Uncertainty of energy consumption and CO2 emissions in the building sector in China

被引:14
|
作者
Guo, Yangyang [1 ,2 ]
Uhde, Helena [1 ,2 ]
Wen, Wen [3 ]
机构
[1] Beijing Inst Technol, Ctr Energy & Environm Policy Res, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China
[3] Beijing Inst Technol, Sch Humanities & Social Sci, Beijing 100081, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Uncertainty; Energy consumption; Building sector; China; NET-Building model; CLIMATE-CHANGE; LONG-TERM; US BUILDINGS; EFFICIENCY; DEMAND; DECARBONIZATION; SCENARIOS; OUTLOOK; IMPACTS; POLICY;
D O I
10.1016/j.scs.2023.104728
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Uncertainty is a major concern in projecting the energy consumption and CO2 emissions from buildings with implications for the formulation of mitigation and adaptation measures. Due to multiple uncertainties, it is difficult to assess how the energy consumption of buildings in China and the associated CO2 emissions will develop in the coming decades. Aiming to give a more accurate picture of the uncertainty of the driving factors, we develop a bottom-up national energy technology model for building sector (NET-Building) to depict the evolutionary trajectories of energy consumption and CO2 emissions in China's building sector by considering the uncertainty of future evolution trends of key variables that affecting the energy consumption and CO2 emissions. The results show that China's building energy consumption and CO2 emissions will peak in 2025-2040 and 2025-2035, with peak energy consumption and CO2 emissions varying from 742-1585 Mtce and 2238-4211 Mt, respectively. Meanwhile, the electricity consumption in the building sector in China will reach 2515-7242 TWh by 2050, indicating a large variation range caused by uncertainties.
引用
收藏
页数:18
相关论文
共 50 条
  • [41] Evaluation of the relationship between energy consumption, economic growth, and CO2 emissions in China’ transport sector: the FMOLS and VECM approaches
    Zhimin Peng
    Qunqi Wu
    [J]. Environment, Development and Sustainability, 2020, 22 : 6537 - 6561
  • [42] Assessing energy consumption, CO2 and pollutant emissions and health benefits from China's transport sector through 2050
    Liu, Lei
    Wang, Ke
    Wang, Shanshan
    Zhang, Ruiqin
    Tang, Xiaoyan
    [J]. ENERGY POLICY, 2018, 116 : 382 - 396
  • [43] Is energy consumption in the transport sector hampering both economic growth and the reduction of CO2 emissions? A disaggregated energy consumption analysis
    Neves, Sonia Almeida
    Marques, Antonio Cardoso
    Fuinhas, Jose Alberto
    [J]. TRANSPORT POLICY, 2017, 59 : 64 - 70
  • [44] CO2 emissions, energy consumption, trade and income: A comparative analysis of China and India
    Jayanthakumaran, Kankesu
    Verma, Reetu
    Liu, Ying
    [J]. ENERGY POLICY, 2012, 42 : 450 - 460
  • [45] Forecasting China's CO2 Emissions for Energy Consumption Based on Cointegration Approach
    Li, Xiangmei
    Song, Yan
    Yao, Zhishuang
    Xiao, Renbin
    [J]. DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2018, 2018
  • [46] Panel estimation for urbanization, energy consumption and CO2 emissions: A regional analysis in China
    Zhang, Chuanguo
    Lin, Yan
    [J]. ENERGY POLICY, 2012, 49 : 488 - 498
  • [47] Adjusting energy consumption structure to achieve China's CO2 emissions peak
    Xu, Guangyue
    Schwarz, Peter
    Yang, Hualiu
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2020, 122
  • [48] How does administrative pricing affect energy consumption and CO2 emissions in China?
    Li, Ke
    Lin, Boqiang
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2015, 42 : 952 - 962
  • [49] China's transportation energy consumption and CO2 emissions from a global perspective
    Institute of Energy, Environment and Economy, Tsinghua University, China
    不详
    不详
    [J]. Energy Policy, (233-248):
  • [50] Chinese growth and dilemmas: modelling energy consumption, CO2 emissions and growth in China
    Ahmad N.
    Du L.
    Tian X.-L.
    Wang J.
    [J]. Quality & Quantity, 2019, 53 (1) : 315 - 338