Instituto Hidrográfico, Rua das Trinas, 49, 1249-093, Lisboa, Portugal; Centro de Química Estrutural, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-01, Lisboa, Portugal.
Instituto Hidrográfico, Rua das Trinas, 49, 1249-093, Lisboa, Portugal.
Anal Chim Acta. 2021 Aug 29;1175:338732. doi: 10.1016/j.aca.2021.338732. Epub 2021 Jun 5.
Many chemical analyses involve a complex sample preparation, and some, based on an instrumental method of analysis such as spectrometric or chromatographic methods, are affected by matrix effects. The objective interpretation of the results of these analyses performed in the framework of a research or a conformity assessment requires quantifying the measurement uncertainty. This work presents a novel methodology for the bottom-up modelling of the performance of complex analytical operations, such as sample digestion or extraction, by the Monte Carlo simulation of their performance independently of the performance of the other analytical steps. The simulation of between-days precision of complex sample preparation and mean measurement error observed from the analysis of various reference materials and their combination with models of instrumental quantification performance allow the detailed modelling of the measurement uncertainty. The developed methodology adapts to the complex distribution of observed measurement performance data avoiding the under evaluation of the measurement uncertainty by assuming the normal distribution of systematic and random effects. The developed methodology was successfully applied to the determination of total or acid-extractable As (following OSPAR or EPA 3051A methods, respectively) in sediments where measurement trueness was assessed from the analysis of one Certified Reference Material and two spiked samples. The evaluated uncertainty is fit for environmental monitoring considering performance criteria defined for Quasimeme proficiency tests. The developed measurement models were successfully cross-validated by randomly extracting data from the validation set subsequently used to check the compatibility between estimated and reference values for 95% or 99% confidence level. The observed success rate of these assessments is compatible with the confidence level of the tests.
许多化学分析涉及复杂的样品制备,而有些分析则基于仪器分析方法,如光谱或色谱方法,会受到基质效应的影响。在研究或一致性评估框架内进行这些分析的结果的客观解释需要量化测量不确定度。这项工作提出了一种新的方法学,用于通过对其性能进行独立于其他分析步骤的蒙特卡罗模拟,自上而下地对复杂分析操作(如样品消解或提取)的性能进行建模。通过对复杂样品制备的日间精密度和从各种参考材料的分析中观察到的平均测量误差的模拟,以及与仪器定量性能模型的结合,可以对测量不确定度进行详细建模。所开发的方法学适应观察到的测量性能数据的复杂分布,避免通过假设系统和随机效应的正态分布来低估测量不确定度。该方法学已成功应用于沉积物中总砷或酸可提取砷(分别遵循 OSPAR 或 EPA 3051A 方法)的测定,其中测量准确度是通过对一个认证参考物质和两个加标样品的分析来评估的。所评估的不确定度适用于环境监测,考虑了针对 Quasimeme 能力验证定义的性能标准。通过从验证集中随机提取数据并随后用于检查估计值和参考值之间的兼容性,成功地对所开发的测量模型进行了交叉验证,置信水平为 95%或 99%。这些评估的观察成功率与测试的置信水平兼容。