黄河流域城市减污降碳协同与绿色技术创新、产业结构升级的互动关系研究

Research on the interactive relationship of pollution and carbon reduction synergy, green technological innovation, and industrial structure upgrading in Yellow River Basin cities

  • 摘要: 黄河流域作为我国生态安全与高质量发展的关键区域,其减污降碳协同效应及其与绿色技术创新、产业结构升级之间的互动机制亟待系统性分析。基于2013—2022年黄河流域53个地级城市数据,构建减污降碳耦合协调度模型,结合核密度分析、空间自相关分析与面板向量自回归(PVAR)模型,揭示减污降碳协同效应的时空演化特征,并系统剖析其与绿色技术创新、产业结构升级之间的互动关系。结果表明:黄河流域城市减污降碳协同效应整体呈上升趋势,空间呈“东高西低”格局,重心由晋中向吕梁迁移,城市间差异虽存在收敛趋势,但中下游内部分化显著,碳污协同治理效果存在周期性波动;绿色技术创新、减污降碳协同效应与产业结构升级均存在自我强化机制,其中绿色技术创新路径依赖最强;减污降碳协同效应对绿色技术创新存在滞后性抑制;产业结构升级则在碳污协同—绿色技术创新—产业结构升级三位一体系统中发挥双重驱动作用。揭示了当前黄河流域碳污协同治理中存在协同效应分异化、产业结构推动滞后与技术扩散障碍等问题,提出构建差异化协同目标体系、绿色技术创新激励机制和老工业城市绿色产业转型的建议,为推动区域绿色转型与高质量发展提供理论支撑与实证依据。

     

    Abstract: The Yellow River Basin, a critical region for China's ecological security and high-quality development, urgently requires a systematic analysis of the synergy between pollution reduction and carbon reduction (PCR) and its interaction with green technological innovation (GTI) and industrial structure upgrading (ISU). Using data from 53 prefecture-level cities in the Yellow River Basin (2013-2022), this study constructed a coupling coordination model to measure the synergy effect of PCR. It then integrated kernel density estimation, spatial autocorrelation analysis, and a panel vector autoregression (PVAR) model to reveal the spatiotemporal evolution of PCR synergy effect and systematically analyzed the interaction mechanism between PCR, GTI, and ISU. The results revealed that: (1) The PCR synergy effect exhibited an overall upward trend in cities of the Yellow River Basin, with an evident east–west gradient and a consistent spatial shift of the synergy center from Jinzhong to Lüliang. Though there was a convergence trend in the differences between cities, significant intra-regional disparities persisted in the middle and lower reaches. The synergistic governance of PCR demonstrated a cyclical pattern in its effectiveness. (2) All three subsystems (PCR, GTI, ISU) displayed strong path dependence, with GTI showing the highest inertia. (3) PCR synergy had a lagging inhibitory effect on GTI, while ISU played a dual driving role in the triadic system of "PCR, GTI, ISU". This study highlighted systemic challenges in the basin's collaborative governance, including differentiated synergistic effects, lagging industrial structural transformation, and barriers to technology diffusion. Accordingly, it proposed recommendations such as establishing a regionally differentiated PCR target system, implementing green technology innovation-driven incentive mechanisms, and fostering green industrial transition in old industrial cities, providing theoretical support and empirical evidence for promoting regional green transformation and high-quality development.

     

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