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At least 55 records · Page 3

Empirical evidence that mean soil contaminant concentration is not a conservative indicator of external exposure to wildlife

Adequate information on external exposure is often a limiting factor in ecological risk assessments because of a lack of exposure data for free-ranging animals as they interact with a heterogeneous distribution of contaminants. Instead, most wildlife exposure data are estimated from model simulations. However, empirical exposure data are rarely available to verify model results, or to test fundamental assumptions inherent in exposure assessments. We used novel, GPS-coupled radiation dosimeters on reindeer (Rangifer tarandus) to quantify their external exposure for five months in a Chernobyl fallout affected mountainous area of Norway. The exposure data were then used to test a fundamental assumption in screening-level risk assessments: Mean soil contaminant concentrations can be used to conservatively estimate chronic external exposures to representative animals. External exposure and GPS coordinates were obtained hourly and compared to model simulations of exposure based on airborne surveys of 137 Cs soil contamination. Our objectives were to determine 1) if modelled dose estimates based on mean 137 Cs soil concentrations were conservative, and 2) if modelled dose estimates could be improved by adjusting for spatial–temporal heterogeneity of contaminants using 137 Cs concentrations within reindeers’ GPS-defined home ranges and core areas. We found that external exposure modelled from mean soil contaminant concentrations underestimated exposure by 70% compared to empirical measurements from GPS-dosimeter collars worn on individual animals. Using area-weighted mean contaminant levels within the animals’ home range improved the model estimates, but still underestimated the field dosimeter data by 53%. The best estimate of external exposure was obtained when high-use areas within their home range, along with spatial heterogeneity of the contaminant, was accounted for by using area-weighted mean soil contaminant levels within GPS-derived core areas. Accounting for temporal use of core areas within animals’ home range provided a 24% improvement. Here, a comparison of our analyses to similar work performed on Chernobyl wolves found the two studies concur that risk assessors should be cautious in relying on the paradigm of using averaged soil contaminant levels to provide conservative estimates of external exposure to representative individuals. Results of modelled external exposure based on mean soil contaminant concentrations could misguide assessors and cause inappropriate management decisions.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Mechanical Property Assessment of Unirradiated Cladding After Exposure to Time at Temperature

Light water reactors in the United States are operated within inherent safety limits designed to account for anticipated operational occurrences (AOOs). Unlike more severe reactor transients, these events permit the potential reuse of reactor cladding, highlighting the nuanced role of thresholds in influencing reactor efficiency compared to design-basis or beyond-design-basis transient conditions. The threshold designated for AOO peak cladding and fuel temperatures are currently grounded around thermal hydraulic limits such as surpassing the critical heat flux (CHF), rather than in fuel-cladding material performance. This CHF criterion therefore represents a conservative approach to AOO transients during the reactor lifetime. Extending this threshold to higher temperatures than CHF can result in additional operation efficiency gains. Here, a material performance-based approach is assessed to better understand the physical material limits of short time scale exposures to elevated temperatures. This approach, termed time at temperature (t@T), references fuel cladding microstructural and mechanical response to rapid temperature transients in absence of radiation damage. The results of this work are expected to help identify margin for the United States reactor fleet, which could be utilized to increase operational efficiencies through decreased reactor outages.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Volatiles from the necrophagous fly Cochliomyia macellaria (Diptera: Calliphoridae) as indicators of Salmonella exposure

Blow flies (Diptera: Calliphoridae) are crucial in forensic investigations due to their association with both living and dead humans and other animals. Additionally, their interactions with various resources and potential as vectors of pathogens of humans and other animals, thus, make them potential tools for biosurveillance. This study investigated the potential of monitoring volatile organic compounds (VOCs) emitted by blow flies exposed to Salmonella as a method for pathogen surveillance. Adult blow flies ( Cochliomyia macellaria ) were exposed, or not, to Salmonella enterica . Following exposure, VOCs released by the blow flies were collected and analyzed using gas chromatography-mass spectrometry (GC-MS). Results indicate a treatment by time interaction (P < 0.01). Indicator species analysis identified a single compound significantly associated with S. enterica exposure (P = 0.02), Nonane, 2,2,4,4,6,8,8-heptamethyl, potentially indicating an immune system response. Given a compound indicating exposure was detected, future research should determine if more replicates could detect more differences after Salmonella ingestion. This research highlights the potential of blow flies as biosurveillance tools and the potential value of volatiles for assessing their exposure to pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

The relationship between urinary selenium levels and risk of gestational diabetes mellitus: A nested case–control study

Background Selenium (Se) is an essential trace element for the human body. Serum Se and urinary Se are also biomarkers to assess Se exposure status. However, studies focusing on the association between urinary Se and the risk of gestational diabetes mellitus (GDM) are rare. Objective To investigate the association between urinary Se and the risk of GDM. Methods A nested case–control study based on a prospective birth cohort in Wuhan, China, which focuses on the effects of prenatal environmental factors exposure on pregnant women and children’s health was conducted. Two hundred and twenty-six cases and 452 controls were included. Maternal urine samples were collected before GDM diagnosis, and the urinary Se levels were determined. We assessed the association of urinary Se with GDM by conditional logistic regression with maternal urinary Se level as a categorical variable, and estimated the association between Se and glucose levels by multiple linear regression. The potential modifier roles of maternal age and fetal sex have also been assessed. Results Lower urinary level of Se was significantly associated with a higher risk of GDM (OR = 2.35 for the tertile 1, 95% CI:1.36-4.06; adjusted OR = 1.79 for the tertile 2, 95%CI:1.09-2.95; p for trend = 0.01). Fetal sex had an interaction with Se in the association with GDM. The association was more pronounced among pregnant women with female fetuses than with male fetuses. Discussion Our study suggested a significant negative association between urinary Se and the risk of GDM, and this association may vary depending on the fetal sex.

Liu, Yuanxia↗

Landscape analysis of environmental data sources for linkage with SEER cancer patients database

Abstract One of the challenges associated with understanding environmental impacts on cancer risk and outcomes is estimating potential exposures of individuals diagnosed with cancer to adverse environmental conditions over the life course. Historically, this has been partly due to the lack of reliable measures of cancer patients’ potential environmental exposures before a cancer diagnosis. The emerging sources of cancer-related spatiotemporal environmental data and residential history information, coupled with novel technologies for data extraction and linkage, present an opportunity to integrate these data into the existing cancer surveillance data infrastructure, thereby facilitating more comprehensive assessment of cancer risk and outcomes. In this paper, we performed a landscape analysis of the available environmental data sources that could be linked to historical residential address information of cancer patients’ records collected by the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program. The objective is to enable researchers to use these data to assess potential exposures at the time of cancer initiation through the time of diagnosis and even after diagnosis. The paper addresses the challenges associated with data collection and completeness at various spatial and temporal scales, as well as opportunities and directions for future research.

60 APPLIED LIFE SCIENCES↗

Chemical Process Safety at TRISO-Based, Metal-Based, and Salt-Based Fuel Fabrication Facilities: Technical Assessment and Guidance Assessment

As part of efforts to prepare for potential and ongoing safety reviews for licensing of advanced non-light-water reactor fuel cycles, the U.S. Nuclear Regulatory Commission (NRC) tasked Pacific Northwest National Laboratory to prepare an assessment on the state of knowledge of potential chemical processes at fuel cycle facilities supporting the front end of these fuel cycles, and to assess the associated regulatory guidance. This report provides a technical assessment of chemical process safety considerations to support NRC licensing reviews of fabrication processes for tri-structural isotropic (TRISO) based, metallic-based, and salt-based fuels. The assessments involved collecting publicly available information on the fuel fabrication processes to (i) identify the operational process steps, characteristics and chemicals involved, (ii) identify the physical safety considerations and health safety considerations during licensing reviews of the various process steps, and (iii) collect information to support assessments of severity of accidents and potential mitigative measures to be implemented. The assessment provides a foundational basis on chemical process safety considerations for advanced fuel fabrication activities, although it is recognized that licensing reviews may necessitate design-specific considerations. The specific conditions under which chemical hazards emerge will require process-specific considerations, highlighting the importance of process-informed interpretation. The assessment also determined that exposure guidelines and limits to assess the consequences of acute exposures are limited for some chemicals, although alternative limits and supplementary information from databases or safety data sheets provide sufficient information to evaluate consequences of acute exposures. In addition, it was identified that metallic and salt fuel fabrication processes may involve beryllium, which is an exposure hazard. The regulatory framework for the licensing of advanced fuel cycle facilities, per 10 CFR Part 70 Domestic Licensing of Special Nuclear Material, is deemed robust and flexible to address the chemical safety considerations in this report. A review was conducted on various regulatory guidance and technical basis documents. This included reviewing NUREG-1520, Revision 2, Standard Review Plan for Fuel Cycle Facilities License Applications – Final Report and the process descriptions in Appendix A of NUREG/CR-6410, Nuclear Fuel Cycle Facility Accident Analysis Handbook, to address advanced fuel types. As new fuels will involve process-specific chemical uses, process-specific considerations are provided in this report. Additionally, it is noted that the U.S. Department of Energy protective action criteria database includes Temporary Emergency Exposure Limits (TEELs) for process-specific chemicals. This report provides technical information to support chemical safety assessments of new advanced fuel cycle facilities and identifies technical and safety information to support licensing reviews. No regulatory barriers were identified for the licensing of advanced fuel cycle facilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Insights from application of a hierarchical spatio-temporal model to an intensive urban black carbon monitoring dataset

Existing regulatory pollutant monitoring networks rely on a small number of centrally located measurement sites that are purposefully sited away from major emission sources. While informative of general air quality trends regionally, these networks often do not fully capture the local variability of air pollution exposure within a community. Recent technological advancements have reduced the cost of sensors, allowing air quality monitoring campaigns with high spatial resolution. The 100×100 black carbon (BC) monitoring network deployed 100 low-cost BC sensors across the 15 km 2 West Oakland, CA community for 100 days in the summer of 2017, producing a nearly continuous site-specific time series of BC concentrations which we aggregated to one-hour averages. Leveraging this dataset, we employed a hierarchical spatio-temporal model to accurately predict local spatio-temporal concentration patterns throughout West Oakland, at locations without monitors (average cross-validated hourly temporal R 2 =0.60). Using our model, we identified spatially varying temporal pollution patterns associated with small-scale geographic features and proximity to local sources. In a sub-sampling analysis, here we demonstrated that fine scale predictions of nearly comparable accuracy can be obtained with our modeling approach by using ~30% of the 100×100 BC network supplemented by a shorter-term high-density campaign.

54 ENVIRONMENTAL SCIENCES↗

Influence of alveolar mixing and multiple breaths of aerosol intake on particle deposition in the human lungs

Predictive dosimetry models play an important role in assessing health effect of inhaled particulate matter and in optimizing delivery of inhaled pharmaceutical aerosols. Here, in this study, the commonly used 1D Multiple-Path Particle Dosimetry model (MPPD) was improved by including a mechanistically based model component for alveolar mixing of particles and by extending the model capabilities to account for multiple breaths of aerosol intake. These modifications increased the retained fraction of particles and consequently particle deposition predictions in the deep lung during tidal breathing. Comparison with an existing dataset (J. Aerosol Sci., 99:27-39, 2016) obtained under two breathing conditions referred to as slow and fast breathing showed significant differences in 1 µm particle deposition between predictions (slow: 30±1%, fast: 21±1%) and measurements (slow: 43±9%, fast: 30±5%) when the prior version of MPPD (single breath and no mixing, J. Aerosol Sci., 151:105647, 2021) was used. Adding a mixing model and multiple breaths moved the predictions (slow: 34±2%, fast:25±2%) closer to the range of deposition measurements. For 2.9 µm particles, predictions from both the original (slow: 70±2%, fast: 57±2%) and the revised MPPD model (slow: 71±2%, fast: 59±3%) compared well with experiments (slow: 67±8%, fast: 58±10%). This was expected as suspended fraction of 2.9 µm particles was small and thus the addition of alveolar mixing and multi breath capability only slightly increased the retained fraction for particles of this size and greater. The revised 1D model improves dose predictions in the deep lung and support human risk assessment from exposure to airborne particles.

60 APPLIED LIFE SCIENCES↗

The efficacy and ecological impact of mercury sorbents on the physiology and reproductive fitness of Daphnia magna

Environmental mercury (Hg) contamination threatens ecosystems due to its bioaccumulation and toxicity. Effective and sustainable remediation strategies are essential, with carbon-based sorbents like biochar (BC) and activated carbon (AC) gaining attention for their high adsorption capacity and cost-effectiveness. However, their ecological impacts remain poorly understood. This study evaluates the Hg removal efficacy and ecological effects of three sorbents—BC, granular AC (GAC), and AC fiber (ACF)—in a flow-through column system with and without Hg additions. We tested Hg removal at two concentrations (1 and 4 µg/L Hg) and assessed chronic exposure effects on a sentinel and sensitive freshwater organism, Daphnia magna, over 30 days of exposure to the columns’ effluent. GAC removed 100 % of Hg, while BC and ACF achieved 99 % removal. The ACF + 4 µg/L Hg effluent induced 70 % lethality in D. magna after nearly three weeks of exposure, while the GAC effluent significantly reduced fecundity, even in the absence of Hg exposure. In contrast, the BC effluent enhanced reproductive output, likely due to inputs of carbon and nitrogen in the effluent. These findings highlight the need to balance Hg removal efficacy with ecological safety, emphasizing the importance of considering both remediation effectiveness and potential environmental impacts.

Activated carbon↗

Evaluating Exposures of Bay Mussels (Mytilus trossulus) to Contaminants of Emerging Concern through Environmental Sampling and Hydrodynamic Modeling.

Bay mussels (Mytilus trossulus) were transplanted to 18 locations representing a range of potential exposures throughout Puget Sound, WA. Tissues were analyzed for over 200 organic contaminants. Results indicated the widespread exposure of marine organisms to trace levels of organic contaminants including the synthetic opioid oxycodone, present at three urban sites, and the chemotherapy drug melphalan, present at nine locations, at levels that may be of biological concern. Land-use and wastewater outfalls were evaluated as potential sources of CECs to the nearshore. Exposure to alkylphenol ethoxylates was associated with increased impervious surfaces in upland watersheds. A hydrodynamic simulation was performed using the Salish Sea Model to integrate inputs from 99 wastewater sources to Puget Sound. Predictions were consistent with concentrations of several wastewater-associated contaminants and d15N enrichment. These results support the notion that Puget Sound nearshore biota suffer chronic exposures to a suite of contaminants from multiple sources and provide critical to focus future monitoring and management.

toxic contamination, Salish Sea, Sish Sea Model, m↗

Exposure, health effects, sensing, and remediation of the emerging PFAS contaminants – Scientific challenges and potential research directions

Per- and polyfluoroalkyl substances (PFAS) make up a large group of persistent anthropogenic chemicals which are difficult to degrade and/or destroy. PFAS are an emerging class of contaminants, but little is known about the long-term health effects related to exposure. In addition, technologies to identify levels of contamination in the environment and to remediate contaminated sites are currently inadequate. In this opinion-type discussion paper, a team of researchers from the University of Connecticut and the University at Albany discuss the scientific challenges in their specific but intertwined PFAS research areas, including rapid and low-cost detection, energy-saving remediation, the role of T helper cells in immunotoxicity, and the biochemical and molecular effects of PFAS among community residents with measurable PFAS concentrations. Potential research directions that may be employed to address those challenges and improve the understanding of sensing, remediation, exposure to, and health effects of PFAS are then presented. Here, we hope our account of emerging problems related to PFAS contamination will encourage a broad range of scientific experts to bring these research initiatives addressing PFAS into play on a national scale.

Challenges and research directions↗

A comprehensive framework to assess elemental mercury in the Department of Energy: A descriptive analysis

Objective: This study investigated the relationship between personal breathing zone air samples and associated biological monitoring urine samples collected in the U.S. Department of Energy Operations. Methods: We performed standard descriptive analyses of the air sample and BEI monitoring data. We also provide a list of direct-reading instruments used in mercury field assessments. Results: A total of 2,330 air samples and 265 BEI data were analyzed. These data were grouped into 16 job titles, excluding categories with fewer than 10 samples, which resulted in 11 job titles. Conclusions: We conclude that industrial hygiene airborne sample data alone may not provide a complete assessment in exposure determination. We suggested the necessity of incorporating biological monitoring to determine the exposure.

60 APPLIED LIFE SCIENCES↗

Thermal Effects on Gas Pipelines

Irradiance from a nuclear weapon can be the source of heat on gas infrastructure. This exposure when sufficiently intense can result in failure. An estimation tool for this behavior is the object of this study. A lumped capacity technique is employed to estimate the system temperature rise. The temperature rise is related to three possible outcomes. Two of the outcomes are relatively certain failure and relatively certain lack of effect. A large range of exposures are assessed with the model, and a relatively small number of cases are in the uncertain range. This model is presented as a tool that can be used in conjunction with a structural assessment model to sensitivities to the overpressure and shock to screen potential outcomes from subject events .

02 PETROLEUM↗

Sodium Chemistry Assessment and Initiation of Sodium Exposure Experiment on A709 Commercial Heats and LPBF 316H SS

This report documents sodium chemistry characterization and the initiation of forced‑convection sodium exposure experiments for two structural materials for sodium‑cooled fast reactors (SFRs): Alloy 709 (solution‑annealed and with an additional 775 °C/10 h precipitation treatment) and laser powder bed fusion (LPBF) 316H stainless steel tensile specimens printed with an as‑built surface condition. The sodium exposure experiment was conducted in a forced‑convection sodium loop with two vessels operated at 550 °C and 600 °C, and a cold trap maintained at <130 °C. Carbon activity in sodium was quantified using a nickel‑foil equilibration method. Initial post‑exposure evaluation after ~1,000 h indicates negligible thickness change for Alloy 709 and a small but measurable mass decrease. To isolate thermal effects from sodium effects, parallel thermal‑aging experiments were performed on Alloy 709 at 550 °C and 600 °C. Baseline tensile tests at room temperature, 550 °C, and 600 °C show expected reduction in strength with increasing temperature and serration tensile curves at elevated temperatures, consistent with dynamic strain aging. After 3,000 h thermal aging, Alloy 709 exhibits modest strengthening and reduced ductility at 550 °C. Together, these results establish the loop chemistry conditions and provide the initial corrosion and mechanical property results for ongoing long‑duration sodium exposure of Alloy 709 and LPBF 316H stainless steel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗

Evaluating county-level lung cancer incidence from environmental radiation exposure, PM 2.5 , and other exposures with regression and machine learning models

Characterizing the interplay between exposures shaping the human exposome is vital for uncovering the etiology of complex diseases. For example, cancer risk is modified by a range of multifactorial external environmental exposures. Environmental, socioeconomic, and lifestyle factors all shape lung cancer risk. However, epidemiological studies of radon aimed at identifying populations at high risk for lung cancer often fail to consider multiple exposures simultaneously. For example, moderating factors, such as PM 2.5 , may affect the transport of radon progeny to lung tissue. This ecological analysis leveraged a population-level dataset from the National Cancer Institute’s Surveillance, Epidemiology, and End-Results data (2013–17) to simultaneously investigate the effect of multiple sources of low-dose radiation (gross γ activity and indoor radon) and PM 2.5 on lung cancer incidence rates in the USA. County-level factors (environmental, sociodemographic, lifestyle) were controlled for, and Poisson regression and random forest models were used to assess the association between radon exposure and lung and bronchus cancer incidence rates. Tree-based machine learning (ML) method perform better than traditional regression: Poisson regression: 6.29/7.13 (mean absolute percentage error, MAPE), 12.70/12.77 (root mean square error, RMSE); Poisson random forest regression: 1.22/1.16 (MAPE), 8.01/8.15 (RMSE). The effect of PM 2.5 increased with the concentration of environmental radon, thereby confirming findings from previous studies that investigated the possible synergistic effect of radon and PM 2.5 on health outcomes. In summary, the results demonstrated (1) a need to consider multiple environmental exposures when assessing radon exposure’s association with lung cancer risk, thereby highlighting (1) the importance of an exposomics framework and (2) that employing ML models may capture the complex interplay between environmental exposures and health, as in the case of indoor radon exposure and lung cancer incidence.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of an Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST by extending the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5,000 annual synthetic storm events in a 2,227 $km^2$ Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

58 GEOSCIENCES↗