Key Outcomes of Phase 1
Learn more about key achievements of EURECA-PRO 1.0
Phase 1 of EURECA-PRO delivered key achievements, including research on responsible consumption and production, enhanced public engagement, science communication strategies, and a joint innovation strategy. The alliance also developed a diversity glossary, assessed inclusivity in scientific communities, and advanced research skills. A number of publications related to the research Lighthouse Missions of EURECA-PRO contributed to combating global environmental change, with findings integrated into teaching through problem-based learning and openly shared via an open-access approach.
The RE-EURECA-PRO project, which served as the research dimension of the alliance, successfully concluded in September 2024. Over its three-year span, the project had produced 46 deliverables and achieved 16 milestones, with contributions from over 30 researchers and coordinators across the partner universities. Notable activities had included seven project weeks, children’s universities, final exhibitions, and science slams, all aimed at fostering community engagement and disseminating research findings. The project had also resulted in the development of a new Gender Equality Plan and the submission of policy briefs to the European Union.
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Life Cycle Assessment for the Primary Raw Materials Extraction Industry
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Fair trade and the Sustainable Development Goals: an opportunity for sustainable production and consumption
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About responsibility in production and consumption
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Reducing Food Waste in Supermarkets with Machine Learning
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Around one-third of produced food is wasted, which is almost 1.3 billion tons of food per year, affecting the world economically, environmentally, and socially. Over the years, different solutions for food waste have been developed; however, machine learning within this area has not been sufficiently explored. The food rescue process is very time sensitive since the food can be close to turning rancid, so forecasting the supply of food to be donated could significantly increase the amount of food being rescued. Our objective is to optimise the use of food and reduce food waste in supermarkets. We propose a framework to predict the amount of expiring products donated with machine learning models.
In the paper, a first test of the framework, using simulated data, is presented, showing that the Support Vector Regression would be the most appropriate machine learning model for the framework, giving a score of 0.732While the paper shows that the framework can generate valuable results, the difficulties with applying it to the real world lie in the data acquisition phase. Supermarkets are private companies that might not be willing to share their business data, which is a problem for future research.
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Circularity and sustainability of bio-based polymer/natural fiber reinforced composite
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Biodeposition of diatoms in recycled aggregates
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Circular economy policies in the concrete production
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Plastic pollution and the need for responsible plastic consumption and waste management
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Health, habits and responsible and sustainable consumption
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Damage Tolerance Approach in the Concept of Quality Control Workflow of Passive CFRP Strengthening of Reinforced Concrete Structures
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Unconscious and conscious aspects of healthy food consumption: a neuromarketing and artificial intelligence approach
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Ecological risks of post-artisanal mining sites and their sustainable cleaning techniques
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Multitemporal optical remote sensing to support forest health condition assessment of Mediterranean pine forests in Italy
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The Cost of Going Green in the Jiu Valley
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The zero pollution ambition. European main cities urban sound environment analysis
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The role of public policies and sustainable tourism to face the demographic challenge and sustainable production
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Evaluation of different environmental covariates performance for modeling soil salinity using Digital Soil Mapping in a susceptible irrigated rural area
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Investigating the Relation between Raw Materials and Climate Change in the Literature
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Contrasting compositional and abundance patterns in zooplankton communities between mountain and lowland ponds
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Mapping and estimation of carbon dioxide storage in forest plantations. The contribution of the Sentinel-2 time series in increasing estimates precision
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Near-real time forest health monitoring using ecophysiological sensors and the Internet of things (IoT). A study case for water stress in sustainable poplar plantations
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Study on the soil formation process on the mining waste dumps from Jiu Valley (Romania). A case study
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The present paper is in fact a continuation of a research effort started approx. 16 years ago, and whose main purpose is to follow the process of trans-formation of rocks from coal mining waste dumps into a fertile soil. Thus, during 2022, a new sampling campaign was carried out from the Petrila waste dump, which was later subjected to laboratory tests in order to determine the main characteristics that define the soil. These new data can be seen as the result of a periodic monitoring process and they complement the systematic study carried out between 2006 and 2011 (this study also included research related to the ecological succession of the phytocoenoses present on the Petrila dump). According to these latest analyses, the soil formation process is an active one, relatively slow, being highlighted by the increase in the content of nutrients and organic substances in the composition of the dumped material compared to the previously determined concentrations, as well as by the increase in the total and physiologically useful thickness of the soil layer. The results of this study are important for the next period, when the last 4 active dumps in Jiu Valley will be put into conservation, providing relevant information regarding the pedogenesis process that takes place on these dumps, under the exclusive influence of natu-ral factors.
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Can the fate of the non-avian dinosaurs help us to predict the consequences of the ongoing biodiversity crisis?
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Teacher's perceptions of fisheries ecolabels and game-based learning activities in the framework of Education for Sustainable Consumption
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Paredes-Rodríguez, A.C., Torralba-Burrial, A., Dopico, E. (2023). Teachers’ Perceptions of Fisheries Ecolabels and Game-Based Learning Activities in the Framework of Education for Sustainable Consumption. In: Benítez-Andrades, J.A., García-Llamas, P., Taboada, Á., Estévez-Mauriz, L., Baelo, R. (eds) Global Challenges for a Sustainable Society . EURECA-PRO 2022. Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-25840-4_54
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Effective biomass delignification with deep eutectic solvents
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Innovative treatment of municipal sewage sludge using hydrothermal carbonization and nutrient recovery technologies
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Resin degradation of end-of-life wind turbine blades to produce useful chemical compounds in the context of waste to resource recovery
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Sustainable Food, Key for the Future of the Planet: Getting to Know the European Consumer of Sustainable Products
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In recent decades, the unsustainability of mass production and consumption models has become evident. The sustainable food market is born in response to the growing demand for products that are respectful with the Planet and compromised with the health of human beings. Responsible Consumers lead this new market, by being conscious of the impact of their consumption patterns and by choosing the products, to make up their diet and lifestyle, that contribute to build a more Sustainable and Fair Food System. The present study focuses on analyzing and defining Sustainable Consumer profile’s: its behavior, its habits, its preferences; as well as those variables and factors that inhibit or motivate the consumption of Sustainable Food. Reaching a better understanding of one the main agents of the transition of the agri-food system towards a more sustainable one is key for both, private and public organizations, as this new market is booming and will continue growing in the coming years.
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Alonso, M.A.S., Abella, V.M., Martínez, I.B. (2023). Sustainable Food, Key for the Future of the Planet: Getting to Know the European Consumer of Sustainable Products. In: Benítez-Andrades, J.A., García-Llamas, P., Taboada, Á., Estévez-Mauriz, L., Baelo, R. (eds) Global Challenges for a Sustainable Society . EURECA-PRO 2022. Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-25840-4_16
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How implementing SDG 12 in teaching helps students develop prosocial skills?
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Research on Hard Drives in the Context of the Construction of Shredding Knives in the Recovery of Rare Earth Elements
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The publication presents an inventory of waste electrical and electronic equipment (WEEE) equipped with neodymium (NdFeB) magnets, which, when
decommissioned, will be able to become a source of REE procurement. These magnets contain Rare Earth Elements (REEs) such as neodymium, dysprosium and praseodymium. Products equipped with NdFeB magnets have been identified: computer hardware, consumer electronics, wind power generators, and electric-powered vehicles. A prospective source of REE acquisition could be HDDs and speakers in laptops and phones, which account for about 10% of the analysed equipment containing NdFeB magnets.
A study of the selected WEEE – hard disk drive in terms of material properties was carried out. The following analyses were performed: phase composition studies (XRD), microstructure studies (SEM-EDS), micro-area chemical composition studies (S/TEM) and hardness studies. Based on the studies, the material for the cutting knives of the twin-shaft shredder was selected. Three variants of cutting knives differing in the number of blades on the perimeter were developed in Autodesk Inventor 2023. Variants with three, four and five blades were considered. Strength calculations were then carried out using the Nastran plug-in. A force was applied to the cutting knife blades, from which von Mises stresses and strains were determined.
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Physical Processing in Waste Printed Circuit Boards Recycling: current state of research
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An insulation panel made from local plant-based lightweight concrete
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Research on the valorization of green sludge resulting from the manufacture of sodium dichromate in Romania
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Sustainable alternative to antimicrobial uses: new probiotics.
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Energy Saving Technology Integration into the Transport Sector; the Influence of Years of Driving and Gender on Electric Vehicles
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Production of nanobiochar from sewage sludge for the adsorption of Emerging Contaminants (ECs) from water and wastewater
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Influence of ground PV glass addition on selected properties of geopolymer mortars
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Responsible heritage protection actions
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Introduction of Integrated Resource Management for Sustainable Development of Industries methods
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Improving sustainability in Industrial Plant Construction Available tools and methods
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Consumption behaviour in the context of sustainable energy: theoretical approache
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Impact of the Operation Conditions on the Reverse-Water-Gas Shift Reaction
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Markowitsch, C., Lehner, M. (2023). Impact of the Operation Conditions on the Reverse-Water-Gas Shift Reaction. In: Benítez-Andrades, J.A., García-Llamas, P., Taboada, Á., Estévez-Mauriz, L., Baelo, R. (eds) Global Challenges for a Sustainable Society . EURECA-PRO 2022. Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-25840-4_10
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Monitoring electrical and weather parameters in bifacial system
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Thermal hydrogen production from petroleum reservoirs using steam reforming and in-situ catalyst application: A technical and economic analysis
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Bauer, J.F., Marrune, C.R., Amro, M. (2023). Thermal Hydrogen Production from Petroleum Reservoirs Using Steam Reforming and In-Situ Catalyst Application: A Technical and Economic Analysis. In: Benítez-Andrades, J.A., García-Llamas, P., Taboada, Á., Estévez-Mauriz, L., Baelo, R. (eds) Global Challenges for a Sustainable Society . EURECA-PRO 2022. Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-25840-4_58
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Comparative Exergy Analysis of Heat Pumps for Heat Recovery Applications
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Ion Dosa*
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Dosa, I. (2023). Comparative Exergy Analysis of Heat Pumps for Heat Recovery Applications. In: Benítez-Andrades, J.A., García-Llamas, P., Taboada, Á., Estévez-Mauriz, L., Baelo, R. (eds) Global Challenges for a Sustainable Society . EURECA-PRO 2022. Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-25840-4_56
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Rooftop Solar Photovoltaic systems for building of Industrial
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Energy Analysis of a Wastewater Treatment Plant
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Radu, S.M., Petrilean, D.C., Mija, N. (2023). Energy Analysis of a Wastewater Treatment Plant. In: Benítez-Andrades, J.A., García-Llamas, P., Taboada, Á., Estévez-Mauriz, L., Baelo, R. (eds) Global Challenges for a Sustainable Society . EURECA-PRO 2022. Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-25840-4_43
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Validation of double wall reactor for direct biogas upgrading via catalytic methanation
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Autonomous Smart Electric Vehicle integrated into a Smart Grid type System
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Virtual Exchange as a Sustainable Approach to Intercultural Learning
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Scale model showcase to drive policy making via IoT composite indices and low-resource equipment at the edge of the computing continuum
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The application of nanotechnology in the development of concrete coatings
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Automation of the assessment and diagnosis process in rehabilitation: a proposal to reduce costs and optimize the health care system
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Web application based on Sentinel-2 satellite imagery for water stress detection and monitoring in poplar plantations
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AppPopuli: Web application for real-time damage report in poplar plantations using citizen science
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AppPopuli is a citizen science project developed by a multidisciplinary team, in the fields of forest health and computer science. The core of the project was to develop a web application that allows both foresters and ordinary citizens to inform, in real-time, about damages in hybrid poplar plantations (Populus spp.) caused by pests or diseases. The damage report is done individually by the user through a form that they fill in with information related to the damaged tree, such as, for example, the name of the pathogen causing the damage (if known), the geographical location, photographs, etc.; so that this data is stored in a database. The database aims to monitor the status of poplar plantations and provide feedback to the app users about the damage they have reported. On the other side, the application also includes a help section with information about the pests and diseases that could damage poplar trees, so that non-experts in the field are able to identify damages found in poplar trees correctly; and an explore section with a table that contains some of the data of the reports sent by the users with their location marked on a world map. The application is focused on its use using mobile devices (but not limited to), which has been kept in mind while designing the user interface in order to guarantee a good user experience, no matter the device you are using and the size of its screen. This application will contribute to sustainable and responsible wood production, providing more resilient poplar plantations and promoting the early control of potential pests and diseases.
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Wireless industrial access control systems for autonomous transportation
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The inextricable link among climate change, pandemic, migrations, and geopolitics: how Artificial Intelligence can help us
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Text classification of users claiming to have ASD using traditional machine learning techniques
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Autism spectrum disorders (ASD) are developmental disabilities caused by differences in the brain. According to the WHO, ASD affects 1% of the population. However, many people are still undiagnosed. Thanks to artificial intelligence, more and more research is being carried out with the aim of obtaining early diagnoses that help to reduce the negative impact of the diseases or even prevent them. For all these reasons, this research has been carried out by collecting and tagging data through the social network Twitter. These tweets were obtained from users who, in their biography, indicated that they suffered from ASD or were relatives of someone with ASD. Subsequently, the set of tweets obtained was preprocessed, generating a set of 404,627 tweets, thanks to which text classification techniques, Random Forest and Support Vector Classifications, were applied. The results show predictive models with an accuracy of over 74% when classifying texts that may come from people with ASD. The research, despite its limitations, opens up a new line of research that may improve the diagnosis of this disease.
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Industrial applications of the Internet of Things
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In the age of Industry 4.0, a substantial concern for modern manufacturing organizations in optimizing production processes under an Internet of Things (IoT) framework is noted. Moreover, given the significant volume of production, energy efficiency is an inevitable issue. To a great extent, improving production performance depends on the development of new technologies. As a result, this research targets to conduct a research review for the implementation of industry 4.0 technologies in continuous manufacturing. While there is a significant amount of research on batch manufacturing and industry 4.0, continuous manufacturing is less addressed in these scientific works. In an attempt to fill this gap, we try to understand the transition from batch processing manufacturing to continuous processing manufacturing within certain industries, emphasizing the benefits of industry 4.0 relevant to the industry and sustainability. Another crucial part of this study is identifying open issues and challenges of industry 4.0 infrastructure in continuous manufacturing. For such reason, we developed two research questions that we will try to answer during this work. The first one is which are the technologies being implemented as part of industry 4.0 in continuous manufacturing and the second one, does the implementation of such technologies in continuous manufacturing led to energy efficiency improvement.

