Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning

Murphy, Benjamin N.; Woody, Matthew C.; Jimenez, Jose L.; Carlton, Ann Marie G.; Hayes, Patrick L.; Liu, Shang; Ng, Nga L.; Russell, Lynn M.; Setyan, Ari; Xu, Lu; Young, Jeff; Zaveri, Rahul A.; Zhang, Qi; Pye, Havala O. T.

doi:https://doi.org/10.5194/acp-17-11107-2017

Articles | Volume 17, issue 18

https://doi.org/10.5194/acp-17-11107-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/acp-17-11107-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 17, issue 18

Research article

|

20 Sep 2017

Research article |

| 20 Sep 2017

Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning

Benjamin N. Murphy, Matthew C. Woody, Jose L. Jimenez, Ann Marie G. Carlton, Patrick L. Hayes, Shang Liu, Nga L. Ng, Lynn M. Russell, Ari Setyan, Lu Xu, Jeff Young, Rahul A. Zaveri, Qi Zhang, and Havala O. T. Pye

Supplement

https://doi.org/10.5194/acp-17-11107-2017-supplement

Model code and software

NOAA Earth System Research Laboratory, CalNex 2010 CalNex measurement data https://www.esrl.noaa.gov/csd/groups/csd7/measurements/2010calnex/

DOE Atmospheric Radiation Measurement Program, Carbonaceous Aerosol and Radiative Effects Study CARES measurement data http://www.archive.arm.gov/discovery/\#v/results/s/fiop::aaf2009carbonaerosol

NOAA Earth System Research Laboratory, SENEX 2013 SOAS measurement data https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/

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Short summary

We incorporate recent findings about the behavior of organic pollutants in urban airsheds into the Community Multiscale Air Quality (CMAQ) model to refine predictions of organic particulate pollution in the United States. The new techniques, which account for the volatility and ongoing chemistry of airborne organic compounds, substantially reduce biases, particularly in the winter time and near emission sources.