A general approach is presented to derive probabilistic radionuclide distribution coefficients (Kd) in soils from a Kd dataset. The main aim was to derive informed estimates with a low inherent uncertainty by restricting the Kd value data to subsets based on key soil factors and the experimental approach used to calculate the Kd value (e.g., sorption and desorption tests). As an example, the general approach was applied to uranium (U) Kd values that are part of a critically reviewed dataset containing more than 5000 soil Kd entries for 83 elements and an additional 2000 entries of Kd data for 75 elements gathered from a selection of other, non-soil, geological materials. The overall soil U Kd dataset included 196 values spanning a range of four orders of magnitude (1-67,000 L kg-1), with additional 50 entries for other geological materials. Whereas the effect of the experimental approach could be disregarded, major factors in decreasing U Kd variability were pH and organic matter content (OM). Limitation in the number of entries made it difficult to use texture information (sand, silt, clay) to further decrease U Kd variability. The integrated combination of pH + OM permitted some soil groups to have U Kd confidence intervals as narrow as two orders of magnitude. Specifically for U Kd, data in the Mineral (< 20% OM) and Organic (≥ 20% OM) partial datasets were significantly different. Analogue data from geological materials other than soils, such as subsoil, till and gyttja (a lacustrine mud having elevated organic matter (OM) contents), were also statistically evaluated to determine whether they could be used to fill U Kd data gaps. It was shown that U Kd from subsoils and tills, but not gyttjas, could be used to enhance soil U Kd datasets. Selection of probabilistic Kd values for risk modelling can be made more reliably and with less uncertainty by using appropriate geochemical data representative of the study site to narrow the wide range of potential Kd values.

中文翻译：

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推导概率土壤分布系数（Kd）。第1部分：使用铀Kd值降低和描述变异性的通用方法和示例。

提出了一种从Kd数据集推导土壤中概率放射性核素分布系数（Kd）的通用方法。主要目的是通过基于关键土壤因素和用于计算Kd值的实验方法（例如，吸附和解吸试验）将Kd值数据限制在子集中，从而得出具有较低固有不确定性的明智估计。例如，将通用方法应用于铀（U）Kd值，该值是经过严格审查的数据集的一部分，该数据集包含从83个元素中收集的5000多个土壤Kd条目和从75个元素中选择的75个元素的另外2000个Kd数据条目。其他非土壤地质材料。整个土壤U Kd数据集包括196个值，范围涵盖四个数量级（1-67,000 L kg-1），另外还有50个用于其他地质材料的条目。尽管可以忽略实验方法的影响，但降低U Kd变异性的主要因素是pH和有机物含量（OM）。条目数量的限制使得难以使用纹理信息（沙，粉砂，粘土）来进一步降低U Kd的可变性。pH + OM的综合组合使某些土壤群体的U Kd置信区间窄至两个数量级。特别是对于U Kd，矿物（<20％OM）和有机（≥20％OM）部分数据集中的数据显着不同。还对来自土壤以外的地质材料的模拟数据进行了统计评估，以确定是否可将其用于填补U Kd数据空白，这些模拟数据来自地下土壤，土壤和土壤（gytja）（湖泥中有机物含量较高）。结果表明，来自地下和耕作的U Kd 但不是gyttjas，可用于增强土壤U Kd数据集。通过使用代表研究地点的适当地球化学数据来缩小潜在Kd值的范围，可以更可靠地选择风险Kd值，并进行较小的不确定性。