UC Irvine

Accurately characterizing anthropogenic emissions is of utmost importance for atmospheric chemistry modeling, improving air quality, and monitoring climate change. Current emission inventories predominantly rely on bottom-up approaches using statistical data on activity levels and emission factors. Given the critical role of these inventories in modeling and informing policymakers on air pollution, independent validation through top-down methods can significantly enhance their reliability.

In this dissertation, I present data from a three-year airborne field campaign conducted in Taean, South Korea, aimed at refining measurement-based emission estimates to validate bottom-up emission inventories. In the first study, I enhance the aircraft mass balance approach by introducing a 3D interpolation method known as radial basis function, enhancing the accuracy of measurements. The method's uncertainty is also assessed, with ground extrapolation accounting for the largest uncertainty, up to 28%. The second study involves improving the temporal resolution of hourly aircraft-based emission estimates to derive annual estimates, enabling direct comparisons with bottom-up inventories. By analyzing emission estimates and comparing them with the inventories, I observe a notable average 44% decrease in SO2 emissions following improved scrubber enforcement at the facilities. Ratios between robust SO2 emissions and NO2 and CO2 emissions are derived, paving the way for potential future emission scaling. Lastly, I apply the airborne mass balance method to estimate VOC emissions and their ozone formation potential at a Petrochemical Facility, revealing substantial variability in speciation profiles and underestimation of total VOC emissions in the inventory by a factor of 2.9. These underestimations have a profound impact on simulating ozone and secondary organic aerosol formation, underscoring the need for precise VOC source representation.

The results presented in this thesis emphasize the importance of constraining anthropogenic emissions and validating bottom-up inventories. Estimating emissions of these primary species is crucial, as they influence the formation of secondary species, impacting regional and global model simulations. By incorporating emission estimates into global inventories, we can better inform international agreements on emissions, enabling targeted and effective climate change mitigation strategies. This work marks a significant step towards accurately representing emissions' implications for air quality and our planet's future.