## 3 Results and Discussion
### Modelling Results
#### 3.5.2 Ship Emissions Impact  
The ship emissions impact on NO\({}_{\rm X}\), O\({}_{3}\), PM\({}_{2.5}\), and PM\({}_{10}\) has been evaluated using both BOLCHEM and ADMS-Urban. The impact was calculated as (C\({}_{\it{with\_ships}}-C_{\it{mo\_ships}}\))/C\({}_{\it{with\_ships}}\), with \(C\) the average concentration over the simulation period, C\({}_{\it{with\_ships}}\) the concentration calculated with the inclusion of ship emissions, \(C_{\it{no\_ships}}\) that calculated without ship emissions (which is the concentration employed as background in ADMS-Urban simulations). Figure 6 shows the relative impact on NO\({}_{\rm X}\), O\({}_{3}\), PM\({}_{2.5}\), and PM\({}_{10}\) ground concentration obtained from BOLCHEM, while Figure 7 shows the relative impact obtained from ADMS-Urban at 2 m. As regards gas species, both figures show that, due to ship emissions, NO\({}_{\rm X}\) concentration increased in the port area, while O\({}_{3}\) decreased due to enhanced titration caused by NO\({}_{\rm X}\) emissions. Figure 5: Time series of BOLCHEM modelled (green dotted line) and observed (blue solid line) daily averaged concentrations (\(\rm{\upmu m^{-3}}\)) of (**a**) NO\({}_{\rm X}\), (**b**) O\({}_{3}\), (**c**) PM\({}_{2.5}\), and (**d**) PM\({}_{10}\), averaged over ARPA-Puglia and ASI monitoring stations. \begin{table}
\begin{tabular}{c c c c c c} \hline  & **Modelled** & **Measured** & **MB** & **RMSE** & **R** \\  & **(\(\rm{\upmu m^{-3}}\))** & **(\(\rm{\upmu m^{-3}}\))** & **(\(\rm{\upmu m^{-3}}\))** & **(\(\rm{\upmu m^{-3}}\))** & **R** \\ \hline NO\({}_{\rm X}\) & 25.61 & 24.68 & 0.93 & 11.17 & 0.68 \\ \hline O\({}_{3}\) & 83.54 & 79.71 & 3.83 & 16.19 & 0.78 \\ \hline PM\({}_{2.5}\) & 14.91 & 13.59 & 1.32 & 5.69 & 0.64 \\ \hline PM\({}_{10}\) & 21.53 & 20.85 & 0.68 & 5.97 & 0.61 \\ \hline \end{tabular}
\end{table} 
Table 5: BOLCHEM modelled and measured concentrations (\(\rm{\upmu m^{-3}}\)) averaged over ARPA-Puglia and ASI monitoring stations and over the whole period June–October 2012. Figure 6: _Cont._  
Table 6 summarizes the impact obtained from BOLCHEM in the port area. In the cell of the port, the estimated ship emissions contribution was 6.1% for PM\({}_{2.5}\) and 4.3% for PM\({}_{10}\). For PM\({}_{2.5}\) the contribution of the primary component was 2.7%. These results are comparable with results found by [PERSON] et al. (2011) (2.8% \(\pm\) 1.1%) and [PERSON] et al. (2012) (7.4% \(\pm\) 0.5%) for the same port at the ASI sampling site. The secondary contribution to PM\({}_{2.5}\) (3.4%) was lower of that estimated in [PERSON] et al. (2011), who found a contribution of secondary ammonium sulphate of about 11% of PM\({}_{2.5}\). This can be due to the different used approach ([PERSON] et al., 2012). We also recall the strong dependence of model results on model formulation ([PERSON] et al., 2012; [PERSON] et al., 2012) and applied inventory ([PERSON] et al., 2012), whose structure identifies the source in the CTMs model ([PERSON] et al., 2012). As for NO\({}_{\chi}\) and O\({}_{3}\) the impact on NO\({}_{\chi}\) concentration was 37.6%, with a corresponding decrease of 11.7% on O\({}_{3}\) concentration. ADMS-Urban, although the simplified chemical scheme, showed values consistent with BOLCHEM results. Further, it allowed to investigate the spatial distribution showing maximum located in the hotelling areas. We recall that the net formation of O\({}_{3}\) depends on the levels of NO\({}_{\chi}\) and NMVOC, as well as their ratio. In regions with high NO\({}_{\chi}\) concentrations, O\({}_{3}\) production is limited by the availability of NMVOC, while in areas limited by the availability of NOx, an increase in NOx emissions will lead to an increase of O\({}_{3}\) production ([PERSON] et al., 2012; [PERSON] et al., 2012).