Relationships Between Urban Green Innovation Network Structure Characteristics and Synergistic Efficiency of Pollution and Carbon Emission Reduction in Three Provinces in Northeastern China

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.

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Publication Details

Journal
Sustainability
Published
2026-02-01
DOI
https://doi.org/10.3390/su18031438
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
0.00
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Relationships Between Urban Green Innovation Network Structure Characteristics and Synergistic Efficiency of Pollution and Carbon Emission Reduction in Three Provinces in Northeastern China

Junyang Sun, Xiuting Cai, Qian Zhao
Sustainability
Energy, Environment, Economic Growth
article

Relationships Between Urban Green Innovation Network Structure Characteristics and Synergistic Efficiency of Pollution and Carbon Emission Reduction in Three Provinces in Northeastern China

Junyang Sun, Xiuting Cai, Qian Zhao
article en

Abstract

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.

SustainabilityVol. 18(3)
Northeast Forestry University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 76%
Energy, Environment, Economic Growth
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