# Examining the Amount of Particulate Matter (PM) Emissions in Urban Areas
## 2 Measurement Methodology  
For our research, we chose the measuring points where the measurements were carried out. We performed the study in a city located in central Slovakia. We selected places with a high intensity of pedestrians and traffic congestion that are located directly in the built-up area of the city. We aim to quantify the concentration of particulate matter at selected locations (Figure 1). A thorough analysis of the monitoring stations showed that there were no places in the vicinity that could affect the measurements and distort the results of the particulate matter concentration research. Our results highlight that air pollution is mainly due to traffic activity. \begin{table}
\begin{tabular}{c c c} \hline
**Air Quality Evaluated According to Slovak Hydrometeorological Institute [ug/m3]** \\ \hline
**Quality Level** & **PM2.5** & **PM10** \\ \hline very good & 0-14 & 0-21 \\ \hline good & 14-25 & 20-40 \\ \hline worse & 25-70 & 40-100 \\ \hline bad & 70-140 & 100-180 \\ \hline very bad & -140 & -180 \\ \hline \end{tabular}
\end{table} 
Table 1: Evaluation of air quality in measurement of particulate matter (according to Slovak Hydrometeorological Institute). Figure 1 shows the distribution of the measurement points. We selected the points based on the high intensity of pedestrian movement in the area. Additionally, a high intensity of vehicle movement was also a key consideration when choosing a location. In our paper, we examine whether an increase in the number of vehicles in a given location can negatively affect air quality. We chose the following locations for conducting our research: a bus station, a location near elementary schools, and a railroad crossing. We chose places where there is an increased intensity of vehicles and pedestrian movement. In the research on the number of vehicles, a record of the passage of vehicles was made. Each vehicle was assigned to a category. Three categories were monitored: passenger vehicles, trucks (weight over 3.5 tons), buses. Because the measuring points are located in the city center, the passage of non-passenger vehicles is excluded furthermore, as only vehicles with a valid exemption are allowed to enter the area. For that reason, we do not record these vehicles in our results. Moreover, their ratio to the passenger vehicles we recorded at the measurement points is negligible. (For example, for a measurement point near a railway crossing, the number of passenger vehicles/number of trucks/number of buses was 10,296:24:21.) Regarding trains, most are powered exclusively by electric energy; therefore, we do not expect the results to be distorted by the passage of trains. We selected all locations based on their pre-observed characteristics, such as traffic intensity, the number of departures and arrivals of buses at the bus station, the number of trains passing, and the average length of stops at the railway crossing. During our research, we monitored the values of PM\({}_{2.5}\) and PM\({}_{10}\) particulate matter. We measured and recorded these values using a measuring device at regular intervals. For research purposes, we repeated particulate matter measurements every 15 min for the duration of the survey. This means that we conducted four particulate matter measurements within 1 h of the survey. At the same intervals, we also monitored the number of vehicles that passed through the road near the measurement point. Figure 2 shows the individual measuring points. We took the measurements immediately one after the other during working days. We carried out the first measurement on Tuesday and the last on Thursday. We excluded the beginning and end of the week due to distorted measurement results. Figure 1: Distribution of measuring points in the city (based on mappy.cz). Figure 2 shows the individual measuring points. Each measuring point is located near a road or a place with increased vehicle traffic. Figure 2(2) shows particulate matter levels measured at the bus station.