Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7459-2021
https://doi.org/10.5194/gmd-14-7459-2021
Model experiment description paper
 | 
07 Dec 2021
Model experiment description paper |  | 07 Dec 2021

The effect of accounting for public holidays on the skills of the atmospheric composition model SILAM v.5.7

Yalda Fatahi, Rostislav Kouznetsov, and Mikhail Sofiev

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Cited articles

Beirle, S., Platt, U., Wenig, M., and Wagner, T.: Weekly cycle of NO2 by GOME measurements: a signature of anthropogenic sources, Atmos. Chem. Phys., 3, 2225–2232, https://doi.org/10.5194/acp-3-2225-2003, 2003. 
Brasseur, G. P., Xie, Y., Petersen, A. K., Bouarar, I., Flemming, J., Gauss, M., Jiang, F., Kouznetsov, R., Kranenburg, R., Mijling, B., Peuch, V.-H., Pommier, M., Segers, A., Sofiev, M., Timmermans, R., van der A, R., Walters, S., Xu, J., and Zhou, G.: Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1, Geosci. Model Dev., 12, 33–67, https://doi.org/10.5194/gmd-12-33-2019, 2019. 
Carslaw, K. S., Luo, B., and Peter, T.: An analytic expression for the composition of aqueous HNO3-H2SO4 stratospheric aerosols including gas phase removal of HNO3, Geophys. Res. Lett., 22, 1877–1880, https://doi.org/10.1029/95GL01668, 1995. 
Chen, P.-Y., Tan, P.-H., Chou, C. C.-K., Lin, Y.-S., Chen, W.-N., and Shiu, C.-J.: Impacts of holiday characteristics and number of vacation days on “holiday effect” in Taipei: Implications on ozone control strategies, Atmos. Environ., 202, 357–369, https://doi.org/10.1016/j.atmosenv.2019.01.029, 2019. 
Damski, J., Thölix, L., Backman, L., Taalas, P., and Kulmala, M.: FinROSE – middle atmospheric chemistry transport model, Boreal Environ. Res., 12, 535–550, 2007. 
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Short summary
Incorporating information on public holidays into anthropogenic sector emissions results in substantial short-term improvement of the chemistry transport model SILAM scores. The largest impact was found for NOx, which is controlled by the changes in the traffic intensity. Certain improvements were also found for other species, but the signal was weaker than that for NOx.