## Materials and Methods
### Air Pollution Data  
The pollutants concentrations for O\({}_{3}\), NO\({}_{2}\), PM\({}_{10}\), NO, and CO were obtained through the Portuguese Environmental Agency Online Database on Air Quality (QualAr), an online tool that provides information on air quality indexes and pollutant concentrations statistics at each monitoring station, throughout continuous measurements based on 1 h averages with data registration every  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Municipality**} \\ \cline{2-5}  & **Amadora** & **Lisbon** & **Odivelas** \\ \hline
**Ageing index** & 148.8 & 187 & 123.2 \\
**Elderly dependency index** & 35.6 & 50 & 30.2 \\
**Percentage of senior population** & 22.3 & 28.3 & 19.5 \\
**Transition/completion rate in secondary education** & 76.1 & 81.5 & 75.1 \\
**Average monthly earnings (c)** & 1283.60 & 1548.90 & 894.00 \\
**Median sales value per m\({}^{2}\) of dwellings (c)** & 895 & 2065 & 1110 \\
**Purchasing power (Portugal = 100))** & 103.87 & 214.54 & 90.27 \\
**Proportion of socially most valued professionals** & 20.81 & 42.46 & 21.44 \\
**Proportion of employment in consulting, scientific, technical, and similar activities** & 5.26 & 10.41 & 5.19 \\
**Beneficiaries of social insertion income, per 1000 inhabitants of active age** & 30.4 & 45.22 & 22.23 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Population characteristics [101].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Vulnerability** & **Senior** & **Population** & **Socioeconomic** & **Traffic** & **Overall** \\
**Rank** & **Population** & **Density** & **Characteristics** & **Traffic** & **Overall** \\ \hline
1 & Lisbon & Amadora & Lisbon & Lisbon & Lisbon \\
2 & Amadora & Odivelas & Odivelas & Odivelas & Odivelas \\
3 & Odivelas & Lisbon & Amadora & Amadora & Amadora \\ \hline \hline \end{tabular}
\end{table}
Table 3: Vulnerability to air pollution synthesis [101; 103].  
15 min (information for the period from 1 January 2005 to 31 December 2015). This data refers to nine air pollution measuring stations within an urban environment located in the three selected municipalities (Table 4).  
In the cases of Amadora (3 stations) and Lisbon (5 stations), the municipality data was obtained through the construction of a daily municipal average for each of the pollutants. This implied that at least one station had information for the pollutant in a given day. In Amadora, one station had no O\({}_{3}\) information, whilst in Lisbon there were two stations out of five with considerable missing data for O\({}_{3}\), PM\({}_{10}\), and CO (Table 5 presents information about data completion in all measuring stations). This was surpassed with the daily means construction, giving a daily data availability of information of over 90% (generally over 94%) in all AP for Amadora and over 99.7% in Lisbon. However, the case of Odivelas was substantially different, because in this municipality only one station was present, here the daily data availability was of almost 84.5% (except for O\({}_{3}\)--63.5%--and CO--76.4%).  
Due to the existence of some missing data, mainly in Odivelas municipality, and our overall modeling strategy, we opted to use the Expectation-Maximization algorithm--in SPSS (Statistical Package for the Social Sciences)--to impute the missing values. This method has one of the best yields when the matter is AP data [104; 105].