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The western U.S. wildfire smoke plumes observed by the upward-pointing Wyoming Cloud Lidar (WCL) during the Biomass Burning Fluxes of Trace Gases and Aerosols (BB-FLUX) project are investigated in a two-part paper. Part II here presents the reconstructed vertical structures of seven plumes from airborne WCL measurements. The vertical structures evident in the fire plume cross sections, supported by in situ measurements, showed that the fire plumes had distinct macrophysical and microphysical properties, which are closely related to the plume transport, fire emission intensity, and thermodynamic structure in the boundary layer. All plumes had an injection layer between 2.8 and 4.0 km above mean sea level, which is generally below the identified boundary layer top height. Plumes that transported upward out of the boundary layer, such as the Rabbit Foot and Pole Creek fires, formed a higher plume at around 5.5 km. The largest and highest Pole Creek fire plume was transported farthest and was sampled by University of Wyoming King Air aircraft at 170 km, or 2.3 h, downwind. It was associated with the warmest, driest, deepest boundary layer and the highest wind speed and turbulence. The Watson Creek fire plume intensified in the afternoon with stronger CO emission and larger smoke plume height than in the morning, indicating a fire diurnal cycle, but some fire plumes did not intensify in the afternoon. There were pockets of relatively large irregular aerosol particles at the tops of plumes from active fires. In less-active fire plumes, the WCL depolarization ratio and passive cavity aerosol spectrometer probe mass mean diameter maximized at a height that was low in the plume.

 

Characterizing pre‐fire fuel load and fuel consumption are critical for assessing fire behavior, fire effects, and smoke emissions. Two approaches for quantifying fuel load are airborne laser scanning (ALS) and the Fuel Characteristic Classification System (FCCS). The implementation of multitemporal ALS (i.e., the use of two or more ALS datasets across time at a given location) in conjunction with empirical models trained with field data can be used to measure fuel and estimate fuel consumption from a fire. FCCS, adapted for use in LANDFIRE (LF), provides 30 m resolution estimates of fuel load across the contiguous United States and can be used to estimate fuel consumption through software programs such as Fuel and Fire Tools (FFT). This study compares the two approaches for two wildfires in the northwestern United States having predominantly sagebrush steppe and ponderosa pine savanna ecosystems. The results showed that the LF FCCS approach yielded higher pre‐fire fuel loads and fuel consumption than the ALS approach and that the coarser scale LF FCCS data did not capture as much heterogeneity as the ALS data. At Tepee, 50.0% of the difference in fuel load and 87.3% of the difference in fuel consumption were associated with distinguishing sparse trees from rangeland. At Keithly, this only accounted for 8.2% and 8.6% of the differences, demonstrating the significance of capturing heterogeneity in rangeland vegetation structure and fire effects. Our results suggest future opportunities to use ALS data to better parametrize fine‐scale fuel load variability that LF FCCS does not capture.

 

During the summer of 2018, the upward-pointing Wyoming Cloud Lidar (WCL) was deployed on board the University of Wyoming King Air (UWKA) research aircraft for the Biomass Burning Flux Measurements of Trace Gases and Aerosols (BB-FLUX) field campaign. This paper describes the generation of calibrated attenuated backscatter coefficients and aerosol extinction coefficients from the WCL measurements. The retrieved aerosol extinction coefficients at the flight level strongly correlate (correlation coefficient, rr > 0.8) with in situ aerosol concentration and carbon monoxide (CO) concentration, providing a first-order estimate for converting WCL extinction coefficients into vertically resolved CO and aerosol concentration within wildfire smoke plumes. The integrated CO column concentrations from the WCL data in nonextinguished profiles also correlate (rr = 0.7) with column measurements by the University of Colorado Airborne Solar Occultation Flux instrument, indicating the validity of WCL-derived extinction coefficients. During BB-FLUX, the UWKA sampled smoke plumes from more than 20 wildfires during 35 flights over the western United States. Seventy percent of flight time was spent below 3 km above ground level (AGL) altitude, although the UWKA ascended up to 6 km AGL to sample the top of some deep smoke plumes. The upward-pointing WCL observed a nearly equal amount of thin and dense smoke below 2 km and above 5 km due to the flight purpose of targeted fresh fire smoke. Between 2 and 5 km, where most of the wildfire smoke resided, the WCL observed slightly more thin smoke than dense smoke due to smoke spreading. Extinction coefficients in dense smoke were 2–10 times stronger, and dense smoke tended to have larger depolarization ratio, associated with irregular aerosol particles.

 

Abstract. Smoke from wildfires is a significant source of air pollution, which can adversely impact air quality and ecosystems downwind. With the recently increasing intensity and severity of wildfires, the threat to air quality is expected to increase. Satellite-derived biomass burning emissions can fill in gaps in the absence of aircraft or ground-based measurement campaigns and can help improve the online calculation of biomass burning emissions as well as the biomass burning emissions inventories that feed air quality models. This study focuses on satellite-derived NOx emissions using the high-spatial-resolution TROPOspheric Monitoring Instrument (TROPOMI) NO2 dataset. Advancements and improvements to the satellite-based determination of forest fire NOx emissions are discussed, including information on plume height and effects of aerosol scattering and absorption on the satellite-retrieved vertical column densities. Two common top-down emission estimation methods, (1) an exponentially modified Gaussian (EMG) and (2) a flux method, are applied to synthetic data to determine the accuracy and the sensitivity to different parameters, including wind fields, satellite sampling, noise, lifetime, and plume spread. These tests show that emissions can be accurately estimated from single TROPOMI overpasses.The effect of smoke aerosols on TROPOMI NO2 columns (via air mass factors, AMFs) is estimated, and these satellite columns and emission estimates are compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America. Our results indicate that applying an explicit aerosol correction to the TROPOMI NO2 columns improves the agreement with the aircraft observations (by about 10 %–25 %). The aircraft- and satellite-derived emissions are in good agreement within the uncertainties. Both top-down emissions methods work well; however, the EMG method seems to output more consistent results and has better agreement with the aircraft-derived emissions. Assuming a Gaussian plume shape for various biomass burning plumes, we estimate an average NOx e-folding time of 2 ±1 h from TROPOMI observations. Based on chemistry transport model simulations and aircraft observations, the net emissions of NOx are 1.3 to 1.5 times greater than the satellite-derived NO2 emissions. A correction factor of 1.3 to 1.5 should thus be used to infer net NOx emissions from the satellite retrievals of NO2.