Revealing the origin of fine particulate matter in the Sichuan Basin from a source-oriented modeling perspective. Qiao, X., Yuan, Y., Tang, Y., Ying, Q., Guo, H., Zhang, Y., & Zhang, H. ATMOSPHERIC ENVIRONMENT, PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, JAN 1, 2021.
doi  abstract   bibtex   
The Sichuan Basin (SCB) with 18 cities is one of the regions that are greatly affected by PM2.5 (i.e., particulate matter (PM) with an aerodynamic equivalent diameter less than or equal to 2.5 mu m) in China. In this study, we used the Weather Research Forecasting (WRF) model and a source-oriented version of the Community Multiscale Air Quality (CMAQ) model to quantify the contributions from different sectors and regions to PM2.5 for the SCB in 2015. The annual PM2.5 concentrations in the 18 SCB urban centers (i.e., the central urban areas) are 42-112 mu g m(-3), much higher than the World Health Organization (WHO) guideline (10 mu g m(-3)) and having 20-86, 6-17, and 6-10 mu g m(-3) due to SCB, non-SCB, and unidentified emissions, respectively. Non-SCB emissions can contribute up to 87 mu g m(-3) to 24-h PM2.5 concentrations for an urban center. Industrial and residential activities are the largest sectors for annual PM2.5 concentrations in the urban centers, and each of them contributes similar to 25%-50%. The combined residential and industrial contributions (>similar to 60%) are always much higher than that from each of the other sources on PM2.5 pollution and extreme pollution days (>75 and > 150 mu g m(-3), respectively). This study suggests that China's standard for annual PM2.5 (35 mu g m(-3)) in most of the SCB cities might be achieved mainly through controlling SCB emissions (particularly those from industrial and residential activities); however, to meet the WHO guideline and to reduce PM2.5 pollution days and extreme pollution days, both SCB and non-SCB emissions should be greatly reduced.
@article{ WOS:000591734100006,
Author = {Qiao, Xue and Yuan, Yanping and Tang, Ya and Ying, Qi and Guo, Hao and
   Zhang, Yueying and Zhang, Hongliang},
Title = {{Revealing the origin of fine particulate matter in the Sichuan Basin
   from a source-oriented modeling perspective}},
Journal = {{ATMOSPHERIC ENVIRONMENT}},
Year = {{2021}},
Volume = {{244}},
Month = {{JAN 1}},
Abstract = {{The Sichuan Basin (SCB) with 18 cities is one of the regions that are
   greatly affected by PM2.5 (i.e., particulate matter (PM) with an
   aerodynamic equivalent diameter less than or equal to 2.5 mu m) in
   China. In this study, we used the Weather Research Forecasting (WRF)
   model and a source-oriented version of the Community Multiscale Air
   Quality (CMAQ) model to quantify the contributions from different
   sectors and regions to PM2.5 for the SCB in 2015. The annual PM2.5
   concentrations in the 18 SCB urban centers (i.e., the central urban
   areas) are 42-112 mu g m(-3), much higher than the World Health
   Organization (WHO) guideline (10 mu g m(-3)) and having 20-86, 6-17, and
   6-10 mu g m(-3) due to SCB, non-SCB, and unidentified emissions,
   respectively. Non-SCB emissions can contribute up to 87 mu g m(-3) to
   24-h PM2.5 concentrations for an urban center. Industrial and
   residential activities are the largest sectors for annual PM2.5
   concentrations in the urban centers, and each of them contributes
   similar to 25\%-50\%. The combined residential and industrial
   contributions (>similar to 60\%) are always much higher than that from
   each of the other sources on PM2.5 pollution and extreme pollution days
   (>75 and > 150 mu g m(-3), respectively). This study suggests that
   China's standard for annual PM2.5 (35 mu g m(-3)) in most of the SCB
   cities might be achieved mainly through controlling SCB emissions
   (particularly those from industrial and residential activities);
   however, to meet the WHO guideline and to reduce PM2.5 pollution days
   and extreme pollution days, both SCB and non-SCB emissions should be
   greatly reduced.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Qiao, X (Corresponding Author), Sichuan Univ, Inst New Energy \& Low Carbon Technol, 24 South Sect One,First Ring Rd, Chengdu 610065, Peoples R China.
   Zhang, HL (Corresponding Author), Fudan Univ, Dept Environm Sci \& Engn, Shanghai 200438, Peoples R China.
   Qiao, Xue; Yuan, Yanping; Zhang, Yueying, Sichuan Univ, Inst New Energy \& Low Carbon Technol, 24 South Sect One,First Ring Rd, Chengdu 610065, Peoples R China.
   Qiao, Xue, Sichuan Univ, State Key Lab Hydraul \& Mt River Engn, Chengdu 610065, Peoples R China.
   Qiao, Xue; Guo, Hao; Zhang, Hongliang, Louisiana State Univ, Dept Civil \& Environm Engn, Baton Rouge, LA 70803 USA.
   Tang, Ya, Sichuan Univ, Coll Architecture \& Environm, Dept Environm, Chengdu 610065, Peoples R China.
   Ying, Qi, Texas A\&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA.
   Zhang, Hongliang, Fudan Univ, Dept Environm Sci \& Engn, Shanghai 200438, Peoples R China.}},
DOI = {{10.1016/j.atmosenv.2020.117896}},
Article-Number = {{117896}},
ISSN = {{1352-2310}},
EISSN = {{1873-2844}},
Keywords = {{PM2.5; Source apportionment; Extreme event; Air pollutant transport}},
Keywords-Plus = {{HEAVY AIR-POLLUTION; SOURCE APPORTIONMENT; SOUTHWESTERN CHINA; EMISSION
   INVENTORY; PM2.5 NITRATE; 18 CITIES; TRANSPORT; PERFORMANCE; POLLUTANTS;
   FRAMEWORK}},
Research-Areas = {{Environmental Sciences \& Ecology; Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Environmental Sciences; Meteorology \& Atmospheric Sciences}},
Author-Email = {{qiao.xue@scu.edu.cn
   zhanghl@fudan.edu.cn}},
ResearcherID-Numbers = {{Zhang, Hongliang/C-2499-2012
   }},
ORCID-Numbers = {{Zhang, Hongliang/0000-0002-1797-2311
   Ying, Qi/0000-0002-4560-433X
   Qiao, Xue/0000-0001-7412-5090}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China (NSFC) {[}41929002]; International Collaboration
   Project of the Science and Technology Department of Sichuan Province
   {[}2017HH0048]; Program of Introducing Talents of Discipline to
   UniversitiesMinistry of Education, China - 111 Project {[}B08037]; PM2.5
   monitoring in the campuses of Sichuan University {[}SCU2015CC0001]}},
Funding-Text = {{The modeling work in this study was carried out by using the
   high-performance computing resources at the Louisiana State University
   (http://www.hpc.lsu.edu). This study is supported by the National
   Natural Science Foundation of China {[}41929002], the International
   Collaboration Project of the Science and Technology Department of
   Sichuan Province {[}2017HH0048], the Program of Introducing Talents of
   Discipline to Universities {[}B08037], and PM2.5 monitoring in the
   campuses of Sichuan University {[}SCU2015CC0001].}},
Number-of-Cited-References = {{41}},
Times-Cited = {{2}},
Usage-Count-Last-180-days = {{8}},
Usage-Count-Since-2013 = {{16}},
Journal-ISO = {{Atmos. Environ.}},
Doc-Delivery-Number = {{OU7WA}},
Unique-ID = {{WOS:000591734100006}},
DA = {{2021-12-02}},
}
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