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The Spatial and Heterogeneity Impacts of Population Urbanization on Fine Particulate (PM 2.5 ) in the Yangtze River Economic Belt, China

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  • Weiwei Xie

    (School of Economics and Management, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

  • Hongbing Deng

    (School of Economics and Management, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

  • Zhaohui Chong

    (Business School, Shantou University, 243 Daxue Road, Shantou 528400, China)

Abstract

This paper addresses the effect of population urbanization on Fine Particulate (PM 2.5 ) in the Yangtze River Economic Belt in China from 2006 to 2016 by employing PM2.5 remote sensing data and using the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. The study contributes to the growing empirical literature by addressing heterogeneity, spillover, and dynamic effects in the dynamic spatial panel modeling process simultaneously. The empirical results show that population urbanization has a significant impact on PM 2.5 with a positive spillover effect and a dynamic effect being detected and controlled. The heterogeneity effects of population urbanization on PM 2.5 due to geographical positions show evidence of an obvious inverted U-shaped curve relationship in the upstream area and an increasing function curve in the midstream and downstream areas. The heterogeneity effects due to population urbanization levels show that an inverted N-shape curve relationship exists in low and medium urbanization level areas, while a U-shape curve relationship exists in high urbanization level areas. It is hoped that this study will inform the local governments about the heterogeneity of population urbanization and spillover effects of air pollution when addressing air pollution control.

Suggested Citation

  • Weiwei Xie & Hongbing Deng & Zhaohui Chong, 2019. "The Spatial and Heterogeneity Impacts of Population Urbanization on Fine Particulate (PM 2.5 ) in the Yangtze River Economic Belt, China," IJERPH, MDPI, vol. 16(6), pages 1-17, March.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:6:p:1058-:d:216637
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    as
    1. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    2. Zhou, D.Q. & Wang, Qunwei & Su, B. & Zhou, P. & Yao, L.X., 2016. "Industrial energy conservation and emission reduction performance in China: A city-level nonparametric analysis," Applied Energy, Elsevier, vol. 166(C), pages 201-209.
    3. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    4. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    5. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    6. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    7. Lee, Sanghoon & Oh, Dae-Won, 2015. "Economic growth and the environment in China: Empirical evidence using prefecture level data," China Economic Review, Elsevier, vol. 36(C), pages 73-85.
    8. Song, Tao & Zheng, Tingguo & Tong, Lianjun, 2008. "An empirical test of the environmental Kuznets curve in China: A panel cointegration approach," China Economic Review, Elsevier, vol. 19(3), pages 381-392, September.
    9. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    10. Selden Thomas M. & Song Daqing, 1995. "Neoclassical Growth, the J Curve for Abatement, and the Inverted U Curve for Pollution," Journal of Environmental Economics and Management, Elsevier, vol. 29(2), pages 162-168, September.
    11. Wang, Mingwei & Che, Yue & Yang, Kai & Wang, Min & Xiong, Lijun & Huang, Yuchi, 2011. "A local-scale low-carbon plan based on the STIRPAT model and the scenario method: The case of Minhang District, Shanghai, China," Energy Policy, Elsevier, vol. 39(11), pages 6981-6990.
    12. Friedl, Birgit & Getzner, Michael, 2003. "Determinants of CO2 emissions in a small open economy," Ecological Economics, Elsevier, vol. 45(1), pages 133-148, April.
    13. Lottmann, Franziska, 2012. "Spatial dependencies in German matching functions," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 27-41.
    14. Shao, Shuai & Yang, Lili & Gan, Chunhui & Cao, Jianhua & Geng, Yong & Guan, Dabo, 2016. "Using an extended LMDI model to explore techno-economic drivers of energy-related industrial CO2 emission changes: A case study for Shanghai (China)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 516-536.
    15. Bai, Chong-En & Ma, Hong & Pan, Wenqing, 2012. "Spatial spillover and regional economic growth in China," China Economic Review, Elsevier, vol. 23(4), pages 982-990.
    16. Beidi Diao & Lei Ding & Panda Su & Jinhua Cheng, 2018. "The Spatial-Temporal Characteristics and Influential Factors of NOx Emissions in China: A Spatial Econometric Analysis," IJERPH, MDPI, vol. 15(7), pages 1-19, July.
    17. Ji, Xi & Yao, Yixin & Long, Xianling, 2018. "What causes PM2.5 pollution? Cross-economy empirical analysis from socioeconomic perspective," Energy Policy, Elsevier, vol. 119(C), pages 458-472.
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