Refractory black carbon (rBC) is a primary aerosol species, produced through incomplete combustion, that absorbs sunlight and contributes to positive radiative forcing. The overall climate effect of rBC depends on its spatial distribution and atmospheric lifetime, both of which are impacted by the efficiency with which rBC is transported or removed by convective systems. These processes are poorly constrained by observations. It is especially interesting to investigate rBC transport efficiency through the Asian Summer Monsoon (ASM) since this meteorological pattern delivers vast quantities of boundary layer air from Asia, where rBC emissions are high, to the upper troposphere/lower stratosphere (UT/LS) where the lifetime of rBC is expected to be long. Here we present in-situ observations of rBC made during the Asian Summer Monsoon Chemistry and Climate Impact Project (ACCLIP) of summer, 2022. We use observed relationships between rBC and CO in ASM outflow to show that rBC is removed nearly completely (>98%) from uplifted air, and that rBC concentrations in ASM outflow are statistically indistinguishable from the UT/LS background. We compare observed rBC and CO concentrations to those expected based on two chemical transport models and find that the models reproduce CO to within a factor of 2 at all altitudes while rBC is overpredicted by a factor of 20-100 at altitudes associated with ASM outflow. We find that the rBC particles in recently convected air have thinner coatings than those found in the UTLS background, suggesting non-zero transport of rBC number that is not relevant to concentration.

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.