Recycling plays a vital role in preserving resources like steel and consequently in a circular economy. Scrap dealers and steel mills, the main business units in this system, often encounter opposing financial and sustainability incentives in using scrap as feedstock because regular sorting and scrap-preparation infrastructure cannot deal with the increasing complexity of steel scrap. Mismatches between the inputs and the target composition of the recycled steel result in trade-offs that favor the economics at the expense of resource efficiency. By examining literature and interviewing several actors, different scrap characteristics were identified as dimensions of scrap quality. Quality is typically associated with chemical composition, which is important, but this study aims to elaborate the concept of quality further and to connect it to the realities of scrapyard operations. Industry actors have different definitions for desired content, physical condition, shape and size, and homogeneity, based on their needs. Very few studies examine these details. Additionally, the relationship of quality and the level of information about the characteristics of the material was established. Having more definitive information on scrap increases opportunities for resource-efficient actions. This work offers an alternative perspective on how to address issues pertinent to recycling. Graphical Abstract

The current nature of steel design and production is a response to meet increasingly demanding applications but without much consideration of end-of-life scenarios. The scrap handling infrastructure, particularly the characterization and sorting, is unable to match the complexity of scrapped products. This is manifested in problems of intermixing and contamination in the scrap flows, especially for obsolete scrap. Also, the segmentation of scrap classes in standards with respect to chemical compositions is based on tolerance ranges. Thus, variation in scrap composition exists even within the same scrap type. This study applies the concept of expected value of perfect information (EPVI) to the context of steel recycling. More specifically, it sets out to examine the difference between having partial and full information on scrap composition by using a raw material optimization software. Three different scenarios with different constraints were used to appraise this difference in terms of production and excess costs. With access to perfect information, production costs decreased by 8–10%, and excess costs became negligible. Overall, comparing the respective results gave meaningful insights on the value of reestablishing the compositional information of scrap at the end of its use phase. Furthermore, the results provided relevant findings and contribute to the ongoing discussions on the seemingly disparate prioritization of economic and environmental incentives with respect to the recycling of steel.