Prediction of Organic-Vapor Wall Deposition Using a Qualitative Structure Activity Relationship and its Application to the Secondary Organic Aerosol (SOA) Model

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Environmental chambers are frequently used to investigate atmospheric chemistry in a controlled setting. This research is focused on developing a model to predict the interactions of gases and particles with the walls of an environmental chamber, and to predict what effects these interactions might have on the results of a study. For example, the wall effects in an environmental chamber often result in the underestimation of the formation of small particles in the chamber, an error that can be carried through to air-quality and climate models. This project is expected to ultimately improve the predictive capability for the formation of SOA in the atmosphere and improve the estimates of both the direct and indirect effects of SOA on human health and climate. The three objectives of the proposal are to: (1) Predict the gas-wall process partitioning constant of various semivolatile organic compounds (SVOCs) and their deposition rate constants using a Quantitative Structure Activity Relation (QSAR) approach; (2) Integrate the gas-wall process model parameters with the model that predicts secondary organic aerosol (SOA) formation; and (3) Evaluate the potential for SOA formation produced via multiphase reactions of various hydrocarbons using the amended model including the bias due to the gas-wall process. A model that uses an explicit gas mechanism to predict SOA formation from multiphase reactions, will be amended and applied to investigate the impact of gas-wall processes on the formation of SOA.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.