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ARTICLE

Pollution Dispersion in Urban Street Canyons with Green Belts

Xiaoxuan Zhu1, Xueyan Wang2, Li Lei1,*, Yuting Zhao1
1 School of Energy and Power Engineering, Shandong University, Jinan, 250061, China
2 CNPC Ji Chai Power Equipment Company, Jinan, 250306, China
* Corresponding Author: Li Lei. Email:
(This article belongs to this Special Issue: Numerical Methods in Engineering Analysis, Data Analysis and Artificial Intelligence)

Computer Modeling in Engineering & Sciences 2022, 132(2), 661-679. https://doi.org/10.32604/cmes.2022.020427

Received 25 November 2021; Accepted 27 December 2021; Issue published 15 June 2022

Abstract

In this study, numerical simulations were used to explore the effects of roadside green belt, urban street spatial layout, and wind speed on vehicle exhaust emission diffusion in street canyon. The diffusion of different sized particles in the street canyon and the influence of wind speed were investigated. The individual daily average pollutant intake was used to evaluate the exposure level in a street canyon microenvironment. The central and leeward green belts of the road were the most conducive to the diffusion of pollutants, while the positioning of the green belts both sides of a road was least conducive to the diffusion of pollutants. Pollutant levels increased with increasing canopy height, canopy width, and decreasing tree spacing, with optimal values of 12 m, 7 m, and 0.4 H, respectively. This provides protection from pollution for low-rise residents and pedestrians. The results presented here can be used to improve the air quality of the street microenvironment and provide a basis for the renovation of old street buildings.

Keywords

Street canyons; roadside green belts; pollutant exposure; particulate matter; fluent software

Cite This Article

Zhu, X., Wang, X., Lei, L., Zhao, Y. (2022). Pollution Dispersion in Urban Street Canyons with Green Belts. CMES-Computer Modeling in Engineering & Sciences, 132(2), 661–679.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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