SUMMARY

In the last few decades, there has been a surge in urban energy contribution resulting in elevated urban air temperatures. To study the effects of urban heat, numerical modeling of urban thermal environments has seen the rise of several atmospheric modeling software packages, however, there are inherent and unintentional biases introduced by each modeling software package that inhibit validity and accuracy for general engineering use. The main challenges of modeling urban thermal environments are the scale and resolution at which to perform such tasks. Current modeling of urban thermal environments is typically limited to either mesoscale (1 km to 2,000 km) or microscale (<1 km) phenomena. A one-way upstream coupled microscale urban thermal environment simulation is examined and validated. This coupled simulation can provide valuable insights about the flow behavior and energy transport between mesoscale and microscale interactions. The mesoscale to microscale boundary conditions are coupled together using simulated data from the Advanced Research Weather Research and Forecasting Model (WRF-ARW) and assimilating it into Parallelized Large-eddy Simulation Model (PALM). The microscale urban thermal environment simulations are tested for grid sensitivity to variations in model input and control parameters, and then experimentally validated against distributed sensor measurements at the Georgia Tech campus in Atlanta, GA. The validated microscale model is used and expanded upon to develop an open-source framework for coupled multiscale urban thermal environment simulations, which can provide valuable information on two-way atmospheric energy transport between spatial scales. A city-wide multiscale model with over 500,000 building, road, and tree canopy data points parameterizing Atlanta, GA is developed and validated with a spatial scale of 5 m. The validated model was used to perform a parametric study on the implications bulk surface albedo has on the cities anthropogenic heat release in terms of heat flux. The study demonstrates that anthropogenic heat flux for building waste energy accounts for a small part of the total surface heat flux, and a detailed understanding of the components of urban heat (particularly with respect to total surface heat flux) is required to predict and simulate an urban thermal environment. An internet-of-things (IoT) based low-cost sensor network can be used to collect the data necessary to study both Urban Heat Islands (UHI) and air pollution. There are several key challenges associated with an IoT based solution to environmental data monitoring, including packaging and deployment. These challenges are explored by looking at effects the packaging has on the deployed environmental sensors. The findings conclude that the IoT sensors presented are not significantly affected by flow velocities or require advanced packaging designs when paired with street side outdoor digital displays.