Brazil is envisaging a large scale plan for indoor radon assessment. Radon levels shall be mapped and priority areas identified. Given the size of the country and its diversity in natural and socio-economical respects, this is a challenging project. Pilot studies and local surveys have been performed in the past but no country-wide assessment exists. In November 2023, the IAEA organized a workshop on radon survey planning in Poços de Caldas, Minas Gerais, Brazil, to support the project. The objective was to identify items which have to be resolved before starting the actual experimental, i.e., field and laboratory work; so to speak, asking the right questions beforehand to render work as efficiently as possible. Experts from several scientific disciplines related to radon participated (physics, statistics, geology, geography, radiology, national demographic database management, etc.). Among the questions which result from experiences with past surveys, are: Which is the objective of the survey? (Assessment of radon hazard, of collective risk, of detriment attributable to radon, decision base for mitigation action, etc.) Which is the target quantity? (Mean concentration in living rooms over an area, probability to exceed a reference level within an area, status of an area as priority area, etc.) Which is the mapping support, i.e., the geographical area to which a value of the target quantity shall be assigned? (Municipality, administrative region, geological unit, grid cell, etc.) Which spatial estimation strategy is chosen: design based (inference only from radon measurements) or model based (inference from predictor quantities such as geology or ambient dose rate)? How to generate a representative sampling scheme, and how to verify it? In case of a design based strategy: which sample size is required to achieve a given accuracy of the result? More generally: which information is necessary to establish an uncertainty budget of the target quantity? How should an operational database be structured, which metadata should be included? How should a "cooking recipe" look like, which generation of new data should follow? ("Bottom-up harmonization") How can existing data be integrated into the database ("Top-down harmonisation")? How can experiences gained during pilot and local projects be transferred and "upscaled" to different environments and larger regions? How should a QA/QC scheme look like, appropriate to the project? These questions, some of which are by no means trivial, should be thoroughly discussed and answered before actually starting a survey. Some of them will be addressed in the presentation.

Safecast, a Citizen Science project devoted to monitoring ambient dose rate, initiated in Japan 2011 after the Fukushima NPP accident and soon spread worldwide. Its standard instrument is bGeigie Nano, featuring a pancake-type thin-window GM-sensor coupled to a GPS receiver and data-storage, in a sturdy plastic case allowing field use. Recorded ADR tracks are shown on a publicly accessible map on Safecast.org, containing almost 200 M records by 2022. Interpretability of results depends on quality assurance of the measurement process, covering both metrological characterization of the instrument and its practical use—relevant because users are citizens in general not familiar with metrological procedures, measurement statistics, the concept of representativeness, etc. Here we focus on the former aspect. In field use, the source of GM response is internal background (BG), ambient gamma-rays and secondary cosmic radiation (SCR). Through dedicated experiments, mainly performed on lakes (where the terrestrial gamma component is largely absent), we quantified the BG and SCR response and investigated the variance of response between instruments. We investigated conformity to count-rates Poisson statistics and the occurrence of spurious extreme signals, which can lead to artefacts in ADR maps. Impact of experimental results on practice and uncertainties are discussed.

In spite of decades of scientific research about radon, which has resulted in an immense corpus of literature and deep knowledge about all aspects of radon physics, its behaviour in the environment, its measurement and its dangers and benefits, many technical challenges remain. In course of increasingly strict regulation, new challenges emerged, mostly related to quality assured decision making in radon abatement policy and to application of advanced statistical methodology. In this paper, we give an overview about a number of topics of radon research, whose discussion and deeper investigation we find, at the one hand, important for the sake of implementing efficient radon abatement policy and interesting scientifically, on the other, as they elucidate the complexity of environmental systems up to their interaction with society in a paradigmatic manner.

Citizen Science has raised much interest for the last decades. In many scientific disciplines, citizens contribute to acquisition of field data mostly out of scientific interest. Institutional science used to look sceptically upon laypeople, but the attitude has largely changed as the benefits of Citizen Science for both active citizens and scientific institutions became apparent. One very successful project is SAFECAST, devoted to monitoring ambient ionizing radiation. The paper introduces the project and its measurement tool. Benefits and problems are discussed, the latter consisting primarily of uncertainty introduced by deviations from standard measurement protocol, in turn contributing to problems of interpretability. Altogether, measuring ambient dose rate is easy, but interpretation of results is not trivial and prone to spurious conclusions. One should have in mind that especially in case of real emergency (like Chernobyl and Fukushima accidents) the measurements of ambient dose-rate level only are not sufficient for proper decision-making on protective measures.

Between the end of September and early October 2017, Ru-106 was recorded by air monitoring stations across parts of Europe. In the environment, this purely anthropogenic radionuclide can be detected very rarely only. As far as known, Ru-106 is only used in radiotherapy and possibly in radiothermal generators. Therefore, the episode drew considerable interest in the monitoring community, although the activity concentrations and resulting exposure were far below radiological concern. Health consequences can be practically excluded except possibly near the source. Ru-106 in aerosols could be detected for several weeks and in some regions of Central and Eastern Europe tens, up to over 100 mBq/m(3) were measured as one-day means. Discussions about a possible source continue until today (early 2019). Atmospheric back-modelling led to trajectories likely originating in the Southern to Northern Ural region of Russia and possibly Northern Kazakhstan. Suspiciously, no other anthropogenic radionuclides have been observed alongside, except minute concentrations of comparatively short-lived Ru-103 (half life 39 d vs. 376 d for Ru-106). Due to the absence of other anthropogenic radionuclides, a reactor accident can be excluded, although both Ru isotopes are fission products generated in nuclear reactors. The exposure resulting from Ru-106 activity concentration in air exceeded 200 mBq x d/m(3) in some parts of Central and Eastern Europe. This leads to inhalation doses of up to about 0.3 mu Sv regionally, assuming the radiologically most efficient speciation, lacking better information, and inhalation dose conversion factors from ICRP 119. We show an interpolated map of the dose distribution over parts of Europe where sufficient measurements are available to us. Overlaying population density, we give an estimate of collective dose. The opportunity is also used to give a short review of origin, properties and use of Ru-106, as well as of accidents which involved release of this radionuclide.

The vertical distribution of radio-caesium (137Cs and 134Cs) in undisturbed soil profiles of grassland and forest soils, derived from the Fukushima-Daiichi Nuclear Power Plant (FDNPP) accident that occurred on 11 March 2011, was studied. Surface soil and depth profile soil samples were collected from six locations within the 20 km zone of FDNPP, during November 2012 and June 2013. The activity ratio for 137Cs and 134Cs was found to be almost constant about 1 within the soil profiles as well as in the surface soil, indicative of FDNPP accident origin. From soil depth profile distribution of Cs activity, it is observed that Cs is strongly bound to soil materials, which slows Cs migration. > 90% of the activity was found to be retained within the upper 5 cm layer. Retardation of Cs movement has been quantified by measuring sorption of Cs in soil in terms of distribution coefficient (Kd) using the laboratory batch method. Faster migration has been observed in case of forest land soil compared to grassland soil. The empirical migration velocity of Cs radio isotope was estimated from the depth profile Cs concentration and found to vary from 1.1 to 1.7 and 0.85 to 3.5 cm y− 1 in grassland and forest soil, respectively. The residential half life for Cs isotopes was found to be 1.03–7.75 y and 1.18–4.67 y for grassland and forest land respectively using a compartmental model. In addition to the empirical analysis of the profiles, analytical models were fitted to the data which may help elucidate the physical nature of the transport of trace elements.

Machine learning is a class of statistical techniques which has proven to be a powerful tool for modelling the behaviour of complex systems, in which response quantities depend on assumed controls or predictors in a complicated way. In this paper, as our first purpose, we propose the application of machine learning to reconstruct incomplete or irregularly sampled data of time series indoor radon (222Rn). The physical assumption underlying the modelling is that Rn concentration in the air is controlled by environmental variables such as air temperature and pressure. The algorithms "learn" from complete sections of multivariate series, derive a dependence model and apply it to sections where the controls are available, but not the response (Rn), and in this way complete the Rn series. Three machine learning techniques are applied in this study, namely random forest, its extension called the gradient boosting machine and deep learning. For a comparison, we apply the classical multiple regression in a generalized linear model version. Performance of the models is evaluated through different metrics. The performance of the gradient boosting machine is found to be superior to that of the other techniques. By applying learning machines, we show, as our second purpose, that missing data or periods of Rn series data can be reconstructed and resampled on a regular grid reasonably, if data of appropriate physical controls are available. The techniques also identify to which degree the assumed controls contribute to imputing missing Rn values. Our third purpose, though no less important from the viewpoint of physics, is identifying to which degree physical, in this case environmental variables, are relevant as Rn predictors, or in other words, which predictors explain most of the temporal variability of Rn. We show that variables which contribute most to the Rn series reconstruction, are temperature, relative humidity and day of the year. The first two are physical predictors, while "day of the year" is a statistical proxy or surrogate for missing or unknown predictors.

Cryoconites ("cold dust", derived from the Greek) are aeolian sediments accumulated on glacier surfaces. In cryoconites from the surface of the Stubacher Sonnblickkees, a temperate Austrian glacier, extremely high activity concentrations of artificial and natural radionuclides were found. Artificial radionuclides stem from two clearly distinguishable sources, global fallout from the nuclear weapons testing era deposited over a period of years until roughly 1966 and the fallout from Chernobyl in 1986, which was essentially deposited as a single input during one week. Anthropogenic radionuclides identified were Cs-137, Cs-134, (238)pu, (239+240)pu, Sr-90, (241)A m, (CO)-C-612, Sb-125, Eu-154, and Bi-207. The naturally occurring radionuclides detected were the long-lived radon decay product Pb-210, the primordial radionuclide K-4 and the cosmogenic Be-7. Isotopic ratios of Cs-134/Cs-137 and Pu239+240/(23)8Pu were used to separate the nuclide inventory into the contributions of the two aforementioned sources, which show varying degrees of mixing and provide information on the mixing age of the cryoconites. Since isotopic ratios of Pu often have high uncertainties due to low absolute concentrations, age estimation based on this method can be quite inaccurate. Additional information about the age of cryoconites was obtained through analysis of 210Pb, which is constantly deposited over time. (C) 2017 Published by Elsevier Ltd.

This article deals with the variation of radon (Rn), thoron (Tn) and their progeny concentrations expressed in terms of equilibrium equivalent concentrations (EERC and EETC), in 40 houses, in four villages of Sokobanja municipality, Southern Serbia. Two types of passive detectors were used: (1) discriminative radon-thoron detector for simultaneous Rn and Tn gases measurements and (2) direct Tn and Rn progeny sensors (DRPS/DTPS) for measuring Rn and Tn progeny concentrations. Detectors were exposed simultaneously for a single period of 12 months. Variations of Tn and EETC appear higher than those of Rn and EERC. Analysis of the spatial variation of the measured concentrations is also reported. This work is part of a wider survey of Rn, Tn and their progeny concentrations in indoor environments throughout the Balkan region started in 2011 year.

An extensive network of dose rate monitoring stations continuously measures ambient dose rate across Europe, as part of the EURDEP system. Its purpose is early warning in radiological emergencies and documenting its temporal and spatial evolution. In normal conditions, when there is no contribution to the dose rate signal coming from fresh anthropogenic contamination, the data represent the radiation "background", i.e. the combined natural radiation and existing anthropogenic contamination (by global and Chernobyl fallout). These data are being stored, but have so far not been evaluated in depth, or used for any purpose. In the framework of the EU project 'European Atlas of Natural Radiation' the idea has emerged to exploit these data for generating a map of natural terrestrial gamma radiation. This component contributes to the total radiation exposure and knowing its geographical distribution can help establishing local 'radiation budgets'. A further use could be found in terrestrial dose rate as a proxy of the geogenic radon potential, as both quantities are related by partly the same source, namely uranium content of the ground. In this paper, we describe in detail the composition of the ambient dose equivalent rate as measured by the EURDEP monitors with respect to its physical nature and to its sources in the environment. We propose and compare methods to recover the terrestrial component from the gross signal. This requires detailed knowledge of detector response. We consider the probes used in the Austrian, Belgian and German dose rate networks, which are the respective national networks supplying data to EURDEP. It will be shown that although considerable progress has been made in understanding the dose rate signals, there is still space for improvement in terms of modelling and model parameters. An indispensable condition for success of the endeavour to establish a Europe-wide map of terrestrial dose rate background is progress in harmonising the European dose rate monitoring network.

Recognized as a significant health hazard, radon (Rn) has been given increasing attention for years. Surveys of different kinds have been performed in many countries to assess the intensity and the geographical extent of possible Rn problems. Common surveys cover mainly dwellings, the indoor place with highest occupancy, and schools, where people spend a large fraction of their lifetime and which can also be considered exemplary for Rn exposure at workplaces; it has however been observed that relating them is difficult. It was unclear whether residential Rn at a location, or in a region, can be predicted by Rn at a school of that location, or vice versa. To current knowledge, no general rule seems applicable, as few models to describe the relationship between Rn in dwellings and in schools have been developed.In Southern Serbia, a Rn survey in a predominantly rural region was based on measurements in primary schools. The question arose whether or to which degree the results can be considered as indicative or even representative for residential Rn concentrations. To answer the question an additional survey of indoor Rn concentrations in dwellings was initiated, designed and performed in Sokobanja district in 2010-2012 in a manner to be able to detect a relationship if it exists. In the study region, 108 dwellings in 12 villages and towns were selected, with one primary school each.In this paper, we investigate how a relation between Rn in schools and dwellings could be identified and quantified, by developing a model and using experimental data from both the above main and additional surveys. The key criterion is the hypothesis that the relation dwellings schools, if it exists, is stronger for dwellings closer to a school than for those dwellings further away. We propose methods to test the hypothesis.As result, the hypothesis is corroborated at 95% significance level. More specifically, on town level (typical size about 1 km), the Rn concentration ratio dwelling/school is about 0.8 (geometrical mean), with geometrical standard deviation (GSD) about 1.9. For dwelling and school hypothetically in the same location, the ratio is estimated about 0.7 with GSD about 1.5.We think that the methodology can be applied to structurally similar problems. The results could be used to create "conditional maps" of Rn concentration in dwellings, i.e., for example a map of probabilities that indoor Rn concentrations in dwellings exceed 100 Bq/m(3), as function of Rn concentration in the local school. (C) 2016 Elsevier Ltd. All rights reserved.

Variance of radon concentration in dwelling atmosphere is analysed with regard to geogenic and anthropogenic influencing factors. Analysis includes review of 81 national and regional indoor radon surveys with varying sampling pattern, sample size and duration of measurements and detailed consideration of two regional surveys (Sverdlovsk oblast, Russia and Niška Banja, Serbia). The analysis of the geometric standard deviation revealed that main factors influencing the dispersion of indoor radon concentration over the territory are as follows: area of territory, sample size, characteristics of measurements technique, the radon geogenic potential, building construction characteristics and living habits. As shown for Sverdlovsk oblast and Niška Banja town the dispersion as quantified by GSD is reduced by restricting to certain levels of control factors. Application of the developed approach to characterization of the world population radon exposure is discussed.

This article reports results of the first investigations on indoor radon, thoron and their decay products concentration in 25 primary schools of Banja Luka, capital city of Republic Srpska. The measurements have been carried out in the period from May 2011 to April 2012 using 3 types of commercially available nuclear track detectors, named: long-term radon monitor (GAMMA 1)- for radon concentration measurements (C-Rn); radon-thoron discriminative monitor (RADUET) for thoron concentration measurements (C-Tn); while equilibrium equivalent radon concentration (EERC) and equilibrium equivalent thoron concentrations (EETC) measured by Direct Radon Progeny Sensors/Direct Thoron Progeny Sensors (DRPS/DTPS) were exposed in the period November 2011 to April 2012. In each school the detectors were deployed at 10 cm distance from the wall. The obtained geometric mean concentrations were C-Rn = 99 Bq m(-3) and C-Tn = 51 Bq m(-3) for radon and thoron gases respectively. Those for equilibrium equivalent radon concentration (EERC) and equilibrium equivalent thoron concentrations (EETC) were 11.2 Bq m(-3) and 0.4 Bq m(-3), respectively. The correlation analyses showed weak relation only between C-Rn and C-Tn as well as between C-Tn and EETC. The influence of the school geographical locations and factors linked to buildings characteristic in relation to measured concentrations were tested. The geographical location and floor level significantly influence C-Rn while C-Tn depend only from building materials (ANOVA, p <= 0.05). The obtained geometric mean values of the equilibrium factors were 0.123 for radon and 0.008 for thoron. (C) 2015 Elsevier Ltd. All rights reserved.

According to the EURATOM (European Atomic Energy Community) Treaty, one of the missions of the Joint Research Centre (JRC) of the European Commission (EC) is to collect, process, evaluate and present data on environmental radioactivity. In 2006, the JRC started the 'European Atlas of Natural Radiation' project, in order to give an overview of the geographic distribution of sources of, and exposures to, natural radiation. As a first task, a map of indoor radon concentration was created, because in most cases this is the most important contribution to exposure, and since it could be expected that data collection would take quite some time, because radon (Rn) surveys are very differently advanced between European countries. The authors show the latest status of this map. A technically more ambitious map proved the one of the geogenic Rn potential (RP), due to heterogeneity of data sources across Europe and the need to develop models to estimate a harmonised quantity which adequately measures or classifies the RP. Further maps currently in the making include those of secondary cosmic radiation, of terrestrial gamma radiation and of the concentrations of the elements U, Th and K that are its source. In this article, the authors show the progress of some of these maps.

Human hair and nails can be considered as bio-indicators of the public exposure to certain natural radionuclides and other toxic metals over a long period of months or even years. The level of elements in hair and nails usually reflect their levels in other tissues of body. Niška Banja, a spa town located in southern Serbia, with locally high natural background radiation was selected for the study. To assess public exposure to the trace elements, hair and nail samples were collected and analyzed. The concentrations of uranium, thorium and some trace and toxic elements (Mn, Ni, Cu, Sr, Cd, and Cs) were determined using inductively coupled plasma mass spectrometry (ICP-MS). U and Th concentrations in hair varied from 0.0002 to 0.0771 μg/g and from 0.0002 to 0.0276 μg/g, respectively. The concentrations in nails varied from 0.0025 to 0.0447 μg/g and from 0.0023 to 0.0564 μg/g for U and Th, respectively. We found significant correlations between some elements in hair and nails. Also indications of spatial clustering of high values could be found. However, this phenomenon as well as the large variations in concentrations of heavy metals in hair and nail could not be explained. As hypotheses, we propose possible exposure pathways which may explain the findings, but the current data does not allow testing them.

In 2006, the Joint Research Centre of the European Commission launched a project to map radon at the European level, as part of a planned European Atlas of Natural Radiation. It started with a map of indoor radon concentrations. As of May 2014, this map includes data from 24 countries, covering a fair part of Europe. Next, a European map of geogenic radon, intended to show 'what earth delivers' in terms of radon potential (RP), was started in 2008. A first trial map has been created, and a database was established to collect all available data relevant to the RP. The Atlas should eventually display the geographical distribution of physical quantities related to natural radiation. In addition to radon, it will comprise maps of quantities such as cosmic rays and terrestrial gamma radiation. In this paper, the authors present the current state of the radon maps and the Atlas.

In this work the strong influence of geological factors on the variability of indoor radon is found in two of three geologically very different regions of South-Eastern Europe. A method to estimate the annual mean concentration when one seasonal measurement is missing is proposed. Large differences of radon concentrations in different rooms of the same house and significant difference in radon concentrations in one season comparing it to the others are noted in certain cases. Geological factors that can lead to such behavior are discussed.