Chemical Composition and Source Apportionment of PM2.5 in a Border City in Southwest China

被引:5
|
作者
Shi, Jianwu [1 ]
Zhao, Chenyang [1 ]
Wang, Zhijun [1 ]
Pang, Xiaochen [1 ]
Zhong, Yaoqian [1 ]
Han, Xinyu [2 ]
Ning, Ping [1 ]
机构
[1] Kunming Univ Sci & Technol, Fac Environm Sci & Engn, Kunming 650500, Yunnan, Peoples R China
[2] Kunming Univ Sci & Technol, Fac Civil Engn & Mech, Kunming 650500, Yunnan, Peoples R China
基金
中国国家自然科学基金;
关键词
PM2; 5; PMF; backward trajectories; chemical composition; source; SOLUBLE INORGANIC-IONS; POSITIVE MATRIX FACTORIZATION; SEASONAL-VARIATIONS; PARTICULATE MATTER; PRIMARY EMISSIONS; FINE PARTICLES; AIR-QUALITY; AEROSOL; IMPACT; URBAN;
D O I
10.3390/atmos13010007
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper studied the chemical characteristics and seasonal changes of PM2.5 in plateau cities on the southwest border of China. Urban air was sampled in Baoshan City during the rainy and dry seasons. Finally, 174 PM2.5 filters were collected (including 87 quartz and 87 Teflon samples for PM2.5). The mass concentrations, water-soluble inorganic ions, organic and inorganic carbon concentrations, and inorganic elements constituting PM2.5 were determined. Positive definite matrix factorization was used to identify potential sources of PM2.5, and the backward trajectory model was used to calculate the contribution of the long-distance transmission of air particles to the Baoshan area. It was found that in the wet season, most of the air masses come from the Indian Ocean and Myanmar. In the dry season, the air mass mainly comes from the China and Myanmar border area. The average concentration of PM2.5 in the wet and dry seasons was 23.17 +/- 12.23 mu g/m(3). The daily mean value of OC/EC indicated that the measured SOC content was generated by the photochemical processes active during the sampling days. However, elements from anthropogenic sources (Na, Mg, Al, Si, P, K, Ca, Ti, Fe, Cu, Zn, Sb, Ba, and Pb) accounted for 99.51% and 99.40% of the total inorganic elements in the wet season and dry season, respectively. Finally, source apportionment showed that SIA, dust, industry, biomass burning, motor vehicle emissions, and copper smelting emissions constituted the major contributions of PM2.5 in Baoshan. Using combined data from three measurement sites provides a focus on the common sources affecting all locations.
引用
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页数:19
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