ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus GmbHGöttingen, Germany10.5194/acp-15-1901-2015An estimation of the 18O / 16O ratio of UT/LMS ozone based on artefact CO in air sampled during CARIBIC
flightsGromovS.sergey.gromov@mpic.dehttps://orcid.org/0000-0002-2542-3005BrenninkmeijerC. A. M.Max Planck Institute for Chemistry, Mainz, GermanyS. Gromov (sergey.gromov@mpic.de)24February20151541901191225July201415August20145January201523January2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://www.atmos-chem-phys.net/15/1901/2015/acp-15-1901-2015.htmlThe full text article is available as a PDF file from https://www.atmos-chem-phys.net/15/1901/2015/acp-15-1901-2015.pdf
An issue of O3-driven artefact production of O3 in the upper
troposphere/lowermost stratosphere (UT/LMS) air analysed in the CARIBIC-1
project is being discussed. By confronting the CO mixing and isotope ratios
obtained from different analytical instrumentation, we (i) reject
natural/artificial sampling and mixing effects as possible culprits of the
problem, (ii) ascertain the chemical nature and quantify the strength of the
contamination, and (iii) demonstrate successful application of the isotope
mass-balance calculations for inferring the isotope composition of the
contamination source. The δ18O values of the latter indicate that the
oxygen is very likely being inherited from O3. The δ13C values
hint at reactions of trace amounts of organics with stratospheric O3
that could have yielded the artificial CO. While the exact contamination
mechanism is not known, it is clear that the issue pertains only to the
earlier (first) phase of the CARIBIC (Civil Aircraft for the Regular Investigation of the
atmosphere Based on an Instrument Container) project. Finally, estimated UT/LMS ozone
δ18O values are lower than those observed in the stratosphere
within the same temperature range, suggesting that higher pressures
(240–270 hPa) imply lower isotope fractionation controlling the local
δ18O(O3) value.
Introduction
Accurate determination of the atmospheric carbon monoxide (CO) content based
on the collection of air samples depends on the preservation of the mixing
ratio of CO inside the receptacle, from the point of sampling to the moment
of physicochemical analysis in a laboratory. A well known example in our
field of research is the filling of pairs of glass flasks at South Pole
Station for analysis at NOAA in Boulder, Colorado, USA (Novelli et al.,
1998). There, the duplicate air sampling allowed for a degree of quality
control, which in view of the long transit times, especially during polar
winter, was a perhaps not perfect, but certainly a practical measure. Here we
deal with a different case: using aircraft-based collection of very large air
samples rendered duplicate sampling unpractical, yet analyses could be
performed soon after the sampling had taken place because of the proximity of
the aircraft's landing location to the laboratory involved. A presumption of
the analytical integrity of the process was that the growth of CO in
receptacles is gradual and takes its time. We remember Thomas Henry Huxley's
statement, “The great tragedy of science – the slaying of a beautiful
hypothesis by an ugly fact”; it turned out, however, that for air we
collected in stainless steel tanks in the upper troposphere/lowermost
stratosphere (UT/LMS), higher CO values were measured in the laboratory than
measured in situ during the collection of these air samples. Moreover,
measurement of the stable oxygen isotopic composition of CO from these tanks
revealed additional isotopic enrichments in 18O of 10 ‰ or
more. It was soon realised that this phenomenon was due to the formation of
CO in these tanks and/or possibly in the sampling system and inlet tubing
used, by reactions involving ozone (Brenninkmeijer et al., 1999).
Unexpectedly high 18O / 16O ratios in stratospheric ozone
(O3) were discovered by Konrad Mauersberger using a balloon-borne mass
spectrometer (Mauersberger, 1981), which has triggered a series of
theoretical and experimental studies on atmospheric O3 heavy isotope
enrichments (see, e.g. Schinke et al. (2006) for a review). In view of the
advances in theoretical and laboratory studies on the isotopic composition of
O3 atmospheric measurements are welcome, they do however form a
challenge. In the stratosphere, O3 number concentrations are high, but
the remoteness of the sampling domain is a problem. In the troposphere, low
O3 number densities are the main obstacle, as indicated by few
experiments performed to date (Krankowsky et al., 1995; Johnston and Thiemens,
1997; Vicars and Savarino, 2014). Nevertheless, recent analytical
improvements, namely the use of an indirect method of reacting atmospheric
O3 with a substrate that can be analysed for the isotopic composition of
the O3-derived oxygen (Vicars et al., 2012), has greatly improved our
ability to obtain information on the O3 isotopic composition.
Although the increase of CO concentrations in air stored in vessels is a well
recognised problem, to our knowledge a specific O3-related process has
not been reported yet. Here we discuss this phenomenon and turn its
disadvantage into an advantage, namely that of obtaining an estimate of the
oxygen isotopic composition of O3 in the UT/LMS, an atmospheric domain not
yet covered by specific measurements. The air samples we examine in this
study were collected onboard a passenger aircraft carrying an airfreight
container with analytical and air/aerosol sampling equipment on long distance
flights from Germany to South India and the Caribbean within the framework of
the CARIBIC (Civil Aircraft for the Regular Investigation of the
atmosphere Based on an Instrument Container,
http://www.caribic-atmospheric.com) project.
Experimental and resultsWhole air sampling
CARIBIC-1 (Phase #1, abbreviated hereafter “C1”) was operational from
November 1998 until April 2002 using a Boeing 767-300 ER operated by LTU
International Airlines (Brenninkmeijer et al., 1999). Using a whole air
sample (WAS) collection system, 12 air samples were collected per flight
(of 8–10 h duration at cruise altitudes of 10–12 km) in stainless steel
tanks for subsequent laboratory analysis of the mixing ratios (i.e. mole
fractions) of various trace gases, including 14CO. Large air samples
were required in view of the ultra-low number density of this mainly
cosmogenic tracer (10–100 molecules cm-3 standard temperature and
pressure (STP), about 0.4–4 amol mol-1). Hereinafter STP denotes dry
air at 273.15 K, 101 325 Pa. Each C1 WAS sample (holding 350 L of air
STP) was collected over 15–20 min intervals representing the number
density-weighted average of the compositions encountered along flight
segments of about 250 km. The overall uncertainty of the measured WAS CO is
less than ±1 % for the mixing ratio and
±0.1 ‰ / ±0.2 ‰ for
δ13C(CO)/δ18O(CO), respectively (Brenninkmeijer, 1993;
Brenninkmeijer et al., 2001). Isotope compositions are reported throughout
this manuscript using the so-called delta value
δi=(iR/iRst-1) relating the ratios R of rare
(13C, 18O or 17O) over abundant isotopes of interest to the
standard ratios Rst. The latter are Vienna Standard Mean Ocean Water
(VSMOW) for 18O / 16O (Gonfiantini, 1978; Coplen, 1994) and
17O / 16O (Assonov and Brenninkmeijer, 2003), and Vienna Pee Dee
Belemnite (VPDB) for 17O / 16O (Craig, 1957), respectively. As we
mention above, the oxygen isotope composition of the CO present in these WAS
samples was corrupted, in particular when O3 levels were as high as
100–600 nmol mol-1.
CARIBIC-2 (Phase #2, referred to as “C2”)
started operation in December 2004 with a Lufthansa Airbus A340-600
fitted with a new inlet system and air sampling lines, including
perfluoroalkoxy alkane (PFA) lined tubing for trace gas intake
(Brenninkmeijer et al., 2007). No flask CO mixing/isotope ratio measurements
are performed in C2.
On-line instrumentation
In addition to the WAS collection systems, both C1 and C2 measurement setups
include different instrumentation for on-line detection of [CO] and [O3]
(hereinafter the squared brackets [] denote the mixing ratio of the
respective species). In situ CO analysis in C1 is done using a gas
chromatography (GC)-reducing gas analyser which provides measurements every
130 s with an uncertainty of ±3 nmol mol-1 (Zahn et al., 2000).
In C2, a vacuum ultraviolet fluorescence (VUV) instrument with lower
measurement uncertainty and higher temporal resolution of
±2 nmol mol-1 in 2 s (Scharffe et al., 2012) is employed.
Furthermore, the detection frequency for O3 mixing ratios has also
increased, viz. from 0.06 Hz in C1 to 5 Hz in C2 (Zahn et al., 2002, 2012).
(a) Distribution of CO mixing ratios as a function of concomitant
O3 mixing ratios measured by CARIBIC in the LMS ([O3] > 300 nmol mol-1). The shaded area is the two-dimensional histogram of the C2
measurements (all C2 data obtained until June 2013) counted in 5 × 1 nmol mol-1 size [O3] × [CO] bins, thus darker areas emphasise
greater numbers of particular CO–O3 pairs observed. Small symbols
denote the original C1 in situ measurements (black) and corrected for the
artefacts (red); the C1 WAS analyses (11 of total 408) are shown with large
symbols. Thin and thick step lines demark the inner and outer statistical
fences (ranges outside which the data points are considered mild or extreme
outliers, see text) of the C2 data, respectively. The dashed curve
exemplifies compositions expected from the linear mixing of very different
(e.g. tropospheric and stratospheric) end members. (b) Statistics on CO
mixing ratios from C1 and C2 data shown in box-and-whisker diagrams for
samples clustered in 20 nmol mol-1 O3 bins (whiskers represent
9th / 91st percentiles). (c) Sample statistic for each CARIBIC
data set (note the C2 figures scaled down by a factor of 1000). (d) Estimates
of the C1 in situ CO contamination strength [COc] as a function of
[O3] (solid line) obtained by fitting the difference Δ[CO]
between the C2 and C1 in situ [CO] (small symbols) as detailed in Appendix A
(Eq. A2). Step line shows the Δ[CO] for the statistical averages
(the shaded area equals the height of the inner statistical fences of the C2
data). Large symbols denote the estimates of [COc] in the C1 WAS data
(slight variations vs. the in situ data are due to the sample mixing
effects, see Sect. 3). Colour denotes the respective C1 WAS
δ18O(CO) (note that typically 6–7 in situ measurements correspond
to one WAS sample).
Results
When comparing the CO mixing ratios in relation to those of O3 for C1
and C2, differences are apparent in the LMS, where C2 [CO] values are
systematically lower. This is illustrated in Fig. 1a which presents the
LMS CO–O3 distribution of the C2 in situ measurements overlaid with the
C1 in situ and WAS data. The entire C1 CO/O3 data set is presented in
Fig. 2. For the in situ CO data sets we calculated the statistics (Fig. 1b) of the samples with respective O3 mixing ratios
clustered in 20 nmol mol-1 bins, i.e. the median and spread of [CO] as a function of [O3]
analysed. The interquartile range (IQR) is used in the current analysis as a
robust measure of the data spread instead of the standard deviation. The LMS
data exhibit large [CO] variations for [O3] between 300 and
400 nmol mol-1, which primarily reflect pronounced seasonal variations
in the NH tropospheric CO mixing ratio. With increasing [O3], [CO]
decreases to typical stratospheric values, and its spread reduces to mere
3.5 nmol mol-1 and less, as [O3] surpasses 500 nmol mol-1.
Despite the comparable spread in C1 and C2 [CO], from 400 nmol mol-1
of [O3] onwards the C1 CO mixing ratios start to level off, with no
samples below 35 nmol mol-1 having been detected, whereas the C2
levels continuously decline. By the 570–590 nmol mol-1 O3 bin,
C1 [CO] of 39.7-1.3+0.7 nmol mol-1 contains some extra
14 nmol mol-1 compared to 25.6-1.1+1.2 nmol mol-1 typical for
C2 values. Overall, at [O3] above 400 nmol mol-1 the
conspicuously high [CO] is marked in about 200 in situ C1 samples, of which
158 and 69 emerge as statistically significant mild and extreme outliers,
respectively, when compared against the number of C2 samples
(n>3×105). The conventions here follow Natrella (2003),
i.e. ±1.5 and ±3 IQR ranges define the inner and outer statistical
fences (ranges outside which the data points are considered mild and extreme
outliers) of the C2 [CO] distribution in every O3 bin, respectively. The
statistics include the samples in bins with average [O3] of
420–620 nmol mol-1. None of C1 CO at [O3] above
560 nmol mol-1 agrees with the C2 observations. Because the CO–O3
distribution cannot have changed over the period in question, we find that an
apparent relative excess CO of up to 55 % justifies and investigation
into sampling artefacts and calibration issues.
Unnatural elevations in
δ18O(CO) from WAS measurements are also evident, as shown in
Figs. 3 and 4. The large δ18O(CO) elevations that reach beyond
+16 ‰ are found to be proportional to the concomitant O3
mixing ratios (denoted with colour in Fig. 3) and are more prominent at lower [CO].
Lower δ18O(CO) values, however, are expected based on our knowledge
of UT/LMS CO sources (plus their isotope signatures) and available in situ
observations (Fig. 3, shown with triangles), as elucidated by Brenninkmeijer
et al. (1996) (hereafter denoted as “B96”). That is, the greater the
proportion of stratospheric CO, the greater its fraction stemming from
methane oxidation with a characteristic δ18O of 0 ‰ or
lower (Brenninkmeijer and Röckmann, 1997). This occurs because the sink of CO
at ruling UT/LMS temperatures proceeds more readily than its production, as the
reaction of hydroxyl radical (OH) with CO, being primarily
pressure-dependent, is faster than the temperature-sensitive reaction of OH
with CH4. Furthermore, as the lifetime of CO quickly decreases with
altitude, transport-mixing effects take the lead in determining the vertical
distributions of [CO] and δ18O(CO) above the tropopause, hence
their mutual relationship. This is seen from the B96 data at [CO] below 50
nmol/mol that line-up in a near linear relationship towards the end members
with lowest 18O / 16O ratios. These result from the largest share
of the 18O-depleted photochemical component and extra depletion caused
by the preferential removal of C18O in reaction with OH (fractionation
about +11 ‰ at pressures below 300 hPa, Stevens et al., 1980;
Röckmann et al., 1998b).
We are confident that the enhancements of C1
C18O originate from O3, whose large enrichment in 18O (above
+60 ‰ in δ18O, Brenninkmeijer et al., 2003) is typical
and found transferred to other atmospheric compounds (see Savarino and
Morin (2012) for a review). In Fig. 3 it is also notable that not only the LMS
compositions are affected but elevations of (3–10) ‰ from the bulk
δ18O(CO) values are present in more tropospheric samples with [CO]
of up to 100 nmol mol-1. These result from the dilution of the least
affected CO-rich tropospheric air by CO-poor (however substantially
contaminated) stratospheric air, sampled into the same WAS tank. Such
sampling-induced mixing renders an unambiguous determination of the artefact source isotope signature rather difficult, because neither mixing nor isotope ratios of the admixed air portions are known sufficiently well (see
below).
Differences between the WAS and in situ measured [CO] – a possible
indication that the δ18O(CO) contamination pertains specifically to
the WAS data – average at
Δ‾(WAS – in situ)=5.3± 0.2 nmol mol-1 (±1 standard deviation of
the mean, n=408). These differences also happen to be random with respect to any operational
parameter or measured characteristic in C1, i.e. irrespective of CO or
O3 abundances. The above-mentioned discrepancy remained after several
calibrations between the two systems had been performed, and likely results
from the differences in the detection methods, drifts of the calibration
standards used (see details in Brenninkmeijer et al., 2001) and a short-term
production of CO in the stainless steel tanks during sampling. The large
spread of Δ(WAS – in situ) of ±3.5 nmol mol-1
(±1σ of the population) ensues from the fact that the in situ
sampled air corresponds to (2–4) % of the concomitantly sampled WAS
volume, as typically 6–7 in situ collections of 5 s were made throughout one
tank collection of 17–21 min. The integrity of the WAS CO is further
affirmed by the unsystematic distribution of the artefact compositions among
tanks (in contrast to that for δ18O(CO2) in C1 discussed by
Assonov et al., 2009). Overall, the WAS and in situ measured CO mixing ratios
correlate extremely well (adj. R2=0.972, slope of 0.992 ± 0.008
(±1σ), n=408). However, both anomalies in [CO] and
δ18O(CO) manifest clear but complex influences of the concomitant
[O3]. That is, the C1 in situ and WAS [CO] and δ18O(CO) data
very likely evidence artefacts pertaining to the same O3-driven effect.
Below we discuss and quantify these influences.
(accompanies Fig. 1) Carbon monoxide and ozone mixing ratios measured
in C1. Small black symbols denote the C1 in situ measurements (n = 12 753). The C1 WAS analyses (n=408) are shown with large symbols;
colour denotes the concomitant δ18O(CO) measurements. Thin and
thick step lines denote the inner and outer statistical fences of the C2
data, respectively. The dashed curve exemplifies compositions expected from
the linear mixing of tropospheric and stratospheric end members (see caption
to Fig. 1 for details).
18O / 16O isotope composition of CO as a function of its
reciprocal mixing ratio. Triangles present the data from the remote SH UT/LMS
obtained by Brenninkmeijer et al. (1996) (B96). Colour refers to the
concomitantly observed O3 abundances; note the extremely low [O3]
encountered by B96 in the Antarctic “ozone hole” conditions. Filled and
hollow circles denote the original and corrected (as exemplified by the
dashed arrow) C1 WAS data, respectively, with the symbol size scaling
proportional to the estimated contamination magnitude (see text).
Measured C1 WAS δ18O(CO) (not corrected for artefacts) as a
function of concomitant O3 mixing ratio. Symbol colour denotes the
artefact CO component (integral [COc] per each WAS); symbol size scales
proportionally to the WAS CO mixing ratio corrected for artefacts (see Sect. 3 for details).
Discussion
Three factors may lead to the (artefact) distributions seen for C1 in situ
[CO] at LMS O3 mixing ratios, namely:
Strong (linear) natural
mixing, such as enhanced stratosphere–troposphere exchange (STE), when a [CO]
outside the statistically expected range results from the integration of air
having dissimilar ratios of the tracers' mixing ratios,
viz. [O3] : [CO]. For example, mixing of two air parcels in a
16 % : 84 % proportion (by moles of air) with typical
[O3] : [CO] of 700 : 24 (stratospheric) and 60 : 125
(tropospheric), respectively, yields an integrated composition with
[O3] : [CO] of 598 : 40, which indeed corresponds to C1 data (this
case is exemplified by the mixing curve in Fig. 1). Nonetheless, occurrences
of rather high stratospheric CO mixing ratios (in our case, 40 nmol mol-1 at
the concomitant [O3] of 500–600 nmol mol-1 compared to the
typical 24–26 nmol mol-1) are rare. For instance, a deep STE similar
to that described by Pan et al. (2004) was observed by C2 only once (cf. the
outliers at [O3] of 500 nmol mol-1 in Fig. 1), whereas the C1
outliers were exclusively registered in some 12 flights during 1997–2001. No
relation between these outliers and the large-scale [CO] perturbation due to
extensive biomass burning in 1997/1998 (Novelli et al., 2003) is established,
otherwise elevated CO mixing ratios should manifest themselves at lower
[O3] as well. Other tracers detected in CARIBIC provide supporting
evidence against such strongly STE-mixed air having been captured by C1. That
is, the binned distributions for water vapour and de-trended N2O mixing
ratios (not shown here) are similar for C1 and C2. Whereas the small relative
variations in atmospheric [N2O] merely confirm matching [O3]
distributions in CARIBIC, the stratospheric [H2O] distributions witness
no [O3] : [H2O] values corresponding to those of the C1 outliers,
suggesting the latter being unnaturally low.
Mixing effects can also
occur artificially, originating from sampling peculiarities or data
processing. Since the CARIBIC platform is not stationary, about 5 s long
sampling of an in situ air probe in C1 implies integration of the air
compositions encountered along some hundred metres, owing to the high
aircraft speed. This distance may cover a transect between tropospheric and
stratospheric filaments of different compositions. The effect of such
“translational mixing” can be simulated by averaging the sampling data with
higher temporal frequency over longer time intervals. In this respect, the
substantially more frequent CO data in C2 (sampling interval < 1 s)
were artificially averaged over a set of increasing intervals to reckon
whether the long sampling period in C1 could be the culprit for skewing its
CO–O3 distribution. As a result, the original C2 data and their
averages (equivalent to the C1 CO sample injection time) differ negligibly,
as do the respective [O3] : [CO] values. Our simulations of the
“translational mixing” effects confirm that the actual C2 CO–O3
distribution in the region of interest ([O3] of
540–620 nmol mol-1) remains insensitive to averaging intervals of up
to 300 s. Furthermore, a very strong artificial mixing with an averaging
interval of at least 1200 s (comparable to C1 WAS sampling time) is required
to yield the averages from the C2 data with [O3] : [CO] characteristic
for the C1 outliers.
In view of the above, it is unlikely that any
natural or artificial mixing processes are involved in the stratospheric [CO]
discrepancies seen in C1. We therefore conclude that the sample contamination
in C1 occurred prior to the probed air reaching the analytical
instrumentation and WAS sampling tanks in the container, since clearly
elevated stratospheric CO mixing ratios are common to WAS and in situ data.
Two more indications, viz. growing [CO] discrepancy with increasing O3
abundance, and the strong concomitant signal in δ18O(CO), suggest
that O3-mediated production of CO took place. Furthermore, by confronting
the C1 and C2 [CO] measurements in a regression analysis (detailed in
Appendix A), we quantify the artefact component COc as chiefly a
function of O3 mixing ratio as[COc]=b⋅[O3]2,b=(5.19±0.12)×10-5[molnmol-1],
which is equivalent to
8–18 nmol mol-1 throughout the respective [O3] range of
400–620 nmol mol-1 (see Fig. 1d). Subtracting this artefact signal
yields the corrected in situ C1 CO–O3 distribution conforming to that
of C2 (cf. red symbols in Fig. 1a).
Importantly, since we can quantify the contamination strength using only the
O3 mixing ratio, the continuous in situ C1 [O3] data allow
estimating the integral artefact CO component in each WAS sample and, if the
isotope ratio of contaminating O3 is known, to derive the initial
δ18O(CO). The latter, as it was mentioned above, is subject to
strong sample-mixing effects, which is witnessed by δ18O(CO)
outliers even at relatively high [CO] up to 100 nmol mol-1.
Accounting for such cases is, however, problematic since it is necessary to
distinguish the proportions of the least modified (tropospheric) and
significantly affected (stratospheric) components in the resultant WAS sample
mix. Since this information is not available, we applied an ad hoc
correction approach, as described in the following. This approach is capable
of determining the contamination source (i.e. O3) isotope signature as
well.
Contamination isotope signatures
We use the differential mixing model (MM, originally known as the
“Keeling plot”) in combination with the parameterisation of the artefact CO
component (Eq. 1) to derive the isotopic composition of the latter. This
approach makes no assumptions on the isotope signatures of CO in the air
portions mixed in a given WAS tank. The MM parameterises the admixing of the
portion of artefact CO to the WAS sample with the “true” initial composition,
as formulated below:
[CO]=[COt]+[COc],δ(CO)[CO]=δ(COt)[COt]+δ(COc)[COc],
where indices c and t distinguish the components pertaining to the
estimated contamination and “true” composition
sought (i.e. [COt] and δ(COt)), respectively. Here the
contamination strength [COc] is derived by integrating Eq. (1) using the
in situ C1 [O3] data for each WAS sample. By rewriting the above
equation with respect to the isotope signature of the analysed CO, one
obtains
δ(CO)=δ(COc)+(δ(COt)-δ(COc))[COt]/[CO],
which signifies that linear regression of δ(CO) as a function of the
reciprocal of [CO] yields the estimated contamination signature δ(COc) at ([CO])-1→ 0 when invariable “true” compositions
([COt], δ(COt)) are taken (the Keeling plot detailing these
calculations is shown in Fig. 5). We therefore apply the MM described by Eq. (4) to the subsets of samples picked according to the same reckoned
[COt] (within a ±2 nmol mol-1 window, n>7).
Such selection, however, may be insufficient: due to the strong sampling
effects in the WAS samples (see previous Section), it is possible to
encounter samples that integrate different air masses to the same [COt]
but rather different average δ(COt). The solution in this case
is to refer to the goodness of the MM regression fit, because the R2
intrinsically measures the linearity of the regressed data, i.e. closeness
of the “true” values in a regarded subset of samples, irrespective of
underlying reasons for that.
Keeling plot of the data used in the calculations with the mixing
model (MM). The C1 WAS isotope CO measurements are shown with symbols, solid
lines denote the linear regressions through the various sets of samples
selected by the MM (n=80 sets are plotted). Colours refer to the
δ13C (red) and δ18O (green) data, colour intensity
indicates the coefficient of determination (R2) of each regression,
respectively. Darker colours denote higher R2 values, with maxima of
0.92 for δ18O and 0.54 for δ13C data, respectively. The
inferred contamination signatures δ(COc) are found at
([CO])-1→ 0. Regression uncertainties are shown in Fig. 6. Note
that because different subsets of samples contain same data points, some of
the symbols are plotted over (i.e. not all symbols contributing to a
particular regression case may be seen).
Results of the regression calculation with the MM. Shown with symbols
are the contamination source isotope signatures δ(COc) as a
function of the respective coefficient of determination (R2). Colour
denotes the number of samples in each subset selected. Solid and dashed lines
present the best guess ±1 standard deviation of the mean for the
δ18O(COc) and δ13C(COc) estimates. Dashed
circles mark the estimates obtained at highest R2 for
δ18O(COc) regression (above 0.9). See text for
details.
Higher R2 values thus imply higher consistency of the estimate, as
demonstrated in Fig. 6 showing the calculated δ(COc) for
[COt] below 80 nmol mol-1 as a function of the regression
R2. The latter decreases with greater [COt] (i.e. larger sample
subset size, since tropospheric air is more often encountered) and,
correspondingly, larger variations in δ(COt). Ultimately, at
lower R2 the inferred δ18O(COc) converge to values
slightly above zero expected for uncorrelated data, i.e. C1
δ18O(CO) tropospheric average. A similar relationship is seen for
the δ13C(COc) values (they converge around -28 ‰),
however, there are no consistent estimates found (R2 is generally below
0.4). Since such is not the case for δ18O, the MM is not
sufficiently sensitive to the changes caused by the contamination, which
implies that the artefact CO δ13C should be within the range of the
“true” δ13C(CO) values. Interestingly, the MM is rather
responsive to the growing fraction of the CH4-derived component in CO
with increasing [O3], as the δ13C(COc) value of
-(47.2 ± 5.8) ‰ inferred at R2 above 0.4 is characteristic
for the δ13C of methane in the UT/LMS. It is important to note that we
have accounted for the biases in the analysed C1 WAS δ13C(CO)
expected from the mass-independent isotope composition of O3 (see
details in Appendix B).
We derive the “best-guess” estimate of the admixed
CO 18O signature at δ18O(COc) = +(92.0 ± 8.3) ‰,
which agrees with the other MM results obtained at R2
above 0.75. Taking the same subsets of samples, the concomitant 13C
signature matches δ13C(COc) = -(23.3 ± 8.6) ‰, indeed at the upper end of the expected LMS
δ13C(CO) variations of -(25-31) ‰. Because of that, the
MM is likely insensitive to the changes in δ13C(CO) caused by the
contamination (the corresponding R2 values are below 0.1). Upon the
correction using the inferred δ18O(COc) value, the C1 WAS
δ18O(CO) data agree with B96 (shown with red symbols in Fig. 3).
That is, variations in the observed C18O are driven by (i) the
seasonal/regional changes in the composition of tropospheric air and by (ii) the
degree of mixing or replacement of the latter with the stratospheric
component that is less variable in 18O. This is seen as stretching of
the scattered tropospheric values ([CO] above 60 nmol mol-1) towards
δ18O(CO) of around -10 ‰ at [CO] of 25 nmol mol-1, respectively. The corrected C1 δ13C(CO) data (shown in Fig.7) are
found to be in a ±1 ‰ agreement with the observations by B96,
except for several deep stratospheric samples ([CO] below
40 nmol mol-1). The latter were encountered during “ozone hole”
conditions and carried extremely low δ13C(CO) values, which was
attributed to the reaction of methane with available free Cl radicals
(Brenninkmeijer et al., 1996).
Ozone 18O / 16O isotope ratios from literature and this
study.
Notes: values in parentheses denote the average of the estimates' standard errors.
The expected O3 isotope composition on the VSMOW scale is calculated from enrichment 18ϵ
reported relative to O2 using δ18O(O3)VSMOW=δ18O(O2)VSMOW+18ϵ(O3)Air-O2+[δ18O(O2)VSMOW×18ϵ(O3)Air-O2].1 Observations (see Krankowsky et al. (2007) and refs. therein), lowermost values (19–25 km).
Quoted temperature range is derived by matching measured δ18O(O3) and laboratory data (see note 3). 2 This study, C1 observations (10–12 km). Letters denote the estimates derived using the data from Bhattacharya et al. (2008) and assuming only terminal
(T), only central (C) and equiprobable terminal and central (TC) O3 atoms transfer to the artefact CO. 3 Calculated using the laboratory KIE temperature
dependence data summarised by Janssen et al. (2003). 4 Calculated assuming a pressure dependence of the O3 formation KIE similar to that
measured at 320 K (see Guenther et al. (1999) and refs. therein).
18O / 16O and 17O / 16O isotope composition of
CO measured in C1. Triangles present the data from the remote SH UT/LMS obtained
by Brenninkmeijer et al. (1996) (B96). Colour refers to the concomitantly
observed O3 abundances; note the extremely low [O3] encountered by
B96 in the Antarctic ozone-hole conditions. Filled and hollow circles denote
the original and corrected (as exemplified by the dashed arrow) C1 WAS data,
respectively, with the symbol size scaling proportional to the estimated
contamination magnitude (see text for details).
Estimate of δ18O(O3)
The contamination 18O signature inferred here (δ18O(COc) = +(92.0 ± 8.3) ‰) likely pertains to O3 and
is comparable to δ18O(O3) values measured in the stratosphere
at temperatures about 30 K lower than those encountered in the UT/LMS by C1 (see
Table 1 for comparison). If no other factors are involved (see below), this
discrepancy in δ18O(O3) should be attributed to the local
conditions, i.e. the higher pressures (typically 240–270 hPa for C1
cruising altitudes) at which O3 was formed. Indeed, the molecular
lifetime (the period through which the species' isotope reservoir becomes
entirely renewed, as opposed to the “bulk” lifetime) of O3 encountered
along the C1 flight routes is estimated on the order of minutes to hours at
daylight (H. Riede, Max Planck Institute for Chemistry, 2010), thus the
isotope composition of the photochemically regenerated O3 resets quickly
according to the local conditions. Virtual absence of sinks, in turn, leads
to “freezing” of the δ18O(O3) value during night in the UT/LMS.
Verifying the current δ18O(O3) estimate against the kinetic
data, in contrast to the stratospheric cases, is problematic. The laboratory
studies on O3 formation to date have scrutinised the concomitant kinetic
isotope effects (KIEs) as a function of temperature at only low pressures
(67 mbar); the attenuation of the KIEs with increasing pressure was studied only
at room temperatures (see Table 1, also Brenninkmeijer et al. (2003) for
references). A rather crude attempt may be undertaken by assuming that the
formation KIEs become attenuated at higher pressures in a similar
(proportional) fashion to that measured at 320 K, however applied to the
nominal low-pressure values reckoned at (220–230) K. A decrease in
δ18O(O3) of about (6–8) ‰ is expected from such
calculation (cf. last row in Table 1), yet accounting for a mere
one-half of the (13–15) ‰ discrepancy between the stratospheric
δ18O(O3) values and δ18O(COc).
Lower δ18O(COc) values could result from possible isotope
fractionation accompanying the production of the artefact CO. Although not
quantifiable here, oxygen KIEs in the O3→ CO conversion chain
cannot be ruled out, recalling that the intermediate reaction steps are not
identifiable and the artefact CO represents at most 4 % of all O3
molecules. Furthermore, the yield λO3 of CO from O3 may be
lower than unity (see details in Appendix A). On the other hand, the
inference that the contamination strength primarily depends on [O3]
indicates that the kinetic fractionation may have a greater effect on the
carbon isotope ratios of the artefact CO produced (the
δ13C(COc) values) in contrast to the oxygen ones. That is
because all reactive oxygen available from O3 becomes converted to CO,
whilst the concomitant carbon atoms are drawn from a virtually unlimited pool
whose apparent isotope composition is altered by the magnitude of the
13C KIEs.
Besides KIEs, selectivity in the transfer of O atoms from
O3 to CO affects the resulting δ18O(COc) value. The
terminal O atoms in O3 are enriched with respect to the molecular (bulk)
O3 composition when the latter is above +70 ‰ in
δ18O (Janssen, 2005; Bhattacharya et al., 2008), therefore an
incorporation of only central O atoms into the artefact CO molecules should
result in a reduced apparent δ18O(COc) value. Such exclusive
selection is, however, less likely from the kinetic standpoint and was not
observed in available laboratory studies (see Savarino et al. (2008) for a
review). For instance, Röckmann et al. (1998a) established the evidence
of direct O transfer from O3 to the CO produced in alkene ozonolysis. A
reanalysis of their results (in light of findings of Bhattacharya et
al. (2008)) suggests that usually the terminal atoms of the O3 molecule
become transferred (their ratio over the central ones changes from the bulk
2:1 to 1:0 for various species). Considering the alternatives of the O
transfer in our case (listed additionally in Table 1), the equiprobable
incorporation of the terminal and central O3 atoms into CO should result
in the δ18O(O3) value in agreement with the “crude” estimate
based on laboratory data given above.
Furthermore, the conditions that supported the reaction of O3 (or its derivatives) followed by the
production of CO are vague. A few hypotheses ought to be scrutinised here.
First, a fast O3→ CO conversion must have occurred, owing to short
(i.e. fraction of a second) exposure time of the probed air to the
contamination. Accounting for the typical C1 air sampling conditions (these
are as follows: sampled air pressure of 240–270 hPa and temperature of 220–235 K
outboard to 275–300 K inboard, sampling rate of
12.85 × 10-3 mol s-1 corresponding to 350 L STP sampled in 1200 s, inlet/tubing
volume gauged to yield exposure times of 0.01 to 0.1 s due to variable air
intake rate, [O3] of 600 nmol mol-1), the overall reaction rate
coefficient (kc in Eq. (A3) from Appendix A) must be on the order of
(6 × 10-15/τc) molecules-1 cm3, where
τc is the exposure time. Assuming the case of a gas-phase CO
production from a recombining O3 derivative and an unknown carbonaceous
compound X, the reaction rate coefficient for the latter (k in Eq. (A2) in
Appendix A) must be unrealistically high, at least 6 × 10-10 molec-1 cm3 s-1 over τc = 1/100 s. This number
decreases proportionally with growing τc and [X], if we take less
strict exposure conditions. Nonetheless, in order to provide the amounts of
artefact CO we detect, a minimum mixing ratio of 20 nmol mol-1 (or up
to 4 µg of C per flight) of X is required, which is not available in
the UT/LMS from the species readily undergoing ozonolysis, e.g. alkenes.
Second, a more complex heterogeneous chemistry on the inner surface of the
inlet or supplying tubing may be involved. Such can be the tracers' surface
adsorption, (catalytic) decomposition of O3 and its reaction with
organics or with surface carbon that also may lead to the production of CO
(Oyama, 2000). Evidence exists for the dissociative adsorption of O3 on
the surfaces with subsequent production of the reactive atomic oxygen species
(see, e.g. Li et al., 1998, also Oyama, 2000). It is probable that
sufficient amounts of organics have remained on the walls of the sampling
line, exposed to highly polluted tropospheric air, to be later broken down by
the products of the heterogeneous decomposition of the ample stratospheric
O3. Unfortunately, the scope for a detailed quantification of intricate
surface effects in the C1 CO contamination problem is very limited.
Conclusions
Recapitulating, the in situ measurements of CO and O3 allowed us
to unambiguously quantify the artefact CO production from O3 likely in
the sample line of the CARIBIC-1 instrumentation. Strong evidence of that is
provided by the isotope CO measurements. We demonstrate the ability of the
simple mixing model (“Keeling-plot” approach) to single out the
contamination isotope signatures even in the case of a large sampling-induced
mixing of the air with very different compositions. Obtained as a collateral
result, the estimate of the δ18O(O3) in the UT/LMS appears
adequate, calling, however, for additional laboratory data (e.g. the
temperature-driven variations of the O3 formation KIE at pressures above
100 hPa) for a more unambiguous verification.
Contamination assessment
We quantify the C1 CO contamination strength (denoted [COc], obtained by
discriminating the C1 outliers from respective C2 data) in a sequence of
regression analyses. We foremost ascertain that no other species or
operational parameter (e.g. temperature, pressure, flight duration, season,
latitude, time of day, etc.) measured in C1 appear to determine
(e.g. systematically correlate with) [COc], except that for
[O3]. We hypothesise therefore that a production of artefact CO
molecules was initiated by O3 (via either its decomposition or a
reaction with an unknown educt) and proceeded with incorporation of carbon
(donated by some carbonaceous species X) and oxygen (donated by O3 or
its derivatives) atoms into final CO. Despite that neither the actual
reaction chain nor its intermediates are known, it is possible to describe
the artefact component COc produced (hereinafter curly brackets
{} denote number densities) as
{COc}=λO3vτc,
where the yield λO3, a diagnostic quantity, relates the amount of
artefact CO molecules produced to the total number of O3 molecules
consumed in the system, τc denotes the reaction time (period
throughout which sampled air is exposed to contamination), and v stands for
the overall rate of the reaction chain. The latter, being regarded
macroscopically (empirically), is parameterised to account for the order of
reaction chain rate with respect to hypothesised reactants (McNaught and
Wilkinson, 1997) as
v=k{X}K{O3}κ,
where κ and K are the partial orders with respect to X and
O3 number densities, respectively, and k is the rate coefficient. Here
it is implied that changes to {X} and
{O3} are negligible throughout the exposure
time τc (typically < 0.1 s for C1 sample line). As stated
above, we find that variations in {COc}
correlate exclusively with variations in {O3}, hence Eq. (A2) can be reduced by assuming constancy
of {X} and K to
vc=kc{O3}κ.
Here, kc=k{X}K (often
referred to as pseudo-first-order or “observed” rate coefficient)
quantifies the rate of reaction chain exclusively propelled by O3.
Finally, using Eqs. (A1) and (A3), the artefact {COc} component is expressed as
{COc}=b⋅{O3}κ,b=λO3kcτc,
where the constant proportionality factor b integrates the influence of the
unknown (and as we explicate below, likely invariable) {X}, k, K and τc.
Equation (A4) defines the regression expression using which we attempt to fit the
values of {COc} as a function of κ,
{O3} and b. In the first regression
iteration we keep both κ and b as free parameters, which provides
best approximation at κ=2.06± 0.38, suggesting reactions
of two O3 molecules in case elementary reactions constitute the reaction
mechanism, or two elementary steps involving O3 or its derivatives in
case a stepwise reaction is involved (McNaught and Wilkinson, 1997). In a
subsequent regression iteration we set κ=2, which yields
better (as opposed to the first iteration) estimate of b of (5.19 ± 0.12) × 10-5 mol nmol-1 (±1σ, adj. R2=0.83, red. χ2=4.0; here the value of b in mole fraction
units is derived using the air density at C1 sampling conditions for relating
fitted [COc] and observed [O3]2). At last, we ascertain that
the best regression results are obtained particularly at κ=2,
as indicated by the regression statistic (R2 and χ2) that
asymptotically improves when a set of regressions with neighbouring (i.e. below and
above 2) integer values of κ is compared. The low
uncertainty (within ±3 %) associated with the estimate of b confirms
an exclusive dependence of the contamination source on the O3 mixing
ratio, as well as much similar reaction times τc. The regressed value
of [COc] as a function of [O3] is presented in Fig. 1d (solid
line). It is possible to constrain the overall yield λO3 of CO
molecules in the artefact source chain to be between 0.5 and 1, comparing the
magnitude of [COc] to the discrepancy between the [O3] measured in
C1 and C2 (±20 nmol mol-1, taken equal to the [O3] bin size
owing to the N2O–O3 and H2O–O3 distributions matching
well between the data sets). Lower λO3 values, otherwise, should
have resulted in a noticeable (i.e. greater than 20 nmol mol-1)
decrease in the C1 O3 mixing ratios with respect to the C2 levels.
Corrections to measured δ13C(CO) values due to the
oxygen MIF
Atmospheric O3 carries an anomalous isotope composition (or
mass-independent fractionation, MIF) with a substantially higher relative
enrichment in 17O over that in 18O (above +25 ‰ in
Δ17O = (δ17O+1)/(δ18O+1)β-1,
β=0.528) when compared to the majority of terrestrial oxygen
reservoirs that are mass-dependently fractionated (i.e. with Δ17O
of 0 ‰) (see Brenninkmeijer et al. (2003) and refs. therein). CO
itself also has an unusual oxygen isotopic composition, possessing a moderate
tropospheric MIF of around +5 ‰ in Δ17O(CO) induced by
the sink KIEs in reaction of CO with OH (Röckmann et al., 1998b, 2002) and a minor source effect from the ozonolysis of
alkenes (Röckmann et al., 1998a; Gromov et al., 2010). A substantial
contamination of CO by O3 oxygen induces proportional changes to
Δ17O(CO) that largely exceed its natural atmospheric variation. On
the other hand, the MIF has implications in the analytical determination of
δ13C(CO), because the presence of C17O species interferes with
the mass-spectrometric measurement of the abundances of 13CO possessing
the same basic molecular mass (m/z is 45). When inferring the exact
C17O / C18O ratio in the analysed sample is not possible, analytical
techniques usually involve assumptions (e.g. mass-dependently fractionated
compositions or a certain non-zero Δ17O value) with respect to the
C17O abundances (Assonov and Brenninkmeijer, 2001). In effect for the C1
CO data, the artefact CO produced from O3 had contributed with
unexpectedly high C17O abundances that led to the overestimated
δ13C(CO) analysed. The respective bias 13δb is
quantified using
13δb=7.26×10-2Δ17O(CO),
where the actual Δ17O(CO) value is approximated from the
natural CO MIF signal 17Δn and the typical O3 MIF
composition 17Δc as
Δ17O(CO)==(17Δn([CO]-[COc])+17Δc[COc])([CO])-1.
Here [CO] and [COc] denote the analysed CO mixing ratio and contamination magnitude, respectively, used in the contamination assessment
(see Appendix A, Eq. (A4)) and in calculations with the MM (see Sect. 3.1).
For the purpose of the current estimate it is sufficient to take
17Δn of +5 ‰ representing equilibrium enrichments
expected in the remote free troposphere and UT/LMS. For the O3 MIF
signature 17Δc, the value of +30 ‰ (the average
Δ17O(O3) expected from the kinetic laboratory data at
conditions met along the C1 flight routes, see Sect. 3.2 and Table 1) is
adopted. The coefficient that proportionates 13δb and
Δ17O in Eq. (B1) is derived by linearly regressing the
δ13C(CO) biases (simulated using the calculation apparatus detailed
by Assonov and Brenninkmeijer, 2001) as a function of Δ17O(CO)
varying within a (0–30) ‰ range for the CO with initially
unaccounted MIF (e.g. the sample is assumed to be mass-dependently
fractionated). It therefore quantifies some extra +(0.726 ± 0.003) ‰ in the analysed δ13C(CO) per every
+10 ‰ of Δ17O(CO) excess. The most contaminated C1 WAS
CO samples at [O3] above 300 nmol mol-1 are estimated to bear
Δ17O(CO) of +(6–12) ‰ corresponding to fractions of
(0.10–0.27) of the artefact CO in the sample. Accordingly, the reckoned
δ13C(CO) biases span (0.5–0.9) ‰. Although not large,
these well exceed the δ13C(CO) measurement precision of ±0.1 ‰ and were corrected for, and therefore are taken into account
in the calculations with the MM presented in Sect. 3.1.
Acknowledgements
The authors are indebted to Claus Koeppel, Dieter Scharffe and Andreas
Zahn for their work and expertise on the carbon monoxide and ozone
measurements in C1 and C2. Hella Riede is acknowledged for comprehensive
estimates of the species lifetimes along the CARIBIC flight routes. We are
grateful to Patrick Jöckel, Taku Umezawa, Angela K. Baker, Emma C. Leedham,
Sergey Assonov, the anonymous reviewer and Jan Kaiser for the helpful
discussions and comments on the manuscript.The service charges for this open access publicationhave been covered by the Max Planck Society.
Edited by: J. Kaiser
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