Determination of the triple oxygen and carbon isotopic composition of CO₂ from atomic ion fragments formed in the ion source of the 253 Ultra high-resolution isotope ratio mass spectrometer

Rationale: Determination of δ17O values directly from CO2 with traditional gas source isotope ratio mass spectrometry is not possible due to isobaric interference of 13C16O16O on 12C17O16O. The methods developed so far use either chemical conversion or isotope equilibration to determine the δ17O value of CO2. In addition, δ13C measurements require correction for the interference from 12C17O16O on 13C16O16O since it is not possible to resolve the two isotopologues. Methods: We present a technique to determine the δ17O, δ18O and δ13C values of CO2 from the fragment ions that are formed upon electron ionization in the ion source of the Thermo Scientific 253 Ultra high-resolution isotope ratio mass spectrometer (hereafter 253 Ultra). The new technique is compared with the CO2-O2 exchange method and the 17O-correction algorithm for δ17O and δ13C values, respectively. Results: The scale contractions for δ13C and δ18O values are slightly larger for fragment ion measurements than for molecular ion measurements. The δ17O and Δ17O values of CO2 can be measured on the 17O+ fragment with an internal error that is a factor 1–2 above the counting statistics limit. The ultimate precision depends on the signal intensity and on the total time that the 17O+ beam is monitored; a precision of 14 ppm (parts per million) (standard error of the mean) was achieved in 20 hours at the University of Göttingen. The Δ17O measurements with the O-fragment method agree with the CO2-O2 exchange method over a range of Δ17O values of −0.3 to +0.7‰. Conclusions: Isotope measurements on atom fragment ions of CO2 can be used as an alternative method to determine the carbon and oxygen isotopic composition of CO2 without chemical processing or corrections for mass interferences.</p

Performance related pay: Objectives and application

The stable isotope ratios of atmospheric CO2 (18O/16O and 13C/12C) have been monitored since 1977 to improve our understanding of the global carbon cycle, because biosphere–atmosphere exchange fluxes affect the different atomic masses in a measurable way. Interpreting the 18O/16O variability has proved difficult, however, because oxygen isotopes in CO2 are influenced by both the carbon cycle and the water cycle. Previous attention focused on the decreasing 18O/16O ratio in the 1990s, observed by the global Cooperative Air Sampling Network of the US National Oceanic and Atmospheric Administration Earth System Research Laboratory. This decrease was attributed variously to a number of processes including an increase in Northern Hemisphere soil respiration; a global increase in C4 crops at the expense of C3 forests; and environmental conditions, such as atmospheric turbulence and solar radiation, that affect CO2 exchange between leaves and the atmosphere. Here we present 30 years’ worth of data on 18O/16O in CO2 from the Scripps Institution of Oceanography global flask network and show that the interannual variability is strongly related to the El Niño/Southern Oscillation. We suggest that the redistribution of moisture and rainfall in the tropics during an El Niño increases the 18O/16O ratio of precipitation and plant water, and that this signal is then passed on to atmospheric CO2 by biosphere–atmosphere gas exchange. We show how the decay time of the El Niño anomaly in this data set can be useful in constraining global gross primary production. Our analysis shows a rapid recovery from El Niño events, implying a shorter cycling time of CO2 with respect to the terrestrial biosphere and oceans than previously estimated. Our analysis suggests that current estimates of global gross primary production, of 120 petagrams of carbon per year, may be too low, and that a best guess of 150–175 petagrams of carbon per year better reflects the observed rapid cycling of CO2. Although still tentative, such a revision would present a new benchmark by which to evaluate global biospheric carbon cycling models.