During the record-breaking 2023 Canadian wildfire season, extreme drought exposed normally saturated peatlands and deep organic soils to high-severity combustion, revealing underestimations in the top-down emissions inventories used by flagship operational systems, such as HRRR-Smoke and the upcoming RRFS-Smoke. While these systems captured smoke transport pathways well, they underestimated smoke PM2.5 concentrations across North America. Using high-resolution geospatial masks, we isolate regions dominated by organic soils and permanent wetlands and then update both the emission factors (EFs) and the biomass combustion coefficient (𝛽), which is used to convert Fire Radiative Energy (FRE) into total biomass consumed. We test two 𝛽 formulations: one based on land-use-dependent values from published literature and another ecosystem-dependent 𝛽 derived by calibrating NOAA’s Regional ABI and VIIRS fire Emission product (RAVE) FRP against total biomass consumption estimates from the bottom-up Global Fire Emissions Database (GFED5.1). Initial RRFS-Smoke simulations using these adjusted coefficients show a substantial increase in smoke emission estimates for fires influenced by organic-soil combustion. This update significantly reduces the low model biases observed during the 2023 season and brings model output into closer agreement with surface observations. These improvements address a low bias likely resulting from limitations in satellite-derived Fire Radiative Power (FRP) to detect weak smoldering signals from newly vulnerable carbon reservoirs, as well as retrieval uncertainty under the dense smoke conditions of 2023.