Acid Rain Links to Methane Emissions from Wetlands Vincent Gauci - - PowerPoint PPT Presentation

Acid Rain Links to Methane Emissions from Wetlands

Vincent Gauci

The Global Methane Budget

2% 1% Enteric Fermentation 15%

Natural Wetlands

22% Freshwater 1% Landfill 7% Natural Gas 8% Coal 7% Biomass Burning 10% Termites 7% Rice paddies 20% Hydrates Oceans

Atmospheric Methane Growth Rate

Dlugokencky et al 1998

LAND OCEAN

anthropogenic emission anthropogenic emission

11

70 + 2.5

wet and dry deposition 6 + 53 22-37+17

River runoff River runoff

47 + 53

weathering weathering

33 + 53

volcanic emission volcanic emission

5 7

magma

volatile sulfur from waterlogged soil volatile sulfur from waterlogged soil

2

volatile biogenic sulfur e.g.. DMS volatile biogenic sulfur e.g.. DMS

15-30 40 4

sea-spray sea-spray sea air to land air sea air to land air land air to sea air land air to sea air

10+17 3

The Sulfur Cycle(values in Tg-S/year) (modified from Graedel and Crutzen 1993)

Distribution of Wetland Ecosystems

FORESTED BOG NONFORESTED BOG FORESTED SWAMP NONFORESTED SWAMP ALLUVIAL

• E. Mathews and I. Fung (1987)

Global interpolated distribution

• f

total (wet + dry) S- deposition (mg/m2/year) for the years 1960 (a), 1990 (b) and 2030 (C)

2030 1990 1960 Modelled total S-dep 1960-2030

How does the addition of sulfate affect the rate of methane emission

• Microbially mediated processes.
• Two anaerobic microbial communities (sulfate

reducers and methane producers) are in direct competition over limiting substrates

Microbial Competition

M SRB

CH4+ CO2

Acetate

H2 + CO2 substrate

CH4

M

CO2 + H2S

Acetate

H2 + CO2 substrate

Sulfate absent Sulfate present

SRB

Previous work investigating the link between sulphate and methane emission

• Single, large fertilisation doses

(103 kg/ha) rice paddies.

• Lab peat cores in controlled environments

(single ‘pollution’ doses of around 50kg/ha)

• Continuous pollution level doses -

(limited data)

Methods

CH CH4

4

• Field location
• Experimental design
• Static Chamber method

Field Location

Moidach More

x

ITE Edinburgh

x

Moidach More

N

Study Site Inset

Chamber Design

Neoprene ‘O’ ring Polypropylene pipe (300mm ID) 6mm acrylic Suba-seal Sample syringe

R2 = 0.4775

10 20 30 40 50 20 40 60 80 100 120 140

Sedge shoot number

Flux /mgCH4/m2/day

Relationship between the number of sedge shoots and methane flux

Experimental Design

KEY Controls TREATMENT 25 Kg SO4-S 50 Kg SO4-S 100 Kg SO4-S 50 Kg SO4-S (single) BLOCK 1 BLOCK 2 BLOCK 3

R2 = 0.4775

10 20 30 40 50 20 40 60 80 100 120 140

Sedge shoot number

Flux /mgCH4/m2/day

Relationship between the number of sedge shoots and pre-treatment methane flux

Control vs. 25kg SO4-S/ha/yr

date µgCH4/plant/day

50 100 150 200 250 11/03/97 19/06/97 27/09/97 05/01/98 15/04/98 24/07/98 01/11/98 09/02/99

control 25kg

Control vs. 50kg SO4-S/ha/yr

µgCH4/plant/day date

50 100 150 200 11/03/97 19/06/97 27/09/97 05/01/98 15/04/98 24/07/98 01/11/98 09/02/99

control 50kg

date

Control vs. 100kg SO4-S/ha/yr

50 100 150 200 11/03/97 19/06/97 27/09/97 05/01/98 15/04/98 24/07/98 01/11/98 09/02/99 control 100kg

µgCH4/plant/day

5 10 15 20 25 30 M A M J J A S O N D J F M A M J J A S O N D J

Control

24.5g

25kg 17.4g (-29%) 50kg 19.0g (-22%) 100kg 16.6g (-32%)

1997 1998 g CH4m-2 Cumulative mean daily methane flux from Moidach More

P-value (Control vs. Treatment)TREATMENTMean CH4 Flux (±s.e.)(mg CH4 .m-2.day-1)(a)(b)Pre-tre

Total monthly rainfall (a), peat temperature 10 cm below water table (b) and mean water-table position (c) over the course of the experiment.

1997 1998 b) a)

5 10 15 A M J J A S O N D J F M A M J J A S O N

• 25
• 20
• 15
• 10
• 5

20 40 60 80 100 120 140 160

c)

Total monthly rainfall /mm Temperature 10cm below water-table Water-table /cm from surface

Date Mean % variation in treatment flux mean water table/ cm % variation in (treatment) methane flux and mean water table in 1997 -1998

• 70
• 60
• 50
• 40
• 30
• 20
• 10

10 20 30/05/97 07/09/97 16/12/97 26/03/98 04/07/98 12/10/98 20/01/99

• 25
• 20
• 15
• 10
• 5

5

3 per. Mov. Avg. (mean CH4 variation) 3 per. Mov. Avg. (water table)

• 70
• 60
• 50
• 40
• 30
• 20
• 10

2 4 6 8 10 12 14 16

• 10
• 8
• 6
• 4
• 2

% difference in treatment flux

• vs. control flux

temp (deg C) 10cm below Water table depth from peat surface to water table (cm)

PVCH4 = 2.2*temp - 44.7*WT-1 -71.7 R2 = 0.67 P<0.0001

Measured data (•) and modelled data surface showing the relationship between treatment effect, temperature and water table (specific to Moidach More where water-table varied temporally). Heavy lines excludes areas for which no data is available.

** P< 0.01 * P < 0.05

Porewater Chemistry

Porewater [CH4], µM Porewater [SO4-S], µM

20 40 60

*

50 100 10 20 30

**

Depth below peat surface /cm

control 50 Kg SO4-S

a) b)

*

What ar What are the implications e the implications f for global

• r global

atmos atmospheric pheric methane in the methane in the future? future?

Method: Method:

• Tropospheric

Tropospheric S simulation in GISS GCM S simulation in GISS GCM

• CH

CH4

4 from natural wetlands in GISS GCM

from natural wetlands in GISS GCM

• Estimat

Estimation of rice CH ion of rice CH4

4 using IPCC method

using IPCC methodologies

• logies

Global interpolated distribution of total (wet + dry) S-deposition (mg/m2/year) for the years 1960 (a), 1990 (b) and 2030 (C) and areas impacted with S in excess of the 15kg/ha/year threshold for the same years (i,ii,iii respectively).

i ii iii

2030 1990 1960

Modelled global S - deposition

Natural wetlands CH4 emissions 1960-2030

1960 1990 2030

Nothern Wetland (>50 deg Nth) CH4 flux/Tg CH4 flux with S -deposition (Tg) % flux reduction

33.9 39.3 46.2 29.2 15.4

17.3

13.9 32.4 39.1

Modelled Northern Wetland CH4 Emissions As Affected by S deposition (annual CH4 emissions /Tg)

Estimated Rice Paddy Methane emissions

59.8 86.2 56.4 70.6 63.6 56.4

40 50 60 70 80 90 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 year

annual CH4 emissions from rice /Tg Changes in rice production + S-dep Changes in rice production only