Numerical investigations on urban roadside vegetation for efficient mitigation of airborne ultra-fine particles pollution: Model development, validation and implementation

Abstract

Urban traffic-released ultra-fine particles (UFPs) significantly threats human health due to their distinctive composition/size and high toxicity. The roadside vegetation has potential to effectively purify UFPs. Optimal urban vegetation design relies on reliable prediction of UFPs motion and purification. The existing models mainly focused on vegetation removal of PM_2.5/PM₁₀, while less attention was paid to UFPs. Therefore, the current study proposed a turbulence-induced particle deposition model to predict the removal of size-dependent UFPs by roadside vegetation. This model simultaneously incorporated air turbulence characteristics, particle size, leaf area density (LAD), and surface roughness into UFPs removal simulation. Experimental particle size-dependent data from literature was utilized for model validation, and relative errors were below 7 %. Then this validated numerical model was utilized to optimize urban roadside vegetation design. Compared with the scene without roadside vegetation, utilization of “trees+shrubs” can decrease 57 %–95 % of UFPs concentration (1–100 nm) at sidewalks area on the downstream side of urban road, while large UFPs (> 50 nm) locally accumulated on the upstream side. The UFPs concentrations in the whole target zone decreased by 11 %–78 % due to vegetation purification. The newly proposed numerical model can be used for sustainable design of roadside vegetation to effectively mitigate UFPs pollution.