Thesis Title: Constraining Atmospheric Emissions and Chemical Processes Across Spatial Scales Using Modeling and Observational Techniques

Thesis Abstract: This thesis presents three interconnected studies that advance our understanding of atmospheric chemistry through improved emissions modeling and source attribution techniques. The research addresses critical knowledge gaps in biogenic volatile organic compound (BVOC) emissions, ozone pollution control strategies, and global methane source identification. In the first work, we developed the Speciated Isoprene Emission Model with the MEGAN Algorithm for China (SieMAC), a comprehensive biogenic isoprene emissions model specifically designed for China's diverse ecosystems. By integrating extensive local emission factor measurements, high-resolution vegetation distributions, and plant functional type-specific leaf area indices, SieMAC significantly improves upon existing MEGAN versions. The model incorporates optional water stress effects through vapor pressure deficit calculations and modified temperature response algorithms for boreal grasslands. Evaluation against ground-based CARE-China observations and satellite formaldehyde data demonstrates superior performance compared to MEGAN v2.1 and v3.1, particularly in northern China where previous models showed systematic underestimation. SieMAC estimates summer 2013 emissions of 10.92-15.83 TgC, revealing a smaller north-south emission gradient than previously recognized and highlighting the significant role of biogenic emissions in China's ozone pollution. The flexible open-source framework of SieMAC allows for continuous improvement and regional customization as new datasets and measurements become available, making it a valuable tool for both research and policy applications. In the second work, through analysis of ~1,400 monitoring sites across China and comparison with historical data from the United States and Europe, we identified two key mechanisms explaining China's limited ozone response to substantial NOx emission reductions since 2013. First, China's high-ozone regions exhibit weak or negative correlations between odd oxygen (Ox = O3 + NO2) and NO2, indicating NOx-saturated chemical regimes resistant to initial emission cuts. A critical threshold of NO2 is identified, below which ozone begins responding positively to further NOx reductions. Second, using the REAM model, we found that the emission redistribution process creates a "redistribution penalty" that undermines reduction benefits through enhanced regional radical production. In the third work, to resolve the ongoing scientific debate regarding the location of significant methane emission increases during 2020-2021, we applied the 12-box AGAGE atmospheric model. We successfully optimized the model transport parameters using SF6 observations and OH radical distributions using HFC-134a observations. This framework isolates emissions as the primary control on methane concentrations, enabling robust attribution of enhanced methane sources during the recent emission surge.

Defense Date: 7/9
Defense Time: 2pm-5pm
Defense Location: ES & T L1114
Committee members: Dr. Yuhang Wang (Advisor), Dr. Lewis G. Huey, Dr.
Rodney Weber, Dr. Pengfei Liu, Dr. Da Pan