Abstract:
Current chemical theory is incomplete to accurately predict product formation and structure from radical reactions under non-ideal conditions such as complex, multi-component environmental matrices. Radical reactions occur ubiquitously in the atmosphere and drive the complex, multiphase chemistry of volatile organic compound (VOC) oxidation to particulate mass, a key health concern. A significant constituent of fine particulate matter (PM2.5) is secondary organic aerosol (SOA) and oxidation pathways that yield SOA are studied extensively. However, a complete understanding of the mechanistic steps in the evolution of VOCs to particle mass and resulting ambient pollution burden remains elusive. For example, the full mechanistic pathways for side reactions are relatively neglected and identification of individual SOA species is often incomplete. The products of less favorable branching pathways of VOC oxidation such as water-soluble organic carbon (WSOC) are not frequently studied in terms of SOA formation. Measurements of WSOC via wet chemical oxidation (WCO) are subject to interference in the presence of salts, which are abundant in nearly all ambient aquatic samples, including aerosols. Further, ambient PM2.5 mass measured by the federal reference method/federal equivalence method are prone to negative sampling artifacts through loss of semi-volatile species such as ammonium nitrate. This dissertation-defense presents three projects aimed to resolve uncertainties in particle mass formation and ambient burden: (1) an elementary step radical reaction database used to train a deep learning system, Reaction Predictor (RP), (2) a kinetic model that predicts chloride interferences in WSOC measurements via WCO methods, and (3) thermodynamic calculations to elucidate uncertainties from ammonium nitrate volatilization in atmospheric measurements of PM2.5. The radical reaction database is utilized to train a deep learning system with single-step radical reactions and fosters collaboration by enabling users to add reactions. Preliminary tests with myrcene demonstrate plausible single-step predictions from RP. Postulated mechanisms suggest the formation of stable chlorinated byproducts during WCO analysis of organic acids. A kinetic model mimicking analyzer conditions reproduces empirical measurements in close agreement. Estimates of ammonium nitrate volatilization suggest up to 20% PM2.5 loss during ambient sampling in regulatory PM2.5 networks. Collectively, this work highlights the application of fundamental chemistry to plausibly explain uncertainties in measurements of WSOC and PM2.5 in order to better understand environmental burdens of pollution.
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