The estimation of absorbed dose rates for non-human biota: An extended intercomparison

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Vives I Batlle, J. | Beaugelin-Seiller, K. | Beresford, N.A. | Copplestone, D. | Horyna, J. | Hosseini, A. | Johansen, M. | Kamboj, S. | Keum, D.-K. | Kurosawa, N. | Newsome, L. | Olyslaegers, G. | Vandenhove, H. | Ryufuku, S. | Vives Lynch, S. | Wood, M.D. | Yu, C.

Edité par CCSD ; Springer Verlag -

International audience. An exercise to compare 10 approaches for the calculation of unweighted whole-body absorbed dose rates was conducted for 74 radionuclides and five of the ICRP's Reference Animals and Plants, or RAPs (duck, frog, flatfish egg, rat and elongated earthworm), selected for this exercise to cover a range of body sizes, dimensions and exposure scenarios. Results were analysed using a non-parametric method requiring no specific hypotheses about the statistical distribution of data. The obtained unweighted absorbed dose rates for internal exposure compare well between the different approaches, with 70% of the results falling within a range of variation of ±20%. The variation is greater for external exposure, although 90% of the estimates are within an order of magnitude of one another. There are some discernible patterns where specific models over- or under-predicted. These are explained based on the methodological differences including number of daughter products included in the calculation of dose rate for a parent nuclide; source-target geometry; databases for discrete energy and yield of radionuclides; rounding errors in integration algorithms; and intrinsic differences in calculation methods. For certain radionuclides, these factors combine to generate systematic variations between approaches. Overall, the technique chosen to interpret the data enabled methodological differences in dosimetry calculations to be quantified and compared, allowing the identification of common issues between different approaches and providing greater assurance on the fundamental dose conversion coefficient approaches used in available models for assessing radiological effects to biota. © 2010 Springer-Verlag.

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