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Comprehensive Assessment and Obstacle Analysis on Low-Carbon Development Quality of 30 Provincial Regions in China

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Listed:
  • Haoran Zhao

    (Business School, Beijing Information Science & Technology University, Beijing 100085, China)

  • Zhen Yang

    (Business School, Beijing Information Science & Technology University, Beijing 100085, China)

  • Shunan Wu

    (China Energy Capital Holdings Co., Ltd., Beijing 100044, China)

  • Zhuowen Zhang

    (Business School, Beijing Information Science & Technology University, Beijing 100085, China)

  • Chuan Li

    (Business School, Beijing Information Science & Technology University, Beijing 100085, China)

  • Chunhua Jin

    (Business School, Beijing Information Science & Technology University, Beijing 100085, China)

  • Sen Guo

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

Low-carbon development (LCD) in China has become the critical measure to achieve sustainable development and handle climate change. This investigation evaluates 30 provincial regions’ LCD quality from dimensions of low-carbon (LC) economy, resources utilization, LC environment, and LC society. According to the integrated weights combined subjective weights identified through the best–worst method (BWM) and objective weights attained through the anti-entropy weight (AEW) method, the top five sub-criteria in 2021 were coal consumption relative to total primary energy consumption, industrial sulfur dioxide (SO 2 ) emission, carbon dioxide emissions intensity, industrial dust emission, and forest coverage rate. According to the comprehensive evaluation results obtained through the MARCOS model, Beijing’s comprehensive score is far ahead, and its scores in resource utilization, LC environment, and LC economy are also in a leading position. Moreover, the level of LCD quality shows a gradually reduced pattern from east to west. The obstacle analysis demonstrates that the obstacle factors with high frequency of occurrence include real GDP, energy intensity, coal consumption relative to total primary energy consuming, carbon dioxide emissions intensity, industrial dust emission, industrial SO 2 emission, forest coverage rate, and the number of private vehicles. Suggestions are proposed based on the results, including increase infrastructure construction, optimize energy structure and develop renewable energy, protect the ecological environment with intensify efforts, and accelerate industrial transformation and upgrading to optimize industrial structure.

Suggested Citation

  • Haoran Zhao & Zhen Yang & Shunan Wu & Zhuowen Zhang & Chuan Li & Chunhua Jin & Sen Guo, 2025. "Comprehensive Assessment and Obstacle Analysis on Low-Carbon Development Quality of 30 Provincial Regions in China," Sustainability, MDPI, vol. 17(6), pages 1-27, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2425-:d:1609169
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    References listed on IDEAS

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    2. Glaeser, Edward L. & Kahn, Matthew E., 2010. "The greenness of cities: Carbon dioxide emissions and urban development," Journal of Urban Economics, Elsevier, vol. 67(3), pages 404-418, May.
    3. Haixiang Guo & Xiao Liu & Yijing Li & Deyun Wang & Xiaohong Chen, 2015. "Comparison Analysis and Evaluation of Urban Competitiveness in Chinese Urban Clusters," Sustainability, MDPI, vol. 7(4), pages 1-23, April.
    4. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    5. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
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