An exploration of fuel poverty in the Scottish housing market by using new forms of urban big data

Authors: Qunshan Zhao*, University of Glasgow
Topics: Spatial Analysis & Modeling, Geographic Information Science and Systems, Urban and Regional Planning
Keywords: fuel poverty, Zoopla, energy efficiency, urban data science
Session Type: Virtual Paper
Day: 4/8/2021
Start / End Time: 8:00 AM / 9:15 AM
Room: Virtual 33
Presentation File: No File Uploaded

Many homeowners and tenants are at risk of fuel poverty in the UK and all over the world. Those on low incomes are also experiencing “double deprivation” due to the low energy efficiency of their houses or rental properties. These poor thermal conditions may cause chronic health problems and threaten lives. Properties in the private rented sector and low-income neighborhood are known to have particularly significant problems with energy efficiency while the proportion of low-income households in private renting is rising rapidly.

In this research, we explored whether low-income neighborhoods experience worse energy efficiency in both the private rental market and homeowner communities. We examined if a lack of energy efficiency also increases the fuel poverty level and how we can help those on low incomes. In this analysis, we used Glasgow as an example and attempt to accurately identify the fuel poverty area within the city by using new forms of urban big data including Zoopla data hosted in Urban Big Data Centre, Scottish income data, and the Scottish energy performance certificate (EPC) data. Results from research can serve as guidance for the Scottish Government to identify “double deprivation” (low energy efficiency and low income) areas and help prioritize the fuel poverty improvement plan in the near future.

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