MODULE

4AGRICULTURE

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AGRICULTURE

4. A G R I C U L T U R E
4.1

Introduction
The Agriculture module looks at greenhouse gas emissions from fivesources:

4.2•

Domestic Livestock: Enteric Fermentation and Manure Management•

Rice Cultivation: Flooded Rice Fields•

Prescribed Burning of Savannas•

Field Burning of Agricultural Residues•

Agricultural Soils

Domestic Livestock
4.2.1 Introduction
This submodule deals with methane and nitrous oxide from two sources:• enteric fermentation• manure management
Methane from enteric fermentation is produced in herbivores as aby-product of the digestive process by which carbohydrates are broken
down by micro-organisms into simple molecules for absorption into theblood-stream. Both ruminant animals (e.g., cattle, sheep) and some nonruminant animals (e.g., pigs, horses) produce methane, although ruminants
are the largest source. The amount of CH4 that is released depends upon
the type, age and weight of the animal and the quantity and quality of thefeed consumed.
Methane from the management of animal manure occurs as the result of its
decomposition under anaerobic conditions. These conditions often occur
when a large number of animals are managed in a confined area (e.g., dairy
farms, beef feedlots, and swine and poultry farms).
Emissions of methane from wild animals and termites are not included in thissubmodule. The focus in the IPCC Guidelines is on anthropogenic emissions.
While there are human interactions with natural sources such as wild
animals and termites, they are complex and highly uncertain.

4.2.2 Data sources
There are no individual sources that will provide all the data needed toestimate methane emissions from domestic livestock. The Food andAgriculture Organisation (FAO) of the United Nations publishes a series
entitled The FAO Production Yearbook (e.g., FAO, 1991). This series has
information about livestock populations and the production andRevised 1996 IPCC Guidelines for National Greenhouse Gas Inventories:

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AGRICULTURE

consumption of livestock products. The FAO data should be supplemented
with studies conducted for individual countries. Many countries publish
results of their agricultural census that includes data on production levels in
addition to livestock populations. Table 4-1 summarises the data needed.

TABLE 4-1
LIVESTOCK POPULATION DATA COLLECTED IN TIER 1 STEP 1
Data Collected
Population by Climate (%)
Livestock

Population(# head)Dairy Cattle

Milk Production(kg/head/yr)

Cool

Temperate

Warm

Average Annual
Population

Milk Production per % Cool
Head

% Temp.

% WarmNon-dairy
CattleAverage Annual
Population

Not Applicable (NA) % Cool

% Temp.

% WarmBuffalo

Average Annual
Population(NA)% Cool% Temp.

% WarmSheep

Average Annual
Population(NA)% Cool% Temp.

% WarmGoats

Average Annual
Population(NA)% Cool% Temp.

% WarmCamelsAverage Annual
Population(NA)% Cool% Temp.

% WarmHorsesAverage Annual
Population(NA)% Cool% Temp.

% WarmMules and
Asses

Average Annual
Population(NA)% Cool% Temp.

% WarmSwine

Average Annual
Population(NA)% Cool% Temp.

% WarmPoultry

Average Annual
Population(NA)% Cool% Temp.

% WarmClimate regions are defined in terms of annual average temperature as follows: Cool = less than
15°C; temperate = 15°C to 25°C inclusive; and warm = greater than 25°C.

4.2.3 Methodology
Although the methodological issues are very complex, a simplified
methodology is used for the purposes of this Workbook.
For a detailed discussion of the methodology, see the Greenhouse Gas
Inventory Reference Manual. Broadly, emissions are calculated by applying anemission factor to the number of animals of each livestock type in the
country to produce a total for enteric fermentation. Default emission
factors are provided for developed and developing countries with moreregional detail for cattle, the most important source from this activity.

4.2

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The same basic methodology is used to estimate emissions from manure
management. In this area default emission factors are provided by region
and for three different climate regimes. Simple multiplication of populations
by emission factors produces emissions estimates.

Completing the Worksheet
Use WORKSHEET 4-1 METHANE AND NITROUS OXIDE EMISSIONS FROMDOMESTIC LIVESTOCK ENTERIC FERMENTATION AND MANURE MANAGEMENT atthe end of this module to record the data.

STEP 1 ESTIMATING EMISSIONS FROMENTERIC FERMENTATION
1USING THE WORKSHEET•

Copy the Worksheet at the endof this section to complete theinventory.

•

Keep the original of theWorksheet blank so you canmakefurthercopiesif
necessary.

For each type of livestock in the Worksheet, enter the number inthousands in column A.
Refer to FAO Production Yearbooks (e.g., FAO 1991) if there are no
locally available data. It is recommended that national experts use
three-year averages for activity data if available so that the data not be
skewed in the event that the base year of the inventory was an
exceptional year not representative of the country’s normal activity
level.

2

For each type of livestock, enter an average Emission Factor in column B
in kilograms per head per year (this is the same as tonnes per thousand
head per year). Use a figure from the tables below or more precise
locally available data. Because cattle are the most important source andbecause the emission factors for cattle vary significantly among regions,region-specific default factors are provided. Choose emission factors
for cattle that are most appropriate for your national situation.

TABLE 4-2
ENTERIC FERMENTATION METHANE EMISSIONS FACTORS(KG CH4 PER HEAD PER YEAR OR T CH4 PER 1000 HEAD PER YEAR)

Livestock

Developed Countries

Developing Countries

Buffalo

55

55

Sheep

8

5

Goats

5

5

Camels46

46

Horses18

18

Mules and Asses

10

10

Swine

1.5

1.0

Poultry

Not estimatedNot estimatedAll Estimates are + or - 20%.
See the Greenhouse Gas Inventory Reference Manual for sources.

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AGRICULTURE

3

Multiply the number of cattle by the Average Emissions Factors to give
Emissions from Enteric Fermentation in tonnes per year. Enter the
result in column C.

TABLE 4-3
ENTERIC FERMENTATION METHANE EMISSION FACTORS FOR CATTLE
Regional Characteristics

Cattle Type

Emissions Factor(kg CH4/head/yr)

Comments

North America:
Highly productive
commercialised dairy sector feeding highquality forage and grain. Separate beef cow
herd, primarily grazing with feed supplements
seasonally. Fast-growing beef steers/heifers
finished in feedlots on grain. Dairy cows are asmall part of the population.

Dairy

118

Average milk
production of
6700 kg/head/yr

Non-dairy

47

Includes beef
cows, bulls,
calves, growing
steers/heifers,
and feedlot cattle.

Dairy

100

Average milk
production of4200 kg/head /yr

Non-dairy48

Includes bulls,
calves, andgrowingsteers/heifers.

Dairy

81

Average milk
production of2550 kg/head/yr

Non-dairy

56

Includes beef
cows, bulls, andyoung.

Dairy

68

Average milk
production of
1700 kg/head/yr

Non-dairy

53

Includes beef
cows, bulls, andyoung.

Dairy

57

Average milk
production of
800 kg/head/yr

Non-dairy

49

Includes beef
cows, bulls, andyoung.

Western Europe:
Highly productive
commercialised dairy sector feeding highquality forage and grain. Dairy cows also used
for beef calf production. Very small dedicatedbeef cow herd. Minor amount of feedlot
feeding with grains.

Eastern Europe:
Commercialised dairy
sector feeding mostly forages. Separate beef
cow herd, primarily grazing. Minor amount offeedlot feeding with grains.

Oceania: Commercialised dairy sector basedon grazing. Separate beef cow herd, primarily
grazing range lands of widely varying quality.
Growing amount of feedlot feeding with grains.
Dairy cows are a small part of the population.

Latin America: Commercialised dairy sector
based on grazing. Separate beef cow herdgrazing pastures and range lands.
Minoramount of feedlot feeding with grains.
Growing beef cattle comprise a large portionof the population.

4.4

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TABLE 4-3 (CONTINUED)ENTERIC FERMENTATION METHANE EMISSION FACTORS FOR CATTLE
Regional Characteristics

Cattle Type

Emissions Factor(kg CH4/head/yr)

Comments

Asia:
Small commercialised dairy sector.
Most cattle are multi-purpose, providing draft
power and some milk within farming regions.
Small grazing population. Cattle of all types
are smaller than those found in most otherregions.

Dairy

56

Average milk
production of1650 kg/head /yr

Non-dairy

44

Includes multipurpose cows,
bulls, and young.

Dairy

36

Average milk
production of
475 kg/head /yr

Non-dairy

32

Includes multipurpose cows,
bulls, and young.

Dairy

46

Average milk
production of
900 kg/head /yr

Non-dairy

25

Includes cows,
bulls, and young.
Young comprisea large portion of
the population.

Africa and Middle East: Commercialised
dairy sector based on grazing with low
production per cow. Most cattle are multipurpose, providing draft power and some milk
within farming regions. Some cattle graze oververy large areas. Cattle of all types are smaller
than those found in most other regions.
Indian Subcontinent: Commercialised dairy
sector based on crop by-product feeding withlow production per cow.
Most bullocks
provide draft power and cows provide somemilk in farming regions.
Small grazing
population. Cattle in this region are thesmallest compared to cattle found in all otherregions.

See the Greenhouse Gas Inventory Reference Manual for sources.

STEP 2 ESTIMATING EMISSIONS FROM
MANURE MANAGEMENT SYSTEMS
1

For each type of animal, enter the Emissions Factor for Manure
Management in column D in kilograms per head per year. Use default
data in the tables which follow or more precise locally available data.
Table 4-4 provides default emission factors for most livestock types
with different values for developed and developing countries to reflect
different conditions and typical practices. Factors are also provided for
3 different climates. Users should select the factors which best
represent their conditions. For large countries it may be necessary to
subdivide populations into more than one climate region. In that casethe user can proceed with calculations in one of two ways.
aDevelop an average emissions factor. For example:
If 25 per cent of sheep are in a temperate region and 75 per cent ina warm region, thenEF= (0.25 x 0.16) + (0.75 x 0.21) = 0.20 kg/head/yr

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AGRICULTURE

If users do develop and average emission factors, they should state
what they have done and should document their sources.
b

An alternative approach is to make extra copies of the Worksheet
and complete one for each region for the manure portion, then add
the results and enter the sum on the main Worksheet.
Swine, buffalo and cattle are the most important source of manure
emissions and the most variable by region, therefore detailed
emission factors are provided in a separate table.

2

Multiply the Number of Animals by the Emission Factor for Manure
Management to give the Emissions from Manure Management in t/yr.
Enter the results in column E.
TABLE 4-4
EMISSIONS FACTORS FOR MANURE MANAGEMENT(KG CH4 PER HEAD PER YEAR)

Livestock

Developed Countries

Developing Countries

Cool

Temp.aWarm

Cool

Temp.a

Warm

Sheep

0.19

0.28

0.37

0.10

0.16

0.21

Goats

0.12

0.18

0.23

0.11

0.17

0.22

Camels

1.59

2.38

3.17

1.28

1.92

2.56

Horses

1.39

2.08

2.77

1.09

1.64

2.18

Mules and
Asses

0.76

1.14

1.51

0.60

0.90

1.19

0.078

0.117

0.157

0.012

0.018

0.023

b

Poultry

The range of estimates reflects cool to warm climates. Climate regions are defined in terms of annual
average temperature as follows: Cool = less than 15°C; Temperate = 15°C to 25°C inclusive; andWarm = greater than 25°C. Cool, Temperate and Warm regions are estimated using Methane
Conversion Factors of 1%, 1.5% and 2%, respectively.
a Temp. = Temperate climate region.
b Chickens, ducks, and turkeys.
All estimates are ± 20 percent.
Sources: Emission factors developed from: feed intake values and feed digestibilities used to develop theenteric fermentation emission factors (see Appendix A of the Reference Manual Chapter 4); MCF, andBo values reported in Woodbury and Hashimoto (1993). All manure is assumed to be managed in dry
systems, which is consistent with the manure management system usage reported in Woodbury andHashimoto (1993).

4.6

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TABLE 4-5
MANURE MANAGEMENT EMISSION FACTORS FOR CATTLE, SWINE, AND BUFFALO
Regional Characteristics

Emissions Factor by Climate Regiona(kg/head/year)

Livestock Type

Dairy Cattle
North America: Liquidbased systems are commonly
Non-dairy Cattle
used for dairy and swine
manure. Non-dairy manure Swineis usually managed as a solidand deposited on pastures orranges.

Cool

Temperate

Warm

36

54

76

1

2

3

10

14

18

Western Europe: Liquid /slurry and pit storage
systems are commonly used
for cattle and swine manure.
Limited cropland is available
for spreading manure.

Dairy Cattle

14

44

81

Non-dairy Cattle

6

20

38

Swine

3

10

19

Buffalo3

817

Eastern Europe: Solidbased systems are used forthe majority of manure.
About one-third of livestock
manure is managed in liquidbased systems.

Dairy Cattle

6

19

33

Non-dairy Cattle

4

13

23

Swine

4

7

11

Buffalo3

916

Oceania: Virtually all
livestock manure is managed
as a solid on pastures andranges. About half of theswine manure is managed inanaerobic lagoons.

Dairy Cattle

31

32

33

Non-dairy Cattle

5

6

7

Swine

20

20

20

Latin America: Almost all
livestock manure is managed
as a solid on pastures andranges. Buffalo manure isdeposited on pastures andranges.

Dairy Cattle

0

1

2

Non-dairy Cattle

1

1

1

Swine

0

1

2

Buffalo112

Asia: About half of cattle
manure is used for fuel withthe remainder managed indry systems. Almost 40% ofswine manure is managed asa liquid. Buffalo manure ismanaged in drylots anddeposited in pastures andranges.

Dairy Cattle

7

16

27

Non-dairy Cattle

1

1

2

Swine

1

4

7

Buffalo123Africa: Almost all livestock
manure is managed as a solidon pastures and ranges.

Dairy Cattle

1

1

1

Non-dairy Cattle

0

1

1

Swine

0

1

2

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AGRICULTURE

TABLE 4-5 (CONTINUED)
MANURE MANAGEMENT EMISSION FACTORS FOR CATTLE, SWINE, AND BUFFALO
Regional Characteristics

Livestock Type

Middle East: Over two-thirds ofcattle manure is deposited on
pastures and ranges. About onethird of swine manure is managed inliquid-based systems. Buffalo manure
is burned for fuel or managed as asolid.

Dairy Cattle
Non-dairy Cattle
Swine
BuffaloEmissions Factor by Climate Regiona(kg/head/year)
Cool

Temperate

Warm

1
1
1
4

2
1
3
5

2
1
6
5

Indian Subcontinent:
About Dairy Cattle
5
6
5
half of cattle and buffalo manure is Non-dairy Cattle2
22
used for fuel with the remainder Swine4
63
managed in dry systems. About
55
Buffalo4
one-third of swine manure ismanaged as a liquid.
aCool climates have an average temperature below 15°C; temperate climates have an average temperature ranging from
15°C to 25°C inclusive; warm climates have an average temperature above 25°C. All climate categories are notnecessarily represented within every region. For example, there are no significant warm areas in Eastern or Western
Europe. Similarly, there are no significant cool areas in Africa and the Middle East.
Note: Significant buffalo populations do not exist in North America, Oceania, or Africa.

See the Greenhouse Gas Inventory Reference Manual for sources.

STEP 3 ESTIMATING METHANE EMISSIONSFROM ENTERIC FERMENTATION AND
MANURE MANAGEMENT
1 Sum emissions for Enteric Fermentation and Manure Management andenter the totals at the bottom of the Worksheet.
2 Add the two totals together to give Total Annual Emissions from
Domestic Livestock.
3 Divide the final result by 1,000 to express it as gigagrams. Enter the
result in column F.

4.8

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STEP 4 ESTIMATING N2O EMISSIONS FROMANIMAL WASTE MANAGEMENT SYSTEMSEQUATION 1
Nex(AWMS) = ∑(T)[N(T) x Nex(T) x AWMS(T)]
Where :
Nex(AWMS)=

N excretion per Animal Waste Management System(kg/yr) (see Step 1 in the agricultural soils Section
4.6);

N(T)

=

number of animals of type T in the country;

Nex(T)=

N excretion of animals of type T in the country (kgN/animal /yr) (see Table 4-6);

AWMS(T)=

fraction of Nex(T) that is managed in one of thedifferent distinguished animal waste management
systems for animals of type T in the country; (seeTable 4-7);

T=

type of animal category.

Worksheet 4-1 (Supplemental) NITROGEN EXCRETION PER AWMS
Use the Supplemental Worksheet 4-1 to calculate Nitrogen Excretion per
Animal Waste Management System (AWMS). Make extra copies of the
Worsheet and complete one for each AWMS.
1 Enter the Number of Animals, N, in a country in column A.
2 Enter the Nitrogen Excretion, Nex, for each animal type in column B.
Default data are provided in Table 4-6.
3 Enter the Fraction of Manure Nitrogen per AWMS in column C. Default
data are provided in Table 4-7.
4 Multiply columns A, B, and C, and enter the results into column D.
5 Sum the values in column D and enter the total in the bottom of thecolumn to obtain the Nitrogen Excretion for each AWMS, Nex(AWMS), in
kilograms per year.

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AGRICULTURE

EQUATION 2
N2O(AWMS)=∑[ Nex (AWMS) x EF3(AWMS)]
where:
N2O(AWMS)=

N2O emissions from all Animal Waste Management
Systems in the country (kg N/yr);

Nex (AWMS)=

See Equation 1, above;EF3(AWMS)=

N2O emission factor for an AWMS (kg N2O-N/kg of
Nex in AWMS); (see Table 4-8).

Use Worksheet 4-1, Sheet 2 of 2 to calculate N2O Emissions from all Animal
Waste Management Systems.
NITROUS OXIDE FROM AWMS
Nitrogen Excretion Nex from all
AWMS
areestimated
here.
However, note that N2O emissions
from anaerobic lagoons, liquid
systems, solid storage and drylot, and“other systems” are reported in thissection while daily spread andpasture range and paddock arereported under Agricultural Soils(see Section 4.6).

1 Enter the values of Nitrogen Excretion Nex(AWMS) from the bottom ofcolumn D of each Supplemental Worksheet into the corresponding
Animal Waste Management System in column A.
2 For each type of Animal Waste Management System, enter Emission
Factor for Animal Waste Management Systems in column B. Use default
values provided in Table 4-8 or more precise locally available data.
3 Multiply the value of N excretion (column A) by the N2O Emission
Factor for Animal Waste Management System (column B) and then by
the conversion ratio 44/28 to give the Total Annual Emissions of N2O.
Multiply the final result by 10-6 to express it as gigagrams. Enter the
results in column C.
4 Sum the values in column C and enter the result in the bottom of thecolumn.

TABLE 4-6
TENTATIVE DEFAULT VALUES FOR NITROGEN EXCRETION PER HEAD OF ANIMAL PER REGION(kg/animal/yr)a
RegionType of Animal
Non-dairy
cattleDairycattlePoultry

Sheep

Swine

OthersNorth America

70

100

0.6

16

20

25

Western Europe

70

100

0.6

20

20

25

Eastern Europe

50

70

0.6

16

20

25

Oceania

60

80

0.6

20

16

25

Latin America

40

70

0.6

12

16

40

Africa

40

60

0.6

12

16

40

Near East &Mediterranean

50

70

0.6

12

16

40

Asia & Far East

40

60

0.6

12

16

40

a Source: Ecetoc (1994), Vetter et al. (1988), Steffens and Vetter (1990).

4.10

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WorkbookEastern Europe

Western Europe

North America

Region00000Poultry (E)

Sheep

Swine

Other animals (F)0

Other animals (F)Dairy Cattle

0

Swine

8

0

Sheep

Non-dairy Cattle (D)00Other animals (F)Poultry (E)

25

Swine

0

0

Sheep

Dairy Cattle

5

Poultry (E)010Dairy Cattle

Non-dairy Cattle (D)0Anaerobic
LagoonNon-dairy Cattle (D)Type of Animal

0

29

0

28

18

39

0

77

0

13

46

55

0

50

0

4

23

1

LiquidSystem

0

0

0

0

1

0

0

0

0

0

24

0

0

0

0

0

37

0

Daily
Spread

0

0

0

0

67

52

0

23

2

1

21

2

0

18

2

0

23

14

Solid Storage
and Drylot

92

27

73

1

13

0

96

0

87

2

8

33

92

0

88

1

0

84

PastureRange and
Paddock

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Used Fuel

Percentage of Manure Production per Animal Waste Management Systems

TABLE 4-7
DEFAULT VALUES FOR PERCENTAGE OF MANURE N PRODUCED IN DIFFERENT ANIMAL WASTE MANAGEMENT SYSTEMSIN DIFFERENT WORLD REGIONS (FROM SAFLEY ET AL., 1992)

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4

8

45

27

71

0

1

4

0

11

84

1

9

8

6

10

90

7

1

Other System

4 . 11AGRICULTURE

4.12

0
0
0
55
0
0
0
0
0
0
0
0
0
0
0
0
1

Poultry (E)

Sheep

Swine

Other animals (F)Non-dairy Cattle (D)Dairy Cattle

Poultry (E)

Sheep

Swine

Other animals (F)Non-dairy Cattle (D)Dairy Cattle

Poultry (E)

Sheep

Swine

Other animals (F)AfricaLatin America0Non-dairy Cattle (D)Dairy Cattle

Oceania

Anaerobic
Lagoon

0

7

0

0

0

0

0

8

0

9

1

0

0

0

0

0

0

0

LiquidSystem

3

42

0

93

1

0

99

0

99

81

83

96

3
0

99

0

100
0

51

0

0

36

99

0
1

100

0

100

0

17

0

0

100

100

0
0

PastureRange and
Paddock

Solid
Storage andDrylot

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Used Fuel

1

0

1

19

5

0

1

40

0

49

0

1

0

28

0

97

0

0

Other System

Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories:

0

0

0

0

12

1

0

2

0

0

62

0

0

0

0

0

0

0

Daily
SpreadPercentage of Manure Production per Animal Waste Management Systems

Type of Animal

TABLE 4-7 (CONTINUED)DEFAULT VALUES FOR PERCENTAGE OF MANURE N PRODUCED IN DIFFERENT ANIMA L WASTE MANAGEMENT SYSTEMS IN DIFFERENT WORLDREGIONS(FROM SAFLEY ET AL., 1992)

RegionAGRICULTURE

Workbook

0

0
0
0

Poultry (E)

Sheep

Swine

0

1
0
1
0

Poultry (E)

Sheep

Swine

Other animals (F)38

6Dairy Cattle
0

2

4

0

0
0

Other animals (F)

0

1

0

Non-dairy Cattle (D)(D) Includes buffalo(E) Includes chickens, turkeys and ducks(F) Includes goats, horses, mules, donkeys and camels

Asia and Far East

32

0

Dairy Cattle

00

Non-dairy Cattle (D)Near East andMediterranean

LiquidSystemType of Animal

RegionAnaerobic
Lagoon

0

1

0

0

21

16

0

0

0

0

3

2

Daily
Spread

0

53

0

0

0

14

0

68

0

0

3

0

Solid
Storage andDrylot

95

0

83

44

24

29

100

0

100

71

77

77

PastureRange and
Paddock

Per centage of Manure Production per Animal Waste Management Systems

0

7

0

1

46

40

0

0

0

0

18

18

Used Fuel

5

0

17

52

0

0

0

0

0

28

0

2

Other System

TABLE 4-7 (CONTINUED)DEFAULT VALUES FOR PERCENTAGE OF MANURE N PRODUCED IN DIFFERENT ANIMAL WASTE MANAGEMENT SYSTEMS IN DIFFERENT WORLDREGIONS (FROM SAFLEY ET AL., 1992)

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TABLE 4-8
TENTATIVE DEFAULT VALUES FOR N2O EMISSION FACTORS FROM ANIMAL WASTE PERANIMAL WASTE MANAGEMENT SYSTEM(KG N2O–N/KG NITROGEN EXCRETED)Animal Waste Management Systema

Emission Factor EF3

Anaerobic lagoonsb

0.001 (<0.002)

Liquid systemsb

0.001 (<0.001)

Daily spreadc

0.0 (no range)

Solid storage and drylotc

0.02 (0.005-0.03)

Pasture range and paddock (grazing)d0.02 (0.005-0.03)

Used as fuele

Not included in this Chapter

Other systemsb

0.005

a The fraction of manure nitrogen produced in different Animal Waste Management Systems for cattle, swine
and buffalo can be estimated as proposed in Table 4-7, or as given by Safley et al. (1992).
b To be reported under “Manure Management”.
c To be reported under “Agricultural Soils” (Section 4.6) under direct soil emissions from agricultural fields
after spreading. (Emissions are assumed not to occur before spreading).
d To be reported under “Agricultural Soils” (Section 4.6) under direct soil emissions from animal production.
e To be reported in the Energy Chapter.

4.3

Rice Cultivation
4.3.1 Introduction
Anaerobic decomposition of organic material in flooded rice fields produces
methane (CH4), which escapes to the atmosphere primarily by diffusivetransport 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 riceproduction and about 15 per cent of the global rice area under cultivation.
The remaining area is grown for wetland rice, consisting of irrigated, rainfed,
and deepwater rice. The global wetland rice area harvested annually in theearly 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).1
The measurements at various locations of the world show that there arelarge temporal variations 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
1 The term "harvested area" has a different meaning from "cultivatedarea" in that the former 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 of rice are grown on eachhectare each year), then this country has 20 million hectares of rice area
harvested annually.

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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 thesame location and under similar 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 orcountry level. Thus, at the current level of understanding, a reported range
in methane emission levels for a country is more realistic than a single
number.

4.3.2 Data sources
Area Statistics
Table 4-9 contains information on harvested area of rice according tostatistics 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 rice-producing countries werebased on the IRRI Rice Almanac (IRRI, 1994) and for other rice-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 are continuously flooded or have an aeration period greaterthan 3 days or multiple aerations, are to be obtained from the country
specific data.

ESTIMATING HARVESTED AREA
The annual harvested area cultivatedunder these conditions is given by
the cultivated area (in m2/yr) times
the number of cropping seasons per
year. If some areas are double
cropped, they would be counted
twice as the harvested area.

Seasonally Integrated flux values
Tables 4-10 and 4-11 provides default emission factors, EF, for various
categories of water regimes and multiplication factors for organic
amendments. Emissions from upland rice are assumed to be 0 and ignoredin the emission calculations.
See the Reference Manual for a more detailed discussion of available data
sources.

4.3.3 Methodology
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 ricewater regime and for a given organic amendment, in Tg /yr;EF=methane emission factor integrated over integrated cropping
season, in g/m2;A=annual harvested area cultivated under conditions specified
above. It is given by the cultivated area times the number ofcropping seasons per year, i.e., in m2/yr.

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AGRICULTURE

Completing the Worksheet
Use WORKSHEET 4-2 METHANE EMISSIONS FROM FLOODED RICE FIELDS at theend of this module to enter your data. Table 4-9 gives default data for the
distribution of rice growing areas and water management types throughout
the world.

USING THE WORKSHEET•

Copy the Worksheet at the endof this section to complete theinventory.

•

Keep the original of theWorksheet blank so you canmakefurthercopiesif
necessary.

ESTIMATING METHANE EMISSIONS BY
WATER MANAGEMENT REGIME
1

The annual harvested area cultivated under these conditions is given by
the cultivated area (in m2/yr) times the number of cropping seasons per
year. Area cultivated under upland (or dry conditions) is excluded frommethane calculations. Table 4-9 provides some default information
which can be used if data are not locally available. Note that the data
for area harvested provided in Table 4-9 are expressed in units ofthousands of hectares. If these data are used they must first be
converted to square metres (1000h = 107 sq.m).

REFLECTING MORE DETAIL
If you have the necessary data, you
can sub-divide your data further toaccount for different fertilising
practices. Furthermore, if regionalvariations in temperature, cultivation
practices, etc. justify it, calculations
can be done at sub-national regional
level. In either case you should use
extra copies of the Worksheet andlabel them clearly by subcategory or
region. You should then aggregate
the results to provide a national
summary table from the basic
categories described in the method.

4.16

Enter the Harvested Area by water management regime (in square
metres x 10-9) in column A.

2Enter the Scaling Factor for Methane Emissions in column B. Default
factors are given for rice ecosystems relative to continuously flooded
fields, without organic amendments. Values are provided in Table 4-10
and can be used if more detailed data are not locally available.

3

For conversion to soils with organic amendment, enter a Correction
Factor for Organic Amendment in column C. The default value is 2.
For soils without organic amendment, correction is not necessary. In
this case, enter 1 in column C.

4Enter the Seasonally Integrated Methane Emission Factor for
Continuously Flooded Rice without Organic Amendment (in g/m2) incolumn D. Some country specific data are given in Table 4-11. The
arithmetic mean of the dataset can be used as a default value, if no otherinformation is available.

5

For each category, multiply the Harvested Area (column A) by the
Scaling Factor for Methane Emissions (column B), the Correction Factor
for Organic Amendment (column C), and the Seasonally Integrated
Methane Emission Factor for Continuously Flooded Rice without
Organic Fertilisers (column D). This gives CH4 Emissions in gigagramsfor each rice category. Enter the result in column E.

6

Sum emissions and enter the total at the bottom of column E.

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TABLE 4-9
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

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

21

0

Country or Region
Americas

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AGRICULTURE

TABLE 4.9 (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)

10Country or Region

Asia

4.18

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)

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TABLE 4.9 (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

Country or Region
Europe

PACIFIC

Africa

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AGRICULTURE

TABLE 4.9 (CONT.)DEFAULT ACTIVITY DATA - HARVESTED RICE
1990 Area(1000s ha)

Irrigateda(%)

Upland Rice(%)

Rainfedb
(%)

Ghana

85

24

76

0

Guinea Bissau

57

25

75

0

Guinea

608

8

47

45

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.
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).

4.20

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