Spatiotemporal analysis and drivers of urban building carbon dioxide emissions: Chongqing case study

This study addresses city-scale carbon analysis by analysing the spatiotemporal distributions of both operational and embodied carbon flows in the urban building stock and extending single-building frameworks to urban stock assessments. By way of the use of cleaned point of interest data reclassified by functional typology and integrated with geographic information system technology, we modelled the spatiotemporal distributions of operational/embodied carbon flows across Chongqing’s public facilities and residential, industrial, and transportation sectors. The framework enables multiscale analysis of emission dynamics and sectoral variations. With the Kaya identity and logarithmic mean Divisia index decomposition methods, we identified the drivers of emission trajectories. The results revealed that metropolitan areas exhibited higher population densities and increased emission levels. Public building emissions were evenly distributed district-wide, yet urban cores remained emission hotspots. Embodied carbon flows reflected operational emission patterns, which were concentrated in central zones. Decomposition analysis revealed capital investment and economic growth as the primary drivers of increased emissions, whereas technological progress and investment efficiency gains served as critical mitigation factors. A scalable methodology is proposed, and empirical insights are provided to support urban carbon management and low-carbon policy design.