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DOE OSTI2020

Probabilistic Groundwater Modeling of the RDX Plume at Los Alamos National Laboratory to Support Risk Assessment - 20359

A plume of the contaminant hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) with concentrations greater than the New Mexico tap water drinking standard (9.66 ppb) is present in the regional aquifer near the southwestern boundary of Los Alamos National Laboratory (LANL). A risk assessment is performed for exposure to regional aquifer groundwater, with long-term predictions of RDX concentrations provided by a calibrated, probabilistic, numerical fate and transport model. The structure of the model is hierarchical, with the RDX Regional Aquifer (RA) groundwater model acting as the primary tool for analysis of downgradient RDX concentrations. The RA model is deeply informed by the conceptual site model (CSM) and is calibrated using site RDX concentration data and hydraulic head measurements, along with other analyses. The model is calibrated using data through December 2019. Where data are scarce other lines of evidence are used to inform inputs, including the multiphase RDX Vadose Zone (VZ) model and Pipe and Disk analytical screening tool. Model inputs are described with informative prior distributions using a robust approach to development that incorporates all available lines of evidence for every parameter used as an input to the RA model. Calibration is performed using a classical nonlinear optimization routine, which is then used to initialize a Bayesian calibration. The Bayesian calibration constrains the uncertainty in the classical calibration, ultimately providing posterior distributions for all model parameters. The challenges of the calibration include high-dimensional parameter space, including spatially heterogeneous hydraulic conductivities, comparatively sparse data, and low RDX concentrations. Posterior parameter distributions developed in the calibration process are then used for stochastic predictive model runs into the future. The result of the forward runs is spatially and temporally explicit estimates of head and concentration with uncertainty at all points in space and time. The probabilistic modeling approach presented here includes innovative computational and statistical methods that leverage high-performance computing (HPC) resources. It makes use of prior modeling work performed at the chromium plume site in the central LANL area, with extensive updates. The risk assessment will ultimately be used to support decision-making at the site, using multiple appropriately weighted sources of information, as well as uncertainty, sensitivity, and value-of-information analyses. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Heterogenous activation of dynamic recrystallization and twinning during friction stir processing of a Cu-4Nb alloy

An interplay between high degree of shear deformation and deformation-induced heating occurs during friction stir processing (FSP) of metals. In medium-to-low stacking fault energy Cu alloys, this can lead to a complex spatially heterogenous activation of dynamic recrystallization (DRX) and twinning mechanisms. Within the Cu-Nb system, the presence of Nb is further expected to influence the DRX mechanism of the Cu matrix. However, the microstructural changes induced by the co-deformation of Nb during FSP are still not well understood. So, this study uses a combination of multimodal microstructural characterization, solution thermodynamics-based predictions, and computational crystal plasticity simulation to reveal the various microstructural evolution mechanisms that can occur during FSP of a Cu-4at.%Nb binary model alloy. The formation of softer DRX zones, and harder shear localization regions are revealed using electron backscatter diffraction, transmission electron microscopy, atom probe tomography, and crystal plasticity modeling.

36 MATERIALS SCIENCE↗

NASA NTRS2023

Fine particulate concentrations over East Asia derived from aerosols measured by the Advanced Himawari Imager using machine learning

Fine particulate matter with a diameter below 2.5 μm (PM 2.5 ) is deleterious to the cardiovascular and respiratory systems. It is often difficult to assess the effects of PM 2.5 on human health over regions with limited ground monitoring sites, especially in East Asia. As an alternative, we estimated near-surface PM 2.5 concentrations by analyzing Advanced Himawari Imager (AHI) Yonsei Aerosol Retrieval (YAER) products. This study incorporates daytime data for East Asia covering the Korean Peninsula, China, Japan, Southeast Asia, and southern Mongolia. We collocated AHI YAER product pixels with meteorological, land-cover, and other ancillary data for the period from March 2018 to February 2019. To estimate PM 2.5 concentrations over wide areas spanning many countries displaying various relationships between aerosol optical depth and PM 2.5 , monthly models were developed by considering both the spatial and temporal characteristics of ground-based PM 2.5 measurements. Random forest machine learning model estimated ground-level mass concentrations of PM 2.5 ; subsequent 10-fold cross validation (CV) yielded a CV R 2 value of 0.81 and a CV root mean squared error (RMSE) of 12.3 μg m -3 . We investigated the spatial pattern of PM 2.5 concentrations over multiple countries and seasonal variation in PM 2.5 concentrations. Diurnal variation of a severe PM 2.5 event in the Korean Peninsula was investigated as a case study. The model captured the extremely heterogeneous spatial distribution of PM 2.5 concentrations peaked around local noon. To measure the capability of the developed model to estimate PM 2.5 concentrations in areas with few in-situ data, its predictive performance was evaluated using a dataset independent of the training process with an R 2 of 0.60 and RMSE of 8.18 μg m −3 . This study demonstrates the potential for satellite-based PM 2.5 estimation for areas with insufficient measuring stations.

Pm2.5↗

NASA NTRS1993

Study of atmospheric and bidirectional effects on surface reflectance and vegetation index time series: Application to NOAA AVHRR and preparation for future space missions

The objectives of the investigation, namely 'to characterize the atmospheric and directional effects on surface reflectance and vegetation index using the First International Satellite Cloud Climatology Project (ISLCSP) Field Experiment (FIFE) data set, develop new algorithms to obtain better Advanced Very High Resolution Radiometer (AVHRR) indices, and define possible improvements for future satellite missions', were addressed in three separate, yet complementary studies. First, it was shown, from theoretical calculations, that visible and near infrared reflectances combined linearly at optimum (one or two) viewing angles relate linearly to the fraction of photosynthetically available radiation absorbed by plants, f(sub par), can be used independently of the type of foliage and substrate, eliminate the effects of sub-pixel spatial heterogeneity, and improve the accuracy of the f(sub par) estimates when compared to the Normalized Difference Vegetation Index, NDVI. Second, it was demonstrated that NDVI, even though it is not a linear combination of radiances or reflectances, can be spatially integrated without significant loss of information from scales of 300 to 1000 m. Third, AVHRR visible and near-infrared reflectances over the FIFE site, separating temporal and bidirectional components and determining the model parameters through an original iterative scheme was successfully modeled. It appears that NDVI generated from the top-of-atmosphere reflectances normalized by the bidirectional effects (as determined in the scheme) is a better vegetation index than maximum NDVI. Details about the three studies are presented.

Frouin, Robert↗

NASA NTRS2011

Numerical Model Sensitivity to Heterogeneous Satellite Derived Vegetation Roughness

The sensitivity of a mesoscale weather prediction model to a 1 km satellite-based vegetation roughness initialization is investigated for a domain within the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database, specific to the domain, that was previously derived using a physically based procedure and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, and iii) a MODIS climatologic roughness database that like (i) is a function only of land cover type, but possesses domain specific mean values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations within a domain including Oklahoma, Eastern Arkansas, and Northwest Louisiana during a 4-day period within IHOP 2002. Sensitivity analysis compares the impact the three roughness initializations on time-series temperature, precipitation probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE). Overall, the results indicate that, for the current investigation, replacement of the standard look-up table values with the satellite-derived values statistically improves model performance for most observed variables. Such natural roughness heterogeneity enhances the surface wind speed, PBL height and TKE production up to 10 percent, with a lesser effect over grassland, and greater effect over mixed land cover domains.

Jasinski, Michael↗

DOE OSTI2026

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.

Wu, Yunhan [ORNL] (ORCID:0000000178842994)↗

DOE OSTI2026

Time-dependent-bases with local CUR decomposition method for accelerating turbulent combustion simulations

Here, this study presents a novel reduced-order modeling framework, Time-Dependent Bases with Local CUR decomposition (TDB-L-CUR), designed to efficiently and accurately approximate the species transport equations in reacting flow simulations. The method extends the existing TDB-CUR approach for chemically reacting flows (Jung et al. Comput. Methods Appl. Mech. Engrg. 437 (2025) 117758), which leverages matrix decomposition techniques to form a global-in-space, time-dependent low-dimensional manifold. While TDB-CUR performs well in homogeneous systems, it may be less well-suited to spatially heterogeneous systems such as turbulent flames, where higher-rank approximations are typically required. The proposed TDB-L-CUR framework introduces two methodological extensions to the baseline approach. First, it applies unsupervised clustering to partition the physical domain into distinct regions, enabling spatially localized manifold construction, thereby reducing the rank required for the reduced-order representation. Second, it incorporates a computational singular perturbation (CSP)-based scheme for identifying and penalizing fast species, allowing for spatio-temporally adaptive mitigation of chemical stiffness. The proposed framework is validated on a hierarchy of test cases, including a one-dimensional premixed flame, a two-dimensional nonpremixed ignition case with vortex interaction, and a three-dimensional turbulent premixed flame. TDB-L-CUR significantly improves accuracy over TDB-CUR while further reducing computational cost. The fully on-the-fly formulation of TDB-L-CUR (i.e., requiring no offline training or prior knowledge) makes it a robust and scalable tool for reduced-order modeling of reactive flows.

Local manifold↗

DOE OSTI2026

Spatiotemporal and Statistical Mapping of Transition Metal Equilibria in Alkaline Media

Transition metal dissolution and redeposition (D/R) kinetics in alkaline media play a critical role in various chemical and electrochemical processes. Competitive reaction kinetics between different transition metals can modulate individual metal behavior in these processes. To date, these phenomena have remained largely unmeasured, and even when captured, they are difficult to statistically characterize due to their dynamic nature, simultaneous occurrence, and spatially heterogeneous nature. Here, in this study, we develop a statistical analysis framework based on in situ and operando X-ray fluorescence microscopy (XFM) to investigate the relative D/R kinetics of multiple transition metals in alkaline media. By employing statistical analysis, we quantify the spatial distribution of D/R species and assess the rate at which the system reaches equilibrium under varying reaction conditions. We show that pH does not simply change the rate of dissolution and redeposition, but reorganizes the cross-element kinetic correlations among Ni, Fe, and Mn and accelerates the spatial equilibration of D/R events, as quantified through correlation analysis, reaction-rate estimation, probability function distributions, and texture-based monitoring statistics. Additionally, we demonstrate how modifying the solvent environment can influence D/R kinetics, providing a pathway for tuning materials synthesis and process optimization. Our study offers valuable insights into the complex interplay between different transition metals and provides a reliable statistical framework for spatial analysis of diverse imaging data sets, enabling deeper extraction of latent information across multiple modalities.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2

In the Energy Exascale Earth System Model (E3SM) Multi-scale Modeling Framework (MMF), where parameterizations of convection and turbulence are replaced by a 2-D cloud-resolving model (CRM), there are multiple options to represent land–atmosphere interactions. Here, we propose three different coupling strategies, namely the (1) coupling of a single land surface model to the global grid (MMF), (2) coupling a single land copy directly to the embedded CRM (SFLX2CRM), and (3) coupling a single copy of land model to each column of the CRM grid (MAML). In the MAML (Multi-Atmosphere Multi-Land) framework, a land model is coupled to CRM at the CRM-grid scale by coupling an individual copy of a land model to each CRM grid. Therefore, we can represent intra-CRM heterogeneity in the land–atmosphere interaction processes. There are 5-year global simulations run using these three coupling strategies, and we find some regional differences but overall small changes with respect to whether a land model is coupled to CRM or a global atmosphere. In MAML, the spatial heterogeneity within CRM induces stronger turbulence, which leads to the changes in soil moisture, surface heat fluxes, and precipitation. However, the differences in the MAML from the other two cases are rather weak, suggesting that the impact of using MAML does not justify the increase in cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2003

Regional Impacts of Woodland Expansion on Nitrogen Oxide Emissions from Texas Savannahs: Combining Field, Modeling and Remote Sensing Approaches

Woody encroachment has contributed to documented changes world-wide and locally in the southwestern U.S. Specifically, in North Texas rangelands encroaching mesquite (Prosopis glandulosa var. glandulosa) a known N-fixing species has caused changes in aboveground biomass. While measurements of aboveground plant production are relatively common, measures of soil N availability are scarce and vary widely. N trace gas emissions (nitric and nitrous oxide) flom soils reflect patterns in current N cycling rates and availability as they are stimulated by inputs of organic and inorganic N. Quantification of N oxide emissions from savanna soils may depend upon the spatial distribution of woody plant canopies, and specifically upon the changes in N availability and cycling and subsequent N trace gas production as influenced by the shift from herbaceous to woody vegetation type. The main goal of this research was to determine whether remotely sensible parameters of vegetation structure and soil type could be used to quantify biogeochemical changes in N at local, landscape and regional scales. To accomplish this goal, field-based measurements of N trace gases were carried out between 2000-2001, encompassing the acquisition of imaging spectrometer data from the NASA Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) on September 29, 2001. Both biotic (vegetation type and soil organic N) and abiotic (soil type, soil pH, temperature, soil moisture, and soil inorganic N) controls were analyzed for their contributions to observed spatial and temporal variation in soil N gas fluxes. These plot level studies were used to develop relationships between spatially extensive, field-based measurements of N oxide fluxes and remotely sensible aboveground vegetation and soil properties, and to evaluate the short-term controls over N oxide emissions through intensive field wetting experiments. The relationship between N oxide emissions, remotely-sensed parameters (vegetation cover, and soil type), and physical controls (soil moisture, and temperature) permitted the regional scale quantification of soil N oxides emissions. Landscape scale analysis linking N oxide emissions with cover change revealed an alleviation from N limitation following mesquite invasion. This study demonstrated the advantage of using N trace gases as a measure of ecosystem N availability combined with remote sensing to characterize the spatial heterogeneity in ecosystem parameters at a scale commensurate with field-based measurements of these properties. Woody vegetation encroachment provided an opportunity to capitalize on detection of the remotely-sensible parameter of woody cover as it relates to belowground biogeochemical processes that determine N trace gas production. The first spatially-explicit estimates of NO flux were calculated based on Prosopis fractional cover derived from high resolution remote sensing estimates of fractional woody cover (< 4 m) for a 120 sq km region of North Texas. An assessment of both N stocks and fluxes from the study revealed an alleviation of N limitation at this site experiencing recent woody encroachment. Many arid and semi-arid regions of the world are experiencing woody invasions, often of N-fixing species. The issue of woody encroachment is in the center of an ecological and political debate. Improving the links between biogeochemical processes and remote sensing of ecosystem properties will improve our understanding of biogeochemical processes at the regional scale, thus providing a means to address issues of land-use and land-cover change.

Asner, Gregory P.↗

DOE OSTI2022

Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed: Modeling Archive

This Modeling Archive is in support of a NGEE-Arctic publication: Shirley et al. (2022) “Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed". [DOI].The dataset contains outputs from the global sensitivity analysis (GSA) of the “ecosys” model as reported in Shirley et al. (2022). The study showed that discontinuous permafrost environments are characterized by complex feedback loops and strong spatial heterogeneity which is created by variability in near-surface hydrology and soil properties. Additionally, the study demonstrated that missing representation of sub-grid heterogeneity in terrestrial ecosystem models can lead to biased estimates of the high-latitude carbon budget. Included in this dataset are the factor values for each run in the GSA and the model outputs used in this study. Included are two *.csv data files and one *.pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Assessing heterogeneity of patient and health system delay among TB in a population with internal migrants in China

Backgrounds The diagnostic delay of tuberculosis (TB) contributes to further transmission and impedes the implementation of the End TB Strategy. Therefore, we aimed to describe the characteristics of patient delay, health system delay, and total delay among TB patients in Shanghai, identify areas at high risk for delay, and explore the potential factors of long delay at individual and spatial levels. Method The study included TB patients among migrants and residents in Shanghai between January 2010 and December 2018. Patient and health system delays exceeding 14 days and total delays exceeding 28 days were defined as long delays. Time trends of long delays were evaluated by Joinpoint regression. Multivariable logistic regression analysis was employed to analyze influencing factors of long delays. Spatial analysis of delays was conducted using ArcGIS, and the hierarchical Bayesian spatial model was utilized to explore associated spatial factors. Results Overall, 61,050 TB patients were notified during the study period. Median patient, health system, and total delays were 12 days (IQR: 3–26), 9 days (IQR: 4–18), and 27 days (IQR: 15–43), respectively. Migrants, females, older adults, symptomatic visits to TB-designated facilities, and pathogen-positive were associated with longer patient delays, while pathogen-negative, active case findings and symptomatic visits to non-TB-designated facilities were associated with long health system delays (LHD). Spatial analysis revealed Chongming Island was a hotspot for patient delay, while western areas of Shanghai, with a high proportion of internal migrants and industrial parks, were at high risk for LHD. The application of rapid molecular diagnostic methods was associated with reduced health system delays. Conclusion Despite a relatively shorter diagnostic delay of TB than in the other regions in China, there was vital social-demographic and spatial heterogeneity in the occurrence of long delays in Shanghai. While the active case finding and rapid molecular diagnosis reduced the delay, novel targeted interventions are still required to address the challenges of TB diagnosis among both migrants and residents in this urban setting.

Sun, Ruoyao↗

DOE OSTI2020

GPS-Based Gamma Survey for Characterizing and Decommissioning NORM Sites - 20389

Gamma survey techniques are an especially powerful decommissioning tool at naturally occurring radioactive material (NORM) sites due to both the low cost to obtain data over a large spatial scale and the abundance of gamma emitters in the uranium and thorium decay series. Gamma surveys are executed by coupling a detector - most often a sodium iodide crystal - to a global positioning system (GPS), then reporting a location and gross gamma reading coincidentally to a data logger. Systems may be carried by workers or mounted to a car, all-terrain vehicle, or unmanned aerial system (UAS). The resulting data set provides a high-resolution but low precision map of the gamma radiation field over the area surveyed. Frequently this map is also correlated to soil concentrations of NORM radionuclides (most often, Ra-226) and/or exposure rate. Gamma survey parameters such as movement speed, transect spacing, and data logging frequency define the spatial resolution of the resulting surface, and can be optimized depending on the desired survey sensitivity. This paper examines gamma survey as a tool for decommissioning NORM sites and provides an overview of current gamma survey technology designed to improve the efficiency and effectiveness of the decommissioning process. Topics to be discussed in the paper include: - An overview of gamma survey systems, and the utility of different delivery vehicles depending on desired cost, desired spatial resolution, and site topography. - The influence of physical detector characteristics on detection sensitivity and survey planning. - The tradeoff between high-resolution and large spatial extent, but inherently uncertain data, and low-resolution, low spatial extent, but highly certain data, as well as the specific utility of each of these types of data during NORM facility decommissioning. - Confounding variables that may limit the utility of gamma survey at some sites (e.g., radon gas and spatial heterogeneity / hot spots), and methods to plan for and control these conditions. Results show that the confounding variables, such as radon and data output can greatly influence the overall data quality associated with the decommissioning process. In addition, the use of real-time and aerial survey platforms provides a method for ensuring proper spatial extent of the data. When applied thoughtfully, gamma survey is a powerful tool for detecting NORM radionuclides in the environment and a cost-effective technique for identifying areas requiring remediation. However, entities performing or using gamma survey as a decommissioning tool must be aware of both its advantages and its limitations before basing remediation or regulatory action on gamma survey results. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Heterogeneous isotope effects decouple conifer leaf and branch sugar δ 18 O and δ 13 C

Isotope ratios of tree-ring cellulose are a prominent tool to reconstruct paleoclimate and plant responses to environmental variation. Current models for cellulose isotope ratios assume a transfer of the environmental signals recorded in bulk leaf water to carbohydrates and ultimately into stem cellulose. However, the isotopic signal of carbohydrates exported from leaf to branch may deviate from mean leaf values if spatial heterogeneity in isotope ratios exists in the leaf. We tested whether the isotopic heterogeneity previously observed along the length of a ponderosa pine (Pinus ponderosa) leaf water was preserved in photosynthetic products. We observed an increase in both sugar and bulk tissue δ 18 O values along the needle, but the increase in carbohydrate δ 18 O values was dampened relative to the trend observed in leaf water. In contrast, δ 13 C values of both sugar and bulk organic matter were invariant along the needle. Additionally, phloem-exported sugar measured in the branch below the needles did not match whole-needle values of δ 18 O or δ 13 C. Instead, there was a near-constant offset observed between the branch and needle sugar δ 13 C values, while branch δ 18 O values were most similar to δ 18 O values observed for sugar at the base of the needle. The observed offset between the branch and needle sugar δ 18 O values likely arises from partial isotope oxygen exchange between sugars and water during phloem loading and transport. An improved understanding of the conditions producing differential δ 13 C and δ 18 O isotope effects between branch phloem and needle sugars could improve tree-ring-based climate reconstructions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Methane emission hotspots in a boreal forest-fen mosaic potentially linked to deep taliks

Permafrost thaw is transforming boreal forests into mosaics of wetlands and drier uplands. Topographic controls on hydrological and ecological conditions impact methane (CH 4 ) fluxes, contributing to uncertainty in local and regional CH 4 budgets and underlying drivers. The objective of this study was to explore CH 4 fluxes and their drivers in a transitioning boreal forest-fen ecosystem (Goldstream Valley, Alaska, USA). This landscape is characterized by thawing discontinuous permafrost and heterogeneous mosaics of fens, collapse-scar channels, and small mounds of permafrost soils. From a survey in July 2021, observed chamber CH4 fluxes included fen areas with intermediate to very high emissions (29.8–635.3 mg CH 4 m −2 d −1 ), clustered locations with CH 4 uptake (−2.11 to −0.7 mg CH 4 m −2 d −1 ), and three anomalous emission hotspots (342.4–772.4 mg CH 4 m −2 d −1 ) that were located near samples with lower emissions. Some surface and near-surface variables partially explained the spatial variation in CH 4 flux. Log-transformed CH 4 flux had a positive linear relationship with soil moisture at 20 cm depth ( R 2 = 0.31, p -value < 1e-5) and negative linear relationships with microtopography ( R 2 = 0.13, p -value < 0.006) and slope ( R 2 = 0.28, p -value < 2e-5). Methane emissions generally occurred in flat, wet, graminoid-dominated fens, whereas CH 4 uptake occurred on permafrost mounds dominated by feather mosses and woody vegetation. However, the CH 4 hotspots occurred on drier, slightly sloped locations with low or undetectable near-surface methanogen abundance, suggesting that CH 4 was produced in deeper soils. When the hotspot samples were omitted, log-transformed CH 4 flux had a positive linear relationship with near-surface methanogen abundance ( R 2 = 0.29, p -value = 0.0023), and stronger linear relationships with soil moisture, slope, and soil macronutrient concentrations. Our findings suggest that some CH 4 emission hotspots could arise from CH 4 in deep taliks. The inference that methanogenesis occurs in deep taliks was strengthened by the identification of intrapermafrost taliks across the study area using low-frequency geophysical induction. This study assesses surface spatial heterogeneity in the context of subsurface permafrost conditions and highlights the complexity of CH 4 flux patterns in transitioning forest-wetland ecosystems. To better inform regional CH 4 budgets, further research is needed to understand the spatial distribution of terrestrial CH 4 hotspots and to resolve their surface, near-surface, and subsurface drivers.

boreal↗

NASA NTRS2023

The Spatial Distribution of Soluble Organic Matter and Their Relationship to Minerals in the Asteroid (162173) Ryugu

We performed in-situ analysis on a ~1 mm-sized grain A0080 returned by the Hayabusa2 spacecraft from near-Earth asteroid (162173) Ryugu to investigate the relationship of soluble organic matter (SOM) to minerals. Desorption electrospray ionization-high resolution mass spectrometry (DESI-HRMS) imaging mapped more than 200 CHN, CHO, CHO–Na (sodium adducted), and CHNO soluble organic compounds. A heterogeneous spatial distribution was observed for different compound classes of SOM as well as among alkylated homologues on the sample surface. The A0080 sample showed mineralogy more like an Ivuna-type (CI) carbonaceous chondrite than other meteorites. It contained two different lithologies, which are either rich (lithology 1) or poor (lithology 2) in magnetite, pyrrhotite, and dolomite. CHN compounds were more concentrated in lithology 1 than in lithology 2; on the other hand, CHO, CHO–Na, and CHNO compounds were distributed in both lithologies. Such different spatial distribution of SOM is likely the result of interaction of the SOM with minerals, during precipitation of the SOM via fluid activity, or could be due to difference in transportation efficiencies of SOMs in aqueous fluid. Organic-related ions measured by time-of-flight secondary ion mass spectrometry (ToF–SIMS) did not coincide with the spatial distribution revealed by DESI-HRMS imaging. This result may be because the different ionization mechanism between DESI and SIMS, or indicate that the ToF–SIMS data would be mainly derived from methanol-insoluble organic matter in A0080. In the Orgueil meteorite, such relationship between altered minerals and SOM distributions was not observed by DESI-HRMS analysis and field-emission scanning electron microscopy, which would result from differences of SOM formation processes and sequent alteration process on the parent bodies or even on the Earth. Alkylated homologues of CHN compounds were identified in A0080 by DESI-HRMS imaging as observed in the Murchison meteorite, but not from the Orgueil meteorite. These compounds with a large C number were enriched in Murchison fragments with abundant carbonate grains. In contrast, such relationship was not observed in A0080, implying different formation or growth mechanisms for the alkylated CHN compounds by interaction with fluid and minerals on the Murchison parent body and asteroid Ryugu.

Ryugu↗

DOE OSTI2023

Spatial and temporal variation in forest transpiration across a forested boreal peatland complex

Transpiration is a globally important component of evapotranspiration. Careful upscaling of transpiration from point measurements is thus crucial for quantifying water and energy fluxes. In spatially heterogeneous landscapes common across the boreal biome, upscaled transpiration estimates are difficult to determine due to variation in local environmental conditions (e.g., basal area, soil moisture, permafrost). Here, we sought to determine stand-level attributes that influence transpiration scalars for a forested boreal peatland complex consisting of sparsely treed wetlands and densely treed permafrost plateaus as land cover types. The objectives were to quantify spatial and temporal variability in stand-level transpiration, and to identify sources of uncertainty when scaling point measurements to the stand-level. Using heat ratio method sap flow sensors, we determined sap velocity for black spruce and tamarack for 2-week periods during peak growing season in 2013, 2017 and 2018. We found greater basal area, drier soils, and the presence of permafrost increased daily sap velocity in individual trees, suggesting that local environmental conditions are important in dictating sap velocity. When sap velocity was scaled to stand-level transpiration using gridded 20 × 20 m resolution data across the ~10 ha Scotty Creek ForestGEO plot, we observed significant differences in daily plot transpiration among years (0.17–0.30 mm), and across land cover types. Daily transpiration was lowest in grid-cells with sparsely treed wetlands compared to grid-cells with well-drained and densely treed permafrost plateaus, where daily transpiration reached 0.80 mm, or 30% of the daily evapotranspiration. When transpiration scalars (i.e., sap velocity) were not specific to the different land cover types (i.e., permafrost plateaus and wetlands), scaled stand-level transpiration was overestimated by 42%. To quantify the relative contribution of tree transpiration to ecosystem evapotranspiration, we recommend that sampling designs stratify across local environmental conditions to accurately represent variation associated with land cover types, especially with different hydrological functioning as encountered in rapidly thawing boreal peatland complexes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Data-Driven Insights into the Structural Essence of Plasticity in High-Entropy Alloys

The heterogeneous mechanical response of a crystalline alloy with multiple principal elements was investigated using molecular dynamics simulations. The local configuration of the alloy in its quiescent state was characterized by the variables derived from the gyration tensor and the atomic electronegativity. A multivariate analysis identified the geometric and chemical factors that influenced the atomic packing variations. Further, upon straining, the non-affine displacement exhibited spatial heterogeneity. A statistical correlation was established between the local yield events and the specific features of the local configuration. Our findings, validated by the performance metrics analysis, provided a structural criterion for the instability mechanisms in high-entropy alloys (HEAs) and enhanced the understanding of their plasticity.

36 MATERIALS SCIENCE↗