Source apportionment of PM2.5 pollution in an industrial city in southern China

被引:35
|
作者
Zou, Bei-Bing [1 ]
Huang, Xiao-Feng [1 ]
Zhang, Bin [1 ]
Dai, Jing [1 ]
Zeng, Li-Wu [1 ]
Feng, Ning [1 ]
He, Ling-Yan [1 ]
机构
[1] Peking Univ, Sch Environm & Energy, Key Lab Urban Habitat Environm Sci & Technol, Shenzhen Grad Sch, Shenzhen 518055, Peoples R China
基金
中国国家自然科学基金;
关键词
PM2.5; Source apportionment; Secondary organic aerosol (SOA); Positive matrix factorization (PMF); Pearl River Delta (PRD); POSITIVE MATRIX FACTORIZATION; PEARL RIVER DELTA; FINE PARTICULATE MATTER; CHEMICAL MASS-BALANCE; AEROSOL; PARTICLE; PM10; GUANGZHOU; EMISSIONS; CARBON;
D O I
10.1016/j.apr.2017.05.001
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Severe PM2.5 pollution has become a great challenge to atmospheric pollution control in China. Most of previous aerosol source apportionment studies in China focused only on part of PM2.5 (e.g., organic matter in composition or PM1 in size) or lacked source contributions identified with necessary tempospatial variations, which makes the results not convincible enough for policy making. In this study, five various sites were selected for simultaneous PM2.5 observation in an industrial city in the Pearl River Delta (PRD) of South China during all four seasons of 2014. A positive matrix factorization (PMF) model was applied to the datasets of measured chemical species to perform source apportionment with the results as: (1) The annual mean PM2.5 concentration was 53 mu g/m(3), with vehicle emissions, secondary sulfate, biomass combustion, and secondary organic aerosol (SOA) identified as the major sources, contributing 21%, 20%, 11%, and 10% to PM2.5, respectively. Ship emissions, fugitive dust, secondary nitrate, industrial emissions, and coal burning each contributed 5%-8%. (2) The tempo-spatial variations of sources reveal that secondary sulfate, biomass combustion, SOA, and ship emissions had obvious regional pollution characteristics; however, vehicle emissions, secondary nitrate, coal burning, fugitive dust, and industrial emissions showed obvious local emission characteristics. (3) The exceeding standard days (PM2.5 > 75 mu g/m(3)) appeared with secondary nitrate, SOA, and biomass burning increasing mostly in concentration, indicating that the relevant primary sources or precursor emissions should be controlled more strictly. This study highlights the importance of SOA in PM2.5 pollution in China, which has been scarcely quantified for bulk PM2.5 in the literature. (C) 2017 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved.
引用
收藏
页码:1193 / 1202
页数:10
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