Date of Completion
Iron Oxides, Surface Complexation Modeling, Surface Charge, MUSE, CD-MUSIC, Chromate, Adsorption
Nadine Kabengi (Associate Advisor)
Field of Study
Doctor of Philosophy
Iron oxides and hydroxides are highly reactive mineral phases in natural systems since they interact with pollutants, controlling their fate and transport in the environment. Goethite (GH) and hematite (HT) are the most abundant iron minerals in nature, while ferrihydrite (FH) is a nanomineral with high surface reactivity. Subsurface transport modeling has usually represented the adsorption processes by empirical relationships, such as distribution coefficients (Kd) or isotherm equations. However, empirical approaches cannot account for variable geochemical conditions. These effects can be addressed by the mechanistic surface complexation models (SCMs). So far, the application of SCMs has been limited mostly to the description of laboratory experiments, resulting in highly variable parameters even when a pure sorbent–ligand system is described. This limits their usefulness and transferability in reactive transport models.
This study is an attempt to bridge the gap between laboratory and field studies, but keep the predictive power of SCMs. The latter is achieved by analyzing several adsorption datasets systematically to extract unified parameters, and understand the driving forces leading to parameter variability. The optimization process is a problem itself that may lead to non-unique parameters. With this in mind, a hybridized optimization approach (MUSE algorithm), based on a multi–start algorithm combined with a local optimizer, has been developed to allow the simultaneous optimization of SCM parameters. A unified model for surface charge was developed to simulate the variable charging behavior of FH. The model was able to capture differences in both surface charge magnitude and points of zero net proton charge (PZNPCs). Finally, the ultimate purpose of this work was to study the adsorption of one ligand (i.e. chromate) on a group of iron oxides (FH, HT, and GH), and examine whether the complexation parameters can be represented by a unified framework. The results of this analysis showed that thermodynamic constants are highly dependent on the surface properties, an effect that can be quantified by the model calculations, while differences in adsorption energetics are also present under different surface coverages. The latter is reflected in thermodynamic parameters and added to the complexity of the model.
Bompoti, Nefeli Maria, "Modeling Iron Oxide Reactivity in the Environment" (2017). Doctoral Dissertations. 1676.