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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Compound flood simulations indicate rising public exposure to sewage-contaminated waters in Waikīkī, Hawai‘i

Waikīkī, Hawai‘i serves as a valuable case study for flood vulnerability due to its low elevation, present-day exposure to multiple flood sources, and role as the state’s economic engine. This study applies the high-resolution, open-source WRF-Hydro-CUFA (Coastal Urban Flood Application) model to simulate compound flood interactions among pluvial, fluvial, coastal, storm drain-driven, and subsurface processes, and to evaluate how flood characteristics in Waikīkī evolve under projected sea-level rise (SLR). Simulated water levels in an estuarine drainage canal, serving as the primary outlet for gravity-flow drainage from Waikīkī, show strong agreement with observations (r ≥ 0.935, R 2 ≥ 0.874), accurately reproducing flooding observed during recent 5-year and 50-year storm events. Simulations incorporating SLR demonstrate a shift in dominant flood drivers as sea levels rise. In addition, results identify critical thresholds at which elevated estuarine tailwater conditions cause widespread drainage backflow, eventually occurring in the absence of rainfall. These findings suggest that tidally driven flooding will progressively dominate over rainfall-driven events, increasing public exposure to highly contaminated canal and groundwater sources. The results underscore the urgent need to integrate water quality issues and drainage failure into coastal flood management strategies for low-lying urban environments, particularly those reliant on polluted estuarine waterways for stormwater management.

Compound flooding↗
DOE OSTI2025

Learning to Simulate Aerosol Dynamics with Graph Neural Networks

Aerosol effects on climate, weather, and air quality depend on characteristics of individual particles, which are tremendously diverse and change in time. Particle-resolved models are the only models able to capture this diversity in particle physiochemical properties, and these models are computationally expensive. As a strategy for accelerating particle-resolved microphysics models, we introduce Graph-based Learning of Aerosol Dynamics (GLAD) and use this model to train a surrogate of the particle-resolved model PartMC-MOSAIC. GLAD implements a Graph Network-based Simulator (GNS), a machine learning framework that has been used to simulate particle-based fluid dynamics models. In GLAD, each particle is represented as a node in a graph, and the evolution of the particle population over time is simulated through learned message passing. Here, we demonstrate our GNS approach on a simple aerosol system that includes condensation of sulfuric acid onto particles composed of sulfate, black carbon, organic carbon, and water. A graph with particles as nodes is constructed, and a graph neural network (GNN) is then trained using the model output from PartMC-MOSAIC. The trained GNN can then be used for simulating and predicting aerosol dynamics over time. Results demonstrate the framework's ability to accurately learn chemical dynamics and generalize across different scenarios, achieving efficient training and prediction times. We evaluate the performance across four scenarios, highlighting the framework's robustness and adaptability in modeling aerosol microphysics and chemistry.

aerosol chemistry dynamics↗
DOE OSTI2025

PAVC: The foundation for a Pan-Arctic Vegetation Cover database

Field-measured Arctic vegetation cover data is essential for creating accurate, high-quality vegetation structure and composition maps. Extrapolating field data into high-resolution cover maps provides detailed, function-specific information for use in Earth System Models, vegetation classifications, and monitoring vegetation change over time and space. However, field campaigns that collect plant cover vary substantially in scope, method, and purpose, which makes them difficult to unify across data stores, and they are often not designed to meet remote sensing needs. In this work, we synthesized and harmonized field-based fractional cover data from various data stores to create a high-quality, consistent repository schema for remote sensing-based vegetation cover mapping applications. We developed a reproducible workflow for synthesizing visual estimate and point-intercept fractional cover data. The resultant Pan-Arctic Vegetation Cover (PAVC) database contains synthesized fractional cover at both the species and plant functional type levels. The latter includes absolute foliar cover for deciduous shrubs and trees, evergreen shrubs and trees, forbs, graminoids, lichen, bryophytes, and “other” vegetation, as well as absolute cover for litter and top cover for water and bare ground.

Steckler, Morgan R. [Oak Ridge National Laboratory↗
DOE OSTI2025

High-precision monitoring of outgassing species in model extreme ultraviolet photoresists with a cavity ring-down spectrometer

Background Extreme ultraviolet (EUV) photoresists play a pivotal role in advancing nanopatterning technologies by balancing image quality and sensitivity. The outgassing behavior of photoresist thin films under EUV and deep ultraviolet (DUV) exposure reveals chemical details relevant to their performance. Aim Here, we focus on utilizing an analytical technique not previously used in photolithography, the tabletop cavity ring-down spectrometer, to investigate outgassing dynamics in EUV photoresists, enabling precise chemical identification and deeper insights into resist processing. Approach The spectrometer’s enhanced laser path length (∼ 20 km) and broadband absorption capabilities in the C–H overtone region allow for sensitive and temporally resolved detection of mixtures of outgassed species. Using a model resist comprising a polymer matrix with a photoacid generator and quencher, we analyzed the influence of time delays between exposure and post-exposure bake (PEB) as well as storage under varying environmental conditions. Results Suppression of isobutylene outgassing and thickness loss was observed with extended delays between exposure and PEB, potentially linked to water absorption and acid deactivation. The technique proved highly effective in distinguishing subtle chemical differences between processing stages. Conclusions Delay times and their environmental conditions, particularly humidity, reduce outgassing and thickness loss of photoresists during PEB, suggesting decreased acid-driven deprotection. This can potentially impact sensitivity, defectivity, and roughness of resist patterns, necessitating precise monitoring and control.

Extreme ultraviolet photoresists↗
DOE OSTI2020

Progress in Simulating the Quasi–Biennial Oscillation in CMIP Models

The quasi–biennial oscillation (QBO) of the zonal mean zonal wind is the primary mode of variability in the tropical lower stratosphere. The QBO is characterized by alternating easterly westerly shear layers that descend down from ~10 to 100 hPa. The QBO is also seen in lower stratospheric tropical temperature, water vapor, and ozone and affects tropospheric variability through various teleconnections. We examine here the progress in simulating the QBO in the Coupled Model Intercomparison Project (CMIP) models, more specifically in CMIP3, CMIP5, and CMIP6 models. We show that the number of models that are able to simulate the QBO has increased from 0 in CMIP3, to 5 in CMIP5, to 15 in CMIP6. While the number of models with an internally generated QBO has tripled from CMIP5 to CMIP6, the fidelity of the simulation averaged over the CMIP models has not improved. We show that CMIP5 and CMIP6 models represent the QBO period and latitudinal extent quite well; however the QBO amplitude is shifted upwards relative to observations resulting in large underestimation of QBO amplitude at all levels below 20 hPa. As a result, the underestimation of QBO amplitude in the lowermost stratosphere and lack of variations downward to the tropopause and below will likely impact the quality of teleconnections seen in the current generation Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Development of a hardware-in-the-loop testbed for laboratory performance verification of flexible building equipment in typical commercial buildings

The goals of reducing energy costs, shifting electricity peaks, increasing the use of renewable energy, and enhancing the stability of the electric grid can be met in part by fully exploiting the energy flexibility potential of buildings and building equipment. The development of strategies that exploit these flexibilities could be facilitated by publicly available high-resolution datasets illustrating how control of HVAC systems in commercial buildings can be used in different climate zones to shape the energy use profile of a building for grid needs. This article presents the development and integration of a Hardware-In-the-Loop Flexible load Testbed (HILFT) that integrates physical HVAC systems with a simulated building model and simulated occupants with the goal of generating datasets to verify load flexibility of typical commercial buildings. Compared to simulation-only experiments, the hardware-in-the-loop approach captures the dynamics of the physical systems while also allowing efficient testing of various boundary conditions. The HILFT integration in this article is achieved through the co-simulation among various software environments including LabVIEW, MATLAB, and EnergyPlus. Although theoretically viable, such integration has encountered many real-world challenges, such as: 1) how to design the overall data infrastructure to ensure effective, robust, and efficient integration; 2) how to avoid closed-loop hunting between simulated and emulated variables; 3) how to quantify system response times and minimize system delays; and 4) how to assess the overall integration quality. Lessons-learned using the examples of an AHU-VAV system, an air-source heat pump system, and a water-source heat pump system are presented.

Chen, zhelun↗
DOE OSTI2021

SAM Co-Development to Support Fluoride-salt-cooled High-temperature Reactor Design and Licensing (CRADA 2018-18177 Final Report)

This project aims to raise the SAM code's technical and commercial maturity level to enable the Kairos Power ("Kairos") to use SAM to support its KP-FHR design analysis and licensing application. Argonne National Laboratory ("Argonne") has actively developed and maintained SAM, a modern system-level analysis tool for advanced nonlight water reactors safety analysis. Kairos is currently actively pursuing development of an FHR design and associated technology, and consequently requires a pedigreed safety analysis tool. The purpose of this project is to increase the maturity of the SAM code for the modeling and simulation of the KP-FHR design, thus enabling its use in safety analyses that support licensing application. Argonne will primarily be responsible for software design, development, and testing; while Kairos will be responsible for software requirements, assessment of software capabilities, needs, gaps, and priorities, and development of proprietary models. The research and development activities for the joint SAM development project include: a series of identification and prioritization studies on design characteristics, event sequences, relevant phenomena, and software capabilities; SAM capability enhancements for specific KP-FHR systems and components; performing code verification and validations; integrating uncertainty quantification (UQ), model calibration, and sensitivity analysis (SA) techniques in safety analyses; and raising the software quality rigor level for commercial-grade applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Development of a Test-Bed for Testing and Refining EarthEn’s Supercritical CO 2 Based Energy Storage System

EarthEn’s energy storage concept leverages supercritical carbon dioxide (sCO 2 ) as a working fluid and relies on compact, high-performance components operating at elevated pressures and temperatures. To accelerate component development and reduce technical risk prior to larger-scale demonstrations, Oak Ridge National Laboratory (ORNL) developed a 100 kW-scale sCO 2 test-bed under a Cooperative Research and Development Agreement with EarthEn (CRADA NO. NFE-24-10050). The objective of the work was to design and construct a flexible experimental facility capable of reproducing key thermodynamic state points and heat-transfer conditions relevant to EarthEn’s thermal energy storage (TES) cycle, with particular emphasis on enabling development and evaluation of next-generation heat exchangers and TES concepts. The test-bed consists of a closed-loop sCO 2 circulation system housed within an open-topped enclosure. In its as-installed configuration, dense-phase sCO 2 is recirculated through a printed circuit recuperator, an electrically heated section, a throttling device used to simulate turbine expansion, and a water-cooled printed circuit heat exchanger that rejects heat to the building chilled-water system before returning to the pump. The pump is driven by a variable frequency drive, enabling controlled adjustment of flow and operating point. A comprehensive instrumentation suite was integrated to support both safe operation and high-quality data collection. Installed sensors include Coriolis flow meters for sCO 2 flow rate and density, resistance temperature detectors and thermocouples distributed throughout the loop (including the heated section and key heat exchanger ports), and pressure transducers for absolute and differential pressure measurements. The facility was designed to support high-pressure (19 MPa nominal) and high-temperature (575°C nominal) operation with credited overpressure protection provided by a rupture disk. Nominal operating conditions were selected to support 100 kW-class testing while maintaining flexibility for non-heated and heated shakedown, control development, and future integration of advanced TES test sections. In parallel with facility development, a system-level thermal-hydraulic model was created using Modelica-based tools to support component sizing, anticipate performance over targeted test conditions, and establish a framework for future model calibration against experimental data. At the conclusion of the project performance period, the facility was in final assembly, and the pressure boundary was nearly completed. However, several practical challenges associated with high-pressure/high-temperature systems and specialized component procurement impacted schedule and prevented initial pump-driven operation and full commissioning within the available resources. This report documents the as-built design, operating capabilities, and instrumentation, and it summarizes key lessons learned related to heater fabrication and testing, first-of-a-kind assembly factors, specialty flange supply constraints, and fill pump corrective actions. Finally, it outlines a phased plan for future commissioning and experimental campaigns, including control and instrumentation shakedown, heater characterization, model calibration, and testing at state points representative of EarthEn’s TES cycle.

25 ENERGY STORAGE↗
DOE OSTI2025

Root genetics in the field to understand drought adaptation and carbon sequestration (Final Scientific/Technical Report)

For all crop plants, roots play a critical role in growth. Roots anchor the plants, and are the primary site of nutrient and water uptake. Roots are also the main source of C to soil in the form of root tissues and exudates, and thus greatly influence SOM stocks. To perform these functions, primary roots extend into soil, producing a network of branching roots of characteristic form, known as its root system architecture (RSA). RSA varies among species, and among varieties within a species that are adapted to different environments. Root traits are major targets for the second green revolution because of their potential to improve crop productivity, increase drought tolerance and nutrient acquisition, and increase C capture of soil. Improving the quality of roots in maize will be particularly valuable, since this crop is planted on over 92 million acres annually in the US. The future sustainability of agricultural systems relies on their ability to enhance soil organic matter (SOM) storage and reduce GHG emissions, while maintaining or enhancing productivity. This program had two components, Sensors and Models. For the first component, we designed and built a high-throughput phenotyping platform for root pulling of maize plants. This eliminated the physical labor of manually pulling up plants and reduced the number of personnel required down to one. The standardized pulling mechanism allowed recording force curves during the pulling process, providing additional information. We validated that the maximum force for pulling the root system was well-correlated with the root system mass and provided root crowns for further RSA analysis. These root crowns identified significant correlations with 2D root area and root depth, along with 3D root volume, total root length and number of root tips. We then used this system for field-based studies in maize on the genetics of root system architecture and its relation to nitrogen-use efficiency (NUE), including using lines relevant to the Corteva breeding program. Varieties were also evaluated at Corteva sites in the cornbelt and Danforth farm in Missouri, to establish responses across sites. From these studies we have identified genetic loci associated with root traits and created mutant lines for these loci and correlations of root traits with NUE. For the Models component, we worked to incorporate root and soil characteristics into the MEMS 2.0 soil and ecosystem biogeochemical model. Existing soil C models, such as Century, are unable to represent specific root trait interactions with the soil environment and therefore to accurately forecast the potential C sequestration benefits of root breeding under different climatic and soil type conditions. We have developed the MEMS 2.0 ecosystem biogeochemical model to improve quantification of farm-scale soil carbon and greenhouse gas emissions. The new knowledge and large datasets produced by this project will be used to develop and drive an innovative model capable of forecasting the impacts on soil C stocks and nutrient dynamics. An innovation was to use the empirical data from the field studies (in 1, above) to model genetic variation in nitrogen use efficiencies and soil C input. Our work demonstrated that maize root-derived C rapidly replaces existing soil C and after 3 years of continuous maize, up to 20% of soil organic C in the topsoil (0-15cm) and 3% in the subsoil (15-30cm) was contributed by maize. However, this contribution did not entirely represent a net increase. Root C contribution to soil was affected by maize genetics. We have analyzed soils derived from the CSU field trials for C and N stocks, in the different soil physical fractions represented by the MEMS model, using both physical fractionation with elemental analyses, and Fourier transformed infrared spectroscopy. Data will be used to link crop nitrogen use efficiencies with soil C sequestration and provide data to bridge the field trials with the model development, for verification of model predictions. The project had a number of successful outcomes: we have used the new phenotyping platform to identify new genetic loci that can enhance root phenotypes; we have partnered with multiple maize seed companies phenotype varieties in their breeding programs; we have developed the MEMS model that can help inform industry on the potential for carbon sequestration in the agricultural sector, and which is now available at the CSU Soil Carbon Solutions Center for use.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Evaluation of New Additions to OLI Software in Predicting Mercuric and Mercurous Species in Liquid Waste Operations

Speciation of mercury during the pretreatment steps of tank waste processing is critical to successful mercury removal prior to vitrification during Liquid Waste Operations (LWO) at SRS. OLI software has been used to predict mercury speciation and activity throughout LWO. The OLI software operates based on a thermodynamic framework called the Mixed Solvent Electrolyte (MSE) framework. The MSE framework allows prediction in theoretically infinitely dilute to concentrated mixtures (e.g., purely solute solutions). Before modification to the MSE framework databanks, certain critical mercury species were missing in the MSE databank, and some thermodynamic data needed to be updated for the OLI software to accurately predict mercury chemical species in SRS waste tanks. To better reflect streams across LWO, new mercury species were integrated into the MSE database. To evaluate the changes to the OLI MSE framework per the Technical Task Request (TTR) and the Task Technical and Quality Assurance Plan (TTQAP), waste stream compositions from Tanks 38, 43, and Tank 50 decontaminated salt solution (DSS) were used as model inputs. Models were developed and executed using both the old and new databases. Compositional analyses from caustic Tank 50 DSS and caustic Tanks 38 and 43 were used as the input streams. These streams represent the most comprehensive chemical data sets where both mercury and tank constituents were measured together. Results for Tank 50 DSS predict HgO as the predominant species in both databases. Both methyl and dimethyl Hg species are present when the new database is ‘on’ and are not predicted with the new database turned ‘off’. The new database predicts a greater amount of HgO and a greater fraction of it in the solid phase. Pourbaix diagrams (potential vs. pH) generated for each Tank 50 DSS were identical regardless of which database was used. Elemental Hg and HgO were predicted in the water stable region under basic conditions. Tanks 38 and 43 follow similar trends as the Tank 50 DSS models. Unlike Tanks 38 and 50 DSS, the Tank 43 Pourbaix plot shows a region of stability for an aqueous HgOHCO3 - species between approximately pH 7-11. In all streams, when MeHg+ is included in the inputs, the new database predicts aqueous MeHgOH as the dominant species. If elemental or dimethyl mercury is in the waste stream, the new database model predicts they are unchanged and remain in those states and quantities. Additionally, the total mercury values are reported for both the measured input data and the OLI output data for all considered tanks. The summary indicates that the percentage error between the measured and calculated values is less than 1% in all cases The reconciliations and generation of the Pourbaix diagrams for Tank 50 DSS took approximately ten times longer with the new database ‘on’. In addition, over the course of that time, models with the new database ‘on’ were more likely to crash or display an error. Some modest performance improvements were noted when modeling with an i7 processor versus an i5. An example error is found in Appendix A. Furthermore, Appendix B provides V&V for two chemical systems analyzed with the OLI software, results were satisfactory. It is recommended to utilize the new databases (i.e., HCO.ddb and SR-Hg.ddb) in future Savannah River Mission Completion applications of OLI to represent pseudo steady-state. Furthermore, the integration and utilization of the new databases (i.e., HCO.ddb and SR-Hg.ddb) in modeling applications (e.g., Aspen) is also recommended.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)

Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.

Rahimi, Stefan (ORCID:0000000331884462)↗
DOE OSTI2021

Griffin Software Development Plan

Griffin is a MOOSE-based reactor physics application for advanced reactor multiphysics modeling and simulation. The application is developed in a consistent multiphysics environment with strong software quality assurance. Griffin inherited most of the capabilities of MAMMOTH/Rattlesnake and is adopting the capabilities from PROTEUS that are needed in the code. The toolset includes a variety of deterministic radiation transport solvers for fixed source, k-eigenvalue, ad-joint, and subcritical multiplication, as well as transient solvers for point-kinetics, improved quasi-static, and spatial dynamics. The code contains the cross-section preparation capabilities applicable to fast and thermal reactors, including TRISO-fueled reactors. Core management capabilities include core performance, fuel depletion and shuffling, equilibrium core calculation, pebble-bed reactor run-in and equilibrium core, molten-salt reactor delayed neutron precursor drift, and control rod and drum movement with cusping correction. This software development plan presents the current and future capabilities and features in Griffin for the design and analysis of non-light-water reactor systems in steady-state and transient conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Constraints and Drivers of Dissolved Fluxes of Pyrogenic Carbon in Soil and Freshwater Systems: A Global Review and Meta‐Analysis

Abstract Pyrogenic carbon (PyC) is a significant component of the global soil carbon pool due to its longer environmental persistence than other soil organic matter components. Despite PyC's persistence in soil, recent work has indicated that it is susceptible to loss processes such as mineralization and leaching, with the significance and magnitude of these largely unknown at the hillslope and watershed scales. We present a review of the work concerning dissolved PyC transport in soil and freshwater. Our analysis found that the primary environmental controls on dissolved PyC (dPyC) transport are the formation conditions and quality of the PyC itself, with longer and higher temperature charring conditions leading to less transport of dPyC. While correlations between dPyC and dissolved organic carbon in rivers and other pools are frequently reported, the slope of these correlations was pool‐dependent (i.e., soil‐water, precipitation, lakes, streams, rivers), suggesting site‐specific environmental controls. However, the lack of consistency in analytical techniques and sample preparation remains a major challenge to quantifying environmental controls on dPyC fluxes. We propose that future research should focus on the following: (a) consistency in methodological approaches, (b) more quantitative measures of dPyC in pools and fluxes from soils to streams, (c) turnover times of dPyC in soils and aquatic systems, and (d) improved understanding of how mechanisms controlling the fate of dPyC in dynamic post‐fire landscapes interact. With more refined quantitative information about the controls on dPyC transport at the hillslope and landscape scale, we can increase the accuracy and utility of global carbon models.

58 GEOSCIENCES↗
DOE OSTI2022

Anthropogenically driven climate and landscape change effects on inland water carbon dynamics: What have we learned and where are we going?

Inland waters serve as important hydrological connections between the terrestrial landscape and oceans but are often overlooked in global carbon (C) budgets and Earth System Models. Terrestrially derived C entering inland waters from the watershed can be transported to oceans but over 83% is either buried in sediments or emitted to the atmosphere before reaching oceans. Anthropogenic pressures such as climate and landscape changes are altering the magnitude of these C fluxes in inland waters. Here, we synthesize the most recent estimates of C fluxes and the differential contributions across inland waterbody types (rivers, streams, lakes, reservoirs, and ponds), including recent measurements that incorporate improved sampling methods, small waterbodies, and dried areas. Across all inland waters, we report a global C emission estimate of 4.40 Pg C/year (95% confidence interval: 3.95–4.85 Pg C/year), representing a 13% increase from the most recent estimate. In this work, we also review the mechanisms by which the most globally widespread anthropogenically driven climate and landscape changes influence inland water C fluxes. The majority of these drivers are expected to influence terrestrial C inputs to inland waters due to alterations in terrestrial C quality and quantity, hydrological pathways, and biogeochemical processing. We recommend four research priorities for the future study of anthropogenic alterations to inland water C fluxes: (1) before-and-after measurements of C fluxes associated with climate change events and landscape changes, (2) better quantification of C input from land, (3) improved assessment of spatial coverage and contributions of small inland waterbodies to C fluxes, and (4) integration of dried and drawdown areas to global C flux estimates. Improved measurements of inland water C fluxes and quantification of uncertainty in these estimates will be vital to understanding both terrestrial C losses and the “moving target” of inland water C emissions in response to rapid and complex anthropogenic pressures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Tracking natural CO 2 migration through a sandstone aquifer using Sr, U and C isotopes: Chimayó, New Mexico, USA

The geochemical and isotopic characteristics of groundwaters in Chimayó, New Mexico, reflect processes that affect water quality in the Tesuque Aquifer, which overlies a leaking natural CO 2 source in a structurally complex region. In this study, select isotopes (δ 13 C, 87 Sr/ 86 Sr, 234 U/ 238 U) are applied to groundwaters to better understand CO 2 transport mechanisms and related water-rock interactions that impact Chimayó groundwater. Carbon stable isotope ratios of dissolved inorganic carbon (DIC; δ 13 CDIC = -15.10‰ to 4.50‰) identify a distinct source of upward-migrating CO 2 that interacts with the groundwater. Additionally, groundwater 87 Sr/ 86 Sr compositions (0.7098 to 0.7154) reflect intrusion of varying amounts of saline water associated with the high CO 2 source, while 234 U/ 238 U ratios corroborate presence of deep groundwater and suggest impacts from distinctive natural uranium sources are affecting groundwater. Previous work proposed two CO 2 transport mechanisms at the site: (1) dissolved in deep brine that underlies the aquifer and (2) in the gas phase; this study uses isotope mixing models to identify wells that are affected by these CO 2 transport mechanisms and demonstrates that both transport mechanisms are associated with impaired groundwaters. Overall, this study demonstrates that applying multiple isotope systems (δ 13 CDIC, 87 Sr/ 86 Sr, 234 U/ 238 U) is a dynamic tool for identifying and measuring the impact of CO 2 leakage from a sequestration site.

58 GEOSCIENCES↗
DOE OSTI2021

Grassland-to-cropland conversion increased soil, nutrient, and carbon losses in the US Midwest between 2008 and 2016

After decades of declining cropland area, the United States (US) experienced a reversal in land use/land cover change in recent years, with substantial grassland conversion to cropland in the US Midwest. Although previous studies estimated soil carbon (C) loss due to cropland expansion, other important environmental indicators, such as soil erosion and nutrient loss, remain largely unquantified. In this study, we simulated the environmental impacts from the conversion of grassland to corn and soybeans for 12 US Midwestern states using the EPIC (Environmental Policy Integrated Climate) model. Between 2008 and 2016, over 2 Mha of grassland were converted to crop production in these states, with much less cropland concomitantly abandoned or retired from production. The net grassland-cropland conversion increased annual soil erosion by 7.9%, nitrogen (N) loss by 3.7%, and soil organic carbon loss by 5.6% relative to that of existing cropland, despite an associated increase in cropland area of only 2.5%. Notably, the above estimates represent the scenario of converting unmanaged grassland to tilled corn and soybeans, and impacts varied depending upon crop type and tillage regime. Corn and soybeans are dominant biofuel feedstocks, yet the grassland conversion and subsequent environmental impacts simulated in this study are likely not attributable solely to biofuel-driven land use change since other factors also contribute to corn and soybean prices and land use decisions. Nevertheless, our results suggest grassland conversion in the Upper Midwest has resulted in substantial degradation of soil quality, with implications for air and water quality as well. Additional conservation measures are likely necessary to counterbalance the impacts, particularly in areas with high rates of grassland conversion (e.g. the Dakotas, southern Iowa).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Probabilistic risk-based Area of Review (AoR) determination for a deep-saline carbon storage site

Regulatory oversight of a geologic carbon sequestration (GCS) project relies on iterative estimations, throughout the project lifetime, of the area where increased risks to underground sources of drinking water (USDWs) may occur due to injection of CO2. This area, referred to as Area of Review (AoR), is typically delineated by predicting the migration of fluid between the reservoir and the lowermost USDW via an open wellbore using predictions from physics-based reservoir simulators. The inherent uncertainty in input parameters used in reservoir modeling therefore affects the accuracy of determining the AoR for a project. Furthermore, the standard analytical approaches for calculating a critical pressure to delineate the risk area yield an infinite AoR for cases where the injection reservoir is overpressured relative to the USDW. A methodology is presented in this paper to better characterize the risk to USDWs while accounting for the uncertainty in reservoir modeling, with an application to a permitted GCS project with an overpressured injection formation, FutureGen 2.0. The methodology is demonstrated using the National Risk Assessment Partnership’s open-source integrated assessment model (NRAP-Open-IAM) to develop a probabilistic estimate of impact risk to USDW quality. CO2 and pressure predictions from the reservoir modeling conducted using the STOMP-CO2 simulator for the FutureGen 2.0 site are used in a NRAP-Open-IAM model with reservoir, wellbore, and aquifer components to: (1) assess the extent of potential leakage into the USDW for the predicted reservoir pressure conditions; (2) evaluate the extent of potential impact using “no-net-degradation” thresholds; and (3) account for uncertainty in reservoir permeabilities.

03 NATURAL GAS↗