Spatio-Temporal Variation of PM2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China

International Journal of Environmental Research and Public Health

Gang Lin¹  Jingying Fu²  Dong Jiang²  Wensheng Hu²  Donglin Dong¹  Yaohuan Huang² 

[1] College of Geoscience and Surveying Engineering, China University of Mining & Technology, Ding No.11 Xueyuan Road, Haidian District, Beijing 100083, China; E-Mails:;State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China; E-Mails:

关键词: PM_2.5;    GDP;    population;    land use change;    geographically weighted regression;   

DOI  :  10.3390/ijerph110100173

来源: mdpi

【 摘 要 】

The air quality in China, particularly the PM_2.5 (particles less than 2.5 μm in aerodynamic diameter) level, has become an increasing public concern because of its relation to health risks. The distribution of PM_2.5 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 PM_2.5 gridded data, together with land use data, gridded population data and Gross Domestic Product (GDP) data, this paper explored the spatial-temporal characteristics of PM_2.5 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 PM_2.5 concentrations were analyzed using the Geographically Weighted Regression (GWR) model. The results indicated that the spatial pattern of PM_2.5 concentrations in China remained stable during the period 2001–2010; high concentrations of PM_2.5 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 PM_2.5 concentrations.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.