The identification of areas vulnerable to radiocaesium deposition in Hungary

Abstract

Radiocaesium is an important and persistent environmental contaminant that can be deposited following nuclear accidents. It became apparent after the Chernobyl accident that some regions were vulnerable to radiocaesium deposition. Prior identification of vulnerable areas using spatial models that incorporate variation in radiocaesium soil-to-plant transfer as a function of soil properties would allow post-accident management options to be prioritised and effectively implemented. In this paper, an assessment of the influence of different input soil property data sets for Hungary upon spatial model predictions of cow milk 137 Cs activity concentrations and the identification of vulnerable areas is presented. Although predictions of cow milk 137 Cs activity concentrations after Chernobyl made using the three input soil property data sets are all broadly similar and in reasonable agreement with national monitoring data, the identification of vulnerable areas is greatly influenced by the input soil property data set used. Our results suggest that using soil property databases derived from amalgamation of soil properties into broad soil categories will lead to vulnerable areas not being identified. The findings presented in this paper have important implications for the use of spatial models in the prediction of radiocaesium transfer, identification of vulnerable areas and management of contaminated areas.