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Impact of Environmental Regulation and Industrial Agglomeration on Carbon Emissions in the Yangtze River Economic Belt

Author

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  • Xiaoling Zhang

    (School of Law and Business, Sanjiang University, Nanjing 210012, China)

  • Zhiwei Pan

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Decai Tang

    (School of Law and Business, Sanjiang University, Nanjing 210012, China
    School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Zixuan Deng

    (School of Geography, Nanjing Normal University, Nanjing 210023, China)

  • Valentina Boamah

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

Abstract

Carbon reduction is an important aspect of achieving high-quality environmental development; environmental regulation and industrial agglomeration are important ways to affect carbon emissions. Therefore, studying the relationship between industrial agglomeration, environmental regulation, and carbon emissions has important theoretical and practical significance. Firstly, this article adopts the method of location entropy to measure the indicators of industrial agglomeration. Secondly, it proposes an environmental regulation indicator system based on the experience of previous scholars and measures the environmental regulation indicators using the entropy method. Next, eight types of energy consumption are used to measure carbon emissions based on the carbon emission coefficient method provided by the IPCC. Finally, based on the Moran index, the spatial correlation of carbon emission levels in various regions of the Yangtze River Economic Belt (YREB) is tested. A spatial econometric model was introduced to explore the relationship between industrial agglomeration, environmental regulation, and carbon emissions at a deeper level, and the following conclusions were drawn: (1) The regression coefficient of the spatial term of industrial agglomeration on carbon emissions is 0.848, which is significantly positive at the 10% level, indicating that under the influence of spatial effects, industrial agglomeration has a significant promoting effect on carbon emissions. (2) The regression coefficient of the spatial term of environmental regulation on carbon emissions is −0.011, which is significantly negative at the 10% level, indicating that environmental regulation has an inhibitory effect on carbon emissions under the influence of spatial effects. Based on the above conclusions, useful suggestions have been provided for optimizing industrial structure, improving environmental regulation levels, and alleviating carbon emission issues.

Suggested Citation

  • Xiaoling Zhang & Zhiwei Pan & Decai Tang & Zixuan Deng & Valentina Boamah, 2023. "Impact of Environmental Regulation and Industrial Agglomeration on Carbon Emissions in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(10), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8308-:d:1151106
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    References listed on IDEAS

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    1. Xu, Yong & Li, Shanshan & Zhou, Xiaoxiao & Shahzad, Umer & Zhao, Xin, 2022. "How environmental regulations affect the development of green finance: Recent evidence from polluting firms in China," Renewable Energy, Elsevier, vol. 189(C), pages 917-926.
    2. Zhao, Jun & Dong, Xiucheng & Dong, Kangyin, 2021. "How does producer services’ agglomeration promote carbon reduction?: The case of China," Economic Modelling, Elsevier, vol. 104(C).
    3. Smulders, Sjak & Tsur, Yacov & Zemel, Amos, 2012. "Announcing climate policy: Can a green paradox arise without scarcity?," Journal of Environmental Economics and Management, Elsevier, vol. 64(3), pages 364-376.
    4. Zhao, Jun & Jiang, Qingzhe & Dong, Xiucheng & Dong, Kangyin, 2020. "Would environmental regulation improve the greenhouse gas benefits of natural gas use? A Chinese case study," Energy Economics, Elsevier, vol. 87(C).
    5. Lan, Fei & Sun, Li & Pu, Wenyan, 2021. "Research on the influence of manufacturing agglomeration modes on regional carbon emission and spatial effect in China," Economic Modelling, Elsevier, vol. 96(C), pages 346-352.
    6. Akihiro Otsuka & Mika Goto & Toshiyuki Sueyoshi, 2014. "Energy efficiency and agglomeration economies: the case of Japanese manufacturing industries," Regional Science Policy & Practice, Wiley Blackwell, vol. 6(2), pages 195-212, June.
    7. Tuochen Li & Dongri Han & Shaosong Feng & Lei Liang, 2019. "Can Industrial Co-Agglomeration between Producer Services and Manufacturing Reduce Carbon Intensity in China?," Sustainability, MDPI, vol. 11(15), pages 1-15, July.
    8. Ding, Jian & Liu, Baoliu & Shao, Xuefeng, 2022. "Spatial effects of industrial synergistic agglomeration and regional green development efficiency: Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    9. Al-Hadi, Ahmed & Al-Abri, Almukhtar, 2022. "Firm-level trade credit responses to COVID-19-induced monetary and fiscal policies: International evidence," Research in International Business and Finance, Elsevier, vol. 60(C).
    10. Lai, Aolin & Wang, Qunwei & Cui, Lianbiao, 2022. "Can market segmentation lead to green paradox? Evidence from China," Energy, Elsevier, vol. 254(PC).
    11. Li, Xuehui & Xu, Yangyang & Yao, Xin, 2021. "Effects of industrial agglomeration on haze pollution: A Chinese city-level study," Energy Policy, Elsevier, vol. 148(PA).
    12. Lv, Zhike & Liu, Wangxin & Xu, Ting, 2022. "Evaluating the impact of information and communication technology on renewable energy consumption: A spatial econometric approach," Renewable Energy, Elsevier, vol. 189(C), pages 1-12.
    13. Xie, Li & Zhou, Zhichao & Hui, Shimin, 2022. "Does environmental regulation improve the structure of power generation technology? Evidence from China's pilot policy on the carbon emissions trading market(CETM)," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    14. Wu, Haitao & Xu, Lina & Ren, Siyu & Hao, Yu & Yan, Guoyao, 2020. "How do energy consumption and environmental regulation affect carbon emissions in China? New evidence from a dynamic threshold panel model," Resources Policy, Elsevier, vol. 67(C).
    15. Wu, Jianxin & Xu, Hui & Tang, Kai, 2021. "Industrial agglomeration, CO2 emissions and regional development programs: A decomposition analysis based on 286 Chinese cities," Energy, Elsevier, vol. 225(C).
    16. Liu, Jin & Tian, Jiayu & Lyu, Wenjing & Yu, Yitian, 2022. "The impact of COVID-19 on reducing carbon emissions: From the angle of international student mobility," Applied Energy, Elsevier, vol. 317(C).
    17. Zhang, Wei & Li, Guoxiang & Guo, Fanyong, 2022. "Does carbon emissions trading promote green technology innovation in China?," Applied Energy, Elsevier, vol. 315(C).
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    1. Yunpeng Fu & Zixuan Wang, 2024. "The Impact of Industrial Agglomeration on Urban Carbon Emissions: An Empirical Study Based on the Panel Data of China’s Prefecture-Level Cities," Sustainability, MDPI, vol. 16(23), pages 1-28, November.

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