Surface complexation models: An evaluation of model parameter estimation using FITEQL and oxide mineral titration data

Abstract

The ability of surface complexation models (SCMs) to fit sets of titration data as a function of changes in model parameters was evaluated using FITEQL and acid-base titration data of α-FeOOH, α-Al 2O 3, and TiO 2. Three SCMs were evaluated: the triple-layer model (TLM), the constant capacitance model (CCM), and the diffuse-layer model (DLM). For all models evaluated, increasing the model input value for the total number of surface sites caused a decrease in the best-fit Log K values of the surface protolysis constants. In the case of the CCM, the best-fit surface protolysis constants were relatively insensitive to changes in the value of the capacitance fitting parameter, C 1, particularly for values of C 1 greater than 1.2 F/m 2. Similarly, the best-fit values of TLM surface electrolyte binding constants were less influenced by changes in the value of C 1 when C 1 was greater than 1.2 F/m 2. For a given C 1 value, the best-fit TLM values of the electrolyte binding constants were sensitive to changes in Δp K a up to Δp K a values of 3. For Δp K a values above 3, no changes in the best-fit electrolyte binding constants were observed. Effects of the quality and extent of titration data on the best-fit values for surface constants are discussed for each model. A method is suggested for choosing a unique set of parameter values for each of the models.