Oil sands GHG lifecycle study using operating data finds lower emitting oil sands cases outperform higher emitting conventional crude cases; a call for more sophisticated tools and reporting
A new well-to-wheel (WTW) lifecycle analysis (LCA) by a team from the University of Calgary and the University of Toronto of greenhouse gas (GHG) emissions from transportation fuels produced from Canadian oil sands finds that, on a WTW basis, lower emitting oil sands cases can outperform higher emitting conventional crude cases.
The LCA, reported in the ACS journal Environmental Science & Technology, is the first based on confidential operating data from oil sands projects, the authors said. The wide range of potential emissions intensities for both oil sands and conventional crudes suggests that treating all oil sands or all conventional crudes as having the same emissions may lead to unintended consequences, according to the team. In addition, they note, the emissions associated with all of the petroleum sources will continue to change over time (e.g., a transition to heavier conventional oil, technology improvements, deteriorating reservoir conditions as the oil sands resource is further developed).
Their observations reinforce the need for an integrated model to evaluate a range of technologies, pathways, and products using a consistent set of assumptions.
Jurisdictions implementing LCFSs [Low Carbon Fuel Standards] have elevated the importance of getting life cycle carbon intensity values for fuel pathways “right”. Most prominent is California’s LCFS that requires a reduction in the average fuel carbon intensity of the State’s transportation fuels of at least 10% by 2020 which will be complicated by the overlapping ranges of emissions associated with oil sands and conventional crude pathways. WTW emissions for pathways vary by more than ±10% (e.g., there are differences of 28%, 27%, and 23% between the lower and upper WTW emissions results for SAGD, surface mining, and conventional crude, respectively).
GHG emissions of the oil sands should be put into perspective considering the full set of WTW activities and, more broadly, emissions from all sectors of the economy. Vehicle operation (i.e., fuel combustion) comprises 64−74% of WTW emissions in our oil sands pathways. Even a 50% reduction in WTT emissions from, for example, the SAGD synbit pathway would only reduce WTW emissions by 16−26%. Tackling emissions from the personal transportation sector requires a transition to low carbon fuels/energy carriers, increasingly efficient vehicles, and changes in consumer/driver behavior. Actions to lower GHG intensity must be prioritized by efficiency ($/t CO2eq reduced) and effectiveness.—Bergerson et al.
Existing LCA studies of oil sands-derived fuels are not sufficient to characterize the emissions performance of the industry due to their reliance on limited (and often low quality) publicly available data, inconsistency in boundary definitions, and limited transparency of the majority of studies, Bergerson et al. suggest. They call for WTW emissions estimates for oil sands pathways that employ a consistent method and utilize operating data from current projects so as better to inform environmental policies, and to enable improved management of emissions from the industry.
The researchers developed GHOST—the GreenHouse gas emissions of current Oil Sands Technologies model—to address those issues. GHOST is the first oil sands life cycle-based model to be based on confidential data from a set of operating projects, and the model’s development was informed by industry, government, and academic technical experts, according to the authors. GHOST accounts for the GHG emissions associated with the recovery, extraction, dilution, transportation, and upgrading of bitumen, quantifying emissions associated with the activities up to the refinery entrance gate (well-to-refinery entrance gate, WTR).
For the full WTW modeling, they combined the WTR results from GHOST with relevant downstream activities (refining, fuel delivery, vehicle refueling, and vehicle use). Refining estimates are taken from a consulting study by TIAX contracted by the Alberta Government; fuel delivery, refueling, and use stage estimates are taken from GHGenius, a Government of Canada WTW model.
Their analysis included nine base case oil sands pathways: surface mining, SAGD (in situ Steam Assisted Gravity Drainage), and CSS (in situ Cyclic Steam Stimulation) with the WTR pathways producing SCO (synthetic crude oil), dilbit (blend of 75% bitumen and 25% diluent), or synbit (blend of 50% bitumen and 50% SCO) and the resulting WTW pathways producing gasoline and including fuel use in a light-duty vehicle. The diluent used in the dilbit can be natural gas condensate or naphtha.
They found that although a high degree of variability exists in well-to-wheel emissions due to differences in technologies employed, operating conditions, and product characteristics, the surface mining dilbit and the in situ SCO pathways have the lowest and highest emissions, respectively, of 88 and 120 g CO2eq/MJ reformulated gasoline.
Our sensitivity analyses reveal that for all pathways, emissions associated with steam and electricity generation are the largest contributors to emissions (e.g., responsible for 71−99% of recovery and extraction emissions across all pathways) and the most sensitive parameters overall, followed by emissions associated with hydrogen production for upgrading when this activity is included. These results indicate that the ranges of emissions calculated are driven much more by interproject variability rather than uncertainty in the data or modeling methods; however, further work is required to quantify the specific contribution of each.
The best performing (lowest GHG intensity) in situ pathways tend to have low SORs [steam-to-oil ratios] (close to 2) and electricity requirements (∼45 kWh/m3 bitumen) and use a high proportion of solution gas (dissolved gas in produced bitumen) (∼12 m3/m3 bitumen). The latter reduces solution gas-related flare or fugitive emissions and lowers indirect emissions associated with natural gas. The best performing surface mining projects have low natural gas, diesel, and electricity requirements (∼20 m3, ∼7 L, and ∼50 kWh/m3 bitumen, respectively).—Bergerson et al.
Approaches to reducing GHG emissions could include:
Lowering SORs of in situ projects. While a project’s SOR is largely dictated by geological conditions in the reservoir, they note, there is a role for operators to improve performance through better well configuration, scheduling the shut-down of underperforming wells, etc. The steam required by in situ projects can be reduced through the use of solvents, in situ combustion, or electrothermal technologies, but new technologies such as these also have the potential for unintended consequences and therefore require further assessment.
Reducing natural gas use in surface mining projects. As for in situ projects, natural gas use in surface mining projects is also the largest source of emissions but to a lesser extent. Emissions from electricity production and diesel production and combustion, as well as fugitive emissions, play a larger role in surface mining pathways. This implies that most emissions reduction opportunities for these pathways tend to be incremental and will have lesser impact individually (e.g., management of transport logistics on-site).
Replace or supplementing natural gas with lower carbon fuels. Nuclear, geothermal, biomass, and wind have all been considered to varying extents to provide some or all of the energy and hydrogen requirements in the oil sands. However, they note, each of these energy sources poses its own challenges so there is no obvious replacement for natural gas in the near term. Carbon capture and storage could be applied to oil sands projects, although cost and other factors must be considered.
Near-term incremental process improvements. This is likely to be more feasible, they suggested, although the potential for emissions reductions is lower. These include adjusting operating conditions (e.g., boiler feedwater temperature), using higher efficiency equipment, optimizing operating conditions, selecting a diluent with low associated GHG emissions, on-site heat integration, and minimizing transportation distances. Companies have deployed these to varying extents to date.
Using more sophisticated analytical tools and reporting requirements would assist policymakers in better understanding the factors influencing variability and uncertainty across and within oil-sands projects, the authors suggest. Recommended improvements include:
Clearer and more consistent analysis boundaries (both physical and temporal), e.g., a project might have a high SOR because it is at start-up with only the first few wells operating or it might have been operating at a high SOR for several years but is not shutdown because the project is still economically viable;
Reporting of key operating conditions not typically specified in previous studies, e.g., intermediate products/which pathway is being pursued and type/amount of diluent used; and
Stating the verification process used and trigger periodic updates as performance changes (e.g., extreme events like outages, a switch of supplier).
The focus on oil sands GHG emissions must be integrated into a more comprehensive view of reducing emissions across the entire economy and expanding this focus to other environmental impacts such as those on air, land, and water. Policies such as LCFSs and a focus on reducing oil sands operations emissions alone is an initial step but will not be sufficient to achieve meaningful long-term environmental policy goals.—Bergerson et al.
Alberta Innovates—Energy and Environment Solutions, Natural Resources Canada, Carbon Management Canada, AUTO21 NCEs, and the Oil Sands Industry Consortium provided financial support and insights for the work.
Joule A. Bergerson, Oyeshola Kofoworola, Alex D. Charpentier, Sylvia Sleep, and Heather L. MacLean (2012) Life Cycle Greenhouse Gas Emissions of Current Oil Sands Technologies: Surface Mining and In Situ Applications. Environmental Science & Technology doi: 10.1021/es300718h