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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 3, issue 2
Geosci. Model Dev., 3, 487-499, 2010
https://doi.org/10.5194/gmd-3-487-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 3, 487-499, 2010
https://doi.org/10.5194/gmd-3-487-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  12 Oct 2010

12 Oct 2010

On the attribution of contributions of atmospheric trace gases to emissions in atmospheric model applications

V. Grewe1, E. Tsati1, and P. Hoor2 V. Grewe et al.
  • 1Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 2Institut für Physik der Atmosphäre, Universität Mainz, Mainz, Germany

Abstract. We present an improved tagging method, which describes the combined effect of emissions of various species from individual emission categories, e.g. the impact of both, nitrogen oxides and non-methane hydrocarbon emissions on ozone. This method is applied to two simplified chemistry schemes, which represent the main characteristics of atmospheric ozone chemistry. Analytical solutions are presented for this tagging approach. In the past, besides tagging approaches, sensitivity methods were used, which estimate the contributions from individual sources based on differences in two simulations, a base case and a simulation with a perturbation in the respective emission category. We apply both methods to our simplified chemical systems and demonstrate that potentially large errors (factor of 2) occur with the sensitivity method, which depend on the degree of linearity of the chemical system. This error depends on two factors, the ability to linearise the chemical system around a base case, and second the completeness of the contributions, which means that all contributions should principally add up to 100%. For some chemical regimes the first error can be minimised by employing only small perturbations of the respective emission, e.g. 5%. The second factor depends on the chemical regime and cannot be minimized by a specific experimental set-up. It is inherent to the sensitivity method. Since a complete tagging algorithm for global chemistry models is difficult to achieve, we present two error metrics, which can be applied for sensitivity methods in order to estimate the potential error of this approach for a specific application.

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