The isotopic record of Northern Hemisphere atmospheric carbon

The isotopic record of Northern Hemisphere atmospheric carbon
Atmos. Chem. Phys., 12, 4365–4377, 2012
© Author(s) 2012. CC Attribution 3.0 License.
and Physics
The isotopic record of Northern Hemisphere atmospheric carbon
monoxide since 1950: implications for the CO budget
Z. Wang1 , J. Chappellaz2 , P. Martinerie2 , K. Park1,* , V. Petrenko3,** , E. Witrant4 , L. K. Emmons5 , T. Blunier6 ,
C. A. M. Brenninkmeijer7 , and J. E. Mak1
1 Institute
for Terrestrial and Planetary Atmospheres/School of Marine and Atmospheric Sciences, Stony Brook University,
Stony Brook, NY 11794, USA
2 UJF – Grenoble 1/CNRS, Laboratoire de Glaciologie et Géophysique de l’Environnement (LGGE) UMR5183, Grenoble,
38041, France
3 Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309, USA
4 Grenoble Image Parole Signal Automatique (GIPSA-lab), Université Joseph Fourier/CNRS, BP 46, 38 402 Saint Martin
d’Hères, France
5 National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder CO 80301, USA
6 Centre for Ice and Climate, Niels Bohr Institute, University of Copenhagen, Juliane Maries vej 30,
2100 Copenhagen Ø, Denmark
7 Max Planck Institute for Chemistry, 55128 Mainz, Germany
* now at: Division of Polar Climate Research, Korea Polar Research Institute, Incheon, South Korea
** now at: Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY, USA
Correspondence to: Z. Wang ([email protected])
Received: 24 October 2011 – Published in Atmos. Chem. Phys. Discuss.: 15 November 2011
Revised: 4 April 2012 – Accepted: 24 April 2012 – Published: 16 May 2012
Abstract. We present a 60-year record of the stable isotopes of atmospheric carbon monoxide (CO) from firn
air samples collected under the framework of the North
Greenland Eemian Ice Drilling (NEEM) project. CO concentration, δ 13 C, and δ 18 O of CO were measured by gas
chromatography/isotope ratio mass spectrometry (gc-IRMS)
from trapped gases in the firn. We applied LGGE-GIPSA firn
air models (Witrant et al., 2011) to correlate gas age with
firn air depth and then reconstructed the trend of atmospheric
CO and its stable isotopic composition at high northern latitudes since 1950. The most probable firn air model scenarios show that δ 13 C decreased slightly from −25.8 ‰ in
1950 to −26.4 ‰ in 2000, then decreased more significantly
to −27.2 ‰ in 2008. δ 18 O decreased more regularly from
9.8 ‰ in 1950 to 7.1 ‰ in 2008. Those same scenarios show
CO concentration increased gradually from 1950 and peaked
in the late 1970s, followed by a gradual decrease to present
day values (Petrenko et al., 2012). Results from an isotope
mass balance model indicate that a slight increase, followed
by a large reduction, in CO derived from fossil fuel combus-
tion has occurred since 1950. The reduction of CO emission
from fossil fuel combustion after the mid-1970s is the most
plausible mechanism for the drop of CO concentration during this time. Fossil fuel CO emissions decreased as a result
of the implementation of catalytic converters and the relative
growth of diesel engines, in spite of the global vehicle fleet
size having grown several fold over the same time period.
The importance and interest for measuring atmospheric CO
arises from its significant role in the chemistry of the troposphere, since CO is a major sink for hydroxyl radical (OH).
Hydroxyl radical is the most important oxidant in Earth’s atmosphere, thus its abundance affects the lifetimes of reactive
greenhouse gases and ozone depleting gases. In addition to
its significance for OH, oxidation of CO by OH acts as a
source (in high NOx conditions) or a sink (in low NOx conditions) for ozone, which is a major contributor to ground
Published by Copernicus Publications on behalf of the European Geosciences Union.
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
level photochemical smog (Levy, 1971; Logan et al., 1981).
The major sources of atmospheric CO in today’s atmosphere
include oxidation of methane (CH4 ) and non-methane hydrocarbons (NMHC), biomass burning, fossil fuel and biofuel
combustion (Duncan et al., 2007; Seiler, 1974). In addition
to a complex mixture of sources, atmospheric CO has a relatively short atmospheric lifetime (weeks to months), resulting in large temporal and spatial variations and complicating
the global CO budget. Certain sources produce atmospheric
CO with distinct ratios of 13 C/12 C and 18 O/16 O (Stevens et
al., 1972; Stevens and Wagner, 1989; Brenninkmeijer, 1993),
hence isotopic information can help to determine the various
sources and their relative magnitudes (Mak et al., 2003; Mak
and Kra, 1999; Mak and Brenninkmeijer, 1998; Röckmann et
al., 2002; Manning et al., 1997). Bergamaschi et al. (2000a,
b) reported that including isotope data in model simulations
helps to constrain the source strengths of CO. Thus, measuring the stable isotopes of CO from firn and ice cores would
help constrain relative source strengths in the past. To date,
however, few such observations exist. Polar ice core analyses have provided hints about the evolution of CO from its
concentration (Ferretti et al., 2005; Haan et al., 1996; Haan
and Raynaud, 1998) and isotopic ratios over the last few centuries. For example, recent work revealed the importance of
biomass burning changes in the Southern Hemisphere during
the past 650 years (Wang et al., 2010). Also, a recent study
based on firn air analyses provided a reconstruction of atmospheric CO from Berkner Island, Antarctica, roughly covering the last four decades, which is important for understanding the past CO budget in the Southern Hemisphere (Assonov
et al., 2007). The only available firn air CO measurements
from the Northern Hemisphere are from samples collected
from the summit of Devon Island Ice Cap, Nunavut, Canada
(75◦ 200 N; 82◦ 080 W; 1929 m a.s.l.) in April 1998 (Clark et
al., 2007). However, they showed the existence of in-situ CO
production at depth, which is likely related to the relatively
high temperature of this site, resulting in systematic summer
melting and thick melt layers in the firn column, as well as
relatively high levels of impurities in Devon Island ice (Clark
et al., 2007).
Greenland ice core records have shown that CO concentrations at high northern latitudes increased from ∼90 ppbv
to ∼110 ppbv between 1800 and 1950 (Haan et al., 1996),
which is believed to result from rising anthropogenic emissions, such as fossil fuel combustion (Marland et al., 2008),
and from growing methane concentration. Today’s annual
mean CO concentration over Summit, Greenland (72.58◦ N;
38.48◦ W; 3238 m a.s.l.) is around 120 ppbv based on flask
measurements by National Oceanic and Atmospheric Administration Global Monitoring Division (NOAA/GMD)
(Novelli and Masarie, 2010). Therefore, comparing ice core
and direct atmospheric CO measurements suggests that significant variations of CO concentration and concurrent CO
budget have occurred at high northern latitudes over the last
60 years. However, there is very limited information about
Atmos. Chem. Phys., 12, 4365–4377, 2012
the CO record in the Northern Hemisphere prior to 1980. The
only available atmospheric CO concentration for 1950–1951
was deduced indirectly from infrared total column amount
measurements at the Jungfrau Scientific Station in the Swiss
Alps (Rinsland and Levine, 1985). Sporadic field measurements of atmospheric CO started in the early 1970s (Seiler
and Junge, 1970; Seiler, 1974; Heidt et al., 1980) and systematic global monitoring of atmospheric CO by National
Oceanic and Atmospheric Administration Global Monitoring & Diagnostics Laboratory (NOAA/CMDL) started in the
late 1980s (Novelli et al., 1992, 1994). An increasing trend of
atmospheric CO at Cape Meares, Oregon (45◦ N; 125◦ W),
was first recognized in 1979–1982 (Khalil and Rasmussen,
1984), and a decrease in global CO concentrations was observed in the early 1990s (Khalil and Rasmussen, 1994; Novelli et al., 1994).
In this study, measurements of CO concentration and stable isotopic ratios are carried out on Greenland firn air samples to provide the longest CO isotope records for the Northern Hemisphere. Because of signal smoothing by diffusion
of gases in firn air (Schwander and Stauffer, 1984), firn air
measurements do not provide discretely resolved time evolutions of trace gas concentrations and isotopic ratios. Models of trace gas transport in firn are thus used to derive a reconstruction from the observed firn air profile. The evolving
CO budget over the last 50 years at high northern latitudes is
then calculated based on measurements of CO concentration,
δ 13 C, δ 18 O and an isotope mass balance model (Wang et al.,
2010; Mak and Kra, 1999).
Experimental procedures
Eighteen firn air samples from surface to 75.9 m of depth
were obtained close to the NEEM deep drilling site
(77.445◦ N; 51.066◦ W; 2484 m a.s.l.) in July 2008. Details
of the NEEM 2008 firn air campaign have been described
recently (Buizert et al., 2011). The NEEM firn air samples
used here were collected from the 2008 EU borehole (Buizert et al., 2011) in 3 l SilcoCan canisters (Restek Inc.) at
a pressure of 2.8 bar. Before being filled, the SilcoCans already included polar firn air from previous expeditions, at
pressure above ambient. The firn air was dried through a
Mg(ClO4 )2 trap placed inline between the pumping unit and
the SilcoCan. The filling procedure included evacuation of
the SilcoCan first, then filling to 1 atm above ambient by
evacuation twice, and lastly filling to 2.8 bar. The surface
sample was collected on 16 July 2008 at 10:00 p.m. local
time. The air samples were analyzed using a previously established protocol (Wang and Mak, 2010) at Stony Brook
University in November/December 2008. Concentration and
isotopic ratios (δ 13 C and δ 18 O) were determined by cryogenic vacuum extraction, gas chromatographic separation,
and continuous-flow isotope ratio mass spectrometry (CFIRMS) (Wang and Mak, 2010). A 100 ml sample (STP) was
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
CO mixing ratio (ppbv)
 O of CO (per mil, VSMOW)
793 794 795 CO concentration and isotope profiles from NEEM firn air
are shown in Fig. 1. A comprehensive discussion of CO concentration will be presented in a separate paper (Petrenko
et al., 2012); in this work, the CO concentration is mainly
used to intercompare our CO observations with other data
sets. Good agreement of the CO concentration trend was observed among four independent labs, although there are differences in absolute values, most probably reflecting different calibration scales (Petrenko et al., 2012). The concentration profiles show that, on the Stony Brook scale, [CO] increases from 85 ppbv to 140 ppbv between the surface and
20 m of depth, followed by a relatively constant value of
around 130 ppbv to a depth of 60 m. The first feature results
from the seasonal variation of atmospheric CO concentrations, which ranged from ∼160 ppbv in February 2008 to
∼90 ppbv in August 2008 in Summit, Greenland (72.58◦ N;
38.48◦ W; 3238 m a.s.l.) (Novelli and Masarie, 2010). The
surface observation on 16 July 2008 thus lies on the downward trend of the seasonal cycle, whereas below about 35 m
depth, the observed firn air CO concentration already reflects
an average atmospheric concentration spanning at least one
year. A gradual increase of CO concentration is then observed from 60 m to 70 m, with a measured peak value of
around 155 ppbv at 70 m, followed by a gradual decrease to
the bottom of the firn.
The CO concentration peak at 70 m in the NEEM firn layer
is reproduced in deep NGRIP (North Greenland Ice Core
Project) firn, as well as deep firn at Summit, Greenland, with
similar peak values (Petrenko et al., 2012), indicating CO
is well preserved in NEEM firn. The measured mixing ratio
profiles for other trace gases such as SF6 also confirm that
most NEEM samples are free of contamination from ambient air and that contamination in the deepest/oldest samples
is minimal (Buizert et al., 2011).
 C of CO (per mil, VPDB)
processed at a flow rate of 50 ml min−1 for each run and 3
to 12 replicates were conducted for each sample. Calibration
gas (CO mixing ratio 141 ppbv; δ 13 C = −45.56 ‰ VPDB;
δ 18 O = −1.94 ‰ VSMOW) (Wang and Mak, 2010) was processed frequently between firn air samples. Analytical precision of 3 ppbv (±1σ ) for CO concentration, 0.3 ‰ (±1σ )
for δ 13 C and 0.8 ‰ (±1σ ) for δ 18 O was obtained for the
100 ml firn air samples (STP).
Firn air samples were also collected from the same borehole (EU borehole in glass flasks and analyzed for CO concentration at CSIRO, Australia; University of Heidelberg,
Germany; as well as at NOAA/GMD, USA, allowing for
inter-laboratory comparison. In addition, the 2008 US borehole (Buizert et al., 2011) was sampled and measured for CO
concentration at NOAA/CMDL and the University of Heidelberg (Petrenko et al., 2012).
Depth (m)
Fig. 1. Observations for the mixing ratio and isotopic ratios of CO
Fig. 1.
in NEEM firn air collected from the EU 2008 borehole. Top panel:
[CO] in this study (triangles); middle panel: δ 13 C of CO in this
study (circles); bottom: δ 18 O of CO in this study (squares). Error
bars are ±1σ standard deviation on replicates of 3 to 12 measurements at each depth level.
A seasonal imprint of both δ 13 C and δ 18 O in the first 0–
50 m is observed in NEEM firn (Fig. 1 and Sect. 4.2). δ 13 C
32 of atmospheric CO at Alert was −29 ‰ in September 1997
−24 ‰ in May 1998, where δ 18 O ranged from −2 ‰ in
August 1997 to 10 ‰ in February 1998 (Röckmann et al.,
2002). The isotope data reflect more enriched values for δ 13 C
below 50 m and for δ 18 O below 60 m. Isotopic fractionation
is expected due to gravitational separation, but its magnitude
can be estimated. As the mass difference between 13 CO and
12 CO is 1 amu, the enrichment with depth of 13 CO with respect to the 12 CO resulting from gravitational fractionation
must be similar as gravitational enrichment of 15 N–14 N versus 14 N–14 N of molecular nitrogen (same mass difference).
In NEEM firn, δ 15 N of N2 amounts to 0.3 ‰ in the deepest
air samples (Buizert et al., 2011). Thus, gravitational enrichment is estimated to be 0.3 ‰ for δ 13 C and 0.6 ‰ for δ 18 O
over the depth of the firn, and cannot account for all of the
observed enrichment of the heavier CO isotopologues. The
remaining isotopic variation is a result of diffusion gradients
in the NEEM firn as well as changes in the isotopic abundance of CO over time.
LGGE-GIPSA models of gas transport in firn
Model description
A 1-D inverse model, initially developed by Rommelaere et
al., 1997, and recently extended to isotopologues, was used to
reconstruct the atmospheric trends of CO isotopes. The full
procedure involves a suite of three models of gas transport
Atmos. Chem. Phys., 12, 4365–4377, 2012
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
in firn (Witrant et al., 2011). The LGGE-GIPSA forward and
diffusivity optimization models used in this study (Witrant et
al., 2011) showed very good performances in a model comparison study based on the two NEEM 2008 firn air pumping
operations (Buizert et al., 2011).
Once the forward model has been properly constrained for
a given firn air pumping site, the second step is to calculate
the atmospheric trend scenario. An infinite number of solutions can fit the data satisfactorily within uncertainties, thus a
regularization term aiming at selecting the simplest solution
is used (Rommelaere et al., 1997). It is based on bounding the
values of the scenario’s second derivative. Isotopic records
in firn are expressed as the deviation from a reference of a
concentration ratio between the major isotopologue and the
target minor isotopologue (δ unit). The variations with depth
of isotopic ratios in firn can be due to atmospheric variations
in the major isotopologue concentrations, the minor isotopologue concentrations, or isotopic fractionation in firn (see e.g.
Trudinger et al., 1997). The scenario reconstruction method
used here is based on separating the effects of the major and
minor isotopologues on their concentration ratio. The effect
of the major isotopologue is first evaluated by using its atmospheric time trend as input to the forward model. A second forward model simulation calculates minor isotopologue
concentrations in firn resulting from the latter scenario and a
constant isotopic ratio in the atmosphere. Then the isotopic
ratios measured in firn are corrected from this major isotopologue effect. This correction approach has been used in previous studies (Trudinger et al., 1997; Francey et al., 1999).
The corrected values are inverted, assuming a constant atmospheric concentration of the major isotopologue. The final
evaluation of the reconstructed atmospheric isotopic ratio is
done by running again both the major and minor isotopologue trends in the forward model (the concentration of the
minor isotope is calculated with the concentration of the major isotope and regular conversion from δ value to minor isotope concentration) in order to check the consistency of the
resulting isotopic ratios in firn with the measured values.
In the case of CO isotopes, a data-based CO concentration
trend at Barrow, Alaska (71.32◦ N; 156.61◦ W; 11 m a.s.l.) is
available only since 1988 (Novelli and Masarie, 2010), thus
an inverse model CO concentration trend (Petrenko et al.,
2012) is used in the reconstruction of atmospheric isotopic
ratios for CO isotopes. Sensitivity tests were performed in
order to evaluate the effect of the uncertainty of the past CO
trend on isotope reconstructions (see Sect. 4.4).
Impact of seasonal cycles on CO firn signals
Atmospheric CO and its stable isotopic ratios undergo strong
seasonal variations (Mak et al., 2003; Manning et al., 1997;
Röckmann et al., 2002). In this section, we aim at understanding how and up to which depth firn results are affected
by seasonality. The regularization term used in the inverse
model for long-term atmospheric trend reconstruction reAtmos. Chem. Phys., 12, 4365–4377, 2012
quires the use of a small second derivative of the scenario.
Thus, the inverse model scenarios cannot capture seasonal
changes. This mathematical limit can be grasped physically
from the fact that a ∼50-year long scenario is reconstructed
from 18 measurement depths in the firn. Our sampling resolution does not allow for a trend reconstruction at sub-annual
time scale. As a consequence, the reconstruction of a long
term atmospheric trend requires us to discard the firn data
strongly influenced by seasonality and/or correct the data
from the effect of seasonality. However, the effect of seasonality on concentrations in firn can be assessed using atmospheric data-based scenarios as input to the forward firn
Mean atmospheric seasonal cycles were estimated from atmospheric records of CO, δ 13 C, and δ 18 O of CO in Iceland
(Supplement). The effect of seasonality on firn records is estimated in Fig. 2 by comparing the impact of two scenarios
with and without seasonality. As recent trends in CO isotopes
are not well known, we assume constant mean annual values
([CO] = 132 ppbv, δ 13 C = −27.5 ‰, and δ 18 O=8 ‰) for the
recent past. The difference between scenarios with/without
seasonality indicates that CO isotopic ratios in firn can be
seasonally influenced down to 50 m depth, and that most of
the observed δ 13 C and δ 18 O variations in the upper ∼40 m
of the NEEM firn can be explained by the effect of seasonality (Fig. 2). However, the amplitude of the seasonal effect
is small between 30 and 40 m depth (less than 0.1 ‰). Between 20 and 30 m, sub-monthly time scale events in the atmosphere still potentially have a significant influence.
For the purpose of inverse modeling, our estimate of the
seasonal effect was considered as acceptable when the corrected values fall within the mean uncertainty of the measured values. Thus, the uppermost 3 data points for δ 13 C and
2 data points for δ 18 O of CO were discarded. Seasonally corrected data were used for deeper firn samples.
Atmospheric trend reconstructions for δ 13 C and
δ 18 O of CO
Best estimate atmospheric trends of CO concentration (from
Petrenko et al., 2012), δ 13 C, and δ 18 O of CO are shown
in Fig. 3. CO concentration trend will be discussed in Petrenko et al., 2012. We focus on CO isotopes here. Atmospheric trends of δ 13 C and δ 18 O are required to explain the
observed variations in deep firn but show small amplitude
variations. The bell shape of the firn signals around 65 m
depth (Fig. 1) is mainly explained by the effect of the major isotopologue which peaks at similar depth in the firn. The
root mean square deviation of the model results with respect
to firn data (RMSDmod ) is 0.27 ‰ for δ 13 C and 0.65 ‰ for
δ 18 O. These numbers are comparable to the experimental
uncertainties. Varying the weight of the regularization term
(e.g. the imposed smoothness of the scenario) has more influence on δ 13 C than δ 18 O (Fig. 4). The optimal solution for
δ 18 O is nearly a linear trend with time. With a less regular
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
796 170
 O of CO (per mil, VSMOW)
798 799 800 801 12
 C of CO (per mil, VPDB)
CO mixing ratio (ppbv)
Fig. 2. Effect of atmospheric seasonality on δ 13 C (left) and δ 18 O (right) of CO in NEEM firn. Measured isotopic ratios are shown as black
2. and green stars show δ 13 C and δ 18 O values corrected from the effect of seasonality. Simulated values with decircles 797 with error
seasonalized atmospheric scenarios are plotted as black lines; simulated values with atmospheric seasonal cycles are plotted as green dashed
lines. The differences between uncorrected (black circles) and corrected (green stars) firn data are the same as the differences between
simulated values without (black lines) and with (green lines) seasonality. The increasing isotopic ratios with depth obtained from constant
scenarios (black lines) illustrate the effect of gravitational fractionation. The purple and blue dashed lines show the effect of shifting the final
date of the simulation (firn drilling date) by plus or minus 15 days, respectively. They are intended to illustrate the effect of atmospheric
variations at a sub-monthly time scale.
firn (0–60 m). The higher/lower atmospheric values with respect to the optimal scenario can be related to higher/lower
values in different depth ranges in firn which result in the oscillating behavior of the scenario (the increasing values below 65 m are associated with an atmospheric increase before
1952). The decreasing atmospheric trend in δ 13 C in 2004–
2008 is overall consistent with atmospheric data in Iceland
(Wang et al., 2012) but it should be noted that at such a
short time scale, the model may not discriminate between
the multi-annual trend and sub-annual events such as seasons
with strong biomass burning events.
Date (yr)
Fig. 3. Best estimate trends of CO concentration (Petrenko et al.,
Fig. 3. and isotopic ratios simulated by LGGE-GIPSA models of
gas transport in firn. Best estimate time trends and uncertainty envelopes in firn are shown as continuous lines and dashed lines, respectively.
scenario, the model essentially tries to reduce the data-model
discrepancy with the data point at 70 m depth. However, due
to the gas age overlaps with the neighboring data points at
68 and 72 m depth, an exact fit of the 70 m depth data would
require a very strong and unrealistic variation in the atmospheric scenario. The variations of RMSDmod when vary34 ing the weight of the regularization term by five orders of
magnitudes are small: 0.63–0.70 ‰. RMSDmod varies more
strongly for δ 13 C of CO: 0.19–0.31 ‰, in relation with a less
stable behavior of the solution (Fig. 4). In the firn, a less regular scenario for δ 13 C produces a steeper slope in the upper
Effect of past CO trend on isotope reconstructions
Isotopic ratios in firn are sensitive to variations of both the
major and minor isotope (see Sect. 4.1). Here we test the effect of uncertainties in the past CO trend on isotopic ratios.
Eleven CO scenarios were built, aiming at covering the range
of uncertainties (see Supplement Fig. S2). Five of them use
NEEM EU hole only CO data and smoothing factors differing by five orders of magnitude, the others use different ways
of averaging single or multi-site simulations and connecting
them to the ice core data (Haan et al., 1996) (with or without rescaling). Supplement Fig. S2 shows the impact on δ 13 C
and δ 18 O of using these different CO scenarios
to reconstruct
33 atmospheric isotopic trends. The induced differences in both
the atmospheric trends and the matching of firn data fall well
within uncertainties illustrated in Figs. 3 and 4. This indicates that the impact on δ 13 C and δ 18 O of using these different CO scenarios to reconstruct atmospheric isotopic trends
is very small.
Atmos. Chem. Phys., 12, 4365–4377, 2012
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
802 803 Fig. 4.trends of CO isotopes and influence of the regularization factor. Best estimate time trends (in black) and the resulting
Fig. 4.804 Best estimate
805 isotopic
ratios in firn are the same as in Fig. 4. The red lines on the right panels show the effect of the CO trend scenario with constant
atmospheric isotopic ratio. Blue lines show the effect of increasing the weight of the regularization term by a factor of 10 (short dashed lines)
and 100 (long dashed lines). Green lines show the effect of decreasing the weight of the regularization term by a factor of 10 (short dashed
lines) and 100 (long dashed lines). The circles with error bars on the right panels show the measurements, and those in grey were not used in
the scenario reconstruction. Grey lines on the left panels show the de-seasonalized atmospheric trends in Iceland (Wang et al., 2012).
Sensitivity to the deepest measurement for
δ 13 C of CO
Trace gas concentrations in deep firn are affected by air removal from the firn by trapping in bubbles. They also undergo wide age distributions. For example, the modeled concentration in firn at the deepest measurement level is dependent on scenario values at earlier dates of its mean age. Thus,
the early scenario values are only partially constrained by firn
Supplement Fig. S3 illustrates the effect of not using the
deepest measurement of δ 13 C as a constraint for the inverse
model. The results remain within error bars between 1940
and 2008 but lead to a somewhat different shape of the scenario for the whole period. Figure S3 suggests that the early
trend in δ 13 C (before ∼1975) is influenced by the last data
source strengths and/or CO loss rates. Isotopic ratios help
to distinguish between CO from different sources (Brenninkmeijer, 1993; Stevens et al., 1972; Stevens and Wagner, 1989). Notably, C18 O is a good tracer for distinguishing combustion-derived CO (e.g. fossil fuel combustion or
biomass burning) from non-combustion-derived CO (e.g.
hydrocarbon oxidation) (Brenninkmeijer and Röckmann,
1997). 18 O enriched sources are fossil fuel combustion,
biomass burning, and biofuel burning (Stevens et al., 1972;
Stevens and Wagner, 1989; Kato et al., 1999; Brenninkmeijer
and Röckmann, 1997).
An isotope mass balance model is used to quantify the different source partitioning (Mak and Kra, 1999; Wang et al.,
2010). The isotope mass balance model
35 used in this study
includes the following equations:
[COi ] = [CO]
[COi ] × δ 18 Oi = [CO] × δ 18 O
Isotope mass balance model and discussions
The variation of CO concentration and the shifts of both isotopic ratios since 1950 indicate significant variations in CO
Atmos. Chem. Phys., 12, 4365–4377, 2012
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
where i denotes a given CO source: fossil fuel combustion, methane oxidation, NMHC oxidation, biofuel burning, biomass burning, direct biogenic and oceanic emission. [COi ] stands for CO concentration from each source
and [CO] is the atmospheric CO concentration derived from
Greenland firn air measurements and diffusion model simulations (Petrenko et al., 2012). δ 18 Oi is the δ 18 O source signature at high northern latitude and δ 18 O is the δ 18 O of atmospheric CO from NEEM firn air measurements and LGGEGIPSA model simulations in this study (Fig. 3). Both the best
estimate of CO concentration and δ 18 O values and envelope
values from LGGE-GIPSA model simulations will be used
to calculate the mean source partitioning and uncertainties.
Only δ 18 O data are used in the mass balance model. δ 13 C
data are not used because δ 13 C signatures for different Northern Hemisphere CO sources are not as isotopically distinct.
For example, the range of values of δ 13 C from biomass burning largely overlaps with the range of values from NMHCderived CO. A more detailed discussion of δ 13 C data is provided in the Supplement .
δ 18 O signatures for different sources and [CO] contributions from these sources in the modern atmosphere at high
northern latitude (Iceland: 63◦ 150 N; 20◦ 090 W) have been
determined using MOZART-4 model simulations (Model for
Ozone and Related Chemical Tracers, version 4) (Emmons
et al., 2010; Park, 2010) (Table 1). Simulations at other high
northern latitudes such as Alert (78.5◦ N; 11.5◦ W) and Spitsbergen (81.3◦ N; 62.3◦ W) show very consistent results for
CO contributions and δ 18 O. δ 18 O source signatures are assumed to be constant over time since the mechanisms of CO
production from different sources, such as fossil fuel combustion, biomass burning, NMHC/CH4 oxidation, etc., are
assumed to have been unchanged over the last 60 years. Concerning the impact of technological advancements on δ 18 O
signature of the road transportation source (an important
source in the following discussion), the δ 18 O signature from
modern automobiles with catalytic converters is very similar to that from old automobiles without catalytic converters
(Tsungaosi et al., 2003; Stevens et al., 1972). Diesel engine
vehicles have depleted δ 18 O emissions compared to gasoline
engine vehicles, but much smaller CO emissions. Thus, we
believe that the impact of the diesel engine vehicle market
share on CO isotopic composition is also very small. We thus
believe technological advancements have a negligible impact
on δ 18 O of CO from the road transportation source.
Methane oxidation
We can effectively determine the contribution of methane to
CO by direct calculation. Assuming steady state, which is
reasonable since the lifetime of CO is much shorter than
the decadal scale we are interested in, the contribution of
methane to CO is only dependent on the abundance of
methane and the ratio of the rate constants for the CH4 -OH
and CO-OH reactions (Eq. 3),
[CO]CH4 = k1 /k2 × [CH4 ]
where [CO]CH4 is the methane-derived [CO], k1 is the rate
constant of the CH4 + OH reaction, k2 is the rate constant of
the CO + OH reaction, and [CH4 ] is the methane concentration. Assuming these rate constants have not changed with
time since 1950, [CO] from methane oxidation at high northern latitudes is calculated based on an atmospheric methane
concentration trend (Buizert et al., 2011) and the following
[CO]CH4 ,n = [CO]CH4,2000 ×[CH4 ]n /[CH4 ]2000
where [CO] CH4 ,n is the methane-derived [CO] in the year
“n”, [CO] CH4 ,2000 is the methane-derived [CO] in the year
2000 by MOZART-4 simulation and inverse model (Park,
2010), [CH4 ]n is the methane concentration in the year “n”,
and [CH4 ]2000 is the methane concentration in the year 2000.
Direct biogenic and marine emissions
In order to reduce the number of parameters in the mass
balance model, two minor sources, direct biogenic and marine emissions, are fixed at today’s estimated values (Table 1). Marine emissions are dependent on the solar radiation (particularly UV irradiance) and dissolved organic matter (DOM) (Bauer et al., 1980; Conrad and Seiler, 1980). UV
irradiance may have increased by 1.4 % since 1610 (Lean et
al., 1995). Large variations of global or hemispheric ocean
DOM amounts did not likely occur either. Marine emissions
are also tiny (1 % of the whole). Direct biogenic emissions
account for 4 % of the CO budget and are likely a result
of direct photochemical transformation occurring inside the
leaf (Tarr et al., 1995). We thus assume that biogenic emissions are dependent on solar radiation and total aboveground
biomass (or roughly vegetation area), both of which have
been relatively constant over the time period of interest (Lean
et al., 1995; Pongratz et al., 2008).
Biomass/biofuel burning emissions
Only two of the remaining three sources (biomass/biofuel
burning, NMHC oxidation, and fossil fuel combustion) can
be calculated. There are no observations indicating the degree of variation for historical NMHC-derived CO, so this
emission is treated as an unknown. For biomass/biofuel burning and fossil fuel combustion, we choose to solve for fossil
fuel instead of biomass burning because of the predominant
impact of fossil fuel combustion source on CO isotopic ratio
(δ 18 O) at high northern latitudes. Model simulations show
that fossil fuel combustion and biomass burning account for
34 % and 10 % of the total CO emission, respectively (Table 1). Fossil fuel combustion is the most enriched source for
18 O (Table 1), which suggests it has the largest impact on
Atmos. Chem. Phys., 12, 4365–4377, 2012
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
Table 1. Atmospheric CO source contributions and δ 18 O at Iceland in Jan 1997–Dec 2004.
Fossil fuel
Methane oxidation
NMHC oxidation
Biomass burning
Source δ 18 O
δ 18 O at Iceland
34 %
21 %
15 %
15 %
10 %
Note: a : these source contributions are a posteriori results based on MOZART-4 and inverse model simulations
(Park, 2010); b : these are original δ 18 O signatures used for each type of emission in the model; c : δ 18 O values
at Iceland are the isotopic ratios calculated in the model based on the source signatures. Note these δ 18 O values
reflect the fractionation of CO after undergoing oxidation by OH during the transport (Wang et al., 2010). Data
after Park (2010).
δ 18 O of CO. More importantly, the δ 18 O value of biomass
burning at high northern latitudes (9 ‰) is close to the δ 18 O
of our firn air observations (7–10 ‰), indicating that a significant biomass burning source change has only a small impact
on firn δ 18 O. Even though fossil fuel emission estimates are
more accurate than biomass burning estimates, a relatively
small variation of the former may have a larger impact than
the uncertainty in biomass burning emissions on our calculation. Therefore we choose to solve for fossil fuel instead of
biomass burning.
The biomass burning contribution is calculated from
present-day model simulations at Iceland for the years 1997–
2004 (Table 1) and historical biomass burning reconstructions. We use historical Northern Hemisphere CO emissions
from biomass burning between 1950 and 2000 (Ito and Penner, 2005) and biomass burning CO contribution at Iceland in
1997–2004 from MOZART-4 and inverse model simulations
(Table 1, Park, 2010) to scale the biomass burning contribution at the NEEM site since 1950 (See Fig. 5). An uncertainty of ±50 % is assigned to the scaling based on the uncertainty suggested in Ito and Penner, 2005. The CO contribution from biomass burning has a ±35 % uncertainty if we
use historical global biomass burning CO emission data instead of Northern Hemisphere biomass burning CO emission
data (Ito and Penner, 2005). CO contributions from biomass
burning calculated from other databases and model simulations (van Aardenne et al., 2001; Lamarque et al., 2010) as
well as global wildfire simulations (Pechony and Shindell,
2010) are within 50 % of the estimates used in this study.
CO derived from biofuels originates mainly from the
Northern Hemisphere (Park, 2010). Between 1950 and 2000,
biofuel use in Asia and Africa grew rapidly as a result of
population growth, and they are now the dominant regions
for such emissions (Fernandes et al., 2007). We use the same
approach for biofuels as for biomass burning, applying both
historical CO emissions from biofuel burning in 1950–2000
(Ito and Penner, 2005) and calculated biofuel-derived CO at
Atmos. Chem. Phys., 12, 4365–4377, 2012
Iceland in 1997–2004 from MOZART-4 and inverse model
simulations (Table 1) to scale the biofuel burning contribution at the NEEM site since 1950 (Fig. 5). Again, an uncertainty of ±50 % is used in the scaling based on the uncertainties suggested in Ito and Penner, 2005. The range of these two
estimates is within the assigned uncertainty. Results based on
other historical global biofuel burning CO emission model
simulations (van Aardenne et al., 2001) are also within the
±50 % envelope. The biomass and biofuel burning inventory
during 1997–2000 used in MOZART-4 simulation is within
the uncertainty of those in historical reconstructions (Ito and
Penner, 2005). The 1997–2000 CO contributions calculated
by MOZART-4 and inverse model simulation also agree well
with those from the scaling method decribed above, except
for the year 1998, which is affected by large wildfires.
Fossil fuel combustion and NMHC oxidation
The two remaining variables are fossil fuel combustion and
NMHC oxidation, which can be evaluated from the above
equations based on the CO reconstruction data from LGGEGIPSA models (Fig. 3).
The temporal evolution of CO partitioning between fossil fuel combustion and NMHC oxidation since 1950 calculated by the isotope mass balance model (Wang et al., 2010)
is shown in Fig. 6. It clearly suggests a dominant control
from fossil fuel combustion variation at high northern latitudes since 1950 on the CO trend (Fig. 3). CO from methane
oxidation has continuously increased since 1950, and since
methane-derived CO is depleted in 18 O, this would lead to a
decrease in δ 18 O. We see no evidence for a significant change
in NMHC oxidation since 1950. However, large changes in
CO emission from fossil fuel combustion are suggested to
have occurred since 1950. CO from fossil fuel combustion
increased slightly from 1950 to the mid-1970s, and decreased
since then by ∼30 % from the mid-1970s to 2000. CO from
fossil fuel combustion was as large as 56 % of all CO sources
at high northern latitudes in 1950, and this is much larger
CO emissions from NH
biofuel burning (Tg CO/yr)
[CO]BF (ppbv)
CO]BB (ppbv)
than the present day contribution (34 % in Table 1). The increase of [CO] from 1950 to the mid-1970s is thus the result
of a combined increase of all sources except for the two fixed
sources. The decrease of δ 18 O during this time is mainly
caused by the increase in CO from methane oxidation. The
simultaneous decrease of CO and δ 18 O after the mid-1970s
requires the decrease of CO contribution from fossil fuel
combustion during this time.
In the above mass balance calculations, OH is assumed to
be constant, and model simulations use a seasonally varying, perpetual annual OH field. It is possible, however, that
the removal rate of CO by OH could have changed. Previous
studies have shown that interannual variations in OH abundance are less than 10 % since the late 1970s (Prinn et al.,
2005; Bousquet et al., 2005). A recent study even suggests
that the interannual variability of global [OH] was less than806 5 % during 1985–2008 (Montzka et al., 2011). As mentioned807 in Petrenko et al., 2012, the possible few percent increase
808 of [OH] during the 1980s could still partially have caused
the decrease of [CO] after 1980 and slightly attenuate our
strong decrease of [CO] from fossil fuel combustion during
that time. However, there is no evidence of significant variations in OH during the time period of interest and we find
it unlikely that a significant component of the temporal variations in CO observations is a result of variations in atmospheric OH.
CO emissions from NH
biomass burning (Tg CO/yr)
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
Year (AD)
Fig. 5. (a) and (c): Estimated CO emissions from Northern Hemisphere biomass and biofuel burning (Tg CO yr−1 ) based on model
Fig. 5.
simulation (Ito and Penner, 2005). Also shown are 1997–2004
Northern Hemisphere CO emission inventory of biomass burning
(van der Werf et al., 2006) (green stars) and biofuel burning (Petron
et al., 2004) (red squares), used in MOZART-4 simulation (Park,
2010). (b) and (d): Calculated CO contribution (ppbv) from biomass
([CO]BB ) and biofuel ([CO]BF ) burning by scaling (see text), which
is used in the isotope mass balance model. Also shown are CO contributions from biomass burning (grey diamonds) and biofuel burning (blue crosses) at high northern latitudes in MOZART-4 simulation (Park, 2010). Shaded areas show the ±50 % uncertainty for
estimating both biomass burning and biofuel burning emissions.
MOZART-4 simulations show that CO at high northern latitudes originates from three major regions: North America,
Western Europe, and Northern Asia (Park, 2010). The historical fossil fuel CO2 emissions in 1950–2006 for these three
regions are shown in Fig. 7. CO2 emissions from fossil fuel
combustion increased from 1950 to the mid-1970s, implying an increase of CO emissions from fossil fuel combustion
during this time (Fig. 6). On the other hand, the decrease
of CO contribution after the mid-1970s from our calculation
(Fig. 6c) goes opposite with a net CO2 emission increase of
∼20 % between the mid-1970s and 2000.
We propose that the reduction of CO from fossil fuel
combustion after the mid-1970s reflects the implementation
of catalytic converters in thermal-engine vehicles in North
America during this time. The catalytic converter was installed in vehicles since the mid-1970s in the United States
and Canada (Kummer, 1980; Young and Finlayson, 1976).
Catalytic converters effectively reduce the CO emission from
vehicle exhaust (Tsunogai et al., 2003) based on the catalyzed oxidation reaction 2CO + O2 →CO2 (Kummer, 1986;
Santra and Goodman, 2002) and their use resulted in a significant decrease of on-road vehicle CO emissions in the US
since 1975 (Parrish, 2006). CO emissions from fossil fuel
combustion would thus have dropped since the mid-1970s,
counteracting the CO growth due to the concomitant CH4 increase.
Catalytic converters were introduced in Europe in 1975
36 and became mandatory in 1993. As a result, CO emissions from fossil fuel combustion in Europe have likely decreased since the 1990s, which can be seen in different emission inventories (Granier et al., 2011). Moreover, growth
of market share for diesel engine vehicles, improvements
in the automobile technologies including three-way oxidation/reduction catalytic converters, electronic ignition, fuel
injection, and engine computer control in the period 1990–
present have possibly resulted in further reductions in vehicle
CO emissions.
Lead in gasoline can “poison” catalytic converters by coating the surface of the catalyst. Vehicle manufacturers thus
required the oil companies to remove lead from gasoline and
substitute it with other chemical compounds to maintain the
octane number (methyl tert-butyl ether (MTBE) in the USA,
or higher concentration of benzene, toluene, ethylbenzene
and xylenes (BTEX) in Europe). The temporal variations of
leaded gasoline consumption in North America and Europe
should roughly reflect the timeline of the application of catalytic converters. In the US, the first step of gradual reduction
of lead in gasoline started in the early 1970s, which preceded
the application of catalytic converters. This suggests the decrease of leaded gasoline consumption preceded the decrease
of CO emissions from fossil fuel combustion. The historical
leaded gasoline consumption in the US and Western Europe
Atmos. Chem. Phys., 12, 4365–4377, 2012
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
812 2000
[CH4] from NEEM firn (Buizert et al., 2011)
[CO] from methane oxidation deduced from Buizert et al., 2011
[CO] from methane oxidation at Iceland (Park, 2010)
813 814 10
Year (AD)
Fig. 7.
Fig. 7. Fossil fuel CO2 emissions in these mid-high latitude Northern Hemisphere regions (Marland et al., 2008). Symbols link to left
y-axis and indicate the CO2 emissions in three different regions:
green triangles: North Asia; blue diamonds: Western Europe; red
squares: North America. Black line links to right y-axis and stands
for the sum of CO2 emissions from the above three regions.
[CO]FF (ppbv)
Mean value from firn air data (This study)
Iceland in 1997-2004 (Park, 2010)
CO]NMHC (ppbv)
Carbon (× 10 g)
North Asia
Western Europe
North America
Total emission of carbon (× 10 g)
Mean value from firn air data (This study)
Iceland in 1997-2004 (Park, 2010)
Year (AD)
Fig. 6.
[CH4] (ppbv)
[CO]CH4 (ppbv)
Fig. 6. Modeled CO source partitioning based on observations
and isotope mass balance model: (a): Methane atmospheric trend at
high northern latitude (Buizert et al., 2011) (red squares) and [CO]
from methane oxidation ([CO]CH4 ) deduced from the methane
concentration (green circles), (b): [CO] from NMHC oxidation
([CO]NMHC ), and (c): [CO] from fossil fuel combustion ([CO]FF ).
Thick lines in (b) and (c) represent the mean values of different
scenarios and shaded areas represent the uncertainties which arise
from the LGGE-GIPSA models simulation uncertainties on both
CO concentration and δ 18 O, as well as the uncertainties for estimating historical CO emissions from biofuel and biomass burning (Ito
and Penner, 2005). [CO] derived from the three major sources since
1950 is calculated based on an isotope mass balance model (Wang
et al., 2010). CO source partitioning at present day is calculated
based on MOZART-4 and inverse modeling and CO measurements
in 1997–2004 at Iceland (orange squares) (Park, 2010).
with the CO reconstruction from different measurement sets
on the same firn air (Petrenko et al., 2012) and an isotope
mass balance model, we calculated the temporal evolution
of CO source partitioning since 1950. Mass balance model
results suggest that variations in fossil fuel-derived CO are
the primary factor behind the observed CO concentration
and its δ 18 O trends at high northern latitude since 1950. The
decrease of CO emission from fossil fuel combustion since
38 the mid-1970s is ascribed to the invention and application
of catalytic converters in the Northern Hemisphere and the
growth of diesel engine vehicle market share in Europe, both
of which reduce CO emissions from vehicles.
Supplementary material related to this article is
available online at:
37 between 1930 and 1990 indicates that the consumption of
leaded gasoline increased sharply in the 1950s and 1960s,
remained high until about 1970 and started to decrease in
the early 1970s (Wu and Boyle, 1997, and reference therein).
Furthermore, vehicle lead emissions in the US dropped more
than 99 %, from 156 003 metric tons in 1970 to 17 metric
tons in 1998 (EPA, 2000). The drop of lead emissions from
vehicles was followed by that of CO emissions from fossil
fuel combustion.
In this study, we present the first record of isotopic ratios
of carbon monoxide at high northern latitudes since 1950
based on measurements on NEEM firn air and the use of
the LGGE-GIPSA models of gas transport in firn. Combined
Atmos. Chem. Phys., 12, 4365–4377, 2012
Acknowledgements. We sincerely thank J. F. Lamarque, O. Pechony, and A. Ito for sharing with us the biomass/biofuel burning
reconstruction data. NEEM is directed and organized by the Center
of Ice and Climate at the Niels Bohr Institute and US NSF, Office of
Polar Programs. It is supported by funding agencies and institutions
in Belgium (FNRS-CFB and FWO), Canada (NRCan/GSC), China
(CAS), Denmark (FIST), France (IPEV, CNRS/INSU, CEA and
ANR), Germany (AWI), Iceland (RannIs), Japan (NIPR), Korea
(KOPRI), The Netherlands (NWO/ALW), Sweden (VR), Switzerland (SNF), United Kingdom (NERC) and the USA (US NSF,
Office of Polar Programs). This work was supported by the National
Science Foundation grant OCE0731406, the European Science
Foundation (ESF) EURO-CORES Programme EuroCLIMATE
(contract ERAS-CT-2003-980409 of the European Commission,
DG Research, FP6), Institut National des Sciences de l’Univers
(INSU) project ISOTRACE-FP21, and the French ANR NEEM
(ANR-O7-VULN-09-001). This work has also received funding
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
from the European Community’s Seventh Framework Programme
(FP7) in the project PEGASOS (grant agreement 265148). We
would like to acknowledge high-performance computing support
provided by NCAR’s Computational and Information Systems
Laboratory, sponsored by the National Science Foundation. The
National Center for Atmospheric Research is funded by the
National Science Foundation.
Edited by: R. van de Wal
Assonov, S. S., Brenninkmeijer, C. A. M., Jöckel, P., Mulvaney, R.,
Bernard, S., and Chappellaz, J.: Evidence for a CO increase in
the SH during the 20th century based on firn air samples from
Berkner Island, Antarctica, Atmos. Chem. Phys., 7, 295–308,
doi:10.5194/acp-7-295-2007, 2007.
Bauer, K., Conrad, R., and Seiler, W.: Photo-oxidative production
of carbon monoxide by phototropic mocroorganisms, Biochim.
Biophys. Acta, 589, 46–55, 1980.
Bergamaschi, P., Hein, R., Brenninkmeijer, C. A. M., and Crutzen,
P. J.: Inverse modeling of the global CO cycle 2. Inversion of
13 C/12 C and 18 O/16 O isotope ratios, J. Geophys. Res.-Atmos.,
105, 1929–1945, 2000a.
Bergamaschi, P., Hein, R., Heimann, M., and Crutzen, P. J.: Inverse
modeling of the global CO cycle 1. Inversion of CO mixing ratios, J. Geophys. Res.-Atmos., 105, 1909–1927, 2000b.
Bousquet, P., Hauglustaine, D. A., Peylin, P., Carouge, C., and
Ciais, P.: Two decades of OH variability as inferred by an inversion of atmospheric transport and chemistry of methyl chloroform, Atmos. Chem. Phys., 5, 2635–2656, doi:10.5194/acp-52635-2005, 2005.
Brenninkmeijer, C. A. M.: Measurement of the abundance of 14 CO
in the atmosphere and the 13 C/12 C and 18 O/16 O ratio of atmospheric CO with applications in New Zealand and Antarctica, J.
Geophys. Res.-Atmos., 98, 10595–10614, 1993.
Brenninkmeijer, C. A. M. and Röckmann, T.: Principal factors determining the 18 O/16 O ratio of atmospheric CO as derived from
observations in the southern hemispheric troposphere and lowermost stratosphere, J. Geophys. Res.-Atmos., 102, 25477–25485,
Buizert, C., Martinerie, P., Petrenko, V. V., Severinghaus, J. P.,
Trudinger, C. M., Witrant, E., Rosen, J. L., Orsi, A. J., Rubino,
M., Etheridge, D. M., Steele, L. P., Hogan, C., Laube, J. C.,
Sturges, W. T., Levchenko, V. A., Smith, A. M., Levin, I., Conway, T. J., Dlugokencky, E. J., Lang, P. M., Kawamura, K., Jenk,
T. M., White, J. W. C., Sowers, T., Schwander, J., and Blunier, T.:
Gas transport in firn: multiple-tracer characterisation and model
intercomparison for NEEM, Northern Greenland, Atmos. Chem.
Phys., 12, 4259–4277, doi:10.5194/acp-12-4259-2012, 2012.
Clark, I. D., Henderson, L., Chappellaz, J., Fisher, D., Koerner, R.,
Worthy, D. E. J., Kotzer, T., Norman, A. L., and Barnola, J. M.:
CO2 isotopes as tracers of firn air diffusion and age in an Arctic
ice cap with summer melting, Devon Island, Canada, J. Geophys.
Res.-Atmos., 112, D01301, doi:10.1029/2006jd007471, 2007.
Conrad, R. and Seiler, W.: Photooxidative production and microbial
consumption of carbon monoxide in seawater, Fems Microbiol.
Lett., 9, 61–64, 1980.
Duncan, B. N., Logan, J. A., Bey, I., Megretskaia, I. A., Yantosca, R. M., Novelli, P. C., Jones, N. B., and Rinsland, C. P.:
Global budget of CO, 1988–1997: Source estimates and validation with a global model, J. Geophys. Res.-Atmos., 112, D22301,
doi:10.1029/2007jd008459, 2007.
Emmons, L. K., Walters, S., Hess, P. G., Lamarque, J.-F., Pfister,
G. G., Fillmore, D., Granier, C., Guenther, A., Kinnison, D.,
Laepple, T., Orlando, J., Tie, X., Tyndall, G., Wiedinmyer, C.,
Baughcum, S. L., and Kloster, S.: Description and evaluation of
the Model for Ozone and Related chemical Tracers, version 4
(MOZART-4), Geosci. Model Dev., 3, 43–67, doi:10.5194/gmd3-43-2010, 2010.
EPA: National air pollutant emission trends: 1900–1998, EPA
Report 454/R-00-002, United States Environmental Protection
Agency, Research Triangle Park, NC 27711, 2000.
Fernandes, S. D., Trautmann, N. M., Streets, D. G., Roden, C. A.,
and Bond, T. C.: Global biofuel use, 1850–2000, Global Biogeochem. Cy., 21, Gb2019, doi:10.1029/2006gb002836, 2007.
Ferretti, D. F., Miller, J. B., White, J. W. C., Etheridge, D. M.,
Lassey, K. R., Lowe, D. C., Macfarling Meure, C. M. M.,
Dreier, M. F., Trudinger, C. M., van Ommen, T. D., and Langenfelds, R. L.: Unexpected changes to the global methane
budget over the past 2000 years, Science, 309, 1714–1717,
doi:10.1126/science.1115193, 2005.
Francey, R. J., Allison, C. E., Etheridge, D. M., Trudinger, C. M.,
Enting, I. G., Leuenberger, M., Langenfelds, R. L., Michel, E.,
and Steele, L. P.: A 1000-year high precision record of δ 13 C in
atmospheric CO2 , Tellus B, 51, 170–193, 1999.
Granier, C., Bessagnet, B., Bond, T., D’Angiola, A., van der Gon,
H. D., Frost, G. J., Heil, A., Kaiser, J. W., Kinne, S., Klimont,
Z., Kloster, S., Lamarque, J.-F., Liousse, C., Masui, T., Meleux,
F., Mieville, A., Ohara, T., Raut, J.-C., Riahi, K., Schultz, M.
G., Smith, S. J., Thompson, A., van Aardenne, J., van der Werf,
G. R., and van Vuuren, D. P.: Evolution of anthropogenic and
biomass burning emissions of air pollutants at global and regional scales during the 1980-2010 period, Climatic Change,
109, 163–190, doi:10.1007/s10584-011-0154-1, 2011.
Haan, D. and Raynaud, D.: Ice core record of CO variations during
the last two millennia: atmospheric implications and chemical interactions within the Greenland ice, Tellus B, 50, 253–262, 1998.
Haan, D., Martinerie, P., and Raynaud, D.: Ice core data of atmospheric carbon monoxide over Antarctica and Greenland during
the last 200 years, Geophys. Res. Lett., 23, 2235–2238, 1996.
Heidt, L. E., Krasnec, J. P., Lueb, R. A., Pollock, W. H., Henry,
B. E., and Crutzen, P. J.: Latitudinal distributions of CO and
CH4 over the Pacific, J. Geophys. Res.-Oc. Atm., 85, 7329–7336,
Ito, A. and Penner, J. E.: Historical emissions of carbonaceous aerosols from biomass and fossil fuel burning for the
period 1870–2000, Global. Biogeochem. Cy., 19, Gb2028,
doi:10.1029/2004gb002374, 2005.
Kato, S., Akimoto, H., Röckmann, T., Braunlich, M., and Brenninkmeijer, C. A. M.: Stable isotopic compositions of carbon
monoxide from biomass burning experiments, Atmos. Environ.,
33, 4357–4362, 1999.
Khalil, M. A. K. and Rasmussen, R. A.: Carbon monoxide in the
earth’s atmosphere: increased trend, Science, 224, 54–56, 1984.
Khalil, M. A. K. and Rasmussen, R. A.: Global decrease in atmospheric carbon monoxide concentration, Nature, 370, 639–641,
Atmos. Chem. Phys., 12, 4365–4377, 2012
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
Kummer, J. T.: Catalysis for automobile emission control, Prog. Energ. Combust., 6, 177–199, 1980.
Kummer, J. T.: Use of noble-metals in automobile exhaust catalysts,
J. Phys. Chem.-US, 90, 4747–4752, doi:10.1021/j100411a008,
Lamarque, J.-F., Bond, T. C., Eyring, V., Granier, C., Heil, A.,
Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B.,
Schultz, M. G., Shindell, D., Smith, S. J., Stehfest, E., Van Aardenne, J., Cooper, O. R., Kainuma, M., Mahowald, N., McConnell, J. R., Naik, V., Riahi, K., and van Vuuren, D. P.: Historical (1850–2000) gridded anthropogenic and biomass burning
emissions of reactive gases and aerosols: methodology and application, Atmos. Chem. Phys., 10, 7017–7039, doi:10.5194/acp10-7017-2010, 2010.
Lean, J., Beer, J., and Bradley, R.: Reconstruction of solar irradiance since 1610 – implications for climate change, Geophys.
Res. Lett., 22, 3195–3198, 1995.
Levy, H.: Normal atmosphere – Large radical and formaldehyde
concentrations predicted, Science, 173, 141–143, 1971.
Logan, J. A., Prather, M. J., Wofsy, S. C., and McElroy, M. B.: Tropospheric chemistry: a global perspective, J. Geophys. Res.-Oc.
Atm., 86, 7210–7254, 1981.
Mak, J. E. and Brenninkmeijer, C. A. M.: Measurement of 13 CO
and C18 O in the free troposphere, J. Geophys. Res.-Atmos., 103,
19347–19358, 1998.
Mak, J. E. and Kra, G.: The isotopic composition of carbon
monoxide at Montauk Point, Long Island, Chemosphere: Global
Change Science, 1, 205–218, 1999.
Mak, J. E., Kra, G., Sandomenico, T., and Bergamaschi, P.: The
seasonally varying isotopic composition of the sources of carbon
monoxide at Barbados, West Indies, J. Geophys. Res.-Atmos.,
108, 4635, doi:10.1029/2003jd003419, 2003.
Manning, M. R., Brenninkmeijer, C. A. M., and Allan, W.: Atmospheric carbon monoxide budget of the southern hemisphere: Implications of 13 C/12 C measurements, J. Geophys. Res.-Atmos.,
102, 10673–10682, 1997.
Marland, G., Boden, T. A., and Andres, R. J.: Global, Regional, and
National Fossil-Fuel CO2 Emissions, in: Trends: A Compendium
of Data on Global Change, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of
Energy, Oak Ridge, Tenn., USA, 2008.
Montzka, S. A., Krol, M., Dlugokencky, E., Hall, B., Jockel,
P., and Lelieveld, J.: Small Interannual Variability of
Global Atmospheric Hydroxyl, Science, 331, 67–69,
doi:10.1126/science.1197640, 2011.
Novelli, P. and Masarie, K. A.: Atmospheric Carbon Monoxide Dry Air Mole Fractions from the NOAA ESRL Carbon
Cycle Cooperative Global Air Sampling Network, 1988-2009,
Version: 2010-07-14, Path:
event/, last access: November 2011, 2010.
Novelli, P. C., Steele, L. P., and Tans, P. P.: Mixing ratios of carbon monoxide in the troposphere, J. Geophys. Res.-Atmos., 97,
20731–20750, 1992.
Novelli, P. C., Masarie, K. A., Tans, P. P., and Lang, P. M.: Recent
changes in atmospheric carbon monoxide, Science, 263, 1587–
1590, 1994.
Park, K.: Joint Application of Concentration and Isotope Ratios to
Investigate the Global Atmospheric Carbon Monoxide Budget:
Atmos. Chem. Phys., 12, 4365–4377, 2012
An Inverse Modeling Approach, PhD Thesis, Stony Brook University, Stony Brook, NY, USA, 2010.
Parrish, D. D.: Critical evaluation of US on-road vehicle emission inventories, Atmos. Environ., 40, 2288–2300,
doi:10.1016/j.atmosenv.2005.11.033, 2006.
Pechony, O. and Shindell, D. T.: Driving forces of global wildfires over the past millennium and the forthcoming century, Proc. Natl. Acad. Sci. U.S.A., 107, 19167–19170,
doi:10.1073/pnas.1003669107, 2010.
Petrenko, V., Martinerie, P., Novelli, P., Etheridge, D. M., Levin,
I., Wang, Z., Petron, G., Blunier, T., Chappellaz, J., Kaiser, J.,
Lang, P., Steele, L. P., Vogel, F., Leist, M. A., Mak, J., Langenfelds, R. L., Schwander, J., Severinghaus, J. P., Forster, G.,
Sturges, W., Rubino, M., and White, J. W. C.: Records of Northern Hemisphere carbon monoxide and hydrogen back to ∼1950
from Greenland firn air, Atmos. Chem. Phys., in preparation,
Petron, G., Granier, C., Khattatov, B., Yudin, V., Lamarque, J. F., Emmons, L., Gille, J., and Edwards, D. P.:
Monthly CO surface sources inventory based on the 20002001 MOPITT satellite data, Geophys. Res. Lett., 31, L21107
doi:10.1029/2004gl020560, 2004.
Pongratz, J., Reick, C., Raddatz, T., and Claussen, M.: A reconstruction of global agricultural areas and land cover for
the last millennium, Global Biogeochem. Cy., 22, GB3018,
doi:10.1029/2007gb003153, 2008.
Prinn, R. G., Huang, J., Weiss, R. F., Cunnold, D. M., Fraser, P.
J., Simmonds, P. G., McCulloch, A., Harth, C., Reimann, S.,
Salameh, P., O’Doherty, S., Wang, R. H. J., Porter, L. W., Miller,
B. R., and Krummel, P. B.: Evidence for variability of atmospheric hydroxyl radicals over the past quarter century, Geophys.
Res. Lett., 32, L07809, doi:10.1029/2004gl022228, 2005.
Rinsland, C. P. and Levine, J. S.: Free tropspheric carbon monoxide concentrations in 1950 and 1951 deduced from infrared total
column amount measurements, Nature, 318, 250–254, 1985.
Röckmann, T., Jöckel, P., Gros, V., Bräunlich, M., Possnert, G., and
Brenninkmeijer, C. A. M.: Using 14 C, 13 C, 18 O and 17 O isotopic variations to provide insights into the high northern latitude surface CO inventory, Atmos. Chem. Phys., 2, 147–159,
doi:10.5194/acp-2-147-2002, 2002
Rommelaere, V., Arnaud, L., and Barnola, J. M.: Reconstructing
recent atmospheric trace gas concentrations from polar firn and
bubbly ice data by inverse methods, J. Geophys. Res.-Atmos.,
102, 30069–30083, 1997.
Santra, A. K. and Goodman, D. W.: Catalytic oxidation of CO
by platinum group metals: from ultrahigh vacuum to elevated pressures, Electrochim. Acta, 47, 3595–3609, PII S00134686(02)00330-4, doi:10.1016/S0013-4686(02)00330-4, 2002.
Schwander, J. and Stauffer, B.: Age Difference between Polar Ice
and the Air Trapped in Its Bubbles, Nature, 311, 45–47, 1984.
Seiler, W.: Cycle of atmospheric CO, Tellus, 26, 116–135, 1974.
Seiler, W. and Junge, C.: Carbon monoxide in atmosphere, J. Geophys. Res., 75, 2217–2226, 1970.
Stevens, C. M., Walling, D., Venters, A., Ross, L. E., Engelkem,
A., and Krout, L.: Isotopic Composition of Atmospheric CarbonMonoxide, Earth Planet. Sc. Lett., 16, 147–165, 1972.
Stevens, C. M., and Wagner, A. F.: The Role of Isotope Fractionation Effects in Atmospheric Chemistry, Z. Naturforsch. A, 44,
376–384, 1989.
Z. Wang et al.: The isotopic record of Northern Hemisphere atmospheric carbon monoxide
Tarr, M. A., Miller, W. L., and Zepp, R. G.: Direct carbon monoxide photoproduction from plant matter, J. Geophys. Res.-Atmos.,
100, 11403–11413, 1995.
Trudinger, C. M., Enting, I. G., Etheridge, D. M., Francey, R. J.,
Levchenko, V. A., Steele, L. P., Raynaud, D., and Arnaud, L.:
Modeling air movement and bubble trapping in firn, J. Geophys.
Res.-Atmos., 102, 6747–6763, 1997.
Tsunogai, U., Hachisu, Y., Komatsu, D. D., Nakagawa, F.,
Gamo, T., and Akiyama, K.: An updated estimation of
the stable carbon and oxygen isotopic compositions of automobile CO emissions, Atmos. Environ., 37, 4901–4910,
doi:10.1016/j.atmosenv.2003.08.008, 2003.
van Aardenne, J. A., Dentener, F. J., Olivier, J. G. J., Goldewijk, C.,
and Lelieveld, J.: A 1 degrees × 1 degrees resolution data set of
historical anthropogenic trace gas emissions for the period 1890–
1990, Global Biogeochem. Cy., 15, 909–928, 2001.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J.,
Kasibhatla, P. S., and Arellano Jr., A. F.: Interannual variability in global biomass burning emissions from 1997 to 2004, Atmos. Chem. Phys., 6, 3423–3441, doi:10.5194/acp-6-3423-2006,
Wang, Z. and Mak, J. E.: A new CF-IRMS system for quantifying
stable isotopes of carbon monoxide from ice cores and small air
samples, Atmos. Meas. Tech., 3, 1307–1317, doi:10.5194/amt-31307-2010, 2010.
Wang, Z., Chappellaz, J., Park, K., and Mak, J. E.: Large Variations
in Southern Hemisphere Biomass Burning During the Last 650
Years, Science, 330, 1663–1666, doi:10.1126/science.1197257,
Witrant, E., Martinerie, P., Hogan, C., Laube, J. C., Kawamura,
K., Capron, E., Montzka, S. A., Dlugokencky, E. J., Etheridge,
D., Blunier, T., and Sturges, W. T.: A new multi-gas constrained
model of trace gas non-homogeneous transport in firn: evaluation
and behavior at eleven polar sites, Atmos. Chem. Phys. Discuss.,
11, 23029–23080, doi:10.5194/acpd-11-23029-2011, 2011.
Wu, J. and Boyle, E. A.: Lead in the western North Atlantic Ocean:
completed response to leaded gasoline phase-out, Geochim. Cosmochim. Acta, 61, 3279–3283, 1997.
Young, L. C. and Finlayson, B. A.: Mathematical models of monolith catallytic converter 2: application to automobile exhaust,
Aiche J., 22, 343–353, 1976.
Atmos. Chem. Phys., 12, 4365–4377, 2012
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