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Estimates of uncertainty in urban air quality model predictions

Abstract : A practical methodology for quantifying uncertainties in air quality model predictions was developed and tested on experimental data obtained in two street canyons in Paris. This method was based on the use of three different models, independent meteorological data sets and different emission factors, for creating ensemble sets of street canyon simulations. That enabled us to calculate best estimates of CO and benzene concentrations, and related error bounds. It was not the intention of the authors to simulate all possible sources of uncertainty in urban dispersion modelling. Uncertainties due to stochastic atmospheric processes or due to errors in some of the input parameters (e.g. dimensions of the street, traffic volumes, etc.) were not here taken into consideration. However, it is believed that the above presented methodology strikes a reasonable balance between simplicity and reliability on urban dispersion models.
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Submitted on : Wednesday, April 2, 2014 - 3:31:54 PM
Last modification on : Wednesday, February 13, 2019 - 9:36:03 AM


  • HAL Id : ineris-00969780, version 1
  • INERIS : PU-2001-072



Sotiris Vardoulakis, Bernard E.A. Fisher, Norbert Gonzalez-Flesca. Estimates of uncertainty in urban air quality model predictions. 25. NATO/CCMS International Technical Meeting on Air Pollution Modelling and its Application, Oct 2001, Louvain-la-Neuve, Belgium. ⟨ineris-00969780⟩



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