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This paper considers the drop-time technique in electrocapillary measurements and focuses on calibration methods required to convert the drop-time t of a mercury electrode into the value of the interfacial tension γ. The relationships between t and γ, described in the literature, are reviewed and six calibration methods identified. On the basis of high-precision drop-time electrocapillary measurements carried out in 0.1 mol l−1 KCl aqueous solution, with γ values known from the absolute measurement method, the performance of the calibration methods, expressed in terms of measurement bias and uncertainty, is evaluated and compared. Better performance is observed for the methods that involve a nonlinear model such as γ=αtβ fitted to calibration data, instead of a single-point linear calibration commonly used. The measurement uncertainty U ⩽ 0.12 mN m−1 evaluated with these advanced calibration approaches corresponds to the level of accuracy achieved with the classical capillary electrometer.

The rational strategy in the evaluation of analytical measurement uncertainty is to combine the “whole method” performance data, such as precision and recovery, with the uncertainty contributions from sources not adequately covered by those data. This paper highlights some common mistakes in evaluating the uncertainty when pursuing that strategy, as revealed in current chromatographic literature. The list of the uncertainty components usually taken into account is discussed first and fallacies with the LOD- and recovery uncertainties are noted. Close attention is paid to the uncertainty arising from a linear calibration normally used. It is demonstrated that following a well-known formula for the standard deviation of an analytical result obtained from a straight line calibration leads to double counting the precision contribution to the uncertainty budget. Furthermore, the precision component itself is often estimated improperly, based on the number of replicates taken from the precision assessment experiment. As a result, the relative uncertainty from linear calibration is overestimated in the budget and may become the largest contribution to the combined uncertainty, which is clearly shown with an example calculation based on the literature data.