Search NASA⌕ Search

SEARCH · Search NASA

Results for “Data Abstractions and Types”

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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Trumpler 16-26: a new centrifugal magnetosphere star discovered via SDSS/APOGEE H -band spectroscopy

ABSTRACT We report the discovery of a new example of the rare class of highly magnetized, rapidly rotating, helium enhanced, early B stars that produce anomalously wide hydrogen emission due to a centrifugal magnetosphere (CM). The star is Trumpler 16-26, a B1.5 V member of the Trumpler 16 open cluster. A CM was initially suspected based on hydrogen Brackett series emission observed in SDSS/APOGEE H-band spectra. Similar to the other stars of this type, the emission was highly variable and at all times remarkable due to the extreme velocity separations of the double peaks (up to 1300 km s−1.) Another clue lay in the TESS light curve, which shows two irregular eclipses per cycle when phased with the likely 0.971 8115-d rotation period, similar to the behaviour of the well-known CM host star σ Ori E. To confirm a strong magnetic field and rotation-phase-locked variability, we initiated a follow-up campaign consisting of optical spectropolarimetry and spectroscopy. The associated data revealed a longitudinal magnetic field varying between −3.1 and +1.6 kG with the period found from photometry. The optical spectra confirmed rapid rotation (v sin i = 195 km s−1), surface helium enhancement, and wide, variable hydrogen emission. Tr16-26 is thus confirmed as the 20th known, the fourth most rapidly rotating, and the faintest CM host star yet discovered. With a projected dipole magnetic field strength of Bd > 11 kG, Tr16-26 is also among the most magnetic CM stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Evaluating the impact of anatomical and physiological variability on human equivalent doses using PBPK models

Abstract Addressing human anatomical and physiological variability is a crucial component of human health risk assessment of chemicals. Experts have recommended probabilistic chemical risk assessment paradigms in which distributional adjustment factors are used to account for various sources of uncertainty and variability, including variability in the pharmacokinetic behavior of a given substance in different humans. In practice, convenient assumptions about the distribution forms of adjustment factors and human equivalent doses (HEDs) are often used. Parameters such as tissue volumes and blood flows are likewise often assumed to be lognormally or normally distributed without evaluating empirical data for consistency with these forms. In this work, we performed dosimetric extrapolations using physiologically based pharmacokinetic (PBPK) models for dichloromethane (DCM) and chloroform that incorporate uncertainty and variability to determine if the HEDs associated with such extrapolations are approximately lognormal and how they depend on the underlying distribution shapes chosen to represent model parameters. We accounted for uncertainty and variability in PBPK model parameters by randomly drawing their values from a variety of distribution types. We then performed reverse dosimetry to calculate HEDs based on animal points of departure for each set of sampled parameters. Corresponding samples of HEDs were tested to determine the impact of input parameter distributions on their central tendencies, extreme percentiles, and degree of conformance to lognormality. This work demonstrates that the measurable attributes of human variability should be considered more carefully and that generalized assumptions about parameter distribution shapes may lead to inaccurate estimates of extreme percentiles of HEDs.

Toxicology↗
DOE OSTI2022

Estimation of pollen productivity and dispersal: How pollen assemblages in small lakes represent vegetation

Abstract Quantitative understanding of vegetation dynamics over timespans beyond a century remains limited. In this regard, the pollen‐based reconstruction of past vegetation enables unique research opportunities by quantifying changes in plant community compositions during hundreds to thousands of years. Critically, the methodological basis for most reconstruction approaches rests upon estimates of pollen productivity and dispersal. Previous studies, however, have reached contrasting conclusions concerning these estimates, which may be perceived to challenge the applicability and reliability of pollen‐based reconstruction. Here we show that conflicting estimates of pollen production and dispersal are, at least in part, artifacts of fixed assumptions of pollen dispersal and insufficient spatial resolution of vegetation data surrounding the pollen‐collecting lake. We implemented a Bayesian statistical model that related pollen assemblages in surface sediments of 33 small lakes (<2 ha) in the northeastern United States, with surrounding vegetation ranging from 10 1 to >10 5 m from the lake margin. Our analysis revealed three key insights. First, pollen productivity is largely conserved within taxa and across forest types. Second, when local (within a 1‐km radius) vegetation abundances are not considered, pollen‐source areas may be overestimated for some common taxa (Cupressaceae, Pinus , Quercus , and Tsuga ). Third, pollen dispersal mechanisms may differ between local and regional scales; this is missed by pollen‐dispersal models used in previous studies. These findings highlight the complex interactions between vegetation heterogeneity on the landscape and pollen dispersal. We suggest that, when estimating pollen productivity and dispersal, both detailed local and extended regional vegetation must be taken into account. Also, both deductive (mechanistic models) and inductive (statistical models) approaches are needed to better understand the emergent properties of pollen dispersal in heterogeneous landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Host population diversity as a driver of viral infection cycle in wild populations of green sulfur bacteria with long standing virus-host interactions

Abstract Temperate phages are viruses of bacteria that can establish two types of infection: a lysogenic infection in which the virus replicates with the host cell without producing virions, and a lytic infection where the host cell is eventually destroyed, and new virions are released. While both lytic and lysogenic infections are routinely observed in the environment, the ecological and evolutionary processes regulating these viral dynamics are still not well understood, especially for uncultivated virus-host pairs. Here, we characterized the long-term dynamics of uncultivated viruses infecting green sulfur bacteria (GSB) in a model freshwater lake (Trout Bog Lake, TBL). As no GSB virus has been formally described yet, we first used two complementary approaches to identify new GSB viruses from TBL; one in vitro based on flow cytometry cell sorting, the other in silico based on CRISPR spacer sequences. We then took advantage of existing TBL metagenomes covering the 2005–2018 period to examine the interactions between GSB and their viruses across years and seasons. From our data, GSB populations in TBL were constantly associated with at least 2-8 viruses each, including both lytic and temperate phages. The dominant GSB population in particular was consistently associated with two prophages with a nearly 100% infection rate for >10 years. We illustrate with a theoretical model that such an interaction can be stable given a low, but persistent, level of prophage induction in low-diversity host populations. Overall, our data suggest that lytic and lysogenic viruses can readily co-infect the same host population, and that host strain-level diversity might be an important factor controlling virus-host dynamics including lytic/lysogeny switch.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

In Situ Study of Resistive Switching in a Nitride‐Based Memristive Device

Abstract Resistive switching (RS) devices with ultra‐low‐voltage threshold and reliable switching repeatability exhibits great potential applications in energy‐efficient data storage and neuromorphic computing. Understanding switching mechanisms at nanoscale is critical to design RS devices with improved performance. In this work, a lamella memristive device using focused ion beam (FIB) method based on the metal/TiO x /TiN/Si structure device is fabricated. In situ transmission electron microscopy (TEM) and current–voltage ( I–V ) characteristic demonstrate that the lamella device shows a volatile RS behavior with a threshold switching at ≈ ± 0.4 V. In situ scanning transmission electron microscopy (STEM) experiments with electron energy loss spectroscopy (EELS) reveal that the charge carriers such as oxygen vacancies migrate under positive/negative DC bias and modulate Schottky barriers at the top and bottom metal/semiconductor interfaces. The RS mechanism of the lamella device is based on the Schottky barriers modulation and Joule heating assisted electric field triggered thermal runaway (FTTR) occurred at the metal/semiconductor interfaces. The fundamental insights gained from this study presents a perspective on interface‐type RS devices processing and opens up new technological opportunities of fabricating ultra‐low‐energy memristive devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Image-Based Fracture Surface Defect Characterization Methods for Additively Manufactured Ti-6Al-4V Tested in Fatigue

Abstract Fatigue initiation in additively manufactured samples/parts often occurs at processed-induced defects such as lack-of-fusion (LoF), keyhole, or other morphological/microstructural defects that have unique characteristics and measurable qualities. Attempts at identifying and minimizing such defects have utilized optimized processing conditions along with in situ and ex situ characterization that includes metallography and/or X-ray computed tomography (XCT). This paper highlights the benefits of using fracture surface analyses to detect and quantify defects that may not be detected by metallography/XCT due to sectioning and resolution limits. In addition to using manual quantification of fatigue initiating LoF and keyhole defects on fracture surfaces, image-based machine learning using convolutional neural networks such as U-Net were also used to automate the process. Statistical analyses were used to identify the extreme cases of defects that initiated and accelerated fatigue and to model the distribution of defect size and shape characteristics to distinguish the type of defect. Initial results show agreement between trained machine learning models and ground truth data in defect segmentation, and the distributions of defect characteristics are distinguishable to particular process-induced defect types.

Materials Science↗
DOE OSTI2020

Future projections and uncertainty assessment of precipitation extremes in the Korean peninsula from the CMIP5 ensemble

Abstract Projections of changes in extreme climate are sometimes predicted by multimodel ensemble methods that combine forecasts from individual simulation models using weighted averaging. One method to assign weight to each model is the Bayesian model averaging (BMA) in which posterior probability is used. For the cases of extreme climate, the generalized extreme value distribution (GEVD) is typically used. We applied the approach of GEV‐embedded BMA to a series of 35 years of the annual maximum daily precipitation data (both historical data and data gathered from simulation experiments for future periods) over the Korean peninsula as simulated by the models in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Simulation data under two Representative Concentration Pathway (RCP) scenarios, namely RCP4.5 and RCP8.5, were used. Observed data and 17 CMIP5 models for 12 gird cells in Korea have been examined to predict future changes in precipitation extremes. A simple regional frequency analysis of pooling observations from three stations in each cell was employed to reduce the estimation variance and local fluctuations. A bias correction technique using the regression‐type transfer function was applied to these simulation data. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1971–2005), were estimated for two future periods, namely Period 1 (2021–2050) and Period 2 (2066–2095). From these analyses, relative increase observed in the spatially averaged 20‐year (50‐year) return level was approximately 23% (16%) and 45% (36%) in the RCP4.5 and RCP8.5 experiments, respectively, by the end of the 21st century. We concluded that extreme rainfalls will likely occur two times and four times more frequently in the RCP4.5 and RCP8.5 scenarios, respectively, as compared to in the reference years by the end of the 21st century.

Lee, Youngsaeng↗
DOE OSTI2023

Habitat quality influences trade-offs in animal movement along the exploration–exploitation continuum

Abstract To successfully establish itself in a novel environment, an animal must make an inherent trade-off between knowledge accumulation and exploitation of knowledge gained (i.e., the exploration–exploitation dilemma). To evaluate how habitat quality affects the spatio-temporal scale of switching between exploration and exploitation during home range establishment, we conducted experimental trials comparing resource selection and space-use of translocated animals to those of reference individuals using reciprocal translocations between habitat types of differing quality. We selected wild pigs ( Sus scrofa ) as a model species to investigate hypotheses related to the movement behavior of translocated individuals because they are globally distributed large mammals that are often translocated within their introduced range to facilitate recreational hunting. Individuals translocated to higher quality habitat (i.e. higher proportions of bottomland hardwood habitats) exhibited smaller exploratory movements and began exploiting resources more quickly than those introduced to lower quality areas, although those in lower-quality areas demonstrated an increased rate of selection for preferred habitat as they gained knowledge of the landscape. Our data demonstrate that habitat quality mediates the spatial and temporal scale at which animals respond behaviorally to novel environments, and how these processes may determine the success of population establishment.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

The evolution of the FIGARO data reduction system

The Figaro data reduction system originated at Caltech around 1983. It was based on concepts being developed in the U.K. by the Starlink organization, particularly the use of hierarchical self-defining data structures and the abstraction of most user-interaction into a set of 'parameter system' routines. Since 1984 it has continued to be developed at AAO, in collaboration with Starlink and Caltech. It was adopted as Starlink's main spectroscopic data reduction package, although it is by no means limited to spectra; it has operations for images and data cubes and even a few (very specialized) for four-dimensional data hypercubes. It continued to be used at Caltech and will be used at the Keck. It is also in use at a variety of other organizations around the world. Figaro was originally a system for VMS Vaxes. Recently it was ported (at Caltech) to run on SUN's, and work is underway at the University of New South Wales on a DecStation version. It is hoped to coordinate all this work into a unified release, but coordination of the development of a system by organizations covering three continents poses a number of interesting administrative problems. The hierarchical data structures used by Figaro allow it to handle a variety of types of data, and to add new items to data structures. Error and data quality information was added to the basic file format used, error information being particularly useful for infrared data. Cooperating sets of programs can add specific sub-structures to data files to carry information that they understand (polarimetry data containing multiple data arrays, for example), without this affecting the way other programs handle the files. Complex instrument-specific ancillary information can be added to data files written at a telescope and can be used by programs that understand the instrumental details in order to produce properly calibrated data files. Once this preliminary data processing was done the resulting files contain 'ordinary' spectra or images that can be processed by programs that are not instrument-specific. The structures holding the instrumental information can then be discarded from the files. Much effort has gone into trying to make it easy to write Figaro programs; data access subroutines are now available to handle access to all the conventional items found in Figaro files (main data arrays, error information, quality information etc), and programs that only need to access such items can be very simple indeed. A large number of Figaro users do indeed write their own Figaro applications using these routines. The fact that Figaro programs are written as callable subroutines getting information from the user through a small set of parameter routines means that they can be invoked in numerous ways; they are normally linked and run as individual programs (called by a small main routine that is generated automatically), but are also available linked to run under the ADAM data acquisition system and there is an interface that lets them be called as part of a user-written Fortran program. The long-term future of Figaro probably depends to a large extent on how successfully it manages the transition from being a VMS-only system to being a multi-platform system.

Shortridge, K.↗
NASA NTRSDate not supplied

Categorization of planets and exoplanets for Astrobiology.

Introduction: The number of exoplanets detected is astounding –and was not predicted. Note that Bo-rucki’s foundational paper for the Kepler mission in 1984 predicted:“...a detection rate of one planet per year of observation appears possible.”[1]. Even more astounding is the enormous diversity of exoplanets [2,3]. It is already clear from the data, that our Solar System does not bound the diversity and the range of processes seen in the exoplanets [2,3,4]. As telescopes improve it is certain that the number of exoplanets will become astronomical and the diversity will increase apace. The search for habitable locations and for evidence of life is a central part of the approach and excitement of exoplanet research [5,6]. Based on our experience to date we can expect that there will be enormous diversity in the types of habitability and life on exoplanets and that the Earth and our Solar System do not bound the possibilities for either habitability and life, and may not even provide a definite guide to selecting c and i-dates for detailed study from the enormous lists of exoplanets that will emerge. How can we develop a system for categorizing exoplanets in a way that allows for selection and prioritization in the search for diverse habitats and for diverse lifeforms?The short answer is we have no idea. In this short abstract I will venture some suggested approach-es. (see also[7]). To date, our solar system provides three classes for a habitable world:1) Earth. Water worlds, represented, of course, by Earth, and Earth-like worlds Venus and Mars. 2) Europa. Ice-covered worlds represented by Europa and including Enceladus and others, and 3) Titan. Cryogenic liquid covered worlds, represented by Titan. Earth and Europa world simply life made from carbon compounds in a water medium. Interest in these“ water worlds” is rooted in our understanding of life on Earth–the only example of life we have. The primary difference between Earth and Europa worlds is access to sunlight as an energy source on Earth. Titan represents the concept of carbon-based life in a cryogenic liquid such as CH4or C2H6 [8-13]. It is unlikely that Earth, Europa, and Titan represent the full range of possible classes of habitability for the many exoplanets that have been, or will be, discovered. It is also unlikely that life as we know it on Earth represents the full range of possible life on exoplanets. I am suggesting here that we start with these three classes (Earth, Europa, Titan) for exoplanet characterization and add others based on predicted types, such as “Hycean” worlds, a hypothetical type of planet with a hot, water-covered surface with a hydrogen dominated atmosphere [14] and the many examples considered in [15,16] and even imagined habitability and life forms [7] such as Sarr -a small, hot (500°C) rocky planet with an atmosphere over liquid sulfur. And that hosts only sulfur-based life. We are probably safe in the assumption that the richness and diversity of the exoplanets will exceed that of our collective imaginations.

Christopher P Mckay↗
DOE OSTI2024

Coastal bacteria and protists assimilate viral carbon and nitrogen

Abstract Free viruses are the most abundant type of biological particles in the biosphere, but the lack of quantitative knowledge about their consumption by heterotrophic protists and bacterial degradation has hindered the inclusion of virovory in biogeochemical models. Using isotope-labeled viruses added to three independent microcosm experiments with natural microbial communities followed by isotope measurements with single-cell resolution and flow cytometry, we quantified the flux of viral C and N into virovorous protists and bacteria and compared the loss of viruses due to abiotic vs biotic factors. We found that some protists can obtain most of their C and N requirements from viral particles and that viral C and N get incorporated into bacterial biomass. We found that bacteria and protists were responsible for increasing the daily removal rate of viruses by 33% to 85%, respectively, compared to abiotic processes alone. Our laboratory incubation experiments showed that abiotic processes removed roughly 50% of the viruses within a week, and adding biotic processes led to a removal of 83% to 91%. Our data provide direct evidence for the transfer of viral C and N back into the microbial loop through protist grazing and bacterial breakdown, representing a globally significant flux that needs to be investigated further to better understand and predictably model the C and N cycles of the hydrosphere.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A 5 per cent measurement of the Hubble–Lemaître constant from Type II supernovae

ABSTRACT The most stringent local measurement of the Hubble–Lemaître constant from Cepheid-calibrated Type Ia supernovae (SNe Ia) differs from the value inferred via the cosmic microwave background radiation (Planck+ΛCDM) by ∼5σ. This so-called Hubble tension has been confirmed by other independent methods, and thus does not appear to be a possible consequence of systematic errors. Here, we continue upon our prior work of using Type II supernovae to provide another, largely independent method to measure the Hubble–Lemaître constant. From 13 SNe II with geometric, Cepheid, or tip of the red giant branch (TRGB) host-galaxy distance measurements, we derive H$_0= 75.4^{+3.8}_{-3.7}$ km s−1 Mpc−1 (statistical errors only), consistent with the local measurement but in disagreement by ∼2.0σ with the Planck+ΛCDM value. Using only Cepheids (N = 7), we find H$_0 = 77.6^{+5.2}_{-4.8}$ km s−1 Mpc−1, while using only TRGB (N = 5), we derive H$_0 = 73.1^{+5.7}_{-5.3}$ km s−1 Mpc−1. Via 13 variants of our data set, we derive a systematic uncertainty estimate of 1.5 km s−1 Mpc−1. The median value derived from these variants differs by just 0.3 km s−1 Mpc−1 from that produced by our fiducial model. Because we only replace SNe Ia with SNe II – and we do not find statistically significant difference between the Cepheid and TRGB H0 measurements – our work reveals no indication that SNe Ia or Cepheids could be the sources of the ‘H0 tension.’ We caution, however, that our conclusions rest upon a modest calibrator sample; as this sample grows in the future, our results should be verified.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Constraining RV variation using highly reddened Type Ia supernovae from the Pantheon+ sample

ABSTRACT Type Ia supernovae (SNe Ia) are powerful tools for measuring the expansion history of the Universe, but the impact of dust around SNe Ia remains unknown and is a critical systematic uncertainty. One way to improve our empirical description of dust is to analyse highly reddened SNe Ia [E(B − V) > 0.4, roughly equivalent to the fitted SALT2 light-curve parameter c > 0.3]. With the recently released Pantheon+ sample, there are 57 SNe Ia that were removed because of their high colour alone (with colours up to c = 1.61), which can provide enormous leverage on understanding line-of-sight RV. Previous studies have claimed that RV decreases with redder colour, though it is unclear if this is due to limited statistics, selection effects, or an alternative explanation. To test this claim, we fit two separate colour–luminosity relationships, one for the main cosmological sample (c < 0.3) and one for highly reddened (c > 0.3) SNe Ia. We find the change in the colour–luminosity coefficient to be consistent with zero. Additionally, we compare the data to simulations with different colour models, and find that the data prefers a model with a flat dependence of RV on colour over a declining dependence. Finally, our results strongly support that line-of-sight RV to SNe Ia is not a single value, but forms a distribution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Short-period post-common envelope binaries with Balmer emission from SDSS and LAMOST based on ZTF photometric data

ABSTRACT We present here 55 short-period post-common envelope binaries (PCEBs) containing a hot white dwarf (WD) and a low-mass main sequence (MS). Based on the photometric data from Zwicky Transient Facility survey data Release 19 (ZTF DR19), the light curves are analysed for about 200 WDMS binaries with emission line(s) identified from the Sloan Digital Sky Survey (SDSS) or the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) spectra, in which 55 WDMS binaries are found to exhibit variability in their luminosities with a short period and are thus short-period binaries (i.e. PCEBs). In addition, it is found that the orbital periods of these PCEBs locate in a range from 2.2643 to 81.1526 h. However, only six short-period PCEBs are newly discovered and the orbital periods of 19 PCEBs are improved in this work. Meanwhile, it is found that three objects are newly discovered eclipsing PCEBs, and a object (i.e. SDSS J1541) might be the short-period PCEB with a late M-type star or a brown dwarf companion based on the analysis of its spectral energy distribution. At last, the mechanism(s) being responsible for the emission features in the spectra of these PCEBs are discussed, the emission features arising in their optical spectra might be caused by the stellar activity or an irradiated component owing to a hot WD companion because most of them contain a WD with an effective temperature higher than $\sim$10 000 K.

Li, Lifang↗
DOE OSTI2025

Calcium is associated with specific soil organic carbon decomposition products at Blodgett Forest Research Center, Georgetown, California as analysed with scanning transmission X-ray microscopy carbon near-edge X-ray absorption fine structure spectroscopy

This data is from the paper calcium is associated with specific soil organic carbon decomposition products, published in SOIL. DOI: https://doi.org/10.5194/soil-11-381-2025, 2025.This file contains CSVs with spectral data and bulk soil data and there is no specific program required to open this data. The data includes Scanning transmission X-ray microscopy carbon near-edge X-ray absorption fine structure spectroscopy. data from the measurement of samples from the Whole-soil Warming project, run by the Belowground Biogeochemistry team at Blodgett Forest Research Center, Georgetown, California run by the University of California, Berkeley. It also includes bulk soil chemical properties. The University of California's Blodgett Forest Research Station (Forest) is situated in the Sierra Nevada foothills (1370 m a.s.l.) near Georgetown, California. The samples were collected from here: 38.912013, -120.661469, https://maps.app.goo.gl/291bCJ1zVqUhgktz6. The Forest soils were characterised as Alfisols, which are equivalent to Dystric Cambisols (IUSS Working Group WRB, 2015), and formed in granitic parent materials, in a temperate climate, under thinned, mixed-coniferous forest (Fig. S3; Gaudinski et al., 2009). With these analyses we aimed to answer the question, is calcium associated with a specific type of organic matter enriched in aromatic and phenolic carbon at the microscale in samples from Blodgett Forest Research Center? and how does this specific type of carbon respond to experiments targetted at removing and adding calcium to the soils, specifically cation exchange and incubation after calcium addition? Abstract from the paper can be found below: Calcium (Ca) may contribute to the preservation of soil organic carbon (SOC) in more ecosystems than previously thought. Here we provide evidence that Ca is co-located with SOC compounds that are enriched in aromatic and phenolic groups, across different acidic soil-types and locations with different ecosystem properties, differing in terms of climate, parent material, soil type, and vegetation. In turn, this co-localised fraction of Ca-SOC is removed through cation-exchange, and the association is then only re-established during decomposition in the presence of Ca (Ca addition incubation). Thus, highlighting a causative link between decomposition and the co-location of Ca with a characteristic fraction of SOC. Decomposition increases the relative proportion of negatively charged functional groups, which can increase the propensity for the association between SOC and Ca, and in turn, this association inhibits dissolved organic carbon export or further decomposition. We propose that this mechanism could be driven by Ca hotspots on the microscale shifting local decomposition processes and thereby explaining the colocation of Ca with SOC of a specific composition across different acidic soil environments. Incorporating this biogeochemical process into Earth System Models could improve our understanding, predictions, and management of carbon dynamics in soils, and account for their response to Ca-rich amendments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A robust clustering algorithm for analysis of composition-dependent organic aerosol thermal desorption measurements

Abstract. One of the challenges of understanding atmospheric organic aerosol (OA) particles stems from its complex composition. Mass spectrometry is commonly used to characterize the compositional variability of OA. Clustering of a mass spectral dataset helps identify components that exhibit similar behavior or have similar properties, facilitating understanding of sources and processes that govern compositional variability. Here, we developed an algorithm for clustering mass spectra, the noise-sorted scanning clustering (NSSC), appropriate for application to thermal desorption measurements of collected OA particles from the Filter Inlet for Gases and AEROsols coupled to a chemical ionization mass spectrometer (FIGAERO-CIMS). NSSC, which extends the common density-based special clustering of applications with noise (DBSCAN) algorithm, provides a robust, reproducible analysis of the FIGAERO temperature-dependent mass spectral data. The NSSC allows for the determination of thermal profiles for compositionally distinct clusters of mass spectra, increasing the accessibility and enhancing the interpretation of FIGAERO data. Applications of NSSC to several laboratory biogenic secondary organic aerosol (BSOA) systems demonstrate the ability of NSSC to distinguish different types of thermal behaviors for the components comprising the particles along with the relative mass contributions and chemical properties (e.g., average molecular formula) of each mass spectral cluster. For each of the systems examined, more than 80 % of the total mass is clustered into 9–13 mass spectral clusters. Comparison of the average thermograms of the mass spectral clusters between systems indicates some commonality in terms of the thermal properties of different BSOA, although with some system-specific behavior. Application of NSSC to sets of experiments in which one experimental parameter, such as the concentration of NO, is varied demonstrates the potential for mass spectral clustering to elucidate the chemical factors that drive changes in the thermal properties of OA particles. Further quantitative interpretation of the thermograms of the mass spectral clusters will allow for a more comprehensive understanding of the thermochemical properties of OA particles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Generalizing Microbial Parameters in Soil Biogeochemical Models: Insights From a Multi‐Site Incubation Experiment

Abstract Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case‐specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial‐ENzyme Decomposition model, this study aimed to test whether a common set of microbially‐relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two‐year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial‐relevant parameters for large‐scale soil model projections.

58 GEOSCIENCES↗