pyDOSEIA: A Python Package for Radiological Impact Assessment during Long-term or Accidental Atmospheric Releases.

Abstract

Abstract: pyDOSEIA is a Python package designed for meteorological data processing and radiological impact assessment in diverse scenarios, including nuclear and radiological accidents. Built upon robust computational models and using modern programming techniques, pyDOSEIA employs the Gaussian Plume Model and follows IAEA and AERB guidelines, offering a comprehensive suite of tools for estimating radiation doses from various exposure pathways, including inhalation, ingestion, groundshine, submersion, and plumeshine. The package enables age-specific, distance-specific, and radionuclide-specific radiation dose computations, providing accurate and reliable calculations for both short-term and long-term exposures. Additionally, pyDOSEIA leverages up-to-date dose conversion factors, features parallel processing capabilities for rapid analysis of large datasets, and facilitates applications in machine learning and deep learning research. With its user-friendly interface and extensive documentation, pyDOSEIA empowers researchers, practitioners, and policymakers to assess radiation risks effectively, aiding in decision making and emergency preparedness efforts. The package is open-source and available on GitHub at https://github.com/BiswajitSadhu/pyDOSEIA.