Experimental and Modeling Investigation of Arsenate adsorption on Synthetic Iron-coated sand

Abstract

Arsenic is an environmental contaminant of worldwide concern due its high toxicity and presence in groundwater aquifers. Adsorption of arsenic onto metal-oxides is an important phenomenon that locally controls the transport of arsenic in groundwater systems. In this study, we have investigated adsorption of arsenic(V) onto iron (goethite) coated sands. We also developed novel methods to scale the adsorption models. The study is divided into three phases: (i) In the first phase, we developed a scalable surface complexation modeling framework for predicting arsenic(V) adsorption onto various types of iron (goethite) coated sands. We first synthesized four different types of goethite-coated sands with iron content varying by nearly an order of magnitude and generated adsorption isotherms and pH edges for these four sands. We then used experimental data from one of the sands to develop a surface complexation model for the sand. We then scaled the surface complexation model developed for the sand, based on measured surface site density values, to predict adsorption onto the three other sands using the scaling procedure we developed. In addition, we also scaled the model to make predictions for several other arsenate-goethite adsorption datasets available in literature. The scaled models gave successful predictions for all datasets, with an average error of less than 5%, as quantified using RMSE values.

(ii) Currently there are no suitable experimental setups available for studying equilibrium-controlled geochemical reactive transport. In the second phase of the study, we developed a new experimental setup to study equilibrium- reactive transport of arsenate on goethite-coated sands. The proposed experimental setup, identified as the sequential equilibration reactor (SER) system, consists of several equilibrium batch reactors that are linked in series. The reactors are operated in a sequential manner analogous to the operations performed in a one-dimensional numerical model. Arsenic(V) solution is introduced into the first reactor and is allowed to react until equilibrium is reached in the first reactor. The solution phase is then transferred to the second reactor. This process is repeated until the solution reaches the last reactor. The effluent from the last reactor is analyzed. We conducted several SER experiments to study equilibrium arsenic transport under a wide range of pH, solid/solution ratio, and concentration conditions. The experimental datasets generated were also used to test whether the surface complexation models developed in the first phase were able to model the equilibrium reactive transport observed in the sequential equilibration reactor system. (iii) In the third phase of the study, we developed a novel Unified Langmuir-Freundlich (ULF) model, to describe pH-dependent arsenate adsorption on goethite-coated sands. The ULF model was integrated within a semi-analytical solution to predict arsenate transport observed in SER experiments. The semi-analytical solution was then validated by using experimental datasets from SER experiments completed at various pH, solid/solution ratio, and concentration conditions. The predictions form the ULF isotherm based semi-analytical model matched with surface complexation model predictions. The approach was further tested by recreating a well-known benchmark problem (Cederberg et al., 1985). The ULF isotherm-based transport codes were more than 10 times faster than surface-complexation-coupled transport codes.

Overall, the study has made the following three contributions to the field: 1) Development of scalable surface complexation modeling framework for arsenic-goethite system 2) A new experimental system to study equilibrium-controlled reactive transport problems 3) A unified pH-dependent isotherm model and a semi-analytical modeling framework to predict equilibrium-controlled reactive transport at different pH values.