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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Iron mineral dissolution releases iron and associated organic carbon during permafrost thaw

It has been shown that reactive soil minerals, specifically iron(III) (oxyhydr)oxides, can trap organic carbon in soils overlying intact permafrost, and may limit carbon mobilization and degradation as it is observed in other environments. However, the use of iron(III)-bearing minerals as terminal electron acceptors in permafrost environments, and thus their stability and capacity to prevent carbon mobilization during permafrost thaw, is poorly understood. We have followed the dynamic interactions between iron and carbon using a space-for-time approach across a thaw gradient in Abisko (Sweden), where wetlands are expanding rapidly due to permafrost thaw. We show through bulk (selective extractions, EXAFS) and nanoscale analysis (correlative SEM and nanoSIMS) that organic carbon is bound to reactive Fe primarily in the transition between organic and mineral horizons in palsa underlain by intact permafrost (41.8 ±10.8 mg carbon per g soil, 9.9 to 14.8% of total soil organic carbon). During permafrost thaw, water-logging and O 2 limitation lead to reducing conditions and an increase in abundance of Fe(III)-reducing bacteria which favor mineral dissolution and drive mobilization of both iron and carbon along the thaw gradient. By providing a terminal electron acceptor, this rusty carbon sink is effectively destroyed along the thaw gradient and cannot prevent carbon release with thaw.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Intensive agricultural management‐induced subsurface accumulation of labile phosphorus in Midwestern agricultural soils dominated by tile lines

Abstract In addition to surface runoff, subsurface P loss through tile lines in agricultural lands has received attention over the last decade. It is not clearly understood how this strong ligand, phosphate, is distributed in subsoils (≤180 cm), contributing to subsurface P loss. We hypothesized that subsurface accumulation of labile P as a result of long‐term intensive agricultural management contributes to subsurface P loss. The depth sequence distribution of P and its speciation and reactivity were investigated in tile‐line‐dominated Midwestern agricultural fields via chemical extraction and digestion, batch desorption experiments, and X‐ray absorption near‐edge structure spectroscopy. The results suggest that labile P in subsoils exceeds the eutrophication‐inducing level (>0.01 mg L –1 ). Because of intensive agricultural management, total P was ∼400 mg kg –1 in surface soils and ∼200‐300 mg kg –1 in subsoils. The depth sequence distribution of P indicated the translocation of P to subsoils. Although phosphate and phytic acid adsorbed by Al or Fe (oxyhydro)oxides and calcite were found in surface soils, phosphate adsorbed to calcite, hydroxyapatite, or both were the dominant P species in subsoils. Phosphate was highest in surface soils and decreased sharply with increasing depth. Slightly alkaline soil in subsoils suppressed the release of P but the process was continuous after 30 d. Subsurface P loss was influenced by the dissolution and desorption process of inorganic P phases and preferentially transported P from surface soils. Subsurface P loss should be considered in strategies to reduce agricultural P loss in the Gulf of Mexico.

Xu, Suwei↗
NASA NTRS1975

Separation of man-made and natural patterns in high-altitude imagery of agricultural areas

A nonstationary linear digital filter is designed and implemented which extracts the natural features from high-altitude imagery of agricultural areas. Essentially, from an original image a new image is created which displays information related to soil properties, drainage patterns, crop disease, and other natural phenomena, and contains no information about crop type or row spacing. A model is developed to express the recorded brightness in a narrow-band image in terms of man-made and natural contributions and which describes statistically the spatial properties of each. The form of the minimum mean-square error linear filter for estimation of the natural component of the scene is derived and a suboptimal filter is implemented. Nonstationarity of the two-dimensional random processes contained in the model requires a unique technique for deriving the optimum filter. Finally, the filter depends on knowledge of field boundaries. An algorithm for boundary location is proposed, discussed, and implemented.

Samulon, A. S.↗
NASA NTRS2004

Detecting Organic Compounds in Martian Soil Analogues Using Gas Chromatography Mass Spectrometry

One of the primary objectives of the 1976 Viking missions was to determine whether organic compounds, possibly of biological origin, were present in the Martian surface soils. The Viking gas chromatography mass spectrometry (GCMS) instruments found no evidence for any organic compounds of Martian origin above a few parts per billion in the upper 10 cm of surface soil [l], suggesting the absence of a widely distributed Martian biota. However, Benner et d. have suggested that significant amounts of non-volatile organic compounds, possibly including oxidation products of bioorganic molecules (e.g. carboxylic acids) would not have been detected by the Viking GCMS [2]. Moreover, other key organic compounds important to biology, such as amino acids and nucleobases, would also likely have been missed by the Viking GCMS as these compounds require chemical derivatization to be stable in a GC column [3]. Recent pyrolysis experiments with a Mars soil analogue that had been innoculated with Escherichia coli bacteria have shown that amino acid decomposition products (amines) and nucleobases are among the most abundant products generated after pyrolysis of the bacterial cells [4,5]. At the part per billion level (Viking GCMS detection limit), these pyrolysis products generated from several million bacterial cells per gram of Martian soil would not have been detected by the Viking GCMS instruments [4]. Analytical protocols are under development for upcoming in situ lander opportunities to target several important biological compounds including amino acids and nucleobases. For example, extraction and chemical derivatization techniques [3] are being adapted for space flight use to transform reactive or fragile molecules that would not have been detected by the Viking GCMS instruments, into species that are sufficiently volatile to be detected by GCMS. Recent experiments carried out at NASA Goddard have shown that using this derivatization technique all of the targeted compounds mentioned above can be separated on a GC column and detected by MS at sub-picomole (< 10(exp -l2 mole) levels. With these methods, the detection limit for amino acids, carboxylic acids and nucleobases is several orders of magnitude more sensitive than the Viking GCMS instruments for these compounds. Preliminary results using this analytical technique on a variety of Martian soil analogues will be presented.

Glavin, D. P.↗
DOE OSTI2022

Environmental controls on the light use efficiency of terrestrial gross primary production

Abstract Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf‐level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy‐level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C 3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed‐effects model. The same model design was fitted to site‐based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU)processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RAS-SOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar sur-face, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensing. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensory. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
DOE OSTI2026

Synchrotron resolved microscale mineralogy and elemental composition of individual plinthic and manganiferous nodules from agricultural soils

Iron and manganese oxides are strong sorbents and elemental scavengers in the environment that can form macroscopic nodules in soils. Despite their importance in the geochemical cycling of nutrients and contaminants, nodules are rarely characterized. When analyzed, they are often combined into bulk samples, obscuring individual characteristics. This study investigates the composition and mineralogy of individual plinthic and manganiferous nodules in soil from cropping systems in the Farming Systems Project in Beltsville, Maryland. Elemental composition indicates the accumulation of contaminants and nutrients, including copper in all nodules and high levels of phosphorus in select nodules. Sequential extractions determine that highly crystalline minerals comprise the nodules, locking away these nutrients and contaminants. Bulk X-ray diffraction (XRD) demonstrated distinct mineralogies in the plinthic and manganiferous nodules, with the former comprised of quartz, goethite, and kaolinite, and the latter consisting of quartz, Mn 2 O 3 , and hematite. Synchrotron and laboratory-based X-ray fluorescence (XRF) mapping gives critical insight into the elemental distribution within the nodules and elucidates spatial elemental associations, including the coupling of manganese and iron in the manganiferous nodules. XRF maps paired with µXRD provide microscale spatial resolution in mineralogy, which resolved several phases not apparent in bulk XRD, manganese’s association with goethite, and minerals indicative of redox transformations, including magnetite and maghemite. These novel results provide critical insight into the microscale mineralogy and individual elemental composition of plinthic and manganiferous nodules, as well as how they alter bulk soil geochemistry in ways largely unaccounted for in research on soil systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs

This submission aimed to assess differences in short-term step warming manipulations and long-term chronic response to climate change in Alaskan ecosystems. Briefly, climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.The model used in the current study is available publicly (https://github.com/jinyun1tang/ECOSYS), and the current submission contains the python/ matlab codes for analyzing output from the model (includng a readme file to explain the codes). The benchmark data, also enclosed, was collected from a range of published and publicly available sources (extracted using GRABIT: https://www.mathworks.com/matlabcentral/fileexchange/7173-grabit). These sources describe warming induced changes in tundra/ boreal ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Pigmenting agents in Martian soils: inferences from spectral, Mossbauer, and magnetic properties of nanophase and other iron oxides in Hawaiian palagonitic soil PN-9

We have examined a Hawaiian palagonitic tephra sample (PN-9) that has spectroscopic similarities to Martian bright regions using a number of analytical techniques, including Mossbauer and reflectance spectroscopy, X-ray diffraction, instrumental neutron activation analysis, electron probe microanalysis, transmission electron microscopy, and dithionite-citrate-bicarbonate extraction. Chemically, PN-9 has a Hawaiitic composition with alkali (and presumably silica) loss resulting from leaching by meteoric water during palagonitization; no Ce anomaly is present in the REE pattern. Mineralogically, our results show that nanophase ferric oxide (np-Ox) particles (either nanophase hematite (np-Hm) or a mixture of ferrihydrite and np-Hm) are responsible for the distinctive ferric doublet and visible-wavelength ferric absorption edge observed in Mossbauer and reflectivity spectra, respectively, for this and other spectrally similar palagonitic samples. The np-Ox particles appear to be imbedded in a hydrated aluminosilicate matrix material; no evidence was found for phyllosilicates. Other iron-bearing phases observed are titanomagnetite, which accounts for the magnetic nature of the sample; olivine; pyroxene; and glass. By analogy, np-Ox is likely the primary pigmenting agent of the bright soils and dust of Mars.

Minerals/analysis↗
NASA NTRS1996

On the Capabilities of Using AIRSAR Data in Surface Energy/Water Balance Studies

The capabilities of using remote sensing data, and in particular multifrequency/multipolarization SAR data, like AIRSAR, for the retrieval of surface parameters, depend considerably on the specificity of each application. The potentials, and limitations, of SAR data in ecological investigations are well known. Because the chemistry is a major component in such studies and because of the almost lacking chemical information at the wavelengths of SAR data, the capabilities of using SAR-derived information in such studies are considerably limited. However, in the case of surface energy/water balance studies, the determination of the amount of water content, both in the soil and in the plants, is a major component in all modeling approaches. As the information about water content is present in the SAR signal, then the role of SAR data in studies where water content is to be determined becomes clearly predominant. Another situation where the role of SAR data becomes dominant over other remote sensing systems is the case of dense canopies. Because of the penetration capabilities of microwave data, which is especially superior as compared to optical data, information about the canopy as a whole and even the underlying soil is contained in the SAR data, while only the top canopy provides the information content in the case of optical data. In the case of relatively dense canopies, as has been demonstrated in this study, such different penetration capabilities provide very different results in terms of the derived total canopy water content, for instance. However, although all such capabilities are well known, unfortunately there are also well known limitations. Apart from calibration-related aspects (that we will not consider in this study), and apart from other intrinsic problems (like image noise, topographic corrections, etc.) which also significantly affect the derived results, we will concentrate on the problem of extracting information from the data. Even at this level, methods are still not fully well established, especially over vegetation-covered areas. In this paper, an algorithm is described which allows derivation of three fundamental parameters from SAR data: soil moisture, soil roughness and canopy water content, accounting for the effects of vegetation cover by using optical (Landsat) data as auxiliary. Capabilities and limitations of the data and algorithms are discussed, as well as possibilities to use these data in energy/water balance modeling studies. All the data used in this study were acquired as part of the Intensive Observation Period in June-July 1991 (European Multisensor Aircraft Campaign-91), as part of the European Field Experiment in a Desertification- threatened Area (EFEDA), a European contribution to the global-change research sponsored by the IGBP program (Bolle et al., 1993).

Moreno, Jose F.↗
NASA NTRS2008

Exploration of the Habitability of Mars with the SAM Suite Investigation on the 2009 Mars Science Laboratory

The 2009 Mars Science Laboratory (MSL) with a substantially larger payload capability that any other Mars rover, to date, is designed to quantitatively assess a local region on Mars as a potential habitat for present or past life. Its goals are (1) to assess past or present biological potential of a target environment, (2) to characterize geology and geochemistry at the MSL landing site, and (3) to investigate planetary processes that influence habitability. The Sample Analysis at Mars (SAM) Suite, in its final stages of integration and test, enables a sensitive search for organic molecules and chemical and isotopic analysis of martian volatiles. MSL contact and remote surface and subsurface survey Instruments establish context for these measurements and facilitate sample identification and selection. The SAM instruments are a gas chromatograph (GC), a mass spectrometer (MS), and a tunable laser spectrometer (TLS). These together with supporting sample manipulation and gas processing devices are designed to analyze either the atmospheric composition or gases extracted from solid phase samples such as rocks and fines. For example, one of the core SAM experiment sequences heats a small powdered sample of a Mars rock or soil from ambient to -1300 K in a controlled manner while continuously monitoring evolved gases. This is followed by GCMS analysis of released organics. The general chemical survey is complemented by a specific search for molecular classes that may be relevant to life including atmospheric methane and its carbon isotope with the TLS and biomarkers with the GCMS.

Mahaffy, P. R.↗
NASA NTRS1990

Availability of hydrogen for lunar base activities

Hydrogen will be needed on a lunar base to make water for consumables, to provide fuel, and to serve as reducing agent in the extraction of oxygen from lunar minerals. The abundance and distribution of solar wind implanted hydrogen were studied. Hydrogen was found in all samples studied with concentrations varying widely depending on soil maturity, grain size, and mineral composition. Seven cores returned from the moon were studied. Although hydrogen was implanted in the upper surface layer of the regolith, it was found throughout the cores due to micrometeorite reworking of the soil.

Bustin, Roberta↗
NASA NTRS1997

Passive Microwave Observation of Diurnal Surface Soil Moisture

Microwave radiometers operating at low frequencies are sensitive to surface soil moisture changes. Few studies have been conducted that have involved multifrequency observations at frequencies low enough to measure a significant soil depth and not be attenuated by the vegetation cover. Another unexplored aspect of microwave observations at low frequencies has been the impact of diurnal variations of the soil moisture and temperature on brightness temperature. In this investigation, observations were made using a dual frequency radiometer (1.4 and 2.65 GHz) over bare soil and corn for extended periods in 1994. Comparisons of emissivity and volumetric soil moisture at four depths for bare soils showed that there was a clear correspondence between the 1 cm soil moisture and the 2.65-GHz emissivity and between the 3-5 cm soil moisture and the 1.4-GHZ emissivity, which confirms previous studies. Observations during drying and rainfall demonstrate that new and unique information for hydrologic and energy balance studies can be extracted from these data.

Jackson, Thomas J.↗
NASA NTRS2003

Software for a GPS-Reflection Remote-Sensing System

A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

Lowe, Stephen↗
NASA NTRS1974

Geologic information from satellite images

The author has identified the following significant results. Extracting geologic information from ERTS and Skylab/EREP images is best done by a geologist trained in photointerpretation. The information is at a regional scale, and three basic types are available: rock and soil, geologic structures, and landforms. Discrimination between alluvium and sedimentary or crystalline bedrock, and between units in thick sedimentary sequences is best, primarily because of topographic expression and vegetation differences. Discrimination between crystalline rock types is poor. Folds and fractures are the best displayed geologic features. They are recognizable by topographic expression, drainage patterns, and rock or vegetation tonal patterns. Landforms are easily discriminated by their familar shapes and patterns. It is possible to optimize the scale, format, spectral bands, conditions of acquisition, and sensor systems for best geologic interpretation. Several examples demonstrate the applicability of satellite images to tectonic analysis and petroleum and mineral exploration.

Lee, K.↗
NASA NTRS1991

NASA 1990 Multisensor Airborne Campaigns (MACs) for ecosystem and watershed studies

The Multisensor Airborne Campaign (MAC) focus within NASA's former Land Processes research program was conceived to achieve the following objectives: to acquire relatively complete, multisensor data sets for well-studied field sites, to add a strong remote sensing science component to ecology-, hydrology-, and geology-oriented field projects, to create a research environment that promotes strong interactions among scientists within the program, and to more efficiently utilize and compete for the NASA fleet of remote sensing aircraft. Four new MAC's were conducted in 1990: the Oregon Transect Ecosystem Research (OTTER) project along an east-west transect through central Oregon, the Forest Ecosystem Dynamics (FED) project at the Northern Experimental Forest in Howland, Maine, the MACHYDRO project in the Mahantango Creek watershed in central Pennsylvania, and the Walnut Gulch project near Tombstone, Arizona. The OTTER project is testing a model that estimates the major fluxes of carbon, nitrogen, and water through temperate coniferous forest ecosystems. The focus in the project is on short time-scale (days-year) variations in ecosystem function. The FED project is concerned with modeling vegetation changes of forest ecosystems using remotely sensed observations to extract biophysical properties of forest canopies. The focus in this project is on long time-scale (decades to millenia) changes in ecosystem structure. The MACHYDRO project is studying the role of soil moisture and its regulating effects on hydrologic processes. The focus of the study is to delineate soil moisture differences within a basin and their changes with respect to evapotranspiration, rainfall, and streamflow. The Walnut Gulch project is focused on the effects of soil moisture in the energy and water balance of arid and semiarid ecosystems and their feedbacks to the atmosphere via thermal forcing.

Wickland, Diane E.↗