Along the life cycle of oil sands-derived products, variability in terms of resource heterogeneity, operating decisions, as well as extraction and processing technologies affect a project’s GHG intensity. Previous LCAs that have quantified emissions from bitumen production and processing have not captured all sources of variability along the life cycle, either by including only some projects or employing simplified refinery modeling or modeling refining only of some crude types. Three studies are completed to address this literature gap.

In the first study, a statistically-enhanced version of the GreenHouse gas emissions of current Oil Sands Technologies model (GHOST-SE) is developed. Median lifetime GHG intensities for projects producing synthetic crude oil (SCO) range from 89-137 kg CO2eq/bbl SCO and for the project producing dilbit are 51 kg CO2eq/bbl dilbit. Projects show significant temporal variability. No project reaches steady-state in terms of GHG intensity. Next, GHOST-SE is integrated with a pipeline transportation model (COPTEM) and a refinery model (PRELIM) and

variability in life cycle emissions intensities are quantified. Allocation to products affects the relative GHG intensities of different projects (e.g., Project 1 has lowest median life cycle GHG intensity per MJ gasoline but highest per MJ diesel). These results demonstrate that there is no

representative project or crude type, even across projects within the same pathway (e.g., Mining SCO pathway).

In the final study, expert elicitation methods are employed to assess the potential role for emerging technologies to decrease upstream GHG intensity between 2014 and 2034. Experts surveyed do not expect emerging technologies to play a major role in reducing upstream oil

sands energy consumption but are more likely to be applied to access marginal resources not economic with current production technologies.

Accurate characterizations of the emissions from the life cycle of oil-sands derived fuels has the potential to assist oil sands operators and policymakers to:​ set benchmarks, develop projections of future emissions, and identify opportunities for GHG intensity reductions along the life cycle of the fuel. The findings of this thesis can also inform operators and policymakers about the potential unintended consequences of policy decisions.