C - Politecnico di Torino

Estimate of boundary layer parameters and
background concentrations for pollutant
dispersion modeling in urban areas
Dipartimento di Matematica
Laboratoire de Mécanique des Fluides et Acoustique
Engineering earth’s development, preserving earth’s integrity
S. Biemmi1, R. Gaveglio1, P. Salizzoni2, M. Boffadossi3, S. Casadei4, M. Bedogni4, V. Garbero1,5, L. Soulhac2
1 Golder Associates S.r.l ,2 LMFA – Ecole Centrale de Lyon, France , 3DIASP – Politecnico di Milano ,4Agenzia Mobilità e Ambiente (A.M.A) del Comune di Milano, 5DIMAT – Politecnico di Torino
INTRODUCTION
Pollutant dispersion models require a careful preparation and validation of atmospheric data set since the accuracy of the model output strongly depend on the accuracy of the meteorological input. The characterization of the dynamical state of the atmospheric boundary layer is therefore an important challenge in urban air quality studies, as well as the estimation of the background concentration. Meteorological data
Estimation of boundary layer parameters
Dispersion model SIRANE*
Evaluation of pollutant background concentration
Pollutant concentration, CSIRANE
The aim of this study is to identify the most critical parameters in the estimation of pollutant concentration in urban areas by comparing model results and in situ measurements in the central neighbourhoods of Milan.
*Soulhac L. (2002), Notice d’utilisation de SIRANE, Ecole Centrale de Lyon.
METEOROLOGICAL DATA
BOUNDARY LAYER PARAMETERS
A detailed intercomparison of the meteorological data acquired in 3 different stations was performed: 1. Piazza Duomo, equipped with sodar
2. Via Juvara, a conventional weather station
3. Linate airport, equipped with radiosonde
The validated data set has been used to compute the meteorological parameters that could not be measured directly, such as the Monin Obukhov height (L) and the boundary layer depth (h). These were estimated according to the Monin Obukhov similarity theory using different methods proposed in the literature.
INSTABLE CONDITIONS
NEUTRAL CONDITIONS
h = 0.15u*/f (Capanni­Gualtieri)
Data validation Biemmi, S., Gaveglio, R., Salizzoni, P., Boffadossi, M., Casadei, S. and Bedogni, M. (2008) Analisi dei dati meteorologici e parametrizzazione dello strato limite terrestre nell'area urbana milanese. Nimbus, 49­50, 6­16. BACKGROUND CONCENTRATION
(Batchvarova e Gryning)
STABLE CONDITIONS
A correct estimation of the background value of pollution characterizing the investigated area is a tricky problem. Hourly background concentrations were selected among those measured at different monitoring stations external to the domain. An optimal background concentration, Copt, was calculated:
Copt = CSIRANE – CMEASURED
(Arya, 1981)
(Nieuwstadt, 1984)
CSIRANE = concentration calculated by the urban dispersion model SIRANE
CMEASURED = concentration measured at the monitoring stations within the domain
The background concentration that showed the lower standard deviation and fractional bias compared to Copt has been assumed as the background value of the pollutant concentration. RESULTS
A sensibility analysis has been performed to evaluate the influence of the estimation of background concentration and meteorological parameters on the calculated pollutant concentration.
The most significant influence on the accuracy of the model results is related to the estimation of the background concentrations, which affect the pollutant concentration values of about 70­90%. Different estimations of the boundary layer depth lead to slighter variations in model results, i.e. 9%. Compared to these two parameters, the differences in all other meteorological variables did not affect significantly the results.
The concentration distribution of CO, NOx and O3 in Milan
have been simulated by SIRANE and the model results have been compared by in situ measurements.
The performance of the model has then been analysed by means of statistical parameters.
Pollutant C SIRANE (μg/m3) C measured (μg/m3)
Comparison between CO concentration values computed by SIRANE using different estimates of the boundary layer depth FB
ER
R
CO
1016
986
­0.03
0.36
0.49
NOx
107
115
0.07
0.45
0.49
NO
28
38
0.3
0.70
0.47
NO2
40
56
0.33
0.46
0.51
O3
50
31
­0.46
0.47
0.73