Articles | Volume 15, issue 1
https://doi.org/10.5194/gmd-15-219-2022
https://doi.org/10.5194/gmd-15-219-2022
Development and technical paper
 | 
12 Jan 2022
Development and technical paper |  | 12 Jan 2022

Development of aerosol optical properties for improving the MESSy photolysis module in the GEM-MACH v2.4 air quality model and application for calculating photolysis rates in a biomass burning plume

Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen

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Cited articles

AERONET: AERONET, NASA [data set], available at: https://aeronet.gsfc.nasa.gov/, last access: 5 February 2020 
Alvarado, M. J., Lonsdale, C. R., Yokelson, R. J., Akagi, S. K., Coe, H., Craven, J. S., Fischer, E. V., McMeeking, G. R., Seinfeld, J. H., Soni, T., Taylor, J. W., Weise, D. R., and Wold, C. E.: Investigating the links between ozone and organic aerosol chemistry in a biomass burning plume from a prescribed fire in California chaparral, Atmos. Chem. Phys., 15, 6667–6688, https://doi.org/10.5194/acp-15-6667-2015, 2015. 
Alvarado, M. J., Lonsdale, C. R., Macintyre, H. L., Bian, H., Chin, M., Ridley, D. A., Heald, C. L., Thornhill, K. L., Anderson, B. E., Cubison, M. J., Jimenez, J. L., Kondo, Y., Sahu, L. K., Dibb, J. E., and Wang, C.: Evaluating model parameterizations of submicron aerosol scattering and absorption with in situ data from ARCTAS 2008, Atmos. Chem. Phys., 16, 9435–9455, https://doi.org/10.5194/acp-16-9435-2016, 2016. 
Anderson, B. E., Cofer, W. R., Bagwell, D. R., Barrick, J. W., Hudgins, C. H., and Brunke, K. E.: Airborne observations of aircraft aerosol emissions 1: total non-volatile particle emission indices, Geophys. Res. Lett., 25, 1689–1692, 1998. 
Anderson, K. and cast of thousands: CFFEPS v2.03, Canadian Forest Service, Natural Resources Canada, Zenodo [code], https://doi.org/10.5281/zenodo.2579383, 2019. 
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A new lookup table for aerosol optical properties based on a Mie scattering code was calculated and adopted within an improved version of the photolysis module in the GEM-MACH in-line chemical transport model. The modified version of the photolysis module makes use of online interactive aerosol feedback and applies core-shell parameterizations to the black carbon absorption efficiency based on Bond et al. (2006) to the size bins with black carbon mass fraction of less than 40 %.
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