Volume 55, May 2020Coping with uncertainties for improved modelling and decision making in nuclear emergencies. Key results of the CONFIDENCE European research project
|Page(s)||S51 - S55|
|Section||EARLY PHASE MODELLING|
|Published online||26 June 2020|
Ranking uncertainties in atmospheric dispersion modelling following the accidental release of radioactive material
2 EEAE/NCSRD – Greek Atomic Energy Commission)/National Center for Scientific Research “Demokritos”, Agia Paraskevi, Greece
3 PHE – Public Health England, Didcot, UK
4 IRSN – Institute for Radiation Protection and Nuclear Safety, Fontenay-aux-Roses, France
5 KNMI – Royal Netherlands Meteorological Institute, De Bilt, The Netherlands
6 BfS – Federal Office for Radiation Protection, Neuherberg, Germany
7 NMI – The Norwegian Meteorological Institute, Oslo, Norway
8 EK – Centre for Energy Research, Budapest, Hungary
9 PHIMECA Engineering, Clermont-Ferrand, France
10 DTU Wind Energy, Roskilde, Denmark
11 RIVM – National Institute for Public Health and the Environment, Bilthoven, The Netherlands
* Corresponding author: firstname.lastname@example.org
During the pre-release and early phase of an accidental release of radionuclides into the atmosphere there are few or no measurements, and dispersion models are used to assess the consequences and assist in determining appropriate countermeasures. However, uncertainties are high during this early phase and it is important to characterise these uncertainties and, if possible, include them in any dispersion modelling. In this paper we examine three sources of uncertainty in dispersion modelling; uncertainty in the source term, uncertainty in the meteorological information used to drive the dispersion model and intrinsic uncertainty within the dispersion model. We also explore the possibility of ranking these uncertainties dependent on their impact on the dispersion model outputs.
Key words: uncertainty / atmospheric dispersion model / source terms / ensemble simulation / CONFIDENCE
© The Authors, published by EDP Sciences 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.