Chemical analogues and probabilistic functions to derive distribution coefficients of radium in soils.

The existing data gaps in the sorption and desorption parameters of naturally occurring radionuclides (e.g., radium (Ra)) challenge the use of radioecological risk assessment models. We present two alternatives for deriving Ra distribution coefficients (K (Ra)) in soils when the physicochemical information on the solid and liquid phases involved is too scarce to apply parametric prediction models: the deduction of sorption parameters from those of chemical analogues (such as Ba and Sr) and the proposal of best estimate K (Ra) values deduced from probabilistic distribution functions of data grouped according to relevant factors affecting K (Ra) variability. Regarding the use of chemical analogues, partial least squares regression analysis and univariate linear correlations revealed that Ba and Ra sorption in soils was governed by the same soil properties (K (Ca + Mg) and Mn), related to exchangeable sites on the soil surface. The derivation of K (Ra) values from K (Ba) and also K (Sr) is feasible by applying suitable correction factors. Furthermore, several K (Ra) best estimates were derived from the distribution functions of K (Ra) datasets obtained from own and literature data. Statistical differences were noticed for the sorption and desorption datasets (the latter significantly affected by data from native Ra), leading to the proposal of distinct K (Ra) values (870 and 2760 L kg, respectively) for uptake and remobilisation scenarios. Regarding the desorption data, diverse K (Ra) best estimates were suggested for acidic (1540 L kg) and alkaline (6440 L kg) soils. For the sorption data, statistically different K (Ra) best estimates were suggested according to pH (100 and 1240 L kg for pH < 4.5 and pH ≥ 7, respectively) and water-soluble Ca + Mg content, allowing for the selection of the most appropriate best estimate values for use in risk assessment models depending on the available information.