Turbulence is a significant factor in near-road air quality, as it affects the initial dilution, dispersion, and the ultimate fate of pollutants. This study used computational fluid dynamics simulations to model the turbulent kinetic energy (TKE) on roadways, focusing on vehicle-induced turbulence. TKE was shown to decay with different power-law exponents depending on vehicle types; vehicle speeds and winds affect TKE; and thermal impacts are negligible. It was found that TKE is superimposed for vehicles in series; TKE does not dissipate far laterally, and the side-by-side interactions are not significant regardless of the directions. Thus, TKE for different traffic compositions may be expressed as a sum of the contribution from each type of vehicle. Insights gained in this study may enable the quantification of TKE for various traffic scenarios based on TKE values of single vehicle of different types, and simplify the TKE estimations in regional air quality models.

Turbulence is a significant factor in near-road air quality, as it affects the initial dilution, dispersion, and the ultimate fate of pollutants. This study used computational fluid dynamics simulations to model the turbulent kinetic energy (TKE) on roadways, focusing on vehicle-induced turbulence. TKE was shown to decay with different power-law exponents depending on vehicle types; vehicle speeds and winds affect TKE; and thermal impacts are negligible. It was found that TKE is superimposed for vehicles in series; TKE does not dissipate far laterally, and the side-by-side interactions are not significant regardless of the directions. Thus, TKE for different traffic compositions may be expressed as a sum of the contribution from each type of vehicle. Insights gained in this study may enable the quantification of TKE for various traffic scenarios based on TKE values of single vehicle of different types, and simplify the TKE estimations in regional air quality models.

This thesis has two major purposes: (1) to investigate the impact carshave on Particulate Matter (PM) level in a limited area and (2) to demonstratethrough Computational Fluid Dynamics (CFD) the possibility toclean a limited area of PM with a system installed on a car.This thesis was performed in collaboration with Volvo Car Corporation(VCC) at Torslanda, Göteborg. All experimental data was sampledat three occasions: 24th of February, 14th of March and 3rd of June andwere compared to similar recent studies for verication. Computer calculationwere conducted in July and August with experimental data asinitial conditions. ANSYS v16.0 Fluent Meshing and ANSYS v16.0 Fluentwere used as computational software to set up and calculate the problem.The result of the experiments shows that with increased number ofcars there is an increased value of PM. It also shows that a cars ventilationsystem can be used to collect small PM. Result from CFD derivationsdisplayed that a cleaning system mounted in a car will decrease number ofPM with 5-20% in 250 seconds in a closed domain and 4% in 135 secondsin a open domain.

<p>A three-dimensional computational fluid dynamics (CFD) model has been developed to simulate the distribution of automobile emissions on and near a highway. A variety of k-ε turbulence models were adopted to simulate the turbulence flow, and a non-reaction species model was coupled to simulate the dispersion of emissions. The models were first validated by comparing velocity profiles and normalized emission concentration with wind tunnel experiments, and good agreement was observed. Next, further simulation and analysis revealed that T-shaped noise barriers could reduce more emissions concentration in downstream areas than rectangular noise barriers; however, the noise barrier shape effects on the dispersion of emissions were also influenced by inflow conditions. Thirdly, the traffic flow conditions on the highway made a difference to the dispersion of emissions. Automobile wakes not only existed behind vehicles but also induced turbulence on adjacent lanes, causing more emissions on the highway. Low traffic speed, such as congestion, would result in more emissions remaining on the highway as well. At last, vehicle body shapes modified the flow patterns by their slant angles and heights. Vehicles with slant angles on both front and rear sides had the least concentration of emissions at the center of the highway.</p>