American Association for Aerosol Research - Abstract Submission

AAAR 35th Annual Conference
October 17 - October 21, 2016
Oregon Convention Center
Portland, Oregon, USA

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Unified Method for Predicting Aerosol Formation and Composition from Aromatic Hydrocarbon under NOX Conditions in Urban Atmosphere

LIJIE LI, Ping Tang, David R. Cocker III, Kelley Barsanti, University of California, Riverside

     Abstract Number: 522
     Working Group: Aerosol Chemistry

Abstract
A simplified algorithm, derived from generalized reaction mechanisms, is required to enhance the efficiency of SOA predictive models. Current SOA models include increasing amount of constraints and parameters to bridge the gap between field observation and model perdition. Aromatic hydrocarbons, a class of major anthropogenic SOA precursors, are usually photooxidized in the presence of NO$_X in urban areas. Understanding the determinant structure in aromatic hydrocarbons to SOA formation under NO$_X conditions in urban region is important to SOA model prediction. This work evaluates the leading role of the aromatic ring in SOA formation from aromatic hydrocarbons under NO$_X conditions comparable to urban atmosphere by investigating SOA yield and elemental ratio from aromatic precursors with differing the number of alkyl substitutes, alkyl substitute length and branch ratio. Unified methods for predicting aerosol composition and formation is developed on an aromatic ring basis as both "Ring normalized SOA yield (yield′)" and "Ring based elemental ratio (O/R and H/R)". It is demonstrated that four oxygens are obtained per aromatic ring during the oxidation of aromatic hydrocarbons regardless of the alkyl substitutes attached to the ring. Ring normalized SOA yield among all aromatic hydrocarbons show similar trend to mass based SOA yield of benzene. Further, the sensitivity of current SOA model to the new batch of SOA yield parameters under low NO$_X conditions is presented. The SOA model predictions based on single ring normalized yield curve and multiple mass based yield curves are compared and evaluated.