Land-cover-based indoor gamma-ray dose after a nuclear accident: location factor mapping via Monte Carlo simulation, GIS, and remote sensing

Abstract

Long-term indoor dose prediction is critical for health risk assessment and disaster management of accidental radionuclide releases. The gamma rays emitted from the ground deposition of ¹³⁷Cs are the primary concern in this context. This deposition exhibits variations in the relative initial source strength, ecological half-life, and vertical migration depending on the ground material. The dose response is further influenced by the attenuation within the ground, air, and building structures. Therefore, evaluating indoor doses in complex urban environments is challenging, particularly when accounting for directional variations in factors such as building density and ground materials. To address this issue, this study draws on the Local Climate Zone (LCZ) concept to propose a universal urban classification method suited to areas with mixed land cover and low-rise detached wooden structures, such as Fukushima. Monte Carlo simulations are then used to identify time-dependent indoor dose location factors across various environment type combinations. A mapping approach referencing LCZ recognition is developed using geographic information systems and remote sensing.