GHG Emissions from Oil Sands Tailings Ponds: Overview and Modelling Based on Fermentable Substrates

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  • Surface mining of Alberta bitumen is probably the biggest mining operation in the world. It has a significant environmental footprint with about 840 km2 total active footprint in 2012 and 895 km2 in 2013 (Fig 1) (AESRD 2014). Of this area, tailings ponds covered 239.3 km2 in 2013 including dykes, berms and beaches. Reclaimed tailings areas covered about 19.2 km2 leaving 220.1 km2 in active pond structures. However only 88.5 km2 is covered with process-affected water within ponds, which is about 40.2% of the total pond surface area, or 9.9% of the total active footprint that includes cleared, disturbed and other categories. Extraction and upgrading/refining of mined bitumen are energy intensive operations that require significant fuel consumption resulting in emissions of greenhouse gases (GHG) – carbon dioxide, methane and nitrous oxide. Emissions of nitrous oxide are production/machinery related, originating mostly from combustion processes such as diesel fuel burning in heavy trucks. Nitrous oxide emissions were considered as insignificant in GHG emissions from tailings ponds. The less understood part of GHG emissions from surface mining operations is methane and carbon dioxide production from fluid tailings ponds, primarily as a result of microbial biodegradation/fermentation of lost diluent. The diluent originates in froth treatment tailings that also contain significant concentrations of residual bitumen, and associated heavy minerals that contain pyrite whose potential oxidation may be a cause of carbon dioxide emissions. The quantity of the lost diluent and its historical changes and future projections are not well understood by general public and academia despite data provided by the operators and regulators. In Part I, this paper will explain past, current and future practices that affect greenhouse gas (GHG) emissions from tailings ponds and present a few facts that contrast with assumptions commonly made in literature regarding fugitive emissions from oil sands mines. Part I demonstrates that due to the diversity of operations and project history, it is not accurate to assess industry average GHG intensity from tailing ponds based on the measurement of one project and one point in time, and assume that it is applicable to others. Both directly measured historic data such as diluent losses and GHG reports made by companies as well as companies’ tailings management plans are now available. Those reports take into account the unique facility processes, the variety of current and future tailing treatment technologies applied, and Closure and Reclamation Scenarios expected. Part I also shows that current measurement of emissions from ponds using flux chambers is better than high level estimates. Fugitive GHG measurements are continuously improving in terms of frequency and coverage of sampling campaigns and accuracy of the instruments, but still have uncertainties especially when projected forward in time. Historically, GHG emissions intensity from oil sands has decreased and it still has a potential to decrease further. Part II proposes a Base GHG Model for calculating future GHG emissions. This modelling effort presents a different approach to calculate GHG emissions from ponds based on fermentable substrates with a focus on diluent, which has been shown to be the most bioavailable part of tailings. It shows how it may be possible to decrease emissions by affecting fermentation pathways and applying processing or treatment technologies. Different scenarios based on the Base GHG Model show potential pathways toward lowering the Alberta bitumen GHG profile. This modelling approach, as compared to the published literature is more realistic, and allows easy adjustment due to changing technologies. The Model could work together with the current measurement and reporting system to address potential time and place sampling bias of local GHG measuring campaigns. It may also help to quantify future GHG emissions. Initial application of the Model conservatively shows total average GHG (CO2+CH4) fugitive emissions intensity from ponds to be below 1.0 g CO2eq/MJ bitumen produced, and distinguishes emissions from different producers based on the type of diluent and the associated carbon content and physical behavior such as volatility and solubility in water. The Model also demonstrates the influence of applied or potential tailing technologies on changing GHG profiles. The Base GHG Model will need further validation and adjustment for ensuing technological changes. Its simplicity almost guarantees further application, but its application in the field and by regulators still needs to be determined.

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