Constraining Modeled Emissions and Transformation of Light-absorbing Organic Aerosols from Wildfires Using In Situ and Space-borne Measurements

Wildfires are a major source of primary carbonaceous aerosol particles and volatile organic compounds (VOCs) that can form secondary particulate matters. Light-absorbing carbonaceous particles, namely black carbon (BC) and light-absorbing organic carbon (LAOC), interact with radiation across a wide range of solar spectrum. In particular, LAOC strongly absorbs solar radiation in the near-ultraviolet and short visible wavelengths. Recent studies of the United States’ wildfire events highlighted that LAOC becomes the dominant contributor in the total light absorption of particulate matters at those wavelengths. Despite evident importance of LAOC as a climate forcer, there exists a large discrepancy between model- and observation-based of LAOC’s microphysical properties, resulting in the uncertainty in the estimate of LAOC radiative forcing. The discrepancies between modeling and observations can be attributed to several factors, including uncertainties in the estimates of fire emissions and their relationship with combustion conditions, mischaracterizations of the diverse and dynamic formation of LAOC in wildfire plumes, and poor parameterizations of the spectral absorption properties of LAOC and the evolution of its physiochemical properties in long-range transport. To first provide a more reliable estimate of fire emissions, this study applied a semi-empirical heat transfer model to satellite active fire products to retrieve the fire area and combustion conditions at a subpixel level. These retrieved parameters can be used to update the existing fire emission inventories in chemical transport models (CTM) to reflect the dependencies of fire emissions and plume injection height on resolved proportions of various burning conditions. By further developing an advanced numerical testbed in CTM containing a LAOC optical module inferred from chemical composition, this study provides insights of the variated LAOC’s physiochemical properties due to atmospheric aging. The modeled parameters of LAOC properties will be optimized through comparison with satellite and in situ observations. We plan to apply this optimized parameterization scheme for LAOC to the global climate models, to comprehensively study the radiative effects of wildfire emissions.