Abstract Regional to global-scale biomass burning emissions inventories are primarily based on satellite-derived burned 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 spaceborne 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 (kg·m− 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°, and hourly averages or better), including per km2 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).

中文翻译：

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一种新的自上而下的方法，用于直接估算地球同步卫星火辐射功率 (FRP) 的生物质燃烧排放和燃料消耗率以及总量

摘要 区域到全球范围的生物质燃烧排放清单主要基于卫星衍生的燃烧面积或火辐射功率 (FRP)，并且大多数依赖于排放估算阶段之前的燃料消耗转换。这通常被认为是引入最大不确定性的步骤，并且一些明显离散的清单并非完全独立，因为它们已被交叉校准以帮助此阶段。我们提出了一种绕过燃料消耗步骤的新型排放清单方法，通过从烟羽气溶胶光学深度 (AOD) 观察得出的系数，直接将地球静止 FRP 测量与总颗粒物 (TPM) 的排放率联系起来。该方法完全是“自上而下”的，仅基于星载观测，在 FRP 数据处或接近 FRP 数据处执行 s 原始像素分辨率，并避免在排放计算之前假设或模拟每单位面积的燃料消耗。痕量气体和碳排放的比率和总量可以从 TPM 通量中推断出来，并结合卫星燃烧面积 (BA) 产品，该方法提供了一种创新的自上而下的方法来绘制单位面积的燃料消耗 (kg·m− 2)作为计算的最后一步。使用这种我们称为“FREemissions”（FREM）的创新方法，我们根据 Meteosat FRP-PIXEL 数据生成了 2004-2012 年南部非洲的火灾排放清单。我们发现基本年平均 TPM 排放量比广泛使用的 GFASv1.2 清单高 45%，我们更高的总量符合独立评估，需要显着增加 GFAS TPM 排放量以匹配观察到的 AOD。我们的估计也比 GFEDv4.1s 高 12%，GFEDv4.1s 已经包括对 MODIS MCD64A1 BA 产品检测到的小火的大幅向上调整。如果我们因 SEVIRI 无法检测到区域火灾状况的较低 FRP 成分而调整 FREM 衍生的排放，那么 FREM 和 GFAS/GFED 之间的差异会进一步扩大，例如就 GFED4.1s TPM 排放而言，平均为 64% . 这些向上调整的 FREM 估计与 FEER 非常吻合，FEER 是一种基于 FRP 和 AOD 的清单，由极地轨道 MODIS FRP“快照”而不是地球静止观测驱动。类似地，FREM 火灾排放的痕量气体的总量也更高，这是使用气体与颗粒物的排放因子比得出的。与使用极地轨道飞行器 FRP 测量相比，我们对地球静止 FRP 的开发需要更少的假设，避免来自不完整的火灾昼夜循环采样的偏差，并使 FREM 方法能够以比任何方法都更高的时空分辨率提供火灾排放和燃料消耗估计。当前可用的清单（例如 0.05°，每小时平均值或更好），包括每平方公里的燃烧面积。该方法具有为热带、亚热带和潜在温带地区生成超高分辨率火灾排放数据集的巨大潜力，并且可以从 EUMETSAT (Meteosat) 等组织运营的全球地球静止气象卫星套件中近乎实时地提供更新, NOAA (GOES) 和 JMA (Himawari)。并使 FREM 方法能够以比当前可用的任何清单（例如 0.05°，每小时平均值或更好）更高的时空分辨率提供火灾排放和燃料消耗估计，包括每平方公里燃烧面积。该方法具有为热带、亚热带和潜在温带地区生成超高分辨率火灾排放数据集的巨大潜力，并且可以从 EUMETSAT (Meteosat) 等组织运营的全球地球静止气象卫星套件中近乎实时地提供更新, NOAA (GOES) 和 JMA (Himawari)。并使 FREM 方法能够以比当前可用的任何清单（例如 0.05°，每小时平均值或更好）更高的时空分辨率提供火灾排放和燃料消耗估计，包括每平方公里燃烧面积。该方法具有为热带、亚热带和潜在温带地区生成超高分辨率火灾排放数据集的巨大潜力，并且可以从 EUMETSAT (Meteosat) 等组织运营的全球地球静止气象卫星套件中近乎实时地提供更新, NOAA (GOES) 和 JMA (Himawari)。