IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i13p5811-d1431096.html
   My bibliography  Save this article

Decomposition Analysis of Carbon Emission Drivers and Peaking Pathways for Key Sectors under China’s Dual Carbon Goals: A Case Study of Jiangxi Province, China

Author

Listed:
  • Xinjie Jiang

    (School of Economics and Management, Nanchang Hangkong University, Nanchang 330063, China)

  • Fengjun Xie

    (School of Economics and Management, Nanchang Hangkong University, Nanchang 330063, China
    Institute of Civil-Military Integration and Aviation Development, Nanchang Hangkong University, Nanchang 330063, China
    Jiangxi Regional Economy and Competitiveness Research Center, Nanchang Hangkong University, Nanchang 330063, China)

Abstract

Clarifying the factors influencing CO 2 emissions and their peaking pathways in major sectors holds significant practical importance for achieving regional dual-carbon goals. This paper takes Jiangxi, a less developed demonstration zone in central China, as an example. It pioneeringly combines the LMDI method, Tapio decoupling model, and LEAP model to multi-dimensionally analyze the driving mechanisms, evolution patterns, and dynamic relationships with the economic development of carbon emissions in Jiangxi’s key sectors from 2007 to 2021. It also explores the future carbon emission trends and peaking potentials of various sectors under different scenarios. Our results show that (1) Carbon emissions in various sectors in Jiangxi have continued to grow over the past fifteen years, and although some sectors have seen a slowdown in emission growth, most still rely on traditional fossil fuels; (2) Economic growth and industrial structure effects are the main drivers of carbon emission increases, with a general trend towards decoupling achieved across sectors, while agriculture, forestry, animal husbandry and fishery, and ferrous metal smelting have shown a decline in their decoupling status; (3) In the carbon reduction and low-carbon scenarios, the carbon emission peaks in Jiangxi are estimated to be 227.5 Mt and 216.4 Mt, respectively, and targeted strategies for high-emission industries will facilitate a phased peak across sectors and enhance emissions reduction benefits. This has significant reference value for the central region and even globally in formulating differentiated, phased, sector-specific carbon peaking plans, and exploring pathways for high-quality economic development in tandem with ecological civilization construction.

Suggested Citation

  • Xinjie Jiang & Fengjun Xie, 2024. "Decomposition Analysis of Carbon Emission Drivers and Peaking Pathways for Key Sectors under China’s Dual Carbon Goals: A Case Study of Jiangxi Province, China," Sustainability, MDPI, vol. 16(13), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:13:p:5811-:d:1431096
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/13/5811/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/13/5811/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Gene M. Grossman & Alan B. Krueger, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 353-377.
    3. Kumar, Amit & Bhattacharya, S.C & Pham, H.L, 2003. "Greenhouse gas mitigation potential of biomass energy technologies in Vietnam using the long range energy alternative planning system model," Energy, Elsevier, vol. 28(7), pages 627-654.
    4. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    Full references (including those not matched with items on IDEAS)

    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. Li-Jing Liu & Qiao-Mei Liang & Felix Creutzig & Nan Cheng & Lan-Cui Liu, 2021. "Electricity end-use and construction activity are key leverage points for co-controlling greenhouse gases and local pollution in China," Climatic Change, Springer, vol. 167(1), pages 1-22, July.
    2. Wang, Enci & Su, Bin & Zhong, Sheng & Guo, Qinxin, 2022. "China's Embodied SO2 Emissions and Aggregate Embodied SO2 Intensities in Interprovincial and International Trade," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    3. Duan, Yuwan & Jiang, Xuemei, 2017. "Temporal Change of China's Pollution Terms of Trade and its Determinants," Ecological Economics, Elsevier, vol. 132(C), pages 31-44.
    4. Cohen, Gail & Jalles, Joao Tovar & Loungani, Prakash & Marto, Ricardo & Wang, Gewei, 2019. "Decoupling of emissions and GDP: Evidence from aggregate and provincial Chinese data," Energy Economics, Elsevier, vol. 77(C), pages 105-118.
    5. Kenichi Shimamoto, 2017. "Decomposition analysis of the pollution intensities in the case of the United Kingdom," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1316553-131, January.
    6. Rao, Guangming & Liao, Jiao & Zhu, Yanping & Guo, Lin, 2022. "Decoupling of economic growth from CO2 emissions in Yangtze River Economic Belt sectors: A sectoral correlation effects perspective," Applied Energy, Elsevier, vol. 307(C).
    7. Wang, Jing & Rickman, Dan S. & Yu, Yihua, 2022. "Dynamics between global value chain participation, CO2 emissions, and economic growth: Evidence from a panel vector autoregression model," Energy Economics, Elsevier, vol. 109(C).
    8. Nishijima, Daisuke, 2017. "The role of technology, product lifetime, and energy efficiency in climate mitigation: A case study of air conditioners in Japan," Energy Policy, Elsevier, vol. 104(C), pages 340-347.
    9. Shigemi Kagawa & Yuriko Goto & Sangwon Suh & Keisuke Nansai & Yuki Kudoh, 2012. "Accounting for Changes in Automobile Gasoline Consumption in Japan: 2000–2007," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 1(1), pages 1-27, December.
    10. Shi, Changfeng & Zhi, Jiaqi & Yao, Xiao & Zhang, Hong & Yu, Yue & Zeng, Qingshun & Li, Luji & Zhang, Yuxi, 2023. "How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning," Energy, Elsevier, vol. 269(C).
    11. Xie, Rui & Wang, Fangfang & Chevallier, Julien & Zhu, Bangzhu & Zhao, Guomei, 2018. "Supply-side structural effects of air pollutant emissions in China: A comparative analysis," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 89-95.
    12. Löschel, Andreas & Pothen, Frank & Schymura, Michael, 2015. "Peeling the onion: Analyzing aggregate, national and sectoral energy intensity in the European Union," Energy Economics, Elsevier, vol. 52(S1), pages 63-75.
    13. Zaim, Osman & Uygurtürk Gazel, Tuğçe & Akkemik, K. Ali, 2017. "Measuring energy intensity in Japan: A new method," European Journal of Operational Research, Elsevier, vol. 258(2), pages 778-789.
    14. Zhu, Bangzhu & Su, Bin & Li, Yingzhu & Ng, Tsan Sheng, 2020. "Embodied energy and intensity in China’s (normal and processing) exports and their driving forces, 2005-2015," Energy Economics, Elsevier, vol. 91(C).
    15. Wang, Jianda & Yang, Senmiao & Dong, Kangyin & Nepal, Rabindra, 2024. "Assessing embodied carbon emission and its drivers in China's ICT sector: Multi-regional input-output and structural decomposition analysis," Energy Policy, Elsevier, vol. 186(C).
    16. Ling Yang & Michael L. Lahr, 2019. "The Drivers of China’s Regional Carbon Emission Change—A Structural Decomposition Analysis from 1997 to 2007," Sustainability, MDPI, vol. 11(12), pages 1-18, June.
    17. Wang, Miao & Feng, Chao, 2017. "Analysis of energy-related CO2 emissions in China’s mining industry: Evidence and policy implications," Resources Policy, Elsevier, vol. 53(C), pages 77-87.
    18. Yulei Xie & Ling Ji & Beibei Zhang & Gordon Huang, 2018. "Evolution of the Scientific Literature on Input–Output Analysis: A Bibliometric Analysis of 1990–2017," Sustainability, MDPI, vol. 10(9), pages 1-17, September.
    19. Daniel Croner & Ivan Frankovic, 2018. "A Structural Decomposition Analysis of Global and NationalEnergy Intensity Trends," The Energy Journal, , vol. 39(2), pages 103-122, March.
    20. Lach, Łukasz, 2022. "Optimization based structural decomposition analysis as a tool for supporting environmental policymaking," Energy Economics, Elsevier, vol. 115(C).

    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:gam:jsusta:v:16:y:2024:i:13:p:5811-:d:1431096. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.