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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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NASA NTRS2005

National Aeronautics and Space Administration (NASA) Earth Science Research for Energy Management: Overview of Energy Issues and an Assessment of the Potential for Application of NASA Earth Science Research - Part 1

Effective management of energy resources is critical for the U.S. economy, the environment, and, more broadly, for sustainable development and alleviating poverty worldwide. The scope of energy management is broad, ranging from energy production and end use to emissions monitoring and mitigation and long-term planning. Given the extensive NASA Earth science research on energy and related weather and climate-related parameters, and rapidly advancing energy technologies and applications, there is great potential for increased application of NASA Earth science research to selected energy management issues and decision support tools. The NASA Energy Management Program Element is already involved in a number of projects applying NASA Earth science research to energy management issues, with a focus on solar and wind renewable energy and developing interests in energy modeling, short-term load forecasting, energy efficient building design, and biomass production.

Atmospheric models↗
DOE OSTI2022

Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing

Soil organic carbon (SOC) is a key variable to determine soil functioning, ecosystem services, and global carbon cycles. Spectroscopy, particularly optical hyperspectral reflectance coupled with machine learning, can provide rapid, efficient, and cost-effective quantification of SOC. However, how to exploit soil hyperspectral reflectance to predict SOC concentration, and the potential performance of airborne and satellite data for predicting surface SOC at large scales remain relatively underknown. Here, this study utilized a continental-scale soil laboratory spectral library (37,540 full-pedon 350–2500 nm reflectance spectra with SOC concentration of 0–780 g·kg –1 across the US) to thoroughly evaluate seven machine learning algorithms including Partial-Least Squares Regression (PLSR), Random Forest (RF), K-Nearest Neighbors (KNN), Ridge, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) along with four preprocessed spectra, i.e. original, vector normalization, continuum removal, and first-order derivative, to quantify SOC concentration. Furthermore, by using the coupled soil-vegetation-atmosphere radiative transfer model, we simulated twelve airborne and spaceborne hyper/multi-spectral remote sensing data from surface bare soil laboratory spectra to evaluate their potential for estimating SOC concentration of surface bare soils. Results show that LSTM achieved best predictive performance of quantifying SOC concentration for the whole data sets (R 2 = 0.96, RMSE = 30.81 g·kg –1 ), mineral soils (SOC ≤ 120 g·kg –1 , R 2 = 0.71, RMSE = 10.60 g·kg –1 ), and organic soils (SOC > 120 g·kg –1 , R 2 = 0.78, RMSE = 62.31 g·kg –1 ). Spectral data preprocessing, particularly the first-order derivative, improved the performance of PLSR, RF, Ridge, KNN, and ANN, but not LSTM or CNN. We found that the SOC models of mineral and organic soils should be distinguished given their distinct spectral signatures. Finally, we identified that the shortwave infrared is vital for airborne and spaceborne hyperspectral sensors to monitor surface SOC. This study highlights the high accuracy of LSTM with hyperspectral/multispectral data to mitigate a certain level of noise (soil moisture <0.4 m 3 ·m –3 , green leaf area < 0.3 m 2 ·m –2 , plant residue <0.4 m 2 ·m –2 ) for quantifying surface SOC concentration. Forthcoming satellite hyperspectral missions like Surface Biology and Geology (SBG) have a high potential for future global soil carbon monitoring, while high-resolution satellite multispectral fusion data can be an alternative.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

An Electric Propulsion "Shepherd" for Active Debris Removal that Utilizes Ambient Gas as Propellant

There is a growing consensus among the space debris technical community that limiting the long ]term growth of debris in Low-Earth Orbit (LEO) requires that space users limit the accumulation of mass in orbit. This is partially accomplished by mitigation measures for current and future LEO systems, but there is now interest in removing mass that has already accumulated in LEO from more than 50 years of space activity (termed "Active Debris Removal", or ADR). Many ADR proposals face complex technical issues of how to grapple with uncooperative targets. Some researchers have suggested the use of conventional ion thrusters to gently "blow" on objects to gradually change their orbits, without ever having to come into physical contact with the target. The chief drawback with these methods is the cost per object removed. Typically, a space "tug" or an ion-drive "shepherd" can only remove a few objects per mission due to limited propellant. Unless a costeffective way that removes tens of objects per mission can be found, it is not clear that any of the ideas so far proposed will be economically viable. In this paper, a modified version of the ion-drive "shepherd" is proposed that uses ambient atmospheric gases in LEO as propellant for the ion drives. This method has the potential to greatly extend the operational lifetime of an ADR mission, as the only mission limit is the lifetime of the components of the satellite itself, not on its fuel supply. An ambient-gas ion-drive "shepherd" would the local atmospheric drag on an object by ionizing and accelerating the ambient gas the target would have encountered anyway, thereby hastening its decay. Also, the "shepherd" satellite itself has a great deal of flexibility to maneuver back to high altitude and rendezvous with its next target using the ion drive not limited by fuel supply. However, the amount of available ambient gas is closely tied to the altitude of the spacecraft. It may be possible to use a "hybrid" approach that supplements high-altitude ion-drive operations with stored gas, and transitions to ambient gas at lower altitudes. This paper will include realistic numbers on the estimated times needed to deorbit objects from different orbit regimes using drives that either partially or completely take advantage of ambient gas. It will conclude with recommendations on whether this is a viable candidate for future ADR efforts.

Matney, Mark J.↗
NASA NTRS2006

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Quattrochi, Dale A.↗
NASA NTRS2013

An Electric Propulsion "Shepherd" for Active Debris Removal that Utilizes Ambient Gas as Propellant

There is a growing consensus among the space debris technical community that limiting the long-term growth of debris in Low-Earth Orbit (LEO) requires that space users limit the accumulation of mass in orbit. This is partially accomplished by mitigation measures for current and future LEO systems, but there is now interest in removing mass that has already accumulated in LEO from more than 50 years of space activity (termed "Active Debris Removal", or ADR). Many ADR proposals face complex technical issues of how to grapple with uncooperative targets. Some researchers have suggested the use of conventional ion thrusters to gently "blow" on objects to gradually change their orbits, without ever having to come into physical contact with the target. The chief drawback with these methods is the cost per object removed. Typically, a space "tug" or an ion-drive "shepherd" can only remove a few objects per mission due to limited propellant. Unless a cost-effective way that removes tens of objects per mission can be found, it is not clear that any of the ideas so far proposed will be economically viable. In this paper, a modified version of the ion-drive "shepherd" is proposed that uses ambient atmospheric gases in LEO as propellant for the ion drives. This method has the potential to greatly extend the operational lifetime of an ADR mission, as the only mission limit is the lifetime of the components of the satellite itself, not on its fuel supply. An ambient-gas ion-drive "shepherd" would enhance the local atmospheric drag on an object by ionizing and accelerating the ambient gas the target would have encountered anyway, thereby hastening its decay. Also, the "shepherd" satellite itself has a great deal of flexibility to maneuver back to high altitude and rendezvous with its next target using the ion drive not limited by fuel supply. However, the amount of available ambient gas is closely tied to the altitude of the spacecraft. It may be possible to use a "hybrid" approach that supplements high-altitude ion-drive operations with stored gas, and transitions to ambient gas at lower altitudes. This paper will include realistic numbers on the estimated times needed to deorbit objects from different orbit regimes using drives that either partially or completely take advantage of ambient gas. It will conclude with recommendations on whether this is a viable candidate for future ADR efforts.

Matney, Mark↗
NASA NTRS2015

SLS-SPEC-159 Cross-Program Design Specification for Natural Environments (DSNE) Revision D

This document is derived from the former National Aeronautics and Space Administration (NASA) Constellation Program (CxP) document CxP 70023, titled "The Design Specification for Natural Environments (DSNE), Revision C." The original document has been modified to represent updated Design Reference Missions (DRMs) for the NASA Exploration Systems Development (ESD) Programs. The DSNE completes environment-related specifications for architecture, system-level, and lower-tier documents by specifying the ranges of environmental conditions that must be accounted for by NASA ESD Programs. To assure clarity and consistency, and to prevent requirements documents from becoming cluttered with extensive amounts of technical material, natural environment specifications have been compiled into this document. The intent is to keep a unified specification for natural environments that each Program calls out for appropriate application. This document defines the natural environments parameter limits (maximum and minimum values, energy spectra, or precise model inputs, assumptions, model options, etc.), for all ESD Programs. These environments are developed by the NASA Marshall Space Flight Center (MSFC) Natural Environments Branch (MSFC organization code: EV44). Many of the parameter limits are based on experience with previous programs, such as the Space Shuttle Program. The parameter limits contain no margin and are meant to be evaluated individually to ensure they are reasonable (i.e., do not apply unrealistic extreme-on-extreme conditions). The natural environments specifications in this document should be accounted for by robust design of the flight vehicle and support systems. However, it is understood that in some cases the Programs will find it more effective to account for portions of the environment ranges by operational mitigation or acceptance of risk in accordance with an appropriate program risk management plan and/or hazard analysis process. The DSNE is not intended as a definition of operational models or operational constraints, nor is it adequate, alone, for ground facilities which may have additional requirements (for example, building codes and local environmental constraints). "Natural environments," as the term is used here, refers to the environments that are not the result of intended human activity or intervention. It consists of a variety of external environmental factors (most of natural origin and a few of human origin) which impose restrictions or otherwise impact the development or operation of flight vehicles and destination surface systems. These natural environments include the following types of environments: Terrestrial environments at launch, abort, and normal landing sites (winds, temperatures, pressures, surface roughness, sea conditions, etc.); Space environments (ionizing radiation, orbital debris, meteoroids, thermosphere density, plasma, solar, Earth, and lunar-emitted thermal radiation, etc.); Destination environments (Lunar surface and orbital, Mars atmosphere and surface, near Earth asteroids, etc.). Many of the environmental specifications in this document are based on models, data, and environment descriptions contained in the CxP 70044, Constellation Program Natural Environment Definition for Design (NEDD). The NEDD provides additional detailed environment data and model descriptions to support analytical studies for ESD Programs. For background information on specific environments and their effects on spacecraft design and operations, the environment models, and the data used to generate the specifications contained in the DSNE, the reader is referred to the NEDD paragraphs listed in each section of the DSNE. Also, most of the environmental specifications in this document are tied specifically to the ESD DRMs in ESD-10012, Revision B, Exploration Systems Development Concept of Operations (ConOps). Coordination between these environment specifications and the DRMs must be maintained. This document should be compatible with the current ESD DRMs, but updates to the mission definitions and variations in interpretation may require adjustments to the environment specifications.

Roberts, Barry C.↗
DOE OSTI2023

Climate-driven deterioration of future ozone pollution in Asia predicted by machine learning with multi-source data

Ozone (O 3 ) is a secondary pollutant in the atmosphere formed by photochemical reactions that endangers human health and ecosystems. O 3 has aggravated in Asia in recent decades and will vary in the future. In this study, to quantify the impacts of future climate change on O 3 pollution, near-surface O 3 concentrations over Asia in 2020–2100 are projected using a machine learning (ML) method along with multi-source data. The ML model is trained with combined O 3 data from a global atmospheric chemical transport model and real-time observations. The ML model is then used to estimate future O 3 with meteorological fields from multi-model simulations under various climate scenarios. The near-surface O 3 concentrations are projected to increase by 5 %–20 % over South China, Southeast Asia, and South India and less than 10 % over North China and the Gangetic Plains under the high-forcing scenarios in the last decade of 21st century, compared to the first decade of 2020–2100. The O 3 increases are primarily owing to the favorable meteorological conditions for O 3 photochemical formation in most Asian regions. We also find that the summertime O 3 pollution over eastern China will expand from North China to South China and extend into the cold season in a warmer future. Our results demonstrate the important role of a climate change penalty on Asian O 3 in the future, which provides implications for environmental and climate strategies of adaptation and mitigation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Assessment of SNPP VIIRS RSB detector-to-detector differences using deep convective clouds and deserts

An accurate on-orbit characterization of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership satellite is essential to satisfy the requirements from NOAA, NASA, and the general research community for high-quality operational and research products. NASA’s Land Science Investigator-led Processing System (LSIPS) sensor data records (SDRs) are utilized to assess the stability of the calibrated top of atmosphere reflectance over the deep convective clouds (DCCs) and over the Libya-4desert site. The results from DCCs and desert show detector-to-detector (D2D) reflectance differences in the VIIRS reflective solar bands, 10 moderate-resolution bands (M-bands, M1to M5, M7 to M11), and three imagery resolution bands (I-bands, I1-I3). More importantly, the D2D differences exhibit an increase in magnitude over time for bands M1 to M5 and I1to I2, which induces noticeable striping and higher uncertainties in the downstream data products. The largest D2D difference is observed in bands M1 and M2, with magnitudes greater than1.8% in trends among the 16 detectors and standard deviations less than 0.12% over time. TheD2D stability assessment results over DCCs are consistent with those observed over the Libya-4desert site. To improve the quality of the calibrated SDR reflectance data, NASA’s VIIRS characterization support team has improved the calibration algorithm to incorporate corrections based on these DCC measurements to mitigate the striping (detector differences) observed in the current version of the SDR. These improvements are planned to be included in the next mission reprocessing of the LSIPS land products.

SNPP VIIRS↗
DOE OSTI2026

Reduced methane emissions in transgenic rice genotypes are associated with altered rhizosphere microbial hydrogen cycling

Rice paddies significantly contribute to atmospheric methane (CH 4 ). Here, we show that two independent rice genotypes overexpressing genes for PLANT PEPTIDES CONTAINING SULFATED TYROSINE (PSY) reduce cumulative CH 4 emissions by 38% (PSY1) and 58% (PSY2) over 70 days of growth compared with controls. Genome-resolved metatranscriptomic data from PSY rhizosphere soils reveal lower ratios of gene activities for (mostly hydrogenotrophic) CH 4 production versus consumption, decreased activity of H 2 -producing genes, and increased activity of bacterial H 2 oxidation pathways. Metabolic modeling using metagenomic and metabolomic data predicts elevated H 2 oxidation and suppressed H 2 production in the PSY rhizosphere. Assembled genomes of rhizosphere H 2 -oxidizing bacteria are enriched in genes utilizing gluconeogenic acids compared with H 2 -producing counterparts, and their activities are likely stimulated by elevated levels of gluconeogenic acids, primarily amino acids, in PSY root exudates. Overall, our study indicates that decreased CH 4 emissions are due to a lower amount of H 2 available for hydrogenotrophic methanogenesis and provides a powerful strategy to mitigate CH 4 emissions from increasingly widespread rice cultivation.

Biological and medical sciences↗
NASA NTRS2012

Numerical Study of Ammonia Leak and Dispersion in the International Space Station

Release of ammonia into the International Space Station (ISS) cabin atmosphere can occur if the water/ammonia barrier breach of the active thermal control system (ATCS) interface heat exchanger (IFHX) happens. After IFHX breach liquid ammonia is introduced into the water-filled internal thermal control system (ITCS) and then to the cabin environment through a ruptured gas trap. Once the liquid water/ammonia mixture exits ITCS, it instantly vaporizes and mixes with the U.S. Laboratory cabin air that results in rapid deterioration of the cabin conditions. The goal of the study is to assess ammonia propagation in the Station after IFHX breach to plan the operation procedure. A Computational Fluid Dynamics (CFD) model for accurate prediction of airflow and ammonia transport within each of the modules in the ISS cabin was developed. CFD data on ammonia content in the cabin aisle way of the ISS and, in particular, in the Russian On- Orbit Segment during the period of 15 minutes after gas trap rupture are presented for four scenarios of rupture response. Localized effects of ammonia dispersion and risk mitigation are discussed.

Son, Chang H.↗
DOE OSTI2026

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗
DOE OSTI2025

Effect of moisture ingression on material performance and particle generation in molten salts

This report summarizes activities conducted to understand and mitigate the negative consequences that moisture ingressions have upon the operations of pyroprocessing equipment. The objectives of the work conducted in FY25 were to characterize (1) the physicochemical properties of particles generated as a result of moisture ingressions, and (2) the corrosion of relevant structural materials with the introduction of moisture. Compositional and morphological analyses of the generated particles were conducted through a suite of characterization technologies, including X-ray diffraction, microscopy, and particle size analysis. The results gathered this year were compared to those obtained in FY24 when studies with oxygen ingressions were conducted on CeCl 3 -LiCl-KCl and UCl 3 -LiCl-KCl systems. Investigations involving performance evaluations of industrially relevant structural alloys were also conducted under moisture ingress conditions. In-line electrochemical monitoring of the bulk salt was augmented with microscopy of alloy samples to quantify the concentration and accumulation of corrosion products in the bulk salt. The results reported in this work provide a more holistic understanding of the effects of atmospheric ingressions on molten chloride salt chemistry such that effective redox control strategies may be implemented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2006

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
DOE OSTI2025

Evaluating the carbon capture potential of industrial waste as a feedstock for enhanced weathering

Abstract Limiting anthropogenic global climate warming since the start of the industrial period to less than 2 °C will very likely require both deep and rapid reductions in anthropogenic greenhouse gas emissions and a range of approaches toward carbon dioxide removal (CDR). One prominent CDR approach is enhanced weathering (EW), in which crushed silicate rock is applied on land or in the open ocean to accelerate natural weathering processes that absorb carbon dioxide from Earth’s ocean–atmosphere system. However, in addition to a range of potential environmental, socioeconomic, and ethical issues associated with this pathway, bottlenecks in feedstock sourcing represent a key barrier for deployment of EW at scale. Here, we evaluate the potential of silicate wastes produced from industrial processes—such as steel slag and cement waste—as feedstocks for the EW process. An empirical model that links industrial alkaline waste production to gross domestic product at purchase power parity is developed to forecast waste production in the alternative futures described by the shared socioeconomic pathway (SSP) framework. By incorporating these results into an intermediate-complexity Earth system model, we also explore the impacts of EW using industrial waste on changes to global temperature, ocean pH, and ocean aragonite saturation state, while also quantifying overall CDR efficiency through the end of the century. We estimate a maximum cumulative end-of-century capture potential of ∼400 GtCO 2 for industrial waste, which could represent a significant fraction of the projected CDR requirement of many mitigation scenarios in the SSP framework. However, feedstock-dependent environmental impacts and the technoeconomics of feedstock redistribution may ultimately limit deployment scope.

Xu, Pengxiao (ORCID:0009000633724293)↗
DOE OSTI2020

South Africa’s Appliance Energy Efficiency Standards and Labeling Program

Electricity consumption in South Africa comes with a hefty environmental cost to the society. For every kilowatt-hour (kWh) produced, 1 kilogram (kg) of carbon dioxide (CO 2 ) is emitted, 1.4 liters of water are used, and 0.37 grams of particulate emissions are released in the atmosphere. These environmental implications result from the large share of electricity produced from coal (91 percent in 2015). While planned new capacity will ramp up renewable energy, the integrated resource plan for the country still projects the share of col to be 64 percent in 2030. Energy savings provide environmental benefits as well as economic benefits. Energy efficiency standards and labeling (S&L) programs are a policy measure proven to save energy. Such programs have been implemented in many countries to remove inefficient technologies and transform markets to more efficient technologies. In this study, we describe the methodology, assumptions and results of a stock turnover modeling tool that estimates the energy savings achievable by South Africa’s S&L program in the residential sector. We show that if regulations are passed in 2020 and effective in 2021 for 10 major end-use adopting international standards best practices, 6 terawatt-hours (TWh) will be saved in 2030 and 9.5 TWh will be saved in 2040, representing a CO 2 mitigation of 3.7 megatonnes (Mt) in 2030 and 5.8 Mt in 2040, which will contribute to the South African government’s international engagement in fighting against climate change through its National Determined Contribution (NDC). Additional environmental benefits include saving of 6.5 billion liters of water in 2030, representing approximately 100 liters per capita in 2030. Air quality will also improve, as 4 kilotons (kt) of particulate emissions will be avoided, as well as 4.3 Mt of sulfur oxides (SOx) and 23 kt of nitrogen oxides (NOx) in 2030.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Corrosion-Resistant Coatings on Spent Nuclear Fuel Canisters to Mitigate and Repair Potential Stress Corrosion Cracking (FY22 Status)

This report summarizes the activities performed by Sandia National Laboratories in FY22 to identify and test coating materials for the prevention, mitigation, and/or repair of potential chloride-induced stress corrosion cracking in spent nuclear fuel dry storage canisters. This work continues efforts by Sandia National Laboratories that are summarized in previous reports in FY20 and FY21 on the same topic. The previous work detailed the specific coating properties desired for application and implementation to spent nuclear fuel canisters (FY20) and identified several potential coatings for evaluation (FY21). In FY22, Sandia National Laboratories, in collaboration with four industry partners through a Memorandum of Understanding, started evaluating the physical, mechanical, and corrosion-resistance properties of 6 different coating systems (11 total coating variants) to develop a baseline understanding of the viability of each coating type for use to prevent, mitigate, and/or repair potential stress corrosion on cracking on spent nuclear fuel canisters. This collaborative R&D program leverages the analytical and laboratory capabilities at Sandia National Laboratories and the material design and synthesis capabilities of the industry collaborators. The coating systems include organic (polyetherketoneketone, modified polyimide/polyurea, modified phenolic resin), organic/inorganic ceramic hybrids (silane-based polyurethane hybrid and a quasi-ceramic sol-gel polyurethane hybrid), and hybrid systems in conjuncture with a Zn-rich primer. These coatings were applied to stainless steel coupons (the same coupons were supplied to all vendors by SNL for direct comparison) and have undergone several physical, mechanical, and electrochemical tests. The results and implications of these tests are summarized in this report. These analyses will be used to identify the most effective coatings for potential use on spent nuclear fuel dry storage canisters, and also to identify specific needs for further optimization of coating technologies for their application on spent nuclear fuel canisters. In FY22, Sandia National Laboratories performed baseline testing and atmospheric exposure tests of the coating samples supplied by the vendors in accordance with the scope of work defined in the Memorandum of Understanding. In FY23, Sandia National Laboratories will continue evaluating coating performance with a focus on thermal and radiolytic stability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Assessing the Impact of SMAP Soil Moisture Data Assimilation on the Simulation and Prediction of Tropical Cyclone Idai

The role of soil moisture in the evolution of tropical cyclones (TCs) approaching land has long been recognized. Dry land surface conditions can lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions can help sustain or even re-intensify a TC. The ability to forecast post-landfall TC evolution and mitigate the associated socio-economic impact thus hinges on accurate knowledge of land surface conditions prior to landfall. The NASA Soil Moisture Active Passive (SMAP) mission provides accurate observations of soil moisture globally and at high revisit times of 2-3 days. It has been shown that the assimilation of SMAPbrightness temperatures (Tb) significantly improves modeled land surface states and thus has the potential to constrain land surface initial conditions in TC forecasts. In this presentation, we investigate this potential through an extensive set of Observing System Experiments that systematically assess the impact of assimilating SMAP Tbs on TC forecast skill in the Goddard Earth Observing System. Focusing on the case of TC Idai, we show that the assimilation of SMAP generally leads to a drier soil moisture analysis for the land surface underneath much of the storm’s circulation. An exception is the direct TC track, where SMAP assimilation increases soil moisture. These changes are reflected in the surface fluxes, which propagate the land surface state changes to the atmosphere. This results a TC that is overall weaker with lower winds, but with a better-defined eye and a slightly smaller track error than a simulation without SMAP DA. The changes in soil moisture resulting from the assimilation of SMAP also impact the total precipitation amounts as well as the precipitation structure associated with TC Idai.

SMAP↗