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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 [...]

Emissions from biomass burning are an important source of mercury (Hg) to the atmosphere and an integral component of the global Hg biogeochemical cycle. In 2018, measurements of gaseous elemental Hg (GEM) were taken on board a research aircraft along with a series of co-emitted contaminants in the emissions plume of an 88 km 2 boreal forest wildfire on the Garson Lake Plain (GLP) in NW Saskatchewan, Canada. A series of four flight tracks were made perpendicular to the plume at increasing distances from the fire, each with three to five passes at different altitudes at each downwind location. The maximum GEM concentration measured on the flight was 2.88 ng m -3 , which is ≈ 2.4 × background concentration. GEM concentrations were significantly correlated with the co-emitted carbon species (CO, CO 2 , and CH 4). Emissions ratios (ERs) were calculated from measured GEM and carbon co-contaminant data. Using the most correlated (least uncertain) of these ratios (GEM:CO), GEM concentrations were estimated at the higher 0.5 Hz time resolution of the CO measurements, resulting in maximum GEM concentrations and enhancements of 6.76 ng m -3 and ≈ 5.6 × , respectively. Extrapolating the estimated maximum 0.5 Hz GEM concentration data from each downwind location back to source, 1 km and 1 m (from fire) concentrations were predicted to be 12.9 and 30.0 ng m -3 , or enhancements of ≈ 11 × and ≈ 25 × , respectively. ERs and emissions factors (EFs) derived from the measured data and literature values were also used to calculate Hg emissions estimates on three spatial scales: (i) the GLP fires themselves, (ii) all boreal forest biomass burning, and (iii) global biomass burning. The most robust estimate was of the GLP fires (21 ± 10 kg of Hg) using calculated EFs that used minimal literature-derived data. Using the Top-down Emission Rate Retrieval Algorithm (TERRA), we were able to determine a similar emission estimate of 22 ± 7 kg of Hg. The elevated uncertainties of the other estimates and high variability between the different methods used in the calculations highlight concerns with some of the assumptions that have been used in calculating Hg biomass burning in the literature. Among these problematic assumptions are variable ERs of contaminants based on vegetation type and fire intensity, differing atmospheric lifetimes of emitted contaminants, the use of only one co-contaminant in emissions estimate calculations, and the paucity of atmospheric Hg species concentration measurements in biomass burning plumes. [ABSTRACT FROM AUTHOR]

Mercury (Hg) emitted from biomass burning is an important source of the contaminant to the atmosphere and an integral component of the global Hg biogeochemical cycle. In 2018, measurements of gaseous elemental Hg (GEM) were taken on-board a research aircraft along with a series of co-emitted contaminants in the emissions plume of an 88 km2 boreal forest wildfire on the Garson Lake Plain (GLP) in NW Saskatchewan, Canada. A series of four flight tracks were made perpendicular to the emissions plume at increasing distances from the fire each with 3-5 passes at different altitudes at each downwind location. The maximum GEM concentration measured on the flight was 2.88 ng m−3, which represents a ≈2.4x increase in concentration above background. GEM concentrations were significantly correlated with the co-emitted carbon species (CO, CO2, and CH4). Emissions ratios (ERs) were calculated from measured GEM and carbon co-contaminants data. Using the least uncertain of these ratios (GEM : CO), GEM concentrations were estimated at the higher 0.5 Hz time resolution of the CO measurements resulting in maximum GEM concentrations and enhancements of 6.75 ng m−3 and ≈5.6x, respectively. Extrapolating the estimated maximum 0.5 Hz GEM concentration data from each downwind location back to source, 1 km and 1 m (from fire) concentrations were predicted to be 12.9 and 29.9 ng m−3, or enhancements of ≈11x and ≈25x, respectively. ERs and emissions factors (EFs) derived from the measured data and literature values were also used to calculate Hg emissions estimates on three spatial scales: (i) the GLP fires themselves, (ii) all boreal forest biomass burning, and (iii) global biomass burning. The most robust estimate was of the GLP fires (21 ± 10 kg of Hg) using calculated EFs that used minimal literature derived data. Using a Top-down Emission Rate Retrieval Algorithm (TERRA) we were able to determine a similar emission estimate of 22 ± 7 kg of Hg. The elevated uncertainties of the other estimates and high variability between the different methods used in the calculations highlight concerns with some of the assumptions that have been used in calculating Hg biomass burning in the literature. Among these problematic assumptions are variable ERs of contaminants based on vegetation type and fire intensity, differing atmospheric lifetimes of emitted contaminants, the use of only one co-contaminant in emissions estimate calculations, and the paucity of atmospheric Hg species concentration measurements in biomass burning plumes. [ABSTRACT FROM AUTHOR]

We evaluate four high-resolution model simulations of pollutant emissions, chemical transformation and downwind transport for the Athabasca oil sands using the Global Environmental Multiscale – Modelling Air-quality and Chemistry (GEM-MACH) model using surface monitoring network and aircraft observations of multiple pollutants, for simulations spanning a time period corresponding to an aircraft measurement campaign in the region in summer 2013. We have focussed here on the impact of different representations of the model's aerosol size distribution and plume-rise parameterization on model results. The use of a more finely resolved representation of the aerosol size distribution was found to have a significant impact on model performance, reducing the magnitude of the original surface PM2.5 negative biases by 32 %. We compared model predictions of SO2, NO2, and speciated particulate matter concentrations from simulations employing the commonly-used Briggs (1984) plume-rise algorithms to redistribute emissions from large stacks with stack plume observations. As in our companion paper (Gordon et al., 2018), we found these algorithms resulted in under-predictions of plume rise, with 39 to 60 % of predicted plume heights falling below half of the observed plume heights. However, we found here that a layered buoyancy approach for stable to neutral atmospheres, coupled with the assumption of free rise in convectively unstable atmospheres, resulted in much better model performance, both for atmospheric constituent concentrations and the predicted height of the plumes. Persistent issues with over-fumigation of plumes in the model were linked to positive biases in the predicted temperatures between the surface and 1km elevation. These in turn may lead to overestimates of near-surface diffusivity, resulting in excessive fumigation. [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]

Dry deposition is an important yet poorly constrained process that removes reactive organic carbon from the atmosphere, making it unavailable for airborne chemical reactions and transferring it to other environmental systems. Using an aircraft-based measurement method, we provide large-scale estimates of total gas-phase organic carbon deposition rates and fluxes. Observed deposition rates downwind of large-scale unconventional oil operations reached up to 100 tC hour-1, with fluxes exceeding 0.1 gC m-2 hour-1. The observed deposition lifetimes (tdep) were short enough (i.e., 4 ± 2 hours) to compete with chemical oxidation processes and affect the fate of atmospheric reactive carbon. Yet, much of this deposited organic carbon cannot be accounted for using traditional gas-phase deposition algorithms used in regional air quality models, signifying underrepresented, but influential, chemical-physical surface properties and processes. Furthermore, these fluxes represent a major unaccounted contribution of reactive carbon to downwind freshwater ecosystems that outweigh terrestrial sources, necessitating the inclusion of dry deposition in aquatic carbon balances and models. [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.)

Black carbon (BC) emissions from the Canadian oil sand (OS) surface mining facilities in Alberta were investigated using aircraft measurements. BC emission rates were derived with a top-down mass balance approach and were found to be linearly related to the volume of oil sand ore mined at each facility. Two emission factors were determined from the measurements; production-based BC emission factors were in the range of 0.6-1.7 g/tonne mined OS ore, whereas fuel-based BC emission factors were between 95 and 190 mg/kg-fuel, depending upon the facility. The annual BC emission, at 707 ± 117 tonnes/year for the facilities, was determined using the production-based emission factors and annual production data. Although this annual emission is in reasonable agreement with the BC annual emissions reported in the latest version of the Canadian national BC inventory (within 16%), the relative split between off-road diesel and stack sources is significantly different between the measurements and the inventory. This measurement evidence highlights the fact that the stack sources of BC may be overestimated and the off-road diesel sources may be underestimated in the inventory and points to the need for improved BC emission data from diesel sources within facilities.