## 4 Results
For this reason, it can be affirmed that, on an overall level, it is with allergic rhinitis that there is a more significant interrelation between the types of pollen and the two allergic diseases, considering the variations in the different years of study that have been pointed out. On only three occasions does allergic conjunctivitis not lag in its representation in the calculated models, namely: in 2016, for _Cupressaceae_, this pathology exceeds allergic rhinitis in the proportion of six versus three; and in 2017, the interventions of both dependent variables are equal in number (three), also for _Cupressaceae_, and they are equal in number (six) for _Platanus_ (Table 2). As for the atmospheric pollutants, considering that only some are measured at all stations, they have a different probability of appearing in the models. The pollutants most frequently measured at the Air Quality stations are O\({}_{3}\), NO\({}_{2}\), and the particle PM\({}_{10}\); it \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Air Pollutant**} & \multirow{2}{*}{**Year 2014**} & \multirow{2}{*}{**Year 2015**} & \multirow{2}{*}{**Year 2016**} & \multirow{2}{*}{**Year 2017**} & \multicolumn{6}{c}{**Period**} \\  & & & & & & & & & & & & **2014–2017** \\ \hline \multirow{2}{*}{**O\({}_{3}\)**} & **C** & **R** & **T** & **C** & **R** & **T** & **C** & **R** & **T** & **C** & **R** & **T** \\ \hline \multirow{2}{*}{**NO\({}_{2}\)**} & **2** & **6** & **8** & **1** & **3** & **4** & **7** & **6** & **13** & **3** & **7** & **10** & **13** & **22** & **35** \\ \hline \multirow{2}{*}{**NO\({}_{2}\)**} & **1** & **3** & **4** & **1** & **5** & **6** & **4** & **4** & **8** & **6** & **3** & **9** & **12** & **15** & **27** \\ \hline \multirow{2}{*}{**PM\({}_{10}\)**} & **3** & **8** & **11** & **2** & **7** & **9** & **3** & **6** & **9** & **3** & **3** & **6** & **11** & **24** & **35** \\ \hline \multirow{2}{*}{**PM\({}_{2,5}\)**} & **1** & **-** & **1** & **1** & **3** & **4** & **1** & **1** & **2** & **-** & **1** & **1** & **3** & **5** & **8** \\ \hline \multirow{2}{*}{**CO\({}_{2}\)**} & **3** & **3** & **6** & **-** & **1** & **1** & **3** & **2** & **5** & **3** & **2** & **5** & **9** & **8** & **17** \\ \hline \multirow{2}{*}{**SO\({}_{2}\)**} & **2** & **5** & **7** & **-** & **3** & **3** & **3** & **4** & **7** & **4** & **4** & **8** & **9** & **16** & **25** \\ \hline \multirow{2}{*}{**Total C/R**} & **12** & **25** & **5** & **22** & **21** & **23** & & **19** & **20** & & **57** & **90** & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Quantification of the presence of the six air pollutant variables in the calculated models, statistically significant (with adjusted R\({}^{2}>\) 30%) for the allergic diseases allergic conjunctivitis (C) and allergic rhinitis (R), for each of the four years of study. The total number of times (T) that each type of pollen appears in all the equations found for the two pathologies is also counted for each year. The right-hand side of the table shows the summed quantities for each dependent variable and the study period. The right column, shaded in blue, shows the total sum for each air pollutant and the two dependent variables. Finally, the bottom row shows the amounts of air pollutants that occur for each of the pathologies under study, both for the years and the whole period (Total C/R). would not be surprising if they were the most frequently related to the dependent variables. However, this is only the case in some years of study (Table 3). It can be observed that SO\({}_{2}\), with 7 appearances, is the third most present in 2014, after PM\({}_{10}\) (with 11) and O\({}_{3}\) (which appears on 8 occasions in the equations calculated); CO is the fourth most frequent, present in 6 equations and ahead of NO\({}_{2}\), with 4. In 2015, it is the particle PM\({}_{10}\) that is most frequently related to the dependent variables with the bold number 9, followed by NO\({}_{2}\) (6), O\({}_{3}\) (4), and PM\({}_{2.5}\) (4).