Carbon emissions from energy consumption in China: Its measurement and driving factors

To address climate change effectively, it is essential to quantify CO2 emissions and the driving factors in high-energy-consuming countries. China is the top CO2-emitting country; moreover, there is a lack of comprehensive analytical studies on quantifying the contributions of key drivers to high-en...

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Published inThe Science of the total environment Vol. 648; pp. 1411 - 1420
Main Authors Ma, Xiaojun, Wang, Changxin, Dong, Biying, Gu, Guocui, Chen, Ruimin, Li, Yifan, Zou, Hongfei, Zhang, Wenfeng, Li, Qiunan
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 15.01.2019
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Abstract To address climate change effectively, it is essential to quantify CO2 emissions and the driving factors in high-energy-consuming countries. China is the top CO2-emitting country; moreover, there is a lack of comprehensive analytical studies on quantifying the contributions of key drivers to high-energy-consuming countries' CO2 emissions. Therefore, based on data of China's energy consumption from 2005 to 2016, this paper combines the extended Kaya identity with the logarithmic mean Divisia index (LMDI) decomposition method to construct an optimized carbon emission decomposition model. Carbon emission and carbon emission intensity are measured and decomposed. Then, the results of the decomposition are discussed, and the effects of various drivers on carbon emissions from energy consumption in China are analysed. Furthermore, we demonstrate real applications of decomposition analysis in policy-making using examples from China and present some ideas to reduce CO2. The results show that from 2005 to 2016, China's total carbon emissions accounted for nearly one-third of the world's total carbon emissions, and the intensity of carbon emissions in China was generally higher than that of worldwide. The rapid development of economy and acceleration of urbanization are not conducive to reduction of carbon emissions. Reducing the intensity of energy consumption, adjusting the internal structure of the industry and perfecting the economic policy system should be important means used to promote the development of China's low-carbon economy in the future. [Display omitted] •Economic output increase is the largest driving factor promoting the CO2 emissions of China.•In China, CO2 missions from energy consumption in industrial sector accounted for the greatest proportion.•Phasing out excess capacity in China reduced emissions in the industry sector.•Energy intensity reduction is a key for high-energy-consuming countries to reduce CO2 emissions.•Promoting the transformation of the industrial structure is an efficient way to reduce CO2 emissions.
AbstractList To address climate change effectively, it is essential to quantify CO2 emissions and the driving factors in high-energy-consuming countries. China is the top CO2-emitting country; moreover, there is a lack of comprehensive analytical studies on quantifying the contributions of key drivers to high-energy-consuming countries' CO2 emissions. Therefore, based on data of China's energy consumption from 2005 to 2016, this paper combines the extended Kaya identity with the logarithmic mean Divisia index (LMDI) decomposition method to construct an optimized carbon emission decomposition model. Carbon emission and carbon emission intensity are measured and decomposed. Then, the results of the decomposition are discussed, and the effects of various drivers on carbon emissions from energy consumption in China are analysed. Furthermore, we demonstrate real applications of decomposition analysis in policy-making using examples from China and present some ideas to reduce CO2. The results show that from 2005 to 2016, China's total carbon emissions accounted for nearly one-third of the world's total carbon emissions, and the intensity of carbon emissions in China was generally higher than that of worldwide. The rapid development of economy and acceleration of urbanization are not conducive to reduction of carbon emissions. Reducing the intensity of energy consumption, adjusting the internal structure of the industry and perfecting the economic policy system should be important means used to promote the development of China's low-carbon economy in the future. [Display omitted] •Economic output increase is the largest driving factor promoting the CO2 emissions of China.•In China, CO2 missions from energy consumption in industrial sector accounted for the greatest proportion.•Phasing out excess capacity in China reduced emissions in the industry sector.•Energy intensity reduction is a key for high-energy-consuming countries to reduce CO2 emissions.•Promoting the transformation of the industrial structure is an efficient way to reduce CO2 emissions.
To address climate change effectively, it is essential to quantify CO emissions and the driving factors in high-energy-consuming countries. China is the top CO -emitting country; moreover, there is a lack of comprehensive analytical studies on quantifying the contributions of key drivers to high-energy-consuming countries' CO emissions. Therefore, based on data of China's energy consumption from 2005 to 2016, this paper combines the extended Kaya identity with the logarithmic mean Divisia index (LMDI) decomposition method to construct an optimized carbon emission decomposition model. Carbon emission and carbon emission intensity are measured and decomposed. Then, the results of the decomposition are discussed, and the effects of various drivers on carbon emissions from energy consumption in China are analysed. Furthermore, we demonstrate real applications of decomposition analysis in policy-making using examples from China and present some ideas to reduce CO . The results show that from 2005 to 2016, China's total carbon emissions accounted for nearly one-third of the world's total carbon emissions, and the intensity of carbon emissions in China was generally higher than that of worldwide. The rapid development of economy and acceleration of urbanization are not conducive to reduction of carbon emissions. Reducing the intensity of energy consumption, adjusting the internal structure of the industry and perfecting the economic policy system should be important means used to promote the development of China's low-carbon economy in the future.
To address climate change effectively, it is essential to quantify CO2 emissions and the driving factors in high-energy-consuming countries. China is the top CO2-emitting country; moreover, there is a lack of comprehensive analytical studies on quantifying the contributions of key drivers to high-energy-consuming countries' CO2 emissions. Therefore, based on data of China's energy consumption from 2005 to 2016, this paper combines the extended Kaya identity with the logarithmic mean Divisia index (LMDI) decomposition method to construct an optimized carbon emission decomposition model. Carbon emission and carbon emission intensity are measured and decomposed. Then, the results of the decomposition are discussed, and the effects of various drivers on carbon emissions from energy consumption in China are analysed. Furthermore, we demonstrate real applications of decomposition analysis in policy-making using examples from China and present some ideas to reduce CO2. The results show that from 2005 to 2016, China's total carbon emissions accounted for nearly one-third of the world's total carbon emissions, and the intensity of carbon emissions in China was generally higher than that of worldwide. The rapid development of economy and acceleration of urbanization are not conducive to reduction of carbon emissions. Reducing the intensity of energy consumption, adjusting the internal structure of the industry and perfecting the economic policy system should be important means used to promote the development of China's low-carbon economy in the future.To address climate change effectively, it is essential to quantify CO2 emissions and the driving factors in high-energy-consuming countries. China is the top CO2-emitting country; moreover, there is a lack of comprehensive analytical studies on quantifying the contributions of key drivers to high-energy-consuming countries' CO2 emissions. Therefore, based on data of China's energy consumption from 2005 to 2016, this paper combines the extended Kaya identity with the logarithmic mean Divisia index (LMDI) decomposition method to construct an optimized carbon emission decomposition model. Carbon emission and carbon emission intensity are measured and decomposed. Then, the results of the decomposition are discussed, and the effects of various drivers on carbon emissions from energy consumption in China are analysed. Furthermore, we demonstrate real applications of decomposition analysis in policy-making using examples from China and present some ideas to reduce CO2. The results show that from 2005 to 2016, China's total carbon emissions accounted for nearly one-third of the world's total carbon emissions, and the intensity of carbon emissions in China was generally higher than that of worldwide. The rapid development of economy and acceleration of urbanization are not conducive to reduction of carbon emissions. Reducing the intensity of energy consumption, adjusting the internal structure of the industry and perfecting the economic policy system should be important means used to promote the development of China's low-carbon economy in the future.
To address climate change effectively, it is essential to quantify CO₂ emissions and the driving factors in high-energy-consuming countries. China is the top CO₂-emitting country; moreover, there is a lack of comprehensive analytical studies on quantifying the contributions of key drivers to high-energy-consuming countries' CO₂ emissions. Therefore, based on data of China's energy consumption from 2005 to 2016, this paper combines the extended Kaya identity with the logarithmic mean Divisia index (LMDI) decomposition method to construct an optimized carbon emission decomposition model. Carbon emission and carbon emission intensity are measured and decomposed. Then, the results of the decomposition are discussed, and the effects of various drivers on carbon emissions from energy consumption in China are analysed. Furthermore, we demonstrate real applications of decomposition analysis in policy-making using examples from China and present some ideas to reduce CO₂. The results show that from 2005 to 2016, China's total carbon emissions accounted for nearly one-third of the world's total carbon emissions, and the intensity of carbon emissions in China was generally higher than that of worldwide. The rapid development of economy and acceleration of urbanization are not conducive to reduction of carbon emissions. Reducing the intensity of energy consumption, adjusting the internal structure of the industry and perfecting the economic policy system should be important means used to promote the development of China's low-carbon economy in the future.
Author Dong, Biying
Li, Yifan
Gu, Guocui
Zou, Hongfei
Wang, Changxin
Zhang, Wenfeng
Chen, Ruimin
Ma, Xiaojun
Li, Qiunan
Author_xml – sequence: 1
  givenname: Xiaojun
  surname: Ma
  fullname: Ma, Xiaojun
  organization: School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
– sequence: 2
  givenname: Changxin
  surname: Wang
  fullname: Wang, Changxin
  organization: School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
– sequence: 3
  givenname: Biying
  surname: Dong
  fullname: Dong, Biying
  email: 514922818@qq.com
  organization: School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
– sequence: 4
  givenname: Guocui
  surname: Gu
  fullname: Gu, Guocui
  organization: AECOM Asia Company Limited (Hong Kong), HongKong 8/F, Tower 2, Grand Central Plaza 138 Shatin Rural Committee Road, Shatin N.T. 999077, Hong Kong, China
– sequence: 5
  givenname: Ruimin
  surname: Chen
  fullname: Chen, Ruimin
  organization: School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
– sequence: 6
  givenname: Yifan
  surname: Li
  fullname: Li, Yifan
  organization: College of Letters and Science, University of California-Los Angeles, Los Angeles, CA 90024, USA
– sequence: 7
  givenname: Hongfei
  surname: Zou
  fullname: Zou, Hongfei
  organization: School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
– sequence: 8
  givenname: Wenfeng
  surname: Zhang
  fullname: Zhang, Wenfeng
  organization: School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
– sequence: 9
  givenname: Qiunan
  surname: Li
  fullname: Li, Qiunan
  organization: School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
BackLink https://www.ncbi.nlm.nih.gov/pubmed/30340286$$D View this record in MEDLINE/PubMed
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Energy consumption
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China
Carbon emissions
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Snippet To address climate change effectively, it is essential to quantify CO2 emissions and the driving factors in high-energy-consuming countries. China is the top...
To address climate change effectively, it is essential to quantify CO emissions and the driving factors in high-energy-consuming countries. China is the top CO...
To address climate change effectively, it is essential to quantify CO₂ emissions and the driving factors in high-energy-consuming countries. China is the top...
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SubjectTerms carbon
carbon dioxide
Carbon emissions
China
climate change
Driving factors
economic policy
emissions factor
energy
Energy consumption
greenhouse gas emissions
industry
Kaya-LMDI
urbanization
Title Carbon emissions from energy consumption in China: Its measurement and driving factors
URI https://dx.doi.org/10.1016/j.scitotenv.2018.08.183
https://www.ncbi.nlm.nih.gov/pubmed/30340286
https://www.proquest.com/docview/2116863850
https://www.proquest.com/docview/2123718455
Volume 648
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