Towards Monte Carlo based Full Spectrum Modeling of Airborne Gamma-Ray Spectrometry Systems

This monograph presents advancements in Airborne Gamma-Ray Spectrometry (AGRS), a critical tool for emergency response to radiological incidents such as severe nuclear accidents or nuclear weapon detonations. Current AGRS calibration and data evaluation methods struggle to accurately quantify many radioactive materials expected in radiological emergencies, limiting the risk assessment and, hence, the effectiveness of emergency response actions. To address these limitations, this work introduces a full spectrum numerical modeling approach that features three key innovations: high-fidelity Monte Carlo simulations that combine an advanced scintillation physics model with detailed geometric representations of the aircraft and detector system; a surrogate model that replicates the Monte Carlo simulations with significantly reduced computation time; and a data evaluation methodology that leverages the surrogate model within a Bayesian inversion framework, enabling the quantification of arbitrarily complex gamma-ray fields. The methodology presented here, rigorously validated through laboratory and field measurements, achieves not only a significant improvement in accuracy and sensitivity over traditional methods but also substantially expands the operational capabilities of AGRS systems for both emergency response scenarios and geophysical surveys. These innovations lay the groundwork for establishing a new global standard for AGRS, ultimately supporting better-informed protective actions and reducing health risks during radiological emergencies.