INVESTIGATING THE SPATIOTEMPORAL PM2.5 DYNAMIC AND SOCIOECONOMIC DRIVING FORCES IN BEIJING BASED ON GEOGRAPHICAL WEIGHTED REGRESSION

JOURNAL OF NONLINEAR AND CONVEX ANALYSIS(2021)

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摘要
The atmospheric haze brings about immeasurable damage to the area it covers and has a negative impact on people's physical and mental health, which has become a global concern. Based on this, this study, taking Beijing city as the research subject, analyzed the spatiotemporal variation characteristics, and identified the regional social-economic driving factors of PM2.5 pollution, using spatial gravity model and geographically weighted regression model, respectively. Temporally, the annual average concentration of PM2.5 pollution showed an overall rising trend during 2014-2015 (mostly in the range of 75-135 mu g/m(3)), and then maintained a downward trend during 2016-2018 (mostly in the range of 35-75 mu g/m(3)) due to the implementation of the policy. In 2019, the PM2.5 concentration remained on a downward trend, generally within the range of 15-35 mu g/m(3), satisfying the Level II limit by the Ambient Air Quality Standard (GB3095-2012). Spatially, during 2014-2019, the spatial pattern of PM2.5 pollution in Beijing remains stable, with generally higher concentrations in the southeast of Beijing than the northwest during the same period. For driving forces, there is an obvious spatial difference between the effects of different social-economic driving factors on PM2.5. The permanent population density, proportion of second industry, civil car owned, and sown area of crops are mainly positively relevant, while per capita GDP and green rate of trees are mainly negatively relevant. Finally, some targeted suggestions were proposed for promoting equitable and coordinated development of the economic environment in all municipal districts of Beijing, based on the spatiotemporal variation characteristics and driving force sources of PM2.5 pollution.
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关键词
PM2.5, driving forces, geographical weighted regression, countermeasures
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