Low modeled ozone production suggests underestimation of precursor emissions (especially NO x ) in Europe

High surface ozone concentrations, which usually occur when photochemical ozone production takes place, pose a great risk to human health and vegetation. Air quality models are often used by policy makers as tools for the development of ozone mitigation strategies. However, the modeled ozone production is often not or not enough evaluated in many ozone modeling studies. The focus of this work is to evaluate the modeled ozone production in Europe indirectly, with the use of the ozone–temperature correlation for the summer of 2010 and to analyze its sensitivity to precursor emissions and meteorology by using the regional air quality model, the Comprehensive Air Quality Model with Extensions (CAMx). The results show that the model significantly underestimates the observed high afternoon surface ozone mixing ratios (≥  60 ppb) by 10–20 ppb and overestimates the lower ones ( x ) emissions by a factor of 2, (iii) a combination of the first two scenarios and (iv) increased traffic-only NO x emissions by a factor of 4. For southern, eastern, and central (except the Benelux area) Europe, doubling NO x emissions seems to be the most efficient scenario to reduce the underestimation of the observed high ozone mixing ratios without significant degradation of the model performance for the lower ozone mixing ratios. The model performance for ozone–temperature correlation is also better when NO x emissions are doubled. In the Benelux area, however, the third scenario (where both NO x and VOC emissions are increased) leads to a better model performance. Although increasing only the traffic NO x emissions by a factor of 4 gave very similar results to the doubling of all NO x emissions, the first scenario is more consistent with the uncertainties reported by other studies than the latter, suggesting that high uncertainties in NO x emissions might originate mainly from the road-transport sector rather than from other sectors. The impact of meteorology was examined with three sensitivity tests: (i) increased surface temperature by 4 °C, (ii) reduced wind speed by 50 % and (iii) doubled wind speed. The first two scenarios led to a consistent increase in all surface ozone mixing ratios, thus improving the model performance for the high ozone values but significantly degrading it for the low ozone values, while the third scenario had exactly the opposite effects. Overall, the modeled ozone is predicted to be more sensitive to its precursor emissions (especially traffic NO x ) and therefore their uncertainties, which seem to be responsible for the model underestimation of the observed high ozone mixing ratios and ozone production.