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Effect of traffic tidal flow on pollutant dispersion in various street canyons and corresponding mitigation strategies 被引量:3

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摘要 Increasing traffic emission presents a high risk of exposure to residents in near-road buildings.Traffic tidal flow(TTF)has gradually become one of the most important components of urban traffic congestion.By computational fluid dynamics simulation,the present study examines the airflow,spatial distribution of pollutant concentration,and personal intake fraction(IF_p)of CO in five street canyon structures(shallow,regular,deep,step-up,and step-down street canyons),with non-uniform TTF-induced traffic emission considered.Optimal urban design devices(wind catchers)are subsequently introduced to reduce IF_p.The results suggest that leeward IF_p is far higher in concentration than the windward wall in the shallow,regular,step-up,and step-down street canyons but lower than the windward side in the deep street canyon under different TTF conditions.Moreover,the TTF condition S L(leeward source)/S W(windward source)=3/1 leads to a higher leeward IF_p in the shallow,regular,deep,and step-up street canyons,compared with S L/S W=1/3;however,no significant difference in windward IF_p is found under the different TTF conditions.The highest IF_p and lowest IF_p for both TTF configurations occur in the step-down and shallow street canyons,respectively.Finally,the effect of wind catchers(WCs)varies between the street canyon structures under different TTF conditions.WCs can lead to at least 30.6%reduction in leeward overall average IF_p(<IF_p>)in the shallow,regular,step-up,and step-down street canyons,as well as 12.8%-78.4%decrease in windward<IF_p>owing to the WCs in the regular,deep,step-up,and step-down street canyons.
出处 《Energy and Built Environment》 2020年第3期242-253,共12页 能源与人工环境(英文)
基金 supported by the National Natural Science Foun-dation of China(Grant No.51778511) Hubei Provincial Natural Science Foundation of China(Grant No.2018CFA029) Key Project of ESI Discipline Development of Wuhan University of Technology(Grant No.2017001).
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