Numerical Investigation on Dynamic Impact of Moving Vehicles on Airflow and Pollutant Dispersion


Student thesis: Doctoral Thesis

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Awarding Institution
Award date11 Jul 2018


The problems associated with urban atmospheric pollution have garnered increasing interests during the past decades owing to the hazardous implications on human health. Vehicle emission is one of the primary sources of the anthropogenic atmospheric pollutants in urbanized cities, especially at those areas where population and traffic densities are relatively high. However, it is still an open question that how the moving vehicles, which pollute the air in urban environments, would at the same time contribute to the additional ventilation effect. This study aims to identify the basic mechanisms of the dynamic impact induced by the moving vehicles.

Innovations are made in the wind tunnel experiments in order to realize the vehicle movement and pollutant discharging simultaneously. The wind tunnel test section is modified to accommodate the MMR, on which the scaled vehicle model is mounted and fired across the test section under control. Both the time-averaged and time-dependent flow variables (airflow velocity magnitude and tracer gas concentration) are collected for the numerical model development and validation.

The Standard k-ɛ Model for the airflow turbulence, the Species Transport Model for the tracer gas dispersion, as well as the Dynamic Mesh Model for the vehicle movement are employed based on the FLUENT commercial software. By comparing with the wind tunnel measurements and the published data from literatures, the performances of the numerical models are validated. Dynamic impacts of the moving vehicles on the airflow and pollutant dispersion on two typical urban units—the open roadway and the street canyon are numerically investigated.

The “propelling effect”, the “wake effect”, as well as the “recovery process” are identified as the three basic mechanisms of the vehicle-induced dynamic impact. This leads to continuous interactions between the ambient wind and the moving vehicles, generating the secondary airflow and additional ventilation effect strong enough to promote the pollutant mixing and dispersion consequently. Relative motion between vehicles will create complex disturbances by the mutual interferences. Within the semi-confined street canyon environment, the combined effect of “propelling” and “wake” can be regarded as an equivalent “piston effect”.

Detail effects of some influencing factors, such the ambient wind speed, the absolute and relative speeds of moving vehicles, the number of moving vehicles, the traffic type (one-way or two-way), the geometrical configuration of the street canyon, as well as the positions of monitoring sites, are analysed in this study. Generally, the strong wind will suppress the “propelling effect” but enhance the “wake effect”. Vehicle running with fast speed will strengthen the “propelling effect” but attenuate the “wake effect”. Receptors are prone to high exposure risks when the vehicles drive with slow speed under the calm wind condition. In the street canyon, the “piston effect” created by the moving vehicles will be reinforced in the one-way traffic but get offset in the two-way traffic. The geometrical configuration of the street canyon is another decisive factor. Nature ventilation is less effective in the deep street canyon than the uniform street canyon, resulting in the relatively stronger dynamic impact and higher concentration of vehicle exhaust pollutant in the deep street canyon.

Transient fluctuations of airflow velocity magnitude and gaseous pollutant concentration induced by the moving vehicles will decay with the increase of monitoring distance. Receptor close to the moving path of vehicles suffers from a relatively stronger dynamic impact. However, enhanced vertical dispersion with potential exposure risk is figured out at the upper level in the deep street canyon, suggesting the advantages of the dynamic simulation method.