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At least 145 records · Page 8

Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana

Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3, followed by PurpleAir PA-II (4.54 μg/m3) and Clarity Node-S (13.68 μg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.

Humidity

QuikSCAT Mission

The QuikSCAT Mission of the National Aeronautics and Space Administration (NASA) is planned for launch in Spring 1999, reducing the data gap in ocean-wind vector created by the loss of the NASA Scatterometer (NSCAT) on the Japanese Advanced Earth Observing Satellite (ADEOS) spacecraft. The NSCAT instrument ceased functioning when ADEOS failed on June 30, 1997. The follow-on scatterometer for monitoring ocean winds, called SeaWinds, is scheduled for launch on the Japanese ADEOS-II spacecraft in 2000. The Jet Propulsion Laboratory (JPL) has met the challenge to develop and integrate the instrument, ground system, and launch vehicle in less than a year. QuikSCAT will use pencil-beam-antennas in a conical-scan design which is more compact than the fixed fan-beam design of NSCAT. The antenna will radiate ku-band microwaves at 40 and 46 incident angle and measure the backscatter power across a continuous 1800 km swath. QuikSCAT is capable of providing wind-speed and wind-direction at 25 km resolution over 92 percent of the Earth's ice-free oceans every day, under both clear and cloudy conditions. Standard data products will be delivered to science users within 14-days, and fast data products will be available to operational users within two hours of data acquisition. QuikSCAT will be managed by JPL for the NASA's Office of Earth Science Enterprise. It will be launched from Vandenberg Air Force Base, aboard a Titan II vehicle. The satellite core-systems was built by Ball Aerospace Systems Division, Boulder, CO. The operation of QuikSCAT is expected to overlap with ERS-2 and SeaWinds. Spaceborne scatterometers have demonstrated a broad spectrum of scientific applications, including weather systems, wind-driven ocean circulation, land vegetation, polar ice morphology and dynamics, and Ocean-atmosphere-ice interaction.

Liu, W. Timothy

Test Plan for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change. One of the major objectives of CLARREO is to advance the accuracy of SI traceable absolute calibration at infrared and reflected solar wavelengths. This advance is required to reach the on-orbit absolute accuracy required to allow climate change observations to survive data gaps while remaining sufficiently accurate to observe climate change to within the uncertainty of the limit of natural variability. While these capabilities exist at NIST in the laboratory, there is a need to demonstrate that it can move successfully from NIST to NASA and/or instrument vendor capabilities for future spaceborne instruments. The current work describes the test plan for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the testing and evaluation of calibration approaches , alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result of efforts with the SOLARIS CDS will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections. The CLARREO mission addresses the need to observe high-accuracy, long-term climate change trends and advance the accuracy of SI traceable absolute calibration. The current work describes the test plan for the SOLARIS which is the calibration demonstration system for the reflected solar portion of CLARREO. SOLARIS provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections.

Thome, Kurtis

Large spatiotemporal variability in aerosol properties over central Argentina during the CACTI field campaign

Abstract. Few field campaigns with extensive aerosol measurements have been conducted over continental areas in the Southern Hemisphere. To address this data gap and better understand the interactions of convective clouds and the surrounding environment, extensive in situ and remote sensing measurements were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign conducted between October 2018 and April 2019 over the Sierras de Córdoba range of central Argentina. This study describes measurements of aerosol number, size, composition, mixing state, and cloud condensation nuclei (CCN) collected on the ground and from a research aircraft during 7 weeks of the campaign. Large spatial and multiday variations in aerosol number, size, composition, and CCN were observed due to transport from upwind sources controlled by mesoscale to synoptic-scale meteorological conditions. Large vertical wind shears, back trajectories, single-particle measurements, and chemical transport model predictions indicate that different types of emissions and source regions, including biogenic emissions and biomass burning from the Amazon and anthropogenic emissions from Chile and eastern Argentina, contribute to aerosols observed during CACTI. Repeated aircraft measurements near the boundary layer top reveal strong spatial and temporal variations in CCN and demonstrate that understanding the complex co-variability of aerosol properties and clouds is critical to quantify the impact of aerosol–cloud interactions. In addition to quantifying aerosol properties in this data-sparse region, these measurements will be valuable to evaluate predictions over the midlatitudes of South America and improve parameterized aerosol processes in local, regional, and global models.

54 ENVIRONMENTAL SCIENCES

Advancing an integrated understanding of land–ocean connections in shaping the marine ecosystems of coastal temperate rainforest ecoregions

Land and ocean ecosystems are strongly connected and mutually interactive. As climate changes and other anthropogenic stressors intensify, the complex pathways that link these systems will strengthen or weaken in ways that are currently beyond reliable prediction. In this review we offer a framework of land–ocean couplings and their role in shaping marine ecosystems in coastal temperate rainforest (CTR) ecoregions, where high freshwater and materials flux result in particularly strong land–ocean connections. Using the largest contiguous expanse of CTR on Earth—the Northeast Pacific CTR (NPCTR)—as a case study, we integrate current understanding of the spatial and temporal scales of interacting processes across the land–ocean continuum, and examine how these processes structure and are defining features of marine ecosystems from nearshore to offshore domains. We look ahead to the potential effects of climate and other anthropogenic changes on the coupled land–ocean meta-ecosystem. Finally, we review key data gaps and provide research recommendations for an integrated, transdisciplinary approach with the intent to guide future evaluations of and management recommendations for ongoing impacts to marine ecosystems of the NPCTR and other CTRs globally. In the light of extreme events including heatwaves, fire, and flooding, which are occurring almost annually, this integrative agenda is not only necessary but urgent.

54 ENVIRONMENTAL SCIENCES

Assessing hydrogen supply chains: An integrated review of leakage and energy efficiency studies

This paper examines hydrogen leakage and efficiency across the supply chain for liquid, gaseous, and mixed hydrogen systems. These factors are crucial for assessing hydrogen's role in mitigating emissions and facilitating a clean energy transition. Drawing on a comprehensive review of existing literature and model-based analysis, the study compiles leakage rates and efficiency metrics at each stage of the supply chain: production, storage, transmission, distribution, and end-use. These data inform system scenarios that estimate the impact of leakage on overall performance and climate benefits. The analysis also identifies persistent data gaps, particularly for liquid and mixed system configurations, and outlines priorities for future research. A comparison of hydrogen system types shows that gaseous pathways generally achieve the highest efficiencies (28 %–39 %) and the lowest leakage rates (∼4.5 %) across the supply chain. Liquid hydrogen systems, while favorable for long-distance and high-volume transport due to their higher energy density, exhibit lower efficiency (∼28 %) and a greater leakage potential (∼12 %). Mixed systems, which combine gaseous and liquid elements (e.g., pipeline transmission followed by liquefaction and truck distribution), show compounded energy losses and moderate-to-high leakage rates (6.8 %–9.4 %), highlighting trade-offs associated with added system complexity. The study highlights opportunities for technological advancements, including optimizing liquefaction, enhancing insulation for storage and transportation, and refining refueling equipment. These improvements are crucial for maximizing the climate benefits of hydrogen. The results offer actionable insights for researchers, industry, and policymakers working to develop low-leakage, high-efficiency hydrogen infrastructure.

08 HYDROGEN

Dopant, coating, and grating effects in silica optical fibers under extreme neutron irradiation

Radiation effects on fiber Bragg gratings (FBGs) have been studied but data gaps related to the effects of displacement damage resulting from high fast neutron fluence remain. In this work, Type-I and Type-II FBGs inscribed in optical fibers with various core dopants (Ge and F) and fiber coatings (acrylate, polyimide) were monitored in situ during 75 days of neutron irradiation to a peak fast (>0.1 MeV) neutron fluence of 3 X 10 21 n fast /cm 2 . Further, the reflected intensity of the Type-I FBGs inscribed in a Ge-doped core fiber decreased by > 30 dB within 7 h of irradiation (10 19 n fast /cm 2 ), whereas Type-II FBGs inscribed in a pure silica core fiber eventually approached >40 dB attenuation after accumulating a fast neutron fluence on the order of 10 20 n fast /cm 2 . Type-II FBGs inscribed in F-doped core fiber improved stability: the attenuation approached an equilibrium value in the range of 10 to 20 dB.

47 OTHER INSTRUMENTATION

In-situ strain behavior and BISON simulations of Zircaloy cladding subjected to temperature cycling separate-effects tests in a steam environment

Understanding fuel system performance during anticipated transients without scram (ATWSs) in boiling water reactors (BWRs) is necessary for refining current and future safety limits. High-fidelity material models and simulations are fundamental to rigorous assessment of zirconium-based cladding performance. However, experimental thermomechanical data during simulated ATWSs to validate these modes are limited. To provide relevant in-situ data, Zircaloy-4 cladding was subjected to cyclic heating in a steam environment to simulate an out-of-pile BWR ATWS. Digital image correlation was used to capture the cladding strain behavior in-situ for comparison against simulations using the BISON finite element code. Conventional high-temperature models were compared using multiple schemes to gain a better understanding of the applicability of three BISON models to BWR ATWS: (1) the default combination of creep models in BISON, (2) the high-temperature Erbacher model alone, and (3) the low-temperature Limback-Andersson model alone. The cases run with the Limback-Andersson model alone produced the lowest root mean square error (RMSE). The lowest RMSE for the Limback-Andersson model alone was 0.659%, and the highest RMSE reported was 4.22%. A data gap within the model in the temperature regime of interest was also identified, and to account for this gap, the current model in BISON is linearly interpolated between two separate datasets. In conclusion, this evaluation highlights the need to either develop a new model or to improve the existing model to capture transient creep effects resulting from a cyclic temperature transient.

Anticipated transient without SCRAM

Comparative post-irradiation examination of high burnup U-19Pu-10Zr: Assessing steady-state irradiation behavior against historical and modeled fuel performance

Here, the development of next-generation sodium-cooled fast reactors necessitates comprehensive research on metallic fuels to maximize economic performance while ensuring safe operation. In this study, we investigated the steady-state irradiation behavior of two high burnup U-19Pu-10Zr fuel pins, DP-36 and DP-40, in preparation for planned safety testing. Post-irradiation examination (PIE) was performed to quantify fuel column elongation, regions of low-density at the top of the fuel column, pin deformation, fission product distribution, fractional fission gas release, microstructural evolution, and fuel constituent redistribution. Benchmarking against existing PIE data from U-19Pu-10Zr fuel pins irradiated in EBR-II revealed consistent patterns in fuel column elongation and cladding diametral strain. However, both pins exhibited longer low-density structures, and destructive examination of DP-36 revealed more complex constituent redistribution patterns compared to previously reported data for ternary fuel pins. The steady-state irradiation of both pins was also modeled using BISON. Comparisons of PIE results with modeled predictions showed overall agreement in fractional fission gas release but consistent overestimation of axial and radial swelling due to gaseous and solid swelling models. These findings underscore the critical importance of pre-test characterization on test and sibling pins to accurately capture steady-state fuel behavior ahead of transient testing, thus establishing a baseline for post-test comparison. Additionally, these analyses identified key data gaps that warrant further investigation to improve the understanding and prediction of fuel swelling, thereby enhancing the synergy between modeling and experimental efforts in supporting accident testing.

BISON

The state of the art for neutron irradiation experiments from the perspective of the High Flux Isotope Reactor (HFIR)

Irradiation experiment campaigns are critical to advancing nuclear energy technologies by providing data on material performance under relevant radiation conditions. Successful irradiation experiments require integrated design efforts that balance technical goals with facility constraints. Here, this paper presents an expert-informed overview of irradiation experiment design at the High Flux Isotope Reactor. It addresses the nuclear materials research and irradiation experiment communities to guide them toward developing technically sound, facility-compatible campaigns. The High Flux Isotope Reactor is a multipurpose reactor supporting isotope production, neutron scattering, and materials testing. Its high, steady-state neutron flux is ideal for irradiation experiments, but successful execution demands coordinated thermal, structural, and reactor physics analyses. The paper outlines the complete development workflow from concept definition and design optimization to safety qualification and post-irradiation examination. Standardized capsule platforms are also discussed in terms of flexibility, specimen capacity, and thermal performance. Common failure modes such as unanticipated geometric variations, can impact temperature-dose profiles and compromise data reliability. Therefore, detailed thermal modeling and accurate as-built characterization are essential for meaningful post-irradiation data interpretation. Key recommendations include early engagement all stakeholders, clearly defined design expectations, and alignment of specimen geometries with post-irradiation examination capabilities. This approach reduces design iterations, enhances data quality, and supports more efficient use of irradiation resources. Strategic and well-planned irradiation testing not only improves individual campaign success but also accelerates the deployment of advanced nuclear technologies. By closing critical data gaps and reducing development risks, the nuclear materials community can more effectively contribute to the future of clean, resilient energy systems.

Experiments

How Representative Are Uncrewed Aircraft System Measurements of the Convective Boundary Layer?

Abstract Uncrewed aircraft systems (UAS) demonstrate significant potential for filling data gaps in the atmospheric boundary layer. However, the extent to which UAS observations—typically vertical profiles taken over 15 min—are representative of the boundary layer as a whole remains poorly characterized. Using large eddy simulations (LES) of the daytime convective boundary layer (CBL), we quantify random errors in UAS measurements that occur due to insufficient statistical convergence of the time average to the true ensemble mean. Random errors in first‐order moments increase as the CBL becomes increasingly unstable, and are largest near the surface for most quantities. Errors are on the order of 2–6 m for wind speed, 15–60 for wind direction, 0.2–3 K for potential temperature, and 0.1–1 g for specific humidity, with errors in turbulent fluxes on the order of 50%–100%. Sampling strategies that mitigate random errors are discussed in light of our results.

Greene, Brian R. [Now at Verisk Extreme Event Solu

The Imprint of Southern Ocean Storms on Modeled Surface Chlorophyll, Their Drivers and Satellite Biases

Southern Ocean (SO) phytoplankton chlorophyll is highly variable on sub-seasonal time scales. Although the SO is the windiest ocean basin globally, it is not conclusively understood how storms impact SO phytoplankton dynamics. Much of our existing knowledge stems from satellites, but biases due to data gaps from cloud cover and low solar angles remain unquantified. Here, we use ocean–sea-ice simulations with the Community Earth System Model to quantify the climatological 1997–2018 imprint of storms on chlorophyll and phytoplankton dynamics in the ice-free SO. Additionally, by comparing the full-field model output to synthetic satellite observations, we quantify sampling biases in satellite-derived estimates. We find that both the sign and the magnitude of the average surface chlorophyll imprint vary substantially across storms but last for at least 4 days after the storm passing. Based on our analysis, more than one third of the storms explain the majority of local non-seasonal chlorophyll variability, but satellite-derived storm imprints are often too large in magnitude. On the day of the storm passing, changes in vertical mixing predominantly cause surface chlorophyll anomalies, and reduced light availability due to enhanced cloud cover outweighs the enhanced nutrient availability due to entrainment. Interestingly, storms imprint differently on total net primary production than on surface chlorophyll, demonstrating the difficulty to derive carbon-cycle impacts from a surface-chlorophyll assessment. With SO future storm activity projected to increase, complementing satellite observations with other observing technologies, for example, profiling floats, is necessary to better constrain how storms impact biological carbon cycling in the SO.

Nissen, Cara [University of Colorado, Boulder, CO

Dynamic in-context learning with conversational models for data extraction and materials property prediction

The advent of natural language processing and large language models (LLMs) has revolutionized the extraction of data from unstructured scholarly papers. However, ensuring data trustworthiness remains a significant challenge. In this paper, we introduce PropertyExtractor, an open-source tool that leverages advanced conversational LLMs such as Google gemini-pro and OpenAI gpt-4, blends zero-shot with few-shot in-context learning, and employs engineered prompts for the dynamic refinement of structured information hierarchies—enabling autonomous, efficient, scalable, and accurate identification, extraction, and verification of material property data. Our tests on material data demonstrate precision and recall that exceed 95% with an error rate of ∼9%, highlighting the effectiveness and versatility of the toolkit. Finally, databases for 2D material thicknesses, a critical parameter for device integration, and energy bandgap values are developed using PropertyExtractor. In particular, for the thickness database, the rapid evolution of the field has outpaced both experimental measurements and computational methods, creating a significant data gap. Our work addresses this gap and showcases the potential of PropertyExtractor as a reliable and efficient tool for the autonomous generation of various material property databases, advancing the field.

Ekuma, Chinedu E. (ORCID:0000000258527556)

Fate of Listeria monocytogenes Serotypes on Frozen Mixed Vegetables During Consumer‐Simulated Thawing and Storage

ABSTRACT Recent outbreaks and recalls associated with frozen vegetables in the United States and Europe have been linked to Listeria monocytogenes . This study aims to understand the extent to which frozen vegetables support the growth of L. monocytogenes once thawed and held at different temperatures. Six L. monocytogenes strains, two of each from serotypes 1/2a, 1/2b, and 4b, were individually inoculated onto frozen vegetables and stored at −18°C for 7 days. After 7 days, the vegetables were thawed and stored at 5°C or 10°C for up to 14 days or at 25°C for up to 7 days. L. monocytogenes was enumerated from the thawed vegetables throughout the storage period. Population data were fitted to the primary Baranyi model to estimate growth rates and lag phase durations; the secondary Ratkowsky square root model was used to model the relationship of the growth rates with storage temperature. Five of the L. monocytogenes strains survived and grew on the thawed vegetables (population increases of > 1 log CFU/g) stored at 5°C, and all six of the strains proliferated at 10°C and 25°C (population increases of > 3 log CFU/g after 14 days and > 4 log CFU/g after 7 days, respectively). A secondary model was successfully generated based on the growth rates of the six L. monocytogenes strains on the thawed vegetables ( r 2 = 0.8888, RMSE = 0.2057). Results from this study fill a data gap associated with L. monocytogenes survival on thawed vegetables and can be used to determine safe handling and storage practices for these products to protect public health.

Salazar, Joelle K. [Division of Food Processing Sc

Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2

The project Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2 is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Los Angeles Basin presents an opportunity for large-scale geologic CO2 storage. Due to its large population and historical and geologic setting as one of the most prolific oil and gas producing basins in the United States, the region is home to more than 12 major power plants and oil refineries that produce more than 5 million metric tons of fossil fuel-related CO2 emissions each year. GeoMechanics Technologies worked to characterize the Pliocene and Miocene sediments in the Wilmington Graben, offshore of Los Angeles, California, for high-volume CO2 storage. The Graben is located offshore of the Los Angeles and Long Beach Harbor area, making it accessible yet geologically isolated from the nearby Wilmington oilfield and onshore areas. These sediments span more than 5,000 feet of vertical interval with an estimated storage resource of more than 100 million metric tons of CO2. The project team analyzed and interpreted existing geologic data within the region, including detailed exploration well log data and 2-D and 3-D seismic data. New seismic lines were acquired to fill in current data gap areas and two new characterization wells were drilled and logged. This information was integrated with existing geologic interpretations for adjacent onshore areas to help characterize optimal areas for CO2 storage and seals to safely store CO2. Integrated 3-D geologic and geomechanical models for the Wilmington Graben were developed to simulate the fate and transport of injected CO2 in the subsurface and to assess risks. This project contributed to the understanding of injectivity, containment mechanisms, rate of dissolution and mineralization, and storage capacity of the Wilmington Graben and associated analogous basins. This effort also provided greater insight into the potential for offshore geologic formations to safely and permanently store CO2.

.las

Advancing Manufacturing Water Resilience: Addressing Risks through New Approaches and Technologies

Water is indispensable in manufacturing operations, and many manufacturers operate on the assumption that water of sufficient quality and quantity will be available whenever and wherever needed. As such, the importance of water to this sector has been overlooked, despite its critical importance for operations and meeting production demands, due to perceived sufficient availability and low cost of water to manufacturers. However, the situation is changing as water-related risks are markedly increasing due to aging infrastructure, changing climate, and resource extraction, which alter global and regional water cycles and characteristics. These changes are occurring against a backdrop of intensifying competition from other sectors for scarce and/or unevenly distributed water resources and changing trends in water needs. Section 1 of this report explores those risks in the U.S. context, while the remaining sections detail the work needed to advance the resilience of manufacturing water supplies to these changing risks by filling critical data gaps, re-evaluating the value of water to manufacturers, and advancing opportunities for novel technologies and analyses. The intended audience for this report is broad, including manufacturers, decision makers, researchers, and policymakers.

36 MATERIALS SCIENCE

Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments

Presentation slides on "Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments" for CCUS 2025 Annual Meeting. The Basin-Scale Structural Features database contains a series of basin-scale spatial datasets representing structural features, including faults, fractures, folds, and earthquakes. Designed to support carbon storage feasibility and resources assessments for Carbon Capture and Storage (CCS) projects, the database leverages publicly available data resources from authoritative sources (e.g. US Geological Survey, State Geologic Surveys), and aims to help users better understand basin-scale structural features, as well as potential data gaps in areas with sparse information.

basin scale