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City cluster is an effective platform for encouraging regionally coordinated development. Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management, realize sustainable development, and assist China in achieving the carbon peaking and carbon neutrality goals. This paper applies the improved gravity model and social network analysis (SNA) to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the the Yangtze River Delta (YRD) city cluster in China and its influencing factors. The results demonstrate that: 1) the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure. The network association number and density show an upward trend, indicating closer spatial association between cities, but their values remain generally low. Meanwhile, the network hierarchy and network efficiency show a downward trend but remain high. 2) The spatial association network of carbon emissions in the YRD city cluster shows an obvious 'core-edge' distribution pattern. The network is centered around Shanghai, Suzhou and Wuxi, all of which play the role of 'bridges', while cities such as Zhoushan, Ma'anshan, Tongling and other cities characterized by the remote location, single transportation mode or lower economic level are positioned at the edge of the network. 3) Geographic proximity, varying levels of economic development, different industrial structures, degrees of urbanization, levels of technological innovation, energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster. Finally, policy implications are provided from four aspects: government macro-control and market mechanism guidance, structural characteristics of the 'core-edge' network, reconfiguration and optimization of the spatial layout of the YRD city cluster, and the application of advanced technologies. [ABSTRACT FROM AUTHOR]

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities. [ABSTRACT FROM AUTHOR]