Articles | Volume 16, issue 15
Atmos. Chem. Phys., 16, 10045–10061, 2016
https://doi.org/10.5194/acp-16-10045-2016
Atmos. Chem. Phys., 16, 10045–10061, 2016
https://doi.org/10.5194/acp-16-10045-2016

Research article 09 Aug 2016

Research article | 09 Aug 2016

Simulations of organic aerosol concentrations during springtime in the Guanzhong Basin, China

Tian Feng et al.

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Bei, N., de Foy, B., Lei, W., Zavala, M., and Molina, L. T.: Using 3DVAR data assimilation system to improve ozone simulations in the Mexico City basin, Atmos. Chem. Phys., 8, 7353–7366, https://doi.org/10.5194/acp-8-7353-2008, 2008.
Bei, N., Lei, W., Zavala, M., and Molina, L. T.: Ozone predictabilities due to meteorological uncertainties in the Mexico City basin using ensemble forecasts, Atmos. Chem. Phys., 10, 6295–6309, https://doi.org/10.5194/acp-10-6295-2010, 2010.
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Binkowski, F. S. and Roselle, S. J.: Models-3 Community Multiscale Air Quality (CMAQ) model aerosol component 1. Model description, J. Geophys. Res., 108, 4183, https://doi.org/10.1029/2001JD001409, 2003.
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The springtime organic aerosol (OA) concentrations in the Guanzhong Basin, China are simulated using the WRF-Chem model with two secondary OA (SOA) modules. Model results are verified with near-surface observations. The non-traditional SOA module significantly improves SOA simulation. Oxidation and partitioning of primary OAs is the most important pathway in SOA formation. Residential emissions are the dominant anthropogenic OA source.
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