ETC/ATNI Report 2019/14: Statistical modelling for long-term trends of pollutants. Use of a GAM model for the assessment of measurements of O3, NO2 and PM.

Previous studies under the European Topic Centre on Air pollution and Climate change Mitigation (ETC/ACM) on the link between trends and meteorology have shown that these links could be estimated by CTMs (chemical transport models). CTMs are useful tools for explaining pollutant trends in terms of the separate impact of individual physio-chemical drivers, such as emissions, and meteorology. It requires, however, multi-year calculations with CTMs designed in specific ways to allow the subtraction of various model scenarios. The method could also be sensitive to the years selected for calculating the perturbations in boundary conditions and meteorology and to uncertainties in emission data. The statistical GAM model that has been developed under ETC/ACM and European Topic Centre on Air pollution, noise, transport and industrial pollution (ETC/ATNI) provides a complementary method for separating the influence of meteorological variability from other processes. This model represents a completely different approach that is based only on observed links between local meteorological parameters (like temperature, wind, etc) and observed pollutant concentration levels. Thus, the model does not contain any representation of the real processes in the atmosphere. We found clear differences in model performance both with respect to geographical area and atmospheric species. In general, the best performance was found for O 3 (although not for the peak levels) with gradually lower performance for NO 2 , PM 10 and PM 2.5 in that order. With respect to area, the model generally produced the best predictions for Central Europe (Germany, Netherlands, Belgium, France, Austria, Czech Republic) and the poorest for (southern Europe). For wintertime NO 2 , particularly poor agreement between the GAM model and the measurements was found for the North Italian region. The model agreement for southern Europe and the Iberian Peninsula was also fairly low, although it is variable from site to site. The number of stations with measurements of ...