Progress and challenges in dual- and triple-isotope (δ O, δ H, Δ O) analyses of environmental waters: An international assessment of laboratory performance.

Rationale: Stable isotope analyses of environmental waters (δ H, δ O) are an important assay in hydrology and environmental research with rising interest in δ O, which requires ultra-precise assays. We evaluated isotope analyses of six test water samples for 281 laboratory submissions measuring δ H and δ O along with a subset analyzing δ O and Δ O by laser spectrometry and isotope ratio mass spectrometry (IRMS).

Methods: Six test waters were distributed to laboratories spanning a wide δ range of natural waters for δ H, δ O and δ O and Δ O. One sample was a blind duplicate to test reproducibility and claims of analytical precision.

Results: Results showed that ca 83% of the submissions produced acceptable δ O and δ H results within 0.2‰ (mUr) and 1.6‰ of the benchmark values, respectively. However, 17% of the submissions gave questionable to unacceptable results. A blind duplicate revealed many laboratories reported overly optimistic precision, and many could not replicate within their claimed precision. For Δ O, dual-inlet results for IRMS using quantitative O conversion were accurate and highly precise, but the results for laser spectrometry ranged by ca 200 per meg (μUr) for each sample, with ca 70% unable to replicate the duplicate to their claimed Δ O precision. One complicating factor is the lack of certified primary reference waters for δ O.

Conclusions: No single factor or combination of factors was identifiable for poor or good performance, and underperformance came from issues like data normalization including inadequate memory and drift corrections, compromised working reference materials and underperforming instrumentation. We recommend isotope laboratories include high and low δ value controls of known isotope composition in each run. Progress in Δ O analyses by laser spectrometry requires extraordinary proof of performance claims and would benefit from the development of adoptable and systematic advanced data processing procedures to correct for memory and drift.