Spatial correlation network structure of carbon emission reduction capacity on urban agglomerations and its driving factors: A perspective of Sustainable Development Goals

• Published in: Sustainable cities and society Vol. 113; p. 105646
• Main Authors: Yang, Yi, Su, Xiaoyuan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.10.2024
• Subjects: Carbon emission reduction capacity; Social network analysis; Spatial correlation; Sustainable Development Goals; Urban agglomeration; Carbon emission reduction capacity; Social network analysis; Sustainable Development Goals; Urban agglomeration; Spatial correlation
• ISSN: 2210-6707
• DOI: 10.1016/j.scs.2024.105646

•Carbon emission reduction capacity evaluation system oriented towards SDGs has been constructed.•Reduction of carbon emission and environmental pollution were integrated into synergistic governance.•Spatial correlation network of carbon emission reduction capacity follows core-edge pattern.•Differences in technology level significantly affect the spatial correlation network structure.•Synergistic governance of carbon emission reduction has been promoted in line with the SDGs. Sustainable Development Goal 7 and Goal 13 are important for evaluating carbon emission reduction capacity in urban agglomerations. Exploring the spatial correlation network structures of carbon emission reduction capacity can help synergize carbon reduction actions between cities. Existing research regarding the urban agglomerations to address carbon emission reduction goals has neglected both coordination with Sustainable Development Goals and the impact of spatial correlation network structures. Based on Sustainable Development Goals, an evaluation system of carbon emission reduction capacity is constructed. The characteristics of spatial correlation network structure for carbon emission reduction capacity are described using the social network analysis method. Its driving factors are described using the quadratic assignment procedure method. The Guanzhong Plain urban agglomeration in China is used for validation. The spatial distribution of carbon emission reduction capacity in urban agglomerations is significantly unbalanced, and the spatial correlation network structure follows a stable core-edge pattern. Factors such as differences in technological level, economic level affect the formation of the spatial correlation, but the differences in urbanization level have no significant impact. Countermeasures are proposed to provide a scientific basis for the collaborative management of carbon emission reduction in urban agglomerations. [Display omitted]