Atmospheric Chemistry and Physics (Nov 2017)

Reanalysis of and attribution to near-surface ozone concentrations in Sweden during 1990–2013

  • C. Andersson,
  • H. Alpfjord,
  • L. Robertson,
  • P. E. Karlsson,
  • M. Engardt

DOI
https://doi.org/10.5194/acp-17-13869-2017
Journal volume & issue
Vol. 17
pp. 13869 – 13890

Abstract

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We have constructed two data sets of hourly resolution reanalyzed near-surface ozone (O3) concentrations for the period 1990–2013 for Sweden. Long-term simulations from a chemistry-transport model (CTM) covering Europe were combined with hourly ozone concentration observations at Swedish and Norwegian background measurement sites using retrospective variational data analysis. The reanalysis data sets show improved performance over the original CTM when compared to independent observations. In one of the reanalyses, we included all available hourly near-surface O3 observations, whilst in the other we carefully selected time-consistent observations. Based on the second reanalysis we investigated statistical aspects of the distribution of the near-surface O3 concentrations, focusing on the linear trend over the 24-year period. We show that high near-surface O3 concentrations are decreasing and low O3 concentrations are increasing, which is reflected in observed improvement of many health and vegetation indices (apart from those with a low threshold). Using the CTM we also conducted sensitivity simulations to quantify the causes of the observed change, focusing on three factors: change in hemispheric background concentrations, meteorology and anthropogenic emissions. The rising low concentrations of near-surface O3 in Sweden are caused by a combination of all three factors, whilst the decrease in the highest O3 concentrations is caused by European O3 precursor emissions reductions. While studying the impact of anthropogenic emissions changes, we identified systematic differences in the modeled trend compared to observations that must be caused by incorrect trends in the utilized emissions inventory or by too high sensitivity of our model to emissions changes.