Peat areas, global warming, management and greenhouse gases

17

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Peat areas, global warming, management

and greenhouse gases

2.1 Introduction

In this chapter the context of the research is described. The need for research

investigations of GHG’s in peat areas and the effects of (water) management and climate

change is explained. First, climate change and the enhanced greenhouse effect are

addressed. Secondly, the terrestrial carbon cycle is described and, more specifically, the

existing knowledge of the carbon cycle in peat areas as well as feedbacks to climate and

effects of management practices. Peatlands in the Netherlands are highlighted and the

history of management practices in these areas is summarized. Next, the techniques used

in this research to measure GHG fluxes, the chamber method and eddy covariance, are

described. Finally, an overview of previous research on GHG fluxes and GHG balances of

peat areas in temperate regions is given.

2.2 Climate change and the greenhouse effect

2.2.1 Recent climate change

Over the past 100 years global mean surface temperatures have risen at a relatively high

rate, by 0.74°C ± 0.18°C. Moreover, the rate of warming over the last 50 years almost

doubles that of the last 100 years. Also, precipitation has generally increased over land

north of 30°N over the period 1900 to 2005 and substantial increases of severe

precipitation events are observed. On the other hand, droughts have become more

common, especially in the tropics and subtropics, since the 1970s (Le Treut et al., 2007).

Though changes in climate have occurred since millions of years, the temperature rise

observed over the past century is considered exceptionally high. Numerous scientific

reports have stated that these recent climatic changes are, at least partly, brought about by

human activities on the earth’s natural greenhouse effect (Le Treut et al., 2007).

2.2.2 The greenhouse effect

The natural greenhouse effect is the property of the earth’s atmosphere to absorb thermal

(long wave) radiation that is emitted by the earth’s surface that is heated by solar (short

wave) radiation. This property is part of the earth energy balance. On the long term, the

amount of incoming solar radiation absorbed by the Earth and atmosphere is balanced by

the earth and atmosphere releasing the same amount of outgoing long wave radiation.

About half of the incoming solar radiation is absorbed by the earth’s surface. This energy

is transferred to the atmosphere by warming the air in contact with the surface (sensible

heat), by evaporation and by long wave radiation that is absorbed by clouds and GHG’s.

Chapter 2

18

The atmosphere in turn radiates long wave energy back to earth as well as out to space

(Kiehl and Trenberth, 1997). Without the atmospheric property to absorb part of the long

wave radiation, the annual global surface temperature would be -18oC instead of 15

oC.

Besides by clouds, thermal radiation is absorbed by important long-lived GHG’s, mainly

water vapour (H2O), carbon dioxide (CO2), CH4 and nitrous oxide (N2O). Additionally,

other factors, like ozone, surface albedo and aerosols, influence the surface temperature

through positive or negative radiative forcing. Most of these factors have been affected by

anthropogenic activities, mainly since the industrial revolution around 1750. Figure 2.1

gives an overview of the most important sources of radiative forcing and their current

relative impact on the greenhouse effect.

2.2.3 Global warming

The strongest impact on the greenhouse effect is caused by the increase of long lived

GHG’s in the atmosphere, resulting in increased absorption of thermal radiation and hence

rising tropospheric and surface temperatures. This phenomenon is often referred to as the

enhanced greenhouse effect. The relative contribution to the enhanced greenhouse effect

by atmospheric emissions of a particular GHG is usually compared to that of CO2 by using

the Global Warming Potential (GWP) index, taking into account the atmospheric lifetimes

of the different gases. The GWP’s of CH4 (~25, over 100 years) and N2O (~298, over 100

years) are significantly higher than that of CO2 (1 by definition) (Forster et al., 2007).

In 2005 the global mean

concentration of CO2 was

379 ppm, almost 100 ppm

above its pre-industrial

level, leading to an

additional radiative

forcing of +1.66 ±0.17 W

m–2

(Fig. 2.2). The

atmospheric CO2

concentration has risen

mainly due to industrial

activities and energy

production. From 1995 to

2005 the largest change in

CO2 concentrations was

observed or inferred for

any decade in at least the

last 200 years, probably

due to increased

industrial development of

developing countries. The

atmospheric CH4 concen-

Figure 2.1: Summary of the principal components of the

radiative forcing of climate change between 1750 and 2005

(From Forster et al., 2007).

Peat areas, global warming, management and greenhouse gases

19

tration has increased with 150% since

pre-industrial levels mainly due to

agriculture, energy production, waste

management and biomass burning. In

2005 the global mean concentration

of CH4 was 1,774 ppb, contributing a

radiative forcing of +0.48 ±0.05 W

m–2

. Over the past two decades, CH4

growth rates in the atmosphere have

generally decreased, however the

cause of this inter-annual variability is

not well understood. The atmospheric

N2O concentration has increased with

17% since pre-industrial levels.

Agriculture is the single largest

anthropogenic source. The global

mean N2O concentration rises

approximately linearly (0.26% yr–1

)

and reached a concentration of 319

ppb in 2005, contributing a radiative

forcing of +0.16 ± 0.02 W m–2

(For-

ster et al., 2007). Besides inducing

climate change through the enhanced

greenhouse effect, the additional

burden of GHG’s leads to a

‘perturbed’ global carbon cycle

(Denman et al., 2007).

2.2.4 Future climate change

Based on temperature records of the

past centuries and knowledge of the

enhanced greenhouse effect, future

scenarios of climate change have been

developed. Generally, global mean

temperatures are expected to increase

further (1.1 oC to 6.4

oC over the next

century) and evaporation will increase

as well as precipitation intensity and

variability. However, it should be

taken into account that model

projections often show great variation

and that the effects of the enhanced

greenhouse effect on climate will vary

between regions. Warming over land

Figure 2.2: Atmospheric concentrations of important

long-lived greenhouse gases over the last 1,000 years

(From Forster et al., 2007).

Chapter 2

20

areas is greater than global annual mean warming due to lower water availability for

evaporative cooling and a smaller thermal inertia as compared to the oceans. Spatial

variability of precipitation is enhanced by increasing temperatures, contributing to a

reduction of rainfall in the subtropics and an increase at higher latitudes and in parts of the

tropics. In Europe annual mean temperatures are likely to increase more than the global

mean (2.2 oC to 5.3

oC over the next century). The warming in northern Europe is likely to

be largest in winter. In this area also annual precipitation and extremes of daily

precipitation are very likely to increase (Christensen et al., 2007). Climate scenario’s for

the Netherlands predict a temperature rise of 2°C to 4°C over the coming century, more

frequent heat waves and precipitation extremes (Van den Hurk et al., 2006).

2.3 Terrestrial carbon cycle and feedbacks to climate

2.3.1 The carbon cycle

The main reservoirs of carbon are geologic formations that have formed over the course of

earth history. The turnover rates of this carbon are however very slow and there is little

natural exchange with the atmosphere. On shorter timescales, the processes that regulate

atmospheric carbon are the interactions between terrestrial biosphere and atmosphere, the

interactions between ocean surface and atmosphere and the combustion of fossil fuels

(from geologic reservoirs to atmosphere). Figure 2.3 gives an overview of the global

carbon cycle with both its ‘natural’ and ‘anthropogenic’ fluxes for the 1990’s. Although

uncertainties are considerable (± 20% for each flux), the significant influence of

anthropogenic emissions is apparent. Atmospheric CO2 is increasing at only about half the

rate implied by fossil fuel plus land use emissions. The remainder of these anthropogenic

emissions is currently being taken up by the ocean, and vegetation and soil on land

(Denman et al, 2007). Therefore, the ocean and terrestrial carbon cycles are currently

helping to mitigate CO2-induced climate change.

2.3.2 The terrestrial carbon cycle and climate

Terrestrial ecosystems contain large pools of carbon in direct contact with atmosphere.

The net exchange of carbon between terrestrial biosphere and atmosphere is determined by

the difference between carbon uptake by photosynthesis and release by plant and soil

respiration. Additionally, disturbance processes (e.g. fire, wind throw, deforestation,

afforestation, agriculture) account for a large part of the terrestrial carbon that is released

to the atmosphere. Each year approximately 120 Pg C yr-1

is taken up from atmosphere by

ecosystems through photosynthesis (eq. 2.1):

6CO2 + 6H2O + radiation energy � C6H12O6 + 6O2 (2.1)

Of this gross primary production approximately 60 Pg C yr-1

is consumed by plants

(autotrophic respiration) through oxidation of organic carbon (eq. 2.2):

C6H12O6 + 6O2 � 6CO2 + 6H2O + energy (2.2)

Peat areas, global warming, management and greenhouse gases

21

and approximately 60 Pg C yr-1

is used for growth, stored in living tissue. When this

carbon turns into litter or dead root mass it becomes available for soil microbial activity

(heterotrophic respiration) through oxidation of organic carbon (eq. 2.2). Besides aerobe

respiration by plants and microbes, part of the soil carbon in water saturated, anaerobic

conditions is subjected to methanogenesis (Schlesinger, 1991; Whalen, 2005). The two

best described pathways involve the use of CO2 (eq. 2.3) and acetic acid (eq. 2.4) as

terminal electron acceptors:

CO2 + 4 H2 → CH4 + 2 H2O (2.3)

CH3COOH → CH4 + CO2 (2.4)

Under aerobe soil conditions (above the soil water table), CH4 is oxidized by

methanotrophic microbes that use oxygen as terminal electron acceptor (eq. 2.5):

CH4 +2 O2 → CO2 + 2 H2O (2.5)

Under certain conditions, microbial oxidation of CH4 uses sulphate or nitrate as the

terminal electron acceptor. Other major sinks of CH4 are oxidation by OH in the

troposphere and loss to the stratosphere. Over the last 30 years, the net result of all

processes described above was carbon uptake by terrestrial ecosystems.

Gross primary production, autotrophic respiration, heterotrophic respiration and

methanogenesis are not evenly distributed over the globe, but are dependent on biomass

and litter quantity and properties, available sunlight, moisture, temperature and nutrient

availability. Fluxes of carbon are generally highest in the tropics, however due to the high

respiration rates carbon stocks are not highest in the tropics. The important carbon stocks

are situated in temperate and arctic regions. Here, peat areas have accumulated half of the

current total atmospheric carbon content since the last glacial maximum, despite the

relatively low photosynthesis rates.

Another important factor in the terrestrial carbon cycle is the flux of carbon through water

streams. The role that streams and lakes play in the carbon budgets of terrestrial

ecosystems has long been neglected, even though they may be associated with significant

losses of carbon (Billett et al., 2004). Currently, the amount of terrestrial carbon that is

transported from the land to the oceans via rivers either dissolved carbon or as suspended

particles is estimated at approximately 1 Gt C yr-1

(Denman et al., 2007). Especially, in

peat areas the amount of carbon lost through water streams can be high (Hope et al.,

1994).

Chapter 2

22

2.4 Peatland: greenhouse gases, climate and management

2.4.1 Carbon cycle and feedbacks to climate

A peatland is a type of ecosystem where carbon along with nitrogen and several other

elements has been accumulated as peat originating from the plant litter deposited on the

site. Since favourable conditions include impeded water drainage, high precipitation

and/or limited evaporation due to low temperatures, peatlands occur primarily at northern

and temperate latitudes. In these ecosystems more carbon is accumulated through

photosynthesis than is released through respiration, which is the organic matter

accumulating as peat. As a result peatlands are natural sinks of atmospheric CO2.

Although peatlands cover only 5-6% of the earth surface (Fig. 2.4), they play a central role

in the global carbon cycle. With a long term average uptake rate of 25 gC m-2

yr-1

(Korhola et al., 1995; Borren et al., 2006), peatlands have accumulated approximately 455

Gt g carbon from the atmosphere during the previous 10.000 years. This amount is equal

to half of the current atmospheric CO2 content (Gorham, 1991). Possible destabilizing

effects of climate change could therefore have a large impact on CO2 concentrations in the

atmosphere and create a significant positive feedback to climate change.

Peatlands are not just acting as carbon sinks, but wet and anaerobic soil conditions lead to

methanogenesis and significant CH4 emissions. Wetlands, including peatlands, are

considered the largest single source of atmospheric CH4 (Denman et al., 2007).

Additionally, inter-annual variability of global atmospheric CH4 is suggested to be

Figure 2.3: The global carbon cycle for the 1990s, showing the main annual fluxes in GtC

yr–1: pre-industrial ‘natural’ fluxes in black and ‘anthropogenic’ fluxes in red (From

Denman et al., 2007).

Peat areas, global warming, management and greenhouse gases

23

dominated by wetland emissions (Bousquet et al., 2006). Recently atmospheric conditions

were found to have stabilized over the past two decennia (Foster et al., 2007). However,

according to recent predictions (Denman et al., 2007) future CH4 emissions from wetlands

and peatlands are likely to increase in a warmer and wetter climate, and to decrease in a

warmer and drier climate. Besides playing a central role in the carbon cycle through CO2,

peatlands are thus a key-player in the global atmospheric CH4 budget having a strong

influence global climate.

Additionally, peatlands loose carbon through outflow of dissolved carbon, suspended

particles, and dissolved CH4 exported from the soil profile and transported out of the

ecosystem by water streams (Hope, 1994; Billett, 2004). These carbon fluxes in water

have been reported to form a significant part of the overall carbon budget of peatlands

(Hope et al., 1994; Worrall et al., 2005; Moore and Clarkson, 2007) and in some cases

even equal or exceed the net ecosystem exchange of carbon with atmosphere (Billett et al.,

2004). Although expected, no evidence of an effect of climate change (e.g. increase of

droughts) on dissolved carbon in streams has been observed (Hope et al., 1994; Worrall

and Burt, 2007).

2.4.2 Effects of management practices

In addition to climate change, land use change and management practices pose a serious

threat to the immense carbon stocks of peatland areas. In Europe for instance about 50%

of all peatlands are subject to various sorts of land use (Joosten and Clarke, 2002), often

associated with drainage (Fig. 2.5). When water tables are lowered, soil conditions

become aerobic and respiration rates increase an order of magnitude. While in natural

peatlands the uptake of CO2 through photosynthesis is larger than the release of CO2 and

CH4 due to microbial decomposition, drained peatlands show a net release of CO2. On the

other hand CH4 emissions cease or even turn to net uptake. Management practices

Figure 2.4: Extent and location of global mires and peatlands. (From Lappalainen, 1996).

Chapter 2

24

(drainage, drying and oxidation of peaty soils) also affect discharge regimes and the

transported load as well as changes in hydrological pathways. However, only minor

changes in dissolved carbon in streams in managed peat areas compared to undisturbed

peatlands have been observed (Moore et al., 1987). Additionally, drained peatlands

sometimes show N2O emissions, while natural peatlands are neutral with respect to N2O

(Fig. 2.6). Besides the changes in natural GHG exchange in peatlands under land use

change, other sources of GHG arise in case of agricultural management. Carbon is lost

through mowing of plant biomass, animal body mass and milk production, while carbon is

imported through manuring and slurry application. CH4 and N2O emissions increase as a

result of enteric fermentation, cattle, manure deposits and livestock wastes (Soussana et

al., 2008). In case of management, peatlands are thus big sources of GHG’s in the

landscape. Even in industrialized countries (e.g. Germany), the estimated peatland GHG

accounts for 2.3-4.5% of anthropogenic emissions (Drösler et al., 2008).

(a)

(b)

Figure 2.5: Peatland areas (a) and their greenhouse gas

balances (b) and use of the top ten peat countries of Europe

(From Drösler et al., 2008).

Peat areas, global warming, management and greenhouse gases

25

2.4.3 Peatlands in the Netherlands

In the Netherlands peat areas take up almost 7% of the land surface (2350 km2), while an

additional area of approximately 1500 km2 consists of peaty soils (>15% - 30% of top 40

cm is organic matter). The western part of the Netherlands contains 1600 km2 of peat soils

(80% peat; 20% peaty), typically called peat meadows since most are covered with grass

vegetation (Fig. 2.7). The majority of the Dutch peatland (85%) is in agricultural use with

lowered water tables (Joosten, 1994).

As a result of continuous relative sea level rise, gradual closure of coastline since 6.000

years and freshening of the coastal zone by river water and seepage, extensive and thick (>

8 m) coastal peat deposits were formed in the western part of the Netherlands. The surface

of these peat formations reached up to 2 m above sea level (Borger et al., 1992). In the 10th

century reclamation and cultivation started taking place in the peat meadow areas. Until

the 14th

century this was mainly done by digging channels to lower groundwater tables

and building small dikes to prevent inundations. The lowering of the groundwater table

caused accelerated decomposition, shrinking, compaction and erosion of the peat and

hence subsidence (Fig. 2.8). From the 15th

century on ground water tables were lowered

further by windmill drainage, causing a further acceleration of the processes that induce

land subsidence, finally resulting in a vicious circle of subsidence and groundwater

lowering. During the past hundreds of years peat was dug and dredged for fuel and

drainage for agricultural purposes was intensified even further using mechanical drainage.

Currently, peat meadow areas typically are grasslands dissected by numerous ditches and

bordered by large shallow surface water bodies (Fig. 2.9).

An estimate of the total amount of carbon lost from peat areas in the Western part of the

Figure 2.6: Schematic comparison of relative magnitudes of net exchange of CO2 (dark

grey), CH4 (white) and N2O (light grey) in peatlands. Dotted areas symbolize the water

saturated part of the profile. Waves in last panel: flooded (From Drösler et al., 2008).

Chapter 2

26

Netherlands since the onset of

drainage was made by Van den

Bos (2003). Assuming an

average peat loss of 2 m over

1600 km2 resulted in a loss of

approximately 0.2 Gt C, which

caused an increase of 0.1

ppmv2 in the global

atmospheric CO2

concentration. The estimation

is however conservative,

because the original peat area

was probably larger than 1600

km2 and at many locations

more than 2 m of peat has

disappeared.

Currently peat degradation in

the Netherlands and many

others locations in the world is

still going on, mainly as a

result of drainage for

agriculture. Since the 1990’s

policy makers and nature organizations decided to start restoration of peatland and

wetland areas, both for nature restoration and carbon mitigation purposes (e.g. the Dutch

ministries of agriculture and spatial planning and Dutch nature organisations and the

German ministry of education and research). The restoration practices cover a broad

spectrum of measures, from total abandonment to reduced agricultural activity.

2.4.4 Effects of restoration and climate change and mitigation possibilities

Since the 1980’s CO2, CH4 and N2O flux measurements have been made in peat areas to

assess the effects of climate change and management practices. However, to obtain a full

overview of the total effect of management and drainage, integrated GHG balances over

one or more years need to be compiled. Additionally, although the processes underlying

CO2 fluxes are relatively well known, for CH4, and N2O fluxes many uncertainties still

exist. Also, the effects of the varying restoration measures applied to disturbed peatlands

on fluxes of CO2, CH4 and N2O need to be investigated. For example, what is the effect of

raised water tables in nutrient rich environments on respiration and methanogenesis? Are

GHG fluxes uniformly spread over the area or do local sources of high GHG emissions

exist? And, what is the effect of vegetation transitions on the GHG fluxes? Thorough

analyses should be made to answer these questions and to determine the GHG mitigation

possibilities of restored peat areas. Finally, projected climate change might have a

significant effect on the soil and vegetation conditions of peat areas and accordingly

greenhouse fluxes are expected to change in magnitude and perhaps even in sign. lysis

should thus be made to anticipate on the effects of climate change on GHG balances of

Figure 2.7: Current distribution of peat soils in the

western part of the Netherlands (From SC-DLO, 1992).

Peat areas, global warming, management and greenhouse gases

27

Figure 2.8: Schematic of the continuous land subsidence and sea level rise

during the past 1.000 years in the Netherlands. Y-axis shows the surface level

of the peat with respect to the sea level in meters and the thick green line the

land surface subsidence (From Van der Ven., 1993).

Figure 2.9: Typical peat meadow area with narrow strips of land, ditches

and large surface water bodies.

Chapter 2

28

peat areas. To meet these objectives, innovation of measurement techniques is important

as well as improvement of existing methods. Only by combining several techniques a

complete insight of the full GHG balances and changes in GHG fluxes due to management

and climate change can be obtained.

2.5 Measurement techniques

Over the past decades various techniques have been developed to measure fluxes of trace

gases and energy in the field. The most common techniques were recently summarized by

Denmead (2008) and consist of flux chamber techniques, mass balance techniques,

Langrangian stochastic dispersion models, the eddy covariance technique and disjunct

eddy covariance, relaxed eddy accumulation and flux gradient observations. The

objectives of this thesis required high spatial and temporal resolution as well as continuous

observations of GHG and energy fluxes at the ecosystem level. The flux chamber

technique is very adequate for detection of fine-scale spatial variability, while eddy

covariance provides an effective approach for continuous landscape scale observations and

detection of fine-scale temporal variability. A combination of the flux chamber technique

and the eddy covariance technique was found most appropriate for these purposes.

However, the level of comparability and the complementarities of the two techniques are

still uncertain and need further investigation. Below, both techniques and their technical

development are described in more detail.

2.5.1 The flux chamber technique

Flux chamber measurements are enclosure-based measurements of trace gas exchange.

The enclosures function by restricting the volume of available air for exchange across the

covered surface (Fig. 2.10), so that any net emission or uptake of the enclosed gases can

be measured as a concentration change (Livingston and Hutchinson, 1995). The closed

chamber method is the most widely used approach to measure the fluxes of CO2, CH4 and

N2O from bare soil surfaces and surfaces with low-stature canopies typical for peatlands,

grass lands, steppes, tundra’s and agricultural crop stands (Christensen, 2003; Kutzbach et

al., 2007; Drösler et al., 2008). First flux chamber measurements were made in the 1960’s

and 1970’s by Witkamp (1966), Schulze (1967), Kanemasu et al. (1974) and Edwards et

al. (1973). Usually, for each flux measurement multiple concentration measurements are

performed at fixed time intervals. From the series of concentration measurements fluxes

are calculated by determining regression lines from the concentration changes over time.

Previously, samples were collected in glass syringes and analyzed in the laboratory using

a gas chromatograph or an infrared gas analyser (IRGA). More recently, flux chambers are

connected with tubes to IRGA’s in the field to perform in situ analyses of the gas samples

(Livingston and Hutchinson, 1995).

Despite the apparent advantages of low cost and power consumption, simple operation

and, a variety of potential errors have to be considered (Livingston and Hutchinson, 1995;

Kutzbach et al., 2007). Important errors consist of inaccurate determination of the

headspace volume, leakage of the chamber, temperature changes beneath the chamber, ar

tificial water vapour accumulation, disturbance of pressure gradients and fluctuations, mo-

Peat areas, global warming, management and greenhouse gases

29

dification of the diffusion

resistance of the soil- or

plant-atmosphere boundary,

disturbance of concentration

gradients in the chamber.

Before employment, the

whole set up should be

carefully constructed and

tested for the field

conditions in which it will

be applied. Also, the

conditions in the flux

chamber should be

monitored and if necessary

taken into account in the

flux calculations.

2.5.2 The eddy covariance technique

The eddy covariance technique is an atmospheric flux measurement technique to measure

and calculate vertical turbulent fluxes within atmospheric boundary layers. It is a

statistical method used in meteorology and other applications that analyzes high-frequency

wind and scalar atmospheric data series, and yields values of fluxes of these properties

between an ecosystem and the atmosphere. In eddy covariance, the vertical flux (Fs) of an

atmospheric property (s) is directly determined by the covariance of that property and the

vertical velocity (eq. 2.6). This can be obtained by calculating the time averaged product

(over the period t1 to t2) of the deviation (s’) of the atmospheric property (s),

from 'sss += , and the deviation (w’) of the vertical wind velocity (w)

from 'www += :

∫−

==

2

1

)(')('1

''12

t

t

s dttstwtt

swF (2.6)

The eddy covariance technique requires an instrument with high precision, accuracy and

system stability as well as high sampling rates (>10Hz) and a short instrument response

time. The instruments measuring the vertical wind speed (ultrasonic anemometer) and the

atmospheric properties (IRGA) are usually located at a tower well above the top of the

vegetation (Fig. 2.11). The upwind area where the measured atmospheric flux is generated

is called the flux footprint. This is the upwind area that is “seen” by the instruments

measuring vertical turbulent fluxes and is largely dependent on height of the tower, the

wind speed and the wind direction. With knowledge of the general wind patterns eddy

covariance towers can be placed so that the area of interest is located within the footprint.

The advantages of the eddy covariance technique compared to other techniques for

measuring trace gases are: integrated continuous measurements over a large footprint area

Figure 2.10: Example of an enclosure for flux chamber

measurements (From Livingston and Hutchinson, 1995).

Chapter 2

30

(102 to 10

4 m

2) and longer periods without disturbance from small scale surface features.

These properties enable assessments of temporal variability at the ecosystem level, long

term estimates of net fluxes of ecosystems and differences between ecosystems.

The fundamental concepts of eddy covariance were proposed in 1951 by Swinbank.

However, not before the 1980’s the difficulties of instrumentation and data-collection

were overcome and measurements of H2O, CO2 and energy fluxes were possible. Webb et

al. (1980) showed that Fs as calculated in eq. 2.6 gave incorrect estimates, because of the

measured fluctuations resulted from fluctuations in water vapour density and temperature

not associated with the net transport of the atmospheric property of interest. The

corrections proposed to adjust the flux calculations for these temperature and water vapour

effects have since then been generally applied during the data processing of flux

measurements. Since the 1980’s various eddy covariance systems were developed (Lloyd

et al., 1984; Businger, 1986; McMillen, 1988; Moncrieff, 1997) and short term

measurement campaigns over various types of terrain were carried out for several types of

ecosystems (Verma et al., 1986; Valentini et al., 1991; Hollinger et al., 1994; Baldocchi

and Meyers, 1991). Starting in the early 1990’s CO2 flux measurement campaigns were

made on annual time-scales, which was an important advancement towards full carbon

balance estimates (Wofsy et al. 1993; Black et al. 1996, Goulden et al., 1996; Greco and

Baldocchi, 1996; Greco and Baldocchi, 1996; Lindroth, 1998). In 1996, a group of

scientists expressed the need for regional networks and long term time series of flux

measurements to assess spatial representativeness of the long term and tower-based flux

measurements, to determine spatial variability

of CO2 fluxes and to parameterize

ecophysiological models (Baldocchi et al.,

1996). Several regional networks were initiated

(e.g. Euroflux (later: CarboEurope),

Ameriflux, Asiaflux, Ozflux and Fluxnet-

Canada) and Fluxnet was established as

umbrella organization. Currently, the Fluxnet

database contains over 400 eddy covariance

sites spread over the globe operated on a long

term and continuous basis at many different

types of ecosystems (Baldocchi, 2008).

Long term operation of eddy covariance

sensors presents a number of challenges,

including appropriate maintenance and

calibration of sensors and data-acquisition

equipment. Since the establishment of the

Fluxnet network, two important assessments

have been made to standardize eddy

covariance measurement techniques and data

processing. Aubinet et al. (2000) developed the

Euroflux methodology which described the

technical details of the eddy covariance system

Figure 2.11: Eddy covariance system

consisting of an ultrasonic anemometer and

infrared gas analyser (IRGA).

Peat areas, global warming, management and greenhouse gases

31

for CO2, H2O and energy fluxes. Additionally, computation and correction of acquired

flux data, quality control measures, spatial representativeness of measured fluxes, gap

filling methods, correction of nighttime data and error estimation were assessed. The

method of Aubinet has been applied and refined in over 400 research publications. More

recently, Lee et al. (2004) published the ‘Handbook of meteorology’, which contains

mainly eddy covariance issues. The focus here lies on specific topics concerned with

possible sources of errors, like coordinate systems, averaging, detrending and filtering of

eddy covariance time-series and uncertainties from spectral attenuation and low frequency

atmospheric transport. Also, errors due to advection effects in hilly or mountainous areas

and characteristics of canopy turbulence and the effect on flux measurements were

described.

Since a decade, numerous synthesis papers have been published covering a broad

representation of vegetation types, climates and disturbance stages (e.g. Law et al., 2002;

Wilson et al., 2003; Ciais et al., 2005; Reichstein et al., 2007; Luyssaert et al., 2008;

Baldocchi et al., 2008). Also, the assessment of methodological aspects like gap filling

techniques, energy balance closure and comparison of measurement techniques could be

improved due to the benefit of the extensive databases (e.g. Falge et al., 2001; Gioli et al.,

2004; Wilson et al., 2002). Various sites have now acquired data records of more than 10

years, which is favourable for studying inter-annual variability of CO2 fluxes like net

ecosystem exchange, respiration and gross primary production as well as the influence of

climate, antecedent conditions (drought, freezes, extreme weather events) and the length

of growing season on CO2 balances (Baldocchi et al., 2008).

2.5.3 The eddy covariance technique for CH4 fluxes

Using the eddy covariance technique for CH4 flux measurements also commenced in the

1980’s. However, the low abundance of CH4 in the atmosphere hampers adequate

concentration measurements and the eddy covariance technique therefore has not often

been applied for observation of CH4 emissions. Infrared absorption spectrometry has been

widely used for measurements of trace gases in the laboratory and also equipment has

been made to perform field measurements (Fan et al., 1992; Zahniser et al. 1995; Fowler

et al., 1995; Friborg et al., 1997; Rinne et al, 2007; Lohila et al. 2007; Kroon et al., 2007;

Sachs et al., 2008). Most techniques however experience problems of drift difficult to

control under field conditions. Also, low sensitivity effects occur and there are several

practical drawbacks (e.g. high costs, large and labour intensive field set-ups, no

unattended field deployment possible). To obtain reliable and continuous ecosystem scale

estimates of CH4 fluxes, improvements of the eddy covariance technique for CH4 are

needed.

In this research a new technique using a fast methane analyser is investigated for its

applicability in closed path eddy covariance set-up. At the start of the research it was

hypothesized that obtaining continuous data of CH4 fluxes would significantly improve

the understanding variability of these fluxes as well as the underlying landscape scale.

Also, the development of an eddy covariance technique was expected to improve the GHG

balance of the area. A thorough quality check of the eddy covariance technique is

Chapter 2

32

performed and the new eddy covariance technique for CH4 is subjected to comparison

with the chamber method. In turn, the chamber method is compared with the soil gradient

method.

2.6 Previous research on greenhouse gas fluxes and balances

2.6.1 Assessments of single greenhouse gas fluxes

Various researches have been published concerning the fluxes of CO2, CH4 and N2O in

peat areas in the Netherlands and other temperate regions for both natural and managed

peatlands. In a natural temperate fen in southern Germany CO2 fluxes of -5.4 ± 3.3 g C m-2

d-1

(uptake) were observed during a summer period (Kormann et al., 2001). Net uptake

over the growing season of a natural peatland was also observed by Cagampan et al.

(2008). In the wet areas of the peatland, net uptake was -0.20 g C m-2

d-1

, while in the

relatively dry areas, net uptake was -0.25 g C m-2

d-1

. Hensen et al. (1995) measured CO2

fluxes over agriculturally managed peat soils overlain with clay using aerodynamic flux

techniques and eddy covariance, and found a net CO2 emission of 13.6 – 327.3 g C m-2

yr-

1. Aerts and Toet (1997) observed CO2 emissions of 0.37 – 0.74 g C d

-1 per kg soil

from

peat soil cores with vascular plants and varying fertilization treatments. Lohila et al.

(2004) found an annual net ecosystem exchange of CO2 (NEE) of a Finnish peat grassland

in agricultural use to be 79 ± 25 g C m−2

yr-1

(emission). During the growing season, the

area was a sink of CO2, while during the rest of the year it was a source. Veenendaal et al.

(2007) analyzed annual CO2 fluxes in two agricultural managed peat meadows. The NEE

for a peat meadow under reduced management was found to be −8.4 g C m−2

yr−1

(uptake),

while for a peat meadow under intensive management the NEE was 122.4 g C m−2

yr−1

(emission). In 2005, the average net ecosystem exchange of CO2 (NEE) of European peat

areas was estimated by Janssens et al. (2003) and ranged from -33 g C m-2

yr-1

(uptake) for

undisturbed peatlands to 188 g C m-2

yr-1

(emission) for drained peatlands.

Estimates of annual CH4 emissions from managed and natural peat meadow areas in the

Netherlands were made by Van den Born et al. (1991). The estimates were based on

existing data from peat areas in other countries similar to those in the Netherlands and

application of groundwater classes. With an average of 18 - 46 g C m-2

yr-1

the total

emission of peat areas in the western part of the Netherlands was estimated at 3 – 9% of

the total annual CH4 emission of the Netherlands. CH4 emissions from temperate fens

were reported by Verma et al. (1992) and Kormann et al. (2001). Verma et al. (1992)

observed CH4 emissions of 90 - 203 mg C m-2

d-1

from a natural fen in Minnesota during a

summer period. CH4 emissions from a natural temperate fen reported by Kormann et al.

(2001) were 97 ± 32 mg C m-2

d-1

during a summer period. Considering agriculturally

managed peat areas, Aerts and Toet (1997) observed CH4 emissions of 2.0 – 18.8 mg C d-1

per kg soil from peat cores with vascular plants and varying fertilization treatments. Kroon

et al. (2007) observed significantly higher CH4 emissions with high variability at a dairy

farm on peat meadow in the Netherlands of 42 ± 32 mg C m-2

d-1

. Abandoned peat areas

were repeatedly investigated for CH4 fluxes by Van den Pol-van Dasselaar (1995, 1998a,

1998b and 1999). Oenema Van den Pol-van Dasselaar and Oenema (1995) applied the

flux chamber technique and found large spatial differences in CH4 fluxes (from small

Peat areas, global warming, management and greenhouse gases

33

uptake to emissions of ± 170 mg C m-2

d-1

) for Dutch peat meadows, suggesting strong

influences of soil water table and temperature. During further research, Van den Pol-van

Dasselaar et al. (1998a, 1998b and 1999) observed and analyzed CH4 emissions from

grasslands on wet peat soils in more detail and came to average emissions of 5.9 - 15.3 g

C m-2

yr-1

.

Annual N2O emissions reported by Velthof et al. (1996) showed a strong difference

between unfertilized and fertilized soils. Unfertilized soils had emissions of 0.05 – 1.29 g

N m-2

yr-1

and fertilized soils had emissions of 0.73 – 4.2 g N m-2

yr-1

respectively. Flessa

et al. (1998) observed emissions in a range of 0.42 – 5.64 g N m-2

yr-1

with higher

emissions from managed peatland than from peat meadows. Kroon et al., (2007) observed

N2O emissions at a dairy farm on peat meadow in the Netherlands of 1.7 ± 2.7 mg N m-2

d-1

. From these emissions about 40% of the total N2O emission was due to a fertilizing

event. In general, high N2O fluxes occur where the land receives high doses of nitrogen,

where soils are moist, rich in humus and experience freeze–thaw cycles (Freibauer, 2003).

During this research all three gases were measured simultaneously over multiple years

with different measurement techniques in an abandoned peat meadow. In the hypotheses it

was expected that NEE and N2O emissions would decrease compared to areas with

agricultural management and drainage, while CH4 emissions were expected to be higher.

Also, more insight in the temporal and spatial variability was anticipated as a result of this

research.

2.6.2 Carbon fluxes through water

A first assessment of losses of dissolved organic carbon through water was made by Hope

et al. (1994). Besides topography, the amount and distribution of organic-rich soils in the

catchments appeared very important. Reported losses of dissolved organic carbon ranged

from 0.18 g C m-2

yr-1

to 14.2 g C m-2

yr-1

and dissolved organic losses from

moorland/grassland ranged from 0.96 g C m-2

yr-1

to 8.98 g C m-2

yr-1

. The total net

carbon loss in drainage water from a temperate peat area in Great Britain was observed by

Billett et al. (2004) and amounted to 30.4 ± 6.2 g C m-2

yr-1

. This was slightly higher than

the net annual carbon uptake from atmosphere (-27.8 ± 2.5 g C m-2

yr-1

). In an upland peat

catchment, a seven year record of dissolved organic and inorganic carbon showed

variations between 9.6 and 25.6 g C m-2

yr-1

. This was equivalent to 20% and 36% of the

soil respiration in the area (Worrall et al., 2005). An assessment of New Zealand peatlands

showed that a significant part of the overall carbon budget of peatlands (10 to 50 g C m-2

yr-1

) was exported as dissolved organic carbon (Moore and Clarkson, 2007). Although

several researches of carbon loss through water in highland peat areas have been

published, investigations in lowland peat meadows are less abundant. Also, measurements

of losses of dissolved CH4 are scarce. This research was expected to provide a first insight

in these fluxes through the water in peat meadows.

2.6.3 Full carbon balances and full greenhouse gas balances

Although most investigations were made of single GHG fluxes, attempts were made to

compile and investigate full carbon balances and full GHG balances. Several researches

Chapter 2

34

were published for northern peat areas. Alm et al. (1999) published the carbon balance of

a boreal bog during a year with an exceptionally dry summer. The results showed how

delicately the carbon balance of peat areas and their micro sites depend on climatic

variations. It also showed that summer droughts can lead to severe carbon losses from peat

areas. Whiting and Chanton (2001) reported annual measurements of the relationship

between CH4 emission and net carbon fixation in three wetland ecosystems. Although the

wetlands under investigation functioned as a sink for CO2, due to the release of CH4 with

its relatively high GWP of CH4 (~25, over 100 years) the area still contributed to the

enhanced greenhouse effect. Roulet et al. (2007) reported a 6-year carbon balance of net

ecosystem CO2 exchange (NEE), CH4 emissions and export of dissolved organic C (DOC)

from a northern ombrotrophic bog. The 6-year mean balance was calculated as -21.5 ±

39.0 g C m-2

yr-1

(uptake). Friborg et al. (2003) assessed CO2, CH4 and N2O emissions in a

Siberian wetland for a summer in 1999 and found that CH4 had a stronger effect than CO2

on the GHG budget in terms of radiative forcing on the atmosphere. They concluded that

Siberian wetlands can be important sources of radiative forcing, even in comparison to

anthropogenic emissions.

Additionally, some investigations were made for temperate peat areas in the Netherlands.

Langeveld et al. (1997) estimated GHG emissions from drained peat soils including not

only emissions from the soil-plant continuum of the system, but also CO2 emissions from

cattle and their excreta, and emissions of CH4 and N2O from excreta in grazed pastures.

With an average NEE of 300 g C m-2

yr-1

, CH4 emissions of 22.5 – 7.5 mg C m-2

yr-1

and

N2O emissions between 0.45 – 1.9 g N m-2

yr-1

, the overall GHG emission from Dutch

peat areas was estimated at 244×109 kg CO2-equivalents yr

-1. Van den Bos (2003)

estimated that carbon emissions (both CO2 and CH4) from peat meadows in the western

part of the Netherlands contributed 1 – 3 % to total Dutch carbon emissions. Drösler et al.

(2008) assembled GHG flux data from different types of peat areas over West and North

Europe and estimated full GHG balances for a range of peatland types. GHG balances

included CO2, CH4 and N2O fluxes and varied between uptake of approximately -10 g C-

equivalents m-2

yr-1

for a natural forest bog and emissions of approximately 570 g C-

equivalents m-2

yr-1

for an arable fen.

Compared to CO2, the GHG’s CH4 and N2O have relatively short atmospheric lifetimes,

and consequently the GWP of these GHG’s decreases over time. CH4 has an atmospheric

lifetimes of 12 ± 3 years and a GWP of 72 over 20 years, 25 over 100 years and 7.6 over

500 years. The decrease of CH4 is due to oxidation by OH in the troposphere and loss to

the stratosphere. N2O has an atmospheric lifetime of 114 years and a GWP of 289 over 20

years, 298 over 100 years and 153 over 500 years. The cause of the decrease of

atmospheric N2O is not yet well understood (Forster et al., 2009). Normally, like in the

researches described above, a 100-year time horizon is considered when the effect of

GHG’s on the greenhouse effect is estimated. However, when a 500-year time horizon

would be considered the GWP’s for CH4 and N2O are much lower and the reported effect

of GHG emissions thus depends strongly on the timescale that is used. In case a large part

of the GHG balance consists of CH4 and N2O fluxes, ecosystems that are a net GHG

source and thus increase global warming on a 100-year timescale, can be neutral or GHG

sinks on a 500-year timescale thereby attenuating global warming on long timescales.

Peat areas, global warming, management and greenhouse gases

35

To obtain a full overview of the GHG balance of peat areas all sources and sinks of

GHG’s in peat areas (CO2, CH4, and N2O) should be measured year round. A true

assessment of the sink-source relations of peatland ecosystems requires not only vertical

losses and gains through atmosphere, but also vertical and lateral losses of dissolved gases

through water. Additionally, the different GWP’s of the GHG’s should be taken into

account. Such investigations are scarce, although indispensable for quantifying the current

role of peatlands in the in the carbon cycle and their impact on the greenhouse effect.

Therefore, in this research it was attempted to compile such full GHG balance. Generally,

a reduction of the net GHG emission compared to the managed situation was foreseen.

However, since CH4 emissions the expected to increase, the reduction of the net GHG

balance was expected to be partly cancelled out by the anticipated increase of CH4

emissions.

2.6.4 Variability of methane fluxes

Differences in CH4 emissions from varying types of peatland and wetland areas have been

observed by many researchers (e.g. Moore and Knowles, 1990; Grünfeld and Brix, 1999;

Van den Pol-van Dasselaar et al., 1999; Christensen et al., 2003), while observations of

high spatial variability within a research area are less frequent (Waddington and Roulet,

1996; Hirota et al., 2004; Van Huissteden et al., 2005). In previous research, spatial

variability of CH4 fluxes was attributed most often to differences in water table (e.g.

Moore and Knowles, 1990; Waddington and Roulet, 1996; Van den Pol-van Dasselaar et

al., 1999; Van Huissteden et al., 2005), nutrient availability and net carbon uptake

(Whiting and Chanton, 1993; Christensen et al., 2003; Van Huissteden et al., 2005) and/or

differences in soil temperature (Beckmann and Lloyd, 2001; Christensen et al., 2003).

Furthermore, vegetation differences were found to be an important driver of spatial

variability (Sheppard and Lloyd, 2002; Van Huissteden et al., 2005; Ding et al., 2005).

Considering temporal variability, the temperature dependency of CH4 fluxes has been

established by a wealth of studies (e.g. Zimov et al., 1997; Bubier et al., 2005; Treat et al.,

2007; Rinne et al., 2007). However, longer term changes of CH4 fluxes have been shown

to be related to persistent water table changes with inherent vegetation transitions

(Huttunen et al., 2003; Hirota et al., 2004; Treat et al., 2007; Pelletier et al., 2007).

Considering shorter time scales, diurnal cycles were found in various studies (Schutz et

al., 1989; Knapp and Yavitt, 1992; Whiting and Chanton, 1993; Friborg et al., 1997),

while at other measurement locations no diurnal variations were observed at all (e.g.

Rinne et al., 2007).

So far, most analyses of variability of CH4 fluxes have been performed for natural peat

areas, while the variability of CH4 fluxes in managed and abandoned peat meadows is

relatively unknown. Obtaining more insight on this subject was an important goal of this

research and it was expected that temperature, water level and vegetationcharacteristics

played an important role. In addition, the processes underlying this variability at various

scales were to be investigated by assessing the ecosystem in an integrative manner.

Chapter 2

36

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