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Updated: Oct 3, 2025

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Uncertainty and source term reconstruction with environmental air samples
Ian Hoffman1, Alain Malo2, Kurt Ungar1
1Radiation Protection Bureau, Health Canada, 775 Brookfield Rd., Ottawa, ON, Canada.
Abstract:
Environmental air sampling is one of the principal monitoring technologies employed for the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). By combining the analysis of environmental samples with Atmospheric Transport and Dispersion Modelling (ATDM), and using a Bayesian source reconstruction algorithm, an estimate of the release location, duration, and quantity can be computed. Bayesian source reconstruction uses an uncertainty distribution of the input parameters, or priors, in a statistical framework to produce posterior probability estimates of the event parameters. The quality of the event reconstruction directly depends on the accuracy of the prior uncertainty distribution. With many of the input parameters, the selection of the uncertainty distribution is not difficult. However, with environmental samples, there is one component of the uncertainty at the interface between sample measurements and the ATDM that has been overlooked. Typically, a much smaller volume or quantity of material is sampled from the much larger domain represented in the ATDM. By examining the response of a dense network of radionuclide detectors on the West Coast of Canada during the passage of the Fukushima debris plume, an initial estimate of this uncertainty was determined to be between 20% and 30% depending on sample integration time.
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