## 3 Results  
### Microscopic Analysis  
Descriptive statistical analysis was conducted as an initial step to characterize the fundamental statistical properties of the particle feature distributions, including the mean, median, standard deviation (STD), and range, as defined by the minimum (Min) and maximum (Max) values. The results of this analysis are presented in Tables 1 and 2, summarizing the particle populations sampled from the forest and urban areas, respectively. Descriptive statistical analysis of the particle features (diameter, area, perimeter, length, width) measured from the air samples collected from the two locations revealed that not only the number of particles, but also the variability of the particle features shows prominent differences. While the particle concentration detected by DIC microscopy was lower in the samples collected in the forest region (20 particles/L) compared to the urban area (35 particles/L), all the measured particle features showed a higher range and standard deviation sampled from the forest region. The raw data for measuring particle features and comparing the two sampling locations were obtained from DIC microscope images (Figure 2). \begin{table}
\begin{tabular}{c c c c c c} \hline
**Particle Feature** & **Mean** & **Median** & **STD** & **Max** & **Min** \\ \hline Diameter (\(\upmu\)m) & 1.7 & 0.99 & 2.53 & 25.27 & 0.36 \\ Area (\(\upmu\)m\({}^{2}\)) & 7.26 & 0.76 & 40.53 & 501.68 & 0.1 \\ Perimeter (\(\upmu\)m) & 10.23 & 4.24 & 37.19 & 469.51 & 1.21 \\ Length (\(\upmu\)m) & 4.38 & 1.73 & 18.37 & 232.6 & 0.38 \\ Width (\(\upmu\)m) & 0.78 & 0.43 & 0.73 & 4.55 & 0.18 \\ Number of particles & 178 & 178 & 178 & 178 & 178 \\ \hline \end{tabular}
\end{table} 
Table 1: Descriptive statistical analysis of the particle samples collected in the forest. Feature dimensions: \(\upmu\)m and \(\upmu\)m\({}^{2}\) in the case of area. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Particle Feature** & **Mean** & **Median** & **STD** & **Max** & **Min** \\ \hline Diameter (\(\upmu\)m) & 1.09 & 0.7 & 1.42 & 15.87 & 0.36 \\ Area (\(\upmu\)m\({}^{2}\)) & 2.5 & 0.38 & 13.77 & 197.91 & 0.1 \\ Perimeter (\(\upmu\)m) & 6.15 & 2.76 & 15.27 & 185.77 & 1.21 \\ Length (\(\upmu\)m) & 2.61 & 0.96 & 7.46 & 91.62 & 0.38 \\ Width (\(\upmu\)m) & 0.49 & 0.37 & 0.36 & 3.65 & 0.17 \\ Number of particles & 319 & 319 & 319 & 319 & 319 \\ \hline \end{tabular}
\end{table} 
Table 2: Descriptive statistical analysis of the particle samples collected in the urban area. Feature dimensions: \(\upmu\)m and \(\upmu\)m\({}^{2}\) in the case of area. Figure 2: Representative DIC microscope images illustrate characteristics of particle populations sampled from forest (**A**) and urban (**B**) areas. Statistical Visualization of the Particle Features Measured from the Samples Collected in the Forest and in the Urban Area  
The empirical cumulative distribution function (ECDF) and Box plot representations were utilized to provide a comprehensive analysis and comparison of the particle feature distributions for the samples obtained from the forest and urban areas (Figures 3-7). The ECDF was employed to illustrate the cumulative probability distribution of the particle features, offering insights into their variability and overall distribution trends. In parallel, the Box plot representation provided a detailed summary of the key statistical parameters, including the median, interquartile range (IQR), and potential outliers, enabling a clear visualization of differences between the two sampling environments. Figure 4: ECDF and Box plot representation of particle feature “Diameter” calculated by DIC microscopy. Figure 3: ECDF and Box plot representation of particle feature “Area” calculated by DIC microscopy. Non-parametric statistical analysis of the air particle features collected in the forest and urban areas showed that the samples are distinguishable based on the sampling location in the case of all features.