Lin Gang, Fu Jingying, Jiang Dong, Hu Wensheng, Dong Donglin, Huang Yaohuan, Zhao Mingdong
College of Geoscience and Surveying Engineering, China University of Mining & Technology, Ding No.11 Xueyuan Road, Haidian District, Beijing 100083, China.
Int J Environ Res Public Health. 2013 Dec 20;11(1):173-86. doi: 10.3390/ijerph110100173.
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.
中国的空气质量,尤其是细颗粒物(空气动力学直径小于2.5微米的颗粒物)水平,因其与健康风险的关联,已日益受到公众关注。细颗粒物浓度分布与多种地理和社会经济因素密切相关,但缺乏可靠数据一直是研究该主题的主要障碍。基于最新发布的年均细颗粒物网格化数据,结合土地利用数据、网格化人口数据和国内生产总值(GDP)数据,本文探讨了2001 - 2010年中国细颗粒物浓度的时空特征以及影响这些浓度的因素。利用地理加权回归(GWR)模型分析了城市地区、高人口密度和经济发展对细颗粒物浓度的贡献。结果表明,2001 - 2010年期间中国细颗粒物浓度的空间格局保持稳定;细颗粒物高浓度主要出现在人口密集和城市快速扩张的地区,包括中国北方的京津冀地区、华东地区(包括山东、安徽和江苏省)以及河南省。人口增长、地方经济增长和城市扩张是影响细颗粒物浓度的三个主要驱动力。