A CFD Study of Pollution Dispersion in Street Canyon and Effects of Leaf Hair on PM2.5 Deposition
According to the United Nations, 55% of the world's population currently lives in urban areas and which is projected to increase to 67% by 2050. Thus, it is imperative that effective strategies are developed to mitigate urban pollution. Complementing field experiments, computational fluid dynamics (CFD) analyses are becoming an effective strategy for identifying critical factors that influence urban pollution and its mitigation. This thesis focuses on two scales of the urban micro-climate environment: (i) evaluation of LES simulations with a simplified grid for modeling pollution dispersion in a street canyon and (ii) investigation of the effects of leaf surface micro-characteristics, wind speed, and particle sizes on the dry deposition of fine particulate matter (PM2.5).
The first of these studies focuses on reproducing the pollution dispersion in a street canyon measured in a wind tunnel at Karlsruhe Institute of Technology (KIT), Germany. A simplified grid with the Large Eddy Simulations (LES) approach for canyon ratio W/H = 1 is proposed with the goal to reduce the computational cost by eliminating the need to model the entire canyon while striving to preserve the mixing induced by individual jets used to model vehicle emission in the experiment. LES is also capable of providing transient flow field and pollution concentration data not available with widely-used steady approaches such as RANS. The time-dependent information is crucial for pollution mitigation since pedestrians are usually exposed to pollution on a short-time basis.
The predictions are in satisfactory agreement with the experiment for W/H = 1, yielding the Pearson correlation coefficient R = 0.81, with better performance near the leeward wall. Due to the small span modeled, three-dimensional instabilities fail to develop which could probably explain the overprediction of pollution concentration near ground level. However, other LES investigations where the full canyon was modeled also observed over-predictions. The use of a discrete emission source was not observed to provide benefits. The current model could be further improved by using a larger spanwise domain with a continuous line source to allow large wavelength instabilities to develop and increase turbulent diffusion.
The second part of this thesis investigates the impact of trichome morphology and wind speed on the deposition of 0.3 μm and 1.0 μm particles on leaves. Using the one-way coupling approach to predict the fluid-particle interactions with the assumption that all particles that impact the leaf or trichome surface deposit, trichomes of 5 μm and 20 μm in diameter are modeled as equally spaced and uniform cylinders on an infinitely large plane.
The results show that trichome diameter, density, and wind speed have a favorable impact on deposition velocity. Comparing to the smooth leaf, the presence of the thicker 20 μm hairs increases the deposition velocity by 1.5 – 4 times, whereas, the presence of short 5um trichomes reduces the deposition by 15 - 45%. Increasing trichome height from H/D = 20 to 30 shows benefits for the thinner trichomes but lowers the deposition for the densely packed thicker trichomes. Less aerosol deposition is also observed when the particle diameter increases from 0.3 μm to 1.0 μm.
Due to the non-uniform contributions of these various traits, a non-dimensional ratio Rhp is proposed to model the aerosol deposition on leaf surface at wind speed of 1 m/s which yields a satisfactory linear correlation coefficient of 0.89 for 0 < R_hp < 0.3.
Comparing to other published field and wind tunnel experiments conducted on a much larger scale, the deposition velocities predicted are at the lower end (U_dep^* = 0.002 to 0.012 cm/s) because of the idealized conditions. Nonetheless, the results still offer valuable insight into the effects of trichome morphology on pollutant deposition in isolation from other macro-factors.