Foliar interception of radionuclides in dry conditions: a meta-analysis using a Bayesian modeling approach

Uncertainty on the parameters that describe the transfer of radioactive materials into the (terrestrial) environment may be characterized thanks to datasets such as those compiled within International Atomic Energy Agency (IAEA) documents. Nevertheless, the information included in these documents is too poor to derive a relevant and informative uncertainty distribution regarding dry interception of radionuclides by the pasture grass and the leaves of vegetables. In this paper, 145 sets of dry interception measurements by the aboveground biomass of specific plants were collected from published scientific papers. A Bayesian meta-analysis was performed to derive the posterior probability distributions of the parameters that reflect their uncertainty given the collected data. Four competing models were compared in terms of both fitting performances and predictive abilities to reproduce plausible dry interception data. The asymptotic interception factor, applicable whatever the species and radionuclide to the highest aboveground biomass values (e.g. mature leafy vegetables), was estimated with the best model, to be 0.87 with a 95% credible interval (0.85, 0.89). •145 dry interception factors in grass and vegetables collected in the literature.•Bayesian meta-analysis was performed to characterize uncertainty and variability.•Plant-specific variability and “physical form-specific” variability were assessed.•4 hierarchical models compared regarding their fitting and predictive performances.•Maximum interception factor was estimated at 0.87 with 95%CI (0.85,0.89).