Amy Kim

Concerns around climate change and the environment have motivated the adoption of low impact development (LID) techniques for urban infrastructure. Permeable pavements are one type of LID technique that do not necessitate land use changes, making them particularly suitable for urban environments. This study aims to estimate the global warming potential (GWP) impact of replacing existing concrete sidewalks with permeable pavement systems through a case study in Vancouver, British Columbia.A consequential process-based life cycle assessment (LCA) is proposed to estimate embodied impacts while accounting for reduced downstream effects on the sewer system (i.e., the emission savings brought about by reduced energy consumption in the sewer system due to reduced runoff volumes). Embodied emissions include those created by material manufacturing and their transport, as well as sidewalk construction and maintenance. Emissions savings from the sewer system are estimated by forecasting precipitation and calculating the reduction in runoff volumes in different sewer system configurations (i.e., combined or separate system, with or without pumping).The results suggest that the use of permeable sidewalks will result in a higher GWP impact than conventional concrete sidewalks, on average, across most contexts for Vancouver, British Columbia. The higher GWP attributed to permeable sidewalks stems from literature-based assumptions regarding their durability; specifically, the model assumes a slightly more frequent reconstruction cycle than conventional concrete. Furthermore, the potential operational savings from reduced runoff are marginalized in the Vancouver context due to British Columbia’s low-carbon energy grid, which limits the emissions offset by reduced sewer processing. The results suggest that, for locations with more carbon intensive energy grids, permeable pavements are potentially attractive from a GWP perspective due to their ability to offset energy requirements associated with the sewer system. As a general guiding rule, the results suggest that the use of permeable sidewalks should be attached to other benefits such as flood control or urban heat reduction rather than solely the reduction in carbon releases to the environment.

View record

This thesis investigates healthcare accessibility in the Lower Mainland of British Columbia, which is a geographic area consisting of the regional districts of Metro Vancouver and the Fraser Valley. The research addresses three key questions: (1) What methods and metrics can be used to measure healthcare accessibility, and how can they be adapted to the Lower Mainland 's urban context? (2) What is the current state and spatial distribution of access to healthcare services in the Lower Mainland? (3) How does accessibility change with demographic factors and under disaster scenarios?The Enhanced Two-Step Floating Catchment Area (E2SFCA) method, adapted with a distance decay function, was employed to measure accessibility across Traffic Analysis Zones (TAZs) in the Lower Mainland using network information provided by TransLink. The analysis incorporated total bed capacity in hospitals with emergency rooms as a proxy for healthcare supply, and used normalized scores to compare the results across several case studies. The scenarios evaluated include a baseline assessment, a focus on senior and employed populations, and disaster simulations such as Disaster Response Routes (DRRs) and bridge closures following earthquakes.Results reveal significant spatial disparities in healthcare accessibility. While central and well-connected areas exhibit high accessibility, peripheral regions, such as Chilliwack and areas east of Abbotsford, face notable disadvantages, particularly for seniors. Disaster scenarios highlight the vulnerability of certain regions, where restricted routes and infrastructure disruptions can severely limit access to healthcare services. Despite the limitations of the network model, which excluded local roads and public transit, the findings underscore critical gaps in healthcare and transportation planning.By providing a detailed spatial understanding of healthcare accessibility, this thesis offers valuable insights for policymakers, healthcare providers, and urban planners in developing inclusive and disaster-resilient systems.

View record

Public transit systems rely on efficient scheduling to keep operating costs in check. To this end, the Vehicle Scheduling Problem (VSP) assigns trips to a fleet of vehicles at minimal operational costs. However, minimizing operating costs can result in schedules that have little buffer time between trips; these schedules are then vulnerable to disruption, as delay can propagate through the network.This thesis investigates a variant of the VSP that minimizes both operational cost and delay cost. We formulate a network flow-based stochastic optimization model that jointly sets planned trip travel times and vehicle schedules to reduce both primary and secondary delay. We evaluate our model with computational experiments on real-world transit data from Victoria, BC. We compare against practical schedules that minimize operating cost alone, or enforce fixed buffer time between trips, or rely on infrastructure improvements to reduce delay; our schedules substantially reduce delay cost with modest increases in operational cost. These improvements are achieved by adjusting travel times to balance operating and delay cost, targeting travel time adjustments for peak trips in peak directions, and pairing trips that naturally allow for buffer time and exploit anti-correlated primary delay structure.

View record

U.S. federal infrastructure spending initiatives, such as the Bipartisan Infrastructure Law (BIL), aim to address infrastructure gaps and promote economic growth. However, in light of the current climate crisis, it has become particularly important to quantify the environmental impact of policies, especially large-scale ones, such as the BIL. This thesis aims to take a first step towards understanding the benefits and consequences of increased infrastructure spending on a national level, by studying the effects of renewal spending on the condition of the U.S. Interstate system and the environment over a 20-year planning horizon. It relies on the U.S. Department of Transportation Highway Performance Monitoring System to characterize the relationship between Interstate highway expenditure, average daily traffic, and pavement condition via an autoregressive distributed lag (ARDL) model. The ARDL model outputs are embedded within a probabilistic life cycle assessment model to quantify the environmental impacts resulting from pavement-vehicle interaction (PVI) as a function of Interstate spending. In addition, an economic input-output life cycle assessment is conducted to compute the embodied environmental impacts associated with Interstate expenditures. The results highlight that increased infrastructure spending is expected to improve the physical condition of the U.S. Interstate system, but at the cost of increasing its environmental releases and global warming impact. Simply put, increased spending improves PVI-related environmental impacts for the Interstate system, but these savings are more than offset by anticipated increases in embodied (e.g., materials) impacts. The results of this work can support decision-makers in developing environmentally-informed infrastructure policy.

View record

This thesis presents a methodology for identifying highly impacted locations on the provincial highway system of British Columbia (BC), Canada, due to disruption events caused by five groups of natural disasters, and for visualizing the degree of impact of these disruptions.Data is obtained from the province’s DriveBC road condition and incident information system. A data parsing procedure is developed to improve data governance. Based on the data provided by DriveBC, natural disaster disruption events occurring on the BC highway network for the years 2017 through 2021 were identified and categorized into the five groups of natural disasters.The impact caused by each disruption event was represented by a score calculated using a weighted linear sum multi-criteria decision analysis (MCDA) model, which uses four criteria to produce an impact score for each event based on a pairwise comparison between each pair of criteria.The Kernel Density Estimation (KDE) for Lines method enables the visualization of the degree of impact of natural disaster disruption events by estimating the density of events weighted by the impact scores of all events found within an array of 50-km by 50-km raster cells. Higher resulting total impact scores are linked to higher impacted highway locations.Highway locations most impacted by events in the five groups were identified and mapped. A top ten list is provided for each map. Connections between the top highway locations and extreme weather events are made when possible.

View record