中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Spatio-Temporal Variation of PM2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China

文献类型:SCI/SSCI论文

作者Lin G.; Fu J. Y.; Jiang D.; Hu W. S.; Dong D. L.; Huang Y. H.; Zhao M. D.
发表日期2014
关键词Pm2.5 Gdp Population Land Use Change Geographically Weighted Regression Aerosol Optical Depth Particulate Matter Pm10 Location Models
英文摘要The air quality in China, particularly the PM2.5 (particles less than 2.5 m in aerodynamic diameter) level, has become an increasing public concern because of its relation to health risks. The distribution of PM2.5 concentrations has a close relationship with multiple geographic and socioeconomic factors, but the lack of reliable data has been the main obstacle to studying this topic. Based on the newly published Annual Average PM2.5 gridded data, together with land use data, gridded population data and Gross Domestic Product (GDP) data, this paper explored the spatial-temporal characteristics of PM2.5 concentrations and the factors impacting those concentrations in China for the years of 2001-2010. The contributions of urban areas, high population and economic development to PM2.5 concentrations were analyzed using the Geographically Weighted Regression (GWR) model. The results indicated that the spatial pattern of PM2.5 concentrations in China remained stable during the period 2001-2010; high concentrations of PM2.5 are mostly found in regions with high populations and rapid urban expansion, including the Beijing-Tianjin-Hebei region in North China, East China (including the Shandong, Anhui and Jiangsu provinces) and Henan province. Increasing populations, local economic growth and urban expansion are the three main driving forces impacting PM2.5 concentrations.
出处International Journal of Environmental Research and Public Health
11
1
173-186
语种英语
ISSN号1660-4601
源URL[http://192.168.22.105/handle/311030/29742]  
专题资源利用与环境修复重点实验室_外文论文
推荐引用方式
GB/T 7714
Lin G.,Fu J. Y.,Jiang D.,et al. Spatio-Temporal Variation of PM2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China. 2014.

入库方式: OAI收割

来源:地理科学与资源研究所

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