• Energy Research
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Adoption of new technologies necessitates changes in behaviours, attitudes, and social norms that cannot be sufficiently explained by a single predictor or group of predictors, particularly in heterogeneous populations. Aiming to add a greater understanding of intention to adopt Rooftop Photovoltaic (PV), this paper utilised an established population segmentation tool, the Sinus-Milieus and the Theory of Planned Behaviour (TPB) to account for population heterogeneity of the sample of German homeowners (n = 1800). By employing partial least squares structural equation modelling, we confirmed that attitudes, social norms, and financial evaluation significantly influence adoption intention at the population level. A multi-group analysis revealed noteworthy variations in the relative impact of attitudes and social norms on adoption intention across different milieugroups. Notably, even milieugroups sharing the same broad social status and/or values, as defined by the Sinus-Milieu tool, exhibited significant differences in the influence of attitudes and social norms on adoption intention. Moreover, a Kruskal–Wallis H-test indicated significant differences in the reported level of adoption intention among milieugroups, with the Leading milieus showing the highest intention and the Deprived the lowest. Differences were also observed for the determinants of social norms, attitudes, environmental concern, and novelty-seeking behaviour. Our findings confirm the relevance of considering potential adopters as a heterogeneous group in terms of overall lifestyle characteristics. Tailoring communication strategies to target the underlying motivations of specific milieus can lead to more effective interventions.

Alongside environmental benefits, renewable energy deployment is often evaluated on grounds of regional development. Focusing on wave energy deployment in Ireland, this paper quantifies employment‐related welfare change net of associated subsidy costs. Although the added employment reduces inter‐regional inequality, certain subsidies increase total income inequality by a greater extent. Total inequality increases by 0.25% in the preferred scenario. This pattern of incidence persists under an optimistic scenario where all manufacturing activity is carried out locally. This finding highlights that policies of regional development should consider the spatial distribution of associated subsidy costs. Ademas de los beneficios ambientales, el despliegue de energias renovables suele evaluarse en funcion del desarrollo regional. Centrandose en la captacion de la energia procedente de las olas en Irlanda, este articulo cuantifica el cambio de bienestar relacionado con el empleo, una vez descontados los costos asociados de los subsidios. Si bien el empleo anadido reduce la desigualdad interregional, ciertos subsidios aumentan en mayor medida la desigualdad total de los ingresos. La desigualdad total aumenta en un 0,25% en el escenario preferido. Esta pauta de incidencia persiste en un escenario optimista en el que toda la actividad manufacturera se lleva a cabo localmente. Este hallazgo pone de relieve que las politicas de desarrollo regional deberian considerar la distribucion espacial de los costos asociados de los subsidios. 再生可能エネルギーの導入は、環境保全の評価とともに、地域開発の観点から評価されることが多い。本稿では、アイルランドの波浪エネルギーの導入に注目し、関連する補助金コストを差し引いた雇用関連の福祉の変化を定量化する。雇用の増加は地域間の不平等を減少させるものの、特定の補助金は所得の不平等を大幅に拡大させる。希望的なシナリオでは、不平等は全体で0.25%拡大する。この発生パターンは、すべての製造活動が地域において行われるという楽観的シナリオの下で持続するものである。この知見から、地域開発政策は関連する補助金の空間的分布を考慮したものであるべきことが強調される。

Abstract Using micro-simulation modelling techniques this paper examines methane emissions across Irish farms. The effects of a carbon equivalent tax on average family farm income are analysed at both the farm and regional level. The spatial micro-simulation model developed uses a technique called simulated annealing to match the Irish Census of Agriculture data to a National Farm Survey. The main advantage of the spatial micro-simulation approach is the fact that it allows one to account for the heterogeneity in the farm population across space. The results of the modelling process are presented using GIS mapping techniques and highlight the fact that there would be significant regional variation in the burden of an agricultural tax that was based on a rate per unit of methane emissions. The results also demonstrate that if the methane tax revenue raised was redistributed in the form of an environmental subsidy to farmers participating in an agri-environmental scheme (the Rural Environment Protection Scheme (REPS)) it would encourage farmers to participate in the scheme and could also have the effect of moving low income farms up the earnings distribution ladder.

Wave Energy Conversion (WEC) devices are at a pre-commercial stage of development with feasibility studies sensitive to uncertainties surrounding assumed input costs. This may affect decision making. This paper analyses the impact these uncertainties may have on investor, developer and policymaker decisions using an Irish case study. Calibrated to data present in the literature, a probabilistic methodology is shown to be an effective means to carry this out. Value at Risk (VaR) and Conditional Value at Risk (CVaR) metrics are used to quantify the certainty of achieving a given cost or return on investment. We analyse the certainty of financial return provided by the proposed Irish Feed-in Tariff (FiT) policy. The influence of cost reduction through bulk discount is also discussed, with cost reduction targets for developers identified. Uncertainty is found to have a greater impact on the profitability of smaller installations and those subject to lower rates of cost reduction. This paper emphasises that a premium is required to account for cost uncertainty when setting FiT rates. By quantifying uncertainty, a means to specify an efficient premium is presented.

Linking novel real-time sensor data with comprehensive individual baseline survey data, this study estimates the effect of fuel poverty on the physical and mental health of social housing tenants in the southwest of the UK. Structural equation modeling is applied to show that fuel poverty has a significant negative effect on mental health. Other socio-economic characteristics (such as age, household size) and house characteristics (e.g., energy-efficient rating, house type) are associated with fuel poverty. Fuel poverty is also related to poorer mobility. Our results suggest that special attention should be paid to tenants with disabilities and chronic diseases since they are more vulnerable to fuel poverty and health issues.