Expectations and drivers of future greenhouse gas emissions from Canada's oil sands: An expert elicitation. (January 2017) - McKellar, Jennifer M.; Sleep, Sylvia; Bergerson, Joule A.; MacLean, Heather L.
Abstract: The greenhouse gas (GHG) emissions intensity of oil sands operations has declined over time but has not offset absolute emissions growth due to rapidly increasing production. Policy making, decisions about research and development, and stakeholder discourse should be informed by an assessment of future emissions intensity trends, however informed projections are not easily generated. This study investigates expected trends in oil sands GHG emissions using expert elicitation. Thirteen experts participated in a survey, providing quantitative estimates of expected GHG emissions intensity changes and qualitative identifications of drivers. Experts generally agree that emissions intensity reductions are expected at commercially operating projects by 2033, with the greatest reductions expected through the use of technology in the in situ area of oil sands activity (40% mean reduction at multiple projects, averaged across experts). Incremental process changes are expected to contribute less to reducing GHG emissions intensity, however their potentially lower risk and cost may result in larger cumulative reductions. Both technology availability and more stringent GHG mitigation policies are required to realize these emissions intensity reductions. This paper demonstrates a method to increase rigour in emissions forecasting activities and the results can inform policy making, research and development and modelling and forecasting studies. Highlights: Expert elicitation used to investigate expected trends in oil sands GHG emissions. Overall, emissions intensity reductions are expected at commercial projects by 2033. Reductions are expected due to both technology changes and process improvements. Technology availability and more stringent GHG policies are needed for reductions. Method used increases rigour in emissions forecasting, and results inform policy.