Monte Carlo simulation on gamma spectrometry and application to radioactivity measurement in Honey samples

Abstract

By integrating computational modeling (MCNP5, ANGLE, MEFFTRAN) and experimental techniques (gamma spectrometry, AAS, CHARM II),this thesis develops and applies advanced methodologies for analyzing radioactivity and contaminants in honey, a dense and complex ma-trix with significant value. The study specifically addresses critical challenges in gamma spectrometry, photon attenuation, self-absorption, and true coincidence sum-ming (TCS) effects. The optimized Monte Carlo simulations demonstrated excellent with the experimental data (deviations <5% for low-energy gamma rays). The validated model was then applied to quantify (226Ra, 232Th, and 40K) in honey samples from various geographical origins. Additional analyses using AAS and CHARM II were employed to trace levels of heavy metals (K, Zn, Cu, Al, As) and residues (tetracyclines and ), revealing trends linked to industrial zones and environmental or apicultural practices. This approach offers a robust and for analysis in dense matrices, with important for food safety regulations, environmental monitoring, and public health protection.