Urban pollution–carbon coordination in China: Spatial Spillovers and non-equilibrium dynamics

Examining the temporal and spatial dynamics as well as the underlying drivers for the coordinated reduction of urban pollution and carbon emissions (PCCR) is crucial in light of the difficulties presented by global climate change. By integrating the Tapio decoupling approach with a novel synergy index, this study pioneers the use of advanced spatial econometric models, specifically ESDA, SDM, and the GTWR model, to comprehensively examine the spatiotemporal dynamics, clustering, spillover effects, and core driving forces of urban PCCR synergy in 273 Chinese cities from 2007 to 2023. This multi-method strategy enables unprecedented insight into both spatial and temporal heterogeneity in synergistic governance. The empirical analysis demonstrates several key findings: (1) The urban pollution index has exhibited a steady downward trend, with high-value regions shifting from elongated bands to more concentrated clusters. In contrast, carbon emissions have displayed a tendency toward multi-center spatial diffusion. Overall, there is a noticeable east-center-west gradient in the synergy between pollution and carbon reduction in cities, with slower development in the west, faster improvement in the east, and relative stability in the center; (2) LISA analysis reveals that High–High clusters continue to expand, Low–Low clusters spread to the central and western regions, and PCCR synergy evolves from a “single core” to a “multi-center” distribution. High–Low and Low–High clusters exhibit “island” and “lagging edge” characteristics, respectively; (3) Spatial spillover effects show that energy structure adjustments have a positive spillover effect, economic development positively influences neighboring cities, while population density and industrial structure exhibit negative spillovers or are insignificant. Natural factors primarily impact local areas; (4) The application of the GTWR model uncovers significant spatiotemporal heterogeneity among the determinants of PCCR synergy. Important variables like population density, industrial structure, and economic development show both time variations and clear regional differences, but the effects of environmental control and energy composition are always positive. Analysis of natural endowment patterns indicates a pronounced “south–north gradient,” characterized by stronger advantages in the southern regions and relative weakness in the north, as well as a distinctly polarized spatial distribution. The work offers theoretical understanding and useful recommendations for Chinese cities looking to promote green growth and create regionally coordinated government structures by elucidating these spatial heterogeneities and dynamic mechanisms. • Construct a PCCR synergy index for 273 Chinese cities. • Apply Tapio, SDM, and GTWR to capture spatiotemporal patterns. • Find synergy rising in the east with a multi-center layout. • Detect positive spillovers from energy and economic factors. • Uncover non-stationary, heterogeneous driving forces over space and time.