Two error components model for measurement error: application to radon in homes

In this paper, a simple model for analysing variability in radon concentrations in homes is tested. The approach used here involves two error components, representing additive and multiplicative errors, together with variation between-houses. We use a Bayesian approach for our analysis and apply this model to two datasets of repeat radon measurements in homes; one based on 3-month long measurements for which the original measurements were close to the current UK Radon Action Level (200 Bq m⁻³), and the other based on 6-month measurement data (from regional and national surveys), for which the original measurements cover a wide range of radon concentrations, down to very low levels. The model with two error components provides a better fit to these datasets than does a model based on solely multiplicative errors.     

Uncertainty of block estimates introduced by mis-allocation of point samples: on the example of spatial indoor Radon data

The European indoor Radon map which is currently under production is based on gridded data supplied by the contributing countries. Each grid node represents the arithmetic mean (among other statistics) of the individual measurements within 10 × 10 km², called cells, pixels or blocks, which are aligned to a common metric coordinate system. During work the question emerged, if uncertainty in the geo-referencing of individual data might affect the aggregated “block” statistics to an extent that the statistics have an unpredictably high additional uncertainty, which makes them unusable.     

Radon-222 exhalation from open ground on and around a uranium mine in the wet-dry tropics

Radon-222 exhalation from the ground surface depends upon a number of variables such as the 226Ra activity concentration and its distribution in soil grains; soil grain size; soil porosity, temperature and moisture; atmospheric pressure, rainfall and temperature. In this study, 222Rn exhalation flux density measurements within and around the Ranger uranium mine in northern Australia were performed to investigate the effect of these variables within a tropical region. Measurements were taken at the waste rock dumps, ore stockpiles, mine pits, and at sites where effluent water with elevated 226Ra concentration has been spray irrigated over land, as well as at sites outside the mine. The sites selected represented a variety of geomorphic regions ranging from uranium-bearing rocks to ambient soils. Generally, wet season rains reduced 222Rn exhalation but at a few sites the onset of rains caused a step rise in exhalation flux densities. The results show that parameters such as 226Ra activity concentration, soil grain size and soil porosity have a marked effect on 222Rn flux densities. For similar geomorphic sites, 226Ra activity concentration is a dominant factor, but soil grain size and porosity also influence 222Rn exhalation. Surfaces with vegetation showed higher exhalation flux densities than their barren counterparts, perhaps because the associated root structure increases soil porosity and moisture retention. Repeated measurements over one year at eight sites enabled an analysis of precipitation and soil moisture effects on 222Rn exhalation. Soil moisture depth profiles varied both between seasons and at different times during the wet season, indicating that factors such as duration, intensity and time between precipitation events can influence 222Rn flux densities considerably.     

Increased environmental gamma-ray dose rate during precipitation: a strong correlation with contributing air mass

It has long been observed that the environmental gamma-ray dose rate increases noticeably during precipitation intervals. This increase, due to the presence of radon progeny in the rain droplets (or snow flakes), can affect the reliability of the monitoring of artificial radioactivity and long term estimates of exposure to ambient natural radionuclides in surveillance network. Predicting the amplitude of the dose increase has been shown to be surprisingly challenging. In this work, standard air mass back trajectory analysis is used to show that the amplitude of the increase can be quantitatively linked to the history of the air mass where the precipitation is occurring. Furthermore, we show how back trajectory analysis, environmental gamma and rain data can be used to obtain estimations of relative radon emanation rates for locations far from the actual point of detection.     

Mapping Soil Gas Radon Concentration: A Comparative Study of Geostatistical Methods

Understanding soil gas radon spatial variations can allow the constructor of a new house to prevent radon gas flowing from the ground. Indoor radon concentration distribution depends on many parameters and it is difficult to use its spatial variation to assess radon potential. Many scientists use to measure outdoor soil gas radon concentrations to assess the radon potential. Geostatistical methods provide us a valuable tool to study spatial structure of radon concentration and mapping. To explore the structure of soil gas radon concentration within an area in south Italy and choice a kriging algorithm, we compared the prediction performances of four different kriging algorithms: ordinary kriging, lognormal kriging, ordinary multi-Gaussian kriging, and ordinary indicator cokriging. Their results were compared using an independent validation data set. The comparison of predictions was based on three measures of accuracy: (1) the mean absolute error, (2) the mean-squared error of prediction; (3) the mean relative error, and a measure of effectiveness: the goodness-of-prediction estimate. The results obtained in this case study showed that the multi-Gaussian kriging was the most accurate approach among those considered. Comparing radon anomalies with lithology and fault locations, no evidence of a strict correlation between type of outcropping terrain and radon anomalies was found, except in the western sector where there were granitic and gneissic terrain. Moreover, there was a clear correlation between radon anomalies and fault systems.     

高层建筑、建筑材料与室内氡污染

对高层建筑连续一年的室内氡浓度监测分析，发现室内氡浓度与建筑材料，建筑结构以及人们的生活习惯密切相关。     

辽宁省部分城市室内氡浓度水平

对辽宁省 7个市区的办公室和居室内空气氡浓度水平进行了调查研究 ,结果表明 ,办公室室内空气中氡的平衡当量浓度为 3 9.3 / Bq· m- 3。居室空气中氡的平衡当量浓度为 43 .2 / Bq·m- 3,居民由室内氡及其子体所致年有效剂量为2 .6m Sv     

哈密地区建筑材料氡发射系数测定

本文用FD-125型氡钍分析仪以α-射气闪烁法测定了哈密地区建材氡发射系数,其范围值为0～18.7％.氡发射平均系数的高低顺序是土块>普通水泥>花岗石材>红砖>预制构件>沙>石灰.结果表明,建材氡发射系数的高低不仅取决于建材~(226)Ra含量,很大程度上也取决于建材氡发射系数.测定该系数对评价建材所致居民室内氡浓度有一定意义.     

Radon mapping by retrospective measurements - an approach based on CDs/DVDs

This article points out the ability to map retrospective ²²²Rn concentrations by home stored CDs/DVDs. The method employs the high radon absorption ability of the polycarbonate material of CDs and DVDs and their track-etch properties. The principle steps for the application of the method are addressed. The possibility for individual a posteriori calibration is studied, demonstrating that better than 10% accuracy in retrospective measurements is potentially achievable. Results from retrospective measurements in three different regions are shown, demonstrating the potential of the method for large-scale radon mapping. Comparison with independently evaluated retrospective ²²²Rn concentrations in places with known radon history was made and very good correspondence was observed. The experience indicates that the method can be used for large scale retrospective radon mapping and its applications can be expanded towards mapping of radon concentrations in water and soil gas.     

Modeling the Pb activity concentration in the lower atmosphere

A worldwide radionuclide network of 80 stations, part of the International Monitoring System, is being setup to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The radioactivity sampled at these stations is primarily ²²⁰Rn progenies affecting the detection capability. A model linking the ²²⁰Rn emanation with the sampled ²¹²Pb activity was developed and is presented here. The model and the performed measurements show that the variation of the sampled ²¹²Pb activity can be fully explained by the variation of the local ²²⁰Rn activity concentration.