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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Tandem Mass Spectrometry and Ion Mobility Reveals Structural Insight into Eicosanoid Product Ion Formation

Ion mobility measurements of product ions were used to characterize the collisional cross section (CCS) of various complex lipid [M-H]{sup −} ions using traveling wave ion mobility mass spectrometry (TWIMS). TWIMS analysis of various product ions derived after collisional activation of mono- and dihydroxy arachidonate metabolites was found to be more complex than the analysis of intact molecular ions and provided some insight into molecular mechanisms involved in product ion formation. The CCS observed for the molecular ion [M-H]{sup −} and certain product ions were consistent with a folded ion structure, the latter predicted by the proposed mechanisms of product ion formation. Unexpectedly, product ions from [M-H-H{sub 2}O-CO{sub 2}]{sup −} and [M-H-H{sub 2}O]{sup −} displayed complex ion mobility profiles suggesting multiple mechanisms of ion formation. The [M-H-H{sub 2}O]{sup −} ion from LTB{sub 4} was studied in more detail using both nitrogen and helium as the drift gas in the ion mobility cell. One population of [M-H-H{sub 2}O]{sup −} product ions from LTB{sub 4} was consistent with formation of covalent ring structures, while the ions displaying a higher CCS were consistent with a more open-chain structure. Using molecular dynamics and theoretical CCS calculations, energy minimized structures of those product ions with the open-chain structures were found to have a higher CCS than a folded molecular ion structure. The measurement of product ion mobility can be an additional and unique signature of eicosanoids measured by LC-MS/MS techniques. .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Thermal effects on geologic carbon storage

One of the most promising ways to significantly reduce greenhouse gases emissions, while carbon-free energy sources are developed, is Carbon Capture and Storage (CCS). Non-isothermal effects play a major role in all stages of CCS. In this paper, we review the literature on thermal effects related to CCS, which is receiving an increasing interest as a result of the awareness that the comprehension of non-isothermal processes is crucial for a successful deployment of CCS projects. We start by reviewing CO 2 transport, which connects the regions where CO 2 is captured with suitable geostorage sites. The optimal conditions for CO 2 transport, both onshore (through pipelines) and offshore (through pipelines or ships), are such that CO 2 stays in liquid state. To minimize costs, CO 2 should ideally be injected at the wellhead in similar pressure and temperature conditions as it is delivered by transport. To optimize the injection conditions, coupled wellbore and reservoir simulators that solve the strongly non-linear problem of CO 2 pressure, temperature and density within the wellbore and non-isothermal two-phase flow within the storage formation have been developed. CO 2 in its way down the injection well heats up due to compression and friction at a lower rate than the geothermal gradient, and thus, reaches the storage formation at a lower temperature than that of the rock. Inside the storage formation, CO 2 injection induces temperature changes due to the advection of the cool injected CO 2 , the Joule-Thomson cooling effect, endothermic water vaporization and exothermic CO 2 dissolution. These thermal effects lead to thermo-hydro-mechanical-chemical coupled processes with non-trivial interpretations. These coupled processes also play a relevant role in “Utilization” options that may provide an added value to the injected CO 2 , such as Enhanced Oil Recovery (EOR), Enhanced Coal Bed Methane (ECBM) and geothermal energy extraction combined with CO 2 storage. If the injected CO 2 leaks through faults, the caprock or wellbores, strong cooling will occur due to the expansion of CO 2 as pressure decreases with depth. Finally, we conclude by identifying research gaps and challenges of thermal effects related to CCS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Machine learning and deep learning for mineralogy interpretation and CO 2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin

Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO 2 ) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO 2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO 2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO 2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO 2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. In conclusion, the study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.

58 GEOSCIENCES↗
DOE OSTI2024

Large-scale spatially explicit analysis of carbon capture at cellulosic biorefineries

The large-scale production of cellulosic biofuels would involve spatially distributed systems including biomass fields, logistics networks and biorefineries. Better understanding of the interactions between landscape-related decisions and the design of biorefineries with carbon capture and storage (CCS) in a supply chain context is needed to enable efficient systems. Here we analyse the cost and greenhouse gas mitigation potential for cellulosic biofuel supply chains in the US Midwest using realistic spatially explicit land availability and crop productivity data and consider fuel conversion technologies with detailed CCS design for their associated CO 2 streams. Optimization methods identify trade-offs and design strategies leading to systems with attractive environmental and economic performance. Strategic and operational decisions depend on underlying spatial features and are sensitive to biofuel demand and CCS incentives. US CCS incentives neglect to motivate greenhouse gas mitigation from all supply chain emission sources, which leverage spatial interactions between CCS, electricity prices and the biomass landscape.

09 BIOMASS FUELS↗
DOE OSTI2017

A structural examination and collision cross section database for over 500 metabolites and xenobiotics using drift tube ion mobility spectrometry

The confident identification of metabolites and xenobiotics in biological and environmental studies is an analytical challenge due to their immense dynamic range, vast chemical space and structural diversity. Ion mobility spectrometry (IMS) is widely used for small molecule analyses since it can separate isomeric species and be easily coupled with front end separations and mass spectrometry for multidimensional characterizations. However, to date IMS metabolomic and exposomic studies have been limited by an inadequate number of accurate collision cross section (CCS) values for small molecules, causing features to be detected but not confidently identified. In this work, we utilized drift tube IMS (DTIMS) to directly measure CCS values for over 450 small molecules including primary metabolites, secondary metabolites and xenobiotics. Since DTIMS measurements do not need calibrates, they avoid calibration errors which can cause CCS accuracy problems and difficulties identifying structurally similar molecules. Furthermore, all measurements were performed in triplicate in both positive and negative polarities with nitrogen gas and seven different electric fields, so that relative standard deviations (RSD) could be assessed for each molecule and structural differences studied. The primary metabolites selected for the database are from key metabolism pathways such as glycolysis, the pentose phosphate pathway, and the tricarboxylic acid (TCA) cycle, while the secondary metabolites consist of classes such as terpenes and flavonoids, and the xenobiotics represent a range of molecules from antibiotics to polycyclic aromatic hydrocarbons. Different CCS trends were observed for several of the diverse small molecule classes, allowing insight in their separations and a possible why of classifying unknowns. This CCS database and structural information are freely available for download at http://panomics.pnnl.gov/metabolites/ with new molecules being added monthly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Assessing reservoir performance for geologic carbon sequestration in offshore saline reservoirs

Carbon capture and storage (CCS) is a technological strategy to reduce CO 2 emissions from hydrocarbon-based energy production and non-energy industrial emitters, like fertilizer and cement production. To expand the geographic opportunities for CCS, offshore geologic settings are increasingly considered for saline CO 2 storage, particularly where legacy oil and gas infrastructure may be repurposed for CO 2 transport and injection. In this context, the Gulf of Mexico (GoM), United States (U.S.), may offer tremendous opportunity for CCS because the surrounding states are among the largest CO 2 producers in the U.S. and there has been extensive oil and gas development over the last half century. Nevertheless, there remains significant uncertainty in how GoM reservoir/seal systems will respond to industrial-scale CO 2 injections, particularly in the context of meso-scale (1–10s of meters) permeability variations that are difficult to identify prior to injection. Such permeability variations can have significant impacts on CO 2 migration and fluid pressure propagation, both of which govern the overall effectiveness of the CCS project. This research uses ensemble simulation methods to quantify the influence of spatially variable and a priori unknown permeability fields on CO 2 plume development and fluid pressure propagation when CO 2 is injected at 1 MMt per year for ten years. Results show a number of characteristic patterns that reveal the substantial influence of both near- and far-field permeability on reservoir performance. By focusing on basin characteristics that are common among offshore basins worldwide, results from this study suggest that offshore CCS may be a feasible carbon management strategy in regions where offshore basins are proximal to industrial CO 2 sources.

42 ENGINEERING↗
DOE OSTI2014

Validation of plasma shape reconstruction by Cauchy condition surface method in KSTAR

Cauchy Condition Surface (CCS) method is a numerical approach to reconstruct the plasma boundary and calculate the quantities related to plasma shape using the magnetic diagnostics in real time. It has been applied to the KSTAR plasma in order to establish the plasma shape reconstruction with the high elongation of plasma shape and the large effect of eddy currents flowing in the tokamak structures for the first time. For applying the CCS calculation to the KSTAR plasma, the effects by the eddy currents and the ferromagnetic materials on the plasma shape reconstruction are studied. The CCS calculation includes the effect of eddy currents and excludes the magnetic diagnostics, which is expected to be influenced largely by ferromagnetic materials. Calculations have been performed to validate the plasma shape reconstruction in 2012 KSTAR experimental campaign. Comparison between the CCS calculation and non-magnetic measurements revealed that the CCS calculation can reconstruct the accurate plasma shape even with a small I{sub P}.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

A two-layer approach to the coupled coherent states method

In this paper, a two-layer scheme is outlined for the coupled coherent states (CCS) method, dubbed two-layer CCS (2L-CCS). The theoretical framework is motivated by that of the multiconfigurational Ehrenfest method, where different dynamical descriptions are used for different subsystems of a quantum mechanical system. This leads to a flexible representation of the wavefunction, making the method particularly suited to the study of composite systems. It was tested on a 20-dimensional asymmetric system-bath tunnelling problem, with results compared to a benchmark calculation, as well as existing CCS, matching-pursuit/split-operator Fourier transform, and configuration interaction expansion methods. The two-layer method was found to lead to improved short and long term propagation over standard CCS, alongside improved numerical efficiency and parallel scalability. These promising results provide impetus for future development of the method for on-the-fly direct dynamics calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

CLUSTER FORMATION TRIGGERED BY FILAMENT COLLISIONS IN SERPENS SOUTH

The Serpens South infrared dark cloud consists of several filamentary ridges, some of which fragment into dense clumps. On the basis of CCS (J{sub N} = 4{sub 3}-3{sub 2}), HC{sub 3}N (J = 5-4), N{sub 2}H{sup +} (J = 1-0), and SiO (J = 2-1, v = 0) observations, we investigated the kinematics and chemical evolution of these filamentary ridges. We find that CCS is extremely abundant along the main filament in the protocluster clump. We emphasize that Serpens South is the first cluster-forming region where extremely strong CCS emission is detected. The CCS-to-N{sub 2}H{sup +} abundance ratio is estimated to be about 0.5 toward the protocluster clump, whereas it is about 3 in the other parts of the main filament. We identify six dense ridges with different V {sub LSR}. These ridges appear to converge toward the protocluster clump, suggesting that the collisions of these ridges may have triggered cluster formation. The collisions presumably happened within a few × 10{sup 5} yr because CCS is abundant only for a short time. The short lifetime agrees with the fact that the number fraction of Class I objects, whose typical lifetime is 0.4 × 10{sup 5} yr, is extremely high, about 70% in the protocluster clump. In the northern part, two ridges appear to have partially collided, forming a V-shape clump. In addition, we detected strong bipolar SiO emission that is due to the molecular outflow blowing out of the protostellar clump, as well as extended weak SiO emission that may originate from the filament collisions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association

Abstract Motivation Drift tube ion mobility spectrometry coupled with mass spectrometry (DTIMS-MS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS at multiple electric fields and compute their associated collisional cross sections (CCS), we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of data that can then be used to create a reference library of experimental CCS values for use in high throughput omics analyses. Results We demonstrate the utility of this approach by automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE-generated CCS values were within error of those calculated using commercially available instrument vendor software. Availability and implementation PIXiE is an open-source tool, freely available on Github. The documentation, source code of the software, and a GUI can be found at https://github.com/PNNL-Comp-Mass-Spec/PIXiE and the source code of the backend workflow library used by PIXiE can be found at https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library. Supplementary information Supplementary data are available at Bioinformatics online.

Ma, Jian↗
DOE OSTI2015

The formation of correlated states and optimization of the tunnel effect for low-energy particles under nonmonochromatic and pulsed action on a potential barrier

We consider peculiarities of the formation of a coherent correlated state (CCS) of a low-energy particle under frequency modulation of parameters of a harmonic oscillator that contains this particle by a broadband nonmonochromatic or asymmetric pulsed action. It is shown that in the case of modulation with frequency-normalized intensity, the maximum efficiency of CCS formation corresponds to a narrow-band action, while broadband modulation is optimal for the action with a constant spectral density. As in the case of monochromatic modulation, the maximum correlation coefficient, |r|{sub max}, under the nonmonochromatic action corresponds to parametric resonance at frequency Ω ≈ 2ω{sub 0}. Under a pulsed action, the maximum efficiency of CCS formation and, hence, the maximum probability of the tunnel effect, correspond to pulsed modulation with a short leading edge and a long trailing edge. In particular, under the action of a pulsed magnetic field with an amplitude of 10 kOe and the leading edge duration of 2 × 10{sup –7} s on a gas with deuterium ions, a CCS can be formed with the correlation coefficient |r|{sub max} ≈ 0.9998, for which the tunneling effect probability under the dd interaction at temperature T ≈ 300–500 K increases from D{sub r=0} ≈ 10{sup −80} to D{sub |r|{sub m{sub a{sub x=0.9998}}}}≈0.1. This process can occur in a gas with particle number density n < n{sub cr} ≈ 10{sup 17} cm{sup −3}. The method of CCS formation makes it possible to explain the results of an experiment in which substantial isotope changes were detected when a pulsed electric current and magnetic-field generation occurred.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Considering the Role of Natural Gas in the Deep Decarbonization of the U.S. Electricity Sector. Natural Gas and the Evolving U.S. Power Sector Monograph Series: Number 2

Natural gas generation in the U.S. electricity sector has grown substantially in recent years, while the sector's carbon dioxide (CO2) emissions have generally declined. This relationship highlights the concept of natural gas as a potential enabler of a transition to a lower-carbon future. This work considers that concept by using the National Renewable Energy Laboratory (NREL) Renewable Energy Deployment System (ReEDS) model. ReEDS is a long-term capacity expansion model of the U.S. electricity sector. We examine the role of natural gas within the ReEDS modeling framework as increasingly strict carbon emission targets are imposed on the electricity sector. In addition to various natural gas price futures, we also consider scenarios that emphasize a low-carbon technology in order to better understand the role of natural gas if that low-carbon technology shows particular promise. Specifically, we consider scenarios with high amounts of energy efficiency (EE), low nuclear power costs, low renewable energy (RE) costs, and low carbon capture and storage (CCS) costs. Within these scenarios we find that requiring the electricity sector to lower CO2 emissions over time increases near-to-mid-term (through 2030) natural gas generation (see Figure 1 - left). The long-term (2050) role of natural gas generation in the electricity sector is dependent on the level of CO2 emission reduction required. Moderate reductions in long-term CO2 emissions have relatively little impact on long-term natural gas generation, while more stringent CO2 emission limits lower long-term natural gas generation (see Figure 1 - right). More stringent carbon targets also impact other generating technologies, with the scenarios considered here seeing significant decreases in coal generation, and new capacity of nuclear and renewable energy technologies over time. Figure 1 also demonstrates the role of natural gas in the context of scenarios where a specific low-carbon technology is advantaged. In 2030, natural gas generation in the technology scenarios is quite similar to that in the reference scenarios, indicating relatively little change in the role of natural gas in the near-to-mid-term due to advancements in those technology areas. The 2050 natural gas generation shows more significant differences, suggesting that technology advancements will likely have substantial impacts on the role of natural gas in the longer-term timeframe. Natural gas generation differences are most strongly driven by alternative natural gas price trajectories--changes in natural gas generation in the Low NG Price and High NG Price scenarios are much larger than in any other scenario in both the 2030 and 2050 timeframes. The only low-carbon technology scenarios that showed any increase in long-term natural gas generation relative to the reference case were the Low CCS cost scenarios. Carbon capture and storage technology costs are currently high, but have the potential to allow fossil fuels to play a larger role in low-carbon grid. This work considers three CCS cost trajectories for natural gas and coal generators: a baseline trajectory and two lower cost trajectories where CO2 capture costs reach $40/metric ton and $10/metric ton, respectively. We find that in the context of the ReEDS model and with these assumed cost trajectories, CCS can increase the long-term natural gas generation under a low carbon target (see Figure 2). Under less stringent carbon targets we do not see ReEDS electing to use CCS as part of its electricity generating portfolio for the scenarios considered in this work.

03 NATURAL GAS↗
DOE OSTI2015

SECARB Presentation/Publication of Annual Results [Slides]

Contents include the following: 1) SECARB’s Anthropogenic Test: Phase III Update, March 9, 2010; 2) SECARB Anthropogenic Test Overview: Integrated CO 2 capture, transport, and storage, March 10, 2011; 3) SECARB Phase III Anthropogenic Test–Risk Management Through Detailed Geologic Characterization and Modeling, March 9-10, 2011; 4) SECARB Stakeholders Meeting Plant Barry CCS Demo, March 8, 2012; 5) SECARB Plant Barry to Citronelle 4" CO 2 Pipeline, March 8, 2012; 6) Geologic Characterization and Baseline Injection Modeling, March 7-8, 2012; 7) Permitting and Injection Status, March 7-8, 2012; 8) Southern Company/MHI Ltd. 500 TPD CCS Demonstration; 9) Advanced Monitoring Techniques, March 13, 2013; 10) SECARB Citronelle CO 2 Storage & MVA Status, March 13, 2013; 11) SECARB Plant Barry to Citronelle, March 13, 2013; 12) SECARB Awards Anthropogenic Test, March 4, 2014; 13) SECARB Anthropogenic Test Project Assessment, March 4-5, 2014; 14) Southern Company/MHI Ltd. 500 TPD CCS Demonstration; 15) Southern Company CCS R&D Plant Barry CCS Demo, March 12, 2015; and 16) SECARB Phase III Citronelle Project (Anthropogenic Test) in Alabama, March 12, 2015.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Front-End Engineering and Design: Project Tundra Carbon Capture System (Final Report)

As the next phase of Project Tundra, Minnkota Power Cooperative (MPC) completed a front-end engineering and design (FEED) study to install a post-combustion CO 2 capture system (CCS) at the MPC operated (Square Butte Electric Cooperative-owned) Milton R. Young Station (MRYS) Unit 2 (MRY2), a 477-MW power plant fueled by North Dakota lignite. The project team completed the FEED with Fluor’s Econamine FG Plus℠ (EFG+) technology and is taking the next steps leading up to start of construction. Team members included FEED technical lead Fluor Enterprises (Fluor); owner’s engineer and balance of plant (BOP) engineer Burns & McDonnell (BMcD); leading carbon capture consultants (David Greeson Consulting, Hunt International Energy Services); environmental consultants (AECOM, Agora Environmental), other BOP engineering consultants (Golder Associates, Nels); cost-share funding agency, the North Dakota Industrial Commission (NDIC); and the Energy & Environmental Research Center (EERC). Project Tundra’s goal is to implement carbon capture, utilization, and storage (CCUS) in North Dakota, while preserving the use of lignite. Future options could lead to revitalizing legacy oil fields and creating a new CO 2 enhanced oil recovery (EOR) industry. The topic of this report is the FEED study for the carbon dioxide capture portion of Project Tundra. Building on the findings of a pre-FEED study for MRY2, the key deliverables contained in this FEED study are: a) design, costing, and performance data needed to commence project financing activities; b) engineering and material balances required to file for all project permits; and c) a final project schedule. Based on the results of the previous pre-FEED study, MPC and its team evaluated two options to provide the large amount of steam needed to operate the CCS: 1) installation of new natural gas package boilers and a new pipeline to supply natural gas to the facility and 2) extraction of steam from the existing MRYS steam turbine generator. The FEED study was performed using the package boilers option, as it was deemed to have the lowest technical risk, overall cost, and cost uncertainty. A key feature of the design, however, was the mixing the natural gas boilers’ flue gas with the MRY2 flue gas. This increased the size of the CCS system. This design also enabled the tie-in of Unit 1 flue gas for times when Unit 2 is offline. The CCS was designed to capture a combined 12,978 short tons per day (STPD) of CO 2 from the flue gases produced by the existing MRY Unit 2 along with flue gas produced by the new boiler package within the CCS. The 12,978 STPD CO 2 capture is achieved by normally processing 100% of the total available MRY Unit 2 flue gas (considering full load operation) and 100% of the boiler package flue gas, then removing 90% of the CO 2 available from the processed flue gas streams.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Retrofittable Advanced Combined Cycle Integration for Flexible Decarbonized Generation

This is the final scientific / technical report for Front End Engineering Design (FEED) study “Retrofittable Advanced Combined Cycle Integration for Flexible Decarbonized Generation” funded by the US Department of Energy (DOE), Office of Fossil Energy and Carbon Management (FECM), Carbon Capture R&D Program under award DE-FE0032131. The prime recipient is General Electric Company working through its Gas Power division (GEGP) with subrecipients Southern Company and Linde Engineering plus subcontractor Kiewit. Southern Company’s Plant Barry, a 2x1 7F.04 CCGT, is the host site. GEGP led the overall integration of the carbon capture system (CCS) with the existing natural gas combined cycle (NGCC) facility. Linde provided the detailed process engineering and equipment costing for the carbon capture island. Kiewit focused on plant layout, constructability, and installation. With the FEED study finished, the engineering is approximately 50% complete towards the detailed design package needed to proceed to procure, install, build, commission, and operate the integrated NGCC+CCS facility. This FEED study focuses on retrofitting a 95% CO 2 capture system with attention on plant integration. The study was particularly challenging due to unique and substantial cost impacts related to global sourcing challenges associated with COVID. Additional incentives, regulatory support, and dispatch certainty are needed to move forward with implementing CCS at this or other sites in the US. This FEED study highlights the value of integrating NGCC+CCS and is a template for future CCS retrofit studies.

42 ENGINEERING↗
DOE OSTI2025

CO 2 Transport Infrastructure Outlook in the United States

Carbon capture and storage (CCS) represents one of the most important methods to mitigate anthropogenic carbon emissions at a large scale, playing a key role in meeting climate change targets (Bui et al., 2018) and for net-zero CO 2 by 2050 scenarios in the United States (Browning et al., 2023). This technology involves capturing CO 2 emissions from industrial processes, transporting them via pipelines, trucks, rails, or ships, and ultimately storing them in underground geological sites, such as saline aquifers or depleted oil reservoirs. Thus, to encourage carbon reduction initiatives, the U.S. Congress enacted the Bipartisan Budget Act in 2018, reforming the 45Q tax credit to benefit operators storing CO 2 in geologic formations (Jones and Sherlock, 2021). Additionally, the 2022 Inflation Reduction Act further expanded these incentives, providing additional support for CCS initiatives (Hackett and Kuehn, 2023). Although numerous studies describe the importance of optimal CO 2 transportation to support the decision-making of CCS projects aligned with the objective of net-zero emissions by 2050 (Abramson and Christensen, 2021; Chen and Pawar, 2023; Greig and Pascale, 2021), further efforts are required to optimize the transport infrastructure for national-scale CCS deployment. Therefore, in this study, we examine three nationwide scenarios with the SimCCS 3.0 tool (Ma et al., 2022, 2023, 2024) along with a novel geospatial splitting approach developed by Velasco-Lozano et al. (Velasco- Lozano et al., 2024a, 2024b). We present optimized pipeline networks that meet the dynamic evolution of annual capture amounts, describing the required total pipeline lengths at each stage as a function of the pipeline diameters. Thus, the cases presented demonstrate the feasibility of CO 2 pipeline infrastructure for large-scale CCS projects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Alabama Carbon Storage: Bringing Data to the People

The Gulf Coastal Plain of Alabama has proven potential for geologic carbon storage and current interest in the area for large carbon capture and storage (CCS) projects is high. Extensive CCS relevant data exist in the records of the Geological Survey of Alabama and State Oil and Gas Board of Alabama, however, most of this data is not publicly available or is scattered in separate databases, file cabinets, and tables in publications. The “Alabama Carbon Storage: Data Sharing and Engagement” (ACS-DSE) project seeks to accelerate the responsible development of large CCS projects in the Gulf Coastal Plain of Alabama and offshore in state waters through a publicly accessible database of geologic carbon storage models and data across the region. The ACS-DSE draws on the over 150 years of geologic research and over 20 years of experience in CCS research to place relevant geologic, geophysical, and infrastructure data on a single web platform. Datasets available will include formation depths and elevations, geologic structures, reservoir properties, digital well logs (LAS files), existing penetrations, and geologic models. In addition to downloadable datasets, links to CCS related regulatory agencies and other sources of information will be included (for example, Class VI UIC permitting regulations and pipeline regulations). By making these datasets and models available in commonly used formats on a public website, the project will increase transparency in decision making and decrease the data acquisition time for industry.

01 COAL, LIGNITE, AND PEAT↗