 5 observations for the time period reveal an R2= 0.72.
Figure 1 shows a snapshot for difference of O3 concentration between the urban base case
(BEP) and the scenario case ‘Big Park’, for Aug 13 2003, 6pm. The decrease of urban surface
ozone of up to 8 ppb accounts for approx. 10% reduction (82.9 ppb O3).
Conclusions
The results of the study reveal, that certain urban planning strategies are able to mitigate to
negative effects coming along with urban heat island formation, both in cases of temperature
and urban air quality. For further investigations, improving the modeling results by using 1km
emission data is scheduled.
Fig 1:Difference of O3 between
Base Case and ‘Big Park’
scenario for Aug 13 2003, 6pm
Acknowledgement
This work is funded by the EU- Project “UHI - Development and application of mitigation and adaptation strategies and
measures for counteracting the global UHI phenomenon” (3CE292P3) – CENTRAL Europe. (2011-2014).
References
Arnfield, A.J., 2003: Two Decades of urban climate research: a review of turbulence, exchanges of energy and water, and the
urban heat island. Int. J. Climatol., 23, 1-26.
Oke, T. R., 1982: The energetic basis of the urban heat island. - John Wiley & Sons, Ltd; Quarterly Journal of the Royal
Meteorological Society 108 (455): 1-24
42
PM AIR QUALITY ASSESSMENT IN PMINTER – BRIDGING THE GAPS – A NEW INTEGRAL APPROACH
U. Uhrner (1), R. Reifeltshammer (1), M. Steiner (1), B. Lackner (1), P. J. Sturm(1) and R. Forkel (2)
(1) Institute for Internal Combustion Engines and Thermodynamics, Graz University of Technology, 8010 Graz Austria, (2)
Karlsruher Institut für Technologie, Atmosphärische Umweltforschung (IMK-IFU) 82467 Garmisch-Partenkirchen, Germany
Presenting author email: uhrner@ivt.tugraz.at
Summary
This study aims to obtain a better quantified understanding of PM concentration levels in the program area comprising Styria,
Carinthia and Slovenia during winter time. To resolve valley and basins located sources, emissions were computed or
processed within PMinter on 1 km x 1 km resolution for the program area. A new combined model approach was developed
and tested successfully using a sophisticated CTM WRF-Chem (Grell et al., 2005) on the regional scale and a Lagrangian
particle model GRAL (Öttl et al., 2003) on the local scale. A detailed analysis and comparisons with measurements and
regional/local scale scenario simulations were carried out in order to design integral air quality management plans (AQMP).
Introduction
Many areas located in southern alpine valleys and basins face unusual high particulate burden in particular during winter
time. Due to the complex terrain and related complicated atmospheric processes air quality and exposure assessment is a
difficult task. Although municipalities like Leibnitz (SE-Austria, pop. 8000), Maribor (NE-Slovenia pop. 95000) and
Klagenfurt (S-Austria, pop. 90 000) have quite low population and no big industries, the national and EU air quality
standards have been frequently and significantly exceeded within the last years at winter time. Using wood for residential
heating is very popular in Austria and in Slovenia. To assess the contribution from wood smoke to the total PM burden and
the impact of regional and large scale transport as well as the impact of secondary aerosols are major goals of PMinter.
Methodology and Results
In order to represent processes on various scales a combined modelling approach was utilized, using WRF-Chem, and the
GRAMM/GRAL system for local/micro scale flow and dispersion. A multi nesting technique starting from Europe and at the
end two small well resolved domains (1 km) representing the program area was utilized. These two smaller domains (approx.
100 km x 100 km each) comprise the three micro scale core investigation areas Klagenfurt, Maribor and Leibnitz (12 km x 8
km domain size). An important aspect of the modelling work was the pre-processing of base data and processing of the
emission data; which involved distinguishing between sources and different scales represented by those two model systems,
to account for various scales and to avoid double consideration of emissions.
A good agreement was obtained for simulated total PM10 compared with measurements (see Fig. 1) located in the core
domains. Comparisons with filter analysis and aethalometer measurements sampled at 6 sites indicate that the modelled
PM10 composition is quite realistic. A comparison with a second base run where all emissions were set to “0” in the three
micro scale core domains revealed that inorganic secondary aerosol is formed mainly outside the core domains and advected
into these three core domains (see Fig. 2). In contrast, carbonaceous PM10 (EC/OC/SOAs) is dominated by wood smoke
from residential heating mainly emitted and distributed within the three core domains (see Fig. 2). Various scenarios were
computed. A “local” scenario which may reduce significantly individual heating facilities using solid fuels by district heating
and a regional scenario which may reduce ammonia emissions from agriculture by 35% proved to be most effective.
Fig.1 Simulated PM10 January means for 2010 vs.
monitored values, * indicates differing periods
indicated by *
Fig.2 Mean Jan. PM10 contributions from outside
(regional) and inside (local) micro scale core
domains.
Conclusions
The integral air quality assessment which comprised the creation of a PMinter emission data base and the combination of two
model systems enabled the replacement of an “unspecified PM background” level in micro scale simulations, a better
specification of PM components and therefore a more specified health and environmental assessment. Moreover, the chosen
approach enables an evaluation of measures on regional and local scale level. As a consequence measures affecting emissions
from wood burning may prove successful on a local level, measures affecting precursor emissions from inorganic secondary
formed PM should be implemented on a regional level. Residential heating using wood was identified as the major source
and PM component dominant on the “local scale” (~10 km), secondary inorganic aerosol was the dominant PM component
on the regional scale (~ 10 km – 150 km) and above.
Acknowledgement
This work was supported by the EU interregional SI-AT-2-2-047 programme and the provincial government of Styria
43
CAN A SIMPLE INTERPOLATION MODEL PERFORM BETTER FOR AIR QUALITY ASSESSMENT THAN
DATA ASSIMILATED DETERMINISTIC MODELS?
S. Janssen (1), B. Maiheu (1), N. Veldeman (1), P. Viaene (1), K. De Ridder (1), D. Lauwaet (1), F. Deutsch (1), F. Fierens
(2), E. Trimpeneers (2), L. Vancraeynest (3) and C. Mensink (1)
(1) VITO, Boeretang 200, 2400 Mol, Belgium; (2) Belgian Interregional Environment Agency (IRCEL),
Kunstlaan 10-11, 1000 Brussel, Belgium; (3) Flemish Environment Agency, A. Van de Maelestraat 96, 9320
Aalst, Belgium
Presenting author email: stijn.janssen@vito.be
Summary
Various regional scale air quality modeling techniques are evaluated. Three different models (an interpolation tool, a Eulerian
and a Lagrangian model) with supporting data assimilation techniques were applied to produce concentration maps for PM10,
PM2.5, NO2 and O3 over Belgium. The model intercomparison study pointed out that overall the simple interpolation
technique produces most reliable results, both for the temporal as for the spatial validation.
Introduction
Detailed and reliable regional scale concentration maps are important in the framework of environmental assessment studies,
preparing action plans and documents supporting EU infringement procedures, as well as a basis for negotiations with
stakeholders such as federations, (industrial) sectors and local authorities. For national or regional environment authorities, it
is therefore important to have the best possible set of air quality maps available. Within this study, the various options to
produce such a set of maps were identified and evaluated.
Methodology and Results
We studied and compared different operational modeling techniques that are used to generate maps for PM10, PM2.5, NO2 and
O3 concentrations over Belgium. The different techniques include (i) an intelligent interpolation technique for air pollutant
observations based on land use characteristics (RIO model, Janssen et al., 2008); (ii) a deterministic Eulerian modeling
approach (AURORA model, Van de Vel et al., 2010) taking into account four different data assimilation techniques (simple
classical bias correction, simple bias correction according to orthogonal regression, data assimilation based on ‘Kalman
Filtering’ and ‘Optimal Interpolation’); and (iii) a Lagrangian model calibrated for NO2 and PM10 (VLOPS model, based on
van Jaarsveld, 2004).
The various techniques and resulting maps were analysed, validated and compared aiming at identifying the best possible
regional scale concentration map for each pollutant. Where measurement data was employed for interpolation, assimilation or
bias correction, the validation was based on the ‘leaving-one-out’ technique. Both temporal as well as spatial aspects of the
model performance were evaluated.
The temporal analysis revealed that the RIO model in general performs best in capturing the temporal variability of air
quality in Belgium for the investigated pollutants. The uncorrected, deterministic AURORA model scores the least. The
AURORA model with different data assimilation techniques yields, not surprisingly, significantly better results than the
uncorrected AURORA model, but not better than the RIO model. With the Lagrangian approach no time series can be
generated due to technical model restrictions.
From the spatial analysis it became clear that distinction between the considered pollutants should be made. For PM10 and
PM2.5 the RIO model performs best in generating the spatial pattern of the observed annually averaged concentrations. The
deterministic models AURORA and VLOPS remain far behind, even when corrected with different data assimilation
techniques. The AURORA model corrected with ‘Optimal Interpolation’ performs best in reproducing the spatial pattern of
O3. For NO2 the RIO model manages best in explaining the spatial variability of the observed annually averaged
concentrations in Belgium, but when restricted to the region of Flanders, both RIO and VLOPS are competitive.
Conclusions
Overall, the rather simple spatial interpolation model RIO was identified as the most suitable tool to produce historic regional
scale air quality assessment maps for Belgium. Despite the fact that the output of Eulerian and Lagrangian models
significantly improved after the data assimilation procedure, they were not able to surpass the quality of the interpolation
scheme.
References
Janssen, S., Dumont, G., Fierens, F., Mensink, C., 2008. Spatial interpolation of air pollution measurements using CORINE
land cover data, Atmospheric Environment., 42, 4884-4903.
Van de Vel, K., Mensink, C., De Ridder, K., Deutsch, F., Maes, J., Vliegen, J., Aloyan, A., Yermakov, A., Arytyunyan, V.,
Khodzher, T. and Mijling, B., 2010. Air quality modelling in the Lake Baikal region, Environmental Monitoring and
Assessment, 165, 665-674.
van Jaarsveld, J., 2004. Description and validation of OPS-Pro 4.1, 2004, RIVM report 500045001.
44
EMISSION MODELS /
INVENTORIES
45
REAL-WORLD VERSUS COMPLIANCE SOURCE TESTING: GETTING MORE INFORMATION FOR LESS
MONEY
J. G. Watson (1), J. C. Chow (1)
(1) Desert Research Institute, Nevada System of Higher Education, Reno, Nevada USA 89512
Presenting author email: john.watson@dri.edu
Summary
Compliance testing of source emissions too often follows the U.S. EPA’s single pollutant measurement methods. These were
developed in the 1950s and have been written into U.S. Law. The new International Standards Organization (ISO, 2013)
procedure for dilution source sampling offers more flexibility for countries that are not bound by the U.S. Code of
Regulations (U.S.EPA, 2013a; 2013b).
Introduction
Real-world emission rates from sources that affect ambient air quality are needed to drive air quality models and to provide
accountability for air quality management strategies. Chemical source profiles for particulate matter and volatile organic
compounds are needed for source and receptor modeling. Since the early 1960s, source characterization methods have been
established that quantify emission rates to certify sources and determine their compliance over time. Unfortunately, these
certification and compliance methods have not adapted to changes in emissions processes and controls nor have they
incorporated advances in measurement technology. This results in source tests that are incompatible with each other and
with ambient measurement methods. Source characterization methods need to be improved to better represent real-world
hardware, operating conditions, and feedstocks and to obtain more information at lower costs.
Methodology and Results
Since the early 1960s stack flows have been removed through a
buttonhook nozzle, drawn through a filter, and bubbled through gas
absorbing solutions contained in cooled glass impingers. For PM, the
sample is drawn isokinetically through a filter maintained at stack
temperature, then through distilled water to collect condensible vapors.
When in-stack PM levels were high, the impinger catch was a small
fraction of that on the filter at the in-stack temperature. After PM
controls however, the impinger catch dominates the front filter, and most
of it is from dissolved SO2 and VOCs rather than condensible particles.
No one would design a method today in which the stack is scaled again
and again (once for each pollutant) with glass instruments, ice buckets,
and easily-contaminated chemicals. A more reasonable approach is to
extract a portion of the stack gases into a chamber where it can be
diluted (Figure 1) with filtered air to near ambient temperatures, then
draw air from this chamber through substrates and sensors comparable to
those used at ambient air monitoring stations.
Engine certification tests operate the engine through different cycles,
dilute the exhaust to ~50 °C, draw air through CO, NO/NO2, and NMHC
monitors, and sample PM onto filters. Smaller engines are tested within
the vehicle on a chassis dynamometer while larger engines are tested
outside the vehicle on an engine dynamometer. This is an improvement
Fig.1 Example of a dilution sampling system for
over the stack methods, but the cycles do not represent those of the realstationary source emission characterization.
world. Current microsensor technology allows for portable emission
systems that can be mounted on vehicles to obtain a much larger number of tests during real-world operations. Cross-plume
and in-plume sensors can be located on roadways to determine emission distributions. These real-world tests have shown
that ~20% of the on-road engines are responsible for ~80% of the emissions in a given airshed. The high-emitters are not
detected by laboratory certification or compliance tests.
Conclusions
The new ISO procedure No. 25597:2013 offers substantial flexibility as a better way to obtain multipollutant measurements
from stationary sources. The method can be extrapolated to better accommodate measurements from mobile sources with a
smaller on-board dilution system. Governments that are not bound by U.S. laws should not copy the U.S. EPA’s old
methods; they should be attempting to assess real-world emissions that affect public health and have other adverse
environmental effects.
References
ISO (2013). ISO 25597:2013: Stationary source emissions -- Test method for determining PM2,5 and PM10 mass in stack
gases using cyclone samplers and sample dilution. prepared by International Organization for Standardization, Geneva,
Switzerland, http://www.iso.org/iso/home/store/catalogue_tc/catalogue_detail.htm?csnumber=43029.
U.S.EPA (2013a). Title 40, Part 60-Standards of performance for new stationary sources. Code of Federal Regulations,
http://www.ecfr.gov/cgi-bin/retrieveECFR?gp=&SID=58ca7d63cbd732624780bdb648af1159&r=PART&n=40y7.0.1.1.1.
U.S.EPA (2013b). Title 40, Part 63-National emission standards for hazardous air pollutants for source categories. Code of
Federal Regulations, http://www.ecfr.gov/cgibin/retrieveECFR?gp=&SID=58ca7d63cbd732624780bdb648af1159&r=PART&n=40y10.0.1.1.1.
46
A COMPREHENSIVE INVENTORY OF EMISSIONS FROM SHIP TRAFFIC IN EUROPE IN 2011
J.-P. Jalkanen, L. Johansson and J. Kukkonen
Air Quality, Finnish Meteorological Institute, P.O. Box 503, FI-00101 Helsinki, Finland
Presenting author email: jukka-pekka.jalkanen@fmi.fi
Summary
This study presents a comprehensive, high-resolution inventory of the exhaust emissions of shipping and their geographical
distribution in European sea areas in 2011. The ship activity data was obtained from the vessel navigation system called the
Automatic Identification System (AIS); it is based on actual vessel movements recorded by the maritime authorities of the
EU member states. Shipping emissions on a European scale have not previously been evaluated using an AIS-based system.
This European inventory has been constructed on an unprecedentedly fine spatial resolution. According to our results for
2011, previous ship emission inventories (e.g., EMEP) would have substantially overestimated both the emissions of NOx
from ships in the Mediterranean Sea and the North Sea Emission Control Area (ECA). The emissions of SOx and PM were
substantially high in the Mediterranean Sea, compared with other sea regions in Europe. This has been caused by the use of
higher sulphur content fuels in the Mediaterranean, compared with the European ECA’s, such as the North Sea and the Baltic
Sea.
Introduction
We have compiled a high-resolution, European-wide ship emission inventory for 2011. This inventory is based on the vessel
activity information, recorded by the AIS. This information was collected by the EU member states and archived at the
European Maritime Safety Agency (EMSA). The AIS device typically reports vessel identification, its location and speed for
several times a minute; the use of this system is mandatory for all ships heavier than 300 GT. The use of this data for ship
emission modelling offers a unique possibility to construct emission inventories, which fully reflect the temporal and spatial
variations of ship traffic.
Methodology and Results
Ship Traffic Emission Assessment Model (STEAM, Jalkanen et al 2009;
2012) was used to generate this inventory. The results were computed on an
emission grid with a resolution of ~ 3.5 km by 4 km for annual totals. The
CO2 emissions from (i) the Baltic Sea, (ii) North Sea and the English
Channel, and (iii) the Mediterranean Sea were 14%, 25% and 36%,
respectively, of the European annual total emissions of 131 million tons.
The corresponding shares were 9%, 17% and 45%, respectively, for annual
PM2.5 emissions.
According to the computed results, the ship emissions in the Mediterranean
Sea have previously been substantially overestimated, by approximately
40%. This issue has also been recently reported based on satellite
observations of NOx (Vinken et al., 2013).
Conclusions
The use of the STEAM modelling system that uses AIS-based information
in the construction of emission inventories for shipping has removed
significant uncertainties, especially regarding the vessel activities and times
spent at sea. Sulphur reduction from the marine fuels in the European
ECA’s has had a substantial positive influence on the emissions of SOx
and PM. The shipping in the Mediterranean Sea was responsible for 45
% and 36 % of the total European shipping emissions of PM2.5 and CO2.
Fig.1 The spatial distribution of predicted PM2.5
emissions from shipping in 2011.
Acknowledgement
The research leading to these results has received funding from the European Union’s Seventh Framework Programme
FP/2007-2011 within the project TRANSPHORM, grant agreement no 243406. Support from the European Space Agency
and the SAMBA project is gratefully acknowledged.
References
Jalkanen, J.-P. Brink A., Kalli J., Pettersson H., Kukkonen J. and Stipa T.,2009. A modelling system for the exhaust
emissions of marine traffic and its application in the Baltic Sea area. Atmos. Chem. Phys. 9 9209-9223.
Jalkanen J.-P., Johansson L., Brink A., Kalli J., Kukkonen J. and Stipa T., 2012. Extension of an assessment model of ship
traffic exhaust emissions for particulate matter and carbon monoxide, Atmos. Chem. Phys., 12, 2641-2659.
Vinken G. C. M., Boersma K. F., van Donkelaar A. and Zhang L., 2013. Constraints on ship NOx emissions in Europe using
GEOS-Chem and OMI satellite NO2 observations, Atmos. Chem. Phys. Discuss., 13 19351-19388.
47
A MODEL FOR FEEDBACKS BETWEEN BIOGENIC EMISSIONS AND URBAN AIR QUALITY
R. Grote (2), G. Churkina (1), T. Butler (1), C. Morfopoulos (3)
(1) Institute for Advanced Sustainability Studies, Potsdam, Germany (2) Institute of Meteorology and Climate Research,
Karlsruhe Institute for Technology, Garmisch-Partenkirchen, Germany (3) Kings College, London
Presenting author email: galina.churkina@iass-potsdam.de
Summary
Cities are characterized by elevated air temperatures as well as high anthropogenic emissions of air pollutants. Many cities
have started urban greening programs in order to mitigate urban heat island effects and increasing pollutant deposition.
However, high emissions of biogenic volatile organic compounds (BVOC) from certain popular urban plants in combination
with the elevated concentrations of NOx have the potential to increase ground-level ozone concentrations. To appropriately
consider this effect in models requires a high spatial and temporal resolution as well as a high degree of mechanistic
representation, because the influence of BVOC on air quality is not just one-way; poor air quality impacts physiological
performance or vegetation and thus also BVOC emission. In order to estimate the magnitude of possible feedbacks under a
range of conditions, a new mechanistic BVOC model has been implemented into a regional air chemistry model. The
approach is described and first results are presented.
Introduction
Greening of cities in the form of urban parks, street trees, and vegetation on roofs and walls of buildings is intended to
generally mitigate negative impacts on human health and well-being. However, some of the tree species used are high
emitters of isoprene and monoterpenes. In combination with high concentrations of NOx these emissions have the potential to
increase ground-level ozone concentrations - with negative impacts on health, agriculture, and climate. Policies targeting
reduction of ozone in urban and suburban areas therefore must consider limiting BVOC emissions along with measures for
decreasing NOx and VOC from anthropogenic sources.
Emissions are driven by multiple environmental influences. Current models of urban climate and air quality 1) do not account
for the feedback between ozone concentrations, productivity, and BVOC emission and 2) do not distinguish different
physiological properties of urban tree species. Instead environmental factors such as light, temperature, carbon dioxide, and
water supply are applied disregarding interactions between such influences. Thus we may not yet be able to represent the
impacts of air pollution under multiple changed conditions such as climate change, altered anthropogenic emission patterns,
and new urban structures. For this, we applied a new integrated climate/ chemistry model which considers the speciesspecific physiological responses of urban plants that in turn drive their emission behavior.
Methodology and Results
We present here the implementation of a new BVOC
emission model (Morfopolous et al., in press) that derives
BVOC emissions directly from the electron production
potential and consumption from photosynthesis calculation
that is already supplied by the CLM land surface model.
The new approach has the advantage that many
environmental drivers of BVOC emissions are implicitly
considered in the description of plant photosynthesis and
phenology.
We investigate the tradeoff between vegetation driven
ozone -reduction and -formation processes in dependence
on temperature, radiation, CO2 and O3 concentrations. We
have parameterized suitable plant functional types for
different urban greening structures, currently focusing on
central European vegetation. The modified CLM model is
applied in a regional climate/ air quality model (WRFChem) to calculate realistic ozone concentrations in the
influence zones of urban conglomerations. BVOC
emissions and their impacts are also calculated with the
standard MEGAN2.1 approach for comparison.
Fig.1 Sensitivity of isoprene emission on temperature
with species-specific photosynthesis parameteriszation
(EUGL = eucalypt, LIST = yellow poplar, POTR =
poplar)
The simulation results are analyzed and discussed in view of the model’s suitability for air quality scenario estimates under
simultaneously changing climate, anthropogenic emissions and plant species composition.
References
Morfopoulos, C., Prentice, I.C., Keenan T.F., Friedlingstein, P., Medlyn, B., Penuelas, J., Possel, M. (in press): A unifying
conceptual model for the environmental responses of isoprene emission by plants. Annals of Botany, DOI:
10.1093/aob/mct206
48
PREPARATION OF MODELLING EMISSIONS BASED ON RECENT RECOMMENDATIONS FROM UK
NATIONAL ATMOSPHERERIC EMISSIONS INVENTORY STUDIES.
A. Fraser (1), S. Beevers (2), X. Francis (3), N. Kitwiroon (2), T. P. Murrells (1), R. A. Rose (1), R. S. Sokhi (3)
(1) Ricardo-AEA, Fermi Avenue, Harwell IBC, Oxon, OX11 0QR, UK; (2) Environmental Research Group, King's College
London , Franklin-Wilkins Building, 150 Stamford Street, London, SE1 9NH, UK ; (3) Centre for Atmospheric and
Instrumentation Research (CAIR), University of Hertfordshire, Hatfield, Hertfordshire, AL10 9AB, UK
Presenting author email: Andrea.Fraser@Ricardo-AEA.com
Summary
Emissions are collated for regulatory reporting for international and European regulations. These annual data sets, maps and
projections are used as the base to create the hourly emissions required by air pollution models such as CMAQ (Community
Multiscalar Air Quality). During the UK Department for Environment, Food and Rural Affairs (Defra) model
intercomparison exercise a number of questions were raised related to the consistency in emissions data used by the different
participating groups. This resulted in a series of short studies by the UK National Atmospheric Emissions Inventory (NAEI)
programme aimed at providing a core set of additional information for use with existing UK and European emissions
inventory information for the purpose of air pollution modelling. The areas included: temporal profiles for different source
sectors, recommended methodologies for estimating biogenic emissions, gridded UK and European emissions data for s
defined year based on the most up-to-date methodologies, information on point sources and scaling factors for UK and
European sources to derive emission estimates for other years on a consistent basis.
This study looks at the effect of applying these
recommendations to the preparation of emissions for
CMAQ.
Methodology
This work brings together the emission datasets
required to create model-ready emissions. This
project incorporates the inclusion of new datasets
being developed as part of the (NAEI) programme
where the focus is on developing a range of
supplementary data for the air pollution modelling
community.
For example this includes:
recommendations on temporal profiles (including
ammonia), biogenic VOC emissions, point source
emissions. UK emissions are based on the NAEI
maps and European emissions on the TNO-MACC II
emissions (Pouliot, 2012).
Fig. 1 – Hourly temporal profiles for road transport in the UK.
The NAEI studies have made a series of recommendations an example of these are the recommendations for road transport
temporal profiles as shown in Figure 1. The NAEI study recommended using separate profiles for Monday-Thursday, Friday
and the Saturday-Sunday reflecting the traffic patterns. Previously the same profile had been used for every day of the week.
The effect of this and other changes will be evaluated using CMAQ.
The assumptions made through the emission preparation process were reviewed taking into account the NAEI studies, and
feedback from other modelling groups. The full range of recommendations will be applied to a CMAQ simulation for 2006,
evaluating the sensitivity of air quality pollutants to these changes. The information will eventually be made available to the
wider air pollution modelling community.
Acknowledgement
This work was supported by UK Department for Environment, Food and Rural Affairs including the contributors to the
individual NAEI studies. TNO-MACC European emissions were made available from TNO. The recommendations on
biogenic emissions were provided by Professor Nick Hewitt and Emily House at the University of Lancaster.
References
Pouliot, G., Pierce, T, Denier van der Gon, H., Schaap, M., Nopmongcol, U., 2012. Comparing Emissions Inventories and
Model-Ready Emissions Datasets between Europe and North America for the AQMEII Project. Atmospheric Environment
(AQMEII issue) 53, 4–14.
49
OPEN CHALLENGES IN LOCAL ATMOSPHERIC EMISSION INVENTORIES
E. Angelino, A. Marongiu, G. Fossati, M. Moretti
Environmental Protection Agency of Lombardia Region, ARPA, 20124 Milano, Italy
Presenting author email: e.angelino@arpalombardia.it
Summary
The main goal of this paper is the description of the framework of activities for the compilation of the local emission
inventory of Lombardy region. The overview on the activities in the updating of IN.EM.AR database (INventario
EMmissioni Aria, www.inemar.eu) aims focusing methodology and current challenges in local emission inventory according
to Lombardy experience. The mentioned implemented system was set up in 1998 and is managed since 2002 by Regional
Environmental Protection Agency of Lombardy (ARPA). It is able to provide emission estimates deriving from a
combination of more than 250 activities and 35 fuels for pollutants of main interest for air quality (SO2, NOx, NMVOC, CO,
NH3, PM2.5, PM10, TSP) and greenhouse gases (CO2, CH4, N2O and F-gases) at municipality level. Emission inventories for
Lombardy have been developed using INEMAR for several years (1997, 2001, 2003, 2005, 2007, 2008 and 2010) (ARPA
Lombardia, 2012). Estimates on micro-pollutants like heavy metals and PAHs are also regularly updated.
Introduction
The estimation of the emissions passes through specific algorithms and
methodologies according to the EMEP/EEA Atmospheric Emission
Inventory Guidebook (EEA, 2013). The estimation is based on the
collection of a huge number of information like activities indicators (i.e.
fuel consumptions, traffic flows, industrial productions), emission factors
and statistical data for the spatial and time-based distribution of the
emissions. The periodic updating of the above-mentioned parameters and
their level of details (defined as Tier) affects the overall level of uncertainty
in emission calculations.
Figure 1. Framework of activities in
Lombardy regional emission inventory
Framework in development of local emission inventory and challenges
The system and methodologies implemented by ARPA Lombardy have been shared with other Italian regions increasing
harmonisation in methods and estimates among regional local emission inventories (ARPA, 2012). This latter aim determines
an increase in complexity managing local peculiarities. As a matter of facts,
the implemented framework seems effective answering to different users’
request with a proper codification of standard algorithms and parameters. The
implementation of an edition of the regional emission inventory passes by the
collection of several data as input. As reported in figure 1, different tools have
been developed in order to: insert emission data with the correct codification,
manage input and metafiles in emission inventory and share the methodology
with other partners in an open and common space such as Wiki pages. The
Figure 2. Uncertainty level estimation in
highest Tier algorithms have been implemented according to different modules
emission inventory development.
and welded to the database core and the publication policy according to a
public review system that have been successfully used. The implemented system is able to identify the uncertainty level of
the estimates as a combination of uncertainties of input data, algorithm level of implementation and emission factors. As
implemented in different emission inventory editions (Marongiu, 2012) uncertainty level can be defined considering a factor
varying between 10,5 and 2 (from low to high accurate estimates), determining the amplitude of uncertainties. In IN.EM.AR
highest accuracy is performed defining point emission sources when data of concentration are available at stack exit (eg.
large industrial plants). With a progressive increasing of uncertainties different algorithms are defined, obtained by the
highest tier of AIEG, where the number of parameters can drastically increase (eg. traffic transport). When detailed data are
not available or an emission source is characterised by a spread distribution in the territory (eg. domestic heating), a statistical
approach is used defining average indicators and emission factors.
Conclusions
Regional emission inventory for Lombardy region is regularly updated considering activity data and new methodology
improvements and has been assumed as a reference indicator in regional policy development (PRIA, 2013). The
implementation of the system is shared with other local inventory improvements, allowing the development of common
accepted methodologies and preserving local peculiarities. The methodology is defined in order to obtain the deepest level of
estimation minimizing the uncertainty level. Classification of new and diffuse technologies (e.g. small cogeneration plants)
and uncertainties in determination of indicators (e.g wood consumption in domestic heating) and relative fast updating in
algorithm and emission factor are the current challenges for the emission inventory developments.
References
ARPA Lombardia (2012). INEMAR Inventario delle emissioni in Lombardia, www.inemar.eu/.
EEA (2013). EMEP/EEA Air Pollutant Emission Inventory Guidebook 2013.
A.Marongiu, S. Caserini, M. Moretti, F. Antognazza, A. Giudici, E. Angelino, (2012) IA Ingegneria Ambientale v. XLI n. 5
PRIA (2012) – Piano Regionale degli Interventi per la qualità dell’Aria
50
THE SHIPPING EMISSIONS AND THE COSTS OF EMISSION REGULATIONS IN THE NORTHERN
EUROPEAN EMISSION CONTROL AREA
L. O. Johansson (1), J.-P. Jalkanen (1), J. Kalli (2) and J. Kukkonen (1)
(1) Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland.
(2) University of Turku, Centre for Maritime Studies, P. O. Box 181, 28101 Pori, Finland.
Presenting author email: lasse.johansson@fmi.fi
Summary
The exhaust emissions from shipping in the northern European emission control area (ECA) were evaluated using the Ship
Traffic Emission Assessment Model (STEAM). The emission limitations from 2009 to 2011 have had a significant impact on
reducing the emissions of both SOx and PM2.5 (Johansson et al., 2013). The predicted emissions of SOx originated from IMOregistered marine traffic have been reduced by 33 %, from 322 ktons to 217 ktons, in the ECA from 2009 to 2011. The
corresponding predicted reduction of PM2.5 emissions was 20 %, from 74 ktons to 59 ktons. The highest CO2 and PM2.5
emissions in 2011 were located in the vicinity of the coast of the Netherlands, in the English Channel, near the South-Eastern
UK and along the busiest shipping lines in the Danish Straits and the Baltic Sea. Based on simulations with 2011 data, there
will be a reduction of 85% in SOx emissions and a reduction of 50% in PM2.5 emissions in 2015, compared with the
corresponding shipping emissions in 2011 in the ECA. The corresponding relative increase in fuel costs for all shipping
varied between 10% and 63%, depending on the development of the prices of fuels and the use of the sulphur scrubber
equipment.
Introduction
It has been estimated in the recent literature that the upcoming
Marpol Annex VI agreement will be costly for the shipping
industry. However, the estimates of these costs have up to date
taken into account neither (i) the increases of fuel costs for
individual ships or ship categories nor (ii) spatially and
temporally accurate activity data of ships.
Methodology and Results
The emissions presented in this paper were evaluated using the
STEAM model (Jalkanen et al., 2012). This modelling approach
uses as input values the position reports generated by the
Automatic Identification System (AIS). The model requires as
input also the detailed technical specifications of all fuel
consuming systems onboard and other relevant technical details
of the ships for all the ships considered. Such technical
specifications were collected for over 50000 ships from various sources of information.
Fig.1 The spatial distribution of predicted PM2.5 emissions
Conclusions
from shipping in 2011.
The predicted SOx emissions originated from IMO-registered
marine traffic have been reduced by 33 % in the ECA from 2009 to 2011. The corresponding predicted reduction for PM2.5
was 20%. The emission limitations from 2009 to 2011 have obviously had a significant impact on reducing the emissions of
both SOx and PM2.5. A number of scenario computations simulating the past and forthcoming fuel sulphur regulations
(between 2005 and 2015) were also performed. The simulations showed that significant SOx and PM2.5 emissions reductions
are to be expected in 2015, while the direct fuel costs were estimated to increase by 10% to 63%
Acknowledgement
This work was supported the Finnish Transport Safety Agency (TraFi), the member states of the Marine Environment
Protection Committee of the Baltic Sea (Helcom). Funding for the research was received from Seventh Framework
Programme FP/2010-2013 within the TRANSPHORM project, and in co-operation with the BSR InnoShip project (project
no #051 in the Grant Contract).
References
Johansson, L.O., Jalkanen, J-P., Kalli, J. and Kukkonen, K. The evolution of shipping emissions and the costs of recent and
forthcoming emission regulations in the northern European emission control area. Atmos. Chem. Phys., accepted. 2013
Jalkanen, J-P., Johansson, L.O., Kukkonen, K., Brink, A., Kalli, J. and Stipa, T.: Extension of an assessment model of ship
traffic exhaust emissions for particulate matter and carbon monoxide, Atmos. Chem. Phys., 12, 2641–2659, 2012.
51
ENVIRONMENTAL AND
HEALTH IMPACT
RESULTING FROM AIR
POLLUTION
52
AN INTEGRATED BAP (PAHS) APPROACH TO ESTIMATE CHILDREN AND ELDERLY EXPOSURE IN THE
CITY OF ROME, ITALY
C. Gariazzo (1), M. Lamberti (1), C. Silibello (2), S. Finardi (2), P. Radice (2), A. D’Allura (2), M. Gherardi (1), A. Cecinato
(3), D. Porta (4), F. Sacco (5), O. Hänninen (6), A. Pelliccioni (1)
(1) INAIL Research Center, Monteporzio Catone (RM), Italy; (2) ARIANET S.r.l., Milano, Italy; (3) CNR-IIA,
Montelibretti (RM), Italy; (4) Department of Epidemiology, Lazio Region Health Service, Rome, Italy; (5) Lazio
Environmental Protection Agency, Rome, Italy, (6) National Institute for Health and Welfare, Kuopio, Finland
Presenting author email: c.gariazzo@inail.it
Summary
The identification and quantification of population exposure of children and elderly people to PAHs in urban areas are the
major goals of the EXPAH LIFE+ Project (www.ispesl.it/expah ). To reach these objectives, an integrated approach, based
on measurements and modelling techniques, has been set up to: 1) reconstruct PAH levels in the Rome metropolitan area; 2)
evaluate and correct model results; 3) estimate PAHs exposures according to the mean time spent in the main visited
microenvironments using observation-derived outdoor/indoor infiltration factors and time activities data collected from a
dedicated statistical survey. Results show that the integrated model is able to catch the mean exposure levels of the target
population.
Introduction
PAHs are known to induce health effects on population due to the ability of airborne particles to absorb and transport these
species in the lungs. Since some PAHs are potent carcinogens by a genotoxic mode of action, their levels in air should be
kept as low as possible (WHO, 2013). Consequently, the assessment of PAHs exposure of the most sensitive populations
living in urban areas, such as children and elderly people, represent a relevant issue, addressed by the EXPAH project.
Methodology and Results
In order to estimate PAHs exposure for the target population, a newer version of
the three-dimensional Eulerian chemical-transport model FARM (Flexible Air
quality Regional Model), which includes the PAHs reactions with hydroxyl radical
and their partitioning between gas and aerosol phases, has been applied to an high
spatial resolution (1x1 Km2) domain including the Rome conurbation. Simulations
were carried out for one year period (June 2011-May 2012) to estimate gridded
PAHs in both gaseous a aerosol phases.
Experimental data (particulate PAHs and PM2.5), collected during field campaigns
performed in different sites and microenvironments (homes, schools, cars, buses,
offices) from December 2011 to July 2012, permitted: 1) to evaluate simulated
PAHs concentrations; 2) to obtain microenvironments I/O infiltration factors
necessary to estimate the indoor PAH levels; 3) to collect actual PAHs exposure
data by means of personal exposure measurements. Modelled outdoor PAHs
concentrations showed overestimation, particularly during colder seasons, that have
been corrected, using observed values. Based on these results, a microenvironments
exposure model was developed. It calculates exposures of children and elderly
people according to the time spent in different environments (indoors (I), outdoors
(O), in traffic and living ambient), by using observed outdoor/indoor infiltration
factors and time-activities data. The latter ones were collected from a statistical
survey carried out for the target population living in Rome, according to type of
days (workday; weekend), season (autumn-winter; spring-summer) and
microenvironment visited.
Results show that the exposure model is able to reproduce the mean seasonal
behaviour of PAHs exposure, with higher values during the domestic heating
season and much lower ones during warmer periods. Agreement was found with
personal exposure data, although the day-by-day variations were poorly reproduced.
The yearly BaP exposure was found lower than legal limit, although during the
colder seasons an exceedance is foreseen for most parts of the city.
Fig. 1. Yearly BaP exposure for children.
Fig. 2 Cumulative BaP exposure for children.
Conclusions
The integrated approach, developed within the EXPAH project, has demonstrated its capability to assess the impact of PAHs
environmental exposures on children and elderly people. PAHs emissions and their spatialization were recognized as the
most critical aspects in PAHs modeling at urban scale. Inclusion of uncertanties in both I/O infiltration factors and variations
of population time-activities, can improve the exposure assessment.
Acknowledgement
The LIFE+ EU financial program is acknowledged for the provision of funding for EXPAH project (LIFE09 ENV/IT/082).
References
WHO, 2013. Review of evidence on health aspects of air pollution – REVIHAAP Project Technical Report. Available at
http://www.euro.who.int/__data/assets/pdf_file/0004/193108/REVIHAAP-Final-technical-report.pdf
53
CARDIOVASCULAR HOSPITAL ADMISSIONS DUE TO MULTIPLE AIRBORNE EXPOSURES UNDER THE
CONDITIONS OF SANTIAGO DE CHILE
U. Franck (1), A. M. Leitte (1), P. Suppan (2)
(1) Core Facility Studies, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany; (2) Institute of
Meteorology and Climate Research (IMK-IFU), Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, Germany
Presenting author email: ulrich.franck@ufz.de
Summary
This study aimed to compare the health effects of different airborne pollutants under the meteorological and air pollution
conditions of Santiago de Chile. We found adverse relationships between increasing pollution concentrations of all
investigated pollutants except ozone and the risks for hospital admissions due to cardiovascular diseases. Adverse effects
were strongest immediately up to a lag of two days. Exposure to ozone was not found to be associated with detrimental health
effects.
Introduction and aim of the study:
Santiago de Chile, with more than 6 Million inhabitants, suffers from high contamination levels due to relatively high
emissions and unfavorable atmospheric and geographic conditions. During winter, the main contamination is due to primary
emissions: particulate matter, sulphur dioxide (SO2) and nitrogen dioxide (NO2). A number of studies have demonstrated the
detrimental effects of ambient air pollutants on cardiovascular health. High concentrations of various air pollutants have been
associated with hospitalization due to development of cardiovascular diseases and exacerbation in people with preexisting
conditions. Former investigations also suggested that air pollution arising from common emission sources for CO, NO2, and
PM (e.g., motor vehicle exhausts) has significant associations with cardiovascular morbidity, also at air pollution
concentrations below normal health guidelines.
Study area, study cohort and statistics:
Because of the unique geographic location of Santiago de Chile, ventilation and dispersion of air pollution is highly
restricted. During the summer months, central Chile is generally under the influence of the subtropical anticyclone in the
south-eastern pacific, resulting in clear sky and high temperatures in Santiago (Schmitz, 2005). Under such conditions, the
formation of O3 through the photochemical oxidation of CO and volatile organic compounds (VOC) in the presence of high
concentrations of nitrogen oxides (NOx, NO, NO2) is favored. The study was performed in the metropolitan area of Santiago
de Chile during 2004-2007. Health data included all cases of hospital admissions (in total 75,303) which are registered by the
Fondo Nacional de Salud de Chile (FONASA) and the Instituciones de Salud Previsional (ISAPREs). We applied a timestratified case-crossover analysis taking temporal variation, meteorological conditions and autocorrelation into account. We
computed associations between daily ambient concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), particulate
matter (PM10 and PM2.5 - particulate matter with aerodynamic diameters less than 10 or 2.5 µm, respectively) or ozone (O3)
and hospital admissions for various groups of cardiovascular illnesses.
Results
During the study period, yearly mean values of air pollutant concentrations were high especially for PM10 (72.2 µg/m³) and
PM2.5 (33.7 µg/m³) (Table 1). For only around 25% of the days, the PM10 concentration was below the European daily limit
value of 50 µg/m³. In total 75,303 cases were included into the assessment. We found for CO, NO2, PM10 and PM2.5
adverse relationships to cardiovascular admissions while effect strength and lag depended on the pollutant and on the disease
group. By trend, in 1-pollutant models most adverse pollutants were NO2 and particulate matter (PM10 and PM2.5) followed
by CO, while in 2-pollutant models effects of PM10 persisted in most cases whereas other effects weakened. In addition the
strongest effects seemed to be immediate or with a delay of up to 2 days. Adverse effects of ozone could not be
detectedDichotomous
Conclusions
Our results provided evidence for adverse health effects of combined exposure to airborne pollutants. Different pollutants
accounted for varying adverse effects within different cardiovascular disease groups. Taking case numbers and effect strength
of all cardiovascular diseases into account, mitigation measures should address all pollutants but especially NO2, PM10, and
CO.
Acknowledgement
The authors very appreciated the support of the Departamento de Estadísticas e Información de Salud (DEIS) of the
Ministerio de Salud de Chile. The health data were kindly provided by DEIS The study was funded by 'Initiative and
Networking Fund' of the Helmholtz Association and was carried out under the umbrella of the Risk Habitat Megacity
research initiative (http://www.ufz.de/risk-habitat-megacity).
54
ENHANCING PM EPIDEMIOLOGICAL CONCENTRATION-RESPONSE FUNCTIONS BY INCORPORATING
LUNG DEPOSITION AND OXIDATIVE STRESS
D. A. Sarigiannis, S. Karakitsios, M. Kermenidou
Aristotle University of Thessaloniki, Chemical Engineering Dept., Environmental Engineering Laboratory, Thessaloniki,
54124, Greece
Presenting author email: denis@eng.auth.gr
Summary
The current study provides a methodological framework for refining environment and health associations, through the
derivation and use of a composite exposure metric called “region specific oxidative stress index”. The latter takes into
account the size specific mass deposited to the Human Respiratory Tract (HRT) region as well as the size specific ROS
generating potential of PM; thus, we surmise that it is a more relevant metric for PM exposure-health associations which are
mediated by oxidative stress and chronic inflammation.
Introduction
PM is a well recognized health stressor as shown by several well established associations between ambient air PM and
mortality or morbidity. However, there is still room for improving these associations by better understanding the intermediate
mechanisms determining actual exposure to PM, internal dosimetry and elucidation of potential mechanisms between
exposure and disease. Particulate matter through an oxidative stress mechanism causes a sevenfold increase in Nf-κB
activation in human airway epithelial cells. Nf-κB is a transcription factor that can induce gene transcription in a variety of
pro inflammatory cytokines, enzymes that generate mediators of inflammation and immune receptors. Oxidative stress
mediated by particulate matter may result from direct generation of Reactive Oxygen Species (ROS) from the particle
surface, where transition metals or organic compounds affect the mitochondrial function of inflammatory cells. The
subsequent damage to DNA may explain how increased cancer risk is induced by particulate matter.
Methodology and Results
The study includes a set of PM measurements performed over a three month period (October-December) in 2012 (including
PM10, PM2.5 and PM1), exposure modeling including deposition across respiratory tract and assessment of PM size specific
oxidative potential through the determination of reactive oxygen species (ROS) using the DDT assay. The PM measurements
were carried out in two urban sites in the city of Thessaloniki; the first one at the curbside of an intensively trafficked road
(Egnatia Avenue, Venizelou square) and the second one at the suburbs of the city (Eptapyrgio), representing the urban
background concentration. Internal exposure of PM in terms of deposition at different regions of the HRT was carried out
using the Multiple-Path Particle Dosimetry (MPPD) model. The algorithms in MPPD calculate the deposition and clearance
of monodisperse and polydisperse aerosols in the respiratory tract of rats and human adults and children (deposition only) for
particles ranging from ultrafine (0.01 microns) to coarse (20 microns) sizes. Dithiothreitol (DTT) is commonly used as a cellfree measure of the oxidative potential of particles. In this assay, redox-active chemicals in particulate matter (PM) oxidize
added DTT to its disulfide form and the linear rate of DTT loss is used as a measure of the oxidative capacity of the PM.
Finally, based on the PM size specific oxidative potential and the deposition across HRT, the “region specific oxidative stress
index” is calculated as the product of the size specific mass deposited to the HRT region, multiplied by the oxidative
potential of this size specific PM.
In the traffic station median concentrations for PM1, PM2.5 and PM10 were 25.7, 30.1 and 56 μg/m3, while for the urban
background site the respective concentrations were 12.7, 20.3 and 31.4 μg/m3. From the ROS analysis it was found that PM
from the traffic site was more reactive than the one from the urban background site; this is explained by the higher content of
traffic emitted metals and organics adsorbed on the PM collected there. In addition, oxidative potential increases with
decreasing particle size. This is due to the origin (smaller particles come from combustion processes) and the higher active
surface per mass that characterizes particles of smaller aerodynamic diameter. HRT modelling results indicated that exposure
between the two measurement sites corresponds to different HRT deposition patterns, and the overall daily deposition at the
traffic site is almost twice as high as at the urban background site (493 vs 260 μg deposited respectively). Finally, the
estimation of the region specific oxidative stress index elucidated significant differences between the two sites, since
differences in deposition and toxic potency are both reflected in that metric. As a result, the differences in exposure for
specific regions of HRT, are up to almost 4 times higher between the traffic and the urban background site. The regionspecific oxidative stress index has a much higher discriminating capacity than mass concentrations of PM.
Conclusions
The region specific oxidative stress index proposed abode, could serve as a starting point for re-evaluating environmental
information (PM measurements and ROS analysis), providing an clear advancement compared to existing concentration
response functions that mostly associate PM to mortality and morbidity. The proposed methodology, facilitates the
exploitation of exposure and toxicity related differences that are not captured by single PM10 and PM2.5 measurements. The
new index clearly reflects:
differences in PMs size distributions across the sampling sites, and how these are translated into HRT deposition
values
differences in the oxidative potential of the different size PMs, and more specifically to specific regions of HRT.
Acknowledgement
This work was supported by the FP7 project TRANSPHORM.
55
HIGH-RESOLUTION MODELLING OF HEALTH IMPACTS FROM AIR POLLUTION USING THE
INTEGRATED MODEL SYSTEM EVA
J. Brandt (1), M. S. Andersen (1), J. Bønløkke (2), J. H. Christensen (1), C. Geels (1), K. M. Hansen (1), S. S. Jensen (1), M.
Ketzel (1), M. S. Plejdrup (1), T. Sigsgaard (2), J. D. Silver (1)
(1) Aarhus University, Department of Environmental Science, Frederiksborgvej 399, 4000 Roskilde, Denmark; (2) Aarhus
University, Section of Environment, Occupation, and Health, Institute of Public Health, Bartholins Allé 2, Building
1260, 8000 Aarhus C, Denmark.
Presenting author email: jbr@dmu.dk
Summary
A high-resolution assessment of health impacts from air pollution and related external cost has been conducted for Denmark
using the integrated EVA model system. The EVA system has been further developed by implementing an air quality model
with a 1 km x 1 km resolution covering the whole of Denmark. New developments of the integrated model system will be
presented as well as results for health impacts and related external costs over several decades. Furthermore, the sensitivity of
health impacts to model resolution will be studied.
Introduction
We have developed an integrated model system EVA (Economic Valuation of Air pollution), based on the impact-pathway
chain, to assess the health impacts and health-related economic externalities of air pollution resulting from specific emission
sources or sectors. The system is used to support policymaking with respect to emission control. In Brandt et al. (2013a;
2013b), the EVA system was used to assess the impacts in Europe and Denmark from the past, present and future total air
pollution levels as well as the contribution from the major anthropogenic emission sectors. The EVA system was applied
using the hemispheric chemistry-transport model, the Danish Eulerian Hemispheric Model (DEHM), with nesting capability
for higher resolution over Europe (50 km x 50 km) and Northern Europe (16.7 km x 16.7 km). In this study an Urban
Background Model (UBM) has been further developed to cover the whole of Denmark with a 1 km x 1 km resolution and the
model has been implemented as a part of the integrated model system, EVA.
Methodology and Results
A schematic diagram of the impact-pathway methodology is
shown in Fig. 1. The site-specific emissions will result (via
atmospheric transport and chemistry) in a concentration
distribution, which together with detailed population data, are
used to estimate the population-level exposure. Using
exposure-response functions and economic valuations, the
exposure is transformed into impacts on human health and
related external costs.
In this study we have used a coupling of two chemistry
transport models to calculate the air pollution concentration at
different scales; the Danish Eulerian Hemispheric Model to
calculate the air pollution levels with a resolution down to 5.6
km x 5.6 km and the Urban Background Model to further
calculate the air pollution at 1 km x 1 km resolution using
results from DEHM as boundary conditions. Both the
emission data as well as the population density has been
represented in the model system with the same high resolution.
Fig.1 A schematic diagram of the impact-pathway methodology
Conclusions
Previous health impact assessments related to air pollution have been made on a lower resolution. In this study, the integrated
model system, EVA, has been used to estimate the health impacts and related external cost for Denmark over a 20 year period
(1990-2010) at a 1 km x 1 km resolution. Furthermore, a sensitivity study of the health impact using coarse and fine
resolutions in the model system has been carried out to evaluate the effect of improved description of the geographical
population distribution with respect to location of local emissions.
References
Brandt, J., J. D. Silver, J. H. Christensen, M. S. Andersen, J. Bønløkke, T. Sigsgaard, C. Geels, A. Gross, A. B. Hansen, K.
M. Hansen, G. B. Hedegaard, E. Kaas and L. M. Frohn, 2013. Contribution from the ten major emission sectors in Europe to
the Health-Cost Externalities of Air Pollution using the EVA Model System – an integrated modelling approach.
Atmospheric Chemistry and Physics, Vol. 13, pp. 7725-7746, 2013.
Brandt, J., J. D. Silver, J. H. Christensen, M. S. Andersen, J. Bønløkke, T. Sigsgaard, C. Geels, A. Gross, A. B. Hansen, K.
M. Hansen, G. B. Hedegaard, E. Kaas and L. M. Frohn, 2013. Assessment of Past, Present and Future Health-Cost
Externalities of Air Pollution in Europe and the contribution from international ship traffic using the EVA Model System.
Atmospheric Chemistry and Physics. Vol. 13, pp. 7747-7764, 2013.
56
SHORT-TERM EFFECTS OF AIR TEMPERATURE ON MORTALITY AND EFFECT MODIFICATION BY AIR
POLLUTION IN THREE CITIES OF BAVARIA, GERMANY
S. Breitner (1), K. Wolf (1), R. B. Devlin (2), D. Diaz-Sanchez (2), A. Peters (1), A. Schneider (1)
(1) Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Institute of Epidemiology II,
Neuherberg, Germany; (2) United States Environmental Protection Agency, Environmental Public Health Division, National
Health and Environmental Effects Research Laboratory, RTP, North Carolina, USA
Presenting author email:susanne.breitner@helmholtz-muenchen.de
Summary
We examined the effects of air temperature on cause-specific mortality in Munich, Nuremberg and Augsburg, Germany,
during the period 1990 to 2006 using Poisson regression models combined with distributed lag non-linear models. Moreover,
we investigated effect modification by age and ambient air pollution. The temperature-mortality relationships were non-linear
for all cause-specific mortality categories showing U- or J-shaped curves. Overall, effects of high temperatures were
immediate, whereas cold effects only became predominant with longer time lags. The elderly (≥ 85 years of age) were found
to be more susceptible to heat effects. Temperature effects on mortality varied slightly across different levels of air pollution.
Introduction
The link between ambient air temperature and mortality has been well documented; however, only very few studies have
been conducted in Germany. Further, only a few studies on temperature effects have considered air pollution as a confounder
or effect modifier. This study examined the association between daily air temperature and cause-specific mortality in Bavaria,
Southern Germany. Moreover, we investigated which age and gender groups are affected the most by heat or cold as well as
if ambient air pollution modifies the temperature-mortality relationship.
Methodology and Results
We obtained data from Munich, Nuremberg as well as Augsburg, Germany, for the period 1990 to 2006. Data included daily
death counts due to non-accidental causes as well as cardiovascular and respiratory diseases, mean daily meteorology and air
pollution concentrations (particulate matter with a diameter < 10µm [PM10] and maximum 8-h ozone). We used Poisson
regression models combined with distributed lag non-linear models adjusting for long-term trend, calendar effects, and
meteorological factors to investigate the association between air temperature and different causes of mortality in each city.
Further, for each city air pollutant concentrations were categorized into three levels, and an interaction term was included to
quantify potential effect modification of the air temperature effects. City-specific estimates were then combined in a second
stage using techniques based on multivariate meta-analysis.
The temperature-mortality relationships were non-linear for all cause-specific mortality categories showing U- or J-shaped
curves. An increase from the 90th (20.0°C) to the 99th percentile (24.8°C) of 2-day average temperature led to an increase in
non-accidental mortality by 11.4% (95% confidence interval [95% CI]: 7.6%;15.3%), whereas a decrease in the 15-day
average temperature from the 10th (-1.0°C) to the 1st percentile (-7.5°C) resulted in an increase of 6.2% (95% CI:
1.8%;10.8%). Regarding causes of deaths, largest relative risks were seen for respiratory mortality. The very old (≥ 85 years
of age) were found to be most susceptible to heat effects. Results also suggested some effect modification by ozone, but not
for PM10.
Conclusions
Results indicate that both very low and very high air temperature increase cause-specific mortality in Bavaria. Results also
pointed to the importance of considering effect modification by age and ozone in assessing temperature effects on mortality.
Acknowledgment
This study was funded by the Bavarian State Ministry of the Environment and Public Health and by the U.S. Environmental
Protection Agency (EPA) (PR-ORD-11-00199). We would like to thank the Bavarian State Office for Statistics and Data
Processing, the Bavarian Environment Agency and the German Weather Service for providing data on mortality,
meteorology and air pollution.
The research described in this article has been reviewed by the U.S. EPA National Health and Environmental Effects
Research Laboratory and approved for publication. Approval does not signify that the contents necessarily reflect the views
and the policies of the U.S. EPA, nor does mention of trade names or commercial products constitute endorsement or
recommendation for use. The authors declare they have no competing interests relevant to the study.
57
DETERMINANTS OF PERCEIVED AIR POLLUTION ANNOYANCE AND EXPOSURE-RESPONSE
RELATIONSHIP FOR ANNOYANCE AND PARTICULATE MATTER
M. Machado (1), J. M. Santos (2), N. C. Reis Jr.(2), V. A. Reisen (2)
(1) Instituto Federal do Espírito Santo (IFES), (2) Universidade Federal do Espírito Santo (UFES), Department of
Environmental Engineering, Vitória, Brazil
Presenting author email: milenamm@ifes.edu.br
Summary
This paper deals with the annoyance caused by air pollution in the Metropolitan Region of Vitória, in Brazil. Surveys were
conducted in eight regions, which correspond to the eight monitoring stations of air quality. The particulate matter
concentration, levels of annoyance, air pollution perception, consequences of air pollution, health problems related to effects
of air pollution and socio-demographic aspects were investigated in order to explore possible relationships. The logistic
regression method was used to estimate exposure-effect relationships between annoyance and particulate matter
concentration. The results show that variables, socio-demographics aspects, industrial risk perception, health problems,
sources of air pollution and local play an important role in the annoyance perceived.
Introduction
Annoyance by air pollution is considered to be a public health problem, since it causes stress, affects the quality of life and
may be indirectly related to a few diseases. Many authors have recently addressed this theme, such as Rotko (2002),
Amundsen et al. (2008) and Blanes-Vidal, (2012). Nevertheless, little attention was given to study how and why human being
perceives different air pollutants, reacts against their effects and what are the qualitative variables that can influence the
perception of annoyance. In this context, this paper presents the correlation matrix between variables determining of
annoyance and the exposure-response relationship that expresses different degrees of annoyance caused by particulate matter.
Methodology and Results
Two monitoring campaigns were performed: (i) winter of 2011 and (ii)
summer of 2012, in order to incorporate the seasonal effect. During each
campaign surveys were conducted at 8 locations distributed over the
Metropolitan Region of Vitória-Brazil, where PM10 and Particle Deposition
Flux (PDF) were continuously monitored. The sample size was determined
by using a simple random sampling with proportional allocation method
(Cochran, 1977), comprising 1028 individuals (over 16 years). The
statistical analysis based on Spearman method (Lehman, 2005) showed that
annoyance may be correlated with the qualitative variable: personal
perception (individual assessment) of air quality (r=-0,49), industrial risk
perception (r=0,47), air pollution perception (r=0,30), importance of air
quality (r=0,26), and also with age (r=0,22) gender (r=0,14), occurrence of
Fig.1 Curve estimated the relationship for of PM10
health problems (0,16) for α=0,05.The application of logistic regression
and different degrees of annoyance
helped to identify the relationship between annoyance and air pollution
expressed by particulate matter concentration (PM10 or PTS). For example, in Fig.1 presents the relationship for of PM10 and
different degrees of annoyance, where an exposure level of 30μg/m³ yields to approximately 10% of the population being
extremely annoyed and about 60% would be at least a little annoyed. Although the Brazilian air quality standards are attained
in the studied region, the results indicate that a considerable fraction of the population is significantly annoyed.
Conclusions
The study was capable of determine the current “annoyance level” of the population of the Metropolitan Region of VitóriaBrazil, and was able to identify the exposure-effect relationships between annoyance and particulate matter concentration for
the region. In addition, the regression study suggests that the variables selected for this investigation play an important role in
understanding the problem of air pollution and its effects on the quality of life of the population in the area.
Acknowledgement
This work was supported by FAPES and CAPES (Brazilian government agencies for technology development and scientific
research).
References
Amundsen, A. H., Klaeboe R., Fyhri A. (2008). Annoyance from vehicular air pollution: Exposure–response relationships for
Norway. Atmospheric Environment, Volume 42, 7679-7688.
Blanes-Vidal, V., Suh H., Nadimi E. S., Løfstrøm P., Ellermann T., Andersen H. V., Schwartz J., (2012) Residential
exposure to outdoor air pollution from livestock operations and perceived annoyance among citizens. Environment
International, 40 44-50.
Cochran, W.G. Sampling techiques. 3.ed. New York: John Wiley & Sons. 1977. 555p.
Lehman, A. (2005) "JMP for Basic Univariate and Multivariate Statistics: A Step-by-step Guide"Local: Campus Drive, Cary,
North Carolina, Editora SAS Institute.
Rotko et al., (2002) Determinants of perceived air pollution annoyance and association between annoyance scores and air
pollution (PM2.5, NO2) concentrations in the European EXPOLIS study. Atmospheric Environment 36, 4593–4602.
58
CARCINOGENIC RISK OF PAHS IN PARTICULATE MATTER FROM BIOMASS COMBUSTION
D. A. Sarigiannis (1,2), D. Zikopoulos (1), M. Kermenidou (1), S. Nikolaki (1,2), S. Karakitsios (1,2)
(1) Aristotle University of Thessaloniki, Department of Chemical Engineering, Environmental Engineering Laboratory,
Thessaloniki, 54124, Greece; (2) Centre for Research and Technology Hellas (CE.R.T.H.), Thessaloniki, 57001, Greece
Presenting author email: denis@eng.auth.gr
Summary
The current study deals with the assessment of the risk of cancer that is attributable to exposure to PAHs, in the light of
increased use of biomass for space heating in Greece in the winter of 2012-2013. The study incorporated ambient air PM
sampling in several sites in the city of Thessaloniki, as well as chemical analysis of PAHs and levoglucosan, used here as the
most specific tracer of biomass combustion. To estimate the cancer risk attributed to PAHs, a refined methodology
incorporating exposure, intake, Human Respiratory Tract (HRT) deposition of PM and the Toxicity Equivalent Quotient
(TEQ) concept was developed and implemented. Significant variation in risk was observed among different age groups,
much larger than variation due to geospatial attributes. The risk for children is four times higher than for adults. Only limited
difference was found between traffic and urban background sites in the winter (mean cancer risk for both is close to 10-6); the
latter indicates that biomass emitted PM (main PM source of the urban background site) are not significantly different in
terms of carcinogenic potency compared to traffic ones.
Introduction
Since 2011 the use of biomass as heating source was allowed in Greece as a CO2-neutral means of space heating in the large
metropolitan areas of Athens and Thessaloniki affecting more than half of the country’s population. Under this prism, it is
interesting to evaluate the actual carcinogenic risks imposed by PAHs - which is mostly considered as a traffic originated
component – within two distinct sites within an urban agglomeration, which are characterised by different PM emission
sources profiles.
Methodology and Results
A six-month campaign (October 2012 - April 2013) of ambient air PM measurements was carried out, capturing the
transition between the warm and cold period of the year. PM1, PM2.5 and PM10 particles were collected in Teflon filters
using six low-flow air samplers, in two air pollution monitoring stations, representative of urban and traffic sites respectively.
Nineteen individual PAHs were analysed by GC/MS and concentrations in the air were calculated. Levoglucosan levels were
identified for the different PM fractions, so as to estimate the contribution of biomass on the overall exposure to PAHs and
the associated cancer risk. Outdoor and indoor exposure and intake of PM and PAHs was estimated through the
computational platform INTERA, taking into account time activity patterns, outdoor-to-indoor air penetration rates, locations
encountered by the population during a typical week and inhalation rates associated to the activity intensity. Internal exposure
to PAHs was estimated taking into account the deposition of the respective PM fractions across the human respiratory tract
(HRT). Deposition at different regions of the HRT was carried out using the Multiple-Path Particle Dosimetry (MPPD)
model. Potential cancer risk due to exposure to the mixture of urban ambient air PAHs was calculated using the toxicity
equivalence factor (TEF) approach using as basis the benzo(a)pyrene (B[a]P) cancer potency. The BaP-TEQ (Toxicity
Equivalent Quotient) (carcinogenic equivalent, in ng/m3) was calculated by multiplying the concentrations of each compound
in the PAH mixture with the respective TEF for cancer potency relative to BaP. To estimate cancer risk the TEQ of the
respective fraction of particulate matter deposited across HRT daily, was multiplied to a dose-response function, derived by
the B[a]P Inhalation Unit Risk (the latter is equal to 0.88•10-6 (ng/m3)-1).
Based on chemical analysis of the PM fractions, the respective TEQ was estimated to be equal to 4.2, 4.9, and 4.2 ng/m3 for
PM1, PM2.5 and PM10 at the urban background site. At the traffic site, TEQ was 2.88, 2.89 and 2.88 ng/m3 for PM1, PM2.5
and PM10 respectively. The TEQ values per mass of PM for the urban background site were 11.3, 9.5 and 7.5 ng/g for PM1,
PM2.5 and PM10, while for the traffic station TEQ values were 13.5, 10.4 and 7.5 respectively. Exposure to PM and PAHs
varied significantly across age groups. Bodyweight normalised exposure to PM deposited across the HRT and consequently
to PAHs was almost four times as high for children as for adults. This finding reflects the differences in child physiology
compared to adults. These differences in PAHs exposure are translated into cancer risk. The latter varies between 3·10-5 and
0.5·10-6 (mean 1.55·10-6) for the urban background site, while for the traffic site ranges within 1.3·10-5 and 0.2·10-6 (mean
1.05·10-6). Finally, based on levoglucosan analysis, we estimated the risk attributable to biomass burning; the latter was
found to amount to 36% of the total cancer risk for the urban background and 16% for the traffic site respectively.
Conclusions
Particles produced from biomass combustion do not have a lower cancer potency than the ones emitted from traffic sources.
It is important to differentiate the PAHs intake estimate for different age groups, since children run significantly higher
cancer risk compared to adults, due to the higher exposure to PAHs when the latter is normalised to bodyweight.
Acknowledgement
This work was supported by the FP7 projects TRANSPHORM and URGENCHE.
59
EVALUATION OF AIR QUALITY IMPACTS WITH AN INTEGRATED ASSESSMENT MODEL FOR SPAIN
M. Vedrenne, R. Borge, J. Lumbreras and M. E. Rodríguez
Environmental Modelling Laboratory, Technical University of Madrid (UPM), José Gutiérrez Abascal 2,
28006 Madrid, Spain
Presenting author email: m.vedrenne@upm.es
Summary
The present paper describes the advancement and evaluation of air quality-related impacts with the Atmospheric Evaluation
and Research Integrated system for Spain (AERIS). In its current version, AERIS is able to provide estimates on the impacts
of air quality over human health (PM2.5 and O3), crops and vegetation (O3). The modules that allow quantifying the before
mentioned impacts were modeled by applying different approaches (mostly for the European context) present in scientific
literature to the conditions of the Iberian Peninsula. This application was supported by reliable data sources, as well as by the
good predictive capacity of AERIS for ambient concentrations. For validation purposes, the estimates of AERIS for impacts
on human health (change in the statistical life expectancy-PM2.5) and vegetation (loss of wheat crops-O3) were compared
against results from the SERCA project and GAINS estimates for two emission scenarios. In general, good results evidenced
by reasonable correlation coefficients were obtained, therefore confirming the adequateness of the followed modeling
approaches and the quality of AERIS predictions.
Introduction
The AERIS model was developed initially to quantify air quality levels (expressed as ambient concentrations or percentiles)
resulting from percentual changes in emissions of 18 SNAP sectors, Portugal and international sea transit for NO2, SO2,
PM10, PM2.5, NH3 and O3 (Vedrenne et al., 2013). The main advantage of AERIS is that it has been modeled specifically for
the national scale, using consistent information from national inventories as well as a reliable modeling infrastructure that has
been fully contrasted and published.
Methodology and Results
The quantification of impacts was carried out
according to different modeling methodologies that
are published in literature. Impacts on human health
are only available for PM2.5 (change in the statistical
life expectancy and years of life lost-YOLL) and O3
(mortality cases) (Mechler et al., 2002). Damages on
crops and vegetation by O3 as a function of AOT40
can be quantified for grapes, maize, potato, rice,
tomato, tobacco, watermelon and wheat (Mills et al.,
2002). Demographic data and information on vegetal
covers were obtained from the national ministries,
WHO, and FAO. Validation of results was carried out
by statistically comparing the estimates of AERIS
against the same values obtained by reference models:
the SERCA system and GAINS. The following
indicators were evaluated: (i) loss of wheat crops
(AERIS vs. SERCA) and (ii) change in the statistical
life expectancy-PM2.5 (AERIS vs. GAINS). The
chosen emission scenario was the Gothenburg
Protocol Revision (Nat. Projections 2020) for the first
Fig.1a. Relative yield for wheat (AERIS). 1b. Statistic comparison of
AERIS vs. SERCA. 1c. Loss of life expectancy (AERIS). 1d. Statistic
evaluation and a 2014 National Emission Scenario for
comparison of AERIS vs. GAINS.
the second one. The validation decision basically
consisted in priming high correlation coefficients (r).
Adequate correlations were observed for both comparisons: for the damage to wheat crops-O3, r=0.7043 and for the change
in the statistical life expectancy-PM2.5, r=0.7204. The sources of discrepancy are basically related with the use of datasets,
resolution and parent air quality models.
Conclusions
In general, the advancement of impact quantification to AERIS provided comparable results with those of reference air
quality models such as SERCA or other Integrated Assessment models like GAINS Europe. The modeling approaches that
were followed seem appropriate for having reliable estimates of the relevant impacts associated to pollutants (PM2.5 and O3).
References
Mechler, R., Amann, M., Schöpp, W., 2002. A methodology to estimate changes in statistical life expectancy due to the
control of particulate matter air pollution. IR-02-035. IIASA. Laxenburg, Austria.
Mills, G., Buse, A., Gimeno, B., Bermejo, V., Holland, M., Emberson, L., Pleijel, H., 2007. A synthesis of AOT40-based
response functions and critical levels of ozone for agricultural and horticultural crops. Atmos. Environ. 41, 2630-2643.
Vedrenne, M., Borge, R., Lumbreras, J., de la Paz, D., Rodríguez, M.E., 2013. Development and Implementation of an air
quality integrated assessment model for the Iberian Peninsula. 15th HARMO Conference. ISBN 978-84-695-7353-5.
60
POWER PLANTS AND THE INDUSTRIAL EMISSIONS DIRECTIVE: AIR QUALITY-RELATED IMPACTS
UNDER VARIABLE ENVIRONMENTAL AND TECHNICAL SETTINGS
T. M. Bachmann, J. van der Kamp
European Institute for Energy Research (EIFER), 76131 Karlsruhe, Germany
Presenting author email: bachmann@eifer.org
Summary
This study aims to assess to what extent the proportionality of emission abatement options depends on different
environmental and technical settings. Through a cost-benefit analysis, private costs of retrofitting and operating a DeNOx at a
typical coal-fired power plant at varied Western European locations are confronted with associated monetised environmental
benefits, quantified with the tool EcoSenseWeb. Results are shown to be sensitive to the environmental setting and the
operating time per year. Further methodological development is needed to make the assessment more robust.
Introduction
In the European Union (EU), emissions from industrial installations are largely addressed by requiring that best available
techniques (BAT) are implemented. The current Industrial Emissions Directive (IED, Directive 2010/75/EU) sets stricter
emission limit values (ELVs) for existing combustion plants to be respected from 2016 onwards than previous regulation. As
a new feature, plant operators can apply for less strict ELVs on the basis of the disproportionate cost principle, comparing
environmental benefits to (private) costs. The case is made for installing a DeNOx retrofit at a hard-coal fired power plant
unit investigated at three hypothetical sites, i.e. Brussels (BE), Cartagena (ES) and Helsinki (FI), varying in terms of
population density, background emissions and meteorological conditions. The plant parameters remain constant.
1.4
Building materials
Crops
Ecosystems
Human Health
Climate Change
Private costs 4500 h/a
Private costs 2500 h/a
1.2
[€‐cent(2000)/kWh(el)]
Methodology and Results
Through a cost-benefit analysis (CBA), private costs are confronted
with monetised environmental benefits (i.e. avoided external costs),
following the net present value rule (cf. Pearce et al., 2006). While
assessing private costs is common practice, external costs from NOx,
SO2 and particles are quantified through a marginal damage cost
approach with help of a tool for point sources in Europe, i.e.
EcoSenseWeb (Preiss and Klotz, 2008). Using a Gaussian plume
model (the Industrial Source Complex Model, ISC) as well as a
parameterized version of a European Eulerian model (EMEP/MSCW), external costs respectively at the local and the regional scale are
calculated for 2010 background emissions and a default meteorology
while assuming equal toxicity of different primary and secondary
1.0
0.8
0.6
0.4
0.2
0.0
Brussels
Cartagena
Helsinki
‐0.2
particles on human health. In a sensitivity analysis, the full load hours
Fig.1 Environmental benefits (bars) and private
of the power plant are reduced from 4500 to 2500 (e.g. due to an
costs (lines) of a DeNOx retrofit at a coal-fired
increasing share of fluctuating power generation).
power plant located at three sites: default case
(lower line); reduced full load hours (upper line)
The DeNOx retrofit is generally assessed to be efficient at all
investigated sites, i.e. the disproportionate cost criterion does not
apply (Fig. 1, 4500 h/a case). Nonetheless, the environmental setting substantially changes the magnitude of quantified
environmental benefits. When reducing the full load hours, the annualized private costs per kWh increase while the avoided
external costs per kWh remain the same (Fig. 1, 2500 h/a case). For the location with the lowest environmental benefits
(Helsinki), the result suggests that less full load hours combined with less impacted people may make the DeNOx investment
disproportionate.
Conclusions
The CBA results are sensitive to the environmental setting and key technical assumptions (e.g. full load hours). Besides, the
results are subject to limitations (e.g. insufficient coverage of impacts, and whether or not EcoSenseWeb can reliably
estimate external costs from mid-load operation) and depend on methodological assumptions (e.g. particle toxicity) and other
uncertainties as further discussed in Bachmann and van der Kamp (submitted). No EU-wide standard to calculate
environmental benefits in CBA applications exists at present. Scientific progress is constantly made that should be considered
accordingly. Finally, the IED is concerned also with emissions other than classical air pollutants. Related site-specific
assessments are currently hardly available.
References
Bachmann T.M., van der Kamp J., submitted. Environmental Cost-Benefit Analysis and the EU Industrial Emissions
Directive: comparing air emission abatement costs and environmental benefits to avoid social inefficiencies.
European Commission, 2005. ExternE - Externalities of Energy: Methodology 2005 update.
Pearce D., Atkinson G., Mourato S., 2006. Cost-Benefit Analysis and the Environment: Recent Developments. Organisation
for Economic Co-operation and Development (OECD), Paris. p. 314.
Preiss P., Klotz V., 2008. EcoSenseWeb V1.3. Technical Paper no. 7.4 - RS1b of the NEEDS project. Institute of Energy
Economics and the Rational Use of Energy, University of Stuttgart. p. 63.
61
LAND USE REGRESSION MODELLING FOR AIR QUALITY EXPOSURE: A STEP IN THE WRONG
DIRECTION
B. R. Denby
The Norwegian Institute for Air Research (NILU). PO BOX 100, 2027 Kjeller, Norway.
Presenting author email: bde@nilu.no
Summary
Land use regression (LUR) models are regularly used to assess exposure in health studies due to their simplicity and
accessibility for health experts. In this study we compare dispersion and LUR modelling in Oslo and find poor spatial
correlation between the two models, when used to calculate concentrations at cohort addresses. Despite this poor correlation
both methods show similar correlation with observational data, the same data that are used to build the LUR model. This
discrepancy is investigated and discussed. One investigation, using randomly generated datasets, shows that the LUR
methodology intrinsically overestimates the degree of correlation when sampling sizes are limited and the number of
available predictor variables is large. We recommend that more effort be placed in dispersion modelling, and its combination
with observations, rather than LUR if best estimates of exposure are to be made for health and epidemiological studies.
Introduction
Land use regression (LUR) models are being used extensively in health studies to determine exposure to air pollution. The
popularity of the methodology stems from its simplicity, relative ease of application and generality. This makes it accessible
and attractive to health experts who require air quality exposure data for epidemiological studies. The method requires a
(large) number of representative observations from which a linear data model is established based on a range of predictor
variables, such as distance from road or population density. An alternative, and physically based, method to LUR is air
quality modelling based on emissions and dispersion. Some studies have been undertaken to compare dispersion with LUR
modelling (e.g. Beelen et al., 2010) and/or to determine the limitations of the LUR models. These studies have mostly been
carried out for the traffic related pollutants of NOx or NO2 but have seldom been applied to particulate matter. In this study
we compare dispersion model calculations (TRANSPHORM project) with LUR models (ESCAPE project, Eeftens et al.,
2012), for the pollutants PM10, PM2.5, NOX and PMcoarse in the city of Oslo. We present the results of this analysis and a
statistical investigation of the correlation artefact introduced in LUR when using a limited number of monitoring sites.
Methodology and results
Annual mean concentrations, calculated with both LUR and dispersion models,
are compared at around 20 000 cohort member addresses, for the year 2009 in
Oslo. We find that the coefficient of determination is highest for NOX (R2=0.29)
and lowest for PM10 (R2=0.04). Despite the poor correlation found between the
two models at home addresses, both models have comparable R2 when evaluated
against ESCAPE monitoring data, which is the same data used to generate the
LUR model. e.g. R2 for the dispersion and LUR models is 0.64 and 0.68
respectively for PM2.5 at these sites, where leave-one-out cross validation
(LOOCV) is used for LUR. This result, that the dispersion and LUR models are
poorly spatially correlated but still provide comparable correlation at the
observational sites, is inconsistent and requires further investigation.
To help understand this we investigate the impact of sample size and the number of available predictor variables on the LUR
correlation by generating random and independent ‘observational’ and ‘predictor variable’ datasets and applying the LUR
methodology to these. We find for example that LUR type models, using limited sample sizes (20) and a large number of
available predictor variables (the 3 best selected from 100 possible), produce typically a LOOCV R2 = 0.28, but this can be as
high as R2=0.7. This is despite the fact that the observations and predictor variables are randomly sampled and are
uncorrelated. Increasing sample sizes and reducing the number of predictor variables will reduce this artefact.
Conclusion
We conclude that the limited number of sample sites, 20 for Oslo, and the large number of possible predictor variables
overstate the correlation of the LUR model significantly, providing misplaced confidence in the LUR results. The statistical
nature of the methodology, combined with the limited information used to generate the LUR models, can lead to significant
errors when extrapolating beyond the original dataset used to build the LUR model, e.g. at home addresses. As a result LUR
models may not be providing suitable spatial distributions of pollutants and this can have significant consequences for
epidemiological studies. It is recommended that more effort be made to apply dispersion modelling for exposure estimates,
and that observations be incorporated into these models to achieve the maximum benefit of the available information.
References
Beelen. R.,M. Voogt, J Duyzer, P. Zandveld, G. Hoek (2010). Comparison of the performances of land use regression
modelling and dispersion modelling in estimating small-scale variations in long-term air pollution concentrations in a Dutch
urban area. Atmospheric Environment 44, 4614-4621.
Eeftens, M. et al. (2012). Development of Land Use Regression Models for PM2.5, PM2.5 Absorbance, PM10 and PMcoarse
in 20 European Study Areas; Results of the ESCAPE Project. Environ Sci Technol. 46, 11195−11205.
62
OUTDOOR AIR DOMINATES BURDEN OF DISEASE FROM INDOOR EXPOSURES
O. Hänninen (1), A. Asikainen (1), P. Carrer (2), S. Kephalopoulos (3), E. de Oliveira Fernandes (4), P. Wargocki (5)
(1) National Institute for Health and Welfare, Finland, POB 95, 70701 Kuopio, Finland; (2) University of Milan, Italy, (3) EC
Joint Reasearch Centre, Ispra, Italy; (4) University of Porto, Portugal; (5) Technical University of Denmark
Presenting author email: otto.hanninen@thl.fi
Summary
Both indoor and outdoor sources of air pollution have significant public health impacts in Europe. Based on quantitative
modelling of the burden of disease the outdoor sources dominate the impacts by a clear margin.
Introduction
Ambient air pollution has been suggested to be the dominating source of environmental burden of diseases in Europe
(Hänninen & Knol, 2011, 2013). However, indoor sources can generate extremely high exposure levels in poorly ventilated
conditions. Globally it has been estimated that indoor PM exposures, especially due to combustion of solid fuels, dominate
the burden of disease caused by air pollution (Lim et al., 2012). The aim of this work is to compare the magnitude of indoor
and outdoor air pollution in European countries and further to evaluate their control potentials using ventilation, filtration and
source elimination.
Methods
Burden of disease model developed in the IAIAQ-study (Jantunen et al., 2011) was complemented with a mass-balance
component (Hänninen et al., 2004). Exposure data for PM2.5, VOCs, radon, CO, second hand smoke and dampness and
mould were collected for 26 European coutries (EU27 except Malta). Burden of disease for the baseline at 2010 and for
alternative control scenarios were evaluated.
Results and discussion
Total burden of disease from indoor exposures is estimated to be 2.1 million DALY in EU26. The burden is dominated by
outdoor PM2.5 (62%) followed by indoor PM2.5, radon (8%) and dampness and mould (5%). PM2.5 burden is further
dominated by cardiovascular diseases followed by respiratory diseases.
Outdoor air burden can be controlled by either limiting ventilation or by filtration. However, the former approach increases
the burden from indoor sources if they are not specifically controlled first. Most efficient reduction can be achieved by
combining these strategies, providing an almost 50% reduction. As the energy efficiency demands are shaping the future
building stocks strongly, it is essential to account for also for the indoor source control to protect public health.
Conclusions
Outdoor air remains the dominating source of burden of disease from indoor exposures. Improvement of outdoor air quality
has the largest potential for public health improvements.
Acknowledgement
This work was funded by the EU Health Programme projects HEALTHVENT, Grant Nr. 2009 12 08, and IAIAQ, Grant Nr.
2009 62 02, EU FP6 project EnVIE, SSPE-CT-2004-502671, and Ministry of Social Affairs and Health and intramural
funding for project EBoDE.
References
Hänninen O, Knol A (ed.), 2011. European perspectives on Environmental Burden of Disease; Estimates for nine stressors in
six countries. THL Reports 1/2011, Helsinki, Finland. 86 pp + 2 appendixes. ISBN 978-952-245-413-3. http://www.thl.fi/thlclient/pdfs/b75f6999-e7c4-4550-a939-3bccb19e41c1 (accessed 2011-03-23).
Hänninen, O, Knol A, Jantunen M, Lim T-A, Conrad A, Rappolder M, Carrer P, Fanetti A-C, Kim R, Buekers J, Torfs R,
Iavarone I, Classen T, Hornberg C, Mekel O, and the EBoDE Group, 2013. Environmental Burden of Disease in Europe:
estimates for nine stressors in six countries. Environmental Health Perspectives: Provisionnally accepted.
Hänninen, O.O., Lebret, E., Ilacqua, V., Katsouyanni, K., Künzli, N., Srám, R.J., Jantunen, M.J., 2004. Infiltration of ambient
PM2.5 and levels of indoor generated non-ETS PM2.5 in residences of four European cities. Atmospheric Environment 38
(37): 6411-6423.
Jantunen M, Oliveira Fernandes E, Carrer P, Kephalopoulos S, 2011. Promoting actions for healthy indoor air (IAIAQ).
European Commission Directorate General for Health and Consumers. Luxembourg. ISBN 978-92-79-20419-7.
http://ec.europa.eu/health/healthy_environments/docs/env_iaiaq.pdf (accessed 2011-11-10)
63
PM ATTRIBUTED MORTALITY AND MORBIDITY DUE TO BIOMASS USE IN THESSALONIKI –
ESTIMATION OF SOCIOECONOMIC COST
D.A. Sarigiannis (1,2), S. Karakitsios (1,2), M. Kermenidou (1)
(1) Aristotle University of Thessaloniki, Department of Chemical Engineering, Environmental Engineering Laboratory,
Thessaloniki, 54124, Greece; (2) Centre for Research and Technology Hellas (CE.R.T.H.), Thessaloniki, 57001, Greece
Presenting author email: denis@eng.auth.gr
Summary
The current study deals with the assessment of the seasonal variability of PM exposure and the related health and monetary
impact in the city of Thessaloniki (Greece). A combination of measured and modelled data of outdoor and indoor
PM10/PM2.5 were generated, feeding a composite integrative exposure assessment framework. Health impacts were assessed
adapting well-established exposure-response functions; monetary cost of these impacts was calculated based on the valuation
of the willingness-to-pay/accept (WTP/WTA). Overall the study indicated that biomass use for space heating contributed to a
40% PM attributed socioeconomic cost during the cold period.
Introduction
Over the last couple of years, the use of biomass as heating source was allowed in Greece as a CO2-neutral means of space
heating in the large metropolitan areas of Athens and Thessaloniki affecting more than half of the country’s population. At
the same time the use of light heating diesel was heavily taxed. In the same period Greece faces a financial crisis with
significant repercussions on the average household income. This combination resulted in reduced traffic loads but excessive
biomass use for domestic heating. In this context, the current study deals with the assessment of the seasonal variability of
PM exposure and the related health and monetary impact in the city of Thessaloniki (Greece).
Methodology and Results
A combination of measured and modeled data of outdoor and indoor PM10 and PM2.5 were generated, feeding a composite
integrative exposure assessment framework that takes into account indoor air quality modeling, time activity patterns and
activity based inhalation rates. The measurement campaign included the assessment of outdoor and indoor air quality and the
evaluation of biomass use for domestic heating in open fireplaces and woodstoves. Measured concentrations of PM10 and
PM2.5 were used as input to the computational platform INTERA, for assessing population exposure. INTERA incorporates
the combined effects of outdoor air penetration, presence of indoor sources, housing conditions, and the time activity patterns
of the exposed population. Health impacts were assessed adapting well established exposure-response functions; monetary
cost of these impacts was calculated based on the valuation of the willingness-to-pay/accept (WTP/WTA), to
avoid/compensate for the loss of welfare associated with these health impacts.
Outdoor measurements showed a significant increase of PM10 (from 30.1 to 73.1 μg/m3) and PM2.5 (from 19.4 to 62.7
μg/m3) concentrations during the transition from the warm to the cold period in 2012, in contrast to 2011, when this transition
was accompanied by an increase of 12 μg/m3 for both PM10 and PM2.5. Between the two years, there is a significant
variation in emission patterns. In 2012 the traffic component appears to be reduced, while during the colder period the
component associated with biomass heating dramatically increases; the latter is verified by the positively correlated
levoglucosan concentrations to ambient air PM concentrations. Indoor concentrations followed a similar pattern, while in the
case of fireplace use, average daily concentrations rise up to 10 μg/m3 and 14 μg/m3 for PM2.5 and PM10 respectively.
Regarding the estimated health impacts, the number of additional deaths attributed to PM exposure for 2011 are 1366, while
the respective number for 2012 is 1284. What is significantly different between these two years is the distribution between
the warm and the cold season. Despite the fact that the duration of the cold period is practically half than the one of the warm
period, in 2012 the expected impacts are higher in the cold period (726/1284 deaths), while in 2011 most of the mortality is
related to the warm period exposure (831/1366 deaths). Similar figures are derived for morbidity indexes, new cases of
chronic bronchitis being dominant among them with about 2111 and 1831 new cases for 2011 and 2012 respectively,
followed by respiratory hospital admissions (225 and 214 for 2011 and 2012 respectively) and cardiovascular hospital
admissions (174 and 165 respectively).
Monetary costs related to mortality are within the range of billions, while morbidity cost related to chronic bronchitis is one
order of magnitude lower (hundreds of millions). Morbidity costs related to cardiovascular and respiratory morbidity are
within the range of million euros.
Conclusions
The results indicated an increase in all-cause mortality of about 250 additional deaths (for a population of almost 900.000
inhabitants) for the cold period of year 2012 compared to the year 2011, corresponding to a socioeconomic cost of almost
250 million euro (up to 1.2 billions). Considering the high socioeconomic cost expected, specific financial measures, which
have led to the transition towards biomass-fuelled space heating such as heavy taxation of light heating diesel should be
reconsidered. Based on the results of the study, and taking into and taking into account the importance of public health and
the related socioeconomic cost, specific interventions are recommended, including the uplifting of heavy taxation of light
heating diesel, financial incentives for replacing light heating diesel by natural gas and rational and regulated use of biomass.
Acknowledgement
This work was supported by the FP7 projects TRANSPHORM and URGENCHE.
64
WAVELET ANALYSIS OF HEALTH EFFECT OUTCOMES ATTRIBUTRABLE TO AIR QUALITY AND
ASSOCIATED VARIABLES
V. Garcia (1), P. S. Porter (2), E. Gégo (2), S. T. Rao (3) and S. Lin (4)
(1) US Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory,
Research Triangle Park, NC, 27711, USA; (2) Porter-Gego, Idaho Falls, ID, 83401, USA; (3) North Carolina State
University, Raleigh, NC, 27695, USA; (4) New York State Department of Health, Center for Environmental Health
Empire State Plaza, Albany, NY 12222
Presenting author email: garcia.val@epa.gov
Summary
Measures of health outcomes are collinear with meteorology and air quality, making analysis of connections between human
health and air quality difficult. The purpose of this analysis was to determine time scales and periods shared by the variables
of interest (and by implication scales and periods that are not shared). Respiratory-related hospital admissions, meteorology
(temperature and relative humidity), and air quality (fine particulate matter < 2.5 microns in size (PM2.5) and daily maximum
ozone) for New York City during the period 2000-2006 were decomposed into temporal scales ranging from two days to
greater than two years using a complex wavelet transform. Health effects were modeled as functions of the wavelet
components of meteorology and air quality using the generalized additive model (GAM) framework. This simulation study
showed that the GAM is extremely successful at extracting and estimating a health effect embedded in a dataset. It also
shows that, if the objective in mind is to estimate the health signal but not to fully explain this signal, a simple GAM model
with a single confounder (calendar time) whose smooth representation includes a sufficient number of constraints is as good
as a more complex model.
Introduction
In the context of wavelet regression, confounding occurs
when two or more independent variables interact with the
dependent variable at the same frequency. Confounding also
acts on a variety of time scales, changing the PM2.5
coefficient (magnitude and sign) and its significance
according to the amount of variability at non-confounding
time scales. Removal of time scales that do not interact from
an analysis of hospital admissions and PM2.5 has the potential
for reducing bias and parameter uncertainty. A simulation
using the GAM model as presented in epidemiological
studies was designed to assess how collinearity between
PM2.5 and four confounding variables (calendar time, ozone
8-hr daily maximum concentration, daily maximum
temperature, and relative humidity), limits our ability to
accurately quantify the health effect (β) of PM2.5 on daily
counts of hospital admissions.
Methodology and Results
The expected value of the daily hospital admissions count
(log value) was modeled as the sum of three main
Fig. 1 Observed time series of hospital admissions in New York City (top
components plus white noise: (1) background average
panel) and two simulated time series (lower panel) with different ‘flu season’
number of hospital admissions, (2) the increase in hospital
terms
admissions due to PM2.5 pollution and (3) a zero-mean
periodic signal mimicking seasonality and factors
independent from PM2.5 requiring hospital admissions (flu season in winter, pollen flare up, etc; see fig. 1). In addition to
this basic dataset, a factor variable indicating whether or not a given day coincides with the 3-month (June to August) ozone
season was also integrated in the dataset to allow comparison of GAM results obtained when continuous time series or
temporally unconnected seasons are utilized. In order for the results not to give precedence to the confounding variables, time
series of all confounders were kept unchanged for all model runs while time series of PM2.5 and hospital admissions were
systematically modified. The correlation coefficient increases with the number of knots in the time smooth function,
supporting that the overall effect of PM2.5 pollution on hospital admissions is rather small in comparison to the effects of
other factors such as seasonality. Increasing the number of knots, i.e., increasing the winding of the ‘time’ smooth factor,
quickly causes the significance of the other confounders to vanish. The latter finding suggests that a very simple GAM
model in which ‘time’ is defined as the only confounder but the number of knots in the smooth term is large would be more
adequate than a more complicated model to tease out the health signal embedded in the data.
Conclusions
The objective of this simulation study was to assess the skills of the GAM model at teasing out the health factor hidden in the
data, particularly in the presence of confounding variables. We found that other factors (e.g., seasonality) have a much larger
effect than PM2.5 on respiratory-related hospital admissions in New York State and that sufficiently accounting for these
larger effects in the time-varying term also accounts for the confounders we studied. Thus, a GAM model with a single
confounder (calendar time) whose smooth representation includes a sufficient number of constraints is successful at
extracting and estimating a health effect embedded in a dataset.
65
IMPROVED HEALTHCARE THROUGH NEW AIR POLLUTION RISK TOOL
P. Sicard (1), C. Talbot (1), O. Lesne (1), A. Mangin (1), R. Collomp (2), N. Alexandre (2), H. Zelle (3), A. Mika (3), D.
Melas (4), D. Balis (4), A. Poupkou (4), Th. Giannaros (4), V. Costigliola (5) and D. Chloros (5)
(1) ACRI-ST, 260 route du Pin Montard, BP 234, 06904 Sophia Antipolis Cedex, France; (2) Centre Hospitalier
Universitaire of Nice - 4, Avenue Reine Victoria, BP 1179, 06003 Nice Cedex, France; (3) BMT ARGOSS, P.O. Box 61,
8325 ZH Vollenhove, Voorsterweg 28, 8316 PT Marknesse, The Netherlands; (4) AUTH, Aristotle University of
Thessaloniki, Laboratory of Atmospheric Physics, campus Box 149, 54124 Thessaloniki, Greece; (5) European Medical
Association (EMA), Avenue des Volontaires, 19, 1160 Bruxelles – Belgique
Presenting author email: pierre.sicard@acri-st.fr
Theme(s): Air pollution, Environment and health, Risk assessment
Summary
Scientists have elaborated a new and easy-to-use tool that allows health professionals to monitor the day-to-day sanitary risks
posed by short-term exposure to main urban air pollutants. The tool enables vulnerable groups, such as asthmatics, to take
precautionary measures. It also increases the public awareness to health impacts of air pollution.
Introduction
It has been estimated that in a typical urban environment, citizens are exposed to multiple air pollutants. Among these
pollutants, sulphur dioxide, fine particulate matter, nitrogen dioxide and ground-level ozone have been linked to respiratory
and cardiovascular diseases. Regional authorities are increasingly interested in monitoring air quality in line with the EU Air
Quality Framework Directive. Various indicators of air pollution already exist; many are not accompanied by adequate health
advices nor related to specific pathologies.
Methodology and Results
We have devised a rating system to predict whether the risk of an increase in a particular health defect (e.g., asthma, Chronic
Obstructive Pulmonary Disease or ischemic heart disease) is low, moderate, high or very high for a given location at a given
time. We have tested this forecasting tool in Greece (Thessaloniki and Athens), the Netherlands and South-east of France
(Provence Alpes Côte d’Azur). The chosen sites are known to be among the mostly affected cities by air pollution in Europe.
The “Aggregate Risk Index” (ARI) tool is calculated from reference values (relative risk) for a given health endpoint,
associated with an increase of each pollutant concentration, and are derived from health data collected during
epidemiological studies. Relative risks are ideally computed for each specific region, and known as exposure-response
functions, i.e. mortality rates and daily hospital admissions related to air pollution. For each measured pollutant, the result is
expressed as risks of increasing the incidence for a given health defect. An estimate of the total risk for a given health defect,
is then calculated from the sum of the individual risks for a mixture of pollutants. These are not only accounting for possible
additive effects but also are allowing users to compare relative contributions of each pollutant. This risk is then converted
into a simple numerical rating generally from 1 to 10 (1 = low risk, 10 = very high risk), and specific to the study area.
Conclusions
The ARI tool is intended to manage health responses to pollution events on a regional scale. The ARI rating scale can extend
past a value of 10 in very highly polluted areas, which indicates that even healthy people may suffer negative health effects
from short-term exposure. The ARI rating is accompanied by appropriate health advices for vulnerable people with heart or
lung problems, such as reducing strenuous outdoor activity.
Acknowledgement
This study was financially supported by the European Commission under the FP7 project PASODOBLE (Contract No.
241557).
References
Sicard P. et al. (2012). The Aggregate Risk Index: An intuitive tool providing the health risks of air pollution to health care
community and public. Atmospheric Environment, 46: 11-16.
Sicard P. et al. (2011). Air Quality Trends and Potential Health Effects - Development of an Aggregate Risk Index.
Atmospheric Environment 45: 1145-1153.
66
ASSESSING INDIVIDUAL EXPOSURE TO BLACK CARBON IN THE EUROPEAN DISTRICT IN BRUSSELS
USING OSPMBC MODELLING AND MOBILE MEASUREMENTS
P. Declerck (1a), O. Brasseur (1b), B. Heene (2) and P. Vanderstraeten (1b)
(1a) Dept. Health, Chemistry Lab. & Indoor; Brussels Environment, Gulledelle 100, 1200 Brussels, Belgium;
(1b) Dept. Telemetric Network & IRCEL-CELINE; Brussels Environment, Gulledelle 100, 1200 Brussels, Belgium;
(2) Earth & Life Institute, Université Catholique de Louvain, Place de l’Université 1, 1348 Louvain-la-Neuve, Belgium
Presenting author e-mail: pdeclerck@leefmilieu.irisnet.be
Summary
Several scientific studies already suggested the use of Black Carbon (BC) as a valuable additional air quality indicator to
evaluate health risks of air pollution dominated by primary combustion emissions. A first step in this evaluation process is
BC exposure assessment, which was the subject of this study. Hereto, OSPMBC (Operational Street Pollution Model for Black
Carbon) modelling and mobile measurements were performed. BC exposure of pedestrians and car drivers was determined
for three canyon streets, representative for the European district in Brussels. Our results showed that both were exposed to an
average BC increment of 4-10 µg/m3. Car drivers were generally more exposed to BC (1-3 µg/m3) compared to pedestrians.
Introduction
BC, commonly referred to as soot, is present in primary car exhaust and can induce respiratory and cardiovascular health
problems, as well as premature death. Local BC concentrations can be very high during busy commuting periods, and among
people walking, living, playing close to busy roads and/or canyon streets. These last ones are generally defined as narrow
streets lined with tall buildings.
Methodology and Results
OSPMBC modelling (Brasseur et al., submitted)
and mobile measurements were performed on the
following
assembly
of
canyon
streets,
representative for the European district in Brussels:
the Law, Belliard and Joseph II street. In a first
step of the exposure assessment, OSPMBC
validation was performed using aethalometer
measurements. Mobile data were obtained during
five measurement campaigns performed in the
period October 2012-March 2013 in the morning
rush hour and at noon. Measured and simulated BC
concentrations correlated well with a correlation
coefficient ranging between 0.74 and 0.79.
In a second step, exposure to BC concentration was
modelled for both pedestrians and car drivers
(Fig.1). Concerning the three canyon streets,
pedestrians and car drivers are exposed to an Fig.1 BC exposure of (a) car drivers and (b) pedestrians in three canyon streets
averaged increment in BC concentrations of 4-10 in Brussels. Exposures were simulated using OSPMBC for five measurement
µg/m³. Car drivers were generally more exposed to campaigns. Concerning pedestrians, the results are presented for the left (L) and
right (R) sides of the sidewalk. The circles represent the average BC
BC (1-3 µg/m3) compared to pedestrians.
concentrations; while the intervals represent the concentration range.
Concerning the last ones, a difference was noted
between the left and right sidewalks, with an averaged magnitude of 1-2 µg/m³. This is mainly due to a prevailing wind
blowing from the South-West direction, which favours certain configurations for the recirculation of pollutants in the canyon
street.
BC exposure and the related health impact depend on numerous factors, in particular on traffic and meteorology. In this
study, OSPMBC sensitivity was tested for the following input variables: traffic intensity, traffic speed, wind velocity, and
wind direction. The most sensitive variables were traffic intensity (03000 vehicles/hour: BC increase of 7.9 µg/m3) and
wind velocity (100.5 m/s: BC increase of 4.5 µg/m3).
Conclusions
Based on the comparison of simulated and measured BC concentrations, we can conclude that OSPMBC is able to accurately
simulate individual BC exposures in canyon streets. Pedestrians and car drivers were exposed to enhanced BC concentrations
that can induce on short or long term non-negligible health impacts.
Acknowledgements
This work was financed by the ExpAIR project (Assessment of the Individual Exposure of the Brussels Population to Urban
Air Pollution), financed by the Brussels Region. Authors would like to acknowledge Dario Hamesse for his assistance during
the different sampling campaigns and data analyses.
References
Brasseur O., Declerck P., Heene B., Vanderstraeten P. Modelling Black Carbon concentrations in two busy canyon streets in
Brussels using the OSPM approach. Submitted to Atmospheric Environment.
67
ENVIRONMENTAL
METEOROLOGY –
PROCESSES AND
INTERACTIONS
68
IMAGING OF NITROGEN DIOXIDE DURING AND AFTER AN ACTIVE LIGHTNING STORM
R. R Graves1, R. J. Leigh1, E. Arnone2, J. P. Lawrence1, K. Faloon3 and P. S. Monks3
1Earth
Observation Science Group, The Space Research Centre, The University of Leicester, University Road, Leicester, LE1
7RH, UK, 2 Istituto di Scienze dell'Atmosfera e del Clima (ISAC), Consiglio Nazionale delle Ricerche (CNR), Via Gobetti
101, 40129 Bologna, Italy 3The Department of Chemistry, The University of Leicester, University Road, Leicester, LE1
7RH, UK
Presenting author email: rg82@le.ac.uk
Summary
This study aims to assess the ability of an Imaging Differential Optical Absorption Spectroscopy (IDOAS) instrument,
CityScan, to measure Nitrogen Dioxide (NO2) emissions during and after an active lightning storm. CityScan measurements
will be used in conjunction with in situ monitors to attempt to quantify the additional NO2 which is measured in a city during
a lightning storm.
Introduction
Nitrogen dioxide is an important air pollutant which is produced in all combustion processes and can reduce lung function;
especially in sensitised individuals. A significant natural source of NO2 is lightning. The percentage of NOx emitted by
lightning (LNOx) varies with latitude between 4 and 23%. In urban areas, where regulatory limits for NO2 are often exceeded
it is important for local authorities to understand the contribution to emissions which is caused by natural sources as well as
anthropogenic.
Methodology and Results
The measurement technique which will be used in this
study is based upon the DOAS method. DOAS is now
commonly used as an air quality measuring system;
primarily through the measurements of NO2 both as a
ground-based and satellite technique. CityScan has
been optimised to measure concentrations of nitrogen
dioxide. CityScan has a 95˚ field of view (FOV)
between the zenith and 5˚ below the horizon. Across
this FOV there are 128 resolved elements which are
measured concurrently, the spectrometer is rotated Figure 2 NO2 imaged during an active lightning storm in Bologna, Italy on
the 13th of June 2012.
azimuthally 1˚ per second providing full hemispherical
coverage every 6 minutes. CityScan measures
concentrations of nitrogen dioxide over specific lines of sight and due to the extensive field of view of the instrument this
produces measurements which are representative over city-wide scales.
Two CityScan instruments were deployed in Bologna, Italy throughout June 2012 as part of the PEGASOS campaign. The
imaging capability of the CityScan instruments allowed LNO2 to be imaged both in-cloud and beneath the cloud during the
active part of a storm which occurred on the 13th of June 2012. Also imaged was the city-wide pollution which resulted after
the storm had passed, which is hypothesised to be caused by emissions from the soil. Results from CityScan instruments in
conjunction with the Bologna in situ monitors will be used to assess the contribution of LNO2 within a city during and after
an active lightning storm.
Conclusions
This study has demonstrated the ability of the CityScan technique to monitor natural emissions of NO2 within a complex
urban environment and to quantify the additional NO2 which can be measured owing to these natural processes. This will
prove to be invaluable information for local authorities who have been tasked with emission reduction.
Acknowledgments
This work has been supported by grants from NERC (R8/H12/82), CEOI and the PEGASOS project.
References
Ulrich Platt and Jochen Stutz. 2008, Differential Optical Absorption Spectroscopy: Principles and Applications. Springer,
Berlin, Germany.
U. Schumann and H. Huntrieser, 2007, The global lightning-induced nitrogen oxides source. Atmospheric Chemistry and
Physics, 7(14):3823-3907.
69
INLET AND OUTLET SHAPE DESIGN OF NATURAL CIRCULATION BUILDING VENTILATION SYSTEMS
J. J. Swiegers, R. T. Dobson
Centre for Renewable and Sustainable Energy Studies (CRSES), University of Stellenbosch, Stellenbosch, 7600, South
Africa
Presenting author email: 15664155@sun.ac.za
Summary
This study aims to determine an optimised shape for inlet and outlet configurations for a Solar Chimney Augmented Passive
Downdraught Evaporative Cooling (SCAPDEC) system for a wide range of environmental conditions (see Fig.1). A two
dimensional theoretical model was built and used along with a CFD model to validate experimental results. Four inlet and
four outlet configurations were tested with varying wind direction and intensity and varying SC or PDEC draft speeds. A
good correlation was found between the theoretical and experimental data. The DSI-design (Dobson Swiegers Inlet)
configuration was determined to be the optimised inlet configuration, as it was successful in funnelling wind into the PDEC
tower and performed well in passive and start-up conditions. The optimised outlet configuration was determined to be the
DSO-design (Dobson Swiegers Outlet) configuration. It was determined that kinetic energy from wind could be harnessed to
increase fresh air flow through the ventilation system, if the set of installed configurations were designed to do so.
Introduction
Natural ventilated buildings can significantly reduce environmental emissions when compared with conventional airconditioned buildings (Martinez, 2000). In arid countries it can entirely avoid the need for air-conditioning. Sundell (2002)
states that most people spend up to 90% of their time indoors. The most important environment in relation to our health, is
the indoor environment. Natural ventilation can provide fresh air indoors, without the need for re-circulation. Biological
pollutants and infectious diseases can be re-circulated into the same environment with normal air-conditioning systems.
SCAPDEC systems draw in fresh air, humidifies it, forces it into the living space and flushes out the old air. Humidifying air
does, however, increase the risk
of fungi and bacteria exposure as
declared by the World Health
Organization: Indoor air pollution
(2008). It is therefore vital that
evaporative pads in the PDEC
tower are regularly replaced.
Developing inlet and outlet
shapes that increase the flow rate
of fresh air through the system
could increase the efficiency of
this
system
to
challenge
conventional
air-conditioning
systems on a global scale.
Fig.1 Solar Chimney Augmented Passive Downdraught Evaporative Cooling (SCAPDEC) System
Methodology and Results
A scale model of the system, comprising of the SC and PDEC, was built along independent, full scale models of both the SC
and the PDEC. A wind tunnel that can test configurations at low wind and system draft speeds was also build with points for
measuring temperatures, pressures and relative humidity. The aim of testing these configurations was to determine an energy
loss coefficient for each and to establish the best set of configurations to obtain maximum air flow through the system for
most environmental conditions. The configurations were tested for transient and steady state conditions with and without
wind present. The experimental results were then compared with the theoretical two dimensional and CFD models. The DSIdesign and the DSO-design configurations obtained the lowest loss coefficients for most of the tests administered. They were
also the only set of configurations capable of providing the living space with fresh air in the tests where there was only wind
present and no SC or PDEC draft speeds. The theoretical models also accurately predicted the measured data.
Conclusions
Optimised shapes for inlet and outlet configurations that are capable of providing fresh air to a living space for a wide range
of environmental conditions were determined. Installing the DSI-design and DSO-design configuration on a natural
ventilation system could increase the air flow through the system to meet the cooling load requirements while providing
occupant thermal comfort. The two dimensional model is also accurate in predicting subtle changes and in conjunction with
the CFD model is capable of predicting system temperatures and flow rates for most environmental and operating conditions.
References
Martinez, D., 2000. Thermal Simulation of Passive Downdraught Evaporative Cooling (PDEC) in non-domestic buildings.
MCITI. July 2000.
Sundell, J., 2002. Sustainable built environment. Vol. 1. Health and Comfort in Buildings. Technical University of Denmark,
Lyngby. Denmark.
World Health Organization, 2008. Training for the health sector: indoor air pollution. [pdf]. Available at:
<http://www.who.int/ceh/capacity/Indoor_Air_Pollution.pdf > [Accessed 11 October 2012].
70
INFLUENCE OF SURFACE AND SUBSIDENCE THERMAL INVERSION ON PM2.5 AND BLACK CARBON
CONCENTRATION
E. Gramsch (1), D. Cáceres (1), P. Oyola (2), F. Reyes (2), Y. Vasquez (2), M. A. Rubio (3)
(1)Department of Physics, University of Santiago, Santiago, Chile; (2)Mario Molina Center, Santiago, Chile; (3)Faculty of
Chemistry, University of Santiago, Santiago, Chile
Presenting author email: egramsch@gmail.com
Summary
A study of particulate matter and temperature in the atmosphere in several places in Chile along several years has been
carried out with the objective to determine the influence of thermal inversion on PM2.5 and black carbon. Vertical temperature
profiles have been measured in 2004 from airplanes, in 2005 in a hill, in 2009 from an airplane in Santiago de Chile and in
2011 in a hill in a rural site. These measurements were used to separate the days that had surface and subsidence inversion.
The results indicate that in days with both types of inversion (subsidence and surface) the PM2.5 concentration was 98%
higher than days without any type of inversion. In addition, the days with only surface inversion the concentration during the
morning (1 – 10 AM) was higher than days with only subsidence inversion or without inversion. In the rural site, only the
surface inversion was determined because temperature was measured only at three heights. In this site, on days with surface
temperature inversion, higher concentration of black carbon was found only during the morning.
Introduction
In many urban centers there are hills that restrict wind speed and horizontal transport of pollutants. In such places, dispersion
and dilution through vertical mixing is essential in reducing air pollution concentrations1. In central Chile, during winter,
frequent temperature inversions lead to stable atmospheric conditions which constrain vertical airflow, trapping pollutants
below the inversion cap leading to concentrations that are many times higher the WHO standards.
250
PM2.5, June 2004
Concentration (g/m3)
Methodology and Results
During winter of 2004, temperature profiles up to 10,000 m were
measured from commercial aircraft departing from the main airport
in Santiago de Chile. Data were collected from MADIS
(Meteorological Assimilation Data Ingest System) depending from
NOAA for the months of June, July and August. PM2.5
concentrations were measured in one of the stations of the Macam
Network, which belongs to the Ministry of the Environment. Fine
particle mass, PM2.5 was measured with a Tapered Element
Oscillating Microbalance (TEOM). One hour measurements were
taken in the station closest to the airport (Pudahuel).
200
Surface and subsidence inv.
No Inversion
surface Inversion
150
100
50
0
The temperature data were used to select days in which there were
0
2
4
6
8
10
12
14
16
18
20
22
24
surface and subsidence inversion, days in which there were only
Hour of day surface inversion and days without inversion. The PM2.5 hourly
average was calculated for these three situations and are shown in
Fig. 1 Average PM2.5 in Pudahuel station in Santiago
Figure 1. During days in which there is only surface inversion, PM2.5
de Chile in days with and without thermal inversion.
concentration is higher during the morning (1 – 6 AM). During the
evening or night, the concentration is similar to days without inversion. In contrast, in days in which there is surface and
subsidence inversion, the concentration is higher during the morning, but much higher during the night.
In a rural site, temperature and was measured in a hill during winter of 2011 at three heights. Black carbon (BC) was
measured at the bottom of the hill. The site is located in a small town that uses wood burning for heating. As before, days
with surface temperature inversion were separated from days without inversion. The results show that inversion only has
influence on BC only during the morning, not in the evening or night. Similar measurements in a hill in Santiago de Chile in
winter of 2005 also show that surface inversion only has influence in the morning PM2.5 concentration.
Conclusions
Temperature inversion measured in several places show that surface inversion influences PM2.5 or BC concentrations only
during the morning. Subsidence inversion has influence during the whole day.
References
The effect of temperature inversions on ground-level nitrogen dioxide (NO2) and fine particulate matter (PM2.5) using
temperature profiles from the Atmospheric Infrared Sounder (AIRS), J. Wallace, P. Kanaroglou, Science of the Total
Environment 407 (2009) 5085–5095.
71
PERFORMANCE OF EUROPEAN CHEMISTRY-TRANSPORT MODELS AS FUNCTION OF HORIZONTAL
SPATIAL RESOLUTION
C. Cuvelier (1), P. Thunis (1), D. Karam (1), M. Schaap (2), C. Hendriks (2), R. Kranenburg (2), H. Fagerli (3), A. Nyiri (3),
D. Simpson (3), P. Wind (3), M. Schultz (3), B. Bessagnet (4), A. Colette (4), E. Terrenoire (4), L. Rouil (4), R. Stern (5), A.
Graff (6), J. M. Baldasano (7), M. T. Pay (7)
(1) European Commission, DG Joint Research Centre, Institute for Environment and Sustainability, I-21020 Ispra (Va), Italy;
(2) TNO Built Environment and Geosciences, Dept. of Air Quality and Climate, P.O. Box 80015, NL-3508TA Utrecht, The
Netherlands; (3) Air Pollution Section Research Department, Norwegian Meteorological Institute, P.O. Box 43, Blindern, N0313, Oslo, Norway; (4) INERIS, Institut National de l’Environnement Industriel et des Risques, Parc Technologique,
ALATA, F-60550 Verneuil-en-Halatte, France ; (5) Freie Universität Berlin, Institut für Meteorologie und Troposphärische
Umweltforschung, Carl-Heinrich-Becker Weg 6-10, D-12165 Berlin, Germany ; (6) Umweltbundesamt, Postfach 1406, D06813 Dessau-Roßlau, Germany; (7) Barcelona Supercomputing Center, c/ Jordi Girona 29, E-08034 Barcelona, Spain
Presenting author email: kees.cuvelier@yahoo.fr
Summary
This systematic chemistry-transport model intercomparison study aims to quantify the impact of horizontal spatial resolution
on the simulated concentrations of Ozone, NO2, PM10, and PM2.5, including PM components. Five modelling teams
participated in this study by performing annual runs over Europe at four different horizontal resolutions (56, 28, 14, 7 km).
All model results were analysed at central level, quantification of the intercomparison was based on various statistical
parameters using the Fairmode DeltaTool (cf. Thunis et al. 2011). The complete study is published as an EMEP Technical
Report (cf. Cuvelier et al. 2013).
Introduction
The EMEP MSC-W models have been instrumental to the development of air quality policies in Europe since the late 1970s.
In the 1990s the EMEP models became also the reference tools for atmospheric dispersion calculations as input to the
Integrated Assessment Modelling, which supports the development of air quality policies in the European Union. Since 1999,
the EMEP model has been run on a resolution of 50x50 km2. However, the last years, modification of the EMEP grid has
been discussed, an important aspect of which is the grid resolution. To support EMEP in this decision, an initiative was taken
for a model inter-comparison exercise aimed at analysing the model performance of different chemical-transport models as a
function of model horizontal spatial resolution.
Methodology an Results
Five modelling teams participated in the exercise: EMEP MSC-W, CHIMERE (INERIS), LOTOS-EUROS (TNO), RCGC
(Berlin Freie Universität), and CMAQ (BSC). Each modelling team carried out four model simulations with different
horizontal resolutions (56, 28, 14 and 7km). The simulations were performed for the year 2009 for the EC4MACS domain
encompassing Europe. The horizontal spatial resolution ranges from a 1.0x0.5 degrees to 0.125x0.0625 degrees, which
corresponds to 56x56 km and 7x7 km in the Northern part of the domain and to 88x56 km and 11x7 km in the Southern part
of the domain, respectively. The model-to-model and model-to-measurements intercomparisons were performed at a central
location (JRC) to ensure a harmonised evaluation procedure based.on various statistical indicators. For this purpose the
DeltaTool, developed in the frame of the FAIRMODE activity, has been used. The study focused on the following pollutants:
Ozone, NO2, PM10, and PM2.5 and PM components.
Conclusions
The analysis showed that the grid size does not play a major role for air quality model calculations which are targeted on the
determination of the background (non-urban) air quality. Downscaling model resolution does not change concentration
estimates and model performance at rural and EMEP sites. However, the grid resolution plays an important role in
agglomerations characterized by high emission densities. The urban signal, i.e. the concentration difference between high
emission areas and their surroundings, usually increases with decreasing grid size. This grid effect is more pronounced for
NO2 than for PM10.
This study clearly shows that increasing model resolution is advantageous and that leaving a resolution of 50 km in favour of
a resolution between 10-20 km is practical and worthwhile. Other input data, notably emissions and meteorological data, are
also available at this scale, but become more problematic at finer resolutions. Further improvements of resolution should go
hand in hand with improved resolution of meteorological models, the improved representation of spatial and temporal
variability in emission data as well as process descriptions.
References
Cuvelier C., Thunis P., Karam D., Schaap M., Hendriks C., Fagerli H., Nyiri A., Simpson D., Wind P., Schultz M., Bessagnet
B., Colette A., Terrenoire E., Rouil R., Stern R., Graff A., Baldasano J.M., Pay M.T., 2013, ScaleDep - Performance of
European chemistry-transport models as function of horizontal spatial resolution. EMEP Technical Report 1/2013.
Thunis P., Georgieva E, Pederzoli A., 2011: The DELTA tool and Benchmarking Report template: Concepts and User’s
Guide Version 1. P.. Fairmode report, http://fairmode.ew.eea.europa.eu/
72
INTENSIVE RESEARCH-GRADE NETWORK FOR TURBULENCE OBSERVATIONS OVER HELSINKI
C.R. Wood (1), R.D. Kouznetsov (1,2), A. Nordbo (3), S. Joffre (1), A. Hirsikko (1,4), A. Karppinen (1), L. Järvi (3), P.
Ukkonen (1,3), T. Vesala (3), V. Vakkari (1), E.J. O'Connor (1,5), J. Kukkonen (1)
(1) Finnish Meteorological Institute, Erik Palménin aukio 1, FI-00101, Helsinki, Finland; (2) A.M. Obukhov Institute of
Atmospheric Physics, Moscow, Russia; (3) Department of Physics, University of Helsinki, FI-00014, Helsinki, Finland; (4)
Forschungszentrum Jülich GmbH, Institut für Energie-und Klimaforschung: Troposphäre (IEK-8), Jülich, Germany; (5)
Department of Meteorology, University of Reading, RG6 6BB, Reading, United Kingdom.
Presenting author email: Curtis.Wood@fmi.fi
Summary
Helsinki UrBAN (Urban Boundary-layer Atmosphere Network, http://urban.fmi.fi) is an intensive observational network to
study the physical processes in the urban atmosphere. Helsinki has many unique science features worthy of study, such as a
range of surface types (urban, sea, forest), strong seasonality and fairly frequently occurring extremely stable atmospheric
conditions (Helsinki UrBAN is the world’s most poleward intensive urban research observation network). The network’s key
purpose is for understanding the physical processes which affect fluxes of heat, momentum, moisture and other tracers such
as aerosol and gases. A secondary purpose is to secure a research-grade database which can be used to validate and develop
numerical models of air quality and weather prediction.
Introduction
To understand and predict concentrations of air pollutants,
we need to know emissions, atmospheric processes and
depositions. Here, we focus on physical processes in
atmospheric boundary layer, such as transport and mixing.
Most other international studies of atmospheric boundary
layers (ABLs) above cities have focused on specific
campaigns, often with less than one year of measurements.
This has caused a lack of intensive research-grade long-term
ABL observations over cities—particularly from highlatitude cities.
Thus, Helsinki UrBAN’s (Wood et al., 2013a) major
purposes are: (i) understanding the physical processes in
urban ABL’s, (ii) validation and development of numerical
models (weather prediction, air quality and chemical
transport), and (iii) interaction with instrument developers to
obtain best use of instrumentation.
Fig.1 Helsinki UrBAN map with equipment locations marked
Methodology
(legend). EC is eddy covariance. HARMONIE grid points are
We use a range of research-grade equipment:
from the numerical weather prediction model.
scintillometers, scanning Doppler lidar, ceilometers, sodar,
eddy-covariance stations and radiometers. Those equipment
are supplemented by a range of equipment whose primary purpose is not for studying the atmospheric boundary layer itself
(mostly at the mesoscale), such as vertical soundings and the operational Doppler radar network.
Conclusions
Science examples include, e.g., (i) exceptional evidence of a stable boundary layer above an urban surface (Nordbo et al.,
2012), and (ii) comparison of scintillometer data (temperature structure parameter) with sonic anemometry above an urban
surface (Wood et al., 2013b). Parts of Helsinki UrBAN have been operating since 2004, with large expansion in 2010–2013.
In addition we plan to develop this network’s equipment and collaborations. We invite other people to bring their
instrumentation and/or expertise beside ours, and/or use the already available measured datasets, for the advancement of
technology, science and applications.
Acknowledgement
EC FP7 ERC Grant No. 227915 “Atmospheric planetary boundary layers – physics, modelling and role in Earth system”.
References
Nordbo, A., Järvi, L., Haapanala, S., Moilanen, J. and Vesala, T.: Intra-city variation in urban morphology and turbulence
structure
in
Helsinki,
Finland,
Boundary-Layer
Meteorology,
doi:10.1007/s10546-012-9773-y,
2012.
Wood, C. R., Järvi, L., Kouznetsov, R. D., Nordbo, A., Joffre, S. M., Drebs, A., Vihma, T., Hirsikko, A., Suomi, I., Fortelius,
C., O’Connor, E. J., et al.: An overview on the Urban Boundary-layer Atmosphere Network in Helsinki, Bulletin of the
American
Meteorological
Society,
11,
2013a.
Wood, C. R., Kouznetsov, R. D., Gierens, R., Nordbo, A., Järvi, L., Kallistratova, M. A. and Kukkonen, J.: On the
Temperature Structure Parameter and Sensible Heat Flux over Helsinki from Sonic Anemometry and Scintillometry, Journal
of Atmospheric and Oceanic Technology, 30, 1604–1615, 2013b.
73
MEASUREMENT OF AIR
POLLUTANTS AND
SOURCE
APPORTIONMENT
74
PLUMES WITH ELEVATED MERCURY CONCENTRATIONS OBSERVED DURING CARIBIC FLIGHTS IN
2005 - 2013
F. Slemr (1), A. Weigelt (2), R. Ebinghaus (2), C. A. M. Brenninkmeijer (1), T. Schuck (1), A. Rauthe-Schöch (1), M.
Hermann (3), P. van Velthoven (4), D. Oram (5), A. Zahn (6) and H. Ziereis (7)
(1) Max-Planck-Institut for Chemistry, Hahn-Meitner-Weg 1, D-55128 Mainz, Germany; (2) Helmholtz-Zentrum
Geesthacht, Institute for Coastal Research, Max-Planck-Strasse 1, D-21502 Geesthacht, Germany; (3) Leibniz Institut für
Troposphärenforschung, Permoserstrasse 15, D-04318 Leipzig, Germany; (4) Royal Netherlands Meteorological Institute
(KNMI), P.O.Box 201, NL-3730 AE De Bilt, Netherlands; (5) University of East Anglia, School of Environmental Sciences,
Norwich NR4 7TJ, United Kingdom; (6) Institut für Meteorologie und Klimaforschung (IMK), Forschungszentrum
Karlsruhe, Weberstrasse 5, D-76133 Karlsruhe, Germany; (7) Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institute
for Physics of the Atmosphere, D-82230 Wessling, Germany
Presenting author email: franz.slemr@mpic.de
Summary
Tropospheric sections of CARIBIC (Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrumented
Container) flights from December 2005 until June 2013 were investigated for the occurrence of plumes with elevated Hg and
CO concentration ratios. Additional information on hydrocarbon, halocarbon, acetone, and acetonitrile mixing ratios
combined with backward trajectories enable us to classify the plumes and to determine areas of their origin. Altogether 69
plumes with elevated Hg and CO concentrations were identified at 10 – 12 km altitude and Hg/CO emission ratios for 42 of
them could be calculated. Most of the plumes were found over Far East, Equatorial Africa, South America regions and over
South East Asia. The plumes over the Equatorial Africa and South America originate predominantly from biomass burning as
evidenced by low Hg/CO emission ratios and elevated mixing ratios of acetonitrile, CH3Cl and CH3Br. Backward trajectories
point to sub-Saharan regions and the Amazon basin with its outskirts as the source areas. The plumes encountered over the
Far East and Pakistan and India are predominantly of urban/industrial origin, sometimes mixed with products of
biomass/biofuel burning. Backward trajectories point mostly to source areas in China and northern India.
Introduction
Mercury in the aquatic environment can be converted to methyl mercury, a potent neurotoxin, which is bioaccumulated in the
aquatic nutrition chain to levels harmful to humans and animals. Mercury is emitted by natural and anthropogenic processes
and due to a lifetime of about 1 yr in the atmosphere it can be transported and deposited far away from its sources. Mercury
emissions in the developed countries are being reduced by control measures while they are increasing in the developing
countries with the increasing consumption of energy and materials. Regular CARIBIC flights over northern hemisphere and
some regions of southern hemisphere reveal different types of mercury sources and their changing distribution and provide
emission ratios which can help to quantify anthropogenic emissions.
Methodology and Results
Mercury is being measured during monthly intercontinental flights (Brenninkmeijer et al., 2007) by an instrument with a
temporal resolution of 5-15 min (Ebinghaus et al., 2007; Slemr et al., 2009). Plumes were identified by concurrently elevated
CO and Hg concentrations. Hg/CO emission ratios were calculated from their correlations within the plume. Altogether 69
plumes were identified and the Hg vs CO correlations were significant for 42 of them. Hg/CO emission ratios in plumes over
Equatorial Africa and South America are usually <2.5 pg m-3 ppb-1 which is characteristic for biomass burning. This
conclusion is supported by elevated CH3Cl, CH3Br, and acetonitrile concentrations. Hg/CO emission ratios for plumes over
Far East and South East Asia vary between 2.28 and 18.24 pg m-3 ppb-1 (median 8.04 pg m-3 ppb-1) suggesting sources
ranging from biomass/biofuel burning to urban/industrial, the latter ones with Hg/CO emission ratios usually larger than 5 pg
m-3 ppb-1. Only two plumes were found in other regions: one over Eastern Europe and one over North America.
Conclusions
The results point to biomass/biofuel burning as a substantial mercury source not only in equatorial Africa and South America
but also in Far East and the Indian subcontinent. However, urban/industrial emission, most probably from coal burning and
mercury mining and use is the dominating source in Far East and the Indian subcontinent.
Acknowledgement
This work was supported by the European Commission as a part of the GMOS (Global Mercury Observation System) and by
Fraport AG. We thank Dieter Scharfe, Klaus Koeppel, Stefan Weber, and many others from the CARIBIC team for carrying
out the flights and providing the data.
References
Brenninkmeijer, C.A.M., et al., 2007. Civil aircraft for the regular investigation of the atmosphere based on an instrumented
container: The new CARIBIC system, Atmos. Chem. Phys., 7, 1-24.
Ebinghaus, R., et al., 2007. Emissions of gaseous mercury from biomass burning in South America in 2005 observed during
CARIBIC flights, Geophys. Res. Lett., 34, L08813, doi:10.1029/2006GL028866.
Slemr, F., et al., 2009. Gaseous mercury distribution in the upper troposphere and lower stratosphere observed onboard the
CARIBIC passenger aircraft, Atmos. Chem. Phys. 9, 1957-1969.
75
A SYNERGIC APPROACH FOR PM2.5 SOURCE APPORTIONMENT THROUGH RECEPTOR MODELLING
AND CHEMICAL TRANSPORT MODEL SIMULATIONS
P. Brotto (1)(3), M. C. Bove (1)(3), F. Cassola (1)(3), E. Cuccia (1)(3), D. Massabò (1)(3), A. Mazzino (2)(3) and P. Prati
(1)(3)
(1) Department of Physics & INFN, University of Genoa, via Dodecaneso 33, 16146, Italy; (2) Department of Civil,
Chemical and Environmental Engineering & INFN, University of Genoa, via Montallegro 1, 16145, Italy; (3) PM_TEN srl,
via Dodecaneso 33, 16146, Italy
Presenting author email: brotto@fisica.unige.it
Summary
Receptor Models and Chemical Transport Models are both widely adopted tools in source apportionment studies even if they
require different expertise and are usually used separately. We discuss here the outcomes of an experiment, performed in the
wider frame of the MED-APICE project, in which we used both methods to apportion the main PM2.5 (i.e. Particulate Matter
with aerodynamic diameter lower than 2.5 µm) sources in the urban area of the city of Genoa (Italy). The different
information provided by the two approaches where jointly used to draw a clearer picture of PM2.5 composition and origin
and establishing the basis for a more general methodology.
Introduction
The characterization of emission sources is one of the most important issues with Particulate Matter (PM) pollution even to
assess efficient abatement strategies and verify their effectiveness. Receptor models aim to reconstruct the contribution of
emissions from different sources processing time series of PM compositional values measured at specific monitoring sites.
Positive Matrix Factorization, PMF (Paatero and Tapper, 1994) has rapidly become a reference tool in this research field.
Chemical Transport Models (CTMs) represent instead a different approach widely used for the investigation and assessment
of ambient air quality at various spatial and temporal scales (Pirovano et al., 2012). Source apportionment tools are
implemented in a number of models to help understanding the contributions to specific geographic receptor locations from
particular emission sources, specific model processes, or individual chemical pathways. Receptor models and chemical
transport models are both widely adopted even if rarely with a synergic approach. The research work here described aims to
contribute to this general issue with the outcomes of a field experiment designed to allow a comparison and integration of
receptor models and CTMs.
Methodology and Results
A PM2.5 sampling campaign was carried out collecting daily PM2.5 samples for about six month of year 2011
contemporarily in three sites throughout the urban area of Genoa selected according to the direction of prevailing winds.
Subsequent compositional analyses included the speciation of single elements, major ions and Organic and Elemental Carbon
and produced a large database for receptor modelling through Positive Matrix Factorization. Simulations by the mesoscale
Numerical Weather Prediction (NWP) model WRF (Skamarock, 2008) and the Eulerian CTM CAMx (ENVIRON, 2010)
have been run over the whole monitoring period as well. Through subsequent nesting levels, meteorological and pollutant
concentration fields were obtained up to resolutions of order of 1 km. Source apportionment for PM2.5 was evaluated by
CAMx in the same period of the monitoring campaign through the specific Particulate Source Apportionment Technology
(PSAT) tool. PSAT estimates the contribution from specific emissions source groups, emissions source regions, initial
conditions, and boundary conditions to PM using reactive tracers.
Conclusions
Even if moving from different source categorizations (i.e. groups of time-correlated compounds in PMF vs. activity
categories in CAMx), the PM2.5 source apportionment by PMF and CAMx produced a pretty comparable picture both in
terms of number and impact of sources. Considering both primary and secondary components of PM, the main anthropogenic
sources in the area turned out to be road transport, energy production/industry and maritime emissions, respectively
accounting for 40% - 50%, 20% - 30% and 10% - 15%, of PM2.5.
Acknowledgement
We gratefully acknowledge Regione Liguria and Provincia di Genova for providing an updated emission inventory for the
city of Genoa. Large-scale anthropogenic emission data have been provided by the Aristotle University of Thessaloniki. This
work has been supported by European Program for Territorial Cooperation MED 2007/2013 through the APICE project.
References
ENVIRON, 2010. User's Guide, Comprehensive Air Quality Model with Extensions (CAMx). Version 5.30, ENVIRON
International Corporation, Novato, CA.
Paatero P., Tapper U., 1994. Positive matrix factorization: a non-negative factor model with optimal utilization of error
estimates of data values. Environmetrics 5, 111-126.
Pirovano G., Balzarini A., Bessagnet B., Emery C., Kallos G., Meleux F., Mitsakou C., Nopmongcol U., Riva G.M.,
Yarwood G., 2012. Investigating impacts of chemistry and transport model formulation on model performance at European
scale. Atmos. Environ. 53, 93-109.
Skamarock W.C., Klemp J.B., Dudhia J., Gill D.O., Barker D.M., Huang X.Z., Wang W., Powers J.G., 2008. A Description
of the Advanced Research WRF Version 3, Mesoscale and Microscale Meteorology Division, NCAR, Boulder, Colorado.
76
SOURCE IDENTIFICATION OF TRACE METALS IN URBAN/INDUSTRIAL MIXED SITES OF THE
CANTABRIA REGION (NORTHERN SPAIN)
I. Fernández-Olmo (1), C. Andecochea (1), S. Ruiz (1) and A. Irabien (1)
(1) Department of Chemical Engineering and Inorganic Chemistry, ETSII y T, University of Cantabria, Santander, Spain
Presenting author email: fernandi@unican.es
Summary
This study shows the source identification of trace metals in three urban/industrial mixed sites of the Cantabria region
(Northern Spain) where daily PM10 limit value exceedances were relatively high (more than 35 per year). PM10 samples
were collected over three years in Camargo, Torrelavega and Los Corrales sites and analysed for As, Cd, Cr, Cu, Pb, Ni, Ti,
V, Mo, Mn, Fe, Sb and Zn. Positive Matrix Factorization (PMF) was used to identify the main sources of the studied metals.
The factors obtained from the PMF analysis represent potential emission sources and present a characteristic profile. The
analyses revealed that the main sources at each site are: traffic in Torrelavega, iron foundry and casting industry in Los
Corrales and ferro-manganese alloys industry in Camargo. The other possible sources identified were minor industrial
sources, combustion and traffic mixed with the previous ones.
Introduction
Cantabria is a small coastal region located in the Northern Spain, where the number of exceedances of daily PM10 values in
some areas was higher than that allowed in 2008/50/EC Directive (35 per year). For such reason, local air quality plans have
been developed in three areas of Cantabria: Camargo, Torrelavega and Los Corrales. Those air quality plans should
incorporate at least information related to the origin of the pollution, including the main emission sources. So, the use of
receptor modelling may help in identifying the main pollutant sources in these sites (Reff et al., 2007). Among these
pollutants, trace metals are considered as good tracers of the local sources and therefore they have been chosen in this study.
Methodology and Results
PM10 samples were collected by gravimetric samplers at
the three studied locations by CIMA, which belongs to the
Environmental Department of the Cantabria Government.
These samples were analyzed by ICP-MS after microwave
digestion. In total, 108 samples of airborne PM10 over the
years 2008, 2009 and 2010 were analysed for As, Cd, Cr,
Cu, Pb, Ni, Ti, V, Mo, Mn, Fe, Sb and Zn. PMF3.0 from
EPA was used for the PMF analysis, which is based on a
modified form of preconditioned conjugate gradient
method.
The analysis revealed three potential sources of metals in
the studied sites: the most important factor found in
Barreda (Torrelavega) was associated with high levels of
Cu, Cr and Mo, and its contribution was about 43 %. These
metals are usually associated with the wear of engines and
brakes of vehicles, thus traffic is the source represented by
this factor. Industrial and combustion sources were also
identified in this site. In Los Corrales, the main factor
represents more than 65 % of the metal contribution; it
showed high levels of Fe, Zn and Mn. It was associated
with a local iron foundry and casting plant. Traffic and
combustion sources are less important in this site.
% of species
Conc. of species
(a)
As
Ni
Cd
Pb
Cu
Cr
Ti
Mn
V
Mo
(b)
As
Cd
Ni
Pb Cu
Ti
Mn
V
Mo
Sb
Fe
Zn
Cd
Ni
Pb Cu
Ti
Mn
V
Mo
Sb
Fe
Zn
(c)
As
Fig.1 Main factor profiles from the PMF analysis: (a) Barreda.
(b) Los Corrales. (c) Camargo
Finally, about 40 % of metal contribution in Camargo was associated with a ferro-manganese alloys plant; this factor shows
high levels of Mn and Fe. A minor contribution of traffic, combustion and other industrial sources also arises from the PMF
analysis.
Conclusions
The best PMF models developed in this work were able to associate more than 89% of the metals analysed in the PM
sampled in all receptor points. The analyses revealed the importance of local industrial sources on the levels of trace metals in
the studied sites, mainly in Los Corrales and Camargo; traffic and combustion sources were also important in Torrelavega.
Acknowledgement
This work was supported by the Spanish Ministry of Science and Innovation (CTM2010-16068). The authors also thank the
Regional Environmental Department of the Cantabria Government and CIMA for providing the PM10 samples.
References
Reff A., Eberly S.I., Bhave P.V., 2007. Receptor modeling of ambient particulate matter data using positive matrix
factorization: review of existing methods. Journal of Air and Waste Management Association 57, 146-154.
77
BUILDING AND CONSTRUCTION ACTIVITIES: A SOURCE OF ULTRAFINE PARTICLES?
P. Kumar (1, 2), M. Mulheron (1)
(1) Department of Civil & Environmental Engineering, and (2) Environmental Flow (EnFlo) Research Centre, Faculty of
Engineering & Physical Sciences (FEPS), University of Surrey, Guildford GU2 7XH,
Presenting author email: p.kumar@surrey.ac.uk
Summary
Construction activities are known to produce coarse particulate matter (PM10; <10 µm) as airborne dust. What is less well
understood is if such activities also produce ultrafine particles (UFP; <100 nm in diameter). To investigate this, levels of UFP
arising from three simulated building activities (concrete crushing, impact demolition of concrete slabs, and recycling of
concrete debris) were measured. A fast response differential mobility spectrometer (Cambustion DMS50) was used to
measure particle number concentrations (PNC) and size distributions (PNDs) in the 5–560 nm range at a sampling frequency
of 10 Hz. The measurements were carried out under controlled conditions such that near–steady background PNCs could be
recorded. The sampling point was kept close to the source process. All the activities generated UFP in notable quantities.
Introduction
Over the past 50 years, the rate of growth of the urban population has been significant (2.7% yr-–1) with the total predicted to
reach 5 billion out of the total ~8.3 billion by 2030 (Kumar et al., 2013). Urban development is an inevitable consequence of
this growth and implies the need for both new construction and concurrent demolition or refurbishment activities. Urban
infrastructure is constructed from a complex mixture of construction materials including concrete, metals, ceramics and
plastics. The creation, demolition or refurbishment of such infrastructure requires building activities that are known to
produce PM10, but less is known about the release of fine particles (PM2.5; ≤2.5 µm), and even less regarding the emission of
UFP (Kumar et al., 2012a). Through field and laboratory studies the aims are to investigate the release of UFP dust from
various building activities, understand their physicochemical characteristics, dispersion and transformation behaviour in
outdoor environments, and assess the exposure levels of people working on, passing-by, or living near building activities.
Methodology and Results
The results show a tri–modal particle size distributions for all cases, with
peak diameters in fresh nuclei (<10 nm), nucleation (10–30 nm) and
accumulation (30–300 nm) modes. The measured background size
distributions showed modal peaks at 13 and 49 nm with average
background PNCs ~1.47104 cm–3. These background modal peaks
shifted towards larger sizes during the experiments and the total PNCs
increased between 2-17 times the background. Dry recycling produced
the highest PNCs, followed by impact demolition, wet recycling and then
concrete crushing. The PNDs were converted into particle mass
concentrations (PMCs). Analysis indicated that majority of new PNC and
PMC release was within and over the UFP size range, respectively. The
measured net PNCs (adjusted for background) were comparable with, or
up to an order of magnitude larger than, the levels of PNCs arising from
road–tyre interactions. This suggests that building activities can be a
significant source of UFP dust. Thus field measurements are needed to
study the dispersion of UFP dust into the environment and quantify their
contribution to airborne UFPs and exposure for different groups.
Fig.1 Net release of PNC, after subtracting
background (Kumar et al., 2012b).
Conclusions
The shapes of the PNDs for each activity were distinct. Modal peak analysis indicated relatively fine particles produced by
cube crushing, followed by slab demolition, wet and dry recycling. The results confirm that the majority of particles by
number were in UFP size range. The proportions of particles on a number (<100 nm) and a mass (>100 nm) basis were noted
as ~95, 79, 73 and 90% of total PNCs, and ~71, 92, 93 and 91% of total PMCs, during crushing, impact demolition, “dry”
and “wet” recycling, respectively. The total particle number concentrations during the activities were 2 - 17 times the
background concentrations. The highest UFP contributions came from the ‘dry’ recycling operations and could be suppressed
by the use of water spraying. Comparisons with typical roadside concentrations suggest that, unlike concrete crushing, the
other three process produce ~1.4, 5.3 and 6.6 times larger concentrations close to the source when in continuous operation.
Acknowledgement
Authors thank P. Kunapalan, F. Auckland, T. Pagkalis and R. Packiyarajah for their help during the laboratory experiments.
References
Kumar, P., Mulheron, M., Fisher, B., Harrison, R.M., 2012a. New Directions: Airborne ultrafine particle dust from building
activities - a source in need of quantification. Atmospheric Environment 56, 262-264.
Kumar, P., Mulheron, M., Som, C., 2012b. Release of ultrafine particles from three simulated building processes. Journal of
Nanoparticle Research 14, 771, doi: 10.1007/s11051-012-0771-2.
Kumar, P., Jain, S., Gurjar, B.R., Sharma, P., Khare, M., Morawska, L., Britter, R., 2013. New Directions: Can a “Blue Sky”
return to Indian megacities? Atmospheric Environment 71, 1-4.
78
HIGHLY TIME- AND SIZE-RESOLVED MEASUREMENTS OF TRACE ELEMENTS DURING CLEARFLO,
LONDON
S. Visser (1), M. Furger (1), U. Flechsig (2), K. Appel (3*), R. Dressler (4), P. Zotter (1), J. G. Slowik (1), A. S. H. Prevot (1),
U. Baltensperger (1)
(1) Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
(2) Swiss Light Source, Paul Scherrer Institute, Villigen PSI, Switzerland
(3) DESY Photon Science, Hamburg, Germany; * now: European XFEL, Hamburg, Germany
(4) Laboratory of Radiochemistry and Environmental Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
Presenting author email: suzanne.visser@psi.ch
Summary
The identification and quantification of particle sources has long proven challenging due to the complex composition of
ambient aerosol. Measurements of trace elements provide unique source-specific information; e.g. barium and copper are
emitted by traffic sources, while vanadium and nickel are linked to heavy oil combustion. Here we present highly time- and
size-resolved measurements of trace elements as part of the ClearfLo (Clean Air for London) 2012 field campaign, a
multinational collaborative effort to investigate boundary layer pollution in and around London, UK.
Introduction
The power of source apportionment by trace elemental analysis is greatly enhanced by simultaneous measurements of
complementary aerosol species. Optimization of trace elemental data requires measurements with sufficient temporal
resolution to distinguish sources with different characteristic diurnal patterns such as traffic and sea salt, while size-resolved
measurements can help identify different source classes with similar composition, e.g. iron from resuspension appears in
coarse mode particles while brake wear processes appear in the fine mode.
Methodology and Results
Sampling was performed at several sites in and around London
during two Intensive Observation Periods (IOPs) in 2012. During the
winter IOP particulate matter was sampled at a site with heavy traffic
(Marylebone Road, MR) and an urban background site (North
Kensington, NK) in London, and at a rural site in Detling, southeast
of London. The summer IOP embraced the Olympic Games, and
sampling took place at the two London sites. Rotating drum
impactors (RDIs) collected particles in the three size bins PM10-2.5,
PM2.5-1.0 and PM1.0-0.1 with a high time resolution of only 2 h
(Bukowiecki et al., 2005). The elemental composition of the samples
was analysed by synchrotron radiation induced X-ray fluorescence
spectrometry (SR-XRF) at the Swiss Light Source (Paul Scherrer
Institute, CH) and at HASYLAB (Deutsches ElektronenSynchrotron, DE). The RDI SR-XRF setup provides quantification of
elements with atomic numbers 11 (sodium) to 82 (lead) with a
detection limit close to a few pg (Richard et al., 2010). Fig. 1 shows
the median diurnal variations of selected elements in PM10-2.5 (ng m3) during the winter IOP. The rush hour peaks for iron (Fe) and
barium (Ba) (top panel) are commonly observed in a street canyon
with stop-and-go traffic. Ba is typically related to brake wear (e.g.
Furusjö et al., 2007) and elevated concentrations are thus likely at
such a site (Ba at NK was below detection limit). Elevated
concentrations during daytime for mineral dust elements like
aluminium (Al) and calcium (Ca) (centre panel) occur from
continuous resuspension at MR. NK shows lower levels due to
dilution of air during transport from the traffic to the urban
background site. Rather constant values were observed for e.g.
sodium (Na) and magnesium (Mg) (bottom panel). These sea salt tracers
are likely advected throughout the day, but the elevated values at MR
indicate local emissions as well.
Fig. 1 Median diurnal variations of PM10-2.5 trace elements
(ng m-3) separated into three suggested source categories for a
heavy traffic (MR) and an urban background (NK) site during
ClearfLo 2012, winter IOP
Conclusions
Emission sources with characteristic diurnal patterns are identified with highly time- and size-resolved measurements of trace
elements in London. Correlations with e.g. black carbon, nitrogen oxides and meteorological conditions will enhance the
source separation of the trace elements.
Acknowledgement
This work was funded by the ClearfLo project (NERC grant NE/H00324X/1), the Swiss National Science Foundation (grant 200021_132467
/1) and the European Community’s Seventh Framework Programme (FP7/2007-2013, grant n°312284).
References
Bukowiecki, N. et al., 2005. Environ. Sci. Technol. 39, 5754-5762.
Furusjö, E. et al., 2007. Sci. Total Environ. 387, 206-219.
Richard, A. et al., 2010. Atmos. Meas. Tech. 3, 1473-1485.
79
POLYCYCLIC AROMATIC HYDROCARBONS IN PM1: SEASONAL CHANGES AND SOURCES
IDENTIFICATION USING DIAGNOSTIC RATIOS
D. M. Agudelo-Castañeda (1). E. C. Teixeira (1,2), and H. Silveira (2)
(1) Postgraduate Program in Remote Sensing and Meteorology, Geosciences Institute, Universidade Federal do Rio Grande
do Sul, Av. Bento Gonçalves, 9500, 91501-970, Porto Alegre, RS, Brazil; (2) Research Department, Fundação Estadual de
Proteção Ambiental Henrique Luis Roessler, Rua Borges de Medeiros 261, Porto Alegre, RS, Brazil
Presenting author email: dayanam25@gmail.com
Summary
Samples of PM1 were collected on PTFE filters in the metropolitan area of Porto Alegre, in the sampling period: august
2011-march 2013. The study area has a large number of vehicles in circulation, which use a variety of fuels, especially
gasoline, diesel (5% biodiesel) and flex. PM1 samples were extracted and analyzed 16 polycyclic aromatic hydrocarbons
(PAHs) using gas chromatography coupled to mass spectrometry (GC-MS) according to the methodology U.S. EPA TO-13A.
The objective of this study was to analyze the seasonal changes and identify the emission sources of PAHs in PM1. In winter
the total PAHs concentrations were higher than in summer, with a reason winter / summer of ≈1.68 in the study area, thus
showing their seasonal variation. The analysis of emission sources was performed by applying the analysis of diagnostic
ratios concentration of PAHs. Results showed contributions from mobile sources (gasoline and diesel), especially for diesel
emissions. Also wood combustion, lubricant oils and fossil fuels. Further studies will be performed to apply receptor models
to know the contribution of each source.
Introduction
PAHs are organic compounds of carbon and hydrogen found in the atmosphere and formed during the incomplete
combustion and pyrolysis of organic matter, such as coal, oil, wood, gasoline, diesel, between others. PAHs are highly
dependent of the particles size and the highest concentrations are found in the finest fraction. Some PAHs are carcinogens
and some are associated with acute and chronic health problems. Automobile exhaust has been recognised as the major PAH
contributor in urban areas. Thus, the objective of this study was to analyze the seasonal changes and identify the emission
sources of PAHs in PM1.
Methodology and Results
PM1 was sampled for 72-h over the sampling period: august 2011–march 2013 using PTFE filters (47 mm diameter).
Sequential automatic sampler for particulate matter PM162M (16.7 L·min-1) equipped with a PM1 size selective inlet was
employed in the two sampling sites: Sapucaia do Sul and Canoas in south Brazil. The study area is characterized by different
industries and has a large number of vehicles in circulation, which use a variety of fuels, especially gasoline, diesel (5%
biodiesel) and flex. 16 PAHs were analyzed according to EPA method TO-13A. The filters containing PM1 samples were
extracted with dichloromethane in Soxhlet and the extracts were later analyzed in a gaseous chromatograph coupled to a mass
spectrometer (GS/MS). Napthalene (Nap), acenaphthene (Ace), acenaphthylene (Acy), fluorene (Flu), phenanthrene (Phe),
anthracene (Ant), fluoranthene (Flt), pyrene (Pyr), benzo[a]anthracene (BaA), chrysene (Chry), benzo[b+k]fluoranthene
(BbkF), benzo[a]pyrene (BaP), indeno[1,2,3-cd]pyrene (Ipyr), dibenzo[a,h]anthracene (DahA), benzo[ghi]perylene (BghiP)
were analyzed. The mean total PAH concentration was 0.91 ng·m-3 (summer) and 1.30 ng·m-3 (winter) in Canoas; and 1.17
ng·m-3 (summer) and 2.26 ng·m-3 (winter) in Sapucaia do Sul. Total PAHs mean concentrations were higher in winter and
Student’s t-test for equal means was applied, showing significant differences. The winter total PAHs mean concentration
were 1.93 times higher in Sapucaia do Sul than Canoas and 1.42 times in summer. Moreover, high molecular weight PAHs
(BghiP, DahA, Ipyr, BaP and BbkF) showed the highest concentration profile values in both sites. This seasonal trend
observed in this study has been reported in several works of measurements of PAHs associated to atmospheric particles in
urban sites. Diagnostic ratios were used to identify PAHs sources: Flu/(Flu+Pyr), [Flt/(Flt+Pyr)], [IPyr/(IPyr+BghiP)],
[BaA/( BaA+Chry)], [Phe/(Phe+Ant)], [BaP/BghiP], [BaP/(BaP+Chry)], [Flu/(Flu+Pyr)]. This analysis showed that PAHs in
PM1 sources were principally diesel and gasoline emissions. Also wood combustion, lubricant oils and fossil fuels were
found as sources.
Conclusions
PAHs associated to PM1 concentrations were significantly
higher in winter than in summer for the study area, thus
showing a seasonal trend. High molecular weight PAHs
(BghiP, DahA, Ipyr, BaP and BbkF) showed the highest
concentration profile values. Diagnostic ratios analysis
confirmed that diesel and gasoline emissions were PAHs
sources, also wood combustion, lubricant oils and fossil
fuels.
Gasoline Wood Coal/
coke
1.00
IPyr/(IPyr + BghiP)
0.90
Sapucaia
Canoas
Diesel
0.80
0.70
0.60
0.50
Wood
Diesel
Coal
0.40
0.30
0.20
0.10
0.00
0.00
Acknowledgement
The authors are grateful to FAPERGS and CNPq for their
financial support.
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
BaA/(BaA+Chry)
References
Saarnio, K.; Sillanpaa, M.; Hillamo, R.; Sandell, E.; Pennanen, A.; Salonen, R. 2008. Polycyclic aromatic hydrocarbons in
size-segregated particulate matter from six urban sites in Europe. Atmospheric Environment 42, 9087-9097.
80
MOBILE MONITORING OF AIR QUALITY IN THE CITY OF ROTTERDAM
M. H. Voogt (1), P. J. van der Mark (1), A. R. A. Eijk (1), P. van Breugel (2)
(1) TNO, P.O. 80015, 3508 TA Utrecht, The Netherlands; (2) DCMR, Environmental Protection Agency Rijnmond,
P.O. 843, 3100 AV Schiedam, The Netherlands
Presenting author email: marita.voogt@tno.nl
Summary
In winter 2013 a pilot project was performed to investigate whether 1) it is technically feasible to measure air quality using a
public transport vehicle as a mobile platform and 2) mobile monitoring of air quality has added value to policy makers
(complementary to the fixed monitoring network). During 1,5 month a mobile monitoring device (DUVAS D1000) was
mounted on a tram in the city of Rotterdam. The instrument turned out to be able to measure concentrations of NO and GPS
coordinates with sufficient accuracy and temporal resolution. Combining the mobile measurements with urban background
measurements in a GIS, resulted in maps showing average local contributions to the concentration of NO along the tram
routes. In this way, insight in spatial variation within a city is significantly enhanced with only a limited number of
instruments. The collected information is helpful to policy makers in several ways: e.g. tracing local hot spots, monitoring the
effectiveness of measures and trends in real world vehicle park emissions and increasing public awareness and involvement.
Introduction
Recently, the potential of mobile monitoring of air quality has been investigated in some pilot and
research projects e.g. using a bicycle (Elen et al., 2012) or public transport (e.g. Saukh et al., 2013).
This innovative way of monitoring air quality goes beyond monitoring in the framework of EU
regulations (assessing compliances with limit values). Other devices need to be used that fit the
requirements for mounting them on vehicles. Low cost sensors are upcoming, although the quality
of these sensors is often not yet good enough. The added value of mobile monitoring to policy
makers is subject of this pilot study.
Methodology and Results
During 1,5 month a mobile monitoring device was mounted on a tram in the city of Rotterdam. We
used a DUVAS D1000 UV spectrometer that has been especially developed for mobile
applications. Its size allows mounting on a tram and the gases it measures are indicators for
pollution by local traffic (NO and NO2). The instrument turned out to be able to measure
concentrations of NO and GPS coordinates with sufficient accuracy and temporal resolution (with
a 10 sec rolling average the detection limit for NO was 3 ppb). For accurate measurements of NO2,
the instrument needs (and will get) further development.
In a GIS measured concentration data were assigned to predefined 100 m tracks of
the tram routes and the averages for the tracks were calculated. To get a realistic
visualisation of the spatial variation, it turned out to be necessary to correct the
mobile data for the variation in the urban background level of NO. For this
normalisation, we used real time monitoring data of the fixed monitoring network.
The map in Fig.2 shows average local contributions to the concentration of NO
along the tram routes. NO “hot spots” and “low spots” can be detected, indicating
locations
either
with
more/fewer
emissions
or
streets
with
favourable/unfavourable dispersion circumstances.
Conclusions
The DUVAS D1000 instrument proved to perform well with respect to the NO
and GPS measurements. The strength of mobile monitoring on a tram is that over
a certain period, a high number of data points is acquired since the tram passes
predefined routes many times. This results in reliable estimates of the average
concentration. In this way, insight in spatial variation within a city is significantly
enhanced with only a limited number of instruments. The collected information is
helpful to policy makers for tracing local hot spots and deciding on measures to
improve air quality and monitoring their effectiveness. Also, trends in real world
vehicle park emissions over a longer period can be monitored. Finally, public
awareness and involvement can be increased and the mobile data collection
platform can be extended to deliver air quality and other information (temperature
etc.) for smart city related services.
Fig.1 Mounting of the
instrument on the tram
Fig.2 Visualisation of monitoring data
Acknowledgement
This work was supported by the City Region of Rotterdam and partly funded by TNO. We further acknowledge the RET
(regional public transport company) for their cooperation.
References
Elen, B. et al., 2013. The Aeroflex: A Bicycle for Mobile Air Quality Measurements. Sensors, 13, 221-240.
Saukh O., Hasenfratz D., Thiele L., 2013. Route Selection for Mobile Sensor Nodes on Public Transport Networks. Accepted
by Journal of Ambient Intelligence and Humanized Computing (Springer).
81
NEAR-ROAD PARTICLE NUMBER CONCENTRATIONS IN KUWAIT DURING SUMMERTIME
A. N. Al-Dabbous (1), P. Kumar (1) (2)
(1) Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Science (FEPS), University of
Surrey, Guildford, Surrey, GU2 7XH, United Kingdom; (2) Environmental Flow (EnFlo), FEPS University of Surrey,
Guildford, Surrey, GU2 7XH, United Kingdom
Presenting author email: a.aldabbous@surrey.ac.uk
Summary
The aim of this study is to understand the behaviour of particle number concentration (PNCs) and distributions (PNDs) in the
range of 5-1000nm during summertime climatic conditions in Kuwait. The measured PNDs showed a large nucleation mode
at around 12nm, exhibiting majority (80.5%) of the total PNCs below 30nm. Negligible PNCs (~0.5%) were observed above
300nm, leaving only ~19% between 30 and 300nm range. The highest daily average PNC in the 5-1000 nm range was found
as 1.11105 cm-3 which is much larger than those found along roadside studies in European environments (see, for example,
Kumar et al., 2010). The results presented here are based on the analysis of 8 days of data out of continuously collected one
month long recent experimental campaign. Rest of the data is currently under analysis.
Introduction
Airborne nanoparticles (referred to those below 300nm to represent majority of PNCs) have attracted the scientific
community, decision makers and planners attention due to their possible adverse impact on human health and the
environment (Kumar et al., 2010). Road traffic is considered to be one of the main anthropogenic sources of nanoparticles.
The metrological conditions have a strong effect on the dispersion of nanoparticles, but how do these particles behave in hot,
dry and dusty environments are nearly known. For the first time, this study presents the nanoparticle measurements in any
Middle-East country to understand their emission and dispersion behaviour under the novel meteorological conditions.
Methodology and Results
Particles measurement program was perpetuated in the State of
Kuwait for a period of one month, starting from 27 may 2013. Fast
response differential mobility spectrometer (Cambustion DMS500)
was employed near a major highway in Kuwait in order to collect
particle number and distribution data in the 5-10000nm range at a
sampling frequency of 1 Hz. Meteorological and primary pollutant
data were obtained from Kuwait Environmental Public Authority
fixed station (EPA) for the same period. In parallel, PM10 and VOC
samples were also collected and analysed (data not shown). The
average wind speed (WS), temperature (T) and relative humidity
(RH) during the analysed days was found to be 5.36±1.4m s-1,
35±1.9oC and 15±2.5%, respectively. The average traffic on the road
was ~4350 vehicles per hour. Traffic was dominated by gasoline
cars that contributed ~83% of the total vehicles. PNDs showed a
large peak in the nucleation mode particles at around 12nm along
with two minor modes at around 65nm and 150nm (see Fig.1).
Given the dominance of gasoline driven vehicles in the vehicle fleet,
a noticeable peak at ~12nm was expected. Total PNCs varied in the
range 0.70-1.11×105 cm-3 (see Fig.2). PNC in the 5-30nm range
found to dominate (80.5%) the total PNCs, followed by particles in
the 30-300 and 300-1000nm range with 19 and 0.5%, respectively.
Conclusions
Our preliminary results have shown relatively larger PNCs in hot and arid climate of Kuwait compared with what is generally
observed by studies in European environments. Unlike other freeway studies which had two dominant peaks at ~12 and 30nm
(e.g., Zhu et al., 2002), the PNDs demonstrated a large peak at ~12nm due to the dominance of gasoline vehicles and much
lower heavy duty vehicles. Particles below 100 nm dominated (~93%) the total PNCs. Here, initial finding for eight days are
illustrated. Detailed analysis is currently under progress and thus may lead to new findings.
Acknowledgement
Abdullah Al-Dabbous greatly acknowledges the Kuwait Institute for Scientific Research (KISR) for supporting this PhD
research. Thanks also to Kuwait EPA for providing the meteorological and gaseous pollutant data.
References
Kumar, P., Robins, A., Vardoulakis, S., Britter, R., 2010. A review of the characteristics of nanoparticles in the urban
atmosphere and the prospects for developing regulatory controls. Atmospheric Environment 44, 5035-5052.
Agus, E.L., Young, D.T., Lingard, J.J.N., Smalley, R.J., Tate, J.E., Goodman, P.S., Tomlin, A.S., 2007. Factors influencing
particle number concentrations, size distributions and modal parameters at a roof-level and roadside site in Leicester, UK.
Science of the Total Environment 386, 65-82.
82
MULTIPLE CH4 SOURCE IDENTIFICATION FOR A BIOGAS PLANT
M. Piringer (1), M. Hrad (2) and M. Huber-Humer (2)
(1) Department of Environmental Meteorology, Central Institute for Meteorology and Geodynamics, A-1190 Vienna,
Austria; (2) Institute of Waste Management, BOKU University, A-1190 Vienna, Austria
Presenting author email: martin.piringer@zamg.ac.at
Summary
For a biogas plant NW of Vienna, Austria, CH4 source identification was undertaken by a combination of an Optical Remote
Sensing Technique and a Lagrangian dispersion model resolving the complex building structure and incorporating different
kinds of sources. For six experimental days with different meteorological conditions, the individual and total recovery ratios
were calculated and interpreted with respect to the condition number and meteorological parameters. Source strength
identification works best for higher emissions, larger wind speeds and neutral atmospheric stability.
Introduction
Greenhouse gas emissions and methane losses can arise from diverse parts of biogas facilities along the entire process chain
of biogas generation and utilization. We try to quantify such emissions and losses in the frame of an on-going research
project by combining an Optical Remote Sensing (ORS) technology (OP-TDLS) to detect the spatial and temporal behaviour
of the plumes and Lagrange dispersion modelling to re-construct the emissions using an inverse dispersion technique.
Methodology and Results
The application of the method for a multi-source problem as in the current case is done with a set of linear equations as
described in detail in Flesch et al. (2009) which requires at least as many concentration paths as sources. For two emission
rates Q1 and Q2 and two receptors A and B, the appropriate equation in matrix notation is
 (CA,1 / Q1) sim (CA, 2 / Q 2 ) sim   Q1   CA 
(CB ,1 / Q1) sim (CB , 2 / Q 2 ) sim  Q 2   CB 
(1)
We use two measures to quantify the performance of source identification. The so-called condition number κ is a measure of
“ill-conditioning”, i.e. if the solution is extremely sensitive to changes in the input data (measurements or model estimates).
According to Flesch et al. (2009), source decomposition is possible if 10 < κ < 20; for the total emission of all sources, κ <
50. The accuracy of the emission calculations is measured as so-called
gas recovery ratio R, definable for each source (Ri) as well as for the
sum of sources (Rtotal) investigated (total recovery ratio). A perfect
calculation gives R = 1.
Source identification was tried for six selected days with variable
meteorological conditions. Of all meteorological parameters
investigated, the dependence of the condition number on wind speed is
strongest and given here as an example of the results achieved: large
condition numbers indicating uncertainty in recovering the sources are
found for wind speeds below 4 ms-1 only (Fig. 1). The latter are mainly
associated with two experimental days on which wind speeds were
lowest on average.
Figure 5: Dependence of the condition number κ on
wind speed for all experimental days
More results will be presented at the conference.
Conclusions
The algorithm of source strength identification is based on investigations by Flesch et al. (2009) and was applied here for
real-world case studies. The results are satisfactory for the six days selected for the investigation which are characterized by a
large variety of wind directions, wind speeds and stability conditions.
Acknowledgement
These investigations were part of the research project “KLIMONEFF”, which was funded by the Austrian “Klima- und
Energiefonds – Neue Energien 2020”.
Reference
Flesch, Th. K., L. A. Harper, R. I. Desjardins, Z. Gao, Z. and B. P. Crenna, 2009: Multi-source emission determination using
an inverse-dispersion technique. Boundary-Layer Meteorol., 132, 11-30.
83
MONITORING OUTDOOR AIR PARTICLE CONCENTRATIONS WITH THE PPS-M SENSOR
A. Järvinen (1), H. Kuuluvainen (1), A. Rostedt (1), J. V. Niemi (2), L. Pirjola (3), R. Hillamo (4), J. Keskinen (1) and T.
Rönkkö (1)
(1) Aerosol Physics Laboratory, Tampere University of Technology, P.O. Box 692, FI-33101, Tampere, Finland;
(2) Helsinki Region Environmental Services Authority (HSY), P.O. Box 100, FI-00066 HSY, Finland;
(3) Department of Technology, Metropolia University of Applied Sciences, Kalevankatu 43, FI-00180 Helsinki, Finland;
(4) Air Quality, Finnish Meteorological Institute, Erik Palménin aukio 1, FI-00560 Helsinki, Finland;
Presenting author email: anssi.jarvinen@tut.fi
Summary
In this study the capability of the Pegasor PPS-M particle sensor for outdoor air monitoring was tested in urban environment.
A good correlation with the lung deposited surface area concentration was observed. Correlation with PM2.5 was found to be
lower because the signal is weighted toward smaller particle sizes. The PPS-M was found to be especially suitable for
monitoring vehicle based particle emissions in outdoor air.
Results
The PPS-M signal was found to correlate well with the total current of the ELPI. The PPS-M
signal was 0.27 times the ELPI total current in both stationary measurements stations. A good
correlation with the lung deposited surface area concentration (NSAM) was also observed, see
Fig. 1. The correlation with PM2.5 was found to be lower. Depending on the environment, the
PPS-M response to PM2.5 was between 7-30 fA/(μg m-3). The variation was caused by
differences in aerosol i.e. the mean particle size affect the response. Thus the sensor response
is not directly proportional to the particle mass but to a metric close to lung deposited surface
area concentration. The PPS-M required practically no maintenance during over 2 week
measurements.
PPS current (fA)
1500
1500
y=0.27*x
1000
500
0
0
2000
4000
6000
ELPI total current (fA)
y=5.9*x
1000
500
0
0
50
100 150
200
250
NSAM LDSA (m2/cm3)
PPS current (fA)
Experimental
The PPS-M sensor was used to measure particle concentrations in three different
environments in Helsinki area: (1) Stationary measurement in residential area, (2) Stationary
measurement close to a major road, (3) On board a mobile laboratory in Helsinki city centre.
The PPS-M signal was compared to reference data including PM2.5, NOx, ELPI total current,
CPC number concentration and NSAM lung deposited surface area concentration. The sensor
was installed inside measurement stations or inside the mobile laboratory and it was sampling
outdoor air without any preconditioning. The sampling rate of 1 Hz was used for the PPS-M
(100 Hz maximum), the ELPI and the NSAM.
PPS current (fA)
Introduction
The most important motivation for air quality monitoring is the health effects of air pollutants. Outdoor air quality is typically
analysed by measuring particle mass: PM10 and PM2.5 or gas concentrations: NO, NO2, SO2 and O3. However, in case of
particles, it has been proposed that these mass based quantities PM10 and PM2.5 would not be the best metric to describe the
health effects. The monitoring of particle surface area concentration (e.g. Oberdörster, 2001) has been indicated to correlate
better with the hazardous effects of particulate matter than the monitoring of particulate mass concentration or number
concentration, although the discussion related to topic is still continuing. The real time measurement of surface area requires
different instruments than the PM measurement. The diffusion charging and electrical measurement produces a signal which
is well proportional to the lung deposited surface area concentration (Fissan et al. 2007). The Pegasor PPS-M sensor is based
on this type of construction. The sensor uses compressed air which is ionized and used to charge particles. This flow is also
used to generate the sample flow through the device. The electric measurement signal is generated when the unipolarly
charged particles are extracted from the sensor by the flow, principle introduced by Lehtimäki (1983).
1500
y=30*x
1000
500
0
0
10
20
30
40
PM2.5 (g/m3)
Fig.1 The PPS-M response
to reference instruments in
measurement site 2 (close to
a major road). Each point
represents 1 h average.
Acknowledgement
This work was supported by CLEEN Ltd., the Cluster for Energy and Environment through the Measurement, Monitoring
and Environmental Assessment (MMEA) research program.
References
Fissan H., Neumann S., Trampe A., Pui D.Y.H., Shin W.G., 2007. Rationale and principle of an instrument measuring lung
deposited nanoparticle surface area. Journal of Nanoparticle Research 9, 53-59.
Lehtimäki M., 1983. Modified Electrical Aerosol Detector in Aerosols in the Mining and Industrial Work Environments,
Vol. 3, Marple, V.A. and Liu, B.Y.H. (Eds.), Ann Arbor Science Publishers, Ann Arbor, 1135-1143.
Oberdörster G., 2001. Pulmonary effects of inhaled ultrafine particles. International Archives of Occupational and
Environmental Health 74, 1-8.
84
REAL-TIME MEASUREMENTS OF BIOAEROSOLS IN URBAN ENVIRONMENT
S. Saari (1), J. V. Niemi (2), T. Rönkkö (1), H. Kuuluvainen (1), A. Järvinen (1), L. Pirjola (3), R. Hillamo (4), J. Keskinen (1)
(1) Department of Physics, Tampere University of Technology, P.O. Box 692, FI-33101 Tampere, Finland; (2) Helsinki
Region Environmental Services Authority (HSY), P.O. Box 100, FI-00066 HSY, Finland; (3) Department of Technology,
Metropolia University of Applied Science, Kalevankatu 43, FI-00180 Helsinki, Finland; (4)Air Quality, Finnish
Meteorological Institute, Erik Palménin aukio 1, FI-00560 Helsinki, Finland
Presenting author email: sampo.saari@tut.fi
Summary
This study aims to determine health risks and climatic relevance of bioaerosols in urban environment. Two fluorescence
based real-time instruments were used to measure bioaerosol concentrations and size distributions during winter, spring,
summer and autumn. Supporting PM2.5, PM10, NOx and meteorological data were utilized to estimate bioaerosol sources.
The results showed that there were typically two fluorescent particle modes in urban environment. The modes are probably
originating from fungal spores and bacteria. The concentrations and ratio of the fluorescent particle modes varied between the
seasons. Strong diurnal variation in the fluorescent particle concentrations indicates that local sources are significant in urban
environment. Guidelines for bioaerosol concentration limits in outdoor environment do not exist yet, mainly due to limitation
of the data.
Introduction
Bioaerosols such as bacteria and fungal spores can cause adverse health effects for people and animals both in indoor and
outdoor environments. Atmospheric bioaerosols have been recognized to have important influence in the climate acting as
CCN (Cloud Condensation Nuclei) and IN (Ice Nuclei) and thus contribute cloud formation and precipitation processes.
Information of concentrations, particle size distributions and sources of bioaerosols is needed to estimate their health risks
and climatic relevance. In urban environment, bioaerosol sources are close to people and population is typically dense, thus
health risks are especially high there. However, only few source-tracked bioaerosol studies have been made in urban
environment.
The results showed that there were typically two fluorescent particle
modes during the all seasons, except in the winter, when only one mode
was detected. We assume that the modes are mainly originating from
fungal spores and bacteria. The concentrations and ratio of the
fluorescent particle modes varied between the season periods.
Sometimes there was strong diurnal variation in the fluorescent particle
concentrations (Fig. 1), which is indication of significant local sources.
We found also that the BioScout had much higher fluorescent particle
counting efficiency than the UV-APS. This is consistent with our
laboratory results.
0
10
N [#/cm3]
Methodology and Results
LIF (Laser Induced Fluorescence) based instruments are modern tools
for real-time bioaerosol detection (Saari et al., 2013a; 2013b). In this
study, we used two LIF based real-time instruments, the BioScout
(developed at TUT, manufactured by Environics Ltd.) and the UVAPS
(TSI Inc.), to study bioaerosol concentrations and size distributions in
urban environment at Helsinki region during winter, spring, summer
and autumn. Real-time LIF data combined with PM2.5, PM10, NOx
and meteorological data enables also to estimate bioaerosol sources.
-2
10
FL >1µm
ALL >1µm
24/10 26/10 28/10 30/10 01/11
Date
Fig.1 Real-time data of the fluorescent and total
particle concentrations measured by the BioScout.
Conclusions
Two LIF based real-time instruments were used to observe bioaerosols in urban environment. Preliminary results of outdoor
measurements are promising. Real-time LIF technique seems to be suitable for atmospheric bioaerosol detection, but there
are still many questions to answer and work to do. Investigation of the emission sources and transportation of bioaerosols
needs meteorological data analysis and long term measurements with several instruments in various environments.
Guidelines for bioaerosol concentration limits in urban environment have not progressed yet and the main reason is limitation
of the data.
Acknowledgement
This work was supported by the Cluster for Energy and Environment (CLEEN Ltd) Measurement, Monitoring and
Environmental Assessment (MMEA) Work package 4.5.2.
References
Saari S., Putkiranta M., Keskinen J., 2013a. Fluorescence spectroscopy of atmospherically relevant bacterial and fungal
spores and potential interferences. Atm. Environment, 71, 202-209
Saari S., Reponen T., Keskinen J., 2013b. Performance of violet diode laser induced fluorescence based real-time bioaerosol
detector. Submitted to Aerosol Sci. & Technology
85
QUANTIFICATION OF ORGANIC, ELEMENTAL AND BLACK CARBON IN THE RUHR AREA, GERMANY
M. Küpper (1), U. Quass (1), H. Kaminski (1), A. John (1), T. A. J. Kuhlbusch (1), S. Leinert (2), J. Geiger (2), L. Breuer (2),
D. Gladtke (2), A. Olschewski (2), T. J. Schuck and U. Pfeffer (2)
(1) Institute of Energy and Environmental Technology e.V. (IUTA), Duisburg, Germany; (2) North Rhine-Westphalian State
Agency for Nature, Environment and Consumer Protection, Essen, Germany
Presenting author email: kuepper@iuta.de
Summary
In this recently started study, two methods for carbon quantification in particulate matter (PM) are tested in terms of their
convenience for quantification of carbon species emitted by biomass burning processes and traffic emissions: thermal
analysis of elemental carbon (EC) and organic carbon (OC) as well as the optical determination of black carbon (BC)
concentrations with multiple-wavelength aethalometers. Initial intercomparison of the new aethalometer devices has shown
good agreement with slopes and regression coefficients close to one. Preliminary operation of the instruments at different
sites (urban background and traffic) showed different BC levels with substantial temporal co-variation.
Introduction
Increased concentrations of PM in ambient air are commonly known to be associated with adverse health effects. Due to its
carcinogenicity (e.g. WHO, 2012) and its ubiquitous emission, rising attention has been given to diesel soot during the last
decades. However, in industrialized countries an increase in contributions from biomass burning to the PM burden, most
notably caused by the introduction of low emission zones as well as by the prevalent use of stoves and fireplaces, has been
observed recently. This tendency is also valid within the Ruhr area (e.g. Pfeffer et al., 2013). Therefore, determining the
portion of both types of emissions, those from biomass burning and traffic emissions, in PM seems to be necessary to guide
appropriate mitigation strategies. Recently developed aethalometer devices take advantage of the dependency between
wavelength and the measured attenuation, which differs for the carbon species from different sources. Based on this
principle, several algorithms for aethalometer data permitting the discrimination of BC deriving from biomass burning from
BC emitted by traffic have been developed (e.g. Sandradewi et al., 2008). In this study the just described measurement
technique as well as thermal EC/OC measurements will be applied in order to determine the contribution of the different
carbon species emitted by biomass burning and traffic.
Methodology and Results
In total, a measurement period of 16 month starting by the 30th
of August 2013 was chosen to detect seasonal variations,
particularly with regard to the shift in carbon composition
evoked during the heating period. The measurements are
performed at two monitoring sites of the ambient air quality
monitoring network in North Rhine-Westphalia - a traffic site
(Duisburg) and an urban background site (Mülheim).
Aethalometers (model AE-33, Magee Scientific, Ljubljana,
Slovenia) measuring the attenuation at 7 different wavelengths
are run at each site. For comparison, EC/OC-analyses will be
performed applying the temperature protocols NIOSH 870 and
Fig.1 BC concentrations at both sites measured in 2013
EUSAAR-2. In total, 150 filters from both sites will be
analysed with the Sunset Dual-Optical Laboratory Carbon Analyser (Sunset Laboratory Inc., Tigard, USA). Correlation of
BC, EC and OC with continuously measured data, such as PM10, NO2, NO, NOx, and meteorological data as well as with
levoglucosan (a tracer substance for biomass burning in PM) and benzo(a)pyrene will be tested. Initial comparative
measurements indicated the BC concentrations stated by the two different aethalometer devices to be in good agreement.
Particularly, when both devices were connected to the same gas sampling unit and run for 5 days deviation varied between
5.7 and 3.7 % for different wavelengths. First aethalometer measurements at the two sites revealed distinct parallels in
changes of BC concentrations over time (see Fig.1) despite quite unequal local environments and approximately 6.5 km
linear distance between both sites. However, since the campaign just started, this might only be a temporary trend.
Conclusions
Based on our measurements (by March 2014 much more data will be available) it will be possible to evaluate the suitability
of both measurement techniques for monitoring the share of emissions from biomass combustion and traffic emissions in PM.
In case of good correlation, the substitution of the work intense filter analyses for EC/OC by BC measurements with
aethalometers might even be considered with regard to future standardized measurements of ambient air quality networks.
References
Pfeffer U., Breuer L., Gladtke D., Schuck T.J., 2013. Contribution of wood burning to the exceedance of PM10 limit values
in North Rhine-Westphalia. Gefahrstoffe - Reinhalt. Luft 73, 239-245.
WHO, 2012: Health Effects of Black Carbon. Redaktion: Janssen N.A.H., Gerlofs-Nijland M.E., Lanki T., Salonen R.O.,
Cassee F., Hoek G., Fischer P., Brunekreef B., Krzyzanowski M. - ISBN 978 92 890 0265 3.
Sandradewi J., Prévôt A.S.H., Szidat S., Perron N., Alfarra M.R., Lanz V.A., Weingartner E., Baltensperger U., 2008. Using
aerosol light absorption measurements for the quantitative determination of wood burning and traffic emission contributions
to particulate matter. Environ. Sci. Technol. 42, 3316-3323.
86
CHARACTERIZATION OF SOURCES AND PROCESSES OF ORGANIC AEROSOLS SAMPLED AT REVIN,
FRANCE, DURING THE EMEP 2012 SUMMER CAMPAIGN
A. Setyan (1,2), V. Crenn (1,2,3), V. Riffault (1,2), J.-L. Jaffrezo (4), A. Waked (4), S. Sauvage (1,2), J.-L. Besombes (5), J.-E.
Petit (3,6), O. Favez (6), T. Leonardis (1,2), J. Sciare (3), N. Locoge (1,2)
(1) Université Lille Nord de France, 59000 Lille, France; (2) Mines Douai, CE, 59508 Douai, France; (3) LSCE (CEACNRS-UVSQ), 91190 Gif/Yvette, France; (4) Université de Grenoble/CNRS, LGGE, 38402 Saint-Martin d’Hères, France;
(5) Université de Savoie, LCME, 73376 Le Bourget du Lac, France; (6) INERIS, 60550 Verneuil-en-Halatte, France
Presenting author email: ari.setyan@gmail.com
Summary
A field campaign has been performed in summer 2012 at Revin, a remote site in northeastern France, in order to study the
sources and processes of organic aerosols and volatile organic compounds (VOCs). The particle concentration was low, and
non-refractory submicron particles (NR-PM1) were dominated by organics. Secondary organic aerosols accounted for 82% of
the total organic mass, while primary emissions mainly from traffic accounted for 18%. Three periods of high mass loadings
(June 28, night of June 28-29, and July 3-5) were observed during the study. Back-trajectory analysis showed that the site
was mainly under the influence of long-range transport from the Paris megacity during these periods.
Introduction
Understanding the different processes governing PM concentration remains an important issue for air quality in Europe.
Within the framework of the EMEP Program and in cooperation with the ACTRIS, ChArMEx and PEGASOS projects, two
intensive measurement periods were held in summer 2012 and winter 2012/13. The main objective was to obtain high
resolution and extended measurements of aerosols and their precursors in order to improve the knowledge regarding the
temporal and spatial variability of PM speciation and to assess chemical transport models. Five monitoring sites in France
were equipped with on-line and off-line instruments to measure particle chemical and physical properties, as well as
precursor gases. We present here results obtained in Revin, a remote site in northeastern France, during the summer 2012
campaign.
Methodology and Results
The chemical composition of particles was determined with on-line (AMS,
aethalometer) and off-line (LC/MS, LC/UV, IC, thermal/optical transmittance)
methods. The average concentration of NR-PM1 was low (5.3 μg/m3), and the
chemical composition was dominated by organics (56% of total NR-PM1) and
sulfate (25%). Three organic factors were identified by positive matrix
factorization (PMF), including two oxygenated organic aerosols (OOA) with
different O/C ratios (more oxidized OOA: 0.94; less oxidized OOA: 0.41), and one
hydrocarbon-like organic aerosol (HOA). Taken together, the two OOA factors
accounted for 82% of the total organic mass (42% for the more oxidized OOA, and
40% for the less oxidized) and correspond to secondary organic aerosols (SOA),
while HOA accounted for 18% of organics and corresponds to anthropogenic
emissions. The organic-to-elemental carbon ratio (OC/EC) was 8.4 (±2.8) on
average (±1σ). Three periods of high mass loading (18.6 μg/m3 on June 28, 15.0
μg/m3 during the night of June 28-29, and 16.3 μg/m3 on July 3-5) analyzed with
back-trajectories showed that the site was mainly under the influence of long-range
transport from the Paris megacity (~230 km from the site). Among all the VOCs
measured, oxygenated species from both biogenic and anthropogenic oxidation
products (methylglyoxal, formaldehyde, methacroleine, methylvinylketone,
benzaldehyde) correlated best with organics. New particle formation and growth
events were not observed during this study.
Fig.1 Map of France, with the location
of the sampling site (© GoogleMaps)
and a wind rose plot for the entire
campaign.
Conclusions
The concentration and chemical composition of particles sampled at Revin were typical for remote sites. Our results suggest
that particles were mostly SOA formed during long-range transport.
Acknowledgements
The authors are grateful to Atmo Champagne-Ardenne for technical support and for providing some datasets for Revin and
Reims, and to Airparif for providing some datasets for Paris. This study was funded by the French Agency of Environment
and Energy Management (ADEME, grants 1262C0022 and 1262C0039) and the CaPPA project (ANR-10-LABX-005).
87
SOURCE IDENTIFICATION OF FINE PARTICLE EMISSIONS IN URBAN AIR BY MOBILE
MEASUREMENTS
L. Pirjola (1), J. V. Niemi (2), A. Kousa (2), S. Saarikoski (3), S. Carbone (3), H. Kuuluvainen (4), A. Järvinen (4), T. Rönkkö
(4), J. Keskinen (4), R. Hillamo (3)
(1) Department of Technology, Metropolia University of Applied Sciences, P.O. Box 4021, FI-00180 Helsinki, Finland; (2)
Helsinki Region Environmental Services Authority HSY, P.O. Box 100, FI-00066 HSY, Finland; (3) Finnish Meteorological
Institute, Erik Palménin aukio 1, FI-00560 Helsinki, Finland; (4) Aerosol Physics Laboratory, Tampere University of
Technology, P.O. Box 692, FI-33101 Tampere, Finland
Presenting author email: liisa.pirjola@metropolia.fi
Summary
This study aims to characterize winter aerosols in the hot spot areas of poor air quality in the Helsinki Metropolitan area. An
advanced on-line measurement technique was installed into a mobile laboratory van to measure chemical and physical
characteristics of fine particles. This study shows that the properties of particles from different sources can be distinguished.
For example, the particles originated from residential wood combustion and traffic possessed most abundant concentrations
of black carbon thus affecting the radiative properties of the atmosphere. Furthermore, the number concentration of particles
from traffic was highest, and due to their small sizes they might be most harmful for human health.
Introduction
Particle emissions from traffic and wood combustion are known to significantly contribute to regional air quality and climate.
Detailed monitoring of aerosol particle properties in urban and suburban areas is a challenging task, since their concentration,
size, composition and sources vary strongly in time and space. As a part of the MMEA Programme (Measurement,
Monitoring and Environmental Assessment, 2010-2014), a field campaign in street canyons and densely populated small
house areas with local wood burning as well as on major roads was conducted in the Helsinki Metropolitan area. An
advanced on-line measurement technique was used to monitor composition, size distribution and volatility of fine particles.
Methodology and Results
Two weeks intensive winter campaign by mobile laboratory ´Sniffer´ (e.g. Pirjola
et al., 2012) was performed in the Helsinki Metropolitan area in February 2012.
The particle number concentration and size distribution were measured by ELPI
(diameter > 7 nm) and SMPS (diameter >3 nm), PM1 chemical composition by
soot particle aerosol mass spectrometer SP-AMS and aethalometer, and mass
concentrations PM1 and PM2.5 by DustTraks. Volatility properties of particles were
studied by a thermodenuder. Also measured continuously were NO, NO2, NOx,
CO, CO2, meteorological and geographical parameters.
Four types of winter aerosol were recognized: (1) very clean period (CLEAN) at
urban background site on seashore due to air flows from the Atlantic Ocean, (2)
strong long-range transported pollution episode (LRT-EPI) at urban background
site on seashore due to air flows from eastern Europe, (3) fresh smoke plumes
from residential wood combustion (SMOKE) in suburban small house area mixed
with LRT pollution, and (4) fresh emissions from traffic (TRAFFIC) while
driving on a busy street in Helsinki city centre during morning rush hour.
Fig.1 Averaged number concentration of
particles for four sources
Fig.2 PM1 bulk chemical composition
As a result the characteristic physical and chemical properties of particles from
the different sources were identified (Figs. 1 and 2). Particles of type 1 possessed low number and volume concentrations.
Particles of type 2 and 3 were mostly in the accumulation mode and contained high organic and sulphate concentrations.
Furthermore type 3 particles had high black carbon concentration, like traffic particles. Contrary to type 3 particles, the
number concentration of type 4 particles was high and a major part of particles were in the nucleation mode.
Conclusions
The installed state-of-the-art instrumentation into the mobile laboratory van enabled us to obtain a comprehensive view on
aerosol properties and sources in urban air. To better understand the characteristics of fine particles from different emission
sources is important for air quality assessment and for climate models.
Acknowledgement
This work was partly funded by MMEA Programme. MMEA is supported by Tekes (the Finnish Funding Agency for
Technology and Innovation) and coordinated by the Finnish energy and environment cluster - CLEEN Ltd.
References
Pirjola, L., Lähde, T., Niemi, J.V., Kousa, A., Rönkkö, T., Karjalainen, P., Keskinen, J., Frey, A., Hillamo, R., 2012 Spatial
and temporal characterization of traffic emission in urban microenvironments with a mobile laboratory Atmos. Environ. 63,
156−167.
88
VOLATILE ORGANIC COMPOUNDS SOURCE APPORTIONMENT IN PARIS: FOCUS ON THE TRAFIC AND
WOOD BURNING SOURCES
V. Gros(1), A. Baudic(1), R. Sarda-Esteve (1), H. Petetin (2), O. Sanchez (2), A. Rosso (2), O. Perrusel (2), T. le Priol (3), J.
F. Petit (3), J.-E. Petit (1), O. Favez (4) C. Kalogridis (1), N. Bonnaire (1), B. Bonsang (1), I. Xueref-Rémy (1), L. Ammoura
(1), and J. Sciare (1)
Presenting author email: valerie.gros@lsce.ipsl.fr
1
Laboratoire des Sciences du Climat et de l’Environnement (LSCE), unité mixte CNRS-CEA-UVSQ, Gif sur Yvette, France
2 AIRPARIF,
3
Paris, France
DRIEA-CETE-IF, Trappes en Yvelines, France
4 INERIS, Verneuil en Halatte, France
Summary
One year measurements of selected Volatile Organic Compounds were performed in downtown Paris (2010-2011). A source
apportionment study using PMF model was performed and suggested traffic related emissions as the main VOC source, in
contradiction with the emission inventory.
Introduction Volatile organic compounds (vocs) are key species in atmospheric chemistry as their oxidation lead to the
formation of ozone and of secondary organic aerosols, pollutants which limit values are regularly overtaken in Paris in its
region. Complementary to the measurements performed by the air quality network airparif (www.airparif.asso.fr), research
programs are regularly organized with the aim to better characterize the variability and sources of the main pollutant sources.
Following the EU project MEGAPOLI (intensive campaigns in Paris in summer 2009 and winter 2010), one year of selected
Volatile Organic Compounds measurements was performed in downtown Paris.
Methodology and results Measurements were performed in downtown Paris with a PTR-MS (Proton Transfer Mass
Spectrometry) from March 2010 to March 2011. Methanol and acetone showed seasonal cycles with maxima in spring summer seasons in agreement with their dominating biogenic sources whereas benzene, a typical anthropogenic compound
showed maximum values in winter. During the period where additional measurements of non-methane hydrocarbons by gas
chromatography were available (April-October 2010), a source apportionment study using Positive Matrix Factorization
approach was performed. Five sources (with two of them mixed) were identified and their respective contributions were
determined (see Figure 1). The main source identified was linked with traffic activities (almost 50%), in disagreement with
the local emission inventory (where the solvent source is dominating) but confirming results from a preliminary study
(Gaimoz et al., 2011). To confirm the source profiles determined by the PMF model, additional measurements were
performed (within a tunnel, from wood burning) and their corresponding source profile will be presented here (see for
example the traffic source profile on Figure 2).
Gasoline evpaoration
25%
Vehicle exhaust
21%
Solvent + bacgkround
26%
Biomass combustion +natural gas
18%
Biogenic
10%
Fig. 1 Source apportionment of VOCs in Paris
Fig.2 Mean source profile measured in tunnel (mass contribution in %)
Conclusions
Although VOC traffic emissions in European cities have significantly decreased over the last two decades, it still represents a
main source of VOCs emissions (as shown here for Paris) which emission inventories may underestimate. More studies are
needed to help further evaluating and improving emission inventories.
Acknowledgments
This program was funded by the French agency PRIMEQUAL. Additional financial support from CNRS, CEA and Ile de
France region are acknowledged.
References
C. Gaimoz, S. Sauvage, V. Gros, F. Herrmann, J. Williams, N. Locoge, B. Bonsang, O. d’Argouges, R. Sarda-Estève, and J.
Sciare, Volatile Organic Compounds Sources in Paris in spring 2007. Part II: Source apportionment, Environmental
Chemistry, 8, 91-103, 2011.
89
OBSERVATION OF TRACE GAS DISTRIBUTIONS WITH AN AIRBORNE IMAGING DOAS INSTRUMENT
D. Pöhler (1), S. General (1), J. Zielcke (1), U. Frieß (1), P. Shepson (2), B. Stirm (2), W. Simpson (3), H. Sihler (1,4), K. P.
Heue (1,4), D. Walter (1,4), K. Weber (5), C. Fischer (5) and U. Platt (1)
Institute of Environmental Physics, University of Heidelberg, Germany;
Purdue University, Dept. of Chemistry, West Lafayette, IN
Department of Chemistry & Biochemistry, University of Alaska, Fairbanks
Max Planck Institute for Chemistry (Otto Hahn Institute), Mainz
University of Applied Sciences, Düsseldorf, Germany
Presenting author email: denis.poehler@iup.uni-heidelberg.de
Summary
Airborne measurements with the new imaging DOAS instrument Heidelberg Airborne Imaging DOAS Instrument (HAIDI)
are presented. It can map the horizontal distribution as well as the vertical profile for a number of relevant trace gases,
including NO2, BrO, HCHO, O4, SO2, IO, C2H2O2, H2O and O3 at the same time. All data are gained with just one overfly of
the investigated area with the DOAS remote sensing technique. It can achieve a spatial resolution of better than 100x100m².
Thus quantitative information about the spatial variability of the air quality can be achieved. We present the instrument and
several measurements at urban sites (e.g. Indianapolis, USA; Johannesburg, South Africa), volcanoes and at oil fields in
Alaska. The data are also used to derive total emission fluxes of NO2 from e.g. an urban area.
Introduction
In the troposphere many chemical processes are driven by the emission of trace gases. The emitters can thereby be of
anthropogenic origin, like power plants and traffic or natural sources, such as volcanoes. The sources are often
inhomogeniously distributed and the involved chemistry can be fast on scales of seconds. Thus the relevant chemical
processes take place on a relative small spatial scale of several meters. In order to investigate the spatial variability of air
quality, identify sources and sinks of trace gases, to further study chemical processes or to improve chemical transport
models it is therefore necessary not only to measure the trace gas concentrations at one location, but to map the distribution
of trace gases in two or even three dimensions with high spatial resolution. Here we present the new Heidelberg Airborne
Imaging DOAS Instrument (HAIDI) which is capable to map the horizontal distribution as well as the vertical profile for a
number of relevant trace gases.
Methodology and Results
The HAIDI system is based on the remote sensing technique DOAS
(Differential Optical Absorption Spectroscopy) to observe the trace
gas concentration of several components even far from the airplane
itself. It measures the sunlight reflected at the ground or scattered in
the atmosphere to the instrument located in an airplane. The sunlight
is spectrally analysed to derive the trace gas signal. In the HAIDI
system the optic scans with a high frequency to observe
measurements of a wide area (Fig. 1). Thus maps of the trace gas
distribution can be derived with just one over flight. The instrument
can also observe the vertical trace gas distribution with an additional
forward telescope. Also aerosol optical properties, which can be
used to quantify aerosol concentrations, are measured.
The instrument features several advantages and improvements in
comparison to former airborne imaging DOAS instruments which
will be presented. The system is relatively small, compact, versatile
and has low power consumption. Therefore, it may be operated even
on light weight aircrafts on which space, payload weight and power
are limited.
We report on flights showing NO2 emissions in the metropolitan
area of Indianapolis (USA) (Fig. 2) and Johannesburg, South Africa.
The data are also used to derive the total NO2 flux of these areas.
Also emissions and chemical influence of oil fields in Alaska, USA
will be presented. Measurements of a volcanic plume with SO2 and
BrO at Mt. Etna (Italy) will be shown which can significantly
influence the air quality locally.
Fig.1 Measurement principle of the HAIDI system.
Fig.2: Example of urban NO2 pollution measurements in
Conclusions
the metropolitan area Indianapolis, USA. From these
The new airborne instrument HAIDI is presented to observe trace gas
data also the total NO2 emission of the area is derived.
distributions of several constituents. We demonstrate how unique
such measurements are with results from several field campaigns. They are useful to increase our understanding of air quality
monitoring and the involved chemical processes. The instrument will be used in the future on the new German research
aircraft HALO e.g. to study trace gas distributions and chemical processes and also the air quality, in and around
metropolitan areas.
90
SECONDARY POLLUTANTS IN THE LAKE TAHOE BASIN, USA
B. Zielinska (1), A. Bytnerowicz (2), A. Gertler (1), M. McDaniel (1) and J. Burley (3)
(1) Desert Research Institute, Reno, NV 89512, USA
(2) US Forest Service, Pacific Southwest Research Station, Riverside, CA 92507, USA
(3) St. Mary's College, Moraga, CA, USA
Presenting author e-mail: Barbara.Zielinska@dri.edu
Summary
Primary objective of this study was to characterize the precursors and pathways of secondary pollutant formation, including
ozone, secondary organic aerosol (SOA) and ammonium nitrate in the Lake Tahoe Basin, USA. Samples were collected
during summer of 2012 to characterize diurnal concentrations of ozone, oxides of nitrogen, volatile organic compounds,
organic and elemental carbon and speciated particulate organic compounds. The concentrations of photooxidation reaction
products of isoprene and α-pinene, 2-methyltetrols and cis-pinonic acid, respectively, were significant.
Introduction
Lake Tahoe, located at 6,225 ft. (1,897 m) in the Sierra Nevada mountain range, is the largest alpine lake in North America.
Known for the clarity of its water and the panorama of surrounding mountains on all sides, Lake Tahoe is a prime tourist
attraction in the California – Nevada area. However, the Lake Tahoe Basin is facing significant problems related to an
increasing trend in ambient ozone levels and declining water clarity.
Methodology and Results
During the period of July 21 - 26, 2012, we conducted a field study in the Basin designed to characterize the precursors and
pathways of secondary pollutant formation, including ozone, secondary organic aerosol (SOA) and ammonium nitrate. Four
sites were selected; two were located at high elevation (one each on the western and eastern sides of the Basin) and two were
positioned near the Lake level. Ozone and NO/NO2 concentrations were continuously measured. With a resolution of several
hours over a 6-day sampling period canister samples were collected for detailed speciation of volatile organic compounds
(VOC), 2,4-dinitrophenylhydrazine (DNPH) impregnated Sep-Pak cartridges for analysis of carbonyl compounds, and
honeycomb denuder/filter pack samples for measurement of concentrations of ammonia, nitrous acid, nitric acid, and fine
particulate ammonium nitrate. In addition, PM2.5 Teflon and quartz filter samples were collected for determination of mass,
organic and elemental carbon (OC/EC) concentrations, and speciation of organic compounds.
Whereas the concentrations of lower molecular weight (mw) C2 – C3 hydrocarbons were generally the highest at all sampling
sites, ranging from 25 to 76% of the total measured VOC (over 70 species from C2 to C10), the concentrations of biogenic
hydrocarbons, isoprene and α-pinene were significant, ranging from 1.4 to 26% and 1.5 to 30%, respectively, of the total
VOC. For comparison, the sum of benzene, toluene, ethylbenzene and xylenes (BTEX) constituted from 2.5 to 37% of the
total VOC. The photooxidation reaction products of isoprene and α-pinene, 2-methyltetrols and cis-pinonic acid,
respectively, were measured in combined PM2.5 day and night samples from four sampling sites and their concentrations
ranged from 16 to 47 ng/m3 for 2-methylthreitol, from 34 to 87 ng/m3 for 2-methylerythritol and from 14 to 42 ng/m3 for cispinonic acid. Organic carbon (OC) constituted from 87 to 99.9% of total carbon. All four sites showed maximum ozone
concentrations in the range of 60 ppb. However, the lower sites show a pronounced diurnal pattern (i.e. maximum
concentrations during the daytime hours, 0900 to 1700, with minimum values at night and in the early morning hours),
whereas the upper sites shows much less variability over the 24-hour diurnal period.
91
EFFECTS OF WOOD COMBUSTION EMISSIONS ON THE AIR QUALITY IN RESIDENTIAL AREAS MEASUREMENTS AND MODELLING
G. Baumbach (1), M. A. Bari, (1), W. Juschka (1), M. Struschka (1), G. Scheffknecht (1), B. Kuch (2), W. Baechlin (3)
(1) Institute of Combustion and Power Plant Technology, Department of Air Quality Control, University of Stuttgart,
Pfaffenwaldring 23, 70569 Stuttgart, Germany; (2) Institute of Sanitary Engineering, Water Quality and Solid Waste
Management, University of Stuttgart, Bandtaele 2, 70569 Stuttgart, Germany; (3) Ing. Company Lohmeyer, An der
Rossweid 3, 76229 Karlsruhe, Germany
Presenting author email: Guenter.Baumbach@ifk.uni-stuttgart.de
Summary
In this study, results of measurements of particulate matter, PAHs and tracer compounds in wood combustion exhaust gases
and as well in ambient air of a residential area are presented. The results of both compartments are compared by PAH and
tracer compound fingerprints. Thus, the contribution of wood smoke to the air pollution situation in residential areas could be
determined and the health effects estimated. During winterly inversion conditions the contribution of the local domestic
emission sources is much higher than under windy conditions with remote transport of pollutants.. Based on this project a
tool was developed with which communities can calculate the additional pollution load when the heating systems in the area
shall be changed to more biomass combustion units.
Introduction
In Germany wood combustion for heating purposes in residential areas is permanently increasing. On the one hand, the use of
wood as renewable energy is desired. On the other hand, the combustion in small scale firings is often running incompletely
which causes annoyances by odours and negative health effects by toxic substances like PAHs. That is a serious problem for
air quality efforts in Germany. Therefore, investigations about the pollution load in residential areas caused by wood
combustion in domestic facilities are requested. Due to this public concern about the need of emission reduction and to justify
the evidence, we investigated wood smoke emissions from old and modern wood stoves as well as from ambient
measurements in residential areas in Southern Germany.
Methodology and Results
Emission samples were collected from a manually fed wood stove and a modern pellet stove. Ambient PM10 samples were
collected during winter time in the village Dettenhausen located in a forest area near the city of Stuttgart. The collected
emission and ambient samples were analysed by gas chromatography mass spectrometry (GC-MS). Twenty-one polycyclic
aromatic hydrocarbons (PAHs) were detected and quantified as well as tracer compounds like levoglucosan, dehydroabietic
acid and others. The results of both compartments are compared by fingerprints as shown in Figure 1. The emission factors
were calculated under different combustion conditions. They were higher in log wood stoves than in pellet firings and higher
during incomplete than during complete combustion. The Pm10 concentrations were simulated for a residential area, see Fig.
2, and validated by ambient air measurements.
Fig. 1 Emission and ambient air wood combustion tracer profiles
Fig. 2 PM10 simulation for a residential area the exhaust gases
and in ambient air
Conclusions
The results underline the importance of controlling wood smoke emissions in residential areas and suggest using good wood
combustion technologies to improve the air quality.
Acknowledgement
This work was supported by the Umweltbundesamt, Germany, and Alfred Teufel Foundation, Germany
92
SOURCE APPORTIONMENT OF URBAN FINE PARTICLE NUMBER CONCENTRATION DURING
SUMMERTIME IN BEIJING
Z. R. Liu (1), B. Hu (1), Q. Liu (1,2), Y. Sun (1) and Y. S. Wang (1)
(1) State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of
Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; (2) Beijing Weather Modification Office,
Beijing 100089, China
Presenting author email: wys@mail.iap.ac.cn
Summary
Continuous particle size distribution (15nm-2.5µm), particle chemical composition, gaseous species and meteorological
variables were collected at an urban site in Beijing to investigate the source apportionment of ambient fine particles. Hourly
data sets were analyzed using the positive matrix factorisation (PMF) which indentified a total of eight factors: cooking, two
traffic factors, secondary nitrate factors, secondary sulfate + secondary organic aerosol (SOA), coal-fired power plant,
fugitive dust and regionally transported aerosol. Traffic, cooking and regionally transported aerosol were found to be the
most important sources for particle number concentration, which cumulatively accounting for as much as 71.4% of the
apportioned concentrations. Local and remote sources were distinguished using size distributions associated with each factor.
Overall, the introduction of combination of particle size distribution and chemical composition data in PMF model is
successful at separating the components and quantifying relative contributions to the particle number and volume size
distributions in a complex urban atmosphere.
Introduction
Evidence from many studies has indicated that the particle number concentration (PNC, mainly ultrafine particles, diameter
<100 nm) may be a cause of adverse health effects, especially cardiovascular diseases (Liu et al., 2013). However,
conventional source apportionment studies typically use chemical composition (PCC) data from filter sampling to provide
information on particle matter sources, obscuring the dynamic changes of particle size, number, and chemical composition.
Considering this, combined PNC and PCC data were include in the PMF analysis to more clearly identify and apportion
contribution from those sources that contribute more to the particle numbers than to the particle mass concentrations.
Methodology and Results
Particle counts and size distributions (PSD, 14.5nm-20µm) were
determined using a scanning mobility particle sizer (SMPS) and a TSI
aerosol particle sizer (APS). Hourly means of particle chemical
composition and size distribution (PCC, organic matter, sulfate, nitrate,
ammonium and chlorine) during the study period were measured using
an Aerodyne high-resolution time-of-flight aerosol mass spectrometer
(HR-ToF-AMS). Combining PSD and PCC data sets were used in the
PMF model, and eight sources were successfully identified from the
size distribution, diurnal variation and their relationship to chemical
composition and gaseous pollutants (Fig.1). The aforementioned
analysis results in the obtaining of specific emission sources such as
cooking (22.8%), traffic (37.5%), secondary nitrate (8.9%), secondary
Fig.1 Source profiles and diurnal pattern
sulfate + SOA (7.9%), coal-fired power plant (6.8%), fugitive dust
(2.3%) and regionally transported aerosol (13.8%) (Fig.2). Local and
remote secondary aerosols were also successfully distinguished: local
sources were generally characterised by unimodal or bimodal number
distributions consisting mostly of particles less 0.1 µm in diameter. The
regional source was defined by mostly accumulation mode particles.
Conclusions
The majority of the apportioned particle number concentrations were
attributed to local sources, especially for traffic emissions. As traffic
volume continues to increase in Beijing, our country needs urgent and
effective air pollution abatement strategies since the health risks of air
pollution are more evident every day.
Fig.2 Source apportionment of fine particle number
concentrations
Acknowledgement
This work was supported by the National Natural Science Foundation of China (41230642) and the Science and Technology
Project of Beijing (D09040903670902). We acknowledge G. R. Liu, W. K. Gao and W. Zhang for their cooperation during
the intensive observation periods.
References
Liu, L Q, Breitner, S, Schneider,A, Cyrys,J, Brüske, I, Franck, U, Schlink,U, MarianLeitte, A, Herbarth, O, Wiedensohler, A,
Wehne, B, Pan, X. C, Wichmann, H. E., Peters, A., 2013. Size-fractioned particulate air pollution and cardiovascular
emergency room visits in Beijing, China. Environ. Res. 121, 52-63.
93
5 YEAR MEASUREMENTS OF LUNG DEPOSITED SURFACE AREA CONCENTRATIONS
AND PARTICLE NUMBER SIZE DISTRIBUTIONS AT AN URBAN BACKGROUND STATION IN GERMANY
J. Meyer (1), H. Kaminski (1), U. Quass (1), C. Nickel (1), M. Küpper (1), and T. A. J. Kuhlbusch (1)
(1) Air Quality & Sustainable Nanotechnology, Institute of Energy and Environmental Technology e.V. (IUTA), Duisburg,
Germany
Presenting author email: j.meyer@iuta.de
Summary
Here we report on results from ongoing measurements of particle size distributions and surface area concentrations, carried
out over a five year period at an urban background station in Mülheim-Styrum in the Ruhr area in North-Rhine Westphalia,
Germany. First analysis of the data set revealed distinct variations; one interesting being an increase in diurnal particle
number concentration and lung deposited surface area concentration (LDSA) every day of the week at night which is as high
as or even exceeds the morning traffic peak. First results obtained using positive matrix factorization (PMF) indicates road
traffic and wood combustion in winter as possible key factors.
Introduction
Epidemiological studies have indicated a potential link between ambient particles and adverse health effects (Dockery et al.
1993; Oberdörster et al., 2001). The exact exposure-response functions are yet unknown though and the particle parameter
best used to estimate the potential human risk is controversially debated. Two particle properties being discussed are the
surface area of particles deposited in the lung system and the particle number concentration of ultrafine particles (UFP).
Consequently, the determination and monitoring in ambient air quality networks of these metrics as well as the determination
of their source regions seems to be reasonable.
Methodology and Results
In this study we use particle measurements which were obtained between
September 2008 and December 2013 at an urban background station
(situated in a light traffic residential zone) in Mülheim-Styrum. The
measurements encompass ambient particle size distributions (PSD)
measured with a scanning mobility particle sizer (SMPS Model 3936,
TSI Inc., Shoreview, USA) and LDSA measured with a nanoparticle
surface area monitor (NSAM Model 3550, TSI Inc., Shoreview, USA).
Figure 1 exemplarily shows the average diurnal variation. Most
noticeable is the increase in particle number concentration (Figure 1 top)
and LDSA (Figure 1 bottom) on weekday mornings which most likely
results from commuter traffic. The evening traffic rush hour peak is not
seen in these average diurnal variations. Interestingly, a night time
maximum in both metrics is observed every day which even seems to
exceed the weekday morning peaks.
In this study we will present diurnal as well as seasonal variations in
particle number concentration and size distribution as well as LDSA
measured over a five year period in a highly populated urban
surrounding. The source apportionment results will be presented in view
of the main influencing sources and factors. This will be further
exploited in view of the development of efficient abatement strategies.
The general use of such data for future ambient air quality monitoring
will be discussed.
Fig.1: Diurnal variations of total particle number
and lung deposited surface area concentrations at
the urban background station Mühlheim-Styrum.
Conclusions
The diurnal and seasonal variations show expected behaviour with the exception of a night time concentration maximum
which will be further investigated. The yearly averages do not show any significant long term trends. First PMF analyses
showed significant influences of combustion sources, e.g. traffic and wood burning, on the PSD and LDSA concentrations.
Anyhow, the monitoring of further parameters, such as elemental carbon, to better discriminate sources is recommended.
Acknowledgement
The support of this work by the North Rhine-Westphalian State Agency for Nature, Environment and Consumer Protection,
Essen, Germany is gratefully acknowledged.
References
Dockery D.W., Pope C.A., Xu X., Spengler J.D., Ware J.H., Fay M.E., Ferris B.G., Speizer F.E., 1993. An association
between air pollution and mortality in six U.S. cities. N. Engl. J. Med. 329, 1753–1759.
Oberdörster G., 2001. Pulmonary effects of inhaled ultrafine particles. Int. Arch. Occup. Environ. Health, 74, 1-8.
94
A NOVEL METHODOLOGY FOR ASSESSING THE SPATIAL REPRESENTATIVENESS OF AIR QUALITY
MONITORING STATIONS IN EUROPE
E. Solazzo (1), O. Kracht (1), D. Carruthers (2), M. Gerboles (1), J. Stocker (2), S. Galmarini (1)
(1) European Commission, Joint Research Centre, Institute for the Environment and Sustainability, Ispra (Italy)
(2) Cambridge Environmental Research Consultants (CERC), Cambridge (UK)
Presenting author email: stefano.galmarini@jrc.ec.europa.eu
Summary
The assessment of spatial representativeness of air quality monitoring stations is an outstanding issue that impinges on
several areas relevant to risk assessment and population exposure as well as on the design of monitoring networks, model
development, evaluation and data assimilation. There are several approaches proposed in the literature that try to define the
area of representativeness of a monitoring station as “a similar area” or “spatial homogeneous field of pollution” (e.g. Bobbia
et al.2008). Such a definition cannot fit the intrinsic anisotropy of the atmospheric flow and dispersion, and is limited in time.
To overcome these shortcomings we propose a modified geostatistical procedure which has been adopted for climatological
data by Janis and Robeson (2004). We use the procedure with modelled concentration values of NO2, O3, and PM10 on a high
resolution grid, which serves as a dense explicative variable for the field of pollutant in the neighbourhood of a monitoring
station.
Introduction
So far, a quantitative definition of the spatial representativeness of monitoring stations is still missing. Our proposal is to use
the area within which the level of confidence is 95 % that the true pollutant value is included in the interval xi ± V, where xi is
the monitoring station measurement value and V combines the contributions of the measurement uncertainty and uncertainty
arising from the spatial variability within the area. The latter contribution is calculated from spherical models fitted to pointcentered variograms and their directional evolution over time. To build this type of variograms, the pairs of values shall
consist of one monitoring station value and one value of a densely known explicative variable. In our case, the explicative
variable consisted of modelled concentration values of NO2, O3, and PM10. The application is novel for two reasons: 1) it was
never applied before to air quality monitoring stations, and 2) it is used for spatial outputs of a city-scale dispersion model.
Methodology and Results
The Atmospheric Dispersion Modelling System ADMS
(Carruthers et al. 2001) developed by CERC has been run with a
high resolution output grid over the city of London for the years
2008 and 2011, with a model domain exceeding 50 km by 50 km.
Annual average hourly concentrations of NO2, O3, and PM10 were
calculated at each grid node. The locations of eleven air quality
receptors from the AIRBASE network have been overlaid on a
contour plot showing NO2 concentrations (Figure 1); these have
been used as the origins of a point-centred kriging semi-variance
analysis discussed above. Relevant model parameters (nugget, sill,
range) have been extracted for a number of spatial directions, hour
of the day, different species, and years. This rich collection of
parameters obtained have been used to draw some initial
considerations about the range of representativeness of stations
positioned in some of the world’s most polluted hotspots, such as
Marylebone Road in London.
Fig.1 ADMS contour map of annual averaged NO2
concentration and the AIRBASE monitoring stations analysed
in this study (year 2008).
Conclusions
Initial results indicate an area of representativeness of a few hundred meters for stations within highly polluted regions which
correspond to high emissions, large traffic volumes and highly populated areas of the city. The range of spatial
representativeness increases up to 2 km for stations in less polluted areas. These values, however, are affected by the hour of
the day and by the directionality, more so for stations whose range is larger. The uncertainty associated to the model fitting
and the model variance is more pronounced for dense urban stations. Current investigations concentrate on the trend of
ranges and uncertainties for all the pollutants available. We further aim to extend the analysis to urban areas where
topographic influence is of importance.
References
Janis, M.J., Robeson, S.M., 2004. Determining the spatial representativeness of air-temperature records using variogram
nugget time series. Physical Geography 25, 513-530.
Bobbia, M., Cori, A., De Fouquet, C., 2008. Représentativité spatiale d’une station de mesure de la pollution atmosphérique.
Pollution Atmosphérique N°197.
Carruthers D.J., and et al. 2001. Determination of compliance with UK and EU air quality objectives from high resolution
pollutant concentration maps calculated using ADMS-Urban. Int. J. Environment and Pollution, 16, no. 1-6, 460-471.
95
CHEMICAL COMPOSITION OF PM2.5 AND PM10: IMPLICATIONS FOR SOURCE APPORTIONMENT
STUDIES OVER EUROPE
H. Price (1), K. Douglas (1), R. S. Sokhi (1), M. Keuken (2), M. Kermenidou (3), D. A. Sarigiannis (3)
(1) Centre for Atmospheric and Instrumentation Research (CAIR), University of Hertfordshire, Hatfield, Hertfordshire, AL10
9AB, UK; (2) TNO, Netherlands Applied Research Organisation, PO Box 80015, 3508 TA Utrecht, The Netherlands; (3)
Aristotle University of Thessaloniki (AUTH), School of Engineering, Building D, University Campus, Thessaloniki,
GR-54124, Greece.
Presenting author email: h.price2@herts.ac.uk
Summary
In this paper we present results from a detailed source apportionment (SA) campaign carried out within the EU project
TRANSPHORM (http://www.transphorm.eu/). The identification and quantification of sources of PMx in different cities is
vital to target air pollution reductions effectively. We chemically analysed PM2.5 and PM10 at four sites (rural, urban
background, traffic, shipping) in two cities in Europe (Rotterdam and Thessaloniki) to investigate the source variability
within cities as well as between cities. The study has shown that suitable campaign design is vital to ensure meaningful SA
results.
Introduction
PM10 (Particulate matter 10 μm and under) is formed of a cocktail of different particle types including particles from traffic
exhaust, non-exhaust, biological material, domestic heating, industry, crustal material and road wear. Due to the variability of
these sources, source apportionment carried out at a single location is unlikely to capture the spatial and temporal diversity
within a city. This chemical analysis of PM campaign was designed to provide the temporal/spatial resolution and sample
sizes required for in depth SA analysis of a city.
Methodology and Results
PM2.5 and PM10 were collected at rural, urban background, traffic and shipping sites in
Rotterdam, Netherlands and Thessaloniki, Greece during winter 2012 (October-December).
Twenty four hour samples were collected onto Teflon filters using 16.7 l.min-1 instruments
with size-selective inlets. On average 54 filters were collected for each size fraction and site
in Rotterdam and 66 filters were collected for each size fraction and site in Thessaloniki.
Including blanks, over 1000 filters were collected over the course of the campaign. Filters
were analysed using photometric detection, EDXRF, IC, GC-MS and HPLC for black carbon
(converted to elemental carbon), inorganic species, ions, organics and levoglucosan
respectively. Chemical data feed into source apportionment analysis using receptor
modelling (USEPA PMF).
Figure 1: Photo of the street
sampling site in Rotterdam,
Netherlands.
Rotterdam
Thessaloniki
Rural
UB
Traffic
Shipping
Rural
UB
Traffic
Shipping
PM10 (μg/m3)
17.0
18.4
22.5
19.8
26.7
46.4
62.4
62.3
PM2.5 (μg/m3)
12.6
11.2
14.4
13.3
17.1
36.0
41.0
43.0
EC PM2.5 (μg/m3)
1.0
1.1
2.6
1.7
0.96
2.5
5.8
2.8
Table 1: Comparison of mean values of selected variables at the four sites in Rotterdam and Thessaloniki (UB=Urban background).
70
a)
50
40
30
20
10
Rs = 0.82**
7
Nickel (ng/m3)
Titanium (ng/m3)
8
Rs = 0.73**
60
b)
6
Figure 2: Correlation diagrams (and
associated
Pearson’s
correlation
coefficients)
comparing
elemental
concentrations at street site in Rotterdam for
PM2.5; a) Correlation between Ca and Ti, b)
V and Ni over the campaign.
5
4
3
2
1
0
0
0
200
400
600
800
Calcium (ng/m3)
1000
1200
0
2
4
6
Vanadium (ng/m3)
8
10
Concentrations of PM10, PM2.5 and EC were generally higher in Thessaloniki compared to Rotterdam (Table 1). However,
there was also a large amount of variation within-cities. For PM10, concentrations in both cities were ordered from highest to
lowest concentration traffic>shipping>urban background>rural. The results have shown that there are relationships within the
data that suggest specific source origins, e.g. the correlation between calcium and titanium (Figure 2a) is characteristic of a
crustal origin, and vanadium and nickel (Figure 2b) is characteristic of residual oil combustion. These relationships should
continue through the source apportionment work.
Conclusions
Source apportionment is an important tool in the abatement of air pollution issues. By understanding more about the spatial
variation of PM sources, more targeted PM reduction plans can be put in place. This study is one of the first to
simultaneously investigate the sources to PMx at different sites within a city. First results have highlighted the chemical
variability not only between cities but between different sites within cities. Comparison with other available datasets has
highlighted the importance of campaigns designed for source apportionment, rather than analysis of residual chemical
composition datasets.
Acknowledgement: The research leading to these results has received funding from the European Community's Seventh Framework
Programme (FP7/2007-2013) project TRANSPHORM under the grant agreement no. 243406.
96
ANALYSIS OF AN EPISODE OF HIGH PM POLLUTION IN THE PO VALLEY, ITALY OBSERVED IN THE
FRAMEWORK OF THE SUPERSITO PROJECT
V. Poluzzi1, D. Bacco2, G. Bonafè1, P. Ugolini1, C. Maccone1, S. Ferrari1, and I. Ricciardelli1
(1) ARPA, Agenzia Regionale per la Prevenzione e Ambiente, Via Rocchi 19, 40138, Bologna, Italy
(2) Università di Ferrara, Dipartimento di scienze chimiche e farmaceutiche, Via Fossato di Mortara 17 – 27, 44121 Ferrara
Presenting author email: vpoluzzi@arpa.emr.it
Summary
An exceptional pollution episode interested the Po Valley (Northern Italy) from 15th to 19th February 2012, and was
responsible for very high PM concentrations principally in its western and southern parts. In particular in Parma and Milan,
PM10 concentrations reached about 250 µg/m3. Analysis of meteorological and chemical parameters has been carried out to
understand the complexity of the event.
Introduction
The Regione Emilia-Romagna and its Environmental Agency (Agenzia Regionale per la Prevenzione e l’Ambiente, ARPA)
has approved and financed the Supersito project to better understand the sources of the aerosol atmospheric pollution and its
conncection with the health. A lot of measure has been carried out in the 2012 in the framework of this project.
The Po Valley region, in the north of Italy, has been identified as one of the Europe areas where pollutant levels are often
problematic. It is characterized by a high density of anthropogenic emissions and by the frequent occurrence of stagnant
meteorological conditions, being between the Alps in the north and west and the Apennines in the south.
High pollution events are often the result of the concomitant occurrence of low-mobility atmospheric conditions, that tend to
trap pollutants, and aerosols formation processes.
During the 2012 wintertime measures of the Supersito project, from the meteorological point of view, the Po Valley was
interested by heavy snowfalls from 1st to 12th February in particular in its southern area.
The chemical analyses of the species was performed on PM1 and PM2.5 samples collected at urban and rural background
sites in southern Po Valley and the aerosol mass closure was calculated.
Methodology and Results
An analysis of meteorological parameters and chemical species observed on the PM samples collected in the framework of
Supersito project has been carried out to understand the dynamics and the chemical processes of the event. From the
meteorological point of view the Po Valley was interested by heavy snowfalls from 1st to 12th February in particular in its
southern area. A period characterized by atmospheric stagnation followed until 19th, but it was interrupted from an outbreak
of northerly dry winds on the lee side of the Alps (foehn) on 15th and 16th. Observed PM concentrations started to increase
from 15th February, reaching a maximum on 19th February. Starting from 20th February, PM concentrations significantly
decreased in the entire Po Valley due to the rainfall. A gradual accumulation of aerosols progressed from 15th to 19th
February mainly due to lowering of mixing height, while the factors responsible for the second maximum observed after 16th
February are more complex. The chemical composition in this second period was characterized by a large fraction of
ammonium nitrate particles (up to 70%) suggesting that chemical processes beside the meteorological factors came into play.
To investigate the origin of air masses in the Po valley during the event it has been used a probabilistic back trajectories
lagrangian particle model (Lapmod_SA, Enviroware srl).
Conclusions
The following possible explanation for the high peak concentrations of PM has been investigated: a) contribution of
transboundary transport of pollutants, b) manure spreading on agricultural land and consequent increase of ammonia
concentration in atmosphere, c) snow melting and releasing of aerosol precursors in the atmosphere.
Acknoweledgents
This research was conducted as part of the "Supersito" Project, which was supported and financed by Emilia-Romagna
Region and Regional Agency for Prevention and Environment under Deliberation Regional Government n. 428/10.
References
Bock J., Jacobi H.W., J. Phys. Chem. A, 114, 1790-1796, 2010;
Helmig D., Seok B., Williams M.W., Hueber J., Sanford R., Biogeochemistry, 95, 115-130, 2009;
Stanier C., Singh A., Adamski W., Baek J., Caughey M., Carmicheal G., Edgerton E., Kenski D., Koerber M., Oleson J.,
Rohlf T., Lee S.R., Riemer N., Shaw S., Sousan S., Spak S.N., Atmos. Chem. Phys., 12 11037-11056, 2012;
Jacobi H.W., Hilker B., J. Photochem. Photobiol. Chem., 185 (2-3), 371-382, 2007;
Tugnoli S., Rumberti V., Atmospheric Emissions Inventory in Emilia-Romagna region, Agency for Prevention and
Environment (ARPA-ER), 2010.
97
ANALYSIS OF ATMOSPHERIC AEROSOL (PM2.5) IN RIO DE JANEIRO CITY, BRAZIL
L. H. M. dos Santos (1), A. A. F. S. Kerr (1), T. G. Veríssimo (1), M. de Fatima Andrade (2), R. M. de Miranda (3), A.
Fornaro (2), and P. Saldiva (4)
(1) Instituto de Física da Universidade de São Paulo (USP), São Paulo, Brasil; (2) Instituto de Astronomia, Geofísica e
Ciências Atmosféricas - USP, São Paulo, Brasil; (3) Escola de Artes, Ciências e Humanidades - USP, São Paulo, Brasil; (4)
Faculdade de Medicina - USP, São Paulo, Brasil.
Presenting author email: akerr@if.usp.br
Summary
The PM2.5 (particulate matter with aerodynamic diameter <2.5 µm) in Rio was analysed in the context of a main project
designed to evaluate the automotive sources contribution to the PM2.5 atmospheric concentrations, and its impacts to human
health in six Brazilian metropolitan areas. Concentrations of chemical elements, Black Carbon, and total mass of PM2.5
samples were measured. Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) were used, and
confronting the results of these methodologies, and using meteorological data as well as local sources mapping, the main
source of PM2.5 impacting the sampling site could be identified.
Introduction
Rio de Janeiro city has 6.3 million inhabitants, while the population of all the 28 cities in the metropolitan area (RMRJ)
arrives to 11.8 million people. It is internationally known as the "Marvellous City" due to the "exceptional urban setting
encompassing the key natural elements that have shaped and inspired the development of the city: from the highest points of
the Tijuca National Park’s mountains down to the sea", as says UNESCO when introducing Rio as a Cultural World
Heritage. But it is well known that the city faces major social problems. Although less divulged, the RMRJ undergoes else
environmental problems of a major metropolis with high industrialization level, intense commercial activities, and a
vehicular fleet with 4.61 million unities (by 2008). There are other research analysis of the PM in Rio. But this analysis of the
local PM2.5, focus on obtaining its specific source contribution to the local PM2.5. This knowledge will play an important role
in the context of the simultaneous experiments conducted in the other 5 Brazilian metropolis, directed to study the PM2.5
health impact.
Methodology and Results
Figure-1 shows the RMRJ area with the sampling
site, important sources and urbanized area. The
sampling period was from May 2007 to
September 2008, providing 325 samples of 24 hr.
The PM2.5 was collected on 37 mm polycarbonate
filters (0.4 µm pore size) using Harvard samplers
with a flow rate of 10.0 L/min. A volume
integrator gave sampled volumes. The filters were
weighted before and after sampling using a
microbalance and following standard procedures.
The filters were analysed by Energy Dispersive
X-ray Fluorescence (XRF-ED) to determine the
concentrations of the elements with atomic
number
(Z)>11.
Black
Carbon
(BC)
concentrations were obtained by light reflectance,
using an inter-calibration with thermal/optical
transmittance (TOT) equipment.
Figure 1: Metropolitan Region of Rio de Janeiro. UFRJ is the sampling site
The PM2.5 mean concentration was 17.5 µg/m³, (22º50'29”S; 43º14'08”W, 9 m amsl) at the Federal University of Rio de Janeiro.
exceeding the WHO guide lines for the annual The Gray colour indicates urbanized areas. Main roads are in yellow and some
important sources are signed in.
average (10 µg/m³). The BC average
concentration was 1.6 µg/m³. Five components were extracted when applying Principal Component Analysis (PCA),
identifying the following sources: 1) Oil combustion (Ni, V, Cr, S); 2) Soil dust (Ti, Al, Si, Fe); 3) Biomass Burning (Total
Mass, BC, K, Br); 4) Light Vehicles (Zn, Cu, Pb); Sea Spray (Cl, Ca). The 5 factors obtained by PMF provided a similar
source identification, although the light vehicles and sea spray were blended and the model identified a new factor associated
to metallurgical activities. PMF source apportionment gave: 1) Oil combustion explaining 44% of the mass; 2) Soil dust with
6%; 3) Biomass Burning with 31%; 4) Light Vehicles/Sea Spray with 15%; and 5) Metallurgy with 4%. The oil combustion
may be from the port (that has an average traffic of 5 ships day), ~5 km upstream the prevalent wind direction in the area
(135º). The intense traffic of heavy duty vehicles in the main roads around the sampling site could also give a contribution, as
well as the main Oil Refinery called Reduque (~14 km at ~330º). Biomass burning may even come from accidental fire along
the nearby Rio Petrópolis road, as from the usage of wood by low income population nearby the same road (coming with the
wind around 310º).
Conclusions
This analysis of the local PM2.5, gives a valuable contribution to the local PM2.5 source knowledge in Rio. It can help the air
quality control actions in an area of the RMRJ, plenty of air contamination sources and densely populated. Further, the results
will play an important role in the context of the simultaneous experiments conducted in the other 5 Brazilian metropolis,
directed to study the PM2.5 health impact.
98
COMPOSITION AND SOURCE APPORTIONMENT OF NON-METHANE VOLATILE ORGANIC
COMPOUNDS (NMVOCS) IN BEIRUT, LEBANON
T. Salameh (1,2,3), S. Sauvage (1,2), C. Afif (3), A. Borbon (4), N. Locoge (1,2)
(1) Université Lille Nord de France F-59000, Lille France ; (2) Mines Douai, Département Chimie et Environnement, F59508 Douai Cedex, France ; (3) Centre d'Analyses et de Recherche, Faculty of Sciences, Saint Joseph University, Beirut,
Lebanon ; (4) Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA), Universités Paris 12 et Paris 7, France
Presenting author email: therese.salameh@mines-douai.fr; therese.salameh@usj.edu.lb
Summary
Based on a large database of NMVOC observations obtained in Beirut, the capital of Lebanon, the overall objective of the
present study is to apportion the sources of NMVOCs encountered in Lebanon (a small developing country in the Middle
East region, located in Western Asia on the eastern shore of the Mediterranean Sea). First, source profiles were determined
with field measurements close to the main potential emitters namely the road transport, gasoline vapour, power generation
and solvent uses. The results obtained are compared to other studies held in other regions and are used to assess the emission
inventory developed by Waked et al, 2012. Secondly two intensive field campaigns were held in a receptor site in Beirut
during summer 2011 and winter 2012 in order to determine the contribution of the main sources. The comparison with other
studies showed the consistency of our results.
Introduction
NMVOCs, emitted from various sources, are of particular interest since they contribute to the formation of tropospheric
ozone, PAN and secondary organic aerosols. Air pollution is still a major problem in the Middle East region, where data
related to NMVOC are sparse or nonexistent, reductions of emissions are necessary. To identify abatement measures, a
profound knowledge of emission sources and their composition is a prerequisite. Though, air pollution in the MEA region
remains difficult to assess and understand because of a lack of ground-based measurements and the limited information on
NMVOC chemical speciation and source apportionment. Nevertheless, for a successful development of air pollution control
strategies, these information are crucial to support model implementation as well as to assess the emission inventory
established for Lebanon for the year 2010 by Waked et al. 2012 according to the EEA/EMEP guidelines because of the lack
of Lebanon-specific emission factors.
Methodology and Results
The chemical composition of emissions from several major NMVOC anthropogenic sources in Lebanon was established
including: road transport, gasoline vapour (hot soak, refueling vapour in service stations and emissions from fuel storage
facilities), power generation and solvent use from architectural coatings, furniture paints and auto paints. These profiles are
then compared to those obtained by PMF receptor model. In fact, the source apportionment receptor modelling PMF was run
for a large dataset of NMVOC collected in two campaigns during summer 2011 and winter 2012 in Beirut.
Near field samplings have been carried out in Beirut city and in the suburban area by canisters and the analyses were
performed by the gas chromatograph equipped with a flame ionization detector (GC-FID, Perkin Elmer). Around 67
NMVOC of C2 – C9 were identified and quantified. The same analytical method was used with an on-line sampling system
during the summer and winter measurement campaigns.
Characteristic features of the roadway emission profile included high concentrations of isopentane (13.5%), butane (11.5%),
toluene (10.5%), xylenes (6.8%), ethylene (2.9%) and ethyne (2.8%). Gasoline evaporation profiles included high
concentrations of the C4-C5 saturated hydrocarbons. For instance, isopentane accounted for 23.1% in refueling cars, 17.2%
in fuel storage facility and 14.2% in hot-soak profile. As per the power generator emissions, the main compounds are related
to combustion (ethane, ethylene, propylene and toluene). Toluene and C8-C9 aromatics were found to be the most abundant
species in emissions from paint applications. Toluene accounted for 69% in paint solvents for furniture profile and for 23% in
automobile paint use. Comparisons with other similar studies in different regions showed that the source profiles obtained are
consistent. Then, the obtained profiles are used to identify source factors determined with the PMF v3.0 applied to summer
and winter campaign databases. In both seasons, combustion (Road transport and power generation) and gasoline evaporation
were the main sources contributing to the NMVOCs in Beirut.
Conclusions
Reduction of NMVOCs emission should be prioritized in the air pollution control efforts. This unique work is of high
importance for the MEA region where available information on NMVOC measurements and speciation is scarce but essential
for air quality modeling and abatement strategies. The identification analyses of the emissions of NMVOCs from various
sources in Beirut and the assessment of the contribution of the sources to ambient levels of the NMVOCs will help in
validating the emission inventory established for the year 2010 by Waked et al. 2012 according to the EEA/EMEP guidelines.
Acknowledgement
This work was supported by Mines Douai Institution, the Lebanese National Council for Scientific Research, the Saint
Joseph University (Faculty of Sciences and the Council for Research) and CEDRE.
References
Waked A., Afif C., Seigneur C., 2012. An atmospheric emission inventory of anthropogenic and biogenic sources for
Lebanon. Atmospheric Environment 50, 88-96.
99
PARTICULATE MATTER SOURCE APPORTIONMENT IN THE AREA OF THESSALONIKI, GREECE.
D.E. Saraga (1, 2), E. Tolis (1), E.M. Kougioumtzidis (1) and J.G. Bartzis (1)
(1) Environmental Technology Laboratory, University of Western Macedonia, UOWM, Kozani, Greece
(2) Environmental Research Laboratory, INRASTES, National Center for Scientific Research "DEMOKRITOS", Aghia
Paraskevi Attikis, P.O.B. 60228, 15310 Athens, Greece
Presenting author email: dsaraga@ipta.demokritos.gr
Summary
The present study aimed to identify and quantify the contribution of particulate matter (PM) sources in the port city of
Thessaloniki, in Northern Greece. In the frame of APICE project (Common Mediterranean strategy and local practical
Actions for the mitigation of Port, Industries and Cities Emissions), PM2.5 measurements were conducted in five large
Mediteranean cities. In the city of Thessaloniki, PM2.5 concentration measurements were conducted at two sites, one in the
centre of the city and one in the nearby port. A total of 322 samples, 161 from each site, were collected during two seasons.
The samples were analysed for 25 chemical compounds (Polycyclic Aromatic Hydrocarbons, ions, metals, elemental and
organic carbon). A source apportionment study using Positive Matrix Factorization v3.0 model was conducted for both
sampling sites of Thessaloniki (city center and port) in order to identify the pollutant sources. PMF application results
indicated six PM2.5 sources in both sampling sites.
Introduction
Harbors represent a significant potential for the economic development, although having a potential negative environmental
impact. Port activities mainly include emissions from shipping (passenger ships, ferries, fishing boats, cargo ships etc) and
other local activities as (un)loading and transport of dusty loose materials as far as exhaust emissions from vehicles moving
in the port areas, comprising important particulate matter and gaseous pollutant sources. The present study aimed at
identifying and quantifying the contribution of particulate matter (PM) sources in the port city of Thessaloniki (northern
Greece), through a receptor model application (Positive Matrix Factorization-PMFv3.0).
Methodology and Results
For the purpose of the study, two low volume samplers (Derenda LVS 3.1) were used for the PM2.5 samples collection at the
two sampling sites: the city center and the port of Thessaloniki. PAHs, ions and metals analysis were conducted using gas
chromatography, ion chromatography and atomic spectrometry while elemental and organic carbon were analysed using the
NIOSH 5040 method.
An input concentration matrix of 322 samples and 25 species was created. A corresponding matrix of sample-specific
uncertainty values was also injected in the model (EPA PMFv3.0). Concentration data below the detection limit was
substituted with one-half of the detection limit and missing concentration data were substituted with the median value. From
the data included, none of the species presented high percentage of data below the detection limit. Finally, Ζn and Ni species
which presented low signal-to-noise ratio (<2) were characterized as "weak". The model was run for 3 to 12 factors and a
random seed. The optimal number of factors was determined by examining the Q values for PMF solutions resulting from a
range of the -number of factors- values without excluding the solution’s physical validity. The optimal number of factors in
this analysis was six for both sampling sites. The two final steps were the bootstrap and Fpeak runs in order to examine the
stability and the rotational ambiguity of the solution, respectively.
PMF analysis lead to a solution of six factors, which correspond to six sources or groups of sources for both sites. For the
Thessaloniki’s city center, the following sources were identified: a traffic (vehicle exhausts) source (23.7% contribution to
PM2.5), an industry/mineral source (7.5%), a source of marine (mixed sea+ships emissions) origin (4.1%), a road dust-source
(12.8 %), a combustion/central heating source (9.3%) and a source connected to secondary aerosols (24.6%). The
unapportioned fraction of PM2.5 was 18%. For the port site the following sources were identified: a mixed traffic-origin
source (vehicle exhausts + road dust) (22.7% contribution to PM2.5), an industry/mineral source (19.6%), a sea-origin source
(4.1%), a fuel oil combustion (possibly ships emissions)- related source (15.6%), a combustion/central heating source (7.2%)
and a source connected to secondary aerosols (19.5%). The unapportioned fraction of PM2.5 was 11.2%.
Conclusions
Two traffic-related sources are presented at the city center: one related to vehicle exhausts and one to road dust. These two
sources are combined and presented as one source for the case of the port. Additionally, a marine-origin source with rather
low PM2.5 contribution is presented at the city center. The same source is split to two different sources for the port site: a
natural sea origin source and a fuel oil combustion (ships emissions) source. The combustion-related source presents seasonal
variation, being more intense during the cold season (October to March), therefore it can be connected to central heating
emissions. The mineral/industry source contribution is stronger at the port site, without presenting significant seasonal
variation.
Acknowledgement
The APICE project (Common Mediterranean strategy and local practical Actions for the mitigation of Port, Industries and
Cities Emissions) is financed by the European program for territorial Cooperation MED 2007/2013.
100
MODEL EVALUATION
STUDIES
101
EVALUATION OF THE ON-LINE NMMB/BSC-CTM MODEL GAS-PHASE RESULTS ON THE EUROPEAN
DOMAIN FOR 2010 IN THE FRAMEWORK OF THE AQMEII-PHASE2 INITIATIVE
A. Badia (1),O. Jorba (1)
(1) Earth Sciences Department, Barcelona Supercomputing Center – Centro Nacional de Supercomputación (BSC-CNS).
Barcelona, Spain.
Presenting author email: alba.badia@bsc.es
Summary
The Air Quality Model Evaluation International Initiative (AQMEII) Phase-2 aims to inter-compare on-line couple
regional-scale models over North America and Europe. In this contribution, the evaluation of 2010 air quality simulations for
gas-phase of the integrated model NMMB/BSC-CTM contributing to the European domain simulations of AQMEII-Phase2
initiative is presented.
Introduction
It is well known that weather conditions influence air quality. Moreover, numerous studies show that meteorological
processes such as boundary layer turbulence, precipitation, radiation budget, are a key drivers for accumulation of chemical
pollutants in the atmosphere. On the last decades due to the complexity and the computer resources limitation, air quality and
meteorological models had been developed as separate fields. However, with the huge increase of the computational power
during the last years, several on-line coupled meteorology-chemistry global and regional-scale models have been developed
for research and forecasting applications. The COST Action ES-1004 European framework for online integrated air quality
and meteorology modelling (EuMetChem - http://eumetchem.info) reviews those integrated models developed or applied in
Europe. In this framework, a model intercomparison effort is designed within the Action ES-1004 and is coordinated with the
AQMEII-Phase2 international initiative, that focuses inter-comparison of on-line coupled regional-scale models.
Methodology and Results
AQMEII-Phase2 exercise defines a common model configuration suite:
chemical boundary conditions from MACC re-analysis data, anthropogenic
emissions from TNO database for the year 2009, forest fires emission by
FMI (http://is4fires.fmi.fi/data/data_main.htm) and domain configuration
over Europe and North America with a horizontal resolution of 0.25◦
x0.25◦. Data from different observational networks, available on the
AQMEII-Ensemble system, is used in this study to carry out the model
evaluation.
Under this framework, the NMMB/BSC-CTM (Jorba et al., 2012) is
applied over the European domain for the year 2010. NMMB/BSC-CTM is
a fully on-line integrated system for meso-to global scale applications. The
meteorological driver is the multiscale NCEP/NMMB meteorological
model and the gas-phase chemical mechanism used is the CBM-05. The
model has been configured with 24 and 48 vertical layers.
Results show that there is a good performance from May-November for O3
(Fig.1), with a good correlation over central EU and Iberian Peninsula (0.60.8) and lower over North and East EU and UK (0.1-0.4). The best
correlation for NO2 is produced over central EU (0.4-0.7) and lower
Fig.1 O3 hourly May-Nov mean concentration
values are obtained over the Mediterranean areas (0.1-0.4). A general
(ug/m3) for all stations. Model results are in black
trend to overestimate in central and North EU and underestimate closer
line/ grey bar and observations in red line/orange bar
to Alps and Pyrenees regions is identified.
Conclusions
The obtained results have shown a general trend to overestimate O3 but good agreement is found from May to November. As
illustrated in Fig.1, the model hourly results reproduce properly the observed hourly variability. A larger correlation is found
in central EU for NO2 and model skills are lower for CO and SO2.
Acknowledgement
The authors wish to thank the initiative of AQMEII-Phase2 for providing an automatic evaluation system with a large set of
observations. We also want to acknowledge the support from projects CGL2010/19652 and CSD2007-00050 of the Spanish
Ministry of Economy and Competitiveness, and support of the grant SEV-2011-00067 of Severo Ochoa Program, awarded by
the Spanish Goverment. BSC simulations were performed with the Marenostrum Supercomputer at BSC.
References
Jorba, O., Dabdub, D., Blaszczak-Boxe, C., Pérez, C., Janjic, Z., Baldasano, J. M., Spada, M., Badia, A., and Gonçalves, M.:
Potential Significance of Photoexcited NO2 on Global Air Quality with the NMMB/BSC Chemical Transport Model, Journal
of Geophysical Research, 117, 2012.
102
CAN WE EXPLAIN THE OBSERVED DECREASE IN SECONDARY INORGANIC AEROSOL AND ITS
PRECURSORS BETWEEN 1990 AND 2009 OVER EUROPE USING LOTOS-EUROS?
S. Banzhaf (1), M. Schaap (2), R. Kranenburg (2), A. Manders (2), A. Segers (2), A. Visschedijk (2), H. Denier van der Gon
(2), J. Kuenen (2), C. Hendriks (2), E. van Meijgaard (3), L. van Ulft (3) and P. Builtjes (1/2)
(1) Freie Universitaet Berlin, Institute of Meteorology, Germany; (2) TNO, The Netherlands; (3) KNMI, The Netherlands
Presenting author email: sabine.banzhaf@met.fu-berlin.de
Summary
In this study we investigate the ability of the Chemistry Transport Model (CTM) LOTOS-EUROS to explain the observed
decrease in secondary inorganic aerosol (SIA) and its precursors between 1990 and 2009 over Europe. The model explicitly
accounts for cloud chemistry and aerosol thermodynamics. The results have shown that the model largely captures the
observed trends in SIA and its precursors’ concentrations while it underestimates the interannual variability. Using a sourceapportionment module the amount of SIA formed per unit emission was traced for 4 regions. The results show 20-50% more
efficient SO42- formation in 2009 compared to 1990, whereas the change in NO3- formation per unit NOx emission changed
less (-10% to +20%) over the same time period.
Introduction
SIA forms a substantial fraction of PM, which has adverse impact on public health (Pope et al., 2006). Moreover, sulphur and
nitrogen deposition fluxes damage ecosystems by eutrophying and acidifying soils and fresh water. In the last two decades
emission abatement strategies have been implemented all over Europe targeting the adverse effects of SIA and its precursors
on human health and the environment (e.g. NEC Directive). The implemented mitigation measures have led to significant
emission reductions. However, the responses of the pollutants’ concentrations to the emission changes are not one to one but
show non-linear behaviour. CTMs are used to analyse potential emission reduction strategies and quantify their effectiveness.
Modelling the non-linear relationships between gas- and particle-phase i.e. modelling secondary species is still challenging
for state of the art CTMs. Thus, analysing the ability of CTMs to capture non-linear responses and interannual variability of
the last 15-20 years is fundamental before the models can be used to analyse future emission strategies. In this study we
compare concentrations of SIA and its precursors of a 20 years LOTOS-EUROS model run to observations to investigate if
the model is able to explain the observed decrease in SIA and its precursors between 1990 and 2009 over Europe.
Methodology and Results
Observational data for the years 1990-2009 have been provided by EMEP
and the AirBase database. Using the off-line 3D CTM LOTOS-EUROS a
model run of 20 years (1990-2009) has been performed on a domain
covering Europe (grid resolution approx. 25km x 25km). The meteorological
data set was obtained from RACMO2. Emissions were generated using
IIASA RAINS/GAINS output. Figure 1 shows the mean 60 days moving
average for NO2 (upper panel) and TNO3 (lower panel) at several stations
spread over Europe. The model underestimates concentrations and interannual variability for NO2 while for TNO3 both features are captured well.
As the upper plot indicates the model overestimates the negative trend in
NO2 concentrations. It was found that the model reproduces the observed
relative trends better than the absolute trends for all investigated components. A source apportionment module has been applied to trace the amount
of SIA formed per unit emission of SO2, NOx and NH3 for 4 different
regions over Europe. The results reveal an increase in SO42- formation
efficiency by 20-50% from 1990-2009 for all regions. The NO3- formation
per unit NOx emission shows a slight increase for the region
Netherlands/Belgium (+20%) whereas the formation efficiency slightly
decreases for Romania (-10%).
Conclusions
The results of the study have shown that the model captures the observed
relative trends in SIA and its precursors’ concentrations better than the
absolute trends. Applying a source-apportionment module the results have
revealed changes in SIA formation efficiency from 1990-2009. This nonlinear effect seems to also exist in the observations. The latter is induced by
shifts in the partinioning between aerosol- and gas-phase and changes in
oxidant levels due to changes in the emission regime following emission
reductions over Europe.
Fig.1 Mean 60 days moving average for
NO2 (upper panel) and TNO3 (lower
panel) at 57 and 9 European rural
background stations, respectively.
Acknowledgement
This work was funded by TNO within the framework of the R&D Project 3712632401-PINETI II (Umweltbundesamt, GER).
References
Pope C.A., Dockery D.W., 2006. Health Effects of Fine Particulate Air Pollution: Lines that Connect. Journal of Air and
Waste Management Association 56, 709-742.
103
MODELLING THE SPATIAL AND TEMPORAL PATTERN OF AMMONIA OVER THE PO VALLEY
V. Capiaghi (1,2), G. Pirovano (2), C. Colombi (3), G. Lonati (1), G. M. Riva (2), A. Toppetti (2), V. Gianelle (3), A.
Balzarini (2)
(1) DICA Politecnico di Milano, P.za L. da Vinci 32, 20133 Milano, Italy; (2) RSE Spa, via Rubattino 54, 20134 Milano,
Italy; (3) ARPA Lombardia Settore Monitoraggi Ambientali, via Juvara 22 – 20129 Milano, Italy
Presenting author email: guido.pirovano@rse-web.it
Summary
The CAMx chemical transport model (CTM) has been applied over the Po Valley (Northern Italy) to investigate the spatial
and temporal pattern of ammonia, the gas phase precursor of ammonium particulate. Model results have been compared with
systematic ammonia measurements of the Air Quality Network. CAMx proved to be skilful in reproducing the temporal
evolution of ammonia concentration at receptors located in the most emitting areas, while it underestimated ammonia levels
in urban and remote areas. Nevertheless, Particulate Matter (PM) concentration has been correctly reproduced at most sites.
Model results suggest that the annual emission burden of ammonia is correctly quantified. Conversely, the underestimation
taking place outside the high emission areas is probably related to an incorrect hourly modulation profile of ammonia
emissions as well as to a poor reconstruction of the Planetary Boundary Layer (PBL), both contributing to dampen the effect
of ammonia transport at basin scale. Conversely, the good performance in reproducing the PM concentration suggests that
those effects are less relevant for secondary pollutants, the main fraction of PM in the Po Valley during these episodes.
Introduction
Reduced nitrogen is one of the key factors driving the development of PM concentrations over the Po Valley, due to the
presence of a large amount of agricultural and livestock activities. A reliable reconstruction of the spatial and temporal
pattern of ammonia in the atmosphere represents an inescapable aspect in order to investigate its role as aerosol precursor and
then to design and asses air quality policies aiming at reducing PM pollution and dealing, among the others, with the
agricultural sector. This study represents one of the first attempts to evaluate ammonia modelled concentrations against
observed data in the Po Valley.
Methodology and Results
The CAMx model has been applied over a computational domain covering the whole Po Valley and adopting a 5 km grid
step size. The analysis has covered two periods (summer and fall) of 2010 characterized by different emissions and
meteorological features. Meteorological fields have been derived from WRF. Emissions have been arranged in CAMx ready
format by applying the SMOKE emission model. Regional high resolution emission inventories have been used for the Po
Valley area; additionally, the Italian emission inventory and the EMEP inventory have been used for the leftover part of the
Italian domain as well as outside Italy. Results have been compared with observed ammonia concentrations at four sites of
the Lombardy, characterized by different emission strength: two in South Lombardy (the most ammonia emitting area),
Milan, and a prealpine valley. Additionally, 244 meteorological and 202 air quality stations belonging to the operational
regional networks have been considered too. Figure 1 displays the results obtained at one of the rural sites (Bertonico, left
panels), and at Milan site (right panels) for a fall episode. NH3 concentration has been well reproduced at the rural site, with
the exception of a strong episode taking place on September 22th. Differently, at Milan site ammonia concentration has been
clearly underestimated. As for PM, CAMx concentration levels are in a good agreement with the observations, particularly
during the second half of the period, where the model has been able to reconstruct the development of both episodes.
Fig.1 Daily series of CAMx (red) and observed (black) concentrations of NH3 (top) and PM (bottom) at Bertonico (left) and Milano (right).
Conclusions
The good results obtained at rural sites suggest that the annual emission burden of ammonia is correctly quantified.
Conversely, the underestimation taking place outside the emission areas is probably related to an incorrect hourly modulation
profile of ammonia emissions as well as to a poor reconstruction of the PBL, both contributing to dampen the effect of
ammonia transport at basin scale. Conversely, the good performance in reproducing the PM concentration suggests that those
effects are less relevant for secondary pollutants, representing the main fraction of PM in the Po Valley during these
episodes.
104
COMPARISON OF MEASURED DATA AND MODEL-RESULTS DURING PEGASOS-CAMPAIGN 2012
C. Ehlers, D. Klemp, A. Wahner, H. Elbern
Forschungszentrum Jülich, Institut für Energie und Klimaforschung – IEK-8 Troposphäre
Presenting author email: c.ehlers@fz-juelich.de
Summary
Mobile ground-based measurements with a mobile lab (MOBILAB) yield a dataset with a high temporal and spatial
resolution and a large areal coverage. Evaluating the forecast quality of the EURAD-model this dataset gives the opportunity
to determine the effects of the input values and the processes on which the model calculations are based.
Introduction
In the Forschungszentrum Jülich a mobile Lab (MOBILAB,
see figure 1) has been developed to perform mobile
Measurements with a high temporal resolution in rural
background regions as well as in highly polluted urban areas.
The MOBILAB has been used for various campaigns (e.g.
[Ehlers, 2013]). During the west campaign of the PEGASOSproject the MOBILAB was used as a mobile ground station as
well as a tool for mapping the concentrations in the rural
background regions in the Netherlands.
In the framework of the PEGASOS-project high resolution day
by day forecasts have been calculated. The forecast quality is
based on the atmospheric chemistry and transport processes as
well as the consistency of the emission inventories.
The values calculated in the EURAD-model represent average
values for the corresponding 1x1 km grid-cells of the model.
For comparison with the mobile ground-based measurements
the lowest layer from the model has been used.
Based on the GPS-track recorded from MOBILAB the
corresponding model-results were derived via a web interface
provided by EURAD.
Results
As the MOBILAB has been measuring while driving along the
roads, the effects of local emissions from single cars were
eliminated from the data using a 5%-percentile filter with a
180 seconds time base.
For the model-evaluation an example was chosen where the
measurements covered a wide range from urban areas,
motorways as well as rural agricultural areas and a large forest.
CO is often used as a marker for an anthropogenic influence.
Here the model results are in good agreement width the
background values calculated from the measurements (see
figure 2).
A comparison of the ozone values (see figure 3) shows a
significant overestimation of the ozone values in the EURADmodel. In contrast to this the ozone production rates estimated
from the EURAD-model and from the measurements are in
good agreement. A box-Model (MCM 3.2) calculation based
on the measured precursor concentrations showed the same
ozone production rate, indicating, that the chemical processes
in the EURAD-model are in good agreement with the
measurements.
Figure 1: MOBILAB - schematic view
Figure 2: CO-concentration
Figure 3: Ozone-concentration
Conclusions
The results shown above indicate that the model can predict the concentrations for CO very well while the nitric oxides are
significantly underestimated by a factor of two. As transport and mixing processes would affect both species in the same
way, the results indicate that deviations of the emission inventories are the most probable explanation for the underestimation
found for the nitric oxides. Furthermore, the detailed analysis on the ozone concentrations showed that the chemical
processes in the atmosphere that lead to ozone formation are represented very well by the model, whereas the absolute
concentrations showed a significant discrepancy.
References
Ehlers, C., 2013, Mobile Messungen – Messung und Bewertung von Verkehrsemissionen, thesis, University of Cologne
PEGASOS, Pan-European Gas-AeroSOls-climate interaction Study, http://pegasos.iceht.forth.gr/
EURAD, 2013, H. Elbern, http://db.eurad.uni-koeln.de/de/vorhersage/eurad-im.php
105
INVESTIGATING RELATIONSHIPS BETWEEN MODEL PERFORMANCE AND MODELING OUTCOMES
N. Kumar (1), B. Koo (2), O. Nopmongcol (2), T. Odman (3), A. G. Russell (3), E. M. Knipping (1), G. Yarwood (2)
(1) Electric Power Research Institute (EPRI), 3420 Hillview Ave, Palo Alto, CA 94536, USA; (2) Environ International
Corp, 773 Bel Marin Keys Blvd Novato, CA 94998, USA; (3) Georgia Institute of Technology, School of Civil and
Environmental Engineering, 790 Atlantic Drive,Atlanta, Georgia 30332-0355 USA
Presenting author email: nkumar@epri.com
Summary
In this study we conduct modelling experiments to investigate how use of different regional air quality models in a way that
is prevalent in the user community could affect various policy outcomes. The outcomes investigated are:

Response to emission reductions (e.g., effectiveness of control strategy demonstrations)

Source/regions contribution assessments

Setting standards or nonattainment area boundaries
The purpose of the study is to show how in the absence of any guidelines for evaluating air quality models, one may obtain
very different policy outcomes depending on the model being used in spite of the models meeting the commonly accepted
model performance criteria.
Introduction
Air quality models are the primary tools used by regulators, states, industry, and other agencies for a variety of applications,
including the development of regulations, design of air quality control strategies and implementation plans, and short-term
operational air quality forecasting. Recently their use is also being extended to establishing air quality standards when the
monitoring data are unavailable. Given the widespread use of air quality models for a variety of applications, these models
need to be rigorously evaluated to ensure that one can reliably use the modelled results. Currently, no guidelines exist on how
to evaluate such models before they are used for regulatory or other applications. Most practitioners conduct minimum
evaluation by comparing modelled quantities against measurements averaged over space and time such that one may not get a
true picture of the model’s ability to accurately predict the observed concentrations. In this study, we conducted modelling
experiments to see how use of different models in a way that is prevalent in the user community could affect various policy
outcomes.
Methodology and Results
We ran two regional air quality models predominantly used in the United States, the CAMx (Comprehensive Air Quality
Model with Extensions) and the CMAQ (Community Multiscale Air Quality) model for an annual simulation for the Year
2005 using available modelling inputs (emissions and meteorology). The model evaluation was performed using commonly
used statistical measures (normalized bias and error) averaged over an annual period and for different monitoring networks.
Both the models were shown to perform adequately based on commonly “acceptable criteria” used by the air quality
community. We then ran the two models for a future year (2014) with proposed air quality control policies in the United
States and determined the response (i.e., change in concentrations of ozone and particulate matter concentrations) of the
models to those control strategies. We also conducted source apportionment studies to determine contributions of different
source regions to air quality at different receptor sites using both the models using brute force methods (i.e., by zeroing out
the anthropogenic emissions from a given source region).
In this paper we present the results from the different control strategy simulations and the emissions sensitivity simulations
(i.e., zeroing out of emissions). The results show that even though the two models used showed model performance that
would be deemed acceptable based on commonly used criteria by the air quality community, the response of the models to
control strategies was quite different. In addition, the contribution of the different source regions was also significantly
different at certain downwind receptors. The next step would be to conduct diagnostic simulations to improve the
performance of the models at different spatial and temporal scales and redo the sensitivity simulations to examine if the two
models converge in the response to those sensitivities.
Conclusions
The results from this study suggest that running the existing air quality models in a manner prevalent in the community, i.e,
showing model performance using statistical measures averaged spatially over long periods, may not give robust results that
can be reliably used to make policy decisions. A better approach may be to develop a stricter set of criteria that the models
must pass for a particular application before they can be used for policy decisions.
106
AIR QUALITY OVER ASIA, A MODELLING STUDY WITH WRF-CHEM
A. K. Petersen (1), G. P. Brasseur (1), R. Kumar (2)
(1) Max Planck Institute for Meteorology, Hamburg, Germany
(2) National Center for Atmospheric Research (NCAR), Boulder/Colorado, USA
Presenting author email: katinka.petersen@zmaw.de
Summary
In this study, the WRF-Chem model was run for a domain covering 60°E to 150°E, 5°S to 50°N at a resolution of
60kmx60km for January and July 2006 with the Maccity emission inventory. The model results are compared with
observations to evaluate the its capability for simulating air pollution over the Asian domain, especially the chemical species
related to ozone formation. In addition, a run with increased NOx emissions by a factor of 1.5 for January 2006 has been
performed to get an insight of the consequences of ongoing increasing emissions on the air quality in Asia.
Introduction
The degradation of air quality in Asia resulting from the intensification of human activities, and the related impacts on the
health of billions of people have become an urgent matter of concern. A prerequisite for air quality improvement is the
development of a reliable monitoring system with surface instrumentation and space platforms as well as an analysis and
prediction system based on an advanced chemical-meteorological model.
WRF-Chem model is a regional chemical dynamical model designed to serve both for operational forecasting and
atmospheric research needs. In order to use the WRF-Chem for the forecast of air pollution over Asia, the model performance
needs to be evaluated.
Methodology and Results
The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), version 3.4.1, has been used in this
study, with the chemistry module based on MOZART and the aerosol module based on GOCART. Global boundary
conditions are provided by the global chemistry transport model MOZART-4 driven by NCEP/NCAR reanalysis
meteorology at 2.8x2.8 deg horizontal resolution at 28 levels. The WRF-chem model was driven by NCEP FNL (Final)
Operational Global Analysis meteorology fields. The time step of the model was set to 240s. The model domain is defined on
Mercator projection, covering the domain 60°E to 150°E, 5°S to 50°N at a resolution of 60x60 km with 51 vertical levels and
4 soil levels. The Yonsei University (YSU) scheme has been used for the planetary boundary layer parametrization. The
resolved-scale cloud physics are represented by the Thompson microphysics scheme, while sub-grid scale effects of
convective and shallow clouds are parameterized according to the Kain-Fritsch convective scheme.
The WRF-Chem model was run for January 2006 and July 2006 with the Maccity emission inventory. In addition, a run with
increased NOx emissions by a factor of 1.5 for January 2006 has been performed in order to study the effects of further
increased emissions.
The model simulations have been compared with observations from ground and from space. Different methods of
determining if ozone is under NOx or VOC limitation have been applied in order to understand the ozone formation in Asia.
Figure 1: WRF-Chem simulation of surface NO2 (log-scale) for
January 2006.
Figure 2: WRF-Chem simulation of surface ozone [ppbv] for
January 2006.
Conclusions
The results show that the WRF-Chem model is able to simulate the general distributions of air pollutants over Asia. The
ozone formation is strongly under VOC limiting conditions over areas with high human activities, such as East Central China
and North India. In East Central China, with very high NOx emissions and very low solar radiation in winter, ozone is
titrated, leading to very low ozone levels at the surface.
A further increase of NOx emissions during winter would extend areas where ozone is under VOC limitation, expecially over
India, and results in higher ozone over Asia, apart from areas with very high NOx as in North India and East Central China,
where ozone would further decrease due to titration.
107
LOCAL-SCALE MODELLING OF ACCIDENTAL RELEASES IN BUILT ENVIRONMENTS – SELECTED
RESULTS OF THE ‘MICHELSTADT’ MODEL EVALUATION EXERCISE IN COST ACTION ES1006
K. Baumann-Stanzer (1), B. Leitl (2), S. Trini Castelli (3), M. Milliez (4), G. Rau (1) and all COST ES1006 Members
(1) Central Institute for Meteorology and Geodynamics (ZAMG), Hohe Warte 38, 1190 Vienna, Austria (2) Max Planck
Institute for Meteorology (ZMAW), Bundesstr. 53, 20146 Hamburg, Germany (3) Institute of Atmospheric Sciences and
Climate (ISAC) of the Italian National Research Council, Corso Fiume 4, 10133 Torino, Italy (4) Centre d'Enseignement et
de Recherche en Environnement Atmosphérique (CEREA), 6-8 avenue Blaise Pascal, Cité Descartes Champs-sur-Marne
77455 Marne la Vallée Cedex 2, France
Presenting author email: k.baumann-stanzer@zamg.ac.at
Summary
COST Action ES1006 focuses among other objectives on the evaluation of local-scale hazmat dispersion modelling in
complex built-up environments. Appropriate data-sets are identified and methodologies for quality assessment in the light of
practical use are developed. Experiences from a first model evaluation exercise conducted as non-blind and blind tests based
on the comparison to wind tunnel measurements of continuous and puff releases are presented.
Introduction
COST Action ES1006 "Evaluation, improvement and guidance for the use of local-scale emergency prediction and response
tools for airborne hazards in built environments" (http://www.elizas.eu) has been set up to improve, assure and evaluate the
quality of local-scale hazmat dispersion modelling with a particular focus on the needs of end-users in responding to releases
in complex urban and industrial environments. CBRN threats in cities may result from accidents, or as a consequence of
criminal or malevolent activities. Although these events are quite different in nature, effective emergency response to them
requires similar atmospheric dispersion modelling and health impact assessment tools. In an emergency situation, the model
must be able to predict the transient dispersion process associated with a continuous (leakage, fire) or a short duration (puff)
release. Furthermore, the dispersion of the agent in an urban or industrial environment is strongly influenced by small scale
obstacles, and the resulting concentrations are therefore highly inhomogeneous in space and intermittent in time.
Main objectives of the action are to establish scientifically and practically justified methods for the assessment of
local-scale airborne hazard dispersion model performance and to prepare reference data sets qualified for model evaluation.
Methodology and Results
The “Michelstadt” wind-tunnel experiment (Fischer et al., 2010) is chosen
as first test case. A non-blind and a blind test are conducted. Both
continuous and short-term (puff) releases are considered in this model
evaluation exercise. Different modelling methodologies are applied, from
the simple parametric models to advanced CFD, with an applicationoriented approach. In this way, not only the physical reliability of the
models is considered, but also their applicability in terms of run-time and
response speed, simplicity to use and computational costs and for purpose
adaptability. Aspects of data selection for hazard model evaluation are
addressed in this presentation and the approach for inter-comparison of
models and measurements developed within COST ES1006 (Stern and
Milliez, 2013) as well as selected results are presented.
Conclusions
Fig.1 Measured near-ground air concentrations
Major differences are found between models that explicitly account for
from source 2 (continuous release, non-blind test)
the presence of buildings and those that do not resolve the obstacles. This
aspect is particularly important for correctly describing the pattern of the
plume in such complex geometries.
As expected, more advanced models in general better reproduce the observed
plume structure but are also more expensive in terms of required effort in setup and computing time.
Acknowledgement
The European Cooperation in Science and Technology (www.cost.eu) is
acknowledged for supporting the cooperations essential for the presented
work within the COST ESSEM framework.
References
Fischer R., Bastigkeit I., Leitl B. and Schatzmann M., 2010. Generation of
Fig.2: Simulated near-ground air concentrations
spatio-temporally high resolved datasets for the validation of LES-models
from source 2 (continuous release, Langrangian
simulating flow and dispersion phenomena within the lower atmospheric
model LASAT)
boundary layer. Proc. 5th International Symposium on Computational Wind
Engineering (CWE2010), Chapel Hill, North Carolina, USA.
Stern M. and Milliez M., 2013. Developing tools for comparison of physical measurements and results of numerical
simulations. Scientific Report. COST Action ES1006 – STSM.
108
TRANSNATIONAL MODEL INTERCOMPARISON AND VALIDATION EXCERSICE (JOAQUIN)
S. Adriaenssens (1), F. Fierens (1), E. Trimpeneers (1), E. Van der Swaluw (2), F. Deutsch (3) and H. Denier Van der Gon
(4)
(1) Belgian Interregional Environment Agency (IRCEL), 1210 Brussels, Belgium (2) National Institute for Public Health and
the Environment (RIVM), 3721 Bilthoven, Netherlands (3) Flemish Institute for Technological Research (VITO), 2400 Mol,
Belgium (4) Netherlands organization for Applied Scientific Research (TNO), 3584 Utrecht, Netherlands
Presenting author email: adriaenssens@irceline.be
Summary
Although air quality has improved considerably in Europe in recent decades (EEA, 2012), airborne fine particles still have a
significant impact on our health and life expectancy (Amman et al., 2005). Recent research shows that other pollutants, such
as the smaller ultra fine particles (UFP) and “Elemental Carbon (EC)” are more likely to be linked to health problems, than
the current parameters of NO2 (nitrogen dioxide) and PM10 (PM with a diameter less than 10μm) (Janssen et al., 2011). At
present there is no clear understanding of the presence of these particles, especially at local and regional level. Since air
pollution, especially of the current parameters, is by its nature a truly transnational problem, a jointly identified and
implemented transnational approach is therefore an essential requirement for a successful reduction of air pollution. Such
approach is complicated by the use of different models and emission inventories within and between countries. The aim of
this study is to compare the four currently used regional models Chimère, BelEUROS, Aurora and LotosEuros used by
Belgium and the Netherlands with a unified emission inventory.
Introduction
The aim of the Joaquin project is to support health-oriented air quality policies in the Northwest European Region (NWE). To
achieve this, the project is broken up in three work packages. The first work package consists of capacity building, in which
innovative knowledge will be gained by e.g. setting up a novel monitoring infrastructure for UFP and EC. In the second work
package, measures are assessed to identify, pilot and evaluate the most efficient and cost-effective measures to reduce
exposure. In the third work package, communication is set-up between the involved policy levels, stakeholder groups and the
general public. Within the second work package a transnational assessment of health relevant parameters will be conducted.
Currently there is no insight in the relative importance of health relevant pollutants across the NWE region and no maps of
UFP and EC emissions and concentrations exist.
Methodology and Results
The first part, which comprises this study, is the comparison of
four currently used regional models with regard to EC and PM10
concentrations, i.e. Lotos-Euros, BelEuros, Chimère and Aurora.
Model simulations are performed for base year 2009 and for the
same domain, which comprises Belgium, the Netherlands, WestGermany, North-France, and a large part of the UK. Model
resolutions are also comparable and approximately 7x7 km².
Emissions are based on the TNO MACC inventory adapted with
high resolution bottom-up emissions for Flanders, The Netherlands
and the UK. The effect of meteorology on the model
intercomparison exercise was assessed by repeating the model
simulation with meteorology of 2009, 2010 and 2011. The results
of this exercise are validated with available EC/BC and PM10
measurements from the telemetric monitoring networks of each
participating country.
Fig.1 EC annual mean 2009 (µg/m³)
Conclusions
The core goal of the Joaquin project is to provide health-oriented air quality information to support air quality policies in the
Northwest European Region. Since modelling exercises are complementary to measurements in this regard, it is important to
provide a good agreement of information at national boundaries and to highlight problems and possible causes for
discrepancies. This model intercomparison exercise will contribute to this purpose.
Acknowledgement
This work was supported by the European Union through the Interreg IV-B NWE program.
References
Amman M., Bertok, I., Cofala, J., Gyarfas, F., Heyes, C., Klimont, Z., et al., 2005. Baseline Scenarios for the Clean Air for
Europe (CAFE) Programme , IIASA, Austria
EEA 2012. Air quality in Europe 2012, European Environment Agency, Denmark.
Janssen N., Hoek, G., Simic-Lawson, M., Fisher, P., van Bree, L., et al., 2011. Environ. Health Perspect. 119,1691-1699.
109
APPLICATION OF NINFA/AODEM OVER NORTHERN ITALY: MODEL EVALUATION IN THE
FRAMEWORK OF SUPERSITO PROJECT
T. C. Landi (1,2), M. Stortini (2), G. Bonafè (2), P. Cristofanelli (1) and P. Bonasoni (1)
(1) National Research Council, Institute of Atmospheric Sciences and Climate (ISAC-CNR), via
Gobetti 101, 40129, Bologna, Italy
(2) ARPA-SIMC, Agenzia Regionale per la Prevenzione e Ambiente, Viale Silvani 6, Bologna, Italy
Presenting author email: tlandi@arpa.emr.it
Summary
A comprehensive evaluation of 3-D air quality modeling system NINFA/AODEM has been carried out over northern Italy
for the year 2012. Simulated meteorological variables, particulate matter concentrations and aerosol optical properties are
compared with both ground-based and satellite measurements. Basic statistics were calculated for pointing out model's
strength and weakness.
Introduction
Po Valley region (Northern Italy) has been identified as one hot spot place where pollutant levels remain problematic in spite
of the application of the current European legislation (2008/50/EC) devoted to air pollution control. It is characterized by a
high density of anthropogenic emissions and by the frequent occurrence of stagnant meteorological conditions, being
between two mountain ranges, the Alps in the north and west and the Apennines in the south. In recent literature is reported
that large fraction of aerosol is from local sources, even if there is a contribution from a regional origin (Saarikoski et al.,
2012). Generally, high pollution events are the result of the concomitant occurrence of low-mobility atmospheric conditions,
that tend to trap pollutants, and aerosols formation processes. Investigations based on both ground-based and satellite
measurements and air quality modelling are needed to shed light on air pollution and related health issues as well as on
understanding of the origin of pollution.
A comprehensive evaluation of 3-D air quality modelling system implemented by ARPA Emilia Romangna over northern
Italy is reported in this work. In particular, model's skills in representing the formation and cycling of aerosols on hourly
basis and over the variation in the boundary layer height has been evaluated by using data collected during 2012 at SuperSito
sampling sites (i.e. 3 in urban areas, 1 in rural area, and 1 in remote area).
Methodology and Results
Emilia Romagna Environmental Agency (Agenzia Regionale per la Prevenzione Ambientale, ARPA) has implemented an
operational air quality modeling system, called NINFA, for both operational forecasts and long-term analysis. NINFA is
based on the chemical transport model CHIMERE (Bessagnet et al., 2008), driven by COSMO-I7, the meteorological Italian
Limited Area Model, (Steppeler et al., 2003). Boundary conditions are provided by Prev'air data (www.prevair.org), and
emission input data are based on regional, national and european inventory. The simulations domain cover the northern Italy,
with an horizontal resolution of 5km. Basically, predicted mass concentrations of aerosols and traces gases for the first
vertical level are compared with ground-based measurements. In addition, a post-processing tool for aerosol optical
properties (AOP) calculation, called AODEM (Landi T. C. 2013), was implemented. Thus, ground-based and satellite
measurements of Aerosol Optical Depth, aerosol extinction coefficient and single scattering albedo can be also used for 3-D
model assessment. For the year 2012, predictions of gaseous, particulate matter, and AOP have been compared with widely
used observational datasets, such as regional ground level measurements, AERONET, MODIS/terra and MODIS/aqua, and
CALIPSO. Besides, for this experiment, NINFA/AODEM has been evaluated by using measurements of size-segregated
aerosol samples, number particles concentration and aerosol optical properties collected on hourly or daily basis at 3 sites in
urban areas (Bologna, Parma and Rimini), 1 in rural area (San Pietro Capofiume) and 1 in remote area (Monte Cimone).
Therefore, acute pollution episodes were deeply investigated.
Conclusions
Despite a underestimation of about factor 2 remains, operational air quality modeling system NINFA well reproduces the
seasonal trend of aerosols levels over northern Italy, in terms of spatial variability as well. Compared with observations,
predictions of particulate matter both at ground level and of columnar load present a likely behaviour on seasonal basis. Even
if limitation in capturing vertical distribution of aerosols was diagnosed, model simulates maxima of PM10 concentrations and
AOD during winter and summer, respectively.
References
Bessagnet, Bertrand, Laurent Menut, Gabriele Curci, Alma Hodzic, Bruno Guillaume, Catherine Liousse, Sophie Moukhtar,
Betty Pun, Christian Seigneur, and Michaël Schulz (2008). "Regional modeling of carbonaceous aerosols over europe—focus
on secondary organic aerosols." Journal of Atmospheric Chemistry 61, no. 3 : 175-202.
Landi Tony Christian (2013). AODEM: A post-processing tool for aerosol optical properties calculation in the Chemical
Transport Models. Book published by LAP - Lambert Academic Publishing ISBN: 978-3-659-31802-3.
Saarikoski, S., S. Carbone, S. Decesari, L. Giulianelli, F. Angelini, M. Canagaratna, N. L. Ng et al (2012). "Chemical
characterization of springtime submicrometer aerosol in Po Valley, Italy." Atmospheric Chemistry and Physics 12, no. 18 :
8401-8421.
Steppeler, J., G. Doms, U. Schättler, H. W. Bitzer, A. Gassmann, U. Damrath, and G. Gregoric (2003). "Meso-gamma scale
forecasts using the nonhydrostatic model LM." Meteorology and Atmospheric Physics 82, no. 1-4 : 75-96.
110
EVALUATION OF THE MACC OPERATIONAL FORECAST SYSTEM WITH RESPECT TO GLOBAL
REACTIVE GASES
Annette Wagner (1), Harald Flentje (1), Werner Thomas (1) and the MACC Team
(1) Deutscher Wetterdienst (DWD) Dept. Research and Development, Hohenpeissenberg Meteorological Observatory, AlbinSchwaiger-Weg 10, 82383 Hohenpeissenberg.
Presenting author email: Annette.wagner@dwd.de
Summary
The MACC-II (Monitoring Atmospheric Composition and Climate- phase II) project is the current pre-operational
Atmosphere Service of the European earth observation program Copernicus. MACC-II combines state-of-the-art atmospheric
modelling with earth observation data to provide information services covering European air quality, global atmospheric
composition, climate forcing, the ozone layer, UV and solar energy, and emissions and surface fluxes in Near-Real-Time.
The sub group “VAL” of the MACC-II project is focusing on the evaluation of modelled reactive gases, thus, stratospheric
and tropospheric ozone as well as its precursors and aerosols. Here, we will give an overview on some results of the NearReal-Time (NRT) evaluation of the global MACC forecast system based on O3 and CO observational data of the Global
Atmosphere Watch (GAW) network. Our contribution will also contain an assessment and discussion of the potential and the
limitations of modelling reactive gases globally with the MACC model. Examples of model behaviour will be presented in
single representative case studies.
Introduction
MACC-II uses a comprehensive global monitoring and forecasting system that estimates the state of the atmosphere on a
daily basis, combining information from models and observations. The global modelling system is also used to provide the
boundary conditions for an ensemble of more detailed regional air quality models. We focus on the MACC_osuite, which is
the pre-operational coupled IFS-MOZART modelling system with assimilation, which is the Near-Real-Time Analysis
production run for MACC Aerosol and Global Reactive Gases.
Methodology and Results
For the validation of MACC_osuite, 6-hourly model values (0, 6, 12, 18 h) have been matched with hourly observational
GAW station data. In order to compare modelled and observed reactive gas mixing ratios, model values at the stations’
location have been interpolated linearly from the model data in the horizontal. In the vertical, modelled gas concentrations
have been extracted at the model level which matches the GAW stations’ real altitude. Evaluation metrics include the simple
bias, the MNM bias, the RMSE and correlation coefficients. Time
series plots for all stations serve as an additional means for the
interpretation of validation results. Bullet plots enable a spatial
investigation of results (see Fig.1).
Results show that the MACC_osuite model run is able to
reproduce the seasonal cycle of CO and O3 mixing ratios as
observed by GAW stations in most cases. However, observed O3
mixing ratios are globally slightly overestimated, except for in the
Polar regions. CO mixing ratios are systematically underestimated
for Europe. Effects in the observations that go back to local
processes are not captured by the global model. The model has
been able to improve over time.
Fig.1 MNM bias in % of the MACC_osuite model run between
Conclusions
09/2009 and 12/2012 in comparison with GAW observational
MACC-II is the current pre-operational atmospheric service of the
data
European Copernicus (formerly GMES) programme, that provides
analysis and daily 5-day forecasts of global reactive gases, combining information from models and observations. The
evaluation of the MACC_osuite Near-Real-Time model run between 2009 and 2012 revealed that: the MACC model
(MACC_osuite) is able to reproduce the annual cycles of O3 and CO correctly. However, observed O3 mixing ratios are
globally slightly overestimated, except for in the Polar regions. There is a systematic underestimation of observed CO surface
mixing ratios for Europe.
Acknowledgement
This work was supported by the NRT GAW observational data providers : Institute of Atmospheric Sciences and Climate
(ISAC) of the Italian National Research Council (CNR), South African Weather Service, National Centre for Atmospheric
Science (NCAS, Cape Verde), National Air Pollution Monitoring Network (NABEL) (FOEN and EMPA), Atmospheric
Environment Division Global Environment and Marine Department Japan Meteorological Agency, Chinese Academy of
Meteorological Sciences (CAMS), Alfred Wegener Institut, Umweltbundesamt (Austria), National Meteorological Service
(Argentina), Umweltbundesamt (UBA, Germany)
References
Stein, O., Schultz, M.G., Flemming, J., Inness, A., Kaiser, J., Jones, L., Benedetti, A., Morcrette, J.-J.: MACC Global air
quality services – Technical Documentation. MACC project deliverable D_G- RG_3.8, 2011. 111
SPECIAL SESSION AIR POLLUTION IN
CITIES
112
SEASONAL VARIATION OF PAHS CONCENTRATION IN ROME METROPOLITAN AREA AND SOURCE
ATTRIBUTION THROUGH DIAGNOSTIC RATIOS ANALYSIS
S. Finardi (1), A. Cecinato (2), C. Gariazzo (3), M. Gherardi (3), P. Radice (1), P. Romagnoli (2)
(1) ARIANET S.r.l., Milano, Italy; (2) CNR-IIA, Montelibretti (RM), Italy; (3) INAIL Research Center, Monteporzio
Catone (RM), Italy
Presenting author email: s.finardi@aria-net.it
Summary
Atmospheric concentrations of polycyclic aromatic hydrocarbons (PAH) have been measured in different locations in Rome
metropolitan area during EXPAH LIFE+ project (www.ispesl.it/expah) field campaigns. The large number of samples
gathered from November 2011 to July 2012 allowed to quantify a seasonal variation of more than one order of magnitude for
heavy PAH congeners concentration, with B[a]P varying between min/max values of 0.01-3.0 ng/m3 recorded during summer
and winter months. The comparison of PAHs diagnostic ratios with emission profiles suggests the concurrent contribution of
different sources on a yearly basis, with prevalence of traffic during the summer and heating emissions during the winter.
Introduction
The population exposure to PAHs in urbanised areas is of great concern for the possible health impact of these carcinogenic
substances. The routinely available measurements performed to fulfil the EC Air Quality Directives requirements are limited
to B[a]P and do not allow a clear insight of space and time variability of concentrations over the whole Rome conurbation.
The extensive measurement campaigns realised by EXPAH project allowed to analyse the seasonal concentration variability,
investigate the possible sources contribution and verify sources profiles included in emission inventories.
Data Analysis and Results
EXPAH field campaigns have been carried out from November 2011 to July 2012
in both indoor and outdoor environments. The monitoring involved 17 locations
(nine houses, six schools and two offices), together with three stations of the urban
air quality network. All outdoor measured PAH congeners show a large time
variation spanning more than one order of magnitude from winter maximum to
summer minimum values. Figure 1 shows B[a]P, B[b]F, B[k]F and IP average
concentrations for each sampling period. The time variation of PAHs
concentration is much larger than that of PM2.5 mass concentration of the
corresponding samples indicating the possible contribution of different sources
along the year. A large variation of concentrations is observed even for contiguous
winter sampling periods, when B[a]P average concentrations ranges between 2-3
ng/m3 during polluted periods, and 0.5 ng/m3 during “clean” periods. The space
variability of PAHs concentrations, evaluated by the ratio of the standard Fig. 1. PAHs average concentrations
deviation to the mean for each sampling period, is larger during summer than in winter, with average values of 0.4 and 0.2 for
B[a]P. The identification of specific sources footprint has been attempted by analysing the ratios of individual PAH
concentrations with the approach indicated by Ravindra et al. (2008). In particular, we analysed the seasonal variation of
B[a]P/B[ghi]P, IP/(IP+B[ghi]P), B[b]F/B[k]F, B[a]P/(B[a]P+CH) and B[a]A/(B[a]A+CH). All the diagnostic ratios show a
continuous variation from winter to summer with values indicating the presence of multiple sources influencing the Rome
area, with different relative contributions during the year. The sources
contribution variation is synthesised in Figure 2 by the cross plot
B[a]A/(B[a]A+CH) vs. IP/(IP+B[ghi]P), which indicates the relevance of
biomass burning connected to house heating during winter and the
prevailing contribution of petroleum combustion and road traffic during
summer. The mentioned sources influence is confirmed by the comparison
of diagnostic ratios with emission profiles measured during the latest years
in Italy by CNR/IIA for mobile and industrial sources, and by some of the
emission profiles available in literature (see e.g. Ravindra et al., 2008).
Conclusions
EXPAH field campaigns allowed to quantify PAHs concentration
variability in Rome. The seasonal behavior of PAH diagnostic ratios
permitted to identify different sources contributions better than long term
average values, highlighting the influence of winter house heating and, in
particular, of biomass burning in determining high values measured in
wintertime.
Acknowledgement
The LIFE+ EU financial program is acknowledged for the provision of funding for EXPAH project (LIFE09 ENV/IT/082).
References
Ravindra K., Sokhi R.S., Van Grieken R., 2008. Atmospheric polycyclic aromatic hydrocarbons: Source attribution, emission
factors and regulation. Atmos. Environ. 42, 2895-2921.
113
A FEASIBILITY STUDY OF MAPPING LIGHT ABSORBING CARBON USING A TAXI FLEET AS A MOBILE
PLATFORM
P. Krecl (1), C. Johansson (2,3), J. Ström (2), J.-C. Gallet (4) and B. Lövenheim (3)
(1) Federal University of Rio Grande do Sul, Porto Alegre, Brazil; (2) Department of Applied Environmental Science (ITM),
Atmospheric Science Unit, Stockholm University, Stockholm, Sweden; (3) Stockholm Environment and Health
Administration, Stockholm, Sweden; (4) Norwegian Polar Institute, Tromsø, Norway.
Presenting author e-mail: patricia.krecl@iph.ufrgs.br
Summary
This work reports on the first mobile measurements of light-absorbing carbon mass concentrations (MLAC) conducted in
Stockholm using taxis as rolling platforms with no selected route. Concentrations were higher during daytime and showed a
large geographic variability along the different roads with maxima levels inside road tunnels, followed by main roads and
street canyons. There is a clear relationship between MLAC and traffic rates values, with higher concentrations for highlytrafficked roads. The present study shows that this novel approach is a very cost-effective way to gather spatially-resolved air
pollution data.
Introduction
Carbon-containing particles are associated with cardiopulmonary morbidity and mortality (e.g., Janssen et al., 2012), and its
light-absorbing fraction was recently estimated to be the second largest contributor to global warming after carbon dioxide
(Bond et al., 2013). Detailed knowledge on the spatiotemporal variability of light absorbing carbon particles in urban areas is
relevant for air quality management and to better diagnose the population exposure to these particles. Considering this, we
mapped the MLAC values in Stockholm by combining measurements on-board taxis and at fixed sites on 7-17 Nov. 2011.
Methodology and Results
Micro-Aethalometers model AE51 (Magee Scientific, USA) with no pre-cut size
device were used to gather ambient 1-min MLAC concentrations on-board four
taxis. Vehicle speed and geographical position were recorded with portable global
positioning system (GPS) data loggers every 6 sec. Simultaneous MLAC
measurements were conducted at two fixed sites in Stockholm using custom-built
Particle Soot Absorption Photometers (PSAP) and logged every 15 min. Daily
mean traffic rates (TR), based on annual average counts, were determined for
each GPS position. Mobile MLAC measurements were classified according to road
characteristics (tunnels, street canyons, inner city, local and main roads) and also
TR categories (very low: <3600, low: 3600-10700, moderate: 10700-23100, high
> 23100 vehicles day-1). Individual datasets per taxi captured the grand statistical
pattern made up by the drive-by composite measurements, with median and
median absolute deviation MLAC concentrations ranging from 1.4 to 1.7 µg m-3,
and from 0.7 to 1.0 µg m-3, respectively. On average at night (21:00-05:00),
mobile measurements presented similar concentrations as the ones monitored at
the urban background fixed site (median of 0.9 µg m-3). Mobile measurements
showed a large geographic variability along the different roads with maxima
levels inside road tunnels (median and 95th percentile of 7.6 and 40.7 µg m-3,
respectively). Main roads presented the second highest concentrations (median
and 95th percentile of 1.9 and 9.0 µg m-3, respectively) associated with highest
vehicle speed (median of 70 km h-1), TR (median of 65000 vehicles day-1), and
diesel vehicles share (7-10%) when compared to inner city, street canyon and local
roads. There is a clear relationship between MLAC concentrations and TR values
as depicted in Fig. 1.
Fig. 1 MLAC concentrations, TR
and vehicle speed classified
according to different TR
categories. Represented are P5, 1st
quartile, median, 3rd quartile, and
Conclusions
Using taxis as measuring platforms proved to be a time- and cost-effective approach to map out the MLAC concentrations in
Stockholm and more research is required to represent the distribution in other periods of the year. Simultaneous monitoring
of NOx concentrations, closely correlated to MLAC levels in traffic-polluted environments, and including video recording of
road and traffic changes would be an asset.
Acknowledgement
This work was supported by the Environmental Fund of the Stockholm County Administration, the Norwegian Research
Council and the Arctic Earth Observatory project. Taxi Stockholm is acknowledged for providing the four taxis.
References
Bond, T.C., Doherty, S.J., Fahey, D.W., Forster, P.M., Berntsen, T., co-authors, 2013. Bounding the role of black carbon in
the climate system: A scientific assessment. J. Geophys. Res. DOI: 10.1002/jgrd.50171.
Janssen, N.A.H., Gerlofs-Nijland, M.E., Lanki, T., Salonen, R.O., Cassee, F. co-authors, 2012. Health effects of black
carbon. World Health Organization, Regional Office for Europe. ISBN: 978 92 890 0265 3.
114
INDOOR PSYCHOTROPIC SUBSTANCES IN ROME, ITALY
A. Cecinato, P. Romagnoli, M. Perilli, C. Patriarca, C. Balducci
National Research Council of Italy, Institute of Atmospheric Pollution Research (CNR-IIA), I-00015 Monterotondo Stazione
RM, Italy
Presenting author email: cecinato@iia.cnr.it
Summary
Experiments performed at schools, homes and offices in Rome, Italy, demonstrated that psychotropic substances (PSs), both
licit and illicit, affect the indoor environments. A new test conducted in winter 2013 included a shop (bar) and a new school,
none of sites being known as frequented by illicit substance addicts. Measurements at two homes were also replicated.
Indoors, the psychotropic substances’ burdens often exceeded the corresponding levels detected in open air.
Introduction
Important data bases of PSs occurring in the air are restricted to Italy, whilst only spotty measurements have been carried out
in Spain and the rest of the world. By contrast, the concern on indoor PSs was overall restricted till now to nicotine, as
component of tobacco smoke; the first extensive investigation on indoor PSs was conducted in the frame of EXPAH Project
(1). Nicotine and caffeine were investigated as licit drugs, cocaine and three cannabinoids ( 9-THC, cannabinol and
cannabidiol) among the illicit ones. A new test was conducted in winter 2013, when two new sites, i.e. a bar shop and a
school, were investigated.
Methodology and Results
Low-volume samplers equipped with PM2.5 inlets and running
at 10 L min-1 were adopted to collect indoor particulates;
outdoors, twin devices (homes, office) or medium-volume
samplers (schools, ARPA stations) were used in parallel. PM
was accumulated daily, then two-, three- or five-day pools were
gathered to perform chemical characterization. PM2.5 and PAHs
were also evaluated, as markers of pollution. The sample pools
were extracted with organic solvent, purified through column
chromatography and analysed through CGC-MSD using
perdeuterated congeners as reference compounds.
Fig. 1 shows the concentrations reached by PSs at IGM school
and BSP bar shop. Concentrations detected (outdoors) at BEL
Fig.1. Airborne nicotine, caffeine, cocaine and cannabinoids
station are also reported. It is worth noting that all
(ng/m3) at IGM school, BSP bar shop and BEL station.
environments were drug-contaminated, although formally lived
by no-consumers except for coffee-based beverages. In particular, in the school all substances were more abundant than at
BEL, whilst PAHs were less (2.3 vs. 3.1 ng/m3 as average).
Both at BSP and IGM all PSs were more abundant in
weekdays than in weekends. This behaviour was not
respected at BEL by nicotine and cocaine.
The concurrent values of PSs detected at HCB and HPR
homes are reported in Fig.2. At HCB two environments
were investigated, namely the bedroom (B) and the dining
room (D).
Nicotine was very high (≈500 ng/m3) in the home
frequented by tobacco smokers (HCB), while outdoor
values were “normal” <100 ng/m3). Caffeine, cocaine and
cannabinoids were higher in HCB than in HPR, and all
indoor values exceeded the corresponding outdoor ones.
The bedroom in HCB was less drug-contaminated than
dining room. Similar behaviours showed PAHs and PM2.5.
All concentration patterns were in agreement with the
tobacco smoking at HCB. Worth to note, indoor PAHs
exceeded the outdoor ones at HCB (in/out ratio 1.2÷3.6),
whilst the reverse was observed at HPR (ratio ~0.6).
Fig.2 Airborne nicotine (A), caffeine (B), cocaine (C) and
cannabinoids (D) at homes. HCB B: bedroom;
HCB D: dining room
115
ON THE EFFECT OF A PARK ON FLOW AND POLLUTANT DISPERSION IN THE BUILT ENVIRONMENT
- CFD STUDY FOR AN IDEALZED URBAN NEIGHBOURHOOD C. Gromke (1), B. Blocken (1,2)
(1) Building Physics and Services, Eindhoven University of Technology, Eindhoven, 5600 MB, Netherlands
(2) Building Physics Section, Leuven University, Heverlee, 3001, Belgium
Presenting author email: c.b.gromke@tue.nl
Summary
Traffic pollutant dispersion in a completely built-up urban neighbourhood and alternatively in one with a park in place of the
central building block was investigated. In comparison to the completely built-up neighbourhood, the park was found to lead
to a general improvement in air quality in particular in its immediate vicinity and at downwind locations. For the entire
neighbourhood, reductions of 19% in the average concentration and of 34% in the maximum concentration were obtained at
pedestrian level. However, some spots with increased concentrations were also found.
Introduction
Densely built-up cities frequently suffer from bad air quality caused by traffic
emissions which get trapped within the building canopy. Wide open areas or green
spaces are two possibilities to increase the natural ventilation and hence to facilitate
the dispersion and escape of pollutants from within the building canopy. The aim of
this study is analyse to what extent an intelligent urban design with green spaces can
contribute to improved air quality.
Methodology
The neighbourhood consisted of a 5 x 5 square array with 90 m long and 18 m broad
streets. Two configurations were studied: (i) building blocks of height h = 30 m in
each sector, and (ii) a park in the central sector instead of a building block. The park
consisted of trees with medium dense crowns of leaf area density LAD = 1 m2m-3
forming a closed canopy from 6 to 18 m above ground.
Steady-state Computational Fluid Dynamics (CFD) simulations were performed for a
neutral atmospheric boundary layer with Uh = 10 ms-1 at building height and a
homogeneous emission rate Q of traffic pollutants from the streets. The simulations
were performed with a Reynolds Stress Model (RSM) extended with terms to account
for the effects of trees on flow and turbulence (Ayotte et al., 1999). The extended
RSM was validated against wind tunnel experiments of Gromke and Ruck (2012) and
a grid sensitivity study was performed. For the dispersion calculations of pollutant c,
a turbulent Schmidt number of Sct = 1.0 was used. Second order discretizations were
employed and boundary conditions and computational settings were specified
according to Blocken et al. (2007), Franke et al. (2007) and Tominaga et al. (2008).
Normalized concentrations c+ = c∙Uh/Q
Results
The central park resulted in comparison to the completely built-up configuration in lower concentrations at downwind
locations in the central wind-parallel street canyons (G4, I4). In particular the high concentrations in street G4 were
considerably reduced. Decreased concentrations were also present in the street next to the park (E4), however, immediately
windward, in street D5, higher concentrations were observed. The traffic emissions enter the park at its windward side where
concentration levels were similar to those in the street network and escape from the urban canopy at the leeward park side.
Conclusions
The results of this study suggest that parks are an effective measure for warranting or improving air quality in urban areas. A
distributed arrangement of parks increases the natural ventilation within the building canopy and results in decreased traffic
pollutant charges. In particular hot spots with high concentrations are defused.
Acknowledgement
The research was supported by a Marie Curie Intra European Fellowship within the 7th European Community Framework
Programme.
References
Ayotte, K.W., Finnigan, J.J., Raupach, M.R., 1999. A second-order closure for neutrally stratified vegetative canopy flows. Boundary-Layer
Meteorology 90, 89-216.
Blocken, B., Stathopoulos, T., Carmeliet, J., 2007. CFD simulation of the atmospheric boundary layer: wall function problems. Atmospheric
Environment 41, 238-252.
Franke, J., Hellsten, A., Schlünzen, H., Carissimo, B., 2007. Best practice guideline for the CFD simulation of flows in the urban
environment. COST Action 732, pp52.
Gromke, C., Ruck, B., 2012. Pollutant concentrations in street canyons of different aspect ratio with avenues of trees for various wind
directions. Boundary-Layer Meteorology 144, 41-64.
Tominaga, Y., Mochida, A., Yoshie, R., Kataoka, H., Nozu, T., Yoshikawa, M., Shirasawa, T., 2008. AIJ guidelines for practical
applications of CFD to pedestrian wind environment around buildings. J. of Wind Engineering and Industrial Aerodynamics 96, 1749-1761.
116
PARTICLE SURFACE AREA SIZE DISTRIBUTIONS IN DIFFERENT URBAN AEREAS
H. Kuuluvainen (1), A. Järvinen (1), L. Pirjola (2), J. V. Niemi (3), R. Hillamo (4), J. Keskinen (1) and T. Rönkkö (1)
(1) Tampere University of Technology, Department of Physics, P.O. Box 692, 33101 Tampere, Finland
(2) Department of Technology, Metropolia University of Applied Sciences, P.O. Box 4021, 00180 Helsinki, Finland
(3) Helsinki Region Environmental Services Authority HSY, P.O. Box 100, 00066 HSY, Helsinki, Finland
(4) Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
Presenting author email: heino.kuuluvainen@tut.fi
Summary
The size distributions of the lung deposited surface area were measured in different urban areas in the metropolitan area of
Helsinki. The electrical low pressure impactor (ELPI) was calibrated and used in these measurements. The average surface
area size distributions from different urban environments clearly show different sources for the lung deposited surface area,
from which the traffic seems to be most significant.
Introduction
Numerous of studies are reporting particle mass and number concentrations in urban areas (e.g. Putaud et al., 2004).
However, it has been argued that none of these metrics describes properly the negative effect of particles on human health. In
this respect, particle surface area concentration is more relevant (Oberdörster, 2001). Some surface related quantities, as the
lung deposited surface area or the active surface area, have been proposed to be the metric for the negative health effects.
Common for these surface related quantities is that they are rather close to the response of a diffusion charger. For example,
the nanoparticle surface area monitor (NSAM) is based on diffusion charging and it measures the lung deposited surface area
concentration. In this study, an electrical low pressure impactor (ELPI) is calibrated and used to measure the lung deposited
surface area concentrations in different urban areas in Helsinki. The advantage of the ELPI is that, in addition to the total
concentration, also the surface area size distributions can be analysed. Thus, the previous knowledge of the number size
distributions, the chemical composition and the morphology of the particles can be compared to the lung deposited surface
area.
Experimental
Measurements were carried out during two different measurement campaigns in the metropolitan area of Helsinki. The first
campaign was held in February 2012 and the second campaign in October 2012. Both campaigns included stationary
measurements at different measurement sites and on-road measurements with a mobile laboratory ‘Sniffer’. One of the
measurement stations was located at a residential area in Espoo, the second in a park close to the city centre representing
urban background and the third next to a busy main road. On-road measurements represent the variety of different routes in
the metropolitan area including the city centre, main roads and residential areas. In order to use the ELPI for surface area
measurements, the instrument was calibrated by comparing the output of the instrument to the signal of an NSAM and to the
size distributions given by a differential mobility particle sizer (DMPS). In all the experiments, an ELPI was used to measure
particle surface area size distributions. The results were also compared to simultaneous PM2.5, PM10 and particle number
measurements.
Results
The average surface area size distribution from three different
measurement stations and on-road measurements are shown in
Fig. 1. It is seen that the shape of the distributions varies and the
surface area is emphasized in different size ranges at different
environments. The total surface area concentration is clearly
higher in the on-road and road side measurements compared to
the results from urban background and residential area, as
expected. Especially, the soot mode and non-volatile particles
from traffic seem to dominate in the surface area distribution. In
the residential area, the surface area distribution was highly
affected by the amount of long range transported background
aerosol.
Acknowledgement
This work was supported by CLEEN Ltd., the Cluster for Energy
and Environment through the Measurement, Monitoring and
Environmental Assessment (MMEA) research program.
References
Oberdörster G., 2001. Pulmonary effects of inhaled ultrafine
particles. Int. Arch. of Occup. and Environ. Health 74, 1-8.
Putaud J.-P. et al., 2004. A European aerosol phenomenology - 2:
chemical characteristics of particulate matter at kerbside, urban,
rural and background sites in Europe. Atmos. Environ. 38, 25792595.
117
Fig. 1: The average surface area distributions from
different environments. The distributions are normalized
but comparable to each other.
SYNCHRONOUS MOBILE MEASUREMENTS WITHIN A DENSE URBAN VALLEY
E. R. Somervell (1), J. Salmond (2), I. D. Longley (1), K. Dirks (2), G. Olivares (1), S. Grange (2)
(1) National Institute for Water and Atmosphere (NIWA), Auckland, New Zealand; (2) University of Auckland, Auckland,
New Zealand
Presenting author email: elizabeth.somervell@niwa.co.nz
Summary
The PENAP study sets out to determine the Personal Exposure to Noise and Air Pollution within the central business district
of Auckland, New Zealand. Particle number, carbon monoxide (CO) and noise levels were measured on a per second basis
along streets with varying traffic dynamics to determine the range of air quality and ambient noise that the public are exposed
to in downtown Auckland. Preliminary results indicate differences that may be connected to traffic volume and the
proportion of heavy duty vehicles, in particular, buses. This has implications for future planning of public transport routes
into and around the CBD.
Introduction
Auckland is New Zealand’s largest city both in area and population, with a small dense urban central business district (CBD).
The main street – Queen Street (shown in red in Figure 1) runs along the floor of a narrow valley channel approximately 1.5
km long and 300 m ridge to ridge. The channel outflows to the harbour. At the bottom of the valley is Auckland’s central bus
and train station. Queen St has the highest pedestrian counts in the Auckland region. Along with adjacent streets it is also
where high volumes of cars and diesel buses converge. Slow moving traffic, particularly diesel buses, can produce high
levels of air pollution which, along with noise, have huge effects on public health, amenity and subjective wellbeing.
The aims of PENAP were to: 1) Characterise levels of traffic-related air pollutants in the Queen Street valley, 2) Determine
the contribution of bus emissions to levels of traffic-related air pollutants in the Queen Street valley, and 3) Characterise the
nature of the noise in the Queen Street Valley and assess peoples’ perceptions of the urban soundscape. It was expected that
large differences would be observed in pollutants and noise levels between heavy
trafficked routes and more pedestrianised streets. However, a number of physical
factors might also influence this relationship. The predominant wind direction in
the area is South-east, running almost parallel to Queen Street, and building
heights and configurations are not uniform, with smaller roads having a more
“classic” canyon structure than larger streets. In addition, the cross roads are at
gradient, which leads to additional vehicle emissions.
Methodology and Results
Multiple routes were devised for researchers to traverse on foot at 15 minute
intervals. The routes included Queen Street and streets running parallel and
crossways from Queen Street and were chosen to represent pedestrianised, low
and high traffic volumes with diesel buses. The routes were walked from 08:30
to 09:30 during morning peak traffic and from 12:30 to 13:30 during lunchtime
on week days of late winter/early spring (September 2013).
Along each route a researcher carried a dosimeter to record frequency and
intensity of noise, a CO monitor (T15N, Langan Inc) and a portable CPC (Ptrak,
TSI Inc) counting particle number at one second resolution. If a peak in the realtime particle count could be attributed to a source, then a note was made. Sources
observed included buses, municipal trucks, smokers and eating establishments. In
total, 129 runs were completed over eight different routes.
Preliminary results indicate differences in routes can be discerned in the data.
Figure 2 shows the distribution of CO along two main streets. The x axis shows
the concentration recorded by the Langan and the y axis the number of records
with that concentration. Queen Street has peak concentrations at approximately
1.0 ppm, whilst Wellesley Street, a cross street with more bus traffic shows a
much lower peak near 0.5 ppm.
N
Fig.1 3-D map of Auckland CBD (Queen
Street in red) from the National Business
Review, http://www.nbr.co.nz/article/a-3dview-auckland-super-city-112320 accessed
19/09/2013
Conclusions
PENAP extends the knowledge base around environmental quality within the
Auckland CBD, and will enable greater engagement with this knowledge base by
interested stakeholders, including the public. The results will inform planning
decisions regarding transport in the CBD (e.g. vehicle numbers, technologies,
routes and operating patterns).
Acknowledgement
This work was supported by the Heart of the City, the Auckland Council, The
University of Auckland, NIWA and Auckland University of Technology. We
acknowledge the invaluable assistance of all those who talk part in the sampling
during the campaign.
118
Fig.2 Distribution of CO concentrations (in
ppm/100 along Queen and Wellesley Streets
MODELLED URBAN ACETALDEHYDE CONCENTRATION ASSOCIATED WITH BIOETHANOL FUELLED
TRANSPORT
S. López-Aparicio and I. Sundvor
NILU – Norwegian Institute for Air Research, Instituttveien 18, Kjeller 2027, Norway
Presenting author email: sla@nilu.no
Summary
The use of bioethanol fuelled vehicles has increased worldwide and may create new undesired pollution effects. This study
shows the preliminary results obtained from air dispersion modelling of acetaldehyde concentration in Oslo associated with
the circulation of bioethanol vehicles. Different scenarios, both realistic and hypothetical, have been considered such as 1) a
realistic baseline scenario where one bus line is running with bioethanol (E95; 95% ethanol - 5% gasoline); 2) a hypothetical
scenario where all heavy duty vehicles are running with E95; and 3) a hypothetical scenario with an entire E95-fleet.
Introduction
A previous study carried out in Oslo (López-Aparicio and Hak, 2013) showed that the use of bioethanol as fuel for
transportation can have adverse impact on urban air quality. Acetaldehyde and acetic acid were identified as of concern based
on ambient and on-line measurements. Acetaldehyde was 1) measured at very high concentration in the exhausts of an
E95-bus (> 150 ppm), 2) measured at higher ambient concentrations at locations exposed to the E95-buses than not expose,
and 3) estimated to be above the threshold limit value at close distance to the bus. Air dispersion modelling has been applied
to estimate acetaldehyde concentration in the urban area (i.e. Oslo) and associated with combustion from bioethanol vehicles
considering different scenarios.
Methodology
Ambient urban concentration of acetaldehyde has been modelled with the Air Quality Information System, AirQUIS, which
performs emission-, dispersion- and exposure calculations. The applied dispersion model (EPISODE) is an Eulerian finite
difference grid model for area sources with embedded sub-grid models for the treatment of line and point sources.
Modelled Acetaldehyde (µg m -3)
Results
Acetaldehyde is harmful to human health and contributes to the formation of O3 and peroxyacyl nitrates (PAN), harmful
photochemical oxidants. The increased chance of developing cancer is one-in-a-hundred thousand for an individual breathing
air containing 5 µg m-3 of acetaldehyde during the entire life. The modelled gridded results for a baseline scenario show
average acetaldehyde concentrations in winter below 1.5 µg m-3. For the worst case scenario however, the model results show
that winter average acetaldehyde levels reach values well above 5 µg m-3 for a large part of the highly populated areas in
Oslo. Figure 1 shows the comparison of modelled results in the baseline (acetaldehyde levels < 10 µg m-3) and E95-fleet
scenarios (acetaldehyde levels < 65 µg m-3) at street side in one of the streets in Oslo along the E95-bus line.
70
60
50
40
70
Baseline Scenario
60
10
50
40
5
30
30
20
0
20
10
10
0
E95-fleet Scenario
Oct’09
Nov’09
Dec’09
Jan’10
Feb’10
Mar’10
0
Oct’09
Nov’09
Dec’09
Jan’10
Feb’10
Mar’10
Fig. 1: Modelled hourly acetaldehyde concentration at a roadside in Oslo (Sannergate) in the baseline, one E95-bus line
(left) and entire E95-fleet (right) scenario.
Conclusions
The modelled acetaldehyde concentration supports the conclusions from previous study based on measurement data,
indicating that the use of bioethanol as fuel for transportation can have adverse impact on urban air quality and therefore on
human exposure. This study shows an example of how climate change policies, as changing from fossil fuels to biofuels,
need to be carefully assessed as their consequences may involve a worsening of the local air quality.
Acknowledgement
This study was made possible thanks to the financial support of the Norwegian Research Council (208275/F40).
References
López-Aparicio S., Hak C., 2013. Evaluation of the use of bioethanol fuelled buses based on ambient air pollution screening
and on-road measurements. Science of the Total Environment 452-453, 40-49.
119
DEVELOPMENT AND ASSESSMENT OF TRAFFIC-RELATED EMISSION ABATEMENT MEASURES FOR
THE MADRID CITY (SPAIN) THROUGH THE WRF-SMOKE-CMAQ MODELLING SYSTEM
R. Borge, J. Lumbreras, D. de la Paz, J. Pérez, M. E. Rodríguez
Laboratory of Environmental Modelling. Technical University of Madrid, (UPM). C/ José Gutiérrez Abascal 2, 28006
Madrid, Spain
Presenting author email: jlumbreras@etsii.upm.es
Summary
The achievement of the limit values established in the European legislation pose an important handicap for large urban areas
with intense road traffic, such as Madrid (Spain). Despite permanent measures included in air quality plans it is important to
assess additional measures that may be temporally applied under unfavourable conditions. This paper reports on the
simulation of different traffic restriction strategies in Madrid for high-pollution episodes.
Introduction
As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable modelling tools are
needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large cities across
Europe, particularly for NO2. Besides a consistent and robust multi-scale modelling system, comprehensive and flexible
emission inventories are needed. This paper discusses the application of the WRF (Skamarock and Klemp, 2008)-SMOKE
(Institute for the Environment, 2009)-CMAQ (Byun and Schere, 2006) system to the Madrid city (Spain) to assess the impact
of the local strategy to improve air quality and meet the legal requirements in the near future.
Methodology and Results
A detailed emission inventory and a future-year scenario were compiled for the development of an urban air quality plan for
Madrid. The inventory relies on bottom-up methods for the most important sources. It is coupled with the regional traffic
model and it makes use of an extensive database of industrial, commercial and residential combustion plants.
The future-year scenario takes into account the expected result
of a package of 70 measures included in the Madrid Air
Quality Plan (AQP). According to Borge et al. (2014), this
AQP would cut down NOX emissions by 31% and would
allow the fulfilment of NO2 limit values in Madrid by the end
of 2014.
Nonetheless, this paper explores the complementary effect of
additional, temporal measures to be applied during highpollution episodes. The effect of road traffic access restriction
under a 10-day high pollution episode to the city centre (LEZ)
are modelled and discussed. The effect of limiting the access
of 20% and 50% of passenger cars, both including and
excluding residents in the LEZ as well as specific limitations
to taxis was modelled.
The results show that under unfavourable meteorological
conditions and high NO2 concentration the effects of temporal
restrictions to road traffic in central area of Madrid have a
limited effect except for rather stringent limitations (50% of
passenger cars including residents) that would bring about
reductions in the peak hour up to 25 µg/m3 (Fig 1).
Fig.1 Effect of traffic restrictions (maximum 1-h NO2 concentration)
Conclusions
Road traffic is the main responsible of air quality issues in Madrid. Temporal traffic restrictions may help to avoid very high
pollution levels but only if strong measures are applied in relatively large areas. It was found that traffic restrictions turn out
in a net reduction of traffic although redistribution may produce slight increases of emissions in the LEZ surroundings. The
experiments also indicate that the effect diminishes rapidly with distance, so the reduction in the city outskirts may be
negligible depending on meteorological conditions.
Acknowledgments
The Madrid City Council provided the traffic model outputs and funded this study.
References
Borge, R., Lumbreras, J., Pérez, J., de la Paz, D., Vedrenne, M., de Andrés, J.M., Rodríguez, M.E., 2014. Emission
inventories and modeling requirements for the development of air quality plans. Application to Madrid (Spain). Science of
The Total Environment 466–467, 809-819.
Byun, D.W., Schere, K.L., 2006. Review of the governing equations, computational algorithms and other components of the
models-3 community multiscale air quality (CMAQ) modeling systems. Applied Mechanics Review 59 (2), 51–77.
Institute for the Environment, 2009. SMOKE v2.7 user's manual.University of North Carolina, Chapel Hill, NC (2009).
Skamarock, W.C. and Klemp, J.B., 2008. A time-split non-hydrostatic atmospheric model. Journal of Computational Physics
227, 3465–3485.
120
THE VERTICAL PROFILES OF PM2.5 AND O3 MEASURED IN AUTUMN AND WINTER FROM A 325METER-METEOROLOGICAL TOWER IN URBAN BEIJING, CHINA
D. S. Ji, Y. S. Wang, Y. Sun
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric
Physics, Chinese Academy of Sciences, Beijing, 100191, PR China
Presenting author email: jds@mail.iap.ac.cn
Summary
To gain a better understanding of the complex interactions between air pollutants and meteorological variables, and influence
on the air quality of a polluted megacity, simultaneous measurements of near-surface O3, PM2.5 and meteorological
parameters were conducted at 325-m meteorological tower in the urban areas of Beijing. Vertical profiles of O3 (8m, 47m,
120m and 280m) and PM2.5 (8m, 80m and 240m) were investigated at a 325-m meteorological tower from Sep. 1, 2004 to
Feb. 28, 2005 and from Sep. 1, 2009 to Feb. 28, 2010. The results showed the O3 concentrations increased with altitude in
both the autumn and the winter. Unlike O3, the PM2.5 concentrations were very similar at 8-m and 80-m levels while the
PM2.5 concentrations at 280-m level were lower than those at 8-m and 80-m levels. Moreover, the clearly defined vertical O3
and PM2.5 gradients were found at night except at around 0:00. However, the vertical PM2.5 and O3 gradients were less
evident or were negligible when a well-mixed convective layer developed.
Introduction
Increasing amounts of gaseous pollutants are emitted into the atmosphere on local, regional and global scales, resulting in
damage to human health and the environment. Especially, air pollution attributed to PM2.5 and ozone (O3) has caused great
concern. With the development of urbanization, the space of human activity gradually expands from the ground to high
altitude. Wide attention is paid to vertical distribution of air pollutants in planetary boundary layer (PBL) and the complicated
processing driven by interplay between chemistry and vertical mixing. Considering this, this present study aimed to obtain a
detailed and comprehensive data set for use in understanding the chemistry of air pollutants in complex meteorological
conditions in the urban Beijing and for use in the testing of an upcoming modeling study.
Methodology and Results
Four O3 monitoring stations were built at platforms located at heights of 8, 47,
120 and 280m on the tower. Three PM2.5 monitoring stations were built at
platforms located at heights of 8, 80m and 240m on the tower. Early morning and
later night profiles show very structured vertical distributions of all parameters
indicating as expected, limited vertical mixing under the nocturnal inversion. The
ozone concentrations were higher than at 280 m because of the lack of vertical
exchange, thus avoiding the titration of NO. The urban site experienced more
influence because of the high NO emissions near the ground. Once the NBL breaks
up, ground-based measurements of O3 and PM2.5 are similar at different heights.
The diurnal variation of the PM2.5 concentration shows two peaks, one in the early
morning and the other during the evening at 8-m and 120-m levels. While an
obvious peak of PM2.5 was observed from 9:00 to15:00 at 280-m level. The
measurement with a flat vertical gradient and low surface O3 and PM2.5
concentrations is found in type-1(strong wind days); a gradual increase of O3 with
altitudes and modest surface O3 and PM2.5 concentrations is found in type-2 (clear
days); a weak vertical gradient with low surface. O3 and PM2.5 concentrations is
found in type-3 (rainy days); a sharp vertical gradient (NOx and O3 being strongly
Fig.1 Sampling location in Beijing 325-m
Meteorological Tower.
depressed in the PBL) with high surface O3 and PM2.5 concentrations is found
in type-3 (hazy days). The results showed detailed vertical distributions of O3
and PM2.5 are very important for assessing the impacts of atmospheric stability
on O3 and PM2.5 chemistry.
Conclusions
The results showed detailed vertical distributions of O3 and PM2.5 are very
Fig.2 The vertical distribution of O3 and PM2.5
important for assessing the impacts of atmospheric stability on O3 and PM2.5
during the autumn and winter.
chemistry. This study provided a complete and detailed analysis of
meteorological and chemical data in the lower boundary layer of an urban environment. Therefore, understanding these
features will provide a significant challenge for coupled meteorological-chemical models. The measurements may be applied
to improve the results of models.
Acknowledgement
This work was supported by the Key Project of the Chinese Academy of Sciences (XDB05020200) and the Key Project of National Natural
Science Foundation of China (Y312011801).
References
Tang, G., Wang, Y., Li, X., Ji, D., Hsu, S., Gao, X., 2012. Spatial-temporal variations of surface ozone and ozone control strategy for
Northern China.
121
MULTI-YEAR CHARACTERISATION OF METALS CONCENTRATIONS IN AEROSOL COLLECTED IN
DIFFERENT SITES OF THE VENICE LAGOON
E. Morabito (1), D. Cesari (2), D. Contini (2), A. Gambaro (3), P. Campostrini (4), C. Dabalà (4), F. Belosi (5)
(1) CNR-IDPA, Venezia, Italy; (2) ISAC-CNR, Lecce, Italy; (3) DAIS Dep., Ca’Foscari University, Venezia, Italy; (4)
CORILA, Venezia, Italy; (5) ISAC-CNR, Bologna, Italy
Presenting author email: elisamora@unive.it
Summary
This work presents and discusses the results from measurements of PM10 concentrations and of its content in metals obtained
in different sites of the Venice lagoon area where the construction of the mobile gates (MOSE) is going on. Measurements
were taken between 2007 and 2013 and were statistically analysed, using correlation with local meteorology. The objective of
the analysis was to characterise the spatial and seasonal variability in concentrations getting information on probable aerosol
sources. Multi-year trends in absolute and relative concentrations will be discussed in relation to air quality in the lagoon
area.
Introduction
The Venice Lagoon is exposed to atmospheric pollutants emitted by a number of sources such as industrial activities,
thermoelectric power plants, petrochemical plants, incinerator plants, domestic heating, ship traffic, glass factories and
vehicular emissions transported from the mainland (Prodi et al, 2009; Stortini et al., 2009).
Concentration(ng/m3)
Methodology and Results
The PM10 samples were collected using low volume sequential aerosol samplers (Skypost PM-TCR Tecora). The filters
employed were in quartz (Sartorius, diameter 47 mm) were
50
Chioggia
carefully decontaminated in an atmosphere-controlled
45
P.Sabbioni
laboratory, using a procedure described elsewhere (Stortini
40
Malamocco
al., 2009). Inorganic elements (V, Cr, Fe, Co, Ni, Cu, Zn, As,
35
Mo, Cd, Sb, Tl, and Pb) in PM10 samples were measured by
30
Inductively
Coupled
Plasma-M
Quadrupole
Mass
25
Spectrometer (ICP-QMS, Agilent 7500). In cases of
20
concentrations below the LOD, or not detectable above the
15
average variability of the field blanks, a threshold
10
concentration equal to the maximum between the LOD and
5
B was assumed. Particularly, the thresholds (in ng) were: V
0
(10.9), Cr (346.6), Fe (3839.7), Co (7.0), Ni (435.1), Cu
V
Cr
Co
Ni
Cu
Zn
As
Mo
Cd
Sb
Pb
(105.8), Zn (3349.0), As (17.1), Mo (2922.9), Cd (1.4), Sb
Fig.1 Average metals concentrations in PM10.
(93.4), Tl (6.2) and Pb (148.8). Recovery and accuracy was
evaluated using standard reference material (NIST®1684). Figure 1 shows the average concentrations and the standard errors
for different metals in PM10 collected at three sites: Punta Sabbioni (199 daily samples), Malamocco (190 daily samples) and
Chioggia (168 daily samples). Samples were collected in different measurement campaigns between 2007 and 2013.
Conclusions
The statistical comparison of the measurements of the inorganics elements in the different years showed limited differences
in the concentrations measured at the three sites indicating a relatively homogeneous spatial distribution of metals in PM10 in
the Venice lagoon area. This was probably due to the presence of the specific meteorological circulation, which mixes air
masses arriving from different directions, favouring the re-circulation and spread of pollutants in the lagoon area. The
evaluation of the crustal enrichment factors (EFs) indicated significant enrichment for Pb, Cd, Sb, As, Zn, Cu and Ni, while
elements mainly of crustal origin were Tl, and Co. V and Cr are enriched but the values of EFs are lower than the threshold
of 20 so that it is not possible to exclude also a contribution of crustal nature. The EF of V is larger at Malamocco and this is
compatible with a possible contribution of ship traffic emissions (characterised by V and Ni) at the Malamocco site, which is
located near the path of commercial shipping.
Acknowledgement
This work was supported by the Italian Ministry of Infrastructure and Transport - Venice Water Authority – through its
dealer Consorzio Venezia Nuova. The authors wish to thank the Venice Water Authority for permission to use the data and
CORILA (Consortium for Managing the Research Activities Concerning the Venice Lagoon System) for the valuable
assistance and logistic support during the sampling campaigns.
References
Prodi F., Belosi F., Contini D., Santachiara G., Di Matteo L., Gambaro A., Donateo A., Cesari D., 2009. Aerosol fine fraction
in the Venice Lagoon: particle composition and sources. Atmos. Res. 92(2), 141–150.
Stortini A.M., Freda A., Cesari D., Cairns W.R.L., Contini D., Barbante C. et al., 2009. An evaluation of the PM2:5 trace
elemental composition in the Venice Lagoon area and an analysis of the possible sources. Atmos. Environ. 43(40), 6296–
6304.
122
VALIDATION OF NEW PARAMETERISATIONS FOR THE
OPERATIONAL STREET POLLUTION MODEL (OSPM)
M. Ketzel (1), O. Hertel (1), T.-B. Ottosen (1,2), K. Kakosimos (2) and R. Berkowicz (1)
(1) Department of Environmental Science, Aarhus University, 4000 Roskilde, Denmark;
(2) Department of Chemical Engineering, Texas A&M University at Qatar, Doha, Qatar
Presenting author email: mke@dmu.dk
Summary
The formulations within the Operational Street Pollution Model (OSPM) have been widely applied in the air pollution
community for more than two decades. In the presented work some of the paramerisations used by OSPM have been revised
and tested against several street datasets. One of the parameters concerns special cases with variable height of the buildings
along the street canyon including one-sided street canyons as often observed under practical applications. The so-called
“general building height” that is now estimated by the program, while it was not clearly defined earlier, leading to arbitrary
results. This issue has been pointed out by several OSPM users and is of interest for a wider community.
Introduction
OSPM is a semi-empirical parametrised model (Berkowicz, 2000 or: www.au.dk/OSPM) and frequently used for local- or
street-scale assessment of air pollution. OSPM is a present state of the art model and has undergone more evaluations than
any other model (Kakosimos et al. 2010). As one of the most often used street pollution models, OSPM is part of many air
pollution forecast systems (e.g. Danish THOR, Swedish SIMAIR, Norwegian VLUFT) and single air pollution models (e.g.
UK-ADMS, Belgian IFDM model). For the last 10 years most of the work on OSPM was focused on the development and
improvement of the health impact assessment and of the functionality of the graphical user interface (Kakosimos et al. 2010).
An on-going comprehensive review of OSPM (Ottosen et al. 2013) is addressing some shortcomings of the original model
and extending the applicability of the model. In connection with this review, we present here some improvements in OSPM
e.g. concerning the definition of the general building height that has previously led to incorrect model results (Ketzel et al.
2012) and the formulation of the recirculation.
Methodology and Results
In OSPM the building configuration of an “ideal” street
canyon is defined by the parameters: default building height
and street width. In real world applications the buildings along
the street usually don’t have the same height. To account for
this, exceptions of the building height for relevant wind
direction intervals can be defined including zero height for
missing buildings or openings in the street canyon.
-Fig. 1 shows an example for a street with variable building
heights with respect to wind direction seen from the receptor
point (H_upwnd_bldg, blue line). The suggested procedure
sorts all the building sectors (including the width of the
buildings) for all directions 0…360 deg according to the
building height in descending order (H_up_sort in Fig.1). The
Figure 1. Example of a street with variable building height and
implementation of new general building height (GBH)
new general building height is now defined as the weighted
average over the building heights in the range 0…180. This
procedure is consistent with the simple definition in the special
case of no exception (uniform building height) or uniform
buildings on one side of the canyon.
Another change in the OSPM parameterisation presented
concerns the calculation of the recirculation component of the
pollution for wide street canyons where the recirculation zone
is not covering the full canyon, see Fig. 2.
Conclusions
The new formulation of the “general building height” in
OSPM solves the problem of ambiguous results in cases of
variable building height.
Figure 2. Sketch of the principle assumptions for calculation of
recirculation component within OSPM
References
Berkowicz, R., OSPM - A parameterised street pollution model. Environ. Monit. and Assessment, 2000. 65(1-2): p. 323-331.
Ketzel M, Jensen SS, Brandt J, Ellermann T, Olesen HR, et al. (2012) Evaluation of the Street Pollution Model OSPM for
Measurements at 12 Streets Stations Using a Newly Developed and Freely Available Evaluation Tool. J Civil Environ Eng S1:004.
doi:10.4172/2165-784X. S1-004
Kakosimos K., Hertel O., Ketzel M., Berkowicz R., 2010. Operational Street Pollution Model (OSPM) – a review of performed application
and validation studies, and future prospects. Environ. Chem. 7, 285-503.
Ottosen T-B, Kakosimos K., Ketzel M., Hertel O., Berkowicz R., 2013. Application and Development of the Operational Street Pollution
Model (OSPM) to Complex Geometries and Dry Climates, This Volume.
123
HIGH RESOLUTION MAPPING OF ATMOSPHERIC POLLUTANTS IN URBAN ENVIRONMENTS UTILISING
DATA FROM SENSOR NETWORKS
M. D. Mueller (1), C. Hueglin (1), D. Hasenfratz (2), O. Saukh (2), V. B. Bright (3), O. A. M. Popoola (3), R. Jones (3)
(1) Empa, Swiss Federal Laboratories for Materials Science and Technology, Duebendorf, Switzerland; (2) ETH Zurich,
Computer Engineering and Networks Laboratory, Zurich, Switzerland; (3) Department of Chemistry, University of
Cambridge, Cambridge, UK
Presenting author email: michael.mueller@empa.ch
Summary
We present first results of statistical models for real-time mapping of atmospheric pollutants with high spatial and temporal
resolution in urban environments utilising data obtained from low-cost sensor networks.
Introduction
Current knowledge between concentrations of atmospheric pollutants and health effects is to a large extent based on
epidemiological studies. Such studies require accurate estimates of the personal exposure of the participating individuals.
However, high quality exposure estimates are difficult to obtain, especially for pollutants with high spatial and temporal
variability such as nitrogen dioxide (NO2), soot (or black carbon, BC) and ultrafine particles (UFPs). Epidemiological studies
at present are either based on data from the existing monitoring networks or on dedicated measurement campaigns with
sampling designs that allow for an improved (but still limited) representation of the spatial variation of air pollutants (e.g.
Beelen et al., 2013).
Possible approaches to improve exposure estimations are dispersion modelling and spatially much denser air pollutant
measurements than existing conventional networks can provide. Sufficiently dense networks have become viable with the
recent development of small and inexpensive sensors for the measurement of trace gases or aerosols in ambient air. These
devices have typically a low power consumption and can easily be deployed in a large number to form a wireless sensor
network. These networks offer new opportunities for the mapping of pollutant concentrations in cities with high temporal and
spatial resolution and therefore for personal exposure estimation and other applications in air quality assessment.
Methodology
We use the data obtained from two sensor networks together with land-use information (GIS data) for statistical modelling of
the spatial distribution of air pollutants in cities. One of the networks is the OpenSense mobile sensor network consisting of
10 sensor nodes installed on top of 10 streetcars operating since 2012 on a regular schedule in Zurich, Switzerland
(www.opensense.ethz.ch). The second sensor network is a static one consisting of 46 sensor nodes deployed for two months
in 2010 in Cambridge, UK (Mead et al., 2013).
We investigate the potential of statistical models such as land-use regression (LUR) models and classification approaches for
the generation of air pollution concentration maps with high spatio-temporal resolution. Sensor performance together with the
spatial and temporal variability of the pollutants are quantified. Spatio-temporal characteristics of pollutant concentrations are
analysed in order to determine suitable predictor variables which are then incorporated into the statistical models. Limits for
the minimum temporal and spatial resolution of maps derivable from the available data set are assessed.
Conclusions
Low-cost, high density sensor networks provide a unique opportunity for the assessment of the small-scale variability of air
pollutants in cities. In order to fully exploit this opportunity, further research on the design of sensor networks (e.g. number
and siting of sensor nodes), their operation (e.g. quality assurance and quality control) and the use of sensor data for high
resolution mapping of air pollutants in cities is needed.
Acknowledgement
Support from the Nanotera.ch (projects OpenSense and inUse) is gratefully acknowledged.
References
Beelen, R., G. Hoek, D. Vienneau, M. Eeftens, K. Dimakopoulou, et al., 2013. Development of NO2 and NOx land use
regression models for estimating air pollution exposure in 36 study areas in Europe – The ESCAPE project. Atmospheric
Environment 72(0): 10-23.
Mead, M. I., O. A. M. Popoola, G. B. Stewart, P. Landshoff, M. Calleja, et al., 2013. The use of electrochemical sensors for
monitoring urban air quality in low-cost, high-density networks. Atmospheric Environment 70(0): 186-203.
124
IMPACT OF THE ECONOMIC CRISIS ON WINTERTIME AIR QUALITY IN THESSALONIKI, GREECE
Arian Saffari (1), Nancy Daher (1), Constantini Samara (2), Dimitra Voutsa (2), Athanasios Kouras (2), Evangelia Manoli
(2), Olga Karagkiozidou (2), Christos Vlachokostas (3), Nicolas Moussiopoulos (3), Martin M. Shafer (4), James J. Schauer
(4), Constantinos Sioutas (1)
(1)University of Southern California, Department of Civil and Environmental Engineering, 3620 South Vermont Avenue,
Los Angeles, CA 90089, USA; (2)Aristotle University of Thessaloniki, Department of Chemistry, Environmental Pollution
Control Laboratory, 54124 Thessaloniki, Greece; (3)Aristotle University of Thessaloniki, Department of Mechanical
Engineering, Laboratory of Heat Transfer and Environmental Engineering, 54124 Thessaloniki, Greece; (4)University of
Wisconsin-Madison, , Environmental Chemistry and Technology Program, Madison, WI, USA
Presenting author email: sioutas@usc.edu
Summary
A wintertime sampling campaign of PM2.5 was conducted in Thessaloniki during winters of 2012 and 2013, in an effort to
quantify the extent to which the ambient air was impacted by the increased wood smoke emissions. The results indicated a 25-fold increase in the concentration of wood smoke tracers in 2013 compared to 2012. Concentrations of fuel oil tracers, on
the other hand, declined by 20-30% during 2013 compared to 2012. Moreover, a distinct diurnal variation was observed for
wood smoke tracers, with significantly higher concentrations in the evening compared to the morning. Correlation analysis
indicated a strong association between reactive oxygen species (ROS) activity and concentration of levoglucosan, galactosan
and potassium, underscoring the potential impact of wood smoke on PM-induced toxicity.
Introduction and Methodology
During the period of Greek financial crisis, switching from fuel oil burning for domestic heating to uncontrolled biomass
burning has caused significant air quality deterioration in Thessaloniki. In this study, urban PM2.5 samples were collected in
Thessaloniki during the wintertime of 2012 and 2013 along with a subset of morning and evening samples to determine the
diurnal variations. Chemical composition including metals and elements, ions, carbonaceous species and speciated organic
compounds were quantified using inductively coupled plasma mass spectrometry (ICPMS), ion chromatography (IC),
NIOSH EC/OC method and gas chromatography mass spectrometry
(GC-MS), respectively. Redox activity was also assessed by the
biological reactive oxygen species (ROS) assay.
Results and Discussion
PM2.5 mass concentration increased by 2-fold during the evening
compared to the morning (see Fig. 1) likely due to the increased
emissions from residential heating sources. PM2.5 mass concentration
in 2013 has also increased by 30% compared to 2012. Organic matter
(OM) was the dominant PM constituent with higher evening-time
contribution to the total mass compared to the morning (74%
compared to 58%), which is mostly due to the increased wood smoke
emissions in the evening time. Concentrations of V and Ni (tracers of
residual/fuel oil combustion) dropped by 30-50% in 2013. The
concentration of K, on the other hand, increased by 2-fold in 2013
suggesting that the residential heating method in Thessaloniki is
changing from the conventional fuel oil burning to the less expensive
Fig.1 Mass reconstruction of PM2.5 particles.
wood and biomass combustion. Concentrations of levoglucosan,
mannosan and galacsosan (organic tracers of wood smoke) (Nolte et al., 2001), are considerably (4-6 fold) higher in 2013
compared to 2012, which implies a significant increase in wood and
biomass burning in 2013 compared to 2012 (see Fig. 2).
Concentrations are also 3-4 times higher in the evening compared to
the morning. Moreover, positive correlations were observed between
ROS activity and water-soluble potassium, levoglucosan and
galactosan (R=0.74, 0.72 and 0.75, respectively), which indicates a
potentially significant effect of wood smoke emissions on the redox
activity of PM2.5.
Conclusions
The increase in total PM2.5 mass, OC, and tracers of biomass
combustion in 2013 compared to 2012 as well as association of wood
smoke tracers and PM-induced redox activity altogether imply the
deterioration of Thessaloniki’s air quality during the period of
economic recession. Active involvement of public authorities is thus
required to implement effective air pollution control strategies in the
area.
Fig.2 Variation of organic wood smoke tracers
Acknowledgements
We would like to thank the staff at the Wisconsin State Laboratory of Hygiene for their assistance with the chemical analyses
as well as the support of USC’s Provost and Viterbi fellowships. The authors also acknowledge the assistance of Mr.
Apostolos Kelessis from municipality of Thessaloniki for facilitating the sampling campaign.
125
ASSESMENT OF ORGANIC COMPOUNDS AS VEHICULAR EMISSION TRACERS IN THE ABURRA
VALLEY REGION OF COLOMBIA
M. Gómez (1), E. Posada (2), V. Monsalve (2)
(1) Politécnico Colombiano Jaime Isaza Cadavid, Carrera 48 # 7-151, Medellín, Colombia;
(2) INDISA S.A. Carrera 75 # 48 A 27, Medellín, Colombia
Presenting author email: enrique.posada@indisa.com
Summary
The Aburrá Valley region in Colombia, with Medellín as its main city, is an urban centre with about three million people. An
investigation was carried on to determine a set of baseline concentrations for n-octane, n-decane, n-pentadecane and
methylnaphtenes as vehicular emission tracers in the region. The VOC measurement campaigns based on TENAX tube
sampling and analysis according to TO-17 EPA method were done in areas of low and high vehicular flow as well as onboard measurements covering major Medellín road networks during a 24 hour period. The results show that there is a relation
between VOCs concentrations and vehicular activity. The diesel fuel sulfur content was detected as an important factor on
aliphatic hydrocarbon formation..
Introduction
VOCs tend to be highly polluting both from their inhalation effects and as a source of secondary pollutants. For the present
study they were classified into two (2) groups: polynuclear aromatic hydrocarbons (PAHs) and aliphatic hydrocarbons (AH).
These contaminants play an important role in today's environmental problems by their accumulation and persistence in the
environment (Wiederkehr et al, 1998). Some VOCs, especially those of high molecular weight, resists oxidation processes
and become persistent, being adsorbed on particles and transported over long distances (Guo et al., 2007), powering the
global greenhouse effect. So far no studies of these compounds have been done locally, so it was deemed important to carry
an exploratory work, in parallel with the fact that S content of diesel fuel was undergoing changes at the time, from 2000 to 5
ppm and it was desired to correlate those changes with the said VOCs concentrations.
Methodology and Results
A measurement campaign was conducted in three sites, two of them with heavy traffic, the other one with low or inexistent
traffic, from July to August 2011, with sampling periods of 24 hours. Each zone was evaluated during a week. Additional
samples were taken in the discharge of a diesel motor working under standardized laboratory conditions with diesel fuel of
variable S content. Another sample was taken sampling during 24 hours continuously within a vehicle moving through
designed zones in the city. The method applied was EPA TO-17 using 90 mm length, 5 mm dia. stainless steel TENAX
adsorption tubes filled with appropriate sorbent materials.
Table 1
S content in
VOCs in emisions,
diesel,ppm
μg/m3
1832
50
2155
500
3869
2100
Fig 1 Average results for the 4 zones
Figure 1 shows the results found for the zones. It was found that the higher concentrations of the studied tracers, correspond
to pentadecane and naphthalene. The On Board sample shows higher VOC´s concentration. The study of the diesel motor
emissions showed a clear effect of the S content of the fuel on the emissions of the studied VOC´s, see (table 1)
Conclusions
The region atmosphere is clearly polluted by VOC emissions generated by the diesel fuel and VOC concentrations are related
to vehicular traffic. An initial baseline has been established which should be useful for future work and public policy in
relationship to vehicle related pollution control. Reducing S content on diesel fuel has been a beneficial step in this direction.
Acknowledgement
This work was supported by POLITÉCNICO COLOMBIANO JAIME ISAZA CADAVID and ECOPETROL. We
acknowledge the DRI Institute for the analytical and sampling assistance and the University of Antioquia, GIMEL group, for
the work done in the laboratory motor testing.
References
Wiederkehr, P. et al, 1998. Urban Air Pollution. European Aspects. Kluwer Academic Publishers, Dordrecht, pp. 403-418.
Guo, H., et al, 2007. C1-C8 volatile organic compounds in the atmosphere of Hong Kong: Overview of atmospheric
processing and source apportionment. Atmospheric Environment, 41, 1456-1472
126
OVERVIEW OF ANTHROPOGENIC EMISSIONS OF VOC IN NORTHERN MID-LATITUDE CITIES
INFERRED FROM INTENSIVE AND LONG TERM OBSERVATIONS
A.Borbon (1), A. Boynard (2), V. Gros (3), N. Locoge (4), J. de Gouw (5)
(1) Laboratoire Interuniversitaire des Systèmes Atmosphériques, CNRS UPR7583, IPSL, UPEC & UPD; (2) LATMOS,
IPSL, CNRS, UPMC Uni. Paris 06; UVSQ; (3) LSCE UVSQ, CEA, CNRS, Gif sur Yvette, France (4) Mines Douai, DCE,
Douai, France (5) NOAA, CIRES, Boulder, CO, USA
Presenting author email: agnes.borbon@lisa.u-pec.fr
Summary
This presentation provides an overview of the spatial variability of the composition of anthropogenic Volatile Organic
Compound (VOC) emissions and the evaluation of regional emission inventories in urban areas of Europe and North
America with a special focus on Paris and Los Angeles megacities. First, we show that VOC urban composition is usually
consistent within a factor of 2 between all cities with no industrial influence. An exception is the atmosphere of Paris, which
shows an enhancement in C7-C9 aromatics by a factor of 3 compared to other cities. These results suggest that the emissions
of gasoline-powered vehicles still dominate the distribution for many hydrocarbons in northern mid-latitude urban areas,
which disagrees with the most recent emission inventories. However, regional characteristics like the gasoline composition
could affect the composition of hydrocarbon emissions. Secondly, the evaluation of emission inventories from observations
shows that there are still large discrepancies by a factor of 3 to 4 between observations and reference emission databases.
Introduction
VOC affect urban air quality and regional climate change by contributing to ozone formation and the build-up of Secondary
Organic Aerosols (SOA). Quantification of VOC emissions is a first critical step to design effective abatement strategies and
to predict VOC environmental impacts. However, commonly used bottom-up approaches are highly uncertain due to source
multiplicity and their great variability in time and space. Field observations of VOC from field campaigns and monitoring
programs can provide valuable constraints to evaluate emission inventories at the urban scale.
Methodology and Results
This work is based on hourly, in-situ observations collected during intensive field
campaigns in summertime (CalNexin Los Angeles, 2010 and MEGAPOLI in Paris,
2009) at ground level and on aircraft and by Air Quality Monitoring Networks.
VOCs were measured by state-of-the-art on-line techniques: a PTRMS and GCFID/MS. Two independent methods that take into account the effect of chemistry
were used to determine the emission ratios of anthropogenic VOCs relative to
acetylene and carbon monoxide (CO). Emission ratios from both methods agree
within ±20% showing the reliability of our approach. Emission ratios are fairly
consistent within a factor of 2 between all urban areas (Figure 1). One exception is
Paris where the fraction of C7-C9 aromatics, and to a lesser extent alkanes >C4, is 3
times higher than LA and other French and European urban areas. Large
discrepancies of a factor of 4 between observed emissions ratios and those
calculated from the inventories were revealed. Finally, changes in the seasonal
composition of urban air suggest that emission ratios determined on a seasonal basis
is an added value to constraint temporally resolved emission inventories for
different seasons.
Conclusions
Emissions of gasoline-powered vehicles still dominate the distribution for many
hydrocarbons in northern mid-latitudes urban areas despite efficiency control
emission measures at exhaust pipe, which disagrees with the most recent regional
emission inventories.
Acknowledgement
EU-FP/2007-2011 within the project MEGAPOLI, grant agreement
n°212520MEGAPOLI, ANR-MEGAPOLI-Paris, INSU/LEFE, NOAA,
CIRES, AASQA (AIRPARIF, ASPA, ATMOPACA, ATMO-RH).
Figure 1: Comparison of NMHC Emission Ratios
relative to acetylene in Los Angeles and Paris to
previous published studies in the US [Warneke et
al., 2007] and Europe [Borbon et al., 2003;
Dollard et al., 2007], respectively.
References
Borbon, A., J.B. Gilman, W. C. Kuster, N. Grand, S. Chevaillier, A. Colomb, C. Dolgorouky, V. Gros, M. Lopez, R. SardaEsteve, J. Holloway, J. Stutz, O. Perrussel, H. Petetin, S. McKeen, M. Beekmann, C. Warneke, D.D. Parrishand J.A. de
Gouw, Emission ratios of anthropogenic VOC in northern mid-latitude megacities: observations vs. emission inventories in
Los Angeles and Paris, J. Geophys. Res., 118, 2041-2057, 2013.
Boynard A., A. Borbon, T. Leonardis, B. Barletta, S. Meinardi, D.R. Blake, N. Locoge, Spatial and seasonal variability of
measured anthropogenic non-methane hydrocarbons in urban atmospheres: implication on emission ratios. Accepted for
publication in Atmos. Environ. (September 2013).
127
ATMOSPHERIC POLLUTION IN NORTH AFRICA. FACTS AND LESSONS IN THE SPANISH CITY OF
CEUTA
S. García Dos Santos (1), R. Benarroch Benarroch (2), R. Fernández Patier (1), M.A. Sintes Puertas (1), A. Aguirre Alfaro
(1), J.M. Cantón Gálvez (2), J. Alonso Herreros (1) and S. Guevara Hernández (1)
(1) Área de Contaminación Atmosférica. Centro Nacional de Sanidad Ambiental, Instituto de Salud Carlos III. Crta.
Majadahonda a Pozuelo km 2, 28220 Majadahonda (Madrid). Spain.
(2) Servicio Sanidad Ambiental. Consejería de Sanidad y Consumo. San Amaro s/n. 51001 Ceuta. Spain
Presenting author email: sgarcia@isciii.es
Summary
Ceuta is a 65 000 inhabitants Spanish city located on the North African shore line of the Gibraltar strait. Because of its
location and its special administrative status no an air quality network, with continuous monitoring, has been established yet.
Moreover, the local authorities have not a clear idea about the quality of the city ambient air pursuant to the provisions of EU
legislation. So, since 2010 to 2013 three field work campaigns were performed to determine the concentration of NO2, O3 and
VOC (benzene, toluene, etilbenzene, m+p-xilene and o-xilene) and PM10 and PM2,5. Therefore, for first time the analysis
showed the high importance of these pollutant concentrations especially for ozone, data which may be extrapolated to the
North Morocco nearby cities. Using those findings Ceuta local authorities decided to set a local air quality network for year
2014 and the Environmental Health Department obtained its first hint of the population exposure levels and their associated
health effects.
Introduction
Air pollution is one of the main environmental problems of the
European cities. In this contest, due to the lack of an air quality
network in the City of Ceuta, a number of field campaigns were
scheduled for the period 2010 to 2013, for some of main pollutants
cover by EU Directive 2008/50/EC. So, the levels of gaseous
pollutants and particle matter were quantified to know if these
concentrations will be high enough to be a risk for the exposed
population.
Figure 1 – Map of NO2 levels (4-11/07/13)
Methodology and Results
Three campaigns were performed in fall-winter (2010/2011), spring
(2012) and summer (2013). Gaseous species were sampled by radial
diffusive samplers during 7 days for NO2 and VOC and 15 days for
O3, in 55 points of a net (200 m x 200 m) which covered all Ceuta
territory. While NO2 was analyzed by espectrofotometry O3 was
measured by ion chromatography and VOC by gas chromatography
Figure 2 – Map of O3 levels (4-18/07/13)
PM10 and PM2,5 particles were sampled in a site in the middle of
the city using European reference samplers set by EN
PM10
PM2,5
12341 and EN 14907 standards. Both gas and particle
days > 50 days > 25 3
3
year
days
µg/m
days
µg/m
3
3
analysis were performed under a quality system, based on
µg/m
µg/m
31 ± 11 (max 63)
14 ± 8 (max 63)
the requirements of EN ISO/IEC 17025 standard. In fact,
2010‐11
89
3
66
6
29 ± 16 (max 76)
2012
89
7
90 13 ± 12 (max 68)
13
ACA is accredited for NO2, PM10 and PM2,5 analyses,
29 ± 7 (max 47)
17 ± 7 (max 47)
2013
65
0
69
7
using either and internal procedure or its specific EN
standard by ENAC (Spanish Accreditation Body), since
Table 1 - PM10 and PM2,5 (maximum) and days >
2000. The campaigns showed, for gaseous species, a
different pollutant behavior and higher spatial distribution.
While NO2 and O3 have presented very high levels the VOC resulted in relative low ones. As an example, daily NO2 (see
figure 1) had a mean level (50 sampling points) of (11 ± 8) µg/m3 with a maximum value of 48 µg/m3 as a 7 days mean value
in the city center. On the other hand, the ozone (see figure 2) had a mean level (50 sampling points) of (114 ± 68) µg/m3 with
a maximum valium of 549 µg/m3 as a 7 days mean value in a urban area East of the city center. This could mean the O3 alert
level of 240 µg/m3 was commonly exceeded, by larger. Finally, as expected PM10 and PM2,5 (see table 1) were strongly
dependent of Saharan episodes. PM10 and PM2,5 levels could meet in Ceuta the required EU limit value. Also, the PM10
levels exceeded the WHO guideline value of 10 µg/m3.
Conclusions
Gases species analyzed in Ceuta showed high spatial and concentration variability. Ozone is producing an important health
risk on the population of Ceuta and this fact should be extrapolated to the all nearby North African cities. NO2 and particles
show levels closed but below of the EU limit values. PM10 levels, which were higher than the WHO guideline, are mainly
due to Saharan dust intrusions. The VOC levels are lower and they are not so important. So, Ceuta Environmental Health
Authorities have decided to improve the measurements and a continuous monitoring of O3, NO2 and particles will be on
place, next year.
References
EU Directive 2008/50/EC of 21 May, on ambient air quality and cleaner air for Europe
128
CHEMICAL CHARACTERISTICS OF PM2.5 IN HAZE EPISODES IN BEIJING
R. R. Shen (1), K. Schäfer (1), P. Suppan (1), Y. S. Wang (2), J. Schnelle-Kreis (3), L. Y. Shao (4)
(1) Institute of Meteorology and Climate Research (IMK-IFU), Karlsruhe Institute of Technology (KIT), 82467, GarmischPartenkirchen, Germany; (2) Institute of Atmospheric Physics, Chinese Academy of Sciences (CAS), 100029, Beijing, P. R.
China; (3) Joint Mass Spectrometry Centre, Comprehensive Molecular Analytics, Helmholtz Zentrum München, 85764
Neuherberg, Germany; (4) Department of Resources and Earth Sciences, China University of Mining and Technology
(CUMTB), 100083 Beijing, P. R. China
Presenting author email: rongrong.shen@kit.edu
Summary
This study aims to investigate the chemical characteristics of PM2.5 during haze episodes in Beijing in 2013 spring and to find
out the differences between haze days and non-haze days as well as the possible sources of chemical compounds during haze
episodes. Analytical techniques like ICP-MS, IC and thermal/optical carbon analyzer were used to identify the inorganic
compounds, inorganic water-soluble ions, EC and OC of PM2.5, respectively. This study shows that major chemical species
of PM2.5 which affect human health are originated from anthropogenic sources.
Introduction
Haze episodes becomes much more frequent in Beijing (Wang et al., 2006) and received much more attention during the past
decade because of its influences on visibility and human health (Sun et al., 2006). Because the chemical characteristics and
sources of haze are different from the normal urban aerosols, studies of haze pollution are important for the control of air
pollution in Beijing.
1000.00
150
100.00
50
05.06.2013
29.05.2013
22.05.2013
15.05.2013
08.05.2013
01.05.2013
24.04.2013
17.04.2013
0
Non‐haze
Haze
10.00
1.00
0.10
0.01
0.00
PM2.5
TC
OC
EC
Cl‐
NO3‐
SO42‐
Na+
NH4+
K+
V
Cr
Ni
Cu
Zn
As
Cd
Sb
Ba
Pb
100
Mass concentration (µg m‐3)
200
10.04.2013
PM2.5 mass concentration (µg/m3)
Methodology and Results
Two sequential High-Volume Samplers (HVS, Digitel DHA-80, Hegnau, Switzerland) were used to collect PM2.5 samples
automatically. Three obvious accumulation processes of haze episodes were found (see Fig. 1), from 18th April to 25th April,
3rd May to 9th May, 1st June to 8th June, respectively. The average PM2.5 mass concentration during haze days was 129 µg
m-3 but during in non-haze days it was 65 µg m-3 only. An obvious increase of secondary inorganic pollutants (NO3-, SO42and NH4+) in PM2.5 was observed (see Fig. 2). NO3-, SO42- and NH4+ in the atmosphere are basically formed by a gas-toparticle process as a result of chemical reactions of precursor gases. The acidities of PM2.5 during haze days were higher than
during non-haze days. The higher concentrations of pollutants during haze episodes were mainly from anthropogenic sources.
Sampling date
Fig.1: Daily PM2.5 mass concentration.
Fig.2: Comparison between haze days and non-haze days.
Conclusions
Haze pollution is becoming a frequent phenomenon in Beijing and enhances the pollution of the urban air. Furthermore, the
main compounds of haze aerosols have several influences on human health. Therefore, there is need to do further research on
formation mechanisms and sources of haze in order to improve the urban air quality.
Acknowledgement
This work is supported by the China Scholarship Council (CSC) and the KIT Center for Climate and Environment.
References
Sun, Y. L., G. S. Zhuang, et al., 2006. Chemical characteristics of PM2.5 and PM10 in haze-fog episodes in Beijing.
Environmental Science & Technology 40 (10), 3148-3155.
Wang, Y., Zhuang, G., Sun, Y., An, Z., 2006. The variation of characteristics and formation mechanisms of aerosols in dust,
haze, and clear days in Beijing. Atmos. Environ. 40, 6579–6591.
129
SPECIAL SESSION AIR QUALITY AND
CLIMATE
METEOROLOGY
INTERACTIONS AND
FEEDBACKS
130
DOWNSCALING OF MONTHLY PM10 CONCENTRATIONS IN BAVARIA BASED ON CIRCULATION TYPE
CLASSIFICATIONS
C. Beck (1), C. Weitnauer (1) and J. Jacobeit (1)
(1) Institute of Geography (IGUA), University of Augsburg, Alter Postweg 118, 86135 Augsburg, Germany
Presenting author email: christoph.beck@geo.uni-augsburg.de
Summary
In this contribution different downscaling approaches for linking monthly indices of local PM10 concentrations to
atmospheric circulation and weather types are applied to PM10 data from different sites in Bavaria and varying circulation
type classifications. A leave one out cross validation procedure and several skill metrics are used to evaluate and compare the
skill of all downscaling approaches. Remarkable skill is generally achieved in winter and spring while model performance is
worse in summer and autumn. In most cases multiple linear regression models using occurrence frequencies of daily
circulation types as predictors outperform alternative approaches that estimate monthly PM10 by aggregating type specific
daily mean values. Comparable model skill is reached for monthly means and extremes indicators (no. of days exceeding a
certain threshold).
Introduction
Large-scale atmospheric circulation features have distinct effects on local PM10 concentrations (e.g. Buchanan et al. 2002).
E.g. via the prevention of air mass exchange during anticyclonic conditions or through the long-range transport of PM10
related to specific synoptic scale wind directions. Therefore it can be expected that frequency changes of particular
circulation types that will probably occur under possible future climate change conditions will also bring about respective
variations in PM10 concentration levels. Against this background it is intended to develop statistical downscaling approaches
for the estimation of climate change induced variations in local PM10 concentrations from corresponding changes in
frequencies of circulation types.
Methodology and Results
Varying circulation type classifications (e.g. different classification methods varying spatial and temporal domains and
atmospheric input variables) are applied to daily gridded atmospheric reanalysis data for the North Atlantic European region.
Resulting circulation types are utilised in two different approaches for the estimation of monthly PM10 data. Firstly monthly
frequencies of circulation types serve as predictors in multiple linear regression analyses for estimating monthly predictand
values (monthly PM10 indices). Secondly type specific (daily) mean values of the target variable – determined for a
calibration period – are used to estimate aggregated monthly predictand values. All variants of both modelling approaches are
tested via a leave one out cross validation procedure for the period 1980 to 2011. The skill of all models is quantified with
different skill metrics (e.g. reduction of variance, Pearson R).
Fig. 1 shows exemplary the observed and (best) modelled time series of monthly mean PM10 concentrations in winter (DJF)
at station Nürnberg/Ziegelsteinstrasse. Model skill varies between seasons (highest skill in winter and spring, distinctly lower
skill in summer and autumn), between stations and as well depending on the specific configuration of the classification and
downscaling approach. Beside the spatial
and temporal domain used for the
classification the choice of the downscaling
approach appears to have the greatest effect
on model skill. In the overwhelming number
of cases the highest model skill is achieved
with the downscaling approach based on
multiple regression using monthly type
frequencies as predictors. It is furthermore
worth mentioning that the downscaling of
indices for extreme PM10 levels (number of
days exceeding a certain threshold) reaches
Fig.1 Observed and (best) modelled time series of monthly mean PM10 for
comparable skill as the downscaling of
Nürnberg/Ziegelsteinstrasse in winter (DJF). Additionally the squared Pearson
correlation coefficient between observed and modelled series is indicated.
monthly mean values.
Conclusions
Results achieved so far in general prove the capability of classification based approaches for downscaling of local PM10
concentrations on a monthly time scale. Accordingly future research objectives will focus on the application of the here
presented approaches to varying scenarios of CMIP5 climate models for the 21st century.
Acknowledgement
The work presented here is supported by the German Science Foundation (DFG) under contract BE 2406/2-1.
References
Buchanan C.M., Beverland I.J., Heal M.R. 2002. The influence of weather-type and long-range transport on airborne particle
concentrations in Edinburgh, UK. Atmospheric Environment 36, 5343-5354.
131
CHANGES TO THE EUROPEAN PARTICLE COMPOSITION DURING THE 21ST CENTURY
C. Andersson (1), M. Engardt (1) and C. Geels (2)
(1) Swedish Meteorological and Hydrological Institute, SE-60176 Norrköping, Sweden; (2) Department of Environmental
Science, Aarhus university, Denmark
Presenting author email: camilla.andersson@smhi.se
Summary
Models have been employed to simulate future particulate matter (PM) concentration over Europe, also investigating for
sensitivity to future climate realisation and chemistry-transport models. Emission decrease over Europe causes decreased PM
concentration, whereas climate change seems to modulate the change, causing lower decrease than expected.
Introduction
Change in climate and emissions are expected to affect future concentration of particulate matter (PM2.5 and PM10 and its
chemical constituents) over Europe. Only a few studies have focused on the effect of climate and emission change on future
PM concentration over Europe. In this study we employ a regional, off-line, chemistry-transport model, MATCH, to simulate
present and future particle concentration in Europe, in a number of scenarios to assess the respective impacts of climate and
emission change. We also conducted simulations assessing for the sensitivity in future change due to different global and
regional climate models, and global, hemispheric and regional chemistry-transport models, and for different anthropogenic
emission scenarios.
Methodology
MATCH (Robertson et al., 1999) has previously
used in studies of climate change and surface
ozone and nitrogen deposition in Europe (e.g.
Langner et al., 2012). The model is driven by
meteorological data from a state-of-the-art
regional climate model in two versions, RCA3
and RCA4. The regional climate model is driven
by data from a coarser resolution global climate
models (ECHAM5, ECEARTH) on its
boundaries and increasing greenhouse gas
concentration (RCP4.5, SRES A1B). The global
climate models are also used to simulate global
(INCA) or hemispheric (DEHM; see setup in Fig
1) particle and chemical trace specie
concentrations. These are used as lateral and top
boundary concentration to MATCH.
The regional particle simulations were performed
by simulating windows in the beginning, middle
and end of 21st century.
Fig.1 Modelling set up of one set of MATCH simulations.
Results and Conclusions
Our results show decreases are expected in both
mid-century and end-of-the-century PM10
concentrations across Europe (see Fig. 2).
However, climate change will act to increase
PM10 concentrations, causing smaller decrease
than expected.
Acknowledgement
This study was supported by the Nordic Council
of Ministers (Future Nordic Air), the European
network ERA-ENVHEALTH and its partner
organizations ANSES, ADEME, BelSPO, UBA
and the Swedish EPA (ACCEPTED, agreement
no 219337), the EU (FP7 project IMPACT2C,
agreement no 282746) and the Swedish EPA
(CLEO).
Fig.2 Current (left) and change in PM10 concentration
due to climate and emission change
to mid-century (middle) and end of the century (right)
modelled with MATCH (top row) and DEHM (bottom row).
References
Langner et al., 2012. European summer surface ozone 1990-2100. Atmos. Chem. Phys. 12, 10097-10105.
Robertson, L. et al., 1999. An Eulerian limited-area atmospheric transport model. J. Appl. Meteor. 38, 190–210.
132
AIR QUALITY PROJECTIONS OVER EUROPE UNDER CLIMATE CHANGE AND EMISSION MITIGATION
SCENARIOS: HORIZONS 1971-2060
P. Navarro (1), J. P. Montávez (1) and P. Jiménez-Guerrero (1)
(1) Department of Physics, University of Murcia, Ed. CIOyN, Campus de Espinardo, Regional Campus of International
Excellence ``Campus Mare Nostrum'', University of Murcia, 30100 Murcia (Spain)
Presenting author email: pedro.jimenezguerrero@um.es
Summary
The main objective of this work is to show the situation of air quality in Europe by using air quality-climate simulations from
1971-2060. This simulation database was compared with target and limit values of the European Directive 2008/50/EC in
order to assess present and future air quality over Europe. Since climate change alone may influence air pollution levels
through changes in certain variables that govern air quality, concentrations were studied in the decades of the 2020s, 2030s,
and 2050s under the SRES A2 scenario of climate change and compared to present situation. Finally, we explore the efficacy
of implementing mitigation measures of emissions of atmospheric pollutants for the same decades as aforementioned.
Introduction
The definition of air quality management strategies based on emission abatement is one of the predominant factors for
controlling regional air pollution, which will be aggravated under climate change scenarios due to the impacts of climate
variation on the dispersion and removal of air pollutants. Climate change alone will play a part in future air quality through
modifications of gas-phase chemistry, transport, removal and natural emissions (Jacob and Winner, 2009). Considering this,
we quantified the variation of future European air quality under two scenarios: considering only the influence of climate
change (SRES A2) and this climate change scenario when emission management strategies are implemented.
Methodology and Results
The methodology includes the use of a climate version of the MM5EMEP-CHIMERE modeling system. Experiments span the periods
1971-2000, taken as a reference, and 2001-2060, as a future
enhanced greenhouse gas and aerosol scenarios (driven by SRES
A2). Present-day air qualiy climatologies have been compared to
three time slices: 2021-2030 (2020s), 2031-2040 (2030s) and 20512060 (2050s). The simulations have an horizontal resolution of 25
km. Another hypothetical scenario of emission control has been
implemented -as stated in the EC COM (2011) 102-, involving
reductions up to 80% in several pollutants. We performed a
comparison between those years and the present, to see how the
spatio-temporal patterns of air pollution vary under these future
scenarios and how the exceedances of the thresholds set in the
European Directive 2008/50/EC are modified in the future. The
results indicate a present widespread non-attainment of air quality
objetives with respect mainly PM10 and sulphur dioxide (SO2) (Fig.
1). If climate-change alone scenario is implemented, the simulations
indicate a general increase of air pollutants (especially PM10 and
PM2.5 levels) both in maximum and mean levels. These pollutants
will increase their concentrations for 2020s, 2030s and 2050s mainly
in all Europe due to the temperature increase, reduced precipitation
in more southern areas, diminished cloud cover –enhancing
secondary pollutants- and an increase in solar radiation. Not only the
levels of pollutants will increase, but also the area covered by those
zones where the limit values of the European Directive 2008/50/CE
are not met. Considering the scenario with reduction in the emission
of regulatory pollutants, a noticeable and general decrease with
respect not only to SRES A2 scenario, but also with respect to
present-day levels (1971-2000) is found, mainly for particulate matter
and sulphur dioxide (Fig. 2).
Fig.1 PM10 climatological levels (g m-3) for 1971-2000.
Fig.2 Variation of PM10 levels in 2051-2060 (2050s) with
respect to 1971-2000. Influence of climate-change alone.
Conclusions
Emission control policies of regulatory pollutants can not only overcome the increases in air pollutants caused by climate
change alone, by also may lead to concentrations lower than those simulated for the 1971-2000 period. It also reduces the
area (number of cells) with exceedances of the limit values set by Directive 2008/50/EC.
Acknowledgement
This work was funded by the Spanish Ministry of Economy and Competitiveness (project CGL2010-22158-C02-02) and the
“Fondo Europeo de Desarrollo Regional” (FEDER). Dr. Pedro Jiménez-Guerrero thanks the Ramón y Cajal programme.
References
Jacob, D.J., Winner, D.A., 2009. Effect of climate change on air quality. Atmos. Environ. 43, 51-63.
133
INVESTIGATING AEROSOL OPTICAL PROPERTIES USING WRF/CHEM
A. Balzarini (1), G. Pirovano (1), G. M. Riva (1)
(1) Research on Energy System (RSE S.p.A.), via Rubattino 54, 20134, Milano Italy.
Presenting author email: alessandra.balzarini@rse-web.it
Summary
This study aims to investigate the relationship between the outcome of the traditional model performance evaluation and the
reconstruction of the aerosol optical properties. The analysis has been performed through the application of the WRF/Chem
model in the framework of the AQMEII modeling initiative. Results show that PM10 and PM2.5 general pattern is well
reproduced by the model, but it underestimates the maxima daily episodes during winter months. AOD analysis indicates a
significant model difficulty in reconstructing optical properties.
Introduction
Online-coupled meteorology and chemistry models are becoming more and more popular in air quality modeling applications
as they allow achieving a significant reduction of inconsistency in the interaction between meteorological and chemical
processes. However, even recent air quality modeling studies highlight significant difficulties in correctly reproducing such
interactions, e.g. the effects of particulate matter on radiation budget, whose estimation relies on the correct reconstruction of
the optical aerosol properties. Till recent times, model performance evaluation (MPE) has been widely based on the
comparison of modeled concentration of the aerosol bulk mass and main chemical compound against observed data.
Differently, less consideration has been devoted the evaluation of model performance in reproducing aerosol optical
properties, mainly due to reduced availability of experimental data.
This study aims to investigate the relationship between the outcome of the traditional MPE and the reconstruction of the
aerosol optical properties. The analysis has been performed through the application of the WRF-Chem model in the
framework of the AQMEII modeling initiative.
Methodology and Results
WRF/Chem model has been applied over Europe for the calendar year 2010, adopting a horizontal resolution of 23 km. The
model has been driven by the input data set provided in the framework of the exercise, including the TNO-MACC
anthropogenic and FMI biomass burning emission inventory, and by archiving ECMWF meteorological fields.
Model configuration adopted the following physical parameterization: YSU PBL scheme, Noah LSM, Morrison
microphysics, RRTMG radiation schemes, and G3 cumulus scheme. As for chemistry, the model implemented CBM-Z gas
phase mechanism and MOSAIC aerosol module. Traditional MPE have been performed against ground level observed at
around 500 Airbase sites as well as PM composition data provided by EMEP network. Differently, model ability in
reproducing aerosol optical properties has been investigated against AERONET network observed data.
As an example, Fig.1 shows PM10 and PM2.5 daily time series at Avignon Airbase site. Mean modeled concentrations of
PM10 stay around 15.2 μg/m3, while observed data reach up to 25.1 μg/m3. As far as PM2.5 is concerned, average modeled
and observed concentrations are 11.9 μg/m3 and 18 μg/m3, respectively. The overall pattern is well reproduced by the model,
but it underestimates the maxima daily episodes during winter months. The current study has also focused on aerosol optical
properties, namely the aerosol optical depth (AOD). Simulated and observed AOD values varied between 0.004-1.518 and
0.021- 0.475 respectively, indicating model difficulties in reconstructing optical parameters. In the study, the causes of model
biases are investigated as well as the different impact of anthropogenic and natural aerosol loads is discussed.
Fig.1 Time series of modelled (red) and observed (back) data of PM10 (left) and PM2.5 (right) at Avignon Airbase station.
Conclusions
This study aims to investigate the relationship between the outcome of the traditional model performance evaluation and the
reconstruction of the aerosol optical properties. The analysis has been performed through the application of the WRF/Chem
model in the framework of the AQMEII modeling initiative. The PM10 and PM2.5 general pattern is well reproduced by the
model, but it underestimates the maxima daily episodes during winter months. AOD analysis indicates a significant model
difficulty in reconstructing optical properties.
Acknowledgement
This work has been financed by the Research Fund for the Italian Electrical System under the Contract Agreement between
RSE S.p.A. and the Ministry of Economic Development - General Directorate for Nuclear Energy, Renewable Energy and
Energy Efficiency in compliance with the Decree of March 8, 2006. We also gratefully acknowledge the contribution of
various groups to the second air Quality Model Evaluation international Initiative (AQMEII) activity.
134
AIRBORNE SOURCE APPORTIONMENT FOR ULTRAFINE ATMOSPHERIC PARTICLES AND THE
DEPENDENCE OF LOCAL SURFACE CONCENTRATIONS ON REGIONAL SCALE METEOROLOGY
W. Junkermann
Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Garmisch-Partenkirchen, Germany
Presenting author email: Wolfgang.Junkermann@kit.edu
Summary
This study uses airborne investigations of ultrafine and fine particles for source apportionment of climate and health relevant
particulate matter. A strong dependence of the distribution of local emissions on transport and advection as well as on the
diurnal variability of the planetary boundary layer can be documented which is controlling the levels of particulate matter of
all size fractions both on the ground (for health impact) and below cloud base (for climate impact).
Introduction
Atmospheric pollution is significantly controlled and affected by transport and convection processes. That way urban
pollution is exported into remote rural areas or strong sources of extraurban pollution can contribute to urban pollution levels.
An example is particulate mass, PM2.5/PM10. PM exceedance is often related to long range transport from Saharan dust.
Similar to the fine particulate mass ultrafine particles can be transported even more efficiently as dry deposition in the main
transport layers aloft for the smaller particles is probably less significant. Thus in case, large sources of ultrafine particles are
located upwind of urban agglomerations, innerurban the number concentrations of health relevant ultrafine particulate matter
might be affected and even dominated by regional scale transport processes.
Methodology and Results
Airborne measurements of ultrafine and fine particle size distributions and concurrent in situ wind and turbulence
measurements were used to characterize major single sources and source regions for ultrafine particles. Source apportionment
of ultrafine particles is based on particle size distributions and in-situ wind data. Transport, turbulence, convection and
vertical mixing intensity can be derived from the in situ turbulence measurement. Combined with HYSPLIT backtrajectories
these measurements allow a detailed 3-dimensional analysis of regional scale transport and vertical pollution distribution.
We investigated both, rural nucleation events affected by extraurban
nanometer size particle emissions that we were able to follow over more
than 1000 km and the effect of extraurban sources on urban nucleation
mode particle size distributions and their temporal behaviour. Particle
number concentrations and their physico-chemical properties in these
studies were well in ranges considered to be either climate or health
relevant.
Conclusions
Climate and health relevant ultrafine particle concentrations on ground
based stations are dependent on long range transport and vertical mixing of
the planetary boundary layer. Local or regional scale nucleation events
Fig. 1:Development of particle size
can be traced back to upwind strong single particle sources in distances of
distributions
within a power plant plume
up to several hundred km. Plumes of ultrafine particles were detected
within the first 2 hours or ~ 40 km of
even 1500 km downwind of single sources. Also these plumes travelling
transport (Junkermann et al, 2011).
in the upper layers of the PBL affect the surface concentrations after
vertical mixing. Thus interpretation of local diurnal variability of UFparticle concentrations and their temporal development cannot be simply
derived from a local box model but have to take into account at least regional, possibly even larger scale three dimensional
meteorology.
References
Junkermann, W., Hagemann, R., and Vogel, B., Nucleation in the Karlsruhe plume during the COPS / TRACKS - Lagrange
experiment, QJRMS, 137, 267-274, 2011
135
WRF-CHEM SIMULATIONS ON THE EFFECT OF AEROSOL-METEOROLOGY FEEDBACK
ON REGIONAL POLLUTANT DISTRIBUTIONS OVER EUROPE
R. Forkel (1), A. Balzarini (2), R. Baró (3), G. Curci (4), P. Jiménez-Guerrero (3), M. Hirtl (5), L. Honzak (6), J. L. Pérez
(7); G. Pirovano (2), R. San José (7); P. Tuccella (4), J. Werhahn (1), R Žabkar (6)
(1) Karlsruhe Inst. of Technology, IMK-IFU, Garmisch-Partenkirchen; (2) RSE, Milano; (3) University Murcia, MAR-UMU;
(4) University L’Aquila, CETEMPS; (5) ZAMG, Vienna; (6) University Ljubljana, SPACE-SI;
(7) Technical Univ. of Madrid, ESMG
Presenting author email: renate.forkel@kit.edu
Summary
Results of one-year simulations with different configurations of WRF-Chem are analyzed with respect to the effect of the
aerosol radiative impact on meteorological fields and pollutant concentrations.
Introduction
Simulated feedback effects between aerosol concentrations and meteorological variables and on pollutant distributions are
expected to depend on model configuration and the meteorological situation. In order to quantity these effects the second
phase of the AQMEII (Air Quality Model Evaluation International Initiative; http://aqmeii.jrc.ec.europa.eu/) model intercomparison exercise focused on online coupled meteorology-chemistry models. Among others, several of the participating
groups contributed simulations with WRF-Chem (Grell et al., 2005) for Europe, which differ by the chosen chemistry or
boundary layer options, and by the degree of aerosol feedback that was considered. The results of this small ensemble are
analyzed with respect to the effect of gas phase chemistry, aerosol module, and liquid phase reactions.
Methodology and Results
Simulations with WRF-Chem were performed for Europe for the entire year 2010 within AQMEII by seven groups.
According to the common simulation strategy for AQMEII phase 2, the year was simulated as a sequence of 2-day time
slices. For better comparability, the seven groups applied the same grid spacing of 23 km and shared common processing of
initial and boundary conditions as well as anthropogenic and fire emissions. With exception of a simulation with different
cloud microphysics, identical physics options were chosen while the chemistry options were varied (Table 1).
2
3
4
5
6
7
Case
1a,b
Microphysics
Morrisona
Morrison
Morrison
Morrison
Linb
Morrison
Morrison
Gas phase chem..
RADM2 c
RADM2mod RADM2
RACMd
RADM2
CBMZe
CBMZ
Inorg. aerosol
MADEf
MADE
MADE
MADE
MADE
MOSAICg
MOSAIC
Org. aerosol
SORGAMh SORGAM
SORGAM
VBSi
SORGAM
Aq. chem., grid scale WTk
FPl
WT
FP
FP
Aerosol direct effect
a: no, b: yes yes
yes
yes
yes
no
yes
Aerosol indir. effect
no
yes
yes
yes
yes
no
yes
Table 1: Configuration of the different WRF-Chem simulations ( aLin et al 1983, bMorrison et al.2008, cStockwell et al.,
1990, dStockwell et al.1997, eZaveri & Peters 1999, fAckermann et al. 1998, gZaveri et al.2008, hSchell et al., 2001;
iAhmadov et al, 2012, kWalcek & Taylor 1986, lFahey & Pandis 2001, for complete references
please see
http://ruc.noaa.gov/wrf/WG11/Users_guide.pdf )
A first analysis for July 2010 indicated only a small impact of the direct aerosol radiative effect on monthly mean
temperature and ozone concentrations (ca. 1 ppb). Mean differences between simulated aerosol concentrations for cases 1a
and 1b were below 1 g m-3 except for North Africa and North of Moscow (–4 g m-3). The additional inclusion of the
aerosol indirect effect (cases 2-5, and 7) resulted for areas with low aerosol concentrations in a more than 50 W m-2 higher
global radiation for cloudy conditions than in the cases 1 and 6. The choice of the chemical mechanism and aerosol module
on simulated pollutant concentrations obscures sometimes the effect of the aerosol feedbacks on pollutant concentrations.
Mean ozone for cases 2, 4, and 6 (different mechanisms) differed from case 1 by ±10 ppb over large areas, while the
difference between cases 3 and 1a was below 2 ppb. The differences of the mean PM2.5 concentrations over Central Europe
between cases 3 and 1a (same aerosol module) were -6 to 0 g m-3, and -6 to 4 g m-3 between case 6 and case 1a.
Conclusions and Outlook
For the applied horizontal resolution, the impact of aerosol feedbacks on pollutant distributions was frequently smaller than
the effect of the choice of the chemistry mechanism and aerosol module. As a next step, a more systematic analysis, also for
other seasons, is necessary in order to identify the episodes and regions with more pronounced feedback effects.
Acknowledgement
We gratefully acknowledge the contribution of various groups to the second air Quality Model Evaluation international
Initiative (AQMEII) activity: TNO (anthropogenic emissions database); ECMWF/MACC project & Météo-France/CNRMGAME (chemical boundary conditions), FMI (fire emissions). Joint Research Center Ispra/Institute for Environment and
Sustainability provided its ENSEMBLE system for model output harmonization and analyses, and evaluation.
References
Grell, G.A., Peckham, S.E., Schmitz, R., McKeen, S.A., Frost, G., Skamarock, W.C., Eder, B., 2005. Fully coupled online
chemistry within the WRF model. Atmos. Environ. 39, 6957-6975.
136
REPRESENTATION OF COUPLING PROCESSES IN ONLINE COUPLED METEOROLOGY AND
CHEMISTRY MODELS – AN EXPERT POLL SURVEY RESULTS
X. Kong (1), M. Gauss (2), G. Tsegas (3), A. Baklanov (4), R. Forkel (5), P. Suppan (5), D. Brunner (6), R. S. Sokhi (1), K. H.
Schlünzen (7) and the COST ES1004 EuMetChem team
(1) University of Hertfordshire, Hatfield, UK; (2) Norwegian Meteorological Institute, Norway; (3) Aristotle University of
Thessaloniki, Greece; (4) Danish Meteorological Institute, Denmark; (5) Karlsruhe Institute of Technology (KIT), Germany;
(6) EMPA, Switzerland; (7) Meteorological Institute, University Hamburg, Germany
Presenting author email: x.kong@herts.ac.uk
Summary
An expert survey has been conducted in COST Action ES1004 to get an expert judgement on which meteorology and
chemistry coupling processes might be most relevant and how well they are represented in the current online coupled models.
The survey results are presented together with some supported case studies and provided guidance on how to improve the
representation of meteorology and chemistry coupling processes in numerical models.
Introduction
The COST Action ES1004 - European framework for online integrated
air
quality
and
meteorology
modelling
(EuMetChem;
http://eumetchem.info/) - is focusing on a new generation of online
integrated Atmospheric Chemical Transport and Meteorology
modelling with two-way interactions between different atmospheric
processes including chemistry, clouds, radiation, boundary layer,
emissions, meteorology and climate (Baklanov et al., 2013). Co
mpared with traditional offline models, online coupled meteorology and
chemistry modelling system is a new and emerging area. Which
meteorology and chemistry interactions are the most important and how
well they are implemented in the current model system are not well
documented in the literature. Therefore, an expert survey has been
conducted in COST Action ES1004 to get an expert judgement on
which coupling processes might be most relevant.
Methodology and Results
The survey questionnaire includes 24 meteorology-chemistry
interactions for three different modelling communities: numerical
weather prediction (NWP), chemical weather forecasting (CWF) and
climate models (listed in Table1). The survey was sent to different
experts in these communities in Europe and beyond, and the results of
its analysis (based on 30 responses) are shown in Figure 1. The original
data collected from survey are including a) rates the importance of the
interactions and b) rates how well they are represented in current online
models. Two indicators are derived from the weighted mean of original
data: ‘score1’ – importance of the interaction for models and ‘score2’ adequacy of the representation of the interaction in models. The results
show that the perceived most important interactions differ from one
model category to another. In general, most of the meteorology and
chemistry interactions are more important for CWF models than NWP
and climate models, and those interactions are represented better in
CWF models than in NWP and climate models (see figure 1).
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Table 1 List of meteorology-chemistry interactions
Temperature  reaction rates
Radiation  reaction rates
Temperature  biogenic emissions
Radiation  photosynthesis  biogenic emissions
Temperature  volatility of species
Temperature  aerosol dynamics
Liquid water  wet scavenging, concentrations
Temperature & humidity  gas/particle partitioning
Precipitation (frequency/intensity)  concentrations
Soil moisture  dust emissions
Soil moisture  dry deposition (biosphere and soil)
Wind speed  dust & sea salt emissions
Temperature vertical gradients  vertical diffusion
Lighting  NOx emissions
Water vapour  OH radicals  ozone
AerosolsSW scattering/absorption, LW absorption
Radiatively active gases  radiation
Aerosol  haze
Soot deposition  ice albedo
Aerosol  cloud droplet/crystals  cloud O.D.
Aerosol  cloud morphology (e.g., reflectance)
Aerosol  precipitation (initiation, intensity)
Climate change  forest fire emissions
Changes in land surface  BVOC emissions
Future Research and Recommendations
Based on survey results, we have made some recommendations for the
science community and model developers. Primary attention needs to be
given to the interactions with high rank of importance (score1) together
with low score in the model representation (score2), such as
Figure 3 COST ES1004 expert survey results
“improvement of aerosol indirect effects” for both NWP and climate
models, “liquid water  wet scavenging and atmospheric composition”
and “improvement of wind speed  dust/sea-salt interactions” for CWF models. As the survey itself is somewhat subjective
due to different individual opinions, a few supported case studies on evaluation of coupled processes have been included to
assess the survey results.
Acknowledgement
This work was realized within and supported by the COST Action ES1004 EuMetChem.
References
Baklanov et al., 2013. Online coupled regional meteorology-chemistry models in Europe: current status and prospects.
Atmospheric Chemistry and Physics. 184 p (in discussion in ACPD, doi:10.5194/acpd-13-1-2013).
137
QUANTIFYING THE RESPONSES OF FUTURE AIR QUALITY OF EUROPE TO CHANGES IN CLIMATE
AND EMISSIONS WITH WRF-CMAQ AND HADGEM
X. Kong (1), R. S. Sokhi (1), X. Francis (1), C. Chemel (1), G. Folberth (2) and B. Collins (3)
(1) University of Hertfordshire, Hatfield, UK; (2) Met Office Hadley Centre, Exeter, UK; (3) University of Reading, UK.
Presenting author email: x.kong@herts.ac.uk
Summary
In this study, the regional WRF-CMAQ modelling system, driven by the global climate model HadGEM2-ES (RCP 8.5
scenario), has been applied for base year 2000s and future year 2030s over Europe at 54km horizontal resolution. The climate
and emission change effects on particulate matter (PM) and ozone have been examined respectively over the European
domain. The sensitivity of the simulated surface PM to changes in climate between 2000s and 2030s are relatively small
compared with the changes due to emission reductions, but with substantial spatial heterogeneity. Climate change effects on
ozone are stronger, with annual mean increasing exceed 1 ppbv in 2030s in most area over Europe.
Introduction
The importance of interactions between climate change (CC) and air quality (AQ) has been widely recognised (e.g. IPCC
2007). As a result of these interactions, changes in climate could potentially also affect air quality which has implications for
associated health effects. This study demonstrates the use of WRF-CMAQ interfaced to HadGEM global scale model to
quantify the influence of climate change on future concentrations of PM and ozone.
Methodology and Results
The global climate data HadGEM2-ES (Collins et al., 2011) provided by the UK Met Office are representing the decade
mean of 2000s and 2030s under the RCP8.5 scenario (driven by decadal means of sea surface temperature, sea ice
concentration and emissions). These data have been interfaced into the regional WRF-CMAQ modelling system and applied
for base year 2000s and future year 2030s over Europe at 54km horizontal resolution. In order to reduce the effects from
inter-annual variability, the regional model was run in ten ensembles to represent the decadal mean of 2000s and 2030s. Four
model experiments have been carried out for base year and future year with and without climate/emission changes. The
effects of climate change (delta_C) and emission change (delta_E) on PM and ozone have been calculated respectively:
delta_C = 2030Met_2000Emiss – 2000Met_2000Emiss; and delta_E = 2000Met_2030Emiss - 2000Met_2000Emiss.
The results (see Figure 1) from this study
indicate that climate effects generally reduce the
surface PM concentration in 2030s by 0.1μg/m3
on domain average. However, they exhibit
substantial spatial heterogeneity with some
locations could either increase or reduce up to 5
μg/m3. The climate change effects on PM
reduction are between 5 to 10 times smaller than
the reduction brought about by emission changes
between 2000s and 2030s. Climate change
effects on ozone are much stronger due to effects
of
increased
temperature
on
ozone
photochemistry, with annual mean increasing
exceed 1 ppbv in 2030s in most area over
Europe.
Conclusions and Future work
The results from this study indicate that climate
effects generally lead to an increase in ozone
concentrations. While the effects on PM2.5 and
PM10 are weaker, they exhibit substantial
Figure 4 change in mean surface PM10 and Ozone concentration 2030spatial heterogeneity. A long-term modelling
2000
simulation study is needed in order to be able to
extract robust signals of climate change impacts. The ongoing work is to look at the climate change effects on each PM
species (such as sulphate, nitrate, ammonia and black carbon components) and examine which species are most sensitive to
climate change. On a time scale beyond the implementation of expected emission reduction strategies, it is possible that
climate change effects on air quality will become relatively more significant. This is an off-line modelling study and there
may be effects of online coupled feedbacks that have not been taken into account.
Acknowledgement
The research leading to these results has received funding from the EU FP 7 MEGAPOLI and TRANSPHORM.
References
Collins, W.J. et al., 2008. Evaluation of the HadGEM2 model, Hadley Centre technical note 74, the UK Met Office.
IPCC 2007. Forster, P. M., et al., Changes in atmospheric constituents and in radiative forcing, in Climate Change 2007.
138
AIR QUALITY AND CLIMATE CHANGE IMPACT ON URBAN HEAT ISLAND IN CENTRAL EUROPE
T. Halenka (1), P. Huszar (1), M. Belda (1), K. Zemankova (2)
(1) Department of meteorology and environmental protection, Faculty of Mathematics and Physics, Charles University in
Prague, 18000 Prague 8, Czech Republic, (2) LATMOS, IPSL, Paris, France
Presenting author email: tomas.halenka@mff.cuni.cz
Summary
To include the effect of urbanized areas into regional climate model RegCM, the surface parameterization based on Single
Layer Urban Canopy Model (SLUCM) has been adopted. Preliminary tests of the urban parameterization have been
performed on Central Europe region in 10 km resolution with 1 km resolution of SUBBATS scheme in 10-years simulation.
Results clearly show urban heat island (UHI) patterns for most the big cities or urbanized areas in the region. The effect of air
quality and climate change on the intensity of urban heat island is studied in the similar simulations under different
conditions.
Introduction
The primary reason for temperature increase and other changes within the cities, is the effect of urban heat island (UHI, Oke,
1973). The surface of urban elements clearly differs from natural surfaces which affects the properties of the atmosphere,
especially in canopy layer. Moreover, the cities with their emissions of pollutants are major source for adverse conditions of
air quality. Thus, the effect of air quality on UHI and the interaction with UHI are of interest in this study, as well as the
climate change, which is bringing the temperature and other changes with potential to contribute to UHI.
Methodology and Results
We are using the model RegCM4.3 (ICTP) by Giorgi et al. (2012). The SLUCM
model by Chen et al. (2010) has been implemented into RegCM4.3 with 10 km
resolution for Central Europe by linking it to the BATS surface scheme, applying
SUBBATS at 1 km sub-grid resolution (Pal et al., 2007), where SLUCM is called
whenever urban or sub-urban land-use categories are recognized.
We have performed the experiments with the RegCM4.3 both with SLUCM switched
on and off in period of 2005-2009 driven by boundary conditions from ERA-Interim
reanalysis (Simmons et al. 2007). Fig. 1 presents the UHI for Vienna and Prague
where the effect of SLUCM parameterization can be seen. We have analized the
changes of selected meteorological parameters between experiments SLUCM (the
urban canopy model turned on) and NOURBAN (urban canopy not considered). The
effects are the strongest in summer, for temperature, there is an evident increase with
urban canopy introduced of 1K over urbanized areas (effect of cities like Budapest,
Vienna, Prague, Berlin is well seen), but it is statistically significant elsewhere with
up to 0.4K increase even over non-urban areas. The simulations of the couple of
RegCM and CAMx (Huszar et al., 2011) are used to assess the effect of air quality
changes on the UHI effect. For climate change experiment, boundary conditions from
the simulation of CNRM model for CMIP5 are used for near future. The changes
with respect to the control period 2005-2009 are studied.
Fig.1Urban heat island (temperature)
of Vienna (above) and Prague (below)
Conclusions
The effect of air quality can be splitted to the gaseous pollutants which can contribute to the UHI, especially the short lived
species, while aerosols effect is less clear due to the less uncertainty of the aerosol impact processes parameterization.
Climate change conditions, at least for the near future, contribute slightly moving the UHI on the temperature scale, but the
changes in intensity of UHI are not so clear.
Acknowledgement
The presented work was funded by the project of Czech Grant Agency No. 13-19733P, as well as by the project UHI founded
in the framework of EC OP NN (No. 3CE292P3).
References
Giorgi, F., E. Coppola, F. Solmon, F., L. Mariotti, M. Sylla, X. Bi, N. Elguindi, G. T. Diro, V. Nair, G. Giuliani, S. Cozzini,
I. Guettler, T. A. O’Brien, A. Tawfik, A. Shalaby, A. Zakey, A. Steiner, F. Stordal, L. Sloan and C. Brankovic, 2012:
RegCM4: Model description and preliminary tests over multiple CORDEX domains, Clim. Rev., 52, 7–29.
Huszar, P., K. Juda-Rezler, T. Halenka, H. Chervenkov and others, 2011: Effects of climate change on ozone and particulate
matter over Central and Eastern Europe, Clim. Res., 50,51–68.
Oke, T.R., 1973: City size and the urban heat island. Atmos. Environment (1967) 7(8):769–779.
Pal, J. S., F. Giorgi, X. Bi, N. Elguindi, F. Solomon, X. Gao, R. Francisco, A. Zakey, J. Winter, M. Ashfaq, F. Syed, J. L.
Bell, N. S. Diffenbaugh, J. Karmacharya, A. Konare, D. Martinez, R. P. da Rocha, L. C. Sloan and A. Steiner, 2007: The
ICTP RegCM3 and RegCNET: Regional Climate Modeling for the Developing World, B. Am. Meterol. Soc., 88, 1395–1409.
Simmons, A., S. Uppala, D. Dee and S. Kobayashi, 2007: ERA - Interim: new ECMWF reanalysis products from 1989
onwards. Newsletter 110, Winter 2006/07, ECMWF, Reading.
139
INFLUENCES OF METEOROLOGICAL PARAMETERS AND MIXING LAYER HEIGHT UPON AIR
POLLUTANT CONCENTRATIONS IN URBAN AREA
K. Schäfer (1), P. Wagner (2), H. Ling (1, 3), C. Münkel (4), S. Emeis (1), P. Suppan (1)
(1) Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research, Department of Atmospheric
Environmental Research (IMK-IFU), 82467 Garmisch-Partenkirchen, Germany
(2) University of Duisburg-Essen (UDE), Faculty of Biology, Applied Climatology and Landscape Ecology, 45127 Essen,
Germany
(3) State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of
Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), 100029, Beijing, P. R. China
(4) Vaisala GmbH, 22607 Hamburg, Germany
Presenting author email: klaus.schaefer@kit.edu
Summary
Ceilometers are applied by KIT/IMK-IFU to detect layering of the lower atmosphere continuously. This is necessary because
not only wind speeds and directions but also atmospheric layering and especially the mixing layer height (MLH) influence
exchange processes of ground level emissions. It will be discussed how the ceilometer monitoring information can be used to
interpret the traffic-related air pollution near the ground.
The information about atmospheric layering is continuously monitored by uninterrupted remote sensing measurements with
the ceilometers which are eye-safe commercial mini-lidar systems. Air pollutant concentrations are measured as pathaveraged concentrations (NO, NO2 and HCHO) with a DOAS (Differential Optical Absorption Spectroscopy) as well as by in
situ methods (NO, NO2, CO and PM10). Benzene, Toluene and Isoprene concentrations are measured by an on-line gaschromatograph. Meteorological data from ground-based station and radiosonde measured by German National
Meteorological Service (DWD) are taken.
It is found that MLH determines not only urban background but also traffic-related air pollutant concentrations.
Introduction
Wind speed and direction and MLH are important factors which influence exchange processes of ground-level emissions and
thus high air pollutant concentrations. This is generally known (Schäfer et al., 2006) but the detailed understanding of
processes directing certain air pollutant concentrations like PM10, gases and VOC is not complete. To study these processes
campaigns in Augsburg and Essen, Germany, were performed in 2012.
Methodology and Results
Ceilometers LD40, CL31 and CL51 from Vaisala which are eye-safe commercial mini-lidar systems are applied by
KIT/IMK-IFU to detect layering of the lower atmosphere continuously. Special software for these ceilometers with
MATLAB provides routine retrievals of lower atmosphere layering from vertical profiles of laser backscatter data (Emeis et
al., 2006). In the absence of low stratus clouds and precipitation ceilometers can estimate the MLH fairly well. The
concentrations of NO, NO2 and HCHO are measured with a DOAS from OPSIS in Augsburg across main traffic roads by
KIT/IMK-IFU. NO, NO2, CO and PM10 concentrations in Essen and Augsburg are measured by state environmental agencies
of North Rhine Westphalia (LANUF) and Bavaria (LfU) as well as KIT/IMK-IFU (Schäfer et al., 2011). Benzene, Toluene
and Isoprene concentrations are measured by an on-line gas-chromatograph GC 955 of Synspec b.v. by UDE (Wagner,
2013). Meteorological data from ground-based station (Airport Augsburg, Essen) and radiosonde (Oberschleißheim, Essen)
measured by German National Meteorological Service (DWD) are taken.
Correlation analyses are applied to show that the daily variations of NO, NO2, PM10, HCHO, Benzene, Toluene and Isoprene
concentrations are coupled with MLH and wind speed.
Conclusions
Mainly the maximum concentration of air pollutants is affected by MLH. A significant part of the variance of the observed
NO, NO2, CO, PM10, HCHO, Benzene, Toluene and Isoprene concentrations is caused by MLH. Isoprene which is emitted
from both anthropogenic and biogenic (during summer time, not shown here) sources shows a significant correlation for
maximum concentration with MLH.
References
Emeis, S., Schäfer, K.: Remote sensing method to investigate boundary-layer structures relevant to air pollution. Boundary
Layer Meteorology 121 (2006), 377-385.
Schäfer, K., Emeis, S., Hoffmann, H., Jahn, C.: Influence of mixing layer height upon air pollution in urban and sub-urban
area. Meteorol. Z. 15 (2006), 647-658.
Schäfer, K.; Emeis, S.; Schrader, S.; Török, S.; Alföldy, B.; Osan, J.; Pitz, M.; Münkel, C.; Cyrys, J.; Peters, A.; Saragiannis,
D.; Suppan, P.: A measurement based analysis of the spatial distribution, temporal variation and chemical composition of
particulate matter in Munich and Augsburg. Meteorol. Z. 21 (2011), 47-57.
Wagner, P.: Influence of isoprene on ozone formation in an urban environment. IAUC Newsletter 47 (2013), 33-37.
140
DEVELOPING A NEW DATABASE FOR SOURCE FINGERPRINTS IN THE ASIAN REGION – AN OVERVIEW
OF THE IAEA/RCA PROGRAMME ON AIR PARTICULKATE MATTER POLLUTION RAS0723
A. Markwitz (1), D. D. Cohen (2), B. A. Begum (3), B. F. Ni (4), G. G. Pandit (5), M. Santoso (6) , Y. S. Chung (7), S. Abd
Rahman (8), D. Shagjjamba (9), S. Waheed (10), P. C. B. Pabroa (11), M. C. S. Seneviratne (12), T. B. Vuong (13)
(1) Department of Ion Beam Technologies, GNS Science, Lower Hutt 5010, New Zealand; (2) Australian Nucl Sci and
Technology Organisation, Div Phys, Menai, NSW 2234, Australia; (3) Dhaka AECD, Atom Energy Ctr, BAEC, Dhaka,
Bangladesh; (4) China Natl Nucl Corp, CIAE, Beijing 102413, Peoples R China; (5) Bhabha Atom Res Ctr, Bombay
400085, Maharashtra, India; (6) Natl Nucl Energy Agcy BATAN, Ctr Nucl Technol Mat & Radiometry, Bandung
40132, Indonesia; (7) KAERI, Hanaro Ctr, Taejon 305600, South Korea; (8) Malaysian Nucl Agcy, Waste and
Environm Technol Div, Kajang 43000, Selangor, Malaysia; (9) National University of Mongolia, Ulaanbaatar
Mongolia; (10) PAEC, Div Nucl Chem, PINSTECH, Islamabad, Pakistan; (11) PNRI, Quezon City 1101, Philippines;
(12) Atom Energy Author, Orugodawatta, Wellampitiya, Sri Lanka; (13) Inst Nucl Sci and Technol, Ctr Radiat Protect,
Hanoi, Cau Giay, Vietnam
Presenting author email: a.markwitz@gns.cri.nz
Summary
In 2012, a new programme was started at the International Atomic Energy Agency (IAEA), Vienna, Austria to bring together
scientists from 15 countries in Australasia to develop a new database for fingerprints from local, regional and transboundary
sources of natural and anthropogenic sources.
Participants in the programme use nuclear based techniques to obtain elemental information for fine and coarse particulate
matter by using GENT samplers and twice weekly filter changing regimes (e.g. Santoso, 2013; Ancelet, 2013: Begum, 2013;
Waheed, 2012; Hopke, 2011).
In the regional cooperative agreement in Australasia (RCA), a large number of organizations operate in the environment and
health sectors benefit from this project. For the first time ever, a regional source receptor inventory database based on fine
and coarse particles is under development and will be made publicly available by the end of the programme. This data is of
significant importance for local, national, regional and world-wide operating end-users complementing the first ever database
of fine and coarse particle concentration in Asia provided by RAS/07/15. End-users from environmental protection agencies
are directly involved in this project.
Outcome of the programme is “Enhanced recognition of applicability and end-user use of nuclear analytical methods for air
particulate matter monitoring using source apportionment and fingerprinting techniques in urban areas.”
Four outputs have been identified:
(1) Effective project management and coordination at both a regional and national level;
(2) Regional air pollution database of source fingerprints and source contributions with time series spanning 2012-2015
inclusive established;
(3) Identification of long range transport of air pollution preliminarily associated with: power generation, windblown soil,
biomass burning, sea salt and volcanic emission and
(4) A preliminary assessment of impact of APM on cultural heritage objects in the region.
This presentation provides an overview of the programme and progress to date.
Acknowledgement
This work is supported by the International Atomic Energy Agency, Vienna, Austria (RAS0723) and by internal funding
from all associated government organisations and institutes across the Asia Pacific Region.
References
Santoso M, Lestiani D.D., Markwitz A., 2013. Characterization of airborne particulate matter collected at Jakarta roadside of
an arterial road. J. of Radioanalytical and Nucl. Chem. 297, 165-169.
Ancelet T., Davy P.K., Trompetter W.J., Markwitz A., Weatherburn, D.C., 2013. Carbonaceous aerosols in a wood burning
community in rural New Zealand. Atmospheric Pollution Res. 4, 245-249.
Begum B.A., Hopke, P.K., Markwitz, A., 2013. Air pollution by fine particulate matter in Bangladesh. Atmospheric Pollution
Res. 4, 75-86.
Waheed S., Siddique S.N., Arif M., Daud M., Markwitz A., 2012. Size-fractionated airborne particulate matter
characterization of a residential area near Islamabad airport by IBA methods. J. of Radioanalytical and Nucl. Chem. 293,
279-287.
Hopke P.K. et al, 2011. Urban air quality in the Asian region. Science of the Total Env. 409, 4140-4140.
141
SPECIAL SESSION AIR QUALITY
FORECASTING AND
EARLY WARNING
SYSTEMS
142
DO AIR QUALITY INFORMATION, FORECASTING AND EARLY WARNING SYSTEMS REACH
VULNERABLE TARGET GROUPS?
M. Capellaro (1), D. Sturm (2), U. Reis (3) and H.-G. Mücke (4)
(1) Marcus Capellaro - Konzeption & Evaluation kommunikativer Maßnahmen, Steilshooper Str. 211, 22307 Hamburg,
Germany; (2) HBF – Unabhängiges Institut für hausärztliche Bildung und Forschung Dr. Sturm GmbH, Richterweg 29b,
09125 Chemnitz, Germany; (3) Kantar Health GmbH, Landsbergerstr. 284, 80687 München, Germany;
(4) Umweltbundesamt/UBA, Dept. of Environmental Hygiene, Corrensplatz 1, 14195 Berlin, Germany
Presenting author email: hans-guido.muecke@uba.de
Summary
How do we approach vulnerable population groups, which suffer from environmental burden, for example extreme air
pollution events, and how can we improve their individual resilience as well as their adaptation capacity? Do we reach these
groups of people at all? To answer these questions, we recently started a two years research investigation (2012-2014) to
evaluate existing air quality and climate change associated information systems (for tropospheric ozone, solar UV radiation,
pollen and heat) in Germany. Hence, a first German-wide representative telephone survey among 4,000 residents has been
carried out during late summer 2013 in cooperation with local physicians. The project results should give guidance to
improve the public’s understanding of published information and to modify current communication ways and concepts.
Background
For more than a decade air quality forecasting and early warning systems have been established in Germany. Their aim is to
inform the general population and vulnerable groups (e.g. elderly, one-person household) on the current and predicted
situation to prevent health damages by better individual adaptation. Recently these systems were expanded by the heat health
warning system. From environmental health viewpoint it is of utmost interest to know if, when and how the information
reaches the people. Important is also, whether the information is sufficient and understandable. For effective adaptation
people need adequate information. Due to the fact that information about the reception of the air quality information systems
already existing is missing, the Ministry for the Environment (BMU) and the Federal Environment Agency (UBA) launched
in 2012 a research investigation to evaluate selected information systems in Germany: (1) tropospheric ozone forecasting, (2)
solar UV radiation index, (3) pollen forecasting, and (4) heat health warnings. The project also aims at optimizing current
communication strategies and concepts.
Methodology and first results
The study investigation has started with a baseline search on established information channels, multipliers and applied
measures and scientific studies. In an additional unrepresentative pre-test survey among representatives (n=77) of the
national, state and local German public health sector the usefulness and relevance of air quality information and warning
systems has been estimated in spring 2013. Strong or some benefit is expected by the majority of asked representatives (75 %
heat health warnings, 67 % solar UV radiation index, 56 % tropospheric ozone forecasting and 44 % pollen flight
information). The rest of the respondents anticipate “no effect” or does not know. No public health body expects any harmful
unintended effects of air quality warnings.
Following the reflections to the pre-test study, one main project module is a representative telephone survey of the general
German population (20 minute interviews of up to 4,000 German residents, aged 14 years and older; about 250 per Federal
State), which was has been carried out during late summer 2013. The questionnaire used for the survey was pretested to
assure understanding. A further project module will investigate the knowledge of local physicians/medical practitioners about
air quality information and warning systems and their access to it. This part is supported by both National and Regional
Associations of Statutory Health Physicians. First analyses and results of both survey modules are expected by the end of
2013, and will be presented at Air Quality 2014.
Conclusion
To prevent public health damages and to strengthen individual health resilience of the population it seems to be essential to
adapt an approved strategy appropriate to cope with (extreme) events of air pollution and changes of human bioclimate.
Acknowledgement
As part of the National Environment Research Programme the study is financially granted by the German Ministry for the
Environment, Nature Conservation and Nuclear Safety (UFOPLAN2012; FKZ 371262207). The two years project is
conducted by the consortium M. Capellaro and partners in co-operation with the Federal Environment Agency (UBA).
References
Sperk C. and Mücke H.-G., 2009 Klimawandel und Gesundheit: Informations- und Überwachungssysteme in Deutschland.
‚Umwelt & Gesundheit‘, 03/2009, ISSN 1862-4340. Hrsg. Umweltbundesamt, Dessau-Roßlau, Germany.
143
IMPROVING AIR QUALITY MODELING FORECASTING SYSTEMS BY USING ON-LINE WILD LAND FIRE
FORECASTING TOOLS: AN APPLICATION OF WRF/CHEM/FIRE MODEL OVER EUROPE
R. San José (1), J. L. Pérez (1), R. M. González (2) , J. Pecci (3) and M. Palacios (3)
(1) Environmental Software and Modelling Group, Computer Science School, Technical University of Madrid,
Campus de Montegancedo, Boadilla del Monte, 28660 Madrid, Spain.
(2) Department of Meteorology and Geophysics, Faculty of Physics, Ciudad Universitaria, 28040 Madrid, Spain.
(3) Indra S.A., C/ Mar Egeo, 4, Pol. Industrial 1, 28830 San Fernando de Henares, Madrid (Spain)
Presenting author email: roberto@fi.upm.es
Summary
This paper presents how to estimate wildfire emissions in on-line mode into the regional air quality model WRF/Chem. The
developed system links the mesoescale air quality and meteorological model WRF/Chem, with the fire model Sfire and
remote sensing data (MODIS fire products) to know the ignition point and date for each fire. WRF-Fire was employed to
simulate the spread and behaviour of the real fires occurred. The system has been applied for one week, in July 2010 for
Europe. All fires have been simulated from the starting and ignition point derived from MODIS data with 20 meters
resolution. On-line emissions have been aggregated to the European domain with 23 Km grid as input to the WRF/Chem
model every time step. Results from the simulations with and without simulated fire emissions have been compared with air
quality data from the Airbase datasets.
Introduction
Emissions from wildland fires remain one of the largest uncertainties from modelling pollution. Obtaining detailed and
accurate emissions data for forest fires for application in air quality simulations is especially difficult. Hourly emissions are
required, so fires behaviour have to be known every hour. In order to predict emissions from forest fires, it is first necessary
to estimate fires behaviour, including date and time that the fire ignition starts, fire spread contours and fire end time for all
fires above a selected size criterion based on the final burnt area observed from a satellite. Wildland fire spread and behavior
are complex phenomena due to both the number of involved physical and chemical factors, and the nonlinear relationship
between variables. After fire activity, data are collected, this information plus fuel information are combined with appropriate
emission factors to predict the emissions. There are several other satellite-based methods that estimate biomass burning
emissions for air quality applications but these techniques are limited to provide the final total emission based on the final
burnt area. The tool presented in this paper differs from those other techniques since we are using a fire behaviour model to
know the fire evolution (contours) every hour. We are using satellite information to set the ignition point and start date. The
fire model provides enough information to refine the spatial and temporal characterization of biomass burning emissions.
Methodology and Results
The global monthly fire location product (MCD14ML) contains the geographic coordinates of individual fire pixels (1 km
spatial resolution approx.) for all Terra and Aqua MODIS fire pixels in a single monthly ASCII file. The MODIS active fire
product detects fires that are burning at the time of overpass using infrared data. The burnt area product (MCD45A1) contains
the date (day) of burning with 500 m spatial resolution. The first step was to identify the start date and ignition point for each
fire event. For that purpose the active-fires and burnt areas data sets were combined and matched.
The core of the system is the WRF-Fire model, which is a two-way coupled fire atmospheric model. It provides forecasts of
the fire spread based on the local meteorological conditions, taking into account the feedback between the fire and the
atmosphere. The fire model is also coupled with WRF-, so the smoke emitted from the fire is added at the location of the
simulated fire and transported within the atmosphere, and undergoes chemical reactions resolved by WRF-Chem. Coupling
with WRF-Chem is implemented by inserting the smoke intensity and air pollution emissions in the WRF-Chem arrays at the
ground layer. The amount of the chemical species released into the atmosphere is computed from the amount of fuel burnt
directly by emissions, table (g/kg fuel or mol/kg fuel for each of the 13 Anderson´s fuel categories used). Emissions are
computed at the fire model resolution (in this experiment 20 meters) and aggregated to the 23 km European spatial resolution
model. The fire simulation is only active when a 23 Km grid cell contains a fire ignition point. A new Fuel Moisture Content
(FMC) model has been developed and integrated into the WRF-Chem-Fire system. The new module allows each time step to
calculate the fuel moisture content of the dead (1hr, 10hr, and 100hr) and live fuels
The tool presented in this study was applied to the European fires in one week period of July 2010. We have run the model
over the European domain with and without fire emissions (calculated as presented in this work). The selected domain covers
all Europe with 279 by 225 grid cells and 33 vertical levels.
Conclusions
The combined use of satellite derived burnt perimeters, active-fires and fire model provide a realistic picture of the complex
spatial temporal distribution of wild land fires. The use of satellite data within the fire behaviour model provides valuable
information to improve the forecasting forest fire emissions. The methodology presented in this work can be applied to any
region of the globe. We demonstrate with a case study how this system can be a useful approach for improving air quality
model predictions when extremely limited information is available. In this work we need only a start point and date.
144
LOTOS-EUROS CONTRIBUTION TO MACC-II-REANALYSIS-2011 TO ASSESS THE AIR QUALITY OF
EUROPE
U. Kumar1, A. Segers2, R. L. Curier2, R. Timmermans2, H. Eskes1
1. KNMI-Royal Netherlands Meteorological Institute, The Netherlands
2. TNO, Climate Air and Sustainabilty Unit, The Netherlands
Summary:
One year reanalysis of regional air quality data of Europe for the year 2011 was constructed using the chemical transport
model LOTOS-EUROS as part of the regional cluster of “Monitoring Atmospheric Composition and Climate (MACC) – II”
project. The model was run at (0.5o x 0.25o) resolution. The reanalysis provides for the surface as well as column analyzed
fields for the air pollutants O3, NO2 ,PM10 and PM2.5. The surface observations of O3, PM10 and PM2.5 from AIRBASE
stations and the satellite observations of OMI NO2 were assimilated into the model using the Ensemble Kalman Filter
technique. The assimilation of O3, PM10, PM2.5 and OMI NO2 were carried out simultaneously. The comparison of model,
assimilated and the observations reveal that the assimilated O3 concentrations are closer to observations than the model for all
the three categories of stations. The PM10 assimilation has its impact to move assimilated PM10 concentrations closer to the
observed, however, the peaks of PM10 episodes are not captured well but the trends are indeed captured. The simultaneous
assimilation of all the four pollutants also provide an opportunity to look if this has any adverse impact on the pollutants
output, however, in this experiment rather favorable impact has been observed.
Introduction:
The importance of air quality forecasts is increasingly being recognized and various air quality models are being used for this
purpose. However, due to nonlinearly coupled equations, it is almost inevitable to use observations into the model by data
assimilation technique not only in order to make good forecasts but also to create reanlaysis. The present work is part of
MACC-II Regional cluster (EVA) project. LOTOS-EUROS is one among seven air quality models that contribute to this
cause. The present study is focussed to create the air quality reanalysis data for the year 2011 using LOTOS-EUROS and the
data assimilation technique Ensemble Kalman Filter.
Methodology
In this study, the LOTOS-EUROS v1.9 (Segers, 2013) in association with Ensemble Kalman filter has been used to create the
2011 reanalysis for the Europe by assimilating AIRBASE surface observations O3, NO2 ,PM10 and PM2.5.and satellite OMI
NO2 data. About 1/3th of the total surface observation stations for each pollutant were kept for the validations. The three
categories of observation stations (background-rural, background urban and background suburban) were assimilated in the
model. The assimilation of O3, PM10, PM2.5 and OMI NO2 were carried out simultaneously. The assimilation system used in
this study is well described in Curier et al, 2012. An ensemble of 12 members is used and each member is created by
applying random noise to emissions and the boundary conditions. The noise factors are assumed to follow a normal
distribution with a mean of 1 and a standard deviation of 0.5.
Results and Conclusion
The correlation for assimilated O3 concentration
has increased by a factor about 10-15% and RMSE
has decreased by a factor of about 15-20%, though
at some stations it has increased too. This works
well both in the summer as well as winter season.
The PM10 is known to be normally underestimated
by chemical transport models, hence, assimilation
of surface observations is expected to benefit the
results. The correlation has increased from about
0.3-0.4 to 0.6-0.65 at some stations, though at few
other stations it has remained the same. RMSE has
slightly decreased. These results are valid both for
the summer as well as winter season. Similar
assimilation impact on PM2.5 concentrations are
also observed. The surface assimilated NO2
concentrations were observed to be underestimated
Fig : Time series of observed, model and assimilate O3 (July), NO2,
for many of the stations though for some other
PM10 and PM2.5(Dec)
rural/suburban background stations it does capture
the peak episodes, especially, during the winter. The simultaneous assimilation of surface O3, PM10, PM2.5 and OMI NO2
has no adverse impacts rather each pollutant concentration output has significantly improved in one single assimilation run.
Acknowledgement
This work is supported by MACC-II project funded by European Community's Seventh Framework Programme (FP7 THEME
[SPA.2011.1.5-02]) under grant agreement n° 283576.
References:
Curier, R. L., Timmermans, R., Calabretta-Jongen, S., Eskes, H., Segers, a., Swart, D., & Schaap, M. (2012). Improving ozone forecasts over
Europe by synergistic use of the LOTOS-EUROS chemical transport model and in-situ measurements. Atmospheric Environment, 60, 217226. Elsevier Ltd. doi:10.1016/j.atmosenv.2012.06.017
Segers, A., 2013. LOTOS EUROS v1.9.000 user guide. http://www.lotos-euros.nl/doc/LOTOS-EUROS-v19-user-guide.pdf
145
AIR QUALITY FORECASTING AND INFORMATION TOWARDS PUBLIC DEMONSTRATED IN WUHAN,
HUBEI PROVINCE, CHINA
L. Liu (1), C. Hak (1), N. Chen (2)
(1) Norwegian Institute for Air Research (NILU), Instituttveien 18, PO Box 100, 2027 Kjeller, Norway
(2) Hubei Environmental Monitoring Center (HBEMC), Bayi Road 338, Hongshan District, Wuhan, Hubei province, China
Presenting author email: lli@nilu.no
Summary
“Hubei air quality information and early warning system, complementing Hubei “1+8” city cluster haze monitoring project”
(Hubei-AQ.info) is an EU funded ongoing project in China. The project is aiming to establish an air quality (AQ) information
system to make air quality (concentrations and Air Quality Index), both for present and for the near future (48-72 hours),
accessible to the public. The project will establish an AQ information system for Wuhan and its surrounding cities, so called
“1+8” city cluster (Figure), and the air quality forecasting system will be made for Wuhan only. The established system can
be expanded to other cities in Hubei with the same methodology provided that emission data are collected in these cities.
Introduction
People in China have been suffering from severe air quality problems in many areas. The air quality problem has been
recognised by the Chinese government and many measures are taken to understand the present situation, to reduce the
emission, and to prevent impact on human health and ecosystem. The public also has strong desire for more air quality
information, especially for people living in cities. Air quality forecasting became an important demand by the public to the
government. Among all air quality issues, the “haze” problem has become an increasing public concern in China and in
Hubei. Several events with extremely high particle concentrations have been experienced in Wuhan in 2012, more studies are
needed to identify sources, conditions, to predict and to provide warning to the public to reduce the impact on human health.
These tasks are addressed by the project Hubei-AQ,info with the objective of developing AQ forecasting and providing
forecasting results to the public in Wuhan.
Methodology and Results
The project is carried out by applying the integrated AQ management and information system, AirQUIS, developed by
NILU. The AirQUIS system contains four modules, including a GIS module, a measurement module, an emission module
and a modelling module. The forecasting system is a comprehensive multi-scale modelling system (right-hand panel of the
figure below). A similar system has been applied in Oslo as an operational AQ forecasting system.
Expected results are: 1. Establish an integrated AQ monitoring database and emission inventory for the 9 cities. 2. Develop a
demonstration case for Wuhan to provide early warning to the public for prediction of pollution episodes. 3. Provide more
AQ information based on the desire for sufficient AQ information of the public. 4. Training and capacity building.
Conclusions
The project complements the large ongoing infrastructure-building and monitoring project “Hubei “1+8” city cluster haze
monitoring” in Hubei, and will substantially extend its capacity and range of achievements. The developed methodology for
air quality forecasting will build up an emission inventory applying both top-down and bottom-up approach, and the
knowledge of the methodology, model tools and database that is applied the project will be transferred to the local partner.
The local government will for the first time provide AQ forecasting to public in Wuhan, and apply the tools and knowledge
to expand it to other cities in Hubei province.
Acknowledgement
This work is supported by EuropeAid, EU-China environmental Government Programme (EGP).
146
SPECIAL SESSION LOCAL AND REGIONAL
AIR QUALITY SERVICES
147
THE PASODOBLE AIRSHEDS - BRIDGING THE GAP BETWEEN THE COPERNICUS ATMOSPHERIC
SERVICE AND LOCAL FORECASTING SERVICES
R. Timmermans (1), D. Balis (2), H. Elbern (3), T. Erbertseder (4), H. Eskes (5), E. Friese (3), C. Hendriks (1), E. Katagrou
(2), R. Kouznetsov (6),U. Kumar (5), O. Lesne (7), A. Poupkou (2), M. de Ruyter de Wildt (5), M. Schaap (1), A. Segers (1),
M. Sofiev (6), and C. Talbot (7)
(1) Netherlands Organisation for Applied Scientific Research (TNO), Utrecht, The Netherlands; (2) Aristotle University of
Thessaloniki, Thessaloniki, Greece; (3) Rheinisches Institute für Umweltforschung an der Universität zu Köln (RIUUK),
Köln, Germany; (4) Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, Germany; (5) Royal Netherlands
Meteorological Institute (KNMI), de Bilt, The Netherlands; (6) Finnish Meteorological Institute (FMI), Helsinki, Finland; (7)
ACRI-ST, Sophia-Antipolis, France
Presenting author email: renske.timmermans@tno.nl
Summary
To bridge the gap between the high-resolution local/urban air quality forecasting services developed with the EU project
PASODOBLE and the lower resolution services on the European scale provided by the Copernicus Atmosphere Service
(MACC-II), five operational systems have been set up. These provide air quality forecasts of a.o. PM, O3 and NO2 at an
intermediate resolution of approximately 6 km for different regions over Europe, the so-called airsheds. The systems are
developed by five different teams using different chemistry transport models driven by the boundary conditions from the
European scale MACC core service air quality forecasts. The airsheds forecasts are subsequently used as boundary
conditions and initialization for local/urban scale services defined within the PASODOBLE project. But also new services
are able to use the airsheds forecasts. This is one of the important advantages of PASODOBLE: a generic and harmonized
infrastructure allowing easy application of new services.
Introduction
Within the frame of the European Earth Observation Programme Copernicus, PASODOBLE has considerably improved
information and tools on air quality in more than 30 regions and cities throughout Europe. This has been achieved through
the development of local services in close interaction with users. Local/urban services which provide air quality forecasts at
high resolution (of 1-2 km) do rely on larger scale models with a lower resolution for the provision of background pollutant
concentrations. To bridge the gap between the local high resolution services and the lower resolution core service from the
EU MACC II project on the European scale, five operational systems (so-called airsheds) have been set-up.
Methodology and Results
The location of the five airsheds have been defined in such a way that
they cover most of the downstream services developed within the
PASODOBLE project (see Figure 1):

Central, Western and Southern Europe (~3W-20E; 41-59N).

Central and Southern Europe (4-18E; 41-51N).

Northern Europe (4-33E; 54-71N).

South-East Europe (~13E-30E; 35N-48N).

Joint airshed (2W-30E; 35-62N).
The nesting within the MACC ensemble service, which provides
forecasts for 6 species on a limited number of levels, has been evaluated.
Results show that the set of required boundary species depends on airshed
location, airshed size, the used model and it’s chemistry scheme, the
species that is computed, and possibly also the time of the year (de Ruyter
de Wildt et al., 2012). In the final operational set-up two airsheds are
using the MACC ensemble data in combination with one of the ensemble
models for missing species. The other three airsheds use data from one of
the ensemble models or from the global MACC product (Mozart) as the
MACC European forecasts coverage was not sufficient.
Conclusion
The five air quality forecast services at an intermediate resolution of 6-7
km have been made available within the PASODOBLE project for use by
local/urban forecasting models over Europe. Some of these airsheds
forecasts will remain available after the project depending on availability
of resources and users.
Fig.1 Location of 5 airsheds (white boxes)
overlapping most of the PASODOBLE services
Fig.2 Ozone forecast example by the joint airshed.
Acknowledgement
This research was funded by EU FP7 project PASODOBLE.
References
De Ruyter de Wildt M.S., Eskes H., Timmermans R., Sofiev M., Prank M., Vira J., Erbertseder T., 2012, Report on Common
standards and interfaces for nesting of air quality models, PASODOBLE report, D_IC-AIRSHEDS_2.1.
148
SATELLITE BASED MAPPING OF PARTICULATE MATTER
M. Kosmale, D. Martynenko, T. Holzer-Popp
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, 82234 Wessling, Germany
Presenting author email: miriam.kosmale@dlr.de
Summary
SYNAER, a DLR developed retrieval technique for aerosol optical depth and aerosol composition from satellite
measurements, enables the differentiation of natural and anthropogenic particulate matter contributions. PASODOBLE1
introduced satellite-based information as complementary source for supporting compliance monitoring of particulate matter.
Introduction
The EU air quality directive 2008/50/EC permits only 35 exceedances of daily mean PM10 above 50μg/m3 per station per
year to safeguard the population from adverse health effects. The directive allows the subtraction of exceedances caused by
natural origin. It was the goal of this dedicated PASODOBLE service to demonstrate support to compliance monitoring by
satellites with their comprehensive view on a region as complementary tool to in-situ measurements for regional authorities.
Individual satellite-based PM2.5 observations typically show errors of 30% and reach correlations up to 0.6 with root mean
square error (RMSE) up to 10µg/m3. This uncertainty is inherent to all methods, which convert aerosol optical depth (AOD)
into PM with the most critical unknowns being vertical profile shape, varying aerosol properties and horizontal smoothing in
large satellite pixels versus in-situ observations2.
Methodology and Results
A synergetic method (SYNAER3,4) developed at DLR for a radiometer spectrometer combination on board polar orbiting
satellites such as ENVISAT and MetOp allows the retrieval of aerosol optical depth (AOD) and aerosol composition, which
serves as basis for deriving PM. Information on aerosol type in SYNAER tackles one of the critical issues lined out above, so
that the method can be applied all over Europe without any need for local tuning. To overcome the latter aspect of large
satellite pixels, the product of choice is mapping annual mean PM values under the assumption of a well-mixed boundary
layer. The aerosol type offers the innovative possibility to produce maps of so-called “local PM”, after subtracting coarse
mode aerosols like sea salt and mineral dust from the total particulate matter load.
Satellite-based PM results are dependent on the underlying AOD retrieval: Limited temporal coverage and individual pixel
AOD uncertainties determine the quality of the annual mean PM maps. The transition of SYNAER from ENVISAT to
MetOp (with much better temporal coverage) and their radiometer/spectrometer instruments AATSR/SCIAMACHY to
AVHRR/GOME-2 showed the need for extra efforts to adapt the parameterization of surface brightness to broader radiometer
channels.
Annual mean maps of PM2.5 and PM10 together with “local PM10” were produced from ENVISAT and METOP covering
entire Europe and selected regions such as Northrhine-Westphalia and the Po basin. The data were validated against annual
mean PM concentrations calculated from in-situ measurements of ambient air operated by LANUV (Environmental Agency
of Northrhine-Westphalia) and EMEP (European Monitoring and Evaluation Programme). This satellite derived product is
unique for air quality monitoring according to the core user LANUV and could become valuable complementary information
for regional authorities all over Europe. This however, depends on the evolution of the European air quality directives and the
threshold levels and margins therein. With an RMSE of 5µg/m3 against rural LANUV stations the annual METOP product
shows a better performance than individual satellite PM pixels. It must be noted that validation is difficult due to limited
station representatives for the satellite pixel size (60x30 km2), as well as the matching of a satellite snapshot around 10:30
local time with daily mean in situ data.
Conclusions
This work showed the possibility for customizing satellite-based measurements of aerosol optical depth for a user specific
application on particulate matter. The calculations were implemented as post-processing to the aerosol retrieval from satellite
data, and were validated against in-situ measurements at ground level. As complementary information to ambient air
monitoring stations, SYNAER’s specific retrieval of aerosol type allows deduction of natural sources of aerosol, and
monitoring particulate matter in compliance with duties of environmental authorities.
Acknowledgement
This work was supported by the European Commission within 7th framework.
References
1. Erbertseder, T. and the PASODOBLE consortium: Take a deep breath with Myair Services - Window on GMES, p.4451, 2012, available from: http://copernicus4regions.eu/publications/window-on-copernicus-en/at_download/file
2. Hoff Raymond M., Christopher Sundar A., 2009. Remote Sensing of Particulate Pollution from Space: Have we reached
the promised Land? Air & Waste Management, 59, 645-675.
3. Holzer-Popp T., 2002. Monitoring of aerosol properties from space for air quality studies, Air Pollution X, WIT Press,
423-433.
4. Holzer-Popp T., Schroedter-Homscheidt, M., Breitkreuz, H., Klüser, L., Martynenko, D., 2008. Improvements of
synergetic aerosol retrieval for ENVISAT, Atmospheric Chemistry and Physics, 8, 7651-7672.
149
AN INTEGRATED PLUME RISE MODEL FOR WILD-LAND FIRES
J. Kukkonen (1), J. Nikmo (1), M. Sofiev (1), K. Riikonen (1), T. Petäjä (2), A. Virkkula (1,2), J. Levula (3), S. Schobesberger
(2) and D. M. Webber (4)
(1) Finnish Meteorological Institute, Erik Palménin aukio 1, FI-00101, Helsinki, Finland; (2) Department of Physics,
University of Helsinki, FI-00014, Helsinki, Finland; (3) Hyytiälä Forestry Field Station, University of Helsinki, FI-35500,
Korkeakoski, Finland; (4) Integral Science and Software Ltd, 484 Warrington Rd., Culcheth, Warrington WA3 5RA, UK
Presenting author email: jaakko.kukkonen@fmi.fi
Summary
A crucial near-fire process for dispersion from wild-land fires is the initial plume rise that determines the injection height of
the fire plume. We have presented an overview of a mathematical model, called BUOYANT, the original version of which
was described by Martin et al. (1997) and Kukkonen et al. (2000). The model addresses the variations of the cross-plume
integrated properties of a buoyant plume in the presence of a vertically varying atmosphere. The model also includes a
treatment for a rising buoyant plume interacting with an inversion layer. We have compared the model predictions with the
data of two prescribed wild-land fire experiments. These are the “Smoke, Clouds and Radiation – California” experiment,
SCAR-C, in Quinault in the U.S. in 1994 and an experiment in Hyytiälä in Finland in 2009 (Virkkula et al., 2013).
Comparison of the model predictions with these data provided more confidence that the BUOYANT model can be used to
fairly good accuracy for evaluating the dispersion from wild-land fires.
Introduction
Pollutant plumes from wild-land fires may cause substantial health effects to populations. The pollutants may be transported
to the upper part of the atmospheric boundary layer, to the free troposphere and in some cases even to the stratosphere.
Methodology and Results
For the SCAR-C experiment in Quinault (U.S.) in 1994, the predicted
vertical extents of the plume at maximum plume rise were between
500–800 m and 200–700 m, using two alternative meteorological
datasets. The corresponding observed injection heights of the aerosol
particles measured using an airborne LIDAR ranged from 250 and
600 m.
For the prescribed burning experiment in Hyytiälä (Finland) in 2009,
the model predictions were compared with plume elevations and
diameters, determined based on particulate matter number
concentration measurements on board an aeroplane. The agreement of
modelled and measured results was good, provided that one assumes
the measured maximum convective heat fluxes as input data for the
model.
Conclusions
The results demonstrate that in field experiments on wild-land fires,
there are substantial uncertainties in estimating both (i) the source terms
for the atmospheric dispersion computations, and (ii) the relevant
vertical meteorological profiles. The results provide more confidence
that cross-plume integrated mathematical models, such as the
BUOYANT model, could be used with a fairly good accuracy for
evaluating the dispersion from major wild-land fires.
Fig. 1. The predicted altitudes of fire plumes as a
function of downwind distance, compared with
aircraft-based measured particle number
concentrations (grey and black dots, corresponding
to two ranges of concentrations) for the Hyytiälä
prescribed burning experiment. Two modelling
options were used (cases 1 and 2).
Acknowledgement
We wish to thank Jörg Trentmann (Deutscher Wetterdienst) for the availability of the measured aeroplane data, and support
of the EU-funded projects PEGASOS and PASODOBLE, the Academy of Finland project ASTREX, and the Fire Protection
Fund in Finland.
References
Kukkonen, J. et al., 2000. Dispersion from strongly buoyant sources. In: Gryning, S.-E. and Batchvarova, E. (eds.), Air
Pollution Modeling and its Application XIII, Kluwer Academic/Plenum Publishers, pp. 539-547.
Martin D. et al., 1997. Near- and intermediate-field dispersion from strongly buoyant sources, AEA Technology Report
AEAT/1388, Warrington, 277 pp.
Virkkula A. et al., 2013. Overview of a prescribed burning experiment within a boreal forest in Finland, Atmos. Chem. Phys.
Discuss., 13, 21703-21763, 2013.
150
ON THE IMPACT OF AIR QUALITY ON HUMAN HEALTH: APPLICATION OF AN AIR QUALITY INDEX
FOR THESSALONIKI, GREECE
Th. Giannaros (1), P. Siropoulou (1), A. Poupkou (1), S. Dimopoulos (1), D. Melas (1) and D. Balis (1)
(1) Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, 54 124, Greece
Presenting author email: thgian@auth.gr
Summary
In this study, we present the implementation and evaluation of an advanced air quality index for the coastal Mediterranean
city of Thessaloniki, Greece. The selected index, namely the Aggregate Risk Index (ARI), was integrated into an operational
air quality forecasting system, comprised of the meso-scale meteorological WRF model and the air quality CAMx model.
Results from the operational implementation of the coupled WRF/CAMx modelling system for a six-month period in the year
2012 were used for evaluating the respective ARI estimates. The evaluation process was carried out using health data
provided by a major hospital in the greater Thessaloniki area. Several different scenarios were investigated in order to verify
the presence of any correlation between the predicted ARI values and the number of either hospital admissions or examined
patients. This analysis revealed the existence of a time lag between the ARI forecasts and health data. In particular, it was
found that the health data of the current day correlate better with the simulated daily maximum ARI values of the previous
two to three days. This study suggests that ARI is a promising tool for assessing the impact of air quality on human health.
Introduction
Extensive research over the past decade has shown that exposure to air pollutants is strongly connected to health endpoints
such as increased hospital admissions for respiratory and/or cardiovascular diseases, and mortality. Further, there is a
profound relation between human health and well being from the one side and air pollution levels from the other. Therefore,
it is not surprising that the impact of deteriorated air quality on human health has become a critical component in relevant
policy discussions. Taking this into consideration, we implemented an advanced air quality index as part of an operational air
quality forecasting system. The goal of this study is to evaluate the suitability of the selected index as a tool for assessing the
impact of air quality conditions on human health.
Methodology and Results
The air quality modelling system employed consists of the
meteorological WRF model off-line coupled with the photochemical air
quality CAMx model (see Fig. 1). The air quality index integrated into
the WRF/CAMx modelling system is ARI, described in detail in Sicard
et al. (2011). The modelling system was implemented operationally
over a high resolution (2 km) domain, focused on the city of
Thessaloniki, during a six-month period spanning January through June
2012. Domain-averaged values of the predicted daily maximum,
minimum and mean ARI, classified per targeted pathology, were
compared to health data acquired from the “Georgios Papanikolaou”
General Hospital of Thessaloniki. The conducted analysis focused on
examining potential associations between the predicted ARI values and
the health data. At a first stage, the health data of the current day were
contrasted to the forecasted ARI data for the same day, revealing the
absence of any statistically significant correlation. At a second stage,
Fig.1 Flow chart of the WRF/CAMx modelling
the health data of the current day were compared against the modeled
system.
ARI data of the previous N days. This particular time lag scenario
revealed the existence of statistically significant correlations between
ARI and the health endpoints represented by the provided medical data. It was found that the forecasted daily maximum ARI
of the previous 2-3 days correlates with the hospital admissions of the current day. For instance, the correlation coefficient
between the daily maximum value of ARI of the previous 2 days and daily hospital admissions for cardiac diseases was
found to equal 0.40 (statistically significant at the α=0.05 level). Similar results were also obtained for other pathologies,
such as for cardiovascular and respiratory diseases.
Conclusions
The current study has shown that ARI can be exploited as a tool for assessing the impact of deteriorated air quality on human
health. The conducted preliminary analysis revealed that forecasts of this particular index might be of great usefulness to
authorities involved in the health sector.
Acknowledgement
This work was funded by FP7-PASODOBLE (Contract No.: 241557). Model simulations have been conducted using the EGI
and HellasGrid infrastructures and support has been provided by the Scientific Computing Centre of A.U.Th.
References
Sicard P., Lesne O., Alexandre N., Mangin A., Collomp R., 2011. Air quality trends and potential health effects –
Development of an aggregate risk index. Atmos. Environ. 45, 1145-1153.
151
AIR QUALITY FORECASTS FOR THE BLACK FOREST REGION
C. C. Bergemann (1), T. Erbertseder (1)
(1) Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, Germany
Presenting author email: christoph.bergemann@dlr.de
Summary
Rural areas may still be strongly influenced by anthropogenic air pollution from sources located in neighbouring urban or
industrial areas. For the modeller, simulating regions away from the emissions poses additional complexities as the
uncertainty caused by largely unknown emission rates is further increased by longer transport pathways through complex
terrain. Besides adding complexity to the transport process, in mountainous areas a single model grid cell covers a large
range of terrain heights leading to large subgrid variability asking to be addressed. Within this work, we present the
POLYPHEMUS/DLR air quality model that is used for routine forecasts of air pollution for the Black Forest, Germany.
Introduction
Monitoring of atmospheric pollutants using in-situ observations by automatized instruments is routinely performed in the
larger cities of Europe and at some more remote locations. These areas are often visited by people travelling there for the
supposedly clean and healthy air. The touristic importance of rural areas asks for improved, i.e. reliable and area-wide air
quality assessments. Without or only few observations at hand, this is best done using numerical chemical dispersion models.
Furthermore, model forecasts can provide additional value for tourists, aiding them in their desire to spend a healthy holiday.
Model description
The POLYPHEMUS/DLR model (Bergemann and Baier, 2013) is based on the POLYPHEMUS air quality system (Mallet et
al. 2007). Input meteorology is computed using the WRF-ARW model (Skamarock et al. 2008) with GFS input data. Within
the Black Forest region, a resolution of 2km is achieved. Emissions are based on the inventory by TNO (Denier van der Gon
et al., 2010) and are further downscaled using information about land cover, population density and road distribution.
Even at high model resolutions, high mountains and steep valleys cause high subgrid variability within the orography. As a
consequence, large deviations between model results and observations are detected at the mountain tops. A correction
procedure has been implemented that allows diagnosing the resulting variability in trace gas concentrations. A reference
simulation was performed for the year 2011. Observations from AirBase are used for model evaluation.
Results
Figure 5 shows the annual mean distribution of surface ozone as
determined by POLYPHEMUS/DLR and the height correction
procedure. We can clearly see the elevated ozone concentrations at
the mountain tops. This is especially important, when the boundary
layer drops below the mountain tops such as during inversion periods
or at night. In this way the model is able to better reproduce station
observations during such periods.
Conclusion
An operational forecasting system for the Black Forest has been
developed. Forecast quality has been improved by accounting for
subgrid variability of terrain height.
Acknowledgements
This work was supported by the European Commission in the
framework of the project PASODOBLE.
Figure 5: Average concentration of surface ozone through
the year 2011 in the study region.
References
Bergemann, C.C., Baier, F., 2013. Particle filter based data assimilation into an air quality model. Submitted to Nonlin.
Processes Geophys.
Denier van der Gon H. A. C., Visschedijk A., van der Brugh H., Dröge R., 2010. A High Resolution European Emission Data
Base for the Year 2005. Report TNO-034-UT-2010-01895_RPT-ML, TNO, Utrecht, 2010.
Mallet V., Quélo D., Sportisse, B., Ahmed de Biasi M., Debry É., Korsakissok I., Wu L., Roustan Y., Sartelet K., Tombette
M., Foudhil, H., 2007, Technical Note: The air quality modeling system Polyphemus. Atmos. Chem. Phys. 5(7), 1855-1877.
Skamarock W. C., Klemp J. B., Dudhia J., Gill D. O., Barker D. M., Duda M. G., Huang X.-Y., Wang W., Powers J. G.,
2008. A Description of the Advanced Research WRF Version 3. Technical Not TN-475+STR, NCAR.
152
AIRINFORM: DEVELOPMENT OF AIR QUALITY INFORMATION AND AWARENESS TOOLS FOR
CHINESE CITIES
N. Veldeman (1), L. Blyth (1), P. Viaene (1), B. Maiheu (1), S. van den Elshout (2), J. Hui (3), W. Shuying (3)
(1) VITO, Boeretang 200, 2400 Mol, Belgium; (2) DCMR Environmental Protection Agency Rijnmond, PO Box 843,
3100AV Schiedam, the Netherlands; (3) LIBOVITO Environmental Technology Co. Ltd, 18 Zhong Guan Cun East Road,
Hai Dian District, Beijing, China (100083)
Presenting author email: nele.veldeman@vito.be
Summary
With China’s fast economic development and the increasing expectations from the general public for a better living
environment, ways to enhance public access to environmental information and environmental governance are pressing for the
Chinese government at all levels. Especially in recent years, there has been significant criticism from the scientific
community and general public regarding the fact that the air quality reported by the government has not seemed to be
consistent with the actual state of the air quality. This presentation focuses on the implementation (including challenges
thereof) of state-of-the-art web based air quality information systems such as those developed in Europe, that are improving
the capabilities of local Chinese Environmental Protection Bureaus (EPBs) in assessing and providing reliable and timely air
quality information to their citizens.
Introduction
AirINFORM is one of fifteen component 1 Partnership Projects taking part in the Environmental Governance Programme
(EGP), which is a key priority of the EU-China environmental cooperation co-financed by the European Commission. The
overall objective of the project is to improve air quality information and communication and awareness tools in pilot cities of
China to enhance public access to environmental information and environmental governance. The pilot cities are Yangzhou,
Taiyuan and Urumqi.
Methodology and Results
In 2012, a new Ambient Air-Quality Standard was released in China. This standard outlines a newly developed Air Quality
Index (AQI) system which includes the pollutants PM2.5 and Ozone (O3). In AirINFORM we are undertaking a
comprehensive review of this revised AQI scheme, comparing it with international AQIs, whilst also considering the newly
regulated pollutant PM2.5. Alongside this, in close co-operation with our Chinese partners and local stakeholders, state-ofthe-art web-based atmospheric modelling tools, based on those in Europe, are being implemented in each of the pilot cities.
Not only will these tools provide the air quality information needed to generate the AQI for each city, they will also provide
valuable information to our pilot cities to assist them in assessing their air quality. Ensuring that they can provide timely and
reliable air quality information to their citizens.
During the stakeholder consultations, it was found that Near Real Time
(NRT) Air Quality (AQ) information, rather as maps than as tables, and the
preference for statistical forecasting models (rather than deterministic
models) might be considered as the most important user requirements.
Furthermore, the tools should help the pilot cities to provide air quality
information to their citizens which cover both variability in time and space
as well as providing alerts. It was therefore decided to build a framework
(OPAQ) for operational NRT and statistical AQ predictions in an
operational context, meaning that the tools provided within the framework
can serve as the calculation kernels of any larger operational AQ service,
both spatially (AQ maps) and temporally (NRT and forecasts). The OPAQ
framework provides the functionality for AQ mapping via interpolation
models and statistical forecasting models based on any number of
techniques (neural networks, multiple regression, pattern matching etc…).
The development of this AQ framework in the context of an EU-China
capacity building project and the first results of the tools established in the
pilot cities shall be demonstrated.
Fig. 1 AQ information tool developed for
Yangzhou, China
Conclusions
In early September 2013 China released its most stringent ‘Action Plan on Air’. The overall goal, is within 5 years to
improve the overall air quality of the country and substantially reduce the days with heavy pollution. The primary focus is on
the Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta regions, where the AirINFORM pilot cities are located.
It states further that the “central government shall disclose the list of ten cities with the best air quality and ten cities with
worst air quality on a monthly basis”. This plan clearly emphasizes the relevance of projects such as AirINFORM, in helping
Chinese cities to quantify and address the AQ problem in China.
Acknowledgement
AirINFORM is being funded by the European Commission as part of the EU-China Environmental Governance Programme
(EGP, www.ecegp.com).
153
SILAM OERATIONAL FORECASTS AT THREDDS SERVER
R. D. Kouznetsov, M. A. Sofiev, J. Vira, M. Prank, J. Soares, C. T. M. Silam
Finnish Meteorological Institute, PL 503, 00101 Helsinki, Finland
Presenting author email: rostislav.kouznetsov@fmi.fi
Summary
Within the MACC and PASODOBLE projects the operational air-quality forecasting has been set up at FMI for three nested
domains in Europe. The data are publicly available via interfaces provided by Unidata THREDDS server. The talk introduces
the SILAM forecasting products and data interfaces to them, and discusses the applicability of OGC standards to operational
forecasting data.
SILAM AQ forecasts
The operational air-quality forecasting has been set up at FMI for three domains:

Europe, including Iceland, eastern Russia ans North of Africa (25W-45E,30N-74N; 0.15°x0.15°), driven by
ECMWF meteorological model,

Regional, including Scandinavia, Finland, and Baltic States, also covering parts of North-Western Russia, Poland
and Germany (4E-33E; 54N-71N; 0.12°x0.07°), driven by Hirlam regional model

HiRes, covering Gulf of Finland region (17.3E-31.25E, 57.5N-62.75N; 0.04°x0.022°), Driven by Arome model
The simulations performed daily with TNO anthropogenic emission inventories and custom sources for volatile organic
compounds, sea-salt and desert-dust aerosols. The European-domain forecast is performed within the MACC-II project and
uses its standard setup and boundary conditions from Mozart model.
Service availability and means of distribution
The SILAM dissemination service uses Uniata THREDDS data server set up at http://silam.fmi.fi/thredds (Fig. 1). The server
provides flexible interface to the data according to user demands. It can provide the data via several protocols including
OpenDAP, NetCDFsubset and WCS. The NetCDF files with full output of model runs can be downloaded from the server
with plain HTTP protocol. On the user request, the server can extract individual variables, for a subdomain or a geographic
point, and/or needed time intervals. Along with the data interface, the server provides the maps and animations for the data.
Maps and animations can be accessed either via Godiva2 web interface at the SILAM web site, or remotely via WMS
protocol.
There are several views on the operational forecast runs. Most used views are “Best timeseries” and “Forecast model run”.
The “Best timeseries” view provides a tailored data set of forecasted fields with minimum available forecast times,
combining available data into a single timeline. Individual forecasts and their subsets can be accessed with “Forecast model
run” view. Besides that the server provides “Fixed forecast time” and “2D time” views. The latter allows for a uniform
representation of the whole forecast chain.
The service contains rolling archives of operational forecasts over three nested domains and provides access to hourly data on
pollutant concentrations and depositions. Fig. 1 shows the input data flows for the FMI THREDDS setup.
Figure. 1 FMI operational AQ forecast data served with thredds.
Current Uses
The FMI AQ forecasting service provides universal means to access the data of operational AQ information. Basic datasets
outlined above are available directly from the Web site. Upon request, FMI also provides users with URL templates and/or
simple scripts to extract the needed data. This significantly simplifies the dissemination procedure and eliminates the need of
custom pre-processing to meet most of user demands. Currently, the setup is used to serve AQ-forecast data for
PASODOBLE user interface, and boundary conditions for local-scale forecasts produced by NIMH Bulgaria, University of
Tartu, and city of Vilnus.
Acknowledgement
EU FP7 MACC-II and PASODOBLE projects
154
INTERACTIVE WEBSITE FOR AIR QUALITY AT ADDRESS LEVEL IN DENMARK
S. S. Jensen (1), M. Fuglsang (1), T. Becker (1), M. Ketzel (1), J. Brandt (1), M. Plejdrup (1), M. Winther (1), T. Ellermann
(1), O. Hertel (1)
(1) Department of Environmental Science, Aarhus University, Roskilde, Denmark
Presenting author email: ssj@dmu.dk
Summary
We developed, tested and demonstrated an internet-based and interactive website for predicted air pollution at street level
which gives all citizens an easy and quick opportunity to get information about air pollution levels anywhere in Denmark.
The website also presents a brief popular interpretation of the data related to health risk together with a description of models
and data used, as well as the uncertainty on the data presented.
Introduction
The public has a general interest to know how much air pollution is where they live, where they may move to, where they
work or where their children go to school etc. Authorities also want to get information about air pollution at address level e.g.
in relation to urban planning or complains in relation to air pollution.
Methodology and Results
Air quality calculations are carried out with a coupled model system consisting of a regional long-range transport model
(DEHM) (Brandt et al. 2001), an urban background model (UBM) (Berkowicz 2000) and a street air quality model (OSPM)
(www.au.dk/ospm) with associated meteorology and emissions data (SPREAD) (Plejdrup & Gyldenkærne, 2011), as well as
the AirGIS system for generating input about traffic and street geometry for OSPM (Jensen et al. 2001;Ketzel et al. 2011).
Calculations are presented for PM10, PM2.5 and NO2 as annual means for urban background concentrations and street
concentrations for 2012 and 2020. An internet based interactive interface presents air quality data using open source WebGIS
and background maps. The interface features GIS functions like navigate, zoom in and out, identify, and search for user
specified postal addresses.
Fig.1 Background concentrations
visualised for Denmark
Fig.2 Street concentrations visualised as dots at
address level on background map
Fig.3 Popup of street concentrations for a
specific address (in Danish)
Conclusions
An internet-based and interactive website for air pollution at street level has been developed for Denmark based on webGIS.
Acknowledgement
Supported by DCE - Danish Centre for Environment and Energy, Aarhus University under a contract for 2012-13.
References
Berkowicz, R. 2000. A Simple Model for Urban Background Pollution. Environmental Monitoring and Assessment Vol. 65,
Issue
1/2,
pp.
259-267.
Brandt, J., Christensen, J.H., Frohn, L.M., Palmgren, F., Berkowicz, R., Zlatev, Z. 2001. Operational air pollution forecasts
from European to local scale. Atmospheric Environment, Vol. 35, Sup. No. 1, pp. S91-S98, 2001.
Jensen, S. S., Berkowicz, R., Hansen, H. S. and Hertel, O. 2001. A Danish decision-support GIS tool for management of
urban air quality and human exposures. Transportation Research Part D-Transport and Environment 6, 229-241.
Ketzel, M., Berkowicz, R., Hvidberg, H., Jensen, S.S., Raaschou-Nielsen, O. 2011. Evaluation of AirGIS - A GIS-Based Air
Pollution And Human Exposure Modelling System. Int. J. of Environment and Pollution. Vol. 47, Nos. 1/2/3/4, 2011.
Plejdrup, M.S. & Gyldenkærne, S. 2011: Spatial distribution of emissions to air – the SPREAD model. National
Environmental Research Institute, Aarhus University, Denmark. 72 pp. – NERI Technical Report no. FR823.
http://www.dmu.dk/Pub/FR823.pdf
155
THE COMBINED USE OF MEASUREMENT DATA AND MODEL RESULTS - THE DATA FUSION OF THE
PESCADO PROJECT
A. Karppinen (1), L. Johansson (1), J. Kukkonen (1), K. Karatzas (2), L. Wanner (3)
(1) Finnish Meteorological Institute, Erik Palménin aukio 1, FI-00101, Helsinki, Finland; (2)Aristotle University of
Thessaloniki, Dept. of Mechanical Engineering, Informatics Systems and Applications Group, 54124 Thessaloniki,
Greece. (3) Dept. of Information and Communication Technologies Pompeu Fabra University, Barcelona, Spain
Presenting author email: ari.karppinen@fmi.fi
Summary
The PESCaDO system (Personal Environmental Service Configuration and Delivery Orchestration) is designed to receive
environment related queries from end users, to discover reliable environmental data in the web, to process these data in order
to convert them into knowledge and to use this knowledge for the provision of human-centered information. In this paper, we
concentrate on the fusion methodology developed for PESCaDO and demonstrate how this approach could be utilized to
overcome one of the major problems in air–quality assessment and modeling: optimizing the use of information originating
from heterogeneous sources (measurements, models) operating in different temporal and spatial scales.
Introduction
The number of various freely accessible services providing environmental information is continuously increasing, the
INSPIRE directive being one of the driving factors behind this rapid development in Europe. The challenge with this growing
amount of available information is simply “information overload”: the amount of available information is beyond the
capabilities of any single users to reliably assess and process to provide a simple and reliable answer to user-specific practical
needs. Thus, there is a strong demand for automatic provision of accurate and reliable user need- and profile-tailored
environmental information. The PESCaDO system is designed to solve the problem: to receive environment related queries
from end users, to discover reliable environmental data in the web, to process these data in order to convert them into
knowledge and to use this knowledge for the provision of human-centered information
Methodology
Studies in Human-Computer Interaction have shown that both the satisfaction of the users with an application and the
objective performance of a service increases if the users can take an active role in the system. Based on this premise, we have
built and demonstrated an interactive environmental information acquisition and generation framework, which has been
realized in the FP7 project PESCaDO. The service involves the experts in four central tasks: (i) determination of criteria for
the search of environmental nodes in the web; (ii) assessment of the relevance of the identified nodes; (iii) assessment of the
quality of the data provided by the nodes, and (iv) selection of the content to be communicated to the user.
In this paper, we focus on the sub-task of post-processing and fusion of the data into a coherent information corpus. By
utilizing a novel fusion method based on statistical regression modeling, which uses as input environmental measurements
data (e.g. meteorology, airquality), model results, land use masks and population density information, we are able to
demonstrate that the service can provide its users reliable information e.g. about local air pollution in the form of highresolution concentration maps over urban and rural landscapes. We also present evaluation results of the system based on two
different types of datasets on pollutant concentrations and ambient temperatures.
Conclusions
Although the fusion module is originally built as an integral part of the PESCaDO system with much wider scope and greater
ambitions than just numerically fusing data from various sources, it has also already opened up new possibilities related to
traditional air-quality modeling. One of the major challenges with air quality assessment and modeling has been the effective
utilization of measurement data and model results in extremely varying temporal and spatial scales. This has been tackled, for
instance with 2-way nesting of models, data-assimilation, empirical scaling coefficients, urban increments, land-use
regression models and other semi empirical models – just to name a few proposed and demonstrated solutions. The
methodology proposed and demonstrated in this paper, can be seen to offer an alternative, and a very general way out of the
multitude of varying solutions currently implemented.
Acknowledgement
EU PESCaDO (FP7-ICT-249584)
References
Johansson, L.O., Karppinen, A. and Wanner, L. Fusion of environmental information for orchestrated services.Proceedings
of the FUSION2013 conference. Istanbul, Turkey, July 2013.
Karatzas, K. and Kukkonen, J., COST Action ES0602: Quality of life information services towards a sustainable society for
the atmospheric environment, ISBN: 978-960-6706-20-2, Thessaloniki: Sofia Publishers, 2009.
Wanner L., Vrochidis S., Rospocher M., Moßgraber J., Bosch H., Karppinen A., Myllynen M., Tonelli S., Bouayad-Agha N.,
Casamayor G., Ertl Th., Hilbring D., Johansson L., Karatzas K., Kompatsiaris I., Koskentalo T., Mille S., Moumtzidou A.,
Pianta E., Serafini L. and Tarvainen V. (2012), Personalized Environmental Service Orchestration for Quality Life
Improvement, 8th IFIP WG 12.5 International Conference, AIAI 2012 Workshops, IFIP AICT 382 (L. Iliadis et al., eds),
Proceedings, Springer, pp.351-360
156
SPECIAL SESSION TRANSPORT RELATED
AIR POLLUTION SCIENCE AND IMPACTS
157
IMPACT OF EMISSIONS FROM INLANDS SHIPPING ON AIR QUALITY AND HEALTH IN THE
NETHERLANDS
M. P. Keuken (1), M. Moerman (1), S. Jonkers (1), J. Hulskotte (1) and G. Hoek (2)
(1) Netherlands Organization for Applied Research (TNO), Utrecht, the Netherlands
(2) Institute for Risk Assessment Sciences (IRAS), University of Utrecht, the Netherlands
Presenting author email: menno.keuken@tno.nl
Summary
This study aims to quantify the contribution of inland shipping on the air quality of black carbon, expressed as elemental
carbon (EC) near inland waterways in the Netherlands. Based on the concentration-response function for EC, the health
impact on the population living near these waterways was estimated. Measurements of particle number concentrations and
elemental carbon were performed to establish emission factors of EC for inland shipping. These emission factors were
combined with data on the volume of inland shipping, the plume height of shipping exhaust plumes and meteorology. A line
source model was applied to derive the contribution of inland shipping on the annual average EC concentration up to 200 m
near waterways with intense inland water transport. In this area live 140 000 people in the Netherlands. The results showed
that most of this population is exposed to additional EC concentrations in the order of 0.1 to 0.3 µg EC per m3. About 10% of
this population is exposed up to 1 µg EC per m3 which may reduce their life expectancy up to 6 months. In view of the
envisaged growth of water transport, there is urgent need for measures to reduce the soot emissions from inland shipping.
Introduction
The link between exposure to combustion or soot particles and adverse health effects has been established (e.g. WHO, 2012),
2012). Soot particles in ambient air may be characterized by the concentration of “ black or elemental” carbon. Inland
shipping has three times lower CO2 emissions per ton transported goods compared to road transport. European transport
policy is therefore directed at the increase of the volume of water transport the coming years. However, the emission
standards for inland ships are still lagging far behind the strict standards for road traffic. In this study, the impact of inland
shipping on air quality and health with emphasis on elemental carbon was estimated near waterways with intense water
transport in the Netherlands.
Methodology and Results
On-line measurements of particle number concentrations and elemental carbon
were employed near two waterways in the Netherlands alongside shipping
monitoring and meteorological measurements. Emission factors for EC were
established by inverse modelling. These factors were about 15 to 60% of PM10
emissions from inland shipping. This information was combined with data from
the national emission inventory of PM10 emissions from inland shipping to
estimate EC emissions from the water ways in the Netherlands. The modelled
contribution of shipping emissions to annual average EC concentrations up to 200
m from the water ways were linked to the population density. The results showed
that the additional exposure to EC was less than 0.1 µg/m3 EC for 60% of the
population, in the range of 0.1-0.3 µg/m3 EC for 30% of the population and more
than 0.3 µg/m3 EC for 10% of the population. Exposure up to 1 µg EC per m3 may
reduce populations life expectancy up to 6 months.
The largest health impact is envisaged for the population in river towns with
residential areas along the waterway front.
Conclusions
Emission standards for shipping are still lagging far behind the strict standards for
road transport. Shipping emissions contribute significantly to elemental carbon
concentrations near water ways with intense water transport. This may have
considerable local health impacts. In addition black carbon emission contributes to
climate forcing as well The expected growth of water transport underlines the need
for emission reduction measures in this sector.
Figure 1: Additional EC (µg/m3)
near water ways in the
Netherlands
Acknowledgement
This work was supported by the Netherlands Ministry of Infrastructure and Environment.
References
WHO, 2012. Health Effects of Black Carbon. World Health Organization, Regional Office for Europe, Copenhagen,
Denmark. http://www.euro.who.int/pubrequest.
158
AN IMPROVED MODEL FOR EVALUATING THE URBAN POPULATION EXPOSURE
J. Soares (1), A. Kousa (1), J. Kukkonen (1), L. Matilainen (1), L. Kangas (1), M. Aarnio (1), M. Kauhaniemi (1), K. Riikonen
(1), J.-P. Jalkanen (1), T. Rasila (1), O. Hänninen (3), T. Koskentalo (2) and A. Karppinen (1)
(1) Finnish Meteorological Institute, Erik Palmenin aukio 1, P.O.Box 503, FI-00101 Helsinki, Finland (2) Helsinki Region
Environmental services Authority P.O.Box 521, FI-00521 Helsinki, Finland (3) National Institute for Health and Welfare,
P.O.Box 95, 70701 Kuopio, Finland
Presenting author email: joana.soares@fmi.fi
Summary
This study presents a substantially improved version of a previously developed mathematical model EXPAND (EXposure
model for Particulate matter And Nitrogen oxiDes; Kousa et al., 2002). The model combines predicted concentrations,
information on people’s activities and location of the population to evaluate the spatial and temporal variation of average
exposure of a population in different microenvironments. Numerical results have been presented on the population exposures
to PM2.5 in the Helsinki Metropolitan Area in 2008 and 2010. The results show the contributions to population exposure from
long-range transport, urban vehicular traffic and shipping. The model could also be applied in other major cities worldwide,
if the required model input data, such as activity and concentration data will be available.
Introduction
Most of the epidemiological studies have been conducted based on pollution concentrations (i) measured at fixed ambient air
quality monitoring sites or (ii) predicted using land-use regression models. However, exposure in an urban area is known to
vary substantially from one microenvironment to another, and it depends on the movements and time use of the population.
Methodology and Results
This paper describes a new model version that includes: (i) an
improved treatment of the emissions and dispersion of both fine
particulate matter (PM2.5) and respirable particulate matter (PM10),
(ii) a detailed treatment of the time-use of population in various
traffic modes, including cars and buses, trains, trams, metro,
pedestrians and cyclists, (iii) an improved treatment of the infiltration
coefficients from outdoor to indoor air, and (iv) a treatment of
various population sub-groups. The revised model version can also be
used to compute intake fractions for the available pollutants, and
applied using several alternative coordinate systems.
The highest total population exposures (originated from all sources
and addressing the whole population in all microenvironments) to
PM2.5 occurred in the centre of Helsinki, in regional population
centres and along major traffic routes (Figure 1). The exposures at
homes and at workplaces were higher than exposures while in traffic
and in recreational activities, partly caused by the longer times spent
at home and at work. The population exposure while in traffic varies
temporally most significantly. The contribution of shipping emissions
to the total population exposure can be up to 20% in the vicinity of
the major harbour areas.
Figure 1: The total exposure of population to PM2.5
originated from vehicular sources in the Helsinki
Metropolitan Area in 2010 (µg/m3*people).
Conclusions
A substantially improved population exposure model is presented. The model was used to compute example results on the
exposure of population to PM2.5 in 2008 and 2010. The highest total population exposures occurred in the centre of Helsinki,
in some regional centres and along major traffic routes. The contribution of shipping emissions can be up to 20 % in the
vicinity of the major harbour areas. The model can be used for evaluating source-category –specific population exposures
separately in four selected microenvironments, for selected population subgroups. The model could also be applied in other
major cities worldwide, if the required activity and concentration data will be available.
Acknowledgements
The study was supported by the EU-funded TRANSPHORM EU Contract FP7-ENV-2009-1-243406; and jointly funded by
the European Regional Development Fund, Central Baltic INTERREG IV A Programme within the project SNOOP.
References
Kousa, A., Kukkonen, J., Karppinen, A., Aarnio, P. and Koskentalo, T., 2002. A model for evaluating the population
exposure to ambient air pollution in an urban area. Atmos. Environ. 36, 2109-2119.
Loh, Miranda M., Joana Soares, Ari Karppinen, Jaakko Kukkonen, Leena Kangas, Kari Riikonen, Anu Kousa, Arja
Asikainen and Matti J. Jantunen, 2009. Intake fraction distributions for benzene from vehicles in the Helsinki metropolitan
area. Atmos. Environ., 43, 301–310.
159
CAN THE PREDICTIONS OF ROAD DUST EMISSION MODELS BE DIRECTLY COMPARED WITH ON-SITE
MOBILE MEASUREMENTS?
M. Kauhaniemi (1), A. Stojiljkovic (2), L. Pirjola (3), A. Karppinen (1), J. Härkönen (1), K. Kupiainen (2), L. Kangas (1), M.
A. Aarnio (1), G. Omstedt (4), B. R. Denby (5), J. Kukkonen (1)
(1) Finnish Meteorological Institute (FMI), Air Quality, P.O. Box 503, 00101 Helsinki, Finland; (2) Nordic Envicon Oy,
Huopalahdentie 24, 00350 Helsinki, Finland; (3) Metropolia University of Applied Sciences, Department of Technology,
P.O. Box 4021, 00180 Helsinki, Finland; (4) Swedish Meteorological and Hydrological Institute (SMHI), 60176 Norrköping,
Sweden; (5) The Norwegian Institute for Air Research (NILU), P.O. Box 100, 2027 Kjeller, Norway
Presenting author email: mari.kauhaniemi@fmi.fi
Summary
The predictions of two road dust suspension models were compared with the on-site mobile measurements of suspension
emission factors. Such a quantitative comparison has not previously been reported in the reviewed literature. The models
used were the Nordic collaboration model NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions, Denby and
Sundvor, 2012) and the Swedish-Finnish FORE model (Forecasting Of Road dust Emissions, Kauhaniemi et al., 2011). An
experimental measurement campaign was conducted using a mobile laboratory called SNIFFER (Pirjola et al., 2009), along
two selected road segments in central Helsinki in 2007 and 2008. Both models reproduced the measured seasonal variation of
suspension emission factors fairly well, during both years at both measurement sites. However, both models substantially
under-predicted the values of the emission factors. The results indicate that road dust emission models can be directly
compared with mobile measurements. However, more extensive and carefully planned experimental datasets in various
climatic and street maintenance conditions will be needed in the future, for the evaluation of road dust emission models.
Introduction
Road suspension emission models have previously been evaluated either (i) by combining these with atmospheric dispersion
models or (ii) using NOx concentration measurements and emissions as tracers, and subsequently comparing the predicted
concentrations with measurements. However, using either of these methods is not totally satisfactory, as the evaluation
method itself causes substantial additional uncertainties. The aim of this study was to evaluate, whether the predictions of
road dust emission models could instead be evaluated more directly, by comparison with field-scale measurements.
Methodology and Results
The mobile laboratory SNIFFER was used to measure non-exhaust particle concentrations behind a tyre under real driving
conditions. The instrumentation has been set in a Volkswagen diesel van. Both the FORE and NORTRIP models describe
particulate matter generated by the wear of road surface due traction control methods and processes that control the
suspension of road dust particles into the air. The predicted suspension emission factors for the whole traffic fleet were
converted to suspension emission factors for a van. The measured hourly average suspension emission factor for van varies
from 37 to 1860 µg/veh/m depending on the year and location. The corresponding modelled values varied from 4 to 893
µg/veh/m by NORTRIP model and from 7 to 759 µg/veh/m by FORE model.
Conclusions
The comparison of mobile measurements and model predictions showed an encouraging agreement regarding the seasonal
variation of suspension emission factors. However, the model predictions were significantly lower than the measurements.
One reason that causes uncertainty to the measured values is the modest temporal representativity of the mobile
measurements. Despite the limitations of the experimental dataset, this study was able to provide for the first quantitative
results on the comparability of these two key sources of information regarding suspension emissions.
Acknowledgement
We acknowledge the funding from the Nordic Council of Ministers (NORTRIP project), the European Community
(TRANSPHORM and LIFE+ REDUST), and the Academy of Finland (APTA).
References
Denby, B.R., and Sundvor, I., 2012. In collaboration with: Johansson, C., Kauhaniemi, M., Härkönen, J., Kukkonen, J.,
Karppinen, A., Kangas, L., Omstedt, G., Ketzel, M., Pirjola, L., Norman, M., Gustafsson, M., Blomqvist, G., Bennet, C.,
Kupiainen, K., Karvosenoja, N. NORTRIP model development and documentation: NOn-exhaust Road TRaffic Induced
Particle emission modelling. Norwegian Institute for Air Research (NILU OR 23/2012). URL: www.nilu.no
Kauhaniemi, M., Kukkonen, J. Härkönen J., Nikmo J., Kangas L., Omstedt G., Ketzel M., Kousa A., Haakana M., Karppinen
A., 2011. Evaluation of a road dust suspension model for predicting the concentrations of PM10 in a street canyon. Atmos.
Environ. 45, 3646-3654.
Pirjola, L., Kupiainen, K.J., Perhoniemi, P., Tervahattu, H., Vesala, H. 2009. Non-Exhaust Emission Measurement System of
the Mobile Laboratory SNIFFER. Atmos. Environ. 43, 4703-4713.
160
EVALUATION OF THE PRESENT AND FUTURE AIR QUALITY IN EUROPE BASED ON TRANSPHORM
MULTI-MODEL ENSEMBLE
M. Prank (1), M. Sofiev (1), B. Amstrup (2), A. Baklanov (2), H. Denier van der Gon (3), C. Hendriks (3), X. Kong (4), A.
Mažeikis (2), R. Nuterman (2), S. Tsyro (5), S. Valiyaveetil (5), X. Vazhappilly Francis (4), J. Kukkonen (1), R. S. Sokhi (4)
(1) Finnish Meteorological Institute, (2) Danish Meteorological Institute, (3) TNO, (4) University of Hertfordshire,
(5) Met Norway
Presenting author email: marje.prank@fmi.fi
Summary
Within TRANSPHORM project five regional dispersion models were applied to evaluate the air quality for present and
future emissions in Europe. The present-state estimates were compared with air quality observations to evaluate the reliability
of individual models and ensemble predictions. Future-emission scenarios were analysed with respect to the present situation
and the agreement between the models was evaluated.
Special attention was given to chemical composition of
particulate matter and the models ability to reproduce the
specific components.
Introduction
According to the experience of both meteorological and air
quality modelling, even limited size ensembles have
routinely shown better skills in comparison with
observations than the individual simulations. The spread
between the individual ensemble members indicates the
range of uncertainties in the simulation results, which is
especially important for future scenario simulations, where
no observations exist to verify the simulations.
Methodology and Results
The regional dispersion models participating in the ensemble
were CMAQ, EMEP, HIRLAM-CAMx, LOTOS-EUROS
and SILAM. The European emission inventory for 2005,
including improved traffic emissions and the future
projections developed within TRANSPHORM project, were
used for the current-state analysis and the baseline future
scenarios for 2020 and 2030. All simulations were made
with the same meteorological data for 2005, i.e. only the
effect of the most-probable future emission developments
was evaluates.
The present-state estimates of each dispersion model, as
well as ensemble median and average were compared with
European air quality observations stored in AIRBASE and
EMEP databases (Fig.1). It was found that the models tend
to agree with each other for the well-observed pollutants,
whereas the divergence for the species with smaller
observational networks was larger. The ensemble median
and average usually are closer to measurements than any
individual model or, at least, at the level of the best model.
The trends in concentration and deposition of the primary
pollutants (Fig.2) were constrained by the emission
changes, while for the secondary species, the spread
between the models was much wider.
There were significant differences between the
representations of PM composition by the models.
Fig.1 Histogram of the number of EMEP stations against the
correlation coefficient of predictions and measurements, for the
daily concentrations of PM2.5 in 2005 for individual models and
the mean and median of the ensemble.
Fig.2 Difference in predictions for the annual mean surface
concentrations of NO2, 2030 - 2005, for five chemical transport
models and the ensemble median. Blue colours indicate decrease in
time of the concentrations, red colours increase of concentrations.
Conclusions
The results demonstrate the use of multi-model ensemble for
the model studies of emission- and climate-related trends in
the air quality in Europe. Model inter-comparison, in
addition to comparison with observations, proved to be
instrumental for model improvement.
Acknowledgement
This work was performed within FP7 TRANSPHORM project.
161
TRAFFIC-RELATED AIR POLLUTION AND THE ONSET OF MYOCARDIAL INFARCTION: DISCLOSING
BENZENE AS A TRIGGER? A SMALL-AREA CASE-CROSSOVER STUDY
D. Bard (1), W. Kihal (1), C. Schillinger (2), C. Fermanian (1), C. Ségala (3), S. Glorion (1), D. Arveiler (4), C. Weber (5)
(1) EHESP, Rennes and Sorbonne Paris Cité, Paris, France; (2) Association pour la Surveillance de la Qualité de l’Air en
Alsace-ASPA, Schiltigheim, France; (3) SEPIA-Santé, Baud, France; (4) Department of Epidemiology and Public Health,
EA 3430, University of Strasbourg, Strasbourg, France; (5) LIVE UMR7362 CNRS, University of Strasbourg, Strasbourg,
France.
Presenting author email: denis.bard@ehesp.fr
Summary
Exposure to traffic is an established risk factor for the triggering of myocardial infarction (MI). Particulate matter, mainly
emitted by Diesel vehicles, appears to be the most important stressor. However, the possible role of benzene from gasolinefuelled cars has not been explored so far. We conducted a case-crossover study from 2,134 MI cases recorded by the local
Coronary Heart Disease Registry (2000-2007) in the Strasbourg Metropolitan Area (France). Nitrogen dioxide, particles of
median aerodynamic diameter <10 µm (PM10), ozone, carbon monoxide and benzene air concentrations were modeled on an
hourly basis at the census block level over the study period using the deterministic ADMS-Urban air dispersion model. We
have found a positive, statistically significant association between concentrations of benzene and the onset of MI: per cent
increase in risk for a 1 µg/m3 increase in benzene concentration in the previous 0, 0-1 and 1 day was 10.4 (95% confidence
interval 3-18.2), 10.7 (2.7- 19.2) and 7.2 (0.3-14.5), respectively. The associations between the other pollutants and outcome
were much lower and in accordance with the literature. Benzene emissions from gasoline-fuelled cars may be an important
trigger of MI.
Introduction
The effects of traffic-related air pollution on cardiorespiratory mortality have been consistently established since the late
1980s and further studies specifically investigated the association between exposure to traffic and the onset of myocardial
infarction (MI), one of the most frequent causes of death. PM10, mainly emitted by Diesel engines, is the air pollutant most
consistently associated with MI onset. However, some components of traffic exposure remain ill-defined. In particular,
gasoline-fuelled benzene emissions have never been tested for this specific outcome. For exploring such an association, we
carried out a time-stratified case-crossover study, using a very small area as the statistical unit.
Methodology and Results
Cases (n = 2,134) were all MI events (ICD-9: 410) either fatal or non-fatal, occurring in the age group 35-74 years between
January 1, 2000 and December 31, 2007, in the Strasbourg (France) Metropolitan Area, ascertained by the local Bas-Rhin
Coronary Heart Disease Registry. Available individual data were age, gender, previous history of ischemic heart disease, and
address of residence (to which subjects were geocoded) at the time of the event. NO2, PM10, O3, CO and benzene air
concentrations were modeled on an hourly basis at the census block level over the study period using the deterministic
ADMS-Urban air dispersion model. Model input data comprised of emissions inventories, background pollution
measurements and meteorological data. We have found a positive, statistically significant association between incremental
concentrations of benzene and the onset of MI for our study population (base model), for all lags tested (lag 0 = average air
pollution indicators’ concentrations of the day of the event; lag 0-1 = average of the day of the event and the 1st previous day;
lag 1 =average of the previous day), slightly more marked for the first two lags studied (Table 1). The associations between
the other individual pollutants and outcome were similar in size and direction to those reported in the literature.
Table 1. Exposure to air pollution and the onset of a myocardial infarction in the
Strasbourg (France) Metropolitan Area, 2000-2007.a
Lag 0
Lag 0-1
Lag 1
Pollutant
eOR (95%CI)
eOR (95%CI)
eOR (95%CI)
Benzene
10.4 (3.0-18.2)*
10.7 (2.7-19.2)*
7.2 (0.3-14.5)‡
PM10
2.6 (-2.7-8.2)
3.5 (-2.3-9.7)
3.1 (-2.0-8.5)
NO2
4.7 (-0.2-9.9)
5.4 (-0.1-11.2)
3.6 (-1.0-8.5)
CO
3.2 (-6.1-13.3)
4.4 (-6.6-16.7)
3.0 (-6.2-13.1)
O3
-1.3 (-3.8-1.3)
-2.7 (-5.5-0.2)
-3.1 (-5.7- -0.5)‡
aAssociations
observed for different lag
times; excess odds ratios (eOR) are
expressed as per cent (95% confidence
interval) increase for i) a 1 µg/m3 increase in
benzene concentrations; ii) a 10 µg/m3 in
NO2, O3 and PM10 concentrations and iii) a
100 µg/m3 increase in CO concentrations.
Adjusted for the previous day maximum
atmospheric pressure, same day minimum
temperature and influenza epidemics.
*p<0.01; ‡p<0.05
Conclusion
We have observed a benzene-associated risk for the triggering of myocardial infarction, using a very precise characterization
of cases and of exposure. This association has not been documented in previous literature. In addition, the strength of the
association was much greater for benzene as compared to traffic-related pollutants usually investigated, such as particulate
matter.
References
Peters A, et al. Exposure To Traffic And The Onset Of Myocardial Infarction. N Engl J Med 2004;351(17):1721-1730.
162
HEALTH IMPACT ASSESSMENT OF LONG-TERM EXPOSURE TO PARTICULATE AIR POLLUTION
WITHIN TRANSPHORM. (FOR SPECIAL SESSION ON TRANSPHORM PROJECT)
B. G. Miller (1), J. F. Hurley (1), R. S. Sokhi (2), M. Keuken (3) and B. Brunekreef (4)
(1) Institute of Occupational Medicine, Riccarton, Edinburgh EH14 4AP, United Kingdom; (2) Centre for Atmospheric
and Instrumentation Research (CAIR), University of Hertfordshire, Hatfield, Hertfordshire, AL10 9AB, United
Kingdom; (3) Nederlandse Organisatie Voor Toegepast Natuurwetenschappelijk Onderzoek, P.O. Box 80015, NL-3508
TA Utrecht, Netherlands; (4) Institute of Risk Assessment Sciences, Universiteit Utrecht, P.O. Box 80178, NL-3508 TD
Utrecht, Netherlands
Presenting author email: brian.miller@iom-world.org
Summary
Quantitative Health Impact Assessment (HIA) is an integral part of the EU project TRANSPHORM, quantifying and
comparing the health impacts of pollution changes associated with future transport policies. We highlight the methodological
advances made in adapting to the project’s specific requirements, by estimating impact as a change in per annum burden of
mortality or disease; and show provisional results of HIAs for mortality in five European cities selected as case studies.
Introduction
Quantitative Health Impact Assessment (HIA) aims to create predictions of the impacts on health of changes in the human
environment. Within TRANSPHORM, the aim of HIA is to predict changes in health in the populations affected by
pollution from transport sources; and, specifically, to compare impacts in future years across different policy options and
additional measures. This has required new and adapted approaches to HIA quantification; a secondary objective is to
illustrate these here with provisional results from case studies in five cities with different pollution concentrations.
Methodology
In the TRANSPHORM project, the focus is on impacts of future policies, but air quality predictions modelling those policies
are available only for a current baseline and selected future years. We therefore predict the impact of the changes in pollution
as the change in mortality burden for those specific years, expressed as an amount per annum. Burdens of disease from air
pollution are dominated by mortality. Concentration-response functions (CRFs) linking change in mortality rates to change in
concentrations of PM2.5, elemental carbon (EC) and particle number (PNC) are applied to the modelled population-weighted
mean concentrations to produce relative risks; these are applied to background all-cause mortality statistics for those aged
30+ to estimate numbers of attributable adult deaths, and age-specific life expectancies are used to convert these to life-years
lost. Future burdens are predicted by proportionality in the relative risks, and the policy impacts as reductions in burdens. A
similar approach is applied to non-mortality health outcomes, integrating the results via DALYs. The methods are being
piloted in case studies on mortality data and modelled pollution concentrations from five cities (London, Rotterdam, Athens,
Helsinki and Oslo), and will be extended to all urban areas of Europe. Once proven, they will be incorporated into an
Integrated Assessment Tool for others to use.
Results
Models for London predict that measures already agreed, designed to reduce emissions from transport sources, will reduce
mean PM2.5 concentrations by about 25% by 2020. We provisionally estimate that this will reduce attributable deaths from a
current 3,200 to 2,400. Additional transport policy measures, such as increasing numbers of electric cars or creating lowemission zones, are predicted to further reduce concentrations little or not at all. The other case-study cities show similar
patterns, albeit with different degrees of reduction in PM2.5 (Rotterdam 44%, Oslo 7.5%, Athens 16%, Helsinki 4%). HIAs
using CRFs for EC or PNC tend to predict smaller gains in mortality.
Future developments
The approaches developed can be tailored to many different scenarios and sets of assumptions, with varying levels of
uncertainty. One principal concern for any HIA is to have a reliable (set of) concentration-response function(s). EU projects
REVIHAAP and HRAPIE have been reviewing the available literature, and the result will be authoritative recommendations
on what health outcomes should be included in an HIA, and what CRFs to use for them. We anticipate that those
recommendations, to be reported soon, will guide final decisions on elements of HIAs within TRANSPHORM.
Acknowledgement
Our methods have been developed within EU-funded projects such as CAFE, HEIMTSA and TRANSPHORM, and work
funded by the UK Department of Health to inform the COMEAP committee; see their report (2010).
References
COMEAP. (2010). The Mortality effects of long-term exposure to particulate air pollution in the United Kingdom. A report
by the Committee on the Medical Effects of Air Pollution, prepared by the QUARK II subgroup. Chilton, Oxfordshire, UK:
Health Protection Agency.
http://comeap.org.uk/images/stories/Documents/Reports/comeap%20the%20mortality%20effects%20of%20longterm%20exposure%20to%20particulate%20air%20pollution%20in%20the%20uk%202010.pdf
163
EUROPEAN PARTICLE NUMBER EMISSIONS FOR 2005, 2020 AND 2030 WITH SPECIAL EMPHASIS ON
THE TRANSPORT SECTOR.
H. A. C. Denier van der Gon (1), A. J. H. Visschedijk (1), J. Kuenen (1), C. Schieberle (2), I. Vouitsis (3), Z. Samaras (3), J.
Moldanova (4), A. Petzold (5)
(1) TNO, Princetonlaan 6, 3584 CB Utrecht, The Netherlands; (2) IER, University of Stuttgart, Heßbrühlstrasse 49a, 70565
Stuttgart, Germany; (3) Laboratory of Applied Thermodynamics, Aristotle University of Thessaloniki, GR - 541 24,
Thessaloniki, Greece; (4) IVL, Swedish Environmental Research Institute, Box 5302, 40014 Gothenburg, Sweden; (5) DLR,
82234 Oberpfaffenhofen, Germany; now at Forschungszentrum Jülich, IEK-8, GmbH, 52425 Jülich, Germany
Presenting author email: hugo.deniervandergon@tno.nl
Summary
PN emissions are the most accurate measure to characterize ultrafine particle (UFP) emissions. A new particle number(PN)
inventory for UNECE Europe was made for 2005 and the projection years 2020 and 2030. The new inventory focuses on the
contribution of the transport sectors. The aim of this new inventory was 1) to use the new TRANSPHORM emission factors,
2) to make a preliminary calculation of the PN emissions in 2020 and 2030 and 3) to provide input for regional scale PN
modelling. The results show the importance of the transport sectors for UFP emissions but also suggest strong reductions in
the future due to decreasing sulphur content of the fuels and improving engine technologies including end-of-pipe measures.
Introduction
Epidemiologic data have provided indirect evidence that ultrafine particles from fossil fuel combustion are important in
explaining cardiovascular hospital admissions and mortality due to outdoor air pollution (e.g. Delfino et al, 2005). UFP
emissions are best based on PN emission data because the mass fraction of UFP in PM is too small. A first European sizeresolved anthropogenic PN emission inventory was made in the frame work of FP6 EUCAARI (Denier van der Gon et al.,
2010). Here we present a new PN inventory based on the previous work with new assessments for each transport mode.
Methodology and Results
For each transport sector a new bottom-up calculation was made,
including gap-filling for unknown technologies or activities. For
modelling all source sectors need to be present. To approximate the
future year emissions for the non-transport sectors, scaling factors were
used based on the IIASA primes baseline scenario for PM2.5
(http://gains.iiasa.ac.at/). Hence we assumed that PN emissions for the
non-transport sectors would follow the trend in PM2.5 emissions. Total
PN emissions by country group are presented in Fig. 1. PN emissions are
projected to halve in the future. International shipping is a dominating
source in 2005, but is expected to decline due to the introduction of low
sulphur fuels. Shipping is more dominant in the new inventory but the
Fig.1 Total particle number emissions for 2005, 2020 and
2030 by country group (Sea is international shipping)
data are limited and clearly warrant additional research. In 2005 the
transport sectors contribute ~60% to total land-based PN emission in
UNECE-Europe. The emissions of land-based transport change
significantly over time, especially road transport declines strongly (Fig.
2). In the new inventory aviation is now recognized as a significant
source of (semi-volatile) PN.
Conclusions
PN emissions due to fuel combustion in road transport and shipping may
change significantly as a consequence of motor and fuel modifications
such as low-sulphur fuels and particulate matter filters. This impact is
reflected in our 2020 and 2030 projections. Another remarkable change
compared to the previous inventory is that we believe that aviation is a
stronger source of UFP than previously assumed, most of these are not
Fig.2 Transport sector total particle number emissions
solid PN and may have escaped attention in previous emission factor
in 2005, 2020 and 2030 excluding International
measurements. The EU 15 emissions decline strongly in future years, due to
shipping. (Aviation = airport LTO’s upto 1000 m)
implementation of emission standards in road transport and the phase-out of
the older vehicles with less stringent emission limits. Both inland shipping and coastal shipping are expected to decline.
Acknowledgement
This work was partly funded by EU Seventh Framework Programme - (ENV.2009.1.2.2.1) project TRANSPHORM.
References
Denier van der Gon, H.A.C., Visschedijk, A., Johansson, C., Ntziachristos, L., Harrison, R.M., (2010): Size-resolved PanEuropean Anthropogenic Particle Number Inventory , International Aerosol conference, 29/8-3/9 2010, Helsinki.
Delfino R.J., Sioutas C., Malik S., 2005. Potential role of ultrafine particles in associations between airborne particle mass
and cardiovascular health. Environ Health Perspect. 113, 934-946.
164
AIR QUALITY IMPACTS OF ELECTRIC VEHICLES IN BARCELONA
A. Soret (1), M. Guevara (1), and J. M. Baldasano (1,2)
(1) Barcelona Supercomputing Center – Centro Nacional de Supercomputación (BSC-CNS). Earth Sciences Department.
Jordi Girona 29, Edificio Nexus II, 08034 Barcelona, Spain; (2) Technical University of Catalonia (UPC). Avda. Diagonal
647, Edificio H, Oficina 10.23, 08028 Barcelona, Spain
Presenting author email: albert.soret@bsc.es
Summary
This study applies the WRF-ARW/HERMESv2/CMAQ model system to analyse potential reduction in traffic emissions and
related urban air quality improvement as a result of the electric vehicle (EV) introduction. The studio is performed in
Barcelona city (Spain) which presents several air quality problems, mainly related to NO2 and particulate matter. Results
show that the introduction of EV offers potential air quality benefits, especially for NO2 and CO. Even considering overnight
electric generation emission associated with EV charging in a power station located in Barcelona, significant air quality
benefits are observed. However, the gradual EV introduction cannot be considered as a single solution. Its implementation
may be complemented with other strategies to further reduce traffic emissions.
Introduction
The largest contribution of atmospheric pollutant emissions in urban areas today comes from on-road transport. There have
been significant efforts to study the effects of strategies that are utilized to reduce on-road traffic emissions and the
subsequent impacts of these emissions on air quality. Currently, the main objectives of these strategies are targeted by: 1)
reducing the emission per vehicle by adopting lower polluting fuels and technologies or 2) adopting mobility management
strategies in order to reduce either the vehicle kilometre travelled (VKT), or the speed circulation. The EV introduction
represents one of those strategies under consideration. EV are particularly suitable to improve urban air quality where short
distances are prevalent. The main objective of this work is to analyse how EV would reduce urban air pollution. It has
focused on the improvement of air quality due to the abatement of urban traffic emissions taking also into account electric
generation emission associated with EV charging.
Methodology and Results
The study is conducted in the coastal area of Barcelona city, where the presence of sea breezes and the development of a
thermal boundary layer involve layering and accumulation of pollutants. A critical episode of air quality pollution has been
selected (3-5 October, 2011). The WRF-ARW/HERMESv2/CMAQ model system is applied at high spatial (1x1 km2) and
temporal (1 h) resolution to assess air quality analysis at urban scales. Detailed information of urban traffic and power
generation has been collected as input information for the emission inventory. The model performance has been evaluated
against available air quality observations (Fig. 1). Base case scenario has been compared with three EV introduction
scenarios (low: 10% of VKT in electrical mode; medium: 19%; and high: 29%), taking also into account electric generation
emission associated with EV charging.
Fig.1 Observations and modelled NO2 levels for the four EV scenarios at
Poblenou station.
Fig.2 NO2 maximum differences for the more
ambitious scenario.
Results show that the more ambitious scenario would reduce 10.7% of NOx emissions in Barcelona. Those emissions
reductions may involve air quality improvements of around 7-13%% in the NO2 daily levels, while for the maximum levels
would be a little bit higher: 8-16% (Fig. 1 and 2). Air quality impacts of using overnight electricity generation to charge EV
would not imply significant NO2 hourly increases (<2 µg/m3). The highest potential air quality improvements are observed
for NO2 and CO levels, for the other pollutants the impact is lower. Regarding particulate matter, the potential air quality
improvements are under 5%. This is because exhaust emissions represent ± 30% of the total on-road traffic emissions, the
rest cannot be reduced by the EV (resuspension and brake, tyre and road abrasion).
Conclusions
Despite EV presents potential air quality benefits, some consideration may be taken into account. First that EV introduction
may involve all the vehicle categories (two-wheelers, heavy duty vehicles) not only light-duty vehicles. Second, that the
percentage of EV required (20-30%) to acquire a significant NO2 levels improvement suggest that all the stakeholders may
work together in order to assess such paradigm shift. Finally it should be noted that EV introduction cannot be considered as
a unique solution and may be complemented with other traffic and mobility strategies, especially regarding particulate matter.
165
CALCULATIONS OF PRESENT AND FUTURE EFFECTS OF DIFFERENT TRANSPORT MODES ON AIR
QUALITY AND HUMAN HEALTH IN EUROPE
J. E. Jonson(1), R. Friedrich (2), S. Tsyro (1), J. Roos (2) and V. S. Semeena (1)
(1) Norwegian Meteorological Institute, Oslo, Norway; (2) Institute of Energy Economics and the Rational Use of Energy
(IER), University of Stuttgart, Germany
Presenting author email: j.e.jonson@met.no
Summary
The EMEP/MSC-W chemical transport model is used to calculate the effects of emissions from transport sources on
European air quality. The effects of present (2005) and future (2020 and 2030) emissions on air quality in Europe have been
compared. A new bottom-up emission set for transport modes, developed under the EU FP7 TRANSPHORM project, is
integrated in the TNO-MACC European emission data base (Kuenen et al., 2010). Future emissions is projected using the
scaling factors developed for the EU FP7 project MEGAPOLI (Theloke et al, 2010) combined with newly calculated within
the TRANSPHORM future emissions for the transport sectors. In a second step, the health damage caused by the modelled
concentrations is estimated. Updated concentration-response relationships are used developed in the TRANSPHORM project
based on the findings of the ESCAPE project.
Introduction
Despite a considerable progress in improving air quality air pollution still poses threat to people health, causing unnecessary
premature deaths and cancer, cardiovascular and respiratory diseases, with associated human suffering (WHO, 2013). Recent
studies provide considerable support the earlier scientific conclusions regarding PM adverse health effects (WHO, 2005) and
suggest additional health outcomes associated with long-term exposure to
PM2.5 (WHO, 2013). Transport sources represent considerable contribution
to air pollution and the assessment of present and future health effects of
transport pollution is thus of much importance.
Methodology and Results
For a detailed description of the EMEP model see Simpson et al. (2012)
and references therein. Air pollution levels have been calculated on a
European domain with a 1/4 x 1/8 degrees longitude-latitude resolution for
the meteorological conditions of the year 2005. The effect of transport has
been segregated for different transport modes, including aviation, rail, sea
transport and road transport. In addition to the Baseline emission reduction
scenarios, the effects of possible mitigation options have been explored.
To estimate the exposure to PM2.5 in cities, a newly developed model for
estimating the urban increment is used (Torras et al., 2013). The
calculations of air pollutants are supplemented by estimation of health
effects.
Conclusions. Results show that the health impacts stemming from road
transport are declining due to the EU regulations (e.g. EURO 5 and 6
standards), while the impacts of maritime ship transport decline less and
thus become the largest contributors to transport related health impacts,
especially in certain areas in Southern Europe. The aircraft emissions are
shown to have a small contribution to the surface PM2.5 and thus to people
health effects.
Figure 1: Model calculated PM2.5 levels in
Europe for year 2020: top – Baseline, bottom
- including further mitigation options, mainly
affecting ship emissions.
Acknowledgement
This work was supported by the EU 7'th framework project TRANSPHORM.
References
Kuenen, J. H. Denier van der Gon, A. Visschedijk, H. van der Brugh, High resolution European emission inventory for the
years 2003 – 2007, TNO report TNO-060-UT-2011-00588, Utrecht, 2011.
Simpson, D., A. Benedictow, H. Berge, R. Bergström, L. Emberson, H. Fagerli, G.D. Heyman, M. Gauss, J.E.Jonson, M.E.
Jenkin, A. Nyíri, C. Richter, V.S. Semeena, S. Tsyro, J.-P. Tuovinen, A. Valdebenito and P. Wind (2012) The EMEP
MSC-W chemical transport model – Part 1: Model description, Atmos. Chem. Phys. Discuss., 12, 3781-3874,
doi:10.5194/acpd-12-3781-2012, 2012.
Theloke J., M.Blesl, D. Bruchhof, T.Kampffmeyer, U. Kugler, M. Uzbasich, K. Schenk, H. Denier van der Gon, S. Finardi,
P. Radice, R. S. Sokhi, K. Ravindra, S. Beevers, S. Grimmond, I. Coll, R. Frie-drich, D. van den Hout, (2010): European
and megacity baseline scenarios for 2020, 2030 and 2050. Deliverable D1.3, MEGAPOLI Scientific Report 10-23,
MEGAPOLI-26-REP-2010-12, 57p, ISBN: 978-87-92731-04-3
Torras Ortiz, S.;R. Friedrich: A modelling approach for estimating background pollutant concentrations in urban areas;
Atmospheric Pollution Research 4 (2013) 147‐156.
WHO (2006): WHO Air Quality Guidelines for particulate matter, ozone, nitrogen dioxide and sulphur dioxide.
WHO (2013): Newsletter, No. 51, June 2013.
166
MODELLING OF PARTICULATE MATTER CONCENTRATIONS IN THE HELSINKI METROPOLITAN
AREA IN 2008 AND 2010
M. A. Aarnio (1), L. Kangas (1), M. Kauhaniemi (1), A. Karppinen (1), A. Kousa (2), T. Petäjä (3), C. Hendriks (4), J.
Kukkonen (1)
(1)Finnish Meteorological Institute, Erik Palménin aukio 1, FI-00101 Helsinki, Finland; (2) Helsinki Region Environmental
Services Authority (HSY), Opastinsilta 6 A, 00520 Helsinki, Finland; (3) University of Helsinki, FI-00014 Helsinki,
Finland.(4) Netherlands Applied Research Organization, Princetonlaan 6, 3584 CB Utrecht, The Netherlands.
Presenting author, email: mia.aarnio@fmi.fi
Summary
We have evaluated a refined urban scale modeling system including the road dust suspension model FORE, the road network
dispersion model CAR-FMI and the chemical transport model LOTOS-EUROS, against PM2.5 and PM10 measurement data
from the Helsinki Metropolitan Area (HMA) from the years 2008 and 2010. We have taken into account the long-range
transport and urban vehicular sources, including separately exhaust emissions and suspended road dust. Source contributions
of these source categories have also been evaluated for 2008. Street and urban increments were also evaluated, based on both
measurements and modelling. We have also tentatively modelled total particle number concentration (PNC) for the HMA,
assuming for simplicity it to be an inert species, and compared the results with the measurements, which were available only
at one location.
Introduction
Earlier work by Kauhaniemi et al. (2011) has reported on the development and evaluation of road dust suspension model
included in the street canyon model OSPM for PM10 in a street canyon. In this study, we have modelled PM2.5 and PM10,
including also road dust suspension modelling for the first time for the whole metropolitan area.
Methodology and results
Traffic volumes and average travel speeds were estimated using the EMME/2 Traffic Assignment model. Cold start and cold
driving emissions were included based on laboratory measurements for PM. Emission factors of PM for suspension of road
dust were modelled using the ‘Forecasting of Road Suspension Emission’ model (FORE)(Kauhaniemi et al., 2011). For the
PNC calculations for 2008, we have used the exhaust emission factors provided by Denby et al. within the TRANSPHORM
project. The dispersion modeling of these emissions was done with the CAR-FMI model.
The regional background PM concentrations were estimated by LOTOS-EUROS model for 2008, and with Luukki regional
background measurement site measured values for 2010, but regional background estimate for PNC was not available.
Hourly measurement data from the Helsinki Region Environmental Services Authority (HSY) was used for the evaluation of
the mass-based PM fractions, and integrated number concentration from DMPS data from the University of Helsinki SMEAR
III site was used for the PNC comparison. For instance, for 2008, the IA for the comparison of PM2.5 was about 0.72 at all 3
stations regarded, while FB was between -0.16 and -0.22. The modelled source contributions of LRT for PM2.5 were between
99.84% (Luukki) and 83% (Mannerheimintie), while for PM10 the corresponding estimates were between 99.5% and 66%.
Conclusions
Underprediction of mass-based PM at all sites is mostly explained by the underestimation of regional background PM
concentrations by the LOTOS-EUROS model. We did not include the contributions from domestic wood combustion,
shipping or stationary sources; however, these are known to be lower than those for LRT and vehicular traffic. PM2.5 was
estimated better than PM10 by our modeling system, probably due to a higher fraction of PM2.5 being from LRT and also
caused by uncertainties in determining suspension emissions for PM10. As expected, the use of observed data from a regional
background measurement site significantly improves the predictions of PM2.5. The modelled PNC’s from local sources were
lower than measured concentrations; it was not possible to make quantitative comparisons due to lack of regional
background concentration data.
Acknowledgements
This study has been a part of the EU-funded research project TRANSPHORM.
References
Kauhaniemi, M., Kukkonen, J. Härkönen J., Nikmo J., Kangas L., Omstedt G., Ketzel M., Kousa A., Haakana M., Karppinen
A., 2011. Evaluation of a road dust suspension model for predicting the concentrations of PM10 in a street canyon. Atmos.
Environ., 45, 3646-3654.
167
EMISSIONS FROM THE PORT OF RIJEKA (CROATIA) AND THEIR IMPACT ON AIR QUALITY
A. Alebic-Juretic (1), A. van Hyfte (2), K. Devoldere (2), I. Hladki (3) and V. Jelavic (3)
(1)Teaching Institute of Public Health/ School of Medicine, University of Rijeka, 51000 Rijeka, (2) ARCADIS Belgium
nv/sa, B-9000 Gent, Belgium; (3) EKONERG, HR-10000 Zagreb, Croatia
Presenting author email: ana.alebic@zzjzpgz.hr
Summary
The first emission inventory (with adequate measures for further reduction) within the port area and its impact on air quality
is done for the year 2008. The emission comprised those from vessels, cargo handling equipment (CHE), truck and trains at
four different locations: Rijeka, Susak and Omisalj (island of Krk), as well as dry bulk handling in the Bakar area. The total
emission from the port activity was estimated to 849 t y-1 of NOx, 424 t y-1 of SO2 and 117 t y-1 of PM10. Application of
ISCST3 dispersion model indicated the affected areas in the Rijeka Bay during two dominant wind events: bora and sirocco.
The highest impact of port on air quality is found with ship hotelling mode affecting two monitoring stations just opposing
the port area, particularly during south winds (sirocco). Though, impact of port emissions to urban air quality is minor
relative to industrial sources (SO2) and traffic (NOx).
Introduction
Due to second cycle of industrialization during late sixties and seventies (new petroleum refinery facilities, oil fired power
plant, coke plant), the city of Rijeka became one of the most polluted cities in Croatia during the eighties. In order to reduce
the air pollution, four emission inventories were done in the last 25 years (Alebic, 2008), but none of these took into account
emissions from the port activities. The first emission inventory (with adequate measures for further reduction) within the port
area and its impact on urban air quality was estimated for the year 2008.
Methodology and Results
The emission comprised those from vessels, cargo handling equipment (CHE), truck and trains at three different locations:
Rijeka, Susak and Omisalj (island of Krk), as well as dry bulk handling in the Bakar area (Figure 1)
20
15
10
5
SW
SSE
Bora
SW
SSE
Bora
SW
SSE
Bora
SW
SSE
0
Bora
NO2 concentration (ug m‐3) 25
Rijeka‐1 Rijeka‐2 Kresimirova Trogirska Figure 1: The Rijeka Bay area with Rijeka/Sušak terminals,
Omišalj, a petroleum port and Bakar with dry dust handling.
cruising
maneuvering
hotelling
on anchor
Figure 2: Contribution of different port activities to ground
level NO2 concentrations at urban monitoring sites
The study area for emission calculation comprised everything north from the island of Cres (Figure 1) on the water side, and
everything in-between the water and the terminal gates on the landward side. The emissions for the port maritime traffic were
calculated according to ENTEC study (2007) and Rijeka Port Authorities register on ships calling the port, taking into
account ships’ technical characteristics and sailing mode within the port boundaries (cruise, reduced speed, manoeuvring and
hotelling). Emission from land based sources comprised mobile sources from CHE and port related traffic (rail and road
transport) as well as diffuse source due to dry bulk handling. In addition, the emission inventory was updated, and impact of
port in relation to overall emission to air quality in the Rijeka area was estimated with ISCST3 dispersion model.
Conclusions
The total emission from the port activity was estimated to 849 t y-1 for NOx, 424 t y-1 of SO2 and 117 t y-1 of PM10, , i.e. 14.9,
2.0 and 8.0 % relative to total emissions of these pollutants. The major impact on air quality is due to SO2 and NO2 (Figure 2)
at two closest monitoring sites. Though, impact of port emissions to air quality was minor relative to industrial sources (SO2)
and traffic (NOx), but can be rose according to planned expansion of cargo handling.
References
Alebic-Juretic A., 2008: Airborne Ammonia and Ammonium within the Northern Adriatic Area, Croatia, Environ Pollut, 154 (3), 439-447
ENTEC UK Limited, 2007: Ship emission Inventory- Mediterranean Sea, Final report to Concawe, April 2007.
168
REFINEMENT AND EVALUATION OF A STATISTICAL APPROACH FOR DETERMINING
CONCENTRATION INCREMENTS IN URBAN AREAS
N. Moussiopoulos (1), S. Torras Ortiz (2), I. Douros (1), E. Chourdakis (1), R. Friedrich (2)
(1) Laboratory of Heat Transfer and Environmental Engineering, Aristotle University, Greece – University Campus, P.O.
Box 483, 54124 Thessaloniki; (2) Institute of Energy Economics and the Rational Use of Energy (IER),
University of Stuttgart, Heßbrühlstr. 49a, 70565 Stuttgart, Germany
Presenting author email: moussio@eng.auth.gr
Summary
In order to have a better insight into the complicated and multivariate problem of the contribution of local emissions to the
urban pollution levels, the use of computational methods is essential. The Urban Increment (UI) method is a computational
tool for the assessment of the pollutant concentration increment caused by traffic, as well as other local sources. The method
operates by establishing a functional relationship between the concentration increment and the local meteorological situation,
city morphology, urban emissions and background concentrations (Moussiopoulos et al., 2011; Torras Ortiz and Friedrich,
2013). The method has already been tested by taking into account atmospheric stability and in the frame of this work, it is
evaluated by utilising alternative meteorological variables such as the mixing height and precipitation.
Introduction
The statistical method presented here aims at the determination of an urban concentration increment on top of the regional
background. This is especially relevant for the purposes of air pollution management and health impact assessment of various
pollutants. However, it is here demonstrated specifically for PM10 and NO2. The presented approach attempts to define a
functional relationship on the basis of measured increments at a number of sample locations. This functional relationship is
then applied and tested either to different urban areas or for different time periods in the same urban area. Special care is
taken during the selection of sampling locations in order to ensure geographical representativeness and adequate
measurement data availability.
Methodology and Results
The overall procedure for determining the urban increment can be described as a sequence of three main processing stages,
namely spatial sampling, multiple regression analysis and generalisation of the method. More specifically, in the stage of the
spatial sampling a selection of representative rural-urban measurement station pairs takes place in representative urban areas,
while in the stage of multiple regression analysis a functional relationship between the urban concentrations and the
meteorological, morphological and emission parameters is calculated (calibration). Finally, in the generalisation stage the
estimation of urban increments for the areas or years of interest is carried out. In the frame of this work, enhancements in the
main computational procedures are introduced and validated. In this direction, modelled estimates for two additional
meteorological variables, namely mixing height and precipitation, were introduced in order to examine the possibility of
replacing the atmospheric stability classification in the application of the method, aiming at a more robust and scientifically
sound approach, accounting for the atmospheric mixing and its effects on pollution concentrations. This new implementation
of the method is validated and found to outperform earlier versions of the method which incorporated a classification of the
atmospheric stability. On the other hand, precipitation was found to have modest correlation with the urban concentration
increment and was thus finally not incorporated in the method.
Conclusions
An urban increment was determined based on a functional relationship scheme which allows for a correction of regional
background concentrations inside areas with significant urban density by establishing an operational correlation between the
observed concentration increment and the local meteorological parameters, the city characteristics, the urban emissions and
background concentrations. The introduction of the mixing height as a variable that accounts for the development of the
boundary layer was found to improve upon the previous implementations of the method.
References
Moussiopoulos N., Douros J., Tsegas G., Chourdakis E. and Ortiz S.T., 2011. An approach for determining urban
concentration increments. 14th Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory
Purposes – 2-6 October 2011, Kos, Greece
Torras Ortiz S. and Friedrich R., 2013. A modelling approach for estimating background pollutant concentrations in urban
areas, Atmospheric Pollution Research 4, 147-156
169
MONITORING OF AIR POLLUTION BY TRANSPORT RELATED NITROGEN OXIDES ON ROADS AND
HIGHWAYS OF ST. PETERSBURG
O. V. Lozhkina, V. S. Marchenko, V. N. Lozhkin
St. Petersburg University of State Fire Service of EMERCOM of Russia, 196105, Moskovsky 149, St. Petersburg, Russia
Presenting author email: olojkina@yandex.ru
Summary
The aims of the present study were: 1) to investigate NOX emissions from passenger cars depending on speed (from 0 to 120
km/h), emission class (Euro 0 - Euro 5), engine type (gasoline, diesel); 2) to determine NOX emission factors for different
types of vehicles in dependence on the speed; 3) to evaluate the level of air pollution by exhaust NOX near main roads and
highways in St. Petersburg by means of an appropriate calculating methodology with "real life" NOX emission factors. The
study shows that high NOX emissions relate to old Russian cars, Euro 1 - Euro 2 Russian and foreign cars and to Euro 2- Euro
4 diesel cars. The estimation of NO2 level near main roads of St. Petersburg revels that there are still short-term periods when
the concentration of NO2 in the air surpasses acceptable limit at 2-10 times. The propriety of the results is proven by the data
of road-side air quality monitoring. The study is useful for the development of engine technologies, for the optimization of
urban planning and for the management of air quality.
Introduction
The problem of excess pollution of the air by transport related nitrogen oxides is still significant for St. Petersburg. The
analysis of statistics on vehicle fleet structure showed that: 1) the number of vehicles in St. Petersburg has reached 1,8 mln.
units by 2013 mostly due to the growing of light vehicle fleet (about 90% of the total fleet number) 2) the fleet of passenger
cars has been renovated over the last decade, the share of cars corresponding to Euro 3 - Euro 5 standards has risen to 41 %
by 2013; 3) the structures of HDV and buses fleet have not undergone a significant change in 2003-2013. The estimation of
"real life" NOX emissions from passenger cars (which fleet structure has been considerably changed in the last decade) in real
traffic was very important for the correction of NOX emission factors and for the assessment of air pollution by exhaust NOX
near roads and highways in St. Petersburg by means of an appropriate calculating methodology.
Methodology and Results
Ten gasoline and diesel powered passenger vehicles corresponding to
Euro 0 - Euro 5 emission classes were engaged in the on-board
monitoring of NOX exhaust emissions in real traffic. The investigations
were carried out on urban roads to get emission data at low speed (0-60
km/h) and on St. Petersburg Ring Road (SPbRR) to receive emission
data at high speed (60-120 km/h). The concentration of NOX in exhaust
emissions was measured using Testo-300 portative gas analyser (Testo,
Germany).
The calculating assessment of NOX concentrations near main urban
streets and highway was done using Methodology for the definition of
emissions of harmful substances related to traffic flows on roads and
streets of St. Petersburg (Committee on Environment Management,
Environmental Protection and Ecological Safety of the Government of St.
Petersburg, Russia, 2010) & software ECOLOG-3 (Integral, Russia) using
"real life" NOX exhaust emission factors for passenger cars.
It was established that the highest level of NOX emission was inherent
to old national gasoline cars (> 10 years) without catalytic converter,
the emissions of NOX from Euro 1 and Euro 2 gasoline cars changed
Fig. 1. Map of air pollution of the areas
within 0,15-0,9 g/km. The lowest emissions of NOX (0,003 to 0,08 g/km)
near SPbRR by exhaust NО2 at adverse
were observed for the Euro 3 - Euro 5 gasoline vehicles equipped with
traffic and weather conditions
three-component catalytic convertor. Diesel vehicles satisfying Euro 3
and Euro 4 emission standards demonstrated 3-5 times higher emissions of NOX than gasoline cars of the same type and
emission class. The minimum emissions of NOX were observed at uniform movement of the cars without stops and
accelerations at speed ranging from 40 to 90 km/h independentely on vehicle type, age and emission class.
The received NOX emission factors were used for the evaluation of NOX exhaust emissions and for the determination of NOX
level near main roads and highway (St.PbRR) by means of the Methodology and software mentioned above.
It was determined that even HDV-free large streets (Nevsky and Moskovsky prospects) are sometimes exposed to the
enhanced levels of NО2 exceeding national health-based ambient standards by 2-5 times at adverse traffic and weather
conditions. The areas near St. Petersburg Ring Road is exposed to 5-10 multiple excess of limit value of NО2 in single cases
(Fig. 1). The obtained results were in good correlation with the data of road-side monitoring of air quality in St. Petersburg.
Conclusions
The study of NOX emissions from vehicles in real traffic under different weather conditions as well as the estimation of links
between NOX exhaust emissions and the level of NO2 on roads and near roads will contribute to the development of engine
technologies, to the optimization of urban planning and to the improvement of air quality management.
170
ASSESSING THE HEALTH BENEFITS OF DECREASED POPULATION EXPOSURES VERSUS DISBENEFITS
OF INCREASED DRIVER EXPOSURES IN AN 18 KM LONG HIGH-WAY ROAD TUNNEL BY-PASS IN
STOCKHOLM
H. Orru (1, 2), B. Lövenheim (3), C. Johansson (3, 4), B. Forsberg (1)
(1) Department of Public Health and Clinical Medicine, Umea University, Umea, SE-901 87, Sweden; (2) Department of
Public Health, University of Tartu, Tartu, 50411, Estonia; (3) Environment and Health Administration, Stockholm, SE-104
20, Sweden; (4) Department of Applied Environmental Science, Stockholm University, Stockholm, SE-106 91, Sweden
Presenting author email: hans.orru@ut.ee
Summary
To meet increased traffic in Stockholm, a 21 km long by-pass (18 km in a tunnel) is planned. The by-pass is expected to
reduce traffic emissions in central Stockholm but at the same time tunnel users could be exposed to high concentrations of
vehicle exhaust and road dust. The main objective of this study is to estimate the expected health benefits for the general
population associated with improved ambient air quality and the expected adverse effects for tunnel users from additional
exposure. Health risks were calculated based on health impact assessment principles using established methodsand AirQ
software. It appeared that the calculations were highly sensitive to the assumptions regarding the tunnel exposure, thus the
health impact can be beneficial or adverse.
Introduction
The Stockholm bypass – Förbifart Stockholm – will be a new motorway linking southern and northern Stockholm, which is
divided by water. This bypass should meet the growing transport needs due to the increased population in the region. More
than 18 km of the total of 21 km of the bypass are going to be road tunnels. By 2035, it is estimated that Förbifart Stockholm
will be used by approximately 140,000 vehicles per day. The by-pass is expected to reduce traffic emissions in central
Stockholm but at the same time tunnel users could be exposed to high concentrations of vehicle exhaust.
Methodology
For the exposure reduction, the change in annual ambient NOX and PM10 levels were modelled using 100x100 m grids and
the population (1 628 528 inhabitants) average exposure was calculated for Greater Stockholm area. The tunnel exposure was
estimated based on annual average NOX and PM10 levels, time spent in tunnel and number of persons using the tunnel. Health
risks were calculated based on health impact assessment principles and AirQ software. In calculations the following E-R
coefficients for non-external mortality were used: 8% per 10 μgm-3 increase of NOX (Nafstad et al., 2004) and 1.68% per 10
μgm-3 increase of coarse (non-exhaust) PM10 (Meister et al., 2012).
Results
It appeared that for the general population there would be annually 23.0 (95% CI 17.2–31.3) premature death less; mainly
from traffic exhaust (indicated by NOX) and somewhat from coarse particles (indicated by PM10), contributing 22.5 and 0.5
fewer deaths, respectively. At the same time, tunnel users (daily 55 219 cars each way) will be exposed to NOX
concentrations up to 1957 μgm-3 during rush-hours. Passing the whole tunnel daily would correspond to an additional annual
NOX exposure of 9.6 μgm-3 and PM10 exposure of 4.1 μgm-3. Assuming there would be 1.3 persons in car from the age group
30–74, this exposure would result in 22.9 (95% CI 17.2–31.3) preterm deaths. If there would be more persons per car or older
people travelling, the estimate becomes bigger.
Conclusions
The analysis showed that depending on the in-vehicle exposure of tunnel users, age (and sensitivity) of tunnel users and
number of persons in the vehicle, the total impact on health of the changes in air pollution exposure driven by the bypass
project can be beneficial or adverse. The calculations were highly sensitive to assumptions that have to be included. First of
all, the higher the concentrations of harmful pollutants in the tunnel and vehicles are, the bigger the increase in risk will be.
Moreover, the longer the time spent in the tunnel (especially during more congest situations during rush hours), the higher
dose will become. Second, if we expect older more vulnerable people using the tunnel users, this would increase the mortality
risk. As older people probably will work and commute in the future, this exposure of elderly will likely increase. Third, the
more persons in the car, the larger number of people will be exposed and the larger the impact will become.
Acknowledgement
This work was supported by a grant from The Swedish Transport Administration.
References
Nafstad P., Haheim L.L., Wisloff T., Gram F., Oftedal B., Holme I., Hjermann I., Leren P., 2004. Urban air pollution and
mortality in a cohort of Norwegian men. Environmental Health Perspectives 112, 610-615.
Meister K., Johansson C., Forsberg B., 2012. Estimated Short-Term Effects of Coarse Particles on Daily Mortality in
Stockholm, Sweden. Environmental Health Perspectives 120, 431-436.
171
INTERCOMPARISON OF URBAN SCALE AIR QUALITY MODELS
S. Jonkers (1), E .W. Meijer (1), P. Y. J. Zandveld (1), B. R. Denby (2), I. Douros, (3), N. Moussiopoulos (3), V. Singh (4), R.
S. Sokhi (4), A. Karppinen (5), L. Kangas (5) and J. Kukkonen (5)
(1) Netherlands Organisation for Applied Scientific Research (TNO), Utrecht, Netherlands, (2) Norwegian Institute for Air
Research (NILU), Kjeller, Norway (3) Aristotle University of Thessaloniki (AUTh), Thessaloniki, Greece, (4) University of
Hertfordshire, Hatfield, Hertfordshire, United Kingdom (UH); (5) Finnish Meteorological Institute (FMI), Helsinki, Finland
Presenting author email: sander.jonkers@tno.nl
Summary
This study compares the performance of five urban scale air quality models with diverse approaches. The models involved
were Urbis Real-Time (TNO), Episode (NILU), MEMO/MIMO (AUTh), OSCAR (UH), and UDMS (FMI). The comparison
is based on modelled and observed concentrations in the Rijnmond area, an urban-industrial region in the Netherlands. The
comparison focusses on near-road increments of species nitrogen oxide and elemental carbon. Modelled concentrations are
compared to observations. Analysis shows that 4 out of 5 models resolve the near-road concentration increments reasonably
well (R2 over 0.5 and NRMS of 0.3 or lower). Furthermore, 2 out of 5 models follow the observed concentration patterns
during low wind speed episodes rather well. One out of 5 models performs well in resolving both spatial and temporal
variances.
Introduction
Urban air pollution is identified by the United Nations’ World Health Organization as a ‘key priority environment and health
risk’ (http://www.who.int/heli/risks/en/). Epidemiological studies such as Hoek et al., 2002 have demonstrated the adverse
health effects of traffic emissions of particulate matter in particular. Uncertainty assessment in air quality studies is of high
importance. This study compares 5 urban scale dispersion models and assesses their uncertainty, when compared to
observations. These models are all operated by participants in the TRANSPHORM project.
Methodology and Results
The models involved in this study are Urbis Real-Time (TNO), Episode (NILU), MEMO/MIMO (AUTh), OSCAR (UH), and
UDMS (FMI). The models cover a wide range of approaches and complexity. The same set of input values was available for
all models; however, the models use these input data in various ways. For instance, some dispersion models are used in
connection with meteorological pre-processors that use data from sounding stations, while some other models use simpler
treatments for meteorology. The regional background concentrations were calculated with the regional scale model LotosEuros. The area of interest is the Rijnmond area, an urban-industrial region of about 25x15 km, in the west of the
Netherlands. We strongly focus on the local increment of nitrogen oxide (NOx) and elemental carbon (EC) due to road
traffic. Figure 1 shows modeled and observed NOx concentrations at 8 locations in the Rijnmond area.
Figure 1: Modelled and observed NOx concentration at 8 - equal colour indicated -monitoring locations (motorway, street or background).
Results from MEMO/MIMO will be added later on.
Conclusions
From the models among the ensemble, 4 out of 5 resolve the near-road concentration increments reasonably well (R2 over
0.5 and NRMS of 0.3 or lower). Another experiment within this study shows 2 out of 5 models follow the observed
concentration patterns during low wind speed episodes rather well. Other models are rather insensitive to low wind
conditions. This is still commonplace in most dispersion models and an interesting issue for future work as concentrations
during these episodes can exceed the tenfold of the long term average concentrations.
Acknowledgement
This work was performed within the framework of the EU FP7 project TRANSPHORM (ENV.2009.1.2.2.1 e Transport
related air pollution and health impacts).
References
Hoek G., Brunekreef B., Goldbohm S., Fischer P. And van den Brandt P.A.,2002. Association
between
indicators of traffic-related air pollution in the Netherlands: a cohort study. Lancet 360, 1203-1209.
172
mortality
and
CONTRIBUTION OF EMISSION SOURCES TO CONCENTRATIONS OF FINE PARTICULATE MATTER
(PM2.5) IN EUROPE
X. Francis (1), R. S. Sokhi (1), C. Chemel (1) H. Denier van der Gon (2)
(1) Centre for Atmospheric and Instrumentation Research (CAIR), University of Hertfordshire, Hatfield, Hertfordshire,
AL10 9AB, United Kingdom, (2) TNO, dept. Climate, Air and Sustainability, Princetonlaan 6, 3584 CB Utrecht,
The Netherlands
Presenting author email: x.francis@herts.ac.uk
Summary
This study aims to assess the relative importance of specific emission sources and their impact on surface concentrations of
PM2.5 by “zeroing” out emissions sources. The regional chemical transport model, WRF-CMAQ modelling system has been
employed to study the impact of different sources of emission on European air quality. The model simulations conducted
including emissions from all the sources as well as excluding specific sources. The spatial distribution of monthly mean
percentage contribution show that emissions from industrial as well as non-industrial combustions contribute more to
concentration of PM2.5 over Europe as compared to other emission sources. The calculation of monthly-mean domain wide
contribution to concentrations of PM2.5 shows that transport sector contributes ~5 % in January and ~11 % in July. Non-road
transport sector contribute more to concentration of PM2.5 as compared to the road-transport sector in July.
Introduction
In recent times considerable attention has been paid on atmospheric particulate matter (PM) because of its adverse effects on
human health, environment, and its influence on climate change. Therefore it is essential to understand the main emission
sources that contribute PM2.5 concentrations over Europe. The approaches widely used in the source apportionment studies
are based on the receptor modelling and sensitivities of emissions sources in dispersion models. In this study we have applied
Brute Force Method (BFM) in WRF-CMAQ modelling system to determine the impacts of different emission sources in
Europe.
percentage contribution (%)
Methodology and Results
The Community Multi-scale Air Quality (CMAQ)
35
January
July
modelling system version 4.7.1 was used for this
30
study. CMAQ was applied on horizontal grid
25
dimension with 18 km grid resolution. The chemical
boundary conditions for CMAQ simulation were
20
derived from the EMAC and MATCH models. The
15
meteorological inputs were generated from the
10
Weather Research and Forecast (WRF) model version
5
3.2.1. The hourly emission data of primary pollutants
0
used in CMAQ modelling system were prepared with
Sparse Matrix Operator Kernel Emissions system
(SMOKE) version 2.6. As a part of EU FP7 Transport
related Air Pollution and Health impacts - Integrated
Methodologies for Assessing Particulate Matter
(TRANSPHORM, http://www.transphorm.eu), the
annual total anthropogenic gridded emission inventory
for Europe was provided by Netherlands organisation
for applied scientific research (TNO). In total, there
Fig.1 Domain-wide monthly-mean percentage contributions to the
were 19 CMAQ model simulations were conducted for
concentrations of PM
January and July 2005, which includes simulations
2.5
with all emissions, without industrial combustion, nonindustrial combustion, industrial process, fossil fuel and geo-thermal, road transport, non-road transport, waste treatment and
disposal, agriculture, and biomass burning emissions.
biomass burning
agriculture process
waste treatment and disposal
non‐road transport
road transport
Fossil fuel and geothermal
Industrial process
Non‐Industrial Combustion
Industrial Combustion
Conclusions
This study found that industrial combustion and non-industrial combustions are the two important sources in January with
contributions of 20 % and 19 %, respectively to the surface monthly-mean concentration of PM2.5 over Europe. Industrial
combustion is the most important source in July, with a contribution of 31% to surface monthly-mean PM2.5. Biomass
burning and agriculture process are the two next largest sources in July with contributions of 14 % and 8 %, respectively.
Due to increase in number of international shipping and other related activities in summer, non-road transport sector
contribute more to concentration of PM2.5 in July than in January. Generally, source apportionment studies help in defining
the control strategies to reduce PM concentrations and this study will support to identify the main emission sources that
contribute to concentrations of PM in Europe.
Acknowledgement
This work was supported by EU FP7-Transport related Air Pollution and Health impacts - Integrated Methodologies for
Assessing Particulate Matter (TRANSPHORM, http://www.transphorm.eu).
173
URBAN AND TRAFFIC CONTRIBUTIONS TO PM2.5 IN LONDON
V. Singh (1), R. S. Sokhi (1) and J. Kukkonen (2)
(1) CAIR, University of Hertfordshire College Lane, Hatfield, AL10 9AB, UK; (2) Air Quality Research, Finnish
Meteorological Institute, Sahaajankatu 20 E, Helsinki, Finland
Presenting author email: v.singh3@herts.ac.uk
Summary
This paper reports on the analysis of contributions from urban and road traffic sources to PM2.5 concentrations within London
for 2008 with the OSCAR Air Quality Assessment System. Modelling analysis shows that the urban traffic contributes
approximately 1 µg/m3 of PM2.5 to the urban background across London, however its distribution is spatially heterogeneous.
The urban increment was evaluated to be varying from 20% at suburban environments to 50% near busy roads where the
total concentrations can be almost three times the regional background. The total urban increment close to busy roads was
around 7-8 µg/m3 in which the estimated traffic contribution is more than 2 µg/m3.
Introduction
Road transport is one of the most important sources of particulate matter (PM). Numerous studies have shown that the traffic
emissions are particularly associated with short to long-term health effects. This is especially of concern in urban areas,
where large numbers of people spend significant amount of time at the immediate vicinity of the roads. Moreover the spatial
extent of exposure to certain specific components and size fraction of PM are different. The aim of this paper is to examine
the spatial extent of the PM2.5 concentration across London in 2008 and focuses on the importance of the PM2.5 originating
from urban road transport sources.
Methodology and results
OSCAR Air Quality Assessment System (Singh et al., 2013,
Sokhi et al. 2008) has been used to calculate the concentrations
originating from traffic emissions in London. The study area
covers greater London including the M25 motorway (Figure 1).
The dispersion equations are based on the Gaussian finite line
source model and include dry deposition. The dispersion
parameters are modelled as function of the Obukhov length, the
friction velocity and the mixing height. Traffic emissions are
calculated for over 63000 road links in London. The
concentrations originating from traffic have been modelled at
higher resolution receptor points near roads, then have been
added to the Defra background concentration (Grice S et al.,
2009) to obtain the total concentration. We estimate the spatial
distribution of the contribution of traffic to total PM2.5
concentrations, and compare it to contributions from other urban
sources and regional backgrounds derived from measurement
stations. Figure 1 shows the spatial distribution of the calculated
traffic increment for PM2.5 in London. Figure 2 shows the
predicted median urban traffic increment and median urban
increment from all other urban sources except for urban traffic,
and regional background at different categories of sites.
Figure 1. Spatial map of the urban traffic percentage increment
of PM2.5 in London.
Conclusion
This study shows that the urban increment including the traffic
contribution in London is very significant and spatially
heterogeneous across London. The total concentrations can be up
to three times the regional background near urban major roads.
The increment is higher near the busy roads, and lower at urban
Figure 2. Urban and traffic increment at different locations.
background and suburban locations. The information on highly
heterogeneous distribution of PM2.5 can be used to quantify
health impacts resulting from specific sources of PM2.5 such as traffic emissions to aid city and national decision makers
when formulating pollution control strategies.
Acknowledgement
This work was supported by 7th Framework Programme project TRANSPHORM (Grant agreement: 243406) and the APTA
project funded by the Academy of Finland.
References
Grice S. et al 2009. UK air quality modelling for annual reporting 2007 on ambient air quality assessment under Council
Directives 96/62/EC, 1999/30/EC and 2000/69/EC.
Sokhi et al. 2008. An integrated multi-model approach for air quality assessment: Development and evaluation of the
OSCAR Air Quality Assessment System. Environ. Model. Softw. 23, 3 (March 2008), 268-281.
DOI=10.1016/j.envsoft.2007.03.006.
Singh V., Sokhi R.S. and Kukkonen J., 2013, PM2.5 concentrations in London for 2008 - A modelling analysis of
contributions from road traffic. Journal of air waste management association. Accepted
174
ROADSIDE AND URBAN BACKGROUND MEASUREMENTS OF ULTRAFINE PARTICLES
IN THESSALONIKI, GREECE – 7 YEARS LATER
Ι. Vouitsis, S. Amanatidis, L. Ntziachristos and Z. Samaras
Laboratory of Applied Thermodynamics (LAT), Aristotle University of Thessaloniki, GR 541 24, Thessaloniki, Greece
Presenting author email: zisis@auth.gr
Summary
The goal of this study is to provide detailed information on the physical characteristics of airborne material in the atmosphere
of Thessaloniki. To this aim, measurements were conducted at a busy roadside and at a nearby urban background site of the
city. Particle characteristics measured included mass, number and active surface concentration as well as particle volatility
and size distribution. Good correlation was observed between airborne particle concentration particles characteristics and
change in traffic volume and domestic heating. Comparison with measurements conducted 7 years ago showed, in most
cases, a significant reduction in particle pollution which is attributed to the reduction of car usage by Greeks consumers.
Introduction
Several studies suggest that Thessaloniki is one of the most polluted cities within Europe, especially with respect to airborne
particles. The situation is expected to differentiate due to several reasons, such as the construction of metro and the financial
crisis which forced Greek consumers to seek out alternative ways of heating their homes (demand for wood and pellets has
soared) and to reduce car usage. Considering the above, several particle characteristics were measured at two different sites
and the results were compared with those of similar measurements conducted 7 years ago (Vouitsis et al, 2008).
Methodology and Results
Measurements were conducted at two different sites (one in the centre of the citytraffic affected (site 1) and one in the urban background-not traffic affected (site 2))
during two different periods: February 2013 (winter period) and June 2013 (summer
period). Instrumentation used included: a Dekati Mass Monitor for airborne PM2.5
mass concentration, a CPC for number concentration, an SMPS for size distributions,
a diffusion charger for active surface concentration and a thermodenuder for particle
volatility (Fig. 1). Working days average mass concentration at site 1 during the
winter period was 49 μg m-3 (SD=15), about 38% lower than 2006, while weekends
value was 70 μg m-3 (SD=26), about 10% higher than 2006. Corresponding values for
the summer period were 24 μg m-3 (SD=8) in working days and 22 μg m-3 (SD=6) in
weekends. Working days average mass concentration at site 2 during the winter
period was 13 μg m-3 (SD=6), 35% lower than 2006, while weekend value was 21 μg
m-3 (SD=7), 35% lower than 2006. Corresponding values for the summer period were
10 μg m-3 (SD=3) in working days and 8 μg m-3 (SD=3) in weekends. Working days
average number concentration at site 1 during the winter period was 32035 cm-3
(SD=6780), about 57% lower than 2006, while weekends value was 27600 cm-3
(SD=8860), about 60% lower than 2006. Corresponding values for the summer period
were 16200 cm-3 (SD=4640), working days and 17500 cm-3 (SD=3780), weekends.
Working days average number concentration at site 2 during the winter period was
14450 cm-3 (SD=6045), 6% higher than 2006, while weekend value was 19300 cm-3
(SD=8950), 6% lower than 2006. The values for the summer period were 8020 cm-3
(SD=2435), working days, and 7600 cm-3 (SD=2170), weekends. During the winter
period both particle mass and number concentrations were significantly increased
during the evening at both sites, which could be attributed to wood-based domestic
heating. Active surface concentrations showed a very good correlation with mass
concentrations. Particle volatility fluctuated during the day and increased with traffic
volume. It was higher during winter working days and lower during summer
weekends. The size distribution of particles exhibited a pattern which depended on
the time of the weekday and differed over weekends. This was observed both at the
busy roadside and at the background site.
Fig.1 Measurement set-up
Fig.2 Average size distributions
monitored in two sites during winter
and summer period (working days)
Conclusions
As traffic volume decreases in Greece due to financial crisis, particle pollution reduces correspondingly. Domestic heating
seems to contribute more to airborne particles in comparison with previous years, probably due to increased use of wood and
pellets.
Acknowledgement
This research was co-financed by the European Social Fund and Greek national funds - Program: THALES.
References
Vouitsis, I., Ntziachristos, L., Samaras, Ζ. Roadside and urban background measurements of ultrafine particles in
Thessaloniki. European Aerosol Conference 2008, Thessaloniki, Greece, 25-29 August 2008.
175
USE OF REMOTE
SENSING AND
SATELLITE DATA FOR
AIR QUALITY RESEARCH
176
A REGIONAL SCALE NOX EMISSION INVERSION USING OMI OBSERVATIONS
J. Vira (1), M. Sofiev (1)
(1) Finnish Meteorological Institute
Presenting author email: julius.vira@fmi.fi
Summary
This paper discusses results of an inverse modelling study aiming to estimate European scale NO2 emissions using
satellite observations by the Ozone Monitoring Instrument (OMI). The observations are assimilated into the chemistry
transport model SILAM, and a variational technique is employed to obtain an optimized emission distribution. The
inversion is performed for July 2011 using the 2007 background emission inventory, which allows comparing the
inversion results with the reported emission trends. The results are consistent at several areas, however, some features in
the optimized emissions cannot be explained by the reported changes.
Introduction
The availability of remote sensed observations of atmospheric composition has made satellite-based, top-down emission
estimates technically feasible. Such estimates could supplement the existing emission inventories for sources or areas
where traditional emission inventories are not available. However, assessing the quality of the satellite-based estimates is
not straightforward, since emission fluxes are not observed directly. This work aims to evaluate the capabilities of an
emission inversion scheme for NO2 emission in European scale.
Methodology and Results
This study employs the 3D chemistry-transport model SILAM and the NO2 column observations by the Ozone
Monitoring Instrument (OMI) on board the Aura satellite. The simulated area is shown in Fig 1. The initial (a priori)
pollutant emissions were given by the 2007 TNO-MACC emission inventory. A variant of the 4D-Var data assimilation
method was used in the inversion. The method adjusts the daily emission fluxes iteratively to optimize the agreement
between the observations and their modelled counterparts. The a priori emission inventory is used as an additional
constraint to keep the solution fully determined.
Compared to the observations (Fig. 1, panel a), the a posteriori NO2 columns show clearly improved agreement in many
areas including Britain, northern Spain, and parts of southern Scandinavia. Although the results for a single month cannot
be directly generalized to yearly level, some of the changes are qualitatively consistent with reported emission reductions
(EEA 2013, ~30% for UK, ~25% for Spain) between the inventory base year 2007 and the simulated year 2011. The
inversion results show relatively strong positive NOx emission increments for south-eastern Europe, where the a priori
NO2 columns were significantly underestimated. This is not explainable by changes in the reported emissions but may
indicate a deficiency in the initial estimates or the model itself. In addition to NOx emissions, due to chemical coupling,
the inversion results in adjusted emissions of VOCs, mainly isoprene. This highlights the role of the chemical mechanism
in the inversion process.
Conclusions
The inversion was technically successful, and the refined emission field is consistent with reported emission reductions
especially in Western Europe. In parts of South-Eastern Europe, a low bias in the a priori simulation results in enhanced a
posteriori NOx emissions, which is not attributable to reported changes in yearly emissions.
Acknowledgements
This work has been supported by the projects SAMBA (ESA) and MACC-II (EU). We acknowledge the free use of
tropospheric NO2 column data from the OMI sensor from www.temis.nl.
References
European Environment Agency, 2013. European Union emission inventory report 1990–2011 under the UNECE
Convention on Long-range Transboundary Air Pollution (LRTAP).
a) OMI b) A priori c) A posteriori d) scaling Figure 1. From left: the average observed, a priori and a posteriori NO2 columns (1015 molec/cm-2) for July 2011. Panel
d: the average emission scaling (a posteriori / a priori).
177
AIRBORNE MAPPING OF NITROGEN DIOXIDE CONCENTRATIONS IN URBAN ENVIRONMENTS
R. J. Leigh (1), J. P. Lawrence (1), J. Vande Hey(1), R. R. Graves (1),and P. S. Monks (2)
(1) Earth Observation Science Group, Department of Physics and Astronomy, University of Leicester, Leicester, LE1
7RH, United Kingdom; (2) Atmospheric Chemistry Group, Department of Chemistry, University of Leicester,
Leicester, LE1 7RH, United Kingdom;
Presenting author email: R.J.Leigh@leicester.ac.uk
Summary
Remote sensing of nitrogen dioxide from space has been widely exploited to explore regional and continental trends and
spatial patterns in urban air quality. This project employed a satellite breadboard demonstrator within a light aircraft to map
nitrogen dioxide concentrations over an urban environment at 20 x 80 m resolution. This fine-scale mapping of NO2
concentrations provides a valuable insight into small-scale variability at street scales, with indications of small-scale
industrial emission sources, traffic emissions, dynamics and chemistry.
Introduction
Remote sensing of NO2 has been previously demonstrated from ground-based DOAS and MAX-DOAS systems, and
employed in a range of satellites starting with GOME in 1995, and continuing through the Sentinel missions. The range of
applications of remotely-sensed NO2 is increasing, with notable milestones including the assessment of regional trends over
China in Richter et al. 2005, and the use of inversion modelling to assess emission inventories by Mijling et al. in 2013. In
this project, an imaging spectrometer was employed from 900 m altitude in a light aircraft, to explore the information content
of relatively high spatial resolution remotely-sensed maps of nitrogen dioxide concentration.
Methodology and Results
The CompAQS instrument is a concentric spectrometer
designed by Dan Lobb of Surrey Satellite Technologies
Ltd, and described in Whyte et al. 2009. For these
experiments, CompAQS was configured to image 128
across-track pixels along a 600 m swath, recording
spectra from 420 – 590 nm at 1-2 nm resolution. On
28th February 2013, this instrument was flown in a light
aircraft over the city of Leicester in the United
Kingdom from 12:30 to 14:00 GMT. A flight pattern
was used to produce gridded measurements over the
entire city centre, and some suburban areas. From these
measurements, nitrogen dioxide slant column
concentrations can be derived using the traditional
technique
of
differential
optical
absorption
spectroscopy. A map of retrieved nitrogen dioxide slant
columns is shown in Figure 1. The technique was
Fig 1. Nitrogen Dioxide concentrations mapped over Leicester on 28th
demonstrated to reliably retrieve NO2 concentrations at
Feb 2013.
20 x 80 m resolution, and provide a number of novel
perspectives on urban emission and chemistry.
Significant spatially-constrained (<400m) features were identified around busy transport junctions, car parks, some industrial
locations, and densely vegetated areas. The flight path also retrieved high NO2 concentrations around the regional coal-fired
power station.
Conclusions
Airborne mapping of nitrogen dioxide has not been widely used to address operational and scientific requirements for air
quality measurements. These results provide some direct information on emissions, chemistry and dynamics in the urban
environment, and illustrate the potential use of such data in model assimilation and future air quality services.
Acknowledgement
This work was funded under the UK’s Centre for Earth Observation Instrumentation, and has received significant support
under the Natural Environment Research Council’s Knowledge Exchange scheme. The optical design for the CompAQS
spectrometer was provided by Surrey Satellite Technology Ltd, and flight logistical support was provided by Bluesky
International Ltd.
References
Mijling, B., van der A, R. J., and Zhang, Q.: Regional nitrogen oxides emission trends in East Asia observed from space,
Atmos. Chem. Phys. Discuss., 13, 17519-17544, doi:10.5194/acpd-13-17519-2013, 2013.
Richter, A., Burrows, J. P., Nüß, H., Granier, C, Niemeier, U., Increase in tropospheric nitrogen dioxide over China observed
from space, Nature, 437, 129-132, doi: 10.1038/nature04092, 2005
Whyte, C., R. J. Leigh, D. Lobb, T. Williams, J. J. Remedios, M. Cutter, and P.S. Monks, Assessment of the performance of
a compact concentric spectrometer system for Atmospheric Differential Optical Absorption Spectroscopy, Atmos. Meas.
Tech., 2, 789-800, 2009
178
OBTAINING PM2.5 IN THE STOCKHOLM REGION FROM SPACEBORNE MEASUREMENTS
M. Tesche (1), P. Glantz (1), and C. Johansson (1, 2)
(1) Department of Applied Environmental Science, Stockholm University, Stockholm, Sweden; (2) SLB-Analys,
Environment and Health Administration, Stockholm City, Box 8136, SE-10420 Stockholm, Sweden
Presenting author email: matthias.tesche@itm.su.se
Introduction
The aim of this study is to deduce surface concentrations of PM2.5 for the region of Stockholm from satellite observations of
aerosol optical thickness (AOT). Previous studies showed the potential for using spaceborne AOT observations for air-quality
monitoring (Hoff and Christopher, 2009) – especially for tracking the exceedance of threshold values. It is yet to be explored
if similar methods can also be applied in a rather clean environment. Following Glantz et al. (2009), we intended to obtain an
AOT–PM2.5-relationship representative for the clean conditions that prevail over the region of Stockholm.
Methodology and Results
We use AOT at 555 nm from the MODIS collection 5 Atmosphere and Land product for MODIS-Terra (since 1999) and
MODIS-Aqua (since 2002). AOT is provided with a spatial resolution (pixel size) of 10×10 km2 at ground. MODIS AOTs
were compared to measurements at the AERONET stations Gotland, Gustav Dalen Tower, Palgrunden, and SMHI. MODIS
AOT was found to be within the expected uncertainty of ±0.05±0.05×AOT over land, if median values of the pixels adjacent
to the ground stations were used. Using the mean value of these pixels causes MODIS to underestimate AERONET
measurements by about 20%. It was also found that periods with AOT higher than 0.2 were scarce.
In the next step, spaceborne AOT was related to PM2.5 measurements
at stations in the Stockholm region that are representative for regional
Fig.1: AOT–PM2.5-relationships at different stations
for cases with at least 5 pixels around a site, AOT bins
and urban background conditions: Aspvreten (rural, 70 km south of
of 0.05, and 5-h PM2.5 means around an overpass.
Stockholm), Norr Malma (rural, 65 km north of Stockholm), Lilla
Essingen (kerb site), Torkel Knutssonsgatan (urban background),
Uppsala (kerb side, 65 km north of Stockholm), and Vavihill (rural, 500
km south of Stockholm). AOT–to–PM2.5 relationships were obtained
for cases in which AOT for at least 7 of the 9 pixel adjacent to a ground
site were available. We use the binning approach of Wang and
Christopher (2003) to account for the wide spread in the data of both insitu and MODIS observations. Furthermore, the AOT–to–PM2.5
relationship was obtained by using the median values for bins of 0.05
AOT rather than the mean values, which reduces the impact of extreme
values. Meteorological parameters (i.e., relative humidity, wind speed
and direction) were also measured at the in-situ stations. Additional
AOT–to–PM2.5 relationships were inferred for cases in which these
parameters showed values above and below their respective median
values to investigate effects of meteorological conditions on the median
AOT–to–PM2.5 relationship and to assess the error of the PM2.5
retrieval. Few cases were associated with PM2.5 > 30 µg/m3 or AOT > 0.45.
Summary and Conclusions
The validity of an AOT–to–PM2.5 relationship depends on an assumption of homogeneous aerosol conditions in the
planetary boundary layer and an absence of elevated aerosol layers. Lidar observations at Stockholm and of the CALIPSO
satellite show a small influence of elevated aerosol layers. The relationship between AOT and PM2.5 showed little variation
for the sites in the Stockholm region. Preliminary findings suggest that the obtained AOT–PM2.5 relationship allows us to
reproduce ground observations, in particular of pollution episodes, with an estimated error of ±25-40%.
MODIS collection 5 AOT is provided with a pixel size of 10×10 km2. The upcoming release of collection 6 with a resolution
of 3×3 km2 will be applied to test the obtained AOT–PM2.5 relationship on a higher resolution for a more detailed view on
air quality in the Stockholm region. In selected cases, another aerosol retrieval algorithm (Glantz et al., 2009) could be
applied to MODIS measurements of spectral radiances (1 km2 pixel size) to compile PM2.5 maps with finer spatial resolution. This would enable a more detailed investigation of local sources and the impact of pollution events on surface PM2.5.
Acknowledgement
This investigation was financed by Formas contract 216-2010-910. We thank also like to thank the colleagues at ITM and
SLB for maintaining the in-situ instruments at the stations used in this study.
References
Glantz, P., A. Kokhanovsky, W. von Hoyningen-Huene, and C. Johansson (2009), Estimating PM2.5 over southern Sweden
using space-borne optical measurements, Atmos. Environ. 43, doi:10.1016/j.atmosenv.2009.05.017.
Hoff, R. M. and Christopher, S. A. (2009), Remote sensing of particulate pollution from space: Have we reached the
promised land?, J. Air & Waste Manage. Assoc. 59, doi:10.3155/1047-3289.59.6.645.
Wang, J. and S. A. Christopher (2003), Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass:
Implications for air quality studies, Geophys. Res. Lett. 30, doi:10.1029/2003GL018174.
179
ON POSSIBILITY OF REMOTE-SENSING COMPLIANCE MONITORING OF SHIP-FUEL SULPHUR
CONTENT: A MODELLING STUDY IN GULF OF FINLAND
M. Sofiev (1), M.Prank (1), L.Johansson (1), J.-P.Jalkanen (1), T.Stipa (1)
(1) Finnish Meteorological Institute
Presenting author email: Mikhail.sofiev@fmi.fi
Summary
Stricter regulations are being imposed on sulphur content of ship fuel on Baltic Sea. Within ESA-SAMBA project, a
modelling study was conducted to figure out whether ships violating the regulations could be identified from currently
available satellite observations of SO2 column amounts and, if not, what are the instrument parameters required for such task.
The study concentrated on the relation between the spatial resolution and sensitivity of the instrument used to observe the
SO2 content in plumes coming from ships. The modelling results demonstrated that currently available devices lack both
resolution and sensitivity for the task – by at least an order of magnitude.
Introduction
Presently, the allowed sulphur content in fuel of ships ceiling in Baltic Sea is
1%, down from 2.7% in the past, and is expected to go down to 0.1%.
However, strict regulations only have an effect if a control mechanism exists to
ensure compliance. Monitoring ships in open sea is possible only via remote
sensing, which raises the problem of sufficient instrument resolution and
sensitivity to measure the plumes coming out of individual ships. The
resolution and sensitivity limitations come from partly independent technical
reasons, which sometimes compete. Therefore, within ESA-SAMBA project, a
modelling study was conducted to understand the necessary sensitivity and
resolution for recognising the difference between the low- and high0sulphur
emitting ships.
Methodology and Results
STEAM ship emission model, which processes the
information on actual position of every ship in
Baltic Sea to the emission estimates, was applied to
provide two emission scenarios. The first case is
when all ships follow the regulation of 0.1%
sulphur limit, wherease the second case included
10% of ships using the cheaper fuel with 2.7%
sulphur content. For both scenarios, sulphur
emission in April 2011 were generated. Model
horizontal resolution was 1 km and temporal
resolution 6 minutes; domain covered the Gulf of
Finland. The STEAM data were supplied to
SILAM, which was used to compute the dispersion
and chemistry of the emitted SO2. The key output
quantity included SO2 column amounts – a typical
quantity observed visible from satellites (example
Fig. 1). SILAM was run with the same horizontal
and temporal resolution as STEAM. The SILAM
output was averaged to 2, 4, 8, 16 and 32 km resolutions
and the distributions of the differences in column SO2
between the two scenarios were analysed (Figs 2 and 3).
Conclusions
The results demonstrate that there is no way of detecting
the ships using high-sulphur fuel with current
observational devices. However, a low-orbit satellites
with <1 km pixel size would need to recognise 0.02 DU
to be able to explore the rule-breaking ships.
Acknowledgement
This work was performed within ESA-SAMBA project.
Fig.1 SO2 column amount, baseline
scenario, example 2011.04.21 20:00
Fig.2 Example of SO2 columns, difference between the scenarios,
2011.04.21 20:00
1
0.1
0.01
0.001
1km
2km
0.0001
4km
8km
0.00001
16km
32km
0.000001
0.0000001
0.00000001
0.000000001
0.1
0.05
0.02
0.01
0.005
0.002
0.001
0.0005
0.0002
0.0001
5.00E-05
2.00E-05
1.00E-05
0
-1
Fig.3 Differences between the scenarios - fraction of grid cells with
difference in SO2 column amounts exceeding the given value.
180
BOUNDARY LAYER AEROSOL INVESTIGATION WITH LASER CEILOMETER
C. Münkel (1), K. Schäfer (2), S. Emeis (2) and P. Suppan (2)
(1) Vaisala GmbH, 22607 Hamburg, Germany
(2) Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research,
Department of Atmospheric Environmental Research (IMK-IFU), 82467 Garmisch-Partenkirchen, Germany
Presenting author email: christoph.muenkel@vaisala.com
Summary
Laser ceilometers are backscatter lidars designed for continuous operation in all meteorological situations. One lens design
systems with overlap already in the lowest range gate are a good choice for accurate monitoring of aerosol structures in the
lower boundary layer relevant for air quality applications. This study evaluates backscatter data from ceilometers installed in
environments ranging from arctic sites to megacities, in respect of mixing layer height determination, monitoring of local
particle emissions, and discrimination of stable, convective, and residual layers.
Introduction
The main purpose of eye-safe laser ceilometers is regular reporting of cloud base height, vertical visibility, and cloud cover.
These instruments operate unattended in harsh weather conditions. The application of state-of-the-art electronics increases the
quality of backscatter profiles and thus qualifies modern ceilometers for applications beyond cloud base detection. These
include the automated characterization of the boundary layer structure, determination of the height of the mixing layer, and
monitoring of elevated aerosol layers like dust and volcanic ash clouds.
Methodology and Results
The Vaisala ceilometer CL51 is a one lens system that uses the inner
part of its lens for transmitting and the outer part for receiving light
(see Fig.1). This provides sufficient overlap of the transmitter light
cone and the receiver field-of-view over the whole measuring range
and allows reliable monitoring of near range boundary layer
structures below 200 m not seen by other instrument types (Münkel
et al., 2009). Interpretation of near-range attenuated backscatter
profiles with 10 m height resolution and signal averaging intervals
ranging from 0.5 s to 60 s is done in respect of mixing layer height
determination with an enhanced gradient method (Emeis, Schäfer,
Münkel, 2008, Emeis et al., 2012), monitoring of local particle
emissions, and discrimination of stable, convective and residual
layers with special emphasize on the morning hours (see Fig.2). The
examples presented include a variety of environments ranging from
clear arctic atmospheres to densely populated megacities.
Fig.1 Vaisala ceilometer CL51 and its optical setup
Conclusions
Based on enhanced near range performance, one lens ceilometers
provide valuable additional information for air quality monitoring.
Environmental agencies show increased interest in these novel
applications; there are plans under way to add ceilometers to air
quality monitoring station instrumentation in large and densely
populated urban areas.
References
Emeis S., Schäfer K., Münkel C., 2008. Surface-based remote
sensing of the mixing-layer height - a review. Meteorologische
Zeitschrift 17, 621-630.
Fig.2 CL51 ceilometer attenuated backscatter
density plot covering morning hours
Emeis S., Schäfer K., Münkel C., Friedl R., Suppan P., 2012. Evaluation of the interpretation of ceilometer data with RASS
and radiosonde data. Boundary-Layer Meteorology 143, 25-35.
Münkel C., Emeis S., Schäfer K., Brümmer B., 2009. Improved near-range performance of a low-cost one lens lidar scanning
the boundary layer. Proceedings of the SPIE, Volume 7475.
181
WIND TUNNEL PHYSICAL MODELLING
182
A COMPARISON OF NUMERICAL AND EXPERIMENTAL STUDIES OF THE WIND FLOW IN URBAN
STREET CANYONS
F. C. Cezana (1), E. V. Goulart (1), R. R. C. de Paula (2), J. C. F. Queiroz (2), L. B. Föeger (1) and D. Z. Matta (2)
(1) Energy Laboratory of Mechanic Technical Department, Federal Institute of Technology of Espirito Santo, Vitoria, Brazil
(2) Environmental Engineering Department, Ufes, Vitoria, ES, Brazil
Presenting author email: cottoreginaldo@gmail.com
Summary
Results of a numerical simulation of flow around a group of obstacles have been compared with experimental data obtained
in an atmospheric boundary layer wind tunnel. The idealized urban street canyon was formed by six cubical building models
of the same size which were arranged in a symmetric configuration with two aspect ratios. External flow was parallel to the
buildings. Results were compared to numerical simulations of the same configurations using the standard - turbulence
model from commercial program CFX 13.0. The numerical results give a good estimate of the wind flow in an urban street
canyon.
Introduction
Understanding of the flow pattern and mechanism over a group of obstacles are of particular interest for environmental
engineers and meteorologists Knowledge of these processes can provide information to be used in guidelines for optimizing
of ventilation systems, reducing heat island effects and for risk assessments of hazardous materials emitted to the atmosphere
in urban regions (Kim and Baik, 2004). In the present study, the incompressible and viscous and stationary Navier-Stokes
equations were solved using - turbulence model from the Computational Fluid Dynamic (CFD) ANSYS CFX.
Methodology and Results
The flow field considered in this work was investigated in an open
return wind tunnel with test section of (2.0  0.5  0.5) m located at
the Energy Laboratory of IFES, Vitoria, Brazil. Smoke flow
technique was used to visualize the wind flow around the six cubical
buildings (H = 0.08 m) in the urban street-canyons. Fluid from a
smoke machine was generated and emitted into the wind tunnel. A
green laser light (500 mW) passing through a semi-cylindrical lens
was used to illuminate the vicinity of the buildings. A commercial
CFD code (ANSYS CFX 13.0) was used to calculate the flow field
around a group of buildings. The code solves three-dimensional
Reynolds-average Navier-Stokes (RANS) equation using a second
order scheme. Data from both numerical and experimental simulations
showed a standing vortex near the ground and below the stagnation
point (see Figs. 1 and 2) at H/W=2.0, in front of the first building.
Wind tunnel results showed that the flow field was defined by
interaction between both buildings forming two vortices, one near the
ground level and other in the upper region. From flow visualization
was also possible to capture the vortex-shedding phenomenon behind
upwind buildings. In the numerical velocity field it was observed that
between building near the ground, flow was predominantly outward
(see Fig. 2). Due to the smaller space between buildings the wakes
were disturbed, resulting in a skimming flow as described by Oke
(1988). The flow patterns on the plane x-y at H/W = 1.0. Within the
canyon space near the street bottom level, flow was horizontally
outward. One main features of the plan view was two large vortices
which form in the wake behind the last building (see Fig. 3).
Conclusions
By the use of numerical and experimental data it was possible to
investigate the wind field in an idealized urban street canyon. The
pictures of flow visualization showed that with the increasing canyon
space, different vortices systems occurred with positive and negative
vorticity.
Fig.1 Flow visualization x-z plane for H/W =2.0.
z
x
Fig.2 Numerical velocity field x-z plane for H/W=2.0
y
x
Fig.3 Numerical and experimental flow x-y plane for
H/W=1.0
Acknowledgement
The authors would like to acknowledge the financial support from CNPq and Vale.
References
Kim, J. and Baik, J., 2004. A numerical study of the effects of ambient wind direction on flow and dispersion in urban street
canyons using the RNG - turbulence model. Atmospheric Environment, 38, 3039-3048.
Oke, T.R., 1988. Street design and urban canopy layer climate. Energy and Buildings, 11, 103-113.
183
IMPACT OF URBAN-AREA GEOMETRY ON POLLUTION VENTILATION
L. Kukačka (1,2), V. Fuka (1), Š. Nosek (2), Z. Jaňour (2)
(1) Charles University in Prague, Faculty of Mathematics and Physics, Department of Meteorology and Environment
Protection, V Holešovičkách 2, Prague, 180 00, Czech Republic; (2) Institute of Thermomechanics AS CR, Dolejškova
1402/5, Prague, 182 00, Czech Republic
Presenting author email: kukacka@it.cas.cz
Summary
In order to quantify the influence of building geometry on the vehicle pollution ventilation within street canyons, a wind
tunnel experiment and a large eddy simulation (LES) was performed. A model of an idealised urban area with a line source
was designed with different building arrangements. Concentration, horizontal and vertical advective and turbulent pollution
fluxes were computed from the measured data as ventilation characteristics. A domination of advective pollution transport
was determined within street canyons. The turbulent transport was significant in vertical direction within as well as above the
built-up area. The ventilation intensity was evaluated for each model arrangement separately.
Introduction
Vehicle traffic became often a dominant pollution source in large cities all over the world (e.g. Fenger, 1999). Air quality
improvement in urban areas is necessary to avoid risk for human health (e.g. Hoek et. al., 2000). The geometry of the streets
and buildings in a city plays an important role in the pollution dispersion (Carpentieri et al., 2012). In this study, we follow
our recent research (Kukacka et. al., 2013) and we have focused on vertical advective and turbulent pollution transport above
a finite street canyon within the idealised urban area. The aim of the present work is to quantify the effect of varying urban
geometry complexity on turbulence and pollution dispersion using the wind tunnel modelling with the large eddy simulation.
Methodology and Results
For the wind tunnel experiment, a model was designed as an
idealised typical European inner city urban-area formed by
apartment houses with pitched roofs arranged in courtyards. We used
several types of geometry with different building height variation
and approach flow direction. A line source of passive scalar was
placed into the model simulating vehicle traffic emissions. We
assembled an experimental set-up for a simultaneous measurement
of the flow velocity and the tracer gas concentration based on laser
Doppler anemometry and fast flame ionisation detector. A numerical
part was computed by LES numerical model CLMM - Charles
University Large-eddy Microscale Model, (Fuka and Brechler,
2011). Longitudinal and vertical velocity components with pollutant
concentration were evaluated for different model geometries in
several horizontal and vertical planes. The advective and turbulent
pollution fluxes were computed from the data as ventilation
characteristics (see Fig. 1).
Conclusions
The results of the LES and the wind tunnel experiment, aimed to air
Fig.1 Advective pollution flux within the street canyon
with a line source situated perpendicular to approach
pollution dispersion in the idealized urban canopies with a different
flow – LES and wind tunnel comparison.
geometry complexity, showed a domination of advective pollution
transport within the street canyons of the investigated built-up area.
However, the turbulent transport with an opposite direction to the advective one, played a significant role within and above
the canopy. Further, we determined a significant influence of the geometry variation on the pollution dispersion. A building
arrangement with the most ventilation intensity was found.
Acknowledgement
This work was supported by the Charles University in Prague (project GAUK No. 535412), the Czech Science Foundation
GACR (project GAP101/12/1554) and the institutional support RVO: 61388998.
References
Carpentieri M., Hayden P., Robins A.G., 2012. Wind tunnel measurements of pollutant turbulent fluxes in urban
intersections. Atmospheric Environment 46, 669–674.
Fenger J., 1999. Urban air quality. Atmos. Environ. 33, 4877–4900.
Fuka V., Brechler J., 2011. Large Eddy Simulation of the Stable Boundary Layer. Finite Volumes for Complex Applications
VI - Problems & Perspectives, Springer Proceedings in Mathematics 4, Heidelberg, Germany, 485–493.
Hoek G., Brunekreef B., Verhoeff A., Wijnen J., Fischer P., 2000. Daily Mortality and Air Pollution in the Netherlands.
Journal of the Air & Waste Management Association 50, 1380-1389.
Kukačka L., Nosek Š., Kellnerová R., Jurčáková K., Jaňour, K., 2013. Quadrant analysis of turbulent pollution flux above the
modelled street intersection. EPJ Web of Conferences 45, 01053.
184
EVAPORATION AND SORPTION OF TOXIC SUBSTANCES IN ATMOSPHERIC BOUNDARY LAYER FLOW
K. Jurčáková (1), T. Dropa and M. Weisheitelová (2)
(1) Institute of Thermomechanics, Academy of Sciences of the Czech Republic, Prague, Czech Republic; (2) The National
Institute for Nuclear, Chemical and Biological Protection, Kamenná, Czech Republic
Presenting author email: klara.jurcakova@it.cas.cz
Summary
This study aims to improve understanding of evaporation of toxic substances into a fully turbulent atmospheric boundary
layer and of sorption of these substances on various materials. Very toxic gases such sarin, were considered and an
appropriate substituent was found (pentyl acetate). The whole study was conducted in the atmospheric boundary layer wind
tunnel and the model scale was 1:50. First the evaporation rate of pentyl acetate from the free surface was measured, than the
concentration field around a building and a cylinder (a model of a person), and the sorption of the substance to the surfaces of
the building and the cylinder. The surface materials varied from an external wall plaster to different tissues using for
protective suit manufacturing. The sorption is significantly influenced by the air moisture, but general behaviour like no
sorption on the airproof materials (e.g. teflon) and best sorption on the active carbon tissue were recognised.
Introduction
There is growing need of protection against toxic agents. Emergency responders such firemen are usually equipped with
protection suits, which can be made by different materials. The material can be airproof (e.g. Teflon, tyvak), which is
impenetrable by most of the agents, but very uncomfortable to wear for a longer time. Materials, which can breathe is not
suitable for wearing for longer periods. These materials easily absorb toxic agents and release them afterwards. Moving
firemen can cause contamination in much larger area than a simple dispersion into air flow. This phenomenon is called
secondary contamination and this study should help to understand and quantify it.
Methodology
The study was conducted in the Environmental wind tunnel of the Institute of Thermomechnics in Novy Knin, Czech
Repulic. The wind tunnel consists of an inlet chamber with dust filters, flow straighteners, vortex generators, a flow
establishment section, a test section, and a centrifugal fan, which can be continuously controlled and is working in suction
mode. A control system maintains test-section wind speeds ranging from 0 to 15 m/s. The effective working section is 1.5 m
high, 1.5 m wide and 4 m long. A boundary layer is generated typically in the scales 1:50 to 1:1000, it is about 0.4 m thick
that means about 80 to 400 m in the full scale. The vertical velocity distribution may be described by a power law or a
logarithmic law in the region where the boundary layer is turbulent and fully developed. Pentyl acetate was avaporated from
shallow pool of constant temperature 55°C and area size 0.0079 m2. The evaporation ratio was 9.5•10-5 m3/s/m2 for
undisturbed boundary layer with free stream velocity 2.5 m/s and temperature 16°C and 8.4•10-5 m3/s/m2 if the source was
placed 150 mm in front of the model building (cube, size of 158 mm) for the same free stream conditions. The concentration
field was measured by Photo Ionisation detectors (PID), which were regularly calibrated and have precision of 0.01 ppm. The
sorption on surfaces was judged from measurements of weight of the expose material before and after exposition inside the
wind tunnel. The checking model was always placed upstream to characterize humidity effects. Materials were weighted on
the analytical balance with precision 0.00001g.
Results
The visualization of the flow by glycerine smoke and laser light sheet showed that the source was placed inside the
recirculation zone in front of the building. The toxic substance was therefore lifted on the front face of the building to the roof
level very quickly. Part of the vapours streamlines on side of the building entered the wake behind the building. Thus the
whole building surface was exposed by concentration about 10 ppm. The situation was similar with cylindrical structure, only
there was no recirculation area in front of the cylinder, therefore weaker lift of the vapour on the front face. The materials on
the surfaces (external wall plaster, Teflon, tyvek, active carbon tissue) were exposed to the flow for 10 to 60 minutes. There
was always checking surface exposed only to the humid air in the wind tunnel (temperature 16°C, humidity about 65%). The
weight difference of the checking surface was due to captured air humidity. This was subtracted from the difference
measured on the exposed surface. External wall plaster easily absorbed humidity as well as pentyl acetate, but we were not
able to reach the saturation state. Teflon and tyvek materials are airproof and they absorb only very small amount of air
humidity and pentyl acetate. The absorbed amount was proportional to the time of exposure. The active carbon surface was
the best absorbent for the pentyl acetate. The absorbed amount was increasing with the exposure time, but not proportionally.
Conclusions
The wind tunnel modelling is useful tool for studying processes within atmospheric boundary layer. The evaporation rate
from free surface was constant; the concentration field around the cube building and cylinder follows the well-known pattern.
Sorption processes were much influenced by ambient humidity, but we were able to take this to account. Evaporation and
sorption within the turbulent boundary layer are still not very well parameterised to be computed by standard computational
fluid dynamics model and further investigation is needed.
Acknowledgement
This work was supported with institutional support RVO:61388998 and project VG20102014049 by the Ministry of the
Interior of the Czech Republic.
185
DEVELOPMENT AND VALIDATION OF THE HYBRID WIND TUNNEL/NUMERICAL MODEL HYWINMOD
A. Beyer-Lout (1), R. L. Petersen (1)
(1) CPP, Inc., 1415 Blue Spruce Drive, Fort Collins, CO, USA
Presenting author email: abeyer-lout@cppwind.com
Summary
HYWINMOD is a theoretical merging of wind tunnel model predictions and AERMOD (Cimorelli et al, 2005) plume rise
and dispersion algorithms to allow for accurate concentration estimates for any averaging time for direct comparison with
health limits, odour thresholds and/or national ambient air quality standards (NAAQS). The method is ideally suited for
complex building or terrain configurations where AERMOD, the US EPA recommended and approved model, is not
appropriate (i.e., urban area, very complex building configuration, upwind terrain wakes, etc.). Currently in the US,
AERMOD is used for these complicated modelling situations regardless of the fact that it was only developed to handle
simple solid buildings and elevated downwind terrain.
This paper discusses the HYWINMOD methodology and the validation against two field databases.
Introduction
In the past wind tunnel modelling has not been used directly to obtain hourly concentration estimates for assessing regulatory
compliance. The primarily reasons for this are: 1) the time and expense to evaluate all meteorological conditions in the wind
tunnel; 2) the wind tunnel cannot accurately simulate buoyant plume rise at a reasonable model scale and hence will
significantly overestimate maximum concentrations; 3) the wind tunnel has not been shown to adequately simulate the stable
or convective boundary layer; and 4) the wind tunnel has not been evaluated against EPA field data bases.
This paper describes a hybrid approach where wind tunnel modelling combined with the latest dispersion and boundary-layer
theory can be used to overcome these problems.
Methodology and Results
The HYWINMOD approach consists of three parts: 1) measurement of concentration in the wind tunnel under neutral
conditions; 2) data post processing and correction; 3) prediction of hourly concentrations incl. plume buoyancy for all
stabilities.
A scale model of the facility to be evaluated is constructed and placed in the wind tunnel. The appropriate approach mean
wind speed and turbulence profiles are set up and the model operating conditions assuming a neutral atmosphere and
neutrally buoyant plume are specified. The concentration is measured as a function of wind speed and wind direction at each
receptor location of interest. The concentration data is then used to define a fit function at each receptor location. The fit
function is used in conjunction with hourly meteorological data that is appropriate for the site (hourly wind speed, wind
direction and temperature close to or at stack height, as well as Monin-Obukhov length) as well as hourly source data
(emission rate, temperature, flow rate, exit velocity) to predict the hourly concentrations. Stability and plume rise adjustment
factors are applied.
HYWINMOD was evaluated using the two data bases: 1) the US EPA Bowline Point data base (EPA, 2003) and 2) hourly
SO2 measurements near an industrial facility (SO2 monitor 600 m downwind of stack which is located near a tall boiler
building). Wind tunnel tests were carried out for both sites, the Bowline Point Power Plant and the industrial facility, as
described above. The HYWINMOD predicted concentrations were compared to AERMOD predicted concentrations using QQ plots. In addition, the difference between HYWINMOD and AERMOD was assessed using the robust highest
concentration, or RHC (EPA, 2003). The 26th
Table 1. Summary of HYWINMOD Evaluation Results
highest concentration values were used to
characterize the upper end of the concentration
Ratio of Modelled/Observed Robust Highest
distribution for determining the RHC.
Concentrations
Data Base
Table 1 shows the ratio of modelled over
AERMOD
HYWINMOD
Receptor/Scenario
observed robust highest concentrations for
243241-hr
3-hr
1-hr
AERMOD and HYWINDMOD for the two
hr
hr
hr
data bases discussed above. The best results for
Bowline Point
each concentration averaging time are
1
0.76
1.14
1.47
0.88
0.83 0.61
highlighted in green
3
0.85
1.12
1.62
1.44
1.26 0.58
Industrial Facility
Conclusions
2009 average sulphur 0.40
0.52
0.53
0.80
0.63 0.70
The results of this evaluation show that
2009 high sulphur
0.47
0.62
0.63
0.96
0.74 0.81
HYWINMOD agrees as well with field
observations as AERMOD, and in some case better than AERMOD. The results confirmed that HYWINMOD should be
considered an alternate approach for situations where AERMOD is not appropriate.
References
Cimorelli, A.J.; S.G. Perry; A. Venkatram; J.C. Weil; R.J. Paine; R.B. Wilson; R.F. Lee; W.D. Peters; and R.W. Brode.
“AERMOD: A Dispersion Model for Industrial Source Applications. Part I: General Model Formulation and Boundary Layer
Characterization,” JAM, 44, 682-693. American Meteorological Society, Boston, MA. 2005.
EPA. AERMOD: Latest Feature and Evaluation Results. EPA-454/R-03-003, June 2003
186
COMPARISON OF PIV EXPERIMENT AND LES ON STREET CANYON DYNAMICS
R. Kellnerová (1,2), L. Kukačka (1,2), V. Fuka (2), V. Uruba (1), Z. Jaňour (1), Š. Nosek (1)
(1) Institute of Thermomechanics, Czech Academy of Sciences, Prague, Czech Republic;
(2) Department of Meteorology and Environment Protection, Charles University, Prague, Czech Republic
Presenting author email: radka.kellnerova@it.cas.cz
Summary
The paper deals with comparison between experimental data and numerical simulation concerning street canyon dynamics.
Experimental data were obtained in the wind channel with Time-Resolved Particle Image Velocimetry (TR-PIV). By PIV,
two components of velocity were measured in a vertical plane. The almost identical boundary conditions were simulated by
LES. The wind dynamics inside the street canyon was then analysed by Fourier analysis, Wavelet analysis, Quadrant
Reynolds decomposition, spatial and temporal correlation and Proper orthogonal decomposition (POD). Consequently, these
methods were used for the mutual comparison between LES and experimental data.
Although, some discrepancies were found out in the time-mean values between LES and PIV, the spectrum, momentum flux
and especially POD yielded very similar results what suggests that dynamics in terms of variance was properly modelled by
LES.
Introduction
The model of series of street canyon represented a very rough surface, which generates a very turbulent flow that is difficult
to describe due to whole complexity of the nature of turbulence. Thus, two challenges in comparison between experimental
and numerical data arise. Firstly, it is important to choose representative flow characteristics to capture both the complexity
and the non-stationarity of the dynamics. The mean values, time-mean moments of higher orders and spectra are often used
but they do not capture the spatial information of the structures in the flow. Therefore, Wavelet analysis (as an extension of
Fourier analysis) and spatial-temporal correlation were utilized in this paper. Second problem is to find an easilyimplemented and fast-applicable method that enables to effectively compare huge amount of data from PIV and LES in order
to avoid very tedious and time-consuming work. Herein, POD was used to reveal if the structures modelled by LES have
similar shape, dimension, turbulent kinetic energy and frequency of appearance as the ones from PIV record.
Methodology and Results
Experiment was conducted in the wind channel with floor covered by 30
rows of street canyons with unity aspect ratio. The dimension of street
was 50 mm. The two shapes of roof were used – triangle and flat. The
2D velocity information was obtained by PIV with frequency sampling
of 500 Hz and 1000 Hz. Spatial resolution of PIV in 50 mm high street
canyon reached 1.2 mm x 1.2 mm.
Identical wind-channel and street canyons were simulated by LES, only
the number of rows was reduced down to 6 due to computational
demands. The LES was performed with temporal sampling of 1000 Hz
and spatial resolution was 1.5 mm x 2 mm.
Primarily, the mean values were compared. Surprisingly, in the case with
triangle roofs, the vertical profile yielded by LES deviates from the
measured one. This was lately improved by implementation of free-slip
top configuration. Notwithstanding, the momentum flux and spectral
analysis showed similar results for both geometrical arrangements. Very
nice match was found with help of POD for the triangle roof case (Figure
1). The shape of the modes, the turbulent kinetic energy contained inside
of them or the statistics of the expansion coefficients, all were in
agreement with the experimental data. Unfortunately, essential
dissimilarity between POD modes from LES and PIV was found out in
the flat case, where slight variation in the flat-building heights caused by
manufacturing in experiment possibly introduced difference between
measured and simulated flow.
Conclusions
LES proved to be a reliable method for simulation of a complex
turbulent flow above large obstacles. To overcome difficulties with
processing of a large bank of data coming from LES and PIV, POD
confirmed to be a useful tool for comparison purpose.
Acknowledgement
The authors kindly thank the Czech Science Foundation GACR
(project GAP101/12/1554) for their financial support.
Project was also done with institutional support RVO 61388998.
187
Fig. 1: The most dominant mode in terms of TKE for
triangle roof case. Upper: LES. Lower: Experiment.
PART TWO:
POSTER SESSIONS
188
AIR QUALITY AND
IMPACT ON LOCAL TO
GLOBAL SCALES
189
MODELLING AND ANALYSIS OF THE ROLE OF MESOMETEOROLOGICAL PROCESSES ON TRANSPORT
AND ACCUMULATION OF POLLUTANTS IN THE WESTERN MEDITERRANEAN AND THEIR INFLUENCE
ON CHEMICAL DEGRADATION MECHANISMS
J. L. Palau (1), M. Vázquez (1), F. Rovira (2), M. J. Sales (2), A. Muñoz (1), E. Borrás (1) T. Vera (1), F. Santa-Cruz (1), J. I.
Roselló (1) and P. Sánchez (1)
(1) Fundación Centro de Estudios Ambientales del Mediterráneo; C/ Charles R. Darwin-14, 46980 Paterna (Valencia); Spain
(2) MODELIZA, S.L.; Parque Científico Universitat València; C/ Catedrático Agustín Escardino-9, 46980 Paterna
(Valencia); Spain
Presenting author email: joseluis@ceam.es
Summary
With the aim of characterizing the main air pollutants (anthropogenic, biogenic and secondary reaction products) present in
the Mediterranean coast of the Iberian Peninsula under different meteorological conditions (summer and winter) two field
campaigns (February and June 2011) were performed in the context of the MODELISMOS project (Modelling and analysis
of mesometeorological processes on transport and accumulation of pollutants in the Western Mediterranean and their
influence on chemical degradation mechanisms).
Introduction
The atmospheric flow regime in the Turia Basin (Eastern of Spain) favours the accumulation of water vapour and
atmospheric pollutants during much of the year. This accumulation can determine not only the rainfall but also, due to a
change on the oxidative capacity of the atmosphere (variations of the OH, HO2 and H2O2 concentrations) the prevailing
chemical mechanisms under those weather conditions (Millan et al., 2009). The study presented in this communication
deepens on the knowledge of the seasonality of meso-meteorological processes responsible of the transport and accumulation
of air pollutants, and its influence on the predominant chemical degradation mechanisms under different weather conditions
(winter/summer) on the Mediterranean coast of the Iberian Peninsula.
Methodology
Two intensive field campaigns (21-25/February 2011 and 20-24/June 2011) have been carried out around the city of Valencia
(Spain) evidencing how under sea breeze conditions the anthropogenic emissions coming from the city are driven inland
through the Turia River Basin. Measurements were performed using two instrumented (mobile) vehicles; one radiosounding
system; three chemical sampling sites, the Regional Air Quality Surveillance network and three meteorological towers. For
the chemical analysis of the air masses, samples were taken at three locations along the Turia river basin: Valencia (at the
coast, Altitude 7m), Paterna (14 km inland from Valencia, Altitude 122m) and Villar del Arzobispo (51 km inland from
Valencia, Altitude 430m). Air samples were collected by triplicate with three different types of cartridges; C18 (Waters,
Spain) for the analysis of alcohols, acids, aldehydes and ketones, DNPH (Waters, Spain) for aldehydes and ketones and
XAD-2 (Supelco, USA) for VOCs with more than five carbon atoms. To study the different atmospheric dispersive
conditions along the day, different daily sampling periods were selected. In total 297 cartridges in winter and 396 in summer
were collected and analyzed afterwards by GC-MS and LC-MS (Thermo-Fisher Sci., USA). To analyse the origin of sampled
pollutants and the seasonality of atmospheric pollutant accumulation processes, we used the mesoscale model RAMS coupled
to the Lagrangian particle dispersion model HYPACT to simulate backward trajectories from the sampling sites.
Results and Conclusions
In this contribution we present the main findings related to the impact that different weather conditions (summer and winter)
have on the dynamics of the advection and diffusion of measured atmospheric pollutants around the Valencia conurbation.
From the modelling analysis we analysed the origin of airmasses and the apportionment of anthropogenic and biogenic
sources responsible of the pollutants sampled during the fields campaigns. Regarding air quality, different C2-Cn hydroxyl
carbonyl compounds were also determined in the three sampling points. Trends between them and their VOCs precursors
have been observed. Pinonic acid, nonanal, glyoxal, methylglyoxal, 2,3 butanedione, glutaraldehyde, formaldehyde,
acetaldehyde and acetone among others were detected. VOC’s/NOx ratios obtained confirm that Valencia and Paterna can be
considered as urban environments and Villar del Arzobispo as rural (VOC’s/NOx limit 8:1); this ratio was higher in summer
than in winter at the three locations. Differences in chemical composition between winter and summer were also observed.
The impact of the emissions from the city of Valencia (coastal city) was observed in the detections of secondary pollutants
such as ozone in Villar del Arzobispo. Average of percentage concentration of aldehydes and aromatic compounds was very
similar in winter and summer, but in the case of acids, alcohols, alkanes, ketones and monoterpenes differences were
observed. Impact on ozone and other secondary products depends more on the chemical nature of the compound (rate
constants) than on its concentration, i.e., aromatics were the most important species in terms of reactivity but not in terms of
concentration in air during winter and summer campaigns.
Acknowledgement
The Instituto Universitario CEAM-UMH is partly supported by Generalitat Valenciana. This work was supported by the
Spanish research projects MODELISMOS (CGL2010-17623/CLI), GRACCIE (CSD2007-00067) and FEEDBACKS
(Prometeo Program- Generalitat Valenciana).
190
ROLE OF THE LONG-RANGE TRANSPORT IN THE AEROSOL CONCENTRATION FORMATION IN
HUNGARY
Z. Ferenczi
Hungarian Meteorological Service
1024-Budapest Kitaibel P. u.1., Hungary
Presenting author email: ferenczi.z@met.hu
Summary
In recent years it was demonstrated that the air pollution has harmful effects on human health, therefore systems providing
information on the actual and expected air quality are increasingly required by the city dwellers, who are most affected by air
pollution. One of the most important background information of these early warning systems is the long-range transport of
the air pollutants, and without this information accurate predictions cannot be made, especially for pollutants which have
long atmospheric residence time. The EMEP chemical transport model calculations were used to determine the role of the
long-range transport in the aerosol concentration in Hungary. The results of this examination are important not only to refine
the PM10 predictions, but provide important basic information to the action to reduce the PM pollution in Hungary.
Introduction
In recent years, the PM10 episodes, which in many cases are associated with extreme weather situations, caused the most
critical air quality problems in Budapest and Hungary. The first step before developing a successful air quality forecast
system is a detailed analysis of the meteorological background of the PM10 high-level situations and the effect of the longrange transport on the PM concentration.
In this work only the yearly average of the long-range transport was analysed. In some cases the effect of long-range
transport can be negligible but sometimes it can be responsible for the episode situation.
Methodology and Results
The effect of the long-range transport on the PM10 concentration was determined by the EMEP chemical transport model
(Simpson et al., 2012).
Determining the long-range transport of the particulate matter, the effect of the national emission from all countries in the
EMEP model calculations area and the natural resources in the region were taken into account. Our study was carried out for
five years (2006-2010) in order to filter the variability of the weather as much as possible. Since the emission values show
considerable variability from year to year (not only in case of Hungary), it is difficult to separate the effects of the weather
from the effect of the emissions in the results.
During the studied five years trend, change in the impact of the long-range transport could not be observed, the difference
between the years mainly explained by changes in the PM10 emissions of Hungary. In the years when the emission of
Hungary was decreased significantly the proportion of the long-range transport increased slightly.
Besides the PM10 situation the main contributor countries were also determined, which have significant effect on the PM2.5
pollution formation in Hungary. Among the European states, Romania and Poland are the greatest polluters of Hungary's
atmosphere.
Conclusions
In Hungary the contribution of the long-range transport to the PM air pollution is 70-80%. The effect of the long-range
transport shows significant spatial variability, the most important area is the western frontier of Hungary, and the smallest is
in the central part of the country. 37% of the particulate matters emitted by Hungary remain in the country and 63% cross the
border of Hungary increasing the PM contaminations of other countries. In case of Hungary the aerosol particles arrive to the
area of Hungary from outside sources are 30% more than the particles emitted by the country in all.
The results of this investigation can be summarized as follows: the long-range transport is very determinant in Central
Europe, and could not be neglected in the transport model calculations.
References
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D.,
Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á.,
and Wind, P., 2012: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 78257865, doi:10.5194/acp-12-7825-2012.
191
LONG RANGE TRANSPORT OF PM10 TO MARMARA REGION
E. Oksuz (1), M. Kafadar (1)
(1)Eurasian Institute of Earth Sciences, Istanbul Technical University, Maslak, 34469, Istanbul, Turkey
Presenting author email: mugekafadar@gmail.com
Summary
The aim of this study is identifying contributions to high particulate matter with diameter of 10 micrometres or less (PM10)
concentrations and its important transfer pattern that affect PM10 levels in Marmara Region during the period of 2008-2010.
High PM10 days for 11 cities of Marmara Region, which are defined based on results of R Statistical Software analysis, and 6
March 2009 selected as episode. HYSPLIT(Hybrid Single-Particle Lagrangian Integrated Trajectory) model has been run to
observe vertical atmospheric structure and how the atmospheric transport behave in this period. By taking into consideration
5 days backward trajectory of air masses results and meteorological conditions for the episode, it is determined that the air
masses commonly originated from Sahara Desert and comes to Marmara Region by long range transport.
Introduction
The studied area, Marmara Region, include 11 cities ( Istanbul, Balikesir, Kirklareli, Kocaeli, Tekirdag, Bilecik, Bursa,
Edirne, Yalova, Canakkale, Sakarya) and while 4 of them in Europe, 7 of them is in Asia. Since the region of the Marmara is
highly urbanized, there faces significant air pollution problem today. Particulate matter is one of the most challenging air
pollution problem of the cities that has serious effects on public health such as decreased lung function, increased respiratory
morbidity and cardiopulmonary disease mortality (Unal, A., et. al, 2010, Donaldson, K., et. al.,2005). Although air pollution
causes from local emission, long range transport of air pollution also has a great impact on regional air quality when the
emission sources at upwind regions are intensive and the meteorological conditions are available to transport the pollution.
Methodology and Results
The hourly PM10 concentrations during the period of 2008-2010
were obtained from the 25 stations for 11 cities in Marmara
Region. . Using statistical software R, concentrations were studied
as a function of time and episode of increase in PM10
concentrations were determined. It was identified that the PM10
concentration over Marmara Region peaked only on March 6,
2009 for all cities at the same time during the period of 20082010. As a result of statistical
% PM10 Increase
analyses for the episode it was
ISTANBUL
251
observed
that,
PM10
values
EDIRNE
259
KIRKLARELI
364
significantly increased with respect
TEKIRDAG
145.5
to average values of the three years
CANAKKALE
406
KOCAELI
135
(see Fig.1). For the selected episode,
YALOVA
232
HYSPLIT model was applied to
SAKARYA
identify contributions that cause
BILECIK
72
BURSA
86
high PM10 concentrations in air over
BALIKESIR
304
all cities in Marmara Region. 24
hourly intervals, 5 days backward
trajectories for all cities were
computed using HYSPLIT model. As the model outputs showed Fig 2. HYSPLIT model output of Istanbul for 6 March
that there was long range PM10 transport from Saharan Desert
2009
(see Fig.2). In order to ensure dust originating from the desert
stayed over Marmara Region and influenced concentrations of daily PM10, meteorological data (mean wind speed and
pressure) taken for Marmara Region were analyzed. As a result of analysis meteorological conditions were observed as stable
that causes dust originating from the desert to become trapped near ground level in studied area.
Fig 6. PM10 concentration
increment (%)
Conclusions
Results show that the Saharan Dust is the main contributing PM10 source for the cities of Marmara Region during the studied
episode. In conclusion, local emission management is not enough to handle with air quality problem of a regional area, an
integrated management scheme covering local, regional, and global air quality is needed.
References
1.Unal, A., Kindap, T., Im, U., Markakis, K., Mihalopoulos, N., Gerasopoulos, E., Kocak, M., Mangir, N., Kubilay, N., Kana
kidou, M. (2010). Megacity and Air Pollution in the Eastern Mediterranean : Istanbul Case Study, 12, 11402.
2.Donaldson, K., Mills, N., MacNee, W., Robinson, S., Newby, D. (2005). Role of inflammation in cardiopulmonary health
effects of PM. Toxicology and Applied Pharmacology, 207, 483–8.
192
MEASUREMENT AND MODELING ACTIVITIES IN NEPAL IN FRAMEWORK OF THE SUSKAT PROJECT
A. Mues (1), A. Lauer (1), M. Rupakheti (1), A. Panday (2,3)
(1) IASS Potsdam; (2) International Centre for Integrated Mountain Development (ICIMOD), Nepal; (3) University of
Virginia, USA,
Presenting author email: andrea.mues@iass-potsdam.de
Summary
Kathmandu in Nepal has been rapidly growing over the last two decades, and now experiences one of the worst air pollution
problems in Asia. The SusKat project (Sustainable Atmosphere for the Kathmandu Valley) has been designed to be an endto-end project aimed at understanding and addressing air pollution in Nepal focusing on the Kathmandu Valley and its
surroundings. The main activities include an intensive measurement campaign as well as a set of different modeling studies.
Measurement results from the recent field campaign highlight the severe air pollution and the necessity to better understand
the emissions as well as the meteorological and chemical processes leading to high pollution levels in the valley. As an
example black carbon (BC) concentrations of up to 50µg/m3 were frequently measured at Bode, a site slightly downwind (in
winter season) of the two major cities Kathmandu and Patan in the Kathmandu Valley. The analysis and interpretation of
these measurement data will be complemented by experiments using WRF/Chem (Weather Research and Forecasting
Model/Chemistry) model (Grell et al., 2005) to get better insights into the relevant processes and impacts. Because of the
complex topography of the Himalayan mountains near the Kathmandu Valley, modeling this region is very challenging and
requires a careful evaluation of both meteorology and air quality.
Introduction
Air pollution is a major environmental and health concern in Nepal and particularly in the capital city Kathmandu. Large
parts of South Asia including this region are among the most polluted and at the same time among the least studied regions in
the world in terms of air quality. In Nepal particularly, there have only been a few past studies, which were not sufficient for
designing and assessing effective mitigation measures. The SusKat project implemented by the Institute for Advanced
Sustainability Studies (IASS Potsdam) and the International Centre for Integrated Mountain Development (ICIMOD)
addresses specifically the main gaps and aims at a better understanding of the observed severe air pollution in the Kathmandu
Valley and its surroundings. Here the background of the project, the set-up and first results of the measurement campaign as
well as the design of the model studies are introduced. First modeling results focusing on meteorology and black carbon are
presented.
Methodology and Results
In collaboration with 40 plus scientists representing 19 research
institutions from nine countries, including Nepal, an unprecedented
atmospheric characterization campaign (SusKat-ABC) was
conducted in Nepal from December 2012 through June 2013.
Different atmospheric chemical compounds (e.g. BC, O3, CO,
speciated VOCs) and meteorological parameters were measured at
seven major sites in the Kathmandu Valley and several sites in
other parts of Nepal. This measurement campaign is unique for
Nepal in its temporal and spatial resolution as well as in its
complexity in view of the measured chemical compounds. First
results show very high levels of BC and a well-defined diurnal
pattern with prominent peak around 9 am and less pronounced Figure 7: Diurnal pattern of BC concentrations measured at
peak around 7 pm influenced by both emissions and Bode, Kathmandu valley during Jan-March 2013. The top
meteorological conditions. Model studies with WRF/Chem help to end and bottom end of whisker represents 95 percentile and 5
better understand the physical processes and mechanisms relevant percentile respectively while the box represents 75 percentile
to meteorology and air pollution in the Kathmandu Valley and the and 25 percentile.
broader region. They also help to assess the impact of air pollution on health, agriculture and climate. The state-of-the-art
WRF model is online coupled with a chemistry model (WRF/Chem) and set-up over South Asia with a resolution of
15x15km2 and a higher resolution of 3x3km2 over the Nepal region. So far only few modeling studies were conducted for
Nepal and surrounding region, and thus a thorough evaluation of the model is needed. Reanalysis data and air pollution
measurements from the SusKat campaign as well as relevant data available from other stations in South Asia are compared to
the WRF/Chem results to assess the model performance in this region.
Conclusions
The first results of the measurement campaign show exceptionally high levels of air pollution in the Kathmandu Valley and
clearly show the need for actions aimed at better understanding of the air pollution that leads to mitigation actions. Model
studies bring more insight into physical and chemical processes leading to such high pollution events. Due to the complexity
of the topography and meteorological conditions in this region, a logical first step is to understand and simulate the
meteorological processes and then look into air quality related questions.
References
Grell GA, Peckham SE, Schmitz R, and McKeen SA, Frost G, Skamarock WC, and Eder B. 2005. "Fully coupled 'online'
chemistry within the WRF model." Atmos. Environ., 39:6957-6976.
193
DETECTION OF FUKUSHIMA ORIGIN CEASIUM ISOTOPES AT POLISH POLAR STATION IN HORSUND
(SPITSBERGEN) AND ITS EFFECTS TO ATMOSPERIC ELECTRICITY PARAMETERS
B. Mysłek-Laurikainen (1), M. Matul (1), S. Mikołajewski (1), H. Trzaskowska (1), M. Kubicki (2), P. Baranski (2), A. Ozimek
(2), S. Michnowski (2)
(1)National Centre for Nuclear Research (NCBJ)Otwock ,(2)Geophysical Observatory, Institute of Geophysics Polish
Academy of Science Warsaw,Poland
Presenting author email: b.laurikainen@ncbj.gov.pl
Summary
The Polish high –volume air sampler AZA-1000 in Hornsund(77 00 N, 15 33, E) is one of the radionuclide monitoring
stations positioned close to the polar pole and most to the North of all. The measurements of radioactive pollution of ground
level air present in atmospheric aerosols started in July 2002 when in the fjord Hornsund stationAZA-1000 was assembled (at
the premises of the Polar Station of Institute of Geophysics of the Polish Academy of Science).The ceasium isotopes were
detected after Fukushima accident and its influence to electric conductivity is discussed in comparison with Polish
Geophysical Observatory at Świder near Warsaw.
Introduction
Ions in atmosphere are generated by cosmic rays Radioactive aerosols of ground level air contain numerous natural
radioisotopes formed by cosmic origin ions, as well as man made which appears as standard release of nuclear facilities,
nuclear weapon tests (in the past) and nuclear power plants accidents like Chernobyl or lately Fukushima . The migration
with air masses transport of this contamination caused that they spread all over the North Hemisphere where the most of
releases took place. This radioactivity gives significant contribution to ionizing phenomena and electric field changes in
particular electric conductivity is sensitive to this contamination. Observation of this phenomena in not polluted regions , far
from industrial pollution bringing up great amount of dust forming aerosols is possible in Polar region.
Methodology and Results
The Polish high –volume air sampler AZA-1000 in Hornsund(77 00 N, 15 33, E) is one of the radionuclide monitoring
stations positioned close to the polar pole and most to the North of all. The measurements of radioactive pollution of ground
level air present in atmospheric aerosols started in July 2002 when in the fjord Hornsund stationAZA-1000was assembled (at
the premises of the Polar Station of Institute of Geophysics of the Polish Academy of Science). The station was built as air
aerosol sampler to be installed at the Polish Polar Station in Hornsund, so the instrument was designed to operate in allweather condition of the cold polar region. In order to avoid the influence of extremely low temperature and severe snow
precipitation, this device was not installed in open air, but in a container where temperature inside does not drop below 00 C .
The station is accommodated for continuous operation in different meteorological conditions. The sampling part which
collects aerosol from the air inlet is placed at a roof about 3m above the summer season ground level when snow disappears.
The high air flow rate about 400m3/h through a chlorinated vinyl polychloride filter or a polypropylene filter allows to take
representative aerosol air samples. Collection of aerosol from about 10 000-60 000 m3 enables accurate spectrometric
measurements of radionuclides in wide range of their concentration with detection sensitivity above 0.5-1.0mBq/m3.
Detailed description of air sampler and technology of measurements are in ref.[1].
The origin and concentration of radionuclides in air are described in numerous publications, among them[2] Manmade
radionuclides in Earth atmosphere appeared as a result of nuclear weapon tests and use in Hiroshima and Nagasaki and latter
as the result of releases in nuclear industry and nuclear reactors accidents. The most often the ceasium isotopes 137 Cs and
132 Cs are detected. Seasonal variation of natural and antropogenic radionuclides at Hornsund are presented and two
ceasium isotopes are analyzed. The presence of 132 Cs is evident proof of Fukushima origin , and this isotope was not
observed in any of air filters since 2002 year up to this event where the ratio of 137/132 Cs is typical for Fukushima origin
detected in numerous places in Poland and in the World.
References
1.Bogumła Mysłek-Laurikainen et al. Air aerosol sampling station AZA-1000 at Polish Polar Station in Hornsund,
Spitsbergen. NUKLEONIKA 2006;51(2):137-140
2.B.Mysłek-Laurikainen et al . Radionuclides in ground level air in Poland. NUKLEONIKA 43 NO.4 439-448 1998
194
ATTEMPT TO IDENTIFY OF EPISODES THE CONTRIBUTION OF STRATOSPHERIC OZONE IN THE
GROUND LAYER OF THE ATMOSPHERE
E. Krajny (1), L. Osrodka (1), M. Wojtylak (1) and M. Pajek (2)
(1) Department of Monitoring and Modelling of Air Pollution, Institute of Meteorology and Water Management National
Research Institute (IMWM-NRI), Branch in Cracow, Bratkow 10, 40-045 Katowice, Poland; (2) Department of Satellite
Remonte Sensing, Institute of Meteorology and Water Management National Research Institute (IMWM-NRI), P. Borowego
14, 30-215 Krakow, Poland
Presenting author email: ewa.krajny@imgw.pl
Summary
The aim of this study was to identify a situation of intense exchange of air masses STE, and then answer the question whether
the 7Be can be a good marker of stratospheric ozone origin in ground layer of the atmosphere. Ten sets of data covering the
2005-2009 period are examined: weekly concentration of 7Be and hourly O3 measured in the ground layer of the atmosphere.
The measuring were carried out at several measuring points located at different latitudes in Poland area. The data obtained
were statistical and Fourier analyzed. The Fourier analysis is applied to eliminate the periodicity associated with the annual
variability of solar radiation incoming to the Earth's surface. Subtracting the component of the annual enabled analysis of
variability the non-periodic concentrations of beryllium. On this basis, were selected weekly periods during which the
concentration of beryllium significantly exceeded the average of its value. The selected periods were then analyzed in terms
of synoptic assessment of the impact of meteorological conditions on indexed elevated levels of 7Be. For the selected case of
such a phenomenon, a detailed analysis of weather conditions by using, inter alia, remote sensing, data aerological,
actinometric and air quality in the surface layer of the atmosphere.
Introduction
Beryllium-7 (7Be) is a radioactive element about half-life 53.3 days, produced by cosmic rays in spallation processes, in the
lower stratosphere (~70%) and the upper troposphere (~30%). Beryllium gets into the surface layers of the atmosphere
boundary layer (ABL) as a result of stratosphere to troposphere exchange mass air (STE). Stratosphere to troposphere mass
transport (STT) can sometimes be accompanied by stratospheric ozone (O3) origin.
Methodology and Results
Airborne particle sampling was carried out in the surface air (1.5 m above ground level) using a sampler pump ASS-500
(Aerosol Sampling Station). Airborne aerosols samples were collected weekly in Petranowa filters type FPP-15-1.5 with a
high collection efficiency, filter surface area was 0.2 m2. The average weekly volume range from 50 000 to 90 000 m3 (at the
nominal air flow rate of 500 m3/h). Radioactivity in the filters was measured in laboratory with high-efficiency gamma ray
spectroscopy. Ozone ground level is measured using a UV absorption spectrophotometer. Ozone analyzer measures with
norm ISO 13964:1998. We can draw the following conclusions: (1) 7Be exhibited a seasonal behaviour, with exception in
spring/summer and agree with results obtained at other locations in the world, particularly located on the same latitude. (2)
The correlation coefficient between 7Be and average O3 generally is significant correlation in autumn, which implies that
their concentrations are driven by the same processes, and not very significant correlation in winter. (3) Analysis the
relationship between of monthly or weekly concentrations of 7Be even with 1-hour ozone ground-level does not allow
unambiguous identification of contribution of stratospheric ozone in the its total concentration in the surface layer of the
ABL. Daily and hourly values 7Be are more appropriate for this research. and a more detailed study should be performed. (4)
Study monthly or weekly 7Be/O3 ratio only allows to identify potential situations of air mass exchange stratospheretroposphere (STE) and the appearance of stratospheric ozone origin in surface layer of the ABL.
Conclusions
In summary, 7Be can be one of the indicators of stratospheric ozone in the surface layer of the ABL, but as the only is not a
very good indicator. Due to the, not all typed on the basis of STE situations are then confirmed in the course of the synoptic
situation, satellite remote sensing, upper atmospheric sounding, back trajectories, and meteorological conditions. Stratosphere
to troposphere air mass transport is a temporary phenomenon and sometimes in local scale in vertical column of atmosphere.
In the study of phenomena STE the important role of data, to be the best short-term data (hourly, daily). On the other hand, it
is difficult to determine the existence of a situation STE without upper airborne observations and measurements.
Acknowledgement
This study has been supported by the National Science Centre through the research project No. N N523 564838. The authors
wish thank for making data 7Be, that were elaborated basin upon the investigations performed by the Central Laboratory for
Radiological Protection. The authors thank for sharing O3 concentrations by Main Inspectorate of Environmental Protection.
References
Dutkiewicz V.A., Husain L., 1979. Determination of stratospheric ozone at ground level using 7Be/O3 ratios. Geophysical
Research Letters 6, 3, 171-174.
Feely H.W., Larsen R.J., Sanderson C.G., 1989. Factors that cause seasonal variations in beryllium-7 concentrations in
surface air. Journal of Environmental Radioactivity 9, 223-249.
195
REGIONAL EMISSION FACTORS OF CARBON DIOXIDE FROM AGRICULTURAL WASTE RESIDUES
BURNING IN NORTHEASTERN REGION THAILAND
N. Khosavithitkul (1), N. Chuersuwan (2), and T. Wannasook (3)
(1) The Center for Scientific and Technological Equipment; (2) School of Environmental Health, Institute of Medicine,
Suranaree University of Technology; (3) Regional Environment Office 11, Office of Permanent Secretary, Ministry of
Natural Resources and Environment, Nakhon Ratchasima, 30000, Thailand
Presenting author email: nkhosavithitkul@yahoo.com
Summary
Agricultural residue (137 samples), taken from forty sub districts in twenty districts of ten provinces in the Northeastern (NE)
region of Thailand, were analyzed for major physical and chemical properties and subjected to simulated burning. Rice straw
had the highest dry weight and bagasse the lowest. Bagasse had the highest moisture and carbon contents. Sugarcane leaf
emitted more CO2 than the other residues. Weight loss on combustion was in the range of 75-92 %, The simulated burn of
agricultural residues showed CO2 emission values at 67% of the IPCC values.
Introduction
The longest-running continuous-monitored atmospheric CO2 concentration data (Mauna Loa Observatory, Hawaii) indicates
that atmospheric CO2 concentration has steadily increased since 1958 [1]. Several scientific models indicate possible negative
impacts of rising global temperatures, ‘global warming’, as a result of increased CO2 and other greenhouse gases in the atmosphere. While the rise in average temperature might date to the end of the so-called ‘Little Ice Age’ in the late 19th century,
temperature data (NASA Goddard Institute for Space Studies) indicates that the earth's mean surface temperature has
increased by about 0.8 °C since the early 20th century with about two-thirds of the increase occurring since 1980. Other data
indicate a long-term cooling trend over the last 2000 years with periods warmer than today during Roman and Medieval
times [2]. The coincident increases in CO2 levels and in average temperature during the last century heighten concern that the
raising global temperature may in part be caused by greenhouse gases released into the atmosphere as a result of human
activities such as deforestation, burning of fossil fuels, and even biomass burning [3]. The concerns led to 195 governments
ratifying the United Nations Framework Convention on Climate Change which entered into force March 21, 1994, with the
objective of stabilizing atmospheric CO2 concentrations and preventing ‘dangerous anthropogenic interference with the
global climate’, and most of those ratifying the subsequent Kyoto Protocol that actually sets mandatory limits on emissions.
Methodology and Results
The study was carried out at the Center for Scientific and Technological Equipment in Nakhon Ratchasima, Thailand. One
hundred and thirty seven waste residue samples were collected from randomly selected areas in the Northeastern region of
Thailand based on a stratify sampling method. The waste included rice straw, sugarcane leaf, bagasse, grass leaf, leaf, and
eucalyptus bark. All waste residues were air dried prior to the experiment. The physical and chemical properties of the waste
residues were analyzed according to standard method ASTM D1762-84 and ASTM D5373 Combustion experiments were
carried out to simulate the conditions of waste burning. Results from simulated burning found that sugarcane leaf emitted
more CO2 than other residues, 4.25±0.46 mg/m3 while other residues emitted less than 3 mg/m3. However, ranges of CO2
emission were 0.44-7.30 mg/m3. Loss of weight after combustion was about 75.90-92.49%. CO2 emission of each residue are
the following: rice straw 1,111.25 g CO2/kg, bagasse 1,322.75 g CO2/kg, sugarcane leaf 1,075.75 g CO2/kg, leaf 1,171.25 g
CO2/kg, dry grass 1,100.75 g CO2/kg, eucalyptus bark 1,187.25 g CO2/kg. Average CO2 emission of residue burning reported
by the IPCC was 1,515±177 g CO2/kg. Simulated burn of residues showed lower values of CO2 emissions. Average emission
rate of the IPCC of the activities associated with various kinds of incineration residues arising from agricultural activity was
1,515±177 g/kg which is higher than the average emissions observed here. CO2 values obtained from the experiments are
lower than the values obtained from IPCC. However, the IPCC values may include the burning of biomass in the forest.
Conclusions
Spatial estimation of CO2 in the Northeastern region was performed using data from satellite hotspots coupled with land use
classification by the Department of Land Development, and agricultural statistics. From March through December 2008,
hotspots accounted for 1,141 areas resulting in the estimation of CO2 emission of 0.04-1.60 million tons compared to IPCC
emission factor of about 1.8-1.9 million tons. Rice and sugarcane in the area had the potential to generate 11.4-11.6 million
tons of CO2 emission in 2008 but other plants with limited data on burning practices, e.g., cassava and corn, cannot be
reliably estimated. Not all residues were subjected to burn, if the burning occurred for 1 and 5% of rice and sugarcane
growing areas, CO2 emission was about 0.1 and 0.6 million tons, respectively.
Acknowledgement
Financial support by the National Research Council of Thailand.
References
1 Keeling, C.D. and Whorf, T.P., 2000. Atmospheric CO Concentrations-Mauna Loa Observatory, Hawaii, 1958-1997
2
(revised Aug. 2000) NDP-001, CO2 Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge TN.
2 Esper, J., Frank, D.C., Timonen, M., Zorita, E., Wilson, R.J.S., Luterbacher, J., Holzkämper, Fischer, S.N., Wagner, S.,
Nievergelt, D., Verstege, A., and Büntgen, U., 2012. Nature Climate Change. 2, 862-866.
3 Andreae, M.O. and Merlet, P.,2001. Glogal Biogeochemical Cycles. 15(4), 955-966.
196
AIR QUALITY
MANAGEMENT AND
POLICY
197
UFIREG PROJECT: ULTRAFINE PARTICLES - AN EVIDENCE BASED CONTRIBUTION TO THE
DEVELOPMENT OF REGIONAL AND EUROPEAN ENVIRONMENTAL AND HEALTH POLICY
S. Lanzinger (1), A. Schneider (1), S. Breitner (1), R. Rückerl (1), A. Peters (1), S. Bastian (2), A. Zscheppang (3), J. Cyrys (1)
(4)
(1) Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology II, 85764
Neuherberg, Germany; (2) Saxon State Office for Environment, Agriculture and Geology, 01326 Dresden, Germany; (3)
Technische Universität Dresden, 01307 Dresden, Germany; (4) University of Augsburg, Environment Science Center
(WZU), 86159 Augsburg, Germany
Presenting author email: stefanie.lanzinger@helmholtz-muenchen.de
Summary
Information on health effects of ultrafine particles (UFPs) is still limited because UFP ambient concentrations are not
routinely monitored in most locations. Most monitoring in previous studies relies primarily on measures of total particle
number concentrations (PNC). Moreover, European research activity on UFPs is concentrated mostly in Western European
countries and studies are rare. Accordingly, no directives exist for regulation of UFP measurements in ambient air. Hence,
within the framework of the UFIREG project, UFP measurements are conducted in five European cities in order to provide
an evidence-based contribution to the development of environmental and health policy.
Introduction
Measurements of UFP are currently conducted in the five European cities: Dresden and Augsburg (Germany), Prague (Czech
Republic), Ljubljana (Slovenia), and Chernivtsi (Ukraine). The specific objectives of the project are: (a) to prepare a
cost-efficient UFP measurement strategy applicable in all European regions, (b) to demonstrate the applicability of the
measurement strategy in the involved cities, (c) to investigate the short-term effects of size-fractioned UFP on mortality and
morbidity in the five cities and (d) to integrate results into the regional political decision-making and concrete local measures
by developing differentiated solutions to the respective regional settings.
Methodology and Results
UFP measurements within UFIREG are performed using Differential or Scanning Mobility Particle Sizer. In addition, two
Ultrafine Particle Monitors, recently developed within the former EU project UFIPOLNET, are operated in Prague and
Augsburg. An extensive quality assurance program is an essential part of UFIREG comprising of staff training, an initial
intercomparison of the instruments and frequent on-site comparisons against reference instruments.
Preliminary results of 2012 indicate no large differences between annual averages of UFP in the size range between 20 and
200 nm at all stations (except Chernivtsi). The annual means range between 6.000 and 6.500 particles per cm³. However,
more pronounced differences were observed for weekly and monthly variation of UFP.
Conclusions
On the basis of the measured air quality data, epidemiological studies will be carried out in all participating cities. These
studies shall contribute to the environmental policy in Europe and concrete local measures by developing differentiated
solutions to the respective regional settings. Therefore, the results will be passed on to local and national policy makers,
environmental and health authorities, health insurance providers, as well as city citizens.
198
TEN YEARS OF WOODBURNER RESEARCH IN NEW ZEALAND: LESSONS LEARNED AND FUTURE
DIRECTIONS
G. Coulson (1), E. Wilton (2), E. R. Somervell (1), R. Bian (1)
(1) National Institute for Water and Atmosphere (NIWA), Auckland, New Zealand; (2) University of Auckland, Auckland,
New Zealand; (3) Auckland University of Technology, Auckland, New Zealand
Presenting author email: elizabeth.somervell@niwa.co.nz
Summary
Woodburning is the dominant source of PM10 in most of New Zealand over the winter season, and the principal cause of
exceedances of the National Environmental Standard (NES) for PM10 – a 24 hour mean concentration limit of 50 µg/m-3.
Since 2005 New Zealand researchers have used multiple techniques to characterise woodburner emission factors, and
exposures to woodsmoke in ambient and indoor air. This work reviews a decade of woodburning research, highlighting
significant findings and remaining knowledge gaps. PM10 emission factors from in situ tests exhibit a log-normal distribution
with a geometric mean of 9.8 g/kg (±2.4 g/kg) and 3.9 g/kg (±3.8 g/kg) (dry wood) for older and low-emission woodburners
respectively. The ‘user’ appears to be a significant variable which introduces substantial variability in woodburner emissions.
Associating combustion efficiency with particular households or locations remains a challenge.
Introduction
Research into the air quality impacts of burning wood for domestic heating has been carried out for some ten years in New
Zealand as a response to this being one of the primary sources of pollutant emission. Source apportionment studies, census
data and home-heating surveys, mobile monitoring of woodsmoke dominated ‘airsheds’ and in situ measurements of
woodburning emissions are all methods that have contributed to an understanding of woodsmoke in New Zealand. Interest
has principally been in emissions of particulates measured as PM10 for regulatory purposes. Consequently much of the work
carried out has been to measure PM10 emissions from woodburners under a variety of conditions. Management plans have
been predicated upon estimates of the number and type of burners in an area and what emissions can be expected from them.
Many of the worst affected regions limit the installation of new woodburners to NES compliant burners that have been
certified through laboratory testing to an emission standard of 1.5 g/kg. Targeting homes with older burners for swap out
programmes and natural attrition as older burners are replaced with lower emitting NES compliant woodburners or
alternative heating has achieved some improvements, but in many places, not as much as expected.
Methodology and Results
Measurements have often been made
in situ, that is, in volunteers’ homes,
using the woodburner as they would
normally. Figure 1 shows the range of
emission factors as grams of PM10
emitted per kilogram of wood burned
calculated daily for 39 houses that
have NES compliant woodburners
over four different studies with
comparable methodology. A wide
Fig.1 Daily PM10 emissions factors per household from in situ testing. Each box and whisker
variation of emissions can be seen in
plot represents one house with mean, upper and lower quartiles and 1st and 99th centiles
some houses compared to others. On
a “per burn” basis, the emissions behave as if they are essentially random, although
there is insufficient data to determine if they genuinely are random. The sampling
methodology is intensive and reliant upon public goodwill and so necessarily
constrained. However, without understanding the long-term variation in emissions of
individual burners it will not be possible to identify or predict “gross emitters”. The
same burner may be “clean” one day and a “gross emitter” the next.
When compared to older, non-compliant burners there has been a definite
improvement in emissions. Figure 2 shows the distribution of daily emission factors
from NES compliant and older burners. Both have lognormal distributions and
although the geometric mean has gone down (9.8 g/kg for older vs. 3.9 g/kg for
compliant burners, the variance has increased, with the geometric standard deviation
for older burners being 2.4 g/kg and ±3.8 g/kg for compliant burners. This indicates
that although ultra-low emissions may be achieved with compliant burners, high
emissions are possible with older or NES compliant burners.
Conclusions
Research carried out to date can describe the variation in emissions from compliant
and older woodburners, but is not able to explain that variation. It indicates that the
make and model of burner is not a key factor in the emissions measured, however, one
of the key variables may be behaviour. New research to investigate the causes of the
variation observed so far will require different methodologies.
Fig.2 Distribution of daily emissions
factors for old and NES compliant
woodburners
Acknowledgement
This research summarised here has been funded by NIWA, Auckland Council and Environment Canterbury.
199
A DYNAMIC PROGRAMMING APPROACH FOR AIR QUALITY PLANNING AT REGIONAL SCALE
C. Carnevale (1), G. Finzi (1), F. Padula (1), E. Turrini (1) and M. Volta (1)
(1) Department of Mechanical and Industrial engineering, University of Brescia, Brescia, Italy
Presenting author email: fabrizio.padula@ing.unibs.it
Summary
This work presents a technique to plan a cost-effective optimal control policy over a finite time horizon to improve air
quality. The air quality improvement problem is first formalized as an optimal control problem and then addressed using
dynamic programming. Clearly, in order to plan a feasible solution, the control problem is both constrained, both from the
technical and the economical side. Examples of the application of the proposed methodology over northern Italy testify the
effectiveness of the proposed solution.
Introduction
In order to define efficient air quality plans, Regional Authorities need suitable tools to evaluate both the impact of emission
reduction strategies on pollution indexes and the costs of such emission reductions. Due to difficulty to cope with the
complexity of environmental models, decision support systems are essential tools to help Environmental Authorities to plan
air quality policies that fulfill EU Directive 2008/50 requirements in a cost-efficient way. Thus, in order to improve air
quality, it appears to be of main concern to search policies capable of take into account both the environmental problem and
the economical one.
Emission reduction policies should be implemented in order to improve air quality. Clearly, the cost/benefit ratio of each
decision must be also taken into account during the strategy planning. Dynamic programming [Luenberger, 1979] offers a
powerful tool to approach this problem. It allows an iterative formalization of the environmental problem as a constrained
optimal control problem. Here, an objective function has to be minimized along a given finite time horizon. In order to obtain
a feasible reduction policy, the optimization problem must be constrained. A set of dynamic varying constraints on the
applicability thresholds of emission reductions (control variables) is considered. Finally, aimed at reducing the computational
burden, artificial neural networks are used to describe the nonlinear relations between the control variables and the output
variables (air quality indexes) over a given domain.
Methodology and Results
Given a set of technologies, a model relating an air quality index (e.g., PM10) and the application levels of those
technologies is first defined. Then, an objective function to be minimized is defined (e.g. average PM10 over Lombardia), as
well as a set of constrained over the model inputs (i.e., the technologies application levels). In particular, when minimizing
the objective function, the non-increasing property of each precursor emission and the maximum feasible reduction levels
have been constrained. Starting from this formalization, the problem is first addressed using dynamic programming. In order
to face the computational complexity of the problem, an heuristic is defined in order to find a quasi-optimal solution
[Carnevale et al., 2013]. Finally, the quasi-optimal air quality improvement plan is proven to be indeed optimal via
simulation, comparing the global optimal solution (unconstrained) to the quasi-optimal one.
Fig.1 PM10 over Lombardia, northern Italy at the beginning and at the end of the AQ improvement policy
Conclusions
Air quality and EU directive non-compliance are critical problems in some regions in Europe. The proposed dynamic
programming approach is a viable solution to assess and select effective policies on a finite time horizon in a computationally
efficient way.
References
Luenberger D. G., 1979. Introduction to Dynamic Systems, John Wiley and Sons.
Carnevale C., Finzi G., Padula F., Pederzoli A., Pisoni E., Turrini E.,Volta M., 2013.The Selection of Efficient Air Quality
Control Strategies: A Dynamic Programming Approach.ACCENT-Plus Symposium, Urbino (I).
200
A MULTI-STRESSOR, MULTI-MODAL APPROACH TO BRIDGE THE GAP BETWEEN CHEMICAL AND
PHYSICAL HEALTH STRESSORS IN URBAN AREAS
Ch. Vlachokostas (1), G. Banias (2), A. Athanasiadis (1), V. Akylas (1), Ch. Achillas (2) and N. Moussiopoulos (1)
(1) Laboratory of Heat Transfer and Environmental Engineering, Aristotle University, Greece – University Campus, P.O.
Box 483, 54124 Thessaloniki, Greece; (2) School of Economics and Business Administration, International Hellenic
University, 57001, Thermi, Greece
Presenting author email: vlahoco@aix.meng.auth.gr
Summary
In a modern urban environment, individuals are often exposed to several health stressors simultaneously, while the variations
between different modes of transport and activities add to the complexity of an already difficult to study thematic area such
as personal exposure. The Combined Environmental Stressors’ Exposure (CENSE) software, was developed (see Fig. 1) in
order to assess combined exposure in urban areas in an integrated and easy-to-comprehend manner.
Introduction
Urban areas often present high levels of environmental health stressors (physical and chemical) while they are often densely
populated by citizens (who either work, live or commute through those areas). As a result, there is a need to address
combined exposure in a more integrated way (Vlachokostas et al., 2012), since simultaneous exposure to multiple health
stressors possibly represents an increased risk to public health. The temporal and spatial variation of air quality, and
ultimately, the direct and indirect responses to human health, highlight the need to characterize an urban space according to
its environmental quality, especially if it is densely populated or usually crowded. This study demonstrates the use of the
CENSE tool, in an attempt to characterize a Greek city’s centre regarding its environmental quality.
Methodology and Results
Thessaloniki’s city centre was selected due to high stressor
concentration levels and high population density.
Concentration data for ten stressors (PM10, CO, O3, NO2,
VOCs, noise and BTEX) and for different modes of transport
was provided for two sampling periods, representing the
morning and evening rush hours. In addition to the
concentration data, stressor parameters such as weighting
factors and limit values for each stressor were defined.
Finally, after defining the desired activities and their
corresponding respiration rates and typical durations, the
Combined Exposure Indicator (CEI), Combined Exposure and
Dose Indicator (CEDI) and Normalised Combined Exposure
and Dose Indicator (nCEDI) were calculated. The area was
then characterized regarding its exposure levels according to
the above indicator values. The characterization deriving from
the CEDI and nCEDI values highly differs than the one
deriving from the CEI value and is in fact, in most cases that
are related with intense physical activities and/or activities
with high duration, worse.
Conclusions
As population density in urban centres continues to increase,
Fig.1 CENSE work flow diagram
the exposure levels as a result of human activity will continue
to deteriorate. Given the fact that citizens spend a substantial
amount of time in areas where stressor concentrations are often elevated, the need for personal exposure studies is
emphasized. The CENSE tool can be useful for decision makers in various aspects such as urban planning, transportation
infrastructure and sustainability issues as it incorporates the local characteristics into a well identified interface. It is designed
to provide a holistic and easy-to-comprehend co-exposure assessment to several chemical and physical stressors, in negligible
time. Furthermore, the tool’s flexibility derives mostly from exploiting the co-exposure indicator concept, which has
significant potential in decision making. However, combined exposure presents complexity, mainly because of the
knowledge gaps in stressor synergies and scarcity of data in transport modes and population exposure patterns. In any case,
CENSE can be useful in an effort to bridge the gap between chemical and physical stressors in urban areas, when a multistressor, multi-modal framework is under consideration.
References
Vlachokostas Ch., Achillas Ch., Michailidou A.V., Moussiopoulos N. 2012. Measuring combined exposure to environmental
pressures in urban areas: An air quality and noise pollution assessment approach. Environment International 39, 8-18.
201
HEALTH BENEFITS FROM TRANSPORT RELATED GREENHOUSE GAS EMISSION POLICIES
D. A. Sarigiannis, P. Kontoroupis, S. Karakitsios, D. Chapizanis
Aristotle University of Thessaloniki, Department of Chemical Engineering, Environmental Engineering Laboratory, 54124
Thessaloniki, Greece
Presenting author email: denis@eng.auth.gr
Summary
The objective of this work is to investigate the co-benefits to urban air quality and public health from the introduction of
greenhouse gas (GHG) emission reduction policies in the city of Thessaloniki. A number of traffic related policies are
implemented, including the introduction of underground rail in the city centre and changes in transportation modes. Traffic
pollution is assessed for the baseline scenario in year 2010 and two future scenarios in year 2020, a business-as-usual (BAU)
and a GHG emission reduction scenario (CO2 scenario).
Introduction
Using an integrated methodological framework, GHG emission reduction policies related to traffic are investigated, taking
into account for the year 2020, the presence of underground rail in the city centre and changes in transportation modes
including a higher share of diesel-fuelled, hybrid and electrical vehicles. The proposed methodological framework is data
intensive, requiring a variety of type of data including geo-referenced road geometry and building footprints, building
heights, population data per building block, traffic composition per vehicle class (passenger cars, lorries, buses, motorcycles,
mopeds and bicycles) per road, hourly traffic flow per road for typical days, hourly urban background concentration (PM10,
PM2.5, NO2, NOX, O3 and CO) and meteorological data from stations in the city centre, as well as across the Greater
Thessaloniki Area (GTA).
Methodology and Results
The aforementioned integrated methodological framework is composed of a series of interconnected models and repeated for
the years 2010 and 2020. Specifically, it includes (a) SIBYL, used to project vehicle stock numbers; (b) VISUM, utilized to
simulate traffic flow as a result of changes in travel demand; (c) COPERT IV, used to compute the pollutant emission (PM10,
PM2.5, NO2, NOX, O3, CO and benzene) per vehicle engine and type; (d) OSPM, utilized to compute pollutant concentrations
in traffic corridors; and (e) CALPUFF, used to compute pollutant concentrations on motorways and urban/peri-urban roads.
Exposure to the entire population is assessed via the inhalation pathway and its health impact is estimated by well established
concentration response functions on high resolution population data (differentiated by age and gender). The health end points
computed include the annual number of deaths attributable to PM10 and NO2 exposure and the leukaemia lifetime expected
cases due to benzene exposure, at 100x100m grid and then aggregated at the municipality level.
For the baseline year 2010, results show that the annual number of deaths for the municipality of Thessaloniki is 150 per 105
and 189 per 105 of population attributed to PM10 and NO2 and 3 per 105 of population lifetime expected cases attributed to
benzene exposure. In comparison, in suburban Panorama the computed health impacts are 65 per 105 of population and 91
per 105 of population deaths due to PM10 and NO2 exposure and 1.3 per 105 of population lifetime expected cases due to
benzene exposure.
For the business-as-usual (BAU) and the Greenhouse Gas (GHG) emission reduction scenarios, changes in traffic flow as a
result of the underground rail introduction are significant. Simulations show that traffic flow will decrease by 33% on roads
in direct proximity to the metro line (e.g. Monastiriou, Egnatia, Nea Egnatia, Delfwn), by 44% on roads within the historic
center and by 22% decrease in all adjacent roads to the historic centre. These reductions in flow are further amplified by
changes in the traffic mode, where diesel, hybrids and electric cars will constitute 22%, 7.7% and 2% respectively, to the total
vehicle fleet. Furthermore, for the municipality of Thessaloniki, the expected % decrease in the annual number of deaths for
the GHG scenario are 8% and 11% attributed to the PM10 and NO2 and 27% to the leukaemia lifetime expected cases due to
Benzene. In comparison, for the municipality of Panorama, the expected % decrease in the annual number of deaths for the
GHG scenario are 1% and 23% from PM10 and NO2 respectively and 33% to the leukaemia lifetime expected cases due to
benzene.
Conclusions
It is shown that GHG emission reduction policies will improve the air quality in the city of Thessaloniki. Specifically, the
introduction of an underground rail system will reduce PM10 concentration in the city centre, changes in vehicle composition
in favour of diesel and hybrid passenger cars reduce the NO2 and benzene concentrations in the GTA. No significant changes
in air quality are credited to the electric passenger cars since their projected market penetration is small within the time frame
of the analysis.
Acknowledgement
This work was funded partially by the European Commission through the TRANSPHORM and URGENCHE projects (EC
FP7). We acknowledge the Hellenic Institute of Transport (HIT) in CERTH, Greece for their help providing the necessary
VISUM transportation data.
202
DEVELOPMENT APPLICATION OF AIR
QUALITY AND RELATED
MODELS
203
SENSITIVITY OF THE SEMI-EMPIRICAL URBAN STREET (SEUS) MODEL TO VARIATIONS IN NO2/NOX
EMISSIONS RATIOS
S. Vardoulakis (1), N. A. Mazzeo (2) and L. E. Venegas (2)
(1) Centre for Radiation, Chemical and Environmental Hazards, Public Health England, U.K.
(2) CONICET, National Technological University, Avellaneda, Buenos Aires, Argentina
Presenting author email: sotiris.vardoulakis@phe.gov.uk
Summary
This paper explores the response of the Semi-Empirical Urban Street (SEUS) model to different input NO2/NOx emissions
ratios (f). Hourly NO2 concentrations are modelled in two street canyons in the UK, Marylebone Rd. (MR) in London and
Stratford Rd. (SR) in Birmingham for different f. The statistical evaluation of the model results indicatesthat the best
agreement between modelled and observed NO2 concentrations is for f of 15-20% in MR and 10-15% in SR. The higher
NO2/NOx emissions ratio in MR is consistentwith the higher fraction of heavy duty vehicles in this street compared to SR.
Introduction
Long-term exposure to ambient concentrations of NO2, which arehigher near busy roads (Vardoulakis et al., 2011), has been
associated with all-cause mortality (Hoek et al., 2013). Dispersion modelling studies of ambient NO2 in urban areas in the
UK, usually take into account a fraction of NOx directly emitted by vehicles as NO2 of approximately 5-10%. However,
recent studies have indicated that the increasing number of diesel engines and heavy duty vehicles may result in higher
NO2/NOx emissions ratios. Diesel cars have higher NO2/NOx emissions ratios compared with petrol cars. Also, higher
f=NO2/NOx emissions ratios have been observed at low vehicle speeds. Therefore, f generally varies with fleet composition
and traffic flow conditions. The Semi-Empirical Urban Street (SEUS) model (Mazzeo et al., 2012) includes a simple
photochemistry algorithm between NO, NO2 and O3 which accounts for the fraction f, which is user defined. SEUS has been
applied to estimate NO2 hourly concentrations in two street canyons in the UK, Marylebone Rd. (MR) and Stratford Rd. (SR)
for varying f values. Model estimates are statistically evaluated to determine the range of f that gives the best agreement with
observations for each site.
Methodology and Results
One year of NO2hourly concentrations are modelled in MR and SR using
Table 1. Evaluation of the agreement between
SEUS with f(%)=NO2/NOx=5, 10, 15, 20, 25.MR is a busy dual observed and estimated hourly NO2 concentrations
carriageway road in central London and SR is a busy street with two traffic
for different fractions of primary NO2
lanes in Birmingham. Annual average daily traffic was 76,000vehicles/day
MARYLEBONE Rd.
Mean
FA2
in MR and 22,000vehicles/day in SR over the assessment period.
NMSE
R
FB
(ppb)
(%)
The average vehicle speed was 10-30km/h in MR and10-25km/h in SR,
Observed
54.48
while the fraction of heavy duty vehicles was around 12% in MR and 5% in
43.09 0.27
0.58 84.8 0.234
SR. Permanent air quality monitoring stations are operated in both streets f: 5%
f:10%
47.85 0.20
0.61 88.5 0.130
and therefore observed NOx and NO2 hourly concentrations are available.
f:15%
52.59 0.17
0.63 90.1 0.035
Model estimates for different f values are compared with observations at f:20%
57.32 0.17
0.64 89.8 -0.051
both streets. The statistical evaluation of model results (Table 1) includes f:25%
62.02 0.20
0.64 88.3 -0.129
the comparison of (Chang and Hanna, 2004): mean concentrations;
STRATFORD Rd.
normalised mean square error (NMSE); correlation coefficient (R); fraction Observed 25.65
of model predictions within a factor two (FA2) and fractional bias (FB). f: 5%
24.03 0.17
0.79 91.5 0.065
25.62 0.15
0.80 91.7 0.001
There is generally a good agreement between calculated and observed NO2 f:10%
27.21 0.16
0.80 91.1 -0.059
hourly concentrations at both sites, with the best agreement between SEUS f:15%
f:20%
28.79 0.17
0.79 90.3 -0.115
results and observations for f=15-20% in MR and f=10-15% in SR.
30.36 0.20
0.79 89.1 -0.168
Taking into account that annual mean background ozone concentrations in f:25%
London and Birmingham were quite similar (19-20 ppb), the differences in f(%) giving the best fit with the observations at
each site are likely to be due to the difference in the fraction of heavy duty vehicles using the two streets.
Conclusions
SEUS estimates of NO2 hourly concentrations are sensitive to variations in input NO2/NOx emissions ratios. This sensitivity
has been used to explore the NO2/NOx emissions ratio in Marylebone Rd. (London) and in Stratford Rd. (Birmingham). The
higher f for MR than for SR is consistent with the higher fraction of heavy duty vehicles in MR.
Acknowledgement
This work was supported by CONICET-PIP 0304. The authors wish to thank the British Atmospheric Data Centre for data
used in this study.
References
Chang J.C., Hanna S.R. 2004. Air quality model performance evaluation. Meteor. Atmos. Physics 87, 167-196.
Hoek G., Krishnan R., Beelen R., Peters A., Ostro B., Brunekreef B., Kaufman, J. 2013. Long-term air pollution exposure and cardiorespiratory mortality: a review. Environ. Health 12, 43.
Mazzeo N.A., Dezzutti M.C., Venegas L.E. 2012. A Semi-Empirical Urban Street Canyon Model. Proc. 8th Int. Conf. on Air Quality-Science
and Appl., 825-828.
Vardoulakis S., Solazzo, E., Lumbreras J. 2011. Intra-urban and street scale variability of BTEX, NO2 and O3 in Birmingham, UK:
Implications for exposure assessment. Atmos. Environ. 45, 5069-5078.
204
DOWNSCALING MESOSCALE WIND FIELDS THROUGH A MASS-CONSISTENT MODEL TO DRIVE
DISPERSION SIMULATIONS WITH ADMS
P. Brotto (1)(3), F. Cassola (1)(3), A. Mazzino (2)(3) and P. Prati (1)(3)
(1) Department of Physics & INFN, University of Genoa, via Dodecaneso 33, 16146, Italy; (2) Department of Civil,
Chemical and Environmental Engineering & INFN, University of Genoa, via Montallegro 1, 16145, Italy; (3) PM_TEN srl,
via Dodecaneso 33, 16146, Italy
Presenting author email: cassola@fisica.unige.it
Summary
We discuss here the outcomes of an experiment, in which we used the high-resolution wind field obtained by coupling the
mesoscale meteorological model WRF with the diagnostic mass-consistent code WINDS to drive pollutant dispersion
simulations with the ADMS model in a very complex topography area. The obtained concentration fields have been
compared with a reference case, in which the wind field is reconstructed from point values by the ADMS meteorological preprocessor. This kind of approach is a significant step towards the realization of an integrated multiscale air quality forecasting
system.
Introduction
At present, Numerical Weather Prediction (NWP) models can provide wind forecast information on scales up to a few
kilometres but for several applications, like in particular simulation of pollutant dispersion, wind prediction on scales smaller
than 1 km is desirable. In principle, increasing the NWP model resolution might provide considerable improvement in the
representation of smaller-scale flows. Nevertheless, an open question remains as to whether the increasing computational
requirements for running very high-resolution NWP models are compensated by a corresponding improvement of the
forecast skill. In order to overcome these drawbacks, diagnostic models can be used to simulate three-dimensional wind
fields over complex terrain. Such models can be nested in a NWP model to obtain higher-resolution wind fields on a smaller
integration domain. Moreover, thanks to their simplicity, the computational effort needed by diagnostic codes is considerably
reduced. The downscaling methodology proposed here is based on the diagnostic mass-consistent model WINDS (Wind-field
Interpolation by Non Divergent Schemes), cascaded to the state-of-the-art non-hydrostatic mesoscale model WRF (Weather
Research and Forecasting; Skamarock et al., 2008). WRF is currently operational at the Department of Physics (DIFI) of the
University of Genoa in a three-grid configuration and provides atmospheric fields forecasts with resolutions up to about 1 km
over the territory of Liguria Region.
Methodology and Results
WINDS is a diagnostic mass-consistent code developed at DIFI to perform three-dimensional wind flow simulations over
complex terrain (Ratto et al., 1994; Burlando et al., 2007). This model performs the simulation in two steps: a first guess
wind field is built by both horizontal and vertical interpolation of measured or assumed data of various kinds (wind speed
upon the ground, aloft wind, vertical wind profiles, etc.); the final field is then calculated by imposing the constraint of mass
conservation. In order to downscale the WRF wind fields, defined on a 1.1 km-spaced horizontal grid and on constant
pressure surfaces, essentially flat, along the vertical, a specific procedure has been implemented in WINDS. The interpolation
is applied not only to the wind velocity components, but also to all the variables of interest in the description of the PBL
physics, such as surface heat flux, Obukhov length and friction velocity. Then, the meteorological information provided by
WRF can be combined with the WINDS topography and roughness data, in order to build the initial wind profiles on every
node of the WINDS horizontal grid. In particular, the profiles in the surface layer are constructed starting from classical
profiles derived from the Monin-Obukhov similarity theory under the constraint of a minimal modification of the original
WRF profiles. The final field is then obtained by imposing to the first-guess wind field the mass conservation. A validation of
the proposed downscaling methodology, through a comparison with anemometrical data on the Ligurian territory, indicated a
significant improvement in the prediction of wind speed, especially for strong wind events over complex topography. The
downscaled wind fields can then be used to drive air quality simulations. In particular, we used the high-resolution (about
200 m) wind fields provided by WINDS to simulate the dispersion from a given point source with the ADMS model and
compared the results with a reference case, in which the wind field was reconstructed from values in a given point by the
ADMS meteorological pre-processor (based on the linearized FLOWSTAR model).
Conclusions
A downscaling methodology has been developed to provide high-resolution wind fields to drive air quality simulations with
the ADMS model. Through this kind of approach an integrated multiscale air quality forecasting system is planned to be
implemented, using ADMS to refine the concentration fields provided by the mesoscale Eulerian chemical transport model
CAMx, already operational at the Department of Physics.
References
Burlando M., Georgieva E., Ratto C.F., 2007. Parameterisation of the planetary boundary layer for diagnostic wind models.
Bound. Layer Meteor. 125(2), 389–397.
Ratto C.F., Festa R., Romeo C., Frumento O.A., Galluzzi M., 1994. Mass-consistent models for wind fields over complex
terrain: the state of the art. Environ. Software 9, 247-268.
Skamarock W.C., Klemp J.B., Dudhia J., Gill D.O., Barker D.M., Huang X.Z., Wang W., Powers J.G., 2008. A Description
of the Advanced Research WRF Version 3, Mesoscale and Microscale Meteorology Division, NCAR, Boulder, Colorado.
205
TIME EVOLUTION OF OZONE PRODUCTION FROM VOCS
K. A. Mar (1), J. Coates (1), S. Zhu (1), T. M. Butler (1)
(1) Institute for Advanced Sustainability Studies e.V. (IASS Potsdam), Berliner Strasse 130, D-14467 Potsdam
Presenting author email: kathleen.mar@iass-potsdam.de
Summary
This study attributes tropospheric ozone formation to emissions of VOC precursors by tagging the chemical mechanisms in a
box model and in a 3-D regional model over a European domain. We find that alkanes, in comparison to other VOCs, have a
high potential to form ozone over longer (multiple-day) timescales. The extent to which this delayed reactivity leads to ozone
production downwind of VOC emission sources will be explored. These results may be relevant for designing strategies to
reduce ambient ozone concentrations.
Introduction
Achieving air quality standards for ozone in Europe continues to be a challenge, in large part due to the complex relationship
between ambient ozone concentrations and the emissions of its precursor gases, in particular nitrogen oxides (NOx) and
volatile organic compounds (VOCs). While emissions of NOx and total VOCs in Europe have shown robust decreases since
the 1990s, concentrations of ozone, which is formed from reactions of VOCs and NOx in the presence of sunlight (Atkinson,
2000), have either remained stable or increased (Colette et al., 2011). In this study we use a box model and a 3-D regional
model to probe the detailed pathways for ozone formation from VOC precursors. In particular, we attribute production of odd
oxygen (Ox, which represents ozone and the family of molecules that rapidly interconvert with ozone including NO2, oxygen
atoms, and reservoir species) to emissions of specific VOCs. Further, we investigate how the reactivity of emitted VOCs
evolves over time. This type of detailed understanding of VOC reactivity is necessary to inform emission reduction strategies
aimed at reducing ozone levels in Europe.
Methodology and Results
We attribute modeled production of Ox to emissions of primary VOC using a tagging approach (Butler et al., 2011), in which
VOC oxidation intermediates are tagged with the identity of the primary emitted compound, allowing the formation of Ox to
be directly traced back to an emitted VOC. Using this approach in a photochemical box model, we calculated daily Tagged
Ozone Production Potentials (TOPPs), which represent the maximum potential of an emitted VOC species to result in the
production of Ox over the course of a day (Butler et al., 2011). As shown in Fig. 1, we find that the multi-day TOPP profiles
are noticeably different for different types of hydrocarbons. In particular, the TOPP of alkanes remains significant over
multiple days and doesn’t peak until the
second day of photochemical processing,
whereas for alkenes, the TOPP peaks on the
first day and drops sharply thereafter. This
suggests that alkanes in particular could
continue to significantly affect ozone
production downwind of the original
emissions
source.
To
quantitatively
investigate this question, we set up the WRFCHEM model over Europe for tagging
implementation. With this regional model we
aim to evaluate the degree to which the TOPP
of VOCs is reached under realistic
atmospheric conditions and evaluate the
geographical extent to which VOC emissions
affect ozone production in the region
surrounding the emissions source.
Conclusions
Despite successful efforts to reduce precursor emissions, ozone pollution remains a problem in Europe. Understanding this
problem demands a better understanding of the complex chemical and meteorological processes leading to ozone formation.
In this study we explored the detailed, time-dependent photochemical evolution of VOCs and presented work towards
examining how this chemistry impacts ozone formation downwind of emission sources. This analysis could inform new
approaches to air quality management.
References
Atkinson, R., 2000. Atmospheric Chemistry of VOCs and NOx. Atmos. Environ. 34, 2063-2101.
Butler, T. M., Lawrence, M. G., Taraborrelli, D., and Lelieveld, J., 2011. Multi-day Ozone Production Potential of Volatile
Organic Compounds Calculated with a Tagging Approach. Atmos. Environ. 45, 4082-4090.
Colette, A., Granier, C., Hodnebrog, Ø., et al., 2011. Air Quality Trends in Europe Over the Past Decade: A First MultiModel Assessment. Atmos. Chem. Phys. 11, 11657-11678.
206
MATCH-SALSA - MULTI-SCALE ATMOSPHERIC TRANSPORT AND CHEMISTRY MODEL
COUPLED TO THE SALSA AEROSOL MICROPHYSCIS MODEL
C. Andersson (1), R. Bergström, (1,2), H. Kokkola (3), C. Bennet (1), M. Thomas (1), H. Korhonen (3), K. Lehtinen (3) and L.
Robertson(1)
(1) Swedish Meteorological and Hydrological Institute, SE-60176 Norrköping, Sweden; (2) University of Gothenburg,
Department of Chemistry, SE-41296 Göteborg, Sweden; (3) Finnish Meteorological Institute, Kuopio Unit, P.O. Box 1627,
FI-70211 Kuopio, Finland
Presenting author email: camilla.andersson@smhi.se
Summary
The aerosol dynamics module SALSA (Kokkola et al., 2008) has been implemented in the regional scale chemistry transport
model MATCH (Robertson et al., 1999) and the resulting model, MATCH-SALSA (Andersson et al., 2013), has been
evaluated. The new part of the model describes particle number size distribution and growth processes.
Introduction
The demand for improved representation of aerosols in
atmospheric models has increased during recent years; more
accurate and detailed description on aerosol size distribution
and chemical content is needed both for estimating impact of
particles on radiative forcing and in health impact
investigations. For this reason aerosol dynamics was
introduced in the MATCH-model, and the resulting model
was evaluated and tested for sensitivities to different
parameterisations and input data.
Methodology and Results
The model was evaluated using measurement data from
EBAS (http://ebas.nilu.no) of particle number size
distribution, particle mass and chemical species. The new
model underestimates the total particle number concentration
(PNC) at northerly sites, and overestimates at K-Puszta. The
modelled total PNC is very sensitive to the fractions of SOx
emitted as different oxidated states of sulphur (sulphur
dioxide, sulphuric acid, sulphate). Further, the growth by
condensation seems to be underestimated. This is expected
since the new model does not yet include coupling between
particle growth and nitrogen partitioning between the gasand solid phase. The new model does includes simplified
secondary organic chemistry coupled to the aerosol
dynamics. Future development of this should improve the
model performance. The new model includes coupling
between cloud dynamics and wet scavenging of particles.
The results indicate that such advanced handling of particle
wet scavenging does not improve the model performance on
PNC.
Conclusions
A new model called MATCH-SALSA has been developed.
Sensitivity test using the new model indicates that coupling
of particle activation in clouds to wet scavenging has little
effect on ground level concentrations. The model needs to be
further improved in terms of condensation processes in order
to describe particle growth more accurately. The distribution
of SOx emission on oxidative state of sulphur strongly
affects the PNC.
Acknowledgement
This work was conducted within the Swedish Clean Air
Programme, SCARP, funded by the Swedish EPA.
References
Andersson, C. et al., 2013. MATCH-SALSA – Multi-scale atmospheric transport and chemistry model coupled to the
SALSA aerosol microphysics model. SMHI report and manuscript to be submitted to Geophys. Model Develop. Discuss.
Kokkola, H. et al., 2008. SALSA – a sectional aerosol module for large scale applications. Atmos. Chem. Phys. 8, 2469-2483.
Robertson, L. et al., 1999. An Eulerian limited-area atmospheric transport model. J. Appl. Meteor. 38, 190–210.
207
MEASUREMENTS AND MODELLING OF BLACK CARBON IN TWO CITIES IN SOUTH-WEST SPAIN
C. Milford (1,2), R. Fernández-Camacho (1), A. Sánchez de la Campa (1), S. Rodríguez (2), N. Castell (3), C. Marrero (2), J.
De la Rosa (1) and A. F. Stein (4)
(1) University of Huelva, Joint Research Unit to CSIC “Atmospheric Pollution”, Huelva, Spain;
(2) Izaña Atmospheric Research Center, AEMET, Tenerife, Spain; (3) Norwegian Institute for Air Research (NILU), Kjeller,
Norway; (4) Earth Resources and Technology on assignment to Air Resources Laboratory, NOAA, MD, USA.
Presenting author email: cmilford@aemet.es
Summary
Black carbon (BC) has been measured and simulated for two city sites in south-west Spain with high temporal resolution
(1 h). The daily variation at each site and the spatial variation between sites were captured by the modelling system. The
parallel measurement and modelling of BC constitutes a useful tool to characterise and quantify the behaviour and dynamics
of this species.
Introduction
Black carbon has been identified as one of three key short-lived climate forcers (SLCFs) for which emission reduction
measures would contribute to slowing near-term climate change while having the additional benefit of improving air quality
and thereby reducing the adverse health effects of air pollution (UNEP and WMO, 2011). In addition, BC has been identified
as a more sensitive indicator to vehicle exhaust related air pollution compared with other regulated pollutants such as PM10
and PM2.5. A BC measurement program with high temporal resolution was initiated in two cities in south-west Spain in 2012
to characterise the behaviour of this species. In addition, the three-dimensional air quality model (CAMx) was implemented
to investigate the dynamics of this primary aerosol and its spatial and temporal resolution. This study presents measurements
and modelling of BC for a winter period from this measurement dataset.
PM2.5 EBC (g m-3)
PM2.5 EBC (g m-3)
16
Methodology and Results
a) Seville
Meas
14
Sim
Black Carbon was measured in two cities, Seville (700,000
12
inhabitants) and Huelva (150,000 inhabitants), in the south-west of
10
Spain. Hourly measurements of black carbon in PM10 were conducted
8
with a Multi-Angle Absorption Photometer and these were converted to
6
equivalent black carbon (EBC) measurements for each site by
4
comparing with PM10 samples collected in a high volume sampler (68
2
0
m3 h-1) analysed for EC in the laboratory using the Thermo Optical
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
Transmittance technique (see Fernandez-Camacho et al., 2010). The
16
b) Huelva
Meas
site specific mass absorption cross sections obtained were 9.79 and
14
Sim
10.31 m2 g-1 for Seville and Huelva, respectively. The mean
12
PM2.5/PM10 BC ratio (0.74 ± 0.025) was utilised to determine the PM2.5
10
8
BC concentration (Fernandez-Camacho et al., 2010). Primary
6
Elemental Carbon (PEC) was simulated using CAMx driven by the
4
MM5 meteorological model, both models used three nested domains
2
with 18 x 18 km, 6 x 6 km and 2 x 2 km horizontal resolution.
0
Emissions of PEC include those from on-road traffic and from large
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
Day (Jan 2013)
industrial sources. Results of the measured and simulated PM2.5 EBC
concentrations at the two sites are shown in Fig. 1 for 2-17 January
Fig.1 Measured PM2.5 EBC and simulated PM2.5 PEC
2013. This demonstrates that the modelling system is capable of
concentrations at a) Seville and
capturing both the temporal variation at each site and the spatial
b) Huelva, 2-17 Jan 2013.
variation between sites. The mean and maximum PM2.5 EBC
concentration observed at the Seville site were 1.8 μg m-3 and 10.9 μg m-3 during this winter period. At the Huelva site the
observed concentrations were lower; the mean concentration was 0.7 μg m-3 and the maximum 5.7 μg m-3. The modelling
system tended to overestimate the peak concentrations at the Seville site (Mean Bias = 0.6 μg m-3) while slightly
underestimating the concentrations at the Huelva site (Mean Bias = -0.1 μg m-3).
Conclusions
A measurement and modelling program has been initiated in south-west Spain to characterise the concentrations and
behaviour of black carbon in two different cities. This will aid us in understanding the dynamics of this primary aerosol and
as regulatory pressure continues to reduce particulate emissions from vehicle traffic, the parallel measurement and modelling
of BC constitutes a useful tool to both guide and monitor any proposed traffic emission reduction measures.
Acknowledgement
The authors gratefully acknowledge funding from the Department of Environment, Andalusian Regional Government
(project: 168/2011/C/00) and the Spanish Ministry of Economy and Competitiveness (POLLINDUST: CGL2011-26259).
References
UNEP and WMO, 2011. Integrated Assessment of Black Carbon and Tropospheric Ozone, United Nations Environment
Program and World Meteorological Organization, Nairobi, Kenya, 2011.
Fernández-Camacho, R., Rodríguez, S., de la Rosa, J., Sánchez de la Campa, A. M., Viana, M., Alastuey, A. and Querol X.,
2010. Ultrafine particle formation in the inland sea breeze airflow in Southwest Europe. Atmos. Chem. Phys. 10, 9615–9630.
208
A METHODOLOGY TO ESTIMATE PM10 OUTDOOR URBAN CONCENTRATIONS USING GLM
J. M. Garcia (1), F. Teodoro (1), R. Cerdeira (1), L. M. R. Coelho (1), M. G. Carvalho (2)(3)
(1) Escola Superior de Tecnologia de Setubal, Instituto Politécnico de Setúbal, Campus do IPS, 2910-761 Setúbal, Portugal
(2) Instituto Superior Técnico, Portugal, (3) European Parliament Brussels, Belgium
Presenting author email: joao.garcia@estsetubal.ips.pt
Summary
This study presents a methodology that uses Generalized Linear Model (GLM) to predict PM10 concentrations based in the
previous study of the relations between PM10 air concentrations and CO, NO2, NOx, VOCs, SO2 atmospheric concentrations,
but also meteorological variables as air temperature, relative humidity and wind speed. The study is applied to a particular
city (Barreiro, Portugal) and the model uses data from the monitoring air quality stations Portuguese network, and
meteorological data. The developed GLM consider as dependent variable (or response variable) PM10 outside air
concentrations, and considers as explanatory independent variables or covariates the air concentrations of pollutants NO2,
NOx, CO, O3 but also meteorological variables, air temperature, relative humidity and wind speed. A logarithmic link
function was considered with a Poisson probability distribution. The studied model includes detailed inspection for cases
with maximum air temperature below 25ºC and maximum air temperature above 25ºC. Results indicate that best performance
is achieved for model considering only data with maximum air temperature values above 25ºC (R2=0,649) when compared
with model considering all data (R2=0,386) and also when compared with model that considerers only data with maximum
air temperature below 25ºC (R2=0,149). The best performance model was tested with data from other Portuguese city
(Oporto) showing reasonable fit results.
Introduction
In past recent, the concern about air quality has growth mainly due to the increasing knowledge of relations between
respiratory problems, especially in children’s and air pollution. In the case of PM, is known that airborne particulate matter
has its origin in a wide variety of natural and anthropogenic sources. Some particles are directly emitted into the atmosphere
and others may be formed in the air as a result of the chemical reaction of gases. Articles dedicated to study the contribution
to air pollution from different sources, conclude that there is a strong relation between gaseous air pollutants and atmospheric
PM.
Methodology and Results
General Linear Model (GLM) (Nelder et Wedderburn, 1972) was used to building a methodology to estimate PM10 outside
concentrations, based on known values of other outside gaseous air pollutant concentrations. GLM are based in the
assumption that there are K independent values Y1, ..., YK, from a variable of interest or response variable (effect) that
follows an exponential family distribution with expected value E (Yi) = μi [Conceição et al, 2001]. Considering K vectors xi
= (1 xi1 x12 … xip)t, i=1, ..., K, containing the values of p explanatory variables, independent or covariates. A link
logarithmic function was considered and Yi has a Poisson distribution, the model results in a Poisson regression model and
each term βi is the effect of variable Xi in g (μi). In fact, βi represents the “effect” of variable Xi in the function g(µi). In this
case the objective is to estimate PM10 concentration values based on other variables, which are gaseous air pollutant
concentrations namely CO, NO2, NOx, O3 and SO2 but also meteorological variables namely temperature (T,ºC), relative
humidity (RH,%) and wind velocity (WV, m/s). Statistical Package software for Social Sciences SPSS 10.0 for windows was
used to build and analyse the model.
Conclusions
Results show that model considering all data predicts, poorly results for PM10 concentrations (R2=0,386) but when two sub
models were developed, considering only data with the criteria of maximum temperature of air i) above 25ºC and ii) below
25ºC results improved substantially. Comparisons of the three models show that best performance results are achieved for
model with values of Tmax air>25ºC (R2=0,649) showing the importance of air temperature in the formation of the secondary
particles in air.
Acknowledgement
The authors wish to acknowledge Comissão de Coordenação e Desenvolvimento Regional de Lisboa e Vale do Tejo (CCDRLVT) and Instituto de Metereologia (IM) by the information provided.
References
Nelder J.A., Wedderburn R.W.M. (1972). “Generalized linear models”. J R Stat Soc A; 35: pg 370-84.
Conceição G.M.S, Saldiva P. H. N.,Singer J. M., (2001). “Modelos MLG e MAG para análise da associação entre poluição
atmosférica e marcadores de morbi-mortalidade: uma introdução baseada em dados da cidade de São Paulo”. Rev. Bras.
Epidemiol. 206 Vol. 4, Nº 3, pp 206-219.
209
IMPLEMENTATION OF THE ON LINE COUPLED MODEL WRF/CHEM OVER THE PO VALLEY
C. Carnevale (1), G. Finzi (1), E. Pisoni (2), A. Pederzoli (1), E. Turrini (1), M. Volta (1)
(1) Department of Industrial and Mechanical Engineering (DIMI), University of Brescia, Via Branze 38, 25123
Brescia, Italy
(2) European Commission – Joint Research Centre (JRC), Via Fermi, 2749 - 21027 Ispra (VA) - Italy
Presenting author email: carneval@ing.unibs.it
Summary
This study presents the preliminary results related to the implementation of the on line coupled atmospheric model
WRF/Chem over the Po valley. O3 surface concentrations over a 6x6 km2 resolution domain are compared to observations
provided by approximately 300 monitoring sites distributed across the area.
Introduction
The Po Valley, one of the most industrialized and highly populated areas in Northern Italy, is characterized by very high
levels of ozone and particulate matter concentrations, which often exceed the European air quality standards. This is due to
high urban and industrial emissions as well as frequent stagnant meteorological conditions (low wind speed and temperature
inversions) associated to the complex topography of the area. In order to provide a good estimate of the air quality state in
this region, a detailed description of both meteorological and air quality conditions is therefore required. This work aims at
describing both the meteorology and the spatial and temporal distribution of particulate and ozone concentrations over the Po
Valley through the application of an on-line atmospheric coupled model (WRF/Chem).
Methodology and Results
The fully coupled ‘‘on-line’’ Weather Research and Forecasting/Chemistry (WRF/Chem) model, developed by the National
Oceanic and Atmospheric Administration (NOAA), simulates the emission, transport, mixing and chemical transformation of
trace gases and aerosols simultaneously with the meteorology. The model is used for air quality and weather forecast as well
as for studying interactions between meteorology and chemistry (i.e. aerosols feedback). The air quality component of the
model is fully consistent with the meteorological one, given by the non-hydrostatic model WRF; they both use the same
transport scheme (mass and scalar preserving), the same grid (horizontal and vertical components), and the same physics
parameterizations. Several chemical schemes can be selected in WRF/Chem, including the Regional Acid Deposition Model
(RADM2, Stockwell et al., 1990) and the Carbon Bond 4 (CB-4, Gery et al, 1988). The chemistry package also includes dry
deposition (‘‘flux-resistance’’ method), biogenic emission treatment and the MADE/SORGAM aerosol parameterization
scheme.
The model has been installed on a parallel machine at University of Brescia. A monthly run was carried out on a 6x6km2
resolution grid covering Northern Italy. Emissions at at 6x6 km2 resolution for CO, NH3, NOX, SO2,VOC provided by the
POMI exercise (http://aqm.jrc.ec.europa.eu/POMI/index.html) have been used. Emissions have been temporally speciated by
using temporal profiles from the POMI website. The VOC chemical speciation has also been preformed for the RADM
chemical scheme. NCEP operational data at 1 degree resolution (http://da.ucar.edu) were used as input for WRF. BC and
initial conditions were extracted from the global model MOZART. An example of WRF/Chem output is given in figure 1.
Output modeled concentrations have been compared to observations provided by monitoring stations across Northern Italy
(figure 2).
Fig.1. Example of WRF/Chem output. Map of O3
hourly ozone concentration. Units:ppmV
Fig 2. Scatter plot of observed versus modelled
surface O3 hourly concentration. Units:gm-3of
WRF/Chem output. Map of O3 hourly ozone
Conclusions
The aim of this study is to describe in detail the temporal and spatial distribution of O3 and PM concentrations over the Po
Valley, through the use of the on line model WRF/Chem. A comparison with observations from 300 monitoring sites has
been carried out. Future sensitivity tests will be performed in order to indentify the best model configuration to be used for
emission scenarios studies over the area.
References
Gery, M. W., G. Z. Whitten, and J. P. Killus (1988): “Development and Testing of the CBM-IV For Urban and Regional
Modeling,”, EPA-600/ 3-88-012, January.
Stockwell, W. R., Middleton, P., Chang, J. S., and Tang, X., 1990: The second generation regional acid deposition model
chemical mechanism for regional air quality modeling, J. Geophys. Res. 95, 16343–16367.
210
IMPACT OF SHIPPING EMISSIONS FROM A MEDITERRANEAN PORT CITY BY COUPLING OF THE
MESO-SCALE MODEL BOLCHEM WITH THE MICRO-SCALE MODEL ADMS-URBAN
R. Cesari (1), R. Buccolieri (2), A. Maurizi (3), R. Quarta (2) and S. Di Sabatino (2)
(1) National Research Council, Institute of Atmospheric Sciences and Climate, S. P. Lecce-Monteroni km 1.2, 73100, Lecce,
Italy;
(2) University of Salento, Dipartimento di Scienze e Tecnologie Biologiche ed Ambientali, S.P. Lecce-Monteroni km 1.2,
Lecce, Italy;
(3) National Research Council, Institute of Atmospheric Sciences and Climate, via Gobetti 101, 40100, Bologna, Italy
Presenting author email: r.cesari@isac.cnr.it
Summary
This study aims to evaluate the contribution of shipping emissions to local concentration in a port city located in southern
Italy, using a numerical approach based on the off-line coupling of the meso-scale model BOLCHEM (Mircea et al., 2006)
with the micro-scale advanced-Gaussian model ADMS (CERC Ltd). The potential benefit of this coupling is tested.
Simulations are performed during summer and winter period in the year 2010. Overall, a larger contribution to the total
concentration levels is found for NOx (with peaks up to 40%), while for PM concentration the contribution is below 10%.
Introduction
Maritime transport represents a major source of air pollution in the world (Mueller et al., 2011). In this context, the project
CESAPO (Contribution of Emission Sources on the Air Quality of the Port-cities in Greece and Italy –
www.cesapo.upatras.gr), implemented in the frames of the European program INTERREG “European Territorial
Cooperation Programme Greece-Italy 2007-2013” has the objective to quantify the impact of maritime activities of the port
of Patras (Greece) and Brindisi (Italy) on air quality. Here we present some numerical results obtained in the area of port of
Brindisi, one of the main port city on the south Adriatic coast of Italy, in Apulia region, characterized by a traffic volume of
over 2,000 ships/year. Numerical simulations, using ADMS dispersion model coupled with the meso-scale model
BOLCHEM, for both NOx, O3 and primary PM concentrations are presented and the impact of maritime activity is evaluated.
Methodology and Results
BOLCHEM simulations have been performed over the Apulia region domain with the inclusion of anthropogenic emissions
from all the sources with the exclusion of the shipping emissions. The meso-scale model is then used to calculate
meteorological input variables and background concentrations which were then fed into the micro-scale model. Shipping
emission inventory used as input in ADMS has been built according to the MEET methodology (Trozzi and Vaccaro, 1998)
on the basis of the knowledge of local maritime traffic volume and specific parameters of the ships available from the
Avvisatore Marittimo (http://www.porto.br.it/bpi/index.php) of the Brindisi port. Numerical simulations were evaluated using
data from monitoring stations (managed by the Regional Agency for Environmental Protection ARPA-Puglia). Analyses of
numerical results show that, in line with findings in several Italian ports, shipping emissions and associated concentrations
are dependent on seasonality, as summer emissions are about 10% larger compared to the winter ones and are also associated
to low wind speed. A larger contribution to the total concentration levels is found for NOx (with peaks up to 40%), while for
PM concentration the contribution is below 10%. Predictions obtained by coupling of a meso-scale model to a micro-scale
dispersion model are improved when using wind fields and background concentration produced by downscaling BOLCHEM
output as initial and boundary conditions.
Conclusions
As ship emissions are expected to continue to increase in future years and since numerical results in the area of Brindisi put
into evidence that their impact on air quality concentration levels is not negligible, there is a need to account for NOx and PM
emissions in the assessment of air quality in port cities. This study is also the first attempt of coupling BOLCHEM with a
microscale dispersion model. Results are encouraging which further suggest the usefulness of such approach.
Acknowledgement
This work was supported by European Territorial Cooperation Programme Greece-Italy 2007-2013 CESAPO (Contribution
of Emission Sources on the Air quality of the Port-cities in Greece and Italy) project. The authors wish to thank CERC Ltd
for making available ADMS model, ARPA Puglia for concentration data, Avvisatore Marittimo of Brindisi port for traffic
maritime data and the Italian Air Force for meteorological data.
References
CERC Ltd. ADMS model. Available from Cambridge Environmental Research Consultant, Cambridge, UK.
http://www.cerc.co.uk
Mircea, M., D’Isidoro, M., Maurizi, A., Vitali, L., Conforti, F., Zanini, G., Tampieri, F. 2006. A comprehensive performance
evaluation of the air quality model BOLCHEM to reproduce the ozone concentrations over Italy. Atmospheric Environment
42, 6, 1169-1185.
Mueller, D., Uibel, S., Takemura, M., Klingelhoefer, D., Groneberg, D.A., 2011. Ships, ports and particulate air pollution –
an analysis of recent studies. Journal of Occupational Medicine and Toxicology, 6:31.
Trozzi, C., Vaccaro, R., 1998. TECHNE report MEET RF98, Methodologies for estimating air pollutant emissions from
ships, August 1998.
211
ADVANCED ODOUR DISPERSION MODELLING IN A NEW ENVIRONMENTAL INFORMATION SYSTEM
U. Uhrner (1), G. Grosso (1), D. Öttl (2)
(1) Institute for Internal Combustion Engines and Thermodynamics, Graz University of Technology, 8010 Graz Austria,
(2) Dep. 15 Housing, Energy and Engineering, Provincial Government Styria, 8010 Graz
Presenting author email: grosso@ivt.tugraz.at
Summary
This work aims to present the development of a new specific odour dispersion model which is embedded in a communitybased environmental monitoring and information system using citizen’s information. A specific odour dispersion model will
be developed to obtain interrelated spatial odour exposure levels due to the release by the sources. First promising results
using the new dispersion model were obtained in transient simulations for PM10 within the EU project PMinter.
Introduction
Odours from industry or livestock breeding are a great deal of annoyance for neighbours in rural and urban locations and they
are listed as the second source of complaints by ADEME in France and the Environmental Policy in Wallonia (Belgium). The
EU RP7 project OMNISCIENTIS brings together state of the art technologies and open communication capabilities to
mitigate odour annoyance. Odour cannot be monitored or regulated like a pollutant: its perception is linked to a human sense
and it must be evaluated in terms potential annoyance on people (Nicolas et al., 2010). The level of the annoyance depends in
a complex way on the release and strength of odour emissions, their dispersion under ambient conditions and finally on the
exposure and perception of citizens. Particular care has to be devoted to one peculiar characteristic of odour human
perception: few minutes above the perception threshold are enough to give the impression of odour annoyance. Such a
phenomenon, which was demonstrated by several studies and researches, cannot be neglected for a proper modelling of odour
impact. So far, dispersion models use hourly or half hourly meteorological data and if available simple temporal cycles (e.g.
diurnal cycles based on hourly values) to describe the temporal emission behaviour. Consequently, they provide hourly or
maybe half hourly mean concentrations and are not able to capture odour fluctuations due to turbulent perturbations of the
flow motion (see Fig. 1).
Methodology and Results
In the OMNISCIENTIS solution, the neighbours (citizens) can use a mobile device (Smartphone, Tablet) to provide
information and get direct feedback. The information provided from the mobile devices will be used calibrating the
measuring equipment, developing and validating a new odour dispersion model. The system performances will be tested and
validated on the field, using two distinct pilot cases: a pig fattening farm in Austria and a major industrial site in Belgium.
The new improved odour modelling system will use information on wind and turbulence as well as time-varying behaviour of
emissions (electronic noses and flow measurements) in order of minutes. The odour dispersion model must operate on time
scales order of minutes to provide citizens and other stakeholder’s immediate feedback. At this aim, the “GRAL-System”
(Öttl & Uhrner, 2011) is employed and modified to be applied for odour simulations. Main parts of the GRAL-System are
transferred so that they can run on GPUs (Graphical Processing Units) instead of CPUs. First test simulations for winter time
PM10 using emission inventories established during the EU project PMinter (see companion paper by Uhrner et al.) indicate
promising results of the new model under development.
Fig.1 Peak above the perception threshold cause annoyance
even if the mean concentration is below the threshold
Fig.2 Test-run with the transient model simulating
total PM10 for Leibnitz/Austria
First Conclusions
First test runs with the new model system revealed promising results for complicated air pollution simulations during winter
time for PM10.
Acknowledgement
This work is supported by FP7-ENV.2012.6.6-1 OMNISCIENTIS (308427).
References
Nicolas, J., Cors, M., Romain, A.-C., Delva, J., Identification of odour sources in an industrial park from resident diaries
statistics, Atmospheric environment, 44, 13 (2010) 1623-1631.
Öttl D., Uhrner U. (2011), “Development and evaluation of GRAL-C dispersion model, a hybrid Eulerian-Lagrangian
approach capturing NO-NO2-O3 chemistry”, Atmospheric Environment 45, 839-847.
212
MAKING AIR QUALITY INDICES COMPARABLE – ASSESSMENT OF TEN YEARS OF AIR POLLUTANT
LEVELS IN WESTERN EUROPE
H. Lokys (1, 2), J. Junk (1), A. Krein (1)
(1) Department Environment and Agro-biotechnologies (EVA), Centre de Recherche Public - Gabriel Lippmann, 41 rue du
Brill, L-4422 Belvaux, GD Luxembourg;
(2) University of Münster, Climatology Working Group, Heisenbergstr. 2, D-48149 Münster, Germany
Presenting author email: lokys@lippmann.lu
Summary
We present a new method to directly compare air quality indices based on the current valid WHO recommendations for NO2,
O3 and PM10. Using the new normalization method we compared three air quality indices based on the current valid European
guidelines, related them to another air quality index based on the relative risk (RR) concept and used them to assess the air
quality and its trends in northwest central Europe. The new method allows a direct comparison of the air quality indices as it
does not change the structure and the ten-year trends in air quality. The average air quality in the area of investigation is
below the index values recommended by the European guidelines. The majority of index values exceeding this threshold are
caused by PM10, which is also, in most cases, responsible for degrading trends in air quality. Overall more than 50 % of all
stations show a trend of decreasing index values.
Introduction
Air quality indices differ in many aspects like the purpose of the index, health-relatedness and calculation methods. The
variety of indices, even if well suited to the original location, complicates a direct comparison of air quality via these indices.
To address this incomparability we propose a new normalization method that is suited to directly compare the air quality
indices “Daily Air Quality Index” (DAQx) (Mayer et al. 2004), the “Common Air Quality Index” CAQI (van den Elshout et
al. 2008), and the “Multi Pollutant Index” (MPI) (Gurjar 2008) - all based on European air quality guidelines.
Methodology and Results
A two-stage normalization was chosen to make the air quality indices directly comparable. Stage one normalized the range
from zero till the index value correspondent to the WHO guideline value. On stage two the index values from the guideline
value up to the maximum index value were also normalized. This approach does not change the structure of the air quality
indices as well as their trends, and is therefore well suited for direct index comparisons.
It could be shown, that the non-aggregating air quality indices DAQx and CAQI indicate in general inferior air quality
(higher index values) than the aggregating index MPI at all stations.
In addition, we compared the health impact relation of the three indices by comparing them to the RR based index ARI (“Air
Risk Index”, Sicard et al. 2011). Results of this correlation indicate that the MPI is most consistent with the relative risk
approach (R=0.81), while both non-aggregating indices (DAQx (R=0.63), CAQI (R=0.48)) suffer from problems to indicate
the health outcome as described by the RR.
To assess the air quality in the “Greater Region” we analysed emission data of 29 stations. Beside index calculations, we
performed the non-parametric Mann-Kendall test for monotonic annual trends as well as the Sen’s method to estimate the
linear slope of the linear trend. The average air quality in the area of investigation is below the index values recommended by
the European guidelines. Overall more than 50 % of the stations exhibit trends of improving air quality, most of them are
rural background stations. The urban and suburban background stations as well as industry and traffic ones show similar
amounts of stations with increasing or decreasing air quality.
Conclusions
According to the correlation with the ARI we conclude that the non-aggregating air quality indices might be less suitable to
investigate relationships between morbidity and mortality levels and the current air quality. Nevertheless, they can serve as
good indicators of the air quality for policy makers and stakeholders. End users must be aware of these facts and must
carefully choose an air quality index appropriate for the relevant purpose or research question, e.g. in order to either focus
more on average pollution via aggregating indices or on peaks of at least one pollutant via non aggregating air quality
indices.
Acknowledgement
We gratefully acknowledge the financial support of the National Research Fund in Luxembourg for the PhD scholarship of
Hanna Lokys (4965163). Parts of the work have been done in the framework of the “Small Particles - environmental
behaviour and toxicity of nanomaterials and particulate matter” (SMALL) project.
References
Directive 2008/50/EC of the European Parliament and of the council of 21 May 2008 on ambient air quality and cleaner air
for Europe, 2008. Off J Eur Union.
Gurjar, B.R., et al., 2008. Evaluation of emissions and air quality in megacities. Atmos Environ 42, 1593-1606.
Mayer, H., et al., 2004. Air stress and air quality indices. Meteorol Z 13, 395-403.
Sicard, P., et al., 2011. Air quality trends and potential health effects – Development of an aggregate risk index. Atmos
Environ 45, 1145-1153.
van den Elshout, S., Leger, K. and Nussio, F., 2008. Comparing urban air quality in Europe in real time a review of existing
air quality indices and the proposal of a common alternative. Environ Int 34, 720-726.
213
EMISSION MODELS INVENTORIES
214
RESIDENTIAL HEATING EMISSIONS OF PM2.5 AND NOX IN ESTONIA
M. Kaasik (1), M. Maasikmets (2;3), E. Teinemaa (2)
(1) University of Tartu, Ülikooli 18, 50090, Tartu, Estonia. (2) Estonian Environmental Research Centre, Marja
4D, 10617 Tallinn, Estonia. (3) Estonian University of Life Science (EULC), Institute of Agricultural and
Environmental Sciences, Kreutzwaldi 5, 51014 Tartu, Estonia
Presenting author email: marek.maasikmets@klab.ee
Summary
A questionnaire-based investigation and combustion experiments were carried on to quantify the PM2.5 and NOx emissions
from residential heating in Estonia. Although relatively low emission factors were found, the residential emissions cause
PM2.5 episodes due to sharp annual and diurnal cycles. Wood combustion is highly dominating in these episodes.
Introduction
This investigation was carried out to quantify the PM2.5 and NOx emissions from residential heating in Estonia and aimed to
create an up-to-date input dataset for modelling the air quality in urban and regional scales. Particular attention is paid to
diurnal cycle of emissions that is expected to play a major role in urban peak levels of particulate matter.
Methodology and Results
Wood burning PM2.5 and NOx EF measurements were carried out in EERC stove test laboratory. PM2.5 measurements
included both filter sampling (10 l/min, Dekati PM10 Impactor, PM10, PM2.5, PM1, PM<1) and online (30 l/min ELPITM)
methods. Simultaneously gas samples (O2, SO2, NO, NO2, CO, CO2, VOC), temperature (°C), relative humidity (%) and gas
flow (m/s) were measured during the whole burning process. Samples for the gas analyses were taken through an insulated,
externally heated (up to 180 °C) sample line and through the filter units to the gas analyser (Testo 360, Testo AG). Conifer
and hardwood logwood with different humidity were used. Each log batch was weighed, heating value was measured and the
RH of each log was measured separately. All samples were taken from the hot flue gas. Samples were taken during the startup phase (up to 20 min) and during the constant flaming process (up to 30 min).
The survey of local heating, carried out in 2013, includes 200 households
questioned about fuels and their quantities used for heating. Upscaling the
data to entire country was based on 1 km gridded data from population
census. The emission factors (EF) from burning of wood (Teinemaa et al.,
2013) and fossil fuels (EMEP/EEA…, 2013) were applied to estimate the
gridded emissions of PM2.5 and NOx.
Compared to earlier studies, 1998 – 2004, the use of log wood and pellets
has become even more dominating. In new suburbs, built in recent 20
years, natural gas and electric heating (incl. heat pumps) are spread.
Formerly rather wide-spread fossil fuels (coal, fuel oil, peat products) have
become marginal yet. As a result, the emissions from local heating are
decreasing. A sharp maximum appears in diurnal cycle of emissions during
evening hours (17 – 21) and a secondary maximum in morning hours (8 –
12), Fig. 1. The average measured concentrations in residentialdominated Tartu monitoring station have similar diurnal cycle with 2 – 3
hour shift and gentle smoothing.
Fig.1. Average diurnal cycle of PM2.5 emissions
and .concentration in Tartu monitoring station,
heating season 2011/12.
Conclusions
As a result of combustion experiments, it was found that PM2.5 emission factors from traditional stoves in Estonia are 1.5 – 3
times lower than confidence limit supposed by EEA (EMEP/EEA…, 2013). Even lower emission factors have been reported
for Finland (Karvosenoja, 2001). Despite that, the emissions in certain urban areas induce high PM2.5 concentrations due to
intense heating in cold and calm wintertime anticyclonic weather, during evening hours in particular.
Acknowledgement
This work was supported by the Estonian MoE and by the Estonian Science Foundation project BioAtmos. Partial funding
was provided by Estonian Research Council, grant 7895.
References
EMEP/EEA Air pollutant emission inventory guidebook 2013. 1.A.4. Small combustion, Technical report No 12/2013.
Karvosenoja, N., 2001. Primary particulate emissions from stationary combustion processes in Finland, Finnish
Meteorological Institute, Publ. No. 232.
Teinemaa, E., Maasikmets, M., Vainumäe, K., Heinsoo, A., Arumäe, T., Lehes, L., 2013. Fulfilling the requirements of
Convention on Long-Range Transboundary Air Pollution (Geneva) Convention. Estonian Environmental Research Centre,
(report), contract No. 4-1.1/178, 64 p. (in Estonian).
215
CALORIFIC VALUES AND PARTICULATE EMISSION ESTIMATES OF DISTRIBUTED BIOMASS FUELS
OVER RURAL WESTERN INDIA
Rohtash, A. Sen, T. K. Mandal, M. Saxena, S. K. Sharma
CSIR-National Physical Laboratory, Dr. K S Krishnan Marg, New Delhi, India – 110012
Presenting author email: rosiga.vansh86@gmail.com
Summary
We have determined calorific value of residential fuels (n=624 samples) used for cooking purpose in rural western India
(Rajasthan, Gujarat and Maharashtra) using Bomb calorimeter. In addition, we have also determined the distribution,
humidity as well as emission factor of particulate matter (PM) emitted during burning of biomass. It has been noticed
calorific value has been varied substantially with types of fuels such as fuel wood, agricultural residue and dung cake and it is
negative correlated with humidity and emission factor of particulates.
Introduction
Biomass fuel is a major component of total energy use in rural residential sector of India. Heat of biomass from all these
sources is well known to be associated with the emission of smoke which is consists of particulate and gaseous species
(Andreae and Merlet, 2001). Due to lack of energy efficient processes the fuels are not burnt completely. The emitted species
and their concentrations depend on the type of biomass and other factors including physical parameters associated with
consumption of the biomass. The fate of initial fire emissions strongly depends on their composition, calorific value (CV) and
the regional state of the atmosphere. Emission factor of various biomass fuel used in rural Indian household could be
evaluated by determining their calorific values which is affected by humidity. Comprehensive efforts have been made to
evaluate calorific values of biomass and its correlation with emission factors (EF) of particulate matter (PM) emitted during
burning of biomass fuels.
80
% Distribution
70
60
50
40
30
20
10
Acacia nilotica
Dung cake
Azadirachta indica
Gossypium arboreum
Cajanus cajan
Prosopis juliflora
Brassica campestris
Richinus communis
Zea mays
Tectona grandis
Mangifera indica
Acacia Karoo
Sesamum indicum
Eucalyptus cinerea
Tamarindus indica
Saccharum officinarum
Acacia catechu
Cactus Spp.
Pistacia Integerrima
Abelmoschus esculentus
Madhuca latifolia
Ipomoea carnea
Prunus persica
Sesbania bispinosa
Sorghum vulgare
Anogeissus latifolia
Artocarpus hirsutus
Butea monosperma
Albizzia lebbek
Cocos nucifera
Phyllostachys aurea
Salvadora oleoides
Ficus glomerata
Camel dung
Shorea robusta
Citrus reticulata
Terminalia paniculata
Ziziphus mauritiana
0
Sample Type of Western Region
Fig. 1 % Distribution of Biomass Sample
EF (g/kg) of Particulates
Methodology and Results
Biomass samples were collected from 624 sites (Rajasthan, Gujarat and
Maharashtra) of western India, used in rural sector and small industries for energy
purpose. These samples were analyzed for CV (MJkg-1) using Bomb Calorimeter
and biomass burning sampler for finding emission factor (gkg-1) of particulate.
Biomasses evaluated for CV were then burned in the biomass burning sampler.
Emissions from biomasses collected on the 47mm quartz filter paper were evaluated
for emission factor of PM (T. Saud et. al. 2011). Distribution of bio-fuel varies
spatially and seasonally shown in figure 1. The Calorific value of residential fuels
ranged from 12.99 MJ/kg to 24.58 MJ/kg in the rural western India. It has been
observed that fuel wood (Av: 19 MJ/kg) has higher calorific value than agriculture
residue (Av: 17.34 MJ/kg) and dung cake (Av: 14.36 MJ/kg).The calorific value of
biomass was found to be negatively correlated with humidity (r = -0.88) in biomass
as well as with emission factor of particulates (r = -1.0) shown in figure 2.
5
4
Du
ng
Ca
ke
Ag
ric
ult
ure
Re
sid
ue
3
2
Fua
l wo
od
Conclusion
Calorific Value (MJ/kg)
We have analyzed of residential fuels used in rural sector of western rural India for
Fig.2 Relation Between CL And EF
energy purpose. Spatial variability of calorific values of the residential fuels is also
noticed in the present study. In earlier reported study, it has been that cow dung and
agricultural residues shows higher emission of pollutants due to lower calorific value. Briefly, this study alludes towards the
usage of dried biomass by the people living in the rural areas, as these biomasses will be having the higher CV and
consequently less emission of particulates. It would make the combustion process more economically and energetically
efficient
1
14
15
16
17
18
19
Acknowledgement
Authors are grateful to Director, National Physical Laboratory for support. This work is sponsored by Department of Science
and Technology, India. We thank Mr. R.P. Bhatnagar and Mr. Rishu Gautam for constant support of collecting biomass
samples used in this study.
References
Andreae, Meinrat O., and P. Merlet. "Emission of trace gases and aerosols from biomass burning." Global biogeochemical
cycles 15.4 (2001): 955-966.
T. Saud, T.K. Mandal, Ranu Gadi, D.P. Singh, S.K. Sharma, M. Saxena, A. Mukherjee “Emission estimates of particulate
matter (PM) and trace gases (SO2, NO and NO2) from biomass fuels used in rural sector of Indo-Gangetic Plain,
India”Atmospheric Environment 45.32 (2011): 5913-5923.
216
USING TRACERS FOR ESTIMATION OF CO2 SOURCE IN THE URBAN ENVIRONMENT
J. M. Necki, D. Jelen, M. Zimnoch
AGH-University of Science and Technology, Faculty of Physics and Applied Computer Science
al. Mickiewicza 30, 30-059 Kraków, Poland
Presenting author email: necki@agh.edu.pl
Summary
However CO2 is not defined as a pollutant influencing air quality, it plays important role in the Earth radiation budget.
Anthropogenic emission of carbon dioxide connected with fossil fuel combustion is usually accompanied by release of trace
gases (e.g. CO and PAHs). Simultaneous measurement of these gases in the air of Kraków city may lead to estimation of
fossil fuel input to atmospheric carbon balance. Radiocarbon analyses were performed in weekly accumulated samples and
used for direct estimation of the average fossil fuel CO2 constituent (CO2ff). For the calculation of high frequency
anthropogenic source efficiency observation of CO2 concentration in free troposphere is required and data were delivered by
Kaslab remote station. Excess of CO, PAH and CO2 concentrations accumulated in the lower troposphere were continuously
measured and correlated. Even more than 100 ppm of CO2 can originate in fossil fuel combustion during the winter season
and 10ppm in summer.
Introduction
The observation of carbon dioxide concentration in urban air may wrongly be misinterpreted. Its highest values observed at
Kraków station (Poland, Europe) located over the roof of the building approx. 50m from the street traffic are far over the
500ppm while free tropospheric concentration oscillates around 400ppm. The station represents urban averaged level of
concentrations. Only part of added “by the city” carbon dioxide originates from fossil fuel combustion. Large fraction comes
also from heterotrophic respiration processes. This work was aimed at high frequency observation of CO2 partition budget.
Methodology and Results
Carbon dioxide and carbon monoxide concentrations were measured chromatographically with time resolution 15min while
PAHs concentration were determined using UV spectrophotometer. CO2 and CO samples were dried cryogenically before
analysis and their concentration were expressed in WMO scale via secondary calibration mixtures. Records of both gases
reveals similarities as both gases have partly common source (combustion of fossil fuel) and their concentration increase
simultaneously during evening rush hours. CO might be useful tracer exactly during that time and its excess may indicate
amount of carbon dioxide emitted to the atmosphere. Additionally, assuming invariable ratio of CO/CO2 in calculation of
sources efficiency, balance might be extended to other periods of the day resulting high frequency values. Although
assumption is not always fulfilled, it gives at least estimates of traffic during the summer season and “low emission” during
winter. Weekly or bi-weekly samples were collected in aluminium bags and measured subsequently with gas chromatograph.
Average values of CO2, CO concentration as well as measured activity of radiocarbon in CO2 was base for the calculation of
average fossil fuel constituent of carbon dioxide. PAH concentration was determined with highest resolution 1min. Free
tropospheric air level was measured at Kasprowy Wierch mountain station (2000m a.s.l.). In case of Kraków background
level was calculated as lowest value during sunny periods in winter or early afternoon hours in summer season. Its excess in
urban air was also calculated and included into the balance. The simplified balance of CO2 was calculated for 3 years record
of data from AGH University station data (fig.1). Additionally CO concentrations were compared with city CO monitoring
network for better characterisation of CO source used in the balance.
160
140
CO2 ff [ppm]
120
100
80
60
40
20
0
2007-03-01
2008-03-01
2009-03-01
2010-03-01
Fig.1 Carbon dioxide originated from fossil fueldcombustion(CO2ff) record from Kraków city.
Conclusions
Carbon monoxide and PAH monitoring network might be applied for partitioning of carbon dioxide as an indicator of fossil
fuel combustion. High frequency balance basing on tracer method plays only indicative role, however information is valuable
for proper construction of the urban carbon balance.
Acknowledgement
This work was supported by statutory funds of the AGH University of Science and Technology - project No.11.11.220.01).
217
MICRO AND MACRO MODELLING OF COLD START EMISSIONS FROM ROAD TRAFFIC: A CASE STUDY
IN ATHENS
C. Samara (1), E. Mitsakis (2), I. Stamos (2), J. M. Salanova-Grau (2), G. Aifadopoulou (2), L. Ntziachristos (1) and Z.
Samaras (1)
(1) Laboratory of Applied Thermodynamics (LAT), School of Engineering, Aristotle University, 54124, Thessaloniki,
Greece; (2) Centre for Research and Technology Hellas (CERTH), Hellenic Institute of Transport, 6th km Charilaou-Thermis
str., 57001, Thessaloniki, Greece
Presenting author email: cesamara@auth.gr
Summary
This study aims to quantify the contribution of cold start emissions on the overall emissions from the transport sector of
Athens. The developed bottom-up methodology was based on the combination of PTV VISUM and COPERT Micro for
traffic and emissions modelling respectively. The hourly and daily CO, CO2, NOx and VOC emissions from passenger cars
were calculated for both hot and cold start conditions and for every traffic link of a typical weekday of October 2010. The
study focuses on passenger cars only, since they constitute the main category of the Athens vehicle fleet. The calculated trip
length distribution (percentage of trips finished within given length categories) highlights the importance of cold start
emissions on the overall emissions estimation. The results indicating that for specific areas and for specific traffic links cold
start emissions can be the major contributor on CO and VOC total emissions.
Introduction
During the cold-start phase of vehicles, the exhaust emissions of regulated pollutants are high, since the engine, catalyst,
drive train and tyres haven’t reach their operating temperatures. Several studies have been carried out trying to identify the
impact of various parameters, such as vehicle technology, average speed, ambient temperature, travelled distance and parking
duration, on the cold start emissions from passenger cars (André and Joumard, 2005). Several methodologies have been
developed, each of which having its own advantages and limitations (Boulter and Latham, 2009). Considering that passenger
cars are a major contributor in transport emissions we tried to quantify the impact of cold start emissions on micro (per traffic
link) and macro level (entire city) using measured traffic data and applying traffic and emissions modelling.
Methodology and Results
The Athens network used in this study consists of 81880
directed links and 36725 nodes. The links contain
information about the number of lanes, the road type and
its hierarchy in the network, width, length, free flow
speed, design and effective capacity, direction, allowed
transport systems. The demand side is comprised by 24
hourly Origin-Destination (OD) matrices which were
corrected using the hourly volume data measured by
inductive loop detectors installed at 557 locations across
the city. The output traffic data from PTV VISUM –
traffic volume, average speed and vehicle fleet
composition pet link, as well as the trip length
distribution per hour, along with the parking time
distribution were inserted to COPERT Micro, a specially
developed version of COPERT IV software
(Ntziachristos, 2009). COPERT Micro calculates both
hot and cold start emissions per traffic link following an
approach similar to COPERT IV and ARTEMIS project
(André and Joumard, 2005) respectively. The results
indicating that for CO and VOC cold start emissions constitute the major contributor on overall road transport emissions
(over 70%), whereas their impact on NOx and CO2 emissions is relatively smaller (around 20%). In certain traffic links,
which are closer to locations where the majority of trips start, the contribution of cold start emissions is even higher.
Conclusions
Cold start emissions can be a significant contributor to the total emissions from urban areas. Moreover, in specific traffic and
ambient conditions they seem to be more important than hot emissions. Hence, during emissions inventories and new
transport policies assessments should be taken seriously into account.
References
André, J.-M. and Joumard, R., 2005. Modelling of cold start excess emissions for passenger cars. INRETS.
Boulter, P. G. and Latham, S., 2009. Emission factors 2009: Report 4 – a review of methodologies for modelling cold-start
emissions. TRL.
Ntziachristos, L., Gkatzoflias, D., Kouridis, C., and Samaras, Z., 2009. COPERT: A European Road Transport Emission
Inventory Model. 4th International ICSC Symposium on Information Technologies in Environmental Engineering.
Thessaloniki.
218
ENVIRONMENTAL AND
HEALTH IMPACT
RESULTING FROM AIR
POLLUTION
219
AIR QUALITY MEASUREMENTS IN INDOOR ENVIRONMENT OF MODERN OFFICES IN ATHENS,
GREECE (OFFICAIR PROJECT)
I.A. Sakellaris (1), D.E. Saraga (1,2), K.K. Kalimeri (1), E.M. Kougioumtzidis (1), V.G. Mihucz (3), R. Mabilia (4) and J.G.
Bartzis (1)
(1) University of Western Macedonia (UOWM), Department of Mechanical Engineering, Environmental Technology
Laboratory, Sialvera & Bakola Street, 50100 Kozani, Greece; (2) Environmental Research Laboratory, INRASTES, National
Center for Scientific Research "DEMOKRITOS", Aghia Paraskevi Attikis, P.O.B. 60228, 15310 Athens, Greece; (3)
Department of Analytical Chemistry, Institute of Chemistry, Eötvös Loránd University, Budapest, 1117, Hungary; (4) CNRIIA, National Research Council, Institute of Atmospheric Pollution Research, Rome, Italy
Presenting author email: isakellaris@me.com
Summary
The present study presents the status of the indoor air quality at the work environment of modern office buildings. In
particular, five buildings were investigated in Greece, during two seasons (summer 2012 and winter 2013). Measurements
involving passive and active sampling of VOCs, aldehydes, O3, NO2 and particulate matter as well as temperature, relative
humidity and air exchange rate were conducted during weekdays. Indicative results from summer period show that toluene
and formaldehyde concentration presented the highest level in all buildings. PM2.5, O3 and NO2 concentration was higher
outdoors than indoors. All measured pollutants levels were found to be lower than the proposed guidelines, except for PM2.5
outdoor concentration in one building. Further data analysis will be conducted in the frame of OFFICAIR project.
Introduction
Exposure of office occupants to compounds emitted from potential sources in modern offices can be quite substantial and
might significantly affect comfort and human health. OFFICAIR, a European research project, titled "On the reduction of
health effects from combined exposure to indoor air pollutants in modern offices" takes place in eight European countries:
Greece, Italy, France, Hungary, Portugal, Netherlands, Spain and Finland. In total, 167 office buildings participated in a
questionnaire-survey and 36 of them took part in a detailed air quality survey. One of the objectives of the project, is to
investigate and verify causes (mechanisms, events and sources) that have been identified as possible sources of indoor air
quality issues in European modern offices, via a field investigation (questionnaires, checklists, air pollutants’ monitoring and
ventilation measurements) during two seasons. This study presents the results of the OFFICAIR summer and winter
campaign in Greece, which took place in five modern office buildings during July – September 2012 and December 2012February 2013.
Methodology and Results
Targeted measurements of chemical and physical parameters were conducted in five modern office buildings located in urban
and suburban area of Athens. Specifically, in each building, sampling took place at four indoor (office rooms) and one
outdoor site. Each sampling period lasted for five weekdays (Monday to Friday). In particular, measurements included
passive sampling of VOC (Volatile Organic Compounds), Aldehydes, O3 (Radiello passive samplers) and NO2 (GRADKO
passive sampling tubes). Additionally, PM2.5 samples were collected with low volume samplers on quartz fiber filters.
Physical parameters (temperature, relative humidity, visible and UVA radiation, wind speed, ultra-fine particles) were also
monitored. Finally, ventilation was estimated by the passive PerFluorocarbon Tracer (PFT) technique as well as the
mechanical flow rate was measured actively using a TSI flow meter. Preliminary indicative results (from the summer
campaign) show that the indoor concentration of benzene ranged from 1.9 to 4.4 μg/m3, toluene from 13.9 to 19.4 μg/m3,
xylenes from 5.9 to 9 μg/m3 while the outdoor concentrations ranged respectively from 0.6 to 1 μg/m3, from 4.8 to 5.3 μg/m3
and from 2.7 to 3.7 μg/m3. Formaldehyde concentrations were found to be from 10.4 to 26 μg/m3 indoors and from 3.2 to 3.9
μg/m3 outdoors. Focusing on PM2.5, the 5-day average concentration ranged from 8.7 to 15.7 μg/m3. The indoor ozone
concentration levels reached up to 30.4 μg/m3 and the nitrogen dioxide up to 20.9 μg/m3. The rooms’ air exchange levels
ranged from 0.45 to 2.3 ACH.
Conclusions
This study presents the preliminary results of the targeted measurements of chemical and physical parameters that took place
in five Greek modern office buildings participating in OFFICAIR project campaigns. The concentration values found to be
below the proposed guidelines limits. Among the VOCs, toluene presented the highest levels in all buildings. Also, among
aldehydes, formaldehyde presented the highest level in all buildings. PM2.5, O3 and NO2 outdoor concentration was found
higher outdoors than indoors in all buildings (except for NO2 in one building). Further data analysis will be conducted in the
frame of OFFICAIR project.
Acknowledgement
The OFFICAIR project (On the reduction of health effects from combined exposure to indoor air pollutants in modern
offices) is funded by the European Union 7th Framework (Agreement 265267) under the Theme: ENV.2010.1.2.2-1.
220
ANALYSING THE BIOLOGICAL INTERVENTION OF FINE PARTICULATE FRACTIONS IN HUMAN BODY
I. Mukherjee (1), T. Chakraborty (2)
(1) Civil Engineering Department, Techno India College of Technology (Affiliated to West Bengal University of
Technology, Govt. of West Bengal & Approved By All India Council for Technical Education, Govt. Of India) Netwown,
Rajarhat, Kolkata-700156, West Bengal, India; (2) Environmental Engineering & Management, Indian Institute of
Technology, Kanpur, PIN-208016, India
Presenting author email: indra_1978@rediffmail.com
Summary
The present study happens to not only present a review of the various studies conducted to positively correlate the
occurrences of high fine particulate concentrations with adverse complications to human health but also presents some
findings on the occurrences of fine particulate concentrations for an unique mangrove ecosystem over a substantial period
and their effects on human health. The study is important from the perspective of its reporting ambient concentrations of fine
particulate fractions over a substantial period for the highly vulnerable mangrove ecosystem and thereby to ascertain the
probable impact of the concentrations on these two types of inhabitants. In addition, the seasonal variations in the occurrence
of the fine particulate fractions have been also reported in the study. The study also reported the possible sources of the
particulate fractions in the area along with the probable health complications. As for the mangrove ecosystem, the study
reported high occurrences of finer fractions compared to the coarser fractions which makes the matter worse considering the
vulnerability and susceptibility of the mangrove ecosystems to intense pollution loads. Lastly, the study tries to draw a
correlation of the occurrences of the fine particulate exposures with special emphasis on early incidences of mortality in
adults and increased frequency of complications in infants in the area.
Introduction
Sustainable development is very much desirable. However, over the years, a reverse trend has resulted in serious
complications to the environment and to human beings, being inherent parts of the environment. Pollution is the direct
consequence of “development” and researchers (Hauck et al,2004), (Neuberger et al,2004) have attributed finer particulates
to be the most lethal of all the pollutant types. In fact, the need to carry out further studies to correlate the occurrences of the
fine particulate fractions with severe complications to human health is indeed very vital considering the ever so increasing
atmospheric pollution. Moreover, the need to carry out assessment of pollution load for populations of varying type is also
very important considering their immunity type and also to the type of area they reside and its susceptibility to the
atmospheric pollution. This has been well reflected in the study by reporting the concentrations for the population residing in
the mangrove ecosystem.
Methodology and Results
Fine Particulate Sampler and Respirable Dust Samplers were used to monitor the finer fractions (PM2.5) and the PM10
fractions respectively. The PM10 and PM2.5 concentrations varied between (57-118) μg/m3 and (35-80) μg/m3 respectively
over the period of study as reported in the paper. The seasonal fluctuations influenced by the meteorological parameters were
also studied. The study has indeed reported occurrences of relatively high concentrations of PM2.5 with reference to PM10,
and thereby the need to adopt suitable mitigation strategies to address this. Household surveys conducted in the area have
truly reflected the prevalence of respiratory diseases in conjunction to the occurrence of the finer fractions. Lastly, an attempt
was also made in the paper to ascertain the probable sources of the particulate fractions so that the remedial strategies can be
formulated.
Conclusions
As the mangrove ecosystems are highly sensitive, so the need to reduce the fine particulate pollution for the area is a must.
This is also required to address the adverse complications in human health reported for the area due to these finer fractions
predominantly.
Acknowledgement
This work was funded by CSIR (Council of Scientific & Industrial Research, Govt. of India) and carried out in active co
operation from Jadavpur University.
References
Hauck, H., Berner, A., Frischer, T., Gomiscek, B., Kundi, M., Neuberger, M., Puxbaum,H., Preining, O., AUPHEP-Team,
(2004), “AUPHEP-Austrian Project on Health Effects of Particulates-general overview”, Atmospheric Environment, 38, pp
3905-3915.
Neuberger, M., Schimek, Michael G., Horak (Jr), F., Moshammer, H., Kundi, M., Frischer, T., Gomiscek, B., Puxbaum, H.,
Hauck, H., AUPHEP-Team, (2004), “Acute effects of particulate matter on respiratory diseases, symptoms and functions:
epidemiological results of the Austrian Project on Health Effects of Particulate Matter (AUPHEP)”, Atmospheric
Environment, 38, pp 3971-3981.
221
CHEMICAL MECHANISM OF CU-TIO2/GF PHOTOCATALYST FOR DISINFECTION OF E. COLI IN
AEROSOL UNDER VISIBLE LIGHT
T. D. Pham, B. K. Lee, C. H. Lee
School of Civil and Environmental Engineering, University of Ulsan, Daehakro 93, Namgu, Ulsan 680-749, Korea
Presenting author email: bklee@ulsan.ac.kr
Summary
This study investigated the chemical mechanism of Cu to enhance photocatalytic activity of TiO2. Cu acted as a doping agent
to enhance photocatalytic activity of TiO2.The sol-gel method was applied to immobilize TiO2 and Cu-TiO2 on glass fiber to
synthesize a flexible material working well for air purification purposes. The synthesized photocatalysts were applied to
disinfect E. coli in aerosol under visible light irradiation. As compared to TiO2/glass fiber (TiO2/GF), the Cu-TiO2/glass fiber
(Cu-TiO2/GF) exhibited a very high photocatalytic disinfection activity even under visible light. Under visible irradiation, the
E. coli disinfection efficiencies by TiO2/GF and Cu-TiO2/GF were 2.27 and 87.61%, respectively.
Introduction
It has been well documented that TiO2 could be acted as a disinfectant when it is excited by UV irradiation, which requires
energy that is equal to or higher than its band gap energy (3.2 eV). However, in practical systems using light sources, such as
a white light fluorescent lamp and solar light, where UV radiation intensity for photo-exciting TiO2 is very weak, the TiO2
exhibits low photocatalytic disinfection activity. Therefore, a large number of studies have been carried out to improve
photocatalytic activity of TiO2 and to expand its application in practical system using visible light as excitation source. In this
study, Cu, a relatively abundance and low cost metal, was used as a doping agent to enhance photocatalytic activity of TiO2.
Methodology and Results
CuO contained in Cu-TiO2/GF is a semiconductor with a band gap energy around 1.7
eV. Therefore, TiO2 and CuO created a suitable semiconductor–semiconductor system
increasing electron-hole separation efficiency (Fig. 1). The recombination of electrons
and holes of TiO2 is also prevented due to the migration of photo-generated electrons
to the conduction band and the valance band of CuO, hence increasing the
photocatalytic activity of Cu-TiO2/GF photocatalyst. The formation of Ti3+ in CuTiO2/GF was due to the reduction of Ti4+ (Fig. 2). The reduction of Ti4+ into Ti3+ could
be attributed to the presence of Cu species in the formation process of TiO2 (Nair et al.,
1999). Because of the similarity in ionic radius of Cu2+ (0.73 Å) to that of Ti4+ (0.64
Å), Cu2+ enabled to substitutionally replace Ti4+ in the titanium lattice during the
calcinations process where TiO2 particles are formed from the ionic state in TIOT sol
solution. The substitution of Ti4+ by Cu2+ increased the oxygen vacancy concentration
leading to the reduction of Ti4+ into Ti3+. The formation of Ti3+, which contains one
more electron than Ti4+, might promote electron generation from TiO2. Therefore, the
electron separation capacity of Cu-TiO2 could be higher than that of TiO2. In CuTiO2/GF, the electron-hole pairs could be easily generated when the photocatalyst was
irradiated by even visible light, and then the generated electron-hole pairs reacted with
water and molecular oxygen absorbed on the photocatalysis surface leading to more
oxidized the species to form hydroxyl radicals (.OH) and superoxide radical anions (.O2) (Sunada et al., 2003). These oxy radicals attack organic components of E. coli,
including outer membrane, DNA, RNA and lipid, to oxidize or decompose them
resulting in bacterial death (Sunada et al., 2003).
Conclusions
Cu in the Cu-TiO2/GF photocatalyst acted as an intermediate agent for the transfer of
photo-generated electrons from the valance band to the conduction band of TiO2, which
aimed to increase the electron-hole pair separation efficiency and inhibit their
recombination. Cu also defected into the TiO2 lattice, resulting in formation of Ti3+
ions, which increase electron generation capacity of the prepared photocatalyst.
Therefore, the photocatalytic activity of Cu-TiO2/GF was enhanced resulting from
increasing separation capacity and separation efficiency of electron-hole pair.
Acknowledgment
This work was supported by the National Research Foundation of Korea (NRF) grant
funded by the Ministry of Education (2013R1A2A2A03013138).
Fig.1 Electron-hole pair separation
mechanism of CuO-TiO2 system
Fig.2 High-resolution XPS spectra
of Ti 2p of TiO2/GF and CuTiO2/GF
References
Nair J., Nair P., Mizukami F., Osawa Y., Okubo T., 1999, Microstructure and phase transformation behavior of doped
nanostructured titania, Material Research Bulletin 34, 1275-1290.
Sunada K., Watanabe T., Hashimoto K., 2003, Bactericidal Activity of copper deposited TiO2 thin film under weak UV Light
illumination, Environmental Science and Technology 37, 4785-4789.
222
EXTERNAL COSTS OF AIR POLLUTION FROM ENERGY SUPPLY: REVIEWING METHODOLOGIES FROM
EXTERNE TO NEEDS
J. van der Kamp, T. M. Bachmann
European Institute for Energy Research (EIFER), 76131 Karlsruhe, Germany
Presenting author email: vanderkamp@eifer.org
Summary
This study aims at looking back on more than 15 years of external cost quantification in Europe and discusses the main
methodological evolutions from the 1990s until recently. The focus is on the variability of human health costs caused by
classical air pollutants (mainly NOx, SO2, particles). Using a case from the energy sector, major influencing parameters are
identified: exposure modelling is shown to lead to variations in results of up to 30% between different assessment
frameworks. Concerning risk functions and monetary valuation, changes in assessing mortality risks due to long term
exposure together with assumptions on particle toxicity explain most of the observed variability.
Introduction
“Getting the prices right” through internalising external costs is a regularly expressed intention of EU environmental policy
making. The revision of key European air quality policies in 2013 contributes to this objective. It is supported by scientific
impact assessments, including the monetary valuation of environmental and health damages. For over 20 years now, related
methodological developments have taken place in the Externalities of Energy (ExternE) project series and follow-up
activities. Against this backdrop, the methodological evolution and the major influencing parameters have been reviewed.
6
5.21
[€-Cent(2000) / kWh(el)]
5
4
2.78
3
1.77
2
1
0
Morbidity
Mortality
ExternE 1998
0.88
4.33
NewExt 2004
0.59
1.18
NEEDS 2009
0.93
1.85
Fig.1 Development of marginal external costs of an
exemplary power plant due to changes in the
assessment framework
8
7
[€‐Cent(2000) per kWh(el)]
Methodology and Results
The evolution of exposure modelling, health risk assessment
parameters as well as of the monetary values has been reviewed. Their
influence is illustrated for an exemplary coal-fired power plant unit,
relying on published and self-produced results at the local and regional
scale. Published external costs are taken from European Commission
(1999, 2004). The results relating to the NEEDS 2009 methodology are
calculated with EcoSenseWeb (Preiss and Klotz 2008). All assessment
frameworks used a Gaussian Plume model for assessing air quality at
the local scale but partly different models at the regional (i.e. European)
scale (parameterized version of a European Eulerian model
(EMEP/MSC-W) in NEEDS 2009 vs. Windrose Trajectory
(Lagrangian) Model earlier). Also, population data have been updated.
The quantified marginal health-related external costs vary between 1.77
(NewExt 2004) and 5.21 (ExternE 1998) €-cent2000 per kWh of
electricity produced (Fig. 1). The share of mortality varies between 67%
(NewExt 2004 and NEEDS 2009) and 87% (ExternE 1998).
When using the exposure model from EcoSenseWeb (NEEDS 2009)
instead of the original models, the quantified health-related external
costs are around 29% and 21% higher for the ExternE 1998 and the
NewExt 2004 framework, respectively (Fig. 2). Assuming
EcoSenseWeb exposure modelling results for all frameworks would
increase the overall variability (blue versus green bars in Fig. 2).
6
5
4
6.73
3
5.21
2
1
1.77
2.15
2.78
2.78
0
ExternE 1998
Original exposure modelling
NewExt 2004
NEEDS 2009
EcoSenseWeb exposure modelling
Fig.2 Marginal health-related external costs of an
Conclusions
exemplary power plant under different exposure
Relying on a case study and using partly simplified assumptions, the
modelling frameworks
findings on methodological developments in this study are indicative
rather than conclusive. Notably, the overall influence of exposure modelling and the evolution of marginal external costs over
time depend on the source emission profile. Nevertheless, through a detailed review of assessment parameters (cf. van der
Kamp and Bachmann, in preparation), major influencing factors are identified. These are the risk function and monetary
valuation of long-term (chronic) mortality risks as well as assumptions on particle toxicity. Given that the methodology
frameworks have been used to support the design of air quality policies, efforts to further increase the robustness of the
scientific assessment approach should be pursued.
Referen