China's carbon emissions and energy demand under different methods of global mitigation cooperation: Application of an extended RICE model with energy details

被引:6
|
作者
Zhang, Kun [1 ,2 ]
Yang, Zili [2 ,3 ]
Liang, Qiao-Mei [2 ,4 ,5 ,6 ]
Liao, Hua [2 ,4 ,5 ]
Yu, Bi-Ying [2 ,4 ,5 ]
Wei, Yi-Ming [2 ,4 ,5 ]
机构
[1] Beijing Univ Technol, Sch Econ & Management, Beijing 100124, Peoples R China
[2] Beijing Inst Technol, Ctr Energy & Environm Policy Res, Beijing 100081, Peoples R China
[3] SUNY Binghamton, Dept Econ, Dept Psychol, Binghamton, NY 13902 USA
[4] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China
[5] Beijing Key Lab Energy Econ & Environm Management, Beijing 100081, Peoples R China
[6] Beijing Inst Technol, Sch Management & Econ, 5 South Zhongguancun St, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
RICE model; Energy demand; Cooperation; Emission reduction; Climate damages; ECONOMIC-GROWTH; CLIMATE; TRANSFERS; ENTICE;
D O I
10.1016/j.energy.2023.129290
中图分类号
O414.1 [热力学];
学科分类号
摘要
This study extends the classic RICE model by introducing energy factors into the economic module and comprehensively describes different types of energy demands. Taking China as an example, we constructed the RICE-China model and further explored the impact of different cooperation methods on China's carbon emissions and energy demand. The main results are as follows. First, there are significant differences in China's emission reduction under different cooperation scenarios. In the Lindahl cooperation scenario, China's carbon emissions in 2100 have reduced by 90.5 % to achieve the two-degree goal, which is lower than the utilitarian cooperation scenario. Second, the decline in China's fossil energy under the utilitarian scenario is higher than that under the Lindal scenario. Specifically, China's fossil energy demand decreased by 91.4 % in 2100 under the Lindal scenario, with non-fossil energy accounting for 94.7 % of total energy consumption. Third, China's emission reduction in the later period under the RICE-China model is lower than that of the RICE model, and the corresponding GDP loss has also decreased. Specifically, China's GDP losses under the RICE-China model are approximately 1.5-2.8% points lower than those under the RICE model. This study provides new insights for China to participate in international climate cooperation.
引用
收藏
页数:14
相关论文
共 50 条
  • [31] RETRACTED: Level and Drivers of China's Construction Industry Energy Efficiency under Carbon Dioxide Emissions (Retracted Article)
    Xie, Yani
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2022, 2022
  • [32] China's energy Consumption, Carbon Emissions and Economic Growth Coordinated Development Evaluation Indicating System and Its Application
    Wang Enchuang
    Liu Bin
    Dai Chunyan
    2012 INTERNATIONAL CONFERENCE ON FUTURE ENERGY, ENVIRONMENT, AND MATERIALS, PT B, 2012, 16 : 1241 - 1246
  • [33] Factor Decomposition Analysis of China's Energy-Related CO2 Emissions Using Extended STIRPAT Model
    Wen, Lei
    Cao, Ye
    Weng, Jianfeng
    POLISH JOURNAL OF ENVIRONMENTAL STUDIES, 2015, 24 (05): : 2261 - 2267
  • [34] Japan's energy transition scenarios to achieve carbon neutrality under multiple energy service demand: Energy system analysis using the AIST-TIMES model
    Gonocruz, Ruth Anne
    Ozawa, Akito
    Kudoh, Yuki
    APPLIED ENERGY, 2025, 383
  • [35] Medium and long-term energy demand forecasts by sectors in China under the goal of "carbon peaking & carbon neutrality": Based on the LEAP-China model
    Li, Shanshan
    Kong, Weiling
    Wang, Yujie
    Yuan, Liang
    ENERGY, 2024, 310
  • [36] The economic benefits, energy use efficiency, and carbon footprint of fragrant super rice and nonfragrant super rice under different planting methods and nitrogen levels
    Zheng, Jiewen
    Lin, Li
    Li, Yuzhan
    Wang, Zaiman
    Tang, Xiangru
    Pan, Shenggang
    Mo, Zhaowen
    JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, 2025,
  • [37] An Empirical Study on China's Energy Supply-and-Demand Model Considering Carbon Emission Peak Constraints in 2030
    Chen, Jinhang
    ENGINEERING, 2017, 3 (04) : 512 - 517
  • [38] A neural network grey model based on dynamical system characteristics and its application in predicting carbon emissions and energy consumption in China
    He, Chenglin
    Duan, Huiming
    Liu, Yongshan
    EXPERT SYSTEMS WITH APPLICATIONS, 2025, 266
  • [39] The impacts of driving variables on energy-related carbon emissions reduction in the building sector based on an extended LMDI model: a case study in China
    Jiang, Boya
    Sun, Lin
    Zhang, Xiaoxiao
    Li, Hong Xian
    Huang, Baolin
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (59) : 124139 - 124154
  • [40] The impacts of driving variables on energy-related carbon emissions reduction in the building sector based on an extended LMDI model: a case study in China
    Boya Jiang
    Lin Sun
    Xiaoxiao Zhang
    Hong Xian Li
    Baolin Huang
    Environmental Science and Pollution Research, 2023, 30 : 124139 - 124154