# Seasonal Characteristics of Particulate Matter by Pollution Source Type and Urban Forest Type
## 2 Materials and Methods
### Monitored Data  
To investigate the PM reduction effects of urban forests, AICAN data were obtained from the Korea Public Data Portal (Korea Public Data Portal, 2023), while downtown plot data were obtained from AirKorea (Korea, 2023). Because AICAN data were observed every 10 min and AirKorea data were observed hourly, the AICAN data were averaged hourly to synchronize the data timelines for AICAN and AirKorea. Then, the location data for road areas and industrial complexes were merged by PM\({}_{10}\) concentration (source, forest, residential area (AICAN) and downtown area (AirKorea)) together with the corresponding city data from AirKorea by date and were ordered in the format of year/month/day/hour. In this study, the Kruskal-Wallis test (KW test; it is a non-parametric counterpart to the parametric one-way analysis of variance (ANOVA)) was used to compare medians by ordering the data for each group. Because this method is rank based, it is less affected by outliers, and given the multiple causes of high PM concentrations at pollution sources, outlier removal was not performed. Due to the varying distances of measurements from the road source, the plots were categorized as road, forest interior 1, forest interior 2, and downtown areas (Table 1). In addition, since PM concentrations are high in spring and winter in South Korea, these seasons were further divided in half, resulting in a total of six periods for comparing PM concentrations.  
Seasonal criteria were established using the method provided by [PERSON], [PERSON], and [PERSON] (2016), defined by Equation (1). This equation calculates the Summed Daily Temperature (\(SDT_{i}\)) as the seven-day moving average of the daily maximum \((MaxT_{i})\), minimum  
Figure 2: Measuring instrument at each plot.  
\((Min\)T\({}_{i})\), and mean \((MeanT_{i})\) temperatures, where i refers to the number of days, and i = 1, \(\ldots\), 365.  
\[SDT_{i}=\frac{\sum_{n=i-3}^{i+3}(MinT_{n}+MeanT_{n}+MaxT_{n})}{7}. \tag{1}\]  
The seasonal transitions were identified as follows. Winter ends and spring begins on the last day when the SDT falls below 15 \({}^{\circ}\)C, calculated as 24 February 2021. Spring ends and summer begins on the first day when the SDT reaches or exceeds 60 \({}^{\circ}\)C, noted as 6 June. Summer ends and autumn begins on the last day with the SDT is at or above 60 \({}^{\circ}\)C, calculated as 11 October. Autumn transitions to winter on the first day when the SDT drops below 15 \({}^{\circ}\)C, which was November 28. Given the typically high PM concentrations during winter and spring in Korea, the analysis was segmented into six periods: early winter (1 January 2021-23 February 2021), early spring (24 February 2021-16 April 2021), late spring (17 April 2021-5 June 2021), and late winter (28 November 2021-31 December 2021). PM concentration levels were categorized according to environmental ministry standards as good (0-30 \(\mu\)g/m\({}^{3}\)), not bad (31-80 \(\mu\)g/m\({}^{3}\)), bad (81-150 \(\mu\)g/m\({}^{3}\)), and very bad (above 150 \(\mu\)g/m\({}^{3}\)).