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| Titel |
A computationally-efficient secondary organic aerosol module for three-dimensional air quality models |
| VerfasserIn |
P. Liu, Y. Zhang |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 8, no. 14 ; Nr. 8, no. 14 (2008-07-24), S.3985-3998 |
| Datensatznummer |
250006300
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| Publikation (Nr.) |
 copernicus.org/acp-8-3985-2008.pdf |
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| Zusammenfassung |
| Accurately simulating secondary organic aerosols (SOA) in three-dimensional
(3-D) air quality models is challenging due to the complexity of the physics
and chemistry involved and the high computational demand required. A
computationally-efficient yet accurate SOA module is necessary in 3-D
applications for long-term simulations and real-time air quality
forecasting. A coupled gas and aerosol box model (i.e., 0-D CMAQ-MADRID 2)
is used to optimize relevant processes in order to develop such a SOA
module. Solving the partitioning equations for condensable volatile organic
compounds (VOCs) and calculating their activity coefficients in the
multicomponent mixtures are identified to be the most
computationally-expensive processes. The two processes can be speeded up by
relaxing the error tolerance levels and reducing the maximum number of
iterations of the numerical solver for the partitioning equations for
organic species; conditionally activating organic-inorganic interactions;
and parameterizing the calculation of activity coefficients for organic
mixtures in the hydrophilic module. The optimal speed-up method can reduce
the total CPU cost by up to a factor of 31.4 from benchmark under the rural
conditions with 2 ppb isoprene and by factors of 10–71 under various test
conditions with 2–10 ppb isoprene and >40% relative humidity while
maintaining ±15% deviation. These speed-up methods are applicable to
other SOA modules that are based on partitioning theories. |
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