Articles | Volume 21, issue 16
https://doi.org/10.5194/acp-21-12783-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-12783-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impact of Athabasca oil sands operations on mercury levels in air and deposition
Ashu Dastoor
CORRESPONDING AUTHOR
Air Quality Research Division, Environment and Climate Change Canada,
2121 Trans-Canada Highway, Dorval, Québec, Canada
Andrei Ryjkov
Air Quality Research Division, Environment and Climate Change Canada,
2121 Trans-Canada Highway, Dorval, Québec, Canada
Gregor Kos
Department of Chemistry and Biochemistry, Concordia University, 7141
Sherbrooke Street West, Montreal, Québec, Canada
Junhua Zhang
Air Quality Research Division, Environment and Climate Change Canada,
4905 Dufferin Street, Toronto, Ontario, Canada
Jane Kirk
Aquatic Contaminants Research Division, Environment and Climate Change
Canada, 867 Lakeshore Road, Burlington, Ontario, Canada
Matthew Parsons
Meteorological Service of Canada, Environment and Climate Change
Canada, 9250 49 Street NW, Edmonton, Alberta, Canada
Alexandra Steffen
Air Quality Research Division, Environment and Climate Change Canada,
4905 Dufferin Street, Toronto, Ontario, Canada
Related authors
Kirill Semeniuk, Ashu Dastoor, and Alex Lupu
Geosci. Model Dev., 18, 6479–6515, https://doi.org/10.5194/gmd-18-6479-2025, https://doi.org/10.5194/gmd-18-6479-2025, 2025
Short summary
Short summary
The Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) inorganic aerosol sub-model has been implemented in the Global Environmental Multiscale – Modeling Air Quality and Chemistry (GEM-MACH) air quality model. MOSAIC includes metal cation reactions and is a non-equilibrium, double-moment scheme that conserves aerosol number. Compared to the current aerosol sub-model, MOSAIC produces a more accurate size distribution and aerosol number concentration. It also improves the simulated nitrate and ammonium distribution. This work serves to expand the capacity of GEM-MACH for chemistry and weather coupling.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Short summary
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Mohammad Mortezazadeh, Jean-François Cossette, Ashu Dastoor, Jean de Grandpré, Irena Ivanova, and Abdessamad Qaddouri
Geosci. Model Dev., 17, 335–346, https://doi.org/10.5194/gmd-17-335-2024, https://doi.org/10.5194/gmd-17-335-2024, 2024
Short summary
Short summary
The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach. In this paper we implement a new interpolation scheme into the semi-Lagrangian approach which has the same computational cost as a third-order polynomial scheme but with the accuracy of a fourth-order interpolation scheme. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps.
Robin Stevens, Andrei Ryjkov, Mahtab Majdzadeh, and Ashu Dastoor
Atmos. Chem. Phys., 22, 13527–13549, https://doi.org/10.5194/acp-22-13527-2022, https://doi.org/10.5194/acp-22-13527-2022, 2022
Short summary
Short summary
Absorbing particles like black carbon can be coated with other matter. How much radiation these particles absorb depends on the coating thickness. The removal of these particles by clouds and rain depends on the coating composition. These effects are important for both climate and air quality. We implement a more detailed representation of these particles in an air quality model which accounts for both coating thickness and composition. We find a significant effect on particle concentrations.
Kirill Semeniuk, Ashu Dastoor, and Alex Lupu
Geosci. Model Dev., 18, 6479–6515, https://doi.org/10.5194/gmd-18-6479-2025, https://doi.org/10.5194/gmd-18-6479-2025, 2025
Short summary
Short summary
The Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) inorganic aerosol sub-model has been implemented in the Global Environmental Multiscale – Modeling Air Quality and Chemistry (GEM-MACH) air quality model. MOSAIC includes metal cation reactions and is a non-equilibrium, double-moment scheme that conserves aerosol number. Compared to the current aerosol sub-model, MOSAIC produces a more accurate size distribution and aerosol number concentration. It also improves the simulated nitrate and ammonium distribution. This work serves to expand the capacity of GEM-MACH for chemistry and weather coupling.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Short summary
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Mohammad Mortezazadeh, Jean-François Cossette, Ashu Dastoor, Jean de Grandpré, Irena Ivanova, and Abdessamad Qaddouri
Geosci. Model Dev., 17, 335–346, https://doi.org/10.5194/gmd-17-335-2024, https://doi.org/10.5194/gmd-17-335-2024, 2024
Short summary
Short summary
The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach. In this paper we implement a new interpolation scheme into the semi-Lagrangian approach which has the same computational cost as a third-order polynomial scheme but with the accuracy of a fourth-order interpolation scheme. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps.
Robin Stevens, Andrei Ryjkov, Mahtab Majdzadeh, and Ashu Dastoor
Atmos. Chem. Phys., 22, 13527–13549, https://doi.org/10.5194/acp-22-13527-2022, https://doi.org/10.5194/acp-22-13527-2022, 2022
Short summary
Short summary
Absorbing particles like black carbon can be coated with other matter. How much radiation these particles absorb depends on the coating thickness. The removal of these particles by clouds and rain depends on the coating composition. These effects are important for both climate and air quality. We implement a more detailed representation of these particles in an air quality model which accounts for both coating thickness and composition. We find a significant effect on particle concentrations.
Paul A. Makar, Craig Stroud, Ayodeji Akingunola, Junhua Zhang, Shuzhan Ren, Philip Cheung, and Qiong Zheng
Atmos. Chem. Phys., 21, 12291–12316, https://doi.org/10.5194/acp-21-12291-2021, https://doi.org/10.5194/acp-21-12291-2021, 2021
Short summary
Short summary
Vehicle pollutant emissions occur in an environment where upward transport can be enhanced due to the turbulence created by the vehicles as they move through the atmosphere. An approach for including these turbulence effects in regional air pollution forecast models has been derived from theoretical, observation, and higher-resolution modeling. The enhanced mixing, which occurs in the immediate vicinity of roadways, changes pollutant concentrations on the regional to continental scale.
Paul A. Makar, Ayodeji Akingunola, Jack Chen, Balbir Pabla, Wanmin Gong, Craig Stroud, Christopher Sioris, Kerry Anderson, Philip Cheung, Junhua Zhang, and Jason Milbrandt
Atmos. Chem. Phys., 21, 10557–10587, https://doi.org/10.5194/acp-21-10557-2021, https://doi.org/10.5194/acp-21-10557-2021, 2021
Short summary
Short summary
We have examined the effects of airborne particles on absorption and scattering of incoming sunlight by the particles themselves via cloud formation. We used an advanced, combined high-resolution weather forecast and chemical transport computer model, for western North America, and simulations with and without the connections between particles and weather enabled. Feedbacks improved weather and air pollution forecasts and changed cloud behaviour and forest-fire pollutant amount and height.
Katherine Hayden, Shao-Meng Li, Paul Makar, John Liggio, Samar G. Moussa, Ayodeji Akingunola, Robert McLaren, Ralf M. Staebler, Andrea Darlington, Jason O'Brien, Junhua Zhang, Mengistu Wolde, and Leiming Zhang
Atmos. Chem. Phys., 21, 8377–8392, https://doi.org/10.5194/acp-21-8377-2021, https://doi.org/10.5194/acp-21-8377-2021, 2021
Short summary
Short summary
We developed a method using aircraft measurements to determine lifetimes with respect to dry deposition for oxidized sulfur and nitrogen compounds over the boreal forest in Alberta, Canada. Atmospheric lifetimes were significantly shorter than derived from chemical transport models with differences related to modelled dry deposition velocities. The shorter lifetimes suggest models need to reassess dry deposition treatment and predictions of sulfur and nitrogen in the atmosphere and ecosystems.
Attilio Naccarato, Antonella Tassone, Maria Martino, Sacha Moretti, Antonella Macagnano, Emiliano Zampetti, Paolo Papa, Joshua Avossa, Nicola Pirrone, Michelle Nerentorp, John Munthe, Ingvar Wängberg, Geoff W. Stupple, Carl P. J. Mitchell, Adam R. Martin, Alexandra Steffen, Diana Babi, Eric M. Prestbo, Francesca Sprovieri, and Frank Wania
Atmos. Meas. Tech., 14, 3657–3672, https://doi.org/10.5194/amt-14-3657-2021, https://doi.org/10.5194/amt-14-3657-2021, 2021
Short summary
Short summary
Mercury monitoring in support of the Minamata Convention requires effective and reliable analytical tools. Passive sampling is a promising approach for creating a sustainable long-term network for atmospheric mercury with improved spatial resolution and global coverage. In this study the analytical performance of three passive air samplers (CNR-PAS, IVL-PAS, and MerPAS) was assessed over extended deployment periods and the accuracy of concentrations was judged by comparison with active sampling.
David S. McLagan, Geoff W. Stupple, Andrea Darlington, Katherine Hayden, and Alexandra Steffen
Atmos. Chem. Phys., 21, 5635–5653, https://doi.org/10.5194/acp-21-5635-2021, https://doi.org/10.5194/acp-21-5635-2021, 2021
Short summary
Short summary
An assessment of mercury emissions from a burning boreal forest was made by flying an aircraft through its plume to collect in situ gas and particulate measurements. Direct data show that in-plume gaseous elemental mercury concentrations reach up to 2.4× background for this fire and up to 5.6× when using a correlation with CO data. These unique data are applied to a series of known empirical emissions estimates and used to highlight current uncertainties in the literature.
Cited articles
Alexander, A. C. and Chambers, P. A.: Assessment of seven Canadian rivers in
relation to stages in oil sands industrial development, 1972–2010,
Environ. Rev., 24, 484–494, https://doi.org/10.1139/er-2016-0033,
2016.
AMAP and UNEP: Technical Background Report for the Global Mercury Assessment 2013, Arctic Monitoring and Assessment Programme, Oslo, Norway/UNEP Chemicals Branch, Geneva, Switzerland, 263 pp., 2013.
Angot, H., Dastoor, A., De Simone, F., Gårdfeldt, K., Gencarelli, C. N., Hedgecock, I. M., Langer, S., Magand, O., Mastromonaco, M. N., Nordstrøm, C., Pfaffhuber, K. A., Pirrone, N., Ryjkov, A., Selin, N. E., Skov, H., Song, S., Sprovieri, F., Steffen, A., Toyota, K., Travnikov, O., Yang, X., and Dommergue, A.: Chemical cycling and deposition of atmospheric mercury in polar regions: review of recent measurements and comparison with models, Atmos. Chem. Phys., 16, 10735–10763, https://doi.org/10.5194/acp-16-10735-2016, 2016.
APEI: Government of Canada, Air Pollutant Emissions Inventory, available at:
https://www.canada.ca/en/environment-climate-change/services/pollutants/air-emissions-inventory-overview.html,
last access: 25 July 2019.
Bieser, J., Slemr, F., Ambrose, J., Brenninkmeijer, C., Brooks, S., Dastoor, A., DeSimone, F., Ebinghaus, R., Gencarelli, C. N., Geyer, B., Gratz, L. E., Hedgecock, I. M., Jaffe, D., Kelley, P., Lin, C.-J., Jaegle, L., Matthias, V., Ryjkov, A., Selin, N. E., Song, S., Travnikov, O., Weigelt, A., Luke, W., Ren, X., Zahn, A., Yang, X., Zhu, Y., and Pirrone, N.: Multi-model study of mercury dispersion in the atmosphere: vertical and interhemispheric distribution of mercury species, Atmos. Chem. Phys., 17, 6925–6955, https://doi.org/10.5194/acp-17-6925-2017, 2017.
Bloom, N. S. and Crecelius, E. A.: Determination of mercury in seawater at
sub-nanogram per liter levels, Mar. Chem., 14, 49–59,
https://doi.org/10.1016/0304-4203(83)90069-5, 1983.
CAPMoN: Canadian Acid Precipitation Monitoring Network, available at: https://www.canada.ca/en/environment-climate-change/services/air-pollution/monitoring-networks-data/canadian-air-precipitation.html, last access: 16 August 2021.
CMSA: Canadian Mercury Science Assessment 2016, Clean Air Regulatory Agenda,
437–556, 2016.
Cooke, C. A., Kirk, J. L., Muir, D. C. G., Wiklund, J. A., Wang, X.,
Gleason, A., and Evans, M. S.: Spatial and temporal patterns in trace
element deposition to lakes in the Athabasca oil sands region (Alberta,
Canada), Environ. Res. Lett., 12,
https://doi.org/10.1088/1748-9326/aa9505, 2017.
Dastoor, A. P. and Durnford, D. A.: Arctic Ocean: Is it a sink or a source
of atmospheric mercury?, Environ. Sci. Technol., 48,
1707–1717, https://doi.org/10.1021/es404473e, 2014.
Dastoor, A. P., Davignon, D., Theys, N., Van Roozendael, M., Steffen, A.,
and Ariya, P. A.: Modeling dynamic exchange of gaseous elemental mercury at
polar sunrise, Environ. Sci. Technol., 42, 5183–5188, 2008.
Dastoor, A., Ryzhkov, A., Durnford, D., Lehnherr, I., Steffen, A., and Morrison, H.: Atmospheric mercury in the Canadian Arctic. Part II: insight from modeling, Sci. Total Environ., 509–510, 16–27, https://doi.org/10.1016/j.scitotenv.2014.10.112, 2015.
De Simone, F., Cinnirella, S., Gencarelli, C. N., Yang, X., Hedgecock, I.
M., and Pirrone, N.: Model study of global mercury deposition from biomass
burning, Environ. Sci. Technol., 49, 6712–6721, 2015.
Durnford, D., Dastoor, A., Figueras-Nieto, D., and Ryjkov, A.: Long range transport of mercury to the Arctic and across Canada, Atmos. Chem. Phys., 10, 6063–6086, https://doi.org/10.5194/acp-10-6063-2010, 2010.
Durnford, D., Dastoor, A., Ryzhkov, A., Poissant, L., Pilote, M., and Figueras-Nieto, D.: How relevant is the deposition of mercury onto snowpacks? – Part 2: A modeling study, Atmos. Chem. Phys., 12, 9251–9274, https://doi.org/10.5194/acp-12-9251-2012, 2012.
ECCC: Environment and Climate Change Canada, Oil Sands Data Portal, available at:
https://www.canada.ca/en/environment-climate-change/services/oil-sands-monitoring/monitoring-air-quality-alberta-oil-sands.html, last access: 16 August 2021.
Eckley, C. S., Parsons, M. T., Mintz, R., Lapalme, M., Mazur, M., Tordon,
R., Elleman, R., Graydon, J. A., Blanchard, P., and St Louis, V.: Impact of
closing Canada's largest point-source of mercury emissions on local
atmospheric mercury concentrations, Environ. Sci. Technol., 47, 10339–10348,
https://doi.org/10.1021/es401352n, 2013.
Emmerton, C. A., Cooke, C. A., Wentworth, G. R., Graydon, J. A., Ryjkov, A.,
and Dastoor, A.: Total Mercury and Methylmercury in Lake Water of Canada's
Oil Sands Region, Environ. Sci. Technol., 52, 10946–10955,
https://doi.org/10.1021/acs.est.8b01680, 2018.
EPA: Method 1669: sampling ambient water for trace metals at EPA water quality criteria levels, Washington, D.C., United States, Environmental Protection Agency, Office of Water, Engineering and Analysis Division, 1996.
EPA: United States Government: EPA Air Emissions Inventories,
available at: https://www.epa.gov/air-emissions-inventories, last access: 25 July 2019.
Faïn, X., Helmig, D., Hueber, J., Obrist, D., and Williams, M. W.: Mercury dynamics in the Rocky Mountain, Colorado, snowpack, Biogeosciences, 10, 3793–3807, https://doi.org/10.5194/bg-10-3793-2013, 2013.
Fraser, A., Dastoor, A., and Ryjkov, A.: How important is biomass burning in Canada to mercury contamination?, Atmos. Chem. Phys., 18, 7263–7286, https://doi.org/10.5194/acp-18-7263-2018, 2018.
Friedli, H. R., Radke, L. F., and Lu, J. Y.: Mercury in smoke from biomass
fires, Geophys. Res. Lett., 28, 3223–3226, 2001.
GoC: Government of Canada, Historical Climate Data, available at:
https://climate.weather.gc.ca, last access: 19 February 2019.
Gopalapillai, Y., Kirk, J. L., Landis, M. S., Muir, D. C. G., Cooke, C. A.,
Gleason, A., Ho, A., Kelly, E., Schindler, D., Wang, X., and Lawson, G.:
Source Analysis of Pollutant Elements in Winter Air Deposition in the
Athabasca Oil Sands Region: A Temporal and Spatial Study, ACS Earth
Space Chem. 3, 1656–1668,
https://doi.org/10.1021/acsearthspacechem.9b00150, 2019.
Graydon, J. A., St. Louis, V. L., Lindberg, S. E., Hintelmann, H., and
Krabbenhoft, D. P.: Investigation of Mercury Exchange between Forest Canopy
Vegetation and the Atmosphere Using a New Dynamic Chamber, Environ.
Sci. Technol., 40, 4680–4688,
https://doi.org/10.1021/es0604616, 2006.
Gustin, M. S., Huang, J., Miller, M. B., Peterson, C., Jaffe, D. A.,
Ambrose, J., Finley, B. D., Lyman, S. N., Call, K., Talbot, R., Feddersen,
D., Mao, H., and Lindberg, S. E.: Do We Understand What the Mercury
Speciation Instruments Are Actually Measuring? Results of RAMIX.,
Environ. Sci. Technol., 47, 7295–7306, https://doi.org/10.1021/es3039104,
2013.
Gustin, M. S., Amos, H. M., Huang, J., Miller, M. B., and Heidecorn, K.: Measuring and modeling mercury in the atmosphere: a critical review, Atmos. Chem. Phys., 15, 5697–5713, https://doi.org/10.5194/acp-15-5697-2015, 2015.
Jia, L.: Oil Sands Bitumen Emulsion Upgrading by Using In Situ Hydrogen Generated through the Water Gas Shift Reaction, PhD Thesis, University of Waterloo, Waterloo, ON, Canada, available at: http://hdl.handle.net/10012/8969 (last access: 17 August 2021), 2014.
Kelly, E. N., Schindler, D. W., Hodson, P. V., Short, J. W., Radmanovich,
R., and Nielsen, C. C.: Oil sands development contributes elements toxic at
low concentrations to the Athabasca River and its tributaries, P.
Natl. Acad. Sci. USA, 107, 16178–16183,
https://doi.org/10.1073/pnas.1008754107, 2010.
Kirk, J. L., Muir, D. C. G., Gleason, A., Wang, X., Lawson, G., Frank, R.
A., Lehnherr, I., and Wrona, F.: Atmospheric deposition of mercury and
methylmercury to landscapes and waterbodies of the Athabasca oil sands
region, Environ. Sci. Technol., 48, 7374–7383, 2014.
Kos, G., Ryzhkov, A., Dastoor, A., Narayan, J., Steffen, A., Ariya, P. A., and Zhang, L.: Evaluation of discrepancy between measured and modelled oxidized mercury species, Atmos. Chem. Phys., 13, 4839–4863, https://doi.org/10.5194/acp-13-4839-2013, 2013.
Larter, S. R. and Head, I. M.: Oil sands and heavy oil: origin and
exploitation, Elements, 10, 277–283, 2014.
Lynam, M., Dvonch, J. T., Barres, J., and Percy, K.: Atmospheric wet
deposition of mercury to the Athabasca oil sands region, Alberta, Canada,
Air Qual. Atmos. Hlth., 11, 83–93, 2018.
Ma, J., Hintelmann, H., Kirk, J., and Muir, D.: Mercury concentrations and
mercury isotope composition in lake sediment cores from the vicinity of a
metal smelting facility in Flin Flon, Manitoba, Chem. Geol., 336, 96–102,
https://doi.org/10.1016/j.chemgeo.2012.10.037, 2012.
Makar, P., Akingunola, A., Pabla, B., Stroud, C., Chen, J., Cheung, P.,
Moran, M., Gong, W., Zheng, Q., and Li, S. M.: Experimental Forecasting Using the High-Resolution Research Configuration of GEM-MACH, in: Air Pollution Modeling and its Application XXVI, edited by: Mensink C., Gong W., Hakami A., ITM 2018, Springer Proceedings in Complexity, Springer, Cham, https://doi.org/10.1007/978-3-030-22055-6_35, 2018.
Muir, D. C. G., Wang, X., Yang, F., Nguyen, N., Jackson, T. A., Evans, M. S.,
Douglas, M., Kock, G., Lamoureux, S., Pienitz, R., Smol, J. P., Vincent,
W. F., and Dastoor, A.: Spatial trends and historical deposition of
mercury in eastern and northern Canada inferred from lake sediment cores,
Environ. Sci. Technol., 43, 4802–4809, 2009.
NPRI: Government of Canada, Access the reporting guide for the National
Pollutant Release Inventory, available at:
https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/report/access-reporting-guide.html,
last access: 25 July 2019.
Obrist, D., Pearson, C., Webster, J., Kane, T., Lin, C., Aiken, G. R., and Alpers, C. N.: A synthesis of terrestrial mercury in the western United States:
Spatial distribution defined by land cover and plant productivity, Sci. Total Environ., 568,
522–535, https://doi.org/10.1016/j.scitotenv.2015.11.104, 2016.
Parsons, M., McLennan, D., Lapalme, M., Mooney, C., Watt, C., and Mintz, R.:
Total gaseous mercury concentration measurements at Fort McMurray, Alberta,
Canada, Atmosphere 4, 472–493, https://doi.org/10.3390/atmos4040472, 2013.
Steffen, A. and Schroeder, W. H.: Standard Operating Procedures Manual
Procedure for Total Gaseous Mercury Measurements-Canadian Atmospheric
Mercury Measurement Network (CAMNet), Meteorological Service of Canada 4905,
1999.
Travnikov, O., Angot, H., Artaxo, P., Bencardino, M., Bieser, J., D'Amore, F., Dastoor, A., De Simone, F., Diéguez, M. D. C., Dommergue, A., Ebinghaus, R., Feng, X. B., Gencarelli, C. N., Hedgecock, I. M., Magand, O., Martin, L., Matthias, V., Mashyanov, N., Pirrone, N., Ramachandran, R., Read, K. A., Ryjkov, A., Selin, N. E., Sena, F., Song, S., Sprovieri, F., Wip, D., Wängberg, I., and Yang, X.: Multi-model study of mercury dispersion in the atmosphere: atmospheric processes and model evaluation, Atmos. Chem. Phys., 17, 5271–5295, https://doi.org/10.5194/acp-17-5271-2017, 2017.
UN: Minamata Convention on Mercury, 72, available at: http://www.mercuryconvention.org (last access: 17 August 2021), 2017.
UNEP: The Global Atmospheric Mercury Assessment: Sources, Emissions and Transport, UNEP-Chemicals, Geneva, 2008
UNEP: Global Mercury Assessment 2013: Sources, Emissions, Releases
and Environmental Transport, UNEP Chemicals Branch, Geneva, Switzerland, 2013.
UNEP: Global Mercury Assessment, UN Environment Programme, Chemicals and Health Branch, Geneva, Switzerland, 2018.
Wasiuta, V., Kirk, J. L., Chambers, P. A., Alexander, A. C., Wyatt, F. R.,
Rooney, R. C., and Cooke, C. A.: Accumulating Mercury and Methylmercury
Burdens in Watersheds Impacted by Oil Sands Pollution, Environ. Sci. Technol.,
53, 12856–12864, https://doi.org/10.1021/acs.est.9b02373, 2019.
Whaley, C. H., Galarneau, E., Makar, P. A., Akingunola, A., Gong, W., Gravel, S., Moran, M. D., Stroud, C., Zhang, J., and Zheng, Q.: GEM-MACH-PAH (rev2488): a new high-resolution chemical transport model for North American polycyclic aromatic hydrocarbons and benzene, Geosci. Model Dev., 11, 2609–2632, https://doi.org/10.5194/gmd-11-2609-2018, 2018.
Wiedinmyer, C. and Friedli, H.: Mercury emission estimates from fires: An
initial inventory for the United States, Environ. Sci.
Technol., 41, 8092–8098, https://doi.org/10.1021/es071289o, 2007.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Willis, C. E., Kirk, J. L., St Louis, V. L., Lehnherr, I., Ariya, P. A., and
Rangel-Alvarado, R. B.: Sources of Methylmercury to Snowpacks of the Alberta
Oil Sands Region: A Study of In Situ Methylation and Particulates, Environ.
Sci. Technol., 52, 531–540, https://doi.org/10.1021/acs.est.7b04096, 2018.
Willis, C. E., St Louis, V. L., Kirk, J. L., St Pierre, K. A., and Dodge,
C.: Tailings ponds of the Athabasca Oil Sands Region, Alberta, Canada, are
likely not significant sources of total mercury and methylmercury to nearby
ground and surface waters, Sci. Total Environ., 647, 1604–1610,
https://doi.org/10.1016/j.scitotenv.2018.08.083, 2019.
Wright, L. P., Zhang, L., and Marsik, F. J.: Overview of mercury dry deposition, litterfall, and throughfall studies, Atmos. Chem. Phys., 16, 13399–13416, https://doi.org/10.5194/acp-16-13399-2016, 2016.
Zhang, L., Wright, L. P., and Blanchard, P.: A review of current knowledge
concerning dry deposition of atmospheric mercury, Atmos. Environ.,
43, 5853–5864, 2009.
Zhang, J., Moran, M. D., Zheng, Q., Makar, P. A., Baratzadeh, P., Marson, G., Liu, P., and Li, S.-M.: Emissions preparation and analysis for multiscale air quality modeling over the Athabasca Oil Sands Region of Alberta, Canada, Atmos. Chem. Phys., 18, 10459–10481, https://doi.org/10.5194/acp-18-10459-2018, 2018.
Zhang, L., Wu, Z., Cheng, I., Wright, L. P., Olson, M. L., Gay, D. A.,
Risch, M. R., Brooks, S., Castro, M. S., Conley, G. D., Edgerton, E. S.,
Holsen, T. M., Luke, W., Tordon, R., and Weiss-Penzias, P.: The estimated
six-year mercury dry deposition across North America, Environ. Sci.
Technol., 50, 12864–12873, https://doi.org/10.1021/acs.est.6b04276, 2016.
Zhou, J., Obrist, D., Dastoor, A., Jiskra, M., and Ryjkov, A.: Vegetation
uptake of mercury and impacts on global cycling, Nat. Rev. Earth
Environ., 2, 269–284, https://doi.org/10.1038/s43017-021-00146-y, 2021.
Short summary
An assessment of mercury levels in air and deposition in the Athabasca oil sands region (AOSR) in Northern Alberta, Canada, was conducted to investigate the contribution of Hg emitted from oil sands activities to the surrounding landscape using a 3D process-based Hg model in 2012–2015. Oil sands Hg emissions are found to be important sources of Hg contamination to the local landscape in proximity to the processing activities, particularly in wintertime.
An assessment of mercury levels in air and deposition in the Athabasca oil sands region (AOSR)...
Altmetrics
Final-revised paper
Preprint