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

Related authors

An improved representation of aerosol mixing state for air quality–weather interactions
Robin Stevens, Andrei Ryjkov, Mahtab Majdzadeh, and Ashu Dastoor
Atmos. Chem. Phys., 22, 13527–13549, https://doi.org/10.5194/acp-22-13527-2022,https://doi.org/10.5194/acp-22-13527-2022, 2022
Short summary

Related subject area

Atmospheric sciences
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024,https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024,https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024,https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024,https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024,https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary

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. 
Download
Short summary
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 %.