[Spatial Correlation Network Characteristics and Influencing Factors of Carbon Emission in Yangtze River Delta Urban...

Promoting the integrated development of China's urban agglomerations and realizing regional coordinated carbon reduction is an important starting point for the "dual carbon" goal. Taking 26 cities in the Yangtze River Delta urban agglomeration as research objects， this paper discusses the change trend and driving factors of carbon emission spatial correlation network from the dual perspectives of "attribute data" and "relational data" through slope trend analysis， the generalized Divisia index decomposition method （GDIM）， gravity model， social network analysis （SNA）， QAP method， and exponential random graph model （ERGM）. The results show that： ① From 2000 to 2011， the carbon emission of each city was in a rapid growth stage. From 2011 to 2021， the overall growth of carbon emissions in the Jiangsu and Zhejiang regions slowed down， and Hangzhou and Jinhua showed a downward trend. The promoting effects of per capita carbon emissions and energy consumption on carbon emissions gradually remained stable after 2010， and the promoting effects of carbon emission intensity on carbon emissions were increasing after 2010. ② Among the promoting factors of carbon emission， economic scale was the most influential factor， followed by per capita carbon emission and energy consumption. Among the limiting factors of carbon emission， carbon emission intensity was the most influential factor， followed by per capita economic scale. The promoting effects of per capita carbon emissions and energy consumption on carbon emissions gradually remained stable after 2010， and the promoting effects of carbon emission intensity on carbon emissions were increasing after 2010. In addition， population size， energy intensity， and energy consumption carbon emission intensity had little influence on carbon emission change. ③ The network level of correlation gravity intensity evolved over time. The first level gradually shifted from the eastern part of the Yangtze River Delta urban agglomeration to the central and western part. The carbon emission correlation developed toward multi-polarization and multi-direction， and the correlation intensity shifted along the gradient of economic development level. The number of network relations was increasing， the network density was increasing， and the network had strong connectivity and toughness without rigid hierarchical structure. There was obvious spatial differentiation of carbon emission "club" in the Yangtze River Delta urban agglomeration， and the plates were constantly reorganized over time. In 2021， all sectors of the Yangtze River Delta urban agglomeration showed carbon emission spillover paths of "net spillover plate ⇆ net benefit plate" and "net spillover plate ⇆ two-way spillover plate ⇆ broker sector → net benefit plate，" and the net benefit plates were mainly concentrated in the central and western parts of the Yangtze River Delta urban agglomeration， resulting in a "carbon emission refuge" effect to a certain extent. ④ From the perspective of exogenous factors， geographical adjacency， economic level difference， energy intensity difference， and economic agglomeration difference had a significant positive influence on the formation of the carbon emission spatial correlation network， while industrial structure difference had a negative influence on the formation of the carbon emission spatial correlation network. From the perspective of endogenous factors， reciprocity significantly positively affected the formation of the carbon emission spatial correlation network， and agglomeration significantly negatively affected the formation of the carbon emission spatial correlation network.