Simulating the Oxidative Aging of Ambient Organic Compounds
BENJAMIN N. MURPHY (1), Neil M. Donahue (1), Spyros N. Pandis (1,2)
(1) Carnegie Mellon University, Center for Atmospheric Particle Studies, Pittsburgh, USA, (2) University of Patras, Institute of Chemical Engineering and High Temperature Chemical Processes (ICE-HT), Foundation of Research and Technology (FORTH), Patra, Greece
Abstract Number: 767
Preference: Platform Presentation
Last modified: May 14, 2010
Working Group: Aerosol Chemistry
Organic compounds are subject to continued oxidation (aging) throughout their atmospheric lifetime. These complex reactions change the volatility and degree of oxygenation of the aerosol, thus affecting the concentrations and chemical composition measured in the atmosphere. We employ a regional-scale, Lagrangian model with a volatility basis-set module that explicitly tracks oxidation state (or O/C ratio) as well as saturation concentration to simulate aging and evaluate predictions with measurements from the Pittsburgh Air Quality Study (PAQS) and the Finokalia Aerosol Measurement Experiment (FAME).
Traditionally, secondary organic aerosol (SOA) formation is simulated as the condensation of semivolatile gases produced by volatile organic precursor oxidation. Most large-scale models that consider this process do not consider the aging that continues to change the properties of those products. Representing this aging accurately could be an important feature for developing reliable organic aerosol models. There are significant uncertainties in this process though, including the reaction rates, the volatility distribution of the products and the roles of functionalization versus fragmentation pathways.
Organic species gas/particle partitioning has been described in previous lab- and large-scale models using the volatility basis-set approach, which tracks the saturation concentration of organic vapor and particle mass. We have extended this model to describe variations in oxidation state so the degree of oxygenation can be tracked explicitly. The model simulates 2 days of transport and chemistry for each parcel arriving at a measurement site and takes into account emissions and dry deposition of gases and particles. This model can therefore predict the organic aerosol concentration, the volatility distribution and the oxidation state, and these metrics are compared to measurements taken during the PAQS and FAME studies in order to reduce the uncertainties in simulating the aging process. The results from this explicit model will improve the way large-scale 3-dimensional models treat organic aerosol aging.