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DOI	10.5194/acp-20-12047-2020
	Source apportionment of PM2.5 in Shanghai based on hourly organic molecular markers and other source tracers
	Li R.; Wang Q.; He X.; Zhu S.; Zhang K.; Duan Y.; Fu Q.; Qiao L.; Wang Y.; Huang L.; Li L.; Yu J.Z.
发表日期	2020
ISSN	1680-7316
起始页码	12047
结束页码	12061
卷号	20 期号:20
英文摘要	Identification of various emission sources and quantification of their contributions comprise an essential step in formulating scientifically sound pollution control strategies. Most previous studies have been based on traditional offline filter analysis of aerosol major components (usually inorganic ions, elemental carbon-EC, organic carbon-OC, and elements). In this study, source apportionment of PM2.5 using a positive matrix factorization (PMF) model was conducted for urban Shanghai in the Yangtze River Delta region, China, utilizing a large suite of molecular and elemental tracers, together with water-soluble inorganic ions, OC, and EC from measurements conducted at two sites from 9 November to 3 December 2018. The PMF analysis with inclusion of molecular makers (i.e., MMPMF) identified 11 pollution sources, including 3 secondarysource factors (i.e., secondary sulfate; secondary nitrate; and secondary organic aerosol, SOA, factors) and 8 primary sources (i.e., vehicle exhaust, industrial emission and tire wear, industrial emission II, residual oil combustion, dust, coal combustion, biomass burning, and cooking). The secondary sources contributed 62.5 % of the campaign-average PM2.5 mass, with the secondary nitrate factor being the leading contributor. Cooking was a minor contributor (2.8 %) to PM2.5 mass while a significant contributor (11.4 %) to the OC mass. Traditional PMF analysis relying on major components alone (PMFt) was unable to resolve three organicsdominated sources (i.e., biomass burning, cooking, and SOA source factors). Utilizing organic tracers, the MM-PMF analysis determined that these three sources combined accounted for 24.4 % of the total PM2.5 mass. In PMFt, this significant portion of PM mass was apportioned to other sources and thereby was notably biasing the source apportionment outcome. Backward trajectory and episodic analysis were performed on the MM-PMF-resolved source factors to examine the variations in source origins and composition. It was shown that under all episodes, secondary nitrate and the SOA factor were two major source contributors to the PM2.5 pollution. Our work has demonstrated that comprehensive hourly data of molecular markers and other source tracers, coupled with MM-PMF, enables examination of detailed pollution source characteristics, especially organics-dominated sources, at a timescale suitable for monitoring episodic evolution and with finer source breakdown. © 2020 Author(s).
语种	英语
scopus关键词	algorithm; molecular analysis; organic matter; particulate matter; source apportionment; tracer; China; Shanghai
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/247452
作者单位	College of Environmental and Chemical Engineering, Shanghai University, Shanghai, 200444, China; Department of Chemistry, Hong Kong University of Science and Technology, Hong Kong, Hong Kong; Division of Environment and Sustainability, Hong Kong University of Science and Technology, Hong Kong, Hong Kong; State Environ. Protection Key Laboratory of the Cause and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, 200233, China; Shanghai Environmental Monitoring Center, Shanghai, 200235, China
推荐引用方式 GB/T 7714	Li R.,Wang Q.,He X.,et al. Source apportionment of PM2.5 in Shanghai based on hourly organic molecular markers and other source tracers[J],2020,20(20).
APA	Li R..,Wang Q..,He X..,Zhu S..,Zhang K..,...&Yu J.Z..(2020).Source apportionment of PM2.5 in Shanghai based on hourly organic molecular markers and other source tracers.ATMOSPHERIC CHEMISTRY AND PHYSICS,20(20).
MLA	Li R.,et al."Source apportionment of PM2.5 in Shanghai based on hourly organic molecular markers and other source tracers".ATMOSPHERIC CHEMISTRY AND PHYSICS 20.20(2020).