Source apportionment of fine particulate matter in China in 2013 using a source-oriented chemical transport model. Shi, Z., Li, J., Huang, L., Wang, P., Wu, L., Ying, Q., Zhang, H., Lu, L., Liu, X., Liao, H., & Hu, J. SCIENCE OF THE TOTAL ENVIRONMENT, 601:1476-1487, ELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS, DEC 1, 2017.
doi  abstract   bibtex   
China has been suffering high levels of fine particulate matter (PM2.5). Designing effective PM2.5 control strategies requires information about the contributions of different sources. In this study, a source-oriented Community Multiscale Air Quality (CMAQ) model was applied to quantitatively estimate the contributions of different source sectors to PM2.5 in China. Emissions of primary PM2.5 and gas pollutants of SO2, NOx, and NH3, which are precursors of particulate sulfate, nitrate, and ammonium (SNA, major PM2.5 components in China), from eight source categories (power plants, residential sources, industries, transportation, open burning, sea salt, windblown dust and agriculture) were separately tracked to determine their contributions to PM2.5 in 2013. Industrial sector is the largest source of SNA in Beijing, Xi'an and Chongqing, followed by agriculture and power plants. Residential emissions are also important sources of SNA, especially in winter when severe pollution events often occur. Nationally, the contributions of different source sectors to annual total PM2.5 from high to low are industries, residential sources, agriculture, power plants, transportation, windblown dust, open burning and sea salt. Provincially, residential sources and industries are the major anthropogenic sources of primary PM2.5, while industries, agriculture, power plants and transportation are important for SNA in most provinces. For total PM2.5, residential and industrial emissions are the top two sources, with a combined contribution of 40-50% in most provinces. The contributions of power plants and agriculture to total PM2.5 are about 10%, respectively. Secondary organic aerosol accounts for about 10% of annual PM2.5 in most provinces, with higher contributions in southernprovinces such as Yunnan (26%), Hainan (25%) and Taiwan (21%). Windblown dust is an important source in western provinces such as Xizang (55% of total PM2.5), Qinghai (74%), Xinjiang (59%). The large variation in sources of PM2.5 across China suggests that PM2.5 mitigation programs should be designed separately for different regions/provinces. (C) 2017 Elsevier B.V. All rights reserved.
@article{ WOS:000406294900144,
Author = {Shi, Zhihao and Li, Jingyi and Huang, Lin and Wang, Peng and Wu, Li and
   Ying, Qi and Zhang, Hongliang and Lu, Li and Liu, Xuejun and Liao, Hong
   and Hu, Jianlin},
Title = {{Source apportionment of fine particulate matter in China in 2013 using a
   source-oriented chemical transport model}},
Journal = {{SCIENCE OF THE TOTAL ENVIRONMENT}},
Year = {{2017}},
Volume = {{601}},
Pages = {{1476-1487}},
Month = {{DEC 1}},
Abstract = {{China has been suffering high levels of fine particulate matter (PM2.5).
   Designing effective PM2.5 control strategies requires information about
   the contributions of different sources. In this study, a source-oriented
   Community Multiscale Air Quality (CMAQ) model was applied to
   quantitatively estimate the contributions of different source sectors to
   PM2.5 in China. Emissions of primary PM2.5 and gas pollutants of SO2,
   NOx, and NH3, which are precursors of particulate sulfate, nitrate, and
   ammonium (SNA, major PM2.5 components in China), from eight source
   categories (power plants, residential sources, industries,
   transportation, open burning, sea salt, windblown dust and agriculture)
   were separately tracked to determine their contributions to PM2.5 in
   2013. Industrial sector is the largest source of SNA in Beijing, Xi'an
   and Chongqing, followed by agriculture and power plants. Residential
   emissions are also important sources of SNA, especially in winter when
   severe pollution events often occur. Nationally, the contributions of
   different source sectors to annual total PM2.5 from high to low are
   industries, residential sources, agriculture, power plants,
   transportation, windblown dust, open burning and sea salt. Provincially,
   residential sources and industries are the major anthropogenic sources
   of primary PM2.5, while industries, agriculture, power plants and
   transportation are important for SNA in most provinces. For total PM2.5,
   residential and industrial emissions are the top two sources, with a
   combined contribution of 40-50\% in most provinces. The contributions of
   power plants and agriculture to total PM2.5 are about 10\%,
   respectively. Secondary organic aerosol accounts for about 10\% of
   annual PM2.5 in most provinces, with higher contributions in
   southernprovinces such as Yunnan (26\%), Hainan (25\%) and Taiwan
   (21\%). Windblown dust is an important source in western provinces such
   as Xizang (55\% of total PM2.5), Qinghai (74\%), Xinjiang (59\%). The
   large variation in sources of PM2.5 across China suggests that PM2.5
   mitigation programs should be designed separately for different
   regions/provinces. (C) 2017 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Hu, JL (Corresponding Author), Nanjing Univ Informat Sci \& Technol, Sch Environm Sci \& Engn,Jiangsu Key Lab Atmospher, Collaborat Innovat Ctr Atmospher Environm \& Equi, Jiangsu Engn Technol Res Ctr Environm Cleaning Ma, 219 Ningliu Rd, Nanjing 210044, Jiangsu, Peoples R China.
   Ying, Q (Corresponding Author), Texas A\&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA.
   Zhang, HL (Corresponding Author), Louisiana State Univ, Dept Civil \& Environm Engn, Baton Rouge, LA 70803 USA.
   Shi, Zhihao; Li, Jingyi; Huang, Lin; Ying, Qi; Zhang, Hongliang; Liao, Hong; Hu, Jianlin, Nanjing Univ Informat Sci \& Technol, Sch Environm Sci \& Engn,Jiangsu Key Lab Atmospher, Collaborat Innovat Ctr Atmospher Environm \& Equi, Jiangsu Engn Technol Res Ctr Environm Cleaning Ma, 219 Ningliu Rd, Nanjing 210044, Jiangsu, Peoples R China.
   Wang, Peng; Wu, Li; Ying, Qi, Texas A\&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA.
   Zhang, Hongliang, Louisiana State Univ, Dept Civil \& Environm Engn, Baton Rouge, LA 70803 USA.
   Lu, Li; Liu, Xuejun, China Agr Univ, Coll Resources \& Environm Sci, Beijing 100193, Peoples R China.}},
DOI = {{10.1016/j.scitotenv.2017.06.019}},
ISSN = {{0048-9697}},
EISSN = {{1879-1026}},
Keywords = {{Source contributions; Primary particulate matter; Secondary inorganic
   aerosols; Source oriented model; Province}},
Keywords-Plus = {{SECONDARY ORGANIC AEROSOL; YANGTZE-RIVER DELTA; AIR-QUALITY MODEL;
   REGIONAL SOURCE APPORTIONMENT; SEVERE HAZE; PM2.5 POLLUTION;
   UNITED-STATES; SULFATE; NITRATE; WINTER}},
Research-Areas = {{Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Environmental Sciences}},
Author-Email = {{qying@civil.tamu.edu
   hlzhang@lsu.edu
   jianlinhu@nuist.edu.cn}},
ResearcherID-Numbers = {{Wang, Peng/AAA-3887-2021
   Zhang, Hongliang/C-2499-2012
   Liao, Hong/T-7963-2017
   Hu, Jianlin/D-7663-2018
   }},
ORCID-Numbers = {{Wang, Peng/0000-0002-7877-5557
   Zhang, Hongliang/0000-0002-1797-2311
   Liao, Hong/0000-0002-9315-4839
   Hu, Jianlin/0000-0001-7709-439X
   Ying, Qi/0000-0002-4560-433X}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China (NSFC) {[}91544220, 41275121]; Natural Science
   Foundation of Jiangsu ProvinceNatural Science Foundation of Jiangsu
   Province {[}BK20150904, BK20151041]; Jiangsu Distinguished Professor
   Project {[}2191071503201]; Jiangsu Six Major Talent Peak Project
   {[}2015-JNHB-010]; Startup Fund for Talent at NUIST {[}2243141501008];
   Priority Academic Program Development of Jiangsu Higher Education
   Institutions (PAPD); Jiangsu Province Innovation Platform for
   Superiority Subject of Environmental Science and Engineering {[}KHK1201]}},
Funding-Text = {{This project is partly funded by the the National Natural Science
   Foundation of China (91544220 and 41275121), Natural Science Foundation
   of Jiangsu Province (BK20150904 and BK20151041), Jiangsu Distinguished
   Professor Project (2191071503201), Jiangsu Six Major Talent Peak Project
   (2015-JNHB-010), the Startup Fund for Talent at NUIST (2243141501008)
   and the Priority Academic Program Development of Jiangsu Higher
   Education Institutions (PAPD), and Jiangsu Province Innovation Platform
   for Superiority Subject of Environmental Science and Engineering (No.
   KHK1201). We would like to thank the computation resources from the
   Texas A\&M Supercomputing Facility (http://sc.tamu.edu/) and the high
   performance computing resources provided by Louisiana State University
   (http://www.hpc.lsu.edu) for completing some of the model simulations
   reported in this study.}},
Number-of-Cited-References = {{66}},
Times-Cited = {{54}},
Usage-Count-Last-180-days = {{8}},
Usage-Count-Since-2013 = {{212}},
Journal-ISO = {{Sci. Total Environ.}},
Doc-Delivery-Number = {{FB7BA}},
Unique-ID = {{WOS:000406294900144}},
DA = {{2021-12-02}},
}
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