2026-08-19T08:18:32Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/111992026-03-09T11:01:20Zcom_10259_6168com_10259_5086com_10259_2604com_10259_3924col_10259_6775col_10259_7224col_10259_5684

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 2026-01-12T12:34:41Z 2026-01-12T12:34:41Z 2025-12-15 Carreira-Barral, I., García Moral, A., Iñigo Martinez, M. E., Díez-Hernández, J., Ibanez, J., Mario Alonso Terán, De La Fuente, P., Barros Garcia, R., & Martel-Martín, S. (2025). Dataset of the work 'A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: application in the steel industry' [Data set]. Universidad de Burgos. https://doi.org/10.71486/MCTS-0K15 https://hdl.handle.net/10259/11199 10.71486/mcts-0k15 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' eng http://creativecommons.org/licenses/by-nc/4.0/ info:eu-repo/semantics/openAccess Atribución-NoComercial 4.0 Internacional Circularity assessment Criticality assessment Early-stage evaluation Metal scrap Raw material Steel Sustainability index Dataset of the work 'A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: application in the steel industry' dataset