Journal
FORESTS
Volume 13, Issue 1, Pages -Publisher
MDPI
DOI: 10.3390/f13010046
Keywords
computation fluid dynamics (CFD) simulation; particulate matter; urban air quality; green infrastructure
Categories
Funding
- Rural Development Administration, The Republic of Korea [PJ01427002]
Ask authors/readers for more resources
This study investigated the effect of vegetation configurations on particulate matter (PM) flows for pedestrians in road traffic environments. The results showed that planting structures, such as multi-layer planting vegetation barriers, were effective at reducing PM concentrations on sidewalks, especially on wider roads.
As a green infrastructure component, urban street vegetation is increasingly being utilized to mitigate air pollution, control microclimates, and provide aesthetic and ecological benefits. This study investigated the effect of vegetation configurations on particulate matter (PM) flows for pedestrians in road traffic environments via a computation fluid dynamics analysis based on the road width (four and eight-lane) and vegetation configuration (single-, multi-layer planting, and vegetation barrier). Airflow changes due to vegetation influenced PM inflow into the sidewalk. Vegetation between roadways and sidewalks were effective at reducing PM concentrations. Compared to singlelayer planting (trees only), planting structures capable of separating sidewalk and roadway airflows, such as a multi-layer planting vegetation barrier (trees and shrubs), were more effective at minimizing PM on the sidewalk; for wider roads, a multi-layer structure was the most effective. Furthermore, along a four-lane road, the appropriate vegetation volume and width for reducing PM based on the breathing height (1.5 m) were 0.6 m(3) and 0.4 m, respectively. The appropriate vegetation volume and width around eight-lane roads, were 1.2-1.4 m(3) and 0.8-0.93 m, respectively. The results of this study can provide appropriate standards for street vegetation design to reduce PM concentrations along sidewalks.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available