Literature DB >> 22191713

Variability and uncertainty in life cycle assessment models for greenhouse gas emissions from Canadian oil sands production.

Adam R Brandt1.   

Abstract

Because of interest in greenhouse gas (GHG) emissions from transportation fuels production, a number of recent life cycle assessment (LCA) studies have calculated GHG emissions from oil sands extraction, upgrading, and refining pathways. The results from these studies vary considerably. This paper reviews factors affecting energy consumption and GHG emissions from oil sands extraction. It then uses publicly available data to analyze the assumptions made in the LCA models to better understand the causes of variability in emissions estimates. It is found that the variation in oil sands GHG estimates is due to a variety of causes. In approximate order of importance, these are scope of modeling and choice of projects analyzed (e.g., specific projects vs industry averages); differences in assumed energy intensities of extraction and upgrading; differences in the fuel mix assumptions; treatment of secondary noncombustion emissions sources, such as venting, flaring, and fugitive emissions; and treatment of ecological emissions sources, such as land-use change-associated emissions. The GHGenius model is recommended as the LCA model that is most congruent with reported industry average data. GHGenius also has the most comprehensive system boundaries. Last, remaining uncertainties and future research needs are discussed.

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Year:  2012        PMID: 22191713     DOI: 10.1021/es202312p

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  1 in total

1.  Measured Canadian oil sands CO2 emissions are higher than estimates made using internationally recommended methods.

Authors:  John Liggio; Shao-Meng Li; Ralf M Staebler; Katherine Hayden; Andrea Darlington; Richard L Mittermeier; Jason O'Brien; Robert McLaren; Mengistu Wolde; Doug Worthy; Felix Vogel
Journal:  Nat Commun       Date:  2019-04-23       Impact factor: 14.919

  1 in total

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