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DOE OSTI2023

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from Machine-Learning-Informed Sites across the Contiguous United States (v6)

This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023. In addition to the widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files); December 2023 (v3; new and modified files); June 2024 (v4; new and modified files); April 2024 (v5; new and modified files); and September 2025 (v6; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) surface water major cations and anions and averages; (4) sediment grain size data; (5) sediment iron (II) data and averages; (6) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment specific surface area; (11) sediment percent carbon and nitrogen; (12) sediment gravimetric moisture and averages; (15) sediment X-ray diffraction (XRD) data; (16) sediment adenosine triphosphate (ATP) and averages; (17) a subfolder with sediment incubation respiration data, scripts, and plots; (18) surface water and sediment FTICR methods; and (19) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS).The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1975

Thermodynamic and related properties of parahydrogen from the triple point to 300 K at pressures to 1000 bar

Compressibility measurements and thermodynamic properties data for parahydrogen were extended to higher temperatures and pressures. Results of an experimental program are presented in the form of new pressure, volume and temperature data in the temperature range 23 to 300 K at pressures up to 800 bar. Also given are tables of thermodynamic properties on isobars to 1000 bar including density, internal energy, enthalpy, entropy, specific heats at constant volume and constant pressure, velocity of sound, and surface derivatives. The accuracy of the data is discussed and comparisons are made with previous data.

Weber, L. A.↗

DOE OSTI2024

Geophysical and Environmental Monitoring Data, and Subsurface Flow Modelling Results for Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO

This dataset includes geoelectrical monitoring data acquired between October 2021 and November 2022, soil moisture and temperature data, groundwater data obtained from borehole SNIB covering the period from June 2021 to September 2022, and hydrological modelling results. The data were acquired to investigate how variations in bedrock type and topography, and vegetation cover control subsurface flow dynamics. To provide insights into the subsurface flow dynamics and their controls, a monitoring transect was installed at the Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO, measuring the spatio-temporal variations of soil moisture, soil and snow temperature, subsurface electrical resistivity variations, and groundwater dynamics. Field data are organized in a folder structure, with Electrical Resistivity Tomography (ERT) data being provided as one file per measurement, and data of the soil moisture and temperature sensors being provided as text files covering the entire monitoring period. The ‘Locations.csv’ file contains the location of all sensors, given in NAD83 – UTM Zone 13N. ERT monitoring data has been processed to filter data based on reciprocal errors (data with errors > 30% were removed), a linear error model was fitted to each survey, and to ensure a constant set of measurements for time-lapse inversion, filtered data were interpolated and assigned a 100% measurement error. Soil moisture and temperature data were acquired at 15 min intervals, and averaged to provide 1h data. Weather data and borehole data (groundwater depth, conductivity and temperature) were acquired at 30 min intervals, and are provided as daily measurements; all measurements are averaged, except of precipitation values, which are given as daily accumulation. The hydrological model was set up along the ERT monitoring transect, and net infiltration was used as surface boundary condition and derived from the weather data. Four different results are provided, (1) results for a parameterization using hydraulic permeability and porosity as derived from the ERT data through petrophysical relationships, and (2) three simplified model results, using 1 to 3 geological layers above the bedrock. Modelling was performed using PFLOTRAN, and for each model the PFLOTRAN input files are provided. The result files include weekly hydrological modelling results (e.g., saturation, velocities, pressures), as well as the model parameterization. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

Base pressure and heat transfer tests of the 0.0225-scale space shuttle plume simulation model (19-OTS) in yawed flight conditions in the NASA-Lewis 10x10-foot supersonic wind tunnel (test IH83)

Wind tunnel tests were performed to determine pressures, heat transfer rates, and gas recovery temperatures in the base region of a rocket firing model of the space shuttle integrated vehicle during simulated yawed flight conditions. First and second stage flight of the space shuttle were simulated by firing the main engines in conjunction with the SRB rocket motors or only the SSME's into the continuous tunnel airstream. For the correct rocket plume environment, the simulated altitude pressures were halved to maintain the rocket chamber/altitude pressure ratio. Tunnel freestream Mach numbers from 2.2 to 3.5 were simulated over an altitude range of 60 to 130 thousand feet with varying angle of attack, yaw angle, nozzle gimbal angle and SRB chamber pressure. Gas recovery temperature data derived from nine gas temperature probe runs are presented. The model configuration, instrumentation, test procedures, and data reduction are described.

Foust, J. W.↗

NASA NTRS2018

Assimilating GCOM-W AMSR2 Radiance Data in Future GEOS Reanalysis

Surface and atmospheric radiation are being measured by space-borne conical scanning microwave radiometers with high accuracy and spatial resolution since 1980s'. These radiometers include Special Sensor Microwave Imager (SSM/I) onboard various NOAA's polar-orbiting satellites, Special Sensor Microwave Imager Sounder (SSMIS) onboard Defense Meteorological Satellite Program (DMSP) satellites, and Advanced Microwave Scanning Radiometer for EOS (AMSR-E), Advanced Microwave Scanning Radiometer 2 (AMSR2), Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI), and Global Precipitation Measurement (GPM) Microwave Imager (GMI) onboard NASA and JAXA's satellites. Atmospheric temperature, humidity, clouds, and precipitation are retrieved using brightness temperature data at frequencies between 22 GHz â€“ 183 GHz. Some of the brightness temperature and retrieved rain rate data made by these imagers are assimilated in NASA Global Modelling and Assimilation Office (GMAO)'s weather and climate data sets including the Modern-Era Retrospective analysis for Research and Applications (MERRA) and its version 2 (MERRA-2) data sets. However, those radiance data are assimilated with the Goddard Earth Observing System model, version 5 (GEOS-5) only in clear-sky conditions. Recently, we started assimilate GPM/GMI radiance data with GEOS-5's atmospheric data assimilation system GSI under all-sky conditions in order to have better constraints in analyzed hydrological properties. GMAO plans to assimilate more microwave radiometers' brightness temperature data in its analyses. In this talk, we will discuss TMI and AMSR2 data's impact in temperature, humidity, clouds and precipitation under all-sky conditions in future GEOS reanalysis.

Jin, Jianjun↗

DOE OSTI2022

Structure of Offshore Low-Level Jet Turbulence and Implications to Mesoscale-to-Microscale Coupling

This paper explores realistic nonstationary atmospheric boundary layer (ABL) turbulence arising from nonstationarity at the mesoscale, particularly within offshore low-level jets with implications to offshore wind farms, using high-fidelity multiscale large-eddy simulations (LES). To this end, we analyzed the single-point turbulence statistical structure of a North-Atlantic offshore LLJ event simulated using high-resolution LES (AMR-Wind). The nonstationary LLJ is simulated using a mesoscale-to-microscale coupled (MMC) simulation procedure involving data assimilation of mesoscale velocity and temperature data from the Weather Research and Forecasting (WRF) model. Unlike the assimilation of mesoscale velocity data into the LES, the direct assimilation of temperature profiles had a strong impact on turbulence stratification, thereby causing erroneous predictions of turbulence both above and within the jet layer. Various approaches to mitigate this effect have resulted in multiple (four) variants of this MMC strategy. Outcomes from this work clearly show that the turbulence within the low-level jet is a strong function of the MMC approach as the turbulence structure within the low-level jet is dependent on the flux of residual turbulence from outside the jet, which in turn depends on the temperature forcing history. Additionally, the turbulence predicted by all these different methods (as well as the observation data) show similar deviations from equilibrium as evidenced by comparisons with idealized atmospheric turbulence structure obtained using the same numerical method. In general, we observe that the predicted LLJ turbulence tends to differ from canonical ABL turbulence with comparable shear. Particularly, the combination of shear and turbulence observed in such nonstationary low-level turbulence cannot be matched using equilibrium settings and therefore, represents a critical use-case for both testing and leveraging meso–micro coupling strategies.

17 WIND ENERGY↗

DOE OSTI2014

Interactive Effects of Climate Change and Decomposer Communities on the Stabilization of Wood-Derived Carbon Pools: Catalyst for a New Study

Globally, forest soils store ~two-thirds as much carbon (C) as the atmosphere. Although wood makes up the majority of forest biomass, the importance of wood contributions to soil C pools is unknown. Even with recent advances in the mechanistic understanding of soil processes, integrative studies tracing C input pathways and biological fluxes within and from soils are lacking. Therefore, our research objectives were to assess the impact of different fungal decay pathways (i.e., white-rot versus brown-rot)—in interaction with wood quality, soil temperature, wood location (i.e., soil surface and buried in mineral soil), and soil texture—on the transformation of woody material into soil CO 2 efflux, dissolved organic carbon (DOC), and soil C pools. The use of 13 C-depleted woody biomass harvested from the Rhinelander, WI free-air carbon dioxide enrichment (Aspen-FACE) experiment affords the unique opportunity to distinguish the wood-derived C from other soil C fluxes and pools. We established 168 treatment plots across six field sites (three sand and three loam textured soil). Treatment plots consisted of full-factorial design with the following treatments: 1. Wood chips from elevated CO 2 , elevated CO 2 + O 3 , or ambient atmosphere AspenFACE treatments; 2. Inoculated with white rot (Bjerkandera adusta) or brown rot (Gloeophyllum sepiarium) pure fungal cultures, or the original suite of endemic microbial community on the logs; and 3. Buried (15cm in soil as a proxy for coarse roots) or surface applied wood chips. We also created a warming treatment using open-topped, passive warming chambers on a subset of the above treatments. Control plots with no added wood (“no chip control”) were incorporated into the research design. Soils were sampled for initial δ 13 C values, CN concentrations, and bulk density. A subset of plots were instrumented with lysimeters for sampling soil water and temperature data loggers for measuring soil temperatures. To determine the early pathways of decomposition, we measured soil surface CO 2 efflux, dissolved organic C (DOC), and DO 13 C approximately monthly over two growing seasons from a subsample of the research plots. To determine the portion of soil surface CO 2 efflux attributable to wood-derived C, we used Keeling plot techniques to estimate the associated δ 13 C values of the soil CO 2 efflux. We measured the δ 13 CO 2 once during the peak of each growing season. Initial values for soil δ 13 C values and CN concentrations averaged across the six sites were -26.8‰ (standard error = 0.04), 2.46% (se = 0.11), and 0.15% (se = 0.01), respectively. The labeled wood chips from the Aspen FACE treatments had an average δ13C value of -39.5‰ (se 0.10). The >12 ‰ isotopic difference between the soil and wood chip δ 13 C values provides the basis for tracking the wood-derived C through the early stages of decomposition and subsequent storage in the soil. Across our six research sites, average soil surface CO 2 efflux ranged from 1.04 to 2.00 g CO 2 m -2 h -1 for the first two growing seasons. No wood chip controls had an average soil surface CO 2 efflux of 0.67 g CO 2 m -2 h -1 or about half of that of the wood chip treatment plots. Wood-derived CO 2 efflux was higher for loam textured soils relative to sands (0.70 and 0.54 g CO 2 m -2 h -1 , respectively; p = 0.045)), for surface relative to buried wood chip treatments (0.92 and 0.39 g CO 2 m -2 h -1 , respectively; p < 0.001), for warmed relative to ambient temperature treatments (0.99 and 0.78 g CO 2 m -2 h -1 , respectively; 0.004), and for natural rot relative to brown and white rots (0.93, 0.82, and 0.78 g CO 2 m -2 h -1 , respectively; p = 0.068). Our first two growing seasons of soil surface CO 2 efflux data show that wood chip location (i.e., surface vs. buried chip application) is very important, with surface chips loosing twice the wood-derived CO 2 . The DOC data support this trend for greater loss of ecosystem C from surface chips. This has strong implications for the importance of root and buried wood for ecosystem C retention. This strong chip location effect on wood-derived C loss was significantly modified by soil texture, soil temperature, decomposer communities, and wood quality as effected by potential future CO 2 and O 3 levels.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1975

Measurement of viscosity and elasticity of lubricants at high pressures

The oscillating quartz crystal viscometer has been used to investigate possible viscoelastic behavior in synthetic lubricating fluids and to obtain viscosity-pressure-temperature data for these fluids at temperatures to 300 F and pressures to 40,000 psig. The effect of pressure and temperature on the density of the test fluids was measured concurrently with the viscosity measurements. Viscoelastic behavior of one fluid, di-(2-ethylhexyl) sebacate, was observed over a range of pressures. These data were used to compute the reduced shear elastic (storage) modulus and reduced loss modulus for this fluid at atmospheric pressure and 100 F as functions of reduced frequency.

Rein, R. G., Jr.↗

NASA NTRS1987

Further information on structure of the atmosphere of Venus derived from the Vega Venus balloon and lander mission

Continued analysis of the pressure and temperature data returned by the two Vega mission balloons has revealed an apparently significant difference in mean atmospheric static stability between the two data sets. Furthermore, the stability is time dependent within each data set. The 6.5 K temperature contrast between the two balloons remains, and appears to have a counterpart in the contrast between two of the Pioneer Venus probes at these levels, which has been attributed to planetary scale waves. Comparisons of the Vega 2 lander data with those of the Pioneer Venus Large Probe shows relatively close agreement in the state properties and in the atmospheric static stability profiles as well.

Seiff, A.↗

DOE OSTI2018

Diagnostic Models for Wind Turbine Gearbox Components Using SCADA Time Series Data: Preprint

This paper presents a scalable, autonomous framework for diagnostics of wind turbine gearbox failures using a multi-feature supervisory control and data acquisition data set spanning multiple years. Because of the size of the data set studied, all algorithms were constructed to be scalable using a Spark-Hadoop data framework. An unsupervised approach was used to detect significant failures based on predetermined criteria. The initial criteria selected were an abnormal spike in turbine component temperature followed by a turbine power off, which helps reduce the number of potential false alarms. To detect abnormal spikes in component temperature, a model was introduced to adjust the temperature data for effects caused by ambient temperature and normal temperature increases when loaded. This study evaluates methods for normalizing temperature sensor data to identify anomalies. The models that performed the best were a linear regression and a multivariate polynomial regression. The proposed process for finding failures has tunable parameters that can be adjusted to be more or less sensitive. The combination of sensor data normalization and application of these criteria is successful in finding turbine failures resulting in downtime. The proposed methods can operate without failure or maintenance logs and can be utilized for offline analysis of large high-resolution data sets.

17 WIND ENERGY↗

DOE OSTI2026

Warming amplifies the variability of methane emissions from a coastal wetland, 2025, Maryland.

These data accompany the published paper Lewis et al., 202X and are from a brackish coastal wetland in situ soil warming experiment (GENX) equipped with automated flux chambers. Methane (CH4) and carbon dioxide (CO2) fluxes were measured in 12 automated chambers using custom-built automated chambers connected to an LI-7810 CH4/CO2 analyzer. The chambers are 1.5 m tall and contain the dominant vegetation species of the site (Schoenoplectus americanus, Spartina patens, and Distichlis spicata). The chambers are also distributed across a soil warming gradient, ranging from ambient to 6°C above ambient, that was started in February 2022. This dataset contains the following files: (1) CH4 and CO2 fluxes from each chamber for March to November 2025, statistics for each flux, and environmental data (water depth, salinity, air temperature) at the time of the flux measurement; (2) 15-minute soil temperature data for each chamber; (3) Aboveground vegetation biomass (total and by species) and stem counts and dimensions for S. americanus; (4) Elevation for each chamber. All data processing code is available on Github.

Coastal wetland↗

DOE OSTI2022

Multimodal sensor fusion framework for residential building occupancy detection

For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This work proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Thermal equation of state for zoisite: Implications for the transportation of water into the upper mantle and the high-velocity anomaly in the Farallon plate

Seismic tomography studies have revealed a high-velocity anomaly at depths between 100 km and 300 km in the Farallon plate. However, the reasons for the high-velocity anomaly continue to be debated. An analysis of the mineral proportions of eclogites exhumed from the Farallon plate shows that the average amount of zoisite in eclogite is ∼16.0 vol%. Therefore, the presence of zoisite eclogite needs to be considered to explain the high-velocity anomaly of the Farallon plate. However, the thermal equation of state and stability of zoisite have not been fully investigated under high pressure−temperature (P-T) conditions. We investigated the high-pressure and high-temperature behavior of natural zoisite utilizing synchrotron single crystal-X-ray diffraction (XRD). The results indicate that zoisite is metastable up to 24.8 GPa and 700 K. We obtained the ambient unit-cell volume V0 = 901.26(3) Å3 by synchrotron single crystal-XRD measurement. We also fitted the pressure-volume-temperature data to a high-temperature Birch-Murnaghan equation of state and obtained the zero-pressure bulk modulus K0 = 134.7(8) GPa, the temperature derivative of the bulk modulus (∂K/∂T)P = −0.011(4) GPa/K, and the thermal expansion coefficients α0V = 1.9(7) × 10−5 K−1 and α1V = 3(2) × 10−8 K−2 when the pressure derivative of bulk modulus (K′0) is fixed at 4. By incorporating the results from previous studies, we calculated the density and bulk sound velocity profiles of zoisite eclogite along the Farallon plate geotherm. Finally, we infer that zoisite could carry water to depths of ∼300 km within cold subducting slabs and that the bulk sound velocity of typical zoisite eclogite with ∼61.0 vol% omphacite, ∼23.0 vol% garnet, and ∼16.0 vol% zoisite could cause the high-velocity anomalies at depths of 100−300 km in the Farallon plate.

Geology↗

DOE OSTI2013

Soda Lake Well Lithology Data and Geologic Cross-Sections

Comprehensive catalogue of drill-hole data in spreadsheet, shapefile, and Geosoft database formats. Includes XYZ locations of well heads, year drilled, type of well, operator, total depths, well path data (deviations), lithology logs, and temperature data. Plus, 13 cross-sections in Adobe Illustrator format.

15 GEOTHERMAL ENERGY↗

NASA NTRS1975

ATS-6 millimeter wavelength propagation experiment

An empirical relation for path diversity gain as a function of terminal separation distance and single site fade depth is presented. This relation is based on existing 15.3 GHz ATS-5 attenuation data and 16.0 GHz radiometric temperature data for earth-space propagation paths. Preliminary 30 GHz ATS-6 diversity data are presented and are found to agree well with this empirical relation.

Hodge, D. B.↗

NASA NTRSDate not supplied

Exposure of Plant Seeds to the Space Environment outside the International Space Station

If crop seeds are to be stored on space vehicles for long-duration missions, the effects of the space environment on the seeds must be understood for developing mitigation strategies to prevent seed degradation. The MISSE-Seed project was designed to investigate the effects of space exposure on seed quality and storage. The project also tested the Materials International Space Station Experiment (MISSE) platform for exposing biological samples to the space environment and evaluated the capability of a newly designed passive sample containment vessel for the provision of acceptable storage conditions for seeds, or other biological samples, to be preserved upon exposure to the space environment outside the ISS. The experiment was launched to the ISS on NG-15and returned to Earth aboard SpX-24. The specimens consisted of eleven seed varieties (Lettuce, Scarlet Frills, Amara, Garnet Giant, Pac Choi, Radish, Mizuna, Tomato, Cauliflower, Pepper, and Arabidopsis). The exposure lasted eight months outside the ISS in the MISSE hardware at the Zenith position. Data-loggers and thermoluminescent dosimeters (TLDs) were included in each container to record the environmental data. Temperature profiles and radiation/UV exposure data were also provided by Aegis Aerospace, the MISSE Implementation Partner. In this presentation, the hardware and experimental design, the environmental profiles, and the results of post-flight germination tests will be presented.

Jeffrey T Richards↗

NASA NTRSDate not supplied

Exposure of Plant Seeds to the Space Environment Outside the International Space Station

Jeffrey T Richards↗

NASA NTRSDate not supplied

Exposure of Plant Seeds to the Space Environment Outside the International Space Station

Crop seeds may prove to be a vital component of future long-term spaceflight missions, and the impacts of extended exposure on seed degradation is not well understood. The MISSE-Seed project was designed to investigate the effects of space exposure on seed quality and storage. The project also served as a test of biological materials aboard the Materials International Space Station Experiment (MISSE) platform, and evaluated the capability of a newly designed passive sample containment vessel for the provision of acceptable storage conditions for seed and other biological samples to be preserved upon exposure to the space environment outside the ISS. MISSE-Seed was launched to the ISS on NG-15 in July of 2021 and returned to Earth aboard SpX-24 after approximately 8 months of exposure to the space environment. The specimens consisted of eleven seed varieties (Lettuce, Scarlet Frills, Amara, Garnet Giant, Pac Choi, Radish, Mizuna, Tomato, Cauliflower, Pepper, and Arabidopsis). Data-loggers and thermoluminescent dosimeters (TLDs) were included in each container to record environmental data. Temperature profiles and radiation/UV exposure data were also provided by Aegis Aerospace, the MISSE Implementation Partner. Hardware and experimental design, environmental profiles, and post-flight germination and growth results will be presented.

Alexander D Meyers↗