https://hdl.handle.net/10259/6168 2026-04-17T13:00:37Z https://hdl.handle.net/10259/11472 A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: Application in the steel industry Carreira Barral, Israel; García-Moral, Ana; Iñigo Martínez, María Emilia; Díez Hernández, Julieta; Ibáñez Porras, Jesús; Alonso-Terán, Mario; Fuente Gamero, Patricia de la; Barros García, Rocío; Martel Martín, Sonia This work proposes a straightforward methodology for integrating the environmental, economic, social, criticality and circularity dimensions as normalised indicators into a single equation, yielding a sustainability index, and demonstrates its applicability in the context of the steelmaking industry. This new approach, designed for early development stages and based on the elemental composition of the input materials (metal scraps and raw materials), allows the identification of those within a dataset that are of greatest concern according to their sustainability index and facilitates decision-making regarding their use in alloy production. A sensitivity analysis, with 11 studied scenarios, was conducted to evaluate the influence of the five indicators on the outcome, assigning different weights to them. The developed strategy, compatible with the Safe and Sustainable by Design framework, was successfully applied to a family of 207 materials of varying qualities. A set of raw materials, including both ferroalloys and pure elements, was identified as the most worrying group from the sustainability viewpoint, in line with previous works (e.g., ferroniobium, ferrotungsten, pure cobalt and pure copper), thereby validating the described framework. However, metal scraps should, whenever feasible, be prioritised, as their recovery would reduce the reliance on mineral resources. Consequently, a number of them are presented as alternatives to the least sustainable raw materials according to their sustainability indexes. The application of this methodology provides a holistic view of sustainability and enables rapid decisions regarding which products from a given set are more suitable for use, based on their index values and stakeholder needs. 2026-06-01T00:00:00Z https://hdl.handle.net/10259/11199 Dataset of the work 'A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: application in the steel industry' Carreira Barral, Israel; García-Moral, Ana; Iñigo Martínez, María Emilia; Díez Hernández, Julieta; Ibáñez Porras, Jesús; Alonso-Terán, Mario; Fuente Gamero, Patricia de la; Barros García, Rocío; Martel Martín, Sonia This dataset contains the data provided by ArcelorMittal España (commercial names, quality and elemental composition of the studied metal scraps and raw materials) in the context of the 'IRIDISCENTE' research project, and the analysis, results and conclusions for each of the 11 scenarios considered in the work 'A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: application in the steel industry' 2025-12-15T00:00:00Z https://hdl.handle.net/10259/11129 Assessment of Polluted Soil Remediation Using Bacterial Community Tolerance to Heavy Metals as an Indicator Campillo Cora, Claudia; Soto Gómez, Diego; Arias Estévez, Manuel; Fernández Calviño, David The assessment of remediation on metal-polluted soils is usually focused on total and/or bioavailable metal content. However, these chemical variables do not provide direct information about reductions in heavy metals pressure on soil microorganisms. We propose the use of bacterial communities to evaluate the efficiency of three remediation techniques: crushed mussel shell (CMS) and pine bark (PB) as soil amendments and EDTA-washing. A soil sample was polluted with different doses of Cu, Ni, and Zn (separately). After 30 days of incubation, the remediation techniques were applied, and bacterial community tolerance to heavy metals determined. If bacterial communities develop tolerance, it is an indicator that the metal is exerting toxicity on them. Soil bacterial communities developed tolerance to Cu, Ni, and Zn in response to metal additions. After remediation, bacterial communities showed decreases in bacterial community tolerance to Cu, Ni, and Zn for all remediation techniques. For Cu and Ni, soil EDTA-washing showed the greatest reduction of bacterial community tolerance to Cu and Ni, respectively, while for Zn the soil amendment with PB was the most effective remediation technique. Thus, bacterial community tolerance to heavy metals successfully detect differences in the effectiveness of the three remediation techniques. 2022-09-01T00:00:00Z https://hdl.handle.net/10259/11128 Estimation of baseline levels of bacterial community tolerance to Cr, Ni, Pb, and Zn in unpolluted soils, a background for PICT (pollution-induced community tolerance) determination Campillo Cora, Claudia; Soto Gómez, Diego; Arias Estévez, Manuel; Bååth, Erland; Fernández Calviño, David The PICT method (pollution-induced community tolerance) can be used to assess whether changes in soil microbial response are due to heavy metal toxicity or not. Microbial community tolerance baseline levels can, however, also change due to variations in soil physicochemical properties. Thirty soil samples (0–20 cm), with geochemical baseline concentrations (GBCs) of heavy metals and from five different parent materials (granite, limestone, schist, amphibolite, and serpentine), were used to estimate baseline levels of bacterial community tolerance to Cr, Ni, Pb, and Zn using the leucine incorporation method. General equations (n = 30) were determined by multiple linear regression using general soil properties and parent material as binary variables, explaining 38% of the variance in log IC50 (concentration that inhibits 50% of bacterial growth) values for Zn, with 36% for Pb, 44% for Cr, and 68% for Ni. The use of individual equations for each parent material increased the explained variance for all heavy metals, but the presence of a low number of samples (n = 6) lead to low robustness. Generally, clay content and dissolved organic C (DOC) were the main variables explaining bacterial community tolerance for the tested heavy metals. Our results suggest that these equations may permit applying the PICT method with Zn and Pb when there are no reference soils, while more data are needed before using this concept for Ni and Cr. 2021-11-01T00:00:00Z