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Study on Dynamic Total Factor Carbon Emission Efficiency in China’s Urban Agglomerations

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  • Fan Zhang

    (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Center for Chinese Agricultural Policy, Chinese Academy of Sciences, Beijing 100101, China)

  • Gui Jin

    (College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China)

  • Junlong Li

    (School of Economics and Management, Sanming University, Sanming 365004, China
    Research Center of Low Carbon Economy, Research Base of Humanities and Social Sciences of Fujian Institutions of Higher Learning, Sanming 365004, China)

  • Chao Wang

    (State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China)

  • Ning Xu

    (College of Geography and Environment, Shandong Normal University, Jinan 250358, China)

Abstract

The scale effect of urbanization on improving carbon emission efficiency and achieving low-carbon targets is an important topic in urban research. Using dynamic panel data from 64 prefecture-level cities in four typical urban agglomerations in China from 2006 to 2016, this paper constructed a stochastic frontier analysis model to empirically measure the city-level total-factor carbon emission efficiency index (TCEI) at different stages of urbanization and to identify rules governing its spatiotemporal evolution. We quantitatively analyzed the influences and functional characteristics of TCEI in the four urban agglomerations of Pearl River Delta, Beijing-Tianjin-Hebei, the Yangtze River Delta, and Chengdu-Chongqing. Results show that the TCEI at different stages of urbanization in these urban agglomerations is increasing year by year. The overall city-level TCEI was ranked as follows: Pearl River Delta > Beijing-Tianjin-Hebei > Yangtze River Delta > Chengdu-Chongqing. Improvements in the level of economic development and urbanization will help achieve low-carbon development in a given urban agglomeration. The optimization of industrial structure and improvement of ecological environment will help curb carbon emissions. This paper provides decision-making references for regional carbon emission reduction from optimizing industrial and energy consumption structures and improving energy efficiency.

Suggested Citation

  • Fan Zhang & Gui Jin & Junlong Li & Chao Wang & Ning Xu, 2020. "Study on Dynamic Total Factor Carbon Emission Efficiency in China’s Urban Agglomerations," Sustainability, MDPI, vol. 12(7), pages 1-17, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2675-:d:338303
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    2. Bin Wang & Qiuxia Zheng & Ao Sun & Jie Bao & Dianting Wu, 2021. "Spatio-Temporal Patterns of CO 2 Emissions and Influencing Factors in China Using ESDA and PLS-SEM," Mathematics, MDPI, vol. 9(21), pages 1-24, October.
    3. Da Gao & Xinlin Mo & Ruochan Xiong & Zhiliang Huang, 2022. "Tax Policy and Total Factor Carbon Emission Efficiency: Evidence from China’s VAT Reform," IJERPH, MDPI, vol. 19(15), pages 1-17, July.
    4. Yu, Ying & Dai, Yuqi & Xu, Linyu & Zheng, Hanzhong & Wu, Wenhao & Chen, Lei, 2023. "A multi-level characteristic analysis of urban agglomeration energy-related carbon emission: A case study of the Pearl River Delta," Energy, Elsevier, vol. 263(PB).
    5. Qizhen Wang & Qian Zhang, 2022. "Foreign Direct Investment and Carbon Emission Efficiency: The Role of Direct and Indirect Channels," Sustainability, MDPI, vol. 14(20), pages 1-23, October.

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