modeling of microscale variations in methane fluxes
DESCRIPTION
Modeling of microscale variations in methane fluxes. Anu Kettunen Jan 17th, 2003. Solar energy and cycling of elements. Natural green house phenomenon. Atmosphere surface temperature of Earth ca 30 o C higher than without atmosphere - PowerPoint PPT PresentationTRANSCRIPT
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Modeling of microscale variations in methane fluxes
Anu Kettunen
Jan 17th, 2003
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Solar energy and cycling of elements
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Natural green house phenomenon• Atmosphere surface
temperature of Earth ca 30oC higher than without atmosphere
• Green house gases prevent Solar energy from escaping from Earth
• H2O, CO2, CH4, N2O, CFC compounds
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Human activities
• Use of fossil fuel etc. human actions increase green house gas concentrations = enhances green house phenomenon climate change
Indicators of the Human Influenceon the Atmosphere during the Industrial Era
Robert T. Watson, IPCC chair
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Future climate
• On average warmer
• Regional differences
• Precipitation patterns
• Likelihood for extreme events (drought, storms) increases
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Mires• Northern mires carbon
sinks during last millenia, huge amount of carbon in peat
• Sources of green house gases (CO2 ja CH4)
• Important to understand role of mires in carbon cycle
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Methane
• CH4 important green house gas
• Concentration increases ca 1% per year
• Wetlands (20-30 %), rice paddies, ruminants, landfills, artificial lakes
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Research problem
• Previously no satisfactory description of spatial and seasonal variations in methane fluxes
• Growing season measurument: CH4, T, WT etc. from different mire surfaces
• Methane production and oxidaton potentials• Process model connects methane flux to
vegetation cover, photosynthetic cycle and peat thermal and moisture conditions
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Process model
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Model predictions
a. Carex lawn A
-400
-200
0
200
400
600
800
6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu
x, m
g C
H4
m-2
d-1
-40
-20
0
20
40
60
80
Wat
er t
able
,cm
fro
m p
eat
surf
ace
b. Flark B
-400
-200
0
200
400
600
800
6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu
x, m
g C
H4
m-2
d-1
-40
-20
0
20
40
60
80
Wat
er t
able
,cm
fro
m p
eat
surf
ace
c. Eriophorum lawn A
-400
-200
0
200
400
600
800
6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu
x, m
g C
H4
m-2
d-1
-40
-20
0
20
40
60
80
Wat
er t
able
,cm
fro
m p
eat
surf
ace
d. Lawn-low hummock B
-400
-200
0
200
400
600
800
6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu
x, m
g C
H4
m-2
d-1
-40
-20
0
20
40
60
80
Wat
er t
able
, cm
fro
m p
eat
surf
ace
e. Hummock A
-400
-200
0
200
400
600
800
6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu
x, m
g C
H4
m-2
d-1
-40
-20
0
20
40
60
80
Wat
er t
able
, cm
fro
m p
eat
surf
ace
f. Hummock B
-400
-200
0
200
400
600
800
6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu
x, m
g C
H4
m-2
d-1
-40
-20
0
20
40
60
80
Wat
er t
able
,cm
fro
m p
eat
surf
ace
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Fresh carbon, NPP and T
0
500
1000
1500
2000
2500
3000
3500
4000
4500
6-May 26-May 15-Jun 5-Jul 25-Jul 14-Aug 3-Sep 23-Sep 13-Oct
Flu
x,
mg
CH
4 m
-2 d
-1
a.
• Model sensitive to fresh carbon
• If T ja CO2 NPP substrate CH4
• If only T CH4 less
0
100
200
300
400
500
600
700
800
6-May 26-May 15-Jun 5-Jul 25-Jul 14-Aug 3-Sep 23-Sep 13-Oct
Flu
x,
mg
CH
4 m
-2 d
-1
(T&GPP)-2
(T&GPP)+2
T+2
T-2
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Transport of oxygen to peat
• The more sedges transport oxygen to peat, the lower the CH4 flux
• If methane oxidation CH4
0
100
200
300
400
500
600
700
800
6-May 26-May 15-Jun 5-Jul 25-Jul 14-Aug 3-Sep 23-Sep 13-Oct
Flu
x,
mg
CH
4 m
-2 d
-1
c.
Change in transport capacity of sedges
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The effect of drought
• Long dry periods methanogens CH4
• If > 4-6 week drought, no recovery even after rains come
0
100
200
300
400
500
600
700
800
6-May 26-May 15-Jun 5-Jul 25-Jul 14-Aug 3-Sep 23-Sep 13-Oct
Flu
x,
mg
CH
4 m
-2 d
-1
8 wk
6 wk4 wk
2 wk
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Main contribution of the thesis• Simulation model for CH4 fluxes from
different mire surfaces CH4 fluxes from boreal mires can be predicted under current and future climate
• Increased understanding
• Connection to general circulation models