Articles | Volume 12, issue 8
https://doi.org/10.5194/gmd-12-3585-2019
https://doi.org/10.5194/gmd-12-3585-2019
Model description paper
 | 
19 Aug 2019
Model description paper |  | 19 Aug 2019

Global simulation of semivolatile organic compounds – development and evaluation of the MESSy submodel SVOC (v1.0)

Mega Octaviani, Holger Tost, and Gerhard Lammel

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Cited articles

Batjes, N.: Total carbon and nitrogen in the soils of the world, Eur. J. Soil Sci., 47, 151–163, https://doi.org/10.1111/j.1365-2389.1996.tb01386.x, 1996. a
Dalla Valle, M., Codato, E., and Marcomini, A.: Climate change influence on POPs distribution and fate: A case study, Chemosphere, 67, 1287–1295, https://doi.org/10.1016/j.chemosphere.2006.12.028, 2007. a
Daly, G. L. and Wania, F.: Simulating the influence of snow on the fate of organic compounds, Environ. Sci. Technol., 38, 4176–4186, https://doi.org/10.1021/es035105r, 2004. a
de Boyer Montégut, C., Madec, G., Fischer, A. S., Lazar, A., and Iudicone, D.: Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology, J. Geophys. Res.-Oceans, 109, C12003, https://doi.org/10.1029/2004JC002378, 2004. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERAInterim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
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This work presents a submodel description for the atmospheric cycling and air–surface exchange processes of semivolatile organic compounds. The submodel is meant to be applied within a global atmospheric chemistry–climate model. The simulation results for polycyclic aromatic hydrocarbons confirm progress in modelling semivolatile species, verified by comparison with surface monitoring data. The significance of new modelling features for tracer distributions was quantified in a sensitivity study.
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