Under the dual context of economic transformation and carbon peak and neutrality goals in Northeast China’s three provinces, old industrial bases in these regions are facing challenges such as fragmented green innovation resources and imbalanced cooperation, which constrain coordinated pollution and carbon reduction. This paper examines the mechanism between the urban green innovation network structure and synergistic pollution–carbon reduction efficiency in the region. Based on panel data from 34 prefecture-level cities (2013–2022), this paper employs social network analysis to characterize the green innovation network, a super-efficient SBM model to evaluate synergistic pollution–carbon reduction efficiency, and the Haken model to reveal the dynamic evolution mechanism. Results show that the green innovation network is fragmented and uneven, with significant efficiency disparities between the Central–Southern Liaoning and Harbin–Changchun urban agglomerations. A multi-core radiating network centered on Shenyang, Dalian, and Changchun has begun to form, alongside a rise in synergistic efficiency from 0.56 to 0.82. Further analysis identifies a mutually reinforcing mechanism: the green innovation network enhances synergistic efficiency mainly by increasing network density, while synergistic efficiency promotes the network by strengthening centrality. The findings provide pathways for Northeast China to achieve coordinated pollution control and carbon reduction through optimizing innovation networks.
Sun et al. (2026) studied this question.