Spatiotemporal Distributions and Source Apportionment of PM2.5-Bound Antimony in Beijing, China

被引:2
|
作者
Yang, Chenmeng [1 ,2 ]
Wu, Yunjie [1 ,3 ]
Zhang, Leiming [4 ]
Sun, Guangyi [1 ]
Yao, Heng [1 ]
Li, Zhonggen [5 ]
Bi, Xiangyang [3 ]
Huang, Qiang [1 ]
Feng, Xinbin [1 ]
机构
[1] Chinese Acad Sci, Inst Geochem, State Key Lab Environm Geochem, Guiyang, Peoples R China
[2] Univ Chinese Acad Sci, Beijing, Peoples R China
[3] China Univ Geosci, Sch Earth Sci, Wuhan, Peoples R China
[4] Environm & Climate Change Canada, Sci & Technol Branch, Air Qual Res Div, Toronto, ON, Canada
[5] Zunyi Normal Coll, Sch Resources & Environm, Zunyi, Guizhou, Peoples R China
基金
美国国家科学基金会; 中国博士后科学基金;
关键词
antimony pollution; fine particles; emission sources; decadal trends; BRAKE ABRASION DUSTS; TOXIC HEAVY-METALS; PARTICULATE-MATTER; TRACE-ELEMENTS; ANTHROPOGENIC ACTIVITIES; ATMOSPHERIC EMISSIONS; SOURCE IDENTIFICATION; CHEMICAL-COMPOSITION; SPATIAL-DISTRIBUTION; SIZE DISTRIBUTIONS;
D O I
10.1029/2021JD036401
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Antimony (Sb) is a toxic heavy metal, and PM2.5-bound Sb (Sb-PM2.5) in the air impacts human health via inhalation pathways. In this study, we analyzed multiyear measurements of ambient Sb-PM2.5 in Beijing to characterize its spatiotemporal distributions, identify main sources, and predict future trends. The results show that ambient Sb-PM2.5 has been decreasing with fluctuations from 2005 to 2012 and decreased rapidly after 2013, which was likely a result of the government's enhanced air pollution control plan that targeted main sources of industrial Sb. Across the city, average Sb-PM2.5 concentrations were relatively higher at nonemission locomotive traffic sampling sites and in densely populated areas (9.45-19.45 ng/m(3)) and lower in background areas (0.6-0.9 ng/m(3)). Regional-scale emissions and local human activities both affected the spatial distributions of Sb-PM2.5. Notably, Sb-PM2.5 concentration increased by 58.3% from 2006 to 2013 in one suburban background area, indicating the changing emission distributions and intensities over the study period. A neural network model was developed and tested to predict future Sb-PM2.5 levels, results from which showed that with simulated massive reductions in coal supplies and a rapid boom in the waste incineration industry, Sb-PM2.5 concentration would vary in a smaller range (from 4.08 to 4.38 ng/m(3)) over the next decade as compared to the observed range during 2011-2018 (19.0-5.44 ng/m(3)). The impact of the continued expansion of the waste incineration industry on Sb-PM2.5 pollution needs to be considered in future emission control policies.
引用
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页数:17
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