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Nowadays, 3D flow and dispersion models gain increasing interest for decision-making in case of hazardous releases into the atmosphere. Such models benefit from the integration of parallel algorithms and availability of parallel computing resources. They are particularly relevant for highly resolved giant urban domains as demonstrated in the EMERGENCIES project over the “Great Paris” area. A new project, called SURE, has been launched in 2021 as a follow-up of EMERGENCIES to investigate the effect of uncertain meteorological and source location input data on the flow and dispersion results. To do this, 21 meteorological members and 27 possible source positions were considered and the fields of concentration variances were assessed over time. A first outlook of the analysis is given in this paper highlighting the high variability of the ensemble results and therefore the need to estimate uncertainties to ensure the safety of the rescue teams and the population.

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Accounting for Uncertainties in High-Resolution 3D Dispersion Simulations of Hazardous Materials Over Huge Urban Domains

  • 会议论文

  • 发表日期：

    2025年

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  • Patrick Armand,
  • Christophe Duchenne,
  • Olivier Oldrini,
  • Sylvie Perdriel

摘要

Nowadays, 3D flow and dispersion models gain increasing interest for decision-making in case of hazardous releases into the atmosphere. Such models benefit from the integration of parallel algorithms and availability of parallel computing resources. They are particularly relevant for highly resolved giant urban domains as demonstrated in the EMERGENCIES project over the “Great Paris” area. A new project, called SURE, has been launched in 2021 as a follow-up of EMERGENCIES to investigate the effect of uncertain meteorological and source location input data on the flow and dispersion results. To do this, 21 meteorological members and 27 possible source positions were considered and the fields of concentration variances were assessed over time. A first outlook of the analysis is given in this paper highlighting the high variability of the ensemble results and therefore the need to estimate uncertainties to ensure the safety of the rescue teams and the population.