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Projecting climate change in South America using variable‐resolution Community Earth System Model: An application to Chile

Abstract We introduce variable‐resolution enabled Community Earth System Model (VR‐CESM) results simulating historical and future climate conditions at 28 km over South America and 14 km over the Andes. Three 30‐year simulations are performed: a historic (1985–2014), a near future (2030–2059), and an end‐century (2070–2099) simulation under the RCP8.5 scenario. Historic results compare favourably to several temperature and precipitation reanalysis products, though local biases are present, particularly during austral summer. Future simulations highlight broad warming patterns (+3–6°C by end‐century) and heterogeneous precipitation responses across South America that qualitatively agree with prior modelling efforts. Our results reveal that the interaction between temperature and precipitation changes produce shifts in several Köppen–Geiger climates. Notable changes include the near‐elimination of the Andean Tundra or Alpine climates, a 15% decrease in Tropical Rainforests and a Tropical Savannah expansion of 20%. To provide a regionally focused analysis of projected climate change and to illustrate the benefits of variable resolution modelling, we analyse changes in the magnitude and trend in seasonal and daily temperature and precipitation in Chile. We also examined several metrics [e.g., snow water equivalent (SWE), temperatures on wet days, and days below 0°C] to evaluate potential impacts of climate change on the Chilean cryosphere between the end‐of‐century and historic periods, finding wide‐ranging indications of cryospheric decline. These changes are interpreted through reductions in the timing (1–2.5 months earlier peak SWE) and magnitude (200–1,000 mm SWE decreases) of water stored as snow in the Andes, a 10–30% decrease in number of cool season wet days with temperatures below 1°C, and 50–200 fewer days (annually) with minimum temperatures below 0°C. Our aim in producing a high‐resolution dataset of climate projections from VR‐CESM is to support analyses of climate change throughout South America but especially in vulnerable montane regions and to provide additional results for comparison with previous, ongoing, and upcoming modelling efforts.

variable-resolution global climate models↗

Evaluating Methods of Software Bill of Materials Generation to Enhance Nuclear Power Plant Cybersecurity

Instrumentation and control (I&C) systems in nuclear power plants (NPPs) are potential targets of cyberattacks and can prove deleterious for the safety of the NPPs. A Software Bill of Materials (SBOM) provides a detailed list of the various components and their dependencies in software, which helps in vulnerability and risk assessment for cyber hygiene and situational awareness. For an NPP, the process of generating an accurate SBOM report can be complex due to the legacy systems and firmware binaries involved. While most current SBOM tools are focused more on modern internet technology software, this research provides insights and guidelines for an NPP to generate an accurate and efficient SBOM. Here, the paper proposes a new methodology to help NPPs categorize software and use appropriate tools to generate SBOMs for their digital I&C systems.

SBOM↗

Impact of cyber attacks on distributed compressive sensing based state estimation in power distribution grids

Modern power distribution grids suffer from multiple vulnerabilities due to the tight integration between the physical system and the cyber infrastructure. Sophisticated and malicious cyber attacks continue to adversely impact the grid operation leading to performance degradation, service interruption, and grid failure. State estimation plays an essential role in grid monitoring and advancing cyber-attack situational awareness. In this regard, this paper first proposes a distributed compressive sensing (CS) state estimation approach for an unobservable distribution grid. Further, the proposed distributed CS approach divides the distribution grid into sub-areas to perform local state estimation. Then an alternating direction method of multipliers (ADMM) based iterative information exchange among neighboring areas is employed to complete the estimation process. In this estimation process, the impact of loss of measurement data, false data injection (FDI), replay, and neighborhood cyber-attacks is analyzed. Extensive simulations are performed on the IEEE 37-bus and IEEE 123-bus standard networks to demonstrate the algorithm’s robustness to the aforementioned cyber-attacks. A quantitative analysis of computational complexity and simulation time of the distributed CS based approach is also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Q 10 of in situ microbial soil respiration varies with mean annual temperature, precipitation, pH, and plant cover: a meta-analysis and spatial prediction of Q 10

The temperature sensitivity of soil microbial respiration, commonly quantified using the Q 10 coefficient, is a key parameter in carbon cycle models. Uncovering how environmental factors affect in situ Q 10 values can therefore provide critical insight into potential shifts in global carbon stocks under climate change. We collected data from previously published field experiments that measured soil microbial respiration across a range of temperatures. We hypothesized that the Q 10 coefficient of in situ soil microbial respiration would vary based on environmental factors including mean annual temperature (MAT), mean annual precipitation (MAP), plant cover type, pH, soil C:N, and latitude. Linear regression revealed that Q 10 correlates negatively with MAT and MAP and positively with pH and absolute latitude. Additionally, average Q 10 varied significantly across different plant cover types; it was highest in mountain grasslands and lowest in tropical moist forests. Variation in microbial Q 10 across environmental factors may arise from underlying mechanisms such as enzyme kinetics, substrate availability and complexity, and microbial adaptation. To capture patterns in Q 10 more comprehensively, we developed a multiple linear regression model of Q 10 based on the most individually significant environmental drivers and applied it to public datasets to generate a global map of predicted Q 10 . Q 10 was higher in high-latitude and high-altitude regions, where large permafrost carbon stores are vulnerable to thawing and decomposition. We also compared fits between the Q 10 equation and a model produced from macromolecular rate theory (MMRT). We found that the MMRT model had the superior fit and may be better suited to model temperature sensitivity of complex biological reactions. Overall, our results emphasize that relationships between microbial Q 10 and environmental variables should be accounted for in climate models. Incorporating these variations in the Q 10 parameter, rather than using a fixed value, will help predict whether CO 2 emissions will be buffered or exacerbated by soil microbial respiration under climate change.

54 ENVIRONMENTAL SCIENCES↗

Origins of Acid-Gas Stability Behavior in Zeolitic Imidazolate Frameworks: The Unique High Stability of ZIF-71

Zeolitic imidazolate frameworks (ZIFs) are promising materials for industrial process separations, but recent literature reports have highlighted their vulnerability to acid gases (e.g., SO 2 , CO 2 , NO 2 , H 2 S), often present in practical applications. While previous work has documented the widely varying stability behavior of many ZIFs under varying (humid and dry) acid gas environments, efforts to explain or correlate these experimental observations via empirical descriptors have not succeeded. A key observation is that ZIF-71 (RHO topology) is an extraordinarily stable ZIF material, retaining both structure and porosity under prolonged humid SO 2 exposure whereas many other well-known ZIFs with different linkers and topologies (such as ZIF-8) were shown to degrade. Through a combination of hybrid quantum mechanics/molecular mechanics (QM/MM) based methods and statistical mechanical models, we successfully explain this important experimental observation via atomistic investigations of the reaction mechanism. Our holistic approach reveals an ~9 times lower average defect formation rate in ZIF-71 RHO compared to ZIF-8 SOD, leading to the conclusion that the observed experimental stability of this material rises from kinetic effects. Moreover, our analysis reveals that differing stability of the two materials is determined by the distributions of acid gas molecules, which is difficult to capture using empirical descriptors. Furthermore, our results suggest wider applicability of the present approach, toward identifying tuned functional groups and topologies that move the acid gas distributions away from more reactive sites and thus allow enhanced kinetic stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermal shock resistance of multilayer silicon carbide receiver tubes for 800°C molten salt concentrating solar power application

CSP power tower receiver systems during rapid transient weather periods can be vulnerable to thermal shock conditions from rain that which can facilitate the onset of leaks and failures that can have catastrophic consequences. Silicon carbide (SiC) materials have attractive receiver application characteristics for being light weight, having high-strength and excellent thermal shock resistance performance which make them a particularly good fit for receiver absorber materials in CSP. In this investigation, the performance characteristics of Ceramic Tubular Products (CTP) SiC ceramic matrix composite (CMC), multilayered tubes were explored with respect to thermal shock performance for solar receiver applications in next generation CSP plants. Here, thermal shock testing was performed at the Sandia National Laboratories (SNL) Solar Furnace facility using a dynamic stage and thermal shock tube test setup. The tubes tested under incident solar heat flux of 100 W/cm2 were heated with inner tube temperatures reaching approximately 800 °C, with outer temperatures exceeding or just reaching 1000 El for the multilayer and monolithic SiC tubes respectively. The tubes were then quenched with simulated rain. The tubes were then cooled and subjected to hoop stress analysis using an Instron device to assess their subsequent mechanical strength. Furthermore, the on-sun study experimental results indicate an average of 24.2% and 97% higher hoop strength for the CMC tubes than those composed of monolithic SiC and aluminum oxide (A1203) respectively.

14 SOLAR ENERGY↗

Autonomous Tools for Attack Surface Reduction (Final Report)

The electric power grid is a complex critical infrastructure that forms the lifeline of modern society, and its secure and reliable operation is of paramount importance to national security and economic wellbeing. However, recent findings documented in authoritative sources indicate the threat of cyber-based attacks growing in numbers and sophistication. However, securing the grid against stealthy cyberattacks is a challenging task due to legacy nature of the infrastructure coupled with dynamic nature of threat landscape and ever-growing sophistication of the adversaries. Additionally, the grid’s attack surface continues to grow with the increased dependence on digital communications and control that now extends to each consumer through smart meters and distributed energy resources. Unfortunately, this expansive surface increases the grid’s vulnerability and further exposes critical control systems in both substations and control centers. To respond to this emerging need, we had successfully assembled an interdisciplinary team with academic- industry partnership to successfully conduct research, development, evaluation, demonstration, and commercialization of attack surface reduction tools, whose goal was to significantly reduce the cyber attack surface in the North American power grid. Our proposed project was a synergistic collaborative effort leveraging the synergistic expertise of the team members across power systems, cyber security and CPS security, testbeds, field deployments and demonstration, and successful commercialization. The following are the specific tasks that have been successfully completed two phases (2016-2020). Phase I: Task 1: Developed and implemented a robust Project Management and Data Management Plan, coupled with a well thought out Risk Mitigation Plan. Task 2.1: Developed a comprehensive framework that continually assesses and autonomously reduces the attack surface for the power grid control environment spanning across substations, control center and the SCADA network to significantly reduce the risks of cyber attacks. Task 2.2: Developed attack surface analysis techniques, metrics, and tools that assess the attack surface at multiple levels including the control center, substations, and the SCADA network. Task 2.3: Developed attack surface reduction techniques and tools that dynamically reduce attack surface and hence increase attacker’s cost without interfering in the critical functions of the system. Task 2.4: Prototyped, implemented, and quantitatively evaluated/validated the techniques and tools on a realistic industrial CPS security testbed environment by leveraging the unique resources of the team. Task 3: Developed Commercialization plan to transition the developed tools into power system industry stakeholders for a broader adoption by leveraging the expertise of our industrial members. Phase II: Task 4: Successfully completed field demonstration, verification, and evaluation of the effectiveness of the attack surface analysis and reduction techniques on a realistic utility testbed environment. This also involved the development of realistic scenarios, sound metrics, data sets, evaluation criteria, and documentation. Technology integration & Field demonstration: The project had significantly advanced the state-of-the-art research and practice in improving the cybersecurity of our nation’s power grid infrastructure against cyber threats. In particular, the proposed, designed, and deployed attack surface analysis and reduction algorithms and tools have contributed to significantly reducing the exposure and risk of the devices, substations, and the integrated SCADA/EMS/ DMS grid environment to cyber threat. Strong demonstration and evaluation techniques have verified the feasibility of the developed techniques on realistic cyber-physical testbeds and utility partner's real grid environment, and collaborative research and evaluation of attack surface reduction techniques (for wide-are monitoring and control) within a vendor (GE) EMS platform. The Attack Host Analyzer (AHA) tool that was developed through this project was made available through GitHub.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Impact of cyberattacks on safety and stability of connected and automated vehicle platoons under lane changes

Connected and automated vehicles (CAVs) offer a huge potential to improve the operations and safety of transportation systems. However, the use of smart devices and communications in CAVs introduce new risks. CAVs would leverage vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication, thus providing additional system access points compared to traditional systems. Automation makes these systems more vulnerable and increases the consequences of cyberattacks. This study utilizes an infrastructure-based communication platform consisting of cooperative adaptive cruise control and lane control advisories developed by the authors to perform cyber risk assessment of CAVs. The study emulates three types of cyberattacks (message falsification, dedicated denial of service, and spoofing attacks) in a representative traffic environment consisting of multiple CAV platoons and lane change events to analyze the safety and stability impacts of the cyberattacks. Simulation experiments using VISSIM reveals that traffic stream and CAV string is unstable under all three types of cyberattacks. The worst case is represented by the message falsification attack. Increases in volatility are observed over a no attack case, with variations increasing by an average of 43%–51% along with an increase of over 3000 crash conflicts. Similarly, lane change crash conflicts are observed to be more severe compared to rear end crash conflicts, showing a higher probability of severe injuries. Further, the case of slight cyberattack on a single CAV also creates significant disruption in the traffic stream. Analysis of variance (ANOVA) reveals the statistical significance of the results. Furthermore, these results pave the way for future design of secure systems from a monitoring perspective.

97 MATHEMATICS AND COMPUTING↗

Assessing mean climate change signals in the global CORDEX-CORE ensemble

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25 $\,\mathrm {km}$ (0.22 $^{\circ }$ /jats:inline-formula>) versus 50 $\,\mathrm {km}$ (0.44 $^{\circ }$ )) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

54 ENVIRONMENTAL SCIENCES↗

Individual and Collective Strategies to Limit the Impacts of Large Power Outages of Long Duration

As modern society becomes ever more dependent on the availability of electric power, the costs that could arise from individual and social vulnerability to large outages of long duration (LLD-outages) increases. During such an outage, even a small amount of power would be very valuable. Here, this article compares individual and collective strategies for providing limited amounts of electric power to residential customers in a hypothetical New England community during a large electric power outage of long duration. We develop estimates of the emergency load required for survival and assess the cost of strategies to address outages that last 5, 10, and 20 days in either winter or summer. We find that the cost of collective solutions could be as much as 10 to 40 times less than individual solutions (less than $2 per month per home). However, collective solutions would require community-wide coordination, and if local distribution system lines are destroyed, only individual back-up systems could provide contingency power until those lines are repaired. Costs might be reduced if more robust distributed generation were employed that could be operated continuously with the ability to sell power back to the grid. Our cost-effectiveness analysis only assesses what could be done, developing estimates of preparedness cost. A decision about what should be done would require additional input from a range of stakeholders as well as some form of analytical deliberative process.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Conflicts of Greens’ in Renewable Energy Landscapes: Case Studies and a Planning Framework

Reducing greenhouse gas emissions (GHG) through renewable energy deployment is a goal for many cities and nations to mitigate the effects of a rapidly changing climate while securing energy needs. Given national and state level policies on green energy to achieve GHG reduction targets, localities are considering utility-scale renewable energy (USRE) facilities on remote lands, rural areas, oceans, coastal waters and large rivers to meet the energy needs for urban residents and industries. Although these USRE facilities generate much “greener” electricity than fossil fuel power plants, locating them can pose conflicts with wildlife, including endangered, threatened and/or special status species, and the habitats that support wildlife populations (Brunette et al., 2013; Gasparatos et al. 2016; Mulvaney 2017), which lead to a “Conflict of Greens” (Ko et al., 2011). In addition to ecological impacts, conflicts over social and cultural resources in local communities lead to concerns over environmental justice, in this context “energy justice,” where negative environmental, social, and economic impacts of energy projects fall more heavily upon marginalized, vulnerable, or indigenous communities. The Pacific Rim region is a center of major and growing economies, and it has become a battlefield for competing “green” objectives. In addition to progressive renewable energy goals, such as in California, Hawaii, and Taiwan, countries around the Pacific Rim have the majority of the growth in manufacturing of wind and solar energy devices and also some of the highest levels of renewables deployment with China, India, and the US leading the way in wind and solar installations. Developing renewable energy source in the ocean such as offshore wind, tidal, and wave energy, are beginning to add to this mix. Given this challenge, the APRU SCL energy working group provides six case studies that address questions about the “Conflict of Greens” across the Pacific Rim including South Korea, Taiwan, and the United States (California, Hawaii, and Massachusetts). The literature review highlights the emerging ecological, social, and economic aspects of conflicts over siting renewables on the landscape. Using case studies, we examine the trial and errors in least-conflict spatial planning, data collection and analysis, public participation in decision-making, mitigation, social planning for energy transitions, and multi-scalar approaches. Lastly, we recommend interdisciplinary policy, planning, and design actions for sustainable energy landscapes across the Pacific Rim and beyond.

green versus green, renewable energy↗

Sustainability assessment of alternative jet fuel for the U.S. Department of Defense

The United States Department of Defense (DoD) is considering replacing the 2.8 billion gallons of petroleum jet fuel consumed within the continental United States (CONUS) annually with alternative jet fuels to reduce vulnerability to price and supply fluctuations and improve sustainability. We evaluate the feasibility of replacing DoD CONUS jet fuel with alternative jet fuel from domestic feedstocks and assess the cost, greenhouse gas (GHG) emissions, energy balance, land, water, and fertilizer impacts of nine alternative jet fuel pathways. The feedstocks include terrestrial crops (soy, corn, wood, and grass), marine microalgae, and by-products (forestry residue, municipal solid waste, and waste oil) converted by extraction, fermentation, or thermo-chemical conversion, paired with upgrading steps. We found that domestic biomass feedstocks can meet the DoD CONUS jet fuel demand without significantly affecting food supply. Alternative pathways cost more than petroleum jet fuel ($0.78 l -1 and emitting 89 g CO 2 equivalent (CO 2e ) MJ -1 ), but many lowered GHG emissions. The forestry residue and waste oil pathways yielded the lowest costs ($\$0.92$ and $\$0.82$ l -1 , respectively), decreased emissions (23 and 35 g CO 2 e MJ -1 , respectively), and had negligible effects on land, water, and fertilizer resources. Finally, tradeoffs among sustainability metrics are further explored with a sensitivity analysis and by evaluating carbon-cost scenarios.

09 BIOMASS FUELS↗

EVSE Cybersecurity and Resilience

Consequence-driven Cybersecurity Analysis for Extreme Fast Charging Electric Vehicle Infrastructure Electric vehicle (EV) development and associated charging infrastructure are expected to advance rapidly. Thirty percent of all global vehicle sales may be EVs and hybrid EVs by 2025, and they will rely on increasingly sophisticated strategies for grid integration. Next-generation EV charging infrastructure is expected to include interconnected renewable resources, such as photovoltaic (PV) arrays and battery storage systems, along with grid-edge devices. Although distributed energy resources (DERs) are useful in several ways, such as peak shaving at high demand times and backup supply for added resilience, the integration of vehicle charging and DERs could create more avenues for cyberattack. Physical and/or remote access to EV charging station components, including charge ports, power electronics, controllers, and local generation (e.g., PV and energy storage) could be paths to cause power fluctuations, leading to altered operations at the charging station, escalated privileges to administrative systems, exfiltration of financial information (including personally identifiable information), and reduced grid stability. One compromised EV supply equipment component can open the door to a variety of exploitable vulnerabilities. Cloud computing and mobile application control have the potential to expand the threat surface to non-repudiation and firmware integrity challenges. Vendor clouds have access to hundreds of chargers, and if compromised, can scale the attack surface exponentially. The high power and voltage levels of xFC infrastructure (e.g., 400 kW at 1000- V DC) increase the hazards and ability to impact the grid and vehicles more than lower-power charging systems. Legacy communications systems and protocols could also put EV infrastructure at risk of cyberattacks requiring a robust patch management process. Communications networks link EVs and chargers to several stakeholders - including charging station operators, grid operators, vendors/manufacturers, and aggregators - who have both physical and network access to share information for control, monitoring, and analytics. Information in these networks that is vulnerable to compromise includes the state of charge, charging duration, payment information, electricity price, and load control. Analyzing and prioritizing these interconnections risks could help address cybersecurity related to data leakage and manipulation.

charging↗

Cyber-physical security framework for Photovoltaic Farms

With the evolution of PV converters, a growing number of vulnerabilities in PV farms are exposing to cyber threats. To mitigate the influence of cyber-attack on PV farms, it is necessary to study attacks' impact and propose detection methods. To meet this requirement, a cyber-physical security framework is proposed for PV farms. Data integrity attacks (DIAs) are studied on different control loops. As μPMU is gaining in popularity, a lower sampling rate of μPMU data is applied to develop a detection algorithm. We have evaluated two data-driven methods, which are support vector machine (SVM) and long short-term memory (LSTM). Lastly, the data-driven methods verify the feasibility of μPMU data in attack detection.

Attack Impact Analysis↗

Comprehensive Study of the Potential of Extracting and Processing Critical Minerals from Coal-Based Resources - Phase I

The Phase I report prepared for the Department of Energy addresses U.S. Executive Order 13817 titled A Federal Strategy to Ensure Secure and Reliable Supplies of Critical Minerals, issued on December 20, 2017, that lists 35 critical minerals that are vulnerable to supply disruption. A comprehensive review of each of the minerals was conducted to determine the criticality based primarily on extractability from coal-based resources. Several other factors were also considered such as gaps in supply and demand, use in current technology, and the existence of viable substitutes. It was determined that the critical minerals that show highest potential for extraction from coal-based resources are lithium, rare earth elements (REEs), cobalt, and manganese. All four of the critical minerals listed serve an important role in the technology industry, have few substitutes, and have a heavy import reliance. Most notably are lithium, which is widely used in the electric vehicle industry, and the REEs which can be found in virtually all electronic devices. The research of critical mineral extraction from coal-based resources was completed using a combination of literature review from public sources as well as cooperation from coal mines and power plants across the United States. Samples collected from six different geographical locations across the U.S. were subjected to sample preparation (i.e., pH measurement, moisture content, particle size analysis) and characterization studies using Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS) and Scanning Electron Microscopy, Energy Dispersive X-Ray Spectroscopy (SEM-EDX) instruments. 27 samples of coal waste materials such as refuse, sludge, and fly ash were tested to characterize the rare earth element concentration by total rare earth elements (TREEs), heavy rare earth elements (HREEs), and light rare earth elements (LREEs). Of the 27 samples tested, 22 contained a TREE concentration higher than the threshold of 300 ppm, which is considered a viable feedstock material. 3 samples contained less than 300 ppm of TREEs; however, they were within 20 ppm of the threshold, and could potentially be considered viable sources in the future pending the advancement of more efficient extraction technologies. 2 of the 27 samples had significantly low TREE concentrations, which does not imply any potential for being a source for REEs. For the minerals identified as most critical in the literature review, a conceptual process flow diagram (PFD) was developed for their extraction from different coal-based feedstocks. The process targets selective recovery of one commodity (i.e., rare earths, lithium, cobalt, and manganese) via several hydrometallurgical separation methods. By identifying potentially extractable coal-based critical mineral resources, a study of the current and future market environments for each critical mineral, and a review of current processing methodologies for critical mineral extraction from coal-based resources, the foundation has been laid to further characterize and explore new resources and extraction techniques. As reliance on technologies in industries such as the production of electronic devices, batteries, and alloys containing critical minerals utilizing critical minerals continues to increase, a sound understanding of our nation’s dependence on and even the global criticality of certain critical minerals, will serve as a catalyst for innovation in virtually all fields of science.

01 COAL, LIGNITE, AND PEAT↗

Quantifying agricultural productive use of energy load in Sub-Saharan Africa and its impact on microgrid configurations and costs

The use of advanced energy technologies for agricultural purposes—such as irrigation, refrigeration, crop processing, and egg incubation—has the potential to increase crop yield, reduce vulnerability to changing precipitation patterns, increase shelf life, strengthen income and employment opportunities in rural areas, and reduce emissions by displacing fossil fuel-based technologies. These productive uses of energy (PUE) in remote areas could potentially be powered by microgrids that additionally serve otherwise unelectrified communities, most of which are located in rural Sub-Saharan Africa. Here, in this paper, we use high-resolution geospatial data to estimate the end-use electricity demand for a range of agricultural PUE across Sub-Saharan Africa, and we share these data in an open-access mapping tool. Next, we use REopt®, a techno-economic optimization model of energy systems, to determine the cost and system sizing implications of incorporating agricultural PUE into microgrid designs in Kenya and Zambia. We estimate the upper bound of agricultural PUE demand for irrigation, milling, shelling, refrigeration, and egg incubation across Sub-Saharan to be 16.8 TWh/yr. We find that incorporating local agricultural PUE into microgrid system designs increases the required system sizing while having minimal impact on the levelized cost of energy of these systems. Our analysis is the first to demonstrate the PUE potential in the agricultural sector at a 10x10-kilometer resolution across Sub-Saharan Africa and to show, at scale, how site-specific PUE can impact the cost and sizing of microgrids that are otherwise deployed to serve local household and community load.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Influence of extreme temperature conditions on CO 2 direct air capture using amino-acid solutions

Geological features play a pivotal role in determining the feasibility of deploying CO₂ direct air capture (DAC) technologies, primarily because they influence the availability of cost-effective energy sources, such as natural gas and geothermal energy, and also due to the potential for CO₂ sequestration. Many regions face challenges due to variable weather conditions including seasonal temperature fluctuations, high or low humidity, and sub-ambient temperatures. These extremes can reduce DAC performance or even lead to catastrophic events. Aqueous solvents considered for DAC systems are particularly vulnerable to seasonal variations in colder climates, where the solvent may underperform or freeze. It is therefore essential to investigate the CO₂ capture efficiency of aqueous solvents across a broad range of environmental temperatures, spanning sub-zero to hot conditions (>30 °C). In this study, DAC operation is examined using a high-flux solvent–air crossflow contactor under two major weather scenarios: (i) cold conditions below 0 °C and (ii) hot conditions above 30 °C. A parametric study is conducted to investigate the contactor performance regarding CO₂ removal efficiency, uptake capacity, and reaction kinetics versus temperature when the air velocity through the contactor exceeds 1 m/s. The efficacy of the contactor is systematically investigated using various anti-freeze amino-acid solvent formulations. A mass-transfer mechanistic model is developed to assess the process performance over a wide temperature range and propose scalable design guidelines. Machine learning is also employed to identify key parameters affecting the CO₂ capture efficiency. It is shown that air velocity and temperature are the primary factors influencing CO₂ uptake. Based on performance data obtained under subfreezing temperatures, a technoeconomic analysis is conducted to evaluate the feasibility of using aqueous solvents in seasonal cold regions. In conclusion, the findings of this study provide valuable insights into siting considerations for deploying solvent-based DAC, thereby contributing to the advancement of sustainable carbon removal solutions.

Air–liquid contactor↗

Sister Rod Destructive Examinations (FY23): Appendix J: Leaching of High Burnup Used Nuclear Fuel in Deionized Water

The leaching experiment aims to understand the trends in the radiolysis-enhanced dissolution of HBU SNF when exposed to water (e.g., in-reactor or in-pool cladding failures). Specimens from a baseline M5-clad rod and a heat-treated M5 rod were cut from the fractured CIRFT specimens and placed in 100 mL deionized water for a period of 128 days. Both radial and axial sections were cut to provide different surface areas of fuel in contact with the leachate. During the four-month exposure period, aliquot samples of the leachate were analyzed using gamma spectroscopy and inductively coupled plasma - mass spectrometry (ICP-MS). The analysis quantified the amount of fuel leached into the solutions and provided individual isotopic release fractions (of 30+ isotopes) which were compared as a function of time and surface area of the fuel exposed. Consistent with existing literature, the leaching followed a trend in which isotopes of certain elements such as Cs and Mo were among the first species in the matrix to dissolve, and with the highest release rates. This was followed by a gradual matrix dissolution consisting of uranium and other actinides and a slower-than-matrix release from some isotopes, including Ru and Rh. It was also observed that the circumferential samples having less exposed fuel surface area (to begin with) leached more than the axial samples for a majority of the isotopes during the timespan of the study. Previous experiments were conducted by decladding or exposing the pellet-clad surface completely, but the samples used in this study retained the cladding. One possible explanation for the higher leaching rate of the circumferential samples is that the pellet-clad interface, which has a greater density of grain boundaries and defects, may be the most vulnerable area to leaching of fuel in the presence of water.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗