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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Western North Pacific Tropical Cyclone Model Tracks in Present and Future Climates

Western North Pacific tropical cyclone (TC) model tracks are analyzed in two large multimodel ensembles, spanning a large variety of models and multiple future climate scenarios. Two methodologies are used to synthesize the properties of TC tracks in this large data set: cluster analysis and mass moment ellipses. First, the models' TC tracks are compared to observed TC tracks' characteristics, and a subset of the models is chosen for analysis, based on the tracks' similarity to observations and sample size. Potential changes in track types in a warming climate are identified by comparing the kernel smoothed probability distributions of various track variables in historical and future scenarios using a Kolmogorov-Smirnov significance test. Two track changes are identified. The first is a statistically significant increase in the north-south expansion, which can also be viewed as a poleward shift, as TC tracks are prevented from expanding equatorward due to the weak Coriolis force near the equator. The second change is an eastward shift in the storm tracks that occur near the central Pacific in one of the multimodel ensembles, indicating a possible increase in the occurrence of storms near Hawaii in a warming climate. The dependence of the results on which model and future scenario are considered emphasizes the necessity of including multiple models and scenarios when considering future changes in TC characteristics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Protonation Dynamics of Confined Ethanol–Water Mixtures in H-ZSM-5 from Machine Learning-Driven Metadynamics

Zeolites are indispensable heterogeneous catalysts in industrial chemical processes, valued for their strong Brønsted acidity, well-defined microporous frameworks, and tunable pore structures. Their catalytic activity arises primarily from Brønsted acid sites (BAS), typically present as bridging hydroxyl groups (Si–OH–Al). Under aqueous reaction conditions, these protons interact dynamically with water and alcohol molecules, leading to complex solvation and protonation behavior within confined pores. In this study, we investigate the protonation equilibrium occurring between ethanol and water at the BAS of acidic zeolites under varying hydration levels, i.e., C2H5OH–(H2O)n, n=1–4. Local structure was analyzed through an adaptive-learning global optimization algorithm, while enhanced sampling molecular dynamics simulations with Well-Tempered Metadynamics (WMetaD) and machine learning interatomic potentials (MLPs) provide free-energy surfaces (FES) at variable hydration levels. The results reveal a strong dependence of proton localization on the degree of hydration. At low hydration (1 water molecule), the proton resides predominantly on ethanol; with 2 water molecules, it shifts toward water, and at higher hydration (3 or more water molecules), it becomes extensively delocalized over the water cluster. These findings underscore the critical role of solvation in modulating acid site behavior and suggest that a minimum of three water molecules is necessary to fully stabilize the proton on water within the zeolite framework. This solvation threshold has significant implications for catalytic processes, particularly in biomass conversion reactions where alcohol protonation is a key step in dehydration mechanisms.

machine learning↗
DOE OSTI2023

Automatic detection of cataclysmic variables from SDSS images

Abstract Investigating rare and new objects have always been an important direction in astronomy. Cataclysmic variables (CVs) are ideal and natural celestial bodies for studying the accretion process of semi-detached binaries with accretion processes. However, the sample size of CVs must increase because a lager gap exists between the observational and the theoretical expanding CVs. Astronomy has entered the big data era and can provide massive images containing CV candidates. CVs as a type of faint celestial objects, are highly challenging to be identified directly from images using automatic manners. Deep learning has rapidly developed in intelligent image processing and has been widely applied in some astronomical fields with excellent detection results. YOLOX, as the latest YOLO framework, is advantageous in detecting small and dark targets. This work proposes an improved YOLOX-based framework according to the characteristics of CVs and Sloan Digital Sky Survey (SDSS) photometric images to train and verify the model to realise CV detection. We use the Convolutional Block Attention Module to increase the number of output features with the feature extraction network and adjust the feature fusion network to obtain fused features. Accordingly, the loss function is modified. Experimental results demonstrate that the improved model produces satisfactory results, with average accuracy (mean average Precision at 0.5) of 92.0%, Precision of 92.9%, Recall of 94.3%, and $F1-score$ of 93.6% on the test set. The proposed method can efficiently achieve the identification of CVs in test samples and search for CV candidates in unlabeled images. The image data vastly outnumber the spectra in the SDSS-released data. With supplementary follow-up observations or spectra, the proposed model can help astronomers in seeking and detecting CVs in a new manner to ensure that a more extensive CV catalog can be built. The proposed model may also be applied to the detection of other kinds of celestial objects.

Astronomy & Astrophysics↗
DOE OSTI2019

Radiation damage effects in chlorite investigated using microfocus synchrotron techniques

A detailed understanding of the mechanisms and effects of radiation damage in phyllosilicate minerals is a necessary component of the evaluation of the safety case for a deep geological disposal facility (GDF) for radioactive waste. Structural and chemical changes induced by a-particle damage will affect these mineral’s performance as a reactive barrier material (both in the near and far-field) over timescales relevant to GDF integrity. In this study, two examples of chlorite group minerals have been irradiated at a-particle doses comparable to those predicted to be experienced by the clay buffer material surrounding high level radioactive waste canisters. Crystallographic aberrations induced by the focused 4He2+ ion beam are revealed via high-resolution, microfocus X-ray diffraction mapping. Interlayer collapse by up to 0.5 Å is prevalent across both macro- and micro-crystalline samples, with the macro-crystalline specimen displaying a breakdown of the phyllosilicate structure into loosely-connected, multi-oriented crystallites displaying variable lattice parameters. The damaged lattice parameters suggest a localised breakdown and collapse of the OH- rich, ‘brucite-like’ interlayer. Microfocus Fe K-edge X-ray absorption spectroscopy illustrates this defect accumulation, manifest as a severe damping of the X-ray absorption edge. Subtle Fe2+/Fe3+ speciation changes are apparent across the damaged structures. A trend towards Fe reduction is evident at depth in the damaged structures at certain doses (8.76 x 1015 alpha particles/ cm2). Interestingly, this reductive trend does not increase with radiation dose, indeed at the maximum dose (1.26 x 1016 alpha particles/ cm2) administered in this study, there is evidence for a slight increase in Fe binding energy, suggesting the development of a depth-dependant redox gradient concurrent with light ion damage. At the doses examined here, these damaged structures are likely highly reactive, as sorption capacity will, to an extent, be largely enhanced by lattice disruption and an increase in available ‘edge’ sites.

Bower, William R.↗
DOE OSTI2024

Metadynamics investigation of lanthanide solvation free energy landscapes and insights into separations energetics

Lanthanide ion solvation chemistry in nonaqueous phases is key to understanding and developing effective separation processes for these critical materials. Due to the complexity and inherent disorder of the solution phase, a comprehensive picture of the solvated metal ion is often difficult to generate solely from conventional spectroscopic approaches and electronic structure calculations, particularly in the extractant phase. In this work, we use classical molecular dynamics (MD) simulation with an advanced sampling technique, metadynamics, supplemented by experimental spectroscopy and speciation analysis, to measure lanthanide solvation free energy landscapes. We define coordination-based collective variables to probe the entire range of solvation configurations in the organic phase of lanthanum (La), europium (Eu), and lutetium (Lu) nitrate salts bound with a commonly used extractant, N,N′-dimethyl, N,N′-dioctylhexylethoxymalonamide (DMDOHEMA). The known lanthanide extraction trend of La ≈ Eu > Lu is readily explained by the measured free energy surfaces, which show consistent DMDOHEMA coordination from La to Eu, followed by loss of DMDOHEMA coordination from Eu to Lu. These simulations suggest how ligand crowding at the metal center can control selectivity, in this case resulting in the opposite extraction trend as observed with other conventional extractants, where the enthalpic contribution from increasing lanthanide charge density across the series dominates the extraction energetics. We also find that the presence of inner-sphere water, verified by time-resolved fluorescence, diversifies the accessible solvation structures. As a result, understanding solvation requires consideration of an entire thermodynamic ensemble, rather than the single dominant lowest-energy structure, as is often considered out of necessity in interpretation of spectroscopic data or in electronic structure-based ligand design approaches. In general, we demonstrate how metadynamics uniquely enables investigation of complex, multidimensional solvation energetic landscapes, and how it can explain selectivity trends where extraction is controlled by more complex mechanisms than simple charge density-based selectivity.

Wang, Xiaoyu↗
DOE OSTI2021

Mechanical Response of Castlegate Sandstone under Hydrostatic Cyclic Loading

The stress history of rocks in the subsurface affects their mechanical and petrophysical properties. Rocks can often experience repeated cycles of loading and unloading due to fluid pressure fluctuations, which will lead to different mechanical behavior from static conditions. This is of importance for several geophysical and industrial applications, for example, wastewater injection and reservoir storage wells, which generate repeated stress perturbations. Laboratory experiments were conducted with Castlegate sandstone to observe the effects of different cyclic pressure loading conditions on a common reservoir analogue. Each sample was hydrostatically loaded in a triaxial cell to a low effective confining pressure, and either pore pressure or confining pressure was cycled at different rates over the course of a few weeks. Fluid permeability was measured during initial loading and periodically between stress cycles. Samples that undergo cyclic loading experience significantly more inelastic (nonrecoverable) strain compared to samples tested without cyclic hydrostatic loading. Permeability decreases rapidly for all tests during the first few days of testing, but the decrease and variability of permeability after this depend upon the loading conditions of each test. Cycling conditions do affect the mechanical behavior; the elastic moduli decrease with the increasing loading rate and stress cycling. The degree of volumetric strain induced by stress cycles is the major control on permeability change in the sandstones, with less compaction leading to more variation from measurement to measurement. The data indicate that cyclic loading degrades permeability and porosity more than static conditions over a similar period, but the petrophysical properties are dictated more by the hydrostatic loading rate rather than the total length of time stress cycling is imposed.

58 GEOSCIENCES↗
DOE OSTI2021

Anomaly Attribution with Likelihood Compensation

This paper addresses the task of explaining anomalous predictions of a black-box regression model. When using a black-box model, such as one to predict building energy consumption from many sensor measurements, we often have a situation where some observed samples may significantly deviate from their prediction. It may be due to a sub-optimal black-box model, or simply because those samples are outliers. In either case, one would ideally want to compute a responsibility score indicative of the extent to which an input variable is responsible for the anomalous output. In this work, we formalize this task as a statistical inverse problem: Given model deviation from the expected value, infer the responsibility score of each of the input variables. We propose a new method called likelihood compensation (LC), which is founded on the likelihood principle and computes a correction to each input variable. To the best of our knowledge, this is the first principled framework that computes a responsibility score for real valued anomalous model deviations. We apply our approach to a real-world building energy prediction task and confirm its utility based on expert feedback.

Idé, Tsuyoshi↗
DOE OSTI2017

Stan : A Probabilistic Programming Language

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can also be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Microbiomes Associated With Foods From Plant and Animal Sources

Food microbiome composition impacts food safety and quality. The resident microbiota of many food products is influenced throughout the farm to fork continuum by farming practices, environmental factors, and food manufacturing and processing procedures. Currently, most food microbiology studies rely on culture-dependent methods to identify bacteria. However, advances in high-throughput DNA sequencing technologies have enabled the use of targeted 16S rRNA gene sequencing to profile complex microbial communities including non-culturable members. In this study we used 16S rRNA gene sequencing to assess the microbiome profiles of plant and animal derived foods collected at two points in the manufacturing process; post-harvest/pre-retail (cilantro) and retail (cilantro, masala spice mixes, cucumbers, mung bean sprouts, and smoked salmon). Our findings revealed microbiome profiles, unique to each food, that were influenced by the moisture content (dry spices, fresh produce), packaging methods, such as modified atmospheric packaging (mung bean sprouts and smoked salmon), and manufacturing stage (cilantro prior to retail and at retail). The masala spice mixes and cucumbers were comprised mainly of Proteobacteria, Firmicutes, and Actinobacteria. Cilantro microbiome profiles consisted mainly of Proteobacteria, followed by Bacteroidetes, and low levels of Firmicutes and Actinobacteria. The two brands of mung bean sprouts and the three smoked salmon samples differed from one another in their microbiome composition, each predominated by either by Firmicutes or Proteobacteria. These data demonstrate diverse and highly variable resident microbial communities across food products, which is informative in the context of food safety, and spoilage where indigenous bacteria could hamper pathogen detection, and limit shelf life.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A SEARCH FOR SHORT-PERIOD ROCKY PLANETS AROUND WDs WITH THE COSMIC ORIGINS SPECTROGRAPH (COS)

The search for transiting habitable exoplanets has broadened to include several types of stars that are smaller than the Sun in an attempt to increase the observed transit depth and hence the atmospheric signal of the planet. Of all spectral types, white dwarfs (WDs) are the most favorable for this type of investigation. The fraction of WDs that possess close-in rocky planets is unknown, but several large angle stellar surveys have the photometric precision and cadence to discover at least one if they are common. Ultraviolet observations of WDs may allow for detection of molecular oxygen or ozone in the atmosphere of a terrestrial planet. We use archival Hubble Space Telescope data from the Cosmic Origins Spectrograph to search for transiting rocky planets around UV-bright WDs. In the process, we discovered unusual variability in the pulsating WD GD 133, which shows slow sinusoidal variations in the UV. While we detect no planets around our small sample of targets, we do place stringent limits on the possibility of transiting planets, down to sub-lunar radii. We also point out that non-transiting small planets in thermal equilibrium are detectable around hotter WDs through infrared excesses, and identify two candidates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Variability in the Massive Open Cluster NGC 1817 from K2: A Rich Population of Asteroseismic Red Clump, Eclipsing Binary, and Main-sequence Pulsating Stars

We present a survey of variable stars detected in K2 Campaign 13 within the massive intermediate-age (∼1 Gyr) open cluster NGC 1817. We identify a complete sample of 44 red clump stars in the cluster, and have measured asteroseismic quantities (ν {sub max} and/or Δν) for 29 of them. Five stars showed suppressed dipole modes, and the occurrence rates indicate that mode suppression is unaffected by evolution through core helium burning. A subset of the giants in NGC 1817 (and in the similarly aged cluster NGC 6811) have ν {sub max} and Δν values at or near the maximum observed for core helium–burning stars, indicating they have core masses near the minimum for fully nondegenerate helium ignition. Further asteroseismic study of these stars can constrain the minimum helium core mass in red clump stars and the physics that determines this limit. Two giant stars show photometric variations on timescales similar to previously measured spectroscopic orbits. Thirteen systems in the field show eclipses, but only five are probable cluster members. We identify 32 δ Sct pulsators, 27 γ Dor candidates, and 7 hybrids that are probable cluster members, with most being new detections. We used the ensemble properties of the δ Sct stars to identify stars with possible radial pulsation modes. Among the oddities we have uncovered are: an eccentric orbit for a short-period binary containing a δ Sct pulsating star; a rare subgiant within the Hertzsprung gap showing δ Sct pulsations; and two hot γ Dor pulsating star candidates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Age and chemistry of dissolved organic carbon reveal enhanced leaching of ancient labile carbon at the permafrost thaw zone

Abstract. Climate change will alter the balance between frozen and thawed conditions in Arctic systems. Increased temperatures will make the extensive northern permafrost carbon stock vulnerable to decomposition and translocation. Production, cycling, and transport of dissolved organic carbon (DOC) are crucial processes for high-latitude ecosystem carbon loss that result in considerable export off the Arctic landscape. To identify where and under what conditions permafrost DOC is mobilized in an Arctic headwater catchment, we measured radiocarbon (14C) of DOC and assessed DOC composition with ultraviolet–visible spectroscopy (UV–Vis) of surface waters and shallow and deep subsurface porewaters from 17 drainages in the Barrow Environmental Observatory in Alaska. Samples were collected in July and September 2013 to assess changes in age and chemistry of DOC over time. DOC age was highly variable ranging from modern (19 ‰ Δ14C) to approximately 7000 BP (−583 ‰ Δ14C). DOC age increased with depth, over the summer as the active layer deepened, and with increasing drainage size. DOC quality indicators reflected a DOC source rich in high molecular-weight and aromatic compounds, characteristics consistent with vegetation-derived organic matter that had undergone little microbial processing, throughout the summer and a weak relationship with DOC age. In deep porewaters, DOC age was also correlated with several biogeochemical indicators (including dissolved methane concentration, δ13C, and the apparent fractionation factor), suggesting a coupling between carbon and redox biogeochemistry influencing methane production. In the drained thawed lake basins included in this study, DOC concentrations and contributions of vegetation-derived organic matter declined with increasing basin age. The weak relationship between DOC age and chemistry and consistency in DOC chemical indicators over the summer suggest a high lability of old DOC released by thawing permafrost.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

PageRank as a Collective Variable to Study Complex Chemical Transformations and Their Energy Landscapes

A reduced set of reaction coordinates are often employed in chemistry to describe the collective change between reactants and products within the context of rare event theories and in the exploration of energy landscapes. While incredibly powerful, use of these collective variables becomes increasingly challenging as the systems under study become more complex. Recent advancement of new descriptions of collective molecular coordinates have included PageRank (PR) analysis of the network of interactions about molecules and atoms within a system. Herein, PR is developed as a continuous variable that not only captures chemical transformations but can also be employed as a collective variable for a process that could span a highly dimensional energy surface. The derivatives of PR with respect to atomic coordinates are presented, and subsequently combined with forces during a chemical transformation within biased molecular dynamics sampling simulations to create the potential of mean force (PMF). This technique is demonstrated for two reactions: 1) the transformation of tetrahedral [Al(OH)4]-(aq) to octahedral [Al(OH)4(H2O)2]-(aq), and 2) the formation of contact ion pairs (CIPs) and solvent separated ion pairs (SSIPs) of Na+ and OH- in bulk water. Comparison of the behavior of the PR collective variable in both examples reveals that the ability of the PR to resolve local versus extended configurational attributes is tuned by the size of the network employed. This is a unique feature of PageRank that enables control over the resolution of the PMF that is produced.

chemistry, theories, PageRank↗
DOE OSTI2017

Synchrotron FTIR imaging of OH in quartz mylonites

Previous measurements of water in deformed quartzites using conventional Fourier transform infrared spectroscopy (FTIR) instruments have shown that water contents of larger grains vary from one grain to another. However, the non-equilibrium variations in water content between neighboring grains and within quartz grains cannot be interrogated further without greater measurement resolution, nor can water contents be measured in finely recrystallized grains without including absorption bands due to fluid inclusions, films, and secondary minerals at grain boundaries. Synchrotron infrared (IR) radiation coupled to a FTIR spectrometer has allowed us to distinguish and measure OH bands due to fluid inclusions, hydrogen point defects, and secondary hydrous mineral inclusions through an aperture of 10 µm for specimens > 40 µm thick. Doubly polished infrared (IR) plates can be prepared with thicknesses down to 4–8 µm, but measurement of small OH bands is currently limited by strong interference fringes for samples < 25 µm thick, precluding measurements of water within individual, finely recrystallized grains. By translating specimens under the 10 µm IR beam by steps of 10 to 50 µm, using a software-controlled x - y stage, spectra have been collected over specimen areas of nearly 4.5 mm 2 . This technique allowed us to separate and quantify broad OH bands due to fluid inclusions in quartz and OH bands due to micas and map their distributions in quartzites from the Moine Thrust (Scotland) and Main Central Thrust (Himalayas). Mylonitic quartzites deformed under greenschist facies conditions in the footwall to the Moine Thrust (MT) exhibit a large and variable 3400 cm -1 OH absorption band due to molecular water, and maps of water content corresponding to fluid inclusions show that inclusion densities correlate with deformation and recrystallization microstructures. Quartz grains of mylonitic orthogneisses and paragneisses deformed under amphibolite conditions in the hanging wall to the Main Central Thrust (MCT) exhibit smaller broad OH bands, and spectra are dominated by sharp bands at 3595 to 3379 cm -1 due to hydrogen point defects that appear to have uniform, equilibrium concentrations in the driest samples. The broad OH band at 3400 cm -1 in these rocks is much less common. The variable water concentrations of MT quartzites and lack of detectable water in highly sheared MCT mylonites challenge our understanding of quartz rheology. However, where water absorption bands can be detected and compared with deformation microstructures, OH concentration maps provide information on the histories of deformation and recovery, evidence for the introduction and loss of fluid inclusions, and water weakening processes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud top occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography over land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing. The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. Lastly, in Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.

58 GEOSCIENCES↗
DOE OSTI2016

Source and distribution of naturally occurring arsenic in groundwater from Alberta’s Southern Oil Sands Regions

Arsenic (As) concentrations as high as 179 μg/L have been observed in shallow groundwater in the Alberta’s Southern Oil Sand Regions. The geology of this area of Alberta includes a thick cover (up to 200 m) of unconsolidated glacial deposits, with a number of regional interglacial sand and gravel aquifers, underlain by marine shale. Arsenic concentrations observed in 216 unconsolidated sediment samples ranged from 1 and 17 ppm. A survey of over 800 water wells sampled for As in the area found that 50% of the wells contained As concentrations exceeding drinking water guidelines of 10 μg/L. Higher As concentrations in groundwater were associated with reducing conditions. Measurements of As speciation from 175 groundwater samples indicate that As(III) was the dominant species in 74% of the wells. Speciation model calculations showed that the majority of groundwater samples were undersaturated with respect to ferrihydrite, suggesting that reductive dissolution of Fe-oxyhydroxides may be the source of some As in groundwater. Detailed mineralogical characterization of sediment samples collected from two formations revealed the presence of fresh framboidal pyrite in the deeper unoxidized sediments. Electron microprobe analysis employing wavelength dispersive spectrometry indicated that the framboidal pyrite had variable As content with an average As concentration of 530 ppm, reaching up to 1840 ppm. In contrast, the oxidized sediments did not contain framboidal pyrite, but exhibited spheroidal Fe-oxyhydroxide grains with elevated As concentrations. The habit and composition suggest that these Fe-oxyhydroxide grains in the oxidized sediment were an alteration product of former framboidal pyrite grains. X-ray absorption near edge spectroscopy (XANES) indicated that the oxidized sediments are dominated by As(V) species having spectral features similar to those of goethite or ferrihydrite with adsorbed As, suggesting that Fe-oxyhydroxides are the dominant As carriers. XANES spectra collected on unoxidized sediment samples, in contrast, indicated the presence of a reduced As species (As(-I)) characteristic of arsenopyrite and arsenian pyrite. The results of the mineralogical analyses indicate that the oxidation of framboidal pyrite during weathering may be the source of As released to shallow aquifers in this region.

58 GEOSCIENCES↗
DOE OSTI2024

Soil Carbon and Nitrogen Stocks Across Hillslopes Underlain by Continuous Permafrost in the Northern Arctic Foothills, Alaska, United States

Constraining the variability of soil organic carbon (SOC) and total nitrogen (TN) stocks across hillslopes in Low Arctic permafrost-affected landscapes remains a significant challenge for improving global estimates of permafrost SOC stocks. We investigated SOC and TN stocks across hillslopes at two sites in the Arctic Foothills of Alaska, United States (Happy Valley and Sagwon Hills). Average SOC and TN stocks for the 0–1-m depth interval were high (52.0 ± 15.1 kg C m −2 and 2.74 ± 0.82 kg N m −2 ) and linearly related ( R 2 = 0.74, p < 0.0001). Unlike soils of other permafrost and nonpermafrost landscapes, variability was greatest within rather than between hillslope positions. Furthermore, SOC and TN stocks in the surface 1 m did not exhibit strong patterns by hillslope position and were only weakly associated with major geomorphic parameters that typically predict SOC and TN stocks well in other landscapes. Although sampling at upper hillslope positions was largely limited to depths of less than 1.5 m due to the presence of coarse fragments in reworked glacial till, deeper observations at lower hillslope positions (footslopes, toeslopes, and basins) revealed significantly larger SOC stocks (92.0 ± 18.0 kg C m −2 at 2 m; 117.1 ± 10.4 kg C m −2 at 3 m). The unique small-scale variability in ice content, cryoturbation, patterned ground, and organic layer thickness on these broad, Low Arctic sites contributes to the relatively homogeneous distribution of SOC and TN stocks across hillslope positions in the top 1 m, but a future focus on deeper sampling may reveal greater differences in SOC and TN stocks.

54 ENVIRONMENTAL SCIENCES↗