Influence of Meteorological Conditions on Pollutant Dispersion in Street Canyon

Zhang, Hao; Xu, Tiantian; Zong, Yuzhao; Tang, Huajun; Liu, Xueting; Wang, Yuancheng

doi:10.1016/j.proeng.2015.09.047

Cited by 27 publications

(9 citation statements)

References 4 publications

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“…In urban street canyons, surrounding built-up environment around roads can obstruct the natural wind flows and result in either reducing or increasing atmospheric advection and air pollution dispersion depending mainly on the wind direction and position on the street (Vardoulakis et al, 2003). For example, high concentration of pollutants were observed on the leeward side of street canyons under perpendicular wind conditions (Afiq et al, 2012;Zhang et al, 2015). Close to waterways, the wind speed may increase (Ruel et al, 1998) due to little obstruction to wind flows caused by built-up urban structures and consequently favouring the dispersion of pollutants.…”

mentioning

confidence: 99%

Impact of route choice and period of the day on cyclists' exposure to black carbon in London, Rotterdam and São Paulo

Brand

Kumar

Damascena

et al. 2019

Journal of Transport Geography

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mentioning

confidence: 99%

Impact of route choice and period of the day on cyclists' exposure to black carbon in London, Rotterdam and São Paulo

Brand

Kumar

Damascena

et al. 2019

Journal of Transport Geography

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“…These results illustrate that a breeze may not contribute to the diffusion of PM but rather might increase its concentration. Zhang et al (2015) found that pollutant concentrations were much higher on the leeward side of street canyons than on the windward side. On the experiment days, the weather was fine to reduce the influence of drastic changes of wind.…”

Section: Correlation Analysis Between Influencing Factors and Pm 25 mentioning

confidence: 97%

PM2.5 concentrations in the greenbelt near the Lin’an toll station of the Hang Rui expressway and related influencing factors

Shao

et al. 2019

Atm.

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Las vías rápidas se están desarrollando con gran celeridad en China y junto con ellas la contaminación por tráfico, que es una de las mayores fuentes de contaminación urbana. En este estudio se eligió como área de muestreo el cinturón verde ubicado en la zona de amortiguamiento cercana a la estación de peaje Lin'an en la autopista Hang Rui. Se seleccionaron cinco puntos verticales a lo largo de la carretera Qianjin a distancias de 0, 15, 30, 45 y 60 m para monitorear las concentraciones de PM 2.5 y conocer tanto sus patrones de variaciones como los factores que influyen en ellos. Los resultados mostraron que durante la primavera (marzo, abril y mayo) las concentraciones promedio de PM 2.5 en el cinturón verde fueron de 32.56 ± 22.51, 77.71 ± 32.11 y 64.15 ± 29.00 μg m-3 , respectivamente. La categorización de las concentraciones en diferentes puntos de monitoreo en el mismo periodo fue de 0 > 15 > 60 > 30 > 45 m. Las concentraciones promedio en invierno (noviembre y diciembre de 2017, y febrero de 2018) fueron de 33.56 ± 9.34, 60.78 ± 17.67 y 124.71 ± 43.19 μg m-3 , respectivamente. Sin embargo, la categorización de las concentraciones en diferentes puntos de monitoreo mostró algunas diferencias. Con excepción del punto de muestreo ubicado a 0 m, las concentraciones de PM 2.5 en los otros cuatro puntos fueron superiores en invierno que en primavera. La tasa de reducción a una distancia de 45 m alcanzó su máximo tanto en primavera como en invierno. Las concentraciones de PM 2.5 tuvieron una correlación significativa con factores meteorológicos, la estructura de la comunidad vegetal y el flujo de tráfico; asimismo, tuvieron una correlación negativa con la temperatura, correlación positiva con la humedad relativa, y correlación no significativa con la velocidad del viento. Las correlaciones de PM 2.5 con la densidad y el grado de porosidad de la cubierta vegetal difirieron de manera considerable como resultado de la estacionalidad, y las concentraciones se correlacionaron significativamente con la densidad del flujo de tráfico, especialmente en presencia de camiones pesados.

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“…Since the time-varying boundary conditions in the calculation domain of STAR-CCM+ are obtained from the WRF model, the simulation performance of the WRF model has an important influence on the STAR-CCM+ simulation results. The wind has an important influence on the transport of air pollutants in the area (Zhang et al, 2015). Figure 4 shows the hourly wind observations and simulations at the BSC monitoring site in January 2019.…”

Section: Model Evaluationmentioning

confidence: 99%

Development and application of a street-level meteorology and pollutant tracking system (S-TRACK)

et al. 2022

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Abstract. A multi-model simulation system for street-level circulation and pollutant tracking (S-TRACK) has been developed by integrating the Weather Research and Forecasting (WRF), the STAR-CCM+ (computational fluid dynamics model – CFD), and the Flexible Particle (FLEXPART) models. The winter wind environmental characteristics and the potential contribution of traffic sources to nearby receptor sites in a city district of China are analysed with the system for January 2019. It is found that complex building layouts change the structure of the wind field and thus have an impact on the transport of pollutants. The wind speed inside the building block is lower than the background wind speed due to the dragging effect of dense buildings. Ventilation is better when the dominant airflow is in the same direction as the building layout. Influenced by the building layout, the local circulations show that the windward side of the building is mostly the divergence zone, and the leeward side is mostly the convergence zone, which is more obvious for high buildings. With the hypothesis that the traffic sources are uniformly distributed on each road and with identical traffic intensity, the potential contribution ratios (PCRs) of four traffic sources to certain specific sites under the influence of the street-level circulations are estimated with the method of residence time analysis. It is found that the contribution ratio varies with the height of the receptor site. As a result of the generally upward motion in the airflow, the position with the greatest PCR from the four road traffic sources is located at a certain height which is commonly influenced by the distance of this location from the traffic source and the background wind field (about 15 m in this study). The potential contribution of a road to one of the receptor sites is also investigated under different wind directions. The established system and the results can be used to understand the characteristics of urban wind environment and to help the air pollution control planning in urban areas.

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Influence of Meteorological Conditions on Pollutant Dispersion in Street Canyon

Cited by 27 publications

References 4 publications

Impact of route choice and period of the day on cyclists' exposure to black carbon in London, Rotterdam and São Paulo

Impact of route choice and period of the day on cyclists' exposure to black carbon in London, Rotterdam and São Paulo

PM2.5 concentrations in the greenbelt near the Lin’an toll station of the Hang Rui expressway and related influencing factors

Development and application of a street-level meteorology and pollutant tracking system (S-TRACK)

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