IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i9p3272-d805970.html
   My bibliography  Save this article

Simulation of China’s Carbon Emission based on Influencing Factors

Author

Listed:
  • Haojia Kong

    (School of Economics and Management, Nanjing University of Science & Technology, Nanjing 210094, China)

  • Lifan Shi

    (School of Business, Jiangsu Vocational College of Electronics and Information, Huai’an 223001, China)

  • Dan Da

    (School of Business, Jiangsu Open University, Nanjing 210000, China)

  • Zhijiang Li

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Decai Tang

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Wei Xing

    (Office of Financial Affairs, Hu’nan Moderen Logistics College, Changsha 410131, China)

Abstract

China is one of the world’s largest energy consumers and carbon emitters, and the situation of carbon emission reduction is serious. This paper forecasts the future trend of China’s carbon emissions by constructing a system dynamics model of China’s carbon emissions. The results show that China cannot fulfill its commitment to peak its carbon emissions in 2030 as scheduled. Secondly, the Logarithmic Mean Divisia Index model (LMDI) was used to analyze the influencing factors of China’s carbon emissions. The contribution rates of the five factors to China’s carbon emissions are as follows: economic development (226.30%), technological innovation (−105.92%), industrial structure (−26.55%), population scale (11.44%) and energy structure (−5.28%). Finally, this paper formulates five carbon emission reduction paths according to the size and direction of various factors that affect China’s carbon emissions. The paths of carbon emission reduction were simulated by using the system dynamics model of China’s carbon emissions. It is found that technological innovation is the key pathway for China to realize its commitment to carbon emission reduction. Slowing economic growth will delay the arrival time of peak carbon emissions and increase the intensity of carbon emissions. Optimizing the industrial structure, reducing the population scale and adjusting the energy structure can reduce the peak and carbon emissions in China, but the effect is small.

Suggested Citation

  • Haojia Kong & Lifan Shi & Dan Da & Zhijiang Li & Decai Tang & Wei Xing, 2022. "Simulation of China’s Carbon Emission based on Influencing Factors," Energies, MDPI, vol. 15(9), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3272-:d:805970
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/9/3272/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/9/3272/
    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. Decai Tang & Yan Zhang & Brandon J. Bethel, 2019. "An Analysis of Disparities and Driving Factors of Carbon Emissions in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 11(8), pages 1-13, April.
    3. Feng, Y.Y. & Chen, S.Q. & Zhang, L.X., 2013. "System dynamics modeling for urban energy consumption and CO2 emissions: A case study of Beijing, China," Ecological Modelling, Elsevier, vol. 252(C), pages 44-52.
    4. Liu, Jiaguo & Li, Sujuan & Ji, Qiang, 2021. "Regional differences and driving factors analysis of carbon emission intensity from transport sector in China," Energy, Elsevier, vol. 224(C).
    5. Homer, J.B. & Hirsch, G.B., 2006. "System dynamics modeling for public health: Background and opportunities," American Journal of Public Health, American Public Health Association, vol. 96(3), pages 452-458.
    6. Tobias, M.I. & Cavana, R.Y. & Bloomfield, A., 2010. "Application of a system dynamics model to inform investment in smoking cessation services in New Zealand," American Journal of Public Health, American Public Health Association, vol. 100(7), pages 1274-1281.
    7. Decai Tang & Tingyu Ma & Zhijiang Li & Jiexin Tang & Brandon J. Bethel, 2016. "Trend Prediction and Decomposed Driving Factors of Carbon Emissions in Jiangsu Province during 2015–2020," Sustainability, MDPI, vol. 8(10), pages 1-15, October.
    8. Inas El-Gafy, 2014. "System Dynamic Model for Crop Production, Water Footprint, and Virtual Water Nexus," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4467-4490, October.
    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. Feng Xiong & Yue Su & Jingyue Wu, 2024. "Research on the Performance Management of Carbon Reduction by Local Governments from a Game Perspective—The Case of the Zhejiang Power Restriction Incident," Sustainability, MDPI, vol. 16(6), pages 1-32, March.

    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. Ming Meng & Manyu Li, 2020. "Decomposition Analysis and Trend Prediction of CO 2 Emissions in China’s Transportation Industry," Sustainability, MDPI, vol. 12(7), pages 1-20, March.
    2. Simon K Chiu & Louise Freebairn & Louise A Baur & L. Kurt Kreuger & Adam Skinner & Jo‐An Occhipinti, 2023. "Modeling distribution parameters in system dynamics: an application in childhood obesity," System Dynamics Review, System Dynamics Society, vol. 39(2), pages 103-124, April.
    3. Negar Darabi & Niyousha Hosseinichimeh, 2020. "System dynamics modeling in health and medicine: a systematic literature review," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 29-73, January.
    4. Xingpeng Chen & Guokui Wang & Xiaojia Guo & Jinxiu Fu, 2016. "An Analysis Based on SD Model for Energy-Related CO 2 Mitigation in the Chinese Household Sector," Energies, MDPI, vol. 9(12), pages 1-18, December.
    5. Huang, Fei & Zhou, Dequn & Wang, Qunwei & Hang, Ye, 2019. "Decomposition and attribution analysis of the transport sector’s carbon dioxide intensity change in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 343-358.
    6. Lei Jin & Yuanhua Chang & Xianwei Ju & Fei Xu, 2019. "A Study on the Sustainable Development of Water, Energy, and Food in China," IJERPH, MDPI, vol. 16(19), pages 1-16, September.
    7. Ang, B.W. & Goh, Tian, 2019. "Index decomposition analysis for comparing emission scenarios: Applications and challenges," Energy Economics, Elsevier, vol. 83(C), pages 74-87.
    8. Li, Yonglin & Zuo, Zhili & Cheng, Yue & Cheng, Jinhua & Xu, Deyi, 2023. "Towards a decoupling between regional economic growth and CO2 emissions in China's mining industry: A comprehensive decomposition framework," Resources Policy, Elsevier, vol. 80(C).
    9. Zhai, Yijie & Bai, Yueyang & Wu, Zhen & Hong, Jinglan & Shen, Xiaoxu & Xie, Fei & Li, Xiangzhi, 2022. "Grain self-sufficiency versus environmental stress: An integration of system dynamics and life cycle assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    10. Xia, Yin-Shuang & Sun, Lu-Xuan & Feng, Chao, 2022. "What causes spatial inequalities of low-carbon development in China's transport sector? A newly proposed meta-frontier DEA-based decomposition approach," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    11. 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).
    12. Li, Guohao & Chen, Xue & You, Xue-yi, 2023. "System dynamics prediction and development path optimization of regional carbon emissions: A case study of Tianjin," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    13. 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.
    14. Chen, Huadun & Du, Qianxi & Huo, Tengfei & Liu, Peiran & Cai, Weiguang & Liu, Bingsheng, 2023. "Spatiotemporal patterns and driving mechanism of carbon emissions in China's urban residential building sector," Energy, Elsevier, vol. 263(PE).
    15. Guangyao Deng & Liujuan Wang & Yanan Song, 2015. "Effect of Variation of Water-Use Efficiency on Structure of Virtual Water Trade - Analysis Based on Input–Output Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2947-2965, June.
    16. 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).
    17. 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.
    18. Meimei Wang & Steffen Flessa, 2020. "Modelling Covid-19 under uncertainty: what can we expect?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(5), pages 665-668, July.
    19. Zhang, Shulin & Su, Xiaoling & Singh, Vijay P & Ayantobo, Olusola Olaitan & Xie, Juan, 2018. "Logarithmic Mean Divisia Index (LMDI) decomposition analysis of changes in agricultural water use: a case study of the middle reaches of the Heihe River basin, China," Agricultural Water Management, Elsevier, vol. 208(C), pages 422-430.
    20. 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.

    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:15:y:2022:i:9:p:3272-:d:805970. 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.