Spatial Energy Footprints

Project Details

Lead Supervisor: Dr. Anne Owen (University of Leeds)
Other Supervisors: Dr. Andy Newing
Contact Email:
Partners: University of Leeds
External Partners: CallCredit

Start Date: October 2018

Deadline 3rd June 2018

It is important for the UK Government to be able to predict the future energy needs of the country to meet climate change reduction targets. Currently, the Government uses estimates of economic growth, the price of fuel and the number of households to calculate its Carbon Budget. This technique for predicting future energy needs is deficient, because it fails to take account of the fact that the major driver of industrial energy use is household demand for goods and services.

This PGR scholarship will use annual estimates of household expenditure data, provided by CallCredit, to calculate the contribution different types of households make towards the UK’s total energy needs and how this has changed over time. The project will generate a time-series dataset of household energy footprints, covering the period either side of the recession, at the census output area level. Using this fine grained spatial and temporal data it will be possible to use spatial analysis techniques (such as local indicators of spatial clustering) to discover the areas of the UK where residents contribute most and least to the UK’s energy use. Linkage with area based geodemographics will enable local benchmarking linked to underlying neighbourhood characteristics (e.g. as a result of population ageing), identification of change over time and possible explanations for the change in impact. For example, it might be possible to correlate the effect of localised retrofit schemes on the home energy footprint (drawing on localised cases studies using LIDA local government partners) or to consider the effectiveness of healthy eating plans on the food energy footprint. The recession changed the spending behaviours of different types of households – in which parts of the UK do we find households changing their consumption to an energy intensive basket of goods and where have we found pro-environment behaviours? The findings from this PGR Scholarship will provide useful insights as to the effectiveness of behaviour change policy.

The ideal candidate would be from a highly numerate background and with interests and/or experience in: consumer data analytics and/or geodemographics and neighbourhood targeting, sustainable energy policy.

Reference number LE26

Apply online here

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