Dimethyl sulfide in the summertime Arctic atmosphere: measurements and source sensitivity simulations
- 1Department of Chemistry, University of Toronto, Toronto, Canada
- 2Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada
- 3Québec-Océan, Department of Biology, Université Laval, Québec, Canada
- 4Sorbonne Universités, UPMC Univ. Paris 06, Université Versailles St-Quentin, CNRS/INSU, LATMOS-IPSL, Paris, France
- 5Air Quality Processes Research Section, Environment Canada, Toronto, Ontario, Canada
Abstract. Dimethyl sulfide (DMS) plays a major role in the global sulfur cycle. In addition, its atmospheric oxidation products contribute to the formation and growth of atmospheric aerosol particles, thereby influencing cloud condensation nuclei (CCN) populations and thus cloud formation. The pristine summertime Arctic atmosphere is strongly influenced by DMS. However, atmospheric DMS mixing ratios have only rarely been measured in the summertime Arctic. During July–August, 2014, we conducted the first high time resolution (10 Hz) DMS mixing ratio measurements for the eastern Canadian Archipelago and Baffin Bay as one component of the Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments (NETCARE). DMS mixing ratios ranged from below the detection limit of 4 to 1155 pptv (median 186 pptv) during the 21-day shipboard campaign. A transfer velocity parameterization from the literature coupled with coincident atmospheric and seawater DMS measurements yielded air–sea DMS flux estimates ranging from 0.02 to 12 µmol m−2 d−1. Air-mass trajectory analysis using FLEXPART-WRF and sensitivity simulations with the GEOS-Chem chemical transport model indicated that local sources (Lancaster Sound and Baffin Bay) were the dominant contributors to the DMS measured along the 21-day ship track, with episodic transport from the Hudson Bay System. After adjusting GEOS-Chem oceanic DMS values in the region to match measurements, GEOS-Chem reproduced the major features of the measured time series but was biased low overall (2–1006 pptv, median 72 pptv), although within the range of uncertainty of the seawater DMS source. However, during some 1–2 day periods the model underpredicted the measurements by more than an order of magnitude. Sensitivity tests indicated that non-marine sources (lakes, biomass burning, melt ponds, and coastal tundra) could make additional episodic contributions to atmospheric DMS in the study region, although local marine sources of DMS dominated. Our results highlight the need for both atmospheric and seawater DMS data sets with greater spatial and temporal resolution, combined with further investigation of non-marine DMS sources for the Arctic.