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Research on Environmental Kuznets Curve of Construction Waste Generation Based on China’s Provincial Data

Author

Listed:
  • Buhan Wang

    (School of Architectural Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Renfu Jia

    (School of Architectural Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Jiahui Xu

    (School of Architectural Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Yi Wei

    (School of Architectural Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Qiangsheng Li

    (School of Architectural Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Yi Yao

    (School of Architectural Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Xiaoxia Zhu

    (School of Architectural Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Anqi Xu

    (School of Architectural Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Jiaxin Zhang

    (School of Economics and Management, Inner Mongolia University of Science & Technology, Baotou 014010, China)

Abstract

The mounting volume of construction waste in China has been steadily rising over the years, yet has largely been overlooked. The environmental Kuznets curve offers a theoretical framework for understanding environmental management by illustrating the relationship between economic development and environmental degradation. This paper applies the environmental Kuznets curve concept to China’s construction waste generation, utilizing per capita construction waste and gross domestic product per capita as environmental and economic indicators, respectively. Panel data from 31 Chinese provinces, municipalities, and autonomous regions spanning from 2000 to 2022 are analyzed. This study reveals an N-shaped relationship between per capita construction waste generation and gross domestic product per capita in China. Additionally, this paper employs the stochastic impacts by regression on population, affluence, and technology model to assess the factors influencing construction waste generation. In descending order of impact, these factors are the size of China’s secondary industry value added (19.34%), construction labor productivity (19.33%), gross domestic product per capita (18.54%), urbanization rate (17.77%), year-end resident population (17.22%), and the technical equipment rate of construction enterprises (8.83%). All these factors contribute positively to construction waste generation. These findings are pivotal in guiding efforts towards minimizing construction waste at its source and for the sustainable development of the construction industry.

Suggested Citation

  • Buhan Wang & Renfu Jia & Jiahui Xu & Yi Wei & Qiangsheng Li & Yi Yao & Xiaoxia Zhu & Anqi Xu & Jiaxin Zhang, 2024. "Research on Environmental Kuznets Curve of Construction Waste Generation Based on China’s Provincial Data," Sustainability, MDPI, vol. 16(13), pages 1-14, June.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:13:p:5610-:d:1426298
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    References listed on IDEAS

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    1. Shen, Junyi, 2006. "A simultaneous estimation of Environmental Kuznets Curve: Evidence from China," China Economic Review, Elsevier, vol. 17(4), pages 383-394.
    2. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    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. Lu, Weisheng & Tam, Vivian W.Y., 2013. "Construction waste management policies and their effectiveness in Hong Kong: A longitudinal review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 214-223.
    5. Friedl, Birgit & Getzner, Michael, 2003. "Determinants of CO2 emissions in a small open economy," Ecological Economics, Elsevier, vol. 45(1), pages 133-148, April.
    6. Danesh Miah, Md. & Farhad Hossain Masum, Md. & Koike, Masao, 2010. "Global observation of EKC hypothesis for CO2, SOx and NOx emission: A policy understanding for climate change mitigation in Bangladesh," Energy Policy, Elsevier, vol. 38(8), pages 4643-4651, August.
    7. 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.
    8. Park, Soonae & Lee, Youngmi, 2011. "Regional model of EKC for air pollution: Evidence from the Republic of Korea," Energy Policy, Elsevier, vol. 39(10), pages 5840-5849, October.
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