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A methodology for the worst case measurement uncertainty estimation for analytical methods which include an instrumental quantification step, adequate for routine determinations, is presented. Although the methodology presented should be based on a careful evaluation of the analytical method, the resulting daily calculations are very simple. The methodology is based on the estimation of the maximum value for the different sources of uncertainty and requires the definition of limiting values for certain analytical parameters. The simplification of the instrumental quantification uncertainty estimation involves the use of the standard deviation obtained from control charts relating to the concentrations estimated from the calibration curves for control standards at the highest calibration level. Three levels of simplification are suggested, as alternatives to the detailed approach, which can be selected according to the proximity of the sample results to decision limits. These approaches were applied to the determination of pesticide residues in apples (CEN, EN 12393), for which the most simplified approach showed a relative expanded uncertainty of 37.2% for a confidence level of approximately 95%.

The expression of results with an uncertainty through the “bottom-up” approach, involving the estimation and combination of all the sources of uncertainty, represents a challenge when the analytical method includes mass transfer steps (MTS). These steps (e.g. extraction, evaporation, digestion, etc.) with inherently different from 100% recoveries lack models capable of describing their precision and efficiency. Recently, a new methodology was published aimed at the estimation of the performance of these critical steps. Comparison of the experimental dispersion from the replicated analysis of spiked samples with the combination of the uncertainty associated with gravimetric, volumetric and instrumental quantification steps (described by well established models) allows the estimation of the MTS uncertainty. Evaluation of the behaviour of the MTS within the analytical range supports the use of developed estimations over a wide concentration range. This methodology was applied, with success, to the determination of pesticide residues in melon in one particular proficiency test organised by the Food Analysis Performance Assessment Scheme (FAPAS) between November 2000 and February 2001.

A ‘bottom-up’ approach for the expression of results obtained from analytical methods that include analytical steps with recovery inherently different from 100% [mass transfer steps (MTS): extraction, evaporation, clean-up procedures, digestion, etc.] is presented. The estimation of the combination of all MTS uncertainty involves the comparison of the experimental dispersion of replicated analyses of spiked samples with the estimation of the uncertainty obtained for the combination of all uncertainty sources except MTS ones (‘incomplete’ estimation). The estimation of MTS uncertainty by difference is performed after evaluating the statistical difference between the ‘incomplete’ estimation and the experimental dispersion (F-test). When the two estimations are statistically equivalent, the MTS uncertainty is considered to be negligible in relation to the other sources budget. The assumption of constancy of MTS performance within the analytical range is tested through single analyses at several concentration levels and is evaluated by the inclusion of the expected values at the intervals resulting from the combination of the MTS uncertainty estimation performed at one concentration level and the ‘incomplete’ estimation. The developed methodology can also be useful for method optimisation and validation and for the detection of small trends in results. The determination of pesticides in sweet peppers by GC-NPD was used to explore the above concepts.