Measuring the stable isotope compositions of atmospheric CO2 is common in earth and atmospheric sciences, and various analytical methods have been developed utilizing continuous-flow (CF) or dual-inlet (DI) isotope ratio mass spectrometry (IRMS). Air is typically collected via passive, manual, or automated collection methods and the volume of the air sample ranges from 10 to 300 mL for CF-IRMS to >1 L for DI-IRMS to yield a measurable amount of atmospheric CO2 gas. It has been determined that the integrity of vials and flasks for air sample storage can be compromised after 3 days of air collection for δ13C values and within 10 hours for δ18O values. Air samples must be purified after collection to remove constituents of air, such as Ar, O2, N2, N2O, and water vapor, to avoid isobaric interferences during mass spectrometric measurement. Purification is generally undertaken by utilizing commercial or custom-made preconcentration devices, the blanking method for CF-IRMS, or an offline/online cryogenic separation using a vacuum line for DI-IRMS. Ambient N2O is a component of air that may affect analytical results and thus must either be corrected for or be removed using a gas chromatographic column. In some cases, water is removed during air collection by using a common chemical desiccant, magnesium perchlorate (Mg(ClO4)2), or by a dry ice/alcohol mixture (−78°C). Lastly, a linearity issue for IRMS due to the low amount of purified CO2 from a typical ambient air sample must be considered. In general, analytical precisions of 0.02–0.21‰ and 0.04–0.34‰ for CF-IRMS and 0.01–0.02‰ and 0.01–0.02‰ for DI-IRMS are expected for δ13C and δ18O measurements, respectively.

Measuring the stable isotope compositions of atmospheric CO2 is common in earth and atmospheric sciences, and various analytical methods have been developed utilizing continuous-flow (CF) or dual-inlet (DI) isotope ratio mass spectrometry (IRMS). Air is typically collected via passive, manual, or automated collection methods and the volume of the air sample ranges from 10 to 300 mL for CF-IRMS to >1 L for DI-IRMS to yield a measurable amount of atmospheric CO2 gas. It has been determined that the integrity of vials and flasks for air sample storage can be compromised after 3 days of air collection for δ13C values and within 10 hours for δ18O values. Air samples must be purified after collection to remove constituents of air, such as Ar, O2, N2, N2O, and water vapor, to avoid isobaric interferences during mass spectrometric measurement. Purification is generally undertaken by utilizing commercial or custom-made preconcentration devices, the blanking method for CF-IRMS, or an offline/online cryogenic separation using a vacuum line for DI-IRMS. Ambient N2O is a component of air that may affect analytical results and thus must either be corrected for or be removed using a gas chromatographic column. In some cases, water is removed during air collection by using a common chemical desiccant, magnesium perchlorate (Mg(ClO4)2), or by a dry ice/alcohol mixture (−78°C). Lastly, a linearity issue for IRMS due to the low amount of purified CO2 from a typical ambient air sample must be considered. In general, analytical precisions of 0.02–0.21‰ and 0.04–0.34‰ for CF-IRMS and 0.01–0.02‰ and 0.01–0.02‰ for DI-IRMS are expected for δ13C and δ18O measurements, respectively.

Abstract Tree growth rings from three specimens in two different aged (14- and 77-year old) white pine plantation forests were analyzed for stable carbon isotope ratios to identify both short- and long-term variations in physiological response to changing environmental conditions. Three isotopic (δ13Ccorr) time series records were constructed from whole wood samples extracted from paths parallel to the growth rings in each forest. These δ13Ccorr records were corrected for the long-term anthropogenically induced CO2 and compared to historical climate (temperature, precipitation) data from 1935 to 2016. High resolution inter-annual variations in trees in each stand displayed similar intra-annual cycles in δ13Ccorr, demonstrating the seasonal physiological response of these forests to environmental stressors. In both stands, growing season temperature acted as a significant control (p