A case study of radon-222 transport from continental North-East Asia to the Japanese islands in winter by numerical analysis

Design and Development of a New Methodology Based on Expert Systems Applied to the Prevention of Indoor Radon Gas Exposition Risks

Exposure to high concentration levels of radon gas constitutes a major health hazard, being nowadays the second-leading cause of lung cancer after smoking. Facing this situation, the last years have seen a clear trend towards the search for methodologies that allow an efficient prevention of the potential risks derived from the presence of harmful radon gas concentration levels in buildings. With that, it is intended to establish preventive and corrective actions that might help to reduce the impact of radon exposure on people, especially in places where workers and external users must stay for long periods of time, as it may be the case of healthcare buildings. In this paper, a new methodology is developed and applied to the prevention of the risks derived from the exposure to radon gas in indoor spaces. Such methodology is grounded in the concurrent use of expert systems and regression trees that allows producing a diagram with recommendations associated to the exposure risk. The presented methodology has been implemented by means of a software application that supports the definition of the expert systems and the regression algorithm. Finally, after proving its applicability with a case study and discussing its contributions, it may be claimed that the benefits of the new methodology might lead on to an innovation in this field of study.

Testing of 222Rn application for recognizing tectonic events observed on water-tube tiltmeters in underground Geodynamic Laboratory of Space Research Centre at Książ (the Sudetes, SW Poland)

Research on relationships between variation in ²²²Rn activity concentration and tectonic events recorded using the instruments of the Geodynamic Laboratory of SRC PAS at Książ (the Sudetes, SW Poland) had been conducted since 2014. The performed analyses of variation have demonstrated the spatial character of changes in ²²²Rn activity concentration. Their time-course is comparable in all parts of the underground laboratory. This means that gas exchange between the lithosphere and the atmosphere occurs not only through fault zones but also through all surfaces of the underground workings: the floors, the sidewalls and the roofs. Further, some relationships between ²²²Rn activity concentration and tectonic activity of the orogen have been demonstrated with the use of Pearson's linear correlation coefficient. The comparison between temporal distribution (times series) of radon activity concentration and water-tube tiltmeters (WTs) demonstrated that radon data have regular oscillations which can be approximated using the sine function with a 12 month cycle (seasonal changes) and amplitude in the range of 1000-1500 Bq/m³. To compare the collected radon signal data and tectonic activity, we used linear function as the simplest method of trend assessment. Pearson's correlation coefficient r cannot be accepted as appropriate for assessing the interdependencies between variables because they do not have a normal distribution, and the relationship between them is not linear. It was noted that each series of data, namely radon activity concentration and tectonic activity determine the series of deviations above and below the trend function. Because of the non-fulfillment of the above assumptions, we used nonparametric equivalents such as Spearman's rank correlation coefficient r_s and Kendall's tau. The obtained results showed that the value of the r_s coefficient ranges from 0.38 to even 0.43. The best relationship at the level of r_s = 0.43 was determined between the radon activity concentration recorded by detector no. 3 and the tectonic activity of the rock mass registered on the WT-2 channel. Similar at the r_s level of 0.37-0.38 between detector no. 5 and 4 and the WT-2 channel. A bit higher than r_s = 0.39 between detector no. 3 and the WT-2 channel. In each case, these were positive correlations. The obtained Spearman's r_s coefficients indicate the correlation between ²²²Rn activity concentration and tectonic activity of the rock mass. The t-statistic, which analyzes the significance of Spearman's coefficient r_s is a descriptive measure of the accuracy of regression matching to empirical data. It takes values in the range of percentage and provides informations about which part of the total variability of the radon activity concentration (Y) observed in the sample has been explained (determined) by regression in relation to tectonic activity of the rock mass (X). In our case, approximately f 40% to more than 50% of the radon activity concentration (Y) was explained by regression in relation to the tectonic activity of the rock mass. We obtained similar results with the use of Kendall's tau coefficient. Precise description of the character of this relationship requires further, more detailed analyses, such as comparing characteristics of the distributions based on trend variation like Monte Carlo simulation, Multivariate Adaptive Regression Splines or neural networks.

Development and application of a continuous measurement system for radon exhalation rate

A continuous measurement system, with a ventilation-type accumulation chamber, was developed for radon exhalation rate determination. A reasonable sampling flow rate for the measurement system was determined by comparing the values obtained by the system with those obtained by a grab sampling method. The sampling flow rate of passage through the scintillation cell from the accumulation chamber was varied from 0.05 to 2.0 l min(-1). The difference in pressure between the inside and outside of the accumulation chamber increased as the sampling flow rate became large, and the estimated radon exhalation rate also increased with the sampling flow rate. From these results, a reasonable sampling flow rate was estimated to be less than 0.2 l min(-1).

Inverse modeling of Asian (222)Rn flux using surface air (222)Rn concentration

When used with an atmospheric transport model, the (222)Rn flux distribution estimated in our previous study using soil transport theory caused underestimation of atmospheric (222)Rn concentrations as compared with measurements in East Asia. In this study, we applied a Bayesian synthesis inverse method to produce revised estimates of the annual (222)Rn flux density in Asia by using atmospheric (222)Rn concentrations measured at seven sites in East Asia. The Bayesian synthesis inverse method requires a prior estimate of the flux distribution and its uncertainties. The atmospheric transport model MM5/HIRAT and our previous estimate of the (222)Rn flux distribution as the prior value were used to generate new flux estimates for the eastern half of the Eurasian continent dividing into 10 regions. The (222)Rn flux densities estimated using the Bayesian inversion technique were generally higher than the prior flux densities. The area-weighted average (222)Rn flux density for Asia was estimated to be 33.0 mBq m(-2) s(-1), which is substantially higher than the prior value (16.7 mBq m(-2) s(-1)). The estimated (222)Rn flux densities decrease with increasing latitude as follows: Southeast Asia (36.7 mBq m(-2) s(-1)); East Asia (28.6 mBq m(-2) s(-1)) including China, Korean Peninsula and Japan; and Siberia (14.1 mBq m(-2) s(-1)). Increase of the newly estimated fluxes in Southeast Asia, China, Japan, and the southern part of Eastern Siberia from the prior ones contributed most significantly to improved agreement of the model-calculated concentrations with the atmospheric measurements. The sensitivity analysis of prior flux errors and effects of locally exhaled (222)Rn showed that the estimated fluxes in Northern and Central China, Korea, Japan, and the southern part of Eastern Siberia were robust, but that in Central Asia had a large uncertainty.

Atmospheric radon in Hong Kong

For the first time in Hong Kong, atmospheric radon concentration was continuously monitored between November 2007 and October 2008. This paper presents the results obtained during the 12-month period. The annual mean atmospheric radon concentration in Hong Kong was found to be 9.3 Bqm(-3) which was close to the level at neighbouring places like Guangdong and Taiwan. An estimation of the dose arising from atmospheric radon to the Hong Kong population was made. The meteorological effects on the variation of atmospheric radon concentration were discussed. It was found that the origin of the airmass and stability of the local atmosphere played vital roles in the seasonal and diurnal variations respectively, whereas precipitation caused abrupt changes in rainy days. An attempt was also made to find out the contribution of atmospheric radon to the ambient gamma dose rate.

Estimating the amount and distribution of radon flux density from the soil surface in China

Based on an idealized model, both the annual and the seasonal radon ((222)Rn) flux densities from the soil surface at 1099 sites in China were estimated by linking a database of soil (226)Ra content and a global ecosystems database. Digital maps of the (222)Rn flux density in China were constructed in a spatial resolution of 25 km x 25 km by interpolation among the estimated data. An area-weighted annual average (222)Rn flux density from the soil surface across China was estimated to be 29.7+/-9.4 mBq m(-2)s(-1). Both regional and seasonal variations in the (222)Rn flux densities are significant in China. Annual average flux densities in the southeastern and northwestern China are generally higher than those in other regions of China, because of high soil (226)Ra content in the southeastern area and high soil aridity in the northwestern one. The seasonal average flux density is generally higher in summer/spring than winter, since relatively higher soil temperature and lower soil water saturation in summer/spring than other seasons are common in China.