## 3 Results and Discussion
The estimated parameter values for the distributions depicted in Figures 4 and 5 are listed in Tables 3 and 4, respectively. However, it should be kept in mind that the great concentration of \(\Lambda\) values in the aforementioned narrow range make it difficult to find a good approximating distribution, as may be verified from Figure 5.  
Figure 4: Plots of the distributions of the E-field values. The bar diagrams represent the measured data, whereas the curves are the corresponding approximating distributions of their values. (**a**) Urban and (**b**) suburban environment. Figure 5: Same as Figure 4, but the distributions refer to the total exposure ratio \(\Lambda\). (**a**) Urban and (**b**) suburban environment. Subsequently, a worst-case scenario is examined, i.e., only the highest measured value is taken into account among all measurements in the vicinity of each school. Thus, a total of 69 audits (as many as the schools) constitute the aforementioned scenario; 29 audits were conducted in urban areas and the remaining 40 in the suburbs. The results are summarized in Figure 1:0 It is evident that the mean values of the exposure ratio are slightly higher compared with the ones given in Figure 1:1 This is an expected outcome as the results of Table 5 include only the maximum values acquired around each school. However, even in this worst-case scenario, the mean exposure ratio is well below 1 for all cases examined. The last column of Table 5 comprises the p-value obtained from Mood's Median tests (95% confidence level) in order to investigate the statistically significant differences in median values of \(\lambda_{f}^{j}\) between urban and suburban environments. The result \(p\) > 0.05, for all frequency bands, indicates that the two environments are found as not statistically different. This outcome may be attributed to the fact that, regarding the worst case, i.e., the highest possible values of the E-field around each school, the two environment types do not differ significantly, as expected. \begin{table}
\begin{tabular}{c c c c} \hline
**Environment** & **Distribution** & **Parameter** & **Estimated Value** \\ \hline \multirow{6}{*}{Urban} & \multirow{2}{*}{Lognormal} & \(\mu\) (mean) & \(-2.91\) \\  & & \(\sigma\) (standard deviation) & \(0.85\) \\ \cline{2-4}  & & \(\alpha\) (shape alpha) & \(1.07\) \\  & & \(\theta\) (scale thita) & \(0.09\) (deg) \\ \cline{2-4}  & & \(\alpha\) (scale alpha) & \(0.09\) \\  & & \(\beta\) (shape beta) & \(0.91\) \\ \cline{2-4}  & & \(\mu\) (mean) & \(0.09\) \\  & & \(\sigma\) (standard deviation) & \(0.17\) \\ \hline \multirow{6}{*}{Suburban} & \multirow{2}{*}{Lognormal} & \(\mu\) (mean) & \(-3.13\) \\  & & \(\sigma\) (standard deviation) & \(0.65\) \\ \cline{1-1} \cline{2-4}  & & \(\alpha\) (shape alpha) & \(1.35\) \\ \cline{1-1}  & & \(\theta\) (scale thita) & \(0.05\) (deg) \\ \cline{1-1} \cline{2-4}  & & \(\mu\) (mean) & \(0.07\) \\ \cline{1-1}  & & \(\sigma\) (standard deviation) & \(0.15\) \\ \hline \end{tabular}
\end{table} 
Table 4: Estimated parameters for the distributions that approximate the values of the total exposure ratio \(\Lambda\) in urban and suburban environments.