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Skill and uncertainty of a regional air quality model ensemble

  • R. Vautard
  • , M. Schaap
  • , R. Bergström
  • , B. Bessagnet
  • , J. Brandt
  • , P. J.H. Builtjes
  • , J. H. Christensen
  • , C. Cuvelier
  • , V. Foltescu
  • , A. Graff
  • , A. Kerschbaumer
  • , M. Krol
  • , P. Roberts
  • , L. Rouïl
  • , R. Stern
  • , L. Tarrason
  • , P. Thunis
  • , E. Vignati
  • , P. Wind
  • Service d'Aéronomie
  • Netherlands Organisation for Applied Scientific Research (TNO)
  • Swedish Meteorological and Hydrological Institute
  • INERIS Institut National de l'Environnement Industriel et des Risques
  • Aarhus University
  • European Commission Joint Research Centre
  • UBA
  • Free University of Berlin
  • Institute for Marine and Atmospheric Research Utrecht
  • Shell Global
  • MSC-W

Research output: Contribution to journal › Article › peer-review

78 Citations (Scopus)

Abstract

Recently several regional air quality projects were carried out to support the negotiation under the Clean Air For Europe (CAFE) programme by predicting the impact of emission control policies with an ensemble of models. Within these projects, CITYDELTA and EURODELTA, the fate of air quality at the scale of European cities or that of the European continent was studied using several models. In this article we focus on the results of EURODELTA. The predictive skill of the ensemble of models is described for ozone, nitrogen dioxide and secondary inorganic compounds, and the uncertainty in air quality modelling is examined through the model ensemble spread of concentrations. For ozone daily maxima the ensemble spread origin differs from one region to another. In the neighbourhood of cities or in mountainous areas the spread of predicted values does not span the range of observed data, due to poorly resolved emissions or complex-terrain meteorology. By contrast in Atlantic and North Sea coastal areas the spread of predicted values is found to be larger than the observations. This is attributed to large differences in the boundary conditions used in the different models. For NO2 daily averages the ensemble spread is generally too small compared with observations. This is because models miss highest values occurring in stagnant meteorology in stable boundary layers near cities. For secondary particulate matter compounds the simulated concentration spread is more balanced, observations falling nearly equiprobably within the ensemble, and the spread originates both from meteorology and aerosol chemistry and thermodynamics.

Original languageEnglish
Pages (from-to)4822-4832
Number of pages11
JournalAtmospheric Environment
Volume43
Issue number31
DOIs
Publication statusPublished - 1 Jan 2009
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Air quality model
  • Ensemble modelling
  • Model evaluation
  • Uncertainty

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