WRF-Chem modeling of particulate matter in the Yangtze River Delta region: Source apportionment and its sensitivity to emission changes
Li, Nan2; Lu, Yilei3; Liao, Hong2; He, Qingyang4; Li, Jingyi2; Long, Xin1
刊名PLOS ONE
2018-12-07
卷号13期号:12页码:15
ISSN号1932-6203
DOI10.1371/journal.pone.0208944
通讯作者Li, Nan(linan@nuist.edu.cn)
英文摘要China has been troubled by high concentrations of fine particulate matter (PM2.5) for many years. Up to now, the pollutant sources are not yet fully understood and the control approach still remains highly uncertain. In this study, four month-long (January, April, July and October in 2015) WRF-Chem simulations with different sensitivity experiments were conducted in the Yangtze River Delta (YRD) region of eastern China. The simulated results were compared with abundant meteorological and air quality observations at 138 stations in 26 YRD cities. Our model well captured magnitudes and variations of the observed PM2.5, with the normal mean biases (NMB) less than +/- 20% for 19 out of the 26 YRD cities. A series of sensitivity simulations were conducted to quantify the contributions from individual source sectors and from different regions to the PM2.5 in the YRD region. The calculated results show that YRD local source contributed 64% of the regional PM2.5 concentration, while outside transport contributed the rest 36%. Among the local sources, industry activity was the most significant sector in spring (25%), summer (36%) and fall (33%), while residential source was more important in winter (38%). We further conducted scenario simulations to explore the potential impacts of varying degrees of emission controls on PM2.5 reduction. The result demonstrated that regional cooperative control could effectively reduce the PM2.5 level. The proportionate emission controls of 10%, 20%, 30%, 40% and 50% could reduce the regional mean PM2.5 concentrations by 10%, 19%, 28%, 37% and 46%, respectively, and for places with higher ambient concentrations, the mitigation efficiency was more significant. Our study on source apportionment and emission controls can provide useful information on further mitigation actions.
资助项目National Natural Science Foundation of China[41705128] ; Nanjing University of Information Science and Technology[2016r063] ; Opening Project of Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3)[FDLAP17003] ; Nanjing Star-jelly Environmental Consultants Co., Ltd.
WOS关键词SUMMERTIME OZONE FORMATION ; NORTH CHINA PLAIN ; MEXICO-CITY ; AIR-QUALITY ; POLLUTION EPISODES ; GUANZHONG BASIN ; PM2.5 ; HAZE ; IMPACTS ; URBAN
WOS研究方向Science & Technology - Other Topics
语种英语
出版者PUBLIC LIBRARY SCIENCE
WOS记录号WOS:000452640900055
资助机构National Natural Science Foundation of China ; Nanjing University of Information Science and Technology ; Opening Project of Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3) ; Nanjing Star-jelly Environmental Consultants Co., Ltd.
内容类型期刊论文
源URL[http://ir.ieecas.cn/handle/361006/14471]  
专题地球环境研究所_粉尘与环境研究室
通讯作者Li, Nan
作者单位1.Chinese Acad Sci, Inst Earth Environm, Key Lab Aerosol Chem & Phys, Xian, Shaanxi, Peoples R China
2.Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Sch Environm Sci & Engn, Jiangsu Key Lab Atmospher Environm Monitoring & P, Nanjing, Jiangsu, Peoples R China
3.Nanjing Gaochun Dist Meteorol Bur, Nanjing, Jiangsu, Peoples R China
4.Nanjing Star Jelly Environm Consultants Co Ltd, Nanjing, Jiangsu, Peoples R China
推荐引用方式
GB/T 7714
Li, Nan,Lu, Yilei,Liao, Hong,et al. WRF-Chem modeling of particulate matter in the Yangtze River Delta region: Source apportionment and its sensitivity to emission changes[J]. PLOS ONE,2018,13(12):15.
APA Li, Nan,Lu, Yilei,Liao, Hong,He, Qingyang,Li, Jingyi,&Long, Xin.(2018).WRF-Chem modeling of particulate matter in the Yangtze River Delta region: Source apportionment and its sensitivity to emission changes.PLOS ONE,13(12),15.
MLA Li, Nan,et al."WRF-Chem modeling of particulate matter in the Yangtze River Delta region: Source apportionment and its sensitivity to emission changes".PLOS ONE 13.12(2018):15.
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