globalchange  > 气候变化事实与影响
DOI: 10.1016/j.atmosenv.2015.09.006
Scopus记录号: 2-s2.0-84941273675
论文题名:
Spatial-temporal analysis and projection of extreme particulate matter (PM10 and PM2.5) levels using association rules: A case study of the Jing-Jin-Ji region, China
作者: Qin S; , Liu F; , Wang C; , Song Y; , Qu J
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 120
起始页码: 339
结束页码: 350
语种: 英语
英文关键词: Analysis and projection ; Association rules ; Extreme particulate matter ; Spatial-temporal
Scopus关键词: Association rules ; Pollution ; Pollution control ; Analysis and projection ; Apriori algorithms ; Particulate Matter ; Quantitative association rules ; Spatial and temporal variation ; Spatial temporal analysis ; Spatial temporals ; Temporal association ; Air pollution control ; algorithm ; atmospheric pollution ; concentration (composition) ; particulate matter ; pollution control ; public health ; spatial distribution ; spatiotemporal analysis ; air pollution control ; algorithm ; Article ; China ; health ; human ; particulate matter ; priority journal ; spatiotemporal analysis ; China
Scopus学科分类: Environmental Science: Water Science and Technology ; Earth and Planetary Sciences: Earth-Surface Processes ; Environmental Science: Environmental Chemistry
英文摘要: The Jing-Jin-Ji region of Northern China has experienced serious extreme PM concentrations, which could exert considerable negative impacts on human health. However, only small studies have focused on extreme PM concentrations. Therefore, joint regional PM research and air pollution control has become an urgent issue in this region. To characterize PM pollution, PM10 and PM2.5 hourly samples were collected from 13 cities in Jing-Jin-Ji region for one year. This study initially analyzed extreme PM data using the Apriori algorithm to mine quantitative association rules in PM spatial and temporal variations and intercity influences. The results indicate that 1) the association rules of intercity PM are distinctive, and do not completely rely on their spatial distributions; 2) extreme PM concentrations frequently occur in southern cities, presenting stronger spatial and temporal associations than in northern cities; 3) the strength of the spatial and temporal associations of intercity PM2.5 are more substantial than those of intercity PM10. © 2015 Elsevier Ltd.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81475
Appears in Collections:气候变化事实与影响

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作者单位: Department Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, Canada; MOE Key Laboratory of Western China's Environmental Systems, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China; School of Statistics, Dongbei University of Finance and Economics, Dalian, China; School of Mathematics and Statistics, Lanzhou University, Lanzhou, China; Information Center for Global Change Studies, Lanzhou Information Center, Chinese Academy of Sciences, Lanzhou, China

Recommended Citation:
Qin S,, Liu F,, Wang C,et al. Spatial-temporal analysis and projection of extreme particulate matter (PM10 and PM2.5) levels using association rules: A case study of the Jing-Jin-Ji region, China[J]. Atmospheric Environment,2015-01-01,120
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