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Synergistic Governance of Pollution and Carbon Emissions Reduction in the Yellow River Basin Urban Agglomerations: Spatiotemporal Evolution and Regional Disparities

Author

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  • Jiao Guo

    (College of Economics and Management, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Rongrong Yang

    (College of Economics and Management, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Qi Zhang

    (College of Economics and Management, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Zhen Wang

    (College of Economics and Management, Taiyuan University of Science and Technology, Taiyuan 030024, China)

Abstract

Enhancing the synergistic governance of pollution control and carbon emission reduction is essential for achieving high-quality development in the Yellow River Basin urban agglomerations. Based on the connotation of synergistic governance of pollution control and carbon emission reduction, we adopt the two-stage network SBM model to calculate the pollution and carbon emission reduction efficiency (PCRE) and synergistic governance efficiency (SGE) of 73 cities in the Yellow River Basin urban agglomerations during 2011–2023. Subsequently, the paper explores the spatiotemporal characteristics, regional disparities, and spatial evolution patterns of the two efficiencies. The results indicate that: (1) Both the PCRE and SGE present considerable fluctuations during the study period. (2) In terms of spatial characteristics, the PCRE and SGE show a spatial pattern of overall dispersion and local concentration. (3) There exist significant differences between PCRE and SGE. The PCRE shows a fluctuating trend and the interregional difference is the primary source of this disparity, while the SGE presents a steady evolutionary tendency, and the transvariation density is the significant factor contributing to the disparity. (4) The spatial analysis reveals significant positive spatial autocorrelation in PCRE. Both PCRE and SGE exhibit state persistence and path dependence in their spatial evolution, with a potential Matthew effect in some transition paths. Spatial Markov results further show that high-efficiency neighborhoods promote upward transitions in neighboring cities, whereas low-efficiency neighborhoods reinforce low-efficiency state persistence.

Suggested Citation

  • Jiao Guo & Rongrong Yang & Qi Zhang & Zhen Wang, 2026. "Synergistic Governance of Pollution and Carbon Emissions Reduction in the Yellow River Basin Urban Agglomerations: Spatiotemporal Evolution and Regional Disparities," Sustainability, MDPI, vol. 18(13), pages 1-26, July.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:13:p:6686-:d:1980928
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