spatiotemporalevolutionandtheinfluencingfactorsofpm25inchinabetween2000and2015

	spatiotemporalevolutionandtheinfluencingfactorsofpm25inchinabetween2000and2015
	Zhou Liang 5; Zhou Chenghu 1; Yang Fan 2; Che Lei 3; Wang Bo 4; Sun Dongqi 1
刊名	journalofgeographicalsciences
	2019
卷号	29 期号:2 页码:253
ISSN号	1009-637X
英文摘要	High concentrations of PM2.5 are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM2.5 concentrations for regional air quality control and management. In this study, PM2.5 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 PM2.5 concentration in China were evaluated. The main results are as follows. (1) In general, the average concentration of PM2.5 in China increased quickly and reached its peak value in 2006; subsequently, concentrations remained between 21.84 and 35.08 g/m(3). (2) PM2.5 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 PM2.5 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 PM2.5. (3) The center of gravity of PM2.5 has generally moved northeastward, which indicates an increasingly serious haze in eastern China. High-value PM2.5 concentrations have moved eastward, while low-value PM2.5 has moved westward. (4) Spatial autocorrelation analysis indicates a significantly positive spatial correlation. The High-High PM2.5 agglomeration areas are distributed in the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan Plain regions. The Low-Low PM2.5 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 PM2.5 concentration. Geographical location, population density, automobile quantity, industrial discharge, and straw burning are the main driving forces of PM2.5 concentration in China.
资助项目	[Strategic Priority Research Program of the Chinese Academy of Sciences] ; [China Postdoctoral Science Foundation] ; [National Natural Science Foundation of China] ; [State Key Laboratory of Resources and Environmental Information System]
语种	英语
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/122395]
专题	中国科学院地理科学与资源研究所
作者单位	1.中国科学院地理科学与资源研究所 2.南京大学 3.西北师范大学 4.香港大学 5.兰州交通大学
推荐引用方式 GB/T 7714	Zhou Liang,Zhou Chenghu,Yang Fan,et al. spatiotemporalevolutionandtheinfluencingfactorsofpm25inchinabetween2000and2015[J]. journalofgeographicalsciences,2019,29(2):253.
APA	Zhou Liang,Zhou Chenghu,Yang Fan,Che Lei,Wang Bo,&Sun Dongqi.(2019).spatiotemporalevolutionandtheinfluencingfactorsofpm25inchinabetween2000and2015.journalofgeographicalsciences,29(2),253.
MLA	Zhou Liang,et al."spatiotemporalevolutionandtheinfluencingfactorsofpm25inchinabetween2000and2015".journalofgeographicalsciences 29.2(2019):253.