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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Examining the Reactions of Ethanolamine’s Thermal Degradation Compounds in Carbon Capture through 1 H NMR and 13 C NMR

In amine scrubbing carbon capture, concerns about amine solvent degradation include whether it can affect the ability of the solvent to capture CO 2 . This study examines the interactions between the three most reported monoethanolamine (MEA) thermal degradation compounds namely, oxazolidine-2-one (OZD), N-(2-hydroxyethyl)-ethylenediamine (HEEDA), and N-(2- hydroxyethyl)-imidazoline-2-one (HEIA) with CO 2 in the presence and absence of MEA. We compared 1 H NMR, 13 C NMR, and heteronuclear single-quantum coherence (HSQC) NMR for neat OZD, HEEDA, and HEIA samples with CO 2 -loaded samples to observe changes in protonation and unique carbamate species formation. We found that OZD and HEIA did not directly react with CO 2 or undergo proton shifting based on our comparison of the neat OZD and HEIA samples with CO 2 -loaded spectra. However, we observed that the OZD can protonate when sparged with CO 2 in the presence of MEA, which suggests that the OZD acts as an intermediate. The NMR spectra for HEEDA indicated that HEEDA directly reacts with CO 2 at both amino groups and can protonate. In the presence of MEA, HEEDA and MEA can act like a solvent blend, resulting in multiple carbamates forming within the solvent. The neat HEIA spectrum, compared with CO 2 -loaded HEIA spectra, revealed similar results as OZD, where it does not react with CO 2 or protonate directly. However, HEIA does not protonate in the presence of MEA. These degradation compound reactions can increase the number of general equilibrium reactions during carbon capture and impact the model MEA solvent. This work helps provide a more complete picture of the reactions as the solvent degrades. Although this study examines CO 2 effects on thermal degradation products for MEA, other amines such as piperazine or 1- amino-3-propanol will degrade, and the degradation may speciate similarly with CO 2 . Furthermore, this study can impact and improve process models by assessing the degradation compounds’ reactions with CO 2 and potentially incorporating them into the model based on a neat solvent.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Cycloalkane-rich sustainable aviation fuel production via hydrotreating lignocellulosic biomass-derived catalytic fast pyrolysis oils

Sustainable aviation fuel (SAF) produced from lignocellulosic biomass is emerging as an ideal alternative to conventional jet fuel for aviation sector decarbonization. Catalytic fast pyrolysis (CFP) can convert lignocellulosic biomass into relatively stable bio-oil that can be selectively transformed to various transportation fuels through hydroprocessing under conditions of different severities. In this contribution, two CFP oils produced from pine-based feedstocks over different types of catalysts (i.e., ZSM-5 and Pt/TiO 2 catalysts) were hydrotreated at 125 bar in a non-isothermal process with a maximum temperature of 385 °C over a sulfided NiMo/Al 2 O 3 catalyst to produce SAF with high cycloalkane concentrations of 89–92 wt%. Cycloalkanes are an important component of jet fuel with advantageous fuel properties, such as high energy density, low sooting, and potential for replacing aromatic hydrocarbons to provide good seal swelling properties. The hydrotreating process successfully converted 91–92% of the biogenic carbon in the CFP oil intermediates to liquid-phase hydrotreated products. Through distillation, 39–40 wt% of the hydrotreated oils were collected in the jet-fuel range as SAF fractions. The rest of the hydrotreated product could be valorized as fuels (e.g., diesel) or chemicals. The SAF fractions with oxygen contents below the detection limit (<0.01 wt%) met ASTM D7566 finished fuel blend and D4054 Tier 1 specifications with respect to density, lower heating value (LHV), volatility, flash point, and freeze point. These results indicate hydrotreating lignocellulosic biomass-derived CFP oil as a promising pathway to produce high-quality SAF rich in cycloalkanes. Continued research is required to increase the SAF yield by process improvements, such as increased CFP oil yields, and an enhanced production of SAF-range molecules via e.g., cracking of high-molecular weight compounds either during CFP or hydrotreating, as well as evaluation of a broader range of jet fuel properties and performance requirements.

09 BIOMASS FUELS↗
DOE OSTI2024

Security constrained optimal power shutoff for wildfire risk mitigation

Abstract Electric grid faults are increasingly the source of ignition for major wildfires. To reduce the likelihood of such ignitions in high risk situations, utilities use preemptive de‐energization of power lines, commonly referred to as Public Safety Power Shutoffs (PSPS). Besides raising challenging trade‐offs between power outages and wildfire safety, PSPS removes redundancy from the network at a time when component faults are likely to happen. This may leave the network particularly vulnerable to unexpected line faults that may occur while the PSPS is in place. Previous works have not explicitly considered the impacts of these outages. To address this gap, the Security Constrained Optimal Power Shutoff problem is proposed which uses post‐contingency security constraints to model the impact of unexpected line faults when planning a PSPS. This model enables, for the first time, the exploration of a wide range of trade‐offs between both wildfire risk and pre‐ and post‐contingency load shedding when designing PSPS plans, providing useful insights for utilities and policy makers considering different approaches to PSPS. The efficacy of the model is demonstrated using the EPRI 39‐bus system as a case study. The results highlight the potential risks of not considering security constraints when planning PSPS and show that incorporating security constraints into the PSPS design process improves the resilience of current PSPS plans.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Dephasing of ion beams as magnetic vortex acceleration regime transitions into a bubble-like field structure

The interaction of an ultra-intense laser pulse with a near critical density target results in the formation of a plasma channel, a strong azimuthal magnetic field and moving vortices. An application of this is the generation of energetic and collimated ion beams via magnetic vortex acceleration. The optimized regime of magnetic vortex acceleration is becoming experimentally accessible with new high intensity laser beamlines coming online and advances made in near critical density target fabrication. The robustness of the acceleration mechanism with realistic experimental conditions is examined with three-dimensional simulations. Of particular interest is the acceleration performance with different laser temporal contrast conditions, in some cases leading to pre-expanded target profiles prior to the arrival of the main pulse. Preplasma effects on the structure of the accelerating fields are explored, including a detailed analysis of the ion beam properties and the efficiency of the process. Improved scaling laws for the magnetic vortex acceleration mechanism, including the laser focal spot size effects, are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Low damping (111) oriented lithium aluminum ferrite thin films for spin wave applications

Spin wave-based spintronics are an alternative to conventional electronics due to their potential for efficient energy consumption, improved processing speed, and smaller device dimensions. Low damping magnetic insulators provide the medium for efficient propagation of spin waves for information transfer. Here, we have synthesized by pulsed laser deposition epitaxial spinel structure ferrite thin films of Li 0.5 (Al 1.0 Fe 1.5 )O 4 (LAFO) on (111)-oriented MgAl 2 O 4 that support isotropic magnon propagation in the film plane. Our ferromagnetic resonance measurements show low magnetic damping with a typical Gilbert damping parameter of α = 0.006 and weak-spin–orbit coupling with g = 2.02. These films have low effective magnetization, μ o M eff = 20 mT, similar to that of yttrium iron garnet, the gold standard of low loss magnetic insulators. Our findings show that LAFO is a good candidate as a spin wave medium since it can be grown at low temperatures in different crystal orientations.

Takana, Lerato [Stanford Univ., CA (United States)↗
DOE OSTI2024

DESI Early Data Release Milky Way Survey value-added catalogue

We present the stellar value-added catalogue based on the Dark Energy Spectroscopic Instrument (DESI) Early Data Release. The catalogue contains radial velocity and stellar parameter measurements for $\simeq$ 400 000 unique stars observed during commissioning and survey validation by DESI. These observations were made under conditions similar to the Milky Way Survey (MWS) currently carried out by DESI but also include multiple specially targeted fields, such as those containing well-studied dwarf galaxies and stellar streams. The majority of observed stars have $16\lt r\lt 20$ with a median signal-to-noise ratio in the spectra of $\sim$ 20. In the paper, we describe the structure of the catalogue, give an overview of different target classes observed, as well as provide recipes for selecting clean stellar samples. We validate the catalogue using external high-resolution measurements and show that radial velocities, surface gravities, and iron abundances determined by DESI are accurate to 1 km s −1 , 0.3 dex, and $\sim$ 0.15 dex respectively. We also demonstrate possible uses of the catalogue for chemo-dynamical studies of the Milky Way stellar halo and Draco dwarf spheroidal. The value-added catalogue described in this paper is the very first DESI MWS catalogue. The next DESI data release, expected in less than a year, will add the data from the first year of DESI survey operations and will contain approximately 4 million stars, along with significant processing improvements.

Galaxy: general↗
DOE OSTI2026

Enhanced antineutrino emission from 𝛽 decay in core-collapse supernovae with self-consistent weak decay rates

Nuclear weak-interaction rates are known to exert a prominent effect in the late stages of stellar collapse. Despite their importance, most studies to date on core-collapse supernovae (CCSNe) have focused primarily on the effects of electron captures, neglecting 𝛽 decay contributions. In this work, we present the first CCSNe simulation incorporating global 𝛽 decay rates from a microscopic theory. These are enabled by a large-scale evaluation of both electron capture and 𝛽 decay rates, obtained self-consistently utilizing the relativistic energy density functional theory and finite-temperature quasiparticle random-phase approximation. Including 𝛽 decay leads to a dramatic enhancement of the pre-bounce antineutrino signal as the antineutrino emissivity increases by more than two orders of magnitude and the luminosity by a factor of 50 relative to thermal emission alone, while the average antineutrino energy increases by over 1 MeV. Furthermore, it is expected that these new rates could help us constrain the model uncertainties related to weak-interaction processes, improving the prediction of antineutrino signal during the final stages of stellar death.

Beta decay↗
DOE OSTI2025

BuildingSync® v.2.7.0 (released 9.11.2025) [SWR-18-28]

BuildingSync® is a building data exchange schema to better enable integration between software tools and building data workflows. The schema's original use case was focused on commercial building energy audits; however, several additional use cases have been realized including building energy modeling and more high-level generic building data exchange. Version 2.7.0 adds new elements for file attachment feature and FederalBuilding, and generalizes usage of Optional Elements (e.g. EquipmentCondition, EquipmentID) to all assets/systems. BuildingSync helps streamline the data exchange process, improving the value of the data, minimizing duplication of effort for subsequent building data collection efforts (including audits), and facilitating the achievement of greater energy efficiency. This in done in part by standardizing on (a) reporting audits in an electronic format, (b) tracking proposed, implemented, and discarded energy conservation measures, and (c) storing building characteristics (at multiple levels) for audits, benchmarking, and building energy analysis. BuildingSync has several documents and tools available to help users understand how to best leverage BuildingSync. The list below are only a subset of the resources available. If new resources are discovered, then feel free to create a new pull request with the additions. Generic BuildingSync information is available on the DOE website and the project website. BuildingSync Examples - These examples are kept up to date and show a wide range of implementations. Any new update to BuildingSync is required to pass validation on these example files. BuildingSync Use Case Validator allows for users to determine if their instance complies with a specific use case for BuildingSync by checking if the required elements are implemented in an uploaded instance. An API is also provided for automated integration into other tools. Also, the website contains an easy way to view the entirety of the schema and how elements relate to the Building Exchange Data Exchange Specification. The Validator is open sourced here Use Case TestSuite provides a Python package for easier generation of BuildingSync use cases. BuildingSync use cases depend on the generation of schematron documents, which is time-consuming and difficult to implement well. The TestSuite allows users to define a use case using a more palatable CSV template, which it then turns into a Schematron document. The source code is available here. BuildingSync to OpenStudio/EnergyPlus. The translator is open sourced here. This project will translate a Level 1 (and partial Level 2) ASHRAE Energy Audit to a fully defined OpenStudio and EnergyPlus model. This project is in early Beta testing and any feedback is welcome!

Long, Nicholas [National Renewable Energy Lab. (NR↗
DOE OSTI2024

Enhancing monolignol ferulate conjugate levels in poplar lignin via OsFMT1

The phenolic polymer lignin is one of the primary chemical constituents of the plant secondary cell wall. Due to the inherent plasticity of lignin biosynthesis, several phenolic monomers have been shown to be incorporated into the polymer, as long as the monomer can undergo radicalization so it can participate in coupling reactions. In this study, we significantly enhance the level of incorporation of monolignol ferulate conjugates into the lignin polymer to improve the digestibility of lignocellulosic biomass. Overexpression of a rice Feruloyl-CoA Monolignol Transferase (FMT), OsFMT1, in hybrid poplar (Populus alba x grandidentata) produced transgenic trees clearly displaying increased cell wall-bound ester-linked ferulate, p-hydroxybenzoate, and p-coumarate, all of which are in the lignin cell wall fraction, as shown by NMR and DFRC. We also demonstrate the use of a novel UV–Vis spectroscopic technique to rapidly screen plants for the presence of both ferulate and p-hydroxybenzoate esters. Lastly we show, via saccharification assays, that the OsFMT1 transgenic poplars have significantly improved processing efficiency compared to wild-type and Angelica sinensis-FMT-expressing poplars. The findings demonstrate that OsFMT1 has a broad substrate specificity and a higher catalytic efficiency compared to the previously published FMT from Angelica sinensis (AsFMT). Importantly, enhanced wood processability makes OsFMT1 a promising gene to optimize the composition of lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2024

Active Layer Depth and Permafrost Temperatures at the Teller 47 Field Site, Seward Peninsula, Alaska, 2022

With extreme climate warming in the Arctic, there is increasing focus on mapping permafrost stability and improving understanding of the impacts of thawing permafrost. Summer active layer depths and temperatures at the top of the permafrost were collected at the Teller 47 field site on the Seward Peninsula, Alaska to better understand permafrost thermal state in areas of discontinuous permafrost. Measurements were taken between August 14th and August 20th, 2022. Active layer depths were measured with a 120 cm thaw probe, and temperature measurements were taken with a SpotOn Temperature probe at the top of permafrost and at a maximum depth of XYZ, when no near-surface permafrost (within 120 cm of the surface) was present. Measurements were co-located with ground surface displacement measurements, which can be found in the associated dataset, NGA254. Precise location data were collected at each observation point using a GNSS RTK GPS unit. This dataset contains a *.csv file of permafrost temperature and active layer depths and a *.kml file of measurement locations.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

NGEE Arctic 2019 Alder Ground Truth Survey, Seward Peninsula AK

In July 2019 we made traveled the road system outside of Nome, AK and detailed the GPS coordinates of alder shrublands for the purpose of ground-truthing alder maps of the region. Both visual and ground-based observations were made for patches of alder shrublands greater 5x5m and larger, ideally 10x10m. Visual observations were made from the car and GPS coordinates are approximate, placed by dropping pins on georeferenced pdfs using the Avenza app. Visual observations included positive identified alder shrublands as well as thickets of non-alder shrubs. Ground Observations were made at a subset of locations where we were able to hike to alders shrubland areas. Ground observations include GPS points (made with Garmin InReach) as well as relevant features of a centrally located, representative alder shrub in the patch (max height, basal diameter of all ramets, soil depth). Aboveground biomass (weight dry mass) of the surveyed shrub was calculated based on alder-specific allometric equations in Berner et al 2015 which our team checked for accuracy for the Seward Peninsula as part of Salmon et al 2019. This dataset contains three data files, three data dictionaries, and one file-level metadata file all in*.csv format plus one *.txt README 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).

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 OSTI2024

Aqueous Organic Matter from Kougarok Fire Complex, Alaska, 2023

Chemical analyses of aqueous organic matter extracted by filtration from a small set of organic layer samples collected from burned and unburned tussock tundra sites in the Kougarok Fire Complex, near Nome, Alaska. 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 OSTI2024

Sun-induced chlorophyll fluorescence/eddy covariance measurements at NGEE Arctic Council site, Seward Peninsula, Alaska, 2022

Sun-induced chlorophyll fluorescence (SIF) is emitted from the chlorophyll antenna complexes during the light harvesting and photophysical reactions of photosynthesis. It is directly coupled with and therefore can be used to estimate photosynthetic electron transport and CO2 assimilation. SIF, when observed at the ecosystem level, provides information about ecosystem functions that complements the net ecosystem exchange (NEE) of CO2, CH4, water vapor, and sensible heat. NEE observations have been conducted with the eddy covariance (EC) approach at the NGEE Arctic Council, Alaska site for years. However, concurrent SIF observations have not been available. In June 2022, we installed the fluorescence automated measurement equipment (FAME) at the NGEE Arctic Council site. The zip file contains 3,187 *.dat files that can be opened with a text editor or in *.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 OSTI2025

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.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

NDVI and Multispectral Images, UAS Flights, Council Road Site, Seward Peninsula, Alaska, June 2022

The dataset contains Normalized Difference Vegetation Index (NDVI) and multispectral images collected on June 18, 2022 using an UAS (Unmanned Aerial System) Yuneec H520, Mapir Survey 3, and Parrot Sequoia cameras. This data was created to accompany the following datasets:- NGEE Arctic CO2, CH4 and Energy Eddy-Covariance (EC) Flux Tower Auxiliary Measurements, Council Road Mile Marker 71, Seward Peninsula, Alaska (https://doi.org/10.5440/1526749)- Sun-induced chlorophyll fluorescence/eddy covariance measurements at NGEE Arctic Council site, Seward Peninsula, Alaska, 2022 (https://doi.org/10.15485/2466175)- NGEE Arctic Meteorological Data from Instrumented PCDC Stations, Council Site, Seward Peninsula, Alaska, 2018 - 2023 (https://doi.org/10.5440/1529604)Survey 3 is RGN (Red, Greeen, Near Infra Red) camera with 87° Horizontal Field of View (HFOV) (19mm) f/2.8 Aperture, 550nm/660nm/850nm (Red+Green+NIR) filter transmission and produced geo referenced jpg and raw format images. Parrot Sequoia is a camera with 16 megapixel RGB (Red, Green, Blue) sensor and 1.2 megapixel monochrome sensors in discrete spectral bands: Green (550nm - 40Nm Bandwidth), Red (660nm - 40nm Bandwidth), Red Edge (735nm - 10nm Bandwidth) and Near Infrared (790nm - 40nm Bandwidth).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

The Pan-Arctic Vegetation Cover (PAVC) database v1.1

The Pan-Arctic Vegetation Cover (PAVC) database contains synthesized field-data observations of vegetation cover from 978 Arctic Alaska plots with observations from 2010 to 2021. The cover datasets contain plot data at both the plant functional type (PFT) and species-level resolution, with standardized PFT definitions and species names. We synthesized publicly available point-intercept and visual estimate plots from the Arctic Vegetation Archive of Alaska, the Alaska Vegetation Plots Database, the North Slope Science Catalog, and the National Ecological Observatory Network; as well as previously unpublished data from the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic).Users will find four synthesized datasets, 4 associated data descriptor (dd) files, and 1 metadata file in the PAVC database:synthesized_species_fcover.csv contains fractional cover (fcover) for unique accepted species names, where names include vegetation identified at the family, genus, species, subspecies, and variety levels, as well as general functional types across all 5 data sources. The synthesized_species_fcover_dd.csv accompanies this dataset with header information.synthesized_pft_fcover.csv contains fcover for the following PFTs: non-vascular plants with lichen and bryophyte subcategories, trees with deciduous and evergreen subcategories, shrubs with deciduous and evergreen subcategories, graminoids (grasses), and forbs (herbaceous flowering plants) measured as total cover. Litter and “other” cover are also included as total cover. Additional “types” include water and bare ground, which were measured as top cover. The synthesized_pft_fcover_dd.csv accompanies this dataset with header information.species_pft_checklist.csv is a lookup table containing the translation from a dataset species name to an accepted species name and to a PFT. This table can be used to clarify our species to PFT adjudications, and to aid users in assigning their own PFTs. Any issues found in this checklist should be reported in the Issues tab of our github.survey_unit_information.csv contains auxiliary information about the plots synthesized in this database. It contains useful information for filtering plots of interest based on temporal, geospatial, and contextual information about the plot surveys.flmd.csv contains metadata information about each file in the database.This research was performed as a part of the NGEE Arctic project. The NGEE Arctic project 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

Reference Shapefiles and Pre-trained Random Forest Classification Models for Detecting Aufeis on the North Slope of Alaska in Landsat Imagery

This dataset provides shapefiles and trained machine learning models used for aufeis detection at four sites on the North Slope of Alaska. It includes reference data for evaluating Landsat-based detection methods, supporting research on remote sensing approaches for identifying aufeis. The ReferenceData folder contains ArcGIS shapefiles of semi-automated land cover classifications for 217 Landsat Collection 2 images, categorizing pixels into six classes: aufeis, snow, ground, none, water, and cloud. The SiteBuffers.zip file includes 10-kilometer buffer shapefiles defining regions of interest around four aufeis fields (Canning21, FH1, Firth, and Kuparuk), used to test three detection techniques. Additionally, the TrainedRFModels folder contains six pre-trained Scikit-Learn Random Forest classifiers (100 trees, max depth = 30) designed to predict aufeis presence in Landsat Collection 2 Surface Reflectance images using Red, Blue, SWIR2, NDVI, and NDWI bands. This dataset supports the development and validation of remote sensing methods for mapping aufeis in Arctic environments.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↗