4.7 Article

Designing valid and optimised standard addition calibrations: Application to the determination of anions in seawater

Journal

TALANTA
Volume 142, Issue -, Pages 72-83

Publisher

ELSEVIER
DOI: 10.1016/j.talanta.2015.04.031

Keywords

Standard addition; Optimisation; Validation; Uncertainty; Ion chromatography; Seawater

Funding

  1. Fundacao para a Ciencia e a Tecnologia (FCT) [UID/QUI/00100/2013]

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A strategy for designing valid standard addition calibrations and for optimising their uncertainty is presented. The design of calibrations involves the development of models of the sensitivity and precision of the instrumental signal, in a wide range of analyte concentration (or any other studied quantity), and the definition of sample dilution and standard addition procedures that allow fulfilling the assumptions of the linear unweighted regression model in, typically, a smaller range of standard addition calibrations. Calibrators are prepared by diluting the sample and adding analyte with negligible uncertainty to fit in a concentration range where signals are homoscedastic. The minimisation of the uncertainty is supported on detailed measurement uncertainty models function of the calibrators preparation procedure and of analytical instrumentation performance. The number of collected signals replicates is defined by balancing their impact on the estimated expanded uncertainty, the resources needed and the target (maximum) uncertainty for the intended use of measurements. The calibration design strategy was successfully applied to the determination of the mass concentration (mg L-1) of Cl-, Br-, NO3- and SO4-2 in seawater by ion chromatography. A target expanded uncertainty of 20% was defined for the determination of Cl-, NO3- and SO4-2, or 40% for the determination of the smaller mass concentration of Br-. The developed measurement model produced reliable predictions of the measurement uncertainty from approximate concentration of the analyte in the sample, before its accurate quantification, thus proving optimisation is effective. Predictions are more prone to the variability of the measurement uncertainty estimation if based on low number of calibrators signals. The reported relative expanded uncertainty ranged from 7.1 % to 49%. (C) 2015 Elsevier B.V. All rights reserved.

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