This aim of this paper is to show that this is indeed one way to go with atmospheric transport chemistry models (ATCMs) by presenting results of data assimilation simulations of ozone with the model LOTOS. The assimilation technique used in this study is the Ensemble Kalman Filter. A simulation for a period of 4 weeks has been performed in which ground-level ozone measurements have been assimilated. The necessary noise input consisted of uncertainties in the emissions of NOx, SOx, VOC and CO in 17 groups of countries. The main conclusion is that it is possible to improve ATCM simulations of ozone by data assimilation, but t