Electricity generation contributes a large proportion of the total greenhouse gas emissions in the United Kingdom (UK), due to the predominant use of fossil fuel (coal and natural gas) combustion for this purpose. A range of future UK energy scenarios has been employed to determine their resulting environmental and carbon footprints. Methodologies have been established to calculate these footprints for the UK electricity supply industry on both a historic timescale and in accordance with the three selected scenarios. The latter scenarios, developed by the UK SUPERGEN Consortium on ‘Highly Distributed Power Systems’ (HDPS), were characterised as ‘Business As Usual’ (BAU), ‘Low Carbon’ (LC) and ‘Deep Green’ (DG) futures, and yielded possible electricity demands out to 2050. It was found that the environmental footprint of the current power network is 41 million (M) global hectares (gha). If future trends follow a ‘Business As Usual’ scenario, then this footprint is observed to fall to about 25 Mgha in 2050. The LC scenario implies an extensive penetration of micro-generators in the home to satisfy heat and power demands. However, these energy requirements are minimised by way of improved insulation of the building fabric and other demand reduction measures. In contrast, the DG scenario presupposes a network where centralised renewable energy technologies – mainly large-scale onshore and offshore wind turbines - have an important role in the power generation. However, both the LC and DG scenarios were found to lead to footprints of less than 4 Mgha by 2050. These latter two scenarios were found to give rise to quite similar trajectories over the period 2010–2050. They are therefore more likely to reflect an effective transition pathway in terms of meeting the 2050 UK CO2 reduction targets associated with decarbonisation of its power network. However, this appears unlikely to be achieved by 2030–2040 as advocated by the UK Government's advisory Committee on Climate Change in order to meet overall national carbon reduction targets.
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