China's provincial carbon emission driving factors analysis and scenario forecasting

被引:14
|
作者
Li, Siyao [1 ]
Yao, Lili [1 ]
Zhang, Yuchi [1 ]
Zhao, Yixin [1 ]
Sun, Lu [1 ]
机构
[1] Northwest A&F Univ, Coll Econ & Management, Yangling 712100, Peoples R China
关键词
Carbon emissions; LMDI model; STIRPAT model; Carbon emission forecasting; CO2; EMISSIONS; ENERGY-CONSUMPTION; PEAK; DECOMPOSITION;
D O I
10.1016/j.indic.2024.100390
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Studying the drivers of China's carbon emissions at the provincial level can clarify differences in carbon emissions due to initial resource endowments and explore pathways to achieve China's 2030 carbon peak and 2060 carbon -neutral commitments (China's 30.60 decarbonization target). In this paper, the carbon emissions of 30 provinces in China during 2000-2019 were calculated using the emission coefficient method. The LMDI model was used to investigate each province's carbon emission drivers. On this basis, the STIRPAT model is used to predict the carbon emissions of each province under three scenarios: low carbon, baseline, and high carbon. The results show that: (1) China's carbon emissions have significant regional differences, and the trend of total carbon emissions is consistent with that of per capita carbon emissions; (2) Economic development contributes the most to regional carbon emission; (3) China's carbon emission trend can be divided into four patterns: gathering type, discrete type, overlapping type, and idiotype. The results enrich the research on carbon emission drivers and forecasts, provide targeted policy recommendations for China to coordinate regional economic development, energy conservation, and carbon emission reduction, and explore a path for China to achieve the 30.60 decarbonization goal.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Research on carbon emission driving factors of China's provincial construction industry
    Shang, Mei
    Dong, Rui
    Fu, Yujie
    Hao, Wentao
    3RD INTERNATIONAL CONFERENCE ON ENERGY EQUIPMENT SCIENCE AND ENGINEERING (ICEESE 2017), 2018, 128
  • [2] On the driving factors of China’s provincial carbon emission from the view of periods and groups
    Da Liu
    Runkun Cheng
    Xinran Li
    Mengmeng Zhao
    Environmental Science and Pollution Research, 2021, 28 : 51971 - 51988
  • [3] On the driving factors of China's provincial carbon emission from the view of periods and groups
    Liu, Da
    Cheng, Runkun
    Li, Xinran
    Zhao, Mengmeng
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2021, 28 (37) : 51971 - 51988
  • [4] Driving factors of carbon embodied in China's provincial exports
    Zhang, Youguo
    Tang, Zhipeng
    ENERGY ECONOMICS, 2015, 51 : 445 - 454
  • [5] China's carbon dioxide emission and driving factors: A spatial analysis
    Yang, Yu
    Zhou, Yannan
    Poon, Jessie
    He, Ze
    JOURNAL OF CLEANER PRODUCTION, 2019, 211 : 640 - 651
  • [6] Analysis of China's carbon emission driving factors based on Kaya model
    Liu Xuezhi
    Hou Pengfei
    Qiao Yu
    Zheng Yanyan
    MANUFACTURE ENGINEERING AND ENVIRONMENT ENGINEERING, VOLS 1 AND 2, 2014, 84 : 933 - 939
  • [7] Analysis and Short-Term Peak Forecasting of the Driving Factors of Carbon Emissions in the Construction Industry at the Provincial Level in China
    Dai, Chao
    Tan, Yuan
    Cao, Shuangping
    Liao, Hong
    Pu, Jie
    Huang, Haiyan
    Cai, Weiguang
    ENERGIES, 2024, 17 (16)
  • [8] Measurement of provincial carbon emission efficiency and analysis of influencing factors in China
    Sun, Wei
    Dong, Hengye
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (13) : 38292 - 38305
  • [9] Measurement of provincial carbon emission efficiency and analysis of influencing factors in China
    Wei Sun
    Hengye Dong
    Environmental Science and Pollution Research, 2023, 30 : 38292 - 38305
  • [10] Analysis of driving factors and allocation of carbon emission allowance in China
    Yu, Ang
    Lin, Xinru
    Zhang, Yiting
    Jiang, Xia
    Peng, Lihong
    SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 673 : 74 - 82