Tracking isotopic signatures of CO<sub>2</sub> at the high altitude site Jungfraujoch with laser spectroscopy: analytical improvements and representative results

Abstract

Abstract. We present the continuous data record of atmospheric CO2 isotopes measured by laser absorption spectroscopy for an almost four year period at the High Altitude Research Station Jungfraujoch (3580 m a.s.l.), Switzerland. The mean annual cycles derived from data of December 2008 to September 2012 exhibit peak-to-peak amplitudes of 11.0 μmol mol−1 for CO2, 0.60‰ for δ13C and 0.81‰ for δ18O. The high temporal resolution of the measurements also allow us to capture variations on hourly and diurnal timescales. For CO2 the mean diurnal peak-to-peak amplitude is about 1 μmol mol−1 in spring, autumn and winter and about 2 μmol mol−1 in summer. The mean diurnal variability in the isotope ratios is largest during the summer months too, with an amplitude of about 0.1‰ both in the δ13C and δ18O, and a smaller or no discernible diurnal cycle during the other seasons. The day-to-day variability, however, is much larger and depends on the origin of the air masses arriving at Jungfraujoch. Backward Lagrangian particle dispersion model simulations revealed a close link between air composition and prevailing transport regimes and could be used to explain part of the observed variability in terms of transport history and influence region. A footprint clustering showed significantly different wintertime CO2, δ13C and δ18O values depending on the origin and surface residence times of the air masses. Several major updates on the instrument and the calibration procedures were performed in order to further improve the data quality. We describe the new measurement and calibration setup in detail and demonstrate the enhanced performance of the analyzer. A measurement precision of about 0.02‰ for both isotope ratios has been obtained for an averaging time of 10 min, while the accuracy was estimated to be 0.1‰, including the uncertainty of the calibration gases.

Monitoring CO2 concentration and δ13C in an underground cavity using a commercial isotope ratio infrared spectrometer

“…A linear approximation for the concentration dependence law is commonly used for IRIS analyzers [3,7,18]. The concentration dependence law obtained in this study is consistent with this approximation, as least in the limited range of concentration that was investigated.…”

“…Third, the δ 13 C dependence on CO 2 concentration is known to be one of the largest sources of uncertainty for IRIS analyzers [3,7,9,18,19] and needs to be carefully checked. Reference gases with 17,800 as well as 2,002 ppm CO 2 concentrations (F and G, Table 1) were stepwise diluted by CO 2 -free synthetic air with 78 % N 2 , 21 % O 2 (Air Products), using two mass flow controllers (SLA5850S, Brooks, range 1 L min −1 ).…”

“…Based on the above performance and concentration dependence measured in the laboratory, as well as on methodologies proposed by others [3,7], the following calibration method was used to process the raw data. Raw data files from the CCIA-EP analyzer were first handled with a program written in Fortran, in order to:…”

“…They also emphasized the need for users to thoroughly assess the analyzers' performance in the field and to establish calibration strategies to correct raw data for the identified biases [3,6]. Commercial IRIS instruments are often designed for atmospheric monitoring and present good accuracy at low and not strongly variable CO 2 concentration [3,7,8]. But there is also a need for carbon isotope monitoring at higher and more variable concentrations, in volcanic [2] or underground [9] environments, as well as for soil [10] and fermentation plants monitoring [11].…”

Mixing ratio and carbon isotopic composition investigation of atmospheric CO 2 in Beijing, China

“…Highresolution and long-term monitoring of atmospheric CO 2 mixing ratios and isotopic compositions can provide information about urban CO 2 sources and quantify the effects of plant photosynthesis, respiration and fossil fuel combustion on atmospheric CO 2 over various temporal scales from days to years (Wada et al, 2011;Pataki et al, 2006). These data can be used in high-resolution transport models, regional-scale ecosystem models and regional-scale flux inversions to improve our understanding of carbon cycle processes in urban ecosystems (Sturm et al, 2013) and also shed light on the effects of vegetation, soil and anthropogenic emissions on urban carbon cycles.…”