**3. Results**

Based on the results of the field measurements, 3D maps were drawn using ArcGis software of the dispersion of pollution in the analyzed area. This form of 3D spatial analysis is an innovative approach, so the results are not comparable with the literature data. Due to the fact that dust pollution has similar field dispersion characteristics [14], PM10 pollution was selected for the graphic presentation. Figure 4 shows the results of PM10 dispersion for series A and B in the winter period, together with a longitudinal and vertical cross-section for series B to show changes in the altitude of the pollution.

**Figure 4.** Spatial distribution of PM10 concentrations during the winter season in series A and B.

The selected series of representative measurements for the winter period show a variable concentration of PM10. In series A, the average concentration of PM10 was 21.80 μg/m3 and the maximum concentration was 42.40 μg/m3. According to the air quality index adopted in Poland [30], the air quality of series A is classed as "Good" (limit of PM10 20.1–50.0 μg/m3). The spatial analysis shows that the entire area of analysis was characterized by an even concentration of PM10. In comparison, series B showed double the concentrations of PM pollutants. The mean concentration of PM10 was 54.80 μg/m3 and the maximum 77.60 μg/m3. According to the air quality index in relation to PM10, the air quality of series B is "Moderate" (50.1–80.0 μg/m3). In series A, the concentration of PM10 did not exceed the level of 50 μg/m3 allowed by EU standards, whereas in series B the EU limit was exceeded in many places by 55%. The increased concentration of particulate matter in series B can be explained by the fact that the average wind speed was less than half that in the series A. Tall buildings, with heights of 15–30 m, also contributed to the accumulation of pollution in the analyzed area. In series B, there are spaces with lower and higher PM10 concentrations. Elevated levels of PM10 > 60 μg/m<sup>3</sup> (red in Figure 4) occur at

street crossings and in more densely built-up areas. Lower PM10 concentrations (green in Figure 4) relative to the mean value occur in the highest part of the analyzed area. This is probably related to the stronger ventilation. From the vertical cross-section view of the 3D dispersion, it can be concluded that concentrations above 40 μg/m<sup>3</sup> occur mainly close to the ground surface. At the intersections, the concentration of PM10 increases with height, which is probably related to the upward movement of pollutants and car exhaust fumes.

The concentrations of PM10 in series C and D in the summer period (Figure 5) were up to four times lower compared to the winter period. The mean concentrations of PM10 in series C and D were 8.20 μg/m3 and 12.10 μg/m3, respectively. In contrast to the winter period, during the summer period the concentration of PM10 was similar in the whole analyzed area. There were no areas with concentrations of particulate matter above the average value. Only in series D, during a period of high temperatures and low humidity, were PM10 concentrations observed exceeding 30 μg/m3, as can be seen in the upper left area of Figure 5. The source was earthworks at a construction site. To sum up, during the summer period the permissible level PM10 of 50 μg/m3 was not exceeded [4]. In the summer, the use of fuel for heating purposes in individual heating systems is reduced and the average speed of road transport increases. This contributes to lower emissions of particulate matter. To facilitate comparison of the 3D dispersion maps, further analysis of the air quality parameters was limited to two of the selected representative measurement series in order to facilitate the graphical reception and comparison of the results.

**Figure 5.** Spatial distribution of PM10 concentrations during the summer season in series C and D.

The emissions of pollutants selected in this study are mostly related to the combustion of fossil fuels. Therefore, SO2, which is another of the products of the combustion of fuels used in motor vehicles, was also included in the analysis. In series A of the winter period, the concentration of SO2 varied from 0.006 ppm to 0.346 ppm, i.e., from 20 μg/m<sup>3</sup>

to 970 μg/m3. Spatial analysis (Figure 6) showed the presence of an area with a high concentration of SO2 above 0.24 ppm (>670 μg/m3) at the sites of traffic jams before the eastern intersection. It may also be due to SO2 being transported downwind from industrial emitters such as EC3. The second place with a high concentration of SO2 was at the extreme western intersection. Concentrations of SO2 below 0.16 ppm (<450 μg/m3) were recorded only at a height of more than 30 m above ground level, in an area of lowrise single-family housing. This was probably due to the stronger ventilation in the area. According to the cross-section of the 3D dispersion map, the highest SO2 concentrations above 0.24 ppm were measured at ground level. With increasing heights above ground level, the concentration of SO2 decreased up to threefold. This suggests that the main sources of SO2 were car exhaust fumes and exhaust fumes from individual heating systems (single-family buildings). According to the EU, 15% of SO2 emissions are caused by individual heating systems [2]. Across the entire area, at a height of 2 m the permissible level of SO2 (350 μg/m3) according to EU standards [4] was exceeded by about 20–277%.

**Figure 6.** Spatial distribution of SO2 concentrations during the winter season in series A and during the summer season in series C.

In the summer period, the SO2 concentration decreased significantly, and was up to three times lower compared to the winter period. In series C (Figure 6), the concentration of SO2 ranged from 0.001 ppm to 0.122 ppm (max 320 μg/m3). Similar to the winter period, the spatial distribution showed the presence of areas with increased SO2 concentrations at the intersections and the sites of traffic congestion. However, according to the cross-section of the pollution dispersion map, in summer the highest concentration of SO2 was not at ground level, as it was in winter. This can be explained by the fact that there was no thermal inversion in the summer period. This prevented the accumulation of pollutants and enabled faster mixing (dilution) in the atmospheric air. The concentration of SO2 was lowest at the highest point of the area of analysis and in the open space behind the crossing from the eastern side. This was probably related to the fact that these are zones of increased ventilation [31].

Finally, we considered the concentrations of Volatile Organic Compounds (Figure 7). In the winter and summer periods, the average VOCs concentration was about 20 μg/m<sup>3</sup> (0.005 ppm). However, in the winter period the VOCs concentration reached 0.09–0.12 ppm (310–420 μg/m3), i.e., 53% higher than the maximum VOCs concentration in the summer period (0.023–0.079 ppm). This can be explained by a higher degree of photochemical reactions in the summer period, which reduce the concentration of VOCs. The cross-section of the pollution dispersion map for the winter months shows that the highest concentrations of VOCs were recorded close to the ground surface. As the altitude increased, the VOCs concentration quickly decreased to levels below 0.005 ppm (20 μg/m3). In summer, the highest concentrations of VOCs pollution occurred in the area around Pojezierska Street and towards the western intersection, where the heat and power plant is located. Xu et al. similarly identified a heat and power plant as the main origin of VOCs [32].

**Figure 7.** Spatial distribution of VOCs concentrations during the winter season in series A and during the summer season in series D.

Table 2 presents the results of actual measurements from the representative series (A–D) taken during the 3 months of research in the winter and summer periods. The data show that in the winter period the concentration of particulate matter was almost four times higher relative to the average value than in the summer period. The concentration of SO2 was three times higher in the winter than in the summer. The average VOCs concentration remained at a similar level, regardless of the season.

**Table 2.** Measured concentrations of pollutants in a representative measurement series during the winter and summer periods in 2021.


The next part of the analysis used numerical software to calculate the dispersion of selected pollutants in relation to their probable sources of emissions.

The area of interest includes a heat and power plant with a chimney 120 m tall, from which emissions are released. Data were obtained from Veolia Energia Łód´z, comprising a collective measurement of emissions (kg/h) from the chimney after desulphurization and dedusting of flue gases from five boilers. As can be seen in Table 3, the emissions were mostly composed of SO2 (despite the exhaust gas treatment systems). This suggests that the EC-3 CHP plant may be responsible for the high concentrations of SO2 found in our analysis.

**Table 3.** Maximum hourly emissions of pollutants for the EC-3 CHP plant (own calculations based on data from Veolia Energia Łód ´z).


Based on the parameters of the emitter and the amounts of pollutants, OPA03 software was used to simulate the dispersion of emissions from the EC-3 CHP plant. The results are shown in Figures 8–12. According to the simulation, in winter, the maximum concentration of PM10 emitted from EC-3 was 0.21 μg/m3 (Figure 8).

**Figure 8.** Dispersion diagram of the maximum 1-h concentrations of PM10 emitted in the summer and winter periods from EC-3.

**Figure 9.** Dispersion diagram of the maximum 1-h concentrations of SO2 emitted in the summer and winter periods from EC-3.

**Figure 10.** Dispersion diagram of the maximum 1-h concentrations of PM10 emitted in the summer and winter periods from road traffic.

**Figure 11.** Dispersion diagram of the maximum 1-h SO2 concentration in the summer and winter periods from road traffic.

**Figure 12.** Dispersion diagram of the maximum 1-h PM10 concentrations of emissions from individual heating systems in the summer and winter periods.

In summer, the maximum concentration of PM10 according to our simulation was 0.42 μg/m3, i.e., twice as high as in the winter period. This can be explained by the exhaust velocity from the chimney in the summer period, which at 5.24 m/s was three times lower than in the winter period (16.2 m/s). A slower exhaust outlet in the summer period allows for faster precipitation of pollutants, and this results in a higher concentration of dust pollutants in the vicinity of the heat and power plant. However, in both the winter and summer periods the concentration of PM10 caused by the emission from EC-3 did not exceed 0.5 μg/m3 at a height of 2 m, which is less than 1% of the permissible value (50 μg/m3).

The analysis shows that SO2 was emitted from the CHP plant at a higher concentration than PM10 (Figure 9). In the winter period, the highest one-hour concentration according to the simulation was 20.35 μg/m3. This value occurred in the immediate vicinity of EC-3, covering the entire area of the analyzed street. At a distance of about 2 km from the CHP plant, the concentration of SO2 decreased to between 15 μg/m3 and 20 μg/m3. At a distance of about 6 km, it fell to below 15 μg/m3. In the summer period, the scope of the EC-3 s environmental impact area was reduced by about 16%, which translated into a higher concentration than 25 μg/m3 of SO2 within a 1 km radius of EC-3. Based on computer simulations, Lee et al. [7] also observed higher SO2 concentrations in the summer period, which were also explained by the lower outlet velocity in the summer period compared to the winter period. This resulted in a greater accumulation of pollution in the immediate vicinity of the heat and power plant.

The permissible maximum one-hour concentration of SO2 in the air is 350 μg/m3 [4]. The emissions of SO2 from the combined heat and power plant amounted to only 8.9% of the limit value in the summer period and to 5.8% in the winter period.

According to traffic volume studies carried out during the air quality measurements, an average of 983 vehicles per hour traveled between the west and the east intersections in the winter period, at an average speed of 32 km/h. In the summer period, the intensity increased by 14% to 1118 vehicles per hour. The average vehicle speed increased to

approximately 39 km/h. The analyzed street was used mainly by passenger cars, which accounted for 89% (summer period) and 91% (winter period) of the total number of vehicles. Light trucks accounted for 8% or 7% of the traffic in each period, trucks for 2% or 1%, and public buses for 1%. These results were used to create a numerical simulation in the OPA03 program of the dispersion of linear pollutants (Figures 10 and 11). Comparing the simulations of PM10 dispersion in the summer and winter periods (Figure 10), it can be observed that in the summer period there were higher concentrations of PM10 emissions. In the winter period, the maximum one-hour concentration was 12 μg/m3, whereas in the summer period it was 17.7 μg/m3. This was related to a 14% higher number of vehicles in the summer season, with a simultaneous increase in speed of only 7 km/h compared to the winter period. According to the simulation, the emissions from vehicle traffic had a small range of influence, as they were limited mainly to the immediate area of the street. This was due to the densely built-up area and the presence of tree stands (15–30 m tall trees). As Long et al. observed [27], local rough terrain has an impact on local meteorological conditions, especially in terms of wind direction and speed. Highly rough terrain contributes to protection against low windspeed and reduced airing, reducing the accumulation of pollutants. According to the simulation, the maximum concentration of PM10 was 35.4% of the permissible average daily concentration of 50 μg/m<sup>3</sup> [4].

The spatial distribution of SO2 (Figure 11) according to the simulation was similar to the data for particulate matter. It was concentrated mainly in the road area and a small area of the surroundings (about 40 m). According to the simulations, the highest concentrations of SO2 occurred within the lanes of the road, reaching 43.5 μg/m<sup>3</sup> in winter and 52.3 μg/m<sup>3</sup> in summer. In the area of the pedestrian sidewalks, the one-hour concentration decreased to below 15 μg/m3. Road traffic emissions were at 12.4% of the maximum permissible level of 350 μg/m3 stipulated by the EU [4] in winter and 14.9% of the maximum in summer.

In the immediate vicinity of the analyzed street, there are about 170 single-family houses with individual heating systems (70% coal fired and 30% natural gas). Based on detailed data in the literature on this source of emissions [33], presented in Table 4, calculations were made in the OPA03 program for point emitters located using the map of the analyzed area (Figure 2).


**Table 4.** Hourly emissions of pollutants from individual heating systems (source: [33]).

There was a visible difference between the summer and winter periods in terms of the concentrations of PM10 and SO2 (Figures 12 and 13). Therefore, different scales were used in the figures to present the results. During the summer period, the PM10 concentration (hourly maximum) (Figure 12) fluctuated between 0.03 μg/m3 and 0.161 μg/m3, because the heating systems were used mainly for the purpose of preparing domestic hot water. In the winter period, the concentration of PM10 emitted from individual heating systems was higher than the highest value calculated in the summer period, ranging from 0.6 μg/m<sup>3</sup> to 4.0 μg/m3. This can be explained by the increased combustion of fuels for the production of thermal energy to heat the buildings in winter. Kaczmarczyk et al. [8] and Specjał et al. [34] made similar observations.

**Figure 13.** Dispersion diagram of the maximum 1-h SO2 concentrations of emissions from individual heating systems in the summer and winter periods.

The concentration of SO2 in the summer was more than 10 times lower than in the winter period, when there is increased production of heat energy. According to the results presented in Figure 13, in the summer period the maximum hourly SO2 concentration varied in the range of 0.12–0.72 μg/m3, whereas in the winter period it was in the range of 5.0–16.0 μg/m3. The maximum value calculated in the summer period was 0.2% of the permissible value, and in the winter period it was 4.6% of the permissible value (350 μg/m3).

The pollution from individual heating systems depended strongly on local factors, especially the wind direction. The highest concentrations of PM10 and SO2 recorded in the axis of the location of the emitters, as the pollutants moved mainly in the direction of the WSW wind, which is dominant in the area. As a result, the emissions from individual heat sources did not affect the whole area of the analyzed street, but only the part in the direction of the wind.

#### **4. Conclusions**

In this study, we have compared the results of simulations performed using numerical software with data from actual field measurements. Maps were created of the distributions of air pollution in the vicinity of a heat and power plant and a communication route. For the numerical simulations, we assumed the highest concentrations of emissions from the selected pollution sources. According to the simulations, in the winter and summer periods, the maximum concentrations of PM10 were 16.22 μg/m3 and 18.29 μg/m3, respectively. According to our actual measurements, the maximum hourly concentration was in winter about 58.8 μg/m3 and in summer 23.5 μg/m3. The difference between the results of the simulation and the actual concentration of PM10 indicates the possibility of an additional source of dust pollution not included in the study, or the influence of background pollutants transported by the wind. There may also have been calculation errors associated with our method.

According to the simulation data shown in Figure 14, road transport accounted for the largest percentages of total PM10 emissions, at around 74% in winter and 96.9% in summer. The CHP was responsible for the smallest share of PM10 emissions, amounting to 1.3% or 2.3% of the total emissions according to the numerical calculations. This was related to the legal restrictions on dust emissions from power plants and the use of modern flue gas cleaning systems. The total maximum concentrations of SO2 according to the numerical calculations were 81.0 μg/m3 in winter and 84.0 μg/m3 in summer. The concentration of SO2 according to the actual measurements was about 350% higher than in the simulation for the winter period and about 140% higher than in the simulation for the summer period. Similar differences between real measurements and the results of simulations were reported by [7]. As in the case of PM10, it can be explained by the high concentrations of pollutants transported by the air close to the ground surface, especially in winter during so-called thermal inversion. This causes the phenomenon of smog in the winter (poor air quality), as demonstrated by Wielgosi ´nski et al. [35]. The vertical cross-sections through the dispersion maps of pollutants in winter (Figures 4, 6 and 7) showed the highest concentrations close to the ground level (approx. 2 m).

**Figure 14.** Percentage share of selected air pollution sources in the total maximum hourly concentrations of air pollutants in the summer and winter periods, based on numerical calculations.

According to the calculations performed by the OPA03 program (Figure 14), most emissions of SO2 were caused by road transport, which was responsible for 53.8% and 62.2% of the total maximum concentrations in winter and summer, respectively. Road transport has a particularly strong impact on air quality in densely populated areas [36], where vehicles generate much higher concentrations of pollutants due to slow traffic and

high vehicle aggregation with little airflow [37]. This is especially important in Poland where, according to comparative studies, the air quality is worse than in other European Union countries [38]. According to data from the European Union [2] and Poland [28], road transport is one of the main sources of PM and gas emissions. Individual heating systems were responsible for the smallest share of SO2 emissions, amounting to 21.1% in winter and 0.8% of total emissions in summer. Similarly, Kaczmarczyk et al. [8] reported that individual heating systems were primarily responsible for the emission of particulate matter, especially when hard coal was used as fuel. Comparing the results from numerical calculations with the actual measurements shows the importance of using mobile measuring devices in air quality analyses, because simulations do not take into account all potential sources of air pollution or the correct level of background pollution. The presented research methodology can be implemented in any urban area, with a particular focus on local scale analysis.

**Author Contributions:** Conceptualization, R.C. and M.D.; methodology, R.C., M.D.; software, M.D., R.C.; writing—original draft, R.C., M.D.; review and editing, R.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was conducted as part of the research project entitled "Spatial analysis of air pollution changes in the Lodz agglomeration (in Polish: Analiza przestrzenna zmian stanu zanieczyszczenia powietrza w aglomeracji łódzkiej)", which was co-financed approx. 80% by the Provincial Fund for Environmental Protection and Water Management in Łód ´z (in Polish: Wojewódzki Fundusz Ochrony Srodowiska i Gospodarki Wodnej w Łodzi). ´

**Institutional Review Board Statement:** Not applicable

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data available on request.

**Conflicts of Interest:** The authors declare no conflict of interest.
