Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China

Liang Chen · Zhifeng Yang · Bin Chen

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Energy, Environment, Economic Growth Environmental Impact and Sustainability Efficiency Analysis Using DEA

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.

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References

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2012Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis 2019Decomposition analysis of energy-related CO2 emission in the industrial sector of China: Evidence from the LMDI approach 2016The Analysis of CO2Emissions and Reduction Potential in China’s Transport Sector 2018Dynamic evolution of characteristics and decomposition of factors influencing industrial carbon dioxide emissions in China: 1991–2015

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