A new top-down approach for directly estimating biomass burning emissions and fuel consumption rates and totals from geostationary satellite fire radiative power (FRP)
A new top-down approach for directly estimating biomass burning emissions and fuel consumption rates and totals from geostationary satellite fire radiative power (FRP)
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DOI：
10.1016/j.rse.2017.12.016
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发表时间：
2018-03-01
影响因子：
13.5
通讯作者：
Wooster, Martin J.
中科院分区：
文献类型：
--
作者：
Mota, Bernardo;Wooster, Martin J.
从区域到全球范围的生物质燃烧排放清单主要是根据从卫星获得的燃烧面积或火辐射功率编制的，而且大多数依赖于在排放估计阶段之前转换成燃料消耗量。这通常被认为是引起最大不确定性的步骤，有些显然是离散的清单并不是完全独立的，因为它们已经过交叉校准，以帮助这一阶段。我们提出了一种新的排放清单的方法，绕过燃料消耗的步骤，直接联系地球静止FRP措施的总颗粒物（TPM）的排放率，通过系数来自烟羽气溶胶光学厚度（AOD）的观测。该方法是完全自上而下的，仅基于空间观测，以FRP数据的原始像素分辨率或接近于FRP数据的原始像素分辨率执行，并且避免了在排放计算之前假设或模拟每单位面积燃料消耗的需要。微量气体和碳排放的速率和总量可以从TPM通量中推断出来，并且与卫星燃烧面积（BA）产品相结合，该方法提供了一种创新的自上而下的方法来绘制每单位面积的燃料消耗（kgm（-2）），作为计算的最后一步。使用这种创新方法（我们称之为“FREemissions”（FREM）），我们根据Meteosat FRP-PIXEL数据生成了南部非洲2004-2012年火灾排放清单。我们发现，基本年平均TPM排放量比广泛使用的GFASv1.2清单高出45%，我们的较高总量与独立评估一致，需要显著提升GFAS TPM排放量以匹配观察到的AOD。我们的估计也比GFEDv4.1s高出12%，其中已经包括了对MODIS MCD 64 A1 BA产品无法检测到的小火灾的大幅上调。如果我们调整FREM衍生的排放SEVIRI的无法检测到较低的FRP组件的区域火灾制度，然后FREM和GFAS/GFED之间的差异进一步增长，以64%的平均值相对于GFED4.1的TPM排放为例。这些向上调整的FREM估计同意非常好的FEER，玻璃钢和AOD为基础的库存驱动极轨道的中分辨率成像光谱仪玻璃钢的快照，而不是地球静止观测。同样，FREM的火灾排放的痕量气体的总量也较高，这是使用气体与颗粒物的排放系数比率得出的。我们利用地球静止FRP比使用极地轨道器FRP措施需要更少的假设，避免了来自火灾昼夜周期的不完整采样的偏差，并使FREM方法能够以比目前可用的任何库存更高的时空分辨率（例如0.05度和小时平均值或更好）提供火灾排放和燃料消耗估计，包括每公里（2）燃烧面积。该方法提供了巨大的潜力，为热带，亚热带和潜在的温带地区生成非常高分辨率的火灾排放数据集，并从EUMETSAT（Meteosat），NOAA（GOES）和JMA（Himawari）等组织运营的全球地球静止气象卫星套件近实时更新。
Regional to global-scale biomass burning emissions inventories are primarily based on satellite-derived bumed area or fire radiative power (FRP), and most rely on conversions to fuel consumption prior to the emissions estimation stage. This is generally considered the step introducing greatest uncertainty, and some apparently discrete inventories are not fully independent, as they have been cross-calibrated to aid this stage. We present a novel emissions inventory approach that bypasses the fuel consumption step, directly linking geostationary FRP measures to emission rates of total particulate matter (TPM), via coefficients derived from observations of smoke plume aerosol optical depth (AOD). The approach is fully top-down', being based on spacebome observations alone, is performed at or close to the FRP data's original pixel resolution, and avoids the need to assume or model fuel consumption per unit area prior to the emissions calculation. Rates and totals of trace gas and carbon emission can be inferred from the TPM fluxes, and in combination with satellite burned area (BA) products the approach provides an innovative top down approach to mapping fuel consumption per unit area (kgm(-2)) as a last step in the calculation. Using this innovative methodology, which we term 'FREemissions' (FREM), we generate a 2004-2012 fire emissions inventory for southern Africa, based on Meteosat FRP-PIXEL data. We find basic annual average TPM emissions 45% higher than the widely used GFASv1.2 inventory, with our higher totals in line with independent assessments that necessitate a significant upscaling of GFAS TPM emissions to match observed AODs. Our estimates are also 12% higher than GFEDv4.1s, which already includes a substantial upward adjustment for fires too small to be detected by the MODIS MCD64A1 BA product. If we adjust the FREM-derived emissions for SEVIRI's inability to detect the lower FRP component of the regions fire regime then the differences between FREM and GFAS/GFED grow further, to a mean of 64% with respect to GFED4.1s TPM emissions for example. These upwardly adjusted FREM estimates agree very well with FEER, an FRP- and AOD-based inventory driven by polar-orbiting MODIS FRP 'snapshots' rather than geostationary observations. Similarly higher totals are seen for FREM's fire-emitted trace gases, derived using the emission factor ratios of gases to particulates. Our exploitation of geostationary FRP requires fewer assumptions than use of polar orbiter FRP measures, avoids biases coming from incomplete sampling of the fire diurnal cycle, and enables the FREM approach to provide fire emissions and fuel consumption estimates at a higher spatio-temporal resolution than any inventory currently available (e.g. 0.05 degrees and hourly averages or better), including per km(2) of area burned. The approach offers great potential to generate very high resolution fire emissions datasets for the tropics, sub-tropics and potentially temperate zones, with updates available in near real-time from the global suite of geostationary meteorological satellites operated by organisations such as EUMETSAT (Meteosat), NOAA (GOES) and JMA (Himawari).