Articles | Volume 21, issue 17
https://doi.org/10.5194/acp-21-13247-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-13247-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Sep 2021
Research article |
| 07 Sep 2021
| 07 Sep 2021
Quantification of uncertainties in the assessment of an atmospheric release source applied to the autumn 2017 106Ru event
Joffrey Dumont Le Brazidec
CORRESPONDING AUTHOR
IRSN, PSE-SANTE, SESUC, BMCA, Fontenay-aux-Roses, France
CEREA, Joint laboratory École des Ponts ParisTech and EDF R&D, Université Paris-Est, Marne-la-Vallée, France
Marc Bocquet
CEREA, Joint laboratory École des Ponts ParisTech and EDF R&D, Université Paris-Est, Marne-la-Vallée, France
Olivier Saunier
IRSN, PSE-SANTE, SESUC, BMCA, Fontenay-aux-Roses, France
Yelva Roustan
CEREA, Joint laboratory École des Ponts ParisTech and EDF R&D, Université Paris-Est, Marne-la-Vallée, France
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Cited
20 citations as recorded by crossref.
- A Multi‐Model Ensemble Kalman Filter for Data Assimilation and Forecasting E. Bach & M. Ghil
- Inverse modeling of 137Cs during Chernobyl 2020 wildfires without the first guess O. Tichý et al.
- Bayesian reconstruction of atmospheric radionuclide releases from sparse observations using nonuniform continuous priors for both spatial location and temporal release Y. Xu & S. Fang
- Efficient Bayesian source reconstruction and uncertainty quantification of atmospheric radionuclide releases by replacing release rate sampling with Maximum-A-Posteriori estimation of time-varying release rates Y. Xu et al.
- Investigation of short-term chemical changes in stable ruthenium added to soil by using X-ray absorption fine-structure analysis Y. Unno & A. Takeda
- Spatial-temporal source term estimation using deep neural network prior and its application to Chernobyl wildfires A. Brožová et al.
- Single MCMC chain parallelisation on decision trees E. Drousiotis & P. Spirakis
- A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases Y. Xu et al.
- Intuitively tuned elastic bias correction of atmospheric inversion using Gaussian process prior: Application to accidental radioactive emissions A. Brožová et al.
- Bayesian transdimensional inverse reconstruction of the Fukushima Daiichi caesium 137 release J. Dumont Le Brazidec et al.
- Development of source term estimation model using Kalman filter technique and its evaluation against reversal method D. Kundu et al.
- An experimental, computational, and uncertainty analysis study of the rates of iodoalkane trapping by DABCO in solution phase organic media K. Grubel et al.
- Accounting for meteorological biases in simulated plumes using smarter metrics P. Vanderbecken et al.
- Sensitivity of Bayesian source reconstruction to likelihood functions: analyses based on ETEX field experiments Y. Zhao et al.
- Source reconstruction via deposition measurements of an undeclared radiological atmospheric release S. Van Leuven et al.
- Source term determination with elastic plume bias correction O. Tichý et al.
- Source reconstruction for atmospheric radionuclide leakage: Recent advances in decoding information from atmospheric transport physics Y. Xu et al.
- Method of Source Identification Following an Accidental Release at an Unknown Location Using a Lagrangian Atmospheric Dispersion Model S. Andronopoulos & I. Kovalets
- Robust source reconstruction of atmospheric radionuclides from observations of different sparsity with spatial preselection and non-smooth constraints Y. Xu et al.
- Lagrangian and Eulerian modelling of 106Ru atmospheric transport in 2017 over northern hemisphere L. Adenis et al.
20 citations as recorded by crossref.
- A Multi‐Model Ensemble Kalman Filter for Data Assimilation and Forecasting E. Bach & M. Ghil
- Inverse modeling of 137Cs during Chernobyl 2020 wildfires without the first guess O. Tichý et al.
- Bayesian reconstruction of atmospheric radionuclide releases from sparse observations using nonuniform continuous priors for both spatial location and temporal release Y. Xu & S. Fang
- Efficient Bayesian source reconstruction and uncertainty quantification of atmospheric radionuclide releases by replacing release rate sampling with Maximum-A-Posteriori estimation of time-varying release rates Y. Xu et al.
- Investigation of short-term chemical changes in stable ruthenium added to soil by using X-ray absorption fine-structure analysis Y. Unno & A. Takeda
- Spatial-temporal source term estimation using deep neural network prior and its application to Chernobyl wildfires A. Brožová et al.
- Single MCMC chain parallelisation on decision trees E. Drousiotis & P. Spirakis
- A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases Y. Xu et al.
- Intuitively tuned elastic bias correction of atmospheric inversion using Gaussian process prior: Application to accidental radioactive emissions A. Brožová et al.
- Bayesian transdimensional inverse reconstruction of the Fukushima Daiichi caesium 137 release J. Dumont Le Brazidec et al.
- Development of source term estimation model using Kalman filter technique and its evaluation against reversal method D. Kundu et al.
- An experimental, computational, and uncertainty analysis study of the rates of iodoalkane trapping by DABCO in solution phase organic media K. Grubel et al.
- Accounting for meteorological biases in simulated plumes using smarter metrics P. Vanderbecken et al.
- Sensitivity of Bayesian source reconstruction to likelihood functions: analyses based on ETEX field experiments Y. Zhao et al.
- Source reconstruction via deposition measurements of an undeclared radiological atmospheric release S. Van Leuven et al.
- Source term determination with elastic plume bias correction O. Tichý et al.
- Source reconstruction for atmospheric radionuclide leakage: Recent advances in decoding information from atmospheric transport physics Y. Xu et al.
- Method of Source Identification Following an Accidental Release at an Unknown Location Using a Lagrangian Atmospheric Dispersion Model S. Andronopoulos & I. Kovalets
- Robust source reconstruction of atmospheric radionuclides from observations of different sparsity with spatial preselection and non-smooth constraints Y. Xu et al.
- Lagrangian and Eulerian modelling of 106Ru atmospheric transport in 2017 over northern hemisphere L. Adenis et al.
Saved (final revised paper)
Latest update: 11 May 2026
Short summary
The assessment of the environmental consequences of a radionuclide release depends on the estimation of its source. This paper aims to develop inverse Bayesian methods which combine transport models with measurements, in order to reconstruct the ensemble of possible sources.
Three methods to quantify uncertainties based on the definition of probability distributions and the physical models are proposed and evaluated for the case of 106Ru releases over Europe in 2017.
The assessment of the environmental consequences of a radionuclide release depends on the...
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