A new online technique for the simultaneous measurement of the δ13C value of dissolved inorganic carbon and the δ18O value of water from a single solution sample using continuous-flow isotope ratio mass spectrometry

Rapid Commun Mass Spectrom. 2014 Mar 15;28(5):553-62. doi: 10.1002/rcm.6812.

Abstract

Rationale: The oxygen isotope study of water reservoirs (δ(18)OH2O values) and the carbon isotope study of dissolved inorganic carbon (δ(13)CDIC values) are powerful tools to decipher Earth's past and present environmental changes. This study presents a novel online analytical technique, namely the DIC evolved CO2 Gas Equilibration Method (DIC-CO2-GEM), in which the δ(18)OH2O and δ(13)CDIC values can be simultaneously determined from a single solution sample.

Methods: The DIC-CO2-GEM measures both δ(18)OH2O and δ(13)CDIC values concurrently by combining the fundamental principles of the classic CO2-H2O equilibration and gas evolution methods, respectively. Phosphoric acid is used to convert dissolved inorganic carbon in a solution sample of 0.2 mL into gaseous CO2, which is then equilibrated with the solution at 25 °C. The oxygen and carbon isotope compositions are subsequently determined via continuous-flow isotope ratio mass spectrometry from the single solution sample.

Results: Results obtained employing the DIC-CO2-GEM are in good agreement (<± 0.07‰ for δ(18)OH2O values and < < ± 0.1‰ for δ(13)CDIC values) with those acquired using each of the traditional techniques. For both oxygen and carbon isotope measurements, an addition of 0.01 mL phosphoric acid yields the most consistent results between our technique and the traditional methods.

Conclusions: Devised to combine the traditional approaches independently assessing δ(18)OH2O and δ(13)CDIC values, the DIC-CO2-GEM is less complex and highly efficient. It preserves the modern precision requirements for oxygen (± 0.09‰) and carbon (± 0.18‰) isotope analyses while accurately measuring both parameters simultaneously. This innovative method generates an abundance of data while minimizing resources and is suitable for a variety of practical applications.