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At least 235 records · Page 13

A 13‐Year Record Indicates Differences in the Duration and Depth of Soil Carbon Accrual Among Potential Bioenergy Crops

Six years after replacing a maize/soybean cropping system, perennial grasses miscanthus (Miscanthus × giganteus) and switchgrass (Panicum virgatum), and a 28-species restored prairie increased particulate organic carbon in surface soils without increasing soil organic carbon (SOC). To resolve potential changes in the quantity and distribution of SOC, soils were resampled after seven to thirteen years to measure bulk density, carbon (C) content, and stable C isotopes to a depth of 1 m. SOC stocks increased between 1.75 and 2.5 Mg ha −1 year −1 in all perennial crops between 2008 and 2016 (nine growing seasons). Despite relatively low litter inputs and belowground biomass, the highest rate of SOC accrual was in restored prairie (2.5 Mg ha −1 year −1 ), followed by miscanthus (2.0 Mg ha −1 year −1 ) and switchgrass (1.75 Mg ha −1 year −1 ). The change in SOC in maize/soybean was not significant. After 2016, total SOC decreased in maize/soybean and miscanthus, resulting in slower overall rates of SOC accumulation over the full sampling period for miscanthus (0.8 Mg ha −1 year −1 ). The rate of SOC accumulation was greatest below 50 cm depth for restored prairie and switchgrass but in the top 10 cm for miscanthus. Stable isotope analysis showed 13 C enrichment in all depths of switchgrass soils, an indication of new organic C accumulation, but mixed results in all other crops. Planting perennial crops on land formerly in an annual maize/soybean cropping system can slow or reverse soil carbon losses, with the greatest increases in SOC from species-rich prairie.

agriculture↗

Flexural strength of a conventionally processed and additively manufactured debased 94% alumina

Mechanical strength of a 94 wt% debased alumina was measured using ASTM-C1161 specimens fabricated via conventional and lithography-based ceramic manufacturing (LCM) methods. The effects of build orientation and a 1500°C wet hydrogen fire added to the LCM firing sequence on strength were evaluated. Additionally, a Weibull fit to the conventional flexural specimen data yielded 20 and 356 MPa for the modulus and characteristic strength, respectively. Weibull fits of the data from the LCM specimens yielded moduli between 7.5 and 11.3 and characteristics strengths between 333 and 339 MPa. A Weibull fit to data from LCM specimens subjected to the wet hydrogen fire yielded 14.2 and 376 MPa for the modulus and characteristic strength, respectively. The 95% confidence intervals for all Weibull parameters are reported. Average Archimedes bulk densities of LCM and conventional specimens were 3.732 and 3.730 g/cm 3 , respectively. Process dependent differences in surface morphology were observed in scanning electron microscope (SEM) images of specimen surfaces. SEM images of LCM specimen cross-sections showed alumina grain texture dependent on build direction, but no evidence of porosity concentrated in planes between printed layers. Fracture surfaces of LCM and conventionally processed specimens revealed hackle lines and mirror regions indicative of fracture initiation at the sample surface rather than the interior.

36 MATERIALS SCIENCE↗

On the bulk compaction of brittle granular materials, part I: SeS analysis of axial compression to 4000 MPa

The bulk compaction of granular materials has been studied for decades to interpret and manage responses for soils and powder-based component fabrication, and geophysical, celestial, and ballistic impact. Their bulk or macroscopic compaction response is limited by what occurs at the granular or microstructural scale. Motivation existed to more closely examine that association specific to granular brittle materials (e.g., ceramics and glasses). That examination is offered in a series of three companion papers where Part I describes a new supplemental analysis adopted to bulk compaction response involving relatively high compaction stresses (4000 MPa). Bulk compactions of vitreous silicates and crystalline quartzes were interpreted in three ways, including that of a new analysis that considers the product of void ratio (e) and stress (S) as a function of S, hereafter referred to as “SeS analysis”. In conclusion, the SeS analysis was found to be an informative supplement to conventional bulk compaction analyses because it provides more consistent higher sensitivity for the identification of bulk density rate increase with increasing compaction (softening); a rate increase that arises from the cumulative effect of the onsets and progression of compaction-induced yielding, fracture or comminution, densification, phase change, or combinations thereof occurring at the granular or microstructural scale.

compaction↗

Exploring limitations in the induced polarization versus surface conductivity relationship in the case of wetland soils

Recent induced polarization studies suggest that the real part of surface conductivity (σ' surf ) scales linearly with the imaginary conductivity (σ'' = σ'' surf ) or normalized chargeability (Mn) for a range of soil types. The coefficients of this relationship l and l_Mn ( l = σ''/σ' surf or l_Mn = Mn/σ' surf ) allow the separation of the surface and electrolytic conductivities from the bulk conductivity. However, the dependence of these constants on varying soil physicochemical properties, including under unsaturated conditions, is yet to be assessed. Using estimates of σ' surf from 18 undisturbed soil samples from a restored wetland and σ'' measured over a frequency range of 0.01 Hz to 10 kHz, the σ' surf and σ'' were compared with the laboratory measurements of soil properties. Also, l and l_Mn were calculated for each soil sample and regressed them against the soil properties. We find an apparent dependence of l on soil texture, bulk density, organic matter, and moisture contents, with coefficients of determination (R 2 ) ranging from 0.5 to 0.65 at low frequencies (e.g., 1 Hz) but not at high frequencies (e.g., 936 Hz). This dependence of l on soil texture results from the insensitivity of σ'' at low frequency to σ' surf and, by implication, to the soil properties controlling σ' surf . In contrast, l_Mn indicates no correlation with the soil properties because Mn is linearly correlated with σ' surf and correlated with the soil properties controlling σ' surf . Finally, our results call for caution on the application of σ'' at a single frequency as a proxy of σ' surf because σ'' is not necessarily correlated with σ' surf across all soil types. Although using l_Mn derived from multifrequency measurements overcomes this limitation, field acquisition of spectral information (e.g., up to 1000 Hz) remains a challenge.

54 ENVIRONMENTAL SCIENCES↗

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗

Epoxy Coating of Biofiber: An Effective Modifier of Biofiber Physical and Flow Properties for Improved Tensile Behavior of Biofiber-Reinforced Biocomposite

Biocomposites combine renewable, plant-based fibers with degradable polymers and are an attractive option for sustainable, lightweight, and cost-effective materials with a low carbon footprint, especially for large-scale additive manufacturing. One of the major challenges in the widespread adoption of biocomposites is that their mechanical performance is significantly inferior to that of synthetic composites. Surface treatment is a common and effective technique to improve the mechanical properties of the biofibers used in biocomposites. This study aims to investigate the physical and flow properties of surface-treated biofibers, as well as the tensile properties of their PLA-based biocomposite, to gain insights into how surface treatment changes the fiber‘s characteristics and biocomposite‘s mechanical properties. Surface treatment was created using a two-component epoxy system by reacting poly(bisphenol A-co-epichlorohydrin) glycidyl end-capped (PBG) and dicyandiamide (DICY). The treatment was tested on two different biofibers (loblolly pine and corn stover fibers) with three different PBG/DICY molar ratios (0.25, 0.5, and 2). Results showed that surface-treated fibers improved the tensile strength and Young‘s modulus of the biocomposites. Loblolly pine biocomposites from fibers treated with a PBG/DICY ratio of 0.25 exhibited the best tensile properties. The surface treatment resulted in a more loosely dispersed fiber bulk structure, as evidenced by less fiber agglomeration into smaller particle sizes, higher fiber sphericity, and lower loose bulk density. This can enhance stress distribution and the overall mechanical performance of the biocomposites. Additionally, surface-treated fibers exhibited better dynamic flow properties.

36 MATERIALS SCIENCE↗

Intraspecific variability in plant and soil chemical properties in a common garden plantation of the energy crop Populus

Optimizing crops for synergistic soil carbon (C) sequestration can enhance CO 2 removal in food and bioenergy production systems. Yet, in bioenergy systems, we lack an understanding of how intraspecies variation in plant traits correlates with variation in soil biogeochemistry. This knowledge gap is exacerbated by both the heterogeneity and difficulty of measuring belowground traits. Here, we provide initial observations of C and nutrients in soil and root and stem tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes—established for aboveground biomass-to-biofuels research. Our goal was to explore the value of such field sites for evaluating genotype-specific effects on soil C, which ultimately informs the potential for optimizing bioenergy systems for both aboveground productivity and belowground C storage. To do this, we investigated variation in chemical traits at the scale of individual trees and genotypes and we explored correlations among stem, root, and soil samples. We observed substantial variation in soil chemical properties at the scale of individual trees and specific genotypes. While correlations among elements were observed both within and among sample types (soil, stem, root), above-belowground correlations were generally poor. We did not observe genotype-specific patterns in soil C in the top 10 cm, but we did observe genotype associations with soil acid-base chemistry (soil pH and base cations) and bulk density. Finally, a specific phenotype of interest (high vs low lignin) was unrelated to soil biogeochemistry. Our pilot study supports the usefulness of decade-old, genetically-variable, Populus bioenergy field test plots for understanding plant genotype effects on soil properties. Finally, this study contributes to the advancement of sampling methods and baseline data for Populus systems in the Pacific Northwest, USA. Further species- and region-specific efforts will enhance C predictability across scales in bioenergy systems and, ultimately, accelerate the identification of genotypes that optimize yield and carbon storage.

54 ENVIRONMENTAL SCIENCES↗

Nutrient and carbon concentrations in dated soil cores at US-OWC Ameriflux wetland site (OWC NERR)

Soil cores were sampled at the Old Woman Creek (OWC) National Estuarine Research Reserve at the south shore of Lake Erie, near Huron, Ohio, USA. OWC is a temperate mineral soil marsh. We dated the soil cores using lead isotope analysis and measured the concentrations of carbon and nutrients (nitrogen, phosphorus) throughout the core depths. We analyzed 36 cores, sampled along three transects at areas of the wetland with different hydrological regimes. Each transect included three coring sites at different water depth categories (shallow, intermediate deep) with four core samples per coring site. The data can be used to determine the carbon sequestration rates and nutrient accumulation rates, at multiple locations throughout OWC wetland.Dataset, in csv format, with data variables in columns, and different cores and core depths slices in rows, includes results from 36 sediment cores (0-30 cm depth) taken at 9 locations (4 replicates at each location) along 3 gradients of water depth (shallow, intermediate, deep), each at a different hydrologic location (outflow, backflow, middle). At each depth slice within a core, we provide depth, date (using 210Pb), bulk density, and the concentrations of carbon, nitrogen, phosphorus, d13C, and d15N.

54 ENVIRONMENTAL SCIENCES↗

Substantial and overlooked greenhouse gas emissions from deep Arctic lake sediment - supporting data and code

This data package contains data, descriptions, and code-based analyses that were used to support conclusions drawn in “Substantial and overlooked greenhouse gas emissions from deep Arctic lake sediment”, by Freitas et al. (2025) (https://doi.org/10.1038/s41561-024-01614-y). The study evaluated greenhouse gas production along a deep sediment core (20 m) taken in 2018 from below Goldstream Lake, a field site approximately 15 km north of Fairbanks, Alaska.The file “ESSDive_NFreitas_2024_flmd.csv” includes an overview of all other csv files in this data package, namely: sediment descriptions (depth and type of sediment), sediment characterizations (bulk density, gravimetric water content, total carbon, etc.), calculated respiration and temperature sensitivity values associated with year-long incubations of the sediment core, and the R code used to process the dataset. Additional details regarding the content of these files and how the calculations were performed are described in the Methods section of this archive. The “data_dictionary_ESSDive_NFreitas_2024_dd.csv” is a data dictionary for all files included in the data package. Each row in the data dictionary represents a column name in a given file. 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).Data package updates- August 2024: Title was updated, R code now includes a process for calculating potential production across the whole sediment column, the "sediment_column_production_potentials_ESSDive_NFreitas_2024.csv" is the associated data output file, and the file level metadata and data dictionaries were updated to reflect the contents of the additional csv file.- October 2024: Title was updated, and a statement was added to Step 2 of the Methods that describes that samples were collected (and exported) in a responsible manner and in accordance with relevant permits and local laws.- January 2025: Updated the associated manuscript details in the Abstract (manuscript title, publication date, DOI link) and in the Related References section (full citation).

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes from topsoils collected during NEON campaign in East River, CO (06/14/2018-06/28/2018)

The Watershed Function Science Focus Area (WF SFA) at Lawrence Berkeley National Lab is working to build a mechanistic understanding of the distribution and dynamics of biogeochemical processes in mountainous watersheds and their response to perturbation. In June 2018, the NEON (National Ecological Observatory Network) Airborne Observatory Platform (AOP) performed a taskable airborne imaging campaign to collect visible to shortwave infrared (VSWIR) imaging spectroscopy and LiDAR data across 330 km2 in the Upper East River at Crested Butte, CO. We conducted a parallel ground sampling campaign to sample vegetation traits, as well as soil physical, chemical, and microbiological characteristics. We collected these samples from 438 sites across 12 locations spanning much of the elevation, topographic, and geologic variability across the study area. A subset of 250 samples were used for soil metagenomics which is presented here. In addition, at each site, vegetation samples were collected to measure species-specific leaf water content and leaf mass area, foliar elemental composition and foliar CN stable isotope ratios. Soil samples were collected to measure soil physical properties which include bulk density and soil texture analysis. A suite of soil chemical properties was measured from the samples collected at each site, including pH, organic matter, concentrations exchangeable cations, total elemental composition, and the concentrations of extractable N pools (e.g. total free amino acids, ammonium, nitrate, dissolved organic N, and total dissolved N). Additionally, we have measured soil microbial biomass CN stoichiometry. Here, we present 1982 metagenome-assembled genomes (MAGs) for the bacterial and archaeal community from topsoil collected from during NEON 2018 campaign. All metagenomes were sequenced at JGI (Joint Genome Institute) (GOLD Study ID: Gs0149986). Metagenomes were assembled using JGI Metagenome Workflow (10.1128/mSystems.00804-20). The dataset includes (1) zip files for 1982 MAG fasta files (neon_genomes1-5.tar.gz, split into 5 tarballs to keep tarballs under 0.5 GB), (2) neon_Gs0149986_samples_soilproperties_metagenomes.csv: the sample information together with the accession numbers for the underlying metagenomes and the associated soil physical and chemical measurements in NMDC (National Microbiome Data Collaborative) compliant format, (3) neon_Gs0149986.kml: location bounding box file for the sampled locations, (4) samples.csv: sample metadata file used to register Internationall Generic Sample Numbers (IGSNs), (5) flmd.csv: file level metadata file, and (6) dd.csv: data dictionary file. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

Meteoric 10Be Flux Calibration Data for the East River Watershed, Colorado, USA

This data package contains tabular and geospatial data used to quantify and model meteoric beryllium-10 fluxes in the East River watershed, Colorado, USA. The tabular component includes calibration-site data from five glacial moraine sites and includes environmental variables used to evaluate spatial controls on meteoric 10Be delivery, including elevation, mean annual precipitation (MAP), mean snow depth, and mean snow water equivalent (SWE). These site-level data were used to compare observed fluxes with environmental gradients across the watershed and to evaluate the effects of erosion correction on flux estimates. The package also includes supporting slope and curvature values used to assess topographic inputs to the erosion analysis. A second component of the data package contains updated manuscript tables and regression outputs used to summarize the relationships between meteoric 10Be flux and environmental predictors. These tables include meteoric 10Be sample information and AMS results, site-level environmental values, site-level meteoric 10Be inventory and flux values, watershed-averaged predicted fluxes, soil bulk density measurements, fine-fraction values, soil pH measurements, and regression statistics including slope, intercept, coefficient of determination, and p-value. The regression products include both standard linear regressions and regressions in which the intercept is constrained to pass through zero, and they support the analyses presented in the companion manuscript. Together, these tabular files provide the numerical basis for the manuscript tables and the regression-based interpretation of meteoric 10Be flux variability in a snow-dominated mountain watershed. The geospatial component of the package consists of GeoTIFF raster files used to generate the map products presented in Figures 2 and 6 of the companion manuscript. These rasters represent watershed-scale spatial layers for environmental variables and regression-based predictions of meteoric 10Be flux. This dataset contains comma-separated values files (.csv), Microsoft Excel files (.xlsx), GeoTIFF raster files (.tif), and upporting metadata files, including CSV data dictionaries and readme text files (.csv, .txt). The tabular files can be opened with standard spreadsheet software, and the raster files can be viewed and analyzed in GIS software such as ArcGIS Pro or QGIS. Together, these files document the numerical and spatial datasets used to calibrate and predict meteoric 10Be delivery in the East River watershed.

East River↗

Soil carbon stocks from soil organic carbon at the Teller 47, Teller 27, and Kougarok 86 field sites, Seward Peninsula, Alaska, 2021 – 2023

Carbon stored in permafrost soils represents the largest terrestrial storage and hence has key significance for the global carbon cycle, yet the site-specific estimates of permafrost soil carbon are limited. To better understand permafrost carbon storage, soil organic content (SOC) was measured from soils collected at the Teller 27, Teller 47, and Kougarok 86 field sites on the Seward Peninsula, Alaska in the summers of 2019 and 2021-2023. Soil samples were collected from locations with and without near-surface permafrost to varied depths within the permafrost, where present. In addition to sample collection for soil organic carbon analysis, bulk density samples were also collected within each soil profile to allow for calculation of carbon stocks. Carbon to nitrogen ratios are also reported. Location data were collected at each observation point using a handheld GPS unit with waypoint averaging to reduce location measurement error to within 3 m. SOC was measured using elemental analysis in the laboratory. This dataset contains a *.csv file of soil carbon stocks, a *.kml file of measurement locations, a *.pdf user guide, a *.csv data dictionary, and a *.csv file level metadata.

EARTH SCIENCE > CRYOSPHERE > FROZEN GROUND↗

Dated soil C–N–P profiles, water quality, and chamber fluxes across Ohio and Michigan wetlands (2024–2025)

This dataset includes dated soil core chemistry (bulk density, phosphorus, nitrogen and carbon concentrations), water quality, and chamber flux measurements collected from wetlands in the Midwest United States—12 sites in Ohio, one site in Indiana, one site in Michigan—collected in the spring or summer of 2024 or 2025, all in (.csv) format. These data were generated to examine how wetland restoration, management activities, and time since restoration affect biogeochemical processes, carbon sequestration, nutrient accumulation, water quality, and greenhouse gas emissions. Specifically, these data aim to investigate how restored wetlands differ from natural wetlands in terms of carbon, nitrogen, phosphorus dynamics, as well as carbon dioxide and methane fluxes. Also included are surface and porewater quality parameters and chamber flux measurements across these different wetlands. Sampling was conducted at various sites representing a range of restoration stages, from about 4 years post-restoration up to 105 years post-restoration, and also includes a natural wetland used as a reference in Michigan. These data can be used to determine carbon sequestration rates, nutrient cycling, and to enhance our understanding of biogeochemical responses to wetland restoration in temperate ecosystems. This data package contains (1) a csv file (Water_Quality.csv) containing water quality data (dissolved organic carbon, total dissolved nitrogen, and temperature) organized by location; (2) a csv file (Soil_C_N_P_Seq.csv) containing carbon, nitrogen, and phosphorus concentrations at each soil level and time of each soil level, as well as their sequestration rates; (3) a csv file (CH4_CO2_Flux.csv) including methane and carbon dioxide fluxes that were measured with a chamber; (4) a file-level metadata (FLMD.csv) file that lists each file contained in the dataset with associated metadata; (5) a data dictionary (DD.csv) file that contains terms/column headers used throughout the files along with a definition, units, and data type; and (6) a locations metadata file (Location_metadata.csv).

Earth Science > Atmosphere > Atmospheric Chemistry↗

Vadose Zone Flow and Transport Parameters Data Package for the Hanford Site Composite Analysis

This report provides a description of the basis for the development and implementation of a conceptual model for vadose zone flow and transport for the Hanford Site composite analysis (CA) groundwater pathway analysis. The parameterization for a numerical model is intimately linked to the conceptual model framework. This report describes the basis for the selection of hydraulic and transport parameters for the hydrostratigraphic units (HSUs) identified in the 200 East and 200 West Areas. The following three-step process was used to develop the hydraulic properties and transport parameters for the CA modeling: 1. Breakdown of existing database on hydraulic properties by HSUs 2. Constitutive model parameters for laboratory, core-scale hydraulic properties 3. Upscaling for macroscopic, field-scale flow, and transport parameters This document provides data and information on the following items: A brief description and technical basis for the conceptual model selected to represent vadose zone flow and transport for the CA modeling. Variation in sediment particle size distribution for representative sites in the 200 East and West Areas. A summary of effective (upscaled) moisture retention, and saturated and unsaturated hydraulic conductivity estimates for the HSUs in the 200 East and West Areas. A summary of effective transport parameters, including sediment bulk density and macrodispersivity estimates for various HSUs. The 200 East Area B Complex perched water aquifer hydraulic properties

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Hydraulic Properties Data Package for the E-Area Soils, Cementitious Materials, and Waste Zones–Update

Hydraulic property estimates for the soils, cementitious materials, and waste zones associated with the E-Area low-level radioactive waste disposal units have been provided to support the Performance Assessments (PA) for the E-Area Low-Level Waste Facility (LLWF). Nominal or “best estimate” hydraulic property values for use in the deterministic modeling are provided along with representations of the hydraulic property value uncertainty for use in sensitivity and uncertainty modeling. The hydraulic properties provided for each of the E-Area materials include: porosity ( η ), dry bulk density ( ρ b ), particle density (ρ p ), saturated hydraulic conductivity ( K sat ), characteristic curves (suction head, saturation, and relative permeability), and effective diffusion coefficient ( D e ). A representation of the uncertainty associated with each property, except for the characteristic curves, is provided for each material, except for the E-Area waste zones. These nominal parameter values for each of the E-Area soils, cementitious materials, and waste zones, and, where indicated, parameter uncertainty representations, are based upon the following in order of priority: Site-specific field data, Site-specific laboratory data, Similarity to material with site-specific field or laboratory data, and Literature data. Additionally, a methodology to represent long-term concrete degradation is provided. Finally, because much of the nominal hydraulic property values and uncertainty representations for the E-Area soils, cementitious materials, and waste zones are based on similarity to other materials or literature data, a methodology to prioritize additional work to better define these values and representations is outlined. Prioritization should be based on the importance of the material and/or property to the results of deterministic, sensitivity, and uncertainty modeling. This prioritization should be established through a process of sensitivity modeling. This report supersedes the previous hydraulic properties data package. Revision 1 contains clarifications, updates and corrections to text, figures and tables in a number of places in the report along with some minor editing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Implementing an aerosol dynamic shape factor for cerium oxide powder

The shape factor (X B ) of bulk powder CeO 2 (cerium oxide) particles is estimated to be X B = 1.34 (dimensionless). This is defined in relation to the measured aerated bulk density (0.91 g cm -3 , Hosokawa Micron, Summit NJ, 2018) of the CeO 2 powder. This information is used to determine the RRF (respirable release factor), and other parameters during drop test experiments of nuclear material storage containers at Los Alamos National Laboratory. The calculation is based on an experimental shape factor (X P = 2.66 dimensionless) for CeO 2 particles of the same (chain aggregate) morphology studied by other researchers. In that work, the shape factor was defined in terms of the maximum possible (compacted) density of CeO 2 material (7.13 g cm -3 ).

61 RADIATION PROTECTION AND DOSIMETRY↗

Radionuclide Screening Analysis and Transport Parameters for Pahute Mesa Detonations, Nevada National Security Site

A “screening analysis” is implemented at Pahute Mesa (PM), Nevada National Security Site (NNSS), to determine subsets of the 43 radionuclides listed in the radionuclide inventory of Finnegan et al. (2016) that are of relevance or potential relevance to the hydrologic source term (HST) for assessment of radionuclide transport in groundwater. Consideration is added to how levels of contamination are defined and whether any other radionuclides not in the inventory are relevant to the HST. A model is developed to estimate a range of possible source concentrations in groundwater that account for uncertainty in partitioning into melt glass and sorption into surrounding rock of the exchange zone for the 82 PM underground nuclear tests detonated in vertical shafts. The model also accounts for the varied hydrogeochemical settings. Transport parameters needed for the screening model calculations are developed from databases for hydrogeologic units, chemistry, mineralogy, fracture spacing, fracture aperture, fracture openness, matrix porosity, bulk density, saturation, and alteration. Of key importance is consideration of diagenetic zonation of the mineralogy related to hydrothermal alteration. The screening analysis compares model results with available groundwater radiochemistry data. Consistency between screening model results and available data helps validate the model for application to all 43 radionuclides, most of which have no measurements or only non-detect measurements of concentration in groundwater. The screening analysis determines that ten radionuclides – tritium, Sr-90, I-129, Cs-137, U-232, U-233, U-234, U-238, and the total of Pu-239 and Pu-240 are relevant to the HST. Determination of relevance is primarily based on data and/or model results indicating source concentration exceeding a maximum contaminant level (MCL) out to 100 years since the time of detonation. U-238 is relevant to assessment of contamination relative to MCLs for uranium and gross alpha particle activity. Five other radionuclides – C-14, Cl-36, Tc-99, Np-237, and Pu-238 – are determined potentially relevant to the HST based on a 0.1 MCL threshold. The screening analysis recommends additional attention to the natural daughter radionuclides of the uranium series (U-238) and thorium series (Th-232) decay chains, particularly Ra-226 and Ra-228, that were not included the inventory.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗