Marine carbonyl sulfide (OCS) and carbon disulfide (CS 2 ): a compilation of measurements in seawater and the marine boundary layer

Carbonyl sulfide (OCS) and carbon disulfide ( CS 2 ) are volatile sulfur gases that are naturally formed in seawater and exchanged with the atmosphere. OCS is the most abundant sulfur gas in the atmosphere, and CS 2 is its most important precursor. They have attracted increased interest due to their...

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Bibliographic Details
Published in:Earth System Science Data
Main Authors: S. T. Lennartz, C. A. Marandino, M. von Hobe, M. O. Andreae, K. Aranami, E. Atlas, M. Berkelhammer, H. Bingemer, D. Booge, G. Cutter, P. Cortes, S. Kremser, C. S. Law, A. Marriner, R. Simó, B. Quack, G. Uher, H. Xie, X. Xu
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2020
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Online Access:https://doi.org/10.5194/essd-12-591-2020
https://doaj.org/article/ab56a40ac0f04798a247d3b8f3acc6d3
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Summary:Carbonyl sulfide (OCS) and carbon disulfide ( CS 2 ) are volatile sulfur gases that are naturally formed in seawater and exchanged with the atmosphere. OCS is the most abundant sulfur gas in the atmosphere, and CS 2 is its most important precursor. They have attracted increased interest due to their direct (OCS) or indirect ( CS 2 via oxidation to OCS) contribution to the stratospheric sulfate aerosol layer. Furthermore, OCS serves as a proxy to constrain terrestrial CO 2 uptake by vegetation. Oceanic emissions of both gases contribute a major part to their atmospheric concentration. Here we present a database of previously published and unpublished (mainly shipborne) measurements in seawater and the marine boundary layer for both gases, available at https://doi.org/10.1594/PANGAEA.905430 (Lennartz et al., 2019). The database contains original measurements as well as data digitalized from figures in publications from 42 measurement campaigns, i.e., cruises or time series stations, ranging from 1982 to 2019. OCS data cover all ocean basins except for the Arctic Ocean, as well as all months of the year, while the CS 2 dataset shows large gaps in spatial and temporal coverage. Concentrations are consistent across different sampling and analysis techniques for OCS. The database is intended to support the identification of global spatial and temporal patterns and to facilitate the evaluation of model simulations.