Measuring and modeling the effects of green barriers on the spatial distribution of fine particulate matter at roadside

Xin Chen, Jie Wu,Wenbin Yang,Zhanyong Wang, Shuting Chen,Xisheng Hu,Kaifa Lu, Zhongmou Fan, Mei Lin, Pu Chen

URBAN CLIMATE(2023)

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摘要
Green barriers are regarded as a viable strategy for improving road air quality, and yet there lacks consensus regarding how they can actively regulate air pollution, particularly under dynamic traffic, meteorology and built environments. To address this, field measurements were conducted to assess the levels of fine particulate matter (PM2.5) before and after green barriers along an urban expressway. The measurements revealed distinct spatial attenuation patterns in vegetationrich and vegetation-sparse areas. Specifically, the first-layer green barriers were found to significantly reduce PM2.5 levels by 8.4-9.3% in the vegetation-rich area. The magnitude of PM2.5 reduction at all locations distant from the motorway varied depending on the wind direction. On average, there are reductions of 7.8% (winter) and 13.0% (summer) in PM2.5 levels under crossroad winds. A validated hybrid model further demonstrated the significant impact of green barriers on pollutant diffusion, showing an unstable spatial variation trend under changing wind conditions. A combination of trees and hedgerows with a tree spacing of 3 m and obovate or spherical tree crowns proved effective in reducing roadside pollution. Simulations also suggested significant pollution reduction when considering appropriate spatial distribution of traffic flow and solid barrier alongside green barriers. These findings underscore the potential of combining green barriers with diverse measures to maximize the reduction of traffic-related pollution at roadside.
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关键词
Air pollution,Spatial variation,Field measurement,Numerical simulation,Road greenbelt
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