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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

East River Pore Water FTICR-MS Data associated with "Geomorphic and Hydrogeochemical Controls on Fine-Scale Hyporheic Microbiome Assembly and Function"

Pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory).This study aimed to understand organic matter assemblages differ within a streambed with differing geomorphology and the interplay between streambed organic matter and microbiome function. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterization of Extreme Hydroclimate Events in Earth System Models using ML/AI

Focal Area(s): (1) We put forward the concepts of data assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization and unsupervised learning applied to downscale information within Earth System Models (ESMs). (2) We discuss predictive modeling through the use of AI techniques and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection) to improve the characterization of extreme hydroclimate events in ESMs. The AI-based models will run five-six order of magnitude times faster, yet will provide similar accuracy, allowing us to provide range bounds on uncertainty faster and thus enabling faster extreme event identification. (3) Further, we consider the insight gleaned from complex data (observed/simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI to improve the characterization of extreme hydroclimate events in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

GNSS Installation at the ARM North Slope of Alaska Atmospheric Observatory Field Campaign Report

GRUAN, the Global Climate Observing System (GCOS) Reference Upper Air Network, is an international reference observing network of sites measuring essential climate variables above Earth's surface, designed to fill an important gap in the current global observing system. GRUAN’s objectives are to (1) provide long-term, high-quality climate records, (2) constrain and calibrate data from more spatially comprehensive global observing systems (including satellites and current radiosonde networks) and (3) fully characterize the properties of the atmospheric column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Transcriptomic and metabolomic analysis of recalcitrant phosphorus solubilization mechanisms in Trametes gibbosa

Introduction Phosphorus (P) is a crucial growth-limiting nutrient in soil, much of which remains challenging for plants to absorb and use. Unlike chemical phosphate fertilizers, phosphate-solubilizing microorganisms (PSMs) offer a means to address available phosphorus deficiency without causing environmental harm. PSMs possess multiple mechanisms for phosphorus solubilization. Although the phosphorus-solubilizing mechanisms of phosphate-solubilizing bacteria (PSB) have been well characterized, the mechanisms utilized by phosphate-solubilizing fungi (PSF) remain largely unexplored. Methods This study isolated a PSF strain, Trametes gibbosa T-41, from soil and evaluated its phosphorus solubilizing capacity with organic (calcium phytin; Phytin-P) and inorganic (tricalcium phosphate; Ca-P) phosphorus sources. The phosphorus solubilization, enzyme activity, and organic acid production of T-41 were measured. And the P-solubilizing mechanism conducted by transcriptomic and metabolomic analyses. Results and discussion T-41 exhibited varying phosphorus solubilizing capacity when grown with organic (calcium phytin; Phytin-P) and inorganic (tricalcium phosphate; Ca-P) phosphorus sources (109.80 ± 8.9 mg/L vs. 57.5 ± 7.9 mg/L, p < 0.05). Compared with the Ca-P treatment, T-41 demonstrated a stronger alkaline phosphatase (ALP) production capacity under Phytin-P treatment (34.5 ± 1.2 μmol/L/h vs. 19.8 ± 0.8 μmol/L/h, p < 0.05). Meanwhile, the production of oxalic acid, maleic acid, and succinic acid was higher under Phytin-P treatment ( p < 0.05). Transcriptomic and metabolomic analysis revealed that different phosphorus sources altered metabolic pathways such as galactose metabolism, glyoxylate and dicarboxylic acid metabolism, and ascorbate and aldolate metabolism. Key metabolites like myo-inositol, 2-oxoglutarate, and pyruvate were found to impact the performance of T. gibbosa T-41 differently under the two P sources. Notably, synthesis in Ca-P vs. Pytin-P, T-41 upregulated genes involved in myo-inositol synthesis, potentially enhancing its P-solubilizing ability. These results provide new insights into the molecular mechanisms of PSF at the transcriptomic and metabolomic levels, laying a theoretical foundation for the broader application of PSF as bio-phosphorus fertilizers in the future.

Chen, Yulan↗
DOE OSTI2023

Collaborative Proposal: Improving Understanding of the Internal Structure and Dynamics of Deep Convection Using ARM Observations and Large Eddy Simulations (Final progress report)

This is the final technical report for the DOE Atmospheric System Research funded project entitled "Collaborative Proposal: Improving Understanding of the Internal Structure and Dynamics of Deep Convection Using ARM Observations and Large Eddy Simulations". This project addressed several science questions related to the structure and behavior of deep convective clouds in the atmosphere. It applied knowledge gained from this work to improve the deep cumulus convection parameterization in the Community Earth System Model (CESM). Specific outcomes related to the project include an improved understanding of: (1) how convective cloud environments regulate the size of thermals reaching the upper troposphere, and hence the shallow-to-deep convective transition; (2) the role of dynamic pressure forcing in thermal and convective cloud evolution; and (3) the role of vertical wind shear on the behavior of moist thermals and the transition from shallow to deep convection. Although the primary motivation of this project was to improve basic understanding of thermal dynamics in atmospheric convection, an important component of this work was using this improved understanding to modify the representation of entrainment and vertical velocity profiles in the Zhang-McFarlane cumulus parameterization used in CESM. This work also had a strong observational component, with analyses of Atmospheric Radiation Measurement (ARM) observations to characterize thermal characteristics and behavior. Observations collected during the ARM-supported CACTI field project were used with high-resolution simulations to explore environmental controls on deep convection initiation. Data from the ARM-supported MC3E field project were also used to evaluate the representation of updraft vertical velocities in the Zhang-McFarlane cumulus parameterization. This project directly supported the training of two post-doctoral researchers and led to 16 peer-reviewed published papers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing↗
DOE OSTI2020

Combining Chemistry, Material Science, Inspiration from nature, and Serendipity to Develop Stimuli-responsive Polymeric Materials

Neither of us can remember people talking about stimuli-responsive polymers when we were students. Even though this was still in the last century, it was almost 70 years after Staudinger's seminal paper "uber Polymerisation"![1] By the time we entered graduate school in the early 1990 s, the first papers on polymer light emitting diodes appeared, while research on electrically conducting, nonlinear optical, and other "functional" polymers was already in full swing. Looking back, there were some stimuli-responsive materials that were around at the time, but it took the better part of the last 30 years until the field had developed into what we think is one of the most vibrant areas of polymer science. Before the potential usefulness of this class of materials was recognized, researchers were focused on developing polymeric materials that would not respond to external influences, and in fact maintain (in particular) their mechanical properties in a wide range of environments. This has led to the development of many environmentally robust polymers, which have come to impact basically every aspect of our daily life. Ironically, this long-sought stability now comes back to haunt us in the form of plastic pollution, but this is another story. The concept of materials that adapt their properties in response to changing environmental conditions might appear like a complete reversal with respect to the original goals of creating stable materials. However, eventually a) it was recognized that materials that respond to a specific stimulus in a predictable and useful manner would significantly broaden the potential usefulness of polymers, and b) the field of polymer science had developed to the point where the rational design, preparation, and characterization of such materials became possible. The expression 'stimuli-responsive polymer' had been first used in the 1980's, however its use really only gained popularity a few decades later. In the early days, terms such as environmentally-sensitive or environmentally-responsive polymers, stimuli-reversible or stimuli-sensitive polymers, or polymers with phase transitions have also been used.

Rowan, Stuart J.↗
DOE OSTI2025

PFAS Removal by Ion Exchange Resins: Background and Knowledge Gaps with Respect to the Hanford Site

Per- and polyfluoroalkyl substances (PFAS) have been a rising concern for the past two decades, with the United States Department of Defense and Environmental Protection Agency investing millions of dollars in research into remediation and clean-up technologies. Due to the environmental persistence, toxicity, biological uptake, and ongoing changes in both federal and state regulatory space, understanding the fate and transport of PFAS compounds has been of growing concern to the US Department of Energy (DOE). The DOE’s Hanford Site is investigating historical use of PFAS and will be doing site characterization for PFAS. Thus, PFAS have not yet been identified as a contaminant concern in regulatory documents. Based on historical records that mention the discharge of aqueous film-forming foam containing PFAS and having on-site fire stations (a risk factor for PFAS contamination), it seems likely that environmental releases of PFAS may have occurred. Pump and treat (P&T) remediation is the selected remedy for multiple groundwater contaminant plumes at Hanford. These P&T systems use ion exchange (IX) as a component of aboveground treatment, with the specific resins depending on the target contaminants. There is potential that these IX resins may be able to remove PFAS from groundwater, but investigation is needed to understand affinity/selectivity and removal capacity given the groundwater composition and the operating conditions. This report provides background on PFAS uses and chemistry, then provides a review of IX resin applications for PFAS, identifying knowledge gaps. Recommendations are provided regarding research needed to address knowledge gaps and acquire information needed to propose IX as a future PFAS remediation technology at the Hanford Site, as well as other U.S. Department of Energy sites. Generally, PFAS compounds are fluorinated substances that contain at least one fully fluorinated methyl or methylene carbon – with a few noted exceptions, any chemical with at least a perfluorinated methyl group (–CF3) or a perfluorinated methylene group (–CF2–) is a PFAS. These chemical compounds are characterized as non-biodegradable, non-reactive, non-photolytic, and hydrolysis resistant. This makes them highly recalcitrant within the environment, however polyfluoroalkyl materials are less recalcitrant as the carbon chains contain C–H bonds which are more easily broken than carbon – fluorine (C–F) bonds. The backbone carbon structures are commonly punctuated with a head group, the most well-known of them are perfluorooctanesulfonic acid and perfluorooctanoic acid, which possess a sulfonate and a carboxylate group, respectively. IX resins are marketed for the removal of PFAS from water systems and industrial water, however, the mechanism of removal is not as well understood as for anion or cation removal. A better understanding of the mechanism of removal would enable the development of IX resins that have improved specificity for PFAS removal. Four knowledge gaps were identified: 1) the effect of dissolved ions on the IX resin PFAS removal effectiveness, 2) the effect of additional primary contaminants of concern (PCOCs) or secondary contaminants of concern (SCOCs) on the effectiveness of PFAS via IX resin, 3) the mechanisms of PFAS removal from water, and 4) practical solutions to IX resin regeneration and waste disposal.

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

Plasma Flow Reactor Investigation into Nucleation of Uranium Oxide on Silica Substrates to Better Understand Fallout Formation

Understanding particulate formation in nuclear debris is critical for predicting fallout transport after a nuclear event. Improved characterization of fallout formation and transport could lead to better guidance for emergency response in a post-detonation scenario. By analyzing how U-oxides nucleate onto different forms of SiO 2 (crystalline and amorphous), we can gain insight into how entrained environmental materials may incorporate into fallout. In this experiment a Plasma Flow Reactor (PFR), was used to replicate the high temperature and extreme flow conditions in a nuclear fireball. Uranyl nitrate was injected into the plasma, and PFR-generated Uranium oxides were allowed to condense onto amorphous (nanoparticles of varying sizes) or crystalline (quartz) SiO 2 substrates. SiO 2 substrates were characterized before and after U-oxide deposition using Scanning Electron Microscopy (SEM) based techniques (i.e. EDS) in order to characterize how U-oxides may nucleate onto these substrates. After a collection time of 4 minutes at an RF coil distance of 25cm, both the amorphous SiO 2 nanoparticles and the crystalline structures demonstrated dendritic nucleation of U-oxide species as identified by SEM/EDS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Advanced Characterization of Wastewaters with a Focus on the Environment & Economics (Final Technical Progress Report)

This project, funded by the U.S. Department of Energy under award DE-FE0032457 and conducted at the University of Illinois at Urbana-Champaign, focused on advancing the characterization of coal combustion residual (CCR) effluents. The primary objectives were to develop analytical methods for detecting major cations, anions, trace metals, and rare earth elements (REEs) in CCR wastewater, assess environmental impacts, and explore opportunities for resource recovery. The project advanced the development of a "One-Shot" analysis system designed to simultaneously analyze multiple analytes in CCR effluents.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Characterizing Families of Spectral Similarity Scores and Their Use Cases for Gas Chromatography–Mass Spectrometry Small Molecule Identification

Metabolomics provides a unique snapshot into the world of small molecules and the complex biological processes that govern the human, animal, plant, and environmental ecosystems encapsulated by the One Health modeling framework. However, this “molecular snapshot” is only as informative as the number of metabolites confidently identified within it. The spectral similarity (SS) score is traditionally used to identify compound(s) in mass spectrometry approaches to metabolomics, where spectra are matched to reference libraries of candidate spectra. Unfortunately, there is little consensus on which of the dozens of available SS metrics should be used. This lack of standard SS score creates analytic uncertainty and potentially leads to issues in reproducibility, especially as these data are integrated across other domains. In this work, we use metabolomic spectral similarity as a case study to showcase the challenges in consistency within just one piece of the One Health framework that must be addressed to enable data science approaches for One Health problems. Here, using a large cohort of datasets comprising both standard and complex datasets with expert-verified truth annotations, we evaluated the effectiveness of 66 similarity metrics to delineate between correct matches (true positives) and incorrect matches (true negatives). We additionally characterize the families of these metrics to make informed recommendations for their use. Our results indicate that specific families of metrics (the Inner Product, Correlative, and Intersection families of scores) tend to perform better than others, with no single similarity metric performing optimally for all queried spectra. This work and its findings provide an empirically-based resource for researchers to use in their selection of similarity metrics for GC-MS identification, increasing scientific reproducibility through taking steps towards standardizing identification workflows.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Using scalable computer vision to automate high-throughput semiconductor characterization

Abstract High-throughput materials synthesis methods, crucial for discovering novel functional materials, face a bottleneck in property characterization. These high-throughput synthesis tools produce 10 4 samples per hour using ink-based deposition while most characterization methods are either slow (conventional rates of 10 1 samples per hour) or rigid (e.g., designed for standard thin films), resulting in a bottleneck. To address this, we propose automated characterization (autocharacterization) tools that leverage adaptive computer vision for an 85x faster throughput compared to non-automated workflows. Our tools include a generalizable composition mapping tool and two scalable autocharacterization algorithms that: (1) autonomously compute the band gaps of 200 compositions in 6 minutes, and (2) autonomously compute the environmental stability of 200 compositions in 20 minutes, achieving 98.5% and 96.9% accuracy, respectively, when benchmarked against domain expert manual evaluation. These tools, demonstrated on the formamidinium (FA) and methylammonium (MA) mixed-cation perovskite system FA 1−x MA x PbI 3 , 0 ≤ x ≤ 1, significantly accelerate the characterization process, synchronizing it closer to the rate of high-throughput synthesis.

Science & Technology - Other Topics↗
DOE OSTI2024

Integrating in situ environmental covariates in an American lobster catch model to improve impact assessment

The installation and operation of floating offshore wind power is an integral component of societal transition to renewable energy generation where fixed bottom offshore wind is not possible. However, it will cause unique ecosystem changes. To disentangle the effects of offshore wind installations from the concurrent effects of climate change and the fishing practices on commercially significant resources, we must develop detailed characterizations of the resources before development occurs. In the Gulf of Maine, American lobster is the most commercially and culturally important fishery. At the time of writing, this is the largest fishery by value in North America. Our understanding of baseline localized parameters (such as catch per trap at the spatial scale of individual turbines) should be informed by relationships to environmental, biological, and survey-specific functional drivers of catch. A more mechanistic understanding of catch will allow for strategic adjustments to Post- Deployment fishery responses and ultimately, the development of research- and commercial-scale floating offshore wind development. Here, we used survey data from the New England Aqua Ventus Pre-Construction Commercial Trapping Survey to develop Generalized Additive Models describing seasonal catch per trap for legal and sublegal lobsters. We found fall catch to be nearly twice that of spring. Bottom temperature dynamics could be used to predict catch, and the Fall survey was associated with a warmer temperature regime. By using analytical tools that incorporate environmental heterogeneity, we developed monitoring methods from preconstruction baseline data that will be applicable over the post-construction operating period of an offshore wind farm.

BACI↗
DOE OSTI2022

Systematic characterization of gene function in the photosynthetic alga Chlamydomonas reinhardtii

Most genes in photosynthetic organisms remain functionally uncharacterized. Here, using a barcoded mutant library of the model eukaryotic alga Chlamydomonas reinhardtii, we determined the phenotypes of more than 58,000 mutants under more than 121 different environmental growth conditions and chemical treatments. A total of 59% of genes are represented by at least one mutant that showed a phenotype, providing clues to the functions of thousands of genes. Mutant phenotypic profiles place uncharacterized genes into functional pathways such as DNA repair, photosynthesis, the CO 2 -concentrating mechanism and ciliogenesis. We illustrate the value of this resource by validating phenotypes and gene functions, including three new components of an actin cytoskeleton defense pathway. The data also inform phenotype discovery in land plants; mutants in Arabidopsis thaliana genes exhibit phenotypes similar to those we observed in their Chlamydomonas homologs. We anticipate that this resource will guide the functional characterization of genes across the tree of life.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗
DOE OSTI2022

Underwater Noise Measurements around a Tidal Turbine in a Busy Port Setting

Acoustic emissions from current energy converters remain an environmental concern for regulators because of their potential effects on marine life and uncertainties about their effects stemming from a lack of sufficient observational data. Several recent opportunities to characterize tidal turbine sound emissions have begun to fill knowledge gaps and provide a context for future device deployments. In July 2021, a commercial-off-the-shelf hydrophone was deployed in a free-drifting configuration to measure underwater acoustic emissions and characterize a 25 kW-rated tidal turbine at the University of New Hampshire’s Living Bridge Project in Portsmouth, New Hampshire. Sampling methods and analysis were performed in alignment with the recently published IEC 62600-40 Technical Specification for acoustic characterization of marine energy converters. Results from this study indicate acoustic emissions from the turbine were below ambient sound levels and therefore did not have a significant impact on the underwater noise levels of the project site. As a component of Pacific Northwest National Laboratory’s Triton Field Trials (TFiT) described in this Special Issue, this effort provides a valuable use case for the IEC 62600-40 Technical Specification framework and further recommendations for cost-effective technologies and methods for measuring underwater noise at future current energy converter project sites.

tidal turbine↗
DOE OSTI2026

Extracellular DNA Alters Detection of Subtle Bacterial Responses to Soil Rewetting

Microbial communities are often characterized using DNA-based sequencing, but these approaches also capture extracellular DNA (exDNA) released from dead cells, potentially altering inference about microbial responses to environmental change. This may be especially important during pulse disturbances, such as soil drying–rewetting, which can increase microbial mortality and transient necromass pools. We assessed whether exDNA altered inference about bacterial responses to drying–rewetting (an 80 mm simulated rainfall event following a 28-day drought) in conventionally tilled corn and perennial switchgrass soils. We quantified bacterial abundance (16 S rRNA gene copies), alpha diversity, and community composition in paired soil samples with exDNA included (+ exDNA) and in samples treated with propidium monoazide (PMAxx) to reduce amplification of exDNA (− exDNA). At our level of replication (n = 4), PMAxx treatment did not significantly alter overall temporal response patterns (i.e., no significant main effect of DNA treatment or DNA × time interaction). However, PMAxx treatment increased sensitivity to detect some pairwise temporal changes in bacterial abundance and community composition in corn soils following rewetting. exDNA pools were proportionally highest immediately after rewetting in corn soils, suggesting transient extracellular DNA may contribute to masking during disturbance recovery. In contrast, PMAxx treatment had comparatively small effects in switchgrass soils, which exhibited weaker temporal responses overall. Inclusion of exDNA also changed which taxa appeared most responsive to rewetting. Together, our results suggest that exDNA does not uniformly bias soil microbial inference, but may reduce detectability of subtle disturbance-driven shifts in certain soils. Future studies should advance knowledge of microbial turnover and necromass dynamics, particularly using multiple complementary methods, to help predict when exDNA is most likely to influence ecological inference.

drying-rewetting↗