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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO 2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO 2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO 2 later in the season.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Potential impacts of mercury released from thawing permafrost

Abstract Mercury (Hg) is a naturally occurring element that bonds with organic matter and, when converted to methylmercury, is a potent neurotoxicant. Here we estimate potential future releases of Hg from thawing permafrost for low and high greenhouse gas emissions scenarios using a mechanistic model. By 2200, the high emissions scenario shows annual permafrost Hg emissions to the atmosphere comparable to current global anthropogenic emissions. By 2100, simulated Hg concentrations in the Yukon River increase by 14% for the low emissions scenario, but double for the high emissions scenario. Fish Hg concentrations do not exceed United States Environmental Protection Agency guidelines for the low emissions scenario by 2300, but for the high emissions scenario, fish in the Yukon River exceed EPA guidelines by 2050. Our results indicate minimal impacts to Hg concentrations in water and fish for the low emissions scenario and high impacts for the high emissions scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Grassland carbon-water cycling is minimally impacted by a photovoltaic array

Agrivoltaic systems, whereby photovoltaic arrays are co-located with crop or forage production, can alleviate the tension between expanding solar development and loss of agricultural land. However, the ecological ramifications of these arrays are poorly known. We used field measurements and a plant hydraulic model to quantify carbon-water cycling in a semi-arid C 3 perennial grassland growing beneath a single-axis tracking solar array in Colorado, USA. Although the agrivoltaic array reduced light availability by 38%, net photosynthesis and aboveground net primary productivity were reduced by only 6–7% while evapotranspiration decreased by 1.3%. The minimal changes in carbon-water cycling occurred largely because plant photosynthetic traits underneath the panels changed to take advantage of the dynamic shading environment. Our results indicate that agrivoltaic systems can serve as a scalable way to expand solar energy production while maintaining ecosystem function in managed grasslands, especially in climates where water is more limiting than light.

14 SOLAR ENERGY↗
DOE OSTI2023

Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology

Abstract Elucidating how an organism's characteristics emerge from its DNA sequence has been one of the great triumphs of biology. This triumph has cumulated in sophisticated computational models that successfully predict how an organism's detailed phenotype emerges from its specific genotype. Inspired by that effort's vision and empowered by its methodologies, a grand challenge is described here that aims to predict the biotic characteristics of an ecosystem, its metaphenome, from nucleic acid sequences of all the species in its community, its metagenome. Meeting this challenge would integrate rapidly advancing abilities of environmental nucleic acids (eDNA and eRNA) to identify organisms, their ecological interactions, and their evolutionary relationships with advances in mechanistic models of complex ecosystems. Addressing the challenge would help integrate ecology and evolutionary biology into a more unified and successfully predictive science that can better help describe and manage ecosystems and the services they provide to humanity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Fe-rich X-ray amorphous material records past climate and persistence of water on Mars

X-ray amorphous material comprises 15-73 wt.% of sedimentary rocks and eolian sediments in Gale crater. This material is variably siliceous and iron rich but aluminum poor. The presence of volatiles is consistent with the existence of incipient weathering products. To better understand the implications of this material for past aqueous conditions on Mars, here we investigate X-ray amorphous material formation and longevity within terrestrial iron rich soils with varying ages and environmental conditions using bulk and selective dissolution methods, X-ray diffraction, and transmission electron microscopy. Results indicate that in situ aqueous alteration is required to concentrate iron into clay-size fraction material. Cooler climates promote the formation and persistence of X-ray amorphous material whereas warmer climates promote the formation of crystalline secondary phases. Iron rich X-ray amorphous material formation and persistence on Mars are therefore consistent with past cool and relatively wet environments followed by long-term cold and dry conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Assessing the life-cycle environmental impacts of the wood pallet sector in the United States

Wood pallets play a critical role in the movement and storage of goods worldwide. They are an important component in the complex global supply chain and used by almost every industry. It is therefore important to assess the environmental implications of the wood pallet supply chain and identify optimization strategies that can be implemented. In this paper, primary 2018 annual production data collected from U.S. pallet manufacturers were used to develop the first industry-average life-cycle inventory (LCI). A new functional unit was proposed to perform a more refined and accurate environmental life-cycle assessment of the wood pallet supply chain. Using the LCI data developed, a cradle-to-grave industry-average life-cycle impact assessment was performed. This novel approach quantifies environmental impacts of a generic multi-use pallet, including repair and remanufacturing. The total global warming impact was 10.4 kg CO 2 e per 45.4 t of pallet loads of product delivered using wood pallets. The manufacturing stage contributed the most, about 35%, followed by the raw material supply stage. About 41% of total primary energy consumption was from renewable sources, with most sourced from biomass. Fossil fuels comprised about 52% of the total (225 MJ per functional unit) primary energy consumption. Total environmental impact was significantly affected by two main parameters: reference service life and load-bearing capacity. Pallet repair was also found to be an important component of the wood pallet supply chain, which has a low environmental footprint compared with the overall impact of a pallet and enables mitigation of overall impact by extending the reference service life. Finally, at end-of-life, common industry practices demonstrated substantial potential environmental benefits that can minimize overall environmental impact.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effects of Lead and Arsenic in Soils from Former Orchards on Growth of Three Plant Species

Abstract Historical use of lead arsenate as a pesticide in former orchards of eastern Washington State (USA) has resulted in legacy lead (Pb) and arsenic (As) soil contamination. However, the impacts on plant growth in soils with residual Pb and As contamination have not yet been quantified. To this end, a comparative study of plant growth impacts was performed for native bluegrass ( Poa secunda ), invasive cheatgrass ( Bromus tectorum ), and buttercrunch lettuce ( Lactuca sativa ). Using standard plant growth protocols, germination frequency and biomass growth were measured over a wide range of Pb and arsenate concentrations, with maximum concentrations of 3400 and 790 mg kg −1 for Pb and As, respectively. Results indicated that only the biomass growth for all species decreased in soils with the highest concentrations of Pb and As in the soil, with no impacts on soils with lower residual Pb and arsenate concentrations. No impact on percentage of germination was observed at any soil concentration. These results can be used to determine site‐specific soil screening levels for use in ecological risk assessments for Pb and arsenate in soils. Environ Toxicol Chem 2022;41:1459–1465. © 2022 Battelle Memorial Institute. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Machine learning and process-based modeling of spatiotemporal changes in active layer thickness across Alaska

Permafrost degradation poses a growing threat to infrastructure stability and ecosystem resilience in the rapidly warming Arctic. We investigated the spatiotemporal dynamics of active layer thickness (ALT) across Alaska by integrating field observations, environmental datasets, a physically based Stefan model, and machine learning (ML) techniques. Using weather projections from the Coupled Model Intercomparison Project Phase 6 under two Shared Socioeconomic Pathways (SSP 2-4.5 and SSP 5-8.5), we assessed ALT sensitivity to projected future weather conditions. The random forest (RF) model outperformed the Stefan approach in predicting ALT on the training dataset (R² = 0.84 vs. 0.53) but demonstrated lower generalizability on the test dataset (R² = 0.24 vs. 0.54). The root mean square error (RMSE) for the RF model for training and testing ranged from 14 to 22 cm, compared to 17 and 18 cm for the Stefan model. Variable importance analysis revealed that mean annual temperature and slope angle were the strongest predictors of ALT, accounting for 19% and 18% of the variance, respectively, followed by sediment transport index (14%) and stream power index (11%). Comparative analysis of baseline ALT predictions showed the Stefan model tended to project a thicker active layer (mean ± SD: 65 ± 16 cm), compared to the RF model (mean ± SD: 59 ± 8.8) cm). Both models indicated a latitudinal gradient in ALT, with shallower depths at higher latitudes. Projected ALT increases by 2100 were estimated at 3.3 ± 2.2 cm under SSP 2-4.5 and 5.9 ± 4.0 cm under SSP 5-8.5 for the ML model, whereas the Stefan model projected substantially larger increases of 13 ± 2.6 cm (SSP 2-4.5) and 28 ± 4.4 cm (SSP5-8.5). Spatial analysis showed the greatest ALT increases in northern Alaska, with relatively smaller changes in southern regions. These findings highlight the complex, multifactorial nature of ALT dynamics and the value of hybrid modeling approaches. As rising temperatures accelerate permafrost thaw, changes in ALT can disrupt ecosystems, damage infrastructures, and enhance the release of stored soil carbon, highlighting the urgent need for improved predictive capabilities to inform adaptation strategies in the Arctic.

Climate sciences↗
DOE OSTI2022

Characterization of ambient polychlorinated biphenyl background conditions in surface waters of the Pajarito Plateau, New Mexico

Abstract This study presents the development of polychlorinated biphenyl (PCB) background threshold values (BTVs) that statistically characterize ambient background conditions for surface waters in undeveloped and developed landscapes of the Pajarito Plateau in the Rio Grande Basin of New Mexico. Between 2009 and 2018, surface water data were collected at 45 locations under a variety of flow conditions and regimes. A total of 163 samples were collected, with roughly 1/3 of samples and locations being in undeveloped areas (n = 53 from 17 locations), and the remainder being in developed areas (n = 110 from 28 locations). While there are areas on the Pajarito Plateau where PCB point sources are known or likely to have contributed to PCBs in soils, PCB BTVs calculated for undeveloped portions of watersheds (upstream of areas where PCB point sources are known or likely to have contributed to PCBs in soils, and therefore not affected by PCB sources within the watershed) are well above New Mexico's human health organism-only (HH-OO) water quality criterion (0.64 ng/L). Background threshold values are even higher in developed areas upstream of managed soil sites, suggesting that in developed areas, both diffuse ambient PCB sources (e.g., atmospheric deposition) and localized urban sources (e.g., building materials, paints, and electrical equipment) contribute to PCBs in those watersheds. These findings indicate that New Mexico's current HH-OO water quality criterion for PCBs cannot practicably be met due to ambient conditions. It is also impracticable to meet the US Environmental Protection Agency (EPA) criterion continuous concentration (CCC) of 14 ng/L in developed background areas, where the BTV is approximately 1.5 times the CCC. Integr Environ Assess Manag 2023;19:1307–1319. © 2022 SETAC

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Analysis of incentive policies for phosphorus recovery at livestock facilities in the Great Lakes area

Livestock operations have been highly intensified over the last decades, resulting in the advent of large concentrated animal feeding operations (CAFOs). Intensification decreases production costs but also leads to substantial environmental impacts. Specifically, nutrient runoff from livestock waste results in eutrophication, harmful algal blooms, and hypoxia. The implementation of nutrient recovery systems in CAFOs can abate nutrient releases and negative ecosystem responses, although they might negatively affect the economic performance of CAFOs. We design and analyze potential incentive policies for the deployment of phosphorus recovery technologies at CAFOs considering the geospatial vulnerability to nutrient pollution. The case study demonstration consists of 2217 CAFOs in the U.S. Great Lakes area. The results reveal that phosphorus recovery is more economically viable in the largest CAFOs due to economies of scale, although they also represent the largest eutrophication threats. For small and medium-scale CAFOs, phosphorus credits progressively improve the profitability of nutrient management systems. The integration of biogas production does not improve the economic performance of phosphorus recovery systems at most of CAFOs, as they lack enough size to be cost-effective. Furthermore, phosphorus recovery proves to be economically beneficial by comparing the net costs of nutrient management systems with the negative economic impact derived from phosphorus releases. The incentives necessary for avoiding up to 20.7.10 3 ton/year phosphorus releases and achieve economic neutrality in the Great Lakes area are estimated at $223 million/year. Additionally, the fair distribution of limited incentives is studied using a Nash allocation scheme, determining the break-even point for allocating monetary resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Is satellite Sun-Induced Chlorophyll Fluorescence more indicative than vegetation indices under drought condition?

Droughts represent one of the most severe abiotic stress factors that could result in great crop yield loss. Numerous vegetation indices have been proposed for monitoring the vegetation condition under stress and assessing drought impacts on yield loss. However, the understanding and comparison between traditional vegetation indices (VIs) and the newly emerging satellite Sun-Induced Chlorophyll Fluorescence (SIF) for monitoring vegetation condition is still limited especially under drought stress and at multiple spatial scales. In this study, the potential of satellite observation SIF for monitoring corn response to drought was investigated based on the 2012 drought in the US Corn Belt. The standardized precipitation evapotranspiration index (SPEI) was used here to quantify drought. We found that all SPEI were above –1, except for July (–1.27), August (–1.39) and September (–1.14) in 2012, indicating the severity of this drought. We examined the relationship between satellite measurements of SIF, SIF yield , VIs (e.g., NDVI and EVI) and SPEI. Results indicated that SIF yield was sensitive to drought and SIF captured the stress more accurately both at the regional and state scales for the US Corn Belt. Quantitatively, SIF yield had a high correlation with SPEI (r = 0.987, p < 0.05) over the entire Corn Belt, and it indicated losses in response to drought approximately one month earlier than SIF/NDVI/EVI. Furthermore, our results demonstrated that SIF could be trusted as an effective indicator to study the relationship between GPP (R 2 ≥ 0.8664, p < 0.01) under drought conditions across the Corn Belt. Finally, this study highlighted the advantage of using satellite SIF observations to monitor the drought stress on crop growth especially GPP at regional scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Immobilization of active ammonia-oxidizing archaea in hydrogel beads

Abstract Ammonia-oxidizing archaea (AOA) are major players in the nitrogen cycle but their cultivation represents a major challenge due to their slow growth rate and limited tendency to form biofilms. In this study, AOA was embedded in small (~2.5 mm) and large (~4.7 mm) poly(vinyl alcohol) (PVA)—sodium alginate (SA) hydrogel beads cross-linked with four agents (calcium, barium, light, or sulfate) to compare the differences in activity, the diffusivity of nitrogen species (NH 4 + , NO 2 − , and NO 3 − ), and polymer leakage in batch systems over time. Sulfate-bound PVA-SA beads were the most stable, releasing the lowest amount of polymer without shrinking. Diffusion coefficients were found to be 2 to 3 times higher in hydrogels than in granules, with ammonium diffusivity being ca . 35% greater than nitrite and nitrate. Despite a longer lag phase in small beads, embedded AOA sustained a high per volume rate of ammonia oxidation compatible with applications in research and wastewater treatment.

42 ENGINEERING↗
DOE OSTI2023

Differentiable modelling to unify machine learning and physical models for geosciences

Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. Here, in this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.

58 GEOSCIENCES↗
DOE OSTI2022

Disturbance: a double-edged sword for restoration in a changing climate

Ecological restoration often relies on disturbance as a tool for establishing target plant communities, but disturbance can be a double-edged sword, at times initiating invasion and unintended outcomes. Here, in this study, we test how fire disturbance, designed to enhance restoration seeding success, combines with climate and initial vegetation conditions to shift perennial versus annual grass dominance and overall community diversity in Pacific Northwest grasslands. We seeded both native and introduced perennial grasses and native forbs in paired, replicated burned-unburned plots in three sites along a latitudinal climate gradient from southern Oregon to central-western Washington. Past restoration and climate manipulations at each site had increased the variation of starting conditions between plots. Burning promoted the expansion of extant forbs and perennial grasses across all sites. Burning also enhanced the seeding success of native perennial grass and native forbs at the northern and central site, and the success of introduced perennial grasses across all three sites. Annual grass dominance was driven more by latitude than burning, with annuals maintaining their dominance in the south and perennials in the north. At the same time, unrestored grasslands surrounding all sites remained dominated by perennial grasses, suggesting that initial plot clearing may have allowed for annual grass invasion in the southern site. When paired with disturbance, further warming may increase the risk of annual grass dominance, a potentially persistent state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The interplay of labile organic carbon, enzyme activities and microbial communities of two forest soils across seasons

Soil labile organic carbon (LOC) responds rapidly to environmental changes and plays an important role in carbon cycle. In this study, the seasonal fluctuations in LOC, the activities of carbon-cycle related enzymes, and the bacterial and fungal communities were analyzed for soils collected from two forests, namely Betula albosinensis (Ba) and Picea asperata Mast. (Pa), in the Qinling Mountains of China. Results revealed that the seasonal average contents of microbial biomass carbon (MBC), easily oxidized organic carbon (EOC), and dissolved organic carbon (DOC) of Pa forest soil were 13.5%, 30.0% and 15.7% less than those in Ba soil. The seasonal average enzyme activities of β-1,4-glucosidase (βG), and β-1,4-xylosidase (βX) of Ba forest soils were 30.0% and 32.3% higher than those of Pa soil while the enzyme activity of cellobiohydrolase (CBH) was 19.7% lower. Furthermore, the relative abundance of Acidobacteria was significantly higher in summer than in winter, whereas the relative abundance of Bacteroidetes was higher in winter. Regarding the fungal communities, the relative abundance of Basidiomycota was lowest in winter, whereas Ascomycota predominated in the same season. In addition, the soil LOC was significantly positively correlated with the CBH, βG and βX activities. Changes in LOC were significantly correlated with Acidobacteria, Bacteroidetes and Basidiomycota. We conclude that the seasonal fluctuations in forest soil LOC fractions relied on carbon cycle-associated enzymatic activities and microorganisms, which in turn were affected by climatic conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fungal Spore Seasons Advanced Across the US Over Two Decades of Climate Change

Abstract Phenological shifts due to climate change have been extensively studied in plants and animals. Yet, the responses of fungal spores—organisms important to ecosystems and major airborne allergens—remain understudied. This knowledge gap limits our understanding of their ecological and public health implications. To address this, we analyzed a long‐term (2003–2022), large‐scale (the continental US) data set of airborne fungal spores collected by the US National Allergy Bureau. We first pre‐processed the spore data by gap‐filling and smoothing. Afterward, we extracted 10 metrics describing the phenology (e.g., start and end of season) and intensity (e.g., peak concentration and integral) of fungal spore seasons. These metrics were derived using two complementary but not mutually exclusive approaches—ecological and public health approaches, defined as percentiles of total spore concentration and allergenic thresholds of spore concentration, respectively. Using linear mixed‐effects models, we quantified annual shifts in these metrics across the continental US. We revealed a significant advancement in the onset of the spore seasons defined in both ecological (11 days, 95% confidence interval: 0.4–23 days) and public health (22 days, 6–38 days) approaches over two decades. Meanwhile, total spore concentrations in an annual cycle and in a spore allergy season tended to decrease over time. The earlier start of the spore season was significantly correlated with climatic variables, such as warmer temperatures and altered precipitations. Overall, our findings suggest possible climate‐driven advanced fungal spore seasons, highlighting the importance of climate change mitigation and adaptation in public health decision‐making.

Environmental Sciences & Ecology↗
DOE OSTI2022

Degradation and fate of 2,4-dinitroanisole (DNAN) and its intermediates treated with Mg/Cu bimetal: Surface examination with XAS, DFT, and LDI-MS

In this article, a novel Mg-based bimetal reagent (Mg/Cu) was used as an enhanced reductive system to degrade insensitive munition 2,4-dinitroanisole (DNAN), a contaminant found in energetic-laden waste. Degradation of DNAN was significantly impacted by dissolved oxygen and studied in anoxic and oxic bimetal systems (i.e., purging with N 2 , air, or O 2 gas). Degradation occurred through sequential nitroreduction: first one nitro group was reduced (ortho or para) to form short-lived intermediates 2-amino-4-nitroanisole or 4-amino-2-nitroanisole (2-ANAN or 4-ANAN), and then subsequent reduction of the other nitro group formed 2,4-diaminoanisole (DAAN). The nitro-amino intermediates demonstrated regioselective reduction in the ortho position to 2-ANAN; Regioselectivity was also impacted by the anoxic/oxic environment. Under O 2 -purging DNAN degradation rate was slightly enhanced, but most notably O 2 significantly accelerated DAAN generation. DAAN also further degraded only in the oxygenated Mg/Cu system. Adsorption of DNAN byproducts to the reagent occurred regardless of anoxic/oxic condition, resulting in a partition of carbon mass between the adsorbed phase (27%-35%) and dissolved phase (59%-72%). Additional surface techniques were applied to investigate contaminant interaction with Cu. Density functional theory (DFT) calculations identified preferential adsorption structures for DNAN on Cu with binding through two O atoms of one or both nitro groups. X-ray absorption spectroscopy (XAS) measurements determined the oxidation state of catalytic metal Cu and formation of a Cu-O-N bond during treatment. Laser desorption ionization mass spectrometry (LDI-MS) measurements also identified intermediate 2-ANAN adsorbed to the bimetal surface.

54 ENVIRONMENTAL SCIENCES↗