Disaggregating energy demand reductions across income groups in UK Low Energy Scenarios: insights from the residential and transport sectors

Extended abstract 2-079-26

As indicated by the proliferation of low energy demand climate mitigation scenarios in the literature, national and international climate ambitions are not likely to be achieved without significant action to reduce GHG emissions through energy demand reduction. While demand-led pathways unlock significant ecological and social benefits left unrealised by many technologically focused scenarios, there are legitimate concerns as to the changes aggregate reductions in final energy demand entail for different household types, particularly those currently unable to consume to a level required to live a good life. At present, detailed exploration of this problem is omitted by mitigation scenario modelling studies. Scenarios calculate aggregate energy demand at their respective geographical scales, and thus, per-capita level energy use can be calculated. However, there are few attempts to disaggregate this further, to unpick the implications of demand reduction for the energy service demand levels of different groups within society.

This study aims to quantify how much change in energy service demands are implied by the reductions in aggregate final energy demand within the UK’s Positive Low Energy Future scenarios. Exploring energy service demands in the mobility and shelter categories, we find significant inequality in the implied action required by different income groups. Without changing the relative inequality in service demands, higher income groups responsible for disproportionate levels of the demand reduction achieved in the PLEF scenarios. Disaggregating these changes leads to relevant policy evidence, highlighting the sections of the income distribution that require targeted policy, if the aggregate demand reductions are to be successfully achieved. We conclude by evaluating current energy demand reduction strategies from modelling studies and the wider literature, to understand their effectiveness for targeting those with the greatest responsibility for demand reduction.

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