Spatiotemporal Variability of Remotely Sensed PM 2.5 Concentrations in China from 1998 to 2014 Based on a Bayesian Hierarchy Model
Junming Li,
Meijun Jin and
Zheng Xu
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Junming Li: Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Xudong Street 340, Wuhan 430077, China
Meijun Jin: College of Architecture and Civil Engineering, Taiyuan University of Technology, Yingze Street 79, Taiyuan 030024, China
Zheng Xu: Henan University, Jin Ming Avenue, Kaifeng 475001, China
IJERPH, 2016, vol. 13, issue 8, 1-17
Abstract:
With the rapid industrial development and urbanization in China over the past three decades, PM 2.5 pollution has become a severe environmental problem that threatens public health. Due to its unbalanced development and intrinsic topography features, the distribution of PM 2.5 concentrations over China is spatially heterogeneous. In this study, we explore the spatiotemporal variations of PM 2.5 pollution in China and four great urban areas from 1998 to 2014. A space-time Bayesian hierarchy model is employed to analyse PM 2.5 pollution. The results show that a stable “3-Clusters” spatial PM 2.5 pollution pattern has formed. The mean and 90% quantile of the PM 2.5 concentrations in China have increased significantly, with annual increases of 0.279 ?g/m 3 (95% CI: 0.083?0.475) and 0.735 ?g/m 3 (95% CI: 0.261?1.210), respectively. The area with a PM 2.5 pollution level of more than 70 ?g/m 3 has increased significantly, with an annual increase of 0.26 percentage points. Two regions in particular, the North China Plain and Sichuan Basin, are experiencing the largest amounts of PM 2.5 pollution. The polluted areas, with a high local magnitude of more than 1.0 relative to the overall PM 2.5 concentration, affect an area with a human population of 949 million, which corresponded to 69.3% of the total population in 2010. North and south differentiation occurs in the urban areas of the Jingjinji and Yangtze Delta, and circular and radial gradient differentiation occur in the urban areas of the Cheng-Yu and Pearl Deltas. The spatial heterogeneity of the urban Jingjinji group is the strongest. Eighteen cities located in the Yangtze Delta urban group, including Shanghai and Nanjing, have experienced high PM 2.5 concentrations and faster local trends of increasing PM 2.5 . The percentage of exposure to PM 2.5 concentrations greater than 70 ?g/m 3 and 100 ?g/m 3 is increasing significantly.
Keywords: PM 2.5 concentrations; spatiotemporal variation; Bayesian hierarchy model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:13:y:2016:i:8:p:772-:d:75161
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