## 6 Conclusions
As far as we know, this is the first time this method has been applied to estimate the volatility of the number of flights, taking into account that the number must be an integer or zero and that volatility can vary with certain factors such as the time and day of the week. The results shown here should enable airspace to be managed in a safer, economically optimal fashion. The method proposed can also be applied in three other ways:  
1. By combining different methods to estimate expected flights and using the methodology presented here to estimate volatility and risk measures. 2. By using a higher level of disaggregation in time periods such as months combined with minutes, hours and days of the week. 3. By linking volatility and risk with welfare, employment and CO2 emissions. Availability of data and the possibility of making those data public are thus the only limiting factors in undertaking a much more in-depth, detailed analysis. Conceptualisation, I.G., L.M.A., T.S., I.R.d.G. and N.G. ; methodology, I.G. and L.M.A. ; software, L.M.A. ; validation, I.G. and T.S. ; formal analysis, L.M.A., I.R.d.G. and N.G. ; investigation, I.G., L.M.A. and T.S. ; resources, T.S. ; data curation, I.G., L.M.A. and I.R.d.G. ; writing--original draft preparation, I.G., L.M.A. and N.G. ; writing--review and editing, T.S. and N.G. ; visualisation, L.M.A., T.S. and I.R.d.G. ; supervision, I.G. and T.S. ; funding acquisition, I.G. and N.G. All authors have read and agreed to the published version of the manuscript. This research is supported by Maria de Maeztu Excellence Unit 2020-2027 Ref. CEX2021-001201-M, funded by MCIN/AEI/10.13039/501100011033. Further support is provided by the Spanish Ministry of Science, Innovation and Universities (MINECO) (Grant RTI-2018-093352-B-100). [PERSON] and [PERSON] are grateful for financial support from Research Group B at the University of the Basque Country (Ref. IT1777-22). Not applicable. The data presented in this study are available on request from the corresponding author. The data are not publicly available due to restrictions from the data owner. \begin{table}
\begin{tabular}{r c c c c c} \hline
**Hour** & **Alpha Value** & **Standard Deviation** & **z** & _p-Value_ & \\ \hline
9 & 0.004061 & 0.001554 & 2.6130 & 0.0090 & *** \\
10 & 0.002289 & 0.001170 & 1.9570 & 0.0504 & * \\
11 & 0.002441 & 0.001143 & 2.1350 & 0.0328 & ** \\
12 & 0.002760 & 0.000892 & 3.0950 & 0.0020 & *** \\
13 & 0.001910 & 0.00652 & 2.9280 & 0.0034 & *** \\
14 & 0.002354 & 0.000469 & 5.0200 & 0.0000 & *** \\
15 & 0.001920 & 0.000297 & 6.4700 & 0.0000 & *** \\
16 & 0.003658 & 0.000192 & 19.0700 & 0.0000 & *** \\ \hline \end{tabular} Note: Asterisks denote significance as follows: *** 0.1\% level; * 1\%.  
\end{table} 
Table 2: Alpha values for Germany. \begin{table}
\begin{tabular}{r c c c c c} \hline
**Hour** & **Alpha Value** & **Standard Deviation** & **z** & _p-Value_ & \\ \hline
9 & 0.004175 & 0.001376 & 3.0340 & 0.0024 & *** \\
10 & 0.003457 & 0.001239 & 2.7900 & 0.0053 & *** \\
11 & 0.003336 & 0.001194 & 2.7940 & 0.0052 & *** \\
12 & 0.004130 & 0.001079 & 3.8270 & 0.0001 & *** \\
13 & 0.002843 & 0.000652 & 4.3590 & 0.0000 & *** \\
14 & 0.004047 & 0.000541 & 7.4740 & 0.0000 & *** \\
15 & 0.003186 & 0.000345 & 9.2320 & 0.0000 & *** \\
16 & 0.002619 & 0.000324 & 8.0830 & 0.0000 & *** \\ \hline \end{tabular} Note: Asterisks denote significance as follows: *** 0.1\% level.  
\end{table} 
Table 3: Alpha values for the Netherlands.