Preprints
https://doi.org/10.5194/acp-2020-1129
https://doi.org/10.5194/acp-2020-1129

  25 Jan 2021

25 Jan 2021

Review status: this preprint is currently under review for the journal ACP.

Quantification of the modelling uncertainties in atmospheric release source assessment and application to the reconstruction of the autumn 2017 Ruthenium 106 source

Joffrey Dumont Le Brazidec1,2, Marc Bocquet2, Olivier Saunier1, and Yelva Roustan2 Joffrey Dumont Le Brazidec et al.
  • 1IRSN, PSE-SANTE, SESUC, BMCA, Fontenay-aux-Roses, France
  • 2CEREA, Joint laboratory École des Ponts ParisTech and EDF R&D, Université Paris-Est, Marne-la-Vallée, France

Abstract. Using a Bayesian framework in the inverse problem of estimating the source of an atmospheric release of a pollutant has proven fruitful in recent years. Through Markov chain Monte Carlo (MCMC) algorithms, the statistical distribution of the release parameters such as the location, the duration, and the magnitude as well as the likelihood covariances can be sampled so as to get a complete characterisation of the source. In this study, several approaches are described and applied to improve on these distributions, and therefore to get a better representation of the uncertainties. First, a method based on ensemble forecasting is proposed: physical parameters of both the meteorological fields and the transport model are perturbed to create an enhanced ensemble. In order to account for model errors, the importance of ensemble members are represented by weights and sampled together with the other variables of the source. Secondly, the choice of the statistical likelihood is shown to alter the nuclear source assessment, and several suited distributions for the errors are advised. Finally, two advanced designs of the covariance matrix associated to the observation error are proposed. These methods are applied to the case of the detection of Ruthenium 106 of unknown origin in Europe in autumn 2017. A posteriori distributions meant to identify the origin of the release, to assess the source term, to quantify the uncertainties associated to the observations and the model, as well as densities of the weights of the perturbed ensemble, are presented.

Joffrey Dumont Le Brazidec et al.

Status: open (until 22 Mar 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2020-1129', Pieter De Meutter, 15 Feb 2021 reply
  • RC2: 'Comment on acp-2020-1129', Anonymous Referee #1, 19 Feb 2021 reply
    • RC5: 'Reply on RC2', Anonymous Referee #1, 23 Feb 2021 reply
  • RC3: 'Comment on acp-2020-1129', Ondřej Tichý, 22 Feb 2021 reply
  • RC4: 'Comment on acp-2020-1129', Anonymous Referee #3, 23 Feb 2021 reply

Joffrey Dumont Le Brazidec et al.

Joffrey Dumont Le Brazidec et al.

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