In this study, the inlets of two CO2δ13C analyzers of Picarro Inc., Sunnyvale, CA, G1101-i (manufactured in 2010) and G2201-i (manufactured in 2014), were connected in parallel and then connected with three three-way solenoid valves, which constitutes the sampling and calibration system with one ambient air inlet and three calibration gas inlets (Fig. 1). The switch sequence of valves was controlled by the valve sequencer software on the G2201-i analyzer. The built-in pressure and temperature monitoring systems of G1101-i and G2201-i maintained the cavity temperature of both systems at 45 ∘C and the cavity pressures at 140 and 148 Torr, respectively. The observed stability of temperature over 24 h was 45.0 ± 0.0024 and 45.0 ± 0.0005 ∘C, and the observed stability of pressure was 140.0429 ± 0.0580 and 147.9990 ± 0.0165 Torr for G1101-i and G2201-i, respectively. No relationship between temperature and pressure variation and the δ13C difference of either instrument was found. A diaphragm pump was used to pump the sample air and calibration gas continuously to the cavity (volume of 35 mL) at a flow rate of 0.03 L min-1 at standard temperature and pressure (STP); measurement frequencies were approximately 0.3 and 1 Hz for G1101-i and G2201-i, respectively. Note that the turnover time of sample air in the analyzer is not fast enough for 0.3 and 1 Hz data to be meaningful. In this study, the data reported were block-averaged to average time intervals after deleting the data collected during transitional periods in response to valve switching between the two sample intakes. The physical laser arrays and the software of the G1101-i analyzer were upgraded in March 2012 and August 2014 to correct the cross-interference caused by CH4 and water vapor, respectively. In the following laboratory and atmospheric measurements, the water vapor sensitivity test and atmospheric measurements were done before the upgrade of G1101-i (G1101-i-original) and after the upgrade of G1101-i (G1101-i-upgraded) in August 2014.

The sample air stream passed through a filter (pore size 2 µm, Swagelok model B-4F-05, Connecticut Valves and Fittings, Norwalk Connecticut) to the analyzers without being dried. In this study, only the water vapor dilution effect was corrected, without considering the water vapor pressure broadening effect and the spectral interference effect (Wen et al., 2013). Data from the transitional periods, i.e., the first 180 s of each sample measurement cycle after valve switching, were discarded. The transitional periods in response to valve switching between two air sample intakes were about 120 s.

Three reference gases (Ref1, Ref2, and Ref3) were produced by Beijing AP BAIF Gases Industry Co., Ltd, with CO2 mixing ratios of 368.1, 451.7, and 550.1 ppm. The δ13C values were measured using an isotope ratio mass spectrometer (Thermo Finnigan MAT 253) at the Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. Because the three reference gases originated from the same gas source, the δ13C values were -20.38 ± 0.06 ‰ for all three reference gases.

The air sample inlet was located outside the Key Laboratory of Ecosystem Network Observation and Modeling, 10 m above the ground (Wen et al., 2008, 2010, 2012, 2013). The first atmospheric measurement dataset was collected, for both the G1101-i-original and G2201-i analyzers, from 15 June 2015 to 23 June 2015 (DOY 164–174), and the second dataset was collected, for both G1101-i-upgraded and G2201-i analyzers, from 14 December to 22 December 2014 (DOY 348–356). The first atmospheric measurement sampled Ref1 and Ref3 for 10 min each, followed by alternate measurements of ambient air (50 min) and Ref2 (10 min) for 5 h. The total duration of the sampling and calibration cycle was 320 min. The second atmospheric measurement sampled Ref1, Ref2, and Ref3 for 10 min each, followed by ambient air measurement for 300 min, i.e., a total duration of 330 min for each sampling and calibration cycle. The atmospheric sample and Ref2 were calibrated by Ref1 and Ref3 for each measurement cycle, and the calibrated atmospheric sample data were used to obtain hourly mean values.

The two-point mixing ratio gain and offset calibration method (Bowling et al., 2003) was used to calibrate the 12CO2 and 13CO2 mixing ratio measured by G1101-i and G2201-i. Additional details about the calibration method can be found in Wen et al. (2013). Following this method, the calibrated mixing ratios of 12CO2 (x12) and 13CO2 (x13) are calculated as xa,t12=x3,t12-x1,t12x3,m12-x1,m12xa,m12-x1,m12+x1,t12 xa,t13=x3,t13-x1,t13x3,m13-x1,m13xa,m13-x1,m13+x1,t13, where m and t represent the measured and true mixing ratios, and the subscripts 1, 3, and a represent Ref1, Ref3, and ambient air, respectively.

The isotopic composition of CO2 in the ambient air is expressed in the delta notation: δ13C=(Rsample/RVPDB-1)×1000, where Rsample is the 13C / 12C ratio of the sample, and RVPDB is the 13C / 12C ratio of the reference standard (i.e., the VPDB).

Figure 2 shows the Allan variance (Allan, 1987) as a function of the average time of the δ13C measurements for Ref1, Ref2, and Ref3 measured by G1101-i-original and G2201-i. If the Allan variance is dominated by the random white (Gaussian) noise, the Allan variance should decrease linearly with average time, and the precision should increase with the average time. However, for longer average times, the precision worsens because of instrumental drift. In addition, the precision should increase with increasing CO2 concentrations because of high signal-to-noise ratio. The δ13C precision improved with the average time and achieved optimum values of 0.08, 0.15, and 0.10 ‰ for G1101-i-original at 7600, 1900, and 1900 s for Ref1, Ref2 and Ref3, respectively and 0.03, 0.04, and 0.01 ‰ for G2201-i at 7600, 3800, and 7600 s for the three reference gases, respectively. The 5 min precision was 0.24–0.34 ‰ and 0.08–0.12 ‰ for G1101-i-original and G2201-i, respectively (Table 1).

The precisions of G1101-i-original and G2201-i δ13C values were comparable with other reported performances of IRIS instruments. The precision of TDLAS instruments ranged from 0.03 to 4 ‰ (Bowling et al., 2003, 2005; Griffis et al., 2004; Pataki et al., 2006). Picarro EnviroSense 2050 had a precision of 0.08 ‰ at 130 min (Friedrichs et al., 2010). The Picarro G1101-i had a precision of 0.2 ‰ at 5 min (Vogel et al., 2013), and the best precision of 0.08 ‰ at 2000 s (Wen et al., 2013). For Los Gatos DLT-100, the optimal precision of 0.04 ‰ was obtained at 1000 s (Wen et al., 2013). The QCLAS typically has a precision of 0.18 ‰ at 350 ppm CO2 (McManus et al., 2005), and the optimal precision of 0.16 ‰ was obtained at 500 s (Tuzson et al., 2008). Nicolet Avatar 370 (Thermo Electron, USA) based on FTIR technology obtained the optimal precision of 0.15 ‰ at 16 min (Mohn et al., 2007), and an improved version had a precision of 0.02 ‰ at 10 min (Griffith et al., 2012).

Figure 3 shows the dependence of δ13C on CO2 concentration for G1101-i-original and G2201-i. The dependence of δ13C on CO2 concentration is the nonlinearity of the analyzer response to CO2 concentration variance (Griffith et al., 2012; Guillon et al., 2012; Wen et al., 2013). The δ13C values of Ref1, Ref2, and Ref3 measured by G1101-i-original were -23.46 ± 0.26, -22.99 ± 0.28, and -22.62 ± 0.27 ‰, with an average value of -23.02 ± 0.27 ‰. The δ13C values measured by G2201-i were -21.65 ± 0.07, -21.51 ± 0.08, and -21.49 ± 0.05 ‰, with an average value of -21.55 ± 0.07 ‰ (Fig. 3). In the range of 368.1–550.1 ppm, δ13C values measured by G1101-i-original and G2201-i showed an increase with an increase of CO2 concentration at 0.46 ‰ per 100 ppm and 0.09 ‰ per 100 ppm, respectively, and the peak-to-peak amplitudes were 1.75 and 0.47 ‰, respectively.

The concentration dependence of the measured δ13C values is the main error source affecting IRIS measurements. Guillon et al. (2012) found that the DLT-100 based on ICOS technology had a nonlinear concentration dependence in the range 300–2000 ppm. After correcting the concentration dependence by a fifth-order polynomial calibration curve, the accuracy improved from 2.7 to 1.3 ‰ for δ13C. The Picarro G1101-i analyzer, based on CRDS technology, showed no significant concentration dependence of δ13C with a standard deviation of ∼ 0.2 ‰ in the range 303–437 ppm (Vogel et al., 2013). Griffith et al. (2012) used a series of different CO2 mixing ratios at constant δ13C, and found that a residual curvature against the reciprocal of CO2 was caused by a small nonlinear response of the analyzer.

Based on the same data measured in Sect. 3.2, the temporal drift and accuracy of δ13C values of Ref1, Ref2, and Ref3 measured by G1101-i-original and G2201-i are shown in Fig. 4. The two-point mixing ratio gain and offset calibration method (Bowling et al., 2003) was used to calibrate the measured δ13C value for each 120 min measurement cycle. The instrument temporal drift was calculated as the maximum variability during the measurement period, which mainly resulted from the sensitivity to the changing environmental conditions (e.g., temperature dependence). During the 48 h measuring period, the standard deviations of δ13C values of Ref1, Ref2, and Ref3 measured by G1101-i-original were 0.26, 0.28, and 0.27 ‰, respectively, with temporal drifts (peak-to-peak magnitude) of 0.92, 1.09, and 0.93 ‰. The standard deviations of the δ13C values of Ref1, Ref2, and Ref3 measured by G2201-i were 0.07, 0.08, and 0.05 ‰, with temporal drifts of 0.23, 0.37, and 0.19 ‰. The differences between the CRDS and IRMS measurements were -3.08 ± 0.26, -2.61 ± 0.28, and -2.24 ± 0.27 ‰ for G1101-i-original and -1.27 ± 0.07, -1.13 ± 0.08, and -1.11 ± 0.05 ‰ for G2201-i. After calibration, the differences reduced to 0.09 ± 0.34, 0.04 ± 0.20, and 0.06 ± 0.21 ‰ for G1101-i and -0.13 ± 0.21, 0.03 ± 0.08, and -0.10 ± 0.14 ‰ for G2201-i (Table 2). Much improved accuracy was obtained when the calibration was interpolated for Ref2 with Ref1 and Ref3 rather than extrapolated for Ref1 with Ref2 and Ref3 or Ref3 with Ref1 and Ref1.

As for the drift of IRIS instruments, Vogel et al. (2013) monitored two gas cylinders sequentially with 10 min and 20 min for each cylinder lasting 3 days; the drift of G1101-i was around 0.3 ‰ day-1. Hammer et al. (2013) measured a target gas continuously for 6 days; the FTIR instrument showed a drift of 0.02 ‰ day-1 for δ13C after sensitivity correction. Tuzson et al. (2008) measured identical air samples for 1 min every 15 min for 7 h; the standard deviation of the δ13C measured by QCLAS was 0.14 ‰ (n = 28). Schaeffer et al. (2008) monitored two quality control tanks in the field over 2.44 years, and the standard deviations of the difference between actual and measured values were 0.31 and 0.33 ‰ (n = 2318 and n = 2254). Wehr et al. (2008) monitored a CSIRO standard gas over a period of 30 min, and the standard deviations for integration times of 20 and 120 s were 0.71 and 0.64 ‰, respectively. In this study, over a period of 48 h, the standard deviations of δ13C measured by G1101-i-original and G2201-i were 0.26–0.28 and 0.05–0.08 ‰, respectively, and the drift values were 0.92–1.09 and 0.19–0.37 ‰, respectively.

Regarding the accuracy of IRIS instruments, Guillon et al. (2012) found that in the range 300–2000 ppm, the accuracy of δ13C measured by DLT-100 was 2.7 ‰ for raw measurements and improved to 1.3 ‰ after correction. Over the entire 2.44-year period, two quality control gases measured by TDLAS in the field showed agreement between actual and measured values of -0.17 ± 0.33 and -0.14 ± 0.4 ‰ for tank 1 and tank 2 (Schaeffer et al., 2008). Over a period of 30 min, the δ13C values measured by optical feedback cavity enhanced absorption spectroscopy (OF-CEAS) showed a systematic error of 0.9 ‰ between the measured and IRMS values (Wehr et al., 2008). Using the optimized PLS algorithm, the accuracy of δ13C measured by FTIR was 0.4 ‰ with CO2 concentrations in the range 364–530 ppm (Mohn et al., 2007). Over a 1-year period, Vogel et al. (2013) found that although a single measurement was imprecise, the G1101-i δ13C analyzer provided a mean accuracy of 0.002 ± 0.025 ‰ after proper calibration. In this study, the accuracies of G1101-i-original and G2201-i δ13C analyzers were -3.06 to -2.22 and -1.25 to -1.09 ‰ before calibration and improved to -0.02–0.11 and -0.11–0.05 ‰ after calibration for each 120 min measurement cycle over a measurement course of 48 h.

The sensitivities of δ13C to water vapor concentration of G1101-i-original and G2201-i before the upgrade of G1101-i and G1101-i-upgraded and G2201-i after the upgrade of G1101-i are shown in Fig. 5. For the first test, the dew point temperature of the reference gas ranged from 5 to 25 ∘C. The mean δ13C values measured by G1101-i-original and G2201-i were -20.64 ± 0.72 and -21.60 ± 0.19 ‰, the sensitivity of δ13C to the water vapor mixing ratio was 0.86 ‰ / % H2O and 0.20 ‰ / % H2O, and the peak-to-peak amplitudes of δ13C under different water vapor mixing ratios were 1.96 and 0.45 ‰, respectively. For the second test, the mean δ13C values measured by G1101-i-upgraded and G2201-i were -22.34 ± 0.09 and -22.27 ± 0.18 ‰, the sensitivity of δ13C to the water vapor mixing ratio was 0.13 ‰ / % H2O and -0.19 ‰ / % H2O, and the peak-to-peak amplitudes of δ13C under different water vapor mixing ratios were 0.22 and 0.32 ‰, respectively. Note that with the dew point in the range of 5–20 ∘C, the mean δ13C values measured were -20.84 ± 0.66 and -21.68 ± 0.07 ‰ by G1101-i-original and G2201-i, respectively, and -22.34 ± 0.10 and -22.34 ± 0.08 ‰ by G1101-i-upgraded and G2201-i, respectively. The sensitivity of δ13C to the water vapor mixing ratio was 1.01 ‰ / % H2O and 0.09 ‰ / % H2O, and the peak-to-peak amplitudes were 1.47 and 0.14 ‰ by G1101-i-original and G2201-i, respectively. The sensitivity of δ13C to the water vapor mixing ratio was 0.15 ‰ / % H2O and 0.13 ‰ / % H2O, and the peak-to-peak amplitudes were 0.22 and 0.19 ‰ for G1101-i-upgraded and G2201-i, respectively.

The dilution and pressure broadening effects are the two major factors leading to the dependence of the measured δ13C on water vapor concentrations (Chen et al., 2010; Nara et al., 2012). Variations in sample water vapor significantly affect the mixing ratio of 12CO2 and 13CO2 via the dilution effect. In addition, the variability of water vapor also introduces the broadening effect along the spectroscopic line, which includes the Lorentzian line broadening and Dicke line narrowing effect. The CRDS instruments measured 12CO2 and 13CO2 concentrations by the peak height of the absorption peak whose baseline and shape can be affected by the absorption peaks of water (Nara et al., 2012; Rella et al., 2013). As for CO2, the systematic errors caused by the broadening effects would be 40 % of the dilution effects if they were not corrected (Chen et al., 2010). The transferability of water correction functions among multiple instruments also biases the measurement data among different instruments. Rella et al. (2013) found that for analyzers CFADS15 and 30, the transferability of both CO2 and CH4, after correction of the water vapor mole fraction in the range no more than 2 %, meets the Global Atmosphere Watch (GAW) Programme quality. For three instruments based on CRDS technology, however, the residual errors of CO2 showed substantially large values with increasing water vapor concentration (Nara et al., 2012). The incompatibility of these results indicates the need for more precise experiments to evaluate the transferability of water correction functions (Kwok et al., 2015). Moreover, potential long-term drift of the water vapor correction coefficients of individual instruments needs to be assessed (Nara et al., 2012; Rella et al., 2013).

In this study, the standard deviations of δ13C measured by G2201-i (0.07 and 0.08 ‰) under a dew point in the range 5–20 ∘C are better than the precision given by manufacturer (0.15 ‰), and the standard deviation of δ13C measured by G1101-i-upgraded (0.10 ‰) is also smaller than the specified precision. These results indicate that the water corrections embedded in the instruments' software work sufficiently within the dew point range of 5–20 ∘C.

The δ13C of atmospheric CO2 was measured continuously by G1101-i-original and G2201-i analyzers and by G1101-i-upgraded and G2201-i analyzers. The temporal variations of atmospheric δ13C, the difference between G1101-i and G2201-i analyzers, and the distribution of differences are shown in Fig. 6. The measured atmospheric δ13C values were calibrated using Ref1 and Ref3, and Ref2 was used as a quality control gas to assess the accuracy of atmospheric sample measurements (Fig. 7).

Atmospheric δ13C measured by G1101-i and G2201-i showed good agreement, and both instruments captured the rapid changes in atmospheric δ13C on hourly to diurnal cycle scales. Before G1101-i was upgraded (DOY 164–174), atmospheric δ13C measured by G1101-i-original and G2201-i ranged from -13.24 to -7.47 and -13.41 to -7.62 ‰, with average values of -9.49 ± 1.22 and -9.42 ± 1.17 ‰, respectively. The difference between δ13C measured by G1101-i-original and G2201-i analyzers ranged from -0.62 to 0.76 ‰, with an average value of 0.07 ± 0.24 ‰. The difference exhibits a Gaussian distribution. A significant systematic bias of δ13C values was identified between these two analyzers (t test, p < 0.01). After G1101-i was upgraded (DOY 348–356), atmospheric δ13C measured by G1101-i-upgraded and G2201-i ranged from -14.08 to -8.64 and -13.89 to -9.06 ‰, with average values of -10.61 and -10.56 ‰, respectively. The difference of δ13C measured by G1101-i-upgraded and G2201-i analyzers ranged from -0.57 to 0.85 ‰, with an average value of 0.05 ± 0.30 ‰. A significant systematic bias of δ13C values still existed between these two analyzers (t test, p=0.018). In addition, field measured values of Ref2 during the atmospheric measurement period (DOY 164–174 and DOY 348–356) were used to assess the stability and accuracy of both analyzers (Fig. 7). During the first atmospheric measurement period, the average δ13C values of Ref2 were -21.32 ± 0.51 and -21.91 ± 0.12 ‰ for G1101-i-original and G2201-i, respectively. After calibration, the average δ13C values were -20.30 ± 0.40 and -20.56 ± 0.17 ‰, respectively. The accuracy (the difference between calibration and actual values) respectively ranged from -0.70 to 0.91 and -0.42 to 0.19 ‰, with average values of 0.09 ± 0.40 and -0.17 ± 0.17 ‰. During the second atmospheric measurement period, the average δ13C values of Ref2 were -24.37 ± 0.59 and -21.92 ± 0.18 ‰ for G1101-i-upgraded and G2201-i. After calibration, the average δ13C values were -20.56 ± 0.23 and -20.57 ± 0.09 ‰, respectively. The accuracy ranged from -0.60 to 0.30 and -0.42 to 0.02 ‰, with average values of -0.17 ± 0.23 and -0.18 ± 0.09 ‰, respectively. These results indicate that G2201-i is more stable than G1101-i, which is consistent with the Allan variation results.

In general, all of the IRIS instruments aim to maintain high enough precision and accuracy such that the data are traceable to international scales. However, sensitivity to changing environmental conditions (e.g., temperature dependence) and dependence of δ13C on the CO2 concentration affect the performance of IRIS measurements (Wada et al., 2011; Guillon et al., 2012; Wen et al., 2013). Reliable and accurate measurements similar to that of IRMS can be obtained with proper calibration (Bowling et al., 2005; Guillon et al., 2012; Hammer et al., 2013; Vogel et al., 2013; Wen et al., 2013). In theory, both issues of delta scale stretching and the concentration dependence should be corrected by generating multiple delta values over a range of mixing ratios under ambient conditions. In practice, ignoring the effect of the delta scale stretching, the two-point mixing ratio gain and offset calibration method was successfully applied to calibrate the mixing ratios of 12CO2 and 13CO2 separately (Bowling et al., 2003; Wen et al., 2013). For the instrument performance diagnoses, it was suggested that another reference gas be measured to monitor the long-term precision and accuracy. Three-point or higher calibration schemes with CO2 concentration signals spanning a range of ambient concentrations were suggested to ensure the linearity of the analyzer and diagnose the instrument performance. With proper calibration frequency, the instrument drifts would be eliminated. Calibration frequency and sampling interval are instrument-specific characteristics. Note that considering the δ13C dependence on H2O, researchers should consider drying moist sample air when H2O is above 2.4 % as is factory-recommended, even though the water correction works sufficiently well (Fig. 5).

Figure 8 shows the dependence of the δ13C difference between G1101-i-original and G2201-i and between G1101-i-upgraded and G2201-i on water vapor concentration and CO2 mixing ratio. Before and after G1101-i was upgraded, there was no significant correlation between the δ13C difference and CO2 mixing ratio (Fig. 8a and 8b). Before G1101-i was upgraded, a significant linear correlation was observed between the δ13C difference and water vapor concentration (P<0 01, Fig. 8c); after the upgrade of G1101-i, there was no significant correlation between the δ13C difference and water vapor concentration (P> 0.05, Fig. 8d). This relationship was mainly due to the upgrade of G1101-i, which excluded δ13C measurement errors that originated from variations in water vapor concentration and improved the accuracy of δ13C measurement. This result is consistent with the results of the sensitivity of δ13C to water vapor concentration test. In addition, note that the second measurement was conducted in winter when the atmospheric water vapor concentration was relatively low and the water vapor interference was small.

The isotopic composition of source CO2 (δ13CS) was used to gain insight into the potential local CO2 sources and underlying mechanisms at different temporal and spatial scales. In this study, δ13CS was calculated using the calibration dataset of δ13C and 1/CO2 by the Keeling plot intercept method (Keeling, 1958; Fig. 9). The total CO2 was calculated using the 12CO2 and 13CO2 from the Picarro data. During the first atmospheric measurement period, the δ13CS values were -24.80 ± 0.39 and -23.98 ± 0.30 ‰, with a mean difference of 0.82 ‰, respectively, for G1101-i-original with a range of CO2 concentrations from 390.92 to 630.92 ppm and G2201-i with a range of CO2 concentrations from 391.76 to 631.29 ppm. Note that the uncertainties are the standard error of the intercept from the fitting algorithm. If we assumed that the atmospheric δ13C is a linear function of 1/ CO2 with a small concentration-dependent error d (Eq. 18; Wen et al., 2013), then error propagation through the concentration dependence would be a function of ε with respect to the intercept of the Keeling plot. When ε= 0.05 ‰, this error would propagate through the Keeling plot and cause a difference of 0.99 ‰. This result is close to the actual difference of 0.82 ‰ between G1101-i-original and G2201-i. When we used only the nighttime data (22:00–04:00) for the Keeling analysis, the δ13CS values were -28.35 ± 1.34 and -27.11 ± 1.02 ‰ for G1101-i-original and G2201-i, respectively, with a mean difference of 1.24 ‰. The δ13CS value deduced from nighttime data was a mixed value of various local CO2 sources, including the combustion of natural gas, gasoline, and coal as well as the respiration of plants and soil (Pang et al., 2016a).

During the second atmospheric measurement period, the δ13CS values were -25.90 ± 0.28 and -25.97 ± 0.12 ‰, with a mean difference of 0.07 ‰, for G1101-i-upgraded with a range of CO2 concentrations from 398.51 to 552.66 ppm and G2201-i with a range of CO2 concentration from 399.92 to 555.90 ppm, respectively. When we used only the nighttime data (22:00–04:00) for the Keeling analysis, the δ13CS values were -26.05 ± 0.16 and -25.69 ± 0.41 ‰, with a mean difference of 0.36 ‰ for G1101-i-upgraded and G2201-I, respectively. The systematic bias of δ13CS decreased from 1.24 ‰ between G1101-i-original and G2201-i to 0.36 ‰ between G1101-i-upgraded and G2201-i. The results confirm that we should pay attention to the measurement difference resulting from the uncorrected dependencies on CO2 or H2O concentrations among different IRIS instruments and that this difference will result in error propagation through Keeling plot analysis (Wen et al., 2013).

The potential problems caused by incompatibility include the integrity of an internal calibration scale and modifications to analytical procedures in decade-long records (Levin et al., 2012). In this study, the Keeling plot intercepts of G1101-i and G2201-i measurements should be identical because of the common air samples. Differences in the Keeling plot intercepts of 1.24 or 0.36 ‰ were caused by a systematic error between G1101-i (before and after upgrade) and G2201-i. Note that the uncertainty of the Keeling plot intercept was related to its underlying assumption, CO2 range, and uncertainty in the CO2 and isotopic measurements. Generally speaking, the standard error of the Keeling plot intercept should be less than 1 ‰ (Pataki et al., 2003; Zobitz et al., 2006).