Bottom-Up Approach to Spatial–Temporal Mapping of Urban Community-Scale Carbon Emissions: A Case Study in Guangzhou, China

This study develops a bottom-up carbon emission accounting framework at the urban community scale and applies it to 642 communities in Guangzhou, China, using the Local Climate Zone (LCZ) classification. Carbon emissions from buildings, transportation, water use, waste, and urban road lighting, together with green space carbon sinks, are quantified to establish a high-resolution spatiotemporal emission dataset. The results show that total community-scale carbon emissions range from 0 to 5852.88 tCO2, with building-related emissions dominating the carbon footprint and accounting for approximately 75% of the total emissions, followed by water use (15%) and waste (8%), while transportation and road lighting together contribute less than 3%. Building and transportation emissions exhibit pronounced temporal variability, with citywide building emissions peaking at 21:00 (994.6 tCO2 h−1). Strong spatial heterogeneity is observed across LCZ types and administrative districts. LCZ1 records the highest total emissions (60,401.71 tCO2), whereas LCZ6 exhibits substantially lower emissions due to greater green space coverage. Spatial autocorrelation analysis reveals significant clustering of high-emission communities (Global Moran’s I = 0.2486, p < 0.0001), indicating an outward diffusion of carbon emissions from central urban areas. These findings demonstrate the role of building energy use in carbon emissions and validate LCZ-based bottom-up accounting for mitigation.