# Examining the Amount of Particulate Matter (PM) Emissions in Urban Areas
## 5 Discussion  
Our results show that the concentration of particulate matter does not only depend on the number of vehicles but also on their category and vehicle emission class. These facts were also confirmed by studies aimed at identifying the biggest polluters by category and vehicle emission class [45; 46]. In addition to vehicle emission class, the type of fuel is also important, e.g., diesel engines recorded a lower amount of PM compared to LNG and CNG [47]. Researchers have also studied the environmental impacts of trucks using LNG [48]. The stationary measuring location within the city's urban area is also an important factor. Researchers conducting studies on PM\({}_{2.5}\) pollution within the city of Philadelphia recorded lower values in locations surrounded by greenery. In addition, they found that proximity to major roads (60 m) was associated with higher pollution levels [49]. The graphs displaying the results of our research show the immediate impact of traffic during the day on PM values; however, the results of other studies also show that temporal variations of air pollutants are related to traffic during the morning/evening peaks in the winter/summer seasons. Increased concentration levels of PM\({}_{10}\), PM\({}_{2.5}\), and PM\({}_{1}\) were observed more often during the morning and in winter seasons than at other times in all locations of the city of Dhanbad in India [50]. To a large extent, it is also necessary to pay attention to the correct location of the sensor that records the quality of the surrounding air. In the research, the sensor is placed according to land use and also according to the possibility and logical behavior of the traffic stream. A similar procedure was described in a study by [PERSON] et al. [51]. Another study [52] presents a new approach based on information theory to the deployment of air pollution sensors. This entropy-based approach has been compared with methods based on hotspots and random metrics. A final approach to sensor placement is their ability to produce accurate pollution maps [53]. The results found during the research show that the highest concentration (PM\({}_{10}\)) was measured at the railway crossing (68.5 \(\mu\)g/m\({}^{3}\)), while PM\({}_{2.5}\) values (15.25 \(\mu\)g/m\({}^{3}\)) reached their lowest values when there were lower numbers of vehicles at other time intervals. These figures represent an hourly average value. The concentration was at a relatively low level in the areas near the elementary school and the bus station. This could be caused, on the one hand, by low traffic intensity, but also by the location of the measured places, which were located on the outskirts of the city [54; 55; 56]. This can also point to sources of emissions other than transportation. In terms of dispersion and concentration, mobility in individual parts of cities is also important [57; 58]. However, meteorology itself also has a high influence on PM concentration. Researchers have found that they reach their maximum values in the morning peaks, decrease during the day due to atmospheric dilution processes (increases in wind speed and the height of the boundary layer), and then rise again in the evening [59]. Values measured during the winter period with the lowest mean solar radiation are characterized by a sharp increase in pollutant levels during peak \begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{2}{c}{**Degree of Dependence of Monitored Data**} \\ \hline very high dependence & 0.9–1 \\ \hline high dependence & 0.7–0.9 \\ \hline moderate dependence & 0.5–0.7 \\ \hline low dependence & 0.3–0.5 \\ \hline no dependence & 0–0.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Evaluation of correlation coefficients [44]. hours, especially in the evening when wind speeds are at their lowest levels [60]. In the case of relative humidity, a strong positive correlation with fine particles was observed during the peak hours of winter morning (r = 0.75; PM\({}_{2.5}\)) and evening (r = 0.67; PM\({}_{2.5}\)).