Modeling metal ion sorption to heterogeneous sorbents

摘要

Studies have demonstrated the importance of inorganic ion sorption processes in both natural environments and engineered systems. Recently, there has been a considerable interest in establishing risk-based cleanup standards for contaminated sites, a process that must consider the role of sorption processes in influencing contaminant migration pathways. Chemical equilibrium models have often been used to determine the migration pathways of toxic contaminants and the potential risk they pose. A common difficulty with these models is accurately simulating the interaction of metals with heterogeneous environmental materials, such as humic substances and soils. Environmental soils and sediments are assemblages of various minerals, colloids, organic debris and biota that form a complex medium for interaction with ions in the aqueous phase. This complex mixture of abioitc and biotic compounds often have been represented by discrete ligan models without electrostatics or by continuous distribution models. The distribution of binding sites as a function of binding strength is referred to as a sorbent's affinity spectrum. Electrostatic models in which the sorbent is represented by a combination of ligands having a discrete or continuous distribution of binding constants have also been developed. These models are capable in representing simple systems in which one or two aqueous chemical parameters are varied (e.g., metal binding vs. pH at fixed salt, ligand and metal concentration). However, as the data set becomes more complex, (e.g., simultaneous representation of proton and metal binding as aftion of pH, total salt, metal and ligand concentration) the task of developing a model that accurately describes sorption data is challenging. For environmental applications, it is the predictive capability of a model under varying chemical conditions that is of significance.