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Enantiomer Ratios of Meteoritic Sugar Derivatives

Carbonaceous meteorites contain a diverse suite of soluble organic compounds. Studies of these compounds reveal the Solar System's earliest organic chemistry. Among the classes of organic compounds found in meteorites are keto acids (pyruvic acid, etc.), hydroxy tricarboxylic acids (1), amino acids, amides, purines and pyrimidines. The Murchison and Murray meteorites are the most studied for soluble and insoluble organic compounds and organic carbon phases. The majority of (indigenous) meteoritic compounds are racemic, (i.e., their D/L enantiomer ratios are 50:50). However, some of the more unusual (non-protein) amino acids contain slightly more of one enantiomer (usually the L) than the other. This presentation focuses on the enantiomer analyses of three to six-carbon (3C to 6C) meteoritic sugar acids. The molecular and enantiomer analysis of corresponding sugar alcohols will also be discussed. Detailed analytical procedures for sugar-acid enantiomers have been described. Results of several meteorite analyses show that glyceric acid is consistently racemic (or nearly so) as expected of non-biological mechanisms of synthesis. Also racemic are 4-C deoxy sugar acids: 2-methyl glyceric acid; 2,4-dihydroxybutyric acid; 2,3-dihydroxybutyric acid (two diastereomers); and 3,4-dihydroxybutyric acid. However, a 4C acid, threonic acid, has never been observed as racemic, i.e., it possesses a large D excess. In several samples of Murchison and one of GRA 95229 (possibly the most pristine carbonaceous meteorite yet analyzed) threonic acid has nearly the same D enrichment. In Murchison, preliminary isotopic measurements of individual threonic acid enantiomers point towards extraterrestrial sources of the D enrichment. Enantiomer analyses of the 5C mono-sugar acids, ribonic, arabinonic, xylonic, and lyxonic also show large D excesses. It is worth noting that all four of these acids (all of the possible straight-chained 5C sugar acids) are present in meteorites, including the rare lyxonic acid, and their relative abundances are in equilibrium proportions. In addition (in contrast to the above D-only excesses), some of the above acids are found in biology as the L enantiomer. Whether rare are common, all of the 6C sugar acids that are present in sufficient amounts to allow enantiomer analysis (Mannonic, gluconic, altronic, talonic, idonic, gulonic, and galactonic) also, apparently, possess significant D excesses.

Cooper, George↗

Kennedy Space Center: Swamp Works

When I began my internship with the Granular Mechanics and Regolith Operations laboratory (GMRO), also known as Swamp Works, I was given the unique opportunity to shadow many teams working on various projects, and decide what projects I wanted to take part in. Before I go into details of my experiences at Swamp Works, I would like to take a moment to explain what I discovered Swamp Works to be. Swamp Works is a family of hardworking, dedicated, and driven people from various backgrounds and skill sets. These people all work to advance technologies and make science fiction science fact through means of rapid prototyping. They support and encourage failure as an option when learning new things, as long as lesson learned from said failure. In fact, their motto states "Fail, Fast, Forward." What this means is, not if but when one fails he or she must do so quickly and spring forward from the failure so that his or her progress is not delayed. With this acceptance, it provided me the confidence to dive into a multitude of projects working in various fields and with a wide range of skill sets. The first project I joined was Badger. My motivation for taking on this project was the opportunity I would have to obtain valuable experience working with 3D modeling and 3D printing technologies. Badger was a digging apparatus to be used in a highly dusty environment in a material known as Regolith. Regolith is a scientific term for the dirt or top soil found on planetary bodies. Regolith contains a large quantity of sediments less than lOppm and as a result poses a challenge of keeping it out of any cracks and crevices. Furthermore, regolith can create high levels of electrostatic energy, which can prove damaging to sensitive electrical hardware. With these characteristics in mind, I decided to take on the task of designing and manufacturing a dust proof cover for the sensitive electrical hardware. When I began this project, I did not have the slightest idea as to how to use 3D modeling software or a means of manufacturing a viable product. As I went along with variants of the design, I became very proficient with a 3D modeling program known as CREO 2.0. Upon completion of my 3D design, I then had the task of manufacturing and having, in my hands, a usable model. To do this I had to work with additive printing technologies also known as 3D printing. Through my experiences working with Badger, I realized that 3D modeling is the focal point in much of engineering. With this in mind, I have embraced this fact and decided to further my experience with this software so that I may become a more valuable asset to any firm later in my career. Mid-way through work with Badger, I picked up another project in which I found much interest. I ha~ the opportunity to work side by side with a materials and composites guru in manufacturing carbon composite coupons (test strips) for performing stress, strain, and sheer analysis on. Being from a surfing, kiteboarding, and other water sport background I have always been interested in board design. With this in mind, it is no wonder why I found interest in such a project. I had the opportunity to refine Mold preparatory, composite layup, and composite curing techniques. Following manufacturing of these composite strips, I then performed various stress tests and logged my results. With these results, future teams could create lighter, stronger, and more cost effective composite structures for use in varieties of applications. After my experiences with materials and composites testing, I have obtained crucial appreciation for detailed documentation and analysis that material sciences involve. However, as interesting as composite materials testing has been, I do not feel this is where my future career lies. Another, more on the side, project I have been involved in is building a 626 cubic foot regolith containment chamber for doing full scale testing of robotic systems. This chamber is built of high strength aluminum scaffold materials, 80/20, and massive panels of Lexan. Once the chamber is completed, it is be filled with 120 tons of regolith and dubbed the largest regolith test chamber in the world. Through my experiences with building "Big Bin" as we called it, I discovered my demand for engaging and hands on activities. Through all of my incredible experiences working with the Swamp Works at Kennedy Space Center; I have obtained crucial knowledge, insights, and experiences that have fuelled, shaped, and will continue to drive me toward my ultimate goal of obtaining not only a degree in Engineering, but obtaining a job that I can call a career. I want to give much thanks to all of those who mentored me along my journey, and to all who made this opportunity a reality.

DeFilippo, Anthony Robert↗

Satellite Observations of Desert Dust-induced Himalayan Snow Darkening

The optically thick aerosol layer along the southern edge of the Himalaya has been subject of several recent investigations relating to its radiative impacts on the South Asian summer monsoon and regional climate forcing. Prior to the onset of summer monsoon, mineral dust from southwest Asian deserts is transported over the Himalayan foothills on an annual basis. Episodic dust plumes are also advected over the Himalaya, visible as dust-laden snow surface in satellite imagery, particularly in western Himalaya. We examined spectral surface reflectance retrieved from spaceborne MODIS observations that show characteristic reduction in the visible wavelengths (0.47 nm) over western Himalaya, associated with dust-induced solar absorption. Case studies as well as seasonal variations of reflectance indicate a significant gradient across the visible (0.47 nm) to near-infrared (0.86 nm) spectrum (VIS-NIR), during premonsoon period. Enhanced absorption at shorter visible wavelengths and the resulting VIS-NIR gradient is consistent with model calculations of snow reflectance with dust impurity. While the role of black carbon in snow cannot be ruled out, our satellite-based analysis suggests the observed spectral reflectance gradient dominated by dust-induced solar absorption during premonsoon season. From an observational viewpoint, this study underscores the importance of mineral dust deposition toward darkening of the western Himalayan snow cover, with potential implications to accelerated seasonal snowmelt and regional snow albedo feedbacks.

Remote Sensing↗

Quantification of Aerosol Type, and Sources of Aerosols Over the Indo- Gangetic Plain

Differences and similarities in aerosol characteristics, for the first time, over two environmentally distinct locations in Indo-Gangetic plain (IGP) e Kanpur (KPR) (urban location) and Gandhi College (GC) (rural site) are examined. Aerosol optical depths (AODs) exhibit pronounced seasonal variability with higher values during winter and premonsoon. Aerosol fine mode fraction (FMF) and Ångstrom exponent (a) are higher over GC than KPR indicating relatively higher fine mode aerosol concentration over GC. Higher FMF over GC is attributed to local biomass burning activities. Analysis of AOD spectra revealed that aerosol size distribution is dominated by wide range of fine mode fractions or mixture of modes during winter and postmonsoon, while during premonsoon and monsoon coarse mode aerosols are more abundant. Single scattering albedo (SSA) is lower over GC than KPR. SSA spectra reveals the abundance of fine mode (coarse mode) absorbing (scattering) aerosols during winter and postmonsoon (premonsoon and monsoon). Spectral SSA features reveal that OC contribution to enhanced absorption is negligible. Analysis shows that absorbing aerosols can be classified as Mostly Black Carbon (BC), and Mixed BC and Dust over IGP. Mixed BC and dust is always higher over KPR, while Mostly BC is higher over GC throughout the year. The amount of long range transported dust exhibits a gradient between KPR (higher) and GC (lower). Results on seasonally varying aerosol types, and absorbing aerosol types and their gradients over an aerosol hotspot are important to tune models and to reduce the uncertainty in radiative and climate impact of aerosols.

Organic Carbon↗

Indigenous Amino Acids in Iron Meteorites

Understanding the organic content of meteorites and the potential delivery of molecules relevant to the origin of life on Earth is an important area of study in astrobiology. There have been many studies of meteoritic organics, with much focus on amino acids as monomers of proteins and enzymes essential to terrestrial life. The majority of these studies have involved analysis of carbonaceous chondrites, primitive meteorites containing approx. 3-5 wt% carbon. Amino acids have been observed in varying abundances and distributions in representatives of all eight carbonaceous chondrite groups, as well as in ungrouped carbonaceous chondrites, ordinary and R chondrites, ureilites, and planetary achondrites [1 and references therein].

carbonaceous chondrites↗

Air Quality Forecasts Using the NASA GEOS Model

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

Knowland, K. Emma↗

Collaborative Data Curation to Support the Multi-Mission Algorithm and Analysis Platform (MAAP)

Upcoming space-borne missions will offer unprecedented data about Earth but will also feature exponentially high data volumes. These high data volumes will change the way the scientific community works with data and will also create a unique need for improved data sharing and collaboration. NASA and ESA are working together to address these issues by collaboratively developing the Multi-Mission Algorithm and Analysis Platform (MAAP) to improve the understanding of global aboveground terrestrial carbon dynamics. The MAAP will support ESA’s BIOMASS mission, NASA’s GEDI mission and NASA/ISRO’s NISAR mission. The MAAP will be developed in two phases: a pilot phase and a full production phase. The pilot phase will demonstrate collaboration and basic capabilities. The pilot phase will focus on biomass relevant airborne and field campaign data. Two NASA teams are supporting the development of the MAAP. The MAAP engineering team is responsible for the development, maintenance and operations of the MAAP system while the MAAP data team ensures the ongoing quality of the data, metadata and other information provided in the MAAP. The MAAP data team also supports the ingest and archive of identified data to the MAAP platform. This poster describes the use case development process for the pilot MAAP and the data curated in support of those use cases. Additionally, this presentation will outline the pilot MAAP data ingest process and metadata curation effort along with efforts to ensure interoperability between ESA and NASA data and metadata.

Bugbee, Kaylin↗

Near Real-Time Global Composition Forecasts at 25km Horizontal Resolution

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

Near Real-Time Air Quality Forecasts Using the NASA GEOS Model

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

Near Real-Time Air Quality Forecasts Using the NASA GEOS Model

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

Air Pollution Forecasts Using the NASA GEOS Model: A Unified Tool from Local to Global Scales

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

Near real-time air quality forecasts using the NASA GEOS model

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke. The assimilation system is being expanded to include chemically reactive trace gases. We discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions, notably incorporating new observations (TROPOMI, geostationary satellites) and machine learning techniques. We show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Air Quality Forecast↗

A Drilling Mission to Search for Biosignatures of Life on Mars Simulated in Atacama Chile

Missions to search for evidence of life on Mars, including Mars Science Laboratory(MSL)are using drilling systems to get beneath the high oxidized and radiated surface where biomolecules may be preserved. MSL drill holes show that even at shallow depth the subsurface is more reduced and therefor more likely to preserve biosignatures. Analysis of these reduced materials yielded the first detection of organic carbon compounds on Mars[1].While MSL was capable of drilling only 10 cm, the ExoMars mission now planned for a 2022 launch will feature a rover carrying a 2 m drill, motivated by desire to penetrate beneath the irradiated surface. The Atacama Rover Astrobiology Drilling Studies(ARADS)was a PSTAR project that used flight prototype technologies in a highly relevant Mars analog site, together with related scientific studies, to better understand how to best search for life on Mars. ARADS field work was performed in Atacama Chile and featured a rover-mounted 1.2m auguring drill to acquire subsurface samples that were analyzed with flight prototype instruments designed to search for chemical signatures of life.

C R Stoker↗

Near Real-time Air Quality Forecasts Using the NASA GEOS Model

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Future developments for the next GEOS-CF version will be discussed, including the assimilation system is being expanded to include chemically reactive trace gases, specifically using the capabilities of the GEOS Constituent Data Assimilation System (CoDAS).

CoDAS↗

NASA's High-Resolution GEOS Forecasting and Reanalysis Products: A Unified Tool from Local to Global Scales

NASA's GMAO produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric chemical composition at unprecedented horizontal resolution of 0.25 degrees (~25 km), freely available to the public. This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). GEOS-CF also assimilated satellite observations into the system for improved representation of weather and smoke. The assimilation system is currently being expanded to include chemically reactive trace gases. While the main focus of this new product is on tropospheric air quality information, the GEOS-Chem chemistry model used in this system includes the unified tropospheric stratospheric chemistry mechanism for improved forecasts of total column ozone during anomalous dynamical and chemical events. I will discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions for GEOS-CF and reanalysis products. In addition, I will show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Co-DAS↗

Evolved Gas Analyses of Sedimentary Rocks from the Glen Torridon Clay-Bearing Unit, Gale Crater, Mars: Results From the Mars Science Laboratory Sample Analysis at Mars Instrument Suite

Evolved gas analysis (EGA) data from the Sample Analysis at Mars (SAM) instrument suite indicated Fe-rich smectite, carbonate, oxidized organics, Fe/Mg sulfate, and chloride in sedimentary rocks from the Glen Torridon (GT) region of Gale crater that displayed phyllosilicate spectral signatures from orbit. SAM evolved H2O data indicated that the primary phyllosilicate in all GT samples was an Fe-rich dioctahedral smectite (e.g., nontronite) with lesser amounts of a phyllosilicate such as mixed layer talc-serpentine or greenalite-minnesotaite. CO(2) data supported the identification of siderite in several samples, and CO(2) and CO data was also consistent with trace oxidized organic compounds such as oxalate salts. SO(2) data indicated trace and/or amorphous Fe sulfates in all samples and one sample may contain Fe sulfides. SO(2) data points to significant Mg sulfates in two samples, and lesser amounts in several other samples. A lack of evolved O(2) indicated the absence of oxychlorine salts and Mn3+/Mn4+ oxides. The lack of, or very minor, evolved NO revealed absent or very trace nitrate/nitrite salts. HCl data suggested chloride salts in GT samples. Constraints from EGA data on mineralogy and chemistry indicated that the environmental history of GT involved alteration with fluids of variable redox potential, chemistry and pH under a range of fluid-to-rock ratio conditions. Several of the fluid episodes could have provided habitable environmental conditions and carbon would have been available to any past microbes though the lack of significant N could have been a limiting factor for microbial habitability in the GT region.

A. C. McAdam↗

Near Real Time Air Quality Forecasts Using the NASA GEOS Model

This presentation provides an overview of NASA's Global Modeling and Assimilation Office (GMAO) high-resolution global forecast and reanalysis products for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model radiatively coupled to GOCART aerosol module assimilates 2-dimensional column-integrated aerosol optical depth (AOD) at one wavelength (550 nm) in order to constrain the model's background AOD in order to have the best historical estimate and forecasts of AOD and particulate matter. Furthermore, the GEOS model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

K Emma Knowland↗

Near Real Time Air Quality Forecasts Using the NASA GEOS Model

This presentation provides an overview of NASA's Global Modeling and Assimilation Office (GMAO) high-resolution global forecast and reanalysis products for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model radiatively coupled to GOCART aerosol module assimilates 2-dimensional column-integrated aerosol optical depth (AOD) at one wavelength (550 nm) in order to constrain the model's background AOD in order to have the best historical estimate and forecasts of AOD and particulate matter. Furthermore, the GEOS model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

K Emma Knowland↗