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Dimethylsulfide Chemistry: Annual, Seasonal, and Spatial Impacts on Sulfate
Citation:
Sarwar, G., J. Xing, K. Fahey, K. Foley, David-C Wong, R. Mathur, C. Gan, B. Gantt, AND H. Simon. Dimethylsulfide Chemistry: Annual, Seasonal, and Spatial Impacts on Sulfate. Air Pollution Modeling and its Application XXV. Springer International Publishing AG, Cham (ZG), Switzerland, , 347-352, (2017).
Impact/Purpose:
This Work is a collection of selected papers presented at the 35th International Technical Meeting on Air Pollution Modeling and its Application, held in Chania (Crete), Greece, Oct 3-7, 2016. Current developments in air pollution modelling are explored as a series of contributions from researchers at the forefront of their field. This newest contribution on air pollution modelling and its application is focused on local, urban, regional and intercontinental modelling; long term modelling and trend analysis; data assimilation and air quality forecasting; model assessment and evaluation; aerosol transformation. Additionally, this work also examines the relationship between air quality and human health and the effects of climate change on air quality.
Description:
We incorporated oceanic emissions and atmospheric chemistry of dimethylsulfide (DMS) into the hemispheric Community Multiscale Air Quality model and performed annual model simulations without and with DMS chemistry. The model without DMS chemistry predicts higher concentrations of sulfate (SO2−4)(SO42−) over land compared to the low concentrations over seawater. Including DMS chemistry substantially increases (SO2−4)(SO42−) concentrations over seawater and many coastal areas. It enhances the annual mean surface (SO2−4)(SO42−) by >0.8 μg/m3 in some areas of the Pacific Ocean, Atlantic Ocean, Arabian Sea, and Caribbean Sea. The largest enhancement occurs in summer in which DMS chemistry increases surface SO2−4SO42− by 70% over seawater. The model without DMS chemistry underestimates the summer-time observed SO2−4SO42− in the U.S. while the model with DMS chemistry improves model performance in the U.S. coastal areas.
