Aerosol optical properties based on ground measurements over the

Atmospheric Environment 44 (2010) 2587e2596
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Atmospheric Environment
journal homepage: www.elsevier.com/locate/atmosenv
Aerosol optical properties based on ground measurements
over the Chinese Yangtze Delta Region
Liang Pan a, Huizheng Che b, *, Fuhai Geng a, Xiangao Xia c, Yaqiang Wang b,
Chize Zhu d, Min Chen a, Wei Gao a, Jianping Guo b
a
Shanghai Urban Environmental Meteorology Center, Pudong New Area Weather Office, SMB, Shanghai 200135, China
Key Laboratory for Atmospheric Chemistry, Center for Atmosphere Watch and Services, Chinese Academy of Meteorological Sciences,
CMA, 46 Zhong-Guan-Cun S. Ave., Beijing 100081, China
c
LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
d
Zhejiang Meteorological Institute, Hangzhou 310017, China
b
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 14 January 2010
Received in revised form
16 March 2010
Accepted 12 April 2010
The characteristics of Aerosol Optical Depth (AOD) and Angstrom exponent were analyzed and compared
using Cimel sunphotometer data from 2007 to 2008 at five sites located in the Yangtze River Delta region
of China. The simultaneous measurements between Lin’an and ZFU showed a very high consistency of
AOD at all wavelengths. The differences are less than 0.02 for Angstrom exponent and AOD at all
wavelengths. The mean values of AOD at 440 nm at the Pudong, Taihu and Lin’an were about 0.74 0.43,
0.85 0.46, and 0.89 0.46, respectively. The mean values of Angstrom exponents were about 1.27
0.30, 1.20 0.28 and 1.32 0.35, respectively. The variation of monthly averaged AOD over Pudong
showed a single peak distribution, with the maximum value occurring in July (AOD440nm 1.26 0.61) and
minimum in January (AOD440nm 0.50 0.27). However, the variations of monthly averaged AOD at Taihu
and Lin’an showed a bi-modal distribution. There were peak values of AOD occurring in July (AOD440nm
1.41 0.49) and September (AOD440nm 1.22 0.52) for Taihu. For Lin’an, the two peak values of AOD
occurred in June (AOD440nm 1.17 0.69) and September (AOD440nm 1.28 0.46). The AOD accumulated
mainly between 0.30e0.90(68%), 0.30e1.20(75%) and 0.30e1.20 (w75%) at Pudong, Taihu, and Lin’an,
respectively. The Angstrom exponent accumulated mainly between 1.10e1.60 (75%), 1.10e1.50 (63%) and
1.20e1.60, 50% (50%) at Pudong, Taihu, and Lin’an, respectively.
The synchronized observation showed that the AOD at Pudong was larger than those at Dongtan by
0.03, 0.03, 0.04, 0.07, and 0.08 at wavelengths of 1020 nm, 870 nm, 670 nm, 500 nm and 440 nm,
respectively. The synchronized observations at Pudong, Taihu and Lin’an showed that the three stations
had high level AOD with means at 440 nm about 0.68, 0.73, and 0.78, respectively. The relationship
between MODIS retrieved and ground-based measured AOD shows good agreement with R2 ranging
from 0.68 to 0.79 at Pudong, Taihu, Lin’an and Dongtan. The MODIS results were overestimated
comparing the ground measurements at Pudong, Taihu, and Dongtan but exceptional at Lin’an.
The analysis results between aerosol optical properties and wind measurement at Pudong showed that
the wind speed from the east correlates with the lower observed AOD. The back trajectory analysis
indicates that more than 50% airmasses were from the marine area at Pudong, while back trajectories
distribution is relatively homogeneous at Lin’an.
Ó 2010 Elsevier Ltd. All rights reserved.
Keywords:
Aerosol optical properties
Yangtze Delta Region
China
1. Introduction
Aerosol particles play a very important role in the studies of global
and regional climate change (Charlson et al., 1992) and can result in
direct radiative forcing as well as indirect effects on clouds (e.g.
* Corresponding author. Tel.: þ86 10 58995247; fax: þ86 10 62176414.
E-mail address: chehz@cams.cma.gov.cn (H. Che).
1352-2310/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved.
doi:10.1016/j.atmosenv.2010.04.013
droplet properties, cloud dynamics, albedo and lifetimes) (Twomey
et al., 1984; Hansen et al., 1997). It has been speculated that aerosol
particles could contribute to the global and regional dimming
(Stanhill and Cohen, 2001; Che et al., 2005) and to the change of
regional precipitation (Menon et al., 2002) and visibility (Che et al.,
2007). Despite many aerosol studies, the aerosol concentrations
and optical properties are one of the largest sources of uncertainty in
current assessments and predictions of global climatic change
(Hansen et al., 2000). Aerosol optical depth (AOD) and Angstrom
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L. Pan et al. / Atmospheric Environment 44 (2010) 2587e2596
exponent are two basic optical parameters of aerosol particles and
key factors for the climate change research (Breon et al., 2002).
To systematically study the global aerosol optical properties, the
simplest and most accurate way in principle is to establish groundbased measurement networks (Holben et al., 2001). Ground-based
measurement networks are a very useful and accurate way to
research aerosol optical properties (Holben et al., 2001) and validation of satellite results (Kleidman et al., 2005). AErosol RObotic
NETwork (AERONET) is one of the well known two ground-based
aerosol-monitoring networks which use the Cimel sunphotometers
making the direct spectral solar irradiance and sky radiance for
solar almucantar scenario or principal plane scenario measurements within a 1.2 full field-of-view at different wavelengths
(Holben et al., 1998). It has been used to derive the aerosol optical
properties for the purpose of aerosol radiative forcing studies
(Holben et al., 2001; Dubovik et al., 2002; Smirnov et al., 2002; Eck
et al., 2005).
China has experienced unprecedented economic growth over
the past two decades characterized by the development of industries and anthropogenic activities, which caused the degradation of
visibility (Che et al., 2007), solar radiation (Che et al., 2005) and air
quality (Han et al., 2008) especially in eastern China like the Yangtze
River Delta and southern China like the Pearl River Delta, and
the Jing-Jin-Ji (Beijing, Tianjin and Hebei) region. There were many
studies about aerosol optical properties over Yangtze River Delta
region in recent years (Luo et al., 2002; Li et al., 2003; Duan and Mao,
2007). Wang et al. (2006) found larger range daily variation and the
weak seasonal variation of AOD with heavy aerosol load and steady
aerosol mode in Yangtze delta area. Chen et al. (2008) studied
the aerosol optical properties and its spatial and temporal variability
at four sites in Hangzhou region. Xia et al. (2007) retrieved and
analyzed the characters of aerosol in Taihu area based on the sunphotometer data and surface irradiance data. All these studies
contribute to the understanding of the aerosol optical properties
over Yangtze River Delta region comprehensively. However, few
aerosol optical property studies carried on using the simultaneous
Cimel sunphotometer measurements over different sites of this
region, which could benefit to further optimize the satellite retrieval
algorithm and make it possible to retrieve AOD with higher resolution (Mi et al., 2007).
The aims of this study are: (1) to analyze the spatial-temporal
distribution and variation of aerosol optical properties, (2) to
compare and verify the MODIS AODs by using the ground-based
measurements and (3) to study the relationship between aerosol
optical properties and meteorological conditions over different
areas of Yangtze River Delta region.
2. Experimental procedures
2.1. Site distribution
In this study, five ground-based Cimel sunphotometer observation sites (Fig. 1) were selected over the Yangtze Delta region,
including two sites, i.e. Taihu and ZFU, from the AERONET and three
sites, i.e. Pudong, Lin’an and Dongtan, from the China Aerosol
Remote Sensing Network (CARSNET).
Taihu site (121130 E, 31250 N,, 20 m) is situated on the northern
edge of the Taihu Lake. Observation at this site could roughly
reflects the optical properties over Lake surface characteristics
and also the anthropogenic aerosol emitted from big cities in the
Yangtze Delta Region (Mi et al., 2007). The Cimel sunphotometer
was installed in September 2005 and kept running till present.
The Cimel sunphotometer at Pudong was installed in August
2007 on the roof of the Pudong Meteorology Bureau (121330
E, 31130 N, 14 m), Shanghai. This site is located at the urban area of
Metropolitan Shanghai with many industrial and anthropogenic
Fig. 1. Site distribution of Cimel sunphotometer measurement over Yangtze River region.
L. Pan et al. / Atmospheric Environment 44 (2010) 2587e2596
activities around. The observation at this site could represent the
aerosol characteristics over urban area of Yangtze River Delta region.
The sun photometer at Dongtan (121450 E, 31300 N, 10 m) was
installed in August 2008 at the Dongtan Natural Reserve of Birds in
Chongming Island, Shanghai. This site is encircled by rivers on three
sides and by sea on one side. It is linked to the billowy Yangtze River
in the west; faces to the China East Sea in the east. Observation data
of this site can be used to study the aerosol optical properties over
sub-urban area and also to evaluate the effect of marine on aerosol
optical properties over Yangtze River Delta region.
The sunphotometer at Lin’an was installed in June 2005 at
Lin’an Atmospheric Background Station (119 450 E, 30170 N, 139 m). It
is located about 50 km to the west of Hangzhou city and about 8 km to
the north-east of Lin’an County. The observation data could represent
the background characteristics of aerosol optical properties in Yangtze
River Delta Region (Tang et al., 2007). There was also one AERONET site
of ZFU (119 430 E, 30150 N, 14 m) located at Lin’an in 2007 (Chen et al.,
2008) which is about 5 km south-west of the Lin’an site (Fig. 1).
2.2. Instrument calibration and data processing method
The instruments located at Taihu and ZFU are calibrated using
the AERONET calibration facilities in NASA. The master instrument
was calibrated by Langley plot analysis at Mauna Loa Observatory
(155 350 E, 19 320 N, 3397 m Hawaii, USA) following the AERONET
calibration protocol. AOD accuracy is better or at around 0.01,
and radiance is better than 4e5% with the standard laboratory
integrating sphere (Holben et al., 1998; Eck et al., 1999).
Aerosol optical property data of Taihu and ZFU in this study were
from AERONET website (http://aeronet.gsfc.nasa.gov/cgi-bin/type_
piece_of_map_opera_v2_new). Data employed are level 1.5 and
level 2.0 quality-assured data that have been calibrated regularly,
automatically cloud-screened (Smirnov et al., 2000), and manually
inspected for the period of January 2007 to December 2008.
Sunphotometer at Lin’an was firstly calibrated at Izana Observatory (16 300 W, 28 180 N, 2391 m), Spain in 2005. In 2007, it
was inter-compared in Beijing Lingshan Mountain (115 29.760 E,
40 02.960 N, 1517 m) with a new sunphotometer calibrated in Izana.
In 2008, it was re-calibrated by using CARSNET masters at Chinese
Academy of Meteorological Sciences. The calibration protocol has
been given in Che et al. (2008). During the inter-calibration process,
only the raw data during 10:00 AM to 2:00 PM (local time) on the
clean and clear days were used. The AOD at 500 nm measured
by the master instruments on the calibration day should be less
than 0.20 and without much fluctuation. The interval of the
measurements between the two masters and the instruments to be
calibrated should be less than 10 s. The sunphotometer at Pudong
was firstly calibrated in 2006 at Izana Observatory and recalibrated
in February 2008 by inter-comparing with CARSNET masters at
Chinese Academy of Meteorological Sciences. The AOD difference
between the master and the recalibrated instrument is about
0.005 0.015. The sunphotometer at Tongtan was calibrated
twice at Izana Observatory in 2007 and 2008.
By using the calibration coefficients, the AODs of the three
CARSNET sites were retrieved using the AOD module of ASTPWin
software. The Level 1.5 data were cloud screened according to
2589
Smirnov et al. (2000) were used in this study. The data periods
selected in this study are from July 2007 to December 2008 at
Pudong, August 2008 to January 2009 for Dongtan and from
January 2007 to December 2008 at Lin’an.
2.3. Accuracy validation of AOD observed at CARSNET site
On the basis of a comparison between the AOD calculated by
ASTPWin and AERONET, the AOD values by ASTPWin are about 0.03,
0.01, 0.01, and 0.01 larger than those from AERONET at 1020 nm,
870 nm, 670 nm, and 440 nm, respectively (Che et al., 2008). To
valid the AOD results observed at three CARSNET sites in this study,
synchronized observations were compared between two nearby
sites of ZFU and Lin’an. Firstly, the instantaneously observed AODs
within 1-min were selected to be synchronized data from all of
the measurement results at ZFU and Lin’an, respectively. There
were 965 pairs of one-minute synchronized AOD obtained finally.
Secondly, the AOD mean values at ZFU and Lin’an were calculated
respectively according to these 965 synchronized observations.
The comparison showed that the AOD mean values at two sites were
highly correlated (Table 1). The differences of AODs for 1020 nm,
870 nm, 670 nm, 500 nm, 440 nm and Angstrom exponent at Lin’an
were 0.02 less than those at ZFU, respectively, indicating similar
result accuracy between AERONET and CARSNET.
2.4. Comparison method of MODIS AODs with
ground-based observations
To valid the Moderate Resolution Imaging Spectroradiometer
(MODIS) satellite retrieved AOD products (Kaufman et al., 1997;
Remer et al., 2005) over the Yangtze River Delta region in China,
the AODs at 500 nm from the sunphotometer have been converted
to AODs at 550 nm by using Angstrom exponent calculated between
440 nm and 870 nm. The MODIS AODs at 550 nm from the latest
version 5 data collection (C005) (Levy et al., 2007) in Level 2 products during January 2007 to January 2009 were used for comparison. The C005 is granule-based dataset of 5-min segment,
10 10 km pixel and 0.5 0.5 scale (Chu et al., 2003; Ichoku et al.,
2002; Remer et al., 2005). Terra and Aqua passes through Yangtze
River Delta region at 11:00 am and 14:30 pm local time, respectively.
The mean AOD from a 50 50 km scanning region with center close
to each site has been used. The MODIS AODs are compared with
the Cimel 318 sun-photometers mean AODs 2-h before and after the
Terra and Aqua passing, respectively (Yang and Wenig, 2009).
3. Results analysis
3.1. Variation of monthly averaged AOD and Angstrom exponent
Table 2 shows the variation of monthly averaged AODs and
Angstrom exponents at 1020 nm, 870 nm, 670 nm, 500 nm, and
440 nm over Pudong, Taihu, and Lin’an. There are two peaks in the
AOD distributions at Taihu and Lin’an. High AOD occurs in the
summer time at Taihu with a maximum of about 1.41 0.49 at
440 nm in July. High AOD also appears at Lin’an with the maximum
AOD at 440 nm about 1.28 0.46 in September. Low AODs over
Table 1
The result of synchronized observation.
Site
AOD1020
Dongtan
Pudong
ZFU
Lin’an
0.17 0.11
0.20 0.11
0.27 0.16
0.27 0.18
nm
AOD870
nm
0.20 0.14
0.23 0.14
0.35 0.20
0.33 0.22
AOD670
nm
0.28 0.19
0.32 0.20
0.47 0.30
0.47 0.30
AOD500
nm
0.41 0.27
0.48 0.29
0.70 0.43
0.68 0.41
AOD440
nm
0.48 0.31
0.56 0.32
0.81 0.48
0.81 0.48
a440-870 nm
No.
0.80 0.23
1.33 0.22
1.24 0.26
1.32 0.30
359
359
965
965
2590
L. Pan et al. / Atmospheric Environment 44 (2010) 2587e2596
Table 2
Monthly mean AOD and Angstrom exponent at Pudong, Taihu, and Lin’an.
Pudong
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Taihu
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Lin’an
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
AOD1020
AOD870
AOD670
AOD500
AOD440
a440-870
Day
0.17 0.10
0.32 0.13
0.31 0.22
0.39 0.18
0.34 0.32
0.47 0.31
0.30 0.23
0.26 0.17
0.21 0.12
0.22 0.12
0.20 0.11
0.24 0.14
0.20 0.12
0.39 0.16
0.34 0.22
0.46 0.19
0.46 0.27
0.58 0.37
0.38 0.27
0.34 0.23
0.27 0.18
0.27 0.15
0.24 0.14
0.28 0.17
0.28 0.16
0.54 0.22
0.43 0.25
0.60 0.23
0.62 0.37
0.79 0.46
0.52 0.35
0.48 0.35
0.37 0.26
0.38 0.21
0.32 0.19
0.38 0.24
0.43 0.24
0.80 0.32
0.59 0.30
0.85 0.28
0.90 0.54
1.14 0.60
0.78 0.48
0.73 0.51
0.55 0.37
0.60 0.30
0.50 0.28
0.56 0.34
0.50 0.27
0.90 0.35
0.67 0.34
0.97 0.31
1.04 0.59
1.26 0.61
0.90 0.53
0.81 0.55
0.63 0.40
0.69 0.34
0.60 0.30
0.65 0.37
1.37 0.24
1.27 0.22
1.04 0.30
1.14 0.25
1.19 0.32
1.23 0.23
1.31 0.29
1.28 0.23
1.24 0.52
1.41 0.17
1.38 0.14
1.26 0.31
18
12
24
13
22
13
41
29
25
42
39
39
0.31 0.17
0.27 0.13
0.33 0.18
0.39 0.26
0.37 0.20
0.48 0.29
0.63 0.48
0.26 0.17
0.40 0.18
0.34 0.14
0.20 0.13
0.32 0.17
0.37 0.21
0.34 0.17
0.40 0.21
0.46 0.28
0.46 0.23
0.63 0.35
0.75 0.47
0.34 0.23
0.52 0.23
0.43 0.18
0.25 0.16
0.38 0.21
0.49 0.27
0.48 0.24
0.53 0.27
0.59 0.37
0.59 0.29
0.87 0.47
0.94 0.47
0.48 0.34
0.76 0.34
0.67 0.26
0.35 0.22
0.50 0.28
0.71 0.37
0.72 0.34
0.75 0.36
0.81 0.43
0.85 0.41
1.22 0.59
1.26 0.48
0.71 0.50
1.09 0.47
1.00 0.36
0.53 0.34
0.69 0.37
0.81 0.41
0.83 0.37
0.85 0.40
0.92 0.47
0.97 0.46
1.36 0.63
1.41 0.49
0.81 0.55
1.22 0.52
1.22 0.41
0.62 0.31
0.78 0.40
1.18 0.26
1.31 0.20
1.08 0.29
1.06 0.26
1.11 0.33
1.19 0.24
0.99 0.37
1.13 0.23
1.32 0.22
1.48 0.19
1.34 0.19
1.08 0.25
21
45
41
35
49
30
7
28
25
29
39
39
0.34 0.17
0.30 0.18
0.33 0.21
0.52 0.33
0.35 0.22
0.43 0.34
0.27 0.33
0.32 0.30
0.38 0.17
0.27 0.14
0.21 0.12
0.28 0.19
0.41 0.20
0.38 0.21
0.39 0.22
0.59 0.35
0.42 0.25
0.52 0.39
0.33 0.34
0.39 0.32
0.50 0.21
0.34 0.17
0.26 0.16
0.34 0.22
0.56 0.27
0.54 0.27
0.52 0.25
0.74 0.41
0.59 0.32
0.73 0.50
0.46 0.37
0.56 0.38
0.74 0.30
0.50 0.23
0.38 0.23
0.46 0.29
0.79 0.37
0.77 0.34
0.72 0.30
0.98 0.51
0.84 0.42
1.01 0.62
0.66 0.41
0.83 0.47
1.08 0.40
0.75 0.31
0.57 0.32
0.62 0.38
0.92 0.43
0.91 0.38
0.83 0.35
1.10 0.58
0.99 0.47
1.17 0.69
0.79 0.44
0.98 0.52
1.28 0.46
0.89 0.35
0.68 0.38
0.72 0.43
1.22 0.26
1.36 0.31
1.16 0.37
0.93 0.29
1.29 0.32
1.33 0.42
1.49 0.42
1.49 0.38
1.41 0.23
1.48 0.25
1.42 0.24
1.10 0.28
22
35
25
16
45
20
49
42
33
34
38
36
Taihu and Lin’an both occur in November with values about
0.62 0.31 and 0.68 0.38 at 440 nm, respectively. This variation
of AOD at Taihu and Lin’an may be related to weather patterns. Since
the cold air activities are more active in autumn and winter time at
the lower Yangtze River Delta region, the diffusion of pollutants is
accelerated because of the strong wind, which leads to a smaller
aerosol optical depth in Taihu and Lin’an. Moreover, Yangtze River
Delta region could be affected by the dust storm from North China as
well as local pollution sources in spring when precipitation is relatively low (Gong et al., 2003; Cui et al., 2009). The longer residence
time of aerosol particles in the atmosphere could cause large aerosol
optical depth in spring. Precipitation remarkably increases in the
Yangtze River Delta in July and August due to summer Monsoon and
decreases the concentration of atmospheric aerosol. Thus the value
of the aerosol optical depth is the lowest in July and August. Because
the subtropical anticyclone begins to move to north and precipitation decreases from the end of August to the beginning of September,
the AOD in Taihu and Lin’an slightly increases in September.
In contrast, the monthly averaged AOD at Pudong has a single
peak distribution with a maximum of 1.26 0.61 appearing in June
and a minimum of 0.50 0.27 at 440 nm in January. This could be
also related to weather patterns. During the winter time, frequent
cold air activities contribute to the transportation and diffusion
of pollutants. Large-wind days does not occur frequently during the
summer time, which could cause the accumulation of pollutants
due to the stable weather (Duan and Mao, 2007). In addition, more
precipitation in summer could raise the water vapor in the atmospheric over Yangtze Delta region and the aerosol hygroscopic
growth causes the AOD increasing (Li et al., 2007a).
An obvious variation of Angstrom exponent can be seen at the
three stations (Table 1). The maximum value appears in October
with 1.41 0.17 and the minimum appears in March with
1.04 0.30 at Pudong. The maximum value appears in October with
1.48 0.19 and the low values in March, June, and December at
Taihu. The maximum value is 1.46 0.19 in July and August and the
minimum value in April is 0.93 0.29 at Lin’an.
From the above analysis, one can see that the Angstrom exponent reaches a minimum value in spring (w1.10) and maximum
value in autumn (w1.30e1.40). It is probably due to the longdistance transport of dust particles from the north and north-west
China (Gong et al., 2003). In Lin’an, the Angstrom exponent reaches
the maximum value in July and August, indicating that the primary
particles are fine particles during this period. Pollutants in Yangtze
River Delta region are mainly industrial pollutants caused by
anthropogenic emissions or the products of photochemical reactions (Xu et al., 2002). The Angstrom exponent at Taihu station is
a little bit smaller than that at Lin’an station in the same period,
which indicates that there are more and larger particles in the
atmosphere. The Angstrom exponent at Pudong is between Taihu
and Lin’an. The variations of the Angstrom exponent are similar at
all three stations in autumn, indicating that the primary particles
are fine particles in autumn in the Yangtze Delta.
L. Pan et al. / Atmospheric Environment 44 (2010) 2587e2596
3.2. Frequencies of the AOD and Angstrom exponent
The frequency distributions of AOD and Angstrom exponent are
shown in Figs. 2 and 3 respectively. The bin intervals for the AOD at
440 nm and Angstrom exponent between 440 and 870 nm were set
up to 0.20 in this study. It can be seen from Fig. 2 that the frequency
histograms of AOD at Pudong, Taihu and Lin’an showed obvious single
peak distributions. It is found that the AOD can be better characterized
by a lognormal distribution (O’Neill et al., 2000). The results in this
study confirm this point. AOD at Pudong ranged primarily between
0.30-0.90 (Fig. 2a), accounting for 68% of the total occurrence, with the
most frequent distribution of AOD between 0.30 to 0.60 accounting
for 39%. The AOD at Taihu ranged between 0.30 to 1.20 (Fig. 2b),
accounting for 75%, with the most frequent distribution between 0.40
to 0.70 with 31%. The AOD at Lin’an ranged between 0.30e1.20
(Fig. 2c), accounting for 75% frequency of occurrence, with the most
frequent distribution between 0.50 to 0.80 accounting for 30%.
Similar to the distribution of AOD, the frequency histograms of
Angstrom exponent at Pudong, Taihu and Lin’an also showed an
obvious single peak distribution (Fig. 3). The range of the Angstrom
exponent at Pudong varied from 0.20 to 1.80 with a peak between
1.10 and 1.60 (w75%). The same range was observed for Taihu but
the peak between 1.10 and 1.50 (w63%). A broader range of the
Angstrom exponent was observed at Lin’an from w0.05 to 2.15
peaking between 1.20 and 1.60 (w50%).
3.3. Comparison of simultaneous observations over different sites
To decrease the effect of the different of the sample number
during the statistic process and more comprehend the aerosol
2591
optical properties at different sites, synchronized AOD measurements were selected to compare each other. The 359 pairs of
simultaneous AOD (1-min) showed that AOD at 1020 nm, 870 nm,
670 nm, 500 nm and 440 nm over Pudong was larger than those
over Dongtan by 0.03, 0.03, 0.04, 0.07, and 0.08, respectively
(Table 2). It can be concluded that aerosol loadings at Pudong is
obviously larger than Dongtan because of more anthropogenic
activities. The synchronized observations at Pudong, Taihu and
Lin’an (Fig. 4) showed that the three stations had high level AOD at
all wavelengths and the averaged AOD at 440 nm were about 0.68,
0.73, and 0.78, respectively. From the high AOD values over all three
stations, it could be speculated that the aerosol pollution was not
a local but regional phenomenon in the whole Yangtze River Delta
region. The simultaneously measured AOD at Lin’an is similar to
that at Taihu because both sites are surrounded by parkland with
little local aerosol emission. AOD440nm at Pudong were w0.05e0.10
lower than those at Taihu Lake and Lin’an, which may be due to the
situation of Pudong closer to China East Sea. Local emitted aerosol
particles could diffuse to marine area (Liu and Zhou, 1999).
3.4. Comparison of MODIS AODs with the ground-based ones
Fig. 5 shows the retrieved AODs from the MODIS in comparison
with AODs from the ground-based sunphotometer. There are about
193, 280, 334 and 50 coincident days with available data at Pudong,
Taihu, Lin’an and Dongtan, respectively. There are general agreements between the MODIS retrievals and the ground-based AODs at
Pudong, Taihu, Dongtan and Lin’an. The two AODs have a total least
squares linear regression relationship as AODMODIS ¼ AODPudong 0.89 þ 0.33 (R2 ¼ 0.68); AODMODIS ¼ AODTaihu 0.96 þ 0.27 (R2 ¼
Fig. 2. Frequency distribution of Aerosol Optical Depth at (a) Pudong, (b) Taihu and (c) Lin’an.
Fig. 3. Frequency distribution of Angstrom exponent at (a) Pudong, (b) Taihu and (c) Lin’an.
Fig. 4. Synchronized observation within one-minute a (a) Pudong, (b) Taihu and (c) Lin’an.
L. Pan et al. / Atmospheric Environment 44 (2010) 2587e2596
2593
Fig. 5. Comparison between MODIS retrieved AOD and ones measured by ground based sunphotometer at (a) Pudong, (b) Taihu, (c) Lin’an and (d) Dongtan.
0.73); AODMODIS ¼ AODLin’an 0.81 þ 0.03 (R2 ¼ 0.71); AODMODIS ¼
AODDongtan 0.98 þ 0.18 (R2 ¼ 0.79), respectively. The obtained
linear regression relationship indicates that the C005 algorithms
systematically overestimate AOD at Pudong, Taihu, and Dongtan
although these stations show statistically significant positive
correlations, which could be because that most of the aerosols come
from industrial pollution, which are highly scattering sulfate aerosols with small particle size (Mi et al., 2007). However, MODIS
retrieved AODs were systematically underestimate the ground-
based ones at Lin’an with significant positive correlations. This is
similar to the findings at other forest sites in China because the
surface reflectance in MODIS retrieval algorithm is overestimated
and the AOD is underestimated (Li et al., 2007b).
3.5. The effect of wind on AOD and Angstrom exponent
The influence of wind on aerosol optical properties at Pudong
was studied using the meteorological data acquired from the
Table 3
Statistics of AOD, Angstrom exponent, and wind data at 16 azimuths of Pudong.
Wind direction
WD (days)
WS (ms1)
AOD
0
22.5
45
67.5
90
112.5
135
157.5
180
202.5
225
247.5
270
292.5
315
337.5
PPC
1
12
11
27
22
25
24
9
9
e
7
13
9
10
11
5
94
1.50
1.93
1.45
1.84
2.10
2.40
2.07
1.90
1.77
e
1.31
1.69
2.04
1.57
1.82
1.30
0.20
0.19
0.25
0.26
0.25
0.26
0.29
0.27
0.32
0.23
e
0.29
0.36
0.26
0.25
0.31
0.29
0.32
WD: prevailing wind direction occurrence; WS: wind speed.
1020nm
AOD
0.22
0.30
0.31
0.30
0.32
0.35
0.33
0.40
0.28
e
0.34
0.43
0.31
0.31
0.38
0.36
0.39
870nm
AOD
0.28
0.39
0.42
0.41
0.43
0.46
0.42
0.55
0.39
e
0.46
0.58
0.42
0.43
0.53
0.50
0.54
670nm
AOD
0.48
0.66
0.71
0.67
0.72
0.73
0.67
0.95
0.70
e
0.77
0.92
0.69
0.78
0.88
0.85
0.91
440nm
AOD
0.41
0.57
0.62
0.59
0.63
0.65
0.60
0.83
0.61
e
0.68
0.82
0.61
0.67
0.78
0.75
0.80
500nm
Alpha
1.17
1.23
1.27
1.20
1.19
1.03
1.15
1.27
1.38
e
1.23
1.15
1.25
1.39
1.28
1.31
1.31
2594
L. Pan et al. / Atmospheric Environment 44 (2010) 2587e2596
meteorological observation at the Pudong Meteorology Bureau. The
wind data include daily predominant wind direction and averaged
wind speed. Table 3 displays the statistics of AOD, Angstrom
exponent, and wind data at 16 azimuths of Pudong. During the
available sunphotometer measurement period, there were no wind
data occurring at 202.5 . There were 94 calm condition (PPC) days
with wind speed <0.2 ms1 during the measurement period, which
was more than the occurrence days at other directions. The days
with wind direction from east to south-east (67.5 e135 ) were
more than 20 days, while there were only about 10 days at other
directions.
Under the stagnant weather condition (PPC), averaged AOD
and Angstrom exponent at Pudong exponent were as high as 0.90
and 1.30, characterizing the high fine particle loadings. However,
smaller AOD and Angstrom exponent occurred when the wind
direction was from east to south-east (67.5 e135 ) with wind
speed larger than 2.00 ms1 at Pudong. This indicates that wind
from easterly and south-easterly has had contributed to the coarse
aerosols (e.g. sea salt) and that a high wind speed is favorable to
the diffusion of atmospheric particles to reduce the AOD. Larger
values of AOD and Angstrom exponent occurred when the wind
was from other directions. The large AOD occurred under wind
directions from south-westerly and south-easterly directions,
which probably reflects the influences of aerosol particles from
the Jinshan industrial area, the harbor in Nanhui area to Putong,
respectively.
3.6. Back trajectory analysis over different sites
Backward trajectory analysis is a simple and powerful tool for
clarifying the course of the air mass transport (Pack et al., 1978).
The 3-day back trajectory analysis on 850 hPa were calculated to
examine the aerosol sources of different sites by using the hybrid
single-particle Lagrangian integrated trajectory (HYSPLIT) model
of NOAA (Draxler and Rolph, 2003). The analysis resulted in the
identification of 8 clusters for Pudong, Taihu, and Lin’an respectively. One can see that the trajectories for Pudong (Fig. 6a) show
that the majority of the air masses are from the eastern sectors.
There are about 52% airmass (cluster 2, 3, 7, and 8) from marine area
east to Pudong, which corresponds to the low AOD and Angstrom
exponent occurred (Table 4). About 35% air masses (cluster 4, 5, and
6) are from remote areas of Northern China, while w 13% (cluster 1)
are from west of Pudong where there are many industrial activities.
There were about 39% of the airmesses (cluster 2, 6, 7, and 8) for
Taihu from the marine area (Fig. 6b), which is more than that of
Lin’an but less than that of Pudong. This phenomenon proved further
that the simultaneous AOD at Taihu is lower than Lin’an but higher
than Pudong. There are about 20% from local areas (cluster 1), and
28% from north China (cluster 3 and 5), and 11% from the remote area
of Mongolia (cluster 4).
From Fig. 6c one can see that the trajectories for Lin’an distributed more homogeneously than Pudong and Taihu. There were w
35% airmasses (cluster 3, 7, and 8) for Lin’an from marine area,
Fig. 6. Back trajectory analysis at (a) Pudong, (b) Taihu and (c) Lin’an.
L. Pan et al. / Atmospheric Environment 44 (2010) 2587e2596
Table 4
Frequency of the air masses according to the classification method at Lin’an, Taihu
and Pudong.
No.
Lin’an
Taihu
Pudong
Cluster1
Cluster2
Cluster3
Cluster4
Cluster5
Cluster6
Cluster7
Cluster8
16%
15%
20%
4%
21%
9%
9%
6%
21%
24%
18%
11%
10%
9%
5%
1%
13%
25%
17%
10%
8%
17%
9%
1%
and w15% (cluster 2) from south coastal area, and 9% (cluster 6)
from the north-western area. There were 16% were from Yangtze
River Delta region (cluster 1) and 25% of airmasses were from
remote areas of North China and Mongolia (cluster 4 and 5). These
relatively homogeneous back trajectories could reflect the aerosol
sources of Lin’an are more various than Pudong and Taihu. Its
aerosol characteristics could be regarded as a representative of the
whole Yangtze River Delta region.
4. Conclusions and discussions
Aerosol optical properties of Yangtze River Delta region were
analyzed using Cimel sun photometer data from 5 sites of Pudong,
Taihu, Lin’an, Dongtan and ZFU. The conclusions could be drawn as
following:
AOD is high over most areas of the Yangtze River Delta region.
The monthly averaged AOD at 440 nm is above 0.70 at Pudong and
above 0.80 at Taihu and Lin’an. It indicates heavy aerosol loadings in
this region. The AOD has a summer peak, which is possibly related
to the high frequency of stagnant weather and hygroscopic growth
of aerosol particles due to higher levels of atmospheric water vapor.
Angstrom exponent is larger than 1.00 during the whole year at
all sites, which suggests the aerosol were composed mostly of fine
particles. The lower value of Angstrom exponent in spring time
possibly reflects the influences of dust aerosols from north China on
Yangtze River Delta region.
Both AOD and Angstrom exponent occurrence frequencies
at these sites have a normal distribution. The AOD accumulated
mainly between 0.30e0.90, 0.30e1.20 and 0.30e1.20 at Pudong,
Taihu, and Lin’an, respectively. The Angstrom exponent accumulated mainly between 1.10e1.60, 1.10e1.50 and 1.20e1.60 at
Pudong, Taihu, and Lin’an, respectively.
The simultaneous AOD at Pudong was larger than those at
Dongtan by 0.03, 0.03, 0.04, 0.07 and 0.08 at 1020 nm, 870 nm,
670 nm, 500 nm and 440 nm, respectively, which is probably due to
more anthropogenic activities there. The simultaneous AODs at
Pudong are obviously lower than Taihu and Lin’an, which could
be attributed to the coastal effects. The MODIS retrieved AOD
systematically overestimate AOD at Pudong Taihu and Dongtan but
underestimate at Lin’an although all the stations show statistically
significant positive correlations.
Meteorological conditions affect the aerosol optical properties
obviously at Yangtze River Delta region. HYSPLIT results showed
different air masses reaching in this area. The airmasses from
the marine could make the AOD lower in a degree. However, the
characterization of the aerosol type in Yangtze River Delta region is
quite difficult and long-term data are required in order to have clear
aerosol climatology.
Acknowledgement
This work is financially supported by grants from the CAMS
Basis Research Project (2008Y02), Project (40875077) supported
2595
by NSFC, and the National Key Project of Basic Research
(2006CB403702), and. We thank the PIs and their staff for establishing and maintaining the AERONET sites of Taihu and ZFU used in
this study.
References
Breon, F., Tanré, D., Generoso, S., 2002. Aerosols effect on the cloud droplet size
monitored from satellite. Science 295, 834e838.
Charlson, R.J., Schwartz, S.E., Hales, J.M., Cess, D., Coakley, J.A., Hansen, J.E., 1992.
Climate forcing by anthropogenic aerosols. Science 255, 423e430.
Che, H.Z., Shi, G.Y., Zhang, X.Y., Arimoto, R., Zhao, J.Q., Xu, L., Wang, B., Chen, Z.H.,
2005. Analysis of 40 years of solar radiation data from China, 1961e2000.
Geophysical Research Letters 32, L06803. doi:10.1029/2004GL022322.
Che, H., Zhang, X., Li, Y., Zhou, Z., Qu, J.J., 2007. Horizontal visibility trends in
China 1981e2005. Geophysical Research Letters 34, L24706, doi:10.1029/
2007GL031450.
Che, H., Zhang, X., Chen, H., Damiri, B., Goloub, P., Li, Z., Zhang, X., Wei, Y., Zhou, H.,
Dong, F., Li, D., Zhou, T., 2008. Instrument Calibration and Aerosol Optical Depth
(AOD) Validation of the China Aerosol Remote Sensing Network (CARSNET).
Journal of Geophysical Research 114. doi:10.1029/2008JD011030.
Chen, R., Jiang, H., Xiao, Z., Yu, S., Jiao, L., Hong, S., 2008. Monitoring aerosol optical
properties using ground based remote sensing and the change of atmospheric
environment in Hangzhou region. Research of Environmental Sciences 21, 22e26.
Chu, D.A., Kaufman, Y.J., Zibordi, G., Chern, J.D., Mao, J., Li, C., Holben, B.N., 2003.
Global monitoring of air pollution over land from the Earth Observing SystemTerra Moderate Resolution Imaging Spectroradiometer (MODIS). Journal of
Geophysical Research 108, 4661. doi:10.1029/2002JD003179.
Cui, W., Guo, R., Zhang, H., 2009. The long-range transport of dust from Mongolia
Gobi to the Yangtze River basin and its mixing with pollutant aerosols. Journal
of Fudan University (Natural Science) 48 (5), 585e592.
Draxler, R.R., Rolph, G.D., 2003. HYSPLIT (HYbrid Single-Particle Lagrangian Integrated
Trajectory) Model access via NOAA ARL READY. NOAA Air Resources Laboratory,
Silver Spring, MD. Website. http://www.arl.noaa.gov/ready/hysplit4.html.
Duan, J., Mao, J., 2007. Study on the distribution and variation trends of atmospheric
aerosol op tical dep th over the Yangtze River Delta. Acta Scientiae Circumstantiae 27 (4), 537e543.
Dubovik, O., Holben, B.N., Eck, T.F., Smirnov, A., Kaufman, Y.J., King, M.D., Tanré, D.,
Slutsker, I., 2002. Variability of absorption and optical properties of key aerosol
types observed in worldwide locations. Journal of the Atmospheric Sciences 59,
590e608.
Eck, T.F., Holben, B.N., Reid, J.S., Dubovik, O., Smirnov, A., O’Neill, N.T., Slutsker, I., Kinne, S.,
1999. Wavelength dependence of the optical depth of biomass burning, urban, and
desert dust aerosols. Journal of Geophysical Research 104, 31333e31349.
Eck, T.F., Holben, B.N., Dubovik, O., Smirnov, A., Goloub, P., Chen, H.B., Chatenet, B.,
Gomes, L., Zhang, X.Y., Tsay, S.C., Ji, Q., Giles, D., Slutsker, I., 2005. Columnar
aerosol optical properties at AERONET sites in central eastern Asia and aerosol
transport to the tropical mid-Pacific. Journal of Geophysical Research 110,
D06202. doi:10.1029/2004JD005274.
Gong, S.L., Zhang, X.Y., Zhao, T.L., McKendry, I.G., Jaffe, D.A., Lu, N.M., 2003. Characterization of soil dust aerosol in China and its transport and distribution
during 2001 ACE-Asia: 2. Model simulation and validation. Journal of
Geophysical Research 108 (D9), 4262,. doi:10.1029/2002JD002633.
Han, Z., Zhang, R., Wang, Q., Wang, W., Cao, J., Xu, J., 2008. Regional modeling of
organic aerosols over China in summertime. Journal of Geophysical Research
113, D11202,. doi:10.1029/2007JD009436.
Hansen, J., Sato, M., Ruedy, R., 1997. Radiative forcing and climate response. Journal
of Geophysical Research 102, 6831e6864.
Hansen, J., Sato, M., Ruedy, R., Lacis, A., Oinas, V., 2000. Global warming in the
twenty-first century: An alternative scenario. Proceedings of the National
Academy of Sciences of the United States of America 97, 9875e9880.
Holben, B.N., Eck, T.F., Slutsker, I., Tanré, D., Buis, J.P., Setzer, A., Vermote, E.,
Reagan, J.A., Kaufman, Y.J., Nakajima, T., Lavenu, F., Jnnkowiak, I., Smirnov, A.,
1998. AERONET e a federated instrument network and data archive for aerosol
characterization. Remote Sensing of Environment 66 (1), 1e16.
Holben, B.N., Tanré, D., et al., 2001. An emerging ground-based aerosol climatology: aerosol
optical depth from AERONET. Journal of Geophysical Research 106, 12067e12097.
Ichoku, C., Chu, D.A., Mattoo, S., Kaufman, Y.J., Remer, L.A., Tanré, D., Slutsker, I.,
Holben, B.N., 2002. A spatiotemporal approach for global validation and analysis of MODIS aerosol products. Geophysical Research Letters 29, 8006.
doi:10.1029/2001GL013206.
Kaufman, Y.J., Tanré, D., Remer, L.A., Vermote, E.F., Chu, A., Holben, B.N., 1997.
Operational remote sensing of tropospheric aerosol over land from EOS
moderate resolution imaging Spectroradiometer. Journal of Geophysical
Research 102 (D14), 17,051e17,067.
Kleidman, R.G., O’Neill, N.T., Remer, L.A., Kaufman, Y.J., Eck, T.F., Tanré, D.,
Dubovik, O., Holben, B.N., 2005. Comparison of Moderate Resolution Imaging
Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) remotesensing retrievals of aerosol fine mode fraction over ocean. Journal of
Geophysical Research 110, D22205. doi:10.1029/2005JD005760.
Levy, R.C., Remer, L.A., Mattoo, S., Vermote, E.F., Kaufman, Y.J., 2007. Second-generation
operational algorithm: Retrieval of aerosol properties over land from inversion of
2596
L. Pan et al. / Atmospheric Environment 44 (2010) 2587e2596
Moderate Resolution Imaging Spectroradiometer spectral reflectance. Journal of
Geophysical Research 112, D13211,. doi:10.1029/2006JD007811.
Li, C.C., Mao, J.T., Lau, A.K.H., Chen, J.C., Yuan, Z.B., Liu, X.Y., Zhu, A.H., Liu, G.Q., 2003.
Characteristics of distribution and seasonal variation of aerosol optical depth in
eastern China with MODIS products. Chinese Science Bulletin 48 (22), 2488e2495.
Li, Z., Xia, X., Cribb, M., Mi, W., Holben, B., Wang, P., Chen, H., Tsay, S.-C., Eck, T.F.,
Zhao, F., Dutton, E.G., Dickerson, R.R., 2007a. Aerosol optical properties and
their radiative effects in northern China. Journal of Geophysical Research 112,
D22S01. doi:10.1029/2006JD007382.
Li, Z., Niu, F., Lee, K.-H., Xin, J., Hao, W.-M., Nordgren, B., Wang, Y., Wang, P., 2007b.
Validation and understanding of Moderate Resolution Imaging Spectroradiometer aerosol products (C5) using ground-based measurements from the
handheld Sun photometer network in China. Journal of Geophysical Research
112, D22S07. doi:10.1029/2007JD008479.
Liu, Y., Zhou, M., 1999. Atmospheric input of aerosols to the eastern seas of China.
Acta Oceanologica Sinica 21 (5), 38e45.
Luo, Y., Lu, D., Zhou, X., Li, W., 2002. Analyses on the spatial distribution of aerosol
optical depth over china in recent 30 years. Chinese Journal of Atmospheric
Sciences 26, 721e730.
Menon, S., Hansen, J.E., Nazarenko, L., Luo, Y.F., 2002. Climate effects of black carbon
aerosols in China and India. Science 297, 2249e2252.
Mi, W., Li, Z., Xia, X., Holben, B., Levy, R., Zhao, F., Chen, H., Cribb, M., 2007. Evaluation of the Moderate Resolution Imaging Spectroradiometer aerosol products
at two Aerosol Robotic Network stations in China. Journal of Geophysical
Research 112, D22S08. doi:10.1029/2007JD008474.
O’Neill, N.T., Ignatov, A., Holben, B.N., Eck, T.F., 2000. The lognormal distribution as
a reference for reporting aerosol optical depth statistics: empirical tests using
multi-year, multi-site AERONET sunphotometer data. Geophysical Research
Letters 27 (20), 3333e3336.
Pack, D.H., Ferber, G.J., Heffter, J.L., Telegadas, K., Angell, J.K., Hoecker, W.H.,
Machta, L., 1978. Meteorology of long-range transport. Atmospheric Environment 12 (1e3), 425e444.
Remer, L.A., Kaufman, Y.J., Tanré, D., Mattoo, S., Chu, D.A., Martins, J.V., Li, R.R.,
Ichoku, C., Levy, R.C., Kleidman, R.G., Eck, T.F., Vermote, E., Holben, B.N., 2005.
The MODIS aerosol algorithm, products, and validation. Journal of the Atmospheric Sciences 62, 947e973.
Smirnov, A., Holben, B.N., Eck, T.F., Slutsker, I., Chatenet, B., Pinker, R.T., 2002. Diurnal
variability of aerosol optical depth observed at AERONET (Aerosol Robotic Network)
sites. Geophysical Research Letters 29 (23), 2115. doi:10.1029/2002GL016305.
Smirnov, A., Holben, B.N., Eck, T.F., Dubovik, O., Slutsker, I., 2000. Cloud screening
and quality control algorithms for the AERONET database. Remote Sensing of
Environment 73, 337e349.
Stanhill, G., Cohen, S., 2001. Global dimming: a review of the evidence for a widespread and significant reduction in global radiation with discussion of its
probable causes and possible agricultural consequences. Agricultural and Forest
Meteorology 107, 255e278.
Tang, J., Wang, M., Cheng, H., 2007. Variation Characteristics of Ambient NMHCs at
Shangdianzi and Lin’an Regional GAW Sites. Acta Meteorologica Sinica 21 (3),
334e341.
Twomey, S.A., Piepgrass, M., Wolfe, T.L., 1984. An Assessment of the impact of
pollution on the global cloud Albedo. Tellus 36B, 356e366.
Wang, Y., Xin, J., Li, Z., Wang, P., Wang, S., Wen, T., Sun, Y., 2006. AOD and Angstrom
parameters of aerosols observed by the Chinese Sun Hazemeter Network from
August to December 2004. Environmental Science 27, 1703e1711.
Xia, X., Li, Z., Holben, B., Wang, P., Eck, T., Chen, H., Cribb, M., Zhao, Y., 2007.
Aerosol optical properties and radiative effects in the Yangtze Delta
region of China. Journal of Geophysical Research 112, D22S12. doi:10.1029/
2007JD008859.
Xu, J., Bergin, M.H., Yu, X., Liu, G., Zhao, J., Carrico, C.M., Baumann, K., 2002.
Measurement of aerosol chemical, physical and radiative properties in
the Yangtze delta region of China. Atmospheric Environment 36 (2),
161e173.
Yang, X., Wenig, M., 2009. Study of columnar aerosol size distribution in Hong Kong.
Atmospheric Chemistry and Physics 9, 6175e6189.