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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Wabash CarbonSAFE Static and Dynamic Modeling: Task 9.0 (Technical Report)

The objective of the Wabash CarbonSAFE project’s static and dynamic modeling task is to assess the feasibility of storing 50 million tonnes (1.67 million metric tonnes annually; MMTA) of industrially-sourced carbon dioxide (CO 2 ) in a commercial-scale geological storage complex at Wabash Valley Resources LLC (WVR) gasification facility near Terre Haute, Indiana over a period of 30 years. The targeted formations for storing CO 2 are: 1) Mt. Simon Sandstone (MSS) and the 2) Potosi Dolomite (Knox Group). All of the available data from the recently drilled Wabash #1 stratigraphic test well (now plugged and abandoned) were used in the construction of both the static and dynamic models. Geologic models were constructed to characterize both the Mt. Simon Sandstone and Potosi Dolomite storage complexes. Dynamic simulation models were constructed and used to assess the feasibility of injecting CO 2 into the Mt. Simon and Potosi formations. The geocellular models for the Potosi Dolomite and Mt. Simon Sandstone were built using Petrel™, Schlumberger’s reservoir modeling software. The dynamic simulations were run using Landmark’s Nexus ® reservoir simulation software.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Initial Engineering and Design for CO 2 Capture from Ethanol Facilities

The Energy & Environmental Research Center, in partnership with the U.S. Department of Energy (DOE) and North Dakota ethanol producer Red Trail Energy, LLC (RTE) and with technical support from Trimeric Corporation and the KLJ engineering firm, completed an initial engineering design (IED) for a hybrid capture system to estimate associated costs for retrofitting the operational RTE ethanol plant. The project goal supports the DOE objective to achieve negative emissions using commercially available technologies to attain Technology Readiness Level 6+ from a facility emitting >100,000 tonnes of carbon dioxide (CO 2 ) annually. The RTE CCS (carbon capture and storage) Project is currently operating a CO 2 capture facility, adjacent to the RTE ethanol facility in western North Dakota, and injecting the CO 2 more than a mile below RTE property for permanent storage. This novel hybrid capture system would process about 310,000 tonnes of CO 2 annually for the RTE host site and includes CO 2 capture and compression from bioprocessing as well as capturing CO 2 produced from natural gas boilers. The bioprocessing capture process, based on past RTE studies investigating ammonia liquefaction technology with CO 2 produced from natural gas boilers captured utilizing chemical absorption with amine, was shown to be technically feasible for the RTE site. Activities conducted to support the project goal included 1) designing a hybrid capture system using CO 2 emissions from both bioprocessing and heat production at the host site facility; 2) conducting a pre-front-end engineering and design analysis of the hybrid capture system to include environmental health and safety, a constructability report, identification of permits, and corporate approvals; and 3) performing a techno-economic assessment in accordance with DOE’s methodology, as demonstrated by the bituminous baseline study. In addition, a life cycle assessment (LCA) was completed for the RTE site to estimate the carbon life cycle for ethanol-CCS implementation using the designed hybrid capture system to determine potential for net-negative carbon emissions. Results of the IED showed the hybrid system to be technically viable, with a moderate estimated cost of $55/tonne CO 2 captured for the hybrid system. The cradle-to-gate LCA showed preliminary net-negative carbon emissions potential anticipated from implementing a hybrid CCS system at a commercial scale. Recommended next steps toward potential implementation include hybrid capture system demonstration testing for detailed engineering and LCA model comparisons with low-carbon fuel incentive programs for financial support.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Sustainable Aviation Fuels from 30,000 feet – Scoping Report

A literature review, first principles analysis, and mapping of the airline-fuel infrastructure were performed to reassess the potential for various means of realizing a sustainable aviation sector. The literature review found a plethora of technical methods to make the airline industry net-zero CO 2 but limited work on the emergent barriers to sustainable aviation implementation such as land use, repurposing of fuel refining assets, and airline cost structures. First principles analyses of the energy, land, and costs of three broad net-zero strategies were performed to determine if sustainable aviation is feasible even in the most optimistic scenarios. Those methods were biomass-derived sustainable aviation fuel (SAF), fuel produced from CO 2 captured from the air and H 2 produced from water electrolysis (air-to-fuel: ATF), and offsetting fossil-derived Jet Fuel with carbon dioxide removal from the atmosphere (direct air capture and storage: DACS). Offsetting CO 2 emissions from using fossil Jet Fuel with DACS was found to consume the least energy, require the smallest quantity of land, and be the cheapest option. Replacing Jet Fuel with SAF was found to be only slightly more expensive than DACS but require substantially more land. ATF was found to be the most expensive and energy intensive option, though it did spare land relative to SAF. We found that calls to utilize waste biomass are well-founded, but wastes alone cannot cover the needs of the global airline industry. This means additional land will need to be allocated for biomass cultivation if SAF becomes the primary pathway to sustainable aviation. While differences were found in the performance of different types of biomass, those differences were small relative to differences with ATF and DACS. An analysis of the pricing structure of the airline industry suggests that some of the cost advantage of DACS may be erased by consumer sentiment which could explain why, to-date, the airline industry is focused primarily on SAF and to a lesser extent ATF. Further work is required to estimate the transportation, capital cost, and financing cost implications of greenfield and brownfield sites for SAF, DACS, and ATF. In the final report, we will analyze the potential to retrofit corn ethanol facilities to operate the ethanol-to-jet fuel process in response to decreasing gasoline demand as the electrification of road transport progresses. We will also construct a prioritization of land use to determine whether each net-zero CO 2 aviation pathway can make claim to the land required by their technology.

09 BIOMASS FUELS↗
DOE OSTI2024

Carbon neutrality in Malaysia and Kuala Lumpur: Insights from stakeholder-driven integrated assessment modeling

Several cities in Malaysia have established plans to reduce their CO2 emissions, in addition to Malaysia submitting a Nationally Determined Contribution to reduce its carbon intensity (against GDP) by 45% in 2030 compared to 2005. Meeting these emissions reduction goals will require a joint effort between governments, industries, and corporations at different scales and across sectors. In collaboration with national and sub-national stakeholders, we developed and used a global integrated assessment model to explore emissions mitigation pathways in Malaysia and Kuala Lumpur. Guided by current climate action plans, we created a suite of scenarios to reflect uncertainties in policy ambition, level of adoption, and implementation for reaching carbon neutrality. Through iterative engagement with all parties, we refined the scenarios and focus of the analysis to best meet the stakeholders’ needs. We found that Malaysia can reduce its carbon intensity and reach carbon neutrality by 2050, and that action in Kuala Lumpur can play a significant role. Decarbonization of the power sector paired with extensive electrification, energy efficiency improvements in buildings, transportation, and industry, and the use of advanced technologies such as hydrogen and carbon capture and storage will be major drivers to mitigate emissions, with carbon dioxide removal strategies being key to eliminate residual emissions. This study highlights the participatory process in which stakeholders contributed to the development of the model and guided the analysis, as well as insights into Malaysia’s decarbonization potential and the role of multilevel governance.

cities↗
DOE OSTI2021

Decarbonization of Residential Building Energy Supply: Impact of Cogeneration System Performance on Energy, Environment, and Economics

Electrical and thermal loads of residential buildings present a unique opportunity for onsite power generation, and concomitant thermal energy generation, storage, and utilization, to decrease primary energy consumption and carbon dioxide intensity. This approach also improves resiliency and ability to address peak load burden effectively. Demand response programs and grid-interactive buildings are also essential to meet the energy needs of the 21st century while addressing climate impact. Given the significance of the scale of building energy consumption, this study investigates how cogeneration systems influence the primary energy consumption and carbon footprint in residential buildings. The impact of onsite power generation capacity, its electrical and thermal efficiency, and its cost, on total primary energy consumption, equivalent carbon dioxide emissions, operating expenditure, and, most importantly, thermal and electrical energy balance, is presented. The conditions at which a cogeneration approach loses its advantage as an energy efficient residential resource are identified as a function of electrical grid’s carbon footprint and primary energy efficiency. Compared to a heat pump heating system with a coefficient of performance (COP) of three, a 0.5 kW cogeneration system with 40% electrical efficiency is shown to lose its environmental benefit if the electrical grid’s carbon dioxide intensity falls below 0.4 kg CO 2 per kWh electricity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Reservoir Simulations and Accuracy Measures for CO 2 and Pressure Plumes for the Broom Creek Formation in Central North Dakota

Conference paper presented at 17th International Conference on Greenhouse Gas Control Technologies (GHGT-17), Calgary, Alberta, Canada, October 20–24, 2024. This study estimated the accuracy of the predicted 5-year carbon dioxide (CO 2 ) and pressure plumes for a hypothetical geological storage project injecting CO 2 into the Broom Creek Formation near central North Dakota.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

SUBTASK 1.6 – BASIN ELECTRIC CARBON STORAGE RESEARCH PROJECT: NOVEL MONITORING TECHNIQUES

The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.

42 ENGINEERING↗
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 OSTI2023

A Deep Learning-Based Workflow for Fast Prediction of 3D State Variables in Geological Carbon Storage: A Dimension Reduction Approach

In this study, we used deep learning techniques, which are a form of artificial intelligence, to create fast and effective models for predicting how fluids flow in underground geological formations. This is important for managing geological carbon storage, a method used to fight climate change by storing carbon dioxide underground. The challenge lies in the complex nature of these underground spaces and the large amount of data needed to accurately simulate them. To overcome these issues, we developed a new workflow that reduces the data’s complexity before training the deep learning model and then reconstructs the predicted results in their original form. We also proposed a unique approach to handle the specific complexities found in 3D saturation fields, a crucial aspect of fluid flow prediction. We tested our method using real-world data from the Gulf of Mexico. Our results show that our approach not only accurately predicts fluid behavior but also significantly reduces computation time. This will greatly improve real-time decision-making and risk assessment in large-scale geological carbon storage operations.

Wang, Hongsheng↗
DOE OSTI2024

FECM/NETL CO 2 Saline Storage Cost Model (2024): User’s Manual

The U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM), in collaboration with the National Energy Technology Laboratory (NETL), has developed the FECM/NETL CO 2 Saline Storage Cost Model (CO2_S_COM). This Excel-based tool provides a comprehensive framework for estimating the costs and breakeven prices associated with storing carbon dioxide (CO 2 ) in deep saline formations. Designed from the perspective of a CO 2 storage site owner, the CO2_S_COM incorporates four integrated modules—project management, financial analysis, activity cost estimation, and geological evaluation—to deliver fast, robust, and actionable insights for evaluating project finances. This is the user's manual for CO2_S_COM. The model may be accessed at this link: FECM/NETL CO2 Saline Storage Cost Model CO2_S_COM 2024 (v4) - Submissions - EDX

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

NRAP-Open-IAM: FutureGen2 Component Models

This report describes the development and testing of three component models for NRAP-Open-IAM, the National Risk Assessment Partnership’s open-source integrated assessment model. The FutureGen2 Lookup Table Reservoir component model is based on interpolation of data from a set of lookup tables. The lookup tables contain pressures and saturations predicted by multiphase flow simulations performed with a reservoir simulator. The FutureGen2 Above Zone Monitoring Interval (AZMI) component is a surrogate model that can be used to estimate the impact that carbon dioxide (CO 2 ) and brine leaks from the CO 2 storage reservoir at the FutureGen 2.0 site might have had on overlying aquifers or monitoring units were a leak to occur. The model estimates the size of “impact plumes” according to five metrics: pH, Total Dissolved Solids (TDS), pressure, dissolved CO 2 and temperature. The FutureGen2 Aquifer component is similar, but is limited to four metrics: pH, Total Dissolved Solids (TDS), pressure, and dissolved CO 2 . The input parameters for each model are the same, but the Aquifer component is applicable to depths between 100 m and 700 m and the AZMI component is applicable from depths between 700 m and 1050 m.

42 ENGINEERING↗
DOE OSTI2022

Autonomous measurements of carbon dioxide uptake in a blue carbon habitat

A better understanding of carbon cycling dynamics in coastal ecosystems is critical to quantify “blue carbon” storage. However, obtaining the necessary measurements is complicated due to the dynamic conditions that characterize these ecosystems, and requires both spatially and temporally resolved measurements of carbon dioxide concentrations and complementary water quality parameters. In this study, we evaluate the use of a utility-class autonomous surface vehicle as a platform for measuring carbon dioxide dynamics in a shallow, intertidal, blue carbon ecosystem. We integrated a carbon dioxide sensor, a water quality sonde, and hydroacoustic sensors with an autonomous surface vehicle and performed measurements in and around a meadow of Zostera marina eelgrass. Results demonstrate the utility of this system to provide insight into complex carbon cycling dynamics in and around a shallow, intertidal blue carbon habitat.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

An assessment of ocean alkalinity enhancement using aqueous hydroxides: kinetics, efficiency, and precipitation thresholds

Abstract. Ocean alkalinity enhancement (OAE) is a promising approach to marine carbon dioxide removal (mCDR) that leverages the large surface area and carbon storage capacity of the oceans to sequester atmospheric CO2 as dissolved bicarbonate (HCO3-). One OAE method involves the conversion of salt in seawater into aqueous alkalinity (NaOH), which is returned to the ocean. The resulting increase in seawater pH and alkalinity causes a shift in dissolved inorganic carbon (DIC) speciation toward carbonate and a decrease in the surface ocean pCO2. The shift in the pCO2 results in enhanced uptake of atmospheric CO2 by the seawater due to gas exchange. In this study, we systematically test the efficiency of CO2 uptake in seawater treated with NaOH at aquarium (15 L) and tank (6000 L) scales to establish operational boundaries for safety and efficiency in advance of scaling up to field experiments. CO2 equilibration occurred on the order of weeks to months, depending on circulation, air forcing, and air bubbling conditions within the test tanks. An increase of ∼0.7–0.9 mol DIC per mol added alkalinity (in the form of NaOH) was observed through analysis of seawater bottle samples and pH sensor data, consistent with the value expected given the values of the carbonate system equilibrium calculations for the range of salinities and temperatures tested. Mineral precipitation occurred when the bulk seawater pH exceeded 10.0 and Ωaragonite exceeded 30.0. This precipitation was dominated by Mg(OH)2 over hours to 1 d before shifting to CaCO3,aragonite precipitation. These data, combined with models of the dilution and advection of alkaline plumes, will allow the estimation of the amount of carbon dioxide removal expected from OAE pilot studies. Future experiments should better approximate field conditions including sediment interactions, biological activity, ocean circulation, air–sea gas exchange rates, and mixing zone dynamics.

Ringham, Mallory C. (ORCID:0000000348020185)↗
DOE OSTI2026

Prairie State Generating Company Static and Dynamic Modeling

A reservoir modeling study was conducted to assess the feasibility of storing 162.5 million tonnes (8.125 million tonnes annually) of industrially sourced carbon dioxide (CO 2 ) in the St. Peter – Everton and Knox storage complexes at the Prairie State Generating Company’s (PSGC) site near Marissa, Washington County, Illinois (PSGC site). Two separate models were constructed for the St. Peter – Everton and the Knox storage complexes. The St. Peter and Everton sandstones are the target storage units for the St. Peter – Everton storage complex. The Knox Group formations are the target storage units for the Knox storage complex. The Maquoketa Shale is the primary confining unit for both storage complexes. The static reservoir models used as input to the dynamic reservoir models of the storage complexes were developed from interpretations of logs (e.g., gamma ray, resistivity, porosity, photoelectric, and sonic), structure surfaces using data from 36 wells, thickness maps, well test data, seismic data, and permeability data in PetrelTM.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Jackson, L., Johnson, M.B., Latrach, A., Grimes, D., Martinez, C., and Mclaughlin, J.F., 2024, Multidisciplinary geotechnical data collection, curation, and analysis for conformity with the regulatory framework for geologic carbon storage in Wyoming, USA: Geological Society of America Abstracts with Programs. Vol. 56, No. 5, 2024, doi: 10.1130/abs/2024AM-405024

Title: Multidisciplinary Geotechnical Data Collection, Curation, and Analysis for Conformity with the Regulatory Framework for Geologic Carbon Storage in Wyoming, USA. Text: Construction and operation of wells for geologic sequestration of carbon dioxide necessitate that they are permitted under the Environmental Protection Agency’s Underground Injection Control Class VI requirements. Class VI wells conform to stringent requirements to ensure long-term safety and integrity of the storage site and the protection of Underground Sources of Drinking Water. Entities pursuing Class VI permitting must provide comprehensive geologic site characterization, including regional geologic structure and stratigraphy, aquifer information, reservoir and confining unit geomechanical properties, geochemical analyses, assessment of trapping capacity and mechanisms, and a variety of other of multidisciplinary geotechnical data. The Wyoming Class VI Site Characterization Database Project is focused on developing a geologic site characterization database of geotechnical information, which has been compiled and verified from established, public databases/entities and scientific literature to expedite Class VI permitting in Sweetwater County within the Greater Green River Basin of southern Wyoming. The preliminary suite of compiled data from 14,000 wells includes 8,000 wells with logs and 7,250 wells with formation tops, ~70 wells with core data (e.g., X-Ray diffraction, petrographic, and petrophysical data), ~2,500 water analyses, ~740 seismic events data, and ~520 bottom-hole temperature measurements. Future work on—and stemming from—this project will include new core analyses, calculation and interpolation of subsurface temperature gradients, mechanical earth models, geochemical simulations, storage capacity estimation, stratigraphic column generation and correlation, and construction of subsurface maps. Finally, this work will help to inspire and facilitate subsurface data compilation and curation beyond Sweetwater County, Wyoming.

42 ENGINEERING↗
DOE OSTI2025

Quantifying Climate Change Effects of Bioenergy and BECCS: Critical Considerations and Guidance on Methodology

Bioenergy is a critical element in many national and international climate change mitigation efforts, including as a carbon dioxide removal strategy combined with the capture and durable geological storage of flue gas emissions (BECCS). However, divergent results on the effectiveness of bioenergy as a climate change mitigation measure are reported in the scientific literature. Climate impacts of bioenergy depend on case-specific factors, primarily biophysical features of the biomass production system, and the design and efficiency of conversion and capture processes. Estimates of climate impacts are also strongly affected by methodological choices and assumptions, and much of the divergence between studies derives from differences in the assumed alternate use of the land or feedstock, the alternate energy source and the system boundaries applied. We present a methodology to support robust estimates of the climate change effects of bioenergy systems, updating the standard methodology developed by the International Energy Agency's Technology Collaboration Program on Bioenergy. We provide guidance on the key choices including the reference land use and energy system that bioenergy is assumed to displace, spatial and temporal system boundaries, co-product handling, climate forcers considered, metrics applied and time horizon of impact assessment. Researchers should consider the whole bioenergy system including all life cycle stages, and choose system boundaries, reference systems and treatment of co-products that are consistent with the intended application of the results. The assessment should be normalised to a functional unit that can be compared with other systems delivering an equivalent quantity of the same function. All significant climate forcers should be included, and climate effects should be quantified using appropriate impact assessment methods that distinguish the impact of time. Consistency in methodology and interpretation will facilitate comparison between studies of different bioenergy systems.

09 BIOMASS FUELS↗
DOE OSTI2021

CO 2 electro-reduction on Cu 3 P: Role of Cu(I) oxidation state and surface facet structure in C 1 -formate production and H 2 selectivity

We report the catalytic activity and mechanism of copper(I) phosphide, Cu 3 P, with predominant [00Ι] facet exposure for the electrochemical reduction of CO 2 (CO 2 RR) to formic acid. Crystalline nanosheets of this compound that show a preferential [00Ι] facet orientation exhibit undiminished CO 2 RR activity after 16 hours with full retention of crystal structure and surface chemical speciation and no detectable corrosion. In contrast to the range of products formed on Cu metal, CuO, and Cu 2 O, the CO 2 RR on Cu 3 P [00Ι] produces mainly hydrogen and formate as the sole carbon product in KHCO 3 electrolyte. Analysis of the Cu 3 P [00Ι] facet by HAADF-STEM was used to determine the surface lattice structure, while both XPS and Auger spectroscopies were used to determine the surface chemical speciation from the kinetic energies of ionized electrons. The presented analysis identifies isolated trigonal CuP 3 sites on the Cu 3 P[00Ι]-Cu 3 P 3 terminated surface and the Cu(I) oxidation state as precursor to the active catalyst. The CO 2 RR selectivity to formate and the higher turnover rate for H 2 production on the [00Ι] facet allows a structure-activity analysis and chemical mechanism to be proposed. Formation of a surface hydride at isolated *H-CuP 3 sites is proposed as the catalytic site in forming both H 2 and formate, while the long Cu—Cu separation retards forming C-C coupling products. In conclusion, these results disprove previously published claims of Cu(I) oxidation state as a sufficient criterion to promote CO 2 RR to C 2+ products, show that stronger bonded hydrides, *H-CuP 3 on Cu 3 P, favor production of the C1 product formate over all other carbon products, and predict that stronger formate binding (bidentate) is needed for CO 2 RR currents to compete with H 2 production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Catalytic Reduction of Residual Oxygen for the Purification of Carbon Dioxide Streams from Pressurized Oxy-Combustors

Pressurized oxy-combustion (OC) is regarded as an energy-efficient alternative to atmospheric OC. To utilize the captured carbon dioxide (CO2) from pressurized OC for enhanced oil recovery or carbon storage in geological formations, the CO2 product stream must meet the required purity specifications. One major impurity in OC flue gases is residual O2 (e.g., 3 vol%). In this study, a catalytic approach has been investigated to remove the residual O2 through a reduction reaction with injected methane (CH4) in a reverse-flow fixed-bed (RFFB) reactor. The performance was tested for a supported copper (Cu)-based catalyst synthesized by incipient wetness impregnation and a cobalt-manganese (CoMn) oxide catalyst synthesized by a coprecipitation method. A commercial Cu-based catalyst was also studied as the reference. Experimental results revealed that under the reverse-flow operation, the temperature profiles in the reactor were symmetrical on both sides of the catalyst zone and were more homogenous than those under the conventional one-direction-flow operation. Among the tested catalysts, the CoMn catalyst was the most reactive for promoting the reduction of O2 with CH4, able to attain >95% O2 removal at 475 °C and a gas hourly space velocity (GHSV) of 18,000 h-1 with a feed gas containing 3 vol% O2. Under all experiments, the concentrations of carbon monoxide (CO) were lower than 30 ppmv in the effluent gas streams. The reaction between O2 and CH4 could be depicted by using the Mars–van Krevelen redox mechanism based on a two-step reduction–oxidation reaction pathway.

36 MATERIALS SCIENCE↗