A novel sorbent, water treatment residual nanoparticles (nWTR), was synthesized and used to remove As(V) from water solutions. The kinetics and equilibrium of As(V) adsorption by nWTR were evaluated. The kinetic data for nWTR at 3 different pH values indicate that As(V) sorption is biphasic, is favored at low pH values, and followed the power function and first-order kinetics models fit. The results of the batch adsorption study showed that nWTR was effective in As(V) removal and its removal capability was 16 times higher than that of bulk WTR. Fourier transmission infrared (FTIR), SEM-EDX spectra, and As fractionation results indicate the crucial role of surface hydroxyl groups in As retention onto nWTR and the high capability of nWTR to immobilize As(V). The stability of As-nWTR surface complexes is suggested as less than 2% of adsorbed As(V) was released from nWTR after 4 consecutive desorption cycles.

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There is increasing interest in using water treatment residuals (WTRs) for heavy metals removal from wastewater due to their low cost, availability, and high efficiency in removing various pollutants. In this study, novel water treatment residuals nanoparticles (nWTRs) were prepared using high energy ball milling and used for efficient removal of Cd(II) in single- and multi-ion systems. The WTR nanoparticles demonstrated high removal efficiency for Cd from aqueous solution as the adsorption capacities of nWTR were 17 and 10 times higher than those of bulk WTR in single- and multielement systems, respectively. Noticeably, Cd(II) adsorption was clearly suppressed in the multi-ion system as Cu and Pb form the most stable monohydroxo complexes. Fourier transmission infrared (FTIR) analyses suggested the participation of OH−, O-Al-O, FeOH, and FeOOH entities in the adsorption process. The stability of Cd-nWTR surface complexes is evident as less than 0. 2% of adsorbed Cd(ll) was released at the highest Cd(II) concentration load after 4 consecutive desorption cycles. Moreover, the real efficiency of nWTR for Cd(II) removal from wastewater samples studied was calculated to be 98.35%. These results highlight the potential of nWTR for heavy metals removal from wastewater.

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