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Spatial-Temporal Evolution of PM 2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017

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  • Yazhu Wang

    (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

  • Xuejun Duan

    (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

  • Lei Wang

    (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

Abstract

PM 2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM 2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM 2.5 patterns and a spatial econometric model to quantify the socio-economic driving factors of PM 2.5 concentration changes. The results are as follows: (1) The annual average value of PM 2.5 concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM 2.5 concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014–2017, the overall PM 2.5 pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 μg/m 3 ) regulated by Chinese government. PM 2.5 pollution patterns showed high values in central and eastern Chinese cities and low values in peripheral areas, with the distinction evident along the same line that delineates China’s uneven population distribution. (3) Population agglomeration, industrial development, foreign investment, transportation, and pollution emissions contributed to the increase of PM 2.5 concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM 2.5 concentration. The results also suggest that China in general remains a “pollution shelter” for foreign-funded enterprises.

Suggested Citation

  • Yazhu Wang & Xuejun Duan & Lei Wang, 2019. "Spatial-Temporal Evolution of PM 2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017," IJERPH, MDPI, vol. 16(6), pages 1-18, March.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:6:p:985-:d:215157
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    5. Lisa C. Vinikoor-Imler & J. Allen Davis & Thomas J. Luben, 2011. "An Ecologic Analysis of County-Level PM 2.5 Concentrations and Lung Cancer Incidence and Mortality," IJERPH, MDPI, vol. 8(6), pages 1-7, June.
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