Fire emissions are an important component of global models, which help; to understand the influence of sources, transport and chemistry on; atmospheric composition. Global fire emission inventories can vary; substantially due to the assumptions made in the emission creation; process, including the defined vegetation type, fire detection, fuel; loading, fraction of vegetation burned and emissions factors. Here, we; focus on the uncertainty in emission factors and the resulting impact on; modeled composition. Our study uses the Community Atmosphere Model with; chemistry (CAM-chem) to model atmospheric composition for 2014, a year; chosen for the relatively quiet El Niño Southern Oscillation activity.; We focus on carbon monoxide (CO), a trace gas emitted from incomplete; combustion and also produced from secondary oxidation of volatile; organic compounds (VOCs). Fire is a major source of atmospheric CO and; VOCs. Modeled CO from four fire emission inventories (CMIP6/GFED4s,; QFED2.5, GFAS1.2 and FINN1.5) are compared after being implemented in; CAM-chem. Multiple sensitivity tests are performed based on CO and VOC; emission factor uncertainties. We compare model output in the 14 basis; regions defined by the Global Fire Emissions Database (GFED) team and; evaluate against CO observations from the Measurements of Pollution in; the Troposphere (MOPITT) satellite-based instrument. For some regions,; emission factor uncertainty spans the results found by using different; inventories. Finally, we use modeled ozone (O3) to briefly investigate; how emission factor uncertainty influences the atmospheric oxidative; environment. Overall, accounting for emission factor uncertainty when; modeling atmospheric chemistry can lend a range of uncertainty to; simulated results.
