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 in | The Science of the total environment Vol. 648; pp. 1411 - 1420 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier B.V
15.01.2019
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Subjects | |
Online Access | Get full text |
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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.
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•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. |
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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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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 |
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