Examining spatial variations in the relationship between domestic energy consumption and its driving factors using multiscale geographically weighted regression: a case study in Nottingham, England.

Background: Domestic energy consumption contributes to over a quarter of the UK's carbon emissions, understanding how it is driven can be helpful for delivering a fair energy transition to net zero. Energy usage is noted as a spatial phenomenon, however, the spatial variability of how it is driven is rarely considered in existing UK studies. To contribute to this research gap, this study examines the spatial variations in the relationship between domestic energy consumption and its driving factors using the local spatial statistical modelling technique Results: The study reveals domestic energy consumption is driven by factors at different spatial scales with spatially varied or even spatially heterogeneous patterns. Specifically, higher domestic energy consumption is affected differently across local areas by larger percentages of dwellings with 4 or more bedrooms, unemployment, terraced dwellings, whilst by smaller percentages of social-rented housing tenures and central heating type of district heating. The impacts of dwelling energy efficiency, median household income, percentage of households with 3 or more people, fuel poverty, and central heating with renewable energy, vary across different local areas. Therefore, while there are identifiable relationships between these factors and domestic energy consumption, they differ by locality, and aggregated level analysis may fail to accurately to capture these patterns. Conclusions: Nuanced local patterns of how domestic energy consumption is driven suggest placed-based approaches and more local deliberation to devise policies may be more suitable than "one-size-fit-all" policy plans to achieve the envisioned outcomes of rapid and fair domestic energy decarbonisation and just energy transition to net zero.