Assonov Sergey
Independent Researcher, Austria.
Isotopes Environ Health Stud. 2024 Jun;60(3):331-363. doi: 10.1080/10256016.2024.2355194. Epub 2024 Jun 12.
Comparing and combining stable isotope datasets from different laboratories and different years is essential for many research areas, such as isotope hydrology, greenhouse gas observations, food studies, isotope forensics, palaeo-reconstructions, etc. Data compatibility (i.e. the ability to combine data) is related to the data quality. The prerequisite for data comparability is data normalization to a common stable isotope scale (often referred to as calibration) based on reliable reference materials (RMs) with accurately assigned values and uncertainties. Still, that does not guarantee the data compatibility (mutual agreement). Albeit metrological concepts related to data compatibility and measurement uncertainty have been developed and applied to analytical chemistry in general, these concepts have not yet been fully applied to stable isotope research. This can affect daily calibrations, analytical data and, therefore, data compatibility. In addition, IRMS users often prepare different laboratory standards themselves. Thereafter, users should then understand the contemporary concepts used for assigning RM value and uncertainty, as well as the limitations and potential problems associated with RMs. The history of RMs, preparation reports and also some problems in the past provide lessons to be learned. These include the C drift of LSVEC (the second anchor on the C scale before 2017), revisions to the value assignment principles, the introduction of replacements for LSVEC, related disputes and the potential underestimation of uncertainties for secondary RMs. The review describes metrological concepts related to isotopic scales, RMs and calibration hierarchies and data compatibility. The main RMs and their uncertainties are reviewed through the lens of metrology concepts. Additional focus is given to the VPDB scale for C and issues of scale discontinuity, which can significantly reduce data compatibility in C. The given examples of value and uncertainty assignment for RMs should be viewed as an example of value and uncertainty calculation in daily practice.
对于许多研究领域而言，比较和整合来自不同实验室、不同年份的稳定同位素数据集至关重要，比如同位素水文学、温室气体观测、食品研究、同位素法医鉴定、古重建等。数据兼容性（即整合数据的能力）与数据质量相关。数据可比性的前提是基于具有准确赋值和不确定度的可靠参考物质（RM），将数据归一化到通用的稳定同位素标度（通常称为校准）。然而，这并不能保证数据兼容性（相互一致性）。尽管与数据兼容性和测量不确定度相关的计量学概念已得到发展并普遍应用于分析化学，但这些概念尚未完全应用于稳定同位素研究。这可能会影响日常校准、分析数据，进而影响数据兼容性。此外，同位素比值质谱（IRMS）用户通常自己制备不同的实验室标准物质。因此，用户应该了解用于赋予参考物质值和不确定度的当代概念，以及与参考物质相关的局限性和潜在问题。参考物质的历史、制备报告以及过去出现的一些问题都能提供经验教训。这些包括LSVEC（2017年之前碳标度上的第二个基准）的碳漂移、值赋值原则的修订、LSVEC替代品的引入、相关争议以及二级参考物质不确定度的潜在低估。本综述描述了与同位素标度、参考物质、校准层次结构和数据兼容性相关的计量学概念。通过计量学概念的视角对主要参考物质及其不确定度进行了综述。额外关注了碳的维也纳盆地白垩标准（VPDB）标度以及标度不连续性问题，这可能会显著降低碳数据的兼容性。所给出的参考物质值和不确定度赋值示例应被视为日常实践中值和不确定度计算的一个例子。
