Decomposition analysis of energy-related industrial CO2 emissions in China

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Abstract

Based 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. © 2013 by the authors.

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APA

Chen, L., Yang, Z., & Chen, B. (2013). Decomposition analysis of energy-related industrial CO2 emissions in China. Energies, 6(5), 2319–2337. https://doi.org/10.3390/en6052319

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