Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sample Collection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16

Patchy burn severity explains heterogeneous soil viral and prokaryotic responses to fire in a mixed conifer forest

ABSTRACT Effects of fire on soil viruses and virus–host dynamics are largely unexplored, despite known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we assessed how viral and prokaryotic communities responded to a prescribed burn in a mixed conifer forest. We sequenced 91 viral-size fraction metagenomes (viromes) and 115 16S rRNA gene amplicon libraries from 120 samples: four samples at five timepoints (two before fire and three after fire) at six sites (four treatment, two control). We hypothesized that compositional differences would be most significant between burned and unburned soils, but instead, plot location best distinguished viral communities, more than treatment (burned or not), depth (0–3 or 3–6 cm), or timepoint. For both viruses and prokaryotes, some burned communities resembled unburned controls, while others were significantly different, revealing heterogeneous responses to fire. These patterns were explained by burn severity, here defined by soil chemistry. Viral but not prokaryotic richness decreased significantly with burn severity, and low viromic DNA yields indicated substantial loss of viral biomass at higher severity. The relative abundances of Firmicutes, Actinobacteriota, and the viruses predicted to infect them increased significantly with burn severity, suggesting survival and viral infection of these fire-responsive and potentially spore-forming taxa. The degree of burn severity experienced by each patch of soil, rather than burn status alone, differed over mere meters in the same fire. Therefore, our analyses highlight the importance of high-resolution, paired biogeochemical data to explain soil community responses to fire. IMPORTANCE The impact of fire on the soil microbiome, particularly on understudied soil viral communities, warrants investigation, given known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we collected 120 soil samples before and after a prescribed burn in a mixed conifer forest to assess the impacts of this disturbance on soil viral and prokaryotic communities. We show that simple categorical comparisons of burned and unburned areas were insufficient to reveal the underlying community response patterns. The patchy nature of the fire (indicated by soil chemistry data) led to significant changes in viral and prokaryotic community composition in areas of high burn severity, while communities that experienced lower burn severity were indistinguishable from those in unburned controls. Our results highlight the importance of considering highly resolved burn severity and biogeochemical measurements, even in nearby soils after the same fire, in order to understand soil microbial responses to prescribed burns.

Microbiology↗

2009 National Household Travel Survey - California Add-On

The California add-on survey supplements the 2009 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. The NHTS was conducted by the Federal Highway Administration, which collected data on the demographic and socioeconomic composition of households, as well as detailed information on travel behavior nationwide. State transportation departments and metropolitan planning agencies had the opportunity to purchase extra household samples as part of the NHTS add-on program. These additional samples, along with national samples collected in the add-on areas, are compiled for use in transportation planning, forecasting, and research. The California Department of Transportation participated in the NHTS add-on program and received a total of 21,225 household samples in California, from March 2008 through May 2009.

1Hz data↗

2017 National Household Travel Survey - California Add-On

The California add-on survey supplements the 2017 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. The NHTS was conducted by the Federal Highway Administration, which collected data on the demographic and socioeconomic composition of households, as well as detailed information on travel behavior nationwide. State transportation departments and metropolitan planning agencies had the opportunity to purchase extra household samples as part of the NHTS add-on program. These additional samples, along with national samples collected in the add-on areas, are compiled for use in transportation planning, forecasting, and research. The California Department of Transportation participated in the NHTS add-on program and received a total of 26,095 household samples in California, from April 2016 through April 2017.

1Hz data↗

Evaluation of dried blood spot sampling for verification of exposure to chemical threat agents

Abstract Purpose Exposure to chemical threat agents (CTAs), including nerve agents, the vesicating agent sulfur mustard, and opioids, remains a significant threat to warfighter and civilian populations. Definitive analytical methods to verify exposure to CTAs require shipping refrigerated or frozen biomedical samples to reference laboratories for analysis. Logistical and financial burdens arise as the transport of biomedical samples is subject to strict restrictions and complex packaging, which, if done incorrectly, can lead to sample deterioration. The use of dried blood spot (DBS) sampling could provide operational improvements for collecting, storing, and shipping important forensic samples. Therefore, this effort focuses on developing DBS techniques with Mitra® 30-µL volumetric absorptive microsampling (VAMS®) devices for use in CTA exposure verification. Methods VAMS® devices were loaded and dried with human whole blood that was exposed to the metabolites pinacolyl methylphosphonic acid (PMPA), ethyl methylphosphonic acid (EMPA), 1,1’sulfonylbis[2-(methylsulfinyl)ethane] (SBMSE), norfentanyl, norcarfentanil, norsufentanil, and norlofentanil. Following extraction from the VAMS® devices, metabolites were detected using liquid chromatography-tandem mass spectrometry (LC–MS/MS). The methods were validated for performance by assessing sensitivity, precision, accuracy, and recovery. Results These methods were sensitive to 1 ng/mL for SBMSE, 0.5 ng/mL for PMPA, EMPA, and norfentanyl; 0.1 ng/mL for norlofentanil, and 0.05 ng/mL for norsufentanil and norcarfentanil. All methods met acceptable precision and accuracy criteria with favorable recovery. Conclusions These results demonstrated the utility of VAMS® in stabilizing human whole blood and show promise as an improved collection method for verification of exposure to various CTAs.

Toxicology↗

Spatial mapping of dissolved methane using an in situ sensor in Puget Sound

Release of methane, as gas bubbles or in the dissolved phase, from the seafloor has been observed in coastal waters (< 200 m) and deep ocean basins (> 1000 m). Methane dissolution within the water column affects the geochemistry of the surrounding water, leading to localized oxygen loss and potential escape to the atmosphere, particularly from shallower sites. Traditional methods for detecting and quantifying dissolved methane rely on collecting discrete water samples for ship- or land-based ex situ analysis and post processing. Here, we report on the use of a reduced response time, in situ methane sensor, the Sensor for Aqueous Gases in the Environment (SAGE), for detecting and quantifying dissolved methane concentrations in a wide range of seafloor environments. During a Fall 2022 research cruise on the R/V Thomas G. Thompson in Puget Sound, SAGE was integrated onto a towed conductivity/temperature/depth rosette and deep-sea camera system with live-stream 1 Hz telemetry and used to spatially map the concentration of methane approximately 1 m above the seafloor. The site had been previously identified as an active methane plume field characterized by gas bubbles, fluid venting, and a faulted seabed. The widespread background dissolved concentration of methane measured by SAGE was 83 nM, and a range of 78–670 nM was observed throughout the survey. The results highlight the capacity of SAGE to map the spatial and temporal variability of dissolved methane concentrations in situ and to identify and localize sites of variable methane emissions from the seafloor.

Padilla, Alexandra M. [Woods Hole Oceanographic In↗

Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds

Abstract Quantifying the relative influence of factors and processes controlling riverine ecosystem function is essential to predicting future conditions under global change. Dissolved organic matter (DOM) is a fundamental component of riverine ecosystems that fuels microbial food webs, influences nutrient and light availability, and represents a significant carbon flux globally. The heterogeneous nature of DOM molecular composition and its propensity for interaction (i.e., functional diversity) can characterize riverine ecosystem function across spatiotemporal scales. To investigate fundamental drivers of DOM diversity, we collected seasonal water samples from 42 nested locations within five watersheds spanning multiple watershed sizes (~ 5 to 30,000 km 2 ) across the United States. Patterns in DOM molecular richness, aromaticity, relative abundance of N-containing formulas, and putative biochemical transformations derived from high-resolution mass spectrometry were assessed across gradients of explanatory variables associated with watershed characteristics (e.g., watershed area, water residence time, land cover). We found that putative biochemical transformations were more strongly related to explanatory variables across watersheds than common bulk DOM parameters and that watershed area, surface water residence time and derived Damköhler numbers representing DOM reactivity timescales were strong predictors of DOM diversity. The data also indicate that catchment-specific land cover factors can significantly influence DOM diversity in diverging directions. Overall, the results highlight the importance of considering water residence time and land cover when interpreting longitudinal patterns in DOM chemistry and the continued challenge of identifying generalizable drivers that are transferable across watershed and regional scales for application in Earth system models. This work also introduces a Findable Accessible Interoperable Reusable (FAIR) dataset (> 300 samples) to the community for future syntheses.

54 ENVIRONMENTAL SCIENCES↗

Eddy covariance towers as sentinels of abnormal radioactive material releases

Ensuring accurate detection and attribution of abnormal releases of radioactive material is critical for protecting human health and safety. Most commonly, such detection is accomplished via active monitoring approaches involving the collection of physical samples. Further, this is labor intensive and limits the temporal and spatial resolution of any detected events to a relatively coarse level. As an alternative first step towards passive monitoring, we developed an approach using eddy flux tower data records to identify signals from a known abnormal release and quantify the extent to which that signal also occurs at other times in the data record. Through two case studies, one of which targeted the Fukushima nuclear disaster and the other targeting an abnormal release event at a radioisotope production facility in Fleurus, Belgium, we tested our approach and identified several potential heretofore unidentified abnormal events that were consistent with atmospheric circulation patterns and/or wind direction from known release sites. Because our approach is relatively simple and is resistant to systematic errors in the observational record, it has broad applicability beyond specific constituents and ecosystem types to identify a wide variety of limited-duration anomalies in flux tower data to ensure human health and industrial safety.

54 ENVIRONMENTAL SCIENCES↗

Identification of Common Types of Plastics by Vibrational Spectroscopic Techniques

Polyethylene Terephthalate (PET), High-Density Polyethylene (HDPE), Polyvinyl Chloride (PVC), Low-Density Polyethylene (LDPE), Polypropylene (PP), and Polystyrene (PS) account for most plastic use worldwide, with production nearing 380 million tons annually. A considerable portion enters municipal solid waste and landfills, creating long-term environmental concerns. Scaling recycling operations requires automated sorting technologies, with spectroscopy and machine learning offering promising solutions. In this study, a six-class convolutional neural network (CNN) was developed for plastic identification using vibrational spectroscopies. Raman Scattering (RS) spectra collected from recycling samples enabled accurate chemical differentiation while assessing the influence of visible features such as color. A CNN trained on RS data achieved 100% classification accuracy. To strengthen field applicability, Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy was incorporated, achieving 95% accuracy with a similar CNN model. These findings demonstrate the potential of integrating spectroscopy with deep learning for reliable plastic classification, advancing development of scalable, field-ready recycling technologies.

Garcia Tovar, Maria P.↗

Getting to the root of the problem: Soil carbon and microbial responses to root inputs within a buried paleosol along an eroding hillslope in southwestern Nebraska, USA

Large quantities of soil carbon (C) can persist within paleosols for millennia due to burial and subsequent isolation from plant-derived inputs, atmospheric conditions, and microbial activity at the modern surface. Erosion exposes buried soils to modern root-derived C influx via root exudation and root turnover, thus stimulating microbial activity leading to SOC decomposition and accumulation through organo-mineral stabilization of modern C. With this study we aim to quantify how modern root-derived C inputs impact paleosol C decomposition and stabilization across varying degrees of isolation from modern surface conditions in southwestern Nebraska, USA, where hillslope erosion is bringing a buried Late-Pleistocene-early Holocene paleosol (the “Brady Soil”) closer to the modern surface. We collected Brady Soil samples from 0.2m, 0.4m, and 1.2m below the modern surface and conducted two lab-based incubations. Soils were amended with either (1) a lab-synthesized mixture of low molecular weight compounds (12 atom% 13 C), or (2) 13 C enriched root residues (92 atom% 13 C), in 30-day and 240-day incubation experiments, respectively. Here we determined microbial responses to synthetic root exudates and residues by partitioning the 13 C label from Brady Soil C, including measurements of total, root, and primed C respiration, microbial biomass C (MBC), microbial C use efficiency (CUE). To assess the capacity of isolated paleosols to accrue modern plant C, we used Nano-scale Secondary Ion Mass Spectrometry imaging. We found that: (1) adding root-derived C inputs primed Brady Soil C across all depths, and was mediated by depth and composition of root additions; (2) root-derived C inputs stimulated microbial biomass C (MBC) growth similarly across depths, but the magnitude of CUE and MBC varied by chemistry of root-derived additions; (3) new particulate organic matter was incorporated into mineral-associated pools over time; (4) material from the added root residues was found in association with bacterial cells and fungal hyphae as well as with soil aggregate and mineral surfaces. Our study shows that paleosols defy expectations of C content and reactivity with depth, and changes in land cover and climate will expose buried paleosols to modern surface conditions, increasing respired C. This work highlights the importance of evaluating the role resurfacing buried soils through landscape change plays in C cycle feedbacks to the climate system.

54 ENVIRONMENTAL SCIENCES↗

Measurement of 𝐵 meson production fraction ratios in proton-proton collisions at √𝑠 = 13 TeV using open-charm and charmonium decays

Production fraction ratios of 𝐵 + , 𝐵 0 , and 𝐵$^{0}_{𝑠}$ mesons are measured in proton-proton collisions at √𝑠 = 13 TeV using a special dataset recorded in 2018 with high-rate triggers designed to collect an unbiased sample of 1⁢010 𝑏 hadrons with the CMS experiment at the LHC. These data allow the study of the open-charm decays of 𝐵 mesons (𝐵 (𝑠) → 𝜋⁢𝐷 (𝑠) ) where the 𝐷 meson decays into fully hadronic final states. By utilizing known branching fractions and precise theoretical calculations, production fraction ratios as functions of 𝐵 meson transverse momentum (𝑝 T ) and rapidity (𝑦) are measured using open-charm decays in the kinematic range of 8 < 𝑝 T < 60 GeV and |𝑦| <2.25. In addition, the same dataset is used to measure the relative production fraction ratios with the charmonium decay channels [𝐵 (𝑠) →𝑋⁢𝐽/𝜓 with 𝑋 indicating a 𝐾 + , 𝐾*(892) 0 , or 𝜙⁡(1020) meson] where the 𝐽/𝜓 meson decays into a pair of muons. The open-charm results are used to normalize the relative production fraction ratios obtained from the charmonium samples. Measurements of the ratios of branching fractions of 𝐵 meson decays to charmonium and open-charm final states are also reported, which will improve the world-average values of these ratios. Finally, we test isospin invariance in 𝐵 meson production in proton-proton collisions and observe that it holds within the experimental precision.

Bottom mesons↗

Time-series metagenomics reveals changing protistan ecology of a temperate dimictic lake

Abstract Background Protists, single-celled eukaryotic organisms, are critical to food web ecology, contributing to primary productivity and connecting small bacteria and archaea to higher trophic levels. Lake Mendota is a large, eutrophic natural lake that is a Long-Term Ecological Research site and among the world’s best-studied freshwater systems. Metagenomic samples have been collected and shotgun sequenced from Lake Mendota for the last 20 years. Here, we analyze this comprehensive time series to infer changes to the structure and function of the protistan community and to hypothesize about their interactions with bacteria. Results Based on small subunit rRNA genes extracted from the metagenomes and metagenome-assembled genomes of microeukaryotes, we identify shifts in the eukaryotic phytoplankton community over time, which we predict to be a consequence of reduced zooplankton grazing pressures after the invasion of a invasive predator (the spiny water flea) to the lake. The metagenomic data also reveal the presence of the spiny water flea and the zebra mussel, a second invasive species to Lake Mendota, prior to their visual identification during routine monitoring. Furthermore, we use species co-occurrence and co-abundance analysis to connect the protistan community with bacterial taxa. Correlation analysis suggests that protists and bacteria may interact or respond similarly to environmental conditions. Cryptophytes declined in the second decade of the timeseries, while many alveolate groups (e.g., ciliates and dinoflagellates) and diatoms increased in abundance, changes that have implications for food web efficiency in Lake Mendota. Conclusions We demonstrate that metagenomic sequence-based community analysis can complement existing efforts to monitor protists in Lake Mendota based on microscopy-based count surveys. We observed patterns of seasonal abundance in microeukaryotes in Lake Mendota that corroborated expectations from other systems, including high abundance of cryptophytes in winter and diatoms in fall and spring, but with much higher resolution than previous surveys. Our study identified long-term changes in the abundance of eukaryotic microbes and provided context for the known establishment of an invasive species that catalyzes a trophic cascade involving protists. Our findings are important for decoding potential long-term consequences of human interventions, including invasive species introduction.

59 BASIC BIOLOGICAL SCIENCES↗

HighDimMixedModels.jl: Robust high-dimensional mixed-effects models across omics data

High-dimensional mixed-effects models are an increasingly important form of regression in which the number of covariates rivals or exceeds the number of samples, which are collected in groups or clusters. The penalized likelihood approach to fitting these models relies on a coordinate descent algorithm that lacks guarantees of convergence to a global optimum. Here, we empirically study the behavior of this algorithm on simulated and real examples of three types of data that are common in modern biology: transcriptome, genome-wide association, and microbiome data. Our simulations provide new insights into the algorithm’s behavior in these settings, and, comparing the performance of two popular penalties, we demonstrate that the smoothly clipped absolute deviation (SCAD) penalty consistently outperforms the least absolute shrinkage and selection operator (LASSO) penalty in terms of both variable selection and estimation accuracy across omics data. To empower researchers in biology and other fields to fit models with the SCAD penalty, we implement the algorithm in a Julia package, HighDimMixedModels.jl .

Gorstein, Evan↗

Advancing Molecular Level Understanding of Aerosol Processes in the Amazon and Integration with Modeling (Final Report)

The Amazon forest is being converted to urban and agricultural uses through land clearing including large scale burning. It is also the dominant source of biogenic hydrocarbons globally, which can chemically transform in the atmosphere to form secondary organic aerosol (SOA). Most aerosols (solid or liquid particles suspended in air) are organic and formed through secondary chemical processes. This means that SOA chemical composition and their physical properties can impact cloud formation, the hydrologic cycle, and radiative balance in this region. The 2014 GoAmazon field campaign at the DOE/ARM facility at T3 afforded study of chemical transformations in the region downwind of Manaus. Local biogenic hydrocarbons emissions are high, and their chemical oxidation can be studied with varying degrees of influence by the urban plume. We collected aerosol filter samples and made time-resolved molecular level measurements by deploying a sequential filter sampler and a Semi-Volatile Thermal desorption Aerosol Gas Chromatograph (SV-TAG) during Jan-Mar 2014 (wet season) and Aug-Oct 2014 (dry season).

54 ENVIRONMENTAL SCIENCES↗

Bringing Alaska's Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) into Perspective

The final report outlines the outcomes of the Alaska CORE-CM Program, funded by the U.S. Department of Energy under award DE-FE0032050. Led by the University of Alaska Fairbanks and the Alaska Division of Geological and Geophysical Surveys, with assistance from other organizations, the project assessed Alaska's potential for Carbon Ore, Rare Earth Elements, and Critical Minerals (CORE-CM). Leveraging advanced analytical techniques, the project identified high-potential resource basins, evaluated geochemical and satellite data, and conducted targeted field investigations. Findings revealed promising concentrations of critical minerals in legacy samples and newly collected materials. The project also investigated innovative extraction technologies, including BioExtraction and use of supercritical CO2, which show significant promise for sustainable resource recovery. Additionally, the study explored the reuse of waste streams from active mining operations and coal byproducts such as using alkali-activated coal ash to manufacture concrete. Infrastructure and logistical challenges in Alaska’s remote regions are discussed, alongside strategies to establish a Technology Innovation Center aimed at advancing CORE-CM development in Alaska. The report includes actionable insights to support Alaska’s critical role in securing domestic supplies of essential minerals while addressing economic, environmental, and technological challenges.

01 COAL, LIGNITE, AND PEAT↗

An Advanced Machine Learning and Artificial Intelligence System for Demonstrating Radiation Regulatory Compliance in DOE Accelerator Facilities

In this Phase II proposal, Applied Research LLC (ARLLC), Thomas Jefferson National Accelerator Facility (Jefferson Lab), and Old Dominion University (ODU) propose the combination of domain knowledge (beam characteristics, fixed structural shielding, earthen burden (the soil and foliage added to the dome of the experimental halls as additional shielding), etc.), machine learning (ML) and/or artificial intelligence (AI) to correlate a variety of multi-modal onsite signals and the radiation fields seen in accessible areas of the accelerator site and the site boundary. The ML/AI will consider the complex influence of environmental parameters affecting the radon contribution of the measurements, focusing on actual data obtained from Jefferson Lab. In Phase I, the coded beam and location data were fed into a deep learning model to predict doses at several designated locations in Jefferson Lab’s facility. Moreover, a dense radiation map was generated using only a sparse collection of the samples in a facility. In Phase II, we will develop a software prototype containing a radiation prediction algorithm, dense radiation map algorithms, and background noise prediction algorithms, with actual data used to evaluate the prototype. This work will provide a framework for evaluation of radiation measurement results around the site based on learned responses. In addition, the proposed approach allows more granular mapping of radiation levels. Better understanding and communication of these levels is related to the overall approach in keeping doses to personnel ALARA.

43 PARTICLE ACCELERATORS↗

Towards combination of charge and light readout at O(10) MeV energies in DUNE

The Deep Underground Neutrino Experiment (DUNE) is an experiment under construction that will employ 10-kt scale liquid-argon-TPC technology to do precision measurements of neutrino oscillations. Apart from the determination of CP violation in neutrino interactions, one of the main scientific goals of DUNE is the detection of neutrinos from a supernova burst. It is imperative to maximise the potential of the detector for extracting information for these rare events. The use of light signals to aid the calorimetry of neutrino interactions provides such potential. We will present current efforts to demonstrate the application of combined calorimetry in one of the DUNE prototype detectors at CERN. The ground-level placement of the detector allows collection of large samples of cosmic-ray muons stopping within its volume. Michel electrons from muon decay can be identified in both the ionization charge and scintillation light, serving as a proxy for supernova neutrino interactions at O(10) MeV energies. The method for demonstrating combined calorimetry and its associated challenges will be introduced. We will also summarise the current analysis status and future prospects.

Pěč, Viktor [Prague, Inst. Phys.] (ORCID:000000034↗

Baltimore Turfgrass Field Experiment Campaign Report

The Baltimore Turfgrass Field Experiment (BTFE) consisted of an observation eddy covariance flux station, measuring CO 2 , H 2 O, and turbulent energy fluxes between the turfgrass field and the atmosphere. The tower was sited before the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s arrival, but for the purposes of this report, we can say that the campaign lasted as long as the Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) campaign, 12 months, 12/2024 through 11/2025. As stated, the flux tower was part of the COURAGE campaign on the M1 site. We set out to measure turfgrass because it is a ubiquitous part of the urban environment—in fact, it is the dominant vegetation land cover type in Baltimore and most cities. It contributes small but significantly to greenhouse gas balances as well as the energy balance in the urban environment. We also installed a soil temperature and matric potential profiling system as part of this experiment. Additionally, AmeriFlux asked us to participate in their soil matric potential soil moisture mapping experiment. We collected 12 soil samples to be analyzed by a team in Bloomington, Indiana: results are pending.

54 ENVIRONMENTAL SCIENCES↗

Compressed sensing methods with applications to advanced air sampling

Environmental sampling methods developed by the Savannah River National Laboratory (SRNL) employ collectors with sorbent media tubes set at various locations to collect airborne emissions. Laboratory analyses of these tubes results in one-dimensional signals regarding what chemicals are being released and transported within the atmosphere. The analysis process is time consuming especially when analyzing a full year’s worth of tubes (hourly sample collection results in nearly 9,000 tubes per year). Using a signal processing method such as compressed sensing allows for recreation of the full signal while greatly reducing the number of analyzed samples required. Due to the sparsity of data retrieved from the air tubes, it is possible to use measurements a fraction of the size of the original data to gain much of the same information. This would improve the overall time and cost of analysis when modeling one-dimensional sampling signals.

54 ENVIRONMENTAL SCIENCES↗