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

Data sets

MOPITT CO gridded monthly means (Near and Thermal Infrared Radiances) V009 NASA/LARC/SD/ASDC https://doi.org/10.5067/TERRA/MOPITT/MOP03JM.009

Download
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.
Altmetrics
Final-revised paper
Preprint