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

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/00216208:11320/17:10372578 RIV/86652052:_____/17:N0000066

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>

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 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.

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 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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/7F14287" target="_blank" >7F14287: Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI)</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

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

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