Atmos. Chem. Phys. Discuss., 11, 3885-3935, 2011
www.atmos-chem-phys-discuss.net/11/3885/2011/
doi:10.5194/acpd-11-3885-2011
© Author(s) 2011. This work is distributed
under the Creative Commons Attribution 3.0 License.
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This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Development of a simple unified volatility-based scheme (SUVS) for secondary organic aerosol formation using genetic algorithms
A. G. Xia, C. A. Stroud, and P. A. Makar
Air Quality Research Division, Science and Technology Branch, Environment Canada, Toronto, Ontario, Canada

Abstract. A new method is proposed to simplify complex atmospheric chemistry reaction schemes, while preserving SOA formation properties, using genetic algorithms. The method is first applied in this study to the gas-phase α-pinene oxidation scheme. The simple unified volatility-based scheme (SUVS) reflects the multi-generation evolution of chemical species from a near-explicit master chemical mechanism (MCM) and, at the same time, uses the volatility-basis set speciation for condensable products. The SUVS also unifies reactions between SOA precursors with different oxidants under different atmospheric conditions. A total of 412 unknown parameters (product yields of parameterized products, reaction rates, etc.) from the SUVS are estimated by using genetic algorithms operating on the detailed mechanism. The number of organic species was reduced from 310 in the detailed mechanism to 31 in the SUVS. Output species profiles, obtained from the original subset of the MCM reaction scheme for α-pinene oxidation, are reproduced with maximum fractional error at 0.10 for scenarios under a wide range of ambient HC/NOx conditions. Ultimately, the same SUVS with updated parameters could be used to describe the SOA formation from different precursors.

Citation: Xia, A. G., Stroud, C. A., and Makar, P. A.: Development of a simple unified volatility-based scheme (SUVS) for secondary organic aerosol formation using genetic algorithms, Atmos. Chem. Phys. Discuss., 11, 3885-3935, doi:10.5194/acpd-11-3885-2011, 2011.
 
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