IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v239y2022ipcs0360544221024233.html
   My bibliography  Save this article

China's carbon intensity factor decomposition and carbon emission decoupling analysis

Author

Listed:
  • Pan, Xiongfeng
  • Guo, Shucen
  • Xu, Haitao
  • Tian, Mengyuan
  • Pan, Xianyou
  • Chu, Junhui

Abstract

China's carbon emissions have been ranking first in the world. This study filled in the gaps in research, decomposed carbon intensity from the perspective of time, space and industry. A decoupling effort model based on factor decomposition models was constructed to analyze the driving factors of carbon emissions and economic decoupling, which builded a foundation for achieving sustainable economic development. Using the Logarithmic Mean Divisia Index method (LMDI), the paper measured the carbon emission intensity of 29 provinces and cities in China from 1998 to 2019, and decomposed the decoupling effect between GDP and carbon emission on the basis of factor decomposition by tapio. The results showed that: (1) Carbon intensity declined first, then rise lightly, and finally declined steadily. For the primary industry and the tertiary industry, the carbon intensity declined steadily, while the carbon intensity increased accordingly to the overall carbon intensity. In terms of spatial evolution, the regional differences between different provinces decreased correspondingly. (2) The cumulative contribution rates of these three effects, i.e., technological progress, industrial structure and regional scale were 106.3299%, −15.1486% and 8.8188%, respectively. There were obvious differences of these cumulative contribution rates of carbon intensity among different provinces. (3) From the perspective of industrial, technological progress effect is the largest contribution for carbon intensity in the secondary industry. The Industrial structure effect mainly affects the primary and tertiary industries; and no significant difference in regional scale effect. (4) The decoupling effect gradually improved, and technological progress has played an absolute leading role in promoting the decoupling effect. Based on the research results, the key policy recommendation are put forward as follows: (1) Further improve the technological level and support clean technology enterprises. (2) Promote industrial upgrading in backward industrial provinces (3) Promote regional assistance and the introduction of high-quality foreign investment.

Suggested Citation

  • Pan, Xiongfeng & Guo, Shucen & Xu, Haitao & Tian, Mengyuan & Pan, Xianyou & Chu, Junhui, 2022. "China's carbon intensity factor decomposition and carbon emission decoupling analysis," Energy, Elsevier, vol. 239(PC).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pc:s0360544221024233
    DOI: 10.1016/j.energy.2021.122175
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221024233
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.122175?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    2. Xie, Pinjie & Yang, Fan & Mu, Zhuowen & Gao, Shuangshuang, 2020. "Influencing factors of the decoupling relationship between CO2 emission and economic development in China’s power industry," Energy, Elsevier, vol. 209(C).
    3. Zhang, Yue-Jun & Da, Ya-Bin, 2015. "The decomposition of energy-related carbon emission and its decoupling with economic growth in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1255-1266.
    4. Tapio, Petri, 2005. "Towards a theory of decoupling: degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001," Transport Policy, Elsevier, vol. 12(2), pages 137-151, March.
    5. Fırat Emir & Festus Victor Bekun, 2019. "Energy intensity, carbon emissions, renewable energy, and economic growth nexus: New insights from Romania," Energy & Environment, , vol. 30(3), pages 427-443, May.
    6. Kaltenegger, Oliver, 2020. "What drives total real unit energy costs globally? A novel LMDI decomposition approach," Applied Energy, Elsevier, vol. 261(C).
    7. de Freitas, Luciano Charlita & Kaneko, Shinji, 2011. "Decomposition of CO2 emissions change from energy consumption in Brazil: Challenges and policy implications," Energy Policy, Elsevier, vol. 39(3), pages 1495-1504, March.
    8. Gregor Semieniuk & Victor M. Yakovenko, 2020. "Historical Evolution of Global Inequality in Carbon Emissions and Footprints versus Redistributive Scenarios," Papers 2004.00111, arXiv.org.
    9. Kimberly M. Carlson & James S. Gerber & Nathaniel D. Mueller & Mario Herrero & Graham K. MacDonald & Kate A. Brauman & Petr Havlik & Christine S. O’Connell & Justin A. Johnson & Sassan Saatchi & Paul , 2017. "Greenhouse gas emissions intensity of global croplands," Nature Climate Change, Nature, vol. 7(1), pages 63-68, January.
    10. Liu, Kui & Bai, Hongkun & Yin, Shuo & Lin, Boqiang, 2018. "Factor substitution and decomposition of carbon intensity in China's heavy industry," Energy, Elsevier, vol. 145(C), pages 582-591.
    11. Nag, Barnali & Parikh, Jyoti, 2000. "Indicators of carbon emission intensity from commercial energy use in India," Energy Economics, Elsevier, vol. 22(4), pages 441-461, August.
    12. Chong, ChinHao & Ma, Linwei & Li, Zheng & Ni, Weidou & Song, Shizhong, 2015. "Logarithmic mean Divisia index (LMDI) decomposition of coal consumption in China based on the energy allocation diagram of coal flows," Energy, Elsevier, vol. 85(C), pages 366-378.
    13. Wang, Zhaohua & Huang, Wanjing & Chen, Zhongfei, 2019. "The peak of CO2 emissions in China: A new approach using survival models," Energy Economics, Elsevier, vol. 81(C), pages 1099-1108.
    14. Wang, Keying & Wu, Meng & Sun, Yongping & Shi, Xunpeng & Sun, Ao & Zhang, Ping, 2019. "Resource abundance, industrial structure, and regional carbon emissions efficiency in China," Resources Policy, Elsevier, vol. 60(C), pages 203-214.
    15. Zhang, Xi & Geng, Yong & Shao, Shuai & Wilson, Jeffrey & Song, Xiaoqian & You, Wei, 2020. "China’s non-fossil energy development and its 2030 CO2 reduction targets: The role of urbanization," Applied Energy, Elsevier, vol. 261(C).
    16. Linghui Zhang & Xin Ma & Shushen Zhang, 2020. "District Heating Energy Consumption of the Building Sector in the Jing-Jin-Ji urban Agglomeration: Decomposition and Decoupling Analysis," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    17. Lu, I.J. & Lin, Sue J. & Lewis, Charles, 2007. "Decomposition and decoupling effects of carbon dioxide emission from highway transportation in Taiwan, Germany, Japan and South Korea," Energy Policy, Elsevier, vol. 35(6), pages 3226-3235, June.
    18. Ang, B.W. & Liu, F.L., 2001. "A new energy decomposition method: perfect in decomposition and consistent in aggregation," Energy, Elsevier, vol. 26(6), pages 537-548.
    19. Pan, Xiongfeng & Ai, Bowei & Li, Changyu & Pan, Xianyou & Yan, Yaobo, 2019. "Dynamic relationship among environmental regulation, technological innovation and energy efficiency based on large scale provincial panel data in China," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 428-435.
    20. Giblin, S. & McNabola, A., 2009. "Modelling the impacts of a carbon emission-differentiated vehicle tax system on CO2 emissions intensity from new vehicle purchases in Ireland," Energy Policy, Elsevier, vol. 37(4), pages 1404-1411, April.
    21. Yue-Jun Zhang & Zhao Liu & Huan Zhang & Tai-De Tan, 2014. "The impact of economic growth, industrial structure and urbanization on carbon emission intensity in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(2), pages 579-595, September.
    22. Albrecht, Johan & Francois, Delphine & Schoors, Koen, 2002. "A Shapley decomposition of carbon emissions without residuals," Energy Policy, Elsevier, vol. 30(9), pages 727-736, July.
    23. Ang, B. W. & Liu, F. L. & Chew, E. P., 2003. "Perfect decomposition techniques in energy and environmental analysis," Energy Policy, Elsevier, vol. 31(14), pages 1561-1566, November.
    24. G. Boyd & J. F. McDonald & M. Ross & D. A. Hansont, 1987. "Separating the Changing Composition of U.S. Manufacturing Production from Energy Efficiency Improvements: A Divisia Index Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 77-96.
    25. Huang, Lizhen & Krigsvoll, Guri & Johansen, Fred & Liu, Yongping & Zhang, Xiaoling, 2018. "Carbon emission of global construction sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1906-1916.
    26. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    27. Wang, Can & Chen, Jining & Zou, Ji, 2005. "Decomposition of energy-related CO2 emission in China: 1957–2000," Energy, Elsevier, vol. 30(1), pages 73-83.
    28. Ozturk, Ilhan & Acaravci, Ali, 2013. "The long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in Turkey," Energy Economics, Elsevier, vol. 36(C), pages 262-267.
    29. Du, Limin & Wei, Chu & Cai, Shenghua, 2012. "Economic development and carbon dioxide emissions in China: Provincial panel data analysis," China Economic Review, Elsevier, vol. 23(2), pages 371-384.
    30. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    31. Li, Aijun & Lin, Boqiang, 2013. "Comparing climate policies to reduce carbon emissions in China," Energy Policy, Elsevier, vol. 60(C), pages 667-674.
    32. Li, Man, 2010. "Decomposing the change of CO2 emissions in China: A distance function approach," Ecological Economics, Elsevier, vol. 70(1), pages 77-85, November.
    33. Zhang, Wei & Wang, Nan, 2021. "Decomposition of energy intensity in Chinese industries using an extended LMDI method of production element endowment," Energy, Elsevier, vol. 221(C).
    34. Pan, Xiongfeng & Uddin, Md. Kamal & Saima, Umme & Jiao, Zhiming & Han, Cuicui, 2019. "How do industrialization and trade openness influence energy intensity? Evidence from a path model in case of Bangladesh," Energy Policy, Elsevier, vol. 133(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yayun Ren & Jian Yu & Shuhua Xu & Jiaomei Tang & Chang Zhang, 2023. "Green Finance and Industrial Low-Carbon Transition: Evidence from a Quasi-Natural Experiment in China," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    2. Xiaochun Zhao & Mei Jiang & Wei Zhang, 2022. "Decoupling between Economic Development and Carbon Emissions and Its Driving Factors: Evidence from China," IJERPH, MDPI, vol. 19(5), pages 1-15, March.
    3. Meng Yang & Yisheng Liu & Jinzhao Tian & Feiyu Cheng & Pengbo Song, 2022. "Dynamic Evolution and Regional Disparity in Carbon Emission Intensity in China," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    4. Shangjiu Wang & Shaohua Zhang & Liang Cheng, 2023. "Drivers and Decoupling Effects of PM 2.5 Emissions in China: An Application of the Generalized Divisia Index," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    5. Pan, Xianyou & Song, Malin & Wang, Yuqing & Shen, Zhiyang & Song, Jinbo & Xie, Pinjie & Pan, Xiongfeng, 2022. "Liability accounting of natural resource assets from the perspective of input Slack—An analysis based on the energy resource in 282 prefecture-level cities in China," Resources Policy, Elsevier, vol. 78(C).
    6. Ozdemir, Ali Can, 2023. "Decomposition and decoupling analysis of carbon dioxide emissions in electricity generation by primary fossil fuels in Turkey," Energy, Elsevier, vol. 273(C).
    7. Li, Rongrong & Han, Xinyu & Wang, Qiang, 2023. "Do technical differences lead to a widening gap in China's regional carbon emissions efficiency? Evidence from a combination of LMDI and PDA approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    8. Sensen Zhang & Zhenggang Huo, 2023. "Analysis of Spatial Correlation and Influencing Factors of Building a Carbon Emission Reduction Potential Network Based on the Coordination of Equity and Efficiency," Sustainability, MDPI, vol. 15(15), pages 1-21, July.
    9. Dong, Jia & Li, Cunbin, 2022. "Scenario prediction and decoupling analysis of carbon emission in Jiangsu Province, China," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    10. Niu, Xiaoqin & Yüksel, Serhat & Dinçer, Hasan, 2023. "Emission strategy selection for the circular economy-based production investments with the enhanced decision support system," Energy, Elsevier, vol. 274(C).
    11. Ye, Li & Yang, Deling & Dang, Yaoguo & Wang, Junjie, 2022. "An enhanced multivariable dynamic time-delay discrete grey forecasting model for predicting China's carbon emissions," Energy, Elsevier, vol. 249(C).
    12. Wang, Juan & Li, Ziming & Wu, Tong & Wu, Siyu & Yin, Tingwei, 2022. "The decoupling analysis of CO2 emissions from power generation in Chinese provincial power sector," Energy, Elsevier, vol. 255(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lingling Chen & Brijesh Thapa & Wei Yan, 2018. "The Relationship between Tourism, Carbon Dioxide Emissions, and Economic Growth in the Yangtze River Delta, China," Sustainability, MDPI, vol. 10(7), pages 1-20, June.
    2. Yue-Jun Zhang & Ya-Bin Da, 2013. "Decomposing the changes of energy-related carbon emissions in China: evidence from the PDA approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(1), pages 1109-1122, October.
    3. Wang, Miao & Feng, Chao, 2017. "Decomposition of energy-related CO2 emissions in China: An empirical analysis based on provincial panel data of three sectors," Applied Energy, Elsevier, vol. 190(C), pages 772-787.
    4. Md. Afzal Hossain & Jean Engo & Songsheng Chen, 2021. "The main factors behind Cameroon’s CO2 emissions before, during and after the economic crisis of the 1980s," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 4500-4520, March.
    5. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry," Energy, Elsevier, vol. 68(C), pages 688-697.
    6. Liang, Wei & Gan, Ting & Zhang, Wei, 2019. "Dynamic evolution of characteristics and decomposition of factors influencing industrial carbon dioxide emissions in China: 1991–2015," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 93-106.
    7. Wang, Miao & Feng, Chao, 2018. "Decomposing the change in energy consumption in China's nonferrous metal industry: An empirical analysis based on the LMDI method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2652-2663.
    8. Leal, Patrícia Alexandra & Marques, António Cardoso & Fuinhas, José Alberto, 2019. "Decoupling economic growth from GHG emissions: Decomposition analysis by sectoral factors for Australia," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 12-26.
    9. Hongwei Xiao & Zhongyu Ma & Peng Zhang & Ming Liu, 2019. "Study of the impact of energy consumption structure on carbon emission intensity in China from the perspective of spatial effects," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(3), pages 1365-1380, December.
    10. Lima, Fátima & Nunes, Manuel Lopes & Cunha, Jorge & Lucena, André F.P., 2016. "A cross-country assessment of energy-related CO2 emissions: An extended Kaya Index Decomposition Approach," Energy, Elsevier, vol. 115(P2), pages 1361-1374.
    11. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2015. "Driving factors behind carbon dioxide emissions in China: A modified production-theoretical decomposition analysis," Energy Economics, Elsevier, vol. 51(C), pages 252-260.
    12. Cansino, José M. & Sánchez-Braza, Antonio & Rodríguez-Arévalo, María L., 2015. "Driving forces of Spain׳s CO2 emissions: A LMDI decomposition approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 749-759.
    13. Fernández González, P., 2015. "Exploring energy efficiency in several European countries. An attribution analysis of the Divisia structural change index," Applied Energy, Elsevier, vol. 137(C), pages 364-374.
    14. Chen, Jiandong & Xu, Chong & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2019. "Driving factors of CO2 emissions and inequality characteristics in China: A combined decomposition approach," Energy Economics, Elsevier, vol. 78(C), pages 589-597.
    15. Zhao, Xingrong & Zhang, Xi & Shao, Shuai, 2016. "Decoupling CO2 emissions and industrial growth in China over 1993–2013: The role of investment," Energy Economics, Elsevier, vol. 60(C), pages 275-292.
    16. Du, Kerui & Xie, Chunping & Ouyang, Xiaoling, 2017. "A comparison of carbon dioxide (CO2) emission trends among provinces in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 19-25.
    17. Fernández González, P. & Presno, M.J. & Landajo, M., 2015. "Regional and sectoral attribution to percentage changes in the European Divisia carbonization index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1437-1452.
    18. Jana, Sebak Kumar & Lise, Wietze, 2023. "Carbon Emissions from Energy Use in India: Decomposition Analysis," MPRA Paper 117245, University Library of Munich, Germany.
    19. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    20. Yang Yu & Qiuyue Kong, 2017. "Analysis on the influencing factors of carbon emissions from energy consumption in China based on LMDI method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1691-1707, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:239:y:2022:i:pc:s0360544221024233. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.