Be a model for neighbour provinces: research on the spatiotemporal differences and influencing factors of energy intensity in China

被引:0
|
作者
Chen, Yinlan [1 ]
Zhuang, Guiyang [2 ]
Yang, Yang [3 ]
机构
[1] Univ Chinese Acad Social Sci, Fac Appl Econ, Beijing 102488, Peoples R China
[2] Chinese Acad Social Sci, Res Inst Ecocivilizat, Beijing 100710, Peoples R China
[3] China Three Gorges Univ, Coll Econ & Management, Yichang 443002, Peoples R China
关键词
Energy intensity; Carbon dioxide peaking and carbon neutrality; Green and low-carbon transformation; Spatial spillovers; Spatial econometric modelling; ECONOMIC-GROWTH; CONVERGENCE; DIVERSIFICATION; EMISSIONS;
D O I
10.1016/j.energy.2025.135075
中图分类号
O414.1 [热力学];
学科分类号
摘要
Significant efforts have been made by China to support and promote the United Nations Sustainable Development Goals. Reducing energy intensity, improving overall energy efficiency and completing the green and low- carbon transition of energy are inherent requirements for China's energy sustainable development. This study focuses on the energy intensity in China. The analysis is conducted at three levels, namely, national, eight comprehensive economic zones and provincial levels. A time-series analysis of China's overall energy status from 2014 to 2023 is performed, along with the calculation of energy intensity for 30 provinces. Subsequently, the spatiotemporal differences of each province and the eight comprehensive economic zones are analysed. The sigma convergence model is employed to assess the characteristics of China's long-term changes in energy intensity. Finally, the spatial regression model is used to examine the influencing factors of energy intensity and the spatial spillovers. Results show the following. (1) At the national level, across the comprehensive economic zones and at the provincial level, energy intensity in China has shown a consistent decreasing trend, indicating continuous improvement in energy utilisation efficiency. Moreover, there are obvious regional heterogeneity and echelon stratification phenomena in energy intensity. (2) Among the eight comprehensive economic zones, the energy intensity differences between provinces in the three zones exhibit a narrowing gap. The other five zones show an increasing divergence in energy intensity across provinces. (3) Positive spatial spillovers of energy intensity are observed in provincial energy intensity, suggesting that provinces may imitate each other to form a beneficial competition or cooperation. (4) Economic development level (EDL) and industrial structure change (ISC) significantly and positively influence energy utilisation efficiency. Policy implications for industrial restructuring based on regional heterogeneity and establishing regions as role models for green and low-carbon transition with positive spatial spillovers are proposed.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] The spatiotemporal evolution and influencing factors of urban green innovation in China
    Liu, Kai
    Xue, Yuting
    Chen, Zhongfei
    Miao, Yi
    SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 857
  • [42] The Spatiotemporal Variation Characteristics and Influencing Factors of Green Vegetation in China
    Zhang, Xiaodong
    Han, Haoying
    Dai, Anran
    Xie, Yianli
    FORESTS, 2024, 15 (04)
  • [43] Spatiotemporal Patterns and Influencing Factors of Agriculture Methane Emissions in China
    Wang, Guofeng
    Liu, Pu
    Hu, Jinmiao
    Zhang, Fan
    AGRICULTURE-BASEL, 2022, 12 (10):
  • [44] Spatiotemporal evolution characteristics and influencing factors of digital industry in China
    Zhang, Hong
    Li, Fengjiao
    Wei, Suqiong
    Jiang, Lili
    Xiong, Junfeng
    Zhang, Tianwei
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [45] Analysis of the spatiotemporal trends and influencing factors of Hyphantria cunea in China
    Hongwei Zhou
    Chaoqun Gong
    Xiaodong Li
    Yue Wang
    Yunbo Yan
    Journal of Forestry Research, 2024, 35 (06) : 299 - 310
  • [46] Spatiotemporal Variation and Influencing Factors of AOD in the North China Plain
    Guo L.
    Meng F.
    Ma M.-L.
    Huanjing Kexue/Environmental Science, 2022, 43 (07): : 3483 - 3493
  • [47] Analysis of the spatiotemporal trends and influencing factors of Hyphantria cunea in China
    Zhou, Hongwei
    Gong, Chaoqun
    Li, Xiaodong
    Wang, Yue
    Yan, Yunbo
    JOURNAL OF FORESTRY RESEARCH, 2024, 35 (01)
  • [48] Research on spatial and temporal differences of carbon emissions and influencing factors in eight economic regions of China based on LMDI model
    Jiang, Pan
    Gong, Xiujuan
    Yang, Yirui
    Tang, Kai
    Zhao, Yuting
    Liu, Shu
    Liu, Liang
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [49] Research on spatial and temporal differences of carbon emissions and influencing factors in eight economic regions of China based on LMDI model
    Pan Jiang
    Xiujuan Gong
    Yirui Yang
    Kai Tang
    Yuting Zhao
    Shu Liu
    Liang Liu
    Scientific Reports, 13
  • [50] Research on China's Regional Energy Efficiency Evaluation and Influencing Factors Based on the DEA-Tobit Model
    Liang, Hong Jing
    Liu, Jin Sheng
    Wang, Rong
    Song, Ya Qin
    Zhou, Yuan Yuan
    POLISH JOURNAL OF ENVIRONMENTAL STUDIES, 2020, 29 (05): : 3691 - 3701