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Int. J. Environ. Res. Public Health 2014, 11(1), 173-186; doi:10.3390/ijerph110100173

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

1
College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, Ding No.11 Xueyuan Road, Haidian District, Beijing 100083, China
2
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
3
University of Chinese Academy of Sciences, No. 19 Yuquan Road, Beijing 100049, China
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Received: 11 October 2013 / Revised: 9 December 2013 / Accepted: 10 December 2013 / Published: 20 December 2013
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Abstract

The air quality in China, particularly the PM2.5 (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 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.
Keywords: PM2.5; GDP; population; land use change; geographically weighted regression PM2.5; GDP; population; land use change; geographically weighted regression
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Lin, G.; Fu, J.; Jiang, D.; Hu, W.; Dong, D.; Huang, Y.; Zhao, M. Spatio-Temporal Variation of PM2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China. Int. J. Environ. Res. Public Health 2014, 11, 173-186.

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