The aim of this work was to experimentally and theoretically study some surface complexation models and how well these can be applied to a simple system. This is done while keeping in mind the interest in including some type of chemical model in performance assessment calculations for much more complex systems. One matter if importance has been that it should be possible to determine all the input parameters that affect the prediction of the sorption. This work contains studies of the sorption of five different cations, and the results have been interpreted in terms of surface complexation models. Sorption has been studied as a function of pH, concentration of sorbing cation and ionic strength using a radioactive tracer. The results of the sorption studies are presented as the distribution ratio with respect to surface area (Ka) between the phases as a function of pH or concentration. Some comparisons of the results are made with other sorption studies of similar character in the literature. None of the cations studied in this work have shown a dependence on ionic strength. Different surface complexation modeling approaches were employed in this work. All the sorption data on TiO2) were fitted with a non electrostatic model, which does not include the effect of the charge build-up of the surface on the sorption. The input parameters of the surface complexation models are discussed and the impact of these on the fitting of the models to the data have been examined. To investigate the effect of some parameters that are difficult to determine experimentally, their values have been varied in the fitting. It was found that a simple 1-pK non electrostatic model could fit all the sorption data onto TiO2 satisfactorily with no indeterminable input parameters. So far, the model might thus be useful. However, the model was not able to fit the sorption behaviour at high concentrations. If a model is to be employed in such a case, it must be extended by including some kind of surface precipitation or other reaction to be able to model the observed isotherm
