Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/10259/11199
Título
Dataset of the work 'A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: application in the steel industry'
Autor
Editorial
Universdad de Burgos
Fecha de publicación
2025-12-15
DOI
10.71486/mcts-0k15
Resumen
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'
Palabras clave
Circularity assessment
Criticality assessment
Early-stage evaluation
Metal scrap
Raw material
Steel
Sustainability index
Materia
Industria siderúrgica
Steel industry and trade
Residuos metálicos
Scrap metals
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