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Spatiotemporal investigation of energy network patterns of agglomeration economies in China: Province-level evidence

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  • Hong, Jingke
  • Gu, Jianping
  • Liang, Xin
  • Liu, Guiwen
  • Shen, Geoffrey Qiping
  • Tang, Miaohan

Abstract

China is currently in the fast track of urbanization and industrialization. This poses a series of challenges pertaining to environmental issues given the resultant boom in energy consumption and carbon emissions. To tackle these problems, this study explores the effects of economic agglomerations and geographic attributes on energy transmission patterns using multi-regional input-output model, complex network analysis, and exploratory spatial data analysis. The results show that Shandong, Jiangsu, and Zhejiang are the three leading regions with regard embodied energy consumption; they have distinct energy utilization models but can also provide instructive lessons for energy conservation at the provincial level. Energy interactions represent self-organizing agglomerative patterns, and the physical geographic clusters are highly consistent with the virtual administrative division of agglomeration economies. The in-depth investigation of major agglomerations has revealed that infrastructure construction remains a vital driver of local economies in developing areas, whereas more developed agglomeration economies have more balanced and service-oriented development. Bilateral connections in current major agglomeration economies have been enhanced, but multilateral connections are still rare. The findings of this study provide a bottom-up insight into the spatiotemporal effect on embodied energy system of China.

Suggested Citation

  • Hong, Jingke & Gu, Jianping & Liang, Xin & Liu, Guiwen & Shen, Geoffrey Qiping & Tang, Miaohan, 2019. "Spatiotemporal investigation of energy network patterns of agglomeration economies in China: Province-level evidence," Energy, Elsevier, vol. 187(C).
  • Handle: RePEc:eee:energy:v:187:y:2019:i:c:s0360544219316925
    DOI: 10.1016/j.energy.2019.115998
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    5. Jingke, Hong & Chenyu, Wang & Chang-Richards, Alice & Jingxiao, Zhang & Qiping, Geoffrey Shen & Bei, Qiao, 2022. "A spatiotemporal analysis of energy use pathways in the construction industry: A study of China," Energy, Elsevier, vol. 239(PC).
    6. Hui Peng & Yifan Wang & Yisha Hu & Hong Shen, 2020. "Agglomeration Production, Industry Association and Carbon Emission Performance: Based on Spatial Analysis," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    7. Liu, S. & Xiao, Q., 2021. "An empirical analysis on spatial correlation investigation of industrial carbon emissions using SNA-ICE model," Energy, Elsevier, vol. 224(C).
    8. Yao, Huizong & Zang, Chuanfu, 2021. "The spatiotemporal characteristics of electrical energy supply-demand and the green economy outlook of Guangdong Province, China," Energy, Elsevier, vol. 214(C).

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