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NASA NTRS2016

Parametric Analysis of Surveillance Quality and Level and Quality of Intent Information and Their Impact on Conflict Detection Performance

A loss-of-separation (LOS) is said to occur when two aircraft are spatially too close to one another. A LOS is the fundamental unsafe event to be avoided in air traffic management and conflict detection (CD) is the function that attempts to predict these LOS events. In general, the effectiveness of conflict detection relates to the overall safety and performance of an air traffic management concept. An abstract, parametric analysis was conducted to investigate the impact of surveillance quality, level of intent information, and quality of intent information on conflict detection performance. The data collected in this analysis can be used to estimate the conflict detection performance under alternative future scenarios or alternative allocations of the conflict detection function, based on the quality of the surveillance and intent information under those conditions.Alternatively, this data could also be used to estimate the surveillance and intent information quality required to achieve some desired CD performance as part of the design of a new separation assurance system.

Guerreiro, Nelson M.↗

NASA NTRSDate not supplied

Planned Investigations to Address Acute Central Nervous System Effects of Space Radiation Exposure with Human Performance Data

This work intends to generate evidence of acute, incremental human performance decrement similar to that due to space radiation andits impacts on the brain, to accompany ongoing human performance modeling work. The planned work will explore the boundaries of human behavioral and performance decrement after exposure to stress, which may be expected based in part on rodent responses found afterexposure to ionizing radiation. The collection of evidence via simulation studies can characterize real human errors toward determining what stress levels lead to significantly-low levels of performance (below permissible outcome limits) which would imperilmission accomplishment. If mission-relevant animal-study-linked tasks are used, human and animal performance levels may be aligned to enable quantitative assignment of permissible exposure limits based on animal exposure studies. Ultimately, a transfer function between the performances of exposed rodents and humans under stress can be developed using shared impairment mechanisms.

human performance↗

NASA NTRSDate not supplied

Planned Investigations to Address Acute Central Nervous System Effects of Space Radiation Exposure with Human Performance Data

This work intends to generate evidence of acute, incremental human performance decrement similar to that due to space radiation and its impacts on the brain, to accompany ongoing human performance modeling work. The planned work will explore the boundaries of human behavioral and performance decrement after expo-sure to stress, which may be expected based in part on rodent responses found after exposure to ionizing radiation. The collection of evidence via simulation studies can characterize real human errors toward determining what stress levels lead to significantly-low levels of performance (below permissible outcome limits) which would imperil mission accomplishment. If mission-relevant yet animal-study-linked tasks are used, human and animal performance levels may be aligned to enable quantitative assignment of permissible exposure limits based on animal exposure studies. Ultimately, a transfer function between the performances of exposed rodents and humans under stress can be developed using shared impairment mechanisms.

human performance↗

NASA NTRS2022

Drill-Site Selection for Cosmogenic-Nuclide Exposure Dating of the Bed of the Greenland Ice Sheet

Direct observations of the size of the Greenland Ice Sheet during Quaternary interglaciations are sparse yet valuable for testing numerical models of ice-sheet history and sea level contribution. Recent measurements of cosmogenic nuclides in bedrock from beneath the Greenland Ice Sheet collected during past deep-drilling campaigns reveal that the ice sheet was significantly smaller, and perhaps largely absent, sometime during the past 1.1 million years. These discoveries from decades-old basal samples motivate new, targeted sampling for cosmogenic-nuclide analysis beneath the ice sheet. Current drills available for retrieving bed material from the US Ice Drilling Program require < 700 m ice thickness and a frozen bed, while quartz-bearing bedrock lithologies are required for measuring a large suite of cosmogenic nuclides. We find that these and other requirements yield only ∼ 3.4 % of the Greenland Ice Sheet bed as a suitable drilling target using presently available technology. Additional factors related to scientific questions of interest are the following: which areas of the present ice sheet are the most sensitive to warming, where would a retreating ice sheet expose bare ground rather than leave a remnant ice cap, and which areas are most likely to remain frozen bedded throughout glacial cycles and thus best preserve cosmogenic nuclides? Here we identify locations beneath the Greenland Ice Sheet that are best suited for potential future drilling and analysis. These include sites bordering Inglefield Land in northwestern Greenland, near Victoria Fjord and Mylius-Erichsen Land in northern Greenland, and inland from the alpine topography along the ice margin in eastern and northeastern Greenland. Results from cosmogenic-nuclide analysis in new sub-ice bedrock cores from these areas would help to constrain dimensions of the Greenland Ice Sheet in the past.

Greenland↗

NASA NTRSDate not supplied

Airborne Observations of Particle Density in High Ice Water Content (HWC) Cloud Systems

A series of airborne field campaigns has been conducted since 2014 to measure the microphysical properties of high ice-water content (HIWC) clouds in maritime mesoscale convective systems (MCS) and tropical storms. Two of these, the HIWC RADAR-2 campaign (2018) targeting cloud systems in the Gulf of Mexico and Pacific Ocean, and the HIWC-2022 campaign targeting cloud systems in the Gulf of Mexico, Caribbean Sea, and Atlantic Ocean, have been analyzed to investigate graupel encounters at typical jet aircraft cruise altitudes. In-situ cloud observations from these two campaigns confirmed results from the prior studies, indicating that high concentrations of small ice particles exist in areas of HIWC. However, in the 2022 campaign, 90% of the cloud regions with ice water content (IWC) above 2.0 g/m3 also contained significant amounts of graupel and/or frozen drops. Using a mass-size parameterization that accounts for both small ice and larger high-density particles, we show that the mass distributions in cloud regions above 2.0 g/m3 are often strongly bimodal, with the small particle mode containing roughly half of the collective cloud mass, and the graupel mode containing the other half. In contrast, HIWC cloud passes in a 2018 tropical cyclone contained less relative graupel mass than the MCS cloud systems of 2018 and 2022. We present two different methods of estimating particle mass for mixed populations of small-ice and graupel particles, one using a hybrid two-class approach, and another using a single-class approach that takes both particle size and shape metrics into account. Derived IWC using these methods are compared to bulk IWC measurements collected during the campaigns. We also show the relative occurrence of graupel at various IWC levels and discuss the potential application of these results in evaluating density-aware microphysical schemes in cloud and weather models.

Aircraft Icing↗

DOE OSTI2020

My vehicle is a data mine

In this talk we explore how analysis of vehicle data provides information of individual vehicle behaviors, information of other vehicles in the flow of traffic, and insights into the behavior of drivers. Over the last two decades traditional passenger vehicles have been transformed from integrated two-port electrical nodes to cyber-physical systems of communicating computational nodes whose individual state and control variables are shared on a standard controller area network (CAN) bus. As driver assistance systems have crept into vehicles as safety features, driver behaviors can be observed through analysis of the data streams on the CAN bus as these new nodes communicate with one another. The properties of these data streams, as well as architectures and approaches to gather the data, are important to consider when drawing conclusions on the relevance of the data in making decisions at varying levels of the information hierarchy. We will demonstrate several technical challenges associated with these data collection processes, as well as preliminary results that demonstrate application relevance of the data to behavior, traffic, and systems domains.

42 ENGINEERING↗

DOE OSTI2020

Accelerating Ab Initio Simulation via Nested Monte Carlo and Machine Learned Reference Potentials

As a corollary of the rapid advances in computing, ab initio simulation is playing an increasingly important role in modeling materials at the atomic scale. Two strategies are possible, ab initio Monte Carlo (AIMC) and molecular dynamics (AIMD) simulation. The former benefits from exact sampling from the correct thermodynamic distribution, while the latter is typically more efficient with its collective all-atom coordinate updates. In this study, using a relatively simple test model comprised of helium and argon, we show that AIMC can be brought up to, and even above, the performance levels of AIMD via a hybrid nested sampling/machine learning (ML) strategy. Here, ML provides an accurate classical reference potential (up to three-body explicit interactions) that can pilot long collective Monte Carlo moves that are accepted or rejected in toto à la nested Monte Carlo (NMC); this is in contrast to the single move nature of a naive implementation. Our proposed method only requires a small up front expense from evaluating the ab initio energies and forces of (100) random configurations for training. Importantly, our method does not totally rely on the trained, assuredly imperfect, interaction. We show that high performance and exact sampling at the desired level of theory can be realized even when the trained interaction has appreciable differences from the ab initio potential. Remarkably, at the highest levels of performance realized via our approach, a pair of statistically uncorrelated atomic configurations can be generated with (1) ab initio calculations.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2025

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Growth and biochemical composition of the carrageenophyte Eucheumatopsis isiformis (Solieriaceae, Rhodophyta) under cultivation at different irradiance levels

Long-term production of a few species of Eucheuma and Kappaphycus from the Indo-Pacific Ocean supports the global carrageenan industry. The widespread use of vegetative propagation has resulted in low genetic diversity among farmed populations, making these crops increasingly vulnerable to diseases and environmental stressors, and resulting in declining yields and reduced biomass production over time. Insufficient efforts to develop and select new native cultivars, combined with the ecological risks posed by introducing nonindigenous species, underscore the urgent need to enhance cultivar diversification in eucheumatoid farming. Eucheumatopsis isiformis , a native carrageenophyte to the Atlantic Ocean, has potential for its cultivation in the Yucatán peninsula, Mexico. This study evaluated the growth and biochemical composition (pigments, elemental C and N, kappa/iota carrageenan ratio) of E. isiformis under different irradiance conditions in an indoor cultivation system. Specimens were collected in a subtidal population in Yucatán, Mexico, characterized, acclimatized to laboratory conditions, and exposed to five irradiance levels (71 ± 10.59 –1014 ± 65.85 µmol quanta m −2 s −1 ; 23.4 °C, salinity 33–34). Growth was measured weekly for six weeks, and elemental C and N content, pigment composition, and the kappa/iota-carrageenan ratio were evaluated. Growth and chromatic photoacclimation to light conditions were observed in all treatments. Highest growth rates (3.1–3.2% day −1 ) were registered between 238 ± 28.3 – 518 ± 44.3 µmol quanta m −2 s −1 , with a predominant iota-type carrageenan (0.97 ± 0.02) observed in all treatments. This study aims to provide guidelines for the successful development of the aquaculture of this carrageenophyte.

FTIR↗

NASA NTRS1989

Connectionist model-based stereo vision for telerobotics

Autonomous stereo vision for range measurement could greatly enhance the performance of telerobotic systems. Stereo vision could be a key component for autonomous object recognition and localization, thus enabling the system to perform low-level tasks, and allowing a human operator to perform a supervisory role. The central difficulty in stereo vision is the ambiguity in matching corresponding points in the left and right images. However, if one has a priori knowledge of the characteristics of the objects in the scene, as is often the case in telerobotics, a model-based approach can be taken. Researchers describe how matching ambiguities can be resolved by ensuring that the resulting three-dimensional points are consistent with surface models of the expected objects. A four-layer neural network hierarchy is used in which surface models of increasing complexity are represented in successive layers. These models are represented using a connectionist scheme called parameter networks, in which a parametrized object (for example, a planar patch p=f(h,m sub x, m sub y) is represented by a collection of processing units, each of which corresponds to a distinct combination of parameter values. The activity level of each unit in the parameter network can be thought of as representing the confidence with which the hypothesis represented by that unit is believed. Weights in the network are set so as to implement gradient descent in an energy function.

Hoff, William↗

DOE OSTI2021

Charge collection and trapping mechanisms in hexagonal boron nitride epilayers

Understanding charge collection and trapping mechanisms is crucial for using hexagonal boron nitride (h-BN) as active layers for many photonic and electronic devices such as deep UV detectors and emitters, neutron detectors, and single photon emitters. Charge collection and trapping mechanisms in h-BN epilayers have been investigated by probing impurity related optical emissions under an applied electrical field. Our results suggested that the existence of oxygen impurities affects the charge collection efficiency and results in an additional emission peak at 3.75 eV, corresponding to a donor-acceptor pair (DAP) recombination involving O N (oxygen residing on the nitrogen site) donors and the V B -H (boron vacancy bonded with hydrogen complex) deep level acceptors. Experimental results further revealed that the applied electric field induces an anti-correlation between the emission intensity of the DAP transition and the charge collection efficiency from which it was shown that it is possible to find an expression to quantitatively measure the maximum charge collection efficiency in h-BN. The results introduce not only a coherent picture for the relationship between common impurities in h-BN and charge collection and trapping mechanisms but also useful insights into possible approaches to improve the quality, purity, and charge collection of the h-BN epilayers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRSDate not supplied

Cleanroom Microbes Survive Drying, Vacuum, and Proton Irradiation

Introduction : The goal of planetary protection at NASA is to mitigate the risk of contaminating sensitive target bodies with biological life. While many cleaning procedures have been put in place to reduce bioburden on spacecraft, microbes are experts at evolving to survive harsh conditions. Specifically, the dry, low-nutrient environment of a cleanroom (commonly used for assembly of spacecraft) can represent an environment where extremophiles can survive. Methods : Scientists at NASA MSFC wished to gather a snapshot of the microbial population within a variety of cleanrooms on site. A study was undertaken to collect air, surface, and floor samples from clean-rooms and isolate unique morphologies. From this study, 95 isolates were collected and saved in a microbial library. About 86% of these were identified at least to a genus level. Following identification, 24 microbes were selected, based on a literature review, as potential extremophiles. These were grown in liquid cultures, diluted to a set optical density, washed with water, and then applied to a sterilized Kapton coupon. Droplets were allowed to dry overnight in a biosafety cabinet. Coupons were then installed in a pelletron and pumped down to high vacuum (~1E-6 Torr). Samples were then subjected 100 keV protons at a fluence of 2x10 15 p+/cm 2 up to 4x10 15 p+/cm 2 . Following exposure, samples were returned to the microbiology lab where they were pro-cessed by submerging in water, vortexing, and then plating either droplets or spread plates. Recovery data collected was qualitative with a ranking or +, minor, or – for growth. Some selected radiotolerant strains were sequenced using the Illumina sequencing platform. The resulting genomes were annotated with the Rapid Annotations using Subsystems Technology (RAST) server and analyzed for conserved and unique stress response relevant genomic signatures to identify clues related to specific tolerances. Results and Discussion : After five rounds of proton radiation, we narrowed our isolates to five, non-spore forming bacteria that demonstrated survival: Arthrobacter koreensis, Paenarthrobacter nitroguajacolicus, Mycetocola manganoxydans , and an Erwinia sp. Furthermore, we exposed these four microbes to 254 nm wavelength light at an intensity of 80 W/m 2 at a distance of ~18 cm for 10 minutes. Only A. koreensis demonstrated survival following UV exposure. Finally, we performed whole genome sequencing on the four strains to look for genetic markers of stress resistance. When we compared the genomes of the four strains, we found that genes coding for GGDEF and EAL domains with PAS/PAC sensors were only found in A. koreensis . These domains, modulated by PAS/PAC sensors, are hypothesized to facilitate survival under drying, desiccation, and proton irradiation. Drying and Desiccation : PAS domains sense hydration changes and modulate GGDEF and EAL domain activity to adjust c-di-GMP levels, enhancing resistance to desiccation. For instance, in Pseudomonas aeruginosa , the PAS domain of RbdA modulates activity under varying hydration conditions, affecting stress responses [1]. Proton Irradiation : Proton irradiation causes oxidative stress, leading to ROS generation. PAS domains detect this stress and modulate GGDEF and EAL domains to manage oxidative stress responses. In Shewanella , EAL domain proteins modulated by PAS sensors help bacteria adapt to extreme conditions [2]. These genes upregulate other stress response genes, protecting membrane function, protein stability, DNA repair, and antioxidant defenses. The modulation of c-di-GMP by PAS domains is crucial for bacterial adaptation to stress conditions, enabling dynamic physio-logical adjustments [3]. Understanding these mechanisms provides insights into bacterial stress responses and strategies for controlling bacterial growth [4]. Conclusions : These findings indicate that clean-rooms harbor extremophile microbes that may be able to survive conditions in deep space. Furthermore, while we identified certain stress-response genes that may be at least partly responsible for the phenotypes observed in this study, there are likely unidentified genes or characteristics about A. koreensis , and other bacteria, that may allow them to survive in harsh environments. Future studies will focus on identifying these unknown genes and characteristics, further elucidating the mechanisms of extremophile survival and potentially informing the development of new biotechnologies for space exploration and other extreme environments.

Chelsi Cassilly↗

NASA NTRS2020

UAS Service Supplier Network Performance

This report summarizes the performance of Unmanned Aircraft System (UAS) Service Suppliers (USS) in the Technical Capability Level 4 (TCL4) flight test performed by NASA and its partners in support of the UAS Traffic Management (UTM) concept. TCL4 is the final in a series of TCL demonstrations of a traffic management system for small UAS (sUAS). All demonstrations have been executed in collaboration with industry partners. The [FAA 2018] UTM Concept of Operations document describes UTM as:...the manner in which the FAA will support operations for predominantly sUAS operating in low altitude airspace. UTM utilizes industry’s ability to supply services under FAA’s regulatory authority where these services do not currently exist. It is a community-based traffic management system, where the Operators are responsible for the coordination, execution, and management of operations, with rules of the road established by FAA. UTM is designed to support the demand and expectations for a broad spectrum of operations with ever-increasing complexity and risk. UTM should be considered a collection of services rather than a monolithic application. The following section describes the architecture at a high level. For further insight, the FAA’s concept document [FAA 2018] or NASA’s earlier concept publication [NASA 2016] should be consulted.

Rios, Joseph L.↗

NASA NTRS2007

Use of AIRS, OMI, MLS, and TES Data in Assessing Forest Ecosystem Exposure to Ozone

Ground-level ozone at high levels poses health threats to exposed flora and fauna, including negative impacts to human health. While concern is common regarding depletion of ozone in the stratosphere, portions of the urban and rural United States periodically have high ambient levels of tropospheric ozone on the ground. Ozone pollution can cause a variety of impacts to susceptible vegetation (e.g., Ponderosa and Jeffrey pine species in the southwestern United States), such as stunted growth, alteration of growth form, needle or leaf chlorosis, and impaired ability to withstand drought-induced water stress. In addition, Southern Californian forests with high ozone exposures have been recently subject to multiyear droughts that have led to extensive forest overstory mortality from insect outbreaks and increased incidence of wildfires. Residual forests in these impacted areas may be more vulnerable to high ozone exposures and to other forest threats than ever before. NASA sensors collect a wealth of atmospheric data that have been used recently for mapping and monitoring regional tropospheric ozone levels. AIRS (Atmospheric Infrared Sounder), OMI (Ozone Monitoring Instrument), MLS (Microwave Limb Sounder), and TES (Tropospheric Emission Spectrometer) data could be used to assess forest ecosystem exposure to ozone. Such NASA data hold promise for providing better or at least complementary synoptic information on ground-level ozone levels that Federal agency partners can use to assess forest health trends and to mitigate the threats as needed in compliance with Federal laws and mandates. NASA data products on ozone concentrations may be able to aid applications of DSTs (decision support tools) adopted by the USDA FS (U.S. Department of Agriculture Forest Service) and by the NPS (National Park Service), such as the Ozone Calculator, in which ground ozone estimates are employed to assess ozone impacts to forested vegetation.

Spruce, Joseph P.↗

DOE OSTI2026

Lifetimes of low-lying levels in 158 Gd

The low-lying structure of the well-deformed nucleus 158 Gd has been revisited to elucidate the nature of the low-lying states in 158 Gd. Earlier (p, t) studies identified numerous 0 + states below 4.3 MeV, prompting questions about whether these states correspond to collective vibrations or shape coexistence. New and previously reported (n, n' γ) measurements are combined, including γ-γ coincidences, excitation functions, and angular distributions, to extract lifetimes and transition probabilities for 44 excited states up to 2.7 MeV, including 32 previously unmeasured levels. Our results confirm or revise γ-ray placements and provide detailed transition strengths, revealing both weakly collective and strongly enhanced B(E2) and B(E1) transition probabilities. In particular, a tentative 0 + state at 2437.8 keV exhibits a strong interband B(E2) transition, which may be a candidate for a possible two-phonon (ββ) excitation. Systematic comparisons with neighboring Gd isotopes, Hartree–Fock–Bogoliubov, and interacting-boson model predictions suggest that the first excited 0 + state in 158 Gd is predicted to be a β-vibration, although it is weakly collective.

158Gd↗

DOE OSTI2023

Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System

The Inflation Reduction Act of 2022 (IRA) and the Infrastructure Investment and Jobs Act of 2021, commonly referred to as the 'Bipartisan Infrastructure Law (BIL),' collectively represent the largest commitment of the U.S. Federal Government to invest in the modernization and decarbonization of the U.S. energy system. The Congressional Budget Office (CBO) estimates that total support for the broad range of climate and clean energy programs, tax credits, and other incentives authorized through the two laws will exceed $430 billion from 2022 through 2031 (CRS 2022; CBO 2021, 2022). While the climate and clean energy provisions are numerous and have the potential to impact all aspects of the U.S. energy system from fuel and electricity production to final consumption in industry, transportation, and buildings, the provisions relevant to the electricity sector - in particular the suite of tax credits for clean generation, storage, and carbon dioxide ( CO 2 ) capture and storage - are expected to be some of the most consequential in terms of emissions reduction and clean energy deployment (Larsen et al. 2022; Jenkins, Mayfield, et al. 2022; Mahajan et al. 2022; Zhao et al. 2022). In this report, we detail the methods and results of a study estimating the potential impacts of key provisions of IRA and BIL on the contiguous U.S. power sector from present day through 2030. The analysis employs an advanced power system planning model, the Regional Energy Deployment System (ReEDS), to evaluate how major provisions from both laws impact investment in and operation of utility-scale generation, storage, and transmission, and, in turn, how those changes impact power system costs, emissions, and climate and health damages. While not exhaustive in capturing every provision, the analysis estimates the possible scale of power-sector impacts that could result from the modeled provisions in IRA and BIL. The study is structured around two scenarios to evaluate the potential impacts of both laws on the power sector: 1) No New Policy: A counter-factual scenario that reflects all Federal and state policies enacted as of September 2022, with exception to IRA and BIL, and assumes load growth consistent with the Energy Information Administration's Annual Energy Outlook 2022 (AEO22) Reference case (EIA 2022a); 2) IRA-BIL: A scenario reflecting all Federal and state policies enacted as of September 2022, including key IRA and BIL provisions, most notably the investment and production tax credits for zero-carbon emitting electricity generation and storage (ITC and PTC), the tax credit for CO 2 capture and storage (45Q), and the tax credit for existing nuclear plants (described further in Section 2.3). To account for the impacts of IRA and BIL on electrification, assumes increased load growth consistent with a scaled version of the Medium Electrification scenario from the Electrification Futures Study (Mai et al. 2018). These scenarios are simulated across seven sets of assumptions with varying projected future electricity market conditions, including technology costs and performance, natural gas prices, and the degree of availability, feasibility, and cost of development of renewable resources, electricity transmission, and CO 2 pipeline, injection, and storage infrastructure. In addition, we simulate two sensitivities on the 'policy' treatment in which we vary key assumptions pertaining to the realized value of the clean electricity ITC and PTC: 1) the cost of monetization of tax credits, and 2) the level of bonus crediting realized by project developers. We demonstrate that IRA and BIL have the collective potential to drive substantial growth in clean electricity by 2030, while reducing costs for consumers, mitigating climate change, and decreasing the human health impacts of power sector emissions. However, we also demonstrate that if expected cost improvements of clean technologies are not realized and/or constraints on deployment driven by factors such as supply-chain challenges, regulatory hurdles, and the social acceptability of energy infrastructure development limit the rate of clean energy and associated infrastructure deployment (such as transmission), then the share of clean generation achieved and the associated emissions benefits realized may be substantively reduced.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

MOSAiC-Colorado State University Ice Spectrometer

This data set contains atmospheric ice nucleating particle (INP) measurements, using Colorado State University’s (CSU) Ice Spectrometer (IS), of filter collections taken at the U.S. DOE ARM AMF2 site onboard the R/V Polarstern P-deck during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign. Samples were collected from October 27, 2019 to September 24, 2020. A filter sampler was mounted approximately 15 m above ground level on a railing in proximity to (and approximately 3 m below) the Aerosol Observation System (AOS) inlet. Single-use filter units open to the atmosphere were pre-cleaned and pre-loaded with 47-mm diameter Nuclepore polycarbonate (0.2 µm pore-diameter) filters. Filters were typically drawn for a three-day period, with an average volume of air filtered of 87,000 standard liters. Total volumes were calculated through recorded daily flow rates using a mass flow meter (TSI). After collection, filters were stored and transported frozen until analysis using CSU’s IS instrument (McCluskey et al., 2018). Aerosol particles were first re-suspended in 8 mL of 0.1 µm-filtered deionized (DI) water. Aliquots of each suspension, and corresponding 11-fold dilutions, were dispensed into polymerase chain reaction (PCR) trays and placed into the aluminum blocks of the IS. Samples were cooled at approximately 0.33 °C min -1 and freezing detected optically with corresponding temperatures recorded. Cumulative INP concentrations were determined through calculating the number of INPs per mL of suspension (Vali, 1971) and converting to concentration per standard L of air by accounting for the proportion of liquid used and volume of air collected. All samples were corrected for the number of INPs on the average of four field blanks (cleaned, handled, transported, and analyzed in the same way without air flow). Two-tailed, 95% confidence intervals for binomial sampling are provided (Agresti and Coull, 1998). Select samples were also heat treated (95 °C for 20 min) to denature and deactivate biological INPs present and digested in 10% H 2 O 2 at 95 °C under UV-B for 20 min to remove any organic carbon INPs. Agresti, A, and BA Coull. 1998. "Approximate is better than “exact” for interval estimation of binomial proportions." American Statistics 52: 119–126. https://doi.org/10.2307/2685469 McCluskey, CS, J Ovadnevaite, M Rinaldi, J Atkinson, F Belosi, D Ceburnis, … and PJ DeMott. 2018. "Marine and Terrestrial Organic Ice-Nucleating Particles in Pristine Marine to Continentally Influenced Northeast Atlantic Air Masses." Journal of Geophysical Research: Atmospheres 123 (11): 6196–6212, https://doi.org/10.1029/2017JD028033 Vali, G. 1971. "Quantitative Evaluation of Experimental Results and the Heterogeneous Freezing Nucleation of Supercooled Liquids." Journal of the Atmospheric Sciences 28: 402-209. https://doi.org/10.1175/1520-0469(1971)028<0402:QEOERA>2.0.CO;2

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Comparative genomics reveals the high diversity and adaptation strategies of Polaromonas from polar environments

Abstract Background Bacteria from the genus Polaromonas are dominant phylotypes found in a variety of low-temperature environments in polar regions. The diversity and biogeographic distribution of Polaromonas have been largely expanded on the basis of 16 S rRNA gene amplicon sequencing. However, the evolution and cold adaptation mechanisms of Polaromonas from polar regions are poorly understood at the genomic level. Results A total of 202 genomes of the genus Polaromonas were analyzed, and 121 different species were delineated on the basis of average nucleotide identity (ANI) and phylogenomic placements. Remarkably, 8 genomes recovered from polar environments clustered into a separate clade (‘polar group’ hereafter). The genome size, coding density and coding sequences (CDSs) of the polar group were significantly different from those of other nonpolar Polaromonas . Furthermore, the enrichment of genes involved in carbohydrate and peptide metabolism was evident in the polar group. In addition, genes encoding proteins related to betaine synthesis and transport were increased in the genomes from the polar group. Phylogenomic analysis revealed that two different evolutionary scenarios may explain the adaptation of Polaromonas to cold environments in polar regions. Conclusions The global distribution of the genus Polaromonas highlights its strong adaptability in both polar and nonpolar environments. Species delineation significantly expands our understanding of the diversity of the Polaromonas genus on a global scale. In this study, a polar-specific clade was found, which may represent a specific ecotype well adapted to polar environments. Collectively, genomic insight into the metabolic diversity, evolution and adaptation of the genus Polaromonas at the genome level provides a genetic basis for understanding the potential response mechanisms of Polaromonas to global warming in polar regions.

54 ENVIRONMENTAL SCIENCES↗