Evaluation of Uncertainty in the Determination of Lead in Blood by Anodic Stripping Voltammetry, Applying the Weighted Calibration Model of Standard Addition Generated by Monte Carlo Simulation

Abstract

The present work aims to demonstrate that the evaluation of the uncertainty in the determination of lead in blood by anodic stripping voltammetry, applying the weighted linear regression analysis by standard addition and generated by Monte Carlo simulation, is more consistent with the experimental results obtained. with those obtained by applying the classical approach based on the law of propagation of uncertainty. For the first case, the program was developed in Maple 13, based on the algorithm obtained from Supplement 1 of the GUM 2008 guide, taking into account both the uncertainties in the readings of the instrumental signal and those involved in the preparation of the concentrations of the calipers. The characteristic values ​​of lead for a blood sample were: 3.02 μg/dL, with an uncertainty of 0.15 μg/dL, with a coverage interval of 2.74 μg/dL to 3.29 μg/dL. The results obtained by applying the uncertainty propagation law from the classical weighted calibration model were the following: 3.08 μg/dL, uncertainty 0.042, coverage interval from 3.00 to 3.16 μg/dL. It was observed that there is greater uncertainty in the numerical method. However, they are consistent with experimental results from a blood sample