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This paper uses large-scale micro data to identify key factors affecting the decision to adopt renewable energy generation (wind, solar and biomass) on farms in Scotland. We construct an integrated dataset that includes the compulsory agricultural census and farm structural survey that cover almost all farms in Scotland. In addition to farm owner demographics and farm business structures, we also assess the effect of diversification activities such as tourism and forestry, as well as the spatial, biophysical and geophysical attributes of the farms on the adoption decision. We find that diversified farms are more likely to adopt renewable energy, especially solar and biomass energy. Farms are also more likely to adopt renewable energy if they have high local demand for energy, or suitable conditions for renewable energy production. We find that biophysical factors such as the agricultural potential of farm land are important in adoption decisions. We identify adopter profiles for each type of renewable energy, and map the geographic location of potential adopters. We argue that renewable energy policy should be more integrated with farm diversification policy and farm support schemes. It should also be tailored for each type of renewable energy, for the potential adopter profiles of wind, solar and biomass energy all differ in farm characteristics and geographic distribution.

The paper presents the results of a study that developed and applied social metabolism methods to assess the sustainability of a regional economy, particularly the dynamics related to changes in the production and use of energy. The first objective of the study was to assess the feasibility of using existing secondary data sources as a basis for sub-nation state and regional analysis (with the regions in this case differentiating the area based on rurality). The second was to structure the outputs of the analysis in ways that provided comprehensive yet succinct and interpretable assessments of the balance of flows of material, energy and money that underpin the economy, with the intention that ultimately these assessments would be used to inform policymaking. The paper provides an introduction to the key concepts used within social metabolism analysis particularly the use of emergy (a measure of the cumulative environmental support provided to a social-ecological system). This is a unifying metric into which the myriad flows within an economy can be translated and combined in meaningful ways. It does so by, preserving information on both the quantity and quality of flows and so avoiding the need for arbitrary weightings. The paper presents a range of options for the use of emergy-based metrics that could be used to inform policy making. Comparisons for the years 2001 and 2010 are made at country level for Scotland and for three degrees of rurality. The analysis highlights how decisions on the share of the offshore energy sector attributed to Scotland and on the share of services (particularly those imported from beyond U.K.) have profound effects on the sustainability trajectory of the economy and the conclusions that might be drawn for policy. The paper concludes that the methods have the potential to add value to existing administrative datasets, and provide new perspectives that may be of value to policy making, but acknowledges that challenges remain in translating this potential into tangible use within policymaking.