Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model
Multi-generational gas-phase oxidation of organic vapors can influence the abundance, composition and properties of secondary organic aerosol (SOA). Only recently have SOA models been developed that explicitly represent multi-generational SOA formation. In this work, we integrated the statistical ox...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2015-08-01
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| Series: | Geoscientific Model Development |
| Online Access: | http://www.geosci-model-dev.net/8/2553/2015/gmd-8-2553-2015.pdf |
| _version_ | 1818957484722749440 |
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| author | S. H. Jathar C. D. Cappa A. S. Wexler J. H. Seinfeld M. J. Kleeman |
| author_facet | S. H. Jathar C. D. Cappa A. S. Wexler J. H. Seinfeld M. J. Kleeman |
| author_sort | S. H. Jathar |
| collection | DOAJ |
| description | Multi-generational gas-phase oxidation of organic vapors can influence the
abundance, composition and properties of secondary organic aerosol (SOA).
Only recently have SOA models been developed that explicitly represent
multi-generational SOA formation. In this work, we integrated the statistical
oxidation model (SOM) into SAPRC-11 to simulate the multi-generational
oxidation and gas/particle partitioning of SOA in the regional UCD/CIT (University of California, Davis/California Institute of Technology) air
quality model. In the SOM, evolution of organic vapors by reaction with the
hydroxyl radical is defined by (1) the number of oxygen atoms added per
reaction, (2) the decrease in volatility upon addition of an oxygen atom and
(3) the probability that a given reaction leads to fragmentation of the
organic molecule. These SOM parameter values were fit to laboratory smog
chamber data for each precursor/compound class. SOM was installed in the
UCD/CIT model, which simulated air quality over 2-week periods in the South
Coast Air Basin of California and the eastern United States. For the regions
and episodes tested, the two-product SOA model and SOM produce similar SOA
concentrations but a modestly different SOA chemical composition. Predictions
of the oxygen-to-carbon ratio qualitatively agree with those measured
globally using aerosol mass spectrometers. Overall, the implementation of the
SOM in a 3-D model provides a comprehensive framework to simulate the
atmospheric evolution of organic aerosol. |
| first_indexed | 2024-12-20T11:10:35Z |
| format | Article |
| id | doaj.art-b4059eaf2ee645edbf5e6f5f78c25db2 |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-12-20T11:10:35Z |
| publishDate | 2015-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-b4059eaf2ee645edbf5e6f5f78c25db22022-12-21T19:42:46ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032015-08-01882553256710.5194/gmd-8-2553-2015Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality modelS. H. Jathar0C. D. Cappa1A. S. Wexler2J. H. Seinfeld3M. J. Kleeman4Civil and Environmental Engineering, University of California, Davis CA, USACivil and Environmental Engineering, University of California, Davis CA, USACivil and Environmental Engineering, University of California, Davis CA, USAChemical Engineering, California Institute of Technology, Pasadena CA, USACivil and Environmental Engineering, University of California, Davis CA, USAMulti-generational gas-phase oxidation of organic vapors can influence the abundance, composition and properties of secondary organic aerosol (SOA). Only recently have SOA models been developed that explicitly represent multi-generational SOA formation. In this work, we integrated the statistical oxidation model (SOM) into SAPRC-11 to simulate the multi-generational oxidation and gas/particle partitioning of SOA in the regional UCD/CIT (University of California, Davis/California Institute of Technology) air quality model. In the SOM, evolution of organic vapors by reaction with the hydroxyl radical is defined by (1) the number of oxygen atoms added per reaction, (2) the decrease in volatility upon addition of an oxygen atom and (3) the probability that a given reaction leads to fragmentation of the organic molecule. These SOM parameter values were fit to laboratory smog chamber data for each precursor/compound class. SOM was installed in the UCD/CIT model, which simulated air quality over 2-week periods in the South Coast Air Basin of California and the eastern United States. For the regions and episodes tested, the two-product SOA model and SOM produce similar SOA concentrations but a modestly different SOA chemical composition. Predictions of the oxygen-to-carbon ratio qualitatively agree with those measured globally using aerosol mass spectrometers. Overall, the implementation of the SOM in a 3-D model provides a comprehensive framework to simulate the atmospheric evolution of organic aerosol.http://www.geosci-model-dev.net/8/2553/2015/gmd-8-2553-2015.pdf |
| spellingShingle | S. H. Jathar C. D. Cappa A. S. Wexler J. H. Seinfeld M. J. Kleeman Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model Geoscientific Model Development |
| title | Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model |
| title_full | Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model |
| title_fullStr | Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model |
| title_full_unstemmed | Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model |
| title_short | Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model |
| title_sort | multi generational oxidation model to simulate secondary organic aerosol in a 3 d air quality model |
| url | http://www.geosci-model-dev.net/8/2553/2015/gmd-8-2553-2015.pdf |
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