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Using LMDI to Analyze the Decoupling of Carbon Dioxide Emissions from China’s Heavy Industry

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  • Lin Boqiang

    (Collaborative Innovation Center for Energy Economics and Energy Policy, China Institute for Studies in Energy Policy, School of Management, Xiamen University, Xiamen 361005, Fujian, China)

  • Kui Liu

    (The School of Economics, China Center for Energy Economics Research, Xiamen University, Xiamen 361005, Fujian, China)

Abstract

China is facing huge pressure on CO 2 emissions reduction. The heavy industry accounts for over 60% of China’s total energy consumption, and thus leads to a large number of energy-related carbon emissions. This paper adopts the Log Mean Divisia Index (LMDI) method based on the extended Kaya identity to explore the influencing factors of CO 2 emissions from China’s heavy industry; we calculate the trend of decoupling by presenting a theoretical framework for decoupling. The results show that labor productivity, energy intensity, and industry scale are the main factors affecting CO 2 emissions in the heavy industry. The improvement of labor productivity is the main cause of the increase in CO 2 emissions, while the decline in energy intensity leads to CO 2 emissions reduction, and the industry scale has different effects in different periods. Results from the decoupling analysis show that efforts made on carbon emission reduction, to a certain extent, achieved the desired outcome but still need to be strengthened.

Suggested Citation

  • Lin Boqiang & Kui Liu, 2017. "Using LMDI to Analyze the Decoupling of Carbon Dioxide Emissions from China’s Heavy Industry," Sustainability, MDPI, vol. 9(7), pages 1-16, July.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:7:p:1198-:d:103923
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