Temperature, Precipitation, and Lightning Modification in the Vicinity of the Athabasca Oil Sands

Abstract. 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 13 August and 7 September 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 VOCs), 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 t of CH4 h−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 t CH4 h−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 t CH4 h−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 Greenhouse 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 as temporally constant, which is an uncertain assumption. The emission rates reported here are relevant for the summer season. In the future, effort should be devoted to measurements in different seasons to further our understanding of the seasonal parameters impacting fugitive emissions of CH4 and to allow for better estimates of annual emissions and year-to-year variability.

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Quantification of Methane Sources in the Athabasca Oil Sands Region of Alberta by Aircraft Mass-Balance

10.5194/acp-2017-925 ◽

2017 ◽

Author(s):

Sabour Baray ◽

Andrea Darlington ◽

Mark Gordon ◽

Katherine L. Hayden ◽

Amy Leithead ◽

...

Keyword(s):

Mass Balance ◽

Oil Sands ◽

Surface Mining ◽

Open Pit ◽

Emission Rates ◽

Athabasca Oil Sands ◽

Emissions Inventory ◽

Athabasca Oil Sands Region ◽

Major Surface ◽

Tailings Ponds

Abstract. 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.

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Moose refugia from predation by wolves near mines in the Athabasca oil sands

10.7287/peerj.preprints.1967 ◽

2016 ◽

Author(s):

Eric Neilson ◽

Stan Boutin

Keyword(s):

Population Growth ◽

Human Disturbance ◽

Oil Sands ◽

Forest Cover ◽

Habitat Model ◽

Open Pit ◽

Natural Habitats ◽

Athabasca Oil Sands ◽

Human Use ◽

Tailings Ponds

Areas near human disturbance may become prey refugia when predators avoid human activities more than their prey leading to decreased predation rates and/or increased prey population growth. Alberta’s Athabasca oil sands region (AOSR) is home to moose (Alces alces) and wolf (Canis lupus) populations and is characterized by extensive human disturbance including open pit mines, tailings ponds and industrial facilities. We examined the extent to which moose could be released from predation near Alberta’s Athabasca oil sands due to wolf avoidance of mining infrastructure. Using moose and wolves GPS telemetry, we compared the use of natural habitats and distance to mining features to the availability of these variables. We split mining features into high human-use facilities and low human-use pit mines and tailings ponds. We binned distance to mining features variables into distance buffers covering the range of moose home range diameters resulting in buffers of < 2.5 km, 2.5-5 km and 5-10 km. Moose models included an interaction between distance to mining features buffers and the distribution of wolves to assess whether moose exposure to wolves varies with proximity to human activity. We compared a habitat model including forest cover type, streams and rivers to a disturbance model using AIC. The model fitting habitat and distance to facilities was top-ranked for both species. Moose selection for areas near facilities was higher than wolves. Wolves avoided areas within 10 and 5 km of facilities but exhibited an equivocal response within 2.5 km. Moose exposure to wolves increased with distance to mines indicating that use of areas in proximity to human disturbance releases moose from predation by wolves. Human induced prey refugia could increase moose population growth and increase human-moose conflict. Additionally, moose dispersal out of the refuge areas could produce subsequent increases in the wolf population.

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Using carbon-14 and carbon-13 measurements for source attribution of atmospheric methane in the Athabasca Oil Sands Region

10.5194/acp-2021-622 ◽

2021 ◽

Author(s):

Regina Gonzalez Moguel ◽

Felix Vogel ◽

Sébastien Ars ◽

Hinrich Schaefer ◽

Jocelyn Turnbull ◽

...

Keyword(s):

Oil Sands ◽

Surface Mining ◽

Atmospheric Methane ◽

Source Attribution ◽

Athabasca Oil Sands ◽

Ch4 Emissions ◽

Athabasca Oil Sands Region ◽

Carbon 14 ◽

Isotopic Characterization ◽

Tailings Ponds

Abstract. The rapidly expanding and energy intensive production from the Canadian oil sands, one of the largest oil reserves globally, accounts for almost 12 % of Canada’s greenhouse gas emissions according to inventories. Developing approaches for evaluating reported methane (CH4) emission is crucial for developing effective mitigation policies, but only one study has characterized CH4 sources in the Athabasca Oil Sands Region (AOSR). We tested the use of 14C and 13C carbon isotope measurements in ambient CH4 from the AOSR to estimate source contributions from key regional CH4 sources: (1) tailings ponds, (2) surface mines and processing facilities, and (3) wetlands. The isotopic signatures of ambient CH4 indicate that the CH4 enrichments measured at the site were mainly influenced by fossil CH4 emissions from surface mining and processing facilities (53 ± 18 %), followed by fossil CH4 emissions from tailings ponds (36 ± 18 %), and to a lesser extent by modern CH4 emissions from wetlands (10 < 1 %). Our results confirm the importance of tailings ponds in regional CH4 emissions and show that this method can successfully separate wetland CH4 emissions. In the future, the isotopic characterization of CH4 sources, and measurements from different seasons and wind directions are needed to provide a better source attribution in the AOSR.

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Moose refugia from predation by wolves near mines in the Athabasca oil sands

10.7287/peerj.preprints.1967v1 ◽

2016 ◽

Author(s):

Eric Neilson ◽

Stan Boutin

Keyword(s):

Population Growth ◽

Human Disturbance ◽

Oil Sands ◽

Forest Cover ◽

Habitat Model ◽

Open Pit ◽

Natural Habitats ◽

Athabasca Oil Sands ◽

Human Use ◽

Tailings Ponds

Areas near human disturbance may become prey refugia when predators avoid human activities more than their prey leading to decreased predation rates and/or increased prey population growth. Alberta’s Athabasca oil sands region (AOSR) is home to moose (Alces alces) and wolf (Canis lupus) populations and is characterized by extensive human disturbance including open pit mines, tailings ponds and industrial facilities. We examined the extent to which moose could be released from predation near Alberta’s Athabasca oil sands due to wolf avoidance of mining infrastructure. Using moose and wolves GPS telemetry, we compared the use of natural habitats and distance to mining features to the availability of these variables. We split mining features into high human-use facilities and low human-use pit mines and tailings ponds. We binned distance to mining features variables into distance buffers covering the range of moose home range diameters resulting in buffers of < 2.5 km, 2.5-5 km and 5-10 km. Moose models included an interaction between distance to mining features buffers and the distribution of wolves to assess whether moose exposure to wolves varies with proximity to human activity. We compared a habitat model including forest cover type, streams and rivers to a disturbance model using AIC. The model fitting habitat and distance to facilities was top-ranked for both species. Moose selection for areas near facilities was higher than wolves. Wolves avoided areas within 10 and 5 km of facilities but exhibited an equivocal response within 2.5 km. Moose exposure to wolves increased with distance to mines indicating that use of areas in proximity to human disturbance releases moose from predation by wolves. Human induced prey refugia could increase moose population growth and increase human-moose conflict. Additionally, moose dispersal out of the refuge areas could produce subsequent increases in the wolf population.

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Fish tainting in the Alberta oil sands region: a review of current knowledge

Water Quality Research Journal ◽

10.2166/wqrjc.2012.027 ◽

2012 ◽

Vol 47 (1) ◽

pp. 1-13 ◽

Cited By ~ 6

Author(s):

Janelle L. Tolton ◽

Rozlyn F. Young ◽

Wendy V. Wismer ◽

Phillip M. Fedorak

Keyword(s):

Oil Sands ◽

Current Knowledge ◽

Open Pit ◽

Open Pit Mining ◽

Science Literature ◽

Athabasca Oil Sands ◽

Oil Sands Mining ◽

The Media ◽

Northeastern Alberta ◽

Tailings Ponds

The Athabasca oil sands in northeastern Alberta, Canada represent the second largest petroleum reserve in the world. The process of extracting bitumen from the oil sands uses huge volumes of water, drawn from sources in the Athabasca River basin, and numerous mining companies operate adjacent to the river. Oil sands process-affected water (OSPW) from open pit mining is placed in large settling basins or tailings ponds that have the potential to leak. The goal is to eventually reclaim the tailings ponds to become functional ecosystems. Natural outcrops of oil sands in contact with surface waters also occur, and there are anecdotal reports in the media that fish caught near the Athabasca oil sands have an unusual flavor or odor. Several analytical and sensory studies have been undertaken to address this issue. Two major questions related to fish tainting arise: (1) Do the current oil sands mining, extraction and upgrading processes cause fish tainting in surrounding waters? (2) What is the tainting potential for fish that become established in reclaimed waters in the future? This review examines the types of compounds in OSPW that might contribute to tainting and the sensory science literature available related to fish tainting and the oil sands.

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WRF Model Simulations of the Influence of the Athabasca Oil Sands Development on Convective Storms

Earth Interactions ◽

10.1175/ei-d-17-0013.1 ◽

2018 ◽

Vol 22 (3) ◽

pp. 1-25 ◽

Cited By ~ 1

Author(s):

Daniel Brown ◽

Gerhard Reuter

Keyword(s):

Land Surface ◽

Oil Sands ◽

Waste Heat ◽

Model Simulation ◽

Wrf Model ◽

Initiation Time ◽

Athabasca Oil Sands ◽

Model Simulations ◽

Surface Disturbance

Abstract The Athabasca oil sands development has created a land surface disturbance of almost 900 km2 in northeastern Alberta. Both through industrial processes and the removal of boreal forest vegetation, this surface disturbance impacts meteorology in the vicinity by releasing waste heat, raising the surface temperature, and lowering the surface humidity. To investigate the effects of the Athabasca oil sands development on thunderstorm intensity, initiation time, and duration, the Weather Research and Forecasting (WRF) Model was employed to simulate the effect of the surface disturbance on atmospheric conditions on 10 case study days. The results suggested the oil sands surface disturbance was not associated with substantial increases in thunderstorm intensity on any of the case study days. On two case study days, however, the WRF Model simulations differed substantially from the observed meteorological conditions and only approached the observations when the oil sands surface disturbance was included in the model simulation. Including the oil sands surface disturbance in the model simulations resulted in thunderstorm initiation about 2 h earlier and increased thunderstorm duration. Data from commercial aircraft showed that the 850–500-mb temperature difference was greater than 30°C (very unstable) only on these 2 days. Such cases are sufficiently rare that they are not expected to affect the overall thunderstorm climatology. Still, in these very unstable cases, the oil sands development appears to have a significant effect on thunderstorm initiation time and duration.

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Novel Techniques for Anticipating the Focus of Visual Attention across Different Mining Landscapes

Materials Proceedings ◽

10.3390/materproc2021005020 ◽

2021 ◽

Vol 5 (1) ◽

pp. 20

Author(s):

Loukas-Moysis Misthos ◽

Maria Menegaki

Keyword(s):

Visual Attention ◽

Eye Tracking ◽

Socioeconomic Development ◽

Surface Mining ◽

Focus Of Attention ◽

Open Pit ◽

Mining Activities ◽

Open Pit Mines ◽

Attention Focus ◽

Landscape Alteration

Surface mining activities support socioeconomic development but also cause significant landscape alteration and degradation. By definition, the concept of landscape requires observers; thus, the way mining landscapes are actually observed needs to be taken into consideration for mitigating visual nuisance from open pit mines. This paper utilizes eye tracking techniques for recording and rendering the actual attention patterns of observers, along with saliency models that ‘predict’ the focus of attention in mining landscape photographs. As it turns out, saliency models can aid in reliably anticipating the attention focus across a range of different mining landscapes.

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Principal component analysis of summertime ground site measurements in the Athabasca oil sands: Sources of IVOCs

10.5194/acp-2017-1026 ◽

2018 ◽

Cited By ~ 1

Author(s):

Travis W. Tokarek ◽

Charles A. Odame-Ankrah ◽

Jennifer A. Huo ◽

Robert McLaren ◽

Alex K. Y. Lee ◽

...

Keyword(s):

Principal Component Analysis ◽

Organic Compounds ◽

Mass Spectrometer ◽

Oil Sands ◽

Principal Component ◽

Component Analysis ◽

Open Pit ◽

Open Pit Mining ◽

Mining Operations ◽

Athabasca Oil Sands

Abstract. 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.

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