Please use this identifier to cite or link to this item:
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
Author(s): 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:
Issue Date: Nov-2008
Date Deposited: 10-Aug-2012
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.
DOI Link: 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.
Licence URL(s):

Files in This Item:
File Description SizeFormat 
copplestone_radiatenvironbiophys_2008.pdfFulltext - Published Version308.79 kBAdobe PDFUnder Permanent Embargo    Request a copy

Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.

This item is protected by original copyright

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved

If you believe that any material held in STORRE infringes copyright, please contact providing details and we will remove the Work from public display in STORRE and investigate your claim.