Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Vast CO2 release from Australian fires in 2019–2020 constrained by satellite


Southeast Australia experienced intensive and geographically extensive wildfires during the 2019–2020 summer season1,2. The fires released substantial amounts of carbon dioxide into the atmosphere3. However, existing emission estimates based on fire inventories are uncertain4, and vary by up to a factor of four for this event. Here we constrain emission estimates with the help of satellite observations of carbon monoxide5, an analytical Bayesian inversion6 and observed ratios between emitted carbon dioxide and carbon monoxide7. We estimate emissions of carbon dioxide to be 715 teragrams (range 517–867) from November 2019 to January 2020. This is more than twice the estimate derived by five different fire inventories8,9,10,11,12, and broadly consistent with estimates based on a bottom-up bootstrap analysis of this fire episode13. Although fires occur regularly in the savannas in northern Australia, the recent episodes were extremely large in scale and intensity, burning unusually large areas of eucalyptus forest in the southeast13. The fires were driven partly by climate change14,15, making better-constrained emission estimates particularly important. This is because the build-up of atmospheric carbon dioxide may become increasingly dependent on fire-driven climate–carbon feedbacks, as highlighted by this event16.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Comparison of fire emission estimates for Southeast Australia.
Fig. 2: Comparison of simulated and observed CO column mixing ratios.
Fig. 3: CO emissions from inventories and satellite constraints.
Fig. 4: CO2 emissions from inventories and satellite constraints.

Data availability

TROPOMI measurements of CO can be downloaded from GFED4s-based fire emissions can be downloaded from GFAS-based fire emissions can be downloaded from QFED-based fire emissions can be downloaded from FEER-based fire emissions can be downloaded from FINN-based fire emissions can be downloaded from Prior and posterior emissions and CO concentrations can be downloaded from

Code availability

The Weather Research and Forecasting with Chemistry (WRF-CHEM) atmospheric transport model version 4.0 can be downloaded from Inversion and emission preparation codes are available at Python notebooks used to create the figures and tables are at


  1. 1.

    Bowman, D. M. et al. Wildfires: Australia needs national monitoring agency. Nature 584, 188–191 (2020).

    ADS  CAS  Article  Google Scholar 

  2. 2.

    Australian Government Annual Climate Statement 2019. (last accessed 23 July 2021) (2019).

  3. 3.

    Australian Government Technical Update 2020. Estimating greenhouse gas emissions from bushfires in Australia’s temperate forests: focus on 2019–20. (last accessed 23 July 2021) (2020).

  4. 4.

    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).

    ADS  CAS  Article  Google Scholar 

  5. 5.

    Veefkind, J. P. et al. TROPOMI on the ESA Sentinel-5 precursor: a GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications. Remote Sens. Environ. 120, 70–83 (2012).

    ADS  Article  Google Scholar 

  6. 6.

    Tarantola, A. Inverse Problem Theory and Methods for Model Parameter Estimation (Soc. Indust. Appl. Math., Philadelphia, PA, 2005).

  7. 7.

    Guérette, E.-A. et al. Emissions of trace gases from Australian temperate forest fires: emission factors and dependence on modified combustion efficiency. Atmos. Chem. Phys. 18, 3717–3735 (2018).

    ADS  Article  Google Scholar 

  8. 8.

    Van der Werf, G. R. et al. Global fire emissions estimates during 1997–2016. Earth Syst. Sci. Data 9, 697–720 (2017).

    ADS  Article  Google Scholar 

  9. 9.

    Wiedinmyer, C. et al. The Fire Inventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning. Geosci. Model Dev. 4, 625–641 (2011).

    ADS  Article  Google Scholar 

  10. 10.

    Kaiser, J. W. et al. Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power. Biogeosciences 9, 527–554 (2012).

    ADS  CAS  Article  Google Scholar 

  11. 11.

    Darmenov, A. & da Silva, A. The quick fire emissions dataset (QFED): documentation of versions 2.1, 2.2 and 2.4. NASA Global Modeling and Assimilation Office (last accessed 23 July 2021) (2015).

  12. 12.

    Ichoku, C. & Ellison, L. Global top-down smoke-aerosol emissions estimation using satellite fire radiative power measurements. Atmos. Chem. Phys. 14, 6643–6667 (2014).

    ADS  Article  Google Scholar 

  13. 13.

    Bowman, D. M. J. S., et al. Australian forests, megafires and the risk of dwindling carbon stocks. Plant Cell Environ. 44, 347–355 (2021).

    CAS  Article  Google Scholar 

  14. 14.

    Van Oldenborgh, G. J. et al. Attribution of the Australian bushfire risk to anthropogenic climate change. Nat. Hazards Earth Syst. Sci. 21, 941–960 (2021).

    ADS  Article  Google Scholar 

  15. 15.

    Abram, N. J. et al. Connections of climate change and variability to large and extreme forest fires in southeast Australia. Commun. Earth Environ. 2, 8 (2021).

    ADS  Article  Google Scholar 

  16. 16.

    Shukla, P. R. et al. (eds). in Climate Change and Land: an IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems (eds Shukla, P. R. et al.) (in the press).

  17. 17.

    Andreae, M. O. & Merlet, P. Emission of trace gases and aerosols from biomass burning. Glob. Biogeochem. Cycles 15, 955–966 (2001).

    ADS  CAS  Article  Google Scholar 

  18. 18.

    Van Leeuwen, T. T. et al. Biomass burning fuel consumption rates: a field measurement database. Biogeosciences 11, 7305–7329 (2014).

    ADS  Article  Google Scholar 

  19. 19.

    Seiler, W. & Crutzen, P. J. Estimates of gross and net fluxes of carbon between the biosphere and the atmosphere from biomass burning. Clim. Change 2, 207–247 (1980).

    ADS  CAS  Article  Google Scholar 

  20. 20.

    Wooster, M. J. et al. Fire radiative energy for quantitative study of biomass burning: derivation from the BIRD experimental satellite and comparison to MODIS fire products. Remote Sens. Environ. 86, 83–107 (2003).

    ADS  Article  Google Scholar 

  21. 21.

    Global Fire Emissions Database, version 4.1 (GFED4s): monthly and daily 1997–present. (last accessed 23 July 2021)

  22. 22.

    Yin, Y. et al. Variability of fire carbon emissions in equatorial Asia and its nonlinear sensitivity to El Niño. Geophys. Res. Lett. 43, 10472–10479 (2016).

    ADS  Article  Google Scholar 

  23. 23.

    Huijnen, V. et al. Fire carbon emissions over maritime Southeast Asia in 2015 largest since 1997. Sci. Rep. 6, 26886 (2016).

    ADS  CAS  Article  Google Scholar 

  24. 24.

    Heymann, M. et al. CO2 emission of Indonesian fires in 2015 estimated from satellite-derived atmospheric CO2 concentrations. Geophys. Res. Lett. 44, 1537–1544 (2017).

    ADS  CAS  Article  Google Scholar 

  25. 25.

    Lohberger, S. et al. Spatial evaluation of Indonesia’s 2015 fire-affected area and estimated carbon emissions using Sentinel-1. Glob. Change Biol. 24, 644–654 (2018).

    ADS  Article  Google Scholar 

  26. 26.

    Nechita-Banda, N. et al. Monitoring emissions from the 2015 Indonesian fires using CO satellite data. Phil. Trans. R. Soc. Lond. B 373, 20170307 (2018).

    Article  Google Scholar 

  27. 27.

    Schneising, O. et al. Severe Californian wildfires in November 2018 observed from space: the carbon monoxide perspective. Atmos. Chem. Phys 20, 3317–3332 (2020).

    ADS  CAS  Article  Google Scholar 

  28. 28.

    Van der Velde, I. R. et al. Biomass burning combustion efficiency observed from space using measurements of CO and NO2 by the TROPOspheric Monitoring Instrument (TROPOMI). Atmos. Chem. Phys. 21, 597–616 (2021).

    ADS  Article  Google Scholar 

  29. 29.

    Taylor, K. E. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. 106, 7183–7192 (2001).

    ADS  Article  Google Scholar 

  30. 30.

    Wain, A. et al. Managing smoke from wildfires and prescribed burning in southern Australia. Dev. Env. Sci. 8, 535–550 (2008).

    Google Scholar 

  31. 31.

    Akagi, S. K. et al. Emission factors for open and domestic biomass burning for use in atmospheric models. Atmos. Chem. Phys. 11, 4039–4072 (2011).

    ADS  CAS  Article  Google Scholar 

  32. 32.

    Yokelson, R. J. et al. Emissions of formaldehyde, acetic acid, methanol, and other trace gases from biomass fires in North Carolina measured by airborne Fourier transform infrared spectroscopy. J. Geophys. Res. 104 (D23), 30109–30125 (1999).

    ADS  CAS  Article  Google Scholar 

  33. 33.

    Houghton, R. A. & Nassikas, A. A. Global and regional fluxes of carbon from land use and land cover change 1850–2015. Glob. Biogeochem. Cycles 31, 456–472 (2017).

    ADS  CAS  Article  Google Scholar 

  34. 34.

    Lucas, C. et al. Bushfire weather in Southeast Australia: recent trends and projected climate change impacts. Technical Report (Bushfire CRC and CSIRO Marine and Atmospheric Research, Melbourne, Australia, 2007).

  35. 35.

    Clarke, H. et al. Regional signatures of future fire weather over eastern Australia from global climate models. Int. J. Wildland Fire 20, 550–562 (2011).

    Article  Google Scholar 

  36. 36.

    Matthews, S. et al. Climate change, fuel and fire behaviour in a eucalypt forest. Glob. Change Biol. 18, 3212–3223 (2012).

    ADS  Article  Google Scholar 

  37. 37.

    Muntean, M. et al. Fossil CO2 Emissions of All World Countries: 2018 Report. (European Commission JRC Science for Policy Report, 2018).

  38. 38.

    Hurst, D. F. et al. Trace-Gas Emissions from Biomass Burning in Australia, in: Biomass Burning and Global Change. (ed. Levine, J. S.) (MIT Press, 1996).

  39. 39.

    Lawson, S. J. et al. Biomass burning emissions of trace gases and particles in marine air at Cape Grim, Tasmania. Atmos. Chem. Phys. 15, 13393–13411 (2015).

    ADS  CAS  Article  Google Scholar 

  40. 40.

    Paton-Walsh, C. et al. New emission factors for Australian vegetation fires measured using open-path Fourier transform infrared spectroscopy. Part 1. Methods and Australian temperate forest fires. Atmos. Chem. Phys. 14, 11313–11333 (2014).

    ADS  Article  Google Scholar 

  41. 41.

    Rea, G. et al. Impact of the New South Wales fires during October 2013 on regional air quality in eastern Australia. Atmos. Environ. 131, 150–163 (2016).

    ADS  CAS  Article  Google Scholar 

  42. 42.

    Reisen, F. et al. Ground-based field measurements of PM2.5 emission factors from flaming and smoldering combustion in eucalypt forests. J. Geophys. Res. 123, 8301–8314 (2018).

Download references


We thank the team that realized the TROPOMI instrument, comprising a partnership between Airbus Defence and Space Netherlands, the Royal Netherlands Meteorological Institute (KNMI), the SRON Netherlands Institute for Space Research and the Netherlands Organisation for Applied Scientific Research (TNO), commissioned by the Netherlands Space Office (NSO) and the European Space Agency (ESA). The Sentinel-5 Precursor is part of the European Union (EU) Copernicus programme, and Copernicus Sentinel data from 2019 and 2020 have been used here. The WRF model computations were carried out on the Dutch national e-infrastructure with the support of the SURF Cooperative. We also thank the large team of scientists and technicians who worked on the fire emission data sets available online. G.R.v.d.W. and I.R.v.d.V. are partly supported by the Netherlands Organization for Scientific Research (NWO; VICI research programme 016.160.324).

Author information




I.R.v.d.V. analysed data, designed and ran the model simulations and wrote the paper. G.R.v.d.W., S.H. and I.A. provided scientific advice and detailed comments on the manuscript. J.D.M., T.B., T.A.v.K. and P.T. provided additional comments on the manuscript and TROPOMI products. J.L. and T.B. developed the TROPOMI CO product. R.v.H., T.A.v.K., P.T. and R.H. contributed to the TROPOMI shortwave-infrared (SWIR) calibration. J.P.V. is the principal investigator for the TROPOMI instrument.

Corresponding author

Correspondence to Ivar R. van der Velde.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Johannes Kaiser and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Extended data figures and tables

Extended Data Table 1 Comparison of prior and posterior emissions of CO from fire for Southeast Australia
Extended Data Table 2 Comparison of prior and posterior emissions of CO2 from fire for Southeast Australia
Extended Data Table 3 Comparison of published CO2 and CO emission factors and their ratios
Extended Data Table 4 Overview of CO and CO2 emission estimates for different experiments

Supplementary information

Supplementary Information

This file contains Supplementary Methodology and additional information, including Supplementary Figures 1-6, and additional references.

Supplementary Video 1

Video of daily simulated and observed CO column mixing ratios. The video shows on the first row the daily prior (using GFAS emissions), posterior and TROPOMI CO column mixing ratios [ppb]. The second row shows prior minus TROPOMI and posterior minus TROPOMI, and the third panel shows the average wind direction in the planetary boundary layer from WRF-CHEM.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

van der Velde, I.R., van der Werf, G.R., Houweling, S. et al. Vast CO2 release from Australian fires in 2019–2020 constrained by satellite. Nature 597, 366–369 (2021).

Download citation


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing