Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China

Energies

Liang Chen²  Zhifeng Yang¹ 

[1] State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China; E-Mail

关键词: decomposition analysis;    energy-related industrial CO₂ emissions;    industrial discrepancy;   

DOI  :  10.3390/en6052319

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.