Hydrometallurgical strategies for the selective recovery of valuable metals from electric arc furnace dust (EAFD): A critical review.

Saved in:
Bibliographic Details
Title: Hydrometallurgical strategies for the selective recovery of valuable metals from electric arc furnace dust (EAFD): A critical review.
Authors: Pereira, Antonio Clareti1 (AUTHOR) claretipereira@gmail.com, Fonseca, Rafael Bruno da Cunha2 (AUTHOR), dos Santos, José Rubens3 (AUTHOR)
Source: Canadian Journal of Chemical Engineering. May2026, Vol. 104 Issue 5, p2225-2241. 17p.
Subjects: Hydrometallurgy, Leaching, Metal recycling, Industrial wastes, Lead, Cadmium, Zinc, Solvent extraction
Abstract: Electric arc furnace dust (EAFD), a hazardous byproduct of steelmaking, is increasingly recognized as a secondary resource for critical metals, including zinc (Zn), lead (Pb), and cadmium (Cd). This critical review examines advancements in the hydrometallurgical processing of EAFD, with a focus on the physicochemical properties of dust, leaching mechanisms, selective complexation, purification techniques, and product recovery. Acidic, alkaline, and complexing agents are compared in terms of efficiency, selectivity, and environmental performance, with sulphuric acid and ammonia‐based systems demonstrating high zinc recovery. Downstream purification methods, such as solvent extraction and electrowinning, are examined in the context of metal separation and sustainability. Economic and environmental assessments highlight the potential for reducing carbon footprint and hazardous waste through optimized hydrometallurgical routes. Current challenges, including reagent recyclability and the management of iron‐rich residues, are critically analyzed, and future research directions are outlined. The review provides a comprehensive framework for advancing EAFD valorization through cleaner, more efficient hydrometallurgical strategies. [ABSTRACT FROM AUTHOR]
Copyright of Canadian Journal of Chemical Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Be the first to leave a comment!
You must be logged in first