1. Source vs. Sink Contributions to Atmospheric Methane Trends: 1990-2004
Arlene M. Fiore
Larry Horowitz (NOAA/GFDL)
Ed Dlugokencky (NOAA/GMD)
Jason West (Princeton)
Informal Seminar at NOAA GMD
January 24, 2006

2. More than half of global methane emissions
are influenced by human activities
~300 Tg CH4 yr-1 Anthropogenic [EDGAR 3.2 Fast-Track 2000; Olivier et al., 2005]
~200 Tg CH4 yr-1 Biogenic sources [Wang et al., 2004]
BIOMASS BURNING + BIOFUEL 30
ANIMALS 90
WETLANDS
180
LANDFILLS +
WASTEWATER 50
GLOBAL METHANE
SOURCES
(Tg CH4 yr-1)
GAS + OIL 60
COAL 30
TERMITES 20
RICE 40

3. Observed trend in Surface CH4 (ppb) 1990-2004
Global Mean CH4 (ppb)
Hypotheses for leveling off
discussed in the literature:
1. Approach to steady-state
2. Source Changes
Anthropogenic
Wetlands
Biomass burning
3. Transport
4. Sink (OH)
Humidity
Temperature
OH precursor emissions
overhead O3 columns
GMD Network
Data from 42 GMD stations with 8-yr minimum record is area-weighted, after averaging in bands
60-90N, 30-60N, 0-30N, 0-30S, 30-90S
How does a 3-D forward model compare with GMD observations?

4. Captures flattening post-1998 but underestimates abundance
Model with constant emissions largely captures observed trend in CH4 during the 1990s
MOZART-2 [Horowitz et al., 2003]
NCEP
1.9°x1.9°
28 s-levels
EDGAR v.2.0
emissions
CH4 EDGAR
for 1990s
Global Mean Surface Methane (ppb)
OBSERVED
Captures flattening post-1998
but underestimates abundance
Emissions problem?

5. Bias and Correlation vs. GMD Surface CH4: 1990-2004
Mean Bias (ppb) r2
BASE
BASE simulation with constant emissions:
Overestimates interhemispheric gradient
Correlates poorly at high northern latitudes

6. Estimates for Changing Methane Sources in the 1990s
Inter-annually varying wetland emissions
from Wang et al. [2004]
(Tg CH4 yr-1); distribution changes
Biogenic adjusted to maintain
constant total source
547
Apply climatological mean
(224 Tg yr-1) post-1998
Tg CH4 yr-1
ANTH
BASE
ANTH + BIO
EDGAR anthropogenic inventory

7. Bias & Correlation vs. GMD CH4 observations: 1990-2004
Mean Bias (ppb)
OBS
BASE
ANTH
ANTH simulation with time-varying EDGAR 3.2 emissions:
 Improves abundance post-1998
Interhemispheric gradient too high
Poor correlation at high N latitudes r2

8. Bias & Correlation vs. GMD CH4 observations: 1990-2004
Mean Bias (ppb)
OBS
BASE
ANTH
ANTH+BIO
ANTH+BIO simulation with time-varying EDGAR wetland emissions improves:
 Global mean surface conc.
 Interhemispheric gradient
Correlation at high N latitudes r2
S Latitude N

9. OBS (GMD) BASE ANTH ANTH+BIO
Alert (82.4N,62.5W)
1900
1850
1800
Model with
BIO wetlands
improves:
1)high N latitude
seasonal cycle
Midway (28.2N,177.4W)
1840
1820
1800
1780
1760
1740
2)trend
Methane Concentration (nmol/mol = ppb)
3)low bias
at S Pole,
especially
post-1998
Mahe Island (4.7S,55.2E)
1800
1750
1700
Model
captures
distinct
seasonal
cycles at
GMD
stations
South Pole (89.9S,24.8W)
1990
1995
2000
2005
1740
1720
1700
1680
1660
1640

10. Time-Varying Emissions: Summary
Annual mean CH4 in the
“time-varying ANTH+BIO”
simulation best captures
observed distribution
OBS
BASE
ANTH
ANTH+BIO
Next: Focus on Sinks
-- Examine with BASE model (constant emissions)
-- Recycle NCEP winds from 2004 “steady-state”

11. Not just simple approach to steady-state
Methane rises again when winds are applied to “steady-state” 2004 concentrations
Area-weighted global mean CH4 concentrations in
BASE simulation (constant emissions)
 Recycled NCEP
 Meteorological drivers for observed trend
Not just simple approach to steady-state

12. How does meteorology affect the CH4 lifetime?
 Recycled NCEP
CH4 Lifetime against Tropospheric OH
Rapid transport to sink regions
Candidate Processes:
t =
Temperature
Humidity
Lightning NOx
Photolysis
Lifetime Correlates Strongly With Lower Tropospheric
OH and Temperature
r2 = 0.89 vs. OH
if 1998 neglected
(0.80 for Temp)
r2 = 0.51
r2 = 0.83
105 molecules cm-3

13. Deconstruct Dt (-0.17 years) from to into individual contributions by varying OH and temperature separately + =
DT(+0.3K)
DOH(+1.4%)
BASE
OH increases in the model by 1.4% due to a 0.3 Tg N yr-1
increase in lightning NOx emissions
Large uncertainties in magnitude (and trend) of lightning NOx
emissions in the real atmosphere

14. Methane Distribution and Trends: Conclusions
Global Mean CH4 (ppb)
BASE (constant emissions) captures observed rate of increase and leveling off post-1998
ANTH improves modeled CH4 post-1998
Wetland emissions in ANTH+BIO best match observed seasonality, inter-hemispheric gradient and global trend
OBSERVED
tCH4 decreases by ~2% from to due to warmer temperatures (35%) and higher OH (65%), resulting from a 10% increase in lightning NOx emissions
Potential for strong climate feedbacks

15. Q: How will future global change influence atmospheric CH4
Q: How will future global change influence atmospheric CH4? Potential for complex biosphere-atmosphere interactions… can be studied with GFDL earth system model
CH4 + OH …products
Higher in a warmer climate?
BVOC
NOx
Soil