Urban radiological risk assessment using HotSpot and Geant4: From probabilistic dose estimates to shielding effects

Radiological dispersal devices (RDDs) present a significant threat in urban environments due to their potential to deliver high radiation doses over populated areas. This study presents a novel integrated framework for assessing radiological risk from potential urban RDD incidents by integrating probabilistic uncertainty analysis with advanced computational modeling, including automated HotSpot simulations and Geant4-based urban shielding. This combined approach captures both the variability inherent in environmental conditions and the complex interactions of radiation with densely built structures. A total of 2500 stochastic simulations were conducted for scenarios involving uncertain parameters such as wind speed and direction, deposition velocities, receptor height, and radionuclide activities (¹³⁷Cs and ²⁴¹Am). Results indicate that in open-air conditions, the mean total effective dose equivalent (TEDE) reaches 8.65 Sv at 0.1 km from the source, decreasing to 1.78 Sv at 1 km and 0.16 Sv at 10 km. Incorporation of urban shielding via Geant4 dramatically reduces near-field doses: at 0.1 km, TEDE falls to 0.57 Sv, representing a >15-fold decrease; at 1 km, it drops to 0.034 Sv, and at 10 km to 0.0015 Sv. Analysis of effective attenuation coefficients shows that photon fluxes decrease exponentially with distance, falling below 0.02 m^-1 beyond 600 m. Organ-specific assessment identifies the liver as the most exposed organ, with its mean dose decreasing from 28.1 Sv to 1.84 Sv after attenuation, while the lung dose declines from 1.37 Sv to 0.09 Sv at 0.1 km. These reductions highlight the substantial shielding effect of dense urban structures, which not only lowers exposure levels but also reduces probabilistic variability, thereby providing more reliable dose estimates. The findings underscore the critical importance of probabilistic, organ-specific assessment and realistic urban modeling to guide emergency planning, early evacuation strategies, and public safety. The reported dose estimates are based on probabilistic HotSpot simulations coupled with Geant4 calculations performed for a representative high-density urban configuration using simplified building geometries and homogeneous material properties. The integrated HotSpot-Geant4 methodology provides a robust and scientifically rigorous framework that can be extended to support radiological emergency planning in diverse urban environments.