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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Development and Experimental Validation of Large Eddy Simulation Techniques for the Prediction of Combustion-Dynamic Process in Syngas Combustion: Characterization of Autoignition, Flashback, and Flame-Liftoff at Gas-Turbine Relevant Operating Conditions

The objective of this closely coordinated experimental and computational research effort is the development of simulation techniques for the prediction of combustion processes, relevant to the oxidation of syngas and high hydrogen content (HHC) fuels at gas-turbine relevant operating conditions. Specifically, the research goals are (i) the characterization of the sensitivity of syngas ignition processes to hydrodynamic processes and perturbations in temperature and mixture composition in rapid compression machines and ow-reactors and (ii) to conduct comprehensive experimental investigations in a swirl-stabilized gas turbine (GT) combustor under realistic high-pressure operating conditions in order (iii) to obtain fundamental understanding about mechanisms controlling unstable flame regimes in HHC-combustion.

10 SYNTHETIC FUELS↗
DOE OSTI2017

Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment. Workshop report, September 21–23, 2016

The Biological Systems Science Division (BSSD) within the U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) funds basic research on plants and microbes relevant to several DOE bioenergy and environmental mission areas. BSSD’s long history of developing and supporting genomic characterization of biological systems has led, in part, to the high-throughput DNA sequencing technology available to researchers worldwide. In recent years, genome sequencing has vastly outpaced the ability to interpret genome function. Fully maximizing this wealth of data will require new technology advancements, along with improvements and an increase in the throughput of existing methods for characterizing molecular- to cellular-level processes important for inferring biological function. BSSD research seeks to understand the fundamental genome-encoded properties of plants and microbes that can be harnessed or redesigned for beneficial purposes. Current emphases are leading to the discovery, development, and understanding of numerous plant and microbial species with traits suitable for the production of fuels and chemical products from renewable biomass that could be grown synergistically with food or animal feed crops while not competing with other societal needs. Additionally, BSSD further supports research leading to an understanding of the complex and essential interactions among plants, microbial communities, and the environment to find new ways to sustainably produce biomass for a range of bioenergy and bioproduct applications. This research also is relevant for incorporation into larger-scale environmental models such as those developed through the research supported by BER’s Earth and Environmental Systems Sciences programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Potential Academic Research Topics of National Security Relevance

Since even before its establishment as an independent national security laboratory in 1949, Sandia has been devoted to an overarching mission of developing advanced technologies for global peace. These technologies have taken a variety of forms, and they exist in and must address an ever-changing global security environment. An understanding of that global security environment and its possible or likely evolution is therefore critical to ensuring that Sandia can maintain its focus on strategic technology investments that will benefit the nation in the next 20- 30 years. Sandia sustains multiple Systems Analysis organizations whose responsibility includes maintaining an understanding of the global security environment as it applies across multiple mission domains. The topics below include two from Sandia's emerging threats and biodefense mission, three with relevance to Sandia's cyber defense mission, and four of particular but not exclusive relevance to Sandia's nuclear deterrence mission. All are intended to spur independent academic thought that could assist Sandia as well as the broader national security community in anticipating and adapting to a continually changing world. Sandia anticipates periodic interactions between Sandia Systems Analysis staff and SciPol Scholars Program faculty and students who choose to expand upon these topics in order to provide opportunities for feedback and communication throughout 2020-2021.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Relevant Advanced Reactor Benchmarks for Nuclear Data Assessment

Advanced reactor concepts currently being developed throughout the industry are significantly different from light water reactor (LWR) designs with respect to geometry, materials, and operating conditions, and consequently, with respect to their reactor physics behavior. Given the limited operating experience with non-LWRs, the accurate simulation of reactor physics and the quantification of associated uncertainties are critical for ensuring that advanced reactor concepts operate within the appropriate safety margins. Nuclear data are a major source of input uncertainties in reactor physics analysis. As part of an ongoing project at Oak Ridge National Laboratory, the effects of nuclear data uncertainties on key figures of merit associated with advanced reactor safety are being assessed for selected advanced reactor technologies. Key nuclear data relevant for reactor safety analysis for each selected advanced reactor technology were identified in Phase 1, and their impact on important key figures of merit was assessed in Phase 2. This report describes the outcome of Phase 3. Available benchmarks and fuel irradiation data for use in evaluating the impact of uncertainties and gaps in nuclear data that impact reactivity control for advanced reactor designs through the fuel cycle were identified and assessed. Benchmarks were identified by searching (1) the Organisation for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) International Criticality Safety Benchmark Evaluation Project (IRPhEP) handbook, (2) the OCED/NEA International Reactor Physics Experiment Evaluation Project (IRPhEP) handbook, (3) ongoing OECD/NEA benchmark activities, and (4) documentation in public literature. Relevant benchmarks were identified by selecting reactors with geometry, materials, and neutron energy spectra similar to those of selected advanced reactor technologies. This assessment identified six benchmarks, of which three are experimental and three are purely computational. One experimental and one computation benchmark contain depleted fuel; all others are limited to fresh fuel. This report provides short descriptions of the selected benchmarks along with the availability of measured data for comparison.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

MFIX DEM Enhancement for Industry-Relevant Flows (Final Report)

The overall goal of this two-phase project is to implement performance improvements of the Multiphase Flow with Interphase Exchanges (MFIX) Discrete Element Model (DEM) code that enable a transformative shift for industrial use. Prior to this effort, the largest simulations performed using MFIX are O(10 7 ) particles. This falls short of the O(10 9 ) particle simulations that must be completed on a timescale of days or weeks (vs. months or years) to enable simulations with physically-relevant domain sizes to be incorporated into industrial design cycles within five years. This was accomplished by tailoring best-in-class practices to bear on the unique challenges posed by the MFIX-DEM algorithm and code base. Scientific simulations (e.g., in cosmology, turbulent combustion) routinely use massively parallel computing to update far more particles in short wall clock times. Results from Phase 1 (1.5 years in duration) indicated significant gains in speed were possible for a wide range of benchmark cases. Moreover, a survey sent to >35 companies indicates that the timing is ideal for such an enhanced tool, with >80% of the respondents indicating that DEM is already value-added or will be within the next 5 years, and >70% of the respondents indicating that improved speed is the top computational priority. In Phase 2 (3.5 years in duration), the two major barriers that hinder industry from effectively using multiphase Computational Fluid Dynamics (CFD) to cut costs and improve performance, namely computational overhead and confidence in predictions, continued to be addressed. Regarding the former, the results from Phase 1 to guide the effort, with enhancements focused on an improved time-stepping algorithm and particle sorting. Four target problems of 1 billion particles each and increasing complexity were identified: homogeneous cooling, tumbler with continuous particle size distribution, discharge from a rectangular hopper and a cylindrical riser. Each of these were successfully simulated for relevant time scales (on order of seconds) using less than 24 hours of wall clock time. These represent the first 1-billion particle DEM simulations performed with MFIX, namely using the MFIX-Exa code. This code is currently under development at NETL in collaboration with Lawrence Berkeley National Laboratory. Regarding the second barrier on predictive uncertainty, experiments from Phase 1 (interacting nozzles - hydrodynamics only) and Phase 2 (very small-scale segregation experiments) were used to demonstrate the ability of two simplified approaches to uncertainty quantification (UQ). By limiting the number of particles, UQ based on the simplified treatment was compared to standard UQ, which was shown to have much higher computational demands. Experiments were also performed on a pilot-scale stripper unit to provide validation data for future CFD-DEM simulations and UQ.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods

The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) is supporting the Geothermal Heating and Cooling Geospatial Datasets and Analysis project conducted by the National Renewable Energy Laboratory (NREL) as part of a broader effort to demonstrate the multi-faceted value of integrating geothermal power and geothermal heating and cooling (GHC) technologies into national decarbonization plans and community energy plans. Currently, there is a need to establish baseline low-temperature geothermal resource datasets and evaluate methods for deploying these technologies to provide the basis for supporting private sector investment. This project is focused on collecting baseline datasets, updating conceptual models, and creating Play Fairway Analysis (PFA) workflows for low-temperature (<150 degrees Celsius) geothermal resources of different geothermal play types (i.e., sedimentary basin, orogenic belts, and radiogenic geothermal play types) that could be used for geothermal heating and cooling (GHC), combined heat and power (CHP), and other geothermal direct uses (GDU) applications. Low-temperature geothermal resources are defined as reservoirs - natural or engineered - with temperatures <150 degrees Celsius. While the focus in the NREL effort is on GHC, resources at the upper end of this temperature range can also be used for small-scale power generation. This project does not include Ground Source Heat Pumps (GSHPs) technologies because they can be effectively developed almost anywhere. Low-temperature geothermal resources have not been studied as extensively as higher- to medium-temperature geothermal resources, but there is recent interest in improving understanding of these types of resources with an uptick of interest in geothermal technologies for decarbonizing heating and cooling systems. In addition, Enhanced Geothermal Systems (EGS) and other emerging technologies for exploiting petrothermal resources have opened the possibility of utilizing deep sedimentary basin systems, where porous media provide permeability and high temperatures can be reached at great depths. This project takes the approach of classifying low- temperature geothermal resources by geothermal play type (GPT). We defined and characterized three major classes of low-temperature GPT: sedimentary basins, orogenic systems, and radiogenic systems. We develop methodologies for evaluating and analyzing the potential for these resources building off the PFA approach to de-risking geothermal exploration and characterization. The proposed PFA approach for low-temperature geothermal resources includes: 1) identifying relevant data (e.g., datasets such bottom-hole temperatures from oil and gas wells, heat flow data, Quaternary faults and stress field data, geophysical data, etc.); 2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, and economic criteria); 3) uncertainty quantification; 4) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and 5) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool (RSAT). This project should facilitate future deployment of GHC, CHP, and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources. Increased deployment of GHC and GDU will help achieve national and local decarbonization goals.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Understanding Decision-Relevant Regional Data Products: Workshop Report

A broad community of climate adaptation practitioners, stakeholders and policymakers rely on historical reconstructions and future projections of local to regional climate. To be of value to these users, climate data must be credible, salient, and authoritative (Cash et al. 2002). Namely, data must be consistent with our physical understanding of the global Earth system, must be relevant for informing the decision-making process, and must be backed by expert judgment. As more and more data products have become available, multiple challenges have emerged around the production, evaluation, selection, and use of these data products. Consequently, to ensure crucial decisions leverage the best possible historical and future physical climate data, there is a pressing need to develop a coordinated national climate data strategy that is inclusive of all relevant communities of practice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Plutonium Oxidation State Distribution in the Presence of WIPP-Relevant Organics and Iron Corrosion Products

The oxidation state and solubility of plutonium (Pu) in high ionic strength synthetic WIPP (Waste Isolation Pilot Plant) brines as a function of pC H+ in the presence and absence of WIPP-relevant organic ligands (EDTA [Ethylenediaminetetraacetic acid], oxalate, citrate, acetate) and iron corrosion products (magnetite and metallic iron) at 𝑇 = 23 ± 2 ∘C was thoroughly studied by long-term batch solubility experiments (between approximately 800-1,100 days) from an undersaturation approach. The oxidation state of Pu in the WIPP environment has been a topic of interest since the initial Compliance Certification Application (CCA). This study aims to investigate the solubility of Pu under the expected WIPP conditions and to determine the oxidation state of the solid phase that will control the solubility. One of the most important results of this study is that the Pu oxidation state was analyzed both from the surface area of the corrosion products and in the precipitated solid. The analysis of the Pu oxidation state on the surface of the iron mineral from the ongoing undersaturated experiments is more relevant to the performance assessment of nuclear waste disposal than short term batch (plutonium-iron phase) experiments. The X-ray Absorption Near-Edge Spectroscopy (XANES) analysis showed that Pu oxidation state is different on the metal surface and in the precipitated solid. Pu(III) is the dominant oxidation state in the metallic iron (Fe 0 ) system in the presence and absence of organics. Pu(IV) is the dominant oxidation state in the magnetite system in the presence and absence of organics. Also, organics stabilize Pu(IV) in the magnetite system. Analysis of Pu in the precipitated solid by Extended X-ray Absorption Fine Structure (EXAFS) analysis showed that Pu formed an inner-sphere complex with iron with minor amounts of PuO 2 present. X-ray diffraction (XRD) results indicate that metallic iron and magnetite did not oxidize in three years in the alkaline and high ionic strength system. Under these conditions (8 < pC H+ < 10 at T = (22 ± 2) °C under nitrogen atmosphere, the solubility of Pu changes by up to three orders of magnitude (10 -5 and 10 -8 M). The spread in solubility is highest at pC H+ = 9. Pu(III) and Pu(IV) showed different solubility behavior in the synthetic WIPP brine. A summary of the data collected in this report will be submitted to Sandia National Laboratories as part of a parameter update report which will outline the changes to the OXSTAT parameter for the 2026 Compliance Recertification Application (CRA-2026). The experiments performed were done according to the U.S. Department of Energy (DOE) approved Test Plan entitled “Effects of Radiolysis, Organic Complexation, and Redox Conditions on the Speciation and Oxidation State Distribution of Pu(III/IV)” (LCO-ACP-25). All data reported were obtained under the Los Alamos National Laboratory-Carlsbad Office (LANL-CO) Quality Assurance Program, which is compliant with the DOE Carlsbad Field Office, Quality Assurance Program Document (CBFO/QAPD).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Demonstrating Advanced Sensors for In-Situ Monitoring Towards Qualification of Nuclear Relevant Components

The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Literature Review of Selected Publications Relevant to Carbon Dioxide Pipeline and Storage Systems

The annotated bibliographies provided in this document focus on identifying and reviewing environmental impact statements (EIS), environmental assessments (EA), and scientific literature relevant to aspects of CO 2 pipeline and storage construction and operation. The purpose of these summaries is to aid stakeholders responsible for the preparation of documents compliant with the National Environmental Policy Act (NEPA) requirements to have access to a quick and comprehensive guide of the literature that can inform their activities. They aim to inform the development of EISs and EAs by identifying potential environmental concerns and mitigation strategies. The annotated bibliographies captured in this document cover the general environmental assessment and impact topics relevant to CO 2 pipeline and storage construction and operation activities, with the subject of waste creation and handling being specifically pulled out into its own section. The reasoning behind a dedicated section for waste is that many EAs and EISs focus on the description of waste and its impacts, be it caused in routine operation or as a result of an accident.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The impact of physiologically relevant temperatures on physical properties of thylakoid membranes: a molecular dynamics study

Thylakoid membranes are energy-converting membranes with a unique lipid composition. Though the membranes are primarily composed of proteins, their photosynthetic function is strongly influenced by the lipid constituents. Here we characterize, with molecular dynamics (MD) simulations, lipid bilayers with compositions representative of plant thylakoid membranes. We determine, in a wide range of temperatures, the physical parameters of the model membranes which are relevant for the photosynthetic function. We found a marked impact of temperature on membrane permeability due to a combination of increased compressibility and curvature of the membrane at elevated temperatures. With increasing temperatures, we observed increasingly smeared transmembrane density profiles of the membrane forming lipid headgroups predicting increased membrane flexibility. The diffusion coefficient of the lipids increased with temperature without apparent specificity for lipid species. Instead of a comprehensive experimental dataset in the relevant temperature range, we quantitatively compared and validated our MD results with MD simulations on a dipalmitoylphosphatidylcholine model system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Editorial: Using high energy density plasmas for nuclear experiments relevant to nuclear astrophysics

Thermonuclear reaction rates and nuclear processes have traditionally been explored by means of accelerator experiments, which are difficult to execute at conditions relevant to nucleosynthesis. High energy density (HED) plasmas generated using lasers, such as the inertial confinement fusion (ICF) platform, more closely mimic astrophysical environments in several ways, including with thermal distributions of reacting ions as opposed to mono-energetic ions impinging on a cold target; stellar-relevant plasma temperatures and densities; and neutron flux densities not found anywhere else on earth. The most extreme conditions can currently be achieved at the National Ignition Facility (NIF) laser in the US, where densities of 10 3 g/cm 3 and neutron fluxes up to 5∙10 27 neutrons/cm/s have been demonstrated over a time period of a few tens of picoseconds. The HED platform is emerging as an interesting complement to accelerator experiments.

charged-particle-induced reactions↗
DOE OSTI2022

A Chemical-Free Pretreatment for Biosynthesis of Bioethanol and Lipids from Lignocellulosic Biomass: An Industrially Relevant 2G Biorefinery Approach

A wide range of inorganic and organic chemicals are used during the pretreatment and enzymatic hydrolysis of lignocellulosic biomass to produce biofuels. Developing an industrially relevant 2G biorefinery process using such chemicals is challenging and requires more unit operations for downstream processing. A sustainable process has been developed to achieve industrially relevant titers of bioethanol with significant ethanol yield. The pretreatment of sorghum biomass was performed by a continuous pilot-scale hydrothermal reactor followed by disk milling. Enzymatic hydrolysis was performed without washing the pretreated biomass. Moreover, citrate buffer strength was reduced to 100-fold (50 mM to 0.5 mM) during the enzymatic hydrolysis. Enzymatic hydrolysis at 0.5 mM citrate buffer strength showed that significant sugar concentrations of 222 ± 2.3 to 241 ± 2.3 g/L (glucose + xylose) were attained at higher solids loadings of 50 to 60% (w/v). Furthermore, hydrolysates were fermented to produce bioethanol using two different xylose-fermenting Saccharomyces cerevisiae strains and a co-culture of xylose-fermenting and non-GMO yeast cultures. Bioethanol titer of 81.7 g/L was achieved with an ethanol yield of 0.48 gp/gs. Additionally, lipids were produced using the oleaginous yeast Rhodosporidium toruloides, yielding 13.2 g/L lipids with cellular lipid accumulation of 38.5% w/w from 100 g/L of sugar concentration. In summary, reducing the strength of the citrate buffer during enzymatic hydrolysis and omitting inorganic chemicals from the pretreatment process enhances the fermentability of hydrolysates and can also reduce operating costs.

Deshavath, Narendra Naik↗
DOE OSTI2020

Assessing the Reliability of Relevant Tweets and Validation Using Manual and Automatic Approaches for Flood Risk Communication

While Twitter has been touted as a preeminent source of up-to-date information on hazard events, the reliability of tweets is still a concern. Our previous publication extracted relevant tweets containing information about the 2013 Colorado flood event and its impacts. Using the relevant tweets, this research further examined the reliability (accuracy and trueness) of the tweets by examining the text and image content and comparing them to other publicly available data sources. Both manual identification of text information and automated (Google Cloud Vision, application programming interface (API)) extraction of images were implemented to balance accurate information verification and efficient processing time. The results showed that both the text and images contained useful information about damaged/flooded roads/streets. This information will help emergency response coordination efforts and informed allocation of resources when enough tweets contain geocoordinates or location/venue names. This research will identify reliable crowdsourced risk information to facilitate near real-time emergency response through better use of crowdsourced risk communication platforms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Uptake, Efflux, and Sequestration of Mercury in the Asian Clam, Corbicula fluminea , at Environmentally Relevant Concentrations, and the Implications for Mercury Remediation

(1) Mercury (Hg) is a persistent, ubiquitous contaminant that readily biomagnifies into higher trophic level species in aquatic environments across the globe. It is crucial to understand the movement of environmentally relevant concentrations of Hg in impacted freshwater streams to minimize risks to ecological and human health. (2) The bioconcentration kinetics of aqueous Hg exposure (20, 100, and 200 ng/L) in the invasive Asian Clam, Corbicula fluminea, were measured. A toxicokinetic model, the first parameterized for Hg accumulation in freshwater clams, was developed to estimate uptake and efflux parameters and compared to previous parameter values estimated for other mollusk species. (3) Results demonstrated that even at low Hg concentrations, Corbicula record signals of contamination through bioconcentration, and both direct measurement and toxicokinetic models demonstrate large Hg bioconcentration factors (as high as 1.34 × 10 5 mL/g dry tissue), similar to partitioning coefficients seen in engineered Hg sorbents. (4) Our study found that Corbicula accumulated Hg at aqueous concentrations relevant to impacted streams, but well below regulatory drinking water limits, demonstrating their utility as a sensitive sentinel species and potential bioremediator.

bioaccumulation↗
DOE OSTI2024

The annual cycle and sources of relevant aerosol precursor vapors in the central Arctic during the MOSAiC expedition

Abstract. In this study, we present and analyze the first continuous time series of relevant aerosol precursor vapors from the central Arctic (north of 80° N) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. These precursor vapors include sulfuric acid (SA), methanesulfonic acid (MSA), and iodic acid (IA). We use FLEXPART simulations, inverse modeling, sulfur dioxide (SO2) mixing ratios, and chlorophyll a (chl a) observations to interpret the seasonal variability in the vapor concentrations and identify dominant sources. Our results show that both natural and anthropogenic sources are relevant for the concentrations of SA in the Arctic, but anthropogenic sources associated with Arctic haze are the most prevalent. MSA concentrations are an order of magnitude higher during polar day than during polar night due to seasonal changes in biological activity. Peak MSA concentrations were observed in May, which corresponds with the timing of the annual peak in chl a concentrations north of 75° N. IA concentrations exhibit two distinct peaks during the year, namely a dominant peak in spring and a secondary peak in autumn, suggesting that seasonal IA concentrations depend on both solar radiation and sea ice conditions. In general, the seasonal cycles of SA, MSA, and IA in the central Arctic Ocean are related to sea ice conditions, and we expect that changes in the Arctic environment will affect the concentrations of these vapors in the future. The magnitude of these changes and the subsequent influence on aerosol processes remains uncertain, highlighting the need for continued observations of these precursor vapors in the Arctic.

Boyer, Matthew↗
DOE OSTI2026

Farm Practice Typologies as a Strategy for Management-Relevant Land Use and Land Cover Mapping in the Great Lakes Region (Version 1) [Dataset]

Dataset overview and development This dataset provides spatially explicit agricultural land-use and land-management typologies developed for the Great Lakes Region (GLR) at the farm-parcel level. The typologies were designed to characterize not only the land-use and land-cover (LULC) associated with individual agricultural farm parcels, but also the land-management practices (LMPs), including irrigation, tile drainage, and conservation easements, occurring within those parcels and how these characteristics change through time. The dataset contains four related typology products: Annual integrated typology – describes the combined LULC and land-management characteristics for each farm parcel for individual years. LULC transition typology – describes the temporal pattern of LULC change for each farm parcel across the study period (2008-2023). LMP trend typology – describes the temporal pattern in the occurrence of LMPs for each farm parcel across the study period. Multi-year integrated typology – combines the LULC transition typology and LMP trend typology to provide an integrated characterization of long-term land-use and management patterns. Purpose of the dataset The purpose of these products is to provide a management-relevant integrated and consistent framework for evaluating the spatial and temporal organization of agricultural landscapes across the GLR. The resulting typologies can: support landscape-scale environmental and land-use analysis; provide spatial information relevant to land-management strategies, conservation planning, policy development, and program evaluation; characterize spatial patterns of agricultural land use and management; examine changes in agricultural landscapes through time; and identify persistent, transitional, and changing agricultural systems. Please refer to the README file provided in Files for more details.

Agriculture↗