Caesium (Cs) is one of the most studied radionuclides in the fields of nuclear waste disposal and environmental sciences. The overall objective of this work is to improve the tools designed to describe and predict migration, retention, and bioaccumulation processes in the geosphere and the biosphere, particularly in the soil/solution soil/plant roots systems. Cs sorption on clay minerals has been extensively measured and modeled because these minerals control Cs mobility and (bio)availability in the environment.
A critical analysis of published experimental data on Cs sorption by clay minerals and natural clay materials along with the different models was performed in an attempt to elaborate and evaluate a generic model for Cs sorption. This work enabled us to propose a robust and parsimonious model for Cs sorption, which combines the surface complexation and cation exchange approaches invoking only two types of surface sites: frayed edge and exchange sites. Our model, referred to as the “1-pK DL/IE model”, takes into account the competition between Cs and other cations as well as the influence of the ionic strength and pH of the solution.
This model was successfully calibrated for Cs sorption on three reference clay minerals (illite, montmorillonite and kaolinite), in a wide range of Cs concentrations and physicochemical conditions. Using the same parameters, we tested our model on several natural clayey materials containing a single to several clay minerals. The goodness-of-fit obtained with natural materials containing a single clay mineral demonstrates the robustness of the model. The results obtained with natural mixed clay materials confirm the predictive capability of the model and also allowed us to test the sensitivity to the mineral composition of these materials (uncertainties). We found that illite is usually the most reactive clay mineral with respect to Cs sorption and that component additivity is applicable when the contribution of other clay minerals becomes non negligible. The whole set of model-measurement comparisons performed in this study provides a high level of confidence in the capabilities of the 1-pK DL/IE model as an interesting predictive tool.