Atmospheric sulfur cycle simulated in the global model GOCART: Model description and global properties

Citation
M. Chin et al., Atmospheric sulfur cycle simulated in the global model GOCART: Model description and global properties, J GEO RES-A, 105(D20), 2000, pp. 24671-24687
Citations number
54
Categorie Soggetti
Earth Sciences
Volume
105
Issue
D20
Year of publication
2000
Pages
24671 - 24687
Database
ISI
SICI code
Abstract
The Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Trans port (GOCART) model is used to simulate the atmospheric sulfur cycle. The m odel uses the assimilated meteorological data from the Goddard Earth Observ ing System Data Assimilation System (GEOS DAS). Global sulfur budgets from a 6-year simulation for SO2, sulfate, dimethylsulfide (DMS), and methanesul fonic acid (MSA) are presented in this paper. In a normal year without majo r volcanic perturbations, about 20% of the sulfate precursor emission is fr om natural sources (biogenic and volcanic), and 80% is anthropogenic; the s ame sources contribute 33% and 67%, respectively, to the total sulfate burd en.,A sulfate production efficiency of 0.41-0.42 is estimated in the model, an efficiency which is defined as a ratio of the amount of sulfate produce d to the total amount of SO2 emitted and produced in the atmosphere. This v alue indicates that less than half of the SO2 entering the atmosphere contr ibutes to the sulfate production, the rest being removed by dry and wet dep ositions. In a simulation for 1990 we estimate a total sulfate production o f 39 Tg S yr(-1), with 36% and 64% from in-air and in-cloud oxidation, resp ectively, of SO2. We also demonstrate that major volcanic eruptions, such a s the Mount Pinatubo eruption in 1991, can significantly change the sulfate formation pathways, distributions, abundance, and lifetime. Comparison wit h other models shows that the parameterizations for wet removal or wet prod uction of sulfate are the most critical factors in determining the burdens of SO2 and sulfate. Therefore a priority for future research should be to r educe the large uncertainties associated with the wet physical and chemical processes.