In South Korea, one of the current environmental issues is reducing and mitigating particulate matters (PM) in urban areas. Due to the recent fast growing public interest in urban forest and its function, it is highly expected by the public that urban forest plays a significant role in effectively solving this PM problem. However, as there is lack of study about the response of PM concentration to physical characteristics of urban forest, it is not easy to design an urban forest having a capacity of effectively mitigating PMs around the forest. In this paper, effects of vegetation structural difference within urban forest on PM10 and PM2.5 concentrations were examined via a pilot study. Study areas were two types of forests, Seoul Forest located in Seoul and Mt. Taehwa in Gyunggi-do. Data about PM10 and PM2.5 and weather factors were collected from April to May in 2017 to statistically analyze the difference in PM concentrations between forest structural types with time. Statistical analysis was conducted using linear mixed model (LMM) and repeated measured anova (RM ANOVA). Study areas included Eco Park, Family Park and Residence in Seoul Forest area, and hardwood forest and conifer plantation in Mt. Taehwa.
Results/Conclusions
Regarding height, diameter at breast height and density of tree species, hardwood forest showed the biggest and densest condition, conifer plantation was the second and Eco Park was the last, and Family Park was covered with grass without tree canopy. The reference sites for Seoul Forest and Mt. Taehwa indicated similar values and patterns about PM, and the PM concentration showed the significant correlation with mean temperature, wind direction and humidity. The regression equations derived from LMM analysis were not sufficient to explain the PM patterns. However, the outcome from RM ANOVA analysis presented whereas the concentrations of PM10 and PM2.5 in Family Park were lowest, those of Eco Park were in the middle and those of Residence were highest within Seoul Forest, those of both hardwood forest and conifer plantation were not significantly distinguished. The result indicated the structural difference in urban forest exerted an effect on the PM concentration but in different ways between PM10 and PM2.5. Therefore, it is required to investigate the significant factors for this outcome such as detailed vegetation structure, physiological functioning and elements of PM. Using this approach with more sufficient data will be helpful to effectively plan and design the structure of an urban forest.