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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Thermal Integration of Advanced Nuclear Reactors with a Reference Refinery, Methanol Synthesis, and a Wood Pulp Plant (Rev.1)

The present report is intended to provide process flow diagrams (PFDs) and energy and mass balance data sheets for a U.S. industrial sector subset with which nuclear heat and power could be integrated—a subset that includes the oil refining, methanol and pulp and paper industries. Coupling options for integrating nuclear energy into these industries are quantitatively outlined for reference systems, and future work will extend this analysis in greater detail. Opportunities for integrating small modular nuclear reactors (SMNRs) were investigated for each of the industrial process configurations. Aspen HYSYS and Cycle-Tempo models for a high-temperature gas-cooled reactor were developed to evaluate the proposed integration. This introductory evaluation provides a general description and assessment of the operating principles, reactor coolant core outlet temperature, and reactor size to be integrated with industry. The industrial processes of oil refining and the production of methanol, pulp and paper were simulated by using Aspen HYSYS, Aspen Plus, and the PRELIM (Petroleum Refinery Life Cycle Inventory Model) tool to develop process details. Cycle-Tempo models then extend the process modeling results to obtain net energy demands (e.g., heat, steam, and electricity) when accounting for process steam and waste heat recovery. This information is intended to foster the analysis of integrating an SMNR to decarbonize industrial facilities. The SMNR would provide reliable, competitive, and sustainable clean energy while reducing carbon emissions and other environmental impacts, such as water withdrawals, consumption, and contamination. The refining industry, exhibited in Figure ES1, is a leading consumer of fossil -fuel-based heat, power, and hydrogen in the U.S. industrial sector, generating over 164 million metric tons (MMT) of CO 2 emissions in 2023. The overall mass and energy pertaining to a generalized complex refinery in the United States is reflected in Figure ES1, along with energy metrics regarding integration with a nuclear power plant (NPP). Data sheets were developed to indicate the energy requirements for the overall refinery and each refinery process. The data sheet for the overall refinery is shown in Table ES2.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Mining a human transcriptome database for chemical modulators of NRF2

Nuclear factor erythroid-2 related factor 2 (NRF2) encoded by the NFE2L2 gene is a transcription factor critical for protecting cells from chemically-induced oxidative stress. We developed computational procedures to identify chemical modulators of NRF2 in a large database of human microarray data. A gene expression biomarker was built from statistically-filtered gene lists derived from microarray experiments in primary human hepatocytes and cancer cell lines exposed to NRF2-activating chemicals (oltipraz, sulforaphane, CDDOIm) or in which the NRF2 suppressor Keap1 was knocked down by siRNA. Directionally consistent biomarker genes were further filtered for those dependent on NRF2 using a microarray dataset from cells after NFE2L2 siRNA knockdown. The resulting 143-gene biomarker was evaluated as a predictive tool using the correlation-based Running Fisher algorithm. Using 59 gene expression comparisons from chemically-treated cells with known NRF2 activating potential, the biomarker gave a balanced accuracy of 93%. The biomarker was comprised of many well-known NRF2 target genes (AKR1B10, AKR1C1, NQO1, TXNRD1, SRXN1, GCLC, GCLM), 69% of which were found to be bound directly by NRF2 using ChIP-Seq. NRF2 activity was assessed across ~9840 microarray comparisons from ~1460 studies examining the effects of ~2260 chemicals in human cell lines. A total of 260 and 43 chemicals were found to activate or suppress NRF2, respectively, most of which have not been previously reported to modulate NRF2 activity. Using a NRF2-responsive reporter gene in HepG2 cells, we confirmed the activity of a set of chemicals predicted using the biomarker. The biomarker will be useful for future gene expression screening studies of environmentally-relevant chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign

Marine boundary layer clouds play a critical role in Earth's energy balance. Their microphysical and radiative properties are highly impacted by ambient aerosols and dynamic forcings. In this study, we evaluate the representation of these clouds and related aerosol–cloud interaction processes in the single-column version of the E3SM climate model (SCM) against field measurements collected during the NASA ACTIVATE campaign over the western North Atlantic, as well as intercompare results with high-resolution process level models. We show that E3SM SCM reproduces the macrophysical properties of post-frontal boundary layer clouds in a cold-air outbreak (CAO) case well. However, it generates fewer but larger cloud droplets compared to aircraft measurements. Further sensitivity tests show that the underestimation of both aerosol number concentration and vertical velocity variance contributes to this bias. Aerosol–cloud interactions are examined by perturbing prescribed aerosol properties in E3SM SCM with fixed dynamics. Higher aerosol number concentration or hygroscopicity leads to more numerous but smaller cloud droplets, resulting in a stronger cooling via shortwave cloud forcing. This apparent Twomey effect is consistent with prior climate model studies. The cloud liquid water path shows a weakly positive relation with cloud droplet number concentration due to precipitation suppression. This weak aerosol effect on cloud macrophysics may be attributed to the dominant impact of strong dynamical forcing associated with the CAO. Our findings indicate that the SCM framework is a key tool to bridge the gap between climate models, process level models, and field observations to facilitate process level understanding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Soil-related developments of the Biome-BGCMuSo v6.2 terrestrial ecosystem model

Terrestrial biogeochemical models are essential tools to quantify climate–carbon cycle feedback and plant–soil relations from local to global scale. In this study, a theoretical basis is provided for the latest version of the Biome-BGCMuSo biogeochemical model (version 6.2). Biome-BGCMuSo is a branch of the original Biome-BGC model with a large number of developments and structural changes. Earlier model versions performed poorly in terms of soil water content (SWC) dynamics in different environments. Moreover, lack of detailed nitrogen cycle representation was a major limitation of the model. Since problems associated with these internal drivers might influence the final results and parameter estimation, additional structural improvements were necessary. In this paper the improved soil hydrology as well as the soil carbon and nitrogen cycle calculation methods are described in detail. Capabilities of the Biome-BGCMuSo v6.2 model are demonstrated via case studies focusing on soil hydrology, soil nitrogen cycle, and soil organic carbon content estimation. Soil-hydrology-related results are compared to observation data from an experimental lysimeter station. The results indicate improved performance for Biome-BGCMuSo v6.2 compared to v4.0 (explained variance increased from 0.121 to 0.8 for SWC and from 0.084 to 0.46 for soil evaporation; bias changed from -0.047 to -0.007 m 3 m -3 for SWC and from -0.68 to -0.2 mm d -1 for soil evaporation). Simulations related to nitrogen balance and soil CO 2 efflux were evaluated based on observations made in a long-term field experiment under crop rotation. The results indicated that the model is able to provide realistic nitrate content estimation for the topsoil. Soil nitrous oxide (N 2 O) efflux and soil respiration simulations were also realistic, with overall correspondence with the observations (for the N 2 O efflux simulation bias was between -0.13 and -0.1 mgNm -2 d -1 , and normalized root mean squared error (NRMSE) was 32.4 %–37.6 %; for CO 2 efflux simulations bias was 0.04–0.17 gCm -2 d -1 , while NRMSE was 34.1 %–40.1 %). Sensitivity analysis and optimization of the decomposition scheme are presented to support practical application of the model. The improved version of Biome-BGCMuSo has the ability to provide more realistic soil hydrology representation as well as nitrification and denitrification process estimation, which represents a major milestone.

58 GEOSCIENCES↗
DOE OSTI2024

Nationwide cost and capacity estimates for sedimentary basin geothermal power and implications for geologic CO 2 storage

Sedimentary basins are naturally porous and permeable subsurface formations that underlie approximately half of the United States. In addition to being targets for geologic CO 2 storage, these resources could supply geothermal power: sedimentary basin geothermal heat can be extracted with water or CO 2 and used to generate electricity. The geothermal power potential of these basins and the accompanying implication for geologic CO 2 storage are, however, understudied. Here, we use the Sequestration of CO 2 Tool (SCO2T PRO ) and the generalizable GEOthermal techno-economic simulator (genGEO) to address this gap by a) estimating the cost and capacity of sedimentary basin geothermal power plants across the United States and b) comparing those results to nationwide CO 2 sequestration cost and storage potential estimates. We find that across the United States, using CO 2 as a geothermal heat extraction fluid reduces the cost of sedimentary basin power compared to using water, and some of the lowest cost capacity occurs in locations not typically considered for their geothermal resources (e.g., Louisiana, South Dakota). Additionally, using CO 2 effectively doubles the sedimentary basin geothermal resource base, equating to hundreds of gigawatts of new capacity, by enabling electricity generation in geologies that are otherwise (with water) too impermeable, too thin, too cold, or not deep enough. We find there is competition for the best sedimentary basin resources between water- and CO 2 -based power, but no overlap between the lowest-cost resources for CO 2 storage and CO 2 -based power. In this way, our results suggest that deploying CO 2 -based power may increase the cost of water based systems (by using the best resources) and the cost of CO 2 storage (by storing CO 2 in locations that otherwise may not be targeted). As such, our findings demonstrate that determining the best role for sedimentary basins within the energy transition may require balancing tradeoffs between competing priorities.

CPG↗
DOE OSTI2024

An Overview of Mesoscale Convective Systems: Global Climatology, Satellite Observations, and Modeling Strategies

Deep convection is responsible for redistributing water as well as energy and providing vital water resources for many regions of the world. Cumulonimbus clouds aggregation into a single storm system develop mesoscale convective systems (MCS). MCSs have precipitation covering a horizontal region on the scale of 100?km or more. After more than the last seven decades, MCS has been gradually received wide attention in the scientific community as an important component of the Earth's hydrologic cycle and energy balance. MCSs differ from ordinary deep convection because of the mesoscale circulations consisting of a layer of air overturning on a scale much larger than those created by individual convective updrafts or downdrafts. Moreover, a key feature that separates MCS from ordinary deep convection is the significant portion of stratiform precipitation that results in the production and detrainment of a large number of ice particles from their organized convective cores and continues the mesoscale ascent that supports ice growth and aggregation as the crystals fall. This significant stratiform precipitation gives rise to top-heavy latent heating profiles that have substantial impacts on the upper-level global circulations, especially for those MCS that have a larger portion of stratiform rainfall. Top-heavy latent heating profiles are more frequent over the ocean than over the land. These unique features of MCS suggest that they are important for the hydrologic cycle, general circulation, and radiative balance of the climate system. In this chapter, we focus on the recent advances in the climatological perspective of MCS as well as the research tools used to better understand MCS after the advent of the satellite era. We will discuss both tropical and midlatitude MCS, the influence of modes of tropical climate variability on MCS, and the new insight from satellite observations on MCS interaction with the land surface.

Chakraborty, Sudip↗
DOE OSTI2023

Experimental determinations of carbon and hydrogen isotope fractionations and methane clumped isotope compositions associated with ethane pyrolysis from 550 to 600°C

Methane clumped isotope compositions signify the relative natural abundances of rare, doubly substituted isotopic species of methane ( 13 CH 3 D and 12 CH 2 D 2 ) and have emerged as a new isotopic tool to trace the sources, sinks, and lifecycles of methane in the environment. Such measurements can identify equilibration (or reequilibration) temperatures if found to be in isotopic equilibrium or non-equilibrium processes (e.g., kinetically controlled reactions or mixing) if not in isotopic equilibrium. Naturally occurring thermogenic methane—formed by the thermally activated breakdown of larger organic molecules—has been found to have clumped isotope compositions consistent with equilibrium at reasonable gas formation temperatures in some settings and non-equilibrium processes occurring during either formation, migration, storage, or extraction in others. To explore the potential controls on the isotopic composition of thermogenic methane, we conducted isothermal time-series ethane pyrolysis experiments at 550 and 600 °C to measure methane and ethane 13 C/ 12 C and D/H fractionations and methane clumped isotope compositions (resolved 13 CH 3 D and 12 CH 2 D 2 ). We explore the effects of modifying the initial clumped isotope composition of ethane and the addition of water vapor to pyrolysis experiments. We observe that ethane and methane 13 C/ 12 C are controlled by kinetic isotope effects and Rayleigh distillation processes. In contrast, ethane and methane D/H and methane clumped isotope compositions appear to be controlled by a combination of these processes and hydrogen isotope exchange. The hydrogen isotope exchange processes lead to isotopic equilibrium as reaction completion is approached for both D/H (ethane/methane) and methane clumped isotope compositions. Here, we develop a chemical model based on a mass balance approach that accounts for inheritance vs. hydrogen-abstraction formation pathways for singly and doubly substituted isotopologues of ethane and methane that is compared to the experimental data. The model allows the determination of carbon and hydrogen kinetic isotope effects associated with ethane cracking and hydrogen abstraction reactions that, where applicable, we compare to prior theoretical constraints. From the comparison of the model to the experimental data, we infer that the kinetically controlled ethane and methane bulk isotope compositions and methane clumped isotope compositions are controlled by kinetic isotope effects (both primary and secondary) associated with both C–C bond and C–H bond cleavage reactions. Specifically, the methane clumped isotope compositions likely result from a combination of clumped isotope effects associated with ethane breakdown and/or assembly of methane isotopologues (expressed in terms of γ-factor parameters ≠ 1) and combinatorial effects that arise probabilistically. We discuss our experimental results in the context of recent pyrolysis experiments and observations of naturally occurring thermogenic methane. We consider a proposal consistent with observations from nature that the hydrogen isotope exchange reactions that promote equilibration of methane isotopic molecules at or near formation temperature may be facilitated by free radicals generated by pyrolysis reactions. In this framework, isotope exchange effectively ceases when pyrolysis effectively ceases locking in compositions that can be consistent with peak formation temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Use Cases and Model Development of Thermal Storage Coupling for Advanced Nuclear Reactors

This report discusses the different options for coupling thermal energy storage (TES) systems to advanced nuclear power plants (A-NPPs) in order to enable flexible and hybrid plant operation. An advanced light-water reactor (ALWR) and a high-temperature gas-cooled reactor (HTGR) were selected as the initial use cases for demonstrating a thermally balanced energy storage coupling design for thermal power extraction. Cost functions for the A-LWR were derived from the fully balanced models that were developed based on three different coupling options with three different thermal energy bypass ratios. For the next steps, cost functions for the HTGR will also be derived, and additional nuclear reactors (e.g., a liquid-cooled fast reactor [LFR] or molten-salt reactor [MSR]) will be evaluated for coupling with TES in similar fashion, including the evaluation of their steady-state condition models and cost functions. The models presented herein showcase several design considerations, focusing on optimal deployment methodologies for achieving steady-state operation with minimum disruption to the nuclear power generation cycle. This report presents the results of steady state models developed using Aspen HYSYS®, wherein the thermal energy bypass for an NPP-TES coupling was varied up to 50%. The various components were sized using Aspen Process Economic Analyzer (APEA) and Aspen Exchanger Design and Rating (EDR), when applicable. Cost functions from these models were developed using the latest publicly available data obtained from APEA V11. The current steady-state models and cost functions provide a baseline for additional work focusing on dynamic operation and process optimization by using Idaho National Laboratory (INL)’s Framework for Optimization of Resources and Economics (FORCE) tools to evaluate the technoeconomic viability and transient operations of TES-coupled A-NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Representing the Future Role of Hydropower and Pumped Storage Hydropower (PSH) in Electricity Planning Tools

Existing tools for long-term electric sector planning struggle to represent hydropower's nuanced site-specific technical and operating characteristics, which depend on technical specifications as well as water management practices and regulations. As a result, long-term planning models and tools insufficiently characterize hydropower value and incentives, and they cannot fully represent the role hydropower can play in a future electricity system that could include a high penetration of variable wind and solar generation, battery storage, and other low-carbon technologies. This presentation demonstrates the culmination of a multi-year effort to enhance hydropower representations in electricity planning models at the National Renewable Energy Laboratory (NREL), as part of the U.S. Department of Energy (USDOE) HydroWIRES Initiative. New modeling techniques are demonstrated using the NREL Regional Energy Deployment System (ReEDS), an open-access electric sector capacity expansion model used extensively in a wide range of technology deployment and integration analysis, including the 2016 USDOE Hydropower Vision. ReEDS uses a least-cost optimization approach to understand investment and operation of electricity generation, storage, and transmission technologies under future scenarios of electricity technology innovation, demand, policy, and other sectoral drivers. ReEDS was modified to better represent value and opportunities for both pumped storage hydropower (PSH) and hydropower systems without pumping. We incorporated a new national closed-loop PSH resource and cost assessment to explore new PSH deployment opportunities and added plant-level data to better represent the existing PSH fleet. New upgrade pathways enable opportunities for enhanced hydropower flexibility by adding pumps, upgrading dispatchability, increasing capacity, or increasing energy availability. The model was also modified to better represent the value of long-duration energy storage beyond diurnal time scales, allowing both hydropower and PSH to better balance energy supply and demand variations in high-renewable systems. These new features are demonstrated under reference and high-renewable futures and a range of sensitivity scenarios to understand which hydropower and PSH deployment and upgrade opportunities are the most attractive. These scenarios indicate potential for new closed-loop PSH deployment and for hydropower flexibility improvements to have important impacts on long-term electricity system emissions and economic outcomes. Increasing flexibility of the existing hydropower fleet can reduce the need to invest in new flexible grid technologies and help achieve decarbonization goals. Systems with sufficient energy storage could also be valuable for balancing seasonal differences in renewable energy availability, particularly from solar energy. The methods developed for ReEDS and subsequent scenario results reveal important considerations for future hydropower and grid system planning, and all data and code is freely available in a public code repository for use throughout the hydropower industry.

capacity expansion↗
DOE OSTI2020

Developing a Decision Support Engine to Enable Irrigation Modernization - Poster

Irrigation systems in the United States are some of the oldest continually utilized infrastructure in existence today, with some systems exceeding 100 years in age. They are operated to meet farming demands but are managed through a balance of varying influence: policies limiting water usage, stakeholder interests, and environmental impacts. Irrigation modernization is defined as a set of activities that update and improve existing irrigation systems, including, but not limited to improving water quantity, development of distributed energy resources for surrounding communities, ecosystem services, and improved agricultural yields. Modernizing an existing irrigation system can enable stakeholders to combat changing environmental and population demands but is difficult because the complexity involved in determining the potential benefits and consequences of irrigation modernization is high. We are combining a large amount of various geospatial, tabular, and temporal data with subject matter expertise into a decision support engine that will enable stakeholders to determine the benefits and consequences of irrigation modernization in their irrigation systems. A web-based GIS will allow the user to construct the modifications out of a palette of modernization options, which will be sent to the analytics engine for computations, and back to the web client for a graphical display and comparison of relevant metrics. Our development process involves four phases: 1) identify mechanisms of modernization, 2) identify data requirements, data streams, first principles and applicable algorithms necessary to quantify modernization mechanisms, 3) create ‘modules’ for each modernization mechanism, these modules will form the decision support engine, each capable of performing independently but can also inform other modules when needed, 4) Merge the decision support engine with a user interface, capable of ingesting user inputs and returning insights into the impacts of a modernization project as they relate to economic, environmental, monetary, and energy generation. Once complete, it is our intention that this tool will be fundamental in irrigation modernization projects, providing a strong analytical basis from which stakeholders can quickly make informed decisions regarding project development.

13 HYDRO ENERGY↗
DOE OSTI2021

Tribal Revegetation Project Final Project Report: 92-Acre Area, Area 5 Radioactive Waste Management Complex, Nevada National Security Site, Nevada

Nuwu (Southern Paiute), Newe (Western Shoshone), and Nuumu (Owens Valley Paiute) are linguistically related, Numic-speaking peoples who are part of the broader Uto-Aztecan language group. Numic peoples view the land as a holistic, living, sentient being with feelings and purpose. The land is personified with human characteristics and it needs to be experienced to be understood through “learning by doing.” Numic peoples do not support ground disturbing activities within their ancestral lands, including activities tied to the storage of low-level radioactive waste or classified materials on the NNSS, which they view as culturally inappropriate. These deep-rooted ancestral connections are the impetus for reinforcing Numic responsibility for healing disturbed areas by integrating respect and patience with consistent Tribal interaction. Tribal Ecological Knowledge (TEK) is the science of describing Tribal approaches for understanding natural resources. Numic TEK is embedded in traditional teachings learned incrementally over time though experience and it evolves through lessons learned and responses to environmental changes over millennia. Therefore, TEK can broaden and enhance Western scientific knowledge associated with revegetation, especially in highly disturbed areas. The project blended TEK with Western scientific ecological methods to create a vegetative cover within test plots on the 92-Acre Area located at the Radioactive Waste Management Complex (RWMC) located in Area 5 on the Nevada National Security Site (NNSS). The vegetated test plots were systematically created for the Department of Energy (DOE) in tandem with the existing Federal Facilities Agreement and Consent Order (FFACO) with the Nevada Department of Environmental Protection (NDEP). Three previous contractor-lead attempts at revegetation, one targeting full cover revegetation and two targeting test plot revegetation, did not achieve the anticipated results at this location. When presented to the 16 American Indian Tribal nations and affiliated groups with cultural and historical ties to the NNSS, the group appointed a Tribal Revegetation Committee (TRC) that included six expert Tribal knowledge holders to collaborate with an ethnoecologist/cultural anthropologist and two biologists. Project design, planning, seed and outplant selection, spiritual land preparation, and methodology were guided by the TRC and an ethnoecologist/cultural anthropologist from Portland State University (PSU) and biologists from Desert Research Institute (DRI). Using TEK, the TRC recommended a specific seed mixture that contained nine native plant species and three species of outplants. The revegetation effort included preparing and planting thirty 10 m × 10 m (32.8 ft × 32.8 ft) seeded plots, twelve of which also included outplants; and eight 10 m × 100 m (32.8 ft × 328 ft) plots that only received outplants, all atop a waste cell cover. The TRC and the project team creatively adapted TEK with Western scientific methods so that the planned revegetation efforts could occur within the safety and security parameters of the RWMC. Test plots were subjected to one of five soil treatments with varying combinations of straw or mulch applications, soil amendment, and/or outplant planting and one of two watering treatments (watered or unwatered). Planting was divided into two events: one in the fall season and another during the subsequent spring season based on TEK and a corresponding recommendation from the TRC. Monitoring and spiritual management was conducted by the TRC to evaluate plant progress on a monthly basis (in conjunction with the biologist and anthropologist) during each respective growing season for a period of three years after planting. This approach allowed Tribal members the opportunity to conduct traditional blessings and other culturally appropriate activities to restore balance to the land in accordance with Tribal protocols. Following TEK-guided methods, successful plant establishment from seed stock and outplants was observed in many plots. Overall, plots planted in the spring, as recommended by the TRC, showed higher rates of outplant survival and native seedling emergence than those planted in the fall. This finding is significant because it is contrary to the original guidance and previous approaches provided for planting in this region. The TRC believes the frequent co-occurrence of native seedlings near surviving outplants indicates an important symbiotic relationship understood by Tribal communities and overlooked by others. Watered outplants displayed much higher survivability than unwatered plants, even after watering was reduced after the plants were established. Soil amendments and mulch created higher densities of native plants from seed. Many native seedlings showed significant delays in germination, which is considered a normal adaptation to desert climates. Some native plants did not germinate until the third growing year, whereas others germinated during the first growing year, which demonstrates the complexity of the desert environment. Evidence of native insects, reptiles, mammals, and birds, as well as native plants that were not part of the planted species, were noted and considered culturally significant. Despite the presence of non-native plants, native outplants continued to thrive and the incidence of native plant germination from seed increased over time. These successful revegetation results where previous efforts were unsuccessful reinforce the importance of integrating regionally appropriate, TEK-guided methodology with Western science to achieve positive results and the necessity of integrating Tribal involvement in all stages of the revegetation effort. Expanded approaches coupled with Tribal knowledge and tools from Western science addressed a complex problem tied to revegetating atop a low-level radioactive waste cell. The level of Tribal participation serves as a progressive model for building collaborative relationships and addressing ecological challenges on the NNSS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Application of electron beam technology to decompose persistent emerging drinking water contaminants: poly- and perfluoroalkyl substances (PFAS) and 1,4-Dioxane

Poly- and perfluoroalkyl substances (PFAS) and 1,4-dioxane are persistent emerging contaminants that are currently under consideration for federal and state-specific regulations in drinking water. Both PFAS and 1,4-dioxane are highly resistant to degradation and are not effectively removed by conventional drinking water treatment systems. Results from the Unregulated Contaminant Monitoring Rule 3 survey showed that >540 sites across the nation are contaminated with both PFAS and 1,4-dioxane. Hence, there is a need to identify technologies that can effectively remove both these contaminants. Water treatment via electron beam (e-beam) has been proven effective at treating a wide range of contaminants, including perfluorooctane sulfonate (PFOS), perfluorooctanoate (PFOA), polychlorinated biphenyls, and trichloroethylene. While the e-beam process is often considered similar to advanced oxidation processes (AOPs), e-beam technology is unique in that it produces both highly oxidizing and reducing species at the same time. The specific objectives of this study were to: (i) determine the effectiveness of 9 MeV electrons provided by the Fermilab’s Accelerator Application Development and Demonstration (A2D2) tool to decompose PFAS and 1,4-dioxane; (ii) assess the formation of byproducts during water treatment; (iii) apply the optimized treatment to field groundwater samples contaminated with PFAS and 1,4-dioxane, and (iv) assess the energy demands for the treatment of these contaminants using e-beam. Results from this study showed that e-beam is effective in treating both 1,4-dioxane and PFAS. Complete degradation of 1,4-dioxane was observed at a dose of 5 kGy for an initial concentration of up to 1 ppm without the need for any sample modification. The electrical energy per order (EEo) for treatment of 1,4-dioxane ranged from 0.46 to 0.72 kWh/m 3 /order and was comparable and even lower, in some cases, than other AOP technologies. Alkaline conditions (pH 13) and low dissolved oxygen concentration (2 mg/L) highly favored the treatment of PFAS by e-beam. Greater than 90% removal of PFOA and PFOS from an initial concentration of 100 to 500 ppb was achieved at a dose of 250 kGy and 500 kGy, respectively, under optimized conditions. The degradation efficiency was not significantly changed when treating other PFAS of fluorinated carbon chain length of 5 to 7 individually at 250 kGy with a removal ranging from 85¬–99% for different compounds. Short chain PFAS (perfluorobutanoate: PFBA and perfluorobutane sulfonate: PFBS) did not degrade under the same conditions at 250 kGy, but 70 to 99% degradation was observed at a higher dose of 1000 kGy. Short chain PFAS (perfluorohexanoate: PFHxA (C5) and perfluoroheptanoate: PFHpA (C6)) were detected after treatment of PFOA, but not after PFOS treatment. Inability to close the mass balance through targeted analysis suggests the presence of other intermediates not detectable by available analytical methods. When treating PFAS mixture containing ten compounds at equimolar concentration of 0.05 µM each, preferential degradation of polyfluorinated compound (6:2 fluorotelomer sulfonate or 6:2 FTS) followed by C8 and C7 compounds was observed as a function of increasing e-beam dose. About 30% degradation of ΣPFAS was observed at 250 kGy and no further removal was observed up to a dose of 1000 kGy. C4 to C6 PFASs showed no degradation, while C3 PFAS (PFBS) showed an increase in concentration by 34% at 1000 kGy due to formation from the breakdown of other long chain PFAS. These results suggested that (a) the reaction kinetics is likely different for different PFAS based on chain length, functional group, and the degree of fluorination of the carbon chain, and (b) there may be intermediates generated from the degradation of 6:2 FTS and C7/C8 compounds that can potentially scavenge hydrated electrons needed for reaction with the untreated PFAS molecules. Treatment of three PFAS-contaminated groundwater samples from two US states showed similar trends as observed in the treatment of equimolar PFAS mixtures. Up to 71% removal of ΣPFAS was achieved in real groundwater samples at 750 kGy and data trend suggested that higher degradation is feasible if higher doses (>1MGy) are applied to treat field samples to overcome matrix effects and competing species. Calculated EEo for PFAS ranged from as low as ~48 to 1081 kWh/m 3 /order depending on the type of PFAS treated. These values are comparable and even lower, in some cases, than other destructive technologies employed for PFAS treatment such as ultrasound, plasma, and photochemical treatment. The results from this study indicate e-beam is a promising approach under favorable conditions and should be explored further as an end-of-train treatment option for PFAS destruction.

1,4-Dioxane↗
DOE OSTI2021

Energy Arbitrage: Comparison of Options for use with LWR Nuclear Power Plants

Arbitrage is the opportunistic buying and selling of a commodity during local pricing valleys and peaks respectively to maximize economic value. This report evaluates options for energy arbitrage integrated with existing light water reactor (LWR) nuclear power plants (NPPs) where nuclear energy could be stored in a variety of forms and later recovered to generate electrical power during periods when grid electricity demand and pricing are high. The forms of energy storage examined in this report include the potential value of batteries, hydrogen, and thermal energy storage for coupling with nuclear power. Various large demand response options are also analyzed, including the production of liquid nitrogen via air separation and liquefaction, liquefaction of hydrogen, compressed hydrogen, and the cryogenic capture of CO2. Demand response refers to dispatchable loads that can cycle up or down depending on-grid electricity demand to aid in balancing the grid. Large demand response options could dispatch to aid nuclear power stations in avoiding power turndowns by providing an alternate disposition for electrical energy by producing marketable products (e.g., liquid nitrogen, hydrogen, or captured CO2). Static conditions were chosen and analyzed in this report for each option. Dynamic operation or optimization of energy arbitrage or demand response are out of scope for this report. The analysis is based on storage systems with discharge capacities of 500 MW for which various durations of storage and costs of charging (electricity cost) are examined. While the value of thermal energy to an industrial user for flexible plant operations has been previously proven as a business case, this report evaluates costs of hydrogen energy storage and leading thermal energy storage options, and large demand response loads that could be integrated with LWRs in comparison to utility-scale battery storage for use of off-peak nuclear energy. Compilation of this information will be used by the Idaho National Laboratory (INL) RAVEN/HERON systems integration and economics tool to evaluate thermal energy dispatch to industrial users. Relative ranking of energy storage options was done using a levelized cost of storage (LCOS) metric which calculates a rough breakeven cost for the system, taking into account the capital and operating costs as well as the revenue from arbitrage. Table ES1 below shows the LCOS for each of the energy storage options considered. First, in the table, lithium iron (Fe) phosphate batteries are listed as the base case for comparison against the other options. Next is hydrogen storage where most of the hydrogen analyses assumed the hydrogen to be produced using solid oxide electrolytic cell (SOEC) high temperature steam electrolysis (HTSE). The others used existing models of polymer electrolyte membrane (PEM) low temperature electrolysis to produce hydrogen. HTSE performance parameters and costs were taken from existing INL models. Various means were assumed to convert the hydrogen to electricity, including PEM fuel cells (FCs) and a gas turbine mixed in a 30 vol% mixture with natural gas. Physical storage (pressure vessels) and geological storage (natural underground features) were used to store the hydrogen as noted. Geological storage is more economical, but the locations are limited because of the requirement for pre-existing geological formations that will support storage. Thermal energy storage (TES) options were also analyzed including electro-thermal energy storage (ETES) and four different liquid sensible heat TES storage media as noted (Hitec, Hitec XL, Therminol-66, and Dowtherm A). The ETES process considered was modified using existing public documentation on an Echogen process and uses a separate supercritical CO2 charge and discharge cycle with sand as the heat storage media.

25 ENERGY STORAGE↗
DOE OSTI2025

S AP F LOWER : an automated tool for sap flow data preprocessing, gap-filling, and analysis using deep learning

Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, outliers, and gaps, creating challenges for analysis and requiring substantial manual processing. We developed S AP F LOWER , a tool that automates data preprocessing, model training, gap-filling, sapwood area scaling and modeling, and water use analysis. It integrates autocleaning, machine learning and deep learning models (e.g. random forest, Gaussian process regression, long short-term memory (LSTM), bidirectional LSTM (BiLSTM)), and efficient workflows to process sap flow data. S AP F LOWER can remove over 90% of noisy data while preserving legitimate variations and achieve high accuracy in gap-filling based on user-determined parameters. Random forest, LSTM, and BiLSTM models reduced root mean square error to 10% or less for long-term gaps. Model training and prediction can be performed efficiently within seconds. S AP F LOWER significantly enhances the efficiency and accessibility of TDP data analysis by automating complex tasks, enabling researchers without programming expertise to employ advanced techniques. Future improvements will focus on species-specific corrections for TDP and support for additional measurement methods. S AP F LOWER is openly available on GitHub (https://github.com/JiaxinWang123/SapFlower) and Zenodo (doi: 10.5281/zenodo.13665919).

ecosystem water balance↗
DOE OSTI2020

Balancing Water Sustainability and Productivity Objectives in Microalgae Cultivation: Siting Open Ponds by Considering Seasonal Water-Stress Impact Using AWARE-US

Microalgae have great potential as an energy crop. Scaling-up algal biofuel production in the United States (US) should be done with careful attention to water stress. This study evaluates the regional and seasonal water-stress impact of potential algae-pond deployments in the US. Three site-selection strategies focusing on biomass yield, water-use efficiency (WUE), and water-stress impact, respectively, are applied and compared to meet a US algae biomass production target of 30 million metric tons/yr ash-free dry weight, which converts to 20.8 billion L renewable diesel, via hydrothermal liquefaction. Ranking algae ponds based on biomass yield leads to freshwater consumption of 2.66 km3/yr, resulting in the highest water-stress impact (39.1 US equivalent km3). Under the WUE scenario, water consumption is reduced by 81%, but biomass yield is reduced by 12%. In contrast, adding a water-stress constraint to the biomass-yield ranking reduces water consumption by 50% and water-stress impact by 97%, with a small yield reduction (1.7%). Results show that pond location has a significant effect on water stress and that water stress is not proportional to water consumption or yield. Furthermore, capturing seasonal water patterns is critical for planning because sites in water-abundant regions can have short-term but significant water-stress impacts.

algae, Biofuel, water scarcity footprint, hydrothe↗
DOE OSTI2020

Interplay of changing irrigation technologies and water reuse: example from the upper Snake River basin, Idaho, USA

Abstract. Careful allotment of water resources for irrigation is critical for ensuring the resiliency of agriculture in semiarid regions, and modernizing irrigation technology to minimize inefficient water losses is an important tool for farmers and agricultural economies. While modernizing irrigation technology can achieve reductions in the nonbeneficial use of water, such as bare soil evaporation and nonconsumptive losses, water returned to the landscape is also reduced, often eliminating flow paths that other users rely on. In basins using a combination of surface and groundwater, replenishing aquifer storage by the managed aquifer recharge (MAR) of seasonally available water can mitigate the aquifer drawdown that results from reduced recharge when irrigation efficiency is improved. We examine the effects of MAR on the system-scale efficiency of modernizing irrigation technology and the resulting changes in the reuse of nonconsumptive losses, using a macroscale hydrologic model applied to the semiarid upper Snake River basin (USRB) of western Wyoming and southern Idaho, USA. Irrigation technologies were represented explicitly in the model, and available data informed baseline parameterizations of the irrigation technology. A suite of parameterizations were simulated that updated the existing technologies to be more efficient, both with and without sufficient MAR to cause a stabilization of the aquifer at the present-day head. As expected, simulated changes in irrigation technology resulted in greater downstream export of pristine water and a higher rate of aquifer drawdown when MAR was not simulated. Under current water use and cropping patterns, we were not able to simulate aquifer stabilization and maintain discharge downstream at any level of irrigation efficiency. We found support for the hypothesis that, as efficiency improves, less MAR is required to maintain a stable aquifer than when return flows are reduced due to increased efficiency. To evaluate the hypothesis, we defined the management benefit as a metric that compared the difference between the change in irrigation's net recharge and the change in MAR required as irrigation technology became more efficient. The metric generally indicated that less MAR was needed than net recharge was lost, but only for the most efficient case did the management benefit exceed the MAR needed at the baseline to stabilize the aquifer. Increasing efficiency of irrigation technology reduced the reuse of the gross irrigation derived from prior nonconsumptive losses, but simulating MAR increased reuse for a given parameterization, leading to higher effective irrigation efficiency. We find that local groundwater storage that users depend on is generally more sensitive to management decisions than downstream flows, and the drawdown of the aquifer without MAR always exceeded any decrease in discharge induced by MAR. Improving resource sufficiency in semiarid systems like the USRB will require an array of solutions that will need to balance benefits to local and downstream users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗
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↗