Articles | Volume 23, issue 1
https://doi.org/10.5194/acp-23-711-2023
© Author(s) 2023. 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-23-711-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Jan 2023
Research article |
| 17 Jan 2023
| 17 Jan 2023
Estimation of biomass burning emission of NO2 and CO from 2019–2020 Australia fires based on satellite observations
Nenghan Wan
Department of Agronomy, Kansas State University, Manhattan, KS 66504, USA
Xiaozhen Xiong
NASA Langley Research Center, Hampton, VA 23618, USA
Gerard J. Kluitenberg
Department of Agronomy, Kansas State University, Manhattan, KS 66504, USA
J. M. Shawn Hutchinson
Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, KS 66504, USA
Robert Aiken
Department of Agronomy, Kansas State University, Manhattan, KS 66504, USA
Haidong Zhao
Department of Agronomy, Kansas State University, Manhattan, KS 66504, USA
Xiaomao Lin
CORRESPONDING AUTHOR
Department of Agronomy, Kansas State University, Manhattan, KS 66504, USA
Related authors
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
Short summary
Short summary
Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Haidong Zhao, Gretchen F. Sassenrath, Mary Beth Kirkham, Nenghan Wan, and Xiaomao Lin
Hydrol. Earth Syst. Sci., 25, 4357–4372, https://doi.org/10.5194/hess-25-4357-2021, https://doi.org/10.5194/hess-25-4357-2021, 2021
Short summary
Short summary
This study was done to develop an improved soil temperature model for the USA Great Plains by using common weather station variables as inputs. After incorporating knowledge of estimated soil moisture and observed daily snow depth, the improved model showed a near 50 % gain in performance compared to the original model. We conclude that our improved model can better estimate soil temperature at the surface soil layer where most hydrological and biological processes occur.
Alex C. Ruane, Charlotte L. Pascoe, Claas Teichmann, David J. Brayshaw, Carlo Buontempo, Ibrahima Diouf, Jesus Fernandez, Paula L. M. Gonzalez, Birgit Hassler, Vanessa Hernaman, Ulas Im, Doroteaciro Iovino, Martin Juckes, Iréne L. Lake, Timothy Lam, Xiaomao Lin, Jiafu Mao, Negin Nazarian, Sylvie Parey, Indrani Roy, Wan-Ling Tseng, Briony Turner, Andrew Wiebe, Lei Zhao, and Damaris Zurell
EGUsphere, https://doi.org/10.5194/egusphere-2025-3408, https://doi.org/10.5194/egusphere-2025-3408, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This paper describes how the Coupled Model Intercomparison Project organized its 7th phase (CMIP7) to encourage the production of Earth system model outputs relevant for impacts and adaptation. Community engagement identified 13 opportunities for application across human and natural systems, 60 variable groups and 539 unique variables. We also show how simulations can more efficiently meet applications needs by targeting appropriate resolution, time slices, experiments and variable groups.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
Short summary
Short summary
Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Xiaozhen Xiong, Xu Liu, Robert Spurr, Ming Zhao, Qiguang Yang, Wan Wu, and Liqiao Lei
Atmos. Meas. Tech., 17, 1965–1978, https://doi.org/10.5194/amt-17-1965-2024, https://doi.org/10.5194/amt-17-1965-2024, 2024
Short summary
Short summary
The term “hotspot” refers to the sharp increase in reflectance occurring when incident (solar) and reflected (viewing) directions coincide in the backscatter direction. The accurate simulation of hotspot directional signatures is important for many remote sensing applications, but current models typically require large values of computations to represent the hotspot accurately. This paper provides a numerically improved hotspot BRDF model that converges much faster and is used in VLIDORT.
Wan Wu, Xu Liu, Liqiao Lei, Xiaozhen Xiong, Qiguang Yang, Qing Yue, Daniel K. Zhou, and Allen M. Larar
Atmos. Meas. Tech., 16, 4807–4832, https://doi.org/10.5194/amt-16-4807-2023, https://doi.org/10.5194/amt-16-4807-2023, 2023
Short summary
Short summary
We present a new operational physical retrieval algorithm that is used to retrieve atmospheric properties for each single field-of-view measurement of hyper-spectral IR sounders. The physical scheme includes a cloud-scattering calculation in its forward-simulation part. The data product generated using this algorithm has an advantage over traditional IR sounder data production algorithms in terms of improved spatial resolution and minimized error due to cloud contamination.
Haidong Zhao, Gretchen F. Sassenrath, Mary Beth Kirkham, Nenghan Wan, and Xiaomao Lin
Hydrol. Earth Syst. Sci., 25, 4357–4372, https://doi.org/10.5194/hess-25-4357-2021, https://doi.org/10.5194/hess-25-4357-2021, 2021
Short summary
Short summary
This study was done to develop an improved soil temperature model for the USA Great Plains by using common weather station variables as inputs. After incorporating knowledge of estimated soil moisture and observed daily snow depth, the improved model showed a near 50 % gain in performance compared to the original model. We conclude that our improved model can better estimate soil temperature at the surface soil layer where most hydrological and biological processes occur.
Seth Kutikoff, Xiaomao Lin, Steven R. Evett, Prasanna Gowda, David Brauer, Jerry Moorhead, Gary Marek, Paul Colaizzi, Robert Aiken, Liukang Xu, and Clenton Owensby
Atmos. Meas. Tech., 14, 1253–1266, https://doi.org/10.5194/amt-14-1253-2021, https://doi.org/10.5194/amt-14-1253-2021, 2021
Short summary
Short summary
Fast-response infrared gas sensors have been used over 3 decades for long-term monitoring of water vapor fluxes. As optically improved infrared gas sensors are newly employed, we evaluated the performance of water vapor density and water vapor flux from three generations of infrared gas sensors in Bushland, Texas, USA. From our experiments, fluxes from the old sensors were best representative of evapotranspiration based on a world-class lysimeter reference measurement.
Cited articles
Abram, N. J., Henley, B. J., Sen Gupta, A., Lippmann, T. J. R., Clarke, H., Dowdy, A. J., Sharples, J. J., Nolan, R. H., Zhang, T., Wooster, M. J., Wurtzel, J. B., Meissner, K. J., Pitman, A. J., Ukkola, A. M., Murphy, B. P., Tapper, N. J., and Boer, M. M.:
Connections of climate change and variability to large and extreme forest fires in southeast Australia, Commun. Earth Environ., 2, 8, https://doi.org/10.1038/s43247-020-00065-8, 2021.
Adams, C., McLinden, C. A., Shephard, M. W., Dickson, N., Dammers, E., Chen, J., Makar, P., Cady-Pereira, K. E., Tam, N., Kharol, S. K., Lamsal, L. N., and Krotkov, N. A.:
Satellite-derived emissions of carbon monoxide, ammonia, and nitrogen dioxide from the 2016 Horse River wildfire in the Fort McMurray area, Atmos. Chem. Phys., 19, 2577–2599, https://doi.org/10.5194/acp-19-2577-2019, 2019.
Andreae, M. O.:
Emission of trace gases and aerosols from biomass burning – an updated assessment, Atmos. Chem. Phys., 19, 8523–8546, https://doi.org/10.5194/acp-19-8523-2019, 2019.
Andreae, M. O. and Merlet, P.:
Emission of trace gases and aerosols from biomass burning, Global Biogeochem. Cy., 15, 955–966, https://doi.org/10.1029/2000GB001382, 2001.
Boer, M. M., Resco de Dios, V., and Bradstock, R. A.:
Unprecedented burn area of Australian mega forest fires, Nat. Clim. Change., 10, 171–172, https://doi.org/10.1038/s41558-020-0716-1, 2020.
Borchers A., N., Palmer, A. J., Bowman, D. M., Morgan, G. G., Jalaludin, B. B., and Johnston, F. H.:
Unprecedented smoke-related health burden associated with the 2019–20 bushfires in eastern Australia, Med. J. Aust., 213, 282–283, https://doi.org/10.5694/mja2.50545, 2020.
Borsdorff, T., aan de Brugh, J., Hu, H., Hasekamp, O., Sussmann, R., Rettinger, M., Hase, F., Gross, J., Schneider, M., Garcia, O., Stremme, W., Grutter, M., Feist, D. G., Arnold, S. G., De Mazière, M., Kumar Sha, M., Pollard, D. F., Kiel, M., Roehl, C., Wennberg, P. O., Toon, G. C., and Landgraf, J.:
Mapping carbon monoxide pollution from space down to city scales with daily global coverage, Atmos. Meas. Tech., 11, 5507–5518, https://doi.org/10.5194/amt-11-5507-2018, 2018.
Bowman, D. M. J. S., Williamson, G. J., Abatzoglou, J. T., Kolden, C. A., Cochrane, M. A., and Smith, A. M. S.:
Human exposure and sensitivity to globally extreme wildfire events, Nat. Ecol. Evol., 1, 0058, https://doi.org/10.1038/s41559-016-0058, 2017.
Cai, W., Cowan, T., and Raupach, M.:
Positive Indian Ocean Dipole events precondition southeast Australia bushfires, Geophys. Res. Lett., 36, L19710, https://doi.org/10.1029/2009GL039902, 2009.
Copernicus Sentinel-5P (processed by ESA): TROPOMI Level 2 Aerosol Layer Height products, Version 01, European Space Agency [data set], https://doi.org/10.5270/S5P-j7aj4gr, 2018.
Copernicus Sentinel-5P (processed by ESA): TROPOMI Level 2 Carbon Monoxide total column products, Version 02, European Space Agency [data set], https://doi.org/10.5270/S5P-bj3nry0, 2021.
de Graaf, M., de Haan, J. F., and Sanders, A. F. J.:
TROPOMI ATBD of the Aerosol Layer Height, S5P-KNMI-L2-0006-RP, http://www.tropomi.eu/sites/default/files/files/publicSentinel-5P-TROPOMI-ATBD-Aerosol-Height.pdf (last access: January 2020), 2019.
Desservettaz, M., Paton-Walsh, C., Griffith, D. W. T., Kettlewell, G., Keywood, M. D., Vanderschoot, M. V., Ward, J., Mallet, M. D., Milic, A., Miljevic, B., Ristovski, Z. D., Howard, D., Edwards, G. C., and Atkinson, B.:
Emission factors of trace gases and particles from tropical savanna fires in Australia, J. Geophys. Res.-Atmos., 122, 6059–6074, https://doi.org/10.1002/2016JD025925, 2017.
Douros, J., Eskes, H., van Geffen, J., Boersma, K. F., Compernolle, S., Pinardi, G., Blechschmidt, A.-M., Peuch, V.-H., Colette, A., and Veefkind, P.:
Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS-regional air quality ensemble, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-365, 2022.
Filkov, A. I., Ngo, T., Matthews, S., Telfer, S., and Penman, T. D.:
Impact of Australia's catastrophic 2019/20 bushfire season on communities and environment. Retrospective analysis and current trends, Journal of Safety Science and Resilience, 1, 44–56, https://doi.org/10.1016/j.jnlssr.2020.06.009, 2020.
Fowler, D., Amann, M., Anderson, R., Ashmore, M., Cox, P., Depledge, M., Derwent, D., Grennfelt, P., Hewitt, N., Hov, O., Jenkin, M., Kelly, F., Liss, P., Pilling, M., Pyle, J., Slingo, J., and Stevenson, D.:
Ground-level ozone in the 21st century: future trends, impacts and policy implications, The Royal Society, ISBN 978-0-85403-713-1301, 2008.
Freeborn, P. H., Wooster, M. J., Hao, W. M., Ryan, C. A., Nordgren, B. L., Baker, S. P., and Ichoku, C.:
Relationships between energy release, fuel mass loss, and trace gas and aerosol emissions during laboratory biomass fires, J. Geophys. Res.-Atmos., 113, D01301, https://doi.org/10.1029/2007JD008679, 2008.
Giglio, L., Randerson, J. T., and van der Werf, G. R.: Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), J. Geophys. Res.-Biogeosci., 118, 317–328, https://doi.org/10.1002/jgrg.20042, 2013.
Global Fire Assimilation System (GFAS): CAMS GFAS Output, [data set], http://apps.ecmwf.int/datasets/ (last access: 22 December 2022), 2019.
Godfree, R. C., Knerr, N., Encinas-Viso, F., Albrecht, D., Bush, D., Cargill, D. C., Clements, M., Gueidan, C., Guja, L. K., Harwood, T., Joseph, L., Lepschi, B., Nargar, K., Schmidt-Lebuhn, A., and Broadhurst, L. M.:
Implications of the 2019–2020 megafires for the biogeography and conservation of Australian vegetation, Nat. Commun., 12, 1023, https://doi.org/10.1038/s41467-021-21266-5, 2021.
Griffin, D., McLinden, C. A., Dammers, E., Adams, C., Stockwell, C. E., Warneke, C., Bourgeois, I., Peischl, J., Ryerson, T. B., Zarzana, K. J., Rowe, J. P., Volkamer, R., Knote, C., Kille, N., Koenig, T. K., Lee, C. F., Rollins, D., Rickly, P. S., Chen, J., Fehr, L., Bourassa, A., Degenstein, D., Hayden, K., Mihele, C., Wren, S. N., Liggio, J., Akingunola, A., and Makar, P.:
Biomass burning nitrogen dioxide emissions derived from space with TROPOMI: methodology and validation, Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, 2021.
Guérette, E.-A., Paton-Walsh, C., Desservettaz, M., Smith, T. E. L., Volkova, L., Weston, C. J., and Meyer, C. P.:
Emissions of trace gases from Australian temperate forest fires: emission factors and dependence on modified combustion efficiency, Atmos. Chem. Phys., 18, 3717–3735, https://doi.org/10.5194/acp-18-3717-2018, 2018.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J-N.: ERA5 hourly data on pressure levels from 1959 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2018.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.:
The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hirsch, E. and Koren, I.:
Record-breaking aerosol levels explained by smoke injection into the stratosphere, Science, 371, 1269–1274, https://doi.org/10.1126/science.abe1415, 2021.
Jin, X., Zhu, Q., and Cohen, R. C.:
Direct estimates of biomass burning NOx emissions and lifetimes using daily observations from TROPOMI, Atmos. Chem. Phys., 21, 15569–15587, https://doi.org/10.5194/acp-21-15569-2021, 2021.
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.:
Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527–554, https://doi.org/10.5194/bg-9-527-2012, 2012.
Kaufman, Y. J., Justice, C. O., Flynn, L. P., Kendall, J. D., Prins, E. M., Giglio, L., Ward, D. E., Menzel, W. P., and Setzer, A. W.:
Potential global fire monitoring from EOS-MODIS, J. Geophys. Res.-Atmos., 103, 32215–32238, https://doi.org/10.1029/98JD01644, 1998.
Konovalov, I. B., Berezin, E. V., Ciais, P., Broquet, G., Zhuravlev, R. V., and Janssens-Maenhout, G.:
Estimation of fossil-fuel CO2 emissions using satellite measurements of “proxy” species, Atmos. Chem. Phys., 16, 13509–13540, https://doi.org/10.5194/acp-16-13509-2016, 2016.
Lama, S., Houweling, S., Boersma, K. F., Eskes, H., Aben, I., Denier van der Gon, H. A. C., Krol, M. C., Dolman, H., Borsdorff, T., and Lorente, A.:
Quantifying burning efficiency in megacities using the
Lambert, J. C., Keppens, A., Kleipool, Q., Langerock, B., Sha, M. K., Verhoelst, T., Wagner, T., Ahn, C., Argyrouli, A., and Balis, D.:
S5P MPC Routine Operations Consolidated Validation Report Series. Version 12.01.00, 2, Quarterly validation report of the Copernicus Sentinel-5 Precursor operational data products, 2, 2018.
Landgraf, J., aan de Brugh, J., Scheepmaker, R., Borsdorff, T., Hu, H., Houweling, S., Butz, A., Aben, I., and Hasekamp, O.:
Carbon monoxide total column retrievals from TROPOMI shortwave infrared measurements, Atmos. Meas. Tech., 9, 4955–4975, https://doi.org/10.5194/amt-9-4955-2016, 2016.
Li, F., Zhang, X., Kondragunta, S., and Csiszar, I.:
Comparison of fire radiative power estimates from VIIRS and MODIS observations, J. Geophys. Res.-Atmos., 123, 4545–4563, https://doi.org/10.1029/2017JD027823, 2018.
Lindaas, J., Pollack, I. B., Garofalo, L. A., Pothier, M. A., Farmer, D. K., Kreidenweis, S. M., Campos, T. L., Flocke, F., Weinheimer, A. J., and Montzka, D. D.:
Emissions of reactive nitrogen from western US wildfires during Summer 2018, J. Geophys. Res.-Atmos., 126, e2020JD032657, https://doi.org/10.1029/2020JD032657, 2021.
Lorente, A., Folkert Boersma, K., Yu, H., Dörner, S., Hilboll, A., Richter, A., Liu, M., Lamsal, L. N., Barkley, M., De Smedt, I., Van Roozendael, M., Wang, Y., Wagner, T., Beirle, S., Lin, J.-T., Krotkov, N., Stammes, P., Wang, P., Eskes, H. J., and Krol, M.:
Structural uncertainty in air mass factor calculation for NO2 and HCHO satellite retrievals, Atmos. Meas. Tech., 10, 759–782, https://doi.org/10.5194/amt-10-759-2017, 2017.
Mebust, A. K., Russell, A. R., Hudman, R. C., Valin, L. C., and Cohen, R. C.:
Characterization of wildfire NOx emissions using MODIS fire radiative power and OMI tropospheric NO2 columns, Atmos. Chem. Phys., 11, 5839–5851, https://doi.org/10.5194/acp-11-5839-2011, 2011.
Niemeijer, S.:
ESA Atmospheric Toolbox, in: EGU General Assembly Conference Abstracts 2017, 23–28 April, 2017, Vienna, Austria, EGUGA2017-8286, https://ui.adsabs.harvard.edu/abs/2017EGUGA..19.8286N (last access: 22 December 2022), 2017.
NASA Fire Information for Resource Management System (FIRMS): MODIS Collection 6 Hotspot/Active Fire Detections MCD14ML, [data set], https://doi.org/10.5067/FIRMS/MODIS/MCD14ML, 2018.
Nolan, R. H., Boer, M. M., Collins, L., de Dios, V. R., Clarke, H., Jenkins, M., Kenny, B., and Bradstock, R. A.:
Causes and consequences of eastern Australia's 2019–20 season of mega-fires, Glob. Change Biol., 26, 1039–1041, https://doi.org/10.1111/gcb.14987, 2020.
Paton-Walsh, C., Deutscher, N. M., Griffith, D. W. T., Forgan, B. W., Wilson, S. R., Jones, N. B., and Edwards, D. P.:
Trace gas emissions from savanna fires in northern Australia, J. Geophys. Res.-Atmos., 115, D16314, https://doi.org/10.1029/2009JD013309, 2010.
Peterson, D. A., Fromm, M. D., McRae, R. H. D., Campbell, J. R., Hyer, E. J., Taha, G., Camacho, C. P., Kablick, G. P., Schmidt, C. C., and DeLand, M. T.:
Australia's Black Summer pyrocumulonimbus super outbreak reveals potential for increasingly extreme stratospheric smoke events, NPJ Clim. Atmos. Sci, 4, 1–16, https://doi.org/10.1038/s41612-021-00192-9, 2021.
Possell, M., Jenkins, M., Bell, T. L., and Adams, M. A.:
Emissions from prescribed fires in temperate forest in south-east Australia: implications for carbon accounting, Biogeosciences, 12, 257–268, https://doi.org/10.5194/bg-12-257-2015, 2015.
Randerson, J. T., Chen, Y., van der Werf, G. R., Rogers, B. M., and Morton, D. C.:
Global burned area and biomass burning emissions from small fires, J. Geophys. Res.-Biogeosci., 117, G04012, https://doi.org/10.1029/2012JG002128, 2012.
R'Honi, Y., Clarisse, L., Clerbaux, C., Hurtmans, D., Duflot, V., Turquety, S., Ngadi, Y., and Coheur, P.-F.:
Exceptional emissions of NH3 and HCOOH in the 2010 Russian wildfires, Atmos. Chem. Phys., 13, 4171–4181, https://doi.org/10.5194/acp-13-4171-2013, 2013.
Roberts, J. M., Stockwell, C. E., Yokelson, R. J., de Gouw, J., Liu, Y., Selimovic, V., Koss, A. R., Sekimoto, K., Coggon, M. M., Yuan, B., Zarzana, K. J., Brown, S. S., Santin, C., Doerr, S. H., and Warneke, C.:
The nitrogen budget of laboratory-simulated western US wildfires during the FIREX 2016 Fire Lab study, Atmos. Chem. Phys., 20, 8807–8826, https://doi.org/10.5194/acp-20-8807-2020, 2020.
Russell-Smith, J. A., Yates, C., Whitehead, P. J., Smith, R., Craig, R., Allan, G. E., Thackway, R., Frakes, I., Crid, S., Meyer, M., and Gill, A. M.:
Bushfires 'down under': patterns and implications of contemporary Australian landscape burning, Int. J. Wildland Fire, 16, 361–377,
https://doi.org/10.1071/WF07018, 2007.
Schneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., and Burrows, J. P.:
Severe Californian wildfires in November 2018 observed from space: the carbon monoxide perspective, Atmos. Chem. Phys., 20, 3317–3332, https://doi.org/10.5194/acp-20-3317-2020, 2020.
Smith, T. E. L., Paton-Walsh, C., Meyer, C. P., Cook, G. D., Maier, S. W., Russell-Smith, J., Wooster, M. J., and Yates, C. P.:
New emission factors for Australian vegetation fires measured using open-path Fourier transform infrared spectroscopy – Part 2: Australian tropical savanna fires, Atmos. Chem. Phys., 14, 11335–11352, https://doi.org/10.5194/acp-14-11335-2014, 2014.
Tanimoto, H., Ikeda, K., Boersma, K. F., van der A, R. J., and Garivait, S.:
Interannual variability of nitrogen oxides emissions from boreal fires in Siberia and Alaska during 1996–2011 as observed from space, Environ. Res. Lett., 10, 065004, https://doi.org/10.1088/1748-9326/10/6/065004, 2015.
Val Martin, M., Kahn, R. A., and Tosca, M. G.:
A Global Analysis of Wildfire Smoke Injection Heights Derived from Space-Based Multi-Angle Imaging, Remote Sens.-Basel, 10, 1609, https://doi.org/10.3390/rs10101609, 2018.
van der Velde, I. R., van der Werf, G. R., Houweling, S., Eskes, H. J., Veefkind, J. P., Borsdorff, T., and Aben, I.:
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, https://doi.org/10.5194/acp-21-597-2021, 2021.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Mu, M., Kasibhatla, P. S., Morton, D. C., DeFries, R. S., Jin, Y., and van Leeuwen, T. T.:
Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009), Atmos. Chem. Phys., 10, 11707–11735, https://doi.org/10.5194/acp-10-11707-2010, 2010.
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.:
Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017.
van Geffen, J., Eskes, H., Compernolle, S., Pinardi, G., Verhoelst, T., Lambert, J.-C., Sneep, M., ter Linden, M., Ludewig, A., Boersma, K. F., and Veefkind, J. P.:
Sentinel-5P TROPOMI NO2 retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data, Atmos. Meas. Tech., 15, 2037–2060, https://doi.org/10.5194/amt-15-2037-2022, 2022.
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele, M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P., Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.:
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, https://doi.org/10.1016/j.rse.2011.09.027, 2012.
Vermote, E., Ellicott, E., Dubovik, O., Lapyonok, T., Chin, M., Giglio, L., and Roberts, G. J.:
An approach to estimate global biomass burning emissions of organic and black carbon from MODIS fire radiative power, J. Geophys. Res.-Atmos., 114, D18205, https://doi.org/10.1029/2008JD011188, 2009.
Whitburn, S., Van Damme, M., Kaiser, J. W., van der Werf, G. R., Turquety, S., Hurtmans, D., Clarisse, L., Clerbaux, C., and Coheur, P.-F.:
Ammonia emissions in tropical biomass burning regions: Comparison between satellite-derived emissions and bottom-up fire inventories, Atmos. Environ., 121, 42–54, https://doi.org/10.1016/j.atmosenv.2015.03.015, 2015.
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.
Wilkie, K.:
Devastating bushfire season will cost Australian economy $20BILLION, Experts Warn: https://www.dailymail.co.uk/news/article-7863335/Devastating-bushfire-season-cost-Australian-economy-20BILLION-experts-warn.html, last access: 19 August 2021, 2021.
Wooster, M. J., Zhukov, B., and Oertel, D.:
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, https://doi.org/10.1016/S0034-4257(03)00070-1, 2003.
Wooster, M. J., Roberts, G., Perry, G. L. W., and Kaufman, Y. J.:
Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release, J. Geophys. Res.-Atmos., 110, D24311, https://doi.org/10.1029/2005JD006318, 2005.
Young, E. and Paton-Walsh, C.:
Emission Ratios of the Tropospheric Ozone Precursors Nitrogen Dioxide and Formaldehyde from Australia's Black Saturday Fires, Atmosphere, 2, 617–632, https://doi.org/10.3390/atmos2040617, 2011.
Yurganov, L. N., Rakitin, V., Dzhola, A., August, T., Fokeeva, E., George, M., Gorchakov, G., Grechko, E., Hannon, S., Karpov, A., Ott, L., Semutnikova, E., Shumsky, R., and Strow, L.:
Satellite- and ground-based CO total column observations over 2010 Russian fires: accuracy of top-down estimates based on thermal IR satellite data, Atmos. Chem. Phys., 11, 7925–7942, https://doi.org/10.5194/acp-11-7925-2011, 2011.
Zhao, Y., Nielsen, C. P., Lei, Y., McElroy, M. B., and Hao, J.:
Quantifying the uncertainties of a bottom-up emission inventory of anthropogenic atmospheric pollutants in China, Atmos. Chem. Phys., 11, 2295–2308, https://doi.org/10.5194/acp-11-2295-2011, 2011.
Short summary
This study used new TROPOMI measurements of NO2 and CO to characterize regional biomass burning characteristics and efficiency. We found that the NO2 / CO emission ratio was consistent with recent studies over temperate forest fires but slightly lower in savanna vegetation fires. Our results can help identify the relative contribution of smoldering and flaming activities as well as their impacts on the regional atmospheric composition and air quality.
This study used new TROPOMI measurements of NO2 and CO to characterize regional biomass burning...
Altmetrics
Final-revised paper
Preprint