## 3 Results and Discussion
### Spatial Dependence of Pollutant Concentrations  
The cross-correlation represents the similitude of two signals depending on a time translation of one of them. In the present study, it was used to evaluate the results from different stations. Cross-correlation of zero represents no dependence of the pollutant concentration for different monitoring stations, the value of +1 represents the same trend and the value of \(-1\) represents an opposite trend. It is possible to consider values greater than 0.4 as representative of a good similarity of two monitoring stations or areas for a specific pollutant. The aim of the cross-correlation analysis is to understand if pollutant monitoring stations in different areas show similar results. It is useful to consider the mean values of contaminants of each station of Roma Green Band, in order to represent the average pollutant concentrations of Rome. Tables 4-12 show the cross-correlation results for each pollutant concentration between the mean values of the Roma Green Band and suburbs or province monitoring stations. In the tables, the values are referred to four periods of the year. \"From July to August\" is the summer period in which there is low urban traffic due to the summer holidays. \"From April to June\" and \"from September to November\" are periods with only urban traffic. \"From November to April\" is the winter period and it is influenced both by urban traffic and building heating systems. In order to summarize the results of Tables 4-13 are shown the average, maximum, and minimum cross-correlation values. Considering all the pollutant concentrations, the average value ranges from 0.18 for [SO2] to 0.88 for [PM10]. Despite the value of [SO2] the average cross-correlation is always higher than 0.4 indicating that the pollutant concentration of Roma Green Band area with the suburbs or province ones have the same trend. This affirmation is more relevant considering [PM10] and [PM2.5] in which the cross-correlation values reach the higher values ranging from 0.57 to 0.96 and from 0.72 to 0.97 respectively. Considering the seasons, it is possible to notice that the cross-correlation \begin{table}
\begin{tabular}{c c c c c c} \hline  & **Monitoring** & **From July to** & **From April** & **From September** & **From November** \\  & **Station** & **August** & **to June** & **to November** & **to April** \\ \hline
**Suburbs** & Malagrotta & 0.15 & 0.22 & 0.39 & 0.69 \\  & Ciampino & 0.54 & 0.56 & 0.53 & 0.65 \\ \hline  & Latina & 0.32 & 0.18 & 0.39 & 0.64 \\
**Provinces** & Frosinone & 0.20 & 0.36 & 0.47 & 0.56 \\  & Rieti & 0.13 & 0.22 & 0.46 & 0.41 \\  & Viterbo & 0.50 & 0.47 & 0.52 & 0.66 \\ \hline \end{tabular}
\end{table} 
Table 4: Cross-correlation values between Roma Green Band and suburbs or province stations of [C6H6] in 2015. \begin{table}
\begin{tabular}{c c c c c c} \hline  & **Monitoring** & **From July to** & **From April** & **From September** & **From November** \\  & **Station** & **August** & **to June** & **to November** & **to April** \\ \hline  & Latina & 0.19 & 0.08 & 0.48 & 0.59 \\  & Frosinone & 0.47 & 0.48 & 0.72 & 0.67 \\
**Provinces** & Rieti & 0.19 & 0.43 & 0.57 & 0.46 \\  & Viterbo & 0.24 & 0.47 & 0.57 & 0.53 \\  & Civitavecchia & 0.30 & 0.46 & 0.51 & 0.53 \\ \hline \end{tabular}
\end{table} 
Table 5: Cross-correlation values between Roma Green Band and suburbs or province stations of [C0] in 2015.  
values increase in the winter because of the higher use of heating systems that seems to be the main pollutant source in this period. Regarding Sulphur dioxide, the cross-correlation reaches the minimum average value with a range from \(-0.24\) to \(0.50\). in this case, the pollutant concentrations of the Roma Green Band area don't have the same trend as the other locations. This is because there is a very low concentration magnitude of [SO\({}_{2}\)], and it behaves as background noise.