Urban Industrial Spatial Structure and Carbon Emissions

Understanding how urban spatial structure shapes carbon emissions is critical for climate mitigation and sustainable energy transition. This study examines the impact of urban industrial spatial structure on carbon emissions, using industrial agglomeration (IA) as a proxy for urban spatial organization and land-use configuration. A unified framework integrating spatial spillover effects and spatio-temporal heterogeneity is developed based on the SLX-GTWR model and applied to panel data from 285 Chinese cities. The results show that IA significantly affects carbon emissions, with total effects largely driven by spatial spillovers, highlighting the importance of inter-city linkages. Both direct and spillover effects exhibit pronounced spatio-temporal heterogeneity. Temporally, the impact follows nonlinear patterns and presents an “inverse relationship”, where local emission reductions are often offset by increases in neighboring areas. Spatially, IA increases emissions in northeast and southwest regions but reduces them in central and northwest China. Overall, optimized urban industrial spatial structure contributes to emission reductions in 125 cities. These findings demonstrate the importance of urban planning and spatial economic organization in shaping carbon emissions, and provide policy-relevant insights for climate-oriented urban planning and low-carbon energy transition.