Spatio-temporal effects of regional resilience construction on carbon emissions: Evidence from 30 Chinese provinces

被引:18
|
作者
Xu, Shan [1 ]
Wang, Xinran [1 ]
Zhu, Ruiguang [1 ]
Wang, Ding [1 ]
机构
[1] Yanshan Univ, Sch Civil Engn & Mech, Qinhuangdao 066004, Peoples R China
关键词
Regional resilience construction; Carbon emissions; Coupling model; Geographically and temporally weighted; regression model (GTWR); K; -means; WEIGHTED REGRESSION; CO2; EMISSIONS; CITY; SUSTAINABILITY; CLASSIFICATION; TARGETS; CITIES;
D O I
10.1016/j.scitotenv.2023.164109
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In response to the threat of rapidly rising carbon emissions, a variety of measures are being implemented to achieve carbon reduction. Resilience construction offers a fresh approach to improving the regional anti-interference ability to cope with various risks, and it is worth considering its impact on carbon emissions. The objective of this study is to investigate the spatio-temporal impacts of resilience construction (RCI) on carbon intensity (CI) in 30 Chinese provinces from 2010 to 2019. The relation pattern between RCI and CI is thoroughly examined after developing a hybrid model by integrating gray correlation analysis (GRA) and coupled coordination degree (CCD). Using the GTWR model, the coefficients reveal the spatio-temporal pattern of the influence of each variable on CI. Furthermore, this study pioneeringly blends GTWR regression results with the K-Means approach to identify areas with homogeneity and heterogeneity of the pattern. Firstly, the findings indicate that there is a significant link between CI and all dimensions -economic resilience (RE), social resilience (RS), and ecological resilience (REn). The relation between REn and CI is the greatest, although it has been declining recently while relations of RS, REn, and CI have all been steadily rising. Secondly, according to the results of CCD, resilience construction and carbon reduction are progressively reaching orderly development but there are still some provinces at low levels of CCD. Thirdly, the study area is divided into four clusters, and the structure of spatial grouping tends to become stable. Moreover, we analyze each cluster's features and suggest appropriate policy measures. The findings aid in the scientific planning of the direction of resilience construction with the goal of collaborative management of carbon emissions.
引用
收藏
页数:13
相关论文
共 50 条
  • [21] Spatialization and Spatio-temporal Dynamics of Energy Consumption Carbon Emissions in China
    Hao R.-J.
    Wei W.
    Liu C.-F.
    Xie B.-B.
    Du H.-B.
    Huanjing Kexue/Environmental Science, 2022, 43 (11): : 5305 - 5314
  • [22] Spatio-Temporal Pattern of Carbon Emissions and Response Strategies in Wuhan Region
    Zhan Qingming
    Zhao Xinyue
    Tang Lujia
    Li Xuan
    Li Min
    China City Planning Review, 2024, 33 (02) : 53 - 64
  • [23] Impact of Financial Inclusion on the Efficiency of Carbon Emissions: Evidence from 30 Provinces in China
    Zhang, Xu
    Sun, Huaping
    Wang, Taohong
    ENERGIES, 2022, 15 (19)
  • [24] Spatio-temporal Evolution and Influencing Factors of Carbon Emissions in Shaanxi Province
    Chen, Yi
    Ling, Li
    Gu, Zhen-Wei
    Zhang, Yu
    Liu, Jing
    Zhongguo Huanjing Kexue/China Environmental Science, 2024, 44 (04): : 1826 - 1839
  • [25] Spatio-temporal impulse effect of foreign direct investment on intra- and inter-regional carbon emissions
    Pan, Xiongfeng
    Wang, Yuqing
    Tian, Mengyuan
    Feng, Shenghan
    Ai, Bowei
    ENERGY, 2023, 262
  • [26] Digital Economy, Entrepreneurship of Small and Medium-Sized Manufacturing Enterprises, and Regional Carbon Emissions: Evidence from Chinese Provinces
    Tan, Juan
    Liu, Rui
    Lu, Jianle
    Tan, Qiong
    SUSTAINABILITY, 2025, 17 (05)
  • [27] Estimation and Spatio-temporal Patterns of Carbon Emissions from Grassland Fires in Inner Mongolia, China
    Yu Shan
    Jiang Li
    Du Wala
    Zhao Jianjun
    Zhang Hongyan
    Zhang Qiaofeng
    Liu Huijuan
    CHINESE GEOGRAPHICAL SCIENCE, 2020, 30 (04) : 572 - 587
  • [28] Estimation and Spatio-temporal Patterns of Carbon Emissions from Grassland Fires in Inner Mongolia, China
    YU Shan
    JIANG Li
    DU Wala
    ZHAO Jianjun
    ZHANG Hongyan
    ZHANG Qiaofeng
    LIU Huijuan
    Chinese Geographical Science, 2020, 30 (04) : 572 - 587
  • [29] Estimation and Spatio-temporal Patterns of Carbon Emissions from Grassland Fires in Inner Mongolia, China
    Shan Yu
    Li Jiang
    Wala Du
    Jianjun Zhao
    Hongyan Zhang
    Qiaofeng Zhang
    Huijuan Liu
    Chinese Geographical Science, 2020, 30 : 572 - 587
  • [30] Spatio-Temporal Differentiation of Carbon Emissions Efficiency and Influencing Factors: From the Perspective of 136 Countries
    Ma, Dalai
    Xiao, Yaping
    Zhang, Fengtai
    Zhao, Na
    Wang, Ling
    Guo, Zuman
    Zhang, Jiawei
    An, Bitan
    Xiao, Yuedong
    SSRN, 2022,