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Published February 2003 | public
Journal Article

A Coupled Hydrophobic-Hydrophilic Model for Predicting Secondary Organic Aerosol Formation


The formation of secondary organic aerosol (SOA) results from the absorption of gas-phase organic oxidation products by airborne aerosol. Historically, modeling the formation of SOA has relied on relatively crude estimates of the capability of given parent hydrocarbons to form SOA. In more recent work, surrogate organic oxidation products have been separated into two groups, hydrophobic and hydrophilic, depending on whether the product is more likely to dissolve into an organic or an aqueous phase, respectively. The surrogates are then allowed to partition only via the dominant mechanism, governed by molecular properties of the surrogate molecules. The distinction between hydrophobic and hydrophilic is based on structural and physical characteristics of the compound. In general, secondary oxidation products, because of low vapor pressures and high polarities, express affinity for both the organic and aqueous aerosol phases. A fully coupled hydrophobic-hydrophilic organic gas-particle partitioning model is presented here. The model concurrently achieves mass conservation, equilibrium between the gas phase and the organic aerosol phase, equilibrium between the gas phase and the aqueous aerosol phase, and equilibrium between molecular and ionic forms of the partitioning species in the aqueous phase. Simulations have been performed using both a zero-dimensional model and the California Institute of Technology three-dimensional atmospheric chemical transport model. Simultaneous partitioning of species by both mechanisms typically leads to a shift in the distribution of products to the organic aerosol phase and an increase in the total amount of SOA predicted as compared to previous work in which partitioning is assumed to occur independently to organic and aqueous phases.

Additional Information

Special thanks to Eladio Knipping of the University of California at Irvine for assistance in implementing the coupled module into the CIT model and to Professor Dharni Vasudevan of the Nicholas School of the Environment and Earth Sciences at Duke University for many helpful discussions. This work was funded, in part, by the Electric Power Research Institute and the CAREER Award Grant ATM-9985025 from the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Additional details

August 22, 2023
October 23, 2023