Reconciling Assumptions in Bottom‐Up and Top‐Down Approaches for Estimating Aerosol Emission Rates From Wildland Fires Using Observations From FIREX‐AQ. Issue 24 (10th December 2021) - Wiggins, E. B.; Anderson, B. E.; Brown, M. D.; Campuzano‐Jost, P.; Chen, G.; Crawford, J.; Crosbie, E. C.; Dibb, J.; DiGangi, J. P.; Diskin, G. S.; Fenn, M.; Gallo, F.; et al.
Abstract: Accurate fire emissions inventories are crucial to predict the impacts of wildland fires on air quality and atmospheric composition. Two traditional approaches are widely used to calculate fire emissions: a satellite‐based top‐down approach and a fuels‐based bottom‐up approach. However, these methods often considerably disagree on the amount of particulate mass emitted from fires. Previously available observational datasets tended to be sparse, and lacked the statistics needed to resolve these methodological discrepancies. Here, we leverage the extensive and comprehensive airborne in situ and remote sensing measurements of smoke plumes from the recent Fire Influence on Regional to Global Environments and Air Quality (FIREX‐AQ) campaign to statistically assess the skill of the two traditional approaches. We use detailed campaign observations to calculate and compare emission rates at an exceptionally high‐resolution using three separate approaches: top‐down, bottom‐up, and a novel approach based entirely on integrated airborne in situ measurements. We then compute the daily average of these high‐resolution estimates and compare with estimates from lower resolution, global top‐down and bottom‐up inventories. We uncover strong, linear relationships between all of the high‐resolution emission rate estimates in aggregate, however no single approach is capable of capturing the emission characteristics of every fire. Global inventory emission rate estimates exhibited weaker correlations with the high‐resolution approaches and displayed evidence of systematic bias. The disparity between the low‐resolution global inventories and the high‐resolution approaches is likely caused by high levels of uncertainty in essential variables used in bottom‐up inventories and imperfect assumptions in top‐down inventories. Plain Language Summary: Smoke emitted by wildland fires is dangerous to human health and contributes to climate change. To predict and evaluate the impacts of fires, we need to know how much smoke is emitted into the atmosphere. There are two state‐of‐the‐art methods used to estimate the mass of smoke emitted by fires, but they often disagree. In this study, we use unusually detailed measurements collected using an aircraft that flew within wildland fire smoke plumes to calculate the amount of smoke emitted from fires in the Western United States. We compare emission rates derived from the exceptionally high spatial and temporal resolution approach to the two traditional, lower resolution approaches to understand why they sometimes diverge. Key Points: In situ measurements of wildland fire smoke plumes provide emission rates for evaluating emissions inventories at unprecedented resolution Fire emissions inventories struggle to capture the emissions rate characteristics of individual fires but may perform well in the aggregate Bottom‐up inventories suffer from major uncertainty in key variables, while top‐down inventories may have bias from imperfect assumptions