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DOE OSTI2024

Genomic and environmental controls on Castellaniella biogeography in an anthropogenically disturbed subsurface

Castellaniella species have been isolated from a variety of mixed-waste environments including the nitrate and multiple metal-contaminated subsurface at the Oak Ridge Reservation (ORR). Previous studies examining microbial community composition and nitrate removal at ORR during biostimulation efforts reported increased abundances of members of the Castellaniella genus concurrent with increased denitrification rates. Thus, we asked how genomic and abiotic factors control the Castellaniella biogeography at the site to understand how these factors may influence nitrate transformation in an anthropogenically impacted setting. We report the isolation and characterization of several Castellaniella strains from the ORR subsurface. Five of these isolates match at 100% identity (at the 16S rRNA gene V4 region) to two Castellaniella amplicon sequence variants (ASVs), ASV1 and ASV2, that have persisted in the ORR subsurface for at least 2 decades. However, ASV2 has consistently higher relative abundance in samples taken from the site and was also the dominant blooming denitrifier population during a prior biostimulation effort. We found that the ASV2 representative strain has greater resistance to mixed metal stress than the ASV1 representative strains. We attribute this resistance, in part, to the large number of unique heavy metal resistance genes identified on a genomic island in the ASV2 representative genome. Additionally, we suggest that the relatively lower fitness of ASV1 may be connected to the loss of the nitrous oxide reductase (nos) operon (and associated nitrous oxide reductase activity) due to the insertion at this genomic locus of a mobile genetic element carrying copper resistance genes. This study demonstrates the value of integrating genomic, environmental, and phenotypic data to characterize the biogeography of key microorganisms in contaminated sites.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

High-Resolution Computed Tomography Dataset of Mount Simon Sandstone

The Illinois Basin is a critical structure for subsurface energy related activities and their implementation in the United States. The Mount Simon Sandstone has been identified as a storage target for permanent and transient storage of fluids in the basin. Known for its exceptional thickness, depth, porosity, and sealing properties of overlying formations, this saline reservoir is crucial for long-term subsurface energy efforts. We present an extensive Computed Tomography (CT) dataset on a high porosity and permeability zone in the lower Mount Simon Sandstone available on the Energy Data eXchange® (EDX). This publicly accessible database comprises over 500 GB of high-resolution CT scans of six core samples, with resolutions ranging from 14.8 µm to 0.7 µm per pixel. The scans include both dry sandstone samples and those saturated with multiple fluids, allowing for comparative analyses across different conditions and resolutions. Coarser scans capture the bedding structure of the sandstone, while finer resolutions reveal detailed pore infill and throat characteristics. Metadata on location, depth, and saturation state enhance usability, enabling quick identification and cross-sample comparisons. By providing a robust resource for research and collaboration, the database contributes to domestic energy advancement by supporting continued progress in the use of the subsurface for energy solutions.

characterization↗

DOE OSTI2023

Combining synchrotron X-ray diffraction, mechanistic modeling and machine learning for in situ subsurface temperature quantification during laser melting

Laser melting, such as that encountered during additive manufacturing, produces extreme gradients of temperature in both space and time, which in turn influence microstructural development in the material. Qualification and model validation of the process itself and the resulting material necessitate the ability to characterize these temperature fields. However, well established means to directly probe the material temperature below the surface of an alloy while it is being processed are limited. To address this gap in characterization capabilities, a novel means is presented to extract subsurface temperature-distribution metrics, with uncertainty, from in situ synchrotron X-ray diffraction measurements to provide quantitative temperature evolution data during laser melting. Temperature-distribution metrics are determined using Gaussian process regression supervised machine-learning surrogate models trained with a combination of mechanistic modeling (heat transfer and fluid flow) and X-ray diffraction simulation. The trained surrogate model uncertainties are found to range from 5 to 15% depending on the metric and current temperature. The surrogate models are then applied to experimental data to extract temperature metrics from an Inconel 625 nickel superalloy wall specimen during laser melting. The maximum temperatures of the solid phase in the diffraction volume through melting and cooling are found to reach the solidus temperature as expected, with the mean and minimum temperatures found to be several hundred degrees less. The extracted temperature metrics near melting are determined to be more accurate because of the lower relative levels of mechanical elastic strains. However, uncertainties for temperature metrics during cooling are increased due to the effects of thermomechanical stress.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Development of a molecularly informed biogeochemical framework for reactive transport modeling of subsurface carbon inventories, transformations and fluxes (Final Report)

The overall objective of the project was to combine new molecular-level characterization strategies with soil carbon flux measurements to develop and evaluate model representations of subsurface carbon cycling. We expanded on existing studies in the East River watershed, Colorado, in collaboration with the Berkeley Lab Watershed Function Scientific Focus Area (SFA), SLAC Groundwater Quality SFA, and Rocky Mountain Biological Laboratory (RMBL) to develop an elevation and vegetation gradient that is now the subject of long-term monitoring by the USGS. To achieve the overall objective, we combined field studies of soil respiration with laboratory analyses, ranging from spectroscopy to incubation studies. This combination of techniques enabled us to develop a new understanding of the drivers of high-elevation soil respiration. In the process, we developed three new modeling approaches that improve our ability to conceptualize and ultimately to represent soil respiration in numerical models. The first approach is a plot-scale transient inverse model that can be used to determine in situ CO 2 production rates from measured concentration profiles and surface fluxes. Application of this method revealed the importance of plant phenology and deep CO 2 production in moderating CO 2 fluxes to the atmosphere. The second modeling approach is a molecular-scale tool that enables spectroscopic and elemental data for carbon speciation to be transformed into functional group abundances, or the ‘SOC-fga model’. This method uniquely enables carbon speciation to be tracked within a reactive transport framework to partition carbon among different pathways and storage zones within the soil. The third modeling tool builds strongly on the previous approaches and captures the microbial processes driving heterotrophic respiration. This ‘dormancy model’ allows the native soil microbial population to respond transiently to the presence or absence of water in order to catalyze carbon respiration. This approach was also compared to the simpler and more widely used first-order model using two experimental datasets with different temporal and spatial resolutions. Our results illustrate that the simpler first order model provides a robust and efficient representation of deep (>1 meter) soil respiration, but that shallow soils, where most respiration occurs, require explicit representation of moisture-dependent activation and dormancy rates. By assessing soil organic carbon turnover at multiple scales, we see a complex array of controls emerge. Atte scale of a hillslope, spatial heterogeneity in soil respiration rates dominates and is uncorrelated with instantaneous soil moisture and plant community. At the profile scale, the balance between plant inputs and water availability is the dominant control. At the microbial to molecular scale, physiological processes associated with carbon use and carbon speciation are important controls. These scale-dependent controls emphasize the need for new modeling approaches that examine their interactions and hierarchies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Nonnegative tensor factorization for contaminant source identification

Unsupervised Machine Learning (ML) is becoming increasingly popular for solving various types of data analytics problems including feature extraction, blind source separation, exploratory analyses, model diagnostics, etc. In this work, we have developed a new unsupervised ML method based on Nonnegative Tensor Factorization (NTF) for identification of the original groundwater types (including contaminant sources) present in geochemical mixtures observed in an aquifer. Frequently, groundwater types with different geochemical signatures are related to different background and/or contamination sources. The characterization of groundwater mixing processes is a challenging but very important task critical for any environmental management project aiming to characterize the fate and transport of contaminants in the subsurface and perform contaminant remediation. This task typically requires solving complex inverse models representing groundwater flow and geochemical transport in the aquifer, where the inverse analysis accounts for available site data. Usually, the model is calibrated against the available data characterizing the spatial and temporal distribution of the observed geochemical types. Numerous different geochemical constituents and processes may need to be simulated in these models which further complicates the analyses. Additionally, the application of inverse methods may introduce biases in the analyses through the assumptions made in the model development process. Here, we substitute the model inversion with unsupervised ML analysis. The ML analysis does not make any assumptions about underlying physical and geochemical processes occurring in the aquifer. Our ML methodology, called NTFk, is capable of identifying (1) the unknown number of groundwater types (contaminant sources) present in the aquifer, (2) the original geochemical concentrations (signatures) of these groundwater types and (3) spatial and temporal dynamics in the mixing of these groundwater types. These results are obtained only from the measured geochemical data without any additional site information. In general, the NTFk methodology allows for interpretation of large high-dimensional datasets representing diverse spatial and temporal components such as state variables and velocities. NTFk has been tested on synthetic and real-world site three-dimensional datasets. Finally, the NTFk algorithm is designed to work with geochemical data represented in the form of concentrations, ratios (of two constituents; for example, isotope ratios), and delta notations (standard normalized stable isotope ratios).

58 GEOSCIENCES↗

DOE OSTI2024

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA): Molecular and Computational Technologies for Environmental Microbiology (Final Scientific/Technical Report)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2012

Microscale geochemical gradients in Hanford 300 Area sediment biofilms and influence of uranium

The presence and importance of microenvironments in the subsurface at contaminated sites were suggested by previous geochemical studies. However, no direct quantitative characterization of the geochemical microenvironments had been reported. We quantitatively characterized microscale geochemical gradients (dissolved oxygen (DO), H(2), pH, and redox potential) in Hanford 300A subsurface sediment biofilms. Our results revealed significant differences in geochemical parameters across the sediment biofilm/water interface in the presence and absence of U(VI) under oxic and anoxic conditions. While the pH was relatively constant within the sediment biofilm, the redox potential and the DO and H(2) concentrations were heterogeneous at the microscale (<500-1000 μm). We found microenvironments with high DO levels (DO hotspots) when the sediment biofilm was exposed to U(VI). On the other hand, we found hotspots (high concentrations) of H(2) under anoxic conditions both in the presence and in the absence of U(VI). The presence of anoxic microenvironments inside the sediment biofilms suggests that U(VI) reduction proceeds under bulk oxic conditions. To test this, we operated our biofilm reactor under air-saturated conditions in the presence of U(VI) and characterized U speciation in the sediment biofilm. U L(III)-edge X-ray absorption spectroscopy (XANES and EXAFS) showed that 80-85% of the U was in the U(IV) valence state.

Nguyen, Hung D.↗

DOE OSTI2015

Reactive transport benchmarks for subsurface environmental simulation

Over the last 20 years, we have seen firsthand the evolution of multicomponent reactive transport modeling and the expanding range and increasing complexity of subsurface applications it is being used to address. There is a growing reliance on reactive transport modeling (RTM) to address some of the most compelling issues facing our planet: climate change, nuclear waste management, contaminant remediation, and pollution prevention. While these issues are motivating the development of new and improved capabilities for subsurface environmental modeling using RTM (e.g., biogeochemistry from cell-scale physiology to continental-scale terrestrial ecosystems, nonisothermal multiphase conditions, coupled geomechanics), there remain longstanding challenges in characterizing the natural variability of hydrological, biological, and geochemical properties in subsurface environments and limited success in transferring models between sites and across scales. An equally important trend over the last 20 years is the evolution of modeling from a service sought out after data has been collected to a multifaceted research approach that provides (1) an organizing principle for characterization and monitoring activities; (2) a systematic framework for identifying knowledge gaps, developing and integrating new knowledge; and (3) a mechanistic understanding that represents the collective wisdom of the participating scientists and engineers. There are now large multidisciplinary projects where the research approach is model-driven, and the principal product is a holistic predictive simulation capability that can be used as a test bed for alternative conceptualizations of processes, properties, and conditions. Much of the future growth and expanded role for RTM will depend on its continued ability to exploit technological advancements in the earth and environmental sciences. Advances in measurement technology, particularly in molecular biology (genomics), isotope fractionation, and high-resolution X-ray spectroscopy, have created new lines of research that can be used to inform the conceptualization of reactions and rate laws and validate mechanistic models. For example, spectroscopy has identified the oxidation states of key components and elemental distributions at increasingly smaller scales and lower concentrations; molecular biology has progressed from identifying the presence of microbes to characterization of which microbial communities are active and what they are doing (i.e., microbial function), which has led in turn to the identification of active processes under conditions beyond what analytical chemistry can discern; isotope ratios in pore water and solid phases that can be used to distinguish between biotic from abiotic processes, sorption from precipitation, and origin and age of groundwater. The other noteworthy development that is expanding the role of RTM in subsurface environmental modeling is he advance in computational technology that is enabling the simulation of more coupled processes with increasing mechanistic detail. In some cases, this involves the inclusion of more reactive species and/or microbial populations in the simulations; in other cases, the impact is through the ability to achieve high resolution of property distributions over longer simulated times. To achieve these ambitious objectives for subsurface reactive transport simulation, the subsurface science and engineering community is being driven to provide accurate assessments of engineering performance and risk for important issues with far-reaching consequences. As a result, the complexity and detail of subsurface processes, properties, and conditions that can be simulated have significantly expanded. This expansion was enabled, in part, by advances in measurement technology, computing technology, and numerical techniques.

benchmarking↗

DOE OSTI2024

Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications

Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring. We have deployed strainmeters and then conducted injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters (30 to 40m depth) was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 n/d over a few days. The signal at two strainmeters at shallow depth were consistent, although the magnitude of the horizontal strains were different reflecting the different radial directions from the well. The signal at a deep strainmeter deployed at reservoir depth was much different, with tensile vertical strains and compressive horizontal strains. These data can be interpreted by inverting poroelastic forward models developed using numerical and analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. This model is fast and can be inverted to estimate reservoir stiffness and geometry. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. The proxy model is periodically updated and refined using the finite element model to ensure accuracy. This approach significantly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. We have shown that the strain tensor in the caprock is sensitive to pressure in the reservoir, boundaries in the reservoir, and pressure in the caprock caused by leaks. These results indicate that coupling strain tensor data with inversion has the potential to help evaluate reservoirs during initial characterization, and to monitor them during the CO2 injection and storage process.

Murdoch, Larry↗

DOE OSTI2019

Ecological and Genomic Attributes of Novel Bacterial Taxa That Thrive in Subsurface Soil Horizons

While most bacterial and archaeal taxa living in surface soils remain undescribed, this problem is exacerbated in deeper soils, owing to the unique oligotrophic conditions found in the subsurface. Additionally, previous studies of soil microbiomes have focused almost exclusively on surface soils, even though the microbes living in deeper soils also play critical roles in a wide range of biogeochemical processes. We examined soils collected from 20 distinct profiles across the United States to characterize the bacterial and archaeal communities that live in subsurface soils and to determine whether there are consistent changes in soil microbial communities with depth across a wide range of soil and environmental conditions. We found that bacterial and archaeal diversity generally decreased with depth, as did the degree of similarity of microbial communities to those found in surface horizons. We observed five phyla that consistently increased in relative abundance with depth across our soil profiles: Chloroflexi , Nitrospirae , Euryarchaeota , and candidate phyla GAL15 and Dormibacteraeota (formerly AD3). Leveraging the unusually high abundance of Dormibacteraeota at depth, we assembled genomes representative of this candidate phylum and identified traits that are likely to be beneficial in low-nutrient environments, including the synthesis and storage of carbohydrates, the potential to use carbon monoxide (CO) as a supplemental energy source, and the ability to form spores. Together these attributes likely allow members of the candidate phylum Dormibacteraeota to flourish in deeper soils and provide insight into the survival and growth strategies employed by the microbes that thrive in oligotrophic soil environments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Distributed Acoustic Sensing (DAS) of Strain at Earth Tide Frequencies: Laboratory Tests

The solid Earth strains in response to the gravitational pull from the Moon, Sun, and other planetary bodies. Measuring the flexure of geologic material in response to these Earth tides provides information about the geomechanical properties of rock and sediment. Such measurements are particularly useful for understanding dilation of faults and fractures in competent rock. A new approach to measuring earth tides using fiber optic distributed acoustic sensing (DAS) is presented here. DAS was originally designed to record acoustic vibration through the measurement of dynamic strain on a fiber optic cable. Here, laboratory experiments demonstrate that oscillating strain can be measured with DAS in the microHertz frequency range, corresponding to half-day (M2) lunar tidal cycles. Although the magnitude of strain measured in the laboratory is larger than what would be expected due to earth tides, a clear signal at half-day period was extracted from the data. With the increased signal-to-noise expected from quiet field applications and improvements to DAS using engineered fiber, earth tides could potentially be measured in deep boreholes with DAS. Because of the distributed nature of the sensor (0.25 m measurement interval over kilometers), fractures could be simultaneously located and evaluated. Such measurements would provide valuable information regarding the placement and stiffness of open fractures in bedrock. Characterization of bedrock fractures is an important goal for multiple subsurface operations such as petroleum extraction, geothermal energy recovery, and geologic carbon sequestration.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (Final Scientific/Technical Report)

The ENIGMA science focus area (SFA) is a multi-disciplinary, multi-institutional research effort focused on addressing foundational knowledge gaps in environmental microbial communities by studying groundwater and sediment microbiomes in the shallow subsurface at the contaminated Oak Ridge Field Research Site (FRC). We seek to discover and characterize the reciprocal interactions between the microbial communities and the geochemical and geophysical parameters of the shallow subsurface within the contamination plume. The goal of the Fields lab is to help manage and conduct laboratory experiments informed by field observations using ecological and physiological approaches to study microbial populations in situ as well as ex situ (in the laboratory). In particular, we aim to study and characterize the impact of hydrological constraints on free-living and biofilm biomass and activity with increasing spatial and temporal resolution under static and flow conditions. We also aim to help characterize novel microbial groups that are present and active under relevant field conditions, including the development of molecular techniques for in situ detection as well as metabolic interactions that underlie pertinent physiology and ecology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Three-Component Spectroelectrochemical Sensor Module for the Detection of Pertechnetate (TcO4-)

This review looks at the advancements in the development of a sensor for technetium (Tc) that is applicable to characterizing and monitoring the vadose zone and associated subsurface water. Subsurface contamination by Tc is of particular concern for two reasons: the extremely long lifetime of its most common isotope 99Tc (half-life = 2 x 105 years) and the fast migration in soils of pertechnetate (TcO4–) which is considered to be the dominant 99Tc species in ground water. TcO4– does not have a characteristic spectral signature which prevents its rapid, sensitive, and economic in-situ detection. To address this problem, a novel spectroelectrochemical sensor has been designed that combines three modes of selectivity (electrochemistry, spectroscopy, and selective partitioning) into a single sensor to substantially improve specificity which is critical in the specific detection of an analyte in the presence of potential interfering species. The sensor consists of a basic spectroelectrochemical configuration: a waveguide with an optically transparent electrode (OTE) that is coated with a thin chemically-selective film that preconcnetrates the analyte. The key to adapting this generic sensor to detect TcO4– and Tc complexes lies in the development of chemically-selective films that preconcentrate the analyte and, when necessary, chemically convert it into a complex with electrochemical and spectroscopic properties appropriate for sensing. This review focuses on the general concept of the sensor and the rationale for the selection of the specific components of choice, the development and characterization of the sensor for the different detection modules, the synthesis and characterization of complexes relevant in the detection of technetium, and the progress in the utilization of the sensor module for the effective detection of these complexes.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2024

Seismic monitoring of EGS fracture stimulations at Utah FORGE (Part 1): Time-lapse variations of b-values and Shear-wave Splitting Rates of induced microearthquakes

Characterizing geologic formations near geothermal wells is crucial for efficient extraction of subsurface geothermal energy resources. To monitor effective fracture stimulation of enhanced geothermal systems (EGS), we analyze a catalog of induced microearthquakes to characterize seismicity induced by Phase 2C fracture stimulations of the Utah FORGE project and derive the b-values for 424 induced microearthquakes in three stages of fracture stimulation. Here, we find the time-lapse variations of these b-values. We apply eigenvector rotation and waveform correlation to 3C geophone data to separate fast S 1 and slow S 2 waves, determine their directions, measure their lag time, and calculate the S-wave splitting rate (SSR) for six induced microearthquakes in Stage 1 and 21 in Stage 3. Both SSR values and b-values increase with time. The increase in these values may be related to heavily fractured zones created by fracture stimulations during Stage 2 injections. Large and highly variable SSR values in Stage 3 may reflect heterogeneities in the fracture zones. Time-lapse variations of SSR values and b-values may be one of the most useful approaches to monitoring and characterizing the effectiveness and efficiency of various types of fracture stimulations.

58 GEOSCIENCES↗

DOE OSTI2019

Electrical Resistivity Tomography of the 216-U-5 and 216-U-6 WA-1 Waste Sites

The subsurface below the 216-U-5 and 216-U-6 sites needs to be characterized as part of the remedial investigation of the 200-WA-1 operable unit at the Hanford Site. Electrical resistivity tomography (ERT) was selected as a first step in this characterization effort to provide information about the three-dimensional distribution of historically disposed waste fluids in the subsurface beneath these sites. ERT does not directly image specific contaminants. However, ERT provides a three-dimensional image of subsurface zones where the bulk electrical conductivity is higher than surrounding background values. Disposed waste fluids can increase the bulk electrical conductivity in the subsurface where they are present by increasing the moisture content and because the high concentration of waste-fluid constituents such as nitrate cause the fluid to have a higher specific conductance than background pore water. Thus, zones of increased bulk electrical conductivity in the subsurface can be interpreted as zones where waste fluids are present. An ERT survey of the subsurface beneath the 216-U-5 and 216-U-6 sites was conducted to collect ERT data suitable for interpreting the bulk electrical conductivity distribution in the subsurface. Data interpretation was applied using the NQA-1 qualified E4D ERT parallel modelling and inversion code (Johnson 2014). A summary cross-section and interpretation of the 216-U-5 and 216-U-6 ERT is provided in Figure S.1. The ERT image reveals two distinct zones of anomalous bulk conductivity emanating from 216-U-5 and 216-U-6 that merge at a depth of approximately 14 m below the surface and continue to a depth of no more than 26 m below the surface, which is approximately 60 m above the current water table elevation. The image also suggests that lateral transport of waste streams disposed into 216-U-5 and 216-U-6 was limited. These results are consistent with historical groundwater monitoring, which indicated that the disposed waste had not migrated to the water table, possibly due to the relatively low volumes of waste discharge into 216-U-5 and 216-U-6. The ERT information provides a line of evidence supporting this conclusion and can be used to guide the selection of characterization borehole(s) location and depth as needed for additional characterization of the contaminant distribution and properties at these sites. Locations of bulk conductivity anomalies associated with 216-U-5 and 216-U-6 releases are offset approximately 10 m to the west of the locations of 216-U-5 and 216-U-6 as recorded in the Waste Information Data System database. There are two predominant regions of elevated bulk conductivity in addition to those associated with 216-U-5 and 216-U-6. The first is located beneath Beloit Ave. from approximately 190 to 195 m in elevation. The small region of high conductivity directly beneath Beloit Ave. is likely an artifact resulting from the failure to account for the Beloit Ave. topographic rise in the ERT modeling, as that information was unavailable. Information concerning the precise positioning of the railroad tracks shown was also unavailable, particularly in the vertical dimension. The high conductivity anomaly beneath the assumed railroad track location is likely caused by misplacement of the tracks in the ERT model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2012

Applications of Subsurface Microscopy

Exploring the interior of a cell is of tremendous importance in order to assess the effects of nanomaterials on biological systems. Outside of a controlled laboratory environment, nanomaterials will most likely not be conveniently labeled or tagged so that their translocation within a biological system cannot be easily identified and quantified. Ideally, the characterization of nanomaterials within a cell requires a nondestructive, label-free, and subsurface approach. Subsurface nanoscale imaging represents a real challenge for instrumentation. Indeed the tools available for high resolution characterization, including optical, electron or scanning probe microscopies, mainly provide topography images or require tagants that fluoresce. Although the intercellular environment holds a great deal of information, subsurface visualization remains a poorly explored area. Recently, it was discovered that by mechanically perturbing a sample, it was possible to observe its response in time with nanoscale resolution by probing the surface with a micro-resonator such as a microcantilever probe (Figure 1). Microcantilevers are used as the force-sensing probes in Atomic Force Microscopy (AFM), where the nanometer-scale probe tip on the microcantilever interacts with the sample in a highly controlled manner to produce high-resolution raster-scanned information of the sample surface. Taking advantage of the existing capabilities of AFM, we present a novel technique, Mode Synthesizing Atomic Force Microscopy (MSAFM) (Figure 1), which has the ability to probe subsurface structures such as non-labeled nanoparticles embedded in a cell. In MSAFM mechanical actuators (PZTs) excite the probe and the sample at different frequencies as depicted in Figure 1. The nonlinear nature of the tip-sample interaction, at the point of contact of the probe and the surface of the sample, in the contact mode AFM configuration permits the mixing of the elastic waves. The new dynamic system comprises new synthesized imaging modes, resulting from sum- and difference-frequency generation of the driving frequencies. The specific electronics of MSAFM allows the selection of individual modes and the monitoring of their amplitude and phase. From these quantities of various synthesized modes a series of images can be acquired. The new images contain subsurface information, thus revealing the presence of nanoparticles inside the cells.

Tetard, Laurene↗

DOE OSTI2012

Phase II Investigation at the Former CCC/USDA Grain Storage Facility in Savannah, Missouri

From approximately 1949 until 1970, the Commodity Credit Corporation of the U.S. Department of Agriculture (CCC/USDA) operated a grain storage facility on federally owned property approximately 0.25 mi northwest of Savannah, Missouri. During this time, commercial grain fumigants containing carbon tetrachloride were commonly used by the CCC/USDA and the private grain storage industry to preserve grain in their facilities. In November 1998, carbon tetrachloride was detected in a private well (Morgan) roughly 50 ft south of the former CCC/USDA facility, as a result of statewide screening of private wells near former CCC/USDA facilities, conducted in Missouri by the U.S. Environmental Protection Agency (EPA 1999). The 1998 and subsequent investigations by the EPA and the Missouri Department of Natural Resources (MDNR) confirmed the presence of carbon tetrachloride in the Morgan well, as well as in a second well on property currently owned by the Missouri Department of Transportation (MoDOT), directly east of the former CCC/USDA facility. The identified concentrations in these two wells were above the EPA maximum contaminant level (MCL) and the Missouri risk-based corrective action default target level (DTL) values of 5.0 μg/L for carbon tetrachloride in water used for domestic purposes (EPA 1999; MDNR 2000a,b, 2006). Because the observed contamination in the Morgan and MoDOT wells might be linked to the past use of carbon tetrachloride-based fumigants at its former grain storage facility, the CCC/USDA is conducting an investigation to (1) characterize the source(s), extent, and factors controlling the subsurface distribution and movement of carbon tetrachloride and (2) evaluate the potential risks to human health, public welfare, and the environment posed by the contamination. This work is being performed in accord with an Intergovernmental Agreement established in 2007 between the Farm Service Agency of the USDA and the MDNR, to address carbon tetrachloride contamination potentially associated with a number of former CCC/USDA grain storage facilities in Missouri. The site characterization at Savannah is being conducted on behalf of the CCC/USDA by the Environmental Science Division of Argonne National Laboratory. The investigation is being conducted in phases, so that information obtained and interpretations developed during each incremental stage can be used most effectively to guide subsequent phases of the program. Phase II objectives: Investigate the more detailed characteristics of groundwater flow in the vicinity of the former CCC/USDA facility and the contaminated Morgan and MoDOT private wells; Obtain additional information on the vertical and lateral distribution and concentrations of carbon tetrachloride in groundwater in the vicinity of the former CCC/USDA facility and the contaminated Morgan and MoDOT private wells; Investigate further for possible evidence of carbon tetrachloride in the subsurface (vadose zone) and deeper soils beneath the former CCC/USDA facility, as well as in the vicinity of the contaminated MoDOT private well.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Coupled land surface–subsurface hydrogeophysical inverse modeling to estimate soil organic carbon content and explore associated hydrological and thermal dynamics in the Arctic tundra

Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface–subsurface hydrological–thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon–climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological–thermal processes associated with annual freeze–thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets – including soil liquid water content, temperature and electrical resistivity tomography (ERT) data – to estimate the vertical distribution of OC content. Our approach relies on the fact that OC content strongly influences soil hydrological–thermal parameters and, therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. We employ the Community Land Model to simulate nonisothermal surface–subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes (e.g., solar radiation balance, evapotranspiration, snow accumulation and melting) and ice–liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate a posteriori distributions of desired model parameters. For hydrological–thermal-to-geophysical variable transformation, the simulated subsurface temperature, liquid water content and ice content are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantify the propagation of uncertainty from the estimated parameters to prediction of hydrological–thermal responses. We find that, compared to inversion of single dataset (temperature, liquid water content or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (top 0.3 m of soil) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (here at about 0.6 m depth), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, which is often observed in organic-rich Arctic soil, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface–subsurface, deterministic–stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological–thermal dynamics.

58 GEOSCIENCES↗