Assessing the contribution of optimizing energy mix to China’s carbon peaking

被引:0
|
作者
Feng Wang
Huadan Han
Liang Liu
Jingfei Zhao
机构
[1] Xi’an Jiaotong University,School of Economics and Finance
[2] People’s Hospital of Ningxiang,undefined
[3] Hunan University of Chinese Medicine,undefined
关键词
Energy mix; Energy consumption; Cointegration model; Scenario analysis; Energy policy; China’s carbon peaking;
D O I
暂无
中图分类号
学科分类号
摘要
To cope with climate change, China commits that it will strive to achieve carbon peaking by 2030. Using the Cointegration model and the Markov Chain model, this paper forecasts China’s carbon emissions during 2019–2030 in six scenarios, and assesses the contribution of optimizing the energy mix to China’s carbon peaking. The research obtains three main conclusions. Firstly, optimizing the energy mix will contribute to achieving China’s carbon peaking. In the economic slow-growth scenario, taking China’s planned target of energy mix (PTEM) into account, the carbon peaking year will be brought forward from 2028 to 2023. In the economic medium-speed-growth scenario, optimizing the energy mix will make China achieve carbon peaking in 2028. Without considering the PTEM, however, the carbon emissions will not peak before 2030. In the economic fast-growth scenario, the peaking year will not occur whether considering the PTEM or not, but the growth rate of carbon emissions with the PTEM will be far lower than that without considering the PTEM. Secondly, in all three economic growth scenarios, optimizing the energy mix will largely reduce the growth rate of carbon emissions, and thus significantly reduce the peak value of carbon emissions. Thirdly, optimizing the energy mix has a negative adjusting effect on the impact of economic growth on the growth rate of carbon emissions, and the negative effect rise as the economic growth rate increases.
引用
收藏
页码:18296 / 18311
页数:15
相关论文
共 50 条
  • [31] Challenges for China's carbon emissions peaking in 2030: A decomposition and decoupling analysis
    Li, Huanan
    Qin, Quande
    JOURNAL OF CLEANER PRODUCTION, 2019, 207 : 857 - 865
  • [32] Mineral Resource Constraints for China's Clean Energy Development under Carbon Peaking and Carbon Neutrality Targets: Quantitative Evaluation and Scenario Analysis
    Luo, Xinyu
    Pan, Lingying
    Yang, Jie
    ENERGIES, 2022, 15 (19)
  • [33] China's power industry's carbon emission intensity in the context of carbon peaking and carbon neutrality: measurement and regional difference
    Xie, Pinjie
    Sun, Baolin
    Liu, Li
    Xie, Yuwen
    Yang, Fan
    Zhang, Rong
    INTERNATIONAL JOURNAL OF CLIMATE CHANGE STRATEGIES AND MANAGEMENT, 2023, 15 (02) : 264 - 281
  • [35] Research on Legal Promotion Mechanism of Biomass Energy Development under "Carbon Peaking and Carbon Neutrality" Targets in China
    Song, Dongdong
    Rui, Jing
    ENERGIES, 2023, 16 (11)
  • [36] Optimizing the Implementation of Small Modular Reactors into Ontario's Future Energy Mix
    Colterjohn, C.
    Nagasaki, S.
    Fujii, Y.
    NUCLEAR TECHNOLOGY, 2024, 210 (01) : 23 - 45
  • [37] Assessing the energy productivity of China's textile industry under carbon emission constraints
    Zhao, Hongli
    Lin, Boqiang
    JOURNAL OF CLEANER PRODUCTION, 2019, 228 : 197 - 207
  • [38] Assessing energy efficiency of natural gas in China's transition towards carbon neutrality
    Zheng, Jinhui
    Guo, Meiyu
    Lo, Kevin
    Lian, Beilei
    Chen, Yumin
    Wu, Yi
    Lin, Lijie
    ENERGY ECOLOGY AND ENVIRONMENT, 2024, 9 (06) : 614 - 630
  • [39] How robot promotes production efficiency under China's carbon peaking and carbon neutrality goals
    Yao, Weizhi
    Li, Lianshui
    Liu, Liang
    Fujii, Hidemichi
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2024,
  • [40] China's carbon emissions peaking pathway in the post-COVID-19 era
    Liu, Da
    Wang, Shengyan
    Zhao, Xudong
    Wang, Jiaying
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (45) : 100959 - 100978