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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Individual Aerosol Particles from Biomass Burning in Southern Africa: Compositions and Size Distributions of Carbonaceous Particles - 1

Individual aerosol particles in smoke plumes from biomass fires and in regional hazes in southern Africa were studied using analytical transmission electron microscopy (TEM), which allowed detailed characterization of carbonaceous particle types in smoke and determination of changes in particle properties and concentrations during smoke aging. Based on composition, morphology, and microstructure, three distinct types of carbonaceous particles were present in the smoke: organic particles with inorganic (K-salt) inclusions, tar ball particles, and soot. The relative number concentrations of organic particles were largest in young smoke, whereas tar balls were dominant in a slightly aged (1 hour) smoke from a smoldering fire. Flaming fires emitted relatively more soot particles than smoldering fires, but soot was a minor constituent of all studied plumes. Further aging caused the accumulation of sulfate on organic and soot particles, as indicated by the large number of internally mixed organic/sulfate and soot/sulfate particles in the regional haze. Externally mixed ammonium sulfate particles dominated in the boundary layer hazes, whereas organic/sulfate particles were the most abundant type in the upper hazes. Apparently, elevated haze layers were more strongly affected by biomass smoke than those within the boundary layer. Based on size distributions and the observed patterns of internal mixing, we hypothesize that organic and soot particles are the cloud-nucleating constituents of biomass smoke aerosols. Sea-salt particles dominated in the samples taken in stratus clouds over the Atlantic Ocean, off the coast of Namibia, whereas a distinct haze layer above the clouds consisted of aged biomass smoke particles.

Posfai, Mihaly↗

Enumeration and Fluorescence In Situ Hybridization of Microbial Bioburden on Cleanroom Surfaces

Introduction: Microorganisms are everywhere on Earth, even in the cleanest of places. Spacecraft assembly cleanrooms can harbor low levels of living and dead microbial cells (e.g., [1,2]), and cleanroom bioburden can also include organic molecules from industrial sources and in situ biomass. Life detection missions require careful attention to avoid contaminants that can be easily convoluted with analytical targets. We are evaluating epifluorescent microscopy and fluorescence in situ hybridization (FISH) as methods to complement organic contamination detection techniques. Epifluorescent cell counting offers an accurate and cost-effective way to quantify low levels of surface biomass. FISH could allow for the identification of residual organisms, and can be targeted to detect active populations of specific organisms such as bacteria known to resist cleaning procedures. This effort is part of a larger study that is concentrated on characterizing the surface and airborne molecular organic contamination background in Johnson Space Center (JSC) Astromaterials curation laboratories and Goddard Space Flight Center (GSFC) spacecraft assembly rooms, and understanding contaminants in the context of cleaning procedures and residual bioburden. Methods: Samples were collected by swabbing surfaces in ISO 5 and ISO 7 equivalent cleanrooms at JSC. Swabs for FISH were fixed in 4% paraformaldehyde (PFA) for 3 hours and then stored in 1:1 ethanol:PBS, while swabs for cell counting were stored in 4% PFA until analysis to avoid any cell loss during centrifugation that could impact quantification of very low biomass samples. Cell counting was performed with SYBR Gold as in [3], but adapted for very low biomass. FISH was performed as in [4], using DAPI as a counterstain for all DNA-containing cells. Negative controls included wells with no probe applied, to test for natural fluorescence, as well as the nonsense probe NONEUB (reverse complement of EUB338) to evaluate non-specific probe binding. Results and Discussion: Cleanroom surfaces had 102-103 cells cm-2. The extremely low biomass of these samples was challenging for enumeration, and required careful and routine use of “field” and laboratory blanks. FISH was performed with the general archaeal and bacterial probes ARCH915 and EUB338 (EUBMIX, [4]), probe GAMBET ([4]), and PSE227, which targets the genus Pseudomonas [5]). The latter two probes were selected because Pseudomonas spp. and other Gammaproteobacteria have not been isolated from cleanroom surfaces but do appear frequently in rRNA gene libraries from these surfaces. While some active bacteria were identified (Fig. 1c), most cells detectable by DAPI did not have a strong or any fluorescent signal (e.g., Fig. 1d), indicating that the vast majority of cells are dead or inactive. This suggests that cleaning protocols are effective at inactivating microbial contaminants, but that dead or inactive cells can remain on surfaces. Cells were often clumped in a weakly autofluorescent matrix, possibly biofilm material (Fig. 1c,d). We also observed other particulate material that was collected by the swabs, including apparent textile fibers (Fig. 1b). Our results are consistent with other studies that show that the bioburden present in clean rooms includes active, dormant, and dead cells. We will discuss how FISH and epifluorescent cell counting could be applied in planetary protection protocols, including the advantages and disadvantages of FISH and cell counting for routine use, as well as different possible applications for more specialized FISH procedures. References: [1] Moissl-Eichinger et al. (2015) Sci Rep, 5, 9156 [2] Hendrickson et al. (2021) Microbiome, 9, 238 [3] Jones et al. (2017) Appl Environ Microbiol, 83, e00909-17 [4] Jones et al. (2015) Appl Environ Microbiol, 81, 1242-1250. [5] Watt et al. (2006) Environ Microbiol, 8, 871-884

C J Huff↗

Accurate Biomass Estimation via Bayesian Adaptive Sampling

The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.

Wheeler, Kevin R.↗

Soil Moisture Estimate Under Forest Using a Semi-Empirical Model at P-Band

Here we present the result of a semi-empirical inversion model for soil moisture retrieval using the three backscattering coefficients: sigma(sub HH), sigma(sub VV) and sigma(sub HV). In this paper we focus on the soil moisture estimate and use the biomass as an ancillary parameter estimated automatically from the algorithm and used as a validation parameter, We will first remind the model analytical formulation. Then we will sow some results obtained with real SAR data and compare them to ground estimates.

soil moisture↗

TEM Study of SAFARI-2000 Aerosols

The aim of our research was to obtain data on the chemical and physical properties of individual aerosol particles from biomass smoke plume s in southern Africa and from air masses in the region that are affec ted by the smoke. We used analytical transmission electron microscopy (ATEM), including energy-dispersive X-ray spectrometry (EDS) and ele ctron energy-loss spectroscopy (EELS), and field-emission electron microscopy (FESEM) to study aerosol particles from several smoke and haz e samples and from a set of cloud samples.

Buseck, Peter R.↗

Development of a Coherent Bistatic Vegetation Model for Signal of Opportunity Applications at VHF UHF-Bands

A coherent bistatic vegetation scattering model, based on a Monte Carlo simulation, is being developed to simulate polarimetric bi-static reflectometry at VHF/UHF-bands (240-270 MHz). The model is aimed to assess the value of geostationary satellite signals of opportunity to enable estimation of the Earth's biomass and root-zone soil moisture. An expression for bistatic scattering from a vegetation canopy is derived for the practical case of a ground-based/low altitude platforms with passive receivers overlooking vegetation. Using analytical wave theory in conjunction with distorted Born approximation (DBA), the transmit and receive antennas effects (i.e., polarization, orientation, height, etc.) are explicitly accounted for. Both the coherency nature of the model (joint phase and amplitude information) and the explicit account of system parameters (antenna, altitude, polarization, etc) enable one to perform various beamforming techniques to evaluate realistic deployment configurations. In this paper, several test scenarios will be presented and the results will be evaluated for feasibility for future biomass and root-zone soil moisture application using geostationary communication satellite signals of opportunity at low frequencies.

UFH↗

Crop growth and associated life support for a lunar farm

Supporting human life on a lunar base will require growing many different food crops. This paper investigates the growth dynamics of four crops (wheat, soybeans, potatoes, and lettuce) for general similarities and differences, along with associated material flows of the gases, liquids, and solids in a lunar farm. The human dietary requirements are compared with the protein, carbohydrate, and lipid contents of these hydroponically grown, high-productivity crops to derive a lunar farm diet. A simple and general analytical model is used to calculate the mass fluxes of CO2, H2O, HNO3, and O2 during the life cycle of each of the four crops. The resulting farm crop areas and corresponding biomass production rates are given. One significant conclusion of this study is that there is a 'lipid problem' associated with the incorporation of these four crops into a viable diet.

Volk, Tyler↗

Spectral Range Within Global aCDOM(440) Algorithms for Oceanic, Coastal, and Inland Waters with Application to Airborne Measurements

The optically active component of dissolved organic material in aquatic ecosystems, or colored dissolved organic matter (CDOM), is represented by the coefficient of absorption due to the dissolved aquatic constituents at 440 nm, aCDOM(440). Remote sensing of aCDOM(440) enables characterization of ecosystem processes and aids in retrieval of chlorophyll a, a proxy for phytoplankton biomass. Spectrally adjacent band-ratio domains, e.g., blue to green, have previously been applied for remote sensing of aCDOM(440) in coastal and oceanic waters with similar results compared to more complex semi-analytical algorithms. Estimation of aCDOM(440) from ratios of the most spectrally separated ocean color wavebands (end members), e.g., ultraviolet (UV) to near-infrared (NIR), termed end-member analysis (EMA), has previously been shown to increase the accuracy of global aCDOM(440) retrievals from in-water observations of diffuse attenuation and to enable a unified algorithmic perspective without requiring regional adjustment of internal bio-optical parameters. EMA of above-water observations is evaluated herein, with a focus on coastal and inland waters in which increasing optical complexity and likelihood of bottom reflectance challenge the oceanic algorithms developed for deep and optically simple (case-1) waters. Analysis herein of three independent, in situ, bio-optical datasets indicates significant correlation between aCDOM(440) and end-member band ratios (next-generation 320 and 780 nm or legacy 412 and 670 nm ratios) with a coefficient of determination, R2, of 0.87 (log-scale) or higher based on a dataset spanning the dynamic range of global, conservative water bodies. For applicable wavelengths, EMA algorithms are shown to agree with case-1 relationships and to produce consistent log-scale uncertainties across more than three orders of magnitude in aCDOM(440) values (0.001–2.305 m􀀀1). EMA using UV and NIR wavelengths (320 and 780 nm) is applied to low-altitude airborne observations and satisfies 25% uncertainty based on unbiased percent differences (UPDs) within each of three dissimilar match-up sites ranging in aCDOM(440) from 0.02–0.57 m􀀀1. Results demonstrate that EMA is a useful and robust approach for the remote sensing of aCDOM(440) in coastal and inland waters, which are generally shallower, contain more optically complex environments, and span a greater range in aCDOM(440) than oceanic waters.

CDOM↗

Remote Sensing of CDOM, CDOM Spectral Slope, and Dissolved Organic Carbon in the Global Ocean

A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245–715 nm, CDOM spectral slopes in eight visible and ultraviolet wavebands, dissolved and particulate organic carbon (DOC and POC, respectively), and inherent optical, physical, and biogeochemical properties. From field optical and radiometric data and satellite measurements, several semi-analytical, empirical, and machine learning algorithms for retrieving global DOC, CDOM, and CDOM slope were developed, optimized for global retrieval, and validated. Global climatologies of satellite-retrieved CDOM absorption coefficient and spectral slope based on the most robust of these algorithms lag seasonal patterns of phytoplankton biomass belying Case 1 assumptions, and track terrestrial runoff on ocean basin scales. Variability in satellite retrievals of CDOM absorption and spectral slope anomalies are tightly coupled to changes in atmospheric and oceanographic conditions associated with El Niño Southern Oscillation (ENSO), strongly covary with the multivariate ENSO index in a large region of the tropical Pacific, and provide insights into the potential evolution and feedbacks related to sea surface dissolved carbon in a warming climate. Further validation of the DOC algorithm developed here is warranted to better characterize its limitations, particularly in mid-ocean gyres and the southern oceans.

Dissolved organic carbon↗

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Comparison↗

Regional to Global Assessments of Phytoplankton Dynamics From The SeaWiFS Mission

Photosynthetic production of organic matter by microscopic oceanic phytoplankton fuels ocean ecosystems and contributes roughly half of the Earth's net primary production. For 13 years, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission provided the first consistent, synoptic observations of global ocean ecosystems. Changes in the surface chlorophyll concentration, the primary biological property retrieved from SeaWiFS, have traditionally been used as a metric for phytoplankton abundance and its distribution largely reflects patterns in vertical nutrient transport. On regional to global scales, chlorophyll concentrations covary with sea surface temperature (SST) because SST changes reflect light and nutrient conditions. However, the oceanmay be too complex to be well characterized using a single index such as the chlorophyll concentration. A semi-analytical bio-optical algorithm is used to help interpret regional to global SeaWiFS chlorophyll observations from using three independent, well-validated ocean color data products; the chlorophyll a concentration, absorption by CDM and particulate backscattering. First, we show that observed long-term, global-scale trends in standard chlorophyll retrievals are likely compromised by coincident changes in CDM. Second, we partition the chlorophyll signal into a component due to phytoplankton biomass changes and a component caused by physiological adjustments in intracellular chlorophyll concentrations to changes in mixed layer light levels. We show that biomass changes dominate chlorophyll signals for the high latitude seas and where persistent vertical upwelling is known to occur, while physiological processes dominate chlorophyll variability over much of the tropical and subtropical oceans. The SeaWiFS data set demonstrates complexity in the interpretation of changes in regional to global phytoplankton distributions and illustrates limitations for the assessment of phytoplankton dynamics using chlorophyll retrievals alone.

phytoplankton↗

ALSSAT Development Status

The development of the Advanced Life Support (ALS) Sizing Analysis Tool (ALSSAT) using Microsoft(Registered TradeMark) Excel was initiated by the Crew and Thermal Systems Division (CTSD) of Johnson Space Center (JSC) in 1997 to support the ALS and Exploration Offices in Environmental Control and Life Support System (ECLSS) design and studies. It aids the user in performing detailed sizing of the ECLSS for different combinations of the Exploration Life support (ELS) regenerative system technologies. This analysis tool will assist the user in performing ECLSS preliminary design and trade studies as well as system optimization efficiently and economically. The latest ALSSAT related publication in ICES 2004 detailed ALSSAT s development status including the completion of all six ELS Subsystems (ELSS), namely, the Air Management Subsystem, the Biomass Subsystem, the Food Management Subsystem, the Solid Waste Management Subsystem, the Water Management Subsystem, and the Thermal Control Subsystem and two external interfaces, including the Extravehicular Activity and the Human Accommodations. Since 2004, many more regenerative technologies in the ELSS were implemented into ALSSAT. ALSSAT has also been used for the ELS Research and Technology Development Metric Calculation for FY02 thru FY06. It was also used to conduct the Lunar Outpost Metric calculation for FY08 and was integrated as part of a Habitat Model developed at Langley Research Center to support the Constellation program. This paper will give an update on the analysis tool s current development status as well as present the analytical results of one of the trade studies that was performed.

Yeh, H. Y. Jannivine↗

Alssat Development Status and Its Applications in Trade Studies

The development of the Advanced Life Support (ALS) Sizing Analysis Tool (ALSSAT) using Microsoft® Excel was initiated by the Crew and Thermal Systems Division (CTSD) of Johnson Space Center (JSC) in 1997 to support the ALS and Exploration Offices in Environmental Control and Life Support System (ECLSS) design and studies. It aids the user in performing detailed sizing of the ECLSS based on suggested default values or user inputs for different combinations of the ALS regenerative system technologies (Ref. 1, 2). This analysis tool will assist the user in performing ECLSS preliminary design and trade studies as well as system optimization efficiently and economically. Since ALSSAT's latest publication in ICES 2001 (Ref. 1) describing the development of ALSSAT with its Air Revitalization Subsystem (ARS), Water Management Subsystem (WMS), and Biomass Subsystem (Biomass) mass balance sheets, ALSSAT has been expanded to include mass balance and sizing models for the remaining three ALS subsystems, namely, the Solid Waste Management Subsystem (SWMS), the Food Management Subsystem (FMS), and the Thermal Control Subsystem (TCS). The external interfaces, including the Extravehicular Activities (EVA) and Human Accommodations (HA), were implemented into ALSSAT in 2002. The overall mass balance sheet, which integrates the six ALS subsystems and the external interfaces applicable to the ECLSS, was also developed. In 2003, ALSSAT was upgraded to include the consideration of redundancy and contingency options in the ECLSS, as well as more ALS regenerative technology selections. ALSSAT has been used for the Metric Calculation for FY02 and FY03 (Ref. 3). Several trade studies were conducted in 2003. The analytical results will be presented in this paper.

Yeh, H. Y. (Jannivine)↗

Biomarkers Detection With the Autonomous and Remotely Operated SOLID-LDChip Instrument in A Mars Drilling Simulating Campaign

One of the main goals in Mars exploration is to determine whether life has ever existed on the red planet. To achieve this goal, it is important to verify the performance, robustness, and maturity of instrumentation devoted to life detection, for example through field-testing in Mars analog environments.The Atacama Desert is considered one of the best terrestrial analogs of the surface of Mars due to abrupt temperature shifts, dryness, high UV radiation, and extremely low biomass. This, together with the lack of vegetation and the geochemistry of the regolith, make it an ideal scenario for testing instrumentation, performance, and concepts of operations. The Atacama Rover Astrobiology Drilling Studies (ARADS) is a NASA PSTAR project conceived for maturing and testing life-detection instrumentation in the Atacama Desert(1). The project is based on the K-REX2 rover equipped with a robotic 1-meter arm that delivers samples toon board instruments. This includes SOLID3.1 (Signs of Life Detector), designed as a life-detection instrument for finding complex organic molecules by means of the LDCHip (Life Detector Chip), an antibody microarray sensor(2). The instrument can extract organic compounds from soil, rocks, and sediments into a liquid solvent in the extraction cell (EC), allowing the search for hundreds of microbial molecular biomarkers at once (3). The robustness and reliability of SOLID were tested in the 2019 ARADS Mars drilling simulating campaign and confirmed with other analytical methods.

M Moreno-Paz↗

The Terrestrial Organism and Biogeochemistry Spatial Sampling Design for the National Ecological Observatory Network

The National Ecological Observatory Network (NEON) seeks to facilitate ecological prediction at a continental scale by measuring processes that drive change and responses at sites across the United States for thirty years. The spatial distribution of observations of terrestrial organisms and soil within NEON sites is determined according to a “design‐based” sample design that relies on the randomization of sampling locations. Development of the sample design was guided by high‐level NEON objectives and the multitude of data products that will be subjected to numerous analytical approaches to address the causes and consequences of ecological change. A requirement framework permeates the NEON design, ensuring traceability from each facet of the design to the high‐level requirements that make the NEON mission statement actionable. Requirements were developed for the terrestrial sample design to guide the key components of the design: Randomizing the sample locations ensures the unbiased collection of data, is appropriate for organisms and soil, and provides data suitable for a variety of analyses. Stratification increases efficiency and allows sampling to focus on those parts of the landscape measured by other NEON observation platforms. Attention to the sample size and spatial plot allocation ensures that data products will be sufficient to inform questions asked of the data and the NEON objectives. Establishing a framework with the capacity for re‐evaluate and design iteration allows for adaption to unexpected challenges and optimization of the sample design based on early data returns. The utility of the NEON sampling design is highlighted by its application across terrestrial systems. The data generated from this unique design will be used to quantify patterns in: the abundance and diversity of small mammals, breeding birds, insects, and soil microbes; vegetation structure, biomass, productivity, and diversity; and soil biogeochemistry.

National Ecological Observatory Network↗

Retrieval of Vegetation Water Content Using Brightness Temperatures from the Soil Moisture Active Passive (SMAP) Mission

In this paper, we explore a time series approach to using the tau-omega (τ-ω) model to retrieve vegetation water content (kg/m2) with minimal use of ancillary data. Analytically, this approach calls for nonlinear optimization in two steps. First, multiple days of co-located brightness temperature observations are used to retrieve the effective vegetation opacity, which incorporates the combined radiometric and polarization effects of surface roughness and vegetation opacity. The resulting effective vegetation opacity is then used to retrieve vegetation water content to within a gain factor α and an offset factor β. By using a climatological vegetation water content ancillary database as the one adopted in the development of the SMAP standard and enhanced soil moisture products, α and β can be determined globally using the annual minimum and annual maximum of vegetation water content. The resulting values of α and β can then be used to reconstruct the retrieved vegetation water content. Formulation, assumptions, and limitations of this approach are presented alongside the preliminary global retrieval of vegetation water content using one year (2016) ofSMAP brightness temperature observations.

radiative transfer↗