The water-soluble ionic composition of PM2.5 in Shanghai and Beijing, China
Introduction
Shanghai and Beijing are two of the largest cities in China. Both cities have populations of over 10 million. These two urban areas have experienced a rapid increase in the use of vehicles, concurrent with large increases in energy consumption. Particulate pollution has become a major problem. Many short-term studies on TSP and PM10 (particle size smaller than 10 μm) have been published since the 1980s (Winchester et al., 1981; Huebert et al., 1988). However, data on PM2.5, especially regarding the semi-volatile species in PM2.5, e.g., NO3− and Cl− and dicarboxylic acids, is very limited. A year-long study characterizing PM2.5 in Shanghai and Beijing, sponsored by the General Motors Co., was initiated in March 1999. The composition and seasonal trends of PM2.5 in Beijing and Shanghai have been described by He et al. (2001) and Ye et al. (2002), respectively. SO42−, NO3− and NH4+ are the dominant ionic species in PM2.5, which account for about one-third of the total PM2.5 mass in Shanghai and Beijing. The sum of SO42−, NO3− and NH4+, the crustal species and the carbonaceous matter (organic and element carbon) were within 5% of the PM2.5 mass in Shanghai and 20% of the PM2.5 mass in Beijing (He et al., 2001; Ye et al., 2002). In their studies, crustal species were believed to originate from local soil and/or dust storms and carbonaceous species principally originated from primary sources. The formation of SO42− and NO3− in PM2.5 was not investigated, but it should be done since an understanding of the origin of these species impacts control decisions. In Beijing, the vehicular population has grown at a rate of 15% per year since 1990. The resulting increase in NOx emissions is expected to have an impact on the PM2.5 nitrate concentration. On the other hand, clean fuels such as natural gas have replaced coal used for small domestic heating boilers in the central urban area in Beijing. This has reduced the SO2 and HCl emissions. In this paper, we focus on the composition, source, and the formation of the secondary ionic species, with an emphasis on sulfate, nitrate, ammonium, chloride and dicarboxylic acids.
Measurements of semi-volatile species are complicated by sampling artifacts, resulting from gas–particle and particle–particle interactions (Sickles et al., 1999). Denuders for absorbing gases prior to particle collection and back filters for absorbing HNO3, HCl and NH3 evaporated from collected particles have been widely accepted as effective tools to minimize sampling artifacts (Chow and Watson, 1998). In this study, a special low flow rate (0.4 l min−1) sampler equipped with three parallel cassettes (one cassette equipped with an Na2CO3-coated denuder and an nylon back filter) was used to collect PM2.5. Correlation analysis along with seasonal variation in ratios will be examined to provide insight into the formation of secondary species and the relative importance of stationary and mobile sources of nitrogen and sulfur in PM2.5.
Dicarboxylic acids and/or their salts are important constituents in the water-soluble organic fraction of PM (Kawamura and Kaplan 1987; Kerminen et al., 2000) and are expected to be useful in source apportionment. Kawamura and Kaplan (1987) proposed that vehicle exhaust is an important source of dicarboxylic acids in PM. Given that organic carbon was the most abundant species in PM2.5 in Shanghai and Beijing (He et al., 2001; Ye et al., 2002), obtaining more information on its source is very important for control purposes. In this study, the composition of dicarboxylic acids in PM2.5 was determined only for samples collected after December 1999. Correlation analyses between dicarboxylic acids and other species, such as organic carbon, sulfate and nitrate in PM2.5 and O3, was performed to understand the source of dicarboxylic acids and the formation of secondary species.
Section snippets
Sampling and chemical analysis
PM2.5 sampling in Shanghai was conducted by Tongji University. The two sampling sites in Shanghai were both downtown and were 5 km apart. One was inside the Tongji University campus and the other was on Hainan Road. The sampler at the Tongji University campus was placed on the roof of a three-story building, 16 m above ground level. About 150 m northwest from this site is a heavily trafficked road. The sampler at the Hainan Road site was also placed on the roof of a building, 18 m above the ground
The concentration of PM2.5 ions
The minimum, annual average and maximum weekly concentrations of the inorganic ions in PM2.5 are listed in Table 1. The annual average SO42− concentration was 15.9 μg m−3 at Hainan Road and 15.2 μg m−3 at Tongji in Shanghai. Hence, sulfate alone would exceed the US NAAQS annual PM2.5 standard of 15 μg m−3. Sulfate accounted for 46% (on average) of the total mass of inorganic ions. The annual average NO3− concentrations at the two sites in Shanghai were 6.8 and 6.5 μg m−3. Nitrate accounted for 18% of
The composition of PM2.5 ions
As listed in Table 1, the annual average SO42− concentrations were 18.4 μg m−3 at Chegongzhuang and 16.9 μg m−3 at Tsinghua in Beijing, which accounted for 44% of the total mass of ions. Sulfate alone also exceeds the US NAAQS annual PM2.5 standard of 15 μg m−3. The maximum SO42− concentration was 62.4 μg m−3 at Chegongzhuang and 55.7 μg m−3 at Tsinghua, which was close to the US NAAQS 24 h PM2.5 standard of 65 μg m−3. The annual average NO3− concentrations at the two sites were 9.9 and 10.3 μg m−3. Nitrate
Conclusion
Overall, SO42− NO3− and NH4+ were dominant ionic species in PM2.5 in both Shanghai and Beijing. In Shanghai, the annual average SO42− NO3− and NH4+ concentrations were 15.5, 6.6 and 6.4 μg m−3, which account for 46%, 18% and 17% of the total mass of ions, respectively. In Beijing, the annual average SO42−, NO3− and NH4+ concentrations were 17.7, 10.1 and 6.4 μg m−3, which account for 44%, 25% and 16% of the total mass of ions, respectively.
In Shanghai, the SO42− concentration was moderately
Acknowledgements
This study was funded by the General Motors Corporation and the HKUST CMI grant.
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