User-friendly spreadsheet for implementing international guidance on the evaluation of measurement uncertainty
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Updated: Oct 30, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Ricardo J N Bettencourt da Silva1
1Centro de Química Estrutural, Institute of Molecular Sciences, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Lisboa, 1749-016, Portugal.
Abstract:
The objective interpretation of quantitative chemical parameters determined in an analysed item or sample requires probabilistic modelling of how close the measured value is to the "true" value of the quantity. This evaluation involves calculating the combined effects of random and systematic influences on the measured value, typically expressed as a "measured value" ± "expanded uncertainty" at a specified confidence level. Although this need is widely recognised, the lack of user-friendly tools for sound evaluations of measurement uncertainty has delayed the contribution that measurement science can make to many research and development areas. Recently, a new Eurachem/CITAC guide on the evaluation of measurement uncertainty has described how data collected during in-house method validation, namely precision and recovery data, can be used to accurately assess the impact of all relevant effects on the measurements. The guide covers how to model the variation of measurement uncertainty with the measured value and how to handle inconsistencies in recovery observed in the analysis of various reference materials. The guide presents a comprehensive framework for evaluating the uncertainty of measurements in chemistry, in which tools for optimising the measurement can be used to meet the most demanding requirements for accuracy and uncertainty. To promote the dissemination and easy application of this relevant guidance, a user-friendly MS Excel spreadsheet is provided. Application examples of the spreadsheet for different types of tests in chemistry, namely the determination of soil pH and fluoranthene in river sediments, are presented. The examples illustrate how to handle inconsistencies in experimental data and include the quality control of the analysis.
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