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At least 451 records · Page 25

Integrated geological, economic, and risk assessment of underground hydrogen storage

Underground hydrogen storage (UHS) is a promising option to buffer variable renewable power and support the hydrogen economy. Yet this technology is early-stage, and key uncertainties remain about how coupled processes such as geochemical and geomechanical impacts affect long-term storage security. In this paper, we seek to integrate the results from a large, multi-scale research program to quantify core feasibility metrics and situate these studies within ongoing efforts. Through this work, we evaluate hydrogen recoverability during storage by assessing diffusive losses, losses to geochemical interactions and their subsequent impact on geomechanical properties, and losses to residual saturation during injection and withdrawal. Molecular and laboratory studies show that lithologic heterogeneity, pore geometry, and mineral surface chemistry govern hydrogen–rock interactions, controlling loss pathways. High-pressure coreflooding is used to estimate relative permeabilities and measure parameters needed for reservoir-scale sensitivity analyses. These core-scale experiments found early hydrogen breakthrough at low saturations driven by capillary and viscous fingering, which limits pore-space utilization at early times, while repeated injection and withdrawal cycles improve deliverability over time. Technoeconomic factors and purity requirements for end uses are also considered as part of our comprehensive feasibility analysis. Finally, we underscore the importance of geophysical monitoring and tailored injection strategies to maintain integrity and efficiency. Together, these results provide a quantitative foundation for safe, scalable deployment of UHS and highlight priorities for future integrated studies.

08 HYDROGEN↗

Design Principles of Single Atoms on Carbons for Lithium–Sulfur Batteries

The study of lithium-sulfur (Li-S) batteries has generated various rationally designed cathodes and modified separators. However, the shuttle of soluble lithium polysulfides (LiPSs) and the sluggish kinetics of transformation of LiPSs to Li2S2/Li2S still hinder the achievement of long-life cycling and high-rate of Li-S batteries. Even though several kinds of nanocatalysts have been studied, the catalytic effects for Li-S batteries are not ideal. Single atoms (SAs) with high surface free energy are found to serve as both anchoring and electrocatalytic centers for LiPSs. Furthermore, atomically dispersed metal catalyst on carbon provide conductive and flexible host for dielectric sulfur. Moreover, SAs as the uniform lithiophilic sites can reduce the nucleation overpotential and ensure uniformly plating of Li. In this review, the latest strategies for preparation of SAs supported on carbons are provided on the application of Li-S batteries, including cathode, modified separator and Li metal anode. In addition, it also discusses how SAs with high catalytic activity can help build better Li-S batteries and the design principles for SAs. Finally, the future directions of SAs in energy storage applications is proposed.

25 ENERGY STORAGE↗

Using Geophysical Technologies Deployed in Inexpensive Monitoring Wells to Monitor the Evolution of a CO 2 Plume: Potential Benefits and R&D Needs

This report demonstrates the potential benefits of an R&D program designed to substantially decrease the cost of drilling monitoring wells. The study determines the costs of monitoring a commercial-scale CO 2 storage project's CO 2 plume using a vertical seismic profile (VSP) array. The VSP array consists of permanent surface orbital vibrator (SOV) seismic sources and distributed acoustic sensing (DAS) fiber optic cable receivers permanently installed in shallow monitoring wells. Several scenarios are assessed varying the costs of drilling monitoring wells for DAS to evaluate the potential benefits of an R&D program to lower well costs. The monitoring costs of VSP are compared against those of 4-D seismic surveys which deploy temporary seismic sources and receivers. If the cost of monitoring wells can be lowered about 50%, VSP monitoring is a more attractive cost option than 4-D seismic for CO 2 plume monitoring, warranting future R&D efforts to lower these costs.

58 GEOSCIENCES↗

Study of Storage Requirements and Costs for Shaping Renewables and Nuclear Energy (FY23 Summary Report)

To decarbonize electricity generation primarily by using wind and solar resources, it is likely that additional low (or zero) carbon dioxide (CO 2 ) alternatives will be required for ensuring a reliable electricity supply. This study extends the work and modeling framework that we consolidated in FY 2022, by assessing the zero-CO 2 pathways of a Texas power system in which the availability of variable renewable energy (VRE), nuclear energy, and energy storage types (i.e., battery and thermal energy storage [TES]) are considered the sole resources available for expansion. Using the Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON) frameworks, this study investigates the market of two nuclear energy technologies (i.e., large light-water reactors [LWRs] and LWR-type small modular reactors [SMRs]) under two plausible storage coupling scenarios (i.e., electric coupling and direct thermal coupling). We also explore optimal environments for nuclear energy deployment, and identify key performance characteristics that make nuclear energy economically viable in areas with significant intermittent energy sources. Our analysis encompasses 24 cases. We model the least-cost grid systems, highlight the potential for a coupled LWR-TES approach, and utilize SMRs to achieve deep decarbonization in an affordable, technically feasible manner. We also examine seasonal variations in balancing electricity supply and demand, and account for varying performance, costs, and grid constraints. Overall, the findings of our modeling afford valuable insights for supporting future technology investment decisions in the energy sector.

25 ENERGY STORAGE↗

Lithium-Ion Battery Life Model with Electrode Cracking and Early-Life Break-in Processes

This paper develops a physically justified reduced-order capacity fade model from accelerated calendar- and cycle-aging data for 32 lithium-ion (Li-ion) graphite/nickel-manganese-cobalt (NMC) cells. The large data set reveals temperature-, charge C-rate-, depth-of-discharge-, and state of charge (SOC)-dependent degradation patterns that would be unobserved in a smaller test matrix. Model structure is informed by incremental capacity analysis that shows loss of lithium inventory and cathode-material loss as the dominant capacity fade mechanisms. The model includes terms attributable to solid-electrolyte interface (SEI) growth, electrode cracking, cycling-driven acceleration of SEI growth, and "break-in" mechanisms that slightly decrease or increase available Li inventory early in life. The study explores what mathematical couplings of these mechanisms best describe calendar aging, cycle aging, and mixed calendar/cycle aging. Various approaches are discussed for extracting relevant stress factors from complex cycling profiles to predict lifetime during real-world battery loads using models trained on constant-current laboratory test results. The complexity of the present human-driven model identification process motivates future work in machine learning to more widely search and statistically discern the optimal model that correctly extrapolates capacity fade based on physical knowledge.

25 ENERGY STORAGE↗

An approach for fast and accurate simulation of phase change material based thermal energy storage in buildings

Latent heat thermal energy storage (LHTES) has significant potential for mitigating peak electricity demand and enabling load shifting in buildings. Phase Change Material embedded heat exchangers (PCM-HX) can significantly improve energy demand management due to high storage capacity. However, PCM-HX evaluation typically depends on computationally expensive fully transient simulations, posing significant challenges for scalable system- and building-level energy assessments across different climates and system architectures. This paper presents a generalized, accurate, and computationally efficient methodology for simulating building energy systems integrated with LHTES. The PCM-HX transient performance is represented by performance maps generated using a Generalized Resistance-Capacitance Model (GRCM) that enables accurate predictions of arbitrary PCM-HXs at low computational cost. The feasibility of the proposed approach was verified using a case study considering a dual-mode heat pump-thermal energy storage (HP-TES) system simulated in Modelica with Spawn of EnergyPlus™ for a DOE prototype small office building in two locations: Tampa, FL, and International Falls, MN. The PCM-HX performance maps provided accurate predictions of PCM-HX transient behavior, with mean absolute percentage deviations within 2–4% compared to GRCM while also achieving at least 1800× reduction in computational time. Moreover, the HP-TES system achieved energy savings of up to 17.4% in Tampa, FL, and 62.2% in International Falls, MN, demonstrating the broader applicability of the proposed methodology across different climate zones. This work highlights the importance of robust PCM-HX models in enabling accurate and computationally efficient building-level simulations and enabling future research opportunities for investigating optimized HP-TES designs and advanced control strategies for grid-interactive buildings.

Modelica↗

An exploration of benchtop X–ray emission spectroscopy for precise characterization of the sulfur redox state in cementitious materials

The evolution of sulfur chemistry in cements is best known in the bailiwick of failure mechanisms via sulfate attack but is equally important for its contributions to the reduction capacity of cementitious materials often used for immobilizing nuclear waste streams destined for long-term storage, e.g., cementitious waste forms (CWF). The total reduction capacity of CWFs, encompassing contributions from both S and Fe reductants, and its implications toward radionuclide immobilization is most often studied by destructive wet chemistry methods requiring acid digestion in the presence of Ce(IV) and subsequent titration and colorimetric interpretation. Here, we investigate a similarly analytical but nondestructive alternative, benchtop high resolution wavelength-dispersive x-ray fluorescence spectroscopy, most commonly known as x-ray emission spectroscopy (XES), for probing the bulk sulfur oxidation state distribution. We present here an initial investigation of S XES, including an improved experimental protocol for lab XES of inhomogeneous samples, both as a complement to the Ce(IV) test and for new scientific opportunities that it enables for observing changes in sulfur chemistry. We discuss future improvements and opportunities, including: (1) the practical challenges associated with coordinating XES and Ce(IV) liquid extraction for a more comprehensive perspective on reduction capacity and for a high-precision evaluation of uncertainties in the Ce(IV) test; and (2) new opportunities, due to the nondestructive nature of XES, for controlled evolution studies aimed at elucidating specific chemical responses of CWF’s exposed to invasive gas or liquid species or to accelerated aging by radiative dose or thermal treatment.

36 MATERIALS SCIENCE↗

Calendar aging of silicon-containing batteries

High-energy batteries for automotive applications require cells to endure well over a decade of constant use, making their long-term stability paramount. This is particularly challenging for emerging cell chemistries containing silicon, for which extended testing information is scarce. While much of the research on silicon anodes has focused on mitigating the consequences of volume changes during cycling, comparatively little is known about the time-dependent degradation of silicon-containing batteries. Here we discuss a series of studies on the reactivity of silicon that, collectively, paint a picture of how the chemistry of silicon exacerbates the calendar aging of lithium-ion cells. Assessing and mitigating this shortcoming should be the focus of future research to fully realize the advantages of this battery technology.

25 ENERGY STORAGE↗

Revisiting the role of Zr doping in Ni-rich layered cathodes for lithium-ion batteries

We report the realization of high performance Ni-rich layered cathodes remains a challenge because of the multiple degradation factors that concurrently operate during battery cycling. In particular, depletion of oxygen charge and consequent lattice oxygen instability at deep charge state accelerate the subsequent chemomechanical degradation mechanisms. Among the proposed methodologies, doping has proven to be effective in enhancing the cathode cycle life by stabilizing the layered structure. Herein, we achieved the electrochemically stabilized Ni-rich LiNi 0.92 Co 0.04 Mn 0.04 O 2 through Zr doping, resulting in a 15% increase of the capacity retention after 100 cycles. In-depth investigations are conducted to unveil the effects of Zr doping on the layered cathode, and in particular, the critical role of Zr doping on the lattice oxygen stability is systematically studied. By combining state-of-the-art magnetometer characterization, X-ray analysis, and first-principles calculation, we reveal that Zr doping positively contributes the to lattice oxygen stability by alleviating the oxygen charge loss at deep charge, thereby improving the cathode electrochemical reversibility. Our findings provide an insight into the Zr doping mechanism and help to design the Ni-rich layered oxides for future applications.

25 ENERGY STORAGE↗

Adaptive Protection and Validated Models to Enable Deployment of High Penetrations of Solar PV (PV-MOD)

The availability and validation of various PV models in commercial tools differ, with some models not yet thoroughly validated for advanced inverter functionalities and reliable performance under weak system conditions. Many existing models do not fully incorporate new inverter control functions, which can affect system stability. The increasing deployment of solar PV and other inverter-based resources (IBRs), including distributed energy resources (DERs), is influencing the reliable operation of protection schemes in distribution systems and microgrids. Emerging adaptive protection schemes (APS) offer new opportunities for protecting these systems during varying configurations and DER operating conditions, though their demonstration and validation remain limited. Adaptive protection schemes face similar challenges, as they are typically designed for specific configurations. There is a growing need for tools and methodologies to streamline the deployment of adaptive protection for safe and reliable DER integration. The project main objective was to develop and validate high-fidelity generic models of solar PV facilities for stability, protection, EMT, and QSTS analyses. This objective was achieved, and these models can now be integrated into commercial software tools, enabling utilities, vendors, and developers to study high-penetration PV systems more confidently. The project also demonstrated advanced applications of these models, including the design and deployment of adaptive protection schemes in high-penetration field applications and microgrids, supporting grid safety and reliability. Several milestones were reached by the end of the project. A sophisticated inverter test plan was developed, and inverters representative of the North American marketplace were selected. EPRI and NREL tested various inverters, conforming to IEEE standards. Improvements were made to existing generic models of IBR units, IBR plants, and aggregated feeders for various analyses. The first generic electromagnetic transient (EMT) model for a solar PV plant was developed, conforming to IEEE Std 2800™-2022 and validated against laboratory measurements of a 2.2 MVA large-scale battery energy storage system (BESS) inverter. That model was then used to produce reference responses illustrating examples of validated and verified IBR plant models that pass or fail tests for technical minimum capability and performance as specified in the IEEE standard. The developed, tested, and validated generic models can be used for transmission planning, stability assessments, expansion planning, and evaluating potential future IBR interconnection requirements. They can also support interconnection screens and conformity assessments of IBR plants, including solar PV. The project significantly contributed to the ongoing standardization and model-based representation and verification of IBR responses. The project further addressed challenges of common distribution protection schemes with increasing deployment of DER by developing, validating, and demonstrating adaptive protection schemes (APS) that can improve the reliable and safe integration of DER into distribution systems. New APS were designed using improved DER models for three common distribution systems: a radial feeder, a meshed network, and a microgrid. Modeling and hardware-in-the-loop (HIL) testing of the APS were conducted, successfully showing their effectiveness and selectivity. Proof-of-concept field demonstration was achieved for two APS, i.e., one on a radial feeder and another one in a microgrid. Field demonstration could not be achieved for the APS on a meshed network, primarily due apprehension of one utility partner and also due to limited access to the protective algorithms in the network protectors. Guidelines developed from the lessons learned in the project lay out the general process followed in the design, installation, and commissioning of APS for various distribution systems. Distribution utility partners’ apprehension about field demonstration of the new APS were addressed—with varying success—by taking a stepped risk-management approach of modeling of a wide range of sensitivities first, performing in-depth proof-of-concept testing in the laboratory including HIL next, and finally deliberately implementing and commissioning the actual protection equipment and algorithms into parts of—or in parallel operation to—the three real distribution systems. Future work should include pilot projects that further show the acceptable performance of the developed APS before these schemes be rolled out more widely. Inclusion of both utility and original equipment manufacturers (OEMs) in future projects could increase chances of successful field demonstration. Despite challenges in achieving the field demonstration goal of the project for all three APS, the research significantly contributed to the innovation of adaptive protection solutions for scalable and reliable DER integration into distribution systems. This project significantly enhances the understanding of the impact of using appropriate inverter models on distribution and transmission (T&D) systems. By addressing the limitations of existing generic models, the project introduces high-fidelity models for stability, protection, electromagnetic transient (EMT), and quasi-static time series (QSTS) analyses. These models, integrated into commercial software tools, enable utilities, vendors, and developers to confidently study high-penetration PV systems. The project also demonstrates advanced applications, including adaptive protection schemes (APS) for distribution systems and microgrids, ensuring grid safety and reliability. The technical effectiveness and economic feasibility of the methods are evident through the development and validation of sophisticated inverter test plans and the selection of representative inverters. Testing by EPRI and NREL on retail, commercial, and utility-scale inverters, conforming to IEEE standards, underscores the robustness of the models. Improvements to existing generic models for various analyses further enhance their validity and applicability. The project also identifies gaps in common distribution protection schemes and designed new APS using improved DER models, demonstrating their effectiveness through modeling and hardware-in-the-loop (HIL) testing. The project’s benefits to the public are manifold. By advancing the standardization and model-based representation of IBR response, it supports transmission planning, stability assessments, and future IBR interconnection requirements. The generic models can facilitate better communication between transmission planners and developers, supporting expected IBR plant capability and performance. Additionally, the development of APS for radial feeders, meshed networks, and microgrids supports the integration of distributed energy resources (DERs) into distribution systems, enhancing grid reliability and safety. The project’s emphasis on thorough testing and simplicity in design ensures practical and scalable solutions for DER integration.

14 SOLAR ENERGY↗

Super p-sulfur cathodes for quasi-solid-state lithium-sulfur-batteries

Lithium-Sulfur (Li-S) batteries have become a promising candidate to meet the current energy storage demand, with its natural abundance of materials, high theoretical capacity of 1672 mAhg-1, high energy density of 2600 Whkg-1, low cost and lower environmental impact. Sulfide based solid state electrolytes (SSEs) have received greater attention due to their higher ionic conductivity, compatible interface with sulfur-based cathodes, and lower grain boundary resistance. However, the interface between SSEs and cathodes has become a challenge in all solid-state Li-S batteries due to the rigidity of the participating surfaces. A hybrid electrolyte containing SSE coupled with a small amount of ionic liquid, was essential to improve the interface contact of the SSE with the electrodes. Coating-based cathodes were successfully fabricated using water-based carboxymethyl cellulose (CMC) solution and Styrene butadiene rubber (SBR) as the binder with low sulfur loading (0.70 mgcm-2) as well as high sulfur loading (4.0 mgcm-2). Solid-state composite powder-based cathodes pressed onto SSE (loading 4.0 mgcm-2) with enhanced electronic and ionic conductivity were fabricated with Super P: Sulfur (SP:S) and SSE. Ionic Liquids (IL) prepared using Lithium bis(trifluoromethyl sulfonyl)imide (LiTFSI) as salt, with premixed pyrrolidinium bis(trifluoromethyl sulfonyl)imide (PYR) as solvent and 1,3-dioxolane (DOL) as diluent were used to wet both SSE-electrode interfaces. The effect of IL dilution, co-solvent amount, LiTFSI concentration, C rate at which the batteries are tested and the effect of SSE inside the cathode, were systematically studied and optimized to develop a quasi-solid-state electrolyte Li-S battery (QSSLSB) with higher capacity retention and cyclability. LiTFSI (2M) dissolved in PYR:DOL(1:1) found to be optimum IL combination for low sulfur loading QSSLSBs reaching 500 mAh/g after 100 cycles while LiTFSI (3M) in PYR:DOL(1:3) was the optimum IL concentration for higher loading QSSLSBs reaching 400 mAh/g after 100 cycles. This work reports promising results of QSSLSB based on novel Li6PS5F0.5Cl0.5 Li-argyrodite solid-state electrolyte (SSE) with minute amount of IL, Super P-Sulfur (SP:S) cathode, and Li-anode. It also offers a new insight into the intimate interfacial contacts between the SSE and carbon-sulfur cathodes, which will be critical for improved electrochemical performance of quasi-solid-state lithium-sulfur batteries with high sulfur loading in the future.

25 ENERGY STORAGE↗

Using stable isotopes to inform water resource management in forested and agricultural ecosystems

Present and future climatic trends are expected to markedly alter water fluxes and stores in the hydrologic cycle. In addition, water demand continues to grow due to increased human use and a growing population. Sustainably managing water resources requires a thorough understanding of water storage and flow in natural, agricultural, and urban ecosystems. Measurements of stable isotopes of water (hydrogen and oxygen) in the water cycle (atmosphere, soils, plants, surface water, and groundwater) can provide information on the transport pathways, sourcing, dynamics, ages, and storage pools of water that is difficult to obtain with other techniques. However, the potential of these techniques for practical questions has not been fully exploited yet. Here, we outline the benefits and limitations of potential applications of stable isotope methods useful to water managers, farmers, and other stakeholders. We also describe several case studies demonstrating how stable isotopes of water can support water management decision-making. Finally, we propose a workflow that guides users through a sequence of decisions required to apply stable isotope methods to examples of water management issues. We call for ongoing dialogue and a stronger connection between water management stakeholders and water stable isotope practitioners to identify the most pressing issues and develop best-practice guidelines to apply these techniques.

54 ENVIRONMENTAL SCIENCES↗

Al2O3 Atomic Layer Deposition on Nanostructured γ-Mg(BH4)2 for H2 Storage

In the context of the growing hydrogen (H 2 ) economy, the demand for H 2 storage materials is high, and metal borohydrides are of particular interest. Magnesium borohydride, Mg(BH 4 ) 2 , has one of the highest hydrogen capacities of all known metal hydrides (14.9 wt % H) but suffers from high operating temperatures, slow kinetics for (de)hydrogenation, and the loss of capacity upon cycling. Strategies to address these challenges include nanoencapsulation and the use of chemical additives. This work is the first to utilize these two strategies simultaneously by using atomic layer deposition (ALD). For this new approach to modify borohydrides, we chose the well-studied Al 2 O 3 ALD process using trimethylaluminum and water. Although there has been limited use of aluminum-based additives for Mg(BH 4 ) 2 , we demonstrate that the low-temperature H 2 capacity was doubled, desorption kinetics were increased by a factor of 3, and 100 cycles of Al 2 O 3 suppressed the release of diborane compared to the uncoated Mg(BH4)2. We identified that the use of trimethylaluminum and water in the ALD process affected the decomposition pathway and that the Al 2 O 3 film growth is dominated by infiltration due to the high porosity of the ..gamma..-phase Mg(BH 4 ) 2 . From these results, the potential of ALD as a method to functionalize solid-state H 2 storage materials is inferred, and recommendations for future ALD processes are presented.

08 HYDROGEN↗

Recent advancements in high performance polymer electrolyte fuel cell electrode fabrication – Novel materials and manufacturing processes

The global effort to introduce polymer electrolyte fuel cells for clean and renewable energy to the market is increasing the demand for high performance, robust and affordable membrane electrode assemblies (MEAs). There is not yet a standard method for large scale production of MEAs, or the methods employed are generally unsatisfactory in terms of quality and performance. A large number of published data of newly developed catalyst and electrolyte materials, claim to improve the state of the art, but are often not fully comparable due to different experimental studies and experimental designs. This article summarizes the trends in material developments and emerging MEA-manufacturing techniques. The materials and techniques are systematically compared in terms of cell performance and scalability. Current and future scientific challenges are identified and analysed based on published findings over the past five years. Finally, the results of the cited papers have been quantitatively compared to each other and to the internal benchmarks used in each cited work to provide a complete picture of the state of the art in PEFC MEA manufacturing.

25 ENERGY STORAGE↗

New Modulation and Impact of Transformer Leakage Inductance on Current-Source Solid-State Transformer

This article presents a novel modulation scheme for device voltage stress mitigation and comprehensive analysis of the impact of transformer leakage inductance in a current-source solid-state transformer (SST). Different from dual active bridge (DAB) SST, the operation of the current-source SST is similar to that of a flyback converter. The device bridge on only one side of the transformer is active to store energy into or release energy from the magnetizing inductance which acts as a current-source dc link. Such flyback operation with reverse-blocking switches can lead to additional device voltage stress and incomplete zero-voltage switching (ZVS) on the current-source soft-switching solid-state transformer (S4T) under conventional modulation. A new modulation scheme is proposed to address this issue. Moreover, different from the DAB, the leakage inductance of the medium-frequency transformer (MFT) in the S4T is a parasitic element similar to that in a matrix SST and can cause additional device voltage stress. Though the resonant capacitors, originally added to achieve ZVS, can absorb and recycle the leakage energy in the S4T, these capacitors need to be increased with larger leakage inductances to limit the voltage stress. However, large resonant capacitors can result in more lost duty cycles and reduced efficiency. The impact of such leakage inductance on device voltage stress is analyzed comprehensively, which is critical to guide future research and design of the S4T. Experimental results from S4T prototypes for DC-DC, multiport AC-DC, and AC-AC conversion with 1:1 and 4:1 MFT comprehensively verify the proposed concepts. Lastly, a case study of a three-phase AC-AC S4T over a power range from 1 kVA to 100 kVA each module reveals that the MFT leakage inductance should be less than 1% of the magnetizing inductance for safe operation.

14 SOLAR ENERGY↗

N and P constrain C in ecosystems under climate change: Role of nutrient redistribution, accumulation, and stoichiometry

Abstract We use the Multiple Element Limitation (MEL) model to examine responses of 12 ecosystems to elevated carbon dioxide (CO 2 ), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO 2 , warming, and decreased precipitation combined because higher water‐use efficiency with elevated CO 2 and higher fertility with warming compensate for responses to drought. Response to elevated CO 2 , warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and P distribution between vegetation and soil, (3) changes in vegetation C:N and C:P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO 2 and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C:N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C‐nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO 2 and climate change.

54 ENVIRONMENTAL SCIENCES↗

Developing a Prototype Methodology to Rank CO2-EOR Wells and Assess Their Reuse Potential for Geologic Carbon Sequestration

This study presents a prototype methodology for evaluating the reuse potential of Class II CO₂-enhanced oil recovery (CO₂-EOR) wells as Class VI wells for geologic carbon sequestration. The approach focuses on assessing wellbore construction materials—casing, cement, tubing, and packers—based on U.S. Environmental Protection Agency (EPA) Class VI well conversion guidelines. Utilizing Python scripts and JSON representations, the methodology automates checks on digitized Texas Railroad Commission (TRRC) data to rank wells based on regulatory and integrity criteria. Key factors include casing integrity, cementing techniques, tubing compatibility, and packer selection. Due to limitations in digitized data, manual verification is required for certain sections. Future enhancements include incorporating non-digitized data via web scraping and machine learning. This research provides a practical framework for well owners and regulators, supporting informed decision-making for sustainable CO₂ storage.

carbon sequestration↗

Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects

This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.

Holcomb, Paul↗