Optimization of a Picarro L2140-i cavity ring-down spectrometer for routine measurement of triple oxygen isotope ratios in meteoric waters

<p>The demanding precision of triple oxygen isotope (<span class="inline-formula">Δ¹⁷</span>O) analyses in water has restricted their measurement to dual-inlet mass spectrometry until the recent development of commercially available infrared laser analyzers. Laser-based measurements of triple oxygen isotope ratios are now increasingly performed by laboratories seeking to better constrain the source and history of meteoric waters. However, in practice, these measurements are subject to large analytical errors that remain poorly documented in scientific literature and by instrument manufacturers, which can effectively restrict the confident application of <span class="inline-formula">Δ¹⁷</span>O to settings where variations are relatively large (<span class="inline-formula">∼</span> 25–60 per meg). We present our operating method of a Picarro L2140-i cavity ring-down spectrometer (CRDS) during the analysis of low-latitude rainwater where confidently resolving daily variations in <span class="inline-formula">Δ¹⁷</span>O (differences of <span class="inline-formula">∼</span> 10–20 per meg) was desired. Our approach was optimized over <span class="inline-formula">∼</span> 3 years and uses a combination of published best practices plus additional steps to combat spectral contamination of trace amounts of dissolved organics, which, for <span class="inline-formula">Δ¹⁷</span>O, emerges as a much more substantial problem than previously documented, even in pure rainwater. We resolve the extreme sensitivity of the <span class="inline-formula">Δ¹⁷</span>O measurement to organics through their removal via Picarro's micro-combustion module, whose performance is evaluated in each sequence using alcohol-spiked standards. While correction for sample-to-sample memory and instrumental drift significantly improves traditional isotope metrics, these corrections have only a marginal impact (0–1 per meg error reduction) on <span class="inline-formula">Δ¹⁷</span>O. Our post-processing scheme uses the analyzer's high-resolution data, which improves <span class="inline-formula"><i>δ</i>²</span>H measurement (0.25 ‰ error reduction) and allows for much more rich troubleshooting and data processing compared to the default user-facing data output. In addition to competitive performance for traditional isotope metrics, we report a long-term, control standard root mean square error for <span class="inline-formula">Δ¹⁷</span>O of 12 per meg. Overall performance (<span class="inline-formula">Δ¹⁷</span>O error of 6 per meg, calculated by averaging three replicates spread across distinct, independently calibrated sequences) is comparable to mass spectrometry and requires only <span class="inline-formula">∼</span> 6.3 h per sample. We demonstrate the impact of our approach using a rainfall dataset from Uganda and offer recommendations for other efforts that aim to measure meteoric <span class="inline-formula">Δ¹⁷</span>O via CRDS.</p>