Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.1 

CHAPTER 10 

EMISSIONS FROM LIVESTOCK AND 

MANURE MANAGEMENT 
Volume 4: Agriculture, Forestry and Other Land Use 

10.2 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Authors 

Hongmin Dong (China), Joe Mangino (USA), and Tim A. McAllister (Canada) 

Jerry L. Hatfield (USA), Donald E. Johnson (USA), Keith R. Lassey (New Zealand), Magda Aparecida de Lima 

(Brazil), and Anna Romanovskaya (Russian Federation) 

Contributing Authors 

Deborah Bartram (USA), Darryl Gibb (Canada), and John H. Martin, Jr. (USA) 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.3 

Contents 

10 Emissions from Livestock and Manure Management 

10.1 Introduction.........................................................................................................................................10.7

10.2 Livestock Population and Feed Characterisation ................................................................................10.7

10.2.1 Steps to define categories and subcategories of livestock ...........................................................10.7

10.2.2 Choice of method ........................................................................................................................10.8

10.2.3 Uncertainty assessment .............................................................................................................10.23

10.2.4 Characterisation for livestock without species: Specific emission estimation methods ............10.23

10.3 Methane Emissions from Enteric Fermentation ................................................................................10.24

10.3.1 Choice of method ......................................................................................................................10.24

10.3.2 Choice of emission factors ........................................................................................................10.26

10.3.3 Choice of activity data...............................................................................................................10.33

10.3.4 Uncertainty assessment .............................................................................................................10.33

10.3.5 Completeness, Time series, Quality Assurance/Quality Control and Reporting.......................10.33

10.4 Methane Emissions from Manure Management................................................................................10.35 

10.4.1 Choice of method ......................................................................................................................10.35 

10.4.2 Choice of emission factors ........................................................................................................10.37 

10.4.3 Choice of activity data...............................................................................................................10.48 

10.4.4 Uncertainty assessment .............................................................................................................10.48 

10.4.5 Completeness, Time series, Quality assurance / Quality control and Reporting.......................10.50 

10.5 N2O Emissions from Manure Management.......................................................................................10.52 

10.5.1 Choice of method ......................................................................................................................10.53 

10.5.2 Choice of emission factors ........................................................................................................10.57 

10.5.3 Choice of activity data...............................................................................................................10.61 

10.5.4 Coordination with reporting for N2O emissions from managed soils........................................10.64 

10.5.5 Uncertainty assessment .............................................................................................................10.66 

10.5.6 Completeness, Time series, Quality assurance/Quality control and Reporting.........................10.68 

10.5.7 Use of worksheets .....................................................................................................................10.69 

Annex 10A.1 Data underlying methane default emission factors for enteric fermentation .............................10.71 

Annex 10A.2 Data underlying methane default emission factors for Manure Management ...........................10.74 

References ...................................................................................................................................................10.84 
Volume 4: Agriculture, Forestry and Other Land Use 

10.4 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Equations 

Equation 10.1 Annual average population..................................................................................................10.8

Equation 10.2 Coefficient for calculating net energy for maintenance.....................................................10.13

Equation 10.3 Net energy for maintenance..............................................................................................10.15

Equation 10.4 Net energy for activity (for cattle and buffalo)..................................................................10.16

Equation 10.5 Net energy for activity (for sheep).....................................................................................10.16

Equation 10.6 Net energy for growth (for cattle and buffalo) ..................................................................10.17

Equation 10.7 Net energy for growth (for sheep) .....................................................................................10.17

Equation 10.8 Net energy for lactation (for beef cattle, dairy cattle and buffalo).....................................10.18

Equation 10.9 Net energy for lactation for sheep (milk production known).............................................10.18

Equation 10.10 Net energy for lactation for sheep (milk production unknown).........................................10.19

Equation 10.11 Net energy for work (for cattle and buffalo)......................................................................10.19

Equation 10.12 Net energy to produce wool (for sheep) ............................................................................10.19

Equation 10.13 Net energy for pregnancy (for cattle/buffalo and sheep)...................................................10.20

Equation 10.14 Ratio of net energy available in a diet for maintenance to digestible energy consumed ...10.20

Equation 10.15 Ratio of net energy available for growth in a diet to digestible energy consumed ............10.21

Equation 10.16 Gross energy for cattle/buffalo and sheep .........................................................................10.21

Equation 10.17 Estimation of dry matter intake for growing and finishing cattle ......................................10.22

Equation 10.18a Estimation of dry matter intake for mature beef cattle .....................................................10.22

Equation 10.18b Estimation of dry matter intake for mature dairy cows....................................................10.22

Equation 10.19 Enteric fermentation emissions from a livestock category ................................................10.28

Equation 10.20 Total emissions from livestock enteric fermentation.........................................................10.28

Equation 10.21 CH4 emission factors for enteric fermentation from a livestock category .........................10.31

Equation 10.22 CH4 emissions from manure management.........................................................................10.37 

Equation 10.23 CH4 emission factor from manure management................................................................10.41 

Equation 10.24 Volatile solid excretion rates .............................................................................................10.42 

Equation 10.25 Direct N2O emissions from manure management .............................................................10.54 

Equation 10.26 N losses due to volatilisation from manure management ..................................................10.54 

Equation 10.27 Indirect N2O emissions due to volatilisation of N from manure management ..................10.56 

Equation 10.28 N losses due to leaching from manure management systems............................................10.56 

Equation 10.29 Indirect N2O emissions due to leaching from manure management..................................10.57 

Equation 10.30 Annual N excretion rates ...................................................................................................10.57 

Equation 10.31 Annual N excretion rates (Tier 2)......................................................................................10.58 

Equation 10.32 N intake rates for cattle......................................................................................................10.58 

Equation 10.33 N retained rates for cattle...................................................................................................10.60 

Equation 10.34 Managed manure N available for application to managed soils, feed, fuel or 

construction uses ...............................................................................................................10.65 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.5 

Figures 

Figure 10.1 Decision tree for livestock population characterisation.......................................................10.9

Figure 10.2 Decision Tree for CH4 Emissions from Enteric Fermentation ..........................................10.25

Figure 10.3 Decision tree for CH4 emissions from Manure Management ............................................10.36 

Figure 10.4 Decision tree for N2O emissions from Manure Management (Note 1) .............................10.55 

Tables 

Table 10.1 Representative livestock categories...................................................................................10.11

Table 10.2 Representative feed digestibility for various livestock categories.................................10.14

Table 10.3 Summary of the equations used to estimate daily gross energy intake 

for Cattle, Buffalo and Sheep ...........................................................................................10.15

Table 10.4 Coefficients for calculating net energy for maintenance ( NEm ).......................................10.16

Table 10.5 Activity coefficients corresponding to animal’s feeding situation ....................................10.17

Table 10.6 Constants for use in calculating NEg for Sheep.................................................................10.18

Table 10.7 Constants for use in calculating NEp in Equation 10.13....................................................10.20

Table 10.8 Examples of NEma content of typical diets fed to Cattle for estimation of 

dry matter intake in Equations 10.17 and 10.18 ...............................................................10.23

Table 10.9 Suggested emissions inventory methods for enteric fermentation.....................................10.27

Table 10.10 Enteric fermentation emission factors for Tier 1 method ..................................................10.28

Table 10.11 Tier 1 enteric fermentation emission factors for Cattle .....................................................10.29

Table 10.12 Cattle/buffalo CH4 conversion factors (Ym ) .....................................................................10.30

Table 10.13 Sheep CH4 conversion factors (Ym)...................................................................................10.31

Table 10.14 Manure management methane emission factors by temperature for Cattle, Swine, 

and Buffalo ........................................................................................................................10.38 

Table 10.15 Manure management methane emission factors by temperature for Sheep, Goats, 

Camels, Horses, Mules and Asses, and Poultry.................................................................10.40 

Table 10.16 Manure management methane emission factors for Deer, Reindeer, Rabbits, 

and fur-bearing animals.....................................................................................................10.41 

Table 10.17 MCF values by temperature for manure management systems .........................................10.44 

Table 10.18 Definitions of manure management systems .....................................................................10.49 

Table 10.19 Default values for nitrogen excretion rate ........................................................................10.59 

Table 10.20 Default values for the fraction of nitrogen in feed intake of livestock that is 

retained by the different livestock species/categories (fraction N-intake 

retained by the animal) ......................................................................................................10.60 

Table 10.21 Default emission factors for direct N2O emissions from manure management.................10.62 

Table 10.22 Default values for nitrogen loss due to volatilisation of NH3 and NOx from manure 

management.......................................................................................................................10.65 

Table 10.23 Default values for total nitrogen loss from manure management......................................10.67 

Table 10A.1 Data for estimating Tier 1 enteric fermentation CH4 emission factors for 

Dairy Cows in Table 10.11................................................................................................10.72 
Volume 4: Agriculture, Forestry and Other Land Use 

10.6 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Table 10A.2 Data for estimating Tier 1 enteric fermentation CH4 emission factors for 

Other Cattle in Table 10.11 ...............................................................................................10.73

Table 10A.3 Data for estimating Tier 1 enteric fermentation CH4 emission factors for Buffalo ..........10.75 

Table 10A-4 Manure management methane emission factor derivation for Dairy Cows.......................10.77 

Table 10A-5 Manure management methane emission factor derivation for Other Cattle ......................10.78 

Table 10A-6 Manure management methane emission factor derivation for Buffalo..............................10.79 

Table 10A-7 Manure management methane emission factor derivation for Market Swine ...................10.80 

Table 10A-8 Manure management methane emission factor derivation for Breeding Swine ................10.81 

Table 10A-9 Manure management methane emission factor derivation for Other Animals .................10.82 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.7 

10 EMISSIONS FROM LIVESTOCK AND 

MANURE MANAGEMENT 

10.1 INTRODUCTION 

This chapter provides guidance on methods to estimate emissions of methane from Enteric Fermentation in 

livestock, and methane and nitrous oxide emissions from Manure Management. CO2 emissions from livestock 

are not estimated because annual net CO2 emissions are assumed to be zero – the CO2 photosynthesized by 

plants is returned to the atmosphere as respired CO2. A portion of the C is returned as CH4 and for this reason 

CH4 requires separate consideration. 

Livestock production can result in methane (CH4) emissions from enteric fermentation and both CH4 and nitrous 

oxide (N2O) emissions from livestock manure management systems. Cattle are an important source of CH4 in 

many countries because of their large population and high CH4 emission rate due to their ruminant digestive 

system. Methane emissions from manure management tend to be smaller than enteric emissions, with the most 

substantial emissions associated with confined animal management operations where manure is handled in 

liquid-based systems. Nitrous oxide emissions from manure management vary significantly between the types of 

management system used and can also result in indirect emissions due to other forms of nitrogen loss from the 

system. The calculation of the nitrogen loss from manure management systems is also an important step in 

determining the amount of nitrogen that will ultimately be available in manure applied to managed soils, or used 

for feed, fuel, or construction purposes – emissions that are calculated in Chapter 11, Section 11.2 (N2O 

emissions from managed soils). 

The methods for estimating CH4 and N2O emissions from livestock require definitions of livestock subcategories, 

annual populations and, for higher Tier methods, feed intake and characterisation. The procedures employed to 

define livestock subcategories, develop population data, and characterize feed are described in Section 10.2 

(Livestock Population and Feed Characterisation). Suggested feed digestibility coefficients for various livestock 

categories have been provided to help estimation of feed intake for use in calculation of emissions from enteric 

and manure sources. A coordinated livestock characterisation as described in Section 10.2 should be used to 

ensure consistency across the following source categories: 

• Section 10.3 - CH4 emissions from Enteric Fermentation; 

• Section 10.4 - CH4 emissions from Manure Management; 

• Section 10.5 - N2O emissions from Manure Management (direct and indirect); 

• Chapter 11, Section 11.2 - N2O emissions from Managed Soils (direct and indirect). 

10.2 LIVESTOCK POPULATION AND FEED 

CHARACTERISATION 

10.2.1 Steps to define categories and subcategories of 

livestock 

Good practice is to identify the appropriate method for estimating emissions for each source category, and then 

base the characterisation on the most detailed requirements identified for each livestock species. The livestock 

characterisation used by a country will probably undergo iterations as the needs of each source category are 

assessed during the emissions estimation process (see Figure 10.1, Decision Tree for Livestock Population 

Characterisation). The steps are: 

• Identify livestock species applicable to each emission source category: The livestock species that 

contribute to more than one emission source category should first be listed. These species are typically: 

cattle, buffalo, sheep, goats, swine, horses, camels, mules/asses, and poultry. 

• Review the emission estimation method for each relevant source category: For the source categories of 

Enteric Fermentation and Manure Management, identify the emission estimating method for each species 

for that source category. For example, enteric fermentation emissions from cattle, buffalo, and sheep should 

each be examined to assess whether the trend or level of emissions warrant a Tier 2 or Tier 3 emissions 

estimate. Similarly, manure management methane emissions from cattle, buffalo, swine, and poultry should 
Volume 4: Agriculture, Forestry and Other Land Use 

10.8 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

be examined to determine whether the Tier 2 or Tier 3 emissions estimate is appropriate. Existing inventory 

estimates can be used to conduct this assessment. If no inventory has been developed to date, Tier 1 

emission estimates should be calculated to provide initial estimates for conducting this assessment. See 

Volume 1, Chapter 4 (Methodological Choice and Identification of Key Categories) for guidance on the 

general issues of methodological choice. 

• Identify the most detailed characterisation required for each livestock species: Based on the 

assessments for each species under each source category, identify the most detailed characterisation required 

to support each emissions estimate for each species. Typically, the ‘Basic’ characterisation can be used 

across all relevant source categories if the enteric fermentation and manure sources are both estimated with 

their Tier 1 methods. An ‘Enhanced’ characterisation should be used to estimate emissions across all the 

relevant sources if the Tier 2 method is used for either enteric fermentation or manure. 

10.2.2 Choice of method 

TIER 1: BASIC CHARACTERISATION FOR LIVESTOCK POPULATIONS 

Basic characterisation for Tier 1 is likely to be sufficient for most animal species in most countries. For this 

approach it is good practice to collect the following livestock characterisation data to support the emissions 

estimates: 

Livestock species and categories: A complete list of all livestock populations that have default emission factor 

values must be developed (e.g., dairy cows, other cattle, buffalo, sheep, goats, camels, llamas, alpacas, deer, 

horses, rabbits, mules and asses, swine, and poultry) if these categories are relevant to the country. More 

detailed categories should be used if the data are available. For example, more accurate emission estimates can 

be made if poultry populations are further subdivided (e.g., layers, broilers, turkeys, ducks, and other poultry), as 

the waste characteristics among these different populations varies significantly. 

Annual population: If possible, inventory compilers should use population data from official national statistics 

or industry sources. Food and Agriculture Organisation (FAO) data can be used if national data are unavailable. 

Seasonal births or slaughters may cause the population size to expand or contract at different times of the year, 

which will require the population numbers to be adjusted accordingly. It is important to fully document the 

method used to estimate the annual population, including any adjustments to the original form of the population 

data as it was received from national statistical agencies or from other sources. 

Annual average populations are estimated in various ways, depending on the available data and the nature of the 

animal population. In the case of static animal populations (e.g., dairy cows, breeding swine, layers), estimating 

the annual average population may be as simple as obtaining data related to one-time animal inventory data. 

However, estimating annual average populations for a growing population (e.g., meat animals, such as broilers, 

turkeys, beef cattle, and market swine) requires more evaluation. Most animals in these growing populations are 

alive for only part of a complete year. Animals should be included in the populations regardless if they were 

slaughtered for human consumption or die of natural causes. Equation 10.1 estimates the annual average of 

livestock population.

EQUATION 10.1 

ANNUAL AVERAGE POPULATION

⎟

⎠

⎞ ⎜

⎝

⎛ = • 365 _ NAPA AAP Days alive

Where: 

AAP = annual average population 

NAPA = number of animals produced annually 

Broiler chickens are typically grown approximately 60 days before slaughter. Estimating the average annual 

population as the number of birds grown and slaughtered over the course of a year would greatly overestimate 

the population, as it would assume each bird lived the equivalent of 365 days. Instead, one should estimate the 

average annual population as the number of animals grown divided by the number of growing cycles per year. 

For example, if broiler chickens are typically grown in flocks for 60 days, an operation could turn over 

approximately 6 flocks of chickens over the period of one year. Therefore, if the operation grew 60,000 

chickens in a year, their average annual population would be 9,863 chickens. For this example the equation 

would be: 

Annual average population = 60 days ● 60,000 / 365 days / yr = 9,863 chickens 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.9 

Figure 10.1 Decision tree for livestock population characterisation 

Start

Ask for

each livestock

species: "Are data 

available to support the level of 

detail required for the

characterisation?"

Collect the data required to

support the characterisation.

Set the level of the

characterisation

to the available data.

Yes

No

Yes

Note:

1: These categories include: CH4 Emission from Enteric Fermentation, CH4 Emission from Manure Management, and N2O Emission from 

Manure Management.

2: See Volume 1 Chapter 4, "Methodological Choice and Identification of Key Categories" (noting Section 4.1.2 on limited resources), for 

discussion of key categories and use of decision trees.

Can

data be collected to

support the level of

characterisation?

No

Perform the

characterisation at the

required level of detail.

Yes

Box 2

Box 1

Identify whether a basic or 

enhanced characterisation is 

required for each livestock 

species based on key

category analyses2

.

Review the emission

estimation methods for each

of the categories1

.

Identify livestock species

applicable to each category.
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10.10 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Dairy cows and milk production: The dairy cow population is estimated separately from other cattle (see 

Table 10.1). Dairy cows are defined in this method as mature cows that are producing milk in commercial 

quantities for human consumption. This definition corresponds to the dairy cow population reported in the FAO 

Production Yearbook. In some countries the dairy cow population is comprised of two well-defined segments: (i) 

high-producing (also called improved) breeds in commercial operations; and (ii) low-producing cows managed 

with traditional methods. These two segments can be combined, or can be evaluated separately by defining two 

dairy cow categories. However, the dairy cow category does not include cows kept principally to produce calves 

for meat or to provide draft power. Low productivity multi-purpose cows should be considered as other cattle. 

Dairy buffalo may be categorized in a similar manner to dairy cows. 

Data on the average milk production of dairy cows are also required. Milk production data are used in estimating 

an emission factor for enteric fermentation using the Tier 2 method. Country-specific data sources are preferred, 

but FAO data may also be used. These data are expressed in terms of kilograms of whole fresh milk produced 

per year per dairy cow. If two or more dairy cow categories are defined, the average milk production per cow is 

required for each category. 

TIER 2: ENHANCED CHARACTERISATION FOR LIVESTOCK 

POPULATIONS 

The Tier 2 livestock characterisation requires detailed information on: 

• Definitions for livestock subcategories; 

• Livestock population by subcategory, with consideration for estimation of annual population as per Tier 1; 

and 

• Feed intake estimates for the typical animal in each subcategory. 

The livestock population subcategories are defined to create relatively homogenous sub-groupings of animals. 

By dividing the population into these subcategories, country-specific variations in age structure and animal 

performance within the overall livestock population can be reflected. 

The Tier 2 characterisation methodology seeks to define animals, animal productivity, diet quality and 

management circumstances to support a more accurate estimate of feed intake for use in estimating methane 

production from enteric fermentation. The same feed intake estimates should be used to provide harmonised 

estimates of manure and nitrogen excretion rates to improve the accuracy and consistency of CH4 and N2O 

emissions from manure management. 

Definitions for livestock subcategories 

It is good practice to classify livestock populations into subcategories for each species according to age, type of 

production, and sex. Representative livestock categories for doing this are shown in Table 10.1. Further 

subcategories are also possible: 

• Cattle and buffalo populations should be classified into at least three main subcategories: mature dairy, other 

mature, and growing cattle. Depending on the level of detail in the emissions estimation method, 

subcategories can be further classified based on animal or feed characteristics. For example, growing / 

fattening cattle could be further subdivided into those cattle that are fed a high-grain diet and housed in dry 

lot vs. those cattle that are grown and finished solely on pasture. 

• Subdivisions similar to those used for cattle and buffalo can be used to further segregate the sheep 

population in order to create subcategories with relatively homogenous characteristics. For example, 

growing lambs could be further segregated into lambs finished on pasture vs. lambs finished in a feedlot. 

The same approach applies to national goat herds. 

• Subcategories of swine could be further segregated based on production conditions. For example, growing 

swine could be further subdivided into growing swine housed in intensive production facilities vs. swine that 

are grown under free-range conditions. 

• Subcategories of poultry could be further segregated based on production conditions. For example, poultry 

could be divided on the basis of production under confined or free-range conditions. 

For large countries or for countries with distinct regional differences, it may be useful to designate regions and 

then define categories within those regions. Regional subdivisions may be used to represent differences in 

climate, feeding systems, diet, and manure management. However, this further segregation is only useful if 

correspondingly detailed data are available on feeding and manure management system usage by these livestock 

categories. 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.11 

TABLE 10.1 

REPRESENTATIVE LIVESTOCK CATEGORIES1,2

Main categories Subcategories 

Mature Dairy Cow or Mature Dairy 

Buffalo 

• High-producing cows that have calved at least once and are used principally for 

milk production 

• Low-producing cows that have calved at least once and are used principally for milk 

production 

Other Mature Cattle or Mature Non-dairy 

Buffalo 

Females: 

• Cows used to produce offspring for meat 

• Cows used for more than one production purpose: milk, meat, draft 

Males: 

• Bulls used principally for breeding purposes 

• Bullocks used principally for draft power 

Growing Cattle or Growing Buffalo • Calves pre-weaning 

• Replacement dairy heifers 

• Growing / fattening cattle or buffalo post-weaning 

• Feedlot-fed cattle on diets containing > 90 % concentrates 

Mature Ewes • Breeding ewes for production of offspring and wool production 

• Milking ewes where commercial milk production is the primary purpose 

Other Mature Sheep (>1 year) • No further sub-categorisation recommended 

Growing Lambs • Intact males 

• Castrates 

• Females 

Mature Swine • Sows in gestation 

• Sows which have farrowed and are nursing young 

• Boars that are used for breeding purposes 

Growing Swine • Nursery 

• Finishing 

• Gilts that will be used for breeding purposes 

• Growing boars that will be used for breeding purposes 

Chickens • Broiler chickens grown for producing meat 

• Layer chickens for producing eggs, where manure is managed in dry systems (e.g., 

high-rise houses) 

• Layer chickens for producing eggs, where manure is managed in wet systems (e.g., 

lagoons) 

• Chickens under free-range conditions for egg or meat production 

Turkeys • Breeding turkeys in confinement systems 

• Turkeys grown for producing meat in confinement systems 

• Turkeys under free-range conditions for meat production 

Ducks • Breeding ducks 

• Ducks grown for producing meat 

Others (for example) • Camels 

• Mules and Asses 

• Llamas, Alpacas 

• Fur bearing animals 

• Rabbits 

• Horses 

• Deer 

• Ostrich 

• Geese 

1

 Source IPCC Expert Group 

2

 Emissions should only be considered for livestock species used to produce food, fodder or raw materials used for industrial processes. 
Volume 4: Agriculture, Forestry and Other Land Use 

10.12 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

For each of the representative animal categories defined, the following information is required: 

• annual average population (number of livestock or poultry as per calculations for Tier 1); 

• average daily feed intake (megajoules (MJ) per day and / or kg per day of dry matter); and 

• methane conversion factor (percentage of feed energy converted to methane). 

Generally, data on average daily feed intake are not available, particularly for grazing livestock. Consequently, 

the following general data should be collected for estimating the feed intake for each representative animal 

category: 

• weight (kg); 

• average weight gain per day (kg)1

; 

• feeding situation: confined, grazing, pasture conditions; 

• milk production per day (kg/day) and fat content (%)2

; 

• average amount of work performed per day (hours day-1); 

• percentage of females that give birth in a year3

; 

• wool growth; 

• number of offspring; and 

• feed digestibility (%). 

Feed intake estimates 

Tier 2 emissions estimates require feed intakes for a representative animal in each subcategory. Feed intake is 

typically measured in terms of gross energy (e.g., megajoules (MJ) per day) or dry matter (e.g., kilograms (kg) 

per day). Dry matter is the amount of feed consumed (kg) after it has been corrected for the water content in the 

complete diet. For example, consumption of 10 kg of a diet that contains 70% dry matter would result in a dry 

matter intake of 7 kg. To support the enteric fermentation Tier 2 method for cattle, buffalo, and sheep (see 

Section 10.3), detailed data requirements and equations to estimate feed intake are included in guidance below. 

Constants in the equations have been combined to simplify overall equation formats. The remainder of this 

subsection presents the typical data requirements and equations used to estimate feed intake for cattle, buffalo, 

and sheep. Feed intake for other species can be estimated using similar country-specific methods appropriate for 

each. 

 For all estimates of feed intake, good practice is to: 

• Collect data to describe the animal’s typical diet and performance in each subcategory; 

• Estimate feed intake from the animal performance and diet data for each subcategory. 

In some cases, the equations may be applied on a seasonal basis, for example under conditions in which 

livestock gain weight in one season and lose weight in another. This approach may require a more refined 

variation of Tier 2 or more complex Tier 3 type methodology. 

The following animal performance data are required for each animal subcategory to estimate feed intake for the 

subcategory: 

• Weight (W), kg: Live-weight data should be collected for each animal subcategory. It is unrealistic to 

perform a complete census of live-weights, so live-weight data should be obtained from representative 

sample studies or statistical databases if these already exist. Comparing live-weight data with slaughterweight data is a useful cross-check to assess whether the live-weight data are representative of country 

conditions. However, slaughter-weight data should not be used in place of live-weight data as it fails to 

account for the complete weight of the animal. Additionally, it should be noted that the relationship 

between live-weight and slaughter-weight varies with breed and body condition. For cattle, buffalo and 

 

1

 This may be assumed to be zero for mature animals. 

2

 Milk production data are required for dairy animals. These can be estimated for non-dairy animals providing milk to 

young, where data are available. 

3

 This is only relevant for mature females. 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.13 

mature sheep, the yearly average weight for each animal category (e.g., mature beef cows) is needed. For 

young sheep, weights are needed at birth, weaning, one year of age or at slaughter if slaughter occurs within 

the year. 

• Average weight gain per day (WG), kg day-1: Data on average weight gain are generally collected for 

feedlot animals and young growing animals. Mature animals are generally assumed to have no net weight 

gain or loss over an entire year. Mature animals frequently lose weight during the dry season or during 

temperature extremes and gain weight during the following season. However, increased emissions 

associated with this weight change are likely to be small. Reduced intakes and emissions associated with 

weight loss are largely balanced by increased intakes and emissions during the periods of gain in body 

weight. 

• Mature weight (MW), kg: The mature weight of the adult animal of the inventoried group is required to 

define a growth pattern, including the feed and energy required for growth. For example, mature weight of a 

breed or category of cattle or buffalo is generally considered to be the body weight at which skeletal 

development is complete. The mature weight will vary among breeds and should reflect the animal’s 

weight when in moderate body condition. This is termed ‘reference weight’ (ACC, 1990) or ‘final shrunk 

body weight’ (NRC, 1996). Estimates of mature weight are typically available from livestock specialists 

and producers. 

• Average number of hours worked per day: For draft animals, the average number of hours worked per 

day must be determined. 

• Feeding situation: The feeding situation that most accurately represents the animal subcategory must be 

determined using the definitions shown below (Table 10.5). If the feeding situation lies between the 

definitions, the feeding situation should be described in detail. This detailed information may be needed 

when calculating the enteric fermentation emissions, because interpolation between the feeding situations 

may be necessary to assign the most appropriate coefficient. Table 10.5 defines the feeding situations for 

cattle, buffalo, and sheep. For poultry and swine, the feeding situation is assumed to be under confinement 

conditions and consequently the activity coefficient (Ca )is assumed to be zero as under these conditions 

very little energy is expended in acquiring feed. Activity coefficients have not been developed for freeranging swine or poultry, but in most instances these livestock subcategories are likely to represent a small 

proportion of the national inventory. 

• Mean winter temperature (oC): Detailed feed intake models consider ambient temperature, wind speed, 

hair and tissue insulation and the heat of fermentation (NRC, 2001; AAC, 1990) and are likely more 

appropriate in Tier 3 applications. A more general relationship adapted from North America data suggest 

adjusting the Cfi of Equation 10.3 for maintenance requirements of open-lot fed cattle in colder climates 

according to the following equation (Johnson, 1986): 

EQUATION 10.2 

COEFFICIENT FOR CALCULATING NET ENERGY FOR MAINTENANCE

Cf (in _ cold) Cf 0.0048 (20 C) i i = + • − °

Where: 

Cfi = a coefficient which varies for each animal category as shown in Table 10.4 (Coefficients for 

calculating NEm), MJ day-1 kg-1

°C = mean daily temperature during winter season 

Considering the average temperature during winter months, net energy for maintenance (NEm) requirements 

may increase by as much as 30% in northern North America. This increase in feed use for maintenance is 

also likely associated with greater methane emissions. 

 

• Average daily milk production (kg day-1): These data are for milking ewes, dairy cows and buffalo. The 

average daily production should be calculated by dividing the total annual production by 365, or reported as 

average daily production along with days of lactation per year, or estimated using seasonal production 

divided by number of days per season. If using seasonal production data, the emission factor must be 

developed for that seasonal period. 

• Fat content (%): Average fat content of milk is required for lactating cows, buffalo, and sheep producing 

milk for human consumption. 

• Percent of females that give birth in a year: This is collected only for mature cattle, buffalo, and sheep. 
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10.14 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

• Number of off spring produced per year: This is relevant to female livestock that have multiple births per 

year (e.g., ewes). 

• Feed digestibility (DE%): The portion of gross energy (GE) in the feed not excreted in the faeces is known 

as digestible feed. The feed digestibility is commonly expressed as a percentage (%) of GE or TDN (total 

digestible nutrients). That percentage of feed that is not digested represents the % of dry matter intake that 

will be excreted as faeces. Typical digestibility values for a range of livestock classes and diet types are 

presented in Table 10.2 as a guideline. For ruminants, common ranges of feed digestibility are 45-55% for 

crop by-products and range lands; 55-75% for good pastures, good preserved forages, and grain 

supplemented forage-based diets; and 75-85% for grain-based diets fed in feedlots. Variations in diet 

digestibility results in major variations in the estimate of feed needed to meet animal requirements and 

consequently associated methane emissions and amounts of manure excreted. It is also important to note 

that digestibility, intake, and growth are co-dependent phenomena. For example, a low digestibility will 

lead to lower feed intake and consequently reduced growth. Conversely, feeds with high digestibility will 

often result in a higher feed intake and increased growth. A 10% error in estimating DE will be magnified to 

12 to 20% when estimating methane emissions and even more (20 to 45%) for manure excretion (volatile 

solids). 

Digestibility data should be based on measured values for the dominant feeds or forages being consumed by 

livestock with consideration for seasonal variation. In general, the digestibility of forages decreases with 

increasing maturity and is typically lowest during the dry season. Due to significant variation, digestibility 

coefficients should be obtained from local scientific data wherever possible. Although a complete census of 

digestibility is considered unrealistic, at a minimum digestibility data from research studies should be 

consulted. While developing the digestibility data, associated feed characteristic data should also be 

recorded when available, such as measured values for Neutral Detergent Fiber (NDF), Acid Detergent Fiber 

(ADF), crude protein, and the presence of anti-nutritional factors (e.g., alkaloids, phenolics, % ash). NDF 

and ADF are feed characteristics measured in the laboratory that are used to indicate the nutritive value of 

the feed for ruminant livestock. Determination of these values can enable DE to be predicted as defined in 

the recent dairy NRC (2001). The concentration of crude protein in the feed can be used in the process of 

estimating nitrogen excretion (Section 10.5.2). 

• Average annual wool production per sheep (kg yr-1): The amount of wool produced in kilograms (after 

drying out but before scouring) is needed to estimate the amount of energy allocated for wool production. 

TABLE 10.2 

REPRESENTATIVE FEED DIGESTIBILITY FOR VARIOUS LIVESTOCK CATEGORIES

Main categories Class Digestibility (DE%) 

Swine • Mature Swine – confinement 

• Growing Swine - confinement 

• Swine – free range 

• 70 - 80% 

• 80 - 90% 

• 50 - 70% 1

Cattle and other 

ruminants 

• Feedlot animals fed with > 90% 

concentrate diet; 

• Pasture fed animals; 

• Animals fed – low quality forage 

• 75 - 85% 

• 55 - 75% 

• 45 - 55% 

Poultry • Broiler Chickens –confinement 

• Layer Hens – confinement 

• Poultry – free range 

• Turkeys – confinement 

• Geese – confinement 

• 85 - 93% 

• 70 - 80% 

• 55 - 90% 1

• 85 - 93% 

• 80 - 90% 

1 The range in digestibility of feed consumed by free-range swine and poultry is extremely variable due to the selective 

nature of these diets. Often it is likely that the amount of manure produced in these classes will be limited by the amount 

of feed available for consumption as opposed to its degree of digestibility. In instances where feed is not limiting and high 

quality feed sources are readily accessible for consumption, digestibility may approach values that are similar to those 

measured under confinement conditions. 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.15 

Gross energy calculations 

Animal performance and diet data are used to estimate feed intake, which is the amount of energy (MJ/day) an 

animal needs for maintenance and for activities such as growth, lactation, and pregnancy. For inventory 

compilers who have well-documented and recognised country-specific methods for estimating intake based on 

animal performance data, it is good practice to use the country-specific methods. The following section provides 

methods for estimating gross energy intake for the key ruminant categories of cattle, buffalo and sheep. The 

equations listed in Table 10.3 are used to derive this estimate. If no country-specific methods are available, 

intake should be calculated using the equations listed in Table 10.3. As shown in the table, separate equations are 

used to estimate net energy requirements for sheep as compared with cattle and buffalo. The equations used to 

calculate GE are as follows: 

TABLE 10.3 

SUMMARY OF THE EQUATIONS USED TO ESTIMATE DAILY GROSS ENERGY INTAKE FOR CATTLE,

BUFFALO AND SHEEP

Metabolic functions and 

other estimates 

Equations for cattle and 

buffalo 

Equations for sheep 

Maintenance (NEm) Equation 10.3 Equation 10.3 

Activity (NEa) Equation 10.4 Equation 10.5 

Growth (NEg) Equation 10.6 Equation 10.7 

Lactation (NEl)* Equation 10.8 Equations 10.9 and 10.10 

Draft Power (NEwork) Equation 10.11 NA 

Wool Production (NEwool) NA Equation 10.12 

Pregnancy (NEp)* Equation 10.13 Equation 10.13 

Ratio of net energy available 

in diet for maintenance to 

digestible energy consumed 

(REM) 

Equation 10.14 Equation 10.14 

Ratio of net energy available 

for growth in a diet to 

digestible energy consumed 

(REG) 

Equation 10.15 Equation 10.15 

Gross Energy Equation 10.16 Equation 10.16 

Source: Cattle and buffalo equations based on NRC (1996) and sheep based on AFRC (1993). 

NA means ‘not applicable’. 

* Applies only to the proportion of females that give birth. 

Net energy for maintenance: (NEm ) is the net energy required for maintenance, which is the amount of energy 

needed to keep the animal in equilibrium where body energy is neither gained nor lost (Jurgen, 1988). 

EQUATION 10.3 

NET ENERGY FOR MAINTENANCE

( )

0.75 NE Cf Weight m i = •

Where: 

NEm = net energy required by the animal for maintenance, MJ day-1

Cfi = a coefficient which varies for each animal category as shown in Table 10.4 (Coefficients for 

calculating NEm), MJ day-1 kg-1

Weight = live-weight of animal, kg 

Net energy for activity: (NEa) is the net energy for activity, or the energy needed for animals to obtain their food, 

water and shelter. It is based on its feeding situation rather than characteristics of the feed itself. As presented in 

Table 10.3, the equation for estimating NEa for cattle and buffalo is different from the equation used for sheep. 

Both equations are empirical with different definitions for the coefficient Ca. 
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10.16 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

EQUATION 10.4 

NET ENERGY FOR ACTIVITY (FOR CATTLE AND BUFFALO) 

NEa = Ca • NE m

Where: 

NEa = net energy for animal activity, MJ day-1

Ca = coefficient corresponding to animal’s feeding situation (Table 10.5, Activity coefficients) 

NEm = net energy required by the animal for maintenance (Equation 10.3), MJ day-1

EQUATION 10.5 

NET ENERGY FOR ACTIVITY (FOR SHEEP) 

NE C (weight) a a = •

Where: 

NEa = net energy for animal activity, MJ day-1

Ca = coefficient corresponding to animal’s feeding situation (Table 10.5), MJ day-1 kg-1

weight = live-weight of animal, kg 

For Equations 10.4 and 10.5, the coefficient Ca corresponds to a representative animal’s feeding situation as 

described earlier. Values for Ca are shown in Table 10.5. If a mixture of these feeding situations occurs during 

the year, NEa must be weighted accordingly. 

TABLE 10.4 

COEFFICIENTS FOR CALCULATING NET ENERGY FOR MAINTENANCE ( NEM ) 

Animal category Cfi (MJ d-1 kg-1) Comments 

Cattle/Buffalo (non-lactating cows) 0.322 

Cattle/Buffalo (lactating cows) 0.386 This value is 20% higher for 

maintenance during lactation 

Cattle/Buffalo (bulls) 0.370 This value is 15% higher for 

maintenance of intact males 

Sheep (lamb to 1 year) 0.236 This value can be increased by 15% 

for intact males 

Sheep (older than 1 year) 0.217 This value can be increased by 15% 

for intact males. 

Source: NRC (1996) and AFRC (1993). 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.17 

TABLE 10.5 

ACTIVITY COEFFICIENTS CORRESPONDING TO ANIMAL’S FEEDING SITUATION

Situation Definition Ca

Cattle and Buffalo (unit for Ca is dimensionless) 

Stall 

Animals are confined to a small area (i.e., tethered, pen, 

barn) with the result that they expend very little or no 

energy to acquire feed. 

 0.00 

Pasture Animals are confined in areas with sufficient forage 

requiring modest energy expense to acquire feed. 0.17 

Grazing large areas Animals graze in open range land or hilly terrain and 

expend significant energy to acquire feed. 0.36 

Sheep (unit for Ca = MJ d-1 kg-1) 

Housed ewes Animals are confined due to pregnancy in final trimester 

(50 days). 0.0090 

Grazing flat pasture Animals walk up to 1000 meters per day and expend very 

little energy to acquire feed. 0.0107 

Grazing hilly pasture Animals walk up to 5,000 meters per day and expend 

significant energy to acquire feed. 0.0240 

Housed fattening lambs Animals are housed for fattening. 0.0067 

Source: NRC (1996) and AFRC (1993). 

Net energy for growth: (NEg) is the net energy needed for growth (i.e., weight gain). Equation 10.6 is based on 

NRC (1996). Equation 10.7 is based on Gibbs et al. (2002). Constants for conversion from calories to joules and 

live to shrunk and empty body weight have been incorporated into the equation. 

EQUATION 10.6 

NET ENERGY FOR GROWTH (FOR CATTLE AND BUFFALO) 

1.097

0.75

22.02 WG

C MW

BW NEg ⎟ • ⎠

⎞ ⎜

⎝

⎛

• = •

Where: 

NEg = net energy needed for growth, MJ day-1

BW = the average live body weight (BW) of the animals in the population, kg 

C = a coefficient with a value of 0.8 for females, 1.0 for castrates and 1.2 for bulls (NRC, 1996) 

MW = the mature live body weight of an adult female in moderate body condition, kg 

WG = the average daily weight gain of the animals in the population, kg day-1 

EQUATION 10.7 

NET ENERGY FOR GROWTH (FOR SHEEP) 

( ( ))

365

0.5 lamb i f

g

WG a b BW BW

NE • + + =

Where: 

NEg = net energy needed for growth, MJ day-1

WGlamb = the weight gain (BWf – BWi), kg yr-1

BWi = the live bodyweight at weaning, kg 
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10.18 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

BWf = the live bodyweight at 1-year old or at slaughter (live-weight) if slaughtered prior to 1 year of age, 

kg 

a, b = constants as described in Table 10.6. 

Note that lambs will be weaned over a period of weeks as they supplement a milk diet with pasture feed or 

supplied feed. The time of weaning should be taken as the time at which they are dependent on milk for half 

their energy supply. 

The NEg equation used for sheep includes two empirical constants (a and b) that vary by animal species/category 

(Table 10.6). 

TABLE 10.6 

CONSTANTS FOR USE IN CALCULATING NEG FOR SHEEP

Animal species/category 

a 

(MJ kg-1) 

b 

(MJ kg-2) 

Intact males 2.5 0.35 

Castrates 4.4 0.32 

Females 2.1 0.45 

Source: AFRC (1993). 

Net energy for lactation: (NEl ) is the net energy for lactation. For cattle and buffalo the net energy for lactation 

is expressed as a function of the amount of milk produced and its fat content expressed as a percentage (e.g., 4%) 

(NRC, 1989): 

EQUATION 10.8 

NET ENERGY FOR LACTATION (FOR BEEF CATTLE, DAIRY CATTLE AND BUFFALO) 

NE = Milk • (1.47 + 0.40 • Fat) 1

Where: 

NEl = net energy for lactation, MJ day-1 

Milk = amount of milk produced, kg of milk day-1

Fat = fat content of milk, % by weight. 

Two methods for estimating the net energy required for lactation (NEl) are presented for sheep. The first method 

(Equation 10.9) is used when the amount of milk produced is known, and the second method (Equation 10.8) is 

used when the amount of milk produced is not known. Generally, milk production is known for ewes kept for 

commercial milk production, but it is not known for ewes that suckle their young to weaning. With a known 

amount of milk production, the total annual milk production is divided by 365 days to estimate the average daily 

milk production in kg/day (Equation 10.9). When milk production is not known, AFRC (1990) indicates that for 

a single birth, the milk yield is about 5 times the weight gain of the lamb. For multiple births, the total annual 

milk production can be estimated as five times the increase in combined weight gain of all lambs birthed by a 

single ewe. The daily average milk production is estimated by dividing the resulting estimate by 365 days as 

shown in Equation 10.10. 

EQUATION 10.9 

NET ENERGY FOR LACTATION FOR SHEEP (MILK PRODUCTION KNOWN) 

NE Milk EVmilk = • 1

Where: 

NEl = net energy for lactation, MJ day-1 

Milk = amount of milk produced, kg of milk day-1
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.19 

EVmilk = the net energy required to produce 1 kg of milk. A default value of 4.6 MJ/kg (AFRC, 1993) can 

be used which corresponds to a milk fat content of 7% by weight 

EQUATION 10.10 

NET ENERGY FOR LACTATION FOR SHEEP (MILK PRODUCTION UNKNOWN) 

( )

milk wean EV WG NE • ⎥

⎦

⎤ ⎢

⎣

⎡ • = 365

5

1

Where: 

NEl = net energy for lactation, MJ day-1

WG wean = the weight gain of the lamb between birth and weaning, kg 

EVmilk = the energy required to produce 1 kg of milk, MJ kg-1. A default value of 4.6 MJ kg-1 (AFRC, 

1993) can be used. 

Net energy for work: (NEwork ) is the net energy for work. It is used to estimate the energy required for draft 

power for cattle and buffalo. Various authors have summarised the energy intake requirements for providing 

draft power (e.g., Lawrence, 1985; Bamualim and Kartiarso, 1985; and Ibrahim, 1985). The strenuousness of the 

work performed by the animal influences the energy requirements, and consequently a wide range of energy 

requirements have been estimated. The values by Bamualim and Kartiarso show that about 10 percent of a day’s 

NEm requirements are required per hour for typical work for draft animals. This value is used as follows: 

EQUATION 10.11 

NET ENERGY FOR WORK (FOR CATTLE AND BUFFALO) 

NE NEm Hours work = 0.10 • •

Where: 

NEwork = net energy for work, MJ day-1

NEm = net energy required by the animal for maintenance (Equation 10.3), MJ day-1

Hours = number of hours of work per day 

Net energy for wool production: (NEwool ) is the average daily net energy required for sheep to produce a year of 

wool. The NEwool is calculated as follows: 

EQUATION 10.12 

NET ENERGY TO PRODUCE WOOL (FOR SHEEP) 

⎟

⎠

⎞ ⎜

⎝

⎛ • = 365

wool wool

wool

EV Production NE 

Where: 

NEwool = net energy required to produce wool, MJ day-1

EVwool = the energy value of each kg of wool produced (weighed after drying but before scouring), MJ 

kg-1. A default value of 24 MJ kg-1 (AFRC, 1993) can be used for this estimate. 

Productionwool = annual wool production per sheep, kg yr-1

Net energy for pregnancy: (NEp) is the energy required for pregnancy. For cattle and buffalo, the total energy 

requirement for pregnancy for a 281-day gestation period averaged over an entire year is calculated as 10% of 

NEm. For sheep, the NEp requirement is similarly estimated for the 147-day gestation period, although the 

percentage varies with the number of lambs born (Table 10.7, Constant for Use in Calculating NEp in Equation 

10.13). Equation 10.13 shows how these estimates are applied. 
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10.20 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

EQUATION 10.13 

NET ENERGY FOR PREGNANCY (FOR CATTLE/BUFFALO AND SHEEP) 

NEp = Cpregnancy • NEm

Where: 

NEp = net energy required for pregnancy, MJ day-1

Cpregnancy = pregnancy coefficient (see Table 10.7) 

NEm = net energy required by the animal for maintenance (Equation 10.3), MJ day-1

TABLE 10.7 

CONSTANTS FOR USE IN CALCULATING NEP IN EQUATION 10.13 

Animal category Cpregnancy 

Cattle and Buffalo 0.10 

Sheep 

 Single birth 0.077 

 Double birth (twins) 0.126 

 Triple birth or more (triplets) 0.150 

Source: Estimate for cattle and buffalo developed from data in NRC (1996). 

Estimates for sheep developed from data in AFRC (1993), taking into account the 

inefficiency of energy conversion. 

When using NEp to calculate GE for cattle and sheep, the NEp estimate must be weighted by the portion of the 

mature females that actually go through gestation in a year. For example, if 80% of the mature females in the 

animal category give birth in a year, then 80% of the NEp value would be used in the GE equation below. 

To determine the proper coefficient for sheep, the portion of ewes that have single births, double births, and 

triple births is needed to estimate an average value for Cpregnancy. If these data are not available, the coefficient 

can be calculated as follows: 

• If the number of lambs born in a year divided by the number of ewes that are pregnant in a year is less than 

or equal to 1.0, then the coefficient for single births can be used. 

• If the number of lambs born in a year divided by the number of ewes that are pregnant in a year exceeds 1.0 

and is less than 2.0, calculate the coefficient as follows: 

Cpregnancy = [(0.126 • Double birth fraction) + (0.077 • Single birth fraction)] 

Where: 

Double birth fraction = [(lambs born / pregnant ewes) – 1] 

Single birth fraction = [1 – Double birth fraction] 

Ratio of net energy available in diet for maintenance to digestible energy consumed (REM): For cattle, buffalo 

and sheep, the ratio of net energy available in a diet for maintenance to digestible energy consumed (REM ) is 

estimated using the following equation (Gibbs and Johnson, 1993): 

EQUATION 10.14 

RATIO OF NET ENERGY AVAILABLE IN A DIET FOR MAINTENANCE TO DIGESTIBLE ENERGY 

CONSUMED 

( ) [ ( ) ] ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ = − • • + • • − − −

%

25.4 1.123 4.092 10 % 1.126 10 % 3 5 2

DE

REM DE DE

Where: 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.21 

REM = ratio of net energy available in a diet for maintenance to digestible energy consumed 

DE% = digestible energy expressed as a percentage of gross energy 

Ratio of net energy available for growth in a diet to digestible energy consumed (REG): For cattle, buffalo and 

sheep the ratio of net energy available for growth (including wool growth) in a diet to digestible energy 

consumed (REG ) is estimated using the following equation (Gibbs and Johnson, 1993): 

EQUATION 10.15 

RATIO OF NET ENERGY AVAILABLE FOR GROWTH IN A DIET TO DIGESTIBLE ENERGY CONSUMED

( ) [ ( ) ] ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ = − • • + • • − − −

%

37.4 1.164 5.160 10 % 1.308 10 % 3 5 2

DE

REG DE DE

Where: 

REG = ratio of net energy available for growth in a diet to digestible energy consumed 

DE% = digestible energy expressed as a percentage of gross energy 

Gross energy, GE: As shown in Equation 10.16, GE requirement is derived based on the summed net energy 

requirements and the energy availability characteristics of the feed(s). Equation 10.16 represents good practice

for calculating GE requirements for cattle and sheep using the results of the equations presented above. 

In using Equation 10.16, only those terms relevant to each animal category are used (see Table 10.3). 

EQUATION 10.16 

GROSS ENERGY FOR CATTLE/BUFFALO AND SHEEP

⎥

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ +

+⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ + + + +

=

100

%

1

DE

REG

NE NE

REM

NE NE NE NE NE

GE

m a work p g wool

Where: 

GE = gross energy, MJ day-1

NEm = net energy required by the animal for maintenance (Equation 10.3), MJ day-1

NEa = net energy for animal activity (Equations 10.4 and 10.5), MJ day-1

NEl = net energy for lactation (Equations 10.8, 10.9, and 10.10), MJ day-1

NEwork = net energy for work (Equation 10.11), MJ day-1

NEp = net energy required for pregnancy (Equation 10.13), MJ day-1

REM = ratio of net energy available in a diet for maintenance to digestible energy consumed (Equation 

10.14) 

NEg = net energy needed for growth (Equations 10.6 and 10.7), MJ day-1

NEwool = net energy required to produce a year of wool (Equation 10.12), MJ day-1

REG = ratio of net energy available for growth in a diet to digestible energy consumed (Equation 10.15) 

DE%= digestible energy expressed as a percentage of gross energy 

Once the values for GE are calculated for each animal subcategory, the feed intake in units of kilograms of dry 

matter per day (kg day-1) should also be calculated. To convert from GE in energy units to dry matter intake 

(DMI), divide GE by the energy density of the feed. A default value of 18.45 MJ kg-1 of dry matter can be used 

if feed-specific information is not available. The resulting daily dry matter intake should be in the order of 2% to 

3% of the body weight of the mature or growing animals. In high producing milk cows, intakes may exceed 4% 

of body weight. 
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10.22 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Feed intake estimates using a simplified Tier 2 method 

Prediction of DMI for cattle based on body weight and estimated dietary net energy concentration (NEma) or 

digestible energy values (DE%): It is also possible to predict dry matter intake for mature and growing cattle 

based on body weight of the animal and either the NEma concentration of the feed (NRC, 1996) or DE%. 

Dietary NEma concentration can range from 3.0 to 9.0 MJ kg-1 of dry matter. Typical values for high, moderate 

and low quality diets are presented in Table 10.8. These figures can also be used to estimate NEma values for 

mixed diets based on estimate of diet quality. For example, a mixed forage-grain diet could be assumed to have 

a NEma value similar to that of a high-quality forage diet. A mixed grain-straw diet could be assumed to have a 

NEma value similar to that of a moderate quality forage. Nutritionists within specific geographical areas should 

be able to provide advice with regard to the selection of NEma values that are more representative of locally fed 

diets. 

Dry matter intake for growing and finishing cattle is estimated using the following equation: 

EQUATION 10.17 

ESTIMATION OF DRY MATTER INTAKE FOR GROWING AND FINISHING CATTLE

( )

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ • − • − = •

ma

ma ma

NE

NE NE DMI BW 0.2444 0.0111 0.472 2

0.75

Where: 

DMI = dry matter intake, kg day-1

BW = live body weight, kg 

NEma = estimated dietary net energy concentration of diet or default values in Table 10.8, MJ kg-1

Dry matter intake for mature beef cattle is estimated using the following equation: 

EQUATION 10.18a 

ESTIMATION OF DRY MATTER INTAKE FOR MATURE BEEF CATTLE

( )

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ • + = •

ma

ma

NE

NE DMI BW 0.0119 0.1938 2

0.75

Where: 

DMI = dry matter intake, kg day-1

BW = live body weight, kg 

NEma = estimated dietary net energy concentration of diet or default values given in Table 10.8, MJ kg-1

For mature dairy cows consuming low quality, often tropical forages, the following alternative equation for 

estimating dry matter intake based on DE% can be used (NRC, 1989): 

EQUATION 10.18b 

ESTIMATION OF DRY MATTER INTAKE FOR MATURE DAIRY COWS

( )

( ) ⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎣

⎡

⎟

⎠

⎞ ⎜

⎝

⎛ −

⎟

⎠

⎞ ⎜

⎝

⎛ •

=

100

100 %

500

5.4

DE

BW

DMI

Where: 

DMI = dry matter intake, kg day-1

BW = live body weight, kg 

DE%= digestible energy expressed as a percentage of gross energy (typically 45-55% for low quality 

forages) 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.23 

Equations 10.17, 10.18a, and 10.18b provide a good check to the main Tier 2 method to predict feed intake. 

They can be viewed as asking ‘what is an expected intake for a given diet quality?’ and used to independently 

predict DMI from BW and diet quality (NEma or DE%). In contrast, the main Tier 2 method predicts DMI based 

on how much feed must be consumed to meet estimated requirements (i.e., NEm and NEg) and does not consider 

the biological capacity of the animal to in fact consume the predicted quantity of feed. Consequently, the 

simplified Tier 2 method can be used to confirm that DMI values derived from the main Tier 2 method are 

biologically realistic. These estimates are also subject to the cross check that dry matter intake should be in the 

order of 2% to 3% of the bodyweight of the mature or growing animals. 

 

TABLE 10.8 

EXAMPLES OF NEMA CONTENT OF TYPICAL DIETS FED TO CATTLE FOR ESTIMATION OF 

DRY MATTER INTAKE IN EQUATIONS 10.17 AND 10.18 

Diet type NEma (MJ (kg dry matter)-1)

High grain diet > 90% 7.5 - 8.5 

High quality forage (e.g., vegetative 

legumes & grasses ) 6.5 - 7.5 

Moderate quality forage (e.g., mid season 

legume & grasses) 5.5 - 6.5 

Low quality forage (e.g., straws, mature 

grasses) 3.5 - 5.5 

Source: Estimates obtained from predictive models in NRC (1996), NEma can also be estimated using 

the equation: NEma = REM x 18.45 x DE% / 100. 

10.2.3 Uncertainty assessment 

The first step in collecting data should be to investigate existing national statistics, industry sources, research 

studies and FAO statistics. The uncertainty associated with populations will vary widely depending on source, 

but should be known within +20%. Often, national livestock population statistics already have associated 

uncertainty estimates in which case these should be used. If published data are not available from these sources, 

interviews of key industry and academic experts can be undertaken. Estimates of digestibility are also 

particularly important in Tier 2 estimates of gross energy intake. Uncertainty estimates for digestibility 

estimates may be as high as +20%. Volume 1, Chapter 3 (Uncertainties) describes how to elicit expert 

judgement for uncertainty ranges. Similar expert elicitation protocols can be used to obtain the information 

required for the livestock characterisation if published data and statistics are not available. 

10.2.4 Characterisation for livestock without species: 

Specific emission estimation methods 

Some countries may have domesticated livestock for which there are currently no Tier 1 or Tier 2 emissions 

estimating methods (e.g., llamas, alpacas, wapiti, emus, and ostriches). Good practice in estimating emissions 

from these livestock is to first assess whether their emissions are likely to be significant enough to warrant 

characterising them and developing country-specific emission factors. Volume 1, Chapter 4 (Methodological 

Choice and Identification of Key Categories) presents guidance for assessing the significance of individual 

source categories within the national inventory. Similar approaches can be used to assess the importance of subsource categories (i.e. species) within a source category. If the emissions from a particular sub-species are 

determined to be significant, then country-specific emission factors should be developed, and a characterisation 

should be performed to support the development of the emission factors. Research into the estimation of 

emission levels from these non-characterized species should be encouraged. The data and methods used to 

characterise the animals should be well documented. 

As emissions estimation methods are not available for these animals, approximate emission factors based on 

‘order of magnitude calculations’ are appropriate for conducting the assessment of the significance of their 

emissions. One approach for developing the approximate emission factors is to use the Tier 1 emissions factor 

for an animal with a similar digestive system and to scale the emissions factor using the ratio of the weights of 

the animals raised to the 0.75 power. The Tier 1 emission factors can be classified by digestive system as follows: 
Volume 4: Agriculture, Forestry and Other Land Use 

10.24 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

• Ruminant animals: Cattle, Buffalo, Sheep, Goats, Camels 

• Non-ruminant herbivores: Horses, Mules/Asses 

• Poultry: Chickens, Ducks, Turkeys, Geese 

• Non-poultry monogastric animals: Swine 

For example, an approximate enteric fermentation methane emissions factor for alpacas could be estimated from 

the emissions factor for sheep (also a ruminant animal) as follows: 

 Approximate emissions factor = [(alpaca weight) / (sheep weight)]0.75 • sheep emissions factor 

Similarly, an approximate manure methane emissions factor for ostriches could be estimated using the Tier 1 

emission factor for chickens. Approximate emission factors developed using this method can only be used to 

assess the significance of the emissions from the animals, and are not considered sufficiently accurate for 

estimating emissions as part of a national inventory. 

10.3 METHANE EMISSIONS FROM ENTERIC 

FERMENTATION 

Methane is produced in herbivores as a by-product of enteric fermentation, a digestive process by which 

carbohydrates are broken down by micro-organisms into simple molecules for absorption into the bloodstream. 

The amount of methane that is released depends on the type of digestive tract, age, and weight of the animal, and 

the quality and quantity of the feed consumed. Ruminant livestock (e.g., cattle, sheep) are major sources of 

methane with moderate amounts produced from non-ruminant livestock (e.g., pigs, horses). The ruminant gut 

structure fosters extensive enteric fermentation of their diet. 

Digestive system 

The type of digestive system has a significant influence on the rate of methane emission. Ruminant livestock 

have an expansive chamber, the rumen, at the fore-part of their digestive tract that supports intensive microbial 

fermentation of their diet which yields several nutritional advantages including the capacity to digest cellulose in 

their diet. The main ruminant livestock are cattle, buffalo, goats, sheep, deer and camelids. Non-ruminant 

livestock (horses, mules, asses) and monogastric livestock (swine) have relatively lower methane emissions 

because much less methane-producing fermentation takes place in their digestive systems. 

Feed intake 

Methane is produced by the fermentation of feed within the animal's digestive system. Generally, the higher the 

feed intake, the higher the methane emission. Although, the extent of methane production may also be affected 

by the composition of the diet. Feed intake is positively related to animal size, growth rate, and production (e.g., 

milk production, wool growth, or pregnancy). 

To reflect the variation in emission rates among animal species, the population of animals should be divided into 

subgroups, and an emission rate per animal is estimated for each subgroup. Types of population subgroups are 

provided in Section 10.2 (Livestock and Feed Characterisation). The amount of methane emitted by a 

population subgroup is calculated by multiplying the emission rate per animal by the number of animals within 

the subgroup. 

Natural wild ruminants are not considered in the derivation of a country’s emission estimate. Emissions should 

only be considered from animals under domestic management (e.g., farmed deer, elk, and buffalo). 

10.3.1 Choice of method 

It is good practice to choose the method for estimating methane emissions from enteric fermentation according 

to the decision tree in Figure 10.2. The method for estimating methane emission from enteric fermentation 

requires three basic steps: 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.25 

Figure 10.2 Decision Tree for CH4 Emissions from Enteric Fermentation 

Start

Is enhanced

livestock characterization

available?

Collect enhanced

species characterization

data for Tier 2 approach.

Estimate emissions

for the species

using Tier 1 approach.

No

Note:

1: See Volume 1 Chapter 4, "Methodological Choice and Identification of Key Categories" (noting Section 4.1.2 on limited resources), for 

discussion of key categories and use of decision trees.

2: As a rule of thumb, a livestock species would be significant if it accounts for 25-30% or more of emissions from the source category.

Is enteric 

fermentation

a key category1

 and is the 

species significant2

?

No

Yes

Estimate emissions for

the species using Tier 2

approach.

No

Yes

Box 2: Tier 2

Box 1: Tier 1

Yes

Estimate emissions for the

species using Tier 3

approach.

Do you have a

country-specific Tier 3 

methodology?

Box 3: Tier 3
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10.26 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Step 1: Divide the livestock population into subgroups and characterize each subgroup as described in Section 

10.2. It is recommended that national experts use annual averages estimated with consideration for the impact of 

production cycles and seasonal influences on population numbers. 

Step 2: Estimate emission factors for each subgroup in terms of kilograms of methane per animal per year. 

Step 3: Multiply the subgroup emission factors by the subgroup populations to estimate subgroup emission, and 

sum across the subgroups to estimate total emission. 

These three steps can be performed at varying levels of detail and complexity. This chapter presents the 

following three approaches: 

Tier 1 

A simplified approach that relies on default emission factors either drawn from the literature or calculated using 

the more detailed Tier 2 methodology. The Tier 1 method is likely to be suitable for most animal species in 

countries where enteric fermentation is not a key source category, or where enhanced characterization data are 

not available. When approximate enteric emissions are derived by extrapolation from main livestock categories 

they should be considered to be a Tier 1 method. 

Tier 2 

A more complex approach that requires detailed country-specific data on gross energy intake and methane 

conversion factors for specific livestock categories. The Tier 2 method should be used if enteric fermentation is 

a key source category for the animal category that represents a large portion of the country’s total emissions. 

Tier 3 

Some countries for which livestock emissions are particularly important may wish to go beyond the Tier 2 

method and incorporate additional country-specific information in their estimates. This approach could employ 

the development of sophisticated models that consider diet composition in detail, concentration of products 

arising from ruminant fermentation, seasonal variation in animal population or feed quality and availability, and 

possible mitigation strategies. Many of these estimates would be derived from direct experimental measurements. 

Although countries are encouraged to go beyond the Tier 2 method presented below when data are available, 

these more complex analyses are only briefly discussed here. A Tier 3 method should be subjected to a wide 

degree of international peer review such as that which occurs in peer-reviewed publications to ensure that they 

improve the accuracy and / or precision of estimates. 

Countries with large populations of domesticated animal species for which there are no IPCC default emission 

factors (e.g., llamas and alpacas) are encouraged to develop national methods that are similar to the Tier 2 

method and are based on well-documented research (if it is determined that emissions from these livestock are 

significant). The approach is described in Section 10.2.4 under the heading ‘Characterisation for livestock 

without species-specific emission estimation methods’ for more information. 

Table 10.9 summarises the suggested approaches for the livestock emissions included in this inventory. 

10.3.2 Choice of emission factors 

Tier 1 Approach for methane emissions from Enteric Fermentation 

This Tier 1 method is simplified so that only readily-available animal population data are needed to estimate 

emissions. Default emission factors are presented for each of the recommended population subgroups. Each 

step is discussed in turn. 

Step 1: Animal population 

The animal population data should be obtained using the approach described in Section 10.2. 

Step 2: Emission factors 

The purpose of this step is to select emission factors that are most appropriate for the country's livestock 

characteristics. Default emission factors for enteric fermentation have been drawn from previous studies, and are 

organised by region for ease of use. 

The data used to estimate the default emission factors for enteric fermentation are presented in Annex 10A.1 at 

the end of this section. 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.27 

TABLE 10.9 

SUGGESTED EMISSIONS INVENTORY METHODS FOR ENTERIC FERMENTATION 

Livestock Suggested emissions inventory methods 

Dairy Cow Tier 2a/Tier 3 

Other Cattle Tier 2a/Tier 3 

Buffalo Tier 1/Tier 2 

Sheep Tier 1/Tier 2 

Goats Tier 1 

Camels Tier 1 

Horses Tier 1 

Mules and Asses Tier 1 

Swine Tier 1 

Poultry Not developed 

Other (e.g., Llamas, 

Alpacas, Deer) Tier 1 

a The Tier 2 method is recommended for countries with large livestock populations. Implementing 

the Tier 2 method for additional livestock subgroups may be desirable when the category emissions 

are a large portion of total methane emissions for the country. 

Table 10.10 shows the enteric fermentation emission factors for each of the animal species except cattle. As 

shown in the table, emission factors for sheep and swine vary for developed and developing countries. The 

differences in the emission factors are driven by differences in feed intake and feed characteristic assumptions 

(see Annex 10A.1). Table 10.11 presents the enteric fermentation emission factors for cattle. A range of 

emission factors is shown for typical regional conditions. As shown in the table, the emission factors vary by 

over a factor of four on a per head basis. 

While the default emission factors shown in Table 10.11 are broadly representative of the emission rates within 

each of the regions described, emission factors vary within each region. Animal size and milk production are 

important determinants of emission rates for dairy cows. Relatively smaller dairy cows with low levels of 

production are found in Asia, Africa, and the Indian subcontinent. Relatively larger dairy cows with high levels 

of production are found in North America and Western Europe. 

Animal size and population structure are important determinants of emission rates for other cattle. Relatively 

smaller other cattle are found in Asia, Africa, and the Indian subcontinent. Also, many of the other cattle in 

these regions are young. Other cattle in North America, Western Europe and Oceania are larger, and young 

cattle constitute a smaller portion of the population. 

To select emission factors from Tables 10.10 and 10.11, identify the region most applicable to the country being 

evaluated. Scrutinise the tabulations in Annex 10A.1 to ensure that the underlying animal characteristics such as 

weight, growth rate and milk production used to develop the emission factors are similar to the conditions in the 

country. The data collected on the average annual milk production by dairy cows should be used to help select a 

dairy cow emission factor. If necessary, interpolate between dairy cow emission factors shown in the table using 

the data collected on average annual milk production per head. 

Note that using the same Tier 1 emission factors for the inventories of successive years means that no allowance 

is being made for changing livestock productivity, such as increasing milk productivity or trend in live weight. If 

it is important to capture the trend in methane emission that results from a trend in livestock productivity, then 

livestock emissions can become a key source category based on trend and a Tier 2 calculation should be used. 
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10.28 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.10 

ENTERIC FERMENTATION EMISSION FACTORS FOR TIER 1 METHOD1

(KG CH4 HEAD-1 YR-1) 

Livestock Developed countries Developing 

countries Liveweight 

Buffalo 55 55 300 kg 

Sheep 8 5 65 kg - developed countries; 

45 kg - developing countries 

Goats 5 5 40 kg 

Camels 46 46 570 kg 

Horses 18 18 550 kg 

Mules and Asses 10 10 245 kg 

Deer 20 20 120 kg 

Alpacas 8 8 65 kg 

Swine 1.5 1.0 

Poultry Insufficient data for 

calculation 

Insufficient data for 

calculation 

Other (e.g., Llamas) To be determined1 To be determined1 

All estimates have an uncertainty of +30-50%. 

Sources: Emission factors for buffalo and camels from Gibbs and Johnson (1993). Emission factors for other livestock from Crutzen et 

al., (1986), Alpacas from Pinares-Patino et al., 2003; Deer from Clark et al., 2003 . 

1 One approach for developing the approximate emission factors is to use the Tier 1 emissions factor for an animal with a similar

digestive system and to scale the emissions factor using the ratio of the weights of the animals raised to the 0.75 power. Liveweight 

values have been included for this purpose. Emission factors should be derived on the basis of characteristics of the livestock and feed 

of interest and should not be restricted solely to within regional characteristics. 

Step 3: Total emission 

To estimate total emission, the selected emission factors are multiplied by the associated animal population 

(Equation 10.19) and summed (Equation 10.20): 

EQUATION 10.19 

ENTERIC FERMENTATION EMISSIONS FROM A LIVESTOCK CATEGORY

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = • 6

( )

( ) 10

T

T

N

Emissions EF

Where: 

Emissions = methane emissions from Enteric Fermentation, Gg CH4 yr-1

EF(T) = emission factor for the defined livestock population, kg CH4 head-1 yr-1 

N(T) = the number of head of livestock species / category T in the country 

T = species/category of livestock 

EQUATION 10.20

TOTAL EMISSIONS FROM LIVESTOCK ENTERIC FERMENTATION

= ∑

i

Total CH4Enteric Ei

Where: 

Total CH4Enteric = total methane emissions from Enteric Fermentation, Gg CH4 yr-1

Ei = is the emissions for the i

th livestock categories and subcategories 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.29 

TABLE 10.11 

TIER 1 ENTERIC FERMENTATION EMISSION FACTORS FOR CATTLE1

Regional characteristics Cattle 

category 

Emission 

factor 2,3

(kg CH4 

head-1 yr-1) 

Comments 

North America: Highly productive commercialized 

dairy sector feeding high quality 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 a small part of the population. 

Dairy 

Other 

Cattle 

128 

53 

Average milk production of 

8,400 kg head-1 yr-1. 

Includes beef cows, bulls, calves, 

growing steers/heifers, and feedlot 

cattle. 

Western Europe: Highly productive commercialised 

dairy sector feeding high quality forage and grain. 

Dairy cows also used for beef calf production. Very 

small dedicated beef cow herd. Minor amount of 

feedlot feeding with grains. 

Dairy 

Other 

Cattle 

117 

57 

Average milk production of 6,000 

kg head-1 yr-1. 

Includes bulls, calves, and growing 

steers/heifers. 

Eastern Europe: Commercialised dairy sector 

feeding mostly forages. Separate beef cow herd, 

primarily grazing. Minor amount of feedlot feeding 

with grains. 

Dairy 

Other 

Cattle 

99 

58 

Average milk production of 

2,550 kg head-1 yr-1. 

Includes beef cows, bulls, and 

young. 

Oceania: Commercialised dairy sector based on 

grazing. Separate beef cow herd, primarily grazing 

rangelands of widely varying quality. Growing 

amount of feedlot feeding with grains. Dairy cows 

are a small part of the population. 

Dairy 

Other 

Cattle 

90 

60 

Average milk production of 2,200 

kg head-1 yr-1. 

Includes beef cows, bulls, and 

young. 

Latin America: Commercialised dairy sector based 

on grazing. Separate beef cow herd grazing pastures 

and rangelands. Minor amount of feedlot feeding 

with grains. Growing non-dairy cattle comprise a 

large portion of the population. 

Dairy 

Other 

Cattle 

72 

56 

Average milk production of 800 kg 

head-1 yr-1

Includes beef cows, bulls, and 

young. 

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 other regions. 

Dairy 

Other 

Cattle 

68 

47 

Average milk production of 

1,650 kg head-1 yr-1

Includes multi-purpose cows, bulls, 

and young 

Africa and Middle East: Commercialised dairy 

sector based on grazing with low production per cow. 

Most cattle are multi-purpose, providing draft power 

and some milk within farming regions. Some cattle 

graze over very large areas. Cattle are smaller than 

those found in most other regions. 

Dairy 

Other 

Cattle 

46 

31 

Average milk production of 475 kg 

head-1 yr-1

Includes multi-purpose cows, bulls, 

and young 

Indian Subcontinent: Commercialised dairy sector 

based on crop by-product feeding with low 

production per cow. Most bullocks provide draft 

power and cows provide some milk in farming 

regions. Small grazing population. Cattle in this 

region are the smallest compared to cattle found in all 

other regions. 

Dairy 

Other 

Cattle 

58 

27 

Average milk production of 900 kg 

head-1 yr-1

Includes cows, bulls, and young. 

Young comprise a large portion of 

the population 

1 Emission factors should be derived on the basis of the characteristics of the cattle and feed of interest and need not be restricted solely to 

within regional characteristics. 

2 IPCC Expert Group, values represent averages within region, where applicable the use of more specific regional milk production data is 

encouraged. Existing values were derived using Tier 2 method and the data in Tables 10 A.1 and 10A. 2. 

 3 The following assumptions have been made in deriving these values: i) mature weights of animals have been used; ii) cows have been 

assumed to be non-lactating as lactation levels were low and, iii) the mix of bulls and castrates among "males" was undetermined as Cfi 

value for castrates was not specified. 
Volume 4: Agriculture, Forestry and Other Land Use 

10.30 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Tier 2 Approach for methane emissions from Enteric Fermentation 

The Tier 2 method is applied to more disaggregated livestock population categories and used to calculate 

emission factors, as opposed to default values. The key considerations for the Tier 2 method are the development 

of emission factors and the collection of detailed activity data. 

Step 1: Livestock population 

The animal population data and related activity data should be obtained following the approach described in 

Section 10.2. 

Step 2: Emission factors 

When the Tier 2 method is used, emission factors are estimated for each animal category using the detailed data 

developed in Step 1. 

The emission factors for each category of livestock are estimated based on the gross energy intake and methane 

conversion factor for the category. The gross energy intake data should be obtained using the approach described 

in Section 10.2. The following two sub-steps need to be completed to calculate the emission factor under the 

Tier 2 method: 

1. Obtaining the methane conversion factor (Ym) 

The extent to which feed energy is converted to CH4 depends on several interacting feed and animal factors. If 

CH4 conversion factors are unavailable from country-specific research, the values provided in Table 10.12, 

Cattle/Buffalo CH4 conversion factors, can be used for cattle and buffalo. These general estimates are a rough 

guide based on the general feed characteristics and production practices found in many developed and 

developing countries. When good feed is available (i.e., high digestibility and high energy value) the lower 

bounds should be used. When poorer feed is available, the higher bounds are more appropriate. A CH4

conversion factor of zero is assumed for all juveniles consuming only milk (i.e., milk-fed lambs as well as 

calves). 

Due to the importance of Ym in driving emissions, substantial ongoing research is aimed at improving estimates 

of Ym for different livestock and feed combinations. Such improvement is most needed for animals fed on 

tropical pastures as the available data are sparse. For example, a recent study (Kurihara et al., 1999) observed 

Ym values outside the ranges described in Table 10.12. 

TABLE 10.12 

CATTLE/BUFFALO CH4 CONVERSION FACTORS (YM ) 

Livestock category Ym b

Feedlot fed Cattle a 3.0% + 1.0% 

Dairy Cows (Cattle and Buffalo) and their young 6.5% + 1.0% 

Other Cattle and Buffaloes that are primarily fed low quality crop residues and byproducts 6.5% + 1.0% 

Other Cattle or Buffalo – grazing 6.5% + 1.0% 

a When fed diets contain 90 percent or more concentrates. 

b The ± values represent the range. 

Source: IPCC Expert Group. 

Regional, national and global estimates of enteric methane generation rely on small scale determinations both of 

Ym and of the influence of feed and animal properties upon Ym. Traditional methods for measuring Ym include 

the use of respiration calorimeters for housing individual animals (Johnson and Johnson, 1995). A tracer 

technique using SF6 enables methane emissions from individual animals to be estimated under both housed or 

grazing conditions (Johnson et al., 1994). The results of recent measurements have been surveyed by Lassey 

( 2006) who also examines the "upscaling" of such measurements to national and global inventories. 

It is also important to examine the influences of feed properties and animal attributes on Ym. Such influences are 

important to better understand the microbiological mechanisms involved in methanogenesis with a view to 

designing emission abatement strategies, as well as to identify different values for Ym according to animal 

husbandry practices. To date, the search for such influences is equivocal, and consequently there is little 

variability evident both in the values reported in Table 10.12 as supported by the recent survey of Ym

measurements in the literature (Lassey, 2006). 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.31 

Table 10.13 proposes a common Ym value for all mature sheep irrespective of feed quality, but with different 

values for mature and juvenile sheep with demarcation at 1 year of age. These values are based on data by 

Lassey et al. (1997), Judd et al. (1999) and Ulyatt et al. (2002a, 2002b, 2005) and while consistent with 

measurements by other researchers (Murray et al., 1978; Leuning et al., 1999), may not span the full range of 

pastures to be found. The median value is appropriate for most applications, but for poor quality feed the upper 

limits may be more appropriate, and for high-digestibility high-energy feeds the lower limits may be used. 

TABLE 10.13 

SHEEP CH4 CONVERSION FACTORS (YM) 

Category Ym a 

Lambs (<1 year old) 4.5% + 1.0% 

Mature Sheep 6.5% + 1.0% 

a The + values represent the range. 

Note that in some cases, CH4 conversion factors may not exist for specific livestock types. In these instances, 

CH4 conversion factors from the reported livestock that most closely resembles those livestock types can be 

reported. For examples, CH4 conversion factors for other cattle or buffalo could be applied to estimate an 

emission factor for camels. 

2. Emission factor development 

An emission factor for each animal category should be developed following Equation 10.21: 

EQUATION 10.21 

CH4 EMISSION FACTORS FOR ENTERIC FERMENTATION FROM A LIVESTOCK CATEGORY

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎣

⎡ ⎟ •

⎠

⎞ ⎜

⎝

⎛ •

= 55.65

365

100

Ym GE

EF

Where: 

EF = emission factor, kg CH4 head-1 yr-1 

GE = gross energy intake, MJ head-1 day-1 

Ym = methane conversion factor, per cent of gross energy in feed converted to methane 

The factor 55.65 (MJ/kg CH4) is the energy content of methane 

This emission factor equation assumes that the emission factors are being developed for an animal category for 

an entire year (365 days). While a full year emission factor is typically used, in some circumstances the animal 

category may be defined for a shorter period (e.g., for the wet season of the year or for a 150-day feedlot feeding 

period). In this case, the emission factor would be estimated for the specific period (e.g., the wet season) and the 

365 days would be replaced by the number of days in the period. The definition of the period to which the 

emission factor applies is described in Section 10.2. 

Step 3: Total emissions 

To estimate total emissions, the selected emission factors are multiplied by the associated animal population and 

summed. As described above under Tier 1, the emissions estimates should be reported in gigagrams (Gg). 

Potential for refinement of Tier 2 or development of a Tier 3 method to enteric 

methane emission inventories 

Increased accuracy and identification of causes of variation in emissions are at the heart of inventory purpose. 

Improvements in country methodology, whether as components of current Tier 1 or 2 or if additional refinements 

are implemented (Tier 3), are encouraged. 

Current Tier 1 and Tier 2 enteric methane emissions factors and estimation procedures are driven by first 

estimating daily and annual gross energy consumption by individual animals within an inventory class which are 

then multiplied by an estimate of CH4 loss per unit of feed (Ym). There is considerable room for improvement in 
Volume 4: Agriculture, Forestry and Other Land Use 

10.32 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Tier 2 prediction of both feed intake and in Ym. Factors potentially impacting feed requirements and/or 

consumption that are not considered include: 

• breed or genotype variation in maintenance requirement; 

• heat and cold stress effects on intake and maintenance requirements; and 

• depression in digestibility with increasing levels of consumption, or diet composition limits to diet intake. 

Likewise, a host of interacting factors that control variations in Ym are not included in Tier 2 methodology, 

including: 

• effects of digestibility (DE%); 

• diet dry matter intake as it relates to live body weight; 

• diet chemical composition; 

• particle passage and digestion kinetics, or plant microbial defensive compounds; and 

• variation in the microbial populations within the digestive tract. 

Accurate estimation of diet DE% is singularly important in the estimation of feed intake and thus emissions, as 

previously emphasized. A 10% error in the average diet DE% or TDN% will result in CH4 errors ranging from 

12 to 20% depending on beginning circumstance. The depression in DE% with increasing daily amounts of diet 

consumed is not considered. This will underestimate feed intakes of high producing dairy cows consuming 

mixtures of concentrates and forages, e.g., as is common in the North America and Europe, although some of the 

resulting error in methane emission estimate will be compensated by reductions in Ym as intake per day increases. 

Methods to estimate digestibility depressions have been described (NRC, 1996; NRC, 2001). 

There have been many attempts to refine estimates of Ym. Several researchers have developed models which 

relate the chemical composition of the diet consumed, or in more detail, the composition of digested 

carbohydrate and other chemical components to Ym. These models typically predict diet particle and chemical 

component rates of passage and digestion in each enteric compartment at varying intake and the resulting H2

balance, volatile fatty acids, and microbial and CH4 yields. These approaches have generated Ym values that are 

consistent with direct measurements using chamber and SF6 techniques. 

The literature contains many examples of the positive relationship of plant cell wall digestion to high acetic to 

propionic end-product ratios, and to high CH4 yields. While fibrous carbohydrate digestion is undeniably the 

strongest single indicator of CH4 yield, the CH4 per digested fiber is not constant, e.g., when soyhulls or beet 

pulp are fed as single feed at varying levels of intake, Ym will vary from 8 to 11% when measured at restricted 

feed intakes and from 5 to 6% when measure at ad libitum intakes (Kujawa, 1994; Diarra, 1994). Thus, enteric 

fermentation of the same fibrous substrate can result in quite different Ym values. Perhaps the most severe 

limitation to development of more complex prediction models lies in the difficulty of applying them to broad 

country inventories. The difficulty is to provide the data needed to drive these more complex models of feed 

intake or Ym. It is often difficult to define animal characteristics, productivity, and %DE accurately for a class of 

livestock in a region of the country, let alone detailed carbohydrate fraction, rates of passage and digestion, etc. 

The amount of global research on mitigation strategies currently going on, such as vaccines, ionophores, 

polyunsaturated vegetable oils, condensed tannins etc, suggests a need to address how they should be reflected in 

inventory compilation at Tier 2 or Tier 3. First, the inventory should reflect only those technologies that conform 

to QA/QC principles and have attracted a wide degree of international acceptance such as through peer-reviewed 

articles that include a description of the technology, its efficacy and its validation under field conditions. Second, 

the inventory should be accompanied by evidence of the take-up of the technology, and apply it only to 

emissions by those livestock where take-up can be validated. Third, for a newly implemented technology (such 

as an administered dose of a mitigating agent), the inventory could also present an accompanying calculation of 

the emissions in the absence of a mitigation measure in order to make transparent the magnitude of the emission 

reductions that are being claimed. Mitigation measures should be supported by peer-reviewed publications. 

Approaches to improve estimates of feed intake and Ym and to consider mitigation approaches are to be 

encouraged, given due care on limitations of scope, production circumstance, etc. to which the predictive 

relationships apply. 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.33 

10.3.3 Choice of activity data 

Livestock population data should be obtained using the approach described in Section 10.2. If using default 

enteric emission factors for livestock (Tables 10.10, 10.11) to estimate enteric emissions, a basic (Tier 1) 

livestock population characterisation is sufficient. To estimate enteric emissions from livestock using estimation 

of Gross Energy Intake (Equations 10.16, 10.17 or 10.18), a Tier 2 characterisation is needed. As noted in 

Section 10.2, good practice in characterising livestock populations is to conduct a single characterisation that 

will provide the activity data for all emissions sources that depend on livestock population data. 

10.3.4 Uncertainty assessment 

Emission factors 

As the emission factors for the Tier 1 method are not based on country-specific data, they may not accurately 

represent a country’s livestock characteristics, and may be highly uncertain as a result. Emission factors 

estimated using the Tier 1 method are unlikely to be known more accurately than +30% and may be uncertain to 

+50%. The uncertainty under the Tier 2 method will depend on the accuracy of the livestock characterisation 

(e.g., homogeneity of livestock categories), and also on the extent to which the methods for defining the 

coefficients in the various relationships that make up the net energy approach correspond to national 

circumstances. Emission factor estimates using the Tier 2 method are likely to be in the order of +20%. 

Inventory compilers using the Tier 2 method should undertake an analysis of uncertainties reflecting their 

particular situation, and in the absence of this analysis the uncertainty under the Tier 2 method should be 

assumed similar to the uncertainty under the Tier 1 method. 

Although a Tier 3 method has the potential to improve the accuracy of emission estimates, a substantial body of 

scientific data is required to develop a viable Tier 3 method. The use of unreliable and unsubstantiated data in a 

Tier 3 method could result in estimates that are inferior to Tier 2 or even Tier 1 methods. In many instances, 

direct measurements of methane emissions from livestock are lacking or have been conducted using a limited 

number of diet types. A considerable amount of research on potential mitigation strategies is ongoing, but few 

of these have been validated to the point that they can be extrapolated to non-research conditions. As the 

foundational research on emission related science continues to expand, Tier 3 method should theoretically result 

in the lowest degree of uncertainty. 

Activity data 

There will be an added uncertainty associated with the livestock and feed characterisation. Improving the 

livestock and feed characterisation will often be the priority in reducing overall uncertainty. Accurate estimates 

of feed digestibility (DE%) are also critical for reducing the degree of uncertainty. Uncertainty estimates can be 

derived from the good practice approach to agricultural census data outlined in the uncertainty section for 

livestock and feed characterisation (see Section 10.2). 

General information on the procedures to assess uncertainty is presented in Volume 1, Chapter 3 (Uncertainties). 

10.3.5 Completeness, Time series, Quality 

Assurance/Quality Control and Reporting 

To achieve completeness, all the major animal categories managed in the country should be considered. In the 

event that animals are included in the inventory for which default data are not available and for which no 

guidelines are provided, the emissions estimate should be developed using the same general principles presented 

in the discussion in Section 10.2. 

Care must be taken to use a consistent set of estimates for the CH4 conversion factors over time. In some cases, 

there may be reasons to modify methane conversion factors over time. These changes may be due to the 

implementation of explicit greenhouse gas (GHG) mitigation measures, or may be due to changing agricultural 

practices such as feed conditions or other management factors without regard to GHGs. Regardless of the driver 

of change, the data and methane conversion factors used to estimate emissions must reflect the change in farm 

practices. If methane conversion factors over a time series are affected by a change in management practice 

and/or the implementation of GHG mitigation measures, the inventory compiler should ensure that the inventory 

data reflect these practices. The inventory text should thoroughly explain how the changes in management 

practice and/or implementation of mitigation measures has affected the time series of methane conversion factors. 

For general good practice guidance on developing a consistent time series, see Volume 1, Chapter 5 (Time 

Series Consistency). 
Volume 4: Agriculture, Forestry and Other Land Use 

10.34 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

It is good practice to implement quality control checks as outlined in Volume 1, Chapter 6 (Quality 

Assurance/Quality Control and Verification). In addition to the guidance in Volume 1, specific procedures of 

relevance to this source category are outlined below: 

Activity data check 

• The inventory compiler should review livestock data collection methods, in particular checking that 

livestock subspecies data were collected and aggregated correctly. The data should be cross-checked with 

previous years to ensure the data are reasonable and consistent with the expected trend. Inventory compilers 

should document data collection methods, identify potential areas of bias, and evaluate the 

representativeness of the data. Population modeling can be used to support this approach. 

Review of emission factors 

• If using the Tier 2/Tier 3 method, the inventory compiler should cross-check country-specific factors against 

the IPCC defaults. Significant differences between country-specific factors and default factors should be 

explained and documented. 

External review 

• If Tier 2/Tier 3 method is used, the inventory compiler is encouraged to conduct national and international 

expert review, including from industry, academic institutions, and extension expertise. 

• It is important to maintain internal documentation on review results. 

To improve transparency, emission estimates from this source category should be reported along with the 

activity data and emission factors used to determine the estimates. 

The following information should be documented: 

• All activity data including animal population data by category and region. 

• Activity data documentation including:

(i) The sources of all activity data used in the calculations (i.e., complete citation for the statistical 

database from which data were collected); 

(ii) The information and assumptions that were used to develop the activity data, in cases where 

activity data were not directly available from databases; and 

(iii) The frequency of data collection, and estimates of accuracy and precision. 

• If Tier 1 method is used, all default emission factors used in the estimation of emissions for the specific 

animal categories. 

• If Tier 2 method is used: 

(i) Values for Ym; 

(ii) DE values estimated or taken from other studies; and 

(iii) Full documentation of the data used including their references. 

• For inventories in which country- or region-specific emission factors are used or in which new methods, 

such as Tier 3 are used, the scientific basis of these emission factors and the principles of the new method 

should be thoroughly documented. Documentation should include definitions of input parameters and a 

description of the principle and process by which these emission factors and methods are derived, as well as 

describing sources and magnitudes of uncertainties. 

 
Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.35 

10.4 METHANE EMISSIONS FROM MANURE 

MANAGEMENT 

This section describes how to estimate CH4 produced during the storage and treatment of manure, and from 

manure deposited on pasture. The term ‘manure’ is used here collectively to include both dung and urine (i.e., 

the solids and the liquids) produced by livestock. The emissions associated with the burning of dung for fuel are 

to be reported under Volume 2 (Energy), or under Volume 5 (Waste) if burned without energy recovery. The 

decomposition of manure under anaerobic conditions (i.e., in the absence of oxygen), during storage and 

treatment, produces CH4. These conditions occur most readily when large numbers of animals are managed in a 

confined area (e.g., dairy farms, beef feedlots, and swine and poultry farms), and where manure is disposed of in 

liquid-based systems. Emissions of CH4 related to manure handling and storage are reported under ‘Manure 

Management.’ 

The main factors affecting CH4 emissions are the amount of manure produced and the portion of the manure that 

decomposes anaerobically. The former depends on the rate of waste production per animal and the number of 

animals, and the latter on how the manure is managed. When manure is stored or treated as a liquid (e.g., in 

lagoons, ponds, tanks, or pits), it decomposes anaerobically and can produce a significant quantity of CH4. The 

temperature and the retention time of the storage unit greatly affect the amount of methane produced. When 

manure is handled as a solid (e.g., in stacks or piles) or when it is deposited on pastures and rangelands, it tends 

to decompose under more aerobic conditions and less CH4 is produced. 

10.4.1 Choice of method 

There are three tiers to estimate CH4 emissions from livestock manure. Guidance for determining which tier to 

use is shown in Figure 10.3 decision tree. 

Tier 1 

A simplified method that only requires livestock population data by animal species/category and climate region 

or temperature, in combination with IPCC default emission factors, to estimate emissions. Because some 

emissions from manure management systems are highly temperature dependent, it is good practice to estimate 

the average annual temperature associated with the locations where manure is managed. 

Tier 2 

A more complex method for estimating CH4 emissions from manure management should be used where a 

particular livestock species/category represents a significant share of a country’s emissions. This method 

requires detailed information on animal characteristics and manure management practices, which is used to 

develop emission factors specific to the conditions of the country. 

Tier 3 

Some countries for which livestock emissions are particularly important may wish to go beyond the Tier 2 

method and develop models for country-specific methodologies or use measurement–based approaches to 

quantify emission factors. 

The method chosen will depend on data availability and national circumstances. Good practice in estimating 

CH4 emissions from manure management systems entails making every effort to use the Tier 2 method, 

including calculating emission factors using country-specific information. The Tier 1 method should only be 

used if all possible avenues to use the Tier 2 method have been exhausted and/or it is determined that the source 

is not a key category or subcategory. 

Regardless of the method chosen, the animal population must first be divided into categories as described in 

Section 10.2 that reflect the varying amounts of manure produced per animal. 

 The following four steps are used to estimate CH4 emissions from manure management: 

Step 1: Collect population data from the Livestock Population Characterisation (see Section 10.2). 

Step 2: Use default values or develop country-specific emission factors for each livestock subcategory in terms 

of kilograms of methane per animal per year. 

Step 3: Multiply the livestock subcategory emission factors by the subcategory populations to estimate 

subcategory emissions, and sum across the subcategories to estimate total emissions by primary livestock species. 

Step 4: Sum emissions from all defined livestock species to determine national emissions. 
Volume 4: Agriculture, Forestry and Other Land Use 

10.36 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Figure 10.3 Decision tree for CH4 emissions from Manure Management 

Start

Is a Tier 2

livestock population

characterization, available and do

you have country-specific VS rates,

MCF values, Bo values, and

management system

usage data?

Collect data for

Tier 2 method.

Estimate CH4 emissions

using Tier 1 method

and IPCC defaults.

No

Note:

1: See Volume 1 Chapter 4, "Methodological Choice and Identification of Key Categories" (noting Section 4.1.2 on limited resources), for 

discussion of key categories and use of decision trees.

2: As a rule of thumb, a livestock species would be significant if it accounts for 25-30% or more of emissions from the source category.

Is CH4 from

manure management a 

key source category1

 and is the 

species a significant share

of emissions2

?

No

Yes (all or some)

Estimate CH4 emissions

using Tier 2 method

with available countryspecific inputs.

No

Yes

Box 2: Tier 2 Box 1: Tier 1

Yes

Estimate emissions

using Tier 3 method.

Do you

have a country-specific

Tier 3 methodology?

Box 3: Tier 3
Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.37 

Equation 10.22 shows how to calculate CH4 emissions from manure management: 

EQUATION 10.22 

CH4 EMISSIONS FROM MANURE MANAGEMENT

( ) ∑ • =

( )

6

( ) ( )

4

T 10

T T

Manure

EF N

CH

Where: 

CH4Manure = CH4 emissions from manure management, for a defined population, Gg CH4 yr-1

EF(T) = emission factor for the defined livestock population, kg CH4 head-1 yr-1 

N(T) = the number of head of livestock species/category T in the country 

T = species/category of livestock 

10.4.2 Choice of emission factors 

The best way to determine emission factors is to conduct non-invasive or non-disturbing measurements of 

emissions in actual systems representative of those in use in the country. These field results can be used to 

develop models to estimate emission factors (Tier 3). Such measurements are difficult to conduct, and require 

significant resources and expertise, and equipment that may not be available. Thus, while such an approach is 

recommended to improve accuracy, it is not required for good practice. This section provides two alternatives 

for developing emission factors, with the selection of emission factors depending on the method (i.e., Tier 1 or 

Tier 2) chosen for estimating emissions. 

Tier 1 

When using the Tier 1 method, methane emission factors by livestock category or subcategory are used. Default 

emission factors by average annual temperature are presented in Table 10.14, Table 10.15, and Table 10.16 for 

each of the recommended population subcategories. These emission factors represent the range in manure 

volatile solids content and in manure management practices used in each region, as well as the difference in 

emissions due to temperature. Tables 10A-4 through 10A-9 located in Annex 10A.2 present the underlying 

assumptions used for each region. Countries using a Tier 1 method to estimate methane emissions from manure 

management should review the regional variables in these tables to identify the region that most closely matches 

their animal operations, and use the default emission factors for that region. 

Table 10.14 shows the default emission factors for cattle, swine, and buffalo for each region and temperature 

classification. Emission factors are listed by the annual average temperature for the climate zone where the 

livestock manure is managed. The temperature data should be based on national meteorological statistics where 

available. Countries should estimate the percentage of animal populations in different temperature zones and 

compute a weighted average emission factor. Where this is not possible, the annual average temperature for the 

entire country could be utilized; however, this may not give an accurate estimate of emissions that are highly 

sensitive to temperature variations (e.g., liquid/slurry systems). 

Tables 10.15 and 10.16 present the default manure management emission factors for other animal species. 

Separate emission factors are shown for developed and developing countries in Table 10.15, reflecting the 

general differences in feed intake and feed characteristics of the animals in the two regions. Except for poultry 

“layers (wet),” these emission factors reflect the fact that virtually all the manure from these animals is managed 

in ‘dry’ manure management systems, including pastures and ranges, drylots, and daily spreading on fields 

(Woodbury and Hashimoto, 1993). 
Volume 4: Agriculture, Forestry and Other Land Use 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.14 

MANURE MANAGEMENT METHANE EMISSION FACTORS BY TEMPERATURE FOR CATTLE, SWINE, AND B

(KG CH4 HEAD-1 YR-1) 

CH4 emission factors by average an

Regional characteristics Livestock species Cool Temp

≤ 10 11 12 13 14 15 16 17 18 19 20 

Dairy Cows 48 50 53 55 58 63 65 68 71 74 78 Other Cattle 1 1 1 1 1 2 2 2 2 2 2 Market Swine 10 11 11 12 12 13 13 14 15 15 16 

North America: Liquid-based systems are commonly used for dairy cows and swine manure. Other cattle manure is usually managed as a solid and deposited on pastures or ranges. 

Breeding Swine 19 20 21 22 23 24 26 27 28 29 31 

Dairy Cows 21 23 25 27 29 34 37 40 43 47 51 Other Cattle 6 7 7 8 8 10 11 12 13 14 15 Market Swine 6 6 7 7 8 9 9 10 11 11 12 Breeding Swine 9 10 10 11 12 13 14 15 16 17 19 

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

Buffalo 4 4 5 5 5 6 7 7 8 9 9 

Dairy Cows 11 12 13 14 15 20 21 22 23 25 27 Other Cattle 6 6 7 7 8 9 10 11 11 12 13 Market Swine 3 3 3 3 3 4 4 4 4 5 5 Breeding Swine 4 5 5 5 5 6 7 7 7 8 8 

Eastern Europe: Solid based systems are used for the majority of manure. About one-third of livestock manure is managed in liquid-based systems. 

Buffalo 5 5 5 6 6 7 8 8 9 10 11 

Dairy Cows 23 24 25 26 26 27 28 28 28 29 29 Other Cattle 1 1 1 1 1 2 2 2 2 2 2 Market Swine 11 11 12 12 12 13 13 13 13 13 13 

Oceania: Most cattle manure is managed as a solid on pastures and ranges, except dairy cows where there is some usage of lagoons. About half of the swine manure is managed in anaerobic lagoons. 

Breeding Swine 20 20 21 21 22 22 23 23 23 23 23 

Dairy Cows 1 1 1 1 1 1 1 1 1 1 1 Other Cattle 1 1 1 1 1 1 1 1 1 1 1 Swine 1 1 1 1 1 1 1 1 1 1 1 

Latin America: Almost all livestock manure is managed as a solid on pastures and ranges. Buffalo manure is deposited on pastures and ranges. 

Buffalo 1 1 1 1 1 1 1 1 1 1 1 
Chapter 10: Emi

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.14 

MANURE MANAGEMENT METHANE EMISSION FACTORS BY TEMPERATURE FOR CATTLE, SWINE, AND B

(KG CH4 HEAD-1 YR-1) 

CH4 emission factors by average an

Regional characteristics Livestock species Cool Temp

≤ 10 11 12 13 14 15 16 17 18 19 20 

Dairy Cows 1 1 1 1 1 1 1 1 1 1 1 Other Cattle 0 0 0 0 0 1 1 1 1 1 1 

Africa: Most livestock manure is managed as a solid on pastures and ranges. A smaller, but significant fraction is burned as fuel. 

Swine 0 0 0 1 1 1 1 1 1 1 1 

Dairy Cows 2 2 2 2 2 2 2 2 2 2 2 Other Cattle 1 1 1 1 1 1 1 1 1 1 1 Swine 1 1 1 2 2 2 2 2 3 3 3 

Middle East: Over two-thirds of cattle manure is deposited on pastures and ranges. About one-third of swine manure is managed in liquid-based systems. Buffalo manure is burned for fuel or managed as a solid. 

Buffalo 4 4 4 4 4 5 5 5 5 5 5 

Dairy Cows 9 10 10 11 12 13 14 15 16 17 18 Other Cattle 1 1 1 1 1 1 1 1 1 1 1 Swine 2 2 2 2 2 3 3 3 3 4 4 

Asia: About half of cattle manure is used for fuel with the remainder managed in dry systems. Almost 40% of swine manure is managed as a liquid. Buffalo manure is managed in drylots and deposited in pastures and ranges. 

Buffalo 1 1 1 1 1 2 2 2 2 2 2 

Dairy Cows 5 5 5 5 5 5 5 5 5 5 5 Other Cattle 2 2 2 2 2 2 2 2 2 2 2 Swine 2 2 3 3 3 3 3 3 4 4 4 

Indian Subcontinent: About half of cattle and buffalo manure is used for fuel with the remainder managed in dry systems. About one-third of swine manure is managed as a liquid. 

Buffalo 4 4 4 4 4 5 5 5 5 5 5 

Source: See Annex 10A.2 , Tables 10A-4 to 10A-8 for derivation of these emission factors, 

The uncertainty in these emission factors is +30 %. 

a When selecting a default emission factor, be sure to consult the supporting tables in Annex 10A.2 for the distribution of manure management systems and anima

an emission factor for a region that most closely matches your own in these characteristics. 

b All temperatures are not necessarily represented within every region. For example, there are no significant warm areas in Eastern or Western Europe. Similarly, t

East. Note: Significant buffalo populations do not exist in North America, Oceania, or Africa. 
Volume 4: Agriculture, Forestry and Other Land Use 

10.40 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.15 

MANURE MANAGEMENT METHANE EMISSION FACTORS BY TEMPERATURE FOR SHEEP, GOATS, CAMELS, HORSES, MULES 

AND ASSES, AND POULTRYa (KG CH4 HEAD-1 YR-1) 

CH4 emission factor by average annual temperature (°C) Livestock 

Cool (<15 ̊C) Temperate (15 to 25 ̊C) Warm (>25 ̊C) 

Sheep 

Developed countries 0.19 0.28 0.37 

Developing countries 0.10 0.15 0.20 

Goats 

Developed countries 0.13 0.20 0.26 

Developing countries 0.11 0.17 0.22 

Camels 

Developed countries 1.58 2.37 3.17 

Developing countries 1.28 1.92 2.56 

Horses 

Developed countries 1.56 2.34 3.13 

Developing countries 1.09 1.64 2.19 

Mules and Asses 

Developed countries 0.76 1.10 1.52 

Developing countries 0.60 0.90 1.20 

Poultry 

Developed countries 

Layers (dry)b 0.03 0.03 0.03 

Layers (wet)c 1.2 1.4 1.4 

Broilers 0.02 0.02 0.02 

Turkeys 0.09 0.09 0.09 

Ducks 0.02 0.03 0.03 

Developing countries 0.01 0.02 0.02 

The uncertainty in these emission factors is +30 %. 

Sources: Emission factors developed from: feed intake values and feed digestibilities used to develop the enteric fermentation emission 

factors (see Annex 10A.1); Except for poultry in developed countries, methane conversion factor (MCF), and maximum methane 

producing capacity (Bo) values reported in Woodbury and Hashimoto (1993). Poultry for developed countries was subdivided into five 

categories. Layers (dry) represent layers in a "without bedding" waste management system; layers (wet) represent layers in an anaerobic 

lagoon waste management system. For layers, volatile solids (VS) are values reported in USDA (1996); typical animal mass values are 

from ASAE (1999); and Bo values for Layers are values reported by Hill (1982). For broilers and turkeys, Bo values are from Hill (1984); 

typical animal mass values are from ASAE (1999); and VS values are those reported in USDA (1996). Bo values for ducks were 

transferred from broilers and turkeys; typical animal mass values are from MWPS-18; and VS values are from USDA, AWMFH. 

Typical mass of sheep, goats and horses, and VS and Bo values of goats and horses for developed countries updated according to the 

analysis of GHG inventories of Annex I countries. All manure, with the exception of Layers (wet), is assumed to be managed in dry 

systems, which is consistent with the manure management system usage reported in Woodbury and Hashimoto (1993). 

a When selecting a default emission factor, be sure to consult the supporting tables in Annex 10A.2 for the distribution of manure 

management systems and animal waste characteristics used to estimate emissions. Select an emission factor for a region that most 

closely matches your own in these characteristics. 

b Layer operations that manage dry manure. 

c Layer operations that manage manure as a liquid, such as stored in an anaerobic lagoon. 
Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.41 

TABLE 10.16 

MANURE MANAGEMENT METHANE EMISSION FACTORS FOR DEER, REINDEER, RABBITS, AND FUR-BEARING ANIMALS

 Livestock 

CH4 emission factor 

(kg CH4 head-1 yr-1) 

Deera 0.22 

Reindeerb 0.36 

Rabbitsc 0.08 

Fur-bearing animals (e.g., fox, mink)b 0.68 

The uncertainty in these emission factors is +30 %. 

a Sneath et al. (1997) 

b Estimations of Agricultural University of Norway, Institute of Chemistry and Biotechnology, Section for Microbiology. 

c Judgement of the IPCC Expert Group 

Tier 2 

The Tier 2 method is applicable when Manure Management is a key source or when the data used to develop the 

default values do not correspond well with the country's livestock and manure management conditions. Because 

cattle, buffalo and swine characteristics and manure management systems can vary significantly by country, 

countries with large populations of these animals should consider using the Tier 2 method for estimating 

methane emissions. The Tier 2 method relies on two primary types of inputs that affect the calculation of 

methane emission factors from manure: 

Manure characteristics: Includes the amount of volatile solids (VS) produced in the manure and the maximum 

amount of methane able to be produced from that manure (Bo). Production of manure VS can be estimated based 

on feed intake and digestibility, which are the variables also used to develop the Tier 2 enteric fermentation 

emission factors. Alternatively, VS production rates can be based on laboratory measurements of livestock 

manure. Bo varies by animal species and feed regimen and is a theoretical methane yield based on the amount of 

VS in the manure. Bedding materials (straw, sawdust, chippings, etc.) are not included in the VS modelled 

under the Tier 2 method. The type and use of these materials is highly variable from country to country. Since 

they typically are associated with solid storage systems, their contribution would not add significantly to overall 

methane production. 

Manure management system characteristics: Includes the types of systems used to manage manure and a 

system-specific methane conversion factor (MCF) that reflects the portion of Bo that is achieved. Regional 

assessments of manure management systems are used to estimate the portion of the manure that is handled with 

each manure management technique. A description of manure management systems is included in Table 10.18. 

The system MCF varies with the manner in which the manure is managed and the climate, and can theoretically 

range from 0 to 100%. Both temperature and retention time play an important role in the calculation of the MCF. 

Manure that is managed as a liquid under warm conditions for an extended period of time promotes methane 

formation. These manure management conditions can have high MCFs, of 65 to 80%. Manure managed as dry 

material in cold climates does not readily produce methane, and consequently has an MCF of about 1%. 

Development of Tier 2 emission factors involves determining a weighted average MCF using the estimates of 

the manure managed by each waste system within each climate region. The average MCF is then multiplied by 

the VS excretion rate and the Bo for the livestock categories. In equation form, the estimate is as follows: 

EQUATION 10.23 

CH4 EMISSION FACTOR FROM MANURE MANAGEMENT

( ) ⎥

⎦

⎤ ⎢

⎣

⎡ = • • • • ∑ • ( , , )

,

3 ,

( ) ( ) ( ) 100

365 0.67 / T S k

S k

S k

T T o T MS

MCF

EF VS B kg m

Where: 

EF(T) = annual CH4 emission factor for livestock category T, kg CH4 animal-1 yr-1

VS(T) = daily volatile solid excreted for livestock category T, kg dry matter animal-1 day-1

365 = basis for calculating annual VS production, days yr-1

Bo(T) = maximum methane producing capacity for manure produced by livestock category T, m3

 CH4 kg-1

of VS excreted 
Volume 4: Agriculture, Forestry and Other Land Use 

10.42 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

0.67 = conversion factor of m3 CH4 to kilograms CH4

MCF(S,k) = methane conversion factors for each manure management system S by climate region k, % 

MS(T,S,k) = fraction of livestock category T's manure handled using manure management system S in 

climate region k, dimensionless 

Even when the level of detail presented in the Tier 2 method is not possible in some countries, country-specific 

data elements such as animal mass, VS excretion, and others can be used to improve emission estimates. If 

country-specific data are available for only a portion of these variables, countries are encouraged to calculate 

country-specific emission factors, using the data in Tables 10A-4 through 10A-9 to fill gaps. 

Measurement programs can be used to improve the basis for making the estimates. In particular, measurements 

of emissions from manure management systems under field conditions are useful to verify MCFs. Also, 

measurements of Bo from livestock in tropical regions and for varying diet regimens are needed to expand the 

representativeness of the default factors. 

As emissions can vary significantly by region and livestock species/category, emission estimates should reflect 

as much as possible the diversity and range of animal populations and manure management practices between 

different regions within a country. This may require separate estimates to be developed for each region. 

Emission factors should be updated periodically to account for changes in manure characteristics and 

management practices. These revisions should be based on reliable scientifically reviewed data. Frequent 

monitoring is desirable to verify key model parameters and to track changing trends in the livestock industry. 

VS excretion rates 

Volatile solids (VS) are the organic material in livestock manure and consist of both biodegradable and nonbiodegradable fractions. The value needed for the Equation 10.23 is the total VS (both degradable and nonbiodegradable fractions) as excreted by each animal species since the Bo values are based on total VS entering 

the systems. The best way to obtain average daily VS excretion rates is to use data from nationally published 

sources. If average daily VS excretion rates are not available, country-specific VS excretion rates can be 

estimated from feed intake levels. Feed intake for cattle and buffalo can be estimated using the ‘Enhanced’ 

characterisation method described in Section 10.2. This will also ensure consistency in the data underlying the 

emissions estimates. For swine, country-specific swine production data may be required to estimate feed intake. 

The VS content of manure equals the fraction of the diet consumed that is not digested and thus excreted as fecal 

material which, when combined with urinary excretions, constitutes manure. Countries should estimate gross 

energy (GE) intake (Section 10.2, Equation 10.16) and its fractional digestibility, DE, in the process of 

estimating enteric methane emissions. 

Once these are estimated, the VS excretion rate is estimated as: 

EQUATION 10.24

VOLATILE SOLID EXCRETION RATES

( ) ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ − • ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟ + • ⎠

⎞ ⎜

⎝

⎛ = • − 18.45

1

100

% 1 ASH UE GE DE VS GE

Where: 

VS = volatile solid excretion per day on a dry-organic matter basis, kg VS day-1

GE = gross energy intake, MJ day-1

DE% = digestibility of the feed in percent (e.g. 60%) 

(UE • GE) = urinary energy expressed as fraction of GE. Typically 0.04GE can be considered urinary 

energy excretion by most ruminants (reduce to 0.02 for ruminants fed with 85% or more grain in the 

diet or for swine). Use country-specific values where available. 

ASH = the ash content of manure calculated as a fraction of the dry matter feed intake (e.g., 0.08 for 

cattle). Use country-specific values where available. 

18.45 = conversion factor for dietary GE per kg of dry matter (MJ kg-1). This value is relatively constant 

across a wide range of forage and grain-based feeds commonly consumed by livestock. 

Representative DE% values for various livestock categories are provided in Section 10.2, Table 10.2 of this 

report. The value for ash content fraction can range substantially between livestock types and should reflect 

national circumstances. 
Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.43 

Bo values 

The maximum methane-producing capacity of the manure (Bo) varies by species and diet. The preferred method 

to obtain Bo measurement values is to use data from country-specific published sources, measured with a 

standardised method. It is important to standardise the Bo measurement, including the method of sampling, and 

to confirm if the value is based on total as-excreted VS or biodegradable VS, since the Tier 2 calculation is based 

on total as-excreted VS. If country-specific Bo measurement values are not available, default values are provided 

in Tables 10A-4 through 10A-9. 

MCFs 

Default methane conversion factors (MCFs) are provided in Table 10.17 for different manure management 

systems and by annual average temperatures. MCFs are determined for a specific manure management system 

and represent the degree to which Bo is achieved. The amount of methane generated by a specific manure 

management system is affected by the extent of anaerobic conditions present, the temperature of the system, and 

the retention time of organic material in the system. Default MCF values for lagoons presented in Table 10.17 

include the effect of longer retention times, and as a result, are higher than other systems under most 

circumstances. 

Since liquid-based systems are very sensitive to temperature effects, where possible default MCF values for 

these systems have been presented in Table 10.17 for specific annual average temperatures in each climate range. 

While these temperature ranges should cover most climate conditions, areas that have extreme high or low 

annual average temperatures outside the 10 to 28 degree Celsius range should utilize the end-of-range (i.e., 10 or 

28 degree) values or investigate developing country-specific values. 

These default values may not encompass the potentially wide variation within the defined categories of 

management systems. Therefore, country-specific MCFs that reflect the specific management systems used in 

particular countries or regions should be developed if possible. This is particularly important for countries with 

large animal populations or with multiple climate regions. In such cases, and if possible, field measurements 

should be conducted for each climate region to replace the default MCF values. Measurements should include 

the following factors: 

• Timing of storage/application; 

• Feed and animal characteristics at the measurement site (see Section 10.2 for the type of data that would be 

pertinent); 

• Length of storage; 

• Manure characteristics (e.g., VS influent and effluent concentrations for liquid systems); 

• Determination of the amount of manure left in the storage facility (methanogenic inoculum); 

• Time and temperature distribution between indoor and outdoor storage; 

• Daily temperature fluctuation; and 

• Seasonal temperature variation. 
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2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.17 

MCF VALUES BY TEMPERATURE FOR MANURE MANAGEMENT SYSTEMS 

MCFs by average annual temperature (°C) 

System Cool Temperate W

a

≤ 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 

Pasture/Range/Paddock 1.0% 1.5% Daily spread 0.1% 0.5% Solid storage 2.0% 4.0% Dry lot 1.0% 1.5% 

With natural crust cover 

10% 11% 13% 14% 15% 17% 18% 20% 22% 24% 26% 29% 31% 34% 37% 41% 44% 

Liquid/Slurry 

Without natural crust cover 

17% 19% 20% 22% 25% 27% 29% 32% 35% 39% 42% 46% 50% 55% 60% 65% 71% 
Chapter 10: Emi

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.17 (CONTINUED) 

MCF VALUES BY TEMPERATURE FOR MANURE MANAGEMENT SYSTEMS 

MCFs by average annual temperature (°C) 

System Cool Temperate W

a

≤ 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 

Uncovered anaerobic lagoon 66% 68% 70% 71% 73% 74% 75% 76% 77% 77% 78% 78% 78% 79% 79% 79% 79% 

< 1 month 3% 3% 

Pit storage below animal confinements 

> 1 month 17% 19% 20% 22% 25% 27% 29% 32% 35% 39% 42% 46% 50% 55% 60% 65% 71% 
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2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.17 (CONTINUED) 

MCF VALUES BY TEMPERATURE FOR MANURE MANAGEMENT SYSTEMS 

MCFs by average annual temperature (°C) 

System Cool Temperate W

a

≤ 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 

Anaerobic digester 0-100% 0-100% 0Burned for fuel 10% 10% Cattle and Swine deep bedding < 1 month 3% 3% Cattle and Swine deep bedding (cont.) > 1 month 17% 19% 20% 22% 25% 27% 29% 32% 35% 39% 42% 46% 50% 55% 60% 65% 71% Composting - In-vesselb 0.5% 0.5% Composting - Static pileb 0.5% 0.5% Composting - Intensive windrowb 0.5% 1.0% Composting – Passive windrowb 0.5% 1.0% 
Chapter 10: Emi

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.17 (CONTINUED) 

MCF VALUES BY TEMPERATURE FOR MANURE MANAGEMENT SYSTEMS 

MCFs by average annual temperature (°C) 

System Cool Temperate W

a

≤ 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 

Poultry manure with litter 1.5% 1.5% Poultry manure without litter 1.5% 1.5% Aerobic treatment 0% 0% 

Formula 1 (Timeframe for inputs should reflect operating period of digester): 

MCF = [{CH4 prod - CH4 used - CH4 flared + (MCFstorage /100 * Bo * VSstorage * 0.67 )}/ (Bo* VSstorage * 0.67)] *100 

Where: CH4 prod = methane production in digester , (kg CH4) . Note: When a gas tight coverage of the storage for digested manure is used, the gas production of the storage should be included. 

CH4 used = amount of methane gas used for energy, (kg CH4) CH4 flared = amount of methane flared, (kg CH4) MCFstorage = MCF for CH4 emitted during storage of digested manure (%) 

VSstorage = amount of VS excreted that goes to storage prior to digestion (kg VS) 

When a gas tight storage is included: MCFstorage = 0 ; otherwise MCFstorage = MCF value for liquid storage 

a Definitions for manure management systems are provided in Table 10. 18. b Composting is the biological oxidation of a solid waste including manure usually with bedding or another organic carbon source typically at thermophilic temperatures produced by microbial heat production. 
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10.48 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

10.4.3 Choice of activity data 

There are two main types of activity data for estimating CH4 emissions from manure management: (1) animal 

population data; and (2) manure management system usage data. 

The animal population data should be obtained using the approach described in Section 10.2. As noted in 

Section 10.2, it is good practice to conduct a single livestock characterisation that will provide the activity data 

for all emissions sources relying on livestock population data. It is important to note, however, that the level of 

disaggregation in the livestock population data required to estimate emissions from manure management, may 

differ from those used for other sources, such as Enteric Fermentation. For example, for some livestock 

population species/categories, such as cattle, the enhanced characterisation required for the Tier 2 enteric 

fermentation estimate could be aggregated to broader categories that are sufficient for this source category. For 

other livestock species, such as swine, it may be preferable to have more disaggregation of weight categories for 

manure management calculations than for enteric fermentation. However, consistency in total livestock 

categories should be retained throughout the inventory. 

Inventory agencies in countries with varied climatic conditions are encouraged to obtain population data for each 

major climatic zone. In addition, where possible, the associated annual average temperature for locations where 

livestock manure is managed in liquid-based systems (e.g., pits, tanks, and lagoons) should be obtained. This 

will allow more specific selection of default factors or MCF values for those systems more sensitive to 

temperature changes. Ideally, the regional population breakdown can be obtained from published national 

livestock statistics, and the temperature data from national meteorological statistics. If regional data are not 

available, experts should be consulted regarding regional production (e.g., milk, meat, and wool) patterns or land 

distribution, which may provide the required information to estimate the regional animal distributions. 

To implement the Tier 2 method, the portion of manure managed in each manure management system must also 

be collected for each representative animal species. Table 10.18 summarizes the main types of manure 

management systems. Quantitative data should be used to distinguish whether the system is judged to be a solid 

storage or liquid/slurry. The borderline between dry and liquid can be drawn at 20% dry matter content. Note 

that in some cases, manure may be managed in several types of manure management systems. For example, 

manure flushed from a dairy freestall barn to an anaerobic lagoon may first pass through a solids separation unit 

where some of the manure solids are removed and managed as a solid. Therefore, it is important to carefully 

consider the fraction of manure that is managed in each type of system. 

The best means of obtaining manure management system distribution data is to consult regularly published 

national statistics. If such statistics are unavailable, the preferred alternative is to conduct an independent survey 

of manure management system usage. If the resources are not available to conduct a survey, experts should be 

consulted to obtain an opinion of the system distribution. Volume 1, Chapter 2 Approaches to Data Collection 

describes how to elicit expert judgement. Similar expert elicitation protocols can be used to obtain manure 

management system distribution data. 

10.4.4 Uncertainty assessment 

EMISSION FACTORS 

There are large uncertainties associated with the default emission factors for Tier 1 (see Tables 10.14 to 10.16). 

The uncertainty range for the default factors is estimated to be +30%. Improvements achieved by Tier 2 

methodologies are estimated to reduce uncertainty ranges in the emission factors to +20%. Accurate and welldesigned emission measurements from well characterised types of manure and manure management systems can 

help reduce these uncertainties further. These measurements must account for temperature, moisture conditions, 

aeration, VS content, duration of storage, and other aspects of treatment. 

The default values may have a large uncertainty for an individual country because they may not reflect the 

specific manure management conditions present within the country. Uncertainties can be reduced by developing 

and using MCF, Bo, and VS values that reflect country/region specific conditions. 
Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.49 

TABLE 10.18 

DEFINITIONS OF MANURE MANAGEMENT SYSTEMS

System Definition 

Pasture/Range/Paddock The manure from pasture and range grazing animals is allowed to lie as deposited, and is not 

managed. 

Daily spread Manure is routinely removed from a confinement facility and is applied to cropland or pasture 

within 24 hours of excretion. 

Solid storage 

The storage of manure, typically for a period of several months, in unconfined piles or stacks. 

Manure is able to be stacked due to the presence of a sufficient amount of bedding material or 

loss of moisture by evaporation. 

Dry lot A paved or unpaved open confinement area without any significant vegetative cover where 

accumulating manure may be removed periodically. 

Liquid/Slurry Manure is stored as excreted or with some minimal addition of water in either tanks or earthen 

ponds outside the animal housing, usually for periods less than one year. 

Uncovered anaerobic 

lagoon 

A type of liquid storage system designed and operated to combine waste stabilization and 

storage. Lagoon supernatant is usually used to remove manure from the associated confinement 

facilities to the lagoon. Anaerobic lagoons are designed with varying lengths of storage (up to a 

year or greater), depending on the climate region, the volatile solids loading rate, and other 

operational factors. The water from the lagoon may be recycled as flush water or used to irrigate 

and fertilise fields. 

Pit storage below 

animal confinements 

Collection and storage of manure usually with little or no added water typically below a slatted 

floor in an enclosed animal confinement facility, usually for periods less than one year. 

Anaerobic digester 

Animal excreta with or without straw are collected and anaerobically digested in a large 

containment vessel or covered lagoon. Digesters are designed and operated for waste 

stabilization by the microbial reduction of complex organic compounds to CO2 and CH4, which 

is captured and flared or used as a fuel. 

Burned for fuel The dung and urine are excreted on fields. The sun dried dung cakes are burned for fuel. 

Cattle and Swine deep 

bedding 

As manure accumulates, bedding is continually added to absorb moisture over a production cycle 

and possibly for as long as 6 to 12 months. This manure management system also is known as a 

bedded pack manure management system and may be combined with a dry lot or pasture. 

Composting - invessela Composting, typically in an enclosed channel, with forced aeration and continuous mixing. 

Composting - Static 

pilea Composting in piles with forced aeration but no mixing. 

Composting - Intensive 

windrowa Composting in windrows with regular (at least daily) turning for mixing and aeration. 

Composting - Passive 

windrowa Composting in windrows with infrequent turning for mixing and aeration. 

Poultry manure with 

litter 

Similar to cattle and swine deep bedding except usually not combined with a dry lot or pasture. 

Typically used for all poultry breeder flocks and for the production of meat type chickens 

(broilers) and other fowl. 

Poultry manure without 

litter 

May be similar to open pits in enclosed animal confinement facilities or may be designed and 

operated to dry the manure as it accumulates. The latter is known as a high-rise manure 

management system and is a form of passive windrow composting when designed and operated 

properly. 

Aerobic treatment 

The biological oxidation of manure collected as a liquid with either forced or natural aeration. 

Natural aeration is limited to aerobic and facultative ponds and wetland systems and is due 

primarily to photosynthesis. Hence, these systems typically become anoxic during periods 

without sunlight. 

a Composting is the biological oxidation of a solid waste including manure usually with bedding or another organic carbon source typically 

at thermophilic temperatures produced by microbial heat production. 
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10.50 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

ACTIVITY DATA – LIVESTOCK POPULATIONS 

See Section 10.2 Livestock and Feed Characterisation for discussion on uncertainty of animal population and 

characterisation data. 

ACTIVITY DATA – MANURE MANAGEMENT SYSTEM USAGE 

The uncertainty of the manure management system usage data will depend on the characteristics of each 

country's livestock industry and how information on manure management is collected. For example, for 

countries that rely almost exclusively on one type of management system, such as pasture and range, the 

uncertainty associated with management system usage data can be 10% or less. However, for countries where 

there is a wide variety of management systems used with locally different operating practices, the uncertainty 

range in management system usage data can be much higher, in the range of 25% to 50%, depending on the 

availability of reliable and representative survey data that differentiates animal populations by system usage. 

Preferably, each country should estimate the uncertainty associated with their management system usage data by 

using the methods described in Volume 1, Chapter 3. 

10.4.5 Completeness, Time series, Quality assurance / 

Quality control and Reporting 

A complete inventory should estimate CH4 emissions from all systems of manure management for all livestock 

species/categories identified in Section 10.2. Countries are encouraged to use manure management system 

definitions that are consistent with those presented in Table 10.18 to ensure that all types of systems are being 

accounted for. Population data should be cross-checked between main reporting mechanisms (such as FAO and 

national agricultural statistics databases) to ensure that information used in the inventory is complete and 

consistent. Because of the widespread availability of the FAO database of livestock information, most countries 

should be able to prepare, at a minimum, Tier 1 estimates for the major livestock categories. For more 

information regarding the completeness of livestock characterisation, see Section 10.2. 

Developing a consistent time series of emission estimates for this source category requires, at a minimum, 

collection of an internally consistent time series of livestock population statistics. General guidance on the 

development of a consistent time series is addressed in Volume 1, Chapter 5 (Time Series Consistency). 

If significant changes in manure management practices have occurred over time, the Tier 1 method will not 

provide an accurate time series of emissions (since the Tier 1 default factors are based on a historical set of 

parameters), and the Tier 2 method should be considered. When developing a time series for the Tier 2 method it 

is also necessary to collect country-specific manure management system data. In cases when manure 

management system data are not available for some period during the time series, trends can be used to 

extrapolate data from a sample area or region to the entire country, if climatic conditions are similar (i.e., 

temperature and rainfall). National livestock experts from government, industry, or universities should be 

consulted where possible to develop trends in management system usage and characteristics. 

If the emission estimation method has changed, historical data that are required by the current method should be 

collected and used to recalculate emissions for that period. If such data are not available, it may be appropriate to 

create a trend with recent data and use the trend to back-estimate management practices for the time series. For 

example, it may be known that certain livestock industries are converting to more intensive management systems 

in lieu of grazing. Historically, this changeover should be captured in the time series of emissions, through 

modifications to the manure management system allocation. It may be necessary to base this allocation on expert 

judgment from national experts where extensive survey data are not available. Volume 1, Chapter 5 provides 

additional guidance on how to address recalculation issues. Also, Section 10.2 suggests approaches for the 

animal population aspects. The inventory text should thoroughly explain how the change in farm practices or 

implementation of mitigation measures has affected the time series of activity data or emission factors. 

It is good practice to implement general quality control checks as outlined in Volume 1, Chapter 6, Quality 

Assurance/Quality Control and Verification, and expert review of the emission estimates. Additional quality 

control checks and quality assurance procedures may also be applicable, particularly if higher tier methods are 

used to determine emissions from this source. The general QA/QC related to data processing, handling, and 

reporting should be supplemented with procedures discussed below. 

ACTIVITY DATA CHECK 

• The inventory agency should review livestock data collection methods, in particular checking that livestock 

subspecies data were collected and aggregated correctly. The data should be cross-checked with previous 

years to ensure the data are reasonable and consistent with the expected trend. Inventory agencies should 

document data collection methods, identify potential areas of bias (e.g., systematic under-reporting of 
Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.51 

animal populations to statistical agencies by individual livestock owners), and evaluate the 

representativeness of the data. 

• Manure management system allocation should be reviewed on a regular basis to determine if changes in the 

livestock industry are being captured. Conversion from one type of management system to another, and 

technical modifications to system configuration and performance, should be captured in the system 

modeling for the affected livestock. 

• National agricultural policy and regulations may have an effect on parameters that are used to calculate 

manure emissions, and should be reviewed regularly to determine what impact they may have. For example, 

guidelines to reduce manure runoff into water bodies may cause a change in management practices, and thus 

affect the MCF value for a particular livestock category. Consistency should be maintained between the 

inventory and ongoing changes in agricultural practices. 

REVIEW OF EMISSION FACTORS 

• If using the Tier 1 method (using default IPCC emission factors), the inventory agency should evaluate how 

well the default VS excretion rates, Bo values, and manure management practices represent the defined 

animal population and manure characteristics of the country. This should be done by reviewing the 

background information from Tables 10A-4 to 10A-9 to see how well the default input parameters match the 

inventory area. If there is not a good match, substitution of more appropriate country-specific parameters 

can be used to develop an improved emission factor. 

• If using the Tier 2 method, the inventory agency should cross-check the country-specific parameters (e.g., 

VS excretion rates, Bo, and MCF) against the IPCC defaults. Significant differences between countryspecific parameters and default parameters should be explained and documented. 

• If using the Tier 2 method, derivation of VS rates should be compared to background assumptions used for 

the enteric fermentation Tier 2 inventory where applicable. For example, the gross energy and digestible 

energy components used in the enteric fermentation inventory can be used to cross-check independentlyderived VS rates. Application of Equation 10.24 (Volatile solid excretion rates) can be used in this case for 

such a cross-comparison on ruminants. For all animals, on a gross basis, VS rates should be consistent with 

the feed intake of the animal (i.e., waste energy should not exceed intake energy) and be consistent with the 

range of DE% values reported in Section 10.2, Table 10.2 of this report. 

• Whenever possible, available measurement data, even if they represent only a small sample of systems, 

should be reviewed relative to assumptions for MCF values and CH4 production estimates. Representative 

measurement data may provide insights into how well current assumptions predict CH4 production from 

manure management systems in the inventory area, and how certain factors (e.g., temperature, system 

configuration, retention time) are affecting emissions. Because of the relatively small amount of 

measurement data available for these systems worldwide, any new results can improve the understanding of 

these emissions and possibly their prediction. 

EXTERNAL REVIEW 

• The inventory agency should utilise experts in manure management and animal nutrition to conduct expert 

peer review of the methods and data used. While these experts may not be familiar with greenhouse gas 

emissions, their knowledge of key input parameters to the emission calculation can aid in the overall 

verification of the emissions. For example, animal nutritionists can evaluate VS production rates to see if 

they are consistent with feed utilization research for certain livestock species. Practicing farmers can provide 

insights into actual manure management techniques, such as storage times and mixed-system usage. 

Wherever possible, these experts should be completely independent of the inventory process in order to 

allow a true external review. 

It is good practice to document and archive all information required to produce the national emissions inventory 

estimates as outlined in Volume 1, Chapter 6 (Quality assurance/Quality control and Verification). When 

country-specific data (e.g., emission factors, manure management practices, and manure characteristics such as 

VS and Bo) have been used, the derivation of or references for these data should be clearly documented and 

reported along with the inventory results under the appropriate IPCC source category. To improve transparency, 

emission estimates from this source category should be reported along with the activity data and emission factors 

used to determine the estimates. 

The following information should be documented: 

• All activity data (e.g., livestock population data by species/category and by region), including sources used, 

complete citations for the statistical database from which data were collected, and (in cases where activity 
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10.52 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

data were not available directly from databases) the information and assumptions that were used to derive 

the activity data. 

• Climatic conditions (e.g., average temperature during manure storage) in regions if applicable. 

• Manure management system data, by livestock species/category and by region, if applicable. If manure 

management systems different than those defined in this chapter are used, these should be described. 

• The frequency of data collection, and estimates of accuracy and precision. 

• Emission factors documentation, including: 

(i) References for the emission factors that were used (IPCC default or otherwise); and 

(ii) The scientific basis of these emission factors and methods, including definition of input parameters 

and description of the process by which these emission factors and methods are derived, as well as 

describing sources and magnitudes of uncertainties. (In inventories, in which country- or regionspecific emission factors were used or in which new methods other than those described here were 

used). 

• If the Tier 1 method is used, all default emission factors used in the emissions estimation for the specific 

livestock population species/category. 

• If the Tier 2 method is used, documentation of emission factor calculation components, including: 

(i) VS and Bo values for all livestock population species/category in inventory, whether countryspecific, region-specific, or IPCC default; and 

(ii) MCF values for all manure management systems used, whether country-specific or IPCC default. 

10.5 N2O EMISSIONS FROM MANURE 

MANAGEMENT 

The section describes how to estimate the N2O produced, directly and indirectly, during the storage and 

treatment of manure before it is applied to land or otherwise used for feed, fuel, or construction purposes. The 

term ‘manure’ is used here collectively to include both dung and urine (i.e., the solids and the liquids) produced 

by livestock. The N2O emissions generated by manure in the system ‘pasture, range, and paddock’ occur directly 

and indirectly from the soil, and are therefore reported under the category ‘N2O Emissions from Managed Soils’ 

(see Chapter 11, Section 11.2). The emissions associated with the burning of dung for fuel are to be reported 

under ‘Fuel Combustion’ (see Volume 2: Energy), or under ‘Waste Combustion’ (see Volume 5: Waste) if 

burned without energy recovery. 

Direct N2O emissions occur via combined nitrification and denitrification of nitrogen contained in the manure. 

The emission of N2O from manure during storage and treatment depends on the nitrogen and carbon content of 

manure, and on the duration of the storage and type of treatment. Nitrification (the oxidation of ammonia 

nitrogen to nitrate nitrogen) is a necessary prerequisite for the emission of N2O from stored animal manures. 

Nitrification is likely to occur in stored animal manures provided there is a sufficient supply of oxygen. 

Nitrification does not occur under anaerobic conditions. Nitrites and nitrates are transformed to N2O and 

dinitrogen (N2) during the naturally occurring process of denitrification, an anaerobic process. There is general 

agreement in the scientific literature that the ratio of N2O to N2 increases with increasing acidity, nitrate 

concentration, and reduced moisture. In summary, the production and emission of N2O from managed manures 

requires the presence of either nitrites or nitrates in an anaerobic environment preceded by aerobic conditions 

necessary for the formation of these oxidized forms of nitrogen. In addition, conditions preventing reduction of 

N2O to N2, such as a low pH or limited moisture, must be present. 

Indirect emissions result from volatile nitrogen losses that occur primarily in the forms of ammonia and NOx. 

The fraction of excreted organic nitrogen that is mineralized to ammonia nitrogen during manure collection and 

storage depends primarily on time, and to a lesser degree temperature. Simple forms of organic nitrogen such as 

urea (mammals) and uric acid (poultry) are rapidly mineralized to ammonia nitrogen, which is highly volatile 

and easily diffused into the surrounding air (Asman et al., 1998; Monteny and Erisman, 1998). Nitrogen losses 

begin at the point of excretion in houses and other animal production areas (e.g., milk parlors) and continue 

through on-site management in storage and treatment systems (i.e., manure management systems). Nitrogen is 

also lost through runoff and leaching into soils from the solid storage of manure at outdoor areas, in feedlots and 

where animals are grazing in pastures. Pasture losses are considered separately in Chapter 11, Section 11.2, N2O 

Emissions from Managed Soils, as are emissions of nitrogen compounds from grazing livestock. 
Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.53 

Due to significant direct and indirect losses of manure nitrogen in management systems it is important to 

estimate the remaining amount of animal manure nitrogen available for application to soils or for use in feed, 

fuel, or construction purposes. This value is used for calculation N2O emissions from managed soils (see Chapter 

11, Section 11.2). The methodology to estimate manure nitrogen that is directly applied to soils, or available for 

use in feed, fuel, or construction purposes is described in this chapter under Section 10.5.4 “Coordination with 

reporting for N2O emissions from managed soils". 

10.5.1 Choice of method 

The level of detail and methods chosen for estimating N2O emissions from manure management systems will 

depend upon national circumstances and the decision tree in Figure 10.4 describes good practice in choosing a 

method accordingly. The following sections describe the different tiers referenced in the decision tree for 

calculating direct and indirect N2O emissions from manure management systems. 

Direct N2O emissions from Manure Management 

Tier 1 

The Tier 1 method entails multiplying the total amount of N excretion (from all livestock species/categories) in 

each type of manure management system by an emission factor for that type of manure management system (see 

Equation 10.25). Emissions are then summed over all manure management systems. The Tier 1 method is 

applied using IPCC default N2O emission factors, default nitrogen excretion data, and default manure 

management system data (see Annex 10A.2, Tables 10A-4 to 10A-8 for default management system allocations). 

Tier 2 

A Tier 2 method follows the same calculation equation as Tier 1 but would include the use of country-specific 

data for some or all of these variables. For example, the use of country-specific nitrogen excretion rates for 

livestock categories would constitute a Tier 2 methodology. 

Tier 3 

A Tier 3 method utilizes alternative estimation procedures based on a country-specific methodology. For 

example, a process-based, mass balance approach which tracks nitrogen throughout the system starting with feed 

input through final use/disposal could be utilized as a Tier 3 procedure. Tier 3 methods should be well 

documented to clearly describe estimation procedures. 

To estimate emissions from manure management systems, the livestock population must first be divided into 

categories that reflect the varying amounts of manure produced per animal as well as the manner in which the 

manure is handled. This division of manure by type of system should be the same as that used to characterize 

methane emissions from manure management (see Section 10.4). For example, if Tier 1 default emission factors 

are used for calculating CH4 emissions, then the manure management systems usage data from Tables 10A-4 to 

10A-8 should be applied. Detailed information on how to characterise the livestock population for this source is 

provided in Section 10.2. 

The following five steps are used to estimate direct N2O emissions from Manure Management: 

Step 1: Collect population data from the Livestock Population Characterisation; 

Step 2: Use default values or develop the annual average nitrogen excretion rate per head (Nex(T)) for each 

defined livestock species/category T; 

Step 3: Use default values or determine the fraction of total annual nitrogen excretion for each livestock 

species/category T that is managed in each manure management system S (MS(T,S)); 

Step 4: Use default values or develop N2O emission factors for each manure management system S (EF3(S)); 

and 

Step 5: For each manure management system type S, multiply its emission factor (EF3(S)) by the total amount of 

nitrogen managed (from all livestock species/categories) in that system, to estimate N2O emissions from that 

manure management system. Then sum over all manure management systems. 

In some cases, manure nitrogen may be managed in several types of manure management systems. For example, 

manure flushed from a dairy freestall barn to an anaerobic lagoon may first pass through a solids separation unit 

where some of the manure nitrogen is removed and managed as a solid. Therefore, it is important to consider 

carefully the fraction of manure nitrogen that is managed in each type of system. 

The calculation of direct N2O emissions from manure management is based on the following equation: 
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10.54 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

EQUATION 10.25

DIRECT N2O EMISSIONS FROM MANURE MANAGEMENT

( ) 28

44

2 ( ) ( ) ( ) ( , ) 3( )⎥ •

⎦

⎤ ⎢

⎣

⎡ • ⎥

⎦

⎤ ⎢

⎣

⎡ = ∑ ∑ • • S

S

T

N OD mm N T Nex T MS T S EF

Where: 

N2OD(mm) = direct N2O emissions from Manure Management in the country, kg N2O yr-1

N(T) = number of head of livestock species/category T in the country 

Nex(T)= annual average N excretion per head of species/category T in the country, kg N animal-1 yr-1

MS(T,S) = fraction of total annual nitrogen excretion for each livestock species/category T that is managed 

in manure management system S in the country, dimensionless 

EF3(S) = emission factor for direct N2O emissions from manure management system S in the country, kg 

N2O-N/kg N in manure management system S

S = manure management system 

T = species/category of livestock 

44/28 = conversion of (N2O-N)(mm) emissions to N2O(mm) emissions 

There may be losses of nitrogen in other forms (e.g., ammonia and NOx) as manure is managed on site. Nitrogen 

in the volatilized form of ammonia may be deposited at sites downwind from manure handling areas and 

contribute to indirect N2O emissions (see below). Countries are encouraged to consider using a mass balance 

approach (Tier 3) to track the manure nitrogen excreted, managed on site in manure management systems, and 

ultimately applied to managed soils. The estimation of the amount of manure nitrogen which is directly applied 

to managed soils or otherwise available for use as feed, fuel or construction purposes is described in the Section 

10.5.4, Coordination with reporting for N2O emissions from managed soils. See Chapter 11, Section 11.2 for 

procedures to calculate N2O emissions from managed manure nitrogen applied to soils. 

Indirect N2O emissions from Manure Management 

Tier 1 

The Tier 1 calculation of N volatilisation in forms of NH3 and NOx from manure management systems is based 

on multiplication of the amount of nitrogen excreted (from all livestock categories) and managed in each manure 

management system by a fraction of volatilised nitrogen (see Equation 10.26). N losses are then summed over all 

manure management systems. The Tier 1 method is applied using default nitrogen excretion data, default 

manure management system data (see Annex 10A.2, Tables 10A-4 to 10A-8) and default fractions of N losses 

from manure management systems due to volatilisation (see Table 10.22): 

EQUATION 10.26 

N LOSSES DUE TO VOLATILISATION FROM MANURE MANAGEMENT 

∑ ∑ ( ) ⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ = • • • −

S T T S

GasMS

volatilization MMS T T T S

Frac N N Nex MS

( , )

( ) ( ) ( , ) 100

Where: 

Nvolatilization-MMS = amount of manure nitrogen that is lost due to volatilisation of NH3 and NOx, kg N yr-1

N(T) = number of head of livestock species/category T in the country 

Nex(T)= annual average N excretion per head of species/category T in the country, kg N animal-1 yr-1

MS(T,S) = fraction of total annual nitrogen excretion for each livestock species/category T that is managed 

in manure management system S in the country, dimensionless 

FracGasMS = percent of managed manure nitrogen for livestock category T that volatilises as NH3 and NOx

in the manure management system S, % 
Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.55 

Figure 10.4 Decision tree for N2O emissions from Manure Management (Note 1) 

Start

Is a 

Tier 2 livestock

population characterization,

available and do you have country-specific 

N excretion rates, fractions of N

losses, EFs and management

system usage

data?

Collect data for

Tier 2 method.

Estimate direct and

indirect N2O emissions

using Tier 1 method and

IPCC defaults.

No

Note:

1: N2O emissions from manure management systems include both direct and indirect sources

2: See Volume 1 Chapter 4, "Methodological Choice and Identification of Key Categories" (noting Section 4.1.2 on limited resources), for 

discussion of key categories and use of decision trees.

3: As a rule of thumb, a livestock species would be significant if it accounts for 25-30% or more of emissions from the source category.

Is N2O from

manure management a 

key category2

 and is the

species a significant

share of

emissions3

?

No

Yes (all or some)

Estimate direct and

indirect N2O emissions

using Tier 2 method with

available country-specific

inputs.

No

Yes

Box 2: Tier 2

Box 1: Tier 1

Yes

Estimate emissions

using Tier 3 method.

Do you

have a country-specific

Tier 3 methodology?

Box 3: Tier 3
Volume 4: Agriculture, Forestry and Other Land Use 

10.56 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

The indirect N2O emissions from volatilisation of N in forms of NH3 and NOx (N2OG(mm)) are estimated using 

Equation 10.27: 

EQUATION 10.27 

INDIRECT N2O EMISSIONS DUE TO VOLATILISATION OF N FROM MANURE MANAGEMENT 

( ) 28

44

2 ( ) 4 = • • N OG mm Nvolatilization−MMS EF

Where: 

N2OG(mm) = indirect N2O emissions due to volatilization of N from Manure Management in the country, 

kg N2O yr-1

EF4 = emission factor for N2O emissions from atmospheric deposition of nitrogen on soils and water 

surfaces, kg N2O-N (kg NH3-N + NOx-N volatilised)-1 ; default value is 0.01 kg N2O-N (kg NH3-N + 

NOx-N volatilised)-1 , given in Chapter 11, Table 11.3 

Tier 2 

Countries may wish to develop a Tier 2 methodology for better consideration of national circumstances and to 

reduce uncertainty of estimates as much as possible. As for direct N2O emission from manure management, a 

Tier 2 method would follow the same calculation equation as Tier 1 but include the use of country-specific data 

for some or all of these variables. For example, the use of country-specific nitrogen excretion rates for livestock 

categories would constitute a Tier 2 method. National NH3 emission inventories developed by some countries 

could be used for Tier 2 estimation of nitrogen volatilisation from manure management systems. A Tier 2 

method would require more detailed characterisation of the flow of nitrogen throughout the animal housing and 

manure management systems used in the country. Double counting of emissions associated with the application 

of managed manure should be avoided, as well as manure associated with pasture and grazing operations, which 

should be calculated and reported under Chapter 11, Section 11.2 (N2O emissions from managed soils). 

There are extremely limited measurement data on leaching and runoff losses from various manure management 

systems. The greatest N losses due to runoff and leaching typically occur where animals are on a drylot. In drier 

climates, runoff losses are smaller than in high rainfall areas and have been estimated in the range from 3 to 6% 

of N excreted (Eghball and Power, 1994). Studies by Bierman et al. (1999) found nitrogen lost in runoff was 5 

to 19% of N excreted and 10 to 16% leached into soil, while other data show relatively low loss of nitrogen 

through leaching in solid storage (less than 5% of N excreted) but greater loss could also occur (Rotz, 2004). 

Further research is needed in this area to improve the estimated losses and the conditions and practices under 

which such losses occur. Equation 10.28 should only be used where there is country-specific information on the 

fraction of nitrogen loss due to leaching and runoff from manure management systems available. Therefore, 

estimation of N losses from leaching and runoff from manure management should be considered part of a Tier 2 

or Tier 3method. 

Nitrogen that leaches into soil and/or runs off during solid storage of manure at outdoor areas or in feedlots is 

derived as follows: 

EQUATION 10.28 

N LOSSES DUE TO LEACHING FROM MANURE MANAGEMENT SYSTEMS

∑ ∑ ( ) ⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ = • • • −

S T T S

leachMS

leaching MMS T T T S

Frac N N Nex MS

( , )

( ) ( ) ( , ) 100

Where: 

Nleaching-MMS = amount of manure nitrogen that leached from manure management systems, kg N yr-1

N(T) = number of head of livestock species/category T in the country 

Nex(T)= annual average N excretion per head of species/category T in the country, kg N animal-1 yr-1

MS(T,S) = fraction of total annual nitrogen excretion for each livestock species/category T that is managed 

in manure management system S in the country, dimensionless 

FracleachMS = percent of managed manure nitrogen losses for livestock category T due to runoff and 

leaching during solid and liquid storage of manure (typical range 1-20%) 
Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.57 

The indirect N2O emissions from leaching and runoff of nitrogen from manure management systems (N2OL(mm)) 

are estimated using Equation 10.29: 

EQUATION 10.29 

INDIRECT N2O EMISSIONS DUE TO LEACHING FROM MANURE MANAGEMENT 

( ) 28

44

2 ( ) 5 = • • N OL mm Nleaching −MMS EF

Where: 

N2OL(mm) = indirect N2O emissions due to leaching and runoff from Manure Management in the country, 

kg N2O yr-1

EF5 = emission factor for N2O emissions from nitrogen leaching and runoff, kg N2O-N/kg N leached and 

runoff (default value 0.0075 kg N2O-N (kg N leaching/runoff)-1, given in Chapter 11, Table 11.3

Tier 3 

To reduce uncertainty of the estimates, a Tier 3 method could be developed with country-specific emission 

factors for volatilisation and nitrogen leaching and runoff based on actual measurements. 

All losses of N through manure management systems (both direct and indirect) need to be excluded from the 

amount of manure N that is available for application to soils and which is reported in Chapter 11, Section 11.2 

N2O Emissions from Managed Soils. Refer to Section 10.5.4, Coordination with reporting for N2O emissions 

from managed soils, for guidance on calculating total N losses from manure management systems. 

10.5.2 Choice of emission factors 

Annual average nitrogen excretion rates, Nex(T)

Tier 1 

Annual nitrogen excretion rates should be determined for each livestock category defined by the livestock 

population characterisation. Country-specific rates may either be taken directly from documents or reports such 

as agricultural industry and scientific literature, or derived from information on animal nitrogen intake and 

retention (as explained below). In some situations, it may be appropriate to use excretion rates developed by 

other countries that have livestock with similar characteristics. 

If country-specific data cannot be collected or derived, or appropriate data are not available from another country, 

the IPCC default nitrogen excretion rates presented in Table 10.19 can be used. These rates are presented in units 

of nitrogen excreted per 1000 kg of animal per day. These rates can be applied to livestock sub-categories of 

varying ages and growth stages using a typical average animal mass (TAM) for that population sub-category, as 

shown in Equation 10.30. 

EQUATION 10.30 

ANNUAL N EXCRETION RATES

365

1000 ( ) ( ) = • • TAM Nex T Nrate T

Where: 

Nex(T) = annual N excretion for livestock category T, kg N animal-1 yr-1

Nrate(T) = default N excretion rate, kg N (1000 kg animal mass)-1 day-1 (see Table 10.19) 

TAM(T) = typical animal mass for livestock category T, kg animal-1

Default TAM values are provided in Tables 10A-4 to 10A-9 in Annex 10A.2. However, it is preferable to 

collect country-specific TAM values due to the sensitivity of nitrogen excretion rates to different weight 

categories. For example, market swine may vary from nursery pigs weighing less than 30 kilograms to finished 

pigs that weigh over 90 kilograms. By constructing animal population groups that reflect the various growth 

stages of market pigs, countries will be better able to estimate the total nitrogen excreted by their swine 

population. 
Volume 4: Agriculture, Forestry and Other Land Use 

10.58 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

When estimating the Nex(T) for animals whose manure is classified in the manure management system burned 

for fuel (Table 10.21, Default emission factors for direct N2O emissions from Manure Management), it should be 

kept in mind that the dung is burned and the urine stays in the field. As a rule of thumb, 50% of the nitrogen 

excreted is in the dung and 50% is in the urine. If the burned dung is used as fuel, then emissions are reported 

under the IPCC category Fuel Combustion (Volume 2: Energy), whereas if the dung is burned without energy 

recovery the emissions should be reported under the IPCC category Waste Incineration (Volume 5: Waste). 

Tier 2 

The annual amount of N excreted by each livestock species/category depends on the total annual N intake and 

total annual N retention of the animal. Therefore, N excretion rates can be derived from N intake and N retention 

data. Annual N intake (i.e., the amount of N consumed by the animal annually) depends on the annual amount of 

feed digested by the animal, and the protein content of that feed. Total feed intake depends on the production 

level of the animal (e.g., growth rate, milk production, draft power). Annual N retention (i.e., the fraction of N 

intake that is retained by the animal for the production of meat, milk, or wool) is a measure of the animal's 

efficiency of production of animal protein from feed protein. Nitrogen intake and retention data for specific 

livestock species/categories may be available from national statistics or from animal nutrition specialists. 

Nitrogen intake can also be calculated from data on feed and crude protein intake developed in Section 10.2. 

Default N retention values are provided in Table 10.20, Default values for the fraction of nitrogen in feed taken 

in by animals that is retained by the different animal species/categories. Rates of annual N excretion for each 

livestock species/category (Nex(T)) are derived as follows: 

EQUATION 10.31 

ANNUAL N EXCRETION RATES (TIER 2) 

( ) Nex(T ) Nint ake(T ) 1− Nretention(T ) = •

Where: 

Nex(T) = annual N excretion rates, kg N animal-1 yr-1

Nintake(T) = the annual N intake per head of animal of species/category T , kg N animal-1 yr-1

Nretention(T) = fraction of annual N intake that is retained by animal of species/category T, dimensionless 

Example of Tier 2 method for estimating nitrogen excretion for cattle 

Nitrogen excretion may be calculated based on the same dietary assumptions used in modelling enteric 

fermentation emissions (see Section 10.2). The amount of nitrogen excreted by cattle can be estimated as the 

difference between the total nitrogen taken in by the animal and the total nitrogen retained for growth and milk 

production. Equations 10.32 and 10.33 can be used to calculate the variables for nitrogen intake and nitrogen 

retained for use in Equation 10.31. The total nitrogen intake rate is derived as follows: 

EQUATION 10.32 

N INTAKE RATES FOR CATTLE

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎝

⎛

= • 6.25

100

%

18.45 ( )

CP

GE Nintake T

Where: 

Nintake(T) = daily N consumed per animal of category T, kg N animal-1 day-1

GE = gross energy intake of the animal, in enteric model, based on digestible energy, milk production, 

pregnancy, current weight, mature weight, rate of weight gain, and IPCC constants, MJ animal-1 day-1

18.45 = conversion factor for dietary GE per kg of dry matter, MJ kg-1. This value is relatively constant 

across a wide range of forage and grain-based feeds commonly consumed by livestock. 

CP% = percent crude protein in diet, input 

6.25 = conversion from kg of dietary protein to kg of dietary N, kg feed protein (kg N)-1
Chapter 10: Emi

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.19 

DEFAULT VALUES FOR NITROGEN EXCRETION RATE a (KG N (1000 KG ANIMAL MASS)-1 DAY-1

Region 

Category of animal 

North America Western Europe Eastern Europe Oceania Latin America 

Dairy Cattle 0.44 0.48 0.35 0.44 0.48 Other Cattle 0.31 0.33 0.35 0.50 0.36 Swineb 0.50 0.68 0.74 0.73 1.64  Market 0.42 0.51 0.55 0.53 1.57  Breeding 0.24 0.42 0.46 0.46 0.55 Poultry 0.83 0.83 0.82 0.82 0.82  Hens >/= 1 yr 0.83 0.96 0.82 0.82 0.82  Pullets 0.62 0.55 0.60 0.60 0.60  Other Chickens 0.83 0.83 0.82 0.82 0.82  Broilers 1.10 1.10 1.10 1.10 1.10  Turkeys 0.74 0.74 0.74 0.74 0.74  Ducks 0.83 0.83 0.83 0.83 0.83 Sheep 0.42 0.85 0.90 1.13 1.17 Goats 0.45 1.28 1.28 1.42 1.37 Horses (and mules, asses) 0.30 0.26 0.30 0.30 0.46 Camelsc 0.38 0.38 0.38 0.38 0.46 Buffaloc 0.32 0.32 0.32 0.32 0.32 Mink and Polecat (kg N head-1 yr1)d 4.59 4.59 4.59 4.59 4.59 Rabbits (kg N head-1 yr-1) 8.10 8.10 8.10 8.10 8.10 Fox and Racoon (kg N head-1 yr-1)d 12.09 12.09 12.09 12.09 12.09 The uncertainty in these estimates is +50%. a Summarized from 1996 IPCC Guidelines, 1997; European Environmental Agency, 2002; USA EPA National NH3 Inventory Draft Report, 2004; and data of GHG 

Secretariat UNFCCC in 2004. 

b Nitrogen excretion for swine are based on an estimated country population of 90% market swine and 10% breeding swine. c Modified from European Environmental Agency, 2002. d Data of Hutchings et al., 2001.
Volume 4: Agriculture, Forestry and Other Land Use 

10.60 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.20 

DEFAULT VALUES FOR THE FRACTION OF NITROGEN IN FEED INTAKE OF LIVESTOCK THAT IS RETAINED BY 

THE DIFFERENT LIVESTOCK SPECIES/CATEGORIES (FRACTION N-INTAKE RETAINED BY THE ANIMAL)

Livestock category Nretention(T)

(kg N retained/animal/year) (kg N intake/animal/year)-1

Dairy Cows 0.20 

Other Cattle 0.07 

Buffalo 0.07 

Sheep 0.10 

Goats 0.10 

Camels 0.07 

Swine 0.30 

Horses 0.07 

Poultry 0.30 

The uncertainty in these estimates is +50%. 

Source: Judgement of IPCC Expert Group (see Co-chairs, Editors and Experts; N2O emissions from Manure Management). 

The total nitrogen retained is derived as follows: 

EQUATION 10.33 

N RETAINED RATES FOR CATTLE

⎥

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎢

⎣

⎡

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ • • −

+

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ •

=

6.25

1000

7.03

268

6.38

100

%

( )

WG

NE

WG Milk PR Milk

N

g

retention T

Where: 

Nretention(T) = daily N retained per animal of category T, kg N animal-1 day-1

Milk = milk production, kg animal-1 day-1 (applicable to dairy cows only) 

Milk PR% = percent of protein in milk, calculated as [1.9 + 0.4 ● %Fat], where %Fat is an input, 

assumed to be 4% (applicable to dairy cows only) 

6.38 = conversion from milk protein to milk N, kg Protein (kg N)-1

WG = weight gain, input for each livestock category, kg day-1

268 and 7.03 = constants from Equation 3-8 in NRC (1996) 

NEg = net energy for growth, calculated in livestock characterisation, based on current weight, mature 

weight, rate of weight gain, and IPCC constants, MJ day-1

1000 = conversion from grams per kilogram, g kg-1

6.25 = conversion from kg dietary protein to kg dietary N, kg Protein (kg N)-1

Annual nitrogen excretion data are also used for the calculation of direct and indirect N2O emissions from 

managed soils (see Chapter 11, Section 11.2, N2O emissions from managed soils). The same rates of N excretion, 

and methods of derivation, that are used to estimate N2O emissions from Manure Management should be used to 

estimate N2O emissions from managed soils. 

Emission factors for direct N2O emissions from Manure Management 

The best estimate will be obtained using country-specific emission factors that have been fully documented in 

peer reviewed publications. It is good practice to use country-specific emission factors that reflect the actual 

duration of storage and type of treatment of animal manure in each management system that is used. Good 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.61 

practice in the derivation of country-specific emission factors involves the measurement of emissions (per unit 

of manure N) from different management systems, taking into account variability in duration of storage and 

types of treatment. When defining types of treatment, conditions such as aeration and temperature should be 

taken into account. If inventory agencies use country-specific emission factors, they are encouraged to provide 

justification for these values via peer-reviewed documentation. 

If appropriate country-specific emission factors are unavailable, inventory agencies are encouraged to use the 

default emission factors presented in Table 10.21, Default emission factors for direct N2O emissions from 

Manure Management. This table contains default emission factors by manure management system. Note that 

emissions from liquid/slurry systems without a natural crust cover, anaerobic lagoons, and anaerobic digesters 

are considered negligible based on the absence of oxidized forms of nitrogen entering these systems combined 

with the low potential for nitrification and denitrification to occur in the system. 

Emission factors for indirect N2O emissions from Manure Management 

In order to estimate indirect N2O emissions from Manure Management, two fractions of nitrogen losses (due to 

volatilization and leaching/runoff), and two indirect N2O emissions factors associated with these losses (EF4 and 

EF5) are needed. Default values for volatilization N losses are presented in the Table 10.22. Values represent 

average rates for N loss in the forms of NH3 and NOx, with most of the loss in the form of NH3. Ranges reflect 

values that appear in the literature. The values represent conditions without any significant nitrogen control 

measures in place. Countries are encouraged to develop country-specific values, particularly related to ammonia 

losses where component emissions may be well characterized as part of larger air quality assessments and where 

emissions may be affected by nitrogen reduction strategies. For example, detailed methodologies for estimating 

NH3 and other nitrogen losses using mass balance/mass flow procedures are described in the EMEP/CORINAIR 

Atmospheric Inventory Guidebook, Chapter 1009 (European Environmental Agency, 2002). 

The fraction of manure nitrogen that leaches from manure management systems (FracleachMS) is highly uncertain 

and should be developed as a country-specific value applied in Tier 2 method. 

Default values for EF4 (N volatilisation and re-deposition) and EF5 (N leaching/runoff) are given in Chapter 11, 

Table 11.3 (Default emission, volatilisation and leaching factors for indirect soil N2O emissions). 

10.5.3 Choice of activity data 

There are two main types of activity data for estimating N2O emissions from manure management systems: (1) 

livestock population data, and (2) manure management system usage data. 

Livestock population data, N(T) 

The animal population data should be obtained using the approach described in Section 10.2. If using default 

nitrogen excretion rates to estimate N2O emissions from manure management systems, a Tier 1 livestock 

population characterisation is sufficient. To estimate N2O emissions from Manure Management using calculated 

nitrogen excretion rates, a Tier 2 characterisation must be performed. As noted in Section 10.2, good practice in 

characterising livestock populations is to conduct a single characterisation that will provide the activity data for 

all emissions sources that depend on livestock population data. 

Manure management system usage data, MS(T,S)

The manure management system usage data used to estimate N2O emissions from Manure Management should 

be the same as those that are used to estimate CH4 emissions from Manure Management (see Table 10.18 for a 

summary of the main types of manure management systems). The portion of manure managed in each manure 

management system must be collected for each representative livestock category. Note that in some cases, 

manure may be managed in several types of manure management systems. For example, manure flushed from a 

dairy freestall barn to an anaerobic lagoon may first pass through a solids separation unit where some of the 

manure solids are removed and managed as a solid. Therefore, it is important to carefully consider the fraction of 

manure that is managed in each type of system. 

The best means of obtaining manure management system distribution data is to consult regularly published 

national statistics. If such statistics are unavailable, the preferred alternative is to conduct an independent survey 

of manure management system usage. If the resources are not available to conduct a survey, experts should be 

consulted to obtain an opinion of the system distribution. If country-specific manure management system usage 

data are not available, default values should be used. The IPCC default values for dairy cows, other cattle, 

buffalo, swine (market and breeding swine), and poultry should be taken from Tables 10A-4 through 10A-8 of 

Annex 10A.2. Manure from other animal categories is typically managed in pastures and grazing operations. 
Volume 4: Agriculture, Forestry and Other Land Use 

10.62 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.21 

DEFAULT EMISSION FACTORS FOR DIRECT N2O EMISSIONS FROM MANURE MANAGEMENT

System Definition 

EF3

[kg N2O-N 

(kg Nitrogen 

excreted)-1] 

Uncertainty 

ranges of EF3 Sourcea

Pasture/Range/ 

Paddock 

The manure from pasture and range 

grazing animals is allowed to lie as is, 

and is not managed. 

Direct and indirect N2O emissions associated with the manure deposited on 

agricultural soils and pasture, range, paddock systems are treated in 

Chapter 11, Section 11.2, N2O emissions from managed soils. 

Daily spread 

Manure is routinely removed from a 

confinement facility and is applied to 

cropland or pasture within 24 hours of 

excretion. N2O emissions during 

storage and treatment are assumed to 

be zero. N2O emissions from land 

application are covered under the 

Agricultural Soils category. 

0 Not applicable 

Judgement by IPCC Expert Group 

(see Co-chairs, Editors and 

Experts; N2O emissions from 

Manure Management). 

Solid storageb

The storage of manure, typically for a 

period of several months, in 

unconfined piles or stacks. Manure is 

able to be stacked due to the presence 

of a sufficient amount of bedding 

material or loss of moisture by 

evaporation. 

0.005 Factor of 2 

Judgement of IPCC Expert Group 

in combination with Amon et al.

(2001), which shows emissions 

ranging from 0.0027 to 0.01 kg 

N2O-N (kg N)-1. 

Dry lot 

A paved or unpaved open 

confinement area without any 

significant vegetative cover where 

accumulating manure may be 

removed periodically. Dry lots are 

most typically found in dry climates 

but also are used in humid climates. 

0.02 Factor of 2 

Judgement of IPCC Expert Group 

in combination with Kulling 

(2003). 

With 

natural 

crust cover 

0.005 Factor of 2 

Judgement of IPCC Expert Group 

in combination with Sommer et 

al. (2000). 

Liquid/Slurry 

Manure is stored as 

excreted or with some 

minimal addition of 

water to facilitate 

handling and is stored 

in either tanks or 

earthen ponds. 

Without 

natural 

crust cover 

0 Not applicable 

Judgement of IPCC Expert Group 

in combination with the following 

studies: Harper et al. (2000), 

Lague et al. (2004), Monteny et 

al. (2001), and Wagner-Riddle 

and Marinier (2003). Emissions 

are believed negligible based on 

the absence of oxidized forms of 

nitrogen entering systems in 

combination with low potential 

for nitrification and denitrification 

in the system. 

Uncovered 

anaerobic 

lagoon 

Anaerobic lagoons are designed and 

operated to combine waste 

stabilization and storage. Lagoon 

supernatant is usually used to remove 

manure from the associated 

confinement facilities to the lagoon. 

Anaerobic lagoons are designed with 

varying lengths of storage (up to a 

year or greater), depending on the 

climate region, the volatile solids 

loading rate, and other operational 

factors. The water from the lagoon 

may be recycled as flush water or 

used to irrigate and fertilise fields. 

0 Not applicable 

Judgement of IPCC Expert Group 

in combination with the following 

studies: Harper et al. (2000), 

Lague et al. (2004), Monteny et 

al. (2001), and Wagner-Riddle 

and Marinier (2003). Emissions 

are believed negligible based on 

the absence of oxidized forms of 

nitrogen entering systems in 

combination with low potential 

for nitrification and denitrification 

in the system. 

Pit storage 

below animal 

confinements 

Collection and storage of manure 

usually with little or no added water 

typically below a slatted floor in an 

enclosed animal confinement facility. 

0.002 Factor of 2 

Judgement of IPCC Expert Group 

in combination with the following 

studies: Amon et al. (2001), 

Kulling (2003), and Sneath et al.

(1997). 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.63 

TABLE 10.21 (CONTINUED) 

DEFAULT EMISSION FACTORS FOR DIRECT N2O EMISSIONS FROM MANURE MANAGEMENT

System Definition 

EF3

[kg N2O-N 

(kg Nitrogen 

excreted)-1] 

Uncertainty 

ranges of EF3 Sourcea

Anaerobic 

digester 

Anaerobic digesters are designed and 

operated for waste stabilization by the 

microbial reduction of complex 

organic compounds to CH4 and CO2, 

which is captured and flared or used 

as a fuel. 

0 Not applicable 

Judgement of IPCC Expert Group 

in combination with the following 

studies: Harper et al. (2000), 

Lague et al. (2004) Monteny et al.

(2001), and Wagner-Riddle and 

Marinier (2003). Emissions are 

believed negligible based on the 

absence of oxidized forms of 

nitrogen entering systems in 

combination with low potential 

for nitrification and denitrification 

in the system. 

The dung is excreted on fields. The 

sun dried dung cakes are burned for 

fuel. 

The emissions associated with the burning of the dung are to be reported 

under the IPCC category 'Fuel Combustion' if the dung is used as fuel and 

under the IPCC category 'Waste Incineration' if the dung is burned without 

Burned for fuel energy recovery. 

or as waste 

Urine N deposited on pasture and 

paddock 

Direct and indirect N2O emissions associated with the urine deposited on 

agricultural soils and pasture, range, paddock systems are treated in 

Chapter 11, Section 11.2, N2O emissions from managed soils. 

No mixing 0.01 Factor of 2 

Average value based on Sommer 

and Moller (2000), Sommer 

(2000), Amon et al. (1998), and 

Nicks et al. (2003). 

Cattle and 

swine deep 

bedding 

As manure 

accumulates, bedding 

is continually added to 

absorb moisture over a 

production cycle and 

possibly for as long as 

6 to 12 months. This 

manure management 

system also is known 

as a bedded pack 

manure management 

system and may be 

combined with a dry 

lot or pasture. 

Active 

mixing 0.07 Factor of 2 

Average value based on Nicks et 

al. (2003) and Moller et al.

(2000). Some literature cites 

higher values to 20% for well 

maintained, active mixing, but 

those systems included treatment 

for ammonia which is not typical. 

Composting - 

In-Vesselc

Composting, typically in an enclosed 

channel, with forced aeration and 

continuous mixing. 

0.006 Factor of 2 

Judgement of IPCC Expert Group. 

Expected to be similar to static 

piles. 

Composting - 

Static Pilec

Composting in piles with forced 

aeration but no mixing. 0.006 Factor of 2 Hao et al. (2001). 

Composting - 

Intensive 

Windrowc

Composting in windrows with regular 

turning for mixing and aeration. 0.1 Factor of 2 

Judgement of IPCC Expert Group. 

Expected to be greater than 

passive windrows and intensive 

composting operations, as 

emissions are a function of the 

turning frequency. 

Composting - 

Passive 

Windrowc

Composting in windrows with 

infrequent turning for mixing and 

aeration. 

0.01 Factor of 2 Hao et al. (2001). 

Poultry manure 

with litter 

Similar to deep bedding systems. 

Typically used for all poultry breeder 

flocks and for the production of meat 

type chickens (broilers) and other 

fowl. 

0.001 Factor of 2 

Judgement of IPCC Expert Group 

based on the high loss of ammonia 

from these systems, which limits 

the availability of nitrogen for 

nitrification/denitrification. 

Poultry manure 

without litter 

May be similar to open pits in 

enclosed animal confinement facilities 

or may be designed and operated to 

dry the manure as it accumulates. The 

latter is known as a high-rise manure 

management system and is a form of 

passive windrow composting when 

designed and operated properly. 

0.001 Factor of 2 

Judgement of IPCC Expert Group 

based on the high loss of ammonia 

from these systems, which limits 

the availability of nitrogen for 

nitrification/denitrification. 
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10.64 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10.21 (CONTINUED) 

DEFAULT EMISSION FACTORS FOR DIRECT N2O EMISSIONS FROM MANURE MANAGEMENT

System Definition 

EF3

[kg N2O-N 

(kg Nitrogen 

excreted)-1] 

Uncertainty 

ranges of EF3 Sourcea

Natural 

aeration 

systems 

0.01 Factor of 2 

Judgement of IPCC Expert Group. 

Nitrification-denitrification is 

used widely for the removal of 

nitrogen in the biological 

treatment of municipal and 

industrial wastewaters with 

negligible N2O emissions. Limited 

oxidation may increase emissions 

compared to forced aeration 

systems. 

Aerobic 

treatment 

The biological 

oxidation of manure 

collected as a liquid 

with either forced or 

natural aeration. 

Natural aeration is 

limited to aerobic and 

facultative ponds and 

wetland systems and is 

due primarily to 

photosynthesis. Hence, 

these systems typically 

become anoxic during 

periods without 

sunlight. 

Forced 

aeration 

systems 

0.005 Factor of 2 

Judgement of IPCC Expert Group. 

Nitrification-denitrification is 

used widely for the removal of 

nitrogen in the biological 

treatment of municipal and 

industrial wastewaters with 

negligible N2O emissions. 

a

Also see Dustan (2002), which compiled information from some of the original references cited. 

b Quantitative data should be used to distinguish whether the system is judged to be a solid storage or liquid/slurry. The borderline 

between dry and liquid can be drawn at 20% dry matter content. c

 Composting is the biological oxidation of a solid waste including manure usually with bedding or another organic carbon source

typically at thermophilic temperatures produced by microbial heat production.

10.5.4 Coordination with reporting for N2O emissions from 

managed soils 

Following storage or treatment in any system of manure management, nearly all the manure will be applied to 

land. The emissions that subsequently arise from the application of the manure to soil are to be reported under 

the category N2O emissions from managed soils. The methods for estimating these emissions are discussed in 

Chapter 11, Section 11.2. In estimating N2O emissions from managed soils, the amount of animal manure 

nitrogen that is directly applied to soils, or available for use in feed, fuel, or construction purposes, are 

considered. 

A significant proportion of the total nitrogen excreted by animals in managed systems (i.e., all livestock except 

those in pasture and grazing conditions) is lost prior to final application to managed soils or for use as feed, fuel, 

or for construction purposes. In order to estimate the amount of animal manure nitrogen that is directly applied 

to soils, or available for use in feed, fuel, or construction purposes (i.e., the value which is used in Chapter 11, 

Equation 11.1 or 11.2), it is necessary to reduce the total amount of nitrogen excreted by animals in managed 

systems by the losses of N through volatilisation (i.e., NH3, N2 and NOx), conversion to N2O and losses through 

leaching and runoff. 

Where organic forms of bedding material (straw, sawdust, chippings, etc.) are used, the additional nitrogen from 

the bedding material should also be considered as part of the managed manure N applied to soils. Bedding is 

typically collected with the remaining manure and applied to soils. It should be noted, however, that since 

mineralization of nitrogen compounds in beddings occurs more slowly compared to manure and the 

concentration of ammonia fraction in organic beddings is negligible, both volatilization and leaching losses 

during storage of bedding are assumed to be zero (European Environmental Agency, 2002). 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.65 

TABLE 10.22 

DEFAULT VALUES FOR NITROGEN LOSS DUE TO VOLATILISATION OF NH3 AND NOX FROM MANURE 

MANAGEMENT

Animal type Manure management system (MMS) a

N loss from MMS due to volatilisation of 

N-NH3 and N-NOx (%) b

 FracGasMS (Range of FracGasMS) 

Anaerobic lagoon 40% (25 – 75) 

Pit storage 25% (15 – 30) 

Deep bedding 40% (10 – 60) 

Liquid/slurry 48% (15 – 60) 

Swine 

Solid storage 45% (10 – 65) 

Anaerobic lagoon 35% (20 – 80) 

Liquid/Slurry 40% (15 – 45) 

Pit storage 28% (10 – 40) 

Dry lot 20% (10 – 35) 

Solid storage 30% (10 – 40) 

Dairy Cow 

Daily spread 7% (5 – 60) 

Poultry without litter 55% (40 – 70) 

Anaerobic lagoon 40% (25 – 75) 

Poultry 

Poultry with litter 40% (10 – 60) 

Dry lot 30% (20 – 50) 

Solid storage 45% (10 – 65) 

Other Cattle 

Deep bedding 30% (20 – 40) 

Deep bedding 25% (10 – 30) Other c

Solid storage 12% (5 – 20) 

a Manure Management System here includes associated N losses at housing and final storage system. 

b Volatilization rates based on judgement of IPCC Expert Group and following sources: Rotz ( 2003), Hutchings et al.

(2001), and U.S EPA (2004). 

c Other includes sheep, horses, and fur-bearing animals. 

The estimate of managed manure nitrogen available for application to managed soils, or available for use in feed, 

fuel, or construction purposes is based on the following equation: 

EQUATION 10.34 

MANAGED MANURE N AVAILABLE FOR APPLICATION TO MANAGED SOILS, FEED, FUEL OR 

CONSTRUCTION USES

( )

[ ]

∑ ∑ ⎪

⎭

⎪

⎬

⎫

⎪

⎩

⎪

⎨

⎧

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎣

⎡

• •

⎥ +

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ • • • − = S T

T T S beddingMS

LossMS

T T T S

MMS Avb

N MS N

Frac N Nex MS

N

( )

( ) ( , )

( ) ( ) ( , )

_ 100

1

Where: 

NMMS_Avb = amount of managed manure nitrogen available for application to managed soils or for feed, 

fuel, or construction purposes, kg N yr-1 

N(T) = number of head of livestock species/category T in the country 

Nex(T)= annual average N excretion per animal of species/category T in the country, kg N animal-1 yr-1 
Volume 4: Agriculture, Forestry and Other Land Use 

10.66 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

MS(T,S) = fraction of total annual nitrogen excretion for each livestock species/category T that is managed 

in manure management system S in the country, dimensionless 

FracLossMS = amount of managed manure nitrogen for livestock category T that is lost in the manure 

management system S, % (see Table 10.23) 

NbeddingMS = amount of nitrogen from bedding (to be applied for solid storage and deep bedding MMS if 

known organic bedding usage), kg N animal-1 yr-1

S = manure management system 

T = species/category of livestock 

Bedding materials vary greatly and inventory compilers should develop values for NbeddingMS based on the 

characteristics of bedding material used in their livestock industries. Limited data from scientific literature 

indicates the amount of nitrogen contained in organic bedding material applied for dairy cows and heifers is 

usually around 7 kg N animal-1 yr-1, for other cattle is 4 kg N animal-1 yr-1, for market and breeding swine is 

around 0.8 and 5.5 kg N animal-1 yr-1, respectively. For deep bedding systems, the amount of N in litter is 

approximately double these amounts (Webb, 2001; Döhler et al., 2002). 

Table 10.23 presents default values for total nitrogen losses from manure management systems. These default 

values include losses that occur from the point of excretion, including animal housing losses, manure storage 

losses, and losses from leaching and runoff at the manure storage system where applicable. For example, values 

provided for dairy anaerobic lagoon systems include nitrogen losses that occur in the dairy barn and milking 

parlour prior to the collection and treatment of manure, as well as those that occur from the lagoon. 

There is a high level of variability in the range of total nitrogen losses from managed manure systems. As shown 

in Table 10.23, the majority of these are due to volatilization losses, primarily ammonia losses that occur rapidly 

following the excretion of the manure. However, losses also occur in the form of NO3, N2O, and N2 as well from 

leaching and runoff that occurs where manure is stored in piles. The values in Table 10.23 reflect average values 

for typical housing/storage combinations for each animal category. Countries are encouraged to develop countryspecific values, particularly related to ammonia losses where component emissions may be well characterised for 

local practices as part of larger air quality assessments and where emissions may be affected by nitrogen 

reduction strategies. 

Countries may wish to develop an alternative approach for better consideration of national circumstances and to 

reduce uncertainty of estimates as much as possible. This approach would entail more detailed characterisation 

of the flow of nitrogen through the components of the animal housing and manure management systems used in 

the country, accounting for any mitigation activity (e.g., the use of covers over slurry tanks), and consideration 

of local practices, such as type of bedding material used. 

10.5.5 Uncertainty assessment 

EMISSION FACTORS – NITROGEN EXCRETION RATES 

Uncertainty ranges for the default N excretion rates are estimated at about +50% (Source: Judgement by IPCC 

Expert Group). The uncertainty ranges for the default N retention values provided here are also +50% (see Table 

10.20). If inventory agencies derive N excretion rates using accurate in-country statistics on N intake and N 

retention, the uncertainties associated with the N excretion rates may be reduced substantially. The degree of 

uncertainty may be further reduced by using direct emission measurements of nitrogen losses from specific 

manure management systems. 

EMISSION FACTORS – DIRECT N2O EMISSIONS 

There are large uncertainties associated with the default emission factors for this source category (–50% to 

+100%). Accurate and well-designed emission measurements from well characterised types of manure and 

manure management systems can help reduce these uncertainties. These measurements must account for 

temperature, moisture conditions, aeration, manure N content, metabolisable carbon, duration of storage, and 

other aspects of treatment. 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.67 

TABLE 10.23 

DEFAULT VALUES FOR TOTAL NITROGEN LOSS FROM MANURE MANAGEMENT 

Animal 

category Manure management system a Total N loss from MMS b

FracLossMS (Range of FracLossMS) 

Anaerobic lagoon 78% (55 – 99) 

Pit storage 25% (15 – 30) 

Deep bedding 50% (10 – 60) 

Liquid/Slurry 48% (15 – 60) 

Swine 

Solid storage 50% (20 – 70) 

Anaerobic lagoon 77% (55 – 99) 

Liquid/Slurry 40% (15 – 45) 

Pit storage 28% (10 – 40) 

Dry lot 30% (10 – 35) 

Solid storage 40% (10 – 65) 

Dairy Cow 

Daily spread 22% (15 – 60) 

Poultry without litter 55% (40 – 70) 

Poultry Anaerobic lagoon 77% (50 – 99) 

Poultry with litter 50% (20 – 80) 

Dry lot 40% (20 – 50) 

Other Cattle Solid storage 50% (20 – 70) 

Deep bedding 40% (10 – 50) 

Deep bedding 35% (15 – 40) Other c

Solid storage 15% (5 – 20) 

a Manure Management System here includes associated N losses at housing and final storage system. 

b Total N loss rates based on judgement of IPCC Expert Group and following sources: Rotz ( 2003), Hutchings et al.

(2001), and U.S EPA (2004). Rates include losses in forms of NH3, NOx, N2O, and N2 as well from leaching and runoff 

from solid storage and dry lots. Values represent average rates for typical housing and storage components without any 

significant nitrogen control measures in place. Ranges reflect values that appear in the literature. Where measures to 

control nitrogen losses are in place, alternative rates should be developed to reflect those measures. 

c Other includes sheep, horses, and fur-bearing animals. 

EMISSION FACTORS – INDIRECT N2O EMISSIONS 

Uncertainty ranges for default N losses due to volatilisation of NH3 and NOx and total N losses from manure 

management systems are presented in the Tables 10.22 and 10.23, respectively. The uncertainty associated with 

default emission factor for nitrogen volatilisation and re-deposition (EF4) is given in Table 11.3 of Chapter 11. 

The uncertainty range for the default emission factor for leaching and runoff (EF5) is also provided in Table 11.3. 

Caution should be taken when developing country-specific emission factors for volatilisation and re-deposition 

of nitrogen, since direct measurements could include transboundary atmospheric transport. 

ACTIVITY DATA – LIVESTOCK POPULATIONS 

See Section 10.2 (Livestock Population and Feed Characterisation) for discussion on uncertainty of animal 

population and feed characterisation data. 

ACTIVITY DATA – MANURE MANAGEMENT SYSTEM USAGE 

The uncertainty of the manure management system usage data will depend on the characteristics of each 

country's livestock industry and how information on manure management is collected. For example, for 

countries that rely almost exclusively on one type of management system, such as dry lot, the uncertainty 

associated with management system usage data can be 10% or less. However, for countries where there is a 

wide variety of management systems used with locally different operating practices, the uncertainty in 

management system usage data can be much higher, in the range of 25% to 50%, depending on the availability 

of reliable and representative survey data that differentiates animal populations by system usage. Preferably, 

each country should estimate the uncertainty associated with their management system usage data by using the 

methods described in Volume 1, Chapter 3. 
Volume 4: Agriculture, Forestry and Other Land Use 

10.68 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

10.5.6 Completeness, Time series, Quality assurance/Quality 

control and Reporting 

A complete inventory should estimate N2O emissions from all systems of manure management for all livestock 

species/categories. Countries are encouraged to use manure management system definitions that are consistent 

with those presented in Table 10.18. Population data should be cross-checked between main reporting 

mechanisms (such as FAO and national agricultural statistics databases) to ensure that information used in the 

inventory is complete and consistent. Because of the widespread availability of the FAO database of livestock 

information, most countries should be able to prepare, at a minimum, Tier 1 estimates for the major livestock 

categories. For more information regarding the completeness of livestock characterisation, see Section 10.2. 

Developing a consistent time series of emission estimates for this source category requires, at a minimum, the 

collection of an internally consistent time series of livestock population statistics. General guidance on the 

development of a consistent time series is addressed in Volume 1, Chapter 5 of this report. In most countries, the 

other two activity data sets required for this source category (i.e., N excretion rates and manure management 

system usage data), as well as the manure management emission factors, will be kept constant for the entire time 

series. However, in some cases, there may be reasons to modify these values over time. For example, farmers 

may alter livestock feeding practices which could affect nitrogen excretion rates. A particular system of manure 

management may change due to operational practices or new technologies such that a revised emission factor is 

warranted. These changes in practices may be due to the implementation of explicit greenhouse gas mitigation 

measures, or may be due to changing agricultural practices without regard to greenhouse gases. Regardless of the 

driver of change, the parameters and emission factors used to estimate emissions must reflect the change. The 

inventory text should thoroughly explain how the change in farm practices or implementation of mitigation 

measures has affected the time series of activity data or emission factors. 

It is good practice to implement general quality control checks as outlined in Volume 1, Chapter 6, Quality 

Assurance/Quality Control and Verification, and expert review of the emission estimates. Additional quality 

control checks and quality assurance procedures may also be applicable, particularly if higher tier methods are 

used to determine emissions from this source. The general QA/QC related to data processing, handling, and 

reporting should be supplemented with procedures discussed below: 

Activity data check 

• The inventory agency should review livestock data collection methods, in particular checking that livestock 

subspecies data were collected and aggregated correctly with consideration for the duration of production 

cycles. The data should be cross-checked with previous years to ensure the data are reasonable and 

consistent with the expected trend. Inventory agencies should document data collection methods, identify 

potential areas of bias, and evaluate the representativeness of the data. 

• Manure management system allocation should be reviewed on a regular basis to determine if changes in the 

livestock industry are being captured. Conversion from one type of management system to another, and 

technical modifications to system configuration and performance, should be captured in the system 

modelling for the affected livestock. 

• National agricultural policy and regulations may have an effect on parameters that are used to calculate 

manure emissions, and should be reviewed regularly to determine what impact they may have. For example, 

guidelines to reduce manure runoff into water bodies may cause a change in management practices, and 

thus affect the N distribution for a particular livestock category. Consistency should be maintained between 

the inventory and ongoing changes in agricultural practices. 

• If using country-specific data for Nex(T) and MS(T,S), the inventory agency should compare these values to 

the IPCC default values. Significant differences, data sources, and methods of data derivation, should be 

documented. 

• The nitrogen excretion rates, whether default or country-specific values, should be consistent with feed 

intake data as determined through animal nutrition analyses. 

Review of emission factors 

• The inventory agency should evaluate how well the implied N2O emission factors and nitrogen excretion 

rates compare with alternative national data sources and with data from other countries with similar 

livestock practices. Significant differences should be investigated. 

• If using country-specific emission factors, the inventory agency should compare them to the default factors 

and note differences. The development of country-specific emission factors should be explained and 

documented, and the results peer-reviewed by independent experts. 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.69 

• Whenever possible, available measurement data, even if they represent only a small sample of systems, 

should be reviewed relative to assumptions for N2O emission estimates. Representative measurement data 

may provide insights into how well current assumptions predict N2O production from manure management 

systems in the inventory area, and how certain factors (e.g., feed intake, system configuration, retention time) 

are affecting emissions. Because of the relatively small amount of measurement data available for these 

systems worldwide, any new results can improve the understanding of these emissions and possibly their 

prediction. 

External review 

• The inventory agency should utilise experts in manure management and animal nutrition to conduct expert 

peer review of the methods and data used. While these experts may not be familiar with greenhouse gas 

emissions, their knowledge of key input parameters to the emission calculation can aid in the overall 

verification of the emissions. For example, animal nutritionists can evaluate N production rates to see if 

they are consistent with feed utilization research for certain livestock species. Practicing farmers can 

provide insights into actual manure management techniques, such as storage times and mixed-system usage. 

Wherever possible, these experts should be completely independent of the inventory process in order to 

allow a true external review. 

It is good practice to document and archive all information required to produce the national emissions inventory 

estimates as outlined in Volume 1, Chapter 6, Quality Assurance/Quality Control and Verification. When 

country-specific emission factors, fractions of N losses, N excretion rates, or manure management system usage 

data have been used, the derivation of or references for these data should be clearly documented and reported 

along with the inventory results under the appropriate IPCC source category. 

N2O emissions from different types of manure management systems have to be reported according to categories 

in Table 10.18. N2O emissions from all types of manure management systems are to be reported under Manure 

Management, with two exceptions: 

• Emissions from the manure management system for pasture, range, and paddock are to be reported under 

the IPCC source category N2O emissions from managed soils because this manure is deposited directly on 

soils by the livestock. 

• Emission from the manure management system burned for fuel, are to be reported under the IPCC category 

Fuel Combustion if the dung is used as fuel and under the IPCC category Waste Incineration if the dung is 

burned without energy recovery. It should be noted, however, if the urine nitrogen is not collected for 

burning it must be reported under N2O emissions from pasture, range, and paddock animals. 

10.5.7 Use of worksheets 

Use the worksheets for Livestock N2O contained in Annex 1 (AFOLU Worksheets) to calculate and report 

inventory information for default methodologies described in Section 10.5 N2O emission from manure 

management. The following is a summary of the step-by-step instructions to follow when completing the 

worksheets. Note that columns are referred to using the symbols of the variables that both appear in the 

equations, as well as in column headings of the worksheets. 

Step 1: Calculation of N excretion from manure management systems (see worksheet for category Manure 

Management: Direct N2O emissions from Manure Management, Category code 3A2, Sheet 1 of 1). Make extra 

copies of the worksheet and complete one for each manure management systems (MMS). 

 Step 1A: Collect population data from the Livestock Population Characterisation and enter 

corresponding values in column N(T); 

 Step 1B: Use default values for Nrate and TAM (Equation 10.30 and using data from Table 10.19 and 

Tables 10A-4 to 10A-9) or develop the annual average nitrogen excretion rate per head (Nex(T)) for each 

defined livestock species/category T and enter these values in columns Nrate and TAM, or Nex(T), respectively; 

 Step 1C: Enter in column MS(T,S) default values (see Tables 10A-4 through 10A-8 of Annex 10A.2) or 

determine the fraction of total annual nitrogen excretion for each livestock species/category T that is 

managed in each manure management system S (MS(T,S)); 

 Step 1D: Multiply the number of heads (column N(T)) by the value of N excretion rate per head (Nex(T)) 

for each livestock species/category T (column Nex(T)) and by the fraction of manure nitrogen per MMS 

(column MS(T,S)) in order to estimate total nitrogen excretion for each MMS in kilograms per year (column 

NEMMS). Enter the results in column NEMMS of this sheet, and in column NEMMS of Sheet 1of 2 and Sheet 2 

of 2 for worksheets under category Indirect N2O emissions from Manure Management, Category code 3C6. 
Volume 4: Agriculture, Forestry and Other Land Use 

10.70 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Step 2: Calculation of direct N2O emissions from manure management systems (see worksheet for category 

Manure Management: Direct N2O emissions from Manure Management, Category code 3A2, Sheet 1 of 1).

 Step 2A: Use default values (see Table 10.21) or develop direct N2O emission factors for each manure 

management system S (EF3(S)) and enter corresponding emission factor in the column EF3(S);

 Step 2B: For each manure management system type S, multiply its emission factor (column EF3(S)) by 

the amount of nitrogen managed (column NEMMS) in that system, to estimate direct N2O emissions per MMS. 

Note that emissions estimates should be reported in kg of N2O. Enter the results in the column N2OD(mm) of 

this sheet. 

Step 3: Calculation of indirect N2O emissions from manure management systems (see worksheet for category 

Indirect N2O emissions from Manure Management, Category code 3C6, Sheet 1 of 2). Make extra copies of the 

worksheet using one for each MMS). 

 Step 3A: Enter in column FracGasMS default values (see Table 10.22) or determine country-specific 

fraction of managed livestock manure nitrogen that volatilises as NH3 and NOx for each defined livestock 

species/category T per each MMS (FracGasMS); 

 Step 3B: Multiply the fraction of manure nitrogen that volatilises as NH3 and NOx (column FracGasMS) 

by the total amount of nitrogen excreted in each MMS per livestock categories (column NEMMS) to estimate 

amount of manure nitrogen that is lost due to volatilisation of NH3 and NOx (Nvolatilizations-MMS); 

 Step 3C: Use default value (see Table 11.3, Chapter 11, Section 11.2 N2O emissions from managed soils) 

or develop country-specific emission factor for indirect N2O emission from atmospheric deposition of 

nitrogen on soils and water surfaces and enter the emission factor in the column EF4;

 Step 3D: Multiply the amount of manure nitrogen that is lost due to volatilisation of NH3 and NOx

(column Nvolatilizations-MMS) by the emission factor (column EF4), to calculate annual indirect N2O emissions 

per MMS. Note that emissions estimates should be reported in kg of N2O. Enter the results in the column 

N2OG(mm) of this sheet. 

Step 4: Calculation of manure N that is available for application to soils or for use in feed, fuel or construction 

purposes from manure management systems (see worksheet for category Indirect N2O emissions from Manure 

Management, Category code 3C6, Sheet 2 of 2). Make extra copies of the worksheet using one for each MMS).

 Step 4A: Enter in column FraclossMS default values (see Table 10.23) or develop country-specific fraction 

of total nitrogen loss from manure managed in each MMS for each livestock species/category T (FraclossMS); 

 Step 4B: If country-specific values for organic bedding usage are available for solid storage or deep 

bedding MMS, calculate the amount of N from bedding by multiplying the number of animals associated 

with these two systems by the N content in bedding per animal. Enter results obtained in the column 

NbeddingMS. 

 Step 4C: Calculate managed manure N available for application to managed soils, feed, fuel or 

construction using Equation 10.34 and enter obtained results in column NMMS_Avb. Then sum over all 

manure management systems. This value is used for calculation of N2O emissions from managed soils (see 

worksheets in Annex 1). 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.71 

Annex 10A.1 Data underlying methane default emission factors 

for Enteric Fermentation 

This annex presents the data used to develop the default emission factors for methane emissions from Enteric 

Fermentation. The Tier 2 method was implemented with these data to estimate the default emission factors for 

cattle and buffalo. 
Volume 4: Agriculture, Forestry and Other Land Use 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10A.1 

DATA FOR ESTIMATING TIER 1 ENTERIC FERMENTATION CH4 EMISSION FACTORS FOR DAIRY COWS IN T

Regions Weight, kg Weight gain, kg day-1 Feeding Situation Milk, kg day-1 Work, hr day-1 %PregNorth Americaa 600 0 Stall fed 23.0 0 90% Western Europe 600 0 Stall fed 16.4 0 90% Eastern Europeb 550 0 Stall fed 7.0 0 80% Oceaniac 500 0 Pasture/Range 6.0 0 80% Latin Americad 400 0 Pasture/Range 2.2 0 80% Asiae 350 0 Stall fed 4.5 0 80% Africa & Middle East 275 0 Stall fed 1.3 0 67% Indian Subcontinentf 275 0 Stall fed 2.5 0 50% 

a Based on estimates for the United States. b Based on estimates for the former USSR. c Based on average estimate for region. d Based on estimates for Brazil. e Based on estimates for China. f Based on estimates for India. 

Source: Gibbs and Johnson (1993). 
 Chapter 10: Emi

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10A.2 

DATA FOR ESTIMATING TIER 1 ENTERIC FERMENTATION CH4 EMISSION FACTORS FOR OTHER CATTLE IN 

Subcategory Weight, 

kg 

Weight gain,

kg day-1

Feeding situation Milk, 

 kg day-1

Work, 

hr day-1

%Pregnant Digestibility of 

feed (DE%) 

CH4 c

fact

North Americaa

Mature females 500 0.0 Pasture/Range 3.3 0.0 80% 60% 6Mature males 800 0.0 Pasture/Range 0.0 0.0 0% 60% 6Calves on milk 100 0.9 Pasture/Range 0.0 0.0 0% NA 0Calves on forage 185 0.9 Pasture/Range 0.0 0.0 0% 65% 6Growing heifers/steers 265 0.7 Pasture/Range 0.0 0.0 0% 65% 6Replacement/growing 375 0.4 Pasture/Range 0.0 0.0 0% 60% 6Feedlot cattle 415 1.3 Stall fed 0.0 0.0 0% 75% 3

Western Europe

Mature males 600 0.0 Pasture/Range 0.0 0.0 0% 60% 6Replacement/growing 400 0.4 Pasture/Range 0.0 0.0 0% 60% 6Calves on milk 230 0.3 Pasture/Range 0.0 0.0 0% 65% 0Calves on forage 230 0.3 Pasture/Range 0.0 0.0 0% 65% 6

Eastern Europeb

Mature females 500 0.0 Pasture/Range 3.3 0.0 67% 60% 6Mature males 600 0.0 Pasture/Range 0.0 0.0 0% 60% 6Young 230 0.4 Pasture/Range 0.0 0.0 0% 60% 6

Oceaniac

Mature females 400 0.0 Pasture/Range 2.4 0.0 67% 55% 6Mature males 450 0.0 Pasture/Range 0.0 0.0 0% 55% 6Young 200 0.3 Pasture/Range 0.0 0.0 0% 55% 6

a Based on estimates for the United States; . b Based on estimates for the former USSR; c Based on average estimate for region.
Volume 4: Agriculture, Forestry and Other Land Use 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10A.2 (CONTINUED)

DATA FOR ESTIMATING TIER 1 ENTERIC FERMENTATION CH4 EMISSION FACTORS FOR OTHER CATTLE IN 

Subcategory Weight, kg Weight gain, kg day-1 Feeding situation Milk, kg day-1 Work, hr day-1 %Pregnant Digestibility of feed (DE%) 

Latin Americad

 Mature females 400 0.0 Large areas 1.1 0.0 67% 60%  Mature males 450 0.0 Large areas 0.0 0.0 0% 60%  Young 230 0.3 Large areas 0.0 0.0 0% 60% 

Asiae

 Mature females- Farming 325 0.0 Stall fed 1.1 0.55 33% 55%  Mature females- Grazing 300 0.0 Pasture/Range 1.1 0.00 50% 60%  Mature males-Farming 450 0.0 Stall fed 0.0 1.37 0% 55%  Mature males-Grazing 400 0.0 Pasture/Range 0.0 0.00 0% 60%  Young 200 0.2 Pasture/Range 0.0 0.00 0% 60% 

Africa 

 Mature females 200 0.0 Stall fed 0.3 0.55 33% 55%  Draft bullocks 275 0.0 Stall fed 0.0 1.37 0% 55%  Mature females- Grazing 200 0.0 Large areas 0.3 0.00 33% 55%  Bulls- Grazing 275 0.0 Large areas 0.0 0.00 0% 55%  Young 75 0.1 Pasture/Range 0.0 0.00 0% 60% 

Indian Subcontinentf

 Mature females 125 0.0 Stall fed 0.6 0.00 33% 50%  Mature males 200 0.0 Stall fed 0.0 2.74 0% 50%  Young 80 0.1 Stall fed 0.0 0.00 0% 50% 

d Based on estimates for the Brazil.; e Based on estimates for the China.; f Based on estimates for India; Source: Gibbs and Johnson (1993)
 Chapter 10: Emi

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

TABLE 10A.3 

DATA FOR ESTIMATING TIER 1 ENTERIC FERMENTATION CH4 EMISSION FACTORS FOR BUFFA

Subcategory Weight, 

kg 

Weight gain, 

kg day-1

Feeding situation Milk, 

kg day-1

Work, 

hr day-1

%Pregnant Digestibility of feed 

(DE%) 

co

fac

Indian Subcontinenta

Adult males 350 - 550 0.00 Stall fed 0.00 1.37 0% 55% Adult females 250 - 450 0.00 Stall fed 2.70 0.55 33% 55% Young 100 - 300 0.15 Stall fed 0.00 0.00 0% 55% 

Other Countriesb

Adult males 350 - 550 0.00 Stall fed 0.00 1.37 0% 55% Adult females 250 - 450 0.00 Stall fed 0.00 0.55 25% 55% Young 100 - 300 0.15 Stall fed 0.15 0.00 0% 55% a Based on estimates for India.b Based on estimates for China.Source: Gibbs and Johnson (1993).
Volume 4: Agriculture, Forestry and Other Land Use 

10.76 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Annex 10A.2 Data underlying methane default emission factors 

for Manure Management 

This annex presents the data used to develop the default emission factors for methane emissions from Manure 

Management. The Tier 2 method was implemented with these data to estimate the default emission factors for 

each livestock category. 
 Chapter 10: Emi

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Pasture/ 

Liquid/ Solid Range/ Daily Burned 

Lagoon1 Slurry1 Storage Drylot Paddock Spread Digester for Fuel Other 

Cool 10 66% 17% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%

11 68% 19% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%12 70% 20% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%13 71% 22% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%14 73% 25% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%

Temp 15 74% 27% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%

16 75% 29% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%17 76% 32% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%18 77% 35% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%19 77% 39% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%20 78% 42% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%21 78% 46% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%22 78% 50% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%23 79% 55% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%24 79% 60% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%25 79% 65% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%

Warm 26 79% 71% 5.0% 2.0% 2.0% 1.0% 10.0% 10.0% 1.0%

27 80% 78% 5.0% 2.0% 2.0% 1.0% 10.0% 10.0% 1.0%28 80% 80% 5.0% 2.0% 2.0% 1.0% 10.0% 10.0% 1.0%

Massa Bob VSc

kg m3CH4/kg VS kg/hd/day 10 11 12 13 14 15 16 17 18 19 

North Americad 604 0.24 5.4 15.0% 27.0% 26.3% 0.0% 10.8% 18.4% 0.0% 0.0% 2.6% 48 50 53 55 58 63 65 68 71 7

Western Europe 600 0.24 5.1 0.0% 35.7% 36.8% 0.0% 20.0% 7.0% 0.0% 0.0% 0.5% 21 23 25 27 29 34 37 40 43 4Eastern Europe 550 0.24 4.5 0.0% 17.5% 60.0% 0.0% 18.0% 2.5% 0.0% 0.0% 2.0% 11 12 13 14 15 20 21 22 23 2Oceania 500 0.24 3.5 16.0% 1.0% 0.0% 0.0% 76.0% 8.0% 0.0% 0.0% 0.0% 23 24 25 26 26 27 28 28 28 2Latin America 400 0.13 2.9 0.0% 1.0% 1.0% 0.0% 36.0% 62.0% 0.0% 0.0% 0.0% 1 1 1 1 1 1 1 1 1 Africa 275 0.13 1.9 0.0% 0.0% 1.0% 0.0% 83.0% 5.0% 0.0% 6.0% 4.0% 1 1 1 1 1 1 1 1 1 Middle East 275 0.13 1.9 0.0% 1.0% 2.0% 0.0% 80.0% 2.0% 0.0% 17.0% 0.0% 2 2 2 2 2 2 2 2 2 Asia 350 0.13 2.8 4.0% 38.0% 0.0% 0.0% 20.0% 29.0% 2.0% 7.0% 0.0% 9 10 10 11 12 13 14 15 16 1Indian Subcontinent 275 0.13 2.6 0.0% 1.0% 0.0% 0.0% 27.0% 19.0% 1.0% 51.0% 0.0% 5 5 5 5 5 5 5 5 5 

Dairy Cow Characteristics

Annual Average Temperature (°C)

Table 10A-4

Manure Management Methane Emission Factor Derivation for Dairy Cows

Manure Management System MCFs

Region Manure Management System Usage (MS%)

Sources: For North America, dairy cow mass values are from Safley (2000) and VS values are estimated based on an analysis of feed data from Petersen et.al (2003). North American manure management system usage values are estimated using data from the 1992 and 1997 USDA's Census of Agriculture and National Animal Health Monitoring System Reports. Bo values are from Morris (1976) and 

Bryant, et.al. (1976). For Western and Eastern Europe manure management system usage, mass and VS values based on the analysis of national GHG inventories of Annex I countires submitted to the secretariat UNFCCC in 2004. For the rest of the world, the detailed information for dairy cows are developed in Gibbs and Johnson (1993), and manure management system usage and Bo estimates are 

from Safley et. al (1992). Methane conversion factor data are from Woodbury and Hashimoto (1993). MCFs for lagoons and liquid/slurry systems are based on data obtained from an analysis of these systems in the United States.

a Average dairy cow mass for each region (default estimates are ±10%)

Emission Factors (EF) for each region are calculated based on eq.10.23.

c Average VS production per head per day for the average dairy cow (default estimates are 

±20%)

b Bo estimates are ±15%d For North America, "Other" manure management system MCFs represent deep pits, which 

have the same MCF values as Liquid/Slurry. 

1 Lagoon and Liquid/Slurry MCFs are calculated based on the van't Hoff-Arrhenius 

equation relating temperature to biological activity. Lagoon MCFs are also calculated based on longer (up to a year) retention times. [Mangino, et. al (2001)] 

Emission 

Cool 

kg CH4 per he
Volume 4: Agriculture, Forestry and Other Land Use 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Pasture/ 

Liquid/ Solid Range/ Daily Burned 

Lagoon1 Slurry1 Storage Drylot Paddock Spread Digester for Fuel Other 

Cool 10 66% 17% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%

11 68% 19% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%12 70% 20% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%13 71% 22% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%14 73% 25% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%

Temp 15 74% 27% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%

16 75% 29% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%17 76% 32% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%18 77% 35% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%19 77% 39% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%20 78% 42% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%21 78% 46% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%22 78% 50% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%23 79% 55% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%24 79% 60% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%25 79% 65% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%

Warm 26 79% 71% 5.0% 2.0% 2.0% 1.0% 10.0% 10.0% 1.0%

27 80% 78% 5.0% 2.0% 2.0% 1.0% 10.0% 10.0% 1.0%28 80% 80% 5.0% 2.0% 2.0% 1.0% 10.0% 10.0% 1.0%

Massa Bob VSc

kg m3CH4/kg VS kg/hd/day 10 11 12 13 14 15 16 17 18 

North America 389 0.19 2.4 0.0% 0.2% 0.0% 18.4% 81.5% 0.0% 0.0% 0.0% 0.0% 1 1 1 1 1 2 2 2 2 Western Europe 420 0.18 2.6 0.0% 25.2% 39.0% 0.0% 32.0% 1.8% 0.0% 0.0% 2.0% 6 7 7 8 8 10 11 12 13 Eastern Europe 391 0.17 2.7 0.0% 22.5% 44.0% 0.0% 20.0% 0.0% 0.0% 0.0% 13.5% 6 6 7 7 8 9 10 11 11 Oceania 330 0.17 3.0 0.0% 0.0% 0.0% 9.0% 91.0% 0.0% 0.0% 0.0% 0.0% 1 1 1 1 1 2 2 2 2 Latin America 305 0.1 2.5 0.0% 0.0% 0.0% 0.0% 99.0% 0.0% 0.0% 0.0% 1.0% 1 1 1 1 1 1 1 1 1 Africa 173 0.1 1.5 0.0% 0.0% 0.0% 1.0% 95.0% 1.0% 0.0% 3.0% 0.0% 0 0 0 0 0 1 1 1 1 Middle East 173 0.1 1.5 0.0% 0.0% 0.0% 1.0% 79.0% 2.0% 0.0% 17.0% 2.0% 1 1 1 1 1 1 1 1 1 Asia 319 0.1 2.3 0.0% 0.0% 0.0% 46.0% 50.0% 2.0% 0.0% 2.0% 0.0% 1 1 1 1 1 1 1 1 1 Indian Subcontinent 110 0.1 1.4 0.0% 1.0% 0.0% 4.0% 22.0% 20.0% 1.0% 53.0% 0.0% 2 2 2 2 2 2 2 2 2 

b Bo estimates are ±15%

Sources: For North America, other cattle mass are from Safley (2000) and USDA's Agricultural Waste Management Field Handbook and VS values are estimated based on an analysis of feed data from Petersen, et.al (2003). North American manure management system usage values are estimated using data from the 1992 and 1997 USDA's Census of Agriculture and National Animal Health Monitoring System Reports. Bo data are values reported in Hashimoto (1981). For Western and Eastern Europe manure management system usage, average mass, Bo, and VS values based on the 

analysis of national GHG inventories of Annex I countires submitted to the secretariat UNFCCC in 2004. For the rest of the world, the detailed information for cattle are developed in Gibbs and 

Johnson (1993), and manure management system usage and Bo estimates are from Safley et. al (1992). Methane conversion factor data are from Woodbury and Hashimoto (1993). MCFs for lagoons 

and liquid/slurry systems are based on data obtained from an analysis of these systems in the United States.

Emission Factors (EF) for each region are calculated based on eq.10.23.

c Average VS production per head per day for the average non-dairy cow (default estimates 

are ±35%)

1 Lagoon and Liquid/Slurry MCFs are calculated based on the van't Hoff-Arrhenius equation relating temperature to biological activity. Lagoon MCFs are also calculated based on longer (up to a year) retention times. [Mangino, et. al (2001)] 

a Average other cattle mass for each region (default estimates are ±25%)

Table 10A-5

Manure Management Methane Emission Factor Derivation for Other Cattle

Manure Management System MCFs

Other Cattle Characteristics

Region Manure Management System Usage (MS%)

Annual Average Temperature (°C)

Emissi

Cool 

kg CH4 pe
 Chapter 10: Emi

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Pasture/ 

Liquid/ Solid Range/ Daily Burned 

Lagoon1 Slurry1 Storage Drylot Paddock Spread Digester for Fuel Other 

Cool 10 66% 17% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%

11 68% 19% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%12 70% 20% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%13 71% 22% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%14 73% 25% 2.0% 1.0% 1.0% 0.1% 10.0% 10.0% 1.0%

Temp 15 74% 27% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%

16 75% 29% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%17 76% 32% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%18 77% 35% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%19 77% 39% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%20 78% 42% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%21 78% 46% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%22 78% 50% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%23 79% 55% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%24 79% 60% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%25 79% 65% 4.0% 1.5% 1.5% 0.5% 10.0% 10.0% 1.0%

Warm 26 79% 71% 5.0% 2.0% 2.0% 1.0% 10.0% 10.0% 1.0%

27 80% 78% 5.0% 2.0% 2.0% 1.0% 10.0% 10.0% 1.0%28 80% 80% 5.0% 2.0% 2.0% 1.0% 10.0% 10.0% 1.0%

Massa Bo VSb

kg m3CH4/kg VS kg/hd/day 10 11 12 13 14 15 16 17 

North AmericaWestern Europe 380 0.1 3.9 0% 20% 0% 79% 0% 0% 0% 0% 0% 4 4 5 5 5 6 7 7 Eastern Europe 380 0.1 3.9 0% 24% 0% 0% 29% 0% 0% 0% 47% 5 5 5 6 6 7 8 8 Oceania Latin America 380 0.1 3.9 0% 0% 0% 0% 99% 0% 0% 0% 1% 1 1 1 1 1 1 1 1 Africa Middle East 380 0.1 3.9 0% 0% 0% 0% 20% 19% 0% 42% 19% 4 4 4 4 4 5 5 5 Asia 380 0.1 3.9 0% 0% 0% 41% 50% 4% 0% 5% 0% 1 1 1 1 1 2 2 2 Indian Subcontinent 295 0.1 3.1 0% 0% 0% 4% 19% 21% 1% 55% 0% 4 4 4 4 4 5 5 5 

a Average buffalo mass for each regionb Average VS production per head per day for the average buffalo

Region Manure Management System Usage (MS%)

1 Lagoon and Liquid/Slurry MCFs are calculated based on the van't Hoff-Arrhenius 

equation relating temperature to biological activity. Lagoon MCFs are also calculated based on longer (up to a year) retention times. [Mangino, et. al (2001)] 

Annual Average Temperature (°C)

Buffalo Characteristics

Sources: The detailed information for buffalo are developed in Gibbs and Johnson (1993),and manure management system usage and Bo estimates are from Safley et. al (1992). Methane conversion factor data 

are from Woodbury and Hashimoto (1993). MCFs for lagoons and liquid/slurry systems are based on data obtained from an analysis of these systems in the United States.

(not applicable) N(not applicable)(not applicable)

Emission Factors (EF) for each region are calculated based on eq.10.23.

(not applicable)

kg CH

(not applicable)(not applicable)

NN

Cool 

Table 10A-6

Manure Management Methane Emission Factor Derivation for Buffalo

Manure Management System MCFs

Em
Volume 4: Agriculture, Forestry and Other Land Use 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Liquid/ Solid Pit Pit Daily 

Lagoon1 Slurry1 Storage Drylot <1 month >1 month Spread Digester Other 

Cool 10 66% 17% 2.0% 1.0% 3.0% 17% 0.1% 10.0% 1.0%

11 68% 19% 2.0% 1.0% 3.0% 19% 0.1% 10.0% 1.0%12 70% 20% 2.0% 1.0% 3.0% 20% 0.1% 10.0% 1.0%13 71% 22% 2.0% 1.0% 3.0% 22% 0.1% 10.0% 1.0%14 73% 25% 2.0% 1.0% 3.0% 25% 0.1% 10.0% 1.0%

Temp 15 74% 27% 4.0% 1.5% 3.0% 27% 0.5% 10.0% 1.0%

16 75% 29% 4.0% 1.5% 3.0% 29% 0.5% 10.0% 1.0%17 76% 32% 4.0% 1.5% 3.0% 32% 0.5% 10.0% 1.0%18 77% 35% 4.0% 1.5% 3.0% 35% 0.5% 10.0% 1.0%19 77% 39% 4.0% 1.5% 3.0% 39% 0.5% 10.0% 1.0%20 78% 42% 4.0% 1.5% 3.0% 42% 0.5% 10.0% 1.0%21 78% 46% 4.0% 1.5% 3.0% 46% 0.5% 10.0% 1.0%22 78% 50% 4.0% 1.5% 3.0% 50% 0.5% 10.0% 1.0%23 79% 55% 4.0% 1.5% 3.0% 55% 0.5% 10.0% 1.0%24 79% 60% 4.0% 1.5% 3.0% 60% 0.5% 10.0% 1.0%25 79% 65% 4.0% 1.5% 3.0% 65% 0.5% 10.0% 1.0%

Warm 26 79% 71% 5.0% 2.0% 30.0% 71% 1.0% 10.0% 1.0%

27 80% 78% 5.0% 2.0% 30.0% 78% 1.0% 10.0% 1.0%28 80% 80% 5.0% 2.0% 30.0% 80% 1.0% 10.0% 1.0%

Massa Bob VSc

kg m3CH4/kg VS kg/hd/day 10 11 12 13 14 15 16 17 18 

North America 46 0.48 0.27 32.8% 18.5% 4.2% 4.0% 0.0% 40.6% 0.0% 0.0% 0.0% 10 11 11 12 12 13 13 14 15 Western Europe 50 0.45 0.3 8.7% 0.0% 13.7% 0.0% 2.8% 69.8% 2.0% 0.0% 3.0% 6 6 7 7 8 9 9 10 11 Eastern Europe 50 0.45 0.3 3.0% 0.0% 42.0% 0.0% 24.7% 24.7% 0.0% 0.0% 5.7% 3 3 3 3 3 4 4 4 4 Oceania 45 0.45 0.28 54.0% 0.0% 3.0% 15.0% 0.0% 0.0% 0.0% 0.0% 28.0% 11 11 12 12 12 13 13 13 13 Latin America 28 0.29 0.3 0.0% 8.0% 10.0% 41.0% 0.0% 0.0% 2.0% 0.0% 40.0% 1 1 1 1 1 1 1 1 1 Africa 28 0.29 0.3 0.0% 6.0% 6.0% 87.0% 1.0% 0.0% 0.0% 0.0% 0.0% 0 0 0 1 1 1 1 1 1 Middle East 28 0.29 0.3 0.0% 14.0% 0.0% 69.0% 0.0% 17.0% 0.0% 0.0% 0.0% 1 1 1 2 2 2 2 2 3 Asia 28 0.29 0.3 0.0% 40.0% 0.0% 54.0% 0.0% 0.0% 0.0% 7.0% 0.0% 2 2 2 2 2 3 3 3 3 Indian Subcontinent 28 0.29 0.3 9.0% 22.0% 16.0% 30.0% 3.0% 0.0% 9.0% 8.0% 3.0% 2 2 3 3 3 3 3 3 4 

bBo estimates are ±15%

Sources: For North America, mass, VS, and Bo values are from Safley (2000), USDA's Agricultural Waste Management Field Handbook, and Hashimoto (1984), respectively. North American manure 

management system usage data are estimated using data from the 1992 and 1997 USDA's Census of Agriculture and National Animal Health Monitoring System Reports. For Western and Eastern Europe manure management system usage, mass of animals, Bo and VS values based on the analysis of national GHG inventories of Annex I countires submitted to the secretariat UNFCCC in 2004. For the rest of 

the world, swine feed intake data are from Crutzen et. al (1986), and manure management system usage and Bo estimates are from Safley et. al (1992). Methane conversion factor data are from Woodbury 

and Hashimoto (1993). MCFs for lagoons and liquid/slurry systems are based on data obtained from an analysis of these systems in the United States.

a Average marker swine mass for each region (default estimates are ±20%)

Market Swine Characteristics

c Average VS production per head per day for the average market swine (default estimates 

are ±25%)

Emission Factors (EF) for each region are calculated based on eq.10.23.

Region

Table 10A-7

Manure Management Methane Emission Factor Derivation for Market Swine

Manure Management System MCFs

Manure Management System Usage (MS%)

1 Lagoon and Liquid/Slurry MCFs are calculated based on the van't Hoff-Arrhenius 

equation relating temperature to biological activity. Lagoon MCFs are also calculated based on longer (up to a year) retention times. [Mangino, et. al (2001)] 

Annual Average Temperature (°C)

Emissi

Cool 

kg CH4 pe
 Chapter 10: Emi

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Liquid/ Solid Pit Pit Daily 

Lagoon1 Slurry1 Storage Drylot <1 month >1 month Spread Digester Other 

Cool 10 66% 17% 2.0% 1.0% 3.0% 17% 0.1% 10.0% 1.0%

11 68% 19% 2.0% 1.0% 3.0% 19% 0.1% 10.0% 1.0%12 70% 20% 2.0% 1.0% 3.0% 20% 0.1% 10.0% 1.0%13 71% 22% 2.0% 1.0% 3.0% 22% 0.1% 10.0% 1.0%14 73% 25% 2.0% 1.0% 3.0% 25% 0.1% 10.0% 1.0%

Temp 15 74% 27% 4.0% 1.5% 3.0% 27% 0.5% 10.0% 1.0%

16 75% 29% 4.0% 1.5% 3.0% 29% 0.5% 10.0% 1.0%17 76% 32% 4.0% 1.5% 3.0% 32% 0.5% 10.0% 1.0%18 77% 35% 4.0% 1.5% 3.0% 35% 0.5% 10.0% 1.0%19 77% 39% 4.0% 1.5% 3.0% 39% 0.5% 10.0% 1.0%20 78% 42% 4.0% 1.5% 3.0% 42% 0.5% 10.0% 1.0%21 78% 46% 4.0% 1.5% 3.0% 46% 0.5% 10.0% 1.0%22 78% 50% 4.0% 1.5% 3.0% 50% 0.5% 10.0% 1.0%23 79% 55% 4.0% 1.5% 3.0% 55% 0.5% 10.0% 1.0%24 79% 60% 4.0% 1.5% 3.0% 60% 0.5% 10.0% 1.0%25 79% 65% 4.0% 1.5% 3.0% 65% 0.5% 10.0% 1.0%

Warm 26 79% 71% 5.0% 2.0% 30.0% 71% 1.0% 10.0% 1.0%

27 80% 78% 5.0% 2.0% 30.0% 78% 1.0% 10.0% 1.0%28 80% 80% 5.0% 2.0% 30.0% 80% 1.0% 10.0% 1.0%

Massa Bob VSc

kg m3CH4/kg VS kg/hd/day 10 11 12 13 14 15 16 17 18 

North America 198 0.48 0.5 32.8% 18.5% 4.2% 4.0% 0.0% 40.6% 0.0% 0.0% 0.0% 19 20 21 22 23 24 26 27 28 Western Europe 198 0.45 0.46 8.7% 0.0% 13.7% 0.0% 2.8% 69.8% 2.0% 0.0% 3.0% 9 10 10 11 12 13 14 15 16 Eastern Europe 180 0.45 0.5 3.0% 0.0% 42.0% 0.0% 24.7% 24.7% 0.0% 0.0% 5.7% 4 5 5 5 5 6 7 7 7 Oceania 180 0.45 0.5 54.0% 0.0% 3.0% 15.0% 0.0% 0.0% 0.0% 0.0% 28.0% 20 20 21 21 22 22 23 23 23 Latin America 28 0.29 0.3 0.0% 8.0% 10.0% 41.0% 0.0% 0.0% 2.0% 0.0% 40.0% 1 1 1 1 1 1 1 1 1 Africa 28 0.29 0.3 0.0% 6.0% 6.0% 87.0% 1.0% 0.0% 0.0% 0.0% 0.0% 0 0 0 1 1 1 1 1 1 Middle East 28 0.29 0.3 0.0% 14.0% 0.0% 69.0% 0.0% 17.0% 0.0% 0.0% 0.0% 1 1 1 2 2 2 2 2 3 Asia 28 0.29 0.3 0.0% 40.0% 0.0% 54.0% 0.0% 0.0% 0.0% 7.0% 0.0% 2 2 2 2 2 3 3 3 3 Indian Subcontinent 28 0.29 0.3 9.0% 22.0% 16.0% 30.0% 3.0% 0.0% 9.0% 8.0% 3.0% 2 2 3 3 3 3 3 3 4 

bBo estimates are ±15%

Sources: For North America, mass, VS, and Bo values are from Safley (2000), USDA's Agricultural Waste Management Field Handbook, and Hashimoto (1984), respectively. North American manure 

management system usage data are estimated using data from the 1992 and 1997 USDA's Census of Agriculture and National Animal Health Monitoring System Reports. For Western and Eastern Europe manure management system usage, mass of animals, Bo and VS values based on the analysis of national GHG inventories of Annex I countires submitted to the secretariat UNFCCC in 2004. For the rest 

of the world, swine feed intake data are from Crutzen et. al (1986), and manure management system usage and Bo estimates are from Safley et. al (1992). Methane conversion factor data are from 

Woodbury and Hashimoto (1993). MCFs for lagoons and liquid/slurry systems are based on data obtained from an analysis of these systems in the United States.

c Average VS production per head per day for the average breed swine (default estimates 

are ±25%)

Emission Factors (EF) for each region are calculated based on eq.10.23.

a Average breed swine mass for each region (default estimates are ±20%)

1 Lagoon and Liquid/Slurry MCFs are calculated based on the van't Hoff-Arrhenius 

equation relating temperature to biological activity. Lagoon MCFs are also calculated based on longer (up to a year) retention times. [Mangino, et. al (2001)] 

Breeding Swine Characteristics

Table 10A-8

Manure Management Methane Emission Factor Derivation for Breeding Swine

Manure Management System MCFs

Region

Annual Average Temperature (°C)

Manure Management System Usage (MS%)

Emiss

Cool 

kg CH4 p
Volume 4: Agriculture, Forestry and Other Land Use 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Layers (dry)

Layers (wet) 

Broilers

Turkeys

Ducks

Animal Characteristics

48.5 28 38.5 30 217 217 377 238 130 130 1.8 1.8 0.9 6.8 2.7 NR

0.60 0.5 0.6 0.5 0.5 0.5 0.7 0.7 0.7 0.7 NR NR NR NR NR NR1.08 0.7 0.76 0.76 5.42 5.42 5.96 5.96 3.25 3.25 NR NR NR NR NR NR8.00 8 8 8 8 8 4 4 4 4 NR NR NR NR NR NR

0.40 0.32 0.3 0.35 2.49 2.49 2.13 1.72 0.94 0.94 0.02 0.02 0.01 0.07 0.02 0.020.19 0.13 0.18 0.13 0.26 0.21 0.3 0.26 0.33 0.26 0.39 0.39 0.36 0.36 0.36 0.24

Cool 10 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.5% 65% 1.5% 1.5% 1.0% 1.0%

11 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.5% 68% 1.5% 1.5% 1.0% 1.0%

12 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.5% 70% 1.5% 1.5% 1.0% 1.0%

13 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.5% 73% 1.5% 1.5% 1.0% 1.0%

14 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.5% 74% 1.5% 1.5% 1.0% 1.0%

Temperate 15 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 75% 1.5% 1.5% 1.5% 1.5%

16 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 76% 1.5% 1.5% 1.5% 1.5%

17 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 76% 1.5% 1.5% 1.5% 1.5%

18 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 77% 1.5% 1.5% 1.5% 1.5%

19 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 78% 1.5% 1.5% 1.5% 1.5%

20 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 78% 1.5% 1.5% 1.5% 1.5%

21 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 78% 1.5% 1.5% 1.5% 1.5%

22 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 78% 1.5% 1.5% 1.5% 1.5%23 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 79% 1.5% 1.5% 1.5% 1.5%

24 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 79% 1.5% 1.5% 1.5% 1.5%

25 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 80% 1.5% 1.5% 1.5% 1.5%

Warm 26 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 1.5% 80% 1.5% 1.5% 2.0% 2.0%

27 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 1.5% 80% 1.5% 1.5% 2.0% 2.0%

28 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 1.5% 80% 1.5% 1.5% 2.0% 2.0%

Cool 10 0.19 0.10 0.13 0.11 1.58 1.28 1.56 1.09 0.76 0.60 0.03 1.13 0.02 0.09 0.02 0.01

11 0.19 0.10 0.13 0.11 1.58 1.28 1.56 1.09 0.76 0.60 0.03 1.18 0.02 0.09 0.02 0.01

12 0.19 0.10 0.13 0.11 1.58 1.28 1.56 1.09 0.76 0.60 0.03 1.21 0.02 0.09 0.02 0.01

13 0.19 0.10 0.13 0.11 1.58 1.28 1.56 1.09 0.76 0.60 0.03 1.26 0.02 0.09 0.02 0.01

14 0.19 0.10 0.13 0.11 1.58 1.28 1.56 1.09 0.76 0.60 0.03 1.28 0.02 0.09 0.02 0.01

Temperate 15 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.30 0.02 0.09 0.03 0.02

16 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.31 0.02 0.09 0.03 0.02

17 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.32 0.02 0.09 0.03 0.02

18 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.33 0.02 0.09 0.03 0.02

19 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.35 0.02 0.09 0.03 0.02

20 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.35 0.02 0.09 0.03 0.02

21 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.36 0.02 0.09 0.03 0.02

22 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.36 0.02 0.09 0.03 0.02

23 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.37 0.02 0.09 0.03 0.02

24 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.38 0.02 0.09 0.03 0.02

25 0.28 0.15 0.20 0.17 2.37 1.92 2.34 1.64 1.14 0.90 0.03 1.38 0.02 0.09 0.03 0.02

Warm 26 0.37 0.20 0.26 0.22 3.17 2.56 3.13 2.19 1.52 1.20 0.03 1.38 0.02 0.09 0.03 0.02

27 0.37 0.20 0.26 0.22 3.17 2.56 3.13 2.19 1.52 1.20 0.03 1.39 0.02 0.09 0.03 0.02

28 0.37 0.20 0.26 0.22 3.17 2.56 3.13 2.19 1.52 1.20 0.03 1.39 0.02 0.09 0.03 0.02

Emission Factors (kg CH4 per head per year)

Animal Sheep Goats

Developed 

Developing 

Developed 

Camels

Developed 

Developing 

Developing 

Developing 

Intake/d (kg Feed)

Digest (%)

Developed 

Annual Average 

Temperature (°C)

Mass (kg)

% Ash (Dry Basis)

VS/day (kg VS)

Bo (m3/kg VS)

Manure Management System MCFs

Table 10A-9

Manure Management Methane Emission Factor Derivation 

Country

Developed 

Developing 

Developed 

Developing 

Horses Mule/Asses Poultry

NR = Not reported. 

Annual Average 

Temperature (°C)

Emission factors, except for poultry, were developed from feed intake values and feed digestibilities used to develop the enteric fermentation emission factors (see Appendix 10A.1). MCFs and Bo values are reported in Woodbury 

and Hashimoto (1993). All manure except for Layers (wet) is assumed to be managed in dry systems, which is consistent with the manure management system usage reported in Woodbury and Hashimoto (1993). Poultry for developed countries was subdivided into five categories. Layers (dry) represent layers in a "without bedding" waste management system; Layers (wet) represent layers in an anaerobic lagoon waste managemnet system. Estimates of animal mass are ±30%, VS values are ±50% and Bo values are ±15%
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.83 

TABLE 10A-9 (CONTINUED) 

MANURE MANAGEMENT METHANE EMISSION FACTOR DERIVATION FOR OTHER ANIMALS

Animal Characteristics 

Animal Mass 

(kg) 

VS 

(kg VS day-1) 

Bo 

(m3 kg VS) 

Manure 

management 

system MCF 

Emission 

factors 

(kg CH4 head-1

yr-1) 

Deer a NR NR NR NR 0.22 

Reindeer b NR 0.39 0.19 2.0% 0.36 

Rabbits c 1.60 0.10 0.32 1.0% 0.08 

Fur-bearing 

animals b NR 0.14 0.25 8.0% 0.68 

Ostrich b NR 1.16 0.25 8.0% 5.67 

a Sneath (1997) cited in the GHG inventory of United Kingdom. 

b Estimations of Agricultural University of Norway, Institute of Chemistry and Biotechnology, Section for Microbiology. 

c Data obtained from GHG inventory of Italy, 2004. 

NR = not reported 
Volume 4: Agriculture, Forestry and Other Land Use 

10.84 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

References 

SECTION 10.2 LIVESTOCK POPULATION AND FEED CHARACTERISATION 

AAC (Australian Agricultural Council) (1990). Feed Standards for Australian Livestock Ruminants. 

Commonwealth Scientific and Industrial Research Organization (CSIRO) Publications, East Melbourne, 

Victoria, Australia. 

AFRC Technical Committee on Responses to Nutrients (1990). Nutritive Requirements of Ruminant Animals: 

Energy. Rep. 5, CAB International, Wallingford, U.K. 

Agricultural and Food Research Council (AFRC) Technical Committee on Responses to Nutrients (1993). 

Energy and Protein Requirements of Ruminants. 24-159, CAB International, Wallingford, U.K. 

Bamualim, A. and Kartiarso (1985). ‘Nutrition of draught animals with special reference to Indonesia.’ In: 

Draught Animal Power for Production. J.W. Copland (ed.). Australian Centre for International 

agricultural Research (ACIAR), Proceedings Series No. 10. ACIAR, Canberra, A.C.T., Australia. 

Food and Agriculture Organisation (FAO) (1999). Statistical Database. 

Gibbs, M.J. and Johnson, D.E. (1993). "Livestock Emissions." In: International Methane Emissions, US 

Environmental Protection Agency, Climate Change Division, Washington, D.C., U.S.A. 

Gibbs, M.J., Conneely, D., Johnson, D., Lassey, K.R. and Ulyatt, M.J. (2002). CH4 emissions from enteric 

fermentation. In: Background Papers: IPCC Expert Meetings on Good Practice Guidance and Uncertainty 

Management in National Greenhouse Gas Inventories, p 297–320. IPCC-NGGIP, Institute for Global 

Environmental Strategies (IGES), Hayama, Kanagawa, Japan. 

Ibrahim, M.N.M. (1985). ‘Nutritional status of draught animals in Sri Lanka.’ In: Draught Animal Power for 

Production, J.W. Copland (ed.). ACIAR (Australian Centre for International Agricultural Research) 

Proceedings Series No. 10. ACIAR, Canberra, A.C.T., Australia. 

Jurgen, M.H. (1988). Animal Feeding and Nutrition, Sixth Edition, Kendall/Hunt Publishing Company, 

Dubuque, Iowa, U.S.A. 

Lawrence, P.R. (1985). ‘A review of nutrient requirements of draught oxen.’ In: Draught Animal Power for 

Production. J.W. Copland (ed.). ACIAR (Australian Centre for International Agricultural Research) 

Proceedings Series No. 10. ACIAR, Canberra, A.C.T., Australia. 

National Research Council (NRC) (1984). Nutrient Requirements of Beef Cattle, National Academy Press, 

Washington, D.C. U.S.A. 

NRC (1989). Nutrient Requirements of Dairy Cattle, 6th, National Academy Press, Washington, D.C. U.S.A. 

NRC (1996). Nutrient Requirements of Beef Cattle, National Academy Press, Washington, D.C. U.S.A. 

NRC (2001). Nutrient Requirements of Dairy Cattle, 7th Ed., Nat. Acad. Press, Washington, DC. 

SECTION 10.3 METHANE EMISSIONS FROM DOMESTIC LIVESTOCK ENTERIC 

FERMENTATION 

Clark, H., Brookes, I. and Walcroft, A. (2003). Enteric methane emissions from New Zealand ruminants 1999-

2001 calculated using an IPCC Tier 2 approach. http://www.climatechange.govt.nz/resources/reports/nirapr03/. 

Crutzen, P.J., Aselmann, I. and Seiler, W. (1986). "Methane Production by Domestic Animals, Wild Ruminants, 

Other Herbivorous Fauna, and Humans," Tellus 38B:271-284. 

Diarra, B. (1994). Net energy value of soybean hulls as feed for sheep. Dissertation. Colorado State University, 

Ft Collins, CO. 

Donovan, K. and Baldwin, L. (1999). Results of the AAMOLLY model runs for the Enteric Fermentation 

Model. University of California, Davis. 

Hindrichsen, I., Kreuzer, M., Machmuller, A., Knudsen, K. E., Madsen, J. and Wettstein, H.R. (2003). Methane 

release and energy expenditure of dairy cows fed concentrates characterized by different carbohydrates. 

In: Prog. in Res. En. & Prot. Metabol. (Souffrant, W.B, and CC. Metges, eds.) Wageningen Acad. Pub, 

The Netherlands, EAAP Publ. 109:413-416. 

Johnson, K., Huyler, M., Westberg, H., Lamb, B. and Zimmerman, P. (1994). Measurement of methane 

emissions from ruminant livestock using a SF6 tracer technique. Environmental. Sci. Tech., 28: 359-362. 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.85 

Johnson, K.A. and Johnson, D.E. (1995). Methane emissions from cattle. J. Anim. Sci., 73: 2483-2492 

Judd, M.J., Kelliher, F.M., Ulyatt, M.J., Lassey, K.R., Tate, K.R., Shelton, I.D., Harvey, M.J. and Walker, C.F. 

(1999). Net methane emissions from grazing sheep, Global Change Biol., 5, pp. 647–657. 

Kujawa, M. (1994). Energy partitioning in steers fed cottonseed hulls or sugar beet pulp. Dissertation, Colorado 

State University, Ft Collins, CO. 

Kurihara, M., Magner, T., Hunter, R.A. and McCrabb, G.J. (1999). Methane production and energy partition of 

cattle in the tropics. British Journal of Nutrition, 81, pp. 227-234. 

Lassey, K.R. (2006). Livestock methane emission: from the individual grazing animal through national 

inventories to the global methane cycle. Agric. For. Meteorol. (in press). 

Lassey, K.R., Ulyatt, M.J., Martin, R.J., Walker, C.F. and Shelton, I.D. (1997). Methane emissions measured 

directly from grazing livestock in New Zealand, Atmos. Environ., 31, pp. 2905-2914. 

Leuning, R., Baker, S.K., Jamie, I.M., Hsu, C.H., Klein, L., Denmead, O.T. and Griffith, D.W.T. (1999). 

Methane emission from free-ranging sheep: a comparison of two measurement methods, Atmos. Environ., 

33, pp. 1357–1365. 

Murray, B.R., Bryant, A.M. and Leng, R.A. (1978). Methane production in the rumen and lower gut of sheep 

given lucerne chaff: effect of level of intake, Br. J. Nutr., 39, pp. 337-345. 

National Research Council (NRC) (1989). Nutrient Requirements of Dairy Cattle, 6th Ed., Nat. Acad. Press, 

Washington, DC. 

National Research Council (NRC) (1996). Nutrient Requirements of Beef Cattle, 7th Edit., Nat. Acad. Press, 

Washington, DC. 

National Research Council (NRC) (2001). Nutrient Requirements of Dairy Cattle, 7th Ed., Nat. Acad. Press, 

Washington, DC. 

Pinares-Patino, C.S., Ulyatt, M.J., Waghorn, G.C., Lassey, K.R., Barry, T.N., Holmes, C.W. and Johnson, D.E. 

(2003). Methane emission by alpaca and sheep fed on Lucerne hay or grazed on pastures of perennial 

ryegrass/white clover or birds foot trefoil. J. Agric. Sci. 140:215-226. 

Ulyatt, M.J., Lassey, K.R., Shelton, I.D. and Walker, C.F. (2002a). “Seasonal variation in methane emission 

from dairy cows and breeding ewes grazing ryegrass/white clover pasture in New Zealand.” New Zealand 

Journal of Agricultural Research 45:217–226. 

Ulyatt, M.J., Lassey, K.R., Shelton, I.D. and Walker, C.F. (2002b). “Methane emission from dairy cows and 

wether sheep fed subtropical grass-dominant pastures in midsummer in New Zealand.” New Zealand 

Journal of Agricultural Research 45:227–234. 

Ulyatt, M.J., Lassey, K.R., Shelton, I.D. and Walker, C.F. (2005). Methane emission from sheep grazing four 

pastures in late summer in New Zealand. New Zealand Journal Agricultural Research 48: 385-390. 

SECTION 10.4 METHANE EMISSIONS FROM MANURE MANAGEMENT 

Amon, B., Amon, Th., Boxberger, J. and Pollinger, A. (1998). Emissions of NH3, N2O, and CH4 from composted 

and anaerobically stored farmyard manure. Pages 209-216 in Martinez J, Maudet M-N (eds) Ramiran 98, 

Proc. 8th Int. Conf. on the FAO ESCORENA Network on Recycling of Agricultural, Municipal and 

Industrial Residues in Agriculture. Rennes, France. 

Amon, B., Amon, Th., Boxberger, J. and Alt, Ch. (2001). Emissions of NH3, N2O, and CH4 from dairy cows 

housed in a farmyard manure tying stall (Housing, Manure Storage, Manure Spreading). Nutrient Cycling 

in Agroecosystems, 60: pp. 103-113. 

ASAE (1999). ASAE Standards 1999, 46th Edition. American Society of Agricultural Engineers, St. Joseph, MI. 

Hashimoto, A. and Steed, J. (1993). Methane emissions from typical U.S. livestock manure management systems. 

Draft report prepared for ICF Incorporated under contract to the Global Change Division of the Office of 

Air and Radiation, US Environmental Protection Agency, Washington, D.C. 

Hill, D.T. (1982). Design of digestion systems for maximum methane production. Transactions of the ASAE, 

25(1): pp. 226-230. 

Hill, D.T. (1984). Methane productivity of the major animal types. Transactions of the ASAE 27(2): pp. 530-540. 

IPCC (1997). Revised 1996 IPCC Guidelines for National Greenhouse Inventories. Houghton J.T., Meira Filho 

L.G., Lim B., Tréanton K., Mamaty I., Bonduki Y., Griggs D.J. Callander B.A. (Eds). Intergovernmental 

Panel on Climate Change (IPCC), IPCC/OECD/IEA, Paris, France. 
Volume 4: Agriculture, Forestry and Other Land Use 

10.86 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

Mangino, J., Bartram, D. and Brazy, A. (2001). Development of a methane conversion factor to estimate 

emissions from animal waste lagoons. Presented at U.S. EPA’s 17th Annual Emission Inventory 

Conference, Atlanta GA, April 16-18, 2002. 

Moller, H.B., Sommer, S.G. and Ahring, B. (2004). Biological degradation and greenhouse gas emissions during 

pre-storage of liquid animal manure. Journal of Environmental Quality, 33: pp. 27-36. 

Peterson, K. and Jacobs, H. (2003). 1990-2002 Volatile solids and Nitrogen excretion rates deliverable under 

EPA Contract No. GS-10F-0124J, Task Order 004-02. Memorandum to EPA from ICF Consulting. 

August 28, 2003. 

Safley, L.M., Casada, M.E., Woodbury, J.W. and Roos, K.F. (1992). Global Methane Emissions from Livestock 

and Poultry Manure. US Environmental Protection Agency, Global Change Division, Washington, D.C., 

February 1992, EPA/400/1091/048. 

Sneath, R.W., Phillips, V.R., Demmers, G.M., Burgess, L.R. and Short, J.L. (1997). Long Term Measurements 

of Greenhouse Gas Emissions from UK Livestock Buildings. Bio-Engineering Division, Silsoe Research 

Institute, Wrest Park, Silsoe, Bedford, MK45 4HS. Livestock Environment: Proceedings of the Fifth 

International Symposium. Bloomington MN. May 29-31, 1997. 

Sommer, S.G., Petersen, S.O. and Sogaard, H.T. (2000). Greenhouse gas emissions from stored livestock slurry. 

Journal of Environmental Quality, 29: pp. 744-751. 

Steed Jr, J. and Hashimoto, A.G. (1994). Methane emissions from typical manure management systems. 

Bioresource Technology 50: pp. 123-130. 

USDA (1996). Agricultural Waste Management Field Handbook, National Engineering Handbook (NEH). Part 

651, U.S. Department of Agriculture, Natural Resources Conservation Service. July. 

Woodbury, J.W. and Hashimoto, A. (1993). Methane Emissions from Livestock Manure. In International 

Methane Emissions, US Environmental Protection Agency, Climate Change Division, Washington, D.C., 

U.S.A. 

Zeeman, G. (1994). Methane production/emission in storages for animal manure. Fertilizer Research 37: 207-

211, 1994. Kluwer Academic Publishers, Netherlands. 

SECTION 10.5 NITROUS OXIDE EMISSIONS FROM MANURE MANAGEMENT 

Amon, B., Amon, Th., Boxberger, J. and Pollinger, A. (1998). Emissions of NH3, N2O, and CH4 from composted 

and anaerobically stored farmyard manure. Pages 209-216 in Martinez J, Maudet M-N (eds) Ramiran 98, 

Proc. 8th Int. Conf. on the FAO ESCORENA Network on Recycling of Agricultural, Municipal and 

Industrial Residues in Agriculture. Rennes, France. 

Amon, B., Amon, Th., Boxberger, J. and Alt, Ch. (2001). Emissions of NH3, N2O, and CH4 from dairy cows 

housed in a farmyard manure tying stall (Housing, Manure Storage, Manure Spreading). Nutrient Cycling 

in Agroecosystems, 60: pp. 103-113. 

Asman, W.A.H., Sutton, M.A. and Schjoerring, J.K. (1998). Ammonia: emission, atmospheric transport and 

deposition. New Phytol., 139, p. 27-48 

Bierman, S., Erickson, G.E., Klopfenstein, T.J., Stock, R.A. and Shain, D.H. (1999). Evaluation of nitrogen and 

organic matter balance in the feedlot as affected by level and source of dietary fiber. J. Anim. Sci.

77:1645-1653. 

Döhler, H., Eurich-Menden, B., Dämmgen, U., Osterburg, B., Lüttich, M., Bergschmidt, A., Berg, W., Brunsch, 

R. (2002). BMVEL/UBA-Ammoniak-Emissionsinventar der deutschen Landwirtschaft und 

Minderungsszenarien bis zum Jahre 2010. Texte 05/02. Umweltbundesamt, Berlin. 

Dustan, A. (2002). Review of methane and nitrous oxide emission factors in cold climates. Institutet for 

jordbruks-och miljoteknik, JTI-rapport, Lantbruk & Industri, 299. 

Eghball, B. and Power, J.F. (1994). Beef cattle feedlot manure management. J. Soil Water Cons. 49:113-122. 

European Environmental Agency (2002). Joint EMEP/CORINAIR Atmospheric Emission Inventory Guidebook, 

3rd ed., July 2002, Copenhagen. 

Groot Koerkamp, P.W.G., Speelman, L. and Metz, J.H.M. (1998). Effect of type of aviary, manure and litter 

handling on the emission kinetics of ammonia from layer houses. Br. Poult. Sci., 39, p. 379-392. 

Hao, X., Chang, C., Larney, F.J. and Travis, G.R. (2001). Greenhouse gas emissions during cattle feedlot manure 

composting. Journal Environmental Quality 30: pp. 376-386. 
 Chapter 10: Emissions from Livestock and Manure Management 

2006 IPCC Guidelines for National Greenhouse Gas Inventories 10.87 

Harper, L.A., Sharpe, R.R. and Parkin, T.B. (2000). Gaseous emissions from anaerobic swine lagoons: 

Ammonia, Nitrous Oxide, and Dinitrogen Gas. Journal of Environmental Quality 29: pp. 1356-1365. 

Hutchings, N.J., Sommer, S.G., Andersen, J.M. and Asman, W.A.H. (2001). A detailed ammonia emission 

inventory for Denmark. Atmospheric Environment, 35, p. 1959-1968. 

Külling, D.R., Menzi, H., Sutter, F., Lischer, P. and Kreuzer, M. (2003). Ammonia, nitrous oxide and methane 

emissions from differently stored dairy manure derived from grass- and hay-based rations. Nutrient 

Cycling in Agroecosystems, 65: pp. 13-22. 

Lague, C., Fonstad, T. A., Marquis, A., Lemay, S.P., Godbout, S. and Joncas, R. (2004). Greenhouse Gas 

Emissions from Swine Operations in Québec and Saskatchewan: Benchmark Assessments. Climate 

Change Funding Initiative in Agriculture (CCFIA), Canadian Agricultural Research Council, Ottawa, ON. 

Meisinger, J.J. and Jokela, W.E. (2000). Ammonia Volatilization from Dairy and Poultry Manure. In: Managing 

Nutrients and Pathogens from Animal Agriculture. Natural Resource, Agriculture, and Engineering 

Service, Ithaca, NY. March 28-30, 2000. NRAES-130, p.334-354. 

Moller, H.B., Sommer, S.G. and Anderson, B.H. (2000). Nitrogen mass balance in deep litter during the pig 

fattening cycle and during composting. Journal of Agricultural Science, Cambridge 137:235-250. 

Monteny G. J., Groesetein C. M. and Hilhorst M. A. (2001). Interactions and coupling between emissions of 

methane and nitrous oxide from animal husbandry. Nutrient Cycling in Agroecosystems, 60: pp. 123-132. 

Monteny, G.J. and Erisman, J.W. (1998). Ammonia emissions from dairy cow buildings: A review of 

measurement techniques, influencing factors and possibilities for reduction. Neth. J. Agric. Sci., 46, p. 

225-247. 

Moreira, V.R. and Satter, L.D. (2004). Estimating nitrogen loss from dairy farms. Pedology. 

National Research Council (NRC) (1996). Nutrient Requirements of Beef Cattle, 7th Revised Ed., Nat. Acad. 

Press, Washington., DC 

Nicks, B., Laitat, M., Vandenheede, M., Desiron, A., Verhaege, C. and Canart, B. (2003). Emissions of 

Ammonia, Nitrous Oxide, Methane, Carbon Dioxide, and Water Vapor in the Raising of Weaned Pigs on 

Straw-Based and Sawdust-Based Deep Litters. Animal Research Journal, 52: pp. 299-308. 

Rotz, C.A. (2004). Management to reduce nitrogen losses in animal production. J. Anim. Sci. 82(E. 

Suppl.):E119-E137. 

Sneath, R.W., Phillips, V.R., Demmers, G.M., Burgess, L.R. and Short, J.L. (1997). Long Term Measurements 

of Greenhouse Gas Emissions from UK Livestock Buildings. Bio-Engineering Division, Silsoe Research 

Institute, Wrest Park, Silsoe, Bedford, MK45 4HS. Livestock Environment: Proceedings of the Fifth 

International Symposium. Bloomington MN. May 29-31, 1997. 

Sommer, S.G. and Moller, H.B. (2000). Emission of greenhouse gases during composting of deep litter from pig 

production – effect of straw content. Journal of Agricultural Science, Cambridge 134:327-335. 

Sommer, S.G., Petersen, S.O. and Søgaard, H.T. (2000). Greenhouse gas emission from stored livestock slurry. 

Journal of Environmental Quality 29: pp. 744-751. 

US EPA (2004). National Emission Inventory – Ammonia Emissions from Animal Husbandry Operations, Draft 

Report. January 30, 2004. 

Wagner-Riddle, C. and Marinier, M. (2003). Improved Greenhouse Gas Emission Estimates from Manure 

Storage Systems. Prepared for Climate Change Funding Initiative in Agriculture, Final Project Report, 

Component 2-3 Projects, Climate Change Science and Technology. 

Webb, J. (2001). Estimating the potential for ammonia emissions from livestock excreta and manures. Environ. 

Pollut. 111, p. 395-406.