Evaluation of Vegetation Configuration Models for Managing Particulate Matter along the Urban Street Environment

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 single-layer 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 m3 and 0.4 m, respectively. The appropriate vegetation volume and width around eight-lane roads, were 1.2–1.4 m3 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.

Barrier Trees of Degenerate Landscapes

The heights of energy barriers separating two (macro-)states are useful for estimating transition frequencies. In non-degenerate landscapes the decomposition of a landscape into basins surrounding local minima connected by saddle points is straightforward and yields a useful definition of macro-states. In this work we develop a rigorous concept of barrier trees for degenerate landscapes. We present a program that efficiently computes such barrier trees, and apply it to two well known examples of landscapes.