Urban road greenbelt configuration: The perspective of PM2.5 removal and air quality regulation.

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The establishment of the road green belt (RGB) is an effective means to reduce particle matter (PM2.5) emissions from road traffic. This study tested the ability of 23 common tree species in Shenzhen to reduce PM2.5 concentrations using field investigations and wind tunnel tests. The association between leaf microstructure and individual reduction ability was also analyzed. Finally, the impact of three RGB configurations (i.e., arbor, shrub, arbor+shrub) on road PM2.5 dispersion and deposition was simulated using the ENVI-met three-dimensional aerodynamic model, based on which an optimal RGB configuration was proposed. There were three key findings of the tests. First, the wind speed was the main factor affecting the PM2.5 concentration (54.2%), followed by vehicle flow (27.7%), temperature (14.2%), and time factor (7.6%). Second, the range of dry deposition velocity (Vd) was 0.04-6.4m/s, and the dominant dust-retaining plant species were the evergreen trees, Ficus microcarpa and Ficus altissima, and the evergreen shrubs, Codiaeum variegatum and Fagraea ceilanica. A higher proportion of grooves or larger stomata would increase the probability that the blade would capture PM2.5. Third, the shrub RGB demonstrated the best performance in terms of pollutant dispersion; its PM2.5 concentration at the respiratory height (RH, 1.5m) on the pedestrian crossing was 15-20% lower than the other RGB configurations. In terms of pollutant deposition, the arbor+shrub composite RGB was two-fold better than the other RGB configurations. Moreover, it was more advantageous to plant shrub RGBs in street canyons to achieve a balance between the lowest concentration and the largest deposition of PM2.5 pollutants. The findings of this study will facilitate the RGB configurations with good dust retention ability.