A long-standing challenge for area-based mass retrofits has been the ability to rapidly and accurately target appropriate dwellings for energy improvements. This paper demonstrates the application of a data-driven localised Geographical Information System (GIS)-based domestic energy mapping approach to create house-by-house baseline energy models and predict the potential for whole house energy retrofits in a case study of 431 dwellings in Oxford (UK). Top-down spatial datasets on energy, housing, socioeconomics and fuel poverty are combined with bottom-up energy modelling underpinned by actual dwelling details gathered through questionnaire surveys by the local community group. Multiple routes of identifying suitable dwellings were tested such as grouping dwellings with high energy use, those with high levels of fuel poverty and by common dwelling characteristics. About 300 dwellings were found to be suitable for a whole house retrofit package, equating to 89-94% mean energy reduction over baseline. While the most common dwelling typology, 1930s semi-detached had high retrofit need, it fell in area with low annual household income. The second most common dwelling typology, 1930s terrace, was dominant in areas with median level of household income. Funding programmes will need to be customised for different household segments to increase the take-up of energy retrofits.
Gupta, RajatGregg, Matt
School of Architecture
Year of publication: 2020Date of RADAR deposit: 2020-10-05