Building renovation was declared a key point for sustainable development, however, the renovation rate of residential buildings in the European Union is insufficient to meet the climate and energy targets set. This paper analyses the main circular economy models used in the construction sector, as well as the situation of the building renovation market, to set a framework for circular economy models in building renovation. Of all the existing strategies in this sector, design, material recovery, building renovation and end-of-life actions would be the best, respectively. It also includes a market analysis consisting of a literature review covering PEST perspectives (political, economic, social and technical) and a SWOT analysis (strengths, weaknesses, opportunities and threats), concluding with a market gap analysis. The results of these analyses allow the development of a series of suggestions and strategies to be followed in order to solve the main barriers that hinder the implementation of the circular economy in the building´s renovation sector.

Urban areas generate more than 70% of the world’s climate change emissions, mainly CO₂, produced by the combustion of fossil fuels. Climate change is increasing cities’ exposure to climate hazards, such as heat waves or floods. Therefore, there is a need to improve risk management with the inclusion of climate resilience in urban policy design. Despite improved urban climate monitoring, there are still relatively few scientific publications on climate change adaptation in urban areas. Adaptation to climate change is not achieved through specific action, but rather through the adoption and continuous implementation of adaptation actions such as housing rehabilitation, green space management and protection measures for vulnerable groups. This variety of actions makes it difficult not only to identify different indicators, but also to use common benchmarks. Considering the role of municipalities in adapting to climate change, it is crucial to identify adaptation indicators that serve as a basis for decision making, as well as evaluation methods that allow the effectiveness of planned and implemented measures in municipalities. It can be used to determine which measures increase the level of adaptation or lead to poor adaptation. Therefore, monitoring indicators makes it possible to evaluate the effectiveness of the measures, in addition to formulating new ones. This paper includes a literature review of existing index designed to address climate hazards and mitigate their impacts in urban areas.

Social impact assessment of products can be approached through different methodologies that need to be adapted to the particularities and features of the studied subject. Thus, the Social Life Cycle Assessment methodology can be used to assess different innovative practices of product manufacturing, under a circular economy approach, by identifying potential positive as well as negative impacts along products’ life cycle. This paper presents the results of the Social Life Cycle Impact Assessment of a reference product from the Spanish meat industry using existing and new innovative methods of social impact analysis. Worker discrimination, health and safety for workers, consumers and local community were identified as the social aspects with relevant significance into the business or for the influence on customer’s perception of the products studied. Therefore, results can represent a reference scenario for the future assessment of innovative solutions in the Spanish meet sector. Despite the scarce use of Social Life Cycle Impact Assessment, this case study is a good example of how this innovative kind of assessment can be helpful for companies to identify their weak and strong social performance areas and design strategies to improve in Social Responsibility Management.

The present work introduces a multi-criteria approach focused on the evaluation of wine production, considering the three dimensions of sustainability: environmental, economic and social. In this sense, the most relevant key performance indicators were selected within each dimension and disaggregated into sub-indicators to address the different sustainability aspects within the wine value chain. Furthermore, the analytic hierarchy process was applied as the method to weight the relevance of the three dimensions and corresponding key performance indicators, in order to allow the producers to understand which aspects need to be covered to improve their production sustainability. Results demonstrate how the approach proposed is able to identify, for both the vineyard and winery, the strengths and weaknesses regarding the sustainability performance of their production. Additionally, this study also contributes by shedding light on the most suitable and recommended actions to increase the company’s sustainability from a sustainable perspective. Additionally, it is important to highlight that, although the developed approach is specifically designed for the wine sector in the Navarrese region, it can be replicated by adjusting the key performance indicator selection to apply this methodology to the reality in other wine production regions.

This study investigates the application of the Analytic Hierarchy Process (AHP) as a decision-support mechanism for managing complex sustainability issues in industrial settings, specifically within the framework of circular economy principles. Focusing on a case from the brewery sector, developed under the EU ECOFACT initiative, this research evaluates ten distinct configurations for the must cooling process. These alternatives are assessed using environmental, economic, and technical criteria, drawing on data from life cycle assessment (LCA) and life cycle costing (LCC) methodologies. The findings indicate that selecting an optimal scenario involves balancing trade-offs among electricity and water consumption, operational efficiency, and overall environmental impacts. Notably, Scenario 3 emerges as the most balanced option, consistently demonstrating superior performance across the primary evaluation criteria. The use of AHP in this context proves valuable by introducing structure and transparency to a multifaceted decision-making process where quantitative metrics and sustainability objectives intersect. By integrating empirical industrial data with an established multi-criteria decision approach, this study highlights both the practical utility and existing limitations of conventional AHP, particularly its diminished ability to discriminate between alternatives when their scores are closely aligned. These insights suggest that hybrid or advanced AHP methodologies may be necessary to facilitate more nuanced decision-making for circular economy transitions in industrial environments.

In developed countries, a large part of the building stock in 2050 will consist of currently existing buildings. Consequently, in order to achieve the objectives in terms of energy efficiency in the building sector we must consider not only new infrastructures but also the old ones. A reduction in energy consumption for climate control of between 50 and 90% can be achieved by rehabilitation and the implementation of different energy efficiency measures. Currently, these measures to reduce energy consumption and associated CO₂ emissions can be modelled using computer tools. However, high precision and detail of thermal behaviour models through simulations can mean a great computational cost for companies, which results in a blockage of servers and workers. In this paper, the Response Surface Methodology (RSM) is presented as an innovative methodology for the simplification of models for calculation of the energy savings associated with thermal comfort improvement in buildings. A single-family house model, located in three different climates, is presented as a case study in order to validate the proposed methodology. Different scenarios were simulated, addressing heating and cooling temperature set points and external wall insulation represented by the transmittance (U-value). Results obtained from energy simulation using Design Builder were contrasted against those estimated from the simplified model extracted from the RSM analysis. The results revealed a deviation lower than 3% when comparing both methods. Therefore, the simplified mathematical prediction models are demonstrated to be suitable for the study of the energy performance of buildings, saving computational time, costs and associated human resources.