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At least 199 records · Page 11

The Fate of Trace Contaminants in a Crewed Spacecraft Cabin Environment

Trace chemical contaminants produced via equipment offgassing, human metabolic sources, and vehicle operations are removed from the cabin atmosphere by active contamination control equipment and incidental removal by other air quality control equipment. The fate of representative trace contaminants commonly observed in spacecraft cabin atmospheres is explored. Removal mechanisms are described and predictive mass balance techniques are reviewed. Results from the predictive techniques are compared to cabin air quality analysis results. Considerations are discussed for an integrated trace contaminant control architecture suitable for long duration crewed space exploration missions.

Perry, Jay L.↗

Ammonia Stability in a Simulated Trace Contaminant Rich Cabin Environment

The off-gassing of ammonia from hardware and metabolic sources presents a unique challenge to trace contaminant control system design, driving process flowrates to meet crewed air quality requirements. Accurately simulating representative trace contaminant cabin loads during ground testing is necessary to validate component design as well as understand potential contaminant propagation across life-support system process interface boundaries. This effort is complicated by the observed temporal concentration instability of gaseous ammonia in ground test chambers. To this end, ammonia concentration decay rates were characterized under controlled environmental conditions to better understand underlying phenomena and quantify incidental mass losses. The suspected chemical interaction between ammonia and trace acetaldehyde was investigated and its effect on species quantification was examined by both gas chromatography-mass spectrometry and Fourier-transform infrared spectroscopy. Recommendations for ground test procedures were made in order to best compensate for undesirable ammonia mass losses and mitigate test artifacts.

Kayatin, Matthew J.↗

Air Pollution Scenario over Pakistan: Characterization and Ranking of Extremely Polluted Cities using Long-Term Concentrations of Aerosols and Trace Gases

Pakistan ranks third in the world in terms of mortality attributable to air pollution, with aerosol mass concentrations (PM2.5) consistently well above WHO (World Health Organization) air quality guidelines (AQG). However, regulation is dependent on a sparse network of air quality monitoring stations and insufficient ground data. This study utilizes long-term observations of aerosols and trace gases to characterize and rank the air pollution scenarios and pollution characteristics of 80 selected cities in Pakistan. Datasets used include (1) the Aqua and Terra (AquaTerra) MODIS (Moderate Resolution Imaging Spectroradiometer) Level 2 Collection 6.1 merged Dark Target and Deep Blue (DTB) aerosol optical depth (AOD) retrieval products; (2) the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis PM1, PM2.5, and PM10 data; (3) the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) reanalysis PM2.5 data, (4) the OMI (Ozone Monitoring Instrument) tropospheric vertical column density (TVCD) of nitrogen dioxide (NO2), and VCD of sulfur dioxide (SO2) in the Planetary Boundary Layer (PBL), (5) the VIIRS (Visible Infrared Imaging Radiometer Suite) Nighttime Lights data, (6) MODIS Collection 6 Version 2 global monthly fire location data (MCD14ML), (7) population density, (8) MODIS Level 3 Collection 6 land cover types, (9) AERONET (AErosol RObotic NETwork) Version 3 Level 2.0 data, and (10) ground-based PM2.5 concentrations from air quality monitoring stations. Potential Source Contribution Function (PSCF) analyses were performed by integrating with ground-based PM2.5 concentrations and the NOAA (National Oceanic and Atmospheric Administration) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) air parcel back trajectories to identify potential pollution source areas which are responsible for extreme air pollution in Pakistan. Results show that the ranking of the top polluted cities depends on the type of pollutant considered and the metric used. For example, Jhang, Multan, and Vehari were characterized as the top three polluted cities in Pakistan when considering AquaTerra DTB AOD products; for PM1, PM2.5, and PM10 Lahore, Gujranwala, and Okara were the top three; for tropospheric NO2 VCD Lahore, Rawalpindi, and Islamabad and for PBL SO2 VCD Lahore, Mirpur, and Gujranwala. The results demonstrate that Pakistan’s entire population has been exposed to high PM2.5 concentrations for many years, with a mean annual value of 54.7 μg/cu. m, over all Pakistan from 2003 to 2020. This value exceeds Pakistan’s National Environmental Quality Standards (Pak-NEQS, i.e., <15 μg/cu. m annual mean) for ambient air defined by the Pakistan Environmental Protection Agency (Pak-EPA) as well as the WHO Interim Target-1 (i.e., mean annual PM2.5 <35 μg/cu. m). The spatial analyses of the concentrations of aerosols and trace gases in terms of population density, nighttime lights, land cover types, and fire location data, and the PSCF analysis indicate that Pakistan’s air quality is strongly affected by anthropogenic sources inside of Pakistan, with contributions from surrounding countries. Statistically significant positive (increasing) trends in PM1, PM2.5, PM10, tropospheric NO2 VCD, and SO2 VCD were observed in ~89%, ~67%, ~48%, 91%, and ~88% of the Pakistani cities (80 cities), respectively. This comprehensive analysis of aerosol and trace gas levels, their characteristics in spatio-temporal domains, and their trends over Pakistan, is the first of its kind. Results will be helpful to the Ministry of Climate Change (Government of Pakistan), Pak-EPA, SUPARCO (Pakistan Space and Upper Atmosphere Research Commission), policymakers, and the local research community to mitigate air pollution and its effects on human health.

Muhammad Bilal↗

Surface-Enhanced Raman Spectroscopy (SERS) for Venus Atmospheric Characterization and Trace Organics Identification

The chemical composition of Venus’ clouds has attracted considerable attention since the first atmospheric probes entered the planet in the early 1980s. We know from these early studies that cloud aerosols consist of micron and submicron droplets of sulfuric acid (~85%) and water (~15%), but outstanding questions still exist regarding their trace chemical composition, especially the identity of the unknown UV absorber(s) and the possible presence of organic material (Spacek & Benner, 2021). Veritas and DaVinci will launch at the end of the decade to advance our understanding of Venus’ surface and atmosphere, however these missions are not designed to sample and analyze cloud aerosols at trace levels. Raman spectroscopy is an ideal candidate for characterizing aerosols and has a track record in studies of Earth’s atmosphere. Raman provides broad chemical screening of organic and inorganic molecules within seconds, and Raman instrumentation can be miniaturized to meet the stringent size, weight, and power (SWaP) constraints of an atmospheric probe while retaining sensitivity and specificity that allow spectral fingerprinting of compounds and functional groups. Raman alone is insufficient to characterize trace constituents however, as limits of detection are typically in the 10s to 100s of ppm at best for planetary Raman spectrometers. Surface-Enhanced Raman Spectroscopy (SERS), a method that utilizes nanoscale materials interacting with a sample to enhance weak Raman signals by orders of magnitude when probed by a laser, has the potential to drastically improve the sensitivity of a Raman instrument while adding little-to-no SWaP nor complexity to a scientific payload. We aim to de-risk SERS technology for rapid infusion in future planetary science missions by developing custom SERS substrates tailored towards Venus atmospheric exploration. We have developed SERS substrates consisting of nanotextured silver films and tested them on potential Venus-relevant organic compounds, with preliminary results indicating sub-ppm sensitivity. Additionally, we have planned tests to investigate durability, longevity, and other key characteristics that impact SERS substrate performance to prepare SERS technology for flight.

Venus↗

Quantative Measurements of Trace Elements and Three-Dimensional Atomic Scale Characterisation of Presolar O-rich Oxides and Silicates: An Atom Probe Tomography Approach

Presolar grains are recordsof a single moment in stellar evolution which have survived nebula and parent body processingwithin our Solar System. These grains condensed within a range of stellar envi-ronments including asymptotic giant branch stars, red giant branch stars, nova, supernova (SN) and hydrogen burning electron capture supernova(ECSN)[1,2]. Iso-topic and chemical compositions can be used to unravel details about environmental conditions at the time of their condensation and physical and chemical processes occurring at the time. For example,nucleosynthesis, stellar evolution, physical properties of stellar atmos-pheres, mixing from inner core to outer envelope, galac-tic chemical evolution, interstellar medium and parent body processing.NanoSIMS enables detailed characterisation of iso-topic compositions and rapid in situidentification of O-rich presolar oxides and silicates using their character-istic 17O/16O and 18O/16O isotopic ratios.Spectroscopic techniques e.g., auger spectroscopyand transmission electron microscopy, have provided additional details on major and minor chemical signatures. However, due tospatial resolution limitations,interaction volumes and interferencesfrom surrounding grains for in situtech-niques, attaining quantative characterisation of trace el-ements,hasproved challenging[1,3]. As the most sensitive geochemical tracers of envi-ronmental changes, trace elements are essential to un-ravelling the geochemical record of their parent stellar environments and evolutionary pathways[4].We car-ried out correlated in situisotopic and chemical analyses of 13 presolar grains to better understand stellar evolu-tion. In this work, we achieved this using a custom ap-proach, coordinating NanoSIMS, Scanning Electron Microscopy Energy Dispersive X-Ray Spectroscopy (SEM-EDX)and Atom Probe Tomography(APT).Our objective was to develop an approach which could ena-ble precise targeting of presolar grains for atom probe tomography and successfully execute atomic scale anal-yses of presolar oxides and silicates, to achieve quantative analysis of their trace elements for the first time.We also aimed to test the capability for Atom Probe tomography to measure isotopic compositions and stoichiometries of presolar oxide and silicate grains.

N D Nevill↗

Modeling of Multicomponent Trace Contaminant Adsorption on Activated Carbon

Modeling of multicomponent trace contaminant adsorption on activated carbon for spacecraft life support applications presents challenges due to the very low contaminant concentrations in cabin air coupled with very strong adsorption of heavier components such as cyclic polydimethylsiloxanes. Both gas-phase and solid-phase micropore mass transfer resistances can be important, and competitive interactions between adsorbed components can result in behavior such as roll-up where lighter components displaced by heavier components have a higher concentration at the outlet than at the inlet. This paper describes the further development of a dynamic trace contaminant adsorption model based on Ideal Adsorbed Solution Theory (IAST). Alternative 1-dimensional and 2-dimensional versions of the model are described with different mass transfer resistance and driving force assumptions. Optimization of solution methods for speed and stability is also described. Mass balance equations are scaled to provide sensitivity over the wide range of component concentrations in cabin air. Model parameters are estimated from isotherm and breakthrough test data on single adsorbate and binary adsorbate systems. Multicomponent results are compared against predictions of a heritage model used extensively by NASA for trace contaminant control system (TCCS) carbon bed sizing. Finally, efforts to implement the model in a second software platform for wider access are described.

Kevin E Lange↗

Near-Complete Sampling of Forest Structure from High-Density Drone Lidar Demonstrated by Ray Tracing

Drone lidar has the potential to provide detailed measurements of vertical forest structure throughout large areas, but a systematic evaluation of unsampled forest structure in comparison to independent reference data has not been performed. Here, we used ray tracing on a high-resolution voxel grid to quantify sampling variation in a temperate mountain forest in the southwest Czech Republic. We decoupled the impact of pulse density and scan-angle range on the likelihood of generating a return using spatially and temporally coincident TLS data. We show three ways that a return can fail to be generated in the presence of vegetation: first, voxels could be searched without producing a return, even when vegetation is present; second, voxels could be shadowed (occluded) by other material in the beam path, preventing a pulse from searching a given voxel; and third, some voxels were unsearched because no pulse was fired in that direction. We found that all three types existed, and that the proportion of each of them varied with pulse density and scan-angle range throughout the canopy height profile. Across the entire data set, 98.1% of voxels known to contain vegetation from a combination of coincident drone lidar and TLS data were searched by high-density drone lidar, and 81.8% of voxels that were occupied by vegetation generated at least one return. By decoupling the impacts of pulse density and scan angle range, we found that sampling completeness was more sensitive to pulse density than to scan-angle range. There are important differences in the causes of sampling variation that change with pulse density, scan-angle range, and canopy height. Our findings demonstrate the value of ray tracing to quantifying sampling completeness in drone lidar.

47 OTHER INSTRUMENTATION↗

Analysis of Process Gases and Trace Contaminants in Membrane-Aerated Gaseous Effluent Streams.

In membrane-aerated biofilm reactors (MABRs), hollow fibers are used to supply oxygen to the biofilms and bulk fluid. A pressure and concentration gradient between the inner volume of the fibers and the reactor reservoir drives oxygen mass transport across the fibers toward the bulk solution, providing the fiber-adhered biofilm with oxygen. Conversely, bacterial metabolic gases from the bulk liquid, as well as from the biofilm, move opposite to the flow of oxygen, entering the hollow fiber and out of the reactor. Metabolic gases are excellent indicators of biofilm vitality, and can aid in microbial identification. Certain gases can be indicative of system perturbations and control anomalies, or potentially unwanted biological processes occurring within the reactor. In confined environments, such as those found during spaceflight, it is important to understand what compounds are being stripped from the reactor and potentially released into the crew cabin to determine the appropriateness or the requirement for additional mitigation factors. Reactor effluent gas analysis focused on samples provided from Kennedy Space Center's sub-scale MABRs, as well as Johnson Space Center's full-scale MABRs, using infrared spectroscopy and gas chromatography techniques. Process gases, such as carbon dioxide, oxygen, nitrogen, nitrogen dioxide, and nitrous oxide, were quantified to monitor reactor operations. Solid Phase Microextraction (SPME) GC-MS analysis was used to identify trace volatile compounds. Compounds of interest were subsequently quantified. Reactor supply air was examined to establish target compound baseline concentrations. Concentration levels were compared to average ISS concentration values and/or Spacecraft Maximum Allowable Concentration (SMAC) levels where appropriate. Based on a review of to-date results, current trace contaminant control systems (TCCS) currently on board the ISS should be able to handle the added load from bioreactor systems without the need for secondary mitigation.

Gaseous Effluent Streams↗

Optical Error Budgeting Using Linearized Ray-Trace Models

The Root-Sum-Squared, or “RSS” wavefront error model is a simple, scalar tool, commonly used for space telescope error budgeting. At the same time, much more detailed models, combining ray-trace and Fourier optics with optical alignments and wavefront controls, can provide accurate, high -resolution simulations for detailed system and subsystem design. This paper makes a connection between the two modeling approaches by deriving RSS model coefficients from ray-trace models, including the effects of wavefront controls, for computing system performance from component error statistics. It is shown that, properly constructed, the simple RSS error budget is a covariance analysis, and can be as accurate as high-resolution wavefront models for statistical wavefront error prediction. A notional segmented-aperture space telescope is used to illustrate this error modeling process.

Wavefront error↗

How Well Satellite Remote Sensing Can Inform Surface Level Ozone Production Sensitivity to Precursor Trace Gas Emissions?

Surface-level ozone (O3) pollution mitigation strategies rely on a clear understanding of the atmospheric chemical processes involving O3, NOx (nitric oxide (NO) + nitrogen dioxide (NO2)) and volatile organic compounds (VOCs). A robust spatiotemporal classification of O3 photochemical regimes with relative chemical sensitivity of local O3 formation to emission reductions of NOx (NOx-limited regime) versus VOCs (radical-limited regime) is required to design anthropogenic emission reduction policies in order to improve surface air quality. Numerous studies found that the ratio of satellite-retrieved Vertical Column Densities (VCDs) of formaldehyde (HCHO) to NO2 can diagnose O3 production sensitivity. However, uncertainty still remains about the accuracy of such estimates using satellite-based retrievals. This study conducts an investigation to identify how well satellite data can inform surface-level O3 sensitivity by validating satellite-based estimates against aircraft-based retrievals taken during the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) and Ozone Water-Land Environmental Transition Study (OWLETS-2) field campaigns. For this study, we use HCHO and NO2 retrievals from the Ozone Monitoring Instrument (OMI) onboard the Aura satellite, and high spatiotemporal resolution TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite. The Community Multiscale Air Quality (CMAQ) modelling system is used to provide trace gas vertical profiles to recalculate air mass factor for deriving consistent satellite-based VCDs. To demonstrate the ability of satellites to diagnose O3 production regimes, we validate satellite-derived O3 sensitivity regimes, along with the OMI and TROPOMI products applied, using HCHO and NO2 retrievals from the aircraft-based instruments: Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) spectrometer and Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) instruments deployed during the LISTOS-2018 and OWLETS-2 campaigns. The results of this work will advance our fundamental knowledge of the spatiotemporal evolution of the complex O3-NOx-VOC chemistry, and will advance our understanding about the quality of remote-sensing, suborbital, and satellite data for accurately observing surface-level O3 production sensitivity.

Satellite↗

Lamination and polar vortex development in fall from ATMOS long-lived trace gases observed during November 1994

Long-lived trace-gas profiles observed by the Atmospheric Trace Molecule Spectroscopy (ATMOS) instrument around the developing polar vortex (the protovortex) during early November 1994 show distinctive inversions (lamiane). High-resolution profiles calculated using a reverse trajectory (RT) model to produce the majority of these laminae, demonstrating that most of these features arise from advection by the large-scale winds.

polar↗

Spectral Bounds on Hyperbolic 3-Manifolds: Associativity and the Trace Formula

We constrain the low-energy spectra of Laplace operators on closed hyperbolic manifolds and orbifolds in three dimensions, including the standard Laplace--Beltrami operator on functions and the Laplacian on powers of the cotangent bundle. Our approach employs linear programming techniques to derive rigorous bounds by leveraging two types of spectral identities. The first type, inspired by the conformal bootstrap, arises from the consistency of the spectral decomposition of the product of Laplace eigensections, and involves the Laplacian spectra as well as integrals of triple products of eigensections. We formulate these conditions in the language of representation theory of PSL 2 (C) and use them to prove upper bounds on the first and second Laplacian eigenvalues. The second type of spectral identities follows from the Selberg trace formula. We use them to find upper bounds on the spectral gap of the Laplace--Beltrami operator on hyperbolic 3-orbifolds, as well as on the systole length of hyperbolic 3-manifolds, as a function of the volume. Further, we prove that the spectral gap λ 1 of the Laplace--Beltrami operator on all closed hyperbolic 3-manifolds satisfies λ 1 < 47.32. Along the way, we use the trace formula to estimate the low-energy spectra of a large set of example orbifolds and compare them with our general bounds, finding that the bounds are nearly sharp in several cases.

Bonifacio, James [University of Mississippi, MS (U↗

Modeling receiver flux of commercial power tower concentrating solar power plants using ray tracing: a round-robin comparison of SolTrace, Solstice, and TieSOL

This study presents a multi-stage, cross-validation comparison of three software packages for Monte Carlo ray tracing (MCRT) applied to central tower concentrating solar power (CSP) systems. The three packages evaluated are: (1) SolTrace, an open-source tool developed by the National Renewable Energy Laboratory (NREL); (2) Solstice, an open-source program created by CNRS-PROMES and Meso-Star, with enhancements for CSP applications (called solsticepy) from the Australian National University; and (3) TieSOL, a commercial software developed by Tietronix. This investigation extends previous ray tracing comparisons by incorporating models of multi-facet heliostats within a commercial-scale solar field, taking into account zoned focal lengths and canting configurations. Receiver flux distributions were compared across the tools using a series of case studies, including single-heliostat scenarios, isolated blocking situations, and comprehensive full-field simulations. The case studies were designed to diagnose differences across the models at varying levels of complexity, and to identify and resolve discrepancies as additional parameters were introduced. Key factors examined in the analysis include sun positions, heliostat location, facet and canting focus, and aimpoint strategies. The comparison aims to improve the accuracy and reliability of these tools while providing benchmark cases for validating future optical modeling tools.

14 SOLAR ENERGY↗

Optical 14 C Tracing for Biological and Pharmaceutical Applications Using Two-Color Cavity Ringdown Spectroscopy

Laser-based 14 C quantitation has been proposed as a more affordable, higher-throughput, table-top alternative to accelerator mass spectrometry (AMS). Here, we demonstrate the feasibility of a mid-IR 14 C detector based on two-color cavity ringdown spectroscopy (2C-CRDS) for low-level 14 C isotope tracing in biological studies. The 2C-CRDS technique quantifies the sample 14 C content by measuring the 14 CO 2 absorption signals from the combusted samples with mid-IR lasers. With 2C-CRDS, we previously demonstrated the most sensitive and accurate optical measurements of 14 CO 2 . The current detection sensitivity and quantitation accuracy of the instrument, at a few parts per quadrillion (where a quadrillion = 10 15 ) 14 C/C mole fraction, is competitive against AMS. Here, by applying the 2C-CRDS 14 C sensor to two applications relevant to 14 C-labeled biochemical analysis and pharmaceutical studies, we demonstrate sub-fCi level (where 1 fCi = 10 –15 Ci) quantitation of sample 14 C activity, with a minimum sample-size requirement of 3 mg of carbon. The current measurement throughput, ~25 min/sample, is largely limited by the sampling efficiency of the online combustion and CO 2 processing interface to the 2C-CRDS instrument. The possibility of a significantly improved measurement throughput of a few minutes per sample is suggested by the results of a flow-through 14 CO 2 sampling scheme. In conclusion, this improved measurement efficiency, combined with the relatively low cost and compact size of a 2C-CRDS sensor, could potentially revolutionize high-sensitivity 14 C tracing in biological, pharmaceutical, and clinical studies.

60 APPLIED LIFE SCIENCES↗

Trace LiBF 4 Enabling Robust LiF-Rich Interphase for Durable Low-Temperature Lithium-Ion Pouch Cells

Lithium-ion batteries (LIBs) with electrolytes containing lithium tetrafluoroborate (LiBF 4 ) can achieve large capacity retention under low temperature, but the accompanying rapid capacity decay inhibits commercialization. Here, in this study, the impact of LiBF 4 as a supplemental salt to LiPF 6 is systematically investigated using low ethylene carbonate (EC)-content electrolytes, along with a low-melting-point cosolvent. It is found that rational adjustment of the amount of LiBF 4 could not only regulate the interactions of anions and solvents in Li + solvation sheaths but also tune the composition and morphology of solid electrolyte interphase (SEI). It is worth noting that electrolytes with trace amount of LiBF 4 (0.05 M) show synergetic interaction between PF 6 - and Li + and decreased interaction between EC and Li + , achieving a dense and LiF-rich SEI, which enables a 200 mAh pouch cell with less gas generation, long-lived cycling, and higher low-temperature capacity, simultaneously. This work provides new insight into utilizing trace LiBF 4 for stable interface construction of durable low-temperature LIBs.

25 ENERGY STORAGE↗

Finding a needle in a haystack: quantitative HERFD-XRF imaging and HERFD-XANES characterization of trace platinum in gold solidi from the Late Roman and Byzantine Empires

High-Energy Resolution Fluorescence Detection X-Ray Fluorescence (HERFD-XRF) imaging and HERFD X-ray Absorption Near Edge Structure (XANES) spectroscopy are used to quantify and characterize trace platinum (Pt) in gold solidi from the Late Roman and Byzantine Empires. Historically, the elemental analysis of coins has been pivotal in distinguishing authentic artifacts from forgeries, elucidating minting practices, and understanding economic shifts. Notably, a new gold source with high platinum content appeared in the fourth century CE, transforming the Roman economy. Traditional methods struggled to detect platinum due to the overwhelming gold matrix. Here, this study demonstrates the effectiveness of HERFD techniques in resolving this challenge. Three gold solidi, minted between 654 and 659 CE, were analyzed alongside reference gold materials with known Pt concentrations. The HERFD-XRF imaging revealed spatial distributions of platinum, highlighting non-uniformities within the coins. Additionally, HERFD-XANES spectroscopy identified the oxidation states and chemical speciation of platinum. Results demonstrate that platinum in the solidi primarily exists as metallic Pt, with some surface oxidation. The findings align with previous measurements but reveal higher Pt concentrations and significant inhomogeneities. This research confirms the reliability of HERFD methods for quantifying trace elements and provides new insights into the raw material sources and minting techniques of ancient gold coins. The non-destructive nature of this approach allows for extensive analyses, offering valuable data for historical, economic, and archaeological studies. This innovative application of HERFD-XRF imaging and XANES in cultural heritage research underscores the potential for detailed material characterization and conservation, enhancing our understanding of ancient economies and trade patterns.

Van Loon, Lisa L.↗