Search NASA⌕ Search

SEARCH · Search NASA

Results for “depth data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Improved Representation of the Global Dust Cycle Using Observational Constraints on Dust Properties and Abundance

Even though desert dust is the most abundant aerosol by mass in Earth’s atmosphere, atmospheric models 25 struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused byfundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, 30 extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global 35 basis, we find that the emission flux of dust with geometric diameter up to 20 μm (PM20) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current 40 model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

aerosols, dust↗
NASA NTRS2014

Mars Science Laboratory (MSL) Entry, Descent, and Landing Instrumentation (MEDLI): Complete Flight Data Set

The Mars Science Laboratory (MSL) entry vehicle (EV) successfully entered the Mars atmosphere and landed the Curiosity rover safely on the surface of the planet in Gale crater on August 6, 2012. MSL carried the MSL Entry, Descent, and Landing (EDL) Instrumentation (MEDLI). MEDLI delivered the first in-depth understanding of the Mars entry environments and the response of the entry vehicle to those environments. MEDLI was comprised of three major subsystems: the Mars Entry Atmospheric Data System (MEADS), the MEDLI Integrated Sensor Plugs (MISP), and the Sensor Support Electronics (SSE). Ultimately, the entire MEDLI sensor suite consisting of both MEADS and MISP provided measurements that were used for trajectory reconstruction and engineering validation of aerodynamic, atmospheric, and thermal protection system (TPS) models in addition to Earth-based systems testing procedures. This report contains in-depth hardware descriptions, performance evaluation, and data information of the three MEDLI subsystems.

Cheatwood, F. McNeil↗
DOE OSTI2023

Robust In-Situ Strain Measurements to Monitor CO 2 Storage

The goal of this project was to develop and demonstrate robust instrumentation to monitor the in-situ strain tensor in order to improve the reliability and security of CO 2 storage in geologic formations. We met the original goals of the project and the major overarching accomplishment is the advancement of strain tensor monitoring from an intriguing concept to a commercially available technology with a solid foundation of novel instruments supported by theoretical analyses and validation experiments. The main accomplishments of the project are summarized below. We designed, built and evaluated nine new optical fiber strainmeters and tiltmeters using Michelson interferometers to measure deformation with ultra-high resolution at both shallow and deep point locations in the subsurface. These are the robust strainmeters that motivated the title of the project. We designed, built and evaluated a novel method of measuring distributed strain in optical fibers with nanostrain resolution, and cm-scale location, and sampling into the seismic band. The new method is called Coherence-length-gated Microwave Photonics Interfereometry (CMPI). CMPI technology has advantages over existing commercial DAS and DSS methods. We developed and demonstrated capabilities to deploy instruments in the field and used them to measure strain caused by ambient signals like barometric pressure and tides, as well as induced signals like surface loading and pore pressure changes from pumping tests. We deployed a working strainmeter at 1,700 ft depth, slightly above an active reservoir. This is to our knowledge the greatest depth a strainmeter has been deployed and the techniques we used can readily be extended to greater depths. Optical fiber borehole tensor strainmeter techology was advanced from a TRL 4 at the start, to a TRL of 7 at the conclusion of the project. The project included advances in simulations and theoretical analyses. We developed and demonstrated a computational workflow that uses machine learning to reduce the computational requirements and make it practical to use Bayesian inversion to solve large numerical poroelastic analyses needed to interpret strain tensor field data. We evaluated the strain tensor fields and time series that would be caused by leaks of CO 2 or other fluids from reservoirs. These simulations demonstrated that signals from leaks could be measured with instruments developed for the project, opening a potentially new method for ensuring storage security. We showed that strains in caprock can be used to estimate pressure in a reservoir. This avoids the need to drill monitoring wells into the reservoir, and it expands the capabilities of monitoring in the caprock. The project includes a derivation and application of a novel analytical solution to the strains in the vicinity of a pressurized poroelastic inclusion. This solution explains field data measured during injeciton tests at the North Avant Field, and it will simplify future interpretation of strain tensor data. The project included a broad range of experiments, and of the most significant is the characterization of the strain tensor at an array three strainmeters during six injection tests at the North Avant Field, Oklahoma. This demonstrated repeatability of the strain signal measured by the new instruments developed for the project, and it showed similarities between the strain signal at shallow depths and pressure in the underlying reservoir. We also demonstrated that useful strain data can be measured at reservoir depths. This confirms that strain tensor data can be measured throughout the caprock over a reservoir. The project demonstrated the feasibility of using the strain tensor and distributed strain measured in caprock during a variety of different well tests where the pumping rate was constant, sinusoidal and positive, or a periodic square wave with zero net rate. This further strengthens the validity of using strain data to characterize reservoirs and aquifers. We also demonstrated that strain caused be fluctuations of air pressure and water pressure in the vadose zone can be measured and interpreted, suggesting that high resolution distributed strain measurements hold promise for monitoring the vadose zone. The project partially supported nine graduate students in the Environmental Engineering, Hydrogeology, Electrical Engineering programs at Clemson University. The research was described in nine journal papers, 23 talks and conference abstracts. Additional journal papers are in preparation. A new company called Tensora was started to provide strainmeter technology for commercial applications.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1962

Investigation of the Damping of Liquids in Right-Circular Cylindrical Tanks, Including the Effects of a Time-Variant Liquid Depth

An experimental investigation was conducted to determine the effects of several basic variables upon the damping of the fundamental antisymmetric mode of liquids in right-circular cylindrical tanks without baffles. The variables examined include liquid depth, efflux rate, liquid amplitude, kinematic viscosity, and tank size. The data are presented in dimensionless form and compared with available theory. For the range of variables examined, variations of efflux rate and liquid amplitude were found to have no significant effects on the liquid damping. The following theoretical relationship was found to be adequate for the prediction of the variation of damping with liquid depth, kinematic viscosity, and tank size: [for equation see full text] where v is the kinematic viscosity, R is the cylinder radius, g is the acceleration due to gravity, and h is the liquid depth. However, the constant K was experimentally found in this investigation to have the value 5.23, which is 50 percent higher than the theoretically predicted value.

TANK↗
DOE OSTI2019

Utah FORGE Seismicity Associated with the 2019 Well 58-32 Stimulation

This catalog describes the seismicity associated with the 2019 stimulation at Utah FORGE. Containing both matched-filter detections (Dzubay et al., 2022) and Schlumberger-recorded events (detected with a 12-level geophone string), the final combined catalog contains a total of 534 microseismic events spanning -2.0 Mw to -0.1 Mw. Users may differentiate between SLB and MF events using the fact that SLB event magnitudes are recorded to a higher level of precision (MF mags determined using relative amplitude ratios). Users should be wary of locations and depths (measured from sea level) for MF events, as all detections were assigned the same locations as their template events.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

A declining spring snowpack is expected to have widespread effects on montane and subalpine forests in western North America and across the globe. The way that tree water demands respond to this change will have important impacts on forest health and downstream water subsidies. Here, we present data from a network of sap velocity sensors and xylem water isotope measurements from three common tree species (Picea engelmannii, Abies lasiocarpa and Populus tremuloides) across a hillslope transect in a subalpine watershed in the Upper Colorado River basin. We use these data to compare tree- and stand-level responses to the historically high spring snowpack but low summer rainfall of 2019 against the low spring snowpack but high summer rainfall amounts of 2021 and 2022. From the sap velocity data, we found that only 40 % of the trees showed an increase in cumulative transpiration in response to the large snowpack year (2019), illustrating the absence of a common response to interannual spring snowpack variability. The trees that increased water use during the year with the large spring snowpack were all found in dense canopy stands – irrespective of species – while trees in open-canopy stands were more reliant on summer rains and, thus, more active during the years with modest snow and higher summer rain amounts. Using the sap velocity data along with supporting measurements of soil moisture and snow depth, we propose three mechanisms that lead to stand density modulating the tree-level response to changing seasonality of precipitation: Topographically mediated convergence zones have consistent access to recharge from snowmelt which supports denser stands with high water demands that are more reliant and sensitive to changing snow. Interception of summer rain in dense stands reduces the throughfall of summer rain to surface soils, limiting the sensitivity of the dense stands to changes in summer rain. Shading in dense stands allows the snowpack to persist deeper into the growing season, providing high local reliance on snow during the fore-summer (early-summer) drought period. Combining data generated from natural gradients in stand density, like this experiment, with results from controlled forest-thinning experiments can be used to develop a better understanding of the responses of forested ecosystems to futures with reduced spring snowpack.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of survey spatial variability on galaxy redshift distributions and the cosmological 3 × 2-point statistics for the Rubin Legacy Survey of Space and Time (LSST)

We investigate the impact of spatial survey non-uniformity on the galaxy redshift distributions for forthcoming data releases of the Rubin Observatory Legacy Survey of Space and Time (LSST). Specifically, we construct a mock photometry data set degraded by the Rubin OpSim observing conditions, and estimate photometric redshifts of the sample using a template-fitting photo-z estimator, BPZ, and a machine learning method, FlexZBoost. We select the Gold sample, defined as $i\lt 25.3$ for 10 yr LSST data, with an adjusted magnitude cut for each year and divide it into five tomographic redshift bins for the weak lensing lens and source samples. We quantify the change in the number of objects, mean redshift, and width of each tomographic bin as a function of the coadd i-band depth for 1-yr (Y1), 3-yr (Y3), and 5-yr (Y5) data. In particular, Y3 and Y5 have large non-uniformity due to the rolling cadence of LSST, hence provide a worst-case scenario of the impact from non-uniformity. We find that these quantities typically increase with depth, and the variation can be $10\!-\!40~{{\rm per\ cent}}$ at extreme depth values. Using Y3 as an example, we propagate the variable depth effect to the weak lensing $3\times 2$ pt analysis, and assess the impact on cosmological parameters via a Fisher forecast. We find that galaxy clustering is most susceptible to variable depth, and non-uniformity needs to be mitigated below 3 per cent to recover unbiased cosmological constraints. There is little impact on galaxy–shear and shear–shear power spectra, given the expected LSST Y3 noise.

cosmology↗
NASA NTRS2000

BOREAS TE-6 1994 Soil and Air Temperatures in the NSA

The BOREAS TE-6 team collected several data sets to examine the influence of vegetation, climate, and their interactions on the major carbon fluxes for boreal forest species. This data set contains measurements of the air temperature at a single height and soil temperature at several depths in the NSA from 25-May to 08-Oct- 1994. Chromel-Constantan thermocouple wires run by a miniprogrammable data logger (Model 21X, Campbell Scientific, Inc., Logan, UT) provided direct measurements of temperature. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distrobuted Activity Archive Center (DAAC).

Hall, Forrest G.↗
DOE OSTI2023

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential while Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗
DOE OSTI2024

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential While Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics: Preprint

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗
DOE OSTI2023

Equation of state for He bubbles in W and model of He bubble growth and bursting near W{100} surfaces derived from molecular dynamics simulations

Abstract Molecular dynamics (MD) simulations are performed to derive an equation of state (EOS) for helium (He) bubbles in tungsten (W) and to study the growth of He bubbles under a W(100) surface until they burst. We study the growth as a function of the initial nucleation depth of the bubbles. During growth, successive loop-punching events are observed, accompanied by shifts in the depth of the bubble towards the surface. Subsequently, the MD data are used to derive models that describe the conditions that cause the loop punching and bursting events. Simulations have been performed at 500, 933, 1500, 2000, and 2500 K to fit the parameters in the models. To compute the pressure in the bubble at the loop punching and bursting events from the models, we derive an EOS for He bubbles in tungsten with an accompanying volume model to compute the bubble volume for a given number of vacancies ( $$N_\text {V}$$ N V ), He atoms ( $$N_\text {He}$$ N He ), and temperature ( T ). To derive the bubble EOS, we firstly derive the EOS for a free He gas. The derived free-gas EOS can accurately predict all MD data included in the analysis (which span up to 54 GPa at 2500 K). Subsequently, the bubble EOS is derived based on the free-gas EOS by correcting the gas density to account for the interaction between He and W atoms. The EOS for the bubbles is fitted to data from MD simulations of He bubbles in bulk W that span a wide range of gas density and sizes up to about 3 nm in diameter. The pressure of subsurface bubbles at the loop punching events as calculated using the bubble-EOS and the volume model agrees well with the pressure obtained directly from the MD simulations. In the loop punching model, for bubbles consisting of $$N_\text {V}$$ N V vacancies and $$N_\text {He}$$ N He helium atoms, the $$N_\text {He}/N_\text {V}$$ N He / N V ratio that causes the event, the resulting increase in $$N_\text {V}$$ N V , and the associated shift of the bubble depth are formulated as a function of $$N_\text {V}$$ N V and T . In the bursting model, a bubble must simultaneously reach a certain depth and $$N_\text {He}/N_\text {V}$$ N He / N V ratio in order to burst. The burst depth and $$N_\text {He}/N_\text {V}$$ N He / N V are also modeled as a function of $$N_\text {V}$$ N V and T . The majority of the loop punching events occur at bubble pressures between 20 and 60 GPa, depending on the bubble size and temperature. The larger the bubble and the higher the temperature, the lower the bubble pressure. Furthermore, our results indicate that at a higher temperature, a bubble can burst from a deeper region.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗
DOE OSTI2023

Utah FORGE 2439: Well 16B(78)-32 Field-Test Data from Mini-Frac Tests

This submittal includes the field-test data collected during stress tests conducted in the Utah FORGE 16B(78)-32 wellbore to measure/characterize the stresses in the geothermal reservoir. The type of stress test performed is referred to as a mini-frac test or a micro-frac test. The test is a hydraulic fracture test that involves injecting a small volume of water into a short interval of the reservoir that is isolated by a straddle packer to create a fracture. The test provides information about the minimum and maximum horizontal stress at the test depths. A total of seven mini-frac tests were performed within the upper (vertical or nearly vertical) section of the 9-5/8-inch diameter uncased wellbore, between depths of 5,202 ft MD [5,202 ft TVD] and 5,980 ft MD [5966.18 ft TVD]. Two types of data were generated as part of the mini-frac tests. The first type of data is time-series data for each mini-frac test (e.g., injection-rate, test-interval pressure), and are contained in the "Mini-Frac Test Data.zip" file below. The second type is geophysical log data, attached below in the "Geophysical Logs.zip" file. Here, two types of image logs and acoustic logs were obtained before and after the mini-frac tests to examine each test depth for visual evidence of induced fracture(s) and to measure the azimuth (orientation) of any observed fractures. The attached Readme file includes the test depth information and contents of each data file included here. Analysis of the field-test data was conducted and is documented in the attached report below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Cavity evolution and void swelling in dual ion irradiated tempered martensitic steels

Microstructural evolutions in two variants of the F82H 8 wt%Cr tempered martensitic steel under dual (He + plus Fe 3+ ) ion irradiations at 500 °C have been characterized by transmission electron microscopy. Emphasis is on understanding the combined effects of displacements per atom (dpa) and the helium/dpa ratio (He/dpa) on cavity evolution and void swelling (f v ). The dual ion database includes 231 alloy-dpa-He/dpa conditions for irradiations up to ~ 82 dpa and 3700 appm helium. Here, we hypothesize that the large “scatter” observed in the f v data is primarily due to local microstructural variations, especially those that shield regions at shallower depths from the effects of injected interstitial atoms, which would otherwise reduce f v . More generally, our hypothesis is that the highest f v data, at a specified dpa and He/dpa, provides the most appropriate estimate of swelling for fusion neutron irradiation conditions. The dose dependence of f v can be described by an incubation dpa i , marking the onset of significant void growth, and a post-incubation swelling rate, f v ’ = Δf v /Δdpa. Both dpa i and f v ’ decrease with increasing He/dpa. The f v ’ data are quantitatively consistent with a simple model for defect partitioning between evolving bubble, void, and dislocation sinks strengths and biases. Most notably, the model correctly predicts both the incubation dpa i , and the subsequent f v ’, in spite of the fact that they reflect somewhat different physics. Our analysis also suggests that defect recombination is modest at 500 °C. Along with other considerations, this supports the hypothesis that, even at high dpa rates, dual ion irradiations can be used to reasonably emulate void nucleation and growth for a range of fusion-relevant neutron irradiation service conditions. A companion paper incorporates the results of this study in a reduced-order, data-driven void swelling model.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Ruggedizing a Commercial Depth Camera for Novel Lunar Exploration.

The novel contribution of this instrument is to take the first depth images on the moon. A commercial Kinect camera from Microsoft has been ruggedized for a CLPS mission to the Lunar South Pole. The 12-megapixel color camera is combined with a 1-megapixel color time-of-flight (ToF) depth sensor. The solid-state depth sensor/LIDAR provides greater resolution, a wider field of view, pixel binning, and reduced power consumption. The high-resolution data collected from the mission can be used to construct a near-field virtual environment of the lunar surface for scientific applications. The depth camera can provide a 360-degree view of the target area by combining ToF data with RGB imagery and rover turning. The unit was evaluated for space flight compliant materials and parts at NASA Ames. The microphone array, RF shield, front face, and outer body parts were removed to reduce mass. Plastic parts were replaced with vacuum-compatible materials; manufactured cables were added to properly interface with the host rover, built by Lunar Outpost. The environmental testing was performed on the Kinect with Random Vibration/Sine Testing (Fig 1a), per GEVS (NASA’s General Environmental Verification Standard for spaceflight launch survival). Thermal Vacuum testing cycled the instrument between expected hot (+ 85 C) and cold survival temperatures, as well as +50 C and -25 C operational temps (Fig 1b). The instrument functioned nominally at the conclusion of vibration and thermal cycling tests. The Azure Kinect is manifested on the Nova-C lander which flies on the Intuitive Machines mission IM-2, landing at the lunar south pole for a mission duration of 14 days (one lunar daylight cycle). The unit will be integrated to the MAPP (Mobile Autonomous Prospecting Platform) rover at Lunar Outpost. The Azure Kinect with ToF feature will improve the resolution of lunar geology data near the south pole and enable ground-based VR experience of details of the lunar surface (Fig 1c).

V. Jha↗
DOE OSTI2023

2017 Meander C sediment characterization from the East River, Colorado

This dataset includes characterization data collected on sediment samples from Meander C as part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected to investigate the nature of mineral-organic associations across the meander transect and with depth. Samples were collected in 2017, and analyzed using sequential extractions (water, pyrophosphate, HCl, and dithionite) and density fractionation. Data collected include: texture, pH, root biomass, and metals (Fe, Al, Ca, Si) of bulk sediment samples; C and N of heavy fraction; and extractable OC, Fe, and Al, and organic matter characterization using high-resolution mass spectrometry (FT-ICR-MS) of sequential extractions. Sample locations are included in the ‘sample_metadata.xlsx” file. Sediment characterization data is included in the accompanying csv files: bulk and density fractions (MCB2017_density-and-bulk-fractions.csv), sequential extractions (MCB2017_sequential-extractions.csv), and FT-ICR-MS data from sequential extractions in three files to be read by the R package ftmsRanalysis (MCB2017_FTICRMS-sequential-edata.csv, MCB2017_FTICRMS-sequential-emeta.csv, and MCB2017_FTICRMS-sequential-fdata.csv). Sediment was collected in triplicate; ID’s refer to individual samples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Agulhas Current Properties Shape Microbial Community Diversity and Potential Functionality

Understanding the impact of oceanographic features on marine microbial ecosystems remains a major ecological endeavour. Here we assess microbial diversity, community structure and functional capacity along the Agulhas current system and the Subtropical convergence in the South Indian Ocean (SIO). Samples collected from the epipelagic, oxygen minimum and bathypelagic zones were analysed by 16S rRNA gene amplicon and metagenomic sequencing. In contrast to previous studies, we found high taxonomic richness in surface and deep water samples, but generally low richness for oxygen minimum zone communities. Beta-diversity analysis revealed significant dissimilarity between the three water depths. Most microbial communities were dominated by marine Gammaproteobacteria, with strikingly low levels of picocyanobacteria. Community composition was strongly influenced by specific environmental factors including depth, salinity, and the availability of both oxygen and light. Carbon, nitrogen and sulphur cycling capacity is the SIO was linked to several autotrophic and copiotrophic Alphaproteobacteria and Gammaproteobacteria. Taken together, our data suggest that the environmental conditions in the Agulhas current system, particularly depth-related parameters, substantially influence microbial community structure. While the capacity for biogeochemical cycling of nitrogen and sulphur is linked primarily by the dominant Gammaproteobacterial taxa, ecologically rare taxa drive carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Association between soil organic carbon and calcium in acidic grassland soils from Point Reyes National Seashore, CA

All data is collected from across 3 soil cores spanning a pH gradient at Point Reyes National Seashore, as part of a recent publication. The bulk data csv includes hygroscopic moisture content, soil pH, total C and N values, particle size distributions, cation exchange capacity and extractable cations. The STXM data package includes raw spectra data from scanning transmission X-ray microscopy C near-edge X-ray absorption fine structure spectroscopy analysis, extracted from STXM Image Reader analysis and then subsequently normalised in Athena (see details in paper). The data file also contains a bulk chemistry and mineralogy dataset, including total and trace element contents from 3 depths and mineral compositions as measured at BL 11-3 SSRL and semi-quantified in HighScore. Finally the final data file is calcium K-edge X-ray absorption near-edge structure spectroscopy (BL 4-3) and micro-XANES and micro-X-ray fluorescence (BL 14-3b) data.

54 ENVIRONMENTAL SCIENCES↗