Open AccessORILAM‐SOA: A computationally efficient model for predicting secondary organic aerosols in three‐dimensional atmospheric models
Author(s) -
Tulet Pierre,
Grini Alf,
Griffin Robert J.,
Petitcol Sebastien
Publication year - 2006
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2006jd007152
Subject(s) - aerosol , log normal distribution , atmospheric model , computation , environmental science , meteorology , atmospheric chemistry , algorithm , computer science , physics , mathematics , ozone , statistics
This paper describes the aerosol model Organic Inorganic Lognormal Aerosol Model including Secondary Organic Aerosol (ORILAM‐SOA) which is an extension of the lognormal aerosol dynamics model ORILAM. ORILAM‐SOA consists of the original aerosol dynamics routines, a photochemical scheme able to predict SOA precursors, and an equilibrium scheme able to predict partitioning of the precursors between the gas and aerosol phases. We show that ORILAM‐SOA is computationally efficient enough to be run in three‐dimensional (3‐D) atmospheric models. ORILAM‐SOA is based on existing models. We use a numerical reduction technique to reduce the Caltech Atmospheric Chemistry Mechanism (CACM) and a new, fast, convergent iteration technique to increase the speed of the Model to Predict the Multiphase Partitioning of Organics (MPMPO). We compare the ORILAM‐SOA to its parent models in terms of gas concentrations, aerosol concentrations, and CPU time spent during the computations. For illustrative purposes we include a 3‐D simulation of SOA over southern France.