Modeling the impact of large-scale solid mass transfers on the gravity field

The focus of this thesis is to explore and quantify the response of large-scale solid mass transfer events on satellite-based gravity observations. The gravity signature of large-scale solid mass transfers has not been deeply explored yet; mainly due to the lack of significant events during dedicated satellite gravity missions‘ lifespans. In light of the next generation of gravity missions, the feasibility of employing satellite gravity observations to detect submarine and surface mass transfers is of importance for geoscience (improves the understanding of geodynamic processes) and for geodesy (improves the understanding of the dynamic gravity field). The aim of this thesis is twofold and focuses on assessing the feasibility of using satellite gravity observations for detecting large-scale solid mass transfers and on modeling the impact on the gravity field caused by these events. A methodology that employs 3D forward modeling simulations and 2D wavelet multiresolution analysis is suggested to estimate the impact of solid mass transfers on satellite gravity observations. The gravity signature of various submarine and subaerial events that occurred in the past was estimated. Case studies were conducted to assess the sensitivity and resolvability required in order to observe gravity differences caused by solid mass transfers. Simulation studies were also employed in order to assess the expected contribution of the Next Generation of Gravity Missions for this application.

Applying life cycle assessment to analyze the environmental sustainability of public transit modes for the City of Toronto

One challenge related to transit planning is selecting the appropriate mode: bus, light rail transit (LRT), regional express rail (RER), or subway. This project uses data from life cycle assessment to develop a tool to measure energy requirements for different modes of transit, on a per passenger-kilometer basis. For each of the four transit modes listed, a range of energy requirements associated with different vehicle models and manufacturers was developed. The tool demonstrated that there are distinct ranges where specific transit modes are the best choice. Diesel buses are the clear best choice from 7-51 passengers, LRTs make the most sense from 201-427 passengers, and subways are the best choice above 918 passengers. There are a number of other passenger loading ranges where more than one transit mode makes sense; in particular, LRT and RER represent very energy-efficient options for ridership ranging from 200 to 900 passengers. The tool developed in the thesis was used to analyze the Bloor-Danforth subway line in Toronto using estimated ridership for weekday morning peak hours. It was found that ridership across the line is for the most part actually insufficient to justify subways over LRTs or RER. This suggests that extensions to the existing Bloor-Danforth line should consider LRT options, which could service the passenger loads at the ends of the line with far greater energy efficiency. It was also clear that additional destinations along the entire transit line are necessary to increase the per passenger-kilometer energy efficiency, as the current pattern of commuting to downtown leaves much of the system underutilized. It is hoped that the tool developed in this thesis can be used as an additional resource in the transit mode decision-making process for many developing transportation systems, including the transit systems across the GTHA.