Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China
AbstractBased on the logarithmic mean Divisia index (LMDI) approach, this paper presents a decomposition analysis of China’s energy-related industrial CO2 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 CO2 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 CO2 emissions from industrial sectors. Meanwhile, CO2 emissions reduction based on the efficiency of energy use still held a large space. (2) Various influencing factors imposed differential impacts on CO2 emissions of six sectors.
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Chen, L.; Yang, Z.; Chen, B. Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China. Energies 2013, 6, 2319-2337.
Chen L, Yang Z, Chen B. Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China. Energies. 2013; 6(5):2319-2337.Chicago/Turabian Style
Chen, Liang; Yang, Zhifeng; Chen, Bin. 2013. "Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China." Energies 6, no. 5: 2319-2337.