Central nodes and polycentricity at the micro-scale: Evaluating carbon emissions across Beijing’s subdistricts

This study aims to clarify the impact mechanisms of urban polycentric spatial structures on carbon emissions within micro-planning frameworks. This paper presents new insights into the implementation of carbon-neutrality strategies from two perspectives of urban structure spatial within micro-granular urban subdistricts: “central nodes” and “polycentricity.” Utilizing spatial data from night-time lights, Open-source Data Inventory for Anthropogenic CO₂ (ODIAC), and China Land Cover Dataset (CLCD), this study adopts a dual perspective of a “dispersed structure layout—concentrated development” model. Initially, it employs a spatial autocorrelation model to depict the urban internal spatial structure and variations in spatial carbon emissions from the perspective of spatial heterogeneity. Subsequently, the spatial Durbin model is used to empirically examine the effects of the evolution of urban spatial multicentric structures on carbon emissions. The findings indicate that from the perspective of polycentricity, both functional polycentricity with multiple high-economic impact centers and the dispersion of urban construction land under morphological polycentricity lead to increased carbon emissions. From the perspective of central nodes, the polycentric development model, characterized by low centralization and high concentration, is more conducive to carbon neutrality. Last, compared to the monocentric model of low centralization and high concentration in urban areas, the “lightweight” dispersed polycentric model in ecological regions helps to minimize urban expansion, thereby mitigating the impact on carbon emissions.