Knowledge Resource Center for Ecological Environment in Arid Area
Spatio-temporal evolution and the influencing factors of PM_(2.5) in China between 2000 and 2015 | |
Zhou Liang; Zhou Chenghu; Yang Fan; Che Lei; Wang Bo; Sun Dongqi | |
来源期刊 | Journal of Geographical Sciences
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ISSN | 1009-637X |
出版年 | 2019 |
卷号 | 29期号:2页码:253-270 |
英文摘要 | High concentrations of PM_(2.5) are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM_(2.5) concentrations for regional air quality control and management. In this study, PM_(2.5) data from 2000 to 2015 was determined from an inversion of NASA atmospheric remote sensing images. Using geo-statistics, geographic detectors, and geo-spatial analysis methods, the spatio-temporal evolution patterns and driving factors of PM_(2.5) concentration in China were evaluated. The main results are as follows. (1) In general, the average concentration of PM_(2.5) in China increased quickly and reached its peak value in 2006; subsequently, concentrations remained between 21.84 and 35.08 mug/m~3. (2) PM_(2.5) is strikingly heterogeneous in China, with higher concentrations in the north and east than in the south and west. In particular, areas with relatively high PM_(2.5) concentrations are primarily in four regions, the Huang-Huai-Hai Plain, Lower Yangtze River Delta Plain, Sichuan Basin, and Taklimakan Desert. Among them, Beijing-Tianjin-Hebei Region has the highest concentration of PM_(2.5). (3) The center of gravity of PM_(2.5) has generally moved northeastward, which indicates an increasingly serious haze in eastern China. High-value PM_(2.5) concentrations have moved eastward, while low-value PM_(2.5) has moved westward. (4) Spatial autocorrelation analysis indicates a significantly positive spatial correlation. The High-High PM_(2.5) agglomeration areas are distributed in the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan Plain regions. The Low-Low PM_(2.5) agglomeration areas include Inner Mongolia and Heilongjiang, north of the Great Wall, Qinghai-Tibet Plateau, and Taiwan, Hainan, and Fujian and other southeast coastal cities and islands. (5) Geographic detection analysis indicates that both natural and anthropogenic factors account for spatial variations in PM_(2.5) concentration. Geographical location, population density, automobile quantity, industrial discharge, and straw burning are the main driving forces of PM_(2.5) concentration in China. |
英文关键词 | air pollution PM_(2.5) haze spatio-temporal evolution environmental influence China |
类型 | Article |
语种 | 英语 |
开放获取类型 | Bronze |
收录类别 | CSCD |
WOS研究方向 | Environmental Sciences & Ecology |
CSCD记录号 | CSCD:6412362 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/336063 |
作者单位 | Zhou Liang, Faculty of Geomatics, Lanzhou Jiaotong University;;Institute of Geographic Sciences and Natural Resources Research, CAS, ;;, Lanzhou;;, ;;Beijing 730070;;100101.; Zhou Chenghu, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China.; Sun Dongqi, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China.; Yang Fan, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing, Jiangsu 210023, China.; Che Lei, College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, Gansu 730070, China.; Wang Bo, Department of Geography, The University of Hong Kong, 999077, Hong Kong. |
推荐引用方式 GB/T 7714 | Zhou Liang,Zhou Chenghu,Yang Fan,et al. Spatio-temporal evolution and the influencing factors of PM_(2.5) in China between 2000 and 2015[J],2019,29(2):253-270. |
APA | Zhou Liang,Zhou Chenghu,Yang Fan,Che Lei,Wang Bo,&Sun Dongqi.(2019).Spatio-temporal evolution and the influencing factors of PM_(2.5) in China between 2000 and 2015.Journal of Geographical Sciences,29(2),253-270. |
MLA | Zhou Liang,et al."Spatio-temporal evolution and the influencing factors of PM_(2.5) in China between 2000 and 2015".Journal of Geographical Sciences 29.2(2019):253-270. |
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