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Global nitrous acid emissions and levels of regional oxidants enhanced by wildfires


Nitrous acid (HONO) is a precursor of the hydroxyl radical in the atmosphere, which controls the degradation of greenhouse gases, contributes to photochemical smog and ozone production, and influences air quality. Although biomass burning is known to contribute substantially to global aerosols and reactive gas emissions, pyrogenic contributions to HONO emissions are poorly constrained and often omitted in models. Here we present a global survey of TROPOMI/Sentinel-5 Precursor satellite sounder observations and show that HONO emissions are consistently enhanced in fresh wildfire plumes. Comparing major ecosystems (savanna, grassland, shrubland and tropical and extratropical forests), we found that the enhancement ratios of HONO to nitrogen dioxide varied systematically with biome type, with the lowest in savannas and grasslands and highest in extratropical evergreen forests. Supported by airborne measurements, we demonstrate that previous assessments underestimate pyrogenic HONO emissions by a factor of 2–4 across all ecosystem types. We estimate that HONO emissions are responsible for two-thirds of the hydroxyl radical production in fresh wildfire plumes worldwide and act to accelerate oxidative plume chemistry and ozone production. Our findings suggest that pyrogenic HONO emissions have a substantial impact on atmospheric composition, which enhances regional ozone levels by up to 7 ppbv.

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Fig. 1: Detection of HONO in wildfire plumes by TROPOMI.
Fig. 2: Comparison between TROPOMI and aircraft (CU-DOAS) measurements of the Rabbit Foot Fire on 12 August 2018.
Fig. 3: Satellite-derived RHNs and relative production rates of OH due to HONO photolysis for fire emissions.

Data availability

The global data and validation data that support the findings of this study are available in the BIRA-IASB Data Repository ( with the identifier The TROPOMI HONO dataset used in this study is also available from the corresponding author upon request. The BB-FLUX dataset is also available on request68. data are provided with this paper.

Code availability

The DOAS code used to generate the satellite and aircraft data can be accessed at The chemical mechanism of the MAGRITTE model used in this study can be obtained at


  1. 1.

    Finlayson-Pitts, B. J. & Pitts, J. N. Chemistry of the Upper and Lower Atmosphere: Theory, Experiments and Applications (Academic, 2000).

  2. 2.

    Spataro, F. & Ianniello, A. Sources of atmospheric nitrous acid: state of the science, current research needs, and future prospects. J. Air Waste Manage. Assoc. 64, 1232–1250 (2014).

    Google Scholar 

  3. 3.

    Ammann, M. et al. Heterogeneous production of nitrous acid on soot in polluted air masses. Nature 395, 157–160 (1998).

    Google Scholar 

  4. 4.

    Stemmler, K., Ammann, M., Donders, C., Kleffmann, J. & George, C. Photosensitized reduction of nitrogen dioxide on humic acid as a source of nitrous acid. Nature 440, 195–198 (2006).

    Google Scholar 

  5. 5.

    Zhou, X. et al. Nitric acid photolysis on forest canopy surface as a source for tropospheric nitrous acid. Nat. Geosci. 4, 440–443 (2011).

    Google Scholar 

  6. 6.

    Oswald, R. et al. HONO emissions from soil bacteria as a major source of atmospheric reactive nitrogen. Science 341, 1233–1235 (2013).

    Google Scholar 

  7. 7.

    VandenBoer, T. C. et al. Nocturnal loss and daytime source of nitrous acid through reactive uptake and displacement. Nat. Geosci. 8, 55–60 (2015).

    Google Scholar 

  8. 8.

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

    Google Scholar 

  9. 9.

    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).

    Google Scholar 

  10. 10.

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

    Google Scholar 

  11. 11.

    Elshorbany, Y. F. et al. Global and regional impacts of HONO on the chemical composition of clouds and aerosols. Atmos. Chem. Phys. 14, 1167–1184 (2014).

    Google Scholar 

  12. 12.

    Veres, P. et al. Measurements of gas-phase inorganic and organic acids from biomass fires by negative-ion proton-transfer chemical-ionization mass spectrometry. J. Geophys. Res. 115, D23302 (2010).

    Google Scholar 

  13. 13.

    Nie, W. et al. Influence of biomass burning plumes on HONO chemistry in eastern China. Atmos. Chem. Phys. 15, 1147–1159 (2015).

    Google Scholar 

  14. 14.

    Monge, M. E. et al. Light changes the atmospheric reactivity of soot. Proc. Natl Acad. Sci. USA 107, 6605–6609 (2010).

    Google Scholar 

  15. 15.

    Ye, C., Zhang, N., Gao, H. & Zhou, X. Photolysis of particulate nitrate as a source of HONO and NOx. Environ. Sci. Technol. 51, 6849–6856 (2017).

    Google Scholar 

  16. 16.

    Li, L. et al. Formation of HONO from the NH3-promoted hydrolysis of NO2-dimers in the atmosphere. Proc. Natl Acad. Sci. USA 115, 7236–7241 (2018).

    Google Scholar 

  17. 17.

    Keene, W. C. et al. Emissions of major gaseous and particulate species during experimental burns of southern African biomass. J. Geophys. Res. 111, D04301 (2006).

    Google Scholar 

  18. 18.

    Burling, I. R. et al. Laboratory measurements of trace gas emissions from biomass burning of fuel types from the southeastern and southwestern United States. Atmos. Chem. Phys. 10, 11115–11130 (2010).

    Google Scholar 

  19. 19.

    Trentmann, J. et al. An analysis of the chemical processes in the smoke plume from a savanna fire. J. Geophys. Res. 110, D12301 (2005).

    Google Scholar 

  20. 20.

    Yokelson, R. J. et al. The tropical forest and fire emissions experiment: overview and airborne fire emission factor measurements. Atmos. Chem. Phys. 7, 5175–5196 (2007).

    Google Scholar 

  21. 21.

    Yokelson, R. J. et al. Emissions from biomass burning in the Yucatan. Atmos. Chem. Phys. 9, 5785–5812 (2009).

    Google Scholar 

  22. 22.

    Akagi, S. K. et al. Measurements of reactive trace gases and variable O3 formation rates in some South Carolina biomass burning plumes. Atmos. Chem. Phys. 13, 1141–1165 (2013).

    Google Scholar 

  23. 23.

    Müller, M. et al. In situ measurements and modeling of reactive trace gases in a small biomass burning plume. Atmos. Chem. Phys. 16, 3813–3824 (2016).

    Google Scholar 

  24. 24.

    Neuman, J. A. et al. HONO emission and production determined from airborne measurements over the Southeast U.S. J. Geophys. Res. Atmos. 121, 9237–9250 (2016).

    Google Scholar 

  25. 25.

    Beirle, S., Boersma, K. F., Platt, U., Lawrence, M. G. & Wagner, T. Megacity emissions and lifetime of nitrogen oxides probed from space. Science 333, 1737–1739 (2011).

    Google Scholar 

  26. 26.

    McLinden, C. A. et al. Space-based detection of missing sulfur dioxide sources of global air pollution. Nat. Geosci. 9, 496–500 (2016).

    Google Scholar 

  27. 27.

    Van Damme, M. et al. Industrial and agricultural ammonia point sources exposed. Nature 564, 99–103 (2018).

    Google Scholar 

  28. 28.

    Clarisse, L., R’Honi, Y., Coheur, P.-F., Hurtmans, D. & Clerbaux, C. Thermal infrared nadir observations of 24 atmospheric gases. Geophys. Res. Lett. 38, L10802 (2011).

    Google Scholar 

  29. 29.

    Platt, U., Perner, D., Harris, G. W., Winer, A. M. & Pitts, J. N. Observations of nitrous acid in an urban atmosphere by differential optical absorption. Nature 285, 312–314 (1980).

    Google Scholar 

  30. 30.

    Platt, U. & Stutz, J. Differential Optical Absorption Spectroscopy (DOAS), Principle and Applications (Springer, 2008).

  31. 31.

    Hendrick, F. et al. Four years of ground-based MAX-DOAS observations of HONO and NO2 in the Beijing area. Atmos. Chem. Phys. 14, 765–781 (2014).

    Google Scholar 

  32. 32.

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

    Google Scholar 

  33. 33.

    Kleffmann, J. Daytime sources of nitrous acid (HONO) in the atmospheric boundary layer. Chem. Phys. Chem. 8, 1137–1144 (2007).

    Google Scholar 

  34. 34.

    Peng, Q. et al. HONO emissions from western U.S. wildfires provide dominant radical source in fresh wildfire smoke. Environ. Sci. Technol. 54, 5954–5963 (2020).

    Google Scholar 

  35. 35.

    Liu, X. et al. Airborne measurements of western U.S. wildfire emissions: comparison with prescribed burning and air quality implications. J. Geophys. Res. Atmos. 112, 6108–6129 (2017).

    Google Scholar 

  36. 36.

    Alicke, B., Platt, U. & Stutz, J. Impact of nitrous acid photolysis on the total hydroxyl radical budget during the Limitation of Oxidant Production/Pianura Padana Produzione di Ozono study in Milan. J. Geophys. Res. Atmos. 107, 8196 (2002).

    Google Scholar 

  37. 37.

    Volkamer, R., Sheehy, P., Molina, L. T. & Molina, M. J. Oxidative capacity of the Mexico City atmosphere—Part 1: a radical source perspective. Atmos. Chem. Phys. 10, 6969–2991 (2010).

    Google Scholar 

  38. 38.

    Kleffmann, J. et al. Daytime formation of nitrous acid: a major source of OH radicals in a forest. Geophys. Res. Lett. 32, L05818 (2005).

    Google Scholar 

  39. 39.

    Friedl, M. A. et al. MODIS Collection 5 global land cover: algorithm refinements and characterization of new datasets. Remote Sens. Environ. 114, 168–182 (2010).

    Google Scholar 

  40. 40.

    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).

    Google Scholar 

  41. 41.

    Levelt, P. F. et al. The ozone monitoring instrument. IEEE Trans. Geosci. Remote Sens. 44, 1093–1101 (2006).

    Google Scholar 

  42. 42.

    Bovensmann, H. et al. SCIAMACHY: mission objectives and measurement modes. J. Atmos. Sci. 56, 127–150 (1999).

    Google Scholar 

  43. 43.

    De Smedt, I. et al. Algorithm theoretical baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project. Atmos. Meas. Tech. 11, 2395–2426 (2018).

    Google Scholar 

  44. 44.

    Wang, Y. et al. MAX-DOAS measurements of HONO slant column densities during the MAD-CAT campaign: inter-comparison, sensitivity studies on spectral analysis settings, and error budget. Atmos. Meas. Tech. 10, 3719–3742 (2017).

    Google Scholar 

  45. 45.

    Behrens, L. K. et al. GOME-2A retrievals of tropospheric NO2 in different spectral ranges—influence of penetration depth. Atmos. Meas. Tech. 11, 2769–2795 (2018).

    Google Scholar 

  46. 46.

    Richter, A. & Burrows, J. P. Retrieval of tropospheric NO2 from GOME measurements. Adv. Space Res. 29, 1673–1683 (2002).

    Google Scholar 

  47. 47.

    Palmer, P. I. et al. Air mass factor formulation for spectroscopic measurements from satellites: application to formaldehyde retrievals from the Global Ozone Monitoring Experiment. J. Geophys. Res. 106, 14539–14550 (2001).

    Google Scholar 

  48. 48.

    Spurr, R. J. VLIDORT: a linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media. J. Quant. Spectrosc. Rad. 102, 316–342 (2006).

    Google Scholar 

  49. 49.

    Wang, P., Tuinder, O. N. E., Tilstra, L. G., de Graaf, M. & Stammes, P. Interpretation of FRESCO cloud retrievals in case of absorbing aerosol events. Atmos. Chem. Phys. 12, 9057–9077 (2012).

    Google Scholar 

  50. 50.

    Leitão, J. et al. On the improvement of NO2 satellite retrievals—aerosol impact on the airmass factors. Atmos. Meas. Tech. 3, 475–493 (2010).

    Google Scholar 

  51. 51.

    Brioude, J. et al. The Lagrangian particle dispersion model FLEXPART-WRF version 3.1. Geosci. Model Dev. 6, 1889–1904 (2013).

    Google Scholar 

  52. 52.

    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).

    Google Scholar 

  53. 53.

    Lerot, C., Stavrakou, T., De Smedt, I., Müller, J.-F. & Van Roozendael, M. Glyoxal vertical columns from GOME-2 backscattered light measurements and comparisons with a global model. Atmos. Chem. Phys. 10, 12059–12072 (2010).

    Google Scholar 

  54. 54.

    Stavrakou, T. et al. Impact of short-term climate variability on volatile organic compounds emissions assessed using OMI satellite formaldehyde observations. Geophys. Res. Lett. 45, 1621–1629 (2018).

    Google Scholar 

  55. 55.

    Müller, J.-F., Stavrakou, T. & Peeters, J. Chemistry and deposition in the Model of Atmospheric composition at Global and Regional scales using Inversion Techniques for Trace gas Emissions (MAGRITTEv1.0)—Part 1: chemical mechanism. Geosci. Model Dev. 12, 2307–2356 (2019).

    Google Scholar 

  56. 56.

    Madronich, S. in Environmental Effects of Ultraviolet Radiation (ed. Tevini, M.) 17–69 (Lewis, 1993).

  57. 57.

    Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011).

    Google Scholar 

  58. 58.

    Trentmann, J., Andreae, M. O. & Graf, H.-F. Chemical processes in a young biomass-burning plume. J. Geophys. Res. 108, 4705 (2003).

    Google Scholar 

  59. 59.

    Jacob, D. J. et al. The Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) mission: design, execution, and first results. Atmos. Chem. Phys. 10, 5191–5212 (2010).

    Google Scholar 

  60. 60.

    Simpson, I. J. et al. Boreal forest fire emissions in fresh Canadian smoke plumes: C1–C10 volatile organic compounds (VOCs), CO2, CO, NO2, NO, HCN and CH3CN. Atmos. Chem. Phys. 11, 6445–6463 (2011).

    Google Scholar 

  61. 61.

    Atkinson, R. et al. Evaluated kinetic and photochemical data for atmospheric chemistry: volume II—gas phase reactions of organic species. Atmos. Chem. Phys. 6, 3625–4055 (2006).

    Google Scholar 

  62. 62.

    Saunders, S. M., Jenkin, M. E., Derwent, R. G. & Pilling, M. J. Protocol for the development of the Master Chemical Mechanism, MCM v3 (Part A): tropospheric degradation of non-aromatic volatile organic compounds. Atmos. Chem. Phys. 3, 161–180 (2003).

    Google Scholar 

  63. 63.

    Jenkin, M. E., Young, J. C. & Rickard, A. R. The MCMv3.3. 1 degradation scheme for isoprene. Atmos. Chem. Phys. 15, 11433–11459 (2015).

    Google Scholar 

  64. 64.

    Colmenar, I. et al. UV absorption cross-sections between 290 and 280 of a series of furanaldehydes: estimation of their photolysis lifetimes. Atmos. Environ. 103, 1–6 (2015).

    Google Scholar 

  65. 65.

    Gandini, A., Parsons, J. M. & Back, R. A. The photochemistry of 2-furaldehyde vapour. II. Photodecomposition: direct photolysis at 253.7 and 313 nm and Hg(3P1)-sensitized decomposition. Can. J. Chem. 54, 3095–3101 (1976).

    Google Scholar 

  66. 66.

    Burkholder, J. B. et al. Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies (Jet Propulsion Laboratory, 2015);

  67. 67.

    Stavrakou, T. et al. Evaluating the performance of pyrogenic and biogenic emission inventories against one decade of space-based formaldehyde columns. Atmos. Chem. Phys. 9, 1037–1060 (2009).

    Google Scholar 

  68. 68.

    Volkamer, R. et al. BB-FLUX: Biomass Burning Fluxes of Trace Gases and Aerosols (University of Wyoming—Research Flight Center, 2019);

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This work was performed in the frame of the TROPOMI and the BB-FLUX projects. We acknowledge financial support from ESA S5P MPC (4000117151/16/I-LG) and Belgium Prodex TRACE-S5P (PEA 4000105598) projects. The BB-FLUX project is supported by US National Science Foundation award AGS-1754019 (principal investigator, R.V.). C.F.L. received summer support from the Department of Chemistry, CU Boulder. H.F. is recipient of a NASA graduate fellowship. L.C. is a research associate supported by the Belgian FRS-FNRS. This paper contains modified Copernicus data (2018/2019) processed by BIRA-IASB. We thank T. Stavrakou for her advices on the model simulations. We acknowledge the open access policy of the GFED4 database. We thank the entire BB-FLUX science team, the pilots and the UW Flight Center staff. The plume age estimates contain modified Copernicus Atmosphere Monitoring Service Information 2019. Neither the European Commission nor ECMWF is responsible for any use that may be made of the information it contains. We acknowledge the use of imagery from the NASA Worldview application (, part of the NASA Earth Observing System Data and Information System (EOSDIS). We acknowledge the use of data and imagery from LANCE FIRMS operated by NASA’s Earth Science Data and Information System (ESDIS) with funding provided by NASA Headquarters.

Author information




N.T., R.V. and J.-F.M. designed the research, M.V.R. supervised the work. N.T, I.D.S., C.L., H.Y. and M.V.R. developed the satellite algorithms and processed the data. K.J.Z., N.K., H.F., T.K.K., C.F.L. and R.V. performed aircraft measurements and data analysis. J.-F.M. performed model calculations. C.K. performed plume age calculations. All the authors contributed to the text and interpretation of the results. N.T. analysed and interpreted the TROPOMI HONO data, with the help of R.V. and K.J.Z. N.T. prepared all the figures and wrote the manuscript, with input from all the co-authors.

Corresponding authors

Correspondence to N. Theys or R. Volkamer.

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The authors declare no competing interests.

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Peer review information Primary handling editor: Clare Davis.

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Extended data

Extended Data Fig. 1 Comparison between TROPOMI and aircraft (CU DOAS) measurements of the Rabbit Foot (Idaho) and Watson Creek (Oregon) fires on August 15 and 19, 2018.

a, b, HONO slant columns from TROPOMI (rectangles) and nearly synchronized (± 15 minutes) aircraft CU-DOAS (dots), for Rabbit Foot fire (a) and Watson Creek fire (b). The fires source locations are indicated by the red points (source: c, d, Comparison between TROPOMI and aircraft RHN as function of plume age (Methods), respectively for (a, b). TROPOMI pixels delineated by grey lines in (a, b) are used for the comparison, and correspond to unambiguous detections of both HONO and NO2 with SCDs>2xretrieval uncertainty (other pixels are considered not suitable for comparison). The two aircraft traverses of the plumes are plotted separately. Aircraft measurements more than 5 km away from the satellite pixels are not considered. Error bars correspond to systematic uncertainties on RHNs.

Source data

Extended Data Fig. 2 RHN and normalized slant columns dependence with distance from HONO maximum.

a, Averages of RHN for extra-tropical forest and savanna ecosystems, as a function of the distance from the measured HONO maxima for the 100 largest measured HONO SCDs. Error bars are RHN standard deviations; numbers are the total pixels per distance bin. RHN peaks are found within the 5–12 km radius of temporary flight restriction (TFR) zone or affected by fire-induced turbulence. The TROPOMI results are classified using MODIS land cover type39. The inset colored bars indicate the range (mean ± standard deviation) of RHN found in the literature (Supplementary Table 2, excluding fresh plumes from large wildfires34). b, same as (a) for the HONO and NO2 slant column densities (normalized).

Extended Data Fig. 3 Modelled impact of pyrogenic HONO.

Calculated enhancement in the near-surface mixing ratios of HONO (a), OH (b) and O3 (c, d) due to the inclusion of pyrogenic HONO emissions, for the month of August 2018.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–3, Tables 1–8 and references.

Source data

Source Data Extended Data Fig. 1

Satellite and aircraft data (HONO slant column, ratio HONO to NO2, plume age).

Source Data Extended Data Fig. 3

Calculated enhancement in the near-surface mixing ratios of HONO, OH and O3.

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Theys, N., Volkamer, R., Müller, JF. et al. Global nitrous acid emissions and levels of regional oxidants enhanced by wildfires. Nat. Geosci. 13, 681–686 (2020).

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