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Title: Deriving probabilistic soil distribution coefficients (Kd). Part 1: General approach to decreasing and describing variability and example using uranium Kd values
Author: Ramirez-Guinart, Oriol
Kaplan, Daniel
Rigol Parera, Anna
Vidal Espinar, Miquel
Keywords: Sòls
Issue Date: 25-Aug-2020
Publisher: Elsevier B.V.
Abstract: 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.
Note: Versió postprint del document publicat a:
It is part of: Journal of Environmental Radioactivity, 2020, vol. 222, p. 106362
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ISSN: 0265-931X
Appears in Collections:Articles publicats en revistes (Enginyeria Química i Química Analítica)

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