Experimental assessment of EAIRMS normalization methodologies for environmental stable isotopes
Sawyer Balint1*, Morgan Schwartz2*, Drew Fowler3†, Stella Linnekogel4†, Sáde Cromratie Clemons5, Laura K. Burkemper6
1ORISE Participant, U.S. EPA Atlantic Coastal Environmental Sciences Division, Narragansett, RI. 02882
2U.S. EPA Atlantic Coastal Environmental Sciences Division, Narragansett, RI. 02882
3U.S. Geological Survey, Louisiana Cooperative Fish and Wildlife Research Unit, Baton Rouge, LA. 70810
4UK Centre for Ecology & Hydrology Lancaster, Library Avenue, Bailrigg, Lancaster, LA1 4AP, United Kingdom
5Department of Geography, University of Boulder, Boulder, CO
6Center for Stable Isotopes, University of New Mexico, Albuquerque, NM
* Authors share first authorship
Authors contributed equally to this manuscript
Corresponding Author :
Sawyer Balint
sjbalint@bu.edu
(518) 258-9510
Morgan Schwartz schwartz.morgan@epa.gov
(401) 782-9624
CRediT author statement :
Sawyer Balint : Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data Curation, Writing – Original Draft, Visualization, Supervision, Project administration.
Morgan Schwartz : Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data Curation, Writing – Original Draft, Supervision, Project administration.
Drew Fowler : Conceptualization, Methodology, Investigation, Writing – Review & Editing.
Stella Linnekogel : Conceptualization, Methodology, Investigation, Writing – Review & Editing.
Sáde Cromratie Clemons: Conceptualization, Methodology, Investigation, Writing – Review & Editing.
Laura K. Burkemper: Conceptualization, Methodology, Validation, Investigation, Resources, Data Curation, Writing – Review & Editing, Supervision, Project administration.

Acknowledgements:

The authors would like to thank Viorel Atudorei, Seth Newsome, and Zachary Sharp for their assistance in the planning and execution of IsoCamp 2022, where the experimental design for this project was conceived. Additionally, the authors thank Renee Brooks, Michaela Cashman, and Autumn Oczkowski for review and feedback on the manuscript. Stella Linnekogel (UKCEH) acknowledges support from the NERC project Diurnal Variation in Soil Nitrous oxide Emissions (DIVINE): drivers and mechanisms (NE/V000837/1). This article has been subjected to Agency review and has been approved for publication. This work was supported in part by an appointment to the Research Participation Program at the Office for Research and Development, Center for Environmental Measurement and Modelling, Atlantic Coastal Environmental Sciences Division, U.S. Environmental Protection Agency (U.S. EPA), administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and U.S. EPA. The views expressed in this presentation are those of the authors and do not necessarily represent the views or polices of the U.S. EPA. This article has been peer reviewed and approved for publication consistent with USGS Fundamental Science Practices (https://pubs.usgs.gov/circ/1367/). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Abstract

RATIONALE : In stable isotope mass spectrometry, isotope values are normalized to internationally recognized reference scales using certified reference materials and working standards. Numerous techniques exist for performing this normalization, but these methodologies need to be experimentally assessed to compare their impact on reproducibility of isotope results.
METHODS : We tested normalization methods by the number of standards used, their matrix, their isotope range, and whether normalization required extrapolating beyond the isotope range. Using 8 certified reference materials and 5 working standards on a ThermoFinnigan Delta-V IRMS and Elementar VisION IRMS for nitrogen and carbon isotope composition via solid combustion with an elemental analyzer, we computed every possible isotope normalization (n=6272). Additionally, we assessed how sample matrix impacted linearity effects on both instruments.
RESULTS : Normalizations composed of three or four reference materials had better performance than one-point and two-point methods, especially when the normalization was matrix-mixed or extrapolated, and normalizations with an isotope range greater than 15‰ were more accurate under these conditions. Normalizations that were matrix-matched and were not extrapolated exhibited the highest accuracy. Linearity effects were found to exceed instrument precision by two orders of magnitude irrespective of sample matrix and were not predicted by reference gas diagnostics.
CONCLUSIONS : To maximize interlaboratory comparability of isotope results, operators of EAIRMS systems should use at least 3 calibration standards to construct their normalizations, select standards with a large isotope range to avoid extrapolation, and match the matrix of their standards to their samples to the best extent possible.

Stable isotope mass spectrometry is a growing tool across disciplines, including in biology where the nitrogen (N) and carbon (C) isotope composition of solid samples are routinely used for investigating a variety of physiological, ecological, and biogeochemical questions1. In recent decades, the broad applications of stable isotopes combined with faster and more accessible instrumentation have led to a large growth in the utilization and publication of stable isotope measurements as they relate to the natural sciences2. Despite the growing importance of this tool, immense variations in analytical methodology exist within the field, leading to poor interlaboratory comparability3and complicating the interpretation and reproducibility of scientific studies that use stable isotopes4.
Continuous flow stable isotope mass spectrometry5 via solid combustion6,7 is the predominant analytical technique used to quantify the C and N isotope composition of solid samples for biological applications2. Samples are delivered to the isotope ratio mass spectrometer (IRMS) in a gaseous form through a peripheral elemental analyzer (EA) and the isotope composition is determined relative to a working gas that is injected sequentially with the sample gas8,9. This methodology allows for high precision measurements, but to facilitate interlaboratory comparison the results must be normalized to internationally referenced isotope scales10-12. Contemporary normalization methods call for standard reference materials to be processed identically to the unknown samples using the “identical treatment” principle5,13, and analyzed in tandem with unknown samples14-16, a normalization curve is then computed with a least-squares linear regression17. As the number of available certified standards has increased in recent decades18-20, operators now have a multitude of certified standards to choose from when performing their isotope normalizations in addition to their own working standards.
Unfortunately, the reproducibility of normalization techniques has not advanced at the same pace as the expanding use of stable isotopes. Although modeling work has suggested that normalization error generally decreases with the number of standards21, stable isotope laboratories vary immensely in the number of standards used due in part to limited experimental assessments of related normalization error. Furthermore, users of elemental analyzer isotope ratio mass spectrometry (EAIRMS) for biological applications often analyze sample matrixes for which certified reference materials do not exist (e.g., sediment22, marine algae23, samples imbedded on glass fiber filters24), but the impact of mixing organic matrixes between samples and standards on normalization accuracy is unknown. Whether standards should be selected to maximize isotope range or closely bracket the unknown samples is another decision that, absent of an experimental assessment across a variety of normalization methods, is left to anecdotal procedures that may vary between laboratories. Some analyses, such as those that incorporate N tracer as part of the methodology25, may require extrapolation beyond the range of the normalization curve – again with unknown consequences. Ultimately, readers of studies that incorporate stable isotopes are left to determine the reproducibility of the study for themselves – assuming the particulars of the normalization are even included in the methods. This matter becomes increasingly more difficult in the era of big data and meta-analysis, as multiple studies using multiple methods are integrated and consequently compared directly.
Here, we aim to better quantify best normalizations practices for EAIRMS analysis using an experimental assessment of a variety of normalization methods using certified reference materials analyzed on two instrument systems in two laboratories. We specifically assess how the accuracy of the normalization is impacted by the number of standards, their matrix relative to the unknown samples, their isotope range, and whether the normalization requires extrapolation beyond the isotope range. We further investigate how instrument linearity effects are impacted by sample matrix through the first known interlaboratory comparison of EAIRMS linearity effects. By developing a refined understanding of EAIRMS best practices, we hope to better facilitate the reproducibility of biological stable isotope applications.

Number of standards used to construct the normalization

Although a variety of methodologies have been used to normalize results from isotope ratio mass spectroscopy8,15, this work focuses on the most common methods used in continuous flow applications: one-point anchoring, two-point linear normalization, or multipoint linear normalization 2,17. Typically, the IRMS software will perform a one-point anchoring relative to the working gas according to the following equations: