Ranking uncertainties in atmospheric dispersion modelling following the accidental release of radioactive material

Susan Leadbetter ,C Twenhöfel,T Hamburger,H De Vries,S Andronopoulos,F Gering,Anne Mathieu ,Csilla Rudas ,A R Jones ,Jasper Tomas ,Irène Korsakissok ,Péter Szántó ,Tamás Pázmándi ,Andrey Sogachev ,Heiko Klein ,Raphaël Périllat ,Gertie Geertsema ,Peter Bedwell ,Karine Chevalier-Jabet ,Joseph Wellings

doi:10.1051/radiopro/2020012

Abstract

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.

Highlights

In the event of an accidental release of radionuclides into the atmosphere, dispersion models would be used to evaluate the consequences and to assist in determining appropriate countermeasures
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
There are several sources of uncertainty in the dispersion model prediction including those related to the source term information and the driving meteorology as well as physical parametrisations and numerical approximations made in the dispersion model

Summary

Introduction

In the event of an accidental release of radionuclides into the atmosphere, dispersion models would be used (in conjunction with dose models) to evaluate the consequences and to assist in determining appropriate countermeasures. In order to model the consequences, the dispersion model requires information about the type, quantity, timing and physical characteristics of the release (referred to as the source term) as well as details of the meteorological conditions during the period of release and transport of pollutants. There are several sources of uncertainty in the dispersion model prediction including those related to the source term information and the driving meteorology as well as physical parametrisations and numerical approximations made in the dispersion model. A useful discussion on the types on uncertainties in dispersion models is given by Rao (2005). As the estimation of uncertainties in the three categories is approached differently it Some comments on combining uncertainties and their relative importance are given at the end of the paper

Meteorological uncertainty

Source term uncertainties

Atmospheric dispersion model uncertainties

Ranking uncertainties

Summary