The Effect of Parameter Uncertainty on Blind Prediction of Np(V) Sorption onto Haematite using Surface Complexation Modelling

Still, the K_D concept of empirical distribution coefficients is the most often utilized approach for description of sorption phenomena. However, as an empirical concept it can not correctly portray the complex processes on the surfaces. A better approach is a Surface Complexation Models (SCM) capable of describing the sorption processes at the mineral-fluid interface on a scientific, quasi-thermodynamic basis. SCM are available in various versions, in which the Diffuse Double Layer Model (DDL), Constant Capacitance Model (CC) and Triple Layer Model (TL) are the most important and applied submodels.
Certainly, during the next decade SCM will replace K_D only in some simple systems or systems dominated by one mineral. However, SCM can help to verify measured K_D's, to identify the most sensitive experimental parameters, to assign uncertainty limits, to fill gaps difficult to access in sorption experiments, and to help to gain a better process understanding.
RES³T [1]– the Rossendorf Expert System for Surface and Sorption Thermodynamics - is a digitized version of a thermodynamic sorption database as required for the parametrisation of SCM, namely in risk assessment studies.
As an example to illustrate the effect of parameter uncertainty in blind predictions the Np(V) sorption onto haematite was selected.