Uncertainty quantification in long-range Lagrangian atmospheric transport and dispersion modelling

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    Abstract

    Atmospheric transport and dispersion models are an important tool for the verification of the Comprehensive Nuclear-Test-Ban Treaty. This Treaty bans nuclear explosions worldwide and by everyone. Part of the verification regime of the Comprehensive Nuclear-Test-Ban Treaty consists of a global network of ground stations that monitor airborne radioactive particles which can be the signature of a nuclear explosion. If such radioactive particles are detected, atmospheric transport and dispersion models can be used to help locate the origin of the radioactive
    particles by calculating trajectories backward in time.
    Atmospheric transport and dispersion models are furthermore used to help assess the impact of routine and accidental releases of radioactive particles into the atmosphere by civilian nuclear facilities. For routine releases, atmospheric transport models allow to estimate their impact on monitoring stations of the radionuclide verification system. For accidental releases, atmospheric transport models can estimate the source parameters (such as the release location and the release profile) using a set of measured radionuclide concentrations in the air.
    This dissertation deals with long-range atmospheric transport and dispersion
    modelling, which covers spatial scales of a few hundred kilometres up to the planetary scale, and how it can contribute to the radionuclide verification part of the Comprehensive Nuclear-Test-Ban Treaty. The findings presented here are also relevant for nuclear emergency management, and could be applied to other fields of research where use is made of atmospheric transport and dispersion models.
    Original languageEnglish
    QualificationDoctor of Science
    Awarding Institution
    • Universiteit Gent
    Supervisors/Advisors
    • Camps, Johan, SCK CEN Mentor
    • Termonia, Piet, Supervisor, External person
    • Delcloo, Andy, Supervisor, External person
    Date of Award8 Nov 2018
    Publisher
    StatePublished - 8 Nov 2018

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