Numerical investigation of the pollutant dispersion in the heterogeneous urban settings from rooftop sources
Creators: Kavian Nezhad, Mohammad Reza
Publisher: name: University of Alberta Library
Year: 2024

<p>Exhaust gases emitted from roof-based sources are recognized as one of the primary sources of urban air pollution that could considerably deteriorate both outdoor and indoor air quality. Urban planners frequently use analytical and semi-empirical dispersion models to assess the pollutant distribution field, leading to extremely conservative and less sustainable guidelines in the design process. In this regard, contributing to the effective and efficient passive approaches to control these contaminants, with the aid of urban morphology modifications, has been set as the ultimate goal of this research.Given the limitations and complexities of the experimental investigations and the known weaknesses of the semi-empirical correlations, Computational Fluid Dynamics (CFD) has been selected as the method used in this study. The Mock Urban Setting Tests experiment (or MUST, performed in Utah in 2001) was simulated in this work to test and evaluate various modeling settings and to introduce a well-tested infrastructure to contribute to the &quot;Best-Practice&quot; in reliable modeling of dispersion flow within complex urban geometries. The performance of three widely suggested closure models of standard k-epsilon, RNG k-epsilon, and SST k-omega were assessed with a specific emphasis on the effects of the source locations. This work demonstrates that the relative over-prediction of the turbulence kinetic energy by the standard k-epsilon model counteracts the general under-predictions by time-averaged methods in geometries with building complexes, leading to the least discrepancies with the measurements. A sensitivity study was also conducted to find the optimum turbulence Schmidt number (Sc<em>t), using both the constant and locally variable values.To further improve the accuracy of the numerical predictions, a re-calibration study is conducted to optimize the standard k-epsilon model by incorporating the recommended modeling settings from the previous step. A modified optimization framework based on a genetic algorithm was adapted to alleviate the computational expenses and to further identify ranges for each empirical coefficient, to achieve the most reliable and accurate predictions. A robust objective function was defined, incorporating both the flow parameters and pollutant concentration through several linear and logarithmic measures. The coefficients were trained using the MUST data set, leading to proposed ranges of 0.14 ≤ C</em>mu ≤ 0.15, 1.30 ≤ C<em>epsilon1 ≤ 1.46, 1.68 ≤ C</em>epsilon2 ≤ 1.80, 1.12 ≤ σ<em>epsilon ≤ 1.20, and 0.87 ≤ σ</em>k ≤ 1.00. Using the modified turbulence closure, the fraction of predictions within the acceptable ranges from measurements increased by 8% for pollutant concentration and 27% for turbulence kinetic energy.Employing the assembled infrastructure designed for CFD simulations of atmospheric pollutant dispersion lays the foundation for the primary objective. In the final step, a series of systematic studies aimed to explore the synergistic effects of unique urban morphologies or heterogeneous geometries on turbulent mixing and pollutant diffusion. This research contributes to ongoing efforts to advance urban planning practices, offering a passive approach to control pollutant dispersion from rooftop sources. Additionally, it advances the understanding of pollutant dispersion patterns in the presence of urban non-uniformities.</p>