Abstract
Coffee capsules have gained high levels of popularity in the last decades due to their convenience of use, flavour choices, and consistent extraction quality. As governmental bodies are promoting more circular solutions for packaging products, concerns have been raised regarding the environmental impacts of single-use coffee capsules, namely their end-of-life treatment and effective recyclability. This paper presents a novel design based on thin steel sheet material application for new packaging solutions that can support a more circular economy. To validate this new design, a framework was presented for a cross-assessment of Life Cycle Assessment with Circularity Analysis to compare the new tinplate capsule with conventional polypropylene and aluminium capsules. The novel design is more circular (0.97 in the material circularity indicator), in comparison with the polypropylene (0.1) and aluminium (0.80) conventional capsules, due to the ferromagnetic properties that allow for better effectiveness during sorting in urban packaging recycling facilities. As for the environmental assessment, the tinplate has higher environmental impacts than the aluminium and the polypropylene capsules (more 63 % and more 92 %, respectively) due to the high energy intensity processes required to produce this material. These results demonstrate that the novel tinplate capsule should complement the strong results in circularity with further improvements in its environmental performance, namely by the transition of the steel industry to the upcoming generation of decarbonized steel production.

Abstract
The transportation industry focuses on reducing vehicle weight for fuel economy and emissions. This emphasis promotes the use of coaches, which raises concerns about passenger safety in frontal collisions. The proposal is to correlate the crashworthiness of coaches with the replacement of fibreglass composite materials by a state-of-the-art polymer (DCPD). Based on the ECE R29 standard, FEM models solved by Pamcrash (R) assess the vehicle's crashworthiness. Cross-referencing these results with the Eco-Design X technique, two models are evaluated in terms of environmental impact. The LeanDfX methodology involves multiple analyses for design domains, including model optimisation, manufacturing processes, and eco-design. On a performance scale of 0% to 100%, different 'X' domains are evaluated. The Eco-Design study allowed the assessing the environmental impacts of the proposed solution compared to the original models, is conducted using Simapro v9.2.0.2 and the ReCiPe 2016 methodology. The novel design proposed modifications to the models resulted in significant structural behaviour improvements for driver's physical integrity. The cross results of Design-for-Crashworthiness and Design-for-Eco-Design using the innovative LeanDfX framework provide a new perspective to be integrated into the automotive industry. The use of DCPD is expected to lead to a more crashworthy and environmentally friendly design, while ensuring passenger safety.

Abstract
Renewable energy and electric mobility are crucial in addressing current environmental and energy challenges. As the number of electric vehicles increases, more charging infrastructure connected to the electricity distribution network is required. This paper proposes an approach to sizing a fast charging station for electric vehicles. This challenge is addressed by including a battery energy storage system (BESS) and considering the self-production from a renewable energy source (solar energy) in the system. The aim is to minimise the total energy costs, avoid future infrastructure upgrades, and take advantage of the integration of renewable energy resources. The methodology used is a Biased Random Key Genetic Algorithm (BRKGA) based meta-heuristic. Computational experiments were conducted for the sizing of a charging station under four different scenarios that minimise energy costs. The results show that incorporating BESS can lead to a significant reduction in the costs related to the purchase of energy from the grid. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract
Sectorization consists of grouping the basic units of a large territory to deal with a complex problem involving different criteria. Resectorization rearranges a current sectorization avoiding substantial changes, given a set of conditions. The paper considers the case of the distribution of geographic areas of fire brigades in the north of Portugal so that they can protect and rescue the population surrounding the fire stations. Starting from a current sectorization, assuming the geographic and population characteristics of the areas and the fire brigades’ response capacity, we provide an optimized resectorization considering two objectives: to reduce the rescue time by maximizing the compactness criterion, and to avoid overload situations by maximizing the equilibrium criterion. The solution method is based on the Non-dominated Sorting Genetic Algorithm (NSGA-II). Finally, computational results are presented and discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Sectorization is the partition of a set or region into smaller parts, taking into account certain objectives. Sectorization problems appear in real-life situations, such as school or health districting, logistic planning, maintenance operations or transportation. The diversity of applications, the complexity of the problems and the difficulty in finding good solutions warrant sectorization as a relevant research area. Decision Support Systems (DSS) are computerised information systems that may provide quick solutions to decision-makers and researchers and allow for observing differences between various scenarios. The paper is an overview of the development of a DSS for Sectorization, its extent, architecture, implementation steps and benefits. It constitutes a quite general system, for it handles various types of problems, which the authors grouped as (i) basic sectorization problems; (ii) sectorization problems with service centres; (iii) re-sectorization problems; and (iv) dynamic sectorization problems. The new DSS is expected to facilitate the resolution of various practitioners’ problems and support researchers, academics and students in sectorization. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Sectorization is the division of a large area, territory or network into smaller parts considering one or more objectives. Dynamic sectorization deals with situations where it is convenient to discretize the time horizon in a certain number of periods. The decisions will not be isolated, and they will consider the past. The application areas are diverse and increasing due to uncertain times. This work proposes a conceptualization of dynamic sectorization and applies it to a distribution problem with variable demand. Furthermore, Genetic Algorithm is used to obtain solutions for the problem since it has several criteria; Analytical Hierarchy Process is used for the weighting procedure. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.