Articles | Volume 17, issue 20
https://doi.org/10.5194/acp-17-12677-2017
https://doi.org/10.5194/acp-17-12677-2017
Research article
 | 
25 Oct 2017
Research article |  | 25 Oct 2017

Bayesian inverse modeling and source location of an unintended 131I release in Europe in the fall of 2011

Ondřej Tichý, Václav Šmídl, Radek Hofman, Kateřina Šindelářová, Miroslav Hýža, and Andreas Stohl

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Cited articles

Annunzio, A. J., Young, G. S., and Haupt, S. E.: Utilizing state estimation to determine the source location for a contaminant, Atmos. Environ., 46, 580–589, 2012.
Berchet, A., Pison, I., Chevallier, F., Bousquet, P., Conil, S., Geever, M., Laurila, T., Lavric, J., Lopez, M., Moncrieff, J., Necki, J., Ramonet, M., Schmidt, M., Steinbacher, M., and Tarniewicz, J.: Towards better error statistics for atmospheric inversions of methane surface fluxes, Atmos. Chem. Phys., 13, 7115–7132, https://doi.org/10.5194/acp-13-7115-2013, 2013.
Bernardo, J. M. and Smith, A. F. M.: Bayesian theory, Vol. 405, John Wiley & Sons, 2009.
Bishop, C. M.: Pattern recognition and machine learning, Springer, 2006.
Bocquet, M.: Reconstruction of an atmospheric tracer source using the principle of maximum entropy, Part I: Theory, Q. J. Roy. Meteor. Soc., 131, 2191–2208, 2005.
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In the fall of 2011, iodine-131 (131I) was detected at several radionuclide monitoring stations in central Europe. We estimate the source location and emission variation using only the available 131I measurements. Subsequently, we use the IAEA report about the source term for validation of our results. We find that our algorithm could successfully locate the actual release site. The findings are also in agreement with the values reported by the IAEA.
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