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[en] Highlights: • Indoor radon was measured in randomly selected newly built houses in 2008 and 2016. • New building regulations with preventive measures on radon was introduced in 2010. • A significant reduction of radon concentrations was found in detached houses. - Abstract: Results from two national surveys of radon in newly built homes in Norway, performed in 2008 and 2016, were used in this study to investigate the effect of the 2010 building regulations introducing limit values on radon and requirements for radon prevention measures upon construction of new buildings. In both surveys, homes were randomly selected from the National Building Registry. The overall result was a considerable reduction of radon concentrations after the implementation of new regulations, but the results varied between the different dwelling categories. A statistically significant reduction was found for detached houses where the average radon concentration was almost halved from 76 to 40 Bq/m3. The fraction of detached houses which had at least one frequently occupied room with a radon concentration above the Action Level (100 Bq/m3) fell from 23.9% to 6.4%, while the fraction above the Upper Limit Value (200 Bq/m3) was reduced from 7.6% to 2.5%. In 2008 the average radon concentration measured in terraced and semi-detached houses was 44 and in 2016 it was 29 Bq/m3, but the reduction was not statistically significant. For multifamily houses, it was not possible to draw a conclusion due to insufficient number of measurements.
[en] Highlights: • Outdoor radon levels can cause departure from lognormal indoor radon distribution. • An analytical method is proposed to evaluate and correct outdoor impact for every radon distribution. • Results of this study can be useful for a correct classification of radon areas. - Abstract: Outdoor radon concentration contributes to indoor radon levels, generally causing a shift from lognormal distribution of measured radon concentration data distribution, and it makes more challenging the estimation of radon distribution parameters on the basis of the lognormal assumption. In particular, lognormal assumption with no correction could lead to a significantly biased estimate of the percentage of dwellings exceeding a certain level, e.g. a reference level (RL), since this is based on biased estimates of geometric mean (GM) and geometric standard deviation (GSD) of radon concentration distribution. Subtracting to each measured data a constant outdoor radon level can usually compensate data distribution departure from log-normality (except for low radon levels), if the appropriate outdoor level value is chosen by means of a lognormal fit of the data. This approach – already (but not always) used in literature – cannot be applied in cases where all the data of radon concentrations are not available (e.g., for a review study). For these cases, this work presents an analytical method to quantitatively evaluate and correct the impact of outdoor on the lognormal distribution parameter estimates and, in particular, on the percentages of dwellings exceeding radon reference levels. The proposed method is applied to a number of possible situations, with different values of outdoor radon level, GM and GSD. The results show that outdoor radon levels generally produce an underestimation of the actual GSD parameter, which increases as the outdoor level increases, and in the worse cases, could lead to an underestimation higher than 50%. Consequently, if the outdoor contribution is not properly taken into account, the percentage of dwellings exceeding a certain RL is almost always underestimated, even by 80%–90% for RL equal to 300 Bq/m3. This could have implications for the classification of areas as regards radon concentration and for the estimation of avertable lung cancers attributable to radon levels higher than some possible RLs.
[en] Concentration ratios (CRs) are used to derive activity concentrations in wild plants and animals. Usually, compilations of CR values encompass a wide range of element–organism combinations, extracted from different studies with statistical information reported at varying degrees of detail. To produce a more robust estimation of distribution parameters, data from different studies are normally pooled using classical statistical methods. However, there is inherent subjectivity involved in pooling CR data in the sense that there is a tacit assumption that the CRs under any arbitrarily defined biota category belong to the same population. Here, Bayesian inference has been introduced as an alternative way of making estimates of distribution parameters of CRs. This approach, in contrast to classical methods, is more flexible and also allows us to define the various assumptions required, when combining data, in a more explicit manner. Taking selected data from the recently compiled wildlife transfer database ( (http://www.wildlifetransferdatabase.org/)) as a working example, attempts are made to refine the pooling approaches previously used and to consider situations when empirical data are limited
[en] There are practically no direct techniques for measuring radon entry rate in the rooms. The suggested technique allows estimating such parameter under real conditions. The technique for radon diagnostic procedures including radon entry rate and air change rate assessment was proposed and tested in the field under various experimental conditions. The method consists of the continuous measurement of radon concentration, temperature and pressure difference between indoor and outdoor atmosphere. It was demonstrated that the study of dependence of radon entry rate on temperature difference ΔT between indoor and outdoor atmosphere allows to estimate the dominant radon entry mechanism – diffusion mechanism (absence of the dependence on ΔT) or convective (radon entry rate increase at ΔT increase). It was shown that simultaneous measurements of time series of radon concentration and pressure difference between building envelope and outdoor atmosphere allow assessing such room parameter as Effective Leakage Area. The approach applied in this paper to estimate the air change rate practically is not differing from tracer gas techniques when the constant gas entry rate is used. It was shown that radon could be used as kind of tracer gas to estimate the air change rate. Obtained measurement results for all buildings confirmed the seasonal variations of radon concentrations. A correlation of radon concentration and air change rate with outside temperature occurred in general. -- Highlights: • Technique of the assessment of radon entry rate in the room is developed. • Continuous measurements of radon concentration and temperature difference are used. • Technique allows estimating the dominant radon entry mechanism: diffusion/advective. • The dominance of diffusion radon entry is demonstrated for some of the rooms. • Dependence of the effective leakage area on temperature difference are demonstrated
[en] Highlights: • Nationwide indoor radon survey in Montenegro. • Distribution of radon concentrations deviates from log-normality. • Log-normality obtained by subtracting contribution from radon in outdoor air. • Fraction of homes with high radon levels estimated using transformed data set. • National reference level, “urgent action level” and radon priority areas proposed. - Abstract: The first nationwide indoor radon survey in Montenegro started in 2002 and year-long radon measurements with CR-39 track-etch detectors, within the national grid of 5 km × 5 km and local grids in urban areas of 0.5 km × 0.5 km, were performed in homes in half of the country's territory. The survey continued in 2014 and measurements in the rest of the country were completed at the end of 2015. The 953 valid results, obtained in the national radon survey, give an average radon activity concentration in Montenegrin homes of 110 Bq/m3. Assuming a log-normal distribution of the experimental results, geometric mean GM = 58.3 Bq/m3 and geometric standard deviation GSD = 2.91 are calculated. However, normality tests show that the experimental data are not log-normal, and that they become closest to a log-normal distribution after subtracting from them radon concentration in the outdoor air of 7 Bq/m3, which is theoretically calculated. Such a transformed distribution has GMtr = 46.7 Bq/m3 and GSDtr = 3.54. The estimations derived from positing a priory that the experimental results conform to a log-normal distribution underestimate the percentage of homes with radon concentrations at the thresholds of 300 Bq/m3 and above, which is better estimated by using GMtr and GSDtr. Based on the results of radon survey, a new national radon reference level of 300 Bq/m3 and an “urgent action level” of 1000 Bq/m3 are suggested, with estimated fractions of the national dwelling stock above these levels of 7.4% and 0.8% respectively. Fractions of homes with radon concentrations above the suggested levels are also estimated for each of the 23 municipalities in Montenegro, using appropriate GMtr and GSDtr. The six municipalities which have more than 10% of homes with radon concentration above 300 Bq/m3 are recommended as radon priority areas.
[en] The predictions of three models of 137Cs transfer in forest ecosystems (FOA, LOGNAT and FORESTLAND) were compared. The scenario for the model-model comparison consisted of an acute dry deposition of 137Cs over a coniferous forest. The model predictions were subsequently compared (model-data comparison) with values derived from experimental data measured in forests of the Bryansk region in Russia that were contaminated by the Chernobyl accident and that have similar characteristics to the forests described in the scenario. The predictions of radiocaesium levels in the litter-soil layer, berries, needles, wood, whole tree and moose made with the models were in relatively good agreement with each other (within a factor of 1.4-2.9). The best agreement was observed for berries and moose and the worst for wood. There was also good agreement between the model predictions for the same variables and the experimental data (within a factor of 1.2-3.2). In this case, the best agreement was observed for the litter-soil layer and the worst for wood and the whole tree. Overall, at least for the studied scenario and for the first 10 years after deposition, any of the models can be used if the final aim is to estimate average concentrations in different forest components. The agreement between the model predictions worsens with time and there were differences in the form of the time dependencies predicted by the models, especially for wood. This may lead to larger differences between the model predictions and the experimental data for times beyond the period for which data were available for comparison (10 years after the deposition)
[en] A review of methods which have been used to describe and predict transfer of radionuclides in biota was undertaken. The intent was to identify approaches that might prove useful in extending predictive estimates to other organisms and environments. Empirical approaches, such as found in the use of transfer factors, were examined. Kinetic methodologies were also presented. Allometric functions, with their ability to make broad generalizations, were also discussed. Data from several earlier radioecological assessments were tested for their potential utility in developing allometric relationships, with the result implying that such an approach might prove useful
[en] The measurement of Kd is difficult for most radionuclides: a different value is expected for every different soil. This study explored a modification of the constituent-Kd approach used to estimate Kd in geological materials. Here we selected five soils of very different compositions, four were field soils and one was an artificial potting soil. The soils were blended together in ratios of 1:1, 1:3 and 1:1:2 for all possible (60) 2- and 3-soil combinations. The Kd was measured for each soil and each of the combined soils using additions of stable iodine. Our hypothesis was that the weighted average of the Kds of the original, unblended soils, weighted by the blending ratios, would be a reasonable estimate of the measured Kds of the blended soils. The ratios of expected/measured Kd values did not deviate significantly from unity (a geometric mean of 0.91) for the four field soils. This result suggests that Kd in the combined field soils could be estimated by the weighted average Kd for the constituent soils. The resulting variation is consistent with other estimation methods. The practical implication of this finding is that, with Kd data for a few benchmark soils in a region, one could estimate Kd for other soils. The potting soil did not conform, and there are several possible explanations for this
[en] During 1996-1998, 16 fruit bodies of different species and 204 soil samples down to 10 cm in the close vicinity of the fruit body sites were collected in a coniferous forest in the Ovruch region of Ukraine. The soil samples were sliced into 1 or 2 cm layers and the fungal mycelium was prepared from each of the layers. The 137Cs activity concentration was determined in both soil and mycelium. The mean weight of fungal mycelium was 13.8 mg g-1 of soil in the upper 4 cm and 7.3 mg g-1 when measured for the upper 10 cm. At the sites of Paxillus involutus and Sarcodon imbricatus, the mycelium was rather homogeneously distributed in the upper 10 cm and at sites of Xerocomus subtomentosus and Cantharellus cibarius, the mycelium was distributed mostly in the upper layers. The highest 137Cs activity concentrations were found in the upper layers of the soil profile. The 137Cs activity concentrations were usually higher in the fruit bodies compared with the mycelium, with ratios ranging from 0.1 to 66 and a mean of 9.9. The percentage of the total inventory of 137Cs in the soil found in the fungal mycelium ranged from 0.1 to 50%, with a mean value of 15%
[en] Highlights: • Computational intelligence (CI) models developed to automatically detect anomalous behaviour in soil radon. • Accuracy of the models is quantified using the mean absolute error, root mean square error and mean square error. • For pre-assumed conditions model accurately predicts radon concentrations and the statistics of their temporal variations. • The FFNN) is the most suitable CI technique to detect anomalies in radon time series triggered by seismic activity. - Abstract: In this article, three computational intelligence (CI) models were developed to automatically detect anomalous behaviour in soil radon gas (222Rn) time series data. Data were obtained at a fault line and analysed using three machine learning techniques with the aim at identifying anomalies in temporal radon data prompted by seismic events. Radon concentrations were modelled with corresponding meteorological and statistical parameters. This leads to the estimation of soil radon gas without and with meteorological parameters. The comparison between computed radon concentration and actual radon concentrations was used in finding radon anomaly based upon automated system. The anomaly in radon time series data could be considered due to noise or seismic activity. Findings of study show that under meticulously characterized environments, on exclusion of noise contribution, seismic activity is responsible for anomalous behaviour seen in radon time series data.