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4.3

Methane Emissions from Rice Cultivation:
Flooded Rice Fields
4.3.1 Overview
Anaerobic decomposition of organic material in flooded rice fields produces methane(CH4), which escapes to the atmosphere primarily by diffusive transport through the rice
plants during the growing season. Upland rice fields, which are not flooded and therefore
do not produce significant quantities of CH4, account for approximately 10 per cent of
the global rice production and about 15 per cent of the global rice area under cultivation.
The remaining area is grown for wetland rice, consisting of irrigated, rainfed, anddeepwater rice. The global wetland rice area harvested annually in the early 1980s was
about 123.2 million hectares (total harvested area including upland rice is 144 Mha), over
90 per cent of which was in Asia (Neue et al., 1990).14
Of the wide variety of sources of atmospheric CH4, rice paddy fields are considered oneof the most important. The Intergovernmental Panel on Climate Change (IPCC, 1996)
estimated the global emission rate from paddy fields at 60 Tg/yr, with a range of 20 to
100 Tg/yr. This is about 5-20 per cent of the total emission from all anthropogenic
sources. This figure is mainly based on field measurements of CH4 fluxes from paddy
fields in the United States, Spain, Italy, China, India, Australia, Japan and Thailand.
The measurements at various locations of the world show that there are large temporalvariations of CH4 fluxes and that the flux differs markedly with soil type and texture,application of organic matter and mineral fertiliser (Neue and Sass, 1994). The wide
variations in CH4 fluxes also indicate that the flux is critically dependent upon several
factors including climate, characteristics of soils and paddy, and agricultural practices,
particularly water regime. The parameters that affect methane emissions vary widely
both spatially and temporally. Multiple year data sets near the same location and undersimilar conditions can lead to substantial differences in seasonal methane emission levels,
making it difficult to establish a single number as the methane emission level from a field,
let alone at a regional or country level. Thus, at the current level of understanding, areported range in methane emission levels for a country is more realistic than a single
number.
Methane production processes
The major pathways of CH4 production in flooded soils are the reduction of CO2 with
H2, with fatty acids or alcohols as hydrogen donor, and the transmethylation of acetic acidor methanol by methane-producing bacteria (Takai, 1970; Conrad 1989). In paddy fields,
the kinetics of the reduction processes are strongly affected by the composition andtexture of soil and its content of inorganic electron acceptors. The period between
flooding of the soil and the onset of methanogenesis can apparently be different for thevarious soils. However, it is unclear if soil type also affects the rates of methanogenesis
and CH4 emission when steady state conditions have been reached (Conrad, 1989).
14 The term "harvested area" has a different meaning from "cultivated area" in that theformer accounts for double and triple cropping. For example, if a country has 10 million
hectares of land under rice cultivation, all of which are double-cropped (i.e., two crops ofrice are grown on each hectare each year), then this country has 20 million hectares ofrice area harvested annually.

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The redox15 potential is one important factor for production of CH4 in soils. The Eh, orelectron activity, of the soil gradually decreases after flooding.
Patrick (1981)
demonstrated that the redox potential of a soil must be below approximately -150 mV inorder to have CH4 production. Yamane and Sato (1964) also showed that the evolutionof CH4 from flooded paddy soils did not commence until the Eh fell below -150 mV.
Carbon substrate and nutrient availability are also important factors. Application of ricestraw to paddy fields significantly increases the CH4 emission rate compared withapplication of compost prepared with rice straw or chemical fertiliser.
Soil temperature is known to be an important factor in affecting the activity of soil microorganisms. This is to a certain extent related to the soil moisture content because boththe heat capacity and the heat conductivity are lower for a dry soil than for a wet soil.
Yamane and Sato (1961) have already found that CH4 formation reached a maximum at
35oC in waterlogged alluvial soils. The rate of methane formation was very small below
20oC.
Because the conversion rate of substrate to CH4 depends on the temperature, it isgenerally observed that the momentary local emission of CH4 from the soil to theatmosphere depends on the temperature. However, the dependence of the seasonallyintegrated emissions of CH4 on temperature is much weaker. That emission depends
primarily on the total input of organic substrate: although the temperature determines
the time it takes to convert the substrate to CH4, that time is generally short compared
to a season. Thus the methodology proposed here will be based on the seasonallyintegrated CH4 emission, whose temperature dependence can be neglected in first
approximation.
It is generally recognised that CH4 formation is only efficient in a narrow pH range
around neutrality (pH from 6.4 to 7.8). The effect of flooding is to increase the pH inacid soil, while it decreases the pH in alkaline soil. The increase of pH in acid soils is
mainly due to the reduction of acidic Fe3+ to Fe2+ which simultaneously reduces the Eh.
The addition of nitrate as chemical fertiliser to flooded soils may suppress the productionof CH4, because nitrate acts, as well as Fe3+, Mn4+, as a terminal electron acceptor in theabsence of molecular oxygen during anaerobic respiration, and poises the redox potentialof soils at values such that the activity of strict anaerobes is prevented. The addition ofsulphate may also inhibit methane production for similar reasons as nitrate.
There are three processes of CH4 release into the atmosphere from rice fields. Diffusion
loss of CH4 across the water surface is the least important process. Methane loss as
bubbles (ebullition) from paddy soils is a common and significant mechanism, especially if
the soil texture is not clayey. During land preparation and initial growth of rice, ebullitionis the major release mechanism. The third process is CH4 transport through rice plants,
which has been reported as the most important phenomenon (Seiler et al., 1984; Schütz
et al., 1989b).
Many researchers reported that more than 90 per cent of total CH4 emitted during the
cropping season is released by diffusive transport through the aerenchyma system of therice plants and not by diffusion or ebullition. Emission through rice plant, may be
expected to show great seasonal variations as a function of changes in soil conditions andvariations in plant growth.

15

Redox (Eh) refers to oxidation-reduction, two processes that take place
simultaneously. Oxidation is the loss of an electron by an atom, and reduction is the gainof an electron by an atom.

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Methane emission rates are also a function of the partial pressure of CH4 in the soil. Partof the CH4 produced in the soil is consumed in the oxidised rhizosphere of rice roots orin the oxidised soil-floodwater interface. It is known that soil methanotrophic bacteria
can grow with CH4 as their sole energy source, and other soil bacteria, such as
Nitrosomonas species are also able to consume CH4 (Conrad, 1993). Methane is alsoleached to ground water, as a small part dissolves in water. Therefore a reduction in soil
methane does not necessarily mean that all this CH4 has been emitted into theatmosphere.
Global emissions from rice fields
The total harvested area of rice has increased from 86 Mha in 1935 to 144 Mha in 1985,
which means an annual average increase of 1.05 per cent. The average annual increase
was 1.23 per cent between 1959 and 1985. However, in the last few years, the rate of
expansion of the total rice acreage has decreased (Minami, 1994).
Table 4-9 provides a summary of measured emissions at a number of specific researchsites around the world. It should be noted that methane fluxes from paddy rice fields
vary substantially from day to day, and during a day (e.g., day and night). The data
presented here are based on frequent measurements which capture the diurnal
variations, and variations over the growing season. Based on area and production
statistics, with average emission values, a number of researchers have estimated global
emissions from rice.

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TABLE 4-9
REPRESENTATIVE METHANE EMISSIONS FROM RICE PADDY FIELDS IN VARIOUS LOCATIONS OF THE WORLDCountry

Location

Season total

Experimental
Treatment

Reference

g/m2

Australia

Griffith

2.8

10

-

NGGIC, 1996

China

Beijing

14.6 - 48.9

27 - 91

OM, WM

Chen et al., 1993

Beijing

9.4 - 26.8

12 - 39

MF, OM, WM

Beijing

1.9 - 48.9

5.3 - 100.9

MF, OM, SO, WM

Hangzhou, Zhejiang

6.9 - 50.6

14 - 82

MF, OM, SE

Wassmann et al., 1993a

Nanjing, Jiangsu

2.6 - 14.3

6 - 34

MF, OM, WM

Chen et al., 1993

Taoyuan, Hunan

6.5 - 56.2

12 - 115

MF, OM, SE

Wassmann et al., 1993b

Tuzhu, Sichuan

58.0

167

Wuxian, Jiangsu

3.2 - 6.2

10 - 19

0.2

0.5

NAV

Mitra, 1992

Barrackpore, West
Benegal0.7, 20.2

1.8, 6.3

NAV

Mitra, 1992

Cuttack, Orissa

2.7-7.2

7-19

CU

Mitra, 1992

Faizabad, Uttar Pradesh

0.8

2

NAV

Mitra, 1992

Garagacha, West
Benegal

11

29

NAV

Mitra, 1992

Jorhat, Assam

18.1

46

NAV

Mitra, 1992

Kalyani, West Bengal

4.1

10.8

NAV

Mitra, 1992

Koirapur, West Bengal

6.1

19

NAV

Mitra, 1992

Madras, Tamil Nadu

5.8

11

NAV

Mitra, 1992

0.02-0.21

0.06-0.58

MF

Mitra, 1992

Purulia, West Bengal

4.2

11

NAV

Mitra, 1992

Trivandrum, Kerala

5.1

9

NAV

Mitra, 1992

Indonesia Taman Bogo, Lampung

18.0 - 27.1

31 - 47

MF, OM

Nugroho et al., 1994a

Taman Bogo, Lampung

17.9 - 31.7

30 - 50

MF, OM

Nugroho et al., 1994b

Sukamandi, West Java

8.7 - 20.2

19 - 44

WM, CU

Husin et al., 1995

5 - 2818 - 75

MF, OM

Schütz et al., 1989a

India

Allahabad, Uttar Pradesh

New Delhi

Italy

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Range of CH4
flux
mg/m2/hrVercelli

Yao and Chen, 1994a,
1994b
Shao, 1993

Khalil et al., 1991
CU, MF, OM, SE, WM Cai et al., 1994

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TABLE 4-9 (CONT.)
REPRESENTATIVE METHANE EMISSIONS FROM RICE PADDY FIELDS IN VARIOUS LOCATIONS OF THE WORLDCountry

Range of CH4
flux
mg/m2/hr

Season total

16.3

45

Mito

1.2 - 4.1

4 - 13

MF, OM

Yagi and Minami, 1990a;
Minami, 1994

Ryugasaki

2.8 - 15.4

11 - 28

MF, OM

Yagi and Minami, 1990a;
Minami, 1994,

Ryugasaki

1.9 - 7.9

7 - 12

WM

Yagi and Minami, 1990a;
Minami, 1994

7.0

26

Tsukuba

0.2 - 0.4

<1.1

OM

Korea

Suwon

0.66 - 4.55

9 - 60OM, WM

Shin et al., 1995

Philippines

Los Banos

0.8 - 18.5

2 - 42

MF, OM

Neue et al., 1994

Los Banos

3.3 - 7.9

7 - 19

SE

4

12

Japan

Location

KawachiTaya

Experimental
Treatment

Reference

g/m2
Yagi and Minami, 1990a;
Minami, 1994

Yagi and Minami, 1990a;
Minami, 1994
Yagi and Minami, 1990a;
Minami, 1994

Wassmann et al., 1994

Spain

SavillaThailandAyutthaya

3.3 - 7.9

13 - 20

CU, OM, WM

Siriratpiraya, 1990

Bang Khen

4.3 - 21.7

16 - 55

SE

Minami, 1994;
Yagi et al., 1994b

Chai Nat

1.6

4

Chiang Mai

3.7 - 5.5

9 - 13

MF, OM

Jermsawatdipong et al.,
1994

Chiang Mai

9.0 - 9.5

20 - 21CU

Siriratpiriya et al 1995

Khlong Luang

3.8

8

Minami, 1994
Yagi et al., 1994b

Khon Kaen

23.0

76

Minami, 1994; Yagi et al.,
1994b

Seiler et al., 1984

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Yagi et al., 1994b

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TABLE 4-9 (CONT.)
REPRESENTATIVE METHANE EMISSIONS FROM RICE PADDY FIELDS IN VARIOUS LOCATIONS OF THE WORLDCountry

Thailand(cont.)

USA

Location

Range of CH4
flux
mg/m2/hr

Season total

Experimental
Treatment

Reference

Nakompathom

9.4-12.0

25-32

SE

Pathumthani

1.9 - 4.6

5 - 11

MF, OM

Phitsanulok

6.6 - 7.2

17 - 18

SE

Katoh et al, 1995

Phrae

16.6 - 22.2

51 - 69

SE

Minami, 1994; Yagi et al., 1994b

Ratchaburi

3.2 - 42.5

9 - 117

MF, OM

Jermsawatdipong et al., 1994

San Pa Tong

10.4 - 16.1

25 - 40

SE

Minami, 1994; Yagi et al., 1994b

Surin

15.0 - 24.5

41 - 66

MF, OM

Jermsawatdipong et al., 1994

Surin

13.3

41

Suphan Buri

19.5 - 32.2

51 - 75

SE

Minami, 1994; Yagi et al., 1994b

Beaumont, Texas

2.5 - 23.5

5 - 36

OM, SO

Sass et al., 1990, 1991a, 1991b

Beaumont, Texas

0.6 - 6.3

1 -15

WM

Sass et al., 1992

Crowley, Louisiana

10.2 - 17.9

21 - 37

MF

Lindau et al., 1991

Crowley, Louisiana

12.6 - 85.0

22 - 149

MF, OM, SE

Crowley, Louisiana

27 - 99

60 - 220

MF

Davis, California

3.4 - 10.4

18Knights Landing,California

0.5 - 18.8

1 - 58g/m2
Tomprayoon et al., 1991
Jermsawatdipong et al., 1994

Jermsawatdipong et al., 1994

Lindau and Bollich, 1993
Lindau, 1994
Cicerone et al., 1983, 1992

MF, OM

Cicerone et al., 1992

Experimental treatment: CU - cultivars, MF - fertilisers, OM - organic matters, SE - seasons (early and late rices, or dry and rainy seasons), SO- soil types, WM - water management.
NAV = not available
Source: Modified from K Minami (1995)

Global emissions of CH4 from rice paddies reported by several researchers are
summarised in Table 4-10. Extrapolation of emission rates to a global scale is very
difficult, because the effects of variations in agricultural practices, number of crops per
year, soil types and other factors discussed above are uncertain.
The IPCC (IPCC, 1996) presented a candidate list of CH4 sources to the atmosphere as
annual release rates. The total annual source is constrained by the observed rate of
atmospheric increase of concentrations and by the estimated atmospheric lifetime to be
535 Tg CH4/yr. Rice paddies are listed as a source of 60 ± 40 Tg CH4/yr.

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TABLE 4-10
REPRESENTATIVE GLOBAL ANNUAL METHANE EMISSIONS*FROM RICE FIELDS AS ESTIMATED BY DIFFERENT AUTHORS

Reference

Estimate (Tg CH4/yr)

Koyama (1964)

190

Ehhalt and Schmidt (1978)

280

Cicerone and Shetter (1981)

59

Khalil and Rasmussen (1983)

95

Seiler et al (1984)

35-59

Blake and Rowland (1988)

142-190

Crutzen (1985)

120-200

Holzapfel-Pschorn and Seiler (1986)

70-170

Cicerone and Oremland (1988)

60-170Schütz et al. (1989a)

50-150Aselman and Crutzen (1989)

60-140Schütz et al. (1990)

50-150Wang et al. (1990)

60-120

Neue et al. (1990)

25-60

Bouwman (1990)

53-114

Yagi and Minami (1990b)

22-73

IPCC (1990)

25-170Minami(1994)

12-113

Sass (1994)

25-54

Parashar et al (1994)

20

IPCC (1996)

20-100Source: Modified from K. Minami (1994)

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4.3.2 Methods For Estimating Emissions
Emissions of methane from rice fields can be represented as follows:

EQUATION 1
Fc = EF × A × 10-12

where:
Fc=

estimated annual emission of methane from a particular
rice water regime and for a given organic amendment, inTg per year;EF=methane emission factor integrated over integrated
cropping season, in g/m2;A=annual harvested area cultivated under conditions defined
above. It is given by the cultivated area times the numberof cropping seasons per year, i.e., in m2/yr.

The seasonally integrated emission factor is evaluated from direct field measurements ofmethane fluxes for a single crop.
In practice, it will be necessary to calculate the total annual emissions from a country as asum of the emissions over a number of conditions. Total rice production can be divided
into subcategories based on different biological, chemical and physical factors that control
methane emissions from rice fields. In large countries, this may include different
geographic regions. To account for the different conditions, F is defined as the sum of Fc(see Equation 1). This approach to emissions estimation can be represented as follows:
EQUATION 2
F = ∑i ∑j ∑k EFijk x 10-12
where:•

ijk: are categories under which methane emissions from rice fields may vary.

For instance, i may represent water levels in the rice fields such as fields inundated for theduration of the growing season (flooded regime) or fields under water onlyintermittently. This occurs either under managed irrigation when water is not readily
available or when rains do not maintain flooded conditions throughout the growing
season (intermittent regime) as given in Table 4-12. j, k, may represent water regimes
modified by other factors like organic inputs, soil textures, fertilisation regimes undereach of the conditions represented by the index i, and so on. As more factors are
identified, more categories need to be included. Inclusion of additional parameters should
lead to an improvement of the estimate of the total emissions. The summation should
include all cropping seasons.
The factors clearly identified by field experiments as being most important are (1) water
regime with inorganic fertilisers (except sulphate-containing inorganic fertilisers which
inhibit CH4 production); (2) organic fertiliser applications; (3) soil type, and soil texture;(4) cultivar; and (5) agricultural practices such as direct seeding or transplanting. Data

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show that in continuously flooded fields, some types of organic fertilisers and certain
cultivars lead to higher emissions compared to rice grown without organic amendments
or intermittent or managed irrigation in which the fields are not continuously inundated
and only where chemical fertilisers are used.
At present there are insufficient data to incorporate most of these factors. Nonetheless,the estimates can be improved substantially by incorporating the current knowledge onwater regimes, organic amendments and soil types etc. For some countries the effects oforganic fertiliser can be included.

4.3.3 Summary of Recommended Method
Basic Method
Data on rice cultivation under different water management techniques should be available
from most of the important rice-producing countries. Therefore, the basic method for
estimating emissions from each country includes estimates based on rice ecosystems(Kush,1984; Neue, 1989) relating to water regime (Table 4-12), namely:•

Upland: Fields are never flooded for a significant period of time.

•

Lowland: Fields are flooded for a significant period of time.
• Irrigated: Water regime is fully controlled.
• Continuously flooded: Fields have standing water throughout
the rice growing season and may only dry for harvest.
• Intermittently flooded : Fields have at least one aeration period of
more than 3 days during the cropping season.
• Single aeration: Fields have a single aeration during the
cropping season at any growth stage.
• Multiple aeration: Fields have more than one aeration
period during the cropping season.
• Rainfed: Water regime depends solely on precipitation.
• Flood prone: The water level may rise up to 50 cm during the
cropping season.
• Drought prone: Drought periods occur during every cropping
season.
• Deep water rice: Floodwater rises to more than 50 cm for a significant
period of time during the cropping season.
• Fields inundated with water depth from 50-100 cm.
• Fields inundated with water depth > 100 cm.

The discussion refers to a single inventory (or base) year, (e.g., 1990) but an average overthree years around the base year (e.g., 1989-1991) is recommended for the activity data,
if possible.

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For the inventory year, a number of input data are required.
•

Area of rice cultivation by water management regime in square metres (m2). As
discussed above, that area is multiplied by the number of crops per year. This
includes areas counted for each crop.

•

Seasonally integrated flux (EF) emission values for areas of different rice ecosystems(water regimes) without organic amendments.

•

of enhancement factors for organic amendments.

The result is methane emissions for each category. The total emissions for the country is
the sum of the individual results for each category.
Default data
In many cases, especially at the beginning of the process, there will be important ricegrowing areas for which specific fluxes will not be available. In such cases the regionaland country-specific default data provided in Tables 4-12 and 4-13 can be used to carryout first order estimates. These data may also be used by national experts forcomparison. Several ongoing activities to improve comparable measurement data havebeen identified. See Appendix for further information.
Area Statistics
Table 4-11 contains information on harvested area of rice according to statistics from the
FAO Yearbook (UN, 1992), China Agricultural Yearbook (1990), IRRI RICE Almanac(IRRI, 1994) and World Rice Statistics (IRRI, 1993). Allocation of areas to categories, e.g.,
irrigated, rainfed (flood prone and lowland rainfed) and upland rice for main riceproducing countries were based on the IRRI Rice Almanac (IRRI, 1994) and for otherrice-producing countries these categories were based on IRRI (1990), Huke (1982) and
Grist (1986). Actual percentage of the irrigated, rainfed, and flood prone areas which arecontinuously flooded or have an aeration period greater than 3 days or multiple
aerations, are to be obtained from the country specific data.
Seasonally Integrated flux values
Tables 4-12 and 4-13 provides default EF values for various categories of water regimes
and multiplication factors for organic amendments. Emissions from upland rice areassumed to be 0 and ignored in the emission calculations.
For continuously flooded rice, a “model” average seasonally integrated emissions for ricegrowing countries of the world was estimated from existing data (Table 4-13) to be
20 g/m2. These flux values are representative of flooded rice fields where organic
fertiliser is not used.
For intermittently flooded rice, a simple correction is applied. Fluxes are taken to be 50
per cent of the flooded (non-organic) value of 20 g/m2 for single aeration and 20 per centfor multiple aeration. For other water regimes new default values are given in Table 4-2.
For irrigated and continuously flooded, lowland rice ecosystems, the default seasonallyintegrated methane emission is 20 g/m2 (see Table 4-13) for soils ‘without organic
amendments’.
For conversion to methane emissions from soils ‘with organic
amendments’, a default correction factor of 2 (Range 2-5) is applied to the corresponding
rice ecosystems for the ‘without organic amendment’ category. This is because organic
amendments of flooded rice paddies increase methane emission to the atmosphere(Yagi and Minami, 1990a; Sass et al., 1991a, 1991b; Neue et al., 1994). A comprehensive

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review of methane flux measurements over the past decade from a variety of countries
and with different organic amendments and inorganic fertiliser treatments, is presented byMinami (1995). The amount of methane that is emitted as a result of organic soil
amendments depends greatly on the amount and condition of readily available
decomposable carbon contained in the treatment. Schütz et al (1989a) observed
increases from a control value of 28.6 g CH4 m2/yr to 68.4 g CH4 m2/yr with added ricestraw, (a factor of 2.4). Cicerone et al. (1992) observed increases from a control value of
1.4 g CH4 m2/yr to up to 58.2 g CH4 m2/yr with added straw, a factor of over 40 times
higher. In field studies in the Philippines, Denier van der Gon and Neue (1995) foundthat fields treated with green manure applied at a rate of 22 tonnes/ha emitted over twice
as much methane as fields in which the application rate was 11 tonnes/ha.
Methane emission rates are highly sensitive to water management. Periodic drainage of
irrigated rice paddies results in a significant decrease in methane emissions. Yagi andMinami (1990a) reported a decrease in methane emission rates as a result of a
mid-season drainage in Japanese rice fields. Sass et al. (1992) found that a single
midseason drain reduced seasonal emission rates by 50 per cent (from 9.27 g/m2 to
4.86 g/m2). In addition, multiple short periods of drainage (2-3 days) approximately every
three weeks during the growing season reduced methane emissions to an insignificant
amount (1.15 g/m2) without decreasing rice grain yield. Yagi et al. (1996) compared acontinuously flooded plot with constant irrigation with an intermittently drained plot withshort-term draining periods several times during the rice growing season. Total seasonal
methane emission rates during the cultivation period were 14.8 g/m2 and 8.6 g/m2 for1991 and 9.5 g/m2 and 5.2 g/m2 for 1993 in the continuously flooded and intermittently
drained plots, respectively. Scaling factors in Table 4-12 have been developed using thedata from the literature.
Default values in Tables 4-12 and 4-13 can be used for initial calculation where local
measurements are not adequate. However, national experts are encouraged to use
locally available data if available. If this is done it is important to ensure that thesecoefficients are based on a sufficient number of measurements to capture the variability
and produce a representative seasonal average value, which is needed for inventory
calculations (see Appendix).
Possible Refinements
National experts are encouraged to go beyond the basic method, and add as much detailas can be scientifically justified, based on laboratory and field experiments on various
amendments and theoretical calculations, to arrive at the estimate of emissions from ricecultivation in their country. These details should be incorporated into subcategories(indices j,k in Equation 2) under each of the main water management categories inEquation 2 so that they can be compared at that level with data from other countries.
For example:
Where emission data are available for different fertiliser types, this may beincorporated into the calculations. Each category, (e.g., continuously flooded) would
be further divided as follows:

F (continuously flooded) = F ( flooded chemical) + F (flooded/organic amendment)This procedure would then be repeated for as many separate subcategories as have been
defined. Each amendment may be incorporated in the same manner.

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In all cases, the emission inventory must be fully documented. The documentation has
two aspects. First, method of calculation must be specified as in Equation 2. Matrices ofamendments must be delineated. Second, all data and original sources must be
referenced, if not included explicitly as part of the inventory report. It is desirable in allcases to rely on published information, whether from the county’s government/scientificinstitutions an international organisation such as the UN-FAO, or the scientific literature.

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TABLE 4-11
DEFAULT ACTIVITY DATA - HARVESTED RICE
1990 Area(1000s ha)

Irrigateda(%)

Upland Rice(%)

Rainfedb
(%)

USA

1114

100

0

0

Belize

2

10

90

0

Costa Rica

53

10

90

0

Cuba

150

100

0

0

Dominican Rep

93

98

2

0

El Salvador

15

10

90

0

Guatemala

15

10

90

0

Haiti

52

40

60

0

Honduras

19

10

90

0

Jamaica

0

40

60

0

Mexico

123

41

59

0

Nicaragua

48

10

90

0

Panama

92

5

95

0

Puerto Rico

0

75

25

0

Trinidad & Tobago

5

45

55

0

Argentina

103

100

0

0

Bolivia

110

25

75

0

Brazil

3945

19

75

6 (0 + 6)

Chile

35

79

21

0

Columbia

435

67

23

10 (0 + 10)

Ecuador

266

40

10

50

Guyana

68

95

5

0

Paraguay

34

50

50

0

Peru

185

84

16

0

Surinam

58

100

0

0

Uruguay

108

100

0

0

Venezuela

119

90

10

0

Country or Region
Americas

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TABLE 4-11 (CONT.)DEFAULT ACTIVITY DATA - HARVESTED RICE
1990 Area(1000s ha)

Irrigateda(%)

Upland Rice(%)

Rainfedb(%)

Brunei

1

79

21

0

Hong Kong

0

100

0

0

Syria

0

100

0

0

Turkey

52

100

0

0

India

42321

53 (16 + 37)

15

32 (16 + 16)

Pakistan

2113

100

0

0

Bangladesh

10435

22

8

70 (23 + 47)

Myanmar

4760

18

6

76 (24 + 52)

Nepal

1445

23

3

74 (8 + 66)

Afghanistan

173

100

0

0

Bhutan25

50

4

46 (42 + 4)

China 3

33265

93

2

5 (0 + 5)

Indonesia10502

72 (22 + 50)

11

17 (10 + 7)

Iran

570

100

0

0

Iraq

78

100

0

0

Japan

2074

99 (2 + 97)

1

0

Malaysia

639

66

12

22 (1 + 21)

Philippines

3319

61

2

37 (2 + 35)

Sri Lanka

828

37

7

56 (3 + 53)

Taiwan

700

97

3

0

Thailand

9650

7

1

92 (7 + 85)

Kampuchea

1800

8

2

90 (42 + 48)

Laos

638

2

37

61 (0 + 61)

Vietnam

6028

53

8

39 (11 + 28)

Democratic Republic of
Korea

670

67

13

20

Republic of Korea

1242

100 (9 + 91)

00Country or Region
Asia

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TABLE 4-11 (CONT.)DEFAULT ACTIVITY DATA - HARVESTED RICE
1990 Area(1000s ha)

Irrigateda(%)

Upland Rice(%)

Rainfedb(%)

Albania

2

100

0

0

Bulgaria

11

100

0

0

France

20

100

0

0

Greece

15

100

0

0

Hungary

11

100

0

0

Italy

208

100

0

0

Portugal

33

100

0

0

Romania

37

100

0

0

Spain

81

100

0

0

Former USSR

624

100

0

0

Former Yugoslavia

8

100

0

0

Australia

102

100

0

0

Fiji

13

50

50

0

Algeria

1

100

0

0

Angola

18

100

0

0

Benin

7

10

90

0

Burkina Faso

19

89

11

0

Burundi

12

25

75

0

Cameroon

15

25

75

0

C African Rep

10

25

75

0

Chad

39

25

75

0

Comoros

13

100

0

0

Congo

4

25

75

0

Egypt

436

100

0

0

Gabon

0

25

75

0

Gambia

14

90

10

0

Ghana

85

24

76

0

Guinea Bissau

57

25

75

0

Guinea

608

8

47

45

Country or Region
EuropePacific

Africa

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TABLE 4-11 (CONT.)DEFAULT ACTIVITY DATA - HARVESTED RICE
1990 Area(1000s ha)

Irrigateda(%)

Upland Rice(%)

Rainfedb(%)

Ivory Coast

583

6

87

7

Kenya

15

25

75

0

Liberia

168

0

94

6

Madagascar

1160

10

14

76 (2 + 74)

Malawi

29

25

75

0

Mali

222

25

75

0

Mauritania

14

100

0

0

Morocco

6

100

0

0

Mozambique

109

25

75

0

Niger

29

35

65

0

Nigeria

1567

16

51

33 (33 + 0)

Rwanda

3

25

75

0

Senegal

73

25

75

0

Sierra Leone

339

1

67

32

Somalia

5

50

50

0

South Africa

1

100

0

0

Sudan

1

50

50

0

Swaziland

0

25

75

0

Tanzania

375

3

22

75 (0 + 75)

Togo

21

4

96

0

Uganda

37

25

75

0

Zaire

393

5

90

5

Zambia

11

25

75

0

Zimbabwe

0

25

75

0

Country or Region

a Numbers in brackets indicate continuously flooded and intermittently flooded respectively.
b Numbers in brackets indicate continuously flood-prone and drought-prone respectively.
c Values are currently being updated.

Sources: DeDatta (1975), Huke, (1982), Grist (1986), IRRI (1990), NGGIC (1996).
Notes: Areas were taken from FAO Yearbook (UN, 1992), China Agricultural Yearbook (1990), World Rice Statistics (IRRI, 1990)
and IRRI Rice Almanac 1993-1995 (IRRI, 1993).

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TABLE 4-12
SCALING FACTORS FOR METHANE EMISSIONS FOR RICE ECOSYSTEMS RELATIVE TO CONTINUOUSLY FLOODED FIELDS(WITHOUT ORGANIC AMENDMENTS)
Category
UplandLowland

Irrigated

Sub-Categorya

Scaling Factors (relative to emission
factors for continuously flooded fields)

None

0

Continuously flooded
Intermittently
floodedb

RainfedDeep water

1.0

Single aeration

0.5 (0.2-0.7)

Multipleaeration

0.2 (0.1-0.3)

Flood prone

0.8 (0.5-1.0)

Drought prone

0.4 (0-0.5)

Water depth 50-100 cm

0.8 (0.6-1.0)

Water depth > 100 cm

0.6 (0.5-0.8)

a Other rice ecosystem categories, like swamps and inland, saline or tidal wetlands may be discriminated within each sub-category according to local

emisson measurements.
b Defined as > 3 days aeration during the vegetative period.
Note: For irrigated and continuously flooded, lowland rice ecosystems, the default seasonally integrated methane emission is 20 g/m2 (see Table 4-13)
for soils ‘without organic amendments’. For conversion to methane emissions from soils ‘with organic amendments’, apply a default correction factor of
2 (Range 2-5) to the corresponding rice ecosystem for the ‘without organic amendment’ category.

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TABLE 4-13
SEASONALLY INTEGRATED METHANE EMISSION FACTORS FOR CONTINUOUSLY FLOODED RICE WITHOUT ORGANIC FERTILISERIN VARIOUS LOCATIONS OF THE WORLDCountry

Seasonally Integrated Emission
Factor, EFa(g/m2)

Literature/Remarks

Australia

22.5

NGGIC, 1996

China

13 (10-22)

Wassman et al., 1993aIndia

10 (5 - 15)

Mitra, 1996
Parashar et al., 1996

Indonesia

18 (5 - 44)

Nugroho et al., 1994a,b

Italy

36 (17-54)

Schütz et al., 1989a

Japan

15

Minami, 1995

Republic of Korea

15

Shin et al., 1995

Philippines(25 - 30)

Neue et al., 1994; Wassman et al., 1994

Thailand16 (4 - 40)

Towpryaoon et al., 1993

USA (Texas)

25 (15 - 35)

Sass and Fisher, 1995

Arithmetic Mean b

20 (12-28)-

a It is recognised that the emission factors presented in Table 4-13 will need to be periodically updated as better data become available. However, thisdataset represents the best available information at the time of compilation.
b The arithmetic mean of the seasonally integrated emission factor, EF, is derived from the values shown in Table 4-13. The range of emission factors

is defined as the standard deviation about the mean.

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Appendix
Intercomparability of Methane
Data from Rice Cultivation

Emission

Chamber measurements
Each laboratory should provide a standardised emission program of control flux
measurements to ensure the intercomparibilty and intercalibration of extended data sets.
An emission standardisation programme will consist of a specified experimental plan forseasonal and annual flux measurements along with specific accompanying data on locationand climate, soil, water management, plant characteristics, fertiliser treatment and adetailed cropping calendar.
•

Methane flux measurements should be recorded at least twice per week over anentire season. Experiments should be continued during fallow and/or alternate
cropping times as well as during the entire normal local rice growing season including
land preparation. In areas where double or triple cropping is practised, data should
be collected for all growing seasons.

•Since emissions are strongly influenced by daily temperature changes, the diel patternof emission (6-12 flux rates within a 24 hour period) should be determined at least
three times during the season.

•

A data log of all agricultural events should be kept., e.g., transplant date, panicle
initiation, heading, anthesis, harvest, etc. as well as fertilisation, water management
schedule, weeding schedule, herbicide and pesticide treatments.

•

At the time of each flux measurement, one should also collect the air temperature,
flood water temperature, and the soil temperature.

•

Fertilisation treatment in the standardisation (continuous irrigation) plots should beaccording to local practices, but limited to inorganic fertiliser. The application rate as
kg N ha-1 and number and timing of applications should be reported.

•

Fertilisation treatment in other experimental areas, including organic fertilisers,
should reflect local practices. Amounts, type, and timing of applications should bereported for each phase of the cropping sequence at all scales.

•

Standardisation chamber plots are to be kept flooded from shortly before
transplanting until maturity. During flood, the water should be kept at a 5 cm
minimum constant depth. A daily log should be kept of the amount of water added
and when.
Other water management regimes should be investigated when they are practised
locally. A daily log should be kept of times and durations of draining, the amounts ofwater added and other applicable data.

For further information, see ‘Global Measurements Standards of methane emissions for
irrigated rice cultivation’, IGAC (1994).

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4.4

Greenhouse Gas Emissions from
Agricultural Burning
4.4.1 Introduction
Where there is open burning associated with agricultural practices, a number ofgreenhouse gases (GHGs) are emitted from combustion. All burning of biomass
produces substantial CO2 emissions. However, in agricultural burning, the CO2 released
is not considered to be net emission. The biomass burned is generally replaced byregrowth over the subsequent year. An equivalent amount of carbon is removed fromthe atmosphere during this regrowth, to offset the total carbon released fromcombustion. Therefore the long term net emissions of CO2 are considered to be zero.
Agricultural burning releases other gases in addition to CO2 which are by-products ofincomplete combustion: methane, carbon monoxide, nitrous oxide, and oxides ofnitrogen, among others. These non-CO2 trace gas emissions from biomass burning are
net transfers from the biosphere to the atmosphere. It is important to estimate theseemissions in national inventories.16
There are two major types of agricultural burning addressed in this section – savanna
burning and field burning of crop residues. The approach is essentially the same as thatused for non-CO2 trace gases for all burning of unprocessed biomass, including traditional
biomass fuels and open burning of cleared forests. For all these activities, there is acommon approach in the proposed methodology, in that crude estimates of non-CO2
trace gas emissions can be based on ratios to the total carbon released. The carbon
trace gas releases (CH4 and CO) are treated as direct ratios to total carbon released.
Non-methane volatile organic compounds (NMVOCs) can be treated in a similar way.
However, no default values for NMVOC are provided in this version of the Guidelines.
To handle nitrogen trace gases, nitrogen to carbon ratios are used to derive total
nitrogen released and then emissions of N2O and NOx are estimated based on ratios ofthese gases to total nitrogen released. Tables 4-15 and 4-16 provide suggested default
values for non-CO2 trace gas emission ratios. These are presented with ranges, which16

For biomass combustion, CO2 emissions are frequently not considered net
emissions, and this is the case for agricultural burning. One could argue, in such cases,that this burning could be considered a short term sink of CO2. That is, a portion ofcarbon in biomass is being released as net emissions of CH4 and CO, while regrowth isremoving the full amount of the original carbon from the atmosphere in the next cycle.
Each year plants take up a certain amount of carbon from the atmosphere. When they
are burned some of that carbon is converted to CO, and CH4, so that an amount lessthan the total CO2 which was taken up by the plants is re-emitted as CO2. See Howden
et al. (1996), for a more detailed discussion of this proposal. Treating emissions of CO
and CH4 to the atmosphere, as a sink for atmospheric CO2, however, is inconsistent withthe proposed IPCC emissions methodology. In particular, the other carbon compounds
emitted are converted back into CO2 in the atmosphere over periods of days up to a
decade or so. Thus, over the time horizons of interest for CO2, (i.e. more than 100
years) there is no sink of CO2.

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emphasise their uncertainty. However, the basic calculation methodology requires thatusers select a best estimate value.17
The calculation of immediate trace gas emissions, based on the default emission ratios
provided in Tables 4-15 and 4-16, produces relatively crude estimates with substantial
uncertainties.18 Use of specific emission ratios which vary by type of burning, region, etc.
may allow for more precise calculations. The calculations described here ignore thecontemporary fluxes associated with past burning activities. These delayed releases are
known to exist, but are poorly understood at present. This and other possible
refinements are discussed at the end of this section.

4.4.2 P r e s c r i b e d B u r n i n g o f S a v a n n a s
Background
The term savanna refers to tropical and subtropical vegetation formations with apredominantly continuous grass cover, occasionally interrupted by trees and shrubs(Bouliere and Hadley 1970). These formations exist in Africa, Latin America, Asia, andAustralia. The growth of vegetation in savannas is controlled by alternating wet and dry
seasons: most of the growth occurs during the wet season; man-made and/or natural fires
are frequent and generally occur during the dry season. The global area of savannas is
uncertain, in part due to lack of data and in part due to differing ecosystem classifications.
Estimates of the areal extent of savannas range from 1300-1900 million hectares worldwide, about 60 per cent of which are humid savannas (annual rainfall of 700 mm or more)
and 40 per cent are arid savannas (annual rainfall of less than 700 mm) (Bolin et al., 1979;
Whittaker and Likens, 1975; Lanly, 1982; Lacey et al., 1982; and Hao et al., 1990). Largescale burning takes place primarily in the humid savannas because the arid savannas lacksufficient grass cover to sustain fire. Humid savannas are burned every one to four years
on average with the highest frequency in the humid savannas of Africa (as cited in Hao etal., 1990).

17 Emissions inventory developers are encouraged to provide estimates of uncertainty

along with these best estimate values where possible or to provide some expression of
the level of confidence associated with various point estimates provided in the inventory.
Procedures for reporting this uncertainty or confidence information are discussed inVolume 1: Reporting Instructions.
18 Emission ratios used in this section and presented in the tables are derived from

Crutzen and Andreae (1990), Delmas (1993), Delmas and Ahuja (1993) and Lacaux, et al.
(1993). They are based on measurements in a wide variety of fires, including forest andsavanna fires in the tropics and laboratory fires using grasses and agricultural wastes asfuel. In many cases these ratios are general averages for all biomass burning. Research willneed to be conducted in the future to determine if more specific emission ratios, e.g.,
specific to the type of biomass and burning conditions, can be obtained. Also, emission
ratios vary significantly between the flaming and smouldering phases of a fire. CO2, N2O,
and NOx are mainly emitted in the flaming stage, while CH4 and CO are mainly emitted
during the smouldering stage (Lobert et al., 1990). The relative importance of these twostages will vary between fires in different ecosystems and under different climaticconditions, and so the emission ratios will vary. As inventory methodologies are refined,
emission ratios should be chosen to represent as closely as possible the ecosystem typebeing burned, as well as the characteristics of the fire.

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Savannas are intentionally burned during the dry season primarily for agricultural
purposes such as ridding the grassland of weeds and pests, promoting nutrient cycling,and encouraging the growth of new grasses for animal grazing. Savanna burning may be
distinguished from other biomass burning activities like open forest clearing because there
is little net change in the ecosystem biomass in the savanna after the vegetation regrows
during the wet season. Consequently, while savanna burning results in instantaneousgross emissions of CO2, it is reasonable to assume that the net carbon dioxide released
to the atmosphere is essentially zero because the vegetation typically regrows between
burning cycles.19 Savanna burning does release several other important trace gases:
methane (CH4), carbon monoxide (CO), nitrous oxide (N2O), oxides of nitrogen (NOx,i.e., NO and NO2) and non-methane volatile organic compounds (NMVOCs).
Estimates of global emissions of these gases due to savanna burning have been based on
estimates of the annual instantaneous gross release of carbon from this activity and on
ratios of the other trace gases released from burning to the total carbon released byburning. Estimates of the annual instantaneous gross release of carbon from savanna
burning are highly uncertain because of lack of data on:•

the aboveground biomass density of different savannas;•

the savanna area burned annually;•

the fraction of aboveground biomass which actually burns; and•the fraction which oxidises.

The methodology that is proposed in the next section, although conceptually quite simple,
takes these factors into account. The approach allows for estimation of non-CO2 tracegases released by savanna burning, based on default data sets and on assumptions fromaverage literature values for various regions and types of savannas. It also allows formore accurate national estimates if data and assumptions can be developed to reflectnational average conditions accurately. Nonetheless, a wide variety of technical details
and open scientific issues remain important research topics.
Calculations
There are two basic components to the calculation. First, it is necessary to estimate thetotal amount of carbon released to the atmosphere from savanna burning. These are notconsidered to be net emissions, but are needed to derive non-CO2 trace gas emissions,which are net emissions. What is required is the annual area burned for the various
types of savannas, where type is based primarily upon above and below ground biomass,and perhaps climatological conditions and nutrient status. It is generally recommended
for all emissions from agriculture that three-year averages of activity data (e.g., hectares
burned) be used instead of a single year’s data where possible. This is especially
important for savanna burning which is highly variable from year to year. This variability
should also be taken into account by national experts in planning data collection
programmes to provide more accurate inputs to national inventory calculations. If data
are not directly available, estimates can be derived based on total savanna area20 and
19 If grazing pressure coupled with burning too often reduces biomass (i.e., degrades

the quality of savannas), then this needs to be considered as a carbon dioxide source. This
is not assumed in the basic calculations but could be included as a refinement if
considered important.
20 Most countries with significant savanna area should have national statistics on the

total area, but FAO publications (e.g. FAO, 1993) also provide country-specific estimates.

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