United States
Environmental Protection
Agency
Air And
Radiation
(ANR-445)
EPA/400/1-91/048
February 1992
&EPA
Global Methane Emissions
From Livestock
And Poultry Manure
•
Printed on Recycled Paper
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GLOBAL METHANE EMISSIONS FROM LIVESTOCK AND POULTRY MANURE
by
L M. Safley, Jr. & M. E. Casada
North Carolina State University
Jonathan W. Woodbury
ICF Consulting Associates, Incorporated
Kurt F. Roos
U.S. Environmental Protection Agency
February 1992
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ACKNOWLEDGEMENTS
The authors would like to thank the many individuals who assisted in the preparation of
this report. In particular the authors are grateful to the many animal waste experts who
contributed to this report with their expertise and insights. The authors are grateful also to the
reviewers who helped to improve this report through their suggestions and comments; especially
Michael Gibbs of ICF.
LM. Safley and M.E. Casada
Biological and Agricultural Engineering Department
North Carolina State University
Box 7625
Raleigh, NC 27695-7625
Jonathan Woodbury
ICF Consulting Associates, Incorporated
10 Universal City Plaza
Suite 2400
Universal City, CA 91608-1097
Kurt Roos
Global Change Division
U.S. Environmental Protection Agency
ANR-445
401 M Street, SW
Washington, D.C. 20460
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TABLE OF CONTENTS
ABBREVIATIONS vi
EXECUTIVE SUMMARY 1
BACKGROUND 1
METHANE PRODUCTION 2
METHODOLOGY 2
RESULTS 3
1. INTRODUCTION 7
BACKGROUND 7
METHANE EMISSIONS FROM ANIMAL WASTE 8
THIS REPORT 8
2. FUNDAMENTALS OF METHANE PRODUCTION FROM ANIMAL WASTES 11
ANIMAL WASTE DECOMPOSITION 11
THE ANAEROBIC DIGESTION PROCESS 12
METHANE PRODUCING CAPACITY OF ANIMAL WASTE 13
FACTORS INFLUENCING METHANE PRODUCTION 14
3. METHODOLOGY AND DATA 17
METHODOLOGY 17
VOLATILE SOLIDS PRODUCTION (VS) 19
MAXIMUM METHANE PRODUCING CAPACITY (BJ 23
WASTE MANAGEMENT SYSTEMS DEFINITIONS 28
METHANE CONVERSION FACTORS (MCFs) .- 29
CLIMATE ADJUSTMENT FACTORS (CAFs) 33
ANIMAL WASTE MANAGEMENT SYSTEM USAGE (WS%) 34
4. ANIMAL WASTE EMISSIONS ESTIMATES 47
UNITED STATES EMISSION ESTIMATE 47
WORLD EMISSION ESTIMATE 52
RANGE OF ESTIMATES 53
5. REFERENCES 61
APPENDICES
APPENDIX A: U.S. ANIMAL POPULATIONS
APPENDIX B: U.S. ANIMAL WASTE METHANE PRODUCTION
APPENDIX C: LIVESTOCK CATEGORY WEIGHTS FOR SELECTED COUNTRIES
APPENDIX D: CANADA ANIMAL WASTE METHANE PRODUCTION
APPENDIX E: GLOBAL ANIMAL WASTE METHANE PRODUCTION
APPENDIX F: REQUESTS FOR DATA - UNITED STATES AND WORLD
APPENDIX G: U.S. WASTE MANAGEMENT SYSTEM METHANE PRODUCTION
APPENDIX H: U.S. ANIMAL WASTE MANAGEMENT SYSTEM USAGE
APPENDIX I: GLOBAL ANIMAL WASTE MANAGEMENT SYSTEM USAGE
APPENDIX J: GLOBAL ANIMAL WASTE PRODUCTION
APPENDIX K: INFORMATION CONTRIBUTORS
APPENDIX L: IPCC WORKSHOP FINDINGS
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IV
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UST OF EXHIBITS
EXHIBIT 1: GLOBAL ANIMAL WASTE METHANE EMISSIONS BY ANIMAL TYPE AND REGION . . 4
EXHIBIT 2: GLOBAL WASTE METHANE EMISSIONS BY REGION AND SYSTEM 5
EXHIBIT 3: SOURCES OF METHANE EMISSIONS 9
EXHIBIT 4: U.S. ANIMAL POPULATIONS, AVERAGE SIZE, AND VS PRODUCTION 21
EXHIBIT 5: AVERAGE ANIMAL STATISTICS FOR DEVELOPED COUNTRIES 22
EXHIBIT 6: ANIMAL WASTE PRODUCTION DATA FOR DEVELOPING COUNTRIES 24
EXHIBIT 7: MAXIMUM METHANE PRODUCING CAPACITY FOR U.S. ANIMAL WASTE 25
EXHIBIT 8: MAXIMUM METHANE PRODUCING CAPACITY ADOPTED FOR U.S. ESTIMATES ... 26
EXHIBIT 9: TYPICAL LIVESTOCK DIETS FOR THE WORLD 27
EXHIBIT 10: B0 VALUES ADOPTED FOR DEVELOPED AND DEVELOPING COUNTRIES 27
EXHIBIT 11: METHANE POTENTIAL BY WASTE MANAGEMENT SYSTEM TYPE 30
EXHIBIT 12: METHANE CONVERSION FACTORS (MCF) FOR WASTE SYSTEMS 31
EXHIBIT 13: COUNTRIES CONSIDERED CLIMATIC EXCEPTIONS 34
EXHIBIT 14: REGIONS OF THE WORLD FOR ANIMAL WASTE MANAGEMENT STUDY 35
EXHIBIT 15: PER CAPITA GROSS NATIONAL PRODUCTS (U.S. DOLLARS) 37
EXHIBIT 16: REGIONS OF THE U.S. FOR WASTE MANAGEMENT CHARACTERIZATION 38
EXHIBIT 17: ANIMAL WASTE SYSTEM USAGE FOR NORTH AMERICA 39
EXHIBIT 18: ANIMAL WASTE SYSTEM USAGE FOR WESTERN EUROPE 40
EXHIBIT 19: ANIMAL WASTE SYSTEM USAGE FOR EASTERN EUROPE 41
EXHIBIT 20: ANIMAL WASTE SYSTEM USAGE FOR OCEANIA 42
EXHIBIT 21: ANIMAL WASTE SYSTEM USAGE FOR LATIN AMERICA 43
EXHIBIT 22: ANIMAL WASTE SYSTEM USAGE FOR AFRICA 44
EXHIBIT 23: ANIMAL WASTE SYSTEM USAGE FOR NEAR EAST AND MEDITERRANEAN 45
EXHIBIT 24: USE OF BIOGAS DIGESTERS IN DEVELOPING COUNTRIES 45
EXHIBIT 25: ANIMAL WASTE SYSTEM USAGE FOR ASIA AND FAR EAST 46
EXHIBIT 26: U.S. METHANE EMISSIONS FROM ANIMAL WASTE 48
EXHIBIT 27: INDIVIDUAL U.S. STATE AND SYSTEM METHANE EMISSIONS 49
EXHIBIT 28: INDIVIDUAL U.S. STATE AND ANIMAL METHANE EMISSIONS (MT/YR) 51
EXHIBIT 29: U.S. METHANE EMISSIONS FROM WASTE MANAGEMENT SYSTEMS 52
EXHIBIT 30: WORLDWIDE METHANE EMISSIONS BY REGIONS (TG/YR) 53
EXHIBIT 31: GLOBAL METHANE EMISSIONS SUMMARY 54
EXHIBIT 32: WORLDWIDE METHANE EMISSIONS BY WASTE SYSTEM 58
EXHIBIT 33: BASE, HIGH, AND LOW CASE EMISSION ESTIMATE ASSUMPTIONS 59
EXHIBIT 34: BASE, HIGH, AND LOW CASE EMISSION ESTIMATES 59
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ABBREVIATIONS
AWMS = animal waste management system
B0 = maximum methane production capacity
CAP = climate adjustment factor
CH4 = methane
CO2 = carbon dioxide
f of B0 = fraction of B0 that is achieved (f of B0 = MCF • CAP).
g = grams
h = head
kg = kilograms
Ib = pounds
m3 = cubic meters
MCF = methane conversion factor
MJ = megajoules = 106 joules
mo = month
mt = metric ton = 106 grams = 103 kilograms
Pop = population
ppmv = part per million by volume
JAM = typical animal mass
Tg = teragram = 1012 grams = 109 kilograms = 106 metric tons
TM = annual mass methane production
Tot = total
TS = total solids
VMP = daily volumetric methane production
VS = volatile solids
WS% = percentage of waste handled by a waste system
wb = weight basis
VI
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EXECUTIVE SUMMARY
This report estimates that global methane emissions from animal waste are about 28
Tg/yr1 with a range of about 20 to 35 Tg/yr, or about 6 to 10 percent of total annual
anthropogenic emissions. These estimates were made by collecting information on the methane
producing potential of animal waste management systems around the world and the quantity of
animal waste managed by each system. Information was collected from government statistics,
literature reviews, and animal waste experts worldwide. This report is one of a series of reports
being prepared by the U.S. Environmental Protection Agency to estimate global methane
emissions and to identify options for stabilizing global methane concentrations.
BACKGROUND
The atmospheric concentration of methane (CH4), currently about 1.7 ppmv,2 is
increasing at a rate of about 1 percent per year and has more than doubled over the last two
centuries. Prior to this doubling, the atmospheric concentration of methane remained fairly
constant, at least as far back as 160,000 years before present. The increased abundance of
methane will have important impacts on global climate change, tropospheric (ground-based)
ozone, and the stratospheric ozone layer. Estimates are that methane contributes about 20
percent of the expected global warming from the greenhouse effect, second only to carbon
dioxide (EPA 1989).
c
As part of the overall strategy to identify options for stabilizing global methane
concentrations, emissions inventories are being prepared and opportunities for reducing methane
emissions are being identified and evaluated by the U.S. Environmental Protection Agency and
others. Methane emission estimates from the decomposition of animal wastes are necessary
both to improve understanding of the emissions sources and to help identify opportunities for
controlling emissions. The estimates presented in this report do not include methane emissions
from the digestive processes of ruminant animals (i.e., due to enteric fermentation) and do not
include emissions resulting from the decomposition of the waste of wild animals.
Tg = 1 teragram = 1012 grams = 109 kilograms = 106 metric tons
2 ppmv is parts per million by volume.
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METHANE PRODUCTION
Methane is produced during the anaerobic decomposition3 of the organic material in
livestock waste. Because the quantity of livestock waste is large and because the waste is
primarily composed of organic material, the potential for methane emissions is large. However,
only a portion of this emissions potential is realized because when waste is kept in contact with
oxygen (e.g., spread on fields) methane production is minimal.
The principal determinants of methane production from animal waste are the following:
• Quantity and Characteristics of the Waste. Potential methane production is
directly related to the quantity of waste and the fraction of the waste available for
decomposition. These factors vary by animal species and their diet.
• Waste Management System. The waste management system strongly influences
methane production from animal waste. Waste management systems that
promote anaerobic (oxygen free) decomposition will produce methane.
• Temperature and Moisture. Temperature and moisture affect both the rate and
total amount of methane production in animal waste. A warm and moist
environment promotes methane production.
METHODOLOGY
The steps used to estimate emissions are:
1. Identify waste management systems in use throughout the world and estimate
their methane producing potential.
2. Estimate the amount of waste managed in each system.
3. Estimate methane emissions by multiplying the amount of waste managed in each
waste system by the estimated emissions rate per unit of waste in the system.
Information was obtained from a variety of sources, including: FAO Production Yearbook; the
U.S. Census of Agriculture and USDA agriculture statistics; animal science experts throughout
the world; and literature reviews.
3 Anaerobic decomposition (fermentation) of animal waste is a micro-biological process that occurs in an oxygen
free environment.
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RESULTS
This report estimates that global methane emissions from animal waste are about 28 Tg/yr
with a range of about 20 to 35 Tg/yr, or about 6 to 10 percent of total annual anthropogenic
emissions. Exhibit 1 illustrates the global distribution of these emissions by region and animal
type. Exhibit 2 presents the global distribution of emissions by region and animal waste
management system. The major findings of this report are that:
• Of the 28 Tg/yr, liquid animal waste management systems (liquid/slurry storage
and anaerobic lagoons) account for over 10 Tg/yr, or about 35 percent of total
emissions from animal waste. These systems are used at confined, energy
intensive livestock operations and may provide profitable opportunities to recover
methane for use as a fuel.
• Of the 28 Tg/yr, three regions account for 78 percent of the total: Europe (Eastern
and Western) with 11.4 Tg/yr (40 percent); Asia and the Far East with 6.4 Tg/yr (23
percent); and North America with 4.2 Tg/yr (15 percent).
• Of the 28 Tg/yr, over 20 Tg are from three animal groups: cattle (beef and draft
animals), dairy cows, and swine.
These methane emission estimates are uncertain for various reasons, including:
• The estimates of the methane produced by pasture and range waste is very
uncertain. Assumptions regarding methane emission from waste in pasture have
a large influence on the overall emissions estimate because a large portion of
animal waste is found in pastures.
• Data on animal numbers, size, and feed are uncertain for many developing
countries.
• Limited data are available to assess the methane producing potential of animal
waste in developing countries.
• Limited data exist on the types and numbers of animal waste systems in
developing countries.
While many of the assumptions used to estimate emissions may be uncertain, this report
provides a framework for estimating emissions. As additional data become available, the
estimates can be improved. The report will focus research by indicating the regions and animal
waste systems that likely produce the greatest emissions. In addition, the report will help identify
regions where profitable opportunities for reducing emissions exist.
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tn
E-
Eastern Europe
.sia and Far East
Western Europe
Hortb Anerica
Latin America
Africa
Oceania
Near East and Mediterranean
Animal
Typo
North
America
West East
Europe Europe
Oceania
Latin
America
Africa
Near
East
&Med
Asia&
Far
East
Total*
Cattle 1.5 1.7 2.2 0.5 1.2 0.7 0.1 1.5 9.4
Dairy 1.1 1.5 2.0 0.2 0.2 0.1 0.1 0.6 5.9
Swine 1.2 1.1 1.3 0.1 0.2 <0.1 <0.1 1.8 5.8
Sheep and Goats <0.1 0.3 0.4 0.4 0.2 0.3 0.2 0.6 2.5
Poultry 0.2 0.1 0.3 <0.1 0.2 0.1 0.1 0.6 1.7
Other Animals 0.1 0.1 0.3 <0.1 0.8 0.2 0.2 1.3 2.9
4.2
4.9
6.5
1.3
2.9
1.5
0.7
6.4 28.3
A Totals may not add due to rounding.
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tXHiKT2j
a)
Q)
tn
E-
Eastern Europe
Asia and Far East
Western Europe
North America
Latin America ,
Africa
Oceania
East and Mediterranean
*
Waste Management North West East
System America Europe Europe
Oceania
Latin
America
Africa
Near
East
&Med
Asia
&Far
East Total*
Pasture/Range 1.3 0.8 1.2 1.2 2.2 1.3 0.5 1.8 10.2
Liquid/Slurry 0.4 3.2 2.6 0.0 0.0 0.0 0.0 0.9 7.2
Solid Storage 0.1 0.4 1.6 0.0 0.0 0.0 0.0 0.0 2.1
Anaerobic Lagoon 1.5 0.0 0.5 0.1 0.0 0.0 0.0 0.7 2.8
Drylot 0.3 0.0 0.1 0.0 0.1 0.1 0.0 0.9 1.5
Burned for Fuel 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0
Daily Spread 0.1 0.1 0.0 0.0 0.1 0.0 0.0 0.2 0.6
Other Systems 0.6 0.3 0.6 0.0 0.4 0.1 0.1 0.9 3.0
Tota^
4.2
4.9
6.5
1.3
2.9
1.5
0.7
6.4 28.3
A Totals may not add due to rounding.
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CHAPTER 1. INTRODUCTION
BACKGROUND
Comprehensive global measurements since the late 1970s indicate that the global
average methane concentration is about 1.7 ppmv4 and is increasing at the rate of about one
percent per year or about 0.017 ppmv per year (Blake and Rowland 1988). Atmospheric
methane concentrations are determined by natural and anthropogenic emissions (sources) and
by destruction mechanisms (sinks).
To explain the observed increases in atmospheric methane, it is believed that methane
emissions related to human activities are increasing. These anthropogenic sources include:
animals (primarily ruminant livestock); animal waste; rice cultivation; biomass burning; oil and gas
production and distribution; coal mining; and landfills. Exhibit 3 summarizes the major
anthropogenic and natural sources of methane.
The observed increased abundance of methane, when coupled with methane's chemical
and radiative properties, will have adverse impacts on environmental quality and human health.
These impacts include:
Global Climate Change: Methane is very effective at absorbing infrared radiation (IR).
Comparatively, a gram of methane will initially absorb about 70 times as much IR as will
a gram of carbon dioxide. Methane's contribution to global warming is believed to be
second only to CO2 (EPA 1989).
Tropospheric Ozone: Methane is primarily destroyed through reaction with the hydroxyl
(OH) radical in the atmosphere. In the presence of NOX (NO and NO2) these reactions
result in the formation of tropospheric ozone (Lashof 1989) which will also contribute to
the greenhouse effect. In addition, increasing concentrations of tropospheric ozone, a
primary component of urban "smog," are considered to be a threat to human health,
crops, ecosystems and polymer-based materials (EPA 1987).
Stratospheric Ozone: Increasing methane concentrations will tend to suppress
tropospheric OH through atmospheric reactions which, unopposed, will deplete the
oxidizing potential of the atmosphere, including its capacity for removing hydrogenated
chlorofluorocarbons (HCFCs) (Thompson and Cicerone 1986; Thompson et al. 1989).
The resulting slower removal of the HCFCs from the atmosphere will exacerbate
stratospheric ozone depletion. In addition, the water vapor that is added to the
stratosphere when methane is oxidized may enhance the destruction of stratospheric
ozone (Blake and Rowland 1988).
4
ppmv is parts per million by volume.
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METHANE EMISSIONS FROM ANIMAL WASTE
The amount of methane produced by animal waste depends on how the waste is
managed. If the waste is managed aerobically, in contact with oxygen (e.g., spread on fields),
then methane production is minimal. If the waste is managed anaerobically, kept out of contact
with oxygen (e.g., placed in lagoons or liquid/slurry storage) then methane production may be
substantial.
Anaerobic conditions are most likely to occur in locations where large numbers of animals
are managed in a confined location (e.g., dairies in the United States and Europe, feedlots in the
United States; swine farms in the United States). Typically, a large amount of waste accumulates
until it is hauled away or washed into a waste treatment lagoon, thereby producing anaerobic
conditions that lead to methane production.
Until recently, methane emissions from animal waste have not been considered explicitly
as a major source of methane emissions. Bingemer and Crutzen (1987) state that the large
amount of organic matter produced in agricultural wastes may contribute a very significant part
of the world's annual methane budget, but they found no information on how much animal waste
is anaerobically decomposed to produce methane. Verma et al. (1988) estimated that if all of the
world's livestock and poultry manure were anaerobically decomposed then up to 152 Tg/yr of
methane would be produced. However, Verma et al. (1988) estimated that less than 10 percent
of this manure actually undergoes anaerobic decomposition.
THIS REPORT
As part of an overall strategy to identify options for stabilizing global methane
concentrations, emissions inventories are being prepared and opportunities for reducing methane
emissions are being identified and evaluated by the U.S. Environmental Protection Agency and
others. By estimating methane emissions from the management of animal wastes throughout
the world, this report provides a next step toward improving emissions estimates and identifying
regions with emission levels and management systems suitable for control.
This report is organized as follows:
Chapter 2 describes the process of methane production in animal waste and the
factors that influence it.
• Chapter 3 describes the methodology and data used to estimate emissions in the
U.S. and rest of the world.
• Chapter 4 presents emission estimates by region, animal type, and waste system.
The appendices at the end of this report detail the emission estimates and list the data and
assumptions used to make the estimates.
8
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,t"^v' v "• 'X^~ *% '/ \ ',, \ " 3
•JV% v«, "osx'^rjcs^f™"'*}**!;
~r/Vv£h't r'"fp?£
Animal Wastes
Animals
Wastewater
Rice paddies
Coal Mining
Oil/Gas Systems
Landfills
Biomass Burning
Natural Wetlands
Termites
Oceans and
Freshwaters
Hydrates
Totalb
*Brr^ SOUR
Annual
Emissions
28
80
NRa
110
NRa
45
NR
55
115
40
15
5?
540
•/ ^v.\\s '"lAV-^™
Range
20-35
65-100
20-25
60-170
30-50
25-50
25-40
50-100
100-200
10-100
6-45
0-100
440-640
S^E^ifefstr^
Comments
Livestock in developed
and developing countries
Anaerobic decomposition
of organic matter in waste
water
Principally in developing
countries
Surface and (mostly) sub-
surface mining
Production, transmission,
and distribution
Decay of organic wastes
Forest clearing and waste
burning
Tundra, bogs, swamps,
and alluvial formations
Bacteria within termites
Potentially important future
source
Well constrained
' , '^, ~v;, " •;..""-
Source
This report
Cicerone and
Oremland
IPCC
Cicerone and
Oremland
IPCC
Cicerone and
Oremland
IPCC
Cicerone and
Oremland
Cicerone and
Oremland
Cicerone and
Oremland
Cicerone and
Oremland
Cicerone and
Oremland
Cicerone and
Oremland
Sources: Cicerone and Oremland (1988), "Biogeochemical Aspects of Atmospheric Methane," Global Biogeochemical
Cycles. December 1988. Japan Environment Agency and United States Environmental Protection Agency (1990), 'Methane Emissions
and Opportunities for Control. Workshop Results of Intergovernmental Panel on Climate Change Response Strategies Working
Group,1 September 1990.
a NR - not reported at the IPCC workshops
b Total annual emissions of 540 Tg ± 100 Tg is well constrained based on observational data. The point estimates of the
individual source estimates presented here do not sum to 540 Tg.
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10
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CHAPTER 2. FUNDAMENTALS OF METHANE PRODUCTION FROM ANIMAL WASTES
Waste decomposition is a process in which microorganisms derive energy and material
for cellular growth by metabolizing organic material in the waste. Under certain conditions,
methane is an end-product of the decomposition process. The factors that determine the amount
of methane produced are: the types of microorganisms present; the environmental conditions
such as temperature and moisture; and the characteristics of the waste.
ANIMAL WASTE DECOMPOSITION
Animal wastes are primarily composed of organic material and water. The portion of this
organic material that can be decomposed by microorganisms is the volatile portion, referred to
as volatile solids.5 Under certain conditions, a portion of the volatile solids is converted to
methane.
A variety of microorganisms are responsible for the decomposition of animal wastes.
These microorganisms are found in the environment in decaying vegetation, marshlands,
stagnant waters, and the digestive tracts of herbivorous animals (Chawla 1986). Like all
organisms, microorganisms require energy and carbon to function and reproduce. One source
of carbon is carbon dioxide in the atmosphere; another source is carbon found in organic
material, including animal waste. The two basic types of microorganisms are:
• Autotrophs. Autotrophic microorganisms derive carbon from atmospheric carbon
dioxide and use either light (photosynthesis) or an inorganic chemical process
(chemosynthesis) as a source of energy. Algae are a common type of autotrophic
microorganism.
• Heterotrophs. Heterotrophic microorganisms derive carbon from organic material
such as animal waste and obtain energy through the oxidation of this organic
material (Metcalf & Eddy 1972). Heterotrophic microorganisms include fungi and
many bacteria.
The primary microorganisms responsible for the decomposition of animal waste are
heterotrophic bacteria. While thousands of species of heterotrophic bacteria can be found under
a broad range of environmental conditions, an individual species may only thrive under a narrow
range of conditions. Heterotrophic bacteria can be broadly classified as aerobic, anaerobic, or
facultative, depending on their need for oxygen. Aerobic bacteria require molecular oxygen (02)
to live; whereas oxygen is fatal to anaerobic bacteria. Facultative bacteria live in either the
presence or absence of oxygen.
5 Volatile solids (VS) are defined as the organic fraction of the total solids (IS) in waste that will oxidize and be
driven off as gas at a temperature of 600° C. Total solids (TS) are defined as the material that remains after evaporation
of waste at a temperature between 103° and 105° C.
11
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The decomposition of animal waste can occur in either an aerobic or anaerobic
environment. Under aerobic conditions, the organic material is decomposed by aerobic and
facultative bacteria using molecular oxygen. The end products of aerobic decomposition are
carbon dioxide and stabilized organic material.6 Under anaerobic conditions, the organic
material is decomposed by anaerobic and facultative bacteria. The end products of anaerobic
decomposition are methane, carbon dioxide, and stabilized organic material. The bacteria
responsible for methane production in animal waste are strictly anaerobic.
THE ANAEROBIC DIGESTION PROCESS
o
The anaerobic digestion process can be described in terms of three stages: hydrolytic;
acid forming; and methanogenic. Carbohydrates in animal wastes are decomposed in these
three stages as follows:9
Stage 1: Hvdrolvtic. In the first stage, complex organic materials in the waste
substrate are broken down through the hydrolytic action of enzymes. Enzymes
are proteins formed by living cells that act as catalysts in metabolic reactions.
The enzyme cellulase is responsible for breaking down carbohydrates such as
cellulose and starch into simple sugars (e.g., glucose and maltose). Simple
organic acids are produced when the enzyme lipase breaks down fats (lipids) into
smaller chained fatty acids and the enzyme protease breaks down proteins into
amino acids. The amount and rate of breakdown can vary substantially and
depend on the enzymes present, the characteristics of the waste, and
environmental factors such as pH and temperature.
• Stage 2: Acid Forming. Anaerobic and facultative bacteria reduce (ferment) the
simple sugars produced in Stage 1 to simple organic acids. Acetic acid is the
primary product of the breakdown of carbohydrates, though other organic acids
such as propionic acid and butyric acid can be formed. In addition, hydrogen and
carbon dioxide are produced. The organic acids, along with hydrogen and
6 Stabilized organic material cannot be broken-down or decomposed further.
7 Aerobic and facultative bacteria, however, can also play a role by providing precursors for methane production.
8 Some authors describe the anaerobic digestion process as a two stage process with the first two stages as
described below being considered as a single stage.
9 This discussion focuses on the decomposition of carbohydrates because carbohydrate digestion accounts for
the majority of the methane produced from animal wastes and because the process of methane production from the
decomposition of carbohydrates is best understood. By weight, the volatile solids portion of cattle and swine wastes
is approximately 40 percent carbohydrate, 15 to 20 percent protein, 10 to 20 percent fat and 20 to 35 percent other
(Hrubant, Rhodes, and Sloneker 1978).
10 A catalyst is a chemical substance that modifies (generally increases) the rate of a chemical reaction without
being consumed or modified in the process.
12
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carbon dioxide form a substrate11 for the methane forming bacteria in Stage 3.
Unlike the methane forming bacteria, the acid formers are fast growing and thrive
at a broad range of temperature and pH. With acetic acid as an end product, the
breakdown of a simple sugar molecule (glucose) in Stage 2 can be represented
as:
C6H12°6 + 2H2° — > 2CH3COOH + 2CO2 + 4H2
glucose + water —> acetic acid + carbon dioxide + hydrogen
Stage 3: Methanogenic. Methane producing bacteria (methanogenes) convert the
simple organic acids, hydrogen, and carbon dioxide from Stage 2 into methane
and carbon dioxide. Methanogenes are strict anaerobes and cannot tolerate the
presence of molecular oxygen. Methanogenes multiply slowly and are very
sensitive to temperature, pH, and substrate composition. With acetic acid,
hydrogen and carbon dioxide as substrate, the reactions producing methane can
be expressed as:
2CH3COOH —> 2CH4 + 2CO2
acetic acid —> methane + carbon dioxide
4H2 + COjj —> CH4 + 2H20
hydrogen + carbon dioxide —> methane + water
METHANE PRODUCING CAPACITY OF ANIMAL WASTE
The specific composition of animal waste determines its maximum methane producing
capacity. The composition of the waste is primarily determined by the animal diet. The
composition and digestibility of the animal diet influences the methane capacity of the waste.
The greater the energy content and digestibility of the feed, the greater the methane producing
capacity of the waste. For example, cattle fed a high energy grain diet produce a highly
biodegradable waste which contains a large fraction of readily available organic material. Cattle
fed a roughage diet will produce a less biodegradable waste containing more complex organics
such as cellulose, hemicellulose, and lignin. Under similar conditions, the waste of cattle fed the
high energy corn-based diet will produce about twice as much methane as the waste of the cattle
fed a roughage diet.
In principal, the ultimate methane producing capacity of a quantity of waste can be
predicted from the gross elemental composition of the manure. In practice, however, insufficient
information exists to implement this approach and the methane producing capacity is determined
through direct laboratory measurement. The methane producing capacity of animal waste is
generally expressed in terms of the quantity of methane that can be produced per kilogram of
volatile solids (VS) in the waste. This quantity is commonly referred to as B0 with units of cubic
meters of methane (CH^ per kilogram VS (m3 CH4 / kg VS). Representative B0 values for a
number of animal waste types are discussed in Chapter 3.
11 Substrate refers to the material that the bacteria use for growth and metabolism.
13
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FACTORS INFLUENCING METHANE PRODUCTION
The characteristics of the animal waste management system and the climate influence the
amount of methane produced during waste decomposition. Realized methane production can
be defined as the quantity of methane produced per kilogram of volatile solids (VS) in the waste
for a given set of waste management practices and climatic conditions:
Realized Emissions = B0 • MCF • CAF (2.1)
where B0 = the maximum methane producing capacity of the waste determined
by animal type and diet (m3 CH4 / kg VS).
MCF(AWMS) = Methane Conversion Factor (MCF) that represents the extent to
which the B0 is realized for a given animal waste management
system {AWMS). Note: 0 * MCF <; 1.
CAF = Climate Adjustment Factor (CAF) that represents the extent to
which the B0 is realized under a given set of climatic conditions
(e.g., temperature and rainfall). Note: 0 ^ CAF <; 1 .
Animal Waste Management System Factors. MCF
The characteristics of the waste management systems determine the MCF of that system.
As defined in Equation 2.1 , waste systems that promote methane production will have an MCF
near 1 and systems that do not promote methane production will have an MCF near 0. The
primary characteristics determining the MCF of a waste system are:
• Contact with Oxygen. Under aerobic conditions where oxygen is in contact with
the waste, there is no potential for methane production in the waste.
• Moisture Content. Liquid based systems promote an oxygen-free environment
and anaerobic decomposition. In addition, water is required for bacterial cell
production and metabolism and acts as a buffer to stabilize pH. Moist conditions
increase the potential for methane production.
pH. Methane producing bacteria are sensitive to changes in pH. The optimal pH
is near 7.0 but methane will be produced in a range between 6.6 and 7.6.
Deviation in pH from 7.0 will decrease the rate of methane production.
• Nutrients. Bacterial growth depends on the availability of nutrients such as
nitrogen, phosphorus, and sulfur. Deficiency in one or more of these nutrients will
inhibit bacterial growth and methane formation. Animal diets typically contain
sufficient nutrients to sustain bacterial growth. Therefore, nutrient availability is not
a limiting factor in methane production under most circumstances.
14
-------
Climate Factors. CAP
The climatic conditions in which the waste decomposes have a strong influence on
methane production by the waste. As defined in Equation 2.1, climatic conditions that promote
methane production will have a CAP near 1 and conditions that inhibit methane production will
have a CAP near 0. These climate conditions include:
• Temperature. Methanogenesis in animal waste has been observed between 4° C
and 75° C. Temperature is one of the major factors affecting the growth of the
bacteria responsible for methane formation (Chawla 1986). Methane production
generally increases with rising temperature.
• Moisture. For non-liquid based waste systems, the moisture content of the waste
is determined by rainfall and humidity. The moisture content of the waste will
determine the rate of bacterial growth and waste decomposition. Moist conditions
promote methane production.
15
-------
16
-------
CHAPTER 3. METHODOLOGY AND DATA
Methane emissions from animal waste depend on the type of waste, the characteristics
of the waste management system, and the climatic conditions in which the waste decomposes.
Emission estimates were developed by identifying the waste management systems in use
throughout the world and their methane producing potential; estimating the amount and type of
waste managed by each system; and estimating emissions by multiplying the amount of waste
managed in each system by the estimated emission rate per unit of waste in the system.
Information was obtained from a variety of sources, including: FAO Production Yearbook; the
U.S. Census of Agriculture; USDA agriculture statistics; animal science experts throughout the
world; and the animal science literature.
METHODOLOGY
The methane emissions per kilogram of volatile solids (VS) depend on: the characteristics
of the waste (BJ; the characteristics of the waste management system (MCF); and the climatic
conditions such as temperature and moisture (CAP). Total emissions will equal the quantity of
volatile solids managed in each system times emissions per kilogram of volatile solids (VS). The
following procedure was performed to estimate total emissions:
• Estimate the amount of waste produced by collecting data on: (1) the populations
of the major animal types throughout the world; and (2) the sizes of the animals
(i.e., in kilograms per head). These data were obtained from published statistics.
• Collect information on the characteristics of the waste produced by each of the
animal populations, including: (1) the amount of volatile solids (VS) produced;
and (2) the methane producing capacity (BQ) of the waste. These data were
available from published sources for most developed countries but were estimated
for the developing countries.
• Identify the animal waste management systems employed in each part of the
world and the amount of waste managed by each. This information is not readily
available and was estimated based on interviews with animal waste experts. In
cases where no data were available, waste management system usage was
estimated using economic measures (e.g., per capita GNP) and regional averages.
• Estimate the methane producing potential (MCF) of each waste management
system. Direct measurements of methane emissions were used where available.
If no measurements were available, the MCFs were estimated by extrapolating
from similar systems based on the characteristics of the waste management
system, including: contact with oxygen, moisture content, and pH.
• Assess climatic conditions (CAP) for each waste system in each region using
temperature and precipitation data for each region of the world.
17
-------
• Estimate methane emissions for each animal and waste system by multiplying the
amount of volatile solids (VS) produced by the methane producing capacity of the
waste (BQ) times the methane producing potential (MCF) of the waste system
times the climate adjustment factor (CAP). Total methane emissions will be the
sum over all animal types and all waste systems.
Using this approach, total annual methane emissions (TM,-) for animal type / in a particular climate
region is the sum of annual emissions over all applicable waste management systems /:
TM, = £ VS, • Boi ' MCFJ ' CAFl ' WS%U
where:
VSj = total volatile solids produced annually (in kilograms) for animal /;
B0 1 = maximum methane producing capacity per kilogram of VS for animal /';
MCF, = methane conversion factor for each waste system y;
CAP, = climate adjustment factor for each waste system / in the region; and
WS%ij = percentage of the animal /"s waste handled using waste system y.
The amount of volatile solids produced depends on the number of animals and their mass:
VS, = N, • TAM, • vs, (3.2)
where:
NJ = number of animals;
TAM, = typical animal mass in kilograms; and
VSj = the average annual volatile solids production per unit of animal mass
(kilograms per kilogram).
In many cases either the typical animal mass (TAMJ) or volatile solids production per unit of
animal mass (vSj), or both, are not known. In these cases, total annual VS production per head
was estimated directly, so that the total annual VS production for the population of animals can
be estimated by:
VS, = N, • VS, (3.3)
where:
NJ = number of animals;
vs, = average volatile solids production per head.
Total annual methane emissions from all animals (TM) is estimated as the sum over all / animal
types as follows:
18
-------
TM = £ TM, (3.4)
These equations show that methane emissions are driven by five main factors: the
quantity of VS produced; the B0 values for the wastes; the MCFs for the waste management
systems; the climatic conditions (CAFs); and the portion of the waste handled by each waste
management system (WS%). The following sections describe the data collected to implement
this method:
• Volatile solids production (VS). Data were collected on the number of animals by
type and the volatile solids production per animal.
• Maximum methane producing capacity (B0). Data were obtained from the
literature for B0 for various animal types by region. In many cases estimates were
made based on diet information.
• Waste management system definitions. The waste systems used to manage
animal wastes in the United States and the rest of the world were defined.
Methane conversion factors (MCFs). The methane producing potential of each
animal waste management system was estimated using published data or
extrapolated from similar systems based on the characteristics of the system.
• Climate adjustment factors (CAFs). The climate adjustment factor for each animal
waste management system was estimated using published temperature and
precipitation data.
• Animal waste management system usage (WS%). Data were obtained for
estimating the portion of waste handled using each animal waste management
system.
VOLATILE SOLIDS PRODUCTION (VS)
Methane emissions from animal waste are directly related to the amount of volatile solids
^VS) produced. The data required to estimate total VS production are shown in Equation 3.2:
the number of animals (A/,-), their average size (TAM,), and their average VS production per unit
of animal size (vst). For developed countries, these data are generally available and Equation
3.2 can be implemented. For most developing countries, however, only animal population data
are available and total VS production must be estimated using Equation 3.3.
19
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Developed Countries
For the United States, considerable data were available that allowed the populations of
animals to be analyzed by: species, production system, and (for cattle) age. Six main categories
of animals were defined: feedlot beef cattle;12 other beef cattle; dairy cattle; swine; poultry;
and other. These main categories were further divided into 20 subcategories. For each
subcategory, VS production was estimated using data on: the animal population; the typical
animal mass (TAM); and the VS production per unit of animal mass. Exhibit 4 lists the data
obtained for the 20 subcategories.
For Canada, the animal populations were divided into the same categories used for the
United States analysis, with the exception that the feedlot beef cattle category was not used due
to a lack of data. Estimates of animal populations, TAMs, and VS production rates were obtained
from Agriculture Canada (1989). The TAM and VS production rates for Canada are very similar
to the rates shown in Exhibit 4 for the United States. Appendix D presents the estimates for
Canada.
For other developed countries, including Eastern Europe,13 the animal populations were
divided into the following 11 categories: beef cattle; dairy cattle; swine; sheep; goats; chickens;
ducks; turkeys; horses; donkeys; and camels. Population statistics were obtained for each
category for each country from FAO (1989). For 13 countries, data for estimating the TAMs for
each category were available from Meat and Dairy Products (1988) and Taiganides and
Stroshine (1971).14 For developed countries without country-specific TAM data, the average
of the values for the 13 countries was used.
The United States total manure and VS production rates per unit of animal mass were
used as the basis for estimating waste production per TAM for the other developed countries.
Small adjustments were made to several of the rates to reflect differences in diets. Exhibit 5
presents average statistics for the TAM, manure, and VS estimates for the other developed
countries. Detailed estimates by country are reported in Appendices C and E.
Developing Countries
The animal populations in developing countries were divided into the same 11 categories
used to analyze the animal populations in the other developed countries. Population data for
each category for each country were obtained from FAO (1989).
12 Feedlot cattle are animals fed a ration of grain, silage, hay and protein supplements for the slaughter market
(ASB 1991).
13 For purposes of this analysis the other developed countries include: Albania, Australia, Austria, Belgium,
Bulgaria, Czechoslovakia, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Japan, the
Netherlands, New Caledonia, New Zealand, Norway, Poland, Portugal, Romania, South Africa, Soviet Union, Spain,
Sweden, Switzerland, United Kingdom, and Yugoslavia.
14 The 13 countries for which TAM data were obtained are: Australia; Austria; Belgium; Denmark; France; Western
Germany; Ireland; Italy; Holland; South Africa; United Kingdom; Soviet Union; and Yugoslavia.
20
-------
f .£ ^i&^b^-fr,m-
Animal Type
Feedlot Beef Cattle
Other Beef Cattle
Dairy Cattle
Swine
Poultry0
Other
Steers
Heifers
Cows/Other
Total
Calves
Heifers
Steers
Cows
Bulls
Total
Heifers
Cows
Total
Market
Breeding
Total
Layers
Broilers
Ducks
Turkeys
Sheep
Goats
Donkeys
Horses and Mules
Population*'8
Ni
7,367,000
3,785,000
87,000
11,239,000
20,248,000
13,547,000
8,430,000
33,583,000
2,221,000
78,029,000
4,199,000
10,217,000
14,416,000
48,259,000
7,040,000
55,299,000
355,469,000
951,914,000
7,000,000
53,783,000
10,639,000
2,396,000
4,000
2,405,000
8£g,Af©V$yROpyCtK»* ^;';;:J
f f f.f •' •-
TAM;°
Kg
383
391
500
181
391
383
680
680
476
680
46
181
1.6
0.7
1.4
3.4
70
64
300
450
Waste per day0
(kg/day per 1000 kg mass)
Total
Manure
58
58
58
58
58
58
58
58
86
86
84
84
64
85
107
47
40
41
51
51
Volatile
Solids
7.2
7.2
7.2
7.2
7.2
7.2
7.2
7.2
10
10
8.5
8.5
12
17
18.5
9.1
9.2
9.5
10
10
A Population data for all animals except goats and horses from ASB (1988). Goat and horse population data from
Bureau of Census (1987). Population data as of January 1, 1988 for cattle, poultry, and sheep and as of
December 1, 1987 for swine, goats, and horses.
B Broiler and turkey populations are estimated yearly average averages based on the average number of flocks
per year (North 1978; Carter 1989).
c Source: Taiganides and Stroshine 1971 (See also Appendix A).
D Source: ASAE (1988).
21
-------
, .BCttBfTSi AVSW
-------
• Lichtman (1983) estimated (with the support of data) that Indian cattle produce 8
kg/day of "collectible" manure (produced at night while the animals are tied up)
at 20 percent total solids content.
Gorkhali (1984) estimated that cattle in Nepal produce 10 kg/day total manure.
• Chen et al. (1988) analyzed manure from dairy cattle fed on low quality roughage
diets (simulating the diet of African cattle) and found 20.1 percent TS and 17.4
percent VS.
Based on these values from the literature, cattle in developing countries were assumed to
produce 12.5 kg/day/head of total manure (about 60 percent of typical U.S. cattle) with 18
percent TS and 15 percent VS (wet basis).
There are rarely any specialized dairy cattle in developing countries. The vast majority
of "dairy" cattle are exactly the same as other cattle in those countries, except that they are
lactating. Comparatively, dairy cattle in the United States produce 78 percent more manure per
unit of live animal mass than do beef cattle in the United States (ASAE 1988). Because the
lactating cattle in developing countries are also generally better fed than the rest of the cattle
(Preston and Leng 1987), but not at the extreme level of specialized dairy breeds, their manure
production was assumed to be 25 percent greater than non-lactating cattle, or 15.6 kg/day per
head.
For horses, goats, and sheep (except for feedlot sheep), U.S. animals are not fed as much
above maintenance levels as are cattle; thus, the daily manure production for these animals in
developing countries is assumed to be 70 percent of that for U.S. animals. For sheep waste Jain
et al. (1981) reported 25.8 percent TS and 20.1 percent VS. These values are slightly below the
the U.S values. In the absence of data for horses and goats, the solids concentrations were
assumed to be the same as those for U.S. animals: horses, 29 percent TS and 20 percent VS;
and goats, 32 percent TS and 27 percent VS. Mules, donkeys, and camels were again assumed
to have the same manure characteristics as horses (except for camel VS which was assumed
to be between cattle and horses), and buffaloes the same characteristics as cattle.
Because the swine diets in developing countries are very similar to swine diets in the U.S.,
total manure production from swine was assumed to be 80 percent of that for typical swine in
the U.S. (ASAE 1988), with the same percentage of volatile solids as in the U.S. Exhibit 6
summarizes the manure and VS production estimates of all these animals for developing
countries.
MAXIMUM METHANE PRODUCING CAPACITY (BQ)
The maximum amount of methane that can be produced per kilogram of VS (BJ varies
by animal type and diet. This section presents the B0 values developed for animal waste in the
U.S. and the rest of the world.
23
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EXHIBITS: ANN
Animal Type
Cattle (non-dairy)
Dairy Cattle
Swine
Sheep
Goats
Chickens
Ducks
Turkeys
Horses and Mules
Donkeys
Camels
ilAL WASTE PRODUCT
Total Manure
Production
Kg/head/day
12.5
15.6
4.1
1.6
1.8
0.12
0.12
0.26
18.4
12.2
18.4
ION DATA FOB DEVELOP
f •? f * ._ f f
Volatile Solids
Percent of Total
Manure Production
15%
15%
10%
23%
27%
19%
17%
19%
20%
20%
16%
m&toti^^ '/ril
>•> % f ,-.*<• f f.rs ,•.*. "V-IA. f s -.
"• f ""* * ~J""' "~ r | " • • • '
i (VS) Production
Kg/head/day
1.9
2.3
0.41
0.37
0.49
0.02
0.02
0.05
3.7
2.4
2.9
United States
The various B0 values for U.S. animals identified from the literature are listed in Exhibit 7.
As shown in the exhibit, values for beef animals range from 0.17 cubic meters of methane per
kilogram of VS (m3/kg-VS) for a corn silage diet to 0.33 m3/kg-VS for a corn-based high energy
diet that is typical of feedlots. Ranges are also shown for the other animal types.
Appropriate B0 values were selected depending on the typical diet of each animal type
and category. For animal types without B0 measurements, the B0 was estimated based on
similarities with other animals and the authors' experience. Ruminants for which there were no
literature values were assumed generally to have the same values as cattle, except for sheep,
which were assumed to have B0 values 10 percent higher than cattle (Jain et al. 1981). Exhibit 8
lists the values selected for the analysis.
World
Unlike the U.S., virtually no data are available describing the B values for wastes
produced in other countries. Consequently, these values were estimated. In making these
estimates, the major impact of the variation in livestock diets around the world on the methane-
producing potential had to be considered. This effect was incorporated into the calculations of
methane emissions for the world by using B0 values that account for the estimated energy
content of the feed consumed by the animals. This approach required characterizing the animal
diets for different regions of the world.
24
-------
: ,, ;:?
Animal
Type
Beef
Beef
Beef
Beef
Beef
Dairy
Dairy
Dairy
Dairy
Horse
Poultry
Poultry
Poultry
Poultry
Swine
Swine
Swine
Swine
Swine
Swine
Swine
Swine
i •, •- J j -.
Diet
7% com silage, 87.6% corn
Corn-based high energy
91.5% com silage, 0% com
58-68% silage
72% roughage
Roughage, poor quality
Grain-based ration
Barley-based ration
Corn-based high energy
Corn-based high energy
Corn-based high energy
Corn-based high energy
Corn-based high energy
Corn-based high energy
'•''"•'•'i', -. '" ' •"• ,.,'''$.!..'.': 4.
, Bo
(m3 CH4 /kg-VS)
0.29
0.33
0.17
0.23
0.33
0.24
0.17
0.14
0.10
0.33
0.39
0.36
0.24
0.24
0.36
0.48
0.32
0.52
0.48
0.47
0.44
0.45
ftftllfi AldiMAf VifA&f£ "
-------
EXHIBIT 8: MAXIMUM METHANE PRODUCING CAPACITY ADOPTED FOR U.S. ESTIMATES
Animal Type, Category
Maximum Potential
Emissions (BJ
Reference
Cattle:
Swine:
Poultry:
Sheep:
Goats:
Horses and Mules:
Beef in Feedlots
Beef Not in Feedlots
Dairy
Breeder
Market
Layers
Broilers
Turkeys
In Feedlots
Not in Feedlots
0.33
0.17
0.24
0.36
0.47
0.34
0.30
0.30
0.36
0.19
0.17
0.33
Hashimoto et al. (1981)
Hashimoto et al. (1981)
Morris (1976)
Summers & Bousfield (1980)
Chen (1983)
Hill (1982 & 1984)A
Authors' estimate8
Authors' estimate8
Authors' estimate0
Authors' estimate0
Authors' estimate0
Ghosh (1984)
A Adjusted value.
B Based on Hill (1984).
C Based on Jain et al. (1981) and Hashimoto et al. (1981).
D Based on Hashimoto et al. (1981).
• Chen et al. (1988) reported that the B0 for African cattle is 0.10, which is 59
percent of the value for U.S. cattle not in feedlots.
Because these values consistently show that cattle in these developing regions consume and/or
excrete energy (B0 taken as a measure of excreted energy) at about 60 percent of the rate for
U.S. cattle, the B0 for non-dairy cattle in developing regions was taken to be 0.10 m3 CH4/kg-VS.
Using the diets in Exhibit 9 (D+ versus D rated diets), the B0 for dairy cattle was assumed
to be 0.13 m3 CH4/kg-VS, or 30 percent higher than the B0 for non-dairy cattle. Based on the
work of Jain et al. (1981), sheep waste was assumed to have a B0 of 0.13 m3CH4/kg-VS (about
30 percent higher than cattle). Goats were assumed to have the same B0 as sheep.
Because swine and poultry diets cannot be substantially reduced while still maintaining
growth, the digestible energy intake in Exhibit 9 is 80 percent of the energy intake for U.S.
animals not on high energy feeding; thus, B0 values for these animals were taken to be 80
percent of the value for U.S. animals. The same factor of 80 percent was used for horses, mules,
donkeys, and camels based on the B0 values for the U.S. (with mule and donkey waste B0
values assumed equal to B0 for horses; buffalo B0 assumed equal to cattle; and camel B
assumed between cattle and horses). Exhibit 10 summarizes the B0 values adopted.
26
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I ^o\V^V;VMXHI81T^ TVPICAfcUV
Region Cattle1 Dairy
Western Europe B
Eastern Europe B
Oceania (Developed) C
Oceania (Developing) D
Latin America D
Africa D
South Africa B/C
Near East and Mediterranean D
Israel B
Asia & Far East D
Japan B
Diets:
A - Dairy, very high energy, 230 MJ/day
B - Corn-based, high energy, 160 MJ/day
C - Pasture, medium energy, 100 MJ/day
D - Roughage, low energy, 60 MJ/day
D-f-Modrfied during lactation, 80 MJ/day
E - Grain, high energy, swine, 42 MJ/day
A
A
A
D+
D+
D+
A
D+
A
D+
A
F
G
H
I
J
Swine
E
E
E
E
H
H
E
H
E
H
E
- Grain, high
- Grain, high
- Roughage,
- Roughage,
- Roughage,
5 FOR
THE WORLD
Sheep Goats Poultry
B
B
C
D
D
D
C
D
B
D
B
energy,
energy,
medium
medium
C
C
C
D
D
D
C
D
C
D
C
F/G
F/G
F/G
-
I/J
I/J
F/G
I/J
F/G
I/J
F/G
..
Horses2
C
C
C
D
D
D
C
D
C
D
C
poultry, 0.30 MJ/day
turkey, 1 .5 MJ/day
energy, swine, 34
MJ/day
energy, poultry, 0.24 MJ/day
medium energy, turkey, 1 .4 MJ/day
1 Including buffaloes and camels; excluding dairy.
2 Including mules and donkeys.
Notes: Energy values are for gross energy. Diets F
diets A, B, C, and D: MJ/day
per
and I
do not include
turkeys.
For
typical cattle live animal mass.
- EXHIBIT 10: B0 VALUES ADOPTED FOR DEVELOPED AND DEVELOPING COUNTRIES
Animal Type
Cattle (non-dairy) and buffalo
Dairy Cattle
Swine
Sheep
Goats
Chickens
Ducks
Turkeys
Horses and Mules
Donkeys
Camels
A The lower value is for cattle
Developed Countries
(Non-U.S.)
(m3 CH4 / kg VS)
0.17/0.33A
0.24
0.45
0.19
0.17
0.32
0.32
0.30
0.33
0.33
0.26
not in feedlots. The higher value is for feedlot cattle.
Developing
Countries
(m3 CH4 / kg VS)
0.10
0.13
0.29
0.13
0.13
0.24
0.24
0.24
0.26
0.26
0.21
27
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WASTE MANAGEMENT SYSTEMS DEFINITIONS
A variety of waste management practices are in use throughout the world. In many parts
of the world, manure is spread on fields as a fertilizer. In other cases, manure is used as an
energy source. The following is a brief description of the major animal waste management
systems in use.
PASTURE/RANGE
DAILY SPREAD
SOLID STORAGE
DRYLOT
DEEP PIT STACKS
LITTER
PADDOCK
LIQUID/SLURRY
ANAEROBIC LAGOON
Animals that are grazing on pasture are not on any true waste handling
system. The manure from these animals is allowed to lie as is, and is not
handled at all.
With the daily spread system the manure is collected in solid form, with or
without bedding, by some means such as scraping. The collected manure
is applied to fields on a regular basis (usually daily).
In a solid storage system the solid manure is collected as in the daily
spread system, but this collected manure is stored in bulk for a long
period of time (months) before any disposal.
In dry climates animals may be kept on unpaved feedlots where the
manure is allowed to dry until it is periodically removed. Upon removal the
waste may be spread on fields.
With caged layers the manure may be allowed to collect in solid form in
deep pits (several feet deep) below the cages. The manure in the pits may
only be removed once a year. This manure generally stays dry.
Broilers and young turkeys may be grown on beds of litter -- shavings,
sawdust, or peanut hulls - and the manure/litter pack is removed periodi-
cally between flocks. This manure will not generally be as dry as with
deep pits, but will still be in solid form.
Horses are frequently kept in paddocks where they are confined to a
limited area, but not entirely confined to their stalls. This manure will be
essentially the same as manure on pasture or a drylot. The manure left in
the stalls will be essentially in a solid storage.
These systems are generally characterized by large concrete lined tanks
built into the ground. Waste is stored in the tank for six or more months
until it can be applied to fields. To facilitate handling as a liquid, water
usually must be added to the manure, reducing its total solids
concentration to less than 12 percent. Slurry systems may or may not
require addition of water.
Anaerobic lagoon systems are generally characterized by automated flush
systems that use water to transport the waste to treatment lagoons that
are usually greater than six feet deep. The waste resides in the lagoon for
periods ranging from 30 days to over 200 days depending on the lagoon
28
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design and other local conditions. The water from the lagoon is often
recycled as flush water. Periodically the lagoon water may be used for
irrigation on fields with the treated waste providing fertilizer value.
PIT STORAGE Liquid swine manure may be stored in a pit while awaiting final disposal.
The pits are often constructed beneath the swine building. The length of
storage time varies, and for this analysis is divided into two categories:
less than one month or greater than one month.
ANAEROBIC DIGESTER The manure, in liquid or slurry form, may be placed in an anaerobic
digester for treatment. Although digester designs vary, all have the
objective of producing methane for energy and reducing the volume of the
waste. The amount of usable methane produced depends on the
operating characteristics of the digester and the characteristics of the
waste. The digester effluent is often used as a fertilizer.
BURNED FOR FUEL Manure is collected and dried in cakes and burned for heating or cooking.
This system is common in Asia and the Far East; in India it is estimated
that two-thirds of cattle manure is burned for fuel (NCAER 1965).
METHANE CONVERSION FACTORS (MCFs)
The extent to which the maximum methane producing capacity (BJ is realized for a given
animal waste management system must be known to determine the amount of methane that can
be emitted. This fraction is defined as the Methane Conversion Factor (MCF) for the waste
system. For example, a waste system that produces no methane emissions would have an MCF
of 0. A waste system that achieves the full potential methane emissions would have an MCF
of1.
To assess the MCF values for the wide range of animal waste management systems
defined in the previous section, three broad classifications of animal waste handling systems can
be defined based on the total solids content of the waste:
• Solid systems have a total solids content greater than about 20 percent.
• Slurry systems have a total solids content between 10 to 20 percent.
• Liquid systems have a total solids content less than about 10 percent.
Waste as excreted may have a total solids content from 9 to 30 percent (Taiganides
1987). This solids content may be modified by adding an absorbent bedding material to increase
the total solids content for easier handling. Alternately, water may be added to lower the total
solids to allow for liquid transport and handling.
These classifications of systems are particularly important to the potential for methane
production from the manure. Liquid and slurry systems will typically cause anaerobic conditions
to develop, which result in methane production. The solid systems limit the development of
anaerobic conditions and, thus, limit the amount of methane that is produced from the manure.
29
-------
11: IfliTHAN!
10
15
20
25
30
100
X TOTAL SO.IDS
METWNE PRODUCTION
DESCRIPTION
FARM MANAGEMENT
VARIABLES
• HIGH POTENTIAL
LOW POTENTIAL
WATER ACCED
AS DEFECATB3
BEDDtNG ADDED
LIQUID MANURE
HANDLING SYSTEMS
SLURRY MANURE
HANDLING SYSTEMS
SOLID MANURE
HANDLING SYSTEMS
Exhibit 11 illustrates the methane producing potential by waste management system
classification.
With this general framework as the background, literature was reviewed to investigate the
appropriate range of MCF values for the waste management systems in use throughout the
world. Although some data were available, MCF values were estimated for most systems as
shown in Exhibit 12. As anticipated, the solid waste management systems were assigned
relatively low MCF values, while the liquid systems received higher values. The highest value,
90 percent, was adopted for lagoons based on the authors' extensive experience with methane
production by lagoons. The most uncertain value is for pasture and range systems. The
following is a summary of the key factors affecting the choice of the MCFs:
PASTURE/RANGE
DAILY SPREAD
The manure will typically dry out and only a minimum amount of anaerobic
activity can be expected. Chen et al. (1988) indicate that about 11 percent
of the methane producing potential of the manure is lost during the drying
process. An MCF of 10 percent is adopted.
The daily spreading process speeds up the drying of the manure, as
compared to drying on pasture, and drastically limits the methane
30
-------
:... - ••• £)91J^T 12fc , MEt RANI C^vifiSiOli ^ACTORS* Wltift
Animal Waste System
Pasture/Range8
Daily spread*
Solid storage8
Drylot8
Deep pit stacking*
Litter*
Paddock*
Liquid/slurry storage*
Anaerobic lagoon*
Pit storage, less than one month*
Pit storage, more than one month*
Anaerobic Digester (Chinese)
Anaerobic Digester (Indian)
Burned for Fuel
* Authors' estimate; no data available in the literature.
8 Based on Chen et al. (1988).
f
FOR WASTE SYSTEMS
MCF
10%
5%
10%
10%
5%
10%
10%
20%
90%
10%
20%
14%
5%
5% to 10%
producing potential of the manure.15 An MCF of 5 percent is adopted.
SOLID STORAGE Large bulk storage of waste may lead to the formation of anaerobic
conditions. The moisture content of the waste will affect methane
production. The manure in this system is assumed to have the same
methane producing potential as manure lying on pasture, 10 percent.
DRYLOT This manure is subject to about the same limited conditions for methane
production as waste on pasture. Therefore, an MCF of 10 percent is
assumed.
DEEP PIT STACKS Although this manure may only be removed once a year, it is generally
very dry. Therefore, an MCF of 5 percent is assumed.
LITTER This manure will not generally be as dry as with deep pits, but will still be
in solid form with a limited methane production potential. An MCF of 10
percent is assumed.
15 It has been suggested that excessive application of manure on land can induce anaerobic conditions in the soil
which may lead to methane emissions. In this case, the MCF for daily spread and possibly for pasture/range systems
may be considerably higher than the values assumed in this analysis.
31
-------
PADDOCK
LIQUID/SLURRY
ANAEROBIC LAGOON
This manure will be essentially the same as on pasture or a drylot and,
thus, will have the same potential for methane production as those
systems. The manure left in the stalls will be essentially the same as in a
solid storage. An MCF value of 10 percent is therefore adopted.
When waste is managed as a liquid or slurry, the methane producing
potential is enhanced because anaerobic conditions will likely form. When
the storage facility is sufficiently deep the conditions may be almost
entirely anaerobic, thereby maximizing the methane production potential
of the manure. For these systems temperature may be an important
process limiting factor, along with residence time in storage. An MCF
value of 20 percent is assumed, although higher values may be observed
in some cases.
Anaerobic lagoons are specifically designed to create anaerobic conditions
as the means of treating the waste. Typically, almost all of the methane
production potential of the waste will be realized in the anaerobic lagoon,
assuming proper design and operation.16 An MCF of 90 percent is
used.
PIT STORAGE
The amount of methane production from pits will depend on the residence
time of the waste in the pit. Because the waste is generally handled as a
liquid, anaerobic conditions form, causing methane production to be
enhanced. Short storage times, less than one month, are assumed to
have an MCF of 10 percent. When storage times exceed one month, an
MCF of 20 percent is assumed.
ANAEROBIC DIGESTER Theoretically, all of the methane produced in a digester will be used as fuel
(combusted). In practice, typical digesters used in developing countries
are subject to numerous problems particularly from leakage (Smil 1984).
Yancun et al. (1985) showed that typical Chinese digesters leaked at least
14 percent of the methane they produced. An MCF of 14 percent is used
for Chinese digesters. No data were found in the literature on leakage
from Indian digesters; but, the typical floating cover digester used in India
(Stuckey 1984 and Lichtman 1983) do not appear to be as leak prone as
the Chinese digesters. An MCF of 5 percent was assumed for Indian
digesters.
BURNED FOR FUEL
When manure is collected and dried in cakes for use as a fuel, methane
may be released during the drying process. The MCF value will depend
on the rate of drying and is assumed to range from 5 to 10 percent
depending on the climate. Methane emissions associated with the
combustion of the waste itself are not considered in this analysis.
16
It is possible to cover these lagoons and harvest methane gas that is evolved for its energy potential (Chandler
et al. 1983 and Safley and Westerman 1988).
32
-------
The assumed MCF values strongly influence estimated emissions. The MCF values,
however, are based on limited data, especially for developing countries. The U.S. Environmental
Protection Agency is sponsoring research to improve the MCF estimates for several key animal
waste systems for which limited emissions data exist. This research will validate many of the
MCF estimates used in this report.
CUMATE ADJUSTMENT FACTORS (CAFs)
Despite similarities in the waste management systems, the methane producing potential
for areas outside the United States may vary due to differences in climate conditions. In this
analysis, climate conditions were considered using a climate adjustment factor (CAF) based on
the temperature and precipitation prevailing in a country. Significant effects from precipitation
are limited to dry waste handling systems where the manure will dry much slower or much faster
than normal due to moisture extremes. Temperature extremes could potentially affect most
systems by enhancing anaerobic digestion at high temperatures or by inhibiting anaerobic
digestion at low temperatures. Stevens and Schulte (1977) found reports of methanogenesis in
the literature at temperatures as low as 4°C. Apparently anaerobic digestion is inhibited below
4°C. Stevens and Schulte (1977) also found that the rate of methanogenesis dramatically
increases as the temperature increases from 4°C to 25°C.
The following climate adjustment factors (CAF) were defined to adjust the realized
methane producing potential to reflect the impact of climate conditions:
• No adjustments were made to the methane potential of the waste in warm or
tropical countries. The CAF for these countries equals 1.
• The dryness and low rainfall of arid and semiarid regions were assumed to reduce
by 50 percent the emission potential for pasture and related systems such as
drylot, solid storage, and paddock. The CAF for these systems in arid/semiarid
regions was assumed to be 0.5.
• The areas with very cold winter temperatures were considered to reduce the
methane producing potential of the waste for all systems by 20 percent when
averaged over the whole year. The CAF for these systems was assumed to
be 0.8.
Exhibit 13 summarizes the climate adjust factors used. Any country not listed in Exhibit
13 has a CAF of 1. The countries listed in Exhibit 13 have either very dry or very cold climates.
The countries designated as arid or semiarid or with very cold winter were defined according to
climatic region maps in Goode's World Atlas (1986). Animal population maps in Goode's
World Atlas (1986) were also used to distinguish the few countries where the sheep population
is largely in arid regions while the cattle population is largely in moist parts of the country. For
the countries where this disparity exists between the sheep and cattle populations, all other
animal types were taken to be largely in the arid region.
Countries in Exhibit 13 with very cold winters were designated based on January normal
temperature maps in Goode's World Atlas (1986). A country was defined as very cold if the
33
-------
EXHIBIT 13: COUNTRIES CONSIDERED CLIMATIC EXCEPTIONS {ARID/SEMIARID AND 't.
- ' * *-,\ - - % fcQLdi mn SutiAii A*uu$tM£Nt rA<#0& &rautie» . , ;:- ' '.- - r •
Country
Afghanistan
Algeria8
Australia8
Botswana
Burkina Faso
Canada
Chad
Czechoslovakia
Egypt0
Ethiopia
Finland
Hungary
Iran
Iraq0
Jordan
Kenya
Lybia
Mali
Mauritania
Climate
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Very Cold Winter
Arid/Semiarid
Very Cold Winter
Arid/Semiarid
Arid/Semiarid
Very Cold Winter
Very Cold Winter
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
A Climate Adjustment Factor: 0 &
B Sheep are
C Major river
s -. :ss
CAFA
0.5
0.5
0.5
0.5
0.5
0.8
0.5
0.8
0.5
0.5
0.8
0.8
0.5
0.5
0.5
0.5
0.5
0.5
0.5
Country
Mongolia
Namibia
Niger
Norway
Oman
Pakistan
Poland
Romania
Saudi Arabia
Somalia
South Africa8
Soviet Union
Sudan
Sweden
Syria
Tunisia
UAE
Yemen Arab Rep
CAF & 1.
' -f f
Climate
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Very Cold Winter
Arid/Semiarid
Arid/Semiarid
Very Cold Winter
Very Cold Winter
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Very Cold Winter
Arid/Semiarid
Very Cold Winter
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
Arid/Semiarid
.,.:..:•.•
-------
EXHIBIT
NORTH AMERICA:
WESTERN EUROPE:
EASTERN EUROPE:
OCEANIA:
LATIN AMERICA:
AFRICA:
East & Subsaharan Africa:
West & Southern Africa:
NEAR EAST & MEDITERRANEAN:
ASIA & FAR EAST:
"Canada, "United States
Austria, "Belgium/Luxembourg, 'Denmark, "Finland,
France, Germany (Western), Greece, "Ireland, "Italy,
"Netherlands, "Norway, Portugal, Spain, "Sweden,
"Switzerland, United Kingdom.
Albania, Bulgaria, "Czech and Slovak Federal Republics,
Germany (Eastern), 'Hungary, Poland, Romania, Soviet
Union (B), Yugoslavia.
*Australia, Fiji(A), New Caledonia, New Zealand, Papua
New Guinea(A), Vanuatu(A).
Argentina, Bolivia, Brazil, "Chile, Columbia, Costa Rica,
Cuba, Dominican Republic, Ecuador, El Salvador,
"Guatemala, "Guyana, Haiti, Honduras, Jamaica, Mexico,
Nicaragua, Panama, Paraguay, Peru, Puerto Rico (C),
Uruguay, Venezuela.
Burundi, Central African Republic, Chad, "Ethiopia,
Kenya, "Mali, Mauritania, Niger, Rwanda, Somalia,
Tanzania, Uganda, Zaire.
Angola, Benin, Botswana, Burkina Faso, Cameroon, C6te
d'lvoire, The Gambia, Ghana, "Guinea, Guinea-Bissau,
Lesotho, Madagascar, "Malawi, Mozambique, "Namibia,
Nigeria, Senegal, Sierra Leone, "South Africa, Swaziland,
Togo, Zambia, Zimbabwe.
Afghanistan, Algeria, Egypt(A), Iran, lraq(A), Israel,
Jordan, Kuwait, Libya, Morocco, Oman, Saudi Arabia,
Sudan, Syria, Tunisia, Turkey, Yemen Arab Republic.
Bangladesh, Bhutan, China, "India, "Indonesia,
*Japan(A), Kampuchea, Myanmar(Burma), North Korea,
South Korea, Laos, Malaysia, Mongolia, Nepal, "Pakistan,
"Philippines, Sri Lanka, Thailand, Viet Nam.
(A) Major exception to the region. (B) As defined before August 1991.
(C) Considered separately from the U.S. for this analysis.
* Supplied estimate of AWMS usage.
35
-------
studied to a manageable size, cattle populations were used as a criterion to select those
countries with sufficiently large livestock populations to make significant contributions to the
world total. Only those countries with 100,000 or more head of cattle (according to FAO 1989)
were retained in the study. Exhibit 14 lists 128 countries that meet this criterion out of
approximately 212 countries listed in the 1988 FAO Production Yearbook (FAO 1989).
Detailed data on waste management system usage were collected for the United States
and selected other countries. Animal waste management system usage in the United States was
determined by obtaining information from Extension Service personnel in each state. For the
other countries listed in Exhibit 14 animal waste system usage was determined by contacting the
Ministry of Agriculture in each country. In addition, individual researchers in many countries were
contacted to provide information. U.S. states or countries that did not supply estimates were
assumed to have waste systems similar to other countries in their region (see below). Appendix
F lists the information requested from each U.S. state and from each country of the world.
As discussed above, for countries that did not supply waste system usage estimates, a
regional average system usage was assumed. These regional averages were then adjusted
based on per capita gross national product (GNP) of the country. Exhibit 15 lists the
countries that were analyzed in this manner and their GNP. Adjustments were made by
weighting poorer countries toward more traditional labor intensive waste systems than those
used by the affluent countries. Only relatively small differences in system usage were assumed
between the adjacent per capita GNP levels for countries in the same region. In general, each
level of income was assumed to make about a 10 to 15 percent difference in the amount of solid
handled manure as compared to liquid handled manure.
The following sections describe the estimated waste management system usage by
region. Appendix H presents detailed estimates of waste system for the U.S. by state and animal,
and Appendix I presents the same information for the rest of the world.
North America
The U.S. was divided into eleven geographic regions based on similarities of climate and
livestock production as shown in Exhibit 16. For states that did not provide information, the
regional average waste system usage was assumed. Some states did not give data for all animal
types and the regional average was used in these cases. A similar process was followed for
Canada. Waste system usage information was obtained for each province except Newfoundland,
Prince Edward Island, and Saskatchewan. The system usage for these provinces is based on
Patni (1989).
Exhibit 17 lists the percentage of waste managed by the major systems in North America.
The important waste management characteristics of this region are:
• Approximately one-third of dairy waste is managed as a liquid and approximately
one-third is spread directly to cropland.
17 Miner (1989) and Ward (1989) observed that animal waste management practices around the world are
correlated with personal income.
36
-------
Region
Western Europe
Eastern Europe
Oceania
Latin America
Near East &
Mediterranean
Asia and Far East
A See Exhibit 14
Source: Goode's
' •" .. ' fm j f •.-.-.
< $1,600
Albania
Fiji
Papua New Guinea
Vanuatu
All Other
CountriesA
Afghanistan
Egypt
Morocco
Sudan
Tunisia
Turkey
Yemen Arab
Republic
All Other
CountriesA
ISS NATIONAL PI
$1,600 -$3,200
Portugal
Hungary
Yugoslavia
Argentina
Brazil
Chile
Ecuador
Mexico
Algeria
Iran
Iraq
Jordan
Kuwait
Syria
South Korea
Malaysia
B As defined before August 1991.
World Atlas (1986).
_ 'jj
f ^ ''*"' *"
$3,200 - $6,400 >$6,400
Ireland
Spain
Bulgaria
Poland
Romania
Soviet Union8
Uruguay
Venezuela
Panama
Isreal
Oman
C Considered
U.S. for this
All Other
Countries*
Czechoslovakia
Eastern
Germany
Australia
New Caledonia
New Zealand
Puerto Ricoc
Libya
Saudi Arabia
Japan
separately from the
analysis.
• Seventy-five percent of swine waste is managed as a liquid.
• Poultry waste is primarily managed by deep pit stacking or litter and is included
in "other systems" in Exhibit 17.
Western Europe
Western Europe is a developed region with slightly fewer cattle than in North America, but
with more than twice as many swine. There is no specialization of either dairy of beef
production; cattle are used first for milking and then slaughtered for beef. Swine and poultry
generally are raised in confinement.
In many parts of Europe, environmental concerns over ground and surface water pollution
and odor emission have affected the management of animal wastes. Odor emissions from animal
37
-------
iXHlBlf
.$. ?OR WASTE MANAOEMENT CHABACTEFHZATfO^
North East
South East
Plains
South
South West
Mid West
North West
Far West
Pacific West
North Pacific
Pacific Islands
Connecticut, Maine, Massachusetts, *New Hampshire, New Jersey, *New
York, Pennsylvania, Rhode Island, Vermont.
*Delaware, *Florida, *Georgia, Maryland, *North Carolina, *South Carolina,
*Virginia, *West Virginia.
*Colorado, *Kansas, 'Montana, *Nebraska, *North Dakota, *South Dakota,
Wyoming.
*Alabama, *Arkansas, Kentucky, Louisiana, *Mississippi, *Tennessee
*New Mexico, *Oklahoma, *Texas.
*lllinois, *lndiana, Michigan, *Ohio, *Wisconsin, *lowa, *Minnesota,
*Missouri.
*ldaho, *Oregon, *Washington
*Arizona, Nevada, *Utah
*California
* Alaska
*Hawaii
States that have supplied estimates of their percent use of waste management systems.
confinement facilities and from the spreading of manure on cropland have become a major
problem in the last two decades, especially in the north (Hartung 1984). Mandatory storage
covers are being considered in northern Europe to control odor (Manneback 1986).
These problems are compounded in many areas because there is not enough cropland
available for spreading the manure. Manure spreading is prohibited during the winter to avoid
ground and surface water contamination. During the winter manure must be stored for three to
six months until it can be spread on fields during the summer (Csoma 1981; O'Rourke 1989).
Exhibit 18 lists the percentage of waste managed by the major systems in Western
Europe. The key characteristics are:
38
-------
••••"V -i\;, -' Effiii&T'i1^ AHay^t»Aft*is <
,. O {* % " « SS^SWSWM 1. 1 f » % MK$HnnibJ: WMp J 15 <
Anaerobic Liquid
Animal Lagoons SystemsA
Non-Dairy Cattle0 o% 1%
Dairy 10% 23%
PoultryE 5% 4%
Sheep 0% o%
Swine 25% 50%
Other AnimalsF o% 0%
A Includes liquid/slurry storage and pit storage.
B Includes anaerobic digesters and burned for fuel.
c Includes deep pit stacks, litter, and other.
ttyftttJiuf il**&&P irrtsi wrtRTW AUfntf*
frlsMJBWI- WWVSrifwrl^lil'iJff frl jfW9t;rl«<»
Solid Pasture, Used
Daily Storage Range & for
Spread & Drylot Paddock Fuel8
0% 14% 84% 0%
37% 23% 0% 0%
0% 0% 1% 0%
0% 2% 88% 0%
0% 18% 0% 0%
0% 0% 92% 0%
D Includes buffalo.
E Includes chickens, turkeys, and ducks.
F Includes goats, horses, mules, donkeys, and
*
Hk
Other
Systems0
1%
7%
90%
10%
6%
8%
camels.
• Over seventy-five percent of swine manure is managed in lagoons and liquid
systems.
• Most non-dairy cattle waste is deposited in pastures.
• One-third of dairy waste is handled as a liquid with most of the remainder spread
directly on fields or stored as a solid.
Eastern Europe
Eastern Europe is classified as a developed region, with livestock grown in confinement
in most of the region. A large portion of manure is handled as a solid. In some areas, municipal
type waste treatment facilities are used to treat manure from confinement facilities. Manure
managed in this manner requires liquid handling. As in other parts of the world, the less affluent
countries utilize more labor intensive solid waste handling systems and the more affluent
countries utilize liquid systems. For example, Czechoslovakia is a relatively affluent country
where all swine and most poultry manure is handled as a liquid.
Exhibit 19 lists the percentage of waste handled by the major waste systems in Eastern
Europe. The key waste management characteristics are:
• About 25 to 45 percent of non-dairy cattle, poultry, and swine wastes are
managed in lagoons or other liquid systems.
• Most dairy waste is managed as a solid and only about 20 percent is managed
as a liquid.
• Very little waste is spread directly to crops.
39
-------
EXHIBIT 18; ANIM
Anaerobic
Animal Lagoons
Non-Dairy Cattle0 0%
Dairy 0%
PoultryE 0%
Sheep 0%
Swine 0%
Other AnimalsF 0%
At WASTES
Liquid
SystemsA
55%
46%
13%
0%
77%
0%
Includes liquid/slurry storage and pit storage.
Includes anaerobic digesters and burned for fuel.
c Includes deep pit stacks, litter, and other.
VStHUI tJ&fi.<££ *#l
Solid
Daily Storage
Spread & Drylot
0% 2%
24% 21%
0% 1%
0% 2%
0% 23%
0% 0%
Pasture,
Range &
Paddock
33%
8%
2%
87%
0%
96%
.UROI
Used
for
Fuel8
0%
0%
0%
0%
0%
0%
0 Includes buffalo.
E Includes chickens, turkeys, and ducks.
F Includes goats, horses, mules, donkeys, and
£p^/.£$P
j _. _.^ '_.,"'
Other
Systems0
9%
1%
84%
11%
0%
4%
camels.
Oceania
The majority of livestock in Oceania are in the developed countries of Australia and New
Zealand. Overall the region does not contain significant numbers of animals except for sheep,
which in Australia and New Zealand account for about 20 percent of the world total. Although
the region is largely developed, there is little confinement of livestock (Ward 1989). Swine
operations are an exception where a large fraction of the waste is managed in anaerobic
lagoons.
Exhibit 20 lists the percentage of waste managed by each of the major waste systems in
Oceania. The primary characteristics are:
• Almost all waste is managed on pastures and range.
• Over half of the swine waste is managed in anaerobic lagoons.
• Animal waste is not spread directly to cropland.
Latin America
Latin America is a developing region with approximately one-third of the world cattle
population and one-fifth of the swine population. Cattle are not specialized and supply draft
power, milk, and meat. The only exception are the large beef herds in Argentina and Brazil.
Most cattle waste in the region is deposited on pasture or range (Ward 1989; Getz 1989). Swine
production is largely limited to small family holdings without any concentrated manure
40
-------
^% vXi, •• ^ ••'"
Animal
Non-Dairy Cattle0
Dairy
PouttryE
Sheep
Swine
Other AnimalsF
T 19: ANIM,
Anaerobic
Lagoons
8%
0%
0%
0%
0%
0%
(VLWASTiJ
Liquid
Systems*
39%
18%
28%
0%
29%
0%
Includes liquid/slurry storage and pit storage.
B Includes anaerobic digesters and burned for fuel.
c Includes deep pit stacks, litter, and other.
jyslEMUS
Daily
Spread
0%
1%
0%
0%
0%
0%
AGEFO
Solid
Storage
& Drylot
52%
67%
0%
0%
0%
0%
R EASTERN
Pasture,
Range &
Paddock
0%
13%
1%
73%
27%
92%
EUROPE
Used
for
Fuel8
0%
0%
0%
0%
0%
0%
-
Other
Systems0
1%
0%
71%
27%
45%
8%
° Includes buffalo.
E Includes chickens, turkeys, and ducks.
Includes goats, horses, mules, donkeys, and camels.
management. Brazil and Mexico are exceptions with some swine waste managed as a liquid.
Unlike cattle and swine, poultry are raised in confinement (Grove 1989) and Western style waste
treatment systems are found, including anaerobic lagoons (Getz 1989).
Exhibit 21 lists the percentage of waste managed by the major systems in Latin America.
The key characteristics are:
• Except for poultry and swine, almost all animal waste is deposited on pastures or
range.
• Almost 50 percent of poultry waste is managed as litter or in deep pit stacks and
about 10 percent is managed as a liquid.
Half of swine waste is managed as a solid and 10 percent is managed as a liquid.
• Animal manure is generally not used for fuel.
Africa
Africa is a developing region with little livestock confinement (Peters 1989). Most cattle
are multi-purpose and there are few specialized dairies. Most livestock graze on communal
pastures and with little waste management. In part this results from an aversion to direct
handling of manure in many parts of Africa. In some areas, however, manure is spread on
cropland for its fertilizer value. South Africa is a major exception to the region with a large
number of specialized feedlot beef and dairy cattle and confined swine production. Most cattle
and swine waste in South Africa is stored as a solid or spread directly to cropland (Cloete 1989).
41
-------
, , EXHIBIT mi ANIMAL WASTE SYSTEM U$A6i FOR OCEANIA ', >', - -
Anaerobic Liquid
Animal Lagoons Systems*
Non-Dairy Cattle0 0% 0%
Dairy 0% 0%
Poultry5 0% 0%
Sheep 0% 0%
Swine 55% 0%
Other AnimalsF 0% 0%
Includes liquid/slurry storage and pit storage.
8 Includes anaerobic digesters and burned for fuel.
c Includes deep pit stacks, litter, and other.
Solid Pasture, Used
Daily Storage Range & for
Spread & Drylot Paddock Fuel6
0% 0% 100% 0%
0% 0% 100% 0%
0% 0% 3% 0%
0% 0% 100% 0%
0% 17% 0% 0%
0% 0% 100% 0%
0 Includes buffalo.
E Includes chickens, turkeys, and ducks.
F Includes goats, horses, mules, donkeys, and
Other
Systems0
0%
0%
98%
0%
28%
0%
camels.
Exhibit 22 lists the percentage of waste managed by the major systems in Africa. The key
characteristics are:
• Except for swine, almost all waste is deposited on pastures and range.
• Between 5 and 10 percent of swine waste is managed as a liquid.
• Manure is not used for fuel.
Near East and Mediterranean
The Near East and Mediterranean is a largely developing arid region with about 5 percent
of the world cattle population and virtually no swine population. The cattle are mostly on range
throughout the region; although, there is some drying and burning of the manure for fuel (Get
1990). The few swine in the region are usually on drylot and a few on liquid/slurry storage
systems. Three-quarters of the poultry are on range while most the remainder are on litter
systems (Getz 1990).
The major exceptions in this region are the fertile valleys of the Nile, Tigris, and Euphrates
rivers. The land is generally irrigated in these areas and about half of the cattle manure is
collected and burned for fuel (Getz 1990). The other half is either kept in solid storage or hauled
and spread on fields (Getz 1990 and Johnson 1989). Most of the cattle and sheep populations
of Egypt are in the Nile river valley, while the majority of Iraq's cattle and sheep populations are
in the valleys of the Tigris and Euphrates rivers (Goode's World Atlas 1986).
Exhibit 23 lists the percentage of waste managed by the major systems in the Near East
and Mediterranean region. The key characteristics are:
42
-------
s <;>?' EXHJBiT>1i;ANJI«/yt;WASTl SYSTEM USAOS fOR tAHN AMERICA
Animal
Non-Dairy
Dairy
PouftryE
Sheep
Swine
Cattle0
Other AnimalsF
A Includes
B Includes
c Includes
Anaerobic
Lagoons
0%
0%
0%
0%
0%
0%
Liquid
Systems*
0%
1%
9%
0%
8%
0%
liquid/slurry storage and pit storage.
anaerobic digesters and burned for fuel.
deep pit stacks, litter, and other.
Daily
Spread
0%
62%
0%
0%
2%
0%
Solid
Storage
& Drylot
0%
1%
0%
0%
51%
0%
Pasture,
Range &
Paddock
99%
36%
42%
100%
0%
99%
Used
for
Fuel6
0%
0%
0%
0%
0%
0%
D Includes buffalo.
E Includes chickens, turkeys, and ducks.
F Includes goats, horses, mules, donkeys, and
Other
Systems0
1%
0%
49%
0%
40%
1%
camels.
Except for swine, almost all animal waste is managed on pastures or range.
One-third of swine waste is managed as a liquid with the remainder managed as
a solid.
Almost twenty percent of the cattle waste is used for fuel.
Asia and the Far East
Asia and the Far East is a developing region with few livestock confinement facilities and
little concentrated manure production. Cattle and most other livestock are generally graze in the
region. However, there is a measure of confinement when the animals are tethered near the
house in family farming operations with one to five animals. Approximately 80 percent of the
livestock in the region are in small mixed farming operations (Getz 1989). When these animals
are confined, the manure is removed occasionally using baskets, often along with earth or some
not too absorptive bedding such as feed residue, and spread in solid form. Numerous countries
in the region use animal manures as their primary source of fertilizer for a variety of crops,
including rice (FIAPA1988). Because commercial fertilizers are very costly throughout the region,
in many instances the fertilizer value of the manure is the major reason for keeping the animals
when they would otherwise be past a useful age (McDowell 1977)
A second important use for collected manure in Asia and the Far East is burning for fuel.
In these cases the manure is dried in cakes and used for heating or cooking. In India, it is
estimated that 66 percent of the cattle manure is burned for fuel (NCAER 1965). In Bangladesh,
acute fuel shortages throughout the country also lead to most cattle manure being burned for
fuel (RAPA 1988).
43
-------
:' '" ^ EKHpiT^jfA&lll^r^^
Anaerobic Liquid
Animal Lagoons SystemsA
Non-Dairy Cattle0 0% 0%
Dairy 0% 0%
Poultry5 0% 0%
Sheep 0% 0%
Swine 0% 7%
Other AnimalsF 0% 0%
Includes liquid/slurry storage and pit storage.
B Includes anaerobic digesters and burned for fuel.
c Includes deep pit stacks, litter, and other.
Solid
Daily Storage
Spread & Drylot
1% 3%
12% 0%
0% 0%
0% 1%
0% 93%
0% 0%
Pasture, Used
Range & for
Paddock Fuel8
96% 0%
83% 0%
81% 0%
99% 0%
0% 0%
99% 0%
Other
Systems0
0%
5%
19%
1%
0%
1%
0 Includes buffalo.
E Includes chickens, turkeys, and ducks.
F Includes goats, horses, mules, donkeys, and camels.
In an effort to make this use cleaner and more efficient, and to retain the fertilizer value
of the manure, many countries in the region are turning to biogas production as shown in Exhibit
24. Small family-size anaerobic digesters are often used, primarily in rural areas of China and
India. Seven million small biogas digesters have been constructed in China (Smil 1984) with
about 4.5 million of them still in operation in 1986 (RAPA1987). Between one-half and one-third
of these work as reasonably reliable energy generators (Smil 1984), with gas leaks being the
major cause of poor operation.
Japan is a major exception to the region, although its cattle population accounts for only
about one percent of the region's cattle population. Japan is a developed country with intensive
livestock production and waste management. With farm land scarce, most livestock are grown
in confinement and land area is not adequate for spreading the manure. The waste systems
utilized are similar to those in the U.S. and Western Europe (Minagawa 1989). About one-third
of the dairy cattle waste in Japan is handled by daily spread. Most of the remaining dairy waste
is kept in solid storage with only a fraction handled in liquid form. Almost 90 percent of beef
cattle are in confinement with about one-third of the animals on anaerobic lagoons and most of
the rest on drylot. About half of the swine waste is in solid storage, one-third is handled with
anaerobic lagoons, and the rest is usually spread on fields. Most of the poultry waste from layers
is in deep pit stacking while most broiler waste is treated with anaerobic lagoons.
Exhibit 25 lists the percentage of waste managed by the major systems in Asia and the
Far East: The key characteristics are:
Between 40 and 50 percent of cattle waste is used for fuel.
• Forty percent of swine waste is managed in liquid systems.
Six percent of dairy waste is managed in anaerobic lagoons, almost entirely in
Japan. '
44
-------
\ jafetfeKrafe A&HMAL WASTE mm U&&E FOB NEAR EAST AND MEDITERRANEAN
Animal
Non-Dairy Cattle0
Dairy
Poultry6
Sheep
Swine
Other AnimalsF
Anaerobic
Lagoons
0%
0%
0%
0%
0%
0%
Liquid
Systems*
0%
0%
1%
0%
32%
0%
Includes liquid/slurry storage and pit storage.
B Includes anaerobic digesters and burned for fuel.
c Includes deep pit stacks, litter, and other.
Daily
Spread
2%
3%
0%
0%
0%
0%
D Includes
E Includes
F Includes
Solid
Storage
& Drylot
0%
3%
0%
0%
68%
0%
Pasture,
Range &
Paddock
77%
77%
71%
100%
0%
100%
Used
for
Fuel8
18%
18%
0%
0%
0%
0%
buffalo.
chickens, turkeys, and ducks.
goats, horses, mules, donkeys, and
Other
Systems0
2%
0%
28%
0%
0%
0%
camels.
% %
^ iXHiBirs
Country
ChinaA-c
lndiaA-c
North KoreaA
South KoreaA
Thailand^0
PakistanA'c
Brazil8
Nepal8-0
Taiwan8
A As of 1986
B As of 1984
C Assuming that 75
4: USE OF BlOGAS DIGESTERS IN
Number Built
7,000,000
700,000
50,000
31,405
7,500
4,000
3,033
1,600
>1,000
percent of built
Number in Use
4,500,000
525,000
37,500
11,470
5,625
3,000
1,820
1,200
Not Available
DEVELOPING OOdWTBliS;, '
References
Smil (1984), Stuckey (1984),RAPA
(1987)
Moulik et al. (1984), RAPA (1987)
RAPA(1987)
Stuckey (1984), RAPA (1987)
Chantavorapap (1984), RAPA (1987)
RAPA (1987)
Caceres & Chiliquinga (1 984)
Gorkhali (1984)
Stuckey (1984)
digesters are still in use.
45
-------
:-\ «xMr?^:^i^ir^rm$?
Anaerobic Liquid
Animal Lagoons Systems*
Non-Dairy Cattle0 0% 0%
Dairy 6% 4%
PoultryE 1% 2%
Sheep 0% 0%
Swine 1% 38%
Other AnimalsF 0% 0%
Includes liquid/slurry storage and pit storage.
Includes anaerobic digesters and burned for fuel.
0 Includes deep pit stacks, litter, and other.
vi&reu'i t^A/MF Win i«ik''A«n. i
Solid Pasture,
Daily Storage Range &
Spread & Drylot Paddock
16% 14% 29%
21% 0% 24%
0% 0% 44%
0% 0% 83%
1% 53% 0%
0% 0% 95%
Used
for
Fuel8
40%
46%
1%
0%
7%
0%
D Includes buffalo.
E Includes chickens, turkeys, and ducks.
F Includes goats, horses, mules, donkeys, and
\^ ' ,"',f-,-;
k$T -; - ^ --fc
Other
Systems0
0%
0%
52%
17%
0%
5%
camels.
46
-------
CHAPTER 4. ANIMAL WASTE EMISSIONS ESTIMATES
This chapter presents estimates of global methane emissions from the anaerobic
decomposition of animal waste. Emission estimates are presented for the U.S. and world by
animal and waste system using the previously described data on volatile solids (VS) production,
maximum methane producing capacity (B^, waste system definitions, methane conversion
factors (MCFs), climate adjustment factors (CAFs), and waste system usage (WS%). In addition,
"high" and "low" case emissions estimates are presented to indicate the uncertainty of the point
estimates.
This report estimates that global methane emissions from animal waste are about 28 Tg/yr
with a range of about 20 to 35 Tg/yr, or about 6 to 10 percent of total annual anthropogenic
emissions. The major findings of this report are that:
• Of the 28 Tg/yr, liquid animal waste management systems (liquid/slurry storage
and anaerobic lagoons) account for over 10 Tg/yr, or about 35 percent of total
emissions from animal waste. These systems are used at confined, energy
intensive livestock operations and may provide profitable opportunities to recover
methane for use as a fuel.
• Of the 28 Tg/yr, three regions account for about 22 Tg/yr, or about 75 percent of
the total: Europe (East and West); Asia and the Far East; and North America.
• Of the 28 Tg/yr, over 20 Tg are from three animal groups: cattle (beef and draft
animals), dairy cows, and swine.
UNITED STATES EMISSION ESTIMATE
Livestock and poultry wastes in the United States emit 3.9 Tg/yr of methane to the
atmosphere, or about 14 percent of the world's total emissions of about 28 Tg/yr. Exhibit 26
summarizes the contribution of the major animal groups. Of the 3.9 Tg/yr, three animal groups
account for 3.5 Tg/yr or about 90 percent of the total:
• Beef cattle wastes produce 1.4 Tg/yr or about 35 percent of the U.S. total
emissions;
• Swine wastes produce 1.1 Tg/yr or about 30 percent of the U.S. total emissions;
and
• Dairy cattle wastes produce 1.0 Tg/yr or about 25 percent of the U.S. total
emissions.
The contributions of each state are summarized in Exhibits 27 and 28 and full details of the U.S.
emission estimate are in Appendix B.
47
-------
EXHIBIT 26: U.S. METHANE
Animal Type
Cattle in Feedlots
Other Beef Cattle
Dairy Cattle
Swine
Caged Layers
Broilers
Turkeys and Ducks
Sheep
Goats
Horses, Mules, and Donkeys
Total
EMISSIONS FROM ANIMAL WASTE
Population
1 1 ,200,000
78,000,000
14,400,000
55,300,000
355,500,000
951 ,900,000
60,800,000
10,600,000
2,400,000
2,409,000
, / , """ '* /\
Methane
0"g/yr)
0.26
1.11
1.01
1.12
0.11
0.09
0.01
0.03
< 0.01
0.09
3.86
The portions of the U.S. methane emissions from the different animal waste management
systems are shown in Exhibit 29. Of the total 3.9 Tg/yr emissions:
Liquid based systems (anaerobic lagoons plus liquid/slurry storage) account for
1.8 Tg/yr or over 40 percent of total emissions. Because liquid based systems are
often used for confined and energy intensive livestock operations, they provide an
opportunity for emissions reduction by capturing the methane for use as an on-
farm energy source. The U.S. EPA is currently assessing the economic and
technical feasibility of these opportunities in several key U.S. states, including:
Texas, California, Iowa, Illinois, and North Carolina.
Solid based systems (pasture/range, drylots, solid storage, daily spread, and
other) account for 2.1 Tg/yr or about 60 percent of total emissions. Solid based
systems make a large contribution to overall emissions in spite of their low
methane conversion factors (MCFs) because a very large number of animals are
on solid based systems.
The details of the contributions of different systems in the United States are in Appendix G and
Appendix H.
48
-------
(O
-. Js •••. f< '•.
V* ,< a
"• ._ "•
State
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MO
ME
Ml
MN
MO
QQfajft jtftt&bQflji^ IP
"• f -,
-•% ^
Anaerobic
Lagoons
123
41,109
637,693
10,161
203,398
4,630
49
506
7,276
56,452
3,738
25,805
9,318
79,966
64,206
35,245
62,493
8,170
48
5,319
13
38,313
0
184,807
"* "* s
) ^ rf- $S X \
Slurry
Storage
130
463
4,035
0
391
862
1,873
287
285
954
670
6,519
15,031
3,926
11,920
4,188
1,957
0
866
5,324
1,472
11,194
27,046
519
' s <
\°" "~ \ v-
Solid
Storage
2
0
0
0
0
0
9
0
0
0
0
10,103
0
1,010
931
0
0
0
186
274
289
2,153
12,651
0
•• ->f
Drylot
0
416
709
3,944
6,143
11,906
0
18
583
1,449
300
30,940
3.003
8,306
5,163
23,669
990
121
93
200
26
3,467
8,763
3,837
•••I" ^ -. ,
Pasture/
Range
262
26,104
26,762
12,526
50,988
36,259
556
294
30,443
21,035
2,643
58,049
20,977
23,025
14,915
69,610
34,603
16,506
798
3,391
856
10,664
25,452
63,100
•.
f •.-•
Litter
0
10,649
14,436
0
4,436
0
0
3,295
1,867
11,769
34
432
0
72
607
11
41
0
6
3,830
0
150
2,410
1,644
"*?*'• x \ •? j f
•V J'V. f ""JL-. ••"•
Pit
Storage
(<1 month)
0
0
0
0
0
262
0
0
8
0
59
8,376
22
3,147
1,210
0
410
0
4
0
1
300
5,213
0
•.
\ , •- "• f^
Pit
Storage
(>1 month)
0
379
571
0
0
598
0
250
0
1,303
166
59,391
314
28,326
29,043
4,902
117
0
148
759
41
5,843
20,852
0
"SSION!
f fj f'' ff "•
*"•_/._ ''•"'f* Z$
Daily
Spread
1
481
1,265
0
0
1,610
411
123
414
130
18
622
86
2,272
931
1,570
1,604
83
415
1,235
644
4,038
8,434
2,280
*/MEt1
v s _.._!: ••' ""
Deep Pit
Stacking
0
116
0
30
1,465
287
453
75
831
572
2
766
40
286
2,105
175
6
0
80
366
413
513
716
519
v^-J l<
f •. "" ""
/%
-------
EXHIBIT 27; INDIVIDUAL U*S, STATE AND SYSTEM METHANE EMISSIONS
State
Anaerobic
Lagoons
Slurry
Storage
Solid
Storage
Dry lot
Pasture/
Range
Pit Pit
Storage Storage
Litter (<1 month) (>1 month)
(METRIC TQNS/YEAK)
Daily Deep Pit
Spread Stacking Paddock
Other
Total
(continued from previous page)
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
Rl
SC
SD
TN
TX
UT
VA
VT
WA
Wl
WV
WY
OTHER
TOTAL
20,377
1,328
101,841
3,940
74,086
24
62
24,247
221
336
50,978
13,846
21,067
0
8
38,567
38,997
46,913
59,583
777
18,801
9
41,822
0
777
707
0
1,438,149
212
472
4,193
68
489
884
938
45
1,622
16,606
11,856
308
3,582
1,876
80
203
3,682
8,784
20,782
80
11,810
4,745
11,599
27,361
1,041
324
0
233,554
68
271
524
849
0
442
197
0
2,836
4,017
2,321
0
49
1,091
16
102
1,346
0
0
3,597
0
1,062
0
13,589
260
97
0
60,342
324
1,582
2,190
793
29,371
48
156
1,708
395
412
3,270
4,059
1,040
2,939
16
356
5,324
1,106
27,075
712
419
17
2,439
1,814
176
1,255
0
203,044
20,387
41,568
11,392
24,609
64,619
425
1,178
20,699
7,733
8,938
17,748
71,247
20,738
14,951
66
8,630
50,993
31,719
196,350
12,996
23,257
1,499
15,582
23,811
7,745
23,554
296
1 ,272,548
5,469
0
9,714
24
105
1
4
0
0
55
360
1,832
344
2,275
0
1,336
117
1,318
4,035
0
3,422
0
427
198
635
0
3,013
90,375
69
334
0
572
12,029
0
5
15
0
37
124
127
212
53
1
0
2,454
0
478
0
0
1
30
1,442
60
24
0
37,077
249
668
4,327
1,144
2,187
5
192
30
0
896
11,365
0
145
6,335
26
246
4,908
585
637
0
464
28
359
10,093
121
56
0
198,070
34
230
1,311
38
856
110
439
146
203
14,058
4,351
130
123
17,277
36
102
1,010
1,018
1,299
160
976
2,369
570
31,708
195
82
0
107,497
0
66
232
22
354
24
133
50
1
259
1,822
308
205
1,312
16
280
106
5
147
98
118
14
464
186
0
2
0
16,042
405
26
107
349
92
131
291
1,396
127
959
2,570
692
947
1,170
13
301
325
560
0
284
17
95
1,036
257
406
292
0
23,498
3,621
253
2,049
28
3,562
0
69
56
6
660
2,570
16,600
2,061
2,630
4
112
0
7,124
9,534
281
549
21
0
1,751
495
152
609
176,017
51,215
46,799
137,882
32,434
187,750
2,094
3,663
48,393
13,145
47,233
109,334
109,149
50,512
51,910
282
50,233
109,262
99,133
319,920
18,984
59,834
9,859
74,329
112,211
11,912
26,545
3,919
3,857,141
-------
State
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
Ml
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
Rl
SC
SO
TN
TX
UT
VA
VT
WA
Wl
WV
WY
OTHER
Total
EXHIBIT 28:
•. --X-.
Beef
103
26,288
25,521
13,492
49,770
55,699
403
238
29,965
20,388
2,855
63,736
22,096
30,304
17,965
100,827
32,508
15,501
481
2,916
674
13,554
28,125
65,792
19,912
38,261
11,047
24,086
95,972
372
594
19,910
7,289
8,500
20,583
71,590
20,019
14,409
41
8,533
56,028
30,115
209,880
10,626
21,602
1,286
16,722
23,899
57,259
21,308
0
1,379,044
tNDMDUAL U.S. STATE AND ANIMAL METHANE EMISSIONS (MT/YR)
Dairy
318
9,144
8,854
7,527
226,078
4,071
2,293
595
9,196
22,209
2,347
21,760
22,589
13,381
21,413
5,758
26,192
6,451
1,432
7,765
2,221
26,469
46,388
63,844
6,410
2,306
7,864
990
4,867
1,436
1,515
23,856
4,659
34,142
28,523
23,733
23,902
19,823
125
15,034
20,863
20,865
61,046
4,196
12,693
8,170
52,977
72,476
1,836
825
0
1,013,428
Swine
40
15,743
19,143
6,398
5,584
3,937
79
589
2,955
42,614
906
137,057
2,044
108,584
87,128
30,230
43,388
3,182
292
5,122
82
35,580
41,703
121,562
8,033
1,671
97,364
5,529
84,202
78
379
282
274
1,493
54,599
7,350
2,019
8,446
51
20,279
27,978
43,570
13,061
557
19,265
54
1,197
12,256
784
365
0
1,125,080
Sheep &
Goats
99
26
34
1,357
3,404
1,472
50
1
33
51
2
1,373
933
448
433
573
129
65
51
116
51
401
766
463
13
1,818
118
558
409
38
113
1,928
285
262
741
567
1,320
440
1
16
2,069
153
9,858
1,700
406
54
263
271
507
2,323
182
35741
Poultry
2
27,893
30,620
30
13,413
627
455
3,370
5,832
15,415
1,684
1,709
278
943
3,188
186
2,359
2,775
142
4,197
699
1,126
4,079
2,682
15,835
143
20,414
108
459
25
230
555
2
918
2,182
2,449
1,148
6,452
27
5,769
699
2,190
17,704
488
4,138
23
1,098
994
986
3
4,533
213,276
Horses
& Other
67
1,245
1,444
2,532
5,339
2,830
248
109
2,731
1,223
127
2,130
2,014
1,991
1,891
1,996
3,227
1,390
429
952
227
2,040
1,949
2,672
1,012
2,599
1,075
1,163
1,840
145
831
1,862
636
1,918
2,706
3,461
2,103
2,341
37
602
1,626
2,240
8,371
1,418
1,730
272
2,072
2,315
542
1,720
132
87,572
Total
629
80,340
85,616
31,336
303,588
68,635
3,529
4,902
50,711
101,900
7,922
227,765
49,953
155,652
132,018
139,571
107,802
29,363
2,827
21,068
3,953
79,171
123,011
257,015
51,215
46,799
137,882
32,434
187,749
2,094
3,663
48,393
13,145
47,233
109,334
109,149
50,512
51,910
282
50,233
109,262
99,133
319,920
18,984
59,834
9,859
74,329
112,211
11,914
26,545
4,258
3,857,141
51
-------
EXHIBIT 29: U.S. METHANE EMISSIONS FROM WASTE MANAGEMENT SYSTEMS
System Type
Pasture/Range
Anaerobic Lagoon
Liquid/Slurry Storage
Drylot
Solid Storage
Daily Spread
Other
Total
MCF
0.1
0.9
0.2
0.1
0.1
0.05
Emissions fTg/Yr)
1.3
1.4
0.2
0.2
<0.1
0.1
0.6
3.9
WORLD EMISSION ESTIMATE
A summary of worldwide methane emissions from animal waste is shown in Exhibit 30.
Of the total 28 Tg/yr emissions:
• Three animal groups account for 21.2 Tg/yr (75 percent) of the world total: non-
dairy cattle wastes account for 9.5 Tg/yr (33 percent); dairy cattle wastes account
for 5.9 Tg/yr (20 percent); and swine wastes account for 5.8 Tg/yr (20 percent).
• Three regions of the world account for 22 Tg/yr (75 percent) of emissions:
Europe (East and West) contributes 11.4 Tg/yr (40 percent); Asia and the Far East
contributes 6.4 Tg/yr (22 percent); and North America contributes 4.2 Tg/yr
(14 percent).
The contribution of each country is summarized in Exhibit 31 and listed in detail in Appendix E.
The worldwide contribution of different types of waste management systems is shown in
Exhibit 32. Of the total 28.3 Tg/yr emissions:
• Liquid based systems (anaerobic lagoons and liquid/slurry storage) account for
10 Tg/yr or about 35 percent of total worldwide emissions. Other than the U.S.,
these emissions are concentrated in Europe. Like the U.S., opportunities may
exist to reduce emissions by capturing this methane for use as an on-farm energy
source.
Solid based systems (Pasture/Range, solid storage, drylots, daily spread, and
other) account for 17.4 Tg/yr or about 60 percent of total worldwide emissions.
As in the U.S., solid based systems make a large contribution despite their low
MCFs because such a large number of animals are on solid based systems
(primarily pasture/range).
52
-------
i^l^jiy
Animal Type
Cattle
Dairy
Swine
Sheep
Goats
Chicken
Ducks
Turkeys
Buffalo
Horses
Mules
Donkeys
Camels
Total
^j&tei^*
North
America
1.50
1.09
1.23
0.03
<0.01
0.21
<0.01
0.02
0.00
0.10
<0.01
<0.01
0.00
4.19
"ttf<"&*~*i
West
Europe
1.70
1.55
1.08
0.27
0.03
0.12
<0.01
0.02
<0.01
0.06
0.01
0.01
0.00
4.87
-..-•* •• -
East
Europe
2.14
2.03
1.29
0.44
0.02
0.29
<0.01
0.02
<0.01
0.25
<0.01
0.02
<0.01
6.51
ri&N&feii
Oceania
0.54
0.16
0.14
0.44
<0.01
<0.01
0.00
<0.01
0.00
0.01
0.00
0.00
0.00
1.31
_ ,,,,-,,
Latin
America
1.23
0.21
0.24
0.14
0.05
0.20
<0.01
<0.01
<0.01
0.51
0.16
0.11
0.00
2.86
\vtrn
Africa
0.72
0.12
0.04
0.18
0.12
0.08
<0.01
<0.01
0.00
0.05
0.02
0.07
0.08
1.47
siof*$(r<3$
Near East
&Med.
0.12
0.10
<0.01
0.14
0.06
0.07
<0.01
<0.01
0.01
0.04
0.02
0.09
0.03
0.70
fftl
Asia&
Far East
1.49
0.64
1.80
0.22
0.37
0.62
0.06
<0.01
0.52
0.34
0.12
0.21
0.04
6.45
^
Total
9.45
5.91
5.84
1.85
0.66
1.59
0.07
0.07
0.55
1.37
0.33
0.51
0.16
28.3
RANGE OF ESTIMATES
The estimates presented above should be regarded with caution. Some of the data used
to make these estimates are uncertain, in particular:
• Little information is available to assess the methane produced by pasture and
range waste. Because a large fraction of animal waste is managed on pastures
and range, this creates uncertainty in the overall emissions estimate.
• The methane producing potential of liquid/slurry and pit storage waste systems
may be much greater than assumed in this report. Because of the widespread
use of these systems, total emission may be underestimated.
Limited data exist on the numbers and characteristics of animal waste systems in
use in some parts of the world.
At this time, insufficient information exists to provide a statistical confidence limit for the emission
estimates presented above. The greatest uncertainty in the emission estimates results from the
methane conversion factor assumptions for the various waste management systems.
53
-------
EXHIBITS: GLOBAL METHANE
Country
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
OCEANIA
Australia
Fiji
New Caledonia
New Zealand
Papua New Guinea
Vanuatu
Total
Non-Dairy
Cattle
116,029
1,379,044
1,495,073
46,213
60,825
25,733
17,841
396,733
276,150
15,067
103,325
191,188
83,645
17,336
22,058
80,202
33,716
37,014
297,421
1 ,704,467
9,269
25,139
107,697
138,350
18,286
102,360
108,081
1,574,132
55,444
2,138,758
418,177
589
2,439
121,308
449
476
543,438
Dairy
81,332
1,013,428 1
1 ,094,760 1
49,900
40,351
48,388
19,010
478,638
255,978
17,877
76,578
145,311
93,345
17,591
16,978
72,743
22,585
28,324
162,348
Swine
102,998
,125,080
,228,078
34,396
59,135
76,435
9,779
124,357
234,040
11,766
4,916
100,638
133,668
6,579
21,533
148,895
19,485
21,111
75,608
1,545,944 1,082,342
9,105
27,582
59,296
85,256
18,032
160,901
71,064
1,492,342
105,652
2,029,230 1
81,798
230
222
81,205
16
0
163,470
(continued
1,411
26,591
92,839
200,547
313,393
94,770
80,282
408,177
71,601
289,612
116,188
84
1,911
17,398
4,935
229
140,744
on following
£wmmn&&tiwb^>:'< t>^
Sheep &
Goats
1,605
38,741
40,346
157
548
365
151
32,816
4,404
40,761
13,208
36,104
2,625
7,591
17,005
59,277
459
1,233
78,325
295,028
6,866
26,560
2,566
7,629
5,359
10,010
45,130
335,770
23,339
463,230
252,176
90
68
189,042
28
18
441,423
page)
Poultry*
15,796
213,276
229,072
2,245
7,669
2,446
942
38,945
12,247
4,641
1,448
23,564
18,179
628
2,452
8,063
1,762
797
23,214
149,242
755
7,739
9,042
9,651
12,766
12,491
25,783
220,771
11,190
310,188
6,466
293
115
1,039
439
0
8,353
Other8
12,406
87,572
99,978
1,618
863
1,043
1,036
11,482
12,586
9,345
2,528
14,174
2,301
734
8,465
16,079
1,669
1,810
6,592
92,325
3,568
13,594
949
3,740
2,627
30,235
22,861
183,378
13,885
274,838
8,652
952
360
3,596
23
68
13,650
Methane
mt/yr
330,166
3,857,141
4,187,307
134,529
169,390
154,411
48,758
1,082,970
795,405
99,458
202,003
510,978
333,764
50,459
88,491
385,259
79,676
90,288
643,508
4,869,348
30,974
127,205
272,389
445,173
370,465
410,765
353,201
4,214,571
281,112
6,505,855
883,457
2,238
5,115
413,588
5,889
791
1 ,31 1 ,079
54
-------
* * " - "" ^IIJH
Country
rr sir $i
Non-Dairy
Cattle
&mi wmmm EMISSIONS SUMMARY
Sheep &
Dairy Swine
(continued from previous
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
217,332
24,361
525,895
12,378
94,756
8,521
19,947
8,629
14,531
4,016
7,728
716
6,572
11,290
1,092
112,401
6,889
6,313
34,785
14,490
2,207
44,679
52,058
1 ,231 ,586
14,006
579
89,582
2,787
26,251
2,393
4,501
1,737
3,964
1,992
3,215
455
733
2,637
378
31 ,675
1,390
647
811
5,428
546
3,267
7,543
206,519
13,092
5,080
104,414
2,112
7,507
647
7,257
1,187
13,283
1,283
2,540
518
2,613
1,742
726
52,686
2,163
766
6,119
6,967
623
687
8,644
242,654
Goats
page)
38,584
14,637
39,678
8,466
4,469
22
607
919
2,427
28
856
255
1,914
46
665
22,736
12
11
705
17,961
29
30,144
2,598
187,769
Poultry*
9,991
1,843
90,763
3,380
5,991
768
4,148
4,148
7,725
461
2,250
2,085
1,997
1,170
922
40,475
768
1,075
2,458
7,988
1,811
1,317
9,382
202,917
Other8
75,355
18,270
202,142
11,476
67,565
2,802
16,719
12,462
16,885
2,659
3,472
60
14,919
5,725
663
258,396
6,807
3,989
8,217
27,196
574
10,826
19,464
786,644
Methane
mt/yr
368,359
64,771
1,052,474
40,598
206,539
15,154
53,179
29,082
58,816
10,439
20,060
4,089
28,748
22,610
4,446
518,370
18,029
12,802
53,095
80,030
5,790
90,920
99,688
2,858,089
EAST & SUBSAHARAN AFRICA
Burundi
Central African Rep.
Chad
Ethiopia
Kenya
Mali
Mauritania
Niger
Rwanda
Somalia
Tanzania
Uganda
Zaire
Total
1,269
10,279
8,280
61,469
17,098
9,663
2,216
6,730
2,266
9,065
48,495
12,826
6,309
195,967
475
356
1,688
16,110
9,375
1,971
1,131
2,203
1,267
4,157
22,173
8,552
63
69,522
(continued
244
1,164
20
32
170
174
0
62
280
17
561
1,341
2,438
6,503
1,533
1,883
2,987
26,695
10,615
8,781
4,778
7,703
2,222
22,851
64,743
6,225
5,592
166,609
571
428
322
4,587
1,851
1,390
322
1,368
143
241
4,671
2,140
2,710
20,743
0
0
7,419
72,695
5,926
7,339
7,365
10,318
0
50,374
2,585
255
0
164,275
4,092
14,110
20,717
181,588
45,035
29,318
15,812
28,385
6,178
86,705
143,228
31,340
17,113
623,619
oh following page)
55
-------
; EXHIBIT 31: GU3ML METHANE EMISSIONS Simmffl
Country
Non-Dairy
Cattle
Dairy
Swine
Sheep &
Goats
Poultry*
Other8
f. f •> f *
Methane
mt/yr
(continued from previous page)
WEST & SOUTHERN AFRICA
Angola
Benin
Botswana
Burkina Paso
Cameroon
C6te d'lvoire
The Gambia
Ghana
Guinea
Guinea-Bissau
Lesotho
Madagascar
Malawi
Mozambique
Namibia
Nigeria
Senegal
Sierra Leone
South Africa
Swaziland
Togo
Zambia
Zimbabwe
Total
14,073
3,617
4,668
5,321
19,824
3,653
1,224
5,008
6,781
1,274
2,017
47,775
2,871
4,396
4,263
49,764
10,642
1,269
299,611
2,253
1,142
10,941
25,186
527,573
2,336
919
1,206
1,917
768
1,219
238
1,544
1,782
467
634
467
752
3,088
669
9,661
2,059
396
16,961
1,212
301
2,138
1,132
51,865
1,463
1,975
15
835
3,590
1,372
40
2,286
152
884
219
4,267
1,219
488
70
3,962
1,433
152
6,015
58
914
549
579
32,537
1,773
2,439
955
5,629
7,722
3,991
532
7,405
1,224
553
3,215
2,331
1,672
702
5,581
15,264
6,115
652
50,794
522
1,470
724
3,153
124,421
856
3,281
80
1,690
2,282
2,282
0
1,712
1,854
143
143
4,819
995
3,126
80
27,104
1,569
856
4,272
143
428
2,140
1,427
61,282
98
151
1,418
2,333
1,153
23
60
466
68
66
4,613
23
15
301
1,146
16,455
7,990
0
8,966
256
68
30
2,062
47,762
20,599
12,381
8,342
17,724
35,340
12,541
2,093
18,421
11,862
3,388
10,841
59,682
7,525
12,101
11,809
122,211
29,808
3,326
386,621
4,442
4,323
16,522
33,539
845,440
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
Egypt
Iran
Iraq
Israel
Jordan
Kuwait
Libya
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Rep.
Total
5,507
4,319
1,331
13,597
3,179
4,445
25
45
376
7,886
213
453
43,170
952
820
31,726
1,598
119,643
4,633
4,514
7,176
9,305
1,730
4,414
71
127
194
12,353
166
495
13,660
1,148
990
39,594
1,378
101,948
(continued
0
17
38
0
0
1,107
0
0
0
30
0
0
0
2
8
33
0
1,236
11,936
10,968
1,892
30,194
6,485
1,162
1,051
377
4,051
26,882
662
7,025
20,853
8,503
4,250
65,966
2,358
204,616
640
2,103
3,282
10,059
6,950
6,804
5,487
4,097
3,383
5,413
183
6,310
2,652
1,097
1,555
9,364
2,103
71,481
20,344
10,274
22,761
22,267
5,317
567
344
188
3,015
28,287
793
4,073
26,610
2,444
5,063
39,338
4,441
196,128
43,059
32,196
36,482
85,422
23,662
18,498
6,979
4,833
11,019
80,852
2,017
18,356
106,945
14,147
12,687
186,021
11,877
695,051
oh following page)
56
-------
;^;|§J&p^ : -
.."..^XM.nV '* \?.f '" "
Country
Oi ••' '•> '•*
Non-Dairy
Cattle
"• .-. '
Dairy
'..''• r '
Swine
•••••• '
Sheep &
Goats
, , : 1 •.
Poultry*
' J
Other8
.. £ "•
Methane
mt/yr
(continued from previous page)
ASIA & FAR EAST
Bangladesh
Bhutan
China
India
Indonesia
Japan
Kampuchea
Myanmar (Burma)
North Korea
South Korea
Laos
Malaysia
Mongolia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Viet Nam
Total
WORLD TOTAL
78,518
1,220
325,305
681,973
22,661
232,070
1,175
31,082
4,956
8,644
2,252
2,572
4.376
23,247
30,169
5,728
4,772
20,118
11,740
1,492,576
9,449,080
26,631
828
30,356
210,700
3,365
320,002
737
17,904
263
2,114
286
366
2,709
5,078
15,097
232
4,890
512
339
642,408
5,905,665
0
247
1,388,076
29,899
26,416
212,554
5,878
11,756
12,148
18,640
5,957
8,286
238
1,877
0
28,604
396
16,694
47,225
1,814,892
5,838,598
16,261
79
235,907
217,747
50,740
199
3
1,996
859
253
114
625
13,031
8,674
40,727
3,131
789
230
649
592,017
2,515,459
16,619
0
316,468
45,649
91,664
116,990
1,467
5,223
3,072
9,626
1,383
9,178
0
1,536
17,984
9,561
1,383
15,146
14,123
677,071
1,730,348
8,974
866
626,042
364,792
43,606
791
3,195
12,328
1,065
68
5,031
1,086
27,285
11,829
67,463
16,623
4,306
24,905
14,541
1,234,797
2,910,397
147,002
3,239
2,922,154
1 ,550,760
238,453
882,605
12,455
80,291
22,364
39,345
15,022
22,112
47,639
52,241
171,441
63,879
16,536
77,604
88,616
6,453,761
28,349,549
A Includes chickens, turkeys and ducks.
B Includes buffalo, horses, mules, donkeys and camels.
While assumptions concerning other factors are somewhat uncertain (i.e., methane producing
capacity of the waste (B0), animal populations and waste quantities, waste system usage), their
contribution to the overall uncertainty is likely to be less.
To capture the uncertainty in these estimates, "high" and "low" case emission estimates
have been defined as follows:
• High Case. The MCF for anaerobic lagoons was assumed to be 1 and the MCFs
for all other liquid systems were assumed to be double that of the base case.
Low Case. The MCFs for each of the major solid systems (pasture/range, solid
storage, and drylots) were assumed to be half that of the base case.
Exhibit 33 lists the MCF values used to estimate the low and high cases.
57
-------
nxHiifr ft* wofttJWKJE aarrH ANS EMISSIONS BY WA$tt SV$TEM jr$W V; ,
Waste System
Pasture/Range
Liquid/Slurry
Solid Storage
An. Lagoon
Drylot
Burned for Fuel
Daily Spread
Other
Total
North
America
1.31
0.36
0.11
1.47
0.25
0.00
0.11
0.58
4.18
West
Europe
0.78
3.21
0.37
0.00
0.04
0.00
0.14
0.34
4.86
East
Europe
1.17
2.62
1.55
0.49
0.10
0.00
0.01
0.62
6.55
Oceania
1.16
0.00
0.00
0.13
0.00
0.00
0.00
0.02
1.31
Latin
America
2.18
0.04
0.03
0.00
0.10
0.00
0.10
0.42
2.86
Near East
Africa & Med
1.25
0.01
0.00
0.00
0.09
0.00
0.02
0.09
1.47
0.53
0.00
0.00
0.00
0.00
0.04
0.00
0.09
0.67
Asia&
Far East
1.82
0.94
0.03
0.68
0.90
0.96
0.21
0.86
6.41
Total
10.19
7.18
2.09
2.77
1.48
1.0
0.59
3.02
28.3
As shown in Exhibit 34, the range of emissions implied by these cases is about 20 Tg/yr
to 35 Tg/yr. The high estimate assumptions have the greatest influence on the estimates for
Europe, where a large number of liquid/slurry based systems are used. Emissions from Eastern
and Western Europe combined increase by almost 6 Tg/yr or by about 50 percent. Because of
the widespread use of solid based waste systems, the high case has only a small effect on
estimated emissions for North America and Asia, and no effect on the emissions estimate for
Latin America, Oceania, Africa, and the Near East and Mediterranean.
On the other hand, the low case estimates are 1.7 Tg/yr or about 40 percent lower for
Latin America, Oceania, Africa, and the Near East and Mediterranean; 0.9 Tg/yr or 20 percent
lower for North America; and 1.9 Tg/yr or about 15 percent lower for Eastern and Western
Europe combined.
The U.S. EPA is currently sponsoring research to verify the estimated MCFs for several
key animal waste systems, including: liquid/slurry storage, drylots, and pasture/range. In
addition, research is necessary to measure the methane capacity (B0) of animal waste in
developing countries and to improve the characterization of animal waste management systems
throughout the world.
While many of the assumptions used to estimate emissions are uncertain, this report
provides a framework for estimating emissions and for identifying regions where opportunities
are available for reducing emissions. As additional data become available, the estimates
presented in this report will be improved.
58
-------
BASE, HIGH, AND LOW CASE EMISSION
Management System
Methane Conversion Factors (MCFs)
Base Case High Case
Low Case
Solid Systems
Pasture/Range 0.10
Drylot 0.10
Solid Storage 0.10
Liquid Systems
Liquid/Slurry Storage 0.20
Pit Storage, less than 1 month 0.10
Pit Storage, greater than 1 month 0.20
Anaerobic Lagoon 0.90
0.10
0.10
0.10
0.40
0.20
0.40
1.00
0.05
0.05
0.05
0.20
0.10
0.20
0.90
EXHIBIT 34: BASE, HIGH, AND LOW CASE EMISSION ESTIMATES
^i^^i
Region
North America
Western Europe
Eastern Europe
Oceania
Latin America
Africa
Near East and Mediterranean
Asia & Far East
Total
f f *
Base Case
4.2
4.8
6.6
1.3
2.9
1.5
0.7
6.4
28.4
%
High Case
4.7
8.1
9.2
1.3
2.9
1.5
0.7
7.4
35.8
(Ka/YR) ;;':-;
••
Low Case
3.3
4.3
5.2
0.7
1.7
0.8
0.4
5.0
21.4
59
-------
60
-------
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68
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APPENDICES
TABLE OF CONTENTS
APPENDIX A: U.S. ANIMAL POPULATIONS APP-3
TABLE A1: U.S. LIVESTOCK AND POULTRY POPULATIONS (1000 HEAD) .... APP-5
TABLE A2: U.S. AVERAGE LIVE ANIMAL MASS APP-6
APPENDIX B: U.S. ANIMAL WASTE METHANE PRODUCTION APP-7
TABLE B1: METHANE EMISSIONS FOR U.S. BEEF CATTLE IN FEEDLOTS APP-9
TABLE B2: METHANE EMISSIONS FOR U.S. BEEF CATTLE NOT IN FEEDLOTS . . . APP-10
TABLE B3: METHANE EMISSIONS FOR U.S. DAIRY CATTLE APP-11
TABLE B4: METHANE EMISSIONS FOR U.S. SWINE APP-12
TABLE B5: METHANE EMISSIONS FOR U.S. CAGED LAYERS APP-13
TABLE B6: METHANE EMISSIONS FOR U.S. BROILERS APP-14
TABLE B7: METHANE EMISSIONS FOR U.S. TURKEYS APP-15
TABLE B8: METHANE EMISSIONS FOR U.S. SHEEP APP-16
TABLE B9: METHANE EMISSIONS FOR U.S. GOATS APP-17
TABLE B10: METHANE EMISSIONS FOR U.S. HORSES APP-18
TABLE B11: METHANE EMISSIONS FOR U.S. DUCKS, MULES, AND DONKEYS APP-19
APPENDIX C: LIVESTOCK CATEGORY WEIGHTS FOR SELECTED COUNTRIES APP-21
TABLE 01: DEVELOPED COUNTRIES AVERAGE LIVESTOCK MASS APP-22
TABLE C2: AUSTRALIA LIVESTOCK DATA 1987 APP-23
TABLE C3: AUSTRIA LIVESTOCK DATA 1987 APP-23
TABLE C4: BELGIUM LIVESTOCK DATA 1987 APP-24
TABLE C5: DENMARK LIVESTOCK DATA 1987 APP-24
TABLE C6: FRANCE LIVESTOCK DATA 1987 APP-25
TABLE C7: ITALY LIVESTOCK DATA 1987 APP-25
TABLE C8: WEST GERMANY LIVESTOCK DATA 1987 APP-26
TABLE C9: IRELAND LIVESTOCK DATA 1987 APP-27
TABLE C10: NETHERLANDS LIVESTOCK DATA 1987 APP-28
TABLE 011: SOUTH AFRICA LIVESTOCK DATA 1987 APP-28
TABLE C12: UNITED KINGDOM LIVESTOCK DATA 1987 APP-29
TABLE C13: SOVIET UNION LIVESTOCK DATA 1987 APP-30
TABLE C14: YUGOSLAVIA LIVESTOCK DATA 1987 APP-30
APPENDIX D: CANADA ANIMAL WASTE METHANE PRODUCTION APP-31
TABLE D1: CANADA METHANE EMISSIONS SUMMARY APP-32
TABLE D2: CANADA METHANE EMISSIONS FROM BEEF CATTLE APP-33
TABLE D3: CANADA METHANE EMISSIONS FROM DAIRY CATTLE MANURE APP-33
TABLE D4- CANADA METHANE EMISSIONS FROM SWINE MANURE APP-34
TABLE D5: CANADA METHANE EMISSIONS FROM SHEEP MANURE APP-34
TABLE D6- CANADA METHANE EMISSIONS FROM BROILER MANURE APP-35
TABLE D7- CANADA METHANE EMISSIONS FROM CAGED LAYER MANURE APP-35
TABLE D8- CANADA METHANE EMISSIONS FROM TURKEY MANURE APP-36
APP-1
-------
APPENDIX E: GLOBAL ANIMAL WASTE METHANE PRODUCTION APP-37
TABLE E1: METHANE EMISSIONS FROM NON-DAIRY CATTLE WASTE APP-39
TABLE E2: METHANE EMISSIONS FROM DAIRY CATTLE WASTE APP-43
TABLE E3: METHANE EMISSIONS FROM SWINE WASTE APP-47
TABLE E4: METHANE EMISSIONS FROM SHEEP WASTE APP-51
TABLE E5: METHANE EMISSIONS FROM GOAT WASTE APP-55
TABLE E6: METHANE EMISSIONS FROM CHICKEN WASTE APP-59
TABLE E7: METHANE EMISSIONS FROM DUCK WASTE APP-63
TABLE E8: METHANE EMISSIONS FROM TURKEY WASTE APP-64
TABLE E9: METHANE EMISSIONS FROM BUFFALO WASTE APP-65
TABLE E10: METHANE EMISSIONS FROM HORSE WASTE APP-66
TABLE E11: METHANE EMISSIONS FROM MULE WASTE APP-70
TABLE E12: METHANE EMISSIONS FROM DONKEY WASTE APP-72
TABLE E13: METHANE EMISSIONS FROM CAMEL WASTE APP-75
APPENDIX F: REQUESTS FOR DATA - UNITED STATES AND WORLD APP-77
APPENDIX G: U.S.
TABLE G1:
TABLE G2:
TABLE G3:
TABLE G4:
TABLE G5:
TABLE G6:
TABLE G7:
TABLE G8:
TABLE G9:
APPENDIX H: U.S.
TABLE H1:
TABLE H2:
TABLE H3:
TABLE H4:
TABLE H5:
TABLE H6:
TABLE H7:
TABLE H8:
TABLE H9:
WASTE MANAGEMENT
METHANE EMISSIONS
METHANE EMISSIONS
METHANE EMISSIONS
METHANE EMISSIONS
METHANE EMISSIONS
METHANE EMISSIONS
METHANE EMISSIONS
METHANE EMISSIONS
METHANE EMISSIONS
SYSTEM METHANE PRODUCTION APP-81
FROM U.S. BEEF AWMS'S APP-82
FROM U.S. DAIRY AWMS'S APP-83
FROM U.S. SWINE AWMS'S APP-84
FROM U.S. CAGED LAYERS AWMS'S APP-85
FROM U.S. BROILER AWMS'S APP-86
FROM U.S. TURKEY AWMS'S APP-87
FROM U.S. SHEEP AWMS'S APP-88
FROM U.S. GOAT AWMS'S APP-89
FROM U.S. HORSE AWMS'S APP-90
ANIMAL
ANIMAL
ANIMAL
ANIMAL
ANIMAL
ANIMAL
ANIMAL
ANIMAL
ANIMAL
ANIMAL
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
MANAGEMENT
MANAGEMENT
MANAGEMENT
MANAGEMENT
MANAGEMENT
MANAGEMENT
MANAGEMENT
MANAGEMENT
MANAGEMENT
MANAGEMENT
SYSTEM USAGE . .
SYSTEMS FOR U.S.
SYSTEMS FOR U.S.
SYSTEMS FOR U.S.
SYSTEMS FOR U.S.
SYSTEMS FOR U.S.
SYSTEMS FOR U.S.
SYSTEMS FOR U.S.
SYSTEMS FOR U.S.
SYSTEMS FOR U.S.
BEEF
DAIRY
SWINE
CAGED LAYERS
BROILERS
TURKEYS
SHEEP
GOATS
HORSES
APP-91
APP-92
APP-93
APP-94
APP-95
APP-96
APP-96
APP-97
APP-97
APP-98
APPENDIX I: GLOBAL ANIMAL WASTE MANAGEMENT SYSTEM USAGE APP-99
TABLE 11: GLOBAL AWMS USAGE FOR NON-DAIRY CATTLE APP-100
TABLE 12: GLOBAL AWMS USAGE FOR DAIRY CATTLE APP-103
TABLE 13: GLOBAL AWMS USAGE FOR SWINE APP-107
TABLE 14: GLOBAL AWMS USAGE FOR POULTRY APP-110
TABLE 15: GLOBAL AWMS USAGE FOR ALL OTHER LIVESTOCK APP-113
APPENDIX J: GLOBAL ANIMAL WASTE PRODUCTION APP-117
APPENDIX K: INFORMATION CONTRIBUTORS APP-121
APPENDIX L: IPCC WORKSHOP FINDINGS APP-129
APP-2
-------
&S, ANIMAL POPULATIONS
APP-3
-------
APPENDIX A: U.S. ANIMAL POPULATIONS
The age and weight classifications in the ASB population statistics were as follows:
Beef Cattle: For beef cattle not in feedlots, two weight classes for all states are defined:
under 500 Ib. and over 500 Ib, For feedlot cattle five weight classes for 13
major cattle producing states
to 899 Ib.; 900 to 1099 Ib.; and 1100 Ib. over, and over.
f are defined: under 500 Ib.; 500 to 699 Ib.; 700
Dairy Cattle: For dairy cattle, two weight classes for all states: under 500 Ib. and over 500 Ib.
Swine:2 For breeding animals, a single weight class is defined for data for all states.
For market animals, four weight classes are defined for all states: under 60 Ib.;
60 to 119 Ib.; 120 to 179 Ib.; 180 Ib. and over.
Chickens: For layers, five classes are defined for all states:2 hens one year and older;
pullets of laying age; pullets three months old and older, not of laying age;
pullets under three months of age; and other chickens (excluding broilers). For
broilers, annual production data (1988) for the 34 major producing states was
collected and converted to average populations. For other chickens, annual
production data (1988) was collected for all states and converted to average
populations.
Turkeys Annual production data (1988) for the 32 major producing states were collected
and converted to average populations.
Sheep For stock sheep, four weight classes are defined for all states: ewes, one year
and older; ewes, lambs less than one year old; rams and wethers, one year
and older; rams and wethers, lambs less than one year old. For sheep on
feed, data are for most states and for the U.S. total.
Goats Populations are for 50 states from census data (USDA 1987).
The animal populations for all 50 states are summarized in Table A1 for the nine major
animal types. The weight class data for cattle on feed in the 13 major producing states can
be found in Table A2. All other age class population data are listed by animal type in Tables
B1 toB11.
ASSUMED ANIMAL MASS
Many of the animal populations in the ASB (1989a, 1989b, 1989c, 1989d, 1989e, and
1989f) releases were divided into several categories that were not ascribed specific weights.
Since livestock produce manure in proportion to their live mass, it was necessary to
determine the proper live animal mass for each category in the animal population data. Table
A2 shows the average animal weights that were assigned to each of these categories,
including the weight classes.
1 Arizona, California, Colorado, Idaho, Illinois, Iowa, Kansas, Minnesota, Nebraska, Oklahoma, South Dakota,
Texas, and Washington.
2 December 1, 1988 data
APP-4
-------
\* ^V^?i^^Vs|r;^'iwiMOflfc-ii* sta* iwrnxzwrn cioea «u»>^ ;<:x '
AK
AL
AR
AZ
CA
CO
CT
IDE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
wv
WY
OTHER
U.S
Beef
7
1,761
1,682
788
3,675
2,675
38
21
1,843
1,396
196
4,440
1,450
1,750
1,110
5,796
2,285
987
40
219
62
880
2,130
4,274
1,322
2,325
743
1,501
5,297
34
45
1,287
482
773
1,393
5,093
1,296
1,201
4
569
3,336
2,098
13,345
696
1,528
127
1,084
2,390
474
1,320
0
89,268
Dairy
3
53
93
112
1,510
105
49
11
222
144
16
430
237
280
260
145
295
113
39
152
62
502
1,180
316
94
32
144
26
133
31
42
79
109
1,107
543
142
138
1,009
4
56
182
282
475
113
222
223
320
2,535
36
11
0
14.416
Swine
1
345
540
130
120
220
7
33
140
1,210
43
13,900
80
5,600
4,300
1,500
1,090
60
31
170
8
1,250
4,690
2,850
237
245
2,700
340
4,050
9
38
26
15
151
2,210
240
100
970
6
450
1,760
1,050
560
33
400
6
53
1,275
37
21
0
55.299
Layers
5
14,650
21,435
310
36,800
3,986
5,600
986
13,890
23,587
1,217
10,100
1,280
3,760
27,800
2,250
2,250
2,100
1,202
4,821
6,425
7,400
11,700
7,900
8,103
910
19,755
255
4,150
309
1,850
1,320
17
5,050
23,000
4,650
3,050
24,400
242
7,050
1,500
2,070
18,200
2,260
4,771
209
6,085
4,060
730
19
0
355,469
i
Broilers
0
127,779
163,060
0
38,567
0
0
39,537
22,400
140,514
411
545
0
0
0
0
492
0
0
45,891
0
136
6,018
9,909
65,631
0
90,927
0
205
0
0
0
0
455
2,182
21,982
3,145
23,073
0
12,879
0
15,818
48,418
0
31,954
0
5,127
2,382
6,394
0
26,082
951.914
Turkeys
0
0
4,000
0
5,889
0
7
0
0
533
0
1,733
0
378
2,867
50
0
0
33
30
0
667
8,556
3,667
0
0
10,644
267
394
6
22
0
0
76
800
0
367
1,756
0
1,238
527
0
0
867
3,622
0
0
0
511
0
4,278
53,783
Sheep
48
0
0
399
1,160
445
18
0
0
0
0
448
291
135
151
164
32
17
14
35
15
115
241
139
0
588
34
189
121
11
46
485
85
81
216
120
420
134
0
0
690
33
1,730
523
115
17
82
76
199
720
57
10,639
Goats
0
11
14
100
29
7
1
0
12
20
1
7
3
8
7
9
10
4
3
3
1
21
7
17
5
2
9
2
4
1
3
135
1
9
17
70
11
9
0
6
2
29
1,750
2
8
7
9
4
4
0
2,396
Horses
2
35
40
71
149
79
7
3
61
34
4
59
56
55
53
56
90
39
12
27
6
57
54
74
28
72
30
32
51
4
23
52
18
53
75
96
59
65
1
17
45
62
233
40
48
58
48
15
48
0
2,404
APP-5
-------
. „ , „ TABLE A2: U.S. AVERAGE LIVE ANIMAL MASS
Layers :
Hens 1 year and older*
Pullets of laying ageA
Pullets , 3 months and older , not of laying ageA
Pullets under 3 months of ageA
Other Poultry:
BroilersB
TurkeysB
Other chickens, lostB
Other chickens , soldB
Sheep:
Ewes 1 year and older*
Rams and Wethers 1 year and older*
Ewe lambs*
Ram and wether lambs*
Sheep and lambs on feed*
Swine :
Breeding*
Market: under 60 Ib*
60 - 119 Ib*
120 - 179 Ib*
180 Ib & overc
Cattle & Calves:
Beef cows and heifers that have calved*
Milk cows and heifers that have calved*
Heifers 500 Ib and over for beef cow replacement*
Heifers 500 Ib and over for milk cow replacement*
Steers 500 Ib and over*
Bulls 500 Ib and overc
Calves under 500 Ib*
Steers and steer calves on feed (except 13 major states)*
Heifers and heifer calves on feed (except 13 major states)*
Cows and others on feed0
Goats :
Horses :
* Taiganides and Stroshine, 1971.
B Calculated from total ASB weight data for type.
c Estimated from related data in this table or in ASB data.
.• ,
** ^* , / f 1 , ,
Mass (kg)
2.0
1.6
0.9
0.6
0.676
3.38
0.37
0.74
86.
82.
36.
39.
25.
181.
14.
41.
68.
95.
680.
680.
391.
476.
383.
680.
181.
383.
391.
500.
64.
450
APP-6
-------
; US, ANJMAt WASTE MiTHANE
APP-7
-------
APPENDIX B: U.S. ANIMAL WASTE METHANE PRODUCTION
Tables B1 to B10 list the methane emissions for each major animal type for each state
of the U.S. Table B11 lists the total U.S. emissions for donkeys, mules, and ducks. Methane
emissions were calculated using Equations 3.1, 3.2, and 3.4 in Chapter 3. The following data
were used:
Volatile Solids (VS) production is calculated with the following data:
Number of animals (N) listed in Tables B1 to B10;
Typical Animal Mass (TAM) listed in Exhibit 4; and
Volatile solids production per unit of animal mass listed in Exhibit 4.
Maximum Methane Producing Capacity for each animal waste type is shown in
Exhibit 8.
• Methane Conversion Factors (MCFs) for each animal waste management system
are listed in Exhibit 12.
Climate Adjustment Factors (CAFs) for each animal waste system in each state
are assigned a value of 1.
• Waste System Usage (WS%) for each state and animal are listed in Appendix I.
The following abbreviations are used in tables B1 through B10.
1000h = 1000 head
VS = volatile solids production (mt/day)
f of B0 = Fraction of B0 that is achieved (f of B0 = MCF • CAF).
Note: 0 s f of B0 <; 1.
Rams/Weth. = rams and wethers
>3mo. = over 3 months of age
<3mo. = under 3 months of age
Other chick = other chickens for laying purposes
mt = Metric ton
Tot = Total
Oth = Other
Pop. = Population
Note: the density of methane is assumed to be 0.662 kg/m3 (72°F, 1 atm).
APP-8
-------
:?!;i^;3
&- " , -
IABLE
>&:>*
n&Bfc'ic
liTwalr
CIX&OJL
1000 head
1 State
AL
AR
AZ
CA
CO
FL
GA
HI
IA
IID
IL
IN
KS 1
KY
LA
MD
MI
MN
MO
MS
MT
NC
ND
NE 1
NJ
NM
NV
NY
OH
OK
OR
PA
SC
SD
TN
TX 2
UT
VA
WA
Wl
wv
WY
US 11
Tot
40
12
275
485
885
15
15
23
640
238
340
230
,546
25
9
12
210
310
95
12
90
23
40
,950
3
130
29
19
200
305
91
75
20
260
20
,070
48
40
190
100
10
-L.VS
109
,239
Steers
29
9
262
365
458
11
11
17
416
160
179
165
1,050
18
7
9
151
217
68
9
65
17
29
1,170
2
94
21
14
144
202
65
54
14
141
14
1,366
35
29
127
72
7
78
7,367
Heifers
10
3
13
118
420
4
4
6
218
68
161
60
496
7
2
3
55
90
25
3
23
6
10
770
1
34
8
5
52
103
24
20
5
109
5
702
13
10
63
26
3
28
3,785
Oth
1
0
0
2
7
0
0
1
6
10
0
5
0
1
0
0
4
3
2
0
2
1
1
10
0
3
1
0
4
0
2
2
0
10
0
2
1
1
0
2
0
2
87
=====
bss>?QS. ths^siEF H&mat-Bi TOESti&u
Tot Mass
(mt)
15,501
4,650
90,064
134,636
292,934
5,813
5,813
8,913
236,996
99,178
130,623
89,134
584,800
9,688
3,488
4,650
81,383
112,864
36,816
4,650
34,878
8,913
15,501
782,620
1,163
50,380
11,239
7,363
77,507
125,673
35,266
29,065
7,751
105,798
7,751
813,117
18,602
15,501
78,339
38,754
3,875
42,242
4,263,894
^^^^^SSSBSSS^— •• "
vs
(mt/day)
112
33
759
1,346
2,471
42
42
64
1,782
669
947
642
4,291
70
25
33
586
863
265
33
251
64
112
5,430
8
363
81
53
558
847
254
209
56
732
56
5,750
134
112
528
279
28
304
31,283
=====
f of B0
0.18
0.10
0.10
0.10
0.18
0.50
0.12
0.10
0.11
0.10
0.19
0.15
0.15
0.10
0.10
0.16
0.16
0.11
0.50
0.11
0.10
0.26
0.19
0.12
0.10
0.10
0.10
0.11
0.15
0.10
0.15
0.10
0.10
0.27
0.10
0.10
0.10
0.11
0.10
0.11
0.10
0.11
Methane
(mt/year)
903
267
6,055
10,736
24,182
342
334
512
14,386
5,364
8,712
5,542
38,731
556
200
275
5,322
6,978
2,267
267
2,003
532
645
45 , 504
67
2,893
905
423
4,713
6,756
2,082
1,670
445
6,438
445
45,870
1,068
892
4,208
2,231
223
2,435
264,384
APP-9
-------
! ' — wo* nt mmm iMimoitf *a**.»* «&*:«&»* w* x* naaww- t --
1000 head
Mass VS
State Bulls Calves Heifers Steers Cows (mt)
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
MM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
US
1
60
55
26
70
45
1
1
72
50
5
80
32
35
25
73
73
34
1
7
2
17
42
110
50
75
26
45
85
1
2
35
13
17
40
105
35
31
0
22
73
60
410
21
40
3
25
33
17
40
2,221
2
495
400
156
1,005
305
14
6
423
377
57
1,040
320
370
300
1,142
617
205
12
64
22
270
615
1,135
325
242
220
230
930
13
11
250
130
268
384
1,195
265
380
1
143
637
600
2,600
127
405
50
175
1,025
90
200
20,248
1
200
212
68
702
340
16
5
176
191
30
687
229
314
180
664
329
138
13
64
25
175
558
560
177
428
113
238
425
12
15
156
59
348
291
687
214
361
1
77
517
270
1,488
127
230
58
229
856
67
227
13,547
1
66
71
0
490
332
2
6
9
63
4
734
121
171
30
921
182
20
4
12
4
87
218
372
46
168
18
128
220
2
3
141
9
19
97
908
120
140
0
22
353
111
1,334
59
151
4
106
228
45
77
8,430
3
900
932
263
923
768
5
3
148
700
77
1,259
510
520
345
1,450
1,059
582
10
60
9
121
387
2,002
712
1,322
343
831
1,687
6
11
575
230
102
381
1,893
571
214
1
286
1,496
1,038
5,443
314
662
12
359
148
245
668
33,583
3
845
853
251
1,319
868
13
8
978
676
79
1,648
562
632
387
1,854
1,079
517
16
86
22
244
704
2,003
663
1,225
341
779
1,623
12
17
575
215
272
506
2,191
589
430
1
273
1,519
1,002
5,543
323
698
43
422
730
237
635
36,537
,492
,917
,569
,344
,297
,141
,636
,059
,333
,954
,196
,499
,362
,637
,822
,809
,919
,161
,267
,688
,769
,337
,707
,035
,734
,483
,674
,436
,725
,571
,828
,131
,789
,655
,657
,316
,708
,273
,396
,347
,563
,814
,370
,035
,472
,460
,932
,595
,823
,416
,154
(mt/dy)
25
6,091
6,146
1,810
9,499
6,251
98
58
7,044
4,874
570
11,869
4,049
4,555
2,792
13,355
7,775
3,724
117
624
164
1,759
5,074
14,422
4,779
8,823
2,460
5,612
11,691
91
128
4,141
1,554
1,963
3,648
15,777
4,246
3,098
10
1,968
10,941
7,220
39,912
2,326
5,029
313
3,045
5,260
1,712
4,575
263,068
Methane
f of B0 (mt/year)
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0-10
25,
25,
7,
39,
31,
29,
20,
2,
49,
16,
21,
12,
62,
31,
15,
2,
8,
21,
63,
19,
36,
10,
23,
50,
17,
6,
8,
15,
64,
17,
12,
8,
49,
29,
164,
9,
20,
1,
12,
21,
7,
18,
1,114,
103
385
254
436
034
517
403
238
623
054
343
349
732
591
423
096
951
301
481
641
674
232
147
525
645
258
514
441
468
372
527
016
384
077
870
834
936
738
41
087
590
670
010
558
710
286
513
668
036
872
660
APP-10
-------
State
AK
AL
AR
AZ
CA 1
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN 1
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY 1
OH
OK
OR
PA 1
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI 2
WV
WY
US 14
Total
3
53
93
112
510
105
49
11
222
144
16
430
237
280
260
145
295
113
39
152
62
502
,180
316
94
32
144
109
133
31
42
79
26
,107
543
142
138
,009
4
56
182
282
475
113
222
223
320
,535
36
11
,416
;;MI '< K
1000 h
Cows
2
39
68
92
1,025
75
35
9
182
104
12
310
170
200
180
104
215
88
30
109
43
345
810
226
68
25
107
88
103
21
30
63
19
811
367
107
94
719
2
41
144
202
355
74
142
170
216
1,740
26
10
10,217
fcTHA&E feS
lead
Heifers
1
14
25
20
485
30
14
2
40
40
4
120
67
80
80
41
80
25
9
43
19
157
370
90
26
7
37
21
30
10
12
16
7
296
176
35
44
290
1
15
38
80
120
39
80
53
104
795
10
1
4,199
=====
ClSSjKJtJS f
Mass
(mt)
1,578
33,184
58,140
72,080
927,860
65,280
30,464
7,072
142,800
89,760
10,064
267,920
147,492
174,080
160,480
90,236
184,280
71,740
24,684
94,588
38,284
309,332
726,920
196,520
58,616
20,332
90,372
69,836
84,320
19,040
26,112
50,456
16,252
692,376
333,336
89,420
84,864
626,960
2,156
35,020
116,008
175,440
298,520
68,884
134,640
140,828
196,384
1,561,620
22,440
7,276
8,946,345
=====
^ *,*, *
VS
(mt/day)
16
332
581
721
9,279
653
305
71
1,428
898
101
2,679
1,475
1,741
1,605
902
1,843
717
247
946
383
3,093
7,269
1,965
586
203
904
698
843
190
261
505
163
6,924
3,333
894
849
6,270
22
350
1,160
1,754
2,985
689
1,346
1,408
1,964
15,616
224
73
89,463
tax* 6&1
f of B0
0.35
0.48
0.26
0.18
0.48
0.11
0.13
0.15
0.11
0.43
0.40
0.14
0.26
0.13
0.23
0.11
0.25
0.16
0.10
0.14
0.10
0.15
0.11
0.56
0.19
0.20
0.15
0.12
0.10
0.13
0.10
0.82
0.11
0.09
0.15
0.46
0.49
0.06
0.10
0.74
0.31
0.21
0.35
0.11
0.16
0.10
0.47
0.08
0.14
0.20
?TI*E ' :
Methane
(mt/year)
318
9,144
8,854
7,527
226,078
4,071
2,293
595
9,196
22,209
2,347
21,760
22,589
13,381
21,413
5,758
26,192
6,451
1,432
7,765
2,221
26,469
46,388
63,844
6,410
2,306
7,864
990
4,867
1,436
1,515
23,856
4,659
34,142
28,523
23,733
23,902
19,823
125
15,034
20,863
20,865
61,046
4,196
12,693
8,170
52,977
72,476
1,836
825
1,013,428
APP-11
-------
„!» ,-,-'' * SABLE Mr
Breeding
Pies
St.
AK
AL
AR
AZ
CA
CT
CO
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
US
0
48
76
15
21
1
32
7
27
165
7
1,600
11
710
540
175
155
11
4
27
2
170
600
410
38
32
320
42
500
2
3
4
2
21
295
35
13
105
1
64
241
160
90
5
50
1
7
185
7
4
7,040
<60
0
109
212
44
42
2
70
15
52
420
15
4,390
26
1,760
1,260
500
410
15
9
55
3
350
1,500
895
77
82
970
107
1,380
3
7
9
4
67
720
95
25
305
2
153
562
380
188
12
120
2
18
415
10
8
17,875
KETHAHE 2HISSIOSS BU& O.S.-fflBIHS - / ' ^ ,;''!*'
Market Pigs
Weieht (Ib)
Mass
60-119 120-179 >180 (mt)
0
86
102
27
26
2
48
5
31
280
11
3,260
18
1,240
1,060
317
215
16
8
40
1
260
1,060
585
48
54
555
75
910
2
11
5
3
31
480
50
23
229
2
104
410
210
118
6
80
2
8
273
7
5
12,399
0
65
87
23
17
1
42
4
20
205
7
2,600
13
1,020
820
293
180
10
5
33
1
230
855
535
38
47
465
62
710
1
8
4
3
16
395
30
20
185
1
77
311
150
94
5
78
1
13
229
5
2
10,016
0
37
63
21
14
1
28
2
10
140
3
2,050
12
870
620
215
130
8
5
15
1
240
675
425
36
30
390
54
550
2
9
4
3
16
320
30
19
146
0
52
236
150
70
5
72
1
7
173
8
2
7,969
54
21,675
32,807
7,997
7,941
407
14,256
2,144
9,196
74,465
2,689
856,270
5,117
356,000
273,500
92,021
67,200
4,297
1,993
10,966
585
84,770
295,325
187,480
15,928
15,200
162,925
21,521
247,660
618
2,491
1,707
1,030
8,618
140,415
14,605
6,811
59,114
357
28,166
111,867
67,340
36,802
2,134
26,154
377
3,396
82,495
2,794
1,367
3,471,048
VS
(mt/dy)
1
184
279
68
68
4
121
18
78
633
23
7,278
44
3,026
2,325
782
571
37
17
93
5
721
2,510
1,594
135
129
1,385
183
2,105
5
21
15
9
73
1,194
124
58
503
3
239
951
572
313
18
222
3
29
701
24
12
29,504
Methane
f of B0 (mt/yr)
0.90
0.83
0.67
0.90
0.82
0.10
0.32
0.33
0.38
0.65
0.39
0.17
0.46
0.35
0.36
0.37
0.74
0.86
0.17
0.54
0.17
0.48
0.16
0.74
0.64
0.13
0.68
0.29
0.43
0.15
0.17
0.19
0.30
0.20
0.44
0.58
0.33
0.16
0.17
0.83
0.38
0.75
0.41
0.30
0.83
0.17
0.40
0.17
0.33
0.32
40
15,743
19,143
6,398
5,584
3,937
79
589
2,955
42,614
906
137,057
2,044
108,584
87,128
30,230
43,388
3,182
292
5,122
82
35,580
41,703
121,562
8,033
1,671
97,364
5,529
84,202
78
379
282
274
1,493
54,599
7,350
2,019
8,446
51
20,279
27,978
43,570
13,061
557
19,265
54
1,197
12,256
784
365
1,125,080
APP-12
-------
p-v5;^/;£<%^ 'oaifr i*&ft6. - "' " "^ " ••
Pullets
st-
AK
AL
AR
AZ
CA
CO
1 CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
>1 yr
3
4,270
6,138
200
18,400
1,570
2,598
193
7,510
5,947
633
3,620
465
1,190
6,300
550
850
740
417
1,054
2,737
2,200
4,500
3,100
2,918
285
4,710
132
1,740
102
735
605
9
1,600
7,000
1,445
1,460
t
6,700
128
2,030
640
730
7,100
1,237
1,748
42
2,768
1,450
271
9
122 779
laying
1
5,695
7,955
100
13,400
1,605
1,590
415
3,830
12,240
372
4,900
405
2,000
15,650
1,120
960
640
541
2,484
1,973
3,600
4,500
2,800
2,387
405
9,700
108
1,840
10
965
477
4
2,550
10,450
2,310
1,040
13,300
53
3,145
630
1,000
6,600
631
1,919
116
2,106
1,750
196
7
152,573
>3 mo
1
1,855
3,113
3
2,200
310
754
235
1,260
1,981
135
740
245
340
2,450
250
70
330
38
241
874
570
1,000
830
1,050
84
2,535
7
185
50
25
123
2
410
2,740
350
60
1,560
39
740
95
150
1,490
202
504
34
609
345
112
1
33,327
<3 mo
0
2,075
3,198
1
2,600
498
650
76
1,160
2,606
77
800
156
200
3,350
320
330
295
182
970
835
1,000
1,645
1,100
1,332
131
2,050
4
370
46
120
112
1
470
2,780
400
470
2,710
21
1,055
131
130
2,500
186
433
16
590
490
116
1
40,789
Other
chick
0
755
1,031
6
200
3
8
67
130
813
0
40
9
30
50
10
40
95
24
72
6
30
55
70
416
5
760
4
15
3
5
3
1
20
30
145
20
130
1
80
4
60
510
4
167
1
12
25
35
1
6,001
Mass
VS
(mt) (mt/day) f
21,
30,
61,
6,
8,
1,
23,
35,
2,
16,
1,
6,
41,
3,
3,
3,
1,
6,
9,
11,
18,
12,
11,
1,
29,
6,
3,
2,
7,
34,
7,
4,
37,
10,
2,
3,
28,
3,
7,
9,
6,
1,
549,
9
246
652
569
960
289
816
367
095
556
029
262
900
033
900
318
533
064
865
946
924
300
137
150
774
377
136
449
826
452
113
154
28
949
881
272
938
827
389
463
456
327
060
781
430
311
819
327
058
32
543
0
255
368
7
744
76
106
16
277
427
24
195
23
72
503
40
42
37
22
83
119
136
218
146
141
17
350
5
82
5
37
26
0
95
419
87
59
454
5
126
30
40
337
45
89
4
118
76
13
0
6,595
Methane
of B0
0.20
0.75
0.48
0.05
0.14
0.10
0.05
0.05
0.17
0.09
0.14
0.08
0.14
0.14
0.06
0.05
0.62
0.86
0.07
0.05
0.07
0.08
0.09
0.08
0.80
0.10
0.34
0.10
0.05
0.05
0.07
0.25
0.06
0.10
0.05
0.08
0.16
0.10
0.07
0.40
0.22
0.25
0.47
0.08
0.09
0.07
0.07
0.12
0.30
0.10
(mt/yr)
15
14
8
3
3
1
1
2
2
2
1
9
9
1
3
4
12
111
2
,610
,510
28
,341
595
435
67
,804
,296
,641
,203
262
803
,376
164
,159
,598
126
343
670
892
,565
959
,231
130
,698
44
337
22
21
526
2
784
,720
574
765
,824
26
,076
533
802
,868
280
623
21
629
733
313
3
,223
APP-13
-------
- wu. **: >*utouM m*im** wr M-$K>®m; ~\~ -?*: •.
State
AL
AR
CA
DE
FL
GA
HI
IA
KY
MD
MI
MN
MO
MS
NC
NE
NY
OH
OK
OR
PA
SC
TN
TX
VA
WA
WI
WV
Other
U.S. 5
Produce
1000 h
702,784
896,832
212,119
217,455
123,198
772,825
2,261
3,000
2,704
252,400
750
33,100
54,500
360,971
500,100
1,129
2,500
12,000
120,900
17,300
126,900
70,832
87,000
266,300
175,748
28,200
13,100
35,166
143,451
,235,605
Average
Pop.
127,779
163,060
38,567
39,537
22,400
140,514
411
545
492
45,891
136
6,018
9,909
65,631
90,927
205
455
2,182
21,982
3,145
23,073
12,879
15,818
48,418
31,954
5,127
2,382
6,394
26,082
951,914
Mass
(Mt)
88,158
112,980
29,307
26,854
15,929
97,488
335
1,169
541
31,405
847
5,037
7,509
45,524
63,303
423
953
3,133
15,296
2,333
18,080
9,412
10,923
34,127
22,021
3,981
2,041
4,392
20,779
674,280
VS
(Mt/day)
1,499
1,921
498
457
271
1,657
6
20
9
534
14
86
128
774
1,076
7
16
53
260
40
307
160
186
580
374
68
35
75
353
11,463
f_ n
of B0
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
Methane
(mt/year)
12,283
15,217
3,759
3,303
2,029
12,000
44
119
200
3,848
86
606
906
6,603
8,342
35
117
284
1,875
302
2,236
1,417
1,388
4,836
2,707
469
261
559
2,824
88,652
APP-14
-------
\ ^ " , ;
State
AR
CA
CT
GA
IA
IL
IN
KS
MA
MD
MI
MN
MO
NC
ND
NE
NH
NJ
NY
OH
OR
PA
SC
SD
UT
VA
WV
OTHER
U.S.
^iii* »
Produced
1000 h
18,000
26,500
30
2,400
7,800
1,700
12,900
227
150
135
3,000
38,500
16,500
47,900
1,200
1,772
26
100
343
3,600
1,650
7,900
5,570
2,370
3,900
16,300
2,300
19,250
242,023
Tif/HEfiJAttt
Average
Pop.
4,000
5,889
7
533
1,733
378
2,867
50
33
30
667
8,556
3,667
10,644
267
394
6
22
76
800
367
1,756
1,238
527
867
3,622
511
4,278
53,783
5 EMISSIONS
Mass
(mt)
13,520
19,904
23
1,803
5,859
1,277
9,689
171
113
101
2,253
28,918
12,393
35,978
901
1,331
20
75
258
2,704
1,239
5,934
4,184
1,780
2,929
12,243
1,728
14,459
181,786
i»«;*,'
vs
(mt/day)
123
181
0
16
53
12
88
2
1
1
21
263
113
327
8
12
0
1
2
25
11
54
38
16
27
111
16
132
1,654
M0*?$
f of B0
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
Methane
(mt/yr)
892
1,313
1
119
387
84
639
11
7
7
149
1,908
818
2,374
59
88
1
5
17
178
82
392
276
117
193
808
114
954
11,996
APP-15
-------
;* : I&BM »? XEXttNnt ftMfiMttfflt'feft &S.'-i«Mt» * " , " * ''' '£'?'
1000 head
St.
AK
AZ
CA
CO
CT
IA
ID
IL
IN
KS
KY
LA
MA
MA
MD
MI
MN
MO
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
SD
TN
TX 1
UT
VA
VT
WA
WI
WV
WY
OTHER
U.S. 7
1 vr
Ewes
1
185
632
355
6
285
220
98
68
135
25
12
11
10
23
72
170
87
410
10
111
97
8
9
384
70
52
165
94
280
91
430
8
,280
405
95
11
51
60
62
555
41
,173
& older under 1 vr.
Rams/
Weth.
1
9
24
13
1
12
6
5
5
8
2
2
1
1
3
4
8
5
14
1
5
4
1
1
21
2
2
7
5
14
10
12
1
70
12
5
1
4
3
3
23
4
333
Ewes
0
26
100
64
1
48
46
19
11
16
4
2
2
2
7
10
40
14
105
2
22
15
2
2
70
12
14
24
14
42
22
70
1
270
57
12
3
14
11
10
125
6
1,337
Rams/
Weth.
0
19
24
13
1
5
5
4
2
5
2
1
1
1
2
3
7
3
9
1
5
3
1
3
10
1
13
4
7
14
11
8
0
110
6
3
2
5
2
7
17
6
345
On
Feed
0
160
380
0
10
98
14
9
65
0
0
0
0
0
0
26
16
30
50
21
46
2
0
31
0
0
0
16
0
70
0
170
23
0
43
0
0
8
0
117
0
0
1,450
Mass
(mt)
1,325
22,325
70,356
34,407
872
29,867
21,613
9,903
8,357
13,037
2,476
1,298
1,135
1,034
2,554
7,647
17,389
9,263
41,789
1,511
12,093
9,377
820
1,832
37,656
6,655
5,647
16.184
9,271
29,036
9,867
45,046
1,378
129,830
39,175
9,129
1,216
5,613
5,880
9,136
54,779
4,304
742,081
VS
(mt/day)
12
205
647
317
8
275
199
91
77
120
23
12
10
10
24
70
160
85
385
14
111
86
8
17
346
61
52
149
85
267
91
414
13
1,194
360
84
11
52
54
84
504
40
6,827
f of B0
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
Methane
(mt/yr)
100
1,090
3,330
1,450
50
1,350
930
430
410
550
100
50
50
40
110
350
750
420
1,810
100
550
400
30
110
1,590
280
240
700
390
1,290
420
2,060
80
5,490
1,700
390
50
240
250
500
2,310
180
32,739
APP-16
-------
State
AK
AL
1 AR
| AZ
D CA
D C0
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
MM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
U.S.
=====
Number
1000 h
0
11
14
100
29
7
1
0
12
20
1
7
3
8
7
9
10
4
3
3
1
21
7
17
5
2
9
2
4
1
3
135
1
9
17
70
11
9
0
6
2
29
1750
2
8
1
7
9
4
4
2,396
-"— "• — —*S g=Sg
Mass
(mt)
14
676
877
6,400
1,837
467
86
30
760
1,300
60
473
167
528
469
565
614
249
176
208
80
1,370
421
1,105
341
127
548
103
279
92
169
8,640
86
599
1,074
4,480
687
582
31
405
119
1,868
112,000
97
517
62
466
566
256
228
153,354
~
VS
(mt/day)
0
6
8
61
17
4
1
0
7
12
1
4
2
5
4
5
6
2
2
2
1
13
4
10
3
1
5
1
3
1
2
82
1
6
10
43
7
6
0
4
1
18
1,064
1
5
1
4
5
2
2
1,457
.
f of B0
0.10
0.10
0.10
0.11
0.10
0.10
0.10
0.10
0.11
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
Methane
(mt/year)
1
26
34
262
72
18
3
1
33
51
2
18
7
21
18
22
24
10
7
8
3
53
16
43
13
5
21
4
11
4
7
337
3
23
42
175
27
23
1
16
5
73
4,372
4
20
2
18
22
10
9
6,002
APP-17
-------
; f wo* wo: wtfam 00*06** ** o; &•*» ; / ' *;:;
Number Mass
State
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
U.S.
1000
2
35
40
71
149
79
7
3
61
34
4
59
56
55
53
56
90
39
12
27
6
57
54
74
28
72
30
32
51
4
23
52
18
53
75
96
59
65
1
17
45
62
233
40
48
8
58
48
15
48
2,404
h (mt)
837
15,606
18,101
31,748
66,932
35,482
3,115
1,363
27,387
15,332
1,598
26,702
25,247
24,964
23,704
25,019
40,456
17,423
5,375
11,931
2,846
25,576
24,436
33,496
12,681
32,584
13,476
14,579
23,069
1,819
10,420
23,341
7,973
24,046
33,921
43,390
26,368
29,341
459
7,546
20,378
28,086
104,941
17,780
21,686
3,415
25,978
21,501
6,794
21,563
1,081,807
VS
(mt/day)
8
156
181
318
669
355
31
14
274
153
16
267
253
250
237
250
405
174
54
119
29
256
244
335
127
326
135
146
231
18
104
233
80
241
339
434
264
293
5
76
204
281
1,049
178
217
34
260
215
68
216
10,818
f of B0
0,10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.13
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.14
0.10
0.10
Methane
(mt/year)
70
1,240
1,440
2,530
5,340
2,830
250
110
2,730
1,220
130
2,130
2,010
1,990
1,890
2,000
3,230
1,390
430
950
230
2,040
1,950
2,670
1,010
2,600
1,070
1,160
1,840
150
830
1,860
640
1,920
2,710
3,460
2,100
2,340
40
600
1,630
2,240
8,370
1,420
1,730
270
2,070
2,320
540
1,720
87,440
APP-18
-------
DUSKS,
Animal
Ducks
Mules
Donkeys
Number
(1000 head)
7,000
1
4
Total
Mass
(mt)
9,800
450
1,200
VS
(mt/day)
182
5
12
f of B0
0.10
0.10
0.10
Methane
(mt/yr)
1,405
36
96
APP-19
-------
APP-20
-------
WEfGHTS POR
APP-21
-------
APPENDIX C: LIVESTOCK CATEGORY WEIGHTS FOR SELECTED COUNTRIES
Data were obtained for livestock populations by age and weight categories for many
developed countries from Meat and Dairy Products (1988). The appropriate live animal mass
assigned to each category was taken from Taiganides and Stroshine (1971), and the average
weight for the given animal type was then calculated for each country. These data are
summarized in Table C1 and all of the data used are given in Tables C2 through C14. Some of
the categories listed by some countries were not assigned a live animal mass in Taiganides and
Stroshine (1971); the assumed live animal masses for all cases are included in Tables C2 through
C14. Australia was not included in obtaining the average sheep mass to avoid skewing the
average from their large sheep population and unusually high average mass. The former Soviet
Union was not included in the average cattle mass to avoid skewing the average from their large
cattle population combined with their limited detail about their cattle population.
% / ":"":*i&mM. diV:; 8£V£iOF.EIM
SO^ER;
Country Cattle
Australia (A)
Austria
Belgium
Denmark
France
Western Germany
Ireland
Italy
Netherlands
South Africa
United Kingdom
Soviet Union (B)
Yugoslavia
Mass Weighted Average
A Australia excluded from
B As defined before August
for cattle.
No Data.
343
310
393
308
365
303
349
319
295
480
369
349
383
361
CES AVERAGE
Dairy
.
-
-
-
-
-
655
-
-
619
657
-
-
649
LIVESTOCK HA,
Sheep
72
59
67
-
-
71
72
-
54
-
66
-
69
67
5$ \//
Pigs
62
52
60
55
59
59
55
64
58
.
57
-
66
59
average for sheep.
1991.
Sources : Heat and Dairy Products
(1971).
Soviet Union excluded
(1988) and
from average
Taiganides and Stroshine
APP-22
-------
: "}"- -;, " ,:' '",'"? 3*BX2 C2'j
•• ' ',
Livestock
CATTLE
Cows & Heifers
Other meat cattle
Calves (under 1 yr)
Totals:
Average Weight:
SHEEP
Ewes (over 1 yr)
Rams/We th. (> 1 yr)
Lambs and hoggets
Totals:
Average Weight:
PIGS
Breeding sows
Others
Totals:
Average Weight;
' ' 1" ' ', ' , TABLE €3
•. ' fV* ' ' j'*, \ J "' ' '
Livestock
CATTLE
Under 3 mo
3 mo-1 yr old
1-2 yr old
Cows over 2 yrs
Totals:
Average Weight:
SHEEP
Under 1 yr
Over 1 yr
Totals:
Average Weight:
PIGS
Under 2 mo
2 mo & over
For slaughtering
6 mo & over
Totals:
Average Weight:
>BSfRAL:&
"
Number
1000 h
10,560
5,510
5.500
21,570
81,500
41,710
35,860
159,070
350
2,290
2,640
: AUSTRIA
Number
1000 h
281
559
628
156
1,624
112
147
259
1,204
1,821
502
406
3,933
k LIVESTOCK DATA; 1987
'
Weight Total Weight
(kg) (kg)
440 4,646,400
318 1,752,180
181 995,500
7,394,080
343 kg
86 7,009,000
82 3,420,220
27 968,220
11,397,440
72 kg
171 59,850
45 103,050
162,900
62 kg
'LIVESTOCK BATA t^SI '- """ '' ' , \
'•• , ^;,,;~ , .. , „
Weight Total Weight
(kg) (kg)
75 21,075
225 125,775
400 251,200
680 106,080
504,130
310 kg
27 3,024
84 12,348
15,372
59 kg
11 13,244
45 81,945
75 37,650
181 73,486
206,325
52 kg
APP-23
-------
Livestock
CATTLE
Calves (under 1 yr)
Cattle (1-2 yr)
Cattle (over 2 yr)
Totals:
Average Weight:
SHEEP
Sheep (under 1 yr)
Rams/Weth. (> 1 yr)
Ewes (over 1 yr)
Totals :
Average Weight:
PIGS
Pigs (under 20 kg)
Pigs (20-50 kg)
Pigs (Fattening)
Boars
Sows
Totals :
Average Weight:
: - ;^^: «BW*,«5
Livestock
CATTLE
Calves (under 1 yr)
Male (1-2 yr)
Female (1-2 yr)
Cows/Bulls over 2 yr
Totals:
Average weight:
PIGS
Pigs (under 20 kg)
Pigs (20-50 kg)
Pigs (Fattening)
Boars
Sows
Totals:
Average Weight:
Number
1000 h
798
651
1,531
2,980
42
6
81
129
1,558
1,626
2,080
24
682
5,970
: DENMARK
Number
1000 h
883
55
396
182
1,516
2,730
2,893
2,393
39
993
9,048
Weight
(kg)
181
400
500
393
27
82
86
67
11
35
75
181
181
60
Weight
(kg)
181
318
420
680
308
11
35
75
181
181
55
Total Weight
(kg)
144,438
260,400
765,500
1,170,338
kg
1,134
492
6,966
8,592
kg
17,138
56,910
156,000
4,344
123,442
357,834
kg
>dt jj&frk i$&?, ;, i- - ', v ,
Total Weight
(kg)
159,823
17,490
166,320
123,760
467,393
kg
30,030
101,255
179,475
7,059
179,733
497,552
kg
APP-24
-------
Livestock
CATTLE
Calves under 1 yr
Males 1-2 yr
Females 1-2 yr
Bulls
Cattle over 2 yr
Totals :
Average Weight:
PIGS
Pigs under 20 kg
Pigs 20-50 kg
Pigs fattening
Boars
Sows
Totals:
Average Weight:
'' -'' -'»'-' '':'* ""' ' - ;"fATO"o
;*v ,-. A ; ,a>', '••.J' ", , ,
Livestock
CATTLE
Cattle under 1 yr
Male 1-2 yr
Female slaughter
Female breeding
Bulls & Steers
Heifers slaughter
Heifers breeding
Cows
Totals:
Average Weight:
PIGS
Boars
Pigs under 20 kg
Pigs 20-50 kg
Pigs over 50 kg
Sows in pig
Sows other
Other not in pig
Totals :
Number
1000 h
5,366
1,231
2,848
608
5,159
15,212
2,801
3,451
4,454
67
1,142
11,915
"¥*~ *fViT\
',;% ;:,: -
Number
1000 h
2,511
903
164
972
113
48
655
430
5,796
46
1,811
1,943
4,797
575
155
82
9,409
Weight
(kg)
181
318
420
680
500
365
11
35
75
181
181
59
I^J^VESTtX
Weight
(kg)
181
318
420
420
355
420
420
680
319
181
11
35
75
181
181
115
64
Total Weight
(kg)
971,246
391,458
1,196,160
413,440
2,579,500
5,551,804
kg
30,811
120,785
334,050
12,127
206,702
704,475
kg
j*c; '»iiii; 'iw ' '- v' , < ,Z- '-.-<-,*
-'"'" * " ,* :;' 'Is '" ?'Ar r
Total Weight
(kg)
454,491
287,154
68,880
408,240
40,115
20,160
275,100
292,400
1 , 846 , 540
kg
8,326
19,921
68,005
359,775
104,075
28,055
9,430
597,587
kg
APP-25
-------
,„.. ,\ TABLE C8i ,fi£S$
,
,; ,,
Number
Livestock 1000 h
CATTLE
Cows over 2 yr
Heif. breed. >2 yr
Heif. slaught.>2 yr
Bulls & Steers
Cattle 1-2 yr
Cattle 6 mo-1 yr
Calves under 6 mo
Totals :
Average Weight:
SHEEP
Ewes breeding
Rams breeding
Wethers and others
Sheep under 1 yr
Totals:
Average Weight:
PIGS
Boars
Young sows in pig
Other sows in pig
Young sows not in pig
Other sows not in pig
Pigs fattening
Young pigs <20 kg
Young pigs 20-50 kg
Totals:
Average Weight:
199
635
64
161
3,502
2,940
2,309
9,810
1,003
33
35
343
1,414
106
331
1,396
265
660
8,477
6,558
5,876
23,669
tisv :f TtnM
EttJalX ii£VJ!ia
Weight
(kg)
680
600
500
355
400
250
100
303
86
82
55
27
71
181
115
181
115
181
75
35
11
59
W/WW •" TV A*i*jk •• 4 &ft^ ' ' " < '•ZfVf:&&"f<'
£ijru&. lfA.l& iyOf z, r'rr "; , *4%;,},
Total Weight
(kg)
135,320
381,000
32,000
57,155
1,400,800
735,000
230,900
2,972,175
kg
86,258
2,706
1,925
9,261
100,150
kg
19,186
38,065
252,676
30,475
119,460
635,775
229,530
64,636
1,389,803
kg
APP-26
-------
p/ 1 ^ >;* ~>: x v "* v ; - V&™ 39
M."1 , ™ TO •• - ••••'••, •••• -' ' ••
Livestock
CATTLE
1 Cows
|| Heifers in calf
Bulls breeding
OTHER CATTLE
1 Male over 2 yr
Female over 2 yr
Male 1-2 yr
Female 1-2 yr
Male under 1 yr
Female under 1 yr
Totals:
Average Weight:
SHEEP
Ewes breeding
Rams breeding
Other Sheep
Totals:
Average Weight:
PIGS
Gilts in pig
Sows in pig
Other sows
Gilts not served
Boars
Other over 80 kg
Other 50-80 kg
Other 20-50 kg
Other under 20 kg
Totals:
Average Weight:
DAIRY CATTLE
Heifers
Cows
Totals:
|| Average Weight:
f 'Tmm>
''•• ''' :: ^\
Number
1000 h
421
50
17
623
213
819
459
727
605
3,934
2,402
67
783
3,252
14
62
23
9
5
76
259
295
217
960
202
1,444
1,646
=======
UVESTC
Weight
(kg)
680
500
680
400
500
318
420
181
181
349
86
82
27
72
115
181
181
115
181
85
65
35
11
55
476
680
655
=====
K3X, M*PA 198? '
, /.ft I,::'"'",: ' , ,
Total Weight
(kg)
286,280
25,000
11,560
249,200
106,500
260,442
192,780
131,587
109,505
1,372,854
kg
206,572
5,494
21,141
233,207
kg
1,610
11,222
4,163
1,035
905
6,460
16,835
10,325
2,387
52,555
kg
96,152
981,920
1,078,072
kg
APP-27
-------
-- \ TABLE Cl<2h SETHERLANBS' LIVESTOCK DATA 3.387 '; . ' ,,
Livestock
CATTLE
Calves under 1 yr
Male 1-2 yr
Female 1-2 yr
Bulls over 2 yr
Cows
Totals:
Average Weight:
SHEEP
Rams
Ewes
Lambs
Totals:
Average Weight:
PIGS
Pigs under 20 kg
Pigs 20-50 kg
Pigs 50-80 kg
Pigs over 80 kg
Boars
Sows
Totals :
Average Weight:
Number
1000 h
1,449
164
712
12
174
2,511
11
389
468
868
4,913
2,906
2,876
1,927
58
1,546
14 226
Weight
(kg)
181
318
420
680
680
295
82
86
27
54
11
35
65
97
181
181
58
Total Weight
(kg)
262,269
52,152
299,040
8,160
181,320
739,941
kg
902
33,454
12,636
46,992
kg
54,043
101,710
186,940
186,919
10,498
279,826
819,936
kg
•. < J J : '' r ^
', ',,'""-""-, 3JA&PJ 613jj ^
-;' ••$•-.'''
Livestock
CATTLE
Bulls
Cows over 2 yr
Heifers 1-2 yr
Calves
Other oxen, tollies
Totals:
Average Weight:
DAIRY CATTLE
Cows
Heifers
Totals:
Average Weight:
SGtfT |t AF&ICA I^ES^FOCK DATA ,t$8J '- , - \
--
Number
1000 h
177
3,133
996
1,463
930
6,699
849
361
1,210
Weight
(kg)
680
680
420
181
300
480
680
476
619
..
Total Weight
(kg)
120,360
2,130,440
418,320
264,803
279,000
3,212,923
kg
577,320
171,836
749,156
kg
APP-28
-------
Number Weight Total Weight
Livestock 1000 h (kg) (kg)
CATTLE
Beef Cows in milk
Beef Cows in calf
Beef Heifers
Bulls over 2 yr
Bulls 1-2 yr
Other over 2 yr
Other 1-2 yr
Other 6 mo-1 yr
Other under 6 mo
Totals :
11 Average Weight:
SHEEP
Ewes breeding
Rams in service
Other
Lambs under 1 yr
Totals:
1 Average Weight:
PIGS
Sows in pig
Gilts in pig
Other sows
Boars in service
Gilts 50 kg & over
Barren sows
Other over 110 kg
Other 80-110 kg
Other 50-80 kg
Other 20-50 kg
Other under 20 kg
Totals :
Average Weight:
DAIRY CATTLE
Dairy cows in milk
Cows not in milk
Dairy heif .in calf
Totals:
Average Weight:
710
654
221
54
18
711
2,740
1,735
1,564
8,407
17,375
487
729
9,228
27,819
536
104
182
45
79
14
67
613
1,822
2,270
2,183
7,915
2,456
596
390
3.442
=======
680
680
420
680
420
500
400
250
100
369 kg
86
82
55
27
66 kg
181
115
181
181
115
181
115
95
65
35
11
57 kg
680
680
476
657 kg
=====
482,800
444,720
92,820
36,720
7,560
355,500
1,096,000
433,750
156,400
3,106,270
1,494,250
39,934
40,095
249,156
1,823.435
97,016
11,960
32,942
8,145
9,085
2,534
7,705
58,235
118,430
79,450
24,013
449,515
1,670.080
405,280
185 , 640
2,261,000
==================
APP-29
-------
'CABLE
^ •. " ••< ..> •. v r , ....
Livestock
CATTLE
Cattle excl.cows
Cows assume &
Totals:
Average Weight:
- /,. - ',* " > •• /-" - ''•-'> ,'«;;*;; - ",- i't
Number Weight Total Weight
1000 h (kg) (kg)
78,500 300 23,550,000
heif 42,000 440 18,480,000
120,500 42,030,000
349 kg
As defined before August 1991.
; ' " , \ fAELE G
Livestock
CATTLE
Cows & Heifers
Other
Totals :
Average Weight:
SHEEP
Breeding sheep
Other
Totals :
Average Weight:
PIGS
Sows
Other
Totals :
Average Weight:
1 &.**' 1VTWlfii*?T.A.1FFA T TvTT/• > '•'•'
^^' •- ^ ^ ^ j j j. j. Vf fS*
"• "• f f v fv f •'f-t- -f -f -• ffj.'*
Number
1000 h
2,902
1,979
4,881
5.804
2,020
7,824
1,385
6,937
8,322
Weight
(kg)
440
300
383
84
27
69
171
45
66
Total Weight
(kg)
1,276,880
593,700
1,870,580
kg
487,536
54,540
542,076
kg
236,835
312,165
549.000
kg
APP-30
-------
-";•;
APP-31
-------
APPENDIX D: CANADA ANIMAL WASTE METHANE PRODUCTION
The methane emissions from livestock and poultry manure in Canada were estimated as
described in Appendix B for the United States. The estimates for Canada are summarized in
Table D1. The livestock populations and other details for Canadian methane emissions are
shown in Tables D2 through D8. The waste management system usage for most provinces was
determined from a request for data as shown in Figure G1. For most provinces a form was
completed by a provincial agricultural specialist. Completed forms were not obtained for
Newfoundland, Prince Edward Island, or Saskatchewan. System usage estimates for these
provinces was supplied by Patni (1989). The livestock populations were taken from the
Handbook of Selected Agricultural Statistics - 1988 (Agriculture Canada 1989). Methane
emissions for each province were calculated using equations B1 and B2.
Abbreviations used in these tables are:
Heif.
Heif. Slaug. =
f-ofB0
VS
Meth
heifers
heifers for slaughter
Percent of B(
volatile solids produced per day
methane emissions
0 that is achieved (f of B0 = MCF
CAF).
™; , ; "L,; TA&fcEDIt CANADA ryJrffiAM Eft/ft&SiQNS SUMMARY l;
: ,., %l! *....*, i
Province
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland
Nova Scotia
Ontario
Prince Edward 1.
Quebec
Saskatchewan
Total
Beef
39,786
7,028
10,493
891
46
891
18,053
801
13,039
25,000
116,029
Dairy
8,226
6,387
4,307
1,566
225
1,697
25,770
1,311
28,670
3,172
81,332
Swine Sheep
12,002
1,982
23,753
2,438
202
1,212
25,686
1,530
23,404
10,790
102,998
Note: 'Other* is the sum of goats, ducks, horses,
populations
(FAO, 1989).
(Weighted among
409
114
49
20
15
82
455
14
262
109
1,531
Chick.
756
790
456
186
93
267
2,614
10
1,981
319
7,472
Layers
542
197
446
58
123
65
1,896
46
740
280
4,395
Turkey
410
387
373
69
4
105
1,352
4
827
196
3,728
••
Other
4,350
770
1,150
100
10
100
1,970
90
1,420
2,730
12,690
^
Total
66,481
17,656
41,027
5,329
720
4,419
77,797
3,805
70,344
42,597
330,174
and mules; taken from FAO
provinces by the
same ratios
as beef cattle.)
APP-32
-------
"f:>"?^ TABtEBfc CANADA METHANE
EMISSIONS FROM BEEF CATTtE \
1000 head
Province
Alberta ,
British Columbia
Manitoba
New Brunswick
Newfoundland
Nova Scotia
Ontario
Prince Edward I.
Quebec
Saskatchewan
Total
Steers
490
46
95
8
<1
9
350
19
58
210
1,286
Calves
1,340
228
375
26
2
31
540
25
374
760
3,702
Bulls
90
15
21
2
<1
2
26
1
26
47
229
Cows
1,360
223
380
19
1
23
350
11
170
810
3,352
Heif.
52
40
29
12
1
16
240
9
248
20
668
Heif.
Slaug.
Mass
mt
2741,516,734
24
44
4
<1
6
230
8
20
85
6954
243,580
400,019
28,316
1,526
33,983
655,450
26,543
331,398
828,735
,066,284
VS
mt/day
10,920
1,754
2,880
204
11
245
4,719
191
2,386
5,967
29,277
'ofBo
0.080
0.080
0.080
0.096
0.092
0.080
0.084
0.092
0.120
0.092
Meth
mt/year
39,786
7,028
10,493
891
46
891
18,053
801
13,039
25,000
116,029
+ **#£ ^vi™'^-. -. •- -•-•.••..•
Province
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland
Nova Scotia
Ontario
Prince Edward I.
Quebec
Saskatchewan
Total
i CANADA METHANE £Ml$SJ0N$ FROM DAIRY CAttt£ W&NURf ^ ~
1000 head
Cows
124
75
66
27
4
34
465
21
568
53
14,365
Heifers
52.0
40.0
29.5
12.0
0.8
16.0
240.0
9.7
248.0
20.0
688.0
Mass
mt
109,072
70,040
58,922
23,936
3,237
30,464
430,440
18,829
504,288
45,560
1,294,788
VS
mt/day
1,091
700
589
239
32
305
4304
188
5,043
456
12,948
fofB0
0.130
0.157
0.126
0.113
0.120
0.096
0.103
0.120
0.098
0.120
Methane
mt/yr
8,226
6,387
4,307
1,566
225
1,697
25,770
1,311
28,670
3,172
81,331
APP-33
-------
TABLE D4: CANADA METHANE EMISSIONS FROM SWINE MANURE
Breeding Pigs
Province
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland
Nova Scotia
Ontario
Prince Edward 1.
Quebec
Saskatchewan
Total
Boars
1000 h
12
2
8
<1
<1
<1
23
<1
14
7
68
Sows
1000 h
175
23
120
10
2
13
355
14
284
91
1,086
' >''/'S'v':
Market Pigs
Pigs
<20kg
488
71
353
34
5
40
1,025
42
962
247
3,267
Pigs
45-60kg
542
71
371
26
6
46
1,032
39
956
256
3,344
Pigs
> 60 kg
518
70
348
25
4
44
935
31
864
244
3082
Mass
mt
103,889
13,846
70,775
5,317
958
8,325
198,578
7,266
174,472
50,947
634,373
VS
mt/day
893
119
609
46
8
72
1,708
63
1,501
438
5,456
fofB0
0.154
0.191
0.448
0.613
0.282
0.195
0.173
0.281
0.179
0.283
Methane
mt/yr
12,002
1,982
23,753
2,438
202
1,212
25,686
1,530
23,404
10,790
102,998
i j ;TABLE D$; : CANADA METHANE EMISSIONS FROM; SHEEP MANURE ; ; ^
^ ........
Province
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland
Nova Scotia
Ontario
Prince Edward 1.
Quebec
Saskatchewan
Total
Sheep (1000
>1 yr
88
26
12
5
4
19
114
3
70
25
366
*
head)
<1 yr
110
28
10
4
4
19
87
3
41
26
332
% % %
Mass
mt
11,572
3,229
1,388
572
435
2,327
12,882
384
7,420
3,097
43,306
% 11 1-. v •:
VS
mt/day
106
30
13
5
4
21
119
4
68
28
398
fofB0
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
A A- /
Methane
mt/yr
409
114
49
20
15
82
455
14
262
109
1,531
APP-34
-------
;,. -TABtE CMfc: CAN&BA ^ETHANE EM&&ONS FHOH8 BROILER MANURE (AHO OTHER
-A ^;h-: f, "\r;ii* CHICKENS, EXCEPT LAYERS), ; „;"/:»-:' ; ,5
Province
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland
Nova Scotia
Ontario
Prince Edward 1.
Quebec
Saskatchewan
Total
Broilers &
Chickens
1000 h
8,516
8,900
5,137
2,090
1,047
3,010
29,449
116
22,318
3,595
84178
Mass
mt
7,664
8,010
4,623
1,881
942
2,709
26,504
104
20,086
3,236
75,760
VS
mt/day
130
136
79
32
16
46
451
2
342
55
1,288
/ofB0
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
Methane
rrrt/yr
756
790
456
186
93
267
2,614
10
1,981
319
7,472
:;' 1 tA8fc£tm CANADA MEtHANE E0H$S|ON$
.. % -.
Province
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland
Nova Scotia
Ontario
Prince Edward Island
Quebec
Saskatchewan
Total
•- *
Layers
1000h
1,984
2,779
2,513
514
411
912
8,615
152
3,723
933
22,536
Mass
mt
3,571
5,002
4,523
925
740
1,642
15,507
274
6,701
1,679
40,565
FROM CAGED i
"• '"'"''
VS
mt/day
43
60
54
11
9
20
186
3
80
20
487
LAVFR MANUFH
fofB0
0.154
0.040
0.100
0.064
0.169
0.040
0.124
0.169
0.112
0.169
»
Methane
mt/yr
542
197
446
58
123
65
1,896
46
740
280
4,395
APP-35
-------
I ; »- , TWKk Bfc CANAOA METHANE EMISSIONS F«0lft WflKE¥;MANUR^
Province
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland
Nova Scotia
Ontario
Prince Edward 1.
Quebec
Saskatchewan
Total
Turkeys
1000 h
1,143
1,078
1,040
193
12
293
3,766
10
2,304
547
10,386
Mass
mt
7,772
7,330
7,072
1,312
82
1,992
25,609
68
15,667
3,720
70,625
VS
mt/day
71
67
64
12
<1
18
233
<1
143
34
643
fofB0
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
:;;::'Jgi
Methane
mt/yr
410
387
373
69
4
105
1,352
4
827
196
3,728
APP-36
-------
APPENDIX E: GLOBAL ANIMAL WASTE METHANE PRODUCTION
APP-37
-------
APPENDIX E: GLOBAL ANIMAL WASTE METHANE PRODUCTION
The methane production rates from animal waste in each country are given in Tables E1
through E14. Methane emissions were calculated using Equations 3.1, 3.2, 3.3, and 3.4 in
Chapter 3. The following data are necessary to estimate emissions:
Volatile Solids (VS) production is calculated with the following data:
Number of animals (N) listed in Tables E1 to E14;
Typical Animal Mass (TAM) listed in Exhibit 5;
Volatile solids production per head listed in Exhibit 6; and
Volatile solids production per unit of animal mass listed in Exhibit 5.
• Maximum Methane Producing Capacity listed in Exhibit 10.
Methane Conversion Factors (MCFs) for each waste system listed in Exhibit 12.
• Climate Adjustment Factors (CAFs) for each animal waste system are listed in
Exhibit 13. All countries not listed are assigned a CAP of 1.
Waste System Usage (WS%1 information is summarized by region in Exhibits 17
to 23, and 25. Appendix I lists detailed waste system usage for the major animal
types for each country of the world. Appendix H lists this information for each
state in the U.S.
The following abbreviations are used in the :
1000h = 1000 head
VS = volatile solids production (mt/day)
fof BQ = Fraction of B0 that is achieved (f of B0 = MCF • CAF).
Note: 0 £ f of BQ * 1.
Note: the density of methane is assumed to be 0.662 kg/m3 (72°F, 1 atm).
APP-38
-------
| TABLE lit ME*NAN£ EJVHSStQNS F&0M tfON-DAIBV
"X.— A: ,..^,,.^:.,.._.'^..,: :..- v :; - *: :, " ^ ,-
Country
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
OCEANIA
Australia
Fiji
' *J'
New Caledonia
New Zealand
Papua New Guinea
Vanuatu
Total
Number
(1000 h)
9,931
89,268
99,199
1,627
2,002
1,459
899
11,863
9,947
455
4,136
5,774
2,606
599
970
3,233
1,102
1,044
8,797
56,513
426
1,001
3,256
3,718
1,084
5,382
5,120
78,593
2,286
100,866
21,290
130
118
5,868
99
105
27,610
Total Manure
mt/day
235,844
2,371,156
2,607,000
29,200
45,551
26,016
18,789
250,684
174,491
9,509
83,569
106,637
44,508
12,519
20,273
67,570
23,032
21,820
187,932
1,122,099
8,903
20,921
68,050
77,706
22,656
112,484
107,008
1,587,991
50,689
2,056,408
422.774
1,625
2,466
122,641
1,238
1,313
552,057
VS
mt/day
29,277
294,351
323,628
3,621
5,648
3,226
2,330
31,085
21,637
1,179
10,363
13,223
5,519
1,552
2,514
8,379
2,856
2,706
23,304
139,140
1,104
2,594
8,438
9,636
2,809
13,948
13,269
196,911
6,285
254,995
52,424
244
306
15,208
186
197
68,564
CATTtE WASTE
fofB0
0.090
0.160
0.135
0.100
0.096
0.160
0.160
0.160
0.125
0.181
0.190
0.140
0.110
0.120
0.148
0.172
0.160
0.105
0.121
0.160
0.180
0.082
0.092
0.102
0.100
0.111
0.100
0.100
0.100
0.100
0.100
0.100
Methane
mt/yr
116,029
1,379,044
1,495,073
46,213
60,825
25,733
17,841
396,733
276,150
15,067
103,325
191,188
83,645
17,336
22,058
80,202
33,716
37,014
297,421
1,704,467
9,269
25,139
107,697
138,350
18,286
102,360
108,081
1,574,132
55,444
2,138,758
418,177
589
2,439
121,308
449
476
543,438
APP-39
-------
s
TABUS £1; MEtHANE E»«SSIOr*S FROM
•;
Country
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
EAST & SUBSAHARAN
Burundi
Central African Republic
Chad
Ethiopia
Kenya
Mali
Mauritania
Niger
Rwanda
Somalia
Tanzania
Uganda
Zaire
Total
%
Number
(1000 h)
47,952
5,375
116,033
2,731
20,907
1,880
4,401
1,904
3,206
886
1,740
158
1,450
2,491
241
24,800
1,520
1,393
7,675
3,197
487
9,858
11,486
271,771
AFRICA
280
2,268
3,654
27,125
7,545
4,264
978
2,970
500
4,000
10,700
2,830
1,392
68,506
V-.
Total Manure
mt/day
599,400
67,188
1,450,413
34,138
261,338
23,500
55,013
23,800
40,075
11,075
21,750
1,975
18,125
31,138
3,013
310,000
19,000
17,413
95,938
39,963
6,088
123,225
143,575
3,397,138
3,500
28,350
45,675
339,063
94,313
53,300
12,225
37,125
6,250
50,000
133,750
35,375
17,400
856,325
NON-DAIRY CATTLE WASTED
vs
mt/day
89,910
10,078
217,562
5,121
39,201
3,525
8,252
3,570
6,011
1,661
3,263
296
2,719
4,671
452
46,500
2,850
2,612
14,391
5,994
913
18,484
21,536
509,571
525
4,253
6,851
50,859
14,147
7,995
1,834
5,569
938
7,500
20,063
5,306
2,610
128,449
f
fofB0
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.098
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.050
0.050
0.050
0.050
0.050
0.100
0.050
0.100
0.100
0.100
f * r •> f >w
Methane
mt/yr
217,332
24,361
525,895
12,378
94,756
8,521
19,947
8,629
14,531
4,016
7,728
716
6,572
11,290
1,092
112,401
6,889
6,313
34,785
14,490
2,207
44,679
52,058
1,231,586
1,269
10,279
8,280
61,469
17,098
9,663
2,216
6,730
2,266
9,065
48,495
12,826
6,309
195,967
APP-40
-------
If '' % v s
•t- f j-
:? JtA&if m , METHANE; EMISSIONS FROM
1 " r ' ' ' " ' ' "ft
Country
WEST & SOUTHERN AFRICA
Angola
1 Benin
Botswana
Burkina Faso
Cameroon
Cote d'lvoire
The Gambia
Ghana
Guinea
Guinea-Bissau
Lesotho
Madagascar
Malawi
1 Mozambique
Namibia
Nigeria
Senegal
Sierra Leone
South Africa
Swaziland
Togo
Zambia
Zimbabwe
Total
f •> •• -f *
Number
(1000 h)
3,105
798
2,060
2,348
4,374
806
270
1,105
1,575
281
445
10,541
905
970
1,881
10,980
2,348
280
10,900
497
252
2,414
5,557
64,692
, ,
Total Manure
mt/day
38,813
9,975
25,750
29,350
54,675
10,075
3,375
13,813
19,688
3,513
5,563
131,763
11,313
12,125
23,513
137,250
29,350
3,500
302,905
6,213
3,150
30,175
69,463
975,305
MON-pAIRY
"
vs
mt/day
5,822
1,496
3,863
4,403
8,201
1,511
506
2,072
2,953
527
834
19,764
1,697
1,819
3,527
20,588
4,403
525
37,560
932
473
4,526
10,419
138,420
CATTiM WASTE
; ', ' ''•'
fofBQ
0.100
0.100
0.050
0.050
0.100
0.100
0.100
0.100
0.095
0.100
0.100
0.100
0.070
0.100
0.050
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
-
Methane
mt/yr
14,073
3,617
4,668
5,321
19,824
3,653
1,224
5,008
6,781
1,274
2,017
47,775
2,871
4,396
4,263
49,764
10,642
1,269
299,611
2,253
1,142
10,941
25,186
527,573
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
Egypt
9f r
Iran
Iraq
Israel
Jordan
Kuwait
Libya
/**
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Republic
1 Total
2,430
953
470
6,000
1,220
215
11
10
166
1,740
94
200
19,050
420
362
7,000
705
41,046
30,375
11,913
5,875
75,000
15,250
4,493
138
125
2,075
21,750
1,175
2,500
238,125
5,250
4,525
87,500
8,813
514,881
4,556
1,787
881
11,250
2,288
557
21
19
311
3,263
176
375
35,719
788
679
13,125
1,322
77,115
0.050
0.100
0.063
0.050
0.058
0.100
0.050
0.100
0.050
0.100
0.050
0.050
0.050
0.050
0.050
0.100
0.050
5,507
4,319
1,331
13,597
3,179
4,445
25
45
376
7,886
213
453
43,170
952
820
31,726
1,598
119,643
APP-41
-------
TAki £1; METHANE EMISSIONS FB0M NON^AIftY CAttCM WASm ?
" " - '•
Country
ASIA & FAR EAST
Bangladesh
Bhutan
Myanmar (Burma)
China
India
Indonesia
Japan
Kampuchea
North Korea
South Korea
Laos
Malaysia
Mongolia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Viet Nam
Total
WORLD TOTAL
Number
(1000 h)
19,249
299
7,620
71,775
164,000
6,250
3,237
288
1,215
2,119
552
582
1,931
5,699
13,313
1,685
1,170
4,932
2,878
308,794
1,038,997
*
Total Manure
mt/day
240,613
3,738
95,250
897,188
2,050,000
78,125
67,653
3,600
15,188
26,488
6,900
7,275
24,138
71,238
166,413
21,063
14,625
61,650
35,975
3,887,116
15,968,328
VS
mt/day
36,092
561
14,288
134,578
307,500
11,719
8,389
540
2,278
3,973
1,035
1,091
3,621
10,686
24,962
3,159
2,194
9,248
5,396
581,308
221,190
', '
fofB0
0.090
0.090
0.090
0.100
0.092
0.080
0.347
0.090
0.090
0.090
0.090
0.098
0.050
0.090
0.050
0.075
0.090
0.090
0.090
OX '-'ff
Methane
mt/yr
78,518
1,220
31,082
325,305
681,973
22,661
232,070
1,175
4,956
8,644
2,252
2,572
4,376
23.247
30,169
5,728
4,772
20,118
11,740
1,492,576
9,449,080
APP-42
-------
EMISSIONS FROM DAIRY CATTLE WASTE
Country
Number Total Manure VS
(1000 h) mt/day mt/day
fofB
Methane
mt/yr
NORTH AMERICA
Canada
USA ,
Total
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
H Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
OCEANIA
Australia
Piii
i-iji
New Caledonia
New Zealand
L Papua New Guinea
Total
2,105
14,416
16,521
963
948
807
535
9,237
4,940
345
1,444
3,020
1,940
346
417
1,747
565
793
3,052
31,099
246
648
1,788
2,003
580
4,940
2,000
42,000
2,595
56,800
2,210
29
6
2,194
2
4,441
111,352
769,386
880,738
52,965
52,140
44,385
29,425
508,035
271,700
18,975
81,281
166,100
106,700
19,030
22,935
96,085
31,075
43,615
172,319
1,716,765
13,530
35,640
98,340
110,165
31,900
271,700
110,000
2,310,000
142,725
3,124,000
121,550
452
330
120,670
OH
O 1
243,034
12,948
89,463
1,02,411
6,144
6,048
5,149
3,413
58,932
31,517
2,201
9,429
19,268
12,377
2,207
2,660
11,146
3,605
5,059
19,989
199,145
1,569
4,134
11,407
12,779
3,700
31,517
12,760
267,960
16,556
362,384
14,100
68
38
13,998
5
28,208
0.11
0.20
0.140
0.115
0.162
0.096
0.140
0.140
0.140
0.140
0.130
0.130
0.137
0.110
0.113
0.108
0.097
0.140
0.100
0.115
0.090
0.115
0.084
0.088
0.096
0.096
0.110
0.100
0.100
0.100
0.100
0.100
81,332
1,013,428
1,094,760
49,900
40,351
48,388
19,010
478,638
255,978
17,877
76,578
145,311
93,345
17,591
16,978
72,743
22,585
28,324
162,348
1,545,944
9,105
27,582
59,296
85,256
18,032
160,901
71,064
1,492,342
105,652
2,029,230
81,798
230
222
81,205
16
163,470
APP-43
-------
; TABi£ £& SHETHAMi EMISSIONS F8Q& DAIRY CATTUiWASl
"•"• -."^ f •.""•• •• ^ •• ^ ""
Country
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
EAST & SUBSAHARAN AFRICA
Burundi
Central African Republic
Chad
Ethiopia
Kenya
Mali
Mauritania
Niger
Rwanda
Somalia
Tanzania
Uganda
Zaire
Total
%.- % •. -. f
Number
(1000 h)
2,830
75
18,100
640
3,400
310
583
225
801
258
400
52
95
333
49
6,400
180
109
105
703
92
550
1,270
37,560
60
45
406
3,875
2,255
474
272
530
160
1,000
2,800
1,080
8
12,965
'X f ...,
Total Manure
mt/day
44,148
1,170
282,360
9,984
53,040
4,836
9,095
3,510
12,496
4,025
6,240
811
1,482
5,195
764
99,840
2,808
1,700
1,638
10,967
1,435
8,580
19,812
585,936
936
702
6,334
60,450
35,178
7,394
4,243
8,268
2,496
15,600
43,680
16,848
125
202,254
. '•. '.../.t'. . " ' ff
VS
mt/day
6,622
176
42,354
1,498
7,956
725
1,364
527
1,874
604
936
122
222
779
115
14,976
421
255
246
1,645
215
1,287
2,972
87,890
140
105
950
9,068
5,277
1,109
636
1,240
374
2,340
6,552
2,527
19
30,338
•: f '••'•' 'f >
fofB0
0.063
0.098
0.063
0.055
0.098
0.098
0.098
0.098
0.063
0.098
0.102
0.111
0.098
0.100
0.098
0.063
0.098
0.075
0.098
0.098
0.075
0.075
0.075
0.100
0.100
0.053
0.053
0.053
0.053
0.053
0.053
0.100
0.053
0.100
0.100
0.100
rp »-' 3S
' j / A-X^ ";
Methane
mt/yr
14,006
579
89,582
2,787
26,251
2,393
4,501
1,737
3,964
1,992
3,215
455
733
2,637
378
31,675
1,390
647
811
5,428
546
3,267
7,543
206,519
475
356
1,688
16,110
9,375
1,971
1,131
2,203
1,267
4,157
22,173
8,552
63
69,522
APP-44
-------
1; , ; ^ TABif feat JWETHAHi EMliSSIONS FROM SAJBY CATTLE WASTE
Number Total Manure
| Country
WEST & SOUTHERN AFRICA
Angola
Benin
Botswana
Burkina Faso
Cameroon
Cote d'lvoire
The Gambia
Ghana
Guinea
Guinea-Bissau
Lesotho
Madagascar
Malawi
Mozambique
Namibia
Nigeria
Senegal
Sierra Leone
South Africa
Swaziland
Togo
Zambia
Zimbabwe
Total
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
Egypt
Iran
Iraq
~
Israel
Jordan
Kuwait
Libya
/*••
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Republic
Total
(1000 h)
295
116
290
461
97
154
30
195
225
59
80
59
95
390
169
1,220
260
50
920
153
38
270
143
5,769
1,170
570
1,450
2,350
380
106
18
16
49
1,560
42
125
3,450
290
250
5,000
348
17,174
mt/day
4,602
1,810
4,524
7,192
1,513
2,402
468
3,042
3,510
920
1,248
920
1,482
6,084
2,636
19,032
4,056
780
48,940
2,387
593
4,212
2,231
124,584
18,252
8,892
22,620
36,660
5,928
5,830
281
250
764
24,336
655
1,950
53,820
4,524
3,900
78,000
5,429
272,091
VS
mt/day
690
271
679
1,079
227
360
70
456
527
138
187
138
222
913
395
2,855
608
117
5,677
358
89
632
335
17,024
2,738
1,334
3,393
5,499
889
676
42
37
115
3,650
98
293
8,073
679
585
11,700
814
40,615
fofB0
0.100
0.100
0.053
0.053
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.100
0.100
0.100
0.052
0.100
0.100
0.100
0.100
0.050
0.100
0.063
0.050
0.058
0.113
0.050
0.100
0.050
0.100
0.050
0.050
0.050
0.050
0.050
0.100
0.050
Methane
mt/yr
2,336
919
1,206
1,917
768
1,219
238
1,544
1,782
467
634
467
752
3,088
669
9,661
2,059
396
16,961
1,212
301
2,138
1,132
51,865
4,633
4,514
7,176
9,305
1,730
4,414
71
127
194
12,353
166
495
13,660
1,148
990
39,594
1,378
101,948
APP-45
-------
, - - tftBiiW l/IETHAHi iMISSioNS FROM BArBV CATTILJE'WA$Ti^|l
•. % •.-.,,:'''
Country
ASIA & FAR EAST
Bangladesh
Bhutan
Myanmar (Burma)
China
India
Indonesia
Japan
Kampuchea
North Korea
South Korea
Laos
Malaysia
Mongolia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Viet Nam
Total
WORLD TOTAL
, * !^
Number
(1000 h)
3,540
110
2,380
2,188
29,000
250
1,430
98
35
267
38
43
595
675
3,813
15
650
68
45
45,240
227,569
> f ^ •-
Total Manure
mt/day
55,224
1,716
37,128
34,133
452,400
3,900
78,650
1,529
546
4,165
593
671
9,282
10,530
59,483
234
10,140
1,061
702
762,086
7,911,488
•~f t f f ^
VS
mt/day
8,284
257
5,569
5,120
67,860
585
9,123
229
82
625
89
101
1,392
1,580
8,922
35
1,521
159
105
111,639
979,654
, , "
fofB0
0.095
0.095
0.095
0.175
0.092
0.170
0.605
0.095
0.095
0.100
0.095
0.108
0.058
0.095
0.050
0.195
0.095
0.095
0.095
-,rf f, ^ j". J '• ffff
fVfv, f -. -, fff / ^
Methane
mt/yr
26,631
828
17,904
30,356
210,700
3,365
320,002
737
263
2,114
286
366
2,709
5,078
15,097
232
4,890
512
339
642,408
5,905,665
APP-46
-------
pfcv^Jfj^ TABLE E£
11^. •"-£•• *•< v-'" ' "
|| Country
METHANE EMISSIONS FROM
" *
Number Total Manure VS
(1000 h) mt/day mt/day
SWINE WASTE
-
Methane
f of B0 mt/yr
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
OCEANIA
Australia
Fiii
i iji
New Caledonia
New Zealand
Papua New Guinea
Vanuatu
Total
10,847
55,299
66,146
3,947
5,881
9,214
1,309
12,577
23,670
1,190
960
9,383
14,226
788
2,800
16,941
2,217
1,941
7,915
114,959
214
4,034
7,235
12,503
8,216
19,605
15,224
77,403
8,323
152,757
2,720
29
47
428
1,700
79
5,003
53,922
291,568
345,490
17,394
29,903
42,947
6,545
62,885
118,350
5,950
4,475
50,891
69,924
3,940
14,000
84,705
11,085
9,705
38,233
570,932
1,070
20,170
36,175
62,515
41,080
98,025
76,120
387,015
46,552
768,722
14,292
119
235
2,140
6,970
324
24,079
5,456
29,504
34,960
1,757
3,020
4,338
661
6,351
11,953
601
452
5,140
7,062
398
1,414
8,555
1,120
980
3,862
57,664
108
2,037
3,654
6,314
4,149
9,901
7,688
39,089
4,702
77,641
1,443
12
24
216
704
33
2,432
0.22
0.44
0.180
0.180
0.162
0.136
0.180
0.180
0.180
0.100
0.180
0.174
0.152
0.140
0.160
0.160
0.198
0.180
0.120
0.120
0.234
0.292
0.694
0.088
0.096
0.096
0.140
0.740
0.100
0.740
0.740
0.100
0.100
102,998
1,125,080
1,228,078
34,396
59,135
76,435
9,779
124,357
234,040
11,766
4,916
100,638
133,668
6,579
21,533
148,895
19,485
21,111
75,608
1,082,342
1,411
26,591
92,839
200,547
313,393
94,770
80,282
408,177
71,601
1,289,612
116,188
84
1,911
17,398
4,935
229
140,744
APP-47
-------
\'
;, TABLE E3;
Country
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
EAST & SUBSAHARAN AFRIO
Burundi
Central African Republic
Chad
Ethiopia
Kenya
Mali
Niger
Rwanda
Somalia
Tanzania
Uganda
Zaire
Total
METHANE
•VIM 9 « *:ri4 «*MC
Number
(1000 h)
4,100
1,750
32,700
1,360
2,586
223
2,500
409
4,160
442
875
185
900
600
250
16,500
745
240
2,108
2,400
195
215
2,707
78,150
\
80
382
12
19
102
60
37
92
10
184
440
800
2,218
EMISSIONS
M»VS • *jf-^lfM ^*r • V VjF
fatal Manure
mt/day
16,810
7,175
134,070
5,576
10,603
914
10,250
1,677
17,056
1,812
3,588
759
3,690
2,460
1,025
67,650
3,055
984
8,643
9,840
800
882
11,099
320,415
328
1,566
49
78
418
246
152
377
41
754
1,804
3,280
9,094
* , S ff >.
FROM SWINE
vs
mt/day
1,698
725
13,541
563
1,071
92
1,035
169
1,723
183
362
77
373
248
104
6,833
309
99
873
994
81
89
1,121
32,362
33
158
5
8
42
25
15
38
4
76
182
331
918
-.-.-.''''
WA^STE
j-w r*^p • "••
V
fofB0
0.110
0.100
0.110
0.054
0.100
0.100
0.100
0.100
0.110
0.100
0.100
0.097
0.100
0.100
0.100
0.110
0.100
0.110
0.100
0.100
0.110
0.110
0.110
0.105
0.105
0.058
0.058
0.058
0.100
0.058
0.105
0.058
0.105
0.105
0.105
'- , ' ,''/^
j f •>
-/' ' "K
Methane
mt/yr
13,092
5,080
104,414
2,112
7,507
647
7,257
1,187
13,283
1,283
2,540
518
2,613
1,742
726
52,686
2,163
766
6,119
6,967
623
687
8,644
242,654
244
1,164
20
32
170
174
62
280
17
561
1,341
2,438
6,503
APP-48
-------
LVx^jV TABLED
?> •.- x»\ ^4 ^;\*S - ,&„ ;„,.,.. <-,<'<• ,"
\
Country
WEST & SOUTHERN AFRICA
Angola
Benin
Botswana
Burkina Faso
Cameroon
Cote d'lvoire
IThe Gambia
Guinea
Guinea-Bissau
Lesotho
Madagascar
Malawi
Mozambique
Namibia
Nigeria
Senegal
Sierra Leone
South Africa
Swaziland
Togo
Zambia
Zimbabwe
Total
METHANE EMISSIONS FROM SWINE WASTE :
«.% %;%A^',
Number
(1000 h)
480
648
9
500
1,178
450
13
50
290
72
1,400
210
160
48
1,300
470
50
1,460
19
300
180
190
10,227
^ \ , ..^\
Total Manure
mt/day
1,968
2,657
37
2,050
4,830
1,845
53
205
1,189
295
5,740
861
656
197
5,330
1,927
205
7,300
78
1,230
738
779
43,245
-. *""**, •• % " '""'
VS
mt/day
199
268
4
207
488
186
5
21
120
30
580
87
66
20
538
195
21
737
8
124
75
79
4,368
v -.
/ofB0
0.105
0.105
0.058
0.058
0.105
0.105
0.105
0.105
0.105
0.105
0.105
0.200
0.105
0.050
0.105
0.105
0.105
0.075
0.105
0.105
0.105
0.105
% , ,
Methane
mt/yr
1,463
1,975
15
835
3,590
1,372
40
152
884
219
4,267
1,219
488
70
3,962
1,433
152
6,015
58
914
549
579
32,537
NEAR EAST & MEDITERRANEAN
Algeria
Egypt
Israel
Morocco
Syria
Tunisia
Turkey
Total
5
15
130
9
1
4
10
174
21
62
650
37
4
16
41
830
2
6
66
4
0
2
4
84
0.115
0.088
0.155
0.115
0.073
0.073
0.115
17
38
1,107
30
2
8
33
1,236
APP-49
-------
TABLE Eft
'
Country
ASIA & FAR EAST
Bhutan
Myanmar (Burma)
China
India
Indonesia
Japan
Kampuchea
North Korea
South Korea
Laos
Malaysia
Mongolia
Nepal
Philippines
Sri Lanka
Thailand
Viet Nam
Total
WORLD TOTAL
METHANE
^ •.
Number 7
(1000 h)
63
3,000
334,862
10,300
6,500
11,354
1,500
3,100
4,281
1,520
2,200
80
479
7,580
101
4,260
12,051
403,231
832,865
EMISSIONS
,' , •;
"otal Manure
mt/day
258
12,300
1,372,934
42,230
26,650
56,770
6,150
12,710
17,552
6,232
9,020
328
1,964
31,078
414
17,466
49,409
1,663,466
3,746,273
FROM SWINE
..'...' """,',
vs
mt/day
26
1,242
138,666
4,265
2,692
5,734
621
1,284
1,773
629
911
33
198
3,139
42
1,764
4,990
168,010
378,439
WASTE
;
/ofB0
0.135
0.135
0.143
0.100
0.140
0.341
0.135
0.135
0.150
0.135
0.130
0.103
0.135
0.130
0.135
0.135
0.135
Methane
mt/yr
247
11,756
1,388,076
29,899
26,416
212,554
5,878
12,148
18,640
5,957
8,286
238
1,877
28,604
396
16,694
47,225
1,814,892
5,838,598
APP-50
-------
|;;w, ,-::*
[^V^t;:.. >";?:•'•; ,... , ;.?
Country
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
OCEANIA
Australia
New Caledonia
New Zealand
Papua New Guinea
Total
% •"• ••
jfME^ANE
Number T
(1000 h)
697
10,639
11,336
24
184
128
63
10,360
1,414
10,816
4,301
11,457
1,100
2,306
5,220
17,894
402
367
27,820
93,856
1,432
8,886
1,075
2,656
2,333
4,377
18,793
140,783
7,824
188,159
164,000
3
64,970
9
228,982
- ,
Dtal Manure
mt/day
1,732
29,683
31,415
57
497
346
170
27,972
4,046
29,203
12,479
30,934
2,394
6,226
14,094
48,314
1,085
991
73,993
252,801
3,866
23,992
2,903
7,171
6,299
11,818
50,741
380,114
21,755
508,660
475,845
8
175,419
14
651,286
i FROM SHE
vs
mt/day
398
6,827
7,225
13
114
79
39
6,434
931
6,717
2,870
7,115
551
1,432
3,242
11,112
250
228
17,018
58,144
889
5,518
668
1,649
1,449
2,718
11,670
87,426
5,004
116,992
109,444
2
40,346
3
149,796
EEPWA&i
'°»B0
0.08
0.10
0.100
0.100
0.100
0.080
0.100
0.100
0.100
0.100
0.100
0.100
0.110
0.100
0.100
0.040
0.100
0.100
0.100
0.100
0.080
0.100
0.080
0.080
0.080
0.080
0.100
0.050
0.100
0.100
0.100
"" '•'•'"" '•"''•
Methane
mt/yr
1,531
32,739
34,270
60
525
365
144
29,548
4,274
30,848
13,182
32,676
2,529
7,235
14,888
51,035
459
1,047
78,161
266,973
4,084
25,344
2,453
7,575
5,323
9,987
42,879
321,219
22,981
441,845
251,323
9
185,299
10
436,642
APP-51
-------
o 5-_; ^
-.'•"• '*J*».|J}I pt
I MDLC
Country
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
EAST & SUBSAHARAN
Burundi
Central African Republic
Chad
Ethiopia
Kenya
Mali
Mauritania
Niger
Rwanda
Somalia
Tanzania
Uganda
Zaire
Total
;; ,
**£• MFTHAfJF
E.4. lUICIiFlMnC.
Number T
(1000 h)
29,202
9,600
20,000
6,540
2,652
6
382
100
1,707
5
660
120
94
7
3
6,000
3
430
13,320
7
26,049
425
117,312
AFRICA
350
120
2,245
23,400
7,300
5,500
4,100
3,500
360
13,500
47,400
1,740
880
110,395
(•• ''•.,'''
£ftjieet&ki£
CMH 1991 \ft »«
Dtal Manure
mt/day
46,723
15,360
32,000
10,464
4,243
10
611
160
2,731
8
1,056
192
150
11
5
9,600
5
688
21,312
11
41,678
680
187,699
560
192
3,592
37,440
11,680
8,800
6,560
5,600
576
21,600
75,840
2,784
1,408
176,632
v •.-- "'<
FftCiM n
VS
mt/day
10,746
3,533
7,360
2,407
976
2
141
37
628
2
243
44
35
3
1
2,208
1
158
4,902
3
9,586
156
43,171
129
44
826
8,611
2,686
2,024
1,509
1,288
132
4,968
17,443
640
324
40,625
c- ,l • * '
pep Vf/A&*f£
C CJr Ttwf+tSf tKi
fo
-------
£*— -^ ;: *
pspLs " " ^tAfiiLE
•" "• %
E4: METHANE
EitiissrONS moM SHEEP WASTE
Number Total Manure
| Country
(1000 h)
mt/day
VS
mt/day
fofB0
Methane
mt/yr
WEST & SOUTHERN AFRICA
Angola
Benin
Botswana
Burkina Faso
Cameroon
Cote d'lvoire
The Gambia
Ghana
Guinea
Guinea-Bissau
Lesotho
Madagascar
Malawi
Mozambique
Namibia
Nigeria
Senegal
Sierra Leone
South Africa
Swaziland
Togo
Zambia
Zimbabwe
Total
265
860
220
2,972
2,897
1,500
200
2,500
460
205
1,440
611
210
119
6,400
13,200
3,792
330
29,800
35
100
80
580
68,776
424
1,376
352
4,755
4,635
2,400
320
4,000
736
328
2,304
978
336
190
10,240
21,120
6,067
528
80,460
56
160
128
928
142,822
98
316
81
1,094
1,066
552
74
920
169
75
530
225
77
44
2,355
4,858
1,395
121
18,506
13
37
29
213
32,849
0.100
0.100
0.050
0.050
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.100
0.100
0.100
0.050
0.100
0.100
0.100
0.100
306
995
127
1,718
3,350
1,735
231
2,891
532
237
1,665
707
243
138
3,700
15,264
4,385
382
42,496
40
116
93
671
82,022
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
Egypt
«p/ ~
Iran
Iraq
Israel
Jordan
Kuwait
Libya
/ ™*
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Republic
Total
17,000
14,325
1,165
34,500
9,200
280
1,220
300
5,750
15,700
218
7,466
18,500
13,304
5,900
40,000
2,674
187,502
27,200
22,920
1,864
55,200
14,720
756
1,952
480
9,200
25,120
349
11,946
29,600
21,286
9,440
64,000
4,278
300,311
6,256
5,272
429
12,696
3,386
174
449
110
2,116
5,778
80
2,747
6,808
4,896
2,171
14,720
984
69,072
0.050
0.050
0.050
0.050
0.050
0.100
0.050
0.100
0.050
0.100
0.050
0.050
0.050
0.050
0.050
0.100
0.050
9,829
8,283
674
19,948
5,319
799
705
347
3,325
18,155
126
4,317
10,697
7,692
3,411
46,256
1,546
141,429
APP-53
-------
•- -. -. •. f \
'• ' ^ -. % ' ""
1 - „ ''jA&li'&l
Country
ASIA & FAR EAST
Bangladesh
Bhutan
Myanmar (Burma)
China
India
Indonesia
Japan
Kampuchea
North Korea
South Korea
Malaysia
Mongolia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Viet Nam
Total
WORLD TOTAL
*%v .•>.. ,
k METHANE
Number 1
(1000 h)
140
27
295
102,655
51,684
5,415
29
1
372
3
99
13,234
833
27,479
30
28
95
23
202,442
1,208,760
•."• •- •.
._ ^
EMISSIONS
'otal Manure
mt/day
224
43
472
164,248
82,694
8,664
78
2
595
5
158
21,174
1,333
43,966
48
45
152
37
323,939
2,575,565
" '•'' 'j. ''^.^^
42CWVM &L!E
rnvivi one
vs
mt/day
52
10
109
37,777
19,020
1,993
18
0
137
1
36
4,870
307
10,112
11
10
35
8
74,506
592,379
•" '^\ "_.
; ,' ,"•;
&!•"•• Tty/VJS I
fofB0
0.100
0.100
0.100
0.100
0.100
0.200
0.100
0.100
0.100
0.100
0.090
0.063
0.100
0.050
0.060
0.100
0.100
0.100
"• ^ A/ f ,
, '''''•. -'*'••
*?, ," >,' 'v ••'' '';<',
Methane
mt/yr
162
31
341
118,710
59,767
12,524
83
1
430
3
103
9,565
963
15,888
21
32
110
27
218,762
1,851,450
APP-54
-------
jl'-X "^ •• ••
P^K;. TABLE
kv^;- ™BL*
1 Country
E& METHANE EMISSIONS FROM GOAT WASTE
Number
(1000 h)
Total Manure
ml/day
VS
mt/day
Methane
f of B0 mt/yr
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Austria
Belgium
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
OCEANIA
Australia
Fiji
' *r
New Caledonia
New Zealand
Papua New Guinea
Vanuatu
Total
26
2,396
2,422
34
8
3
1,150
46
3,488
9
1,206
34
94
745
2,900
72
58
9,847
979
428
50
19
16
10
990
6,400
126
9,018
600
60
21
1,317
12
12
2,022
68
6,288
6,356
88
21
8
2,990
120
9,069
23
3,136
88
244
1,937
7,540
187
151
25,602
2,545
1,113
130
49
42
26
2,574
16,640
328
23,447
1,560
108
55
3,424
22
22
5,190
18
1,457
1,475
24
6
2
795
32
2,412
6
834
24
65
515
2,006
50
40
6,810
677
296
35
13
11
7
685
4,426
87
6,237
415
29
15
911
6
6
1,381
0.100
0.100
0.100
0.100
0.080
0.100
0.100
0.100
0.100
0.100
0.100
0.134
0.100
0.100
0.091
0.100
0.100
0.100
0.080
0.100
0.080
0.080
0.080
0.080
0.100
0.050
0.100
0.100
0.100
0.100
0.100
74
6,002
6,076
97
23
7
3,268
131
9,913
26
3,427
97
357
2,117
8,242
187
165
28,055
2,782
1,216
114
54
36
23
2,251
14,551
358
21,385
853
90
60
3,743
18
18
4,782
APP-55
-------
I ,* -"* STABLE
•f X ^ :\'' '' : f '' "•
Country
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
EAST & SUBSAHARAN
Burundi
Central African Republic
Chad
Ethiopia
Kenya
Mali
Mauritania
Niger
Rwanda
Somalia
Tanzania
Uganda
Zaire
Total
m ME^A
Number
(1000 h)
3,200
2,350
11,000
600
932
10
110
534
301
15
76
77
1,200
25
440
10,500
6
7
138
1,700
14
14
1,400
34,649
AFRICA
750
1,159
2,245
17,500
8,500
5,500
3,200
7,550
1,200
20,000
6,600
2,800
3,040
80,044
- ' / ' ;
,-\
Total Manure
mt/day
5,760
4,230
19,800
1,080
1,678
18
198
961
542
27
137
139
2,160
45
792
18,900
11
13
248
3,060
25
25
2,520
62,368
1,350
2,086
4,041
31,500
15,300
9,900
5,760
13,590
2,160
36,000
11,880
5,040
5,472
144,079
*!«' "ft&mf'fZt*
, - ^/-iT" -
vs
mt/day
1,532
1,125
5,267
287
446
5
53
256
144
7
36
37
575
12
211
5,027
3
3
66
814
7
7
670
16,590
359
555
1,075
8,379
4,070
2,633
1,532
3,615
575
9,576
3,160
1,341
1,456
38,325
' , -"' "
'•'• f < s
fofB0
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.098
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.050
0.050
0.060
0.050
0.050
0.100
0.050
0.100
0.100
0.100
' -' ' '"- ;'-;
,' % "' '" "', ;.,.
Methane
mt/yr
4,815
3,536
16,550
903
1,402
15
166
803
453
23
111
116
1,805
38
662
15,798
9
11
208
2,558
21
21
2,106
52,129
1,128
1,744
1,689
13,165
6,394
4,965
2,407
5,680
1,805
15,046
9,930
4,213
4,574
72,741
APP-56
-------
pljf i x ;^TjiBjLE JE&r
p^sSf^'^ -^ '--'•>•' ••"'••'•
Country
WEST & SOUTHERN AFRICA
Angola
1 Benin
Botswana
Burkina Faso
Cameroon
Cote d'lvoire
The Gambia
Ghana
Guinea
Guinea-Bissau
Lesotho
Madagascar
Malawi
Mozambique
Namibia
Nigeria
Senegal
Sierra Leone
South Africa
Swaziland
Togo
Zambia
Zimbabwe
Total
MErtlANE EMISSIONS FROM QOAT WASTE
, "•-, v< >-?, ' '
Number
(1000 h)
975
960
1,100
5,198
2,906
1,500
200
3,000
460
210
1,030
1.080
950
375
2,500
26,000
1,150
180
5,840
320
900
420
1,650
58,904
' , f - - -/'- '-„
Total Manure
mt/day
1,755
1,728
1,980
9,356
5,231
2,700
360
5,400
828
378
1,854
1,944
1,710
675
4,500
46,800
2,070
324
15,184
576
1,620
756
2,970
110,699
'
VS
mt/day
467
460
527
2,489
1,391
718
96
1,436
220
101
493
517
455
180
1,197
12,449
551
86
4,039
153
431
201
790
29,446
**.'•> ""
fofB0
0.100
0.100
0.050
0.050
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.000
0.100
0.100
0.050
0.100
0.100
0.100
0.100
V
Methane
mt/yr
1,467
1,444
828
3,910
4,372
2,257
301
4,514
692
316
1,550
1,625
1,429
564
1,881
0
1,730
271
8,299
481
1,354
632
2,483
42,400
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
EdVDt
&J r
Iran
Iraq
Israel
Jordan
Kuwait
Libya
ui-'yt*
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Republic
Total
2,800
3,570
1,620
13,620
1,550
128
460
20
965
5,800
712
3,600
13,500
1,078
1,115
13,100
1,079
64,717
5,040
6,426
2,916
24,516
2,790
333
828
36
1,737
10,440
1,282
6,480
24,300
1,940
2,007
23,580
1,942
116,593
1,341
1,709
776
6,521
742
89
220
10
462
2,777
341
1,724
6,464
516
534
6,272
517
31,014
0.050
0.050
0.050
0.050
0.050
0.100
0.050
0.100
0.050
0.100
0.050
0.050
0.050
0.050
0.050
0.100
0.050
2,106
2,686
1,219
10,246
1,166
364
346
30
726
8,727
536
2,708
10,156
811
839
19,710
812
63,186
APP-57
-------
i-
CL< TABLE E5i
METHANE
EMISSIONS
Number Total Manure
Country
ASIA & FAR EAST
Bangladesh
Bhutan
Myanmar (Burma)
China
India
Indonesia
Japan
Kampuchea
North Korea
South Korea
Laos
Malaysia
Mongolia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Viet Nam
Total
WORLD TOTAL
(1000 h)
10,700
32
1,100
77,894
105,000
12,700
41
1
285
166
76
347
4,388
5,125
33,018
2,120
503
80
414
253,990
515,613
mt/day
19,260
58
1,980
140,209
189,000
22,860
107
2
513
299
137
625
7,898
9,225
59,432
3,816
905
144
745
457,215
951,549
f
FROM'
vs
mt/day
5,123
15
527
37,296
50,274
6,081
28
0
136
79
36
166
2,101
2,454
15,809
1,015
241
38
198
121,619
252,896
OQAT WASTE
/ofB0
0.100
0.100
0.100
0.100
0.100
0.200
0.100
0.100
0.100
0.100
0.100
0.100
0.053
0.100
0.050
0.098
0.100
0.100
0.100
' -• rt^ 'r -. *'
/-; u '*;;+
Methane
mt/yr
16,099
48
1,655
117,197
157,980
38,216
117
2
429
250
114
522
3,466
7,711
24,839
3,110
757
120
623
373,255
664,009
APP-58
-------
rx»?N> o <• •• -^ ;-x* •," ' ' *"
;%',j ^ ,•• , ^ *jp*»>| tS
if." ,; -?' ' T/MSUG
P* - 5 '^"' ' ' "„
S> ' " *.?" ..''I1. "..'. '.'.. "
| Country
I NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
(Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
OCEANIA
Australia
Fiji
New Caledonia
New Zealand
Papua New Guinea
[ Total
' ',x ^,,'^ v •• , ;, ;<;, %
E6; METHANE
""f ""Sss •• f*~ ^-, ''' * "•'
' f1* "f •. f Vf~'f-' "• '-J •" %'?' -. \-.
Number
(1000 h)
106,714
1,307,383
1.414,097
15,000
34,000
15,000
6,000
189,000
72,000
31,000
7,000
120,000
98,000
4,000
18,000
55,000
11,000
6,000
127,000
808,000
6,000
40,000
46,000
51.000
61,000
57,000
136,000
1,129,000
73,000
1,599.000
56,000
2,000
1,000
9,000
3,000
71,000
' -1 *< '••'••' ""'' ' '
EMISSIONS
;ft-'fff * „'„" /
s-,f "- f"-'f: ""f^f"'-.
Total Manure
mt/day
6,894
92,648
99,542
1,500
3,400
1,500
600
18,900
7,200
3,100
700
12,000
9,800
400
1,800
5,500
1,100
600
12,700
80,800
600
4,000
4,600
5,100
6,100
5,700
13,600
112,900
7,300
159,900
5,600
240
100
900
360
7,200
FROM CHICKEN
••„<. ^ -, •• / f -.,
""..... *%•'.'.. .. <, ""
vs
mt/day
1,775
58,198
59,973
291
660
291
116
3,667
1,397
601
136
2,328
1,901
78
349
1,067
213
116
2,464
15,675
116
776
892
989
1,183
1,106
2,638
21,903
1,416
31,021
1,086
47
19
175
70
1,397
WASTE
/ofB0
0.086
0.044
0.100
0.150
0.100
0.105
0.100
0.100
0.100
0.098
0.077
0.121
0.105
0.091
0.098
0.107
0.088
0.100
0.084
0.122
0.126
0.126
0.132
0.135
0.121
0.121
0.091
0.077
0.100
0.077
0.077
0.100
Methane
mt/yr
11,867
199,875
211,742
2,245
7,669
2,246
942
28,297
10,780
4,641
1,026
13,857
17,757
628
2,452
8,063
1,762
797
19,014
122,174
755
7,317
8,704
9,651
12,108
11,511
24,642
204,565
9,944
289,197
6,466
293
115
1,039
439
8,353
APP-59
-------
EMISSIONS
'
Country
Number
(1000 h)
Total Manure
rrrt/day
VS
mt/day
fofB
Methane
mt/yr
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
EAST & SUBSAHARAN AFRICA
Burundi
Central African Republic
Chad
Ethiopia
Kenya
I Mali
Mauritania
Niger
Rwanda
Somalia
Tanzania
Uganda
Zaire
Total
55,000
12,000
550,000
21,000
39,000
5,000
27,000
27,000
48,000
3,000
15,000
15,000
13,000
8,000
6,000
224,000
5,000
7,000
16,000
52,000
11,000
8,000
57,000
1,224,000
4,000
3,000
4,000
57,000
23,000
19,000
4,000
17,000
1,000
3,000
30,000
15,000
19,000
199,000
6,600
1,440
66,000
2,520
4,680
600
3,240
3,240
5,760
360
1,800
1,800
1,560
960
720
26,880
600
840
1,920
6,240
1,320
960
6,840
146,880
480
360
480
6,840
2,760
2,280
480
2,040
120
360
3,600
1,800
2,280
23,880
1,280
279
12,804
489
908
116
629
629
1,117
70
349
349
303
186
140
5,215
116
163
372
1,211
256
186
1,327
28,495
93
70
93
1,327
535
442
93
396
23
70
698
349
442
4,632
0.110
0.105
0.110
0.110
0.105
0.105
0.105
0.105
0.110
0.105
0.103
0.095
0.105
0.100
0.105
0.110
0.105
0.105
0.105
0.105
0.113
0.113
0.113
0.098
6.809
0.055
0.055
0.055
0.050
0.055
0.055
0.099
0.055
0.098
0.098
0.098
8,852
1,843
88,517
3,380
5,991
768
4,148
4,148
7,725
461
2,250
2,085
1,997
1,170
922
36,051
768
1,075
2,458
7,988
1,811
1,317
9,382
195,107
571
428
322
4,587
1,851
1,390
322
1,368
143
241
4,280
2,140
2,710
20,352
APP-60
-------
MlfS- &SI^^£& 3$lf$ANi ijiftlSSibiNS FBQM CHICKEN 1&ASTE '
r^/^X" ^** W.^\V'-&A *'J"i \. "" -.
F vX> ;.£.:• .>& ..v ..X-ft "xY'S'V" -IT. "" "" ,."• .%°- "•
Country
WEST & SOUTHERN AFRICA
Angola
Benin
Botswana
Burkina Faso
Cameroon
Cote d'lvoire
Ghana
Guinea
Guinea-Bissau
Lesotho
Madagascar
Malawi
Mozambique
Namibia
Nigeria
Senegal
Sierra Leone
South Africa
Swaziland
Togo
Zambia
Zimbabwe
Total
•"• •" •" "" ''* ff f
.. '' "".' ..,"?. ,,'' f'f..f
Number
(1000 h)
6,000
23,000
1,000
21,000
16,000
16,000
12,000
13,000
1,000
1,000
21,000
8,000
21,000
1,000
190,000
11,000
6,000
37,000
1,000
3,000
15,000
10,000
434.000
•/"•.""). •* "*
. :• V XT.
Total Manure
mt/day
720
2,760
120
2,520
1,920
1,920
1,440
1,560
120
120
2,520
960
2,520
120
22,800
1,320
720
3,700
120
360
1,800
1,200
51,340
., "
•• v . f.
VS
mt/day
140
535
23
489
372
372
279
303
23
23
489
186
489
23
4,423
256
140
718
23
70
349
233
9,960
s
fofB0
0.098
0.098
0.055
0.055
0.098
0.098
0.098
0.098
0.098
0.098
0.098
0.085
0.098
0.055
0.098
0.098
0.098
0.077
0.098
0.098
0.098
0.098
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
Egypt
57* ~
Iran
Iraq
Israel
Jordan
Kuwait
Libya
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Republic
Total
7,000
23,000
30,000
110,000
76,000
23,000
60,000
28,000
37,000
37,000
2,000
69,000
29,000
12,000
17,000
58,000
23,000
641,000
840
2,760
3,600
13,200
9,120
2,300
7,200
3,360
4,440
4,440
240
8,280
3,480
1,440
2,040
6,960
2,760
76,460
163
535
698
2,561
1,769
446
1,397
652
861
861
47
1,606
675
279
396
1,350
535
14,833
0.063
0.063
0.063
0.063
0.063
0.112
0.063
0.100
0.063
0.100
0.063
0.063
0.063
0.063
0.063
0.100
0.063
^
Methane
mt/yr
856
3,281
80
1,690
2,282
2,282
1,712
1,854
143
143
2,996
995
2,996
80
27,104
1,569
856
4,272
143
428
2,140
1,427
59,329
640
2,103
2,743
10,059
6,950
3,849
5,487
4,097
3,383
5,413
183
6,310
2,652
1,097
1,555
8,486
2,103
67,110
APP-61
-------
- . „ TABl£ Eej IKETHAN1
i ^ ^
Country
ASIA & FAR EAST
Bangladesh
Myanmar (Burma)
China
India
Indonesia
Japan
Kampuchea
North Korea
South Korea
Laos
Malaysia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Viet Nam
Total
WORLD TOTAL
% -. •. *
Number
(1000 h)
81,000
34,000
1,849,000
260,000
410,000
334,000
7,000
20,000
59,000
9,000
58,000
10,000
150,000
60,000
9,000
85,000
69,000
3,504,000
9,894,097
EMISSIONS FROM CHICKEN WASTE
, *
Total Manure
mt/day
9,720
4,080
221,880
31,200
49,200
33,400
840
2,400
7,080
1,080
6,960
1,200
18,000
7,200
1,080
10,200
8,280
413,800
1,059,802
;++'"
VS
mt/day
1,886
792
43,045
6,053
9,545
6,480
163
466
1,374
210
1,350
233
3,492
1,397
210
1,979
1,606
80,277
246,263
f«B0
0.105
0.105
0.101
0.120
0.147
0.233
0.105
0.105
0.110
0.105
0.102
0.105
0.082
0.100
0.105
0.105
0.105
'
Methane
mt/yr
12,444
5,223
273,772
45,649
87,881
116,990
1,075
3,072
9,495
1,383
8,656
1,536
17,919
8,779
1,383
13,058
10,600
618,915
1,592,278
APP-62
-------
K'*'V,' yfA&Us
E7V METHANE
elisions
Number Total Manure
Country
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Denmark
France
Germany (Western)
United Kingdom
Total
EASTERN EUROPE
Hungary
Poland
Romania
Yugoslavia
Total
LATIN AMERICA
Argentina
Brazil
Mexico
Total
(1000 h)
1,000
7,000
8,000
1,000
11,000
1,000
2,000
15,000
2,000
4,000
5,000
2,000
13,000
2,000
6,000
7,000
15,000
mt/day
150
1,050
1,200
150
1,650
150
300
2,250
300
600
750
300
1,950
240
720
840
1,800
FROM
vs
nrrt/day
26
182
208
26
285
26
52
389
52
104
130
52
337
42
125
145
311
PUCK WASTE
fofB0
0.100
0.100
0.100
0.100
0.100
0.100
0.080
0.080
0.080
0.100
0.100
0.100
0.100
Methane
mt/yr
201
1,405
1,606
201
2,208
201
401
3,011
321
642
803
401
2,168
261
783
913
1,957
EAST & SUBSAHARAN AFRICA
Tanzania
Total
WEST & SOUTHERN
Madagascar
Mozambique
Total
3,000
3,000
AFRICA
5,000
1,000
6,000
360
360
600
120
720
62
62
104
21
125
0.100
0.100
0.100
391
391
652
130
783
NEAR EAST & MEDITERRANEAN
Egypt
Total
ASIA & FAR EAST
Bangladesh
China
Indonesia
Kampuchea
South Korea
Malaysia
Pakistan
Philippines
Thailand
Viet Nam
Total
WORLD TOTAL
4,000
4,000
32,000
325,000
29,000
3,000
1,000
4,000
1,000
6,000
16,000
27,000
444,000
508,000
=======
480
480
3,840
39,000
3,480
360
120
480
120
720
1,920
3,240
53,280
62,040
=====
83
83
664
6,747
602
62
21
83
21
125
332
561
9,217
10,733
========
0.050
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.100
0.100
0.100
261
261
4,175
42,403
3,784
391
130
522
65
783
2,088
3,523
57,864
68,041
APP-63
-------
, - TABU l&
"• fV -.s* ,\ ^.j. s* f "" ""
Country
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
France
Germany (Western)
Ireland
Italy
Netherlands
United Kingdom
Total
EASTERN EUROPE
Bulgaria
Czechoslovakia
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
LATIN AMERICA
Argentina
Brazil
Mexico
Total
WEST & SOUTHERN AFRICA
Madagascar
Total
METHANE EMl$$10l<$,£BOJ* TURKEY W3Jft6£
Number
(1000 h)
10,386
53,783
64,169
20,000
3,000
1,000
23,000
1,000
9,000
57,000
1,000
1,000
1,000
1,000
1,000
48,000
2,000
55,000
3,000
5,000
12,000
20,000
4,000
4,000
sj *"s,^' "''
Total Manure
mt/day
3,107
8,544
11,651
6,000
900
300
6,900
300
2,700
17,100
300
300
300
300
300
14,400
600
16,500
780
1,300
3,120
5,200
1,040
1,040
> < x % f& < Jt < j ftf S •.
' v,> f f f f .
vs
mt/day
643
1,654
2,297
1,164
175
58
1,339
58
524
3,317
58
58
58
58
58
2,794
116
3,201
151
252
605
1,009
202
202
'"", ". ^'"1':,%
f-ofB0
0.08
0.10
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.080
0.080
0.080
0.080
0.080
0.100
0.100
0.100
0.100
0.100
i'-? i^ify^j^
Methane
mt/yr
3,728
11,996
15,724
8,441
1,266
422
9,707
422
3,798
24,057
422
338
338
338
338
16,207
844
18,823
878
1,463
3,511
5,852
1,170
1,170
NEAR EAST & MEDITERRANEAN
Egypt
Israel
Turkey
Total
ASIA & FAR EAST
China
Total
WORLD TOTAL
1,000
7,000
3,000
11,000
1,000
1,000
212,169
260
2,100
780
3,140
260
260
54,891
50
407
151
609
50
50
10,686
0.095
0.100
0.100
0.100
278
2,954
878
4,110
293
293
70,030
APP-64
-------
£ :»„>*$*&£ Efc ' I&£THA*|E EMISSIONS Fflblll &6F3FA10 WASTE'
1 % -• '" * s\r -.-.'''
1 Country
1 NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Greece
Italy
Total
EASTERN EUROPE
Albania
Bulgaria
Romania
Soviet Union
Yugoslavia
Total
LATIN AMERICA
Brazil
Total
' " .'..•• ,
Number
(1000 h)
0
0
0
1
104
105
2
24
210
320
25
581
1,100
1,100
-.-. ••
Total Manure
mt/day
0
0
0
21
2,174
2,194
42
502
4,389
6,688
522
12,143
13,750
13,750
.. ,
VS
mt/day
0
0
0
3
270
272
5
62
544
829
65
1,506
2,063
2,063
'
fofB0
0
0
0
0.160
0.120
0.105
0.120
0.100
0.100
0.110
0.100
' .. "''
Methane
mt/yr
0
0
0
17
1,329
1,346
22
307
2,236
3,408
293
6,266
4,986
4,986
NEAR EAST & MEDITERRANEAN
Egypt
Iran
Iraq
Syria
Turkey
Total
ASIA & FAR EAST
Bangladesh
Bhutan
Myanmar (Burma)
China
India
Indonesia
Kampuchea
Laos
Malaysia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Viet Nam
TOTAL
WORLD TOTAL
==^— — — - — — =====
2,600
230
145
1
540
3,516
1,950
7
2,200
20,858
72,000
3,000
700
1,000
220
2,900
14,020
2,890
1,050
6,000
2,809
131,604
136,906
===========
32,500
2,875
1,813
13
6,750
43,950
24,375
88
27,500
260,725
900,000
37,500
8,750
12,500
2,750
36,250
175,250
36,125
13,125
75,000
35,113
1,645,050
1,717,087
===============
4,875
431
272
2
1,013
6,593
3,656
13
4,125
39,109
135,000
5,625
1,313
1,875
413
5,438
26,288
5,419
1,969
11,250
5,267
246,758
257,190
==============
0.063
0.050
0.058
0.050
0.100
0.090
0.090
0.090
0.100
0.092
0.080
0.090
0.090
0.098
0.090
0.050
0.075
0.090
0.090
0.090
=====
7,365
521
378
2
2,447
10,714
7,954
rtft
29
8,974
94,534
299,403
10,877
2,855
4,079
972
11,829
31,771
9,824
4,283
24,474
11,458
523,318
546,629
=====
APP-65
-------
ixXJ" '''' ,f '\'' '' ' '
•. •., , .••.-. , .............. | jJtjRljP
Country
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
OCEANIA
Australia
Fiji
New Caledonia
New Zealand
Papua New Guinea
Vanuatu
Total
E10: METHANE EMISSIONS
Number
(1000 h)
341
2,404
2,745
45
23
29
36
292
350
60
55
250
64
17
29
250
58
49
180
1,787
42
123
33
104
88
1,051
693
5,885
362
8,381
401
42
10
100
1
3
557
Total Manure
mt/day
7,843
55,172
63,015
1,035
529
667
828
6,716
8,050
1,380
1,265
5,750
1,472
391
667
5,750
1,334
1,127
4,140
41,101
966
2,829
759
2,392
2,024
24,173
15,939
135,355
8,326
192,763
9,223
773
230
2,300
18
55
12,599
FROM
vs
mt/day
1,537
10,818
12,355
203
104
131
162
1,316
1,578
270
248
1,127
289
77
131
1,127
261
221
811
8,056
189
554
149
469
397
4,738
3,124
26,530
1,632
37,782
1,808
151
45
451
4
11
2,469
HORSE WASTE
fofB0
0.100
0.100
0.100
0.100
0.100
0.080
0.100
0.100
0.100
0.100
0.100
0.100
0.120
0.100
0.100
0.080
0.100
0.100
0.100
0.100
0.080
0.100
0.080
0.080
0.080
0.080
0.100
0.060
0.100
0.100
0.100
0.100
0.100
- " ":;!
Methane
mt/yr
12,262
87,440
99,702
1,618
827
1,043
1,036
10,500
12,586
2,158
1,978
8,990
2,301
734
1,043
8,990
1,669
1,762
6,473
63,706
1,510
4,423
949
3,740
2,532
30,235
19,936
169,297
13,017
245,639
8,652
952
360
3,596
23
68
13,650
APP-66
-------
pffgptAfele
|| Country
El 0: M ETHAN E EM ISSI ON S FROM HORSE WASTE
Number
(1000 h)
Total Manure
mt/day
VS
mt/day
Methane
f of B0 mt/yr
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
EAST & SUBSAHARAN
Chad
Ethiopia
Kenya
Mali
Mauritania
Niger
Somalia
| Total
3,100
315
5,850
490
1,950
114
703
313
438
93
112
2
430
170
4
6,160
250
171
328
655
22
473
495
22,638
AFRICA
150
1,610
2
62
17
296
1
2,138
57,040
5,796
107,640
9,016
35,880
2,098
12,935
5,759
8,059
1,711
2,061
37
7,912
3,128
74
113,344
4,600
3,146
6,035
12,052
405
8,703
9,108
416,539
2,760
29,624
37
1,141
313
5,446
18
39,339
11,180
1,136
21,097
1,767
7,032
411
2,535
1,129
1,580
335
404
7
1,551
613
14
22,215
902
617
1,183
2,362
79
1,706
1,785
81,642
541
5,806
7
224
61
1,067
4
7,710
0.100
0.100
0.100
0.098
0.100
0.100
0.100
0.100
0.100
0.100
0.098
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.050
0.050
0.100
0.050
0.050
0.050
70,263
7,140
132,593
10,828
44,198
2,584
15,934
7,094
9,927
2,108
2,475
45
9,746
3,853
91
139,619
5,666
3,876
7,434
14,846
499
10,721
11,219
512,758
1,700
18,246
23
1,405
193
3,354
11
24,932
APP-67
-------
4 ; ; 'TABLE
Country
WEST & SOUTHERN
Angola
Benin
Botswana
Burkina Faso
Cameroon
Cote d'lvoire
Ghana
Guinea
Guinea-Bissau
Lesotho
Madagascar
Namibia
Nigeria
Senegal
South Africa
Swaziland
Togo
Zimbabwe
Total
E10: METHANE EMISSIONS FROM HQRSB WASTE \ ; V
Number
(1000 h)
AFRICA
1
6
25
70
25
1
4
1
1
119
1
50
250
208
230
2
1
23
1,018
Total Manure
mt/day
18
110
460
1,288
460
18
74
18
18
2,190
18
920
4,600
3,827
5,290
37
18
423
19,789
VS
mt/day
4
22
90
252
90
4
14
4
4
429
4
180
902
750
1,037
7
4
83
3,879
/ofB0
0.100
0.100
0.050
0.050
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.100
0.100
0.075
0.100
0.100
0.100
Methane
mt/yr
23
136
283
793
567
23
91
23
23
2,697
23
567
5,666
4,714
6,203
45
23
521
22,420
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
Egypt
Iran
Iraq
Israel
Jordan
Kuwait
Libya
Morocco
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Republic
Total
410
187
10
316
55
4
3
3
56
182
3
20
43
56
620
3
1,971
7,544
3,441
184
5,814
1,012
92
55
55
1,030
3,349
55
368
791
1,030
11,408
55
36,285
1,479
674
36
1,140
198
18
11
11
202
656
11
72
155
202
2,236
11
7,112
0.093
0.093
0.093
0.093
0.093
0.100
0.093
0.100
0.093
0.100
0.093
0.093
0.093
0.093
0.100
0.093
8,596
3,921
210
6,625
1,153
144
63
68
1,174
4,125
63
419
902
1,174
14,053
63
42,751
APP-68
-------
J|sf?rv \'- %S^!US.5Ji
^ucrc^jL'+V^. '"-'" :.
Country
ASIA & FAR EAST
Bangladesh
Bhutan
Myanmar (Burma)
China
India
Indonesia
Japan
I Kampuchea
North Korea
South Korea
Laos
Malaysia
Mongolia
Pakistan
Philippines
Sri Lanka
Thailand
Viet Nam
Total
WORLD TOTAL
10: METHANE
\: -''''-" '- ''
Number Tc
(1000 h)
45
16
139
10,691
953
722
22
15
43
3
42
5
2,047
455
300
1
19
136
15,654
56,889
EMISSIONS
•. f f 5 f ^ '
)tal Manure
mt/day
828
294
2,558
196,714
17,535
13,285
506
276
791
55
773
92
37,665
8,372
5,520
18
350
2,502
288,135
1,109,566
FROM HORSE
' '. "
vs
mt/day
162
58
501
38,556
3,437
2,604
99
54
155
11
151
18
7,382
1,641
1,082
4
69
490
56,474
217,479
WASTE
-. -. -.
fofB0
0.100
0.100
0.100
0.100
0.100
0.200
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.050
0.100
0.100
0.100
0.100
_, •
Methane
mt/yr
1,020
363
3,150
242,316
21,600
32,729
791
340
975
68
952
113
23,198
5,156
6,800
23
431
3,082
343,106
1,368,665
APP-69
-------
TAB1E £1t* MET«ANE EMISSIONS FfcOiWJMULl WASTE /„>
* s •••:•:•: ^ --^ ^ %
Country
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Belgium
France
Greece
Ireland
Italy
Portugal
Spain
Total
EASTERN EUROPE
Albania
Bulgaria
Soviet Union
Yugoslavia
Total
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
1 Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
' ', ;',
Number
(1000 h)
4
1
5
1
12
83
2
50
90
110
348
22
25
1
10
58
165
80
1,980
10
600
5
32
140
122
23
38
85
68
10
3,130
45
5
14
220
2
4
72
6,850
,'
Total Manure
mt/day
92
23
115
23
276
1,909
46
1,150
2,070
2,530
8,004
506
575
23
230
1,334
3,036
1,472
36,432
184
11,040
92
589
2,576
2,245
423
699
1,564
1,251
184
57,592
828
92
258
4,048
37
74
1,325
126,040
'
VS
mt/day
18
5
23
5
54
374
9
225
406
496
1,569
99
113
5
45
261
595
289
7,141
36
2,164
18
115
505
440
83
137
307
245
36
11,288
162
18
50
793
7
14
260
24,704
, ,,
fofB0
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.080
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
' , ,*,$?:
Methane
mt/yr
144
36
180
36
432
2,985
72
1,798
3,236
3,956
12,514
791
899
29
360
2,078
3,740
1,813
44,877
227
13,599
113
725
3,173
2,765
521
861
1,927
1,541
227
70,943
1,020
113
317
4,986
45
91
1,632
155,258
APP-70
-------
[r^;;VS:nff^;^i;r^^HE EMISSIONS FROM MULE WASTE
p •. <. V V -.V- •• ^ ••
I Country
EAST & SUBSAHARAN
Ethiopia
Somalia
Total
•:•. '
Number
(1000 h)
AFRICA
1,500
23
1,523
•. •"• •• •" ^ "• f
Total Manure
mt/day
27,600
423
28,023
'
VS
mt/day
5,410
83
5,493
'
fofBQ
0.050
0.050
-
Methane
mt/yr
16,999
261
17,260
WEST & SOUTHERN AFRICA
Botswana
Lesotho
Namibia
South Africa
Zimbabwe
Total
4
1
6
14
1
26
74
18
110
322
18
543
14
4
22
63
4
106
0.050
0.100
0.050
0.050
0.100
45
23
68
252
23
410
NEAR EAST & MEDITERRANEAN
Algeria
Egypt
Iran
Iraq
Israel
Jordan
Morocco
Saudi Arabia
Sudan
Tunisia
Turkey
Total
ASIA & FAR EAST
Bhutan
Myanmar (Burma)
China
India
North Korea
Pakistan
Total
WORLD TOTAL
160
1
123
26
2
3
500
6
1
76
210
1,108
9
9
5,248
135
2
65
5,468
15,386
2,944
18
2,263
478
46
55
9,200
110
18
1,398
3,864
20,396
166
166
96,563
2,484
37
1,196
100,611
285,067
577
4
444
94
9
11
1,803
22
4
274
757
3,998
32
32
18,926
487
7
234
19,720
55,873
0.050
0.050
0.050
0.050
0.100
0.050
0.100
0.050
0.050
0.050
0.100
0.100
0.100
0.100
0.100
0.100
0.050
1,813
11
1,394
295
72
34
,11,333
68
11
861
4.760
20,652
204
204
118,948
3,060
45
737
123,198
331,550
APP-71
-------
TABLE E12: METHANE EMISSIONS FROM DONKEY WASTE, ; ;
Country
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
France
Greece
Ireland
Italy
Portugal
Spain
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Hungary
Romania
Soviet Union
Yugoslavia
Total
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Total
Number
(1000 h)
0
4
4
23
175
20
86
175
131
2
5
617
52
333
5
36
300
9
735
90
620
1,310
28
650
7
4
146
279
2
9
1
216
22
23
3,183
8
31
490
2
1
440
7,562
Total Manure
mt/day
0
61
61
352
2,678
306
1,316
2,678
2,004
31
77
9,440
796
5,095
77
551
4,590
138
11,246
1,098
7,564
15,982
342
7,930
85
49
1,781
3,404
24
110
12
2,635
268
281
38,833
98
378
5,978
24
12
5,368
92,256
VS
mt/day
0
12
12
69
525
60
258
525
393
6
15
1,850
156
999
15
108
900
27
2,204
215
1,483
3,132
67
1,554
17
10
349
667
5
22
2
516
53
55
7,611
19
74
1,172
5
2
1,052
18,082
fofB0
0
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.080
0.080
0.080
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
Methane
mt/yr
0
96
96
550
4,186
478
2,057
4,186
3,134
48
120
14,759
1,244
7,966
96
689
5,741
215
15,950
1,353
9,317
19,687
421
9,768
105
60
2,194
4,193
30
135
15
3,246
331
346
47,835
120
466
7,364
30
15
6,612
113,643
APP-72
-------
fe -r* =:f AM£ E12: METHANE EMlSSrONS FROM DONKEY WASTE
f« ?M^x.^;;\^s^% -
I Country
•. l
Number
(1000 h)
,, '' ; '
Total Manure
mt/day
"-
VS
mt/day
..
'°'B0
Methane
mt/yr
EAST & SUBSAHARAN AFRICA
Chad
Ethiopia
Mali
Mauritania
Niger
I Somalia
I Tanzania
| Uganda
Total
WEST & SOUTHERN
Angola
Benin
Botswana
Burkina Faso
Cameroon
I The Gambia
Ghana
Guinea
Guinea-Bissau
Lesotho
Malawi
Mozambique
Namibia
Nigeria
Senegal
South Africa
Swaziland
Toqo
89
Zambia
Zimbabwe
Total
255
3,930
550
149
512
25
172
17
4,610
AFRICA
5
1
145
200
39
4
25
3
3
126
1
20
68
700
210
210
14
3
2
101
1,880
3,111
47,946
6,710
1,818
6,246
305
2,098
207
68,442
61
12
1,769
2,440
476
49
305
37
37
1,537
12
244
830
8,540
2,562
3,213
171
37
24
1,232
23,587
610
9,397
1,315
356
1,224
60
411
41
13,415
12
2
347
478
93
10
60
7
7
301
2
48
163
1,674
502
630
33
7
5
242
4,623
0.050
0.050
0.050
0.050
0.050
0.050
0.100
0.100
0.100
0.100
0.050
0.050
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.050
0.100
0.100
0.050
0.100
0.100
0.100
0.100
1,916
29,530
4,133
1,120
3,847
188
2,585
255
43,574
75
15
1,090
1,503
586
60
376
45
45
1,894
15
301
511
10,520
3,156
2,512
210
45
30
1,518
24,505
APP-73
-------
„ _ ;'r;;fAByE'l12;;ME1^/y^llWfesrONS FROM DbjsikE^,WAfTE!;K;|
Country
Number
(1000 h)
Total Manure
mt/day
VS
rrrt/day
fofBQ
Methane
mt/yr
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
Egypt
Iran
Iraq
Israel
Jordan
Libya
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Republic
Total
ASIA & FAR EAST
Bhutan
China
India
North Korea
Pakistan
Total
WORLD TOTAL
1,300
475
1,950
1,800
410
5
19
61
800
24
110
650
200
220
1,200
520
9,744
18
10,856
1,328
3
3,022
15,227
41,379
15,860
5,795
23,790
21,960
5,002
77
232
744
9,760
293
1,342
7,930
2,440
2,684
14,640
6,344
118,892
220
132,443
16,202
37
36,868
185,769
509,694
3,109
1,136
4,663
4,304
980
15
45
146
1,913
57
263
1,554
478
526
2,869
1,243
23,303
43
25,959
3,176
7
7,226
36,411
99,900
0.050
0.050
0.050
0.050
0.050
0.100
0.050
0.050
0.100
0.050
0.050
0.050
0.050
0.050
0.100
0.050
0.100
0.100
0.100
0.100
0.050
9,768
3,569
14,652
13,525
3,081
120
143
458
12,023
180
827
4,884
1,503
1,653
18,034
3,907
88,327
271
163,145
19,957
45
22,708
206,126
506,981
APP-74
-------
L ; TABLE E13; METl^NE EMISSIONS FROM CAMEL WA3T€
r ^'.~' '"•"'•• vi " i °
Country
1
NORTH AMERICA
Canada
USA
Total
EASTERN EUROPE
Soviet Union
Total
EAST & SUBSAHARAN
Chad
Ethiopia
Kenya
Mali
Mauritania
Niger
Somalia
Total
j •, -.
Number
(1000 h)
0
0
0
265
265
AFRICA
509
1,060
790
241
810
417
6,680
10,507
-. "• "• f
Total Manure
mt/day
0
0
0
6,095
6,095
9,366
19,504
14,536
4,434
14,904
7,673
122,912
193,329
i "" '
VS
mt/day
0
0
0
975
975
1,498
3,121
2,326
710
2,385
1,228
19,666
30,933
•"
fofB0
0
0
0
0.080
0.050
0.050
0.050
0.050
0.050
0.050
0.050
Methane
mt/yr
0
0
0
4,903
4,903
3,803
7,920
5,903
1,801
6,052
3,116
49,914
78,509
WEST & SOUTHERN AFRICA
Burkina Faso
Nigeria
Senegal
Total
5
18
8
31
92
331
147
570
15
53
24
91
0.050
0.100
0.100
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
Egypt
Iran
Iraq
Israel
Jordan
Kuwait
Libya
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Republic
Total
265
130
70
27
55
10
14
8
185
54
82
417
2,850
5
184
3
63
4,422
4,876
2,392
1,288
497
1,012
230
258
147
3,404
994
1,509
7,673
52,440
92
3,386
55
1,159
81,411
780
383
206
79
162
37
41
24
545
159
241
1,228
8,390
15
542
9
185
13,026
0.050
0.050
0.050
0.050
0.050
0.100
0.050
0.100
0.050
0.100
0.050
0.050
0.050
0.050
0.050
0.100
0.050
37
269
120
426
1,980
971
523
202
411
231
105
120
1,382
807
613
3,116
21,296
37
1,375
45
471
33,684
APP-75
-------
TABLE Ei
•.
Country
ASIA & FAR EAST
China
India
Mongolia
Pakistan
Total
WORLD TOTAL
£ METHANE EMISSIONS f^OM CAMEL WASTE, ;?;-;j|f
,..'.-
Number
(1000 h)
475
1,390
547
949
3,361
18,586
, ,-. ,', ^ ___
Total Manure
mt/day
8,740
25,576
10,065
17,462
61,842
343,247
. •• '.
VS
mt/day
1,398
4,092
1,610
2,794
9,895
54,920
'...'.?:• '.'' .' ., " "•.T'.'&r
Methane
fofB0 mVyr
0.100 7,099
0.100 20,772
0.050 4,087
0.050 7,091
39,049
156,572
APP-76
-------
A>PEMD1X fc BEQUESTS F&B DATA - UNITED STAtES AMD WORt-b
Extensive review of the open literature revealed little information on the extent of use of different
types of animal waste management systems around the United States. To overcome this scarcity of
data, Extension personnel in each state were contacted and asked to provide the waste management
system information shown in Exhibit F1.
As with the United States, there was very little information in the open literature on the use of
different animal waste management systems around the world. The Ministries of Agriculture for the 127
countries in Exhibit 14 (excluding the United States) were contacted and asked to provide this
information for their country. In addition, individual researchers in many countries were also contacted
and asked to provide this information. One of the forms shown in Exhibits F2 and F3 was sent with each
request, depending on whether the country is classified as developed or developing by the Food and
Agriculture Organization of the United Nations (FAO, 1989).
APP-77
-------
EXHIBIT Rr REQUEST FOB DATA SENT TO U.S, EXTENSION PERSONNEL
Types of Animal Waste Management Systems
STATE: ' DATE:
NAME OF PERSON COMPLETING FOHM:
For each animal type (1 - 9), please estimate the percentage of animals in your state tnat are currently being
handled with each type of waste management system.
% of Animal Type
1. Dairy
*. Daily spread (solid/semi-solid)
* Tie-stall/stancnion (solid, with storage)
* Free stall - Liquid/slurry storage
- Anaerobic lagoon
* Other (please specify if over 5%):
2. Beef (finishing only)
Dryl<
* Anaerobic lagoon
* Slurry storage
* Other (please specify if over 5%):
3. Swine
* Pit storage - stored less than one month
- stored more than one month
* Anaerobic lagoons
* Dry lot
* Other (please specify if over 5%:
4. Caged layers
* D
eep pit stacking
* Anaerobic lagoons
* Slurry storage
* Other (please specify if over 5%):
5. Broilers
* Litter
* Other (please specify if over 5%) :_
6. Turkeys
* Litter
* Range
* Other (please specify if over 5%):_
7. Sheep
* Pasture
* Other (please specify if over 5%):_
8. Goats
* Pasture
* Other (please specify if over 5%) :_
9. Horses
* Paddock
* Pasture
* Other (please specify if over 5%) :_
Comments:
Total: 100%
Total 100%
Total: 100%
Total: 100%
Total: 100%
Total: 100%
Total: 100%
Total: 100%
APP-78
-------
BEQUEST RJft £AtA'3£NT T& OEVELQPEQ
Types of Animal Waste Management Systems
DATE:
Title
COUNTRY:
NAME OF PERSON COMPLETING FORM:
For each animal type (1 - 9), please estimate the percentage of animals in your country that are currently being
handled with each type of waste management system.
% of Animal Type
1. Dairy Cattle
* Daily spread (solid/semi-solid)
* Solid Storage
* Liquid/slurry storage
* Anaerobic lagoon
* Other (please specify if over 5%):
Total:
100%
2. Beef Cattle, Buffaloes
* Pasture
* Dry tot
* Anaerobic lagoon
* Slurry storage
* Other (please specify if over 5%):_
Total: 100%
3. Swine
* Pit storage - stored less than one month
- stored more than one month
* Solid Storage
* Anaerobic lagoons
* Drylot
* Other (please specify if over 5%):
Total: 100%
4. Laying Hens
* Deep pit stacking
* Anaerobic lagoons
* Slurry storage
* Other (please specify if over 5%):
Total: 100%
5. Broilers
* Litter
* Other (please specify if over 5%) :_
6. Turkeys
* Litter
* Range
* Other (please specify if over 5%):_
Total: 100%
Total: 100%
7. Sheep
* Pasture
•Drylot
8. Goats
* Other (please specify if over 5%):_
Pasture
* Other (please specify if over 5%) :_
Total: 100%
9. Horses, Mules, Donkeys
* Paddock
* Pasture
* Other (please specify if over 5%) :_
Total: 100%
APP-79
-------
EXHIBIT 8k REQUEST FGft DATA SENTTG
Types of Animal Waste Management Systems
DATE:
Title
COUNTRY:
NAME OF PERSON COMPLETING FORM:.
For each animal type (1 - 9), please estimate the percentage of animals in your country that are currently being
handled with each type of waste management system.
% of Animal Type
1. Dairy Cattle
* Pasture
* Daily spread (solid/semi-solid)
* Solid Storage
* Liquid/slurry storage
* Anaerobic lagoon
* Anaerobic digester
* Burned for fuel
* Other (please specify if over 5%):
Total: 100%
2. Beef Cattle, Buffaloes
* Pasture
* Drylot
* Anaerobic digester
* Daily spread (solid/semi-solid)
* Burned for fuel
* Other (please specify if over 5%):
3. Swine
* Daily Spread (solid/semi-solid)
* Solid Storage
* Anaerobic digester
* Drylot
* Liquid/slurry storage
* Other (please specify if over 5%):
4. Chickens, Ducks, Turkeys
* Range
* Anaerobic digester
* Litter
* Deep Pit Stacking
* Slurry storage
* Other (please specify if over 5%) :
5. Sheep
6. Goats
* Anaerobic Digester
* Other (please specify if over 5%):
* Pasture
* Anaerobic digester
* Other (please specify if over 5%) :
7. Horses, Mules, Donkeys, Camels
* Paddock
* Pasture
* Anaerobic digester
* Other (please specify if over 5%)
Comments:
Total:
100%
Total:
100%
Total:
100%
Total:
100%
Total:
100%
APP-80
-------
APPENDIX G: U.S. WASTE MANAGEMENT SYSTEM METHANE
PRODUCTION . . ^ » / •»:.
The amount of methane produced by each type of waste management system for each
animal type in the United States is given in Tables G1 through G9. The state category "other"
refers to animal populations that could not be specifically identified with a state. The following
abbreviations are used in the tables:
AWMS
An.Lag.
Daily-Spr
Sol-Stor
Liq/Slur
Other
Pit <1mo
Pit >1mo
Animal Waste Management System
Anaerobic Lagoon
Daily Spread
Solid Storage
Liquid/Slurry Storage
Other Animal Waste Management Systems
Pit Storage for less than 1 month
Pit Storage for more than 1 month
APP-81
-------
11
- ^ ' IE&BLE'
State
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
Total
,
et*
Rank
49
16
17
33
9
8
46
48
14
24
41
6
20
12
28
2
11
30
45
40
43
32
15
5
26
10
34
18
3
47
44
27
38
37
23
4
25
31
50
36
7
13
1
35
21
42
29
19
39
22
METHANE EMISSIONS FB
An. Lag
0
416
0
0
0
0
0
0
771
0
0
744
0
4,033
1,371
13,185
0
0
0
63
0
1,651
0
4,966
0
0
239
402
5,194
0
0
0
16
0
1,141
0
589
0
0
0
5,708
0
0
0
0
0
0
0
0
0
40,489
Liq/Slur
0
0
0
0
0
0
0
0
0
51
0
165
247
896
305
0
0
0
0
56
0
367
789
0
14
0
213
45
0
0
0
0
2
21
253
0
44
18
0
0
317
0
0
0
93
0
0
115
0
163
4,174
m'x.s.
Dry lot
0
416
137
3,944
6,143
11,594
0
0
86
146
284
8,097
2,935
3,585
2,743
20,401
287
103
0
105
0
2,568
3,550
552
130
1,048
27
411
28,277
0
35
1,604
327
188
2,281
3,679
1,004
880
0
233
2,378
229
26,438
573
419
0
2,439
1,093
116
1,226
142,713
BEEF, ABMS'S
Pasture
103
25,456
25,384
9,548
43,626
32,510
403
238
29,108
20,191
2,571
54,730
18,882
21,789
13,546
67,241
32,221
15,399
481
2,692
674
8,968
23,786
60,274
19,768
37,214
10,355
23,228
62,502
372
559
18,306
6,945
8,281
16,907
67,911
18,382
13,511
41
8,300
47,624
29,886
183,442
10,053
21,090
1,286
14,283
22,692
7,143
19,918
1,179,819
,,
;;
-------
fl^j^W'MfT i&iiijtE' Ebfics'siess^ ?s
£'• '•':_'•_ >. . s.-;
\ State
AK
AL
AR
AZ
CA
CO
CT
IDE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
Total
. s. . . . ^ •- -t ... .-f
Rank
49
25
26
, 30
1
37
40
48
24
15
38
16
14
22
17
33
10
31
45
29
41
9
6
3
32
39
28
46
34
44
43
12
35
7
8
13
11
20
50
21
19
18
4
36
23
27
5
2
42
47
..f ^X.XX
An. Lag
82
8,663
7,589
3,763
193,781
1,704
0
185
1,491
16,403
1,629
4,197
7,701
4,545
8,379
0
18,281
2,247
0
988
0
8,075
0
61,564
3,060
1,274
2,359
85
0
0
0
23,710
0
0
8,702
7,003
18,610
0
0
14,628
15,143
4,580
38,966
360
0
0
41,014
0
234
456
531,451
=====
*..
Liq/Slur
130
0
0
0
0
757
1,873
287
0
521
666
6,217
14,546
3,030
11,172
4,188
1,711
0
831
5,268
1,288
10,767
25,303
0
68
448
3,670
19
489
884
879
0
1,621
16,067
11,603
0
3,446
1,455
73
203
3,365
8,142
20,782
80
11,716
4,739
11,393
27,178
1,041
160
218,074
======
0K}t,S* MIR? ABMEPS {HEmiC ^S^YiM.) \
. -r
Solid
2
0
0
0
0
0
9
0
0
0
0
10,103
0
1,010
931
0
0
0
186
274
289
2,153
12,651
0
68
271
524
849
0
442
197
0
2,836
4,017
2,321
0
49
1,091
16
102
1,346
0
0
3,597
0
1,062
0
13,589
260
97
60,342
=====
Spread
1
481
1,265
0
0
1,610
411
123
414
130
18
622
86
2,272
931
1,570
1,604
83
415
1,235
644
4,038
8,434
2,280
34
230
1,311
38
856
110
439
146
203
14,058
4,351
130
123
17,277
36
102
1,010
1,018
1,299
160
976
2,369
570
31,708
195
82
107,497
=====
Other
103
0
0
3,763
32,297
0
0
0
7,290
5,155
35
622
257
2,525
0
0
4,597
4,120
0
0
0
1,436
0
0
3,179
83
0
0
3,522
0
0
0
0
0
1,547
16,600
1,674
0
0
0
0
7,124
0
0
0
0
0
0
104
30
96,063
=====
•
Total
318
9,144
8,854
7,527
226,078
4,071
2,293
595
9,196
22,209
2,347
21,760
22,589
13,381
21,413
5,758
26,192
6,451
1,432
7,765
2,221
26,469
46,388
63 , 844
6,410
2,306
7,864
990
4,867
1,436
1,515
23,856
4,659
34,142
28,523
23,733
23,902
19,823
125
15,034
20,863
20,865
61,046
4,196
12,693
8,170
52,977
72,476
1,836
825
1,013,428
=================
APP-83
-------
: - ""
,;,
, - TABLE G3
State
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
Total
Rank
50
18
17
24
25
28
46
38
30
10
36
1
31
3
5
13
9
29
42
27
45
12
11
2
22
33
4
26
6
47
40
43
44
34
7
23
32
21
49
15
14
8
19
39
16
48
35
20
37
41
; {- ' ,1^*-,
n^KBISpJp EMljS$£0]SS -
An . Lag .
40
15,364
18,000
6,398
5,516
2,691
49
321
2,449
39,878
665
20,559
1,617
70,816
54,455
22,060
42,158
3,163
48
4,268
13
28,315
0
118,277
7,342
0
90,873
3,432
68,892
24
62
134
205
336
41,135
6,843
1,360
0
8
19,911
17,670
42,108
10,035
418
18,801
9
808
0
543
250
788,317
Drylot
0
0
571
0
0
311
0
18
498
1,303
16
22,843
67
4,721
2,420
3,268
703
18
93
95
26
899
5,213
3,285
194
535
2,164
381
1,094
48
121
104
68
224
988
380
36
2,059
16
123
2,945
877
637
139
0
17
0
721
60
29
60,331
•.-!••.,•.
f f~ft < -JJ.V f
F80» tf,S,; SWISm'jMBHS'S ,{|
Pit < 1 mo
0
0
0
0
0
262
0
0
8
0
39
8,376
22
3,147
1,210
0
410
0
4
0
1
300
5,213
0
69
334
0
572
12,029
0
5
15
0
37
124
127
212
53
1
0
2,454
0
478
0
0
1
30
1,442
60
24
37,057
Pit > 1 mo
0
379
571
0
0
598
0
250
0
1,303
166
59,391
314
28,326
29,043
4,902
117
0
148
759
41
5,843
20,852
0
249
668
4,327
1,144
2,187
5
192
30
0
896
11,365
0
145
6,335
26
246
4,908
585
637
0
464
28
359
10,093
121
56
198,070
(£Tlil#;|KJfS
Other
0
0
0
0
68
75
31
0
0
130
18
25,889
22
1,574
0
0
0
0
0
0
0
225
10,426
0
180
134
0
0
0
0
0
0
0
0
988
0
266
0
0
0
0
0
1,274
0
0
0
0
0
0
7
41,306
**# ^f&&7*$J'ls3£&
•" *....?...•*.<'. * -x- ••
Total
40
15,743
19 , 143
6,398
5,584
3,937
79
589
2,955
42,614
906
137,057
2.044
108,584
87,128
30,230
43,388
3,182
292
5,122
82
35,580
41,703
121,562
8,033
1,671
97,64
5,529
84,202
78
379
282
274
1,493
54,599
7,350
2,019
8,446
51
20,279
27,978
43,570
13,061
557
19,265
54
1,197
12,256
784
365
1,125,080
APP-84
-------
METHANE EMISSIONS FROM U.S.
1 State Rank
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
IID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
Total
50
1
2
44
6
28
32
42
9
10
15
17
37
20
12
39
13
11
41
33
25
19
16
18
5
40
4
43
34
46
38
31
49
22
14
29
23
8
45
7
30
21
3
36
27
47
26
24
35
48
An. Lag. Liq/Slur Deep Pit
1
15,086
10,883
0
3,850
223
0
0
2,460
158
1,441
289
0
535
0
0
1,913
2,583
0
0
0
251
0
0
8,883
49
7,758
20
0
0
0
382
0
0
0
0
482
0
0
3,715
436
207
9,962
0
0
0
0
0
0
1
71,568
0
419
3,628
0
367
99
0
0
273
351
0
128
225
0
413
0
230
0
33
0
176
56
894
479
116
22
287
4
0
0
55
42
0
470
0
287
88
373
7
0
0
591
0
0
0
6
194
62
0
0
10,377
0
105
0
28
1,375
273
435
67
797
526
0
722
37
268
1,963
164
5
0
74
343
396
474
671
479
0
60
216
20
337
22
124
48
1
235
1,720
287
195
1,212
16
258
97
5
138
93
110
12
436
172
0
1
15,016
Other
0
0
0
0
2,750
0
0
0
273
2,262
180
64
0
0
0
0
10
15
18
0
98
111
0
0
232
0
1,437
0
0
0
31
53
1
78
0
0
0
2,238
4
103
0
0
2,767
186
513
3
0
499
313
14,242
-*
Total
2
15,610
14,510
28
8,341
595
435
67
3,804
3,296
1,621
1,203
262
803
2,376
164
2,159
2,598
126
343
670
892
1,565
959
9,231
130
9,698
44
337
22
210
526
2
784
1,720
574
765
3,824
26
4,076
533
802
12,868
280
623
629
733
313
111,203
APP-85
-------
•"
State
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
Other
Total
«•*«*£»
Rank
50
2
1
45
8
34
37
9
13
3
32
27
38
30
26
42
24
25
43
7
36
29
18
17
5
41
4
44
33
47
39
35
51
28
22
14
21
11
48
15
31
16
6
40
10
46
20
23
19
49
12
An. Lag
0
1,579
1,221
0
251
12
0
0
105
14
3
18
0
37
0
0
141
176
0
0
0
21
0
0
1,091
5
611
2
0
0
0
21
0
0
0
0
25
0
0
313
40
18
620
0
0
0
0
0
0
0
0
6,324
^ii/ffdri
Liq/Slur
0
44
407
0
24
5
0
0
12
31
4
8
13
0
30
0
17
0
2
0
8
5
60
40
14
2
23
0
0
0
4
2
0
48
0
21
5
31
0
0
0
51
0
0
0
0
13
5
0
0
0
929
fy^mQii
Litter
0
10,649
13,589
0
3,214
0
0
3,295
1,867
11,710
34
45
0
0
0
0
41
0
0
3,824
0
11
502
826
5,469
0
7,578
0
17
0
0
0
0
38
182
1,832
262
1,923
0
1,073
0
1,318
4,035
0
2,663
0
427
198
533
0
2,174
79,329
'' "Vffo. Afcytf^y 't •ttf ' tf^tiftf'
rfCcK / jfKfHUSf jqt" \£U1*
Deep Pit
0
11
0
2
90
14
18
8
34
46
2
44
2
19
142
11
0
0
5
24
17
40
45
40
0
6
17
2
18
2
9
3
0
24
102
21
10
99
0
22
9
0
9
5
8
1
29
15
0
0
0
1,025
>"ff
Vtiffc TflNf
Other
0
0
0
0
180
0
0
0
12
199
0
4
0
0
0
0
1
1
1
0
4
9
0
0
29
0
113
0
0
0
2
3
0
8
0
0
0
184
0
9
0
0
172
10
36
0
0
42
26
0
0
1,045
Total
0
12,283
15,217
2
3,759
31
18
3,303
2,029
12 , 000
44
119
15
56
172
11
200
177
9
3,848
29
86
606
906
6,603
13
8,342
4
35
2
15
29
0
117
284
1,875
302
2,236
1
1,417
48
1,388
4,836
15
2,707
2
469
261
559
0
2,174
88,652
APP-86
-------
•B
State
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SG
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
OTHER
Total
Rank
5
3
27
15
10
19
8
23
24
25
14
2
6
1
21
18
28
26
22
13
20
9
11
16
12
7
17
4
Range
0
0
45
0
92
0
1
0
0
59
0
0
0
13
32
0
0
0
2
1
0
10
0
0
0
0
237
36
0
0
1
0
0
0
0
0
0
39
0
14
0
0
0
193
48
0
0
0
11
0
114
950
Litter
0
0
848
0
1,222
0
0
0
0
59
0
387
0
72
607
11
0
0
6
6
0
138
1,908
818
0
0
2,137
24
88
1
4
0
0
17
178
0
82
352
0
262
117
0
0
0
759
0
0
0
103
0
840
11,046
Other
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Total
0
0
892
0
1,313
0
1
0
0
119
0
387
0
84
639
11
0
0
7
7
0
149
1,908
818
0
0
2,374
59
88
1
5
0
0
17
178
0
82
392
0
276
117
0
0
193
808
0
0
0
114
0
954
11,996
APP-87
-------
-, fABJ-S
State
AK
AL'
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
Other
Total
f
"«»- .MSlffl
Rank
34
11
2
8
40
9
12
18
21
16
33
37
41
31
39
25
13
19
5
35
15
22
42
32
7
26
29
14
23
10
20
4
36
1
6
24
38
28
27
17
3
30
kHE EMISSIONS
Pasture
99
0
0
1,095
2,999
1,381
23
0
0
0
0
1,341
880
406
373
551
99
55
29
71
32
327
675
378
0
1,777
82
527
358
35
70
1,591
276
155
664
392
1,177
208
0
0
2,064
80
4,389
1,611
386
34
245
241
447
2,199
182
30,000
?SOK U.S.
Other
0
0
0
0
333
73
23
0
0
0
0
14
46
21
41
0
5
0
15
37
16
21
75
42
0
36
15
28
40
0
36
0
6
84
35
0
116
208
0
0
0
0
1,097
85
0
17
0
7
50
116
0
2,739
SHEEP; AWMS' S ;^M&^XO%7GiI$/¥£4lQ!''&' «
Total
99
0
0
1,095
3,332
1,454
46
0
0
0
0
1,355
926
427
415
551
105
55
44
108
48
348
750
420
0
1,813
97
554
398
35
107
1,591
281
239
699
392
1,293
417
0
0
2,064
80
5,486
1,696
386
51
245
248
497
2,315
182
32,739
APP-88
-------
^i^M&ifcfc ifc^ mflaiim^igKsiisiiaaf ri&kJafc"&a' &&*& <#mic JO^/TSAR)
[ State
AK
AL
AR
AZ
CA
CO
CT
DE
FL
IGA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
1 WY
1 Total
Rank
50
14
11
3
6
25
44
49
12
8
47
23
37
21
24
19
15
32
35
34
45
7
27
9
29
38
20
40
30
42
36
2
43
16
10
4
13
17
48
28
39
5
1
41
22
46
26
18
31
33
Pasture
1
31
39
275
0
21
4
1
27
59
2
21
7
24
21
26
27
11
8
9
4
61
19
50
15
6
22
5
13
4
8
391
4
27
49
203
26
26
1
18
5
84
4,050
4
23
3
21
24
9
10
5,801
Other
0
0
0
29
83
0
0
0
10
0
0
0
1
0
0
0
0
0
0
0
0
1
0
0
1
0
2
0
0
0
0
0
0
0
0
0
5
0
0
0
0
0
1,013
0
0
0
0
1
2
0
1,149
^==^=^=
Total
1
31
40
304
83
21
4
1
38
59
3
21
8
24
21
26
28
11
8
9
4
62
19
50
15
6
25
5
13
4
8
391
4
27
49
203
31
26
1
18
5
84
5,063
4
23
3
21
26
12
10
6,950
APP-89
-------
1 1 &BEE G
State
AK
AL
AR
AZ
CA
CO
CT
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
Total
*: METHAKE EMISSIONS
Rank
49
32
29
10
2
5
44
48
6
33
47
14
18
20
23
19
4
31
42
37
45
17
21
8
36
9
35
34
25
46
38
24
39
22
7
3
15
11
50
40
28
13
1
30
26
43
16
12
41
27
Pasture
60
622
1,299
1,646
4,271
2,349
124
54
1,311
734
70
1,960
1,208
797
945
1,796
2,259
1,042
279
619
148
1,306
975
2,405
607
2,573
699
814
1,748
15
540
465
509
480
135
2,769
1,157
1,170
24
301
1,300
1,680
5,023
1,135
1,713
177
1,036
858
135
1,428
56,769
^8OK ¥xS.
Paddock
7
622
144
886
1,068
481
124
54
328
404
57
170
705
597
945
200
968
347
150
333
79
734
975
267
405
26
107
349
92
131
291
1,396
127
959
2,570
692
947
1,170
13
301
325
560
0
284
17
95
1,036
257
406
292
23,498
HOBSE/^BMS'jSL
Other
0
0
0
0
0
0
0
0
1,092
86
0
0
101
597
0
0
0
0
0
0
0
0
0
0
0
0
269
0
0
0
0
0
0
480
0
0
0
0
0
0
0
0
3,348
0
0
0
0
1,201
0
0
7,173
i^MWFU TiT* flVtW'O £W ft. 12 "*i
-------
APPENDIX H: U.S. ANIMAL WASTE MANAGEMENT SYSTEM USAGE
Tables H1 to H9 list the percent of animal wastes managed by the animal waste management
systems in each state of the U.S. The following abbreviations are used in the tables:
An.Lag.
Liq/Slur
Other
Pit St. <1 mnth
Pit St. >1 mnth
Anaerobic Lagoon
Liquid/Slurry Storage
Other Animal Waste Management Systems
Pit Storage for less than 1 month
Pit Storage for more than 1 month
APP-91
-------
1 - ;- ;1ABLE Bit
STATE An.
AL
AK
AZ
AR
CA
CO
CT
DE
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
MI
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VT
VA
WA
WV
WI
WY
U.S. Average
* ANIMAL
WASTE
Lag Drylot
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
2%
1%
0%
2%
0%
0%
0%
0%
0%
2%
0%
0%
1%
0%
1%
0%
0%
0%
0%
0%
0%
0%
1%
0%
0%
0%
0%
0%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
<1%
2%
0%
30%
1%
12%
25%
0%
0%
0%
1%
10%
13%
14%
17%
13%
23%
1%
1%
0%
4%
0%
22%
13%
1%
1%
3%
31%
5%
0%
6%
8%
2%
0%
2%
12%
5%
5%
6%
0%
3%
5%
1%
13%
5%
0%
2%
15%
2%
5%
6%
10%
MANAGEMEI
Liq/Slur
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
2%
1%
0%
0%
0%
0%
0%
1%
0%
2%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
0%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
<1%
W SYSTEM:
Pasture
98%
100%
70%
99%
88%
72%
100%
100%
99%
99%
90%
86%
83%
81%
87%
76%
99%
99%
100%
95%
100%
75%
85%
99%
98%
97%
68%
95%
100%
94%
92%
97%
97%
98%
87%
95%
94%
94%
100%
97%
94%
99%
87%
95%
100%
98%
85%
98%
95%
94%
89%
?• t?^& *tXf """C ttty yp <• *• % f A
a- *? UK. v * «5t + UJ3J1*:.- % »
Other
0%
0%
0%
0%
0%
3%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
APP-92
-------
STATE
AL
AK
AZ
AR
CA
CO
CT
DE
FL
GA
HI
1 ID
| IL
IN
IA
KS
KY
LA
ME
MD
MA
MI
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VT
VA
WA
WV
WI
WY
U.S.
An.
Lagoon
50%
10%
10%
25%
40%
5%
0%
5%
2%
35%
31%
10%
5%
10%
3%
0%
19%
6%
0%
2%
0%
5%
0%
10%
60%
12%
0%
1%
0%
0%
90%
0%
5%
0%
5%
15%
42%
0%
0%
80%
25%
5%
25%
1%
0%
0%
40%
2%
0%
12%
Average 11%
Liq/
Slurry
0%
71%
0%
0%
0%
10%
53%
35%
0%
5%
57%
85%
15%
60%
20%
40%
8%
0%
29%
48%
29%
30%
30%
1%
0%
19%
5%
1%
40%
29%
0%
20%
35%
20%
30%
0%
35%
2%
29%
5%
25%
40%
60%
1%
29%
75%
50%
40%
15%
19%
21%
=====
Daily
Spread
50%
2%
0%
75%
0%
85%
47%
60%
10%
5%
6%
2%
45%
20%
8%
60%
30%
4%
58%
45%
58%
45%
40%
2%
40%
39%
35%
8%
20%
58%
10%
70%
50%
10%
45%
5%
5%
95%
58%
10%
30%
20%
15%
8%
58%
25%
10%
30%
70%
39%
41%
=====
lillllliltii
Solid
Stor
0%
2%
0%
0%
0%
0%
1%
0%
0%
0%
0%
0%
10%
10%
65%
0%
0%
0%
13%
5%
13%
12%
30%
2%
0%
23%
0%
90%
40%
13%
0%
10%
10%
70%
12%
0%
1%
3%
13%
5%
20%
0%
0%
90%
13%
0%
0%
20%
15%
23%
18%
=====
Other
0%
15%
90%
0%
60%
0%
0%
0%
88%
55%
6%
3%
25%
0%
4%
0%
43%
90%
0%
0%
0%
8%
0%
85%
0%
7%
60%
0%
0%
0%
0%
0%
0%
0%
8%
80%
17%
0%
0%
0%
0%
35%
0%
0%
0%
0%
0%
8%
0%
7%
8%
APP-93
-------
t •• \< ' - ,'f.
An.
STATE Lagoon
AL
AK
AZ
AR
CA
CO
CT
DE
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
MI
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VT
VA
WA
WV
WI
WY
U.S.
90%
100%
100%
70%
90%
24%
15%
20%
35%
68%
32%
40%
25%
25%
3%
30%
80%
95%
3%
50%
3%
42%
0%
59%
80%
0%
35%
25%
5%
3%
10%
5%
70%
20%
37%
60%
25%
0%
3%
90%
20%
80%
35%
25%
3%
90%
30%
25%
0%
24%
Average 29%
Drylot
0%
0%
0%
20%
0%
25%
0%
10%
64%
20%
7%
15%
15%
10%
30%
40%
12%
5%
53%
10%
53%
12%
20%
14%
20%
40%
5%
75%
90%
53%
70%
30%
15%
20%
8%
30%
6%
39%
53%
5%
30%
15%
20%
75%
53%
0%
0%
25%
10%
25%
20%
Pit St.
<1 mnth
0%
0%
0%
0%
0%
21%
0%
0%
1%
0%
17%
5%
10%
5%
11%
0%
7%
0%
2%
0%
2%
4%
20%
5%
0%
25%
55%
0%
0%
2%
10%
5%
0%
30%
1%
10%
35%
1%
2%
0%
25%
0%
15%
0%
2%
0%
10%
25%
20%
21%
12%
Pit St.
>1 mnth
10%
0%
0%
10%
0%
24%
0%
70%
0%
10%
36%
35%
45%
60%
39%
30%
1%
0%
42%
40%
42%
39%
40%
9%
0%
25%
5%
0%
5%
42%
10%
60%
15%
30%
46%
0%
12%
60%
42%
5%
25%
5%
10%
0%
42%
10%
60%
25%
70%
24%
32%
^ X^^'^XJ"' *••';'' '"'f 'r '•*•'/!
Other
0%
0%
0%
0%
10%
6%
85%
0%
0%
2%
8%
5%
5%
0%
13%
0%
0%
0%
0%
0%
0%
3%
20%
13%
0%
10%
0%
0%
0%
0%
0%
0%
0%
0%
8%
0%
22%
0%
0%
0%
0%
0%
20%
0%
0%
0%
0%
0%
0%
6%
7%
APP-94
-------
STATE
AL
AK
AZ
AR
CA
CO
CT
DE
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
MI
MN
MI
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VT
VA
WA
WV
WI
WY
An.
Lagoon
80%
15%
0%
40%
7%
4%
0%
0%
12%
1%
80%
0%
10%
0%
2%
0%
61%
95%
0%
0%
0%
3%
0%
85%
0%
4%
0%
0%
0%
0%
20%
0%
30%
5%
0%
0%
11%
0%
0%
40%
20%
7%
40%
0%
0%
0%
0%
0%
0%
4%
U.S. Average 14%
Deep
Pit
10%
63%
100%
0%
45%
88%
100%
100%
70%
30%
10%
40%
90%
95%
90%
100%
3%
0%
81%
100%
81%
85%
75%
0%
80%
88%
100%
75%
100%
81%
45%
60%
15%
90%
100%
80%
80%
65%
81%
50%
80%
3%
10%
50%
81%
30%
90%
0%
55%
88%
56%
======
Liq/
Slurry
10%
12%
0%
60%
3%
8%
0%
0%
6%
5%
0%
60%
0%
5%
4%
0%
33%
0%
9%
0%
9%
3%
25%
5%
20%
8%
0%
0%
0%
9%
10%
30%
5%
5%
0%
20%
9%
5%
9%
0%
0%
90%
0%
0%
9%
0%
10%
0%
5%
8%
10%
=====
,:*^::^^
Other
0%
10%
0%
0%
45%
0%
0%
0%
12%
65%
10%
0%
0%
0%
4%
0%
3%
5%
10%
0%
10%
10%
0%
10%
0%
0%
0%
25%
0%
10%
25%
10%
50%
0%
0%
0%
0%
30%
10%
10%
0%
0%
50%
50%
10%
70%
0%
100%
40%
0%
20%
APP-95
-------
ZABM &S
State
AL
AK
AZ
AR
CA
CO
CT
DE
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MA
MD
MI
MN
MS
MO
MT
NC
ND
NH
NJ
NM
NY
NE
NV
OH
OK
OR
PA
RI
sc
SD
TN
TX
UT
VA
VT
WV
WA
WI
WY
Other
U.S. Aver
S- ANIMAI*
Litter
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
age 100%
WASf B, MRA
-------
p^ISi
S7 ? : ANIMAL WASTE - :
tfflfflffi/ SIESTS&S' JttlL ff.S- .
P^llf^^^f^ ',1-r^ '••-'' - ' *1
1 STATE
AL
AK
AZ
AR
CA
CO
CT
DE
FL
GA
HI
ID
IL
IN
IA
KS
KY
ILA
ME
MD
MA
MI
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
RI
SC
SD
TN
XX
UT
VT
VA
WA
WV
WI
WY
Othei
U.S.
ii^™^^—— •
Pasture
100%
100%
90%
95%
50%
95%
95%
90%
99%
100%
95%
100%
66%
66%
66%
94%
90%
90%
98%
90%
98%
100%
66%
100%
65%
98%
95%
95%
100%
91%
50%
100%
100%
80%
95%
66%
100%
100%
90%
97%
95%
c 100%
Average 92%
Other
0%
0%
10%
5%
50%
5%
5%
10%
1%
0%
5%
0%
34%
34%
34%
6%
10%
10%
2%
10%
2%
0%
34%
0%
35%
2%
5%
5%
0%
9%
50%
0%
0%
20%
5%
34%
0%
0%
10%
3%
5%
B?
' f ABt£ 1J0
<.•• '! •.
STATE
AL
AK
AZ
AR
CA
CO
CT
DE
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
MI
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VT
VA
WA
WV
WI
WY
Other
U.S. Av
~
: . ANIMAL WASTE MANAGEMENT
$m iMk,fla*
Pasture
100%
100%
95%
99%
0%
100%
100%
100%
80%
100%
92%
92%
100%
100%
100%
100%
99%
100%
100%
100%
100%
99%
100%
95%
100%
99%
100%
98%
100%
100%
100%
100%
90%
100%
100%
100%
84%
100%
100%
100%
100%
100%
80%
100%
100%
99%
100%
80%
95%
100%
erage B4T~
*s-_
Other
0%
0%
5%
1%
100%
0%
0%
0%
20%
0%
8%
8%
0%
0%
0%
0%
1%
0%
0%
0%
0%
1%
0%
5%
0%
1%
0%
2%
0%
0%
0%
0%
10%
0%
0%
0%
16%
0%
0%
0%
0%
0%
20%
0%
0%
1%
0%
20%
5%
0%
== '1
APP-97
-------
STATE Paddock
AL
AK
AZ
AR
CA
CO
CT
DE
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
MI
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
RI
SC
SD
TE
TX
UT
VT
VA
WA
WV
WI
WY
U.S.
50%
10%
35%
10%
20%
17%
50%
50%
15%
33%
45%
35%
30%
50%
8%
10%
30%
25%
35%
35%
35%
36%
50%
40%
10%
1%
5%
20%
90%
35%
75%
50%
10%
30%
95%
20%
45%
50%
35%
50%
20%
25%
0%
20%
35%
1%
50%
75%
15%
17%
Average 27%
Pasture
50%
90%
65%
90%
80%
83%
50%
50%
60%
60%
55%
60%
40%
50%
92%
90%
70%
75%
65%
65%
65%
64%
50%
60%
90%
99%
95%
80%
10%
65%
25%
25%
65%
70%
5%
80%
55%
50%
65%
50%
80%
75%
60%
80%
65%
99%
50%
25%
50%
83%
66%
Other
0%
0%
0%
0%
0%
0%
0%
0%
25%
7%
0%
5%
30%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
25%
25%
0%
0%
0%
0%
0%
0%
0%
0%
0%
40%
0%
0%
0%
0%
0%
35%
0%
7%
APP-98
-------
I: mOBAi ANIMAL WASTE WfANASEIVENT
Tables It to 15 list the percent of animal wastes managed by the animal waste management
systems (AWMS) for the major animal types in each country of the world.
APP-99
-------
TABLE It:
OLOBAt AWMS USAGE fOH NOlW3AlfiY CATTLE0
Anaerobic Liquid
Country Lagoons Systems*
NORTH AMERICA
Canada
United States
Average
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Average
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Average
OCEANIA
Australia
Fiji
New Caledonia
New Zealand
Papua New Guinea
Vanuatu
Average
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
0%
<1%
<1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
9%
<1%
1%
60%
35%
0%
20%
60%
60%
60%
25%
79%
90%
75%
10%
20%
85%
80%
60%
55%
5%
20%
100%
80%
2%
15%
25%
25%
10%
29%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Solid
Daily Storage
Spread & Drylot
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
17%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
50%
10%
14%
0%
0%
0%
0%
0%
0%
0%
0%
21%
0%
0%
0%
0%
10%
0%
0%
2%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
0%
0%
1%
1%
1%
1%
0%
Pasture,
Range &
Paddock
27%
89%
84%
30%
30%
100%
30%
30%
30%
30%
60%
0%
10%
0%
90%
80%
5%
3%
30%
33%
95%
40%
0%
20%
49%
25%
25%
25%
90%
27%
100%
100%
100%
100%
100%
100%
100%
99%
99%
99%
99%
99%
99%
99%
99%
99%
Used
for
Fuel8
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Other
Systems0
15%
<1%
1%
10%
35%
0%
50%
10%
10%
10%
15%
0%
0%
25%
0%
0%
0%
0%
10%
9%
0%
40%
0%
0%
49%
60%
50%
50%
0%
45%
0%
0%
0%
0%
0%
0%
0%
1%
0%
1%
1%
0%
0%
0%
0%
1%
APP-100
-------
xV;WTABUm:
GtOBAt AWSflS USASE FOR NON-DAIRY CATTLE1*
Solid Pasture,
Anaerobic Liquid Daily Storage Range &
Country Lagoons SystemsA Spread & Drylot Paddock
Used
for Other
Fuel8 Systems0
LATIN AMERICA (continued)
El Salvador
Guatemala
Guyana
Haiti
Honduras
1 Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Average
AFRICA
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Central African Rep.
Chad
Cote d'lvoire
Ethiopia
The Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Madagascar
Malawi
Mali
Mauritania
Mozambique
Namibia
Niger
Nigeria
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
Swaziland
Tanzania
Togo
Uganda
Zaire
Zambia
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
3%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
10%
0%
0%
0%
0%
60%
9%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
0%
1%
1%
2%
1%
0%
1%
2%
1%
1%
2%
2%
2%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
5%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
20%
0%
0%
0%
0%
0%
0%
99%
95%
98%
99%
98%
99%
99%
99%
98%
99%
99%
98%
98%
98%
99%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
85%
100%
100%
100%
100%
40%
80%
100%
100%
100%
100%
100%
100%
100%
100%
100%
80%
100%
100%
100%
100%
100%
100%
0%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
11%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
1%
0%
0%
0%
1%
0%
0%
0%
0%
0%
0%
0%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
APP-101
-------
. TABLE It: GLOBAt AWMS USAGE FOR tfQtyOAlRV CATOE1
Country
AFRICA (continued)
Zimbabwe
Average
Anaerobic
Lagoons
0%
0%
Liquid
SystemsA
0%
0%
Daily
Spread
0%
1%
Solid
Storage
& Dry lot
0%
3%
Pasture,
Range &
Paddock
100%
96%
Used
for
Fuel8
0%
0%
Tj j :f f ff ? -f
f f f j} ffff *fyjf
Other
Systems0
0%
0%
NEAR EAST & MEDitERRANEAN
Afghanistan
Algeria
Egypt
Iran
Iraq
Israel
Jordan
Kuwait
Libya
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Rep.
Average
ASIA
Bangladesh
Bhutan
China
India
Indonesia
Japan
Kampuchea
Laos
Malaysia
Mongolia
Myanmar (Burma)
Nepal
North Korea
Pakistan
Philippines
South Korea
Sri Lanka
Thailand
Viet Nam
Average
GLOBAL AVERAGE
A Includes liquid/slurry
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
31%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
<1%
storage and
B Includes anaerobic digesters and
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
20%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
6%
pit storage.
0%
0%
25%
0%
15%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
20%
20%
0%
15%
80%
0%
20%
20%
5%
20%
20%
20%
20%
50%
10%
20%
20%
20%
20%
16%
6%
0%
0%
0%
0%
0%
50%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
50%
5%
0%
56%
0%
0%
2%
0%
0%
0%
0%
0%
0%
2%
0%
0%
0%
14%
7%
Includes
85%
85%
0%
85%
30%
50%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
50%
50%
50%
13%
0%
12%
50%
50%
5%
50%
50%
50%
50%
50%
70%
68%
50%
50%
50%
29%
62%
buffalo.
15%
15%
50%
15%
40%
0%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
30%
30%
0%
68%
0%
0%
30%
30%
0%
30%
30%
30%
30%
0%
0%
10%
30%
30%
30%
40%
14%
0%
0%
25%
0%
15%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
88%
0%
0%
0%
0%
0%
20%
0%
0%
0%
0%
0%
5%
burned for fuel.
c Includes deep pit stacks, litter, and other.
APP-102
-------
I " " " v
, !; ; ; 1 "TABLE 12: (SLOSAt AWMS USASE FOR DAIRY CATTLE
Solid Pasture,
Anaerobic Liquid Daily Storage Range &
Country Lagoons Systems* Spread & Drylot Paddock
1 Canada
United States
Average
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Average
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Average
OCEANIA
Australia
Fiii
FIJI
New Caledonia
New Zealand
Papua New Guinea
Average
<1%
11%
10%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
35%
21%
23%
55%
15%
62%
20%
55%
55%
55%
40%
30%
50%
7%
20%
25%
35%
30%
55%
46%
10%
15%
13%
15%
5%
10%
20%
20%
20%
18%
0%
0%
0%
0%
0%
18%
3%
41%
37%
30%
0%
0%
0%
30%
30%
30%
0%
0%
40%
0%
20%
25%
0%
67%
30%
24%
20%
0%
2%
0%
0%
0%
0%
0%
20%
1%
0%
0%
0%
0%
0%
1%
62%
18%
23%
15%
35%
38%
50%
15%
15%
15%
10%
70%
10%
3%
0%
0%
65%
3%
15%
21%
0%
65%
85%
85%
95%
70%
70%
70%
0%
67%
0%
0%
0%
0%
0%
67%
0%
0%
0%
0%
50%
0%
30%
0%
0%
0%
50%
0%
0%
25%
60%
50%
0%
0%
0%
8%
70%
20%
0%
0%
0%
20%
10%
10%
60%
13%
100%
100%
100%
100%
100%
13%
Used
for Other
Fuel8 Systems0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
8%
7%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
65%
0%
0%
0%
0%
0%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
APP-103
-------
.. %
;• ,'
.". -. -• v
f
,: ; 7 TABLE la* cstosAt AWMS ysA> '••
Pasture,
Range &
Paddock
25%
90%
25%
10%
90%
90%
90%
90%
25%
90%
76%
90%
90%
99%
90%
25%
90%
20%
90%
90%
20%
20%
20%
36%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
50%
95%
95%
fctftM:/
•ff "" •• -. "" V1"" f fjf
Used
for
Fuel8
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
5%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
21%
0%
0%
,'^?**Jfff-*f
% "" ffff % ?* J"'\ A < '*•" fj
. HX..M«..V :Y..
Other
Systems0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
4%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
>
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
0%
5%
5%
5%
APP-104
-------
fei^i ;K;:T*J3lE 12; ; dLOB^L AWSflS Cl$AG| fOR
II Anaerobic
| Country Lagoons
Liquid
Systems*
Daily
Spread
Solid
Storage
& Drylot
DAJ8Y CATTLE - "\ ]" ^
Pasture,
Range &
Paddock
Used
for
Fuel8
Other
Systems0
AFRICA (continued)
Namibia
Niger
Nigeria
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
Swaziland
Tanzania
Togo
Uganda
Zaire
Zambia
Zimbabwe
Average
NEAR EAST
Afghanistan
Algeria
Egypt
Iran
Iraq
Israel
Jordan
Kuwait
Libya
J
Morocco
Oman
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
& MEDITERRANEAN
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Saudi Arabia 0%
Sudan
Syria
Tunisia
Turkey
Yemen Arab
Average
0%
0%
0%
0%
Rep. 0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
25%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
97%
0%
0%
0%
0%
0%
0%
0%
12%
0%
0%
25%
0%
15%
25%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
3%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
25%
0%
15%
25%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
3%
100%
95%
95%
95%
95%
95%
95%
0%
95%
95%
95%
95%
95%
95%
95%
83%
85%
85%
0%
85%
30%
25%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
76%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
15%
15%
50%
15%
40%
0%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
18%
0%
5%
5%
5%
5%
5%
5%
3%
5%
5%
5%
5%
5%
5%
5%
5%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
APP-105
-------
: ; TABLE 12: GLOBAL AWMS U$A6£ FOR DAJRY CATTLE- -
Country
ASIA
Bangladesh
Bhutan
China
India
Indonesia
Japan
Kampuchea
Myanmar (Burma)
North Korea
South Korea
Laos
Malaysia
Mongolia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Viet Nam
Average
GLOBAL AVERAGE
Anaerobic
Lagoons
0%
0%
5%
0%
0%
65%
0%
0%
0%
1%
0%
1%
0%
0%
0%
15%
0%
0%
0%
6%
2%
A Includes liquid/slurry storage and
B Includes anaerobic digesters and
Includes deep pit
Solid Pasture,
Liquid Daily Storage Range &
SystemsA Spread & Drylot Paddock
5%
5%
50%
0%
80%
2%
5%
5%
5%
2%
5%
2%
5%
5%
0%
15%
5%
5%
5%
4%
19%
pit storage.
burned for fuel.
20%
20%
32%
15%
20%
32%
20%
20%
20%
20%
20%
5%
20%
20%
50%
20%
20%
20%
20%
21%
19%
0%
0%
0%
0%
0%
1%
0%
0%
0%
5%
0%
5%
0%
0%
0%
0%
0%
0%
0%
0%
29%
50%
50%
10%
18%
0%
0%
50%
50%
50%
62%
50%
5%
50%
50%
50%
20%
50%
50%
50%
24%
23%
" - v'^
Used
for Other
Fuel8 Systems0
25%
25%
3%
68%
0%
0%
25%
25%
25%
10%
25%
0%
25%
25%
0%
0%
25%
25%
25%
46%
6%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
82%
0%
0%
0%
30%
0%
0%
0%
0%
1%
stacks, litter, and other.
APP-106
-------
U3BAL AWMS USAGE FOB SWJNI ::; r
| Solid Pasture,
Anaerobic Liquid Daily Storage Range &
| Country Lagoons Systems* Spread & Drylot Paddock
NORTH AMERICA
Canada
United States
Average
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Average
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Average
OCEANIA
Australia
Fiji
i iji
New Caledonia
New Zealand
Papua New Guinea
Vanuatu
Average
6%
29%
25%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
20%
20%
96%
0%
0%
0%
0%
8%
80%
0%
80%
80%
0%
0%
55%
82%
44%
50%
80%
80%
62%
70%
80%
80%
80%
100%
100%
79%
5%
40%
60%
100%
98%
80%
77%
20%
40%
80%
80%
0%
0%
40%
40%
40%
39%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
12%
20%
18%
20%
20%
38%
30%
20%
20%
20%
0%
0%
21%
10%
60%
40%
0%
2%
20%
23%
80%
60%
0%
0%
4%
90%
60%
60%
60%
52%
0%
55%
0%
0%
55%
55%
17%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Used
for Other
Fuel8 Systems0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
7%
6%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
85%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
10%
0%
0%
0%
1%
20%
45%
20%
20%
45%
45%
28%
APP-107
-------
TABiglgi OLQBAtAWMSUSAOE FOR SWINE ; / X»;&
Anaerobic Liquid
Country Lagoons Systems*
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Average
AFRICA
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Central African Rep.
Chad
Cote d'lvoire
Ethiopia
The Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Madagascar
Malawi
Mali
Mozambique
Namibia
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
10%
0%
10%
0%
0%
0%
0%
0%
10%
0%
5%
1%
0%
0%
0%
10%
0%
10%
0%
0%
10%
10%
10%
8%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
100%
0%
5%
0%
Daily
Spread
0%
0%
0%
90%
0%
0%
0%
0%
0%
0%
5%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
2%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Solid Pasture,
Storage Range &
& Drylot Paddock
50%
55%
50%
5%
55%
55%
55%
55%
50%
55%
80%
90%
55%
10%
55%
50%
55%
60%
55%
55%
60%
60%
60%
51%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
0%
100%
95%
100%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Used
for Other
Fuel8 Systems0
0%
0%
0%
3%
0%
0%
0%
0%
0%
0%
5%
9%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
40%
45%
40%
2%
45%
45%
45%
45%
40%
45%
5%
0%
45%
90%
45%
40%
45%
30%
45%
45%
30%
30%
30%
40%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
APP-108
-------
|iP%:> ' * ' TABUT&J $10BAU AWMS USAai FOR SWINE . ' < -
I Anaerobic
Country Lagoons
Solid Pasture,
Liquid Daily Storage Range &
SystemsA Spread & Drylot Paddock
Used
for Other
Fuel8 Systems0
AFRICA (continued)
Niger
Nigeria
1 Rwanda
Senegal
Sierra Leone
Somalia
South Africa
Swaziland
Tanzania
Togo
Uganda
Zaire
Zambia
Zimbabwe
Average
NEAR EAST
Algeria
Egypt
Israel
Morocco
Tunisia
Turkey
Average
ASIA
Bhutan
China
India
Indonesia
Japan
Kampuchea
Laos
Malaysia
Mongolia
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
AND MEDITERRANEAN
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
31%
0%
0%
0%
0%
Myanmar (Burma) 0%
Nepal
North Korea
Philippines
South Korea
Sri Lanka
Thailand
Viet Nam
Average
0%
0%
0%
0%
0%
0%
0%
1%
GLOBAL AVERAGE 5%
Includes
6 Includes
c Includes
liquid/slurry storage and
anaerobic digesters and
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
7%
15%
25%
35%
15%
15%
15%
32%
35%
40%
0%
60%
0%
35%
35%
30%
35%
35%
35%
35%
50%
50%
35%
35%
35%
38%
42%
pit storage.
burned for fuel.
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
15%
15%
0%
0%
0%
0%
0%
0%
0%
17%
0%
0%
0%
0%
1%
1%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
95%
93%
85%
75%
65%
85%
85%
85%
68%
65%
53%
100%
0%
53%
65%
65%
5%
65%
65%
65%
65%
0%
50%
65%
65%
65%
53%
45%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
7%
0%
25%
0%
0%
0%
1%
0%
0%
0%
0%
33%
0%
0%
0%
0%
7%
3%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
0%
0%
65%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
5%
deep pit stacks, and litter, and other.
APP-109
-------
TABLE 14r <3i00Al. AWIUTS ySA0I FOR POULTB
Anaerobic Liquid
Country Lagoons Systems*
NORTH AMERICA
Canada
United States
Average
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Average
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Average
OCEANIA
Australia
Fiji
New Caledonia
New Zealand
Papua New Guinea
Average
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
1 Ecuador
0%
6%
5%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
6%
4%
4%
15%
46%
14%
5%
11%
13%
15%
10%
0%
27%
5%
9%
14%
46%
7%
12%
13%
5%
28%
44%
47%
34%
35%
28%
27%
8%
28%
0%
0%
0%
0%
0%
0%
9%
5%
10%
10%
5%
5%
5%
5%
10%
Solid Pasture,
Daily Storage Range &
Spread & Drylots Paddock
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
41%
0%
0%
0%
0%
0%
4%
41%
0%
0%
0%
2%
0%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
7%
0%
1%
0%
0%
8%
0%
6%
2%
0%
2%
0%
0%
0%
0%
0%
0%
0%
2%
2%
0%
0%
0%
0%
3%
7%
4%
0%
3%
1%
0%
30%
0%
0%
30%
2%
39%
50%
40%
40%
50%
50%
50%
50%
40%
' *D
' ' -
' 4 tyJi
''*"<,?A;
Used
for Other
Fuel8 Systems0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
87%
90%
90%
85%
54%
78%
54%
84%
85%
85%
89%
100%
69%
54%
91%
86%
54%
91%
86%
84%
95%
72%
56%
53%
62%
58%
68%
73%
88%
71%
100%
70%
100%
100%
70%
98%
53%
45%
50%
50%
45%
45%
45%
45%
50%
APP-110
-------
1 5s '- - ; vS
[ Xs", %\V ' '7,"" Jfl
1 Country
j •. •.
^
V -• ,-. •.
-. .-o ••
n
&I&I4S OtOBALAWMS USAGE FOR POULTRY"
Anaerobic
Lagoons
Liquid
SystemsA
Daily
Spread
Solid
Storage
& Drylots
Pasture,
Range &
Paddock
Used
for
Fuel6
Other
Systems0
1 LATIN AMERICA (continued)
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Average
AFRICA
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Central African Rep.
Chad
Cote d'lvoire
Ethiopia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Madagascar
Malawi
Mali
Mauritania
Mozambique
Namibia
Niger
Nigeria
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
Swaziland
Tanzania
Togo
Uganda
Zaire
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
5%
10%
0%
5%
0%
5%
9%
5%
5%
5%
5%
15%
15%
15%
9%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
50%
40%
36%
50%
45%
50%
38%
50%
50%
50%
50%
30%
30%
30%
41%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
85%
68%
70%
80%
85%
86%
90%
85%
85%
85%
85%
85%
85%
0%
85%
86%
85%
85%
85%
0%
10%
0%
0%
0%
0%
0%
0%
0%
0%
0%
5%
5%
5%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
45%
40%
64%
45%
55%
45%
53%
45%
45%
45%
45%
50%
50%
50%
50%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
15%
32%
30%
20%
15%
14%
10%
15%
15%
15%
15%
15%
15%
100%
15%
14%
15%
15%
15%
APP-111
-------
"" ^ -.X
Country
,
TAPIE14* <3
Anaerobic
Lagoons
•. ..,-. ',
«i' ' ( '
,
tOBAt AWI/TS USAGE FOR POUUBY1* ;f
Liquid
SystemsA
Daily
Spread
Solid
Storage
& Drylots
Pasture,
Range &
Paddock
Used
for
Fuel8
f * "• -• -• '
Other
Systems0
AFRICA (continued)
Zambia
Zimbabwe
Average
NEAR EAST AND
Afghanistan
Algeria
Egypt
Iran
Iraq
Israel
Jordan
Kuwait
Libya
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Rep.
Average
ASIA
Bangladesh
China
India
Indonesia
Japan
Kampuchea
Laos
Malaysia
Myanmar (Burma)
Nepal
North Korea
Pakistan
Philippines
South Korea
Sri Lanka
Thailand
Viet Nam
Average
0%
0%
0%
MEDITERRANEAN
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
9%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
GLOBAL AVERAGE 1%
Includes liquid/slurry storage and
B Includes anaerobic digesters and
Includes deep
0%
0%
0%
0%
0%
0%
0%
0%
12%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
7%
0%
20%
1%
0%
7%
10%
2%
10%
10%
10%
0%
0%
10%
10%
9%
7%
2%
8%
pit storage.
burned for fue
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
<1%
D Includes
85%
85%
80%
75%
75%
74%
75%
75%
5%
75%
75%
75%
75%
75%
75%
75%
75%
75%
68%
75%
70%
33%
54%
20%
56%
0%
35%
10%
17%
10%
10%
10%
37%
17%
21%
10%
23%
33%
44%
34%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
3%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1%
1%
chickens, turkeys, and
15%
15%
20%
25%
25%
26%
25%
25%
83%
25%
25%
25%
25%
25%
25%
25%
25%
25%
32%
25%
29%
59%
43%
60%
42%
91%
58%
80%
81%
80%
80%
80%
63%
83%
69%
80%
69%
59%
52%
57%
ducks.
pit stacks, litter, and other.
APP-112
-------
1 V ;f ABU 15: m.0BAL AWMS USAGE FOR ALL OTHER UVESTOCKP
Solid Pasture,
Anaerobic Liquid Daily Storage Range &
| Country Lagoons SystemsA Spread & Drylot Paddock
NORTH AMERICA
Canada
United States
Average
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Average
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Average
OCEANIA
Australia
Fiji
i iji
New Caledonia
New Zealand
Papua New Guinea
Vanuatu
Average
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
wi im
Colombia
Costa Rica
Cuba
WwWQ
Dominican Republic
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
35%
<1%
1%
0%
0%
0%
0%
0%
0%
0%
0%
15%
0%
0%
0%
0%
0%
0%
0%
2%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
35%
92%
91%
99%
100%
100%
40%
89%
95%
90%
94%
84%
17%
49%
100%
100%
0%
88%
86%
89%
100%
100%
61%
57%
100%
26%
78%
78%
100%
78%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
98%
100%
100%
100%
100%
Used
for Other
Fuel8 Systems0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
2%
0%
0%
0%
0%
30%
8%
9%
1%
0%
0%
60%
11%
5%
10%
6%
1%
83%
51%
0%
0%
100%
12%
14%
9%
0%
0%
39%
43%
0%
74%
22%
22%
0%
22%
0%
0%
0%
0%
0%
0%
0%
f*A/
0%
0%
0%
0%
0%
0%
0%
0%
APP-113
-------
f AM.E IS: GLOBAL AWMS USA<3£ FO^'AUL OtHEfc UVlSTOCk? 4 >:/
Solid
Anaerobic Liquid Daily Storage
Country Lagoons Systems* Spread & Drylot
Pasture,
Range &
Paddock
Used
for Other
Fuel8 Systems0
LATIN AMERICA (continued)
Ecuador
El Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Uruguay
Venezuela
Average
AFRICA
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Central African Rep.
Chad
Cote d'lvoire
Ethiopia
The Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Madagascar
Malawi
Mali
Mauritania
Mozambique
Namibia
Niger
Nigeria
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
Swaziland
Tanzania
Togo
Uganda
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
2%
0%
0%
0%
0%
100%
100%
92%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
81%
100%
100%
100%
100%
100%
87%
100%
100%
100%
100%
100%
100%
100%
100%
100%
98%
100%
100%
100%
100%
0%
0%
4%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
4%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
19%
0%
0%
0%
0%
0%
13%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
APP-114
-------
|\ - TABLE 15:
1 Country
AFRICA (continued)
Zaire
Zambia
Zimbabwe
Average
GLOBAL AWMS tf SAG! FOR ALL OTHER LIVESTOCK0
Anaerobic
Lagoons
0%
0%
0%
0%
Solid Pasture,
Liquid Daily Storage Range &
Systems* Spread & Drylot Paddock
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
100%
100%
100%
99%
Used
for Other
Fuel8 Systems0
0%
0%
0%
0%
0%
0%
0%
1%
NEAR EAST AND MEDitERRANEAN
Egypt
Iran
Iraq
Israel
Jordan
Kuwait
Libya
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Rep.
Average
ASIA
Bangladesh
Bhutan
China
India
Indonesia
Japan
Kampuchea
Laos
Malaysia
Mongolia
Myanmar (Burma)
Nepal
North Korea
Pakistan
Philippines
South Korea
Sri Lanka
Thailand
Viet Nam
Average
GLOBAL AVERAGE
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
A Includes liquid/slurry storage and
B Includes anaerobic
digesters and
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
pit storage.
burned for fuel.
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
D Includes
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
<1%
goats, horses,
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
95%
98%
93%
100%
0%
100%
100%
99%
95%
92%
95%
93%
91%
100%
97%
100%
94%
92%
98%
92%
95%
mules,
c Includes deep pit stacks, litter, and other.
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
2%
0%
0%
0%
0%
0%
0%
donkeys, and
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
5%
2%
7%
0%
100%
0%
0%
1%
5%
8%
5%
7%
9%
0%
0%
0%
6%
8%
2%
8%
5%
camels.
APP-115
-------
APP-116
-------
*: dtDBALANJMAL WASTE W
The following tables list the amount of manure produced by the major animal types in each
country of the world. Manure production was calculated using the animal populations listed in
Appendix E and the manure production per animal values listed in Exhibits 4, 5, and 6. The non-
dairy category includes buffaloes; the poultry category includes chickens, turkeys, and ducks; and
the other category includes sheep, goats, horses, mules, donkeys, and camels.
APP-117
-------
' ' , APPENDIX 4s . GLOBAL AfcHMAL WASTE PRODUCTION {tQQO METRIC TQNWY1ARJ ",„-*• /; :, >' ,
Country
NORTH AMERICA
Canada
USA
Total
WESTERN EUROPE
Austria
Belgium
Denmark
Finland
France
Germany (Western)
Greece
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
Total
EASTERN EUROPE
Albania
Bulgaria
Czechoslovakia
Germany (Eastern)
Hungary
Poland
Romania
Soviet Union
Yugoslavia
Total
OCEANIA
Australia
Fiji
New Caledonia
New Zealand
Papua New Guinea
Vanuatu
Total
LATIN AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Non-Dairy*
86,083
865,472
951,555
10,658
16,626
9,496
6,858
91,500
63,689
3,479
30,503
39,716
16,245
4,569
7,400
24,663
8,407
7,964
68,595
410,367
3,265
7,819
24,838
28,363
8,269
41,057
40,660
582,058
18,692
755,021
154,313
593
900
44,764
452
479
201,501
218,781
24,523
534,419
12,460
95,388
8,578
20,080
8,687
Dairy
40,643
280,826
321,469
19,332
19,031
16,201
10,740
185,433
99,171
6,926
29,668
60,627
38,946
6,946
8,371
35,071
11,342
15,919
62,896
626,619
4,938
13,009
35,894
40,210
11,644
99,171
40,150
843,150
52,095
1,140,260
44,366
165
120
44,045
11
0
88,707
16,114
427
103,061
3,644
19,360
1,765
3,320
1,281
Swine
19,682
106,422
126,104
6,349
10,915
15,676
2,389
22,953
43,198
2,172
1,633
18,575
25,522
1,438
5,110
30,917
4,046
3,542
13,955
208,390
391
7,362
13,204
22,818
14,994
35,779
27,784
141,260
16,992
280,584
5,216
43
86
781
2,544
118
8,789
6,136
2,619
48,936
2,035
3,870
334
3,741
612
Poultry
3,705
37,318
41,023
548
1,241
602
219
9,691
3,011
1,132
365
6,899
3,687
146
657
2,008
402
219
5,731
36,555
219
1,570
1,789
1,862
2,446
2,409
5,347
46,465
2,993
65,098
2,044
88
37
329
131
0
2,628
2,781
526
24,827
920
1,708
219
1,183
1,183
Other
3,520
33,298
36,817
431
390
370
367
13,982
4,459
16,147
5,154
15,434
1,443
2,504
7,828
24,140
883
853
28,601
122,986
3,168
12,265
1,384
3,509
3,081
13,146
25,479
198,128
11,233
271,394
177,619
321
107
66,117
20
28
244,213
41,485
12,564
77,327
7,696
22,181
840
5,249
4,102
Total
153,633
1,323,336
1,476,969
37,317
48,203
42,344
20,573
323,558
213,527
29,855
67,322
141,250
85,843
15,604
29,366
116,799
25,080
28,497
179,779
1,404,917
11,981
42,025
77,109
96,761
40,434
191,561
139,420
1,811,061
102,005
2,512,356
383,558
1,211
1,250
156,035
3,158
625
545,838
285,297
40,659
788,570
26,756
142,507
11,736
33,572
15,865
APP-118
-------
" - "*, V^>'*PPENDIX * 0LQBAL ANIMAL WASTE PRODUCTION (1000 METRIC TON$tt£ARi - \
^ '.'.. '.. .f. ..{... "K ;>.c . ?*;. .
Country
;..".?.. x.> •..*. :...', '
Non-Dairy*
".... "..
Dairy
Swine
^
Poultry
Other
Total
LATIN AMERICA (continued)
Ecuador
IE1 Salvador
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Peru
1 Puerto Rico
Uruguay
Venezuela
Total
AFRICA
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Central African
Chad
Cote d'lvoire
Ethiopia
The Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Madagascar
Malawi
Mali
Mauritania
Mozambique
Namibia
Niger
Nigeria
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
Swaziland
Tanzania
Togo
1 Uganda
Zaire
14,627
4,042
7,939
721
6,616
11,365
1,100
113,150
6,935
6,356
35,017
14,586
2,222
44,977
52,405
1,244,974
14,167
3,641
9,399
10,713
1,278
19,956
Rep. 10,348
16,671
3,677
123,758
1,232
5,042
7,186
1,282
34,424
2,030
48,093
4,129
19,455
4,462
4,426
8,582
13,551
50,096
2,281
10,713
1,278
18,250
110,560
2,268
48,819
1,150
12,912
6,351
4,561
1,469
2,278
296
541
1,896
279
36,442
1,025
621
598
4,003
524
3,132
7,231
213,867
1,680
661
1,651
2,625
342
552
256
2,312
877
22,064
171
1,110
1,281
336
12,840
456
336
541
2,699
1,549
2,221
962
3,018
6,947
911
1,480
285
5,694
17,863
871
15,943
216
6,150
46
6,225
661
1,309
277
1,347
898
374
24,692
1,115
359
3,155
3,592
292
322
4,051
116,951
718
970
13
748
120
1,763
572
18
673
28
19
1,122
75
434
153
108
2,095
314
90
0
239
72
55
1,945
138
703
75
15
2,665
28
275
449
658
1,197
2.102
131
657
657
569
350
263
11,257
219
307
701
2,278
482
350
2,497
56,166
263
1,007
44
920
175
701
131
175
701
2,497
0
526
569
44
1,007
44
1,518
350
832
175
964
44
745
8,322
44
482
263
131
1,351
44
1,445
131
657
832
6,198
801
1,483
139
5,264
1,717
487
86,968
2,023
1,187
2,777
16,954
183
18,430
6,935
322,990
824
1,178
1,692
6,545
697
3,943
832
8,347
1,868
70,669
266
3,569
591
278
15,167
2,885
1,073
751
11,310
10,714
405
6,059
14,073
29,708
999
5,356
311
66,159
38,131
306
32,784
670
2,931
2,511
33,714
7,105
13,666
2,089
14,337
16,226
2,503
272,508
11,316
8,829
42,247
41,413
3,703
67,211
73,119
1,954,948
17,652
7,456
12,799
21,551
2,611
26,915
12,139
27,524
7,797
219,016
1,688
11,369
9,702
2,374
63,591
5,522
53,116
6,086
34,385
16,901
8,254
15,719
31,441
97,018
4,372
18,734
2,211
90,250
170,570
3,517
99,266
2,616
23,308
10,937
APP-119
-------
*'t~ ^PJEHDIX^,^OBAi;/8«M*L WASTE iPROBUOTKiii '&^1&^&$<%®ftet3% \*&'%t&
^; ;x- ,; ;". - , *+,"> ;' ' - 'H\ , - '-"- , s,x&. "^ '- , " /;" ™-/ ' - ^'xer^
Country
AFRICA (continued)
Zambia
Zimbabwe
Total
Non-Dairy*
11,014
25.354
668,545
Dairy
1,537
814
119,296
Swine
269
284
19,104
Poultry
657
438
28,229
Other
332
2,034
345,967
Total
13,809
28,924
1,181,140
NEAR EAST & MEDITERRANEAN
Afghanistan
Algeria
Egypt
Iran
Iraq
Israel
Jordan
Kuwait
Libya
Morocco
Oman
Saudi Arabia
Sudan
Syria
Tunisia
Turkey
Yemen Arab Rep.
Total
ASIA & FAR EAST
Bangladesh
Bhutan
China
India
Indonesia
Japan
Kampuchea
Laos
Malaysia
Mongolia
Myanmar (Burma)
Nepal
North Korea
Pakistan
Philippines
South Korea
Sri Lanka
Thailand
Viet Nam
Total
WORLD TOTAL
11,087
4,348
14,007
28,424
6,228
1,640
50
46
757
7,939
429
913
86,916
1,921
1,652
34,401
3,217
203,973
96,720
1,396
422,638
1,076,750
42,203
24,693
4,508
7,081
3,659
8,810
44,804
39,233
5,543
124,707
20,873
9,668
10,129
49,877
25,947
2,019,241
6,455,177
6,662
3,246
8,256
13,381
2,164
2,128
102
91
279
8,883
239
712
19,644
1,651
1,424
28,470
1,982
99,313
20,157
626
12,458
165,126
1,424
28,707
558
216
245
3,388
13,552
3,843
199
21,711
85
1,520
3,701
387
256
278,161
2,887,693
0
7
22
0
0
237
0
0
0
13
0
0
0
1
6
15
0
303
0
94
501,121
15,414
9,727
20,721
2,245
2,275
3,292
120
4,490
717
4,639
0
11,343
6,407
151
6,375
18,034
607,165
1,367,390
307
1,007
1,584
4,818
3,329
1,606
2,628
1,226
1,621
1,621
88
3,022
1,270
526
745
2,825
1,007
29,229
4,949
0
95,316
11,388
19,228
12,191
438
394
2,716
0
1,489
438
876
6,614
2,891
2,628
394
4,424
4,205
170,579
429,508
22,090
16,030
10,972
40,241
9,130
560
1,234
262
5,882
21,485
1,253
10,076
41,850
9,691
7,280
42,905
5,029
245,969
7,414
285
269,705
121,724
16,355
252
102
332
319
28,033
1,889
3,854
720
61,063
3,425
131
354
236
1,199
517,392
2,107,727
40,145
24,639
34,842
86,865
20,851
6,171
4,014
1,625
8,539
39,940
2,008
14,723
149,680
13,790
11,106
108,616
11,235
578,788
129,240
2,402
1,301,239
1,390,402
88,937
86,565
7,850
10,298
10,231
40,351
66,223
48,085
11,978
214,095
38,618
20,354
14,729
61,299
49,641
3,592,538
13,247,494
A Includes buffaloes.
APP-120
-------
APPENDIX Ki INFOTMAf ION
APP-121
-------
APPENDIX K: INFORMATION CONTRIBUTORS
There were numerous individuals contacted to assist with obtaining information
on the subjects not found in the literature. The authors deeply appreciate the
assistance of the following people and organizations, as well as anyone we have
inadvertently omitted from the list:
Dr. Harold Watson
Auburn University
Cooperative Extension Serv.
Auburn, AL 36830
Dr. Robert F. Cullum
University of Alaska
Alaska Agri. Exp. Sta.
309 O'Neill Bldg.
Fairbanks, AK 99775
Dr. Gene M. Nordby, Head
Agri. Engineering Dept.
University of Arizona
Room 507 Shantz Bldg.
Tucson, AZ 85721
Dr. Raymond C. Benz,
University of Arkansas
P.O. Box 391
Little Rock, AR 72203
Dr. William C. Fairbank
University of California
Soil and Environmental Science
Riverside, CA 95502
Dr. Tim L. Stanton
Colorado State University
Department of Animal Sciences
Fort Collins, CO 80523
Dr. John J. Kolega
University of Conneticut
Dept. of Natural Resources
Management and Engineering
Storrs, CT 06268
Dr. William F. Ritter
University of Delaware
Agri. Engineering Dept.
Newark, DE 19717-1303
Dr. E. A. Ott
University of Florida
Animal Science Department
Gainesville, FL 32611
Dr. David R. Bray
University of Florida
Dairy Science Department
Gainesville, FL 32611
Dr. Carrol Douglas
University of Florida
Poultry Science Department
Gainesville, FL 32611
Dr. Randy Walker
University of Florida
Animal Science Department
Gainesville, FL 32611
Dr. Larry Newton
University of Georgia
Dept. of Animal Science
Coastal Plain Station
P.O. Box 748
Tifton, GA 31793-0748
Dr. Roy Taylor
Dept. of Agri. Engineering
University of Idaho
Moscow, ID 83843
Dr. A. J. Muehling
University of Illinois
Dept. of Agicultural Engineering
1304 W. Pennsylvania Ave.
Urbana, IL 61801
Dr. Don D. Jones,
Purdue University
Agri. Engineering Dept.
West Lafayette, IN 47907
APP-122
-------
Dr. Al Sutton
Purdue University
Agri. Engineering Dept..
West Lafayette, IN 47907
Dr. Vernon M. Meyer
Iowa State Univrsity
Davidson Hall
Ames.IA 50011-3080
Dr. James P. Murphy
Kansas State University
Seaton Hall Room 237
Manhattan, KS 66506
Dr. John W. Branch
Louisiana State University
Room 178, Knapp Hall
Baton Rouge, LA 70803
Dr. Herbert L. Brodie
University of Maryland
Agricultural Engineering Dept.
College Park, MD 20740
Dr. Charles J. Clanton
University of Minnesota
Agri. Engineering Building
1390 Eckles Avenue
St. Paul, MN 55108
Dr. Larry 0. Jacobson
University of Minnesota
Agri. Engineering Building
1390 Eckles Avenue
St. Paul, MN 55108
Dr. James G. Thomas
Mississippi State Univ.
P.O. Box 5446
Mississippi State, MS 39762
Dr. Charles D. Fulhage
University of Missouri
205 Agricultural Engr.
Columbia, MO 65211
Dr. Roy Linn
Montana State University
418 Cobleigh Hall
Bozeman, MT 59717-0007
Dr. Gerald R. Bodman
University of Nebraska
L. W. Chase Hall
East Campus
Lincoln, NE 68583-0771
Dr. Francis E.Oilman
Univ. of New Hampshire
101 Pettee Hall
Durham, NH 03824
Dr. Elston Grubaugh
New Mexico State Univ.
Box 3AE
Las Cruces, NM 88003
Dr. Richard W. Guest
Cornell University
Riley-Robb Hall
Ithaca, NY 14853
Dr. James C. Barker
North Carolina State Univ.
Biological & Agricultural
Engineering Department
Box 7625
Raleigh, NC 27695-7625
Dr. Harvey Hirning
North Dakota State Univ.
Box 5626
Fargo, ND 58105
Dr. Alex T. Bermudez
The Ohio State University
Poultry Science Dept.
Columbus, OH 43210
Dr. Donald E. Pritchard
The Ohio State University
Dairy Science Dept.
Columbus, OH 43210
Dr. Ron Bolze
The Ohio State University
Aniaml Science Dept.
Columbus, OH 43210
Dr. Raymond L. Huhnke
Oklahoma State University
Room 214 Ag Hall
Stillwater, OK 74078
APP-123
-------
Dr. James A. Moore
Oregon State University
Agri. Engineering Dept.
Corvallis, OR 97331-3906
Dr. Paul D. Robillard
Pennsylvania State Univ.
Ag. Engineering Bldg.
University Park, PA 16802
Dr. Jay D. Harman
Clemson University
Agri. Engineering Dept.
McAdams Hall
Clemson, SC 29634-0357
Dr. Steve Pohl
South Dakota State Univ.
Ag. Engineering Dept.
Brookings, SD 57007
Dr. G. F. Grandle
University of Tennessee
P.O. Box 1071
Knoxville, TN 37901-1071
Dr. John M. Sweeten
Texas A&M University
303 Ag. Engineering Bldg.
College Station, TX 77843
Dr. Robert C. Lamb
Utah State University
Department of Animal Dairy &
Veterinary Science
Logan, UT 84322-4800
Dr. Eldridge R. Collins
VPI & SU
Agri. Engineering Dept.
Seitz Hall
Blacksburg, VA 24061-0303
Dr. Ronald E. Hermanson
Washington State University
Agricultural Engineering Dept.
Pullman, WA 99164-6120
Dr. Arthur W. Selders
West Virginia University
2076 Ag Sciences
P.O. Box 6108
Morgantown, WV 26506-6108
Dr. B. Holines
University of Wisconsin
Agri. Engineering Dept.
Madison, WI 53706
Dr. L. Massie
University of Wisconsin
Agri. Engineering Dept.
Madison, WI 53706
Mr. Alan Baker
Economic Research Service
U.S. Department of Agriculture
1301 New York Avenue, N.W.
Washington, DC 20005
Dr. Leonard Bull, Head
Animal Science Dept.
North Carolina State Univ.
Box 7621
Raleigh, NC 27695
Dr. M. Terry Coffey
Animal Science Dept.
North Carolina State Univ.
Box 7621
Raleigh, NC 27695
Ms. Sharon Fee
U.S. Agency for International
Development
Project Development Office
320 21st Street N.W.
Washington, DC 20523
Dr. Hank Fitzhugh
Winrock International Inst.
for Agricultural Development
Route 3
Petit Jean Mountain
Morrilton, AR 72110
Dr. Will Getz
Winrock International Inst.
for Agricultural Development
Route 3
Petit Jean Mountain
Morrilton, AR 72110
APP-124
-------
Dr. Thurman Grove
U.S. Agency for International
Development
Office of Agriculture
Bureau for Science and Technology
Room 403 SA-18
Washington, DC 20523
Dr. Ray Harvey
Animal Nutritionist (Beef Cattle)
Animal Science Dept.
North Carolina State Univ.
Raleigh, NC 27695-7621
Dr. Donald E. Johnson
Colorado State University
Dept. of Animal Scienc
Fort Collins, CO 80523
Mr. Michael Kurtzig
Economic Research Service
(Developing Countries)
U.S. Department of Agriculture
1301 New York Avenue, N.W.
Washington, DC 20005
Mr. Don Ledford
U.S. Department of Agriculture
National Agricultural Statistics
Service
1 W. Edenton St.
Raleigh, NC 27601
Dr. J. Ron Miner
Professor
Oregon State University
International Research & Development
Corvallis, OR 97331
Dr. Jack W. Parker
Sr. Ext. Area Swine Spec.
Animal Science Department
P.O. Box 352
Edenton, NC 27932
Dr. David Sprool, Head
Animal Science Dept.
University of Georgia
Athens, GA
Dr. E. Paul Taiganides
Engineering Consultant
1800 Willow Forge Dr.
Columbus, OH 43220
Dr. Gerry Ward
Colorado State University
Dept. of Animal Science
Fort Collins, CO 80523
Mr. Larry Witucki
Economic Research Service
U.S. Department of Agriculture
1301 New York Avenue, N.W.
Washington, DC 20005
Mr. M. P. Foster
Dept. of Agriculture & Rural Affairs
Agricultural Engineering Centre
Princes Highway
Weeibee, Victoria 3030
Australia
Dr. Richard W. Payne
Dairying and Food Technology Division
Western Australia Department
of Agriculture
South Perth, Western Australia
Australia
M. Y. Raimond & M. Comte Cl. Cornet
Ministere de 1'Agriculture
Administration de la Recheche
Agronomique
Manhattan Office Tower
Avenue du Boulevard, 21 (76 6t.)
1210 Bruxelles, Belgium
Dr. S. F. Barrington
Macdonald College of McGill Univ.
21 111 Lakeshore Road
St. Anne de Bellevue, Quebec H9X ICO
Canada
Dr. Ronald J. Fleming
Centralia College of Agric. Tech.
Huron Park, Ontario NOM 1YO
Canada
APP-125
-------
Mr. Franklin A. Kains
Ontario Ministry of Agriculture
and Food
FOB 1030
Guelph Agricultural Centre
Guelph, Ontario N1H 6N1 Canada
Mr. Rick Van Kleeck
Soils and Engineering Branch, BCMAF
33832 South Fraser Way
Abbotsford, British Columbia V2S 2C5
Canada
Dr. Brian West
University of Alberta
Agricultural Engineering Dept.
751 General Services Building
Edmonton, Alberta T6G 2H1 Canada
Dr. William C. Durant
Head, Agri. Engineering Section
New Brunswick Dept. of Agriculture
FOB 6000
Fredericton, New Brunswick E3B 5H1
Canada
Dr. Abdel Ghaly
Technical University of Nova Scotia
Agricultural Engineering Dept.
FOB 1000
Halifax, Nova Scotia B3J 2X4 Canada
Dr. N. Ross Bulley
Professor and Head
Dept. of Agricultural Engineering
University of Manitoba
Winnipeg, Manitoba R3T 2N2
Canada
Dr. Orly Friesen, Chief
Agricultural Engineering
Manitoba Agriculture
Winnipeg, Manitoba
Canada
Dr. N. K. Patni
Agriculture Canada
Animal Research Centre
Ottawa, Ontario KlA OC6
Canada
Senor Juan Ignacio Dominguez C.
Ministerio de Agricultura
Gabinete del Ministro
Teatinos 40
Santiago, Chile
Dr. Jose Toledo, Leader
Tropical Pastures Program
CIAT
Apartado Aerea 6713
Call, Columbia
Mr. ArpSd Szab6 & Mr. Dolezal Oldrich
Federal Ministry of Agriculture
and Food
Prague Czechoslovakia
Dr. Fens J. Hoy
Institut for Landbrugsplanternes
Ernaering
Askov Forsogsstation
Vejenveg 55
Denmark - 6600 VEJEN
Dr. Erkki Kemppainen
Agricultural Research Centre
Research Station for Kainuu
SF-88600 Sotkamo, Finland
Senor Luis Bernal Larragabal B.
& Dr. Carlos Roel Marroquin
Ministerio de Agricultura
Ganaderfa y Alimentaci6n
Palacio Nacional
Guatemala City, Guatemala
Dr. Seny Mane
Ministere de 1'Agriculture
et des Ressources Animalees
Conakry, Guinee
Mr. L. David
Ministry of Agriculture
Regent and Vlissingen Roads
Gorgetown,Guyana,
Direccion General de Ganaderia
Ministry of Natural Sources
Blvd. Miraflores
Tegucigalpa, Honduras
APP-126
-------
Dr. GyOrgy Meszdros
National Institute of
Agricultural Engineering
Postafidk: 103
2101. Godollfl, Tessedik S. UTCA 4.
Hungary
Dr. S. S. Ramachandra Raja
58 P S K Nagar
Raj apalaiyam, India
Dr. Matthew C. John
Professor and Head
Department of Wildlife and
Forest Resources
Madras Veterinary College
Madras 600 007, India
Dr. Soehadji & Mr. Darso Kusumo
Department of Agriculture
Directorate General of Livestock
Services
16 Jalan Salemba Raya
Jakarta, Indonesia
Mr. John O'Rourke
Department of Agriculture and Food
Agriculture House
Kildare St.
Dublin 2, Ireland
Mr. Owen T. Carton
Agricultural Institute
Johnstown Castle
Research and Development Center
Wexford, Ireland
Dr. Giuseppe Bonazzi, Director
Department of Environment and Energy
C.R.P.A.
Via Crispi, 3
42100-Reggio Emilia, Italy
Dr. H. Tanaka
National Institute of Animal Industry
Tokyo, Japan
Mr. Hideo Minagawa & Mr. E. Shima
Kitasato University
Sanbongi
Towasda, Japan
Mr. Basil A Rosst
D.V.A. P.O. Box 8082 Dasmarinas
Makati, Metro Manila
The Philippines
Mr. B. S. Kambauwa
Ministry of Agriculture
FOB 30134
Capital City Lilongwe 3
Malawi
Mr. Ahmad Tajuddin Bin Zainuddin
Livestock Research Division
MARDI
P.O. Box 12301, Gen. Post Office
50774 Kuala Lumpur, Malaysia
M. Bakary Kone
Ministere de 1'Agriculture
PB 61
Bamako, Mali
Dr. H. Schneider
Ministry of Agriculture, Water
Affairs and Sea Fisheries
Windhoek, Namibia
Mr. Snel & Mr. H. A. C. Verkerk
Ministry of Agriculture, Natural
Management and Fisheries
POB 20401, 2500 EK
The Hague, The Netherlands
Mr. A. A. Jongebreur
Agricultural University
Burg, Prinslaan
20 6711 KD EDE
The Netherlands
Dr. Egil A. Berge
Agricultural University of Norway
P.O. Box 15
N 1432 AAS NLH Norway
Mr. M. Zafarullah Naseem
Deputy Animal Husbandry Commissioner
Government of Pakistan
Livestock Division
Islamabad, Pakistan
Mr. Romeo N. Alcasid, Director
Bureau of Animal Husbandry
Department of Agriculture
Diliman, Quezon City
The Philippines
Mr. Sven Jeppsson
Ministry of Agriculture
Drottninggt 21
103 33 Stockholm, Sweden
APP-127
-------
Mr. Andrzej Sapek
Ministry of Agriculture, Forestry Dr. H. Menzi
and Food Economy Swiss Federal Research Station for
00-930 Warsaw, Ul. Wsplna 30 Agricultural Chemistry and Hygiene
Poland of Environment
CH-3097 Liebefield-Bern, Switzerland
Dr. J. G. Cloete, Director
Animal & Dairy Science Research Inst. Dr. K. J. Peters
Private Bag X2 Deputy Director General (Research)
Irene, South Africa 1675 International Livestock Center
for Africa
P.O. Box 5689
Addis Ababa, Ethiopia
APP-128
-------
IFCC WOKSHOP
Two international workshops held in support of the Intergovernmental Panel on Climate Change
(IPCC) provided information on current methane emissions and opportunities for reducing these
emissions. The first workshop, held on December 12-14, 1989, by the U.S. Environmental Protection
Agency and the U.S. Department of Agriculture, examined greenhouse gas emissions from agriculture
in support of the Agriculture, Forestry, and Other Human Activities Subgroup (AFOS) of the Response
Strategies Working Group.
The second workshop was held on April 9-13,1990. Funded jointly by the Environment Agency
of Japan, the U.S. Environmental Protection Agency and the U.S. Agency for International Development,
this workshop examined methane emissions from natural gas systems, coal mining activities, and waste
management in support of the Energy and Industry Subgroup (EIS) of the Response Strategies Working
Group.
Below are excerpts of the workshop findings for waste management systems and for livestock.
APP-129
-------
7. FINDINGS FOR WASTE MANAGEMENT SYSTEMS
1. Emissions Estimates
1.1 There are currently large uncertainties in estimates of
methane emissions from waste management systems,
including landfills, animal waste management systems,
and wastewater treatment lagoons.
1.2 Despite these uncertainties, waste management systems
appear to be significant anthropogenic sources of
methane emissions.
Landfills emit an estimated 25 to 40 million
metric tons of methane globally each year. This
methane is produced by the anaerobic decomposition
of wastes in the landfills. Although landfill gas
monitoring and other detailed landfill analyses
have been performed in various countries, global
methane emissions from landfills are uncertain
because the factors driving the level of methane
emissions are highly site specific, including:
the waste composition; the extent and rate of
waste decomposition; the pathways of methane
transport out of the landfill; and the extent of
methane oxidation prior to release from the
landfill.
analysis and limited monitoring
indicate that anaerobic wastewater treatment
laaoons that treat wastewater with high BOD
(biochemical oxygen demand) loading can produce
large amounts of methane emissions. Global
emissions from wastewater treatment lagoons may be
on the order of 20 to 25 million metric tons each
year. This estimate of global methane emissions
is very uncertain due to a lacfc of data on the
amount and type of wastewater treated in anaerobic
lagoons .
Preliminary analysis and limited monitoring
indicate that animal wastes emit about 30 to 40
million metric tons of methane each year. Wastes
managed under anaerobic conditions as part of
confined animal management systems are the major
source of these emissions. This estimate of
global methane emissions is uncertain due to a
lack of data on the amount of wastes managed under
APP-130
-------
anaerobic conditions and the extent to which these
wastes are decomposed to methane.
Estimates of methane emissions from these systems have
been developed for a number of different countries or
regions of the world as shown in the following table.
Methane Emissions from Haste Management Systems
(million metric tons)
Reg i on/ C ount rv
Canada
Japan
Oceania
USA
Western Europe
USSR and
Eastern Europe
Developing
Countries
Landfills
1.8
0.17
1.25
8-18
•p
5-8
4-7
Animal
Wastes
.3 -.6
-
1-2
2-5
3-8
5-12
10-19
Wastewater
Treatment
•>
0-02
t
•>
•>
-)
->
Global Total 25-40 20-40 20-25
1.3 Methane emissions from waste management systems could
likely double by 2025 with continued population and
economic growth, assuming the continuation in ongoing
trends in waste management practices.
APP-131
-------
2. Steps to Improve Emissions Estimates
2.1 Landfills. Substantial uncertainty remains in methane
emissions from landfills. To improve the understanding
of these emissions, research is required to:
Understand how the rate of methane emissions is
influenced by key landfill characteristics, such
as landfill design and operation; waste
characteristics (e.g., composition; degradability;
and moisture content); landfill size; and local
conditions (e.g., climate and ground cover).
Characterize current and expected future landfills
in terms of those characteristics that influence
methane emissions.
obtain field measurements of methane emissions
from landfills in different regions using
different management practices and receiving
different types of wastes. Measurement techniques
must be developed to collect these data.
Examine how methane oxidation influences methane
emissions.
Develop a carbon balance for landfills that
describes the fate of the carbon added to
landfills over time. This carbon balance should
describe: carbon storage; methane and carbon
dioxide generation; methane oxidation; and methane
and carbon dioxide emissions. This balance should
be sensitive to various landfill characteristics
such as: waste composition (e.g., lignin/cellu-
lose ratios); moisture content; and landfill
design.
Develop methods for scaling up limited
measurements and data to develop national and
global emissions estimates that reflect
differences in cultures, waste generation, and
waste management practices.
2-2 Wastewater Treatment Systems. The management of
wastewater effluent from domestic, commercial, and
industrial facilities has the potential to produce
globally significant amounts of methane emissions.
While in many cases wastewater is managed in a manner
that is presumed to produce negligible methane
emissions, emissions data from individual facilities in
developed and developing countries indicate that
emissions are large in certain circumstances. To
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better understand methane emissions from wastewater
treatment systems, research is required to:
Collect available data on wastewater management
practices throughout the world.
Identify those areas and facility types that are
potentially important sources of methane
emissions. Candidate facility types include food
processing facilities such as: fruit and
vegetable processing; meat packing; sugar
production; creameries; and distilleries.
Characterize and measure the emissions at the
important facilities.
2-3 Animal Waste^. While animal wastes are potentially a
globally significant source of methane emissions,
uncertainties remain as to the quantity of emissions
due to a lack of field data. To improve the
understanding of these emissions research is required
to:
improve current enumerations of animal numbers and
waste quantities managed with various practices;
develop methane emissions measurement techniques;
• measure methane emissions from those situations
that appear to be most important from an overall
emissions perspective; and
assess changes in methane emissions over rime as
management practices change.
The measurements of methane emissions from animal
wastes must consider local and seasonal factors that
affect emissions.
3. Technical Potential for Reducing Emissions
3.1 Landfills. Technologies and practices exist to reduce
methane emissions from landfills by collecting and
flaring or utilizing the methane generated in the
landfill. In many circumstances these technologies and
practices appear to be cost effective. Use of these
technologies and practices is believed to reduce
methane emissions by 40 to 70 percent at existing
landfills. In new landfills, it is believed that
methane emissions can be reduced by 70 to 95 per cent
using currently available technologies and practice*.
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Steps taken to reduce methane emissions from landfills
provide other significant environmental and safety
benefits. Additionally, when utilized as an energy
source, the methane recovered from landfills to reduce
emissions may displace more carbon intensive fuels,
thereby also reducing carbon dioxide emissions. TO
promote the reduction of methane, emissions from
landfills, analyses of existing technologies and
practices would be useful, including:
Defining the* best control/recovery/utilization
technologies and practices-- that are appropriate
for various landfill situations, including new
versus existing landfills.
Examining- the effect of alternative waste
management and. treatment* programs on emissions of
methane- and other greenhouse- gases, including:
waste stream separation and recycling; and
incineration with energy recovery.
To improve the currently available technologies and
practices, research is necessary to:
Develop techniques for enhancing methane
generation in cases where the methane can be
captured and utilized.
Develop cost beneficial uses of recovered methane
from landfills (particularly small landfills),
such as lower cost electricity generation
technologies.
3-2 w«stewater Treatment systems. Technologies and
practices exist to manage wastewater without producing
methane emissions, including aerobic treatment and
anaerobic treatment with methane recovery and
utilization. Therefore, methane emissions from
wastewater treatment systems can technically be
eliminated virtually entirely. In many circumstances,
anaerobic treatment with methane recovery and
utilization appears to be cost effective due to the
value of the energy produced. To promote the reduction
of methane emissions from vastevater treatment systems,
the best wastevater management practices should be
defined based on the demonstrated technical and
economic feasibility and the other environmental
benefits of the various existing approaches for
managing wastewater. The approach of collecting and
utilizing the methane produced by anaerobic wastevater
treatment should be examined as part of the proce»» of
defining best practices, in some areas, existing
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need to be
Technolo*i« ^d practices «i«t that
ne emissioi« by 50 to 80 percent from
mana9«»ent systems that are used for large
C0nf ined Animals . These approaches
S™1?!! anaerobic treatment (e.g., in a
™N fflet^ane recovery and utilization. These
approaches appear to be cost effective in many
5or^SnC*H dULt0 the value of the ener
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4.2 Analyses of policies that will promote the reduction of
methane emissions from waste management systems are
necessary, including analyses of policies that:
promote capacity expansion in the recycling and
recovery industries;
• encourage methane recovery and utilization, for
example by:
setting fair-market sales prices for
recovered methane or electricity produced.
from recovered methane;
— eliminating institutional barriers that limit
competition in electricity production,
transportation, and sales;
— increasing the costs of producing commercial
energy from fossil sources, e.g., by imposing
carbon dioxide emissions fees;
providing financial incentives for recovering
methane, e.g., by providing tax incentives;
and
creating a market for energy produced from
recovered methane, e.g., by setting goals for
non-fossil fuel energy production.
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9. FINDINGS FOR LIVESTOCK
The following are the findings that were adopted by
consensus by those attending the workshop. These findings
indicate that there are promising opportunities for reducing
methane emissions from livestock management systems. Such
opportunities remain to be assessed and demonstrated in the
field. Undertaking such assessments and demonstrations is a
recognized priority.
1. GENERAL
1.1 Given the fact that methane (CH4) concentrations are
increasing globally and will affect global climate and
tropospheric air quality, it is recognized that
opportunities for reducing CH4 emissions must be
identified, evaluated, and applied in order to reduce
global warming and increases in tropospheric ozone.
1.2 Given the diverse set of CH4 emissions sources
globally, emissions reductions from any single country
or source will be small compared to total CH^
emissions, and small compared to total emissions of all
greenhouse gases. Consequently, programs to reduce CH4
emissions from many sources will be required in many
countries.
1.3 Although emissions-reduction programs will be required
in many countries to achieve significant emissions
reductions, individual countries can make valuable
contributions by developing, demonstrating, and
implementing emissions-reduction technologies.
2. THE ROLE OF MANAGED LIVESTOCK IN THE GLOBAL METHANE BUDGET
2.1 Livestock, and in particular ruminants, are
comparatively an important source of CH4 emissions on a
global scale.
2.2 Animals produce significant quantities of CH4 as
part of their digestive processes. CH^ emissions
from the digestive processes of all animals have
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been estimated to be between 60 and 100 Tg/year,15
accounting for about 15 percent of total global
CH4 emissions from all sources.
2.3 Previous estimates of global CH4 emissions from
ruminant digestive processes have several notable
deficiencies, including the following:
Previous estimates failed to reflect important
differences in CH4 emissions associated with
various stages of animal growth and management.
For example, in the U.S. about 25 percent of beef
cattle are in fact calves with CH4 emissions rates
significantly lower than emissions associated with
adult beef cows.
For cattle on poor quality forages, previous CH4
emissions estimates appear to underestimate feed
intakes and overestimate CH4 yield per amount of
feed intake. The net effect of these two factors
is that overall emissions associated with these
populations of animals appear to be
underestimated, possibly by large amounts.
Previous estimates have neglected potential
emissions from animal wastes.
Previous estimates failed to consider differences
in animal sizes and differences in the feed base
of the animals.
Estimates of global animal populations need to be
refined.
2.4 While previous estimates of CH4 emissions from ruminant
digestive processes are deficient in various respects,
the overall magnitude of the estimates is reasonable.
Key analyses should be undertaken to improve the
emissions estimates, especially for areas in which
interventions are most likely to be cost effective.
The major animal management systems should be
enumerated, and the analyses should focus on the k-y
systems that contribute most to global emissions, <-nd
that have the potential to be controlled.
2.5 Animal wastes (including the wastes from non-ruminants
such as poultry and swine) are a potentially large
source of methane emissions. Under anaerobic waste
management systems, uncontrolled CH4 emissions from
15
1 Tg - 1012 grams - 109 kilograms - 106 metric tons.
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t*%h^ animal wastes- Preliminary analyses
n? ^ ^missions from this source may be on the
CH »i5 Tg/year gl^ally, or about 20 percent of
»T4 emissions from the digestive processes of
als •
emissions ^om animals will assist in
rate °f CH* increases, and may be one
component in attempts to stabilize
atmospheric CH4 concentrations.
3. EMISSIONS REDUCTION OPPORTUNITIES
3.1 While many uncertainties exist, it appears that there
are a number of technologies that can likely reduce CH,
emissions from livestock systems by 25 to 75 percent:
Per unit of
3.2 Total reductions achievable depend on how effectively
available interventions are deployed, and whether
interventions lead to increases in consumption of
livestock products.
3.3 Emerging and available technologies for reducing CH4
emissions from livestock systems should be widely
tested under applicable field conditions as soon as
practical. With adequate resources these tests would
identify the best technologies and practices that could
be implemented where appropriate.
3.4 Promising avenues of investigation have been identified
that could result in additional opportunities for
reducing CH4 emissions from livestock systems.
3.5 Better estimates of CH4 emissions will allow targeting
of cost effective interventions to reduce emissions.
The emissions reductions achievable with the best
technologies will vary within and among countries with
variations in animal, management, and feeding
characteristics .
3.6 Animal production research that aims at increasing
efficiency of animal production will have considerable
impact on CH4 emissions. This research must be
stimulated in all countries with large livestock
populations.
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4. KEY RESEARCH NEEDED ON SPECIFIC EMISSIONS-REDUCTION
OPPORTUNITIES
4-l Strategic supplementation of extensively managed
catt\e. Large populations of cattle are consuming
forages of variable quality (particularly seasonally)
under grazing conditions. The relative productivity of
these animals (e.g., in terms of reproductive
efficiency) is low in some cases. By providing
strategic supplementation of nutrients to these
animals, CH4 emissions could be reduced by: (l)
providing a better balance in the rumen, which would
reduce CH4 emissions per amount of feed consumed; and
(2) increasing efficiency and productivity such that
given levels of production could be achieved with
smaller animal numbers.
The size of the animal population that could
benefit from this supplementation must be
estimated, it is expected that in some areas, the
applicable population may be a significant portion
of the total animal population.
The types of supplementation appropriate for each
area must be defined.
Techniques for delivering the technology
efficiently must be identified. Avenues to
explore include: range improvement; nutrient feed
blocks; bolus.
The monetary and energy costs of producing and
distributing the technology must be estimated and
balanced against improvements in animal
performance.
The reductions in CH4 emissions and improvements
in animal performance (that lead to overall
system-wide CH4 emissions reductions) must be
documented and validated under field conditions.
4'2 Pig* fflOdlflcatiQna for intensively Mn«ff«d animals. A
significant literature of experimental data from whole
animal calorimetry experiments demonstrates that CH.
emissions vary under different diets. Both increasing
the intake of the animals and modifying the composition
of the diet can reduce CH4 emissions per unit of
product, other feed inputs also appear to have
promising impacts on CH4 emissions levels (e.g., whole
cotton seeds or polyunsaturated fats). Modifying
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touarii lo»-cH, rations could
enissions by large
The size and location of the animal populations
for which feed modifications are a promising
alternative must be identified.
Promising strategies for lowering CH4 should be
identified for these populations of animals taking
into account the costs and availability of the
candidate feeds. Opportunities for reducing costs
and increasing the availability of the candidate
feeds should be explored.
The potential CHt emissions reduction from these
approaches should be quantified (e.g., using rumen
digestion and animal production models) and
verified with experimental data.
4'3 Use of bST or nther agents to increase production per
cow. The use of bST (or similar technologies) can
reduce CH4 emissions per amount of product produced by:
(1) further diluting the maintenance requirements of
individual lactating cows (a reduction of about 3 to
5%) ; and (2) reducing (by about 15%) the size of the
herd necessary to support the lactating cows (i.e., dry
cows and growing heifers) . Economic evaluations have
indicated that the use of bST is economic in its own
right in some circumstances.
The potential system-wide reduction in CH4
emissions associated with the use of bST should be
estimated so that its importance in this regard
can be assessed. This assessment should be
performed with a range of accepted values for the
anticipated performance response from the
administration of bST.
— The CH4 emissions implications of using other
growth regulating agents should also be evaluated.
4-4 Defaunation of the rumen. Based on experimental data,
under certain feeding systems, the elimination of
protozoa in the rumen results in lower CH6 emissions
and may enhance animal performance.
The population of animals whose performance could
be increased and whose CH4 emissions could be
decreased through defaunation should be estimated.
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Techniques for achieving defaunation should be
defined and demonstrated under field conditions.
The costs of administering these techniques should
be estimated and balanced against the benefits of
improved animal performance. Initial assessments
are that the costs of the defaunation may be
economically justified solely by improvements in
performance.
— The overall system-wide CH4 emissions reduction
anticipated must be estimated.
Strategic supplementation of ruminants fed crop
residues an? bv-nroduets to correct nutrient
deficiencies- Research and practice in India and other
developing countries indicate that improved rumen
performance can be achieved through the use of locally-
produced supplements. This improved rumen performance
allows for significantly improved animal productivity
and increased digestion efficiency, both of which can
contribute to significant CH6 emissions reductions per
unit of animal product. Based on experience in India,
strategic supplementation systems can be self-
sustaining and economic investments.
While it has been estimated that strategic
supplementation can reduce CH4 emissions
significantly in individual segments of animal
populations (e.g., by over 60%), evaluations of
overall system-wide performance must be performed
that reflect the diverse products produced by
cattle and buffalo. In particular, the economic
responses to changes in costs of production and
demand must be examined. Also, social impacts
must be evaluated. Preferred strategies that
reduce CH4 emissions through the use of
supplementation should be identified, and the
obstacles to their implementation should be
identified.
Key areas where strategic supplementation should
be investigated include those countries with large
cattle and buffalo populations. Examples include:
additional expansion in India; Pakistan;
Bangladesh; Sub-Saharan Africa; and China.
Assessments of these areas should be performed
that include infrastructure and marketing needs as
well as potential local sources of supplementation
inputs.
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4*6 Improve reproductive efficiency to reduce brnori horH
requirements, Improvements in reproductive efficiency
will reduce CH4 emissions by reducing the size of the
brood herd needed to sustain a given level of
production. Opportunities to accelerate promising
developments in this area should be explored.
4-7 Microbiological Approaches.
Improve mierobial growth efficiency to optimize
fiber digestion in the rumen and microbial
sYntnesis. CH4 emissions may be reduced by
balancing the rumen processes so that maximum
efficiency is achieved. Microbiological
approaches for promoting and achieving this
balance should be explored. Analyses of feeds,
feed combinations, feed treatments, bio-
engineering opportunities and other techniques
should be explored.
Reduce CH, production bv manipulating VFA
proportions and/or modifying the activities of the
methanoaens. Techniques for promoting propionate
production (a hydrogen sink) should be explored.
Additionally, inhibiting methanogens may provide
an opportunity for altering the fate of H2 in the
rumen such that less CH4 is produced.
4.8 Modifications to animal waste management practices. It
is anticipated that anaerobic animal waste management
practices produce significant CH4 emissions.
Reductions in these emissions are possible.
— Opportunities for modifying waste management
practices in a manner that is consistent with
other environmental objectives (such as protecting
groundwater quality) should be identified.
Opportunities for recovering CH4 from animal
wastes should be explored on various levels,
including: (1) integrated resource recovery
systems that produce a variety of useful products;
(2) anaerobic digesters that produce gas that can
be used as a commercial energy source or flared;
and (3) small scale projects applicable for small
farmers.
The costs of the alternative waste management
systems must be estimated and balanced against the
value of products produced. Indications are that
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under certain conditions, the systems are economic
to implement in their own right.
5. OTHER KEY RESEARCH NEEDS
5.1 Estimates of global CH4 emissions from livestock should
be improved by enumerating the major livestock
managements systems (including animal waste management
systems) and performing more realistic assessments of
the major systems that drive global emissions. These
assessments should reflect the stages in animal growth
and production and prevailing levels of feed intake.
5.2 Techniques for taking field measurements of CH4
emissions from animal systems should be developed and
applied. Such techniques will be useful for verifying
estimates of emissions and validating the effectiveness
of emissions reduction techniques in the field.
Approaches that should be pursued include:
Explore direct and indirect methods of assessing
CH4 emissions for field applications.
6. INSTITUTIONAL ISSUES
6.1 Reducing emissions from livestock is a particularly
attractive option because it usually is accompanied or
accomplished by improved animal productivity.
6.2 In designing interventions to reduce CH4 emissions from
livestock, consideration should be given to the impacts
of these interventions on other greenhouse gases and
other environmental and social areas of interest.
6.3 The implementation of technologies to reduce CH4
emissions will, in general, succeed only if induced by:
incentives, technology transfer, and/or the provision
of adequate financing. A mandatory emissions
limitation is unlikely to be successful in reducing
emissions.
6.4 It is essential that countries maintain or build up the
scientific infrastructure required to greatly increase
levels of research to find solutions to limiting CH4
emissions from livestock.
6.5 Current funding specifically to investigate, develop,
test, and implement CH4 reduction technologies and
programs does not exist.
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6.6 Key national and international authoritative bodies
should cooperate in identifying and evaluating the best
techniques for reducing CH4 emissions from livestock
6.7 Potential CH4 emissions reductions associated with
modifications to eating habits of humans are beyond the
scope of the meeting, and is primarily a question of
social choice and human nutrition and health needs.
*0.S. Government Printing office : 1992 - 312-014/40046
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