Smoke emissions from wildland fires contribute to concentrations of atmospheric particulate matter and greenhouse gases, influencing public health and climate. Prediction of emissions is critical for smoke management to mitigate the effects on visibility and air quality. Models that predict emissions require estimates of the amount of combustible biomass. When measurements are unavailable, fuel maps may be used to define the inputs for models. Mapped products are based on averages that poorly represent the inherent variability of wildland fuels, but that variability is an important source of uncertainty in predicting emissions. We evaluated the sensitivity of emissions estimates to wildland fuel biomass variability using two models commonly used to predict emissions: Consume and the First Order Fire Effects Model (FOFEM). Flaming emissions were consistently most sensitive to litter loading (Sobol index 0.426–0.742). Smouldering emissions were most often sensitive to duff loading (Sobol 0.655–0.704) under the extreme environmental scenario. Under the moderate environmental scenario, FOFEM-predicted smouldering emissions were similarly sensitive to sound and rotten coarse woody debris (CWD) and duff fuel components (Sobol 0.193–0.376). High variability in loading propagated to wide prediction intervals for emissions. Direct measurements of litter, duff and coarse wood should be prioritised to reduce overall uncertainty.

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量化可燃生物量的不确定性来源如何传播到预测野火排放

野火产生的烟雾会增加大气颗粒物和温室气体的浓度，从而影响公共健康和气候。排放量预测对于烟雾管理至关重要，以减轻对能见度和空气质量的影响。预测排放的模型需要估计可燃生物量的数量。当测量不可用时，燃料图可用于定义模型的输入。映射产品基于平均值，不能很好地代表荒地燃料的固有可变性，但这种可变性是预测排放量的重要不确定性来源。我们使用两种常用来预测排放的模型来评估排放估计对荒地燃料生物量变异性的敏感性：消耗和一阶火灾效应模型 (FOFEM)。火焰排放始终对垫料负荷最敏感（Sobol 指数 0.426–0.742）。在极端环境情景下，阴燃排放最常对达夫载荷（Sobol 0.655-0.704）敏感。在温和的环境情景下，FOFEM 预测的阴燃排放对声音和腐烂的粗木屑 (CWD) 和 duff 燃料成分 (Sobol 0.193–0.376) 同样敏感。负载的高度可变性传播到排放的宽预测区间。应优先直接测量枯枝落叶、碎木和粗木，以减少整体不确定性。FOFEM 预测的阴燃排放物对声音和腐烂的粗木屑 (CWD) 和 duff 燃料成分 (Sobol 0.193–0.376) 同样敏感。负载的高度可变性传播到排放的宽预测区间。应优先直接测量枯枝落叶、碎木和粗木，以减少整体不确定性。FOFEM 预测的阴燃排放物对声音和腐烂的粗木屑 (CWD) 和 duff 燃料成分 (Sobol 0.193–0.376) 同样敏感。负载的高度可变性传播到排放的宽预测区间。应优先直接测量枯枝落叶、碎木和粗木，以减少整体不确定性。