## 3 Results and Discussion  
Although microalgae growth is affected by several physicochemical parameters, such as temperature, light, pH, salinity, nutrients, and others, the results and discussion presented in this paper are limited to the input of solar energy and temperature. The five weeks with the lowest WS values were selected for each WWTP. The selected TMW has a notable persistence and a low difference in \(\Delta\text{Nsol}_{\text{q}}^{\text{w}}\). The persistence of a week corresponds to the number of times it appears in the selection for different weighting factors and lag. By broadening the final choice criteria with more weighting factors and lags, a sequence of new candidate weeks emerges that might be different from their predecessors. In some cases, the same weeks are repeated but in a different order. Finally, the selected TMW is supposed to present the long-term characteristic properties of the meteorological data. The same process is adopted for each of the four meteorological seasons for each of the 18 WWPTs. To facilitate the presentation of the results, only the details of the long-term and weekly statistics are presented in the following tables. The rest of the results are given in Appendix A. Table 2 shows the seasonal quarterly statistics for the Colmenarejo Este location during the period 1991 to 2005. It includes the mean and median of each of the six parameters for the different seasons, as well as the standard deviation, which provides information about the average dispersion of each of these. A standard deviation between 2.48 and 6.10 is observed for the temperature parameters. The PAR has a high standard deviation with values distributed over a range between 16.35 and 28.99, while the Nsol is about one for spring and autumn and less than one for summer and winter. The daily or seasonal variability of these growth parameters significantly affects the production of microalgae. Taking into account seasonal variations, it can be shown that winter has unfavorable meteorological conditions with less light, very low temperatures, and an inadequate photoperiod for microalgae growth. Summer offers the appropriate ranges of values to maximize productivity, while spring and autumn are unfavorable for microalgae metabolism. Extreme variations in these parameters can be observed throughout the year and can have inhibiting effects on microalgae. Due to the large number of weeks to evaluate nine wf options (Table 1), the WS of the FS statistics for the different parameters are not presented in tabular form in this article. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**Parameters** & **wf\_1** & **wf\_2** & **wf\_3** & **wf\_4** & **wf\_5** & **wf\_6** & **wf\_7** & **wf\_8** & **wf\_9** \\ \hline Tmx & 0.10 & 0.05 & 0.05 & 0.10 & 0.05 & 0.05 & 0.05 & 0.05 & 0.10 \\ Tmn & 0.10 & 0.05 & 0.05 & 0.10 & 0.05 & 0.05 & 0.05 & 0.05 & 0.10 \\ Tme & 0.30 & 0.40 & 0.30 & 0.25 & 0.25 & 0.45 & 0.40 & 0.40 & 0.20 \\ Trg & - & - & - & 0.05 & 0.05 & 0.05 & 0.05 & 0.05 & 0.10 \\ PAR & 0.30 & 0.20 & 0.30 & 0.25 & 0.30 & 0.20 & 0.30 & 0.15 & 0.20 \\ Nsol & 0.20 & 0.30 & 0.30 & 0.25 & 0.30 & 0.20 & 0.15 & 0.30 & 0.30 \\ \hline \end{tabular}
\end{table} 
Table 1: Weighting factor (wf) options to obtain the weighted sum. Table 3 shows the results obtained for the spring season in the Colmenarejo Este location: each cell shows the number of the candidate week corresponding to a set of weight factors (column) and a number of lags (rows). For each pair of 'weighting factors set and lag size', we present the five best candidates ordered from top to bottom according to the minimum WS value. In the case of Colmenarejo Este, the total number of weeks analyzed is 1204, so that--for example--week number 235 represents the sequence of seven days that begins on 2 May 1993. The TMW for each season and each of the 18 locations are given in Table 2. In this table, only the first day of the selected week is given.