• Energy Research

This paper applies the so-called Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM), based on Georgescu-Roegen's fund-flow model, to the Spanish region of Catalonia. It arrives to the conclusion that within the context of the end of cheap oil, the current development model of the Catalan economy, based on the growth of low-productivity sectors such as services and construction, must be changed. The change is needed not only because of the increasing scarcity of affordable energy and the increasing environmental impact of present development, but also because of the aging population. Moreover, the situation experienced by Catalonia is similar to that of other European countries and many other developed countries. This implies that we can expect a wave of major structural changes in the economy of developed countries worldwide. To make things more challenging, according to current trends, the energy intensity and exosomatic energy metabolism of Catalonia will keep increasing in the near future. To avoid a reduction in the standard of living of Catalans due to a reduction in the available energy it is important that the Government of Catalonia implement major adjustments and conservation efforts in both the household and paid-work sectors.

Climate change is expected to increase the number of days with meteorological conditions conducive to uncontrollable wildfires. Thus, it is necessary to strengthen the capacity of wildfire-prone regions to minimize the adverse impacts of these wildfires by creating resilient landscapes. In this paper we develop a participatory multi-criteria evaluation to identify and map landscape values and prioritize areas according to these values in the Montseny Biophere Reserve (Catalonia, NE Spain). Then, we draft a wildfire management strategy to protect the areas that have been prioritized through selected fuel reduction sectors that would reduce wildfire intensity. Finally, we emphasize the added value of a participatory multi-criteria evaluation in the adaptation to and management of expected megafires. We find that the integration of landscape values through participatory multi-criteria evaluation has the potential to alter wildfire management strategies by adding fuel reduction sectors and changing their implementation order. However, the implementation of the planned fuel reduction treatments faces socioeconomic and institutional barriers that call for a deeper engagement with transdisciplinary project design and transformative science.

This report comprises the output of Task 2.2 Strategies and indicators for data modelling and data analysis. It provides a suggestion for strategies to monitor CO2 emissions and a list of indicators that can be used to measure the performance of strategies to reduce CO2 emissions. These indicators are grouped and linked to a set of key questions, which are relevant for strategies to plan, design and implement low-carbon urban developments. The indicators identified in this report will be used to monitor and verify the impacts on CO2 emissions in the demonstrations conducted in WP8. The definition of this set of multi-dimensional indicators is based on the accounting framework proposed in D2.3. The indicators identified are most relevant for the three case studies (Manresa, Newcastle and North Harbour). This is because the scope of the work undertaken in Task 2.2 is specific to the problems addressed in the case studies. However, the indicators identified are also relevant to typical urban planning projects. Thus while the indicators presented in this report do not cover all aspects of all urban planning projects, they are adequate for developing strategies for evaluating the energy performance and CO2 emissions in many buildings, neighbourhoods and city development projects. As the SEMANCO platform develops and more case studies/pilot projects are analysed by users/actors it may be necessary to reassess the indicators. This means that a key finding derived from the work of Task 2.2 is that it is necessary to ensure that the SEMANCO platform and associated tools are flexible enough to allow both the introduction of new indicators and the removal of obsolete indicators.

This report presents the final impact verification of the SEMANCO integrated platform. The work presented applies the evaluation criteria established in Deliverable 2.4 Updated impact verification in the light of the final implementation of the demonstration scenarios reported in Deliverable 8.4 Implementation effectiveness. Deliverable 2.4 identified the following criteria as the most appropriate to use when evaluating the SEMANCO integrated platform:1. The functionalities of the platform in relation to the main challenges identified for each case study. This included: a) Urban energy systems operating at different levels, b) Multiple dimensions to represent urban energy systems, c) Energy transformations across scales and, d) Finding a balance between detailed and relevant information.2. The ability of the platform to provide relevant information to support energy efficient urban planning. This includes: a) Creating alternative urban projects, b) integrating data from different sources, c) Simulating the energy performance of an urban area and d) Calculating performance indicators.3. The relevance that the results produced by using the SEMANCO tools have for the users and stakeholders involved in energy efficient urban planning realm.

28 p. The use of multi-criteria evaluation tools in combination with participatory approaches provides a promising framework for integrating multiple interests and perspectives in the effort to provide sustainability. However, the inclusion of diverse viewpoints requires the ""compression"" of complex issues, a process that is controversial. Ensuring the quality of the compression process is a major challenge, especially with regards to retaining the essential elements of the various perspectives. In this article, we suggest a process in which the explicit elicitation of weights (i.e., the prioritisation of criteria) within a participatory multi-criteria evaluation serves as a quality assurance mechanism to check the robustness of sustainability integrated assessment processes from a social perspective. We demonstrate this approach using a case study focused on the sustainable management of the Urdaibai Estuary in the Basque Country (Southern Europe). Drawing on the large body of literature on sophisticated mathematical models that help identify and prioritise criteria, this approach allows (1) an explicit ""social sensitivity"" analysis despite the incommensurability of values regarding individual or group priorities, and (2) participants to learn from and reflect upon diverse social preferences without forcing their consensus.

This article describes a novel methodological approach for the integrated sustainability assessment of pasture-based dairy sheep systems. Most studies on livestock system sustainability focus on animal production, farm profitability, and mitigation strategies of greenhouse gas emissions. However, recent research indicates that pasture-based livestock farming also contributes positively to rural areas, and the associated increase in plant diversity promotes ecosystem functioning and services in natural and managed grasslands. Likewise, little attention has focused on how pasture-based livestock systems affect soil carbon changes, biodiversity, and ecotoxicity. Furthermore, the quality and safety of food products, particularly sheep milk and cheese, and socioeconomic issues such as cultural heritage and consumer behavior are often neglected in livestock system sustainability assessments. To improve the analysis of sustainability and adaptation strategies of livestock systems, we suggest a holistic approach that integrates indicators from diverse disciplines with complementary methods and models capable of capturing the complexity of these systems at multiple scales. A multidisciplinary perspective generates new indicators to identify critical trade-offs and synergies related to the resilience of dairy sheep livestock systems. A multiscale approach provides insights on the effects of socioeconomic and environmental changes associated with current dairy sheep grazing systems across multiple scales. The combined approach will facilitate the development and progressive implementation of novel management strategies needed to adapt pasture-based dairy sheep farms to changing conditions under future socioeconomic and environmental scenarios.

Abandoning fossil fuels and increasingly relying on low-density, land-intensive renewable energy will increase demand for land, affecting current global and regional rural–urban relationships. Over the past two decades, rural–urban relationships all over the world have witnessed unprecedented changes that have rendered their boundaries blurred and have lead to the emergence of “new ruralities.” In this paper, we analyze the current profiles of electricity generation and consumption in relation to sociodemographic variables related to the use of time and land across the territory of Catalonia, Spain. Through a clustering procedure based on multivariate statistical analysis, we found that electricity consumption is related to functional specialization in the roles undertaken by different types of municipalities in the urban system. Municipality types have distinctive metabolic profiles in different sectors depending on their industrial, services or residential role. Villages’ metabolism is influenced by urban sprawl and industrial specialization, reflecting current “new ruralities.” Segregation between work activity and residence increases both overall electricity consumption and its rate (per hour) and density (per hectare) of dissipation. A sustainable spatial organization of societal activities without the use of fossil fuels or nuclear energy would require huge structural and sociodemographic changes to reduce energy demand and adapt it to regionally available renewable energy.

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Experimental & Theoretical Artificial Intelligence on 27.04.2015, available online: http://www.tandfonline.com/doi/10.1080/0952813X.2015.1024489 A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks. Peer Reviewed