BSc/MSc – Source Estimation in Atmospheric Radiological Releases

Abstract

When radioactivity is detected in the atmosphere, a crucial task is to determine both the location of a release and its temporal profile. While the location is often known, the temporal profile and the total quantity of the released substance are usually only roughly estimated or entirely unknown.

The main objective is to reconstruct the temporal profile of a release from available field measurements (concentration or deposition). This can be achieved by optimizing the agreement between the measured data and the outputs of an atmospheric dispersion model.

In this work, the student will become familiar with classical optimization techniques as well as, in particular, the Bayesian approach and parameter estimation methods for probabilistic models. The work may focus, depending on the student’s interest, on analyzing data from a specific real-world event or on modifying a particular component of the mathematical model. The developed methods will be applied to real cases such as the Chernobyl accident, the iodine release in Europe in 2011, the ruthenium release in Eurasia in 2017, or the cesium-137 release during the massive fires around Chernobyl in 2020.

References

[1] M. Hutchinson, H. Oh, W. Chen, A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors. Information Fusion 36, 2017, 130-148.
[2] P. Seibert and A. Frank, Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode. Atmospheric Chemistry and Physics 4(1), 2004, 51–63.
[3] V. Šmídl, A. Quinn, The Variational Bayes Method in Signal Processing. Springer, 2006.
[4] O. Tichý, V. Šmídl, R. Hofman, K. Šindelářová, M. Hýža, A. Stohl, Bayesian inverse modeling and source location of an unintended I-131 release in Europe in the fall of 2011, Atmospheric Chemistry and Physics 17(20), 2017, 12677-12696.
[5] O. Tichý, V. Šmídl, N. Evangeliou, Source term determination with elastic plume bias correction, Journal of Hazardous Materials vol.425 (2022), 127776.

Contact

Ondřej Tichý