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Energies 2013, 6(5), 2319-2337; doi:10.3390/en6052319

Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China

State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
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Received: 31 December 2012 / Revised: 7 April 2013 / Accepted: 7 April 2013 / Published: 25 April 2013
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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.
Keywords: decomposition analysis; energy-related industrial CO2 emissions; industrial discrepancy decomposition analysis; energy-related industrial CO2 emissions; industrial discrepancy
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Chen, L.; Yang, Z.; Chen, B. Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China. Energies 2013, 6, 2319-2337.

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