# Seasonal Characteristics of Particulate Matter by Pollution Source Type and Urban Forest Type
## 5 Conclusions  
This study aimed to identify consistent patterns in \(PM_{10}\) concentrations near pollution sources and interpret the \(PM_{10}\) reduction effects of urban forests. Seasonal, regional, and pollution source-specific data were analyzed using wind speed, wind direction, and \(PM_{10}\) distribution characteristics to understand these patterns. Our findings showed that the proportion of \"good\" \(PM_{10}\) levels was lowest in early spring and highest in summer, with frequent high \(PM_{10}\) events occurring in spring, early spring, and early year winter. Most wind speeds were below 3.3 m/s, and while winter generally had higher wind speeds, \(PM_{10}\) concentrations were also highest in winter.  
To assess differences in \(PM_{10}\) concentrations between urban forests and pollution sources, we compared the median \(PM_{10}\) values of plots using the Kruskal-Wallis test. Given the right skewness of the \(PM_{10}\) data, non-parametric methods were employed; yet, the complex nature of \(PM_{10}\) data as both numeric and categorical, along with the presence of extreme events, presented challenges in fully assessing \(PM_{10}\) reduction by urban forests. To address these challenges, we analyzed the distribution of \(PM_{10}\) data during the first half of the year, when median differences were minimal, and confirmed that \(PM_{10}\) concentrations were clustered at lower levels within forest interiors. During early year and early spring--when median \(PM_{10}\) levels were highest--the distributions for pollution sources and forests were distinctly different, while spring saw lower \(PM_{10}\) concentrations across all plots, reducing the differences. In the second half of the year, median \(PM_{10}\) concentrations were consistently lower in forest interiors and forests, as confirmed by the Kruskal-Wallis test.  
Overall, across all seasons, urban forests exhibited lower \(PM_{10}\) concentrations compared to pollution sources, reaffirming their role as an effective nature-based solution for air purification. These findings highlight the importance of urban forests in mitigating air pollution, and their potential as a strategy for enhancing urban air quality should be further explored in urban planning initiatives.  
The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/app14219988/s1](https://www.mdpi.com/article/10.3390/app14219988/s1)]([https://www.mdpi.com/article/10.3390/app14219988/s1](https://www.mdpi.com/article/10.3390/app14219988/s1)), Figure S1: The location of study and AICAN and AirKorea plots; Table S1: The most frequent wind direction and average wind speed for each plot by season.  
Conceptualization, methodology, formal analysis, investigation, resources, data curation, writing--original draft, writing--review and editing, and visualization: B.L.; conceptualization, methodology, validation, writing--review and editing, supervision, project administration, and funding acquisition: H.-D.S. and S.P.; conceptualization and methodology: C.-R.P, S.C., P.Y. and H.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (NRF-2021R1F1A1064096) and the National Institute of Forest Science (NIFoS) of Korea (grant No. FE0100202403).  
Not applicable.  
AICAN data can be acquired from the Korea Public Data Portal ([[https://www.data.go.kr](https://www.data.go.kr)]([https://www.data.go.kr](https://www.data.go.kr))), and air pollutant data can be obtained from AirKorea ([[https://www.airkorea.or.kr](https://www.airkorea.or.kr)]([https://www.airkorea.or.kr](https://www.airkorea.or.kr))).  
The authors report that there are no competing interests to declare.  
References