Synergizing pollution control and carbon reduction in China’s Yellow River Basin: Exploring the roles of policy, technology, and structural transformation

China stated its "dual carbon" goals at the United Nations General Assembly and during subsequent key economic meetings, emphasized the continued need to combat pollution and promote synergy between pollution reduction and carbon mitigation. Accordingly, this study systematically analyzes the roles of policy, technological, and structural factors in facilitating such synergy, with specific focus on the role of land use policy in supporting this process and advancing China’s comprehensive green transition in the post-pandemic era. Using the Yellow River Basin as a case study, this research employs a dynamic stochastic general equilibrium model to explore the interactions among factors that influence pollution and carbon reduction. A theoretical framework is developed to investigate how different drivers affect synergistic effects. The findings indicate that technological factors, especially abatement technology shocks, significantly contribute to synergy, while structural factors, such as energy and industrial structures, also play key roles. Policy instruments—notably carbon taxes and environmental governance investments—further enhance synergy. Variance decomposition shows that abatement technology shocks exert the most significant impact on reducing both air pollutants and CO₂ emissions under multiple joint shock scenarios. Welfare analysis reveals that abatement technologies substantially improve social welfare, while energy price shocks produce mixed effects. Carbon taxes have limited welfare benefits, whereas environmental governance investments and industrial restructuring show negative welfare impacts. Overall, this study indicates the effectiveness of various policy interventions in optimizing resource allocation and maximizing environmental and climate benefits, offering theoretical and empirical insights to guide sustainable policy design for regional green transitions.