Dominant nuclide identification and progeny contribution to dose with a focus on controlled release scenarios

To establish emergency planning zones, it is necessary to understand how dose to residents changes with distance, represented as a dose–distance(D–D) curve, under different accident scenarios. Previous studies have shown that the nuclide contribution to dose—specifically, whether aerosol or gaseous nuclides are dominant—has a strong influence on the shape of D–D curves. The objective of this study is to identify the dominant nuclides for each accident scenario, focusing on progeny nuclides, to clarify the distinction between aerosol- and gas-dominated scenarios, and to quantitatively understand the characteristics of the D–D curves for each accident scenario under selected range of meteorological conditions. To this end, we developed a Python tool called “Dose Evaluation framework for Consequence-Informed and Scenario-Oriented Navigation: DECISION.” Modeling of progeny nuclides was found to have a substantial effect on controlled releases based on comparisons with monitoring post observations during the Fukushima–Daiichi accident. Dominant nuclides were identified, and the distinction between aerosol- or gas-dominated scenarios was clarified. The dominant nuclides for high decontamination factor (DF) scenarios are Kr-88 and Xe-135 (progeny nuclide of I-135) in 6- and 24-h release timing, respectively, regardless of precipitation. Meanwhile, the dominant nuclide among low DF scenarios is I-131, but the influence of Te-132 becomes evident under precipitation, regardless of release timing. Further, the characteristics of D–D curves for each accident scenario were identified, and it was suggested that the D–D curves were highly dependent on nuclides under precipitation, regardless of the stability class.