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PM2.5 pollution in a megacity of southwest China: source apportionment and implication
Tao, J (Tao, J.)[ 1 ]; Gao, J (Gao, J.)[ 2 ]; Zhang, L (Zhang, L.)[ 3 ]; Zhang, R (Zhang, R.)[ 4 ]; Che, H (Che, H.)[ 5 ]; Zhang, Z (Zhang, Z.)[ 1 ]; Lin, Z (Lin, Z.)[ 1 ]; Jing, J (Jing, J.)[ 6 ]; Cao, J (Cao, J.)[ 7 ]; Hsu, SC (Hsu, S. -C.)[ 8 ]
2014
Source PublicationATMOSPHERIC CHEMISTRY AND PHYSICS
Volume14Issue:16Pages:8679-8699
Subtype期刊论文
Abstract

Daily PM2.5 (aerosol particles with an aerodynamic diameter of less than 2.5 mu m) samples were collected at an urban site in Chengdu, an inland megacity in southwest China, during four 1-month periods in 2011, with each period in a different season. Samples were subject to chemical analysis for various chemical components ranging from major water-soluble ions, organic carbon (OC), element carbon (EC), trace elements to biomass burning tracers, anhydrosugar levoglucosan (LG), and mannosan (MN). Two models, the ISORROPIA II thermodynamic equilibrium model and the positive matrix factorization (PMF) model, were applied to explore the likely chemical forms of ionic constituents and to apportion sources for PM2.5. Distinctive seasonal patterns of PM2.5 and associated main chemical components were identified and could be explained by varying emission sources and meteorological conditions. PM2.5 showed a typical seasonality of waxing in winter and waning in summer, with an annual mean of 119 mu g m(-3). Mineral soil concentrations increased in spring, whereas biomass burning species elevated in autumn and winter. Six major source factors were identified to have contributed to PM2.5 using the PMF model. These were secondary inorganic aerosols, coal combustion, biomass burning, iron and steel manufacturing, Mo-related industries, and soil dust, and they contributed 37 +/- 18, 20 +/- 12, 11 +/- 10, 11 +/- 9, 11 +/- 9, and 10 +/- 12 %, respectively, to PM2.5 masses on annual average, while exhibiting large seasonal variability. On annual average, the unknown emission sources that were not identified by the PMF model contributed 1 +/- 11% to the measured PM2.5 mass. Various chemical tracers were used for validating PMF performance. Antimony (Sb) was suggested to be a suitable tracer of coal combustion in Chengdu. Results of LG and MN helped constrain the biomass burning sources, with wood burning dominating in winter and agricultural waste burning dominating in autumn. Excessive Fe (Ex-Fe), defined as the excessive portion in measured Fe that cannot be sustained by mineral dust, is corroborated to be a straightforward useful tracer of iron and steel manufacturing pollution. In Chengdu, Mo/Ni mass ratios were persistently higher than unity, and considerably distinct from those usually observed in ambient airs. V/Ni ratios averaged only 0.7. Results revealed that heavy oil fuel combustion should not be a vital anthropogenic source, and additional anthropogenic sources for Mo are yet to be identified. Overall, the emission sources identified in Chengdu could be dominated by local sources located in the vicinity of Sichuan, a result different from those found in Beijing and Shanghai, wherein cross-boundary transport is significant in contributing pronounced PM2.5. These results provided implications for PM2.5 control strategies.

DOI10.5194/acp-14-8679-2014
Indexed BySCI
Language英语
Citation statistics
Cited Times:126[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ieecas.cn/handle/361006/9789
Collection粉尘与环境研究室
Corresponding AuthorHsu, SC (Hsu, S. -C.)[ 8 ]
Affiliation1.South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou, China;
2.Chinese Research Academy of Environmental Sciences, Beijing, China;
3.Air Quality Research Division, Science Technology Branch, Environment Canada, Toronto, Canada;
4.RCE-TEA, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China;
5.Key Laboratory of Atmospheric Chemistry (LAC), Institute of Atmospheric Composition, Chinese Academy ofMeteorological Sciences (CAMS), China;
6.Centre for Atmosphere Watch and Services (CAWAS), Meteorological Observation Center of CMA, Beijing, China;
7.Key Laboratory of Aerosol, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an, China;
8.Research Center for Environmental Changes (RCEC), Academia Sinica, Taipei, Taiwan
Recommended Citation
GB/T 7714
Tao, J ,Gao, J ,Zhang, L ,et al. PM2.5 pollution in a megacity of southwest China: source apportionment and implication[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2014,14(16):8679-8699.
APA Tao, J .,Gao, J .,Zhang, L .,Zhang, R .,Che, H .,...&Hsu, SC .(2014).PM2.5 pollution in a megacity of southwest China: source apportionment and implication.ATMOSPHERIC CHEMISTRY AND PHYSICS,14(16),8679-8699.
MLA Tao, J ,et al."PM2.5 pollution in a megacity of southwest China: source apportionment and implication".ATMOSPHERIC CHEMISTRY AND PHYSICS 14.16(2014):8679-8699.
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