Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3813-2021
https://doi.org/10.5194/gmd-14-3813-2021
Development and technical paper
 | 
24 Jun 2021
Development and technical paper |  | 24 Jun 2021

Effects of heterogeneous reactions on tropospheric chemistry: a global simulation with the chemistry–climate model CHASER V4.0

Phuc T. M. Ha, Ryoki Matsuda, Yugo Kanaya, Fumikazu Taketani, and Kengo Sudo

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Cited articles

Akimoto, H., Nagashima, T., Li, J., Fu, J. S., Ji, D., Tan, J., and Wang, Z.: Comparison of surface ozone simulation among selected regional models in MICS-Asia III – effects of chemistry and vertical transport for the causes of difference, Atmos. Chem. Phys., 19, 603–615, https://doi.org/10.5194/acp-19-603-2019, 2019. 
Apodaca, R. L., Huff, D. M., and Simpson, W. R.: The role of ice in N2O5 heterogeneous hydrolysis at high latitudes, Atmos. Chem. Phys., 8, 7451–7463, https://doi.org/10.5194/acp-8-7451-2008, 2008. 
Bates, K. H. and Jacob, D. J.: A new model mechanism for atmospheric oxidation of isoprene: global effects on oxidants, nitrogen oxides, organic products, and secondary organic aerosol, Atmos. Chem. Phys., 19, 9613–9640, https://doi.org/10.5194/acp-19-9613-2019, 2019. 
Battan, L. J. and Reitan, C. H.: Droplet size measurements in convective clouds, in Artificial simulation of Rain, Pergamon Press, New York, 184–191, 1957. 
Betterton, E. A.: Henry's Law constants of soluble and moderately soluble organic gases: effects on aqueous-phase chemistry, in: Gaseous pollutants: Characterization and cycling, Wiley, 24, 1–50, 1992. 
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Short summary
Policies to mitigate air pollution require an understanding of tropospheric oxidizing capacity, which is controlled by mechanisms including heterogeneous processes on aerosols and clouds. This study uses a chemistry–climate model CHASER (MIROC) to explore the heterogeneous effects in the troposphere for -2.96 % O3, -2.19 % NOx, +3.28 % CO, and +5.91 % CH4 lifetime. Besides, these processes affect polluted areas and remote areas and can bring challenges to pollution reduction efforts.
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