A rapid high‐precision analytical method for triple oxygen isotope analysis of CO <sub>2</sub> gas using tunable infrared laser direct absorption spectroscopy
Nathan Perdue, Z. D. Sharp, David D. Nelson, Rick Wehr, Christoph Dyroff
Abstract
Rationale The simultaneous analysis of the three stable isotopes of oxygen—triple oxygen isotope analysis—has become an important analytical technique in natural sciences. Determination of the abundance of the rare 17 O isotope in CO 2 gas using magnetic sector isotope ratio mass spectrometry is complicated by the isobaric interference of 17 O by 13 C ( 13 C 16 O 16 O and 12 C 16 O 17 O, both have mass 45 amu). A number of analytical techniques have been used to measure the 17 O/ 16 O ratio of CO 2 gas. They either are time consuming and technically challenging or have limited precision. A rapid and precise alternative to the available analytical methods is desirable. Methods We present the results of triple oxygen isotope analyses using an Aerodyne tunable infrared laser direct absorption spectroscopy (TILDAS) CO 2 analyzer configured for 16 O, 17 O, and 18 O combined with a custom gas inlet system. We evaluate the sensitivity of our results to a number of parameters. CO 2 samples with a wide range of δ 18 O values (from −9.28‰ to 39.56‰) were measured and compared to results using the well‐established fluorination‐gas source mass spectrometry method. Results The TILDAS system has a precision (standard error, 2 σ ) of better than ±0.03‰ for δ 18 O and ±10 per meg for Δ′ 17 O values, equivalent to the precision of previous analytical methods. Samples as small as 3 μmol CO 2 (equivalent to 300 μg CaCO 3 ) can be analyzed with a total analysis time of ~30 min. Conclusions We have successfully developed an analytical technique for the simultaneous determination of the δ 17 O and δ 18 O values of CO 2 gas. The precision is equal to or better than that of existing techniques, with no additional chemical treatments required. Analysis time is rapid, and the system is easily automated so that large numbers of samples can be analyzed with minimal effort.