Bayesian inverse modeling and source location of an unintended 131I release in Europe in the fall of 2011
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00480506" target="_blank" >RIV/67985556:_____/17:00480506 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/17:10372578 RIV/86652052:_____/17:N0000066
Result on the web
<a href="http://dx.doi.org/10.5194/acp-17-12677-2017" target="_blank" >http://dx.doi.org/10.5194/acp-17-12677-2017</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5194/acp-17-12677-2017" target="_blank" >10.5194/acp-17-12677-2017</a>
Alternative languages
Result language
angličtina
Original language name
Bayesian inverse modeling and source location of an unintended 131I release in Europe in the fall of 2011
Original language description
In this study, we use the ambient concentration measurements of I-131 to determine the location of the release as well as its magnitude and temporal variation. As the location of the release and an estimate of the source strength became eventually known, this accident represents a realistic test case for inversion models. For our source reconstruction, we use no prior knowledge. Instead, we estimate the source location and emission variation using only the available I-131 measurements. Subsequently, we use the partial information about the source term available from the Hungarian authorities for validation of our results. For the source determination, we first perform backward runs of atmospheric transport models and obtain source-receptor sensitivity (SRS) matrices for each grid cell of our study domain. We use two dispersion models, FLEXPART and Hysplit, driven with meteorological analysis data from the global forecast system (GFS) and from European Centre for Medium-range Weather Forecasts (ECMWF) weather forecast models. Second, we use a recently developed inverse method, least-squares with adaptive prior covariance (LS-APC), to determine the I-131 emissions and their temporal variation from the measurements and computed SRS matrices. For each grid cell of our simulation domain, we evaluate the probability that the release was generated in that cell using Bayesian model selection. The model selection procedure also provides information about the most suitable dispersion model for the source term reconstruction. Third, we select the most probable location of the release with its associated source term and perform a forward model simulation to study the consequences of the iodine release.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/7F14287" target="_blank" >7F14287: Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI)</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Atmospheric Chemistry and Physics
ISSN
1680-7316
e-ISSN
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Volume of the periodical
17
Issue of the periodical within the volume
20
Country of publishing house
DE - GERMANY
Number of pages
20
Pages from-to
12677-12696
UT code for WoS article
000413669000003
EID of the result in the Scopus database
2-s2.0-85032448070