Dept. of Geoinformatic Engineering, Inha University, Incheon, 22212, South Korea.
Dept. of Natural Radiation Safety, Korea Institute of Nuclear Safety, Daejeon, 34142, South Korea.
J Environ Radioact. 2019 Nov;208-209:106044. doi: 10.1016/j.jenvrad.2019.106044. Epub 2019 Sep 12.
This paper presents a geostatistical simulation approach to not only map the county-level indoor radon concentration (IRC) distributions in South Korea, but also quantify the uncertainty that can be used as decision-supporting information. For county-level IRC mapping in South Korea, environmental factors including geology, radium concentration in surface soil, gravel content in subsoil, and fault line density, which are known to be associated with the source and migration of radon gas, were incorporated into IRC measurements using multi-Gaussian kriging with local means. These four environmental factors could account for about 36% of the variability of noise-filtered IRCs, implying that regional variations of IRCs were affected by these factors. Sequential Gaussian simulation was then applied to generate alternative realizations of county-level IRC distributions. By summarizing the multiple simulation results, we identified some counties that lay on the great limestone series showed elevated IRCs. In addition, there were some counties in which the proportion of grids exceeding the recommended level was high but the uncertainty was also large according to the analysis of several uncertainty measures, which indicates that additional sampling is required for these counties. From the local cluster analysis in conjunction with simulation results, we found that the counties with higher levels of IRC belonged to the statistically significant clusters of high values, and these counties should be the prime targets for radon management and in-depth survey. The geographical distributions of IRC and uncertainty measures presented in this study provide guidance for effective radon management if they are consistently combined with both future IRC measurements and a geogenic radon potential map.
本文提出了一种地质统计学模拟方法,不仅可以绘制韩国县级室内氡浓度(IRC)分布,还可以量化不确定性,作为决策支持信息。对于韩国县级 IRC 制图,纳入了环境因素,包括地质、表土镭浓度、底土砾石含量和断层线密度,这些因素与氡气的来源和迁移有关,使用局部均值的多高斯克里金法将这些因素纳入 IRC 测量中。这四个环境因素可以解释约 36%的噪声滤波 IRC 变化,这意味着 IRC 的区域变化受这些因素影响。然后应用序贯高斯模拟来生成县级 IRC 分布的替代实现。通过总结多个模拟结果,我们确定了一些位于大石灰岩系列上的县 IRC 较高。此外,根据多个不确定性度量的分析,还有一些县的网格比例超过推荐水平较高,但不确定性也较大,这表明这些县需要进行额外的采样。从局部聚类分析和模拟结果来看,我们发现 IRC 水平较高的县属于高值的统计学显著聚类,这些县应该是氡管理和深入调查的主要目标。本研究中提出的 IRC 和不确定性度量的地理分布,如果与未来的 IRC 测量和地球成因氡潜力图一致,将为有效的氡管理提供指导。