Decoding urban emissions: the overlooked impact of commercial and public service zones across regions and seasons

Urban areas significantly contribute to global carbon emissions from energy consumption, underscoring the need to understand urban emissions for sustainable development. Investigation of urban carbon emissions in functional zones (UFZs), along with their regional and seasonal variations, has remained underexplored. Addressing the absence of unified classification standards and open datasets, this study has manually constructed a comprehensive UFZs dataset based on the OpenStreetMap (OSM) data. Focusing on China for its rich data availability, manageable analytical scope, and representativeness, we utilize nighttime light images to act as an indicator, refining the spatial detail in emission data. Employing an advanced ensemble model XGBoost, emissions and seasonal patterns on UFZs are analyzed across various cities and geographic regions. The results show that (1) Carbon emission levels exhibit substantial regional heterogeneity, with high-emission areas closely tied to economic activity and urban development rather than industrial activities. (2) Emissions stemming from commercial and public service zones surpass those from industrial zones in impact, and natural determinants such as the terrain and climatic conditions are likewise influential. (3) There is a clear seasonality in emissions on UFZs, potentially linked to changes in energy demand and consumption patterns. In conclusion, this study establishes a new UFZ dataset and reveals the regional and seasonal characteristics of urban carbon emissions, highlighting the vital role of UFZs in emissions.