The Dynamics of Per- and Polyfluoroalkyl Substances (PFAS) at Interfaces in Porous Media: A Computational Roadmap from Nanoscale Molecular Dynamics Simulation to Macroscale Modeling.

Managing and remediating perfluoroalkyl and polyfluoroalkyl substance (PFAS) contaminated sites remains challenging. The major reasons are the complexity of geological media, partly unknown dynamics of the PFAS in different phases and at fluid-fluid and fluid-solid interfaces, and the presence of cocontaminants such as nonaqueous phase liquids (NAPLs). Critical knowledge gaps exist in understanding the behavior and fate of PFAS in vadose and saturated zones and in other porous media such as concrete and asphalt. The complexity of PFAS-surface interactions warrants the use of advanced characterization and computational tools to understand and quantify nanoscale behavior of the molecules. This can then be upscaled to the microscale to develop a constitutive relationship, in particular to distinguish between surface and bulk diffusion. The dominance of surface diffusion compared to bulk diffusion results in the solutocapillary Marangoni effect, which has not been considered while investigating the fate of PFAS. Without a deep understanding of these phenomena, derivation of constitutive relationships is challenging. The current Darcy scale mass-transfer models use constitutive relationships derived from either experiments or field measurements, which makes their applicability potentially limited. Here we review current efforts and propose a roadmap for developing Darcy scale transport equations for PFAS. We find that this needs to be based on systematic upscaling of both experimental and computational studies from nano- to microscales. We highlight recent efforts to undertake molecular dynamics simulations on problems with similar levels of complexity and explore the feasibility of conducting nanoscale simulations on PFAS dynamics at the interface of fluid pairs.

Relating Darcy-Scale Chemical Reaction Order to Pore-Scale Spatial Heterogeneity.

Due to spatial scaling effects, there is a discrepancy in mineral dissolution rates measured at different spatial scales. Many reasons for this spatial scaling effect can be given. We investigate one such reason, i.e., how pore-scale spatial heterogeneity in porous media affects overall mineral dissolution rates. Using the bundle-of-tubes model as an analogy for porous media, we show that the Darcy-scale reaction order increases as the statistical similarity between the pore sizes and the effective-surface-area ratio of the porous sample decreases. The analytical results quantify mineral spatial heterogeneity using the Darcy-scale reaction order and give a mechanistic explanation to the usage of reaction order in Darcy-scale modeling. The relation is used as a constitutive relation of reactive transport at the Darcy scale. We test the constitutive relation by simulating flow-through experiments. The proposed constitutive relation is able to model the solute breakthrough curve of the simulations. Our results imply that we can infer mineral spatial heterogeneity of a porous media using measured solute concentration over time in a flow-through dissolution experiment.

Toward a Spatiotemporal Understanding of Dolomite Dissolution in Sandstone by CO2-Enriched Brine Circulation.

In this study, we introduce a stochastic method to delineate the mineral effective surface area (ESA) evolution during a recycling reactive flow-through transport experiment on a sandstone under geologic reservoir conditions, with a focus on the dissolution of its dolomite cement, Ca1.05Mg0.75Fe0.2(CO3)2. CO2-enriched brine was circulated through this sandstone specimen for 137 cycles (∼270 h) to examine the evolution of in situ hydraulic properties and CO2-enriched brine-dolomite geochemical reactions. The bulk permeability of the sandstone specimen decreased from 356 mD before the reaction to 139 mD after the reaction, while porosity increased from 21.9 to 23.2% due to a solid volume loss of 0.25 mL. Chemical analyses on experimental effluents during the first cycle yielded a dolomite reactivity of ∼2.45 mmol m-3 s-1, a corresponding sample-averaged ESA of ∼8.86 × 10-4 m2/g, and an ESA coefficient of 1.36 × 10-2, indicating limited participation of the physically exposed mineral surface area. As the dissolution reaction progressed, the ESA is observed to first increase and then decrease. This change in ESA can be qualitatively reproduced employing scanning electron microscopy-image-based stochastic analyses on dolomite dissolution. These results provide a new approach to analyze and upscale the ESA during geochemical reactions, which are involved in a wide range of geoengineering operations.

Tomographic Reservoir Imaging with DNA-Labeled Silica Nanotracers: The First Field Validation.

This study presents the first field validation of using DNA-labeled silica nanoparticles as tracers to image subsurface reservoirs by travel time based tomography. During a field campaign in Switzerland, we performed short-pulse tracer tests under a forced hydraulic head gradient to conduct a multisource-multireceiver tracer test and tomographic inversion, determining the two-dimensional hydraulic conductivity field between two vertical wells. Together with three traditional solute dye tracers, we injected spherical silica nanotracers, encoded with synthetic DNA molecules, which are protected by a silica layer against damage due to chemicals, microorganisms, and enzymes. Temporal moment analyses of the recorded tracer concentration breakthrough curves (BTCs) indicate higher mass recovery, less mean residence time, and smaller dispersion of the DNA-labeled nanotracers, compared to solute dye tracers. Importantly, travel time based tomography, using nanotracer BTCs, yields a satisfactory hydraulic conductivity tomogram, validated by the dye tracer results and previous field investigations. These advantages of DNA-labeled nanotracers, in comparison to traditional solute dye tracers, make them well-suited for tomographic reservoir characterizations in fields such as hydrogeology, petroleum engineering, and geothermal energy, particularly with respect to resolving preferential flow paths or the heterogeneity of contact surfaces or by enabling source zone characterizations of dense nonaqueous phase liquids.

Silica-Encapsulated DNA-Based Tracers for Aquifer Characterization.

Environmental tracing is a direct way to characterize aquifers, evaluate the solute transfer parameter in underground reservoirs, and track contamination. By performing multitracer tests, and translating the tracer breakthrough times into tomographic maps, key parameters such as a reservoir's effective porosity and permeability field may be obtained. DNA, with its modular design, allows the generation of a virtually unlimited number of distinguishable tracers. To overcome the insufficient DNA stability due to microbial activity, heat, and chemical stress, we present a method to encapsulated DNA into silica with control over the particle size. The reliability of DNA quantification is improved by the sample preservation with NaN3 and particle redispersion strategies. In both sand column and unconsolidated aquifer experiments, DNA-based particle tracers exhibited slightly earlier and sharper breakthrough than the traditional solute tracer uranine. The reason behind this observation is the size exclusion effect, whereby larger tracer particles are excluded from small pores, and are therefore transported with higher average velocity, which is pore size-dependent. Identical surface properties, and thus flow behavior, makes the new material an attractive tracer to characterize sandy groundwater reservoirs or to track multiple sources of contaminants with high spatial resolution.

Experimental observation of permeability changes in dolomite at CO2 sequestration conditions.

Injection of cool CO2 into geothermally warm carbonate reservoirs for storage or geothermal energy production may lower near-well temperature and lead to mass transfer along flow paths leading away from the well. To investigate this process, a dolomite core was subjected to a 650 h, high pressure, CO2 saturated, flow-through experiment. Permeability increased from 10(-15.9) to 10(-15.2) m(2) over the initial 216 h at 21 °C, decreased to 10(-16.2) m(2) over 289 h at 50 °C, largely due to thermally driven CO2 exsolution, and reached a final value of 10(-16.4) m(2) after 145 h at 100 °C due to continued exsolution and the onset of dolomite precipitation. Theoretical calculations show that CO2 exsolution results in a maximum pore space CO2 saturation of 0.5, and steady state relative permeabilities of CO2 and water on the order of 0.0065 and 0.1, respectively. Post-experiment imagery reveals matrix dissolution at low temperatures, and subsequent filling-in of flow passages at elevated temperature. Geochemical calculations indicate that reservoir fluids subjected to a thermal gradient may exsolve and precipitate up to 200 cm(3) CO2 and 1.5 cm(3) dolomite per kg of water, respectively, resulting in substantial porosity and permeability redistribution.

Permeability reduction produced by grain reorganization and accumulation of exsolved CO2 during geologic carbon sequestration: a new CO2 trapping mechanism.

Carbon sequestration experiments were conducted on uncemented sediment and lithified rock from the Eau Claire Formation, which consisted primarily of K-feldspar and quartz. Cores were heated to accentuate reactivity between fluid and mineral grains and to force CO(2) exsolution. Measured permeability of one sediment core ultimately reduced by 4 orders of magnitude as it was incrementally heated from 21 to 150 °C. Water-rock interaction produced some alteration, yielding sub-µm clay precipitation on K-feldspar grains in the core's upstream end. Experimental results also revealed abundant newly formed pore space in regions of the core, and in some cases pores that were several times larger than the average grain size of the sediment. These large pores likely formed from elevated localized pressure caused by rapid CO(2) exsolution within the core and/or an accumulating CO(2) phase capable of pushing out surrounding sediment. CO(2) filled the pores and blocked flow pathways. Comparison with a similar experiment using a solid arkose core indicates that CO(2) accumulation and grain reorganization mainly contributed to permeability reduction during the heated sediment core experiment. This suggests that CO(2) injection into sediments may store more CO(2) and cause additional permeability reduction than is possible in lithified rock due to grain reorganization.

Improved characterization of small "u" for Jacob pumping test analysis methods.

Numerous refinements have been proposed to traditional pumping test analyses, yet many hydrogeologists continue to use the Jacob method due to its simplicity. Recent research favors hydraulic tomography and inverse numerical modeling of pumping test data. However, at sites with few wells, or relatively short screens, the data requirements of these methods may be impractical within physical and fiscal constraints. Alternatively, an improved understanding of the assumptions and limitations of Theis and, due to their widespread usage, Jacob analyses, leads to improved interpretations in data-poor environments. A fundamental requirement of Jacob is a "small" value of u = f(r(2)/t), with radial distance, r, and pumping time, t. However, selection of a too stringent (i.e., too low) maximum permissible u-value, u(max), results in rejection of usable data from wells beyond a maximum radius, r(max). Conversely, data from small radii, less than r(min), where turbulent- and vertical-flow components arise, can result in acceptance of inappropriate data. Usage of drawdown data from wells too close to the pumping well, and exclusion of data from wells deemed too far, can cause unrealistic aquifer transmissivity, permeability, and storativity determinations. Here, data from an extensive well field in a glacial-outwash aquifer in north-central Minnesota, USA, are used to develop a new estimate for u(max). Traditionally quoted values for u(max) range from 0.01 to 0.05. Our proposed value for Jacob distance-drawdown analyses is significantly higher with u(max) up to 0.2, resulting in larger allowable r(max)-values and a higher likelihood of inclusion of additional wells in such pumping test analyses.

Using pyrosequencing to shed light on deep mine microbial ecology.

BACKGROUND: Contrasting biological, chemical and hydrogeological analyses highlights the fundamental processes that shape different environments. Generating and interpreting the biological sequence data was a costly and time-consuming process in defining an environment. Here we have used pyrosequencing, a rapid and relatively inexpensive sequencing technology, to generate environmental genome sequences from two sites in the Soudan Mine, Minnesota, USA. These sites were adjacent to each other, but differed significantly in chemistry and hydrogeology. RESULTS: Comparisons of the microbes and the subsystems identified in the two samples highlighted important differences in metabolic potential in each environment. The microbes were performing distinct biochemistry on the available substrates, and subsystems such as carbon utilization, iron acquisition mechanisms, nitrogen assimilation, and respiratory pathways separated the two communities. Although the correlation between much of the microbial metabolism occurring and the geochemical conditions from which the samples were isolated could be explained, the reason for the presence of many pathways in these environments remains to be determined. Despite being physically close, these two communities were markedly different from each other. In addition, the communities were also completely different from other microbial communities sequenced to date. CONCLUSION: We anticipate that pyrosequencing will be widely used to sequence environmental samples because of the speed, cost, and technical advantages. Furthermore, subsystem comparisons rapidly identify the important metabolisms employed by the microbes in different environments.

Continuum percolation for randomly oriented soft-core prisms.

We study continuum percolation of three-dimensional randomly oriented soft-core polyhedra (prisms). The prisms are biaxial or triaxial and range in aspect ratio over six orders of magnitude. Results for prisms are compared with studies for ellipsoids, rods, ellipses, and polygons and differences are explained using the concept of the average excluded volume, . For large-shape anisotropies we find close agreement between prisms and most of the above-mentioned shapes for the critical total average excluded volume, n(c), where n(c) is the critical number density of objects at the percolation threshold. In the extreme oblate and prolate limits simulations yield n(c) approximately 2.3 and n(c) approximately 1.3, respectively. Cubes exhibit the lowest-shape anisotropy of prisms minimizing the importance of randomness in orientation. As a result, the maximum prism value, n(c) approximately 2.79, is reached for cubes, a value close to n(c)=2.8 for the most equant shape, a sphere. Similarly, cubes yield a maximum critical object volume fraction of phi(c)=0.22. phi(c) decreases for more prolate and oblate prisms and reaches a linear relationship with respect to aspect ratio for aspect ratios greater than about 50. Curves of phi(c) as a function of aspect ratio for prisms and ellipsoids are offset at low-shape anisotropies but converge in the extreme oblate and prolate limits. The offset appears to be a function of the ratio of the normalized average excluded volume for ellipsoids over that for prisms, R=(e)/(p). This ratio is at its minimum of R=0.758 for spheres and cubes, where phi(c(sphere))=0.2896 may be related to phi c(cube))=0.22 by phi(c(cube))=1-[1-phi(c(sphere))](R)=0.23. With respect to biaxial prisms, triaxial prisms show increased normalized average excluded volumes, , due to increased shape anisotropies, resulting in reduced values of phi(c). We confirm that B(c)=n(c)=2C(c) applies to prisms, where B(c) and C(c) are the average number of bonds per object and average number of connections per object, respectively.