IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i8p3584-d1128860.html
   My bibliography  Save this article

Impacts Analysis of Dual Carbon Target on the Medium- and Long-Term Petroleum Products Demand in China

Author

Listed:
  • Li Shang

    (CAS Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Qun Shen

    (CAS Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China)

  • Xuehang Song

    (CAS Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China)

  • Weisheng Yu

    (CAS Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China)

  • Nannan Sun

    (CAS Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Wei Wei

    (CAS Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Petroleum has become a strategic resource to the national economy, and forecasting its demand is a critical step to supporting energy planning and policy-making for carbon reduction. We first conducted a characteristic analysis of end consumption for petroleum products, and the key affecting factors are identified through an extended logarithmic mean Divisia index (LMDI) method. Afterwards, the long-range energy alternatives planning system (LEAP) was adopted to predict the petroleum products demand by considering the potential impacts of different policies on the identified key factors. Through comparative analysis of three scenarios including five sub-scenarios, the findings show that the dual carbon constraints are crucial to petroleum demand control. Under the enforcement of existing carbon peaking policies, the petroleum products demand will peak around 2043 at 731.5 million tons, and the impact of energy intensity-related policies is more significant than that of activity level. However, even if the existing policy efforts are continued, supporting the carbon-neutral target will not be easy. By further strengthening the constraints, the demand will peak around 2027 at 680 million tons, and the abatement contribution will come mainly from industry (manufacturing), construction, and transportation. Additional abatement technologies are necessary for the petroleum industry to achieve carbon neutrality.

Suggested Citation

  • Li Shang & Qun Shen & Xuehang Song & Weisheng Yu & Nannan Sun & Wei Wei, 2023. "Impacts Analysis of Dual Carbon Target on the Medium- and Long-Term Petroleum Products Demand in China," Energies, MDPI, vol. 16(8), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3584-:d:1128860
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/8/3584/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/8/3584/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    2. Jiang, Shan & Zhu, Yongnan & He, Guohua & Wang, Qingming & Lu, Yajing, 2020. "Factors influencing China’s non-residential power consumption: Estimation using the Kaya–LMDI methods," Energy, Elsevier, vol. 201(C).
    3. Chen, Jiandong & Wang, Ping & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2018. "Decomposition and decoupling analysis of CO2 emissions in OECD," Applied Energy, Elsevier, vol. 231(C), pages 937-950.
    4. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    5. 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).
    6. Ren, Xiaohang & Li, Yiying & Qi, Yinshu & Duan, Kun, 2022. "Asymmetric effects of decomposed oil-price shocks on the EU carbon market dynamics," Energy, Elsevier, vol. 254(PB).
    7. Li, Guohao & Niu, Miaomiao & Xiao, Jin & Wu, Jiaqian & Li, Jinkai, 2023. "The rebound effect of decarbonization in China’s power sector under the carbon trading scheme," Energy Policy, Elsevier, vol. 177(C).
    8. Zhang, Dongyu & Liu, Gengyuan & Chen, Caocao & Zhang, Yan & Hao, Yan & Casazza, Marco, 2019. "Medium-to-long-term coupled strategies for energy efficiency and greenhouse gas emissions reduction in Beijing (China)," Energy Policy, Elsevier, vol. 127(C), pages 350-360.
    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. Wang, Zhaojing & Jiang, Qingzhe & Dong, Kangyin & Mubarik, Muhammad Shujaat & Dong, Xiucheng, 2020. "Decomposition of the US CO2 emissions and its mitigation potential: An aggregate and sectoral analysis," Energy Policy, Elsevier, vol. 147(C).
    2. Dong, Kangyin & Hochman, Gal & Timilsina, Govinda R., 2020. "Do drivers of CO2 emission growth alter overtime and by the stage of economic development?," Energy Policy, Elsevier, vol. 140(C).
    3. 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).
    4. Yang, Xue & Xu, He & Su, Bin, 2022. "Factor decomposition for global and national aggregate energy intensity change during 2000–2014," Energy, Elsevier, vol. 254(PB).
    5. Driha, Oana & Cascetta, Furio & Nardini, Sergio & Bianco, Vincenzo, 2023. "Evolution of renewable energy generation in EU27. A decomposition analysis," Renewable Energy, Elsevier, vol. 207(C), pages 348-358.
    6. Trotta, Gianluca, 2020. "Assessing energy efficiency improvements and related energy security and climate benefits in Finland: An ex post multi-sectoral decomposition analysis," Energy Economics, Elsevier, vol. 86(C).
    7. Shiraki, Hiroto & Matsumoto, Ken'ichi & Shigetomi, Yosuke & Ehara, Tomoki & Ochi, Yuki & Ogawa, Yuki, 2020. "Factors affecting CO2 emissions from private automobiles in Japan: The impact of vehicle occupancy," Applied Energy, Elsevier, vol. 259(C).
    8. Kristiana Dolge & Dagnija Blumberga, 2023. "Transitioning to Clean Energy: A Comprehensive Analysis of Renewable Electricity Generation in the EU-27," Energies, MDPI, vol. 16(18), pages 1-27, September.
    9. Baležentis, Tomas & Li, Tianxiang & Chen, Xueli, 2021. "Has agricultural labor restructuring improved agricultural labor productivity in China? A decomposition approach," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    10. 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.
    11. Isik, Mine & Ari, Izzet & Sarica, Kemal, 2021. "Challenges in the CO2 emissions of the Turkish power sector: Evidence from a two-level decomposition approach," Utilities Policy, Elsevier, vol. 70(C).
    12. Zhang, Chenjun & Wu, Yusi & Yu, Yu, 2020. "Spatial decomposition analysis of water intensity in China," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    13. Shigetomi, Yosuke & Matsumoto, Ken'ichi & Ogawa, Yuki & Shiraki, Hiroto & Yamamoto, Yuki & Ochi, Yuki & Ehara, Tomoki, 2018. "Driving forces underlying sub-national carbon dioxide emissions within the household sector and implications for the Paris Agreement targets in Japan," Applied Energy, Elsevier, vol. 228(C), pages 2321-2332.
    14. Jiandong Chen & Sishi Rong & Malin Song, 2021. "Poverty Vulnerability and Poverty Causes in Rural China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(1), pages 65-91, January.
    15. Zhao, Rongqin & Liu, Ying & Tian, Mengmeng & Ding, Minglei & Cao, Lianhai & Zhang, Zhanping & Chuai, Xiaowei & Xiao, Liangang & Yao, Lunguang, 2018. "Impacts of water and land resources exploitation on agricultural carbon emissions: The water-land-energy-carbon nexus," Land Use Policy, Elsevier, vol. 72(C), pages 480-492.
    16. Jiabin Chen & Shaobo Wen, 2020. "Implications of Energy Intensity Ratio for Carbon Dioxide Emissions in China," Sustainability, MDPI, vol. 12(17), pages 1-13, August.
    17. Bianco, V. & Proskuryakova, L. & Starodubtseva, A., 2021. "Energy inequality in the Eurasian Economic Union," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    18. Lin, Boqiang & Raza, Muhammad Yousaf, 2021. "Analysis of electricity consumption in Pakistan using index decomposition and decoupling approach," Energy, Elsevier, vol. 214(C).
    19. Chen, Jiandong & Xie, Qiaoli & Shahbaz, Muhammad & Song, Malin & Li, Li, 2022. "Impact of bilateral trade on fossil energy consumption in BRICS: An extended decomposition analysis," Economic Modelling, Elsevier, vol. 106(C).
    20. Tian Zhao & Zhixin Liu, 2022. "Drivers of CO 2 Emissions: A Debt Perspective," IJERPH, MDPI, vol. 19(3), pages 1-18, February.

    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:jeners:v:16:y:2023:i:8:p:3584-:d:1128860. 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.