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 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.
Citation: Wild, O., Fiore, A. M., Shindell, D. T., Doherty, R. M., Collins, W. J., Dentener, F. J., Schultz, M. G., Gong, S., MacKenzie, I. A., Zeng, G., Hess, P., Duncan, B. N., Bergmann, D. J., Szopa, S., Jonson, J. E., Keating, T. J., and Zuber, A.: Modelling future changes in surface ozone: a parameterized approach, Atmos. Chem. Phys., 12, 2037-2054, doi:10.5194/acp-12-2037-2012, 2012.