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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

FY21 NNSA-IAEC Science Area V, Environmental ISR, Waste Management and Subsurface Science (Final Report)

The FY21 NNSA NA-22 Final Report represents the progress achieved over the past year (FY21) by the research team for Topic Area 3, Waste Management & Subsurface Science (WM3), and Topic Area 7, Radiation and Thermal Effects on Bituminous Rocks (WM7). WM3 and WM7 are part of Science Area V (Subsurface Science and Waste Management) in the NNSA-IAEC Science and Technology Working Group. The project was initiated four years ago (2017) with an MOU agreement between the U.S. National Nuclear Security Administration (NNSA) and the Israel Atomic Energy Commission (IAEC) to evaluate the feasibility of geological subsurface disposal of radioactive waste in Israel. The core WM3 and WM7 teams are comprised of scientists and engineers from Los Alamos National Laboratory, the Geologic Survey of Israel (GSI), and the Nuclear Research Center - Negev (NRCN), with a close collaboration to the teams from Sandia National Laboratory (SNL) and Lawrence Livermore Laboratory (LLNL)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Making an s1G Self-Preserving Environmental DNA (eDNA) Filter from Sustainable Materials

Environmental DNA (eDNA) sampling of aquatic environments is a powerful new tool for resource managers to use in detecting the presence of rare and endangered species. The use of eDNA for species detection is quickly becoming an industry-standard methodology in environmental science, and the technology sector is moving quickly to create purpose-built tools for eDNA sampling. Smith-Root, Inc. pioneered the new technology of self-preserving eDNA filters that automatically preserve the DNA captured on filters by desiccating the internal filter membrane. This capability saves the sampling technician significant time in the field and drastically reduces the potential for sample contamination. One main constraint of this new technology, however, is the necessity of single-use plastics for eDNA sampling. Single-use designs are employed because sampling equipment must be devoid of potential contaminating DNA, and the time required to sterilize equipment is often not cost-effective for practitioners. Thus, this technology is creating a significant new source of plastic waste—something that eDNA practitioners, and society, would like to avoid. This project explores the use of alternative bio based polymers and composites as replacements for incumbent industrial standards for eDNA filtration systems, with an emphasis on ease of processing and biodegradable options. 8 candidate materials, 3 for the top filter housing and 5 for the bottom filter housing, were investigated to replace incumbent housing materials. Of the 8 candidates, 2 materials were identified for future investigation which met performance requirements, were bio-based and could potentially offer better disposal options like soil degradation or composting, features sought by the customers of these products. The top housing candidate, material 1, has comparable performance to the incumbent material and equally manufacturable. The bottom housing candidate, material 6, improved desiccation performance by 81% after 1 hour in comparison to the incumbent material, is 100% bio-based, compostable and can be sourced domestically throughout the U.S.A.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probing Noncovalent Interaction Strengths of Host-Guest Complexes Using Negative Ion Photoelectron Spectroscopy

Noncovalent interactions (NCIs) are crucial for the formation and stability of host-guest complexes, which have wide-ranging implications across various fields, including biology, chemistry, materials science, pharmaceuticals, and environmental science. However, since NCIs are relatively weak and sensitive to bulk perturbation, direct and accurate measurement of their absolute strength has always been a significant challenge. This concept article aims to demonstrate the gas-phase electrospray ionization (ESI)-negative ion photoelectron spectroscopy (NIPES) as a direct and precise technique to measure the absolute interaction strength, probe nature of NCIs, and reveal the electronic structural information for host-guest complexes. Here, our recent studies in investigating various host-guest complexes that involve various types of NCIs such as anion–π, (di)hydrogen bonding, charge-separated ionic interactions, are overviewed. Finally, a summary and outlook are provided for this field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

2023 SAGE-Camp Report

The 7 th Summer Physics Camp for Young Women was successfully held in person in 2023 from June 5 th to 16 th at the New Mexico School for the Arts in Santa Fe, NM at Hilo Intermediate School in Hawaii. This year’s camp was dedicated to the topic of Energy Security and was made possible thanks to the strong collaboration of Los Alamos, Sandia and Hawaii teams and the logistical and financial support of Los Alamos and Sandia National Laboratories, New Mexico Consortium, SAGE- Moore Foundation, LANL Foundation, ACS, IEE, APS four corners, N3B, Hawaii Museum of Science and Technology, New Mexico School for the Arts (NMSA) and Tech Source. The camp mobilized more than 120 volunteers who made the camp a success. The camp is free of charge to the students and included free lunch and snacks for the busy brains to have plenty of energy, also included all materials needed for the hands-on activities (like drone building, crystal structure, solar panels, wind turbine fabrication, soldering, coding etc) and also a stipend for students who attended for the full two weeks and for two educators and two student mentors in NM. The camp offered 32 high school students from New Mexico and 8 from Hawaii a unique opportunity to explore science topics and meet a broad range of role model professionals across STEM fields including astrophysics, cybersecurity, Energy fields, space science, engineering, biophysics, environmental science, robotics, computer science, nuclear engineering, radiological science, physics and chemistry. With nearly 120 volunteers who came mainly from Los Alamos National Laboratory (66%) and Sandia national laboratories (18%), two funded educators from NM, Dr. Weldon Beauchamp and Dr. Ellee Cook, and two educators from Hilo, Dr. Pascale Creek Pinner and LeAnn Ragasa, the camp was educationally sound and extremely varied. The collaboration with school educators is critical for the goal of this camp to not only impact students' lives but also improve STEM education in NM and Hawaii. The ultimate goal of the camp is to increase higher education aspirations of students, empower them to consider careers in STEM and learn more about the opportunities available to them in our local colleges and DOE National Laboratories. In addition, the camp also hired 2 past students as student mentors, Megan Odom and Elisea Jackson, who currently attend NMSA and were students at the camp in 2022 when it was virtual. The in-person camp which aims at empowering under-represented minorities in STEM in our community received more than 52 applications this year from all over NM and 8 applications from Hawaii. Our selection criteria are based on diversity, equity and inclusion, and students for whom the camp can be a life-changing opportunity are given a chance to attend the camp. During COVID, the camp was held virtually and gave the opportunity to students from remote areas in NM and Hawaii to attend from their homes. This year, fantastic families supported students everyday even when home was in remote areas in NM like Lea county, Sandoval county, Bernalillo or Mora county. The organizers hope next year they can offer a residential option for students from remote areas.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Evaluating the Benefits of Bayesian Hierarchical Methods for Analyzing Heterogeneous Environmental Datasets: A Case Study of Marine Organic Carbon Fluxes

Large compilations of heterogeneous environmental observations are increasingly available as public databases, allowing researchers to test hypotheses across datasets. Statistical complexities arise when analyzing compiled data due to unbalanced spatial sampling, variable environmental context, mixed measurement techniques, and other reasons. Hierarchical Bayesian modeling is increasingly used in environmental science to describe these complexities, however few studies explicitly compare the utility of hierarchical Bayesian models to simpler and more commonly applied methods. Here we demonstrate the utility of the hierarchical Bayesian approach with application to a large compiled environmental dataset consisting of 5,741 marine vertical organic carbon flux observations from 407 sampling locations spanning eight biomes across the global ocean. We fit a global scale Bayesian hierarchical model that describes the vertical profile of organic carbon flux with depth. Profile parameters within a particular biome are assumed to share a common deviation from the global mean profile. Individual station-level parameters are then modeled as deviations from the common biome-level profile. The hierarchical approach is shown to have several benefits over simpler and more common data aggregation methods. First, the hierarchical approach avoids statistical complexities introduced due to unbalanced sampling and allows for flexible incorporation of spatial heterogeneitites in model parameters. Second, the hierarchical approach uses the whole dataset simultaneously to fit the model parameters which shares information across datasets and reduces the uncertainty up to 95% in individual profiles. Third, the Bayesian approach incorporates prior scientific information about model parameters; for example, the non-negativity of chemical concentrations or mass-balance, which we apply here. We explicitly quantify each of these properties in turn. We emphasize the generality of the hierarchical Bayesian approach for diverse environmental applications and its increasing feasibility for large datasets due to recent developments in Markov Chain Monte Carlo algorithms and easy-to-use high-level software implementations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

FIU Project 2: Environmental Remediation Science & Technology [Slides]

FIU’s research under this project involves conducting basic and applied science to fill knowledge gaps and validate potential remediation technologies for contaminated soil and groundwater and the assessment of the fate and transport of contaminants in the environment. The aim of FIU’s research is to reduce the potential for contaminant mobility or toxicity in the surface and subsurface through the development and application of state-of-the-art scientific and environmental remediation technologies at the Hanford Site, Savannah River Site (SRS), and the Waste Isolation Pilot Plant (WIPP), which is the Nation’s only mined geologic repository for permanent disposal of transuranic waste. FIU collaborates with scientists from Pacific Northwest National Laboratory (PNNL), Savannah River National Laboratory (SRNL), Savannah River Ecology Laboratory (SREL), Los Alamos National Laboratory (LANL) and the DOE Carlsbad Field Office (CBFO) in order to plan and execute research that is synergistic with the work being conducted at the sites, and that supports the resolution of critical science and engineering needs which leads to a better understanding of the long-term behavior of subsurface contaminants. The knowledge gained through this research will be used to transform experimental and modeling innovations into practical applications deployed at the sites to support EM’s primary goal of expediting the closure of major contaminated soil and groundwater sites and waste units. Collaborative relationships between FIU and the national laboratories have provided large benefits over the years to FIU, the national laboratories, the DOE complex, and the DOE EM mission. By working closely with the national laboratories, FIU’s research is not only closely aligned with the cleanup mission priorities at the DOE sites, but complements and supports ongoing work at the national laboratories for screening of new remedial technologies. This coordination and leveraging of research efforts results in time- and cost-savings, and will accelerate progress of the DOE EM environmental restoration mission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Sample Identifiers and Metadata to Support Data Management and Reuse in Multidisciplinary Ecosystem Sciences

Physical samples are foundational entities for research across biological, Earth, and environmental sciences. Data generated from sample-based analyses are not only the basis of individual studies, but can also be integrated with other data to answer new and broader-scale questions. Ecosystem studies increasingly rely on multidisciplinary team-science to study climate and environmental changes. While there are widely adopted conventions within certain domains to describe sample data, these have gaps when applied in a multidisciplinary context. In this study, we reviewed existing practices for identifying, characterizing, and linking related environmental samples. We then tested practicalities of assigning persistent identifiers to samples, with standardized metadata, in a pilot field test involving eight United States Department of Energy projects. Participants collected a variety of sample types, with analyses conducted across multiple facilities. We address terminology gaps for multidisciplinary research and make recommendations for assigning identifiers and metadata that supports sample tracking, integration, and reuse. Furthermore, our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Lawrence Livermore National Laboratory Environmental Report 2021

The purposes of the Lawrence Livermore National Laboratory Environmental Report 2021 are to record Lawrence Livermore National Laboratory’s (LLNL’s) compliance with environmental standards and requirements, describe LLNL’s environmental protection and remediation programs, and present the results of environmental monitoring at the two LLNL sites—the Livermore Site and Site 300. The report is prepared for the U.S. Department of Energy (DOE) by LLNL’s Environmental Functional Area. Submittal of the report satisfies requirements under DOE Order 231.1B, “Environment, Safety and Health Reporting,” and DOE Order 458.1, “Radiation Protection of the Public and Environment.” The report is distributed electronically and is available at https://saer.llnl.gov/, the website for the LLNL annual environmental report. Previous LLNL annual environmental reports beginning with 1994 are also on the website. Some references in the electronic report text are underlined, which indicates that they are clickable links. Clicking on one of these links will open the related document, data workbook, or website. Sampling location maps throughout this report were created using ArcGIS® software by Esri. The report begins with an executive summary, which provides the purpose of the report and an overview of LLNL’s compliance and monitoring results. The first three chapters provide background information: Chapter 1 is an overview of the location, meteorology, and hydrogeology of the two LLNL sites; Chapter 2 is a summary of LLNL’s compliance with environmental regulations; and Chapter 3 is a description of LLNL’s environmental programs with an emphasis on the Environmental Management System including pollution prevention. The majority of the report covers LLNL’s environmental monitoring programs and monitoring data for 2021: effluent and ambient air monitoring and dose assessment (Chapter 4); waters, including wastewater, storm water runoff, surface water, rain, and groundwater (Chapter 5); and terrestrial, including soil, sediment, vegetation, foodstuff, ambient radiation, and special status wildlife and plants (Chapter 6). The remaining two chapters discuss LLNL’s groundwater remediation program (Chapter 7), and quality assurance for the environmental monitoring programs (Chapter 8). Complete monitoring data, which are summarized in the body of the report, are provided in Appendix A. The report uses Système International units, consistent with the federal Metric Conversion Act of 1975 and Executive Order 12770, “Metric Usage in Federal Government Programs” (1991). For ease of comparison to environmental reports issued prior to 1991, dose values and many radiological measurements are given in both metric and U.S. customary units. A conversion table is provided in the glossary. The report is the responsibility of LLNL’s Environmental Functional Area. Monitoring data were obtained through the combined efforts of the Environmental Functional Area; Environmental Restoration Department; Physical and Life Sciences Environmental Monitoring Radiological Laboratory; and the Radiation Protection Functional Area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

APS Science 2020 (Vol. 2)

The U.S. Department of Energy's Advanced Photn Source (APS) is one of the world’s most productive x-ray light source facilities. Each year, the APS provides high-brightness x-ray beams to a diverse community of more than 5,000 researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. Researchers using the APS produce over 2,000 publications each year detailing impactful discoveries, and solve more vital biological protein structures than users of any other x-ray light source research facility. APS x-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nation’s economic, technological, and physical well-being. The APS occupies an 80-acre site on the Argonne campus, about 25 miles from downtown Chicago, Illinois. It shares a site with the Center for Nanoscale Materials and the Advanced Protein Characterization Facility.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

AmeriFlux US-xRN NEON Oak Ridge National Lab (ORNL)

This is the AmeriFlux version of the carbon flux data for the site US-xRN NEON Oak Ridge National Lab (ORNL). Site Description - Oak Ridge National Laboratory (ORNL) is located at the U.S. Department of Energy's Oak Ridge Reservation in Roane County, Tennessee. The ORNL reservation is situated within the borders of five parallel ridges and valleys to the north of the Clinch River that are part of the Ridge-and-Valley Appalachians physiographic province (Environmental Sciences Division n.d.). The NEON tower site and Walker Branch aquatic site at ORNL are located within the Walker Branch Watershed, a 100 ha area that has served as the site for long-term environmental studies by the Environmental Sciences Division at ORNL, NOAA, and many visiting university researchers.

Network), NEON (National Ecological Observatory↗
DOE OSTI2025

AmeriFlux FLUXNET-1F US-xRN NEON Oak Ridge National Lab (ORNL)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xRN NEON Oak Ridge National Lab (ORNL). This is the FLUXNET version of the carbon flux data for the site US-xRN NEON Oak Ridge National Lab (ORNL) produced by applying the standard ONEFlux (1F) software. Site Description - Oak Ridge National Laboratory (ORNL) is located at the U.S. Department of Energy's Oak Ridge Reservation in Roane County, Tennessee. The ORNL reservation is situated within the borders of five parallel ridges and valleys to the north of the Clinch River that are part of the Ridge-and-Valley Appalachians physiographic province (Environmental Sciences Division n.d.). The NEON tower site and Walker Branch aquatic site at ORNL are located within the Walker Branch Watershed, a 100 ha area that has served as the site for long-term environmental studies by the Environmental Sciences Division at ORNL, NOAA, and many visiting university researchers.

Network), NEON (National Ecological Observatory [N↗
DOE OSTI2024

The influence of exploration activities of a potential lithium mine to the environment in Western Serbia

The proposed exploitation of the Jadar Valley lithium/borate deposit in Serbia, by the Rio Tinto Corporation, indicates that it would become large-scale processing of boron- and lithium-containing ore. It would be one of the world’s very first lithium mines in populated and agricultural area. The company claims that the envisioned mining will be in accordance with environmental protection requirements. The Jadar Valley deposits have been claimed to cover 90% of Europe’s current lithium needs. Yet, local opposition to the mining has arisen due to potential devastating impacts on groundwater, soil, water usage, biodiversity loss, and waste accumulation. Research drilling by the mining company has already produced environmental damage, with mine water containing high levels of boron leaking from exploratory wells and causing crops to dry out. Furthermore, our investigations reveal substantially elevated downstream concentrations of boron, arsenic, and lithium in nearby rivers as compared to upstream regions. Additionally, here we show that soil samples exhibit repeated breaches of remediation limit values with environmental consequences on both surface and underground waters. With the opening of the mine, problems will be multiplied by the tailings pond, mine wastewater, noise, air pollution, and light pollution, endangering the lives of numerous local communities and destroying their freshwater sources, agricultural land, livestock, and assets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Plant single-cell solutions for energy and the environment

Progress in sequencing, microfluidics, and analysis strategies has revolutionized the granularity at which multicellular organisms can be studied. In particular, single-cell transcriptomics has led to fundamental new insights into animal biology, such as the discovery of new cell types and cell type-specific disease processes. However, the application of single-cell approaches to plants, fungi, algae, or bacteria (environmental organisms) has been far more limited, largely due to the challenges posed by polysaccharide walls surrounding these species’ cells. In this perspective, we discuss opportunities afforded by single-cell technologies for energy and environmental science and grand challenges that must be tackled to apply these approaches to plants, fungi and algae. We highlight the need to develop better and more comprehensive single-cell technologies, analysis and visualization tools, and tissue preparation methods. We advocate for the creation of a centralized, open-access database to house plant single-cell data. Finally, we consider how such efforts should balance the need for deep characterization of select model species while still capturing the diversity in the plant kingdom. Investments into the development of methods, their application to relevant species, and the creation of resources to support data dissemination will enable groundbreaking insights to propel energy and environmental science forward.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Attention-based convolutional capsules for evapotranspiration estimation at scale

Evapotranspiration (ET) measures the amount of water lost from the Earth's surface to the atmosphere and is an integral metric for both agricultural and environmental sciences. Understanding and quantifying ET is critical for achieving effective management of freshwater and irrigation systems. However, current ET estimation models suffer from a trade-off between accuracy and spatial coverage. In this study, we introduce our model Quench, a neural network architecture that achieves highly-accurate ET estimates over large continuous spatial extents. Quench uses our novel Attention-Based Convolutional Capsule for its neural network layers to identify areas of focus and efficiently extract ET information from satellite imagery. Benchmarks that profile our model's performance show substantive improvements in accuracy, with up to 128% increase in accuracy compared to traditional convolutional-based and process-based models. Finally, Quench also demonstrates consistent model performance over high geospatial variability and a diverse array of regions, seasons, climates, and vegetations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

New Opportunities for Neutrons in Environmental and Biological Sciences

The use of neutron methods in environmental and biological sciences is rapidly emerging and accelerating with the development of new instruments at neutron user facilities. This article, based on a workshop held at Oak Ridge National Laboratory (ORNL), offers insights into the application of neutron techniques in environmental and biological sciences. Here we highlight recent advances and identify key challenges and potential future research areas. These include soil and rhizosphere processes, root water dynamics, plant-microbe interactions, structure and dynamics of biological systems, applications in synthetic biology and enzyme engineering, next-generation bioproducts, biomaterials and bioenergy, nanoscale structure, and fluid dynamics of porous materials in geochemistry. We provide an outlook on emerging opportunities with an emphasis on new capabilities that will be enabled at the Spallation Neutron Source Second Target Station currently under design at ORNL. The mission of scientific neutron user facilities worldwide is to enable science using state-of-the-art neutron capabilities. We aim to encourage researchers in the environmental and biological research community to explore the unique capability afforded by neutrons at these facilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

BASIN-3D: A brokering framework to integrate diverse environmental data

Diverse observational and simulation datasets are needed to understand and predict complex ecosystem behavior over seasonal to decadal and century time-scales. Integration of these datasets poses a major barrier towards advancing environmental science, particularly due to differences in the structure and formats of data provided by various sources. Here, we describe BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets), a data integration framework designed to dynamically retrieve and transform heterogeneous data from different sources into a common format to provide an integrated view. BASIN-3D enables users to adopt a standardized approach for data retrieval and avoid customizations for the data type or source. We demonstrate the value of BASIN-3D with two use cases that require integration of data from regional to watershed spatial scales. The first application uses the BASIN-3D Python library to integrate time-series hydrological and meteorological data to provide standardized inputs to analytical and machine learning codes in order to predict the impacts of hydrological disturbances on large river corridors of the United States. The second application uses the BASIN-3D Django framework to integrate diverse time-series data in a mountainous watershed in East River, Colorado, United States to enable scientific researchers to explore and download data through an interactive web portal. Thus, BASIN-3D can be used to support data integration for both web-based tools, as well as data analytics using Python scripting and extensions like Jupyter notebooks. The framework is expected to be transferable to and useful for many other field and modeling studies.

Varadharajan, C↗
DOE OSTI2023

Machine learning assisted phase and size-controlled synthesis of iron oxide particles

Synthesis of iron oxides with specific phases and particle sizes is a crucial challenge in various fields, including materials science, energy storage, biomedical applications, environmental science, and earth science. However, despite significant advances in this area, much of the current palette of particle outcomes has been based on time-consuming trial-and-error exploration of synthesis conditions. The present study was designed to explore a very different approach to 1) predict the outcome of synthesis from specified reaction parameters based on using machine learning (ML) techniques, and 2) correlate sets of parameters to obtain products with desired outcomes by a newly designed recommendation algorithm. To achieve this, four ML algorithms were tested, namely random forest, logistic regression, support vector machine, and k-nearest neighbor. Among the models, random forest outperformed the others, attaining 96% and 81% accuracy when predicting the phase and size of iron oxide particles in the test dataset. Surprisingly, the permutation feature importance analysis revealed that volume, which may strongly relate to pressure, was one of the important features, along with precursor concentration, pH, temperature, and time, influencing the phase and size of iron oxide particles during synthesis. To verify the robustness of the random forest models, prediction and experimental results were compared based on 24 randomly generated methods in additive and non-additive systems not included in the datasets. The predictions of product phase and particle size from the models agreed well with the experimental results. Furthermore, a searching and ranking algorithm was developed to recommend potential synthesis parameters for obtaining iron oxide products with the desired phase and particle size from previous studies in the dataset. Furthermore, this study lays the foundation for a closed-loop approach in materials synthesis and preparation, beginning with suggesting potential reaction parameters from the dataset and predicting potential outcomes, followed by conducting experiments and analyses, and ultimately enriching the dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗