## 4 Results and Discussion  
### Data Pre-Processing, Correlations, and Trends  
Figure 2 presents the continuous hourly data for PM\({}_{2.5}\) and PM\({}_{10}\), from 18 February 2022 to 24 September 2024, compared with the data available for other collected variables before preprocessing. The aim is to evaluate data continuity and ensure the availability of all variables. As illustrated, benzene, CO, ethylbenzene, m-Xylene, NO, NO\({}_{2}\), NO\({}_{x}\), o-Xylene, O\({}_{3}\), p-Xylene, and toluene are only available for a portion of the PM\({}_{2.5}\) and PM\({}_{10}\) data period (February-April 2022). In contrast, SO\({}_{2}\) and meteorological variables show consistent availability throughout (18 February 2022-24 September 2024). Based on this, the data are split into two datasets in the next stage. The first covers the full PM\({}_{2.5}\) and PM\({}_{10}\) periods, focusing on their relationship with SO\({}_{2}\) and meteorological variables. The second encompasses the shorter period when all variables are available, allowing for a broader correlation analysis between PM\({}_{2.5}\), PM\({}_{10}\), and the other studied variables. Figure 3 illustrates the second dataset, which covers the shorter time frame during which all variables were consistently recorded. The primary objective of this analysis is to investigate potential relationships between ozone and other variables over this limited period. The key observations are:  
1. **Correlation between PM\({}_{2.5}\) and PM\({}_{10}\):** - PM\({}_{2.5}\) and PM\({}_{10}\) show similar trends, which is expected as PM\({}_{2.5}\) is a subset of PM\({}_{10}\). - Peaks and troughs in PM\({}_{2.5}\) align closely with those in PM\({}_{10}\), suggesting that their variations are driven by common sources or atmospheric conditions. 2. **Possible influencing factors on PM2.5 and PM10:** - Temperature: There may be an inverse relationship where higher temperatures could be linked to lower PM concentrations, possibly due to enhanced atmo  
Figure 2: A visualization of the data used in this work (including missing values). spheric dispersion. Additionally, during colder periods, lower temperatures increase heating demand, leading to higher emissions from fossil fuel combustion--an effect that diminishes during warmer seasons. * Relative Humidity: higher RH could lead to secondary aerosol formation, potentially increasing PM concentrations. * Wind Speed: Higher wind speeds often reduce PM concentrations by dispersing pollutants. Peaks in wind velocity could correspond to lower PM levels. * Precipitations: Rainfall typically reduces PM levels due to wet deposition. Spikes in precipitation may correspond to reductions in PM concentrations. * NO\({}_{\text{x}}\) and SO\({}_{2}\): These pollutants often contribute to secondary PM formation. Peaks in NO\({}_{2}\) or SO\({}_{2}\) might correlate with increases in PM levels. * Ozone: ozone formation is linked to photochemical reactions that also influence secondary aerosol formation, which could affect PM\({}_{2.5}\) levels. * VOC Compounds (Toluene, Xylene, Benzene): These compounds contribute to the formation of secondary organic aerosol (SOA), influencing PM concentrations. If PM peaks align with VOCs, this suggests secondary aerosol formation as a contributing factor. * CO: This pollutant and PM\({}_{2.5}\) are produced by the same sources and under the same atmospheric conditions. Concerning common sources, both CO and PM\({}_{2.5}\) originate from incomplete combustion processes (e.g., heavy traffic, wood and coal burning in thermal power stations and in dwellings, vegetation fires). CO and PM\({}_{2.5}\) also have similar accumulation conditions (they are stable in the atmosphere in the short term, accumulate under conditions of low wind, thermal inversion, and lack of dispersion). CO does not directly participate in the formation of PM\({}_{2.5}\) but in the presence of radicals (OH) it could be an indicator of incomplete oxidation leading to the formation of secondary PM\({}_{2.5}\).