Reconciling Assumptions in Bottom‐Up and Top‐Down Approaches for Estimating Aerosol Emission Rates From Wildland Fires Using Observations From FIREX‐AQ

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.

Fire Influence on Regional to Global Environments and Air Quality (FIREX‐AQ)

“…To more fully evaluate Fuel2Fire estimated emissions versus emission fluxes based on airborne observations, HSRL lidar data were necessary to extrapolate in situ observations across the full cross section of the plume at each downwind distance in combination with transport speeds based on wind observations. Two independent emissions assessments based on DC-8 observations were conducted by Wiggins et al (2021) and Stockwell et al (2022).…”

Assessing Vertical Allocation of Wildfire Smoke Emissions Using Observational Constraints From Airborne Lidar in the Western U.S.

“…Fuel2Fire is developed specifically for the FIREX‐AQ fire events, and the data is publicly available on the FIREX‐AQ data archive under the analysis tab ( https://www-air.larc.nasa.gov/cgi-bin/ArcView/firexaq?ANALYSIS=1#SOJA.AMBER/ ). Fuel2Fire data has been used to intercompare with and validate fire emissions derived from other methods (Stockwell et al., 2022 ; Wiggins et al., 2021 ). The daily burned area is derived using a combination of satellite active fire detections from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite.…”

“…The daily burned area is derived using a combination of satellite active fire detections from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite. Active fire pixels from these products are selected to best match ground‐verified interagency situational reports from fire management teams, as well as Geospatial Multi‐Agency Coordination (GeoMAC) fire perimeters (Wiggins et al., 2021 ). The daily QFED total emissions are spatially reallocated according to the re‐mapped burned area onto the model grid.…”

“…However, the hourly distribution represented by the commonly used temporal patterns prescribed in smoke and air quality models can often differ from actual fire behavior (Ye et al., 2021 ). Thus, we temporally re‐distribute the daily emissions using hourly diurnal patterns obtained also from the Fuel2Fire data, which are estimated using the FRP from geostationary satellite sensors, that is, the Advanced Baseline Instruments on both Geostationary Operational Environmental Satellites −16 and −17 (Schmidt, 2019 ; Schmidt et al., 2013 ), available at every 5 min and nominal spatial resolution of 2 km at nadir (Wiggins et al., 2021 ). A comparison of the emission time series for the Williams Flats fire before and after the temporal redistribution is shown in Figure S1 in Supporting Information S1 .…”

“…In contrast, airborne lidars provide measurements through specific smoke plumes of interest with exceptional temporal and spatial resolutions. The NASA Langley Research Center (LaRC) airborne Differential Absorption and High Spectral Resolution Lidar high spectral resolution lidar (DIAL‐HSRL; Hair et al., 2018 ) has been providing measurements suitable for characterizing the structure of aerosol layers over recent decades, which are used in many perspectives, for example, the evaluations of modeled wildfire plumes (Saide et al., 2015 ; Ye et al., 2021 ), aerosol layer structures (Fast et al., 2016 ), and the quantification of smoke emissions (Stockwell et al., 2022 ; Wiggins et al., 2021 ).…”