Modeling of microscale variations in methane fluxes Anu Kettunen Jan 17th, 2003.

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Modeling of microscale variations in methane fluxes Anu Kettunen Jan 17th, 2003

Transcript of Modeling of microscale variations in methane fluxes Anu Kettunen Jan 17th, 2003.

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

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6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu

x, m

g C

H4

m-2

d-1

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Wat

er t

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m p

eat

surf

ace

b. Flark B

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6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu

x, m

g C

H4

m-2

d-1

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0

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Wat

er t

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,cm

fro

m p

eat

surf

ace

c. Eriophorum lawn A

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0

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6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu

x, m

g C

H4

m-2

d-1

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0

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Wat

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fro

m p

eat

surf

ace

d. Lawn-low hummock B

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6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu

x, m

g C

H4

m-2

d-1

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Wat

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fro

m p

eat

surf

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e. Hummock A

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6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu

x, m

g C

H4

m-2

d-1

-40

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0

20

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Wat

er t

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, cm

fro

m p

eat

surf

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f. Hummock B

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0

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6-May 5-Jun 5-Jul 4-Aug 3-Sep 3-OctFlu

x, m

g C

H4

m-2

d-1

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-20

0

20

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60

80

Wat

er t

able

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fro

m p

eat

surf

ace

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Fresh carbon, NPP and T

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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

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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

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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

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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