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The Cause of China’s Haze Pollution: City Level Evidence Based on the Extended STIRPAT Model

Author

Listed:
  • Jingyuan Li

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

  • Jinhua Cheng

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

  • Yang Wen

    (Chinese Academy of Macroeconomic Research, Beijing 100038, China
    Institute of Spatial Planning & Regional Economy, National Development and Reform Commission, Beijing 100038, China)

  • Jingyu Cheng

    (School of Physical Education, China University of Geosciences, Wuhan 430074, China)

  • Zhong Ma

    (School of Environment and Natural Resources, Renmin University of China, Beijing 100872, China)

  • Peiqi Hu

    (School of Environment and Natural Resources, Renmin University of China, Beijing 100872, China
    Department of Forest and Conservation Science, University of British Columbia, Vancouver, BC V6T 1Z4, Canada)

  • Shurui Jiang

    (School of Environment and Natural Resources, Renmin University of China, Beijing 100872, China)

Abstract

Based on the extended STIRPAT model, this paper examines social and economic factors regarding PM 2.5 concentration intensity in 255 Chinese cities from 2007 to 2016, and includes quantile regressions to analyze the different effects of these factors among cities of various sizes. The results indicate that: (1) during 2007–2016, urban PM 2.5 concentration exhibited declining trends in fluctuations concerning the development of the urban economy, accompanied by uncertainty under different city types; (2) population size has a significant effect on propelling PM 2.5 concentration; (3) the effect of structure reformation on PM 2.5 concentration is evident among cities with different populations and levels of economic development; and (4) foreign investment and scientific technology can significantly reduce PM 2.5 emission concentration in cities. Accordingly, local governments not only endeavor to further control population size, but should implement a recycling economy, and devise a viable urban industrial structure. The city governance policies for PM 2.5 concentration reduction require re-classification according to different population scales. Cities with large populations (i.e., over 10 million) should consider reducing their energy consumption. Medium population-sized cities (between 1 million and 10 million) should indeed implement effective population (density) control policies, while cities with small populations (less than 1 million) should focus on promoting sustainable urban development to stop environmental pollution from secondary industry sources.

Suggested Citation

  • Jingyuan Li & Jinhua Cheng & Yang Wen & Jingyu Cheng & Zhong Ma & Peiqi Hu & Shurui Jiang, 2022. "The Cause of China’s Haze Pollution: City Level Evidence Based on the Extended STIRPAT Model," IJERPH, MDPI, vol. 19(8), pages 1-18, April.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4597-:d:791272
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    References listed on IDEAS

    as
    1. Stern, David I., 2004. "The Rise and Fall of the Environmental Kuznets Curve," World Development, Elsevier, vol. 32(8), pages 1419-1439, August.
    2. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(3), pages 597-625, June.
    3. Shixiong Cheng & Jiahui Xie & De Xiao & Yun Zhang, 2019. "Measuring the Environmental Efficiency and Technology Gap of PM 2.5 in China’s Ten City Groups: An Empirical Analysis Using the EBM Meta-Frontier Model," IJERPH, MDPI, vol. 16(4), pages 1-22, February.
    4. Azam, Muhammad, 2016. "Does environmental degradation shackle economic growth? A panel data investigation on 11 Asian countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 175-182.
    5. 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.
    6. Hering, Laura & Poncet, Sandra, 2014. "Environmental policy and exports: Evidence from Chinese cities," Journal of Environmental Economics and Management, Elsevier, vol. 68(2), pages 296-318.
    7. Wang, Ping & Wu, Wanshui & Zhu, Bangzhu & Wei, Yiming, 2013. "Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China," Applied Energy, Elsevier, vol. 106(C), pages 65-71.
    8. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    9. Nagashima, Fumiya, 2018. "Critical structural paths of residential PM2.5 emissions within the Chinese provinces," Energy Economics, Elsevier, vol. 70(C), pages 465-471.
    10. Kangyin Dong & Xiucheng Dong & Cong Dong, 2019. "Determinants of the global and regional CO2 emissions: What causes what and where?," Applied Economics, Taylor & Francis Journals, vol. 51(46), pages 5031-5044, October.
    11. Peter Pedroni, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 653-670, November.
    12. Dongdong Ma & Guifang Li & Feng He, 2021. "Exploring PM2.5 Environmental Efficiency and Its Influencing Factors in China," IJERPH, MDPI, vol. 18(22), pages 1-15, November.
    13. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    14. Azam, Muhammad & Khan, Abdul Qayyum, 2016. "Testing the Environmental Kuznets Curve hypothesis: A comparative empirical study for low, lower middle, upper middle and high income countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 556-567.
    15. Junliang Yang & Haiyan Shan, 2019. "Identifying Driving Factors of Jiangsu’s Regional Sulfur Dioxide Emissions: A Generalized Divisia Index Method," IJERPH, MDPI, vol. 16(20), pages 1-20, October.
    16. Yan, Dan & Ren, Xiaohang & Kong, Ying & Ye, Bin & Liao, Zangyi, 2020. "The heterogeneous effects of socioeconomic determinants on PM2.5 concentrations using a two-step panel quantile regression," Applied Energy, Elsevier, vol. 272(C).
    17. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    18. J. Lelieveld & J. S. Evans & M. Fnais & D. Giannadaki & A. Pozzer, 2015. "The contribution of outdoor air pollution sources to premature mortality on a global scale," Nature, Nature, vol. 525(7569), pages 367-371, September.
    19. repec:bla:obuest:v:61:y:1999:i:0:p:653-70 is not listed on IDEAS
    20. Miao, Zhuang & Baležentis, Tomas & Shao, Shuai & Chang, Dongfeng, 2019. "Energy use, industrial soot and vehicle exhaust pollution—China's regional air pollution recognition, performance decomposition and governance," Energy Economics, Elsevier, vol. 83(C), pages 501-514.
    21. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
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    Cited by:

    1. Cheng Zhan & Mingjing Guo & Jinhua Cheng & Hongxia Peng, 2022. "Evaluation of Resources and Environment Carrying Capacity Based on Support Pressure Coupling Mechanism: A Case Study of the Yangtze River Economic Belt," IJERPH, MDPI, vol. 20(1), pages 1-21, December.
    2. Xin Xu & Yuming Shen & Hanchu Liu, 2022. "What Cause Large Spatiotemporal Differences in Carbon Intensity of Energy-Intensive Industries in China? Evidence from Provincial Data during 2000–2019," IJERPH, MDPI, vol. 19(16), pages 1-18, August.
    3. Zhen Yang & Weijun Gao, 2022. "Evaluating the Coordinated Development between Urban Greening and Economic Growth in Chinese Cities during 2005 to 2019," IJERPH, MDPI, vol. 19(15), pages 1-25, August.

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