Top-down evaluation of matrix effects uncertainty

Abstract

Many measurements in chemistry are affected by matrix effects responsible for larger deviation between results from the analysis of various matrices than observed from the replicate analysis of the same matrix. The identification of cases where matrix effects are relevant is useful to know if measurement robustness to matrix effects can significantly reduce the measurement uncertainty, e.g. by performing time-consuming standard addition calibrations or additional matrix clean-up. This work presents a methodology to estimate the percentage contribution of matrix effects to the measurement uncertainty by comparing the intermediate precision estimated from the analysis of a sample with the dispersion of analyte recovery observed form the analyses of samples with different matrices. The measurement model was divide in two intervals of the studied quantity: Interval I between the limit of detection and two times the limit of quantification, where the absolute measurement uncertainty is constant, and Interval II above or equal to two times the limit of quantification where the relative measurement uncertainty is constant. The division of measurements scope in these intervals allowed the comparison of information collected at different values of the studied quantity. The developed methodology was successfully applied to the analysis of total Cr, Cu, Li, Mn and Zn using a procedure developed by OSPAR and acid extractable Ni and Pb according to the EPA3051A standard in marine sediments. Matrix effects are responsible for 7.7 to 79% of the global uncertainty. For Interval II, the relative expanded uncertainty ranged from 12% to 25% and is fit for the environmental monitoring of sediments according to the way the performance of laboratories is assessed in QUASIMEME proficiency tests. The developed measurement uncertainty models produced results compatible with reference values of one Certified Reference Material and 65 proficient test samples independent of the ones used to estimate the measurement uncertainty. The used data and performed calculations are presented in a user-friendly MS-Excel spreadsheet, available as Electronic Supplementary Material, that can be used for other determinations.