Effects of Green Network Management of Urban Street Trees on Airborne Particulate Matter (PM2.5) Concentration

Abstract

Street trees are crucial for air pollutant reduction in urban areas. Herein, we used computational fluid dynamics (CFD) simulation to identify changes in airborne particulate matter (PM2.5) concentration based on wind characteristics (direction and velocity) and the green network of street trees. The green network was assessed based on composition of the green area of street trees in the central reserve area and between the motor and pedestrian roads. The PM2.5 concentration varied according to the presence or absence of major reserve planting and the planting structure of the street trees, but not according to the wind direction or velocity. The concentration was lower when the wind direction was 45° (than when the wind direction was 0°), whereas it showed a more significant decrease as the wind velocity increased. Despite variation at each measurement site, the PM2.5 reduction was generally higher when the central reserve and street trees had a multi-planting structure. Hence, to ensure an effective reduction in the PM2.5 concentration on motor roads and reduce its negative impact on pedestrians, both arbors and shrubs should be planted in the central reserve area. The study results will serve as reference for managing the green area network and linear green infrastructure in terms of improving the atmospheric environment.