Scenario simulations for the peak of provincial household CO2 emissions in China based on the STIRPAT model

被引:67
|
作者
Zhao, Litong [1 ]
Zhao, Tao [1 ]
Yuan, Rong [2 ]
机构
[1] Tianjin Univ, Sch Management & Econ, Tianjin 300072, Peoples R China
[2] Chongqing Univ, Sch Business Management & Econ, Chongqing 400045, Peoples R China
关键词
Household CO2 emissions; Provincial disparities; Peaking time; Scenarios; STIRPAT model; Partial least square regression; CARBON EMISSIONS; ENERGY-CONSUMPTION; IMPACT; ACHIEVE; TARGETS; DECARBONIZATION; DECOMPOSITION; POPULATION; SECTOR; TRENDS;
D O I
10.1016/j.scitotenv.2021.151098
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As household CO2 emissions (HCEs) are a key source of China's CO2 emissions, exploring the mitigation potential of HCEs is significant to achieve China's 2030 emission target. However, rare literatures analyzed the future evolution of HCEs from the provincial perspective. Here, we employ the STIRPAT model and build three scenarios (i.e., baseline, low and high scenarios) to investigate the trajectories and peak times of HCEs in 30 provinces up to 2040. The results show that 25 provinces can peak HCEs before 2030 in at least one scenario, while 5 provinces cannot achieve the 2030 emission target in any scenarios. Moreover, Guangxi and Hainan will maintain growth up to 2040 in all three scenarios. At the national level, China's household sector can achieve HCEs peak in all three scenarios. Further reduction of emission intensity helps national HCEs reach the peak around 2025 in the high scenario at 1063 MtCO(2). The findings suggest that Guangdong, Jiangsu, Hebei, Henan, Zhejiang and Anhui are key provinces for future HCEs reductions, because they account for more than 40% of national HCEs in 2040 in all three scenarios. Energy efficiency improvement and clean energy applications will be effective for emission reductions. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Prediction on the Peak of the CO2 Emissions in China Using the STIRPAT Model
    Li, Li
    Lei, Yalin
    He, Chunyan
    Wu, Sanmang
    Chen, Jiabin
    ADVANCES IN METEOROLOGY, 2016, 2016
  • [2] Research on Shanxi's CO2 Emissions Peak Based on STIRPAT Model
    Cong, Jianhui
    Kang, Wenmei
    Qin, Limei
    Zhang, Yixuan
    Wang, Xiaopei
    Liu, Qingyan
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON JUDICIAL, ADMINISTRATIVE AND HUMANITARIAN PROBLEMS OF STATE STRUCTURES AND ECONOMIC SUBJECTS (JAHP 2017), 2017, 159 : 283 - 289
  • [3] Analyses of impacts of China's CO2 emissions factors based on STIRPAT model
    Cao Qun
    Jiao Jianling
    Jin Juliang
    MANUFACTURING SCIENCE AND TECHNOLOGY, PTS 1-8, 2012, 383-390 : 3781 - +
  • [4] Scenario analysis of household energy consumption and CO2 emissions in China
    Ning, Yadong
    Zhang, Chunbo
    Ding, Tao
    ADVANCES IN ENERGY SCIENCE AND EQUIPMENT ENGINEERING, 2015, : 1203 - 1207
  • [5] Using STIRPAT Model to Analyze Impact Factors on CO2 Emissions of China
    Wang, Jianjun
    Li, Li
    INTERNATIONAL JOINT CONFERENCE ON APPLIED MATHEMATICS, STATISTICS AND PUBLIC ADMINISTRATION (AMSPA 2014), 2014, : 1 - 5
  • [6] CO2 emissions from household consumption at the provincial level and interprovincial transfer in China
    Wu, Sanmang
    Lei, Yalin
    Li, Shantong
    JOURNAL OF CLEANER PRODUCTION, 2019, 210 : 93 - 104
  • [7] Analysis on influence factors of China's CO2 emissions based on Path-STIRPAT model
    Li, Huanan
    Mu, Hailin
    Zhang, Ming
    Li, Nan
    ENERGY POLICY, 2011, 39 (11) : 6906 - 6911
  • [8] Exploring the driving forces and scenario analysis for China?s provincial peaks of CO2 emissions
    Zhu, Bangzhu
    Zhang, Yulin
    Zhang, Mengfan
    He, Kaijian
    Wang, Ping
    JOURNAL OF CLEANER PRODUCTION, 2022, 378
  • [9] The determinants of CO2 emissions in Brazil: The application of the STIRPAT model
    Somoye, Oluwatoyin Abidemi
    Ozdeser, Huseyin
    Seraj, Mehdi
    Turuc, Fatma
    ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, 2023, 45 (04) : 10843 - 10854
  • [10] Spatial effect of factors affecting household CO2 emissions at the provincial level in China: a geographically weighted regression model
    Wang, Yanan
    Zhao, Minjuan
    Chen, Wei
    CARBON MANAGEMENT, 2018, 9 (02) : 187 - 200