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Decomposition Analysis of Energy-Related Industrial CO 2 Emissions in China

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  • Liang Chen

    (State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China)

  • Zhifeng Yang

    (State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China)

  • Bin Chen

    (State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China)

Abstract

Based on the logarithmic mean Divisia index (LMDI) approach, this paper presents a decomposition analysis of China’s energy-related industrial CO 2 emissions from 1985 to 2007, as well as a comparative analysis of differential influences of various factors on six sectors. Via the decomposition, five categories of influencing factors are included: (1) Per capita GDP ( PCG ) was the largest positive driving factor for industrial CO 2 emissions growth for all sectors in China, with the largest cumulative contribution value; Population ( P ), economic structure ( YS ) and energy structure ( ES ) also played a positive driving role, but with weak contributions. As the only negative inhibiting factor, energy intensity ( EI ) significantly reduced the energy-related CO 2 emissions from industrial sectors. Meanwhile, CO 2 emissions reduction based on the efficiency of energy use still held a large space. (2) Various influencing factors imposed differential impacts on CO 2 emissions of six sectors.

Suggested Citation

  • Liang Chen & Zhifeng Yang & Bin Chen, 2013. "Decomposition Analysis of Energy-Related Industrial CO 2 Emissions in China," Energies, MDPI, vol. 6(5), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:5:p:2319-2337:d:25289
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