• Energy Research
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Abstract Nuclear power can contribute to cover the increasing demand of energy while keeping the carbon emissions within the desired limits. Many countries are reluctant to implement nuclear technologies in their territories, but might still use them through imports of products that embody nuclear energy in their life cycle. This work quantifies the difference between the production-based (territorial) and consumption-based (global) nuclear energy use in the main 40 economies of the world (85% of the world's GDP) through the application of a multi-regional environmentally extended input–output model. The mismatch between the direct (territorial) and total (global) use of nuclear energy varies from −237% to 44% in the top economies. From a consumption-based viewpoint, 10 out of the 40 countries reduced the per-capita use of nuclear energy in the period 1995–2009, and 7 when following a production-based approach. The per-capita nuclear energy use could differ in up to 26.2 GJ/inhabitant·year, depending on whether the assessment is consumption or production based. It was also found that around 3.5% of the world's nuclear energy production is trade-embodied and that this amount is growing along with the global production of nuclear energy. Our findings might help to develop more effective environmental regulations worldwide.

In the input-output literature, structural decomposition analysis (SDA) has largely been used to disentangle changes in key variables over time. This paper uses the demand-driven input-output model and proposes a simple method to decompose the changes in energy gross output into different determinants. Specifically, the total changes in energy output are divided into two elements: technological changes, showing the effects of changing the technological coefficients of the input-output model, and structural changes, showing the effects of changing the final demand components. The empirical application, which is for the Catalan economy, uses two input-output tables that cover an entire decade (2001 and 2011). The results show a positive contribution of technology to increasing energy output, while the contribution of the final demand for energy is negative. In addition, the various energy activities exert a different repercussion on energy gross output changes. This highlights the importance of using detailed methods in the study of energy issues. Keywords: Energy Output, Input-Output Analysis, Structural Decomposition Analysis, Technological Coefficients, Final Demand.

Abstract Growth of urban population around the world and, particularly, within urban areas, has placed various pressing challenges on Food, Energy, and Water (FEW) such as food security, water safety as well as energy scarcity and so on. Current studies on urban FEW nexus are mainly focused on the correlation analysis of elements by pairs, while these works are developed separately. With respect to the methods, the existing researches mostly adopt the bottom-up approach, accounting for the direct relationship between the individual production sectors. While the associations between the internal elements of the system still lack of simulation. In this study, we aim at developing an online open access tool for cities, the Urban Circular Economy Calculator (UCEC), which enables to develop different circular economy scenarios associated to FEW management. UCEC v1.0 uses Beijing data as test case. In particular, more than 20 circular economy policies related on food, energy and water are selected and divided into 6 categories. Long-term simulations on the social, economic and environmental impacts are provided to test the trajectories of policy effects. Being an open access tool, UCEC can be used also for supporting participatory processes as an urban management instrument. The solution is economically and financially feasible, due to the low level of technical requirements. The necessity of such a tool is proved by the societal need of transition toward a low-carbon and sustainable framework, which can be effectively supported by the introduction of circular economy. This transition, such as the idea behind UCEC, should preserve (or even improve) the societal wellbeing, while increasing basic resources (i.e.: FEW) accessibility, security and preservation.

This paper presents the first financial analysis of the United Kingdom's local energy business sector. This analysis relies on financial ratios and degrees of localism as inputs for descriptive statistics, cluster, and canonical discriminant analyses. Our findings suggest that privately-owned energy businesses, typically with limited commitments to localities, account for the great majority of sectoral assets and turnover, and are in comparatively good financial condition. Highly-local energy businesses typically have low profitability and high reliance on debt. The latter is the key variable differentiating them from other less local energy businesses. Moreover, we find financial commonalities within different groups of local energy businesses, which correlate with their specific level of localism. In the context of increasing digitalisation in energy markets, more technological innovation may help strengthen local energy businesses' revenue sources and value creation. Further research is needed in terms of investability, specific financing terms and conditions, and geographical aspects of value creation, retention, and delivery to localities. This work can improve the understanding of sectoral dynamics and development needs, with value for policy making to incentivise investment in this emerging sector.

Abstract This paper presents a two pronged approach to the study of the rebound effect, with the aim of assessing the magnitude of the effect in the European freight transport sector and proposing a new modelling framework based on network theory. The (direct) rebound effect is assessed with: 1) an econometric regression; 2) a model based on network theory and statistical mechanics. According to the econometric model the European road freight transport sector undergone a negative rebound between of −74% between 1998 and 2007 and −146% between 1998 and 2011. The network analysis delivers an estimation of network rebound ranging between −29.37% and −7.25. Overall, these results indicate that energy efficiency in Europe, between 1998 and 2011, succeed in reducing the energy consumptions amid an increasing demand for transports. Results on rebound estimation depend on the decision of using GDP as an exogenous variable, an assumption that leaves questions open about the causality chain between growth and transports. Furthermore, the network analysis highlights a structural change –a migration of production factors offshore, that might partially explain this negative effect. In this view, rebound effect analysis on a local or regional scale is becoming more and more uncertain in a globally interconnected economic context.