Advances in the estimation of high Spatio-temporal resolution pan-African top-down biomass burning emissions made using geostationary fire radiative power (FRP) and MAIAC aerosol optical depth (AOD) data
Advances in the estimation of high Spatio-temporal resolution pan-African top-down biomass burning emissions made using geostationary fire radiative power (FRP) and MAIAC aerosol optical depth (AOD) data
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DOI：
10.1016/j.rse.2020.111971
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发表时间：
2020-10
影响因子：
13.5
通讯作者：
Hannah M. Nguyen;M. Wooster
中科院分区：
文献类型：
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作者：
Hannah M. Nguyen;M. Wooster
我们对生物质燃烧排放计算的“自上而下”的火灾辐射能排放(FREM)方法进行了重大更新，绕过了燃料消耗的估计，燃料消耗是广泛使用的“自下而上”方法中的一个主要不确定性来源。FREM方法通过空间变化的烟雾发射系数(例如MJ−1)将卫星观测的火焰辐射功率与总颗粒物的发射率联系起来-每个系数都是从火焰辐射功率和烟羽气溶胶光学厚度(AoD)的匹配得出的。在最初的FREMv1方法中，FRP数据来自地球静止气象卫星，AOD数据来自10公里空间分辨率MODIS MOD04气溶胶产品。然而，后者往往表现得相当差，接近生物质燃烧源，因为它的大10千米像素，在高MODIS视角天顶角的偏差，以及饱和和/或去除高AOD限制的区域，为FREM得出的最终烟雾排放估计带来了偏差和不确定性。我们通过一系列重大的方法和输入数据改进来解决这些问题，包括开发1公里的MODIS MAIAC AOD产品，该产品在靠近火源的地方表现要好得多。我们使用我们的FREMv2方法为TPM和碳质气体CO2、CO和CH4生成了一个新的泛非火灾排放清单，我们的年平均TPM排放量不到基于MODIS的FEER自上而下方法的11%，但显著高于GFASv1.2和GFEDv4.1s(分别增加114%和69%)-与独立评估一致，即GFASv1.2的气溶胶排放需要提高2到3.4倍，才能在模拟和观测的AOD之间提供匹配的量级。根据我们的碳排放总量，我们绘制了整个非洲的干物质消耗量地图，并将其除以FireCCISFD11 20米燃烧面积产品，我们提供了首批数据驱动的单位面积燃料消耗泛非地图之一(Kg.m−2)，该地图在许多地区高于GFEDv4.1。我们的估计代表了非洲现有的最高时空分辨率的生物质燃烧排放数据，大大推进了基于全球地球同步卫星网络(气象卫星、气象卫星IOD、GOES和Himawa)的FRP进行泛热带和中纬度清查的目标。
We provide major updates to the ‘top down’ Fire Radiative Energy Emissions (FREM) approach to biomass burning emissions calculations, bypassing the estimation of fuel consumption that is a major source of uncertainty in widely used ‘bottom up’ approaches. The FREM approach links satellite observations of fire radiative power (FRP) to emission rates of total particulate matter (TPM) via spatially varying smoke emissions coefficients (g.MJ−1) – each derived from matchups of FRP and smoke plume aerosol optical depth (AOD). In the original FREMv1 approach, FRP data came from the geostationary Meteosat satellite and AOD data from the 10 km spatial resolution MODIS MOD04 aerosol product. However, the latter often performs quite poorly close to biomass burning sources due to its large 10 km pixels, bias at high MODIS view zenith angles, and saturation and/or removal of areas of high AOD - limitations introducing bias and uncertainty into the final FREM-derived smoke emissions estimates. We address each of these issues through a series of significant methodological and input data improvements, including exploitation of the 1 km MODIS MAIAC AOD product that performs far better close to fire sources. We use our FREMv2 methodology to generate a new pan-African fire emissions inventory for TPM and the carbonaceous gases CO2, CO and CH4, and our annual mean TPM emissions are within 11% of those of the MODIS-based FEER top-down approach, but significantly higher than those of GFASv1.2 and GFEDv4.1s (by 114% and 69% respectively) - agreeing with independent assessments that aerosol emissions of GFASv1.2 require upscaling by a factor of 2 to 3.4 to deliver matching magnitudes between modelled and observed AODs. From our carbonaceous emissions totals we map dry matter consumed (DMC) across Africa, and dividing this by the FireCCISFD11 20 m burned area product we provide one of the first data-driven pan-African maps of fuel consumption per unit area (kg.m−2) which in many areas is higher than in GFEDv4.1s. Our estimates represent the highest spatio-temporal resolution biomass burning emissions data yet available over Africa, and significantly advance the aim of a pan-tropical and mid-latitude inventory based on FRP from the global geostationary satellite network (Meteosat, Meteosat IOD, GOES and Himawari).