Radionuclide Deposition Estimation from Fukushima Daiichi Nuclear Power Plant by Inverse Model

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Monday, 3 February 2014: 1:45 PM
Room C206 (The Georgia World Congress Center )
Takashi Maki, MRI, Tsukuba, Japan; and T. Y. Tanaka, M. Kajino, T. T. Sekiyama, Y. Igarashi, and M. Mikami

A lot of radioactive materials were emitted in the accident of the Fukushima Daiichi nuclear power plant, which occurred in March 2011. The 137Cs deposition is one of the most important issues that affect natural and human activities. Although various organizations released the 137Cs deposition estimation results by using their transport model. The most case assumed source term from independent analysis and resulted that the simulation accuracy was relatively limited. In this study, we combine our tagged tracer simulation result and source term estimated by inverse model to reproduce consistent 137Cs total deposition amount. We used tagged simulation results by global aerosol model named MASINGAR (Tanaka et al., 2005). The horizontal resolution is TL319 (about 60 km). We released an unit (1Tg/hr) tagged tracers (Cs137) from model lowest level. We collected 51 sites' of daily observation data in the world (CTBTO, Ro5, Berkeley, Taiwan and MRI). The analysis period is 40 days from March 11 - April 19. The prior emission information is JAEA posterior (Terada et al., 2012). We find that estimated total emission amount is about 19.5PBq during the period. The important point is that total land deposition rate against total emission amount exceeds 48% (9.4PBq) when we combine tagged simulation results and our inversed source term. When we combine tagged simulation results and Terada (or Stohl) source term, the rate remained only 30% (Terada; 2.4PBq, Stohl; 8.6PBq). The reason is the meteorological field of the maximum release date (March 15). The March 15 release showed the third largest land deposition rate (56%) during the period. To obtain more robust results, we should combine global and regional transport model in this study. We also consider it possible to obtain reliable result by using multi-model (processes) ensemble results with inverse model. The results of this study are available for modification of many processes of aerosol transport models.