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Quantifying Gamma Radiation Exposure and Radon / Thoron Emission in Irish Building Materials

This project assessed the radiological risks associated with commonly used building materials in Ireland by examining their gamma radiation levels and radon/thoron exhalation rates. Building materials can contribute to radiation exposure through naturally occurring radionuclides (NORM) that emit gamma rays and release radon (²²²Rn) and thoron (²²⁰Rn) gases, which can accumulate indoors and increase the risk of lung cancer.

The research was conducted in two phases. In phase one, we identified materials with potentially high NORM levels using remote radiometric data from the Tellus survey, focusing on quarries where materials such as granite and other aggregates are sourced. In phase two, laboratory tests measured radioelement activity, chemical composition, and mineralogical characteristics, along with radon/thoron exhalation rates.

The results provided data on gamma radiation levels and radon/thoron release potential, allowing us to evaluate the radiological risk posed by different materials when used in construction. We also modeled indoor radon and thoron concentrations, emphasizing the importance of material selection for maintaining safe indoor air quality, especially in energy-efficient buildings.

This project aims to support the construction industry and regulatory bodies in Ireland by ensuring compliance with radiation protection standards and promoting safer building practices to minimize indoor radiation exposure for occupants.

Projects Completed in 2024

Application of GIS and spatiotemporal analyses in viral infection modelling using multiple datasets – A case study on the SARS-CoV-2 epidemic

Viral and infectious diseases, such as COVID-19, pose a significant public health threat. To develop an early warning system for new pandemics or emerging virus variants, studying its epidemiology is essential. This study creates a geospatial model to predict the weekly contagion and lethality rates of COVID-19 in Ireland. Over forty parameters, including atmospheric pollutants, meteorological variables, sociodemographic factors, and lockdown phases, serve as input variables for the model. We identify significant predictors for new cases and death tolls, using QGIS for data processing and a principal component regression (PCR) model developed with the XLSTAT statistical add-on. The models predict over half of the variations in contagion and lethality rates, demonstrating their potential to inform future high-risk condition prediction systems. Future models could incorporate additional parameters, such as death rates in care homes, contagion and mortality percentages among health workers, and compliance levels with social distancing.

Development of a Web-Based Geodatabase Platform for Natural Hazard Assessment and Multi-Hazard Susceptibility Mapping

This two-phased project for Enterprise Ireland, completed in 2024, involved creating an advanced web-based platform to assess, model, and map natural hazards across Ireland. The platform integrates over 200 geospatial variables (with more than 60 million data points), covering geology, digital terrain models, weather, and land cover, among others. Using robust geostatistical models, we generated high-resolution risk maps for hazards such as landslides, flooding, soil erosion, radon, thoron, gamma radiation, and climate change susceptibility.

Phase one focused on developing a 500-meter resolution grid, where each cell provides a detailed view of individual hazard risks. Phase two combined these indexes to create a multi-hazard risk map, categorized into five levels from low to high, allowing professionals and the public to monitor and assess evolving risk levels.

Designed to support engineers, planners, and local authorities, this platform enables informed decision-making in spatial planning and natural hazard management. It also serves as a flexible resource for future hazard mapping and geotechnical studies, providing a lasting impact on risk resilience efforts across Ireland.

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