Isotopic composition and concentration measurements ... - Springer Link

Appl Phys B (2010) 101: 411–421 DOI 10.1007/s00340-010-4162-z

Isotopic composition and concentration measurements of atmospheric CO2 with a diode laser making use of correlations between non-equivalent absorption cells L. Croizé · D. Mondelain · C. Camy-Peyret · C. Janssen · M. Lopez · M. Delmotte · M. Schmidt

Received: 22 December 2009 / Revised version: 1 July 2010 / Published online: 21 August 2010 © Springer-Verlag 2010

Abstract Correlations between a sample and a sealed reference cell of a tunable diode laser spectrometer for the measurement of the isotopic composition (δ 13 C) and the concentration of atmospheric carbon dioxide in air have been investigated. Likely due to fluctuations of the laser emission profile, these correlations have been used to improve the performance of the instrument. In a comparison with isotope ratio mass spectrometer and gas chromatographic measurements, an accuracy of 0.15h for δ 13 C and 0.05 ppmv for the CO2 concentration is demonstrated for 40 s integration time. Long-term stability and field deployment of the instrument have been investigated during a few days measurement campaign in Paris.

1 Introduction High-accuracy and high-frequency measurements of the atmospheric CO2 concentration are of primary importance for understanding the carbon cycle. In order to improve estimates of the regional carbon budget, it is essential to assess L. Croizé · D. Mondelain () · C. Camy-Peyret · C. Janssen CNRS, UMR 7092, Laboratoire de Physique Moléculaire pour l’Atmosphère et l’Astrophysique, 75005 Paris, France e-mail: [email protected] Fax: +33-(0)1-44277033 L. Croizé · D. Mondelain · C. Camy-Peyret · C. Janssen UPMC Univ. Paris 06, UMR 7092, Laboratoire de Physique Moléculaire pour l’Atmosphère et l’Astrophysique, 75005 Paris, France M. Lopez · M. Delmotte · M. Schmidt Laboratoire des Sciences du Climat et de l’Environnement, UMR 1572 CEA-CNRS-UVSQ IPSL CE Saclay, L’Orme des Merisiers, Point courrier no. 129, 91191 Gif sur Yvette Cedex, France

the mechanisms driving carbon sources and sinks at the local scale. In that respect measurements of the isotopic composition are particularly interesting complementary tools, because biogeochemical processes, like photosynthesis, or processes linked to fossil fuel combustion lead to different isotopic compositions of carbon dioxide. Isotope measurements of tropospheric CO2 provide information about the source of the carbon dioxide sampled in the air mass. Used in conjunction with inverse models, this provides interesting information to recover CO2 fluxes between the biosphere and the atmosphere. A global estimate of the net fluxes in biosphere-atmosphere and ocean-atmosphere exchanges [1, 2] is also possible. Using a Keeling plot approach [3] the biological discrimination can be estimated at the regional scale by simultaneously measuring changes in the concentration and in the isotopic composition of CO2 within the convective boundary layer when performing aircraft measurements. At ground level a similar approach can be used to estimate the carbon isotopic composition of ecosystem respiration and permits to better understand the processes controlling ecosystem isotope discrimination. The isotopic composition of an air sample is determined in terms of the “δ-value” relative to a standard with the following equation: δ 13 C ≡

Rair {χ(Y )/χ(X)}air −1= − 1. Rstd {χ(Y )/χ(X)}std

(1)

This equation reflects the difference between the isotopic ratio of the air sample Rair and the isotopic ratio of the standard Rstd . In this equation χ is the concentration expressed in terms of the mixing ratio (here in ppmv), X and Y represent respectively the abundant and the rare isotopologue (12 CO2 and 13 CO2 , in our case), and the standard is Vienna Pee Dee Belemnite [4] (RVPDB = 0.0111802). As isotopic compositions differ only very slightly, the quantity δ 13 C is

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Fig. 1 Optical scheme of the SIMCO instrument. InSb is for the indium antimonide photovoltaic detector

expressed in per mil units (h). Accordingly, accuracies better than 0.2h are required to provide a significant contribution to the study of the carbon cycle. Likewise, a high temporal resolution is also desirable. Different techniques can be used to measure the isotopic composition [5, 6]. The standard technique is isotopic ratio mass spectrometry (IRMS) leading to a very precise determination of the isotopic ratio (after having taken mass interferences into account). Yet, it remains a laboratory technique not easily deployable on-line in the field so that flask samples are necessary. Due to the limited number of flasks and the (time costly) requirement of separating the CO2 from other air compounds before IRMS measurements, the technique suffers from low temporal resolution. Isotope measurements by infrared absorption spectroscopy based on the Beer-Lambert law are an alternative that allows distinguishing between molecules of identical mass and between isomers. Moreover, this optical method also allows for the design of compact field deployable instruments with a high sampling frequency. Thanks to these advantages isotopic composition measurements with optical methods have been promoted in recent years [5, and references herein]. Several homemade and commercial instruments based on the principle of absorption spectroscopy have recently been developed to measure the isotopic composition of CO2 at atmospheric concentration levels, either under laboratory conditions and/or in the field [7–16].1 In order to reach the high precision required, a reference cell identical to the sample cell, and with very similar temperature and pressure conditions for the gases in the two cells, is frequently employed [7, 10, 17–19]. This dual cell arrangement is then used to plot the absorbance of the sample cell versus that of the reference cell for both isotopologues, like in Ref. [17], or to 1 Commercially

available instruments: TGA 100A from Campbell Scientific, Inc., G1101-i isotopic CO2 analyzer from Picarro, Inc., the realtime CO2 isotopic analyzer from Aerodyne Research, Inc. and the CO2 isotope analyzer from Los Gatos Research.

ratio sample and reference spectra, as proposed in Ref. [7]. In both cases, high performance thermal stabilization and pressure control of the cells are required. In addition, a reference gas is usually passed permanently through the reference cell [7, 10, 17] and air free of CO2 is used to flush the optical part of the instrument [7, 10, 13] in order to avoid residual absorption by atmospheric CO2 along the beam paths outside the cells. Finally, several (between 3 and 4) working standards are generally needed for calibration purposes [11, 13, 14, 16]. The necessity of having several tanks, for the reference cell, for the calibration and for the purge of the instrument is, however, a serious constraint for field deployment. In this paper we investigate absorbance correlations between a sealed reference cell and the sample cell of our tunable diode laser (TDL) spectrometer, which allow correcting for most instrumental instabilities. In this way, we obtain measurements of high accuracy. The method can be applied to reference cells having quite different path length, pressure and temperature conditions than the sample cells. In addition, no reference gas is consumed, because the reference cell is sealed. Measurements of tanks and of atmospheric air during a measurement campaign are presented here in order to illustrate the high accuracy and the long-term reliability reached using the method proposed. The corresponding results have been obtained without any active thermal regulation, without flushing the instrument with CO2 -free nitrogen, and using a single calibration gas only.

2 Experimental description The TDL spectrometer, named SIMCO (Spectrometer for Isotopic Measurements of CO2 ), has been described elsewhere [12] and we will just give a brief overview here. The instrument (Fig. 1) is based on a cryogenically cooled leadsalt laser diode (SPECDILAS IR diode from Laser Components GmbH) emitting in the mid-IR around 2291.6 cm−1

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Table 1 Position, intensity (S N ), air-broadening coefficient (γair ) and lower state energy (E ) given in HITRAN08 at Tref = 296 K for the two selected lines. J is the quantum number associated with the total angular momentum Identification branch (J ) band

Position [cm−1 ]

S N (Tref ) [cm−1 /(molecule cm−2 )]

γair (Tref ) [cm−1 atm−1 ]

E [cm−1 ]

12 CO

2

P(60) ν3

2291.541602

2.013 × 10−20

0.0638

1426.41520

13 CO

2

R(10) ν3

2291.680391

3.144 × 10−20

0.0780

42.92450

with a maximum power of 0.8 mW. The laser wavenumber is scanned with a 50 Hz triangular current ramp over a 0.4 cm−1 spectral window containing one absorption line for each isotopologue. We have chosen the P(60e) transition for 12 CO and the R(10e) transition for 13 CO , which belong to 2 2 the ν3 fundamental band. These transitions showed the best signal to noise ratio and are free of interferences with other species such as water vapor or other CO2 isotopologues. The spectroscopic parameters of these lines, extracted from the HITRAN08 database [20], are summarized in Table 1. To achieve accurate atmospheric measurements one laser beam traverses a 5 m multi-pass Herriott-type absorption cell (referred as the sample cell hereafter), where the gas flow is regulated to maintain a stable pressure (typically 25– 30 hPa). This pressure range has been optimized to achieve sufficient absorption (for high signal to noise ratio) without too much broadening (to ensure a high selectivity). Another part of the laser beam is directed through a sealed single pass reference cell (path length equal to 100.3 ± 0.1 mm). This cell is built from Pyrex, equipped with CaF2 windows and filled with pure CO2 at low pressure (P < 130 Pa). Both the reference and the sample cells are placed inside the same block of aluminum in order to maintain homogeneous temperatures in the cells. The transmittance spectra measured with two LN2 -cooled photovoltaic InSb detectors are divided by a third spectrum acquired in a channel where the laser beam is directly focused onto a detector of the same type. This last channel is used to account for power variations of the laser diode that are due to changes in the injection current during a spectral scan and allows further to minimize the influence of parasitic absorption by atmospheric CO2 in carefully balancing the optical path lengths outside the cells of all three channels. At the end of each integration cycle (of a duration being defined by the user with a typical value of 0.6 s corresponding to an average of 30 spectra acquired at 50 Hz) the spectra are co-aligned on the same spectral grid (taking laser drift into account) and co-averaged (see [12]). After dark current subtraction and division by the third channel, one obtains a reference and a sample spectrum at high resolution. Each spectrum is composed out of 2000 points separated by ∼1.9 × 10−4 cm−1 . Mixing ratios for both isotopologues (χ(X) and χ(Y )) in the two cells are then determined from these spectra, using a Levenberg–Marquardt

multi-fit algorithm. The fit employs the line shape model developed by Rautian and Sobel’man [21] to best reproduce the molecular line shape and to minimize the residuals [12]. In principle, only the concentrations in the two cells and the spectral baselines need to be varied during fitting the transmission spectra. In reality the acquired spectrum corresponds to the convolution of the theoretical “infinite resolution” transmission spectrum with the (non-negligible) laser emission profile. The laser emission is generally modeled with an empirical Voigt profile resulting from a convolution of a Gaussian with a Lorentzian, with respective halfwidths AG and AL . In our case, the Gaussian component AG is fixed (at 2 × 10−4 cm−1 ) as it cannot be fitted due to the low sensitivity of the residuals to this variable. It is chosen such that the overall residuals are minimized. For a given cycle, the Lorentzian component AL is fitted to the reference spectrum together with the reference mixing ratio A χr , and is used immediately after as a fixed parameter to derive the sample mixing ratio A χs for a given isotopologue A (A = X or Y ). It must be underlined that at this level of precision the laser emission profile has to be considered as wavenumber dependent. It is thus not the same for the two transitions (ν˜ X = 2291.541602 cm−1 for X =12 CO2 and ν˜ Y = 2291.680391 cm−1 for Y =13 CO2 ). Even though the two lines are covered in a single current sweep of the diode, the fitting procedure used to derive concentrations from spectra is performed separately in the vicinity of the two lines (two intervals of 200 spectral points centered at ν˜ X and ν˜ Y ). δ 13 C and the total CO2 concentration are deduced from the concentration of both isotopologues assuming that the fraction of isotopologues other than 12 C16 O2 and 13 C16 O2 is equal to 0.00474 [20].

3 Correlation between cell signals The instrument has been modified only very slightly since the first experiments [12] with SIMCO were reported. In order to adjust the sample gas to the cell temperature a meandering gas line made from ¼ inch stainless steel (1.5 m long), has been installed inside a 10 mm thick aluminum sheet on top of the aluminum block containing the two cells allowing for a very good thermal contact. Moreover, the optical module has been equipped with 13 mm thick insulation foam (Armaflex) for better thermal stability. Most

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Fig. 2 13 CO2 concentration in the sample cell (Yχs ) versus concentration in the reference cell (Yχr ). Reference and sample cells are filled respectively with pure CO2 and with air

importantly, however, we have entirely revised the measurement sequence and the data processing scheme in order to improve instrument performance. Because the reference cell is sealed, the CO2 column or absorber amount (χPtot L/(kB T )) inside is constant so that the instrument should measure stable mixing ratios for both isotopologues. Nevertheless, measured absorbances and derived mixing ratios for the reference cell show fluctuations. Apparent mixing ratio fluctuations are also observed in the sample cell when a steady flow of a calibration gas is passed. Interestingly, the variations in the two cells are strongly correlated and the plot of the mixing ratio derived from the sample cell versus the mixing ratio in the reference cell shows a clear linear relationship, thus firmly establishing a strong correlation between the two cells in terms of observed mixing ratios. Figure 2 illustrates the case for the rare isotopologue (13 CO2 ) using a 20 min time series. The observed correlation between the apparent mixing ratios of a given isotopologue in the sample and in the reference cell are related to the laser emission and its modeling. In fact, a linear relationship is obtained when plotting the fitted mixing ratios versus AL , corresponding to the Lorentzian half-width of the Voigt emission profile, over a short period of time (Fig. 3), both for the reference cell (filled with pure CO2 at low pressure) and for the sample cell (air + CO2 mixture at higher pressure). Note that in case of Figure 3 AL has been fitted separately in both cells, contrary to the standard correction procedure, where AL is determined from the reference cell spectrum only and where this value is then used to determine mixing ratios in the sample cell. The shorttime correlations likely result from uncertainties associated with deriving AL from the spectra. Because the parameter enters in calculating the concentration, any fluctuation in that parameter is transferred into the determination of the mixing ratio. The magnitude of this short-time

correlation between mixing ratios and AL has been confirmed in simulations using synthetic spectra with random noise. Nevertheless, on longer time scales of several minutes we observe correlations between values of AL , separately determined for the two isotopologues 12 CO2 and 13 CO2 in the reference cell. This hints to a systematic evolution of the laser emission profile with time, which is not detectable at short time scales. The parameter AL is then to be considered as an empirical characterization of the slightly fluctuating laser emission profile. Another possible explanation would be changes in laser pointing with temperature leading to a change in the effective absorption path length. The latter is inversely proportional to the determined mixing ratios χ . Because AL and χ are correlated—as we have seen before—this would also lead to correlations in AL for the two isotopologues. However, the changes in the path geometry required to explain the relative amplitude of the observed variations of the mixing ratios in the reference cell (which are typically 1 to 2% over several hours) are far too large to be explained in this way and the hypothesis of laser pointing variations must thus be ruled out.

4 Correction strategy When the data of the entire time series in Fig. 2 are fitted to a straight line by the method of least-squares using equal weights, intercept α (Y = 13 CO2 ) = 2.386 ± 0.008 ppmv and slope β (Y = 13 CO2 ) = 1.745 ± 0.007 × 10−4 can precisely be determined. The parameters can then be used together with the mixing ratios for isotopic species A = X or Y measured in the reference cell A χr to correct the mea-


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Fig. 3 Concentrations plotted versus the Lorentzian component (AL ) of the laser emission profile for the 12 CO2 and 13 CO2 in the reference (Xχr , Yχ ) and sample (Xχ , Yχ ) cells. To obtain these figures the Lorentzian parts are fitted in the reference and in the sample spectra. The Gaussian r s s component is fixed in all cases to a value equal to 2 ×10−4 cm−1

sured mixing ratios in the sample cell A χs using the following equation: A corr χs (t) =

A χ (t) s A χcalib α(A, t) + A χr (t)β(A, t)

(2)

where A χcalib is an overall absolute calibration factor that has been fixed after a series of measurements on a very precisely calibrated sample (by combined GC and IRMS measurements). In (2), a slow evolution of slope and intercept in time is taken into account by determining α and β over time periods of roughly one minute. Further, the isotopic composition measurement of an unknown gas is performed by continuously switching between the measurement gas and the calibration gas. Figure 4 illustrates this change between measurement (MP) and calibration phases (CP). The correlations can then be determined in two ways from the k and k + 1 calibration phase (CPk and CPk+1 ) data points: (1) independently for the two calibration phases leading to the determination of the linear regression coefficients (αk, , βk ,

αk+1 , βk+1 ) which are then averaged; (2) by taking into account all the data points of the two calibration phases simultaneously. According to our observations, these two schemes are equivalent and we have used the second one to correct CPk and MPk . Due to the 5 s transition time in the sample cell the first 10 s of the different phases are rejected and only the last 10 s are kept as reliable data points for determining the correlation. The final measurement k corresponds to the average (without the outliers) over the last 10 s of MPk after correction so that one data point is obtained every 40 s. In fact, data points differing by more than two standard deviations from the mean value are eliminated and the average is calculated again for MPk . To quantify the correction efficiency, the same gas was continuously passed through the sample cell allowing one to record a time series of δ 13 C. The Allan deviation [22] can be calculated for this (uncorrected) time series as shown in Fig. 5. The same time series is then separated in data blocks of 20 s corresponding alternatively to the calibration and to the measurement phases. For each of the cal-

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Fig. 4 12 CO2 concentration measurements (Xχs ) when switching between unknown and calibration gases in the sample cell. CPk and MPk represent the kth calibration and measurement phase, respectively

Fig. 5 Correlation-corrected and uncorrected Allan deviation (σ ) calculated from the δ 13 C time series obtained with the same gas permanently passed through the sample cell

ibration phase data blocks, the α and β coefficients are calculated over a time scale of one minute and used according to (2) to correct the raw data. These corrected data are also shown in Fig. 5. Compared to the uncorrected ones, their Allan deviation shows a real improvement for long integration times. A relative precision of 0.1h is achieved for a 20–30 s integration time. The fact that the standard deviation (σ ) is decreasing continuously with increasing integration time shows that instrumental drifts are well corrected by the procedure proposed. Drifts on the time scale of several 10 s seem to be precision limiting in the case of the uncorrected data, however.

5 Tank analysis To calibrate our system and to characterize the instrumental accuracy obtained in the new configuration, we used three tanks filled with dried and compressed atmospheric air (see Table 2). These tanks were precisely measured by a Finnigan MAT-252 mass spectrometer, equipped with a trapping box adapted from Werner et al. [23], for the isotopic composition of CO2 . Their total CO2 content (χCO2 ) has been determined using an automated gas chromatographic system (HP-6890), described in Pépin et al. [24]. Measurements with the TDL spectrometer have been done using two tanks at a time, considering one as the calibration tank and the


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Fig. 6 Isotopic composition δ 13 C (with respect to VPDB) and total CO2 concentration χCO2 measurements of tank #49 (unknown gas) obtained with the correction method based on correlations and tank #50 as the calibration gas. The measurements are done every 40 s

Table 2 Total CO2 mixing ratio χCO2 and isotopic composition δ 13 C (given with respect to the VPDB standard) of the three tanks used in the present study. Values were obtained on one hand by an automated gas chromatographic (GC) system and an isotope ratio mass spectrometer (IRMS) and on the other hand by the SIMCO instrument. Reported uncertainties correspond to 1σ -standard deviation (SD) for a single measurement δ 13 C [h]/VPDB

#50

IRMS

−9.09 ± 0.02

SIMCO SIMCO

#57

#49

#50–#49

#57–#49

−8.53 ± 0.02

−8.67 ± 0.02

−0.42

+0.14

−8.47 ± 0.27

Calib. gas −8.57 ± 0.15

Calib. gas

SIMCO-IRMS

+0.20 −0.52 −0.10

+0.06

χCO2 [ppmv]

#50

#57

#49

#50–#49

#57–#49

1-6 GC

395.08 ± 0.05

385.90 ± 0.03

387.95 ± 0.04

7.13

−2.05

385.89 ± 0.06

SIMCO SIMCO

Calib. gas

SIMCO-GC

other one containing an “unknown” sample gas. Before analyzing each tank the whole sampling line is carefully purged with the measurement gas. Employing the above correction technique and switching gases every 20 s, a precision (1σ ) of 0.15h for δ 13 C and 0.05 ppmv for χCO2 is demonstrated over a 1.5-hour period (Fig. 6). In this configuration, one data point is obtained every 40 s. The isotopic composition δ 13 C and the total CO2 content χCO2 resulting from the analyses of the different tanks are given in Table 2, together with the differences between the tanks. Note that Xχcalib and Yχ calib in (2) are deduced from the values determined by GC and IRMS and reported in Table 2 for the designated calibration tank. From Table 2 we see that the isotopic compositions and mixing ratios measured with the SIMCO instrument are very close to those determined by IRMS and GC with differences equal to or smaller than 0.1h and 0.03 ppmv, respectively (see values in bold in Table 2). These results show the high precision and high accuracy of the measurements obtained with the SIMCO instrument applying the correction method proposed.

−2.06

Calib. gas 387.98 ± 0.03

7.10 −0.03

+0.01

Note that the method described here imposes only modest instrumental constraints on the different parameters influencing the absorption signals in the different cells. Due to the fact that laser emission seems to be the major cause for the correlations, the reference cell can be filled with pure CO2 or with an air-CO2 mixture. Nevertheless, pure CO2 at low pressure should be preferred to better determine the laser emission line width. The two cells can also have different path lengths as in our case. The sensitivity of the derived isotopic composition on temperature due to a difference of 1383.5 cm−1 between the two lower state energies ( E ) of the selected transitions is strong. A variation of 0.01 K already leads to a 0.23h uncertainty on δ 13 C. It must be pointed out, however, that such a temperature difference between reference and sample cells is not critical, as long as temperatures remain stable over the time of a measurement and calibration period, because we ultimately compare measurement gas with calibration gas. The characteristic time of temperature variations inside the aluminum block where the cells are placed, is so large with respect to one measurement

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phase that rapid switching allows to keep temperature differences between the two gases well below 0.001 K (if we assume that the gases are thermalized at the cell temperature). Consequently, a passive temperature regulation seems by far sufficient. The only active temperature regulation relied on here is the air-conditioning of the laboratory (±0.5 K). It should also be emphasized that no nitrogen purge of the optical module is required, because it is well isolated from the outside so that the time scale of exchange with atmospheric CO2 is much longer than the period in which calibration and the measurement gases are switched. Moreover, interferences due to atmospheric CO2 inside the optical module are compensated through the third channel, whose optical path length is matched carefully to that outside the cells of the other two channels.

6 Measurement campaign Long-term performance has been checked during a new measurement campaign. The instrument was placed on a site in central Paris (Jussieu campus of University Pierre et Marie Curie) during few days in the framework of a campaign dedicated to the determination of CO2 fluxes over the Paris agglomeration (ANR CO2 -MEGAPARIS) and in the context of a much larger project on atmospheric chemistry monitoring (European project MEGAPOLI). Two sampling lines from Dekabon tube were mounted with their inlets installed at the same place on the roof of a building (about 20 m from the ground). These sampling lines (Fig. 7) passed through individual cold traps (glass traps immersed in an alcohol bath at ∼ 220 K) to remove water vapor from the air, with their outlets being connected to an automatic flask sampler [25] and to the SIMCO instrument, respectively. Both instruments were placed in the same room where the temperature varied between 21 ◦ C and 26 ◦ C during the cam-

Fig. 7 Schematic view of the sampling system used during the measurement campaign

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paign. A stainless steel in-line particulate filter (with 0.5 µm pore size) was installed at the laser diode spectrometer inlet to get rid of most of the aerosols. Air entering the sampling line takes about 5 min to reach the spectrometer absorption cell. Due to a similar delay on the line connecting to the flask sampler, the same air masses are measured with an average of 2 min shift between the flask sampler and the SIMCO instrument. This shift, which is slightly variable by a few minutes is mostly explained by the time required to close the automatic flask, which cannot be precisely determined. Different flow rates of the pumping systems also contribute to this shift. Each flask was flushed with atmospheric air during 1 or 2 hours (depending on the prescribed sampling time resolution) before being pressurized during 40 s to reach a pressure of ∼ 0.5 bar above atmospheric pressure. Flask samples have then been analyzed at LSCE using the GC instrument mentioned above. For each flask, the CO2 mixing ratio is measured twice by GC (two injections of air sample) following the current analysis protocol and including quality control check. During the campaign the measurement sequence of the SIMCO instrument was slightly modified by switching every 25 s instead of 20 s between the calibration gas (tank #50) and the atmospheric air. The prolongation of the measurement phase was necessary to account for the increased stabilization time in the sample cell due to air and calibration gas being at different pressures (1.0 and 1.2 bar, respectively), thus implying a significant pressure change in the cell upon switching gases. As recommended in Ref. [15] we used an independent quality control (QC) tank (tank #49), which has been treated as an unknown measurement gas in order to assess the instrumental precision and possible drift. Every hour, this QC gas, which serves to quantify a maximum of possible errors, was passed instead of the atmospheric air for a duration of 10 min. To ensure that calibration gas and atmospheric air both reached the same temperature (that of the sample cell), they have been directed through the meandering steel line described in Sect. 3 above. The performance of this thermalization system was checked by comparing QC tank measurements with and without passing the cold trap (∼ 220 K). The test revealed a small bias of (−0.14 ±0.08)h for the δ 13 C measurements. If this can be attributed to a difference in the gas temperatures, it corresponds to a temperature difference of ∼ 0.006 K, showing the very good efficiency of the thermalization system. Long-term performances are shown on Fig. 8, which displays histograms of the QC gas measurements (50 s measurement time) during the whole campaign (N = 550). The histograms have a normal distribution and are then fitted with a Gaussian profile. The fitted profile for δ 13 C is centered at −8.57h and has a half width corresponding to a 1σ precision of 0.15h. In the case of χCO2 these two parameters are 387.99 ppmv and 0.03 ppmv, respectively. The


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Fig. 8 Histograms of the isotopic composition δ 13 C (with respekt to VPDB) and total CO2 concentration χCO2 measured for the quality control tank (tank #49) during the whole campaign

Fig. 9 Time series of CO2 mixing ratios χCO2 and δ 13 C (with respect to VPDB) obtained by TDLS measurements and analysis of collected flasks

observed level of precision is very close to that demonstrated for the tank analyses (Sect. 5). It also compares well with the long-term precisions of δ 13 C reported by Tuzson et al. [13] (0.29h) and by Schaeffer et al. [15] (0.20h under ideal conditions). During the field campaign 17 flasks containing atmospheric air have been collected. Time series of CO2 mixing ratios and of δ 13 C obtained by TDLS measurements and flask analyses are presented in Fig. 9, taking into account the small sampling delay between flask and laser samples. Measured CO2 concentrations range from 407 ppmv to 440 ppmv and δ 13 C varies between −10h and −12h. Dur-

ing the first two days of measurement relatively large variations of concentration and of δ 13 C between day and night are observed, as expected for a polluted area. These variations are attenuated during the third day. Rapid fluctuations of the CO2 mixing ratio (1 ppmv min−1 ) are measured especially during the second day. A more detailed discussion of the results will be presented elsewhere (article in preparation), but we already note that there is good agreement for the total CO2 concentration between the flasks and the diode laser measurements, which corroborate the validation of the SIMCO instrument conducted on a previous campaign [12].

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Fig. 10 Keeling plot for the TDLS measurements of atmospheric air obtained during the whole campaign

We applied the Keeling plot approach [26] to the time series presented in Fig. 9 to estimate the isotopic composition of CO2 produced by fossil fuel consumed in urban heating systems and car engines. This approach assumes that the atmospheric CO2 concentration is the sum of two sources, which are the background atmosphere above the site of Jussieu and local/regional sources due to fossil fuel combustion. The integrated isotopic composition of the regional sources corresponds to the intercept when plotting δ 13 CO2 versus 1/χCO2 . The corresponding Keeling plot from the SIMCO data during the campaign is shown in Fig. 10. The intercept of the linear fit is equal to (−36.40 ± 0.23)h, which is coherent with the isotopic composition resulting from the mixed combustion of natural gas, petroleum and coal.

7 Conclusion We have investigated the instrumental fluctuations in sample and reference cells of a diode laser spectrometer for the measurement of concentration and isotopic composition of atmospheric CO2 . These fluctuations are most likely due to instabilities of the laser diode and highly correlated between the two cells. We propose a correction of the signal fluctuation based on this correlation. With this correction scheme, we show a measurement precision and accuracy better than 0.2h for δ 13 C and 0.05 ppmv for the total CO2 concentration, over less than 1 min integration time. This level of performance has been demonstrated during short-term (few hours) laboratory measurements and a longer-term (3-days) measurement campaign. A critical point for long-term measurements is the consumption of the calibration gas. With

the current instrumental configuration and measurement sequence a 50 L calibration tank filled at 200 bar is consumed in ∼ 40 days for a full time operation of the instrument. Modifying the measurement sequence can further reduce the consumption of calibration gas. With a sequence of 20 s of calibration and 60 s of sampling we can decrease the consumption compared to the current sequence (20 s of calibration and 20 s of sampling) by a factor of 2. Importantly, the new cycle does also not lead to a loss of precision (1σ = 0.12h calculated with the new sequence instead of 0.16h with the current sequence). This is due to longer averaging the sample gas (85 instead of 17 cycles). This leads to an autonomy of ∼ 80 days for the calibration tank which becomes more suitable for long-term measurements. Autonomy of 80 days also compares favorably with other longterm measurements reported in the literature [15], where 48 calibration tanks have been used during 2.4 years of continuous measurements. Moreover, the 75% duty cycle resulting from this new sequence is higher than duty cycles reported by others (Tuzson et al. (2008) have a duty cycle of 67% with 10 min of calibration + 20 min of measurements and Schaeffer et al. (2008) invoke a duty cycle of 60% with 4 min of calibration + 6 min of measurements). In order to further decrease the consumption of the calibration gas, the volume of the sample cell could be reduced by using the entire mirror surfaces for multi-pass reflections while keeping the actual absorption path length. Developments along these lines show that the instrument is now ready for short- and even long-term atmospheric measurements. The system integrity and reliability has been clearly demonstrated, showing that accurate, high-frequency and on-line measurements of isotopic composition and concentration of CO2 are possible.

Isotopic composition and concentration measurements Acknowledgements Financial support from CNRS/INSU and IPSL is gratefully acknowledged. We deeply acknowledge Vincent Bazantay for the flask analysis (CO2 ) at LSCE.

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