Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data

被引:203
|
作者
Wang, Shaojian [1 ]
Fang, Chuanglin [2 ]
Wang, Yang [3 ]
机构
[1] Sun Yat Sen Univ, Sch Geog & Planning, Guangdong Prov Key Lab Urbanizat & Geosimulat, Guangzhou 510275, Guangdong, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
[3] Guangzhou Inst Geog, Guangzhou 510070, Guangdong, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
CO2; emissions; Spatiotemporal variations; STIRPAT model; Sys-GMM regression; China; CARBON-DIOXIDE EMISSIONS; ECONOMIC-GROWTH; REGIONAL INEQUALITY; IMPACT FACTORS; CONSUMPTION; URBANIZATION; DECOMPOSITION; POPULATION; INCOME; DETERMINANTS;
D O I
10.1016/j.rser.2015.10.140
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper examines carbon dioxide (CO2) emissions from the perspective of energy consumption, detailing an empirical investigation into the spatiotemporal variations and impact factors of energy related CO2 emissions in China. The study, which is based on a provincial panel data set for the period 1995-2011, used an extended STIRPAT model, which was in turn examined using System-Generalized Method of Moments (Sys-GMM) regression. Results indicate that while per capita CO2 emissions in China were characterized by conspicuous regional imbalances during the period studied, regional inequality and spatial autocorrelation (agglomeration) both decreased gradually between 1995 and 2011, and the pattern evolutions of emissions evidenced a clear path dependency effect. The urbanization level was found to be the most important driving impact factor of CO2 emissions, followed by economic level and industry proportion. Conversely, tertiary industry proportion constituted the main inhibiting factor among the negative influencing factors, which also included technology level, energy consumption structure, energy intensity, and tertiary industry proportion. Importantly, the study revealed that the CO2 Kuznets Curve (CKC), which describes the relation between CO2 emissions and economic growth, in fact took the form of N-shape in the medium- and long-term, rather than the classical inverted-U shape of the environmental Kuznets Curve (EKC). Specifically, an additional inflection appeared after the U-shape relationship between economic growth and CO2 emissions, indicating the emergence of a relink phase between the two variables. The findings of this study have important implications for policy makers and urban planners: alongside steps to improve the technology level, accelerate the development of tertiary industry, and boost recycling and renewable energies, the optimization of a country's energy structure that can in fact reduce reliance on fossil energy resources and constitute an effective measure to reduce CO2 emissions. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:505 / 515
页数:11
相关论文
共 50 条
  • [1] Decomposition of energy-related CO2 emissions in China: An empirical analysis based on provincial panel data of three sectors
    Wang, Miao
    Feng, Chao
    [J]. APPLIED ENERGY, 2017, 190 : 772 - 787
  • [2] Influencing Factors of Energy-Related CO2 Emissions in China: A Decomposition Analysis
    Wang, Guokui
    Chen, Xingpeng
    Zhang, Zilong
    Niu, Chaolan
    [J]. SUSTAINABILITY, 2015, 7 (10) : 14408 - 14426
  • [3] Forecasting China's Energy-Related CO2 Emissions up to 2020 Using Provincial Panel Data
    Yang, Yuan
    Zhang, Junjie
    Wang, Can
    [J]. PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON ENERGY, 2013, : 73 - 85
  • [4] Impacts of energy-related CO2 emissions in China: a spatial panel data technique
    Yan-Qing Kang
    Tao Zhao
    Peng Wu
    [J]. Natural Hazards, 2016, 81 : 405 - 421
  • [5] Impacts of energy-related CO2 emissions in China: a spatial panel data technique
    Kang, Yan-Qing
    Zhao, Tao
    Wu, Peng
    [J]. NATURAL HAZARDS, 2016, 81 (01) : 405 - 421
  • [6] Factors influencing renewable energy consumption in China: An empirical analysis based on provincial panel data
    Chen, Yulong
    [J]. JOURNAL OF CLEANER PRODUCTION, 2018, 174 : 605 - 615
  • [7] Analysis of China’s heavy industry energy-related CO2 emissions and its influencing factors: an input–output perspective
    Xiaolong Li
    Shuaiqiang Yuan
    Yang Yu
    Tangyang Jiang
    [J]. Environmental Science and Pollution Research, 2023, 30 : 33917 - 33926
  • [8] Spatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data
    Wei, Wei
    Zhang, Xueyuan
    Cao, Xiaoyan
    Zhou, Liang
    Xie, Binbin
    Zhou, Junju
    Li, Chuanhua
    [J]. ECOLOGICAL INDICATORS, 2021, 131
  • [9] Spatiotemporal Characteristics, Determinants and Scenario Analysis of CO2 Emissions in China Using Provincial Panel Data
    Wang, Shaojian
    Fang, Chuanglin
    Li, Guangdong
    [J]. PLOS ONE, 2015, 10 (09):
  • [10] Analysis of China's heavy industry energy-related CO2 emissions and its influencing factors: an input-output perspective
    Li, Xiaolong
    Yuan, Shuaiqiang
    Yu, Yang
    Jiang, Tangyang
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (12) : 33917 - 33926