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Volume 12, issue 4
Atmos. Chem. Phys., 12, 2037-2054, 2012
https://doi.org/10.5194/acp-12-2037-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 12, 2037-2054, 2012
https://doi.org/10.5194/acp-12-2037-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 21 Feb 2012

Research article | 21 Feb 2012

Modelling future changes in surface ozone: a parameterized approach

O. Wild1, A. M. Fiore2, D. T. Shindell3, R. M. Doherty4, W. J. Collins5, F. J. Dentener6, M. G. Schultz7, S. Gong8, I. A. MacKenzie4, G. Zeng9, P. Hess10, B. N. Duncan11, D. J. Bergmann12, S. Szopa13, J. E. Jonson14, T. J. Keating15, and A. Zuber16 O. Wild et al.
  • 1Lancaster Environment Centre, Lancaster University, Lancaster, UK
  • 2NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
  • 3NASA Goddard Institute for Space Studies and Columbia University, New York, NY, USA
  • 4School of GeoSciences, University of Edinburgh, UK
  • 5Met Office Hadley Centre, Exeter, UK
  • 6European Commission, Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy
  • 7IEK-8, Forschungszentrum-Jülich, Germany
  • 8Science and Technology Branch, Environment Canada, Toronto, ON, Canada
  • 9National Institute of Water and Atmospheric Research, Lauder, New Zealand
  • 10Department of Biological and Environmental Engineering, Cornell University, Ithaca, New York, USA
  • 11NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 12Atmospheric Earth and Energy Division, Lawrence Livermore National Laboratory, CA, USA
  • 13Laboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, France
  • 14Norwegian Meteorological Institute, Oslo, Norway
  • 15Office of Policy Analysis and Review, Environmental Protection Agency, Washington D.C., USA
  • 16European Commission, Directorate General Environment, Brussels, Belgium

Abstract. This study describes a simple parameterization to estimate regionally averaged changes in surface ozone due to past or future changes in anthropogenic precursor emissions based on results from 14 global chemistry transport models. The method successfully reproduces the results of full simulations with these models. For a given emission scenario it provides the ensemble mean surface ozone change, a regional source attribution for each change, and an estimate of the associated uncertainty as represented by the variation between models. Using the Representative Concentration Pathway (RCP) emission scenarios as an example, we show how regional surface ozone is likely to respond to emission changes by 2050 and how changes in precursor emissions and atmospheric methane contribute to this. Surface ozone changes are substantially smaller than expected with the SRES A1B, A2 and B2 scenarios, with annual global mean reductions of as much as 2 ppb by 2050 vs. increases of 4–6 ppb under SRES, and this reflects the assumptions of more stringent precursor emission controls under the RCP scenarios. We find an average difference of around 5 ppb between the outlying RCP 2.6 and RCP 8.5 scenarios, about 75% of which can be attributed to differences in methane abundance. The study reveals the increasing importance of limiting atmospheric methane growth as emissions of other precursors are controlled, but highlights differences in modelled ozone responses to methane changes of as much as a factor of two, indicating that this remains a major uncertainty in current models.

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