Life cycle greenhouse gas (GHG) emissions associated with two major recovery and extraction processes currently utilized in Alberta's oil sands, surface mining and in situ, are quantified. Process modules are developed and integrated into a life cycle model-GHOST (GreenHouse gas emissions of current Oil Sands Technologies) developed in prior work. Recovery and extraction of bitumen through surface mining and in situ processes result in 3-9 and 9-16 g CO(2)eq/MJ bitumen, respectively; upgrading emissions are an additional 6-17 g CO(2)eq/MJ synthetic crude oil (SCO) (all results are on a HHV basis). 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, 88 and 120 g CO(2)eq/MJ reformulated gasoline. Through the use of improved data obtained from operating oil sands projects, we present ranges of emissions that overlap with emissions in literature for conventional crude oil. An increased focus is recommended in policy discussions on understanding interproject variability of emissions of both oil sands and conventional crudes, as this has not been adequately represented in previous studies.

Life 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. K E Y W O R D Searly stage technology assessment, environmental impacts, industrial ecology, life cycle assessment (LCA), research and development (R&D), unintended consequences

The 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 infl uence 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 280 J McKechnie et al.Modeling and Analysis: Production system decisions for lignocellulosic ethanol 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 biomassbased 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. petroleum use is dependent on activities throughout the life cycle of bioenergy production and use; 6 therefore, significant variation can be expected among diff erent production processes. Life cycle assessment (LCA) has been employed to evaluate lignocellulosic ethanol pathways. Th e majority of LCAs have examined the National Renewable Energy Laboratory's (NREL) biochemical conversion process, which utilizes dilute acid pre-treatment followed by enzymatic hydrolysis. 7-9 To a lesser extent, LCAs have examined the Iogen process, which consists of sulfuric acid-catalyzed steam explosion pre-treatment followed by enzymatic hydrolysis, 10, 11 the Ammonia Fiber Expansion (AFEX) process developed at Michigan State University, 12 and consolidated bioprocessing. 13 Th e current study examines, for the fi rst time, the production of lignocellulosic ethanol via uncatalyzed steam explosion pre-treatment and enzymatic hydrolysis from a life cycle perspective. Beyond technology choices, other production decisions can impact the life cycle attributes of lignocellulosic ethanol.Most existing studie...

We present a statistically enhanced version of the GreenHouse gas emissions of current Oil Sands Technologies model that facilitates characterization of variability of greenhouse gas (GHG) emissions associated with mining and upgrading of bitumen from Canadian oil sands. Over 30 years of publicly available project-specific operating data are employed as inputs, enabling Monte Carlo simulation of individual projects and the entire industry, for individual years and project life cycles. We estimate that median lifetime GHG intensities range from 89 to 137 kg COeq/bbl synthetic crude oil (SCO) for projects that employ upgrading. The only project producing dilbit that goes directly to a refinery has a median lifetime GHG intensity of 51 kg COeq/bbl dilbit. As SCO and dilbit are distinct products with different downstream processing energy requirements, a life cycle assessment ("well to wheel") is needed to properly compare them. Projects do not reach steady-state in terms of median GHG intensity. Projects with broader distributions of annual GHG intensities and higher median values are linked to specific events (e.g., project expansions). An implication for policymakers is that no specific technology or operating factor can be directly linked to GHG intensity and no particular project or year of operation can be seen as representative of the industry or production technology.

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