Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sequestration”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Advances in Miscanthus × Giganteus Planting Techniques May Increase Carbon Uptake in the Establishment Year

Agricultural lands hold significant potential for CO 2 sequestration, particularly when utilizing biomass crops and agricultural residues. Among these, Miscanthus × giganteus (mxg) stands out due to its high productivity and carbon sequestration capabilities. Recognizing the importance of such biomass crops, the Intergovernmental Panel on Climate Change (IPCC) has identified Bioenergy with Carbon Capture and Storage (BECCS) as a crucial strategy for achieving net-zero CO 2 emissions by 2050. This study examines the carbon uptake potential of mxg during its establishment year at the Sustainable Advanced Bioeconomy Research (SABR) farm in Iowa, USA, where mxg was planted at a density exceeding previous studies. Using eddy covariance (EC) measurements, we quantified the net ecosystem carbon exchange (NEE), and derived gross primary productivity (GPP), and ecosystem respiration (R eco ). Our findings reveal that SABR's mxg exhibited a significant carbon uptake of –621 g C m –2 , a threefold increase compared to a similar EC site in the “corn-belt” (University of Illinois Energy Research Farm; UIEF), which was established with lower planting density and pre-commercial planting equipment. Favorable growing conditions and advanced planting technologies at SABR likely contributed to this high carbon uptake. Comparisons with other global EC studies indicated a strong correlation between higher planting densities and greater carbon uptake. These results suggest that increasing mxg planting density can enhance carbon uptake, but further studies are necessary to evaluate the impacts under varying environmental conditions and management practices. Additionally, economic analyses are essential to determine the viability of higher planting densities. Our study underscores the potential of optimized mxg management practices to contribute significantly to CO 2 uptake and supports the development of BECCS as a viable climate change mitigation strategy.

09 BIOMASS FUELS↗
DOE OSTI2026

Nanoscale elemental mapping reveals the effect of light and temperature on Gephyrocapsa huxleyi coccoliths

Coccolithophores produce vast quantities of stable calcium carbonate coccoliths, occupying the distinctive position as one of the most productive calcifying organisms on Earth. Gephyrocapsa huxleyi, the most abundant species of coccolithophores across modern oceans, plays an important role in the biological carbon pump and may serve as inspiration for nature-based carbon capture and sequestration technologies. Despite intensive study into G. huxleyi, the biological mechanisms of coccolith synthesis remain unclear. Here, we employ synchrotron X-ray fluorescence to quantitatively map elemental incorporation (calcium, Ca; strontium, Sr; sulfur, S; iron, Fe; and silicon, Si) into G. huxleyi coccoliths at 40-nanometer resolution. Trace elements play a role in determining the thermodynamic stability of coccolith carbonate sequestration and may provide insight into unknown mechanisms of coccolithogenesis. Although the coccolith Sr/Ca ratio has been widely applied as a paleoceanographic proxy, understanding of the Sr/Ca phenomena is limited. Our results confirm that Sr/Ca is temperature dependent but challenge the hypothesis that growth rate is a primary determinant. We find that increased light irradiance led to an ~30% decrease in calcium incorporated into the coccoliths. Surprisingly, X-ray fluorescence spectra and mapping revealed evidence of sulfur, at approximately three times the concentration of Sr, embedded in and around the calcite matrix, suggesting that G. huxleyi coccoliths may play an expanded role in the global sulfur cycle. Here, based on our elemental maps, we postulate that sulfur is active in the intracellular coccolith vesicle and plays a direct role in formation of G. huxleyi coccoliths.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Prospects for silvicultural enhancement of fire resistance in mesic westside forests of the Pacific Northwest

Increasing wildfire activity in mesic, temperate Pacific Northwest forests west of the Cascade Range crest has stimulated interest in understanding whether alternative forest management practices could reduce risk of stand-replacing fire. To explore how management can enhance fire resistance in these forests and assess tradeoffs among resistance enhancement, carbon sequestration and storage, and economic returns, we conducted 40-year simulations of stand development with BioSum, a framework for conducting landscape analysis with the Forest Vegetation Simulator (FVS), utilizing a statistically representative and spatially balanced sample of Forest Inventory and Analysis (FIA) plots. Simulation outcomes under business-as-usual silviculture were contrasted with fire-aware silviculture, and treatment optimization logic was developed and applied to represent landscape-scale outcomes under business-as-usual and fire-focused management scenarios. Simulation results indicate that fire-aware prescriptions and fire-focused management can meaningfully enhance stand- and landscape-scale fire resistance of westside forests under less than extreme fire weather, but at the cost of lower economic returns and reduced net carbon storage and sequestration over the 40-year analysis window. Shifting from business-as-usual regeneration harvests with short rotations to fire-aware, episodic selection harvest improved fire resistance the most, especially in young privately-owned forests, and with only modest tradeoffs in carbon and economic outcomes. While fire-aware treatments generally reduced net present value from forest operations over business-as-usual, most treatments still generated positive net present value and could be implemented without subsidy. Fire-aware prescriptions that removed and utilized non-merchantable harvest residues instead of burning them, via either pile or broadcast burning, partially mitigated carbon emissions associated with fire-aware treatments, with about the same improvement in fire resistance. Given the currently limited institutional and financial capacity to implement fire resistance enhancing treatments at scale, the insights from this analysis may aid managers seeking to elevate fire resistance to prioritize where and how to manage.

Science & Technology - Other Topics↗
DOE OSTI2024

Machine Learning Applications in Analyzing the Role of Shale Barriers and Baffles for CO2 Storage

This study uses machine learning to analyze microseismic data from the Illinois Basin Decatur Project (IBDP) and quantify CO₂ plume extents. By leveraging well logs, microseismic records, and CO₂ injection metrics, the research predicts subsurface CO₂ plume dynamics. Findings show vertical clustering of microseismic events near the injection well, with CO₂ periodically breaching barriers due to buoyancy. K-Means clustering performed best, achieving the highest Silhouette Score and lowest Davies-Bouldin Index. This capability is crucial for real-time monitoring and management of CO₂ sequestration sites, validated against physical models and IBDP data, reinforcing CO₂ geological sequestration's viability and enhancing management tools.

Carr, Timothy↗
DOE OSTI2024

Multi-Scale 3D Imaging for Machine Learning Property Upscaling: Mt. Simon Sandstone Case Study

Petrographic properties of principal target reservoirs for carbon sequestration, such as the Mt. Simon Sandstone, are relevant to broad interest groups. The Mt. Simon Sandstone is a deep, saline, regionally extensive Cambrian sandstone, overlain by low permeability sealing formations, making it one of the viable geologic carbon storage reservoirs in the Midwestern US. Its thickness (exceeding 2400 ft in some localities), depth, and lateral extent, combined with high porosity and permeability make it a high-priority target of multiple ongoing geologic carbon sequestration efforts in the United States of America. The National Energy Technology Laboratory in Morgantown, West Virginia, has been engaged in characterization efforts of the Mt. Simon for over a decade, with a strong focus on Computed Tomographic data acquisition. Data generated during this period has been hitherto not accessible to the public. This archival effort focused on preservation of historical CT data and associated metadata, and facilitating their accessibility, culminating with the publication of the entire dataset on NETL’s Energy Data eXchange (EDX) and the associated Gill et. al (2024) paper.

Gill, Magdalena K.↗
DOE OSTI2024

Monitoring, Reporting, and Verification Considerations for Carbon Dioxide Removal

The project investigates Measurement, Reporting, and Verification (MRV) methods for Enhanced Weathering and Marine Carbon Dioxide Removal (mCDR) technologies. Enhanced Weathering accelerates natural mineral processes to capture CO2, while mCDR leverages oceanic processes for carbon sequestration. The study focuses on developing standardized MRV protocols, assessing environmental impacts, and evaluating the scalability and economic feasibility of these carbon sequestration methods. The goal is to ensure reliable and transparent data for validating and improving CO2 removal technologies.

Priyadarshini↗
DOE OSTI2025

Chemically Enhanced Electrodialysis (CEED) for Recovery of Rare Earth Elements

Rare-earth elements are crucial for numerous technologically relevant industries including energy, electronics, and aerospace; however, both the supply and separation of rare earths are pressing challenges. The long-term goal of the collaborative project is to develop a novel approach to existing extraction behaviors. To achieve this goal, a class of electrodialysis membranes with novel ion-gating functionality will be developed and paired with a conventional electrodialysis strategy. The hypothesis of the work is that incorporating sequestrants of suitable structures at the surface of the electrodialysis membrane will enhance extraction efficiency for ions of interest. Our ability to prepare sequestrants of diverse conformations and to adapt their molecular structure for binding lanthanides renders the proposed technology a versatile method for selective ion separation. Our approach will enable an entirely new technological approach to the separation of valuable rare-earth elements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

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

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

Biomass Co-firing↗
DOE OSTI2026

CRADA Number NFE-22-09333 with Holocene Climate Corporation (CRADA Final Report:)

Holocene Climate Corporation has developed and scaled up a novel technology for Direct Air Capture (DAC) that is based on cutting-edge research initiated at Oak Ridge National Laboratory (ORNL). According to the IPCC, carbon dioxide capture from the air and its sequestration are necessary to keep global temperature rise below 1.5°C by 2050. DAC is a viable and practical way to reach this goal. DAC can happen anywhere in the world, takes up a fraction of the land of forests, and along with the sequestration of CO 2 , provides permanent and verifiable removal of carbon from the atmosphere. The proposed project aimed to facilitate knowledge transfer from ORNL to Holocene focusing on (i) the synthesis of the ORNL patented material which builds the cornerstone of the DAC technology, and (ii) required analytical methods needed to conduct crystallization bench-scale experimentation and technology development. Furthermore, ORNL conducted research centered around CO 2 absorption using an air-liquid contacting structure with an aqueous amino acid solution. The achievements under this project comprise successful knowledge transfer from ORNL to the entire Holocene team to jump-start their internal R&D and technological development activities.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2025

Greenhouse gas emissions reduction strategies that maximize portfolio-wide life cycle cost reduction, resilience, and environmental justice benefits

While strategies to achieve net-zero emissions at an individual site are well understood, new analysis methods are required for organizations seeking to achieve net-zero across multiple facilities, each with concurrent priority goals. At a portfolio level, distinct locations present varied challenges that cannot be addressed through singular solutions, and competing goals can take precedence with the assumption that net-zero emissions strategies deter from energy resilience and cost savings, therefore negatively impacting nearby communities. This study tests these assumptions by analyzing 16 diverse sites (varying in size, climate, and energy use) to identify strategies that reduce emissions and assess the impact these strategies have on life cycle costs, resilience, and communities with environmental justice concerns. Methods were developed to approximate missing information essential to net-zero evaluation. Established methods were augmented to evaluate life cycle costs, resilience, and environmental justice impacts across a set of strategies and accommodate the multi-criteria analyses. Potential benefits from identified strategies were quantified using site characteristics and a set of corresponding metrics. The net-zero analysis found that 11 sites could use on-site strategies to eliminate all but 2% of emissions generated. The remaining emissions can be offset, for instance through sequestration, executed at the portfolio scale. On-site carbon-free energy was found to reduce 51% of emissions across all sites; efficiency reduced 19% of emissions; sequestration 16%; procured carbon-free energy 15%; fuel switching 1.6%; and fleet electrification 1.3%. Building electrification, however, increased emissions by 4.4%. Different strategies also provide cost, resilience, and/or environmental justice benefits—the degree to which varies with individual site conditions. The findings indicate an advantage to considering the strategies as a comprehensive set, which leads to co-benefits, both in the ability to achieve net-zero goals and in advancing other goals. The results present the case for comprehensive advanced planning at the portfolio level to prioritize investments that will balance the minimization of emissions and life cycle cost with the maximization of resilience and environmental justice benefits. The novel methods for evaluation and integration, valuation of benefits, and consideration at the portfolio scale allow organizations to select investments that simultaneously address multiple key priorities.

Net-Zero Emissions↗
DOE OSTI2024

Machine Learning-Driven Quantification of CO2 Plume Dynamics at Illinois Basin Decatur Project Sites Using Microseismic Data

This study utilizes machine learning to quantify CO2 plume extents by analyzing microseismic data from the Illinois Basin Decatur Project (IBDP). Leveraging a unique dataset of well logs, microseismic records, and CO2 injection metrics, this work aims to predict the temporal evolution of subsurface CO2 saturation plumes. The findings illustrate that machine learning can predict plume dynamics, revealing vertical clustering of microseismic events over distinct time periods within certain proximities to the injection well, consistent with an invasion percolation model. The buoyant CO2 plume partially trapped within sandstone intervals periodically breaches localized barriers or baffles, which act as leaky seals and impede vertical migration until buoyancy overcomes gravity and capillary forces, leading to breakthroughs along vertical zones of weakness. Between different unsupervised clustering techniques, K-Means and DBSCAN were applied and analyzed in detail, where K-means outperformed DBSCAN in this specific study by indicating the combination of the highest Silhouette Score and the lowest Davies–Bouldin Index. The predictive capability of machine learning models in quantifying CO2 saturation plume extension is significant for real-time monitoring and management of CO2 sequestration sites. The models exhibit high accuracy, validated against physical models and injection data from the IBDP, reinforcing the viability of CO2 geological sequestration as a climate change mitigation strategy and enhancing advanced tools for safe management of these operations.

Iyegbekedo, Ikponmwosa↗
DOE OSTI2025

Effect of CO 2 Concentration on the Microbial Activity of Orenia metallireducens (Strain Z6) in Surface Inert Materials

Carbon dioxide (CO 2 ) sequestration has garnered widespread attention as a key strategy for mitigating CO 2 emissions and combating the greenhouse effect. However, the mechanisms underlying the interactions between CO 2 , widespread siliceous minerals and biological processes remain unclear. The present study explored the potential impacts of different CO 2 concentrations on microbial activity, environmental conditions and their feedback on the fate of CO 2 . A total of 20 experimental conditions was created, with the variables including different natural and synthetic siliceous minerals (e.g., quartz sand and a type of commercial glass beads), the presence or absence of the iron-reducing microorganism Orenia metallireducens (strain Z6) and varying CO 2 concentrations (0%, 20%, 50%, 100%) in the presence of ferrihydrite and pyruvate. Geochemical, microbial and mineralogical analyses revealed that elevated CO 2 concentrations significantly inhibited microbial Fe(III) reduction and pyruvate metabolism. Interestingly, compared to cultures without mineral amendments or those with glass beads alone, the addition of quartz sand enabled strain Z6 to better withstand the environmental stress caused by elevated CO 2 , promoting pyruvate fermentation and iron reduction. In addition to an increased pH, the formation of siderite, hematite and vivianite was also observed in the bioactive systems. Although both glass beads and quartz sand were primarily composed of silica, differences in the mineral structure, elemental composition and acid neutralization capacity rendered quartz sand more chemically active and unexpectedly led to greater CO 2 sequestration.

CO2 stress↗
DOE OSTI2026

Marginal Soils Index Analysis & Geospatial Data

This data package contains output files associated with Mongird et al. (in prep) organized into four dataset directories. Each dataset is described in more detail below. 1. Marginal Soils Index Analysis Description: This folder contains a csv file with land needs and availability by state, power generating technology type, and scenario in 2050 when suitable siting areas are additionally constrained to areas with increasing levels of soil marginality. Files: msi_constrained_siting_availability_2050.csv Variables: Scenario - Projected 2050 scenario name State - US state abbreviation Technology - Generating technology type solar = solar photovoltaic gas_cc_re = natural gas combined cycle (recirculating cooling) wind = onshore wind gas_cc_ccs_re = natural gas combined cycle with carbon capture sequestration (recirculating cooling) gas_cc_dry = natural gas combined cycle with (dry cooling) gas_cc_pond = natural gas combined cycle with (pond cooling) coal_conv_ccs_re = conventional coal with carbon capture sequestration (recirculating cooling) Req_Capacity_MW - The amount of rated capacity required in 2050 of the given technology type in the given state and under the given scenario from the capacity expansion plan Req_Capacity_Factor - The assumed capacity factor (fraction between 0 and 1) for the given technology type in the given state and under the given scenario by the capacity expansion plan Req_Land_km2 - The amount of land required (in km-squared) to host the required generating capacity that is capable of meeting the specified capacity factor for the given technology type in the given state and under the given scenario Req_Energy_TWh - Product of Req_Capacity_MW, Req_Capacity_Factor, and 8760/1e6 for the given technology type in the given state and under the given scenario MSI_Case - The level of MSI that siting the given technology is additionally constrained to, where >0 means siting is additionally constrained to suitable land areas that have an MSI value greater than 0 >=1 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 1 >=2 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 2 >=3 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 3 Soil Attribute Rasters Description: This folder contains geospatial raster files for individual soil parameters upscaled to the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of non-missing 30m resolution values. All raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. Files: avg_cond_raster_ .tif - Average conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm max_cond_raster_ .tif - Maximum conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm min_ph_raster_ .tif- Min pH values across all soil horizons within a depth of 40 inches. avg_ph_raster_ .tif - Average pH value across all soil horizons within a depth of 40 inches. max_ph_raster_ .tif- Max pH value across all soil horizons within a depth of 40 inches. erosion_factor_raster_ .tif - Product of k-factor and percent slope flood_freq_raster_ .tif - Number of months of the year during which the area is commonly, frequently, or very frequently flooded. max_sar_raster_ .tif - Maximum sodium adsorption ratio across all horizons within a depth of 40 inches rock_frac_raster_ .tif - Fraction of the upper 6 inches of soil composed of rock fragments larger than 3 inches. temp_regime_raster_ .tif - Soil temperature regime with the following key: 0 = pergelic 1 = gelic 2 = cryic 3 = frigid 4 = isofrigid 5 = mesic 6 = isomesic 7 = thermic 8 = isothermic 9 = hyperthermic 10 =isohyperthermic Marginal Soils Index Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index at the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of 30m resolution. Both raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. A value of 0 indicates that there were no soil attributes present that indicate marginal soil. NA values indicate that data was unavailable or bodies of water. Files: marginal_soils_index_30m_raster.tif marginal_soils_index_1km_raster.tif Marginal Soils Index Resource Potential Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index + Resource Potential (MSI+RP) score at 1km resolution for geothermal, solar, and wind technologies. Raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. NA values indicate that the location is not suitable for siting the given technology due to policy, environmental, socioeconomic, topological, and other constraints regardless of soil marginality level. Areas with values greater than or equal to zero represent the product of the normalized MSI value and the normalized resource potential value. Files: geothermal_msi_ep_score_raster.tif solar_msi_ep_score_raster.tif wind_msi_ep_score_raster.tif Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Agriculture↗
DOE OSTI2026

Marginal Soils Index Analysis & Geospatial Data

This data package contains output files associated with the Mongird et al. paper entitled "Can US power grid expansion avoid prime agricultural lands?" and is organized into four dataset directories. Each dataset is described in more detail below. 1. Marginal Soils Index Analysis Description: This folder contains a csv file with land needs and availability by state, power generating technology type, and scenario in 2050 when suitable siting areas are additionally constrained to areas with increasing levels of soil marginality. Files: msi_constrained_siting_availability_2050.csv Variables: Scenario - Projected 2050 scenario name State - US state abbreviation Technology - Generating technology type solar = solar photovoltaic gas_cc_re = natural gas combined cycle (recirculating cooling) wind = onshore wind gas_cc_ccs_re = natural gas combined cycle with carbon capture sequestration (recirculating cooling) gas_cc_dry = natural gas combined cycle with (dry cooling) gas_cc_pond = natural gas combined cycle with (pond cooling) coal_conv_ccs_re = conventional coal with carbon capture sequestration (recirculating cooling) Req_Capacity_MW - The amount of rated capacity required in 2050 of the given technology type in the given state and under the given scenario from the capacity expansion plan Req_Capacity_Factor - The assumed capacity factor (fraction between 0 and 1) for the given technology type in the given state and under the given scenario by the capacity expansion plan Req_Land_km2 - The amount of land required (in km-squared) to host the required generating capacity that is capable of meeting the specified capacity factor for the given technology type in the given state and under the given scenario Req_Energy_TWh - Product of Req_Capacity_MW, Req_Capacity_Factor, and 8760/1e6 for the given technology type in the given state and under the given scenario MSI_Case - The level of MSI that siting the given technology is additionally constrained to, where >0 means siting is additionally constrained to suitable land areas that have an MSI value greater than 0 >=1 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 1 >=2 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 2 >=3 means siting is additionally constrained to suitable land areas that have an MSI value greater than or equal to 3 Soil Attribute Rasters Description: This folder contains geospatial raster files for individual soil parameters upscaled to the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of non-missing 30m resolution values. All raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. Files: avg_cond_raster_ .tif - Average conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm max_cond_raster_ .tif - Maximum conductivity of the saturation extract across all soil horizons within a depth of 40 inches, measured in mmhos/cm min_ph_raster_ .tif- Min pH values across all soil horizons within a depth of 40 inches. avg_ph_raster_ .tif - Average pH value across all soil horizons within a depth of 40 inches. max_ph_raster_ .tif- Max pH value across all soil horizons within a depth of 40 inches. erosion_factor_raster_ .tif - Product of k-factor and percent slope flood_freq_raster_ .tif - Number of months of the year during which the area is commonly, frequently, or very frequently flooded. max_sar_raster_ .tif - Maximum sodium adsorption ratio across all horizons within a depth of 40 inches rock_frac_raster_ .tif - Fraction of the upper 6 inches of soil composed of rock fragments larger than 3 inches. temp_regime_raster_ .tif - Soil temperature regime with the following key: 0 = pergelic 1 = gelic 2 = cryic 3 = frigid 4 = isofrigid 5 = mesic 6 = isomesic 7 = thermic 8 = isothermic 9 = hyperthermic 10 =isohyperthermic Marginal Soils Index Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index at the listed grid resolution (30m or 1 km). 1 km resolution files are a spatial average of 30m resolution. Both raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. A value of 0 indicates that there were no soil attributes present that indicate marginal soil. NA values indicate that data was unavailable or bodies of water. Files: marginal_soils_index_30m_raster.tif marginal_soils_index_1km_raster.tif Marginal Soils Index Resource Potential Rasters Description: This folder contains geospatial raster files of the Marginal Soils Index + Resource Potential (MSIxRP) score at 1km resolution for geothermal, solar, and wind technologies. Raster files use the USA Contiguous Albers Equal Area Conic (ESRI:102003) projection. NA values indicate that the location is not suitable for siting the given technology due to policy, environmental, socioeconomic, topological, and other constraints regardless of soil marginality level. Areas with values greater than or equal to zero represent the product of the normalized MSI value and the normalized resource potential value. Files: geothermal_msi_rp_score_raster.tif solar_msi_rp_score_raster.tif wind_msi_rp_score_raster.tif Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Agriculture↗
NASA NTRS2004

Anthropogenic Land-use Change and the Dynamics of Amazon Forest Biomass

This project was focused on assessing the effects of prevailing land uses, such as habitat fragmentation, selective logging, and fire, on biomass and carbon storage in Amazonian forests, and on the dynamics of carbon sequestration in regenerating forests. Ancillary goals included developing GIs models to help predict the future condition of Amazonian forests, and assessing the effects of anthropogenic climate change and ENS0 droughts on intact and fragmented forests. Ground-based studies using networks of permanent plots were linked with remote-sensing data (including Landsat TM and AVHRR) at regional scales, and higher-resolution techniques (IKONOS imagery, videography, LIDAR, aerial photographs) at landscape and local scales. The project s specific goals were quite eclectic and included: Determining the effects of habitat fragmentation on forest dynamics, floristic composition, and the various components of above- and below-ground biomass. Assessing historical and physical factors that affect trajectories of forest regeneration and carbon sequestration on abandoned lands. Extrapolating results from local studies of biomass dynamics in fragmented and regenerating forests to landscape and regional scales in Amazonia, using remote sensing and GIS. Testing the hypothesis that intact Amazonian forests are functioning as a significant carbon sink. Examining destructive synergisms between forest fragmentation and fire. Assessing the short-term impacts of selective logging on aboveground biomass. Developing GIS models that integrate current spatial data on forest cover, deforestation, logging, mining, highway and roads, navigable rivers, vulnerability to wild fires, protected areas, and existing and planned infrastructure projects, in an effort to predict the future condition of Brazilian Amazonian forests over the next 20-25 years. Devising predictive spatial models to assess the influence of varied biophysical and anthropogenic predictors on Amazonian deforestation.

Laurance, William F.↗
NASA NTRS2010

[Characterization of Black and Dichothrix Cyanobacteria Based on the 16S Ribosomal RNA Gene Sequence]

My project focuses on characterizing different cyanobacteria in thrombolitic mats found on the island of Highborn Cay, Bahamas. Thrombolites are interesting ecosystems because of the ability of bacteria in these mats to remove carbon dioxide from the atmosphere and mineralize it as calcium carbonate. In the future they may be used as models to develop carbon sequestration technologies, which could be used as part of regenerative life systems in space. These thrombolitic communities are also significant because of their similarities to early communities of life on Earth. I targeted two cyanobacteria in my research, Dichothrix spp. and whatever black is, since they are believed to be important to carbon sequestration in these thrombolitic mats. The goal of my summer research project was to molecularly identify these two cyanobacteria. DNA was isolated from each organism through mat dissections and DNA extractions. I ran Polymerase Chain Reactions (PCR) to amplify the 16S ribosomal RNA (rRNA) gene in each cyanobacteria. This specific gene is found in almost all bacteria and is highly conserved, meaning any changes in the sequence are most likely due to evolution. As a result, the 16S rRNA gene can be used for bacterial identification of different species based on the sequence of their 16S rRNA gene. Since the exact sequence of the Dichothrix gene was unknown, I designed different primers that flanked the gene based on the known sequences from other taxonomically similar cyanobacteria. Once the 16S rRNA gene was amplified, I cloned the gene into specialized Escherichia coli cells and sent the gene products for sequencing. Once the sequence is obtained, it will be added to a genetic database for future reference to and classification of other Dichothrix sp.

Ortega, Maya↗