An inverse modeling method to assess the source term of the Fukushima Nuclear Power Plant accident using gamma dose rate observations

Abstract

International audienceThe 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 133Xe, 134Cs, 136Cs, 137Cs, 137mBa, 131I, 132I and 132Te have been assessed. Accordingly, 105.9 PBq of 131I, 35.8 PBq of 132I, 15.5 PBq of 137Cs 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 131I are realistic but that 132I and 132Te 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

Long-term assessment of airborne radiocesium after the Fukushima nuclear accident: re-suspension from bare soil and forest ecosystems

“…Since then, a number of studies have been conducted, particularly during the months that followed the accident. These assessments include primary emission estimations (Chino et al, 2011;Danielache et al, 2012;Stohl et al, 2012;Terada et al, 2012;Katata et al, 2012aKatata et al, , b, 2015Winiarek et al, 2012Winiarek et al, , 2014Hirao et al, 2013;Saunier et al, 2013;Yumimoto et al, 2016;Danielache et al, 2016), field observations (ground aerosol sampling: Masson et al, 2011Masson et al, , 2013Kaneyasu et al, 2012;Adachi et al, 2013;Tsuruta et al, 2014;Igarashi et al, 2015;Oura et al, 2015;aircraft measurements: NRA, 2012; and measurements carried out on foot: Hososhima and Kaneyasu, 2015), and numerical simulations of transport and depositions (deterministic simulation: Chino et al, 2011;Morino et al, 2011;Yasunari et al, 2011;Stohl et al, 2012;Terada et al, 2012;Katata et al, 2012a, b;Winiarek et al, 2012Winiarek et al, , 2014Hirao et al, 2013;Saunier et al, 2013;Katata et al, 2015;Yumimoto et al, 2016;Danielache et al, 2016; deterministic simulation with sensitivity runs: Morino et al, 2013;Adachi et al, 2013;Groëll et al, 2014;Saito et al, 2015;…”

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

“…Compared to the previous studies that also introduced 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), a more detailed sensitivity study is provided to validate the assumptions of our inverse estimation technique.…”

“…Chino et al, 2011;Katata et al, 2012;Terada et al, 2012;Hirao et al, 2013;Kobayashi et al, 2013;Oza et al, 2013;Katata et al, 2014;Achim et al, 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).…”

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

“…Given accurate release information, atmospheric transport models can simulate the radioiodine dispersion and give a more comprehensive view of the situation than the measurements alone. For instance, simulations with atmospheric transport models were used previously to study the distribution of radioactive material after the Chernobyl (e.g., Brandt et al, 2002;Davoine and Bocquet, 2007) and Fukushima Dai-ichi nuclear accidents (e.g., Morino et al, 2011;Stohl et al, 2012;Saunier et al, 2013). Simulations were also already made for the 131 I release from IoI in 2011 (Leelőssy et al, 2017).…”