• Energy Research

Life cycle assessments can help to inform decision-making about greenhouse gas (GHG) emission reduction opportunities but are often not embraced by stakeholders associated with industries where study results are highly scrutinized and often contentious. This project was motivated by stakeholder interest in understanding open source life cycle models (the Oil Production Greenhouse Gas Emissions Estimator, OPGEE, and the Petroleum Refinery Life Cycle Inventory Model, PRELIM) and how accurately they can estimate emissions for existing oil sands projects and emerging technologies. We evaluate the robustness of these models and improve them using data from three existing oil sands projects (mining + upgrading, mining + dilution, and steam assisted gravity drainage, SAGD, + dilution). The models are then applied to estimate the GHG emissions reduction potential for two emerging in situ oil sands technologies. We find that, when boundaries are aligned, OPGEE can generate upstream GHG emissions estimates for the projects modeled within 1-4% of company reported GHG emissions data. Extending the boundary to include indirect (life cycle) emissions can lead to a doubling in upstream GHG emissions intensity. The two emerging technologies evaluated in the study can reduce upstream emissions by 14-19% compared to a SAGD project operating at the same reservoir, or 1.4-1.9% on a well-to-wheel basis. This work contributes a revised process of conducting LCAs that includes stakeholder input throughout and results in more robust and transparent estimations of emissions from deploying existing and emerging technologies.

Abstract Life cycle assessments (LCAs) of early-stage technologies can provide valuable insights about key drivers of emissions and aid in prioritizing research into further emissions-reduction opportunities. Despite this potential value, further development of LCA methods is required to handle the increased uncertainty, data gaps, and confidentially of early-stage data. This study presents a discussion of the life cycle carbon footprinting of technologies competing in the final round of the NRG COSIA Carbon XPRIZE competition—a US$20 million competition for teams to demonstrate the conversion of CO2 into valuable products at the scale of a small industrial pilot using consistent deployment conditions, boundaries, and methodological assumptions. This competition allowed the exploration of how LCA can be used and further improved when assessing disparate and early-stage technologies. Carbon intensity estimates are presented for two conversion pathways: (i) CO2 mineralization and (ii) catalytic conversion (including thermochemical, electrochemical, photocatalytic and hybrid process) of CO2, aggregated across teams to highlight the range of emissions intensities demonstrated at the pilot for individual life cycle stages. A future scenario is also presented, demonstrating the incremental technology and deployment conditions that would enable a team to become carbon-avoiding relative to an incumbent process (i.e. reducing emissions relative to a reference pathway producing a comparable product). By considering the assessment process across a diverse set of teams, conversion pathways and products, the study presents generalized insights about opportunities and challenges facing carbon capture and -utilization technologies in their next phases of deployment from a life cycle perspective.

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.

Life cycle assessment as a decision-making tool in R&D of CO2 conversion technologies. A set of technologies are explored to provide recommendations regarding potential climate impacts. Relevant fundamentals of this type of assessment are provided.

AbstractLife cycle assessment (LCA) analysts are increasingly being asked to conduct life cycle‐based systems level analysis at the earliest stages of technology development. While early assessments provide the greatest opportunity to influence design and ultimately environmental performance, it is the stage with the least available data, greatest uncertainty, and a paucity of analytic tools for addressing these challenges. While the fundamental approach to conducting an LCA of emerging technologies is akin to that of LCA of existing technologies, emerging technologies pose additional challenges. In this paper, we present a broad set of market and technology characteristics that typically influence an LCA of emerging technologies and identify questions that researchers must address to account for the most important aspects of the systems they are studying. The paper presents: (a) guidance to identify the specific technology characteristics and dynamic market context that are most relevant and unique to a particular study, (b) an overview of the challenges faced by early stage assessments that are unique because of these conditions, (c) questions that researchers should ask themselves for such a study to be conducted, and (d) illustrative examples from the transportation sector to demonstrate the factors to consider when conducting LCAs of emerging technologies. The paper is intended to be used as an organizing platform to synthesize existing methods, procedures and insights and guide researchers, analysts and technology developer to better recognize key study design elements and to manage expectations of study outcomes.

Abstract Emerging oil sands technologies could influence industry-wide greenhouse gas emissions, however projecting future emissions is difficult due to limited public reporting of expected performance and deployment of emerging technologies. An expert elicitation was conducted to gauge how experts anticipate emerging in situ, surface mining and upgrading technologies will be deployed and perform compared to current technologies. All experts project the majority (60–98%) of in situ bitumen production in 2034 will be produced using current technologies or hybrid steam-solvent processes. Experts built boxplots to show how they project commercial projects employing emerging technologies would perform in 2034 compared to a current project employing steam-assisted gravity drainage. Across experts, the median reduction in steam-to-oil ratio for hybrid steam-solvent projects and current in situ projects employing process changes (e.g., better well placement) ranged from 3 to 30% and from 12 to 14%, respectively. Median projections from experts about the change in bitumen recovery rate compared to a current (2014) steam-assisted gravity drainage project ranged from 3 to 30% for hybrid steam-solvents and up to 15% for electro-thermal and in situ combustion projects. The responses show that a slight reduction in energy consumption from the adoption of hybrid steam-solvent processes is expected by experts. Experts projected that emerging in situ technologies, which have the largest potential for adoption, will be used primarily for accessing marginal resources and increasing overall production levels, rather than targeting greenhouse gas emissions reductions. Therefore, deployment of emerging technologies is not expected to contribute substantially to meeting greenhouse gas emissions reduction targets for the industry by 2034 under the regulatory conditions at the time of the elicitation, a key insight for policy makers.

AbstractThe performance of lignocellulosic ethanol in reducing greenhouse gas (GHG) emissions and fossil energy use when substituting for gasoline depends on production technologies and system decisions, many of which have not been considered in life cycle studies. We investigate ethanol production from short rotation forestry feedstock via an uncatalyzed steam explosion pre‐treatment and enzymatic hydrolysis process developed by Mascoma Canada, Inc., and examine a set of production system decisions (co‐location, co‐production, and process energy options) in terms of their influence on life cycle emissions and energy consumption. All production options are found to reduce emissions and petroleum use relative to gasoline on a well‐to‐wheel (WTW) basis; GHG reductions vary by production scenario. Land‐use‐change effects are not included due to a lack of applicable data on short rotation forestry feedstock. Ethanol production with wood pellet co‐product, displacing coal in electricity generation, performs best amongst co‐products in terms of GHG mitigation (−109% relative to gasoline, WTW basis). Maximizing pellet output, although requiring import of predominately fossil‐based process energy, improves overall GHG‐mitigation performance (−130% relative to gasoline, WTW). Similarly, lower ethanol yields result in greater GHG reductions because of increased co‐product output. Co‐locating ethanol production with facilities exporting excess steam and biomass‐based electricity (e.g. pulp mills) achieves the greatest GHG mitigation (−174% relative to gasoline, WTW) by maximizing pellet output and utilizing low‐GHG process energy. By exploiting co‐location opportunities and strategically selecting co‐products, lignocellulosic ethanol can provide large emission reductions, particularly if based upon sustainably grown, high yield, low input feedstocks. © 2011 Society of Chemical Industry and John Wiley & Sons, Ltd