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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Back Trajectories during SAIL

This data set contains air mass back trajectories generated during the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT, Stein et al. 2015, Rolph et al. 2017). For each hour from January 1, 2021 to June 30, 2023, a 96-hour back trajectory was initiated at the SAIL sampling site, starting 100 m above ground level. The calculations used the GDAS meteorological data set with model vertical velocity. The files within this dataset show location and meteorological parameters of the back trajectory analysis. There are 21 columns within each data file. The first 2 columns pertain to back trajectory parameters: the trajectory number (which is always 1) and the meteorological grid number. The next 9 columns pertain to spatiotemporal information: the year, month, day, hour (0-23), and minute of the trajectory, the previous time of the trajectory (in negative hours), and the airmass location (latitude, longitude, and height in m AGL). The rest of the parameters within each file pertains to surface and meteorological characteristics of the airmass: pressure (in hPa), potential temperature (in K), temperature (in K), precipitation rate (in mm/hr), mixing depth (in m), relative humidity (in % relative to liquid water), specific humidity (in g/kg), H2O mixing ratio (in g/kg), underlying terrain height (in meters above sea level), and incoming radiation (in W/m^2).

back trajectory↗
DOE OSTI2023

Lime slurry treatment of soils developing on abandoned coal mine spoil: Linking contaminant transport from the micrometer to pedon-scale

Historical and abandoned coal mine spoil continues to generate acid- and metal(loid)-rich porewaters and represents a geographically large and diffuse non-point source of contamination to local watersheds. A potentially inexpensive approach to treat these materials and soils developing on them is through the application of lime slurries, to neutralize acidity and encourage the (co)precipitation of metal(loids) with Fe(III)-(oxy)hydroxides, and potentially other metal-oxides and/or Ca-bearing phases. Here, the efficacy of this approach was evaluated through parallel field application and laboratory-based flow-through column experiments. The field site is Huff Run sub-watershed 25 located in Tuscarawas County, Ohio and was chosen in part because it was previously classified as one of the most highly AMD-impacted sub-watersheds in the region. Two locations with historical spoil were chosen and suction lysimeters were installed at 25 and 75 cm depth to monitor porewater composition on two sides at the base of each pile. Half of each slope received seven lime slurry treatments from June through October of 2017. A suite of aqueous (ICP-OES, IC, and TOC-L) and solid phase geochemical and mineralogical approaches (quantitative SEM-EDS and synchrotron μ-XRF) were used to determine how composition, texture, morphology, and spatial distribution of mineral coatings differ in pre- and post-lime treated soils, and how that impacts the distribution and transport of trace metal(loid)s. Mine spoil porewater at site 1 was slightly less alkaline (pH ranging from 7.04 to 7.37) than at site 2 (ranging from 7.55 to 7.71), and average electrical conductivity values at site 1 (316–405 μS cm —1 ) were slightly lower than at site 2 (358–464 μS cm —1 ), although differences between the sites were not significant. Porewater pH and electrical conductivity in all lysimeters decreased over the course of the field season but there was no obvious response to lime treatment at either site or any depth. At site 1, both treatment and depth were significant factors affecting Ca, K, Ni, SO 4 2— , and DOC concentrations while only treatment effects were significant for dissolved Al and Cu (p < 0.05). For all soils, there were no trends in metal concentration observed over time although DOC and SO 4 2— decreased over the field season. Pedon-scale changes in metal porewater concentrations in response to treatment were linked to micrometer-scale changes in mineral surface coatings; specifically, higher concentrations of Ca, Fe, Mn, and Zn were observed in the coatings and no changes were observed in Fe redox speciation, whereas total S decreased likely due to oxidation of S in coal fragments. In contrast to the field experiment, the column experiments exhibited a much greater response in effluent composition with respect to lime treatment. The untreated columns had approximately an order of magnitude more H + leached over the course of the experiment (p < 0.001) and resulted in greater Ca, Al, Cu, and DIC leached and less Mn, Zn, and SO 4 2— . Soils treated with the lime slurry in the column experiments exhibited larger and thicker secondary Fe-coatings, including the addition of Fe-sulfates. Despite clear trends in the laboratory-based column experiment where the lime-to-soil ratio was higher, the effects were either muted or undetected in the field pilot project, suggesting that a higher application rate of lime in the field is needed to achieve a similar effect. This work provides evidence that a less alkaline lime slurry could be a practical and inexpensive method of treating coal mine spoil-impacted soils and represents an important step in linking laboratory-based remediation studies to implemented field-based studies.

58 GEOSCIENCES↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

ARCUS Vertical-Axis Wind Turbine (Final Scientific/Technical Report)

While land-based wind energy has become economically competitive with traditional energy generation sources in the U.S., offshore wind is not. For floating offshore wind this difference is even more substantial where the levelized cost of energy (LCOE) is projected to be around 3-5 times more expensive than land-based wind. The turbine capital costs represent around 50% of the LCOE for land-based wind sites, but the increased system costs for floating offshore wind reduce this to 20%. The platform and mooring costs are the single largest contributor to the LCOE for floating offshore wind where their mass must counteract the overturning moment caused by the turbine’s thrust force. Despite the high costs of the platform and relatively low cost of the turbine, current offshore wind turbines are designed essentially the same as for land-based sites. Reducing the LCOE is the greatest challenge to realize the benefits of sustained development of floating offshore wind in the U.S. Reducing the complicated system costs of floating offshore wind will enable the industry to continue to grow and outpace current projections if reduced cost curves can be reached. The ideal wind energy system would remove all mass and cost that is not directly capturing energy from the wind. For floating offshore wind energy systems, this objective is even more significant as increased mass above the water level must be supported by larger and more expensive floating platforms. For this reason, vertical-axis wind turbines (VAWTs) are ideal for floating offshore sites and have several advantages over horizontal-axis wind turbines (HAWTs) at this scale. Large VAWTs offer opportunities for improved energy capture over HAWTs as single units and with reduced wind plant aerodynamic losses through enhanced wake recovery. Additionally, the platform-level placement of the VAWT drivetrain greatly reduces the demands placed on the floating platform and its mass and cost. The ARCUS vertical-axis wind turbine concept (U.S. 11,421,650 B2) is an iteration beyond traditional Darrieus-type VAWTs that replaces the rigid tower with blades that are bent into shape and held in place with tensioned center supports, like a bow. The ARCUS design has been shown to further decrease the VAWT rotor mass properties, with a 50% reduction over traditional Darrieus VAWTs quantified in the ATLANTIS program. The ARCUS VAWT’s efficient use of material for the rotor and turbine support structures combined with its lowered center of gravity enables a tension-leg platform (TLP) with simplified installation procedures. TLPs have been an emerging platform architecture in the Oil and Gas industry and demonstrated to have the lowest hull mass requirements while maintaining stability with minimal roll and pitch deflections in operation. A 22 MW ARCUS turbine has been designed with a three-column TLP that enables quayside integration of the turbine while maintaining system stability during tow-out and installation and having optimal mass and cost properties. A comprehensive analysis shows the optimal ARCUS TLP system design minimizes LCOE through efficient material usage and increased energy capture to yield a competitive LCOE estimate of $\$$55/MWh. A comparison with a reference HAWT, having the same swept area, quantifies the advantages that helped to produce this improved LCOE for the ARCUS concept: (1) 30% reduction in total turbine mass, (2) 70% reduction in turbine center of gravity, and (3) 45% increase in energy production over what is optimal for a HAWT. Intellectual property has been generated through the ATLANTIS program providing opportunities to further reduce the LCOE and improve the performance of the ARCUS turbine and TLP system, expanding the list of innovations to support commercial development of the ARCUS concept.

17 WIND ENERGY↗
DOE OSTI2026

Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra: Modeling Archive

This dataset is a model archive of the paper Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra (in prep) to support a modeling study investigating how projected increases in Arctic temperature and precipitation will jointly influence hydrologic conditions in ice-rich tundra landscapes. With this dataset, this study is to address the research question: Will Arctic tundra landscapes become wetter or drier with increasing precipitation and temperature in the future when thaw-induced ground subsidence and associated microtopographic evolution are represented? The simulations focus on ice-wedge polygon tundra, a widespread form of ice-rich permafrost terrain that is highly sensitive to thaw-driven landscape change. This dataset contains model input and output data for four study watersheds in Alaska: Anaktuvuk, Utqiagvik (formerly Barrow), Brooks Foothills, and Prudhoe Bay. Simulations were performed using the Advanced Terrestrial Simulator (ATS, v1.5), a physics-rich integrated surface–subsurface hydrologic model. For each watershed, ten modeling cases were performed representing two landscape evolution conditions (with subsidence and without subsidence) combined with five climate forcing scenarios derived from Shared Socioeconomic Pathways (SSP5, SSP5 with precipitation trend, SSP2, SSP2 with precipitation trend, and SSP2 with double precipitation trend). Particularly, for each watershed under the forcing SSP2 with precipitation trend, there are two additional simulations considering spatially heterogeneous subsidence distributions: one assumes randomly distributed scaling and the other includes elevation dependent distribution scaling. These simulations span 1980–2099 and include spin-up runs (1980–2009) followed by transient projections (2010–2099). To facilitate reproducibility of simulations, all datasets are organized by watershed. For each study watershed, the dataset contains: (1) Pre-partitioned mesh files for 32-core modeling (.par.32.XX), located in EACH_WATERSHED/mesh/basin; and also a non-partitioned mesh file (.exo) located in EACH_WATERSHED/mesh; (2) Climate forcings corresponding to the five SSP scenarios (.h5), located in EACH_WATERSHED/data; (3) Final states (.h5) from column spin-up modeling used to initialize historical watershed-scale spin-up runs from 1980 to 2009, located in EACH_WATERSHED/PreSpinupHistorical; (4) Final states (.h5) of historical watershed-scale spin-up runs from 1980 to 2009 used to initialize projection runs, located in EACH_WATERSHED/Spinup_daymetERA5; (5) ATS modeling input files (.xml), located in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/inputfiles; (6) ATS modeling output files (.dat), located in in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/combined_obs; (7) For the Brooks Foothills watershed, additional spatial model outputs are provided (.h5) for selected years (2033 and 2093) used to generate spatial figures in this study, located in Brooksfoothills/EACH_SIMULATION_SCENARIO/results-WITH/WITHOUT_SUBSIDENCE-year2033/2093. All data files with suffix .h5 can be accessible through Python h5py, and all data files with suffix of .dat can be imported by Python pandas. Mesh file with .exo can be visualized through Paraview or read by Python netCDF. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION↗
DOE OSTI2020

Development and Optimization of a Purification Process to Recover 99 Mo from Low-enriched Uranium

Supported by the DOE-NNSA Office of Material Management & Minimization (M3), a number of domestic entities are pursuing non-highly enriched uranium (non-HEU) production of 99 Mo. As the production technologies of 99Mo pivot toward low-enriched uranium (LEU) or molybdenum targets, new reaction channels and accelerators are being evaluated. Superconducting electron linear accelerators (LINACs) with high-Z converter targets can generate bremsstrahlung photons and neutron fluxes that are capable of inducing photonuclear reactions and LEU fission. A particular advantage of a LINAC is that it does not rely on HEU-fueled reactor cores (which are currently slated for LEU conversion) and can operate on an almost continuous basis. Regarding the chemical purification of 99 Mo from irradiated uranium targets under acidic digestion, there exists a procedure known as Cintichem or modifications thereof with respect to LEU (LEU Modified Cintichem process, LMC). The process relies on a number of selective precipitation steps and column chromatography to purify Mo. It is important to note that LMC prescribes the addition of stable Mo to carry 99 Mo on alpha benzoin oxime, which reduces the specific activity of 99 Mo. This is especially important for processing 99 Mo batches with lower activities (~33 Ci of 99 Mo per batch).

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

OC7 Phase I Definition Document

The Offshore Code Comparison Collaboration 7 (OC7) project is organized under the International Energy Agency Wind Technology Collaboration Programme Task 56 with an objective to evaluate and enhance the predictive accuracy of engineering-level modeling tools used in the design of offshore wind energy systems. Phase I of OC7 is focused on improving the models and modeling practices of hydrodynamic viscous loads on floating offshore wind turbine platforms. In alignment with this goal, Work Package 1.1 of OC7 Phase I is formulated to investigate the modeling of hydrodynamic viscous loads on several different geometric components commonly encountered with floating offshore wind platform designs, including cylindrical columns, heave plates, and rectangular pontoons. Work Package 1.1 also explores the dependence of hydrodynamic coefficients on the sea state to drive toward practical guidance on how these coefficients can be selected or adjusted for different conditions. This report outlines the motivation and objectives behind each subphase of OC7 Phase I, along with the necessary technical specifications and load case definitions to guide the project participants. It also serves as an important part of the project documentation for future modelers who would like to reproduce this work or make use of the data and information generated from the OC7 project.

17 WIND ENERGY↗
DOE OSTI2020

Standoff detection of chemical plumes from high explosive open detonations using a swept-wavelength external cavity quantum cascade laser

A swept-wavelength external cavity quantum cascade laser (ECQCL) is used to perform standoff detection of combustion gases in a plume generated from an outdoor high-explosive (HE) open detonation. The swept-ECQCL system was located at a standoff distance of 830 m from a 41kg charge of LX-14(polymer-bonded high explosive) and was used to measure the infrared transmission/absorption through the post-detonation plume as it propagated through the beam path. The swept-ECQCL was operated continuously to record broadband absorption spectra at 200hz rate over a spectral range from 2050 to 2230 cm -1 (4.48 - 4.88 μm). Fitting of measured spectra was used to determine time-resolved column densities of CO, CO 2 , H 2 O, and N 2 O. Analysis of visible video imagery was used to provide timing correlations and to estimate plume dimensions, from which gas mixing ratios were estimated. Measured emission factors and modified combustion efficiency show good agreement with previously reported values.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive.As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Description and Evaluation of a New Deep Convective Cloud Model Considering In-cloud Inhomogeneity

Convections still need to be parameterized in general circulation models (GCMs) in the coming decades. Performances of GCMs are significantly influenced by the convection schemes used. In contrast to most conventional cloud models that ignore in-cloud inhomogeneities, a new convective cloud model explicitly considering in-cloud inhomogeneities is developed. The new model adopts a single bulk plume approach, but divides the plume into a series of interacting sub-plumes in order to mimic the transition from the plume core to its edges. We implemented the new cloud model in NCAR Community Atmosphere Model version 5.0 (CAM5) and evaluated its performance. Single-column tests show a stronger mass flux profile and low-level detrainment with the new model. In global simulations, the long-lasting wet bias in the tropical free troposphere of CAM5 is alleviated. Spatial pattern and intensity distribution of precipitation is improved, but the global hydrological cycle is slightly over-enhanced. The diurnal cycle of tropical precipitation is also better captured though the precipitation peak still occurs earlier than the observations and the amplitude of the cycle tends to weaken. MJO simulation is slightly improved with the new scheme. In addition, the new cloud model generated more tropical cyclones, in better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Frontal Slice Approaches for Tensor Linear Systems

Inspired by the row and column action methods for solving large-scale linear systems, in this work, we explore the use of frontal slices for solving tensor linear systems. In particular, this paper presents a novel approach for using frontal slices of a tensor $\mathcal{A}$ to solve tensor linear systems $\mathcal{A} ∗\mathcal{X} = \mathcal{B}$ where ∗ denotes the $t$-product. In addition, we consider variations of this method, including cyclic, block, and randomized approaches, each designed to optimize performance in different operational contexts. Our primary contribution lies in the development and convergence analysis of these methods. Experimental results on synthetically generated and real-world data, including applications such as image and video deblurring, demonstrate the efficacy of our proposed approaches and validate our theoretical findings.

Luo, Hengrui↗
DOE OSTI2026

Staged Z-pinch experiment at the double-EAGLE pulsed power facility

The staged Z-pinch is a potential high-energy gain fusion concept where a high atomic number liner implodes on a deuterium target using a pulsed multi-MA current source. Over the past several years this concept has been studied on 0.5–1.0 MA facilities using Ar and Kr gas puffs injected at R = 1.2 cm. Neutron yield up to (2.5 ± 0.34) x 10 10 was measured, Ruskov et al (2023 IEEE Trans. Plasma Sci. 51 3310–6). Here, in this study, we present experimental results from the 4 MA, 110 ns current rise time Double-EAGLE facility at L3Harris (currently, Fisica Inc.) where a larger radius nozzle created gas density profiles peaked at R = 2.5 cm. Modeling with the MACH2 and FLASH codes indicates that the larger radius allows stronger acceleration of the liner plasma and generation of shock waves that preheat a target plasma layer next to the liner to temperatures $T_i >$1 keV. The resulting counter thermal pressure on the liner plasma limits the growth of the Magneto-Rayleigh–Taylor (MRT) instability at the liner-vacuum boundary and the implosion proceeds in a relatively stable manner. Near bang time the enormous target plasma thermal pressure smoothens the MRT perturbations developed during the earlier implosion stages. Time integrated x-ray pinhole images with cutoff energy of 100 eV confirm that a long (∼3 cm), stable and uniform high energy density plasma column is formed in the final implosion stage. Consistent neutron yield in the 10 10 –10 11 range was measured for both Ar and Kr liners imploding on a deuterium target.

Physics - Plasma physics↗
DOE OSTI2025

DeSelenator: A Se-Removal Process for Environmental Decontamination of Wastewaters from Coal-Burning Power Plants

Selenium may become a toxic contaminant of freshwater systems when released into the environment through industrial wastewaters from mining, coal-burning power plants, or oil refining. Efficient and cost-effective Se-removal technologies are therefore necessary to reduce Se concentrations in these wastewaters to below the regulatory discharge limits. In this study, we have demonstrated an effective process that removes Se, mostly as selenate anions, from wastewaters generated by coal-burning power plants. This process, dubbed DeSelenator, leverages the high concentration of sulfate relative to selenate in the wastewater and the propensity of these oxyanions to cocrystallize with benzene-bis-iminoguanidinium (BBIG) cations into extremely insoluble salts (on par with BaSO 4 ). The SO 4 2− /SeO 4 2− cocrystallization with BBIG removes over 90% of S and Se from the wastewater. Following removal of the precipitate by filtration, the filtrate is passed over an anion-exchange resin that further reduces selenium concentration to 5 ppb, the EPA’s regulatory limit for freshwater systems. Finally, the effluent is passed over an activated carbon column, which removes 99.8% of the residual BBIG ligand remaining after crystallization, allowing for the safe discharge of the treated water into the environment. The Se-removal process was first optimized in the lab at the bench scale and then tested in the field at the Tennessee Valley Authority’s Bull Run coal-burning power plant. A technoeconomic assessment found the cost of water treatment with DeSelenator is on par with that of the active biological method, which is currently considered a state-of-the-art Se-removal technology.

anions↗
DOE OSTI2024

Data and scripts associated with the manuscript "Organic Molecules are Deterministically Assembled in River Sediments"

This data package is associated with the publication "Organic Molecules are Deterministically Assembled in River Sediments" submitted to Scientific Reports (Stegen et al., 2024). The study applies community ecology methods to dissolved organic matter (DOM) chemistry from variably inundated riverbed sediments to uncover principles governing DOM composition at a reach-scale. This data package documents the workflow used to process and generate the main findings in the manuscript. The R scripts reference the raw, unprocessed Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data from another data package, available on ESS-DIVE at https://data.ess-dive.lbl.gov/view/doi:10.15485/1834208. The scripts then process the raw FTICR-MS data and generate the findings and figures presented in the associated manuscript. In brief, this study demonstrates that DOM assemblages in variably inundated sediments are primarily governed by deterministic variable selection, including sediment moisture effecting the degree of deterministic assembly. See the manuscript for more details pertaining to interpretation and implications of the findings. This data package is associated with the GitHub repository found at https://github.com/WHONDRS-Hub/ECA_2020_Sed.This data package is comprised of 6 scripts and 7 folders. The file-level metadata file (file ending in "flmd.csv") lists all files contained in this data package and descriptions for each. The data dictionary (file ending in "dd.csv) describes all tabular data columns and their respective definitions and units. The FTICR_Processing_Scripts produce the outputs found in the "Processed_Data" folder. The remaining scripts (located in the parent directory) produce the outputs found in the following four folders: (1) "MCD_Dendrograms", "MCD_Randomizations", "MCD_bNTI_Outcomes", and "OM_Null_Modeling". The fifth script additionally takes the three comma-separated values (CSV) files found in the parent directory as input ("VGC_texture.csv", "merged_weights.csv", and "ECA2_FTICR_BetaDisp.csv"). The outputs of each of the five scripts serve as the input to the following script, with the final outputs stored in the folder "OM_Null_Modeling".

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Generation of low–latitude seamount–trapped waves: a case study of the Seychelles Plateau

Baroclinic seamount-trapped waves are thought to influence their surrounding ecosystem; however, trapped waves are not well-studied in near-equatorial settings, where stratification is strong and Burger numbers are large. Motivated by observations, we use daily output (2005-2009) from the global 0.1-degree Parallel Ocean Program Model (POP) to examine topographically trapped baroclinic waves around the Seychelles Plateau (S > 400) in the tropical Indian Ocean. These trapped waves are associated with velocity and temperature oscillations at periods of 15–16 days, similar to the dominant period of some equatorial Yanai waves. Energy flux maps using POP output suggest that quasi-biweekly equatorial Yanai waves excite trapped waves on the western and south-western flanks of the Seychelles Plateau, near the surface. Here, the anticyclonic energy flux associated with the trapped wave extends vertically throughout the water column and around most of the plateau circumference, diminishing on the eastern flank of the plateau. This work highlights the role that equatorial planetary waves and trapped waves play in facilitating energy redistribution, dissipation, and mixing in the tropical ocean.

58 GEOSCIENCES↗
DOE OSTI2023

Geogenic, Anthropogenic, and Authigenic Minerals Hosting Arsenic and Antimony in Yellowknife Bay Sediments

Abstract Yellowknife Bay (Great Slave Lake, Northwest Territories, Canada) is a water body valued by surrounding communities for its subsistence, recreational, and cultural use. Located directly downstream of the former Giant Mine and Con Mine, Yellowknife Bay has received inputs from mine waste streams enriched in arsenic (As), antimony (Sb), and metals since the late 1930s. Lake sediments in Yellowknife Bay provide a record of metal(loid) contamination from aerially deposited roaster stack emissions, mine effluent, and Giant Mine tailings. A sediment sampling program was conducted in Yellowknife Bay to characterize As and Sb mineralogy using scanning electron microscopy-mineral liberation analysis. Mineralogical analysis of As- and Sb-hosted minerals in nine sediment cores suggests that arsenic trioxide (As2O3), originally deposited during the period of peak-mining emissions, has since been transformed into authigenic sulfides (interpreted to be realgar) down core from peak-mining emissions. Arsenic has also been attenuated by iron (Fe)-oxyhydroxides and roaster-generated iron oxides up-core from peak-mining emissions, near the sediment–water interface. The Sb-bearing minerals appear to be stable in Yellowknife Bay sediments, with no conclusive evidence of post-depositional mobility having been identified. The observed prevalence of arsenic trioxide in surface sediments proximal to Giant Mine suggests that As and Sb contamination is ongoing, likely from terrestrial weathering of contaminated soils and shoreline outcrops. Arsenic-bearing oxide minerals prevalent in surface sediments may become unstable should redox conditions in the hypolimnion change; prolonged anoxia could destabilize the As hosting minerals and release As to bottom waters. Therefore, long-term monitoring of the water column, including hypolimnion conditions, in Yellowknife Bay is recommended.

Mineralogy↗
DOE OSTI2022

Process-oriented stochastic perturbations applied to the parametrization of turbulence and shallow convection for ensemble prediction

Weather forecasting nowadays often requires some estimation of uncertainties associated with the output of meteorological models, in order to better inform decision making, especially in the context of intense weather events. Ensemble prediction systems provide such information through sets of possible scenarios which are designed to represent various uncertainty sources, including model uncertainties. A wide variety of methods have been proposed to estimate model uncertainties, among which perturbation methods targeting uncertain processes are a promising research field. Here, we focus on the representation of small-scale variability by process-oriented perturbation schemes applied to two key physical processes, namely turbulence and shallow convection. The perturbations are applied to a single-column version of the convection-permitting AROME model, in three idealized boundary-layer cases. Large-eddy simulations (LESs) of the same cases serve as a reference for the subgrid variability that has to be represented, and the results are also compared to those given by the Stochastically Perturbed Parametrization Tendencies (SPPT) method, which is a method commonly used by weather forecast centres to represent model uncertainty. The spread produced by our process-oriented perturbations of turbulence and shallow convection does not represent all the small-scale variability implied by the LESs for temperature and humidity. However, it is of a similar order of magnitude for the wind, thanks to perturbations generated by the stochastic turbulence scheme. The dispersion is structurally different from what is obtained with SPPT. It is non-negligible in the lower levels, where SPPT perturbations are usually suppressed because of numerical instabilities, indicating a possible complementarity between the schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Floating Island International PHASE I FINAL TECHNICAL REPORT (Advancing the Development of Floating Solar-Powered Nanobubble Aeration Systems for Use with Floating Treatment Wetlands in Natural and Man-Made Waterbodies)

More and more freshwater lakes are suffering from algae blooms, which deprive water of oxygen and lead to widespread loss of aquatic life and production of dangerous toxins. When oxygen is lacking, methane is generated in the sediments as algae is decomposed; it has been calculated that more than half of global methane emissions come from nutrient-impaired freshwater systems (Beaulieu, 2021). Nutrients, mainly from agricultural run-off, feed algae blooms and are exacerbated by warming related to climate change. Artificial aeration is frequently used to restore oxygen to a waterbody. But diffuser aeration is inefficient and expensive, needs on-site grid power, and is failing to keep pace with the demands of water as it gets warmer with climate change. In the last five years, nanobubble aeration has been introduced into freshwater applications and shows promise for rapidly increasing dissolved oxygen effectively throughout the water column. Nanobubbles deliver oxygen in bubbles that have no buoyancy, so they stay in water longer and release their oxygen more fully, compared to large bubbles that rise and burst at the surface. The prospect of this new technology answering the deficiencies of diffuser aeration drove us to initiate the current project. During our Phase I period, we have successfully tested a nanobubble aeration system that can super-saturate oxygen levels. It is operated on solar power, and both the nanobubbler and solar array are mounted on a proprietary floating island platform, that also performs biological nutrient recycling. A rudimentary system was assembled and tested on a 6.5-acre research lake at our headquarters in Montana, where it was subjected to a summer drought that reduced water levels significantly, periods of severe cold in winter, and spring conditions that included heavy rainfall and violent thunderstorms. Our twice-weekly sampling throughout the project showed that dissolved oxygen levels rose rapidly and were maintained throughout winter and spring, well into June. The nanobubbler was able to run on solar power for long periods. Methane levels were tested periodically and found to decrease as oxygen increased. The nanobubbles appeared to have no adverse impact on fish or other aquatic life exposed to them. The stability of the installation survived the weather conditions. The many problems we encountered taught us what we need to improve in the next iteration. Towards the end of our Phase I, we were awarded a supplementary state grant that enabled us to acquire a new nanobubble system for testing that runs on DC, is extremely efficient and has few moving parts. We plan to team this with low-profile solar panels, lithium batteries and a controller that provides real-time data. The ultimate goal of this project is to commercialize an affordable and scalable lake management system that will oxygenate water from the surface down to the sludge. It will enliven fisheries, prevent toxic algae blooms and – most importantly for the fate of our planet - inhibit the production and release of methane from the sediments. We anticipate that as carbon credits expand to include methane, the cost of remediating waterbodies that produce methane will be offset. We firmly believe that this is a practical technology that works and will make a big difference when fully implemented.

14 SOLAR ENERGY↗