Using Sequential Injection Analysis to Improve System and Data Reliability of Online Methods: Determination of Ammonium and Phosphate in Coastal Waters
Author(s) -
Carsten Frank,
Friedhelm Schroeder
Publication year - 2007
Publication title -
journal of automated methods and management in chemistry
Language(s) - English
Resource type - Journals
eISSN - 1464-5068
pISSN - 1463-9246
DOI - 10.1155/2007/49535
Subject(s) - computer science , reliability (semiconductor) , algorithm , data mining , machine learning , thermodynamics , power (physics) , physics
This article summarises the advantages of the sequential injection analysis (SIA) for the online determination of nutrients in coastal waters. It concentrates on techniques to improve the reliability of the gained data by continuously monitoring one or more standards and on the advantages of online standard additions and offline determination of manually collected samples with the online SIA system. These measures are advantageous during method development and validation and can be used to verify the system performance on a regular base to reduce the amount of erroneous results. No changes in the flow system are necessary and the sample throughput is only slightly reduced. These techniques have been applied to a SIA system which is able to simultaneously determine ammonium and phosphate at a rate of more than 100 samples per hour each and detection limits (3sigma) of 0.06 muM and 0.05 muM. Results from a campaign in summer 2005 are shown.
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