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The scale boundary of urbanized population with peaking PM2.5 concentration: a spatial panel econometric analysis of China’s prefecture-level and above cities

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  • Yongpei Wang
  • Zhenyu Xu

Abstract

In view of China’s rapid urbanization for decades and its environmental effects, this paper focused on the impact of urbanization on fine particulate matter (PM2.5) concentration, and estimated the definitive urbanized population whose PM2.5 concentration reached the peak according to the comparison of classical static/dynamic spatial econometric models. The estimation results of 227 prefecture-level cities and municipalities directly under the central government covering the period 1998–2016 show that the spatial spillover effect is statistically significant, while the exogenous effect stands out in the dynamic spatial Durbin model. In terms of the relationship between urbanized population and PM2.5 concentration, the cities themselves and the exogenous influences from other neighboring cities are U-shaped and inverted U-shaped with urbanized population at the inflection point that 3.77 million and 1.77 million, respectively. Moreover, the exogenous effects occupy the mainstream position, indicating that the PM2.5 concentration of prefecture-level cities mostly comes from the input of surrounding cities. It is proven in this paper that a moderate scale of population urbanization is an important factor in haze control, which should be accompanied by joint governance and coordination of urban agglomeration.

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  • Yongpei Wang & Zhenyu Xu, 2022. "The scale boundary of urbanized population with peaking PM2.5 concentration: a spatial panel econometric analysis of China’s prefecture-level and above cities," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 65(1), pages 126-149, January.
  • Handle: RePEc:taf:jenpmg:v:65:y:2022:i:1:p:126-149
    DOI: 10.1080/09640568.2021.1879033
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    Cited by:

    1. Huiping Wang & Qi Ge, 2022. "Analysis of the Spatial Association Network of PM 2.5 and Its Influencing Factors in China," IJERPH, MDPI, vol. 19(19), pages 1-15, October.

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