U(VI) adsorption on natural iron-coated sands: comparison of approaches for modeling adsorption on heterogeneous environmental materials

Abstract Adsorption of U(VI) on 6 samples of natural Fe-rich sands from Oyster, VA was studied over a range of U(VI) concentrations (0.1–100 μM), pH values (3–7.6), and dithionite–citrate–bicarbonate (DCB) extractable amounts of Fe (3.1–12.3 μmol/g). Four modeling approaches were applied to represent the U(VI) adsorption data. Model I was a two-site, diffuse double layer, surface complexation model based on data for synthetic ferrihydrite [Geochim. Cosmochim. Acta 58 (1994) 5465–5478]. Considering the magnitude of approximations necessary for application of the laboratory-based model to natural sands, Model I was surprisingly accurate, as determined by the goodness of fit parameter, χ 2 / N of 53.1–22.2. Model II was based on the reactions and diffuse double layer treatment of Model I, but was calibrated to a portion of U(VI) adsorption data for each sand, and then used to predict adsorption data for the same sand under different experimental conditions. Model II did not increase the accuracy of the predictions made with Model I, χ 2 / N of 42.4–27.6. Models III and IV were four-site affinity spectrum models, without an explicit electric double layer model or explicit surface hydrolysis reactions. Model III was based on a discrete log K spectrum approach, and Model IV was obtained from adjusting all surface stability constants and site concentrations for all surface sites. Models III and IV represented the U(VI) adsorption data with the greatest accuracy, χ 2 / N ranged from 13.8 to 4.4. Model I provides evidence supporting the practice of using pure phase thermodynamic reaction constants for describing the adsorption characteristics of environmentally important sorbents in certain simple cases. Yet, affinity spectrum approaches (Models III and IV) become increasingly important as more accurate interpolation of adsorption data is necessary, the sorbent becomes increasingly complex, or the range of experimental conditions expands.