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Spatial context matters: Assessing how future renewable energy pathways will impact nature and society

Pathways to decarbonisation are commonly explored by government and industry through the use of energy system models. However, such models rarely consider where new energy infrastructure might be located. This is problematic as the spatial context of new renewable energy infrastructure will determine, in part, the environmental, social, and technical impacts of the energy transition. This paper presents the ADVENT-NEV model which brings together innovations in energy and natural capital modelling to identify the optimal locations of multiple renewable energy technologies at a national scale and high spatial resolution. Using Great Britain as a case study, the results show how the spatial distribution of renewable energy technologies changes when a natural capital approach is taken. In particular, the least-cost locations for onshore wind farms and bioenergy crops are highly influenced by the value of carbon sequestration, or emissions associated with their land use change. Siting using a natural capital approach produced appreciable ecosystem service benefits, such that the overall welfare gain to society was estimated at nearly £25 B. Overall, this paper demonstrates that understanding the geospatial context of the energy transition is essential to identifying which renewable energy pathways are consistent with decarbonisation and environmental objectives.
- University of California, Davis United States
- University of Southampton United Kingdom
- University of Exeter United Kingdom
- University of Aberdeen United Kingdom
- University of East Anglia United Kingdom
690
690
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).5 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
