modeling of microscale variations in methane fluxes

14
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. 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 Presentation

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Page 1: Modeling of microscale variations in methane fluxes

Modeling of microscale variations in methane fluxes

Anu Kettunen

Jan 17th, 2003

Page 2: Modeling of microscale variations in methane fluxes

2

Solar energy and cycling of elements

Page 3: Modeling of microscale variations in methane fluxes

3

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

Page 4: Modeling of microscale variations in methane fluxes

4

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

Page 5: Modeling of microscale variations in methane fluxes

5

Future climate

• On average warmer

• Regional differences

• Precipitation patterns

• Likelihood for extreme events (drought, storms) increases

Page 6: Modeling of microscale variations in methane fluxes

6

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

Page 7: Modeling of microscale variations in methane fluxes

7

Methane

• CH4 important green house gas

• Concentration increases ca 1% per year

• Wetlands (20-30 %), rice paddies, ruminants, landfills, artificial lakes

Page 8: Modeling of microscale variations in methane fluxes

8

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

Page 9: Modeling of microscale variations in methane fluxes

9

Process model

Page 10: Modeling of microscale variations in methane fluxes

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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

Page 11: Modeling of microscale variations in methane fluxes

11

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

Page 12: Modeling of microscale variations in methane fluxes

12

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

Page 13: Modeling of microscale variations in methane fluxes

13

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

Page 14: Modeling of microscale variations in methane fluxes

14

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