Oil sands operations as a large source of secondary organic aerosols

Abstract

Worldwide heavy oil and bitumen deposits amount to 9 trillion barrels of oil distributed in over 280 basins around the world1, with Canada home to oil sands deposits of 1.7 trillion barrels2. The global development of this resource and the increase in oil production from oil sands has caused environmental concerns over the presence of toxic compounds in nearby ecosystems3,4 and acid deposition5,6. The contribution of oil sands exploration to secondary organic aerosol formation, an important component of atmospheric particulate matter that affects air quality and climate7, remains poorly understood. Here we use data from airborne measurements over the Canadian oil sands, laboratory experiments and a box-model study to provide a quantitative assessment of the magnitude of secondary organic aerosol production from oil sands emissions. We find that the evaporation and atmospheric oxidation of low-volatility organic vapours from the mined oil sands material is directly responsible for the majority of the observed secondary organic aerosol mass. The resultant production rates of 45–84 tonnes per day make the oil sands one of the largest sources of anthropogenic secondary organic aerosols in North America. Heavy oil and bitumen account for over ten per cent of global oil production today8, and this figure continues to grow9. Our findings suggest that the production of the more viscous crude oils could be a large source of secondary organic aerosols in many production and refining regions worldwide, and that such production should be considered when assessing the environmental impacts of current and planned bitumen and heavy oil extraction projects globally.

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Figure 1: Relative increase in OA downwind of the OS.
Figure 2: OA mass screens during F1.
Figure 3: PMF analysis for F1.
Figure 4: Modelling SOA formation during F1.

References

  1. 1

    Richard, F., Meyer, E. D. A. & Freeman, P. A. Heavy Oil and Natural Bitumen Resources in Geological Basins of the World (US Geological Survey, 2007)

  2. 2

    Government of Alberta. Environmental Management of Alberta’s Oil Sands (Government of Alberta, 2009)

  3. 3

    Kelly, E. N. et al. Oil sands development contributes polycyclic aromatic compounds to the Athabasca River and its tributaries. Proc. Natl Acad. Sci. USA 106, 22346–22351 (2009)

    CAS  ADS  Article  Google Scholar 

  4. 4

    Kirk, J. L. et al. Atmospheric deposition of mercury and methylmercury to landscapes and waterbodies of the Athabasca oil sands region. Environ. Sci. Technol. 48, 7374–7383 (2014)

    CAS  ADS  Article  Google Scholar 

  5. 5

    Jung, K., Chang, S. X., Ok, Y. S. & Arshad, M. A. Critical loads and H+ budgets of forest soils affected by air pollution from oil sands mining in Alberta, Canada. Atmos. Environ. 69, 56–64 (2013)

    CAS  ADS  Article  Google Scholar 

  6. 6

    Watmough, S. A., Whitfield, C. J. & Fenn, M. E. The importance of atmospheric base cation deposition for preventing soil acidification in the Athabasca Oil Sands Region of Canada. Sci. Total Environ. 493, 1–11 (2014)

    CAS  ADS  Article  Google Scholar 

  7. 7

    Fuzzi, S. et al. Particulate matter, air quality and climate: lessons learned and future needs. Atmos. Chem. Phys. 15, 8217–8299 (2015)

    CAS  ADS  Article  Google Scholar 

  8. 8

    BP. Heavy Oil vs. Light Oil: Legislative Brown Bag (BP, 2011)

  9. 9

    Dusseault, M. Cold Heavy Oil Production with Sand in the Canadian Heavy Oil Industry Ch. 2 (Alberta Energy, 2002)

  10. 10

    Zhang, Q. et al. Ubiquity and dominance of oxygenated species in organic aerosols in anthropogenically-influenced Northern Hemisphere midlatitudes. Geophys. Res. Lett. 34, L13801 (2007)

    ADS  Google Scholar 

  11. 11

    Gentner, D. R. et al. Elucidating secondary organic aerosol from diesel and gasoline vehicles through detailed characterization of organic carbon emissions. Proc. Natl Acad. Sci. USA 109, 18318–18323 (2012)

    CAS  ADS  Article  Google Scholar 

  12. 12

    Zhao, Y. et al. Intermediate-volatility organic compounds: a large source of secondary organic aerosol. Environ. Sci. Technol. 48, 13743–13750 (2014)

    CAS  ADS  Article  Google Scholar 

  13. 13

    Donahue, N. M., Robinson, A. L. & Pandis, S. N. Atmospheric organic particulate matter: from smoke to secondary organic aerosol. Atmos. Environ. 43, 94–106 (2009)

    CAS  ADS  Article  Google Scholar 

  14. 14

    Simpson, I. J. et al. Characterization of trace gases measured over Alberta oil sands mining operations: 76 speciated C2–C10 volatile organic compounds (VOCs), CO2, CH4, CO, NO, NO2, NOy, O3 and SO2 . Atmos. Chem. Phys. 10, 11931–11954 (2010)

    CAS  ADS  Article  Google Scholar 

  15. 15

    de Gouw, J. A. et al. Organic aerosol formation downwind from the Deepwater Horizon oil spill. Science 331, 1295–1299 (2011)

    CAS  ADS  Article  Google Scholar 

  16. 16

    Li, R. et al. Laboratory studies on secondary organic aerosol formation from crude oil vapors. Environ. Sci. Technol. 47, 12566–12574 (2013)

    CAS  ADS  Article  Google Scholar 

  17. 17

    Alberta Energy Regulator. Alberta Mineable Oil Sands Plant Statistics (Alberta Energy Regulator, 2013)

  18. 18

    Gordon, M. et al. Determining air pollutant emission rates based on mass balance using airborne measurement data over the Alberta oil sands operations. Atmos. Meas. Tech. 8, 3745–3765 (2015)

    CAS  Article  Google Scholar 

  19. 19

    Kleinman, L. I. et al. The time evolution of aerosol composition over the Mexico City plateau. Atmos. Chem. Phys. 8, 1559–1575 (2008)

    CAS  ADS  Article  Google Scholar 

  20. 20

    Freney, E. J. et al. Characterizing the impact of urban emissions on regional aerosol particles: Airborne measurements during the MEGAPOLI experiment. Atmos. Chem. Phys. 14, 1397–1412 (2014)

    ADS  Article  Google Scholar 

  21. 21

    Miyakawa, T., Takegawa, N. & Kondo, Y. Photochemical evolution of submicron aerosol chemical composition in the Tokyo megacity region in summer. J. Geophys. Res. 113, D14304 (2008)

    ADS  Article  Google Scholar 

  22. 22

    Kleinman, L. I. et al. Aircraft observations of aerosol composition and ageing in New England and Mid-Atlantic States during the summer 2002 New England Air Quality Study field campaign. J. Geophys. Res. 112, D09310 (2007)

    ADS  Article  Google Scholar 

  23. 23

    de Gouw, J. & Jimenez, J. L. Organic aerosols in the Earth’s atmosphere. Environ. Sci. Technol. 43, 7614–7618 (2009)

    CAS  ADS  Article  Google Scholar 

  24. 24

    Hayes, P. L. et al. Modeling the formation and aging of secondary organic aerosols in Los Angeles during CalNex 2010. Atmos. Chem. Phys. 15, 5773–5801 (2015)

    CAS  ADS  Article  Google Scholar 

  25. 25

    Ng, N. L. et al. Real-time methods for estimating organic component mass concentrations from aerosol mass spectrometer data. Environ. Sci. Technol. 45, 910–916 (2011)

    CAS  ADS  Article  Google Scholar 

  26. 26

    Robinson, N. H. et al. Evidence for a significant proportion of secondary organic aerosol from isoprene above a maritime tropical forest. Atmos. Chem. Phys. 11, 1039–1050 (2011)

    CAS  ADS  Article  Google Scholar 

  27. 27

    Liu, Y., Liggio, J., Staebler, R. & Li, S. M. Reactive uptake of ammonia to secondary organic aerosols: kinetics of organonitrogen formation. Atmos. Chem. Phys. 15, 13569–13584 (2015)

    CAS  ADS  Article  Google Scholar 

  28. 28

    Gentner, D. R. et al. Emissions of organic carbon and methane from petroleum and dairy operations in California’s San Joaquin Valley. Atmos. Chem. Phys. 14, 4955–4978 (2014)

    ADS  Article  Google Scholar 

  29. 29

    Gilman, J. B., Lerner, B. M., Kuster, W. C. & de Gouw, J. A. Source signature of volatile organic compounds from oil and natural gas operations in northeastern Colorado. Environ. Sci. Technol. 47, 1297–1305 (2013)

    CAS  ADS  Article  Google Scholar 

  30. 30

    DeCarlo, P. F. et al. Field-deployable, high-resolution, time-of-flight aerosol mass spectrometer. Anal. Chem. 78, 8281–8289 (2006)

    CAS  Article  Google Scholar 

  31. 31

    Moteki, N. & Kondo, Y. Dependence of laser-induced incandescence on physical properties of black carbon aerosols: measurements and theoretical interpretation. Aerosol Sci. Technol. 44, 663–675 (2010)

    CAS  ADS  Article  Google Scholar 

  32. 32

    Schwarz, J. P. et al. Single-particle measurements of midlatitude black carbon and light-scattering aerosols from the boundary layer to the lower stratosphere. J. Geophys. Res. 111, D16207 (2006)

    ADS  Article  Google Scholar 

  33. 33

    de Gouw, J. & Warneke, C. Measurements of volatile organic compounds in the earth’s atmosphere using proton-transfer-reaction mass spectrometry. Mass Spectrom. Rev. 26, 223–257 (2007)

    CAS  ADS  Article  Google Scholar 

  34. 34

    Garratt, J. R. The Atmospheric Boundary Layer (Cambridge Univ. Press, 1994)

  35. 35

    Vinuesa, J. F. & Galmarini, S. Turbulent dispersion of non-uniformly emitted passive tracers in the convective boundary layer. Boundary-Layer Meteorol. 133, 1–16 (2009)

    ADS  Article  Google Scholar 

  36. 36

    Carter, W. P. L. Development of a condensed SAPRC-07 chemical mechanism. Atmos. Environ. 44, 5336–5345 (2010)

    CAS  ADS  Article  Google Scholar 

  37. 37

    Chen, Y., Sexton, K. G., Jerry, R. E., Surratt, J. D. & Vizuete, W. Assessment of SAPRC07 with updated isoprene chemistry against outdoor chamber experiments. Atmos. Environ. 105, 109–120 (2015)

    CAS  ADS  Article  Google Scholar 

  38. 38

    Xie, Y. et al. Understanding the impact of recent advances in isoprene photooxidation on simulations of regional air quality. Atmos. Chem. Phys. 13, 8439–8455 (2013)

    ADS  Article  Google Scholar 

  39. 39

    de Gouw, J. et al. Sensitivity and specificity of atmospheric trace gas detection by proton-transfer-reaction mass spectrometry. Int. J. Mass Spectrom. 223–224, 365–382 (2003)

    Article  Google Scholar 

  40. 40

    Zhao, J. & Zhang, R. Proton transfer reaction rate constants between hydronium ion (H3O+) and volatile organic compounds. Atmos. Environ. 38, 2177–2185 (2004)

    CAS  ADS  Article  Google Scholar 

  41. 41

    Hakola, H. et al. Seasonal variation of mono- and sesquiterpene emission rates of Scots pine. Biogeosciences 3, 93–101 (2006)

    CAS  ADS  Article  Google Scholar 

  42. 42

    Helmig, D. et al. Sesquiterpene emissions from pine trees—identifications, emission rates and flux estimates for the contiguous United States. Environ. Sci. Technol. 41, 1545–1553 (2007)

    CAS  ADS  Article  Google Scholar 

  43. 43

    Ehn, M. et al. A large source of low-volatility secondary organic aerosol. Nature 506, 476–479 (2014)

    CAS  ADS  Article  Google Scholar 

  44. 44

    Jathar, S. H. et al. Unspeciated organic emissions from combustion sources and their influence on the secondary organic aerosol budget in the United States. Proc. Natl Acad. Sci. USA 111, 10473–10478 (2014)

    CAS  ADS  Article  Google Scholar 

  45. 45

    Tsimpidi, A. P. et al. Evaluation of the volatility basis-set approach for the simulation of organic aerosol formation in the Mexico City metropolitan area. Atmos. Chem. Phys. 10, 525–546 (2010)

    CAS  ADS  Article  Google Scholar 

  46. 46

    Robinson, A. L. et al. Rethinking organic aerosols: semivolatile emissions and photochemical aging. Science 315, 1259–1262 (2007)

    CAS  ADS  Article  Google Scholar 

  47. 47

    Grieshop, A. P., Logue, J. M., Donahue, N. M. & Robinson, A. L. Laboratory investigation of photochemical oxidation of organic aerosol from wood fires 1: measurement and simulation of organic aerosol evolution. Atmos. Chem. Phys. 9, 1263–1277 (2009)

    CAS  ADS  Article  Google Scholar 

  48. 48

    Murphy, B. N., Donahue, N. M., Fountoukis, C. & Pandis, S. N. Simulating the oxygen content of ambient organic aerosol with the 2D volatility basis set. Atmos. Chem. Phys. 11, 7859–7873 (2011)

    CAS  ADS  Article  Google Scholar 

  49. 49

    Shrivastava, M. K., Lane, T. E., Donahue, N. M., Pandis, S. N. & Robinson, A. L. Effects of gas particle partitioning and aging of primary emissions on urban and regional organic aerosol concentrations. J. Geophys. Res. 113, (2008)

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Acknowledgements

We thank the National Research Council of Canada flight crew of the Convair-580, the technical support staff of the Air Quality Research Division, S. Cober for the management of the study, and the community of Fort McKay for the support of the Oski ôtin ground site at Fort McKay. The project was supported by the Clean Air Regulatory Agenda and the Joint Oil Sands Monitoring program.

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Authors

Contributions

All authors contributed to the collection of observations in the field, in the laboratory or the development of the box model. J.L. and S.-M.L. wrote the paper with input from all co-authors. S.-M.L. designed and directed the flights. Y.M.T. and C.S. conducted the box modelling work with input from J.L. D.R.G., D.P., B.D.D. and P.L. provided bitumen volatility distributions.

Corresponding authors

Correspondence to John Liggio or Shao-Meng Li.

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Competing interests

The authors declare no competing financial interests.

Additional information

The data used are available on the Canada-Alberta Oil Sands Environmental Monitoring Information Portal (http://jointoilsandsmonitoring.ca/default.asp?n=5F73C7C9-1&lang=en).

Extended data figures and tables

Extended Data Figure 1 Flight tracks for the three transformation flights, F1, F2 and F3.

The approximate locations of the major OS plumes studied in this work are shown as the white shaded boxes. Map data: Google, image Landsat, 2015. Source data

Extended Data Figure 2 Measured organic and sulfate aerosol concentration during F1.

Successive transects (labelled A, B, C and D) through the same major OS plumes at approximately 600 m altitude and 1 h apart in transit time. Inset pie plots show the mean relative mass fraction for organics (green), sulfate (red), nitrate (blue) and ammonium (orange) during the yellow highlighted section. Organics dominate the aerosol mass throughout the flight; note the change in magnitude between the OA scale on the left and SO4 scale on the right. Map data: Google, image Landsat, 2015. Source data

Extended Data Figure 3 OA mass screens used to estimate SOA production.

a, b, OA mass screens for F2 (a) and F3 (b). The SOA production rate during these flights (~77 km and ~50 km between screens) is the sum of the differences in OA transfer rates between screens (that is,: 2.7 ± 1.0 t h−1 and 2.1 ± 0.9 t h−1). The overall formation rate from the OS source region (S) is the integrated OA transfer rate through screen B (5.3 ± 1.0 t h−1 and 4.3 ± 0.9 t h−1). Map data: Google, image Landsat, 2015. Source data

Extended Data Figure 4 PMF analysis results and comparisons.

a, The OA AMS spectra from an α-pinene + OH radical smog chamber experiment as a function of photochemical ageing time in the chamber. b, PMF factor 1 from F1. A high degree of similarity is observed between these spectra after approximately 6 h of ageing in the chamber. c, Correlations between PMF factors 1 and 2 and the corresponding smog chamber data (terpene oxidation and bitumen vapour oxidation SOA). Source data

Extended Data Figure 5 Bitumen volatility distributions.

The volatility distribution (mass fraction) based on carbon number are for OS that was thermally treated. Volatile hydrocarbons are trapped on polyurethane foam (PUF) tubes at 50–80 °C (red). The volatility of the remaining bitumen material is shown in green (50–80 °C) and that of bitumen which was solvent extracted from the sand without heating is shown in grey. Note the complete loss of hydrocarbons in the C12–C15 range upon heating (denoted in yellow). Data are stacked upon each other for clarity. Error bars represent the s.d. of n = 3 experiments. Source data

Extended Data Figure 6 Bitumen-related IVOCs in ambient ground-based data.

a, Total ion chromatogram from ambient sampling in the OS when impacted by forest-influenced air (blue) and OS-operations air (red). The bitumen vapour headspace chromatogram is also shown (black), demonstrating that a large fraction of the gaseous mass in OS-impacted air has volatilities (C13–C16 range) critical for SOA formation. b, Associated volatility distribution for OS-impacted air scaled by SOA yield11. c, One-hour back trajectory for OS-impacted sample using the hybrid single particle Lagrangian integrated trajectory model (HYSPLIT). d, One-hour HYSPLIT back trajectory for forest-influenced sample. Source data

Extended Data Figure 7 Background concentration time series.

a, b, The BC (a) and OA (b) time series for F1 with associated interpolated backgrounds. The background variability contributed little uncertainty to the overall analysis of ΔOA/ΔBC in Fig. 1. Source data

Extended Data Figure 8 SOA production rate extrapolation.

a, Measured SOA for F1 extrapolated to one photochemical day. Total SOA production is the sum of scaled hourly SOA production rates (orange; see Supplementary Methods). The blue region represents the same scaling performed where only photolysis rate constants are varied in the model. Error bars represent a range of SOA estimates assuming ±20% on the initial OA estimates via the TERRA algorithm. b, Modelled dependence of OH radical concentration on the ozone photolysis frequency (JO1D). Further varying initial conditions for NOx, water vapour and isoprene in the model has a small effect on this relationship. Source data

Extended Data Figure 9 Box-model performance evaluation.

a, b, Measured and modelled gas-phase species during plume intercepts of F1, where only the initial conditions (t = 0) of the species are constrained by measurements. Good agreement between model and observation is achieved. c, Sensitivity of predicted SOA for F1 to changes in the oxidation rate constant and yield (all other variables remain constant). Yield refers to the SOA mass yield during the oxidative ageing. Simulations using a single oxidative rate constant and yield represent upper and lower limits to SOA formation, while the base case simulation most closely resembles measurements. Error bars represent s.d. of the measured OA (n = 7). Source data

Extended Data Figure 10 PMF factors from ground-based data in the OS.

PMF factors 1 (biogenic SOA (B-SOA)) and 2 (OS-SOA) from 1 year of ground-based data in the OS production region (monthly 25th to 90th percentiles shown, n = 22,280), indicating that factor 2 (using a collection efficiency of 1) is derived from the oxidation of OS emissions all year long, while factor 1 is from oxidation of biogenic emissions (that is, summer peak only). Source data

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Liggio, J., Li, S., Hayden, K. et al. Oil sands operations as a large source of secondary organic aerosols. Nature 534, 91–94 (2016). https://doi.org/10.1038/nature17646

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