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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Leaf Nitrogen, Leaf Mass Area, Leaf Water Content, Seward Peninsula, Alaska, 2017

Nitrogen and carbon content, leaf mass per area and leaf water content of leaves sampled from the NGEE Arctic Teller study site, Seward Peninsula, Alaska in 2017. Data is included for 13 species from the deciduous shrub, forb and graminoid plant functional types. See related dataset for leaf reflective spectra, sample photographs and dGPS locations. This data package includes leaf sample information and trait data (*.csv). Note that leaf nitrogen content analysis was performed on a subset of samples. Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA103_flmd.csv. 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

Surface elevation, snow depth, vegetation height, and color imagery from multiple UAV surveys from 2018 to 2023 across a watershed near Teller road mile marker 27, Seward Peninsula, Alaska

Multiple photogrammetric surveys using an unoccupied aerial system (UAS) were performed across a watershed along Teller road on the Seward Peninsula (Alaska) to investigate terrain, vegetation and snowpack properties. This work was led by the environmental geophysics team from Lawrence Berkeley National Laboratory as part of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). The multiple photogrammetric surveys used mostly a DJI Matrice 210 UAS with a DJI X5S camera, Ground Control Points (GCPs) surveyed with a Real Time Kinematic (RTK)-GPS, and a structure from motion (SfM) technique for photogrammetric reconstruction. Digital Surface elevation Models (DSMs) were inferred at various times of year, including near peak in plant and leaf density (July 19 2017), close to peak in snow depth (April 1 2019 and April 11 2022), and at low plant and leaf density of tall after the first bare-ground date (June 9 2019). Snow and canopy height were obtained by subtracting DSMs from a Digital Terrain Model (DTM) proxy inferred from the June 9 2019 survey. The derived products include ortho-mosaiced RGB map, DSMs, a DTM proxy, snow depth (April 2019 and 2022) and canopy height (July 2017). Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.csv), image (*.jpg), and GeoTiff (*.tif) formats. This metadata document contains a description of the survey and processing steps and the inferred products.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) 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

Continuous snow depth, ground interface temperature and shallow soil temperature measurements from 2021-10-1 to 2022-6-14, Seward Peninsula, Alaska

The dataset contains co-located snow depth, ground interface temperature, and shallow soil temperature measured at 98 discrete locations in a watershed located along the Nome-Teller road at mile marker 27 (referred to as T27), and at 53 discrete locations on a hillslope located along the Kougarok road at mile marker 64 (referred to as K64), in Seward Peninsula, Alaska. The dataset aims to understand the local heterogeneity of snow depth, snow temperature, and soil temperature dynamics and their interactions in a discontinuous permafrost region. The dataset is also valuable to train and evaluate machine learning and physical models to predict snow depth or the impact of snow depth on ground surface temperature. At each location, temperatures above and below the ground surface were measured by a pair of vertically deployed distributed temperature profiling probes designed based on Dafflon et al (2022). The probes have high precision temperature sensors spaced at 5 or 10 cm. The mean daily snow depth was estimated by identifying the pair of consecutive sensors with maximum drop of daily temperature high-frequency fluctuations. The ground interface temperature was measured by the sensor located 1-5 cm above the ground surface at 15-minute intervals. The shallow soil temperature was measured by the sensor located 1-5 cm below the ground surface at 15-minute intervals. The dataset includes a description of the probe locations in the "Probe_locations_*.csv" file and the 3 data files (Snow_depths_*.csv, Ground_interface_temperatures_*.csv, Shallow_soil_temperatures_*.csv). * is either T27 or K64, which are the two study sites. In each data file, each column corresponds to a measurement location. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv. A more detailed description of data processing, along with an updated dataset incorporating multiple seasons and improved snow depth estimation is available at https://doi.org/10.15485/2480365 (Wang et al., 2025a, Wang et al., 2025b).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

Visible to near-infrared spectral reflectance along the NGEE-Arctic tram transect, Utqiagvik (Barrow), Alaska, 2015-2018

Canopy spectral reflectance collected measured in 2015-2018 along the NGEE-Arctic tram located on the Barrow Environmental Observatory (BEO), Barrow, Alaska. Measurements were made using a PP-Systems UniSpec-DC spectrometer mounted on an automatically operated instrument cart. Spectra were collected at 137 stop points at 0.5 m intervals along the tram transect. Transect runs were collected daily, or multiple times per day, from April or May through to August or September each year. Downwelling radiance was measured using a 2 meter fiber optic cable connected to a cosine diffuser. Upwelling (i.e. reflected) radiance was measured using a 2 meter cable connected to a 12 degree field-of-view (FOV) lens. Canopy reflectance was calculated using the ratio of upwelling to downwelling radiance measured over a 99.99% reflectance Spectralon standard measured at the start of each measurement set. Unprocessed spectral data are presented in .spu files. Metadata are provided in csv files, and the instrument manual (pdf). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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 OSTI2023

UAS remote sensing (3DR SOLO platform): multispectral reflectance and normalized difference vegetation index, Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using a Parrot Sequoia+ multispectral sensor installed on a 3DR SOLO unoccupied aerial system (UAS) – operated by the Terrestrial Ecosystem Science & Technology group https://www.bnl.gov/envsci/testgroup/ at Brookhaven National Laboratory. This package includes data from 19 flights flown over the NGEE-Arctic, Kougarok Mile Marker (MM) 80, Kougarok Fire Complex (KFC) and Teller MM 27 sites in July 2022. Derived image products include point cloud, ortho-mosaiced multispectral image, a digital surface model (DSM) using the structure from motion (SfM) technique, and a normalized difference vegetation index (NDVI) map. Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.txt, *.json, *hdr,), tabular (*.dat, *.csv), point cloud (*.laz), Cloud Optimized GeoTIFF (COG, *.tif), and image (*.jpg, *.tif, *png) formats.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 OSTI2025

COMPASS-FME Synoptic Sites Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-0 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), 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

Shrub Seedling Experiment: Environmental Conditions, Vegetation Composition, and Seedling Recruitment, Seward Peninsula, Alaska, 2018-2019

In June 2018, a manipulative seed-addition experiment was established at the Council Mile Marker 71 (CN_MM71), Quartz Creek Burn Area (Kougarok Mile Marker 86), and Quartz Creek Unburned (Kougarok Mile Marker 80) sites on the Seward Peninsula, Alaska. At each site, 5 replicate blocks were established in disturbed and intact upland tussock tundra (a total of 40 plots). Disturbed plots at Council were located on thermo-erosional (thermokarst) slopes, while disturbed plots in Quartz Creek were in burned areas affected by the Mingvk Lake fire in 2015. Using a split-plot design, an additional manual disturbance treatment (scraping to remove the surface bryophyte layer) was implemented across all blocks in June 2018. Seeds of five erect, deciduous shrubs were broadcast seeded into each plot in June 2018, and seedlings were censused in August 2018 and August 2019. The dataset includes ancillary measurements of plot-level environmental conditions (soil temperature, moisture, chemistry, thaw depth, microtopography, substrate thickness) and vegetation composition (NDVI and estimated percent cover by species and plant functional type). Dataset contains 10 csv data files (five data files with corresponding data dictionaries and one file-level metadata file) and one pdf user guide. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was 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

Canopy reflectance spectra and photographs (raw data), Seward Peninsula, Alaska, 2022

Measurements of full-range (350–2500 nm) canopy spectral reflectance of Arctic plant species, plots, and transects at the Next Generation Ecosystem Experiment Arctic (NGEE Arctic) Teller Mile Marker (MM27) and Kougarok Fire Complex (KFC) sites, Seward Peninsula, Alaska. Spectra were collected in July 2022 using a handheld SVC HR-2014i spectroradiometer. All spectra were collected as calibrated surface radiance and converted to surface reflectance using 99.99% reflective Spectralon white reference standard. This data package includes unprocessed instrument output of the spectra signals (.sig) and, for some canopy measurements, photographs of the target taken by the SVC instrument camera or handheld digital camera (.jpg), GPS locations and file metadata (.csv).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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 OSTI2022

Microstructural Characterization of the Second High Fluence Baffle-Former Bolt Retrieved from a Westinghouse Two-loop Downflow Type PWR

As one of the pressurized water reactor (PWR) internal components, baffle-former bolts (BFBs) are subjected to significant mechanical stress and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and reduced load-carrying capacity of the bolts. In support of evaluating long-term operational performance of materials used in core internal components, the Oak Ridge National Laboratory (ORNL), through the Department of Energy (DOE), Light Water Reactor Sustainability (LWRS) Program, Materials Research Pathway (MRP) has harvested two high fluence BFBs from a commercial Westinghouse two-loop downflow type PWR. The two bolts of interest, i.e. bolts # 4412 and 4416, were withdrawn from service in 2011 as part of a preventative replacement plan. No identification of cracking or potential damage was found for these bolts during their removal in 2011. However, the bolts required a lower torque for removal from the baffle structure than the original torque specified during installation. Irradiation displacement damage levels in the bolts range from 15 to 41 displacements per atom. The goal of this project is to perform detailed microstructural and mechanical property characterization of BFBs following in-service exposures. The information from these bolts will be integral to the LWRS program initiatives in evaluating end of life microstructure and properties. Furthermore, valuable data will be obtained that can be incorporated into model predictions of long-term irradiation behavior and compared to results obtained in high flux experimental reactor conditions. In this report, we present our latest study in FY22 on microstructural characterizations of the second high fluence baffle-former bolt, i.e., bolt # 4412. Analytical electron microscopy and atom probe tomography characterization were performed. The radiation-induced defects in the material add to the large wealth of knowledge for neutron-induced defects in 304/316 grades of stainless steels, specifically for radiation-induced precipitation after high fluence commercial PWR irradiation. The main findings are summarized as follows: 1) The cavity size was considerably larger in the bolt thread section than in the bolt head, with the bolt thread section having a bimodal distribution of cavities greater than ~6 nm in diameter and less than ~3 nm in diameter. The bolt head only had the small-sized cavities. In addition, there was a denuded zone of large cavities near grain boundaries in the thread section of the bolt. 2) Radiation-induced precipitation in the BFB #4412 was highly complex, with the volume fraction, size, and number density of Ni/Si and Cu-rich precipitates depending strongly on the radiation temperature/dose. In many cases, co-precipitates of adjoined clusters were found with Ni/Si-rich precipitates sandwiched between Cu-rich clusters and Mo/Cr/P-rich clusters. 3) Solute segregation out of solution was highest for most solutes in the thread section of the bolt #4412 with the exception of Cu, which experienced more separation out of solution into Curich clusters in the bolt head section. This highlights the difference in the mechanisms for precipitation of Ni/Si clusters, which have the Ni 3 Si phase composition, and precipitation of Cu-rich clusters. 4) There appear to be multiple simultaneous influences that affect the microstructural variation along the length of the bolt that overcomes the ~2X difference in irradiation dose between the bolt head and the bolt thread. The irradiation temperature, thermal/fast neutron ratio variation, potential strain gradient, and exposure to PWR coolant water that each section of the bolt sees may have more influence on the microstructural evolution than the total irradiation dose. The bolt thread and shank, with higher temperature, higher relative fast neutron flux, higher strain, and exposure to coolant but lower dose, underwent more enhanced cavity formation, precipitation, and solute segregation than the bolt head section.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Kinetic and temperature sensitivity properties of soil exoenzymes through the soil profile down to one-meter depth at a temperate coniferous forest (Blodgett, CA)

This dataset contains data on kinetic and temperature sensitivity parameters of the exoenzymes β-glucosidase (BG), leucine/leucyl aminopeptidase (LAP) and acid phosphatase (AP) across a soil profile down to 90 cm depth at Blodgett forest, CA, USA. These data were generated to determine if kinetic and thermal properties of microbial exoenzymes involved in organic matter decomposition varied with soil depth, following variation in soil properties and microbial communities, as part of the study: Alves et al. (2021). Kinetic Properties of Microbial Exoenzymes Vary with Soil Depth but Have Similar Temperature Sensitivities Through the Soil Profile. Frontiers in Microbiology 12:3618. https://doi.org/10.3389/fmicb.2021.735282. This research was performed within the framework of the TES Belowground Biogeochemistry SFA project, in particular association with a long-term field warming experiment of the whole soil profile at Blodgett forest. Samples for this work were collected from locations representative of the field experimental plots. Potential enzyme activity rates were measured using laboratory fluorometric assays with soils collected at 0-10, 10-20, 30-40, 50-60, 60-70 and 80-90 cm deep in biological triplicates (i.e., three soil cores collected at different representative locations). Assays with each soil were conducted over a gradient of eight substrate concentrations per enzyme, and incubated at 4, 10, 16, 25, 35 or 50°C. Enzyme Michaelis-Menten kinetics were modeled over the eight substrate concentrations at each temperature, and the temperature sensitivity of the kinetic parameters was modeled over the six temperatures using linear Arrhenius/Q10 and non-linear Macromolecular Rate Theory (MMRT) models. The dataset includes the fully processed enzyme activity rate data used to model Michaelis-Menten kinetics, calculated kinetic and temperature sensitivity parameters, and basic soil and microbial biomass chemistry for each sample. All data is provided for each individual biological replicate, and kinetic and temperature sensitivity parameters are also provided as means of the biological replicates. The dataset also includes all raw measurement data and code used to parse, combine and perform the analyses described by Alves et al. (2021). For file descriptions, see the file-level metadata files: “enzymes_dataProcessed_flmd.xlsx” (processed data); “enzymes_dataRaw_flmd.xlsx” (compressed raw data and metadata); and “enzymes_code_flmd.xlsx” (compressed code). The experimental design, list of parameters measured, soil and microbial biomass chemistry data, and means of biological replicates for kinetic and temperature sensitivity parameters are also provided as human-readable tables in file “enzymeTraits_design_results_tables.xlsx”.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

iButton snow temperature measurements at Teller 27 and Kougarok 64, Seward Peninsula, Alaska, 2019-2020

Snow temperature measurements were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) and at the Kougarok Road Site at mile marker 64 (KG_MM64) on the Seward Peninsula. Data were collected from October 1, 2021 to August 16, 2022 using iButton Link DS1926-F5# Thermochron miniature temperature sensors (https://www.ibuttonlink.com/products/ds1921g) and Tinytag TGP-4017 internal sensors (https://www.micronmeters.com/product/tgp-4017-internal-sensor-40-to-85-c-40-f-to-185-f) deployed across the Kougarok and Teller sites. These sensors are a cost-efficient way to collect snowpack temperatures at a higher spatial resolution than what is normally achieved. iButton data were collected every 4 hours beginning on October 1, 2021. Tinytag data collection began between October 9, 2021 and October 12, 2021 depending on the specific Tinytag and data were collected every 30 minutes. In total, data were collected from 236 iButtons and 30 Tinytags. This dataset contains four *.csv files of near-ground surface temperatures at various locations throughout each study site and four *.shp files of sensor locations. Data were collected throughout the snow cover season so that snowpack characteristics could be derived using the temperature data. Sensors were placed both inside and outside of vegetation to better capture the spatial variability of snow properties across each domain.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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 OSTI2025

Soil Core Chemistry of Wetland, Old Woman Creek National Estuarine Research Reserve, Huron, OH, 2023-10-24 to 2024-05-20

This dataset contains the chemistry data of soil samples collected from a wetland, referred to as The Cove, at Old Woman Creek Estuarine Research Reserve in Huron, OH. Soil core extractions were performed to analyze what nutrient and/or metal constituents were present at different depths and what biogeochemical activity this could indicate. Three soil cores were collected at three locations within The Cove. The soil cores were removed from their core tubing and were cut into 4 segments down the length (or depth) of the core: top to 1-inch deep, from 1 inch to 5 inches, 5 inches to 7 inches, and 7 inches to the bottom of the core (approximately 10 inches). These soils segments were each homogenized and sub-sampled for various chemical analyses. Soil chemistry measurements are reported in the SoilChem_DataTable.csv file. Collection information about the samples can be found within the SoilChem_SampleMetdata.csv file. All files associated with this dataset are listed in the SoilChem_FLMD.csv file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Organic layer thickness and carbon concentration in burned and unburned sites, Seward Peninsula, AK, 2022

Measurements associated with organic layer samples collected from naturally burned (1971, 2002, 2015, 2019) and unburned sites at the Kougarok Fire Complex, Seward Peninsula, AK, 2022. Here, a discontinuous permafrost underlies an arctic tundra ecosystem. Measurements include elemental carbon and nitrogen concentrations and stocks, organic layer thickness, and thaw depth. There are five files in *.csv format with one data file and four data description files including data dictionary, methods, terminology, and file-level metadata. 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 OSTI2025

PreSens Dissolved Oxygen and Temperature Data, Old Woman Creek National Estuarine Research Reserve, Huron, OH, 2022-07-06 to 2023-12-15

This dataset contains collected dissolved oxygen (DO) and temperature measurements of the air, surface water, and underlying soil of a wetland at Old Woman Creek Estuarine Research Reserve in Huron, OH. Dissolved oxygen and temperature measurements were made in the first few centimeters of wetland sediment to assess how oxygen profiles changed over time with hydrological events. Measurements taken outside of the sediment were taken as comparison. Measurements were taken by hand with a PreSens Fibox 4 transmitter, paired with an oxygen dipping probe and temperature sensor, at each field outing. Measurements were taken approximately every 2 weeks around 10 AM EST. The PreSens_DO_Temp_Datafile.csv contains the recorded measurements, and the PreSens_InstallationMethods.csv describes the deployment of the sensor.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

iButton and Tinytag snow temperature measurements at Teller 27 and Kougarok 64, Seward Peninsula, Alaska, 2021-2022

Snow temperature measurements were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) and at the Kougarok Road Site at mile marker 64 (KG_MM64) on the Seward Peninsula. Data were collected from October 1, 2021 to August 16, 2022 using iButton Link DS1926-F5# Thermochron miniature temperature sensors (https://www.ibuttonlink.com/products/ds1921g) and Tinytag TGP-4017 internal sensors (https://www.micronmeters.com/product/tgp-4017-internal-sensor-40-to-85-c-40-f-to-185-f) deployed across the Kougarok and Teller sites. These sensors are a cost-efficient way to collect snowpack temperatures at a higher spatial resolution than what is normally achieved. iButton data were collected every 4 hours beginning on October 1, 2021. Tinytag data collection began between October 9 and October 12, 2021 depending on sensor installation date. Tinytag data were collected every 30 minutes. In total, data were collected from 236 iButtons and 30 Tinytags. This dataset contains four *.csv files of near-ground surface temperatures at various locations throughout each study site and four *.shp files of sensor locations. Data were collected throughout the snow cover season so that snowpack characteristics could be derived using the temperature data. Sensors were placed both inside and outside of vegetation to better capture the spatial variability of snow properties across each domain. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), 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 OSTI2021

Experimental and modeling studies of PR and ND oxalate solubility to high ionic strengths: Insight into actinide(III) oxalates

Actinide oxalates are chemical compounds important to nuclear industry, ranging from actinide separation in waste reprocessing, to production of specialty actinides, and to disposal of high level nuclear waste (HLW) and spent nuclear fuel (SNF). In this study, the solubility constants for Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O by performing solubility experiments in HNO 3 and mixtures of HNO 3 and H 2 C 2 O 4 at 23.0 ± 0.2 °C have been determined. The targeted starting materials, Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O, were successfully synthesized at room temperature using PrCl 3 , NdCl 3 and oxalic acid as the source metrials. Then, we utilized the targeted solubility-controlling phases to conduct solubility measurements. There was no phase change over the entire periods of experiments, demonstrating that Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O were the solubility-controlling phases in our respective experiments. Based on our experimental data, we have developed a thermodynamic model for Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O in the mixtures of HNO 3 and H 2 C 2 O 4 to high ionic strengths. The model for Pr 2 (C 2 O 4 ) 3 •10H 2 O reproduces well the reported experimental data for Pu 2 (C 2 O 4 ) 3 •10H 2 O, which are not utilized for the model development, demonstrating that Pr(III) is an excellent analog for Pu(III). Similarly, the model for Nd 2 (C 2 O 4 ) 3 •10H 2 O reproduces the solubility of Am 2 (C 2 O 4 ) 3 •10H 2 O and Cm 2 (C 2 O 4 ) 3 •10H 2 O. The Pitzer model was used for the calculation of activity coefficients. Based on the published, well established model for dissociation constants for oxalic acid and stability constants for actinide-oxalate complexes [i.e., AmC 2 O 4 + , and Am(C 2 O 4 ) 2 - ] to high ionic strengths, we have obtained the solubility constants (log 10 K 0 ) for the following reactions at 25 °C, Pr 2 (C 2 O 4 ) 3 •10H 2 O ⇌ 2Pr 3+ + 3C 2 O 4 2- + 10H 2 O(l). Nd 2 (C 2 O 4 ) 3 •10H 2 O ⇌ 2Nd 3+ + 3C 2 O 4 2- + 10H 2 O(l). to be -30.82 ± 0.30 (2σ), and - 31.14 ± 0.35 (2σ), respectively. These values for can be directly applied to Pu 2 (C 2 O 4 ) 3 •10H 2 O, Am 2 (C 2 O 4 ) 3 •10H 2 O and Cm 2 (C 2 O 4 ) 3 •10H 2 O. The model established for actinide oxalates by this study provides the needed knowledge with regard to solubilities of actinide/REE oxalates at various ionic strengths, and is expected to find applications in many fields, including the geological disposal of nuclear waste and the mobility of REE under the surface conditions, as Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O can be regarded as the pure Pr and Nd end-members of deveroite, a recently discovered natural REE oxalate with the following stoichiometry, (Ce 1.01 Nd 0.33 La 0.32 Pr 0.11 Y 0.11 Sm 0.01 Pb 0.04 U 0.03 Th 0.01 Ca 0.04 ) 2.01 (C 2 O 4 ) 2.99 •9.99H 2 O. Regarding its importance in the geological disposal of nuclear waste, Am 2 (C 2 O 4 ) 3 •10H 2 O/Pu 2 (C 2 O 4 ) 3 •10H 2 O/Cm 2 (C 2 O 4 ) 3 •10H 2 O can be the source-term phase for actinides, as demonstrated by the instance in the disposal in clay/shale formations. This is exemplified by the stability of Am 2 (C 2 O 4 ) 3 •10H 2 O in comparison with Am(OH) 3 (am), Am(OH) 3 (s) and AmCO 3 (OH)(s) under the relevant geological repository conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Site-specific Design Case Study for Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels

Hydrothermal liquefaction (HTL) is a thermal process that converts wet biomass to renewable hydrocarbon fuel blendstocks (i.e., renewable naphtha, renewable diesel, and sustainable aviation fuel (SAF)). It can utilize a wide range of pure and blended wet feedstocks, including sewage sludge from water resource recovery facilities (WRRF), food and agriculture wastes, algae, fats, oils and greases (FOG) and blends of dry and wet wastes/feedstocks. Historically, techno-economic analysis (TEA) and annual state of technology (SOT) assessments with standard economic assumptions used by the Bioenergy Technologies Office (BETO) were conducted for the wet waste HTL pathway leveraging experimental data collected from Pacific Northwest National Laboratory’s (PNNL) continuous flow reactor systems. The objective of the SOT assessment has been to guide and track progress of BETO’s HTL research and development (R&D) toward reduced cost and greenhouse gas (GHG) emissions for the pathway. However, gaps exist between BETO’s traditional SOT updates and the needs of key external stakeholders that – if addressed – will accelerate technology adoption. This Business Case Study aims to bridge this gap by providing an updated design, TEA, and LCA based on PNNL’s FY23 R&D with added analyses and information that provide enhanced relevance for stakeholders of the HTL technology. This includes specific siting, regional wet waste resource inventory and transportation cost analyses, fuel market information, sustainable fuel policy impacts, economic metrics of net present value (NPV) and internal rate of return (IRR), greenhouse gas (GHG) emissions analysis, and statistical analysis of cost and technical uncertainties of the HTL plant design. The study focuses on the “Detroit combined statistical area (CSA)” region for siting of a wet waste HTL plant adjacent to the Great Lakes Water Authority (GLWA) facility with guidance from industry participants. Regional resource and siting analyses were conducted to identify feedstock availability, scale, and cost, as well as a beneficial site location. TEA with detailed rigorous capital cost estimation for the specific site application was conducted to evaluate the key economic metrics of most value to industrial partners. These include total capital investment, operating costs, minimum fuel selling price (MFSP) of the biocrude and fuel blendstock, and NPV and internal rate of return IRR with sustainable fuel credits. Life cycle analysis was conducted to evaluate the supply chain greenhouse gas (GHG) emissions for the wet waste HTL process as compared with petroleum derived diesel. This study is also informed by years of R&D and process de-risking learnings and was conducted with a basic engineering HTL plant design and costing that akin to a “first-of-a-kind” plant economics. This differs from our conventional “nth plant ” SOT assessments. Specifically, the HTL process model has been updated with more operationally reliable methods for feed heating and phase separations. Further, we have implemented additional spare equipment for redundancy, a more rigorous installed equipment cost estimation approach, and additional costs associated with feed formatting and delivery, building, piping and site development. An Excel-based cost sheet based on the basic engineering design is also released alongside the report that allows users to conduct customized TEA with their own feed composition and financial assumptions.

09 BIOMASS FUELS↗