<p>Measurements of radon (&sup2 / &sup2 / &sup2 / Rn) concentration in soil gas are routinely used to locate geological fault zones. This study was undertaken to investigate the systematic effects that influence radon soil-gas measurements, in preparation for the first such fault zone measurements in South Africa.</p>

Thesis (Master of Engineering) in Engineering Physics--University of Maine, 2004. / Includes vita. Includes bibliographical references (leaves 81-83).

Magister Scientiae - MSc / Measurements of radon (222Rn) concentration in soil gas are routinely used to locate geological fault zones. This study was undertaken to investigate the systematic effects that influence radon soil-gas measurements, in preparation for the first such fault zone measurements in South Africa. The measurements were made at two zones (called A and B for ease of reference) on the iThemba LABS site, which is located in Faure, on the Cape Flats, Western Cape (South Africa). There are no known faults located in the vicinity (~ 10 km) of the site. The radon measurements were made using a RAD7 (Durridge) radon monitor, which makes use of alpha spectrometry. A steel soil probe, which is inserted into the soil, was used to transfer radon from a certain depth in the soil to the RAD7 monitor via a flexible tube. Measurements were made at five sampling areas (three in zone A (A1, A2 and A3) and two in zone B (B1 and B2)), on the site during the months of May, August and October 2006. The variation of soilgas radon concentration as a function of depth, time of day and meteorological data were studied. The depths at which measurements were made were generally 25, 50, 75 and 100 cm. (In August and October, some of the depths were not considered due to a high water table.) Atmospheric temperature, air humidity, wind speed and atmospheric pressure were measured using a portable weather tracker (Kestrel 4000). The highest radon concentrations recorded were 11000 ± 776 Bq.m-3 and 26900 ±1370 Bq.m-3 at a depth of 100 cm in zone A and B, respectively (May). Generally, the radon concentrations were significantly quenched during the August and October measurements relative to the May values. The May soil-gas radon concentration profiles as a function of depth were fitted using a chi-square minimization procedure in order to extract diffusion lengths. A functional form derived from a onedimensional diffusion model was used for the fitting. One the parameter of the fit function is the 226Ra activity concentration. This was determined by means of gammaray spectrometry (in-situ and laboratory-based). A MEDUSA-type detector system comprising a CsI(Na) scintillator crystal and a GPS signal receiver were used for the in-situ measurements. A high-purity germanium detector (2.6 keV FWHM resolution at 1.33 MeV, 45 % relative efficiency) was used for the laboratory measurements. Significant seasonal variations in soil-gas radon concentration were observed (concentrations were generally much lower during or after the rainy season due to the presence of a high water table, and possibly the presence of more lush vegetation causing more radon to escape to the atmosphere). Significant (up to a factor of 2) local variation in radon concentration was observed at a particular depth, in a particular zone during autumn (just after the dry season). The soil-gas radon concentrations (for depth > 25 cm) in zone B were ~ factor of 2 higher than in zone A. The difference is largely due to the fact that the 226Ra soil activity concentrations in zone B were higher than in zone A (by a factor of ~ 1.6). Significant correlations (with coefficients > 0.6) were found between soil-gas radon concentrations and soil 226Ra activity concentrations (using a combination of zone A and B data). No significant, robust correlations (with correlation coefficients > 0.6) were found between soil-gas radon concentrations and meteorological parameters. Often contradictory results (in terms of the sign of the coefficient) were found. From measurements made at two depths (25 and 50 cm) in zone A, over a 24 hour period, there is evidence of a statistically significant variation between night and day radon concentrations, with the former being higher. The one-dimensional diffusion model used to fit the measured radon concentration depth profiles failed to fit the data when the results for a depth of 25 cm were included. When the 25 cm data were excluded the fits yielded diffusion lengths that are more realistic, although significant variations in diffusion length were found in a particular zone. / South Africa

Monitoring and mapping the presence and/or intensity of an environmental hazard through space, is an essential part of public health surveillance. Radon, a naturally occurring radioactive carcinogenic gas, is an environmental hazard that is both the greatest source of natural radiation exposure in human populations and the second leading cause of lung cancer worldwide. Concentrations of radon can accumulate in an indoor setting, and, though there is no safe concentration, various guideline values from different countries, organizations and regions provide differing threshold concentrations that are often used to delineate geographic areas at higher risk. Radon maps demarcate geographic areas more prone to higher concentrations but can underestimate or overestimate indoor radon risk depending on the concentration threshold used. The goals of this thesis are to map indoor radon risk in the province of British Columbia, identify areas more prone to higher concentrations and their associations with different radon concentration thresholds and lung cancer mortality trends. The first analysis was concerned with developing a data-driven method to predict and map ordinal classes of indoor radon vulnerability at aggregated spatial units. Spatially referenced indoor radon concentration data were used to define low, medium and high classes of radon vulnerability, which were then linked to regional environmental and housing data derived from existing geospatial datasets. A balanced random forests algorithm was used to model environmental predictors of indoor radon vulnerability and predict values for un-sampled locations. A model was generated and evaluated using accuracy, precision, and kappa statistics. We investigated the influence of predictor variables through variable importance and partial dependence plots. The model performed 34% better than a random classifier. Increased probabilities of high vulnerability were found to be associated with cold and dry winters, close proximity to major river systems, and fluvioglacial and colluvial soil parent materials. The Kootenays and Columbia-Shuswap regions were most at risk. We built upon the first analysis by assessing the difference between temporal trends in lung cancer mortality associated with areas of differing predicted radon risk. We assessed multiple scenarios of risk by using eight different radon concentration thresholds, ranging from 50 to 600 Bq m-3, to define low and high radon vulnerability. We then examined how the following parameters changed with the use of a different concentration threshold: the classification accuracy of each radon vulnerability model, the geographic characterizations of high risk, the population within high risk areas and the differences in lung cancer mortality trends between high and low vulnerability stratified by sex and smoking prevalence. We found the classification accuracy of the model improved as the threshold concentrations decreased and the area classified as high vulnerability increased. The majority of the population were found to live in areas of lower vulnerability regardless of the threshold value. Thresholds as low as 50 Bq m-3 were associated with higher lung cancer mortality trends, even in areas with relatively low smoking prevalence. Lung cancer mortality trends were increasing through time for women, while decreasing for men. We suggest a reference level as low as 50 Bq m-3 is justified for the province. / Graduate

Dajun DaiRadon is a colorless, odorless, naturally occurring gas. It is currently the second leading cause of lung cancer and the number one cause of lung cancer to non-smokers in the United States. DeKalb County offers free screening for radon for residents. However, screening rates vary across the county. This pilot study focused on 14 selected tracts within DeKalb County with relatively low levels of radon screening. Over 200 households were recruited and homes were tested for indoor radon concentrations on the lowest livable floor over an 8-week period from March – May 2016. Tract-level characteristics were examined to understand the varitations of race, income, education, and poverty status between the 14 selected tracts and all of DeKalb County. The 14 selected tracts were comparable to all of DeKalb County in most factors besides race. Radon was detected in 73% of the homes sample and 4% had levels above the EPA guideline of 4 pCi/L. Multi-variate linear regression was used to compare all housing construction characteristics with radon concentrations and suggested that having a basement was the strongest predictive factor for detectable and/or hazardous levels of radon. Radon screening can identify problems and spur home owners to remediate but low screening rates may impact the potential health impact of free screening programs. More research should be done to identify why screening rates vary in order to identify ways to enhance screening and reduce radon exposure in DeKalb County.

published_or_final_version / Radioisotope / Master / Master of Philosophy

This is a study of radon concentration levels in the air and water of homes in East-Central Indiana. The results of a survey of 69 homes in which both an air and water sample were analyzed for radon concentrations will be described; all homes in the survey derived their water sample from a well at the home site. Activated charcoal canisters were exposed in homes for two to three days; radon concentration levels in the air samples were then determined following the EPA procedures described by Gray and Windham (1). Radon concentrations in water were determined by the liquid scintillation method according to protocol utilizing the techniques described by Pritchard and Gesell (2). A questionnaire was completed by each participant which provided information such as home construction type, material, and location. Radon concentration results and questionnaire data were entered into a database; database searches were then conducted in order to establish conclusions associated with the study.(1) D.J. Gray and S.T. Windham, EERF Standard Operating Procedures for RN-222 Measurement Using Charcoal Canisters, EPA 520/5-87-005, (June 1987)(2) H.M. Pritchard and T.F. Gesell, Health Physics 33, 577, (1977). / Department of Physics and Astronomy

Photocopy of typescript.

Thesis (M.S.) in Physics--University of Maine, 2002. / Includes vita. Includes bibliographical references (leaf 33 ).

The Funk–Radon transform assigns to a function on the two-sphere its mean values along all great circles. We consider the following generalization: we replace the great circles by the small circles being the intersection of the sphere with planes containing a common point ζ inside the sphere. If ζ is the origin, this is just the classical Funk–Radon transform. We find two mappings from the sphere to itself that enable us to represent the generalized Radon transform in terms of the Funk–Radon transform. This representation is utilized to characterize the nullspace and range as well as to prove an inversion formula of the generalized Radon transform.