Johnson J E, Hamann L, Dettman D L, Kim-Hak D, Leavitt S W, Monson R K, Papuga S A
Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA.
Department of Global Ecology, Carnegie Institution, 260 Panama Street, Stanford, CA, 94305, USA.
Rapid Commun Mass Spectrom. 2017 Mar 30;31(6):547-560. doi: 10.1002/rcm.7813.
Induction module cavity ring-down spectroscopy (IM-CRDS) has been proposed as a rapid and cost-effective alternative to cryogenic vacuum distillation (CVD) and isotope ratio mass spectrometry (IRMS) for the measurement of δ O and δ H values in matrix-bound waters. In the current study, we characterized the performance of IM-CRDS relative to CVD and IRMS and investigated the mechanisms responsible for differences between the methods.
We collected a set of 75 soil, stem, and leaf water samples, and measured the δ O and δ H values of each sample with four techniques: CVD and IRMS, CVD and CRDS, CVD and IM-CRDS, and IM-CRDS alone. We then calculated the isotopic errors for each of the three CRDS methods relative to CVD and IRMS, and analyzed the relationships among these errors and suites of diagnostic spectral parameters that are indicative of organic contamination.
The IM-CRDS technique accurately assessed the δ O and δ H values of pure waters, but exhibited progressively increasing errors for soil waters, stem waters, and leaf waters. For soils, the errors were attributable to subsampling of isotopically heterogeneous source material, whereas for stems and leaves, they were attributable to spectral interference. Unexpectedly, the magnitude of spectral interference was higher for the solid samples analyzed directly via IM-CRDS than for those originally extracted via CVD and then analyzed by IM-CRDS.
There are many types of matrix-bound water samples for which IM-CRDS measurements include significant errors from spectral interference. As a result, spectral analysis and validation should be incorporated into IM-CRDS post-processing procedures. In the future, IM-CRDS performance could be improved through: (i) identification of the compounds that cause spectral interference, and either (ii) modification of the combustion step to completely oxidize these compounds to CO , and/or (iii) incorporation of corrections for these compounds into the spectral fitting models used by the CRDS analyzers. Copyright © 2016 John Wiley & Sons, Ltd.
感应模块腔衰荡光谱法（IM-CRDS）已被提议作为低温真空蒸馏（CVD）和同位素比率质谱法（IRMS）的一种快速且经济高效的替代方法，用于测量基质结合水中的δO和δH值。在本研究中，我们对IM-CRDS相对于CVD和IRMS的性能进行了表征，并研究了导致这些方法之间差异的机制。
我们收集了一组75个土壤、茎和叶水样本，并用四种技术测量了每个样本的δO和δH值：CVD和IRMS、CVD和CRDS、CVD和IM-CRDS以及单独的IM-CRDS。然后，我们计算了三种CRDS方法相对于CVD和IRMS的同位素误差，并分析了这些误差与指示有机污染的诊断光谱参数组之间的关系。
IM-CRDS技术准确评估了纯水的δO和δH值，但对于土壤水、茎水和叶水，误差逐渐增加。对于土壤，误差归因于同位素异质源材料的二次采样，而对于茎和叶，误差归因于光谱干扰。出乎意料的是，直接通过IM-CRDS分析的固体样品的光谱干扰幅度高于最初通过CVD提取然后通过IM-CRDS分析的样品。
有许多类型的基质结合水样本，对于这些样本，IM-CRDS测量存在来自光谱干扰的显著误差。因此，光谱分析和验证应纳入IM-CRDS后处理程序。未来，IM-CRDS的性能可以通过以下方式提高：（i）识别引起光谱干扰的化合物，以及（ii）修改燃烧步骤以将这些化合物完全氧化为CO，和/或（iii）将这些化合物的校正纳入CRDS分析仪使用的光谱拟合模型中。版权所有©2016约翰威立父子有限公司。
