The passenger transportation sector is notoriously difficult to decarbonize. In this thesis, two distinct and novel methodologies to estimate the environmental impact of alternative and conventional transportation technologies are developed.
In Chapter 2, a provincial fleet policy-driven linear programming model is developed to minimize the cost of three passenger vehicle electrification policies in Ontario under a 30% GHG reduction target by 2030. Provincial life-cycle emissions and total-cost-of-ownership associated with policy allocation is estimated. The results highlight that electrification of on-road passenger transportation will not be sufficient to meet the 30% reduction target despite Ontario's low-carbon electricity grid. Instead, reductions of between 24% to 26% are forecasted at an annual cost (for ten years) of between CAD 0.29 to 0.3 billion annually indicating that additional policies are necessary to realize a 30% reduction target.
In Chapter 3, a trip-level vehicle framework is developed to determine under what operating conditions transit buses and passenger cars will be environmentally beneficial across the dimensions of technology, service mode, and power source pathway. The well-to-wheel energy consumption and GHG emissions are simulated for over 450 operating scenarios. Emissions are then normalized through passenger-trip emission thresholds to facilitate equivalent comparison across all dimensions. The results indicate that the most beneficial solution are fuel-cell electric car-share, battery electric car-share, and battery electric bus all powered by low-carbon intensity power sources at average occupancy (7.9-19.7 gCO2e passenger-service-mode-trip-km-travelled-1). Furthermore, transit bus technologies have the potential to reduce up to 2.3 times more GHG per passenger-trip than comparable ride-share passenger cars at average occupancies.
The results of Chapter 2 and 3 highlight that technology alone may not be sufficient to achieve significant GHG reductions; policy which leverage local operating data and target GHG reduction associated with passenger-trips are critical to informing under what conditions a mobility solution is environmentally beneficial. / Thesis / Master of Civil Engineering (MCE) / There is a dire need to evaluate the effectiveness of transportation GHG mitigation policies as alternative mobility solutions are being adopted and the pressure to respond to climate change intensifies. This work evaluates the effectiveness of policy optimization and vehicle-level simulation techniques to inform GHG mitigation decision-making.
A two-step approach is adopted herein. At the strategic level, a cost optimization model for passenger vehicle electrification policies in Ontario is calibrated to identify the optimal allocation of provincial policy to achieve a 30% GHG reduction by 2030. Next, a micro level focuses on the energy consumption of eight vehicle technologies over 450 operational scenarios is simulated and trip-level passenger emissions are estimated to reveal the environmentally beneficial mobility option, corresponding passenger thresholds, and extent of variability associated with local operating conditions.
Overall, optimization and trip-level vehicle simulation can be used to demystify optimal decision-making related to mobility solutions.
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/26948 |
| Date | January 2021 |
| Creators | Soukhov, Anastasi |
| Contributors | Mohamed, Moataz, Civil Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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