Mapping Building-Based Spatiotemporal Distributions of Carbon Dioxide Emission: A Case Study in England

The spatiotemporal inventory of carbon dioxide (CO₂) emissions from the building sector is significant for formulating regional and global warming mitigation policies. Previous studies have attempted to use energy consumption models associated with field investigations to estimate CO₂ emissions from buildings at local scales, or they used spatial proxies to downscale emission sources from large geographic units to grid cells for larger scales. However, mapping the spatiotemporal distributions of CO₂ emissions on a large scale based on buildings remains challenging. Hence, we conducted a case study in England in 2015, wherein we developed linear regression models to analyze monthly CO₂ emissions at the building scale by integrating the Emissions Database for Global Atmospheric Research, building data, and Visible Infrared Imaging Radiometer Suite night-time lights images. The results showed that the proposed model that considered building data and night-time light imagery achieved the best fit. Fine-scale spatial heterogeneity was observed in the distributions of building-based CO₂ emissions compared to grid-based emission maps. In addition, we observed seasonal differences in CO₂ emissions. Specifically, buildings emitted significantly more CO₂ in winter than in summer in England. We believe our results have great potential for use in carbon neutrality policy making and climate monitoring.