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.
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收藏
页数:13
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