Widespread biomass burning smoke throughout the remote troposphere

Abstract

Biomass burning emits ~34–41 Tg yr−1 of smoke aerosol to the atmosphere. Biomass burning aerosol directly influences the Earth’s climate by attenuation of solar and terrestrial radiation; however, its abundance and distribution on a global scale are poorly constrained, particularly after plumes dilute into the background remote troposphere and are subject to removal by clouds and precipitation. Here we report global-scale, airborne measurements of biomass burning aerosol in the remote troposphere. Measurements were taken during four series of seasonal flights over the Pacific and Atlantic Ocean basins, each with near pole-to-pole latitude coverage. We find that biomass burning particles in the remote troposphere are dilute but ubiquitous, accounting for one-quarter of the accumulation-mode aerosol number and one-fifth of the aerosol mass. Comparing our observations with a high-resolution global aerosol model, we find that the model overestimates biomass burning aerosol mass in the remote troposphere with a mean bias of >400%, largely due to insufficient wet removal by in-cloud precipitation. After updating the model’s aerosol removal scheme we find that, on a global scale, dilute smoke contributes as much as denser plumes to biomass burning’s scattering and absorption effects on the Earth’s radiation field.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: The influence of biomass burning on aerosol in the remote troposphere.
Fig. 2: Sulfate mass fraction of biomass burning particles versus smoke markers.
Fig. 3: Global-scale model–measurement comparisons of biomass burning aerosol for all ATom campaigns.
Fig. 4: GEOS/GOCART r23 biomass burning-only, clear-sky AOD for primary ATom campaign months.

Data availability

Data are publically available at https://daac.ornl.gov/ATOM/guides/ATom_merge.html and https://esrl.noaa.gov/csd/projects/atom/data.php.

Code availability

GEOS is an open-source model, and the code is available at https://gmao.gsfc.nasa.gov/GEOS_systems/.

Change history

  • 25 June 2020

    The ‘Editor recognition’ statement has been amended to additionally include the contribution of Xujia Jiang; the sentence now reads ‘Primary Handling Editors: Clare Davis; Xujia Jiang.’

References

  1. 1.

    Bond, T. C. et al. Bounding the role of black carbon in the climate system: a scientific assessment. J. Geophys. Res. Atmos. 118, 5380–5552 (2013).

    Article  Google Scholar 

  2. 2.

    Andreae, M. O. Emission of trace gases and aerosols from biomass burning—an updated assessment. Atmos. Chem. Phys. 19, 8523–8546 (2019).

    Article  Google Scholar 

  3. 3.

    Bowman, D. M. J. S. et al. Fire in the Earth System. Science 324, 481–484 (2009).

    Article  Google Scholar 

  4. 4.

    Abatzoglou, J. T. & Williams, A. P. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl Acad. Sci. USA 113, 11770–11775 (2016).

    Article  Google Scholar 

  5. 5.

    Westerling, A. L., Hidalgo, H. G., Cayan, D. R. & Swetnam, T. W. Warming and earlier spring increase Western U.S. forest wildfire activity. Science 313, 940–943 (2006).

    Article  Google Scholar 

  6. 6.

    Hudson, P. K. et al. Biomass-burning particle measurements: characteristic composition and chemical processing. J. Geophys. Res. Atmos. 109, D23S27 (2004).

    Article  Google Scholar 

  7. 7.

    Park, R. J., Jacob, D. J. & Logan, J. A. Fire and biofuel contributions to annual mean aerosol mass concentrations in the United States. Atmos. Environ. 41, 7389–7400 (2007).

    Article  Google Scholar 

  8. 8.

    Edwards, D. P. et al. Satellite-observed pollution from Southern Hemisphere biomass burning. J. Geophys. Res. 111, D14312 (2006).

    Article  Google Scholar 

  9. 9.

    Wotawa, G. & Trainer, M. The influence of Canadian forest fires on pollutant concentrations in the United States. Science 288, 324–328 (2000).

    Article  Google Scholar 

  10. 10.

    Andreae, M. O., Andreae, T. W., Ferek, R. J. & Raemdonck, H. Long-range transport of soot carbon in the marine atmosphere. Sci. Total Environ. 36, 73–80 (1984).

    Article  Google Scholar 

  11. 11.

    Zuidema, P. et al. The Ascension Island boundary layer in the remote Southeast Atlantic is often smoky. Geophys. Res. Lett. 45, 4456–4465 (2018).

    Article  Google Scholar 

  12. 12.

    Dahlkötter, F. et al. The Pagami Creek smoke plume after long-range transport to the upper troposphere over Europe—aerosol properties and black carbon mixing state. Atmos. Chem. Phys. 14, 6111–6137 (2014).

    Article  Google Scholar 

  13. 13.

    Ditas, J. et al. Strong impact of wildfires on the abundance and aging of black carbon in the lowermost stratosphere. Proc. Natl Acad. Sci. USA 115, e11595–e11603 (2018).

    Article  Google Scholar 

  14. 14.

    Reddington, C. L. et al. The Global Aerosol Synthesis and Science Project (GASSP): measurements and modeling to reduce uncertainty. Bull. Am. Meteorol. Soc. 98, 1857–1877 (2017).

    Article  Google Scholar 

  15. 15.

    Myhre, G. et al. Radiative forcing of the direct aerosol effect from AeroCom Phase II simulations. Atmos. Chem. Phys. 13, 1853–1877 (2013).

    Article  Google Scholar 

  16. 16.

    Shi, Y. et al. A critical examination of spatial biases between MODIS and MISR aerosol products—application for potential AERONET deployment. Atmos. Meas. Techn. 4, 2823–2836 (2011).

    Article  Google Scholar 

  17. 17.

    Watson-Parris, D. et al. On the Limits of CALIOP for constraining modeled free tropospheric aerosol. Geophys. Res. Lett. 45, 9260–9266 (2018).

    Article  Google Scholar 

  18. 18.

    Thomson, D. S., Schein, M. E. & Murphy, D. M. Particle analysis by laser mass spectrometry WB-57F instrument overview. Aerosol Sci. Technol. 33, 153–169 (2000).

    Article  Google Scholar 

  19. 19.

    Cziczo, D. J., Thomson, D. S., Thompson, T. L., DeMott, P. J. & Murphy, D. M. Particle analysis by laser mass spectrometry (PALMS) studies of ice nuclei and other low number density particles. Int. J. Mass Spectrom. 258, 21–29 (2006).

    Article  Google Scholar 

  20. 20.

    Murphy, D. M. The design of single particle laser mass spectrometers. Mass Spectrom. Rev. 26, 150–165 (2007).

    Article  Google Scholar 

  21. 21.

    Froyd, K. D. et al. A new method to quantify mineral dust and other aerosol species from aircraft platforms using single-particle mass spectrometry. Atmos. Meas. Techn. 12, 6209–6239 (2019).

    Article  Google Scholar 

  22. 22.

    Brock, C. A. et al. Particle characteristics following cloud-modified transport from Asia to North America. J. Geophys. Res. 109, D23S26 (2004).

    Google Scholar 

  23. 23.

    Sofiev, M., Ermakova, T. & Vankevich, R. Evaluation of the smoke-injection height from wild-land fires using remote-sensing data. Atmos. Chem. Phys. 12, 1995–2006 (2012).

    Article  Google Scholar 

  24. 24.

    Val Martin, M., Kahn, R. & Tosca, M. A global analysis of wildfire smoke injection heights derived from space-based multi-angle imaging. Remote Sens. 10, 1609 (2018).

    Article  Google Scholar 

  25. 25.

    Reid, J. S. et al. A review of biomass burning emissions part II: intensive physical properties of biomass burning particles. Atmos. Chem. Phys. 5, 799–825 (2005).

    Article  Google Scholar 

  26. 26.

    Li, J., Pósfai, M., Hobbs, P. V. & Buseck, P. R. Individual aerosol particles from biomass burning in southern Africa: 2, compositions and aging of inorganic particles. J. Geophys. Res. Atmos. 108, 8484 (2003).

    Google Scholar 

  27. 27.

    Chin, M. et al. Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements. J. Atmos. Sci. 59, 461–483 (2002).

    Article  Google Scholar 

  28. 28.

    Colarco, P., da Silva, A., Chin, M. & Diehl, T. Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth. J. Geophys. Res. 115, D14207 (2010).

    Article  Google Scholar 

  29. 29.

    Bian, H. et al. Source attributions of pollution to the Western Arctic during the NASA ARCTAS field campaign. Atmos. Chem. Phys. 13, 4707–4721 (2013).

    Article  Google Scholar 

  30. 30.

    Darmenov, A. & da Silva, A. M. The Quick Fire Emissions Dataset (QFED) – Documentation of Versions 2.1, 2.2 and 2.4 Technical Report Series on Global Modeling and Data Assimilation No. 32 (NASA, 2015).

  31. 31.

    Bian, Q. et al. Secondary organic aerosol formation in biomass-burning plumes: theoretical analysis of lab studies and ambient plumes. Atmos. Chem. Phys. 17, 5459–5475 (2017).

    Article  Google Scholar 

  32. 32.

    Petrenko, M. et al. The use of satellite-measured aerosol optical depth to constrain biomass burning emissions source strength in the global model GOCART. J. Geophys. Res. Atmos. 117, D18212 (2012).

    Article  Google Scholar 

  33. 33.

    Pan, X. et al. Six global biomass burning emission datasets: intercomparison and application in one global aerosol model. Atmos. Chem. Phys. 20, 969–994 (2020).

    Article  Google Scholar 

  34. 34.

    Schwarz, J. P. et al. Global‐scale seasonally resolved black carbon vertical profiles over the Pacific. Geophys. Res. Lett. 40, 5542–5547 (2013).

    Article  Google Scholar 

  35. 35.

    Yu, P. et al. Efficient in-cloud removal of aerosols by deep convection. Geophys. Res. Lett. 46, 1061–1069 (2019).

    Article  Google Scholar 

  36. 36.

    Lund, M. T. et al. Short black carbon lifetime inferred from a global set of aircraft observations. npj Clim. Atmos. Sci. 1, 31 (2018).

    Article  Google Scholar 

  37. 37.

    Toth, T. D. et al. Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products. Atmos. Meas. Tech. 11, 499–514 (2018).

    Article  Google Scholar 

  38. 38.

    Samset, B. H. & Myhre, G. Climate response to externally mixed black carbon as a function of altitude. J. Geophys. Res. Atmos. 120, 2913–2927 (2015).

    Article  Google Scholar 

  39. 39.

    Tegen, I. & Heinold, B. Large-scale modeling of absorbing aerosols and their semi-direct effects. Atmosphere 9, 380 (2018).

    Article  Google Scholar 

  40. 40.

    Mallet, M. et al. Simulation of the transport, vertical distribution, optical properties and radiative impact of smoke aerosols with the ALADIN regional climate model during the ORACLES-2016 and LASIC experiments. Atmos. Chem. Phys. 19, 4963–4990 (2019).

    Article  Google Scholar 

  41. 41.

    Toon, O. B. et al. Planning, implementation, and scientific goals of the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC 4 RS) field mission. J. Geophys. Res. Atmos. 121, 4967–5009 (2016).

    Article  Google Scholar 

  42. 42.

    Brock, C. A. et al. Aerosol size distributions during the Atmospheric Tomography Mission (ATom): methods, uncertainties, and data products. Atmos. Meas. Tech. 12, 3081–3099 (2019).

    Article  Google Scholar 

  43. 43.

    Murphy, D. M. et al. The distribution of sea-salt aerosol in the global troposphere. Atmos. Chem. Phys. 19, 4093–4104 (2019).

    Article  Google Scholar 

  44. 44.

    Williamson, C. et al. Fast time response measurements of particle size distributions in the 3–60 nm size range with the nucleation mode aerosol size spectrometer. Atmos. Meas. Tech. 11, 3491–3509 (2018).

    Article  Google Scholar 

  45. 45.

    Kupc, A., Williamson, C., Wagner, N. L., Richardson, M. & Brock, C. A. Modification, calibration, and performance of the Ultra-High Sensitivity Aerosol Spectrometer for particle size distribution and volatility measurements during the Atmospheric Tomography Mission (ATom) airborne campaign. Atmos. Meas. Tech. 11, 369–383 (2018).

    Article  Google Scholar 

  46. 46.

    McNaughton, C. S. et al. Results from the DC-8 Inlet Characterization Experiment (DICE): airborne versus surface sampling of mineral dust and sea salt aerosols. Aerosol Sci. Technol. 41, 136–159 (2007).

    Article  Google Scholar 

  47. 47.

    Brockmann, J. E. in Aerosol Measurement (eds Kulkarni, P. et al.) Ch. 6 (John Wiley & Sons, 2011).

  48. 48.

    Loo, B. W. & Cork, C. P. Development of high efficiency virtual impactors. Aerosol Sci. Technol. 9, 167–176 (1988).

    Article  Google Scholar 

  49. 49.

    Huebert, B. J., Lee, G. & Warren, W. L. Airborne aerosol inlet passing efficiency measurement. J. Geophys. Res. 95, 16369–16381 (1990).

    Article  Google Scholar 

  50. 50.

    Weber, R. J. et al. Spurious aerosol measurements when sampling from aircraft in the vicinity of clouds. J. Geophys. Res. Atmos. 103, 28337–28346 (1998).

    Article  Google Scholar 

  51. 51.

    Murphy, D. M. et al. Particle generation and resuspension in aircraft inlets when flying in clouds. Aerosol Sci. Technol. 38, 401–409 (2004).

    Article  Google Scholar 

  52. 52.

    Murphy, D. M., Middlebrook, A. M. & Warshawsky, M. Cluster analysis of data from the Particle Analysis by Laser Mass Spectrometry (PALMS) instrument. Aerosol Sci. Technol. 37, 382–391 (2003).

    Article  Google Scholar 

  53. 53.

    Cziczo, D. J., Thomson, D. S. & Murphy, D. M. Ablation, flux, and atmospheric implications of meteors inferred from stratospheric aerosol. Science 291, 1772–1775 (2001).

    Article  Google Scholar 

  54. 54.

    Sullivan, A. P. et al. Biomass burning markers and residential burning in the WINTER aircraft campaign. J. Geophys. Res. Atmos. 124, 1846–1861 (2019).

    Article  Google Scholar 

  55. 55.

    Cziczo, D. J. et al. Observations of organic species and atmospheric ice formation. Geophys. Res. Lett. 31, L12116 (2004).

    Article  Google Scholar 

  56. 56.

    Rienecker, M. M. et al. The GEOS-5 Data Assimilation System: Documentation of Versions 5.0. 1, 5.1. 0, and 5.2. 0 Technical Report Series on Global Modeling and Data Assimilation No. 27 (NASA, 2008).

  57. 57.

    Liu, H., Jacob, D. J., Bey, I. & Yantosca, R. M. Constraints from 210Pb and 7Be on wet deposition and transport in a global three-dimensional chemical tracer model driven by assimilated meteorological fields. J. Geophys. Res. Atmos. 106, 12109–12128 (2001).

    Article  Google Scholar 

  58. 58.

    Randles, C. A. et al. The MERRA-2 aerosol reanalysis, 1980 Onward. Part I: system description and data assimilation evaluation. J. Clim. 30, 6823–6850 (2017).

    Article  Google Scholar 

  59. 59.

    Chou, M. & Suarez, M. J. A Solar Radiation Parameterization for Atmospheric Studies Technical Report Series on Global Modeling and Data Assimilation No. 15 (NASA, 1999).

  60. 60.

    Apel, E. C. et al. Upper tropospheric ozone production from lightning NOx-impacted convection: smoke ingestion case study from the DC3 campaign. J. Geophys. Res. Atmos. 120, 2505–2523 (2015).

    Article  Google Scholar 

  61. 61.

    Wang, S. et al. Atmospheric acetaldehyde: importance of air–sea exchange and a missing source in the remote troposphere. Geophys. Res. Lett. 46, 5601–5613 (2019).

    Article  Google Scholar 

  62. 62.

    Bowman, K. P. Large-scale isentropic mixing properties of the Antarctic polar vortex from analyzed winds. J. Geophys. Res. 98, 23013 (1993).

    Article  Google Scholar 

  63. 63.

    Bowman, K. P. & Carrie, G. D. The mean-meridional transport circulation of the troposphere in an idealized GCM. J. Atmos. Sci. 59, 1502–1514 (2002).

    Article  Google Scholar 

  64. 64.

    Schroeder, W., Oliva, P., Giglio, L. & Csiszar, I. A. The new VIIRS 375 m active fire detection data product: algorithm description and initial assessment. Remote Sens. Environ. 143, 85–96 (2014).

    Article  Google Scholar 

Download references

Acknowledgements

The mission as a whole was supported by NASA’s Earth System Science Pathfinder Program EVS-2 funding. Participation in ATom Mission flights by G.P.S., K.D.F., C.W., C.A.B. and D.M.M. was supported by NOAA climate funding (no. NNH15AB12I). A.K. was supported by the Austrian Science Fund’s Erwin Schrodinger Fellowship (no. J-3613). R.S.H., A.J.H. and E.C.A. received support from the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement no. 1852977.

Author information

Affiliations

Authors

Contributions

G.P.S., K.D.F. and D.M.M. provided PALMS data. H.B., M.C. and P.R.C. provided GEOS/GOCART results. A.K., C.W. and C.A.B. provided size distribution data. E.R. provided back-trajectory results. R.S.H., A.J.H. and E.C.A. provided TOGA data. G.P.S. wrote the paper with assistance from all authors.

Corresponding author

Correspondence to G. P. Schill.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Primary Handling Editors: Clare Davis; Xujia Jiang.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–5 and Tables 1 and 2.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Schill, G.P., Froyd, K.D., Bian, H. et al. Widespread biomass burning smoke throughout the remote troposphere. Nat. Geosci. 13, 422–427 (2020). https://doi.org/10.1038/s41561-020-0586-1

Download citation

Further reading