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Spatial differences in energy performance among four municipalities of China: From both the aggregate and final demand perspectives

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  • Yan, Junna
  • Su, Bin

Abstract

City, which consumes the majority of the total energy consumptions, has great influences on the national energy issues. As the widespread spatial differences, a quantitative energy analysis among multi-city allows exploring the targeted and distinguishing energy policy implications at the city level in China. Considering the significant role of final demands, the input-output model and spatial structural decomposition analysis were adopted to evaluate the energy performances and quantify the spatial differences. In 2012, the spatial differences in the energy consumptions were distinct, with the greatest gap between Shanghai and Chongqing, which were mainly driven by the domestic Leontief structure effect and the total final demand effect. In particular, the spatial differences in the embodied energy by net domestic outflow were remarkable. For the relative energy efficiency, Beijing was discovered the best, followed by Tianjin, Shanghai and Chongqing. The spatial differences in their energy intensity were primarily influenced by the energy intensity effect and the domestic Leontief structure effect. In addition, the spatial differences in the aggregate embodied energy intensity by domestic investment were prominent. Inspired by the results, the structure adjustments with respect to the production and final demands and regional cooperation are strongly advised at the city level.

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  • Yan, Junna & Su, Bin, 2020. "Spatial differences in energy performance among four municipalities of China: From both the aggregate and final demand perspectives," Energy, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:energy:v:204:y:2020:i:c:s0360544220310227
    DOI: 10.1016/j.energy.2020.117915
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    Cited by:

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    2. Sun, Ya-Fang & Yu, Shiwei & Zhang, Yue-Jun & Su, Bin, 2023. "How do imports change the energy consumption of China? An analysis of its role in intermediate inputs and final demands," Energy, Elsevier, vol. 270(C).
    3. Lin Liu & Heinz Schandl & James West & Meng Jiang & Zijian Ren & Dingjiang Chen & Bing Zhu, 2022. "Copper ore material footprints and transfers embodied in domestic and international trade of provinces in China," Journal of Industrial Ecology, Yale University, vol. 26(4), pages 1423-1436, August.
    4. Zhe Yang & Zhenwu Xiong & Wenhao Xue & Yuhong Zhou, 2022. "The Impact of Pollution Fee Reform on the Emission of Water Pollutants: Evidence from Manufacturing Enterprises in China," IJERPH, MDPI, vol. 19(17), pages 1-17, August.
    5. Guevara, Zeus & Henriques, SofiaTeives & Sousa, Tânia, 2021. "Driving factors of differences in primary energy intensities of 14 European countries," Energy Policy, Elsevier, vol. 149(C).
    6. Xia, Quanzhi & Han, Mengyao & Guan, Shihui & Wu, Xiaofang & Zhang, Bo, 2022. "Tracking embodied energy flows of China's megacities via multi-scale supply chains," Energy, Elsevier, vol. 260(C).
    7. Zhang, Xiaomei & Su, Bin & Yang, Jun & Cong, Jianhui, 2022. "Analysis of Shanxi Province's energy consumption and intensity using input-output framework (2002–2017)," Energy, Elsevier, vol. 250(C).

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