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

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.

Photochemical model evaluation of 2013 California wild fire air quality impacts using surface, aircraft, and satellite data.

The Rim Fire was one of the largest wildfires in California history, burning over 250,000 acres during August and September 2013 affecting air quality locally and regionally in the western U.S. Routine surface monitors, remotely sensed data, and aircraft based measurements were used to assess how well the Community Multiscale Air Quality (CMAQ) photochemical grid model applied at 4 and 12 km resolution represented regional plume transport and chemical evolution during this extreme wildland fire episode. Impacts were generally similar at both grid resolutions although notable differences were seen in some secondary pollutants (e.g., formaldehyde and peroxyacyl nitrate) near the Rim fire. The modeling system does well at capturing near-fire to regional scale smoke plume transport compared to remotely sensed aerosol optical depth (AOD) and aircraft transect measurements. Plume rise for the Rim fire was well characterized as the modeled plume top was consistent with remotely sensed data and the altitude of aircraft measurements, which were typically made at the top edge of the plume. Aircraft-based lidar suggests O3 downwind in the Rim fire plume was vertically stratified and tended to be higher at the plume top, while CMAQ estimated a more uniformly mixed column of O3. Predicted wildfire ozone (O3) was overestimated both at the plume top and at nearby rural and urban surface monitors. Photolysis rates were well characterized by the model compared with aircraft measurements meaning aerosol attenuation was reasonably estimated and unlikely contributing to O3 overestimates at the top of the plume. Organic carbon was underestimated close to the Rim fire compared to aircraft data, but was consistent with nearby surface measurements. Periods of elevated surface PM2.5 at rural monitors near the Rim fire were not usually coincident with elevated O3.