Institute of Radiochemistry and Radioecology, University of Pannonia, 8200 Veszprém, Hungary.
Materials and Nuclear Fuel Research School, Nuclear Science and Technology Research Institute, Tehran 11365-8486, Iran.
Int J Environ Res Public Health. 2020 Dec 28;18(1):141. doi: 10.3390/ijerph18010141.
A comprehensive study was carried out to measure indoor radon/thoron concentrations in 78 dwellings and soil-gas radon in the city of Mashhad, Iran during two seasons, using two common radon monitoring devices (NRPB and RADUET). In the winter, indoor radon concentrations measured between 75 ± 11 to 376 ± 24 Bq·m (mean: 150 ± 19 Bq m), whereas indoor thoron concentrations ranged from below the Lower Limit of Detection (LLD) to 166 ± 10 Bq·m (mean: 66 ± 8 Bq m), while radon and thoron concentrations in summer fell between 50 ± 11 and 305 ± 24 Bq·m (mean 115 ± 18 Bq m) and from below the LLD to 122 ± 10 Bq m (mean 48 ± 6 Bq·m), respectively. The annual average effective dose was estimated to be 3.7 ± 0.5 mSv yr. The soil-gas radon concentrations fell within the range from 1.07 ± 0.28 to 8.02 ± 0.65 kBq·m (mean 3.07 ± 1.09 kBq·m). Finally, indoor radon maps were generated by ArcGIS software over a grid of 1 × 1 km using three different interpolation techniques. In grid cells where no data was observed, the arithmetic mean was used to predict a mean indoor radon concentration. Accordingly, inverse distance weighting (IDW) was proven to be more suitable for predicting mean indoor radon concentrations due to the lower mean absolute error (MAE) and root mean square error (RMSE). Meanwhile, the radiation health risk due to the residential exposure to radon and indoor gamma radiation exposure was also assessed.
对伊朗马什哈德市 78 处住宅和土壤气体中的氡/钍浓度进行了全面研究,使用了两种常见的氡监测设备(NRPB 和 RADUET)。在冬季,室内氡浓度测量值在 75±11 至 376±24 Bq·m(平均值:150±19 Bq·m)之间,而室内钍浓度范围从低于下限检测值(LLD)至 166±10 Bq·m(平均值:66±8 Bq·m),而夏季的氡和钍浓度则在 50±11 至 305±24 Bq·m(平均值:115±18 Bq·m)和低于下限检测值至 122±10 Bq·m(平均值:48±6 Bq·m)之间。估计每年的有效剂量为 3.7±0.5 mSv·yr。土壤气体中的氡浓度在 1.07±0.28 至 8.02±0.65 kBq·m(平均值:3.07±1.09 kBq·m)的范围内。最后,使用三种不同的插值技术,通过 ArcGIS 软件生成了 1×1 km 的网格的室内氡地图。在没有观测到数据的网格单元中,使用算术平均值来预测平均室内氡浓度。因此,由于平均绝对误差(MAE)和均方根误差(RMSE)较低,证明距离反比加权(IDW)更适合预测平均室内氡浓度。同时,还评估了居民接触氡和室内伽马辐射的辐射健康风险。