The mitigation strategy of automobile generated fine particle pollutants by applying vegetation configuration in a street-canyon

Abstract

Urban vegetations are widely used as one of the mitigation approaches to combat the public health threat from air particulate matter (PM) pollution for urban residents. However, vegetation effect at the points of interest (e.g. leeward wall, windward wall, pedestrian-level) in street-canyon from different vegetation configurations on the air quality is still not well established. We, therefore, used the numerical simulation approach to evaluate vegetation effect (VE) for different vegetation configurations (VCs) (e.g. tree or tree-shrub plantings in two sides and either side of windward or leeward) with several tree species on the traffic-originated PM pollutants in a street-canyon under a perpendicular wind. The total VE varied from −4.0% to 20.6% while pedestrian-level VE from −3.5% to 15.4% depending on different VCs. Cypress species have better total VE varying from 3.5% to 11.5% and pedestrian-level VE from 4.8% to 10.9% than the other species for same VC due to its higher deposition velocity. For those only trees used cases, the best VEs (pedestrian-level VE: 3.3%–10.9%; total VE: 2.1%–11.5%) were found on the leeward side planting where is closer to the higher polluted domain and had less obstructions for wind movement. We found that two sides planting of enhanced tree-shrub configuration by Cypress in the street-canyon was an optimal strategy to improve the total VE by 19.3%–20.6% and pedestrian-level VE 14.1%–15.4%, as well as mitigate the highly concentrated PM in the street center. The VE for the leeward wall was significantly correlated with aerodynamic parameter (CdLAD) (P < 0.001) while VEs for the windward wall and pedestrian level with deposition parameter (LADvd) (P < 0.001). Clearly, street-canyon air quality can be improved by making good use of pressure loss coefficient of vegetation to alter pollutants distribution and selecting vegetation with high deposition velocity to filter more pollutants. Our research provides insights for urban planners and designers to develop the best management practices of urban forestry.