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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 6, issue 1 | Copyright
Atmos. Chem. Phys., 6, 51-66, 2006
https://doi.org/10.5194/acp-6-51-2006
© Author(s) 2006. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.

  11 Jan 2006

11 Jan 2006

Can we explain the trends in European ozone levels?

J. E. Jonson1, D. Simpson1, H. Fagerli1, and S. Solberg2 J. E. Jonson et al.
  • 1Norwegian Meteorological Institute, Oslo, Norway
  • 2NILU, Kjeller, Norway

Abstract. Ozone levels in Europe are changing. Emissions of ozone precursors from Europe (NOx, CO and non-methane hydrocarbons) have been substantially reduced over the last 10–15 years, but changes in ozone levels cannot be explained by changes in European emissions alone. The observed ozone trends at many European sites are only partially reproduced by global or regional photochemistry models, and possible reasons for this are discussed.

In order to further explain the European trends in ozone since 1990, the EMEP regional photochemistry model has been run for the years 1990 and 1995–2002. The EMEP model is a regional model centred over Europe but the model domain also includes most of the North Atlantic and the polar region. Climatological ozone data are used as initial and lateral boundary concentrations. Model results are compared to measurements over this timespan of 12 years. Possible causes for the measured trends in European surface ozone have been investigated using model sensitivity runs perturbing emissions and lateral boundary concentrations. The increase in winter ozone partially, and the decrease in the magnitude of high ozone episodes, is attributed to the decrease in ozone precursor emissions since 1990 by the model. Furthermore, the model calculations indicate that the emission reductions have resulted in a marked decrease in summer ozone in major parts of Europe, in particular in Germany. Such a trend in summer ozone is likely to be difficult to identify from the measurements alone because of large inter-annual variability.

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