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NASA NTRSDate not supplied

NASA Lunabotics Robotic Mining Competition 10th Anniversary (2010-2019): Taxonomy and Technology Review

Space Mining for resources such as water ice, and regolith, which contain many elements in the form of metals, minerals, volatiles and other compounds, is a necessary step for In-Situ Space Resource Utilization (ISRU). One of the primary goals is to extract propellants from the regolith and water ice, such as oxygen and hydrogen which could then be used for in-space transportation. In addition, the space mining system can be used for various construction tasks that can benefit human and robotic exploration as well as scientific investigations based on excavated exposed topography, such as the side walls of trenches. The National Aeronautics & Space Administration (NASA) "Lunabotics" Robotic Mining Competition (RMC) is a university-level competition designed to engage and retain students in science, technology, engineering and mathematics (STEM). NASA has directly benefited from the competition by encouraging the development of innovative lunar excavation concepts from universities which has resulted in clever ideas and solutions which could be applied to an actual lunar excavation device or payload. The challenge is for students to design and build a remote controlled or autonomous excavator, called a "lunabot", which can collect and deposit a minimum of 10 kilograms of lunar simulant within 15 minutes. In recent years the goal has been changed to excavate a minimum of 1 kg of simulated icy regolith which is found under an overburden of regolith simulant. The complexities of the challenge include the abrasive characteristics of the lunar regolith simulant, the weight and size limitations of the lunabot, and the ability to control the lunabot from a remote-control center or operate it autonomously. This paper will present the results of the ten Lunabotics Robotic Mining Competitions held between May 2010 and May 2019. Each year over 50 university teams have attended, resulting in over 500 lunabot designs and subsequent prototypes. Over 6,000 university students have been part of the on-site competition at KSC. Even more students and the public were engaged via internet broadcasting and social networking media. The various designs have been cataloged and categorized here to provide information to future Lunabotics RMC mining robot designers and competitors. Categories will focus on both the mechanical design as well as the autonomy architecture/design. It is also expected to be of value for actual future space missions, as knowledge is gained from testing many innovative prototypes in simulated lunar regolith. A taxonomy of robotic excavator designs has been presented. In addition, the paper will discuss changes in learning paradigms occurring in the current generation of students, and how this competition leverages those changes to challenge students to develop skills in graduate level concepts and apply them. Examples of how this translates to hiring opportunities for commercial sponsors has also been discussed.

Robert P Mueller↗
NASA NTRSDate not supplied

4-Bed CO2 Scrubber – From Design to Build

Four-bed technology is an International Space Station (ISS) mainstay for metabolic Carbon Dioxide (CO2) removal and crew life support. The current generation is known as the Carbon Dioxide Removal Assembly (CDRA) and has a long history of unplanned maintenance as well as obsolete core components. The 4-bed CO2 Scrubber was commissioned to operate with no unplanned maintenance for 3 years while removing 4 crew-equivalents of CO2 at a target inlet concentration of 2 torr CO2. This work goes into detail of the various design aspects that have been undertaken to ensure a successful project design and successful build leading to an upcoming flight. This work will discuss the compromises caught both early and late in the design cycle and the adaptations in response. Finally, the expected performance of the system once launched will be discussed based on summaries of data from the testbed.

Carbon Dioxide↗
NASA NTRSDate not supplied

Temporal Interpolation of Geostationary Satellite Imagery with Task Specific Optical Flow

Applications of satellite data in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on the trade-offs to spatial, spectral and temporal resolutions of observations. In weather tracking, high-frequency temporal observations are critical and used to improve forecasts, study severe events, and extract atmospheric motion, among others. However, while the current generation of geostationary satellites have hemispheric coverage at 10-15 minute intervals, higher temporal frequency observations are ideal for studying mesoscale severe weather events. In this work, we apply a task specific optical flow approach to temporal up-sampling using deep convolutional neural networks. We apply this technique to 16-bands of GOES-R/Advanced Baseline Imager mesoscale dataset to temporally enhance full disk hemispheric snapshots of different spatial resolutions from 15 minutes to 1 minute. Experiments show the effectiveness of task specific optical flow and multi-scale blocks for interpolating high-frequency severe weather events relative to bilinear and global optical flow baselines. Lastly, we demonstrate strong performance in capturing variability during convective precipitation events.

Optical flow, temporal interpolation, geostationar↗
NASA NTRS2020

Comparison of Equilibrium Climate Sensitivity Estimates From Slab Ocean, 150‐Year, and Longer Simulations

We compare equilibrium climate sensitivity (ECS) estimates from pairs of long (≥ 800‐year) control and abruptly quadrupled CO2 simulations with shorter (150, 300 year) coupled atmosphere‐ocean simulations and Slab Ocean Models (SOM). Consistent with previous work, ECS estimates from shorter coupled simulations based on annual averages for years 1‐150 underestimate those from SOM (‐8% ± 13%) and long (‐14% ± 8%) simulations. Analysis of only years 21‐150 improved agreement with SOM (‐2% ± 14%) and long (‐8% ± 10%) estimates. Use of pentadal averages for years 51‐150 results in improved agreement with long simulations (‐4% ± 11%). While ECS estimates from current generation US models based on SOM and coupled annual averages of years 1‐150 range from 2.6°C to 5.3°C, estimates based longer simulations of the same models range from 3.2°C to 7.0°C. Such variations between methods argues for caution in comparison and interpretation of ECS estimates across models.

Climate sensitivity↗
NASA NTRS2021

The MJO-QBO Relationship in a GCM with Stratospheric Nudging

Observational studies show a strong connection between the intraseasonal Madden-Julian oscillation (MJO) and the stratospheric quasi-biennial oscillation (QBO): the boreal winter MJO is stronger, more predictable, and has different teleconnections when the QBO in the lower stratosphere is easterly versus westerly. Despite the strength of the observed connection, global climate models do not produce an MJO-QBO link. Here the authors use a current-generation ocean-atmosphere coupled NASA Goddard Institute for Space Studies global climate model (Model E2.1) to examine the MJO-QBO link. To represent the QBO with minimal bias, the model zonal mean stratospheric zonal and meridional winds are relaxed to reanalysis fields from 1980-2017. The model troposphere, including the MJO, is allowed to freely evolve. The model with stratospheric nudging captures QBO signals well, including QBO temperature anomalies. However, an ensemble of nudged simulations still lacks an MJO-QBO connection.

Madden-Julian oscillation (MJO)↗
NASA NTRS2021

Challenges in predicting Greenland supraglacial lake drainages at the regional scale

A leading hypothesis for the mechanism of fast supraglacial lake drainages is that transient extensional stresses briefly allow crevassing in otherwise compressional ice flow regimes. Lake water can then hydrofracture a crevasse to the base of the ice sheet, and river inputs can maintain this connection as a moulin. If future ice sheet models are to accurately represent moulins, we must understand their formation processes, timescales, and locations. Here, we use remote-sensing velocity products to constrain the relationship between strain rates and lake drainages across ∼ 1600 ksq.m in Pâkitsoq, western Greenland, between 2002–2019. We find significantly more extensional background strain rates at moulins associated with fast-draining lakes than at slow-draining or non-draining lake moulins. We test whether moulins in more extensional background settings drain their lakes earlier, but we find insignificant correlation. To investigate the frequency at which strain-rate transients are associated with fast lake drainage, we examined Landsat-derived strain rates over 16 and 32 d periods at moulins associated with 240 fast-lake-drainage events over 18 years. A low signal-to-noise ratio, the presence of water, and the multi-week repeat cycle obscured any resolution of the hypothesized transient strain rates. Our results support the hypothesis that transient strain rates drive fast lake drainages. However, the current generation of ice sheet velocity products, even when stacked across hundreds of fast lake drainages, cannot resolve these transients. Thus, observational progress in understanding lake drainage initiation will rely on field-based tools such as GPS networks and photogrammetry.

Kristin Poinar↗
NASA NTRSDate not supplied

High-C3 Applications for NASA's Space Launch System

For numerous high-interest science targets in the outer solar system and elsewhere, the limits of available launch vehicles have placed significant constraints on mission designs. Even for the current generation of heavy-lift launch vehicles, baseline capabilities still impose limitations, for example, the outer solar system in areas such as launch window availability, transit time, science payload mass, time at destination, etc. Initial studies show benefits for ultra-high C3 missions from configurations of NASA’s Space Launch System(SLS) adding third or fourth payload stages.

Robert W Stough↗
NASA NTRS2020

Historical and Future Changes in Air Pollutants from CMIP6 Models

Poor air quality is currently responsible for large impacts on human health across the world. In addition, the air pollutants ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5) are also radiatively active in the atmosphere and can influence Earth's climate. It is important to understand the effect of air quality and climate mitigation measures over the historical period and in different future scenarios to ascertain any impacts from air pollutants on both climate and human health. The Coupled Model Intercomparison Project Phase 6 (CMIP6) presents an opportunity to analyse the change in air pollutants simulated by the current generation of climate and Earth system models that include a representation of chemistry and aerosols (particulate matter). The shared socio-economic pathways (SSPs) used within CMIP6 encompass a wide range of trajectories in precursor emissions and climate change, allowing for an improved analysis of future changes to air pollutants. Firstly, we conduct an evaluation of the available CMIP6 models against surface observations of O3 and PM2.5. CMIP6 models consistently overestimate observed surface O3 concentrations across most regions and in most seasons by up to 16 ppb, with a large diversity in simulated values over Northern Hemisphere continental regions. Conversely, observed surface PM2.5 concentrations are consistently underestimated in CMIP6 models by up to 10 µg m−3, particularly for the Northern Hemisphere winter months, with the largest model diversity near natural emission source regions. The biases in CMIP6 models when compared to observations of O3 and PM2.5 are similar to those found in previous studies. Over the historical period (1850–2014) large increases in both surface O3 and PM2.5 are simulated by the CMIP6 models across all regions, particularly over the mid to late 20th century, when anthropogenic emissions increase markedly. Large regional historical changes are simulated for both pollutants across East and South Asia with an annual mean increase of up to 40 ppb for O3 and 12 µg m−3 for PM2.5. In future scenarios containing strong air quality and climate mitigation measures (ssp126), annual mean concentrations of air pollutants are substantially reduced across all regions by up to 15 ppb for O3 and 12 µg m−3 for PM2.5. However, for scenarios that encompass weak action on mitigating climate and reducing air pollutant emissions (ssp370), annual mean increases in both surface O3 (up 10 ppb) and PM2.5 (up to 8 µg m−3) are simulated across most regions, although, for regions like North America and Europe small reductions in PM2.5 are simulated due to the regional reduction in precursor emissions in this scenario. A comparison of simulated regional changes in both surface O3 and PM2.5 from individual CMIP6 models highlights important regional differences due to the simulated interaction of aerosols, chemistry, climate and natural emission sources within models. The projection of regional air pollutant concentrations from the latest climate and Earth system models used within CMIP6 shows that the particular future trajectory of climate and air quality mitigation measures could have important consequences for regional air quality, human health and near-term climate. Differences between individual models emphasise the importance of understanding how future Earth system feedbacks influence natural emission sources, e.g. response of biogenic emissions under climate change.

Air pollutants↗
NASA NTRS2020

The NASA MODIS-VIIRS Continuity Cloud Optical Properties Products

The NASA Aqua MODIS and Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) climate data record continuity cloud properties products (CLDPROP) were publicly released in April 2019 with an update later that year (Version 1.1). These cloud products, having heritage with the NASA Moderate-resolution Imaging Spectroradiometer (MODIS) MOD06 cloud optical properties product and the NOAA GOES-R Algorithm Working Group (AWG) Cloud Height Algorithm (ACHA), represent an effort to bridge the multispectral imager records of NASA’s Earth Observing System (EOS) and NOAA’s current generation of operational weather satellites to achieve a continuous, multi-decadal climate data record for clouds that can extend well into the 2030s. CLDPROP offers a “continuity of approach,” applying common algorithms and ancillary datasets to both MODIS and VIIRS, including utilizing only a subset of spectral channels available on both sensors to help mitigate instrument differences. The initial release of the CLDPROP_MODIS and CLDPROP_VIIRS data records spans the SNPP observational record (2012-present). Here, we present an overview of the algorithms and an evaluation of the intersensor continuity of the core CLDPROP_MODIS and CLDPROP_VIIRS cloud optical property datasets, i.e., cloud thermodynamic phase, optical thickness, effective particle size, and derived water path. The evaluation includes analyses of pixel-level MODIS/VIIRS co-locations as well as spatial and temporal aggregated statistics, with a focus on identifying and understanding the root causes of individual dataset discontinuities. The results of this evaluation will inform future updates to the CLDPROP products and help scientific users determine the appropriate use of the product datasets for their specific needs.

satellite remote sensing↗
NASA NTRS2013

MRAM Technology Status

Magnetoresistive Random Access Memory (MRAM) is much different from conventional types of memory like SRAM, DRAM, and Flash, where electric charge is used to store information. Instead of exploiting the charge of an electron, MRAM uses its spin to store data. This new type of electronics is known as “spintronics.” The primary focus of this report is the current generation of MRAM technology, and its reliability, vendors, and space-readiness.

Heidecker, Jason↗
NASA NTRS2020

One Planet or Two Planets? The Ultra-sensitive Extreme-magnification Microlensing Event KMT-2019-BLG-1953

We present the analysis of a very high-magnification (A ~ 900) microlensing event KMT-2019-BLG-1953. A single-lens single-source (1L1S) model appears to approximately delineate the observed light curve, but the residuals from the model exhibit small but obvious deviations in the peak region. A binary-lens (2L1S) model with a mass ratio of q ~ 2 × 10^−3 improves the fits by Δχ2 = 181.8, indicating that the lens possesses a planetary companion. From additional modeling by introducing an extra planetary lens component (3L1S model) and an extra source companion (2L2S model), it is found that the residuals from the 2L1S model further diminish, but claiming these interpretations is difficult due to the weak signals with Δχ2 = 16.0 and 13.5 for the 3L1S and 2L2L models, respectively. From a Bayesian analysis, we estimate that the host of the planets has a mass of M(host)=0.31 (+0.37, -0.17) Mꙩ and that the planetary system is located at a distance of D9L)=7.04 (+1.10, -1.33) kpc toward the Galactic center. The mass of the securely detected planet is M(p)=0.64 (+0.76, -0.35) M(J). The signal of the potential second planet could have been confirmed if the peak of the light curve had been more densely observed by follow-up observations, and thus the event illustrates the need for intensive follow-up observations for very high-magnification events even in the current generation of high-cadence surveys.

Cheongho Han↗
NASA NTRSDate not supplied

Tangerine Dream: Observations of Titan from the Earth

From its discovery in 1655 by the Dutch astronomer Christiaan Huygens, Titan perplexed and confounded Earth-based astronomers for three centuries with its stubborn refusal to yield virtually any clues about its nature. Until the Voyager 1 1980, even fundamentals such as its true diameter, surface pressure, and major atmospheric gas were uncertain [1]. Most of the information we now know about Titan has been wrestled at great expense of time and effort by three spacecraft visitors: Voyager 1, Cassini and Huygens. So why then continue to bother with Earth-based telescopic observations? In this review talk I will describe how significant clues about Titan’s atmospheric composition began to emerge from ground-based observations in the 1940s through 1970s, in the run-up to the revolutionary Voyager 1 flyby. These included the discovery of methane [2], and other significant hydrocarbons including ethane and acetylene in Titan’s stratosphere [3, 4]. Further ground and space-based telescopic work in the 1980s and 1990s revealed the presence of the fourth most abundance gas, carbon monoxide [5], spotted for the first time the bright continent on Titan’s leading hemisphere now known as Xanadu [6], and the comings and goings of bright tropospheric clouds [7]. The Cassini-Huygens mission of 2004-2017 [8, 9] greatly expanded our knowledge of Titan, including the first in situ measurements of the atmosphere and detailed imaging of the surface. However in the two-decades long gap before the next mission, Dragonfly, reaches Titan we are finding new ways to further our knowledge of Titan using the current generation of telescopes and instruments. With high-resolution spectroscopy at infrared and sub-millimeter wavelengths we are finding new chemical constituents in the atmosphere, and even measuring wind fields at middle altitudes. I will conclude by discussing how the next generation of Earth and space-based telescopes and instruments promises yet more breakthroughs via astronomy, including with large aperture 30 and 40 meter class telescopes that will become available in the late 2020s, and spectroscopy with airborne

Titan↗
NASA NTRS2021

Temporal Interpolation of Geostationary Satellite Imagery With Optical Flow

Applications of satellite data in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on the tradeoffs to spatial, spectral, and temporal resolutions of observations. In weather tracking, high-frequency temporal observations are critical and used to improve forecasts, study severe events, and extract atmospheric motion, among others. However, while the current generation of geostationary (GEO) satellites has hemispheric coverage at 10-15-min intervals, higher temporal frequency observations are ideal for studying mesoscale severe weather events. In this work, we present a novel application of deep learning-based optical flow to temporal upsampling of GEO satellite imagery. We apply this technique to 16 bands of the GOES-R/Advanced Baseline Imager mesoscale dataset to temporally enhance full-disk hemispheric snapshots of different spatial resolutions from 10 to 1 min. Experiments show the effectiveness of task-specific optical flow and multiscale blocks for interpolating high-frequency severe weather events relative to bilinear and global optical flow baselines. Finally, we demonstrate strong performance in capturing variability during convective precipitation events.

Image processing↗
NASA NTRS2022

Advances in the prediction of MJO-Teleconnections in the S2S forecast systems

This study evaluates the ability of state-of-the-art subseasonal to seasonal (S2S) forecasting systems to represent and predict the teleconnections of the Madden Julian Oscillations and their effects on weather in terms of midlatitude weather patterns and North Atlantic tropical cyclones. This evaluation of forecast systems applies novel diagnostics developed to track teleconnections along their preferred pathways in the troposphere and stratosphere, and to measure the global and regional responses induced by teleconnections across both the Northern and Southern Hemispheres. Results of this study will help the modeling community understand to what extent the potential to predict the weather on S2S time scales is achieved by the current generation of forecasting systems, while informing where to focus further development efforts. The findings of this study will also provide impact modelers and decision makers with a better understanding of the potential of S2S predictions related to MJO teleconnections.

Forecasting↗
NASA NTRS2021

Atacama Cosmology Telescope measurements of a large sample of candidates from the Massive and Distant Clusters of WISE Survey: Sunyaev-Zeldovich effect confirmation of MaDCoWS candidates using ACT

Context. Galaxy clusters are an important tool for cosmology, and their detection and characterization are key goals for current and future surveys. Using data from the Wide-field Infrared Survey Explorer (WISE), the Massive and Distant Clusters of WISE Survey (MaDCoWS) located 2839 significant galaxy overdensities at redshifts 0.7 . z . 1.5, which included extensive follow-up imaging from the Spitzer Space Telescope to determine cluster richnesses. Concurrently, the Atacama Cosmology Telescope (ACT) has produced large area millimeter-wave maps in three frequency bands along with a large catalog of Sunyaev-Zeldovich (SZ)-selected clusters as part of its Data Release 5 (DR5). Aims. We aim to verify and characterize MaDCoWS clusters using measurements of, or limits on, their thermal SZ effect signatures. We also use these detections to establish the scaling relation between SZ mass and the MaDCoWS-defined richness. Methods. Using the maps and cluster catalog from DR5, we explore the scaling between SZ mass and cluster richness. We do this by comparing cataloged detections and extracting individual and stacked SZ signals from the MaDCoWS cluster locations. We use complementary radio survey data from the Very Large Array, submillimeter data from Herschel, and ACT 224 GHz data to assess the impact of contaminating sources on the SZ signals from both ACT and MaDCoWS clusters. We use a hierarchical Bayesian model to fit the mass-richness scaling relation, allowing for clusters to be drawn from two populations: one, a Gaussian centered on the mass-richness relation, and the other, a Gaussian centered on zero SZ signal. Results. We find that MaDCoWS clusters have submillimeter contamination that is consistent with a gray-body spectrum, while the ACT clusters are consistent with no submillimeter emission on average. Additionally, the intrinsic radio intensities of ACT clusters are lower than those of MaDCoWS clusters, even when the ACT clusters are restricted to the same redshift range as the MaDCoWS clusters. We find the best-fit ACT SZ mass versus MaDCoWS richness scaling relation has a slope of p1 = 1.84+0.15 −0.14, where the slope is defined as M ∝ λ p1 15 and λ15 is the richness. We also find that the ACT SZ signals for a significant fraction (∼57%) of the MaDCoWS sample can statistically be described as being drawn from a noise-like distribution, indicating that the candidates are possibly dominated by low-mass and unvirialized systems that are below the mass limit of the ACT sample. Further, we note that a large portion of the optically confirmed ACT clusters located in the same volume of the sky as MaDCoWS are not selected by MaDCoWS, indicating that the MaDCoWS sample is not complete with respect to SZ selection. Finally, we find that the radio loud fraction of MaDCoWS clusters increases with richness, while we find no evidence that the submillimeter emission of the MaDCoWS clusters evolves with richness. Conclusions. We conclude that the original MaDCoWS selection function is not well defined and, as such, reiterate the MaDCoWS collaboration’s recommendation that the sample is suited for probing cluster and galaxy evolution, but not cosmological analyses. We find a best-fit mass-richness relation slope that agrees with the published MaDCoWS preliminary results. Additionally, we find that while the approximate level of infill of the ACT and MaDCoWS cluster SZ signals (1–2%) is subdominant to other sources of uncertainty for current generation experiments, characterizing and removing this bias will be critical for next-generation experiments hoping to constrain cluster masses at the sub-percent level.

large↗
NASA NTRS2022

Western Montana Ecological Forecasting II: Enhancing Habitat Suitability Modeling of Mustelid Species and Contaminant Monitoring in Northern Montana Using NASA Earth Observations

Environmental contaminants in aquatic ecosystems threaten both human and ecosystem health. Western Montana’s rivers possess great economic and ecological value, yet the status of contaminants in these systems can be unclear. Contaminants such as brominated flame-retardants, heavy metals, and pharmaceuticals negatively affect ecosystem health by traveling through the food chain and bioaccumulating in apex predators. Exposure to these contaminants can result in neurological, endocrine, and reproductive impairments in wildlife and humans. American mink (Neovison vison) and North American river otter (Lontra canadensis) have a predominantly aquatic diet and serve as reliable indicator species of environmental health. Working Dogs for Conservation (WD4C) uses detection dogs to locate scat samples of these species which are assessed for contaminants by the Virginia Institute of Marine Science (VIMS). With Software for Assisted Habitat Modeling (SAHM), the team generated current (2013-2020) and projected (2021-2040) habitat suitability models for mink and otter utilizing NASA Earth observations from Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Global Precipitation Measurement Integrated Multi-Satellite Retrievals for GPM (GPM IMERG), Shuttle Radar Topography Mission (SRTM), and Soil Moisture Active Passive (SMAP). The habitat suitability maps’ study region encompassed Flathead National Forest and Blackfeet Indian Reservation. Additionally, the team created site accessibility and precipitation anomaly maps that display the viability of survey locations. The current habitat suitability models performed well (AUC-PR=0.88). The most important predictor variables for suitable habitat were distance to rivers, elevation, and land cover. These end products will further inform WD4C survey site selection and contaminant monitoring.

Chelsea Morton↗
NASA NTRS2022

Pair Production Detectors for Gamma-ray Astrophysics

Electron-positron pair production is the essential process for high-energyγ-ray astrophysical observations. Following the pioneeringOSO-3counter telescope, the field evolved into use of particle tracking instruments, largely derived from high-energy physics detectors. Although many of the techniques were developed on balloon-borneγ-ray telescopes, the need to escape the high background in the at-mosphere meant that the breakthrough discoveries came from theSAS-2andCOS-Bsatellites. The next major pair production success was EGRET on the Comp-ton Gamma Ray Observatory, which provided the first all-sky map at energies above 100 MeV and found a variety ofγ-ray sources, many of which were vari-able. The current generation of pair production telescopes,AGILEandFermiLAT,have broadened high-energyγ-ray astrophysics with particular emphasis on multi-wavelength and multimessenger studies. A variety of options remain open for future missions based on pair production with improved instrumental performance.

Gamma rays↗
NASA NTRSDate not supplied

ISS External Microorganisms: A Payload to Close Planetary Protection Knowledge Gaps for Crewed Missions

Before NASA or COSPAR is able to set planetary protection requirements for crewed missions to locations like Mars there are a number of critical knowledge gaps that must be addressed (1). One of the most important knowledge gaps is an understanding of microbial leakage from crewed habitats and space suits. Current ECLSS (Environmental Control and Life Support System) and PLSS (Portable Life Support System) requirements do not include any provisions to control microbes that may escape along with vented or leaked gasses. The current generation of NASA space suits can leak at rates as high as 100 cm2 /min. during nominal operation (2). ISS (International Space Station) intentionally vents atmospheric gases like CO2 to maintain habitable conditions for the crew. Furthermore, every time an airlock is used for EVA (extravehicular activity)there is an accompanying release of internal atmosphere. Since it is not possible to sterilize a crewed mission, it is important that we understand what if any microbes are entrained in these vented and leaked products. It is also important to understand if these microbes can survive on exterior surfaces. Recent sampling of the Russian segments of ISS suggest that bacteria and fungi from inside ISS may be capable of surviving on external surfaces(3). NASA is developing an aseptic sampling tool for use during EVA and plans to collect samples from vents on ISS to build on these results. The results of this work will be used to develop planetary protection requirements for vented and leaked gasses from crewed volumes. NASA has developed and tested a tool kit for collecting microbiological samples during EVA(4). This tool kit contains eight commercially available, 23 mm. diameter, foam swabs that can be used to aseptically collect samples while at vacuum. The swabs are individually housed in aluminum canisters that are equipped with 0.2 μm Teflon filters. These filters allow the canisters to equilibrate to pressure changes while preventing microbiological contamination. The canisters will be cleaned and sterilized before flight. Results from ground-based testing indicate that this tool kit is capable of aseptically collecting microbes while at vacuum without becoming contaminated during pressure changes(5). Based on the results of this ground testing we have modified the tool kit to meet NASA safety requirements and improve the ergonomics. We added additional mounting points to the tool kit to give astronauts more options for securing it during use. We also changed the opening mechanism to improve the precision with which swabs can be extracted from the tool kit. We plan to use this kit on an upcoming EVA to collect samples from non-propulsive vents and areas near the U.S. airlock on ISS. These samples will be frozen at -80 ̊C and stored on station until they can be returned to Earth. We will analyze these returned samples using next generation DNA sequencing to determine the community composition and function of external ISS environments. The results of this study will close planetary protection knowledge gaps for crewed missions and will help NASA determine appropriate planetary protection requirements for life support systems. The tool kit will also be useful for collecting aseptic samples on upcoming crewed or robotic missions and could easily be modified to collect samples with organic contamination control requirements as well.

A B Regberg↗