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Wren SN, McLinden CA, Griffin D, Li SM, Cober SG, Darlington A, Hayden K, Mihele C, Mittermeier RL, Wheeler MJ, Wolde M, Liggio J. Aircraft and satellite observations reveal historical gap between top-down and bottom-up CO 2 emissions from Canadian oil sands. PNAS NEXUS 2023; 2:pgad140. [PMID: 37168672 PMCID: PMC10165801 DOI: 10.1093/pnasnexus/pgad140] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 05/13/2023]
Abstract
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 CO2 emissions that combines aircraft-measured CO2/NOx emission ratios (ERs) with inventory and satellite-derived NOx 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 CO2 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 CO2 emissions by taking advantage of satellite remote sensing observations.
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Affiliation(s)
- Sumi N Wren
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
| | - Chris A McLinden
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
| | - Debora Griffin
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
| | - Shao-Meng Li
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Stewart G Cober
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
| | - Andrea Darlington
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
| | - Katherine Hayden
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
| | - Cristian Mihele
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
| | - Richard L Mittermeier
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
| | - Michael J Wheeler
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
| | - Mengistu Wolde
- Flight Research Laboratory, National Research Council Canada Aerospace Research Centre, Ottawa, ON K1V 1J8, Canada
| | - John Liggio
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
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Horb EC, Wentworth GR, Makar PA, Liggio J, Hayden K, Boutzis EI, Beausoleil DL, Hazewinkel RO, Mahaffey AC, Sayanda D, Wyatt F, Dubé MG. A decadal synthesis of atmospheric emissions, ambient air quality, and deposition in the oil sands region. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2022; 18:333-360. [PMID: 34676977 PMCID: PMC9299045 DOI: 10.1002/ieam.4539] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 09/24/2021] [Accepted: 10/01/2021] [Indexed: 05/20/2023]
Abstract
This review is part of a series synthesizing peer-reviewed literature from the past decade on environmental monitoring in the oil sands region (OSR) of northeastern Alberta. It focuses on atmospheric emissions, air quality, and deposition in and downwind of the OSR. Most published monitoring and research activities were concentrated in the surface-mineable region in the Athabasca OSR. Substantial progress has been made in understanding oil sands (OS)-related emission sources using multiple approaches: airborne measurements, satellite measurements, source emission testing, deterministic modeling, and source apportionment modeling. These approaches generally yield consistent results, indicating OS-related sources are regional contributors to nearly all air pollutants. Most pollutants exhibit enhanced air concentrations within ~20 km of surface-mining activities, with some enhanced >100 km downwind. Some pollutants (e.g., sulfur dioxide, nitrogen oxides) undergo transformations as they are transported through the atmosphere. Deposition rates of OS-related substances primarily emitted as fugitive dust are enhanced within ~30 km of surface-mining activities, whereas gaseous and fine particulate emissions have a more diffuse deposition enhancement pattern extending hundreds of kilometers downwind. In general, air quality guidelines are not exceeded, although these single-pollutant thresholds are not comprehensive indicators of air quality. Odor events have occurred in communities near OS industrial activities, although it can be difficult to attribute events to specific pollutants or sources. Nitrogen, sulfur, polycyclic aromatic compounds (PACs), and base cations from OS sources occur in the environment, but explicit and deleterious responses of organisms to these pollutants are not as apparent across all study environments; details of biological monitoring are discussed further in other papers in this special series. However, modeling of critical load exceedances suggests that, at continued emission levels, ecological change may occur in future. Knowledge gaps and recommendations for future work to address these gaps are also presented. Integr Environ Assess Manag 2022;18:333-360. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
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Affiliation(s)
- Erin C. Horb
- Resource Stewardship DivisionAlberta Environment and ParksCalgaryAlbertaCanada
| | - Gregory R. Wentworth
- Resource Stewardship DivisionAlberta Environment and ParksEdmontonAlbertaCanada
- Present address: Environmental Protection BranchEnvironment and Climate Change CanadaEdmontonAlbertaCanada
| | - Paul A. Makar
- Air Quality Research DivisionEnvironment and Climate Change CanadaTorontoOntarioCanada
| | - John Liggio
- Air Quality Research DivisionEnvironment and Climate Change CanadaTorontoOntarioCanada
| | - Katherine Hayden
- Air Quality Research DivisionEnvironment and Climate Change CanadaTorontoOntarioCanada
| | | | | | | | - Ashley C. Mahaffey
- Resource Stewardship DivisionAlberta Environment and ParksCalgaryAlbertaCanada
| | - Diogo Sayanda
- Resource Stewardship DivisionAlberta Environment and ParksCalgaryAlbertaCanada
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Synthesis of Rod-Like Co3O4 Catalyst Derived from Co-MOFs with Rich Active Sites for Catalytic Combustion of Toluene. CATALYSIS SURVEYS FROM ASIA 2021. [DOI: 10.1007/s10563-021-09351-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Moussa SG, Staebler RM, You Y, Leithead A, Yousif MA, Brickell P, Beck J, Jiang Z, Liggio J, Li SM, Wren SN, Brook JR, Darlington A, Cober SG. Fugitive Emissions of Volatile Organic Compounds from a Tailings Pond in the Oil Sands Region of Alberta. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:12831-12840. [PMID: 34524801 DOI: 10.1021/acs.est.1c02325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Tailings ponds in the oil sands (OS) region in Alberta, Canada, have been associated with fugitive emissions of volatile organic compounds (VOCs) and other pollutants to the atmosphere. However, the contribution of tailings ponds to the total fugitive emissions of VOCs from OS operations remains uncertain. To address this knowledge gap, a field study was conducted in the summer of 2017 at Suncor's Pond 2/3 to estimate emissions of a suite of pollutants including 68 VOCs using a combination of micrometeorological methods and measurements from a flux tower. The results indicate that in 2017, Pond 2/3 was an emission source of 3322 ± 727 tons of VOCs including alkanes, aromatics, and oxygenated and sulfur-containing organics. While the total VOC emissions were approximately a factor of 2 higher than those reported by Suncor, the individual VOC species emissions varied by up to a factor of 12. A chemical mass balance (CMB) receptor model was used to estimate the contribution of the tailings pond to VOC pollution events in a nearby First Nations and Metis community in Fort McKay. CMB results indicate that Suncor Pond 2/3 contributed up to 57% to the total mass of VOCs measured at Fort McKay, reinforcing the importance of accurate VOC emission estimation methods for tailings ponds.
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Affiliation(s)
- Samar G Moussa
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - Ralf M Staebler
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - Yuan You
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - Amy Leithead
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - Meguel A Yousif
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - Peter Brickell
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - James Beck
- Suncor Energy Inc., Calgary, Alberta T2P 3Y7, Canada
| | - Zhimei Jiang
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - John Liggio
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - Shao-Meng Li
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
- College of Environmental Science and Engineering, Peking University, Beijing 100871, China
| | - Sumi N Wren
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - Jeffrey R Brook
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
- Dalla Lana School of Public Health and Department of Chemical Engineering and Applied Chemistry, University of Toronto, 223 College Street, Toronto, Ontario M5T 1R4, Canada
| | - Andrea Darlington
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
| | - Stewart G Cober
- Air Quality Processes Research Section, Air Quality Research Division, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
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Mamun AA, Celo V, Dabek-Zlotorzynska E, Charland JP, Cheng I, Zhang L. Characterization and source apportionment of airborne particulate elements in the Athabasca oil sands region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 788:147748. [PMID: 34134367 DOI: 10.1016/j.scitotenv.2021.147748] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 04/01/2021] [Accepted: 05/09/2021] [Indexed: 06/12/2023]
Abstract
The oil sands industries in Alberta, Canada are potential sources of particulate-bound elements in the region. This study explored the ambient concentrations and size distributions, and conducted source apportionment of 48 particulate elements, based on samples collected in 2016-2017 at four air monitoring sites in the Athabasca oil sands region: Fort McKay (AMS1), Buffalo Viewpoint (AMS4), Wapasu Creek (AMS17), and Stoney Mountain (AMS18). Element concentrations in fine and coarse particulate matter (PM2.5 and PM2.5-10 respectively) at the four sites were generally lower than their typical concentrations at other urban and industrial sites in North America. Among all elements, S was the most abundant in PM2.5 with mean concentrations ranging from 189 ng/m3 (AMS18) to 284 ng/m3 (AMS1). Of the trace, toxic elements in PM2.5, Zn was the most abundant with mean concentrations ranging from 3.43 ng/m3 (AMS18) to 5.37 ng/m3 (AMS4). Positive Matrix Factorization (PMF) modeling of the element concentrations in PM2.5 was used for source apportionment for Zone1 (including AMS 1, 4, and 17, situated closer to industrial activities) and for Zone2 (including AMS18, a background site). The sources of elements for Zone1, included crustal dust, bitumen processing, haul road dust, and biomass burning that explained ~33%, ~43%, ~15%, and ~9% of the total resolved elemental mass, respectively. The sources of elements for Zone2, included Pb-rich source, biomass burning, fugitive oil sands, crustal dust, and bitumen processing explaining ~8%, ~7%, ~3%, ~22%, and ~60% of the total resolved elemental mass, respectively. Elemental mass concentrations of the bitumen processing source factor at Zone2 was two-thirds of that in Zone1. Overall, mass proportions of the bitumen processing source factor at all four sites were significant, suggesting that the oil sands industries played a key role in ambient element concentration levels in the region.
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Affiliation(s)
- Abdulla Al Mamun
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, Ontario M3H 5T4, Canada
| | - Valbona Celo
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Ottawa, Ontario K1V 1C7, Canada.
| | - Ewa Dabek-Zlotorzynska
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Ottawa, Ontario K1V 1C7, Canada
| | - Jean-Pierre Charland
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Ottawa, Ontario K1V 1C7, Canada
| | - Irene Cheng
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, Ontario M3H 5T4, Canada
| | - Leiming Zhang
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, Ontario M3H 5T4, Canada.
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