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How to Effectively Control Energy Consumption Growth in China’s 29 Provinces: A Paradigm of Multi-Regional Analysis Based on EAALMDI Method

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  • Yunlong Zhao

    (State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Research and Education Centre, Tsinghua University, Beijing 100084, China
    Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, International Joint Laboratory on Low Carbon Clean Energy Innovation, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China)

  • Geng Kong

    (State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Research and Education Centre, Tsinghua University, Beijing 100084, China
    Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, International Joint Laboratory on Low Carbon Clean Energy Innovation, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China)

  • Chin Hao Chong

    (State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Research and Education Centre, Tsinghua University, Beijing 100084, China
    Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, International Joint Laboratory on Low Carbon Clean Energy Innovation, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China)

  • Linwei Ma

    (State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Research and Education Centre, Tsinghua University, Beijing 100084, China
    Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, International Joint Laboratory on Low Carbon Clean Energy Innovation, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China)

  • Zheng Li

    (State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Research and Education Centre, Tsinghua University, Beijing 100084, China
    Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, International Joint Laboratory on Low Carbon Clean Energy Innovation, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China)

  • Weidou Ni

    (State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Research and Education Centre, Tsinghua University, Beijing 100084, China
    Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, International Joint Laboratory on Low Carbon Clean Energy Innovation, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China)

Abstract

Controlling energy consumption to reduce greenhouse gas emissions has become a global consensus in response to the challenge of climate change. Most studies have focused on energy consumption control in a single region; however, high-resolution analysis of energy consumption and personalized energy policy-making, for multiple regions with differentiated development, have become a complicated challenge. Using the logarithmic mean Divisia index I (LMDI) decomposition method based on energy allocation analysis (EAA), this paper aims to establish a standard paradigm for a high-resolution analysis of multi-regional energy consumption and provide suggestions for energy policy-making, taking 29 provinces of China as the sample. The process involved three steps: (1) determination of regional priorities of energy consumption control by EAA, (2) revealing regional disparity among the driving forces of energy consumption growth by LMDI, and (3) deriving policy implications by comparing the obtained results with existing policies. The results indicated that 29 provinces can be divided into four groups, with different priorities of energy consumption control according to the patterns of coal flows. Most provinces have increasing levels of energy consumption, driven by increasing per capita GDP and improving living standards, while its growth is restrained by decreasing end-use energy intensity, improving energy supply efficiency, and optimization of industrial structures. However, some provinces are not following these trends to the same degree. This indicates that policy-makers must pay more attention to the different driving mechanisms of energy consumption growth among provinces.

Suggested Citation

  • Yunlong Zhao & Geng Kong & Chin Hao Chong & Linwei Ma & Zheng Li & Weidou Ni, 2021. "How to Effectively Control Energy Consumption Growth in China’s 29 Provinces: A Paradigm of Multi-Regional Analysis Based on EAALMDI Method," Sustainability, MDPI, vol. 13(3), pages 1-26, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:3:p:1093-:d:484516
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    2. Chong, Chin Hao & Zhou, Xiaoyong & Zhang, Yongchuang & Ma, Linwei & Bhutta, Muhammad Shoaib & Li, Zheng & Ni, Weidou, 2023. "LMDI decomposition of coal consumption in China based on the energy allocation diagram of coal flows: An update for 2005–2020 with improved sectoral resolutions," Energy, Elsevier, vol. 285(C).
    3. Chinhao Chong & Xi Zhang & Geng Kong & Linwei Ma & Zheng Li & Weidou Ni & Eugene-Hao-Chen Yu, 2021. "A Visualization Method of the Economic Input–Output Table: Mapping Monetary Flows in the Form of Sankey Diagrams," Sustainability, MDPI, vol. 13(21), pages 1-56, November.
    4. Yunlong Zhao & Linwei Ma & Zheng Li & Weidou Ni, 2022. "A Calculation and Decomposition Method Embedding Sectoral Energy Structure for Embodied Carbon: A Case Study of China’s 28 Sectors," Sustainability, MDPI, vol. 14(5), pages 1-29, February.
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