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AGU: Journal of Geophysical Research, Atmospheres

 

Keywords

  • inverse modeling
  • emissions
  • chemistry-transport model

Index Terms

  • Atmospheric Processes: Data assimilation
  • Atmospheric Composition and Structure: Troposphere: constituent transport and chemistry
  • Atmospheric Composition and Structure: Troposphere: composition and chemistry
Abstract
Cited By (5)
 

Abstract

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 110, D24310, 18 PP., 2005
doi:10.1029/2005JD006151

Inverse modeling of NOx emissions at regional scale over northern France: Preliminary investigation of the second-order sensitivity

Denis Quélo

Centre d'Enseignement et de Recherche en Environnement Atmosphérique, École Nationale des Ponts et Chaussées–Électricité de France Recherche et Développement, Champs-sur-Marne, France

CLIME, Institut National de Recherche en Informatique et en Automatique–École Nationale des Ponts et Chaussées, Champs-sur-Marne, France

Vivien Mallet

Centre d'Enseignement et de Recherche en Environnement Atmosphérique, École Nationale des Ponts et Chaussées–Électricité de France Recherche et Développement, Champs-sur-Marne, France

CLIME, Institut National de Recherche en Informatique et en Automatique–École Nationale des Ponts et Chaussées, Champs-sur-Marne, France

Bruno Sportisse

Centre d'Enseignement et de Recherche en Environnement Atmosphérique, École Nationale des Ponts et Chaussées–Électricité de France Recherche et Développement, Champs-sur-Marne, France

CLIME, Institut National de Recherche en Informatique et en Automatique–École Nationale des Ponts et Chaussées, Champs-sur-Marne, France

The purpose of this article is to perform the inverse modeling of emissions at regional scale for photochemical applications. The case study is the region of Lille in northern France for simulations in May 1998. The chemistry-transport model, Polair3D, has been validated with 1 year of model-to-observation comparisons over Lille. Polair3D has an adjoint mode, which enables inverse modeling with a variational approach. A sensitivity analysis has been performed so as to select the emission parameters to be modified in order to improve ozone forecasts. It has been shown that inverse modeling of the time distribution of nitrogen oxide emissions leads to satisfactory improvements even after the learning period. A key issue is the robustness of the inverted emissions with respect to uncertain parameters. A brute force second-order sensitivity analysis of the optimized emissions has been performed with respect to other parameters and has proven that the optimized time distribution of NO x emissions is robust.

Received 29 April 2005; accepted 6 September 2005; published 29 December 2005.

Citation: Quélo, D., V. Mallet, and B. Sportisse (2005), Inverse modeling of NOx emissions at regional scale over northern France: Preliminary investigation of the second-order sensitivity, J. Geophys. Res., 110, D24310, doi:10.1029/2005JD006151.

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