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Analysis on the influencing factors of carbon emissions from energy consumption in China based on LMDI method

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  • Yang Yu

    (Beijing University of Chemical Technology)

  • Qiuyue Kong

    (Beijing University of Chemical Technology)

Abstract

Based on the time series decomposition of the Log-Mean Divisia Index, this paper analyzes the driving factors of carbon emissions from energy consumption by introducing the indicators of energy trade in China during the period of 2000–2014. The carbon emissions are decomposed into carbon emission coefficient, population, economic output, energy intensity, energy trade, energy structure and industrial structure effect in the manuscript. The result indicates that economic activity has the largest positive effect on the variation of carbon emissions. The energy trade has a greatest opposite effect on carbon emission change. At the same time, China has achieved a considerable decrease in carbon emission mainly due to the improvement of energy intensity and the optimization of energy and industrial structure. However, the influences of those changes in energy intensity, energy and industrial structure are relatively small. In addition, through the analysis by using a suitable index of energy trade, it was found that improving the conditions of energy trade can effectively optimize the energy structure and reduce the carbon emission in China.

Suggested Citation

  • Yang Yu & Qiuyue Kong, 2017. "Analysis on the influencing factors of carbon emissions from energy consumption in China based on LMDI method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1691-1707, September.
    • Handle: RePEc:spr:nathaz:v:88:y:2017:i:3:d:10.1007_s11069-017-2941-0
    DOI: 10.1007/s11069-017-2941-0
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