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Radon is a natural and radioactive noble gas, which may accumulate indoors and cause lung cancers after long term-exposure. Being a decay product of Uranium 238, it originates from the ground and is spatially variable. Many environmental (i.e., geology, tectonic, soils) and architectural factors (i.e., building age, floor) influence its presence indoors, which make it difficult to predict. However, different methods have been developed and applied to identify radon prone areas and buildings. This paper presents the results of a systematic literature review of suitable statistical methods willing to identify buildings and areas where high indoor radon concentrations might be found. The application of these methods is particularly useful to improve the knowledge of the factors most likely to be connected to high radon concentrations. These types of methods are not so commonly used, since generally statistical methods that study factors predictive of radon concentration are focused on the average concentration and aim to identify factors that influence the average radon level. In this paper, an attempt has been made to classify the methods found, to make their description clearer. Four main classes of methods have been identified: descriptive methods, regression methods, geostatistical methods, and machine learning methods. For each presented method, advantages and disadvantages are presented while some applications examples are given. The ultimate purpose of this overview is to provide researchers with a synthesis paper to optimize the selection of the method to identify radon prone areas and buildings.

BackgroundAlthough data on outdoor gamma radiation are available for many countries, they have generally been obtained with measurements performed in undisturbed environments instead of in urban areas where most of the population lives. Only one large national survey, with on-site measurements in urban areas, has been identified worldwide, probably due to high costs (e.g., personnel and instrumentation) and difficulties in selecting measuring points.MethodsA campaign of outdoor gamma radiation measurements has been carried out in the entire Italian territory. All measurement points were selected at the infrastructures of an Italian telecommunications company as representatives of all the possible situations of outdoor exposure to gamma radiation for population in urban areas. Ten replicates of portable gamma (X) detectors carried out all the measurements.ResultsApproximately 4,000 measurements have been performed. They are distributed across 2,901 Italian municipalities, accounting for 75% of the Italian population. The national population-weighted mean of the gamma ambient dose equivalent rate (ADER) is 117 nSv h−1, and it ranges from 62 to 208 nSv h−1 and from 40 to 227 nSv h−1 for 21 regions and 107 provinces, respectively. The average variability at the municipal level, in terms of the coefficient of variation (CV) is 21%, ranging from 3 to 84%. The impact of land coverage and the distance from a building on the outdoor gamma radiation level was assessed with complementary measurements, leading to differences ranging from −40 to 50% and to 50%, respectively.ConclusionA representative campaign of outdoor gamma dose rate measurements has been performed in Italy, only in urban areas, to assess the exposure effect due to outdoor gamma radiation on the population. It is the largest national campaign in urban areas worldwide, with a total of 3,876 on-site measurements. The land coverage and the distance from surrounding buildings were recognized to strongly affect outdoor gamma radiation levels, leading to high variability within small areas. The collaboration with a company that owns a network of facilities on a national territory as dense as the residing population made this survey feasible and affordable. Other countries might adopt this methodology to conduct national surveys in urban environments.

Naturally occurring radioactive materials (NORM) contribute to the dose arising from radiation exposure for workers, public and non-human biota in different working and environmental conditions. Within the EURATOM Horizon 2020 RadoNorm project, work is ongoing to identify NORM exposure situations and scenarios in European countries and to collect qualitative and quantitative data of relevance for radiation protection. The data obtained will contribute to improved understanding of the extent of activities involving NORM, radionuclide behaviours and the associated radiation exposure, and will provide an insight into related scientific, practical and regulatory challenges.The development of a tiered methodology for identification of NORM exposure situations and complementary tools to support uniform data collection were the first activities in the mentioned project NORM work. While NORM identification methodology is given in Michalik et al., 2023, in this paper, the main details of tools for NORM data collection are presented and they are made publicly available.The tools are a series of NORM registers in Microsoft Excel form, that have been comprehensively designed to help (a) identify the main NORM issues of radiation protection concern at given exposure situations, (b) gain an overview of materials involved (i.e., raw materials, products, by-products, residues, effluents), c) collect qualitative and quantitative data on NORM, and (d) characterise multiple hazards exposure scenarios and make further steps towards development of an integrated risk and exposure dose assessment for workers, public and non-human biota.Furthermore, the NORM registers ensure standardised and unified characterisation of NORM situations in a manner that supports and complements the effective management and regulatory control of NORM processes, products and wastes, and related exposures to natural radiation worldwide.