IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i17p13215-d1232064.html
   My bibliography  Save this article

Research on Provincial Carbon Emission Reduction Path Based on LMDI-SD-Tapio Decoupling Model: The Case of Guizhou, China

Author

Listed:
  • Hongqiang Wang

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Wenyi Xu

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Yingjie Zhang

    (School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China)

Abstract

The successful implementation of the national carbon emissions reduction work necessitates the collaboration of various regions. Carbon emission reduction strategies need to be adjusted according to local circumstances due to the differences in regional development levels. From 2005 to 2020, carbon emissions were measured in Guizhou Province, and the contribution degree and action direction of various influencing factors were analyzed using the LMDI model. Using an SD model, we performed dynamic simulations of carbon emission trends under eight scenarios and calculated the Tapio decoupling relationship between economic growth and CO 2 emissions. According to the study, carbon emissions in Guizhou Province increased from 2005 to 2020, emphasizing the high pressure for carbon emission reduction. The industry sector ranked first in contribution, contributing 62.71% in 2020. Furthermore, this study found a weak decoupling relationship between economic growth and carbon emissions. The economic scale was the key driver driving the increase in carbon emissions, whereas the industrial fossil energy intensity was the main factor inhibiting the growth of carbon emissions. Additionally, it was predicted that carbon emissions would only peak at 277.71 million tons before 2030 if all three measures were implemented simultaneously, and a strong decoupling relationship with economic growth could be achieved as early as possible. These findings provided Guizhou Province with an effective path for reducing carbon emissions.

Suggested Citation

  • Hongqiang Wang & Wenyi Xu & Yingjie Zhang, 2023. "Research on Provincial Carbon Emission Reduction Path Based on LMDI-SD-Tapio Decoupling Model: The Case of Guizhou, China," Sustainability, MDPI, vol. 15(17), pages 1-20, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:13215-:d:1232064
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/17/13215/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/17/13215/
    Download Restriction: no
    ---><---

    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. Fang, Kai & Tang, Yiqi & Zhang, Qifeng & Song, Junnian & Wen, Qi & Sun, Huaping & Ji, Chenyang & Xu, Anqi, 2019. "Will China peak its energy-related carbon emissions by 2030? Lessons from 30 Chinese provinces," Applied Energy, Elsevier, vol. 255(C).
    3. Cai, Liya & Luo, Ji & Wang, Minghui & Guo, Jianfeng & Duan, Jinglin & Li, Jingtao & Li, Shuo & Liu, Liting & Ren, Dangpei, 2023. "Pathways for municipalities to achieve carbon emission peak and carbon neutrality: A study based on the LEAP model," Energy, Elsevier, vol. 262(PB).
    4. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    5. Wang, Shaojian & Fang, Chuanglin & Wang, Yang, 2016. "Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 505-515.
    6. Junwei Gao & Lingying Pan, 2022. "A System Dynamic Analysis of Urban Development Paths under Carbon Peaking and Carbon Neutrality Targets: A Case Study of Shanghai," Sustainability, MDPI, vol. 14(22), pages 1-27, November.
    7. Huo, Tengfei & Ma, Yuling & Xu, Linbo & Feng, Wei & Cai, Weiguang, 2022. "Carbon emissions in China's urban residential building sector through 2060: A dynamic scenario simulation," Energy, Elsevier, vol. 254(PA).
    8. Xu, Guangyue & Schwarz, Peter & Yang, Hualiu, 2019. "Determining China's CO2 emissions peak with a dynamic nonlinear artificial neural network approach and scenario analysis," Energy Policy, Elsevier, vol. 128(C), pages 752-762.
    9. Feipeng Guo & Linji Zhang & Zifan Wang & Shaobo Ji, 2022. "Research on Determining the Critical Influencing Factors of Carbon Emission Integrating GRA with an Improved STIRPAT Model: Taking the Yangtze River Delta as an Example," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    10. Kim, Yong-Gun & Yoo, Jonghyun & Oh, Wankeun, 2015. "Driving forces of rapid CO2 emissions growth: A case of Korea," Energy Policy, Elsevier, vol. 82(C), pages 144-155.
    11. Mengwan Zhang & Fengfeng Gao & Bin Huang & Bo Yin, 2022. "Provincial Carbon Emission Allocation and Efficiency in China Based on Carbon Peak Targets," Energies, MDPI, vol. 15(23), pages 1-13, December.
    12. Xu, Shi-Chun & He, Zheng-Xia & Long, Ru-Yin, 2014. "Factors that influence carbon emissions due to energy consumption in China: Decomposition analysis using LMDI," Applied Energy, Elsevier, vol. 127(C), pages 182-193.
    13. Yang, Fan & Lee, Hyoungsuk, 2022. "An innovative provincial CO2 emission quota allocation scheme for Chinese low-carbon transition," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    14. Lili Sun & Hang Yu & Qiang Liu & Yanzun Li & Lintao Li & Hua Dong & Caspar Daniel Adenutsi, 2022. "Identifying the Key Driving Factors of Carbon Emissions in ‘Belt and Road Initiative’ Countries," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    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. Ruitong Yang & Fuqiang Wang & Zhonghao Rao & Chao Shen & Dong Li, 2024. "Advancing Sustainable Energy Solutions: Innovations in Clean Energy Applications and Conventional Energy Efficiency Upgrade," Energies, MDPI, vol. 17(10), pages 1-4, May.

    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. 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).
    2. Sun, Xiaoqi & Liu, Xiaojia, 2020. "Decomposition analysis of debt’s impact on China’s energy consumption," Energy Policy, Elsevier, vol. 146(C).
    3. Mousavi, Babak & Lopez, Neil Stephen A. & Biona, Jose Bienvenido Manuel & Chiu, Anthony S.F. & Blesl, Markus, 2017. "Driving forces of Iran's CO2 emissions from energy consumption: An LMDI decomposition approach," Applied Energy, Elsevier, vol. 206(C), pages 804-814.
    4. Zhang, Lixiao & Yang, Min & Zhang, Pengpeng & Hao, Yan & Lu, Zhongming & Shi, Zhimin, 2021. "De-coal process in urban China: What can we learn from Beijing's experience?," Energy, Elsevier, vol. 230(C).
    5. Guang, Fengtao & Wen, Le & Sharp, Basil, 2022. "Energy efficiency improvements and industry transition: An analysis of China's electricity consumption," Energy, Elsevier, vol. 244(PA).
    6. Wang, Juan & Hu, Mingming & Rodrigues, João F.D., 2018. "The evolution and driving forces of industrial aggregate energy intensity in China: An extended decomposition analysis," Applied Energy, Elsevier, vol. 228(C), pages 2195-2206.
    7. Tan, Ruipeng & Lin, Boqiang, 2018. "What factors lead to the decline of energy intensity in China's energy intensive industries?," Energy Economics, Elsevier, vol. 71(C), pages 213-221.
    8. Eskander, Shaikh M.S.U. & Nitschke, Jakob, 2021. "Energy use and CO2 emissions in the UK universities: an extended Kaya identity analysis," LSE Research Online Documents on Economics 110764, London School of Economics and Political Science, LSE Library.
    9. Vélez-Henao, Johan-Andrés & Font Vivanco, David & Hernández-Riveros, Jesús-Antonio, 2019. "Technological change and the rebound effect in the STIRPAT model: A critical view," Energy Policy, Elsevier, vol. 129(C), pages 1372-1381.
    10. Jaruwan Chontanawat & Paitoon Wiboonchutikula & Atinat Buddhivanich, 2020. "Decomposition Analysis of the Carbon Emissions of the Manufacturing and Industrial Sector in Thailand," Energies, MDPI, vol. 13(4), pages 1-23, February.
    11. Linwei Ma & Chinhao Chong & Xi Zhang & Pei Liu & Weiqi Li & Zheng Li & Weidou Ni, 2018. "LMDI Decomposition of Energy-Related CO 2 Emissions Based on Energy and CO 2 Allocation Sankey Diagrams: The Method and an Application to China," Sustainability, MDPI, vol. 10(2), pages 1-37, January.
    12. Xian’en Wang & Tingyu Hu & Junnian Song & Haiyan Duan, 2022. "Tracking Key Industrial Sectors for CO 2 Mitigation through the Driving Effects: An Attribution Analysis," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
    13. Lele Xin & Junsong Jia & Wenhui Hu & Huiqing Zeng & Chundi Chen & Bo Wu, 2021. "Decomposition and Decoupling Analysis of CO 2 Emissions Based on LMDI and Two-Dimensional Decoupling Model in Gansu Province, China," IJERPH, MDPI, vol. 18(11), pages 1-20, June.
    14. Li, Hao & Zhao, Yuhuan & Qiao, Xiaoyong & Liu, Ya & Cao, Ye & Li, Yue & Wang, Song & Zhang, Zhonghua & Zhang, Yongfeng & Weng, Jianfeng, 2017. "Identifying the driving forces of national and regional CO2 emissions in China: Based on temporal and spatial decomposition analysis models," Energy Economics, Elsevier, vol. 68(C), pages 522-538.
    15. Juan Wang & Tao Zhao & Xiaohu Zhang, 2017. "Changes in carbon intensity of China’s energy-intensive industries: a combined decomposition and attribution analysis," 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 1655-1675, September.
    16. Chen, Qingjuan & Wang, Qunwei & Zhou, Dequn & Wang, Honggang, 2023. "Drivers and evolution of low-carbon development in China's transportation industry: An integrated analytical approach," Energy, Elsevier, vol. 262(PB).
    17. Jie-Fang Dong & Chun Deng & Xing-Min Wang & Xiao-Lei Zhang, 2016. "Multilevel Index Decomposition of Energy-Related Carbon Emissions and Their Decoupling from Economic Growth in Northwest China," Energies, MDPI, vol. 9(9), pages 1-17, August.
    18. Feng, Chao & Huang, Jian-Bai & Wang, Miao, 2018. "The driving forces and potential mitigation of energy-related CO2 emissions in China's metal industry," Resources Policy, Elsevier, vol. 59(C), pages 487-494.
    19. Qi, Tianyu & Weng, Yuyan & Zhang, Xiliang & He, Jiankun, 2016. "An analysis of the driving factors of energy-related CO2 emission reduction in China from 2005 to 2013," Energy Economics, Elsevier, vol. 60(C), pages 15-22.
    20. Liu, Nan & Ma, Zujun & Kang, Jidong, 2017. "A regional analysis of carbon intensities of electricity generation in China," Energy Economics, Elsevier, vol. 67(C), pages 268-277.

    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:15:y:2023:i:17:p:13215-:d:1232064. 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.