Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/7501
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Inter-comparison of models to estimate radionuclide activity concentrations in non-human biota
Authors: Beresford, Nicholas A
Barnett, Catherine L
Brown, Justin
Cheng, Jing-Jey
Copplestone, David
Filistovic, Vitold
Hosseini, Ali
Howard, Brenda J
Jones, Steve R
Kamboj, Sunita
Kryshev, Alexander I
Nedveckaite, Tatjana
Saxen, Ritva
Sazykina, Tatiana
Vives, i Batlle Jordi
Vives, Lynch Sandra
Yankovich, Tamara L
Yu, Charley
Olyslaegers, Geert
Contact Email: david.copplestone@stir.ac.uk
Issue Date: Nov-2008
Publisher: Springer
Citation: Beresford NA, Barnett CL, Brown J, Cheng J, Copplestone D, Filistovic V, Hosseini A, Howard BJ, Jones SR, Kamboj S, Kryshev AI, Nedveckaite T, Saxen R, Sazykina T, Vives i Batlle J, Vives Lynch S, Yankovich TL, Yu C & Olyslaegers G (2008) Inter-comparison of models to estimate radionuclide activity concentrations in non-human biota, Radiation and Environmental Biophysics, 47 (4), pp. 491-514.
Abstract: A number of models have recently been, or are currently being, developed to enable the assessment of radiation doses from ionising radiation to non-human species. A key component of these models is the ability to predict whole-organism activity concentrations in a wide range of wildlife. In this paper, we compare the whole-organism activity concentrations predicted by eight models participating within the IAEA Environmental Modelling for Radiation Safety programme for a range of radionuclides to terrestrial and freshwater organisms. In many instances, there was considerable variation, ranging over orders of magnitude, between the predictions of the different models. Reasons for this variability (including methodology, data source and data availability) are identified and discussed. The active participation of groups responsible for the development of key models within this exercise is a useful step forward in providing the transparency in methodology and data provenance required for models which are either currently being used for regulatory purposes or which may be used in the future. The work reported in this paper, and supported by other findings, demonstrates that the largest contribution to variability between model predictions is the parameterisation of their transfer components. There is a clear need to focus efforts and provide authoritative compilations of those data which are available.
Type: Journal Article
URI: http://hdl.handle.net/1893/7501
DOI Link: http://dx.doi.org/10.1007/s00411-008-0186-8
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Affiliation: Lancaster Environment Centre
Lancaster Environment Centre
Norwegian Radiation Protection Authority
Argonne National Laboratory
Biological and Environmental Sciences
Institute of Physics, Lithuania
Norwegian Radiation Protection Authority
Lancaster Environment Centre
Westlakes Scientific Consulting Ltd
Argonne National Laboratory
SPATyphoon, Russia
Institute of Physics, Lithuania
Radiation and Nuclear Safety Authority (STUK), Finland
SPATyphoon, Russia
Westlakes Scientific Consulting Ltd
Westlakes Scientific Consulting Ltd
Atomic Energy Canada Limited
Argonne National Laboratory
SCK-CEN - Belgian Nuclear Research Centre

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