## 3 Results
### Spatial Distribution of PM\({}_{2.5}\)  
The spatial distribution of PM\({}_{2.5}\) is represented in Figure 3, where personal monitor measurements of PM\({}_{2.5}\) were used as the dependent variable. The map resulting from the LUR model shows four areas with different spatial distributions of PM\({}_{2.5}\). The first and largest one is represented by a diagonal running from the northwest to east, covering six boroughs: Azcapotzalco, Miguel Hidalgo, Cuauhtemoc, Benito Juarez, Iztacalco, and Iztapalapa. In this area, the median concentration of normalized PM\({}_{2.5}\) was 79.1 \(\upmu\)g/m\({}^{3}\) with an interquartile range between 67.1 to 89.9 \(\upmu\)g/m\({}^{3}\).  
Figure 2: Personal concentrations of PM\({}_{2.5}\) during the days and nights in Mexico City. The left side (**A**) of the figure represents the geometric mean of personal concentrations of PM\({}_{2.5}\) during the day, and the right side (**B**) of the figure represents the geometric mean of personal concentrations of PM\({}_{2.5}\) during the night.  
The second area is situated in the southwest part of the basin, in the boroughs of Tlalpan and Magdalena Contreras. Since the latter is a transition area between the two boroughs, the median concentration of normalized PM\({}_{2.5}\) was only approximately 78.2 \(\upmu\)g/m\({}^{3}\) with an interquartile range 67.8 to 104.1 \(\upmu\)g/m\({}^{3}\).  
The third area runs from the northeast in the borough Gustavo A. Madero, crosses Cuauhitemoc in the center, and ends in Venustiano Carranza, which is located in the northeastern part of the basin; in this case, the median concentration of normalized PM\({}_{2.5}\) was 47.5 \(\upmu\)g/m\({}^{3}\) with an interquartile range between 39.5 to 48 \(\upmu\)g/m\({}^{3}\).  
The fourth and last area was in the southwestern part of the basin, and covered the southern areas of Coyoacan and Iztapalapa, plus the northern part of Xochimilco. The median concentration of normalized PM\({}_{2.5}\) was 60.6 \(\upmu\)g/m\({}^{3}\) with an interquartile range between 51 to 68.6 \(\upmu\)g/m\({}^{3}\).  
The first and second areas showed the largest concentrations of normalized PM\({}_{2.5}\) in Magdalena Contreras, Cuauhitemoc, and Azcapotzalco (78.1 \(\upmu\)g/m\({}^{3}\) (two measurements with the same values) 81.8 \(\upmu\)g/m\({}^{3}\) (75.4-103.4 \(\upmu\)g/m\({}^{3}\)), and 90.7 \(\upmu\)g/m\({}^{3}\) (one measurement), respectively); whereas, the lowest concentrations were observed in the third area, more precisely in Gustavo [PERSON] and Venustiano  
Figure 3: Spatial distribution of PM\({}_{2.5}\) in Mexico City.  
Carranza (43.5 \(\mathrm{\SIUnitSymbolMicro g}\)/m\({}^{3}\) (35.2-47.7 \(\mathrm{\SIUnitSymbolMicro g}\)/m\({}^{3}\)), 58.8 \(\mathrm{\SIUnitSymbolMicro g}\)/m\({}^{3}\) (one measurement), respectively). Finally, it is important to outline the overestimation identified in the concentration of PM\({}_{2.5}\) in the normalized values when compared to the personal measurements originally taken (Table 1).  
Post-processed data showed a reasonable estimate of prediction. The RMS from the fitted model (38.94641) and from the residual error (38.03686) differed only by 2.2% (standardized RMS = 1.022); the validity of Kriging interpolation through Bootstrap and K-fold cross performed similar to that of the predictive surface. Therefore, both the interpolation method and the adjusted interpolated method using the fitted variables were reliable.