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DOE OSTI2024

Life Cycle Greenhouse Gas Emissions of Coal-Biomass Co-Firing Power Plants with Carbon Capture and Storage

The United States has set a target to achieve the net-zero economy by 2050. Bioenergy with Carbon Capture and Sequestration (BECCS) is one of the promising negative-emission routes in the mitigation portfolio to help meet this goal. Coal-biomass co-firing with carbon capture and storage (CCS) is a key BECCS technology to realize the carbon mitigation at fossil-fuel power plants. The mitigation potential of co-firing option is affected by numerous critical factors, such as biomass properties, co-firing level, and carbon capture rate. The objectives of the study are to characterize and estimate the life cycle greenhouse gas (GHG) emissions and performance of coal-biomass co-firing power plants with CCS, determine the breakeven co-firing level at power plants necessary to achieve net-zero life cycle emissions, and quantify the variabilities and uncertainties in life cycle emissions. The scope of the life cycle assessment includes the fuel supply, combustion-based power generation, and CO2 transport and storage. A fuel-based life cycle module is developed and embedded in the Integrated Environmental Control Model (IECM), a fossil-fuel power plant modeling tool. This study then applies the enhanced IECM to conduct the process-based life cycle assessment for an array of biomass co-firing scenarios. Deterministic analysis indicates that reaching net-zero life cycle emissions in a biomass co-firing plant without CCS deployment is challenging. Combining biomass co-firing and CCS deployment can significantly lower the overall life cycle emissions of power plants. Net-zero life cycle emissions can be achieved with a 20 wt.% co-firing level and 90% CCS when the Powder River Basin coal is co-fired with energy crops or forestry residues. However, the breakeven co-firing level for net-zero emissions depend on the selected fuel properties. Fuel supply and plant operation are the critical stages influencing the life cycle emissions of power plants with 90% CCS. Deployment of deep CCS beyond 90% CO2 capture can remarkably reduce operational emissions and the breakeven co-firing level. With 99% CCS, the breakeven co-firing rate can be reduced to 12% on average. These findings highlight the trade-offs between technical performance and environmental impact of biomass co-firing at coal-fired power plants and emphasize the role of deep CCS in achieving a net-zero emissions future.

Wu, Wanying↗

NASA NTRS2014

The Effect of Aqueous Alteration in Antarctic Carbonaceous Chondrites from Comparative ICP-MS Bulk Chemistry

Terrestrial ages of Antarctic carbonaceous chondrites (CC) indicate that these meteorites have been preserved in or on ice for, at least, tens of thousands of years. Due to the porous structure of these chondrites formed by the aggregation of silicate-rich chondrules, refractory inclusions, metal grains, and fine-grained matrix materials, the effect of pervasive terrestrial water is relevant. Our community defends that pristine CC matrices are representing samples of scarcely processed protoplanetary disk materials as they contain stellar grains, but they might also trace parent body processes. It is important to study the effects of terrestrial aqueous alteration in promoting bulk chemistry changes, and creating distinctive alteration minerals. Particularly because it is thought that aqueous alteration has particularly played a key role in some CC groups in modifying primordial bulk chemistry, and homogenizing the isotopic content of fine-grained matrix materials. Fortunately, the mineralogy produced by parent-body and terrestrial aqueous alteration processes is distinctive. With the goal to learn more about terrestrial alteration in Antarctica we are obtaining reflectance spectra of CCs, but also performing ICP-MS bulk chemistry of the different CC groups. A direct comparison with the mean bulk elemental composition of recovered falls might inform us on the effects of terrestrial alteration in finds. With such a goal, in the current work we have analyzed some members representative of CO and CM chondrite groups.

Alonso-Azcarate, J.↗

NASA NTRS2015

Effects of Acute Stress on Aircrew Performance: Literature Review and Analysis of Operational Aspects

Situational stress can adversely affect the cognition and skilled performance of pilots, as well as experts in other domains. Emergencies and other threatening situations require pilots to execute infrequently practiced procedures correctly and to use their skills and judgment to select an appropriate course of action, often under high workload, time pressure, and ambiguous indications, all of which can be stressful. Our current study, consited of three parts, starting with a critical review of the research literature on the effects of stress on skilled performance, going back to World War II and continuing to recent and more sophisticated studies of the cognitive effects of anxiety. In the second part we analyzed the specific ways stress may have impaired the performance of airline crews in twelve major accidents, selected for diversity of the situations the crews encountered. The third part examined the operational significance and practical implications of the findings from the first two parts, suggested specific ways to reduce the harmful effects of stress on flight crews, and identified aspects requiring further research. Even thought this study focused on flight crews, the findings apply to the effects of stress on the skilled performance of experts in almost any domain.

stress↗

DOE OSTI2022

Interrogating organo-mineral interactions by Py-GC/MS and ToF-SIMS

Soil organic matter (SOM) is crucial to soil fertility and agricultural sustainability in the face of climate change, and organo-mineral interactions are a key mechanism for stabilizing SOM. The stability of mineral-associated organic matter (MAOM) can be approximated by the strength of bonds between biomolecules and mineral surfaces. We hypothesized that factors such as mineral reactivity and solution pH would impact bonding strength. To test these factors, sorption isotherms were performed on minerals differing in particle size, morphology, and reactivity (quartz, goethite, gibbsite, kaolinite, montmorillonite), under two pH conditions (4 and 6), and across a range of tannic acid concentration (0-1400 ppm). The quantity and quality of organo-mineral bonds was assessed by quantifying post-sorption solution compounds using an absorbance plate reader and assessing the thermal energy needed to break bonds using evolved gas analysis (EGA) on a pyrolysis gas chromatograph-mass spectrometer (Py-GC/MS). Organo-mineral surfaces were also interrogated using Time-of-flight secondary ion mass spectrometry (ToF-SIMS). Sorption experiments revealed an asymptotic relationship between sorbed tannic acid and increasing initial concentrations which suggests our concentration range saturated available mineral surfaces. Results indicated that mineral identity, chiefly surface area and native pH, impacted the amount of compound sorbed to mineral surfaces. Evolved gas analyses of organo-mineral samples uncovered increased thermal stability of sorbed compounds compared to our tannic acid standard particularly on the iron oxide, goethite. ToF-SIMS revealed that goethite surface ions were covered by increasing concentrations of adsorbed tannic acid with the replacement of chlorine and sulfate ions by tannic acid related ions. Our results indicate that Py-GC/MS and ToF-SIMS are useful techniques to determine the nature and strength of organo-mineral bonds and are steppingstones to understanding controls on carbon sequestration in terrestrial systems.

58 GEOSCIENCES↗

DOE OSTI2019

Wind direction estimation using SCADA data with consensus-based optimization

Abstract. Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. To enable cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving a more efficient wind farm is to develop algorithms that ensure reliable, robust, real-time, and efficient operation of wind turbines in a wind farm using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. This article presents a framework for developing a cooperative wind farm that incorporates information from nearby turbines in real time to better align turbines in a wind farm. SCADA data from multiple turbines can be used to make better estimates of the local inflow conditions at each individual turbine. By incorporating measurements from multiple nearby turbines, a more reliable estimate of the wind direction can be obtained at an individual turbine. The consensus-based approach presented in this paper uses information from nearby turbines to estimate wind direction in an iterative way rather than aggregating all the data in a wind farm at once. Results indicate that this estimate of the wind direction can be used to improve the turbine's knowledge of the wind direction. This estimated wind direction signal has implications for potentially decreasing dynamic yaw misalignment, decreasing the amount of time a turbine spends yawing due to a more reliable input to the yaw controller, increasing resiliency to faulty wind-vane measurements, and increasing the potential for wind farm control strategies such as wake steering.

17 WIND ENERGY↗

DOE OSTI2025

Physics-based hybrid machine learning for critical heat flux prediction with uncertainty quantification

Critical heat flux (CHF) is a key quantity in nuclear system modeling due to its impact on heat transfer, safety margins, and reactor performance. This study develops and validates an uncertainty-aware hybrid modeling approach that combines machine learning with physics-based models to predict CHF in cases of dryout. The Biasi and Bowring empirical correlations were paired with three ML uncertainty quantification (UQ) techniques: deep neural network (DNN) ensembles, Bayesian neural networks (BNNs), and deep Gaussian processes (DGPs). A pure ML model without a base model was evaluated for comparison. Model performance was assessed under plentiful (7,350 points) and limited (9 points) training data scenarios using parity, uncertainty distributions, and calibration curves. Results show that the Biasi hybrid DNN ensemble achieved the best overall performance, with a mean absolute relative error of 1.846%, and well-calibrated uncertainty estimates. The BNN-based hybrids showed slightly higher error (2.14%) but superior uncertainty calibration. DGP models underperformed, with over 6% error and poor uncertainty calibration. All hybrid models outperformed pure machine learning configurations, demonstrating resistance against data scarcity. These findings indicate that hybrid modeling significantly improves predictive accuracy, interpretability, and resilience to data scarcity. The integration of uncertainty awareness provides actionable confidence in CHF predictions, which is vital for safety-critical decisions in nuclear applications. This hybrid approach offers a viable pathway for deploying ML models in reactor analysis tools while preserving domain knowledge and physical consistency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Uncertainty in the response of sudden stratospheric warmings and stratosphere- troposphere coupling to quadrupled CO2 concentrations in CMIP6 models

Major sudden stratospheric warmings (SSWs), vortex formation and final breakdown dates are key highlight points of the stratospheric polar vortex. These phenomena are relevant for stratosphere-troposphere coupling, which explains the interest in understanding their future changes. However, up to now, there is not a clear consensus on which projected changes to the polar vortex are robust, particularly in the Northern Hemisphere, possibly due to short data record or relatively moderate CO2 forcing. The new simulations performed under the Coupled Model Intercomparison Project, Phase 6, together with the long daily data requirements of the DynVarMIP project in preindustrial and quadrupled CO2 (4xCO2 ) forcing simulations provide a new opportunity to revisit this topic by overcoming the limitations mentioned above. In this study, we analyze this new model output to document the change, if any, in the frequency of SSWs under 4xCO2 forcing. Our analysis reveals a large disagreement across the models as to the sign of this change, even though most models show a statistically significant change. The models, however, are in good agreement as to the impact of SSWs over the North Atlantic: there is no indication of a change under 4xCO2 forcing. Over the Pacific, however, the change is more uncertain. Finally, the models show robust changes to the seasonal cycle in the stratosphere. Specifically, we find a longer duration of the stratospheric polar vortex, and thus a longer season of stratosphere-troposphere coupling.

sudden stratospheric warmings (SSWs)↗

DOE OSTI2026

A low-latitude, high-elevation 10Be production-rate calibration from the Rwenzori Mountains, Uganda

Cosmogenic nuclide surface-exposure dating has become a key tool in geomorphology. Robust application of the technique relies on determination of local nuclide production rates using independently dated calibration sites. However, there are few existing calibration sites in certain regions, particularly in low-latitude, high-elevation regions where cosmogenic nuclide production is theoretically more sensitive to changes in Earth's magnetic field and atmospheric conditions. We present a new cosmogenic beryllium-10 (10Be) production-rate calibration from the equatorial Rwenzori Mountains in Uganda. The calibration is based on radiocarbon dating of basal lake sediments (∼21.3 kyr BP) from Lake Mahoma (2900 m asl) and measured 10Be concentrations from boulders on the crest of a moraine which dams the lake. Our results indicate a time-integrated 10Be production rate of 15.83 ± 0.81 at/g/yr at Lake Mahoma. We then use these calibration data and two public online calculators to calculate ages for moraines in a separate Rwenzori valley for which there exists a minimum-limiting radiocarbon age constraint (∼12 kyr BP) on surficial glacial sediments. This enables us to assess the performance of different parameters used to scale production rates spatially and temporally (e.g., scaling frameworks, geomagnetic field reconstructions, atmospheric models) for surface-exposure age calculation in the region. Our results highlight the sensitivity of low-latitude cosmogenic nuclide surface-exposure ages to discrete calculation parameters, such as scaling framework or reconstructions of Earth's magnetic field, and the utility of determining production rates at sites where limiting age data exists for other nearby landforms.

Anderson, N [Dartmouth College]↗

DOE OSTI2026

The Myth of Fungible FTE: A Quantitative Assessment of Matrixed Resource Allocation

Matrix organizations allow scientific facilities to share specialized personnel across projects, operations, maintenance, and strategic initiatives. Nominal staffing allocations, however, may not capture the schedule consequences of fragmented individual commitments, limited access to specialist groups, and intermittent availability of key decision makers. We developed a stochas- tic, daily-time-step simulation of a hypothetical medium-sized accelerator-facility project com- prising sequential phases and parallel tasks. Each task requires role-specific work measured in FTE-days. Ordinary personnel may be unavailable because they contribute concurrently to other institutional activities, while designated key roles have independently specified daily un- availability probabilities. An organization-wide priority factor scales the number of people from each functional group who can effectively contribute to the project. It is interpreted as a composite proxy for project access and workforce fragmentation across competing commit- ments. We examined project completion time as a function of this factor and Project Lead unavailability using 100 Monte Carlo runs per condition. Increasing priority factor from 0.1 to 1.0 reduced median completion time from 1708.5 days (interquartile range 1681.5–1735.25) to 390 days (interquartile range 379–399). At priority factor = 0.1, increasing Project Lead unavailability from 0.5 to 0.9 increased median completion time from 1713.5 days (interquartile range 1691–1733.25) to 4,417 days (interquartile range 4271.75–4550.5). The model quantifies the commonly expected sensitivity of project schedules to fragmented resource commitments and limited coordination availability. Within this model, the results also indicate a possible threshold regime in which small increases in workforce availability yield only modest sched- ule improvements until sufficient capacity becomes accessible, after which project performance improves sharply. With further validation and calibration, this quantitative framework could support resource-allocation decisions during initial project planning and subsequent schedule rebaselining.

Bai, Mei [SLAC National Accelerator Laboratory (SL↗

NASA NTRS2004

"GSFC FSB Application of Perspective-Based Inspections"

The scope of work described in our proposal consisted of developing inspection standards targeted to Branch-specific types of defects (gained from analysis of Branch project defect histories), and including Branch-relevant perspectives and questions to guide defect detection. The tailored inspection guidelines were to be applied on real Branch projects with support as needed from the technology infusion team. This still accurately describes the scope of work performed. It was originally proposed that the Perspective-Based inspection standard would be applied on three projects within the Branch: GPM, JWST, and SDO. Rather than apply the proposed standard to all three, we inserted a new step, in which the standard was instead applied on a single pilot project, cFE (described above). This decision was a good match for the Branch goals since, due to the "design for reuse" nature of cFE, inspections played an even more crucial than usual role in that development process. Also, since cFE is being designed to provide general-purpose functionality, key representatives fiom our target projects were involved in inspections of cFE to provide perspectives from different missions. In this way, they could get some exposure to and the chance to provide feedback on the proposed standards before applying them on their own projects. The Branch-baselined standards will still be applied on GPM, JWST, and SDO, although outside the time frame of this funding. Finally, we originally proposed using the analysis of Branch defect sources to indicate in which phases Perspective-Based inspections could provide the best potential for future improvement, although experience on previous Branch projects suggested that our efforts would likely be focused on requirements and code inspections. In the actual work, we focused exclusively on requirements inspections, as this was the highest-priority work currently being done on our cFE pilot project.

Shell, Elaine↗

DOE OSTI2025

Optimization of the light detection system of the ICARUS detector

The Short Baseline Neutrino (SBN) Program at Fermilab is designed to investigate short-baseline neutrino oscillations and test the hypothesis of sterile neutrinos, motivated by several experimental anomalies observed over the past decades. Within this program, the ICARUS experiment plays a key role. It employs the world’s largest Liquid Argon Time Projection Chamber (LArTPC) and serves as the farthest and most sensitive SBN detector for studying muon and electron neutrino oscillations. A crucial subsystem of the ICARUS detector is the Light Detection System (LDS), which captures the prompt scintillation light produced by neutrino interactions in the 600-ton active liquid Argon volume. This system provides precise timing information that is essential for event reconstruction, the trigger system, and cosmic background rejection. The LDS is composed of 360 Hamamatsu R5912-MOD 8-inch photomultiplier tubes (PMTs), operating under cryogenic conditions ($\sim 87 \ K$) inside the detector’s cryostats. During the detector’s operation at FNAL, a degradation in PMT gain has been observed, attributed to aging under low-temperature conditions. In collaboration with ICARUS teams from INFN Pavia and Catania, I developed an experimental setup to study the temperature-dependent behavior of the PMTs, performing gain measurements both at room temperature and down to $-70°C$ using a climatic chamber at INFN Catania. The results indicate that while the PMTs maintain stable gain at room temperature, a significant and permanent gain reduction occurs at low temperatures. Although $-70°C$ is still warmer than liquid Argon temperatures, the findings clearly demonstrate a gain-dependent performance degradation. The thesis also discusses mitigation strategies implemented in the ICARUS detector to address this issue and presents a simplified model to describe and simulate the observed behavior.

Saia, Clara [Catania U.] (ORCID:0009000464102417)↗

DOE OSTI2020

Integrated network modeling approach defines key metabolic responses of soil microbiomes to perturbations

The soil environment is constantly changing due to shifts in soil moisture, nutrient availability and other conditions. To contend with these changes, soil microorganisms have evolved a variety of ways to adapt to environmental perturbations, including regulation of gene expression. However, it is challenging to untangle the complex phenotypic response of the soil to environmental change, partly due to the absence of predictive modeling frameworks that can mechanistically link molecular-level changes in soil microorganisms to a community’s functional phenotypes (or metaphenome). Towards filling this gap, we performed a combined analysis of metabolic and gene co-expression networks to explore how the soil microbiome responded to changes in soil moisture and nutrient conditions and to determine which genes were expressed under a given condition. Our integrated modeling approach revealed previously unknown, but critically important aspects of the soil microbiomes’ response to environmental perturbations. Incorporation of metabolomic and transcriptomic data into metabolic reaction networks identified condition-specific signature genes that are uniquely associated with dry, wet, and glycine-amended conditions. A subsequent gene co-expression network analysis revealed that drought-associated genes occupied more central positions in a network model of the soil community, compared to the genes associated with wet, and glycine-amended conditions. These results indicate the occurrence of system-wide metabolic coordination when soil microbiomes cope with moisture or nutrient perturbations. Importantly, the approach that we demonstrate here to analyze large-scale multi-omics data from a natural soil environment is applicable to other microbiome systems for which multi-omics data are available.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Calibration, measurement, and characterization of soil moisture dynamics in a central Amazonian tropical forest

Soil moisture plays a key role in hydrological, biogeochemical, and energy budgets of terrestrial ecosystems. Accurate soil moisture measurements in remote ecosystems such as the Amazon are difficult and limited because of logistical constraints. Time domain reflectometry (TDR) sensors are widely used to monitor soil moisture and require calibration to convert the TDR's dielectric permittivity measurement (K a ) to volumetric water content (θ v ). In this study, our objectives were to develop a field-based calibration of TDR sensors in an old-growth upland forest in the central Amazon, to evaluate the performance of the calibration, and then to apply the calibration to determine the dynamics of soil moisture content within a 14.2 -m-deep vertical soil profile. Depth-specific TDR calibration using local soils in a controlled laboratory setting yielded a novel K a –θ v third-degree polynomial calibration. The sensors were later installed to their specific calibration depth in a 14.2-m pit. The widely used K a –θ v relationship (Topp model) underestimated the site-specific θ v by 22–42%, indicating significant error in the model when applied to these well-structured, clay-rich tropical forest soils. The calibrated wet- and dry-season θ v data showed a variety of depth and temporal variations highlighting the importance of soil textural differentiation, root uptake depths, as well as event to seasonal precipitation effects. Data such as these are greatly needed for improving our understanding of ecohydrological processes within tropical forests and for improving models of these systems in the face of changing environmental conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A hybrid Penman-Monteith and machine learning model for simulating evapotranspiration and its components

Integrating physical processes with machine learning has advanced evapotranspiration (ET) simulation, yet most hybrid models fail to partition total ET into its components: soil evaporation (E) and vegetation transpiration (T). This study introduces Residual Neural Network–Penman–Monteith (RNN-PM), a novel hybrid dual-source ET model designed to overcome this limitation. The model synergizes the physically-based Penman–Monteith framework with three specialized residual neural networks trained to estimate key conductance parameters (canopy conductance, soil surface conductance, and aerodynamic conductance). Furthermore this explicit parameterization allows for the direct partitioning of total ET. Validation at National Ecological Observatory Network (NEON) flux sites using high-frequency partitioned E and T shows that RNN-PM reliably reproduces ET and the transpiration fraction (T/ET). For ET, the model achieves an average Kling–Gupta efficiency (KGE) of 0.89 and a root-mean-square error (RMSE) of 0.55 mm/day; for T/ET, the KGE is 0.87 with an RMSE of 0.06. Furthermore, RNN-PM demonstrates robust generalization, accurately simulating ET and its components well beyond the initial training dataset, even under extreme climatic conditions. This study extended the analysis by comparing the RNN-PM model with seven established dual-source ET models. The results indicate that RNN-PM outperforms both conventional machine learning models and purely physical process-based models in simulating ET components in most cases. Among the purely physical process-based dual-source models, those based on surface temperature decomposition showed improved performance as the leaf area index (LAI) decreased when evaluated against high-frequency ET component datasets. In contrast, the performance of conductance-based dual-source models declined with decreasing LAI. Although purely machine learning-based models can produce relatively accurate simulations of ET components, they often exhibit limited generalization capability, an issue that the RNN-PM model effectively overcomes. Ultimately, the RNN-PM model represents a significant advance in simulating ET components, offering a novel and scalable approach for improving the representation of land–atmosphere interactions in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2015

Internal NASA Study: NASAs Protoflight Research Initiative

The NASA Protoflight Research Initiative is an internal NASA study conducted within the Office of the Chief Engineer to better understand the use of Protoflight within NASA. Extensive literature reviews and interviews with key NASA members with experience in both robotic and human spaceflight missions has resulted in three main conclusions and two observations. The first conclusion is that NASA's Protoflight method is not considered to be "prescriptive." The current policies and guidance allows each Program/Project to tailor the Protoflight approach to better meet their needs, goals and objectives. Second, Risk Management plays a key role in implementation of the Protoflight approach. Any deviations from full qualification will be based on the level of acceptable risk with guidance found in NPR 8705.4. Finally, over the past decade (2004 - 2014) only 6% of NASA's Protoflight missions and 6% of NASA's Full qualification missions experienced a publicly disclosed mission failure. In other words, the data indicates that the Protoflight approach, in and of it itself, does not increase the mission risk of in-flight failure. The first observation is that it would be beneficial to document the decision making process on the implementation and use of Protoflight. The second observation is that If a Project/Program chooses to use the Protoflight approach with relevant heritage, it is extremely important that the Program/Project Manager ensures that the current project's requirements falls within the heritage design, component, instrument and/or subsystem's requirements for both the planned and operational use, and that the documentation of the relevant heritage is comprehensive, sufficient and the decision well documented. To further benefit/inform this study, a recommendation to perform a deep dive into 30 missions with accessible data on their testing/verification methodology and decision process to research the differences between Protoflight and Full Qualification missions' Design Requirements and Verification & Validation (V&V) (without any impact or special request directly to the project).

Protoflight↗

DOE OSTI2019

Shale-fluid interactions during forced lmbibition and flow-back

One way to minimize the need for disposal of flow-back waters produced during the hydraulic fracturing of unconventional reservoirs is, potentially, to recycle these fluids by recovering and re-injecting them during hydraulic fracturing of nearby new wells. These flow-back waters contain, however, large concentrations of dissolved salts. During hydraulic fracturing of unconventional reservoirs, a well may undergo extended shut-in periods, following the initial hydraulic-fracture stimulation. The concern here, therefore, is that the salts dissolved in the re-injected flow-back waters may precipitate in the subsurface, thus promoting scale formation; or alternately, because of their high salinity, these same fluids may cause the dissolution of various minerals present in the subsurface. Large divalent cations (e.g., Ca²⁺, Ba²⁺ and Sr²⁺) and anions (e.g., CO3²⁻ and SO4²) may chemically interact with and cause the swelling of clay fractions, thus blocking pores in certain pore size ranges. All these phenomena (i.e., scale formation, clay swelling, minerals dissolution) can influence the petrophysical properties of the formation, including its permeability, porosity, contact angle, etc. One way to potentially overcome some of these technical challenges, is to pre-treat these flow-back waters, prior to re-injection (e.g., via chemical precipitation, followed by membrane filtration) in order to remove unwanted salts. However, such pre-treatment is costly, and the degree of salt removal needed to prevent formation damage is important in determining the economic viability of flow-back water recycle via re-injection. A key focus of this work, therefore, is to study the impact that the injection of flow-back waters, that have undergone varying degrees of pre-treatment and clean-up, will have on the flow-through characteristics of a tight-gas reservoir, particularly of the Marcellus Shale formation. To do so, we have carried-out forced-imbibition experiments with shale samples from various depths in the Marcellus formation, whose properties span high to low ranges of TOC, clay content and matrix permeabilities. We have studied the forced-imbibition characteristics, at an injection pressure of 24,233 kPa (3500 psig), of various flow-back fluids into shale cores saturated with methane at a pore pressure of 17,338 kPa (2500 psig) and a confining stress of 27,680 kPa (4000 psig). Following the forced imbibition experiments, we analyzed the cores for potential changes in permeability and porosity. Quantification of the ion content of the injected and recovered fluids was also performed using Ion Chromatography (IC). The IC analysis of the recovered fluids indicates substantial interactions and geochemical reactions between the invading fluids and the shale cores. The injection of flow-back fluids shows significant impact on the flow-through characteristics, with untreated flow-back fluids, which have the highest cation and anion content, also exhibiting the highest observable reductions in permeability (>90%).

defects, mechanical behavior, carbon sequestration↗

DOE OSTI2022

Land-Based Wind Market Report: 2022 Edition

The U.S. Department of Energy's 2022 edition of its Land-Based Wind Market Report provides an overview of key trends in the U.S. wind power market, with a focus on 2021. You can find a report, data file and presentation on the Files tab, below. Additionally, several data visualizations are available on the Visualizations tab. Despite ongoing supply chain challenges, wind energy in 2021 continued to see strong growth, technology improvements, and low prices in the U.S. Key highlights include: Wind comprises a growing share of electricity supply: U.S. wind power capacity grew at a strong pace in 2021, with the 13.4 GW of new additions representing a $\$20$ billion investment and 32% of all newly added U.S. generation capacity. Wind energy output rose to account for more than 9% of the entire nation’s electricity supply. At least 247 GW of wind are seeking transmission interconnection; 77 GW of this capacity are offshore wind and 19 GW are hybrid plants that pair wind with storage or solar PV. Wind project performance has increased over the decades: The average capacity factor among recently built projects was nearly 40%, considerably higher than projects built earlier. The highest capacity factors are seen in the interior ‘wind belt’ of the country. Turbines continue to get larger: Improved plant performance has been driven by larger turbines mounted on taller towers and featuring longer blades. In 2011, no turbines employed blades that were 115 meters in diameter or larger, but in 2021, 89% of newly installed turbines featured such rotors. Proposed projects indicate that total turbine height will continue to rise. Low wind turbine pricing has pushed down installed project costs over the last decade: Wind turbine prices averaged $\$800$–$\$950$/kW in 2021, a 5% to 10% increase from the year prior but substantially lower than in 2010. The average installed cost of wind projects in 2021 was $\$1,500$/kW, down more than 40% since the peak in 2010, though relatively stable in recent years. The lowest costs were found in Texas and the (non-ISO) West. Wind energy prices are on the rise, but generally remain low, around $\$20$/MWh in the interior of the country with higher prices in the West and East. After topping out above $\$75$/MWh for power purchase agreements (PPAs) executed in 2009, the national average price of wind PPAs has dropped—though supply-chain pressures have resulted in increased prices in recent years. In the interior ‘wind belt’ of the country, recent pricing is around $\$20$/MWh. In the West and East, prices tend to average above $\$30$/MWh. These prices, which are possible in part due to federal tax support, fall below the projected future fuel costs of gas-fired generation. Wind PPA prices are often attractive compared to wind’s grid-system market value: The value of wind in wholesale power markets is affected by the location of wind plants, their hourly output profiles, and how those characteristics correlate with real-time electricity prices and capacity markets. The market value of wind increased in 2021, averaging $\$16$/MWh in MISO, $\$19$/MWh in SPP, $\$23$/MWh in NYISO, $\$31$/MWh in ERCOT, $\$33$/MWh in PJM, $\$44$/MWh in ISO-NE, and $\$48$/MWh in CAISO. The average levelized cost of wind energy was $\$32$/MWh for plants built in 2021: Levelized costs, which exclude the impacts of federal tax incentives, vary across time and geography. The national average stood at $\$32$/MWh in 2021—down substantially historically, though relatively stable in recent years. Levelized costs were lowest in ERCOT, SPP, and the (non-ISO) West. The health and climate benefits of wind in 2021 were larger than its grid-system value, and the combination of all three far exceeds the current levelized cost of wind: Wind generation reduces power-sector emissions of carbon dioxide, nitrogen oxides, and sulfur dioxide. These reductions, in turn, provide public health and climate benefits that vary regionally, but together are economically valued at an average of over $\$90$/MWh-wind for plants built in 2021.

17 WIND ENERGY↗

DOE OSTI2022

Effective Mechanisms for Improving Seed Oil Production in Pennycress (Thlaspi arvense L.) Highlighted by Integration of Comparative Metabolomics and Transcriptomics

Pennycress is a potentially lucrative biofuel crop due to its high content of long-chain unsaturated fatty acids, and because it uses non-conventional pathways to achieve efficient oil production. However, metabolic engineering is required to improve pennycress oilseed content and make it an economically viable source of aviation fuel. Research is warranted to determine if further upregulation of these non-conventional pathways could improve oil production within the species even more, which would indicate these processes serve as promising metabolic engineering targets and could provide the improvement necessary for economic feasibility of this crop. To test this hypothesis, we performed a comparative biomass, metabolomic, and transcriptomic analyses between a high oil accession (HO) and low oil accession (LO) of pennycress to assess potential factors required to optimize oil content. An evident reduction in glycolysis intermediates, improved oxidative pentose phosphate pathway activity, malate accumulation in the tricarboxylic acid cycle, and an anaplerotic pathway upregulation were noted in the HO genotype. Additionally, higher levels of threonine aldolase transcripts imply a pyruvate bypass mechanism for acetyl-CoA production. Nucleotide sugar and ascorbate accumulation also were evident in HO, suggesting differential fate of associated carbon between the two genotypes. An altered transcriptome related to lipid droplet (LD) biosynthesis and stability suggests a contribution to a more tightly-packed LD arrangement in HO cotyledons. In addition to the importance of central carbon metabolism augmentation, alternative routes of carbon entry into fatty acid synthesis and modification, as well as transcriptionally modified changes in LD regulation, are key aspects of metabolism and storage associated with economically favorable phenotypes of the species.

59 BASIC BIOLOGICAL SCIENCES↗