## 3 Results
### Scenario 1 versus Scenario 2
#### 3.2.3 Particle Matter (PM\({}_{2.5}\))  
Reference Case versus Scenario 1  
PM2.5 yearly mean concentrations for SC1 show, in general, a reduction over the western and central part of Europe, see Figure 6. The contribution of road transport to the total emissions of PM\({}_{2.5}\) is relatively low (\(\sim\)9.9% EU average [38]) and do not show large reductions in cities or highways. The largest reductions occurred in the Po Valley (up to 2.2 \(\mathrm{\SIUnitSymbolMicro m}\)\({}^{3}\), or \(\sim\)12%, Figure S6 ES), where traffic contributes significantly to the total PM emissions [39]. During the warm period, the relative reductions in PM concentrations were higher in the Po Valley (up to 11%) than during the cold period (up to 4%), although absolute reductions were of the same magnitude (\(\sim\)2 \(\mathrm{\SIUnitSymbolMicro m}\)\({}^{3}\)), which can be explained by the absence of other emission sources such as domestic heating (prevalent during winter time), and hence the relative larger weight of vehicle emissions during the warm period. Figure 6: Calculated yearly mean differences in PM\({}_{2.5}\) concentrations (\(\mathrm{\SIUnitSymbolMicro m}\)\({}^{3}\)) between Reference Case and Scenario 1 (**a**), together with the differences for three main periods, i.e., (**b**) cold/winter period (November to February), (**c**) warm/summer period (May to September), and (**d**) mild/transition period (March, April, and October). Poland, Czechia, and Hungary have around 30% of diesel vehicles, pre-Euro 5 light-duty vehicles, in their fleets (i.e., without a particle filter). Replacing old diesel vehicles by Euro 6 ones with a filter (that reduce tailpipe emissions by up to two orders of magnitude [40; 41]) result in a reduction in PM emissions as observed in Figure 1, and lower PM\({}_{2.5}\) concentrations as shown in Figure 6. However, the large reduction in PM\({}_{2.5}\) emissions is not fully reflected in the reduction of PM\({}_{2.5}\) concentrations. A possible explanation could be that other emission sources are weakening the effect of the filters in diesel cars in these countries [42]. During the cold period, the largest reductions in PM\({}_{2.5}\) concentrations were found over the Po Valley, and were up to 2.9 \(\upmu\)g/m\({}^{3}\). Looking at individual days, we found a reduction of up to 9 \(\upmu\)g/m\({}^{3}\) for the city of Milan on 27 October (daily average PM\({}_{2.5}\) on 27 October is 100.8 \(\upmu\)g/m\({}^{3}\) by the Reference Case). Even though the NH\({}_{3}\) emitted by vehicles is lower than NH\({}_{3}\) emitted from agricultural sources, the NH\({}_{3}\) emitted by cars in urban areas, close to NOx and SO\({}_{2}\) sources, is likely to increase the PM\({}_{2.5}\) concentration considerably, because of non-linearities in the chemical regimes that lead to the formation of secondary inorganic aerosols [34; 43]. Therefore, it is important to reduce also aerosol precursors which are emitted by the road transport sector. Our simulations showed that reducing PM\({}_{2.5}\), NOx, NMVOC, and NH\({}_{3}\) emissions in urban areas (Figure 7) contribute to a reduction in PM\({}_{2.5}\) concentrations of up to \(\sim\)2.9 \(\upmu\)g/m\({}^{3}\) in the Po Valley during the cold period, as mentioned earlier. However, the complexity of secondary inorganic PM\({}_{2.5}\) formation is high, as described in [34; 43]. It is, for that reason, key to identify the main precursors on which to act and to which extent when air quality plans are designed. For example, a study by [43] showed that in the Po Valley, the formation of secondary PM\({}_{2.5}\) is characterised by contrasting chemical regimes within distances of a few hundreds of kilometres, as well as non-linear responses to emission reductions during wintertime. They also showed that for some areas in the Po Valley, a small increase in PM\({}_{2.5}\) values were found when NOx emission reductions were applied in NOx-rich areas.