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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Soil porous microstructure control over soil organic matter mobility: A multimethod workflow for understanding chemistry-dependent organic matter binding in soil

Soil organic matter (SOM) has attracted a great deal of interest; particularly for its potential to mitigate human derived CO 2 emissions. Studies have demonstrated that SOM plays a critical role in carbon storage and CO 2 sequestration. However, the sorption properties of SOM, which influence its transport in pore water and stabilization within the soil, remain poorly understood. This study develops a workflow to: (1) examine compound-specific advective and diffusive transport and desorption behaviors, (2) quantify desorption rates through stop-flow and continuous-flow column experiments, and (3) evaluate the impact of soil microporosity on SOM mobility using high-resolution imaging and extractions. Intact core column experiments were conducted on Uncultivated (Natural) and Cultivated soil samples, both were arid soils, collected in Washington State. X-ray computed tomography was employed to measure porosity and pore connectivity, while Fourier-transform ion cyclotron resonance mass spectrometry was used to analyze SOM composition. The findings revealed that cultivation increased total carbon and nitrogen levels due to irrigation and fertilization, enhancing carbon capture potential in arid soils. In contrast, the Natural soil, characterized by higher porosity and connectivity, contained more oxidized carbon. Pore network analysis indicated that soil compaction in the Cultivated soil may lead to longer diffusion pathways, significantly influencing SOM transport and stability.

Hydraulic Properties↗
NASA NTRS1979

Microwave backscatter dependence on surface roughness, soil moisture, and soil texture. II - Vegetation-covered soil

Results are presented for an experimental investigation to determine the relationship between radar backscatter coefficient (sigma) and soil moisture for vegetation-covered soil. These results extend a previous report which showed the experimental relationship between sigma and soil moisture for bare soil. It is shown that the highest correlation between sigma and soil moisture is 0.92 for the combined response of four crop types measured at 4.25 GHz, 10 deg incidence angle, and HH polarization. Radar look direction, relative to the crop row direction, is shown to have an insignificant effect on soil-moisture estimation if the radar frequency is higher than 4 GHz. The dependence on soil type can be minimized by expressing soil moisture in units of percent of field capacity. The possibility of using a single radar for measuring soil moisture for both bare and vegetated fields is demonstrated with a linear estimation algorithm having an experimental correlation coefficinet of 0.8.

Ulaby, F. T.↗
NASA NTRS2000

Interactive Soil Dust Aerosol Model in the GISS GCM: Sensitivity of the Soil Dust Cycle to Radiative Properties of Soil Dust Aerosols - Part 1

The sensitivity of the soil dust aerosol cycle to the radiative forcing by soil dust aerosols is studied. Four experiments with the NASA/GISS atmospheric general circulation model, which includes a soil dust aerosol model, are compared, all using a prescribed climatological sea surface temperature as lower boundary condition. In one experiment, dust is included as dynamic tracer only (without interacting with radiation), whereas dust interacts with radiation in the other simulations. Although the single scattering albedo of dust particles is prescribed to be globally uniform in the experiments with radiatively active dust, a different single scattering albedo is used in those experiments to estimate whether regional variations in dust optical properties, corresponding to variations in mineralogical composition among different source regions, are important for the soil dust cycle and the climate state. On a global scale, the radiative forcing by dust generally causes a reduction in the atmospheric dust load corresponding to a decreased dust source flux. That is, there is a negative feedback in the climate system due to the radiative effect of dust. The dust source flux and its changes were analyzed in more detail for the main dust source regions. This analysis shows that the reduction varies both with the season and with the single scattering albedo of the dust particles. By examining the correlation with the surface wind, it was found that the dust emission from the Saharan/Sahelian source region and from the Arabian peninsula, along with the sensitivity of the emission to the single scattering albedo of dust particles, are related to large scale circulation patterns, in particular to the trade winds during Northern Hemisphere winter and to the Indian monsoon circulation during summer. In the other regions, such relations to the large scale circulation were not found. There, the dependence of dust deflation to radiative forcing by dust particles is probably dominated by physical processes with short time scales. The experiments show that dust radiative forcing can lead to significant changes both in the soil dust cycle and in the climate state. To estimate dust concentration and radiative forcing by dust more accurately, dust size distributions and dust single scattering albedo in the model should be a function of the source region, because dust concentration and climate response to dust radiative forcing are sensitive to dust radiative parameters.

Perlwitz, Jan↗
DOE OSTI2026

Effects of 9.5 Years of Whole-Soil Warming on the Fatty Acid and n-Alkanes Composition in Bulk Soil and Density Fractions at Blodgett Experimental Forest, California, USA

Original data of molecular data (fatty acids and n-alkanes) including concentrations and calculated molecular proxies in a whole-soil warming experiment at the Blodgett Forest Research Station after 9.5 years of warming. The study site has a Mediterranean climate with annual average temperature of 12.5 ℃ and annual average precipitation of 1774 mm. The study site is characterized by a mesic Ultic Alfisol formed from granitic parent material, corresponding to a Dystric Cambisol under the World Reference Base for Soil Resources (WRB) classification system. Experimental warming is applied throughout the soil profile to a depth of 1 m using vertically embedded heating cables that raise soil temperature by 4 °C relative to ambient conditions. Soil samples were collected on 1 May 2023, after the experiment had been operating continuously for about 9.5 years since its initiation in January 2014.The data has been processed from raw data and cross-validated by other peers. The dataset includes: - Bulk_Fattyacid_9.5-year_Soil_Warming_Blodgett, California, USA: fatty acid concentrations and proxies including Carbon Preference Index (CPI) and Average Chain Length (ACL) of bulk soil organic carbon; - Fractions_Fattyacid_9.5-year_Soil_Warming_Blodgett, California, USA: fatty acid concentrations and proxies including CPI and ACL of free particulate organic matter (fPOM) and mineral-associated organic matter (MAOM); - Bulk_Alkanes_9.5-year_Soil_Warming_Blodgett, California, USA: n-alkanes concentrations and proxies including CPI and ACL of bulk soil organic carbon; - Fractions_Alkanes_9.5-year_Soil_Warming_Blodgett, California, USA: n-alkanes concentrations and proxies including CPI and ACL of fPOM and MAOM; - n-Alkanes_All_Monomer_Concentration_9.5-year_Soil_Warming_Blodgett, California, USA: concentration of all the n-alkane monomers identified and integrated for bulk soil, fPOM and MAOM; - Fattyacid_All_Monomer_Concentration_9.5-year_Soil_Warming_Blodgett, California, USA: concentration of all the fatty acid monomers including diacids identified and integrated for bulk soil, fPOM, and MAOM. All data are provided in CSV format and can be viewed using Microsoft Excel. We specifically look at fatty acids (FA) and n-alkanes in bulk soil, fPOM and MAOM and calculated molecular proxies such as CPI and ACL to understand the source of oragnic carbon (with ACL) and degree of decomposition (CPI) of each soil fraction. Due to lack of long-chain fatty acids (carbon number ⩾ 20), microorganism-derived organic carbon is characterized by shorter ACL in comparison to plant-derived organic carbon. Fresh SOC is characterized by even-over-odd dominance for fatty acids and odd-over-even dominance for n-alkanes. Therefore, CPI indicates whether soil organic carbon (SOC) represents fresh input (CPI > 10) or is strongly decomposed (close to 1). The research questions should be then, after 9.5-year warming: 1. whether the relative contribution between microorganism-derived and plant-derived SOC in each soil fraction? 2. whether fPOM became more decomposed whereas MAOM remained relatively persistent in each soil fraction across the soil depth?

Carbon↗
DOE OSTI2026

Data for Impacts of Legacy and Contemporary Nitrogen Inputs on N2O and CO2 Emissions in Miscanthus and Maize Cultivated Soils

Nutrient inputs influence the sustainability of bioenergy crop production through contemporary (shortly after addition) and legacy effects (persisting over years) on microbial nitrogen (N) and carbon cycling, which contribute to greenhouse gas emissions. However, the relative importance of contemporary and legacy effects and how that could vary by crop functional types is poorly understood. Considering its rhizomatous roots and perennial growth, we hypothesized that Miscanthus × giganteu s ( M × g ) would be more sensitive to legacy N fertilization and the historical context of its environment than an annual crop like maize. To test this hypothesis, we examined the effects of legacy and contemporary N inputs on nitrous oxide (N2O) and carbon dioxide (CO2) emissions, as well as key N cycling genes in soils where M × g and maize were grown. A 150-day soil incubation experiment was conducted using soils from a long-term M × g and maize fertility experiment with three historic N fertilization rates (0, 112, and 336 kg N ha−1 year−1) and a contemporary amendment (60 mg N kg−1) with negative control (0 mg N kg−1). We observed significant increases in cumulative N2O emissions in M × g soils relative to maize soils, particularly at higher legacy fertilization rates, while contemporary N had no significant effect. Bacterial amoA gene abundance, which plays a significant role in nitrification in nutrient-rich soils, also increased with higher legacy fertilization rates in M × g soils but was unaffected by the contemporary N. In maize soils, legacy and contemporary N did not significantly affect N2O emissions, but cumulative CO2 emissions and amoA gene abundance significantly increased. The abundances of norB genes were not significantly influenced by either legacy fertilization or contemporary N amendments in either soil. Our findings demonstrate the greater importance of fertilization history over contemporary N in mediating soil N2O emissions, particularly for perennial bioenergy crops.

Carbon↗
DOE OSTI2026

Soil Characterizations of Five Urban Sites in Knoxville, Tennessee. 2024-2025

This dataset includes soil characterizations from five urban parks in Knoxville, Tennessee, USA: Cumberland Estates Park (CEP), Socially Equal Energy Efficient Development (SEED), West View Park (WVP), Victor Ashe Park (VAP), and West Hills Park (WHP). The dataset consists of seven CSV files reporting the data from the measurements of gravimetric moisture content, pH, total carbon and nitrogen, soil texture, dissolved organic carbon and nitrogen, and microbial biomass carbon and nitrogen derived from these soil cores. During five separate sampling events conducted in 2024 and 2025, five soil cores were collected at each site within 3 meters of the remote soil monitoring equipment. In 2025, an additional three soil cores were collected adjacent to the monitoring equipment at each site to assess soil bulk density. This dataset is part of a larger study investigating the effects of soil moisture and plant evapotranspiration on ambient temperature and relative humidity across multiple urban parks in Knoxville, Tennessee.

Mayes, Melanie A [ORNL] (ORCID:0000000163689210)↗
DOE OSTI2024

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO2 Fluxes Upon Soil Warming

Abstract Understanding factors influencing carbon effluxes from soils to the atmosphere is important in a world experiencing climatic change. Two important uncertainties related to soil organic carbon (SOC) stock responses to a changing climate are (a) whether soil microbial communities acclimate or adapt to changes in soil temperature and (b) how to represent this process in SOC models. To further explore these issues, we included thermal adaptation of enzyme‐mediated processes in a mechanistic SOC model (ReSOM) using the macromolecular rate theory. Thermal adaptation is defined here to encompass all potential responses of soil microbes and microbial communities following a change in temperature. To assess the effects of thermal adaptation of enzyme‐mediated processes on simulated SOC losses, ReSOM was applied to data collected from a 13‐year soil warming experiment. Results show that a model omitting thermal adaptation of enzyme‐mediated processes substantially overestimates observed CO 2 effluxes during the initial years of soil warming. The bias against observed CO 2 effluxes was lower for models including thermal adaptation of enzyme‐mediated processes. In addition, for a simulated linear 3°C soil warming over 100 years, models including thermal adaptation of enzyme‐mediated processes simulated SOC losses of a factor of three smaller than models omitting this process. As thermal adaptation of microbial community characteristics is generally not included in models simulating feedback between the soil, biosphere and atmosphere, we encourage future studies to assess the potential impact that microbial adaptation has on soil carbon – climate feedback representations in models. Plain Language Summary A major uncertainty in projecting how much soil organic carbon (SOC) will be converted to CO 2 as a consequence of climate change is related to how soil microbes may adapt to increasing soil temperatures. While this “microbial thermal adaptation” has been shown to occur in short‐term lab incubation experiments, its effect on SOC cycling on a decadal timescale is not clear. To address this knowledge gap, a mechanistic SOC model was used to simulate data collected from a 13‐year soil warming experiment, to assess how microbial thermal adaptation affects predicted SOC losses upon soil warming. The model results show that incorporating microbial thermal adaptation into the model led to reduced CO 2 effluxes from the soil to the atmosphere compared to the common approach of omitting this mechanism. Our results imply that projected SOC losses for the decades to come may be reduced when this mechanism is incorporated in land models. We therefore advocate for more research on the mechanisms controlling microbial thermal adaptation, and how to implement this mechanism in SOC models. Key Points A crucial aspect of soil organic carbon (SOC) models is the representation of soil microbes Predicted soil CO 2 fluxes upon soil warming are reduced when accounting for microbial thermal adaptation On a centennial time scale, this thermal adaptation results in up to a factor of three lower predicted SOC loss

Van de Broek, Marijn↗
DOE OSTI2026

How deep is your soil? Quantifying and spatially analyzing understudied deep soil in the United States

Deep soil is largely understudied and important in understanding biogeochemical processes in soil. Here, understudied soil is defined as the difference between soil studied to a known depth and the estimated bedrock depth. To understand more about deep soil, the understudied soil in the US was quantified and spatially analyzed using soil survey data and model estimates of bedrock depth. An equation was derived to find understudied soil using the dataset parameters “max lower depth studied”, “depth to bedrock”, and “likelihood of bedrock in the top 200 cm”. The survey data and bedrock model revealed that soil has been studied to an average depth of 1-2 meters, and the average depth to bedrock is 20 meters. Soil data density in the soil surveys was greatest in the West Coast, Midwest, and areas historically managed for agricultural, while the non-contiguous US and interior West were underrepresented. The soil had been studied deeper than the estimated soil depth in 455 out of 56,889 observation points concentrated in Alaska, California, Texas, Florida, Puerto Rico, and the US Virgin Islands. To understand the diversity and any taxonomic bias of the global soil data available, soil order was compared to US-based National Resource Conservation Service percentages and it was found that Oxisols, Alfisols, Ultisols, Andisols, and Histosols were overrepresented while Gelisols, Aridisols, Vertisols, Entisols, and Spodosols are underrepresented. Soil depth is important in exploring the complexity of biogeochemical processes that take place in soil.

Bedrock↗
DOE OSTI2025

Soil biogeochemical properties and metrics of tree-mycorrhizal dominance for a 25-Ha forest in South Central Indiana, USA.

This data package contains a dataset used in the papers “Seeing the forest for all the trees: Mycorrhizal-associated nutrient economies are modulated by stem density and the synchrony between overstory and understory communities” and “Mycorrhizal associations of tree species influence soil nitrogen dynamics via effects on soil acid–base chemistry”. Four csv files are included along with a dataset. The dataset features chemical soil properties for a single sampling campaign within the 25 Ha Lilly-Dickey Woods Smithsonian Forest Global Earth Observatory (ForestGEO) plot in South Central Indiana, USA (ldw_dat_raw.csv). Also included are separate files focused on pH (pH_data.csv), carbon and nitrogen (CN_data.csv), and nitrification rates (Nitrification_data.csv). These variables are commonly associated with the tree-mycorrhizal dominance of forest stands. In these data subsets, each soil variable was matched to a 10 meter radius neighborhood wherein metrics of tree-mycorrhizal dominance (basal area, stem count, importance value, etc.) were calculated. Models between these soil variables and dominance metrics were used to investigate how different assessments of mycorrhizal associated nutrient economies (MANE) capture these relationships. This research was performed as a part of the Smithsonian ForestGEO project. This data package can be used to explore spatial variability in soil chemistry within a mature hardwood forest, or it can be combined with the included tree data, other fine-scale spatial information, or other tree inventory data for the site to evaluate how soil chemistry varies with tree community composition or edaphic or topographic properties.

Craig, Matthew [ORNL] (ORCID:0000000288907920)↗
NASA NTRS2007

Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals.

Santanello, Joseph A.↗
DOE OSTI2025

Regional-scale soil carbon predictions can be enhanced by transferring global-scale soil–environment relationships

Accurate modelling and mapping soil organic carbon are crucial for supporting soil health restoration and climate change mitigation at both regional and global scales. However, regional soil predictions often suffer from data scarcity and high prediction uncertainty. Utilizing a pre-trained global-to-regional soil carbon predictive model can be a potential solution to address this challenge. Despite its promise, how to construct and apply the global-scale model to enhance regional-scale soil carbon mapping remains largely unexplored. Here, we propose the Global Soil Carbon Pre-trained Model (GSoilCPM), a deep-learning-based domain adaptative model, to enhance regional-scale soil carbon predictions. Based on large amount of environmental covariate data and 106,167 soil samples across the globe, we verify our hypothesis of the effectiveness of this 'global-to-regional' modelling strategy. The pre-trained model can be then transferred and fine-tuned to bridge the regional- and global-scale soil–environment relationships. We applied and validated this modelling strategy in four regional-scale study areas, three in the Northern Hemisphere and one in the Southern Hemisphere, each with distinct environmental background. Compared to traditional modelling approaches as a baseline, four case studies all demonstrated significant improvement in prediction accuracy across diverse environments and varying data availabilities. The average percentage improvement across all regions is 10.93% (absolute values decreased by 1.20 g kg−1 averagely) in MAE and 29.04% (absolute values increased by 0.10 averagely) in CCC. The applicability and future horizons of using GSoilCPM were further discussed. We further reveal that regions with fewer soil samples or lower baseline accuracy benefit more from the pre-trained global model. Our findings highlight the advantages of leveraging the generalized knowledge from global models to enhance specifically localized soil modelling, positioning a potential paradigm shift in digital soil mapping, and far-reaching implications for soil monitoring and land management.

Deep learning↗
NASA NTRS2011

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

Reichle, Rolf H.↗
DOE OSTI2026

Using Artificial Soiling to Rank Anti-Soiling Coatings for Arid Climates

A simple method to evaluate (e.g., screen and rank) the performance of coatings that are fully or partially anti-soiling (AS) is lacking within the PV industry. Artificial soiling may be used as a rapid and economical assessment approach, offering an efficient alternative to time-intensive, site-specific field testing. In this study, we present an artificial soiling method to replicate the anti-soiling performance rankings of two groups of coated glass samples supplied by two manufacturers (group C with CA, CP, and CS coatings; group A with AC coating). These are compared to field aging in two climates: semi-arid Lemoore, California over 4 months, and the hot desert in Mesa, Arizona over 7 months. Both field and indoor performance ranking utilize the transmittance ratio, defined as the optical transmittance between a coated sample and an uncoated reference in each group, as an evaluation metric to assess the effectiveness of the artificial soiling approach in replicating field soiling. It is critical to mimic the dominant field meteorological conditions associated with soiling-prone days and vulnerable times of day during the soiling season. Our results reveal that the use of artificial soiling for field performance ranking among coatings strongly depends on the soil type (composition and particle distribution), dust surface density, and prevalent environmental factors (wetting saturation by humidity, dew condensation extent, and prior weathering history of the coating). The similar rank order relative to the field suggests that the artificial soiling approach presented may be used for down-selecting anti-soiling coatings prior to prolonged field validation.

14 SOLAR ENERGY↗
DOE OSTI2026

Vegetation heterogeneity reflects soil thermal state and surface soil displacement in a thawing permafrost landscape

Thawing permafrost has the potential to dramatically alter the physical and ecological structure of northern landscapes. Warming of the Arctic and subsequent degradation of permafrost have created a need to assess the stability and movement of soils on hillslopes and the potential impacts on ecosystem structure. In this work, we explore the relationships among vegetation heterogeneity, soil temperature, and soil surface displacements observed from 2019 to 2022 in a watershed in the discontinuous permafrost region on the Seward Peninsula of Alaska. Vegetation heterogeneity was measured as the standard deviation (SD) of the normalized difference vegetation index (NDVI) from 3 m PlanetScope satellite imagery around each soil temperature and active layer thickness observation. Locations of observations were clustered into three soil thermal groups, warm, intermediate, and cold, based on soil temperature and active layer thickness. Average annual horizontal surface displacements were significantly lower for soils within the warm thermal group (median = 0.033 m yr −1 ) compared to soils within the cold thermal group (median = 0.090 m yr −1 ; p < 0.001). Conversely, vegetation heterogeneity was significantly higher in the warm (median = 0.014 SD NDVI; p = 0.002) and intermediate (median = 0.015 SD NDVI; p = 0.002) groups compared with the cold thermal group (median = 0.012 SD NDVI), suggesting a warming-induced shift in vegetation community complexity. Because of the observed associations of ground surface displacement rates and vegetation heterogeneity with soil thermal state, we hypothesize that warming soil conditions induce changes in the rates and patterns of hillslope erosion due to an increase in surface movement as near-surface permafrost thaws, followed by a decrease as the permafrost table deepens and excess ice content diminishes. The transition to warm soils promotes surface ecosystem transformation, shifting the dominant vegetation at the site, given the warming climatic conditions of the region. We integrated our observations of soil temperature, vegetation heterogeneity, and soil surface displacements into a conceptual model that describes the co-evolution of hillslopes and vegetation in warming permafrost environments, which is currently unrepresented in earth system models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Effect of soil texture on the microwave emission from soils

The intensity brightness temperature of the microwave emission from the soil is determined primarily by its dielectric properties. The large difference between the dielectric constant of water and that of dry soil produces a strong dependence of the soil's dielectric constant on its moisture content. This dependence is effected by the texture of the soil because the water molecules close to the particle surface are tightly bound and do not contribute significantly to the dielectric properties. Since this surface area is a function of the particle size distribution (soil texture), being larger for clay soils with small particles, and smaller for sandy soils with larger particles; the dielectric properties will depend on soil texture. Laboratory measurements of the dielectric constant for soils are summarized. The dependence of the microwave emission on texture is demonstrated by measurements of brightness temperature from an aircraft platform for a wide range of soil textures. It is concluded that the effect of soil texture differences on the observed values can be normalized by expressing the soil moisture values as a percent field capacity for the soil.

Schmugge, T. J.↗
NASA NTRS1999

Space Weathering in the Fine Size Fractions of Lunar Soils: Soil Maturity Effects

The effects of space weathering on the optical properties of lunar materials have been well documented. These effects include a reddened continuum slope, lowered albedo, and attenuated absorption features in reflectance spectra of lunar soils as compared to finely comminuted rocks from the same Apollo sites. However, the regolith processes that cause these effects are not well known, nor is the petrographic setting of the products of these processes fully understood. A Lunar Soil Characterization Consortium has been formed with the purpose of systematically integrating chemical and mineralogical data with the optical properties of lunar soils. Understanding space-weathering effects is critical in order to fully integrate the lunar sample collection with remotely-sensed data from recent robotic missions (e.g., Lunar Prospector, Clementine, and Galileo) We have shown that depositional processes (condensation of impact-derived vapors, sputter deposits, accreted impact material, e.g., splash glass, spherules, etc.) are a major factor in the modification of the optical surfaces of lunar regolith materials. In mature soils, it is the size and distribution of the nanophase metal in the soil grains that has the major effect on optical properties. In this report, we compare and contrast the space-weathering effects in an immature and a mature soil with similar elemental compositions. For this study, we analyzed <10 micron sieve fractions of two Apollo 17 soils, 79221 (mature, Is/FeO = 81) and 71061 (immature, Is/FeO = 14). Details of the sieving procedures and allocation scheme are given else where. The results of other detailed chemical, mineralogical, and spectroscopic analyses of these soil samples are reported elsewhere. A representative sample of each soil was embedded in low-viscosity epoxy, and thin sections (about 70nm thick) were obtained through ultra microtomy. The thin sections used for these analyses typically contained cross sections of up to 500 individual grains. The thin sections were studied using a JEOL 2010 transmission electron microscope (TEM) equipped with a thin window energy-dispersive X-ray (EDX) spectrometer. An individual thin section was selected from each soil, and for each grain in the section we determined (1) the elemental composition by EDX; (2) whether the grain was crystalline or glassy using electron diffraction and darkfield imaging; (3) the presence or absence of rims and accreted material; and (4) the distribution of nanophase Fe where present. Most of the categories are self-evident; however, we divide the agglutinate derived material into agglutinitic glass (glass with approximately the same composition as the bulk soil that contains nanophase Fe with or without vesicles) and agglutinate fragments, which are composed of crystalline grains and agglutinitic glass. Lithic fragments are defined as polymineralic grains with no glass. Pyroxene grains have been divided into high- and low-Ca groups. As expected, there are a number of differences in the petrography of the <10-microns fractions of 79221 and 71061 given the great difference in their respective maturities, but we focus here on two major distinctions: agglutinate content and the number of grains with micropatina. Slightly over 50% of the particles in 79221 consist of agglutinitic glass and agglutinate fragments, while the remainder are predominantly crystalline mineral grains. The agglutinic glass particles contain abundant nanophase Fe and vesicles. Angular particles are rare, with most showing smooth, rounded exteriors, Of the mineral grains analyzed thus far, over 90% of the grains have amorphous rims that contain nanophase Fe (these rims are believed to have formed by vapor deposition and irradiation effects). The nanophase Fe in these rims probably accounts for a significant fraction of the increase in Is/FeO measured in these size fractions. In addition to the rims, the majority of particles also show abundant accreted material in the form of glass splashes and spherules that also contain nanophase Fe. In stark contrast, the surfaces of the mineral grains in the 71061 sample are relatively prisitine, as only about 14% of the mineral grains in the sample exhibited amorphous rims. Furthermore, the mineral particles are more angular and show greater surface roughness than in the mature sample. Accreted material on particle surfaces is rare. Agglutinitic material is a major component of the 71061 sample; however, nanophase Fe and vesicles are not as well developed as in the 79221 sample. It is now recognized that nanophase Fe is probably the main agent in modifying the optical properties of lunar soil grains. The most important result of this study is the observation that in the fine size fractions of mature soils, nearly every grain has nanophase Fe within 100 run of the particle surface. (Additional Information contained in original)

Keller, L. P.↗
DOE OSTI2026

Composition and persistence of soil organic matter along eroding and depositional transects in buried vs. modern soil layers: A case of the Brady paleosol at Wauneta, Nebraska

Paleosols form when soils are buried through deposition by aeolian, colluvial, alluvial or other processes. Burial of former topsoil isolates soil organic matter (SOM) from surface conditions, allowing carbon to accumulate and potentially remain stable for millennia. In this study, SOM composition, distribution, and persistence were analyzed in the Brady Soil of Nebraska, USA to compare SOM spatial variability in modern and buried soils, as well as the impact of erosional exposure on SOM stability. The Brady Soil, formed as a surface soil during the Pleistocene-Holocene transition and now a paleosol buried up to 6 m deep (or more) by loess deposition during the Holocene, was sampled along burial (up to 5.8 m depth) and erosional (up to 1.8 m depth) transects to compare SOM dynamics in different geomorphic settings. Fourier Transform Infrared Spectroscopy (FTIR) and Fourier Transform ion cyclotron resonance mass spectrometry (FTICR-MS) were used to analyze SOM composition, while δ 13 C isotope analyses identified SOM sources and radiocarbon values were used to estimate turnover rates. Results confirmed a vegetation shift from C3 to C4 plants after Brady Soil formation, reflecting warming climatic conditions. Increasing SOM age and decreasing δ 13 C and δ 15 N values with depth indicated slowing of decomposition rate in buried soils. Higher pH in the Brady Soil suggested greater base cation content, supporting SOM stabilization through organo-mineral associations and aggregate formation. However, exposure of the Brady Soil due to surface erosion caused faster SOM turnover. This result suggested susceptibility of buried SOM to losses via decomposition upon erosional exposure, possibly accelerated by priming in response to modern SOM inputs. These findings highlight the potential loss of carbon stocks in buried soils under future climate change, as shifts in soil physicochemical properties may destabilize long-preserved SOM.

Environmental sciences↗
DOE OSTI2026

Data for Immediate Impacts of Soybean Cover Crop on Bacterial Community Composition and Diversity in Soil Under Long-Term Saccharum Monoculture

Saccharum yield decline results from long-term monoculture practices. Changes in cropping management can improve soil health and productivity. Below-ground bacterial community diversity and composition across soybean (Glycine max (L.) Merr) cover crop, Saccharum monoculture (30+ year) and fallowed soil were determined. Near full length (~1,400 base pairs) of 16S rRNA gene sequences were extracted from the rhizospheres of sugarcane and soybean and fallowed soil were compared. Higher soil bacterial diversity was observed in the soybean cover crop than sugarcane monoculture across all measured indices (observed operationational taxonomic units, Chao1, Shannon, reciprocal Simpson and Jackknife). Acidocateria, Proteobacteria, Bacteroidetes and Planctomycetes were the most abundant bacterial phyla across the treatments. Indicator species analysis identified nine indicator phyla. Planctomycetes, Armatimonadetes and candidate phylum FBP were associated with soybean; Proteobacteria and Firmicutes were linked with sugarcane and Gemmatimonadetes, Nitrospirae, Rokubacteria and unclassified bacteria were associated with fallowed soil. Non-metric multidimensional scaling analysis showed distinct groupings of bacterial operational taxonomic units (97% identity) according to management system (soybean, sugarcane or fallow) indicating compositional differences among treatments. This is confirmed by the results of the multi-response permutation procedures (A = 0.541, p = 0.00045716). No correlation between soil parameters and bacterial community structure was observed according to Mantel test (r = 211865, p = 0.14). Use of soybean cover-crop fostered bacterial diversity and altered community structure. This indicates cover crops could have a restorative effect and potentially promote sustainability in long-term Saccharum production systems.

Field Data↗