Urban agglomeration, an established urban spatial pattern, contributes to the spatial association and dependence of city-level CO₂ emission distribution while boosting regional economic growth. Exploring this spatial association and dependence is conducive to the implementation of effective and coordinated policies for regional level CO₂ reduction. This study calculated CO₂ emissions from 2005–2016 in the Chengdu-Chongqing urban agglomeration with the IPAT model, and empirically explored the spatial structure pattern and association effect of CO₂ across the area leveraged by the social network analysis. The findings revealed the following: (1) The spatial structure of CO₂ emission in the area is a complex network pattern, and in the sample period, the CO₂ emission association relations increased steadily and the network stabilization remains strengthened; (2) the centrality of the cities in this area can be categorized into three classes: Chengdu and Chongqing are defined as the first class, the second class covers Deyang, Mianyang, Yibin, and Nanchong, and the third class includes Zigong, Suining, Meishan, and Guangan—the number of cities in this class is on the rise; (3) the network is divided into four subgroups: the area around Chengdu, south Sichuan, northeast Sichuan, and west Chongqing where the spillover effect of CO₂ is greatest; and (4) the higher density of the global network of CO₂ emission considerably reduces regional emission intensity and narrows the differences among regions. Individual networks with higher centrality are also found to have lower emission intensity.