Neptunium(V) sorption to vadose zone sediments: Reversible, not readily reducible, and predictable based on Fe-oxide content

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Abstract Neptunium (Np) is among the key risk-drivers at the Savannah River Site's (SRS) low-level waste disposal facility located in South Carolina. A series of studies were undertaken to identify and to model the key geochemical processes controlling Np sorption to SRS vadose zone sediments. The approach was to conduct Np(V) laboratory batch and flow studies using two sediments representing end-member depositional facies recovered beneath the disposal facility. Baseline distribution coefficients (Kd values; Np concentration ratio of sediment:porewater) were 9.05 ± 0.61 L kg−1 and 4.26 ± 0.24 L kg−1 for the clayey and sandy end-member sediments, respectively. The addition of natural organic matter (NOM) to the sediment resulted in only a two fold increase in the Kd values, most likely due to the formation of ternary sediment-NOM-Np complexes. None of the reduction treatments (ascorbic acid, dithionite, zero valent iron, hydrogen peroxide, and anaerobic atmosphere), including some long-term (71-day) equilibration experiments, resulted in significant increases in Kd values. This indicated that little to no reduction of Np(V) to the more strongly sorbing Np(IV) occurred. Among the key novel findings in this research was that batch desorption tests and stop-flow stir-cell kinetic experiments indicated that the Np(V) sorption was completely reversible. These observations were used to develop a simple conceptual model describing Np(V) sorption. The conceptual model described NpO2+ reversibly complexation to iron oxide coatings on the sediments. The model was successfully applied without any adjustable parameters to an independent set of experimental data, requiring only the dithionite-extractable Fe concentration from the independent dataset. There is no standard approach for quantifying reactive sorption site concentrations on composite materials (e.g., soils and sediments). In this study we proposed such a method based on an operationally defined fraction of the extractable iron. This parameterization approach was calibrated with two sediments then used to blindly and successfully predict sorption on another end-member soil. The successful modeling approach taken in this work 1) identified key reactions that are or are not influencing the system to develop a simple but appropriate conceptual model and 2) calibrated the fraction of extractable iron required for surface site density determination and used the calibrated model for blind predictions. This modeling approach could be used for other composite materials to allow for comparisons of the fraction of surface reactive extractable metals.