Articles | Volume 23, issue 3
https://doi.org/10.5194/acp-23-2089-2023
© 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-23-2089-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Biomass burning CO, PM and fuel consumption per unit burned area estimates derived across Africa using geostationary SEVIRI fire radiative power and Sentinel-5P CO data
Department of Geography, King's College London, London, WC2R 2ND, UK
Leverhulme Centre for Wildfires, Environment and Society, London, UK
Jiangping He
Department of Geography, King's College London, London, WC2R 2ND, UK
National Centre for Earth Observation (NCEO), London, UK
Martin J. Wooster
Department of Geography, King's College London, London, WC2R 2ND, UK
Leverhulme Centre for Wildfires, Environment and Society, London, UK
National Centre for Earth Observation (NCEO), London, UK
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We examine the impact of diurnally varying African biomass burning (BB) emissions on tropospheric ozone using GEOS-Chem simulations with a high-resolution satellite-derived emission inventory. Compared to coarser temporal resolutions, incorporating diurnal variations leads to significant changes in surface ozone and atmospheric oxidation capacity. Our findings highlight the importance of accurately representing BB emission timing in chemical transport models to improve ozone predictions.
Farrer Owsley-Brown, Martin J. Wooster, Mark J. Grosvenor, and Yanan Liu
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Landscape fires produce vast amounts of smoke, affecting the atmosphere locally and globally. Whether a fire is flaming or smouldering strongly impacts the rate at which smoke is produced as well as its composition. This study tested two methods to determine these combustion phases in laboratory fires and compared them to the smoke emitted. One of these methods improved estimates of smoke emission significantly. This suggests potential for improvement in global emission estimates.
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
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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 %.
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
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Landscape fires are a substantial emitter of greenhouse gases and aerosols. Previous studies have indicated savanna emission factors to be highly variable. Improving fire emission estimates, and understanding future climate- and human-induced changes in fire regimes, requires in situ measurements. We present a drone-based method that enables the collection of a large amount of high-quality emission factor measurements that do not have the biases of aircraft or surface measurements.
Cited articles
Abel, S. J., Haywood, J. M., Highwood, E. J., Li, J., and Buseck, P. R.:
Evolution of biomass burning aerosol properties from an agricultural fire in
southern Africa, Geophys. Res. Lett., 30, 10–13,
https://doi.org/10.1029/2003GL017342, 2003.
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.
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.: Emissions of trace gases and aerosols from
biomass burning, Global Biogeochem. Cy., 15, 955–966,
https://doi.org/10.1029/2000GB001382, 2001.
Baldassarre, G., Pozzoli, L., Schmidt, C. C., Unal, A., Kindap, T., Menzel, W. P., Whitburn, S., Coheur, P.-F., Kavgaci, A., and Kaiser, J. W.: Using SEVIRI fire observations to drive smoke plumes in the CMAQ air quality model: a case study over Antalya in 2008, Atmos. Chem. Phys., 15, 8539–8558, https://doi.org/10.5194/acp-15-8539-2015, 2015.
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.
Borsdorff, T., aan de Brugh, J., Schneider, A., Lorente, A., Birk, M., Wagner, G., Kivi, R., Hase, F., Feist, D. G., Sussmann, R., Rettinger, M., Wunch, D., Warneke, T., and Landgraf, J.: Improving the TROPOMI CO data product: update of the spectroscopic database and destriping of single orbits, Atmos. Meas. Tech., 12, 5443–5455, https://doi.org/10.5194/amt-12-5443-2019, 2019.
Bowman, D. M. J. S., Balch, J. K., Artaxo, P., Bond, W. J., Carlson, J. M.,
Cochrane, M. A., D'Antonio, C. M., DeFries, R. S., Doyle, J. C., Harrison,
S. P., Johnston, F. H., Keeley, J. E., Krawchuk, M. A., Kull, C. A.,
Marston, J. B., Moritz, M. A., Prentice, I. C., Roos, C. I., Scott, A. C.,
Swetnam, T. W., van der Werf, G. R., and Pyne, S. J.: Fire in the earth
system, Science, 324, 481–484, https://doi.org/10.1126/science.1163886,
2009.
Cheng, Z., Wang, S., Fu, X., Watson, J. G., Jiang, J., Fu, Q., Chen, C., Xu, B., Yu, J., Chow, J. C., and Hao, J.: Impact of biomass burning on haze pollution in the Yangtze River delta, China: a case study in summer 2011, Atmos. Chem. Phys., 14, 4573–4585, https://doi.org/10.5194/acp-14-4573-2014, 2014.
Chevallier, F., Fortems, A., Bousquet, P., Pison, I., Szopa, S., Devaux, M., and Hauglustaine, D. A.: African CO emissions between years 2000 and 2006 as estimated from MOPITT observations, Biogeosciences, 6, 103–111, https://doi.org/10.5194/bg-6-103-2009, 2009.
Chin, M., Ginoux, P., Kinne, S., Torres, O., Holben, B., Duncan, B. N.,
Martin, R. V, Logan, J. A., Higurashi, A., and Nakajima, T.: Tropospheric
Aerosol Optical Thickness from the GOCART Model and Comparisons with
Satellite and Sun Photometer Measurements, J. Atmos. Sci., 59, 461–483,
https://doi.org/10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2,
2002.
Choi, M. W., Lee, J. H., Woo, J. W., Kim, C. H., and Lee, S. H.: Comparison
of PM2.5 chemical components over East Asia simulated by the WRF-Chem and
WRF/CMAQ models: On the models' prediction inconsistency, Atmosphere, 10, 618, https://doi.org/10.3390/atmos10100618, 2019.
Formenti, P., Elbert, W., Maenhaut, W., Haywood, J., Osborne, S., and Andreae, M. O.: Inorganic and carbonaceous aerosols during the Southern African Regional Science Initiative (SAFARI 2000) experiment: Chemical characteristics, physical properties, and emission data for smoke from African biomass burning, J. Geophys. Res., 108, 8488, https://doi.org/10.1029/2002JD002408, 2003.
Forster, P., Ramaswamy, V., Artaxo, P., Berntsen, T., Betts, R., Fahey, D.
W., Haywood, J. M., Lean, J., Lowe, D. C., Myhre, G., Nganga, J., Prinn, R.,
Raga, G., Schulz, M., and Van Dorland, R.: Changes in Atmospheric
Constituents and in Radiative Forcing (IPCC 2007), Change, 30, 129–234,
https://doi.org/10.1103/PhysRevB.77.220407, 2007.
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., 113, 1–17, https://doi.org/10.1029/2007JD008679, 2008.
Freeborn, P. H., Wooster, M. J., Roberts, G., Malamud, B. D., and Xu, W.:
Development of a virtual active fire product for Africa through a synthesis
of geostationary and polar orbiting satellite data, Remote Sens. Environ.,
113, 1700–1711, https://doi.org/10.1016/j.rse.2009.03.013, 2009.
Garcia-Menendez, F., Hu, Y., and Odman, M. T.: Science of the Total
Environment Simulating smoke transport from wildland fires with a
regional-scale air quality model: Sensitivity to spatiotemporal allocation
of fire emissions, Sci. Total Environ., 493, 544–553,
https://doi.org/10.1016/j.scitotenv.2014.05.108, 2014.
Giglio, L., Schroeder, W., and Justice, C. O.: The collection 6 MODIS active
fire detection algorithm and fire products, Remote Sens. Environ., 178,
31–41, https://doi.org/10.1016/j.rse.2016.02.054, 2016.
Hall, J. V., Zhang, R., Schroeder, W., Huang, C., and Giglio, L.: Validation
of GOES-16 ABI and MSG SEVIRI active fire products, Int. J. Appl. Earth Obs.
Geoinf., 83, 101928, https://doi.org/10.1016/j.jag.2019.101928, 2019.
Hawbaker, T. J., Vanderhoof, M. K., Beal, Y. J., Takacs, J. D., Schmidt, G.
L., Falgout, J. T., Williams, B., Fairaux, N. M., Caldwell, M. K., Picotte,
J. J., Howard, S. M., Stitt, S., and Dwyer, J. L.: Mapping burned areas using
dense time-series of Landsat data, Remote Sens. Environ., 198,
504–522, https://doi.org/10.1016/j.rse.2017.06.027, 2017.
Holben, B., Tanre, D., Smirnov, A., Eck, T. F., Slutsker, I., Abuhassan, N.,
Newcomb, W. W., Schafer, J. S., Chatenet, B., Lavenu, F., Kaufman, Y.,
Castle, J. V., Setzer, A., Markham, B., Clark, D., Frouin, R., Halthore, R.,
Karneli, A., and O'Neill, N. T.: An Emerging Ground- based Aerosol
Climatology: Aerosol Optical Depth from AERONET, J. Geophys. Res., 106,
12067–12097, 2001.
Hu, J., Chen, J., Ying, Q., and Zhang, H.: One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system, Atmos. Chem. Phys., 16, 10333–10350, https://doi.org/10.5194/acp-16-10333-2016, 2016.
Ichoku, C. and Ellison, L.: Global top-down smoke-aerosol emissions estimation using satellite fire radiative power measurements, Atmos. Chem. Phys., 14, 6643–6667, https://doi.org/10.5194/acp-14-6643-2014, 2014.
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.
Keywood, M., Kanakidou, M., Stohl, A., Dentener, F., Grassi, G., Meyer, C.
P., Torseth, K., Edwards, D., Thompson, A. M., Lohmann, U., and Burrows, J.:
Fire in the air: Biomass burning impacts in a changing climate, Crit. Rev.
Environ. Sci. Technol., 43, 40–83, https://doi.org/10.1080/10643389.2011.604248,
2013.
Kopacz, M., Jacob, D. J., Fisher, J. A., Logan, J. A., Zhang, L., Megretskaia, I. A., Yantosca, R. M., Singh, K., Henze, D. K., Burrows, J. P., Buchwitz, M., Khlystova, I., McMillan, W. W., Gille, J. C., Edwards, D. P., Eldering, A., Thouret, V., and Nedelec, P.: Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES), Atmos. Chem. Phys., 10, 855–876, https://doi.org/10.5194/acp-10-855-2010, 2010.
Koplitz, S. N., Nolte, C. G., Pouliot, G., Vukovich, J. M., and Beidler, J.:
Influence of uncertainties in burned area estimates on modeled wildland fire
PM2.5 and ozone pollution in the contiguous U.S., Atmos. Environ., 191,
328–339, https://doi.org/10.1016/j.atmosenv.2018.08.020, 2018.
Kuik, F., Lauer, A., Beukes, J. P., Van Zyl, P. G., Josipovic, M., Vakkari, V., Laakso, L., and Feig, G. T.: The anthropogenic contribution to atmospheric black carbon concentrations in southern Africa: a WRF-Chem modeling study, Atmos. Chem. Phys., 15, 8809–8830, https://doi.org/10.5194/acp-15-8809-2015, 2015.
Kukkonen, J., Olsson, T., Schultz, D. M., Baklanov, A., Klein, T., Miranda, A. I., Monteiro, A., Hirtl, M., Tarvainen, V., Boy, M., Peuch, V.-H., Poupkou, A., Kioutsioukis, I., Finardi, S., Sofiev, M., Sokhi, R., Lehtinen, K. E. J., Karatzas, K., San José, R., Astitha, M., Kallos, G., Schaap, M., Reimer, E., Jakobs, H., and Eben, K.: A review of operational, regional-scale, chemical weather forecasting models in Europe, Atmos. Chem. Phys., 12, 1–87, https://doi.org/10.5194/acp-12-1-2012, 2012.
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.
Langmann, B., Duncan, B., Textor, C., Trentmann, J., and van der Werf, G. R.:
Vegetation fire emissions and their impact on air pollution and climate,
Atmos. Environ., 43, 107–116, https://doi.org/10.1016/j.atmosenv.2008.09.047, 2009.
Lavorel, S., Flannigan, M. D., Lambin, E. F., and Scholes, M. C.:
Vulnerability of land systems to fire: Interactions among humans, climate,
the atmosphere, and ecosystems, Mitig. Adapt. Strateg. Glob. Chang., 12,
33–53, https://doi.org/10.1007/s11027-006-9046-5, 2007.
van Leeuwen, T. T., van der Werf, G. R., Hoffmann, A. A., Detmers, R. G., Rücker, G., French, N. H. F., Archibald, S., Carvalho Jr., J. A., Cook, G. D., de Groot, W. J., Hély, C., Kasischke, E. S., Kloster, S., McCarty, J. L., Pettinari, M. L., Savadogo, P., Alvarado, E. C., Boschetti, L., Manuri, S., Meyer, C. P., Siegert, F., Trollope, L. A., and Trollope, W. S. W.: Biomass burning fuel consumption rates: a field measurement database, Biogeosciences, 11, 7305–7329, https://doi.org/10.5194/bg-11-7305-2014, 2014.
Lyapustin, A., Wang, Y., Korkin, S., and Huang, D.: MODIS Collection 6 MAIAC algorithm, Atmos. Meas. Tech., 11, 5741–5765, https://doi.org/10.5194/amt-11-5741-2018, 2018.
Marengo, J. A., Tomasella, J., Alves, L. M., Soares, W. R., and Rodriguez, D.
A.: The drought of 2010 in the context of historical droughts in the Amazon
region, Geophys. Res. Lett., 38, 1–5, https://doi.org/10.1029/2011GL047436, 2011.
Mota, B. and Wooster, M. J.: A new top-down approach for directly estimating
biomass burning emissions and fuel consumption rates and totals from
geostationary satellite fire radiative power (FRP), Remote Sens.
Environ., 206, 45–62, https://doi.org/10.1016/j.rse.2017.12.016, 2018.
Nguyen, H. M. and Wooster, M. J.: Advances in the estimation of high
Spatio-temporal resolution pan-African top-down biomass burning emissions
made using geostationary fire radiative power (FRP) and MAIAC aerosol
optical depth (AOD) data, Remote Sens. Environ., 248, 111971,
https://doi.org/10.1016/j.rse.2020.111971, 2020.
Pechony, O., Shindell, D. T., and Faluvegi, G.: Direct top-down estimates of
biomass burning CO emissions using TES and MOPITT versus bottom-up GFED
inventory, J. Geophys. Res.-Atmos., 118, 8054–8066,
https://doi.org/10.1002/jgrd.50624, 2013.
Quennehen, B., Schwarzenboeck, A., Matsuki, A., Burkhart, J. F., Stohl, A., Ancellet, G., and Law, K. S.: Anthropogenic and forest fire pollution aerosol transported to the Arctic: observations from the POLARCAT-France spring campaign, Atmos. Chem. Phys., 12, 6437–6454, https://doi.org/10.5194/acp-12-6437-2012, 2012.
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.-Biogeo., 117, https://doi.org/10.1029/2012JG002128, 2012.
Reddington, C. L., Spracklen, D. V., Artaxo, P., Ridley, D. A., Rizzo, L. V., and Arana, A.: Analysis of particulate emissions from tropical biomass burning using a global aerosol model and long-term surface observations, Atmos. Chem. Phys., 16, 11083–11106, https://doi.org/10.5194/acp-16-11083-2016, 2016.
Reid, J. S., Eck, T. F., Christopher, S. A., Koppmann, R., Dubovik, O., Eleuterio, D. P., Holben, B. N., Reid, E. A., and Zhang, J.: A review of biomass burning emissions part III: intensive optical properties of biomass burning particles, Atmos. Chem. Phys., 5, 827–849, https://doi.org/10.5194/acp-5-827-2005, 2005.
Reid, J. S., Hyer, E. J., Prins, E., Westphal, D. L., Zhang, J., Wang, J.,
Christopher, S. A., Curtis, C. A., Schmidt, C. C., Eleuterio, D. P.,
Richardson, K. A., and Hoffman, J.: Global monitoring and forecasting of
biomass-burning smoke: Description of and lessons from the fire Locating and
Modeling of Burning Emissions (FLAMBE) program, IEEE J. Sel. Top. Appl.
Earth Obs. Remote Sens., 2, 144–162, https://doi.org/10.1109/JSTARS.2009.2027443,
2009.
Roberts, G., Wooster, M. J., Perry, G. L. W., Drake, N., Rebelo, L. M., and
Dipotso, F.: Retrieval of biomass combustion rates and totals from fire
radiative power observations: Application to southern Africa using
geostationary SEVIRI imagery, J. Geophys. Res.-Atmos., 110, 1–19,
https://doi.org/10.1029/2005JD006018, 2005.
Roberts, G., Wooster, M. J., Xu, W., Freeborn, P. H., Morcrette, J.-J., Jones, L., Benedetti, A., Jiangping, H., Fisher, D., and Kaiser, J. W.: LSA SAF Meteosat FRP products – Part 2: Evaluation and demonstration for use in the Copernicus Atmosphere Monitoring Service (CAMS), Atmos. Chem. Phys., 15, 13241–13267, https://doi.org/10.5194/acp-15-13241-2015, 2015.
Roberts, G., Wooster, M. J., Lauret, N., Gastellu-Etchegorry, J. P., Lynham,
T., and McRae, D.: Investigating the impact of overlying vegetation canopy
structures on fire radiative power (FRP) retrieval through simulation and
measurement, Remote Sens. Environ., 217, 158–171,
https://doi.org/10.1016/j.rse.2018.08.015, 2018.
Roteta, E., Bastarrika, A., Padilla, M., Storm, T., and Chuvieco, E.:
Development of a Sentinel-2 burned area algorithm: Generation of a small
fire database for sub-Saharan Africa, Remote Sens. Environ., 222,
1–17, https://doi.org/10.1016/j.rse.2018.12.011, 2019.
Seiler, W. and 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, https://doi.org/10.1007/BF00137988, 1980.
Tomasella, J., Pinho, P. F., Borma, L. S., Marengo, J. A., Nobre, C. A.,
Bittencourt, O. R. F. O., Prado, M. C. R., Rodriguez, D. A., and Cuartas, L.
A.: The droughts of 1997 and 2005 in Amazonia: Floodplain hydrology and its
potential ecological and human impacts, Clim. Change, 116, 723–746,
https://doi.org/10.1007/s10584-012-0508-3, 2013.
Tsela, P. L., Van Helden, P., Frost, P., Wessels, K., and Archibald, S.:
Validation of the modis burned-area products across different biomes in
South Africa, Int. Geosci. Remote Sens. Symp., Honolulu, HI, USA, 3652–3655,
https://doi.org/10.1109/IGARSS.2010.5650253, 2010.
Vermote, E., Ellicott, E., Dubovik, O., Lapyonok, T., Chin, M., Giglio, L., and Roberts, G.: An approach to estimate global biomass burning emissions of
organic and black carbon from MODIS fire radiative power, J. Geophys. Res.-Atmos., 114, 1–22, https://doi.org/10.1029/2008JD011188, 2009.
Vongruang, P., Wongwises, P., and Pimonsree, S.: Assessment of fire emission
inventories for simulating particulate matter in Upper Southeast Asia using
WRF-CMAQ, Atmos. Pollut. Res., 8, 921–929,
https://doi.org/10.1016/j.apr.2017.03.004, 2017.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Kasibhatla, P. S., and Arellano Jr., A. F.: Interannual variability in global biomass burning emissions from 1997 to 2004, Atmos. Chem. Phys., 6, 3423–3441, https://doi.org/10.5194/acp-6-3423-2006, 2006.
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.
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.
Wooster, M. J., Freeborn, P. H., Archibald, S., Oppenheimer, C., Roberts, G. J., Smith, T. E. L., Govender, N., Burton, M., and Palumbo, I.: Field determination of biomass burning emission ratios and factors via open-path FTIR spectroscopy and fire radiative power assessment: headfire, backfire and residual smouldering combustion in African savannahs, Atmos. Chem. Phys., 11, 11591–11615, https://doi.org/10.5194/acp-11-11591-2011, 2011.
Wooster, M. J., Roberts, G., Freeborn, P. H., Xu, W., Govaerts, Y., Beeby, R., He, J., Lattanzio, A., Fisher, D., and Mullen, R.: LSA SAF Meteosat FRP products – Part 1: Algorithms, product contents, and analysis, Atmos. Chem. Phys., 15, 13217–13239, https://doi.org/10.5194/acp-15-13217-2015, 2015.
Xu, W., Wooster, M. J., Roberts, G., and Freeborn, P. H.: New GOES imager
algorithms for cloud and active fire detection and fire radiative power
assessment across North, South and Central America, Remote Sens. Environ.,
114, 1876–1895, https://doi.org/10.1016/j.rse.2010.03.012, 2010.
Xu, W., Wooster, M. J., Kaneko, T., He, J., Zhang, T., and Fisher, D.: Major
advances in geostationary fire radiative power (FRP) retrieval over Asia and
Australia stemming from use of Himarawi-8 AHI, Remote Sens. Environ., 193,
138–149, https://doi.org/10.1016/j.rse.2017.02.024, 2017.
Yang, Z., Wang, J., Ichoku, C., Hyer, E. J., and Zeng, J.: Mesoscale modeling
and satellite observation of transport and mixing of smoke and dust
particles over northern sub-Saharan African region, J. Geophys. Res.-Atmos.,
118, 12139–12157, https://doi.org/10.1002/2013JD020644, 2013.
Yu, S., Eder, B., Dennis, R., Chu, S.-H., and Schwartz, S. E.: New unbiased
symmetric metrics for evaluation of air quality models, Atmos. Sci. Lett.,
7, 26–34, https://doi.org/10.1002/asl.125, 2006.
Zhang, F., Wang, J., Ichoku, C., Hyer, E. J., Yang, Z., Ge, C., Su, S.,
Zhang, X., Kondragunta, S., Kaiser, J. W., Wiedinmyer, C., and Da Silva, A.:
Sensitivity of mesoscale modeling of smoke direct radiative effect to the
emission inventory: A case study in northern sub-Saharan African region,
Environ. Res. Lett., 9, 7, https://doi.org/10.1088/1748-9326/9/7/075002, 2014.
Zhang, X., Kondragunta, S., Schmidt, C., and Kogan, F.: Near real time
monitoring of biomass burning particulate emissions (PM2.5) across
contiguous United States using multiple satellite instruments, Atmos.
Environ., 42, 6959–6972, https://doi.org/10.1016/j.atmosenv.2008.04.060, 2008.
Zheng, B., Chevallier, F., Ciais, P., Yin, Y., and Wang, Y.: On the Role of
the Flaming to Smoldering Transition in the Seasonal Cycle of African Fire
Emissions, Geophys. Res. Lett., 45, 11998–12007,
https://doi.org/10.1029/2018GL079092, 2018.
Short summary
This work presents novel advances in the estimation of open biomass burning emissions via the first fully "top-down" approach to exploit satellite-derived observations of fire radiative power and carbon monoxide over Africa. We produce a 16-year record of fire-generated CO emissions and dry matter consumed per unit area for Africa and evaluate these emissions estimates through their use in an atmospheric model, whose simulation output is then compared to independent satellite observations of CO.
This work presents novel advances in the estimation of open biomass burning emissions via the...
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