[Nonlinear Relationship Between Multidimensional Urbanization and Carbon Emissions and Its Driving Mechanisms].

Understanding the relationships and associated mechanisms between multidimensional urbanization and carbon emissions is essential for the coordinated development of strategies for high-quality urbanization and carbon reduction. Using panel statistical data and remote sensing imagery from cities in the Bohai Rim from 2000 to 2021， in this study， we employed spatial autocorrelation models to investigate the spatiotemporal evolution of CO₂ emissions and applied a system dynamic panel regression model to assess the nonlinear relationship and driving mechanisms between multidimensional urbanization and CO₂ emissions. From 2000 to 2021， CO₂ emissions in the Bohai Rim exhibited an upward trend， with a deceleration in growth after 2016. The CO₂ emission intensity generally declined， with fluctuations post 2019 and a transition from lower to higher emission levels among cities. Spatial agglomeration was not prominent during the study period. However， after 2016， there was a noticeable trend toward stronger correlational characteristics. Significant differences were observed in the nonlinear relationships between the various stages of urbanization subsystems in the Bohai Rim and CO₂ emissions. Economic urbanization showed an inverted "N" curve relationship with CO₂ emissions， indicative of an environmental kuznets curve （EKC） effect. When per capita GDP exceeded 89 278.41 Yuan， economic urbanization exhibited an inhibitory effect on CO₂ emissions， suggesting the importance of enhancing the comprehensive urban quality and shifting development strategies for managing emissions. The relationship between population urbanization and CO₂ emissions was confined to the left side of the inverted "U" curve， indicating that the carbon emissions inflection point had not been reached. The impact of land urbanization on CO₂ emissions mirrored that of economic urbanization， displaying a distinct inverted "N" pattern. Population size， industrial structure， foreign investment， and consumer spending levels promoted or inhibited carbon emissions. The nonlinear relationships between urbanization subsystems and carbon emissions corresponded to the theoretical predictions of EKC. The spatiotemporal heterogeneity of carbon emissions in the Bohai Rim was influenced by multidimensional and iterative interactions， feedback， integration， and reorganization among urbanization subsystems and the associated economic， social， political， ecological， and cultural factors. The Bohai Rim should focus on the coordinated advancement of high-quality urbanization and carbon reduction targets， adjust the interactions and configurations between subsystems according to local conditions， and promote precise policy implementation to harmoniously integrate economic and social development with ecological and environmental protection.