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Report 71. Mechanistic, Sensitivity, and Uncertainty Studies of the Atmospheric Oxidation of Dimethylsulfide

by Donald David Lucas

June 2003

Submitted to the MIT Department of Earth, Atmospheric and Planetary Sciences on May 2, 2003, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Atmospheric Chemistry

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Abstract

The global-scale emissions and reactivity of dimethylsulfide (CH3SCH3, DMS) make it an integral component in the atmospheric sulfur cycle. DMS is rapidly oxidized in the atmosphere by a complex gas-phase mechanism involving many species and reactions. The resulting oxidized sulfur-bearing products are hygroscopic and interact with aerosols through condensation and secondary aerosol formation. Predictions of the impacts of DMS chemistry on aerosols and climate are inhibited by the poorly understood DMS oxidation mechanism. This thesis diagnoses the gas-phase connections between DMS and its oxidation products by simulating comprehensive DMS chemistry (approximately 50 reactions and 30 species) using three atmospheric models of varying size and complexity.

A diurnally-varying box model of the DMS cycle in the remote marine boundary layer is used to identify important DMS-related parameters and propagate parameter uncertainties to the sulfur-containing species. This analysis shows that the concentrations of DMS and sulfur dioxide (SO2) are sensitive to relatively few parameters. Moreover, the concentrations of DMS and SO2 are found to have factor of 2 uncertainties caused primarily (more than 60% of the variance) by uncertainties in DMS emissions and heterogeneous removal, respectively. In contrast, the concentrations of other products, such as sulfuric acid (H2SO4) and methanesulfonic acid (CH3SO3H, MSA), are found to be sensitive to many parameters and have larger uncertainties (factors of 2 to 7) resulting from multiple uncertain chemical and non-photochemical processes.

The DMS oxidation mechanism is quantitatively assessed using a one-dimensional column model constrained by high-frequency aircraft measurements from the First Aerosol Characterization Experiment (ACE-1). From this analysis, the baseline mechanism predicts DMS and SO2 concentrations in statistical agreement with the observations, yet it underestimates MSA concentrations by a factor of 104 to 105. These differences for MSA are statistically very significant and indicative of missing gas-phase reactions in the DMS mechanism. To reconcile these differences, five hypothetical MSA production paths are individually tested which greatly improve the model predictions to within a factor of 2 to 3 of the observations. Overall, the best improvement occurs when MSA is produced from the oxidation of methanesulfinic acid (CH3S(O)OH). Furthermore, the boundary layer model predictions of H2SO4 show improvement after an SO2-independent sulfuric acid production channel is added to the mechanism.

The DMS cycle is simulated in a global three-dimensional chemical transport model using, for the first time, comprehensive DMS oxidation chemistry. Four model cases are considered, which include two new comprehensive mechanisms and two parameterized schemes of 4 to 5 reactions taken from previous global sulfur models. The mole fractions of DMS, SO2, H2SO4, and MSA are compared between these four cases and with observations from the ACE-1 and PEM-Tropics A campaigns. Among the four cases, the calculated mole fractions of DMS and SO2 are largely invariant, while those for H2SO4 and MSA exhibit order-of-magnitude differences. These results indicate that H2SO4 and MSA are sensitive to the details of the mechanism, while DMS and SO2 are not. The comparisons between the model predictions and observations in the lower troposphere show reasonable agreement for DMS and SO2 (within a factor of 5), but larger disagreements for H2SO4 and MSA (factors of 5 to 30) due to the difficulty in constraining their sources and sinks. The four model cases, however, bound the H2SO4 and MSA measurements. Moreover, the comprehensive mechanisms provide a better match to the MSA observations.


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