Articles | Volume 24, issue 11
https://doi.org/10.5194/acp-24-6787-2024
https://doi.org/10.5194/acp-24-6787-2024
Research article
 | 
12 Jun 2024
Research article |  | 12 Jun 2024

Diagnosing uncertainties in global biomass burning emission inventories and their impact on modeled air pollutants

Wenxuan Hua, Sijia Lou, Xin Huang, Lian Xue, Ke Ding, Zilin Wang, and Aijun Ding

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Cited articles

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. 
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. 
Alencar, A., Nepstad, D., and Moutinho, P.: Carbon emissions associated with forest fires in Brazil, in: Tropical Deforestation and Climate Change, IPAM: Belém, Portugal, p. 23, 2005. 
Andreae, M. and Rosenfeld, D.: Aerosol–cloud–precipitation interactions. Part 1. The nature and sources of cloud-active aerosols, Earth-Sci. Rev., 89, 13–41, 2008. 
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Short summary
In this study, we diagnose uncertainties in carbon monoxide and organic carbon emissions from four inventories for seven major wildfire-prone regions. Uncertainties in vegetation classification methods, fire detection products, and cloud obscuration effects lead to bias in these biomass burning (BB) emission inventories. By comparing simulations with measurements, we provide certain inventory recommendations. Our study has implications for reducing uncertainties in emissions in further studies.
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