**5.1. Prediction from chemical monitoring**

The concentrations of PM2.5 are commonly correlated with other air pollutants, such as SO2 , NO2 , CO, etc. [20]. However, the monitoring of these substances involves a more specialized equipment than traffic or weather monitoring. The performance of the models built in this section is used as referential to assess the quality of the previous models and investigates if a selection of the most affordable chemical records can significantly improve the overall prediction accuracy. Four additional criteria pollutants were measured (CO, NO<sup>2</sup> , SO2 , and O3 ). For SO2 concentrations, ThermoFisher Scientific 43i highlevel SO2 analyzer was used based on ultraviolet florescence (EPA No. EQSA-0486-060). For O3 concentration data collection, ThermoFisher Scientific 49i ozone analyzer was used based on ultraviolet absorption (EPA No. EQOA-0880-047). For NOx concentration data collection, ThermoFisher Scientific 42i NOx analyzer was used based on chemiluminescence method (EPA No. RFNA-1289-074). Finally, for CO concentration data collection, ThermoFisher Scientific 48i was used based on infrared absorption (EPA No. RFCA-0981- 054). The used dataset is composed of 1118 observations and 5 features: CO, NO<sup>2</sup> , O3 , SO2 , and PM2.5 (= feature to predict).

The prediction accuracy of the model is evaluated as

**r = 0.75**
