Volume 35, Issue 15 e9118
RESEARCH ARTICLE

Organic contamination detection for isotopic analysis of water by laser spectroscopy

Cody Millar

Corresponding Author

Cody Millar

Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, 11 Innovation Boulevard, Saskatoon, SK, S7N 3H5 Canada

Correspondence

C. Millar, Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, 11 Innovation Boulevard, Saskatoon, SK, S7N 3H5, Canada.

Email: [email protected]

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Kim Janzen

Kim Janzen

Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, 11 Innovation Boulevard, Saskatoon, SK, S7N 3H5 Canada

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Magali F. Nehemy

Magali F. Nehemy

Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, 11 Innovation Boulevard, Saskatoon, SK, S7N 3H5 Canada

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Geoff Koehler

Geoff Koehler

NHRC Stable Isotope Laboratory, Environment and Climate Change Canada, 11 Innovation Boulevard, Saskatoon, SK, S7N 3H5 Canada

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Pedro Hervé-Fernández

Pedro Hervé-Fernández

Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, 11 Innovation Boulevard, Saskatoon, SK, S7N 3H5 Canada

Instituto de la Patagonia, Departamento de Hidrobiología, Universidad de Magallanes, Punta Arenas, Chile

Facultad de Ciencias Liberales, Universidad Adolfo Ibañez, Viña del Mar, Chile

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Jeffrey J. McDonnell

Jeffrey J. McDonnell

Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, 11 Innovation Boulevard, Saskatoon, SK, S7N 3H5 Canada

School of Geography, Earth & Environmental Sciences, University of Birmingham, Birmingham, UK

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First published: 03 May 2021
Citations: 10

Abstract

Rationale

Hydrogen and oxygen stable isotope ratios (δ2H, δ17O, and δ18O values) are commonly used tracers of water. These ratios can be measured by isotope ratio infrared spectroscopy (IRIS). However, IRIS approaches are prone to errors induced by organic compounds present in plant, soil, and natural water samples. A novel approach using 17O-excess values has shown promise for flagging spectrally contaminated plant samples during IRIS analysis. A systematic assessment of this flagging system is needed to prove it useful.

Methods

Errors induced by methanol and ethanol water mixtures on measured IRIS and isotope ratio mass spectrometry (IRMS) results were evaluated. For IRIS analyses both liquid- and vapour-mode (via direct vapour equilibration) methods are used. The δ2H, δ17O, and δ18O values were measured and compared with known reference values to determine the errors induced by methanol and ethanol contamination. In addition, the 17O-excess contamination detection approach was tested. This is a post-processing detection tool for both liquid and vapour IRIS triple-isotope analyses, utilizing calculated 17O-excess values to flag contaminated samples.

Results

Organic contamination induced significant errors in IRIS results, not seen in IRMS results. Methanol caused larger errors than ethanol. Results from vapour-IRIS analyses had larger errors than those from liquid-IRIS analyses. The 17O-excess approach identified methanol driven error in liquid- and vapour-mode IRIS samples at levels where isotope results became unacceptably erroneous. For ethanol contaminated samples, a mix of erroneous and correct flagging occurred with the 17O-excess method. Our results indicate that methanol is the more problematic contaminant for data corruption. The 17O-excess method was therefore useful for data quality control.

Conclusions

Organic contamination caused significant errors in IRIS stable isotope results. These errors were larger during vapour analyses than during liquid IRIS analyses, and larger for methanol than ethanol contamination. The 17O-excess method is highly sensitive for detecting narrowband (methanol) contamination error in vapour and liquid analysis modes in IRIS.

PEER REVIEW

The peer review history for this article is available at https://publons.com/publon/10.1002/rcm.9118.

DATA AVAILABILITY STATEMENT

The authors confirm that the data supporting the findings of this study are available within the article and on request from the corresponding authour: CM.