DOI: 10.1016/j.atmosres.2017.11.017
Scopus记录号: 2-s2.0-85033679689
论文题名: Source apportionment of PM2.5 at the Lin'an regional background site in China with three receptor models
作者: Deng J. ; Zhang Y. ; Qiu Y. ; Zhang H. ; Du W. ; Xu L. ; Hong Y. ; Chen Y. ; Chen J.
刊名: Atmospheric Research
ISSN: 1698095
出版年: 2018
卷: 202 起始页码: 23
结束页码: 32
语种: 英语
英文关键词: Background area
; PCA-MLR
; PM2.5
; PMF
; Source apportionment
; UNMIX
Scopus关键词: Combustion
; Factorization
; Linear regression
; Particles (particulate matter)
; Background area
; PCA-MLR
; PM2.5
; Source apportionment
; UNMIX
; Principal component analysis
; chemical mass balance
; combustion
; concentration (composition)
; numerical model
; particulate matter
; principal component analysis
; regression analysis
; source apportionment
; China
; Linan
; Yangtze Delta
; Zhejiang
英文摘要: Source apportionment of fine particulate matter (PM2.5) were conducted at the Lin'an Regional Atmospheric Background Station (LA) in the Yangtze River Delta (YRD) region in China from July 2014 to April 2015 with three receptor models including principal component analysis combining multiple linear regression (PCA-MLR), UNMIX and Positive Matrix Factorization (PMF). The model performance, source identification and source contribution of the three models were analyzed and inter-compared. Source apportionment of PM2.5 was also conducted with the receptor models. Good correlations between the reconstructed and measured concentrations of PM2.5 and its major chemical species were obtained for all models. PMF resolved almost all masses of PM2.5, while PCA-MLR and UNMIX explained about 80%. Five, four and seven sources were identified by PCA-MLR, UNMIX and PMF, respectively. Combustion, secondary source, marine source, dust and industrial activities were identified by all the three receptor models. Combustion source and secondary source were the major sources, and totally contributed over 60% to PM2.5. The PMF model had a better performance on separating the different combustion sources. These findings improve the understanding of PM2.5 sources in background region. © 2017 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/108966
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China; Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China; University of Chinese Academy of Sciences, Beijing, 100086, China; Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, United States
Recommended Citation:
Deng J.,Zhang Y.,Qiu Y.,et al. Source apportionment of PM2.5 at the Lin'an regional background site in China with three receptor models[J]. Atmospheric Research,2018-01-01,202