Unveiling the impact of urban spatial structure on energy-related carbon emission efficiency: Evidence from the polycentric development pattern of Chinese cities

Abstract

With rapid global urbanization and energy transition, the configuration of urban spatial structure plays a pivotal role in sustainable development. However, the multidimensional nature of urban spatial structure poses significant challenges to understanding its influence on energy-related carbon emission efficiency (ECEE). This study adopts high-resolution population data to quantify the spatial configuration of Chinese cities from the perspective of polycentric development patterns. We apply the super-efficiency SBM model to evaluate ECEE by combining multidimensional indicators. Our study explores the impact characteristics and underlying mechanisms of polycentric spatial structure (PSS) on ECEE. Furthermore, the geographically and temporally weighted regression model is applied to explore the spatio-temporal heterogeneity of PSS impacts on ECEE. The findings demonstrate that a higher degree of urban polycentricity significantly enhances ECEE through industrial structure upgrading and green technological innovation. Road density exhibits a negative moderating effect on the impact of PSS on ECEE. Public transportation contributes to improving ECEE, and the effect is more pronounced in cities with a lower degree of urban polycentricity. Polycentric development pattern is more effective in enhancing ECEE in large and non-resource-based cities, while smaller and resource-dependent cities benefit more from strengthening agglomeration capacity in core areas. Spatiotemporal heterogeneity analysis further reveals that reinforcing the agglomeration effects of core functional zones in Northeast China is crucial for enhancing ECEE. Our research advances the understanding of the carbon reduction effects of urban spatial structures and provides policy insights to support sustainable urban planning.