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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Patterns of indoor radon concentrations, radon-hazard potential, and radon testing on a small geographic scale in Utah

Currently, there are no publicly-available estimates of indoor radon concentration at scales smaller than the county. Radon-hazard potential soil maps that reflect underlying geologic factors can be created at small geographic scale and linked to residential and census data. We determined the association between residential radon tests and high radon-hazard potential soil at the residential and block group levels using a large Utah-based dataset. We also identified characteristics of block groups with limited tests in the dataset.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Method for calculating radon activity and radon rejection using a beta-gamma detector

Radon interferes with concentration measurements used by atmospheric radioxenon systems. We demonstrate a method to quantify the amount of radon that is present in the detectors, the impact of radon activity on the minimum-detectable-concentrations, and how to determine the needed radon rejection levels. An example calculation shows a radon rejection level of 10 5 is sufficient to limit impact on the detector sensitivity. We anticipate this method will give analysist a better understanding of radon present in their measurements and allow system designers to tailor their systems’ radon rejection better for its location.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Low Level Radon Concentration and Radon Daughter Dose Monitoring in an Arid-zone Waste Store - 20081

Radioactive waste containing predominantly soil and rubble from the clean-up of a former uranium and thorium minerals processing research facility is currently stored at the Woomera Test Range in South Australia awaiting final disposal. Prior to commencing any manipulation of the nearly 10,000 waste drums (205 L or 55 gallon each), radon concentration monitoring and radon daughter dosimetry has been undertaken to (i) gain understanding of the temporal and spatial variation of radon and its daughters within the storage facility, which could provide insights into the radiological source term and (ii) confirm that radiological risks to workers are below the guideline values. A time series of nearly 12 months of detailed observations shows low level radon concentrations with annual average values that are slightly above the average radon concentrations in Australian homes. Peak values in summer are about three times higher than the annual average based on the CRM measurements. Both radon concentrations and annual effective dose are well below the regulatory limits. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Radon kinetics in a natural indoor radon chamber

An unusual 180 m 3 storage room in the basement of a two-story laboratory building is unventilated, and separated from occupiable rooms by double steel doors. The space completely borders on soil through the concrete floor and two of its concrete walls. The room also contains a separate inner chamber with 1 m thick concrete walls designed to damp vibrations in the room above it. The space boasts a relatively high radon level, 1083 Bq m –3 , which varies with local outdoor environmental conditions. Measurements were made of radon concentrations at various locations and heights within the facility. More than a year of continuous radon concentration data corresponding to a single location are also available, along with measurements of indoor and outdoor pressure, temperature, and humidity. Data were also collected with as many as five fans placed in different locations and cycled on for variable time periods. First order linear kinetic models were created to explain the observed approaches to steady state due to changing conditions and wash-out resulting from intentional ventilation. Results demonstrate a good fit between changes in the radon concentration level and the developed compartmental models. Furthermore, no significant differences were observed between radon concentration at different locations or heights in the chamber.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Quantifying mean, variability, and uncertainty in indoor radon exposure in Pennsylvania using random forest and quantile regression forest models

Radon is a naturally occurring radioactive gas that poses a serious health risk as the primary cause of lung cancer in non-smokers. Despite the well-known adverse association with health outcomes, current radon exposure assessments are limited to county-level or average-level estimates, which fail to capture regional variability. This study uses Machine Learning models, including Random Forest (RF) and Quantile Regression Forest (QRF), to estimate the indoor radon concentrations at the ZCTA (Zip code tabulation area)-level and characterize uncertainties in model estimates. Incorporating geological, meteorological, and building-specific data, the models aim to improve radon risk assessment by capturing mean exposure, variability, and extreme concentration levels. Processed radon test data (n = 718,111) were analyzed using average, variability, and quantile prediction methods. Models that estimate the average radon exposure at the ZCTA-level can yield promising model-fit results, but they do not capture the underlying variability of indoor radon exposure within a ZCTA. We utilize volatility analyses to identify characteristics indicative of high variability of indoor radon exposure. We also show that a QRF model can be used to estimate upper quantiles of residential radon exposure, thereby uncovering localized areas of elevated exposure that were not apparent in mean estimates. The results highlighted the need for a deep characterization of exposure risk and show that regions with moderate average exposure levels could still harbor extreme outliers with implications for evaluating health risks. Utilizing multiple radon exposure models allows for a deeper characterization of radon risk within a geographic area and can better identify high-risk areas. The results from this study provide a foundation for developing mitigation strategies and examining associations between radon exposure and health outcomes at fine scales. Future research should extend the geographic scope and incorporate additional environmental risk factors to establish a comprehensive framework for risk assessment.

Lee, Heechan [ORNL]↗
DOE OSTI2021

Performance study of charcoal-based radon reduction systems for ultraclean rare event detectors

The continuous emanation of radon due to trace amounts of uranium and thorium in detector materials introduces radon to the active detection volume of low-background rare event search detectors. 222 Rn produces a particularly problematic background in the physics region of interest by the "naked" beta decay of its 214 Pb daughter nucleus. While charcoal-based adsorption traps are expected to be effective for radon reduction in auxiliary circulation loops that service the warm components of current ton-scale detectors at slow flow rates (0.5-2 SLPM), radon reduction in the entire circulation loop at high flow rates $\mathcal{O}$(100s SLPM) is necessary to reach high sensitivity in future generation experiments. In this article we explore radon dynamics with a charcoal-based radon reduction system in the main circulation loop of time projection chamber detectors. Here, we find that even for perfect radon traps, circulation speeds of 2,000 SLPM are needed to reduce radon concentration in a 10 ton detector by 90%. This is faster by a factor of four than the highest circulation speeds currently achieved in dark matter detectors. We further find that the effectiveness of vacuum swing adsorption systems, which have been employed very successfully at reducing atmospheric radon levels in clean-rooms, is limited by the intrinsic radon activity of the charcoal adsorbent in ultra-low radon environments. Adsorbents with significantly lower intrinsic radon activity than in currently available activated charcoals would be necessary to build effective vacuum swing adsorption systems operated at room temperature for rare event search experiments. If such VSA systems are cooled to about 190 K, this requirement relaxes drastically.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Radon Kinetics in a Basement Space Measured with Different Devices

Although indoor monitoring of radon and benchmarking of radon measurement devices remain important research topics, few intercomparisons of active radon measurement devices have been performed under realistic conditions, let alone dynamic ones enabling comparison of their transient behavior. Five different radon monitors were therefore placed in a poorly ventilated basement space under three different conditions: 24 h under a steady, elevated radon level, 24 h with fans turned on to produce a radon washout transient, and 9 d with fans turned off for a radon buildup transient. Resulting radon concentrations varied between ~200 and ~2,000 Bq m -3 . Accuracy of the devices were evaluated using root-mean-square error, and ventilation data were fit to first order linear compartmental models. To more accurately model behaviors such as cyclic diurnal variations, the source term corresponding to entry of radon from soil into the basement was considered to be non-constant, as it is likely to vary drastically with both the indoor-outdoor pressure differential and soil concentration variations. Here, the improved radon washout model fit very well with the measurements. Despite a wide variety in list prices, all devices performed similarly during transients and at different radon concentrations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Automated anomalous behaviour detection in soil radon gas prior to earthquakes using computational intelligence techniques

Here in this article, three computational intelligence (CI) models were developed to automatically detect anomalous behaviour in soil radon gas ( 222 Rn) time series data. Data were obtained at a fault line and analysed using three machine learning techniques with the aim at identifying anomalies in temporal radon data prompted by seismic events. Radon concentrations were modelled with corresponding meteorological and statistical parameters. This leads to the estimation of soil radon gas without and with meteorological parameters. The comparison between computed radon concentration and actual radon concentrations was used in finding radon anomaly based upon automated system. The anomaly in radon time series data could be considered due to noise or seismic activity. Findings of study show that under meticulously characterized environments, on exclusion of noise contribution, seismic activity is responsible for anomalous behaviour seen in radon time series data.

58 GEOSCIENCES↗
DOE OSTI2026

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.

Wu, Yunhan [ORNL] (ORCID:0000000178842994)↗
DOE OSTI2020

Radon Photoionization: Project Technical Report

In most low-background physics experiments, radon is a significant and problematic source of background radiation because it is inert and sufficiently long-lived to pervade laboratory spaces. It may be possible to manipulate (and thus mitigate) radon electromagnetically by taking advantage of its relatively low first ionization energy. When considering ambient-temperature gas phases, only iodine is comparable. The other noble gases, and the most important constituents of breathable air (nitrogen and oxygen), all have higher ionization energies; so it may be possible to selectively manipulate radon in a variety of gas streams by ionizing it with an appropriately low-energy source of photons. Radon’s first ionization energy is in the vacuum UV part of the electromagnetic spectrum, which can be produced using a deuterium lamp. In this report, we present our attempts to manipulate radon via UV photoionization in a laboratory setting. This approach has the potential to increase radon removal efficiency from gases and/or to improve the efficiency of radon detectors. Unfortunately, our experiments suggest that either the life-time of a photoionized radon ion (before it re-neutralizes) is too short to be of much practical use and/or that our low-cost UV-photon source was not sufficiently energetic for efficient photoionization of radon.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A Review of Variables Impacting the Indoor Inhalation Radon Equilibrium Factor (FEQ)

With radon and its daughter products estimated as the second leading cause of lung cancer in the United States, it is imperative to understand their relative equilibrium inside commercial, community, and residential dwellings. The radon indoor inhalation fractional equilibrium factor (F eq ) quantifies the disequilibrium between radon and its progeny in indoor air, and recent advances have shown how air exchange rates (ACH) influence F eq . These numerically derived ACH-dependent F eq values are incorporated into the U.S. EPA's Radon Vapor Intrusion Screening Level (RVISL) calculator, which assists risk assessors in evaluating radon exposure. To advance the risk assessment science of actinon (Rn-219), thoron (Rn-220), and radon (Rn-222), the impact of variables such as indoor aerosol concentration and composition, outdoor air quality, household-specific characteristics, and environmental/meteorological conditions on the F eq must be examined. The primary objective of this research is to analyze these additional variables to determine the usefulness of incorporating such adjustment factors into the RVISL calculator and to identify areas of future research. Studies regarding the influence of these parameters are presented along with recommendations regarding the adjustment of the numerically derived F eq value. For example, elevated indoor aerosol concentrations, such as those originating from outdoor PM 2.5 or cigarette smoke, increase the abundance of accumulation- mode particles indoors, which in turn raises F eq values by facilitating the attachment of radon progeny to these aerosols. Smoking increases both the bronchial dose and F eq , while regions with high smog levels demonstrate the impact of regional air quality on F eq . In contrast, air cleaning systems and purifiers have been shown to reduce the F eq , suggesting that these systems could help mitigate radon exposure. Additionally, higher F eq values are typically observed during winter when ventilation rates are lower. This paper presents adjustment factors that may be applied to the RVISL F eq , emphasizing the need for further research to refine these variables and ensure accurate risk assessments in diverse environments. Applying these adjustment factors will minimize calculator over- and underestimations, providing a more accurate representation of the real-world risk associated with radon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Using the Monte Carlo Method to Evaluate the Reliability of Screening Multifamily Housing for Radon

When screening for radon in a multifamily housing complex using a fixed sample density (e.g., testing 1 in 10 (10%) or 1 in 4 units (25%)), the statistical confidence is dependent upon the assumed elevated radon frequency. For example, testing 25% of units in a complex estimated to have eight units with elevated radon levels will provide 90% confidence. However, if it is assumed that, in the same complex, there are only three units with elevated radon levels, the confidence drops to around 58% for the same sample density. Furthermore, in the previous example, if elevated radon levels are not found during the screening, all that can be stated is that the screening provides 90% confidence that there are no more than seven units in the complex with elevated radon levels. To more fully illustrate this uncertainty, ten separate multifamily housing radon data sets with 1 to 10 units with radon levels ≥4 pCi/L (Table 1) were selected for analysis using the Monte Carlo statistical method. Unlike other mathematically based statistical approaches, the Monte Carlo statistical method relies on repeated analysis of randomly selected data. from a 100% sampled complex at various sample densities. Success for each simulation is defined as finding at least one unit with elevated radon levels. In this statistical method, confidence in the overarching conclusion can be greatly enhanced by repeating the simulated screening hundreds or even thousands of times. For this study, each of the ten data sets was simulated 1,000 times. For each simulation, the data set was randomized three times before the fixed percentage of data was selected.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2019

Indoor Radon Measurements from Residential Buildings with Basements in a Community with Potential LLRW Contamination - 19566

The Port Hope Area Initiative (PHAI) represents the Government of Canada's commitment to the cleanup and safe, local, long-term management of historic low-level radioactive waste (LLRW) in two Southern Ontario municipalities-Port Hope and Clarington. The PHAI (see reference for internet address) is based on community-recommended solutions for the cleanup and safe long-term management of approximately 1.7 million cubic meters of LLRW. It is currently one of Canada's largest environmental remediation projects at a cost of over one billion dollars. Canadian Nuclear Laboratories (CNL) is implementing the PHAI on behalf of Atomic Energy of Canada Limited, a Federal Crown Corporation. An initial characterization and remediation program in the urban area of Port Hope was conducted from 1976 to 1981. The waste is the result of radium and uranium processing in Port Hope by the former Federal Crown Corporation Eldorado Nuclear Limited between 1933 and 1988. One contaminant of concern in the LLRW is radium-226 (Ra-226) which may lead to elevated indoor levels of radon-222 (Rn-222) indoors. As part of CNL's implementation of the PHAI, Arcadis is conducting the Port Hope Project Property Radiological Survey of approximately 4,800 small-scale sites to identify 1) properties that have not been affected by historic operations and 2) properties that have residual historic low-level radioactive waste impacts requiring remediation either for soils or for interior contamination or both. Over the last six years, a component of the Small Scale Sites (SSS) characterization surveys have measured radon concentrations in essentially all buildings in Port Hope using alpha-track detectors. All properties had subsurface characterization including analytical characterization and lithology following the radon measurement reporting to measure if soil concentrations exceeded the PHAI Cleanup Criteria (PHAI CC) for Ra-226 of 0.29 Bq/g. Buildings with radon gas exceeding a trigger level of 200 becquerels per cubic meter (Bq/m{sup 3}) or those with ventilation systems required investigation of soil concentrations around the perimeter of the building. Ra-226 concentrations above the background level of 0.05 Bq/g due to LLRW sources were forwarded to create remedial action plans (RAPs) to remove the contamination near the building. The SSS surveys provide a substantive data set on the approximately 3,000 properties measured to date with interior Rn-222 gas measurements and descriptions of the physical characteristics of the buildings, the lithology of soils near the buildings and the measurements of Ra-226 concentration in the soils on the property. Consideration of the potential for contribution from non-LLRW Ra-226 from natural sources or coal ash was required on some properties. This paper describes the data and exploratory analysis of the relationship(s) between LLRW and non-LLRW factors that affect the variation in indoor radon concentrations. Historical information on the urban area, the measured Ra-226 concentration and the age of the building were correlated with radon concentrations. A large variety of native soils are found in the complex terrain and the type of native soil was correlated with the radon concentrations. A statistical analysis to address the impact of co-related explanatory variables to model indoor radon concentrations is planned when the SSS activities are complete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Characterization of Precipitation-Induced Radon Progeny Deposition Events Using a City-Scale Sensor Network

Networks of radiation detectors provide a platform for real-time radioactive source detection and identification in urban environments. Detection algorithms in these systems must adapt to naturally-occurring changes in background, which requires well-characterized relationships between precipitation events and their corresponding radiological signature. Here, we present a quantitative and qualitative description of rain-induced radon progeny deposition events occurring in Chicago from September 2023 to February 2024. We measure ambient gamma radiation levels, precipitation rate, temperature, pressure, and relative humidity in a network of sensor nodes. For each identified precipitation period, we decompose spectra into static- and radon-associated components as defined by a non-negative matrix factorization (NMF) algorithm. We find a consistent power-law relationship between a precipitation-dependent peak of the radon progeny proxy (RPP) and the peak strength of the radon-associated NMF component for most precipitation events. We conduct a case study of a rainfall period with abnormally high levels of implied radon progeny concentration and describe its temporal and spatial evolution. We hypothesize that this phenomenon is due to the air mass path that intersects a uranium-rich region of Wyoming. Finally, we cluster precipitation events into three distinct categories. One category roughly corresponds to events with deep low-pressure systems and high relative radon concentration, while another is characteristic of light stratiform rain with slightly higher temperatures and intermediate relative radon concentration. The third category appears to contain weak-gradient or lake breeze convection showers with intermittent precipitation and low relative radon concentration. These findings suggest that radiological anomaly detection could be improved by training unique background models corresponding to each category of meteorological event.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗