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Study on the Decoupling and Interaction Effect between Industrial Structure Upgrading and Carbon Emissions under Dual Carbon Targets

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  • Yuqing Sun

    (College of Economics, North China University of Science and Technology, Tangshan 063210, China)

  • Yingchao Liu

    (College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China)

  • Zhiwei Yang

    (College of Science, North China University of Science and Technology, Tangshan 063210, China)

  • Mengyao Wang

    (College of Science, North China University of Science and Technology, Tangshan 063210, China)

  • Chunying Zhang

    (College of Science, North China University of Science and Technology, Tangshan 063210, China)

  • Liya Wang

    (College of Science, North China University of Science and Technology, Tangshan 063210, China)

Abstract

The issue of climate and environment has been paid more and more attention by countries all over the world, especially regarding carbon emissions. Many national policies and scholars’ research contents have focused on this issue, which has become a hot topic in today’s society. As the world’s largest carbon emitter, it is vital for China to achieve green development, upgrade its industrial structure and explore the relationship between industrial structure upgrading and carbon emissions. To explore the decoupling and interactive effects of industrial structure upgrading and carbon emissions, this paper divides industrial structure upgrading into two aspects: rationalization of industrial structure and upgrading of industrial structure. Indicators related to industrial structure upgrading and carbon emissions are selected and the decoupling model of carbon emissions and industrial structure upgrading is constructed using panel data from 30 regions from 1997 to 2019. The core density function is used to analyze the decoupling distribution characteristics, and then the Gini coefficient decomposition method is used to analyze the carbon emissions decoupling index, revealing the regional differences and sources of carbon emissions decoupling index. Finally, spatial factors are included in the regression model to verify the spatial synergy effect of industrial structure upgrading on carbon emissions. The overall and local Moran indexes are used to reveal the spatial internal structure and agglomeration characteristics of industrial structure upgrading and carbon emissions, and, based on the research results, policy recommendations are put forward to promote sustainable and stable development of industrial structure upgrading in China. This provides a new perspective for understanding the relationship between industrial structure upgrading and carbon emissions and also provides a decision-making reference for promoting decoupling of industrial structure upgrading and carbon emissions under high-quality economic development and forcing low-carbon transformation of the industrial structure.

Suggested Citation

  • Yuqing Sun & Yingchao Liu & Zhiwei Yang & Mengyao Wang & Chunying Zhang & Liya Wang, 2023. "Study on the Decoupling and Interaction Effect between Industrial Structure Upgrading and Carbon Emissions under Dual Carbon Targets," IJERPH, MDPI, vol. 20(3), pages 1-19, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:1945-:d:1042490
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    References listed on IDEAS

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    1. Wu, Linfei & Sun, Liwen & Qi, Peixiao & Ren, Xiangwei & Sun, Xiaoting, 2021. "Energy endowment, industrial structure upgrading, and CO2 emissions in China: Revisiting resource curse in the context of carbon emissions," Resources Policy, Elsevier, vol. 74(C).
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    Cited by:

    1. Chen, Zeyu & Tang, Yuhong & Shen, Hebin & Liu, Jiali & Hu, Zheng, 2024. "Threshold effects of Government digital development and land resource disparity on Urban carbon efficiency in China," Resources Policy, Elsevier, vol. 94(C).
    2. Congqi Wang & Rui Zhang & Haslindar Ibrahim & Pengzhen Liu, 2023. "Can the Digital Economy Enable Carbon Emission Reduction: Analysis of Mechanisms and China’s Experience," Sustainability, MDPI, vol. 15(13), pages 1-20, June.

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