Objective 1. The coefficient K(t) determines by the innovative algorithm (Fig.3) using the results of annual continuous monitoring of radon in buildings with elevated radon. To search for such buildings, the “RadonTest” on-line system (www.radontest.online) was developed, and equipment based on the method of radon adsorption on activated charcoal was improved (Fig.4). This helped attract Israeli schoolchildren to conduct short-term (screening) tests in their homes (
https://nbri.net.technion.ac.il/en/radon-project(s’ouvre dans une nouvelle fenêtre)) with the support of TCSS (www.tcss.center). Thus, more than 14 schools located in different regions of Israel were covered, and more than 400 measurements (Fig.5) were carried out. These results are shown on the public radon map (
https://radonmap.online/indoorradon(s’ouvre dans une nouvelle fenêtre)) while ensuring confidentiality. The results of the mass survey made it possible to identify the required number of buildings with elevated radon. Then, after additional tests, the 12 most suitable buildings were selected for carrying out synchronous continuous monitoring of radon for one year. As a result, in 12 rooms (Fig.6) located in 9 different buildings, full annual monitoring was carried out, the results of which are shown in Fig.1,2. The values of the coefficient K(t) depending on the mode and duration of measurements in the experimental rooms (ER) are shown in Fig.7-9.
Objective 2. To assess the influence of various factors on the behavior of indoor radon, data of synchronous annual monitoring of the following environmental factors were also collected (see Fig.10): (a) air temperature and (b) humidity, (c) atmospheric pressure, (d) wind speed, (e) precipitation, (f) insolation (connection with cloudiness), (g) tidal forces (Earth's rotation speed or length of day), (h) seismic activity, (i) concentration of soil radon (under building), and (j) flux of soil radon inside the building. The study of the influence of the parameters (i) and (j) on the behavior of indoor radon was carried out in ER1 (Fig.6) in accordance with the measurement scheme shown in Fig.11. The results of annual continuous monitoring of soil and indoor radon in ER 1 with influencing factors are shown in Fig.12. The correlations between radon concentration in the ERs and influencing factors are shown in Fig.13. The correlations between indoor (ER1) / soil radon and influencing factors are shown in Fig.14.
It has been established that influence of (a)-(h) factors on the behavior of indoor radon is weak and irregular (Fig.13) in contrast to factors (i) and (j). However, both of last factors are not used in mass radon surveys due to the complexity, so the correction factor k=1. Thus, only way to assess the accuracy of AAIR is the algorithm presented in the Fig.3. In addition, the obtained values of K(t) in Israeli buildings are on average higher than for the Moscow region (Fig.9) which leads to the need to verify and clarify data by the accumulation of statistically representative of the array of calculated values of K(t). The actual action on this challenge is to conduct a large number (200-300) of annual continuous indoor radon monitoring in different countries, for example, Europe and America that will allow for the first time to create a basis for the rational regulation of indoor radon.
The obtained results can be exploited to improve the measurement protocol in order to more efficiently organize radon surveys and identify hazardous buildings. The project results are disseminated mainly through the created web-sites and web-pages (see links above), publications, presentations and reports at meetings with European and American experts, including grants and the organization of joint researches which develops and scales RadonACCURACY innovations.
