Study on industrial carbon emissions in China based on GDIM decomposition method and two decoupling effects

被引:2
作者
Shen, Chaofeng [1 ]
Zhang, Jun [1 ]
Pang, Jianfei [2 ]
Xu, Haifeng [3 ]
机构
[1] Inner Mongolia Agr Univ, Coll Sci, Hohhot 010018, Peoples R China
[2] Acad Mil Med Sci, Beijing 100850, Peoples R China
[3] Gen Hosp Xinjiang Mil Command, Urumqi 830000, Xinjiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Carbon emission; Decoupling effect; GDIM; EKC; Chinese industry; ENVIRONMENTAL KUZNETS CURVE; CO2; EMISSIONS; ECONOMIC-DEVELOPMENT; LMDI METHOD; GROWTH; ENERGY; SECTOR; EU;
D O I
10.1007/s11356-024-32055-0
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The driving factors of China's industrial carbon emissions are decomposed by generalized Divisia index method (GDIM), so as to study the reasons for the change of China's industrial carbon emissions. The decoupling effect of China's industrial carbon emissions and economic growth is examined by speed decoupling and quantity decoupling. The speed decoupling is calculated by Tapio decoupling elasticity and emission reduction effort function, and the quantity decoupling is measured by environmental Kuznets curve (EKC). The results show that the positive driving factors are output size effect > industrial energy consumption effect > population size effect, and the negative driving factors are investment carbon emission effect > output carbon intensity effect > per capita output effect > economic efficiency effect > energy intensity effect. The elasticity of emission reduction is basically greater than that of energy conservation, indicating that there is still abundant room for efforts in emission reduction. The overall decoupling effect of carbon emissions is undecoupling-strong decoupling-undecoupling. Quadratic EKC shape is "U" shape, and the inflection point is 11.0987; the shape of cubic EKC is "N," and the inflection points are - 0.0137 and 2.4069, respectively, which satisfies the hypothesis of EKC curve.
引用
收藏
页码:15648 / 15670
页数:23
相关论文
共 38 条
[11]   The decoupling study of agricultural energy-driven CO2 emissions from agricultural sector development [J].
Hossain, M. A. ;
Chen, S. .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, 2022, 19 (05) :4509-4524
[12]   China's CO2 emissions: A systematical decomposition concurrently from multi-sectors and multi-stages since 1980 by an extended logarithmic mean divisia index [J].
Jia, Junsong ;
Xin, Lele ;
Lu, Chengfang ;
Wu, Bo ;
Zhong, Yexi .
ENERGY STRATEGY REVIEWS, 2023, 49
[13]   Multi-perspective comparisons and mitigation implications of SO2 and NOx discharges from the industrial sector of China: a decomposition analysis [J].
Jia, Junsong ;
Gong, Zhihai ;
Gu, Zhongyu ;
Chen, Chundi ;
Xie, Dongming .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2018, 25 (10) :9600-9614
[14]  
Kaya Y., 1989, Impact of Carbon Dioxide Emission Control on GNP Growth: Interpretation of Proposed Scenarios IPCC Energy and Industry Subgroup, DOI DOI 10.1371/JOURNAL.PONE.0297915
[15]  
Kuznets S, 1955, AM ECON REV, V45, P1
[16]  
Li ZG., 2019, E CHINA EC MANAG, V33, P30
[17]   Using LMDI method to analyzed the change of China's industrial CO2 emissions from final fuel use:: An empirical analysis [J].
Liu, Lan-Cui ;
Fan, Ying ;
Wu, Gang ;
Wei, Yi-Ming .
ENERGY POLICY, 2007, 35 (11) :5892-5900
[18]   Pooled mean group estimation of an environmental Kuznets curve for CO2 [J].
Martínez-Zarzoso, I ;
Bengochea-Morancho, A .
ECONOMICS LETTERS, 2004, 82 (01) :121-126
[19]  
Panayotou T, 1993, World Employment Programmer Research, V4, P2
[20]   Carbon intensity and economic development 1962-91: A brief exploration of the environmental Kuznets Curve [J].
Roberts, JT ;
Grimes, PE .
WORLD DEVELOPMENT, 1997, 25 (02) :191-198