An inverse modeling method to assess the source term of the Fukushima Nuclear Power Plant accident using gamma dose rate observations
By O. Saunier, A. Mathieu, D. Didier, M. Tombette, D. Quélo, V. Winiarek, Marc Bocquet. 2013
158 citations recorded by the source corpus.
Abstract. The Chernobyl nuclear accident, and more recently the Fukushima accident, highlighted that the largest source of error on consequences assessment is the source term, including the time evolution of the release rate and its distribution between radioisotopes. Inverse modeling methods, which combine environmental measurements and atmospheric dispersion models, have proven efficient in assessing source term due to an accidental situation (Gudiksen, 1989; Krysta and Bocquet, 2007; Stohl et al., 2012a; Winiarek et al., 2012). Most existing approaches are designed to use air sampling measurements (Winiarek et al., 2012) and some of them also use deposition measurements (Stohl et al., 2012a; Winiarek et al., 2014). Some studies have been performed to use dose rate measurements (Duranova et al., 1999; Astrup et al., 2004; Drews et al., 2004; Tsiouri et al., 2012) but none of the developed methods were carried out to assess the complex source term of a real accident situation like the Fukushima accident. However, dose rate measurements are generated by the most widespread measurement system, and in the event of a nuclear accident, these data constitute the main source of measurements of the plume and radioactive fallout during releases. This paper proposes a method to use dose rate measurements as part of an inverse modeling approach to assess source terms. The method is proven efficient and reliable when applied to the accident at the Fukushima Daiichi Nuclear Power Plant (FD-NPP). The emissions for the eight main isotopes 133 Xe, 134 Cs, 136 Cs, 137 Cs, 137m Ba, 131 I, 132 I and 132 Te have been assessed. Accordingly, 105.9 PBq of 131 I, 35.8 PBq of 132 I, 15.5 PBq of 137 Cs and 12 134 PBq of noble gases were released. The events at FD-NPP (such as venting, explosions, etc.) known to have caused atmospheric releases are well identified in the retrieved source term. The estimated source term is validated by comparing simulations of atmospheric dispersion and deposition with environmental observations. In total, it was found that for 80% of the measurements, simulated and observed dose rates agreed within a factor of 2. Changes in dose rates over time have been overall properly reconstructed, especially in the most contaminated areas to the northwest and south of the FD-NPP. A comparison with observed atmospheric activity concentration and surface deposition shows that the emissions of caesiums and 131 I are realistic but that 132 I and 132 Te are probably underestimated and noble gases are likely overestimated. Finally, an important outcome of this study is that the method proved to be perfectly suited to emergency management and could contribute to improve emergency response in the event of a nuclear accident.
Subfields: Global and Planetary Change, Radiological and Ultrasound Technology, Safety, Risk, Reliability and Quality
View Paper: https://www.semanticscholar.org/paper/e366cdd13764fe34628923a33eaf22608ad47c1f
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In Global and Planetary Change
In Radiological and Ultrasound Technology
Citations in the corpus
- Detailed source term estimation of the atmospheric release for the Fukushima Daiichi Nuclear Power Station accident by coupling simulations of an atmospheric dispersion model with an improved deposition scheme and oceanic dispersion model (2014, methodology): “In other periods,10 Saunier et al. (2013) frequently shows higher release rates with uncertainties when the plume flowed toward the ocean.”
- Source term estimation using air concentration measurements and a Lagrangian dispersion model – Experiments with pseudo and real cesium-137 observations from the Fukushima nuclear accident (2015, methodology): “, 2014), while others used a more formal inverse modeling approach by introducing a cost functional and a priori estimate (e.g. Stohl et al., 2012; Winiarek et al., 2012; Saunier et al., 2013; Winiarek et al., 2014).”