Atmospheric Research 92 (2009) 434–442
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Atmospheric Research
j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / a t m o s
Characteristics of organic and elemental carbon in PM2.5 samples in
Shanghai, China
Yanli Feng a, Yingjun Chen b,c,⁎, Hui Guo d, Guorui Zhi c, Shengchun Xiong a, Jun Li c,
Guoying Sheng a,c, Jiamo Fu a,c
a
b
c
d
Institute of Environmental Pollution and Health, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
Yantai Institute of Coastal Zone Research for Sustainable Development, Chinese Academy of Sciences, Yantai, Shandong Province 264003, China
State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
Mud Logging Company, Great Wall Drilling Project Co. Ltd., Panjin, Liaoning 124010, China
a r t i c l e
i n f o
Article history:
Received 22 April 2008
Received in revised form 4 November 2008
Accepted 5 January 2009
Keywords:
Organic carbon
Elemental carbon
Fine particle (PM2.5)
Seasonal variation
Shanghai
a b s t r a c t
Shanghai is the largest industrial and commercial city in China, and its air quality has been
deteriorating for several decades. However, there are scarce researches on the level and
seasonal variation of fine particle (PM2.5) as well as the carbonaceous fractions when compared
with other cities in China and around the world. In the present paper, abundance and seasonal
characteristics of PM2.5, organic carbon (OC) and elemental carbon (EC) were studied at urban
and suburban sites in Shanghai during four season-representative months in 2005–2006 year.
PM2.5 samples were collected with high-vol samplers and analyzed for OC and EC using
thermal-optical transmittance (TOT) protocol. Results showed that the annual average PM2.5
concentrations were 90.3–95.5 μg/m3 at both sites, while OC and EC were 14.7–17.4 μg/m3 and
2.8–3.0 μg/m3, respectively, with the OC/EC ratios of 5.0–5.6. The carbonaceous levels ranked by
the order of Beijing N Guangzhou N Shanghai N Hong Kong. The carbonaceous aerosol accounted
for ∼ 30% of the PM2.5 mass. On seasonal average, the highest OC and EC levels occurred during
fall, and they were higher than the values in summer by a factor of 2. Strong correlations
(r = 0.79–0.93) between OC and EC were found in the four seasons. Average level of secondary
organic carbon (SOC) was 5.7–7.2 μg/m3, accounting for ∼ 30% of the total OC. Strong seasonal
variation was observed for SOC with the highest value during fall, which was about two times
the annual average.
© 2009 Elsevier B.V. All rights reserved.
1. Introduction
Carbonaceous aerosol constitutes a significant fraction of
fine particles (PM2.5), and it could account for up to 40% of PM2.5
mass in urban atmosphere (Seinfeld and Pandis, 1998).
Carbonaceous species are usually classified into elemental
carbon (EC) and organic carbon (OC). EC (sometimes called
black carbon) derived from incomplete combustion of carboncontained materials, while OC can be either released directly
⁎ Corresponding author. Yantai Institute of Coastal Zone Research for
Sustainable Development, Chinese Academy of Sciences, Yantai, Shandong
Province 264003, China. Tel.: +86 535 2109151; fax: +86 535 2109151.
E-mail address: [email protected] (Y. Chen).
0169-8095/$ – see front matter © 2009 Elsevier B.V. All rights reserved.
doi:10.1016/j.atmosres.2009.01.003
into the atmosphere (primary OC, POC) or produced from gasto-particle reactions (secondary OC, SOC) (Pandis et al., 1992;
Turpin and Huntzicker, 1995). EC has strong absorption of solar
radiation and is one of the important drivers of global warming
(Hansen et al., 2005). OC represents a mixture of hundreds of
organic compounds, some of which are mutagenic and/or
carcinogenic, such as polycyclic aromatic hydrocarbons (PAHs)
and polychlorinated dibenzo-p-dioxins and dibenzofurans
(PCDD/Fs) (Feng et al., 2006; Li et al., 2008).
Carbonaceous aerosol in China has drawn special attention
in recent years due to its adverse effects on environment and
human health and potential influence on climate change
(Hamilton and Mansfield, 1991; Qiu and Yang, 2000; Jacobson,
2002). It has been estimated that China contributes roughly
Y. Feng et al. / Atmospheric Research 92 (2009) 434–442
one-fifth of the global carbonaceous emissions (Bond et al.,
2004). Jacobson (2002) suggested that emission reduction of
fossil-fuel carbonaceous particles was possibly the most
effective method of slowing global warming. The increased
EC aerosols may be responsible for the significant variation of
precipitation in eastern China over the past decades (Menon
et al., 2002). EC also contributed to the marked degradation of
optical depths and visibility in northern China (Qiu and Yang,
2000), and lowered the crop yields by reducing solar radiation
that reaches the earth (Chameides et al., 1999).
There are several studies focusing on the field measurements of carbonaceous abundance in PM2.5 in China's
industrialized areas, such as Guangzhou and Hong Kong in
Pearl River Delta Region (Ho et al., 2002, 2003, 2006; Cao
et al., 2003, 2004, 2005; Chow et al., 2005; Duan et al., 2007),
Beijing (He et al., 2001, 2004a; Dan et al., 2004; Duan et al.,
2006), and other cities (Guo et al., 2004; Cao et al., 2005; Yang
et al., 2005b). However, there are only limited studies in
Shanghai (Ye et al., 2003; Yang et al., 2005a; Feng et al., 2006),
which is the largest commercial and industrial city in China
and also one of the world's largest seaports. World Expositions will be held here in 2010. Furthermore, one-year
carbonaceous measurements by Ye et al. (2003) and Yang
et al. (2005a) were finished during 1999–2000 year, and since
then the air pollution in Shanghai is ameliorating observably.
For example, annual PM10 concentration in Shanghai was
100.5 μg/m3 in 2001 versus 86.2 μg/m3 in 2006 (http://www.
envir.gov.cn/airnews/).
Ambient air quality in Shanghai began to deteriorate in the
1960s due to large consumption of low-quality coal for rapid
industrial development. When coal smoke was somewhat
controlled in the 1990s, vehicular population in Shanghai
soared up to ∼ 2 million, and the type of air pollution in
Shanghai evolved into the combination of coal smoke with
vehicular exhaust (Chen, 2003). Great concern on the
visibility reduction and public health has been drawn by the
heavy PM pollution in Shanghai (Ye et al., 2000), and the
primary carbonaceous emission in 2000 was about 16.3 Gg
(gigagrams or ktons) for EC and 34.0 Gg for OC (Cao et al.,
2006).
435
The purpose of this paper is to present updated knowledge
on abundance and seasonal characteristics of PM2.5-associated EC and OC in Shanghai, which is helpful to investigate
of their sources and PM control strategies.
2. Methodology
2.1. Sampling sites description
Shanghai is located at the east end of the Yangtze River
Delta Region and faces the East China Sea (Fig. 1), and
possesses a population of over 15 million and a land area of
about 6340 km2. Shanghai belongs to the northern subtropical monsoon climate, and northwest wind prevails in
wintertime whereas southeast wind in summertime. Annual
average of temperature in Shanghai is 15.8 °C, with the lowest
in January (3.6 °C) and the highest in July (27.8 °C).
In this study, two sites were selected for PM2.5 sample
collection in Shanghai: one is in Zha-bei district (ZB) of
downtown area, the other is in Jia-ding district (JD) which
belongs to suburban area in northwest (Fig. 1). Brief
descriptions for the sampling sites are given as follows.
ZB Site: It is located in the Yan-chang campus of Shanghai
University in Zha-bei district. The sampler was placed on the
rooftop of nine-storeyed office building (about 25 m above
ground level). This site is surrounded by low-rise office and
residential buildings. A road with moderate traffic passes by
300 m away from this site in the north, and another road with
heavy traffic 1.4 km away in the west. This site represents a
mixed residential, traffic, and commercial environments of
urban area.
JD Site: It is situated at the Environmental Monitoring
Station (EMS) of Jia-ding district, which is a suburban area
with quick urbanization and industrial development in recent
years. The sampler was mounted on the top of four-storeyed
office building (about 10 m above ground) and was adjacent
to other samplers of the EMS. Many two- or three-storeyed
residential buildings are distributed around this site. A road
with slight traffic passes by 50 m away in the south, and some
small chimneys (burning low-quality coal) from a glass
Fig. 1. Location of the sampling sites in Shanghai.
436
Y. Feng et al. / Atmospheric Research 92 (2009) 434–442
Fig. 2. Comparison of monthly average (MA) with seasonal average (SA) of PM10, SO2, and NO2 concentrations in Shanghai, China. (Note: The averaged values in the
figure were calculated from the daily measurements by the Shanghai Environmental Monitoring Center (http://www.envir.gov.cn/airnews/)).
factory are observed ∼100 m away across the road. This site
represents a residential and slightly industrialized environment of suburban area.
2.2. Sample collection
Samples were collected almost simultaneously at both ZB
and JD Sites in four months: October in 2005, January, April, and
July in 2006, which were selected to represent the four seasons
in Shanghai respectively, i.e., fall, winter, spring, and summer.
The representativeness of each selected month for the entire
season was confirmed by the levels of PM10, SO2, and NO2 in
Shanghai during the same calendar year (http://www.envir.gov.
cn/airnews/). As illustrated in Fig. 2, the averaged concentrations of PM10, SO2, and NO2 in the selected four months were
very similar to the four seasonal averages, respectively.
Furthermore, the annually averaged concentrations of PM10,
SO2 and NO2 were very close to the mean levels of the selected
four months, respectively. For example, the annual average of
PM10 was 89.5 μg/m3 while the average value of the four months
was 87.3 μg/m3, and the relative deviation was less than 3%.
During the four weeks of each sampling month, two 24-h
PM2.5 samples (from morning to morning) were collected in
each week to include both weekday (Wednesday) and
weekend (Sunday). Sampler applied was high-volume
Andersen model SA235 equipped with 2.5 μm inlet at flow
rate of 1.13 m3/min (Thermal Electric Inc., USA) and quartzfiber filters (QFFs) of 20.3 × 25.4 cm (Whatman, England). The
meteorological parameters, including ambient temperature,
relative humidity, wind speed/direction, and precipitation of
each sampling day were recorded through a Hand-held
Weather Monitoring (Kestrel-1000, USA). A total of 62 valid
PM2.5 samples were collected at two sites, excluding one
sample during fall at ZB Site and one in winter at JD due to
incidental failure of electrical supply.
All QFFs were pre-baked at 450 °C for 5 h before sampling to
remove residual carbon. Before and after exposure, all filters were
weighed using an electronic balance (Satouris, 0.01 mg, Germany) under constant temperature (25 °C) and relative humidity
(50%) in a climate chamber (Binder KBF-115, Germany) for 24 h.
All samples were stored in refrigerator at −20 °C for late analysis.
All procedures during handling of filters were strictly qualitycontrolled to avoid any possible contamination.
2.3. Carbonaceous analysis and quality control
The samples were analyzed for EC and OC using a thermaloptical transmittance analyzer (TOT, Sunset Laboratory Inc.,
USA) in the State Key Laboratory of Organic Geochemistry in
Guangzhou, China. This instrument has a temperature- and
atmosphere-controlled oven and a laser of 680 nm wavelength to generate an operational EC/OC split (Birch and Cary,
1996). Temperature procedure performed in the present
study was similar to NIOSH method (Birch, 1998): punch
aliquot (1.5 cm2) of a QFF sample was heated stepwise in the
oven at 250 °C (60 s), 500 °C (60 s), 650 °C (60 s), and 850 °C
(90 s) in pure helium atmosphere for OC volatilization, and
550 °C (45 s), 650 °C (60 s), 750 °C (60 s), and 850 °C (80 s) in
2% oxygen-contained helium atmosphere for EC oxidation.
Some charred OC during inert period was corrected by the
laser transmittance. At the end of sample evolvement, a
known volume of methane was analyzed as internal standard
for calculation of OC and EC concentrations.
For quality control, the analyzer was calibrated using filter
blank (pre-heated QFF punch) and standard sucrose solutions
every day. Duplicate punches from each sample were
analyzed to eliminate nonuniformity of depositions on the
filter. Replicate analyses were performed with 10% of total
samples, and the differences indicated by replicate analyses
was within 5% for OC and EC. Four field blanks for each site
Y. Feng et al. / Atmospheric Research 92 (2009) 434–442
437
Table 1
Average concentrations of PM2.5, OC and EC and their ratios in Shanghai.
Sampling site
Season
PM2.5 (μg/m3)
OC (μg/m3)
EC (μg/m3)
OC/EC
TCA/PM2.5 a (%)
ZB
Annual
Fall, 2005
Winter, 2005
Spring, 2006
Summer, 2006
Annual
Fall, 2005
Winter, 2005
Spring, 2006
Summer, 2006
90.3 ± 54.9
106.4 ± 63.2
93.4 ± 44.1
113.5 ± 65.5
50.2 ± 23.0
95.5 ± 41.8
113.3 ± 48.7
88.0 ± 41.8
113.1 ± 36.2
66.9 ± 24.6
14.7 ± 10.1
21.8 ± 14.2
16.7 ± 8.4
14.1 ± 6.5
7.2 ± 5.6
17.5 ± 9.8
25.8 ± 11.4
16.1 ± 8.0
16.4 ± 7.1
11.4 ± 7.2
2.8 ± 1.3
3.9 ± 1.3
2.3 ± 1.0
3.1 ± 1.5
1.9 ± 0.6
3.0 ± 1.2
3.8 ± 1.3
2.3 ± 1.0
3.3 ± 1.2
2.7 ± 0.7
5.0 ± 1.9
5.3 ± 2.0
6.8 ± 1.7
4.5 ± 0.9
3.4 ± 1.5
5.6 ± 2.1
6.8 ± 2.3
6.9 ± 1.9
5.1 ± 1.5
4.0 ± 1.6
28.9 ± 6.5
36.1 ± 4.1
31.5 ± 4.5
23.8 ± 4.1
25.1 ± 4.9
32.0 ± 7.7
40.4 ± 5.4
32.2 ± 3.9
25.9 ± 5.6
29.7 ± 7.1
JD
Values represent average ± one standard deviation.
a
TCA means total carbonaceous aerosol and is calculated by the sum of organic matter (OC multiplies by 1.6) and EC.
were collected by sampling for 5 min and analyzed to
examine operational contamination of the field samples in
four months. Generally, the concentrations of PM2.5, OC, and
EC on the field blanks were less than 1% of the sample batches,
and were not subtracted from the samples.
3. Results and discussion
3.1. Levels of PM2.5, OC and EC in Shanghai
The statistics for PM2.5 mass, OC and EC at both sampling
sites in Shanghai are presented in Table 1. Firstly, it can be
seen that the levels of PM2.5 and carbonaceous fractions at
suburban site (JD) (95.5 ± 41.8 μg/m3) are a little higher than
that at urban site (ZB) (90.3 ± 54.9 μg/m3), suggesting that fine
particle pollution occurred not only in the urban, but also in
the suburban area of Shanghai. Similar situation was observed
by Feng et al. (2006) that there was no clear difference of
carbonaceous concentrations between urban and rural areas
in Shanghai. In spite of the difference of sampling heights at
two sites, it may be inferred that the rapid urbanization and
relocation of industrial plants in the past two decades have
blurred the lines of ambient air pollution between urban and
rural areas in Shanghai.
Secondly, ambient air pollution of PM2.5 in Shanghai is a
serious matter of concern as per the U.S. National Ambient Air
Quality Standard (NAAQS) annual average of 15 μg/m3 (http://
www.epa.gov/air/criteria.html). Ye et al. (2003) also reported
∼60.0 μg/m3 of annual PM2.5 concentration in Shanghai urban
areas. However, it was reported that the air quality in Shanghai in
recent years came up to the Class II Level of Chinese national
PM10 standards (GB3095-1996, the upper limit for annual
average is 100 μg/m3 for Class II areas, such as urban residential,
commercial and traffic, industrial, and rural areas, etc.) (http://
www.envir.gov.cn/airnews/). This situation also occurs in
Guangzhou, which is the dirtiest city in Pearl River Delta Region
(PRDR) and its PM2.5 level (102.7–129.9 μg/m3) (Duan et al.,
2007) is comparable to Shanghai and Beijing (115.0–127.0 μg/m3)
(He et al., 2001), but its annual PM10 concentrations also reached
the Class II Level (http://www.gdepb.gov.cn/). The high percentage of PM2.5 in PM10, e.g., 70% in PRDR (Cao et al., 2003, 2004),
may interpret the severe PM2.5 pollutions in these areas. In a
word, recent air qualities in these cities reached the Chinese
PM10 standard, while were severely polluted as per U.S. PM2.5
standard. This inconsistency implies an urgent demand for PM2.5
standard in China.
The annual average concentrations of OC and EC in Shanghai
are 14.7 ± 10.1 and 2.8 ± 1.3 μg/m3 at ZB Site, and 17.5± 9.8 and
3.0 ± 1.2 μg/m3 at JD, respectively. The inverted condition that
carbonaceous pollution in the suburban area was higher than in
the urban one was consistent with the PM2.5 levels discussed
above. These carbonaceous abundances in Shanghai were
comparable to the reported values in November 2002
(∼16.0 μg/m3 for OC and ∼4.0 μg/m3 for EC) by Feng et al.
(2006). Ye et al. (2003) also presented similar annual
concentrations of total carbon (TC, sum of OC and EC) in
Shanghai (∼21.0 μg/m3), although the EC fractions were a little
higher (6.2–6.8 μg/m3) due to the employment of different
carbon analysis protocol of thermal-optical reflectance (TOR)
(Chow et al., 2001). Source apportionment results suggested
that the carbonaceous pollution in Shanghai mainly derived
from vehicular exhaust (∼50%), coal smoke (∼15%), and kitchen
emissions (∼10%) (Feng et al., 2006), and was also significantly
affected by biomass burning (Yang et al., 2005a).
Fang et al. (2008) recently reviewed carbonaceous
pollution in Asian cities. PM2.5-associated OC and EC
concentrations in mainland China ranged in 1.4–21.2 and
3.3–20.2 μg/m3, respectively. As a matter of comparison, the
values were 17.0 and 10.4–11.6 μg/m3 in Taiwan, 3.3–18.0 and
0.2–8.4 μg/m3 in Korea, and 1.1–5.2 and 2.3–4.5 μg/m3 in
Japan, respectively (Fang et al., 2008 and references therein).
It should be noted that various techniques were used for
OCEC measurements other than TOT in these studies, such as
TOR, TMO (thermal manganese dioxide oxidation), EA (C/H/N
elemental analyzer), combustion method etc. Although a
good agreement for TC values was generally obtained from
these methods, EC concentration usually differs by a factor of
2 or more (Watson et al., 2005). Thus Table 2 only summarizes some measurements by TOT method to compare the
carbonaceous level in Shanghai with other cities in China and
around the world. PM2.5 OC and EC concentrations in China
ranked in the following order: Beijing (21.4–25.6 μg/m3 and
5.6–5.7 μg/m3 for OC and EC, respectively) N Guangzhou
(18.4–22.6 and 4.8–6.4 μg/m3) N Shanghai (9.9–17.4 and 2.8–
3.1 μg/m3) ≈ Nanjing (13.2–14.2 and 2.9–3.7 μg/m3) N Hong
Kong (5.8–12.0 and 1.1–3.4 μg/m3), and the range of concentrations was obviously higher than those in urban sites of
Europe and North America.
438
Y. Feng et al. / Atmospheric Research 92 (2009) 434–442
Table 2
Comparison of PM2.5 OC and EC concentrations measured by TOT method in Shanghai with other cities in China and in the world.
City
Site
Period
OC (μg/m3)
EC (μg/m3)
OC/EC
Reference
Shanghai
ZB (urban)
JD (suburban)
FDU (urban)
SHO (rural)
PKU (urban)
AES (suburban)
TH (urban)
LG (suburban)
WS, LW (urban)
YL, TW (urban)
HT (rural)
NJU (urban)
PMO (suburban)
Urban
Urban
Urban
Urban
Urban
Urban
Urban
Urban
Urban
Oct 2005–Aug 2006
Oct 2005–Aug 2006
Nov 2002, Aug 2003
Nov 2002, Aug 2003
Jul, Nov 2002
Jul, Nov 2002
Dec 2002, Jul 2003
Dec 2002, Jul 2003
Aug–Sep 2004, Feb–Mar 2005
Aug–Sep 2004, Feb–Mar 2005
Aug–Sep 2004, Feb–Mar 2005
Feb, Sep 2001
Feb 2001
Jul–Aug 2005, Jan–Feb 2006
Jul–Aug 2004, Nov–Dec 2004
Jun–Jul 2004, Jan–Feb 2005
2002–2003
Jul 2000–Jul 2001
Apr–May 2002
Aug 2001
Jul 2001
Apr–May 1999
14.7 ± 10.1
17.4 ± 9.7
9.9 ± 8.4
10.7 ± 8.2
21.4 ± 5.4
25.6 ± 11.3
18.4 ± 11.1
22.6 ± 15.1
20.7 ± 3.7
12.0 ± 1.0
5.8 ± 0.2
13.2 ± 3.4
14.2
5.3 ± 2.0
5.3 ± 2.3
4.1 ± 1.9
9.6 ± 6.2
3.0 ± 0.6
6.8
3.6
7.3
5.7
2.8 ± 1.3
3.1 ± 1.5
2.9 ± 1.6
2.9 ± 1.1
5.7 ± 0.0
5.6 ± 0.1
6.4 ± 0.4
6.5 ± 0.1
4.8 ± 0.8
3.4 ± 1.1
1.1 ± 0.4
3.7 ± 0.5
2.9
1.8 ± 0.1
2.1 ± 0.8
1.0 ± 0.3
1.4 ± 0.3
1.1 ± 0.3
3.3
0.3
0.7
0.9
5.0
5.6
3.4
3.8
3.8
4.6
2.9
3.5
4.3
3.5
5.2
3.6
4.9
2.9
2.6
4.1
6.9
2.6
2.1
11.2
10.5
6.1
This study
This study
Feng et al. (2006)
Feng et al. (2006)
Feng et al. (2006)
Feng et al. (2006)
Feng et al. (2006)
Feng et al. (2006)
Duan et al. (2007)
Duan et al. (2007)
Duan et al. (2007)
Yang et al. (2005b)
Yang et al. (2005b)
Viana et al. (2007)
Viana et al. (2007)
Viana et al. (2007)
Lonati et al. (2007)
Viidanoja et al. (2002)
Salma et al. (2004)
Fan et al. (2004)
Fan et al. (2003)
Lewtas et al. (2001)
Beijing
Guangzhou
Hong Kong
Nanjing
Amsterdam, Netherlands
Barcelona, Spain
Ghent, Belgium
Milan, Italy
Helsinki, Finland
Budapest, Hungary
Vancouver, Canada
Toronto, Canada
Seattle, USA
3.2. Seasonal characteristics of PM2.5, OC and EC
Strong seasonal variations of PM2.5, OC and EC in Shanghai
have been shown in Table 1 and Fig. 3. The seasonally
averaged PM2.5 concentrations were highest in spring
(113.5 μg/m3 at ZB) or fall (113.3 μg/m3 at JD) whereas lowest
in summer (50.2 μg/m3 at ZB and 66.9 μg/m3 at JD), and they
differed approximately by a factor of 2; PM2.5 levels in winter
(93.4 μg/m3 at ZB and 87.9 μg/m3 at JD) were close to the
annual average values (Table 1). This pattern of PM2.5 was
very similar to the seasonal average PM10 concentrations
during 2005–2006 year in Shanghai, i.e., 95.6, 83.7, 115.7 and
59.6 μg/m3 from fall to summer, respectively (http://www.
envir.gov.cn/airnews/). Ye et al. (2003) reported similar trends
of PM2.5 concentrations in two urban sites during 1999–
2000 yr except the maxima appeared in winter, which may be
attributed to the highest PM2.5 concentration period of late
fall and early winter (November and December) occurred in
Fig. 3. Variations of PM2.5 mass, OC, EC, OC/EC ratio, and fraction of TCA in PM2.5 at ZB and JD Sites in Shanghai.
Y. Feng et al. / Atmospheric Research 92 (2009) 434–442
their sampling campaign. Fig. 3 illustrates the subtle variations of PM2.5 levels in both the sites. For example, the
maximum PM2.5 concentration of 255.9 μg/m3 occurred on
April 19, 2006 at ZB and 173.5 μg/m3 on October 30, 2005 at
JD, which was 10 and 6 times the minimum values,
respectively.
The seasonal characteristics of PM2.5 concentrations in
Shanghai can be explained as the combined impact of climatic
conditions and local emissions. During monsoon seasons of
Shanghai, i.e., usually from May to September, clean winds
coming from the East China Sea together with abundant
precipitation can relieve ambient air pollution to a great
extent. However, during cold seasons which last from late fall
till early spring, winds mainly blow from mainland China
(north, northwest, and west to Shanghai) where air is
polluted. Large power plants distribute intensively in northern part of Shanghai such as those from Baosteel Group
Corporation Limited. Local emissions also increase rapidly
due to heating in cold seasons. Annually Shanghai consumes
about 45 million tons of coal for industrial and residential
purposes. Low level temperature inversion makes the air
pollution more serious (haze, mostly happens in fall) and
resulted in great fluctuation of PM concentrations during
these seasons together with other added factors such as dust
storms in springtime (Fig. 3).
Carbonaceous species had similar seasonal patterns to
PM2.5 mass at both sites, although their highest concentrations distinctly occurred in fall (Table 1). For example, OC and
EC concentrations at ZB Site from fall to summer were 21.8,
16.7, 14.1, 7.2, and 3.9, 2.3, 3.1, 1.9 μg/m3, respectively. The
levels of OC and EC in fall were higher than in summer by 2–3
times, and the values in winter and spring were almost
equivalent. However, there was asynchronous variation
between carbonaceous species and PM2.5 mass, and it was
attributable to the seasonality of percentages of total
carbonaceous aerosol (TCA) in PM2.5 mass (Table 1 and
Fig. 3). In this paper, TCA was calculated by the sum of EC and
organic matter (OM) which was estimated by multiplying the
amount of OC by 1.6 (Turpin and Lim, 2001). As shown in
Table 1, TCA accounted for an annually averaged 28.9% (ZB)
and 32.0% (JD) of PM2.5 mass, with the seasonal rank of fall N
winter N summer N spring. The obviously lowest contribution
439
of TCA to PM2.5 mass in spring may be affected by the
contributions of Asian dust storms which frequently occur
during the dry spring seasons (particularly during April–
May). A typical example was that a strong dust storm
appeared on April 19, 2006 which affected a broad area in
China and was recorded by the samples in this study. As Fig. 3
demonstrates, TCA/PM2.5 ratio in the sample of that particular day at ZB Site has the minimum value of all the samples
(16.9%) while the maximum PM2.5 concentration was
255.9 μg/m3; similarly in the corresponding sample at JD
(collected on April 20, 2006), the TCA/PM2.5 ratio and PM2.5
were 22.2% and 165.7 μg/m3 respectively, thereby indicating
the obvious contribution of inorganic material.
3.3. The relationship of OC and EC
OC–EC relationship gives some indication of the origin of
carbonaceous particles. Fig. 3 shows the regression between OC
and EC concentrations for all PM2.5 samples from both sites in
Shanghai except for the two samples affected by dust storm, as
mentioned above. Strong correlations (r) of 0.82, 0.93, 0.79, and
0.86 were observed for the four seasons from fall to summer.
This indicated that carbonaceous particles in Shanghai derived
from common emission sources such as vehicular exhaust and/
or coal combustion, underwent a similar atmospheric dispersion process. The variations of regression slopes (6.46–8.29, see
Fig. 4) might have been resulted from the seasonal variability of
emission sources and SOA contributions.
Since carbonaceous aerosol represents a mixture of
various emission sources (EC and primary OC) and secondary
OC formed by atmospheric reaction processes, the ratio of OC
to EC concentrations (OC/EC) can be used to study the
emission and transformation characteristics. Typical emission
sources include diesel- and gasoline-powered vehicular
exhaust (OC/EC = 1.0–4.2) (Schauer et al., 1999, 2002), wood
combustion (16.8–40.0) (Schauer et al., 2001), residential coal
smoke (2.5–10.5) (Chen et al., 2006), kitchen emissions (32.9–
81.6) (He et al., 2004b), and biomass burning (7.7) (Zhang
et al., 2007), etc. It should be noted that the OC/EC ratios
presented above were all measured by TOT method, and were
comparatively higher than the values by TOR (Watson et al.,
2001).
Fig. 4. Seasonal correlations of OC and EC in PM2.5 in Shanghai.
440
Y. Feng et al. / Atmospheric Research 92 (2009) 434–442
Table 3
Levels of SOC and SOA in Shanghai estimated from minimum OC/EC ratios.
Sampling site
Season
(OC/EC)min a
SOC (μg/m3)
POC (μg/m3)
SOC/OC (%)
SOA b (μg/m3)
SOA/PM2.5 (%)
ZB
Annual
Fall
Winter
Spring
Summer
Annual
Fall
Winter
Spring
Summer
3.3 ± 0.7
2.7
4.1
3.6
2.7
3.5 ± 1.3
3.2
5.3
3.4
2.2
5.7 ± 7.1
11.5 ± 11.0
7.2 ± 4.9
2.9 ± 3.5
2.0 ± 4.1
7.2 ± 7.3
13.7 ± 9.0
4.3 ± 3.5
5.1 ± 5.7
5.5 ± 6.0
9.0 ± 4.3
10.2 ± 3.4
9.5 ± 3.9
11.3 ± 5.2
5.2 ± 1.8
10.2 ± 4.5
12.1 ± 4.0
11.8 ± 5.5
11.3 ± 4.0
6.0 ± 1.5
27.0 ± 22.7
41.5 ± 26.2
35.9 ± 19.7
18.3 ± 14.3
14.3 ± 21.1
33.2 ± 22.7
47.1 ± 22.8
21.1 ± 18.0
26.9 ± 19.2
36.1 ± 25.0
9.1 ± 11.4
18.5 ± 17.6
11.4 ± 7.8
4.6 ± 5.5
3.2 ± 6.6
11.6 ± 11.6
22.0 ± 14.4
6.8 ± 5.7
8.1 ± 9.0
8.8 ± 9.6
7.8 ± 7.6
13.7 ± 9.4
10.3 ± 6.2
4.1 ± 3.7
3.8 ± 6.6
10.4 ± 8.7
17.7 ± 9.7
6.0 ± 4.8
6.7 ± 5.9
10.7 ± 8.9
JD
Values represent average ± one standard deviation.
a
The observed minimum ratio of OC/EC.
b
SOA is calculated by multiplying SOC by 1.6.
As Table 1 shows, the seasonal average OC/EC ratios in
PM2.5 at ZB Site varied in the range of 3.4–6.8 with annual
average of 5.0; while at JD, the range was 4.0–6.9 and the
average was 5.6. It can be seen that the OC/EC ratios at JD Site
were slightly higher than that at ZB for all seasons. This can be
explained by the surroundings of both sites: ZB Site was
affected by more traffic emissions, while JD by more emission
sources with high OC/EC ratios, such as cooking exhaust and
coal smoke (small chimneys in a glass factory), etc. Study by
Feng et al. (2006) suggested kitchen emissions was the third
important source for carbonaceous aerosol in Shanghai after
vehicular exhaust and residential coal combustion and cannot
be negligible.
For inter-seasonal comparison, the highest OC/EC ratio
occurred in wintertime versus the lowest in summertime, and
they differed by a factor of 2 (Table 1). Similar phenomenon
was reported in PRDR (Duan et al., 2007), and the reasons
included: (1) more semi-volatile organic compounds condensed into aerosol in lower temperature; (2) stagnant and
dry meteorological conditions resulted in more SOA formation in wintertime; (3) more residential combustion of coal
and wood for space heating occurred in winter; (4) polluted
air with higher OC/EC ratio from mainland China in northwest
and west deteriorated the ambient air quality in Shanghai
during cold seasons (Duan et al., 2007).
3.4. Abundances of SOC and SOA in Shanghai
The importance of SOA has been recognized for decades on
account of its relation to haze, visibility, climate, and human
health. However, difficulties still exist to directly separate
secondary OC (SOC) from primary OC (POC), although there
are many methods for quantification of total OC (TOC). An
indirect method for estimation of SOC has been usually
employed using EC as the tracer for POC, since EC is
essentially emitted from combustion sources together with
primary organic components (Turpin and Huntzicker, 1995),
and the equation is as follows:
SOC = TOC − EC × ðOC =ECÞprimary ;
Where (OC/EC)primary is the ratio for primary sources
contributing to the sample. A OC/EC value of 2.0 has been used
to estimate SOC (Chow et al., 1996). However, the primary ratio
of OC/EC is usually not available because it is affected by many
factors such as the type of emission source as well as its variation
in temporal and spatial scales, ambient temperature, and carbon
determination method, etc. In many case, (OC/EC)primary was
represented by the observed minimum ratio ((OC/EC)min), and
assumptions regarding the use of this procedure as were
discussed in detail by Castro et al. (1999).
As presented in Table 3, the minimum OC/EC ratio at ZB
and JD Sites in Shanghai ranged in 2.7–4.1 (average 3.3) and
2.2–5.3 (3.5) in different seasons, respectively, and the highest
ratios were observed during wintertime. All these lowest
ratios occurred in the samples are affected by the air mass
coming from the East China Sea, according to the backward
trajectory analysis performed with HYSPLIT from the NOAA
ARL website (www.arl.noaa.gov/ready/). These values are
comparable with those of Guangzhou (2.3–4.5) (Duan et al.,
2007), and California, USA (3.7) (Na et al., 2004), but higher
than that of Budapest, Hungary (1.1–2.9) (Salma et al., 2004),
and Helsinki, Finland (1.1) (Viidanoja et al., 2002).
The annual average concentrations of estimated SOC in
Shanghai PM2.5 samples was 5.7 μg/m3 at ZB Site and 7.2 μg/m3
at JD, accounting for 27.0% and 33.2% of OC, respectively. This
implied that SOC was an important component of OC mass in
Shanghai. Compared to the modeling results by chemical mass
balance (CMB) (Feng et al., 2006), i.e., 18–19% of SOC-to-OC
percentage for urban site and 23–25% for rural site in
Shanghai, our data were slightly higher. The seasonally
averaged values showed that SOC concentration was distinctly
higher during fall than in other seasons at both the sites, and
was about two times the annual average (Table 3). This
seasonal pattern of SOC was similar to that of OC and EC
concentrations in PM2.5, but differed with that of the OC/EC
ratio in which highest values occurred in winter, as stated
before. This was attributable to the contributions of various
sources in different seasons while meteorological conditions
during fall (such as temperature inversion) availed the
formation of SOC.
SOA concentration was calculated here by multiplying
SOC by a factor of 1.6, and ranged in 3.2–18.5 μg/m3
(averaged 9.1 μg/m3) at ZB Site while 6.8–22.0 μg/m3
(average 11.6 μg/m3) at JD (Table 3). The average percentages
of 7.8–10.4% at both sites indicated that SOA contributed a
minor fraction of PM2.5 mass in Shanghai, although sometimes it could account for up to 20% in fall.
Y. Feng et al. / Atmospheric Research 92 (2009) 434–442
4. Conclusions
Abundance and seasonal characteristics of PM2.5 and
carbonaceous species were investigated at two sites at
Shanghai, China. On annual average, PM2.5 concentration
was 90.3 μg/m3 at ZB Site and 95.5 μg/m3 at JD, indicating the
serious situation of fine particle pollution in Shanghai. The
concentrations for OC and EC were 14.7 and 2.8 μg/m3 at ZB
whereas 17.4 and 3.0 μg/m3 at JD, respectively, following the
order of Beijing N Guangzhou N Shanghai N Hong Kong.
Carbonaceous aerosol (TCA) accounted for ∼30% of PM2.5
mass at both sites. On seasonal average, the highest levels of
PM2.5 and carbonaceous fractions were generally observed
during fall and were higher than summer by a factor of 2.
Strong correlations (r = 0.79–0.93) between OC and EC
suggested the contributions of common sources and similar
atmospheric process during each season in Shanghai. The
averaged OC/EC ratios were 5.0 at ZB and 5.6 at JD with the
highest values observed during winter, implying the significant contributions of sources with elevated OC/EC ratios
such as residential coal smoke and kitchen emissions. SOC
concentrations were estimated by minimum OC/EC ratio, and
were 5.7 and 7.2 μg/m3 at ZB and JD, respectively, accounting
for ∼ 30% of the total OC. The average ratios of SOA/PM2.5 of
7.8–10.4% indicated that SOA was a minor fraction in fine
particles of Shanghai, although it could constitute up to 20% of
PM2.5 mass during fall.
Acknowledgements
This project was financially supported by the Department
of Science and Technology of Shandong Province
(2006GG2205033, 2007GG2QT06018), National Natural
Scientific Foundation of China (40605033, 40503012), and
Shanghai Leading Academic Disciplines (S30109). The
authors would like to thank Jia-ding Environmental Monitoring Station in Shanghai for the assistant of sampling at the
station, Dr. Xiyong Hou from YIC, CAS and Ms. Paromita
Chakraborty from GIG, CAS for their helps in this manuscript.
The authors also thank all three anonymous reviewers for
their helpful comments and suggestions.
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