Khomutinin Yu, Fesenko S, Levchuk S, Zhebrovska K, Kashparov V
Institute of Agricultural Radiology, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.
Russian Institute of Radiology and Agroecology, Obninsk, Russian Federation.
J Environ Radioact. 2020 Oct;222:106344. doi: 10.1016/j.jenvrad.2020.106344. Epub 2020 Jul 2.
The novel approach for optimising soil sampling strategies in areas affected by radionuclides is suggested. Major factors influencing the efficiency of soil sampling strategies, including (number of samples, sampling area size, sampling depth and spatial resolution of the sample sites are examined to provide optimisation of the soil sampling plan. The experimental field studies to validate the suggested approach were performed in 25 sampling units ranging from 1.2 × 1.2 m to 60 × 60 m size. The sampling units were selected on arable farmlands, natural meadow and former agricultural land), as well as coniferous and deciduous forests with contamination density of Cs ranging from 2.8 kBq·m to 24.5 MBq·m. The studied areas were contaminated by both the global fallout and the Chernobyl radioactive particles of different types. To determine the values of standard deviation of the log of the soil contamination density of Cs, 25 to 256 soil samples were collected with an increment of 0.07-10 m within each sampling unit. It was found that the values of standard deviation of the log of the soil contamination density of Cs were not dependent on the mean contamination density, the type of radioactive deposition and the landscape features. The mean value of standard deviation calculated for all sites studied was estimated as 0.44 ± 0.15 and 0.30 ± 0.10 for the sampling area 0.001 m (∅37 mm) and 0.005 m (∅80 mm) at the relative measurement uncertainties lower than 10% (CI = 95%). Concentrations of Cs in the soil samples were statistically independent when sampling points were situated at a distance larger than 1 m one from each other. A simple method was developed for assessing minimum sample sizes required for estimation of the median or the geometric mean of radionuclide soil contamination with a relative uncertainty set by the user. The approach was also suggested for estimation of the uncertainty of soil contamination for the case of composite samples. The approach was implemented in the Ukrainian national requirements for assessment of quality of the soil.
提出了一种优化受放射性核素影响地区土壤采样策略的新方法。研究了影响土壤采样策略效率的主要因素,包括(样本数量、采样区域大小、采样深度和采样点的空间分辨率),以优化土壤采样计划。在25个面积从1.2×1.2米到60×60米不等的采样单元中进行了验证该方法的实地试验研究。采样单元选在耕地、天然草地和以前的农田),以及铯污染密度从2.8 kBq·m到24.5 MBq·m的针叶林和阔叶林。研究区域受到全球沉降物和不同类型的切尔诺贝利放射性粒子的污染。为了确定铯土壤污染密度对数的标准偏差值,在每个采样单元内以0.07 - 10米的增量采集了25至256个土壤样本。发现铯土壤污染密度对数的标准偏差值不依赖于平均污染密度、放射性沉积类型和景观特征。在所研究的所有地点计算出的标准偏差平均值,对于采样面积为0.001米(∅37毫米)和0.005米(∅80毫米)的情况,在相对测量不确定度低于10%(置信区间 = 95%)时分别估计为0.44±0.15和0.30±0.10。当采样点彼此距离大于1米时,土壤样本中铯的浓度在统计上是独立的。开发了一种简单方法,用于评估在用户设定的相对不确定度下估计放射性核素土壤污染中位数或几何平均值所需的最小样本量。该方法还被建议用于估计复合样本情况下土壤污染的不确定度。该方法已纳入乌克兰土壤质量评估的国家要求中。