Application of airborne geophysical survey data in a logistic regression model to improve the predictive power of geogenic radon maps. A case study in Castleisland, County Kerry, Ireland.

In this study, a novel methodology was investigated to improve the spatial resolution and predictive power of geogenic radon maps. The data inputs comprise indoor radon measurements and seven geogenic factors including geological data (i.e. bedrock and Quaternary geology, aquifer type and soil permeability) and airborne geophysical parameters (i.e. magnetic field strength, gamma-ray radiation and electromagnetic resistivity). The methodology was tested in Castleisland southwest Ireland, a radon-prone area identified based on the results of previous indoor radon surveys. The developed model was capable of justifying almost 75 % of the variation in geogenic radon potential. It was found that the attributes with the greatest statistical significance were equivalent uranium content (EqU) and soil permeability. A new radon potential map was produced at a higher spatial resolution compared with the original map, which did not include geophysical parameter data. In the final step, the activity of radon in soil gas was measured at 87 sites, and the correlation between the observed soil gas radon and geophysical properties was evaluated. The results indicate that any model using only geophysical data cannot accurately predict soil radon activity and that geological information should be integrated to achieve a successful prediction model. Furthermore, we found that EqU is a better indicator for predicting indoor radon potential than the measured soil radon concentrations.

Detailed Geogenic Radon Potential Mapping Using Geospatial Analysis of Multiple Geo-Variables-A Case Study from a High-Risk Area in SE Ireland.

A detailed investigation of geogenic radon potential (GRP) was carried out near Graiguenamanagh town (County Kilkenny, Ireland) by performing a spatial regression analysis on radon-related variables to evaluate the exposure of people to natural radiation (i.e., radon, thoron and gamma radiation). The study area includes an offshoot of the Caledonian Leinster Granite, which is locally intruded into Ordovician metasediments. To model radon release potential at different points, an ordinary least squared (OLS) regression model was developed in which soil gas radon (SGR) concentrations were considered as the response value. Proxy variables such as radionuclide concentrations obtained from airborne radiometric surveys, soil gas permeability, distance from major faults and a digital terrain model were used as the input predictors. ArcGIS and QGIS software together with XLSTAT statistical software were used to visualise, analyse and validate the data and models. The proposed GRP models were validated through diagnostic tests. Empirical Bayesian kriging (EBK) was used to produce the map of the spatial distribution of predicted GRP values and to estimate the prediction uncertainty. The methodology described here can be extended for larger areas and the models could be utilised to estimate the GRPs of other areas where radon-related proxy values are available.

A Study of Natural Radioactivity Levels and Radon/Thoron Release Potential of Bedrock and Soil in Southeastern Ireland.

Radon (222Rn) and thoron (220Rn) account for almost two-thirds of the annual average radiation dose received by the Irish population. A detailed study of natural radioactivity levels and radon and thoron exhalation rates was carried out in a legislatively designated "high radon" area, as based on existing indoor radon measurements. Indoor radon concentrations, airborne radiometric data and stream sediment geochemistry were collated, and a set of soil samples were taken from the study area. The exhalation rates of radon (E222Rn) and thoron (E220Rn) for collected samples were determined in the laboratory. The resultant data were classified based on geological and soil type parameters. Geological boundaries were found to be robust classifiers for radon exhalation rates and radon-related variables, whilst soil type classification better differentiates thoron exhalation rates and correlated variables. Linear models were developed to predict the radon and thoron exhalation rates of the study area. Distribution maps of radon and thoron exhalation rates (range: E222Rn [0.15-1.84] and E220Rn [475-3029] Bq m-2 h-1) and annual effective dose (with a mean value of 0.84 mSv y-1) are presented. For some parts of the study area, the calculated annual effective dose exceeds the recommended level of 1 mSv y-1, illustrating a significant radiation risk. Airborne radiometric data were found to be a powerful and fast tool for the prediction of geogenic radon and thoron risk. This robust method can be used for other areas where airborne radiometric data are available.

Development of a Geogenic Radon Hazard Index-Concept, History, Experiences.

Exposure to indoor radon at home and in workplaces constitutes a serious public health risk and is the second most prevalent cause of lung cancer after tobacco smoking. Indoor radon concentration is to a large extent controlled by so-called geogenic radon, which is radon generated in the ground. While indoor radon has been mapped in many parts of Europe, this is not the case for its geogenic control, which has been surveyed exhaustively in only a few countries or regions. Since geogenic radon is an important predictor of indoor radon, knowing the local potential of geogenic radon can assist radon mitigation policy in allocating resources and tuning regulations to focus on where it needs to be prioritized. The contribution of geogenic to indoor radon can be quantified in different ways: the geogenic radon potential (GRP) and the geogenic radon hazard index (GRHI). Both are constructed from geogenic quantities, with their differences tending to be, but not always, their type of geographical support and optimality as indoor radon predictors. An important feature of the GRHI is consistency across borders between regions with different data availability and Rn survey policies, which has so far impeded the creation of a European map of geogenic radon. The GRHI can be understood as a generalization or extension of the GRP. In this paper, the concepts of GRP and GRHI are discussed and a review of previous GRHI approaches is presented, including methods of GRHI estimation and some preliminary results. A methodology to create GRHI maps that cover most of Europe appears at hand and appropriate; however, further fine tuning and validation remains on the agenda.

A comparison of sampling methods for seawater microplastics and a first report of the microplastic litter in coastal waters of Ascension and Falkland Islands.

To date there is no gold standard for sampling microplastics. Zooplankton sampling methods, such as plankton and Neuston nets, are commonly used to estimate the concentrations of microplastics in seawater, but their ability to detect microplastics is limited by their mesh size. We compared different net-based sampling methods with different mesh sizes including bongo nets (>500 µm), manta nets (>300 µm) and plankton nets (>200 µm and >400 µm) to 1 litre bottle grabbed, filtered (0.45 µm) samples. Concentrations of microplastics estimated using net-based methods were ~3 orders of magnitude less than those estimated by 1 litre grab samples. Some parts of the world with low human populations, such as Ascension Island and the Falkland Islands, lack baseline data on microplastics. Using the bottle grab sampling method we found that microplastic litter was present at these remote locations and was comparable to levels of contamination in more populated coastal regions, such as the United Kingdom.

Multi-scale crystallographic ordering in the cold-water coral Lophelia pertusa.

Lophelia pertusa is a widespread colonial cold-water coral which can form large three-dimensional habitats for benthic communities. Although it is known to construct an aragonite skeleton with optically opaque and translucent bands, details of its biomineralized structure are unclear. New crystallographic data obtained from Lophelia pertusa using electron backscatter diffraction (EBSD) reveal a remarkably high degree of multiscale self-ordering and provide unprecedented detail on crystallographic orientations within the coral skeleton. The EBSD data unequivocally demonstrate a self-regulated architecture across a range of spatial scales, resulting in a specific structure which contributes to the physical robustness of its skeleton and an evolutionary advantage in such habitats.