Development of Emission Factors for GHGs and Associated - - PowerPoint PPT Presentation

• Dr. J.S. Pandey

Deputy Director & Science Secretary National Environmental Engineering Research Institute (NEERI) NAGPUR – 440 020, India

Development of Emission Factors for GHGs and Associated Uncertainties

Development of Region-Specific Emission Factors : Case Study of Methane-Emissions from Wetlands

• Spatio-temporal
• Interactions among physical,

chemical and biological factors responsible for methane emissions

• Wetlands contribute to about

25% [145 Tg CH4 per year)

• f total methane emissions

(natural as well as anthropogenic).

C arbon C ycle

S

• il

O cean B

• ttom

A tm

• sphere

Terrestrial B iosphere*

C H

R h N P P N P P O H

• + C

H

H 2O + C H

• D

O C C O

Respiration &

• utgassing

m icro b ial resp ira tio n R h L itter

U pper O cean

• xid

atio n O rg C C O

ru m in an ts, term ites , an d p lan ts C O

Burial C H

Burial p h y to p lan kto n C H

R ivers * E xcluding soil m icrobes

m icro b ia l m eth an

• g

en esis

W e tlands

Combustion of fossil fuels C O

(to s trato sp h e re ) C H

C O

Fires C H

C O

O rg C

Wetland : Stratification

• Sub-surface

(anaerobic) zone containing methanogenic bacteriaproducing methane

• Surficial (aerobic) zone

containing methanotrophic bacteria which oxidizes methane

C arbon C ycle

Soil O cean Bottom Atm

• sphere

Terrestrial Biosphere*

C H

R h N PP N PP O H

• + C

H

H 2O + C H

• D

O C C O

Respiration &

• utgassing

m icrobial respiration R h Litter

U pper O cean

• xidation

O rg C C O

rum inants, term ites, and plants C O

Burial C H

Burial phytoplankton C H

R ivers * Excluding soil m icrobes

m icrobial m ethanogenesis

W etlands

Combustion of fossil fuels C O

(to stratosphere) C H

C O

Fires C H

C O

O rg C

Methane Release from Wetlands to Atmosphere

• Diffusion
• Ebullition
• Transport

through arenchymous vascular plants

• Daily rates of CH4

emission in wetlands are normaly 100 mg m-2 day-1

Aerenchyma

Ecosystem Controls on CH4 Emissions from Wetlands

• Water Table Position
• Temperature
• Plant

Community Compositions

Importance of Methane

• N2, O2 and Argon comprise 99.9% of the

total dry air.

• Many trace gases including methane exist at

the level of uL/L or even much less.

• However, despite their low concentrations

many of these trace gases profoundly influence the oxidative photochemistry of the the troposphere and the earth’s energy balance.

• CH4 has increased by about 13 % between

(1978 and 1999) [Whalen, 2005]

Lovelock and Margulis (1974)

Composition of the atmosphere has historically been maintained in close homeostasis by

• Various microbial metabolic processes which are responsible

for the production and consumption of trace gases

• The major sources and sinks in the atmospheric CH4 budget

have been presented in the subsequent slides.

• However, many of these terms are poorly quantified and

understood.

• This introduces considerable uncertainty in the model

predictions ( Whalen, 2005).

Methane Sources and Sinks

145 20 15 10 190 50 100 150 200 M eth an e E m issio n s

Ecosystems

Natural Sources (Tg CH4 per year) Series1 145 20 15 10 190 Wetlands Termites Oceans Hydrates Total

80 115 40 25 40 110 410 50 100 150 200 250 300 350 400 450 Methane Emission

1

Source-Types Anthropogenic Sources (Tg CH4 per Year) Rice Ruminants Landfills Watewater Treatment Biomass Burning Energy Total Anthropogenic

30 510 40 580 600 100 200 300 400 500 600 M ethane

1

Sink-Types Sinks vs. Sources (Tg CH4 per Year) : Sinks are mainly dominated by Photochemical processes. Soil-Sink Tropospheric (OH)-Sink Stratospheric-Sink Total Sinks Total Sources

Methane Consumption and Emission

• Roughly 85% of the total CH4 emitted from

the earth’s surface is oxidized in the troposphere by OH-radical.

• About 9% enters the stratosphere, reacts

with with Cl-atoms to form HCl.

• Considering all these removal mechanisms,

the present atmospheric life-time of CH4 is about 8.4 years.

Modelling Approaches [Whalen, 2005; Bubier and Moore, 1994; Ridgewell et al. 1999; Walter and Heimann, 2000]

• The major shortcoming of climate models is the

lack of comprehensive understanding of the linkage between biogeochemical processes and the troposphere.

• Thus, the present modelling thrust is on

integrating site-specific and time-specific studies so as to develop process-oriented simulation models suitable for incorporation into large scale models of climate change .

Uncertainties : Arctic and Boreal (Habitats and Location Types)

Source : Liblik et al. (1997); Bellisario et al. (1999); Whalen and

Reeburgh (1992); Bartlett et al. (1992)

• Fens, bogs, ponds,

palsas (Northwest Territories)

• Bogs,

rich fens (Manitoba)

• Subarctic

tundra (Alaska)

• Wet

meadow (Alaska)

100 200 300 400 500 600 700 L e v e ls o f U n c e r ta in tie s

Habitat (Ecosystem) Types CH4 Flux (mg m

• 2 day
• 1)

NWT (Min.) NWT (Max.) Manitoba (Min.) Manitoba (Max.)

• Sub. Tundra (Min.)
• Sub. Tundra (Max.)

Wet Tundra (Min.) Wet Tundra (Max.)

Uncertainties : Temperate and Sub-tropical (Habitats and Location Types)

Source : Crill et al. (1988); Frolking and Crill (1994); Wilson et al. (1989); Alford et al. (1997)

• Open and forest bog,

fen (Minnesota)

• Poor

fen (New Hampshire)

• Swamp (Virginia)
• Swamp forest, marsh

(Louisiana)

23 254 21 639 83 155 146 912 100 200 300 400 500 600 700 800 900 1000 R ange of U ncertainties

Habitat (Ecosystem) Types CH4 Flux (mg m-2 day-1) Minnesota (Min.) Minnesota (Max.) New Hampshire (Min.) New Hampshire (Max.) Virginia (Min.) Virginia (Max.) Louisiana (Min.) Louisiana (Max.)

Uncertainties : Tropical (Habitats and Location Types)

Source : Bartlett et al. (1988); Devol et al. (1990); Tathy et al. (1992)

• Flooded forests & grass mats (Amazon Floodplain)
• Flooded forests (Congo River Basin)

7 230 10 550 100 200 300 400 500 600 Range of Uncertainties

1

Habitat (Ecosystem) Type CH4 Flux (mg m-2 day-1) Amazon (Min.) Amazon (Max.) Congo (Min.) Congo (max.)

Diurnal Uncertainties 1 2 3 4 5 5 10 15 20 Day Time (Hours)

Methane Emissions (mg m-2 h-1)

Diurnal Uncertainties 5 10 15 20 25 30 5 10 15 20 Day Time (Hours) Methane Emissions (mg m-2 h-1)

• Ref. : Zhang et al. 2007.

There are spatial as well as seasonal variations in methane emissions. Methane emission, inter alia, depends on the following parameters : ฀• Temperature; ฀• Soil (sediment)-pH; ฀• Organic carbon; ฀• Redox-potential; ฀• Wind-speed; ฀• Solar-radiation; ฀• Physico-chemical water quality parameters; and ฀• Adjacent bio-spheric composition.

Some pertinent observations which have helped in developing the emission factors presented in this paper can be summarized as follows : ฀ • For almost all the water bodies, methane emissions are highest in summer months and lowest in winter months. In rainy season, they lie somewhere in-between. ฀ • The vegetated region of the running water (Gomti river) shows wide variations in emissions ranging from 18 mg m-2 h–1 in winter to nearly 80 mg m-2 h–1 in summer. In rainy season the value is around 32 mg m-2 h–1. ฀ • The range of variation, however, is quite small in case

• f non-vegetated zone. For instance, this range is 4.5-8 mg m-2

h–1 in case of running water and 0.5-2.5 mg m-2 h–1 in case of standing water (lake). ฀ • In regard to non-vegetated zones, there is one more interesting observation. For both running (river) as well as standing (lake) water, methane emissions are higher in winter and lower in summer. Whereas for vegetated zone the situation is exactly opposite.

Inferences

• The seasonal variation is mainly attributable to the dependence of

microbial activity (which is the main regulating factor behind methane emission) on temperature. In fact, a closer look at the data (Singh et al., 2000) clearly indicates that temperature-dependence is far more

• verriding (Conrad, 1989; Khalil et al., 1991) than dependence on any
• ther parameter, viz. soil pH, organic carbon and redox potential etc.

Role of pH is limited to providing the optimum range (from 6 to 8) for methanogenesis to occur (Williams and Crawford, 1984; Worakit et al. 1986). There are some variations in methane emissions due to changes in redox-potential. However, the variations do not follow any discernible or systematic trend (Singh et al. 2000).

Inferences (contd….)

• Amount and composition (kind) of organic

carbon load coming to a water body also plays a significant role. However, assuming that there is a constant amount

• f
• rganic

carbon load continuously flowing into the water-body almost every day (quite a valid assumption for Indian cities), it (organic carbon) can not be used as a determinant for predicting variations dependent

• n it.
• Therefore, the main factor which will ultimately

determine the rate of methanogenesis and methane–emission is going to be the sediment or soil temperature. A thorough and systematic analysis of data clearly points towards a direct link between methane emission and temperature.

• Stomatal conductance may also control CH4

emission in some species (Morrissey et al., 1993).

Methanogenesis

• In general, N and P inputs to water bodies, do not

stimulate methanogenesis (Williams and Crawford, 1984;

Bridgham and Richardson, 1992).

• Studies

related with pH-dependence

• f

methanogenesis give very inconsistent results

[Dunfield et al., 1993; Williams and Crawford, 1984; Richardson, 1992; Valentine et al., 1994; Bergman et al., 1998]

• Moreover, Moore and Roulet (1995) suggested that pH, at

best can be a secondary determinant for methanogenesis.

Dependence of Methanogenesis

• n Temperature
• Temperature exercises a strong control on

methanogenesis (Zeikus and Winfrey, 1976; Svensson, 1984; Williams and Crawford, 1984; Dunfield et al., 1993; Wagner and Pfieffer, 1997; McKenzie et al., 1998)

Dependence of Methane Production on Temperature : Variations in Q10-Values

• Bogs : Dunfield et al. (1993);

Velentine et al. (1994); Nedwell and Watson (1995); Updegraff et

• al. (1995); Yavitt et al. (2000);

Frenzel and Karofeld (2000)

• Swamp

:

Westerman and Ahring (1987); Westerman (1993)

• Coastal Meadows : Prieme

(1994)

• Peatlands : Yavitt et al. (1997)
• Acid Mixed Mire : Bergman

et al. (1998)

• Boreal Riverine Wetlands :

McKenzie et al. (1998)

5 10 15 20 25 30 35 Q

1 0

• V

a l u e s Bogs Swamp Coastal Meadow Peatlands Acid Mixed Mire Boreal Riverine Wetlands

• Min. - Max. Values

Methane Production : Temperature Dependence

Methane Oxidation : Temperature- Dependence

• Swamps : Dunfield et
• al. (1993)
• Bogs : Nedwell and

Watson (1995); Whalen and Reeburgh (1996)

• Wetland

Forests : Megonigal and Schlesinger (2002)

0.5 1 1.5 2 2.5 3 Q10 - Values Swamps Bog Wetland Forests

• Min. - Max. Values

Methane Oxidation : Temperature Dependence

Results and Discussion The emission factors as functions of temperature for four different types of zones are presented below (equations 1 through 4) : Running Water (River) : Vegetated Zone Emission Factor = 0.3963 (Temp)2 – 18.021 (Temp) + 209.83

• (1)

Non-Vegetated Zone Emission Factor = 0.0128 (Temp)2 – 0.8654 (Temp) + 19.006

• (2)

Stagnant Water (Lake) : Vegetated Zone Emission Factor = 0.4169 (Temp)2 – 20.860 (Temp) + 256.29

• (3)

Non-Vegetated Zone Emission Factor = 0.0241 (Temp)2 – 1.266 (Temp) + 16.545

• (4)

These models can be used as emission factors for the similar region and provide an important step forward in the area of developing region-specific emission factors (Figures 1 through 4).

F igure 1 : Running Water (River) : Vegetated Zone

18 32 80

M ethane-Emission-Factor (y) = 0.3963 x (Temp)2 - 18.021 x (Temp) + 209.83 10 20 30 40 50 60 70 80 90 10 20 30 40 Temperature oC Methane Emissions (mg m

• 2 hr-1)

F ig u re 2 : R u n n in g W a te r : N

• n
• V

e g e ta te d Z

• n

e

8 4 .5 4 .5

M e th a n e

• E

m issio n

• F

a c to r (y ) = .0 1 2 8 x (T e m p )

2 - 0

.8 6 5 4 x (T e m p )+ 1 9 .0 6 1 2 3 4 5 6 7 8 9 5 1 1 5 2 2 5 3 3 5 4 T e m p e ra tu re (

• C

) Methane Emissions (mg m

• 2 hr-1)

Figure 3 : Stagnant Water (Lake) : Vegetated Surface

22 10 50

Methane-Emission-Factor (y) = 0.4169 x (Temp)2 - 20.869 x (Temp) + 256.29

• 10

10 20 30 40 50 60 5 10 15 20 25 30 35 40 Temperature (oC) Methane Emissions (mg m-2 hr-

1)

Lake : Unvegetated Surface

2 0.5 2.5

y = 0.0241x2 - 1.266x + 16.545 R2 = 1

• 0.5

0.5 1 1.5 2 2.5 3 5 10 15 20 25 30 35 40 Temperature (oC) Methane Emissions (mg m

• 2 hr-1)

Recommendations

• A word of caution : Certain factors can suddenly transform a GHG-

source into a GHG-Sink and vice-versa. For instance , a seasonal reduction in the water table position transformed atemperate swamp from an atmospheric CH4-source to a CH4-sink (Harris et al., 1982).

• In India, some studies have been very recently initiated by dividing the

whole watershed into various smaller grids depending on their ecological characteristics.

• Each of these grids would be monitored and studied under the

following subcategories: (a) open water; (b) flooded forest; and (c) aquatic macrophyte zone.

• These emissions would then be summed up for every grid and then

appropriately integrated over all the grids so as to estimate the emission for the whole watershed area.

Recommendations (contd..)

• Since the main scientific debate at the moment is centered around the

uncertainties associated with extrapolating emissions measured at selected parts at selected intervals of time, monitoring would have to be extended over widely different ecological zones and over longer time frames in order to obtain region-specific spatio-temporal emission-factors (functions).

• This will not only reduce the spatial uncertainties but also the

uncertainties associated with diurnal, seasonal and annual variations.

• There is a growing consensus amongst scientists world-over that these

emissions should be estimated both before and after construction of each dam so as to understand, analyze and quantify the net global warming/GHG-emission potential of various hydroelectric dams.

• The focus of these field studies should be on developing region-

specific emission factors in accordance with recent IPCC guidelines.

Thank You

The "A-Train". The figure on the left illustrates the constellation of satellites known as the "A Train," which will make nearly contiguous observations of many facets of the Earth system. Courtesy : NASA.

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