Removal mechanism of arsenic (V) by stainless steel slags obtained from scrap metal recyclingShow others and affiliations
2020 (English)In: Journal of Environmental Chemical Engineering, E-ISSN 2213-3437, Vol. 8, no 4, article id 103833Article in journal (Refereed) Published
Abstract [en]
With this study, the removal mechanisms of arsenate by steel slag and its potential for treatment of contaminated water were elucidated. While original slag showed a poor fit to the Langmuir equation (R2 = 0.960), washed slag (the original slag is washed by low pH water solutions to remove readily soluble oxides) conformed better (R2 = 0.995). An initial pH of 2.0 give optimal adsorption, with a strong impact from the chemical speciation observed with highest efficiency for the fully protonated (OH)3AsO form. Adsorption capacity of the slag is 4.0 mg g−1, while together with precipitation the retention capacity reaches 13.7 mg g−1. However, removal by precipitation is a non-steady process due to re-dissolution of Ca3(AsO4)2(s). The washed slag shows a similar adsorption capacity to the original one but has not as strong alkaline properties. Batch experiment shows fast adsorption kinetics and column loading tests indicate an instant adsorption kinetics with 80 % As(V) removal for a 10 mg L−1 As(V) solution by 1.0 g of washed slag using a solution flowrate of 1 mL min−1. Common ions like sulfate, carbonate, chloride, iron(III), humic acid and fulvic acid do not significantly interfere with the removal efficiency. In combination with limited hazardous metals leaching, the slag is thus appropriate for use as a filter material for treatment of contaminated water and it has been successfully applied as filter material for treatment of arsenate spiked natural water sample with average removal efficiency of 84 % (solid to liquid ratio of 200).
Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 8, no 4, article id 103833
Keywords [en]
Arsenic, Steel slag, Contaminated waters, Precipitation, Adsorption
National Category
Environmental Sciences
Identifiers
URN: urn:nbn:se:oru:diva-84680DOI: 10.1016/j.jece.2020.103833ISI: 000563932900004Scopus ID: 2-s2.0-85086509805OAI: oai:DiVA.org:oru-84680DiVA, id: diva2:1457373
Note
Funding Agencies:
MINRENT project (Vinnova, Swedens innovation agency) 2016-02830
EnForce profile (KKS, The Knowledge Foundation) 20160019
Faculty of Business, Science and Engineering at Örebro University
2020-08-112020-08-112023-12-08Bibliographically approved