Green economic recovery hindered by increased carbon intensity: Evidence from China

被引:3
|
作者
Luo, Shunjun [1 ,2 ,3 ]
Liang, Junfen [2 ,3 ]
机构
[1] Guangzhou Univ, Sch Management, Guangzhou 510006, Guangdong, Peoples R China
[2] Guangdong Acad Agr Sci, Inst Agr Econ & Informat, Guangzhou 510640, Guangdong, Peoples R China
[3] Minist Agr & Rural Affairs, Key Lab Urban Agr South China, Guangzhou 510640, Guangdong, Peoples R China
关键词
Natural resources; Green economic growth; Environmental framework; Carbon intensity; RENEWABLE ENERGY-CONSUMPTION; FINANCIAL DEVELOPMENT; CO2; EMISSIONS; GROWTH;
D O I
10.1016/j.resourpol.2023.104100
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study looks into how growing carbon intensity affects China ' s usage of non-fossil fuels and green economic recovery. We use an experimental methodology to use information from China ' s Natural Resource Growth and Miscalculation Improvement Framework from 2011 to 2022. This study examines how carbon intensity affects China ' s efforts to support a green economic rebound. We also want to clarify how non-fossil energy might help reduce carbon emissions. We find that expanding the use of non-fossil fuels and the green economic recovery are both hampered by growing carbon intensity. In particular, we find that in years with higher carbon intensity, the growth rate of non-fossil energy use is much lower. Additionally, our findings demonstrate that rising carbon intensity causes energy efficiency and carbon emissions to decline. We discover that provinces with high carbon emissions are more severely affected by the detrimental effects of increased carbon intensity on the green economic recovery. Our findings imply that for China to achieve a green economic recovery and reduce carbon emissions, carbon intensity must be addressed. Increased carbon intensity can have negative effects, but they can be lessened by policies that encourage the use of non-fossil fuels and boost energy efficiency.
引用
收藏
页数:8
相关论文
共 50 条
  • [41] Research on the impact of green finance on carbon emissions: evidence from China
    Bai, Jiancheng
    Chen, Zhonglu
    Yan, Xiang
    Zhang, Yueyan
    ECONOMIC RESEARCH-EKONOMSKA ISTRAZIVANJA, 2022, 35 (01): : 6965 - 6984
  • [42] Impact of financial agglomeration on regional green economic growth: evidence from China
    Qian, Yu
    Liu, Jun
    Forrest, Jeffrey Yi-Lin
    JOURNAL OF PLANNING LITERATURE, 2023, 38 (04) : 622 - 622
  • [43] The impact of government environmental concern on green economic efficiency: evidence from China
    Li, Lihui
    Wang, Shiyu
    Li, Jialin
    APPLIED ECONOMICS LETTERS, 2025,
  • [44] Can artificial intelligence improve green economic growth? Evidence from China
    Yu Qian
    Jun Liu
    Lifan Shi
    Jeffrey Yi-Lin Forrest
    Zhidan Yang
    Environmental Science and Pollution Research, 2023, 30 : 16418 - 16437
  • [45] How big data drives green economic development: Evidence from China
    Wang, Li
    Wu, Yuhan
    Huang, Zeyu
    Wang, Yanan
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [46] Economic growth targets and green technology innovation: mechanism and evidence from China
    Pengfei Sun
    Jia Di
    Chunhui Yuan
    Xiaolong Li
    Environmental Science and Pollution Research, 2023, 30 : 4062 - 4078
  • [47] Economic growth targets and green total factor productivity: evidence from China
    Sun, Yanlin
    Tang, Yuwei
    Li, Ge
    JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT, 2023, 66 (10) : 2090 - 2106
  • [48] Green economic development under the fiscal decentralization system: Evidence from china
    Wang, Bingbing
    Liu, Fengshuo
    Yang, Siying
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [49] Can artificial intelligence improve green economic growth? Evidence from China
    Qian, Yu
    Liu, Jun
    Shi, Lifan
    Forrest, Jeffrey Yi-Lin
    Yang, Zhidan
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (06) : 16418 - 16437
  • [50] Impact of financial agglomeration on regional green economic growth: evidence from China
    Qian, Yu
    Liu, Jun
    Forrest, Jeffrey Yi-Lin
    JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT, 2022, 65 (09) : 1611 - 1636