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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 OSTI2015

Scaling nitrogen and carbon interactions: what are the consequences of biological buffering?

Abstract Understanding the consequences of elevated CO 2 ( eCO 2 ; 800 ppm) on terrestrial ecosystems is a central theme in global change biology, but relatively little is known about how altered plant C and N metabolism influences higher levels of biological organization. Here, we investigate the consequences of C and N interactions by genetically modifying the N‐assimilation pathway in A rabidopsis and initiating growth chamber and mesocosm competition studies at current CO 2 ( cCO 2 ; 400 ppm) and eCO 2 over multiple generations. Using a suite of ecological, physiological, and molecular genomic tools, we show that a single‐gene mutant of a key enzyme ( nia2 ) elicited a highly orchestrated buffering response starting with a fivefold increase in the expression of a gene paralog ( nia1 ) and a 63% increase in the expression of gene network module enriched for N‐assimilation genes. The genetic perturbation reduced amino acids, protein, and TCA ‐cycle intermediate concentrations in the nia2 mutant compared to the wild‐type, while eCO 2 mainly increased carbohydrate concentrations. The mutant had reduced net photosynthetic rates due to a 27% decrease in carboxylation capacity and an 18% decrease in electron transport rates. The expression of these buffering mechanisms resulted in a penalty that negatively correlated with fitness and population dynamics yet showed only minor alterations in our estimates of population function, including total per unit area biomass, ground cover, and leaf area index. This study provides insight into the consequences of buffering mechanisms that occur post‐genetic perturbations in the N pathway and the associated outcomes these buffering systems have on plant populations relative to eCO 2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds

Projected increases in cyclonic storm intensity under a warming climate will have profound effects on forests, potentially changing these ecosystems from carbon sinks to sources. Forecasting storm impacts on these ecosystems requires consideration of risk factors associated with storm meteorology, landscape structure, and forest attributes. Here we evaluate risk factors associated with damage severity caused by Hurricanes María and Irma across Puerto Rican forests. Using field and remote sensing data, total forest aboveground biomass (AGB) lost to the storms was estimated at 10.44 (±2.33) Tg, ca. 23% of island-wide pre-hurricane forest AGB. Storm-related rainfall was a stronger predictor of forest damage than maximum wind speeds. Soil water storage capacity was also an important risk factor, corroborating the influence of rainfall on forest damage. Expected increases of 20% in hurricane-associated rainfall in the North Atlantic highlight the need to consider how such shifts, together with high speed winds, will affect terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Criegee intermediates and their impacts on the troposphere

We report Criegee intermediates (CIs), carbonyl oxides formed in ozonolysis of alkenes, play key roles in the troposphere. The decomposition of CIs can be a significant source of OH to the tropospheric oxidation cycle especially during nighttime and winter months. A variety of model-measurement studies have estimated surface-level stabilized Criegee intermediate (sCI) concentrations on the order of 1 × 10 4 cm -3 to 1 × 10 5 cm -3 , which makes a non-negligible contribution to the oxidising capacity in the terrestrial boundary layer. The reactions of sCI with the water monomer and the water dimer have been found to be the most important bimolecular reactions to the tropospheric sCI loss rate, at least for the smallest carbonyl oxides; the products from these reactions (e.g. hydroxymethyl hydroperoxide, HMHP) are also of importance to the atmospheric oxidation cycle. The sCI can oxidise SO 2 to form SO 3 , which can go on to form a significant amount of H 2 SO 4 which is a key atmospheric nucleation species and therefore vital to the formation of clouds. Lastly, the sCI can also react with carboxylic acids, carbonyl compounds, alcohols, peroxy radicals and hydroperoxides, and the products of these reactions are likely to be highly oxygenated species, with low vapour pressures, that can lead to nucleation and SOA formation over terrestrial regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

The impact of climate change policy on the risk of water stress in southern and eastern Asia

The adequacy of freshwater resources remains a critical challenge for a sustainable and growing society. We present a self-consistent risk-based assessment of water availability and use under future climate change and socioeconomic growth by midcentury across southern and eastern Asia (SEA). We employ large ensemble scenarios from an integrated modeling framework that are consistent across the spectrum of regional climate, population, and economic projections. We find socioeconomic growth contributes to an increase in water stress across the entire ensemble. However, climate change drives the ensemble central tendency toward an increase in water stress in China but a reduction in India, with a considerable spread across the ensemble. Nevertheless, the most deleterious unabated climate-change impact is a low probability but salient extreme increase in water stress over China and India. In these outcomes, annual withdrawals will routinely exceed water-storage capacity. A modest greenhouse gas mitigation pathway eliminates the likelihood of these extreme outcomes and also benefits hundreds of millions of people at risk to various levels of water stress increase. Over SEA we estimate an additional 200 million people under threat of facing at least heavily water-stressed conditions from climate change and socioeconomic growth, but the mitigation scenario reduces the additional population-under-threat by 30% (60 million). Nevertheless, there remains a 1-in-2 chance that 100 million people across SEA experience a 50% increase in water stress and a 1-in-10 chance they experience a doubling of water stress. Therefore, widespread adaptive measures may be required over the coming decades to meet these unavoidable risks in water shortfalls.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Region-Specific Merchant Hydrogen Market Assessment and Techno-Economic Assessment of Electrolytic Hydrogen Generation: Cooperative Research and Development Final Report, CRADA Number CRD-18-00751

Utilities need to recover value from baseload and some renewable assets even when the electricity is curtailed. The declining cost of renewables (particularly solar), the persistently low-cost of natural gas, and the declining electricity demand, have all worked to lower the price of electricity. Furthermore, the baseload assets have a high turndown cost, which is not reflected in the low market electricity prices. One option for utilizing the curtailed electricity is hydrogen generation. One important aspect of this project will be to provide a “go/no-go” recommendation on the economic feasibility of pursuing hydrogen generation vs. other markets that could offtake curtailed electricity or nuclear steam. This project will specifically assess the opportunities for hydrogen production and use in the service territories of Southern Company Services (SCS), Exelon SBC, and Xcel Energy. Each utility partner represents a different mix of generation fleets: Exelon has significant nuclear assets, Xcel is primarily renewables (wind) with some nuclear, and SCS represents both a renewables fleet and a heavily baseload fleet, which includes significant nuclear. The Contractors will conduct the study of hydrogen market opportunities by first considering the approximate electricity demand and price profiles for the year, and power generation capacity that can be used to produce hydrogen. Therefore, a profile for hydrogen generation will also be developed to better understand the quantity and timing of hydrogen production. Once the hydrogen production schedule is estimated, hydrogen storage requirements can be determined. This effort will provide sufficient information to make a go/no-go decision on moving ahead with a detailed regional case study for hydrogen production in any of the three utility areas.

08 HYDROGEN↗
DOE OSTI2014

The effect of compost on carbon cycling and the active soil microbiota

Rangelands cover an estimated 40-70percent of global landmass, approximately one-third of the landmass of the United States and half of California. The soils of this vast land area has high carbon (C) storage capacity, which makes it an important target ecosystem for the mitigation of greenhouse gas emission and effects on climate change, in particular under land management techniques that favor increased C sequestration rates. While microbial communities are key players in the processes responsible for C storage and loss in soils, we have barely shed light on these highly complex processes in part due to the tremendous and seemingly intractable diversity of microbes, largely uncultured, that inhabit soil ecosystems. In our study, we compare Mediterranean grassland soil plots that were amended with greenwaste compost in a single event 6 years ago. Subsampling of control and amended plots was performed in depth increments of 0-10 cm. We present data on greenhouse gas emissions and budgets of carbon, nitrogen, phosphorus, and micronutrients in dependence of compost amendment. Changes in the active members of the soil microbial community were assessed using a novel approach combining flow cytometry and 16S tag sequencing disclosing who is active. This is the first study revealing the nature of actively metabolizing microbial community members linked to the geochemical characteristics of compost-amended soil.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Exploration of the Theoretical Physical Capacity of the John F. Kennedy International Airport Runway System

A design study was completed to explore the theoretical physical capacity (TPC) of the John F. Kennedy International Airport (KJFK) runway system for a northflow configuration assuming impedance-free (to throughput) air traffic control functionality. Individual runways were modeled using an agent-based, airspace simulation tool, the Airspace Concept Evaluation System (ACES), with all runways conducting both departures and arrivals on a first-come first-served (FCFS) scheduling basis. A realistic future flight schedule was expanded to 3.5 times the traffic level of a selected baseline day, September 26, 2006, to provide a steady overdemand state for KJFK runways. Rules constraining departure and arrival operations were defined to reflect physical limits beyond which safe operations could no longer be assumed. Safety buffers to account for all sources of operational variability were not included in the TPC estimate. Visual approaches were assumed for all arrivals to minimize inter-arrival spacing. Parallel runway operations were assumed to be independent based on lateral spacing distances. Resulting time intervals between successive airport operations were primarily constrained by same-runway and then by intersecting-runway spacing requirements. The resulting physical runway capacity approximates a theoretical limit that cannot be exceeded without modifying runway interaction assumptions. Comparison with current KJFK operational limits for a north-flow runway configuration indicates a substantial throughput gap of approximately 48%. This gap may be further analyzed to determine which part may be feasibly bridged through the deployment of advanced systems and procedures, and which part cannot, because it is either impossible or not cost-effective to control. Advanced systems for bridging the throughput gap may be conceptualized and simulated using this same experimental setup to estimate the level of gap closure achieved.

Neitzke, Kurt W.↗
DOE OSTI2018

Statistical analysis of historic hydrocarbon production data from Gulf of Mexico oil and gas fields and application to dynamic capacity assessment in CO 2 storage

Numerical modeling of CO 2 injection and reservoir flow is typically performed to forecast the number of wells, sustainable injection rates, and total storage volume (or mass). A critical determination for CO 2 storage in depleted oil and gas reservoirs is characterization of reservoir compartmentalization which informs boundary conditions in simulating injection scenarios. Constraining boundary conditions during CO 2 injection into geological formations is a key factor for feasible deployment project. Production history data from 616 wells in 100 oil and gas fields from Gulf of Mexico (GOM) offshore basin can be used to evaluate boundary conditions and total production (oil and gas) and therefor constrain the capacity for potential carbon storage. In general, the combination of decline curve analysis and statistical analysis (to specify constraining boundary conditions) allows the determination of the range of reservoir performance if existing inactive production wells in GOM area of study are used reversibly for CO 2 injection. To constrain the mass of CO 2 which can be injected, it is useful to consider estimates of cumulative bulk (hydrocarbon + brine) production (CBP), which can be converted to equivalent CO 2 mass considering reservoir conditions. Summary CBP statistics are presented as a probability of non-exceedance (PNE), providing a forecast of likely injection rates and masses for other located CO 2 storage projects with similar geology and boundary conditions in the future. The 50% PNE for Equivalent CO 2 is a novel quantitative approach to investigate the possible injection capacity in CO 2 storage projects. The PNE sensitivity analysis shows that reservoir age, drive mechanism, reservoir trap, and reservoir porosity are the key controlling parameters for productivity and consequently optimum CO 2 storage capacity. Furthermore another key finding is the negligible correlation between CBP with reservoir transmissivity and porosity, which implies that other factors than just petrophysical parameters should be studied as constraining factors for CO 2 storage statistical analysis.

42 ENGINEERING↗
NASA NTRS2010

Remote Characterization of Biomass Measurements: Case Study of Mangrove Forests

Accurately quantifying forest biomass is of crucial importance for climate change studies. By quantifying the amount of above and below ground biomass and consequently carbon stored in forest ecosystems, we are able to derive estimates of carbon sequestration, emission and storage and help close the carbon budget. Mangrove forests, in addition to providing habitat and nursery grounds for over 1300 animal species, are also an important sink of biomass. Although they only constitute about 3% of the total forested area globally, their carbon storage capacity -- in forested biomass and soil carbon -- is greater than that of tropical forests (Lucas et al, 2007). In addition, the amount of mangrove carbon -- in the form of litter and leaves exported into offshore areas is immense, resulting in over 10% of the ocean's dissolved organic carbon originating from mangroves (Dittmar et al, 2006) The measurement of forest above ground biomass is carried out on two major scales: on the plot scale, biomass can be measured using field measurements through allometric equation derivation and measurements of forest plots. On the larger scale, the field data are used to calibrate remotely sensed data to obtain stand-wide or even regional estimates of biomass. Currently, biomass can be calculated using average stand biomass values and optical data, such as aerial photography or satellite images (Landsat, Modis, Ikonos, SPOT, etc.). More recent studies have concentrated on deriving forest biomass values using radar (JERS, SIR-C, SRTM, Airsar) and/or lidar (ICEsat/GLAS, LVIS) active remote sensing to retrieve more accurate and detailed measurements of forest biomass. The implementation of a generation of new active sensors (UAVSar, DesdynI, Alos/Palsar, TerraX) has prompted the development of new tecm'liques of biomass estimation that use the combination of multiple sensors and datasets, to quantify past, current and future biomass stocks. Focusing on mangrove forest biomass estimation, this book chapter has 3 main objectives: a) To describe in detail the field methodologies used to derive accurate estimates of biomass in mangrove forests b) To explain how mangrove forest biomass can be measured using several remote sensing techniques and datasets c) To give a detailed explanation of the measurement challenges and errors that arise in each estimate of forest biomass

Fatoyinbo, Temilola E.↗
DOE OSTI2019

Subtask 1.1 – Advanced Characterization of Unconventional Oil and Gas Reservoirs to Enhance CO2 Storage Resource Estimates

The Energy & Environmental Research Center (EERC) developed methods and approaches for advanced characterization of unconventional oil and gas reservoirs to enhance CO2 storage resource estimates using samples collected from organic-rich shales of the Bakken Formation. The project was funded under U.S. Department of Energy (DOE) Cooperative Agreement No. DE-FE0024233, with nonfederal cost share provided by Hitachi High Technologies America. The project participants included the EERC, Hitachi High Technologies America, the team at the National Energy Technology Laboratory’s (NETL’s) computed tomography (CT) scanning laboratory in Morgantown, West Virginia, and several NETL staff who have worked on CO2 storage resource estimation. Investigations on the use of subsurface geologic formations for CO2 storage have been ongoing for many years. In the last decade, improvements in directional drilling technology and hydraulic fracturing of organic-rich shale and other tight rock formations have opened new opportunities for CO2 storage, with the potential cobenefit of enhancing gas and oil recovery. Gas-bearing, organic-rich shales have been of particular interest as a carbon storage target because their ability to store large volumes of CO2 is implied by their ability to store methane; however, estimating the CO2 storage resource of organic-rich shales and other unconventional reservoirs is challenging because of the lack of detailed geologic and petrophysical data that are needed to develop improved volumetric equations. According to NETL’s method for estimating regional-scale CO2 storage resources, the key factors that control CO2 storage in geologic formations include void space within induced fractures, natural fractures and matrix pores, as well as the occurrence and distribution of organic matter (OM) and clay minerals. A key goal of this effort was to use field emission scanning electron microscopy (FESEM) analysis of fine-grain unconventional reservoir rocks coupled with advanced image analysis and machine learning techniques to quantify the occurrence and distribution of porosity, OM, and clay minerals. By better understanding the potential migration pathways of CO2 within tight rocks and quantifying the occurrence of sorptive components (OM and clays) along potential flow pathways, methods to estimate the CO2 storage resource of such rocks can be refined. The Bakken petroleum system (Bakken) was used as the source of rock samples for this effort because it includes organic-rich shales with contrasting degrees of thermal maturity as well as tight, nonshale clastic rocks with varying clay mineral content. To better understand the key components of interest in tight rock samples, the EERC worked closely with Hitachi to optimize the FESEM settings necessary to resolve the sample mineralogy, porosity and OM content at micro- to nanoscale resolution. The EERC also worked closely with Hitachi to apply and improve its advanced mineral identification and characterization system (AMICS) software so that it is better suited for mineral identification at the high resolution necessary to resolve features of interest in fine-grained rocks such as organic-rich shales. The EERC also applied advanced image analysis software packages, including Ilastik, to classify and quantify the key components of interest within the samples using FESEM imagery. These advanced techniques allowed for quantification and differentiation of the void space within fractures, pores and OM, as well as a technique to determine and quantify the key mineral and OM components surrounding pore spaces. Being able to better quantify the void space and the potential accessibility of CO2 to sorptive minerals or OM within tight rocks allows for improved estimation of the CO2 storage resource potential of organic-rich shales and other unconventional formations. The information derived from the image analysis techniques was used to refine NETL’s method for estimating regional-scale CO2 storage resources in collaboration with staff from NETL. An additional goal of this work was to better understand rates of CO2 permeation, flow pathways, and sorption in organic-rich shales and nonshale reservoir rocks and to evaluate potential changes in CO2 flow over time. The EERC conducted long-duration (several weeks) CO2 flow-through testing at reservoir conditions using Bakken shale and nonshale samples to assess CO2 permeation rates and retention/sorption within core plugs to represent bulk matrix behavior. Conventional isothermal adsorption testing over a range of pressure conditions was also performed on pulverized Bakken samples to better assess potential maximum sorptive capacity of the samples. The results of this testing illustrated the higher sorptive capacity of the Bakken shales when compared to the sorptive capacity of the nonshale reservoir rock, which contains very little OM when compared to the Bakken shales. The results also illustrate the differences in permeation behavior as a function of fracture flow versus matrix flow. In an attempt to visualize CO2 permeation and flow behavior in Bakken shale samples over time, the EERC collaborated with NETL’s CT Lab in Morgantown, West Virginia. A variety of tests were performed at the NETL lab on unfractured and fractured samples of the Bakken shale. The unfractured Bakken shale samples did not result in CO2 migration within the samples over the testing duration; thus imagery of CO2 migration pathways within the matrix of Bakken samples was not obtained. The results of the flow-through testing within fractured samples illustrate changes in CO2 permeation rates over time, with a trend of decreasing CO2 flow over time. The results of this effort suggest that FESEM analysis coupled with advanced image analysis and machine learning techniques are effective in characterizing and quantifying the mineralogy, porosity, fractures, and OM content of 2-D imagery at the high resolution needed to identify features of interest in tight rocks. In addition, the image analysis techniques allow for identification and quantification of different porosity types as well as the key mineral components and/or OM that CO2 would contact in the reservoir as it migrates through pores and fracture networks. This is key information needed to better estimate the CO2 storage resource potential of organic-rich shales and other tight reservoirs. Additional work is needed to determine the sorptive capacity of the individual sample components (OM and clay minerals) at reservoir conditions so that this approach and the refined CO2 storage resource equation can be applied to other shale and unconventional reservoirs. In addition, subsequent work should be performed to better understand the number of images needed to use stereological approaches to estimate the volume of sample components using 2-D imagery, to explore machine learning techniques to differentiate between induced vs. natural fractures, and to estimate the connectivity of pores and fracture networks using 2-D imagery. Being able to derive this information at the microscale would facilitate scaling up of the sample characterization data used for reservoir modeling and simulation to estimate the CO2 storage resource potential of tight formations.

03 NATURAL GAS↗
NASA NTRSDate not supplied

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. This suite included a network of MEDLI2 Instrumented Sensor Plugs (MISPs). Each MISP was comprised of a cylinder made of Thermal Protection System (TPS) material with 1-3 embedded thermocouples (TCs), and it was flush mounted into the heatshield or backshell. Data from these in-depth TCs were used to reconstruct the aeroheating environment of the vehicle throughout entry. Surface heating was posed as an inverse problem, with the goal of estimating the surface heating by minimizing an objective function of the difference between MISP temperature measurements during flight and the temperature predictions derived from the Fully Implicit Ablation and Thermal response (FIAT) program. Given an aerothermal environment, FIAT calculates the material response and provides in-depth temperatures throughout the TPS material. To achieve the reverse, an internal tool called FIAT_Opt runs through multiple different environments until the output temperature at the TC depth closely matches the flight data. 95% confidence intervals on the reconstructed surface heating were obtained using Monte Carlo analysis, in which uncertainties in the thermocouple depth and the TPS material properties (e.g., density, thermal conductivity, heat capacity, emissivity) based on flight-lot material testing were included. A variance decomposition method using Sobol indices was employed to assess the sensitivity of the reconstructed peak heating to the TC placement and material property uncertainties. Variance decomposition was found to require tens of thousands of FIAT_Opt runs in order for the Sobol indices to converge. With a single FIAT_Opt run taking on the order of 40 minutes, the required number of computations would take months to complete, even if using multiple CPUs. To mitigate this problem, three machine learning models (ridge regression with cross-validation, random forest regression, and a deep neural network) were trained and tested using the 2000 Monte Carlo runs that were already completed. A subset of 1600 runs were used to train the model (i.e., training set), while the remaining 400 runs were used as the test set. The predictions from the deep neural network (DNN) on the test set showed nearly perfect agreement to the actual values computed with FIAT_Opt (R2 > 0.99). Using the DNN as a surrogate model, the variance decomposition using 50,000 runs was completed within minutes. The resulting Sobol indices showed that the reconstructed peak surface heating was most sensitive to the uncertainties in the thermal conductivity (ST = 0.37) and heat capacity (ST = 0.26). This method can be leveraged to provide requirements for material property measurements needed to improve the accuracy of surface heating prediction and ultimately lead to the reduction of design margins in the future. This presentation will include background on the MEDLI2 suite; the method used for inverse heating estimation; the way that material property uncertainties were accounted for using Monte Carlo analysis; a brief background on variance decomposition; the motivation for using machine learning in this context; how a neural network was trained on the data to enable variance decomposition in a fraction of the time; and the variance decomposition results for one of the MISPs.

Hannah Alpert↗
DOE OSTI2021

Pipe Parity Analysis of Seawater Desalination in the United States: Exploring Costs, Energy, and Reliability via Case Studies and Scenarios of Emerging Technology

As climate change-induced variables exacerbate water scarcities, the use of seawater reverse osmosis (SWRO) membrane desalination technology for treating seawater could potentially provide a long-term drought-proof source of drinking water. This study carried out a technoeconomic assessment (TEA) for three SWRO desalination plants in the U.S. and one in Israel to set baselines for the cost and energy consumption for seawater desalination. In addition, a breakeven curve for implementing SWRO desalination was estimated in relation to the cost of water conservation measures to meet drought-induced reduction of the traditional water supply. The results show that the cost of SWRO water production scales with the plant capacity while energy intensity is not dramatically different across the plants. The higher cost in some U.S. plants is due to high capital investment, including land acquisition and permitting. Variations in plant capacity utilization have the greatest impact on the levelized cost of water (LCOW) over the plant service life, suggesting the importance of reducing fouling and maintenance-related downtime. Scenario analysis of fixed labor cost reduction through process automation indicates investments in automation and sensing technology could result in long-term savings. Breakeven analysis shows the decision to adopt SWRO is highly dependent on the local cost associated with water conservation to meet water supply reduction. Moreover, a small reduction in SWRO cost can influence a shift toward the adoption of SWRO over water conservation measures. Incorporation of future water demand, water conservation potential, and water stress data around the nation indicates SWRO desalination could be an important contributor to the future municipal drinking water portfolio in the U.S.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Characterizing the gene–environment interaction underlying natural morphological variation in Neurospora crassa conidiophores using high-throughput phenomics and transcriptomics

Abstract Neurospora crassa propagates through dissemination of conidia, which develop through specialized structures called conidiophores. Recent work has identified striking variation in conidiophore morphology, using a wild population collection from Louisiana, United States of America to classify 3 distinct phenotypes: Wild-Type, Wrap, and Bulky. Little is known about the impact of these phenotypes on sporulation or germination later in the N. crassa life cycle, or about the genetic variation that underlies them. In this study, we show that conidiophore morphology likely affects colonization capacity of wild N. crassa isolates through both sporulation distance and germination on different carbon sources. We generated and crossed homokaryotic strains belonging to each phenotypic group to more robustly fit a model for and estimate heritability of the complex trait, conidiophore architecture. Our fitted model suggests at least 3 genes and 2 epistatic interactions contribute to conidiophore phenotype, which has an estimated heritability of 0.47. To uncover genes contributing to these phenotypes, we performed RNA-sequencing on mycelia and conidiophores of strains representing each of the 3 phenotypes. Our results show that the Bulky strain had a distinct transcriptional profile from that of Wild-Type and Wrap, exhibiting differential expression patterns in clock-controlled genes (ccgs), the conidiation-specific gene con-6, and genes implicated in metabolism and communication. Combined, these results present novel ecological impacts of and differential gene expression underlying natural conidiophore morphological variation, a complex trait that has not yet been thoroughly explored.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Regional Assessment for the CO 2 Storage Potential in the Northern Niagaran Pinnacle Reef Trend

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. The report describes the regional analysis of the Northern Niagaran Pinnacle Reef Trend (NNPRT) in Northern Michigan as part of the MRCSP programs Regional Assessment goals. The goal of this task was to perform an initial assessment of the geologic storage capacity and injectivity of the Northern Fairway of Michigan’s Niagaran Reef Trend. This was achieved through three main objectives: 1) development of a reef atlas, 2) understanding the regional trends in geology, and 3) estimating CO 2 and CO 2 -EOR resources. Data collected across multiple subtasks were integrated into a mappable database that could be accessed from many of the leading software. The reef atlas was used to map the reefs and associated characteristics across the entire NNPRT. Several methodologies were explored to estimate the CO 2 and CO 2 -EOR resources across the trend which included three scenarios: 1) storage only using fluid substitution and volumetric estimations, 2) CO 2 -EOR which applied proximity analysis concepts and measured performance metrics from the Core Energy reefs to predict performance at all oil reefs, and 3) enhanced storage scenario which combined CO 2 -EOR with fluid substitution to represent maximized storage after completion of CO 2 -EOR.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1973

An equation of state for oxygen and nitrogen

Recent measurements of the thermodynamic properties of oxygen and nitrogen have been used to develop a single equation of state for both fluids; with appropriate coefficients, the equation describes the pressure-density-temperature surface for each fluid within the estimated experimental uncertainty of the data. The formulation uses least squares curve fitting of the equation of state to the available experimental data (including pressure-density-temperature data, saturation data, and measured isochoric heat capacities). New vapor pressure equations and equations for the ideal gas heat capacities of oxygen and nitrogen are included for use in calculation of derived thermodynamic properties.

Jacobsen, R. T.↗
DOE OSTI2018

Sequential Mitigation Solutions to Enable Distributed PV Grid Integration: Preprint

This paper provides a method to assess the impact of multiple mitigation solutions including distribution grid upgrades and advanced control technologies on increasing distributed PV penetration in distribution feeders, and thus paves the way to estimate the costs needed for reaching certain PV penetration level. Based on three assumptions of creating increasing PV penetration scenarios, this paper first studies the distribution impact of PV power and quantifies the PV hosting capacity in distribution feeders. Then, it studies multiple mitigation solutions to increase PV penetration on distribution feeders. These mitigation solutions are implemented in a sequential manner according to their typical costs. The proposed study is demonstrated on two representative distribution feeders.

14 SOLAR ENERGY↗
DOE OSTI2016

A Roadmap and Cost Implications of Establishing Comprehensive Cancer Care Using a Teleradiotherapy Network in a Group of Sub-Saharan African Countries With No Access to Radiation Therapy

Purpose: To propose a roadmap and explore the cost implications of establishing a teleradiotherapy network to provide comprehensive cancer care and capacity building in countries without access to radiation therapy. Methods and Materials: Ten low-income sub-Saharan countries with no current radiation therapy facilities were evaluated. A basic/secondary radiation therapy center (SRTC) with 2 teletherapy, 1 brachytherapy, 1 simulator, and a treatment planning facility was envisaged at a cost of 5 million US dollars (USD 5M). This could be networked with 1 to 4 primary radiation therapy centers (PRTC) with 1 teletherapy unit, each costing USD 2M. The numbers of PRTCs and SRTCs for each country were computed on the basis of cancer incidence, assuming that a PRTC and SRTC could respectively treat 450 and 900 patients annually. Results: An estimated 71,215 patients in these countries will need radiation therapy in 2020. Stepwise establishment of a network with 99 PRTCs and 28 SRTCs would result in 155 teletherapy units and 96% access to radiation therapy. A total of 310 radiation oncologists, 155 medical physicists, and 465 radiation therapy technologists would be needed. Capacity building could be undertaken through telementoring by networking to various international institutions and professional societies. Total infrastructure costs would be approximately USD 860.88M, only 0.94% of the average annual gross domestic product of these 10 countries. A total of 1.04 million patients could receive radiation therapy during the 15-year lifespan of a teletherapy unit for an investment of USD 826.69 per patient. For the entire population of 218.32 million, this equates to USD 4.11 per inhabitant. Conclusion: A teleradiotherapy network could be a cost-contained innovative health care strategy to provide effective comprehensive cancer care through resource sharing and capacity building. The network could also be expanded to include other allied specialties. The proposal calls for active coordination between all national and international organizations backed up by strong geopolitical commitment and action from all stakeholders.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Regional patterns in hydrologic response, a new three-component metric for hydrograph analysis and implications for ecohydrology, Northwest Volcanic Aquifer Study Area, USA

Spatial patterns of hydrologic response were examined for the Northwest Volcanic Aquifer Study Area (NVASA). The utility of established hydrograph-separation methods for assessing hydrologic response in permeable volcanic terranes was assessed and a new three-component metric for hydrograph analysis was developed. The new metric, which partitions streamflow into subcomponents defined by the timescales of hydrologic response (e.g., fast-runoff, intermediate-interflow and slow-baseflow), was used to gain a fundamental understanding of the regional hydrology, investigate sub-regional differences, influencing factors, and ecohydrological implications. The combined effects of NVASA’s physiography, climate and geology create a strongly coupled surface-groundwater system that produces copious baseflow and limited quantities of runoff and interflow. Patterns of hydrologic response are influenced by the type and rate of precipitation and permeability of the underlying geology. Under variable precipitation conditions the hydrologic response of volcanic terranes with similar permeability and subsurface-storage capacity can be significantly different. From a water management and ecohydrology perspective, understanding regional patterns of hydrologic response and sub-regional differences is fundamental. Results indicate that minimum-flow methods provide the most conservative estimate of baseflow and may be the most robust for filtering out snowmelt bias in baseflow estimates. Baseflow contributes ~75% of the perennial streamflow across the NVASA and represents a critical component of the regional water supply that provides critical cold-water habitat.

54 ENVIRONMENTAL SCIENCES↗