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Decomposition and scenario analysis of CO2 emissions in China’s power industry: based on LMDI method

Yuhuan Zhao (), Hao Li, Zhonghua Zhang, Yongfeng Zhang, Song Wang and Ya Liu
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Yuhuan Zhao: Beijing Institute of Technology
Hao Li: Beijing Institute of Technology
Zhonghua Zhang: Beijing Institute of Technology
Yongfeng Zhang: Beijing Institute of Technology
Song Wang: Beijing Institute of Technology
Ya Liu: Beijing Institute of Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2017, vol. 86, issue 2, 645-668

Abstract: Abstract The power industry is a major contributor to CO2 emissions in China and thus plays a critical role in achieving the targets of CO2 emission reduction. This study analyzes the historical trajectory and feature of CO2 emissions in China’s power industry, explores the driving factors of CO2 emission change using LMDI method, and develops two emission reduction scenarios to evaluate the reduction potential of CO2 emissions. Results show the following: (1) China’s power industry has experienced a significant but unstable increase in CO2 emissions from 343.18 Mt in 1985 to 3447.57 Mt in 2013, a growth rate of 904.60%. (2) Industrial-scale effect plays a dominant role in promoting CO2 emission growth in China’s power industry, and the corresponding contribution degree reaches 111.73%. Energy intensity effect contributes most to the decrease in CO2 emissions, with a contribution degree of −16.82%. Capital productivity effect is another important factor leading to the increase in CO2 emissions. (3) The aggregate CO2 emission reduction in China’s power industry would reach 18,031.62 Mt in the ideal scenario and 15,466.03 Mt in the current policy scenario during 2014–2030. Finally, this study provides policy implications for energy-saving and CO2 emission reduction in China’s power industry.

Keywords: CO2 emissions; Driving factors; Emission reduction potential; Power industry; LMDI method (search for similar items in EconPapers)
Date: 2017
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