Gary P. Curtis

Experimental Investigation and Modeling of Uranium (VI) Transport Under Variable Chemical Conditions

The transport of adsorbing and complexing metal ions in porous media was investigated with a series of batch and column experiments and with reactive solute transport modeling. Pulses of solutions containing U(VI) were pumped through columns filled with quartz grains, and the breakthrough of U(VI) was studied as a function of variable solution composition (pH, total U(VI) concentration, total fluoride concentration, and pH-buffering capacity). Decreasing pH and the formation of nonadsorbing aqueous complexes with fluoride increased U(VI) mobility. A transport simulation with surface complexation model (SCM) parameters estimated from batch experiments was able to predict U(VI) retardation in the column experiments within 30%. SCM parameters were also estimated directly from transport data, using the results of three column experiments collected at different pH and U(VI) pulse concentrations. SCM formulations of varying complexity (multiple surface types and reaction stoichiometries) were tested to examine the trade-off between model simplicity and goodness of fit to breakthrough. A two-site model (weak- and strong-binding sites) with three surface complexation reactions fit these transport data well. With this reaction set the model was able to predict (1) the effects of fluoride complexation on U(VI) retardation at two different pH values and (2) the effects of temporal variability of pH on U(VI) transport caused by low pH buffering. The results illustrate the utility of the SCM approach in modeling the transport of adsorbing inorganic solutes under variable chemical conditions.

Simulation of reactive transport of uranium(VI) in groundwater with variable chemical conditions

[1] The reactive transport of U(VI) in a shallow alluvial aquifer beneath a former U(VI) mill located near Naturita, CO, was simulated using a surface complexation model (SCM) to describe U(VI) adsorption. The groundwater had variable U(VI) concentrations (0.01-20 μM), variable alkalinity (2.5-18 meq/L), and a nearly constant pH equal to 7.1. U(VI) K D values decreased with increasing U(VI) and alkalinity, and these parameters were more important than sediment variability in controlling K D values. Reactive transport simulations were fit to the observed U(VI) and alkalinity by varying the concentration of U(VI) and alkalinity in recharge at the source area. Simulated K D values varied temporally and spatially because of the differential transport of U(VI) and alkalinity and the nonlinearity of U(VI) adsorption. The model also simulated the observed U(VI) tailing, which would not be expected from a constant K D model. The simulated U(VI) concentrations were sensitive to the recharge flux because of the increased flux of U(VI) to the aquifer. The geochemical behavior of U(VI) was most sensitive to the alkalinity and was relatively insensitive to pH.

Comparison of approaches for simulating reactive solute transport involving organic degradation reactions by multiple terminal electron acceptors

Reactive solute transport models are useful tools for analyzing complex geochemical behavior resulting from biodegradation of organic compounds by multiple terminal electron acceptors (TEAPs). The usual approach of simulating the reactions of multiple TEAPs by an irreversible Monod rate law was compared with simulations that assumed a partial local equilibrium or kinetically controlled reactions subject to the requirement that the Gibbs free energy of reaction (ΔG) was either less than zero or less than a threshold value. Simulations were performed using a single organic substrate and O2, FeOOH, SO4-2 and CO2 as the terminal electron acceptors. It was assumed that the organic substrate was slowly and completely fermented to CO2 and H2 and the H2 was oxidized by the TEAPs. Simulations using the Monod approach showed that this irreversible rate law forced the reduction of both FeOOH and CO2 to proceed even when ΔG was positive. This resulted in an over prediction in amount of FeOOH reduced to Fe(II) in parts of the domain and it resulted in large errors in pH. Simulations using mass action kinetics agreed with equilibrium simulations for the case of large rate constants. The extent of reductive dissolution of FeOOH was strongly dependent on the thermodynamic stability of the FeOOH phase. Transport simulations performed assuming that the reactions of the TEAPs stopped when ΔG exceeded a threshold value showed that only simulated H2 concentrations were affected if the threshold value was the same for each TEAP. Simulated H2 concentrations were controlled by the fastest reaction of the TEAP, but it was common for reactions to occur concomitantly rather than sequentially.

Assessing conceptual models for subsurface reactive transport of inorganic contaminants

In many subsurface situations where human health and environmental quality are at risk (e.g., contaminant hydrogeology petroleum extraction, carbon sequestration, etc.),scientists and engineers are being asked by federal agency decision-makers to predict the fate of chemical species under conditions where both reactions and transport are processes of first-order importance. In 2002, a working group (WG) was formed by representatives of the U.S. Geological Survey, Environmental Protection Agency, Department of Energy Nuclear Regulatory Commission, Department of Agriculture, and Army Engineer Research and Development Center to assess the role of reactive transport modeling (RTM) in addressing these situations. Specifically the goals of the WG are to (1) evaluate the state of the art in conceptual model development and parameterization for RTM, as applied to soil,vadose zone, and groundwater systems, and (2) prioritize research directions that would enhance the practical utility of RTM.

Assessment of parametric uncertainty for groundwater reactive transport modeling

The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM(zs)) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM(ZS)-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood functions, improve model calibration, and reduce predictive uncertainty in other groundwater reactive transport and environmental modeling.

Kinetics of Homogeneous and Surface-Catalyzed Mercury(II) Reduction by Iron(II)

Production of elemental mercury, Hg(0), via Hg(II) reduction is an important pathway that should be considered when studying Hg fate in environment. We conducted a kinetic study of abiotic homogeneous and surface-catalyzed Hg(0) production by Fe(II) under dark anoxic conditions. Hg(0) production rate, from initial 50 pM Hg(II) concentration, increased with increasing pH (5.5-8.1) and aqueous Fe(II) concentration (0.1-1 mM). The homogeneous rate was best described by the expression, r(hom) = k(hom) [FeOH(+)] [Hg(OH)2]; k(hom) = 7.19 × 10(+3) L (mol min)(-1). Compared to the homogeneous case, goethite (α-FeOOH) and hematite (α-Fe2O3) increased and γ-alumina (γ-Al2O3) decreased the Hg(0) production rate. Heterogeneous Hg(0) production rates were well described by a model incorporating equilibrium Fe(II) adsorption, rate-limited Hg(II) reduction by dissolved and adsorbed Fe(II), and rate-limited Hg(II) adsorption. Equilibrium Fe(II) adsorption was described using a surface complexation model calibrated with previously published experimental data. The Hg(0) production rate was well described by the expression r(het) = k(het) [>SOFe((II))] [Hg(OH)2], where >SOFe((II)) is the total adsorbed Fe(II) concentration; k(het) values were 5.36 × 10(+3), 4.69 × 10(+3), and 1.08 × 10(+2) L (mol min)(-1) for hematite, goethite, and γ-alumina, respectively. Hg(0) production coupled to reduction by Fe(II) may be an important process to consider in ecosystem Hg studies.

A computer program for uncertainty analysis integrating regression and Bayesian methods

This work develops a new functionality in UCODE_2014 to evaluate Bayesian credible intervals using the Markov Chain Monte Carlo (MCMC) method. The MCMC capability in UCODE_2014 is based on the FORTRAN version of the differential evolution adaptive Metropolis (DREAM) algorithm of Vrugt et al. (2009), which estimates the posterior probability density function of model parameters in high-dimensional and multimodal sampling problems. The UCODE MCMC capability provides eleven prior probability distributions and three ways to initialize the sampling process. It evaluates parametric and predictive uncertainties and it has parallel computing capability based on multiple chains to accelerate the sampling process. This paper tests and demonstrates the MCMC capability using a 10-dimensional multimodal mathematical function, a 100-dimensional Gaussian function, and a groundwater reactive transport model. The use of the MCMC capability is made straightforward and flexible by adopting the JUPITER API protocol. With the new MCMC capability, UCODE_2014 can be used to calculate three types of uncertainty intervals, which all can account for prior information: (1) linear confidence intervals which require linearity and Gaussian error assumptions and typically 10s-100s of highly parallelizable model runs after optimization, (2) nonlinear confidence intervals which require a smooth objective function surface and Gaussian observation error assumptions and typically 100s-1,000s of partially parallelizable model runs after optimization, and (3) MCMC Bayesian credible intervals which require few assumptions and commonly 10,000s-100,000s or more partially parallelizable model runs. Ready access allows users to select methods best suited to their work, and to compare methods in many circumstances.

Influence of variable chemical conditions on EDTA-enhanced transport of metal ions in mildly acidic groundwater

Adsorption of Ni and Pb on aquifer sediments from Cape Cod, Massachusetts, USA increased with increasing pH and metal-ion concentration. Adsorption could be described quantitatively using a semi-mechanistic surface complexation model (SCM), in which adsorption is described using chemical reactions between metal ions and adsorption sites. Equilibrium reactive transport simulations incorporating the SCMs, formation of metal-ion-EDTA complexes, and either Fe(III)-oxyhydroxide solubility or Zn desorption from sediments identified important factors responsible for trends observed during transport experiments conducted with EDTA complexes of Ni, Zn, and Pb in the Cape Cod aquifer. Dissociation of Pb-EDTA by Fe(III) is more favorable than Ni-EDTA because of differences in Ni- and Pb-adsorption to the sediments. Dissociation of Ni-EDTA becomes more favorable with decreasing Ni-EDTA concentration and decreasing pH. In contrast to Ni, Pb-EDTA can be dissociated by Zn desorbed from the aquifer sediments. Variability in adsorbed Zn concentrations has a large impact on Pb-EDTA dissociation.

Bioremediation in Fractured Rock: 1. Modeling to Inform Design, Monitoring, and Expectations

Field characterization of a trichloroethene (TCE) source area in fractured mudstones produced a detailed understanding of the geology, contaminant distribution in fractures and the rock matrix, and hydraulic and transport properties. Groundwater flow and chemical transport modeling that synthesized the field characterization information proved critical for designing bioremediation of the source area. The planned bioremediation involved injecting emulsified vegetable oil and bacteria to enhance the naturally occurring biodegradation of TCE. The flow and transport modeling showed that injection will spread amendments widely over a zone of lower-permeability fractures, with long residence times expected because of small velocities after injection and sorption of emulsified vegetable oil onto solids. Amendments transported out of this zone will be diluted by groundwater flux from other areas, limiting bioremediation effectiveness downgradient. At nearby pumping wells, further dilution is expected to make bioremediation effects undetectable in the pumped water. The results emphasize that in fracture-dominated flow regimes, the extent of injected amendments cannot be conceptualized using simple homogeneous models of groundwater flow commonly adopted to design injections in unconsolidated porous media (e.g., radial diverging or dipole flow regimes). Instead, it is important to synthesize site characterization information using a groundwater flow model that includes discrete features representing high- and low-permeability fractures. This type of model accounts for the highly heterogeneous hydraulic conductivity and groundwater fluxes in fractured-rock aquifers, and facilitates designing injection strategies that target specific volumes of the aquifer and maximize the distribution of amendments over these volumes.

Bioremediation in Fractured Rock: 2. Mobilization of Chloroethene Compounds from the Rock Matrix

A mass balance is formulated to evaluate the mobilization of chlorinated ethene compounds (CE) from the rock matrix of a fractured mudstone aquifer under pre- and postbioremediation conditions. The analysis relies on a sparse number of monitoring locations and is constrained by a detailed description of the groundwater flow regime. Groundwater flow modeling developed under the site characterization identified groundwater fluxes to formulate the CE mass balance in the rock volume exposed to the injected remediation amendments. Differences in the CE fluxes into and out of the rock volume identify the total CE mobilized from diffusion, desorption, and nonaqueous phase liquid dissolution under pre- and postinjection conditions. The initial CE mass in the rock matrix prior to remediation is estimated using analyses of CE in rock core. The CE mass mobilized per year under preinjection conditions is small relative to the total CE mass in the rock, indicating that current pump-and-treat and natural attenuation conditions are likely to require hundreds of years to achieve groundwater concentrations that meet regulatory guidelines. The postinjection CE mobilization rate increased by approximately an order of magnitude over the 5 years of monitoring after the amendment injection. This rate is likely to decrease and additional remediation applications over several decades would still be needed to reduce CE mass in the rock matrix to levels where groundwater concentrations in fractures achieve regulatory standards.