Impact of meteorology and emissions on methane trends, 1990–2004

Abstract

1] Over the past century, atmospheric methane (CH 4) rose dramatically before leveling off in the late 1990s. The processes controlling this trend are poorly understood, limiting confidence in projections of future CH 4 . The MOZART-2 global tropospheric chemistry model qualitatively captures the observed CH 4 trend (increasing in the early 1990s and then leveling off) with constant emissions. From 1991 – 1995 to 2000 – 2004, the CH 4 lifetime versus tropospheric OH decreases by 1.6%, reflecting increases in OH and temperature. The rise in OH stems from an increase in lightning NO x as parameterized in the model. A simulation including annually varying anthropogenic and wetland CH 4 emissions, as well as the changes in meteorology, best reproduces the observed CH 4 distribution, trend, and seasonal cycles. Projections of future CH 4 abundances should consider climate-driven changes in CH 4 sources and sinks.

Full text

Impact of meteorology and emissions on methane trends, 1990–2004
Arlene M. Fiore,
1
Larry W. Horowitz,
1
Edward J. Dlugokencky,
2
and J. Jason West
3
Received 2 March 2006; revised 4 May 2006; accepted 16 May 2006; published 24 June 2006.
[1] Over the past century, atmospheric methane (CH
4
) rose
dramatically before leveling off in the late 1990s. The
processes controlling this trend are poorly understood,
limiting confidence in projections of future CH
4
. The
MOZART-2 global tropospheric chemistry model
qualitatively captures the observed CH
4
trend (increasing
in the early 1990s and then leveling off) with constant
emissions. From 1991–1995 to 2000 – 2004, the CH
4
lifetime versus tropospheric OH decreases by 1.6%,
reflecting increases in OH and temperature. The rise in OH
stems from an increase in lightning NO
x
as parameterized in
the model. A simulation including annually varying
anthropogenic and wetland CH
4
emissions, as well as the
changes in meteorology, best reproduces the observed CH
4
distribution, trend, and seasonal cycles. Projections of future
CH
4
abundances should consider climate-driven changes in
CH
4
sources and sinks. Citation: Fiore,A.M.,L.W.
Horowitz, E. J. Dlugokencky, and J. J. West (2006), Impact of
meteorology and emissions on methane trends, 1990 – 2004,
Geophys. Res. Lett.,33, L12809, doi:10.1029/2006GL026199.
1. Introduction
[2] Atmospheric methane (CH
4
) increased during the
past century until 1998, with a general decline in the
growth rate in recent decades [e.g., Steele et al., 1992].
Since 1998, CH
4
abundances have been roughly constant,
suggesting that CH
4
may have reached a steady state
[Dlugokencky et al., 2003]. The overall atmospheric CH
4
lifetime is 8–9 years [Prather et al., 2001], reflecting a
balance between diverse sources (wetlands, ruminants,
energy, rice agriculture, landfills, wastewater, biomass
burning, oceans, and termites) and the dominant CH
4
loss
pathway, reaction with the hydroxyl radical (OH) in the
troposphere. Recent work shows that reducing CH
4
emis-
sions is a viable low-cost strategy to improve ozone air
quality while slowing greenhouse warming [West a nd
Fiore, 2005]. Our poor understanding of the processes
governing the methane trend, however, limits confidence
in quantitative assessments of the efficacy of methane
emission controls.
[3] Prior studies with 3-D chemical transport models
(CTMs) attribute much of the observed decrease in the
CH
4
growth rate to increases in global mean OH, but
differ in their explanations for the OH changes, implicat-
ing: increases in tropical tropospheric water vapor from
1979–1993 [Dentener et al., 2003]; increasing NO
x
emissions, particularly from Southeast Asia from 1980–
1996 [Karlsdo´ttir and Isaksen, 2000]; and trends in
photolysis rates (associated with overhead ozone columns)
from 1988 –1997 [Wang et al., 2004]. None of these
studies considered the period after 1998 when observed
CH
4
leveled off.
[4] We examine here whether existing bottom-up esti-
mates of anthropogenic and biogenic CH
4
emissions are
consistent with surface CH
4
observations from 1990 to
2004. To our knowledge, this study is the first forward
modeling analysis that fully includes feedbacks between
CH
4
and the hydroxyl radical [Prather et al., 2001]. We find
that recent CH
4
emission estimates improve the simulation
of CH
4
, but that the large-scale trend from 1990 to 2004 is
mainly controlled by small meteorologically driven changes
in the CH
4
sink.
2. Methane Simulations
[5] We conduct transient simulations for 1990 –2004
with the MOZART-2 global model of tropospheric chem-
istry [Horowitz et al., 2003] driven by NCEP meteoro-
logical fields, at 1.91.9horizontal resolution with 28
vertical levels. Model parameterizations based on the
meteorological fields include lightning NO
x
(tied to con-
vection) and stratosphere-troposphere exchange of ozone
(stratospheric ozone concentrations are relaxed to ob-
served climatologies) [Horowitz et al., 2003], both of
which affect tropospheric OH. We use three sets of CH
4
emission estimates: (i) constant 1990 emissions (BASE),
(ii) BASE except for annually increasing anthropogenic
emissions (ANTH), and (iii) ANTH except for annually
varying biogenic emissions (ANTH+BIO). Emissions for
species other than CH
4
are from Horowitz et al. [2003]
and are held constant in all simulations. In the BASE
simulation, CH
4
emissions are 261 Tg yr
1
from EDGAR
2.0 anthropogenic sources (energy use, landfills, waste-
water, rice, ruminants) and 72 Tg yr
1
from biomass
burning [Horowitz et al., 2003] (see auxiliary material
1
Table S1 for details). We uniformly increase the global
wetland emissions from Horowitz et al. [2003] by 40%, to
204 Tg yr
1
, to reflect recent estimates [Wang et al.,
2004]. Figure 1a (red line) shows the latitudinal distribu-
tion of the BASE emissions.
[6] The ANTH simulation uses EDGAR 3.2 anthropo-
genic CH
4
emission estimates for 1990 and 1995 [Olivier
and Berdowski, 2001], and ‘‘FAST-TRACK’’ (FT2000) for
2000 [Olivier et al., 2005]. Emissions for intermediate years
are obtained by linear interpolation, with emissions for
2001–2004 held at 2000 values. Since the 1990 EDGAR
3.2 CH
4
emissions are lower than EDGAR 2.0, we augment
1
Auxiliary material is available at ftp://ftp.agu.org/apend/gl/
2006gl026199.
GEOPHYSICAL RESEARCH LETTERS, VOL. 33, L12809, doi:10.1029/2006GL026199, 2006
Click
Here
for
Full
A
rticl
e
1
Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, New
Jersey, USA.
2
Earth System Research Laboratory, NOAA, Boulder, Colorado, USA.
3
Program in Atmospheric and Oceanic Sciences, Princeton University,
Princeton, New Jersey, USA.
Copyright 2006 by the American Geophysical Union.
0094-8276/06/2006GL026199$05.00
L12809 1of4

the wetland emissions by 20 Tg yr
1
to maintain the same
1990 total as in BASE. Global anthropogenic CH
4
emis-
sions are nearly constant between 1990 and 1995, but
increase by 10 Tg in 2000 (Table S1), with a redistribution
toward the tropics over the decade.
[7] The ANTH+BIO simulation uses inverse model esti-
mates of wetland emissions from Wang et al. [2004], based
on the spatial and seasonal distributions of Matthews and
Fung [1987]. Wang et al. [2004] conducted their inversion
for 1994 and then extrapolated the resulting emissions to
1988–1998 based on temperature and precipitation [Walter
et al., 2001]. We maintain the relative source strengths
(from tundra, bogs, and swamps) from Wang et al. [2004],
but constrain the mean 1990–1998 wetland emissions to
224 Tg CH
4
yr
1
, as in the ANTH simulation. Wetland
emissions in ANTH+BIO shift from the northern to south-
ern hemisphere relative to BASE and ANTH (Figure 1a).
The annual wetland emissions for 1990 to 1998 are 227,
229, 205, 211, 213, 218, 213, 230, and 266 Tg CH
4
yr
1
;
we apply the 1990–1998 mean in 1999–2004. The unusu-
ally large 1998 wetland emissions are associated with
above-normal temperatures (globally) and precipitation
(southern tropics and north of 30N) [Dlugokencky et al.,
2001; Mikaloff Fletcher et al., 2004].
3. Atmospheric CH
4
Trend and Distribution
[8] We evaluate our simulations with monthly mean
measurements from 42 background sampling sites in the
globally distributed NOAA network (Table S2). Air is
sampled at these sites in duplicate, analyzed by gas chro-
matography with flame ionization detection at 0.1% relative
precision, and CH
4
abundances are reported on the
NOAA04 CH
4
standard scale [Dlugokencky et al., 1994,
2005].
[9] The BASE simulation qualitatively reproduces the
observed CH
4
rise in the early 1990s, along with the
flattening in the late 1990s (Figure 2). Since emissions are
held constant in this simulation, the CH
4
decrease after
1998 implies an increase in the CH
4
sink. The lack of
interannual changes in emissions of CH
4
or other species, or
in overhead O
3
columns, may contribute to the systematic
CH
4
overestimate before 1998 and the underestimate after-
ward. Major shortcomings of the BASE simulation include
a 50% overestimate of the mean 1990 –2004 gradient from
the South Pole to Alert (201 ppb vs. 133 ppb observed) and
a poor simulation of the seasonal cycles at northern hemi-
spheric sites (Figures 1b and 1c, Figure S1, Table S2). The
BASE model captures the observed CH
4
seasonality in the
southern hemisphere (Figure 1c and Figure S1).
[10] The global mean abundances after 1998 increase in
both ANTH and ANTH+BIO relative to the BASE simula-
tion, with ANTH+BIO best matching the 1992–1997
observations (Figure 2). While ANTH slightly improves
the negative bias in the southern hemisphere, ANTH+BIO
best reproduces the observed interhemispheric gradient
(Figure 1b) and captures the seasonal cycles at high north-
ern latitude sites (Figures 1c and Figure S1), indicating that
the CH
4
abundance and seasonal cycle at high northern
latitudes is sensitive to the wetland source, as suggested by
Houweling et al. [2000]. The large negative biases (>35 ppb)
and poor correlations (r
2
< 0.4) at continental and coastal
sites mainly between 30Nand50N in ANTH+BIO
Figure 1. (a) Latitudinal distribution of 1990 CH
4
emissions in the MOZART-2 model within 10bands,
(b) mean 1990 –2004 bias (model - observed) in dry surface
air (nmol mol
1
, abbreviated ppb) and (c) correlation
coefficient of the MOZART-2 model versus surface observa-
tions for each month in 1990–2004, for BASE (red plus
signs), ANTH (blue triangles), and ANTH+BIO (green
crosses). See auxiliary material (Tables S1 and S2) for details.
Figure 2. Weighted global mean annual surface CH
4
in
dry air sampled at 42 NOAA sites where a minimum of
8 years were available (see Table S2 for details). The global
means are calculated consistently by averaging within
latitudinal bands 30–90S, 30– 0S, 0 – 30N, 30–60N, 60–
90N and then weighting by area, for both the observations
(black circles) and the MOZART-2 simulations: BASE (red
plus signs), ANTH (blue triangles), and ANTH+BIO (green
crosses).
L12809 FIORE ET AL.: METHANE TREND ATTRIBUTION, 1990 –2004 L12809
2of4

suggest an inadequate resolution of regional sources in our
global model [Houweling et al., 2000], as these biases are
greater than at sites sampling marine air in the same latitude
band (Figures 1b and 1c, Table S2). In the southern tropics
(15S–2N), the BASE CH
4
is typically within 10 ppb of
observed, while ANTH+BIO exhibits >15 ppb positive
biases, implying that the BASE southern tropical wetland
source is more accurate. The overall success of the ANTH+-
BIO simulation suggests that the upper estimate of the
recently proposed aerobic CH
4
source of 62–236 Tg yr
1
from plants [Keppler et al., 2006] is too high, although the
lower range could be accommodated if the wetland source
were much lower than assumed here.
4. Meteorologically-Driven Changes in the
CH
4
Sink
[11] While the global annual mean CH
4
abundances are
best reproduced by ANTH+BIO, the BASE model simu-
lates the observed increase for 1990 –1997 (slope = 6.3 ppb
yr
1
in BASE vs. 6.1 ppb yr
1
observed) and the flattening
afterward (Figure 2). Since the BASE sources and sinks are
not initially in balance, CH
4
abundances should increase
toward a steady state. In order to examine whether meteo-
rologically driven changes also contribute to the CH
4
trend,
we analyze the BASE simulation where CH
4
emissions are
held constant. The annual mean CH
4
lifetime against loss
by tropospheric OH (t
OH
) varies with temperature and
OH (t
OH
= B/L; B is the annual mean atmospheric burden;
L=Pk
OH
[OH][CH
4
], the annual global loss by OH
integrated over the troposphere). The strong temperature
sensitivity of the rate constant k
OH
(2% K
1
) restricts
the majority of the CH
4
sink (88%) to below 500 hPa, with
75% of this lower tropospheric loss in the tropics (30N–
30S).
[12] In our BASE simulation, the mean annual t
OH
decreases from 10.40 yr in 1991–1995 to 10.23 yr in
2000–2004 (Figure S2). By re-calculating t
OH
, varying
only OH or temperature while fixing the other variable at
its 1990–2004 monthly mean values, we find that increases
in temperature (+0.3 K in the global lower troposphere) and
in OH (+1.2%, airmass-weighted below the 150 ppb O
3
chemical tropopause in 1990) contribute 35% (0.06 yr) and
65% (0.11 yr), respectively, to the total decrease in t
OH
from 1991–1995 to 2000–2004. We estimate that the rise
in CH
4
itself from 1991–1995 to 2000– 2004 in the BASE
simulation should cause OH concentrations to decrease by
0.2% [Prather et al., 2001], implying a net meteorologically
driven OH increase of 1.4% (1.2 + 0.2%) during this period.
Trends in OH are highly uncertain, but estimates based on
methyl chloroform observations suggest an increase of
0.2% yr
1
over the past 25 years [Prinn et al., 2005],
roughly consistent with our results.
[13] We next seek to identify the cause of the OH increase
in the BASE model, which includes meteorological vari-
ability but neglects interannual variability in aerosols,
overhead O
3
columns, and surface emissions. In the BASE
simulation, the annual mean 1991 –2004 tropospheric OH
(airmass-weighted below the chemical tropopause in 1990)
correlates poorly with O
3
photolysis rates (r
2
= 0.0), and
more strongly with specific humidity (r
2
= 0.7), but that
correlation weakens (r
2
= 0.3) if we neglect 1998 when
humidity was anomalously high. Strong correlations exist
between annual mean OH and the tropospheric O
3
burden
(r
2
= 0.6), lightning NO
x
(r
2
= 0.7), and the net flux of
stratospheric O
3
to the troposphere (r
2
= 0.5); these corre-
lations strengthen when we neglect 1998. From 1991 – 1995
to 2000–2004, there are increases in the tropospheric O
3
burden (363 to 376 Tg), lightning NO
x
(2.4 to
2.7 Tg N yr
1
), and the net influx of O
3
from the stratosphere
(725 to 866 Tg O
3
yr
1
), while specific humidity in the lower
troposphere changes little (4.26 to 4.28 g H
2
O/kg air). We
hypothesize that the coincident increases in lightning NO
x
and stratosphere-troposphere exchange reflect a more vigor-
ous mixing circulation in 2000 –2004.
[14] Since lightning NO
x
is most strongly correlated with
annual mean OH, we investigate whether the rise in OH is
caused by the increase in lightning NO
x
. In the model,
lightning NO
x
is parameterized using empirical relation-
ships between cloud top heights and flash frequency (sep-
arately for continental and marine) [Price et al., 1997; see
also Horowitz et al., 2003]. This commonly used approach
allows for interannual variations, but is highly sensitive to
model biases in cloud top heights; flash rate parameter-
izations based on mass fluxes are more consistent with
observations [Allen and Pickering, 2002]. To test the
sensitivity of OH to lightning NO
x
, we decrease the
lightning NO
x
source during model years 1997–2004 to
the 1991–1995 rate (see auxiliary material). Based on this
simulation, we find that the lightning NO
x
increase causes
most of the 0.11 yr decrease in t
OH
attributed to higher OH,
roughly consistent with the relationship found by Labrador
et al. [2004]. The tropospheric O
3
burden decreases by
2.6 Tg in this sensitivity simulation relative to the mean
2000–2004 BASE simulation, but is still 10 Tg higher
than the BASE 1991–1995 value, reflecting a larger influx
from the stratosphere in the later years. Given that the
increase in lightning NO
x
can fully account for the decrease
in t
OH
, we infer that the larger stratospheric O
3
flux (and the
resulting increase in tropospheric O
3
burden) contributes
minimally to the enhanced OH in our simulation, consistent
with the findings of Dentener et al. [2003]. We conclude
that the 0.3 Tg N yr
1
increase in lightning NO
x
from
1991–1995 to 2000– 2004 yields the modeled increase in
OH and the corresponding decrease in t
OH
. Alternatively, a
shift in anthropogenic NO
x
emissions from northern lati-
tudes to the tropics or an increase in total emissions (both of
which occur from 1990 to 2000 in the EDGAR 3.2 and
FT2000 NO
x
inventories, not included in our simulations)
could contribute to the observed CH
4
trend by enhancing
OH [Gupta et al., 1998]. Earlier work, however, suggests
that the net impact of trends in all surface emissions and
photolysis rates (via stratospheric O
3
columns) is small
[Dentener et al., 2003].
5. Discussion
[15] Our simulations with the MOZART-2 tropospheric
chemistry model show that anthropogenic and biogenic CH
4
source estimates are consistent with observed CH
4
abun-
dances. We further use the model to identify the processes
driving the CH
4
trend from 1990 to 2004. When emissions
are held constant, the model successfully captures the
observed rise in the early 1990s and flattening post-1998
L12809 FIORE ET AL.: METHANE TREND ATTRIBUTION, 1990 –2004 L12809
3of4

but overestimates CH
4
abundances in the early 1990s (by
7–15 ppb) and underestimates CH
4
after 1998 (by 13–
20 ppb). We find that the overall CH
4
trend is largely
controlled by small (<2%) changes in the tropospheric CH
4
sink, decreasing the annual mean CH
4
lifetime by 0.17 years
from 1991–1995 to 2000– 2004. We attribute 65% of this
lifetime change to an increase in tropospheric OH (+1.2%
airmass-weighted), and the remainder to a lower tropospheric
warming (+0.3 K) during this period. The OH enhancement
in the model is caused by an increase in lightning NO
x
. The
reduction in CH
4
lifetime in response to rising temperatures is
a negative feedback on greenhouse warming, which we
estimate will offset the initial warming by at most a few
percent (see auxiliary material).
[16] Including annually increasing anthropogenic CH
4
emissions improves agreement with observations after
1998, but this simulation still fails to capture the observed
interhemispheric gradient and seasonal cycles at high north-
ern latitudes. A simulation with annually varying anthropo-
genic and wetland emissions best reproduces the observed
global mean CH
4
trend, interhemispheric gradient, and
seasonal cycles, indicating that CH
4
is sensitive to the
spatial and temporal distribution of wetland emissions.
[17] Future shifts in climate can exert a strong influence
on the CH
4
lifetime by influencing the CH
4
-OH reaction
rate, as well as convective activity and subsequent lightning
NO
x
production. While warmer temperatures and greater
lightning activity induce negative feedbacks on greenhouse
warming via CH
4
, increased wetland CH
4
emissions in a
warmer, wetter climate may offset these feedbacks [Shindell
et al., 2004]. Additional work is needed to determine
whether enhanced lightning activity is a robust feature of
a warming world or if the increase is sensitive to details of
the model parameterization. More physically-based repre-
sentations of lightning NO
x
in chemistry-climate models
would enable the analysis of this feedback together with
other climate-driven feedbacks, such as changes in biogenic
emissions of CH
4
and other species.
[18]Acknowledgments. We thank J.S. Wang for providing emissions
and I. Held, H. Levy, A. Gnanadesikan, S. Fan, H. Liu, and 2 anonymous
reviewers for useful comments.
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A. M. Fiore and L. W. Horowitz, Geophysical Fluid Dynamics
Laboratory, NOAA, Princeton University Forrestal Campus, 201 Forrestal
Road, Princeton, NJ 08540 – 6649, USA. (arlene.fiore@noaa.gov)
J. J. West, Program in Atmospheric and Oceanic Sciences, Princeton
University, Forrestal Campus, 300 Forrestal Road, Princeton, NJ 08540,
USA.
L12809 FIORE ET AL.: METHANE TREND ATTRIBUTION, 1990 –2004 L12809
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