干旱区生态环境知识资源中心(Arid): Investigation of the spatially varying relationships of PM2.5 with meteorology, topography, and emissions over China in 2015 by using modified geographically weighted regression

Arid

DOI	10.1016/j.envpol.2020.114257
	Investigation of the spatially varying relationships of PM2.5 with meteorology, topography, and emissions over China in 2015 by using modified geographically weighted regression
	Yang, Qianqian; Yuan, Qiangqiang; Yue, Linwei; Li, Tongwen
通讯作者	Yuan, QQ
来源期刊	ENVIRONMENTAL POLLUTION
ISSN	0269-7491
EISSN	1873-6424
出版年	2020
卷号	262
英文摘要	PM2.5 pollution is caused by multiple factors and determining how these factors affect PM2.5 pollution is important for haze control. In this study, we modified the geographically weighted regression (GWR) model and investigated the relationships between PM2.5 and its influencing factors. Experiments covering 368 cities and 9 urban agglomerations were conducted in China in 2015 and more than 20 factors were considered. The modified GWR coefficients (MGCs) were calculated for six variables, including two emission factors (SO2 and NO2 concentrations), two meteorological factors (relative humidity and lifted index), and two topographical factors (woodland percentage and elevation). Then the spatial distribution of MGCs was analyzed at city, cluster, and region scales. Results showed that the relationships between PM2.5 and the different factors varied with location. SO2 emission positively affected PM2.5, and the impact was the strongest in the Beijing-Tianjin-Hebei (BTH) region. The impact of NO2 was generally smaller than that of SO2 and could be important in coastal areas. The impact of meteorological factors on PM2.5 was complicated in terms of spatial variations, with relative humidity and lifted index exerting a strong positive impact on PM2.5 in Pearl River Delta and Central China, respectively. Woodland percentage mainly influenced PM2.5 in regions of or near deserts, and elevation was important in BTH and Sichuan. The findings of this study can improve our understanding of haze formation and provide useful information for policy-making. (C) 2020 Elsevier Ltd. All rights reserved.
英文关键词	Fine particulate matter Impacting factors Relationship analysis Spatial heterogeneity Modified GWR
类型	Article
语种	英语
开放获取类型	Bronze
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000533524300092
WOS关键词	PARTICULATE MATTER PM2.5 ; LAND-USE REGRESSION ; SOCIOECONOMIC-FACTORS ; AIR-QUALITY ; POLLUTION ; IMPACT ; CITIES ; HAZE ; PATTERNS ; EXPLORE
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/324487
作者单位	[Yang, Qianqian; Yuan, Qiangqiang] Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430079, Hubei, Peoples R China; [Yuan, Qiangqiang] Wuhan Univ, Key Lab Geospace Environm & Geodesy, Minist Educ, Wuhan 430079, Hubei, Peoples R China; [Yue, Linwei] China Univ Geosci, Sch Geog & Informat Engn, Wuhan 430074, Hubei, Peoples R China; [Li, Tongwen] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China
推荐引用方式 GB/T 7714	Yang, Qianqian,Yuan, Qiangqiang,Yue, Linwei,et al. Investigation of the spatially varying relationships of PM2.5 with meteorology, topography, and emissions over China in 2015 by using modified geographically weighted regression[J],2020,262.
APA	Yang, Qianqian,Yuan, Qiangqiang,Yue, Linwei,&Li, Tongwen.(2020).Investigation of the spatially varying relationships of PM2.5 with meteorology, topography, and emissions over China in 2015 by using modified geographically weighted regression.ENVIRONMENTAL POLLUTION,262.
MLA	Yang, Qianqian,et al."Investigation of the spatially varying relationships of PM2.5 with meteorology, topography, and emissions over China in 2015 by using modified geographically weighted regression".ENVIRONMENTAL POLLUTION 262(2020).