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Exploring the Spatial Variation Characteristics and Influencing Factors of PM 2.5 Pollution in China: Evidence from 289 Chinese Cities

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  • Shen Zhao

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Department of Geography, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yong Xu

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Department of Geography, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Haze pollution has become an urgent environmental problem due to its impact on the environment as well as human health. PM 2.5 is one of the core pollutants which cause haze pollution in China. Existing studies have rarely taken a comprehensive view of natural environmental conditions and socio-economic factors to figure out the cause and diffusion mechanism of PM 2.5 pollution. This paper selected both natural environmental conditions (precipitation (PRE), wind speed (WIN), and terrain relief (TR)) and socio-economic factors (human activity intensity of land surface (HAILS), the secondary industry’s proportion (SEC), and the total particulate matter emissions of motor vehicles (VE)) to analyze the effects on the spatial variation of PM 2.5 concentrations. Based on the spatial panel data of 289 cities in China in 2015, we used spatial statistical methods to visually describe the spatial distribution characteristics of PM 2.5 pollution; secondly, the spatial agglomeration state of PM 2.5 pollution was characterized by Moran’s I ; finally, several regression models were used to quantitatively analyze the correlation between PM 2.5 pollution and the selected explanatory variables. Results from this paper confirm that in 2015, most cities in China suffered from severe PM 2.5 pollution, and only 17.6% of the sample cities were up to standard. The spatial agglomeration characteristics of PM 2.5 pollution in China were particularly significant in the Beijing–Tianjin–Hebei region. Results from the global regression models suggest that WIN exerts the most significant effects on decreasing PM 2.5 concentration ( p < 0.01), while VE is the most critical driver of increasing PM 2.5 concentration ( p < 0.01). Results from the local regression model show reliable evidence that the relation between PM 2.5 concentrations and the explanatory variables varied differently over space. VE is the most critical factor that influences PM 2.5 concentrations, which means controlling motor vehicle pollutant emissions is an effective measure to reduce PM 2.5 pollution in Chinese cities.

Suggested Citation

  • Shen Zhao & Yong Xu, 2019. "Exploring the Spatial Variation Characteristics and Influencing Factors of PM 2.5 Pollution in China: Evidence from 289 Chinese Cities," Sustainability, MDPI, vol. 11(17), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:17:p:4751-:d:262616
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    References listed on IDEAS

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    Cited by:

    1. Ye Yang & Haifeng Lan & Jing Li, 2019. "Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM 2.5 Concentration in China’s Inland Cities: A Case Study from Chengdu Plain Economic Zone," IJERPH, MDPI, vol. 17(1), pages 1-19, December.
    2. Qian Chen & Dongsheng Wang & Xiaobing Li & Bai Li & Ruifeng Song & Hongdi He & Zhongren Peng, 2019. "Vertical Characteristics of Winter Ozone Distribution within the Boundary Layer in Shanghai Based on Hexacopter Unmanned Aerial Vehicle Platform," Sustainability, MDPI, vol. 11(24), pages 1-13, December.
    3. Huanhuan Xiong & Lingyu Lan & Longwu Liang & Yaobin Liu & Xiaoyu Xu, 2020. "Spatiotemporal Differences and Dynamic Evolution of PM 2.5 Pollution in China," Sustainability, MDPI, vol. 12(13), pages 1-18, July.
    4. Xinfei Li & Baodong Cheng & Qiling Hong & Chang Xu, 2021. "Can a Win–Win Situation of Economy and Environment Be Achieved in Cities by the Government’s Environmental Regulations?," Sustainability, MDPI, vol. 13(11), pages 1-20, May.
    5. Wentao Yang & Zhanjun He & Huikun Huang & Jincai Huang, 2021. "A Clustering Framework to Reveal the Structural Effect Mechanisms of Natural and Social Factors on PM 2.5 Concentrations in China," Sustainability, MDPI, vol. 13(3), pages 1-15, January.
    6. Yifeng Xue & Xizi Cao & Yi Ai & Kangli Xu & Yichen Zhang, 2020. "Primary Air Pollutants Emissions Variation Characteristics and Future Control Strategies for Transportation Sector in Beijing, China," Sustainability, MDPI, vol. 12(10), pages 1-10, May.
    7. Xia Li & Guangyao Deng, 2021. "Research on the Effect of an Environmental Protection Tax Policy on Haze Control in China—Empirical Analysis Based on Provincial Panel Data," Sustainability, MDPI, vol. 14(1), pages 1-12, December.

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