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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Soil Sampling Techniques For Alabama Grain Fields

Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.

Thompson, A. N.↗
DOE OSTI2022

Impact of feed variability on cesium removal with multiple actual waste samples from the Hanford site

Here, the Tank Side Cesium Removal (TSCR) system, under development by Washington River Protection Solutions (WRPS), will send initial low-activity Hanford waste tank supernate feeds to the Hanford Waste Treatment and Immobilization Plant (WTP) Low-Activity Waste (LAW) Facility. In addition to entrained solids removal from the supernate, the primary goal of TSCR is to remove cesium-137 ( 137 Cs) by ion exchange, allowing contact handling of the liquid effluent product at WTP. Crystalline silicotitanate (CST) ion exchange media, manufactured by Honeywell UOP (product IONSIV™ R9140-B), was selected as the ion exchange media at TSCR. This lot of material was found to have superior performance in comparison to historic batches of CST. Ion exchange column and batch contact testing with supernate from Hanford tanks AP-105, AP-107 and AW-102 was performed to assess the impact of feed variability on system performance. These tests demonstrated that batch contact measurements provide a reasonable prediction of column capacities with some deviation in performance attributed to column dynamics. In addition, the variability in CST capacity for cesium in the various actual waste samples does not track with historical understanding of the competing cations, suggesting that tank waste samples contain other components that may significantly impact cesium loading.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Say where you sample: Increasing site selection transparency in urban ecology

Urban ecological studies have the potential to extend our understanding of socio-ecological systems beyond that of an individual city or region. Cross-comparative empirical work and synthesis are imperative to develop a general urban ecological theory. This can be achieved only if studies are replicable and generalizable. Transparency in methods reporting facilitates generalizability and replicability by documenting the decisions scientists make during the various steps of research design; this is particularly true for sampling design and selection because of their impact on both internal and external validity and the potential to unintentionally introduce bias. Three interdependent aspects of sample design are study sample selection (e.g., specific organisms, soils, or water), sample specification (measurement of specific variable of interest), and site selection (locations sampled). Of these, documentation of site selection—the where component of sample design—is underrepresented in the urban ecology literature. Using a stratified random sample of 158 papers from 12 major urban ecology journals, we investigated how researchers selected study sites in urban ecosystems and evaluated whether their site selection methods were transparent. We extracted data from these papers using a 50-question, theory-based questionnaire and a multiple-reviewer approach. Our sample represented almost 45 years of urban ecology research across 40 different countries. We found that more than 80% of the papers read were not transparent in their site selection methodology. We do not believe site selection methods are replicable for 70% of the papers read. Key weaknesses include incomplete descriptions of populations and sampling frames, urban gradients, sample selection methods, and property access. Low transparency in reporting the where methodology limits urban ecologists’ ability to assess the internal and external validity of studies’ findings and to replicate published studies; it also limits the generalizability of existing studies. The challenges of low transparency are particularly relevant in urban ecology, a field where standard protocols for site selection and delineation are still being developed. These limitations interfere with the fields’ ability to build theory and inform policy. We conclude by offering a set of recommendations to increase transparency, replicability, and generalizability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Application of a Geochemically Informed Leak Detection (GILD) Model to CO 2 Injection Sites on the United States Gulf Coast

The Gulf Coast region possesses great potential for CO 2 enhanced oil recovery (EOR) and CO 2 storage. A geochemically informed leak detection (GILD) model has been applied to CO 2 injection sites on the Gulf Coast with considerations of measurement variability. The Jasper aquifer in Montgomery County, Texas, was chosen to demonstrate the method. Based on background data from wells in the area, combinations of mineral and fluid compositions were used to create 23 scenarios for the geochemical model. The output from the geochemical model was used to identify sensitive monitoring species, and response functions were generated for these as a function of the CO 2 leakage concentration. The sources of measurement variability for background conditions were characterized from the Jasper aquifer background data, and then normalized using the coefficient of variation of each species across the monitoring wells. Bayesian belief network (BBN) models were constructed, and measurement variability of different levels were added to compare leak detection probabilities. Increasing measurement variability decreased the power to detect a leak of a given size. For a moderately high CO 2 concentration of 0.2 mol/kg, the probability of detecting this leakage effect using pH as the monitoring variable in an aquifer with calcite decreases from 98% (no measurement variability) to 61% (medium variability) to 33% (high variability). The loss in power of the sampling protocol with increasing measurement variability is similar in magnitude when Ca 2+ or HCO 3 - is used as the monitoring parameter, but only for aquifers with calcite.

58 GEOSCIENCES↗
NASA NTRS1982

Combining remotely sensed and other measurements for hydrologic areal averages

A method is described for combining measurements of hydrologic variables of various sampling geometries and measurement accuracies to produce an estimated mean areal value over a watershed and a measure of the accuracy of the mean areal value. The method provides a means to integrate measurements from conventional hydrological networks and remote sensing. The resulting areal averages can be used to enhance a wide variety of hydrological applications including basin modeling. The correlation area method assigns weights to each available measurement (point, line, or areal) based on the area of the basin most accurately represented by the measurement. The statistical characteristics of the accuracy of the various measurement technologies and of the random fields of the hydrologic variables used in the study (water equivalent of the snow cover and soil moisture) required to implement the method are discussed.

Johnson, E. R.↗
DOE OSTI2025

Huge ensembles – Part 1: Design of ensemble weather forecasts using spherical Fourier neural operators

Abstract. Simulating low-likelihood high-impact extreme weather events in a warming world is a significant and challenging task for current ensemble forecasting systems. While these systems presently use up to 100 members, larger ensembles could enrich the sampling of internal variability. They may capture the long tails associated with climate hazards better than traditional ensemble sizes. Due to computational constraints, it is infeasible to generate huge ensembles (comprised of 1000–10 000 members) with traditional, physics-based numerical models. In this two-part paper, we replace traditional numerical simulations with machine learning (ML) to generate hindcasts of huge ensembles. In Part 1, we construct an ensemble weather forecasting system based on spherical Fourier neural operators (SFNOs), and we discuss important design decisions for constructing such an ensemble. The ensemble represents model uncertainty through perturbed-parameter techniques, and it represents initial condition uncertainty through bred vectors, which sample the fastest-growing modes of the forecast. Using the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS) as a baseline, we develop an evaluation pipeline composed of mean, spectral, and extreme diagnostics. With large-scale, distributed SFNOs with 1.1 billion learned parameters, we achieve calibrated probabilistic forecasts. As the trajectories of the individual members diverge, the ML ensemble mean spectra degrade with lead time, consistent with physical expectations. However, the individual ensemble members' spectra stay constant with lead time. Therefore, these members simulate realistic weather states during the rollout, and the ML ensemble passes a crucial spectral test in the literature. The IFS and ML ensembles have similar extreme forecast indices, and we show that the ML extreme weather forecasts are reliable and discriminating. These diagnostics ensure that the ensemble can reliably simulate the time evolution of the atmosphere, including low-likelihood high-impact extremes. In Part 2, we generate a huge ensemble initialized each day in summer 2023, and we characterize the simulations of extremes.

Mahesh, Ankur↗
DOE OSTI2026

Predicted aboveground biomass of Typha angustifolia in an upland brackish tidal marsh, PIE LTER, Byfield, MA (2022-2024)

This dataset contains predicted monthly aboveground Typha angustifolia biomass per sample and per square meter in a brackish tidal marsh site dominated by Typha angustifolia near the Parker River in the upper estuary of the Plum Island Sound, Massachusetts (MA) during the growing seasons (May-September) of 2022, 2023, and 2024. This site is also located within the Plum Island Ecosystems Long Term Ecological Research Station (PIE LTER). Allometric equations were developed from dry weight data and associated maximum heights collected in 2022 and 2023. The goal of this study was to investigate the difference in aboveground biomass between the site’s marsh interior (MI) and the creek bank (CB). Metadata files (Typha_biomass_predictions_dd.csv and Typha_biomass_predictions_flmd.csv) contain detailed information on variable definitions, calculations, sampling methods, and the location of the site.

DATE↗
DOE OSTI2022

Optical variability of quasars with 20-yr photometric light curves

ABSTRACT We study the optical gri photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during ∼1998−2020 with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average ∼200 nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10–15 yr baselines and ≲ 100 epochs. We find that the average damping time-scale τDRW continues to rise with increased baseline, reaching a median value of ∼750 d (g band) in the rest frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained τDRW (less than 20 per cent of the baseline), we confirm a weak wavelength dependence of τDRW∝λ0.51 ± 0.20. We further quantify optical variability of these quasars over days to decades time-scales using structure function (SF) and power spectrum density (PSD) analyses. The SF and PSD measurements qualitatively confirm the measured (hundreds of days) damping time-scales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on time-scales less than ∼ a month for these luminous quasars, and this second break point correlates with the longer DRW damping time-scale.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Rotational modulation and flares on RS Canum Venaticorum and BY Draconis stars. 18: Coordinated VLA, ROSAT, and IUE observations of RS CVn binaries

As part of a coordinated program of multi-wavelength observations of RS CVn close binary systems, we observed 15 systems with the Very Large Array (VLA) and 10 systems with IUE, simultaneously or nearly simultaneously with the ROSAT All Sky Survey observations of these stars. Of the 22 systems observed with ROSAT, three were observed both by IUE and the VLA. Radio observations were made at 3.6, 6 and 20 cm. Of the 15 observed RS CVn systems, we detected 11 with greater than 4 sigma confidence at one or more wavelengths. The IUE observations were made within the RIASS (ROSAT-IUE All Sky Survey) program. We present the results of the VLA observations, along with the corresponding subsets of the ROSAT Position Sensitive Proportional Counter (PSPC) X-ray and Wide Field Camera (WFC) XUV survey, and RIASS IUE observations. We obtained an extended VLA/IUE/ROSAT simultaneous coverage of one system, TY Pyx, covering more than one orbital period. These observations reveal that the quiescent radio flux of TY Pyx is relatively constant over time scales of up to 7 hours, but that it did change by a factor of 3 over 24 hours, probably due to a flare on 1990 Nov. 12. The UV, XUV and X-ray fluxes do not show large day-to-day or phase-related variability. The observation of the decay phase of a radio flare on EI Eri, with no accompanying X-ray or XUV flare, suggests that the lack of a strong correlation between X-ray and radio flares previously noted for dMe flare stars holds for RS CVn systems as well. We suggest that the radio flare may have been due to a coherent emission process such as electron cyclotron emission. The simultaneous measurements presented here provide a unique test of the general correlation between radio and soft X-ray luminosities, L(sub radio) approximately L(sub x exp m) (Drake et al. 1989) with a power-law slope close to unity, which was previously derived using data obtained years apart. Our derived slopes are consistent with and thus support the general correlations between coronal and chromospheric/transition region emissions previously derived from nonsimultaneous measurements of a much larger sample of these variable sources. However, the importance of simultaneous measurements for accurate energy balance calculations is stressed.

Fox, David C.↗
DOE OSTI2016

Modeling Changes in Measured Conductance of Thin Boron Carbide Semiconducting Films Under Irradiation

Semiconducting, p-type, amorphous partially dehydrogenated boron carbide films (a-B 10 C 2+x :H y ) were deposited utilizing plasma enhanced chemical vapor deposition (PECVD) onto n-type silicon thus creating a heterojunction diode. A model was developed for the conductance of the device as a function of perturbation frequency (f) that incorporates changes of the electrical properties for both the a-B 10 C 2+x :H y film and the silicon substrate when irradiated. The virgin model has 3 independent variables (R1, C1, R3), and 1 dependent variable (f). These samples were then irradiated with 200 keV He + ions, and the conductance model was matched to the measured data. It was found that initial irradiation (0.1 displacements per atom (dpa) equivalent) resulted in a decrease in the parallel junction resistance parameter from 6032 Ω to 2705 Ω. Further irradiation drastically increased the parallel junction resistance parameter to 39000 Ω (0.2 dpa equivalent), 77440 Ω (0.3 dpa equivalent), and 190000 Ω (0.5 dpa equivalent). It is believed that the initial irradiation causes type inversion of the silicon substrate changing the original junction from a p-n to a p-p+ with a much lower barrier height leading to a lower junction resistance component between the a-B 10 C 2+x :H y and irradiated silicon. In addition, it was found that after irradiation, a second parallel resistor and capacitor component is required for the model, introducing 2 additional independent variables (R2, C2). This is interpreted as the junction between the irradiated and virgin silicon near ion end of range.

36 MATERIALS SCIENCE↗
NASA NTRS2018

A Detailed Characterization of the Saharan Dust Collected During the Fennec Campaign in 2011: In Situ Ground-Based and Laboratory Measurements

Millions of tons of mineral dust are lifted by the wind from arid surfaces and transported around the globe every year. The physical and chemical properties of the mineral dust are needed to better constrain remote sensing observations and are of fundamental importance for the understanding of dust atmospheric processes. Ground-based in situ measurements and in situ filter collection of Saharan dust were obtained during the Fennec campaign in the central Sahara in 2011. This paper presents results of the absorption and scattering coefficients, and hence single scattering albedo (SSA), of the Saharan dust measured in real time during the last period of the campaign and subsequent laboratory analysis of the dust samples collected in two supersites, SS1 and SS2, in Algeria and in Mauritania, respectively. The samples were taken to the laboratory, where their size and aspect ratio distributions, mean chemical composition, spectral mass absorption efficiency, and spectral imaginary refractive index were obtained from the ultraviolet (UV) to the near-infrared (NIR) wavelengths. At SS1 in Algeria, the time series of the scattering coefficients during the period of the campaign show dust events exceeding 3500 Mm (exp -1), and a relatively high mean SSA of 0.995 at 670 nm was observed at this site. The laboratory results show for the fine particle size distributions (particles diameter <5μm and mode diameter at2–3 μm) in both sites a spectral dependence of the imaginary part of the refractive index Im(m) with a bow-like shape, with increased absorption in UV as well as in the shortwave infrared. The same signature was not observed, however, in the mixed particle size distribution (particle diameter<10 μm and mode diameter at 4 μm) in Algeria. Im(m) was found to range from 0.011 to 0.001i for dust collected in Algeria and 0.008 to 0.002i for dust collected in Mauritania over the wavelength range of 350-2500 nm. Differences in the mean elemental composition of the dust collected in the supersites in Algeria and in Mauritania and between fine and mixed particle size distributions were observed from EDXRF measurements, although those differences cannot be used to explain the optical properties variability between the samples. Finally, particles with low-density typically larger than 10 μm in diameter were found in some of the samples collected at the supersite in Mauritania, but these low-density particles were not observed in Algeria.

Saharan dust measured in real time↗
NASA NTRS2003

New Active Optical Technique Developed for Measuring Low-Earth-Orbit Atomic Oxygen Erosion of Polymers

Polymers such as polyimide Kapton (DuPont) and Teflon FEP (DuPont, fluorinated ethylene propylene) are commonly used spacecraft materials because of desirable properties such as flexibility, low density, and in the case of FEP, a low solar absorptance and high thermal emittance. Polymers on the exterior of spacecraft in the low-Earth-orbit (LEO) environment are exposed to energetic atomic oxygen. Atomic oxygen reaction with polymers causes erosion, which is a threat to spacecraft performance and durability. It is, therefore, important to understand the atomic oxygen erosion yield E (the volume loss per incident oxygen atom) of polymers being considered in spacecraft design. The most common technique for determining E is a passive technique based on mass-loss measurements of samples exposed to LEO atomic oxygen during a space flight experiment. There are certain disadvantages to this technique. First, because it is passive, data are not obtained until after the flight is completed. Also, obtaining the preflight and postflight mass measurements is complicated by the fact that many polymers absorb water and, therefore, the mass change due to water absorption can affect the E data. This is particularly true for experiments that receive low atomic oxygen exposures or for samples that have a very low E. An active atomic oxygen erosion technique based on optical measurements has been developed that has certain advantages over the mass-loss technique. This in situ technique can simultaneously provide the erosion yield data on orbit and the atomic oxygen exposure fluence, which is needed for erosion yield determination. In the optical technique, either sunlight or artificial light can be used to measure the erosion of semitransparent or opaque polymers as a result of atomic oxygen attack. The technique is simple and adaptable to a rather wide range of polymers, providing that they have a sufficiently high optical absorption coefficient. If one covers a photodiode with a uniformly thick sheet of semitransparent polymer such as Kapton H polyimide, then as atomic oxygen erodes the polymer, the short-circuit current from the photodiode will increase in an exponential manner with fluence. This nonlinear response with fluence results in a lack of sensitivity for measuring low atomic oxygen fluences. However, if one uses a variable-thickness polymer or carbon sample, which is configured as shown in the preceding figure, then a linear response can be achieved for opaque materials using a parabolic well for a circular geometry detector or a V-shaped well for a rectangular-geometry detector. Variable-thickness samples can be fabricated using many thin polymer layers. For semitransparent polymers such as Kapton H polyimide, there is an initial short-circuit current that is greater than zero. This current has a slightly nonlinear dependence on atomic oxygen fluence in comparison to opaque materials such as black Kapton as shown in the graph. For this graph figure, the total thickness of Kapton H was assumed to be 0.03 cm. The photodiode short-circuit current shown in the graph was generated on the basis of preliminary measurements-a total reflectance rho of 0.0424 and an optical absorption coefficient a of 146.5 cm(sup -1). In addition to obtaining on-orbit data, the advantage of this active erosion and erosion yield measurement technique is its simplicity and reliance upon well-characterized fluence witness materials as well as a nearly linear photodiode short-circuit current dependence upon atomic oxygen fluence. The optical technique is useful for measuring either atomic oxygen fluence or erosion, depending on the information desired. To measure the atomic oxygen erosion yield of a test material, one would need to have two photodiode sensors, one for the test material and one that uses a known erosion yield material (such as Kapton) to measure the atomic oxygen fluence.

Banks, Bruce A.↗
NASA NTRS2016

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50, 100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed.

upscaling↗
DOE OSTI2018

Metal(loid) bioaccessibility and inhalation risk assessment: A comparison between an urban and an industrial area

Highlights: • Metal(loid) bioaccessibility of PM{sub 10} was evaluated with simulated lung fluids. • Most studied metal(loids) were highly bioaccessible in artificial lysosomal fluid. • Metal(loid)s from the industrial site had the highest bioaccessibility. • Elevated non-carcinogenic risk associated with Mn was found at the studied area. • Carcinogenic risk was slightly exceeded for Cd exposure at the industrial location. The content of metal(loid)s in particulate matter (PM) is of special concern due to their contribution to overall (PM) toxicity. In this study, the bioaccessibility and human health risk of potentially toxic metal(loid)s associated with PM{sub 10} were investigated in two areas of the Cantabrian region (northern Spain) with different levels of exposure: an industrial area mainly influenced by a ferromanganese alloy plant; and an urban area consisting mainly of residential and commercial activities, but also affected, albeit to a lesser extent by the ferroalloy plant. Total content and bioaccessible fractions in simulated lung fluids (SLFs) of Fe, Mn, Zn, Ni, Cu, Sb, Mo, Cd and Pb were determined by ICP-MS. Gamble's solution and artificial lysosomal fluid (ALF) were used to mimic different conditions inside the human respiratory system. A health risk assessment was performed based on the United States Environmental Protection Agency's (USEPA) methodology. Most metal(loid)s showed moderate and high bioaccessibility in Gamble's solution and ALF, respectively. Despite the high variability between the samples, metal(loid) bioaccessibility was found to be higher on average at the industrial site, suggesting a greater hazard to human health in the proximity of the main metal(loid) sources. Based on the results of the risk assessment, the non-carcinogenic risk associated with Mn exposure was above the safe limit (HQ> 1) under all the studied scenarios at the industrial site and under some specific scenarios at the urban location. The estimated carcinogenic inhalation risk for Cd exposure at the industrial site was found to be within the range between 1.0 × 10{sup −6} to 1.0 × 10{sup −4} (uncertainty range) under some scenarios. The results obtained in this study indicate that Mn and Cd inhalation exposure occurring in the vicinities of the studied areas may pose a human health risk.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Stochastic economic dispatch of wind power under uncertainty using clustering-based extreme scenarios

Operation of power systems with high penetrations of renewable energy sources requires tools for robust decision making under uncertainty. Stochastic economic dispatch and stochastic unit commitment are effective techniques for planning and operation under uncertainty, whose effectiveness depends on the cardinality and quality of the scenario set. Here, this article proposes a machine learning method using -means clustering for capturing relevant physical information from a large population of analog scenarios. Extreme scenario samples drawn from the clusters are used in a two-stage stochastic economic dispatch computation. The effectiveness of the proposed approach is assessed on a synthetic 200-bus system with a geographic footprint over Illinois, USA for four months from each season of WIND Toolkit data. The combination of -means clustering with importance sampling is shown to reduce the total operational cost by over 43% compared to sampling from populations based on heuristic clustering-based methods. Additionally, the variability in the mean cost is about 56% lower than the variability using Monte Carlo sampling. Moreover, the operational cost with the presented approach is shown to be close to the cost calculated based on a hindsight exact wind profile, signifying a highly accurate quantification of wind uncertainty by the presented -means clustering based sampling method.

17 WIND ENERGY↗
DOE OSTI2022

Getting lost tracking the carbon footprint of hydropower

In the transition to low-carbon electricity, well-quantified estimates of carbon dynamics are needed to ensure that emissions reduction targets are achieved. Here we review the state of the science on carbon accounting for hydropower reservoirs and identify limitations and future solutions. Nearly all research on reservoir greenhouse-gas (GHG) emissions has focused on individual reservoirs in isolation without considering their position in a freshwater network draining organic matter from upstream watersheds or the coordinated operation of reservoir cascades. Second, carbon inventories have extrapolated from a small, non-probabilistic sample of highly variable measurements of GHG emissions to unsampled reservoirs. A stronger statistical foundation is needed to estimate a global inventory and its uncertainty. Third, attribution to hydropower is based on ranks assigned to reservoir purpose. Instead, the physical influence of hydropower on carbon dynamics could be directly measured. Fourth, current carbon-accounting practices neglect time. A time-varying approach would quantify variation in emissions for electricity portfolios from changes in the fuel mix at different times and account for ancillary services, i.e., the ability to support the grid when variable renewables are not available without using natural gas. Reservoirs also sequester a significant portion of inflowing carbon in sediments and slow the carbon cycle by delaying the return of carbon to the atmosphere for decades to centuries. Together, these refinements would help to illuminate pathways toward meeting energy demand with the longest-possible delay in returning carbon to the atmosphere and without adding ancient sources to the pool of carbon cycling through aquatic ecosystems.

13 HYDRO ENERGY↗
DOE OSTI2022

Comparative Analysis of Corrinoid Profiles across Host-Associated and Environmental Samples

Vitamin B 12 (the cyanated form of cobalamin cofactors) is best known for its essential role in human health. In addition to its function in human metabolism, cobalamin also plays important roles in microbial metabolism and can impact microbial community function. Cobalamin is a member of the structurally diverse family of cofactors known as cobamides that are produced exclusively by certain prokaryotes. Cobamides are considered shared nutrients in microbial communities because the majority of bacteria that possess cobamide-dependent enzymes cannot synthesize cobamides de novo. Furthermore, different microbes have evolved metabolic specificity for particular cobamides, and therefore, the availability of cobamides in the environment is important for cobamide-dependent microbes. Determining the cobamides present in an environment of interest is essential for understanding microbial metabolic interactions. By examining the abundances of different cobamides in diverse environments, including 10 obtained in this study, we find that, contrary to its preeminence in human metabolism, cobalamin is relatively rare in many microbial habitats. Comparison of cobamide profiles of mammalian gastrointestinal samples and wood-feeding insects reveals that host-associated cobamide abundances vary and that fecal cobamide profiles differ from those of their host gastrointestinal tracts. Environmental cobamide profiles obtained from aquatic, soil, and contaminated groundwater samples reveal that the cobamide compositions of environmental samples are highly variable. As the only commercially available cobamide, cobalamin is routinely supplied during microbial culturing efforts. Furthermore, these findings suggest that cobamides specific to a given microbiome may yield greater insight into nutrient utilization and physiological processes that occur in these habitats.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Controls on Barite (BaSO 4 ) Precipitation in Unconventional Reservoirs

Barite (BaSO 4 ) precipitation is one of the most ubiquitous examples of secondary sulfate mineral scaling in shale oil and gas reservoirs. Often, a suite of chemical additives is used during fracturing operations to inhibit the accumulation of mineral scales, though their efficacy is widely varied and poorly understood. This study combines experimental data and multi-component numerical reactive transport modeling to offer a more comprehensive understanding of the geochemical behavior of barite accumulation in shale matrices under conditions typical of fracturing operations. A variety of additives and conditions are individually tested in batch reactor experiments to identify the factors controlling barite precipitation. Our experimental results demonstrate a pH dependence in the rate of barite precipitation, which we use to develop a predictive model including a pH-dependent term that satisfactorily reproduces our observations. Further, this model is then extended to consider the behavior of three major shale samples of highly variable mineralogy (Eagle Ford, Marcellus, and Barnett). This data-validated model offers a reliable tool to predict and ultimately mitigate against secondary mineral accumulation in unconventional shale reservoirs.

54 ENVIRONMENTAL SCIENCES↗