Articles | Volume 14, issue 5
https://doi.org/10.5194/esd-14-1039-2023
https://doi.org/10.5194/esd-14-1039-2023
Research article
 | 
10 Oct 2023
Research article |  | 10 Oct 2023

Dynamic savanna burning emission factors based on satellite data using a machine learning approach

Roland Vernooij, Tom Eames, Jeremy Russell-Smith, Cameron Yates, Robin Beatty, Jay Evans, Andrew Edwards, Natasha Ribeiro, Martin Wooster, Tercia Strydom, Marcos Vinicius Giongo, Marco Assis Borges, Máximo Menezes Costa, Ana Carolina Sena Barradas, Dave van Wees, and Guido R. Van der Werf

Related authors

A quadcopter unmanned aerial system (UAS)-based methodology for measuring biomass burning emission factors
Roland Vernooij, Patrik Winiger, Martin Wooster, Tercia Strydom, Laurent Poulain, Ulrike Dusek, Mark Grosvenor, Gareth J. Roberts, Nick Schutgens, and Guido R. van der Werf
Atmos. Meas. Tech., 15, 4271–4294, https://doi.org/10.5194/amt-15-4271-2022,https://doi.org/10.5194/amt-15-4271-2022, 2022
Short summary
Stable carbon isotopic composition of biomass burning emissions – implications for estimating the contribution of C3 and C4 plants
Roland Vernooij, Ulrike Dusek, Maria Elena Popa, Peng Yao, Anupam Shaikat, Chenxi Qiu, Patrik Winiger, Carina van der Veen, Thomas Callum Eames, Natasha Ribeiro, and Guido R. van der Werf
Atmos. Chem. Phys., 22, 2871–2890, https://doi.org/10.5194/acp-22-2871-2022,https://doi.org/10.5194/acp-22-2871-2022, 2022
Short summary
Intraseasonal variability of greenhouse gas emission factors from biomass burning in the Brazilian Cerrado
Roland Vernooij, Marcos Giongo, Marco Assis Borges, Máximo Menezes Costa, Ana Carolina Sena Barradas, and Guido R. van der Werf
Biogeosciences, 18, 1375–1393, https://doi.org/10.5194/bg-18-1375-2021,https://doi.org/10.5194/bg-18-1375-2021, 2021
Short summary

Cited articles

Adzhar, R., Kelley, D. I., Dong, N., George, C., Torello Raventos, M., Veenendaal, E., Feldpausch, T. R., Phillips, O. L., Lewis, S. L., Sonké, B., Taedoumg, H., Schwantes Marimon, B., Domingues, T., Arroyo, L., Djagbletey, G., Saiz, G., and Gerard, F.: MODIS Vegetation Continuous Fields tree cover needs calibrating in tropical savannas, Biogeosciences, 19, 1377–1394, https://doi.org/10.5194/bg-19-1377-2022, 2022. 
Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D., and Wennberg, P. O.: Emission factors for open and domestic biomass burning for use in atmospheric models, Atmos. Chem. Phys., 11, 4039–4072, https://doi.org/10.5194/acp-11-4039-2011, 2011. 
Andela, N., Kaiser, J. W., van der Werf, G. R., and Wooster, M. J.: New fire diurnal cycle characterizations to improve fire radiative energy assessments made from MODIS observations, Atmos. Chem. Phys., 15, 8831–8846, https://doi.org/10.5194/acp-15-8831-2015, 2015. 
Anderson, M. C., Norman, J. M., Mecikalski, J. R., Otkin, J. A., and Kustas, W. P.: A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation, J. Geophys. Res.-Atmos., 112, 1–17, https://doi.org/10.1029/2006JD007506, 2007. 
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. 
Download
Short summary
Savannas account for over half of global landscape fire emissions. Although environmental and fuel conditions affect the ratio of species the fire emits, these dynamics have not been implemented in global models. We measured CO2, CO, CH4, and N2O emission factors (EFs), fuel parameters, and fire severity proxies during 129 individual fires. We identified EF patterns and trained models to estimate EFs of these species based on satellite observations, reducing the estimation error by 60–85 %.
Altmetrics
Final-revised paper
Preprint