Global oceanic DMS data inter-comparability View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-10-08

AUTHORS

T. G. Bell, G. Malin, G. A. Lee, J. Stefels, S. Archer, M. Steinke, P. Matrai

ABSTRACT

The global surface seawater dimethylsulphide (DMS) database (http://saga.pmel.noaa.gov/dms/) contains >50,000 data points and is the second largest trace gas database after carbon dioxide. However, there has been relatively little quality control on the data that have been collated to date. Furthermore, the recent development of technologies capable of high frequency (>1 Hz) DMS measurements will have a disproportionate effect on the database in future years. At this juncture, the comparability of analytical techniques, sample handling methodologies and standards are pressing issues that the DMS community needs to address. In October 2010, during the Fifth International Symposium on Biological and Environmental Chemistry of DMS(P) and Related Compounds held in Goa, India, attendees participated in a discussion concerning the current DMS database and its future development. We develop some of the ideas from that session and combine them with available data. From the few inter-comparison exercises that have been conducted we show that variability between existing measurements within the DMS database is likely to be ≤25%. Tests comparing different DMSP·HCl standards demonstrate that a reference calibration standard would be beneficial for the DMS community. Confidence in future data collation would be substantially improved with a comprehensive inter-comparison experiment between new analytical techniques and sampling methodologies (e.g., mass spectrometers with equilibrators attached to a continuous flow of seawater) and more established methods (i.e., filtered samples analysed with purge and trap gas chromatography). We conclude with recommendations for the future expansion of the DMS database and its data quality control. More... »

PAGES

147-161

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10533-011-9662-3

DOI

http://dx.doi.org/10.1007/s10533-011-9662-3

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https://app.dimensions.ai/details/publication/pub.1052011845


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