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This study focuses on formulating the most sustainable concrete by incorporating recycled concrete aggregates and other products retrieved from construction and demolition (C&D) activities. Both recycled coarse aggregates (RCA) and recycled fine aggregates (RFA) are firstly used to fully replace the natural coarse and fine aggregates in the concrete mix design. Later, the cement rich ultrafine particles, recycled glass powder and mineral fibres recovered from construction and demolition wastes (CDW) are further incorporated at a smaller rate either as cement substituent or as supplementary additives. Remarkable properties are noticed when the RCA (4–12 mm) and RFA (0.25–4 mm) are fully used to replace the natural aggregates in a new concrete mix. The addition of recycled cement rich ultrafines (RCU), Recycled glass ultrafines (RGU) and recycled mineral fibres (RMF) into recycled concrete improves the modulus of elasticity. The final concrete, which comprises more than 75% (wt.) of recycled components/materials, is believed to be the most sustainable and green concrete mix. Mechanical properties and durability of this concrete have been studied and found to be within acceptable limits, indicating the potential of recycled aggregates and other CDW components in shaping sustainable and circular construction practices. The authors wish to acknowledge the financial support from EU Horizon 2020 Project VEEP ‘‘Cost-Effective Recycling of C&DW in High Added Value Energy Efficient Prefabricated Concrete Compo-nents for Massive Retrofitting of our Built Environment” (No.723582).

This dataset contains the data used to completed the article under peer review: References: Cabezas, A.; Milanés, Y.;Alba, R.; Delgado, A.M. (2023). The need to develop tailored tools for improving the quality of thematic bibliometric analyses: Evidence from papers published in Sustainability and Scientometrics. (Article under peer review) Institutions: Spain (Universidad Internacional de La Rioja, Universidad Pablo de Olavide, Hospital Universitario Virgen de las Nieves)

Organic waste production has greatly increased following human sprawl and led to the development of landfills in recent decades. This abundant and reliable anthropogenic food source has favoured several species, some of which consequently became overabundant. Landfills present hazards to wildlife, which may suffocate on plastic materials, tangle on cords, and get exposed to pollutants and pathogens. In response to environmental and public health concerns over the maintenance of landfills, the European Commission proposed to close the landfills. Our objective was to determine the impact of the Landfill European Directive on the White Stork, Ciconia ciconia, whose population recovery and growth were linked to landfill exploitation. We implemented species distribution models to project future distribution in the absence of landfills in the Community of Madrid (Spain). Habitat suitability was estimated based on nest occurrence and we included data from land cover types, human population density and two different climate change scenarios (i.e., emissions in low and high shared socioeconomic pathways). Given that protection measures, particularly implemented in protected areas, were associated with population recovery, we also evaluated the overlapping degree between protected areas and projected distribution. Our models predicted a sharp decline in breeding population distribution with landfill closure, reaching values similar to the 1984 breeding census when the species was categorized as threatened. Our results also suggest a decrease in maximum habitat suitability. Climate change also contributed to a reduction in breeding population distribution given model predictions for the extreme emission pathway (ssp5). Measures such as gradual change in landfill management, continuous monitoring of breeding populations, and evaluation of the Stork use of natural feeding areas before and after landfill closure, should be considered.  Direct census searching for nests in the whole Community of Madrid.

Renewable energies will represent an increasing share of the electricity supply, while flue and gasification-derived gases can be a promising CO2 feedstock with a heat load. In this study, microbial electrosynthesis of organic compounds from CO2 at high temperature was proposed as an alternative for valorising energy surplus and decarbonizing the economy. The unremitting fluctuation of renewable energy sources was assessed using two bioreactors at 50 °C, under circumstances of continuous and intermittent power supply (ON-OFF; 8-16 h), simulating an off-grid photovoltaic system. Results highlighted that maximum acetate production rate (43.27 g m-2 d-1) and columbic efficiency (98%) were achieved by working with an intermittent energy supply, while current density was reduced three times. This boosted the production of acetate per unit of electricity provided up to 138 g kWh-1 and reinforced the robustness of the technology by showing resilience to tolerate perturbations and returning to its initial state.

Human activities and city routines follow patterns. Transfer learning can help achieve scalable solutions towards the realisation of smart cities accounting for similarities between regions, domains, and activities. In this study, we propose a Transfer Learning-based framework for smart buildings to test this hypothesis in energy-related problems. Our framework has two major components: the network creation and the transferable predictive model. In order to create the network that groups buildings sharing characteristics, we evaluated two strategies: a novel clustering algorithm for mixed data, k-prod, and clustering the image-based representation of time series. Then, a combination of Long Short Term Memory and Convolutional Neural Network was trained on the centroids of the clusters for energy consumption prediction. The Coefficient of Variation of the Root Mean Squared Error (CVRMSE) of the predictions in such clusters varies between 3.85 and 58.85 %. The obtained parameters were transferred to the rest of the buildings for predictive purposes, finding accurate results in buildings with little data. Our framework deals with insufficient training data since parameters from scenarios with more sensors can be received. It also carries out state-of-the-art performance on 3 datasets from different sources having in total 533 rooms/buildings and two energy efficiency domains: consumption prediction reducing the CVRMSE by 21.6 %, and air conditioning usage prediction moving from 4.18 % to 0.28% CVRMSE. Our framework extracts more knowledge from available IoT deployments, so that smartness could be spread between environments at a fewer cost given that less individual effort will be needed.

This study aims to characterize and valorize hemp residual biomass by a slow pyrolysis process. The volatile by-products of hemp carbonization were characterized by several methods (TGA, UV-VIS, TLC, Flash Prep-LC, UHPLC, QTOF-MS) to understand the pyrolysis reaction mechanisms and to identify the chemical products produced during the process. The obtained carbon yield was 29%, generating a gaseous stream composed of phenols and furans which was collected in four temperature ranges (F1 at 20–150 °C, F2 at 150–250 °C, F3 at 250–400 °C and F4 at 400–1000 °C). The obtained liquid fractions were separated into subfractions by flash chromatography. The total phenolic content (TPC) varied depending on the fraction but did not correlate with an increase in temperature or with a decrease in pH value. Compounds present in fractions F1, F3 and F4, being mainly phenolic molecules such as guaiacyl or syringyl derivatives issued from the lignin degradation, exhibit antioxidant capacity. The temperature of the pyrolysis process was positively correlated with detectable phenolic content, which can be explained by the decomposition order of the hemp chemical constituents. A detailed understanding of the chemical composition of pyrolysis products of hemp residuals allows for an assessment of their potential valorization routes and the future economic potential of underutilized biomass.

Open Data that is labelled as ATELIER and provides important information regarding energy transition and smart energy deployment in the City of Bilbao. This dataset will be enlarge along the project life

In the context of our project, we organised a webinar at which almost 200 participants assisted. It was aimed at everyone who cares about a greener and more sustainable future. The development of sustainable and resource-saving processes is a major focus of R&D&I work, also supported heavily by the European Commission as part of the Green Deal and the sustainability efforts. In this context, biotechnology is already acting as a facilitator to achieve a circular economy and a bioeconomy. We aim to achieve these goals with the identification, optimisation, production and application of innovative enzymes to support the transformation of various industrial sectors and their consumer products. In this webinar, we wanted to present the competences and topics we acquire or work on in FuturEnzyme to an interested international audience. With this CLIB Forum event, we want to emphasise and promote the need for collaboration between researchers, entrepreneurs, and manufacturers for a greener and more sustainable future. Furthermore, our webinar was also of interest for policy makers, funding bodies, investors and consumers. The FuturEnzyme project partners CSIC, Barcelona Supercomputing Center and the University of Hamburg presented their activities in the project and beyond to a wide range audience.

The lack of robust studies carried out on urban roads in developing countries makes it difficult to enhance traffic safety, ensuring sustainable roads and cities. This study analyzes the contribution of a number of explanatory variables behind crashes involving injuries on arterial roads in Irbid (Jordan). Five binary logistic regression models were calibrated for a crash dataset from 2014–2018: one for the full database, and the others for the four main crash causes identified by Jordanian Traffic Police reports. The models show that whatever the crash cause, the three most significant factors linked to an injury or fatality lie in urban road sections that are in large-scale neighborhood areas, have fewer than six accesses per kilometer, and have a low traffic volume (under 500 veh/h/ln). Some of these results agree with previous studies in other countries. Jordan’s governmental agencies concerned with urban road safety might use these results to develop appropriate plans and implement priority actions for each crash cause, in addition to undertaking further research for comparative purposes.