Publications by Year: 2005

T. Baumann and Werth, C. J., “Visualization of colloid transport through heterogeneous porous media using magnetic resonance imaging,” Colloids and Surfaces A, vol. 265, no. 1-3, pp. 2–10, 2005. Publisher's VersionAbstract
The effects of heterogeneous grain packing on colloid transport were evaluated in flow-through columns using magnetic resonance imaging (MRI). Two columns were packed, each with a core of fine-grained silica gel surrounded by a shell of coarse-grained silica gel. In column 1, 600–850 μm silica gel was surrounded by 850–1000 μm silica gel. In column 2, 250–600 μm silica gel was surrounded by 850–1000 μm silica gel. Both columns were continuously purged with water and colloids were introduced as pulses.MRI images of column 1 showed that colloid transport in the core and shell was not distinguishable. However, colloid transport was slightly faster along the bottom of the column. T1-weighted images showed that small variations in the packing density of silica gel caused this effect. MRI images of column 2 showed that colloid transport in the core was much slower than colloid transport in the shell. Colloid exchange between the shell and the core was also observed.Colloid transport velocities and collision efficiencies were calculated from the images. In agreement with the visualization, velocities for column 1 increased from the top to bottom of the column and velocities for column 2 were greater in the shell than in the core. Collision efficiencies were calculated, but trends were not apparent because of the difficulty of applying filtration theory to heterogeneous media. Velocities from images were compared to those from conventional experiments where colloid concentrations were measured at the column effluent. While often comparable, results from the latter mask many of the complexities that control the overall rate of colloid transport. Since these complexities can give rise to very different transport behavior, it is critical to understand their effects in real systems. Hence, MRI is a technique that has the power to elucidate many of the small-scale processes that affect the behavior of colloids in the field.
S. Jeong and Werth, C. J., “Evaluation of methods to obtain geosorbent fractions enriched in carbonaceous materials that affect hydrophobic organic chemical sorption,” Environmental Science & Technology, vol. 39, no. 9, pp. 3279–3288, 2005. Publisher's VersionAbstract
To better understand sorption, separation methods are needed to enrich soils and sediments in one or more types of carbonaceous materials (CM), especially in fine grain materials where physical separation is not possible. We evaluated a series of chemical and thermal treatment methods by applying them to four different CMs prepared in our laboratory:  a humic acid (HA), a char, a soot, and a heat-treated soot (HN-soot). Before and after each treatment step, CM properties were evaluated including aqueous phase sorption with trichloroethene (TCE). Results indicate that treatment with hydrofluoric (HF) and hydrochloric acid (HCl) to remove silicate minerals, and with trifluoroacetic acid (TFA) to remove easily hydrolyzable organic matter, has relatively little effect on the humic acid mass (<19% change) and TCE sorption to this material. Subsequent treatment with NaOH to extract fulvic and humic acids results in almost complete removal of the humic acid mass (>92%) and has little to no effect on the masses of the char and two soots (<8% change) and TCE sorption to these materials. Treatment with acid dichromate to remove kerogen and humin also has little effect on masses of the char and soots (<16% change), but TCE sorption to these materials is significantly altered (by >10× in some cases), and there is strong evidence of surface oxidation based on X-ray photoelectron and diffuse reflectance Fourier transform infrared spectroscopy results. The last step, thermal treatment, which targets char removal, also destroys >96% of the soots pretreated with acid dichromate. However, when thermal treatment is applied to the original soots, <32% of these materials are destroyed. Thermal oxidation also affects sorption to one of the soots (by ~2× at low concentration), and surface oxidation is evident. These results suggest that treatment with HCl, HCl/HF, TFA, and NaOH can be applied to soils and sediments to obtain CM enrichment fractions for sorption evaluation, but that acid dichromate and heat treatment may not be appropriate for these purposes.
C. E. Knutson, Werth, C. J., and Valocchi, A. J., “Pore-scale simulation of biomass growth along the transverse mixing zone of a model two-dimensional porous medium,” Water Resources Research, vol. 41, no. 7, 2005. Publisher's VersionAbstract
The success of in situ bioremediation projects depends on the mixing of contaminants and nutrients in the presence of microbes. In this work, a pore-scale model is developed to simulate biomass growth that is controlled by the mixing of an electron donor and acceptor. A homogeneous packing of cylinders representing solid grains is used as the model two-dimensional porous medium. The system is initially seeded with microbes in computational cells located at grain-water interfaces. The solutes enter the system completely unmixed; each solute is input over one half of the inlet boundary. Solute mixing is controlled by molecular diffusion transverse to the flow direction, and solutes are biotransformed according to dual Monod kinetics only where biomass is present. Simulation of biomass growth requires calculation of the water flow field as well as transport and reaction of solutes. The lattice Boltzmann method is used to obtain the flow field. Transport and reaction of the solutes is modeled by a finite volume discretization of the advection-diffusion-reaction equation. Biomass is allowed to grow and spread by means of a cellular automata algorithm. Model parameters are systematically varied to understand their effects on biomass development. Base case parameter values are obtained from batch experiments reported in the literature and are modified to achieve agreement between simulation results and previously reported micromodel experimental results. The most significant mechanisms that control biomass development are shear strength of new biomass and solute degradation rates. The biomass growth model achieves good qualitative agreement with experimental results.