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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 OSTI2022

A Review of Technologies that can Provide a 'Root of Trust' for Operational Technologies

The supply chain attack pathway is being increasingly used by adversaries to bypass security controls and gain unauthorized access to sensitive networks and equipment (e.g., Critical Digital Assets). Cyber-attacks targeting supply chain generally aim to compromise the environments, products, or services of vendors and suppliers to inject, add, or substitute authentic software and hardware with malicious elements. These malicious elements are deemed to be authentic as they arise from the vendor or supplier (i.e., the supply chain). This research aims at providing a survey of technologies that have the potential to reduce exposure of sensitive networks and equipment to these attacks, thereby improving tamper resistance. The recent advances in the performance and capabilities of these technologies in recent years has increased their potential applications to reduce or mitigate exposure of the supply chain attack pathway. The focus being on providing an analysis of the benefits and disadvantages of smart cards, secure tokens, and elements to provide root of trust. This analysis provides evidence that these roots of trust can increase the technical capability of equipment and networks to authenticate changes to software and configuration thereby increasing resilience to some supply chain attacks, such as those related to logistics and ICT channels, but not development environment attacks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Advanced Ab Initio Methods for Nuclear Structure (Final Report)

Over the past decade, there has been enormous progress in the description of nuclear structure from first principles, using interactions from Chiral Effective Field Theory that are rooted in Quantum Chromodynamics, the fundamental theory of strong interactions, and many-body methods that solve the Schrödinger equation with systematically improvable approximations. Amongst those are the family of In-Medium Similarity Renormalization Group (IMSRG) framework developed by the PI and his co-workers. While these methods scale polynomially in the size N of the single-particle basis, computational efforts still grows dramatically as we increase the degrees of freedom for the nucleons by relaxing symmetries or introducing continuum couplings (see below), or as we push to improved truncations to provide precise inputs for experimental efforts, in particular in fundamental symmetry searches. In order to address this growing computational cost, one focus area of this award was the exploration of compression and factorization methods. The key to success or failure is the presence of low-rank structures within the matrix elements of NN and 3N interactions or the IMSRG evolution operator, and a means to reformulate the method that will let us exploit them.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Body surface area equations for physically active men and women

Abstract Objectives To improve predictive formulae for estimating body surface area (BSA) in healthy men and women using a modern three‐dimensional scanner technology. Methods Body surface areas were obtained from a convenience sample of 1267 US Marines (464 women and 803 men) using a whole body surface scanner (Size Stream SS20). The reliability of SS20 measures of total and regional BSA within participants was compared across triplicate scans. We then derived a series of formulae to estimate SS20‐measured BSA using various combinations of sex, height, and mass. We also assessed relationships between percent body fat measured by dual‐energy x‐ray absorptiometry and sex‐specific formulae errors in Marines. Results Body surface areas recorded by the SS20 were highly reliable whether measured for the total body or by region (ICC ≥ .962). Formulae estimates of BSA from sex, height, and mass were precise (root‐mean‐square deviation, 0.031 m 2 ). Errors from the Marine Corps formulae were positively associated with percent body fat for men ( p = .001) but not women ( p = .843). Conclusions Clinicians, military leaders, and researchers can use the newly developed BSA formulae for precise estimates in healthy physically active men and women. Users should be aware that height‐ and mass‐based BSA estimates are less accurate for individuals with extremely low or high percent body fat.

Looney, David P.↗
DOE OSTI2022

Predicting spring green-up across diverse North American grasslands

Vegetation phenology influences many ecosystem and climate processes, such as carbon uptake and energy and water cycles. Thus, understanding drivers of vegetation phenology is crucial for predicting current and future impacts of climate change on ecological systems. Existing models can accurately predict the date of spring green-up in temperate forests but tend to perform poorly in grassland systems. We hypothesize this is because most do not incorporate water availability, a primary limiting factor for grassland plants. In this study, we used long-term datasets of digital imagery from the PhenoCam Network of 43 diverse North American grassland sites (195 site-years) to test existing spring phenology models, as well as develop several new models that incorporate precipitation or soil moisture (53 models). As a result, most of the new models performed substantially better, with the best model requiring sufficient accumulated precipitation followed by warm temperatures to trigger spring onset (root mean square error, RMSE, between predicted and observed dates = 16.0 days). Importantly, the best model performed well across all grassland types using a single set of parameters, from temperate to arid grasslands. Since plants are adapted to their local climates, model performance was further improved when parameters were independently optimized for four separate climate regions (RMSE = 10.4 days). Therefore, both sufficient precipitation and temperature are required for grassland green-up, but optimal thresholds vary by region. Running the top model with projected climate data (representative concentration pathway 8.5) suggests that, depending on the climate region, spring onset will occur up to 12 days earlier within 100 years in temperature-limited sites, but the trend is unclear for precipitation-limited sites (3.5 ± 8.0 days later). This new phenology model improves our ability to understand and predict grassland dynamics, with implications for both current and future ecosystem processes related to carbon and water cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗
DOE OSTI2023

LA100 Equity Strategies. Chapter 4: Lessons Learned and Options for Community Engagement in Los Angeles

The LA100 Equity Strategies project synthesizes community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. Grounded in the analysis of past and ongoing energy inequities and engagement with underserved communities, the project presents community-guided strategies that aim to operationalize recognition and procedural justice. Building on the community-identified problems and solutions, and the analysis of the 11 strategies described in Chapter 3, this chapter continues to focus on the solution space through the lens of recognition and procedural justice. It centers the role of community engagement in energy utility planning and project development with a specific focus on how the Los Angeles Department of Water and Power (LADWP) can engage and work equitably with Los Angeles communities to cocreate a clean and just energy future for LA. LA100 Equity Strategies is rooted in the crucial role community engagement plays in restructuring the energy systems of cities, states, and nations. Scholarship on wind, solar, and other transitional energy technologies and projects has documented that such engagement is commonly used as a top-down mechanism for adapting social practices to fit new technological innovations. Yet, understanding how the clean energy transition - with related changes in technologies, infrastructures, practices, and costs - will fit equitably into the existing socio-political context is a challenge that requires substantive collaboration with local communities. Any form of community engagement opens up government officials and utilities to opposition from their public. Meaningful engagement methods turn such dissent into a strength, embracing critical feedback - particularly from communities historically excluded from decision-making - as contributing to more grounded design and effective implementation. Leveraging this collaborative model to further rectify past and ongoing inequities in the social, cultural, and institutional scaffolding of LA, this chapter presents options and methods to support LADWP in launching a just and equitable clean energy transition. We approach community engagement as a critical process linking recognition, procedural, and distributional justice, outlining how LADWP could learn from past engagement, coordinate such knowledge organization-wide, and use engagement as a key tool for achieving energy justice and equity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

LA100 Equity Strategies. Chapter 5: Low-Income Energy Bill Equity and Affordability

The LA100 Equity Strategies project synthesizes community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. Grounded in the analysis of past and ongoing energy inequities and engagement with underserved communities, the project presents community-guided strategies that aim to operationalize recognition and procedural justice. Building on the community-identified problems and solutions, and the analysis of the 11 strategies described in Chapter 3, this chapter continues to focus on the solution space through the lens of recognition and procedural justice. It centers the role of community engagement in energy utility planning and project development with a specific focus on how the Los Angeles Department of Water and Power (LADWP) can engage and work equitably with Los Angeles communities to cocreate a clean and just energy future for LA. LA100 Equity Strategies is rooted in the crucial role community engagement plays in restructuring the energy systems of cities, states, and nations. Scholarship on wind, solar, and other transitional energy technologies and projects has documented that such engagement is commonly used as a top-down mechanism for adapting social practices to fit new technological innovations. Yet, understanding how the clean energy transition - with related changes in technologies, infrastructures, practices, and costs - will fit equitably into the existing socio-political context is a challenge that requires substantive collaboration with local communities. Any form of community engagement opens up government officials and utilities to opposition from their public. Meaningful engagement methods turn such dissent into a strength, embracing critical feedback - particularly from communities historically excluded from decision-making - as contributing to more grounded design and effective implementation. Leveraging this collaborative model to further rectify past and ongoing inequities in the social, cultural, and institutional scaffolding of LA, this chapter presents options and methods to support LADWP in launching a just and equitable clean energy transition. We approach community engagement as a critical process linking recognition, procedural, and distributional justice, outlining how LADWP could learn from past engagement, coordinate such knowledge organization-wide, and use engagement as a key tool for achieving energy justice and equity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Arctagrostis latifolia Biomass and Chemistry, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of measured tissue specific biomass, %C, % N and APE (atom percentage in excess) of 15N of harvested A. latifolia in vegetation warming experiment enclosures and paired control plots located on the BEO, Utqiagvik, Alaska. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. This dataset includes one csv file and one pdf 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 OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Arctagrostis latifolia Canopy Traits, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of measured Arctagrostis latifolia canopy traits harvested from vegetation warming experiment enclosures and paired control plots located on the BEO, Utqiavik, Alaska. Harvest types include both natural abundance and enriched A. latifolia. Canopy traits measured include leaf area index (LAI), specific leaf area (SLA) and maximum height. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiavik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. This dataset includes one csv file and one pdf 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 OSTI2021

Integrating Arctic Plant Functional Types in a Land Surface Model Using Above‐ and Belowground Field Observations

Abstract Accurate simulations of high‐latitude ecosystems are critical for confident Earth system model (ESM) projections of carbon cycle feedbacks to global climate change. Land surface model components of ESMs, including the E3SM Land Model (ELM), simulate vegetation growth and ecosystem responses to changing climate and atmospheric CO 2 concentrations by grouping heterogeneous vegetation into like sets of plant functional types (PFTs). Many such models represent high‐latitude vegetation using only two PFTs (shrub and grass), thereby missing the diversity of vegetation growth forms and functional traits in the Arctic. Here, we use field observations of biomass and leaf traits across a gradient of plant communities on the Seward Peninsula in northwest Alaska to replace the original ELM configuration for the first time with nine Arctic‐specific PFTs. The newly developed PFTs include: (1) nonvascular mosses and lichens, (2) deciduous and evergreen shrubs of various height classes, including an alder PFT, (3) graminoids, and (4) forbs. Improvements relative to the original model configuration included greater belowground biomass allocation, persistent fine roots and rhizomes of nonwoody plants, and better representation of variability in total plant biomass across sites with varying plant communities and depth to bedrock. Simulations through 2100 using the RCP8.5 climate scenario and constant PFT fractional areas showed alder‐dominated plant communities gaining more biomass and lichen‐dominated communities gaining less biomass compared to default PFTs. Our results highlight how representing the diversity of arctic vegetation and confronting models with measurements from varied plant communities improves the representation of arctic vegetation in terrestrial ecosystem models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Foliar functional traits from imaging spectroscopy across biomes in eastern North America

Summary Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1–19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental‐scale functional diversity.

Wang, Zhihui↗
DOE OSTI2026

From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture

Background Characterizing the physical organization of the genome is essential for understanding long-range gene regulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two-dimensional (2D) genome-wide contact maps of chromatin interactions by capturing the spatial proximity between genomic loci, which reveal interaction frequencies but lack the spatial resolution needed to interpret the three-dimensional (3D) genome structure(s). Emerging evidence suggests that epigenetic regulation is closely linked to 3D genome architecture, and that structural changes over time (4D) drive key biological processes in development, disease, and environmental response. Thus, integrating 3D structure with functional data is critical for a more complete understanding of genome regulation. Previous work, most notably the 4DHiC chromosome modeling framework, has shown that physical multi-dimensional modeling approaches rooted in polymer physics and molecular dynamics can resolve these structures at biologically meaningful resolutions by integrating temporal Hi-C data with physical constraints to uncover dynamic chromosome reorganization. Thus, molecular dynamics simulations, constrained by Hi-C contact matrices, can resolve fine-scale structural changes and reveal functionally significant transitions in chromatin conformation. Results Herein, we present the 4D Genome Browser Workflow (4DGBWorkflow) and the 4D Genome Browser (4DGB). The algorithm is based on the 4DHiC method, and the containerized tool is an end-to-end workflow that can transform, filter, and view 4D epigenomics and chromatin datasets, allowing non-specialists to apply three-dimensional modeling principles to diverse datasets and experimental conditions. The software executes on a laptop running macOS, Linux or Windows. From input Hi-C files (.hic), the 4DGBWorkflow produces 3D reconstructions of chromosomes, integrates the reconstruction with track data (e.g., epigenetic marks, transcriptome profiles), and provides comparative visualization of the results in a single workflow. Conclusions The 4DGBWorkflow and 4D Genome Browser are open-source tools for comparative analysis and visualization of 4D chromosome datasets, including chromatin architecture and epigenomic signals. Automatic integration of Hi-C data with molecular dynamics democratizes the construction of time resolved 3D genome structures, simplifying complex simulations and data integration schemes.

3D Genome Browser↗
DOE OSTI2021

Specialized Plant Growth Chamber Designs to Study Complex Rhizosphere Interactions

The rhizosphere is a dynamic ecosystem shaped by complex interactions between plant roots, soil, microbial communities and other micro- and macro-fauna. Although studied for decades, critical gaps exist in the study of plant roots, the rhizosphere microbiome and the soil system surrounding roots, partly due to the challenges associated with measuring and parsing these spatiotemporal interactions in complex heterogeneous systems such as soil. To overcome the challenges associated with in situ study of rhizosphere interactions, specialized plant growth chamber systems have been developed that mimic the natural growth environment. This review discusses the currently available lab-based systems ranging from widely known rhizotrons to other emerging devices designed to allow continuous monitoring and non-destructive sampling of the rhizosphere ecosystems in real-time throughout the developmental stages of a plant. We categorize them based on the major rhizosphere processes it addresses and identify their unique challenges as well as advantages. We find that while some design elements are shared among different systems (e.g., size exclusion membranes), most of the systems are bespoke and speaks to the intricacies and specialization involved in unraveling the details of rhizosphere processes. We also discuss what we describe as the next generation of growth chamber employing the latest technology as well as the current barriers they face. We conclude with a perspective on the current knowledge gaps in the rhizosphere which can be filled by innovative chamber designs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1

Abstract. This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1∘ horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of changes in 10-year mean zonal averages include the following: up to 0.5 K of warming in the lower troposphere and cooling in the tropical and subtropical upper troposphere, 1 %–10 % decreases in relative humidity throughout the troposphere, and 10 %–20 % decreases in cloud fraction in the upper troposphere and decreases exceeding 20 % in the subtropical lower troposphere. In terms of the 10-year mean geographical distribution, systematic decreases of 20 %–50 % are seen in total cloud cover and cloud radiative effects in the subtropics. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; to regain optimal climate fidelity in the absence of those truncation errors, the model would require retuning. A coarse-grained attribution of the time step sensitivities is carried out by shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection, and stratiform cloud macrophysics and microphysics parameterizations but rather by the step sizes used outside those subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM significantly affects the subtropical marine stratocumulus decks, while deep convection has significant impacts on trade cumulus. The step size of the cloud macrophysics and microphysics subcycle itself appears to have a primary impact on cloud fraction in the upper troposphere and also in the midlatitude near-surface layers. Impacts of step sizes used by the dynamical core and the radiation parameterization appear to be relatively small. These results provide useful clues for future studies aiming at understanding and addressing the root causes of sensitivities to time step sizes and process coupling frequencies in EAM. While this study focuses on EAMv1 and the conclusions are likely model-specific, the presented experimentation strategy has general value for weather and climate model development, as the methodology can help researchers identify and understand sources of time integration error in sophisticated multi-component models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Arctagrostis latifolia 15N Uptake, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of atom percentage of 15N in excess of natural abundance after injection and incubation, uptake rate of 15N during incubation period and percent recovery of 15N labeled ammonia in A. latifolia tissues in vegetation warming experiment enclosures and paired control plots located on the BEO, Utqiagvik, Alaska. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. Files include one *.csv data file and one *.pdf user guide. 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 OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Inorganic Nitrogen and Phosphorus on Resins, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of inorganic ammonia, nitrate, and phosphate bound to anion and cation binding resins deployed from July through September 2018 in the surface soils of vegetation warming experiment enclosures and paired control plots. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. Included is one *.csv data file and one *.pdf user guide. 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 OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Environmental Observations and Thaw Depth, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of measured soil thaw depth, soil temperature, soil moisture, and Arctagrostis latifolia height in vegetation warming experiment enclosures and paired control plots. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. Included are two *.csv data files and one *.pdf user guide. 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 OSTI2023

Organic carbon enables the biotic engineering of beneficial soil structure in Profundihumic and Haplic Ferralsols

We investigated how organic matter may, directly and indirectly, modify the porosity of Ferralsols, that is, deeply weathered soils of the tropics and subtropics. Although empirical and anecdotal evidence suggests that organic matter accumulation may increase porosity, a mechanistic understanding of the processes underlying this beneficial effect is lacking, especially so for Ferralsols. To achieve our end, we leveraged the fact that the Profundihumic qualifier of Ferralsols (PF) is distinguished from Haplic Ferralsols (HF) by both a much larger average carbon content in the first 1 m of soil depth (19 kg C m -3 in PF vs. 10 kg C m -3 in HF) and a significantly lower bulk density (1.05 ± 0.08 kg L -1 in PF vs. 1.21 ± 0.05 kg L -1 in HF). Through exhaustive modelling of carbon – bulk density relationships, we demonstrate that the lower bulk density of PF cannot be satisfactorily explained by a simple dilution effect. Rather, we found that bulk density correlated with carbon content when combined with carbon: nitrogen ratio (r 2 = 0.51), black carbon content (r 2 = 0.75), and Δ 14 C (r 2 =0.81). Total pore space was greater in PF (61± 3%) than in HF (55 ± 2%), but x-ray computed tomography revealed that pore space inside soil aggregates of 4–5 mm diameter does not vary between the studied Ferralsols. We further observed nearly twice as many roots and burrows in PF compared with HF. We thus infer that the mechanism responsible for the increase in porosity is most likely an enhancement of resource availability (e.g., energy, carbon, and nutrients) for the organisms (earthworms, ants, termites, etc.) that physically displace soil particles and promote soil aggregation. As a result of increased resource availability, soil organisms can create especially the mesoscale structural soil features necessary for unrestricted water flow and rapid gas exchange. In conclusion, this insight paves the way for the development of land management technologies to optimize the physical shape and capacity of the soil bioreactor.

54 ENVIRONMENTAL SCIENCES↗