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Chinese Journal of Ecology ›› 2021, Vol. 40 ›› Issue (12): 4044-4052.doi: 10.13292/j.1000-4890.202111.036

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Numerical simulation on the effects of street trees on PM2.5 concentration in street canyon.

LI Ping-ping1,2, MIAO Chun-ping1,3, CHEN Wei1,2,3, HU Yuan-man1,2, HE Xing-yuan1,2,3*   

  1. (1CAS- Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; 2University of Chinese Academy of Sciences, Beijing 100049, China; 3Shenyang Arboretum, Chinese Academy of Sciences, Shenyang 110016, China).
  • Online:2021-12-10 Published:2022-05-10

Abstract: The pollution of atmospheric particulate matter in urban human settlements is one of the major environmental problems faced by human beings. Street canyon is one of the most important space forms and characteristics of modern cities, with the highest frequency of utilization, the most serious pollution by automobile exhaust, and the highest population density. The geometry of urban street canyons plays a crucial role in the dispersion of atmospheric particulate matters. Here, we quantified the impacts of street trees on the distribution of atmospheric particulate matter PM2.5 in the street canyons of Shenyang, China. Meteorological parameters and distribution of street trees were used in ENVI-met software with three aspect ratios (H/W=0.5, 1 and 2), three street canyon directions (NE-SW, NW-SE, E-W), two kinds of street trees (poplar and pine). The diurnal variation of PM2.5 showed a trend of “two peaks and two valleys”. The aspect ratio of street canyons had a significant effect on the concentration of PM2.5, with the highest values in street canyons with an aspect ratio of 1. However, there were obvious differences in the PM2.5 of different types of street trees under street canyons in the same direction and the same aspect ratio. Our results suggest that street trees have negative effects on the reduction of atmospheric fine particulate matters at pedestrian heights in the street canyons.

Key words: street tree, ENVI-met, street canyon, PM2.5, wind.