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. Aerosols from biomass burning (BB) emissions are poorly constrained inglobal and regional models, resulting in a high level of uncertainty inunderstanding their impacts. In this study, we compared six BB aerosolemission datasets for 2008 globally as well as in 14 regions. The six BBemission datasets are (1) GFED3.1 (Global Fire Emissions Database version 3.1), (2) GFED4s (GFED version 4 with small fires), (3) FINN1.5 (FIreINventory from NCAR version 1.5), (4) GFAS1.2 (Global Fire AssimilationSystem version 1.2), (5) FEER1.0 (Fire Energetics and Emissions Researchversion 1.0), and (6) QFED2.4 (Quick Fire Emissions Dataset version 2.4).The global total emission amounts from these six BB emission datasetsdiffered by a factor of 3.8, ranging from 13.76 to 51.93 Tg for organiccarbon and from 1.65 to 5.54 Tg for black carbon. In most of the regions,QFED2.4 and FEER1.0, which are based on satellite observations of fireradiative power (FRP) and constrained by aerosol optical depth (AOD) datafrom the Moderate Resolution Imaging Spectroradiometer (MODIS), yieldedhigher BB aerosol emissions than the rest by a factor of 2–4. By comparison, the BBaerosol emissions estimated from GFED4s and GFED3.1, which are based on satelliteburned-area data, without AOD constraints, were at the low end of the range.In order to examine the sensitivity of model-simulated AOD to the differentBB emission datasets, we ingested these six BB emission datasets separatelyinto the same global model, the NASA Goddard Earth Observing System (GEOS)model, and compared the simulated AOD with observed AOD from the AErosolRObotic NETwork (AERONET) and the Multiangle Imaging SpectroRadiometer(MISR) in the 14 regions during 2008. In Southern Hemisphere Africa (SHAF)and South America (SHSA), where aerosols tend to be clearly dominated bysmoke in September, the simulated AOD values were underestimated in almost allexperiments compared to MISR, except for the QFED2.4 run in SHSA. Themodel-simulated AOD values based on FEER1.0 and QFED2.4 were the closest to thecorresponding AERONET data, being, respectively, about 73 % and 100 % ofthe AERONET observed AOD at Alta Floresta in SHSA and about 49 % and46 % at Mongu in SHAF. The simulated AOD based on the other four BBemission datasets accounted for only ∼50  % of the AERONETAOD at Alta Floresta and ∼20  % at Mongu. Overall, duringthe biomass burning peak seasons, at most of the selected AERONET sites ineach region, the AOD values simulated with QFED2.4 were the highest and closest toAERONET and MISR observations, followed closely by FEER1.0. However, theQFED2.4 run tends to overestimate AOD in the region of SHSA, and the QFED2.4BB emission dataset is tuned with the GEOS model. In contrast, the FEER1.0BB emission dataset is derived in a more model-independent fashion and ismore physically based since its emission coefficients are independentlyderived at each grid box. Therefore, we recommend the FEER1.0 BB emissiondataset for aerosol-focused hindcast experiments in the two biomass-burning-dominated regions in the Southern Hemisphere, SHAF, and SHSA (as well as inother regions but with lower confidence). The differences between these sixBB emission datasets are attributable to the approaches and input data usedto derive BB emissions, such as whether AOD from satellite observations isused as a constraint, whether the approaches to parameterize the fireactivities are based on burned area, FRP, or active fire count, and whichset of emission factors is chosen.

Six global biomass burning emission datasets: intercomparison and application in one global aerosol model