Applying geogenic methods and decision-making tools to model radon at local and regional scales. - Hughes, Meabh Banrion (Trinity College Dublin. School of Natural Sciences. Discipline of Geology, 2023)
Radon is an environmental health hazard for indoor environments, caves and underground mines exposure to which is related to an increased probability of developing lung cancer. Globally, radon is the second leading cause of lung cancer after tobacco smoking, and the leading cause of lung cancer in non-smokers. Radon is geogenic, in that it primarily originates from beneath the Earth?s surface. Specifically, radon has several isotopes which form intermediate decay products from the radioactive decay of uranium and thorium (238U, 235U and 232Th). From a radiological protection perspective 222Rn is the main isotope of interest, given its relatively longer half-life compared to the other radon isotopes. Ireland has a geographically weighted average indoor radon concentration (77 Bq m-3) and population weighted average indoor radon (98 Bq m-3) which is over twice that of the global average (39 Bq m-3), and a disproportionally high number of radon-related lung cancer cases occur here (ca. 300 - 350 cases per year, which equates to 14% of the total lung cancer cases, compared to the global range of between 3% to 15%) (El?o et al., 2018, p. 20; Fuente et al., 2020; Long, 2018; Murphy et al., 2021; World Health Organization, 2009). The high average radon concentrations, geological diversity, and availability of open access data relating to natural and built environments make Ireland an ideal case study to better understand the factors contributing to the concentration and spatial variation of radon. Although the connection between local geology and radon is widely known, radon maps seldom utilise information relating to the radon source or pathway through the natural environment; both factors govern the distribution of indoor radon. For instance, the first national radon map of Ireland (S.G Fennell et al., 2002) although a major achievement in that it estimated the probability of indoor radon exceeding a threshold value from 10 x 10 km grids, it had several shortcomings in that it utilised a limited number of indoor radon measurements, and did not contain any geological data. Not only does Ireland have a high average indoor radon concentration, some exceptionally high indoor radon concentrations have also been found here. In 2003, the highest single measurement of indoor radon (65,000 Bq m-3) was reported in a house in Castleisland Co. Kerry after several occupants tragically died of lung cancer, despite being non-smokers. No previous geological studies have been implemented to investigate the cause of high radon occurring in the area. This research sets out to investigate the use of geological datasets to map radon. This thesis also aims to provide decision-making tools that will aid with efficiently choosing appropriate methods for mapping radon depending on the intended purpose. The primary data collected in this thesis includes (a) subsoil radon gas concentration, (b) subsoil permeability and (c) topsoil geochemistry. A number of additional pre-existing data types have been used as part of this research (e.g. geological maps, geophysical data, geochemical data, indoor radon data). The work presented here utilizes a background knowledge of geological processes and applies it to model radon distribution. Within this thesis, a range of case studies are presented for different spatial scales, and utilising a range of different datasets. Castleisland in Co. Kerry was chosen as a case study due to the geologically unexplained high indoor radon occurring in the area. More than one hundred soil-gas radon and subsoil permeability measurements were collected in a systematic and representative manner over several geology types. Analysis of major and trace elements is completed for 92 topsoil samples and compared with soil-gas radon samples collected from the same locations. In addition, the geochemical data from the topsoils are investigated for covariance and correlation to determine if certain elements are commonly associated with geogenic radon. The general geostatistical methodology developed for Castleisland is scaled and repeated for the Irish Midlands. In this instance various modelling approaches are applied to 4,131 topsoil samples obtained from the Geological Survey Ireland TELLUS Midlands, and combined with a previously published national radon potential map, which was derived from TELLUS radiometric data, and a national subsoil permeability model (El?o et al., 2020). The main findings demonstrate that geology and geological attributes can offer useful insights to the distribution and expected concentration of radon. From this research, it is apparent that different spatial scales of sampling and modelling can result in significantly different radon risk maps even if the same dataset is used. Soil-gas radon and soil permeability mapping can act as a rapid method for quantifying the radon risk in relatively small (i.e. 10 km2) areas, but are not practical for considerably larger areas. Regardless of spatial scale, integration of topsoil geochemistry into radon models shows covariance occurring between elements correlated with geogenic radon, thus demonstrating that chemistry of soils can be indicative of radon prone areas. In this way legacy soil geochemistry data and geological map data can be utilised to assist efforts to highlight radon prone areas, without the need to directly measure radon indoors or in soil gas.
Applying geogenic methods and decision-making tools to model radon at local and regional scales
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Keywords: Soil-gas radon; Topsoil Geochemistry; Regional radon modelling; PCA; Soil-permeability; Radon Policy; Machine Learning; GIS; Castleisland Co Kerry; TELLUS GSI Midlands topsoil geochemistry; Indoor Radon