Copper–gold mining in the eastern Alps, Austria, has produced sulfide-rich tailings that continue to release arsenic (As) into the environment. This study examined the effectiveness of removing arsenic from mining waste using various chemical extractants, nanoparticle (NP) dosages, and different sample grain sizes. The goals are to extract arsenic and produce a concentrate for recovering valuable metals, such as copper and gold, through metallurgical processes. This paper presents an integrated experimental framework designed to simulate realistic remediation scenarios using hematite nanoparticles (HMNPs). Multiple extractants—ultrapure water (UPW), nitric acid (HNO₃), monosodium dihydrogen phosphate (NaH₂PO₄), and hydrogen peroxide (H₂O₂)—were used to explore arsenic mobilization under different chemical stress conditions. Among the tested extractants, 0.1 M HNO₃ showed the highest arsenic removal efficiency, significantly outperforming UPW, 0.1 M NaH₂PO₄, and 3% H₂O₂. The addition of NPs improved overall arsenic removal; however, the efficiency did not increase proportionally with higher NP concentrations. A concentration of 0.05 HNPs g/L resulted in slightly higher arsenic removal rates compared to 2.5 HNPs g/L and 5 HNPs g/L, likely due to particle aggregation at higher concentrations, which reduced the available reactive surface area. The texture of the mining waste also influenced removal efficiency. Finer particles promoted greater arsenic release under the H₂O₂ + HNP treatment, whereas coarser particles showed better responses to UPW and NaH₂PO₄. In contrast, HNO₃ consistently delivered high removal efficiencies across all particle sizes by directly dissolving the mineral compositions. The distinct oxyanion behavior of As underscores the necessity for strong extractants or NP-assisted approaches, as conventional methods optimized for cationic metals are less effective. Overall, HNO₃ proved to be the most effective single extractant, achieving removal efficiencies of up to 87.6% for As, 63.8% for Zn, 90.7% for Pb, and 85.97% for Cu. Post-treatment filtrates were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Instrumental Neutron Activation Analysis (INAA) to quantify As removal.
Copper–gold mining in the eastern Alps, Austria, has produced sulfide-rich tailings that continue to release arsenic (As) into the environment. This study examined the effectiveness of removing arsenic from mining waste using various chemical extractants, nanoparticle (NP) dosages, and different sample grain sizes. The goals are to extract arsenic and produce a concentrate for recovering valuable metals, such as copper and gold, through metallurgical processes. This paper presents an integrated experimental framework designed to simulate realistic remediation scenarios using hematite nanoparticles (HMNPs). Multiple extractants-ultrapure water (UPW), nitric acid (HNO₃), monosodium dihydrogen phosphate (NaH₂PO₄), and hydrogen peroxide (H₂O₂)-were used to explore arsenic mobilization under different chemical stress conditions. Among the tested extractants, 0.1 M HNO₃ showed the highest arsenic removal efficiency, significantly outperforming UPW, 0.1 M NaH₂PO₄, and 3% H₂O₂. The addition of NPs improved overall arsenic removal; however, the efficiency did not increase proportionally with higher NP concentrations. A concentration of 0.05 HNPs g/L resulted in slightly higher arsenic removal rates compared to 2.5 HNPs g/L and 5 HNPs g/L, likely due to particle aggregation at higher concentrations, which reduced the available reactive surface area. The texture of the mining waste also influenced removal efficiency. Finer particles promoted greater arsenic release under the H₂O₂ + HNP treatment, whereas coarser particles showed better responses to UPW and NaH₂PO₄. In contrast, HNO₃ consistently delivered high removal efficiencies across all particle sizes by directly dissolving the mineral compositions. The distinct oxyanion behavior of As underscores the necessity for strong extractants or NP-assisted approaches, as conventional methods optimized for cationic metals are less effective. Overall, HNO₃ proved to be the most effective single extractant, achieving removal efficiencies of up to 87.6% for As, 63.8% for Zn, 90.7% for Pb, and 85.97% for Cu. Post-treatment filtrates were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Instrumental Neutron Activation Analysis (INAA) to quantify As removal.