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

机译:六个全球生物量燃烧发射数据集:在一个全球气溶胶模型中的相互熟练和应用

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Aerosols from biomass burning (BB) emissions are poorly constrained in global and regional models, resulting in a high level of uncertainty in understanding their impacts. In this study, we compared six BB aerosol emission datasets for 2008 globally as well as in 14 regions. The six BB emission datasets are (1)?GFED3.1 (Global Fire Emissions Database version?3.1), (2)?GFED4s (GFED version?4 with small fires), (3)?FINN1.5 (FIre INventory from NCAR version?1.5), (4)?GFAS1.2 (Global Fire Assimilation System version?1.2), (5)?FEER1.0 (Fire Energetics and Emissions Research version?1.0), and (6)?QFED2.4 (Quick Fire Emissions Dataset version?2.4). The global total emission amounts from these six BB emission datasets differed by a factor of 3.8, ranging from 13.76 to 51.93Tg for organic carbon and from 1.65 to 5.54Tg for black carbon. In most of the regions, QFED2.4 and FEER1.0, which are based on satellite observations of fire radiative power (FRP) and constrained by aerosol optical depth (AOD) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), yielded higher BB aerosol emissions than the rest by a factor of 2–4. By comparison, the BB aerosol emissions estimated from GFED4s and GFED3.1, which are based on satellite burned-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 different BB emission datasets, we ingested these six BB emission datasets separately into the same global model, the NASA Goddard Earth Observing System (GEOS) model, and compared the simulated AOD with observed AOD from the AErosol RObotic 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 by smoke in September, the simulated AOD values were underestimated in almost all experiments compared to MISR, except for the QFED2.4 run in SHSA. The model-simulated AOD values based on FEER1.0 and QFED2.4 were the closest to the corresponding AERONET data, being, respectively, about 73% and 100% of the AERONET observed AOD at Alta Floresta in SHSA and about 49% and 46% at Mongu in SHAF. The simulated AOD based on the other four BB emission datasets accounted for only ~50% of the AERONET AOD at Alta Floresta and ~20% at Mongu. Overall, during the biomass burning peak seasons, at most of the selected AERONET sites in each region, the AOD values simulated with QFED2.4 were the highest and closest to AERONET and MISR observations, followed closely by FEER1.0. However, the QFED2.4 run tends to overestimate AOD in the region of SHSA, and the QFED2.4 BB emission dataset is tuned with the GEOS model. In contrast, the FEER1.0 BB emission dataset is derived in a more model-independent fashion and is more physically based since its emission coefficients are independently derived at each grid box. Therefore, we recommend the FEER1.0 BB emission dataset for aerosol-focused hindcast experiments in the two biomass-burning-dominated regions in the Southern Hemisphere, SHAF, and SHSA (as well as in other regions but with lower confidence). The differences between these six BB emission datasets are attributable to the approaches and input data used to derive BB emissions, such as whether AOD from satellite observations is used as a constraint, whether the approaches to parameterize the fire activities are based on burned area, FRP, or active fire count, and which set of emission factors is chosen.
机译:生物量燃烧(BB)排放的气溶胶在全球和区域模型中受到严重限制,导致了解其影响的高度不确定性。在这项研究中,我们将2008年的六个BB气溶胶排放数据集与全球以及14个区域进行了比较。六个BB发射数据集是(1)?GFED3.1(全球火灾排放数据库版本?3.1),(2)?GFED4S(GFED版本?4带小型火灾),(3)?FINN1.5(来自NCAR的Fire Inventory)版本?1.5),(4)?GFAS1.2(全球防火系统版本?1.2),(5)?FEER1.0(消防能量和排放研究版本?1.0),和(6)?QFED2.4(快速消防排放数据集版?2.4)。来自这六个BB发射数据集的全局总排放量不同于3.8倍,有机碳的13.76至51.93Tg,黑碳的1.65至5.54tg。在大多数区域,QFED2.4和FEER1.0基于卫星观察的火辐射功率(FRP)并由来自中等分辨率成像光谱辐射器(MODIS)的气溶胶光学深度(AOD)数据约束,产生更高的BB气溶胶排放比其余的排放量为2-4倍。相比之下,由GFED4S和GFED3.1估计的BB气溶胶排放,其基于卫星烧毁区域数据而没有AOD约束,在该范围的低端。为了检查模型模拟AOD到不同BB发射数据集的灵敏度,我们将这六个BB发射数据集分别摄入到相同的全球模型中,NASA戈达德地球观察系统(Geos)模型,并将模拟AOD与观察到的模拟AOD在2008年期间的14个地区的气溶胶机器人网络(AERONET)和多元成像光谱仪(MISR)。在南半球非洲(SHAF)和南美洲(SHSA),气溶胶往往在9月份被烟雾明确占主导地位,除了SHSA中的QFED2.4之外,与MISR相比,几乎所有实验都低估了模拟AOD值。基于FEER1.0和QFED2.4的模型模拟AOD值是最接近相应的AERONET数据,分别为73%,在SHSA的ALTA Floresta观察AOD的73%和100%,约为49%和46在南部的百年百分比。基于其他四个BB排放数据集的模拟AOD占ALTA Floresta的AeroNet Aod的〜50%,在旺湖〜20%。总体而言,在生物量燃烧峰值季节,在每个区域的大多数选择的AeroNet位点,用QFED2.4模拟的AOD值是最高和最接近的AeroNet和Misr观察,接下来是FEER1.0。但是,QFED2.4 RUN倾向于高估SHSA区域的AOD,并且通过GEOS模型调整QFED2.4 BB发射数据集。相反,FEER1.0 BB发射数据集以更独立的方式导出,并且由于其发射系数在每个网格箱上独立地导出,因此更为基于物理上。因此,我们建议FEER1.0 BB发射数据集在南半球,SHAF和SHSA(以及其他地区)的两种生物量燃烧的地区的两个生物质燃烧主导地区中的雾化的Hindcast实验。这六个BB发射数据集之间的差异可归因于用于导出BB排放的方法和输入数据,例如来自卫星观察的AOD作为约束,是否参数化防火活动的方法是基于烧毁区域,FRP或者主动火数,以及选择哪一组排放因子。

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