Abstract
ABSTRACT It is essential to establish a method for reconstructing the source term and spatiotemporal distribution of radionuclides released into the atmosphere due to a nuclear accident for emergency countermeasures. We examined the dependency of a source term estimation method based on Bayesian inference using atmospheric dispersion simulation and environmental monitoring data on the availability of various monitoring data. Additionally, we examined the applicability of this method to a real-time estimation conducted immediately after an accident. A sensitivity analysis of the estimated source term during the Fukushima Daiichi Nuclear Power Station (FDNPS) accident for combinations of various monitoring data indicated that using monitoring data with a high temporal and spatial resolution and the concurrent use of air concentration and surface deposition data is effective for accurate estimation. A real-time source term estimation experiment assuming the situation of monitoring data acquisition during the FDNPS accident revealed that this method could provide the necessary source term for grasping the overview of surface contamination in the early phase and evaluating the approximate accident scale. If the immediate online acquisition of monitoring data and regular operation of an atmospheric dispersion simulation are established, this method can provide the source term in near-real time.
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