Sara Hesse, MSc
MSc Thesis title: Diurnal effectiveness of urban heat mitigation strategies as a function of weather type
Abstract: Extreme heat episodes are projected to increase in frequency and intensity. Commonly applied heat mitigation strategies, including green infrastructure and reflective materials, have the potential to reduce heat exposure. However, there has been limited assessment of these strategies in Toronto, or the modulation of their local climate impacts by weather type and neighbourhood morphology. Using a neighbourhood-resolving (mesoscale) climate model, the urbanized Weather Research and Forecasting (WRF) model, the dependence of heat mitigation cooling efficacy on two aspects is assessed; 1) local built structure, using the local climate zone (LCZ) scheme, and; 2) weather type, using the spatial synoptic classification (SSC). Large increases to rooftop albedo resulted in the greatest daytime reductions in air and surface temperatures, and Humidex. Replacing impervious surfaces with vegetation provided the greatest nighttime reductions of temperature and Humidex. In general, most daytime cooling was found in the Dry Moderate (DM) SSC type. Heat mitigation strategies yielded the greatest cooling when implemented in LCZs with greater impervious fraction.
Charlie Gibbs, MSc
MSc Thesis title: Spatial opportunities and limitations for Southern Ontario specialty crops in current and future climates
Abstract: The development, yield, and quality of specialty crops (i.e., fruit and vegetable crops) are highly influenced by local climate conditions. Climate change presents a challenge to specialty crop cultivation and suitable regions for agriculture are expected to shift. Determining the extent of future suitable agricultural regions will be an important aid for land use planning. Machine learning algorithms, such as random forest, can utilize a wide range of relevant data to predict spatial distributions of suitable agricultural land. This research developed random forest classification models to predict presence/absence of Southern Ontario specialty crops using contemporary climate indices and distribution for each specialty crop (2014-2021). Trained models were applied to ensemble mean climate projections for mid-century (2040-2069) and late-century (2070-2099) time periods and two Representative Concentration Pathways (4.5 and 8.5). Feature importance was computed for each model. Results identify regions where future climate presents opportunities and limitations for specialty crop production.
Tim Jiang, PhD
PhD Thesis title: Simulating adaptation of urban climates to future heat: A multi-outcome assessment
Abstract: Globally, cities face increasing extreme heat, impacting health, comfort and energy use. While projected urban air temperatures have received attention, projections of pedestrian thermal stress are scarce and usually produced by statistical downscaling. Here we assess urban outdoor thermal exposure for projected climate change and urban development scenarios during heatwaves in three cities with contrasting climates (Toronto, Phoenix, and Miami). We present, evaluate, and apply a novel dynamical downscaling methodology, wherein a regional climate and urban canopy model (WRF-BEP-BEM) is used to dynamically downscale atmospheric reanalyses and global climate projections, and a 3-D microscale outdoor heat exposure model (TUF-Pedestrian) is subsequently applied to simulate shortwave and longwave radiation absorption by pedestrians in cities. We find that pedestrians could experience 2 additional hours/day of extreme heat stress in Phoenix and 5.5 additional hours/day of strong heat stress in Toronto under a high-emission scenario. Additionally, building energy simulations reveal that energy used for space cooling would double in Phoenix and triple in Miami. Infrastructure-based heat adaptation strategies may improve comfort, health and energy outcomes, but each strategy has a unique mix of benefits and drawbacks. Therefore, we apply the new multi-scale modelling methodology to assess five heat adaptation strategies (street trees, cool roofs, green roofs, rooftop photovoltaics, and reflective pavements) under contemporary and end-of-century projected climates in terms of three outcomes: outdoor heat stress, energy use for space cooling, and ventilation of air pollutants. Results suggest that no single adaptation strategy benefits all three outcomes. In tropical Miami, shade provision renders street trees the most effective adaptation strategy for reducing outdoor heat stress. In all cities studied, trees reduce heat stress under a high-emissions scenario to contemporary levels, but inhibit urban ventilation of pollutants. Cool roofs reduce heat stress and, among studied cities, are most effective in temperate Toronto. On the other hand, rooftop photovoltaics can generate sufficient power for space cooling but have marginal effects on outdoor heat stress. Reflective pavements are the least effective in terms of these outcomes. Our results support the combination of street trees and rooftop photovoltaic or cool roof implementation across different climates and neighbourhood densities.
Tim Aiello, MSc
MSc Thesis title: Assessment of seasonal urban outdoor thermal exposure in a humid continental climate
Abstract: Many cities experience both extreme heat and cold weather. Pedestrians are exposed to these thermal extremes, causing bodily stress. With growing urban populations, city design contributing to the mitigation of summer heat while reducing winter cold exposure is important. Pedestrian thermal exposure depends on several microclimatic factors, including shortwave and longwave radiation absorption, quantified by the mean radiant temperature (Tmrt). Little research has been conducted on the radiative components of thermal exposure in hot summers and cold winters. We gathered radiation data from urban microclimates in multiple seasons in Guelph, Canada, using a mobile human-biometeorological weather station (MaRTy cart) that applies the six-directional method to determine Tmrt. Datasets were compared to examine the drivers of thermal exposure and recommend mitigation strategies. In summer, shade is the primary factor that reduces daytime heat exposure. In winter, reduced shade alleviated cold exposure, with snow providing daytime benefits from increased solar reflections.
Jacob Lachapelle, MSc
MSc Thesis title: A microscale 3-D model of urban outdoor thermal exposure (TUF-Pedestrian): Impacts of street tree configuration
Abstract: Street trees provide effective cooling to urban pedestrians during hot weather. However, existing simulation tools may not be sufficient to inform optimization of street tree placement for this purpose. A microscale three-dimensional (3-D) urban radiation and energy balance model, TUF-Pedestrian, was developed to simulate pedestrian radiation exposure and study urban tree placement. TUF-Pedestrian was set up to simulate shortwave and longwave radiative impacts of trees on their surroundings. In addition, radiation absorption from a pedestrian was considered, permitting calculation of a summary metric of radiation exposure: the mean radiant temperature (TMRT). Model evaluation demonstrated that TUF-Pedestrian accurately simulates incoming directional radiative fluxes on pedestrians and associated TMRT in urban environments with and without tree cover. Subsequently, the model is applied to understand the variation of pedestrian TMRT as a function of different street tree configurations in hot weather. Results suggest it is important to consider street orientation and latitude (solar angle) in terms of the placement of street trees relative to pedestrian walkways. Importantly, additional radiant cooling of pedestrians during hot afternoons per unit addition of tree cover decreases modestly as existing tree cover increases. Optimizing street tree configuration in urban canyons for pedestrian thermal comfort is a complex task that can be supported with simulation tools such as TUF-Pedestrian.