Geographical distribution of the annual mean radon concentrations in primary schools of Southern Serbia - application of geostatistical methods

Radon and lung cancer: Current status and future prospects

Beyond tobacco smoking, radon takes its place as the second most significant contributor to lung cancer, excluding hereditary and other biologically related factors. Radon and its byproducts play a pivotal role in exposing humans to elevated levels of natural radiation. Approximately 10-20 % of lung cancer cases worldwide can be attributed to radon exposure, leading to between 3 % and 20 % of all lung cancer-related deaths. Nevertheless, a knowledge gap persists regarding the association between radon and lung cancer, impeding radon risk reduction initiatives globally. This review presents a comprehensive overview of the current state of research in epidemiology, cell biology, dosimetry, and risk modeling concerning radon exposure and its relevance to lung cancer. It also delves into methods for measuring radon concentrations, monitoring radon risk zones, and identifying priorities for future research.

Gini Method Application: Indoor Radon Survey in Kpong, Ghana

In this study, the indoor radon concentrations map, starting from a sparse measurements survey, was realized with the Gini index method. This method was applied on a real dataset coming from indoor radon measurements carried out in Kpong, Ghana. The Gini coefficient variogram is shown to be a good estimator of the inhomogeneity degree of radon concentration because it allows for better constraining of the critical distance below which the radon geological source can be considered as uniform. The indoor radon measurements were performed in 96 dwellings in Kpong, Ghana. The data showed that 84% of the residences monitored had radon levels below 100 Bqm−3, versus 16% having levels above the World Health Organization’s (WHO) suggested reference range (100 Bqm−3). The survey indicated that the average indoor radon concentration (IRC) was 55 ± 36 Bqm−3. The concentrations range from 4–176 Bqm−3. The mean value 55 Bqm−3 is 38% higher than the world’s average IRC of 40 Bqm−3 (UNSCEAR, 1993).

Sorrentina Peninsula: Geographical Distribution of the Indoor Radon Concentrations in Dwellings—Gini Index Application

The radon isotope (222Rn, half-life 3.8 days) is a radioactive byproduct of the 238U decay chain. Because radon is the second biggest cause of lung cancer after smoking, dense maps of indoor radon concentration are required to implement effective locally based risk reduction strategies. In this regard, we present an innovative method for the construction of interpolated maps (kriging) based on the Gini index computation to characterize the distribution of Rn concentration. The Gini coefficient variogram has been shown to be an effective predictor of radon concentration inhomogeneity. It allows for a better constraint of the critical distance below which the radon geological source can be considered uniform, at least for the investigated length scales of variability; it also better distinguishes fluctuations due to environmental predisposing factors from those due to random spatially uncorrelated noise. This method has been shown to be effective in finding larger-scale geographical connections that can subsequently be connected to geological characteristics. It was tested using real dataset derived from indoor radon measurements conducted in the Sorrentina Peninsula in Campania, Italy. The measurement was carried out in different residences using passive detectors (CR-39) for two consecutive semesters, beginning in September–November 2019 and ending in September–November 2020, to estimate the yearly mean radon concentration. The measurements and analysis were conducted in accordance with the quality control plan. Radon concentrations ranged from 25 to 722 Bq/m3 before being normalized to ground level, and from 23 to 933 Bq/m3 after being normalized, with a geometric mean of 120 Bq/m3 and a geometric standard deviation of 1.35 before data normalization, and 139 Bq/m3 and a geometric standard deviation of 1.36 after data normalization. Approximately 13% of the tests conducted exceeded the 300 Bq/m3 reference level set by Italian Legislative Decree 101/2020. The data show that the municipalities under investigation had no influence on indoor radon levels. The geology of the monitored location is interesting, and because soil is the primary source of Rn, risk assessment and mitigation for radon exposure cannot be undertaken without first analyzing the local geology. This research examines the spatial link among radon readings using the mapping based on the Gini method (kriging).

Radon risk mapping: A new geostatistical method based on Lorenz Curve and Gini index

In confined spaces such as living environments and workplaces, the concentration levels of radon (Rn²²²) can be very high as compared to the external environment. Since Rn has been classified as the second leading cause of lung cancer after cigarette smoking, to apply efficient locally based risk reduction actions, dense maps of indoor radon concentration are needed. These maps would provide information about the areas prone to high radon concentrations and therefore more dangerous to human health. The soil is the primary source of the Rn, hence the risk assessment and reduction for the radon exposure cannot disregard the identification of the local geology. In this regard, we propose an innovative method, based on the Gini index computation, for the realization of interpolated maps (kriging) to describe the distribution of concentration of Rn. To validate the method, a tool that simulates sets of radon concentrations is used, whose variability is, to the first order, controlled by a priori imposed different lithologies. A systematic comparison is made between the results achieved by means of a classically used geostatistical method and the proposed Gini-based tool. We show how, by using this latter tool, the kriging solutions appear to be more robust to resolve the different geogenic radon sources independently from the number of the available measurements.

Radon-222: environmental behavior and impact to (human and non-human) biota

As an inert radioactive gas, ²²²Rn could be easily transported to the atmosphere via emanation, migration, or exhalation. Research measurements pointed out that ²²²Rn activity concentration changes during the winter and summer months, as well as during wet and dry season periods. Changes in radon concentration can affect the atmospheric electric field. At the boundary layer near the ground, short-lived daughters of ²²²Rn can be used as natural tracers in the atmosphere. In this work, factors controlling ²²²Rn pathways in the environment and its levels in soil gas and outdoor air are summarized. ²²²Rn has a short half-life of 3.82 days, but the dose rate due to radon and its radioactive progeny could be significant to the living beings. Epidemiological studies on humans pointed out that up to 14% of lung cancers are induced by exposure to low and moderate concentrations of radon. Animals that breed in ground holes have been exposed to the higher doses due to radiation present in soil air. During the years, different dose-effect models are developed for risk assessment on human and non-human biota. In this work are reviewed research results of ²²²Rn exposure of human and non-human biota.

Associations Between School Characteristics and Classroom Radon Concentrations in Utah's Public Schools: A Project Completed by University Environmental Health Students

Radon (²²²Rn), a radioactive gas, is the second leading cause of lung cancer deaths in the U.S. Classroom radon concentrations in public schools in our target area had never been measured or had not been measured in many years. We had university students, primarily enrolled in environmental health courses, measure radon concentrations in 2289 classrooms in 66 of Utah’s public schools and identify school characteristics associated with classroom radon concentrations. The geometric mean (GM) classroom radon concentration was 31.39 (95% confidence interval (CI): 27.16, 36.28) Bq/m³ (GM: 0.85; 95% CI: 0.72, 0.98 pCi/L). Thirty-seven (2%) classrooms in 13 (20%) schools had radon concentrations at or above the U.S. Environmental Protection Agency’s (EPA) recommended action level of 148 Bq/m³ (4.0 pCi/L). Number of classrooms had a u-shaped association with classroom radon concentrations. The year the heating, ventilation, and air conditioning (HVAC) system was installed was inversely associated with having classroom radon concentrations at or above the EPA’s recommended action level. Number of classrooms and number of students had u-shaped associations with having classroom radon concentrations at or above the EPA’s recommended action level. Classroom radon concentrations decreased when schools’ HVAC systems were on. Replacing HVAC systems and turning/keeping them on may be effective radon mitigation strategies to prevent radon-associated lung cancer, especially for small and large schools.

County-level indoor radon concentration mapping and uncertainty assessment in South Korea using geostatistical simulation and environmental factors

This paper presents a geostatistical simulation approach to not only map the county-level indoor radon concentration (IRC) distributions in South Korea, but also quantify the uncertainty that can be used as decision-supporting information. For county-level IRC mapping in South Korea, environmental factors including geology, radium concentration in surface soil, gravel content in subsoil, and fault line density, which are known to be associated with the source and migration of radon gas, were incorporated into IRC measurements using multi-Gaussian kriging with local means. These four environmental factors could account for about 36% of the variability of noise-filtered IRCs, implying that regional variations of IRCs were affected by these factors. Sequential Gaussian simulation was then applied to generate alternative realizations of county-level IRC distributions. By summarizing the multiple simulation results, we identified some counties that lay on the great limestone series showed elevated IRCs. In addition, there were some counties in which the proportion of grids exceeding the recommended level was high but the uncertainty was also large according to the analysis of several uncertainty measures, which indicates that additional sampling is required for these counties. From the local cluster analysis in conjunction with simulation results, we found that the counties with higher levels of IRC belonged to the statistically significant clusters of high values, and these counties should be the prime targets for radon management and in-depth survey. The geographical distributions of IRC and uncertainty measures presented in this study provide guidance for effective radon management if they are consistently combined with both future IRC measurements and a geogenic radon potential map.

Analysis of the spatial variation of indoor radon concentrations (national survey in Bulgaria)

This paper presents the methodology and results of the national radon survey in Bulgaria and its spatial variability. The measurements were carried out in 2778 dwellings using CR-39 track detectors over two successive 9 and 3-month periods from April 2015 to March 2016. The arithmetic (AM) and geometric (GM) means of annual indoor radon concentration were 111 ± 105 Bq/m³ and 81 Bq/m³ (GSD = 2.15), respectively. The distribution of data has been accepted to be log-normal. Two hypotheses have been investigated in the paper. The first one was a spatial variation of indoor radon concentration and the second was spatiality of the factor that influences radon variation. The indoor radon concentrations in the 28 districts have been significantly different, which prove the first hypothesis. The influence of the factors, geology (geotectonic unit, type of rock, and faults distance of the measuring site), type of the region, and the presence of the basement in the building on radon spatial variation, was examined. The analyses have been shown that they significantly affect radon variations but with a relatively small contribution in comparison to the radon variation between district. Furthermore, the significance and contribution of the investigated factors were different in each district, which confirmed the second hypothesis for their spatiality.

REVIEW OF INDOOR RADON CONCENTRATIONS IN SCHOOLS AND KINDERGARTENS

Analysis includes review of 63 national and regional indoor radon surveys in kindergartens and schools. Preliminary assessment of the worldwide population weighted characteristics of radon concentration in children's institutions is: arithmetic mean = 59 and geometric mean = 36 Bq/m3. Higher indoor radon concentrations in children's institutions in comparison with the dwellings can be explained by characteristics of ventilation, attendance regime and construction features. Special protocol of measurements in the kindergartens and schools is required.

The use of gamma-survey measurements to better understand radon potential in urban areas

Accounting for as much as 14% of all lung cancers worldwide, cumulative radon progeny exposure is the leading cause of lung cancer among never-smokers both internationally and in the United States. To understand the risk of radon progeny exposure, studies have mapped radon potential using aircraft-based measurements of gamma emissions. However, these efforts are hampered in urban areas where the built environment obstructs aerial data collection. To address part of this limitation, this study aimed to evaluate the effectiveness of using in situ gamma readings (taken with a scintillation probe attached to a ratemeter) to assess radon potential in an urban environment: DeKalb County, part of the Atlanta metropolitan area, Georgia, USA. After taking gamma measurements at 402 survey sites, empirical Bayesian kriging was used to create a continuous surface of predicted gamma readings for the county. We paired these predicted gamma readings with indoor radon concentration data from 1351 residential locations. Statistical tests showed the interpolated gamma values were significantly but weakly positively related with indoor radon concentrations, though this relationship is decreasingly informative at finer geographic scales. Geology, gamma readings, and indoor radon were interrelated, with granitic gneiss generally having the highest gamma readings and highest radon concentrations and ultramafic rock having the lowest of each. Our findings indicate the highest geogenic radon potential may exists in the relatively undeveloped southeastern part of the county. It is possible that in situ gamma, in concert with other variables, could offer an alternative to aerial radioactivity measurements when determining radon potential, though future work will be needed to address this project's limitations.

INDOOR RADON, THORON AND THEIR PROGENY CONCENTRATIONS IN HIGH THORON RURAL SERBIA ENVIRONMENTS

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.

Thoron, radon and air ions spatial distribution in indoor air

Spatial distribution of radioactive gasses thoron (Tn) and radon (Rn) in indoor air of 9 houses mostly during winter period of 2013 has been studied. According to properties of alpha decay of both elements, air ionization was also measured. Simultaneous continual measurements using three Rn/Tn and three air-ion active instruments deployed on to three different distances from the wall surface have shown various outcomes. It has turned out that Tn and air ions concentrations decrease with the distance increase, while Rn remained uniformly distributed. Exponential fittings function for Tn variation with distance was used for the diffusion length and constant as well as the exhalation rate determination. The obtained values were similar with experimental data reported in the literature. Concentrations of air ions were found to be in relation with Rn and obvious, but to a lesser extent, with Tn.

The relation between radon in schools and in dwellings: A case study in a rural region of Southern Serbia

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/m³, as function of Rn concentration in the local school.

Geogenic and anthropogenic impacts on indoor radon in the Techa River region

Indoor radon concentration was studied in the 14 settlements located near the Techa River, which was contaminated by radioactive wastes in 1950-s. Results of the radon survey were used for analysis of the relationship between the indoor radon and main geologic factors (Pre-Jurassic formations, Quaternary sediments and faults), local geogenic radon potential and anthropogenic factors. Main influencing factors explain 58% of the standard deviation of indoor radon concentration. Association of the air exchange influence over radon concentration with underlying geological media was related to different contributions of geogenic advective and diffusive radon entries. The properties of geological formation to transfer radon gas in interaction with the house can be considered within the radon geogenic potential concept. The study of the radon exposure of the Techa River population can be used to estimate the contribution of natural radon to the overall radiation exposure of the local population during the period of radioactive waste discharges.

Variation of indoor radon concentration and ambient dose equivalent rate in different outdoor and indoor environments

Subject of this study is an investigation of the variations of indoor radon concentration and ambient dose equivalent rate in outdoor and indoor environments of 40 dwellings, 31 elementary schools and five kindergartens. The buildings are located in three municipalities of two, geologically different, areas of the Republic of Macedonia. Indoor radon concentrations were measured by nuclear track detectors, deployed in the most occupied room of the building, between June 2013 and May 2014. During the deploying campaign, indoor and outdoor ambient dose equivalent rates were measured simultaneously at the same location. It appeared that the measured values varied from 22 to 990 Bq/m(3) for indoor radon concentrations, from 50 to 195 nSv/h for outdoor ambient dose equivalent rates, and from 38 to 184 nSv/h for indoor ambient dose equivalent rates. The geometric mean value of indoor to outdoor ambient dose equivalent rates was found to be 0.88, i.e. the outdoor ambient dose equivalent rates were on average higher than the indoor ambient dose equivalent rates. All measured can reasonably well be described by log-normal distributions. A detailed statistical analysis of factors which influence the measured quantities is reported.

Geostatistical simulations for radon indoor with a nested model including the housing factor

The radon prone areas definition is matter of many researches in radioecology, since radon is considered a leading cause of lung tumours, therefore the authorities ask for support to develop an appropriate sanitary prevention strategy. In this paper, we use geostatistical tools to elaborate a definition accounting for some of the available information about the dwellings. Co-kriging is the proper interpolator used in geostatistics to refine the predictions by using external covariates. In advance, co-kriging is not guaranteed to improve significantly the results obtained by applying the common lognormal kriging. Here, instead, such multivariate approach leads to reduce the cross-validation residual variance to an extent which is deemed as satisfying. Furthermore, with the application of Monte Carlo simulations, the paradigm provides a more conservative radon prone areas definition than the one previously made by lognormal kriging.

Long-term measurements of radon, thoron and their airborne progeny in 25 schools in Republic of Srpska

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.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units

PURPOSE

According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction.

METHOD

About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART).

RESULTS

The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty.

CONCLUSION

Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland

PURPOSE

The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information.

METHODS

We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map.

RESULTS

Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation.

CONCLUSIONS

IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

Definition of radon prone areas in Friuli Venezia Giulia region, Italy, using geostatistical tools

Studying the geographical distribution of indoor radon concentration, using geostatistical interpolation methods, has become common for predicting and estimating the risk to the population. Here we analyse the case of Friuli Venezia Giulia (FVG), the north easternmost region of Italy. Mean value and standard deviation are, respectively, 153 Bq/m(3) and 183 Bq/m(3). The geometric mean value is 100 Bq/m(3). Spatial datasets of indoor radon concentrations are usually affected by clustering and apparent non-stationarity issues, which can eventually yield arguable results. The clustering of the present dataset seems to be non preferential. Therefore the areal estimations are not expected to be affected. Conversely, nothing can be said on the non stationarity issues and its effects. After discussing the correlation of geology with indoor radon concentration It appears they are created by the same geologic features influencing the mean and median values, and can't be eliminated via a map-based approach. To tackle these problems, in this work we deal with multiple definitions of RPA, but only in quaternary areas of FVG, using extensive simulation techniques.

Radon in indoor air of primary schools: a systematic survey to evaluate factors affecting radon concentration levels and their variability

In order to optimize the design of a national survey aimed to evaluate radon exposure of children in schools in Serbia, a pilot study was carried out in all the 334 primary schools of 13 municipalities of Southern Serbia. Based on data from passive measurements, rooms with annual radon concentration >300 Bq/m(3) were found in 5% of schools. The mean annual radon concentration weighted with the number of pupils is 73 Bq/m(3), 39% lower than the unweighted 119 Bq/m(3) average concentration. The actual average concentration when children are in classrooms could be substantially lower. Variability between schools (CV = 65%), between floors (CV = 24%) and between rooms at the same floor (CV = 21%) was analyzed. The impact of school location, floor, and room usage on radon concentration was also assessed (with similar results) by univariate and multivariate analyses. On average, radon concentration in schools within towns is a factor of 0.60 lower than in villages and at higher floors is a factor of 0.68 lower than ground floor. Results can be useful for other countries with similar soil and building characteristics.

PRACTICAL IMPLICATIONS

On average, radon concentrations are substantially higher in schools in villages than in schools located in towns (double,on average). Annual radon concentrations exceeding 300 Bq/m3 were found in 5% of primary schools (generally on ground floors of schools in villages). The considerable variability of radon concentration observed between and within floors indicates a need to monitor concentrations in several rooms for each floor. A single radon detector for each room can be used provided that the measurement error is considerable lower than variability of radon concentration between rooms.