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

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652052%3A_____%2F17%3AN0000066" target="_blank" >RIV/86652052:_____/17:N0000066 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/67985556:_____/17:00480506 RIV/00216208:11320/17:10372578

  • Výsledek na webu

    <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>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

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

  • Popis výsledku v původním jazyce

    In the fall of 2011, iodine-131 (131I) was detected at several radionuclide monitoring stations in central Europe. After investigation, the International Atomic Energy Agency (IAEA) was informed by Hungarian authorities that 131I was released from the Institute of Isotopes Ltd. in Budapest, Hungary. It was reported that a total activity of 342GBq of 131I was emitted between 8 September and 16 November 2011. In this study, we use the ambient concentration measurements of 131I 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 131I 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 131I 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. Results of these procedures are compared with the known release location and reported information about its time variation. We find that our algorithm could successfully locate the actual release site. The estimated release period is also in agreement with the values reported by IAEA and the reported total released activity of 342GBq is within the 99% confidence interval of the posterior distribution of our most likely model.

  • Název v anglickém jazyce

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

  • Popis výsledku anglicky

    In the fall of 2011, iodine-131 (131I) was detected at several radionuclide monitoring stations in central Europe. After investigation, the International Atomic Energy Agency (IAEA) was informed by Hungarian authorities that 131I was released from the Institute of Isotopes Ltd. in Budapest, Hungary. It was reported that a total activity of 342GBq of 131I was emitted between 8 September and 16 November 2011. In this study, we use the ambient concentration measurements of 131I 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 131I 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 131I 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. Results of these procedures are compared with the known release location and reported information about its time variation. We find that our algorithm could successfully locate the actual release site. The estimated release period is also in agreement with the values reported by IAEA and the reported total released activity of 342GBq is within the 99% confidence interval of the posterior distribution of our most likely model.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10511 - Environmental sciences (social aspects to be 5.7)

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2017

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Atmospheric Chemistry and Physics

  • ISSN

    1680-7316

  • e-ISSN

  • Svazek periodika

    17

  • Číslo periodika v rámci svazku

    20

  • Stát vydavatele periodika

    DE - Spolková republika Německo

  • Počet stran výsledku

    20

  • Strana od-do

    12677-12696

  • Kód UT WoS článku

    000413669000003

  • EID výsledku v databázi Scopus

    2-s2.0-85032448070