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Carbon emission reduction effects of eco-industrial park policy in China

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  • Qian, Long
  • Xu, Xiaolin
  • Sun, Ying
  • Zhou, Yunjie

Abstract

Scientifically evaluating the carbon emission reduction performance of eco-industrial park (EIP) can provide empirical supports for governments to formulate energy conservation and emission reduction policies. Based on the quasi-natural experiment of China's National Demonstration Eco-Industrial Park (NDEIP) construction, this study adopts the panel data of 285 prefecture-level cities in China from 2003 to 2019 to investigate the effects of EIP policy on urban carbon emission reduction through the multi-period difference in difference method. It was revealed that: (1) NDEIP construction has reduced urban carbon emissions by 3.08%, indicating a significantly inhibiting effect on urban carbon emission level; (2) Improvement the effects of NDEIP construction on urban carbon emission reduction appears in the 2nd year following policy implementation; (3) Carbon emission reduction effects of the NDEIP construction are more significant in small and medium-sized, eastern and western, non-resource-based, and high carbon emission cities; (4) NDEIP construction primarily promotes carbon emission reduction through the improvement of energy use efficiency, while the optimization of energy use structure has a weak effect on carbon emission reduction. Furthermore, NDEIP construction has a strong spatial spillover effect, driving carbon emission reduction in surrounding cities within 450 km.

Suggested Citation

  • Qian, Long & Xu, Xiaolin & Sun, Ying & Zhou, Yunjie, 2022. "Carbon emission reduction effects of eco-industrial park policy in China," Energy, Elsevier, vol. 261(PB).
    • Handle: RePEc:eee:energy:v:261:y:2022:i:pb:s0360544222021995
    DOI: 10.1016/j.energy.2022.125315
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    2. Nie, Changfei & Ye, Susu & Feng, Yuan, 2024. "Place-based policy and urban green technology innovation: Evidence from the revitalization of old revolutionary base areas in China," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 1257-1272.
    3. Luo, Haizhi & Zhang, Yiwen & Gao, Xinyu & Liu, Zhengguang & Song, Xia & Meng, Xiangzhao & Yang, Xiaohu, 2024. "Unveiling land use-carbon Nexus: Spatial matrix-enhanced neural network for predicting commercial and residential carbon emissions," Energy, Elsevier, vol. 305(C).
    4. Ke Huang & Teng Wang & Jiachao Peng & Lijun Sun, 2023. "The Impact of Export Sophistication of the New Energy Industry on Carbon Emissions: An Empirical Study," Energies, MDPI, vol. 16(9), pages 1-15, April.
    5. Lingyu Wang & Hairui Wang & Yingchuan Li & Xingyun Yan & Min Wang & Meixing Guo & Mingzhu Fang & Yue Kong & Jie Hu, 2024. "The Design and Implementation of an Intelligent Carbon Data Management Platform for Digital Twin Industrial Parks," Energies, MDPI, vol. 17(23), pages 1-22, November.
    6. Luo, Haizhi & Wang, Chenglong & Li, Cangbai & Meng, Xiangzhao & Yang, Xiaohu & Tan, Qian, 2024. "Multi-scale carbon emission characterization and prediction based on land use and interpretable machine learning model: A case study of the Yangtze River Delta Region, China," Applied Energy, Elsevier, vol. 360(C).
    7. Xingyun Yan & Lingyu Wang & Mingzhu Fang & Jie Hu, 2022. "How Can Industrial Parks Achieve Carbon Neutrality? Literature Review and Research Prospect Based on the CiteSpace Knowledge Map," Sustainability, MDPI, vol. 15(1), pages 1-29, December.

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