Enhanced characterisation for the management of industrial steel processing by products: potential of sequential...

There is a pressing need for innovative waste management approaches as environmental regulations become more stringent worldwide alongside increasing demand for a more circular economy. Sequential chemical extraction (SE) analysis, which has previously been applied to environmental media such as soils and sediments, offers the potential to provide an understanding of the composition of solid steel processing by products, aiding the waste classification process and improving environmental protection. The definition of seven-phase associations through a SE method evaluated in this study were for (1) water soluble, (2) ion exchangeable, (3) carbonate, (4) amorphous Fe-Mn oxides, (5) crystalline Fe-Mn oxides, (6) sulphides and (7) silicate residues. Steel waste by-products (flue dust and filter cake) were evaluated for both extracted components (ICP analysis) and residual phases (using powder X-ray diffraction, SEM and FTIR), to model the transformations taking place during extraction. The presence and removal of important potentially toxic element (PTE) host solid phases were confirmed during extraction. The SE protocol provides key information, particularly for the association of potentially toxic elements with the first three extracts, which are most sensitive in waste management processes. The water-soluble phase is the most available followed by ion-exchangeable and carbonate fractions, all representing phases more sensitive to environmental change, in particular to pH. This study demonstrates that the distribution of potentially toxic elements such as zinc, lead and copper between sensitive and immobile phases can be reliably obtained in technological process by-products. We demonstrate that despite heterogeneity as a major variable, even for fine particulate matter, SE can provide more refined classification with information to identify reuse potential and ultimately minimise hazardous waste streams.