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Worldwide heavy oil and bitumen deposits amount to 9 trillion barrels of oil distributed in over 280 basins around the world (1), with Canada home to oil sands deposits of [...]

Tailings ponds in the Alberta Oil Sands Region are significant sources of fugitive emissions of methane to the atmosphere, but detailed knowledge on spatial and temporal variabilities is lacking due to limitations of the methods deployed under current regulatory compliance monitoring programs. To develop more robust and representative methods for quantifying these emissions, three micrometeorological flux methods were applied along with traditional flux chambers to determine fluxes over a 5-week period. Eddy covariance flux measurements provided the benchmark. A method is presented to directly calculate stability-corrected eddy diffusivities that can be applied to vertical gas profiles for gradient flux estimation. Gradient fluxes were shown to agree with eddy covariance within 7%, and inverse dispersion model fluxes within 11%, with an overall uncertainty of 28% for the calculated mean flux. Fluxes were shown to have only a minor diurnal cycle (18% variability) and to be mostly independent of wind speed, air and water surface temperatures. Flux chambers underestimated the fluxes by a factor of 2 in this particular campaign. These measurements indicate that the larger footprint of micrometeorological measurements results in more robust emission estimates representing the whole pond. [ABSTRACT FROM AUTHOR]

In this paper, measurements of air pollutants made at a ground site near Fort McKay in the Athabasca oil sands region as part of a multi-platform campaign in the summer of 2013 are presented. The observations included measurements of selected volatile organic compounds (VOCs) by a gas chromatograph &ndash ion trap mass spectrometer (GC-ITMS). This instrument observed a large, analytically unresolved hydrocarbon peak (with retention index between 1100 and 1700) associated with intermediate volatility organic compounds (IVOCs). However, the activities or processes that contribute to the release of these IVOCs in the oil sands region remain unclear. Principal component analysis (PCA) with Varimax rotation was applied to elucidate major source types impacting the sampling site in the summer of 2013. The analysis included 28 variables, including concentrations of total odd nitrogen (NOy), carbon dioxide (CO2), methane (CH4), ammonia (NH3), carbon monoxide (CO), sulfur dioxide (SO2), total reduced sulfur compounds (TRS), speciated monoterpenes (including α- and β-pinene and limonene), particle volume calculated from measured size distributions of particles less than 10 µm and 1 µm in diameter (PM10-1 and PM1), particle-surface bound polycyclic aromatic hydrocarbons (pPAH), and aerosol mass spectrometer composition measurements, including refractory black carbon (rBC) and organic aerosol components. The PCA was complemented by bivariate polar plots showing the joint wind speed and direction dependence of air pollutant concentrations to illustrate the spatial distribution of sources in the area. Using the 95 % cumulative percentage of variance criterion, ten components were identified and categorized by source type. These included emissions by wet tailings ponds, vegetation, open pit mining operations, upgrader facilities, and surface dust. Three components correlated with IVOCs, with the largest associated with surface mining and is likely caused by the unearthing and processing of raw bitumen. [ABSTRACT FROM AUTHOR]

Aircraft-based measurements of methane (CH4) and other air pollutants in the Athabasca Oil Sands Region (AOSR) were made during a summer intensive field campaign between August 13 and September 7 2013, in support of the Joint Canada-Alberta Implementation Plan for Oil Sands Monitoring. Chemical signatures were used to identify CH4 sources from tailings ponds (BTEX VOC's), open-pit surface mines (NOy and rBC) and elevated plumes from bitumen upgrading facilities (SO2 and NOy). Emission rates of CH4 were determined for the five primary surface mining facilities in the region using two mass balance methods. Emission rates from source categories within each facility were estimated when plumes from the sources were spatially separable. Tailings ponds accounted for 45 % of total CH4 emissions measured from the major surface mining facilities in the region while emissions from operations in the open pit mines accounted for ~ 50 %. The average open pit surface mining emission rates ranged from 1.2 to 2.8 tonnes of CH4 hr-1 for different facilities in the AOSR. Amongst the 19 tailings ponds, Mildred Lake Settling Basin, the oldest pond in the region, was found to be responsible for the majority of tailings ponds emissions of CH4 (> 70 %). The sum of measured emission rates of CH4 from the five major facilities, 19.2 ± 1.1 tonnes CH4 hr-1, was similar to a single mass balance determination of CH4 from all major sources in the AOSR determined from a single flight downwind of the facilities, 23.7 ± 3.7 tonnes CH4 hr-1. The measured hourly CH4 emission rate from all facilities in the AOSR is 48 ± 8 % higher than that extracted for 2013 from the Canadian Green House Gas Reporting Program, a legislated facility-reported Emissions Inventory, converted to hourly units. The measured emissions correspond to an emissions rate of 0.17 ± 0.01 Tg CH4 yr-1, if the emissions are assumed temporally constant, an uncertain assumption. The emission rates reported here are relevant for the summer season. In future, effort should be devoted to measurements in different seasons to further our understanding of seasonal parameters impacting fugitive emissions of CH4 and to allow better estimates of annual emissions and year to year variability. [ABSTRACT FROM AUTHOR]

Large-scale oil production from oil sands deposits in Alberta, Canada has raised concerns about environmental impacts, such as the magnitude of air pollution emissions. This paper reports compound emission rates (E) for 69–89 nonbiogenic volatile organic compounds (VOCs) for each of four surface mining facilities, determined with a top-down approach using aircraft measurements in the summer of 2013. The aggregate emission rate (aE) of the nonbiogenic VOCs ranged from 50 ± 14 to 70 ± 22 t/d depending on the facility. In comparison, equivalent VOC emission rates reported to the Canadian National Pollutant Release Inventory (NPRI) using accepted estimation methods were lower than the aE values by factors of 2.0 ± 0.6, 3.1 ± 1.1, 4.5 ± 1.5, and 4.1 ± 1.6 for the four facilities, indicating underestimation in the reported VOC emissions. For 11 of the combined 93 VOC species reported by all four facilities, the reported emission rate and E were similar; but for the other 82 species, the reported emission rate was lower than E. The median ratio of E to that reported for all species by a facility ranged from 4.5 to 375 depending on the facility. Moreover, between 9 and 53 VOCs, for which there are existing reporting requirements to the NPRI, were not included in the facility emission reports. The comparisons between the emission reports and measurement-based emission rates indicate that improvements to VOC emission estimation methods would enhance the accuracy and completeness of emission estimates and their applicability to environmental impact assessments of oil sands developments. [ABSTRACT FROM AUTHOR]

During the global COVID-19 pandemic, anthropogenic emissions of air pollutants and greenhouse gases (GHGs), especially traffic emissions in urban areas, have declined. Long-term measurements of trace gas concentrations in urban areas can be used to quantify the impact of emission reductions on GHG mole fractions. Open-path Fourier transform infrared (OP-FTIR) spectroscopy is a non-intrusive technique that can be used to simultaneously measure multiple atmospheric trace gases in the boundary layer. This study investigates the reduction of mole fractions and mole fraction enhancements above background for surface CO, CO 2 , and CH 4 in downtown Toronto, Canada (the fourth largest city in North America) during the 2020 and 2021 COVID-19 stay-at-home periods. Mean values obtained from these periods were compared with mean values from a reference period prior to the 2020 restrictions. Mean CO mole fraction enhancement declined by 51 ± 23% and 42 ± 24% during the 2020 and 2021 stay-at-home periods, respectively. The mean afternoon CO 2 mole fraction enhancement declined by 3.9 ± 2.6 ppm (36 ± 24%) and 3.5 ± 2.8 ppm (33 ± 26%) during the stay-at-home periods in 2020 and 2021. In contrast, CH 4 mole fraction enhancement did not show any significant decrease. Diurnal variation in CO during the stay-at-home period in 2020 was also significantly reduced relative to the reference period in 2020. These reductions in trace gas mole fraction enhancements coincide with the decline of local traffic during the stay-at-home periods, with an estimated reduction in CO and CO 2 enhancements of 0.74 ± 0.15 ppb and 0.18 ± 0.05 ppm per percentage decrease in traffic, respectively. [ABSTRACT FROM AUTHOR]

The oil and gas (O&G) sector represents a large source of greenhouse gas (GHG) emissions globally. However, estimates of O&G emissions rely upon bottom-up approaches, and are rarely evaluated through atmospheric measurements. Here, we use aircraft measurements over the Canadian oil sands (OS) to derive the first top-down, measurement-based determination of the their annual CO2 emissions and intensities. The results indicate that CO2 emission intensities for OS facilities are 13–123% larger than those estimated using publically available data. This leads to 64% higher annual GHG emissions from surface mining operations, and 30% higher overall OS GHG emissions (17 Mt) compared to that reported by industry, despite emissions reporting which uses the most up to date and recommended bottom-up approaches. Given the similarity in bottom-up reporting methods across the entire O&G sector, these results suggest that O&G CO2 emissions inventory data may be more uncertain than previously considered. Evaluating GHG emissions reported to inventories for the oil and gas (O&G) sector is important for countries with resource-based economies. Here the authors provide a top-down assessment of GHG emissions from the Canadian oil sands and find previous inventory reports underestimate emissions, by as much as 64% for surface mining facilities and 30% for the entire oil sands compared with their assessment. [ABSTRACT FROM AUTHOR]

Measurement-based estimates of greenhouse gas (GHG) emissions from complex industrial operations are challenging to obtain, but serve as an important, independent check on inventory-reported emissions. Such top-down estimates, while important for oil and gas (O&G) emissions globally, are particularly relevant for Canadian oil sands (OS) operations, which represent the largest O&G contributor to national GHG emissions. We present a multifaceted top-down approach for estimating CO 2 emissions that combines aircraft-measured CO 2 /NO x emission ratios (ERs) with inventory and satellite-derived NO x emissions from Ozone Monitoring Instrument (OMI) and TROPOspheric Ozone Monitoring Instrument (TROPOMI) and apply it to the Athabasca Oil Sands Region (AOSR) in Alberta, Canada. Historical CO 2 emissions were reconstructed for the surface mining region, and average top-down estimates were found to be >65% higher than facility-reported, bottom-up estimates from 2005 to 2020. Higher top-down vs. bottom-up emissions estimates were also consistently obtained for individual surface mining and in situ extraction facilities, which represent a growing category of energy-intensive OS operations. Although the magnitudes of the measured discrepancies vary between facilities, they combine such that the observed reporting gap for total AOSR emissions is ≥(31 ± 8) Mt for each of the last 3 years (2018-2020). This potential underestimation is large and broadly highlights the importance of continued review and refinement of bottom-up estimation methodologies and inventories. The ER method herein offers a powerful approach for upscaling measured facility-level or regional fossil fuel CO 2 emissions by taking advantage of satellite remote sensing observations., (© Crown copyright 2023.)