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Embodied Energy Flow Patterns of the Internal and External Industries of Manufacturing in China

Author

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  • Zhijun Feng

    (School of Economic and Management, Dongguan University of Technology, Dongguan 523808, China)

  • Wen Zhou

    (College of System Engineering, National University of Defense Technology, Changsha 410073, China)

  • Qian Ming

    (School of Economic and Management, Dongguan University of Technology, Dongguan 523808, China)

Abstract

The Sino–US trade war has prompted China to re-examine the development of manufacturing, while the energy crisis restricts such development. Scientifically planning industrial energy allocation is important for supporting industrial transformation and the upgrading of manufacturing. The embodied energy flow in China’s manufacturing was investigated by reconstructing the energy flow network; taking a systems perspective, a fine-grained analysis of the emerging patterns and evolution of these flows in the internal and external manufacturing industries was performed, thus providing useful insights for energy planning. The results show that in the internal and external networks of Chinese manufacturing, most of the embodied energy convergence and transmission is concentrated in a few industries Moreover, it is clear that industries with stronger embodied energy convergence and conductivity are generally more likely to be associated with industries with weak convergence and conductivity. Preferential selection is an important mechanism for the generation of embodied energy flow paths. The choices of the embodied energy flow paths of various industries exhibit the preference that ‘the rich get richer,’ and newly generated flow paths are more likely to be chosen for connectivity to a path of strong convergence or conductivity. The embodied energy flow patterns of the internal network of manufacturing mainly include two-focus and multi-focus convergence patterns, while that of the external network of manufacturing is mainly a two-focus transmission pattern. Within in-edge networks, communities of high-end manufacturing have gathered most of the embodied energy, while in out-edge networks, communities of traditional manufacturing have been key in the transmission of embodied energy. The impacts of the internal and external network types, and of the in-edge and out-edge types on the stability of the embodied energy flow pattern are separate, and the embodied energy flow pattern is stable. Based on these findings, an ‘energy-related industrial cluster’ model is proposed here to aid in energy convergence and transmission, as well as to realize network cluster synergy.

Suggested Citation

  • Zhijun Feng & Wen Zhou & Qian Ming, 2019. "Embodied Energy Flow Patterns of the Internal and External Industries of Manufacturing in China," Sustainability, MDPI, vol. 11(2), pages 1-24, January.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:2:p:438-:d:198037
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    References listed on IDEAS

    as
    1. Jack Miller & Timothy J. Foxon & Steve Sorrell, 2016. "Exergy Accounting: A Quantitative Comparison of Methods and Implications for Energy-Economy Analysis," Energies, MDPI, vol. 9(11), pages 1-22, November.
    2. Hao, Xiaoqing & An, Haizhong & Qi, Hai & Gao, Xiangyun, 2016. "Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network," Applied Energy, Elsevier, vol. 162(C), pages 1515-1522.
    3. Jian Hou & Heng Chen & Jianzhong Xu, 2017. "External Knowledge Sourcing and Green Innovation Growth with Environmental and Energy Regulations: Evidence from Manufacturing in China," Sustainability, MDPI, vol. 9(3), pages 1-17, February.
    4. Xiaoqing Chen & Zaiwu Gong, 2017. "DEA Efficiency of Energy Consumption in China’s Manufacturing Sectors with Environmental Regulation Policy Constraints," Sustainability, MDPI, vol. 9(2), pages 1-19, February.
    5. Boqiang Lin & Guanglu Zhang, 2018. "Can Industrial Restructuring Significantly Reduce Energy Consumption? Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(5), pages 1082-1095, April.
    6. Rocco, Matteo V. & Di Lucchio, Alberto & Colombo, Emanuela, 2017. "Exergy Life Cycle Assessment of electricity production from Waste-to-Energy technology: A Hybrid Input-Output approach," Applied Energy, Elsevier, vol. 194(C), pages 832-844.
    7. Shi, Jianglan & Li, Huajiao & Guan, Jianhe & Sun, Xiaoqi & Guan, Qing & Liu, Xiaojia, 2017. "Evolutionary features of global embodied energy flow between sectors: A complex network approach," Energy, Elsevier, vol. 140(P1), pages 395-405.
    8. Chen, G.Q. & Wu, X.F., 2017. "Energy overview for globalized world economy: Source, supply chain and sink," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 735-749.
    9. Liu, Hongtao & Xi, Youmin & Guo, Ju'e & Li, Xia, 2010. "Energy embodied in the international trade of China: An energy input-output analysis," Energy Policy, Elsevier, vol. 38(8), pages 3957-3964, August.
    10. Andersen, Jan Peter & Hyman, Barry, 2001. "Energy and material flow models for the US steel industry," Energy, Elsevier, vol. 26(2), pages 137-159.
    11. Gao, Cuixia & Su, Bin & Sun, Mei & Zhang, Xiaoling & Zhang, Zhonghua, 2018. "Interprovincial transfer of embodied primary energy in China: A complex network approach," Applied Energy, Elsevier, vol. 215(C), pages 792-807.
    12. Chen, B. & Li, J.S. & Wu, X.F. & Han, M.Y. & Zeng, L. & Li, Z. & Chen, G.Q., 2018. "Global energy flows embodied in international trade: A combination of environmentally extended input–output analysis and complex network analysis," Applied Energy, Elsevier, vol. 210(C), pages 98-107.
    13. Sun, Xiaoqi & An, Haizhong & Gao, Xiangyun & Jia, Xiaoliang & Liu, Xiaojia, 2016. "Indirect energy flow between industrial sectors in China: A complex network approach," Energy, Elsevier, vol. 94(C), pages 195-205.
    14. An, Qier & An, Haizhong & Wang, Lang & Gao, Xiangyun & Lv, Na, 2015. "Analysis of embodied exergy flow between Chinese industries based on network theory," Ecological Modelling, Elsevier, vol. 318(C), pages 26-35.
    15. Zeng, Bo & Duan, Huiming & Bai, Yun & Meng, Wei, 2018. "Forecasting the output of shale gas in China using an unbiased grey model and weakening buffer operator," Energy, Elsevier, vol. 151(C), pages 238-249.
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