Drivers of China's Industrial Carbon Emissions: Evidence from Joint PDA and LMDI Approaches

被引:15
|
作者
Dong, Feng [1 ]
Gao, Xinqi [1 ]
Li, Jingyun [1 ]
Zhang, Yuanqing [1 ]
Liu, Yajie [1 ]
机构
[1] China Univ Min & Technol, Sch Management, Xuzhou 221116, Jiangsu, Peoples R China
关键词
carbon emissions; factor decomposition; LMDI; Shephard distance function; PDA; Chinese industry; STRUCTURAL DECOMPOSITION ANALYSIS; CO2; EMISSIONS; EFFICIENCY EVIDENCE; PROVINCIAL-LEVEL; ENERGY; INTENSITY; TRENDS; MODEL; PEAK; SUSTAINABILITY;
D O I
10.3390/ijerph15122712
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As the world's top carbon-emitting country, China has placed great emphasis on understanding the driving factors of carbon emissions and developing appropriate emissions reduction policies. Due to the obvious variations in carbon emissions among various industries in China, corresponding policies need to be formulated for different industries. Through data envelopment analysis, this study introduced the Shephard distance function into the logarithmic mean Divisia index (LMDI) for decomposition analysis, built a carbon emissions decomposition model of 23 industries in China during 2003-2015, and analyzed the impact of 10 factors driving carbon emissions. The main results are as follows. (1) Potential gross domestic production (GDP) is a crucial factor for increasing carbon emissions, whereas potential energy intensity and technological advances of carbon emissions have a significant inhibitory effect on carbon emissions; (2) the technological progress of energy usage and the technological advances of GDP output are manifested by inhibiting carbon emissions at the early stage of development and increasing emissions at the later stage; (3) the structure of coal-based energy consumption is difficult to change in the long term, resulting in a weak effect of energy mix on carbon emissions and an increase in carbon emissions due to the potential energy carbon intensity factor.
引用
收藏
页数:28
相关论文
共 50 条
  • [1] Do technical differences lead to a widening gap in China's regional carbon emissions efficiency? Evidence from a combination of LMDI and PDA approach
    Li, Rongrong
    Han, Xinyu
    Wang, Qiang
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2023, 182
  • [2] Drivers of industrial carbon emissions in the Yangtze River Delta region, China: A combination of decoupling and LMDI models
    Zhang, Yu
    Li, Mengxue
    Cai, Xi
    Mao, Yanying
    Jiao, Liudan
    Wu, Liu
    [J]. ENERGY SOURCES PART B-ECONOMICS PLANNING AND POLICY, 2024, 19 (01)
  • [3] A Study on the Drivers of Carbon Emissions in China's Power Industry Based on an Improved PDA Method
    Wei, Hu
    Zhan, Tian
    Yi, Zhang
    Shuo, Wang
    Yan, Li
    [J]. SYSTEMS, 2023, 11 (10):
  • [4] Carbon Emissions and Socioeconomic Drivers of Climate Change: Empirical Evidence from the Logarithmic Mean Divisia Index (LMDI) Base Model for China
    Hua, Fu
    Alharthi, Majed
    Yin, Weihua
    Saeed, Muhammad
    Ahmad, Ishtiaq
    Ali, Syed Ahtsham
    [J]. SUSTAINABILITY, 2022, 14 (04)
  • [5] When will China’s industrial carbon emissions peak? Evidence from machine learning
    Qiying Ran
    Fanbo Bu
    Asif Razzaq
    Wenfeng Ge
    Jie Peng
    Xiaodong Yang
    Yang Xu
    [J]. Environmental Science and Pollution Research, 2023, 30 : 57960 - 57974
  • [6] When will China's industrial carbon emissions peak? Evidence from machine learning
    Ran, Qiying
    Bu, Fanbo
    Razzaq, Asif
    Ge, Wenfeng
    Peng, Jie
    Yang, Xiaodong
    Xu, Yang
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (20) : 57960 - 57974
  • [7] Driving factors of carbon emissions in China’s municipalities: a LMDI approach
    Yuanxin Liu
    Yajing Jiang
    Hui Liu
    Bo Li
    Jiahai Yuan
    [J]. Environmental Science and Pollution Research, 2022, 29 : 21789 - 21802
  • [8] Driving factors of carbon emissions in China's municipalities: a LMDI approach
    Liu, Yuanxin
    Jiang, Yajing
    Liu, Hui
    Li, Bo
    Yuan, Jiahai
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (15) : 21789 - 21802
  • [9] Driving Factors of Carbon Emission Intensity for China's Planting: A Combination of LMDI and PDA
    Yang, Fuxia
    Fan, Dongshou
    Xu, Fei
    [J]. FRONTIERS IN CLIMATE, 2022, 3
  • [10] Market Integration, Industrial Structure, and Carbon Emissions: Evidence from China
    Zheng, Kun
    Deng, Hongbing
    Lyu, Kangni
    Yang, Shuang
    Cao, Yu
    [J]. ENERGIES, 2022, 15 (24)