United States
Environmental Protection
Agency
Policy, Planning,
And Evaluation
(2122)
EPA 230-6-95-0)1
Revised January 1995
State Workbook
Methodologies For Estimating
Greenhouse Gas Emissions
• • • -' »• y . .»:••,•.-)*„• •
Second Edition
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STATE WORKBOOK
METHODOLOGIES FOR ESTIMATING
GREENHOUSE GAS EMISSIONS
Second Edition
U.S. Environmental Protection Agency
Office of Policy, Planning and Evaluation
State and Local Outreach Program
Washington, DC 20460
January 1995
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TABLE OF CONTENTS
Page
Introduction i
Directions for Completing Workbook
Directions xiv
Emissions Summary Table , xvi
WORKBOOK
1. Carbon Dioxide Emissions from Combustion of Fossil and
Biomass Fuels 1-1
2. Greenhouse Gas Emissions from Production Processes 2-1
3. Methane Emissions from Natural Gas
and Oil Systems 3-1
4. Methane Emissions from Coal Mining 4-1
5. Methane Emissions from Landfills 5-1
6. Methane Emissions from Domesticated Animals 6-1
7. Methane Emissions from Manure Management 7-1
8. Methane Emissions from Flooded Rice Fields : 8-1
9. Emissions from Agricultural Soil Management 9-1
10. Greenhouse Gas Emissions from
Forest Management and Land-Use Change 10-1
11. Greenhouse Gas Emissions from Burning of Agricultural
Crop Waste 11-1
12. Methane Emissions from Municipal Wastewater 12-1
DISCUSSION
1. Carbon Dioxide Emissions from Combustion of Fossil and
Biomass Fuels Dl-1
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2. Greenhouse Gas Emissions from Production Processes D2-1
3. Methane Emissions from Natural Gas
and Oil Systems D3-1
4. Methane Emissions from Coal Mining D4-1
5. Methane Emissions from Landfills D5-1
6. Methane Emissions from Domesticated Animals D6-1
7. Methane Emissions from Manure Management D7-1
8. Methane Emissions from Flooded Rice Fields D8-1
9. Emissions from Agricultural Soil Management D9-1
10. Greenhouse Gas Emissions from
Forest Management and Land-Use Change Dip-l
11. Greenhouse Gas Emissions from Burning of Agricultural
Crop Waste DIM
12. Methane Emissions from Municipal Wastewater D12-1
13. Other Greenhouse Gas Emissions from Mobile Combustion D13-1
14. Other Greenhouse Gas Emissions from Stationary Combustion D14-1
APPENDICES
Glossary, Chemical Symbols, and Conversion Factors . G-l
State Agency Contacts for Climate Change C-l
Bibliography of Key Reports B-l
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INTRODUCTION
A. THE PURPOSE OF THE WORKBOOK
This workbook is intended to provide states with a set of methodologies to estimate their
emissions of greenhouse gases and guidelines for reporting these emission estimates. Compiling an
emissions inventory is a critical first step toward developing policies and strategies to mitigate
greenhouse gas emissions and to assess the various options available for responding to the effects of
climat^ change. This workbook offers both simple and more sophisticated approaches to conducting
an emissions inventory, depending on the resources available and the level of effort a state can
undertake.
B. GREENHOUSE GASES AND CLIMATE CHANGE
The climate of the Earth is affected by changes in radiative forcing attributable to several
sources including the concentrations of radiatively active (greenhouse) gases, solar radiation, aerosols,
and albedo.1 Greenhouse gases in the atmosphere are virtually transparent to sunlight (shortwave
radiation), allowing it to pass through the air and to heat the Earth's surface. The Earth's surface
absorbs the sunlight and emits thermal radiation (longwave radiation) back to the atmosphere.
Because some gases, such as carbon dioxide (CO2), are not transparent to the outgoing thermal
radiation, some of the radiation is absorbed, and heats the atmosphere. In turn, the atmosphere
emits thermal radiation both outward into space and downward to the Earth, further warming the
surface. This process enables the Earth to maintain enough warmth to support life: without this
natural "greenhouse effect," the Earth would be approximately 55° F colder than it is today.
However, increasing concentrations of these greenhouse gases are projected to result in increased
average temperatures, with the potential to warm the planet to a level that could disrupt the activities
of today's natural systems and human societies.
Naturally occurring greenhouse gases include water vapor, carbon dioxide (CO2), methane
(CH4), nitrous oxide (N2O), and ozone (O3).2 Some human-made compounds, including
chlorofluorocarbons (CFCs) and partially halogenated fluorocarbons (HCFCs), their substitutes
hydrofluorocarbons (MFCs), and other compounds such as perfluorinated carbons (PFCs), are also
1 Albedo is the fraction of light or radiation that is reflected by a surface or a body. For example, polar
ice and cloud cover increase the Earth's albedo. "Radiative forcing" refers to changes in the radiative balance
of the Earth, Le., a change in the existing balance between incoming and outgoing radiation. This balance can
be upset by natural causes, e.g., volcanic eruptions, as well as by anthropogenic activities, e.g., greenhouse gas
emissions.
2 Ozone exists in the stratosphere and troposphere. In the stratosphere (about 12.4-31 miles above the
Earth's surface), ozone provides a protective layer shielding the Earth from ultraviolet radiation and
subsequent harmful health effects on humans and the environment. In the troposphere (from the Earth's
surface to about 6.2 miles above), ozone is a chemical oxidant and major component of photochemical smog.
Most ozone is found in the stratosphere, with some transport occurring to the troposphere (through the
tropopause, Le., the transition zone separating the stratosphere and the troposphere) (IPCC, 1992).
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greenhouse gases. In addition, there are photochemically important gases such as carbon monoxide
(CO), oxides of nitrogen (NOX), and nonmethane volatile organic compounds (NMVOCs) that,
although not greenhouse gases, contribute indirectly to the greenhouse effect. These are commonly
referred to as tropospheric ozone precursors because they influence the rate at which ozone and
other gases are created and destroyed in the atmosphere. Box 1-1 contains a brief description of these
gases, their sources, and their roles in the atmosphere.3
Although CO2, CH4, and N2O occur naturally in the atmosphere, their recent atmospheric
buildup appears to be largely the result of anthropogenic activities. This buildup has altered the
composition of the earth's atmosphere, and possibly will affect future global climate. Since 1800,
atmospheric concentrations of carbon dioxide have increased about 25 percent, methane
concentrations have more than doubled, and nitrous oxide concentrations have risen approximately
8 percent (IPCC, 1992). And, from the 1950s until the mid-1980s, when international concern over
CFCs grew, the use of these gases increased nearly 10 percent per year. The consumption of CFCs
is declining quickly, however, as these gases are phased out under the Montreal Protocol on
Substances that Deplete the Ozone Layer.4. Use of CFC substitutes, in contrast, is expected to grow
significantly.
Despite these increases, it is impossible at this juncture to predict with certainty, the timing,
magnitude, or regional distribution of any climatic change. Uncertainties about the climatic roles of
oceans and clouds as well as the climate feedbacks from oceans, clouds, vegetation, and other factors
make it difficult to predict the exact amount of warming that a given level of greenhouse gases, such
as doubled CO2 concentration, would cause and the rate at which any climate change would occur.
If the predicted levels of climate change occur (an average global temperature change between 1.5
and 4.5°F by 2050 (IPCC, 1992)), however, the areas most vulnerable to this disruption include:
forests, fisheries, coastal zones, agriculture, water resources, energy demand and supply, air quality,
and human health. Potential impacts on these sectors include: loss of tree species and reduced land
area of healthy forests, resulting from drier soils or increased pestilence and disease; reduced shellfish
populations resulting from the loss of coastal wetlands; northward regional shifts in agricultural
productivity; increased annual demand for electricity for summer cooling thereby increasing the need
for total generating capacity; water use conflicts as water availability declines and demand for water,
such as for irrigation and power plant cooling, increases; and increased air pollution, as air quality is
directly effected by weather variables such as higher temperatures which speed the reaction rates
among chemicals in the atmosphere, causing higher ozone pollution and urban smog (Smith and
Tirpak, 1989).
3 For convenience, all gases discussed in this document are generically referred to as "greenhouse gases,"
although the reader should keep in mind the distinction between actual greenhouse gases and photochemically
important trace gases.
4 Recognizing the harmful effects of chlorofluorocarbons and other halogenated fluorocarbons on the
atmosphere, many governments signed the Montreal Protocol on Substances that Deplete the Ozone Layer in
1987 to limit the production and consumption of a number of these compounds. As of June 1994, 133
countries had signed the Montreal Protocol. The United States furthered its commitment to phase out these
substances by signing and ratifying the Copenhagen Amendments to the Montreal Protocol in 1992. Under these
amendments, the United States committed to eliminating the production of all halons by January 1, 1994, and
of all CFCs by January 1, 1996.
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Box 1-1. Greenhouse Gases and Photochemically Important Gases
The Greenhouse Cases
Carbon Dioxide (CO,). The combustion of liquid, solid, and
gaseous fossil fuels is the major anthropogenic source of carbon
dioxide emissions. Some other non-energy production processes
(e.g., cement production) also emit notable quantities of carbon
dioxide. CO, emissions are also a product of forest clearing and
biomass burning. Atmospheric concentrations of carbon dioxide
have been increasing at a rate of approximately 0.5 percent per
year (IPCC, 1992), although recent measurements suggest that
this rate of growth may be moderating (Kerr, 1994).
In nature, carbon dioxide is cycled between various
atmospheric, oceanic, land biotic, and marine biotic reservoirs.
The largest fluxes occur between the atmosphere and terrestrial
biota, and between the atmosphere and surface water of the
oceans. While there is a small net addition of CO, to the
atmosphere (i.e., a net source of CO,) from equatorial regions,
oceanic and terrestrial biota in the Northern Hemisphere, and to
a lesser extent in the Southern Hemisphere, act as a net sink of
CO, (i.e., remove more CO, from the atmosphere than they
release) (IPCC, 1992).
Methane (CHA Methane is produced through anaerobic
decomposition of organic matter in biological systems.
Agricultural processes such as wetland rice cultivation, enteric
fermentation in animals, and the decomposition of animal wastes
emit methane, as does the decomposition of municipal solid
wastes. Methane is also emitted during the production and
distribution of natural gas and oil, and is released as a by-
product of coal production and incomplete fuel combustion. The
atmospheric concentration of methane, which has been shown to
be increasing at a rate of about 0.6 percent per year (Steele et
al.,1992), may be stabilizing (Kerr, 1994).
The major sink for methane is its interaction with the hydroxyl
radical (OH) in the troposphere. This interaction results in the
chemical destruction of the methane compound, as the hydrogen
molecules in methane combine with the oxygen in OH to form
water vapor (H,O) and CHj. After a number of other chemical
interactions, the remaining CH, turns into CO which itself reacts
with OH to produce carbon dioxide
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Drastic cuts in emissions would be required to stabilize atmospheric composition. Because
greenhouse gases, once emitted, remain in the atmosphere for decades to centuries, merely stabilizing
emissions at current levels would allow the greenhouse effect to intensify for more than a century.
For example, emissions of carbon dioxide might have to be reduced by 50 to 80 percent to hold its
current concentration constant. While it is not possible to stabilize greenhouse gas concentrations
immediately, implementation of measures to reduce emissions would decrease the risk of global
warming, regardless of the uncertainties about the response of the climate system (Lashof and Tirpak,
1990).
C. INTERNATIONAL, NATIONAL, AND STATE ACTIONS
Scientific consensus that the threat of climate change is real has triggered a wave of response
actions by governments at the international, national, and state levels. For example, since the mid-
1980s, the U.S. has taken an active role in fostering international cooperation and furthering research
into understanding the causes and impacts of climate change. Initially, the U.S. worked with technical
experts from over 50 countries and the Organization for Economic Cooperation and Development
(OECD) to develop methods for estimating emissions and uptake of greenhouse gases. This
cooperative effort supported the charge of the Intergovernmental Panel on Climate Change (IPCC),
a committee jointly established by the United Nations Environment Program (UNEP) and the World
Meteorological Organization (WMO) in 1988 to assess scientific information related to climate
change issues. These activities culminated in the compilation of a set of internationally-accepted
methods for conducting national emission inventories, the IPCC Guidelines for National Greenhouse
Gas Inventories: Vols. 1-3 (IPCC, 1994).
In June of 1992, the U.S. further demonstrated its concern about climate change by joining
with 154 other nations at the United Nations Conference on Environment and Development in
signing the Framework Convention on Climate Change (FCCC). Later, in October of 1992, the U.S.
became the first industrialized nation to ratify the Treaty, which came into force on March 21, 1994.
The FCCC commits signatories to stabilizing anthropogenic greenhouse gas emissions to "levels that
would prevent dangerous anthropogenic interference with the climate system." To facilitate this.
Article 4-1 requires that all parties to the FCCC develop, periodically update, and make available to
the Conference of the Parties, national inventories of anthropogenic emissions of all greenhouse
gases not controlled by the Montreal Protocol, using comparable methodologies. To fulfill its
obligation under the FCCC, the U.S. government published the Inventory of U.S. Greenhouse Gas
Emissions and Sinks: 1990-1993 (U.S. EPA, 1994) and the U.S. Climate Action Report (U.S.
Government, 1994).5
At the national level, the Clinton Administration developed and published the Climate Change
Action Plan (CCAP; Clinton and Gore, 1993) to assist the U.S. in meeting its obligation under the
FCCC — to return greenhouse gas emissions .to 1990 levels by the year 2000. The Climate Change
Action Plan promotes the development and expansion of approximately 50 initiatives that span all
sectors of the economy and focus on reducing emissions of greenhouse gases in a cost-effective
5 The Climate Action Report represents the first formal U.S. communication under the FCCC as required
by Article 4.2 and 12. It is a description of the current U.S. program. It does not seek to identify additional
policies or measures that might ultimately be taken as the U.S. continues to move forward in addressing
climate change, nor is it a revision to the Climate Change Action Plan. It is intended to identify existing
policies and measures, and thus assist in establishing a basis for considering future actions.
IV
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manner. These initiatives call for cooperation between government, industry, and the public, and,
since they are primarily voluntary in nature, are designed for rapid implementation. Also, the
Department of Energy has recently released a set of draft guidelines for entities to report voluntarily
their reductions of greenhouse gas emissions and fixation of carbon, achieved through any measure.
The purpose of these guidelines is (1) to provide a database of information for entities seeking to
reduce their own greenhouse gas emissions; (2) to establish a formal record of emissions and emission
reductions and carbon sequestration achievements; and (3) to inform the public debate in future
discussions on national greenhouse gas policy.
At the state level, the U.S. EPA's Climate Change Division, State and Local Outreach
Program, has been working with states to assist them in (1) identifying their greenhouse gas emission
sources and estimating their overall contribution to radiative forcing, (2) assessing the areas of the
state that are most vulnerable to climate change, and (3) developing state-specific greenhouse gas
mitigation strategies. In November of 1992, the Climate Change Division published the original
version of this document State Workbook: Methodologies for Estimating Greenhouse Gas Emissions
(U.S. EPA, 1992). As part of the next phase of the State and Local Outreach Program, the Climate
Change Division will publish the States Guidance Document: Policy Planning to Reduce Greenhouse
Gas Emissions (forthcoming). In addition to these activities, the National Governors' Association
Task Force on Global Warming has proposed more than 20 strategies, consistent with international
goals, for responding to the threat of global warming (NGA, 1991). Also, the Council of State
Governments' Global Climate Change Task Force has published a plan that recommends 30 ways for
Northeastern states to reduce emissions of greenhouse gases (Environmental Information Networks,
Inc., 1994a).
D. THE ROLE OF THE STATES
States will need to consider a variety of issues, ranging from mass transit to reforestation, and
from the recycling of wastes to the reduction of energy use, in order to develop climate change
policies that reduce emissions of greenhouse gases while maintaining economic growth and
development. Many states have already begun to address these issues. Examples include: a
California law calling for the California Energy Commission to study the potential impact of climate
change on the state's energy supply/demand, economy, environment, and agricultural and water
resources; a Connecticut law establishing a broad range of energy conservation measures; the
adoption of higher levels of energy efficiency standards and the initiation of an energy efficiency
program focused on the reduction of CO2 emissions by the Energy Division of the Minnesota
Department of Public Service; and, an Oregon law requiring the Oregon Department of Energy to
develop strategies for reducing greenhouse gas emissions (Silbiger and Gongring, 1992 and
Environmental Information Networks, Inc., 1994b).
There are several reasons why states can significantly affect their emissions of greenhouse
gases. First, state governments hold direct regulatory authority over the sources of more than half
of all CO2 emissions: gas and electric utilities. Second, states also determine the acceptability of
building specifications and land-use planning, thereby affecting emissions from the residential,
commercial, and transportation sectors. Third, states also have jurisdiction over determining
regulations concerning the use and recycling of paper, glass, and plastic products, the management
of municipal solid wastes (and consequently methane emissions), and the promotion of energy savings
from secondary manufacturing. Finally, many states currently regulate forestry practices on non-
federal lands.
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A wide variety of policy options are available that have the technical potential to reduce
greenhouse gas emissions. Many appear to be consistent with other economic, development,
environmental, and social goals. One such policy includes identifying and implementing opportunities
for cost-effective energy efficiency improvements. For example, efficiency investments that pay for
themselves over the life of the equipment, through reduced energy costs, suggest that the
accompanying reduction in carbon dioxide emissions may be essentially a cost-free by-product of a
more efficient economy.6 Efficiency improvements can also reduce emissions of other pollutants,
improve economic competitiveness, and enhance U.S. environmental quality, energy independence,
national security, and public health (NGA, 1991). Expanding the use of non-fossil energy sources,
capturing and reusing methane from landfills and coal mines, and increasing afforestation and
reforestation efforts are other possible policy options with multiple benefits.
Policy-makers and planners will need to design policies and strategies to deal with the
uncertainties of climate change, the potentially significant impacts climate change could have on their
region's natural resources, and ways to reduce emissions of greenhouse gases to help curb climate
change.7 This requires a three-step process: (1) an assessment of the vulnerability of resources to
climate change impacts; (2) an evaluation of adaptation options; and (3) an evaluation of mitigation
options.
Assessing the vulnerability of a state or region to climate change impacts involves estimating
a range of regional climate change scenarios on local resources. After vulnerability assessments have
been completed, a state can weigh its vulnerabilities against the economic, environmental, and social
costs and benefits of various response options to the possibility of such events as sea-level rise,
changes in rainfall and temperature, water conservation, forest health and production, and protection
of biological diversity. The efficient implementation of these policies can best be achieved through
the establishment of priorities among suggested anticipatory options (EPA, 1991).
Considerable uncertainty exists, however, regarding the economic and social costs and benefits
associated with preventative measures to combat the potential effects of climate change and strategies
to mitigate greenhouse gas emissions. Some estimates show that the costs associated with stabilizing
greenhouse gas emissions will range anywhere from 0 to 6 percent of the U.S. GNP (Manne and
Richels, 1989), while a National Academy of Sciences panel has concluded that the potential exists
to reduce greenhouse gas emissions in the United States by 10 to 40 percent of 1990 levels at a very
low cost and possibly at a net savings (NAS, 1991). The actual costs and benefits of alternative
mitigation and adaptation strategies in an individual state will, of course, depend on the particular
sectoral sources of emissions, currently available technologies, and the vulnerabilities of the
.agricultural, forestry, energy, and other important sectors in that state.
6 According to the National Academy of Science report "Policy Implications of Greenhouse Warming-
Mitigation Panel", NAS Press, 1991, as quoted by Richard A. Kerr, "the most cost-effective measures for
reducing emissions are by increasing the energy efficiency of residential and commercial buildings and
activities, vehicles, and industrial processes that use electricity." (Science, Vol 252, 21 June 1991, pg. 252.)
7Adaptation options will be necessary in the future if current and planned capabilities are found to be
insufficient to address the adverse impacts of climate change. Under these options falls the debate over
anticipatory versus reactive measures. Reactive measures are those which are made as climate change impacts
occur; anticipatory measures are made before climate change impacts are felt. Crucial to this debate is the
analysis of the economic, environmental, and social costs and benefits of any suggested options (EPA, 1991).
VI
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E. GLOBAL WARMING POTENTIAL (GWP)
When discussing greenhouse gases in a policy context, especially when attempting to estimate
the costs and benefits of greenhouse gas emission reduction strategies, it is useful to have some
means of estimating the relative effects of each greenhouse gas on radiative forcing of the
atmosphere over some future time horizon, without performing the complex and time-consuming task
of calculating and integrating changes in atmospheric composition over the period. In short, the need
an index is needed that translates the level of emissions of various gases into a common metric in
order to compare the climate forcing effects without directly calculating the changes in atmospheric
concentrations (Lashof and Tirpak, 1990). This information can then be used for calculations of the
cost-effectiveness of reductions, e.g., CO2 emissions compared to CH4 emissions.
A number of approaches, called Global Warming Potential (GWP) indices, have been
developed in recent years. These indices account for the direct effects of growing concentrations of
carbon dioxide, methane, chlorofluorocarbons, nitrous oxide, hydrofluorocarbons, and perfluorinated
carbons in the atmosphere on radiative forcing. They also estimate indirect effects on radiative
forcing due to emissions which are not themselves greenhouse gases, but lead to chemical reactions
that create or alter greenhouse gases. These emissions include carbon monoxide, nitrogen oxides,
and nonmethane volatile organic compounds, all of which contribute to formation of tropospheric
ozone, which is also a greenhouse gas (Lashof and Tirpak, 1990).
This workbook follows the methodology used by the IPCC (IPCC, 1992). However, there is
no universally accepted methodology for combining all the relevant factors into a single global
warming potential for greenhouse gas emissions. In addition to the IPCC, there are several other
noteworthy attempts to define a concept of global warming potential, including Lashof and Ahuja
(1990), Rodhe (1990), Denvent (1990), WRI (1990), and Nordhaus (unpublished).
The concept of the global warming potential, as developed by the IPCC, is based on a
comparison of the radiative forcing effect of the concurrent emission into the atmosphere of an equal
quantity of CO2 and another greenhouse gas. Each gas has a different instantaneous radiative forcing
effect. In addition, the atmospheric concentration attributable to a specific quantity of each gas
declines with time. In general, other greenhouse gases have a much stronger instantaneous radiative
effect than does CO2; however, CO2 has a longer atmospheric lifetime and a slower decay rate than
most other greenhouse gases. Atmospheric concentrations of certain greenhouse gases may decline
due to atmospheric chemical processes, which in turn create other greenhouse gases or contribute
to their creation or longevity. There is a substantial amount of uncertainty in our understanding of
many atmospheric chemical processes, including latitudinal and temporal variations, that makes it
impossible to quantify how certain gases may indirectly affect climate. Due to these uncertainties
over the indirect effects, they have not been included in the GWP of each gas at this time (IPCC,
1992). Only the ability of gases to directly affect radiative forcing is included here.8
The one exception is methane which has a direct GWP of 11. The indirect effects of methane, however,
are considered comparable in magnitude to the direct effects, therefore a GWP of 22 is used in this document
(IPCC. 1992). Using a GWP of 22 for methane is also consistent with the GWP used in the Climate Change
Action Plan (Clinton and Gore, 1993), and follows the suggestion of the International Negotiating Committee's
(INC) 9th Session that requests that indirect effects of greenhouse gases be included where applicable. The
magnitude of the indirect effects of other gases are either zero or uncertain, and, therefore, are not
recommended for use at this time.
vu
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Box 1-2
Global Warming Potentials for Various Greenhouse Gases
(Direct Effects Only)
GWP
(•IPO-years')
1 ,
11/22
270
1,200
10,000
150
5,400
Following this
convention, the GWP is
defined as the time-
integrated commitment to
climate forcing from the
instantaneous release of 1
kilogram of a trace gas
expressed relative to that
from 1 kilogram of carbon
dioxide. The magnitude of
the GWP is, however,
sensitive to the time horizon
over which the analysis is
conducted (i.e., the time
period over which the
integral is calculated). For
example, Box 1-2
summarizes the GWPs of
key greenhouse gases
assuming a 100-year time
horizon. The assumed
integration period defines
the time period over which
the radiative effects of the
gas are measured. These
GWPs indicate, for example,
that 1 kilogram of nitrous
oxide emissions is estimated
to have approximately 270
times the direct impact on
radiative forcing as 1
kilogram of carbon dioxide
for a 100-year time horizon.
If a 500-year time horizon is assumed, however, nitrous oxide is estimated to have only 170 times the
direct impact on radiative forcing compared to an equivalent amount of carbon dioxide. The
differences between the values for 100 years and 500 years incorporate the differences in atmospheric
lifetime.
Trace Gas
Carbon Dioxide
Methane"
Nitrous Oxide
CFC-llb
CFC-12b
CFG-113"
CFG-114"
HCFC-22b
HFC-134a
HFC-23
HFC-152a
PFCs
CO
NO.,
NMVOCs
Sign of
Indirect Effect
none
positive
uncertain
uncertain
uncertain
uncertain
uncertain
uncertain
positive
positive
positive
positive
positive
uncertain
positive
3 The direct GWP of methane is 11, however, the indirect effects of methane
are considered comparable in magnitude 'to the direct effects, therefore, a
GWP of 22 is recommended for use in this document.
b Although CFCs and related compounds have very large direct GWPs, their
indirect effects are believed to be negative and, therefore, could significantly
reduce the magnitude of their direct effects (IPCC, 1992). Given the
uncertainties surrounding the net effect of these gases, no GWP has been
provided at this time.
Source: IPCC 1992.
For the discussion included in this document, the GWPs presented in Box 1-2 for a 100-year
time horizon are used to convert all greenhouse gases to a CO2-equivalent basis so that the relative
magnitudes of different quantities of different greenhouse gases can be readily compared. There is
nothing particularly unique about this time horizon. Nevertheless, it is sufficiently long that many of
the atmospheric processes currently thought to affect concentrations can be considered without
excessively weighing longer-term impacts on atmospheric processes that are not well understood.
Using the GWPs presented in Box 1-2, the relative contribution of each greenhouse gas to
global warming for any greenhouse gas emission estimates can be calculated. For example, in Figure
1-1, U.S. contributions to global warming by the primary greenhouse gases are represented using U.S.
Vlll
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emission estimates for the year 1990 based on conversion to a CO2-equivalent basis using 100-year
GWPs.
The GWP potential will be an important concept for states in determining the relative
importance of each of the major emissions sources and in developing appropriate mitigation
strategies.
F.
THE INVENTORY PROCESS
Figure 1-1
U.S. Greenhouse Gas Emissions and Sinks: 1990
1500
1352
1444
1000
UJ
O
500
-500
Before a state can effectively
develop policies to reduce
greenhouse gas emissions and
respond to climate change, it needs
to identify its anthropogenic
emissions sources and estimate the
contribution of these emission
sources to overall radiative forcing.
The methodologies presented in this
workbook to assist states in
identifying and estimating their
emissions of greenhouse gases have
been adapted from Volumes 1-3 of
the IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC,
1994)9 and the Inventory of U.S.
Greenhouse Gas Emissions and
Sinks: 1990-1993 (U.S. EPA, 1994).
In many cases, the methodologies
presented are consistent with the
IPCC Guidelines, however, for
emission sources considered to be
major sources in the U.S., the IPCC
default methodologies have been
expanded and more comprehensive,
U.S.-specific methods are provided.
These instances include, energy consumption, forest sinks, and some methane sources. It is suggested.
however, that if a state has access to state- or region-specific emissions factors or has the ability to
take on-site emission measurements at various sources, then the state should pursue these options.
CO2 C02
Emissions Sinks
CH4 N2O HFC/ Net
RFC Emissions
Gas Type
C02
CH4
N20
HFC/PFC
Source: U.S. EPA, 1994
Note: MMTCE stands for million metric tonnes of carbon-equivalent.
Discussions of inventory methods can also be found in Estimation of Greenhouse Gas Emissions and
Sinks: Final Report from the OECD Experts Meeting, 18-21 February 1991 (August 1991). That report
documents baseline inventory methodologies for a variety of source categories, which have subsequently been
further refined based on recommendations provided at an IPCC-sponsored experts workshop held in Geneva,
Switzerland in December 1991 and at an OECD/Netherlands-sponsored workshop in Amersfoort, Netherlands
in February 1993. The proceedings from these meetings, the Final Report (OECD 1991), as well as several
other international meetings, form the basis for the current IPCC Guidelines.
be
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While these methods provide a solid foundation for the development of a more detailed and
comprehensive emission inventory, they have several strengths and weaknesses. First of all, there are
uncertainties associated with some of the emission coefficients presented. Some of the current
"•.mission coefficients, such as those for CO2 emissions from energy-related activities and cement
)rocessing, are considered accurate. For other categories of emissions, however, a lack of data or
in incomplete understanding of how emissions are generated limit the scope or accurac of ta-j
emission coefficients. For certain categories, emission coefficients are given as a specified nge to
eflect the associated uncertainty. Where applicable, specific factors affecting the accuracy f these
estimates are discussed in detail.
Secondly, while the methodologies provided in the IPCC Guidelines and the Inventory of U.S.
Jreenhou.se Gas Emissions and Sinks represent baseline methodologies for a variety of source
;ategories, many of these methodologies are still being refined. Specific areas requiring further
•esearch include:
• Understanding the relationship between emissions and sources. This is a crucial step
in completing and refining existing methodologies and in developing methodologies
for emission source categories where none currently exist. For example, a great deal
of uncertainty exists in how nitrous oxide emissions are produced from energy-related
activities and fertilizer consumption. As a consequence, the quality of emission
factors and activity data for these categories are particularly weak. In addition,
methods for estimating emissions from some land-use activities and industrial
processes are not included in this workbook because the scientific understanding
surrounding these source categories is uncertain.
• Improving the accuracy of emissions factors. A substantial amount of research is
underway that could improve the accuracy of emission factors used to calculate
estimates for a variety of sources. For example, the accuracy of current emission
factors used to estimate emissions from rice production is limited by a lack of
available data. Emission factors for methane from landfills are also currently
undergoing revision. To more accurately assess methane emissions from landfills,
researchers are working to determine the relationship between moisture, climate, and
waste composition and methane generation rates. Emission factors used to estimate
greenhouse gas emissions from biomass burning and land use are also being revised.
• Providing appropriate activity data. Although methodologies exist for estimating
emissions for some source categories, problems arise in obtaining data that are
compatible with methodology requirements. For example, the ability to estimate
emissions from oil and gas systems is constrained by a lack of information on
compressor type, amount of leakage, and emission control technology. In the
agricultural sector, estimating emissions from enteric fermentation of domesticated
livestock, using the more sophisticated approach as recommended in the IPCC
Guidelines, is arduous because of the complexity of the data required. Obtaining
information on animal weights, work habits, and feeding practices by animal type is
difficult. Efforts need to be made to collect activity data appropriate for use in these
more sophisticated methodologies.
The uncertainties and limitations associated with calculating greenhouse gas emissions are
both qualitative and quantitative. The methods provided reflect current best scientific understanding.
-------
Efforts need to be made to improve existing methodologies and data collection activities, so that
methodologies and data are consistent with one another and so that they allow states to estimate
emissions with greater ease, certainty, and consistency.
Regardless of the methodologies or estimation techniques a state may decide to use, the key
to a sound emissions inventory is documentation of the activity data and emission factors being used.
This includes information on their derivation and clear definitions of activities. Any emissions
inventory that is not accompanied by sound documentation is unverifiable. Without clear
documentation on the methods employed and data used, it will be impossible to refine and improve
the accuracy of greenhouse gas inventories. States may also at some point want to compare their
inventories with other states, or pool statistics in a regional inventory. This can only be done if
emissions are estimated using comparable and consistent methods, with data that are understandable
and verifiable.
The remainder of this report is divided into two main sections: /. Workbook Calculations and
//. Discussion of Emission Sources and Sinks. The Workbook Section contains simplified instructions
for completing a state inventory of greenhouse gas emissions. The Discussion Section contains
background information on each source and more detailed information on the recommended methods
for estimating emissions as well as a description of alternate methods. The Directions, beginning on
page xiv, provide specific instructions for completing the workbook in the most efficient manner.
XI
-------
References
Benioff, R. 1990. Potential State Responses to Climate Change. Prepared for the Office of Policy,
Planning, and Evaluation, U.S. Environmental Protection Agency, Washington, D.C. 1990
Clinton, W. and A. Gore. 1993. The Climate Change Action Plan. Coordinated by U.S. DOE,
Office of Policy, Planning, and Program Evaluation. U.S. DOE/PO-0011. October, 1993.
Derwent, R.G. 1990. Trace Gases and Their Relative Contribution to the Greenhouse Effect (Report
AERE-R13716). Atomic Energy Establishment, Harwell, Oxon.
Environmental Information Networks. 1994a. Global Warming On-line, July 15, 1994.
Environmental Information Networks. 1994b. Global Warming On-line, September 12, 1994.
IPCC (Intergovernmental Panel on Climate Change). 1994. IPCC Guidelines for National
Greenhouse Gas Inventories, 3 volumes: Vol. 1, Reporting Instructions; Vol. 2, Workbook; Vol.
3, Draft Reference Manual. Intergovernmental Panel on Climate Change, Organization for
Economic Co-Operation and Development. Paris, France.
IPCC. 1992. Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment.
Report Prepared for IPCC by Working Group. 1.
IPCC. 1990. Scientific Assessment of Climate Change. Report prepared for IPCC by Working Group
1. June 1990.
Kerr, R. 1994. "Did Pinatubo Send Climate-Warming Gases into a Dither?" Science, Vol. 263, 18
March, 1994.
Lashof, D.A. and D.R. Ahuja. 1990. Relative contributions of greenhouse gas emissions to global
warming. Nature 344:529-531.
Lashof, D.A. and E.L. Washburn. 1990. The Statehouse Effect: State Policies to Cool the Greenhouse
Effect. Natural Resources Defense Council, Washington, D.C. 1990.
Lashof, D.A. and D.A. Tirpak. 1990. Policy Options for Stabilizing Global Climate Change. Office
of Policy, Planning, and Evaluation, U.S. Environmental Protection Agency, Washington, D.C.
1990.
Lyman, F., I. Mintzer, K. Courrier, and J. MacKenzie. 1990. The Greenhouse Trap. World
Resources Institute, Washington, D.C. 1990.
Manne, A.S. and R.G. Richels. 1989. CO2 emissions limits ~ An economic cost analysis for the
U.S.A. The Energy Journal. November, 1989.
National Academy of Sciences. 1991. Policy Implications of Greenhouse Wanning. National
Academy Press, Washington, D.C. 127 pp.
xu
-------
NGA (National Governors' Association). 1991. A World of Difference: Report of the Task Force on
Global Climate Change. NGA, Washington, D.C. 36 pp.
Nordhaus, W.D. 1990. Economic Policy in the Face of Global Warming. Unpublished paper.
Oregon Department of Energy (ODOE). 1991. Fourth Biennial Energy Plan. Oregon Department
of Energy, Salem, Oregon.
Rodhe, H. 1990. A comparison of the contribution of various gases to the greenhouse effect.
Science 248:1217-1219.
Siegenthaler, V. 1983. Uptake of excess CO2 by an outcrop-diffusion model of the ocean. Journal
of Geophysical Research 88:3599-3608.
Silbiger, A and N. Gonring. 1992. Selected Summary of Current State Responses to Climate Change.
Prepared for Office of Policy, Planning, and Evaluation, United States Environmental
Protection Agency, Washington, D.C. July 1992.
Smith. J. and D. Tirpak. 1989. The Potential Effects of Global Climate Change on the United States.
Office of Policy, Planning and Evaluation, U.S. Environmental Protection Agency,
Washington, D.C. 1990.
Steele, L.P., EJ. Dlugokencky, P.M. Lang, P.P. Tans, R.C. Martin, and K.A. Masarie. 1992. "Slowing
Down of the Global Accumulation of Atmospheric Methane During the 1980's." Nature 358:
313 - 316. July, 1992.
Trexler, M. 1991. Minding the Carbon Store. World Resources Institute, Washington, D.C. 1991.
U.S. EPA (U.S. Environmental Protection Agency). 1994. U.S. Inventory of Greenhouse Gas
Emissions and Sinks: 1990 - 1993. U.S. EPA, Office of Policy, Planning and Evaluation.
EPA 230-R-94-014. September. 1994.
U.S. EPA. 1991. Adapting to Climate Change: What Governments Can Do. U.S. Environmental
Protection Agency, Office of Policy, Planning and Evaluation. Climate Change Adaptation
Branch. 1991.
U.S. EPA. 1990. Policy Options for Stabilizing Global Climate. Office of Policy, Planning, and
Evaluation, United States Environmental Protection Agency. Report No. 21P-2003.1.
December, 1990.
U.S. Government. 1994. U.S. Climate Action Report. Submission of the U.S. Government Under the
Framework Convention on Climate Change. U.S. Government Printing Office. ISBN 0-16-
045214-7. September, 1994.
World Resources Institute (WRI). 1990. World Resources Report. Oxford University Press. New York.
1990.
Kill
-------
DIRECTIONS
The objectives of this report are: (1) to provide states with methodologies for estimating
greenhouse gas emissions from the major anthropogenic sources; and (2) to provide analysts with
important background information these source categories. In order to best achieve these two objectives,
the report is divided into two sections:
(1) Workbook, and
(2) Discussion.
The workbook section presents step-by-step instructions for estimating emissions from each source
category. For each workbook section, these is a companion discussion chapter that contains background
information pn emissions sources and more detailed information on the methods presented in the
workbook. For example, Workbook Section 1 presents the steps for calculating CO2 emissions from fossil
fuel combustion, while Discussion Section 1 of the discussion section offers more detailed information
on CO2 emissions from energy combustion.
Analysts should first read through the background information in the discussion section. The
background should provide a sufficient informational foundation to allow analysts to begin working on
the calculations as presented in the workbook. Each workbook chapter contains simplified instructions
for estimating emissions from a particular source. The methods presented in the workbook sections are
intended to be straightforward and to require a limited amount of time to complete. Once the
calculations have been completed for each source category, emissions estimates should be recorded-ia
the Summary Table provided on page xvi.
The discussion chapters provide more detailed information on the methodology used to develop
the methods presented in the workbook chapters. Therefore, analysts seeking a more thorough
understanding of the methods should consult the corresponding discussion chapter. Additionally, some
discussion chapters provide alternative methods for estimating emissions. These alternate methods
typically are more time consuming to complete and require more detailed emissions data than those
presented in the workbook section. However, in some instances they may also result in more precise
estimates. States that have access to detailed data are encouraged to estimate emissions following the
alternate methodologies.
WORKBOOK SECTIONS
The Workbook contains 12 sections, each pertaining to a particular anthropogenic activity that
results in emissions of greenhouse gases. This section is organized as follows:
Section 1: Carbon Dioxide Emissions from Fossil and Biomass Fuel Combustion
Section 2: Greenhouse Gas Emissions from Production Processes
Section 3: Methane Emissions from Oil and Natural Gas Systems
Section 4: Methane Emissions from Coal Mining
Section 5: Methane Emissions from Landfills
Section 6: Methane Emissions from Domesticated Animals
Section 7: Methane Emissions from Manure Management
Section 8: Methane Emissions from Rice Cultivation
Section 9: Nitrous Oxide Emissions from Fertilizer Use
xiv
-------
Section 10: Greenhouse Gas Emissions from Land-Use Activities
Section 11: Greenhouse Gas Emissions from the Burning of Agricultural Crop Wastes
Section 12: Methane Emissions from Wastewater Treatment
It is recommended that states complete all 12 chapters.1 While all chapters are important, states should
spend the greatest amount of time on Chapter 1, since CO2 emissions from fossil fuel combustion are
likely to be the single greatest source of greenhouse gas emissions. After this chapter, states should work
on Chapters 2 through 9, because these chapters address the next largest sources of greenhouse gas
emissions.
Each workbook section includes suggested sources for the data that are required to complete the
emissions calculations. In some cases, default values are provided in the event that state information is
not available. However, in all cases, state information should be used where possible.
DISCUSSION SECTIONS
As mentioned previously, each Workbook Section has a corresponding Discussion Section. The
purpose of the discussion chapter is to provide more complete background information on the emissions
sources and to describe the method for calculating emissions in greater detail. Additionally, the discussion'
chapters provide information on alternate methods for calculating emissions, where appropriate. Finally,
the discussion chapters indicate the potential limitations of the methods presented and provide additional
reference information.
Discussion Sections 13 and 14 (Greenhouse Gas Emissions from Mobile Sources and Greenhouse
Gas Emissions from Stationary Sources, respectively) do not have corresponding workbook chapters
because the calculations required to estimate these emissions are very time consuming, data intensive,
and complex. Moreover, states may already be estimating these emissions (at least CO, NOX, and
NMVOCs) as a result of ongoing efforts to monitor their compliance with the Clean Air Act.
Accordingly, it is not recommended that states estimate emissions from these sources. However, it is
recommended that the analyst read through the background information in the discussion chapters.
OTHER INFORMATION
In addition to the Workbook and Discussion. Sections, included in this document are the
following:
• Glossary: Includes definitions of terms related to climate change and a list of chemical
symbols and conversion factors.
• Contacts: Includes a list comprised of state environmental and energy offices that could
aid analysts in their work on climate change.
• Bibliography: Includes a list of key reports on climate change impacts, adaptation
measures, and emissions mitigation activities that could be useful to a state developing
mitigation and adaptation strategies.
1 Most states, however, will not need to complete Chapters 4 and 8, because coal is mined only in
thirteen states and rice is produced in only seven.
xv
-------
SUMMARY TABLE FOR REPORTING EMISSIONS ESTIMATES
SOURCE
GAS
EMISSIONS
(tons, on a
full
molecular
basis)
GWP
EMISSIONS
(CO2-Equivalent)
Fossil Fuel Combustion
Btomass Fuel Combustioo
Production Processes
Natural Gas and Oil Systems
Coal Mining
Landfills
Domesticated Animals
Manure Management
Rice Cultivation
Fertilizer Use
Forest Management & Land-Use
Change
Burning of Agricultural Crop
Wastes
Wastewater Treatment
i
Total Emissions
(All sources, excluding biomass
fuels
C02
C02
CO2
N2O
PFCs
HFC-23
CH4
CH4
CH4
CH4
CH4
CH4
N20
C02
CH4
N2O
NOX
CO
CH4
CO2
CH4
N2O
NOX
CO
PFCs
HFC-23
1
t
1
270
5,400
10,000
22
22
22
22
22
22
270
1 -
22
270
22
1
22
270
5,400
10,000
ff A V.ff •> ff f f
XVI
-------
PARTI
WORKBOOK SECTIONS
-------
WORKBOOK 1
CARBON DIOXIDE EMISSIONS FROM
COMBUSTION OF FOSSIL AND BIOMASS FUELS
Carbon dioxide is emitted during the combustion of fossil and biomass fuels. Fossil fuels include
coal, oil, and natural gas. For this calculation, biomass fuels primarily include wood, charcoal,
bagasse, agricultural wastes, and vegetal fuels.
To estimate state emissions of carbon dioxide from fossil and biomass fuels, seven steps should
be performed: 1) obtain the required energy data; 2) estimate the total carbon content of the fuels;
3) estimate the total carbon stored in products; 4) estimate the carbon potentially emitted from
bunker fuel consumption; 5) estimate the carbon emitted from interstate electricity consumption; 6)
calculate net potential carbon emissions; 7) estimate the carbon actually oxidized from energy uses;
and, 8) convert net carbon emissions from energy consumption to total CO2 emissions. These seven
steps are outlined in detail below. A worksheet has been provided in Table 1-1 to assist in the
calculations. A more detailed description of the method used to calculate carbon dioxide emissions
is provided in Discussion Section 1.
Step (1) Obtain Required Energy Data (Table 1-1, Column A)
• Required Energy Data. The information needed to perform these calculations is annual state
energy consumption data based on fuel type (e.g., gasoline, residual oil, bituminous coal, lignite,
natural gas, etc.) by sector (i.e., residential, commercial, industrial, transportation, and electric
utility). A list of suggested sector/fuel categories is provided in Table 1-1. Additionally, further
disaggregation may be done (i.e., by individual industries within the industrial sector or by specific
fuel types not listed) if the appropriate data are available.
• Data Sources. In-state sources, such as state energy commissions or public utility commissions,
should be consulted first. Alternatively, state energy data by fuel type and sector for fossil fuels
can be found in the U.S. Department of Energy (U.S. DOE), Energy Information
Administration's (EIA) State Energy Data Report and Coal Production. For users attempting to
disaggregate the data further (e.g., by specific end user, such as chemical manufacturers), there
is currently no nationally published source providing this type of information. An appropriate
source would need to be obtained at the state level to obtain these data.
• Units for Reporting Data. Fossil fuel statistics should also be provided on an energy basis (i.e.,
million Btu). Wood data should be reported in pounds, while ethanol should be reported on an
energy basis. If fuel data are reported in other units and documented conversion factors cannot
be obtained within the state, the conversion factors listed in Table 1-2 may be applied in order
to convert to million Btu.
Example According to the EIA State Energy Data Report 1992, total U.S. energy
consumption of distillate fuel for the transportation sector in 1990 was 658
million barrels, which is equivalent to approximately 3.83 x 1015 Btu, or
3,832,850,000 million Btu as shown in the following calculation:
658,000,000 barrels X 5.825 million Btu/barrel = 3,832,850,000 million Btu
1-1
-------
Table 1-1. Worksheet to Calculate CO2 Emissions from Fossil & Biomass Fuels
Input Input (A) x (B) * 2000 Input Input (C) - (D) - (K) (!•') x (G) x 44112
Fraction
Oxidized
(A) (B) (C) (D) (K) (F) («) (II)
Carbon Content Total Stored International Net Total C CO,
Consumption Coefficient Carbon Carbon Bunkers Carbon Oxidized Emissions
Sector/Fuel (10* Btu) (Ibs C/10* Btu) (tons C) (tons C) (tons C) (tons C) (tons C) (tons CO,|
RESIDENTIAL
Asphalt and Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel: Kerosene Type
Jet Fuel: Naphtha Type
Kerosene
LPG
Lubricants
Misc. Petroleum Products
Motor Gasoline
Naphtha (<104°F)
Other Oil (>104°F)
Pentane Plus
Petroleum Coke
Residual Fuel Oil
Still Gas
Waxes
Anthracite Coal
Bituminous Coal
Sub-bituminous Coal
Lignite Coal
Coke
Natural Gas
Wood
Elhanol
Residential Total
-
1-2
-------
Table 1-1. Worksheet to Calculate CO2 Emissions from Fossil & Biomass Fuels
Input Input (A)x(B)+2000 Input Input (C) - (D) • (E) (F) x (G) x 44112
Fraction
Oxidized
(Al (B) (C) (D) (E) (F) (G) (II)
Carbon Content Total Stored International Net Total C CO,
Consumption Coefficient Carbon Carbon Bunkers Carbon Oxidized Emissions
Sector/Fuel (10* Btu) (Ibs C/10* Btu) (tons C) (tons C) (tons C) (tons C) (tons C) (tons CO,)
COMMERCIAL
Asphalt and Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel: Kerosene Type
Jet Fuel: Naphtha Type
Kerosene
LPG
Lubricants
Misc. Petroleum Products
Motor Gasoline
Naphtha (<104°F)
Other Oil (>104°F)
Pentane Plus
Petroleum Coke
ResidualFuel Oil
Still Gas
Waxes
Anthracite Coal
Bituminous Coal
Sub-bituminous Coal
Lignite Coal
Coke
Natural Gas
Wood
Ethanol
f'"nnmercial Total
'
-------
Table 1-1. Worksheet to Calculate CO2 Emissions from Fossil & Biomass Fuels
Input Input (A) x (B) + 2000 Input Input (C) - (D) - (E) (!•') x (G) x 44/12
traction
Oxidized
(A) (B) (C) (D) N (E) (V) (G) (II)
Carbon Content Total Stored International Net Total C CO2
Consumption Coefficient . Carbon Carbon Bunkers Carbon Oxidized Emissions
Sector/Fuel (10* Btu) (Ibs C/10* Btu) (tons C) (tons C) (tons C) (tons C) (tons C) (tons CO.)
INDUSTRIAL
Asphalt and Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel: Kerosene Type
Jet Fuel: Naphtha Type
Kerosene
LPG
Lubricants
Misc. Petroleum Products
Motor Gasoline
Naphtha (<104°F)
Other Oil (>104°F)
Pentane Plus
Petroleum Coke
Residual Fuel Oil
Still Gas
Waxes
Anthracite Coal
Bituminous Coal
Sub-bituminous Coal
Lignite Coal
Coke
Natural Gas
Wood
Ethanol
Industrial Total
-
v
1-4
-------
Table 1-1. Worksheet to Calculate CO2 Emissions from Fossil & Biomass Fuels
Input Input (A) x (B) + 2000 - Input Input (C) - (O) - (E) (F) x (G)x44H2
Fraction
Oxidized
(A) (B) (C) 104QF)
Pentane Plus
Petroleum Coke
Residual Fuel Oil
Still Gas
Waxes
Anthracite Coal
. Bituminous Coal
Sub-bituminous Coal
Lignite Coal
Coke
Natural Gas
Wood
Ethanol
/ "*~ oisportation Total
•v'
,
-------
cf tnissk
Table 1-1. Worksheet to Calculate 0 missions from Fossil & Biomass Fuels
Input Input (A)x(B) + 2000 Input Input (C) - (D) - (E) (F) x (G) x 44/12
Fraction
\ ' Oxidized
(A) (B) (C) (D) (E) , 104QF)
Pentane Plus
Petroleum Coke
Residual Fuel Oil
Still Gas
Waxes
Anthracite Coal
Bituminous Coal
Sub-bituminous Coal
Lignite Coal
Coke
Natural Gas
Wood
Ethanol
Utilities Total
- -•. •
-
1-6
-------
Table 1-2. Conversion Factors to Million Btu.a
Fuel Type
If data is in
Multiply by
Petroleum
Asphalt and Road Oil barrels
Aviation Gasoline barrels
Distillate Fuel Oil . barrels
Jet Fuel: Kerosene Type barrels
Jet Fuel: Naphtha Type barrels
Kerosene , barrels
Liquified Petroleum Gases barrels
Lubricants barrels
Miscellaneous Petroleum Products and Crude Oil barrels
Motor Gasoline barrels
Naphtha (< 104°F)b and Special Naphthas barrels
Other Oil (> 104°F)b and barrels
6.636
5.048
5.825
5.670
5.355
5.670
4.011
6.065
5.800
5.253
5.248
5.825
Unfinished Oils
Pentane Plus
Petroleum Coke
Residual Fuel Oil
Still Gasb
Waxes
Coaf
Anthracite6
Bituminous
Sub-bituminous
Lignite
Coal Coke
barrels-
barrels
barrels
barrels
barrels
short tons
short tons
short tons
short tons
short tons
. 4.620
6.024
6.287
6.000
5.537
— *
21.668 1
23.89
17.14
12.866
24.800
Natural Gas
billion cubic feet
Teracalories
1.03 x 10"
3968
Biofuels
Woodd
Ethanol
Btu
gallons
0.116xl03 (Ibs/Btu)
0.764
Interstate Electricity Consumption^
kilowatthours
10,000 (Btu/kWh)
a. Heat contents of many fuels vary somewhat by source, year, and consumer. Except for coal, biomass, and blended petroleum products,
this variation tends to be relatively small. The values here are national averages for 1990.
b. By EIA definition naphtha (<104°F), other oil (>104°F), and still gas are collectively termed petrochemical feedstocks.
c. Thermal conversion factors for coal can vary extensively by source. More complete state and sector specific factors are available through
U.S. DOE/EIA.
d. The energy content of wood varies with moisture content and type of wood. The conversion factor given is a nationally averaged value
based on dry mass of hardwood. Since wood consumption figures should be in pounds, the factor should be used to convert consumption
from Btu to pounds.
e. The anthracite factor presented here is a national average. Actual anthracite factors could range from as low as 17.5 MMBtu/ton for
anthracite reclaimed from refuse piles to 26 MMBtu/ton or higher for anthracite mined directly from the original seam.
t". This is a national average heat rate based on EIA data (EIA, 1994e) and should only be used for interstate electricity consumption for
which the specific heat rate of the source is unknown.,
Source: Petroleum, natural gas, and wood heat-equivalents are from ElA's Annual Energy Review 1993. Coal heat-equivalents are from EIA's
State Energy Data Report 1992, Cost and Quality of Fuels for Electric Utility Plants, and Quarterly Coal Report. Ethanol heat-equivalents are from
EIA's Estimates of U.S. Biomass Consumption 1992.
1-7
-------
Step (2) Estimate Total Carbon Content in Fuels (Table 1-1, Columns B and C)
• Carbon content represents the total amount of carbon that could be emitted if 100 percent was
released to the atmosphere. To estimate the total carbon that could be released from the fuels,
multiply energy consumption for each fuel type by the appropriate carbon content coefficient.
This calculation should be done for all fuel types in each sector. To estimate carbon content of
wood, the carbon coefficient is replaced by the fraction of carbon in biomass. Table 1-3 presents
default carbon content coefficients, including a national carbon content coefficient for ethanol
as well as a default value for the percent of carbon in wood. State-specific data should be used
in place of these values when they are available and well documented. Multiplying fuel
consumption by these coefficients yields potential emissions in pounds of carbon. The equations
will take the following form:
Tq = q x ccq
where: TCj = Total carbon contained in fuel i (Ibs C);
Cj = Fuel consumption for fuel i (106 Btu); and
CCCj = Carbon content coefficient for fuel i (Ibs C/106 Btu).
• For each fuel type, divide the results by 2000 Ibs/ton to obtain tons of carbon.
• For each sector, sum the results of the fuel types to obtain the total carbon content in tons. The
figures for carbon from biomass consumption should not be included in total emissions (see
Discussion Section 1 for an explanation).
Example To calculate the total carbon content for distillate fuel in the U.S. transportation
sector for the year 1990, obtain the result from Step 1 (3,832,850,000 million Btu
.of distillate fuel) and perform the following calculations:
(a) 3,832,850,000 million Btu x 44.0 Ibs C/106 Btu = 168,645,400,000 Ibs C
(b) 168,645,400,000 Ibs C + 2000'lbs/ton = 84,322,700 tons C
Step (3): Estimate Carbon Stored in Products (Table 1-1, Column D)
• Estimate the quantity of each fuel type that is consumed in non-fuel uses. In-state sources, such
as state energy commissions or public utility commissions, should be consulted first. Otherwise.
rough national estimates can be found in U.S. DOE/EIA Annual Energy Review and the
assumption can be made that the fraction of a fuel used in non-fuel uses at the state level is
roughly equivalent to the fraction used at the national level.
• Calculate the carbon content of fuels consumed in non-fuel uses by multiplying the non-fuel use
quantities by their respective carbon coefficients in Table 1-3.
• Estimate the fraction of carbon in each fuel which is stored for a long period of time (i.e., 20
years or more). National default values are given in Table 1-4, but state level fractions may differ
depending on the type of non-fuel uses present. The values in Table 1-4 should be used only as
1-8
-------
a last resort and with careful consideration given to their defining assumptions (see Discussion
Section 1). State-specific estimates should be used whenever possible and presented with
adequate supporting documentation.
Calculate the carbon stored by multiplying the carbon content of non-fuel uses by the fraction
sequestered. •
Enter the resulting values in Column D of Table 1-1. These values are eventually subtracted
from total carbon potentially emitted (Table 1-1, Column C).
Example To calculate carbon stored by non-fuel use of LPG at the national level in
1990, obtain the quantity consumed from Table 1.15 of Annual Energy Review
1993 and perform the following calculations:
. (a) 1,280,000,000 million Btu x 37.8 Ibs C/106 Btu = 48,384,000,000 Ibs C
(b) 48,384,000,000 Ibs C •+ 2000 Ibs/ton = 24,192,000 tons C
(c) 24,192,000 tons C x 0.80 = 19,353,600 tons C stored
Step (4): Estimate Carbon from Bunker Fuel Consumption (Table 1-1, Column E)
• International bunker fuels and domestic bunker fuels are fuels used in international and interstate
transportation respectively (see Discussion Section 1 for a more detailed description of these
categories). Emissions from domestic bunkers are not addressed in state emission inventories due
to difficulties in obtaining the necessary data. Emissions from international bunkers are
calculated, but should not be included in a state's total emissions figures. This omission of
bunker fuel consumed internationally is consistent with international greenhouse gas reporting
guidelines developed by the IPCC (1994).
• International bunker fuel emissions are calculated in the same manner as other emissions from
fossil fuel combustion. Once consumption of international bunker fuels are determined, they are
multiplied by their appropriate carbon content coefficients (see Table Dl-3). This results in the
amount of carbon potentially emitted by combustion of these fuels, or total carbon contained in
the fuels, as shown in the equation below:
Tq = q x ccq
where: TC; = Total Carbon contained in bunker fuel i (pounds);
Cj — Consumption of bunker fuel i (million Btu); and
CCCj = Carbon Content Coefficient for bunker fuel i (Ibs C / million Btu)
• The total carbon contained in each bunker fuel should be entered in Column E of Table 1-1.
These values should be subtracted from total carbon (Column C of Table 1-1) only if
international bunkers have been captured in the total carbon figures. If the carbon values in
Column C do not include international bunker fuels, then the values in Column E should not be
deducted.
1-9
-------
Example At the national level, distillate fuel oil used for international bunkers is
obtained from U.S. DOE/EIA International Energy Annual. The 1990 figure for
the U.S. and its territories is 19,345,000 barrels. The following calculations
are performed to compute carbon in distillate fuel used for international
bunkers:
(a) 19,345,000 barrels X 5.825 million Btu/barrel = 112,685,000 million Btu
(b) 112,685,000 million Btu X 44.0 Ibs C/million Btu = 4,958,140,000 Ibs C
(c) 4,958,140,000 Ibs C + 2000 Ibs/ton = 2,479,070 tons C
Step (5): Estimate Carbon Emitted from Interstate Electricity Consumption (Reported Separately)
• Electricity derived from fossil fuels is often consumed across state boundaries (i.e., fuel can be
consumed in one state to generate electricity which is consumed in another state). To obtain a
complete accounting of emissions from fossil fuel consumption, emissions from this interstate flux
of energy should be estimated. The first step in calculating these emissions is to estimatenhe
quantity of electricity imported to and exported from a state (i.e., the amount of fuel consumed
in-state to produce energy which is used out of state and vice versa). Energy consumption data
should be reported in million Btu (see Table 1-2 for conversion from physical units and
kilowatthours).
• Determine the source of interstate electricity (e.g., electricity generated at coal fired plants,
natural gas plants, etc.). Source identification is necessary in order to derive accurate heat rates
and proper carbon content coefficients for interstate electricity consumption.
• After interstate electricity sources have been identified and data obtained in the appropriate
units, then the carbon content of the energy can be determined. Carbon contents are directly
related to the type of fuel associated with each energy source. Once the fuel type for each
source has been identified, the carbon content coefficients in Table 1-3 can be applied to fuel
quantities in order to estimate the carbon content of interstate energy consumption.
• The following equation summarizes the steps outlined above:
El; = Impj x HRj x CCq
EEj = Expj x HRj CCCj
where: El = Emissions of carbon due to imports from source i (Ibs carbon);
EE = Emissions of carbon due to exports from source j (Ibs carbon);
Imp = Electricity imported from source i (kwh);
Exp = Electricity exported from source j (kwh);
HR = Heat Rates of generating facilities (Btu/kwh); and
CCC = Carbon Content Coefficients for source fuels (Ibs carbon /Btu).
1-10
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Table 1-3: Carbon Content Coefficients for Fuel Combustion3
(Ibs C/106 Btu)
Fuel Consumed Carbon Coefficient
Asphalt and Road Oil 45.5
Aviation Gas : 41.6
Distillate Fuel Oil 44.0
Jet Fuel (all kinds) 43.5
Kerosene 43.5
LPG 37.8
Lubricants 44.6
Motor Gasoline 42.8
Residual Fuel Oil 47.4
Misc. Petroleum Products and Crude Oil 44.7
Naphtha (<104°F) 40.0
Other Oil (>104°F) . 44.0
Pentanes Plus 40.2
Petrochemical Feed 42.7
Petroleum Coke 61.4
Still Gas 38.6
Special Naphtha 43.8
Unfinished Oils • 44.6
Waxes 43.7
Anthracite Coal 62.1
Bituminous Coal 56.0
Sub-bituminous Coal 57.9
Lignite Coal * 58.7
Natural Gas 31.9
Woodb 0.475
Ethanol 41.8
Except as noted all coefficients are given as pounds of carbon emitted per million Btu of fuel consumed (Ibs C/10"
Btu). When multiplied by consumption in 106 Btu, or pounds for wood, they result in emissions of carbon in
pounds (Ibs C).
a. Content coefficients are sometimes called carbon content coefficients or carbon coefficients.
b. The wood coefficient is a percent of total carbon in biomass (%C).
Sources: Natural gas and petroleum coefficients are from U.S. EPA's Inventory of U.S. Greenhouse Gas Emissions
and Sinks: 1990-1993. Coal coefficients are full combustion figures based on EIA's Emissions of Greenhouse Gases
in the United States: 1985-1990. The wood carbon fraction is from the IPCC Guidelines for National Greenhouse
Gas Inventories. The ethanol coefficient is from OTA's Changing by Degrees.
1-11
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Table 1-4: Percent of Carbon Sequestered by Non-fuel Uses3
Fuel Type
Fraction Stored
Coal Oils and Tars from coke production
. Natural Gas as a chemical feedstock
Asphalt and Road Oil
LPG
Lubricants
Petrochemical Feedstocks'3
Waxes and Miscellaneous Products0
0.75
1.00
1.00
0.80
0.50
0.80
1.00
a. Before using these fractions, see Discussion 1 for assumptions on which they
are based.
b. By EIA definition, "Petrochemical Feedstocks" include naphtha (< 104°F), other oil
(<104°F), and still gas.
c. By EIA definition, "Waxes and Miscellaneous Products" includes waxes, Misc.
petroleum products, residual fuel oil and distillate fuel oil.
Sources: Figures for coal oil and tars, asphalt and road oil, LPG, and lubricants are
from Marland and Rotty (1984). The Figure for natural gas is from communication
with EIA (Rypinski, 1994). Petrochemical feedstocks and waxes and miscellaneous
products are from U.S. EPA (1994).
Emissions from interstate electricity consumption are then summed over all fuel types, and
exported electricity emissions are subtracted from imported electricity emissions.
NE = £ EIj - £ EEj
where: NE = Net Emissions from interstate electricity consumption (Ibs carbon);
El = Emissions of carbon due to imports from source i (Ibs carbon); and
EE = Emissions of carbon due to exports from source j (Ibs carbon);
Report the resulting values separately from other emissions from fossil fuel consumption for
energy. These values should not be used to adjust state emission totals. A negative number for
net emissions indicates a net export of carbon from interstate electricity, while a positive number
indicates a net import of carbon from interstate electricity. If these emissions were distributed
across end-use consumers, a net import would result in an increase in state emission totals,
because it represents additional consumption attributable to end-users within the state. A net
export would result in a decrease in state totals, because it represents fuel consumed in a state
to produce energy used by out-of-state consumers.
Step (6): Calculate Net Potential Carbon Emissions (Table 1-1, Column F)
• Subtract the carbon stored (Table 1-1, Column D) and, if necessary, the carbon emitted from
bunker fuel consumption (Table 1-1, Column E) from the total carbon (Table 1-1, Column C).
• The resulting value is "net carbon content" and should be entered in Column F of Table 1-1.
1-12
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Example At the national leyel the carbon content of LPG consumed in the U.S. is
approximately 30,400,000 tons carbon, the amount sequestered in non-fuel
uses is about 19,400,000 tons carbon, and there is no consumption of LPG
for international bunkers. To calculate the net carbon content of LPG
combusted in the industrial sector perform the following calculation:
(a) 30,400,000 ton C - 19,400,000 ton C stored - 0 ton C bunkers = 11,000,000 ton C
Step (7): Estimate Carbon Oxidized from Energy Uses (Table 1-1, Column G)
• Multiply the net carbon content for each fuel and sector by the fraction of carbon oxidized to
obtain the total amount of carbon oxidized to carbon dioxide from the combustion of the fuel.
The fraction of carbon oxidized is 0.99 for solid and liquid fuels, 0.995 for natural gas, and 0.90
for wood. This calculation will take the following form:
Net Carbon Content (tons) X Fraction Oxidized = Total Oxidized Carbon (tons C)
• Sum the results to obtain the total amount of carbon oxidized from all fuel types. The figures
for carbon from biomass consumption should not be included in total emissions (see Discussion
Section 1 for an explanation).
Example To calculate the total amount of Carbon Oxidized from the combustion of
LPG in the U.S. industrial sector perform the following calculation, where the
net carbon content of industrial LPG is about 11,000,000 ton C:
(a) 11,000,000 tons C X 0.99 = 10,890,000 tons C
Step (8): Convert to Total CO2 Emissions from Energy Consumption (Table 1-1, Column H)
• Multiply Total Carbon Oxidized for each fuel and sector by the molecular weight ratio of CO2
to C (44/12) to obtain Total CO2 Emissions.
^
• Sum across each fuel and each sector to find total state emissions of CO2 from energy
consumption. The figures for carbon from biomass consumption should not be included in total
emissions (see Discussion Section 1 for an explanation).
Example To convert the amount of carbon emitted due to LPG consumption
(10,890,000 tons C) to the amount of CO2 emitted, perform the following
calculation.
(a) 10,890,000 tons C X 44 * 12 = 39,930,000 tons CO2
1-13
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WORKBOOK 2
GREENHOUSE GAS EMISSIONS FROM
PRODUCTION PROCESSES
Emissions are often produced as a by-product of various non-energy related activities. That
is, these emissions are produced directly from the process itself and are not a result of energy
consumed during the process. For example, in the industrial sector raw materials are chemically
transformed from one state to another. This transformation often results in the release of
greenhouse gases such as carbon dioxide, nitrous oxide, hydrofluorocaibons, and perfluorinated
carbons. The production processes addressed in this section include: cement production, nitric acid
production, adipic acid production, lime production, limestone use (e.g., for iron and steel making,
flue gas desulfurization, and glass manufacturing), soda ash production and use, carbon dioxide
manufacture, aluminum production, and HCFC-22 production.
Greenhouse gases are emitted from a number of industrial processes not covered in this
section. For example, ammonia production is believed to be an industrial source of methane, nitrous
oxide, and NMVOC emissions. However, emissions for these sources have not been estimated at this
time due to a lack of information on the emission processes, the manufacturing data, or both. As
more information becomes available, emission estimates for these processes wilj be calculated and
included in future greenhouse gas emission inventories.
The emission methodologies presented here generally follow the IPCC-recommended
guidelines, although the only processes for which the IPCC provides a specific methodology for
estimating emissions are cement, adipic acid, and nitric acid production. The IPCC has not provided
specific details (e.g., default emission factors) to calculate emissions from the other sources, but
recommends a basic approach that can be followed for each source category, i.e., multiplying
production data for each process by an emission factor per unit of production. The methods provided
to estimate emissions in this section generally follow this basic approach. Most of the emission
factors provided below were taken from U.S. EPA (1994), in which they were derived using
calculations that assume precise, efficient chemical reactions. As a result, uncertainties in the
emission coefficients can be attributed to impurities contained in the raw materials or to inefficiencies
in the chemical reactions associated with each production process. Additional sources of uncertainty
specific to an individual source category are discussed in Part II of this document.
2.1 CO2 FROM CEMENT PRODUCTION
Step (1) Obtain Required Data
• Required Data. The information needed to calculate CO2 emissions from cement production
is annual clinker production and annual masonry cement production in short tons in the state.
• Data Source. In-state sources should be consulted first. Additionally, cement production by
state can be found in the Cement: Annual Report, published by the U.S. Bureau of Mines.
• Units for Reporting Data. Annual production of clinker and portland and masonry cement
2-1
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should be supplied in short tons.
Example . According to the Bureau of Mines Cement Annual Report: 1990 (Bureau of
Mines I992a), total U.S. clinker production in 1990 was 70,939,000 short tons,
and total masonry cement production was 3,208,000 short tons.
Step (2) Estimate CO2 Emissions from Clinker Production
• Multiply clinker production by an emissions factor of 0.507 tons CO2/ ton of clinker produced
to yield total CO2 emissions from clinker production.
Total CO2 Emissions (tons) = Total Clinker Production (tons) x 0.507 (tons
CO2/ton of clinker produced)
Example To calculate Total CO2 Emissions from U.S. clinker production in 1990:
70,939,000 tons x 0.507 tons COg/ton cement = 35,966,073 tons CO2
Step (3) Estimate CO2 Emissions from Masonry Cement
• Multiply masonry cement production by an emissions factor of 0.0224 tons of CO2/ ton of
masonry cement produced
Total CO2 Emissions (tons) = Total Masonry Cement Production (tons) x
0.0224 (tons CO2/ton of masonry cement produced)
Example To calculate Total CO2 Emissions from masonry cement production in 1990:
3,208,000 tons x 0.0224 tons COg/ton masonry cement = 71,859 tons CO2
Step (4) Sum the Results of Steps (1) and (2)
Total CO2 emissions from cement production are the sum of the results obtained through
Steps (1) and (2).
Example To calculate Total CO2 Emissions from cement production in 1990,
35,966,073 tons CO2 (clinker) + 71,859 tons CO2 (masonry cement) = 36,037,932 tons CO2
2-2
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2.2 N2O FROM NITRIC ACID PRODUCTION
Step (1) Obtain Required Data
• Required Data. The only information needed to calculate N2O emissions from nitric acid
production is annual nitric acid production in short tons in the state.
• . Data Source. In-state sources should be consulted first. Additionally, nitric acid production
can be found in Chemical and Engineering News (C&EN; published by the American
Chemical Society, Washington, D.C.).
• Units for Reporting Data. Annual production of nitric acid should be supplied in short tons.
Example According to C&EN (1994), total U.S. nitric acid production in 1990 was
approximately 8 million short tons.
Step (2) Estimate N2O Emissions from Nitric Acid Production
• Multiply nitric acid production by an emissions factor of 0.0055 tons N2O/ton of nitric acid
produced to yield total N2O emissions from nitric acid production.
Total N2O Emissions (tons) = Total Nitric Acid Production (tons) x 0.0055 (tons N2O/ton
of nitric acid produced).
Example To calculate Total N20 Emissions from U.S. nitric acid production in 1990,
8 million tons x 0.0055 tons CO2/Jbs nitric acid = 44,000 tons N2O
2.3 N2O FROM ADIPIC ACID PRODUCTION '
Step (1) Obtain Required Data
• Required Data. The information needed to calculate N2O emissions from adipic acid
production is annual adipic acid production in short tons and the pollution control equipment
used at production facilities in the state.
• Data Source. In-state sources should be consulted first. Additionally, adipic acid production
can be found in Chemical and Engineering News.
i
• Units for Reporting Data. Annual production of adipic acid should be supplied in short tons.
Example According to C&EN (1993), total U.S. adipic acid production in 1990 was
approximately 810,000 short tons.
2-3
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Step (2) Estimate N2O Emissions from Adipic Acid Production
• Multiply adipic acid production by an emissions factor of 0.3 tons N2O/ton of adipic acid
produced to yield total N2O emissions from adipic acid production. Subtract the amount of
N2O that is not released as a result of pollution control equipment.
Total N2O Emissions (tons) = Total Adipic Acid Production (tons) x 0.3 (tons N2O/ton
of adipic acid produced) - Amount N2O not Released as a Result of Pollution Control
Equipment.
v
Example To calculate Total N2O Emissions from U.S. adipic acid production in 1990,1
810,000 tons x 0.3 tons N2O/tons adipic acid -181,057 tons N2O = 61,943 tons N2O
Due to existing levels of pollution control, 181,057 tons of N2Q were kept from being released to the
atmosphere.
2.4 CO2 FROM LIME MANUFACTURE
Step (1) Obtain Required Data
Required Data. The information needed to calculate CO2 emissions from lime manufacture
is annual lime production in short tons and the amount of CO2 recovered during
manufacturing and used for other purposes in the state.
Data Source. In-state sources should be consulted first. Additionally, lime production by
state can be found in Lime Annual Report (Bureau of Mines, Washington, D.C.)
Units for Reporting Data. Annual production of lime should be supplied in short tons.
Example According to the Bureau of Mines (1992b), total U.S. lime production in 1990
was approximately 17,481 thousand short tons and 573 thousand tons of
CO2 were recovered and used in sugar refining and precipitated calcium
carbonate production.
Step (2) Estimate CO2 Emissions from Lime Manufacture
• Multiply lime production by an emissions factor of 0.785 tons CO2/ton of lime produced to
yield total CO2 emissions from lime manufacture. If any CO2 is recovered and used for other
purposes, subtract this amount from the total.
Total CO2 Emissions (tons) = Total Lime Production (tons) x 0.785 (tons CO2/ton of lime
produced) - Amount CO2 Recovered (tons).
2-4
-------
Example To calculate Total CO2 Emissions from U.S. lime production in 1990,
[17,481,000 tons x 0.785 tons COg/tons lime} - 573,000 tons CO21 = 13,150,000 tons CO2
Some of the CO2 generated during the production process, however, is recovered for use in sugar refining and
precipitated calcium carbonate (PCC) production. Lime production by these producers was 911 thousand short tons,
generating 716.5 thousand short tons of carbon dioxide. Approximately 80 percent of this CO2 is recovered and not
emitted.
2.5 CO2 FROM LIMESTONE USE
Step (1) Obtain Required Data
• Required Data. The data required for use in this method is the amount of limestone
consumed in each state by type: (1) limestone (calcite), and (2) dolomite.
• Data Source. In-state sources should be consulted first. Additionally, lime production by
state can be found in Crushed Stone: Annual Report (Bureau of Mines, Washington, D.C.).
• Units for Reporting Data. Annual consumption of limestone and dolomite should be supplied
in short tons.
Example . According to the Bureau of Mines (1993b), total U.S. limestone use in 1990 was
approximately 12,606,000 short tons: 11,582,000 short tons limestone (calcite)
and 1,024,000 short tons dolomite.
Step (2) Estimate CO2 Emissions from Limestone Use
• Depending on the type of limestone used, multiply the amount of limestone consumed by the
appropriate emissions factor: (1) 0.12 for limestone (calcite) and (2) 0.13 for dolomite. This
will provide the amount of carbon emitted from the use of limestone. Next, this number will
be multiplied by 44/12 to obtain the amount of carbon dioxide actually emitted.
a) Limestone (Calcite)
Total CO2 Emissions (tons) = Limestone Used (tons) x 0.12 tons C/ton Limestone (Calcite)
x 44/12 CO2/C.
b) Dolomite
Total CO2 Emissions (tons) = Limestone Used (tons) x 0.13 tons C/ton Dolomite x 44/12
CO2/C.
2-5
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Example To calculate Total. CO2 Emissions from lime consumption in 1990,
Calcite
[11,582,000 tons x 0.12 tons C/ton limestone (calcite)] x 44/12CO2/C
= 5,096,080 tons CO2
Dolomite
[1,024,000 tons x 0.13 tons C/ton limestone (dolomite)] x 44/12 CO2/C
= 488,100 tons CO2
Step (3) Sum the Results of Steps 2a and 2b to Obtain Total Emissions
Total CO2 Emissions from Limestone Use = Total CO2 from Limestone (Calcite) (tons CO2)
+ Total CO2 from Dolomite (tons CO2).
Example To calculate Total CO2 Emissions from limestone use in 1990,
5,096,080 tons CO2 limestone (calcite) + 488,100 tons CO2 (dolomite) = 5,584,180 tons CO2
2.6 CO2 FROM SODA ASH MANUFACTURE AND CONSUMPTION
Step (1) Obtain Required Data
• Required Data. The data required for use in this method is the amount of trona (the
principal ore from which natural soda ash is made) produced and the amount of finished soda
ash consumed in short tons in each state.
• Data Source. In-state sources should be consulted first. Additionally, trona production and
soda ash consumption by state can be found in Soda Ash: Annual Report (Bureau of Mines,
Washington, D.C.) and Current Industrial Reports (Bureau of Census, U.S. Department of
Commerce, Washington, D.C.).
• Units for Reporting Data. Annual production of trona and consumption of soda ash should
be supplied in short tons.
Example According to the Bureau of Mines (1993c), total U.S. trona production in 1990
was approximately 16,241,200 short tons, while soda ash consumption was
7,194,700 short tons.
Step (2) Estimate CO2 Emissions Soda Ash Manufacture
• Multiply the amount of trona produced by the emissions factor 0.0974 tons CO2/ton trona:
2-6
-------
Total CO2 Emissions (tons) = Trona Produced (tons) x 0.0974 tons CO2/ton Trona.
Example To calculate Total CO2 Emissions from trona production in 1990,
16,241,200 tons x 0.0974 tons COg/ton trona = 1,581,893 tons CO2
Step (3) Estimate CO2 from Soda Ash Consumption
• Multiply the amount of soda ash consumed by the emissions factor 0.415 tons CO2/ton soda
ash consumed.
Total CO2 Emissions (tons) = Soda Ash Consumed (tons) x 0.415 tons CO2/ton Soda Ash.
Example To calculate Total CO2 Emissions from soda ash consumption in 1990,
7,194,700 tons x 0.415 tons COg/ton soda ash = 2,985,800 tons CO2
Step (4) Sum the Results of Steps 3 and 4 to Obtain Total Emissions
Total CO2 Emissions from Soda Ash Manufacture and Use = Total CO2 from Trona
Production (tons CO2) + Total CO2 from Soda Ash Consumption (tons CO2).
Example To calculate Total CO2 Emissions from soda ash manufacture and consumption
in 1990,
1,581,893 tons CO2 (manufacture) + 2,985,800 tons C02 (consumption)
= 4,567,693 tons CO2
2.7 CO2 EMISSIONS FROM CARBON DIOXIDE MANUFACTURE
Step (1) Obtain Required Data
• Required Data. The data required for use in this method is the amount of carbon dioxide
produced that is not accounted for in other emission sources (e.g., combustion or non-fuel
use).
• Data Source. In-state sources should be consulted first. Additionally, carbon dioxide
manufacture by state can be found in Business Research Report B286: Carbon Dioxide
(Freedonia Group, Inc., Cleveland, Ohio).
• Units for Reporting Data. Annual production of carbon dioxide should be supplied in short
tons.
2-7
-------
Example According to The.Freedonia Group (1991), total U.S. carbon dioxide
manufacture in 1990 for already unaccounted for uses (i.e., enhanced oil
recovery) was approximately 1,322,760 short tons.
Step (2) Estimate CO2 Emissions Carbon Dioxide Manufacture
• Multiply the amount of carbon dioxide consumed by the emissions factor 1 ton CO2/ton CO2.
Total CO2 Emissions (tons) = Carbon Dioxide Consumed (tons) x 1 tons CO2/ton CO2
consumed.
Example To calculate Total CO2 Emissions from carbon dioxide manufactured in 1990,
1,322,760 tons CO2 manufactured x 1 ton CO^ton CO2 manufactured = 1,322,760 tons CO2
2.8 PFC - CF4 AND C2F6 — EMISSIONS FROM ALUMINUM PRODUCTION
Step (1) Obtain Required Data
• Required Data. The data required for use in this method is the amount of aluminum produced
in a state in short tons.
• Data Source. In-state sources should be consulted first. Additionally, aluminum production
by state can be found in Aluminum, Bauxite, and Alumina: Annual Report (Bureau of Mines,
Washington, D.C.) and Current Industrial Reports (Bureau of Census, U.S. Department of
Commerce, Washington, D.C.).
• Units for Reporting Data. Annual production of carbon dioxide should be supplied in short
tons.
Example According to the Bureau of Mines (1993a), total U.S. aluminum production in
1990 was approximately 4,462,000 short tons.
Step (2) Estimate PFC - CF4 and C2F6 — Emissions from Aluminum Production
• Multiply the amount of aluminum produced by the appropriate emissions factor: 0.0006
(range of 0.0003 to 0.0009) tons CF4/ton aluminum produced and 0.00006 (range of 0.00003
to 0.00009) ton C^Fg/ton aluminum produced.
Total PFC Emissions (tons) = [Aluminum Produced (tons) x 0.0006 tons CF4/ton aluminum
produced] + [[Aluminum Produced (tons) x 0.00006 tons C^g/ton aluminum produced]
2-8
-------
Example To calculate Total PFC Emissions from aluminum production in 1990,
[4,462,000 tons x 0.0006 tons CF4/ton aluminum produced] + [4,462,000 tons x 0.00006
tons C2F6/ton aluminum produced] = 2,945 tons CO2
2.9 EMISSIONS OF HFC-23
The only HFC known to be emitted in significant quantities as a by-product from chemical
production processes is HFC-23. HFC-23 is emitted as a by-product of HCFC-22 production.
Step (1) Obtain Required Data
• Required Data. The data required for use in this method is the amount of HCFC-22 produced
in a state.
• Data Source. In-state manufacturers of HCFC-22 should be consulted first. Additionally the
Chemical Manufacturers Association (Washington, D.C.), Alliance for Responsible CFC
Policy (Arlington, VA), and Grant Thorton Consulting (Washington, D.C.) can be contacted
for information on state-by-state production numbers.
• Units for Reporting Data. Annual production of HCFC-22 should be supplied in short tons.
Step (2) Estimate HFC-23 Emissions from HCFC-22 Production
• Multiply the amount of HCFC-22 produced by the appropriate emissions factor: 0.04 tons
HFC-23/ton HCFC-22 produced (or 4% of total HCFC-22 production).
HCFC-22 Produced (tons) x 0.04 tons HFC-23/ton HCFC-22 produced
= Total HFC-23 Emissions (tons)
Example To calculate Total HFC Emissions from HCFC-22 production for a state,
4,000,000 tons HCFC-22 x 0.04 tons HFC/ton HCFC-22 produced
= 160,000 tons HFC-23
2-9
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WORKBOOK 3
METHANE EMISSIONS FROM
NATURAL GAS AND OIL SYSTEMS
Emissions from natural gas and oil systems are primarily methane, although smaller quantities of
non-methane VOCs, carbon dioxide, and carbon monoxide can be emitted. Methane emissions occur
throughout the total fuel cycles of oil and natural gas. From the natural gas systems, methane emissions
occur during field production, processing, refining, storage and injection, transmission, distribution, and
from engine exhaust. From the production and refining of petroleum liquids, methane emissions occur
during field production, storage, refining, marine vessel operations, and from venting and flaring of gas.
To estimate these emissions, the following steps should be taken: 1) obtain the required data on
activity levels for the different segments of the fuel systems; 2) multiply activity levels by the appropriate
emission factor; and 3) sum across activity types to calculate total emissions. A more detailed discussion
of the suggested method for estimating CH4 emissions from oil and natural gas systems is contained in
the Discussion Section, chapter 3.
Step (1) Obtain Activity Data
• Required Data. The information required to estimate emissions from this source is based on
activity (e.g., production) by sector (oil or gas). Data required include: the amount of oil
produced, refined, transported, and stored at oil facilities; and the amount of natural gas
produced, processed and distributed to consumers.
• Data Sources: In-state agencies should be consulted first. However, if it is difficult to obtain data
from these sources, state-by-state data can be found in the Natural Gas Annual (published by
EIA/DOE) and Gas Facts (published by the American Gas Association).
• Units for Reporting Data: Data for oil and gas should be provided in energy units of million BTU
(MMBTU). Since oil data is usually reported in barrels and gas data in million cubic feet
(MMcf), apply the conversion factors listed in Table 3-1 to convert to million BTU.
Example A state producing 60 million barrels would produce an energy equivalent of:
60,000,000 barrels x 5.825 million BTU/barrel = 349,500,000 million BTU
Step (2) Estimate Methane Emissions in Tons
• Multiply activity data by the appropriate emissions factor, as presented in Table 3-2. Do this for
each activity type presented in Table 3-2.
Activity Level (MMBTU) x Emissions Factor (low, Ibs CH4/MMBTU) = Ibs CH4 (low)
3-1
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Table 3-1. Conversion Factors to Million BTU (MMBTU)
Fuel Type
Oil
Gas
a
b
If Data is Reported in
Barrels
Million Cubic Feet (MMcf)
Multiply by
5.825a
0.00 lb
Source: Energy Information Administration (EIA), (1994), '"Annual
Energy Review: 1993," U.S. Department of Energy. Washington
D.C., July 1994.
There are 1000 BTUs in 1 cubic foot of natural gas. i
Table 3-2. Methane Emission Factors for Activities
Sector
Activity Data
(MMBTU)
Emissions Factor
(Ibs CHyMMBTU)
Low
High
Median
Oil & Gas Production
Oil
Gas
Oil & Gas: Venting and Flaring
Oil Production
Gas Production
Oil & Gas Produced3
700
106,770
6,960
11,610
194,960
32,490
6,150
150,870
19,730
Crude Oil Transportation and Refining
Transportation
Refining
Storage Tanks
Oil Tankered
Oil Refined
Oil Refined
1,730
210
50
1,730
3,250
580
' 1,730
1,730
310
Natural Gas Processing, Transport, and Distribution
Gas Processing, Transmission, and
Distribution
Gas Consumption
132,300
273,880
203,090
a Emissions are based on total production of oil and gas.
Source: IPCC, 1994
Activity Level (MMBTU) x Emissions Factor (high, Ibs CH4/MMBTU) = Ibs CH4 (high)
Activity Level (MMBTU) x Emissions Factor (median, Ibs CH4/MMBTU) = Ibs CH4 (median)
Divide the number of lbs/CH4 obtained by 2,000 Ibs/ton to obtain tons of CH4 produced.
Ibs CH4 (low, for each activity) * 2,000 Ibs/ton = tons CH4 (low, for each activity)
3-2
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Ibs CH4 (high, for each activity) * 2,000 Ibs/ton = tons CH4 (high, for each activity)
Ibs CH4 (median, for each activity) * 2.000 Ibs/ton = tons CH4 (median, for each activity)
Example A state producing 1 million BTUs (MMBTUs) of natural gas could expect
emissions from natural gas production facilities of:
Low
1 .(MMBTU) x 106,770 (Ibs CH4/MMBTU) = 106,770 Ibs CH4
106,770 Ibs CH4 * 2,000 Ibs/ton = 53.4 tons CH4
High
1 (MMBTU) x 194,960 (Ibs CH4/MMBTU) = 194,960 Ibs CH4
194,960 Ibs CH4 + 2,000 Ibs/ton = 97.5 tons CH4
Median
1 (MMBTU) x 150,870 (Ibs CH4/MMBTU) = 150,870 Ibs CH4
150,870 Ibs CH4 + 2,000 (Ibs/ton) = 75.4 tons CH4
Step (3) Estimate Total Methane Emissions from Oil and Natural Gas Systems
• Sum across activity types (i) to obtain total methane emissions from oil and natural gas
systems.
'x
'x
'x
tons CH4 (low) = Total CH4 Emissions from Oil and Gas Systems (tons CH4, low estimate)
tons CH4 (high) = Total CH4 Emissions from Oil and Gas Systems (tons CH4, high estimate)
tons CH4 (median) = Total CH4 Emissions from Oil and Gas Systems (tons CH4, median estimate)
'1
3-3
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WORKBOOK 4
METHANE EMISSIONS FROM COAL MINING
Methane and coal are formed together during coalification, a process in which vegetation is
converted by geological and biological forces into coal. Methane is released when pressure within
a coalbed is reduced, either through mining or through natural erosion or faulting.
To estimate state emissions of methane from coal mining, the following steps should be
performed: 1) obtain the required data -- annual coal production from surface and underground
mines; 2) calculate methane emissions from underground coal mining; 3) calculate methane emissions
from surface mining; 4) calculate post-mining emissions; and, 5) calculate total coal mining emissions.
These steps are outlined in detail below. A more thorough description of the methodology used to
.estimate methane emissions from coal mines is provided in Discussion Section 4.
The Discussion Section also includes a more detailed, alternate methodology for estimating
methane emissions from underground mines. This alternate approach uses mine-specific data on 1990
methane emissions from ventilation systems at gassy underground mines. States that produce large
amounts of coal from gassy underground mines are encouraged to calculate underground emissions
using this alternate method. These states are: Alabama, Colorado, Illinois, Kentucky, Maryland,
Ohio, Pennsylvania. Utah, Virginia, and West Virginia.
Step (1) Obtain Required Data
• Required Data. The data required to estimate methane emissions from coal mining are annual
coal production from surface mines and from underground mines.1 For the states of West
Virginia and Kentucky, coal production will need to be obtained for each county rather than
total production for the state. Additionally, coal mine methane that is recovered for pipeline
sales rather than emitted to the atmosphere should be obtained for the states of Alabama,
Utah, and Virginia.
• Data Source. State energy offices should be able to provide data on annual coal production
from surface and underground mines. Alternatively, the annual Coal Production reports
produced by the Department of Energy/Energy Information Administration (DOE/EIA)
contain surface and underground coal production by state and by county. Data on methane
recovered for pipeline sales is typically available from state agencies that track oil and gas
production.
• Units for Reporting Data. Coal production data should be reported in million short tons.
Methane emissions data should be reported in million cubic feet (million cf).
Step (2) Calculate Methane Emissions from Underground Mines
• The first step in calculating methane emissions from underground mines is to find the annual
underground coal production for the state. State underground coal production should be
recorded in the first row of column 1 in Table 4-1, which is located on the last page of this
section. For West Virginia, coal production for counties in northern West Virginia and from
1 It is important to distinguish between underground production and surface production because
shallow, surface mined coals tend to hold less methane than deeper, underground mined coals.
4-1
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counties in southern West Virginia will need to be recorded separately. Also, for Kentucky.
coal production for eastern Kentucky and for western Kentucky will need to be recorded
separately. This is necessary because mines in different regions of these two states are part
of different coal basins, and the methane emissions factors for these basins differ. Following
is a list of counties that are in northern West Virginia and the counties that are in eastern
Kentucky:
Northern .West Virginia Counties: Barbour, Braxton, Brooke, Gilmer, Grant, Harrison,
Lewis, Marion. Marshall, Mineral, Monongalia, Ohio, Pendelton, Preston, Randolph. Taylor,
Tucker, Upshur, Webster. All other coal producing counties are southern West Virginia.
Western Kentucky Counties: Butler, Caldwell, Crittendon, Christian, Daviess. Edmonston,
Grayson, Hancock, Henderson, Hopkins, Logan, McLean, Muhlenberg, Ohio, Todd, Union.
Webster. All other coal producing counties are in eastern Kentucky.
Next, record the appropriate methane emissions coefficient (methane emitted per ton of coal
mined) in column 2 of Table 4-1. Emissions coefficients are shown below for six different
regions in the U.S. Both a low and high emissions coefficient are given so that the potential
range of emissions may be calculated.
Methane Emissions Coefficient for Coal Produced from Underground Mines
Basin
Central Appalachian Basin: Eastern Kentucky, Tennessee,
Virginia, southern West Virginia
Northern Appalachian Basin: Maryland, Ohio, Pennsylvania,
northern West Virginia
Black Warrior Basin (Alabama Only)
Rockies and Southwest Basins: Colorado,' New Mexico, Utah
Illinois Basin: Illinois, Indiana, western Kentucky
All Other States:
Emissions Coefficient
(cf CH4/ton coal mined)
Low High
215 325
425 740
2000 3000
370 470
160 190
50 150
Example According to DOE/EIA's Coal Production 1992, coal production from
underground mines in Illinois was 46,965,000 short tons in 1992. Using the
emissions coefficients in the table above, estimated methane emissions from
underground mines in Illinois are:
Low: 46.965 million tons x
High: 46.965 million tons x
160cf/ton =
190cf/ton =
7,514 million cf.
8,923 million cf.
4-2
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Step (3) Calculate Methane Emissions from Surface Mines
• Coal production from surface mines should be recorded in the second row of column 1 in
Table 4-1. Surface coal mining primarily occurs in the western U.S. and the eastern states
of Illinois, Indiana, western Kentucky, Pennsylvania and Virginia.
• For surface mined coal, the low emissions coefficients are assumed to be from 1 to 3 times
the in-situ methane content of the coal. The surface mining emissions coefficients for the
major coal basins are shown below. Record the appropriate low and high state surface mining
emissions coefficients in row 2 of column 2 in table 4-1.
Methane Emissions Coefficient for
Coal Produced from Surface Mines
Basin
Central Appalachian Basin: Eastern Kentucky, Tennessee,
Virginia, southern West Virginia
Northern Appalachian Basin: Maryland, Ohio, Pennsylvania,
northern West Virginia
Black Warrior Basin: Alabama
Rockies and Southwest Basins: Colorado, New Mexico, Utah
Illinois Basin: Illinois, Indiana, western Kentucky
All Other States: ,
Emissions Coefficient
(cubic feet methane/ton
of coal mined)
Low High
50, ,150
50 150
50 150
15 45
40 120
3 10
Calculate methane emissions from surface mines by multiplying the low and high methane
emissions coefficients by surface coal production. Record the resulting estimated emissions
in row 2 of column 3 in table 4-1.
Example According to DOE/EIA's Coal Production 1992, coal production from surface
mines in Illinois was approximately 12,892,000 short tons. Using the given low
and high emissions coefficients, estimated methane emissions from surface
mines in Illinois are:
Low: 12.892 million tons x 40 cf/ton = 516 million cf.
High: 12.892 million tons x 120 cf/ton = 1,547 million cf.
Step (4) Calculate Post-Mining Methane Emissions
• Some methane remains in the coal after it has been mined and can be emitted during
4-3
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transportation and handling of the coal. Post-mining emissions should be calculated for both
surface and underground mined coals. First, record coal production in column 1 of table 4-1.
Record underground coalproduction in row 3 and surface coal production in row 4 (rows 3
and 4 will be identical to rows 1 and 2 for column 1).
Next, surface and underground coal production should be multiplied by the appropriate
emissions coefficient to estimate post-mining methane emissions. Post-mining emissions
coefficients are determined by assuming that from 25 percent to 40 percent of the in-situ
methane content of the coal escapes during post-mining activities. Post-mining emissions
coefficients for underground and surface-mined coal are shown below. The appropriate state
emissions coefficients should be recorded in column 2 of table 4-1.
Once the appropriate emissions coefficients have been recorded, multiply surface and
underground coal production by the emissions coefficients to calculate post-mining emissions.
Emissions should be recorded in column 3 of table 4-1.
Post-Mining Methane Emissions Coefficients
Surface and Underground Mines
Central Appalachian Basin: Eastern Kentucky,
Tennessee, Virginia, southern West Virginia
Northern Appalachian Basin: Maryland, Ohio,
Pennsylvania, northern West Virginia
Black Warrior Basin: Alabama
Rockies and Southwest Basins: Colorado, New Mexico,
Utah
Illinois Basin: Illinois, Indiana, western Kentucky
All Other States:
Underground
Mines
(cf/ton)
Low
80
40
80
55
14
10
High
130
70
130
90
22
16
Surface
Mines
(cf/ton)
Low
12
12
12
4
10
0.8
High
20
20
20
6
16
1.3
Example Using the surface and underground coal production shown in the examples
above, post-mining methane emissions for Illinois are calculated as follows:
Surface: Low = 12.892 million tons x 10 cf/ton = 129 million cf
High = 12.892 million tons x 16 cf/ton = 206 million cf
Underground: Low = 46.965 million tons x 14 cf/ton = 658 million cf
High = 46.965 million tons x 22 cfAon = 1,033 million cf -
4-4
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Step (5) Calculate Total Methane Emissions from Coal Mining
• To find the low and high total emissions from coal mining, add together emissions from
underground mines and surface mines and post-mining emissions. Record the low and high
total emissions from coal mining in row. 5 of column 3 in Table 4-1. The low and high total
emissions represent the potential range of state coal mine methane emissions.
x
• Next, calculate the average of the low and high total emissions estimates and record that
value in row 6 of Table 4-1. This value may be used as a single approximation of state coal
mining methane emissions. It is important to note, however, that there is a large degree of
uncertainty associated with using a single emissions estimate; the range developed from the
low and high values represent the best approximation of state emissions.
• Next, the amount of coal mine methane that is recovered for energy purposes, rather than
emitted to the atmosphere, must be subtracted from the total emissions estimates. Currently.
recovery projects are in operation at mines in the states of Alabama, Utah, and Virginia. The
coal companies that have developed projects are shown below, along with the estimated
methane that was recovered and sold to pipelines in 1992. More recent data on methane
recovered for pipeline sales is typically available from state agencies that track state oil and
gas production. It is important to note that only coal mine methane that is recovered in
association with active coal mining operations should be included. Production from "stand-
alone" coalbed methane projects (Le., projects that are similar to conventional oil and gas
production but that recover natural gas from coal seams) should not be included. The states
of Alabama, Colorado, and New Mexico are large producers of natural gas from stand-alone
coalbed methane wells.
Current Coal Mine Methane Pipeline Projects
Mining Company
Jim Walter Resources
U.S. Steel Mining
CONSOL Coal Group1
Soldier Creek Coal
1 1992 was the first year of
pipeline sales has increased
Number of
Mines
4
1
4
1
State
Alabama
Alabama
Virginia
Utah
production for these mines.
substantially since that time.
1992 Methane
Recovered (million cf)
12,268
2,260 (est.)
4,000
5,000
Methane recovered for
For those states that have current coal mine methane recovery projects, record the quantity
of methane that is recovered for pipeline sales in row 7 of Table 4-1. The amount recovered
should be recorded in million cf. Subtract the amount recovered from the total average
emissions to obtain total methane emitted to the atmosphere. Record this value in row 8 of
Table 4-1.
Finally, total methane emissions should be converted from million cubic feet to tons by
multiplying by 20.66 tons per million cf. This value should be recorded in row 9 of table 4-1.
4-5
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Example
Total coal mine methane emissions for Illinois are calculated as follows:
(million ef) Low High
Underground: 7,514
Surface: 516
Post-mining (underground): 658
Post-mining (surface): 129
Total: 8,817
8,923
1,547
1,033
206
11,709
Avg. = (8,817 + 11,709)/2 = 10,263 million cf
10,263 million cf x 20.66 tons/cf = 212,034 million tons CH4.
Table 4-1 - Calculations for Estimating Methane Emissions from Coal Mines
I Underground Mines
2 Surface Mines
3 Post-mining
(Underground)
4 Post-raining
(Surface)
1
Coal Production
(million short tons)
2
Emissions
Coefficient
(cf/ton)
Low
High
5
6
7
8
9
3
Methane Emitted
column ,1 x column 2
(million cf methane)
Low
Total
Low:
High
Total
High:
Average:
- CH4 Recovered
Total (cf CH4):
Total (tons CH4):
4-6
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WORKBOOKS
METHANE EMISSIONS FROM LANDFILLS
Landfill gas, consisting prim'arily of methane (CH4) and carbon dioxide (CO2), is produced
as a result of the decomposition of organic waste in an anaerobic (without oxygen) environment.
Most landfill gas is emitted directly to the atmosphere. However, at a few landfills, the gas is
recovered and either flared or used as an energy source. Municipal solid waste (MSW) landfills are
estimated to account for over 90 percent of all methane emissions from landfills in the U.S. (EPA
1993). Industrial landfills, which receive nonhazardous waste from factories, processing plants, and
other manufacturing activities, account for the remainder of landfill methane emissions.
The following steps may be followed to estimate state methane emissions from landfills: (1)
obtain the required data; (2) estimate waste in place at MSW landfills; (3) estimate fraction of waste
in large versus small MSW landfills; (4) classify state as nonarid or arid; (5) estimate methane
generated from waste in place at small MSW landfills; (6) estimate methane generated from waste
in place at large MSW landfills; (7) estimate total methane generated from MSW landfills; (8)
estimate methane generated from industrial landfills; (9) adjust for flaring and recovery; and (10)
adjust for oxidation.
Step (1) Obtain Required Data
• Required Data. The information needed to estimate methane emissions from landfills are the
following:
(1) Waste in place in the state. For the purposes of this exercise, waste in place is
defined as the total quantity of waste that has been landfilled over the previous thirty
years. For some states this information may be readily available. If a state does not
have information on the quantity of waste in place, waste in place may be estimated
based on the current population of the state, the average annual population growth rate
over the past thirty years, the per-capita waste generation rate (default values are
provided on the following page), and the portion of waste generated that is landfilled.
For waste in place at industrial landfills, formulas shown in Step 8 may be used if state
information is not available.
(2) Fraction of waste in place in large versus small MSW landfills and number of large
landfills in the state. For purposes of this exercise, large landfills are those that have
a total of more than 1.1 million tons in place. States will need to estimate the
fraction of total waste in place that is contained in large landfills. Default values are
provided if state information is not available.
(3) Average annual rainfall within the state. A state is considered arid if average rainfall
is less than 25 inches per year. The workbook includes a list of those states that
receive on average less than 25 inches of rainfall per year (the arid states). All other
states are considered to be nonarid.
(4) Quantity of landfill gas that is flared or recovered for energy purposes.
5-1
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• Data Sources. State solid waste offices or other agencies may track the amount of waste
deposited into landfills. .Waste in place may be estimated from this information.
Alternatively, population data and default values for waste generation may be used to
estimate waste in place. If the data on the percentage of waste generated that is landfilled
in each state are not available, they may be obtained from the article "The State of Garbage:
1992 Nationwide Survey" (BioCycle, April 1993). The fraction of total waste in place in large
and small landfills may be available from state solid waste offices, or may be estimated using
the default values shown in this report. Information on methane recovery may be available
from state solid waste offices. If not, methane recovery can be estimated using the Methane
Recovery from Landfill Yearbook (Government Advisory Associates, Inc.), which reports the
amount of methane recovered for energy use on a landfill by landfill basis in the U.S.1 The
amount of landfill gas that is flared must be estimated using in-state data, as national data is
not available on flaring at landfills.
• Units for Reporting Data. Waste in place and the amount of landfill methane flared or
recovered for energy purposes should be reported in tons per year.
Step (2) Estimate Waste in Place at MSW Landfills
• If state data oh waste in place are available, these data should be used.
• If state data on waste in place are not available, the waste in place may be estimated by using
the following formula:
Waste in Place (tons) = 30 years x Current State Population (1,000 head) x Per Capita
Waste Generation Rate (Ibs/capita/yr) x Percent Landfilled x
"Population Growth Correction Factor" + 2,000 Ibs/ton
Where:
Per Capita Waste Generation Rate is about 1,460 to 1,825 Ibs/person/year (4 to 5
Ibs/person/day) -- substitute state specific values if available.
Percent Landfilled is 70 percent -- substitute state specific values if available.
Population Growth Correction Factor is based on Table 5-1 and is discussed below.
Population Growth Correction Factor
In most states, the quantity of waste that is landfilled each year has grown significantly over
the past 30 years. Therefore, using the current waste landfilled as the amount landfilled each
year over the past thirty years could overestimate total waste in place. In order to account
for growth in the annual amount of waste deposited, a correction factor is applied. The
appropriate correction factor depends on the average amount of time that waste produces
methane and on the estimated average annual growth rate in waste landfilled over this period
(For example, in the U.S. waste produces methane for about thirty years and so the growth
rate of waste landfilled over the previous thirty years must be estimated). One method to
1 The Methane Recovery From Landfill Yearbook is available, for a fee, from Governmental Advisory
Associates Inc. (New York, NY), (212) 410-4165.
5-2
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estimate the average annual growth rate in waste landfilled is to use the average population
growth rate. Table 5-1 shows the correction factor to be used for different average annual
growth rates and for different time frames for methane production. For example, assuming
that waste produces methane for 30. years, the growth correction factor for a state with an
average annual population growth rate of 2 percent over the past 30 years would be 75.4
percent.
Table 5-1: Correction Factor for Estimating Waste in Place3
Average Annual Growth Rate of Landfill Waste Disposal
(e.g., Average Annual Growth Rate of Population)
Growth Rate
Growth Correction
Factor
1% ,
86.5%
a Assuming that waste produces methane
2% 3% 4% 5%
75.4% 66.3% 58.8% 52.5%
for 30 years.
6% 7%
47.2% 42.8%
Example Waste in place for a state that has a current population of 2 million and an
average annual growth rate over the past thirty years of 2% would be calculated
as follows:
Waste in Place = 30 years x 2 million people x 75.4% correction factor x 1,460
Ibs/person/year x 70% landfilled + 2,000 Ibs/ton
- 23 million tons waste in place.
Step (3) Estimate Fraction of Waste in Place in Large Versus Small MSW Landfills
• Once the total quantity of waste in place has been estimated, the next step is to estimate the
fraction of total waste in place in large versus small landfills.
• The fraction of waste in large versus small landfills is important because methane generation
rates are different due to a variety of factors, such as different waste composition, different
waste ages, and ease of moisture movement within the landfill. For this exercise, a large
landfill is defined as having more than 1.1 million tons of waste in place.
• Some states may have information on the fraction of waste by landfill size. If these data are
not available, then the fraction may be estimated using default values shown in Table 5-2.
5-3
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Example Assume that total, landfilled waste for a state is 25 million tons, of which 20
percent is in small landfills and 80 percent is in large landfills. Therefore, the
amount of waste in place in small and large landfills is simply:
Waste in place at small landfills:
Waste in place at large landfills:
20% x (25 million tons) = 5 million tons
80% x (25 million tons) = 20 million tons
Table 5-2: Default Values for the Fraction of Waste in Large Versus Small Landfills
Region
Northeast
Southeast
Midwest
West
States Located in Region
Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire,
New Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont
Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi,
North Carolina, South Carolina, Tennessee, Virginia, West Virginia
Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska,
Oklahoma, North Dakota, South Dakota, Texas, Wisconsin
Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada,
New Mexico, Oregon, Utah, Washington, Wyoming
Fraction of
Waste
Landfilled at
Large Landfills
89%
73%
81%
86%
Source: Derived from EPA (1988).
Step (4) Classify State as Nonarid or Arid
• Moisture is an important factor in the production of methane in landfills. Landfills in nonarid
climates are believed to produce more methane per unit of waste in place than do landfills
in arid climates.
• Different methane emission estimates have been developed for nonarid states and for arid
states. Table 5-3 lists those states that are classified as arid states -- states that have average
rainfall of less than 25 inches per year. All other states are considered to be nonarid states.
If a state has distinct arid and non-arid areas, then the additional steps described at the end
of Steps 5 and 6 should be used.
5-4
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Table 5-3: Arid States (States with average annual rainfall less than 25 inches)
Arizona
California
Colorado
Idaho
Source: Department of
Montana
Nebraska
Nevada
New Mexico
Commerce (1988)
North Dakota
South Dakota
Utah
Wyoming
Step (5) Estimate Methane Generated from Waste in Place at Small MSW Landfills
• The following equations are used to estimate the range of methane generated from small
landfills based on the quantity of waste in place. Equation 5.1 should be used for nonarid
states and equation 5.2 for arid states. The equation estimates methane emissions in cubic
feet per ton per day.
Nonarid: Methane (ft3/day )= 0.35 W(tons) ± 20% (5-1)
Arid: Methane (ft3/day )= 0.27 W(tons) ±20% (52)
where W = Waste in place (tons)
• To convert this result to annual methane emissions in tons CH4, multiply the result by:
365 ( days/year ) x 19.2 ( gift3) = QQQ^ ( tonCH4/year )
453.49 (g/lb) x 2,000 (Ib/ton) " ' ( ft3/day )
Example Methane generated at smalt landfills for a nonarid state that has waste in place
at small landfills of 5.0 million tons would be estimated as follows:
Small landfills: 0.35 (ft3/ton/day) x 5 million tons = 1.75 million ft3/day
= 1.75 million ft3/day x 0.0077 (tons CH,/vr)
= 13,475 million tons CH^yr
(fr/day)
If a state is partially arid, then a weighted average can be used to estimate the methane
generated from the landfills. If the amount of landfilled waste in arid and non-arid
regions is known, then both equations can be used with the breakdown of waste in place
between arid and non-arid regions.
-------
Step (6) Estimate Methane Generated from Waste in Place at Large MSW Landfills
• The method for estimating the range of methane emissions from large landfills is slightly
more complex than the method for estimating the range of emissions from small
landfills.2 The additional steps are 1) estimate the total number of large landfills in the
state and, 2) divide total waste in place at large landfills by the total number of large
landfills to obtain average waste in place at large landfills. The number of large landfills
and the average waste in place at these landfills are then used in the equations to estimate
methane generated. Equations 5.3 and 5.4 should be used to estimate methane generated
for nonarid states and arid states, respectively. As with equations 5.1 and 5.2, methane
generated is in cubic feet per day.
Nonarid: Methane (ft3/day ) = N x (419,000 + 0.26 Wavfl(tons) ) ± 15% (5 3)
Arid: Methane (ft3/day ) = N • (419,000 + 0.16 W^tons) ) ± 15% (5.4)
Where N = Number of large landfills in the state
W = Average waste in place (tons) at large landfills
• To convert to methane generated in tons per year multiply the result by:
365 ( days/year) • 19.2 ( g/ft3) -00077 (tonCH4/year)
453.49 (g/lb) • 2,000 (Ib/ton ) ' (ft3/day)
Example Methane generated .for an arid state that has 5 large landfills and waste in place
at large landfills of 20.0 million tons would be estimated as follows:
1. Estimate average waste in place at large landfills
wavg = (20-° mill'°n) tons / 5 landfills = 4.0 million tons/landfill
2. Estimate methane generated at large landfills *
CH4 = 5 x [ 419,000 + (0.16 ft3 CH^day x (4.0 million tons)) }
5.295 million ft3 CH4/day
5.295 million ft3 CH4/day x 0.0077 (tons CH^vrt
(ft3 CH4/day)
= 40,770 million tons CH4/yr
2 The accuracy range of the equations for large landfills (±15 percent) is better than for small
landfills (±20 percent) because the estimate for large landfills is based on a greater number of actual
landfill methane production measurements.
5-6
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If a state is partially arid, then a weighted average can be used to estimate the methane
generated from the landfills. If the exact amount of landfilled waste in arid and non-arid
regions is known, then both equations can be used with the breakdown of waste in place
between arid and non-arid regions.
A more accurate, but slightly more complex, method for estimating methane emissions
from large landfills may be used when state data are available on the quantity of waste in
place at each large landfill in the state. If these data are available, equations 5.5 (for
nonarid states) and 5.6 (for arid states) may be used. These equations are slightly
modified versions of equations 5.3 and 5.4, respectively.
Nonarid: Methane (cf/d) = ( £ [ 419,023 + 0.26 w, ] ) ±15% (5 5)
1-1
Arid: Methane (cf/d) = ( £ [ 419,023 + 0.16 w, ]) ±15% (5-6)
/-i
Where n = number of large landfills in the state
w; = waste in place (tons) at each landfill
Step (7) Estimate Total Methane Generated from MSW Landfills
• Total methane generated from MSW landfills is the sum of methane generated at small
landfills (Step (5)) and methane generated at large landfills (Step (6)).
Step (8) Estimate Methane Generated from Industrial Landfills
• Methane is also generated from waste deposited into non-hazardous industrial landfills.
Although methane generation from non-hazardous industrial landfills is believed to be
small relative to MSW landfills, industrial landfill methane generation is still a significant
source of methane emissions. Note that methane generation from industrial landfills does
not include methane generation from industrial waste disposed of into MSW landfills.
This methane generation is already accounted for under MSW landfills.
• Precise estimates of the quantity of waste in industrial landfills and its methane generation
rate are not available. Based on estimates of the quantity of waste in place at industrial
landfills and on the estimated organic content of industrial landfills compared to MSW
landfills, EPA (1993) estimated that methane generation from industrial landfills in the
U.S. is approximately 7 percent of methane generation from MSW landfills in the U.S.
This 7 percent value may be used to estimate state methane generation from industrial
landfills.
• Alternatively, if state information is available on the quantity of waste in place (WIP) at
industrial landfills, the ratio of emissions from industrial landfills to emissions from MSW
landfills may be calculated as follows:
Average 15% organic content x WIP at Industrial Landfills
Average 65% organic content x WIP at MSW Landfills
5-7
-------
The resulting value would be used in place of the 7 percent default value.
Total methane generation then equals MSW methane generation (Step (7)) plus industrial
landfill methane generation.
Example For a state that has an estimated 0.8 million tons of methane generated from
large MSW landfills and 0.2 million tons from small MSW landfills, methane
emissions from industrial waste landfills would be calculated as follows:
Total
7% x (0.8 million tons CH4+ 0.2 million tons CH^ = 0.07 million tons Ch^
methane generated would be: 1 million tons CH4 from MSW landfills + 0.07 million
tons CH4 from industrial landfills = 1.07 million tons CH4
Step (9) Adjust for Flaring and Recovery
• Some states have landfills that either flare some of the methane that is produced or
recover the methane and use it as an energy source. Methane that is flared or recovered
should be subtracted from total methane generated (Step (8)).
Example A state that recovers or flares 0.1 million tons of landfill CH4 annually and has
, total methane generation of 1.7 million tons per year would be calculated as
follows:
1.7 million tons CH4 generated - 0.1 million tons CH4 recovered = 1.6 million tons CH4
Step (10) Adjust for Oxidation
• Not all of the methane that is generated in a landfill is emitted to the atmosphere. Some
methane may be oxidized in the top layer of soil over the landfill, and thus not emitted to
the atmosphere. The amount of oxidation that,occurs is uncertain and depends on the
characteristics of the soil and the environment. For purposes of this exercise, it is
assumed that 10 percent of the methane generated that is not recovered is oxidized in the
soil. Accordingly, methane generated (minus the amount flared or recovered) (Step (9))
should be multiplied by 90 percent to account for oxidation.
• Once the adjustment for oxidation has been made, the result is total methane emissions
from landfills.
5-8
-------
Example Total methane emitted to the atmosphere from landfills for a state with total
methane generated of 1.7 million tons and 0.1 million tons of methane
recovered would be calculated as follows:
Total methane emissions: = (1.7 million tons CH4 generated - 0.1 million tons CH4
recovered or flared) • 90% oxidized
= 1.44 million tons CH4
5-9
-------
WORKBOOK 6
METHANE EMISSIONS FROM
DOMESTICATED ANIMALS
Methane is a natural by-product of animal digestion. During digestion, methane is produced
through a process referred to as enteric fermentation in which microbes that reside in animal
digestive systems break down feed consumed by the animal. Ruminants, which include cattle, buffalo.
sheep, and goats, have the highest methane emissions among all animal types because of their unique
digestive system. Ruminants possess a rumen, or large "fore-stomach," in which a significant amount
of methane-producing fermentation occurs. Non-ruminant domestic animals, such as pigs and horses,
have much lower methane emissions than ruminants because much less methane-producing
fermentation takes place in their digestive systems. The amount of methane produced and excreted
by an individual animal depends upon its digestive system (i.e.. whether or not it possesses a rumen).
and the amount and type of feed it.consumes.
For cattle, the U.S. EPA used a detailed methodology to estimate emissions for enteric
'fermentation (U.S. EPA, 1993). The U.S. was divided into five geographic regions based on
representative cattle types, diets, and management practices (see Figure 6-1). Nine different cattle
types were evaluated in each of the five regions and emissions factors were estimated for each using
a mechanistic model of rumen digestion (see Table 6-1).
Using the results of the EPA analysis, estimating methane emissions from domesticated
animals requires three steps: 1) obtain data on animal populations; 2) identify geographic region and
corresponding emissions factor; and 3) multiply animal populations by their appropriate emissions
factor. These three steps are outlined below. An alternative approach that requires specific livestock
characteristics is outlined in Discussion Section 6. Since/cattle characteristics may vary significantly
by state, it is recommended that states with large cattle populations consider using the alternative
approach if the state cattle characteristics differ from the cattle characteristics used in the EPA study.
Step (1): Obtain Required Data
• Required Data. The information needed to estimate methane emissions from domesticated
animals is annual average animal populations1 for the following animals: cattle (by type; see
Table 6-1), buffalo, sheep, goats, swine, horses, mules, and asses.
• Data Source. Departments within each state responsible for conducting agricultural research
and overseeing the agricultural sector should be able to provide state animal populations.
Additionally, state animal populations can be found in the Census of Agriculture, Volume 1:
Geographic Area Series, published by the Bureau of the Census. Also, if requested, the
USDA can produce state by state inventories on domesticated animal populations.
• Units for Reporting Data. Animal population should be reported in number of head.
1 Please note that animal populations fluctuate during the year, in some cases by large amounts. For
example, a census done before calving will give a much smaller number than a census done after calving.
The annual average animal population should be used in the estimates.
6-1
-------
Example According to the 7992 Census of Agriculture, the number of milk cows in Ohio
were 295,677 head.
Step (2): Identify Geographic Region
• Determine which of the five geographic regions, defined in Figure 6-L. the state falls into.
The emissions factors corresponding to the region are to be used for Step 3.
Example The state of Ohio falls in the North Central Region.
Step (3): Estimate Methane Emissions
• Multiply each animal population by the appropriate regional emissions factor. Emissions
factors for cattle are presented in Table 6-1. Emissions factors for all other animals are
presented in Table 6-2.
Animal Population (head) x Regional Emissions Factor (Ibs. CH4/head) = Methane
Emissions (Ibs.)
• For each animal, divide the results by 2000 Ibs/ton to obtain tons of methane. Sum across all
animal types to obtain total methane emissions from domesticated animals.
Example Methane emissions from milk cows in Ohio for 1992 are calculated as follows:
(a) 295,677 head x 240.7 (Ibs CH4/head) = 71,169,454 Ibs CH4
(b) 71,169,454 Ibs CH4 + 2000 (Ibs/ton) = 35,585 tons CH4
6-2
-------
Figure 6-1
Geographic Regions
North '
Central
South
Central
South
Atlantic
"•Includes Alaska and Hawaii
6-3
-------
Table 6-1. Emissions Factors for U.S. Cattle by Region (Ibs CH^head/yr)
Animal Type/Region
Dairy Cattle
Replacements 0-12 months3
Replacemen-ts 12-24 months3
Mature Cows
North
Atlantic
42.9
.128.5
258.5
South
Atlantic
45.1
129.1
278.3
North
Central
41.6
126.3
240.7
South
Central
44.7
135.7,
257.7
West
45.5
134.6
262.5
National
Average6
=
43.1
129.4
252.1
Beef Cattle
Replacements 0-12 months3
Replacements 12-24 months3
Mature Cows
Weanling System Steers/Heifersb
Yearling System Steers/Heifers'1
Bulls
42.2
140.4
135.3
NAC
NA
220
49.9
148.5
154.0
NA
NA
220
44.8
133.8
130.9
49.7
103.4
220
51.9
148.9
155.9
52.8
104.7
220
49.9
142.7
152.0
51.7
104.7
220
49.1
143.0
146.7
50.8
104.1
220
a A portion of the offspring are retained to replace mature cows that die or are removed from the herd
(culled) each year. Those that are retained are called "replacements."
b In "weanling systems," calves are moved directly from weaning to confined feeding programs. This system
represents a very fast movement of cattle through to marketing. Weanling system cattle are marketed at
about 420 days of age (14 months).
c These cattle types are typically not found in the North Atlantic and South Atlantic regions. If desired, it i:
appropriate to use the national total emissions factor for these regions.
d "Yearling systems" represent a relatively slow movement of cattle through to marketing. These systems
include a wintering over, followed by a summer of grazing on pasture. Yearling system cattle are
marketed at 565 days of age (18.8 months).
e National Averages are weighted by regional populations as of 1990.
Source: U.S. EPA, 1993.
Table 6-2
Emissions Factors for Other Animals (All Regions)
Animal
Sheep
Goats
Pigs
Horses
Mules/Asses
Sources: Emissions factors from
Emissions Factor
(Ibs CH^head/yr)
17.6
11.0
3.3
39.6
48.5
Crutzen et al. (1986).
6-4
-------
WORKBOOK 7
METHANE EMISSIONS FROM
MANURE MANAGEMENT
When animal manure decomposes in an anaerobic environment, decomposition of the organic
material in the manure produces methane. The way in which manure is managed is the most
important factor affecting the amount of methane produced, since certain types of storage and
treatment systems promote an oxygen-free environment. In particular, liquid systems, e.g., lagoons,
ponds, tanks, or pits, tend to produce a significant quantity of methane. When manure is handled
as a solid or when it is deposited on pastures and rangelands, it tends to decompose aerobically and
produce little or no methane. Higher temperatures and moist climatic conditions also promote
methane production. Only manure from animals managed by humans for production of animal
products is included in the workbook calculations (i.e., wild animals are excluded).
To estimate methane emissions from animal manure, the following steps should be performed:
1) obtain the required data on animal populations and manure management practices; 2) calculate
the amount of volatile solids (VS) produced by each animal; 3) estimate methane emissions from each
manure management system; 4) convert emissions to tons of methane; and 5) sum estimates to obtain
total annual methane emissions for the state. Each of these steps is outlined in detail below. A
worksheet is provided in Table 7-13 to assist in the calculations. A more detailed description of the
methodology is provided in Discussion Section 7.
Step (1) Obtain Required Data
• Required Data. The information needed to estimate methane emissions from manure is
animal populations for the following animal types: cattle (by type), swine (by type), poultry
(by type), sheep, goats, donkeys, horses, and mules (see Exhibit 7-1 for further detail).
In addition, data on the percentage of animal manure handled in each manure management
system are required. A list and description of the major livestock manure systems in use in
the U.S. appear in Discussion Section 7.
• Data Sources. Departments within each state responsible for conducting agricultural research
and monitoring agricultural waste practices should be consulted for animal population data.
Alternatively, animal population data are provided by the Agriculture Statistics Board of the
USDA. Also, these data can be found in the Census of Agriculture, Volume 1: Geographic
Area Series, published by the Bureau of the Census. Manure management usage percentages
for most states and management practices are provided in Tables 7-1 to 7-9.
• Units for Reporting Data. Animal population should be reported in number of head. Manure
management usage should be reported as percentages.
7-1
-------
Exhibit 7-1
Recommended Representative Animal Types
Main Categories
Sub-Categories
Mature Dairy Cattle Milk Cows: used principally for commercial milk production
Mature Non Mature Females:
-Dairy Cattle - Beef Cows: used principally for producing beef steers and heifers
- Multiple-Use Cows: used for milk production, draft power, and
other uses
Mature Males:
~ Breeding Bulls: used principally for breeding purposes
- Draft Bullocks: used principally for draft power
Young Cattle Pre-Weaned Calves
Growing Heifers, Steers/Bullocks and Bulls
Feedlot-Fed Steers and Heifers on High-Grain Diets
Swine
Market: used principally for commercial pork products.
Breeding: used principally for breeding.
Poultry
Layers
Broilers
Ducks
Turkeys
Other \nimals
Sheep
Goats
Donkeys
Horses/Mules
7-2
-------
Step (2) Calculate the Amount of Volatile Solids (VS) Produced. (Table 7-13, Columns A, B,
C and D)
• For each animal type /', multiply the animal population by the typical animal mass (TAMj) and
the average annual volatile solids production per unit of animal mass (vSj). Values for the
TAM and vs for each of the animal types are provided in Table 7-10.
Animalj Population (head) x TAMj (Ibs/head) x vSj (Ibs VS/lb animal mass/yr)
= Total VSj produced (Ibs/yr)
Example According to the 7992 Census of Agriculture, the number of milk cows in Ohio
were 295,677 head. According to Table 7-2, the percentage of this manure
handled in daily spread manure management systems is 45% for Ohio.
Example The total amount of volatile solids (VS) produced by milk cows in Ohio for 1992
is calculated as follows:
295,677 head x 1,345 Ibs/hd. x 3.65 Ibs VS/lb animal mass/yr = 1.45 billion Ibs/yr
Step (3) Estimate Methane Emissions for Each Manure Management System (Table 7-13,
Columns E, F, G, H and I)
(
• For each animal type / and manure system;, multiply the amount of volatile solids produced
(VSj) by the methane producing capacity of the manure (B0 j) times the methane producing
potential (MCF:) of the manure system times the percent of the animals' manure that is
managed in that manure system (WS%; :). Default values for B0 and MCF by state are
presented in Tables 7-11 to 7-12. WS% values for most states and management practices
are provided in Tables 7-1 to 7-9.
VSj x Boi x MCF: x WS%ij = Methane Emissions for animal i in system j (ft3 CH4)
where:
KSj = total volatile solids produced (Ibs/yr) for animal /;
B0 j = maximum methane producing capacity per pound of
VS for animal / (ft3/lb-VS);
MCF. = methane conversion factor for each manure system /
percent of animal fs manure managed in manure
system j (%).
7-3
-------
Example Total annual methane emissions from milk cows in Ohio on a daily spread
manure management system is calculated as follows:
1.45 billion Ibs/yr x 3.84 (ft3 CH4/lb-VS) x 0.2% x 45% = 5.01 million ft3 CH4/yr
Step (4) Convert to Tons of Methane (Table 7-3, Column J)
• For each animal i and manure management system j multiply methane emissions by the
density of methane (0.0413 lbs/ft3) to convert from cubic feet to pounds.
• Divide the results by 2000 to obtain methane emissions from each animal and manure
management system in tons.
Example Annual methane emissions from milk cows in Ohio in a daily spread manure
management system [from Step(3)] are converted from cubic feet to pounds as
follows:
(a) 5.01 million ft3 CH4/yr x 0.0413 lbs/ft3 = 206,913 lbsCH4/yr
(b) 206,913 lbsCH4/yr + 2000 Ibs/ton = 103.5 tons CH4/yr
Step (5) Estimate Total Annual Methane Emissions
• Sum across all manure management systems j and all animal types / to obtain total methane
emissions from animal manure.
Total Annual Methane Emissions (tons CH4) = 51 ETotal Methane Emissionsy (tons)
7-4
-------
TABLE 7-1: MANURE MANAGEMENT SYSTEMS FOR U.S. BEEF
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
U.S. Average
An. Lag'
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%
Drylot
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%
6%
2%
12%
5%.
' .5%
6%
0%
3%
5%
1%
13%
5%
0%
2%
15%
2%
5%
6%
10%
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%
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%
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%
An. Lag. stands for anaerobic lagoon.
7-5
-------
TABLE 7-2: MANURE MANAGEMENT SYSTEMS FOR U.S. DAIRY
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
U.S. Average
An.
Lagoon
50%
10% •
50%
25%
40%
5% •
0%
5%
30%
35%
31%
10%
5%
10%
3%
0%
19%
6%
0%
2%
0%
5%
0%
10%
60%
12%
0%
40%
0%
0%
•90%
0%
20%
1%
5%
15%
42%
0%
0%
80%
25%
5%
25%
1%
0%
0%
40%
2%
0%
12%
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%
10%
40%
29%
6%
20%
20%
1%
30%
0%
' 35%
2%
29%
5%
25%
40%
10%
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%
1 4%
58%
45%
58%
45%
40%
2%
40%
39%
35%
,0%
20%
58%
10%
70%
50%
8%
45% •
5%
5%
95%
58%
10% .
30%
20%
15%
8%
58%
25% '
10%
30%
70%
39%
41%
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%
50%
40%
13%
0%'
10%
10%
90%
12%
0%
1%
3%
13%
5%
20%
0% .
50%
90%
13%
0%
0%
20%
15%
23%
.18%
Other
0%
15%
50%
0%
60%
0%
0%
0%
60%
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%
7-6
-------
TABLE 7-3: MANURE MANAGEMENT SYSTEMS FOR U.S. SWINE
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
U.S. Average
An.
Lagoon
• 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%
45%
75%
3%
90%
30%
25%
0%
24%
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%
30%
25%
53%
0%
0%
25%
10%
25%
20%
Pit St.
<1 mnth
0%
0%
0%
o%-
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%
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%
7-7
-------
TABLE 7-4: MANURE MANAGEMENT SYSTEMS FOR U.S. CAGED LAYERS
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
U.S. Average
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%
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% i
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%
7-8
-------
TABLE 7-5: MANURE MANAGEMEiNT
SYSTEMS FOR U.S. BROILERS
TABLE 7-6: MANURE MANAGEMENT
SYSTEMS FOR U.S. TURKEYS
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. Average
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%
100%
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%
State
AR
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. Average
Litter
95%
93%
0% '
50%
85%
95%
100%
100%
75%
90%
93%
100%
100%
90%
40%
100%
75%
100%
100%
100%
100%
90%
95%
100%
0%
94%
90%
88%
92%
Range
5%
7%
100%
50%
15%
5%
0%
0%
25%
10%
7%
0%
0%
10%
60%
0%
25%
0%
6%
0%
0%
10%
5%
0%
100%
6%
10%
12%
8%
Other
0%
0%
. 0%
0%
0%
0%
0%
p%
0%
0%
0%
0%
0%
, 0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
7-9
-------
TABLE 7-7: MANURE MANAGEMENT
SYSTEMS FOR U.S. SHEEP
TABLE 7-8: MANURE MANAGEMENT
SYSTEMS FOR U.S. GOATS
S'lA'lh
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. Average
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%
100%
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%
v
0%
0%
20%
5%
34%
0%
•0%
10%
3%
5%
8%
.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. Average
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%
84%
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%
16%
7-10
-------
TABLE 7-9: MANURE MANAGEMENT SYSTEMS FOR U.S. HORSES
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
U.S. Average
Paddock
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%
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%
7-11
-------
Table 7-10. U.S. Average Animal Size and VS Production
Animal Type
Feedlot Beef Cattle
Other Beef Cattle
Dairy Cattle
Swine
Poultry
Other
Steers/Heifers
Calves
Heifers
Steers
Cows
Bulls
Heifers
Cows
Market
Breeding
Layers
Broilers
Ducks
Turkeys
Sheep
Goats
Donkeys
Horses and Mules
Typical
Animal
Mass(TAM)
Ibs
915
397
794
794
1102
• 1587
903
1345
101
399
3.5
1.5
3.1
7.5
154
141
661
992
Volatile
Solids (vs)
Ibs VS/
Ib animal mass/yr
2.6
2.6
2.6
2.6
2.6
2.6
3.65
3.65
3.1
3.1
4.4
6.2
6.75
3.32
. 3.36
3.48
3.65
3.65
Table 7-11. Maximum Methane Producing Capacity for U.S. Estimates
Animal Type
Cattle
Swine
Poultry
Sheep
Goats
Horses & Mules
Category
Beef in Feedlots
Beef Not in Feedlots
Dairy
Breeder
Market
Layers
Broilers
Turkeys
Ducks
In Feedlots
Not in Feedlots
Maximum Potential
Emissions (B0)
(ft3 CHVlb-VS)
5.29
2.72
3.84
5.77
7.53
5.45
4.81
4.81
5.13
5.77
3.04
2.72 .
5.29
7-12
-------
Table 7-12. Methane Conversion Factors for U.S. Livestock Manure Systems
Pasture,
Range &
State Paddocks
Alabama
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Other Systems: Pit Storage
MCF for Liquid/Slurry. Pit
liquid/slurry. Anaerobic lag(
MCF of 10%.
l-.4%
1.4%
. 1.3%
1.2%
0.9%
0.9%
1.2%
1.5%
1.4%
0.8%
1.1%
1.0%
' 0.9%
1.1%
1.2%
1.4%
0.8%
1.1%
0.9%
0.8%
0.8%
1.4%
1.1%
0.7%
1.0%
.L2%
0.8%
1.0%
1.2%
0.9%
1.3%
0.7%
1.0%
1.4%
1.1%
0.9%
1.0%
1.3%
0.8%
1.3%
1.4%
0.9%
0.8%
1.2%
1.0%
1.2%
0.8%
0.8%
. Solid
Drylot Storage
1.9%
1.9% .
1.8%
1.4%
1.0%
1.0%
1.4%
2.4% ,
1.8% '
0.8%
1.3%
1.2%
.1.1%
1.5%
1.5%
2.1%
0.8%
1.2%
1:0%
- 0.9%
0.8%
i.9%
-1.4%
0.8%
1.1%
1.4%
0.8%
1.1%
1.3%
0.9%
1.5%
0.7%
1.1%
1.9%
1.1%
1.0%
1.1%
1.7%
0.9%
1.6%
2.1%
1.0%
0.8%
1.4%
1.0%
1.3%
0.8%
0.8%
for less than 30 days is assume
Storage for more than 30 days .
Dons are assumed to have an MC
1.4%
1.4%
1.3%
1.2%
0.9%
0.9%
1.2%
1.5%
1.4%
0.8%
1.1%
1.0%
0.9%
1.1%
1.2%
1.4%
0.8%
1.1%
0.9%
0.8%
0.8%
1.4%
1.1%
0.7%
1.0%
1.2%
0.8%
1.0%
1.2%
0.9%
1.3%
0.7%
1.0%
1.4%
1.1%
0.9%
1.0%
1.3%
0.8%
1.3%
1.4%
0.9%
0.8%
1.2%
1.0%
1.2%
0.8%
0.8%
Daily
Spread
0.4%
0.4%
0.4%
0.3%
0.2%
0.2%
0.3%
0.6%
0.4%
0.2%
0.3%
0.3%
0.2%
0.3%
0.3%
0.5%
0.2%
0.3%
0.2%
0.2%
0.2%
0.4%
0.3%
0.2%
0.2%
0.3%
0.2%
0.3%
0.3%
0.2%
0.3%
0.2%
0.2%
0.4%
0.2%
0.2%
0.2%
0.4%
0.2%
0.3%
0.5%
0.2%
0.2%
0.3%
0.2%
0.3%
0.2%
0.2%
Liquid/
Slurry
29.0%
28.9%
27.6%
21.9%
18.2%
18.5%
22.6%
38.6%
29.0%
15.5%
• 22.8%
21.5%
20.7%
24.7%
23.8%
32.5%
15.5%
21.0%
18.1%
17.0%
18.0%
29.3%
24.1%
15.8%
20.8%
22.1%
16.3%
20.6%
21.3%
18.1%
24.5%
16.8%
20.2%
28.7%
16.2%
18.7%
18.7%
27.3%
19.1%
24.8%
31.7%
17.4%
16.6%
22.5%
15.5%
21.4%
17.0%
15.9%
. have an MCF equal to 50% of the
sumed to have an MCF equal to
i' of 90%; litter and deep pit stacks an
7-13
-------
Table 7-13 Worksheet to Calculate Methane Emissions from Animal Manure
Input
Input
Input
(A)x(B)x(C)
Input
(D) x (E)
(A)
(C)
(D)
(E)
(F)
Typical Animal Volatile Total VS CH4 Producing Max. Potential
Population Mass (TAM) Solids (vs) Produced Capacity (Bo) Emissions
Animal Type (head) (Ibs/head)- (Ibs VS/lb mass) (Ibs) (cubic fl/lb-VS) (cubic ft)
Input
Input
(F)X(G)x(H)
(I) x 0.0413
Manure System
(G)
Methane Conv.
Factor (MCF)
(H)
Waste System
Usage (WS%)
. (I)
Methane
Emissions
(cubic ft)
(J)
Methane
Emissions
(Ibs)
Pasture/Range
Daily Spread
Solid Storage
Drylot
Deep Pit Stacks
Litter
Paddock
Liquid/Slurry
Anaerobic Lagoon
Pit Storage < 1 mo
Pit Storage > 1 mo
Total Methane Emissions (tons/yr):
(Sum Column (10) and divide by 2000]
7-14
-------
WORKBOOK 8
METHANE EMISSIONS FROM
FLOODED RICE FIELDS
When fields are flooded, anaerobic conditions in the soils develop, and methane is produced
through anaerobic decomposition of soil organic matter. Methane is'released primarily through the
rice plants, which act as conduits from the soil to the atmosphere. Non-flooded rice fields, such as
dry upland rice fields, do not produce significant quantities of CH4, however. Additionally,
deepwater, floating rice fields (>3.3 feet floodwater depth) are not believed to produce significant
quantities of CH4. Accordingly, only flooded, non-deepwater, rice fields are accounted for in these
calculations.
Only seven U.S. states produce significant quantities of rice: Arkansas, California, Florida,
Louisiana, Mississippi, Missouri, and Texas. Other states may skip this section of the workbook.
To estimate methane emissions from flooded rice fields, the following steps are required: 1)
obtain the required data on area harvested; 2) calculate the average number of acre-days harvested
annually (both low and high); and 3) apply an emissions rate range to the annual harvested non-
deepwater, wetland area. These steps are outlined in detail below. A more detailed description of
the methodology is provided in Discussion Section 8.
Step (1) Obtain Required Data
• Required Data. The information needed to calculate methane emissions from flooded rice
fields is the total area harvested (not including upland or deepwater rice fields) for three
consecutive years centered on the study year (e.g., to calculate 1990 emissions, data from
1989, 1990, and 1991 are needed), and the length of the growing season (both low and high).
• Data Source. State agencies responsible for overseeing the agricultural sector should be
consulted. Alternatively, rice area harvested for the major rice producing states can be found
in the U.S. Department of Agriculture's annual Crop Production report.
• Units for Reporting Data. Rice area harvested should be reported in acres, while the length
of the growing season should be in days. (Table 8-1 provides the range of flooding season
lengths by state).
Step (2) Calculate the Average Number of Acre-Days Harvested Annually
• Calculate the 3-year average area harvested for the base year.
(Area Harvested Year 1 + Area Harvested Year 2 + Area Harvested Year 3) + 3
= Average Area Harvested Base Year 2
8-1
-------
Table 8-1. Growing Season Lengths by State
State
Arkansas
California
Florida3
primary
ratoon
Louisiana3
primary
ratoon
Mississippi
Missouri
Texas3
primary
ratoon
Growing Season Length (days)
Low
75
123
90
90
75
80
60
High
100
. 153
120
120
82
100
80
a These states have a second, or "ratoon", cropping cycle which may have a
shorter flooding season than the one listed in the table. It is recommended that
the user apply the -same growing season length for both the ratoon and primary
cropping cycles.
Example The average number of acre-days harvested in a state from 1989-1991 is
calculated as follows:
Average Area Harvested
[2,988,000 (acres in 1989) + 3,146,000 (acres in 1990) + 3,102,000 (acres in 1991)] + 3
= 3,079,000 acres
Low
Average for 1990: 3,079,000 acres x 60 days/yr = 184,740,000 acre-days/yr
High
Average for 1990: 3,079,000 acres x 153 days/yr = 471,087,000 acre-days/yr
Multiply the average annual area harvested for the base year by the length of the growing
season range to obtain the average number of acre-days harvested in the base year.
8-2
-------
Average Area Harvested (acres) x Length of Growing Season (days/yr, low estimate)
= Acre-days per year (low estimate)
Area Harvested (acres) x Length of Growing Season (days/yr, high estimate)
= Acre-days per year (high estimate)
Step (3) Estimate Methane Emissions
• Multiply the number of acre-days harvested annually (both low and high) by the
corresponding endpoints of the daily emissions rate range (0.1955 - 1.035 Ibs CH4/acre/day)
to obtain the range of methane emissions from flooded rice fields.
Average # of Acre-Days/yr (low) x 0.1955 Ibs CH4/acre-day
= CH4 Emissions (low) (Ibs CH4/yr)
Average # of Acre-Days/yr (high) x 1.035 Ibs CH4/acre-day
= CH4 Emissions (high) (Ibs CH4/yr)
• Divide the results by 2000 to obtain methane emissions in tons CH4.
Example Annual methane emissions from flooded rice fields for this state in 1990 is
calculated as follows:
(a) Avg. Acre-Days Emissions Coefficient CH., Emissions
low: 184,740,000 acre-days per year x 0.1955 Ibs CH4/acre-day = 36,116,700 Ibs CH4/yr
high: 471,087,000 acre-days per year x 1.035 tbs CH4/acre-day = 487,575,000 Ibs CH4/yr
(b)
low: 36,116,700lbsCH4/yr + 2000 Ibs/ton = 18,058 tons CH4/yr
high: 487,575,000 Ibs CH4/yr + 2000 Ibs/ton = 243,788 tons CH4/yr
8-3
-------
WORKBOOK 9
EMISSIONS FROM AGRICULTURAL SOIL MANAGEMENT
Various agricultural soil management practices contribute to greenhouse gas emissions. The
use of synthetic and organic fertilizers adds nitrogen to soils, thereby increasing natural emissions of
nitrous oxide. Other agricultural soil management practices such as irrigation, tillage practices, or the
fallowing of land can also affect trace gas fluxes to and from the soil since soils are both a source and
a sink for carbon dioxide and carbon monoxide, a sink for methane, and a source of nitrous oxide.
However, there is much uncertainty about the direction and magnitude of the effects of these other
practices, so only the emissions from fertilizer use are included in the inventory at this time.
To estimate state emissions of N2O from fertilizer use, four steps should be performed: 1)
obtain the required data on fertilizer use; 2) calculate the three-year average for annual fertilizer
consumption; 3) estimate nitrous oxide emissions in units of nitrogen; and 4) convert total emissions
to units of N2O. A worksheet is provided in Table 9-2 to assist in the calculations. A more detailed
description of the method used to calculate N2O emissions is provided in Discussion Section 9.
Step (1) Obtain Required Data (Table 9-2, Columns A, B and C)
• . Required Data. The information needed to estimate N2O emissions from fertilizer use is
annual fertilizer consumption, by fertilizer type or total tons of nitrogen consumed in the
state, for three consecutive years centered on the study year (e.g., to calculate 1990 N2O
emissions, data for 1989, 1990, and 1991 are needed). A list of various fertilizer types can be
found in Table 9-1. Three years of data are recommended to avoid unusual annual variations
due to economic, climatic, or other variables.
• Data Sources. Departments within each state responsible for conducting agricultural research
and overseeing the agricultural sector should be consulted first. Additionally, state fertilizer
consumption data can be found in Fertilizer Summary Data and Commercial Fertilizers, both
published by the Tennessee Valley Authority.
• Units for Reporting Data. Fertilizer data should be reported in mass units of nitrogen (i.e.,
tons N). If fertilizer consumption is given in tons of material (as in the TVA Fertilizer
Summary Data) rather than in tons N, the total mass may be converted to nitrogen content
using the'percentages in Table 9-1.
Step (2) Calculate Average Annual Nitrogen Consumption By Fertilizer Type (Table 9-2,
Column D)
For each fertilizer type, calculate the three-year average annual consumption of nitrogen in
the fertilizer.
9-1
-------
Table 9-1. Nitrogen Content of Principal Fertilizers
MATERIAL
Nitrogen
Ammonia, Anhydrous
Ammonia, Aqua
Ammonium nitrate
Ammonium nitrate-limestone mixtures
Ammonium sulfate
Ammonium sulfate-nitrate
Calcium cyanamide
Calcium nitrate
Nitrogen solutions
Sodium nitrate
Urea
Urea-form
Phosphate
Basic slag, Open hearth
Bone meal
Phosphoric acid
Rock phosphate
Superphosphate, Normal
Superphosphate, Concentrated
Superphosphoric acid
Potash
Potassium chloride (muriate)
Potassium magnesium sulfate
Potassium sulfate
Multiple Nutrient
Ammoniated superphosphate
Ammonium phosphate-nitrate
Ammonium phosphate-sulfate
Diammonium phosphate
Monoammonium phosphate
Nitric phosphates
Nitrate of soda-potash
Potassium nitrate
Wood ashes
Blast furnace slag
Dolomite
Gypsum
Kieserite (emjeo)
Limestone
Lime-sulfur solution
Magnesium sulfate (Epsom salt)
Sulfur
% NITROGEN
82
16-25
33.5
20.5
21
26,
21
15
21-49
16
.46
38
-
2-4.5
-
-
•
'
-
'
-
-
3-6
27
13-16
16-21
11
14-22
15
13
-
•
.
-
.
-
-
-
-
Note: A dash (-) indicates that the fertilizer contains either no nitrogen or a
negligible amount of nitrogen.
9-2
-------
Example According to the TV A Fertilizer Summary Data, total U.S. consumption of
ammonium nitrate in tons of material was: 1,898,650 in 1989; 1,777,545 in 1990;
and 1,850,061 in 1991. To convert this to tons of nitrogen, multiply by the
percent N content of ammonium nitrate (33.5%),
1,898,850 tons of material x 33.5% = 636,115 tons N
1,777,545 tons of material x 33.5% = 595,478 tons N
1,850,061 tons of material x 33.5% = 619,770 tons N
Example The three-year average annual consumption for ammonium nitrate in the U.S.
from 1987-1989 is calculated as follows:
(636,115 + 595,478 + 619,770) + 3 = 617,121 tons N
Step (3) Estimate Nitrous Oxide Emissions (Table 9-2, Columns F)
• Multiply the three-year average for each fertilizer type by the appropriate emissions
coefficient. The emission coefficient is taken from U.S. EPA (1994) and is based on research
done by the U.S. Department of Agriculture (CAST, 1992). The recommended emission
coefficient is 1.17 percent or 0.0117. The amount of fertilizer consumed (synthetic nitrogen,
multiple-nutrient, and organic fertilizer, measured in mass units of nitrogen) is multiplied by
this emission coefficient. The result will be N2O emissions in units of N.
Total N2O-N Emissions (tons N2O-N) = Total Nitrogen Content of Fertilizer (tons N)
x 0.0117 (tons N2O-N/ton N applied)
• Sum across all types of fertilizers to produce the total estimate for N2O-N emissions from
fertilizer use.
Example To estimate total N2O-N emissi
emissions for the U.S. from ammonium nitrate,
^
Nitrogen Content Emissions Coefficient NoO Emissions (units of N)
617,121 tons N x 0.0117 = 7,220 tons N2O-N
Step (4) Convert to Units of N2O (Table 9-2, Column G)
• Multiply the emission estimates by 44/28 to convert them from units of N to units of N2O.
Sum across all fertilizer types to produce total N2O emissions from fertilizer use in units of
N2O.
STATES WORKBOOK
9-3
January 10, 1995
-------
Example To convert N2O-N emission estimates from ammonium nitrate [from step (3)]
into units of N2O,
7,220 tons N2O-N x 44/28 = 11,346 tons N2O
Table 9-2. Worksheet to Calculate N,O Emissions from Nitrogen Fertilizer Use
Input
A
Input
B
Input
C
Average
D
Input
E
DxE
F
E x 44/28
G
Fertilizer
Ammonium Sulphate
Ammonium Nitrate
Sodium Nitrate
Urea
Amrnoolum
Phosphate
Anhydrous Ammonia
Aqua Ammonia
Calcium Nitrate
Potassiuni Nitiate
Other
Total
Fertilizer Consumption
(tons N)
1989
: -
1990
1991
3-yr avg
-
••
.,
Emission
Factor
(% N2O-N
produced)
8.9117
0.0117
ton?
0.0117
8.0117
0.0117
«,dur
0.0117
«^H7
0.0117
N2O-N
Emissions
(tons
N20-N)
N2O
Emissions
(tons N2O)
STATES WORKBOOK
9-4
January 10, 1995
-------
WORKBOOK 10
CARBON DIOXIDE EMISSIONS FROM
FOREST MANAGEMENT AND LAND-USE CHANGE
This chapter provides methods for calculating greenhouse gas emissions from human activities
that:
• affect the amount of biomass in existing biomass stocks on forests and other lands,
without changing the way land is used (e.g., management of standing forests, urban
tree planting, logging), or
• change the way land is used (e.g., clearing forests for agricultural use or suburban
development, converting a grassland-to cropland).
The dominant gas of concern in this source category is CO2, and the methodology presented below,
as well as in Discussion Section 10, is specific to CO2. Other important greenhouse gases, including
CH4 and N2O, and photochemically important gases, including CO, NOX, and NMVOCs are also
produced from forest management and land-use change activities. However, emissions of these gases
that result from biomass burning (i.e., wood consumption for energy production) are captured in
Discussion Section 14, and emissions of these gases due to other activities (such as land flooding) are
not yet explicitly included in the methodology. Instead, they are discussed as areas for further
research in Discussion Section 10.
The fundamental basis for the methodology rests upon two linked themes: (1) the flux of CO2
to or from the atmosphere is assumed to be equal to changes in the carbon stocks of existing biomass
and soils, and (2) changes in the carbon stocks can be estimated by first establishing rates of change
in land use and then applying simple assumptions about the biological response to the land use. The
methodology is designed to be comprehensive, i.e., cover all the main land-use change and forestry
activities in the U.S., and to be feasible to implement by all states.
In estimating the effects of land use and land-use change on fluxes of greenhouse gases, it
is reasonable to stage the calculation methods so that the most important components can be
addressed first. Complexities and subtleties of the relationship of forestry and land-use change to
fluxes of CO2 and other gases can be incorporated in a consistent manner into subsequent
calculations as knowledge advances and data improve. The methodology presented here focusses on
a simple, practical, and fair procedure for determining the CO2 flux directly attributable to forest
management and land-use change activities. This procedure also accounts for the influence of past
land-use changes on the contemporary CO2 flux. It should be noted, however, that this method is
based upon many simplifying assumptions in order to allow for implementation with only minimal data
(these simplifying assumptions are discussed in detail in Discussion Section 10). At the same time,
the methodology is sufficiently flexible to accommodate users with different levels of available data,
i.e., data with different levels of complexity and at different geographic scales. States are encouraged
to apply the method in as detailed a manner as their data allow, as well as to estimate emissions from
land use activities that are not explicitly included in the method if expertise and data are sufficient.
This section is divided into three parts, each of which reflects a general category of land-use
10-1
-------
change and forest management
activities. They are (see Figure 10-1
for a breakdown of the activities
associated with each of the
categories described below):
• Changes in Forests and
Other Woody Biomass
Stocks: The most important
effects of human
interactions with existing
forests are considered in this
single broad category, which
includes commercial
management and logging for
forest products, replanting
after logging or other forest
timber removal, the harvest
of fuelwood, and the
establishment and operation
of forest plantations as well
as planting trees in urban,
suburban, or other non-
forest locations.
Figure 10-1. Land-Use Change and Forestry Activities
Covered in Method
Activities
Logging
Planting
Restocking
Urban forestry
Agroforestry
Fuelwood extraction
Permanent forest clearing
Conversion of grasslands to
cultivated lands
Shifting cultivation
Urban development
Suburban development
Parking lots
Abandonment of managed
pastureland. cropland, etc.
Classification
Changes in Forests
and Other Woody
Biomass Stocks
Forest and Grassland
Conversion
Abandonment of
Managed Lands
1.
Forest and Grassland Conversion: This category includes the conversion of forest and
grasslands to pasture, croplands, or other managed uses as well as to shopping malls, parking
lots, and suburban communities. These activities can significantly change the carbon stored
in biomass and in soils.
Abandonment of Managed Lands: Lands that had been managed previously (i.e., croplands,
pasture) and that are abandoned and allowed to regrow naturally, without any human
interference, can re-accumulate significant amounts of carbon in their biomass and soils. This
category includes these lands that are regrowing naturally into their prior grassland or forest
conditions.
CO2 FLUX FROM CHANGES IN FORESTS AND OTHER WOODY BIOMASS STOCKS
(WORKSHEET 10-1)
In this part of the method, net emissions of CO2 due to growth and harvest of woody biomass
are estimated. First, the annual growth increment of biomass in plantations, managed forests, trees
in farms, suburban areas and urban areas, and any other significant stocks of woody biomass are
estimated. Next, annual harvests of biomass, e.g., wood harvested for fuelwood, commercial timber
and other uses, are estimated. It should be noted that emissions from soil carbon are not included
in this section. This is because the effects of these activities on soil carbon are uncertain. Also, the
methodology does not include time lags associated with decay of biomass harvests.
The net carbon emitted is equal to the total harvest of carbon minus the total growth
10-2
-------
increment. If the figure is positive, then this counts as an emission of carbon, and if the figure is
negative, it counts as a removal (or uptake). Finally, the net carbon emission/uptake is expressed as
CO2. These steps in the calculation are displayed in Worksheet 10-1.
Step (1) Obtain Required Data
Required Data. The data required to calculate CO2 flux from changes in forests and other woody
biomass stocks include:
Forests and Other Woody Biomass Areas: (1) managed forests and other woody biomass
areas by type; (2) annual biomass growth rates of managed areas by type; and (3) biomass
carbon fraction.
Tree Planting: (1) number of trees planted in afforestation and other tree planting activities'
by type; (2) annual biomass growth rates of planted trees; and (3) biomass carbon fraction.
Biomass Harvest: (1) annual commercial harvest; (2) biomass conversion/expansion factor1;
(3) fuelwood harvest; (4) other wood removals; (5) biomass carbon fraction; and (6) wood
removed during forest clearing and burned as fuelwood.
Data Sources:
Forests and Other Woody Biomass Areas: The Forest Service of the U.S. Department of
Agriculture (USFS) compiles forest resource data collected from periodic surveys in each
state and Forest Service region, and publishes these data in tabular form. These tables
include information on area, volume, removals, and timber product outputs, by state,
ownership class, and species group. The most recent publications are for the years 1992
(Powell et al., 1993), 1987 (Waddell et al., 1989), and 1977 (USFS, 1982).'
Tree Planting: There are no readily available published, national statistics on non-forest tree
planting. It is recommended that states contact their State Forestry Department, particularly
the urban forestry coordinator in this department, for this information.
Biomass Harvest: There are two approaches analysts can take to estimate wood removals:
• commercial harvest statistics; and
• fuelwood consumption estimates from Workbook Section 1.
For some states, commercial statistics will give only a partial account of wood removals and
using both sources of statistics may provide the most accurate picture. Sources for
1 Commercial harvest statistics are often provided in volumetric units and only account for the
commercial portion of biomass. In this case, the harvested amounts must be adjusted in two ways to
reflect the values needed for the emissions/uptake calculations. The volume of biomass must first be
converted to mass of dry matter by applying a density. In addition, an expansion ratio must be applied to
account for non-commercial biomass (limbs, small trees, etc.) harvested with the commercial biomass and
left to decay or destroyed during processing.
10-3
-------
commercial statistics include the USFS forest resource data publications, as discussed above,
and Row and Phelps (1991).
Units for Reporting Data. Data should be reported in the following units: -
• Forests and other woody biomass areas: 103 acres
• Number of trees planted: 103 trees
• Annual biomass growth rates of forests and woody biomass areas: tons dry matter per acre
per year (t dm/acre/yr)
• Annual biomass growth rates of planted trees: ton dry matter per tree per year (t dm/tree/yr)
• Biomass carbon fraction: tons carbon per ton dry matter (t C/t dm)
• Annual commercial harvest: 103 cubic feet per year (103 ft3/yr)
• Biomass conversion/expansion factor: tons dry matter per cubic foot (t dm/ft3)
• Fuelwood harvest: 103 tons dry matter per year (103 t dm/yr)
• Other wood removed: 103 tons dry matter per year (103 t dm/yr)
• Wood removed during forest clearing and burned as fuelwood: 103 tons dry matter per year
(103 t dm/yr)
Step (2) Estimate Total Carbon Content in Annual Growth of Managed Forests and Other
Woody Biomass Areas (Worksheet 10-1, Columns A - E)
• Obtain the number of acres (in thousands of acres) for each type of managed area on which
biomass is accumulating, e.g., plantations, managed forest areas, etc. Enter this in Column
A.
• . For dispersed trees (e.g., urban tree planting, farm trees, etc.), enter the number of trees of
each type (in 103 trees) in Column A.
• For each type of forest/woody biomass area, enter the Annual Growth Rate (in tons of dry ,
matter per acre) in Column B. The default statistics in Table 10-1 or 10-6 can be used if
state data are not available.
• For other non-forest trees, enter the Annual Growth Rate in tons of dry matter per tree per
year in Column B, i.e., use the average annual growth rate per tree.
• For each type of forest/woody area, multiply the Area of Forest/Biomass Stocks by the
Annual Growth Rate to give Annual Biomass Increment in thousand tons of dry matter.
Enter the result in Column C.
• For non-forest trees, multiply the Number of Trees by the Annual Growth Rate to give
Annual Biomass Increment in thousand tons of dry matter. Enter in Column C.
• For each type of biomass stock, enter the Carbon Fraction of Dry Matter in Column D. The
default value is 0.5 for all biomass, if specific values are not available.* (See Table 1-2 of
Birdsey, 1992 (provided at the end of this chapter) for some species-specific values for the
U.S.)
• Multiply the Annual Biomass Increment by the Carbon Fraction of Dry Matter to give the
Total Carbon Uptake Increment (103 tons carbon). Enter the result in Column E.
10-4
-------
Table 10-1
Average Annual Accumulation of Dry Matter as Biomass in Plantations
Forest Types
Tropical
Temperate
Acacia spp.
Eucalyptus spp.
Tectona grandis
Pinus spp.
Pinus caribaea
Mixed Hardwoods
Mixed Fast-Growing Hardwoods
Mixed Softwoods
Douglas Fir
Loblolly Pine
Average Annual Increment in Biomass
(t dm/acre/yr)
33.6
32.5
17.9
25.8
22.4
15.2
20
32.5
13.5
9.0
Source: Derived from IPCC, 1994
Add the figures in Column E and enter the total in the Total box at the bottom of the
column.
Step (3)
Estimate the Amount of Biomass Harvested (Worksheet 10-1, Columns F - L)
Enter the annual amount of timber harvested in the state for commercial purposes and enter
it in thousands of cubic feet in Column F.
If necessary, enter the Biomass Conversion/Expansion Ratio in tons of dry matter per cubic
foot (t dm/ft3) in Column G. The default conversion ratio (or biomass density) is 16 t dm/ft
(see Table 1-2 of Birdsey, 1992 (provided at the end of this chapter) for some species-specific
densities for the U.S.). In addition, an expansion factor should be applied if the timber
harvest data do not account for all of the biomass that is destroyed during the harvest process,
e.g., limbs, small trees, etc. The following default ratios can be used: 56 t dm/ft3 for
undisturbed forests; 60.91 dm/ft3 for logged forests; and 64.11 dm/ft3 for unproductive forests
(see Table 1-1 of Birdsey, 1992 ( provided at the end of this chapter) for region- and forest
type-specific expansion factors for the U.S.). If both conversion and expansion factors are
needed, they can be combined by using ratios which are the product of the two: 28.19 t
dm/ft3 for undisturbed forests; 30.4 t dm/ft3 for logged forests; and 32 t dm/ft3 for
unproductive forests.
Multiplyathe amount of Commercial Harvest by the Biomass Conversion/Expansion Ratio (if
necessary) to give Total Biomass Removed in Commercial Harvest in thousand tons of dry
matter. Enter the result in Column H.
Enter Total Fuelwood Consumed annually (including wood for charcoal production) in
thousand tons dry matter in Column I. (This accounting should have been done in Workbook
and Discussion Sections 1).
10-5
-------
Enter the quantity of annual Total Other Wood Use in thousand tons dry matter in Column
• Add the Total Biomass Removed in Commercial Harvest (Column H) to the Total Fuelwood
Consumed (Column I) to and Total Other Wood Used (Column J) to give Gross Biomass
Consumption. Enter this result in Column K. Sum this column and enter the result in the
Totals box at the foot of the column.
• Enter Wood Removed During Forest Clearing and Burned as Fuelwood in thousand tons dry
matter (Worksheet 2, Column G) at the bottom of Column L.
• Subtract Wood Removed During Forest Clearing (Column L) from Gross Biomass Consumed
(Column K) to give Net Biomass Consumption (Column M).
Step (4) Convert Wood Harvested to Carbon Removed (Worksheet 10-1, Columns M - O)
• Enter the Carbon Fraction of the biomass in Column N (the general default value for live
biomass is 0.5 t C/t dm).
• Multiply Total Biomass Consumption (Column M) by Carbon Fraction (Column N) to give
Annual Carbon Release (in 103 tons of carbon). Enter the result in Column O.
Step (5) Estimate Net Annual Amount of Carbon Uptake or Release (Worksheet 10-1,
Columns O - Q)
• Subtract Annual Carbon Increment (Column O) from Total Carbon Released (Column E)
to give Net Annual Carbon Uptake or Emissions. Enter the result in Column P.
• Multiply the Net Annual Carbon Uptake or Emissions (Column P) by 44/12 to give Annual
CO2 Emissions (if a positive value) or Uptake (if a negative value). Enter the result in
Column Q.
2. CO2 EMISSIONS FROM FOREST AND GRASSLAND CONVERSION
(WORKSHEETS 10-2 THROUGH 10-4)
Forest and grassland conversion to permanent cropland, pasture, or suburban and urban areas
can result in the release of carbon not only from the clearing of land (Le., through decay of cleared
biomass) but also due to the disturbance of the carbon stored in the soil. It should be noted that in
some instances, some of the biomass cleared is burned as fuelwood. This burning results in emissions
of CO2 as well as CO, CH4, NOX, and N2O. The non-CO2 emissions from this source are assumed
to be accounted for in the biofuels calculations presented in Discussion Section 14. This part of the
method accounts for CO2 emissions from cleared biomass that is burned and decays. As in the
calculations for changes in forests and other woody biomass stocks, the methodology does not include
time lags associated with biomass decay. Time lags associate with soil carbon emissions, however, are
included.
Two sets of calculations are required to produce estimates of CO2 emissions due to
forest/grassland conversion:
10-6
-------
(1) Carbon released by decay or burning of net cleared aboveground biomass.
(2) Carbon released from soil (delayed emissions, occurring over a 25-year period).
The totals are added together to arrive at total carbon released. Total carbon released is then
converted to CO2 emissions. As in the previous calculations, time lags associated with biomass decay
are not included in the method. This simplifying assumption is discussed in Discussion Section 10.
Step (1) Obtain Required Data
Required Data: The following data are required to estimate emissions from forest and grassland
conversion:
• Annual forest and/or grassland areas converted by type; in the inventory year and a
25-year average
• Aboveground biomass per area of forest and/or grassland by type
• Aboveground biomass per area of replacement vegetation
• Carbon in soil per unit forest and/or grassland area by type
• Fraction of carbon released from soil following forest and grassland conversion
Data Sources: The Soil Conservation Service of the U.S. Department of Agriculture (USDA/SCS)
conducts an inventory of all non-Federal rural lands every five years, e.g., USDA/SCS (1989). This
National Resources Inventory (NRI) contains land-use change data by state for croplands,
pasturelands, rangelands, forest lands, and minor land uses. The latest NRI, for the year 1987,
contains land-cover change matrices by state for the 1982 - 1987 period. These matrices not only
provide the total change in each land-use over the period, but also the dynamics of each change (e.g.,
of the total 1982 - 1987 conversion of cropland, how much was to pastureland and how much was to
forest land). However, the NRI data only covers non-federal rural lands, so a large portion of the
U.S. forest lands are not included in this data base. The forest area data in the USFS forest resource
publications discussed in the previous section of this chapter, however, include net changes in forest
areas. Therefore, if these USFS data are used in the previous section, one has already accounted for
conversion of forest lands to other lands.
Units for Reporting Data: Data should be collected in the following units:
• Annual area of forest and grassland converted in the inventory year and averaged over 25
years: 103 acres per year
• Aboveground biomass: tons dry matter per acre (t dm/acre)
• Carbon in soil: tons carbon per acre (t C/acre)
Step (2) Estimate CO2 Released by Decay of Net Cleared Biomass (Worksheet 10-2, Columns
A - I)
• Enter the figures for Annual Area Converted (in inventory year) in thousand acres per year
for each forest/grassland type in Column A.
• Enter the Aboveground Biomass Density in tons of dry matter per acre (t dm/acre) before
conversion in Column B. Default values are provided in'Tables 10-2 and 10-3.
10-7
-------
Table 10-2
Aboveground Dry Matter in Tropical Forests
(t dm/acre)
Moist Forest
Primary
515.6
Secondary
425.9
Seasonal Forest
Primary
313.8
Secondary
269
Dry Forest
Primary
134.5
Secondary
56
Source: Derived from IPCC, 1994
Table 10-3
Aboveground Dry Matter in Temperate and Boreal Forests
(t dm/acre)
Primary
Secondary
Temperate Forests
Evergreen
661.3
493.2
Deciduous
560.4 .
392.3
Boreal Forests
369.8
269
Source: Derived from IPCC, 1994
Enter the Aboveground Biomass Density in tons of dry matter per acre (t dm/acre) after
conversion in Column C. This figure includes any biomass not fully cleared (default value =
0) and the biomass regrowth in agricultural use (the default value is 22.4 tons dry matter per
acre) or other use subsequent to clearing.
Subtract the value in Column C from the value in Column B to produce Net Change in
Biomass Density in tons of dry matter per acre. Enter the results in Column D.
Multiply the Annual Area Converted (Column A) by the Net Change in Biomass Density
(Column D) to calculate the Annual Loss of Biomass (aboveground) for each forest/grassland
type in thousand tons of dry matter. Enter the results in Column E.
Enter the Fraction of Biomass Used as Fuelwood in Column F.
Multiply Fraction of Biomass Used as Fuelwood (Column F) by the Average Annual Loss of
Biomass (Column E) to determine Amount of Annual Loss of Biomass Used as Fuelwood
in thousand tons dry matter. Enter this result in Column G. (This figure is used in Step (3)
of the calculations for changes in forests and woody biomass stocks).
Enter the Carbon Fraction in Aboveground Biomass in Column H (default fraction 0.5 t C/t
dm).
Multiply the Annual Loss of Biomass (Column E) by the Carbon Fraction (Column H) to
10-8
-------
calculate Carbon Released from Loss of Aboveground Biomass. Enter the figures in Column
I.
Add the figures in Column I and enter the total in the Subtotal box at the bottom of the
column.
Step (3)
Estimate Carbon Released by Soil (Worksheet 10-3, Columns A - E)
Enter the Average Annual Forest/Grassland Converted over the last 25 years in thousand
acres per year in Column A.
Enter the Soil Carbon Content Before Conversion by forest or grassland type in Column B.
See Table 10-4 for forest soil defaults. Defaults for grasslands are 134.5 tons/acre for tropical
zones and 156.9 tons/acre for temperate zones.
Table 10-4
Carbon in Forest Soils
(tons C/acre)
Forest Type
Tropical
N
Temperate
Primary
Secondary
Boreal
Primary
Secondary
Moist
257.8
Evergreen
300.4
269.0
461.8
414.7
Seasonal
224.2
Deciduous
300.4
269.0
'
Dry
134.5
-
;
-•
!
Source: Derived from IPCC, 1994
Note: See Table 1-3 of Birdsey (1992) for region-specific values of forest soil carbon in the U.S.
Multiply the Average Annual Forest/Grassland Converted (Column A) by the Carbon
Content of Soil Before Conversion (Column B) to calculate the Total Annual Potential Soil
Carbon Loss in thousand tons carbon per year. Enter the result in Column C.
Enter the Fraction of Carbon Released over 25 years in Column D (default fraction 0.5).
Multiply the Total Annual Potential Soil Carbon Losses by the Fraction of Carbon Released
to give Carbon Release from Soil in thousand tons carbon per year. Enter the result in
Column E.
Add the totals for each forest/grassland type and enter the total in the Subtotal box at the
bottom of the column.
10-9
-------
Step (4) Estimate Total CO2 Emissions from Forest and Grassland Conversion (Worksheet
10-4, Columns A - D)
• Enter the Emissions from Biomass Loss (contained in the Subtotal box of Column I in
Worksheet 10-2) in Column A.
• Enter Long-Term Emissions from Soil Carbon (contained in the Subtotal box of Column E
in Worksheet 10-3) in Column B.
• Add the Figures in Columns A and B to Calculate Total Annual Carbon Release (in the
inventory year from clearing over a 25 year period). Enter the result in Column C.
• Multiply the Total Annual Carbon Release by 44/12 to convert it into the Total Annual CO2
Release. Enter the result in Column D.
3. ABANDONMENT OF MANAGED LANDS
(WORKSHEET 10-5)
This section deals with emissions/uptake from the abandonment of managed lands. Managed
lands include:
• cultivated lands, and
• pasture (e.g., lands used for grazing animals).
Carbon accumulation on abandoned lands is sensitive to the type of natural ecosystem (forest type
or grasslands) which is regrowing. Therefore, data on abandoned lands regrowing should be obtained
by type. For lands that are growing into grasslands, the default assumption is that net accumulation
of aboveground biomass is zero. Only soil carbon is calculated in that case. Also, because regrowth
rates usually decline after a time, the periods considered are land abandoned during the 20 years prior
to the inventory year (i.e., between 1970 and 1990); and land abandoned between 20 and 100 years
prior to the inventory year (Le., between 1890 and 1970).
When managed lands are abandoned, carbon may or may not re-accumulate on the land.
Abandoned areas therefore are split into those which re-accumulate carbon and those which, do not
regrow or which continue to degrade. Only natural lands that are regrowing are explicitly included
in the calculations since lands that do not regrow do not accumulate carbon and abandoned lands that
degrade are not believed to be a significant source of emissions. However, if users of the method
believe that degrading lands contribute significantly to emissions, and data are available with which
to estimate emissions, degrading lands can be included in the calculations.
Four sets of calculations are used to produce estimates of CO2 uptake from biomass regrowth
and soils. They relate to the quantity of land abandoned and the length of time for which it has been
abandoned:
• Annual carbon uptake in aboveground biomass on land abandoned in the last twenty
years.
• Annual, carbon uptake in soils on land abandoned in the last twenty years.
10-10
-------
• Annual carbon uptake in aboveground biomass on land abandoned between twenty
and a hundred years before inventory year (optional step, only complete if data are
readily available).
• Annual carbon uptake in soils on land abandoned between twenty and a hundred
years before inventory year (optional step, only complete if data are readily available).
These are then totaled and the carbon uptake is converted into CO2 removal.
Step (1) Obtain Required Data
Required Data. To calculate uptake from abandoned lands, the following data are necessary:
For Years Between 1970 and 1990: (1) total area abandoned during last 20 years that is
regenerating; (2) annual average biomass accumulation per unit area regenerating; (3) average
annual soil C accumulation per unit area regenerating; and (4) the carbon fraction of
replacement biomass.
For Years Between 1890 and 1970 (optional): (1) total area abandoned between 20 and 100
years that is regenerating; (2) average annual biomass accumulation per unit area
regenerating; (3) average annual soil C accumulation per unit area regenerating; and (4) the
carbon fraction of replacement biomass.
Data Source. There are no readily available national statistics with which to estimate fluxes from this
source, although the NRI data that were discussed in the previous section may be useful. States
could contact their SCS State offices to obtain detailed state-level information.
Units for Reporting Data. Data should be reported in the following units:
For Years Between 1970 and 1990:
• Total area abandoned during last 20 years that is regenerating in thousand acres;
• . Annual average biomass accumulation per unit area regenerating in tons of dry matter per
acre per year (t dm/acre/yr);
• Average annual soil C accumulation per unit area regenerating in tons of carbon per acre per
year (t C/acre/yr);
• Carbon fraction of replacement biomass in tons of carbon per ton of dry matter (t C/t dm).
For Years Between 1890 and 1970 (optional):
• Total area abandoned between 20 and 100 years that is regenerating in thousand acres;
• Average annual biomass accumulation per unit area regenerating in tons of dry matter per
acre per year (t dm/acre/yr);
• Average annual soil C accumulation per unit area regenerating in tons of carbon per acre per
year (t C/acre/yr); and
• Carbon fraction of replacement biomass in tons of carbon per ton of dry matter (t C/t dm).
10-11
-------
Step (2) Calculate Annual Carbon Uptake in Aboveground Biomass (Land Abandoned in the
Last Twenty Years) (Worksheet 10-5, Columns A - E)
• Enter the Total Area Abandoned during the last twenty years that is regrowing (in 103 acres)
in Column A. ' (
• Enter the Annual Rate of Aboveground Biomass Growth (in tons dry matter per acre per
year) in Column B. See Table 10-5 for defaults.
Table 10-5
Average Annual Biomass Uptake by Natural Regeneration
(t dm/acre)
Region
Tropical
Forest Types
Moist Forests
0-20 yrs
'17.9
20-100 yrs
2.0
Seasonal Forests
0-20 yrs
11.2
20-100 yrs
1.1
Dry Forests
0-20 yrs
9.0
20-100 yrs
0.56
Note: Growth rates are derived by assuming that tropical forests regrow to 70 percent of undisturbed
forest biomass in the first twenty years. All forests are assumed to regrow to 100 percent of undisturbed
forest biomass in 100 years. Assumptions on the rates of growth in different time periods are derived
from Brown and Lugo, 1990.
Temperate
Evergreen
Deciduous
Boreal
0-20 yrs
6.7
4.5
2.24
20-100 yrs
6.7
4.5
2.24
•.
>
Source: Derived from IPCC, 1994
Note: Temperate and boreal forests actually require considerably longer than 100 years to reach
the biomass density of a fully mature system. Harmon et al. (1990), for example, report
carefully designed simulations indicating that a 100-year old stand of douglas fir would contain
only a little over half the biomass of a 450-year old growth stand of the same 'species. There is
also evidence that growth rates in temperate and boreal systems are more nearly linear over
different age periods than is the case for tropical systems. Nabuurs and Mohren (1993) suggest
that growth rates for several different species in temperate and boreal zones rise slowly and peak
at ages of 30 - 55 years and decline slowly thereafter. This suggests that using the same default
values for 0-20 years and 20-100 years may be a reasonable first approximation. Nabuurs and
Mohren (1990) also illustrate that growth rates may vary as much as a factor of ten for stands 'of
the same species and age, depending on site-specific conditions.
Multiply the Total Area Abandoned and Regrowing (Column A) by the Annual Rate of
Aboveground Biomass Growth (Column B) to give the Annual Aboveground Biomass Growth
(in 10 tons dry matter). Enter the result in Column C.
Enter the Carbon Fraction of Aboveground Biomass in Column D (Default is 0.5 t C/t dm)
Multiply Annual Aboveground Biomass Growth (Column C) by the Carbon Fraction of
Aboveground Biomass (Column D) to give the Annual Carbon Uptake in Aboveground
Biomass. Enter the result in Column E. ' .
10-12
-------
• Add the figures in Column E and enter the total in the Subtotal box at the bottom of the
column.
Step (3) Calculate Annual Carbon Uptake in Soils (Land Abandoned in Last Twenty Years)
(Worksheet 10-6, Columns F - G)
• Enter Annual Rate of Uptake of Carbon in Soils (in tons of carbon per acre per year) in
, Column F. Default values for soil carbon in temperate and boreal forests are provided in
Table 10-6. No values are available for tropical systems or grasslands.
Table 10-6
Annual Soil Carbon Accumulation in Temperate and Boreal Forests
(tons C/acr~ yr)
Temperate
Evergreen
2.9
Deciduous
2.9
Boreal
4.5
Source: Derived from IPCC (1994).
• Multiply the Total Area Abandoned and Regrowing (Column A) by the Annual rate of
Uptake of Carbon in Soils (Column F) to give the Total Annual Carbon Uptake in Soils (in
10 tons carbon per year). Enter the results in Column G.
• Add the figures in Column G and enter the total in the Subtotal box at the bottom of the
column. ,
Step (4) Calculate Annual Carbon Uptake in Aboveground Biomass (Land Abandoned
Between Twenty and a Hundred Years) (Worksheet 10-6, Columns H - L)
(Optional)
• Enter the Total Area Abandoned for twenty to a hundred years (in 103 acres) in Column H.
• Enter the Annual Rate of Aboveground Biomass Growth (in tons of dry matter per acre per
year) in Column I. See Table 10-6 for default values.
• Multiply the Total Area Abandoned (Column H) by the Annual Rate of Aboveground
Biomass Growth (Column I) to give the Annual Aboveground Biomass Growth (in 103 tons
dry matter per year). Enter the result in Column J.
• Enter the Carbon Fraction of Aboveground Biomass in Column K (default fraction 0.5 t C/t
dm). .
• Multiply the Annual Aboveground Biomass Growth (Column J) by the Carbon Fraction of
Aboveground Biomass (Column K) to give the Annual Carbon Uptake in Aboveground
Biomass. Enter the result in Column L.
10-13
-------
• Add the figures in Column L and enter the total in the Subtotal box at the bottom of the
column.
Step (5) Calculate Annual Carbon Uptake in Soils (Land Abandoned between Twenty and a
Hundred Years) (Worksheet 10-7, Columns M and N)
(Optional)
• Enter the Annual Rate of Uptake of Carbon in Soils (in tons of carbon per acre per year)
in Column M. Default values are 0.5 times the values in Table 10-6.
• Multiply the Total Area Abandoned (Column H) by the Annual Rate of Uptake of Carbon
in Soils (Column M) to give the Total Annual Carbon Uptake in Soils (in 103 tons carbon
per year). Enter the results in Column N.
• Add the figures in Column N and enter the total in the Subtotal box at the bottom of the
column.
Step (6) Calculate Total CO2 Uptake from Abandoned Lands (Worksheet 10-7, Columns E,
G, L, N, O and P)
• Add the subtotals from Columns A, G, L and N and enter the Total Carbon Uptake from
Abandoned Lands in Column O.
• Multiply the Total Carbon Uptake by 44/12 to give Total CO2 Uptake from the abandonment
of managed lands. Enter the result in Column P. For consistency with other emission/uptake
categories, it is necessary to reverse the sign of these results, so that CO2 uptake by
abandoned lands is expressed as a negative value.
4. CO2 EMISSIONS/UPTAKE FROM ALL FOREST MANAGEMENT AND LAND-USE ACTIVITIES
(WORKSHEET 10-6)
• Enter net CO2 emissions/uptake from changes in forests and woody biomass stocks (figure
from Worksheet 10-1, Column Q) in Column A (in 103 tons CO2/yr).
• Enter net CO2 emissions from forest and grassland conversion (figure from Worksheet 10-4,
Column D) in Column B (in 103 tons CO2/yr).
• Enter net CO2 emissions/uptake from abandoned lands (figure from Worksheet 10-5, Column
P) in Column C (in 103 tons CO2/yr).
• Sum Columns A, B, and C to obtain net CO2 Emissions/Uptake from all forest management
and land-use activities in a state. Enter the result in Column D (in 103 tons CO2/yr). If the
figure is positive, then this source category is counted as a net emission of CO2. If the figure
is negative, then this source category is counted as a net uptake of CO2 and can be subtracted
from the total amount of CO2 emitted in a state.
10-14
-------
Worksheet 10-1: Changes in Forests and Woody Biomass Stock
Type
Column A
Area of Biomass/Forest
Stocks
(103 acres)
Column B
Annual Growth Rate
(t dm/acre/tyr)
(AxB)
Column C
Annual Biomass Increment
(1031 dm/yr)
Column D
Carbon Fraction of Dry
Matter
(t C/t dm)
(CxU)
Column E
Tola! Carbon Uptake
Increment
(103t C/yr)
<
I
Column A
Number of Trees
(K^s of trees)
1
-
Column B
Annual Growth
Rate
(t dm/tree/yr)
Follow the Column
Headings Above
-
Total;
-------
Worksheet 10-1: Changes in Forests and Woody Biomass Stocks (Continued)
(F x G) (Column G, (H + 1 + J) (K - L)
Harvest Categories Column F Column G Column H Worksheet 10-2) Column J Column K Column L Column M
Amount of Biomass Total Biomass Column 1 Total Other Gross Biomass Wood Removed Net Biomass
Commercial . Conversion/ Removed in Fuelwbod Wood Used Consumed from Forest Consumption
Timber Expansion Commercial Consumed (103tdm/yr) (I03l dm/yr) Clearing (103 t dm/yr)
Harvested Ratio Harvest (103 1 dm/yr) (103t dm/yr)
(103ft3/yr) (t dm/ft3) (103 1 dm/yr) '
~
Totals:
-
?
' %
10-16
-------
Worksheet 10-1: Changes in Forests and Woody Biomass Stocks (Continued)
Column N
Carbon Fraction of Dry Matter
(t C/t dm)
(M x N)
Column O
Annual Carbon Released
(103t C/yr)
(O - E)
Column P
Net Annual Carbon Uptake or Release
(I03 t C/yr)
(Px44/l2)
Column Q
Annual CO, Emissions or Uptake
(HI3 t CO,/yr)
-------
Worksheet 10-2: Forest and Grassland Conversion
Lund Types
Column A
Annual
Area
Converted
no3
i1"
acres^r)
Column B
Above-
ground
Biomass
Density
Before
Conversion
(t dm/
acre)
Column C
Above-
ground
Biomass
Density
Alter
Conversion
(t dm/
acre)
(B-C)
Column D
Net
Change in
Biomass
Density
(t dm/
acre)
(AxD)
Column E
Annual Loss
of Above-
ground
Biomass
(103 1 dm/yr)
Column F
Fraction
of
Biomass
Used as
Fuelwood
(ExF)
Column G
Amount of
Annual Loss
of Biomass
Used as
Fuelwood
(103 t
dm/yr)
Column H
Carbon
Fraction in
Above-
ground
Biomass
(t C/t dm)
(E x H)
Column I
Carbon
Released
from Loss of
Above-
ground
Biomass
(103t C/yr)
Tropical.
Temperate
Boreal
Grassland
Other
Moist
Forest
Seasonal
Forests
Dry Forests
Evergreen
Deciduous
Primary
Secondary
Primary
Secondary
Primary
Secondary
Primary
Degraded
Primary
Secondary
Primary
Secondary
'
• -
•
""
\
Subtotal:
10-18
-------
Worksheet 10-3: Forest and Grassland Conversion
Land Types
Column A
Average Annual
Forest/Grassland
Converted
(25-year average)
(103 acres/yr)
Column B
Carbon Content
of Soil Before
Conversion
(t C/acre)
(AxB)
Column C
Total Annual
Potential Soil
Carbon Losses
(103t C/yr)
Column I)
Fraction of
Carbon Released
over 25 Years
Column E
Carbon Released
from Soil
(103t C/yr)
Tropical
Temperate
Boreal
Grassland
Other
'
Moist Forest
Seasonal Forests
Dry Forests
Evergreen
Deciduous
Primary
Secondary
Primary
Secondary
Primary
Secondary
Primary
Degraded
Primary
Secondary
Primary
Secondary
-
Subtotal:
-
-------
Worksheet 10-4: Forest and Grassland Conversion
Column A
Emissions from Biomass Loss
(103tC/yr)
(10-year average)
Column B
Long-Term Emissions from Soil
. (103t C/yr)
(25-year average)
(A +B)
Column C
Total Annual Carbon Release
(103 t C/yr)
(Cx 44/12)
Column D
Toial Annual CO2 Release
(103tC02/yr)
10-20
-------
Worksheet 10-5: Abandoned Lands
Kegrowth of Land Type
Column A
20 Year Total Area
Abandoned and
Regrowing
(103 acres)
Column B ,
Annual Rate of
Aboveground Biomass
Growth
(t dm/acretyr)
(AxB)
Column C
Annual Aboveground
Biomass Growth
(103 t dm)
Column D
' Carbon Fraction of
Aboveground Biomass
(t C/t dm)
(CxD)
Column E
Annual Carbon Uptake
in Aboveground
Biomass, < 21)
(103iC7yr)
Tropical Forests
Temperate Forests
Boreal Forests
Grasslands
Other
Moist
Seasonal
Dry
Evergreen
Deciduous
-
;
Subtotal;
-------
Worksheet 10-5: Abandoned Lands (Continued)
/n .. .. (Optional) . (Optional) (Optional)
(A X F) «»>"°"<"> <°<«»n«> (JXK/
Column F Column G Column I r / 1 Column K Column L
. , , . „, Annual Toial Annual . ""* Annual Rale of A . ° ""'" , Carbon Annual Carbon
Regrowth of Land Type ,, . c /-,.,!, Total Area A. , Abovearound „
6 Uptake of Carbon Uptake ... . Aboveground „. e Inaction ol Uptake in
„ . . c- •, Abandoned, „. ° Biomass . . _, '
Carbon in in Soils, _.. _ Biomass „ . Aboveground Aboveground
Soils <20yrs riO» acnSf Gr°Wth no^Tm/vr^ Biomass Biomass, 20 - 100 yrs
(tC/acre/yr) (103 1 C/acre/yr) ( ; (t dm/acre/yr) I'uium/yrj (, C/t dm) (103 1 C/yr)
Tropical
I7orests
Temperate
Forests
Boreal
Forests
Grasslands
Other
'
Moist
Seasonal
Dry
Evergreen
Deciduous
Subtotal:
-
Subtotal:
10-22
-------
Worksheet 10-5: Abandoned Lands (Continued)
Kegrowth of Land Type
(Optional)
Column M
Annual Rate of
Carbon Uptake
(t C/acres/yr)
(Optional)
(HxM)
Column N
Total Annual
Carbon Uptake in
Soils,
20 - 100 yrs
(103 t C/acre/yr)
(E + G + L + N)
Column O
Total Carbon
Uptake from
Abandoned Lands
(103tC/yr)
(O x 44/12)
Column P
Total Carbon Dioxide
Uptake
(103t C0,/yr)
Tropical
Forests
Temperate
Forests
Boreal
Forests
Grasslands
Other
Moist
Seasonal
Dry
Evergreen
Deciduous
Subtotal:
!•
-------
Worksheet 10-6: Total CO, Emissions/Uptake from Forest Management and Land-Use Activities
(Column Q, Worksheet 10-1)
Column A
Net CO2 Emissions/Uptake from Changes
in Forests and Woody Biomass Stocks
(1031 CO2/yr)
(Column U, Worksheet 10-4)
Column B
Net CO, Emissions from Forest and
Grassland Conversion
(1031 CO2/yr)
(Column P, Worksheet 10-5)
Column C
Net CO2 Emissions/Uptake'from
Abandoned Lands
(103t C02/yr)
(A + B + C)
Column I)
Net CO2 Emissions/Uptake from All Foresi
Management and Land-Use Activities
(103tC02/yr)
10-24
-------
TABLES FROM BIRDSEY (1992)
-------
Table 1.1 —Ratio of total volume' to merchantable volume2
Above-ground
ratio3
Region
Southeast
South Central
Northeast
Mid Atlantic
North Central
Central
Rocky Mountain
Pacific Coast
Softwood
1.408
1.495
1.820
1.820
2.087
2.159
1.898
1.410
Hardwood
1.793
2.304
1.808
1.808
2.043
2.240
1.871
1.926
Below-ground
proportion4
Softwood .
.163
.163
..170
.170
.170
.170 .
.158
.158
Hardwood
.197
.1971
.155
.155
.155
.155
.155
.155 .
Ratio5
Softwood
1.682
.7862
2.193
2.193
2.514
2.601
2.254
1.675
Hardwood
2.233
.869
2.140
2.140
2.418
2.651
2.214
2.279
1 Volume of all above- and below-ground tree biomass for all live and dead trees, including main stem, branches and twigs,
foliage, bark, roots, and root bark.
2 The gross volume of the central stem from a 1-foot stump to a minimum 4.0 inch top diameter outside bark, or to the point
where the central stem breaks into limbs; less deductions for rot, roughness, or poor form; for live trees of commercial
species at least 5.0 inches d.b.h., and meeting specified standards of quality.
3 The ratio of total above-ground tree biomass to merchantable tree biomass from Cost and others (1990) and other Forest
Service reports.
4 The proportion of total above- and below-ground biomass below the ground (Koch 1989).
5 The ratio of total volume to merchantable volume = data column 1 or 2 adjusted for the below-ground proportion (e.g., col. 5 ••
col. 1 + [1 - col. 3].
10-26
-------
Table 1.2—Factors to convert tree volume (cubic feet) to carbon (pounds)
Region
Southeast
and
South Central
Northeast
and
Mid-Atlantic
North Central
and
Central
Rocky Mountain
and
Pacific Coast
Specific gravity1
Forest
type Softwood
Pines
Oak-hickory
Oak-pine
Bottomland
hardwoods
Pines
Spruce-fir
Oak-hickory
Maple-beech-
birch
Bottomland
hardwoods
Pines
Spruce-fir
Oak-hickory
Maple-beech
Aspen-birch
Bottomland
hardwoods
Douglas-fir
Ponderosa
pine
Fir-spruce
Hemlock-
Sitka sp. .
Lodgepole
pine
Larch
Redwoods
Hardwoods
.510
.536
.523
,460
.378
' .369
.374
.384
,
.460
.421
.351
.416
.372
.370
.460
.473
.416
.349
.434
.423
.508
.416
.424
Hardwood
.639
.639
.639
.580
.543
.525
.636
.600
.580
.530
.480
.632
.576
.465
.580
.380
.380
.380
.433
.380
.433
.580
.384
Percent carbon^
Softwood Hardwood
.531
.531
.531
.531
.521
.521
.521
.521
.521 •
.521
-.521
.521
.521
.521
.521
.512
.512
.512
.512
.512
.512
.512
.512
.497
.479
.497
.497
.498
.498
.498
.498
.498
.498
.498
.498
.498
.498
.498
.496
.496
.496
.496
.496
.496
.496
.496
Factor^
Softwood Hardwood
16.90
17.76
17.33
15.24
12.29
12.00
12.16
12.48
14.96
13.69
11.41
13.52
12.09
12.03
14.96
15.11
13.29
9.80
12.17
11.86
14.26
11.68
11.90
19.82
19.82
19.82
"?.99
16.87
16.31
19.76
18.65
17.99
16.47
14.92
19.64
17.90
14.45
17.99
11.76
11.76
10.67
12.16
10.67
12.16
16.29
10.77
' Weighted average specific gravity of the three most common (in terms of volume) softwood or hardwood species within the
forest type.
.2 From Koch (1989).
3 Factor =. specific gravity times the weight of a cubic foot of water (62.4 Ibs) times percent carbon.
10-27
-------
Table 1.3. Estimates of organic soil carbon in relatively undisturbed secondary forests in the United States, by region*
Region
Southeast
South Central
Northeast
Mid-Atlantic •
North Central
Central
Rocky Mountain
Pacific Coast
Soil carbon
(Kg/m2) ' (Lbs/ac)
7.74
7.58'
16.21
11.56
13.09
8.33
8.02
9.77
69,044
67,626
144,703
103,173
116,791
74,302
71,571
87,191
Data from Post and others (1982).
Table 1.4—Estimates of organic matter and carbon on the forest floor1 by region and forest type
Region
Southeast
South Central
Northeast and
Mid-Atlantic
North Central
and Central
Forest type
.
Pines
Oak-pine
Oak-hickory
Bottomland hardwood
Pine '
Oak-pine
Oak-hickory
Bottomland hardwood
Pines
Spruce-fir
Hardwoods
Pines
Spruce-fir
Oak-hickory and
Organic
matter2
(Kg/ha)
20,026
15,132
10,237
1 1 ,480
20,026
16,375
12,723
11,480
44,574
44,693
32,207
44,574
44,693
' 23,282
Carbon3
(Lbs/ac)
10,361
7.829
5,296
5,939
10,361
8,472
6,582
5,939
23,061
23,122
16,663
23,061
23,122
. 12,045
Rocky Mountain and
Pacific Coast
bottomland hardwoods
Maple-beech and 32,207
Aspen-birch
Douglas - fir, Redwoods, 44,574
Larch, Ponderosa pine
Fir-spruce 88,520
Lodgepole pine 25,922
Hemlock-Sitka spruce 27,490.
Hardwoods 32,207
16,663
23,061
45,797
13,411
14,222
16,663
1 All dead organic matter above the mineral soil horizons, including litter, humus, and other woody debris (excludes standing
dead trees).
2 Most entries from Vogt and others (1986), based on summaries of ecological studies grouped by broad forest ecosystem (e.g.,
warm temperate deciduous).
3 Carbon (Ibs/ac) = organic matter (kg/ha) x .58 (percent carbon) x .892.
10-28
-------
WORKBOOK 11
GREENHOUSE GAS EMISSIONS FROM BURNING OF
AGRICULTURAL CROP WASTES
In some parts of the U.S., agricultural crop wastes are burned in the field to clear remaining
straw and stubble after harvest and to prepare the field for the next cropping cycle. When crop
residues are burned, a number of greenhouse gases are released, including carbon dioxide, methane,
carbon monoxide, nitrous oxide, and oxides of nitrogen. However, crop residue burning is not
thought to be a net source of carbon dioxid^e because the carbon dioxide released during burning is
reabsorbed by crop regrowth during the next growing season. It is, however, thought to be a net
source of these other gases.
.To estimate emissions of CH4, N2O, CO, and NOX from burning of agricultural wastes, the
following general steps are necessary: 1) obtain the required data for crops whose waste is commonly
burned; 2) estimate the total amount of carbon burned; and 3) calculate emissions based on the
amount of CO2 released and on a range of emission ratios. These steps are outlined in detail below.
A more detailed description of the methodology is provided in the discussion section on agricultural
crop wastes. Greenhouse gas emissions from burning crop residues for energy production should be
estimated as part of biomass material used as energy; this issue is addressed in the CO2 from energy
discussion section.
Step (1) Obtain Required Data
• Required Data. The information needed to estimate greenhouse gas emissions from burning
of agricultural wastes is the annual production of crops with residues that are commonly.
burned over three consecutive years (e.g., to calculate 1990 emissions, data from 1989, 1990,
and 1991 are needed).
• Data Source. State agencies responsible for overseeing the agricultural sector should be
consulted first. Additionally, annual crop production data can be found in the USDA's Crop
Production or in the U.S. Department of Commerce's Census of Agriculture.
• Units for Reporting Data. Annual crop production should be reported in pounds. If
production data are reported in hundred weight (CWT), multiply by 100 to convert to pounds.
If data are reported in bushels, the conversion factors provided in Table 11-1 may be used
to convert to pounds.
11-1
-------
Table 11-1. Conversion Factors for Selected Crops
Crop
Wheat
Barley
Corn
Oats
Rye
Rice
Millet
Sorghum
Conversion
Factor
(Ibs/bu)
60
48
56
32
56
' 45
48-60
60
Crop
Pea
Bean
Soybeans
Potatoes
Feedbeet .
Sugarbeet
Artichoke
Peanut .
Conversion
Factor
(Ibs/bu)
60
60
60
60
50
50'
50
• 17-25
Example
1989:
1990:
1991:
3-yr average
According to the USDA's Crop Production 1990 Summary and Crop Production
1992 Summary, total U.S. wheat production in 1989, 1990, and 1991 was
2,036,618,000 bushels, 2,736,428,000 bushels, and 1,981,139,000 bushels,
respectively.
2,036,618,000 bu x 60 Ibs/bu = 122,197,080,000 pounds
2,736,428,000 bu x 60 Ibs/bu = 164,185,680,000 pounds
1,981,139,000 bu x 60 Ibs/bu = 118,868,340,000 pounds
[ 122,197,080,000 Ibs + 164,185,680,000 Ibs + 118,868,340,000 Ibs] + 3 =
135,083,700,000 Ibs
Step (2) Calculate the Amount of Dry Matter Burned (Table 11-2, Columns A-F)
• For each crop, calculate the amount of dry matter burned. Table 11-2 is provided to assist
the user with this step. In column A, enter the amount of crop produced (in pounds, by crop
type). Using the default data provided in Table 11-2, multiply columns A-E to obtain pounds
of dry matter burned.
Amount of Dry Matter Burned (Ibs) = Amount of Crop Produced (Ibs) x Residue/Crop Ratio
x Fraction of Residue Burned in situ (%) x Dry Matter Content of the Residue (%) x
Fraction Burned (%)
11-2
-------
Example The amount of residue from U.S. wheat production available for combustion in
1990 is calculated as follows:
135,083,700,000 Ibs x 1.3 Ibs residue/lb crop product x 0.10 residue burned in situ* 0.911
dry matter content x 0.93 fraction burned = 14,878,105,210 Ibs
Step (3) Calculate Total Carbon Burned (Table 11-2 , Columns G-J)
• For each crop, take the amount of dry matter (DM) burned (estimated in step (2) - column
F) and enter it in column G of Table 11-2. Next, multiply the amount of DM burned by the
fraction of carbon contained in the fuel to obtain total amount of C burned. Carbon contents
for selected crop residues are presented in Table 11-2. An average value of 0.45 Ibs C/lb dry
matter can be used if data are not available.
. Dry Matter Burned (Ibs) x Carbon Content of the Residue (Ibs C/lb dm) = Total Carbon
Burned (Ibs) . , '
Example The total amount of carbon burned from U.S. wheat residue in 1990 is
calculated as follows:
14,878,105,210 Ibs dm X 0.4853 (Ibs C/lb dm) = 7,220,344,458 Ibs C
Step (4) Estimate Emissions of CH4 and CO (Tables 11-2, Columns G-M)
• For each crop, multiply the amount of carbon burned (column I) by the fraction oxidized, 88
percent (column J), to obtain the amount of carbon dioxide released instantaneously in units
of carbon (columns I x J).
Total Carbon Burned (Ibs C) x 88% (Fraction Oxidized) = Amount of CO2 Released (Ibs
CO2-C)
i
• For each crop, multiply the amount of CO2 released in units of carbon by the emission ratios
of CH4 (column P) and CO (column R) relative to CO2-C (see Table 11-2, columns P and
R) to obtain emissions of CH4 and CO in units of carbon.
Amount of CO2 Released (Ibs CO2-C) x (0.003) = CH4 Emissions (Ibs CH4-C)
Amount of CO2 Released (Ibs CO2-C) x (0.06) = CO Emissions (Ibs CO-C)
11-3
-------
Example CH4-C and CO-C emissions from burning of residue from U.S. wheat production
in 1990 is calculated as follows:
Carbon Oxidized: 7,220,344,458 Ibs C x 88% = 6,353,903,123 Ibs CO2-C
CH4-C Emissions: 6,353,903,123 Ibs CO2-C x 0.003 = 19,061,709 Ibs CH4-C
CO-C Emissions: x 6,353,903,123 Ibs CO2-C X 0.06 = 381,234,187 Ibs CO-C .
Step (5) Estimate Nitrogen Content of the Dry Matter (Table 11-2, Columns I, J, and L)
• For each crop, multiply the amount of carbon burned by the fraction oxidized and the
nitrogen to carbon content of the fuel. Nitrogen to carbon ratios for selected crop residues
are presented in Table 11-2, column L. An average value of 0.23 Ibs N/lb dry matter can be
used if data are not available.
Carbon Burned (Ibs C) x Fraction Oxidized (%) x Nitrogen/Carbon (Ibs N/lbs C) = Total
Nitrogen Released (Ibs N)
Example The total amount of nitrogen released from U.S. wheat residue in 1990 is
calculated as follows:
Nitrogen Released: 7,220,344,458 Ibs C x 88% x 0.0082 (Ibs N/lbs C) = 52,102,006 Ibs N
Step (6) Estimate Emissions of N2O and NOX (Table 11-2, Columns O, T and V)
• For each crop, multiply the amount of nitrogen released in units of nitrogen by the emission
ratios of N2O (column T) and NOX (column V) relative to N (see Table 11-2, columns U and
W) to obtain emissions of N2O and NOX in units of nitrogen.
Amount of N Released (Ibs) x (0.007) = N2O Emissions (Ibs N2O-N)
•d
Amount of N Released (Ibs) x (0.121) = NOX Emissions (Ibs NOX-N)
Example N2O-N and NOX-N emissions from burning of residue from U.S. wheat
production in 1990 are calculated as follows:
N2O-N Emissions: 52,102,006 Ibs N x 0.007 = 364,714 Ibs N2O-N
NOX-N Emissions: 52,102,006 Ibs N x 0.121 = 6,304,343 Ibs N2O-N
11-4
-------
Step (7) Convert to Tons of Full Molecular Weights
• For each crop, multiply the emission estimates of CH4, CO, N2O, and NOX by 16/12, 28/12,
44/28, and 46/14, respectively, to convert to full molecular weights.
• For each gas, sum across all crop types to produce total emissions from burning of crop
residues. Divide the results by 2000 to obtain total emissions in tons.
Example Emissions of CH4, CO, N2O, and NOX from burning of residue from U.S. wheat
production in 1990 are converted to tons of their full molecular weights as
follows:
CH4 Emissions: 19,061,709 Ibs CH4-C x (16/12) * 2000 Ibs/ton = 12,708 tons CH4
CO Emissions: 381,234,187 Ibs CO-C x (28/12) + 2000 Ibs/ton = 444,773 tons CO
N2O Emissions: 364,714 Ibs N2O-N x (44/28) - 2000 IbsAon = 287 tons N2O
NOX Emissions: 6,304,343 Ibs NOX-N x (46/14) + 2000 IbsAon = 10,357 tons NOX
11-5
-------
Table 11-2: Emissions from Agricultural Residue Burning Worksheet
B
D
(AxBxCxDxE)
Crop Type
CEREALS
Wheat
Barley
Maize
Oats
Rye
Rice
Millet
Sorghum
Total
PULSE
Soya
Beans
Peas
Lentils
Total
TUBER and ROOT
Sugarbeet
Artichoke
Peanut
Potatoes
Feeclbeet
Total
SUGARCANE
Crop Production {lb&)
^
-
Residue/Crop
Ratio
1.3
1.2
1
1.3
1.6
1.4
1.4
8
2.1
2.1
1.5
2.1
0.3
0.8
1
0.4
0.4
0.8
Residue Burned <%)
1«
l«
W
1ft
10
10
10
10
1ft
10
10
10
1*
10
10
10
10
10
Dry Matter
(%)
91.1
90.4
88
90.6
90
90
88.5
90
89.3
88.7
90.2
89.3
90
90
90.1
86.7
86.7
90
Fraction Burned (%)
93
93
93
n
93
93
93
93
9$
93
93
93
93
5>3
93
93
93
93
Dry Mutter
(Ibs)
-------
Table 11-2 Continued
G H I J K L M
(ColumnF) (G x H) (I x J) (1 x J x L )
Crop Type
CEREALS
Wheat
Barley
Maize
Oats
Rye
Rice
Millet
Sorghum
Total
PULSE
Soya
Beans
Peas
Lentils
Total
TUBER and
ROOT
Sugarbeet
Artichoke
Peanut
Potatoes
Feedbeet
Total
SUGARCANE
Dry Matter
OtoDM)
Carbon Content
(% C/I)M)
48.53
45.67
47.09
48.53
48.53
41.44
48.53
48.53
45
45
45
45
40.72
42.26
42.26
42.26
42.26
46.95
Total C Burned
(IbsC)
-
'
Fraction
Oxidized (%)
88
88
88
88
88
88
88
88
88
88
88
88
88
88
88
88
88
88
Total Carbon Oxidized
(Jbs COrC>
Nitrogen/Carbon
Ratio (Ibs N/C)
0.0082
0.0026
0.0172
0.0144
0.0144
0.0162
0.0144
0.0175
0.0511
0.051 1
0.0511
0.0511
0.056
0.026
0.026
0.026
0.026
0.0064
Total Nitrogen
Released <|hs N)
'
*
-------
Table
N
(Column K)
O
(Column M)
Q
(N x P H- 2000)
K
(Nx R +2000)
V
(O x T -f 2000)
W
(O x V * 2000)
Crop Type
CEREALS
. Wheat
Barley
Maize
Oats
Rye
Rice
Millet
Sorghum
Total
PULSE
Soya
Beans
Peas
Lentils
Total
TUBER and
ROOT
Sugarbeet
Artichoke
Peanut
Potatoes
Feedbeet
Total
SUGARCANE
Total
Carbon
Oxidized
(Jte C0Z-C)
. -
"•
Total Nitrogen
Released
(Ibs N)
CH4
Emissions
Ratio
0.003
0.003
0*003
0*003
0.00.5
0.003
0.063
, 0.003
0*003
0.003
0.1)03
0.003
0,003
0.003
0.003
0*003
0*003
0*003
CH4 Emitted
(tons CHj-C)
CO
Emissions
Ratio
QM
0.66
&M
0.06
0,06
0.06
0.06
0.06
0,06
0.06
0.06
0.06
0,06
0.06
0.06
0.66
0.06
0.06
CO Emitted
(tons CO-C)
NjO.
Emissions
Ratio
0.007
0.007
0.007
0,007
0,007
0.007
0.007
0.007
0.007
0,007
0.007
0.007
0.007
0.007
0.007
0.007
0,007
0,007
N2O Emitted
(tons N2O-N)
NO,
X ft
Emissions
Ratio
0.121
0421
o,m
o,m
0.121
0,121
O.J21
0.121
«,121
0.121
0.121
0.121
•-
0.121
0,121
0.121
0,121
0,121
0.121
NO, Emitted
(tons NOX-N)
11-8
-------
WORKBOOK 12
METHANE EMISSIONS FROM MUNICIPAL WASTEWATER
Wastewater can be treated using aerobic and/or anaerobic technologies, or if untreated, can
degrade under either aerobic or anaerobic conditions. Methane is produced when organic material
in treated and untreated wastewater degrades anaerobically, i.e., without the presence of oxygen.
Highly organic wastewater streams such as waste streams from food processing or pulp and paper
plants rapidly deplete available oxygen in the water stream as their organic matter decomposes. The
organic content, otherwise known as "loading" of these wastewater streams, is expressed in terms of
biochemical oxygen demand, or "BOD." BOD represents the amounts of oxygen taken up by the
organic matter in the wastewater during decomposition. Under the same conditions, wastewater with
higher BOD concentrations will produce more methane than wastewater with relatively lower BOD
concentrations.
To estimate methane emissions from municipal wastewater, the following steps are required:
(1) obtain the required data on state population; (2) estimate biochemical oxygen demand (BOD5);
(3) estimate gross annual methane emissions; and (4) estimate net annual methane emissions. These
steps are outlined in detail below. A description of the methodology presented here, as well as an
alternative, more precise methodology, is provided in Discussion Section 12.
The following equation summarizes the methane emissions calculation from municipal
wastewater:
IbsCH.
.
(Population)
( Ibs BOD,\ (365
\ capita/day
'0.22 Ibs CH4
Ibs BOD,
(Fraction
Anaerobically
Digested
- (Methane Recovered)
Step (1) Obtain Required Data
• Required Data. The information needed to calculate methane emissions from municipal
wastewater are (1) Ibs BOD5 per capita; (2) state population; (3) the fraction of total
wastewater that is treated anaerobically (wastewater treatment methods that may result in
anaerobic decomposition of waste are sewer systems and septic tanks). Because published
data on the fraction of wastewater that is anaerobically treated is scarce, states are
encouraged to provide their own estimates based on their available data. This section.
however, contains default values for the fraction of wastewater that is treated anaerobically;
and (4) amount of methane that is recovered.
i
• Data Source. Population data can be obtained from state agencies responsible for handling
demographic or census information. Information on biochemical oxygen demand and
wastewater characteristics can be obtained from National Small Flows Clearinghouse (West
Virginia University), Water Supply and Pollution Control (Viessman and Hammer, 1985),
Emissions and Mitigation at Landfills and Other Waste Management Facilities (Thorneloe,
1992), and state and local public works agencies.
• Units for Reporting Data. Population data should be reported in units of 1,000 persons.
12-1
-------
Biochemical Oxygen Demand data should be reported in pounds per day.
Step (2) Estimate Biochemical Oxygen Demand (Table 12-1, Columns A, B, and C)
• Enter the total state population for 1990, in 1,000 persons, in Table 12-1, column A. Enter
wastewater BOD Generation Rate in Table 12-1, column B. (A default value of 0.1356
Ibs/capita/day can be used if state-specific data are unavailable). Multiply the population by
wastewater BOD generation rate to give annual BOD generated. Enter the result in pounds
BOD5, in Table 12-1, column C.
Population (1,000 persons) x BOD Generation Rate (Ibs/capita/day)
= BOD5 Generated (Ibs/day)
Example A state that has a current population of 2 million people would calculate their
BOD5 generated as follows:
2,000 (1,000 persons) x 0.1356 Ibs/capita/day = 271,200 Ibs/day
Step (3) Estimate Methane Emissions (Table 12-1, Columns C, D, E, F, and G)
• Enter Fraction of BOD anaerobically treated in Table 12-1, column D. Default value of 15
percent can be used if state-specific factors are unavailable.
• Multiply annual BOD generated by the fraction of BOD anaerobically treated and 365 days/yr
to give quantity of BOD treated anaerobically per year. Enter this result, in pounds BOD5,
in column E.
BOD5 Generated (Ibs BOD5/day) x Fraction of BOD5 Anaerobically Treated x 365 days/yr
= BOD5 Anaerobically Treated (Ibs BOD5/yr)
Example BOD5 anaerobically treated per year in the state is estimated as follows:
271,200 (Ibs BODg/day) x 0.15 x 365 (days/yr) = 14,848,200 (Ibs BODg/yr)
Enter the methane emissions factor, in pounds CH4/lb BODj, in column F. The
recommended emissions factor is 0.22 Ibs CH4/lbs BOD5.
Multiply, the quantity of BOD treated anaerobically by the methane emissions factor to give
total methane emissions. Enter the result in pounds CH4 in column G.
BOD5 Treated Anaerobically x Methane Emissions Factor (Ibs CH4/lb BOD5)
= Methane Emissions (Ibs CH4)
12-2
-------
Example Gross methane emissions from wastewater treatment in the state are calculated
as follows:
14,848,200 (Ibs BODg/yr) x 0.22 Ibs CH4/lbs BOD5 = 3,266,604 Ibs CH4/yr
Step (4) Estimate Net Annual Methane Emissions (Table 12-1, Columns G, H, and I)
• Estimate the amount of methane recovered (if any) from municipal wastewater treatment.
- Enter the result, in pounds CH4, in column H.
• Subtract methane recovered from total methane emissions to give net methane emissions.
Divide result by 2,000 to obtain CH4 emissions in tons CH4. Enter the result, in tons CH4,
in column I.
Methane Emissions (Ibs CH4) - Methane Recovered * 2,000 Ibs/ton
= Net Methane Emissions (tons CH4)
Example A state that recovers 15 percent of the methane generated from wastewater
treatment would calculate their net emissions, in tons CH4 as follows:
3,266,604 lbs/CH4 - (0.15 x 3,266,604 Ibs CH^ + 2,000 = 1,388 tons CH4
12-3
-------
Table 12-1. Methane Emissions from Municipal Wastewater Treatment Worksheet
B
C
(AxB)
D
E
(CxDx 365)
G
(ExF)
H
(G x H + 2,000)
Population
(1,600 persons)
Wastewater
BOD
Generation
Rate (Ibs
BODs/1,000
persons/day)
BOO
Generated
(IbsBOIV
:
Fraction
Anaerobically
Treated
Quantity of
BOD Trtated
Anfterobicajly
(Ibs BODj/yr)
,
Methane
Emission
Factor (Ibs
CH«/lb BOD5)
CH4
Emissions
(IhS CB^
~
Methane
Recovered
(Ibs CI14)
NeKH,,
Emissio&s
(tORs Cja^)
-
;.
'
12-4
-------
PART II
DISCUSSION SECTIONS
-------
DISCUSSION 1
CARBON DIOXIDE EMISSIONS FROM COMBUSTION
OF FOSSIL AND BIOMASS FUELS
CO2 EMISSIONS FROM THE COMBUSTION OF FOSSIL FUELS
OVERVIEW
Energy-related activities are the most significant contributor to U.S. greenhouse gas
emissions, accounting for nearly 89 percent of total emissions in 1990. Emissions from fossil fuel
combustion comprise the vast majority of these energy-related emissions. These emissions were ^
produced from a variety of fossil fuel combustion activities, including heating in residential and
commercial buildings, energy combustion to generate electricity, steam production for industrial
processes, and gasoline consumption in automobiles and other vehicles. As fossil fuels burn, they
emit carbon dioxide (CO2) as a result of oxidation of the carbon in the fuel. In 1990, CO2
accounted for 96 percent of all greenhouse gas emissions from fossil fuel combustion. The
remaining 4 percent can be attributed to emissions of other gases, such as carbon monoxide (CO),
methane (CH4), or nonmethane volatile organic compounds (NMVOCs), which are emitted as a
by-product of incomplete combustion. These gases are then oxidized to CO2 within anywhere
from a few days to 10 to 11 years. For purposes of this analysis, however, emissions of these
other gases are considered to be a subset of CO2 emissions. That is, all carbon emitted to the
atmosphere is reported as CO2 emissions, while a much smaller portion of the carbon will also be
reported as these other gases. This "double counting" is intentional. By reporting emissions in
this fashion, state estimates of CO2 will reflect total loadings of carbon to the atmosphere. Also,
since all of these gases oxidize to CO2 eventually, they should be viewed as a subset of carbon
emitted as CO2.
The amount of CO2 emitted from fossil fuel combustion is related directly to the type and
amount of fuel consumed, the fraction of the fuel that is oxidized, and the carbon content of the
fuel. This relationship can be described in two parts:
1) The amount of carbon contained in the fuel per unit of useful energy produced
varies among different fuel types. For example, coal contains the highest amount
of carbon per useful unit of energy. Petroleum has about 80 percent of the
carbon per unit of energy as compared to coal, and natural gas has about 55
percent. Even within fuel types, carbon contents will vary, e.g., the lower the
quality of the coal (such as lignite and sub-bituminous coal), the higher the carbon
content coefficient (i.e., more carbon emitted per unit of energy). There are
similar carbon differences among the different types of liquid fuels and natural gas
as well.
2) Not all carbon in fuel products is oxidized to CO2 because of (1) inefficiencies in
the combustion process that leave carbon unburned, and (2) non-fuel uses of the
energy, such as asphalt, naphtha, and lubricants. During the combustion of fossil
fuels not all of the carbon in the fuel oxidizes to CO2, which causes a small
fraction of the carbon to remain unburned as soot or ash. Similarly, some carbon
is not immediately and completely oxidized to CO2, and is emitted in the form of
CH4 or other hydrocarbons. Fossil fuels are also used for non-energy purposes,
Dl-1
-------
primarily as a feedstock for such items as fertilizer, lubricants, and asphalt. In
some cases, as in fertilizer production, ,the carbon from the fuels is oxidized quickly
to CO2- In other cases, as in asphalt production, the carbon is sequestered in the
product, sometimes for as long as several centuries.
DESCRIPTION OF WORKBOOK METHOD
The first step in estimating CO2 emissions from fossil fuel combustion is to define exactly
what is meant by "CO2 emissions." For this discussion, CO2 emissions from fossil fuel combustion
include all of the carbon in fuels that is either immediately oxidized or oxidized within a short
time period (Le., less than 20 years). It includes carbon in the form of gases, like CO and CH4,
and carbon in short lived products that will be burned after use or decompose quickly. CH4
emissions from oil and gas production and coal mining as well as CH4, CO, N2O, NOX and
NMVOC emissions from stationary and mobile source combustion are not included in this section
but are discussed later (see Workbook and Discussion Sections 3, 4, 13, and 14, respectively).
To calculate CO2 emissions from fossil fuel combustion, the following factors must be
identified:
1) Fossil fuel consumption by energy type;
2) Carbon content coefficients;
3) Carbon sequestered in products for long periods of time;
4) Carbon emitted from bunker fuel consumption;
5) Carbon emitted from interstate electricity consumption; and
6) Carbon oxidized during combustion.
Fossil Fuel Consumption
/
As noted above, CO2 is released as fossil fuels are consumed. The carbon content of
these fuels typically varies by fuel type. Therefore, in order to develop an accurate estimate of
CO2 emissions, it is necessary to compile individual consumption data for each type of fuel
consumed. A recommended list of fuels is given in Table Dl-1. It should be noted that certain
primary fuels (such as crude oil) do not appear on this list. This is because primary fuels of this
nature are not combusted directly, but rather are transformed into secondary fuels (such as
gasoline) which are combusted. Therefore, the carbon in these primary fuels is accounted for in
the secondary fuels. Fugitive emissions of greenhouse gases from primary fuel production,
processing, and distribution are included elsewhere (see Workbook and Discussion Sections 3
(natural gas and oil) and 4 (coal)).
Fuel statistics should be provided on an energy basis (preferably in million Btu), since
considerable variation exists in the energy content per weight of fossil fuels. Statistics using other
units, such as barrels or short tons, can be used, but require conversion to energy units. If
conversion is necessary, the conversion factors used should be reported. Default conversion
factors for the various fuel types are presented in Table Dl-1. It should be noted that these
conversion factors are national averages based on 1990 data and may not accurately reflect the
energy content of fuels used in a particular state or for years other than 1990. The degree of
variation geographically and temporally is less significant for natural gas and refined petroleum
fuels than for coal, which may vary significantly from mine to mine and year to year. State
specific thermal conversion factors for coal are compiled by the Energy Information
Dl-2
-------
Table DM. Conversion Factors to Million Btu.a
Fuel Type
If data is in
Multiply by
Petroleum
Asphalt and Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel: Kerosene Type
Jet Fuel: Naphtha Type
Kerosene
Liquified Petroleum Gases
Lubricants
Miscellaneous Petroleum Products and Crude Oil
Motor Gasoline
Naphtha (<104°F)b and Special Naphthas
Other Oil (>104°F)b and
Unfinished Oils
barrels
barrels
barrels
barrels
barrels
barrels
barrels
barrels
barrels
barrels
barrels
barrels
6.636
5.048
5.825
5.670
5.355
5.670
4,011
. 6.065
5.800
5.253
5.248
5.825
Pentane Plus
Petroleum Coke
Residual Fuel Oil
Still Gasb
Waxes
Coaf
Anthracite6
Bituminous
Sub-bituminous
Lignite
Coal Coke
barrels
barrels
barrels
barrels
barrels
short tons
short tons
short tons
short tons
short tons
4.620
6.024
6.287
6.000
5.537
21.668
23.89
17.14
12.866
24.800
Natural Gas
billion cubic feet
Teracalories
1.03 x 10"
3968
Biofuels
Woodd
Ethanol
Btu
gallons
0.116xl03 (Ibs/Btu)
0.764
Interstate Electricity Consumption1
kilowatthours
10,000 (Btu/kWh)
Heat contents of many fuels vary somewhat by source, year, and consumer. Except for coal, biomass, and blended petroleum
products, this variation tends to be relatively small. The values here are national averages for 1990.
By EIA definition naphtha (<104°F), other oil (>104°F), and still gas are collectively termed petrochemical feedstocks.
Thermal conversion factors for coal can vary extensively by source. More complete state and sector specific factors are available
through U.S. DOE/EIA.
The energy content of wood varies with moisture content and type of wood. The conversion factor given is a nationally averaged
value based on dry mass of hardwood. Since wood consumption figures should be in pounds, the factor should be used to convert
consumption from Btu to pounds.
The anthracite factor presented here is a national average. Actual anthracite factors could range from as low as 17.5 MMBtu/ton for
anthracite reclaimed from refuse piles to 26 MMBtu/ton or higher for anthracite mined directly from the original seam.
This is a national average heat rate based on EIA data (EIA, 1994e) and should only be used for interstate electricity consumption
for which the specific heat rate of the source is unknown.
Source: Petroleum, natural gas, and wood heat-equivalents and the interstate electricity heat rate are from EIA's Annual Energy Review 1993.
Coal heat-equivalents are from EIA's Stale Energy Data Report 1992, Cost and Quality of Fuels for Electric Utility Plants, and Quarterly Coal
Report. Ethanol heat-equivalents are from EIA's Estimates of U.S. Biomass Consumption 1992.
f.
Dl-3
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Administration (EIA) of the U.S. Department of Energy (DOE) and presented in a variety of sources. For
example, representative energy-content information based on a survey of electric utility power plants is
contained in EIA's annual Cost and Quality of Fuels for Electric Utility Plants, while more generalized
information is provided in the Quarterly Coal Report and State Energy Data Report.
Next, fuel consumption data should be disaggregated into the following consumption sectors:
residential, commercial, industrial, transportation, and electric utility. Sector-specific consumption figures for
all 50 states can be found in State Energy Data Report 1992 (EIA, 1994b). In many instances, states may find
it is useful to distribute emissions from electric utilities across "end-use sectors," to assist in formulating
emission reduction strategies. To distribute utility emissions accurately, it is necessary to obtain electricity
consumption data by each of the four end-use sectors (residential, commercial, industrial, and transportation)
in the state. Default values for this consumption can be obtained from State Energy Data Report 1992 (EIA,
1994b). Using these figures, states can calculate the fraction of total electricity consumption which is
consumed by each of the four end-use sectors (Le., divide each sector specific consumption figure by total
electricity consumption). Each of these fractions is then multiplied by total emissions from the utility sector,
resulting in the portion of utility emissions attributable to each end-use sector. These end-use emissions from
electricity consumption are then added to the other sectoral emissions.
Determine and Apply the Appropriate Carbon Content Coefficients
Carbon content coefficients represent the amount of carbon emitted per unit of useful energy
obtained by burning a specific type of fuel. Carbon content coefficients vary considerably both between and
within the major fuel types, as noted below:
• For natural gas, the carbon content depends heavily on the composition of the
gas, which includes methane, ethane, propane, other hydrocarbons, CO2, and
other gases. The relative proportions of these gases vary from one gas
production site to another.
• For crude oil, Marland and Rotty (1984) suggest that the API gravity1 acts as
an indicator of the carbon/hydrogen ratio. Carbon content per unit of energy
is usually less for light refined products such as gasoline than for heavier
products such as residual fuel oil.
• For coal, carbon emissions per ton vary considerably depending on the coal's
composition of carbon, hydrogen, sulfur, ash, oxygen, and nitrogen. While
variability of carbon emissions on a mass basis can be considerable, carbon
emissions per unit of energy (e.g., per Btu) vary much less, with lower ranked
coals such as sub-bituminous and lignites usually containing slightly more
carbon than higher-ranked coals.
In general, carbon content coefficients are determined based on the composition and heat contents of
fuel samples. Several studies have tried to estimate carbon content coefficients for fossil fuels (Marland and
Rotty, 1984; Marland and Pippin, 1990; Grubb, 1989; IPCC/QECD, 1994; and others). Based on these
studies and detailed fuel data, fhe Energy Information Administration of DOE estimates carbon content
1 Variations in petroleum are most often expressed in terms of specific gravity at 15 degrees C. The API
gravity, where API gravity = 141.5/specific gravity - 131.5, is an indication of the molecular size,
carbon/hydrogen ratio, and hence carbon content of a crude oil.
Dl-4
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Table Dl-2: Carbon Content Coefficients for Fuel Combustion3
(Ibs C/106 Btu)
Fuel Consumed Carbon Coefficient
Asphalt and Road Oil 45.5
Aviation Gas 41.6
Distillate Fuel Oil 44.0
Jet Fuel (all kinds) 43.5
Kerosene 43.5
LPG • 37.8
Lubricants . 44.6
Motor Gasoline - 42.8
Residual Fuel Oil 47.4
Misc. Petroleum Products and Crude Oil 44.7
Naphtha (<104°F) 40.0
Other Oil (>104°F) . 44.0
Pentanes Plus 40.2
Petrochemical Feed 42.7
Petroleum Coke 61.4
Still Gas 38.6
Special Naphtha . 43.8
Unfinished Oils 44.6
Waxes 43.7
Anthracite Coal 62.1
Bituminous Coal ' 56.0
Sub-bituminous Coal 57.9
Lignite Coal 58.7
Natural Gas 31.9
Woodb 0.475
Ethanol 41.8
Except as noted all coefficients are given as pounds of carbon emitted per million Btu of fuel consumed (Ibs C/106 Btu). When
multiplied by consumption in 106 Btu, or pounds for wood, they result in emissions of carbon in pounds (Ibs C).
a. Carbon content coefficients are sometimes called carbon emission coefficients or carbon coefficients.
b. The wood coefficient is a percent of total carbon in biomass (%C).
Sources: Natural gas and petroleum coefficients are from U.S. EPA's Inventory of U.S. Greenhouse Gas Emissions and Sinks:
1990-1993. Coal coefficients are full combustion figures based on EIA's Emissions of Greenhouse Gases in the United States:
1985-1990. The wood carbon fraction is from the IPCC Guidelines for National Greenhouse Gas Inventories. The ethanol
coefficient is from OTA's Changing by Degrees.
coefficients for a wide range of fuel types. Nationally averaged carbon content coefficients for each fuel type
are listed in Table Dl-2. As with thermal conversion factors, these average carbon emission factors may not
precisely reflect the carbon content of energy used in a particular state or for years other than 1990. The
degree of variation geographically and temporally is generally quite small for natural gas and refined
petroleum fuels, but coal coefficients may vary significantly from mine to mine and year to year. Nationally
averaged figures can be found in U.S. EPA (1994) and non-type-specific state factors can be found in DOE's
Electric Power Annual. States are encouraged to use more detailed data if it is available and well
documented.
Dl-5
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Once determined, carbon content coefficients can then be used to calculate the total potential
that could be released from the combustion of fossil fuels. The basic approach for implementing this
methodology relies on the following equation:
Tctj = c^ x ccq
where: TCj: = Total Carbon contained in fuel i, which is consumed in sector j (pounds);
Cj; = Consumption of fuel i in sector j (million Btu); and
CCCj = Carbon Content coefficient for fuel i (Ibs C / million Btu)
By summing TC; across all fuels and sectors one can calculate a states total potential carbon emissions
from the combustion of fossil fuels.
Carbon Sequestered in Products
After estimating the total carbon contained in the fuels, the next step is to estimate the amount of
carbon from these fuels that is sequestered in non-energy products for a significant period of time (e.g.,
greater than 20 years). All fossil fuels are used for non-energy purposes to some degree. For example,
natural gas is used for ammonia production; LPGs are used for a number of purposes, including production
of solvents and synthetic rubber; oil refineries produce wide variety of non-fuel products, including asphalt,
naphthas, and lubricants; and coal is used to produce coke, yielding crude light oil and crude tar as by-
products which are used in.the chemical industry.
However, not all non-energy uses of fossil fuels result in carbon sequestration. For example, the
carbon from natural gas used in ammonia production is oxidized quickly; many products from the chemica1
and refining industries are burned or decompose within a few years; and the carbon in coke is oxidized w^
the coke is used.
The approach used to determine the portion of carbon sequestered in products is basically similar to
that used by Marland and Rotty (1984) and modified by later information (Grubb, 1989; Okken and Kram,
1990; IPCC/OECD 1994; U.S. EPA, 1994), in which historical data and product knowledge are used to
determine non-energy applications which sequester carbon for long periods of time. Additional non-fuel data
is being collected by the EIA. Based on these data, the following carbon storage assumptions have been
made:
• Coal (i.e., Coal Oil and Tars): Based on Marland and Rotty (1984), approximately 6 percent
of coal carbon entering coke plants is converted to coal oils and tars, of which 75 percent is
sequestered and remains unoxidized for long periods of time.
• Natural Gas: The two main non-fuel uses of natural gas are for ammonia production in
nitrogenous fertilizer manufacture and as a chemical feedstock. It is assumed that 100 percent
of the carbon in natural gas used as a chemical feedstock is sequestered. As noted above, the
carbon from natural gas used in ammonia production oxidizes quickly, and is not sequestered.
• LPG: It is assumed that 80 percent of the carbon in LPG sold for chemical and industrial uses
is sequestered in products.
• Asphalt and Road Oil (i.e., Bitumen): It is assumed that 100 percent of the carbon in this
product is sequestered indefinitely.
Dl-6
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• Lubricants: Of the carbon contained in lubricants (e.g., automotive oil, grease, etc.),
approximately 50 percent is assumed to remain unoxidized for long periods of time.
• Petrochemical Feedstocks: This category includes naphthas (<104°F) and other petroleum
products used as chemical feedstocks in petroleum related .industries. Eighty percent of the
carbon in this category is assumed to end up in products such as plastics, tires, and fabrics,
which sequester carbon over long periods of time.
• Waxes and Miscellaneous Products: Waxes and miscellaneous products is an EIA defined
category which includes waxes and various other petroleum products used for non-fuel
purposes. Until more exact information is available, 100 percent of the carbon contained in
these products is assumed to be sequestered. For example, the carbon contained in waxes for
food industry wrappers is assumed to be sequestered in landfills.
These assumptions comprise the default values to be used by states (see Table Dl-3). As more
detailed information on non-fuel uses of fossil fuels becomes available, estimates of the fraction of carbon
stored will change accordingly. States should use the most up-to-date information available, and document
their assumptions carefully.
Table Dl-3: Percent of Carbon Sequestered by Non-fuel Uses3
Fuel Type
Fraction Stored
Coal Oils and Tars from coke production
Natural Gas as a chemical feedstock
Asphalt and Road Oil
LPG
Lubricants
Petrochemical Feedstocks3
Waxes and Miscellaneous Products'5
0.75
1.00
1.00
0.80
0.50
0.80
1.00
a.
b.
By EIA definition, "Petrochemical Feedstocks" include naphtha (< 104°F),
other oil (<104°F), and still gas.
By EIA definition, "Waxes and Miscellaneous Products" includes waxes, other
miscellaneous petroleum products, residual fuel oil, and distillate fuel oil.
Sources: Figures for coal oil and tars, asphalt and road oil, LPG, and lubricants are
from Marland and Rotty (1984). The Figure for natural gas is from communication
with EIA (Rypinski, 1994). Petrochemical feedstocks and waxes and miscellaneous
products are from U.S. EPA (1994).
Dl-7
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Using the carbon sequestration percentages listed above, the suggested approach for estimating
carbon sequestered in products for each state starts with the following basic equation:
CSj = U; x ccq x FSj
where: CSj = Carbon Sequestered in product i (Ibs of carbon);
Uj = Non-fuel use of energy for product i (million Btu);
CCCj = Carbon Content Coefficient for product i (Ibs C / million Btu); and
FSj = Fraction of carbon in product i which is Sequestered.
Total carbon sequestered in products can be determined by summing CSj over the various products.
The resulting carbon sequestration estimates from non-energy uses of fossil fuels would be considered,
"potential" emissions and are subtracted from the total emissions of carbon in the state that produces the
products. When estimating emissions sector-by-sector, it is suggested that sequestered carbon from these
products be assigned to the industrial sector, unless justification for allocating certain products to another
sector can be clearly demonstrated.
/
Carbon Emitted from Bunker Fuel Consumption
For inventory purposes there are two kinds of bunkers: domestic bunkers and international bunkers.
Domestic bunkers include fuel supplied to vehicles (aircraft, autos, ships, etc.) for use in interstate
transportation. Since it is extremely difficult to obtain accurate activity data on interstate transportation,
there is currently no method to explicitly determine emissions from domestic bunker fuel consumption. Since
general emissions calculations are consumption based, all emissions from interstate transportation should
automatically be included such statistics. Therefore, it is assumed that emissions from all such bunkers wi'"
effectively captured in normal state consumption statistics and domestic bunkers should not be specificaH3
addressed. • ~s
International bunker fuel is fuel which originates in a state, but is supplied to ships and aircraft which
consume it during international transp'ort activities. For example, distillate fuel, residual fuel, and jet fuel
may be sold in a state and be consumed by vehicles which leave the U.S. Since, this fuel is not combusted
solely in the U.S., its emissions cannot be clearly attributed to the U.S. In accordance with international
inventory practices (IPCC, 1994) emissions from international bunkers should be calculated and reported by
the state of origin, but not included in the state's total emission figures. In this way, emissions from these
sources can be quantified without attributing undo emissions to the U.S. or any state therein.
International bunker fuel emissions are calculated in the same manner as other emissions from fossil
fuel combustion. Once consumption of international bunker fuels are determined, they are multiplied by
their appropriate carbon content coefficients (see Table Dl-2). This results in the amount of carbon
potentially emitted by combustion of these fuels. This figure should be reported and clearly labeled in the
state's inventory. These emissions should be subtracted from the state total emissions only if they have
already been captured in the state-wide figures.
Once adjustments have been made to state totals for carbon sequestered and emissions from
international bunker fuel consumption, the resulting figure is the "Net Carbon Content," or "Net Potential
Emissions."
Dl-8
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Carbon Emitted from Interstate Electricity Consumption
Not only can fuels be imported and exported from a state, but electricity derived from these fuels can
be transported across state boundaries (i.e. electricity is often produced in one state for consumption in
another). For various reasons (e.g., mitigation and impact assessments) it is necessary to attribute emissions
from electricity consumption to end-use consumers rather than to the generating state. However, actual
emissions from electricity consumption occur in the generating state and are captured in that state's
consumption figures.
To provide the most complete picture of emissions at the state level, states should calculate emissions
due to interstate electricity flux in addition to the emissions calculated directly from fossil fuel consumption.
In other words, states should calculate and report emissions from all fuel consumption within their
boundaries, including that which is converted to electricity consumed out of state. To clarify consumption
patterns, the. state should also perform separate calculations for emissions due to electricity traded across
state boundaries, which is discussed below. These emissions should not be used to adjust state emission
totals, but should be clearly provided for informational purposes.
Four pieces of information are required to determine emissions from interstate electricity
consumption:
1) The quantity of electricity imported to and exported from other states;
2) The sources of imported and exported electricity;
3) Heat rates for the sources of imported and exported electricity; and
4) Carbon content coefficients of the fuels used to generate the imported and exported
electricity.
The quantity of electricity imported and exported is the fundamental data on which the emission
calculations are based. The sources of imported and exported electricity are needed to determine
appropriate carbon content coefficients for the energy consumed. For example, the amount of carbon
emitted during electricity production depends on the fuel source used to generate the electricity (e.g., a coal,
natural gas, or petroleum fired power plant). This data can be obtained from state or regional Public Utility
Commissions (PUCs) or from individual utilities. At the national level, data on electric power generation and
distribution is collected by EIA and reported in various documents including the Electric Power Annual.
The amount of electricity imported and exported will likely be reported in kilowatthours (kwh), while
the typical carbon content factor is presented in mass of carbon released per unit of energy input (e.g.,
Ibs/MMBtu). Therefore, in order to determine the amount of carbon emitted during electricity generation,
states must obtain the heat rates at the generating facilities concerned. The heat rate of a facility represents
the amount of energy input required by a facility to produce a kilowatthour of electricity. Typical heat rates
can vary from about 7,000 to 15,000 Btu/kwh, with a national average of approximately 10,000 Btu/kwh. This
average is based on an EIA estimate that assumes approximately 67 percent of total energy input is lost
during the conversion process (EIA, 1994e). This national average can be used as a default value, but it is
recommended that states attempt to identify heat rates specific to their localities. Possible sources for such
information are regional PUCs, individual utilities or independent power producers (IPPs).
After the fuel source has been determined and converted to energy units, the carbon content
coefficients can be applied using the following equations:
Dl-9
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x HRj x CCq
j = Expj x HRj x CCCj
where: El = Emissions of carbon due to imports from source i (Ibs carbon);
EE = Emissions of carbon due to exports from source j (Ibs carbon);
Imp = Electricity imported from source i (kwh);
Exp = Electricity exported from source j (kwh);
HR = Heat Rates of generating facilities (Btu/kwh); and
CCC = Carbon Content Coefficients for source fuels (Ibs carbon /Btu).
The carbon content coefficients used in these calculations are the same as those used in the rest of
the energy emission calculations (see Tale Dl-2). It should be noted that state-specific carbon content
coefficients should be used if possible and that the source(s) of this information should be thoroughly
documented.
Emissions calculated by the above equations should then be summed over all fuel sources and
exported electricity emissions should be subtracted from imported electricity emissions:
NE = I EIj - £ EEj
where: El = Emissions of carbon due to imports from source i (Ibs carbon);
EE = Emissions of carbon due to exports from source j (Ibs carbon); and
NE = Net Emissions from interstate energy consumption (Ibs carbon).
A negative number for net emissions indicates a net export of electricity, while a positive number
indicates a net import of electricity. If emissions were distributed across end-use consumers, a net import
would result in an increase in state emission totals, because it represents additional consumption attributable
to end-users within the state. A net export would result in a decrease in state totals, because it represents
fuel consumed in state to produce energy used by out of state consumers.
Estimate Carbon Oxidized during Combustion
As described earlier, not all carbon is oxidized immediately during the combustion of fossil fuels. The
amount of carbon that falls into this category is usually a small fraction of total carbon, with a large portion
of this carbon oxidizing in the atmosphere shortly after combustion. Based on Marland and Rotty (1984);
Bechtel (1993); and other sources (EPA, 1994; IPCC\OECD, 1994), the following factors are recommended:
• For natural gas less than 0.5 percent of the carbon in natural gas is unoxidized
during combustion and remains as soot in the burner, stack, or in the
environment. (This is equivalent to a fraction oxidized of 0.995.)
• For petroleum fuels approximately 1 percent passes through the burners and is
deposited in the environment without being oxidized. (This is equivalent to a
fraction oxidized of 0.99.)
• For coal approximately 1 percent of carbon supplied to furnaces is discharged
unoxidized, primarily as ash. (This is equivalent to a fraction oxidized of 0.99.)
Dl-10
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These values vary based on fuel quality and technology types (particularly for coal). If more specific
values are available for state level combustion, they should be used and clearly documented. In order to
determine the amount of carbon actually oxidized and emitted, carbon sequestered in products and carbon
emitted from interstate bunkers are subtracted from total potential emissions to obtain net potential
emissions. These net emissions are then multiplied by the fraction of carbon oxidized to determine the
amount of carbon oxidized from fuel combustion. This is represented in the following equation:
TOq = NPEj x FOj
where: TOCj = Total Oxidized Carbon for fuel i (Ibs of carbon);
NPEj = Net Potential Emissions for fuel i (Ibs of carbon); and
= Fraction of carbon Oxidized for fuel i.
To obtain the total oxidized carbon for the state (or net carbon emissions from fossil fuel
combustion), TOCj is summed over all fuel types, excluding biomass fuels.
Summary
The previous calculations provide estimates of total carbon in the fossil fuels, carbon sequestered in ,
non-energy products, and carbon emitted due to interstate energy consumption. Given these estimates, total
carbon emissions from fossil fuel combustion can be determined. Total carbon emissions are equal to the
total carbon content in fuel minus carbon sequestered in products and emissions from international bunkers,
adjusted for the carbon unoxidized during combustion, and summed over all fuel types, excluding biomass
fuels. Since the resulting figures are in units of carbon, they should be multiplied by 44/12 to obtain CO2 on
a full molecular weight basis (44/12 is the atomic mass ratio of CO2 to carbon).
Data Sources
Statistics on energy and fossil-fuel production and consumption can be found in a number of sources,
but inconsistencies often exist in how the data are presented, sources of the data, types of information
provided, and reporting units. Information on production of products that sequester carbon also varies. EIA
data could be used as a starting point, but states should use the energy data thought to be the most reliable
(for example, from state energy commissions or PUCs). If states use in-state sources rather than EIA data,
they are strongly urged to provide thorough documentation on the energy statistics, the reporting procedures,
and definitions of sectoral activities. This would help to ensure consistency and comparability among all state
estimates.
CO2 EMISSIONS FROM THE CONSUMPTION OF BIOMASS-BASED FUELS
OVERVIEW
Biomass fuels (biofuels) such as wood and vegetal fuels are used for energy production, domestic
cooking and heating, and industrial heat and power. Consumption of these fuels produces carbon dioxide,
methane, carbon monoxide, nitrogen oxides, nitrous oxide, and non-methane volatile organic compounds.
There are two phases of wood combustion that produce these trace gases: the flaming stage of combustion
and the subsequent smoldering stage (Garrett, personal communication). During the flaming stage of
combustion, which is usually violent and short-lived, oxygen is consumed as CO2 is produced. In the
smoldering phase, in which less oxygen is available, non-CO2 substances are the primary products emitted.
Dl-11
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An important distinction should be made between commercial and non-commercial biofuels
consumption. Commercial consumers typically pay for the biofuels they consume in well-developed mark
on which statistics are often available. Non-commercial consumers, however, typically collect their own
fuelwood or purchase it from vendors. Lack of a formal markets make it difficult to estimate the quantity of
biomass consumed in this fashion. As a result, it may be difficult to estimate the actual amount of biofuels
consumed because market statistics primarily reflect only commercial consumption. The extent of this
problem will vary from state to state. In addition, limited data are available on the relative fuel properties of
biofuels. In order to improve the quality of emission estimates from bioenergy consumption, additional
research is needed to refine information on the total quantity of biomass consumed for energy purposes and
the resulting emission factors under various combustion conditions.
It has been argued that CO2 emissions resulting from bioenergy consumption should not be included
in a state's official emissions inventory in order to avoid double counting CO2 emissions. This double-
counting would occur because: (1) biofuels tend to be produced on a sustainable basis such that no net
increase in CO2 occurs or (2) production of CO2 from biofuels burned on a non-sustainable basis would be
captured as part of emissions resulting from land-use changes (see Workbook and Discussion Section 10).
Even though it is well understood that double-counting could occur, no solution is recommended at this time
to assist analysts in resolving this matter and incorporating emissions from this source into overall CO2
emissions . Therefore, it is currently recommended that states estimate and report CO2 emissions from
bioenergy consumption separately from CO2 emissions from fossil fuel consumption, and that these emissions
not be included in total state emissions. Thus, states should note that CO2 emission estimates from biomass
consumption do not currently represent a net increase in state CO2 emissions, but that they are still
calculated to ensure that all possible CO2 emissions from energy consumption are estimated. The issue of
double-counting CO2 emissions from biofuels consumption should be given special attention in the near
future to determine the most appropriate methods for accounting for these emissions.
DESCRIPTION OF WORKBOOK METHOD
The methodology for calculating CO2 emissions from biomass is very similar to that used for fossil
fuels. To estimate CO2 emissions from biomass consumption, we need to determine biofuel consumption,
carbon contents for the biofuels, and the fraction of fuel which is oxidized during combustion.
Wood consumption data should be reported in tons of dry matter and ethanol consumption should be
reported in million Btu. Some conversion factors that may be used to obtain consumption in the proper
units are given in Table Dl-1.
The carbon content of wood, or the carbon in wood which could potentially be emitted, is simply the
percent of total wood mass which is carbon. It is applied in a way similar to the carbon content coefficients
used for ethanol and fossil fuel consumption, but it represents mass of carbon released per mass of fuel
input, rather than carbon released per unit energy input (e.g., percent of fuel mass rather than Ibs carbon per
Btu of energy). Table Dl-4 contains carbon content assumptions used to estimate the percentage of each
fuel type that is carbon.
/
The carbon potentially emitted must be adjusted for carbon that is not oxidized. Table Dl-4 lists the
default values for the fraction oxidized. It is assumed that 10 percent of all carbon in wood is not oxidized
(Crutzen and Andreae, 1990). However, for purposes of this analysis, ethanol, is assigned a fraction oxidized
of 0.99 due to its similarity to gasoline. These values could vary significantly based on fuel qualities and
combustion processes and should be evaluated to determine their appropriateness.
Dl-12
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Table Dl-4: Carbon Content and Fraction Oxidized for Biofuel Consumption
Fuel
Units of
Consumption
Carbon Content
Fraction
Oxidized
Wood
Ethanol1
tons dry matter
Btu
47.5%
41.9 (Ibs C / Btu)
0.90
0.99
Since ethanol consumption is given in Btu, it has a carbon content
coefficient rather than a carbon content. Its fraction oxidized is assumed to
be about 0.99, since -it is generally combusted in autos as a gasoline additive,
and motor gasoline has a fraction oxidized of about 0.99.
Source: IPCC (1994) and Crutzen and Andreae (1990).
There are two basic equations for estimating CO2 emissions from biofuel consumption. The first is
used for wood and the second is used for ethanol.
(1)
(2)
E = C x CC x FO
EE = EC x CCC x FO
where: E = emissions (Ibs carbon);
C = biofuel consumption (Ibs fuel);
CC = carbon content (percent);
FO = fraction oxidized;
EE = emissions from ethanol (Ibs carbon);
EC = ethanol consumption (Btu); and
CCC = carbon content coefficient (Ibs carbon / Btu).
The resulting values indicate the amount of carbon dioxide that is emitted in pounds of
carbon. To convert this value to full molecular weight of CO2, these values should be multiplied by
44/12, which is the atomic mass ratio of CO2 to carbon .
Data Availability
For ethanol production from biomass, state energy offices, economic development
departments, agriculture departments, or revenue departments should have production figures.
State energy or natural resource departments may also have data on the amount of wood collected
for energy use, because permits are generally required to cut timber. EIA estimates national
annual commercial biomass energy consumption in the U.S. for wood by sector and region and for
ethanol by region (EIA, 1994c). The regions included in the EIA analysis are the South, the West,
the Midwest, and the Northeast. No nationally compiled state-specific data are available in a
published format.
The amount of energy produced from the biomass is difficult to estimate as it varies from
one type of biomass to the next. Additional research will be needed to develop more precise
consumption estimates, including the energy content of the biomass, in order to reduce
uncertainties associated with calculating emissions. In addition to improving the quality of data on
Dl-13
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commercial biomass consumption, research is needed to improve the quality of data on the non-
commercial consumption of biomass.
Emissions from fuelwood also occur at different rates depending on the particular use of
fuelwood since the technology used and the combustion conditions vary from one application to the
next (e.g., wood consumed in industrial wood boilers will emit at different emission rates than wood
stoves for residential needs). Additional research will be needed to determine the range of
technology types that consume fuelwood and to characterize the amount of fuelwood consumed by
each technology type.2
UNCERTAINTIES
Carbon emissions occur from a number of activities associated with the production and
transportation of energy, not all of which are accounted for in energy and non-energy uses of fossil
fuels. These activities include gas venting and flaring, leakages during the transmission and
distribution of natural gas, leakages during the transmission, distribution, and refining of oil, CH4
emissions from coal mines, SO2 scrubbing at coal plants, and burning in coal deposits. The first
four of these activities - gas venting and flaring, leakages during the transmission and distribution of
natural gas, leakages during the transmission, distribution, and refining of oil, and CH4 leaks from
coal mines - are addressed in Workbook and Discussion Sections 3 and 4. Emissions from the
burning of coal in coal deposits and waste banks and CO2 emissions from SO2 scrubbing are highly
variable from one state to another and are a very minor portion of total emissions. At this time,
there is no recommended methodology to estimate emissions from these sources.
Field measurements have yielded some data. See Gofer et al. (1988, 1989) and Hegg et al. (1990).
Dl-14
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REFERENCES
Bechtel. 1993. A Modified EPRI Class II Estimate for Low NOx Burner Technology Retrofit.
Prepared for Radian Corporation by Bechtel Power, Gaithersburg, Maryland.
Crutzen, P.J., and M.O. Andreae. 1990. "Biomass Burning in the Tropics: Impact on Atmospheric
Chemistry and Biogeochemical Cycles," Science 250:1669-1678.
EIA. 1994a. Cost and Quality of Fuel for Electric Utility Plants 1993. Energy Information
Administration, U.S. Department of Energy. DOE/EIA-091(93).
EIA. 1994b. State Energy Data Report 1992. Energy Information Administration, U.S. Department
of Energy. DOE/EIA-0214(92).
EIA. 1994c. Estimates of U.S. Biomass Energy Consumption 1992. Energy Information
Administration, U.S. Department of Energy. DOE/EIA-0548(92).
EIA. 1994d. Quarterly Coal Report: July - September 1993. Energy Information Administration, U.S.
Department of Energy. DOE/ELA-0121(93/3Q).
EIA. 1994e. Annual Energy Review 1993. Energy Information Administration, U.S. Department of
Energy. DOE/EIA-0384(93).
Grubb, M.J. 1989. On Coefficients for Determining Greenhouse Gas Emissions From Fossil Fuel
Production and Consumption. Energy and Environmental Programme, Royal Institute of
International Affairs, London, UK. April. Prepared for OECD/IEA Expert Seminar on
Energy Technologies for Reducing Emissions of Greenhouse Gases, Paris.
IPCC. 1994. IPCC Guidelines for National Greenhouse Gas Inventories, 3 volumes: Vol. 1, Reporting
Instructions; Vol. 2, Workbook; Vol. 3, Draft Reference Manual. Intergovernmental Panel on
Climate Change, Organization for Economic Co-Operation and Development. Paris, France.
Marland, G., and A. Pippin. 1991. "United States Emissions of Carbon Dioxide to the Earth's
Atmosphere by Economic Activity," Energy Systems and Policy 14:101-118.
Marland, G.,and R.M. Rotty. 1984. Carbon Dioxide Emissions from Fossil Fuels: A Procedure for
Estimation and Results for 1950-1982. Tellus 36b:232-261.
OECD/IEA. 1990. Energy Balances of OECD Countries, 1987-1988. International Energy Agency,
OECD, Paris.
OECD/IEA. 1991. Greenhouse Gas Emissions. The Energy Division. OECD, Paris. Forthcoming. -
Okken, P.A., and T. Kram. 1990. Calculation of Actual CO7 Emissions from Fossil Fuels. Presented
at ETSAP-IV workshop Petten, the Netherlands, 9-12 April 1990 and IPCC Preparatory
Workshop, Paris, 22-23 May 1990.
Dl-15
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Rypinski. 1994. Memorandum of July 27, 1994 from Arthur Rypinski of the Energy Information
Administration to Bill Hohenstein of U.S EPA regarding "Unpublished Data for Inventory."
U.S. EPA. 1994. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 - 1993. U.S.
Environmental Protection Agency, Office of Policy, Planning, and Evaluation. EPA 230-R-
94-014
Dl-16
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DISCUSSION 2
GREENHOUSE GAS EMISSIONS FROM
PRODUCTION PROCESSES
OVERVIEW
Emissions are often produced as a by-product of various non-energy related activities. That
is, these emissions are produced directly from the process itself and5are not a result of energy
consumed during the process. For example, in the industrial sector raw materials are chemically
transformed from one state to another. This .transformation often.results in the release of
greenhouse gases such as carbon dioxide. The production processes presented in this section include:
adipic acid production, carbon dioxide manufacture, cement production, lirrie production," limestone'»
use (e.g., for iron and steel making, flue gas desulfurization, and glass-manufacturing),, riitrie acid <
production, soda ash production and use, HCFC-22 production, and aluminum production. ;A section '
is also provided which lists other industrial source categories that potentially contribute to emissions
of greenhouse gases. There are currently no available methodologies for estimating emissions'from
these sources.
DESCRIPTION OF WORKBOOK METHODS
In general, the basic method for estimating emissions from production processes is to gather0
information on the various activity levels required for the calculation (i.e., production and/or
consumption data) and multiply them by their respective emission coefficients.
Activity Level x Emissions Factor = Amount Emitted
In some instances, emission control or recovery technologies have been implemented at facilities
which will reduce the amount of gas actually emitted. These avoided emissions should be accounted^
for by subtracting the amount recovered or avoided from emission totals.
The remainder of this section provides a description of each source category covered in
Workbook Section 2 and a summary of how the emissions factors presented were derived.
Information is also provided on the uncertainties associated with estimating emissions from each
source category.
2.1 CARBON DIOXIDE EMISSIONS FROM CEMENT PRODUCTION
Carbon dioxide emitted during the cement production process represents the most significant
non-energy source of industrial carbon dioxide emissions. Cement is produced in most states (and
in Puerto Rico) and is used in all of them. Carbon dioxide is created when calcium carbonate
(CaCO3) is heated in a cement kiln to form lime (calcium oxide or CaO) and carbon dioxide.. This
process is known as calcination or calcining:
CaCO3 + Heat - CaO + CO2
D2-1
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The lime is then combined with silica-containing materials (provided to the kiln as clays or shales)
to form dicalcium or tricalcium silicates, two of the four major compounds in cement clinker (Griffin,
1987). This lime is combined with other materials to produce clinker (an intermediate product from
which finished portland and masonry cement are made), while the carbon dioxide is released into the
atmosphere.
Carbon dioxide emissions are estimated by applying an emission factor, in tons of CO2
released per ton of clinker produced, to the total amount of clinker produced. The emission factor
recommended for use by states is the product of the fraction of lime used in the cement clinker and
a constant reflecting the mass of CO2 released per unit of lime. The emission factor was calculated
as follows:
(44.01 glmole COj\
= fraction CaO x -
J i 56.08 glmole CaO)
This analysis assumes an average lime fraction for clinker of 64.6 percent, which yields an emission
factor of 0.507 tons of carbon dioxide per ton of clinker produced.
Masonry cement requires additional lime over and above the lime used in the clinker. During
the production of masonry cement, non-plasticizer additives such as lime, slag, and shale are added
to the cement, increasing its weight by 5 percent. Lime accounts for approximately 60 percent of the
added substances. An emission factor for this additional lime can be calculated as follows:
EF -I fraction ofWei8ht added } x \*added\ x \Um S/mole CO,}
"ia* (l + fraction of weight added) X [ substance j \56.08 glmole CaO}
0.05
+ 0.05
= 0.0224
x 0.60 x 0.785.
Thus, 0.0224 tons of additional carbon dioxide are emitted for every ton of masonry cement produced.
Some amount of CO2 is reabsorbed when the cement is used for construction. As cement
reacts with water, alkaline substances such as calcium hydroxide are formed. During the curing
process, these compounds may react with CO2 in the atmosphere to create calcium carbonate. This
reaction only occurs in roughly the outer 0.2 inches of surface area. . Since the amount of CO2
reabsorbed is thought to be minimal, a methodology is not included here.
2.2 NITRIC ACID
The production of nitric acid (HNO3) produces nitrous oxide (N2O) as a by-product via the
oxidation of ammonia. Nitric acid is a raw material used primarily to make synthetic commercial
fertilizer. It is also a major component in the production of adipic acid (a feedstock for nylon) and
explosives. In 1990, this inorganic chemical ranked thirteenth in total production of all chemicals in
the United States. Relatively small quantities of nitric acid are employed for stainless steel pickling,
metal etching, rocket propellants, and nuclear-fuel processing. Virtually all of the nitric acid
produced in the U.S. is manufactured by the catalytic oxidation of ammonia (U.S. EPA, 1985).
D2-2
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During this reaction, nitrous oxide is formed as a by-product and is released from reactor vents into
the atmosphere. While the waste gas stream may be cleaned of other pollutants such as nitrogen
dioxide, there are currently no control measures aimed at eliminating nitrous oxide.
Nitric acid production in the U.S. was approximately 8 million tons in 1990. Off-gas >
measurements at one nitric acid production facility snowed N2O emission rates to be approximately
0.002 to 0.009 tons of N2O per ton of nitric acid produced. It is therefore recommended that states
use the midpoint of the range as the emissions factor to estimate emissions from this source: 0.0055
tons N2O per ton of nitric acid produced.
The emission factors presented are highly uncertain because of insufficient information on
manufacturing processes and emission controls. Although no abatement techniques are specifically
directed at removing nitrous oxide, existing control measures for other pollutants will have .some
effect on the nitrous oxide contained in the gas stream. While the emission coefficients presented
here do account for these other abatement systems, there may be some variation between different
production facilities depending on the existing level of pollution control at a given plant.
2.3 ADIPIC ACID
Adipic acid is a white crystalline solid used in the manufacture of synthetic fibers, coatings,
plastics, urethane foams, elastomers, and synthetic lubricants. Commercially, it is the most important
of the aliphatic dicarbbxylic acids, which are used to manufacture polyesters. Ninety percent of all
adipic acid produced in the United States is used in the production of nylon 6,6, as well as production
of some low-temperature lubricants. It is also used to provide foods with a "tangy" flavor. The U.S.
accounts for approximately one-third of the total annual global production of adipic acid (Thiemens
& Trogler, 1991).
Adipic acid is produced through a two-stage process. The second stage involves the oxidation
of ketone-alcohol with nitric acid. Nitrous oxide is generated as a by-product of this reaction and
enters the waste gas stream. In the U.S., this waste gas is treated to remove NOX and other regulated
pollutants (arid, in some cases, N2O as well) and is then released into the atmosphere. There are
currently four plants in the U.S. that produce adipic acid. In 1990. two of these plants had emission
control measures that destroyed about 98 percent of the nitrous oxide before it was released into the
atmosphere (Radian, 1992). By 1996, all adipic acid production plants will have nitrous oxide
emission controls in place as a result of a voluntary agreement among producers.
Since emissions of N2O in the U.S. are not currently regulated, very little emissions data exist.
However, based on the overall reaction stoichiometry for adipic acid, it is estimated that
approximately 0.3 tons of nitrous oxide is generated for every ton of adipic acid produced (Radian,
1992). Because N2O emissions are controlled in some adipic acid production facilities, the amount
of N2O that is actually released will depend on the level of emission controls in place at a specific
production facility.
2.4 LIME MANUFACTURE
Lime is a manufactured product with many chemical, industrial, and environmental uses. In
1990, lime ranked fifth in total production of all chemicals in the United States. Its major uses are
D2-3
-------
in steelmaking, construction, pulp and paper manufacturing, and water and sewage treatment. Lime
is manufactured by heating limestone (mostly calcium carbonate -- CaCO3) in a kiln, creating calcium
oxide (quicklime) and carbon dioxide. The carbon dioxide is driven off as a gas and is normally
emitted to the atmosphere.
Lime is an important chemical with a variety of industrial, chemical, and environmental
applications in the U.S. Lime production involves three main processes: stone preparation,
calcination, and hydration. Carbon dioxide is generated during the calcination stage, when limestone
(calcium carbonate or a combination of calcium and magnesium carbonate) or other calcium
carbonate materials are roasted at high temperatures. This process is usually performed in either a
rotary or vertical kiln, although there are a few other miscellaneous designs. Carbon dioxide is
produced as a by-product of this process, just as CO2 is released during clinker production (see
previous section on cement production). The carbon dioxide is driven off as a gas and normally exits
/the system with the stack gas. The mass of CO2 released per unit of lime produced can be calculated
based on their molecular .weights:
44.01 g/mole CO2 +' 56.08 g/mole CaO = 0.785
Therefore, an emissions factor of 0.785 tons of CO2 per ton of lime manufactured is recommended
for use by states.
The term "lime" is actually a general term that includes various chemical and physical forms
of this commodity. Uncertainties in emission estimates can be attributed to slight differences in the
chemical composition of these products. For example, although much care is taken to avoid
contamination during the production process, lime typically contains trace amounts of impurities such
as iron oxide, alumina, and silica. Due to differences in the limestone used as a raw material, a rigid
specification of lime material is impossible. As a result, few plants manufacture lime with exactly the
same properties. .
A portion of the carbon dioxide emitted during lime production will actually be reabsorbed
when the lime is consumed. In most processes that use lime (e.g., water softening), carbon dioxide
reacts with the lime to create calcium carbonate. This is not necessarily true about lime consumption
in the steel industry, however, which is the largest consumer of lime. A detailed accounting of lime
use in the U.S. and further research into the associated processes are required to quantify the amount
of carbon dioxide that will be reabsorbed.
2.5 LIMESTONE USE
Limestone is a basic raw material used by a wide variety of industries, including the
construction, agriculture, chemical, and metallurgical industries. For example, limestone can be used
as a flux or purifier in refining metals such as iron. In this case, limestone heated in a blast furnace
reacts with impurities in the iron ore and fuels, generating carbon dioxide as a by-product. Limestone
is also used for glass manufacturing and for SO2 removal from stack gases in utility and industrial
plants.
Limestone is heated during these processes, generating carbon dioxide as a by-product.
Carbon emissions can be calculated by multiplying the amount of limestone consumed by type (i.e.,
calcite or dolomite) by the carbon content of the limestone. Therefore, emissions factors
D2-4
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recommended for use by states are 0.12 tons C per ton of limestone (or calcite) consumed and 0.13
tons C per ton of dolomite consumed.1 Estimates are then multiplied by 44/12 to obtain the
amount of carbon emitted as CO2.
Uncertainties in estimates calculated using this method can be attributed to variations in the
chemical composition of limestone. In addition to calcite, limestone may contain smaller amounts of
magnesia, silica, and sulfur. The exact specifications for limestone or dolomite used as flux stone vary
with the pyrometallurgical process, the kind of ore processed, and the final use of the slag. Similarly,
the quality of the limestone used for glass manufacturing will depend on the type of glass being
manufactured. Uncertainties also exist in the activity data. Much of the limestone consumed in the
U.S. is reported as "other unspecified uses", and therefore, are difficult to dissagregate by type.
2.6 SODA ASH CONSUMPTION AND MANUFACTURE
Commercial soda ash (sodium carbonate) is used in many familiar consumer products such
as glass, soap and detergents, paper, textiles, and food. About 75 percent of world production is
synthetic ash made from sodium chloride; the remaining 25 percent is produced from natural sources.
The U.S. produces only natural soda ash. During the production process, trona (the principal ore
from which natural soda ash is made) is calcined in a rotary kiln and chemically transformed into a
crude soda ash that requires further processing. Carbon dioxide and water are generated as a by-
product of the calcination process. CO2 emissions from the calcination of trona can be estimated
based on the following chemical reaction:
2(Na3H(CO3)2-2H2O) -* 3Na2CO3 + 5H2O + CO2
[trona] [soda ash]
Based on this formula, it takes approximately 10.27 tons of trona to generate 1 ton of CO2, or 0.0974
tons of CO2 per ton of trona produced.
An alternative method of natural soda ash production uses sodium carbonate-bearing brines.
To extract the sodium carbonate, the complex brines are first treated with carbon dioxide in
carbonation towers to convert the sodium carbonate into sodium bicarbonate, which will precipitate
under these conditions. The precipitated sodium bicarbonate is then calcined back into sodium
carbonate. Although CO2 is generated as a by-product, the CO2 is recovered and recycled for use
in the carbonation stage and is never actually released.
Carbon dioxide is also released when soda ash is consumed. Glass manufacture represents
about 49 percent of domestic soda ash consumption, with smaller amounts used for chemical
manufacture, soap and detergents, flue gas desulfurization, and other miscellaneous uses. In each
of these applications, a mole of carbon is released for every mole of soda ash used. Thus,
approximately 0.113 tons of carbon is released for every ton of soda ash consumed, or 0.415 tons of
CO2 per ton of soda ash consumed.
1 Limestone (CaCO3) and dolomite (CaMg(CO3)2) are collectively referred to as limestone by the
industry, and intermediate varieties are seldom distinguished.
D2-5
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2.7 CARBON DIOXIDE MANUFACTURE
Carbon dioxide is used for a variety of industrial and miscellaneous applications, including
food processing, chemical production, carbonated beverages, and enhanced oil recovery. Carbon
dioxide used for enhanced oil recovery is injected into the ground to increase reservoir pressure, and
is therefore considered sequestered2. For the most part, however, carbon dioxide used in these
applications will eventually enter the atmosphere.
With the exception of a few natural wells, carbon dioxide is produced as a by-product from
the production of other chemicals (e.g., ammonia), or obtained by separation from crude oil or natural
gas. Depending on the raw materials that are used, the by-product carbon dioxide generated during
these production processes may already be accounted for in the CO2 emission estimates from fossil
fuel consumption (either during combustion or from non-fuel use). For example, ammonia is
manufactured using natural gas and naphtha as feedstocks. Carbon dioxide emissions from this
process are included in the portion of carbon for non-fuel use that is not sequestered (see Workbook
and Discussion Section 1).
Carbon dioxide emissions are calculated by estimating the fraction of manufactured carbon
dioxide that is not accounted for in these other emission sources and multiplying it by a recommended
emissions factor of 1 ton of CO2 per ton of CO2 manufactured. It is assumed that 100 percent of
CO2 manufactured for these other uses is eventually released to the atmosphere.
2.8 EMISSIONS OF PERFLUORINATED CARBONS (PFCs) AND CO2 FROM ALUMINUM
SMELTING
The aluminum production industry is thought to be the largest source of two PFCs - CF4 and
C2F6. Emissions of these two potent greenhouse gases occur during the reduction of alumina in the
primary smelting process.3 Aluminum is produced by the electrolytic reduction of alumina (A12O3)
in the Hall-Heroult reduction process, whereby alumina is dissolved in molten cryolite (Na3AlF6),
which acts as the electrolyte and is the reaction medium. PFCs are formed during disruptions of the
production process known as anode effects (AE), which are characterized by a sharp rise in voltage
across the production vessel. The PFCs can be produced through two mechanisms: direct reaction
of fluorine with the carbon anode; and electrochemical .formation. In both cases the fluorine
originates from dissociation of the molten cryolite.
Because CF4 and C2F6 are inert, and therefore pose no health or local environmental
problems, there has been little study of the processes by which emissions occur and the important
factors controlling the magnitude of emissions. In general, however, the magnitude of emissions for
a given level of production depends on the frequency and duration of the anode effects during that
production period. The more frequent and long-lasting the anode effects, the greater the emissions.
f\
It is unclear to what extent the CO2 used for enhanced oil recovery will be re-released. For example,
the carbon dioxide used for EOR is likely to show up at the wellhead after a few years of injection
(Hangebrauk et al., 1992). This CO2, however, is typically recovered and reinjected into the well. More
research is required to determine the amount of carbon dioxide that may potentially escape. For the purposes
of this analysis, it is assumed that all of the CO2 remains sequestered.
3 Perfluorinated carbons are not emitted during the smelting of recycled aluminum.
D2-6
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The methodology used to estimate emissions of PFCs from aluminum production first
calculates a per unit production emissions factor as a function of several important operating
variables, including average anode effect frequency and duration. Total annual emissions are then
calculated based on reported annual production levels. The five components of the per unit
production emissions factor are:
• the amount of CF4 and C2F6 emitted during every minute of an anode effect, per kAmp
of current;
• the average duration of anode effects, expressed in anode effect minutes per effect;
• the average frequency of anode effects, expressed in anode effects per day;
• the current efficiency for aluminum smelting (no units); and,
• the current required to produce a metric ton of aluminum, assuming 100 percent
efficiency.
Using currently available data for the U.S., this methodology yields a range in the emissions
factor of 0.0003 to 0.0009 tons CF4 per ton of aluminum produced (with a midpoint of 0.0006 tons
CF4 per ton of aluminum produced) (U.S. EPA, 1993). The emissions factor for C2F6 is estimated
to be an order of magnitude lower, and therefore ranges from 0.00003 to 0.00009 ton C2F6 per ton
of aluminum produced (with a midpoint of 0.00006 tons C2F6 per ton of aluminum produced).
Because there has been relatively little study of emissions from this source, considerable
uncertainty remains in the emissions factors presented here. In particular, the value for emissions
per AE minute per kAmp is based on a single measurement study which may not be representative
of the industry as a whole (U.S. EPA, 1993). For example, this emissions factor may vary by smelter
technology type, among other factors. The average duration of anode effects, according to
preliminary results of ongoing research, may in fact be considerably shorter than the current values
used. The average frequency of anode effects and the current efficiency are well documented,
although they may change over time as operating efficiencies improve. Because recent studies
indicate that the values for the important variables used in developing the emission coefficient may
actually be lower than previously thought, the estimates calculated using these emission factors are
likely to be conservatively high.
Carbon dioxide is also emitted during the aluminum production process when alumina
(aluminum oxide) is reduced to aluminum. The reduction of the alumina occurs through electrolysis
in a molten bath of natural or synthetic cryolite. The reduction cells contain a carbon lining that
serves as the cathode. Carbon is also contained in the anode, which can be a carbon mass of paste,
coke briquettes, or prebaked carbon blocks. During reduction, some of this carbon is oxidized and
released to the atmosphere as carbon dioxide. Approximately 1.5 to 2.2 tons of CO2 are emitted for
each ton of aluminum produced (Abrahamson, 1992). The CO2 emissions from this source, however,
are already accounted for in the non-fuel use portion of CO2 emissions from fossil fuel consumption.
which was estimated in Workbook Section 1 (i.e., the carbon contained in the anode is considered
a non-fuel use of petroleum coke). Thus, to avoid double-counting, CO2 emissions from aluminum
production should not be included the industrial process emission totals.
2.9 EMISSIONS OF PARTIALLY HALOGENATED COMPOUNDS (HFCs)
HFCs are chemicals containing hydrogen, carbon, and fluorine. Only recently have they been
produced on a large scale. As some of the primary alternatives to the ozone depleting substances
D2-7
-------
(ODSs) being phased out under the Montreal Protocol and subsequent amendments, the use of HFCs
is expected to increase in the future. Sources of HFC emissions can be categorized as follows:
• Emissions as by-products of chemical production processes, and
• Emissions of HFCs used as substitutes for ODSs in refrigeration, foam blowing, solvent,
aerosol, and fire extinguishing applications.
The only type of HFC known to be emitted in significant quantities, at present, is HFC-23 emitted
as a by-product of HCFC-22 production. Therefore, a methodology for estimating emissions of HFCs
as an ODS replacement is not presented at this time.
HFC-23 as a By-Product
The suggested methodology for estimating emissions from this source is to obtain estimates
of HCFC-22 production from in-state chemical manufacturers and multiply this production by 0.04
tons of HFC-23 per ton of HCFC-22 produced. The factor of 0.04 tons HFC-23/ton HCFC-22
produced was chosen because it is assumed that, in general, by-product emissions of HFC-23 are
assumed to be 4 percent of HCFC-22 production. However, using this emissions factor may
overestimate emissions, because at some production facilities, emission control measures may have
been implemented that can halve by-product emissions of HFC-23. States should enquire about
emission control devices at individual.production facilities to increase the accuracy of their estimates.
2.10 EMISSIONS FROM OTHER PRODUCTION PROCESSES
Several processes that produce greenhouse gas emissions are listed in Table D2-1. This is not
a definitive list since other activities do generate process emissions, although the major processes are
identified here. Each state may have additional categories that need to be identified in the future.
There are currently no recommended emission estimation methodologies for these sources.
Table D2-1
Emissions From Production Processes
PROCESS
Agricultural Liming
Ferro-alloy Production
Silisium Carbid
Production
Coke Production
Nitrogen Fertilizer
Production
POLLUTANTS
NOX
X
NM
voc
CH4
CO
X
CO2
X
X
X
X
N2O
D2-8
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PROCESS
Petroleum Product
Processing (including
FOC)
Sulphur Recovery
Plants
Storage of Petroleum
Products in a Refinery
Colliery Coke
Production
Metallurgical Coke
Production
Steel Plant (electric,
EOF, etc.)
Sulfuric Acid
Production
Ammonia Production
Sodium Carbonate
Urea Production
Carbon Black
Titanium Dioxide
Ethylene Production
Propylene Production
1,2 Dichlorothane
Production
Vinylchloride
Production
Polyethylene Low
Density Production
Polyethylene High
Density Production
Polyvinylchloride
Production
POLLUTANTS
NOX
X
X
X
NM
voc
X
X
X
X
X
X
X
X
X
X
X
X
CH4
X
X
X
X
X
CO
X
X
<
.
CO2
X
X
X
N2O
X
D2-9
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PROCESS
Polypropylene
Production
Styrene Butadiene
ABS Resins
Ethylene Oxide
Formaldehyde
Production
Ethylbenzene
Production
Styrene Butadiene
Latex
Styrene Butadiene
Rubber
Phtalic Anhydride
Production
Acrylonitrile
Production
Chipboard Production
Paper Pulp Production
Bread Production
Wine Production
Beer Production
Spirits Production
Paint Applications:
manufacture of
automobiles
Paint Applications:
ship building
Paint Applications:
manufactures of metal
articles
POLLUTANTS
NOX
1
NM
voc
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
CH4
,
CO
CO2
X
X
X
X
X
N2O
•
D2-10
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PROCESS
Paint Applications:
wood products
Paint Applications:
construction and
buildings
Paint Applications:
vehicles refinishing
Paint Applications:
domestic use
Metal Degreasing
Dry Cleaning
Polymers Processing
Elastomers Processing
Rubber Processing
Plastics Processing
Pharmaceutical
Processing
Paints Processing
Inks Processing
Glues Processing
Printing Industry
(solvent use only)
Domestic Solvent Use
POLLUTANTS
NOY
A
NM
voc
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
CH4
CO
CO2
N20
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\
Bureau of Mines. 1992a. Cement: Annual Report 1990. U.S. Department of the Interior, Bureau of
Mines. Washington, DC. April, 1992.
D2-11
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Bureau of Mines. 1992b. Lime: Annual Report 1991. U.S. Department of the Interior, Bureau of
Mines. Washington, DC. November, 1992.
Bureau of Mines. 1993a. Aluminum, Bauxite, and Alumina: Annual Report 1991. U.S. Department
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Freedonia Group, Inc. 1991. Business Research Report B286: Carbon Dioxide. The Freedonia
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Corporation, Rochester, NY.
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Thiemens, Mark H. and William C. Trogler. 1991. "Nylon Production: An Unknown Source of
Atmospheric Nitrous Oxide. Science, vol. 251, page 932. February 22, 1991.
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Tresouthick, S.W., and A. Mishulovich. .1990. "Energy and Environment Considerations for the
Cement Industry," In conference proceedings Energy and Environment in the 21st Century.
Massachusetts Institute of Technology, Cambridge, Massachusetts. March 26-28,1990. B-110
to B-123
U.S. EPA. 1993. Proceedings - Workshop on Atmospheric Effects, Origins, and Options for Control
of Two Potent Greenhouse Gases: CF4 and C^F^. Sponsored by the Global Change Division,
Office of Air and Radiation, EPA, April 21-22," 1993.
U.S. EPA. 1985. Compilation of Air Pollutant Emission Factors, AP-42. U.S. EPA, Washington, DC.
D2-13
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DISCUSSIONS
METHANE EMISSIONS FROM
NATURAL GAS AND OIL SYSTEMS
OVERVIEW
Emissions from natural gas and oil systems are primarily methane, although smaller quantities
of non-methane VOCs, carbon dioxide, and carbon monoxide can be emitted. It is important to
account for emissions from oil and natural gas systems separately in order to differentiate between
emissions associated with particular fuels. For purposes of the workbook, the terms natural gas or gas
are used to refer to both natural gas (extracted from the ground), and "synthetic" or "substitute" natural
gas (comprised mostly of methane) produced from other petroleum-based products or sources.
Depending on its origin and how it is processed, commercially distributed natural gas also will include
various amounts of non-methane hydrocarbons (e.g., ethane, butane, propane, and pentane), carbon
monoxide, carbon dioxide, and nitrogen. Oil is used to refer to both oil extracted directly from the
ground and various synthetic processes such as oil shale or tar sands.
Methane is emitted during oil and gas production, storage, transportation and distribution.
"Fugitive" sources of emissions within oil and gas systems include: releases during normal operations,
such as emissions associated with venting and flaring during oil and gas production, chronic leaks or
discharges from process vents; emissions during routine maintenance, such as pipeline repair; and
emissions during system upsets and accidents.
Oil and Natural Gas System Overview: Oil and gas systems are divided into three main parts for this
discussion:
1. Oil and Gas Production: Oil and gas are withdrawn from underground formations using on-
shore and off-shore wells. Oil and gas are frequently withdrawn simultaneously from the same
geologic formation, and then separated. Gathering lines are generally used to bring the crude
oil and raw gas to one or more collection point(s) within a production field. Because methane
is the major component of natural gas, leaks or venting from these systems result in methane
emissions. .
2. Crude Oil Transportation and Refining: Crude oil is transported by pipeline to tankers and
refineries. Often, the crude oil is stored in tanks for a period of time. Methane is usually
found in the crude oil stream, and leaks or venting of vapors from these facilities result in
methane emissions, particularly from crude oil tankering. Methane emissions from crude oil
streams are strongly dependent on the original methane content of the crude oil and its
preparation for transport.
Refineries process crude oil into a variety of hydrocarbon products such as gasoline and
kerosene. During the refining process, methane and other hydrocarbons are separated and
methane may be leaked or vented in some processes. Refinery outputs, referred to as "refined
products," generally contain negligible amounts of methane. Consequently, methane emissions
are not estimated for transporting and distributing refined products.
D3-1
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3. Natural Gas Processing, Transportation, and Distribution: Natural gas is processed to
recover heavier hydrocarbons, such as ethane, propane and butane, and prepare the dried gas
for transporting to consumers. Most gas is transported through transmission and distribution
pipelines. A small amount of gas is shipped by tanker as liquefied natural gas (LNG). Because
only a small portion of gas is transported as LNG. emissions from LNG facilities are not
included in this discussion.
The following are the main processing, transportation, and distribution activities:
• Gas processing plants: Natural gas is usually processed in gas plants to produce
products with specific characteristics. Depending on the composition of the
unprocessed gas, it is dried and a variety of processes may be used to remove most of
the heavier hydrocarbons, or condensate, from the gas. Processed gas is then injected
into the natural gas transmission system and the heavier hydrocarbons are marketed
separately. Unintentional leaks of methane occur during natural gas processing.
• Transmission pipelines: Transmission facilities are high pressure lines that transport gas
from production fields, processing plants, storage facilities, and other sources of supply
over long distances to distribution centers, or large volume customers. Although
transmission lines are usually buried, a variety of above underground facilities support
the overall system including metering stations, maintenance facilities, and compressor
stations located along pipeline routes.
Compressor stations, which maintain the pressure in the pipeline, generally include upstream
scrubbers where the incoming gas is cleaned of particles and liquids before entering the
compressors. Reciprocating engines and turbines are used to drive the compressors.
Compressor stations normally use pipeline gas to fuel the compressor. They also use the gas
to fuel electric power generators to meet the station's electricity requirements.
• Distribution systems: Distribution pipelines are extensive networks of generally small
diameter, low pressure pipelines. Gas enters distribution networks from transmissions
systems, known as "gate stations", where the pressure is reduced for distribution within
cities or towns.
Sources of Methane Emissions in the Oil and Natural Gas Systems: Emissions from oil and gas
systems can be categorized into: (1) emissions during normal operations (2) routine maintenance; and
(3) system upsets and accidents. In Table D3-1 these emission types are linked to the different stages
in oil and gas systems. Typically the majority of the emissions are from normal operations.
1. Normal Operations: Normal operations are the day-to-day operations of a facility absent of
occurrence of abnormal conditions. Emissions from normal operations can be divided into two
main source categories: (1) venting and flaring and (2) discharges from process vents, chronic
leaks, etc.
Venting and Flaring - Venting and flaring refers to the disposal of the gas that cannot be
contained or otherwise handled. Such venting and flaring activities are associated with
combined oil and gas production and take place in production areas where gas and pipeline
infrastructure is incomplete and the natural gas is not injected into reservoirs.
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Table D3-1. Emissions from Oil and Natural Gas Systems
Segment
Oil and Gas Production
Oil and gas wells
Gathering lines
Treatment facilities
Crude Oil Transportation
and Refining
Pipelines
Tankers
Storage tanks
Refineries
Natural Gas Processing,
Transportation, and
Distribution
Gas plants
Underground storage
reservoirs
Transmission
Pipelines
Distribution pipelines
Major Emissions Sources
Venting
Normal operation: fugitive
emissions; deliberate releases
from pneumatic devices and
process vents.
Normal operations: fugitive
emissions; deliberate releases
from process vents at
refineries, during loading and
unloading of tankers and
storage tanks.
Normal operations: fugitive
emissions; deliberate releases
from pneumatic devices and
process vents.
Other Potential Emission
Sources
Flare and combustion in gas
turbines, 1C engines, etc.
Routine maintenance
System upsets and accidents
Combustion in gas turbines,
1C engines, etc.
Routine maintenance
System upsets and accidents
Combustion in gas turbines,
1C engines, etc.
Routine maintenance
System upsets and accidents
Source: IPCC, 1994
Venting activities release methane because vented gas typically has a high methane content.
If the excess gas is burned in flares, the emissions of methane will depend on how efficient the
burning processes are. Generally, the combustion efficiency for flare sources are assumed to
be between 95 and 100 percent. To estimate the methane emissions from venting and flaring
activities satisfactorily, it is required to know the flare efficiency rates and the distributed
quantity of gas vented and gas flared.
Discharges from Process Vents. Chronic Leaks, etc. - Methane emissions will also occur when
gas pipeline infrastructure is available and the market for natural gas is well developed. Oil
and gas production, gas processing, oil and gas transportation and gas distribution facilities emit
methane due to a wide variety of operating practices and factors, including:
• Emissions from pneumatic devices (gas-operated controls such as valves and actuators).
These emissions depend on the size, type, and age of the devices, the frequency of their
operation, and the quality of their maintenance.
• Leaks from system components. These emissions are unintentional and typically consist
of continuous releases associated with leaks from the failure of a seal or the
development of a flaw, crack or hole in a component designed to contain or convey oil
or gas. Connections, valves, flanges, instruments, and compressor shafts can develop
leaks from cracks or from corrosion.
D3-3
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• Emissions from process vents, such as vents on glycol dehydrators and vents on crude
oil tankers and storage tanks. Vapors, including methane, are emitted from the vents
as part of the normal operation of the facilities. However, such process vents are
minor methane sources in most gas production facilities.
• Emissions from starting and stopping reciprocating engines and turbines.
• Emissions during drilling activities, e.g., gas migration from reservoirs through wells.
2. Routine Maintenance: Routine maintenance includes regular and periodic activities performed
in the operation of the facility. These activities may be conducted frequently, such as launching
and receiving scrapers (pigs) in a pipeline, or infrequently, such as evacuation of pipes
("blowdown") for periodic testing or repair. In each case, the required procedures release gas
from the affected equipment. Releases also occur during maintenance of wells ("well
workovers") and during replacement or maintenance of fittings.
3. System Upsets and Accidents: Systems upsets are unplanned events in the system, most
common of which is a sudden pressure surge resulting from the failure of a pressure regulator.
The potential for unplanned pressure surges is considered during facility design, and facilities
are provided with pressure relief systems to protect the equipment from damage due to the
increased pressure.
Release systems vary in design. In some cases, gases released through relief valves may
be collected and transported to a flare for combustion or re-compressed and reinjected into the
system. In these cases, methane emissions associated with pressure relief events will be small.
In older facilities, relief systems may vent gases directly into the atmosphere or send gases to
flare systems where complete combustion may not be achieved.
The frequency of system upsets varies with the facility design and the operating practices. In
particular, facilities operating well below capacity are less likely to experience system upsets and
related emissions. Emissions associated with accidents are also included in the category of
upsets. Occasionally, gas transmission and distribution pipelines are accidentally ruptured by
construction equipment of other activities. These ruptures not only result in methane
emissions, but they can be extremely hazardous as well.
Table D3-1 lists those emissions types that are the most important sources within each segment
of the oil and gas industry. Based on available information, the sources listed as "major"
account for the majority of emissions from each segment. Because our data are limited and
there is considerable diversity among oil and gas systems throughout the U.S., other potential
sources are also listed which may, in some cases, be important contributors to emissions.
DESCRIPTION OF WORKBOOK METHOD
The method presented in the Workbook Section is essentially one in which standard emissions
factors are multiplied by activity data that describe the oil and gas system size or capacity. While it is
relatively easy to obtain the necessary activity data, it should be noted that the basis for developing the
emissions factors is very weak at this time. Because oil and natural gas systems are comprised of a
complex set of facilities, simple relationships between emissions and components of the systems are not
easily defined. Additionally, no single set of emissions factors can apply to all conditions.
D3-4
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Consequently, more detailed assessments are required to reflect the diverse nature of the industry
throughout the U.S.
The emissions factors presented in the Workbook Section were developed as part of the IPCC
emissions inventory guidelines for oil and gas systems (IPCC, 1994). The emissions factors were
developed based on a review of all available published estimates of methane emissions from the various
sectors of the oil and gas industry. Although the objective in developing the emissions factors was to
include all emissions sources and types (described in the previous section), in some cases no published
emissions estimates were found for categories of emissions believed to be negligible.
Using the available published emissions estimates, the implied emissions factors from each study
were developed by dividing the emissions estimates by appropriate measures of system size or capacity
in energy units. Across the studies, the resulting implied emissions factors per unit of energy showed
a wide range. The estimates were grouped by region, and within each region a range of emissions
factors was selected for the IPCC emissions inventory guidelines. The emissions factors used in the
Workbook Section are the factors developed from studies of the U.S. system.
. The emissions factors can be considered to be no better than "order of magnitude" estimates.
Actual emissions depend on site specific characteristics including:
• facility design;
• facility operation; and
• facility maintenance.
While these characteristics were considered to various extents in the studies that formed the basis for
the emissions factor estimates, the variation in characteristics among systems throughout the U.S.
implies that no single set of emissions factors can be adequate for estimating emissions.
ALTERNATE METHODOLOGIES
To estimate emissions from oil and gas systems, it would be preferred to measure emissions with
precise instruments. However, due to the diverse nature of the various types of emissions and the fact
that many emissions occur periodically or unexpectedly, precise measurements are not practical in most
cases. Additionally, no single method for estimating emissions will be appropriate for all the different
types of emissions. Although much of the information required to estimate emissions from oil and gas
systems is not readily-available at this time, the data may be available for the. U.S. or will shortly be
available from ongoing work. A minimum data set should be established separately for oil and natural
gas systems based on this information to estimate the various types of emissions from the different
system components identified above. These two minimum data sets are summarized in Table D3-2.
The data sets summarized in Table D3-2 indicate the minimum amount of activity data needed
to estimate emissions. For each of the data items, an emission factor(s) would need to be developed.
To assist in the development of appropriate emission factors, emission data are currently being
generated by the Gas Research Institute (GRI) and EPA. These could be used to develop the range
of emission factors for the activity data identified in Table D3-2. Information about the systems
examined in the detailed studies would need to be assembled, described, compared, and contrasted so
D3-5
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that states could identify pieces of these systems that are similar to theirs and select appropriate
emissions factors.
In addition to the GRI/EPA study, there are other approaches that could be employed to
determine oil and natural gas system emissions. The following section discusses the range of methods
identified and the types of emissions for which they may be useful; the discussion focuses primarily on
applications for natural gas systems. These more complex approaches could be used for refining
emission estimates derived from the minimum methodology.
Gas Accounting Data
Gas accounting data are routinely developed during the operation of gas systems. These data
describe the quantities of gas that are produced, transported, injected, withdrawn, used, or sold at
various stages. Various instrumentation is used to measure pressure, temperatures, and flow rates to
develop these accounting data.
Gas accounting data can be very useful for estimating emissions associated with routine
maintenance activities. The .quantities of gas released during these activities are often estimated and
recorded using standardized procedures. For example, these data can be used to estimate gas that is
released during scheduled repair of transmission pipelines.
Routinely collected accounting data are often not adequate for estimating fugitive emissions
from production and distribution facilities (i.e., leaks from pipes and equipment). These emissions are
usually too small to be estimated because the meters and instruments used to measure gas flows are
not adequately precise to measure the small leaks that are generally encountered. Additionally, other
factors that are not well quantified (such as theft) reduce the precision of the routinely-collected gas
accounting data.
Unlike routinely-collected accounting data, specially conducted measurement studies using
specially-designed and operated meters and instruments may be useful for estimating fugitive emissions
from designated sections of distribution systems. In conducting such studies, care must be taken to
ensure that the segments of distribution systems that are studied are representative of the overall
distribution system.
Emission Factors
j
Emission factors provide estimates of emissions for specific types of equipment over specified
periods of time, such as 0.1 cubic meter (m3) per hour from a given type of valve. Emission factors
are most commonly used to estimate fugitive emissions from equipment. The most important
consideration in using emission factors is that care must be taken to ensure that the emission factors
are appropriate for the type of equipment in question, including the maintenance practices that are
performed. As described below there are several major sources of emission factors for the types of
equipment commonly found in gas production fields and gas processing plants. To use the emission
factors, the numbers of components of various types are multiplied by the emission factors specific to
those types. The aggregate is an estimate of the total emissions.
Procedures have been developed to estimate emission factors quantitatively (Radian 1982).
These procedures generally require that: ,
D3-6
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Table D3-2
Minimum Data Sets for Oil and Natural Gas Systems"
System Component
Pre-production
Production and Central
Processing
Venting and Flaring
Transportation
Distribution
Oil System Data Set
Activity Data Needed
Number of successfully drilled wells
Number of operating wells
Level of oil production
Composition of the oil
Type of emission controls
Flaring losses
Composition of the oil .
Quantity of oil transported by
ocean tanker or large pipeline
Quantity of oil distributed
Emission Factor
To be determined
To be determined
To be determined
To be determined
To be determined
To be determined
To be determined
To be determined
To be determined
System Component
Pre-production
Production and Central
Processing
Venting and Flaring
Transmission
Distribution
Natural Gas System Data Set
Activity Data Needed
Number of successfully drilled wells
Number of operating wells
Quantity of natural gas produced
Composition of the natural gas
Type of emission controls
Flaring losses
Composition of the gas (% methane)
Length of transmission piping
Length of pipe designed by pipe type
a For each system component, the activity data level would be multiplied by the
determine emissions for that component.
To be determined
To be determined
To be determined
To be determined
To be determined
To be determined
To be determined
To be determined
To be determined
appropriate emission factor to
D3-7
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• the numbers of each type of component be counted (e.g., the number
of valves, etc.);
• - a sample of components be selected randomly (this selection is often
stratified using an indication of the leak rate);
• the actual emission rates (e.g., in m3 per hour) from the individual
components selected are measured;
• the measurements are used to develop emission factors that consider
the different component types and represent the weighting of the strata;
and
• the emission factors are applied to the total number of components
identified.
The advantage of developing emission factors is that the approach reflects the condition of equipment
and maintenance practices at specific facilities and is based on actual physical measurements and
reliable statistical techniques. The drawback of the approach is that it can be costly and can produce
estimates that have a wide range of uncertainty associated with them. Currently, U.S. EPA and GRI
are developing a system that will attempt to quantify uncertainty, especially for sources where emissions
and uncertainty appear to be high.
Emission factors can also be used to estimate emissions from instruments powered by
compressed gas. The number of various types of instruments must be obtained, and the emissions
associated with the use of each type must be estimated or obtained from manufacturers.
Leak Repair Data
Leak detection and repair programs generally produce data on the number of various types of
leaks detected and repaired in distribution systems. Unfortunately, the quantity of gas emitted from
individual leaks is generally not available. Therefore, based on the data that are usually, collected,
emissions from line leaks are not quantifiable.
Activity Studies
Total emissions can also be estimated by multiplying the amount emitted during an activity by
the number of times the activity occurs per year. For example, the emissions associated with starting
a compressor or scraping a given length of pipeline can be estimated based on the procedures used.
The frequency with which these activities are undertaken for, say, a typical compressor station, can then
be estimated based on operating records, i.e., total emissions from this source is equal to the emissions
per occurrence times the number of occurrences per year.
All the methods described here must consider the portion of the gas that is actually methane.
Additionally, all estimates must be careful to consider and report the temperatures and pressures at
which the volumes are estimated. All estimates should therefore be reported on a mass basis (e.g., in
tons) as well as a volume basis.
D3-8
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DATA SOURCES
No individual data source will provide all the information needed to estimate emissions from
oil and gas systems. Several studies have been undertaken that use one or more of the techniques
described above including: Cowgill and Waller (1990), PSI (1989), PSI (1990), INGAA (1989), AGA
(1989), Barns and Edmonds (1990), Radian (1982), Rockwell (1980), Lillie (1989), ADL (1989),
Schneider-Fresenius et al. (1989), and Thorell + VBB (1989). These studies are instructive regarding
the manner in which emissions can be estimated and the uncertainties inherent in the exercise.
Radian (1982) and Rockwell (1980) both involve the development and application of emissions
factors for estimating fugitive emissions. EPA (1985) has a summary of emissions factors for various
types of equipment, including compressors. Detailed emissions data from equipment that can
contribute to the development of emissions factors have been collected and reported in a variety of
studies including: Martin and Thring (1989), Leslie et al. (1989), and EPA (1979).
The studies by PSI (1989 and 1990) include assessments of activity levels and emissions per
activity occurrence. Cowgill and Waller (1990) offers the most detailed and complete analysis of the
fate of gas in a system. This study goes into considerable depth in applying a wide variety of the
approaches discussed above.
In addition to these various emissions-related studies, gas companies and agencies responsible
for gas safety and operations are important sources of data. Finally, McAllister (1988) is a useful
source of methods for estimating gas flows under various circumstances.
UNCERTAINTIES
The ability to estimate emissions from oil and gas systems will be hampered by the general lack
of data on the factors that lead to emissions. These systems are very diverse and variable. Emissions
generally cannot be estimated with simple assumptions or rules of thumb. Nevertheless, recent studies
indicate that the main types of emissions can be assessed with fairly straightforward approaches.
The most difficult emissions to estimate will likely be fugitive emissions from distribution
systems. The precision of gas accounting data is typically not adequate enough to estimate emissions
from these sources. Because these emissions can be quite important, specially-conducted measurement
studies using specially-designed and operated meters and instruments may be required. Such studies
would improve considerably the basis for estimating emissions from this source.
Additional observations have been offered, including:
• Emissions from fuel used in compressor stations and related equipment for providing
the pressure to transport the fuel over land were not included in the fuel production
category but part of the stationary combustion category. Each state should ensure that
the energy consumed for these activities is accounted for accordingly.
• More information is needed on non-methane VOC emission factors.
D3-9
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CO2 emissions from certain gas and oil fields could be significant but
are not well characterized. Additional effort is needed to understand
these emissions.
The factors for methane emitted during incomplete combustion should
be reviewed.
Sources of information for obtaining the data outlined above need to
be investigated in greater detail.
REFERENCES
ADL (Arthur D. Little). 1989. Methane Emissions from the Oil and Gas Production Industries.
Prepared for Ruhrgas A.G. July.
AGA (American Gas Association). 1989. , Survey of member interstate natural gas pipelines.
Arlington, Virginia.
AGA. 1993. Gas Facts. Arlington, Virginia.
Barns, D.W., and J.A. Edmonds. 1990. An Evaluation of the Relationship Between the Production and
Use of Energy and Atmospheric Methane Emissions. Prepared for the Office of Energy
Research, U.S. Department of Energy, Washington, D.C.
Cowgill, R.M., and R.L. Waller. 1990. Unaccounted-for Gas Project. Pacific Gas and Electric
Company (PG&E), San Ramon, California.
Crutzen, P.J. 1987. "Role of the Tropics in Atmospheric Chemistry," In R. Dickenson (ed.)
Geophysiology of Amazonia. John Wiley and Sons, New York. 107-132.
Ehhalt, D.H. 1974. The Atmospheric cycle of methane. Tellus 26(l-2):58-70.
EIA (Energy Information Administration/Department of Energy). 1994. Annual Energy Review 1993.
Energy Information Administration, U.S. Department of Energy, Washington, DC. July 1994.
EIA. 1993. Natural Gas Annual 1992: Volumes 1 & 2, DOE/EIA-0131(92)/1&2, Energy Information
Administration, U.S. Department of Energy, November, 1993.
EIA. 1988. International Energy Annual 1987. Energy Information Administration, Office of Energy
Markets and End Use, U.S. Department of Energy, Washington, D.C.
Hitchcock, D.R., and A.E. Wechsler. 1972. Biological Cycling of Atmospheric Trace Gases. Final
Report (NASW-2128) prepared by Arthur D. Little, Cambridge, Massachusetts.
INGAA (Interstates Natural Gas Association of America). 1989. Survey of member interstate natural
gas pipelines. Washington, D.C.
D3-10
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IPCC. 1994. IPCC Guidelines for National Greenhouse Gas Inventories, 3 volumes: Vol. I, Reporting
Instructions; Vol. 2, Workbook; Vol. 3, Draft Reference Manual. Intergovernmental Panel on
Climate Change, Organization for Economic Co-Operation and Development. Paris, France.
Leslie, N.P., P.G. Ghassan, and E.K. Krug. 1989. Baseline Characterization of Combustion Products
at the GRI Conventional Research House. Prepared for the Gas Research Institute, Chicago,
Illinois. August.
Lillie, I.W. 1989. Emission of Methane by the Gas and Oil Producing Industry in the Federal Republic
of Germany in 1988. German Society for Petroleum Sources and Coal Chemistry, Hamburg,
Germany.
Marland, G., and R.M. Rotty. 1984. "Carbon Dioxide Emissions from Fossil Fuels: A Procedure for
Estimation and Results for 1950-1982," Tellus 36(B):232-261.
Martin, N.L.. and R.H. Thring. 1989. Computer Database of Emission Data for Stationary
Reciprocating Natural Gas Engines and Gas Turbines in Use by the Gas Pipeline Transmission
Industry, Users Manual. Prepared for the Gas Research Institute, Chicago, Illinois. February.
McAllister, E.W. (ed). 1988. Pipe Line Rules of Thumb Handbook. Gulf Publishing Company,
Houston, Texas.
PSI (Pipe!:ne Systems Incorporated). 1989. Annual Methane Emission Estimate of the Natural Gas
flttu Petroleum Systems in the United States. Prepared for the Global Change Division of the
U.S. EPA, Washington, D.C.
PSI. 1990. Annual Methane Emission Estimate of the Natural Gas Systems in the United States: Phase
2. Prepared for the Global Change Division of the U.S. EPA, Washington, D.C.
Radian Corporation. 1982. Frequency of Leak Occurrence and Emission Factors for Natural Gas
Liquid Plants. Prepared for the U.S. EPA (EMB Report No. 80-FOL-l). July.
Rockwell International. 1980. Fugitive Hydrocarbon Emissions from Petroleum Production Operations.
Prepared for the American Petroleum Institute. March.
Schneider-Fresenius, W., R.A. Hintz, U. Hoffman-Meienbrock, W. Klopffer, and J. Wittekind. 1989.
Determination of Methane Emission into the Atmosphere due to Losses in the Natural Gas
Supply System of the Federal Republic of Germany. Battelle-Institut E.V., Frankfurt, Germany.
August.
Seeliger, W., and G. Zimmermeyer. 1989. Private correspondence in ICF Resources (1990).
Seiler, W. 1984. "Contribution of Biological Processes to the Global Budget of CH4 in the
Atmosphere," In Current Perspectives in Microbial Ecology. American Society for Microbiology,
Washington, D.C.
Selzer, H. 1990. "Anthropogenic Methane Emissions," In Proceedings from the International
Workshop on Methane Emissions from Natural Gas Systems, Coal Mining, and Waste
Management Systems. April 9-13, 1990. Washington, D.C.
D3-11
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Thorell + VBB Energikonsulter AB. 1989. Releases of Methane from Natural Gas Activity in Sweden.
Prepared for SwedeGas AB, Stockholm, Sweden. August.
U.S. EPA (U.S. Environmental Protection Agency). 1985. Compilation of Air Pollutant Emission
Factors. Office of Air Quality, Planning and Standards (AP-42). September.
U.S. EPA. 1979. Emissions Assessment of Conventional Stationary Combustion Systems. Industrial
Environmental Research Laboratory (EPA-600/7-79-029b). May.
D3-12
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DISCUSSION 4
METHANE EMISSIONS FROM COALMINING
OVERVIEW1
Methane emissions from coal mines are heavily dependent on the geological characteristics
and history of the coalbed. Factors such as coal rank, depth, and permeability affect the amount and
distribution of methane in the coalbed and surrounding strata, which in turn determine the quantity
and rate of methane release during mining. In addition, the type and rate of mining, as well as the
geometry of the mine, have important implications for methane release. Because methane is a safety
hazard in underground mines, substantial research has been undertaken to. determine ways of
predicting and controlling its emissions into mine working areas.
/
How Coalbed Methane Is Produced, Stored and Released
Coal is formed over millions of years as
organic matter is transformed by complex
processes known as "coalification." Coalification
is controlled by chemical and physical processes,
temperature, pressure and geologic history.
Differing levels of coalification produce
different "rank" coals, as shown in Figure D4-
l.2 Coalification results in both physical and
chemical changes, including methane
generation. Other byproducts of the
coalification process are water and carbon
dioxide.
The amount of methane produced
increases throughout the coalification process.
Thus, higher ranked coals tend to contain more
methane than lower ranked coals. Methane is
stored in the coal itself and can also be
contained in the surrounding strata. In
addition, some of the methane generated by
coalification generally escapes to the
atmosphere as a result of natural processes.
Figure D4-1
Stages in Coalification
d.
O
o
in
<
LJJ
cr
o
t
• Graphite
t
' Anthrac i te
Bi tumi nous
t
Sub- B i tumi nous
t
• L i gn i te
t'
• Peat
1 This overview section is taken from the Coal Mining Chapter of the EPA Report to Congress
entitled Anthropogenic Methane Emissions in the United States: Estimates for 1990.
2 The term "rank" is used to designate differences in coal that are due to the progressive change from
lignite to anthracite. Higher rank coals contain more fixed carbon, less volatile matter, and less moisture.
D4-1
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How Methane Is Stored in Coal
Large amounts of methane ean be stored within the microstructure of coal. Methane storage
in coalbeds, mainly by adsorption onto internal coal surfaces, is a function of rank, and present day
pressure and depth of burial.3 In general, coals of increasing rank have higher storage capacities.
In addition, storage capacity increases almost linearly with increasing pressure or depth. Therefore,
at a given rank, deeper coals store more gas than shallower ones.
Even high rank coals cannot store all of the methane generated during coalification, however.
The highest gas contents measured for anthracite coal in the United States, for example, are only 10
to 12 percent of the total amount of methane that was generated during coalification. The rest of
the methane migrated out of the coal over time. Some of this gas remains stored in the surrounding
strata, and some has likely been emitted to the atmosphere as a result of natural processes.
Factors Determining Methane Emissions
During mining, methane is liberated by
the mined coal seam as well as
surrounding coal seams and/or gas
bearing strata. The amount of methane
liberated can be many times higher than
the amount of methane contained in the
mined coal seam.
Methane is released when pressure
within a coalbed is reduced, either through
mining or through natural erosion or faulting.
Methane will migrate through coal from zones
of higher concentration to zones of lower
concentration until it intersects a pathway, such
as a cleat, joint system ^or fracture. The size,
spacing, and continuity of such pathways
determines the permeability of the coal and
largely controls the flow of methane through
the coal and to the surface or the mine
workings.
As pressure is reduced during mining, methane is liberated from the seam being mined and
from the strata above and below the mined seam. In addition to the rank and depth of the coal, the
amount of disturbance to the surrounding strata as a result of mining activities will also have
important implications for emissions. The amount of methane liberated by mining activities can
exceed the amount of gas contained in the mined coal by as much as 3 to 9 times (Kissell et al. 1973).
U.S. Mining Techniques
Coal is produced in the United States in surface and underground mines, and the choice
between these mining types depends primarily on the thickness of the coalbed and its depth from the
surface. Coalbeds shallower than about 200 feet are generally mined from the surface, while deeper
coalbeds are usually mined by underground methods. Given enough coal thickness, surface mining
methods can be applied to a depth of several hundred meters. Each mining method has different
implications for release of methane to the atmosphere.
The major U.S. coal basins are shown in Figure D4-2. In general, coal in the Western basins
is mined using surface methods, while most Eastern basin coals are mined using underground
3 Adsorption is the adhesion in an extremely thin layer of molecules to the surfaces of solid bodies
with which they are in contact.
D4-2
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Figure D4-2: JLI.S. Coal Basins and Coalbed Methane Resources
Waehlnoto
Northern Aooalachian
61 Tc.1
Q-« a t »r CJre«
31 Tcf
Pieeanc«
84 Tc-f
San Uuan
methods.
Underground Mining
Underground mining accounted for about 40 percent of total U.S. coal production in I990.
Most underground mining occurs in the Eastern United States, primarily in the Northern and Central
Appalachian Basins (including Pennsylvania, Virginia, West Virginia, Ohio, Kentucky) and the Black
Warrior Basin of Alabama.
Most U.S. underground mines are less than 984 feet deep, but several reach depths of 1,968
to 2,296 feet. Methane can be emitted during mine construction, coal production, and from
abandoned mine workings. The bulk of the emissions tend to be associated with coal production,
however, and in particular with the caving of the roof and floor rocks, which creates pathways for the
gas to move into the mine workings from uhmined areas of the target coal seam and other strata.
Longwall mining tends to liberate more
methane than room-and-pillar mining.
Thirty-six of the 50 gassiest underground
mines in the U.S. use longwall mining
methods.
Two underground mining methods are
commonly used in the United States: room-
and-pillar mining and longwall mining. The
choice between these methods depends on
geologic factors, such as depth and terrain, and
economic factors, such as equipment cost.
Longwall mines are typically bigger and deeper
than room-and-pillar mines. They are also more
expensive to equip and operate, but generally
have higher coal production rates. The higher production, coupled with the more extensive caving
typically associated with longwall mines, tends to result in higher methane emissions.
Room-and-pillar mining is the most common underground mining technique in the United
States, although the number of longwall mines is growing. Mechanized longwall mining was
introduced in the U.S. during the 1960's, and today there are almost 100 longwall mines in operation.
D4-3
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Sixty out of the 100 gassiest U.S. .underground mines use longwall mining methods.
Surface Mining
Surface mining, also called strip mining, is used to mine coal at shallow depths. In essence.
it involves large scale earth-moving; first the overburden oh top of the coal is excavated, and then
the coal can be removed. Coal recovery rates at surface mines can exceed 90 percent.
Methane emissions from surface mines
are highly uncertain. Available
information indicates that emissions per
ton of coal mined are likely to be low
because these coals are generally low
ranked and buried close to the surface.
In 1990, 603 million tons of coal was
produced at surface mines, mostly in sub-
bituminous and lignite mines in the Western
United States. This represented about 60
percent of total U.S. coal production. The
largest and fastest growing U.S. surface mining
region is the Powder River Basin of Wyoming
and Montana. Surface mines are also located in
the lignite fields of North and South Dakota
and Montana, and the Eastern bituminous coal
basin in Illinois, Indiana, and Western Kentucky.
Methane emissions at surface mines are not required to be monitored because this methane
is emitted directly into the atmosphere and does not pose a safety hazard to miners. Thus, few
emission measurements are currently available. The U.S. Environmental Protection Agency's Office
of Research and Development (EPA/ORD) has recently undertaken a field measurement study of
methane emissions from surface mines.
Based on available information, it appears that methane emissions from surface mines are low
as compared to underground mines because the coals are typically lower ranked and are buried at
shallower depths. Given the magnitude of coal production from surface mining, however, this
emission source is not insignificant.
Methane Management Systems for Underground Mining
Many gassy U.S. underground mines use
degasification systems in addition to
ventilation to ensure safe mining
conditions. These systems produce high
quality methane that can be sold to
pipelines or used to generate electricity.
Methane is a serious safety threat in
underground coal mines because it is highly
explosive in atmospheric concentrations of 5 to
15 percent. The U.S. Mine Safety and Health
Administration (MSHA), an agency of the U.S.
Department of Labor, requires close monitoring
of methane levels and careful design of mine
ventilation systems to ensure that methane
concentrations are kept below explosive levels
in underground mines. In mine entries used by
personnel, methane levels cannot exceed 1 percent, and in certain designated areas of the mine not
frequented by mine personnel, methane levels cannot exceed 2 percent. If these concentrations are
exceeded, MSHA requires that coal production cease until the ventilation system is able to reduce
methane concentrations to acceptable levels.
A variety of methane control methods are employed in many U.S. mines because of the
hazard and because the costs of elevated methane concentrations can be high if coal production must
D4-4
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be suspended. Historically, ventilation has been the main technique used for controlling methane
concentrations in coal mines. In many mines, however, methane emissions into the mine workings
cannot be economically maintained at safe levels using ventilation alone and other degasification
systems are used. These systems can recover methane before, during or after mining and keep it
from migrating into the mine working areas.
Mine degasification systems are currently used primarily to improve safety and reduce
ventilation costs. However, these systems can recover methane with a'high enough energy content
to warrant sale to pipelines or use for electricity generation. In addition to the potential economic
benefits associated with the sale of this gas, such projects have the added advantage of reducing
atmospheric methane emissions, a potent greenhouse gas. Methane management methods are
summarized in Table D4-1.
Table D4-1
Mine Degasification Approaches
Method
Description
Ventilation
Universal method to dilute and exhaust methane to the atmosphere.
Sufficient, in many mines, to maintain safe mining conditions.
In gassy mines, may be necessary to supplement with other methane
degasification systems.
Vertical Wells in
Advance of Mining
Pre-drains methane via surface wells before mining operations begin.
Can recover large amounts of pipeline quality methane.
Technology also used to produce gas from coal seams that are not
being mined.
Can produce methane from multiple coal seams.
Gob Wells
Used in longwall mining to drain methane from portions of overlying
strata allowed to collapse after mining ("gob areas") via surface wells.
Can recover large amounts of methane, sometimes contaminated with
mine air.
Horizontal
Boreholes
Drilled from inside the mine to degasify the coal seam being mined
either years in advance of or shortly before mining.
Methane is removed through an in-mine piping system.
Can recover pipeline quality gas.
Cross-Measure
Boreholes
Drilled from inside the mine to degasify the overlying or underlying
coal and rock strata.
Methane is removed through an in-mine piping system.
Gas can become contaminated with mine air during production.
Used infrequently in the U.S.
Source: For more information, refer to Baker et al. 1988; Baker et al. 1986; Duel et al. 1988;
Dixon 1987; U.S. EPA 1990a; and U.S. EPA 1990b;
D4-5
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Certain methane recovery techniques, particularly vertical drainage in advance of mining, have
als been used extensively to recover coalbed methane in non-mining areas. These projects, which
were encouraged in part by the Section 29 of the Internal Revenue Code Unconventional Gas tax
credit, recovered almost 350 Bcf (9.9 Bern) of coalbed methane in 1990, primarily in the Black
Warrior Basin of Alabama,and the San Juan Basin of Colorado and New Mexico. Because these
projects are not associated with mining, they did not affect methane emissions from this source.
Methane emissions from stand-alone coalbed methane production, processing and transmissions are
included in the discussion of natural gas systems.
Post-Mining Emissions
Not all of the methane contained in coal is released during mining. Some methane remains
in the coal after it is removed from the mine and can be emitted over the following days as the coal
is transported, processed and stored. Depending on the characteristics of the coal and the way it is
handled after leaving, the mine, the amount of methane released during post-mining activities can be
significant and can continue for days or even months. The greatest releases occur when coal is
crushed, sized, and dried in preparation for industrial or utility uses (U.S. EPA, 1990).
DESCRIPTION OF WORKBOOK METHOD
The basic approach recommended in the workbook section of this report for estimating state
methane emissions from coal mining is to multiply a methane emissions factor by the quantity of coal
produced from underground and surface mines in the state. These emissions factors vary depending
upon the coal basin(s) where the state is located. The emissions factors used in the workbook were
developed based on the emissions estimates shown in the coal mining chapter of the EPA Report to
Congress Anthropogenic Methane Emissions in the U.S. (U.S. EPA 1993).4 This section provides a
brief description of the methodology that was used in the EPA Report to Congress to estimate coal
mine methane emissions from underground mines, surface mines, and post-mining activities.
Underground Mines
The emissions coefficients for underground mines were developed by using selected emissions
data from 1990. Methane emissions from underground mining include: (1) measured methane
emissions from ventilation systems at the gassiest underground mines; (2) estimated emissions from
ventilation systems from mines for which measurements >were not reported; and, (3) estimated
emissions from degasification systems.
Ventilation Emissions
• Measured Ventilation Emissions. Methane emissions from ventilation systems are
reported for about 200 of the gassiest U.S. underground coal mines. A database
compiled from 1990 Mine Safety and Health Administration (MSHA) inspection data
by the U.S. Bureau of Mines (U.S.BOM) shows the daily methane emissions from
4 The emissions estimates shown in the EPA Report are based on 1988 methane emissions data - the
latest year for which data was available at the time the report was published. Recently, the emissions
estimates developed for that report were updated, using 1990 data. The emissions factors used in this
workbook are 'based on the 1990 data.
D4-6
-------
mines with emissions exceeding 100,000 cubic feet per day. The reported methane
emissions for these approximately 200 gassy mines was used to determine the quantity
of methane emitted from ventilation systems.
• Estimated Ventilation Emissions. Methane emissions from ventilation systems were
estimated for the underground mines not included in the U.S. BOM database. These
other mines were classified into three categories: (1) Active mines with detectable
methane emissions; (2) Active mines with non-detectable methane emissions; and (3)
Inactive or abandoned mines. Estimation methodologies were developed based on
information provided by U.S. BOM and MSHA about the mines' characteristics and
regulatory treatment. The estimated ventilation emissions for these mines were
estimated to represent less than 2 percent of the measured ventilation emissions in
1990. This factor was applied to the actual ventilation emissions for each coal basin.
Degasification System Emissions
Specific information on methane emissions from the degasification systems in place at U.S.
coal mines is not currently available because coal mine owner/operators are not required to report
emissions from these systems. In fact, without close examination of the mine ventilation plans
provided to MSHA for each mine, it is difficult to confirm which mines have degasification systems
in place.
Degasification system emissions were estimated for mines known or believed to have such
systems in place/ Low and high estimates were developed based on information about likely coal
mine degasification strategies and on conditions in various coal basins. The percentage of methane
liberations assumed to be recovered by degasification systems at mines in different basins is:
Northern Appalachian and Illinois (30 to 65 percent) and Central Appalachian, Black Warrior, and
Western (40 to 65 percent). Known recovery factors were applied to those mines that reported the
methane recovery from their degasification systems (i.e., those mines that sold the gas to pipelines).
The recovery factors were applied to the measured ventilation emissions of the roughly 30 mines with
degasification systems in place in 1990 to estimate total emissions.
Once ventilation and degasification emissions were calculated for individual mines, total
emissions from underground mines could be calculated for each basin. These emissions were then
divided by total coal production in 1990 for each basin to determine the estimated emissions factor
per ton of coal mined. The emissions factors are:
Basin
Northern Appalachian
Central Appalachian
Black Warrior
Illinois
Rockies & Southwest
Emissions Factor
fcf/ton of coal mined)
423 to 739
217 to 327
2504
160 to 192
369 to 467
5 This list was developed based on discussions with U.S. BOM and MSHA officials, industry
representatives and literature review.
D4-7
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These emissions factors are recommended in the methodology shown in Workbook Section 4.
Surface Mines
Measurements of methane emissions from surface mines are currently unavailable, although
a field measurement study is underway to better quantify emissions from this source.6 In the
absence of measurements, emissions were estimated using reported methane contents for the surface
coals mined in each coal basin. For each coal basin, the estimated methane content of the coal was
multiplied by an emission factor and by the basin's surface coal production. In the low case, an
emission factor of 1 was used; that is, it was assumed that only the methane actually contained in the
mined coal seams would be emitted. In the high case, however, it was assumed that actual emissions
would be 3 times greater than the methane content of the target coal seam due to the release of
methane from the surrounding strata.7 Using this approach, a low and high emissions factors per
ton of coal mined was calculated for each basin. These emissions factors are shown in Workbook
Section 4. • , ,
Post-Mining Emissions
The methane emitted during the post-mining transportation and handling of coal has not been
systematically measured or evaluated. Previous analyses have estimated that 25 to 40 percent of the
in-situ methane content of extracted coal would be released to the atmosphere after the coal leaves
the mine. British Coal, for example, estimates that post-mining emissions are 40 percent of the in-situ
content because their coals have low permeability and the gas desorbs slowly. Similarly,
Environment Canada estimates that only 54 percent of the methane contained in their surface mined
coals is released during mining.9
In the absence of actual measurements for U.S. coals, post-mining emissions were estimated
to range from 25 to 40 percent of in-situ content. The low case estimate of 25 percent represents
a conservative assumption, while the high case is more consistent with experience in other countries.
For each coal basin, these emissions factors were applied to the methane contents reported for
surface and underground coals to develop post-mining emissions factors. These emissions factors are
presented in Workbook Section 4.
A more detailed description of the approaches used to estimate methane emissions from
surface mines, underground mines, and post-mining activities is contained in the EPA Report to
Congress (EPA, 1993).
6 This study is being done by EPA/ORD. . . ,
' This assumption is consistent with the methodology developed by Environment Canada in their
report on greenhouse gas emissions. (Environment Canada, 1992.) Preliminary results of the U.S. EPA
study indicate that the factor could be as high as five (Kirchgessner et al 1992).
8 Quantification of Methane Emissions from British Coal Mine Sources, report produced for the Working
Group on Methane Emissions, the Watt Committee on Energy (1991).
9 Canada's Greenhouse Gas Emissions Estimates for 1990. Draft April, 1992.
D4-8
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ALTERNATE METHODOLOGY
The approach recommended in Workbook Section 4 for calculating methane emissions from
underground mines consists of multiplying.state coal production from underground mines by the
appropriate emissions factor. As described above, the emissions factors shown in the workbook were
developed by summing the measured methane emissions from ventilation systems reported for
individual mines 'and by estimating the quantity of methane emitted from degasification systems.
While the mine-level emissions data were used to estimate total emissions from the major coal basins,
this same approach could be used to estimate state-level emissions. Use of mine-level emissions data
is the focus of the alternative method described here. This approach is the most precise method for
estimating underground emissions since it relies on reported emissions from individual mines.
This alternative, mine-by-mine approach for underground mines is possible because methane
emissions from ventilation systems at the 200 gassiest underground mines are measured by MSHA
and reported in a database developed by the U.S. BOM. However, MSHA is not required to monitor
emissions from degasification systems and these emissions must still be estimated. Furthermore, states
would still need to estimate emissions from ventilation systems at those less gassy mines not included
in the U.S. BOM database (instructions for making these estimates are included here). Finally,
emissions from surface mines and post-mining emissions would still need to be estimated using basin-
specific emissions factors for each ton of coal mined, as shown in the workbook section.
For purposes of facilitating state efforts to estimate methane emissions from underground coal
mines, the U.S. BOM database of methane emissions from gassy mines is included in Appendix A at
the end of this Chapter. Additionally, estimates of emissions from degasification systems for mines
that employ these systems are shown. The information in the database has been sorted by state to
create individual state databases. Databases were created for the following states: Alabama,
Colorado, Illinois, Indiana, Kentucky, Maryland, New Mexico, Ohio, Pennsylvania, Tennessee, Utah,
Virginia, and West Virginia. The information for each state is shown in Tables 1 through 13 in
Appendix A. A few states - Maryland, New Mexico, and Tennessee - have less than five gassy
underground mines in the database.
The steps for calculating emissions using the state emissions databases shown in the Appendix
are as follows:
Step 1: Locate the table in Appendix A containing the emissions data for your state. After
you have located this table, review the instructions for interpreting the state
databases, which appear at the beginning of Appendix A.
As described in the Instructions for Interpreting the State Databases, the total
amount of methane emitted from gassy mines in the state in 1990 is shown in Column
11. Record this amount in Row 1 of Table D4-2 (Table D4-2 appears after the
following page).
Step 2: Next, determine total state coal production from all active underground mines in
1990. Report this amount in Row 2 of Table D4-2. Total state coal production from
underground mines should be available from in-state sources. Alternatively, the
report Coal Production 1990 (DOE/EIA, 1991) provides coal production from
underground and surface mines for all states.
D4-9
-------
Step 3: After recording total state coal production from underground mines in 1990. record
the total amount of coal produced horn gassy mines listed in the U.S. BOM database.
The total amount of coal produced is shown in the last row of Column 4 in the state
database. Report this amount in Row 3 of Table D4-2.
Step 4: Subtract total state coal production from underground mines (Row 2 of Table D4-2)
from total coal production from gassy mines (Row 3 of Table D4-2) to determine the
quantity of coal produced from non-gassy underground mines. Record this amount
in Row 4 of Table D4-2.
Step 5: Multiply the total coal production from non-gassy mines in 1990 by an estimated
average emissions factor of 50 cf/ton to estimate total methane emissions from non-
gassy underground mines. ' "
Step 6: Record this amount in Row 6 of Table D4-2.
Step 7: To determine total state methane emissions from underground mines in 1990, sum the
emissions from gassy mines and the emissions from non-gassy mines. Record this
amount in Row 7 of Table D4-2.
D4-10
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Table D4-2: Calculations for 1990 Methane Emissions from Underground Mines
Using Alternate Methodology
Item to be Reported
(1) Methane Emitted from Gassy Mines in 1990
(Shown in Column 11 of the state database)
(2) Total State Coal Production from All
Underground Mines in 1990
(3) State Coal Production from Gassy Mines in 1990
(shown in Column 4 of the state database)
(4) State Coal Production from Non-gassy Mines in
1990 (Row 2 minus Row 3)
(5) Methane Emissions Factor for Coal Produced
from Non-gassy Mines
(6) Methane Emitted from Non-Gassy Mines in 1990
(Row 4 x Row 5)
(7) Total State Emissions from All Underground
Mines in 1990 (Row 1 + Row 6)
Units
(million cubic
feet/year)
(million
tons/year)
(million
tons/year)
(million
tons/year)
(cf/ton)
(million cubic
feet/year)
(million cubic
feet/year)
Value
50 cf/ton
D4-L1
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REFERENCES
Baker et al. 1988. Cost Comparison of Gob Hole and Cross-Measure Borehole Systems to Control
Methane in Gobs. U.S. Bureau of Mines. RI 9151.
Baker et al. 1986. Economic Evaluation of Horizontal Borehole Drilling for Methane Drainage from
Coalbeds. U.S. Bureau of Mines, 1C 9080.
Dixon. 1987. "A Miner's Viewpoint," Proceedings of the 1987 Coalbed. Methane Symposium, pp.7-10.
Tuscaloosa, Alabama.
DOE/EIA. 1991. Coal Production 1990. Energy Information Administration. Office of Coal.
Nuclear, Electric and Alternate Fuels. U.S. Department of Energy. Washington, DC 20585
Duel et al. 1988. "Methane Control Research: Summary of Results, 1964-80," Bureau of Mines
Bulletin. B-687.
Environment Canada. 1992. Canada's Greenhouse Gas Emissions Estimates for 1990. Draft April.
1992.
Kirchgessner, D.A., S.D. Piccot, and A. Chadha. 1992a. Estimation of Methane Emissions from a
Surface Coal Mine Using Open-Path FUR Spectroscopy and Modeling Techniques.
Chemosphere. (In Press).
Kissell, F.N., C.M. McCulloch, and C.H. Elder. 1973. The Direct Method for Determining Methane
Content of Coalbeds for Ventilation Design. U.S. Bureau of Mines Information Circular 7767.
U.S. Department of the Interior, Washington, D.C. 17 pp.
U.S. EPA (U.S. Environmental Protection Agency). 1994. Identifying Opportunities for Methane
Recovery at U.S. Coal Mines: Draft Profiles of Selected Gassy Underground Mines.
EPA/430/R-94/012. September 1994.
U.S. EPA. 1993. Anthropogenic Methane Emissions in the United States: Estimates for 1990. Report
to Congress. Office of Air and Radiation (6202J). EPA 430-R-93-003. April 1993.
U.S. EPA. 1990a. Methane Emissions and Opportunities for Control: Workshop Results of
Intergovernmental Panel on Climate Change. Office of Air and Radiation (ANR-445).
Washington, DC. EPA/400/9-90/007.
U.S. EPA. 1990b. Methane Emissions From Coal Mining: Issues and Opportunities for Reduction.
Prepared by ICF Resources Incorporated for Office of Air and Radiation, USEPA.
Washington, DC.
D4-12
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APPENDIX A
D4-13
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Instructions for Interpreting State Emissions Databases:
Emissions Data for Gassy Underground Mines
The state databases in this Appendix show estimates of 1990 methane emissions for
approximately the top 200 gassy mines in the United States. These top 200 mines are estimated to
account for over 95 percent of all methane emissions from underground mines. Following are
instructions for how to interpret the data presented in the state databases.
Column 1: The first column of the database lists, ;^ alphabetical order, the gassy mines that are
located in each state.
Column 2: Column 2 shows the county in which the mines are located.
Column 3: Column 3 lists the company that owns the gassy mine.
Column 4: This column provides the amount of coal produced at each mine in 1990. Coal
production is reported in million (mm) tons/year.
Column 5: Column 5 shows the estimated quantity of methane that was emitted from the ventilation
system at each mine during 1990. This amount is based on the daily emissions from ventilation
systems reported by the Mine Safety and Health Administration.
Column 6: This column indicates whether a particular mine is known or believed to have a
degasification system in place (as reported in USEPA, 1994). A "1" in the .column indicates that the
mine does employ such a system. Some states do not have any mines that use degasification systems.
Accordingly, for those states, column 6 will be blank.
Column 7: Column 7 shows the estimated percentage of total emissions that are released from
ventilation systems. For those mines that do not use degasification systems, emissions from
ventilation systems constitute 100 percent of the emissions released from the mine. Accordingly, for
those mines, a value of 100 percent appears in column 7. In contrast, for those mine employing
degasification systems, methane is emitted from both the ventilation systems and from the
degasification systems. As a LOW estimate, it is assumed that ventilation emissions account for
between 60 to 70 percent of total emissions, while degasification emissions account for only 30 to 40
percent of emissions. The specific percentages listed for each mine in the database vary depending
upon the coal basin in which the mine is located and are based on the report USEPA (1993).
While the database only provides calculations corresponding to a LOW estimate of the portion of
emissions contributed by degasification systems, states are also encouraged to develop a HIGH
estimate by assuming that degasification system emissions account for 60 percent of total emissions
at the mines employing these systems (and, therefore, that ventilation emissions account for only 40
percent of total emissions). The LOW estimate should correspond to the LOW emissions factor for
underground mining shown in the workbook section, while the HIGH estimate should correspond
to the HIGH emissions factor shown in the workbook section.
Column 8: Column 8 shows the estimated amount of methane released from degasification systems
based on the percentages shown in Column 7 for ventilation emissions. The value in Column 8 is
calculated as follows:
D4-14
-------
[ventilation emissions (Column 5)] / [ventilation emissions as percentage of total emissions
(Column 7)] = Total Emissions.
Total Emissions x (1 - % shown in Column 7) = emissions from degasification systems.
Column 9: Column 9 shows the total amount of methane released from both ventilation systems
(Column 5) and from degasification systems (Column 8).
Column 10: This column shows the amount of methane that was recovered for pipeline sales' (and,
thus, was not emitted to the atmosphere). In 1990, only six mines recovered methane for pipeline
sales -- five in Alabama and one in Utah. Accordingly, Column 10 will be blank for states other than
Utah and Alabama. Currently, in addition to the six mines that recovered methane in 1990, four
states,in Virginia also recover methane for pipeline sales.
Column 11: Column 11 shows the total amount of methane emitted to the atmosphere. The amount
shown in Column 11 is calculated by subtracting the amount of methane recovered (Column 10) from
the total .amount of methane released (Column 9). Column 11 is the amount of methane emitted
from gassy coal mines in the state during 1990.
Column 12: Column 12 shows the operating status of each mine as of September 1994. This
information is based on the EPA Report Identifying Opportunities for Methane Recovery at U.S. Coal
Mines: Draft Profiles of Selected Gassy Underground Coal Mines. While all of the mines shown in
the database were operating in 1990, a number of them have since been, closed or idled.
Furthermore, during the last four years, new gassy mines have also started production. Unfortunately,
emissions data are not available for these new mines.
D4-15
-------
ALABAMA
1
Mine Name
Blue Creek No. 3
Blue Creek No. 4
Blue Creek No. 5
Blue Creek No.7
Chetopa
Mary Lee No.1
Mary Lee No.2
North River No. 1
Oak Grove
YWMXt&'.tti-
2
County
Jefferson
Tuscaloosa
Tuscaloosa
Tuscaloosa
Jefferson
Walker.
Walker
Fayette
Jefferson
3
Company Name
Jim Walter Resources Inc.
Jim Walter Resources Inc.
Jim Walter Resources Inc.
Jim Walter Resources Inc.
Drummond
Drummond
Drummond
Pittsburgh & Midway
U.S. Steel Mining Co. Inc.
4
Coal
Production
(mmtons/yr)
2.63
2.96
1.61
2.98
0.67
1.63
1.20
1.87
1.82
17.36
5
Vent
Emissions
(mmcf/yr)
5,548
4,344
7,081
6,023
438
767
146
730
4,198
29,2M;:
6
Degas
System
In Place?
1
1
1
1
1
7
Vent Emis
% of Total
66%
66%
66%
66%
1 00%
100%
1 00%
100%
65%
/
8
Low Degas
Released
(mmcf/yr)
2,849
2,230
3,636
3,092
0
0
0
0
2,260
.': :.;:::;::i-;i4;j&68
9
Low TOTAL
Released
(mmcf/yr)
8,397
6,574
10,717
9,115
438
767
146
730
6,458
43,341
10
Methane
Utilized
(mmcf/yr)
2,849
2,230
3,636
3,092
0
0
0
0
2,260
14.068
11
Low TOTAL
Emissions
(mmcf/yr)
5,548
4,344
7,081
6,023
438
767
146
730
4,198
- : :mwm
12
Operating
Status
1994
Utilizing
Utilizing
Utilizing
Utilizing
Operating
Operating
Closed
Operating
Utilizing
-------
COLORADO
1
Mine Name
Cameo No.1
Orchard Valley West
Deserado
Dutch Creek M & B
Eagle No. 5
Golden Eagle
McClane Canyon
Mt. Gunnison No. 1
Roadside
Southfield
TOTAL
2
County
Mesa
Delta
Rio Blanco
Pitkin
Moffat
Las Animas
Garfield
Gunnison
Mesa
Freemont
3
Company Name
Powederhorn Coal Co.
Cyprus Coal Co.
Western Fuels-Utah
Mid-Continent Resources
Cyprus Empire Corp
Wyoming Fuel Co.
Salt Creek Mining
West Elk Coal Co.
Powderhorn Coal Co.
Energy Fuels
4
Coal
Production
(mmtons/yr)
0.58
1.46
0.48
2.25
1.28
0.21
0.56
0.19
0.30
7.30
. 5
Vent
Emissions
(mmcf/yr)
37
219
548
2,117
37
2,227
73
73
73
219
5.621
6
Degas
System
In Place?
1
1
1
7
Vent Emis
% of Total
1 00%
1 00%
60%
60%
60%
100%
1 00%
100%
1 00%
100%
8
Low Degas
Released
(mmcf/yr)
0
0
365
1,411
.24
0
0
0
0
0
1,801
9
Low TOTAL
Released
(mmcf/yr)
37
219
913
3,528
61
2,227
73
73
73
219
7,422
10
Methane
Utilized
(mmcf/yr)
0
0
0
0
0
0
0
0
0
0
0
11
Low TOTAL
Emissions
(mmcf/yr)
37
219
913
3,528
61
2,227
73
73
' 73
219
•: .. 7,422
" ' "12
Operating
Status
1994
Unknown
Operating
Operating
Closed
Operating
Operating
Unknown
Operating
Unknown
Operating
-------
ILLINOIS
1
Mine Name
Baldwin Underground
Big Ridge
Brushy Creek
Crown II
Eagle No.2
Elkhart
Galatia No.56-1
Kathleen
Marissa
Monterey No.1
Monterey No.2
Murdock
Old Ben No.21
Old Ben No.24
Old Ben No.25
Old Ben No.26
Orient No.6
Pattiki
Peabody No. 10
Rend. Lake
Sahara No.21
Spartan
Wabash
Zeigler No. 1 1
TOTAL
2
County
Randolph
Saline
Saline
Macoupin
Gallatin
Logan
Saline
Perry
Washington
Macoupin
Clinton
Douglas
Franklin
Franklin
Franklin
Franklin
Jefferson
White
Christian
Jefferson
Saline
Randolph
Wabash
Randolph
3
Company Name
Peabody Coal Co.
Arclar Co.
Kennellis Energies
Freeman United
Peabody Coal
Turris Coal
Kerr McGee Coal
Cutler Mining Co.
Peabody Coal Co.
Monterey Coal
Monterey Coal
Zeigler
Zeigler/Old Ben Coal
Zeigler/Old Ben Coal
Zeigler/Old Ben Coal
Zeigler/Old Ben Coal
Freeman United
White County Coal
Peabody Coal
Consolidation Coal
Sahara Coal
Zeigler Coal Co.
Amax Coal
Zeigler Coal Co.
4
Coal
Production
(mmtons/yr)
1.87
0.78
1.70
1.15
1.60
1.32
3.02
1.05
1.89
1.98
2.96
0.99
0.27
1.48
2.68
2.57
1.50
1.75
2.32
2.77
0.59
1.29
2.01
1.66
41,18
5
Vent
Emissions
(mmcf/yr)
73
37
255
146
"438
110
986
37
73
219
255
219
329
548
694
657
219
767
255
438
110
37
986
73
7.957
6
Degas
System
In Place?
1
1
7
Vent Emis
% of Total
100%
100%
1 00%
1 00%
1 00%
1 00%
100%
1 00%
100%
1 00%
100%
1 00%
100%
100%
70%
70%
1 00%
100%
1 00%
1 00%
100%
100%
100%
1 00%
8
Low Degas
Released
(mmcf/yr)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
297
282
0
0
0
0
0
0
0
0
579
9
Low TOTAL
Released
(mmcf/yr)
73
37
255
146
438
110
986
37
73
219
255
219
329
548
991
939
219
767
255
438
110
37
986
73
8,536
10
Methane
Utilized
(mmcf/yr)
0
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
Low TOTAL
Emissions
(mmcf/yr)
73
37
255
146
438
110
986
37
73
219
255
219
329
548
991
939
219
767
255
438
110
37
986
73
8.536
12
Operating
Status
1994
Unknown
Unknown
Operating
Unknown
Closed
Unknown
Operating
Unknown
Unknown
Operating
Operating
Unknown
Closed
Operating
Closed
Operating
Operating
Operating
Closed
Operating
Unknown
Unknown
Operating
Unknown
-------
INDIANA
1
Mine Name
Buck Creek
TOTAL
2
County
Sullivan
3
Company Name
Laswell Coal
4
Coal
Production
(mmtons/yr)
0.78
: ; 0.73
5
Vent
Emissions
(mmct/yr)
110
110
6
Degas
System
In Place?
7
Vent Emis
% of Total
1 00%
8
Low Degas
Released
(mmcf/yr)
0
Q
9
Low TOTAL
Released
(mmcf/yr)
110
110
10
Methane
Utilized
(mmcf/yr)
0
0
11
Low TOTAL
Emissions
(mmcf/yr)
110
110
O
u
12
Operating
Status
1994
Unknown
-------
KENTUCKY
1
Mine Name
Aero No 1
Lynch No. 37 .
Baker
Camp No. 1
Camp No. 2
Canada Coal No. 2
Creech No 1
Darby
Day Branch No. 4
Dotiki
EAS No. 1
Green River No.9
Hamilton No. 2
Martwick UG
MCNO1
New ERA No 1
Ohio No. 11
Ovenfork/Scotia
Pontiki No.1
Pontiki No.2
Pyro No. 11 Highway
William Station
Wheatcroft
Retiki
Unicorn No. 2
West Hopkins
Whittaker No. 49
Wolf Creek No.4
TOTAL
2
County
Pike
Harlan
Webster (KY)
Union
Union
Pike
Harlan
Harlan
Harlan
Webster (KY)
Perry
Hopkins
Union
Muhlenberg
Pike
Pike
Union
Letcher
Martin
Martin
Union
Union
Webster (KY)
Henderson
Leslie
Hopkins
Leslie
Martin
3
Company Name
Aero Energy Inc.
Arch of Kentucky Inc.
Pyro Mining Corp.
Peabody Coal Co.
Peabody Coal
Canada Coal Co. Inc.
Jericol Mining Inc.
Jericol Mining Inc.
Day Branch Coal Co. Inc.
Webster County Coal
Whitaker Coal Corp.
Green River Coal
Island Creek Coal Co.
Peabody Coal
Me Mining Inc.
New Era Coal Co.
Island Creek Coal Co.
Cumberland River
Pontiki Coal Corp.
Pontiki Coal Corp.
Pyro Mining Co.
Pyro Mining
Pyro Mining
Webster County Coal
Unicorn Mining Inc.
Sextet Mining Corp.
Whitaker Coal Corp.
Wolf Creek Collieries
4
Coal
Production
(mmtons/yr)
0.76
2.69
1.22
2.30
0.59
0.06
0.49
0.30
0.18
2.41
1.11
1.30
1.18
1.59.
1.19
1.19
0.94
0.74
0.05
1.14
0.75
1.81
- 0.35
2.88
27.22
5
Vent
Emissions
(mmcf/yr)
110
183
255
37
146
37
73
37
37
110
37
438
73
. 110
110
110
37
438
255
183
73
438
219
37
37
146
37
438
4,234
6
Degas
System
In Place?
1
7
Veni Emis
% of Total
1 00%
100%
1 00%
100%
1 00%
100%
1 00%
1 00%
100%
1 00%
100%
1 00%
100%
1 00%
100%
100%
100%
1 00%
100%
1 00%
100%
100%
70%
100%
100%
1 00%
100%
100%
8
Low Degas
Released
(mmcf/yr)
0
0
0
' 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
• , o
94
0
0
0
0
0
.i*'. *"•;&•
9
Low TOTAL
Released
(mmcf/yr)
110
183
255
37
146
37
73
37
37
110
37
438
73
110
110
110
37
438
255
183
73
438
313
37
37
146
37
438
•'n 4,328
10
Methane
Utilized
(mmcf/yr)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
. './:. Q
11
Low TOTAL
Emissions
(mmcf/yr)
110
183
255
37
146
37
.73
37
. 37
110
37
438
73
110
110
110
37
438
255
183
73
438
313
37
37
146
37
438
V: : 4,328:
. ' "12
Operating
Status
1994
Unknown
Operating
Operating
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Closed
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Operating
Unknown
Unknown
Unknown
Operating
Unknown
Unknown
Unknown
Unknown
Operating
-------
MARYLAND
1
Mine Name
Mettiki
TOTAL
2
County
Garrett
3
Company Name
Mettiki Coal Corp. (Mapco)
4
Coal
Production
(mmtons/yr)
1.98
./••:;;,;::;;:;;-:.;;.-i;.98
5
Vent
Emissions
(mmcf/yr)
219
21.9
6
Degas
System
In Place?
7
Vent Emis
% of Total
100%
8
Low Degas
Released
(mmcf/yr)
0
0
9
Low TOTAL
Released
(mmcf/yr)
219
219
10
Methane
Utilized
(mmcf/yr)
0
0
11
Low TOTAL
Emissions
(mmcf/yr)
219
219
12
Operating
Status
1994
Operating
-------
NEW MEXICO
1
Mine Name
Cimarron
TOTAL
2
County
Colfax
3
Company Name
Pittsburgh & Midway Coal Mining
4
Coal
Production
(mmtons/yr)
0.08
0.08
5
Vent
Emissions
(mmcf/yr)
37
•••' M
6
Degas
System
In Place?
7
Vent Emis
% of Total
100%
8
Low Degas
Released
(mmcf/yr)
0
•&o
9
Low TOTAL
Released
(mmcf/yr)
37
37
10
Methane
Utilized
(mmcf/yr)
0
0
11
Low TOTAL
Emissions
(mmcf/yr)
37
37
12
Operating
Status
1994
Unknown
-------
OHIO
1
Mine Name
Meigs No. 2
Meigs No. 31
Powhatan No.4
Powhaton No.6
Saginaw
Sunnyhill No. 9 South
TQTAt'-";:"vV:'; -': '•
2
County
Meigs
Meigs
Monroe
Belmont
Belmont
Perry
3
Company Name
Southern Ohio Coal
Southern Ohio Coal
Quarto Mining
Ohio Valley Coal
Saginaw Mining Co.
Peabody Coal Co.
4
Coal
Production
(mmtons/yr)
3.26
2.15
2.54
2.86
0.47
1.00
•:.-:-:K-:m®
5
Vent
Emissions
(mmct/yr)
329
329
511
146
37
37
1.387::
6
Degas
System
In Place?
7
Vent Emis
% of Total
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
8
Low Degas
Released
(mmcf/yr)
0
0
0
0
0
0
: :: •--•P.;
9
Low TOTAL
Released
(mmcf/yr)
329
329
511
146
37
37
1,387
'0
Meihane
Utilized
(mmcf/yr)
0
0
0
0
0
0
Q
11
Low TOTAL
Emissions
(mmcf/yr)
329
329
511
146
37
37
1.387;
12
Operating
Status
1994
Operating
Operating
Operating
Unknown
Unknown
Unknown'
-------
PENNSYLVANIA
1
Mine Name
Allegheny No. 2
Bailey •
•Cambria No. 33
Clyde
Cumberland
DiAnne
Dilworth
Emerald No. 1
Enlow Fork
Florence No.2
Gateway
Greenwich No.2
Grove No. 1
Homer City
Jane
Mine 84
Lucerne No. 8
Lucerne No.6
Lucerne No.9
Maple Creek
Marion
Mathies
Meadow Run
Newfield
Rushton
Shannopin
Tanoma
Urling No.1
Urling No.3
Warwick Portal
TOfA$.-:;^><
2
County
Allegheny
Greene
Cambria
Washington
Greene
Armstrong
Greene
Greene
Greene
Indiana
Greene
Indiana
Somerset
Indiana
Armstrong
Washington
Indiana
Indiana
Indiana
Washington
Indiana
Washington
Greene
Allegheny
Centre
Greene
Indiana
Indiana
Indiana
Greene
3
Company Name
Penn Allegh Coal Co. Inc.
Consol Pennsylvania Coal Co.
Beth Energy Mines Inc.
BCNR Mining Corp.
U.S. Steel Mining Co. Inc.
Canterbury Coal Co.
Consolidation Coal
Cyprus Emerald Resources Cor
Enlow Fork Mining
Florence Mining
Gateway Coal
Rochester & Pittsburgh Coal Co
Lion Mining
Helen Mining
Keystone Coal Mining
Beth Energy Mines Inc.
Helvetia Coal Co.
Helvetia Coal
Helvetia Coal
U.S. Steel Mining Co.
Tunnelton Mining
Mathies Coal
Genesis Inc.
Penn Hills Energy Co./Kitt Ener
Rushton Mining Co.
Shannopin Mining
Tanoma Mining Co. Inc.
Keystone Coal Mining
Keystone Coal Mining
Duquesne Light
4
Coal
Production
(mmtons/yr)
0.64
5.58
1.97
3.17
0.67
2.40
1.64
0.29
0.69
0.33
1.53
0.61
0.98
0.88
1.33
0.67
0.18
0.73
2.08
0.89
1.25
0.21
0.07
0.72
0.97
0.41
0.97
0.32
0.06
;:- , 3^23
5
Vent
Emissions
(mmcf/yr)
37
1,752
1,241
37
2,117
37
548
1,132
73
110
292
548
219
475
146
1,132
37
110
146
402
183
402
37
73
146
146
146
402
37
146
12,3012
6
Degas
System
In Place?
1
1
1
-
1
7
Vent Emis
% of Total
1 00%
70%
70%
1 00%
70%
1 00%
1 00%
70%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
100%
1 00%
1 00%
100%
1 00%
1 00%
8
Low Degas
Released
(mmcf/yr)
0
751
532
0
907
0
0
485
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2,675
9
Low TOTAL
Released
(mmcf/yr)
37
2,503
1,773
37
3,024
37
548
1,616
73
110
292
548
219
475
146
1,132
37
110
146
402
183
402
37
73
146
146
146
402
37
146
14,975
10
Methane
Utilized
(mmcf/yr)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Q
11
Low TOTAL
Emissions
(mmcf/yr)
37
2,503
1,773
37
3,024
37
548
1,616
73
110
292
548
219
475
146
1,132
37
110
146
402
183
402
37
73
146
146
146
402
37
146
14,975
12
Operating
Status
1994
Unknown
'Operating
Closed
Unknown
Operating
Unknown
Operating
Operating
New
Unknown
Unknown
Unknown
Operating
Closed
Unknown
Operating
Unknown
Unknown
Unknown
Closed
Operating
Operating
Unknown
Unknown
Unknown
Unknown
Unknown
Operating
Unknown
Unknown
-
-------
TENNESSEE
1
Mine Name
Kelly's Creek No. 63
Matthews
TOTAL
2
County
Sequatchie
Claiborne
3
Company Name
Kelly's Creek Resources
Consolidation Coal
4
Coal
Production
(mmtons/yr)
0.85
;:.::-*;':''0,85'-
5"
Vent
Emissions
(mmcf/yr)
37
73
HP
6
Degas
System
In Place?
7
Vent Emis
% of Total
1 00%
1 00%
8
Low Degas
Released
(mmcf/yr)
0
0
0
9
Low TOTAL
Released
(mmcf/yr)
37
73
11Q
10
Methane
Utilized
(mmcf/yr)
0
0
0
11
Low TOTAL
Emissions
(mmcf/yr)
37
73
110
. 12
Operating
Status
1994'
Unknown
Unknown
-------
UTAH
1
Mine Name
Castle Gate
Deer Creek
Emery
Pinnacle
Soldier Canyon
Sunnyside No.1
Sunnyside No.3
Trail Mountain No. 7
TpTAi >:;;-: va-M" :
2
County
Carbon
Emery
Emery
Carbon
Carbon
Carbon
Carbon
Emery
3
Company Name
Castle Gate Coal
Utah Power & Light Co.
Consolidation Coal
Andalex Resources Inc.
Soldier Creek Coal
Sunnyside Coal
Sunnyside Coal
Beaver Creek Coal Co.
4.
Coal
Production
(mmtons/yr))
3.36
0.34
0.84
1.21
0.68
0.50
6,92
5
Vent
Emissions
(mmcf/yr)
146
37
110
146
1,643
621
73
37
2,811
6
Degas
System
In Place?
1
-
7
Vent Emis
% of Total
1 00%
1 00%
1 00%
1 00%
50%
1 00%
1 00%
1 00%
8
Low Degas
Released
(mmcf/yr)
0
0
0
0
1,643
0
0
0
1-§43
9
Low TOTAL
Released
(mmcf/yr)
146
37
110
146
3,285
621
73
37
••".:••-. vi;453:;
10
Methane
Utilized
(mmcf/yr)
0
0
0
0
1,643
0
0
0
V 1,643
11
Low TOTAL
Emissions
(mmcf/yr)
146
37
110
146
1,643
621
73
37
^';2,8*$-
12
Operating
Status
1994
Unknown
Unknown
Unknown
Utilizing
Closed
Unknown
Unknown
-------
VIRGINIA
1
Mine Name
Bear Ridge No 1
B.C Seaboard No.1
B.C Seaboard No.2
Bodie Mining No. 1
Buchanan No. 1
Bullitt
Dominion No. 7
Double R No. 1
Falcon No. 1
G&A coal No. 1
Holton
Jamb Mining No. 1
McClureNo. 2
McClure No.1
MullinsNo. 1
Prescott No. 2
Raven No. 1
Splashdam
VP No. 1
VPNo.3
VP No.5
VP No. 6
Wentz No. 1
Winston No. 10
Youngs Branch 15
TOTAL
2
County
Tazewell
Tazewell
Tazewell
Wise
Buchanan
Wise
Buchanan
Dickenson
Buchanan
Dickenson
Lee
Dickenson
Dickenson
Dickenson
Wibe
Wise
Buchanan
Dickenson
Buchanan
Buchanan
Buchanon
Buchanan
Wise
Buchanan
Buchanan
3
Company Name
Bear Ridge Mining Inc.
Sea B Mining Co.
Sea B Mining Co.
Bodie Mining Co. Inc.
Consolidation Coal
Westmoreland Coal
Dominion Coal Corp.
Double R Coal Co. Inc.
Falcon Coal Corp.
G&A Coal Inc.
Westmoreland Coal
Jamb Mining Inc.
Clinchfield Coal Co.
Clinchfield Coal
Mullins No. 3 Inc.
Westmoreland Coal Co.
Koch Raven
Clinchfield Coal
Island Creek Coal Co.
Island Creek Coal Co.
VPS Mining Co.
Garden Creek Poca Co
Westmoreland Coal Co.
Dominion Coal Corp.
Dominion Coal Corp. .
4
Coal
Production
(mmtons/year)
0.24
0.36
0.19
0.19
2.60
1.07
0.34
0.12
0.24
0.61
0.15
0.13
0.99
0.11
0.30
.0.54
1.93
1.75
1.67
1.78
0.30
0.23
0.40
16.24
5
Vent
Emissions
(mmcf/yr)
292
219
255
37
3,468
292
37
37
73
37
110
37
37
1,387
37
37
73
73
3,540
3,358
3,285
3,358
37
37
37
20,185
6 -
Degas
System
In Place?
1
1
1
1
1
7
Vent Emis
% of Total
1 00%
1 00%
' 1 00%
1 00%
60%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
1 00%
100%
60%
60%
60%
60%
1 00%
1 00%
100%
8
Low Degas
Released
(mmcf/yr)
0
0
• 0
0
2,312
0
0
0
0
0
0
0
0
0
0
.0
0
0
2,360
2,239
2,190
2,239
0
0
0
• y^-^lijatS::
9
Low TOTAL
Released
(mmcf/yr)
292
219
255
37
5,779
292
37
37
73
37
110
37
37
1,387
37
37
73
73
5,901
5,597
5,475
5,597
37
37
37
f:l::;>::;:3i;.5M;::
10
Methane
Utilized
(mmcf/yr)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
•'::-:-X';:;;;:i":Q:-:
11
Low TOTAL
Emissions
(mmcf/yr)
292
219
255
37
5,779
292
37
37
73
37
110
37
37
1,387
37
37
73
73
5,901
5,597
5,475
5,597
37
37
37
••::;;v:-:31,524-;
12
Operating
Status
1994
Operating
Closed
Operating
Unknown
Utilizing
Closed
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Operating
Unknown
Unknown
Unknown
Unknown
Closed
Utilizing
Utilizing
Utilizing
Unknown
Unknown
Unknown
-------
WEST VIRGINIA
1
Mine Name
Amonate No. 31
Arkwright No. 1
Bald Eagle No 1
Beckley
Birchfield No.1
Blacksville No. 1
Blacksville No. 2
Davidson No 1
Dobbin
Eagle Nest Inc.
Federal No. 2
Gary No. 2
Gary No.50
Smokeless No. 4
Harris No.1
Humphrey No.7
Ireland
Justice No.1
Kermit No. 1
Lightfoot No.1
Lightfoot No.2
Loveridge No. 22
Maple Meadow No.1
Martinka No. 1
McElroy
Old Ben No. 20
Osage No. 3
Rex
Robinson No.95
Rocky Hollow No. 1
Sentinel
Shawnee
Shoemaker
Smoot
Sunrise No. 1
Tommy Creek No. 1
Windsor
TOTAL
2
County
McDowell
Monongalia
Nicholas
Wyoming
Boone
Monongalia
Monongalia
Boone
Grant
Boone
Monongalia
McDowell
Wyoming
Raleigh
Boone
Monongalia
Marshall
Nicholas
Mingo
Boone
Boone
Marion
Raleigh
Marion
Marshall
Mingo
Monongalia
Kanawha
Marion
Mingo
Barbour
Wyoming
Marshall
Webster
McDowell
Raleigh
Brooke
3
Company Name
Consolidation Coal
Consolidation Coal Co.
Terry Eagle Coal Co.
New Beckley Mining Corp.
Birchfield Mining Inc.
Consolidation Coal
Consolidation Coal
Davidson Mining Inc.
Island Creek
Eagle Nest Inc.
Eastern Associated Coal
Gary Enterprises
U.S. Steel Mining Co. Inc.
Hansford Smokeless Inc.
Eastern Associated Coal
Consolidation Coal Co.
Consolidation Coal
Eagle Coal & Dock Co.
Kermint Coal Co.
Eastern Associated Coal
Eastern Assoc. Coal
Consolidation Coal
Maple Meadow Mining Co.
Southern Ohio Coal
McElroy Coal
Old Ben Coal Co.
Consolidation Coal Co.
Rebb Energy Inc.
Consolidation Coal
Rocky Hollow Coal Co.
Philippi Development Inc
U.S. Steel Mining
Consolidation Coal
Smoot Coal Co. Inc.
Sunrise Mining Inc.
Tommy Creek Coal Co.
Windsor Coal Co.
4
Coal
Production
(mmtons/yr)
1.90
0.18
1.29
1.61
3.82
0.88
1.83
4.20
0.20
0.48
1.69
3.31
2.21
0.09
0.41
1.48
0.14
2.77
1.26
2.92
2.73
1.43
1.82
1.86
0.68
0.73
3.07
0.14
0.11
0.23
0.50
1.56
47.51
5
Vent
Emissions
(mmcf/yr)
803
1,424
37
110
548
- 1,789.
3,395
110
110
37
3,833
37
2,847
1,095
73
2,300
657
37
73
73
37
1,861
1,205
110
548
37
. 1,387
37
767
37
438
475
803
110
37
37
146
27,448
6
Degas
System
In Place?
1
1
,
1
1
1
.1
1
1
-
1
1
7
Vent Emis
% of Total
60%
70%
100%
100%
100%
70%
70%
100%
100%
1 00%
. 70%
100%
100%
100%
100%
70%
100%
100%
100%
100%
1 00%
70%
100%
100%
100%
100%
70%
100%
70%
1 00%
1 00%
60%
100%
100%
1 00%
100%
100%
8
Low Degas
Released
535
610
0
0
0
767
1,455
0
0
0
1,643
0
0
0
0
986
. 0
0
0
0
0
798
0
0
0
0
594
0
329
0
0
316
0
0
0
0
0
8,032
9
Low TOTAL
Released
1,338
2,034
37
110
548
2,555
4,849
110
110
37
5,475
37
2,847
1,095
73
3,285
657
37
73
73
37
2,659
1,205
110
548
37
1,981
37
1,095
37
438
791
803
110
37
• 37
146
35,480
lo
Methane
Utilized
. 0
0
0
• o
0
0
0
0
0
0
0
0
0
0
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
Low TOTAL
Emissions
1,338
2,034
37
110
548
2,555
4,849
110
110
37
5,475
37
2,847
1,095
73
3,285
657
37
73
73
37
2,659
1,205
110
548
37
1,981
37
1,095
37'
438
791
803
110
37
37
146
35,480
12
Operating
Status
1994
Unknown
Operating
Unknown
Unknown
Unknown
Closed
Operating
Unknown
Unknown
Unknown
Operating
Unknown
Operating
Unknown
Unknown
Operating
Closed
Unknown
Unknown
Unknown
Unknown
Operating
Operating
Unknown
Operating
Unknown
Operating
Unknown
Operating
Unknown
Operating
Operating
Operating
Unknown
Unknown
Unknown
Unknown
-------
DISCUSSIONS
METHANE EMISSIONS FROM LANDFILLS
OVERVIEW
Methane (CH4) "and carbon dioxide (CO2) are produced from anaerobic decomposition of
organic matter in landfills by methanogenic bacteria. Organic waste first decomposes aerobically (in
the presence of oxygen) and is then attacked by anaerobic non-methanogenic bacteria, which convert
organic material to simpler forms like cellulose, amino acids, sugars, and fats. These simple
substances are further broken down to gases and short-chain organic compounds (H2, CO2,
CH^COOH, HCOOH, and CH3OH), which form the substrates for methanogenic bacteria. The
resulting biogas consists of approximately 50 percent CO2 and 50 percent CH4 by volume, although
the percentage of CO2 may be smaller because some CO2 dissolves in landfill water (Bingemer and
Crutzen, 1987). Additionally, some landfills flare recovered landfill gas, which converts the methane
portion of the gas to
Numerous factors affect the amount of CH4 and CO2 produced in landfills. The factors may
be divided into two general categories: management practices and physical factors.
Management Practices Physical Factors
Waste Management Type (portion of waste Waste Composition
that is landfilled) Moisture Content
Density of Refuse Leachate pH
Particle Size of Refuse Nutrients
Landfill Temperature
Municipal solid waste (MSW) constitutes a significant portion of all types of waste produced in the
United States and also the waste deposited in landfills that produce methane. The two types of
waste management practices that lead to methane production are open dumping and sanitary
landfilling. Since CH4 production from open dumping, or waste piles, is highly uncertain and based
on anecdotal evidence, and since the amount of waste that is openly dumped in the United States
is negligible, CH4 emissions from open dumping are assumed to be zero.
In sanitary landfills, a tightly packed, anaerobic environment favorable for landfill gas
production- is created as compacted waste is spread evenly over the active area of the landfill and
1 However, landfill CO2 emissions are small compared to emissions from other sources discussed in this
report. Also, the CO2 generated is primarily from the decomposition of organic materials derived from
biomass sources (e.g.. crops, forests) which are assumed to be regrown on an annual basis. Therefore, these
are not treated as ncs emissions from waste. If biomass raw materials are being unsustainably produced, the
net CO2 releases should be calculated in Workbook Section 10.
2 Other types of waste that may produce methane in landfills are hazardous and industrial solid waste
and agricultural waste. Hazardous and industrial waste landfills may contain compounds that will result in
a low pH environment toxic to the methanogenic bacteria. Agricultural waste, if landfilled, could potentially
be a significant source of methane emissions but is typically not deposited where anaerobic conditions develop
(see Bingemer and Crutzen, 1987).
D5-1
-------
covered with some type of nonporous soil (e.g., clay). In order to avoid discrepancies over the term
"landfill," this definition of sanitary landfill will be used in the methodology described below.
Other variables of management practices that affect CH4 generation are density and particle
size of refuse. By increasing density, a greater mass can be placed into a specified volume. As
density increases, the degree of saturation (i.e., the ability to absorb water) will increase due to
greater mass, which can lead to more gas production per unit volume (Pacey and DeGier, 1986).
One way to increase density is by shredding refuse. Shredding not only increases density, but also
reduces particle size, which results in a greater surface area exposed to bacterial activity, moisture,
and nutrients. In addition, if shredded refuse is spread evenly in thin layers (—12 inches) and then
compacted, size could be further reduced. Extremely dense refuse (Le., baled refuse), however,
cannot be penetrated by water, and consequently, may produce less gas (Pacey and DeGier, 1986).
Other variables that may affect emissions are the design and size of the landfill and the use of cover
soils.
The actual composition of the municipal solid waste is very important in determining the
amount of landfill gas produced. Municipal solid waste supplies the necessary starting material for
methane generation in landfills by providing degradable organic carbon (DOC) with which
methanogenic bacteria interact to produce landfill gas.3 The majority of waste in the United States
is paper and paper products, which contain a higher carbon content than food (40 percent by weight
according to Bingemer and Crutzen, 1987) and will therefore produce more CH4.
Another physical factor influencing landfill gas production is the moisture content of the
landfill environment (Pacey and DeGier, 1986). Moisture is essential to anaerobic decomposition and
the life of methanogenic bacteria. Water serves as a transport medium for nutrients, bacteria, and
alkaline substances within the refuse (Pacey and DeGier, 1986). As moisture increases the bacteria
become more active and multiply, increasing methane production. Unfortunately, no explicit
functional relationship exists between moisture content of the landfill environment and gas production
estimates (Emcon Associates, 1982).4 The moisture of the refuse, however, can be determined by
analyzing the composition of the landfilled MSW and determining the percentage of "wet refuse" (Le.,
food wastes) and "dry refuse" (Le., paper waste). Ahuja (1990) attempts to include the percentage
of dry refuse in the total amount of MSW landfilled, which contains the DOC available for methane
production, in his methodology to estimate methane emissions. This methodology is discussed later
in the section.
Other factors that are important but have not been factored into any emission estimate due
to the lack of data include the leachate pH and nutrient availability. The optimal pH for gas
production is near neutral, between 6.8 and 7.2, which is not usually reached for several years (Pacey
3DOC is biochemically decomposed to form substrates and can be divided into two parts: dissimilated
and assimilated. The dissimilated fraction is the portion of carbon in substrates that is converted to landfill
gas (i.e., CO2 and CH4), and the assimilated fraction is the remainder of carbon that is used to produce new
microbial cell material (Tabasaran, 1981).
4In a study recently conducted by U.S. EPA's Office of Solid Waste, a correlation between landfill gas
generation rate and precipitation rate was obtained (no correlation between precipitation rate and moisture
content in the landfill was evaluated). Based on data from 12 "wet" landfills (precipitation of 1.9 ft. or more)
and data from 8 "dry" landfills (precipitation of less than 1.9 ft.), landfill gas emissions from "wet" landfills were
—2.6 times greater than emissions from "dry" landfills (Thorneloe, 1990).
D5-2
-------
and DeGier, 1986). Methane generation is not inhibited unless the environment is very acidic (pH
<6.Q). Alkaline substances, transported in water, help to balance the pH level and hinder the
formation of organic acids, which in large concentrations decrease methane production. Nutrients
are essential to the life and growth of bacteria.
Temperature, unlike leachate pH, can be related to the amount of degradable organic carbon
that will generate landfill gas (Le., the fraction of DOC dissimilated). At temperatures below 50-59°F.
methane production is drastically reduced (Pacey and DeGier, 1986). Because the majority of
methane production occurs in the deeper Jayers of the landfill, where heat is generated from
anaerobic decomposition, temperatures typically range between 77-104°F. An average of 95°F can
be expected within the anaerobic zone (below 6.5-13 ft.) (Gunnerson and Stuckey, 1986, in Bingemer
and Crutzen, 1987) and will result in —77 percent dissimilated DOC.5 At extremely high
temperatures (above 140°F) methane generation usually ceases (Pacey and DeGier, 1986).
Landfill gas recovery can be an important factor in reducing CH4 emissions from landfills as
well as provide a source of renewable energy. Landfill gas recovery systems are increasing, and the
CH4 generated from landfills is being captured as an energy source. Currently, there are 120 sites
in the U.S. where landfill gas is captured and used as an energy source. It would be beneficial to
estimate the amount of CH4 existing in the recovered landfill gas in order to subtract it from total
CH4 emitted from that state's landfills. This has been accounted for in the methodology, although
each state will need to estimate its own quantity of CH4 capture from biogas recovery sites.
Refuse may be disposed of by other management practices that do not produce methane such
as incineration, materials recovery/recycling, and composting. These alternative methods of disposal
may be more attractive than sanitary landfilling without gas recovery systems as land availability
declines and potential health and environmental risks of landfilling increases in the U.S. For example,
Japan prefers incineration over landfilling; about 73 percent of Japan's waste is disposed of by
incineration and only 23 percent by sanitary landfilling (Hayakawa, 1990, in Thorneloe, 1991).
DESCRIPTION OF WORKBOOK METHOD
The preferred approach for estimating methane emissions from landfills in the U.S. would be
to actually measure the emissions from each of the approximately 6,000 operating landfills and the
thousands of closed landfills. Unfortunately, such an approach is impractical, if not impossible.
Previous efforts to estimate emissions from landfills offer two alternative approaches:
• Determine the emissions "potential" of a representative quantity of refuse through theoretical
considerations (e.g., carbon content) or laboratory simulation. Scale this value to the state
level by estimating the quantity of refuse in landfills statewide.
• Use available data to determine the actual generation rates of methane per unit of refuse and
multiply this value by the estimated quantity of refuse disposed of in landfills statewide.
5Landfill temperature is related to the amount of DOC that is dissimilated to produce biogas by the
relationship: Cc / Cp = (0.014 T + 0.28), where Cc = carbon converted to biogas, Cp = total carbon
compounds in substrates, and T = landfill temperature (Tabasaran, 1981). From this relationship, as
temperature increases, so does the rate of gas formation. •
D5-3
-------
The first approach has been the most frequently used method to estimate emissions from landfills.
It relies on kinetic models of landfill gas formation or on simulations conducted in laboratories. This
method assumes conditions that occur in kinetic models or under laboratory conditions closely
simulate actual field conditions. This assumption limits the accuracy of the method, since it is difficult
to determine whether theoretical or laboratory conditions actually simulate field conditions. The
second approach, which relies on field measurements, is the preferred method of analysis because it
relies on actual data rather than theoretical results.
The approach suggested for -the workbook calculations is based on an emissions model
developed for the report Anthropogenic Methane Emissions in the U.S.: Report to Congress (U.S. EPA
1993). This method uses a statistical model derived initially from analyses performed by the U.S.
EPA Air and Energy Engineering Research Laboratory (AEERL) and enhanced by the U.S. EPA
Office of Air and Radiation (OAR). Emissions estimates may be calculated by collecting data on the
characteristics of the state's landfill population and applying this information to the method. The
method presented in Workbook Section 5 consists of the following ten steps (for a more detailed
description of these steps, please see the workbook):
Step 1: Obtain the required data.
Step 2: Estimate waste in place at MSW landfills.
Step 3: Estimate fraction of waste in large versus small landfills.
Step 4: Classify the state as arid or non-arid. '
Step 5: Estimate waste in place at small MSW landfills.
Step 6: Estimate waste in place at large MSW landfills.
Step 7: Estimate total methane generated from MSW landfills.
Step 8: Estimate methane generated from industrial landfills.
Step 9: Adjust for flaring and recovery.
Step 10: Adjust for oxidation.
\
The emissions model on which this method is based was developed by examining and
confirming data from 85 landfills that recover methane gas to produce energy. The data analyzed in
detail the relationships between methane recovery and (1) refuse quantity; (2) refuse characteristics
(e.g., moisture content, temperature, and pH); and (3) landfill characteristics (such as age, depth,
volume, and surface area).6 The analysis showed that a simple model using the total amount of
waste in place and the landfill's location in an arid or non-arid climate was adequate for estimating
methane production. Because this method is based on the total waste in place at a landfill, and not
on annual waste generation and disposal rates, it accounts for timed releases of methane instead of
assuming that all of the methane generated is released in a single year.
The analysis indicated that the amount of methane gas generated per unit of waste was higher
in landfills with over 1.1 million tons of waste in place than landfills with less than 1.1 million tons
of waste in place. To account for this, a separate model was developed to calculate emissions from
landfills with less than 1.1 million tons of waste in place. In summary, the emissions depend on
6 Please note that the analysis assumes that landfill wastes produce methane over a thirty year
period. If the actual period is significantly longer, the emissions may be greatly understated.
7 The accuracy range of the equations for large landfills (±15%) is better than for small landfills
(±20%) because the estimate for large landfills is based on a greater number of actual landfill
methane production measurements. .
D5-4
-------
three key factors: (1) total waste in place; (2) landfill size; and (3) location in an arid or non-arid
climate. The four equations (arid/large, arid/small, non-arid/large, non-arid/small) are listed below:
k
Small landfills (< 1.1 million tons)
Nonarid: Methane ( ft3/day )= 0.35 W(tons) ± 20 %
Arid: Methane ( ft3/day ) = 0.27 W(tons) ±20%
where:
W = Average waste in place .(tons) at small landfills
Large Landfills (>1.1 million tons)
Nonarid: Methane ( ft3/day ) = N • (419,000 + 0.26 Wmvg(tons) ) ± 15.%
Arid: Methane ( ft3/day ) = N • (419,000 + 0.16 Wlvg(tons) ) ± 15 %
where:
N = Number of large landfills in the state
W = Average waste in place (tons) at large landfills
Because the models only determine the amount of gas generated by the landfill, the results
of the model must be adjusted to determine actual emissions. As previously described, some of the
methane produced by landfills is recovered to produce energy, flared to meet environmental and
safety requirements, or oxidized in the soils covering the landfill.
Facilities that recover methane gas to produce energy should have sufficient records to
estimate the amount of gas that is recovered with relative accuracy. Government Advisory Associates
(GAA) publishes the Methane Recovery from Landfill Yearbook, providing a fairly accurate source
for this information.
Information quantifying the amount of gas recovered by facilities for flaring is limited.
Currently, no information exists explicitly documenting the amount of methane recovered and flared.
Based on anecdotal evidence, it is assumed that the amount of methane flared is equal to 25 percent
of the methane recovered for energy production.
Methane may also be oxidized in the top layer of soil over the landfill. Landfills that recover
methane for energy recovery or flaring utilize a system of wells, pipes, and pumps to prevent the gas
8It should be noted that the analysis used to create the model is based on data describing the
methane recovered from landfills. The methane recovery information is an imperfect surrogate for
emissions measurements. If the landfills used in this analysis are not representative of landfills as a
whole, then the models used in this analysis may not accurately represent state landfill methane
generation.
D5-5
-------
from passing through the landfill cover. However, in landfills that do not operate recovery systems,
the methane will pass through the soil cover of the landfill where it may be oxidized (Whalen,
Reeburch and Sandbeck, 1990). The amount of oxidation that occurs is uncertain and depends on
the soil characteristics and the environment. Currently, there is limited research available to assist
in quantifying the amount of methane that is eliminated during this process. For purposes of this
exercise, it is assumed that 10 percent of the methane generated that is not recovered is oxidized in
the soil.
Methane is also generated from waste deposited in non-hazardous industrial landfills.
Although methane generation from non-hazardous industrial landfills is believed to be small relative
to MSW landfills, industrial landfill methane generation is still a significant source of methane
emissions. Note that methane generation from industrial landfills does not include methane
generation from industrial waste disposed of into MSW landfills. This methane generation is already
accounted for under MSW landfills.
Precise estimates of the quantity of waste in industrial landfills and its methane generation
rate are not available. Based on estimates of the quantity of waste in place at industrial landfills and
on the estimated organic content of industrial landfills compared to MSW landfills, EPA (1993)
estimated that methane generation from industrial landfills in the U.S. is approximately 7 percent of
methane generation from MSW landfills in the U.S. This 7 percent value may be used to estimate
state methane generation from industrial landfills.
Alternatively, if state information is available on the quantity of waste in place (WIP) at
industrial landfills, the ratio of emissions from industrial landfills to emissions from MSW landfills may
be calculated as follows:
Average 15% organic content x WIP at Industrial Landfills
Average 65% organic content x WIP at MSW landfills
The resulting value would be used in place of the 7 percent default value.
Methane emissions to the atmosphere will equal total methane production from municipal
landfills adjusted for the methane produced by industrial landfills, the methane recovered, and the
methane oxidized in the landfills before being released to the atmosphere. These adjustments can
be described as:
Net Methane Emissions = municipal landfill methane generation
plus industrial landfill methane generation
minus municipal methane recovery
minus industrial methane recovery
minus methane oxidation by soil.
ALTERNATE METHODOLOGIES
This section presents two alternative methods for estimating methane emissions from
landfills if states are not able to obtain the data required to use the recommended method. The
simplest methodology for estimating CH4 emissions from landfills is based on a mass balance
approach, where an instantaneous release of methane is assumed to enter the atmosphere during
the same year that refuse is placed in the landfill (Bingemer and Crutzen, 1987). Furthermore,
D5-6
-------
Bingemer and Crutzen do not consider subsequent releases of CH4 to the atmosphere from the
MSW placed in a landfill that will'be emitted in future years nor from previous years. The reason
for this is that their approach implicitly assumes that all waste placed into a landfill during the
year emits all potential methane immediately. Bingemer and Crutzen use four economic regions:
U.S./Canada/Australia, Other OECD, USSR/E. Europe, and Developing Countries. Then they
determine how much MSW is produced for each region and how much of that MSW is
degradable organic carbon. To calculate the annual emissions from MSW, Bingemer a..J Crutzen
used the following equation:
(1) Methane Emissions = Total MSW generated (Ibs/yr) x MSW landfilled (%) x
DOC in MSW (%) x Fraction Dissimilated DOC (%) x
0.5 Ibs CH4/lb biogas x Conversion factor (16 Ibs CH4/12 Ib
C) - Recovered CH4 (Ibs/yr).
The MSW generation rates and composition data for the U.S. can be used to calculate methane
emissions instead of the regional factors for U.S./Canada/Australia (see Table D5-1). Currently,
no state-specific data are available, but each state can estimate its annual MSW generation rate
and percentage of MSW landfilled. MSW generation rates and percentage of MSW landfilled for
the U.S. have been estimated by the OECD/IEA (1989) as well and are presented in Table D5-1.
Bingemer and Crutzen's regional estimates are for 1980 and are somewhat outdated; the country-
specific estimates presented by OECD/IEA (1989) were taken from 1988 data or the nearest year
to 1988 for which data were available. The U.S. EPA's Office of Solid Waste has also provided
MSW and MSW landfilled figures.
Another methodology outlined by Ahuja (1990) is based on Bingemer and Crutzen's
assumptions but is more detailed due to the addition of a new variable -- percentage of MSW that
is dry refuse. Using assumptions by Bingemer and Crutzen (1987), % MSW as dry refuse, and an
average landfill temperature of 95°F to derive the fraction of dissimilated DOC, methane
emissions can be calculated as follows (Ahuja, 1990):
(2) Methane Emissions = Total MSW generated (Ibs/yr) x MSW landfilled (%) x
DOC in MSW (%) x Dry Refuse (%) x Fraction
dissimilated DOC (%) x (0.5 Ibs CH4/lb biogas) x
Conversion factor (16 Ibs CH4/12 Ib C) - Recovered CH4
(Ibs/yr).
A more complex method for estimating methane emissions from landfills is based on a
first-order kinetic model, the Scholl Canyon model, which considers timed releases of methane to
the atmosphere (Thorneloe, 1990). Best results are usually obtained when the model is applied to
individual landfills, but it can be applied to an entire country such as the U.S. Estimates have
been made for the U.S. using this model (e.g., Colt et al., 1990). Detailed information, such as
waste generation and composition, moisture content, pH, temperature, available nutrients,
landfill's age, size, type, and time since closure, is required to calculate emissions (Thorneloe,
1990). This method assumes that gas production will be highest upon initial placement of waste
in the landfill, after a certain negligible lag period during which anaerobic conditions are formed.
The rate then decreases exponentially (i.e., undergoes first-order decay) as the degradable organic
carbon available decreases (U.S. EPA, 1990). The model requires that MSW rates over the life
D5-7
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Table D5-1
Waste Disposal, Composition, and Waste Generation Estimates in the U.S.
Source
Bingemer and Crutzen (1987)
U.S. EPA (1988a)
OECD (1989)
Piccot et al. (1990)
WRI (1990)
Year
1980
1986
1985
1988
1983
% MSW
Landfilled
91
83.2
62
85
NA
% DOC of
MSW
22
NA
NA
21
NA
Waste Generation
(Ibs/cap/yr)
4.0
4.0
4.4
1.9
4.6
of the landfill, or extended period of time (e.g., 1960-1990), be used to estimate methane
emissions more accurately. The model equations and variables are described briefly below:
QCH4 = k x L0 x R x e-kt
where, Q-CH4 = methane generation rate at year t (ft3/yr),
L0 = potential methane generation capacity (ft /tons of refuse),
R = quantity of waste landfilled (tons/yr),
k = methane generation rate constant (yr"1),
t = time since initial refuse placement (yr).
Theoretically, L0 depends on the type of refuse only and is based on the chemical
composition of refuse and its biodegradability. The methane generation constant, k, determines
how quickly the methane generation rate decreases (U.S. EPA, 1990). The rate constant and the
generation rate are related; the higher the value of k, the faster the methane generation rate
decreases over time. The rate constant is affected by the same factors that affect L0, with the
addition of temperature. Some of these variables themselves, such as L0 and k, need to be
calculated even before the equation can be used, although some values have been determined
(see, e.g., U.S. EPA, 1990). To date no functional relationships have been determined among
these key factors and a better understanding of these factors is needed to more accurately
calculate methane emissions from landfills with this approach.
AVAILABILITY OF DATA
In-state sources should be consulted to obtain data on total MSW generated and the
amount of methane recbvered from landfills. Ideally, in-state data sources should also be used for
waste characteristics and waste management practices (e.g., percent of MSW that is landfilled;
percent of DOC contained in the MSW; and percent of DOC that is dissimilated). However, in
many states, such data may not be readily available. In such cases, the average default values
indicated in the workbook section should be used. Additionally, some data on waste generation,
waste composition, and waste disposal are available from U.S. EPA (1988a).
D5-8
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UNCERTAINTIES -> . •
There are several uncertainties associated with using the recommended method for
estimating methane emissions from landfills. First, the actual number and size of landfills and
other waste management facilities are not know with certainty. Many small and unregulated
facilities may exist that are not included in these estimates. Second, the time period over which
landfill waste produces methane also is not certain. At present, the assumed time period is thirty
years. This could be an overestimate or underestimate. Third, this methodology is based on
information from methane recovered from various landfills. These landfills may not be
representative of landfills as a whole. Fourth, little information is available on the amount of
methane oxidized by the soil cover over landfills. The assumed ten percent is based on limited
measurements. Lastly, the method of estimating methane emissions from small landfills is less
accurate than the one for large landfills. This difference is due to the fact that more methane
measurements were taken from large landfills than small ones. The basis for estimating emissions
from small landfills needs to be improved. Other sources of uncertainty in estimating CH4
emissions from landfills are the effects of climate on methane emission rates and the impact of
landfill design characteristics and maintenance procedures (Piccot et al., 1990).
REFERENCES
Ahuja, D. 1990. Estimating Regional Anthropogenic Emissions of Greenhouse Gases.
Forthcoming in The Indian Geosphere Biosphere Programme. Tata Energy Research
Institute, New Delhi, and The Bruce Co., Washington, D.C.
Bhide, AD., and B.B. Sundaresan. 1981. Solid Waste Management in Developing Countries.
National Environmental Engineering Research Institute, Nadpur, India. 210 pp.
Bingemer, H.G., and P.J. Crutzen. 1987. "The Production of Methane from Solid Wastes,"
Journal of Geophysical Research. 92(D2):2181-2187.
BioCycle, 1992. "1992 Nationwide Survey: The State of Garbage." May 1992.
Cointreau, S. J. 1984. "Solid Waste Collection Practice and Planning in Developing Countries,"
In Holmes, J.R. (ed.), Managing Solid Wastes in Developing Countries. John Wiley: New
York. 151-182. :
Colt, J., R. Harvey, M. Lochhead, S. Mayer, L. Boccuti, and 1C Hogan. 1990. Methane Emissions
from Municipal Solid Waste Landfills in the United States. ICF/U.S. EPA, Washington,
D.C. 23 pp.
Department of Commerce. 1988. State, Regional, and National Monthly and Annual Precipitation
for the Contiguous United States: January 1931 - December 1987. Department of
Commerce. National Oceanic and Atmospheric Administration. National Climatic Data
Center. Asheville, North Carolina. August 1988.
Emcon Associates. 1982. Methane Generation and Recovery From Landfills. Ann Arbor Science:
Ann Arbor, Michigan.
D5-9
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GAA (Goverment Advisory Associates). 1991. Methane Recovery From Landfill Yearbook. New
York, NY.
Gunnerson, C.G., and D.C. Stuckey. 1986. Integrated Resource Recovery: Anaerobic Digestion
Principles and Practices for Biogas Systems. World Bank Technical Paper Number 49,
Washington, D.C.
Hayakawa, T. 1990. "The Status Report on Waste Management in Japan - Special Focus on
Methane Emission Prevention. In Proceedings from International Workshop on Methane
Emissions from Natural Gas Systems, Coal Mining and Waste Management Systems.
Environment Agency of Japan, U.S. Agency for Interntaional Development, and the U.S.
EPA, Washington, D.C., 9-13, April 1990. 509-523.
IPCC. 1992. Climate Change: The Supplementary Report to the IPCC Scientific Assessment. J.T.
Houghton, B.A. Callander, and S.K. Varney (eds.). World Meteorological
Organization/United Nations Environment Programme. New York, NY.
OECD/IEA (Organization for Economic Cooperation and Development/International Energy
Agency). 1991. Environmental Indicators: A Preliminary Set., OECD/IEA, Paris.
OECD/IEA. 1989. Environmental Data Compendium 1989. OECD/IEA, Paris.
Orlich, J. 1990. "Methane Emissions from Landfill Sites and Wastewater Lagoons," In
Proceddings from International Workshop on Methane Emissions from Natural Gas
Systems, Coal Mining and Waste Management Systems. April 9-13, 1990, Washington, D.C.
Funded by the Environment Agency of Japan, U.S. Agency for International
Development, and the U.S. Environmental Protection Agency.
Pacey, J.G., and J.P. DeGier. 1986. "The Factors Influencing Landfill Gas Production," In
Proceedings from Energy From Landfill Gas. Conference sponsored by the U.K.
Department of Energy and the U.S. Department of Energy. 51-59.
Piccot, S.D., A. Chadha, J. DeWaters, T. Lynch, P. Marsosudiro, W. Tax, S. Walata, and J.D.
Winkler. 1990. Evaluation of Significant Anthropogenic Sources ofRadiatively Important
Trace Gases. Prepared for the Office of Research and Development, U.S. EPA,
Washington, D.C.
Richards, K.M. 1990. Landfill gas: "Working with Gaia," Biodeterioration Abstracts. 3(4) 317-
331. Also published in Proceedings from International Workshop on Methane Emissions
from Natural Gas Systems, Coal Mining and Waste Management Systems. April 9-13, 1990,
Washington, D.C. Funded by the Environment Agency of Japan, U.S. Agency for
International Development, and the U.S. Environmental Protection Agency.
Tabasaran, O. 1981. "Gas Production from Landfills," In Bridgewater, A.V., and K. Lidgren
(eds.), Household Waste Management in Europe, Economics and Techniques. Van
Nostrand Reinhold Co., New York. 159-175.
D5-10
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Thorneloe, S.A., R.L. Peer, D.L. Campbell, and K.S. Kepford. 1991. Proposed Methodology for
Estimating Global Landfill Methane Emissions. January 28. U.S. EPA and Radian
Corporation, Research Triangle Park, North Carolina.
Thorneloe, S.A. 1991. "United States Research on Enhancing Landfill Gas Production," Landfill,
Gas Enhancement Test Cell Data Exchange. Final report on the Landfill Gas Expert
Working Group, International Energy Agency. AEA-EE-0226. Harwell Laboratory,
Oxfordshire, United Kingdom.
Thorneloe, S.A. 1990. "Landfill Gas and the Greenhouse Effect," Paper presented at the
International Conference on Landfill Gas: Energy and Environment. October 17.
U.S. EPA (U.S. Environmental Protection Agency). 1993. Anthropogenic Methane Emissions in the
United States: Report to Congress. Global Change Division, Office of Air and Radiation,
US EPA, Washington, DC. April 1993. EPA/430-R-93-003
U.S. EPA. 1992. "Characterization of Municipal Solid Waste in the United States. 1992 Update,"
prepared by the Office of Solid Waste and Emergency Response, US EPA, Washington,
DC. July 1992.
U.S. EPA. 1990. Air Emissions from Municipal Solid Waste Landfills-Background Information for
Proposed Standards and Guidelines. Office of Air Quality, Planning and Standards, U.S.
EPA, Washington, D.C.
U.S. EPA. 1988a. Solid Waste Disposal in the United States. Volume II. Office of Solid Waste
and Emergency Response, U.S. EPA, Washington, D.C.
U.S. EPA. 1988b. National Survey of Solid Waste (Municipal) Landfill Facilities. Washington,
D.C. September 1988. EPA/530-SW88-034
World Resources Institute. 1990. World Resources Report: 1990-91. WRI, Washington, D.C.
Whalen, S.C., W.S. Reeburgh, and K.A. Sandbeck. 1990. "Rapid Methane Oxidation in a Landfill
Cover Soil," Applied and Environmental Microbiology. November 1990.
D5-11
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DISCUSSION 6
METHANE EMISSIONS FROM
DOMESTICATED ANIMALS
OVERVIEW
Methane is produced as part of the normal digestive processes of animals. Referred to as
"enteric fermentation," these processes produce emissions that account for a significant portion of the
global methane budget, about 65-100 Tg annually (IPCC, 1994). Of domesticated animals, ruminant
animals (cattle, buffalo, sheep, goats, and camels) are the major source of methane emissions, with
cattle being the most important source. Although wild ruminant animals, such as deer, and wild non-
ruminant herbivores, such as rabbits, also produce methane, they are not included because emissions
from these animals are considered a natural source.
Ruminant animals have a large "fore-stomach," or rumen, within which microbial fermentation
-breaks down feed into soluble products that can be utilized by the animal. Approximately 200 species
and strains of microorganisms are present in the anaerobic rumen environment, although only a small
portion, about 10 to 20 species, are believed to play an important role in ruminant digestion (Baldwin
and Allison. 1983). The microbial fermentation that occurs in the rumen enables ruminant animals
to digest coarse plant material that monogastric animals1 cannot digest.
Methane is produced in the rumen by bacteria as a by-product of the fermentation process.
This methane is exhaled or eructated by the animal and accounts for the majority of emissions from
ruminants. Methane also is produced in the large intestines of ruminants and also is excreted. Non-
ruminant herbivores such as horses, mules, rabbits, pigs, and guinea pigs have a limited amount of
fermentation in the large intestines or ceca. The methane produced in this manner is quite small
compared to the amount produced by ruminant animals.
There are a variety of factors that affect methane production in ruminant animals, such as:
the physical and chemical characteristics of the feed; the feeding level and schedule; the use of feed
additives to promote production efficiency; and the activity and health of the animal. It has also been
suggested that there may be genetic factors that affect methane production. Of these factors, the
feed characteristics and level have the most influence.
To describe the methane production by ruminant animals, it is convenient to refer to the
portion of feed energy intake that is converted to methane. Higher levels of conversion translate into
higher emissions, given constant feed energy intake. Similarly, higher levels of intake translate into
higher emissions, given constant conversion. There are, however, interactions between level of intake
and conversion to methane, so these values are not independent.
As a result of the various interrelationships among feed characteristics, feed intake, and
conversion rates to methane, most well-fed ruminant animals in temperate agriculture systems will
convert about 5.5-6.5 percent of their feed energy intake to methane (Johnson et al., 1991). Given
1 Monogastric animals have a mouth, esophagus, stomach, small intestines, large intestines, pancreas, and
liver (Ensminger, 1983). Examples of monogastric animals include swine,.dogs, monkeys, and humans.
D6-1
-------
this range for the rate of methane formation, methane emissions can be estimated based on the feed
energy consumed by the animals. Because feed energy intake is related to production level (e.g.,
weight gain or milk production), the feed energy intake can be estimated for these regions based on
production statistics.
The rates of conversion of feed energy to methane for the non-ruminant animals are much
lower than those for ruminants. For swine on good quality grain diets about 0.6 percent of feed
consumed is converted to methane (Crutzen et al., 1986). For horses, mules, and asses the estimate
is about 2.5 percent. While these estimates are also uncertain arid likely vary among regions, the
global emissions from these species are much smaller than the emissions from ruminant animals.
Consequently, the uncertainty in these values does not contribute significantly to the uncertainty in
the estimates of total methane emissions from livestock.
DESCRIPTION OF WORKBOOK METHOD
While it is possible to measure methane emissions from cattle directly, it is not practical for
preparing an emissions inventory. Given that direct measurements will not be taken, it is appropriate
to select a model for estimating emissions factors for individual animal types. Once these factors have
been developed, they are multiplied by applicable animal populations to arrive at total emissions for
each animal type; total emissions by animal type are summed to arrive at total annual methane
emissions.
Given their population and size, cattle account for the majority of methane emissions in the
U.S. Additionally, cattle characteristics and emissions vary significantly by region. Therefore, it is
important to develop a good model for cattle which takes into account the diversity of cattle types
and cattle feeding systems in the U.S. Emissions factors for other animals were developed using a
simple functional relationship between feed intake and feed intake released as methane (see Table
D6-1). This approach is reasonable given that cattle characteristics of other animals are more or less
homogeneous across regions. Therefore, the variability in emissions factors among regions for other
animals is much smaller than the variability in emissions factors for cattle.
The emissions factors presented in^the Workbook Section were developed using a validated
mechanistic model2 of rumen digestion and methane production for cattle feeding systems in the
U.S. The digestion model estimates the amount of methane formed and emitted as a result of
microbial fermentation in the rumen. The digestion model is linked to an animal production model
that predicts growth, pregnancy, milk production and other production variables as a function of
digestion products developed by the digestion model. The model evaluates the relationships between
feed input characteristics and animal outputs including weight gain, lactation, heat production,
pregnancy, and methane emissions. The model has been validated for a wide range of feeding
conditions encountered in the U.S.; a total of 32 diets were simulated for 8 animal types in 5 regions.
The emissions factors derived using the approach outline above are provided in Tables D6-1
and D6-2, as well as in Workbook Section 6. Given the detailed, U.S.-specific data used to derive
these emissions factors, the approach presented in'the Workbook Section is likely to be sufficient for
most animal types in most regions of the U.S. However, in some states cattle characteristics may
The mechanistic model is outlined in the U.S. EPA Report to Congress entitled "Anthropogenic
Methane Emissions in the United States: Estimates for 1990."
D6-2
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Table D6-1
Enteric Fermentation Emissions Factors for Other Animals (Ibs/head/year)
Animal Type
Sheep
Goats
Swine
Horses
Mules/Asses
Feed Intake
(MJ/h/day)
20
14
38
110
60
Methane
Conversion
(%)
6%
5%
0.6%
2.5%
2.5%
Emissions Factors
(Ibs/h/yr)
17.6
11.0
3.3
39.6
48.5
Source: Crutzen et al (1986).
Table D6-2
Emissions Factors for U.S. Cattle by Region (Ibs/head/yr)
Mechanistic Model vs. IPCC Model
Animal Type/Region
National Average
Mechanistic Model
IPCC Method
Dairy Cattle
Replacements 0-12 months
Replacements 12-24 months
Mature Cows
43.1
129.4
252.1
46.9
127.5
248.7
Beef Cattle
Replacements 0-12 months
Replacements 12-24 months3
Mature Cows
Weanling System Steers/Heifersb
Yearling System Steers/Heifers
Bulls0
49.1
143.0
146.7
50.8
104.1
220
51.1
121.5
143.9
80.2
113.7
223.4
a The IPCC emissions factors for beef replacements 12-24 months, were calculated to reflect
the NEg for medium frame heifer calves as cited in NRC (1984).
b Feed and growth rates for weanlings in the U.S. are different from the rest of the world;
the IPCC method does not account for these differences, which could explain the deviant
results.
c The IPCC emissions factors for bulls were calculated to reflect the intake requirements as
cited in NRC (1984) • ;
D6-3
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vary significantly from those analyzed by the mechanistic model, from which the emissions factors
were derived. In such a case, an alternative approach may be appropriate, such as the method
presented in the IPCC Guidelines for National Greenhouse Gas Inventories: Vol. 2, Reference Manual
(IPCC. 1994). To compare the accuracy of the IPCC model with that of the mechanistic model,
emissions estimates were generated for both models using identical inputs. The emission factors
derived from each model and used to calculate emission estimates are presented in Table D6-2. As
illustrated in the table, the emission factors are similar. The following section presents the IPCC
model. For completeness, some discussion of the appropriateness of this method to tropical
conditions is provided, although these conditions are not typically found in the U.S.
ALTERNATE METHODOLOGY
The IPCC method for estimating methane emissions from enteric fermentation requires three
basic steps:3
Step 1: Divide the livestock population into subgroups and characterize each
subgroup.
Step 2: Estimate emissions factors for each subgroup in terms of kilograms of
methane per animal per year. Once these have been determined they may be
easily converted to pounds per animal per year.
Step 3: Multiply the subgroup emissions factors by the subgroup populations to
estimate the subgroup emissions, and sum across subgroups to estimate total
emissions.
Step 1: Livestock Populations
To develop precise estimates of emissions, cattle should be divided into categories of relatively
homogeneous groups. For each category a representative animal is chosen and characterized for
purposes of estimating an emissions factor. Table D6-3 presents a set of recommended representative
animal types for cattle. Three main categories, Mature Dairy Cows, Mature Non-Dairy Cattle, and
Young Cattle, are recommended as the minimum set of representative types. The sub-categories
listed should be used when data are available. In particular, the sub-population of cows providing
milk to calves should be identified among non-dairy cattle because the feed intake necessary to
support milk production can be substantial.
For each of the representative animal types defined, the following information is required:4
• annual average population (number of head);
3 The IPCC method is outlined in the IPCC Greenhouse Gas Inventory Reference Manual (IPCC, 1994).
4 Data requirements for this model are expressed in metric units. The reason for this being that the
energetic relationships presented in the equations were developed for use with metric units. After emissions
factors are derived, however, they can be converted to U.S. units by applying the appropriate conversion
factors.
D6-4
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• average daily feed intake (megaJoules (MJ) per day and kg per day of dry matter);
and
• methane conversion rate (percentage of feed energy converted to methane).
Generally, data on average daily feed intake are not available, particularly for grazing animals.
Consequently, the following data should be collected for estimating the feed intake for each
representative animal type:
weight (kg);
• average weight gain per day (kg);5
• feeding situation: confined animals; animals grazing on good quality pasture; and
animals grazing over very large areas;
• milk production per day (kg/day);6
• average amount of work performed per day (hours/day);
• percent of cows that give birth in a year;7 and
feed digestibility (%).8
These data should be obtained from state-specific cattle evaluations. Some data, such as weight,
weight gain, and milk production, may be available from production statistics. Care should be taken
to use the live cattle weights, as contrasted with slaughter weights.
Data on methane conversion rates are also not generally available. As a rule of thumb, a 6
percent conversion rate (±0.5 percent) is recommended for all cattle, except feedlot cattle consuming
diets with a large quantity of grain9. For feedlot cattle on high grain diets a rate of 4 percent (±0.5
percent) is recommended. In circumstances where good feed resources are available (i.e., high
digestibility and high energy value) the lower bounds of these ranges can be used. When poorer feed
resources are available, the higher bounds are more appropriate.
5 This may be assumed to be zero for mature animals.
6 Milk production is required for dairy cows and non-dairy cows providing milk to calves.
7 This is only relevant for mature female cows.
8 Feed digestibility is defined as the proportion of energy in the feed that is not excreted in the feces.
Digestibility is commonly expressed as a percentage (%). Common ranges for feed digestibility for cattle are
50% to 60% for crop by-products and rangelands; 60% to 70% for good pastures, good preserved forages, and
grain-supplemented forage-based diets; and 75% to 85% for grain-based diets fed in feedlots.
9 It should be noted that this rule of thumb applies only to the U.S.
D6-5
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Table D6-3
Recommended Representative Cattle Types
Main Categories
Mature Dairy Cows
Mature Non
-Dairy Cattle
Young Cattle
Sub-Categories
Used principally for commercial milk production
Mature Females:
— Beef Cows: used principally for producing beef steers and heifers
- Multiple-Use Cows: used for milk production, draft power, and
other uses
Mature Males:
- Breeding Bulls: used principally for breeding purposes
- Draft Bullocks: used principally for draft power
Pre-Weaned Calves
Growing Heifers, Steers/Bullocks and Bulls
Feedlot-Fed Steers and Heifers on High-Grain Diets
The above rule of thumb is a rough guide based on the general feed characteristics and
production practices found in states. State-specific exceptions to these general rules of thumb should
be taken into consideration as necessary based on detailed data from cattle experts.
Step 2: Emissions Factors
The emissions factors for each category of cattle are estimated based on the feed intake and
methane conversion rate for the category. Feed intake is estimated based on the feed energy
requirements of the representative animals, subject to feed-intake limitations. The net energy system
described in NRC (1984 and 1989) is recommended as the starting point for the estimates.
The net energy system specifies the amount of feed energy required for the physiological
functions of cattle, including maintenance, growth, and lactation. Feed energy requirements for work
have also been estimated. Energy requirements for pregnancy have also been added for the portion
of cows that give birth in each year. The following information is required to estimate feed energy
intakes:
• Maintenance
Maintenance refers to the apparent feed energy required to keep the animal in
energy equilibrium, i.e., there is no gain or loss of energy in the body tissues (Jurgens,
1988). For cattle, net energy for maintenance (NEm) has been estimated to be a
function of the weight of the animal raised to the 0.75 power (NRC, 1984):
NE (MJ/day) = 0.322 x (weight in kg)
0.75
D6-6
-------
NRC (1989) recommends that lactating dairy cows be allowed a slightly higher
maintenance allowance:
NEm (MJ/day) = 0.335,x (weight in kg)0-75 {dairy cows} (1*)
Additional energy is required for animals to obtain their food. Grazing animals
require more energy for this activity than do stall-fed animals. The following energy
requirements are added for this activity based on their feeding situation:
Confined animals (pens and stalls): no additional NEm;
Animals grazing good quality pasture: 17 percent of NEm; and
Animals grazing over very large areas: 37 percent of NEm.
Growth
The energy requirements for growth can be estimated as a function of the weight of
the animal and the r,ate of weight gain. NRC (1989) presents formulae for large- and
small-frame males and females, the estimates from which vary by about ±25 percent.
The equation for large-frame females is recommended, which is about the average for
the four types:
NE2 (MJ/day) = 4.18 x (0.035 W°-75 x WGL119 + WG) (2)
o »
where:
W = animal weight in kilograms (kg); and
WG = weight gain in kg per day.
The relationships for NE~ were developed for temperate agriculture conditions, and
may over-estimate energy requirements for tropical conditions, particularly for draft
animals that may have a lower fat content in their weight gain (Graham, 1985).
However, no data are available for improving the estimates at this time.
Lactation
Net energy for lactation has been expressed as a function of the amount of milk
produced and its fat content (NRC, 1989):
NE, (MJ/day) = kg of milk/day x (1.47 + 0.40 x Fat %) (3)
At 4.0 percent fat, the NE, in MJ/day is about 3.1 MJ/kg of milk x kg of milk/day.
Draft Power
Various authors have summarized the energy intake requirements for providing draft
power (e.g., Lawrence, 1985; Bamualim and Kartiarso, 1985; and Ibrahim, 1985). The
strenuousness of the work performed by the animal influences the energy
requirements, and consequently a wide range of energy requirements have been
estimated. The values by Bamualim and Kartiarso show that about 10 percent of
NEm requirements are required per hour of typical work for draft animals. This value
is used as follows:
NEdraft (MJ/day) = 0.10 x NEm x hours of work per day (4)
D6-7
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• Pregnancy
Daily energy requirements for pregnancy are presented in NRC (1984). Integrating
these requirements over a 281-day gestation period yields the following equation:
NEpregnancy (MJ/281-day period) = 28 x calf birth weight in kg (5)
The following equation can be used to estimate the approximate calf birth weight as
a function of the cow's weight:10
Calf birth weight (kg) = 0.266 x (cow weight in kg)0'79 (6)
Manipulating equations 5 and 6, in conjunction with equation 1, shows that the NE
required for pregnancy is about 7.5 percent of NEm for the range of cow sizes
considered in this analysis. Therefore, a factor of 7.5 percent of NEm is added to
account for the energy required for pregnancy for the portion of cows giving birth
each year.
Based on these equations, each of the net energy components for each of the cattle categories can
be estimated from the data collected in Step 1: weight in kilograms; feeding situation; weight gain
per day in kilograms; milk production in kilograms of 4 percent fat-corrected milk; number of hours
of work performed per day; and portion that give birth.
These net energy requirements must be translated into gross energy intakes. Also, by
estimating the gross energy intake, the net energy estimates can be checked for reasonableness
against expected ranges of feed intake as a percentage of animal weight. To estimate gross energy
intake, the relationship between the net energy values and gross energy values of different feeds must
be considered. This relationship can be summarized briefly as follows:
Digestible Energy = Gross Energy - Fecal Losses
Metabolizable Energy = Digestible Energy - Urinary and Combustible Gas Losses
Net Energy = Metabolizable Energy - Heat Increment
Net Energy = Gross Energy - Fecal Losses - Urinary and Combustible Gas Losses
- Heat Increment
The quantitative relationship among these energy values varies among feed types. Additionally, the
values depend on how the feeds are prepared and fed, and the level at which they are fed. For
purposes of this method, simplified assumptions are used to derive a relationship between net energy
and digestible energy that is reasonably representative for the range of diets typically fed to cattle.
Gross energy intake is then estimated using this relationship and the digestibility data collected in
Step 1. .
Given the digestibility of the feed (defined in Step 1), a general relationship between
digestible energy and metabolizable energy can be used as follows (NRC, 1984):
10 This species-specific equation from Robbins and Robbins (1979) was adjusted to the mean cow and
calf weight of a typical beef breed of cattle. This adjustment increases the coefficient in the equation from
0.214 to 0.266.
D6-8
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Metabolizable Energy (ME) = 0.82 x Digestible Energy (DE) (7)
Equation 7 is a simplified relationship; larger (smaller) methane conversion rates would tend to
reduce (increase) the coefficient to values below (above) 0.82.
NRC (1984) presents separate quantitative relationships between metabolizable energy and
•net energy used for growth versus net energy'used for other functions. Using equation 7. the NRC
relationships can be re-arranged to quantify the ratio of NE to DE, as follows:
NE/DE = 1.123 - 4.092 x 10'3 x DE% + 1.126 x 10'5 x (DE%)2 - 25.4/DE% (S)
NEg/DE = 1.1.64 - 5.160 x 10'3 x DE% + 1.308 x 10'5 x (DE%)2 - 37.4/DE% (9)
where: -
NE/DE = the ratio of net energy consumed for maintenance, lactation, work'and
pregnancy to digestible energy consumed;
NE./DE = the ratio of net energy consumed for growth to digestible energy
consumed; and
DE% = digestible energy as percentage of gross energy, expressed in percent
(e.g., 65 percent).
Because the. NRC (1984) relationships were developed based on diets with relatively high
digestibilities (generally above 65 percent), they may not be appropriate for the relatively low
digestibility diets that are commonly found in tropical livestock systems. In particular, the non-linear
nature of the relationships could bias the estimates of feed intake upward for low-digestibility feeds.
An upward bias in feed intake would lead to an upward bias in emissions estimates.
Based on a review of other energy systems (e.g., ARC, 1980), a linear relationship between
digestible energy and net energy was derived for digestibilities below 65 percent as follows (see
Appendix C):
NE/DE = 0.298 + 0.00335 x DE% (10)
NEg/DE = -0.036 + 0.00535 x DE% (11)
Given the estimates for feed digestibility (from Step 1) and equations 8 through 11, the gross energy
intake (GE in MJ/day) can be estimated as follows:
GE = [(NEm+NEfeed+NEl+NEw+NEp) / {NE/DE} + (NEg / {NE^DE})] /(DE%AOO) (12)
where:
{NE/DE} is computed from equation 8 for digestibility greater than 65 percent and from
equation 10 for digestibility less than or equal to 65 percent;
{NEJDE} is computed from equation 9 for digestibility greater than 65 percent and from
equation 1 1 for digestibility less than or equal to 65 percent; and
DE% is digestibility in percent (e.g., 60 percent).
D6-9
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To check the estimate of daily gross energy intake from equation 12, the estimate can be converted
in daily intake in kilograms by dividing by 18.45 MJ/kg. This estimate of intake in kilograms should
generally be between 1.5 percent and 3.0 percent of the animal's weight.
Using equation 12, Gibbs and Johnson (1993) found that the intake estimates are consistent
with expected intakes as a percent of body weight and previously published values. For example, the
intake estimate for Indian cattle is the equivalent of about 10,000 MJ per year of metabolizable
energy (ME). Winrock (1978) estimates the average ME requirements for Indian cattle at 10,600
MJ per year. Similarly, the ME values implied for U.S. dairy and beef cows are 58,000 MJ and 31,000
MJ per year, respectively, which are similar to estimates of 62,000 MJ and 31,700 MJ derived in U.S.
EPA (1993). Consequently, for a diverse set of conditions, the intake estimates correspond to
reasonably expected ranges from previously published estimates.
To estimate the emissions factor for each cattle type, the feed intake is multiplied by the
methane conversion rate (from Step 1) as follows:
Emissions (kg/yr) = Intake (MJ/day) x Ym x 365 days / 55.65 MJ/kg of methane (13)
where Ym is the methane conversion rate expressed in decimal form (such as 0.06 for 6 percent).
The result of this step of the method is an emissions factor for each cattle type defined in Step 1.
Step 3: Total Emissions
To estimate total emissions the selected emission factors are multiplied by the associated
animal population and summed.
DATA SOURCES
Unpublished information is available from practitioners in individual states. Departments
within each state responsible for conducting agricultural research and that oversee the agriculture
sector should be consulted. State animal populations can be found in the Census of Agriculture,
Volume 1: Geographic Area Series, published by the Bureau of the Census. Also, the USDA can
produce state by state inventories on domesticated animal populations.
Data on feed characteristics have been compiled in NRC (1989), ARC (1980), and Jurgens
(1988). These, and^similar, sources may be consulted to evaluate the feed consumption of specific
categories of ruminant animals.
REFERENCES
AAC (Australian Agricultural Council) (1990), Feed Standards for Australian Livestock. Ruminants,
Commonwealth Scientific and Industrial Research Organization (CSIRO) Publications, East
Melbourne, Victoria, Australia.
ARC (Agriculture Research Council) (1980), The Nutrient Requirements of Ruminant Livestock,
Commonwealth Agricultural Bureaux, The Lavenham Press Ltd., the United Kingdom.
D6-10
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Baldwin, R.L., and M.J. Allison. 1983. Rumen metabolism. Journal of Animal Science 57:461-477.
Bamualim, A., and Kartiarso. 1985. "Nutrition of Draught Animals with Special Reference to
Indonesia," in Copland, J.W., ed. Draught Animal Power for Production, Australian Centre for
International Agricultural Research (ACIAR) Proceedings Series No. 10. ACIAR, Canberra.
A.C.T., Australia.
N
Blaxter, K.L., and J.L. Clapperton. 1965. "Prediction of the Amount of Methane Produced by
Ruminants," British Journal of Nutrition 19:511-522.
Bureau of Census. 1987. Census of Agriculture. United States Department of Commerce. U.S.
Government Printing Office. Washington, DC 20402.
/
Crutzen, P.J., I. Aselmann, and W. Seiler. 1986. "Methane Production by Domestic Animals, Wild
Ruminants, Other Herbivorous Fauna, and Humans," Tellus 38B:271-284
Ensminger, M.E. 1983. Animal Science. The Interstate Printers and Publishers. Dnasville, IL.
FAO (Food and Agriculture Organization). 1990. Yearbook - Production Vol. 44, FAO, United
Nations, Rome, Italy.
Gibbs, M.J. and D.E. Johnson. 1993. "Livestock Emissions," in International Methane Emissions,
U.S. Environmental Protection Agency, Climate Change Division, Washington, D.C.
Graham, N.M. 1985. "Relevance of the British Metabolizable Energy System to the Feeding of
Draught Animals," in Copland, J.W., ed. Draught Animal Power for Production, ACIAR
(Australian Centre for International Agricultural Research) Proceedings Series No. 10.
ACIAR, Canberra, A.C.T., Australia.
Hashimoto, A. and J. Steed. 1993. Methane Emissions from Typical U.S. Livestock Manure
Management Systems, Draft report prepared for ICF Incorporated under contract to the
Global Change Division of the Office of Air and Radiation, U.S. Environmental Protection
Agency, Washington, D.C.
IAEA (International Atomic Energy Agency). 1992. Manual on Measurement of Methane and
Nitrous Oxide Emissions from Agriculture. International Atomic Energy Agency Publication
IAEA-TECDOC-674, Vienna, Austria.
Ibrahim, M.N.M. 1985. "Nutritional Status of Draught Animals in Sri Lanka," in Copland, J.W., ed.
Draught Animal Power for Production, ACIAR (Australian Centre for International
Agricultural Research) Proceedings Series No. 10. ACIAR, Canberra, A.C.T., Australia.
IPCC. 1994. IPCC Guidelines for National Greenhouse Gas Inventories, 3 volumes: Vol. 1, Reporting
Instructions; Vol. 2, Workbook; Vol. 3, Draft Reference Manual. Intergovernmental Panel on
Climate Change, Organization for Economic Co-Operation and Development. Paris, France.
Johnson, K.A., H. Westberg, M. Hyler, and B. Lamb. 1993. Cattle Methane Measurement Techniques
Workshop, August 9-12, 1993, Washington State University, Pullman, WA, sponsored by the
D6-11
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Global Change Division, Office of Air and Radiation, U.S. Environmental-Protection Agency,
Washington, D.C.
Jurgens, M.H. 1988. Animal Feeding and Nutrition, Sixth Edition, Kendall/Hunt Publishing
Company, Dubuque, Iowa.
Lawrence, P.R. 1985. "A Review of Nutrient Requirements of Draught Oxen," in Copland, J. W., ed.
Draught Animal Power for Production, ACIAR (Australian Centre for International
Agricultural Research) Proceedings Series No. 10. ACIAR, Canberra, A.C.T., Australia.
Lichtman, R. J. 1983. Biogas Systems in India, Volunteers In Technical Assistance (VITA),
Arlington, Virginia.
NRC (National Research Council). 1984. Nutrient Requirements of Beef Cattle, National Academy
Press, Washington, D.C.
NRC. 1989., Nutrient Requirements of Dairy Cattle, National Academy Press, Washington, D.C.
OECD (Organization for Economic Cooperation and Development). 1991. Estimation of Greenhouse
Gas Emissions and Sinks: Final Report from the OECD Experts Meeting, 18-21 February 1991,
OECD, Paris, France.
Robbins, C.T., and D.L. Robbins. 1979. "Fetal and Neonatal Growth Patterns and Maternal
Reproductive Effort in Ungulates and Sub-Ungulates," Amer. Naturalist 114:101.
Safley, L.M., M.E. Casada, J.W. Woodbury, and K.F. Roos. 1992. Global Methane Emissions from
Livestock and Poultry Manure. U.S. Environmental Protection Agency, Global Change
Division. Washington, D.C., February 1992, EPA/400/1091/048.
Safley, L.M. Jr., and P. W. Westerman. 1992. "Performance of a Low Temperature Lagoon Digester,"
Bioresource Technology 41:167-175.
Stuckey, D.C. 1984. "Biogas: A Global Perspective," in El-Halwagi, M.M., ed. Biogas Technology,
Transfer and Diffusion, Elsevier, New York, pages 18-44.
U.S. EPA (U.S. Environmental Protection Agency). 1993. Anthropogenic Methane Emissions in the
United States, Global Change Division, Office of Air and Radiation, Washington, D.C.
Winrock (Winrock International). 1978. The Role of Ruminants in Support of Man, Winrock
International, Morrilton, Arkansas.
Woodbury, J.W. and A. Hashimoto. 1993. "Methane Emissions from Livestock Manure," in
International Methane Emissions, U.S. Environmental Protection Agency, Climate Change
Division, Washington, D.C. (in press).
Yancun, C, H. Cong, and Liang Pusen. 1985. "Development of a New Energy Village - Xinbu,
China," in El Mahgary, Y., and A.K. Biswas, eds. Integrated Rural Energy Planning,
Butterworths Publishing, Guildsford, England, pages 99-108.
D6-12-
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DISCUSSION 7
METHANE EMISSIONS FROM
MANURE MANAGEMENT
OVERVIEW
Manure decomposition is a process in which microorganisms derive energy and material for
cellular growth by metabolizing organic material in the manure. When decomposition occurs without
oxygen present (anaerobically), methane is an end-product of the process. This section will describe
the fundamentals of anaerobic decomposition; the methane producing capacity of livestock manure;
and the factors that influence methane production from livestock manure.1
The Fundamentals of Anaerobic Decomposition
Livestock manure is primarily composed of organic material and water. Under anaerobic
conditions, the organic material is decomposed by anaerobic and facultative (living in the presence
or absence of oxygen) bacteria. The end products of anaerobic decomposition are methane, carbon
dioxide, and stabilized organic material.
The anaerobic decomposition process can be represented in three stages: hydrolytic; acid
forming; and methanogenic. Carbohydrates decomposition can be illustrated as follows:2
• Stage 1: Hydrolvtic. In the first stage, complex organic materials in the manure
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 amount
and rate of breakdown can vary substantially and depend on the enzymes present, the
characteristics of the manure, 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, metabolic hydrogen and
carbon dioxide are produced. With acetic acid as an end product, the breakdown of
a simple sugar molecule (glucose) in Stage 2 can be represented as:
C6H12O6 + 2H2O —> 2CH3COOH + 2CO2 + 4H2
glucose + water acetic acid carbon .dioxide metabolic
hydrogen
1 Background information on animal wastes is taken from Safley et al. (1992).
2 This discussion focuses on the decomposition of carbohydrates because carbohydrate decomposition
accounts for the majority of the methane produced from livestock manure 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 manure is approximately 40 percent carbohydrate, 15 to 20 percent protein, and up to 10
to 20 percent fat with the remainder composed of other material (Hrubant, Rhodes, and Sloneker, 1978).
D7-1
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• Stage 3: Methanogenic. Methane producing bacteria (methanogens) convert the
simple organic acids, ^metabolic hydrogen, and carbon dioxide from Stage 2 into
methane and carbon dioxide. Methanogens are strict anaerobes and cannot tolerate
the presence of molecular oxygen. Methanogens multiply slowly and are very
sensitive to temperature, pH, and substrate composition. With acetic acid, metabolic
hydrogen and carbon dioxide as substrate, the reactions producing methane can be
expressed as:
2CH3COOH — > 2CH4 + 2CO2
acetic acid —> methane + carbon dioxide
4H2 + CO, —> CH4 + 2H,0
metabolic + carbon dioxide — > methane + water
hydrogen
Methane Producing Capacity of Livestock Manure
In general, livestock manure is highly conducive to methane generation due to its high organic
content and the presence of useful bacteria. However, the specific methane producing capacity of
livestock manure depends on the specific composition of the manure which in turn depends on the
composition and digestibility of the animal diet. The greater the energy content and digestibility of
the feed, the greater the methane producing capacity of the resulting manure. For example, feedlot
cattle eating a high energy grain diet produce a highly biodegradable manure with a high methane
producing capacity. Range cattle eating a low energy forage diet produce a less biodegradable
manure with only half the methane producing capacity of feedlot cattle manure.
/
In principal, the ultimate methane producing capacity of a quantity of manure 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 livestock manure is
generally expressed in terms of the quantity of methane that can be produced per kilogram of volatile
solids (VS) in the manure.3 This quantity is commonly referred to as B0 with units of cubic feet of
methane (CH4) per pound VS (ft3 CH4 / Ib VS). Representative B0 values for a number of livestock
manure types are presented later in this discussion.
Factors Influencing Methane Production
While a particular quantity of manure may have a certain potential to produce methane based
on its volatile solids content, the management of the livestock manure and the environment in which
the manure is managed are the major factors influencing the amount of methane actually produced
during manure decomposition.
The characteristics of the manure management systems and environmental conditions can be
expressed in a methane conversion factor (MCF) which represents the extent to which the potential
Volatile solids (VS) are defined as the organic fraction of the total solids (TS) in manure that will
oxidize and be driven off as gas at a temperature of 1,112°F. Total solids (TS) are defined as the material that
remains after evaporation of water at a temperature between 217° and 221°C.
D7-2
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for emitting methane is actually realized. Manure systems and climate conditions that promote
methane production will have an MCF near 1 and manure systems and climate conditions that do not
promote methane production will have-an MCF near 0. The primary characteristics determining the
MCF are: ,
Livestock Manure Management System Factors
• Contact with Oxygen. Under aerobic conditions where oxygen is in contact with the
manure, there is no potential for methane production.
• Water 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 can be produced in a range between 6.6 and 8.0.
• 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.
Climate Factors
• Temperature. Methanogenesis in livestock manure has been observed between 39° F
and 167° F. Temperature is one of the major factors affecting the growth of the
bacteria responsible for methane formation (Chawla, 1986). The rate of methane
production generally increases with rising temperature.
• Moisture. For non-liquid based manure systems, the moisture content of the manure
is determined by rainfall and humidity. The moisture content of the manure will
determine the rate of bacterial growth and decomposition. Moist conditions promote
methane production.
These factors can be combined into the following expression for estimating realized methane
emissions from livestock manure:
Realized Emissions = B0 • MCF (7.1)
where B0 = the maximum methane producing capacity of the manure determined
by animal type and diet (ft3 CH4 / Ib VS).
MCF = Methane Conversion Factor (MCF) that represents the extent to
which the B0 is realized for a given livestock manure management
system and environmental conditions. Note: 0 <. MCF s 1.
D7-3
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DESCRIPTION OF WORKBOOK METHOD
/
Methane emissions from livestock manure depend on the type of manure, the characteristics
of the manure management system, and the climatic conditions in which the manure decomposes.
While limited data are available on which to base emission estimates, a study recently prepared for
the U.S. EPA provides an adequate basis for making initial estimates (Safley et al., 1992). Additional
analysis is ongoing to provide additional data for estimating these emissions.
Based on the Safley et al. (1992) approach, emission estimates are developed by:
• identifying the manure management systems in use in the United States and their
methane producing potential;
• estimating the amount and type of manure managed by each system; and
• estimating emissions by multiplying the amount of manure managed in each system
by the estimated emission rate per unit of manure in the system.
Information can be obtained from a variety of sources, including:
• the U.S. Census of Agriculture;
• USDA agriculture statistics;
• livestock manure management experts throughout the U.S.; and
• scientific literature.
Total emissions will equal the quantity of volatile solids managed in each system times
emissions per kilogram of volatile solids (VS) for that system. Safley et al. (1992) used the following
procedure to estimate total emissions:
• Collect data on: (1) the populations of the major animal types in each state of the
U.S. (N); and (2) their typical animal mass (TAM).
• Collect information on the characteristics of the manure produced by each of the
animal populations in each state, including: (1) the amount of volatile solids (VS)
produced; and (2) the methane producing capacity (5Q) of the manure. The amount
of volatile solids produced depends on the number of animals in the state and their
mass:
VSik = Nik • TAMi • vsi W
where:
Wj k = number of animals of type / in state k.
TAM{ = typical animal mass in pounds of animal i; and
vSj = the average annual volatile solids production per unit of
animal mass (pounds per pound) for animal i.
D7-4
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Identify the livestock manure management systems used in each state and the
percentage of manure managed by each (WS%).
Estimate the methane producing potential (MCF) of each manure management
system in each state based on the average monthly temperature in the state.
Estimate methane emissions for each animal and manure system in each state (TM)
by multiplying the amount of volatile solids (VS) produced by the methane producing
capacity of the manure (B0) times the methane producing potential (MCF) of the
manure system in each state.
where:
KSj k = total volatile solids produced (Ibs/yr) for animal i in
state k;
BQ j = maximum methane producing capacity per pound of
VS for animal i;
MCF: k = methane conversion factor for each manure system/ in
state A:;
WS%-{ j k = percent of animal /'s manure managed in manure
system j in state k.
Estimate total annual methane emissions (TM) for animal / as the sum of annual
emissions over all applicable manure management systems j:
(7.4)
Estimate total annual methane emissions from all animals (TM) as the sum over all
animal types / as follows:
TM = £ TM . • . . (7.5)
These equations show that methane emissions are driven by four main factors: the quantity
of VS produced; the BQ values for the manure; the MCFs for the manure management systems; and
the portion of the manure handled by each manure management system (WS%). The following
sections describe the data collected to implement this method.
Volatile Solids Production (VS]
Methane emissions from livestock manure are directly related to the amount of volatile solids
(VS) produced. The data required to estimate total VS production are the number of animals (/Vj),
average size (TAM^, and average VS production per unit of animal size (vjj).
In the U.S., considerable data are available to allow the populations of animals to be analyzed
by: species, production system, and (for cattle) age. Six main categories of animals were defined:
D7-5
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feedlot beef cattle;4 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. Table D7-1 lists the data obtained for the 20 subcategories.
Maximum Methane Producing Capacity fB0)
The maximum amount of methane that.can be produced per pound of VS (B0) varies by
animal type and diet. Measured B0 values for beef manure range from 2.72 cubic feet of methane
per pound of VS (ft3/lb-VS) for a corn silage diet to 5.29 ft3Ab-VS for a corn-based high energy diet
that is typical of feedlots. Table D7-2 summarizes these values.
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). Table D7-3 lists the values selected for
the analysis.
Manure Management Systems Definitions
A variety of manure management practices are in use throughout the U.S. The following is
a brief description of the major livestock manure management systems in use.
PASTURE/RANGE
DAILY SPREAD
SOLID STORAGE
DRYLOT
DEEP PIT STACKS
Animals that are grazing on pasture are not on any true manure handling
system. The manure from these animals is allowed to lie as is, and is not
managed 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 stored until applied to fields on a regular basis.
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 manure 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.
4 Feedlot cattle are animals fed a ration of grain, silage, hay and protein supplements for the slaughter
market (ASB, 1991).
D7-6
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Table D7-1
U.S. Animal Populations, Average Size, and VS Production
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'VB
Nj
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
Typical
Animal
Mass
(TAMj)c
Ibs
915
915
1102
397
794
794
1102
1587
903
1345
101
399
3.5
1.5
3.1
7.5
154.
141
661
' 992
Volatile
Solids (vsO
Ibs VS/lb
animal mass/yr
2.6.
2.6
2.6
2.6
. 2.6
2.6
2.6
2.6
3.65
3'.65
3.1
3.1
4.4
6.2
6.75
\ - 3.32
3.36
3.48
3.65
3.65
A Population data for animals except goats and horses from ASB (1989a-f). 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/turkey populations estimated yearly based on number of flocks per year (North 1978;
Carter 1989).
c Source: Taiganides and Stroshine (1971).
D Source: ASAE ( 1988).
D7-7
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Table D7-2
Maximum Methane Producing Capacity for U.S. Livestock Manure
Animal
Type
Beef
Beef
Beef
Beef
Beef
Dairy
Dairy
Dairy
Dairy
Horse
Poultry
Poultry
Poultry
Poultry
Swine
Swine
Swine
Swine
Swine
Swine
Swine
Swine
Diet
7% corn silage, 87.6% corn
Corn-based high energy
91.5% corn silage, 0% corn
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
(ft3 CH4°/lb-VS)
4.65
5.29
2.72
3.68
5.29
3.84
2.72
2.24
1.60
5.29
6.25
5.77
3.84
3.84
5.77
7.69
5.13
8.33
7.69
7.53
7.05
7.21
Reference
Hashimoto et al. (1981)
Hashimoto et al. (1981)
Hashimoto et al. (1981)
Hill (1984)
Chen, et al. (1980)
Morris (1976)
Bryant et al. (1976)
Hill (1984)
Chen, et al. (1988)
Ghosh (1984)
Hill (1982)
Hill (1984)
Webb & Hawkes (1985)
Hawkes & Young (1980)
Summers & Bousfield (1980)
Hashimoto (1984)
Hill (1984)
Kroeker et al. ( 1984)
Stevens & Schulte (1979)
Chen (1983)
lannotti et al. (1979)
Fischer et al. (1975)
Table D7-3
Maximum Methane Producing Capacity Adopted For U.S. Estimates
Cattle:
Swine:
Poultry
Sheep:
Goats:
Horses
Animal Type, Category
Beef in Feedlots
Beef Not in
Feedlots
Dairy
Breeder
Market
: Layers
Broilers
Turkeys
In Feedlots
Not in Feedlots
and Mules:
Maximum Potential
Emissions (B0)
5.29
2.72
3.84
5.77
7.53
5.45
. 4.81
4.81
5.77
3.04
2.72
5.29.
Reference
Hashimoto et al. (1981)
Hashimoto et ai. (1981)
Morris (1976)
Summers & Bousfield (1980)
Chen (1983)
Hill (1982 & 1984)
^Safley et al. (1992)
Safley et al. (1992)
Safley et al. (1992)
Safley et al. (1992)
Safley et al. (1992)
Ghosh (1984)
D7-8
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LITTER
PADDOCK
LIQUID/SLURRY
ANAEROBIC LAGOON
Broilers and young turkeys may be grown on beds of litter such as
shavings, sawdust, or peanut hulls, and the manure/litter pack is removed
periodically 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 drylot.
These systems are generally characterized by large concrete lined tanks
built into the ground. Manure 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 manure to treatment lagoons that
are usually greater than six feet deep. The manure resides in the lagoon
for periods ranging from 30 days to over 200 days depending on the
lagoon 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 manure providing fertilizer value.
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.
Methane Conversion Factors (MCFsl
The extent to which the maximum methane producing capacity (B0) is realized for a given
livestock manure management system and environmental conditions is defined as the Methane
Conversion Factor (MCF) for the manure system. For example, a manure system that produces no
methane emissions will have an MCF of 0. A manure system that achieves full potential methane
emissions would have an MCF of 1.
To assess the MCF values for a wide range of livestock manure management systems, two
broad classifications of livestock manure handling systems can be defined based on the total solids
content of the manure:
• Solid systems have a total solids content greater than about 20 percent.
• Liquid/slurry systems have a total solids content less than 20 percent.
Manure 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. Alternatively, water may be added to lower the total solids to allow
for liquid transport and handling.
PIT STORAGE
D7-9
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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. Solid systems promote conditions that limit methane
production even if anaerobic conditions may exist.
Safley et al. (1992) reviewed the literature to investigate the appropriate range of MCF values
for U.S. manure management systems. Although some data were available, MCF values were
estimated for many systems. To improve the MCF estimates, the U.S. Environmental Protection
Agency is sponsoring analysis to better estimate the MCF for several key livestock manure systems.
Preliminary findings from this analysis indicate that:
• The estimated MCF value of dry in situ pasture, range, paddock, and solid storage
manure is 1 to 2 percent. The estimated MCF for drylot manure is 1 to 5 percent.
However, the analysis has not yet considered the effect of moisture or emissions that
may result when the manure is washed into streams, rivers, and lakes or incorporated
into the soil (Hashimoto 1992).
• The MCF value liquid/slurry and pit storage varies greatly by temperature and is on
:he order of 10 percent at SOT to 65 percent at 86°F (Hashimoto 1992).
• The MCF value for daily spread is less than 1 percent (Hashimoto 1992).
• The MCF value for anaerobic lagoons is on the order of 90 percent. This estimate
is based on continuous methane measurements taken over a two and one-half year
period at a North Carolina dairy farm (Safley 1991).
The MCF values for each system are listed in Table D7-4. The MCF for an individual state will
depend on the average monthly temperature and are calculated by:
• estimating the average monthly temperature in each climate division;5
• estimating the MCF value for each month using the average temperature data and the
MCF values listed in Table D7-4;
• estimating the annual MCF by averaging the monthly division estimates; and
• estimating the state-wide MCF by weighting the average MCF for each division by the
fraction of the state's dairy population represented in each division.6
Table D7-5 summarizes the MCF estimates for each state.
5 The average temperature in each climate division of each state was calculated for the normal period of
1951 to 1980 using the National Climatic Data Center (NCDC) time-bias corrected Historical Climatological
Series Divisional Data (NCDC 1991).
6 The dairy population in each climate division were estimated using the dairy population in each county
(Bureau of the Census 1987) and detailed county and climate division maps (NCDC 1991). Using the dairy
population as a weighting factor may slightly over or underestimate the MCFs for other livestock populations.
D7-10
-------
Table D7-4
Methane Conversion Factors for U.S. Livestock Manure Systems
MCFs based on
laboratory measurement
Pasture, Range, PaddocksA
Liquid/Slurry^
Pit Storage < 30 daysA
Pit Storage > 30 daysA
Drylot8
Solid StorageA
Daily SpreadA
MCF measured by
long term field monitoring
MCF at 30°C
2%
65 %
33 %
65 %
5 %.
2%'
1 %
MCF at 20°C
1.5 %
35 %
18%
35 %
1.5%
1.5 %
0.5 %
MCF at 10°C
1 %
10 %
5%
10 %
1 %
1 %
0.1 %
Average Annual MCF
s~>
Anaerobic Lagoons 90 %
MCFs estimated by Safley et al.
Average Annual MCF
Litter0 , 10 %
Deep Pit Stacking0 . 5 %
A Hashimoto (1992)
B Based on Hashimoto (1992).
C Safley et al. (1992) and Safley and Westerman (1992).
D Safley et al. (1992).
D7-11
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Table D7-S
Methane Conversion Factors for U.S.
State
Alabama
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi .
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Other Systems:
Pasture, •
Range &
Paddocks
1.4%
1.4%
1.3%
1.2%
0.9%
0.9%
1.2%
1.5%
1.4%
0.8%
1.1%
1.0%
' 0.9%
1.1%
1.2%
1.4%
0.8%
1.1%
0.9% '
0.8%
0.8%
1.4%
1.1%
0.7%
1.0%
.1.2%
0.8%
1.0%
1.2%
0.9%
1.3%
0.7%
1.0%
• 1.4%
1.1%
0.9%
1.0%
1.3%
0.8%
1.3%
1.4%
0.9%
0.8%
1.2%
1.0%
1.2%
0.8%
0.8%
Pit Storage for less than 30 days
Liquid/Slurry. Pit Storage for more than 30 days
Drylot
1.9%
1.9%
1.8%
1.4%
1.0%
1.0%
1.4%
2.4%
1.8%
0.8%
1.3%
1.2%
1.1%
1.5%
1.5%
2.1%
0.8%
1.2%
1.0%
0.9%
0.8%
1.9%
1.4%
0.8%
1.1%
1.4%
0.8%
1.1%
1.3%
0.9%
1.5%
0.7%
1.1%
1.9%
1.1%
1.0%
1.1%
1.7%
0.9%
1.6%
2.1%
1.0%
0.8%
1.4%
1.0%
1.3%
• 0.8%
0.8%
is assumed to
is assumed to
Livestock Manure Systems
•Solid
Storage
1.4%
1.4%
1.3%
1.2%
0.9%
0.9%
1.2%
1.5%
1.4%.
0.8%
1.1%
1.0%
0.9%
1.1%
1.2%
1.4%
0.8%
1.1%
0.9%
0.8%
0.8%
1.4%
1.1%
0.7%
1.0%
1.2% '
0.8%
1.0%
1.2%
0.9%
1.3%
0.7%
1.0%
1.4%
1.1%
0.9%
1.0%
1.3%
0.8%
1.3%
1.4%
0.9%
0.8%
1.2%
1.0%
1.2%
0.8%
0.8%
have an MCF equal
have an MCF equal
lagoons are assumed to have an MCF of 90%; litter and deep pit stacks an MCF of
Daily
Spread .
0.4%
0.4%
0.4%
0.3%
0.2%
0.2%
0.3%
0.6%
. 0.4%
0.2%
0.3%
0.3%
0.2%
.0.3%
0.3%
0.5%
0.2%
0.3%
0.2%
0.2%
0.2%
0.4%
0.3%
. 0.2%
0.2%
0.3%
0.2%
0.3%
0.3%
0.2%
0.3%
0.2%
0.2%
0.4%
0.2%
0.2%
0.2%
0.4%
0.2%
0.3%
0.5%
0.2%
0.2%
0.3%
0.2%
0.3%
0.2%
0.2%
to 50% of the
to liquid/slurry
10%. .
Liquid/
Slurry
29.0%
28.9%
27.6%
21.9%
18.2%
18.5%
22.6%
38.6%
29.0%
15.5%
22.8%
21.5%
20.7%
24.7%
23.8%
32.5%
15.5%
21.0%
18.1%
17.0%
18.0%
29.3%
24.1%
15.8%
20.8%
22.1%
16.3%
20.6%
21.3%
18.1%
24.5%
16.8%
20.2%
28.7%
16.2%
18.7%
18.7%
27.3%
19.l?'o
24.8%
31.7%
17.4%
16.6%
22.5%
15.5%
21.4%
17.0%
15.9%.
MCF for
Anaerobic
D7-12
-------
Livestock Manure Management System Usage (WS%)
Livestock manure management system usage in the United States was determined by obtaining
information from Extension Service personnel in each state. The U.S. was divided into eleven
geographic regions based on similarities of climate and livestock productioaas shown in Table D7-6.
For states that did not provide information, the regional average manure system usage was assumed.
Some states did not give data for all animal types and a regional average was used in these cases.
Table D7-7 lists the percentage of manure managed by the major systems in the United
States. The important manure management characteristics in the U.S. are:
• ' Approximately one-third of dairy manure is managed as a liquid and approximately
one-third is spread directly to cropland.
• Seventy-five percent of swine manure is managed as a liquid.
• Poultry manure is primarily managed by deep pit stacking or litter and is included in
"other systems" in Table D7-7.
DATA SOURCES
Many states may have their own agricultural census that includes data on animal populations
and production levels. Animal population data can be found from a variety of other sources,
including the U.S. Census of Agriculture, USDA agriculture statistics, and from livestock manure
management experts throughout the U.S. Safley et al. (1992) include animal populations and also
estimate CH^ emitted from their wastes in their report.
UNCERTAINTIES
The method described above for estimating methane emissions from animal manure is based
on sound scientific data and experimental evidence. To the extent possible, emissions should be
'estimated with as much information as possible about the conditions under which animal manure is
managed. This is particularly important when manure is managed under anaerobic conditions, such
as lagoons or other liquid/slurry systems.
The estimates and assumptions used by Safley et al. (1992) are instructive for identifying the
potential magnitude of emissions and the relative importance of various animals and manure
management systems. However, to the extent possible, information that is specific to the individual
state should be used because manure management systems and practices may vary in different states.
The weakest link in the method presented here is the estimates of the methane conversion
factors (MCFs) for the individual management systems. Very few field measurements are available
upon which to base these estimates, particularly for "dry" management systems such as dry lots,
pastures, and paddocks. The MCFs for the "wet" management systems such as lagoons and slurry
storage have a much stronger foundation. The inaccuracy in the emissions estimates due to this lack
of data cannot be quantified. Emissions estimates can be improved significantly once comprehensive
field measurements are performed.
This discussion has focused only on emissions of methane from animal manure. It has been
nentioned, however, that animal waste decomposition also has the potential to produce nitrous oxide.
D7-13
-------
At this time no information is available on the potential for N2O emissions: this should be
investigated in the future.
Table D7-6
Regions of the U.S. for Manure Management Characterization
Plains
South
South West
Mid West
North East *Connecticut, Maine, Massachusetts, *New Hampshire, New Jersey, *New
York, Pennsylvania, Rhode Island, Vermont.
South East *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.
*Illinois, *Indiana, Michigan, *Ohio, *Wisconsin, *Iowa, *Minnesota,
* Missouri.
North West *Idaho, *Oregon, *Washington
Far West * Arizona, Nevada, *Utah
Pacific West * California
North Pacific *Alaska
Pacific
Islands
"Hawaii
States that have supplied estimates of their percent use of manure management.
D7-14
-------
Table D7-7
Livestock Manure System Usage for the U
Animal '
Non-Dairy Cattle
Dairy
Poultry5
Sheep
Swine
Other Animalsc
Anaerobi
c
Lagoons
0%
10%
5%
0%
25%
0%
Liquid/Slurr
y and Pit
Storage
1%
23%
4%
0%
50%
0%
Daily
Spread
0%
37%
0%
0%
0%
0%
A Includes liquid/slurry storage and pit storage.
B Includes chickens, turkeys, and ducks.
C Includes goats, horses, mules, and donkeys.
Solid
Storage
&
Drylot
14%
23%
0%
2%
18%
0%
.S.
Pasture,
Range
&
Paddock
84%
0%
1%
88%
0%
92%
•
Litter,
Deep Pit
Stacks and
Other
1%
7%
90%
10%
6%
8%
Totals may not add due to rounding.
Source: Safley et aj. (1992).
REFERENCES
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ASAE (American Society of Agricultural Engineers). 1988. Manure Production and
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ASB (Agriculture Statistics Board). 1991. Cattle on Feed. Released: October 22, 1991.
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ASB. 1989a. Cattle. Released: February 8, 1989. Agricultural Statistics Board. ERS-NASS,
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ERS-NASS, USDA, P.O. Box 1608, Rockville, MD 20850. 14 pp.
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D7-15
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ASB. I989f. Sheep and Coats. Released: February 8, 1989. Agricultural Statistics Board.
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(ed.). Seminar on Microbial Energy Conversion. E. Goltz KG. Gottingen, Germany.
Bureau of Census, 1987. Census of Agriculture. United States Department of Commerce. U.S.
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Carter, T. A. 1989. Personal communication with Dr. Thomas A. Carter. Extension Professor of
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Chawla, O.P. 1986. Advances in Biogas Technology. Indian Council of Agricultural Research: New
Delhi.
Chen, T. H., D. L. Day, and M. P. Steinberg. 1988. Methane production from fresh versus dry
dairy manure. Biological Wastes. 24:297-306.
Chen, Y. R. 1983. Kinetic analysis of anaerobic digestion of pig manure and its implications.
Agricultural Wastes. 8:65-81.
Chen, Y.R., V.H. Varel, and A.G. Hashimoto. 1980. "Effect of Temperature on Methane
Fermentation Kinetics of Beef-Cattle Maure," Biotechnology and Bioengineering
Symposium. 10:325-339.
Fischer, J. R., D. M. Seivers, and D. C. Fulhage. 1975. Anaerobic digestion in swine wastes, pp.
307-316. In: W. J. Jewell (ed.). Energy, Agriculture and Waste Management. Ann Arbor
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Ghosh, S. 1984. Methane production from farm waste, pp. 372-380. In: M. M. El-Halwagi
(ed.). Biogas Technology, Transfer and Diffusion. Elsevier. New York.
Hashimoto, A. G., V. H. Varel, and Y. R. Chen. 1981. Ultimate methane yield from beef cattle
manure; effect of temperature, ration constituents, antibiotics and manure age. Agricultural
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Hashimoto, A. G. 1984. Methane from swine manure: effect of temperature and influent
substrate composition on kinetic parameter (k). Agricultural Wastes. 9:299-308.
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Department Chairman. Bioresource Engineering Department. Oregon State University.
Corvallis, OR. July 1992.
Hawkes, F. R. and B. V. Young. 1980. Design and operation of laboratory- scale anaerobic
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Hawkes, F. R. and B. V. Young, 1980. Design and operation of laboratory-scale anaerobic
digesters: operating experience with poultry litter. Agricultural Wastes. 2:119-133.
D7-16
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Hill, D. T. 1982. Design of digestion systems for maximum methane production. Transactions of
theASAE. 25(1):226-230.
Hill, D. T. 1984. Methane productivity of the major animal types. Transactions of the ASAE.
27(2):530-540.
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Wastes: A Chemical and Microbial Profile," SEA-NC-59. Northern Regional Research
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Microbiology. 20(49):519-520. ,
Jain, M. K.., R. Singh, and P. Tauro. 1981. Anaerobic digestion of cattle and sheep waste.
Agricultural Wastes. 3:65-73.
Kroeker, E. J., D. D. Schulte, A. B. Sparling, and J. T. Chieng. 1984. Anaerobic treatment
process stability. Journal of the Water Pollution Control Federation. 51:718-727.
Morris, G. R. 1976. Anaerobic fermentation of animal wastes: a kinetic and empirical design
fermentation. M. S. Thesis. Cornell University.
NCDC (National Climatic Data Center) 1991. Historical Climatological Series Divisional Data.
National Oceanic and Atmospheric Administration. Ashville, NC.
North, M. O. 1978. Commercial Chicken Production Manual. AVI. Westport, Connecticut.
Safley, L.M. 1991. Personal communication with Dr. Lawson Safley. Professor of Biological and
Agricultural Engineering. North Carolina State University. Raleigh, North Carolina,
January 1991. -
Safley, L.M., M.E. Casada, J.W. Woodbury, and K.F. Roos (1992). "Global Methane Emissions
from Livestock and Poultry Manure." EPA/400/1091/048. U.S. Environmental Protection
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Safley, L.M., Jr. and P.W. Westerman 1992. "Performance of a Low Temperature Lagoon
Digester." Bioresource Technology. 41:167-175.
Stevens, M. A. and D. D. Schulte. 1979. Low temperature digestion of swine manure. Journal of
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Summers, R. and S. Bousfield. 1980. A detailed study of piggery-waste anaerobic digestion.
Agricultural Wastes. 2:61-78.
Taiganides, E. P. 1987. Animal waste management and wastewater treatment, pp. 91-153, In: D.
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D7-18
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DISCUSSIONS
METHANE EMISSIONS FROM
FLOODED RICE FIELDS
OVERVIEW
Most of the world's rice, and all of the rice in the U.S., is grown on flooded fields. When
fields are flooded, aerobic decomposition of organic material gradually depletes the oxygen present
in the soils and floodwater, and anaerobic conditions in the soils develop. Methane is produced
through anaerobic decomposition of soil organic matter by methanogenic bacteria. However, not all
of the methane that is produced is released into the atmosphere. As much as 60 to 80 percent of
the produced methane is oxidized by aerobic methanotrophic bacteria in the soils (Holzapfel-Pschorn
et al., 1985; Sass et al., 1990). Some of the methane is also leached away as dissolved methane in
floodwater that percolates from the field. The remaining non-oxidized methane is transported from
the submerged soil to the atmosphere primarily by diffusive transport through the rice plants. Some
methane also escapes from the soil via diffusion and bubbling through the floodwaters. Figure D8-1
graphically depicts the process of CH4 production and its emissions.
The water management system under which rice is grown' is one of the most important factors
affecting methane emissions. Upland rice fields are not flooded, and therefore are not believed to
produce methane. In deepwater rice fields (i.e., fields with flooding depths' greater than
approximately 3.3 feet), the lower stems and roots of the rice plants are dead, thereby effectively
blocking the primary CH4 transport pathway to the atmosphere. Therefore, while deepwater rice
growing areas are believed to emit methane, the quantities released are likely to be significantly less
than areas with more shallow, typical flooding depths. Also, some flooded fields are drained
periodically during the growing season, either intentionally or accidentally. If water is drained and
soils are allowed to dry sufficiently, methane emissions decrease or stop entirely. This is due to soil
aeration, which not only causes existing soil methane to oxidize but also inhibits further methane
production in the soils.
Other factors that influence methane emissions from flooded rice fields include soil
temperature, soil type, fertilization practices, cultivar selection, and other cultivation practices (e.g..
tillage, seeding, and weeding practices). Many studies have found, for example, that methane
emissions increase as soil temperature increases. Several studies have indicated that some types of
nitrogen fertilizer inhibit methane generation, while organic fertilizers enhance methane emissions.
However, while it is generally acknowledged that these factors influence methane emissions, the
extent of the influence of these factors individually or in combination has not been well quantified.
Rice cultivation is a very small source of methane in the U.S. In 1990, methane emissions
from this source are estimated to have been approximately 0.65 to 4.5 MMTCE (U.S. EPA, 1994).
This represents less than 1 percent of total .U.S. methane emissions from all sources, and about 4
percent of U.S. methane emissions from agricultural sources. Seven states grow rice: Arkansas,
California, Florida, Louisiana, Mississippi, Missouri, and Texas.
D8-1
-------
Figure D8-1. Methane Emissions from Rice Cultivation
WATER-AIR
EXCHANGE
ANOXIC
SEDIMENTS
CH4-oxidation by
fnethanotrophic
bacteria
CH4
0Q° EBULLITION
production by
methanogenic
bacteria
Source: Schutz, et al. (1989)
D8-2
-------
DESCRIPTION OF WORKBOOK METHOD
Methane emissions from rice cultivation by state can be calculated using the methodology
presented in Equation D8-1. This method utilizes a low and a high daily emission factor, which are
multiplied by the harvested area flooded and the number of days of flooding during the growing
season. Agricultural statisticians in each of the seven states in the U.S. that produce rice can be
contacted to determine water m:":agement practices and flooding season lengths in e :h state. It
should be noted that all rice growing areas in the U.S. are continually flooded; none are either upland
or deepwater.
Equation D8-1. Method for Estimating Methane Emissions from Rice Cultivation
Low estimate (Ibs CH4) = (average # of . acre-days harvested annually) , x
(0.1955 Ibs CH4/acre/day)2
High estimate (Ibs CH4) = (average # of acre-days harvested annually) x
(1.035 Ibs CH4/acre/day)2
The default daily methane emission factors were taken from results of field studies performed
in California (Cicerone et al., 1983); Texas (Sass et al., 1990, 1991a, 1991b, 1992); and Louisiana
(Lindau et al., 1991; Lindau and Bollich, 1993). A range based on the endpoints of the emission
rates measured in these studies -- 0.1955 lbsCH4/acre/day to 1.035 Ibs CH4/acre/day - can be applied
to the areas and season lengths in each state.3 Since these measurements were taken in rice growing
areas of the U.S., they are representative of rice soil temperatures and water and fertilizer
management practices typical of the U.S.
The climatic conditions of southwest Louisiana, Texas, and Florida allow for a second or
"ratoon" rice crop in those areas. This second crop rice is produced from regrowth on the stubble
after the first crop has been harvested. Emission estimates for these states should include this
additional harvested area.
Rice fields for the second crop typically remain flooded for a shorter period of time than for
the first crop. Recent studies indicate, however, that the methane 'emission rate of the second crop
may be significantly higher than that of the first crop. The rice straw produced during the first
harvest has been shown to dramatically increase methane emissions during the ratoon cropping season
1 Technically, wild rice is considered a grain and not a rice variety, and therefore, is not included in these
calculations.
2 The number of acre-days harvested annually is equal to: (the number of acres within a certain cropping
length x the number of days in that cropping cycle) + (the number of acres with another cropping cycle length
x the number of days in that cropping cycle) + The workbook assumes that there is only one cropping
cycle for all states.
3 Two measurements from these studies were excluded when determining the emission coefficient range.
A low seasonal average flux of 0.1091 Ibs/acre/day in Sass et al. (1990) was excluded because this site
experienced a mid-season accidental drainage of floodwater, after. which methane emissions declined
substantially and did not recover for about two weeks. Also, the high seasonal average flux of 3.741
Ibs/acre/day in Lindau and Bollich (1993) was excluded since this emission rate is anomalously high, compared
to other flux measurements in the U.S., as well as in Europe and Asia (see IPCC, 1994).
D8-3
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(Lindau & Bollich, 1993). It is not clear to what extent the shorter season length and higher emission
rates offset each other. As scientific understanding improves, these emission estimates can be
adjusted to better reflect these variables. At this juncture, however, it is recommended that the
methane emission factors and flooding season lengths provided here for the primary rice crop be
applied to the ratoon crop as well (see Table D8-1 for average growing season lengths). .
To avoid unrepresentative results based upon fluctuations in economic or climatic conditions,
a three-year average (centered on 1990) for the area harvested in each state (USDA, 1991; USD A,
1993) should be used to estimate 1990 emissions. Also, since the number of days that the rice fields
remain permanently flooded varies considerably with planting system and cultivar type, a range for
the growing season lengths should be obtained (see Table D8-1 for default growing season lengths
by state).
Table D8-1. Growing Season Length for Rice-Producing States
State
Arkansas
California
Florida3
primary
ratoon
Louisiana3
primary
ratoon
Mississippi
Missouri
Texas3
primary
ratoon
TOTAL
Growing Season Length (days)
low
75
123
90
90
75
. 80
60
high
100
153
120
120
82
100
80
a These states have a second, or "ratoon", cropping cycle
which may have a shorter flooding season than the one
listed in the table.
UNCERTAINTIES
From field experiments it is apparent that methane emissions from rice fields are affected by
many factors. The factors clearly identified by these field experiments are: (1) water level and its
history in the growing season; (2) temperature; (3) fertilizer application; (4) soil type; (5) cultivar; and
(6) agricultural practices such as direct seeding or transplanting. Data show that higher temperature,
D8-4
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continuously flooded fields, some types of organic fertilizers, and certain cultivars lead to higher
emissions compared to rice grown at lower temperatures, with intermittent or managed irrigation in
which fields are not continuously inundated and where chemical fertilizers are used. At present.
however, there are insufficient data to incorporate most of these factors. Nonetheless, estimates can
be improved substantially by incorporating the current knowledge on the first two factors, namely
water levels and temperature. For some states, the effects of organic and mineral fertilizers can be
included.
Application of either the commercial nitrogen fertilizers ammonium sulfate or urea has
generally been found to reduce CH4 emissions, especially if the fertilizer is deeply incorporated into
the soil. This is believed to be due to suppression of CH4 production as a result of the addition of
sulfate or ammonium ions. Application of organic fertilizers (e.g., rice straw, composted rice straw.
animal wastes) whether or not in combination with mineral fertilizers, has been found, in most cases,
to enhance CH4 emissions.' The organic fertilizers provide an additional carbon source for the
production of CH4 in the paddy soil.
Water management practice also influence CH4 emissions since it is only through continuous
flooding that paddy soil remains sufficiently reduced for methane production to occur. Cultivar
selection is likely to affect CH4 emissions through two mechanisms: (1) root exudation and (2) gas
transport. Many studies have observed two or three maxima in CH4 emissions during the growing
season with the last one or two peaks occurring during the reproductive stage of the rice plants.
These latter emission peak(s) may be due to peaks in CH4 production that result from the plants
providing soil organic bacteria with organic root exudates or root litter at this time (Schtitz et al.,
1989). The degree of root exudation that occurs is believed to vary between cultivar types. The rice
plant also affects CH4 emissions through gas transport mechanisms. Downward oxygen transport
through the plant (and subsequent oxidation of CH4 in the rhizosphere) and upward methane
transport probably varies between cultivars. Gas transport mechanisms may also play a role in
controlling the latter emission peaks, e.g., methane transport may be more efficient during the
reproductive stage of rice plants than at other developmental stages (Sass et al., 1990).
States are encouraged to go beyond the basic method provided here and add as much detail
as scientifically justified based on laboratory and field experiments on how the above factors may
influence emissions. For example, states may wish to develop their own emission coefficients.
especially if wetland rice is a major crop.4 Also, where data are available on fertilizer type used,
states may wish to incorporate this information into their calculations.5 If additional detail is
included, then state emission inventories should be fully documented with the corresponding sources.
REFERENCES
Braatz, B.V., and K.B. Hogan, (eds.). 1991. Sustainable Rice Productivity and Methane Reduction
Research Plan. U.S. Environmental Protection Agency, Washington, D.C.
4 As discussed above, because of the major variability in methane emissions over the growing season.
seasonally-averaged daily emission coefficients (i.e., the seasonal average of average daily emissions coefficients
based on semi-continuous measurements taken over an entire growing season) should be.used (see Braatz and
Hogan (1991) for a description of appropriate emission measurement techniques).
5 See IPCC (1994) for details on how to incorporate more detail into calculations.
D8-5
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Cicerone, R.J., J.D. Shelter, and C.C. Delwiche. 1983. Seasonal variation of methane flux from a
California rice paddy. Journal of Geophysical Research 88:11022-11024.
Cicerone, R.J., and J.D. Shelter. 1981. Sources of atmospheric methane: Measurements in rice
paddies and a discussion. Journal of Geophysical Research 86:7203-7209.
Holzapfel-Pschorn, A., and W. Seiler. 1986. Methane emission during a cullivalion period from an
Italian rice paddy. Journal of Geophysical Research 91:11803-11814.
Holzapfel-Pschorn, A., R. Confad, and W. Seiler. 1985. Production, oxidalion, and emission of
melhane in rice paddies. FEMS Microbiology Ecology 31:343-351.
IPCC. 1994. IPCC Guidelines for National Greenhouse Gas Inventories, 3 volumes: Vol. I, Reporting
Instructions; Vol. 2, Workbook; Vol. 3, Draft Reference Manual. Inlergovernmenlal Panel on
Climate Change, Organizalion for Economic Co-Operalion and Development Paris, France.
Lindau, C.W. and P.K. Bollich. 1993. "Melhane Emissions from Louisiana Firsl and Raloon Crop
Rice." Soil Science 156: 42-48. July, 1993. .
Lindau, C.W., P.K. Bollich, R.D. DeL'aune, W.H. Palrick, Jr., and V.J. Law. 1991. "Effect of Urea
Ferlilizer and Environmental Factors on CH4 Emissions from a Louisiana, USA Rice Field."
Plant Soil 136: 195-203.
Sass, R.L., P.M. Fisher, and Y.B. Wang. 1992. "Melhane Emission from Rice Fields: The Effecl of
Floodwaler Management" Global Biogeological Cycles 6(3): 249-262. Seplember, 1992.
Sass, R.L., P.M. Fisher, P.A. Harcombe, and F.T. Turner. 1991a. "Miligalion of Methane Emissions
from Rice Fields: Possible Adverse Effects of Incorporated Rice Straw." Global
Biogeochemical Cycles 5: 275-287.
Sass, R.L., P.M. Fisher, F.T. Turner, and M.F. Jund. 1991b. "Methane Emissions from Rice Fields
as Influenced by Solar Radiation, Temperature, and Straw Incorporation." Global
Biogeochemical Cycles 5:335-350.
Sass, R.L., P.M. Fisher, P.A. Harcombe, and F.T. Turner. 1990. Methane production and emission
in a Texas rice field. Global Biogeochemical Cycles 4:47-68.
Schiilz, H., A Holzapfel-Pschorn, R. Conrad, H. Rennenberg, and W. Seiler. 1989. A 3-year
conlinuous record of the influence of daytime, season, and fertilizer treatmenl on melhane
emission rates from an Italian rice paddy. Journal of Geophysical Research 94:16405-16416.
USDA (U.S. Departmenl of Agriculture). 1993. Crop Production: 1992 Summary. USDA, National
Agricultural Statistics Service, Agricultural Statistics Board, Washington, DC. January, 1993.
USDA. 1991. Crop Production: 1990 Summary. USDA, National Agricultural Statistics Service,
Agricultural Slalislics Board, Washington, DC. January, 1991.
D8-6
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U.S. EPA (U.S. Environmental Protection Agency). 1994. International Anthropogenic Methane
Emissions: Estimates for 1990, Report to Congress. Office of Policy Planning and Evaluation.
U.S. EPA, Washington, DC.
D8-7
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DISCUSSION 9
EMISSIONS FROM AGRICULTURAL SOIL MANAGEMENT
OVERVIEW
Various agricultural soil management practices contribute to greenhouse gas emissions. The
use of synthetic and organic fertilizers adds nitrogen to soils, thereby increasing natural emissions of
nitrous oxide. Other agricultural soil management practices such as irrigation, tillage practices, or the
fallowing of land can also affect trace gas fluxes to and from the soil since soils are both a source and
a sink for carbon dioxide and carbon monoxide, a sink for methane, and a source of nitrous oxide.
However, there is much uncertainty about the direction and magnitude of the effects of these other
practices, so only a methodology for emissions from fertilizer use is included in the States Workbook
at this time.
' Nitrous oxide is produced naturally in soils through the microbial processes of denitrification
and nitrification.1 A number of anthropogenic activities add nitrogen to soils, thereby increasing the
amount of nitrogen available for nitrification and denitrification, and ultimately the amount of N2O
emitted. These activities include application of fertilizers, atmospheric deposition, and cultivation of
nitrogen-fixing crops. Fertilizer use is the most significant source of nitrous oxide in the U.S.
Nitrous oxide emissions in 1990 due to consumption of synthetic fertilizers (both multi-nutrient and
nitrogen) and organic fertilizers were about 13.5 MMTCE. This represents approximately 45 percent
of total U.S. nitrous oxide emissions, and about 97 percent of nitrous oxide emissions from all
agricultural sources. Approximately 55 percent of the fertilizer was consumed in the Midwest (TVA,
1993).
Research has shown that a number of factors affect nitrification and denitrification rates in
soils, including: water content, which regulates oxygen supply; temperature, an important factor in
microbial activity; nitrogen concentration, in particular nitrate and ammonium concentration; available
organic carbon for microbial activity; and soil pH. These conditions vary greatly by soil type, crop
type, management regime, and fertilizer application. Moreover, the interaction of these conditions
and their combined effect on the processes leading to nitrous oxide emissions are not fully
understood.
DESCRIPTION OF WORKBOOK METHOD
Nitrous oxide emissions from commercial fertilizer use can be estimated using the
methodology presented below:
1 Denitrification is the process by which nitrates or nitrites are reduced by bacteria and which results in
the escape of nitrogen into the air. Nitrification is the process by which bacteria and other microorganisms
oxidize ammonium salts to nitrites, and further oxidize nitrites to nitrates.
2 Methods to estimate emissions due to atmospheric deposition and nitrogen fixing crops are not included
at this time for two reasons: these emission sources are highly uncertain, and activity data are not readily
available.
D9-1
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N2O Emissions = FC x EC x 44/28
where: FC = Fertilizer Consumption (tons N-applied)-;
EC = Emission Coefficient = 0.0117 tons N2O-N/ton N applied; and
44/28 is the molecular weight ratio of N2O to N2O as N (N2O/N2O-N).
The methodology includes an emission coefficient of 0.0117 tons N/ton N-applied (i.e., 1.17
percent of the nitrogen applied as fertilizer is released into the atmosphere as nitrous oxide). This
emission coefficient was obtained from the Agricultural Research Service of the. U.S. Department of
Agriculture (USDA), which estimated that 1.84 kg N2O was emitted per 100 kg of nitrogen applied
as fertilizer. After applying the appropriate conversion, this is equivalent 0.0117 tons N2O-N/ton N-
applied.
The total amount of commercial fertilizer consumed.in a state is the sum of all synthetic
nitrogen, multiple-nutrient, and organic fertilizer used (measured in mass units of nitrogen). Fertilizer
data by type and by state can be obtained from the Tennessee Valley Authority's National Fertilizer
and Environmental Research Center (TVA, 1993).4 There may be instances in which fertilizer
consumption is given as the total mass of fertilizer consumed rather than as nitrogen content. In such
cases, total mass by fertilizer type may be converted to nitrogen content using the percentages in
Table D9-1.
Because agricultural activities fluctuate from year to year as a result of economic, climatic,
and other variables, it is recommended that an average of three years of fertilizer consumption
(centered on 1990) be used to account for extraordinary circumstances.
UNCERTAINTIES
Scientific knowledge regarding nitrous oxide production and emissions from fertilized soils is
limited. Significant uncertainties exist regarding the agricultural practices, soil properties, climatic
conditions, and biogenic processes that determine how much fertilizer nitrogen various crops absorb,
how much remains in soils after fertilizer application, and in what ways the remaining nitrogen either
evolves into nitrous oxide or into gaseous nitrogen and other nitrogen compounds.
A major difficulty in estimating the magnitude of emissions from this source has been the
relative lack of emissions measurement data across a suitably wide variety of controlled conditions,
making it difficult to develop statistically valid estimates of emission factors. Previous attempts have
been made to develop emission factors for different fertilizer and crop types for the purposes of
developing state and national emissions inventories. However, the accuracy of these emission factors
has been questioned. For example, while some studies indicate that N2O emission rates are higher
3 In some instances, state fertilizer consumption data may only be provided by fertilizer type and not
aggregated across all types by total N consumed. If this is the case, then analysts must first determine the
amount of N consumed for each fertilizer type (using the percentages in Table D9-1) and then follow the
method presented. To obtain total emissions by state, sum across all types.
4 Fertilizer consumption data may be underestimates since they do not include organic fertilizers that do
not enter the commercial market.
D9-2
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Table D9-1
Nitrogen Content of Principal Fertilizer Materials
MATERIAL
Nitrogen
Ammonia, Anhydrous
Ammonia, Aqua
Ammonium nitrate
Ammonium nitrate -limestone mixtures
Ammonium sulfate
Ammonium sulfate-nitrate
Calcium cyanamide
Calcium nitrate
Nitrogen solutions
Sodium nitrate
Urea
Urea-form
Phosphate
Basic slag, Open hearth
Bone meal
Phosphoric acid
Rock phosphate
Superphosphate, Normal
Superphosphate, Concentrated
Superphosphoric acid
Potash
Potassium chloride (muriate)
Potassium magnesium sulfate
Potassium sulfate
Multiple Nutrient
Ammoniated superphosphate
Ammonium phosphate-nitrate
Ammonium phosphate-sulfate
Diammonium phosphate
Monoammonium phosphate
Nitric phosphates
Nitrate of soda-potash
Potassium nitrate
Wood ashes
Blast furnace slag
Dolomite
Gypsum
Kieserite (emjeo)
Limestone
Lime-sulfur solution
Magnesium sulfate (Epsom salt)
Sulfur
% NITROGEN
82
16-25
33.5
20.5
21
26
21
15
21-49
16
46
38
•
2-4.5
•
-
-
.
-
-
-
-
3-6
27
13-16
16-21
11
'14-22
15
13
-
-
-
-
-
-
-
•
.
Note: A dash (-) indicates no, or a negligible amount of, nitrogen present.
Source: The Fertilizer Institute, 1982.
D9-3
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tor ammonium-based fertilizers than for nitrate, other studies show no particular trend in N2O
emissions related to fertilizer types (see Eichner (1990) and Bouwman (1990) for reviews of the
literature). Therefore, it is possible that fertilizer type is not the most important factor in determining
emissions. One study suggests that N2O emissions from the nitrification of fertilizers may be more
closely related to soil properties than to the type of fertilizer applied (Byrnes et al., 1990).
There is consensus, however, as to the fact that numerous factors influence the biological
processes of the soil microorganisms that determine nitrous oxide emissions from nitrogen fertilizer
use. For discussion purposes, these factors are divided into two general categories; natural processes
and management practices (see Box D9-1 for a description of each category).
While it is relatively well known how the natural processes individually affect N2O emissions,
it is not well understood how the interaction of the processes affects N2O emissions. Experiments
have shown that in some cases increases in each of the following factors (individually) enhance N2O
emissions: pH, soil temperature, soil moisture, organic carbon content, and oxygen supply (Bouwman,
1990; Eichner, 1990). However, how soil moisture, organic carbon content, and microbial population
together, for example, affect N2O emissions, is not readily predictable.
Box D9-1: Factors Affecting N2O Emissions
from Fertilizer Consumption
Natural Processes
temperature
precipitation
soil moisture content
oxygen available porosity
pH
organic carbon content
thaw cycle
microorganisms
soil type
Management Practices
fertilizer type
application rate
application technique
crop type
timing of application
tillage practices
use of other chemicals
irrigation
residual N and O from
crop/fertilizer
Management
practices may also affect
N2O emissions, although
these relationships have not
been well quantified. As
mentioned, levels of N2O
emissions may be dependent
on the type of fertilizer
used, although the extent of
the effect is not clear, as
demonstrated by the wide
range of emission
coefficients for individual
fertilizer types derived in
experiments (Bouwman,
1990). Although high
application rates for
fertilizer may cause higher
N2O emission rates, the relationship between fertilizer application rate arid nitrous oxide emission
is not well understood. Deep placement of fertilizer as an application technique will result in lower
N2O emissions than broadcasting or hand placement (Stangel, 1988). Bremner et al. (1981) found
that emissions from fertilizer applied in the fall were higher than emissions from the same fertilizer
applied in the spring, indicating that the timing of fertilizer application can affect N2O emissions.
Tillage practices can also affect N2O emissions. Tilling tends to decrease N2O emissions; no-till and
use of herbicides may increase N2O emissions (Groffman, 1987; Breitenbeck, 1988). However,
limited research at unique sites under specific conditions has not been able to account for the
complex interaction of the factors, making the effects of combinations of factors difficult to predict.
Emissions may also occur from the contamination of surface and ground water due to nutrient
leaching and runoff from agricultural systems. However, methods to estimate emissions of N2O from
these sources are not included in the States Workbook at this time due to a lack of data and emission
coefficients for each contributing activity. However, because of the potential relative importance of
these N2O emissions, they should be included in the future as data availability and scientific
D9-4
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understanding permit.
REFERENCES
Bpuwman, A.F. 1990. "Exchange of Greenhouse Gases between Terrestrial Ecosystems and the
Atmosphere." In: Bouwman, A.F., ed. Soils and the Greenhouse Effect. John Wiley & Sons,
Chichester. pp.61-127.
Breitenbeck, G.A. 1988. Presentation at U.S. EPA Workshop on Agriculture and Climate Change.
February 29-March 1, 1988. Washington, D.C.
Bremner, J.M., G.A Breitrenbeck, and A.M. Blackmer. 1981. Effect of anhydrous ammonia
fertilization on emission of nitrous oxide from the soil. Journal of Environmental Quality
10:77-80. .
Byrnes, B.H., C.B. Christiansen, L.S. Holt, and E.R. Austin. 1990. "Nitrous Oxide Emissions from
the Nitrification of Nitrogen Fertilizers." In: Bouwman, A.F., ed. Soils and the Greenhouse
Effect. John Wiley & Sons, Chichester. pp.489-495.
CAST (Council for Agricultural Science and Technology). 1992. Preparing U.S. Agriculture for Global
Climate Change. Task Force Report No. 119. Waggoner, P.E., Chair. CAST, Ames, Iowa.
June, 1992.
Eichner, M.J. 1990. "Nitrous Oxide Emissions from Fertilized Soils: Summary of Available Data."
Journal of Environmental Quality 19:272-280.
Fertilizer Institute. 1982. The Fertilizer Handbook. The Fertilizer Institute, Washington, D.C.
Groffman, P., P. Hendrix, D. Crossley. 1987. "Nitrogen Dynamics in Conventional and No-Tillage
Agroecosystems with Inorganic Fertilizer or Legume Nitrogen Inputs. Plant and Soil 97:315 -
332.
Stangel, P. 1988. "Technological Options Affecting Emissions," Presented at U.S. EPA Workshop on
Agriculture and Climate Change, February 29-March 1, 1988. Washington, D.C.
TVA (Tennessee Valley Authority). 1993a. Commercial Fertilizers, 1993. National Fertilizer and
Environmental Research Center, Tennessee Valley Authority, TN. December 1993.
TVA. 1993b. Fertilizer Summary Data. National Fertilizer and Environmental Research Center,
Tennessee Valley Authority, TN. December 1993.
D9-5
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DISCUSSION 10
CARBON DIOXIDE EMISSIONS FROM
FOREST MANAGEMENT AND LAND-USE CHANGE
OVERVIEW
The biosphere emits and absorbs a wide variety of carbon and nitrogen trace gases, including
carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), nitrous oxide (N2O), oxides of
nitrogen (NOX), and nonmethane volatile organic compounds (NMVOCs). When humans use and
alter the biosphere through forest management and land-use change activities, such as clearing an
area of forest to create cropland, restocking a logged forest, draining a wetland, or allowing a pasture
to revert to grassland, the natural balance of these trace gas emissions and uptake is altered and their
atmospheric concentrations adjust. In the U.S., forest management is believed to be the primary
land-use activity responsible for current greenhouse gas fluxes, and carbon dioxide is the most
significant gas affected.
Forests are complex ecosystems with several interrelated components,.each of which acts as
a carbon storage pool, including:
• trees (i.e., living trees, standing dead trees, roots stems, branches and foliage);
• soil;
« the forest floor (Le., woody debris and tree litter); and
• understory vegetation (Le., shrubs and bushes).
As a result of biological processes (e.g., growth and mortality) and anthropogenic activities
harvesting, thinning, and other removals), carbon is continuously cycled through these ecosystem
components, as well as between the forest ecosystem and the atmosphere. For example, the growth
of trees results in the uptake of carbon from the atmosphere and storage in living trees. As these
trees age, they continue to accumulate carbon until they reach maturity, at which point they are
relatively constant carbon stores. As trees die and otherwise deposit litter and debris on the forest
floor, decay processes will release carbon to the atmosphere and also increase soil carbon. The net
change in forest carbon is the change in the total net amount of carbon stored in each of these pools
(Le., in each ecosystem component) over time.
The net change in forest carbon, however, is not likely to be equivalent to the net flux
between forests and the atmosphere. Because most of the timber that is harvested and removed from
U.S. forests is used in wood products, harvests may not always result in an immediate flux of carbon
to the atmosphere. Harvesting in effect transfers carbon from one of the "forest pools" to a "product
pool." Once in a product pool, the carbon is emitted over time as CO2 through either combustion
or decay,1 although the exact rate of emission varies considerably between different product pools
and may in fact result in effective long-term carbon storage. For example, if timber is harvested and
1 Actually, if timber undergoes combustion, some small portion of the carbon - as much as 10 percent
of the total carbon released - will be released as CO and CH4 rather than CO2. In addition, if timber
products are placed in landfills, about 50 percent of the carbon that eventually decomposes is oxidized to
CO2 and about 50 percent is released as CH4. However, eventually both CO and CH4 oxidize to CO2 in
the atmosphere.
D10-1
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subsequently used as lumber in a house, it may be many decades or even centuries before the lumber
is allowed to decay and carbon is released to the atmosphere. If timber is harvested for energy use,
subsequent combustion results in an immediate release of carbon. Paper production may result in
emissions over years or decades.
The U.S. land area is roughly 2,263 million acres, of which 33 percent, or 737 million acres,
is forest land (Powell et al., 1993). The amount of forest land has remained fairly constant over
recent decades declining by'approximately 5 million acres between 1977 and 1987 (USFS, 1990;
Waddell et al., 1989) and increasing by about 0.5 million acres between 1987 and 1992 (Powell et al.,
1993). These changes represent fluctuations of well under 1 percent of the forest land area, or on
average, about 0.1 percent per year. Other major land uses in the U.S. include range and pasture
lands (36 percent), cropland (18 percent), urban uses (3 percent); and other lands (10 percent)
(Daugherty, 1991).2 Urban lands are the fastest growing land use.
Given that U.S. forest land area changed by only about 0.1 percent per year between 1987
and 1992, the major influences on the net carbon flux from forest land are management activities and
ongoing impacts of previous land-use changes. These activities affect the net flux of carbon by
altering the amount of carbon stored in the bipmass3 and soils of forest ecosystems. For example,
intensified management of forests can increase both the rate of growth and the eventual biomass
density of the forest, thereby increasing the uptake of carbon. The reversion of cropland to forest
land through natural regeneration will, over decades, result in increased carbon storage in biomass
and soils (Le., in general, forests contain more biomass and soil carbon than cropland).
The net CO2 flux in 1990 due to forest management activities and the regeneration of
previously cleared forest area is estimated to have been an uptake (sequestration) of 119 MMTCE
( U.S. EPA, 1994). This carbon uptake represents an offset of about 9 percent of the CO2 emissions
from energy-related activities. The Northeast, North Central, and South Central regions of the U.S.
account for 98 percent of the uptake of carbon, largely due to high growth rates that are the result
of intensified forest management practices and the regeneration of forest land previously cleared for
cropland and pasture. Western states are responsible for a small net release of carbon, reflecting
mature forests with a near balance between growth, mortality, and harvest.
DESCRIPTION OF WORKBOOK METHOD
The method provided in Workbook Section 10 focuses on land-use changes and forest
management activities that result in the largest potential flux of CO2 to the atmosphere or have the
largest potential for sequestering carbon. These include activities that:
• .affect the amount of biomass in existing biomass stocks on forests and other land,
without changing the way land is used (e.g., management of standing forests, urban
tree planting, logging), or
2 Other lands include farmsteads, transportation uses, marshes, swamps, deserts, tundra, and
miscellaneous other lands.
3 Biomass is a shorthand term for organic material. The amount of biomass in a given land area
includes all the living and dead organic material, both above and below the ground surface.
D10-2
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• change the way land is used (e.g., clearing forests for agricultural use or suburban
development, converting a grassland to cropland).
The dominant gas of concern in this source category is CO2, and the methodology presented below
is specific to CO2. Other important greenhouse gases, including CH4 and N2O, and photochemically
important gases, including CO, NOX, and NMVOCs are also produced from forest management and
land-use change activities. However, emissions of these gases that result from biomass burning (i.e.,
wood consumption for energy production) are captured in Discussion Section 14, while emissions of
these gases due to other activities (such as land flooding) are not yet explicitly included in the
methodology. Instead, they are discussed as areas for further research in the uncertainties section
of this chapter.
The fundamental basis for the methodology rests upon two linked themes: (1) the flux of CO2
to or from the atmosphere is assumed to be .equal to changes in the carbon stocks of existing biomass
and soils, and (2) changes in the carbon stocks can be estimated by first establishing rates of change
in land use and then applying simple assumptions about the biological response to the land use. The
methodology is designed to be comprehensive, i.e., cover all the main land-use change and forestry
activities in the U.S., and to be feasible to implement by all states.
In estimating the effects of forest management activities, land use and land-use change on
fluxes of greenhouse gases, it is reasonable to stage the calculation methods so that the most
important components can be addressed first. Complexities and subtleties of the relationship of
forestry and land-use change to fluxes of CO2 and other gases can be incorporated in a consistent
manner into subsequent calculations as knowledge advances and data improve. The methodology
presented here focuses on a simple, practical, and fair procedure for determining the CO2 flux
directly attributable to forest management and land-use change activities. This procedure also
accounts for the influence of past land-use changes on the contemporary CO2 flux. It should be
noted, however, that this method is based upon many simplifying assumptions in order to allow for
implementation with only minimal data (these simplifying assumptions are discussed in detail later in
this section). At the same time, the methodology is sufficiently flexible to accommodate users with
different levels of available data, i.e., data with different levels of complexity and at different
geographic scales. States are encouraged to apply the method in as detailed a manner as their data
allow, as well as to estimate emissions from land-use activities that are not explicitly included in the
method if expertise and data are sufficient.
This section is divided into three parts, each of which reflects a general category of land-use
change and forest management activities. They are (see Figure D10-1 for a breakdown of the
activities associated with each of the categories described below):
• Changes in Forests and Other Woody Biomass Stocks: The most important effects of human
interactions with existing forests are considered in this single broad category, which includes
commercial management and logging for forest products, replanting after logging or other
forest timber removal, the harvest of fuelwood, and the establishment and operation of forest
plantations as well as planting trees in urban, suburban, or other non-forest locations.
• Forest and Grassland Conversion: This category includes the conversion of forest and
grasslands to pasture, croplands, or other managed uses as well as to shopping malls, parking
lots, and suburban communities. These activities can significantly change the carbon stored
in biomass and in soils.
D10-3
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1.
Abandonment of Managed
Lands: Lands that had
been managed previously
(i.e., croplands, pasture) and
that are abandoned and
allowed to regrow naturally,
without any human
interference, can re-
accumulate significant
amounts of carbon in their
biomass and soils. This
category includes these lands
that are regrowing naturally
into their prior grassland or
forest conditions.
CO2 FLUX FROM CHANGES
IN FORESTS AND OTHER
WOODY BIOMASS STOCKS
Figure D10-1. Land-Use Change and Forestry Activities
Covered in Method
Activities
Logging
Planting
Restocking
Urban forestry
Agroforestry
Fuenvood extraction
Classification
Changes in Forests
and Other Woody
Biomass Stocks
Permanent forest clearing
Conversion of grasslands to
cultivated lands
Shiffing cultivation
Urban development
Suburban development
Parking lots
Forest and Grassland
Conversion
Abandonment of managed
pastureland, cropland, etc.
Abandonment of
Managed Lands
This category as used in
these basic calculations is very
broad, potentially including a wide
variety of land-uses and
management practices. This discussion focuses heavily on changes in forests, which account for the
largest component of annual changes in biomass stocks in the U.S. However, other types of biomass,
such as non-forest trees (e.g., in towns and cities) and woody shrubs on grasslands should be included
if a state believes these are a significant component of total changes of biomass stocks.
A basic organizing concept in the section is that all existing forests can be allocated into one
of three categories:
(1) Natural, undisturbed forests, where they still exist and are in equilibrium, should not be
considered either an anthropogenic source or sink. They should, therefore, be excluded from
state inventory calculations.
(2) Forests regrowing naturally on abandoned lands are a net carbon sink attributable to past
human activities and ~are accounted for as discussed in the section on emissions from
abandoned lands. While current regrowth is considered a response to past anthropogenic
activity, "abandoned lands" are by definition assumed not to be subject to ongoing human
intervention after abandonment.
(3) All other types of forests are included in the changes in forests and other woody biomass
stocks category. That is, any forest which experiences periodic or ongoing human intervention
that affects carbon stocks should be included here. In the basic calculations, the focus is on
primarily a few types of human interactions with forests which are believed to result in the
most significant fluxes of carbon. State experts are encouraged, however, to estimate
emissions for any activity related to existing forests which is considered to result in significant
D10-4
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carbon emissions or removals and for which necessary data are available.
Some of the activities in the changes in forests or other woody biomass stocks category which
can potentially produce significant carbon fluxes are:
• management of commercial forests -- including logging, selective thinning, restocking,
etc., as practiced by commercial forest products industries;
• establishment and management of commercial plantations4;
• other afforestation or reforestation programs; and
• informal non-commercial fuelwood, timber, and other wood harvest.
This category also includes trees which may not traditionally be considered part of forests,
such as urban trees, trees planted along highways, aircraft runways, etc. These dispersed trees do not
contribute greatly to carbon fluxes to or from the atmosphere, however, they may be of interest to
some states because of their potential use in response strategies.
As illustrated in the above list, the changes in forests and other woody biomass stocks category
includes some tree planting activities which, strictly speaking, are land-use changes. Plantation
establishment and other afforestation/reforestation programs are examples. It is recognized that this
is conceptually inconsistent as the category is intended to account for ongoing interactions with
existing forests. However, from a pragmatic perspective, including these activities within the category
can simplify the calculations. These subcategories are land-use changes which, create new forest
stocks. As soon as the land-use change occurs (i.e., tree planting), the new land becomes part of the
changes in forests and other woody biomass stocks category which is accounted for on an annual
incremental basis. The following three equations summarize the recommended method (which is
presented step-by-step in Workbook Section 10):
Equation 1. Annual Biomass Carbon Uptake
U = £/ lAPfx GPfxCPf) H- (TfxGTfx C7})]
where:
AP = area of plantations and managed forests (103 acres)
• GP = annual biomass growth rate (t dm/acre/yr)
CP = C fraction for plantations and managed forests (t C/t dm)
T = number of trees planted (103s)
GT = annual biomass growth rate (t dm/tree/yr)
CT = C fraction for trees planted (t C/t dm)
f = forest type
4 Plantations are forest stands that have been established artificially to produce a forest product crop.
D10-5
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Equation 2. Annual Biomass Carbon Release
* =
((CHfx EFf!
FWf
owf ~
x c
where:
CH
EF
FW
OW
FC
C
f
commercial harvest (103 ft3/yr)
biomass conversion/expansion factor (t dm/ft3)
annual fuelwood consumption (103 t dm/yr)
other wood use (103 t dm/yr)
wood removed during forest conversion and used as fuelwood (103 t
dm/yr)6
C fraction (t C/t dm)
forest type.
Equation 3. Net CO? Flux from Changes in Forests and Other Woody Biomass Stocks
where:
R
U
Net CO, (tonslyr) = (R - U) x 44/12
annual biomass C release (t C/yr)
annual biomass C uptake (t C/yr)
Estimates of average annual accumulation of dry matter as biomass per acre are presented
for forests naturally regrowing by broad category in Tables D10-1 and D10-2. These values can be
used for default values for growth rates in similarly managed forest categories if no other information
is available. For forests that are more intensely managed, annual growth increments can be quite
different. Values for some typical plantation species are presented in Table D10-3 and can be used
as default values. For non-forest trees, such as urban tree planting, accounting would be done on the
basis of number of trees (e.g., in thousands) rather than for acres of land. The calculations would be
the same, except the average annual growth would be expressed in tons of dry matter per tree rather
than per acre. The recommended unit of calculation is tons of dry matter (or dry biomass), and needs
to be converted to carbon for emissions estimation. A general default value of 0.5 tons C/ton dry
matter is recommended for all biomass calculations. If more accurate conversion values are available
5 To include the decay of forest products left after harvest, the harvested amounts are adjusted in two
ways: (1) the volume of biomass must first be converted to mass of dry matter; and (2) an expansion ratio
is applied to account for non-commercial biomass (limbs, small trees, etc.) harvested with the commercial
biomass and left to decay.
6 For estimating annual biomass emissions, all of the harvested biomass from forests is summed and
the portion of harvested material used as fuelv, ;od is subtracted, because emissions from fuelwood are
accounted for in the following section on forests and grasslands conversion. This subtraction is done to
avoid double-counting emissions.
D10-6
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for the particular species, these should of course be used.7
The methodology is designed to accommodate users at several levels of detail. This is
especially important in the managed forests category. Many states have highly developed forest
industries that keep detailed records of existing commercial forests and forests managed by non-
industrial private forest owners. In addition, the U.S. Forest Service (USFS) compiles detailed forest
inventory statistics every five years. For such states, it is possible to derive from survey results
aggregate values comparable to the data and assumptions used in the approach provided in
Workbook Section 10, and present them in this common format.8
Table D10-1
Aboveground Dry Matter in Tropical Forests
(t dm/acre)
Moist Forest
Primary
515.6
Secondary
425.9
Seasonal Forest
Primary
313.8
Secondary
269
Dry Forest
Primary
134.5
Secondary
56
Source: Derived from IPCC, 1994
Table D10-2
Aboveground Dry Matter in Temperate and Boreal Forests
(t dm/acre)
Primary
Secondary
Temperate Forests
Evergreen
661.3
493.2
Deciduous
560.4
392.3
Boreal Forests
369.8
269
Source: Derived from IPCC, 1994
Changes in forests or other woody biomass may be either a source or a sink of CO2 in a given
year in a state. The simplest way to determine which, is by comparing the annual biomass growth
versus annual harvest, including the decay of forest products produced from harvested biomass.
Harvested wood releases carbon at rates dependent upon its method of processing and its end-use;
waste wood is usually burned immediately or within a couple of years, paper usually decays in up to
5 years (although landfilling paper can result in longer-term storage of carbon and eventual release
of CH4 or CO), and lumber and durable wood products decay in up to 100 years or more. Forest
7 For region-specific data in the U.S., see Birdsey and Heath (1993) and Birdsey (1992).
8 For region-specific data in the U.S., see USFS (1990) and Waddell (1989).
D10-7
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Table D10-3
Average Annual Accumulation of Dry Matter as Biomass in Plantations
Forest Types
Tropical
Temperate
Acacia spp.
Eucalyptus spp.
Tectona grandis
Pinus spp.
Pinus caribaea
Mixed Hardwoods
Mixed Fast-Growing
Hardwires
Mixed Sc.":woods
Douglas Fir
Loblolly Pine
Average Annual Increment in
Biomass
(t dm/acre/yr)
33.6
32.5
17.9
25.S-
22.4
15.2
20
32.5
13.5
9
Source: Derived from IPCC, 1994
harvest could result in a net uptake of carbon if the wood that is harvested is used for long-term
products such as building lumber and furniture, and regrowth is relatively rapid. This may in fact
become part of a response strategy for some states.
For the purposes of the basic calculation, however, the recommended default assumption is
that'all carbon removed in wood and otht:-• biomass from forests is oxidized in the year of removal.
This is because new products from curreri arvests frequently replace existing product.stocks, which
are in turn discarded and oxidized. Thi: clearly would not be accurate if relative sizes of forest
product pools change significantly over time, but is considered a legitimate, conservative assumption
for initial calculations. Storage of carbon in wood products can be included in a state inventory,
however, if a state can document that existing stocks of long-term forest products are in fact
increasing (or decreasing). If data permit, a state could add a component to Equation (2) to account
for increases (or decreases) in forest product pools (see Table D10-4 for default values for recycle
rates and average product lives for various forest products).
To summarize, the net growth of biomass stocks (and accumulation of carbon) depends on
the type of biomass stock and the intensity and type of management. Well managed commercial
forests would, over the long-term, be expected to have net emissions close to zero. In many cases,
where historically cleared areas are regrowing under commercial management, the forest areas act
as a sink. If forests are logged or harvested at a rate which exceeds regrowth, then there is a net loss
of carbon.
D10-8
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Table D10-4. Average Lifetimes for Selected Forest Products
Final End-Use
1 -Family House
Multi-Family House
Mobile Home
Residential Maintenance and Repair
Non-residential Construction
Manufacturers
Shipping
Other Solid Wood Uses
Newsprint
Printing and Writing Paper
Tissue Paper
Packaging Paper
Single-Use Life
60
50
12
30
67
1.2
6
30
1
6
1
1
Recycle Rate
0.030
0.030
0.107
0.107
0.030
0.107
0.107
0.107
0.230
' 0.070
0.000
0.150
Adjusted Life
in Use
61.9
51.5.
13.4
33.6
69.1
13.4
6.7
33.6
1.3
6.5
1
1.2
2.
Source: Row and Phelps, 1991
Note: Carbon held in wood that is transformed into forest products will not be admitted to the atmosphere
until the product burns or decays. To calculate the amount and timing of these emissions requires that
the amount of wood allocated to each end-use and the average life-time of the forest product be
determined. The table above provides the estimated average life for a single-use cycle, the recycle rate,
and the adjusted average use life for 12 final end-use categories. The adjustment for recycling adds
several years to the effective half-life of building materials. This adjustment has an even greater effect
on the average life for most types of paper products. However, the life of paper products is considerably
shorter than that of durable wood products.
FOREST AND GRASSLAND CONVERSION
This category includes conversion of existing forests and natural grasslands to other land uses,
including agriculture, highways, urban development, etc. As with all categories of forest management
and land-use change activity, it is necessary to determine net CO2 flux from biomass loss: The basic
calculations employ the same simplifying assumption regarding biomass removals in this part as in the
previous part, i.e., that biomass removals replace existing stocks that are in turn oxidized. Therefore,
in the calculations, biomass removals are treated like instantaneous emissions. This methodological
simplification in effect accounts for current emissions due to decay of materials cleared in previous
years, assuming that rates of land conversion and allocations to product pools have not changed
significantly over time.
Forest and grassland conversion also results in CO2 emissions through soil disturbance and
oxidation of soil organic matter, particularly when the conversion is to cultivated lands or urban
development. This is a long-term process which may continue for many years after the land-use
change occurs. The basic calculations allow for estimation of current emissions from soil carbon
disturbance due to current and previous land conversion through an averaging approach.
In some countries, when forests are cleared, significant amounts of the cleared biomass are
burned to prepare the lands for cultivation or pasture. In addition to CO2, this biomass burning
releases CO, CH4, N2O and NOX. However, this part of the method does not account for any non-
CO2 emissions from biomass burning. There are two basic reasons for omitting these emissions from
D10-9
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the method presented here:
• Land clearing by burning is rarely practiced in the U.S. due to regulatory and practical
considerations, therefore, emissions from this source are assumed to be zero.
• Any non-CO2 emissions that result from this source are assumed to be due to the use
of cleared biomass as fuelwood in fireplaces, woodstoves, etc. These emissions are
captured in the calculations for wood combustion presented in Discussion Section 14.
Emissions of CO2 due to forest clearing and grassland conversion are calculated through a
sequence of steps that estimate: . -
• the net change in aboveground biomass carbon;
• current emissions from loss (decay and burning) of net biomass cleared; and
• current releases of carbon from soils due to conversions over the previous 25 years.
The method presented in Workbook Section 10 is summarized in equations 4 through 6 below.
Equation 4. Carbon Released from Loss of Biomass
£
C Released as Loss of Aboveground Biomass (1,000 t C/yr) = ^ ]AAf x (BCf - AC^ x CFf
where:
AA = annual area converted (103 acres/yr)
BC = aboveground biomass before conversion (t dm/acre)
AC = aboveground biomass after conversion (t dm/acre)
CF = carbon fraction of aboveground biomass (t C/t dm)
f = forest/grassland type
5. Carbon Released from Soil
Soil Carbon Released (1,000 t C/yr) = J^ [(AA-25f x CC} x CF-25,]
where:
AA-25 = average annual area converted over 25-year period (10 acres/yr)
CC = carbon content of soil before conversion (t/acre)
FC-25 = fraction of carbon released over 25-year period (t C/yr)
f = forest/grassland type
D10-10
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Equation 6. Total CO2 Released
Total Annual CO2 Released (1,000 t COJyr) = £^ (BLf + SLf) x 44/12
where:
BL = emissions from biomass loss (103 t C/yr)
SL = emissions from soil (103 t C/yr)
f ' = forest/grassland type
First, the amount of aboveground biomass affected by conversion in the emissions inventory
year is calculated by multiplying the annual forest area converted to other land uses by the net change
in aboveground biomass. This calculation is carried out for each relevant forest/grassland type. The
net change is the difference between the density (tons dry matter per acre) of aboveground biomass
on that forest/grassland prior to conversion, and the density of aboveground biomass after clearing.
The after clearing value includes the biomass that regrows on land in the year after conversion and
any original biomass that was hot completely cleared.
It is suggested that the annual CO2 flux associated with the loss of soil carbon following forest
clearing or grassland conversion is calculated using a 25-year time horizon to account for delayed
releases of soil carbon. The historical release of carbon from soil is simply the average annual land
clearing times the change in carbon stock in soil between the original land use and a, e.g., 25-year old
pasture or urban development. For simplicity, it is assumed that the soil carbon release is linear over
the 25-year period.
The annual rate of soil carbon loss would be the total change in soil carbon from before
conversion to after conversion, divided by 25. The currently available information on soil carbon
changes after conversion relates primarily to temperate and boreal forests and temperate grasslands.
Research indicates that approximately 50 percent of the soil carbon in the active layer (roughly the
top 3 feet) is lost over a 50-year period, with most of this loss occurring in the first 25 years.
However, these values are highly uncertain. The actual rate of soil carbon loss in a particular area
of agricultural land, for example, is a function of the specific agricultural use of, and management
practices on, the land. However, the general values above can be used as a default for initial
calculations, if more accurate information or measurements are not available. This would imply that
the annual rate of soil carbon loss would be 2 percent (50 percent/25 yrs).
The contemporary flux associated with past land-use change could be calculated by multiplying
the number of acres of land converted in each of the previous 25 years by an annual per acre loss
in soil carbon and summing over all years. Alternatively, the average annual historical conversion rate
over a 25-year period could be multiplied by the annual loss rate times 25. The average rate of
conversion is simply the total acres converted over the period divided by 25 years. The division by
25 and multiplication by 25 cancel each other and can be ignored. The recommendation is to use
average values for the rate of land conversion, soil carbon content, and portion of the soil carbon lost
over time. This averaging approach is used in the method to simplify the calculations and to reduce
data requirements. Table D10-5 provides average values for soil carbon in forest systems.9
For region-specific data in the U.S. see Birdsey (1992).
D10-11
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Table D10-5
Carbon in Forest Soils
(tons C/acre)
Forest Type
Tropical
Temperate
Primary
Secondary
Boreal
Primary
Secondary
Moist
257.8
Evergreen
300.4
269.0
461.8
414.7
Seasonal
224.2 '
Deciduous
300.4
269.0
'
Dry
134.5
3.
Source: Derived from IPCC, 1994
ABANDONMENT OF MANAGED LANDS
If managed lands, e.g., croplands and pastures, are abandoned, carbon may re-accumulate on
the land and in the soil. The response of these converted systems to abandonment depends on a
complexity of issues including soil type, length of time in pasture or cultivation, previous management
practices, and the type of original ecosystem of the land. Some abandoned lands my be too infertile,
saline, or eroded for regrowth to occur. In this case, either the land remains in its current state or
it may further degrade and lose additional organic material (i.e., carbon in the biomass and the soils).
Therefore, to calculate changes in carbon flux from this activity, the area abandoned should first be
split into parts: lands that re-accumulate carbon naturally, and those that do not or perhaps even
continue to degrade.
Abandoned lands must be evaluated in the context of the various natural ecosystems originally
occupying them (e.g., moist forest, dry forest, grassland). In addition, the effect of previous patterns
of management prior to abandonment should be considered while recognizing the desire for simplicity
and practicality of the method. The process of recovery of aboveground biomass is generally slower
than the human-induced oxidation of biomass. With this in mind, it is recommended that abandoned
lands be evaluated in two time horizons: a 20-year horizon to capture the more rapid growth expected
after abandonment; and from 20 years after abandonment up to 100 years. The method
recommended in Workbook Section 10 is divided into five steps and is summarized in the following
equations (note: completing equations 9 and 10 is optional and should only be considered if data are
readily available):
D10-12
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Equation 7. Carbon Uptake from Aboveground Biomass (^ 20 yrs.)
Annual Carbon Uptake for Aboveground Biomass (t C/yr) = ^ IAYe x RBe x C\
where:
AY = total area abandoned and regrown during last 20 years (103 acres)
RB = annual rate of aboveground biomass accumulation (t dm/acre/yr)
C = . C fraction of biomass (t C/t dm)
e = regrowth ecosystem type
Equation 8. Carbon Uptake from Soils (^ 20 yrs.)
Annual Carbon Uptake for Soils (t C/yr) = ^ (AYf x RS()
where:
AY = total area abandoned and regrown during last 20 years (10 acres)
RS = annual rate of C uptake in soils (t C/acre/yr)
e = regrowth ecosystem type
Equation 9. Carbon Uptake from Aboveground Biomass (20 - 100 yrs.)
Annual Carbon Uptake for Aboveground Biomass (t C/yr) = ^ (AOe x RBe x Ce\
where:
AO = total area abandoned and regrown, between 20 and 100 years that is
regenerating (103 acres)
RB = annual rate of aboveground biomass accumulation (t dm/acre/yr)
C = c fraction of biomass (t C/t dm)
e = regrowth ecosystem type
D10-13
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Equation 10. Carbon Uptake from Soils (20 - 100 yrs.)
Annual Carbon Uptake for Soils (t CJyr) = ^ (AOe x RSe)
where:
AO = total area abandoned and regrown, between 20 and 100 years that is
regenerating (103 acres)
RS = annual rate of C uptake in soils (t C/acre/yr)
e = regrowth ecosystem type
Equation 11. Total CO2 Uptake
Total CO2 Uptake on Abandoned Lands (f COJyr) =(A+B + C+D)x 44/12
where:
A = annual C uptake in aboveground biomass, s 20 years (t C/yr) (Step 1)
B = annual C uptake in soils, ^ 20 years (t C/yr) (Step 2)
C = annual C uptake in aboveground biomass, between 20 and 100 years
(t C/yr) (Step 3)
D = annual C uptake in soils, between 20 and 100 years (t C/yr) (Step 4)
In the basic calculation (as presented above), only those lands that begin to return to their
previous natural state are considered. Those that remain constant with respect to carbon flux can
be ignored. Likewise, the CO2 flux to the atmosphere for those lands that continue to degrade is
likely to be small, and hence is ignored in these basic calculations.
Table D10-6 presents estimates of average annual aboveground biomass accumulation in
vegetation in various regrowing forest ecosystems following abandonment of cultivated land or
pasture. These general growth rates should be considered crude approximations as applied to the
particular lands regrowing in a given state. Accumulation of aboveground biomass can be converted
to carbon using a general default'conversion value for biomass of 0.5 tons carbon per ton dry matter.
If lands are regenerating to grasslands, then the default assumption is that no significant
changes in aboveground biomass occur (this can be varied based on locally available data). Default
rates for soil carbon uptake for both forests and grasslands can be derived from the expected soil
carbon values for fully restored natural systems and some simple assumptions. In temperate and
boreal systems, it can be assumed that soil carbon accumulates linearly for some base value (e.g., 50-
70 percent of original stocks). Table D10-7 provides.default soil carbon values for these systems.
(Soil carbon changes in tropical systems are poorly understood and can be included or ignored in the
basic calculations at the discretion of state experts. Experts can consult Birdsey (1992) for region-
specific estimates of soil carbon).
D10-14
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Table D10-6
Average Annual Biomass Uptake by Natural Regeneration
(t dm/acre)
Region
Tropical
Forest Types
Moist Forests
0-20 yrs
17.9
20-100 yrs
2.0
Seasonal Forests
0-20 yrs
11.2
20-100 yrs
1.1.
Dry Forests
0-20 yrs
9.0
20-100 yrs
0.56
Note: Growth rates are derived by assuming that tropical forests regrow to 70 percent of undisturbed
forest biomass in the first twenty years. All forests are assumed to regrow to 100 percent of undisturbed
forest biomass in .100 years. Assumptions on the rates of growth in different time periods are derived
from Brown and Lugo, 1990.
Temperate
Evergreen
Deciduous
Boreal
0-20 yrs
6.7
4.5
2.24
20-100 yrs
6.7
4.5
2.24
%
'
Source: Derived from IPCC, 1994
Note: Temperate and boreal forests actually require considerably longer than 100 years to reach
the biomass density of a fully mature system. Harmon et al. (1990), for example, report
carefully designed simulations indicating that a 100-year old stand of douglas fir would contain
only a little over half the biomass of a 450-year old growth stand of the same species. There is
also evidence that growth rates in temperate and boreal systems are more nearly linear over
different age periods than is the case for tropical systems. Nabuurs and Mohren (1993) suggest
that growth rates for several different species in temperate and boreal zones rise slowly and peak
at ages of 30 - 55 years and'decline slowly thereafter. This suggests that using the same default
values for 0-20 years and 20-100 years may be a reasonable first approximation. Nabuurs and
Mohren (1990) also illustrate that growth rates may vary as much as a factor of ten for stands of
the same species and age, depending on site-specific conditions.
Table D10-7
Annual Soil Carbon Accumulation in Temperate and Boreal Forests
(tons C/acre/yr)
Temperate
Evergreen
2.9
Deciduous
2.9
Boreal
4.5
Source: Derived, from IPCC (1994).
The base value at the start of the re-accumulation process in soils would depend on the
average amount of time that cleared lands had been used for agricultural purposes before
abandonment and on management practices utilized during the agricultural period. Based on simple
default assumptions for soil carbon losses from forest clearing, experts can calculate the level to which
soil carbon would have fallen during the agricultural use period. The default assumption is that after
20 years, soil carbon would have fallen to 50 percent of the pre-clearing value (i.e., 2 percent per year
linear average change).
D10-15
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Available evidence indicates that, on average, soil carbon re-accumulates in soils after
abandonment, at a slower rate than it is lost under cultivation. In the forest clearing calculations the
default assumption is that soil carbon is lost at an average rate of 2 percent of the original carbon
content per year. If no detailed information is available, a default assumption could be that the soil
accumulation occurs linearly at roughly one-half this rate after abandonment. The values derived,
therefore, are 1.43 tons carbon per year for temperate evergreen and deciduous forest soils and 2.2
tons carbon per year for boreal forests.
4. CO2 EMISSIONS/UPTAKE FROM ALL FOREST MANAGEMENT AND LAND-USE ACTIVITIES
To calculate total CO2 emissions/uptake from all forest management and land-use activities
within a state, an analyst must sum the figures estimated in the previous three sections. Specifically:
Equation 12. Net CO2 Emissions/Uptake from Forests and Land-Use Change
Total C02 Emissions/Uptake (1,000 t C/yr) = Step 1 + Step 2 + Step 3
where:
Step 1: Net CO2 emissions/uptake from changes in forests and woody biomass
stocks (103 t CO2/yr)
Step 2: Net CO2 emissions from forest and grassland conversion (10 t
C02/yr) - -
Step 3: Net CO2 emissions/uptake from abandoned lands (10 t CO2/yr)
ALTERNATE METHODOLOGY
A less complex method for estimating net emissions from a state's forest management
activities would be to obtain information from the USFS on forest inventories for two separate years
and determine the change in biomass and soil carbon stocks over time. For example, using timber
volume statistics from 1987 and 1992 U.S. forest inventories (the most recent inventories compiled
by the USFS), a state could derive estimates of the total carbon stored in forest biomass and soils for
each of the two years. The difference between total carbon storage in each year would represent the
net change in carbon stocks over the five year period (including harvests and regrowth). This result
could then be divided by 5 to determine the average annual change in carbon stocks. This is the
approach used by Birdsey (1992) to estimate carbon storage and accumulation in U.S. forests.
If analysts choose this method, they should understand that:
(1) The USFS inventories of timber volume include only timberlands, i.e., forest lands
that are producing or are capable of producing crops of industrial wood and are not
withdrawn from timber utilization by statute or administrative regulation (Waddell et
. al., 1989). Although timberlands are likely to account for the bulk of changes in
carbon stocks on forest lands, there are likely to be other lands on which carbon
stocks are changing. Such lands might include, for example, marginal croplands that
have been planted with trees but that are in the early stages of regrowth so that they
have not yet been reclassified as forest land. In addition, the timberland statistics do
D10-16
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not include disperse tree planting in urban and suburban areas, along highways, etc.
(2) This method ignores carbon uptake on the regrowth of abandoned lands unless they
have been reclassified as forest lands.
(3) This method assumes that all of the carbon removed is oxidized during the period of
removal.
(4) All sources must be documented.
UNCERTAINTIES AND REFINEMENTS
There are a number of areas where the basic method could be improved. Simplifying
assumptions have been made in many places in order to produce methods that accommodate users
with different levels of available data. The basic calculations focus only on the most important
categories for emissions of CO2 within a much larger set of forest management and land-use activities
that impact greenhouse gas fluxes. Some activities are known to affect greenhouse gas fluxes, but
cannot be quantified because of scientific uncertainty. Many of these issues are summarized below
to assist state analysts in considering which, if any, of these possible refinements could be included
in state inventories, either currently, or as future scientific understanding improves. Possible
refinements or additions to basic categories could include:
Changes in Forests and Woody Biomass Stocks Section:
• Prescribed Burning of Forests: Non-CO2 Trace Gases. Prescribed burning is a method
of forest management by which forests are intentionally set on fire in order to reduce
the accumulation of combustible plant debris and thereby prevent forest fires (which
could possibly be even more destructive). Because carbon is allowed to re-accumulate
on the land after burning, no net CO2 emissions occur over time, although emissions
of CH4, CO, N2O, and NOX result from the biomass combustion. The matter of
prescribed burning is complex because of two issues. First, there is the question of
the rate of change that humans have induced and, second, there is the question of
releases of trace gases several years after the burning. Also, some scientists have
suggested that prescribed forest burning may actually increase carbon stocks in forests
and hence serve as a sink for CO2. Unless these uncertainties can be resolved by
state experts, it is suggested that activities associated with prescribed burning not be
included in the method.
• Soil Carbon. In the basic calculations, no soil carbon accumulation is assumed while
plantations are being established (or other tree planting activities are occurring) on
previously non-forested lands. If plantations are established where natural or
managed forests previously existed, then the carbon content of soils may not change
significantly. However, it is possible that the establishment of plantations on
previously non-forested lands could result in accumulation of soil carbon over time.
Further investigation may be useful to determine whether this is a significant enough
effect to warrant addition to the calculations. In addition, it is likely that different
forest management practices can affect soil carbon over long periods of time, as in
the case of agricultural activities.
D10-17
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Import and Export of Wood c.-id Wood Products. A significant portion of wood and
wood products, including lu iber, paper and paper products, furniture, etc., are
shipped across state lines ;, id internationally. This interstate and international
transfer of wood and wood products can potentially have a notable affect on current
existing stocks of woody biomass in a state. This issue should be addressed in a
manner similar to the import and export of energy and international bunker fuels, as
discussed in Workbook and Discussion Section 1. At this juncture, however, there
is no recommended manner for attributing emissions related to the interstate and
international transfer of woody biomass stocks. Also, developing a method for
estimating these emissions is hindered by a lack of appropriate data. For example, the
commercial timber industry has detailed statistics on activities associated with the
export of wood or the production and sale wood products, but state-by-state
consumption figures, especially for paper, paper products, and durable wood products,
such as furniture, are not well-maintained. This is an area that could benefit from
further research and improved consumption statistics.
Forest and Grassland Conversion
• Delayed Release ofNon-CO2 Trace Gases after Land Disturbance. An experiment in
a temperate northeastern forest in the U.S. found that clear-cutting resulted in
enhanced N2O flux to the atmosphere via dissolution of N2Q in the soil water,
transport to surface waters, and degassing from solution (Bowden and Borman, 1986).
Conversion of tropical forests to pasture has also been found to result in elevated
N2O emissions relative to intact forest soils (Luizao et al., 1989). Also, the loss of
forest area may result in increased net CH4 emissions to the atmosphere, because
soils are a natural sink of CH4 (i.e., soils absorb atmospheric methane). Various
experiments indicate that conversion of forests to agricultural lands diminishes this
absorptive capacity (Keller et al., 1990; Scharffe et al., 1990)
.Conversion of natural grasslands to managed grasslands and to cultivated lands may
not only affect the net emission of CO2, but CH4, N2O, and CO emissions as well.
For instance, the conversion of natural grasslands to cultivated lands has been found
in the semi-arid temperate zone to also decrease CH4 uptake by the soils (Mosier et
al., 1991). It is not clear what the effect on N2O would be, unless of course nitrogen
fertilization occurs. CO fluxes may be affected due to changes in soil temperature
and moisture. These effects on trace gas fluxes, however, are highly speculative.
• Fate of Roots in Cleared Forests. The basic calculation ignores the fate of living
belowground woody biomass (roots, etc.) after forest clearing. This belowground
biomass could be treated as slash, but' with perhaps a longer decay time.
Alternatively, it might be more reasonable to deal with the belowground biomass in
conjunction with soil carbon calculations, as both are likely to involve long time
horizons. This is an area for further development.
• Aboveground Biomass After Conversion. In the basic calculation, a single default value
(22.4 tons dm/acre) is recommended for aboveground biomass which regrows after
forests are cleared for conversion to crops or pastures. This may be somewhat
variable depending on the types of crop or other vegetation which regrows. State
experts carrying out more detailed assessments may wish to account more precisely
D10-18
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for this variability.
Abandoned Lands
• The basic calculations account for only the portion of abandoned lands which regrow
toward a natural state. There may be additional releases of carbon from abandoned
lands which continue to degrade. Where data are available, analysts doing detailed
calculations may wish to account for this phenomenon.
Other Lands
• Several other land-use activities affect the flux of CO2 and other trace gases between
the terrestrial biosphere and the atmosphere. For example, the changing areas and
distribution of wetlands may also be adding to or reducing the methane burden to the
atmosphere. Freshwater wetlands are a natural source of CH4, estimated to release
100 - 200 Tg CH4 per year due to anaerobic decomposition of organic material in the
wetland soils (Cicerone and Oremland, 1988). Destruction of freshwater wetlands,
through drainage or filling, would result in a reduction of CH4 emissions, and an
increase in CO2 emissions due to increased oxidation of soil organic material. The
magnitude of these effects is largely a function of soil temperature and the extent of
drainage (i.e., the water content of the soil). Also, since dryland soils are a sink of
CH4, drainage and drying of a wetland could eventually result in the wetland area
changing from a source to a sink of CH4. Loss of wetland area could also affect net
N2O and CO fluxes, although both the direction and magnitude of the effect is highly
uncertain. Some possible methodological approaches for estimating emissions from
freshwater wetlands can be found in IPCC Guidelines for National Greenhouse Gases
Inventories, Volume 3 (IPCC, 1994), if states are interested in estimating these
emissions. However, currently, no agreed-upon method exists for these source
categories.
Some experts have also indicated that changes in surface waters due to human
activities can result in sequestration of carbon, and presumably other emissions or
removals. An example is pollution of lakes due -to runoff, which can cause
eutrophication, increasing the carbon content of waters. Pollution of coastal waters
could also have similar effects. No data have been obtained thus far to indicate
whether the carbon sequestration effects of such changes are significant enough to
warrant inclusion in the method.
REFERENCES
Birdsey, Richard A. and L.S. Heath. 1993. Carbon Sequestration Impacts of Alternative Forestry
Scenarios. USDA Forest Service. Prepared for the Environmental Protection Agency. April,
1993.
Birdsey, Richard A. 1992. Carbon Storage and Accumulation in the United States Forest Ecosystems.
USDA Forest Service. General Technical Report WO-59.
D10-19
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Bowden, W.B. and F.H. Borman. 1986. "Transport and Loss of Nitrous Oxide in Soil Water after
Forest Clear-Cutting," Science. 233: 867-869.
Brown, S. and A.E. Lugo. 1990. "Tropical Secondary Forests," Journal of Tropical Ecology. 6: 1-32.
Cicerone, R.J. and R.S. Oremland. 1988. "Biogeochemical Aspects of Atmospheric Methane," Global
Biogeochemical Cycles. 2: 299-327
Daugherty, A-B. 1991. Major Uses of Land in the United States: 1987. U.S. Department of
Agriculture, Economic Research Service, AER No. 643. 35 pp.
Harmon, M.E., W.K. Ferrel and J.F. Franklin. 1990. "Effects on Carbon Storage of Conversion of
Old-Growth Forests to Young Forests," Science. 264: 699-702
IPCC. 1994. IPCC Guidelines for National Greenhouse Gas Inventories, 3 volumes: Vol. 1, Reporting
Instructions; Vol. 2, Workbook; Vol. 3, Draft Reference Manual. Intergovernmental Panel on
Climate Change, Organization for Economic Co-Operation and Development. Paris, France.
Keller, M., M.E. Mitre, and R.F. Stallard. 1990. "Consumption of Atmospheric Methane in Soils of
Central Panama: Effects of Agricultural Development," Global Biogeochemical Cycles. 4: 21-
27.
Luizao, F.P., P. Matson, .G. Livingston, R. Luizao, and P. Vitousek. 1989. "Nitrous Oxide Flux
Following Topical Land Clearing," Global Biogeochemical Cycles. 3: 281-285.
Mosier, A., D. Schimel, D. Valentine, K. Bronson, and W. Parton. 1991. "Methane and Nitrous
Oxide Fluxes in Native, Fertilized and Cultivated Grasslands," Nature. 350: 330-332.
Nabuurs, G.J. and G.M.J. Mohren. 1993. Carbon Fixation Through Forestation Activities. IBN
Research Report 93/4, Institute of Forestry and Nature Research, Wageningen, The
Netherlands.
Powell, D.S., J.L. Faulkner, D.R. Darr; Z. Zhu, and D.W. MacCleery. 1993. Forest Statistics of the
United States, 1992. USD A Forest Service. Report RM-234. September 1993.
Row, C. and R.B. Phelps. 1991. "Wood Carbon Flows and Storage After Timber Harvest," in
Proceedings Forests and Global Change. June 11-12, 1991, Arlington,' VA. American
Forestry Association.
Scharffe, D., W.M. Hao, L. Donoso, P.J. Crutzen and E Sanhueza. 1990. "Soil Fluxes and
Atmospheric Concentrations of CO and CH4 in the Northern Part of .the Guyana Shield,
Venezuela," Journal of Geophysical Research. 95: 22, 475-22, 480.
USDA/SCS (U.S. Department of Agriculture, Soil Conservation Service). 1989. Summary Report
1987: National Resources Inventory. Statistical Bulletin No. 790. Iowa State Statistical
Laboratory, USDA/SCS.
U.S. EPA. 1994. U.S. Inventory of Greenhouse Gas Emissions and Sinks: 1990 - 1993. U.S. EPA,
Office of Policy, Planning and Evaluation: EPA-230-R-94-014. September, 1994.
D10-20
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USFS (U.S., Forest Service). 1990. An Analysis of the Timber Situation in the United States: 1989 -
2040: A Technical Document Supporting the 1989'USDA Forest Service RPA Assessment.
Forest Service, United States Department of Agriculture. General Technical Report RM-
199.
USFS. 1982. An Analysis of the Timber Situation in the United States: 1952 - 2030. U.S. Department
of Agriculture, Forest Service. Forest Resource Report No. 23. December, 1982.
Waddell, Karen L., D.D. Oswald, and D.S. Powell. 1989. Forest Statistics of the United States, 1987.
U.S. Department of Agriculture, Forest Service. Resource Bulletin PNW-RB-168. 106 pp.
D10-21
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DISCUSSION 11
GREENHOUSE GAS EMISSIONS FROM BURNING
OF AGRICULTURAL CROP WASTES
OVERVIEW
Large quantities of agricultural crop wastes are produced from farming systems. There are
a variety of ways to dispose of these wastes. For example, agricultural residues can be plowed back
into the field, composted, landfilled, or burned in the field. Alternatively, they can be collected and
used as a biomass fuel or sold in supplemental feed markets. This section addresses field burning of
agricultural crop wastes. Field burning of crop wastes is not thought to be a net source of CO2
because the carbon released to the atmosphere during burning is reabsorbed during the next growing
season. Crop residue burning is, however, a net source of CH4, CO, N2O, and NOX, which are
released during combustion. In addition, field burning may result in enhanced emissions of N2O and
NOX many days after burning (Anderson et ai, 1988; Levine et a/., 1988), although this process is
highly uncertain and will not be accounted for in this section. Also, it should be noted that open
burning has been banned in some states. States affected by such regulations can ignore this section.
DESCRIPTION OF WORKBOOK METHOD
The methodology for estimating greenhouse gas emissions from field burning of agricultural
wastes is based on the amount of carbon burned, emission ratios of CH4 and CO to CO-, measured
in the smoke of biomass fires, and emission ratios of N2O and NOX to the nitrogen content of the
fuel. The methodology is presented, in workbook form in Workbook Section 11, and in more detail
below.
Four types of data are required to calculate the amount of carbon burned in agricultural
wastes.
• The amount of crops produced with residues that are commonly burned,
• The ratio of residue to crop product,
• The fraction of residue burned, and
• The carbon content of the residue. .
To avoid unrepresentative results based upon fluctuations in economic or climatic conditions, it is
recommended that a three-year average (centered on 1990) be used for crop production.
After obtaining the data listed above, the next step in estimating emissions from agricultural
waste burning is to multiply annual production data (in pounds) for each of the pertinent crops by
the ratio of residue to crop product for each crop, to generate the amount of residue available for
combustion. Estimates of residue/crop product ratios for certain crops are presented in Table Dll-1.
Next, to calculate the total tonnage of crop residue burned, the total amount of residue
produced, for each crop, is multiplied by the fraction of residue burned in the field. If in-state
estimates of the amounts of crop residues burned in situ, or in the field, are not readily available, it
is recommended that, a default value of 10 percent be used (U.S. EPA, 1994).
Dll-1
-------
Once the amount of crop residue burned is estimated, it must be converted to dry matter mass
units(dm). Dry matter refers to biomass in a dehydrated state. Default values for the percentage
of dry matter in crop residues are provided in table DH-l. For example, 200 tons of crop residue
with a dry matter content of 91.1 percent, would be equal to 182.2 tons dry matter.
After the total mass of crop residue burned is converted to mass of dry matter burned, the
figure must be multiplied by the carbon content per unit of dry matter of the residue to convert to
units of carbon. Carbon contents for selected crop residues are presented in Table Dll-1; an average
value of 0.45 Ibs Gib dm can be used in the cases where data are not available. The steps described
above can be combined into the following equation to calculate the total carbon burned:
Equation 1
v
Carbon Burned = Annual Crop Production (Ibs) x Residue/Crop Product Ratio x
Fraction of Residues Burned in situ (%) x Dry Matter Content of
the Residue (%) x Fraction Burned (%) x Carbon Content of the
Residue (Ibs C/lbs dm) 2
Once the total carbon burned is estimated, the emissions of CH4, CO, N2O, and NOX
can be calculated based on the methodology in Crutzen and Andreae (1990).
To calculate emissions of CH4 and CO due to burning of crop residue, the amount of carbon
burned (Equation 1) is multiplied by the fraction of carbon oxidized to CO2. Fraction oxidized is
defined as the fraction of carbon in the fire that is oxidized completely to CO2- The default value
for fraction oxidized is 0.88 to account for the approximate 12 percent of the carbon that remains
on the ground (Seiler and Crutzen, 1980; Crutzen and Andreae, 1990).3 The resulting figure (the
amount of carbon dioxide released instantaneously, in units of carbon (CO2-C)) is then multiplied
by the ratios of emissions of CH4 and CO relative to CO2 (see Table Dll-2)4 to yield emissions of
CH4 and CO (each expressed in units of C). The emissions of CH4 and CO are then multiplied by
16/12 and 28/12, respectively, to convert to full molecular weights.
1 According to Elgin (1991), the moisture content of crop residue varies depending on the type of crop
residue, climatic conditions (Le., in a humid environment the residue will retain more moisture than in an arid
environment), and the length of time between harvesting and burning of the residue.
2 Fraction burned is defined as the fraction of dry biomass exposed to burning that actually burns.
3 This estimate of the carbon exposed to burning that remains on the ground is probably some
combination of charcoal and unburned material that gets reincorporated into the soil during field preparation
for the next crop. The charcoal represents a long-term sink of carbon, and in a complete accounting of carbon
flows, would be treated as such. The unburned material represents carbon that may be reabsorbed by next
year's crops or emitted as CO2 or remain in the soil. The 12 percent estimate is highly uncertain; the fractions
of this estimate that are charcoal and unburned material have never been measured nor estimated. Because
of the uncertainty and lack of data surrounding these "carbon flows," no attempt will be made to incorporate
them in the methodology at this time.
4 Table Dll-2 provides suggested default values for non-CO2 trace gas emissions. These are presented
with ranges to emphasize their uncertainty.
Dll-2
-------
Table Dll-1
Selected Crop Residue Statistics
Product
Cereals
Wheat
Barley
Maize
Oats
Rye
Rice
Millet
Sorghum
Legumes
Pea
Bean
Lentils
Soya
Tuber and Root
Crops
Potatoes
Feedbeet
Sugarbeet
Jerusalem Artichoke
Peanut
Sugarcane
Residue/Crop
Product
1.3
1.2
1.0
1.3'
1.6
.1-4
1.4
8.0 '
1.5
2.1
2.1
2.1
0.4
0.4
0.3
0.8
1.0
0.8
Dry Matter
(%)
91.1
90.4
88
90.6
90
90 -
88.5
90
90.2
88.7
88.3'
89.3
86.7
86.7
90
90
90.1
90
Nitrogen/Carbon
Ratio (Ibs N/lbs C)
0.0082
0.0026
0.0172
0.0144
0.0144
0.0162
0.0144
0.0175
0.0511
0.0511 .
0.0511
0.0511
•
0.026
0.026
0.056
0.026
0.026
0.0064
Carbon Content
(% dm)
48.53
45.67
47.09 •
• 48.53
48.53
41.44
48.53
48.53
45
45
45
45
42.26
40.721
40.721
42.46
42.46
46.95
1 These statistics are for beet leaves.
Source: U.S. EPA, 1994.
To calculate emissions of N2O and NOX due to burning of crop residue, the amount of carbon
burned (Equation 1) is multiplied by the fraction of carbon oxidized to CO2 (i.e., 0.88) and the
nitrogen/carbon ratio (the N/C ratio of the fuel by weight; the nitrogen/carbon ratios of selected
residues are provided in table Dll-1). This yields the total amount of nitrogen released ((Crutzen
and Andreae, 1990); see Equation 2). The total N released is multiplied by the ratios of emissions
of N2O and NOX relative to the N content of the fuel (see Table Dll-2) to yield emissions of N2O
and NOX expressed in units of N. To convert to full molecular weights, the emissions of N2O and
Dll-3
-------
NOX are multiplied by 44/28 and 46/14, respectively/1
Equation 2
Nitrogen Released = Carbon Burned (Ibs C) x -Fraction Oxidized (%) x
Nitrogen/Carbon Content of the Residue (Ibs N/lbs C)
UNCERTAINTIES
The method presented here provides relatively crude estimates with substantial uncertainties.
Use of specific emission ratios, which vary by type of burning, region, etc., may allow, for more precise
calculations. The ratios presented here are based on measurements taken in a wide variety of fires.
In many cases, these ratios are general averages for all biomass burning. Research will need to be
conducted in the future to determine if more specific emission ratios, e.g., specific to the type of
biomass and burning conditions, can be obtained.. Also, emission ratios vary significantly between the
flaming and smoldering phases of a fire. CO2, N2O, and NOX are mainly emitted during the flaming
stage, while CH4 and CO are mainly emitted during the smoldering stage. The relative importance
of these two stages will vary between fires in different ecosystems and under different climatic
conditions, and so the emission ratios will vary.
Another issue that should be noted is that the basic calculations described here ignore the
contemporary fluxes associated with past burning activities. These releases are known to exist, but
are poorly understood at present. There are also other issues currently not treated in these
calculations. For example, long-term changes in soil carbon are certainly possible as a result of
agricultural practices. In fact, depending on the specific agricultural soil management practices used,
including burning, there may be a variety of effects on soil carbon. In fact, repeated burning of crop
residues in fields can cause an increase in the amount of carbon stored in the soil over time. The
effect of past burning on* current emissions is one such issues. The longer-term release and uptake
of these gases following burning is an important research issue and may be included in future
refinements of the calculations.
Table Dll-2. Emission Ratios for Biomass Burning Calculations
Compound
CH4
CO
N2O
NOX
Ratios
0.003
0.06 (0.04 - 0.08)
0.007 (0.005 - 0.009)
0.121 (0.094 - 0.148)
Source: Crutzen and Andreae, 1990.
Note: Ratios for carbon compounds, i.e., CH4 and CO, are mass of carbon compound released (in units
of C) relative to mass of ,CO2 released from burning (in units of C); those for the nitrogen compounds
are expressed as the ratios of emission relative to the nitrogen content of the fuel.
5 However, the numbers used to convert NOX emissions to full molecular weight are based on the
assumption that all of the NOX emissions are NO2, because NO is assumed to quickly oxidize to NO2 .
Andreae (1990) noted that NO is the primary form of NOX emitted during biomass combustion.
Dll-4
-------
REFERENCES
Anderson, I.C., J.S. Levine, M.A. Poth and P.J. Riggan. 1988. "Enhanced Biogenic Emissions of
Nitric Oxide and Nitrous Oxide Following Surface Biomass Burning." Journal of
Geophysical Research 93: 3893-3898.
Andreae, M.O. 1990. Biomass burning in the tropics: Impact on environmental quality and
global climate. Paper presented at the Chapman Conference on Global Biomass Burning:
Atmospheric, Climatic, and Biospheric Implication, 19-23 March 1990. Williamsburg,
Virginia.
Crutzen, P.J., and M.O. Andreae. 1990. Biomass burning in the tropics: Impact on atmospheric
chemistry and biogeochemical cycles. Science 250:1669-1678.
Elgin, J. 1991. National Program Leader for Forages and Pastures, U.S. Department of
Agriculture. Personal communication.
Levine, J.S., W.R. Cofer, D.I. Sebacher, E.L. Winstead, S. Sebacher, and P.J. Boston. 1988. "The
Effects of Fire on Biogenic Soil Emissions of Nitric Oxide and Nitrous Oxide.".Global
Biochemical Cycles 2: 445-449. December, 1988.
Seiler, W., and P.J. Crutzen. 1980. Estimates of gross and net fluxes of carbon between the
biosphere and the atmosphere from biomass burning. Climatic Change 2:207-247.
Strehler, A., and W. Stutzle. 1987. Biomass residues. In: Hall, D.O., and R.P. Overend (eds.).
Biomass: Regenerable Energy. John Wiley, Chichester. pp. 75-102.
USDA-ARS. 1992. Personal communication.
U.S. EPA. 1994. U.S. Inventory of Greenhouse Gas Emissions and Sinks: 1990 - 1993. U.S.
EPA, Office of Policy, Planning and Evaluation. EPA 230-R-94-014. September, 1994.
Dll-5
-------
DISCUSSION 12
METHANE EMISSIONS FROM
MUNICIPAL WASTEWATER
OVERVIEW
Disposal and treatment of industrial and municipal wastewater can produce emissions of most
of the important greenhouse gases. Wastewater can be treated using aerobic and/or anaerobic
technologies, or if untreated, can degrade under either aerobic or anaerobic conditions. Methane
is produced when organic material in treated and untreated wastewater degrades anae'robically. i.e.,
without the presence of oxygen. Highly organic wastewater streams such as waste streams from food
processing or pulp arid paper plants rapidly deplete available oxygen in the water stream as their
organic matter decomposes. The organic content, otherwise known as "loading" of these wastewater
streams, is expressed in terms of biochemical oxygen demand, or "BOD."1 BOD represents the
amounts of oxygen taken up by the organic matter in the wastewater during decomposition. Under
the same conditions, wastewater with higher BOD concentrations will produce more methane than
wastewater with relatively lower BOD concentrations. Most industrial wastewater has a low BOD
content, while food processing facilities such as fruit, sugar, meat processing plants, and breweries can
produce untreated waste streams with high BOD content.
Although recommended methodologies for estimating methane emissions from municipal and
industrial wastewater exist, the data required by these methodologies are not easily obtained. This
is especially true for data related to industrial wastewater. The methodology for estimating emissions
from industrial wastewater is presented here, but because of the difficulty in obtaining data,
estimating emissions from this source is optional and, therefore, is not presented in Workbook
Section 12.
DESCRIPTION OF WORKBOOK METHOD
Municipal Wastewater
To estimate methane emissions from municipal wastewater, the following steps are required:
1) obtain the required data on state population; 2) estimate biochemical oxygen demand (BOD5); 3)
estimate gross annual methane emissions; and (4) estimate net annual methane emissions. A detailed,
step-by-step description of the methodology is provided in Workbook Section 12.
The simple methodology for calculating emissions from municipal wastewater treatment is
based on BOD loading and relies on state-specific data. The data needed for using this approach
includes information on BOD5 per capita per day. If state-specific information is not available, a
default value of 0.1356 Ibs/capita/day can be used. State population data, the fraction of total
1 A standardized measurement of BOD is the "5-day test" denoted as BOD5. Under the same
conditions, wastewater with higher BOD concentrations will yield more CH4 than wastewater with
relatively lower BOD concentrations. Because of its influence on CH4, BOD is a commonly measured
parameter and in-state data on BOD loading rates should be available. If this is not the case, then a
default value of 0.1356 Ibs/capita/day can be used.
D12-1
-------
wastewater that is treated anaerobically (it in-state data are not available, a default value of 15
percent can be used), and the amount of methane that is recovered is also required. This information
can be plugged into equation 12-1 presented below to estimate emissions from this source.
(12.1) Methane Emissions from .Vunicipal Wastewater — Simplified Approach
Ibs CH. ( Ibs BOD
= (Population)
year (capita/day)'( yr )( Ibs BOD, j [ Digested j
ALTERNATE METHODOLOGY
Municipal Wastewater
A more detailed method exists to obtain more accurate emission estimates, but more detailed
data are required. Therefore, a more precise estimate of methane emissions from wastewater
treatment for a given state is possible,'if the Following additional data are available: (1) the different
wastewater treatment methods used in each state; (2) the total portion of wastewater that is treated
using each of these methods; and (3) the methane conversion factor (MCF) of each, of these
treatment methods (the MCF represents the extent to which the maximum methane producing
capacity of wastewater is realized for a given wastewater treatment system).
Where data are available, the following equation would be used to estimate methane
emissions:
(12.2) Methane Emissions from Municipal Wastewater — Complex Method
\
4
Ibs BODS j
Fraction Wastewater
Treated
Using Method(
(MCF for\
[Method,)
year {capita/day) \ >•*• )
Methane \
Recovered)
Unfortunately, many states may not have.data on the portion of wastewater treated using
different methods. Additionally, at this time, complete information on MCFs for different wastewater
treatment systems is not available. States which have more detailed information on specific methods
treatment and their corresponding MCFs are encouraged to use this information in preparing state
inventories.
Industrial Wastewater
To estimate methane emissions from industrial wastewater treatment, the following data are
required:
• Relevant industries within a state;
• Amount of wastewater outflow by industry;
D12-2
-------
• Concentration of organic material in the wastewater;
• BOD content of wastewater;
• Amount of wastewater anaerobically treated; and
• Methane recovered.
After the relevant data have been obtained, then emissions can be estimated in the same
manner as emissions from the treatment of municipal wastewater:
Step 1: Wastewater outflow by industry must be estimated. If these data are not directly
available, they may be estimated based on the production by industry, and waste consumed
per unit of product. Typical water consumption rates for some key industries are presented
in Table Dl 2-1.
Step 2: The BOD5 content of the wastewater for each product must be estimated. Default
BOD5 values are provided in Table D12-2.
Step 3: Estimate the fraction of wastewater from each industry that is treated anaerobically.
Unfortunately, default values are not available by industry.
Step 4: If anaerobic treatment with methane recovery is employed, the amount of methane
recovered should be subtracted from total emissions.
Step 5: Total methane emissions from this source are estimated by summing the methane
emission estimates for each industry across all relevant industries in the state.
The following equation summarizes the emissions calculation for industrial wastewater treatment:
(12.3) Methane Emissions from Industrial Wastewater — Simplified Approach
JL Ibs CH. (Wastewater Outflow] ( Ibs BOD.} (o.22 Ibs CH.\ ( Fraction \ I Methane \
y = \Anaerobicalfy -
if year ( by Industry } \ Gallon } ( Ibs BOD5 j I Treated } (Recovered)
As with methane emissions from municipal wastewater treatment, more precise estimates of
methane emissions from industrial wastewater treatment can be made if specific methods used to treat
wastewater flow from each industry are known and the MCFs for each method have been estimated.
If this information is available, the following equation can be used:
(12.4) Methane Emissions from Industrial Wastewater — Complex Method
Fraction Wastewater
JL Ibs CH4 _ (Wastewater Outflow} (ibs BODS} 0.22 Ibs CH4
if year { by Industry } ( Gallon } \ Ibs BOD,
( Methane }
{Recovered)
Treated
. Method,
Using Methodi
(MCF for\
D12-3
-------
UNCERTAINTIES
There is uncertainty in estimating emissions from wastewater due to a lack of data
characterizing wastewater management practices, the quantities of wastewater that are subject to
anaerobic conditions, the extent to which methane is emitted under anaerobic conditions, and flaring
or utilization practices. For example, methane production varies.depending upon temperature,
retention time. BOD loading, and lagoon maintenance and depth.2
Table D12-1. Water Consumption Per Unit for Selected Industries
Process
Canneries
Green Beans
Peaches and Pears
Other fruits and vegetables
Food and Beverage
Beer
Wine
Meat Packing
Pulp and Paper
Pulp
Paper
Textiles
Bleaching
Dyeing
Water Consumption
(Gallons/Ton)
19,174
5,273
5,752
14,381
4,794
4,314
156,991
47,936
83,888
14,381
Source: IPCC, 1994
2 Facultative and anaerobic lagoons are often used for storage and treatment. EPA estimated in 1987
that there were approximately 5,500 municipal waste stabilization lagoons in the U.S. The CH4 potential
from these lagoons is not well understood and little field data are available. Industrial and commercial
wastewater processes also use lagoons for treatment and storage. Facultative lagoons, the most common
type, treat wastewater by both anaerobic fermentation and aerobic processes. At the bottom of the lagoon,
where an anaerobic environment exists, organic matter is digested to CH4 and CO2. As these gases bubble
to the surface, much of the CO2 is absorbed by algae and is used, along with nutrients liberated during
digestion, to produce algal biomass. Aerobic conditions, supported by algae growth, are maintained near
the surface. Between 20 and 30 percent of the BOD loading to a facultative pond is anaerobically
metabolized. As BOD loading increases and natural surface aeration diminishes, facultative lagoons
proceed to a more anaerobic state. This results in higher CH4 production, providing that the temperature
is higher than 59°F. Under tnese conditions, a facultative lagoon may act more as an anaerobic pond, with
possibly 95 percent of the lagoon volume functioning anaerobically. Fermentation, and this CH4
production, is negligible at temperatures beknv about 59°F, at which point the lagoons serve principally as
a sedimentation tank.
D12-4
-------
Wastewater treatment is also now being studied as a source of N2O, although there is
currently no methodology to estimate N2O emissions from this source. The effluent of wastewater
treatment plants and all other waste that is disposed of in surface water can also lead to methane and
nitrous oxide emissions from inland and coastal waters. The same applies to untreated sewage or
excess manure and fertilizer application. Runoff can lead to surface water pollution and related
methane and nitrous oxide emissions. However, methods for estimating emissions from these sources
are not available at this time. Future evaluation of ongoing research will give an indication of the
importance of these sources and perhaps provide a method for use by states.
Table D12-2. BOD5 for Selected Industries
Industry
Iron and Steel
Non-Ferrous Metals
Fertilizer
Food and Beverage
Pulp and Paper
Petroleum Refining
Textile
Rubber
Miscellaneous
BOD,
(Ibs/gallon)
0.008
0.008
0.008
0.292
0.033
0.003
0.008
0.008
0.017
Source: IPCC, 1994.
REFERENCES
IPCC. 1994. IPCC Guidelines for National Greenhouse Gas Inventories, 3 volumes: Vol. I, Reporting
Instructions; Vol. 2, Workbook; Vol. 3, Draft Reference Manual. Intergovernmental Panel on
Climate Change, Organization for Economic Co-Operation and Development. Paris, France.
Thorneloe, S.A. 1992. "Emissions and Mitigation at Landfills and Other Waste Management
Facilities," Proceedings from EPA Symposium on Greenhouse Gas Emissions and Mitigation
Research,
Viessman, Jr. and M.J. Hammer. 1985. Water Supply and Pollution Control.
Publishers, New York, NY. 612.
Harper & Row
D12-5
-------
DISCUSSION 13
OTHER GREENHOUSE GAS EMISSIONS
FROM MOBILE COMBUSTION
OVERVIEW
This section discusses emissions of greenhouse gases from mobile sources, including carbon
monoxide (CO), nitrogen oxides (NOX), methane (CH4), nitrous oxide (N2O), and non-methane
volatile organic compounds (NMVOCs). The reader should note before proceeding with this section
that these calculations can be time consuming and complex. Moreover, the amount of gases emitted
from these activities are not thought to be major contributors to climate change. Additionally, data
on gases such as CO, NOX, and NMVOCs may already be collected by state environmental agencies
to determine state compliance with the Clean Air Act or other regulations. For these reasons a
methodology for this source category was not included in the workbook.
Emissions from mobile sources are most easily estimated by major transport activity, i.e., road,
air, rail, and ships. Several major fuel types need to be considered, including gasoline, diesel, jet fuel,
aviation fuel, natural gas, liquified petroleum gas, and residual fuel oil. Road transport accounts for
the majority of mobile source fuel consumption (e.g., U.S. demand for oil accounts for 50 percent of
the worldwide total), followed by air transport. This indicates that the primary emphasis in
developing emission factors should be placed on road vehicles, followed by aircraft.
If transport fuels (mostly composed of hydrocarbons [HC]) were completely combusted, the
only products emitted would be CO2 and H2O. However, under actual conditions, not all the fuel
is completely combusted, resulting in the formation of other gases. For example, motor vehicles emit
a large portion of total anthropogenic NOX emissions. NOX emissions are closely related to air-fuel
mixes and combustion temperatures, as well as pollution control equipment. For uncontrolled
vehicles, NOX emissions from diesel-fueled vehicles are generally lower than from gasoline-fueled
vehicles. In terms of tons of emissions per ton-mile transported, heavy duty vehicles (HDV) are more
efficient than light duty vehicles (LDV), but HDV still contribute a significant share of motor vehicle
NOX emissions. Moreover, HDV are more difficult to control than LDV and are generally subject
to less stringent emission control regulations.
The majority of CO emissions from fuel combustion comes from motor vehicles. CO
emissions, even more so than CH4 emissions, are a function of the efficiency of combustion and post-
combustion emission controls. Like CH4 emissions, CO emissions are highest when air-fuel mixtures
are "rich," with less oxygen than required for complete combustion. This occurs especially in idle, low
speed, and cold start conditions in spark ignition engines.
Methane emissions and NMVOCs from motor vehicles are a function of the methane content
of the motor fuel, the amount of hydrocarbons passing unburnt through the engine, and any post-
combustion control of hydrocarbon emissions, such as use of catalytic converters. The emissions of
unburned HC, including CH4, are lowest in uncontrolled engines when the quantity of hydrogen,
carbon, and oxygen are present in exactly the right combination for complete combustion (the
"stoichiometric ratio"). Thus, CH4 and NMVOC emissions will be determined by the air-fuel ratio.
They are generally highest in low speed and engine idle conditions. Poorly tuned engines may have
D13-1
-------
particularly high output of total HC, including CH4. Emissions are also strongly influenced by the
engine type and the fuel combusted.
For more information on greenhouse gas emissions from mobile.sources, the reader is referred
to Mark DeLuchi's Emissions of Greenhouse Gases from the Use of Transportation Fuels and
Electricity, published by the Argonne National Laboratory (November 1991).
DESCRIPTION OF METHOD
An estimation of mobile source emissions is a very complex undertaking that requires
consideration of many parameters, including information on such factors as:
• transport class
• fuel consumed
• operating characteristics
• emission controls
» maintenance procedures
• fleet age
• other factors
The need for data on several parameters and the wide variety of conditions that can affect the
performance of each category of mobile sources makes it very difficult to generalize the emission
characteristics in this area.
Nevertheless, a minimum emission estimation methodology, as discussed below, is suitable as
a starting point for states to establish emissions estimations. In fact, the complexity of this issue
makes it difficult even for states with extensive experience to develop highly-precise emission
inventories. As such, it may be appropriate to avoid excessive complexity with any starting emission
estimation methodology.
In order to develop a minimum estimation method for greenhouse gas emissions from mobile
sources, basic information is required on the types of fuels consumed in the transport sector, the
combustion technologies that are used to consume the fuels, operating conditions during combustion,
and the extent of emission control technologies employed during and after combustion. The basic
approach for estimating these emissions is presented in the following equation:
Emissions = 2_/ (EFabc x Activityabc)
where Emissions are in pounds of pollutant;
EF = emissions factor (Ibs/mile, Ibs/toh fuel, or lbs/106 Btu);
Activity = amount of energy consumed (miles, tons fuel, or 106 Btu);
a = transport mode (rail, road, air, water);
b = fuel type (diesel, gasoline, LPG1, etc.); and
c = vehicle type (passenger car; light duty truck, train, etc.).
LPG refers to liquified petroleum gas.
D13-2
-------
Basic Methodology
Using tnis general equation, the following basic steps are required to estimate mobile source
emissions:
Step 1: Determine the amount of energy consumed by energy type for all mobile sources
using data from state energy or transportation agencies, the U.S. EPA, U.S. DOE, or
other data sources (all values sho.uld be reported in million Btu).
Step 2: For each energy type, determine the amount of energy that is consumed by each
vehicle and technology type, e.g., gasoline passenger cars, light-duty diesel trucks, etc.
(all units are in million Btu).
Step 3: Determine the percentage of each vehicle type that has some form of emission
control technology. If only a portion of the energy consumed by a particular vehicle
type has emission control technology, then only the energy attributable to this portion
of the vehicle stock should be identified as subject to emission controls.
Step 4: Multiply trie nount of energy consumed by each vehicle type by the appropriate
emissions factors from Tables D13-2 through D13-12. If some or all of a vehicle type
uses emission controls (as determined in the previous step), emissions factors for
these portions should reflect the appropriate level of emission control. For example,
the NOX emission factor for energy consumed by gasoline passenger cars using three
way catalyst control would be 0.0018 Ibs/mile.
Step 5: To obtain total emissions from mobile sources, sum vehicle/technology emissions
estimates across all fuel and technology type categories, including all levels of emission
control.
Regardless of the specific methodology that is used to determine emissions, it is important
to remember that there is a substantial amount of uncertainty surrounding the estimation of emissions
from mobile sources, much of which is a result of uncertainty in emission factors. Some means should
be developed to rank the differences in data quality and the uncertainties affecting emission
estimates. This may involve the use of standard deviations, ranges of uncertainty, or some other
means of indicating to the data consumer the relative reliability of the data.
Emission Factors
This section presents mobile source emission factors for gases contributing to global warming.
Emission factor estimates have been developed for CO, NOX, N2O, methane, and non-methane VOCs
for several classes of highway vehicles, railway locomotives, ships and boats, farm and construction
equipment, and aircraft. This discussion is taken from Weaver and Turner (1991). States are highly
encouraged to identify and discuss with in-state experts if more appropriate in-state emission factors
are.available.
Highway Vehicles - Conventional Fuels
Technical Approach. The emissions estimates developed for NOX, CO, methane, and
NMVOCs from highway vehicles were based on the U.S. EPA's MOBILE4 model (EPA, 1989). This
D13-3
-------
model, the most widely used emission factor model in the U.S., reflects more than a decade of devel-
opment, and incorporates the results of emissions tests on more than 10,000 vehicles in customer use
performed over the last 20 years.2 In addition to testing under standard conditions, many of these
tests have included emissions measurements at other temperatures, with different grades of fuel, arid
under different driving cycles. Much less effort has been expended on testing and modeling of heavy-
duty vehicle emissions than those from light-duty vehicles, so that the emission factor estimates for
these vehicles are considered less reliable.
MOBILE4 calculates exhaust emission factors for U.S. vehicles using gasoline and diesel fuel.
based on the year in which they were manufactured. For gasoline vehicles, it also calculates VOC
emissions due to evaporative, running, and refueling losses (VOC emissions from diesel vehicles due
to these causes are negligible). To develop emissions estimates for different emission control
technology types, calculations were carried out for specific model years during which U.S. vehicles
were equipped with the technology in question. To reflect normal in-use deterioration over the
vehicle's life, emissions were calculated for each vehicle type when they were five years old, or
approximately halfway through their useful lives. For example, estimates of uncontrolled passenger
vehicle emissions were based on MOBILE4 results for model year 1963 vehicles in calendar year
1968, when they would be five years old. Similarly, emissions estimates for advanced-technology
vehicles were based on 1990 U.S. model vehicles, calculated under 1995 operating conditions. Table
D13-1 shows the correlation between technology types and the U.S. model years used to represent
them in the model.
The emission factors calculated by MOBILE4 are affected by the assumptions regarding aver-
age speeds, ambient temperature, diurnal temperature range, altitude, and fuel volatility that are used
in the model. They are also affected by the assumed presence or absence of inspection/maintenance
and anti-tampering programs. Since it would not be possible to represent the state diversity in these
conditions in a single set of factors, the conditions chosen for the modeling were "typical" values of
75 °F, with a diurnal range from 60 to 85 °F (24±8 °C), and Reid vapor pressure of gasoline at 9.0
PSI (62 kPa). Average speed was taken as the MOBILE4 default of 19.5 mph, typical of
uncongested urban driving.
Changes in these input assumptions would change the resulting emission factors. Exhaust
pollutant emission factors increase markedly at low temperatures, while evaporative VOC emissions
decrease with temperature. Exhaust emissions in Ibs/mile also tend to rise with decreasing average
speed, due mostly to the increase in fuel consumption/mile. Evaporative VOC emissions tend to in-
crease with increasing gasoline volatility and increasing diurnal temperature range.
In order to reflect the emissions control potential of the different technologies, we assumed
an effective inspection/maintenance and anti-tampering program, which would help to assure that the
vehicle emission controls were in place and functioning as designed. This assumption may result in
some under-estimation of actual emissions from emission-controlled vehicles, since not all vehicles
are subject to such effective standards.
The estimated vehicle fuel economies were also used to calculate fuel-specific (Ibs/ton fuel)
and energy-specific (lbs/106 Btu) emission factors for all of the pollutants. Since emissions and fuel
consumption tend to vary in parallel (vehicles and operating modes causing high emission rates also
2 A new version of this model, MOBILES, has recently been introduced. Information from MOBILES
was not readily available at the time this report was prepared.
D13-4
-------
tend to result in high fuel consumption, and vice
versa), these energy-specific emission factors are
expected to be more generally applicable than the
factors in Ibs/mile, and use of these factors rather
than the Ibs/mile values is recommended.
Since MOBILE4 does not estimate N2O
emissions, it was necessary to develop separate
estimates of these. N2O formation in internal
combustion engines is not yet well understood,
and data on these emissions are scarce. It is
believed, with substantial evidence, that N2O
emissions come from two distinct processes. The
process occurs during the actual combustion
process in the cylinder. It is believed that the
major contributor is the interaction of NO with
combustion intermediates such as NH and NCO.
This N2O is then very rapidly removed in the
post-flame gas by the reaction between N2O and
hydrogen. While a significant amount of N2O
may be formed in the flame, it can only survive if
there is very rapid quenching of the gases, which
is not common. Thus, only very small amounts of
N2O are produced as engine-out emissions.
The N2O forming process occurs during
catalytic aftertreatment of exhaust gases. Otto,
Shelef, and Kummer (1970) have shown that N2O
is produced during the reaction of NO and NH3
over the platinum in the catalytic converter. The
order of magnitude for the maximum NO
conversion into N2O was about 5 to 10 percent.
The output of N2O from the catalyst is highly
temperature dependent. Prigent and De Soete
(1989) showed that as the catalyst warmed up
after a cold start, N2O levels increased heavily
(4.5 times the inlet value) at around 360°C. The
emissions then decreased to the inlet level at a
catalyst temperature of 460°C. Above this
temperature there is less N2O from the catalyst
downstream than upstream. N2O emissions are
thus formed primarily during cold starts of
catalyst-equipped vehicles. Comparison of N2O
emissions data 'for the U.S. Highway Fuel
Economy Test (HFET) with that for the Federal
Test Procedure (FTP) shows much lower N2O
emissions. The FTP contains a cold-start phase,
Table D13-1: Emission Control Technology
Types and U.S. Vehicle Model Years Used to
Represent Them.
Technology
Model
Year
Gasoline Passenger Cars and Light
Trucks
Uncontrolled
Non-catalyst controls
Oxidation catalyst
Early three-way catalyst
Advanced three-way catalyst
1963 .
1972
1978
- 1983
1990
Heavy-Duty Gasoline Vehicles
Uncontrolled
Non-catalyst control
Three-way catalyst
1968
1983
1991
Diesel Passenger Cars and. Light Trucks
Uncontrolled
Moderate control
Advanced control
1978
1983
1990
Heavy Duty Diesel Vehicles
Uncontrolled
Moderate Control
Advanced control
1968
1983
1991
Motorcycles
Uncontrolled
Non-catalyst controls
1972
, 1990
while the HFET does not.
Several methods were used to estimate N2O emission factors for this study. Prigent and De
Soete (1989), Dasch (1991), Ford (1989-1991), and Warner-Selph and Smith (1991) gave N2O
D13-5
-------
emissions for light-duty gasoline vehicles equipped with different catalyst technologies. The different
catalyst types were divided into four groups: uncontrolled, oxidation catalyst, early three-way catalyst,
and modern three-way catalyst technologies. The FTP emissions data from these studies were
combined and averaged to determine the mean N2O emissions from light-duty vehicles equipped with
each technology. These numbers were used directly to estimate N2O emissions from gasoline
passenger cars. For light-duty gasoline trucks and motorcycles, fuel-specific N2O emissions were
assumed to be the same as for the corresponding passenger car technology. N2O emissions per
kilometer were then calculated from the fuel-specific emissions and the fuel consumption
characteristics for each class.
No data on N2O emissions from heavy-duty gasoline trucks were available. Therefore, since
the engines used in these vehicles are fairly similar to those in passenger cars, it was decided to
approximate the N2O emissions by assuming that emissions per unit of fuel burned would be similar
to those for passenger cars having similar technology. However, since these trucks undergo a heavier
duty cycle, and experience fewer cold-starts, it was considered more appropriate to use N2O emission
factors based on the U.S. highway fuel economy test (HFET) rather than the cold-start FTP
procedure. Fuel-specific emissions N2O emissions for passenger cars in the HFET procedure were
obtained from the same data sources listed above.
Dietzmann, Parness, and Bradow (1980) reported N2O emissions data for four heavy-duty
diesel trucks, including a range of representative engines. The average of these data was used directly
as the N2O emission factor for heavy-duty diesel vehicles. No N2O emissions data were available for
light-duty diesel vehicles. N2O emissions for diesel passenger cars and light-duty trucks were
estimated by assuming the same fuel-specific emission rates as for heavy-duty diesels.
Light-duty gasoline passenger cars. The U.S. EPA considers a passenger car to be any vehicle
with rated gross vehicle weight less than 8,500 Ib (3,855 kg) designed primarily to carry 12 or fewer
passengers, and not possessing special features such as four wheel drive for off-road operation. Table
D13-2 summarizes the estimated emission factors for gasoline passenger cars. Estimates for five levels
of gasoline-vehicle control technology are shown. These technology levels range from completely
uncontrolled (still typical of most vehicles around the world) through non-catalyst emission controls,
oxidation catalysts, and two levels of three-way catalyst control. Non-catalyst emission controls
include modifications to ignition timing and air-fuel ratio to reduce emissions, exhaust gas
recirculation (EGR), and air-injection into the exhaust manifold. Oxidation catalyst systems normally
include many of the same techniques, plus a two-way catalytic converter to oxidize HC and CO. The
"early" three-way catalyst results are representative of those for vehicles sold in the U.S. in the early
to mid '80s, which were mostly equipped with carburetors having electronic "trim". The "advanced"
three-way catalyst values are based on current U.S. technology vehicles, using electronic fuel injection
under computer control.
Light-duty gasoline trucks. Light-duty trucks are defined as vehicles having rated gross vehicle
weight less than 8,500 Ib (3,855 kg), and which are designed primarily for transportation of cargo or
more than 11 passengers at a time, or which are equipped with special features for off-road operation.
They include most pickup trucks, passenger and cargo vans, four-wheel drive vehicles, and derivatives
of these. The engine and other technologies used in these vehicles are basically similar to those used
in passenger cars, but these vehicles usually have larger engines, poorer fuel economy, and somewhat
higher emissions. Table D13-3 summarizes the estimated pollutant emissions for this vehicle class.
The technology classifications used are the same as those for gasoline passenger vehicles.
D13-6
-------
Table D13-2: Estimated Emissions Factors for Gasoline Passenger Cars
EMISSIONS
NOX
CH4
NMVOC
CO
N,0
Advanced Three-Way Catalyst Control
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/106 Btu
0.0018
' 0.0018
15..88
0.398
0.00007
0.00007
0,64
0.016
0.0023
0.0009
0.0004
0.0005
0.0005
20.96
0.530
0.0111
0.0111
99.74
2.497
0.00007
0.00007
0.60
0.015
Early Three-Way Catalyst
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/10* Btu
0.0018
0.0018
12.98
0.331
0.00014
0.00014
1.00
0.025
0.0024
0.0009
0.0004
0.0006
0.0005
16.72
0.420
0.0111
0.0111
77.86
1.945
0.00016
0.00016
1.14
0.029
Oxidation Catalyst
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/10* Btu
0.0056
• 0.0056
25.26
0.641
0.00032
0.00032
1.42
0.036
0.0062
0.0040
0.0007
0.0007
0.0008
27.80
0.707
0.0461
0.0461
206.14
5.171
0.00010
0.00010
[ 0.42
0.011
Non-Catalyst Control
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/10* Btu
0.0070
0.0070
31.28
0.796
0.00062
0.00062
2.76
0.069
0.0112
0.0076
0.0016
0.0010
0.0010
50.02
1.260
0.0844
0.0844
377.97
' 9.502
0.000018
0.000018
0.08
0.002
Uncontrolled
Total - Ibs/mile
Exhaust
Evaporative
Refueling
I Running loss
Ibs/ton fuel
lbs/106 Btu
0.0076
0.0076
33.98
0.862
0.00062
0.00062
/
2.76
0.069
0.0225
0.0155
0.0049
0.0010
0.0011
100.54
2.519
0.1441
0.1441
645.11
16.198
0.000018
0.000018
0.08
0.002
D13-7
-------
Table D13-3: Estimated Emission Factors for Light-Duty Gasoline Trucks.
EMISSIONS
NOX
CH4
NMVOC
CO
N2O
Advanced Three-Way Catalyst Control
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/106 Btu
0.0024
0.0024
16.72
0.420
0.00014
0.00014
1.00
0.025
0.00266
0.00142
0.00035
0.00071
0.00014
. 18.72
0.464
0.0166
0.0166
116.80
2.939
0.000085
0.000085
0.60
0.015
Early Three-Way Catalyst;
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/106 Btu
0.0035
0.0035
18.16
0'.464
0.00025
0.00025
1.28
0.032
0.00415
0.00277
0.00046
0.00075
0.00014
21.24
0.530
0.0327
0.0327
167.52
4.199
0.000224 '
0.000224
1.14
0.029
Oxidation Catalyst
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/106 Btu
0.0057
0.0057
22.06
0.552
0.0003
0.0003
1.22
r 0.031
0.0069
0.0043
0.0008
0.0010
0.0008
26.54
0.663
0.0431
0.0431
165.40
4.154
0.00011
0.00011
0.42
0.011
Non-Catalyst
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/106 Btu
0.0100
0.0100
38.38
0.972
0.0006
0.0006
2.36
0.059
0.0161
0.0107
0.0032
0.0012
0.0010
61.94
1.547
. 0.1022
0.1022
392.17
9.856
0.00002
0.00002
0.08
0.002
Uncontrolled
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/106 Btu
0.0093
0.0093
35.80
0.906
0.0006
0.0006
2.36
0.059
0.0303
0.0177
0.0104
0.0011.
0.0011 j
116.26
2.917
0.1581
0.1581
606.45
15.225
0.00002
0.00002
0.08
0.002
D13-8
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Table D13-4: Estimated Emission Factors for Heavy-Duty Gasoline Vehicles.
EMISSIONS
NOX
CH4
NMVOC
CO
N2O
Three-Way Catalyst Control
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/10' Btu
0.0094
0.0094
20.14
0.508
0.00035
0.00035
0.76
0.022
0.00557
0.00244
0.00115
0.00121
0.00078
11.98
0.309
0.0299
0.0299
64.32
1.613
0.00002
0.00002
0.04
0.001
Non-Catalyst Control
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/106 Btu
. 0.0122
0.0122
25.96
0.641
0.00062
0.00062
1.30
0.022
0.0179
0.0077
0.0078
0.0013
0.0011
16.24
0.398
0.1427
0.1427
302.64
7.602
0.00002
0.00002
0.04
0.001
Uncontrolled
Total - Ibs/mile
Exhaust
Evaporative
Refueling
Running loss
Ibs/ton fuel
lbs/106 Btu
0.0203
0.0203
31.08
0.773
0.0013
'0.0013
2.04
0.044
0.0644
0.0409
0.0204
0.0020
0.0011
98.88
2.475
0.5078
0.5078
779.35
19.579
0.00003
0.00003
0.04
0.001
Heavy-duty gasoline vehicles. A heavy-duty vehicle is defined as one having a manufacturer's
gross vehicle weight rating exceeding 8,500 Ib (3,855 kg). In the U.S., this includes a number of
models of large pickups and vans, along with specialized trucks using pickup and van chassis, as well
as the larger "true" heavy-duty trucks, which typically have gross vehicle weight ratings of eight short
tons or more. In the U.S., the large pickups and vans in this category greatly outnumber the heavier
trucks, so that the emission factors calculated by MOBILE4 are more representative of these vehicles.
This is also reflected in the fuel economy estimate for these vehicles of 6.1 miles/gal. The resulting
emissions estimates are shown in Table D13-4.
D13-9
-------
Estimates were developed for three levels of emission control, technology: uncontrolled, non-catalyst
emission controls, and three-way catalyst technology. Non-catalyst emission controls include control
of ignition timing and air-fuel ratio to minimize emissions, EGR, and air injection into the exhaust
manifold to reduce HC and CO emissions. Three-way catalyst technology is presently used on heavy-
duty gasoline vehicles in the U.S. It includes electronically-controlled fuel injection, EGR, air
injection, and electronic control of ignition timing, as well as the catalyst itself.
Table D13-5: Estimated Emission Factors for Diesel Passenger Gars.
EMISSIONS
NO,
CH4
NMVOC
CO
N2O
Advanced Control
Total - Ibs/mile
Ibs/ton fuel
lbs/10'Btu
0.0023
16.08
0.420
0.000035
0.24
0.007
0.0010
7.18
0.186
0.0031
21.28
0.552
0.000025
0.16
0.004
Moderate Control
Total - Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0033
14.72
0.376
0.000035
0-16
0.004
' 0.0010
4.60
0.119
0.0031
13.62
0.354
0,000035
0.16
0.004
Uncontrolled
Total - Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0036
12.10
0.309
0.000035
0.12
0.002
0.0018
6.18
0.161
0.0038
12.58
0.331
0.00005
0.16
0.004
Light-duty diesel passenger cars. The U.S. EPA defines a diesel passenger car similarly to its
gasoline counterpart, as a vehicle designed primarily to carry fewer than 12 passengers, and with
manufacturer's rated gross vehicle weight less than 8,500 Ib (3,855 kg), and not possessing special
features such as four wheel drive for off-road operation. Table D13-5 summarizes the estimated
emission factors for diesel passenger cars. Estimates are shown for three levels of emission control
technology, ranging from uncontrolled, through moderate emissions control (achieved by changes in
injection timing and combustion system design), through advanced emissions control utilizing modern
electronic control of the fuel injection system, and exhaust gas recirculation.
Light-duty diesel trucks. Again, the U.S. EPA defines light-duty diesel trucks much like their
gasoline counterparts, including gross vehicle weight, utility, and off-road operation features. Table
D13-6 summarizes the estimated pollutant emissions for this vehicle class. The technology
classifications are the same as those for diesel passenger cars.
Heavy-duty diesel vehicles. Although the EPA classification for heavy-duty diesel vehicles is
the same as for gasoline vehicles, the characteristics of the vehicles themselves are rather different.
Unlike heavy-duty gasoline vehicles, heavy-duty diesel vehicles are primarily large trucks, with gross
vehicle weight ratings of 10 to 40 tons. Therefore, the MOBILE4 emission factors are more
representative of large trucks (and buses) than the smaller pickup and van-type vehicles, and this is
reflected in the fuel economy estimates. The resulting emission factors are summarized in Table D13-
7. As with the other diesel categories, thret levels of control are represented: uncontrolled, moderate
control (typical of 1983 U.S.) and advanced control (for engines meeting U.S. 1991 emissions stan-
dards).
Motorcycles. Estimated emission factors for motorcycles are shown in Table D13-8. The
MOBILE4 emission factors for these vehicles are based on the U.S. motorcycle population. The
D13-10
-------
Table D13-6: Estimated Emission Factors for Light-Duty Diesel Trucks.
EMISSIONS
NO,
CH4
NMVOC
CO
N,O
Advanced Control
Total - Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0027
13.54
0.354
0.000035
0.18
0.005
0.0015
7.48
0.199
0.0035
17.46
0.464
0.000032
0.16
0.004
Moderate Control
Total - Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0037
12.34
0.331
0.000035
0.12
0.003
0.0015
4.98
0.133
0.0035
11.64
0.309
0.00005
0.16
0.004
Uncontrolled
Total - Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0051
14.34
0.376
0.00007
0.20
0.000
0.0029
8.22
•0.221
0.0057
15.92
0.420
0.00006
0.16
0.004
Table D13-7: Estimated Emission Factors for Heavy-Duty Diesel Vehicles.
EMISSIONS
NOX
CH4
NMVOC
CO
N,O
Advanced Control
Total - Ibs/mile
Ibs/ton fuel .
lbs/106 Btu
0.0178
32.54
0.840
0.0002
0.38
0.011
0.0045
8.18
0.221
0.0241
44.18
1.149
0.00009
0.16
0.004
Moderate Control
Total - Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0424
76.82
1.989
0.00025
0.46
0.022
0.0060
10.94
0.287
0.0294
53.28
1.392
0.00009
0.16
0.004
Uncontrolled
Total - Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0596
85.72
2.232
0.00035
0.52
0.022
0.0106
15.26
0.398
0.0303
43.60
1.127
0.00011
0.16
0.004
factors for uncontrolled motorcycles include a mixture of two-stroke and four-stroke engines, with
the VOC emissions due primarily to the two-strokes, and the NOX to the four-stroke engines. The
factors for motorcycles with non-catalyst emission controls reflect four-stroke engines only, as U.S.
emission control regulations have essentially eliminated two-stroke engines from the market.
Highway Vehicles - Alternative Fuels
Alternative motor vehicle fuels such as natural gas, LP gas, methanol, and ethanol are
presently being used in a limited way, and are the subjects of a great deal of research and
development effort aimed at increasing their usage in the future. These fuels are considered
attractive for a number of reasons, including potentially lower pollutant emissions, reductions in
emissions of gases contributing to global warming, and increased diversity of fuel supply. Since the
number of vehicles using these fuels is relatively small, and they are, in many cases, still under
development, little information is available on typical pollutant emission levels in service. MOBILE4
D13-11
-------
Table O13-8: Estimated Emission Factors for Motorcycles.
EMISSIONS
NO,
CH4
NMVOC
CO
N,O
Non-Catalytic Control
Total - Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0019
21.04
0.530
0.0005
5.96
0.155
0.0078
85.80
2.143
0.0468
521.99
13.038
0.000007
0.08
0.002
Uncontrolled
Total - Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0007
6.46
0.155
0.0012
11.20
0.287
0.0231
222.00
5.524
0.0844
809.99
20.330
0.000007
0.08
0.002
and other emissions models do not yet address alternative-fuel vehicles. This section presents some
rough estimates of the emissions to be expected from vehicles using these fuels, based on fuel
properties and the limited emissions data available. The reader is cautioned, however, that actual
emission levels from these vehicles may be very different, and further testing would be needed to
confirm these estimates.
Natural gas. Because natural gas is mostly methane, natural gas vehicles (NGVs) have lower
exhaust NMVOC emissions than gasoline vehicles, but higher emissions of methane. Since the fuel
system is sealed, there are no evaporative or running-loss emissions, and refueling emissions are
negligible. Cold-start emissions from NGVs are also low, since cold-start enrichment is not required,
and this reduces both NMVOC and CO emissions. NGVs are normally calibrated with somewhat
leaner fuel-air ratios than gasoline vehicles, which also reduces CO emissions. Given equal energy
efficiency. CO2 emissions from NGVs will be lower than for gasoline vehicles, since natural gas has
a lower carbon content per unit of energy. In addition, the high octane value for natural gas
(Research Otane Number [RON] of 120 or more) makes it possible to attain increased efficiency
by increasing the compression ratio. Optimized heavy-duty NGV engines can approach diesel
efficiency levels. NOX emissions from uncontrolled NGVs may be higher or lower than comparable
gasoline vehicles, depending on the engine technology. Due to the low reactivity of the exhaust,
NGV NOX emissions are more difficult to control using three-way catalysts. Data on N2O emissions
from NGVs are not available, but probably resemble those for gasoline vehicles.
Table D13-9 shows very rough emissions estimates for three types of NGVs: passenger cars,
gasoline-type heavy-duty vehicles, and diesel-type heavy-duty vehicles. Two sets of emission factors
are shown for each: uncontrolled (typical of a simple natural gas conversion, without catalytic
converter or optimization for emissions) and advanced control (reflecting an engine and catalytic
converter factory-produced and optimized for natural gas). The estimates for the passenger car and
gasoline-type heavy duty vehicle are based on a gasoline-type engine, converted to use natural gas.
For the uncontrolled vehicles, no changes in the engine are assumed beyond the fitting of a natural
gas mixer and modified spark timing such that the efficiency would be the same. For the vehicles
with advanced control, a higher compression ratio is assumed to give 15 percent better fuel efficiency.
For the diesel-type heavy-duty vehicles, the engine assumed is a diesel-type engine, converted
to lean. Otto-cycle operation using natural gas. The uncontrolled case reflects no further
optimization beyond the conversion, while the controlled case includes extensive combustion
optimization for NOX control and an oxidation catalytic converter.
D13-12
-------
Table D13-9: Estimated Emission Factors for Light- and Heavy-Duty Natural Gas Vehicles.
EMISSIONS
NO,
CH< .
NMVOC
CO
N,O
Passenger Car
Advanced Control
Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0018
20.60
0.44
0.0025
29.00
0.61
0.00018
2.00
0.042
0.0011
12.40 •
0.25
N/A
N/A
N/A
Uncontrolled
Ibs/mile
Ibs/ton fuel
lbs/10* Btu
0.0075
38.00
0.80
0.0124
63.20
1.32
0.0018
9.00
0.19
0.0142
72.20
1.51
. N/A
N/A
N/A
Heavy-Duty Vehicles: Stoichiotnetric
Advanced Control
Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0092
26.00
0.54
0.0106
30.00
0.63
0.0007
2.00
0.042
0.0035
10.00
0.21
N/A
N/A
N/A
Uncontrolled
Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0202
34.80
0.73
0.0355
61.20
T.28
0.0050
8.60
0.19
0.0426
73.40
1.53
N/A
N/A
N/A
Heavy-Duty Vehicles: Lean Burn Engine
Advanced Control
Ibs/mile
Ibs/ton fuel
lbs/10* Btu
0.0142
26.60
0.57
0.0142
26.60
0.57
0.0014
2.60
0.063
0.0053
10.00
0.21
N/A
N/A
N/A
Uncontrolled
Ibs/mile
Ibs/ton fuel
lbs/10* Btu
0.0816
127.80
2.68
-•0.0355
55.60
1.17
0.0071
11.20
0.23
0.0284
44.40
0.92
N/A
N/A
N/A
In each case, the emissions considered are only those of the vehicle itself-additional emissions
due to, e.g., compression or liquefaction of gas for storage on the vehicle, leakage from pipelines, etc.
are not included, nor are the potential emissions credits due to, e.g., production of methane from
biomass. .
LP gas. LPG has many of the same emissions characteristics as natural gas. The fact that
it is primarily propane (or a propane/butane mixture) rather than methane affects the composition
of exhaust VOC emissions, but otherwise the two fuels are similar. Evaporative and refueling
emissions are nil, and CO and exhaust NMVOC emissions are usually lower than gasoline vehicles.
CO2 emissions should be somewhat lower than gasoline, due to the lower carbon-energy ratio, and
the higher octane allows some increase in efficiency, although less than for natural gas. NOX
emissions from LPG vehicles tend to be higher than for gasoline, but can also be controlled using
three-way catalysts. N2O emissions data are not available, but should be similar to those for gasoline
vehicles. Table D13-10 shows rough emissions estimates for four categories of LPG vehicles. The
engines and technologies considered are the same as those for natural gas, except that the lean,
diesel-derived natural gas engine with propane is not considered.
D13-13
-------
Table D13-10: Estimated Emission Factors for Light- and Heavy-Duty LP Gas Vehicles.
EMISSIONS
NOX
CH4
NMVOC
CO
N2O
Passenger Car
Advanced Control
ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0018
17.60
0.420
0.00007
0.80
0.022
0.0009
8.80
0.221
0.0011
10.60
0.243
N/A
N/A
N/A
Uncontrolled
Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0075
35.40
0.840
0.00064
3.00
0.066
0.0124
59.00
1.414
0.0284
135.00
3.204
N/A
N/A
N/A
Heavy-Duty Vehicles: Stoichiometric
Advanced Control
Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0092
22.40
0.530
0.00035
0.80
0.022
0.0025
6.00
0.155
0.0035
8.60
0.199
N/A
N/A
N/A
Uncontrolled
Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0202
33.60
0.796
0.0014
2.40
0:066
0.0284
47.00
1.127
0.0851
141.20
3.359
N/A
N/A
N/A
Methanol and ethanol. The two alcohols have similar properties, and will be discussed
together. Pure alcohols are handicapped as fuels for Otto-cycle engines by their low vapor pressure,
which makes cold starting difficult. For this reason, development efforts have focused primarily on
mixtures of alcohols with gasoline. Flexible fuel vehicles, capable of running on any combination of
gasoline and up to 85 percent methanol or ethanol have been developed, and a number of fleets of
these vehicles are being demonstrated. The engines and emission control systems on these vehicles
are similar to those for advanced-technology gasoline vehicles, and the overall energy efficiency and
emissions properties are similar. Table D13-11 shows estimated emissions for a vehicle of this type
using M85 (85% methanol/15% gasoline) fuel.
Heavy-duty engines can also be operated on methanol or ethanol, using a variety of technical
approaches. Emissions data for heavy-duty engines on ethanol are not available, but a number of
heavy-duty methanol engines have been developed. The most promising approach is to inject the
methanol in liquid form, as in a diesel engine, so that engines using this approach can attain diesel-
like efficiencies. Table D13-11 also shows some rough emissions estimates for heavy-duty vehicles
equipped with such engines.
In each of the cases in Table D13-11, the estimates include only the emissions produced by
the vehicle itself. The additional methane emissions associated with producing the methanol from
natural gas are not included.
Electric Vehicles. No methodology is provided at this time for emissions from electric vehicles.
Electric vehicles have received much attention because they do not generate emissions while in use;
as a result, they may offer substantial benefits in urban areas with local air quality problems. They
are not, however, "pollution free". Electric vehicles rely on electricity when the vehicles are not in
D13-14
-------
Table D13-11: Estimated Emission Factors for Light- and Heavy-Duty Methanol Vehicles.
EMISSIONS
NO,
CH4
NMVOC | CO
N20
Passenger Car
Advanced Control
Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0018
9.00
0.42
0.00007
0.40
. 0.022
0.0023
11.80
0.55
0.0111
56.00
2.63
N/A
' N/A
N/A
Heavy-Duty Vehicles: Methanol Diesel Engine
Advanced Control
Ibs/mile
Ibs/ton fuel
lbs/106 Btu
0.0142
12.20
0.66
0.00035
0.40
0.022
0.0053
4.60
0.24
0.0142
12.20
0.66
N/A
N/A
N/A
use to recharge the batteries for continued operation. The electricity required for this activity could
be generated from a number of fuels, including renewables, nuclear, natural gas, or coal. An in-depth
examination of total fuel cycle emissions from the use of electric vehicles is beyond the scope of the
current analysis. The reader is cautioned, however, from viewing electric vehicles as zero-emitters
of greenhouse gases since, arguably, the emissions produced to provide the electricity for recharging
are a direct result of fuel consumption by electric vehicles.
Non-Road Mobile Sources
Although mobile sources other than road vehicles account for a significant fraction of total
mobile source emissions, they have received relatively little study compared to passenger cars and
heavy-duty trucks. Major sources of pollutant emissions among non-road vehicles include farm and
construction equipment, railway locomotives, boats, and ships (all primarily equipped with diesel
engines), jet aircraft, and gasoline-fueled piston aircraft.
A recent study by Weaver (1988) for the U.S. EPA compiled the available (extremely scarce)
data on emissions from diesel engines used in railway locomotives, farm equipment such as tractors
and harvesters, construction equipment such as bulldozers and cranes, and diesel boats, and developed
emission factors for each category. Fuel-specific emission factors calculated from Weaver (1988) are
shown in Table D13-12. Since Weaver (1988) did not estimate N2O emissions, and no other data
for off-road diesels were available, we assumed that fuel-specific N2O emissions would be similar to
. those for heavy-duty on-highway diesel engines.
Weaver (1988) did not estimate emission levels for large ocean-going ships, as opposed to
boats used in coastal and inland traffic. Commercial cargo ships are driven primarily by large, slow-
speed and medium-speed diesel engines. Other power sources that are occasionally found include
steam turbines and gas turbines (the latter in high power-weight ratio vessels such as fast ferries and
warships). The number of vessels equipped with steam or gas-turbine propulsion is small, however,
since these vessels are unable to compete with the more efficient diesels in most applications.
A number of emissions measurements have recently become available for large marine diesel
engines. Hadler (1990) reports data from which it can be calculated that a 9800 kW engine in a
containership, operating at 85 percent power, produced 174 Ibs of NOX per ton of fuel burned.
Melhus (1990), studying engines used in Norwegian coastal vessels, found NOX emissions ranging from
86 to 150 Ibs/ton fuel in four-stroke medium-speed engines, and from 100 to 166 Ibs/ton fuel in
D13-15
-------
Table D13-12: Estimated Emission Factors for Non-Highway Mobile Sources.
UNCONTROLLED EMISSIONS
NO,
CH4
NMVOC
CO
N2O
OCEAN-GOING SHIPS
Ibs/ton fuel
lbs/106 Btu
174.0
4.64
n/a
n/a
n/a
n/a
3.80
0.10
0.16
0.0044
BOATS
Ibs/ton fuel
lbs/106 Btu
135.0
3.54
0.46
0.011
9.80
0.24
42.60
1.10
0.16
0.0044
LOCOMOTIVES
Ibs/ton fuel
lbs/106 Btu
148.6
3.98
0.50
0.013
11.00
0.29
52.20
1.35
0.16
0.0044
FARM EQUIPMENT
Ibs/ton fuel
lbs/106 Btu
127.0
3.31
0.90
0.024
19.20
0.51
50.80
1.33
0.16
0.0044
CONSTRUCTION & INDUSTRIAL EQUIPMENT
Ibs/ton fuel
lbs/106 Btu
100.4
2.65
0.36
0.009
7.80
0.20
32.60
0.84
0.16
0.0044
JET & TURBOPROP AIRCRAFT
Ibs/ton fuel
lbs/106 Btu
25.0
0.64
0.17
0.0044
1.56
0.04
10.40
0.27
n/a
n/a
GASOLINE (PISTON) AIRCRAFT
Ibs/ton fuel
lbs/106 Btu
7.04
0.18
5.28
0.133
48.00
1.19
2067.97-
53.03
0.08
0.002
(presumably slow-speed) two-stroke engines. Bremmes (1990) used an average value of 140 Ibs/ton
fuel, based on earlier measurements by Marintek. Alexandersson (1990) used NOX emission factors
of 0.04 Ibs/kWH (188 Ibs/ton fuel) for two-stroke and 0.03 Ibs/kWH (144 Ibs/ton fuel) for four-stroke
marine diesel engines, both at 80 percent load. Although these measurements vary considerably
among themselves, it is apparent that brake-specific and fuel-specific NOX emissions from marine
diesel engines are comparable to those from other uncontrolled diesel engines. For the results shown
in Table D13-12, we used the data of Hadler (1990). NOX emissions reported by this source appear
representative of the range of emission Values reported, and this was also the only data source
reporting CO as well as NOX data. None of the data sources available reported VOC or N2O data.
For lack of better data, fuel-specific N2O emissions for these engines were assumed to be the same
as those for other heavy-duty diesel;-; VOC emissions from these large diesels are probably negligible.
Pollutant emissions from aircraft are another area that has received relatively little attention.
While emission factors have been developed for most commercial aircraft types (EPA, 1985), these
are expressed in terms of emissions per landing and take-off cycle (LTO)-an inconvenient unit for
cross comparison. Another problem with these factors is that they include only emissions in the
immediate vicinity of the airport, i.e., emissions-under cruise conditions are not included. Since most
aircraft operate primarily in cruise, this is a serious concern.
Data on cruise emissions from aircraft are being developed by the U.S. Federal Aviation
Administration, but are not available at this time. The factors for jet (turbine) aircraft shown in
Table D13-12 were developed by Radian (1990) based on emissions from a Pratt and Whitney JT-17
D13-16
-------
engine, one of the most commonly used types. These factors are repeated here for lack of better
data. The emission factors for small gasoline-fueled piston aircraft were also developed by Radian
(1990) based on a Cessna engine. These are also considered very approximate. Additional research
will be necessary to resolve the problems associated with limited data on cruise emissions.
No data on N2O emissions from aircraft turbine engines were available. For the gasoline
piston engines, fuel-specific N2O emissions were assumed to be similar to those for uncontrolled
passenger cars.
DATA SOURCES
The emission factors in Tables D13-2 through D13-12 can only be used if energy consumption
can be adequately characterized by the fuel and technology types contained in these tables. For
example, for .transportation needs, information is required on the percentage of light-duty versus
heavy-duty vehicles by fuel type (gasoline- versus diesel-fueled) and the extent of emission controls
for each category. There is no single data source that comprehensively provides all relevant
information. There are several sources, however, that can help to determine this information.
For example, activity data on vehicle fleet characteristics will be needed. The main sources
of data available on transport are U.S. EPA, U.S. Department of Transportation (U.S. DOT), and
U.S. DOE. State Departments of Motor Vehicles or other state agencies may also be useful data
sources. As discussed earlier, the most reliable source for energy statistics is probably the U.S.
Department of Energy (DOE), where data on transport activities are detailed by fuel type and basic
transport mode. These data are available for most mobile source energy consumption in the U.S..
Similarly, the most reliable source for basic transportation statistics, such as vehicle miles traveled and
airline flight statistics, would be the Federal Highway Administration and the Federal Aviation
Administration respectively, both of which are part of U.S. DOT.
D13-17
-------
MOBILE4
Emission factors for certain greenhouse gas emissions from road vehicles can be
developed using the MOB1LE4 computer model1 This model was the basis for most of the
emission factors presented in Tables D13-2 to D13-12, and can be used to calculate average
emission rates for any selected calendar year (from 1960 to 2020) essentially by aging the fleet
and weighting the emission factors by the shares of distance travelled by vehicles of various,
ages. The emission factors are estimated, as a function of several parameters, including:.
vehicle type,
model year (technology),
vehicle age and accumulated mileage,
percent of driving in cold start, hot start or stabffized conditions,,
average speed,
ambient temperatures,
fuel volatility, and
tampering rates with emission control systems.
Since these variables can be manipulated by the user, the conditions can be altered to reflect
conditions in a variety of geographic regions and regulatory situations.
MOBILE4 calculates emission factors for total and non-methane hydrocarbons (HCand .:
NMHC, the difference between these two .values indirectly determines the methane factors),
NOX and CO for the four vehicle types mentioned above (U>V» LOT, HDT, 2W) and two
fuels (gasoline and diesel). The emissions performance in MOBILES for vehicles under
various conditions is estimated based on years of extensive testing of vehicles in use in the
United States. The user can specify input data for the particular region .or country, and
emission factors that are tailored to that particular region will be estimated.
Several notes of caution need to be given on the use of MOBILE4 for development
of GHG emission factors. First, the pollutant coverage fe incomplete (including only NO^ CO,
VOC, and NMVOCs with methane as a calculated result of.the difference between NMVOC ,.
and VOC). N2O from vehicles is, however, believed to be relatively insignificant. Finally, it
is believed that this method of "difference" calculation may sigaiScantly underestimate methane ;
from vehicles. Since the methane emission factor may be erroneous, it should be cross-checked ?
with available literature on the subject.
Second* alternative fuel vehicles are not yet incorporated into the model.
Supplementary information must therefore be used to develop these factors should the fuel mix
in transport activities require them. Any assumptions used to build these factors should be as
comparable as possible witb_ those for conventional motor fuels. ;
The MOBILE4 Model and its User's Guide can be obtained from:
The U.S. National Technical information Service, U.S. Department of Commerce
Springfield, Virginia 22161
D13-18
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REFERENCES
Alexandersson, A. (1990). "The Swedish Investigation - Exhaust Emissions from Ships," in
Proceedings from EMEP Workshop on Emissions from Ships. Oslo, Norway, June 7-8, 1990.
State Pollution Control Authority, Oslo.
Bremmes, P.K. 1990. "Calculations of Exhaust Gas Emissions from Sea Transport: Methodology and
Results," in Proceedings from EMEP Workshop on Emissions from Ships. Oslo, Norway, June
7-8, 1990. State Pollution Control Authority, Oslo.
Dasch, J.M. 19°0. Nitrous Oxide Emissions from Vehicles. General Motors Research Publication No.
GMR-.-36, Warren Michigan.
Dietzmann, H.E., M.A. Parness, and R.L. Bradow. 1980. Emissions from Trucks by Chassis Version
of 1983 Transient Procedure. SAE Paper No. 801371. SAE International, Warrendale, PA.
Ford Motor Company. 1991. Annual Report to EPA on Non-Regulated Pollutants for Calendar
Year 1990. Dearborn, MI.
Ford Motor Company. 1990. Annual Report to EPA on Non-Regulated Pollutants for Calendar
Year 1989. Dearborn, MI.
Ford Motor Company. 1989. Annual Report to EPA on Non-Regulated Pollutants for Calendar
Year 1988. Dearborn, MI.
Hadler, C. 1990. "Investigation of Exhaust Gas Emission from Heavy Fuel Operated Diesel Engines
On-Board Ships," in Proceedings from EMEP Workshop on Emissions From Ships. Oslo,
Norway, June 7-8, 1990. State Pollution Control Authority, Oslo.
Machiele, P.A. 1988. Heavy-Duty Vehicle Emission Conversion Factors II: 1962-2000. EPA Report
No. EPA-aa-sdsb-89-1. Ann Arbor, MI.
MacKenzie, J.J. and M.P. Walsh. 1990. Driving Forces. World Resources Institute (WRI), 1990.
Melhus, O. 1990. "NOX Emission Factors from Marine Diesel Engines," in Proceedings from EMEP
Workshop on Emissions from Ships. Oslo, Norway, June 7-8, 1990. State Pollution Control
Authority, Oslo.
OECD/IEA. 1991. Greenhouse Gas Emissions: The Energy Dimension. Draft Report by the
OECD, Paris. Forthcoming.
Otto, K., M. Shelef, and J.T. Kummer. 1970. Studies of surface reactions of nitric oxide by nitrogen-
15 isotope labeling; I. The reaction between nitric oxide and ammonia over supported
platinum at 200-250. Journal of Physical Chemistry 74, 2690-2698.
Piccot, S.D., J.A. Buzun, and H.C. Frey. 1990. Emissions and Cost Estimates for Globally Significant
Anthropogenic Combustion Sources of NOy N2O, CH^ CO, and CO2. EPA-600/7-90-010.
Report under EPA Contract No. 68-02-4288, Work Assignment 38. Radian Corporation,
Research Triangle Park, NC.
Prigent, M. and G. De Soete. 1989. Nitrous Oxide N2O in Engines Exhaust Gases- A First Appraisal
of Catalyst Impact. SAE Paper No. 890492. SAE International, Warrendale, PA
D13-19
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Radian Corporation. 1990. Emissions and Cost Estimates for Globally Significant Anthropogenic
Combustion Sources of NO^ N2O, CHj, CO and CO2- Prepared for the Office of Research
and Development, U.S. EPA, Washington, D.C.
U.S. EPA (U.S. Environmental Protection Agency). 1989. User's Guide to Mpbile4 (Mobile Source
Emission Model). Emission Control Technology Division, Ann Arbor, MI.
U.S. EPA. 1985. Compilation of Air Pollution Emission Factors: Highway Mobile Sources. AP-42,
Fourth Edition, Ann Arbor, Michigan. September.
U.S. National Technical Information Service. 1991. MOBILE4 Model and User's Guide. U.S. NTIS,
U.S. Department of Commerce, Springfield, Virginia.
Warner-Seiph, M.A. and L.R. Smith. 1991. Assessment of Unregulated Emissions from Gasoline
Oxygenated Blends. EPA 460/3-91-002. Report under EPA Contract No. 68-C9-0004.
Southwest Research Institute, San Ar.tonio, TX.
Weaver, C.S and S.H. Turner. 1991. Memorandum to Jane Leggett U.S. EPA and Craig Ebert, ICF,
Incorporated, June 3, 1991.
Weaver, C.S. 1988. Feasibility and Cost-Effectiveness of Controlling Emissions from Diesel Engines
Used in Rail, Marine, Construction, Farm, and Other Mobile Off-Highway Equipment. Report
under EPA Contract No. 68-01-7288, Radian Corporation, Sacramento, CA.
D13-20
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DISCUSSION 14
OTHER GREENHOUSE GAS EMISSIONS
FROM STATIONARY COMBUSTION
OVERVIEW
This section discusses non-CO2 greenhouse gas emissions (i.e., NOX, N2O, CO, CH4, and
NMVOCs) from energy consumption in stationary sources. The reader should note before
proceeding with this section that these calculations can be time consuming and complex. Moreover.
the amount of gases emitted from these activities are not thought to be major contributors to climate
change. Additionally, data on gases such as CO, NOX, and NMVOCs may already be collected by
state environmental or air quality agencies to determine state compliance with the Clean Air Act or
other regulations. For these reasons a methodology for this source category was not included in the
workbook.
Emissions of non-CO? greenhouse gases across activities (sectors) will depend upon fuel,
technology type, and pollution control policies. Emissions will also vary more specifically with size
and vintage of the combustion technology, its maintenance, and its operation.
Electricity generation and industrial fuel combustion activities are similar in that they provide
combustion conditions conducive to NOX formation., NOX emissions depend in part on the nitrogen
contained in the fuel (this may be .especially important for coal), but more importantly on the firing
configuration of the technology. Excess air and high temperatures contribute to high NOX emissions.
Such conditions are highly variable by type of boiler; for instance, for oil-fired plants, tangential
burner configurations generally have lower emission coefficients than horizontally opposed units.
Also, the size of the boiler will affect the NOX emission- rate due to the lower temperatures of smaller
units.
The level of equipment use can-also significantly alter the pattern of NOX emissions.
Measurements of emissions show a 0.5 percent to 1.0 percent decrease in NOX emission rates for
every 1.0 percent decrease in load from full load operation. That is, as the usage rate increases, so
does the emission rate associated with the facility.
Finally, control policies and related technological changes to meet emission limits directly
influence NOX emissions. Emissions from large facilities can be reduced by up to 60 percent by
straightforward adjustments to the burner technology.1 These adjustments are often standard in new
facilities, but may not exist in older facilities. NOX controls may also increase the rate of CO
emissions. Information on the stock of combustion facilities, their vintage, and level of control are
therefore necessary to accurately estimate emissions from large combustion facilities.
NQX emissions from small combustion facilities (small industry, commercial, and residential)
tend to be much less significant than for large facilities as a result of lower combustion temperatures.
1 This can be done, for example, by limiting the excess air in combustion or by staging the combustion
process.
D14-1
-------
Nevertheless, emissions will depend on the specific combustion conditions of the activity in question.
and an effort should be made to carefully characterize the type of activity, on average, in order to
select appropriate emission factors.
Combustion conditions in large facilities are less conducive to formation and release of CO
and VOCs (methane included) than to NOX. VOCs and CO are unburnt gaseous combustibles that
are emitted in small quantities due to incomplete combustion. They have also been the target of
emission control policies and hence must be estimated with these controls in mind. They are directly
influenced by usage patterns, technology type and size, vintage, maintenance, and operation of the
technology. Emissions can vary by several orders of magnitude, for example, for facilities that are
improperly maintained or poorly operated, such as may be the case for many older units. Similarly.
during periods of start-up, combustion efficiency is lowest, and CO and VOC emissions are higher
than during periods of full operation.
Size of the unit may indicate that combustion is less controlled and, hence, the VOC and CO
emission coefficients for smaller units are likely to be higher than for large plants. Also, wood stoves.
due to their largely inefficient combustion of the fuel, have particularly high emission rates of CO and
VOCs. For these reasons, an understanding of commercial and residential activities are key to the
estimation of these greenhouse gases.
N2O is also produced from the combustion of fuels and the mechanisms of its formation are
fairly well understood, although its importance is presently considered to be minor relative to other
source categories. Quantitative estimation of N2O emissions is currently sketchy, as earlier data were
affected by a sampling artifact which resulted in erroneously high emission factors. This is discussed
in more detail later, but in general, the data indicate that N2O emissions may be technology
dependent and thus will vary somewhat across sectors, applications, and fuel types.
DESCRIPTION OF METHOD
General Method
Estimation of emissions from stationary sources can be described using the following basic
formula, which shows that total emissions for a particular state is th'e sum across activities,
technologies, and fuel types.
Emissions = 2_, (EFabc x Activityabc x (l-Rabc/100)
where: EF = Emission Factor (lbs/106 Btu);
Activity = Energy Input (106 Btu);
Rabc = Percent reduction in emissions due to controls;
. a = Fuel type;
b = Sector-activity; and
c = Technology type.
As seen in this equation, emission estimation is generally based on three sets of data, each
of which vary by fuel type, sector, and technology: 1) energy activities; 2) emissions factors; and 3)
control technologies. Sources of the emission factors and energy activities data that are relevant are
described briefly below and suggestions on appropriate use of such data are made.
D14-2
-------
Given the general form of emissions calculations noted above, the main steps in the inventory
method can be summarized as follows:
Step 1: Determine the best available state energy activity data, with consideration
given to the compatibility and verifiability of each source.
Step 2: Determine the main categories of emission factors; based on a survey of state
energy activities.
Step 3: Compile best available emission factor data for the state.
Step 4: Develop assumptions regarding the technology splits within the state, based
on the form of the selected emission factor data .
Step 5: Develop estimates, main activity by main activity, of each of the greenhouse
gases.
Step 6: Sum the individual activity estimates to arrive at the state inventory total for
the greenhouse gases.
Energy Activity Data
Stationary sources have been divided into five sectors in EIA data sources: industry,
agriculture, commercial, residential, and electric utilities.3 Each of these sectors uses energy through
a variety of fuel combustion modes. For example, there are a number of technology and fuel options
for heating a household, and emissions will vary according to these options. Sectoral data therefore
provides a useful starting point for emission inventories, but will need to be further specified by the
share of key technologies represented in each sector.
The basic sector/fuel categories for reporting purposes in Table D14-1 are based on EIA's
State Energy Data Report. States are encouraged to provide the most detailed information available.
DOE or EIA data could be used as a starting point, but states should use the energy data thought
to be the most reliable. If states use in-state sources rather than EIA data, they are strongly urged
to provide thorough documentation on the energy statistics, reporting procedures, and definitions of
sectoral activities, and to aggregate their inventories to the categories in Table D14-1 for comparison
purposes. This would help to ensure consistency and comparability among all state estimates.
Emission Factors and Control Technologies: General Data Sources
Preferably, emission factors should be drawn from state sources or detailed national sources
(e.g., U.S. EPA data). If no state source is available, select from the options provided here. Selection
2 This may require assumptions about the pollution control technologies in place.
3 Transportation is another sector frequently encountered in energy consumption statistics, but is not a
stationary source. Other greenhouse gas emissions from transportation are addressed as mobile source
emissions (see Discussion Section 13).
D14-3
-------
among the options should be based on an assessment of the similarity of the state to the source of
original measurements for types of technology and operating conditions across main energy activities.
The selection should also consider the extent to which control technologies may be in place and the
ability to clearly separate and understand control policy assumptions that may be embedded in the
emission factor data.
Table D14-1. Basic Sector/Fuel Categories
FUELS
I. OIL
Asphalt and Road Oil
Aviation Gas
Distillate Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Liquid Fuels
2. COAL AND OTHER SOLIDS
Bituminous Coal and Lignite
Anthracite
Other Solid Fuels
3. NATURAL GAS
SECTORS
1. ELECTRIC UTILITIES
2. INDUSTRY
Iron and Steel
Chemical
Paper, Pulp, and Print
Petroleum Refining
Food and Tobacco
Other Industry
3. COMMERCIAL
4. RESIDENTIAL
5. OTHER
Emission levels are affected by the specific technology used in the combustion process. The
emissions factors discussed here generally represent the average emission performance of a
population of similar combustion technologies. Emission factors for non-CO2 greenhouse gases from
combustion activities also vary, to lesser or greater degrees, with fuel type, equipment vintage,
operating conditions, maintenance practices, and the use of control technologies. Therefore, good
emission factors for gases other than CO2 are technology specific, but may still represent a wide
distribution of possible values. When available, the standard deviation of the emission factor should
be used to show the range of possible emissions factors, and hence emissions, for each particular
energy activity.4
4 Unfortunately, the standard deviation of emission factors is rarely reported with emission factor data.
Eggleston and Mclnnes (1987) have shown that variation of the final estimates by energy activity range from
20 percent to more than 50 percent.
D14-4
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Representative emission factors for NOX5, CO, CH4, N2O, and NMVOCs by main technology
and fuel types are outlined in Tables D14-2 to D14-6 for the major sectoral categories.6 These data
are taken from Radian (1990) arid show uncontrolled emission factors for each of the technologies
indicated. These emission factor data do not consider control technologies that might be in place in
some states. Therefore, in places where control policies may significantly influence the emission
profile, estimates will need to be adjusted by an emissions reduction factor as presented in the
equation on page D14-2.
Alternative control technologies, with representative percentage reductions, are shown in
Tables D14-7 to D14-10 (Radian, 1990) for the main control technologies applicable to each sector.
The total emission estimate should be adjusted downward according to the indicated percentage
reduction. Table D14-11 provides the fuel property assumptions upon which the Radian data are
based.
The Radian data cited above reflect the performance range of main combustion technologies
in place in the U.S. with a few exceptions. Since most of the data are based on measurement samples
taken from the United States, they represent averages of operating conditions, sizes and vintages of
units found in the U.S. Some emissions factors may be available from the U.S. EPA's Compilation
of Air Pollutant Emission Factors, AP-42 (U.S. EPA, 1985) and the overall control efficiency of a
source category may be derived from U.S. EPA's Aerometric Information Retrieval System (AIRS)
database.
Gas Specific Emissions Discussion
Nitrogen Oxides, Carbon Monoxide, and Non-Methane Volatile Organics (NO^ CO, and NMVOCs)
For'many years, NOX has been the target of environmental policies for its role in forming
ozone (O3), as well as for its direct acidification effects. As a result, NOX emission inventories and
related data such as emission factors are more widely available than those for the other non-CO2
greenhouse gases considered here, so state specific emission factor sources should be sought out.
CO emissions from stationary sources are estimated in the same way as for NOX emissions.
CO is an unburnt gaseous combustible that is emitted in small quantities due to incomplete
combustion, and emission coefficients are often higher for small operations with less combustion
control. Additionally, there may be significant variation in the precise size and type of combustion
technologies in place. With this in mind, a main combustion source of CO is the residential sector,
where the variation in technology, and hence emissions, is intensified by the small nature of the
combustion sources and a wide variety of equipment manufacturers.
NMVOCs should also be included in the emissions inventory. At this time, however, no
emission data are readily available in a consistent and comprehensive form from which to reliably
estimate NMVOCs. Additional sources for emission factor data should be consulted if available. As
5 As a general rule, it is recommended that NOX emissions be converted to a full molecular basis by
assuming that all NOk emissions are emitted as NO2.
6 Little information on N2O and NMVOCs emission factors is included at this time for reasons discussed
below (some N2O factors thought to be reliable are included). These factors should be added as the data
become available.
D14-5
-------
with N2O, additional research is needed to improve the emissions factor data from which emissions
inventories can be developed.
Methane (CH4)
At this time no emission data other than the Radian data have been identified in a consistent
and comprehensive form from which to reliably estimate CH4 at the national level. State level
sources may be available and should be used if deemed reliable and well documented. In the event
that no detailed emission factor data can be found, but emission factor data for NMVOCs is located.
estimates can be based on the rough percentage of methane emissions relative to NMVOC emissions.
In this case, some default ratios of CH4 emissions to NMVOCs are provided in Table D14-12. It
should be noted that this method gives vary imprecise estimates and should only be used as a last
resort.
Nitrous Oxide (N2O)
N2O is produced from the combustion of fossil fuels, and the mechanisms that cause N?O
formation are fairly well understood. There has been considerable difficulty, however, in determining
emission factors, because procedures formerly used to measure N2O emissions were found to suffer
from a sampling artifact whereby N?O formed in the sample containers as a result of reactions
between water, sulfur dioxide, and NOX. This "sampling artifact," which generally affected samples
taken prior to July 1988, resulted in erroneous emission factors which were much too high. Since
recognition of the artifact in June 1988, new measurements have led to more reliable emission factors
for some conventional combustion sources (De Soete, 1993 as cited in IPCC, 1994). Fuel specific
(but not necessarily application-specific) emission factors are now available for commercial
combustion. Data further indicate that N2O emissions may be technology dependent, particularly
with respect to reaction temperatures .
Table D14-13 contains general N2O emission factors and preliminary uncertainty ranges by
major fuel type. These factors are not technology or sector specific and do not include emission
controls. They can be used as default values in the event that no technology and sector specific
factors are provided in Tables D14-2 through D14-6. Emission control performance will need to be
factored in if they are present in the state. If other data are used, care should be taken that no
"artifact data" (as described above) were used in deriving the factors.
7For low and high combustion temperatures (much less than 1000K and much greater than
1200K.) N2O emissions are likely negligible, while the highest emission levels are between 800K and
HOOK (maximum around 1000K). Additionally, increasing pressure and oxygen concentration
increase N2O emissions (IPCC, 1994).
D14-6
-------
Table D14-2. Utility Boiler Source Performance
Emissions Factors (lbs/106 Btu energy input)
Source
Natural Gas - Boilers
Gas Turbine Combined Cycle
Gas Turbine Simple Cycle
Residual Oil Boilers
Distillate Oil Boilers
Shale Oil Boilers
MSW - Mass Feed
Coal - Spreader Stoker
Coal - Fluidized Bed Combined Cycle
Coal - Ruidized Bed
Coal - Pulverized Coal
Coal - Tangentially Fired
Coal - Pulverized Coal Wall Fired
Wood-Fired Boilers
CO
0.040
0.067
0.067
0.033
0.033
0.033
0.217
0.267
N/A
N/A
0.031
0.031
0.031
3'.255
CH4
0.0002
0.0128
0.0124
0.0015
0.00007
• 0.0015
N/A
0.0015
0.0013
0.0013
0.0013
0.0013.
0.0013
0.0398
NOX
0.559
0.391
0.394
0.444
0.150
0.444
0.309
0.720
N/A
0.563
1.894
0.729
1.019
0.247
N:O
N/A
N/A
N/A
N/A
N/A
N/A
N/A
0.0018
N/A
N/A
0.0018
0.0018
0.0018
N/A
NMVOCs
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Source: Radian, 1990.
Table D14-3. Industrial Boiler Performance
Emissions Factors (lbs/106 Btu energy input)
Source
Coal-Fired Boilers
Residual Oil-Fired Boilers
Natural Gas-Fired Boilers
Wood-Fired Boilers
Bagasse/Agri. Waste-Fired Boilers
MSW - Mass burn
MSW - Small Modular
CO
0.206
0.033
0.036
3.32
3.77
0.212
0.042
CH4
0.0053
0.0064
0.0029
0.0331
N/A
N/A
N/A'
NOX
0.73
0.36
0.14
0.25
0.19
0.31
•0.31
N:O
N/A
N/A
N/A
N/A
N/A
N/A
N/A
NMVOCs
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Source: Radian. 1990.
D14-7
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Table D14-4. Kilns, Ovens, and Dryers Source Performance
Emissions Factors
Industry
Cement. Lime
Cement, Lime
Cement, Lime
Coking, Steel
Chemical Processes, Wood,
Asphalt Copper, Phosphate
Chemical Processes, Wood,
Asphalt Copper, Phosphate
Chemical Processes, Wood,
Asphalt Copper, Phosphate
Source
.Kilns -
Natural Gas
Kilns - Oil
Kilns - Coal
Coke Oven
Dryer -
Natural Gas
Dryer - Oil
Dryer - Coal
CO
0.174
0.175
0.175
0.466
0.023
0.035
0.396
CH4
0.0023
0.0022
0.0022
0.0022
0.0023
0.0022
0.0022
(lbs/106 Btu energy input)
NOX
2.33 •
! '(•>
1.16
N/A
0.13
0.37
0.50
N,O
N/A
N/A
N/A
N/A
N/A
N/A
N/A
NMVOCs
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Source: Radian, 1990.
Table D14-5 Residential Source Performance
Emissions Factors
Source
Wood Pits
Wood Fireplaces
Wood Stoves
Propane/Butane Furnaces
Coal Hot Water Heaters
Coal Furnaces
Coal Stoves
Distillate Oil Furnaces
Gas Heaters
CO
10.94
13.26
40.95
0.022
0.040
1.070
7.911
0.029
0.021
CH4
0.442
N/A
0.164
0.0024
N/A
N/A '
N/A
0.0110
0.0021
(lbs/106 Btu energy input)
NOS
0.325
0,256
0.442
0.104
0.349
0.513
• 0.396
0.113
0.098
N,O
N/A
N/A
N/A
N/A
• N/A
N/A
N/A
N/A
N/A
NMVOCs
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Source: Radian, 1990.
D14-8
-------
Table D14-6. Commercial Source Performance
Emissions Factors (lbs/106 Btu input)
Source
Wood Boilers'
Gas Boilers
Residual Oil Boilers
Distillate Oil Boilers
MSW Boilers
Coal Boilers
Shale Oil Boilers
Open Burning - MSW1
Open Burning - Agriculture1
Incineration - high efficiency1
Incineration - low efficiency1
CO
0.440
0.020
0.038
0.035
0.042
0.431
0.038
92.8
128.2
11.0
22.1
CH4
0.0331
0.0025
0.0035
0.0013
N/A
6.0221
0.0035
• 14.4
19.9
N/A
N/A
NO,
0.073
0.100 .
0.343
0.141
1.023
0.522
0.411
6.6
.N/A
3.3
2.2
N:O
0.0095
' 0.0050
0.103
0.035
N/A
0.131
0.103
N/A
N/A
N/A
N/A
NMVOCs
N/A
N/A
N/A
N/A
N/A
. N/A
N/A
N/A
N/A
N/A
N/A
Emission factors are presented in Ibs/billion Btu
Source: Radian, 1990.
D14-9
-------
Table D14-7. Utility Emission Controls Performance
Technology
Low Excess Air
Overfire .Air - Coal
Overfire Air - Gas
Overfire Air - Oil
Low NO, Burner -
Coal
Low NO, Burner -
TF
Low NO, Burner -
Oil
Low NO, Burner -
Gas
Cyclone Combustion
Modification
Ammonia Injection
SCR - Coal
SCR - Oil, AFBC
SCR - Gas
Water Injection - Gas
Turbine Simple Cycle
SCR - Gas Turbine
CO, Scrubbing - Coal
CO, Scrubbing - Oil
CO, Scrubbing - Gas
Retrofit LEA
Retrofit OFA - Coal
Retrofit OFA - Gas
Retrofit OFA - Oil
Retrofit LNB - Coal
Retrofit LNB - Oil
Retrofit LNB - Gas
Burners Out of
Service (BOOS)
Efficiency
Loss1
-0.5
. 0.5
1.25
0.5
0.25
0.25
0.25
0.25
0.5
0.5
1
1
1
1
1
22.5
16.0
11.3
-0.5
0.5
1.25
0.5
0.25
.0.25
0.25
0.5
CO CH4 NO,
Reduction Reduction Reduction
-1- + • 15
+ + , 25
+ + 40
+ + 30
+ -I- 35
+ + 35
+ + 35
+ + 50
N/A N/A 40
+ + 60
8 + 80
8 + 80
8 + 80
+ + 70
8 .+ 80
N/A N/A N/A
N/A N/A N/A
N/A N/A N/A
+ + 15
+ + 25
. + + 40
+ + 30
+ + 35
+ + 35
+ + 50
' + + 30
N:O
Reduction
N/A
N/A
N/A
N/A
N/A
' N/A
'N/A .
N/A
N/A
N/A
N/A
N/A
60
N/A
60
N/A
N/A
N/A
. N/A •
N/A
N/A
N/A
N/A
N/A
N/A
N/A .
NMVOCs
Reduction
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Date
Available2
1970
1970
1970
1970
1980
1980
1980
1980
1990
1985
1985
1985
1985
1975
1985
2000
2000
2000
1970
1970
1970
1970
1980
1980
1980
1975
1 Efficiency loss ^- •;' percent of end-user energy conversion efficiency.
1 Date technology ;s assumed to be commercially available.
Note: A "+" indicates negligible reduction.
Source: Radian, 1990.
Negative loss indicates an efficiency improvement.
D14-10
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Table D14-8. Industrial Boiler Emission Controls Performance
Technology
Low Excess Air
Overfire Air - Coal
Overfire Air - Gas
Overfire Air' - Oil
Low NO, Burner -
Coal
Low NO, Burner - .
Oil
Low NO, Burner -
Gas
Flue Gas
Recirculation
Ammonia Injection
SCR - Coal
SCR - Oil. AFBC
SCR - Gas
Retrofit LEA
Retrofit OFA - Coal
Retrofit OFA - Gas
Retrofit OFA - Oil
Retrofit LNB - Coal
Retrofit LNB : Oil
Retrofit LNB - Gas
Efficiency
Loss1
-0.5
0.5
1.25
0.5
0.25
0.25
0.25
0.5
0.5
1
1
1
-0.5
0.5
1.25
0.5
0.25
0.25
0.25
CO CH4 NO,
Reduction Reduction Reduction
+ + 15
+ • + 25
+ + 40
+ + 30
+ + 35
+ + 35
+ + 50
-I- + 40
+ + • 60
8 . + 80
8 + 80
8 + 80
+ • + 15
+ + 25
+ + 40
+ + 30
+ + 35
+ + 35
+ + 50
N,O
Reduction
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A '
N/A
60
N/A
N/A'
N/A
N/A
' N/A
N/A
N/A
NMVOCs
Reduction
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A .
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Date
Available2
1970
1970
1970
1970
1980
1980
1980
1975
1985
1985
1985
1985
1970
1970
1970
1970
1980
1980
1980
'Efficiency loss as a percent of end-user energy conversion efficiency. Negative loss indicates an efficiency improvement.
:Date technology is assumed to be commercially available.
Note: A "+" indicates negligible reduction.
Source: Radian, 1990.
Table D14-9. Kiln, Ovens, and Dryers Emission Controls Performance
Technology
LEA - Kilns, Dryers
LNB - Kilns, Dryers
SCR - Coke Oven
Nitrogen Injection
Fuel Staging
Efficiency
Loss1
(%)
-6.4
0
1.0
N/A
N/A
CO
Reduction
(%)
+
+
8
N/A
N/A
CH4
Reduction
(%)
+
+
+
N/A
N/A
NO,
Reduction
•(.%)
14
35 •
80
30
50
. N20
Reduction
(%)
N/A
N/A
60
N/A
N/A.
NMVOCs
Reduction
(%)
N/A
N/A
N/A
N/A
N/A
Date
Available2
1980
' 1985
1979
1990
1995
'Efficiency loss as a percent of end-user energy conversion efficiency. Negative loss indicates an efficiency improvement.
2Date technology is assumed to be commercially available.
Note: A "+" indicates negligible reduction.
Source: Radian, 1990.
D14-11
-------
Table D14-10. Residential and Commercial Emission Controls Performance
Technology
Catalytic Woodstove
Non-Catalytic MCS
Flame Ret. Burn.
Hd.
Contr. Mix. Burn.
Hd.
Integr. Furn. Syst.
Blueray Burn./Furn.
M.A.N. Burner
Radiant Screens
Secondary Air Baffle
Surface Comb.
Burner
Amana HTM
Modulating Furnace
Pulse Combuster
Catalytic Combuster
Replace Worn Units
Tuning, Seasonal
Maintenance
Red. Excess. Firing
Red fir with new ret
b
Pos. Chimney
Dampers
Inc. thermal anticip.
Night therm, cutback
Low Excess Air
Flue Gas
Recirculation
Over-fire Air
Over-fire Air
Low NO, Burners
Low NO, Burners
Efficiency
Loss1
(%)
-44
-30
-9
-7
-12
-12
-13
-7
N/A
N/A
-21
- -7
-36
-29
N/A '
-2
-19
-40
-8
-1
-15
-0.8
0.6
I
1
0.6
0.6
CO
Reduction
(%)
90
15
28
43
. 13
74
N/A
62
16
55
-55
N/A '
N/A
N/A '
65
16
14
14
11
43
17
N/A
N/A
N/A
N/A
N/A
N/A
CH4 NO,
Reduction Reduction
(%) (%)
90
50
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
\
N/A
N/A
• N/A
N/A
N/A
N/A
N/A
N/A
-27
-5
N/A
44
69
84
71
55
40
79
79
32
47
86
N/A
N/A
N/A
N/A
N/A
N/A
N/A
15
50
20
30
40
50
N:O
Reduction
(%)
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
-N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
NMVOCs
Reduction
(%)
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Date
Available2
1985
1985
1980
1970
1975
1970
1970
1980
1980
'Efficiency loss as a percent of end-user energy conve:
2Date technology is assumed to be commercially avail!
Note: A " + " indicates negligible reduction.
Source: Radian, 1990.
rsion efficiency.
.ible.
Negative loss indicates an efficiency improvement.
D14-12
-------
Table D14-11. Fuel Properties
Fuel
Butane/Propane
Coke Oven Gas
Methane (pure)
Natural Gas
Process Gas
LIQUID
Crude Shale Oil
Diesel/Distillate
Gasoline
Jet A
Methanol
Residual Oil
SOLID
Bagasse/ Agriculture
Charcoal
Coal
MSW
Wood
Heating Value
(106 Btu/ton)1
43.7
35.1
43.0
43.9
46.4
.37.0
38.8
111 x 103 Btu/gal
37.1
53 x 103 Btu/gal
37.0
7.8
25.0
19.9
9.7
9.1
Carbon
(wt percent)
82.0
56.1
75.0
70.6
*
70.6
84.5 .
87.2
85.7
86.1
37.5
85.6
22.6
37:0
65.0
26.7
27.0
1 Unless otherwise indicated.
Source: Radian, 1990.
D14-13
-------
Table D14-12. Ratio of CH4 to NMVOCs Released
During Combustion
Activity
Ratio of CH4 to NMVOC
Emissions
(Low to High)
Coal Combustion
Fuel Oil Combustion
Wood Combustion (Industrial
Use)
Wood Combustion (Residential
Use),
Other
0.05 to 1.00
0.05 to 0.10
0.2 •
2
0.1
Source: U.S. EPA, 1993; except "Other," where the upper end of the fuel oil category
was used as an approximation..
Table D14-13. N2O Emissions Factors for
Conventional Facilities by Fuel Type
Fuel Emission
Factor
(lbs/106Btu)
Coal 0.0032
Oil 0.0014
Gas 0.0002
Uncertainty Range
0 - 0.0234
0 - 0.0065
0 - 0.0026
Source: De Soette (1993) as cited in IPCC (1994)
D14-14
-------
REFERENCES
Cofer III, W.R., J.S. Levine, D.I. Sebacher, E.L. Winstead, P.J. Riggan, B.J. Stocks, J.A. Brass, V.G.
Ambrosia, and P.J. Boston. 1989. "Trace Gas Emissions from Chaparral and Boreal Forest
Fires," Journal of Geophysical Research 94(D2):2255-2259.
Cofer III, W.R., J.S. Levine, P.J. Riggan, D.I. Segacher, E.L. Winstead, E.F. Shaw Jr., J.A. Brass, and
V.G. Ambrosia. 1988. "Trace Gas Emissions from a Mid-Latitude Prescribed Chaparral Fire,"
Journal of Geophysical Research 93(D2):1653-1658.
De Soette, G.G. 1993. "Nitrous Oxide from Combustion and Industry: Chemistry and Emissions
Control." In A.R. van Amstel (ed.), Proceedings of an International IPCC Workshop on
Methane and Nitrous Oxide: Methods in National Emissions Inventories and Options for
Control. RIVM Report No. 481507003, Bilthoven, The Netherlands.
EIA (Energy Information Administration). 1988. State Energy Data Report. DOE/EIA-0214-(86).
Eggleston. H.S., and G. Mclnnes. 1987. Method for the Compilation of UK Air Pollutant Emission
Inventories. ISBN-0-85624-493-7. Warren Spring Laboratory, Stevenage, UK.
Hao, W.M., S.C. Wofsy, M.B. McElroy, J.M. Beer, and M. A. Toqan. 1987. "Sources of Atmospheric
Nitrous Oxide from Combustion," Journal of Geophysical Research 92:3098-3104.
IPCC. 1994. IPCC Guidelines for National Greenhouse Gas Inventories, 3 volumes: Vol. 1, Reporting
Instructions; Vol. 2, Workbook;. Vol. 3, Draft Reference Manual. Intergovernmental Panel on
Climate Change, Organization for Economic Co-Operation and Development. Paris, France.
Linak, W.P., J.A. McSorley, R.E. Hall, J.V. Ryan, R.K. Srivastava, J.O.L. Wendt, and J.B. Mereb.
1990. "Nitrous Oxide Emissions from Fossil Fuel Combustion," Journal of Geophysical
Research 95:7533-7541. .
Montgomery, T.A., G.S. Samuelsen, and L.J. Muzio. 1989. "Continuous Infrared Analysis of N2O
in Combustion Products," Journal of the American Chemical Society 39:721-726.
Muzio, L.J., and J.C. Kramlich. 1988. "An Artifact in the Measurement of N2O from Combustion
Sources," Geophysical Research Letters 15:1369-1372.
Muzio, L.J., M.E. Teague, J.C. Kramlich, J.A. Cole, J.M. McCarthy, and R.KXyon. 1989. "Errors
in Grab Sample Measurements of N2O from Combustion Sources," Journal of the American
Chemical Society 39:287-293.
OECD/IEA. 1991. Greenhouse Gas Emissions: The Energy Dimension. OECD/IEA, Paris.
Forthcoming.
Radian Corporation. 1990. Emissions and Cost Estimates for Globally Significant Anthropogenic
Combustion Sources of NOy N2O, CH^ CO, and CO2. Prepared for the Office of Research
and Development, U.S. Environmental Protection Agency, Washington, D.C.
U.S. EPA (U.S. Environmental Protection Agency). 1993. Anthropogenic Methane Emissions in the
United .States, Estimates for 1990: Report to Congress. Office of Air and Radiation, U.S.
Environmental Protection Agency, Washington, DC.
D14-15
-------
U.S. EPA. 1985. Compilation of Air Pollutant Emission Factors, AP-42. U.S. Environmental
Protection Agency, Office of Air Quality, Planning, and Standards, Technology Transfer
Network.
D14-16
-------
PART III
APPENDICES
-------
GLOSSARY1
Aerosol: Paniculate material, other than water or ice, in the atmosphere. Aerosols are important
in the atmosphere as nuclei for the condensation of water droplets and ice crystals, as
participants in various chemical cycles, and as absorbers and scatterers of solar radiation,
thereby influencing the radiation budget of the earth-atmosphere system, which in turn
influences the climate on the surface of the Earth.
Afforestation: The process of establishing a forest, especially on land not previously forested.
Anaerobic Fermentation: Fermentation that occurs under conditions where oxygen is not present.
For example, methane emissions from landfills result from anaerobic fermentation of the
landfilled waste.
Anthropogenic: Of, relating to, or resulting from the influence of human beings on nature.
Atmosphere: The envelope of air surrounding the Earth and bound to it by the Earth's gravitational
attraction.
Biomass: The total dry organic matter or stored energy content of living organisms that is present
at a specific time in a defined unit (ecosystem, crop, etc.) of the Earth's surface.
Biosphere: The portion of Earth and its atmosphere that can support life.
Carbon Sink: A pool (reservoir) that absorbs or takes up released carbon from another part of the
carbon cycle. For example, if the net exchange between the biosphere and the atmosphere
is toward the atmosphere, the biosphere is the source, and the atmosphere is the sink.
Carbon Dioxide (CO2): Carbon dioxide is an abundant greenhouse gas, accounting for about 66
percent of the total contribution in 1990 of all greenhouse gases to radiative forcing.
Atmospheric concentrations have risen 25% since the beginning of the Industrial Revolution.
Anthropogenic source of carbon dioxide emissions include combustion of solid, liquid, and
gases fuels, (e.g., coal, oil, and natural gas, respectively), deforestation, and non-energy
production processes such as cement-production.
Carbon Monoxide (CO): Carbon monoxide is an odorless, invisible gas created when carbon-
containing fuels are burned incompletely. Participating in various chemical reactions in the
atmosphere, CO contributes to smog formation, acid rain, and the buildup of methane (CH4).
CO elevates concentrations of CH4 and tropospheric ozone (O3) by chemical reactions with
the atmospheric constituents (i.e., the hydroxyl radical) that would otherwise assist in
destroying CH4 and O3.
Chlorofluorocarbons (CFCs): A family of inert non-toxic and easily liquified chemicals used in
refrigeration, air conditioning, packaging, and insulation or as solvents or aerosol propellants.
1 Some of the definitions shown here are taken from the Carbon Dioxide and Climate Glossary produced
by the Carbon Dioxide Information Analysis Center of Oak Ridge National Laboratory.
G-l
-------
Because they are not destroyed in the lower atmosphere, they drift into the upper atmosphere
where their chlorine components destroy ozone.
Climate Change: The long-term fluctuations in temperature, precipitation, wind, and all other
aspects of the Earth's climate.
Deforestation: The removal of forest stands by cutting and burning to provide land for agricultural
purposes, residential or industrial building sites, roads, etc. or by harvesting trees for building
materials or fuel.
Enteric Fermentation: Fermentation that occurs in the intestines. For example, methane emissions
produced as part of the normal digestive processes of ruminant animals is referred to as
"enteric fermentation."
/• sy
Flux: Rate of substance flowing into the atmosphere (e.g. Ibs/ft /second).
Global Warming Potential (GWP): Gases can exert a radiative forcing both directly and indirectly:
direct forcing occurs when the gas itself is a greenhouse gas; indirect forcing occurs when
chemical transformation of the original gas produces a gas or gases which themselves are
greenhouse gases. The concept of the Global Warming Potential has been developed for
policy-makers as a measure of the possible wanning effect on the surface-troposphere system
arising from the emissions of each gas relative to CO2.
Greenhouse Effect: A popular term used to describe the roles of water vapor, carbon dioxide, and
other trace gases in keeping the Earth's surface warmer than it would be otherwise.
Greenhouse Gases: Those gases, such as water vapor, carbon dioxide, tropospheric ozone, nitrous
oxide, and methane that are transparent to solar radiation but opaque to infrared or longwave
radiation. Their action is similar to that of glass in a greenhouse.
Hydrofluorocarbons (HFCs): HFCs are substitutes for CFCs and HCFCs which are being phased-
out under the Montreal Protocol on Substances that Deplete the Ozone Layer. HFCs may have
an ozone depletion potential (ODP) of zero, however, they are very powerful greenhouse
gases. For example, HFC-23 and HFC-134a have a GWPs of 10,000 and 1,200 respectively.
Methane (CH4): Following carbon dioxide, methane is the most important greenhouse gas in terms
of global contribution to radiative forcing (18 percent). Anthropogenic sources of methane
include wetland rice cultivation, enteric fermentation by domestic livestock, anaerobic
fermentation of organic wastes, coal mining, biomass burning, and the production,
transportation, and distribution of natural gas.
Nitrous Oxide (N2O): Nitrous oxide is responsible for about 5 percent of the total contribution in
1990 of all greenhouse gases to radiative forcing. Nitrous oxide is produced from a wide
variety of biological and anthropogenic sources. Activities as diverse as the applications of
nitrogen fertilizers and the consumption of fuel emit N2O.
Nitrogen Oxides (NOX): One form of odd-nitrogen, denoted as NOX is defined as the sum of two
species, NO and NO2. NOX is created in lighting, in natural fires, in fossil-fuel combustion,
and in the stratosphere from N2O. It plays an important role in the global warming process
G-2
-------
due to its contribution to the formation of ozone (O3).
Nonmethane Volatile Organic Compounds (NMVOCs): NMVOCs are frequently divided into
methane and non-methane compounds. NMVOCs include compounds such as propane,
butane, and ethane (see also discussion on Volatile Organic Compounds).
Ozone (O3): A molecule made up of three atoms of oxygen. In the stratosphere, it occurs naturally
and it provides a protective layer shielding the Earth from ultraviolet radiation and
subsequent harmful health effects on humans and the environment. In the troposphere, it
is a chemical oxidant and major component of photochemical smog.
Perfluorinated Carbons (PFCs): PFCs are powerful greenhouse gases that are emitted during the
reduction of alumina in the primary smelting process. Eventually, PFCs are to be used as
substitutes for CFCs and HCFCs. PFCs have a GWP of 5,400.
Radiative Forcing: The measure used to determine the extent to which the atmosphere is trapping
heat due to emissions of greenhouse gases.
Radiatively Active Gases: Gases that absorb incoming solar radiation or outgoing infrared radiation,
thus affecting the vertical temperature profile of the atmosphere. Most frequently cited as
being radiatively active gases are water vapor, carbon dioxide, nitrous oxide,
chlorofluorocarbons, and ozone.
Stratosphere: Region of the upper atmosphere extending from the tropopause (about 5 to 9 miles
altitude) to about 30 miles.
Trace Gas: A minor constituent of the atmosphere. The most important trace gases contributing
to the greenhouse effect include water vapor, carbon dioxide, ozone, methane, ammonia,
nitric acid, nitrous oxide, and sulfur dioxide.
Troposphere: The inner layer of the atmosphere below about 15 km, within which there is normally
a steady decrease of temperature with increasing altitude. Nearly all clouds form and weather
conditions manifest themselves within this region, and its thermal structure is caused primarily
by the heating of the Earth's surface by solar radiation, followed by heat transfer by turbulent
mixing and convection.
Volatile Organic Compounds (VOCs): Volatile organic compounds along with nitrogen oxides are
participants in atmospheric chemical and physical processes that result in the formation of
ozone and other photochemical oxidants. The largest sources of reactive VOC emissions are
transportation sources and industrial processes. Miscellaneous sources, primarily forest
wildfires and non-industrial consumption of organic solvents, also contribute significantly to
total VOC emissions.
G-3
-------
GLOSSARY: CHEMICAL SYMBOLS
AND CONVERSION FACTORS
1. The columns below list symbols and their associated chemical compounds or meanings:
Symbol Compound
CH4 ' Methane
N2O Nitrous Oxide
CO - Carbon Monoxide
NOX Nitrogen Oxides
CO2 Carbon Dioxide
CO2-C Carbon Dioxide in units
of Carbon
-C in units of Carbon
N2O-N Nitrous Oxide in units
of Nitrogen
-N ' in units of Nitrogen
2. The columns below show compounds and conversions by molecular weight equivalents to
other compounds.
To Convert: To: Multiply by:
tons CO2-C
tons CH4-C
tons CO-C
tons N2O-N
tons NOX-N
tons CO2
tons CH4
tons CO
tons N2O
tons NOV
44/12
16/12
28/12
44/28
46/14
G-4
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STATE AGENCY CONTACTS
FOR CLIMATE CHANGE
ENERGY OFFICES
ALABAMA -- Alabama Department of Economic and Community Affairs, Science, Technology,
and Energy Division, P.O. Box 5690, Montgomery, AL 36103-5690. (205) 242-5292. Fax
(205) 242-5515. Dialcom DOE459
ALASKA ~ Alaska Energy Office, Rural Development Division, Department of Community and
Regional Affairs, 333 West 4th Avenue, Suite 220, Anchorage, AK 99501-2341. (907)
269-4630. Fax (907) 269-4520
ARIZONA -- Arizona Energy Office, 3800 North Central, 12th Floor, Phoenix, AZ 85012.
(602) 280-1402, Fax (602) 280-1305, Dialcom DOE472
ARKANSAS - Arkansas Energy Office, One State Capital Mall, Suite 4B-215, Little Rock, AR
72201. (501) 682-1370, Fax (501) 682-7341
CALIFORNIA - California Energy Commission-(SECP), 1516 9th Street, Sacramento, CA 95814.
(916) 654-5000, Fax (916) 654-4420
CALIFORNIA - California Energy Extension Service-(EES), 1400 10th Street, Sacramento,. CA
95814. (916) 323-4388, Fax (916) 324-4523, Dialcom
COLORADO - Colorado Office of Energy Conservation, 1675 Broadway, Suite 1300, Denver,
CO 80202-4613. (303) 894-2144, Fax (303) 620-4288, Dialcom DOE412, 1-800-OEC-
6662
CONNECTICUT -- Connecticut Office of Policy and Management, Energy Division, 80
Washington Street, Hartford, CT 06016. (203) 566-2800, Fax (203) 566-8463, Dialcom
DOE455
DELAWARE -- Delaware Division of Facilities Management, P.O. Box 1401, Dover, DE 19903.
(302) 736-5644, Fax (302) 739-6148, Dialcom DOE458
DISTRICT OF COLUMBIA— District of Columbia Energy Office, 613 G Street, NW, 5th Floor,
Washington, D.C. 20001 (202) 727-1800, Fax (202) 727-9582, Dialcom DOE486
FLORIDA - Florida Energy Office, The Capitol, Tallahassee, FL 32399-0001. (904) 488-6764,
Fax (904) 488-7688, Dialcom DOE470
GEORGIA - Governor's Office of Energy Resources, 254 Washington Street, SW, Suite 401,
Atlanta, GA 30334. (404) 656-5176, Fax (404) 656-7970
C-l
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HAWAII -- Hawaii State Energy Division, Department of Business, Economic Development &
Tourism, 335 Merchant Street, Room 110, Honolulu, HI 96813. (808) 587-3800, Fax
(808) 587-3820
IDAHO -- Idaho Department of Water Resources, Statehouse Mail, Boise, ID 83720-9000.
(208) 327-7900, Fax (208) 327-7866, Dialcom DOE474
ILLINOIS - Illinois Department of Energy & Natural Resources, 325 West Adams Street, Room
300, Springfield, IL 62704. (217) 785-2800, Fax (217) 785-2618, Dialcom DOE438
INDIANA - Indiana Division of Energy Policy, 1 North Capitol, Suite 700, Indianapolis, IN
46204-2243, (317) 232-8940, Fax (317) 232-8995, Dialcom DOE487
IOWA ~ Iowa Department of Natural Resources Energy Bureau, Wallace Building, Des Moines,
IA 50319. (515) 281-8681, Fax (515) 281-8895, Dialcom DOE449
KANSAS - Kansas Corporation Commission, 1500 SW Arrowhead Road, Topeka, KS 66604,
(913) 271-3170, Fax (913) 271-3354
KENTUCKY - Kentucky Division of Energy, 691 Teton Trail, 2nd Floor, Frankfort, KY 40601,
(502) 564-7192, Fax (502) 564-7484, Dialcom DOE439
LOUISIANA - Louisiana Department of Natural Resources, Energy Division, P.O. Box 44156,
Baton Rouge, LA 70804. (504) 342-1399 or (504) 342-2707, Dialcom DOE461
MAINE - State House Station No. 53, Augusta, ME 04333, (207) 624-6000, Fax (207) 624-6023,
Energy Conservation Division Dialcom DOE413
MARYLAND - Maryland Energy Administration, 45 Calvert Street, Annapolis, MD 21401-1907,
(301) 974-3751, Fax (301) 974-2250, Dialcom DOE440
MASSACHUSETTS - Massachusetts Division of Energy Resources, Saltonstall Building, 100
Cambridge Street, Room 1500, Boston, MA 02202, (617) 727-4732, Fax (617) 727-0030
MICHIGAN - Michigan Office of Energy Programs, Public Service Commission, P.O. Box 30221,
Lansing, MI 48909, (517) 334-6272, Fax (517) 882-5170, Dialcom 414
MINNESOTA -- Minnesota Department of Public Service, 790 American Center Building, 150
East Kellogg Boulevard, St. Paul, MN 55101, (612) 296-5120, Fax (612) 297-1959, Dialcom
DOE452
MISSISSIPPI ~ Mississippi Department of Economic and Community Development, Energy and
Transportation Division, 510 George Street, Suite 101 , Jackson, MS 39202-3096, (601)
359-6600, Fax (601) 359-6642, Dialcom DOE467
MISSOURI ~ Missouri Department of Natural Resources, Division of Energy, P.O. Box 176,
Jefferson City, MO 65102, (314) 751-4000, Fax (314) 751-6860, Dialcom DOE421
MONTANA - Montana Department of Natural Resources and Conservation, 1520 East Sixth
Avenue, Helena, MT 59620, (406) 444-6696, Fax (406) 444-6721, Dialcom DOE441
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NEBRASKA -- Nebraska Energy and Policy Research Office, P.O. Box 95085, State Capitol
Building, Lincoln, NE 68509-5085, (402) 471-2867, Fax (402) 471-3064, Dialcom DOE
NEVADA - Nevada Governor's Office of Community Services, 400 West King Street, Carson
City, NV 89710, (702) 687-4990, Fax (702) 687-4914
NEW HAMPSHIRE - New Hampshire Governor's Office of Energy & Community Service, 2
1/2 Beacon Street, Concord, NH 03301-8519, (603) 271-2611, Fax (603) 271-2615,
Dialcom DOE451
NEW JERSEY - New Jersey Board of Regulatory Commissioners, 2 Gateway Center, Newark,
NJ 07102, (201) 648-3621, Fax (201) 648-4298, Dialcom DOE415
NEW MEXICO ~ New Mexico Energy, Minerals and Natural Resources Department, 2040
South Pacheco Street, Santa Fe, NM 87505, (505) 827-5900, Fax (505) 827-5912, Dialcom
DOE484
NEW YORK - New York State Energy Office, 2 Rockefeller Plaza, Albany, NY 12223, (518)
474-7183, Fax (518) 473-2017, Dialcom DOE417
NORTH CAROLINA - North Carolina Department of Economic and Community Development
Energy Division, 430 North Salisbury Street, Raleigh, NC 27611, (919) 733-2230, Fax (919)
733-2953, Dialcom DOE 482
NORTH DAKOTA - North Dakota Office of Intergovernmental Assistance, State Capitol, 14th
Floor, 600 East Boulevard Ave., Bismarck, ND 58505-0170, (701) 224-2094, Fax (701)
224-3000, Dialcom DOE465
OHIO - Ohio Department of Development, Office of Energy Efficiency, 77 South High Street,
24th Floor, Columbus, OH 43266-0413, (614) 466-6797, Fax (614) 466-4708, Dialcom
DOE556
OKLAHOMA - Oklahoma Department of Commerce, P.O. Box 26980, Oklahoma City, OK
73126-0980, (405) 843-9770, Fax (405) 841-5199
OREGON - Oregon Department of Energy, 625 Marion Street, NE, Salem, OR 97310, (503)
378-4040, Fax (503) 229-5173, Dialcom DOE464
PENNSYLVANIA - Pennsylvania Energy Office, 116 Pine Street, Harrisburg, PA 17101-1227,
(717) 783-9981, Fax (717) 783-2703, Dialcom DOE419
RHODE ISLAND ~ Rhode Island Governor's Office of Housing, Energy and Intergovernmental
Relations, State House, Room 111, Providence, RI 02903, (401) 277-2850, Fax (401)
273-5301, Dialcom DOE444
SOUTH CAROLINA -- South Carolina Governor's Division of Energy, Agriculture and Natural
Resources, 1205 Pendleton Street, Suite 333, Columbia, SC 29201, (803) 734-1740, Fax
(803) 734-0356
C-3
-------
SOUTH DAKOTA -- South Dakota Governor's Office of Energy Policy, 217 West Missouri, Suite
200, Pierre, SD 57501-4516, (605) 773-3603, Fax (605) 773-4802, Dialcom DOE
TENNESSEE ~ Tennessee Department of Economic and Community Development Energy
Division, 320 6th Avenue North, 6th Floor, Nashville, TN 37243-0405, (615) 741-2994, Fax
(615) 741-5829, Dialcom DOE420
TEXAS - Texas Governor's Energy Office, P. O. Box 12428, Capitol Station, Austin, TX 78711,
(512) 463-1931, Fax (512) 475-2569, Dialcom DOE439
UTAH - Utah Division of Energy, 3 Triad Center, Suite 450, Salt Lake City, UT 84180-1204,
(801) 538-5428, Fax (801) 521-0657, Dialcom DOE433
VERMONT ~ Vermont Department of Public Services, Energy Efficiency Division, 120 Statew
Street, Montpelier, VT 05620, (802) 828-2393, Fax (802) 828-2342
VIRGINIA ~ Virginia Department of Mines, Minerals, and Energy, Division of Energy, 2201
West Broad Street, Richmond, VA 23220, (804) 367-0979, Fax (804) 367-6211, Dialcom
DOE466
WASHINGTON ~ Washington State Energy Office, 809 Legion Way SE, FA-11, Olympia, WA
98504-1211 or P.O. Box 43615, Olympia, WA 98504-3165, (206) 956-2000, Fax (206)
753-2397
WEST VIRGINIA - West Virginia Fuel and Energy Office, Building 6, Room 553, State Capitol,
Charleston, WV 25305, (304) 348-4010, Fax (304) 348-3248, Dialcom DOE489
WISCONSIN -- Wisconsin Division of Energy and Intergovernmental Relations, P.O. Box 7868,
Madison, WI 53707, (608) 266-8234, Fax (608) 267-0200
WYOMING ~ Wyoming Energy Conservation Office, Dept. of Commerce, Div. of Economic
Development, Energy Section, Herschler Building, Second Floor West, Cheyenne, WY
82002, (307) 777-7284, Fax (307) 777-5840, Dialcom DOE434
ENVIRONMENTAL OFFICES
ALABAMA - Environmental Management Department, 1751 Congressman W.L., Dickinson
Drive, Montgomery, AL 36130
ALASKA - Environmental Conservation Department, P.O. Box O, Juneau, AK 99811-180
ARIZONA - Environmental Quality Department, 2005 N. Central Avenue, Phoenix, AZ 85004
ARKANSAS - Department of Pollution Control and Ecology, P.O. Box 9583, Little Rock, AR
72219
CALIFORNIA - California Air Resources Board, P.O. Box 2815, Sacramento, CA 95812
C-4
-------
CALIFORNIA -- California Environmental Protection Agency, 555 Capitol Mall, Suite 235,
Sacramento, CA 95814
COLORADO -- Office of Environment, Colorado Department of Health, 4210 East llth
Avenue, Denver, CO 80220
CONNECTICUT -- Department of Environmental Protection, 165 Capitol Avenue, Hartford, CT
06101
DELAWARE -- Natural Resources and Environmental Control, P.O. Box 1401, 89 Kings
Highway, Dover, DE 19901
DISTRICT OF COLUMBIA -- Department of Consumer and Regulatory Affairs, 614 H Street.
N.W., Washington, DC 20001
FLORIDA -- Department of Environmental Regulation, 2600 Blair Stone Road, Tallahassee.
Florida 323399-2400
GEORGIA -- Department of Natural Resources, 205 Butler Street, S.W., Suite 1252, Atlanta,
GA 30334
HAWAII -- Hawaii Department of Health, 1250 Punchbowl, Honolulu, HI 96801
IDAHO -- Division of Environmental Quality, 1410 N. Hilton Street, Boise, ID 83720
ILLINOIS ~ Illinois Environmental Protection Agency, 2200 Churchill Road, P.O. Box 19276,
Springfield, IL 02794
INDIANA -- Indiana Department of Environmental Management, 105 S. Meridian Street,
Indianapolis, IN 46225
IOWA ~ Iowa Natural Resources Department, 900 E. Grand Avenue, Des Moines, LA 50319
KANSAS -- Department of Health and Environment, 900 S.W. Jackson, Suite 901, Topeka, KS
66612-1290
KENTUCKY - Department of Environmental Protection, Ft. Boone Plaza, 18 Reilly Road,
Frankfort, KY 40601
LOUISIANA -- Department of Environmental Quality, P.O. Box 44066, Baton Rouge, LA 70804
MAINE - Department of Environmental Protection, State House Station 17, Augusta, ME 04333
MARYLAND - Department of Environment, 2500 Broening Highway, Baltimore, MD 21224
MASSACHUSETTS - Department of Environmental Protection, One Winter Street, Boston,
MA 02108
MICHIGAN - Department of Environmental Protection, Box 30028, Steven T. Mason Building,
Lansing, MI 48909
C-5
-------
MINNESOTA -- Minnesota Pollution Control Agency, 520 Lafayette Road, 6th Floor, St. Paul,
MN 55155-3898
MISSISSIPPI -- Department of Natural Resources, Box 10385, Jackson, MS 39289-0383
MISSOURI - Department of Natural Resources, 2010 Missouri Boulevard, P.O. Box 176,
Jefferson City, MO 65102
MONTANA - Environmental Sciences Division, Health and Environmental Science Department,
Cogswell Building, Helena, MT 39620
NEBRASKA -- Environmental Control, P.O. Box 98922,, Lincoln, NE 68509
NEVADA -- Environmental Protection Division, Nevada Department of Conservation and
Natural Resources, 201 South Fall Street, Carson City, NV 89701
NEW HAMPSHIRE - New Hampshire Department of Environmental Services, Hazen Drive,
P.O. Box 95, Concord, NH 03302
NEW JERSEY - .Department of Environmental Protection, 401 East State Street - CN 402,
Trenton, NJ 08625
NEW MEXICO - Department of Environment, P.O. Box 26110, Sante Fe, NM 87503-0968
NEW YORK ~ Environmental Conservation Department, 50 Wolf Road, Albany, NY 12233
NORTH CAROLINA ~ Division of Environmental Management, Natural Resources and
Community Development, P.O. Box 27687, Raleigh, NC 27611
NORTH DAKOTA - Environmental Health Section, 1200 Missouri Avenue, Bismarck, ND
58505
OHIO - Ohio Environmental Protection Agency, P.O. Box 1049, 1800 Watermark Drive,
Columbia, OH 43266-0149
OKLAHOMA - Environmental Health Services, Health Department, 1000 N.E. 10th Street, P.O.
Box 53551, Oklahoma City, OK 73152
OREGON ~ Department of Environmental Quality, 811 S.W. Sixth Avenue, Portland, OR 97204-
1334
PENNSYLVANIA - Department of Environmental Resources, Fulton Building, 9th Floor, Box
2063, Harrisburg, PA 17120 .
PUERTO RICO - Environment and Quality Board, P.O. Box 11488, Santurce, Puerto Rico
00910
RHODE ISLAND - Director, Department of Environmental Management, 9 Hayes Street,
Providence, RI 02908
C-6
-------
SOUTH CAROLINA -- Deputy Commissioner, Environmental Quality Control, Department of
Health and Environmental Control, 2600 Bull Street, Columbia, SC 29201
SOUTH DAKOTA -- Environment and Natural Resources, 523 E. Capitol Avenue, Pierre, SD
57501
TENNESSEE -- Commissioner, Department of Health and Environment, 344 Cordell Hull
Building, Nashville, TN 37219
TEXAS -- Texas Water Commission, P.O. Box 13087, Capitol Station, Austin, TX 78711
UTAH -- Executive Director, Department of Environmental Quality, 288 N. 1460 West, Salt Lake
City, UT 84116-0700
VERMONT -- Secretary, Natural Resources Agency, 103 S. Main Street, Building 1-South,
Waterbury, VT 05676 "
VIRGINIA -- Secretary, Department of Natural Resources, 9th Street Office Building,
Richmond < VA 23219
WASHINGTON -- Director, Department of Ecology, St. Martin's College Campus, Abbott-
Raphael Hall - PV-11, Olympia, WA 98504-8711
WEST VIRGINIA ~ Director, Natural Resources Department, 1800 Washington Street,
Charleston, WV 25305
WISCONSIN ~ Secretary, Wisconsin Department of Natural Resources, P.O. Box 7921, Madison,
WI 53707
WYOMING -- Director, Environmental Quality Department, Herschler Building, 122 West 25th
Street, Cheyenne, WY 82002
C-7
-------
BIBLIOGRAPHY OF KEY REPORTS
Benioff, R. 1990. Potential State Responses to Climate Change. Office of Policy, Planning and
. Evaluation, U.S. Environmental Protection Agency. 1990.
DeLuchi, M.A. 1991. Emissions of Greenhouse Gases from the Use of Transportation Fuels and
Electricity. Center for Transportation Research, Energy Systems Division, Argonne National
Laboratory. Argonne, Illinois. November 1991.
Fisher, D.C. 1991. Reducing Greenhouse Gas Emissions with Alternative Transporation Fuels.
Environmental Defense Fund. 1991.
IPCC (Intergovernmental Panel on Climate Change). 1990. Climate Change: The IPCC Scientific
Assessment. Report Prepared fov intergovernmental Panel on Climate Change by Working Group
1.
IPCC. 1992. Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment. Report
prepared for Intergovernmental Panel on Climate Change by Working Group 1.
Lashof, D. A., and D.A. Tirpak. 1990. Policy Options for Stabilizing Global Climate Change. Office
of Policy, Planning and Evaluation, U.S. Environmental Protection, Washington, D.C. December.
Lashof, D.A., and E.L. Washborn. 1990. The Statehouse Effect: State Policies to Cool the Greenhouse.
NRDC, Washington, D.C. July.
National Academy of Sciences. 1991. Policy Implications of Greenhouse Warming. National Academy
Press, Washington, D.C. 127 pp.
National Governors' Association. 1991. A World of Difference: Report of the Task Force on Global
Climate Change. NGA, Washington, D.C. 36 pp.
National Wildlife Federation. 1991. Conservation Directory. Washington, D.C.
Oregon Department of Energy. 1991. Fourth Biennial Energy Plan. Oregon Department of Energy,
Salem, Oregon.
Radian Corporation. 1990. Emissions and Cost Estimates for Globally Significant Anthropogenic
Combustion Sources ofNOf N2O, CH^ CO, and CO2. Prepared, for the Office of Research and
Development, U.S. Environmental Protection Agency, Washington, D.C.
Silbiger, A. and N. Gonring. 1991. Selected Summary of Current State Responses to Climate Change.
Prepared for Climate Change Division, Office of Policy, Planning and Evaluation. United States
Environmental Protection Agency. 199!
B-l
-------
United States Environmental Protection Agency (U.S. EPA). 1991. Adapting to Climate Change:
What Governments Can Do. U.S. EPA, Office of Policy, Planning and Evaluation. Climate
Change-Adaptation Branch. 1991.
Walls, M. et al. 1991. Greenhouse Gas Emissions from Alternative Fuels. Prepared for Office of
Policy Analysis, U.S. EPA. 1991.
B-2
-------
• L-
ERRATA SHEETS
Attached are the correction sheets for the States Workbook: Methodologies for Estimating
Greenhouse Gas Emissions(1995)
If their are any other errors in the Workbook, please contact:
The State and Climate Change Program
Climate Change Division (2122)
US Environmental Protection Agency
401 M Street, SW
Washington DC 20460
(202) 260-8825-PHONE
(202) 260-6405-FAX
fc
-------
CORRECTIONS TO THE STATESWORKBOOK: METHODOLOGIES
TO ESTIMATE GREENHOUSE GAS EMISSIONS
Cozrectiona to Workbook Chapter 1
Table 1-2
• The conversion factor for ethanol should be 0.0764 (Btu/gallon) not
0.764 (Btu/gallon)
Cozrectiona to Workbook Chapter 3
Table 3-2. Methane Emission Factors for Activities
Sector
Activity Data
(MMBTO)
Emissions Factor
(Ibs CH«/MMBTO)
Low
High
Median
Oil & Gas Production
Oil
Gas
Oil & Gas : Venting and
Flaring
Oil Production
Gas Production
Oil & Gas
Produced*
0.0007
0.1072
0.0070
0.0117
0.1958
0.0326
0.0062
0.1515
0.0198
«
Crude Oil Transportation and Refining
• Transportation
Refining
Storage Tanks
Oil Tankered ,
Oil Refined
Oil Refined
0.0017
0.0002
0.0000
5
0.0017
0.0033
0.0006
0.0017
0.0017
0.0003
Natural Gas Processing, Transport, and Distribution
Gas Processing,
Transmission, and
Distribution
Gas Consumption
0.1329
0.2751
0.2040
a Emissions are based on total production of oil and gas.
/
Source: IPCC/OECD, 1992
-------
Corrections to Workbook Chapter 4
Page 4-6
Example
Total coal mine methane emissions for Illinois are calculated as follows:
(million cf) Low High
Underground; 7,514
Surface: 51 &
Post-mining (underground): 658
Post-mining (surface): 129
Total: 8.817
8,923
1,547
1,033
-JZQft
1JJ09
Avg. = (6,817 + 11f709)/2 = 10,263 million cf
10,263 million cf x 20.66 tons/million cf * 212,034 Ions CH*
Corrections to Workbook Chapter 5
Page 5-2, Step 2
• For the equation to estimate "Waste in Place", the units for state population should be provided in
"head" instead of "1,000 head".
Page 5-5
Example Methane generated at smalt landfills for a nonarid state that has waste in place at
small landfills of 5.0 million tons would be estimated as follows:
Smalt landfills: 0,35 (ft3/ton/day) x 5 million tons * 1.75 million tip/day
= 1.75 million ft3/day x 0.0077 (tons CHJvrt = 13,475 tons CrVyr
(fr/day)
-------
Corrections to Workbook Chapter 7
Please include the following table in the section as "Table 7-13. Methane Conversion Factors for Other
Manure Management Systems."
AX
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
HI
se
SD
TN
TX
l)T
VA
VT
WA
WI
WV
WY
DAIRY
75%
0%
• 0%
10%
10%
0%
0%
0%
0%
18%
10%
10%
10%
10%
0%
0%
0%
11%
0%
0%
0%
10%
0%
0%
11%
10%
0%
0%
12%
0%
0%
0%
0%
0%
10%
40%
20%
0%
0%
0%
0%
20%
0%
0%
0%
0%
0%
0%
10%
10%
AN IMA
BEEF
0%
0%
0%
0%
0%
90%
0%
0%
0%
0%
0%
0%
10%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
20%
0%
. 0%
0%
0%
0%
0%
10%
0*
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
OH
L TYPES
SWINE
0%
0%
0%
0%
10%
10%
10%
0%
0%
10%
10%
20%
10%
10%
0%
0%
0%
0%
0%
0%
0%
.10%
20%
0%
10%
10%
0%
0%
0%.
0%
0%
- 0%
0%
0%
10%
0%
20%
0%
0%
0%
0%
0%
20%
0%
0%
0%
0%
0%
0%
10%
OTHER
10%
0%
0%
0%
10%
0%
0%
0%
10%
10%
90%
10%
0%
0%
0%
0%
10%
. 10%
10%
0%
10%
10%
0%
0%
20%
0%
10%
0%
0%
0%
10%
10%
10%
10%
0%
0%
0%
20%
10%
10%
0%
0%
20%
10%
10%
10%
0%
20%
30%
0%
-------
Corrections to Workbook Chapter 10
Average Annual Accumulation of Dry Matter as Biomass in Plantations
Forest Types
Tropical
Temperate
Acacia spp.
Eucalyptus spp.
Tectona grandii
Pintu spp.
Pinus caribaea
Mixed Hardwoods
Mixed Fast-Growing Hardwoods
Mixed Softwoods
Douglas Fir
Loblolly Pine
Average Annual Increment in Biomass
(t dm/acre/yr)
6.7
6.5
3.6
5-1
4.5
3.0
5:6
6.5
"2.7
1.8
Source: Derived from IPCC, 1994
Table 10-2
Aboveground Dry Matter in Tropical Forests
(t dm/acre)
Moist Forest
Primary
102.6
Secondary
84.8
Seasonal Forest
Primary
62.5
Secondary
53.5
Dry Forest
Primary
26.8
Secondary
11.2
Source: Derived from IPCC, 1994
Table 10-3
Aboveground Dry Matter in Temperate and Boreal Forests
(t dm/acre)
Primary
Secondary
Temperate Forests
Evergreen
131.6
98.1
Deciduou
s
111.5
78.1
Boreal Forests
73.6
• 53.5
Source: Derived from IPCC, 1994
-------
Table 10-4
Carbon in Forest Soils
(tons C/acre)
Forest Type
Tropical
Moist
51.3
Seasonal
44.6
Dry
26.8
Temperate
Pri
'rimary
econdary
Evergreen
59.8
53.5
Deciduous
59.8
53.5
Boreal
Primary
Secondary
91.9
82.5
Source: Derived from IPCC, 1994
Note: See Table 1-3 of Birdsey (1992) for region-specific values of forest soil carbon in the U.S.
Table 10-5
Average Annual Biomass Uptake by Natural Regeneration
(t dm/acre)
Region
Tropical
Forest Types
Moist Forests
0-20 yrs
3.6
20-100 yn
0.40
. Seasonal
Forests
0-20 yn
2.2
20-100 yrs
0.22
Dry Forests
0-20 yrs
1.8
20-100
yn
0.11
Note: Growth rates are derived by assuming that tropical forests regrow to 70 percent of undisturbed forest
biomass in the first twenty years. All forests are assumed to regrow to 100 percent of undisturbed forest biomass in 100
years. Assumptions on the rates of growth in different time periods are derived from Brown and Lugo, 1990.
Temperate
Evergreen
Deciduous
Boreal
0-20 yn
1
3
0.89
0.45
20-100 yrs
1
3
0.89
0.45
*x^&&&
;- '-.^V'^A
•• , fjf ff> ••'<&?• ;
>' . f ^^ &••*
'f^f;|r*
"Vl>X*^
' '•• *% •?s~gsH
^LlP§3i
wf *, vj- j3^,^^^ -$j$
Source: Derived from IPCC, 1994
Note: Temperate and boreal forests actually require considerably longer than 100 years to reach the biomass
density of a fully mature system. Harmon et al. (1990), for example, report carefully designed simulations indicating that
a 100-year old stand of douglas fir would contain only a little over half the biomass of a 450-year old growth stand of the
same species. There is also evidence that growth rates in temperate and boreal systems are more nearly linear over
different age periods than is the case for tropical systems. Nabuurs and Mohren (1993) suggest that growth rates for
several different species in temperate and boreal zones rise slowly and peak at ages of 30 -55 years and decline slowly
thereafter. This suggests that using the same default values for 0-20 years and 20-100 years may be a reasonable first
approximation. Nabuurs and Mohren (1990) also illustrate that growth rates may vary as much as a factor often for
stands of the same species and age, depending on site-specific conditions.
Table 10-6
Annual Soil Carbon Accumulation in Temperate and Boreal Forests
(tons C/acre/yr)
Temperate
Evergreen
0.58
Deciduous
0.58
Boreal
0.89
Source: Derived from IPeC( 1994).
-------
page 10-5
• If necessary, enter the Biomass Conversion/Expansion Ratio in tons of dry matter per cubic foot (t
dm/ft3) in Column G. The default conversion ratio (or biomass density) is 0.016 t dm/ft3 (see Table 1-2 of
Birdsey, 1992 (provided at the end of this chapter) for some species-specific densities for the U.S.). In
addition, an expansion factor should be applied if the timber harvest data do not account for all of the
biomass that is destroyed during the harvest process, e.g., limbs, small trees, etc. The following default
ratios can be used: 1.75 for undisturbed forests; 1.9 for logged forests; and 2 for unproductive forests (see
Table 1-1 of Birdsey, 1992 (provided at the end of this chapter) for region- and forest type-specific
expansion factors for the U.S.). If both conversion and expansion factors are needed, they can be combined
by using ratios which are the product of the two: 0.027 t dm/ft for undisturbed forests; 0.0301 dm/ft for
logged forests; and 0.0311 dm/ft3 for unproductive forests.
page 10-8
• Enter the Aboveground Biomass Density in tons of dry matter per acre (t dm/acre) after conversion
in Column C. This figure includes any biomass not fully cleared (default value = 0) and the biomass
regrowth in agricultural use (the default value is 4.5 tons dry matter per acre) or other use subsequent to
clearing.
page 10-9
• Enter the Soil Carbon Content Before Conversion by forest or grassland type in Column B. See
Table 10-4 for forest soil defaults. Defaults for grasslands are 26.8 tons/acre for tropical zones and 31.2
tons/acre for temperate zones.
Corrections to Workbook 12
Page 12-2, Step 2
• For the equation to estimate "BODs Generated", the units for population should be provided in
"head" instead of" 1,000 head".
-------
Corrections to Discussion Chapter 4
page D4-7
• The emissions factors in the box presented should read as follows:
Basjn
Northern Appalachian
Central Appalachian
Black Warrior
Illinois Basin
Rockies & Southwest
Emissions Factor
(cf CHj/ton of coal minedt
425 - 740
215-325
2000 - 3000
160 - 190
370 - 470
Corrections to Discussion Chapter 10
Table D10-1
Aboveground Dry Matter in Tropical Forests
(t dm/acre)
Moist Forest
Primary
102.6
Secondary
84.8.
Seasonal Forest
Primary
62.5
Secondary
53.5 .
Dry Forest
Primary
26.8
Secondary
11.2
Source: Derived from IPCC, 1994
Table D10-2
Aboveground Dry Matter in Temperate and Boreal Forests
(t dm/acre)
Primary
Secondary
Temperate Forests
Evergreen
131.6
98.1
Deciduou
s
111.5
78.1
Boreal Forests
73.6
53.5
Source: Derived from IPCC, 1994
-------
Average Annual Accumulation of Dry Matter as Biomass in Plantations
Forest Types
Tropical
Temperate
Acacia spp.
Eucalyptus spp.
Tectona grcmdis
Pinus spp.
Pinus caribaea
Mixed Hardwoods
Mixed Fast-Growing Hardwoods
Mixed Softwoods
Douglas Fir
Loblolly Pine
Average Annual Increment in Biomass
(t dm/acre/yr)
6.7
6.5
3.6
5.1
'4.5
3.0
5.6
6.5
2.7
1.8
Source: Derived from IPCC, 1994
Table D10-5
Carbon, in Forest Soils
(tons C/acre)
Forest Type
Tropical
Moist
51.3
Seasonal
44.6
Dry
26.8
Temperate
rimary
econdary
Evergreen
59.8
53.5
Deciduous
59.8
53.5
Boreal
Primary
Secondary
91.9
82.5
Source: Derived from IPCC, 1994
-------
Table D10-6
Average Annual Biomass Uptake by Natural Regeneration
(t dm/acre)
.,.: . Region
, ;•'"-"
" Tropical
'.,'"' Forest Types
Moist Forests
0-20 yn
3.6
20-100 yn
0.40
Seasonal
Forests
0-20 yn
2.2
20-100 yn
0.22
Dry Forest*
0-20 yn
1.8
20-100
yn
.0.11
Note: Growth rates are derived by assuming that tropical forests regrow to 70 percent of undisturbed forest
biomass in the first twenty years. All forests are assumed to regrow to 100 percent of undisturbed forest biomass in 100
years. Assumptions on the rates of growth in different time periods are derived from Brown and Lugo, 1990.
Temperate
Evergreen
Deciduous
Boreal
0-20 yn
1-3
0.89
0.45
20-100 yn
1
3
0.89
0.45
— "x ; 5,
1 X- f*
^ ^ C< •& -s'-
<.% s \
% * ' '
1 &%J53S$«$
" \ s^^fl
^SfefS
:*;**$
Source: Derived from IPCC, 1994
; . Note: Temperate and boreal forests actually require considerably longer than 100 years to reach the biomass]
density of a fUUy mature system. H&taon et al. (1 990), for example, report carefully designed simulations indicating that
a 100-year' old stand of douglas fir would contain only a little over, half the biomass of a 450-year old growth stand of the
same species. There is also evidence that growth rates in temperate and boreal systems are more nearly linear over^,
different age periods than is the case for tropical systems. Nabuurs and Mohren ( 1 993) suggest that growth rates for
several different species in temperate and boreal zones rise slowly and peak at ages of 30 -55 years and decline slowly
thereafter. This suggests that using the same default values for 0-20 years and 20-100 years may be a reasonable first
approximation. Nabuurs and Mohren ( 1 990) also illustrate that growth rates may vary as much as a factor of ten for
stands- of the same species and age, depending on site-specific conditions.
Table D10-7
Annual Soil Carbon Accumulation in Temperate and Boreal Forests
(tons C/acre/yr)
' - '•-•."- .^; .^"':VV>j-.>_ Tethperate. .• ' ''
.,,'. Evergreen
__•
Deciduous
.•"0.5SF ^ : I , 0,58
Boreal
0.89
Source: Derived from IPCG (1994).
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