AbstractIn performance assessments, sorption of radionuclides dissolved in groundwater is mostly handled by the use of fixed Kd values. It has been well known that this approach is unsatisfying. Only during the last few years, however, tools have become available that make it possible to predict the actual Kd value in an aqueous solution that differs from the one in which the sorption properties were measured.One such approach is surface complexation (SC) that gives a detailed knowledge of the sorption properties. In SC, one tries to find what kinds of sorbed species are available on the surface and the thermodynamics for their formation from species in the bulk aqueous solution. Recently, a different approach, surface phase method (SP), has been developed. In SP, a thin layer including the surface is treated as a separate phase. In the bulk aqueous solution, the surface phase is treated as a virtual component, and from the chemical potential of this component, the sorption properties can be found.In the paper, we compare advantages and disadvantages of the two kinds of models. We also investigate the differences in predicted sorption properties of a number of radionuclides (Co, Np, Th and U). Furthermore, we discuss under which circumstances, one approach or the other is preferable.
Review of "ML for Surface Complexation Model Development"
