| Overview | Carbon Dioxide | Methane | Nitrous Oxide | Criteria Pollutants | Land Use Issues |
Emissions estimates in this report are generated largely by multiplying some activity factor, such as coal or natural gas consumption, by an emissions coefficient. The reliability of both the activity data and the emissions coefficients used in this report varies widely. This Appendix discusses the uncertainties associated with the estimates and extrapolations presented in the report.
The uncertainties in emissions estimates come from collecting data from a limited number of sources. The data are weighted or extrapolated to obtain national estimates for similar sources in each category or industry. This estimation approach is a method to scale up the average emissions from a source, determined by a limited sample, to represent the population of emissions from each category or fuel. This method uses the concepts of emissions coefficient and activity factor for each category. For each category or fuel type:
Since each factor contains both bias and sampling errors, the estimate of the national emissions for a category is:
where EC is the emissions coefficient and AF is the activity factor. Bias is a systematic non-random error which, in this case, is usually imbedded in the AF term and due to systematic imperfections in the data collection process, whereas the random sampling error is generally attributed to small sample size, measurement and reporting errors, and timing problems.
In general, estimates of carbon dioxide emissions are more reliable than estimates for other gases. While this report does not explicitly calculate uncertainty ranges, it is likely that the estimate of carbon dioxide emissions is accurate to within 10 percent, implying an emissions range from 1.3 billion to 1.6 billion metric tons. To the extent that the activity factor is somewhat understated within the point estimate, the actual (unobservable) value is likely to be somewhat higher, because this report cannot capture all emissions sources.
Estimates of methane emissions are much more uncertain. The level of precision is probably on the order of 30 to 50 percent. Estimates of methane emissions are also likely to understate actual emissions, as a result of the exclusion of sources that are unknown or difficult to quantify.
Nitrous oxide emissions estimates are by far the most unreliable. Estimates of emissions from nitrogenous fertilizers are only accurate to an order of magnitude, making them either the largest source of nitrous oxide emissions or, alternatively, an insignificant source. Coefficients for nitrous oxide emissions from fossil fuel combustion are not available for all sources and, where available, may be unreliable. Additionally, several known sources of nitrous oxide are not measured and therefore are excluded from estimated totals.
Most carbon dioxide emissions estimated in this report are the result of the combustion of fossil fuels. The uncertainties in estimates of emissions from fossil fuel combustion can be divided into four types:
In general, EIA energy statistics are most accurate where the energy industry is highly concentrated and/or heavily regulated, and least accurate where activities are decentralized, with large numbers of producers or consumers, or the fuel exists in many heterogeneous states.
While it is impossible to be certain about the absolute magnitude and distribution by type of error in the energy data, it is unlikely that most of the error is “bias error” rather than random “sampling error.” The EIA collects the same data from mostly the same respondents every year (although survey frames are systematically updated), using mostly the same methods. Product flows that escape the coverage of the statistical system are likely to stay outside the statistical system from one year to the next. Similarly, if respondents make undetected definitional or computational errors (for example, misclassifying a petroleum product), they are likely to repeat their mistake for prolonged periods.
There is indirect evidence in favor of the relative unimportance of random error in energy statistics, in the form of the relative lack of variability of these statistics compared with other economic time series. That most EIA surveys are censuses, with what is intended to be 100 percent coverage of eligible respondents, rather than small sample surveys, reduces the scope for random errors.
If, as we suspect, random error is relatively unimportant, then most of the error is bias error, made in essentially the same way every year. This implies that while the level of U.S. emissions of carbon dioxide could be systematically lower or higher than reported here, the reported trends over time are more reliable than the uncertainties in the energy data would suggest. Since energy production and consumption are covered by multiple surveys, it is possible to use this information to gain insight into the possible uncertainties in the energy data.
Coal. Coal production and consumption data are based on weight—short tons of coal. Coal consumption by regulated electric utilities, including both tonnage and energy content, is universally reported to the EIA and the Federal Energy Regulatory Commission (FERC). In 1994 utility coal consumption accounted for about 88 percent of U.S. coal consumption. There are likely to be only minor errors (around 1 percent) in reported utility coal consumption. Industrial, residential, and commercial coal consumption estimates are subject to potentially larger errors, especially in the counting of residential and commercial sector consumption.
The statistical discrepancy for coal production (the difference between reported consumption and reported production less exports, plus imports, plus stock changes) was on the order of 5 million short tons, or about 0.6 percent of consumption, in 1994.
Natural Gas. Most natural gas is sold or transported by State-regulated local distribution companies. Excluding imports, the statistical discrepancy for natural gas has an average value of between 2 and 3 percent of consumption, with reported consumption usually smaller than reported production. This may imply some systematic source of underreporting of consumption.
Inaccuracies in natural gas volumetric data come from inherent limitations in the accuracy of natural gas metering, as well as the usual problems of misreporting and timing differences. For example, natural gas consumption by electric utilities, as reported by the utilities, averaged about a 0.7-percent difference from natural gas consumption as reported by natural gas sellers in 1994 [189].
Petroleum. U.S. petroleum consumption was estimated on the basis of “petroleum products supplied,” which means the volume of petroleum products shipped from primary storage facilities. Since there are only about 200 oil refineries in the United States, coverage of crude oil inputs and refinery outputs is generally complete.
The EIA requires a detailed breakdown and accounting of petroleum products produced by refineries, including refinery fuel. There are several reporting anomalies in EIA petroleum data:
The unfinished oil discrepancy is probably due to the asymmetric treatment of interrefiner sales of unfinished oils. To the buyer, who knows the intended use of the product, it is motor gasoline or distillate fuel. To the seller, it is an unfinished oil. In the State Energy Data Report, the unfinished oil discrepancy is accounted for through an adjustment to “other oils.” However, the implication is that total oil consumption figures are more reliable than the exact distribution of consumption across specific petroleum products. Overall, it is likely that petroleum consumption estimates are accurate to within 5 percent.
Nonfuel Use. Data for nonfuel use of petroleum products are more uncertain than those for total use of petroleum products. There are two main methods of estimating nonfuel use:
The main uncertainty in estimating carbon sequestered from nonfuel use is not the amount of product used, but the fate of its carbon. The sequestration percentages used in this report are estimates, originally based on the typical fate of a particular class of products. The actual distribution of nonfuel uses of products is not always known with precision and could vary considerably from the “typical” usage. However, since sequestration through nonfuel use corresponds to only about 5 percent of total emissions, even large variations in the amount sequestered would have a small effect on estimated total emissions.
EIA oil and gas data are collected in volumetric units: barrels of oil and billion cubic feet of gas. Carbon emissions factors for fossil fuels usually take the form of tons of carbon per unit of energy content. Emissions factors are computed by dividing the carbon content (by weight) of a particular fuel by its energy content. Thus, in order to match an emissions factor to a fuel accurately, it is necessary to know its energy content with precision; and in the case of fuel quantity based on volumetric data, it is also necessary to know the density of the fuel.
Each step that transforms the data from native units into more useful units inevitably reduces the precision of the resulting data, because the conversion factors are themselves statistical estimates or extrapolations, which may not precisely match the actual composition of the fuel.
Coal. Coal data are collected by State, coal rank, and weight (short tons). Electric utilities are asked to report both the rank and the energy content of the coal they burn. Since, in principle, utilities need to know the energy content of the fuels they purchase with precision, the energy content data should be fairly accurate. On the other hand, there is considerably more uncertainty in the rank or energy content of coal distributed outside the utility sector, which in 1994 accounted for about 12 percent of U.S. coal consumption.
The quality of coal can vary considerably within States and within a particular rank. Lignite, for example, is defined as containing 6,300 to 8,300 Btu per pound, a range of about 15 percent. Subbituminous coal, by definition, has a range of 8,300 to 11,500 Btu per pound [193]. Thus, due to the ranking of the heat content, there may be errors of up to 15 percent in the industrial and residential/commercial coal conversion factors. Residential/commercial and industrial coal consumption accounts for only about 5 percent of total U.S. energy-related carbon emissions. Hence, even large errors would have only a small impact on the ultimate estimates.
Natural Gas. The composition of natural gas also varies considerably. In a recent survey of several thousand gas samples taken from local distribution companies around the United States, the Btu content ranged from 970 to 1,208 Btu per thousand cubic feet [194]. However, 80 percent of the samples fell within a much narrower range of 1,006 to 1,048 Btu per thousand cubic feet. Further, the average and median values of the samples fell within 0.3 percent of the national-level figure as reported in EIA’s Natural Gas Annual. This comparison suggests that EIA data on the energy content of natural gas are accurate to within 0.5 percent. This is not surprising, because local distribution companies monitor the energy content of natural gas to ensure adherence to contractual specifications, and they report the average energy content to the EIA.
Petroleum. The energy content of petroleum products varies more by volume than by weight. The density and the energy content of petroleum products are rarely measured by producers or consumers, and hence they are frequently not known with precision. Electric utilities measure the energy content of the residual oil they burn and report it to the EIA. Liquid petroleum gases (propane, butane, and ethane) are pure compounds, and their energy content can be computed directly.
Liquid transportation fuels (jet kerosene, gasoline, and diesel fuel) are complex mixtures of many compounds, whose physical properties can vary considerably. Their energy content is not measured by consumers nor directly defined by product specifications. The EIA estimates the energy content of these fuels on the basis of standard or “typical” values for each product. The standard energy contents for motor gasoline and kerosene-based jet fuel are drawn from a 1968 report produced by the Texas Eastern Transmission Corporation [195]. The energy content of distillate fuel oil is drawn from a Bureau of Mines Standard adopted in January 1950 [196]. Jet fuel and diesel samples obtained for this report showed an average energy content that differs from EIA estimates by about 2 percent. Samples of motor gasoline analyzed by the National Institute of Petroleum and Energy Research displayed an average energy content that differs from EIA estimates by less than 0.5 percent. Reformulated gasoline, with the additives MTBE, ETBE, and TAME typically representing about 10 percent of its volume, can be expected to have an energy content about 1 percent lower than standard gasoline. However, when collecting and disseminating motor gasoline data in units of energy, the EIA does not use a distinct conversion factor for reformulated gasoline.
Carbon emissions coefficients are calculated by dividing the carbon content of a particular fuel (for example, 0.85 metric tons of carbon per metric ton of fuel) by the energy content of that fuel (say, 43 million Btu per metric ton), producing an emissions coefficient (in this example, 19.8 million metric tons of carbon per quadrillion Btu). Both the energy content and the carbon content of the fuel are subject to a degree of uncertainty. The carbon content of fuels has only an indirect and general bearing on their economic value and consequently is not necessarily collected by fuel producers or consumers. While coefficients for coal and natural gas rely on analyses of a large set of fuel samples, coefficients for several petroleum products are based on “typical” or “representative” values, which may or may not perfectly reflect the underlying composition of the fuel. Variation in carbon content is limited to plus or minus 5 percent by the standard ratios of carbon to hydrogen in the hydrocarbon compounds that compose petroleum [197].
Coal. There are large variations in the carbon and energy content of coals in different parts of the United States. Lignite may have as little as 12.6 million Btu per ton and contain 36 percent carbon, while anthracite may have as much as 98 percent carbon and an energy content as high as 27 million Btu per ton [198].
The carbon and heating values of coal are, in general, controlled by two factors:
Most of the gross variation in both energy and carbon content (for example, between lignite and anthracite) is due to variations in nonflammable impurities. Consequently, if the Btu content of coal is estimated accurately, most of the variation in the carbon content is removed.
There is, however, residual uncertainty about the ratio of carbon to hydrogen and sulfur in particular coals. The carbon content of any particular coal sample can be determined by chemical analysis, but characterizing the average carbon content of national coal production creates some uncertainty. For this report, the EIA relied on chemical analyses of several thousand coal samples, sorted by State of origin and coal rank, to compute national weighted average emissions coefficients (in million metric tons of carbon per million Btu) for each coal rank.
Natural Gas. Natural gas also varies in composition, but the range of variation is much smaller than for coal. The emissions coefficient used in this report was based on an analysis of some 6,743 recent samples of U.S. natural gas. While there is some residual uncertainty about the exact carbon content of average U.S. natural gas, it is on the order of 1 percent or less.
Petroleum Products. Crude oil is refined into a wide range of petroleum products, each presenting a different set of uncertainties. In general, the carbon content of petroleum products increases with increasing density. Uncertainties in emissions coefficients arise primarily from estimating the wrong density for a fuel, or from mismatching the carbon and energy content of a particular fuel. The emissions factors for liquefied petroleum gas (LPG) and motor gasoline are probably accurate to within 1 to 2 percent. Coefficients for jet fuel and diesel fuel are probably accurate to within 2 to 4 percent, with much of the uncertainty centered in the standard heat contents used. The estimate for residual fuel is more uncertain but probably accurate within 3 to 5 percent, as there are remaining uncertainties about the exact density and carbon content of the fuel.
The uncertainty for some minor petroleum products remains large, in some cases because it has proven difficult to identify exactly how reporters define particular product categories. Products with large remaining uncertainties include petrochemical feedstocks (density and portion of aromatics), lubricants, and waxes and polishes. The uncertainty of the emissions coefficients for these products is probably on the order of 10 percent. Because these products share a large nonfuel use component, their impact on the total carbon emissions figure is muted. Still gas is a highly variable byproduct of the refining process, which is then described as a petroleum product. Thus, the estimated emissions coefficient for still gas may vary by as much as 40 percent.
U.S. Territories. Energy data for U.S. territories present certain problems. Published petroleum data for Puerto Rico and the Virgin Islands are considerably less detailed than those for the mainland United States. In particular, there is no estimate of nonfuel use for these territories, and much of the petroleum consumption that could potentially be considered nonfuel use is lumped together into “other petroleum.” Hence, the reliability of the emissions estimates is lower than for petroleum emissions estimates generally.
Unmetered Gas Consumption. Since the estimate for unmetered gas consumption is actually a balancing item, the uncertainty of the estimate is very large, on the order of 100 percent. Fortunately, this is only a small source of carbon emissions.
Flare Gas. Estimates of emissions from flare gas are subject to uncertainty from two sources: estimates of the volume of gas flared, and the application of an appropriate emissions coefficient. Estimates of gas flared are based on State-reported volumes of gas “vented or flared” and a State-by-State estimate of the share flared. The 1994 estimate of all vented and flared gas was 228,336 million cubic feet. States may define “flared” gas differently. This suggests that estimates may be upwardly biased by the inclusion of low carbon emitting gases in the statistics, but the degree of bias is unknown.
The emissions coefficient applied to flare gas represents the average coefficient for natural gas samples with heat contents between 1,100 and 1,127 Btu per standard cubic foot. The EIA estimates the heat content of “wet” gas at 1,110 Btu per standard cubic feet [199]. Anecdotal evidence suggests that most flared gas is flared at gas processing facilities, where the wet gas energy content would be representative. However, if flared gas is mostly “rich” associated gas with a heat content between 1,300 and 1,400 Btu per standard cubic feet, the current coefficient seriously biases estimates downward. Alternatively, it is possible that flare gas from treatment plants is “off spec” gas with a large content of hydrogen sulfide or inert gas and, hence, an emissions coefficient lower than the one actually used.
The principal source of uncertainty in cement manufacture is the lime content of cement, which is estimated to within about 3 percent. There may also be a degree of imprecision in the estimate of cement production, due to possible production in Puerto Rico (excluded in this report) and limitations on the inherent accuracy of the Interior Department data used to calculate the estimate.
A second source of uncertainty, common to all the industrial estimates, is the use of stoichiometric computations to estimate emissions. This method calculates an emissions factor based on a chemical reaction known to have taken place. It assumes, in effect, that the product produced (cement, lime, soda ash) is 100 percent pure, and that no raw materials are wasted in its production. In practice, impurities in the output would tend to reduce emissions below the stoichiometric estimate, while “wastage” of raw materials would tend to raise emissions above the estimate.
Appendix D lists several sources of emissions that are excluded because of uncertainty. Sources excluded because of insufficient data include emissions from natural gas plants, emissions from shale oil production, and carbon dioxide in geothermal steam. Taking what is known about all excluded sources, additional emissions would probably be less than 10 million metric tons, or less than 1 percent of estimated emissions. Nonetheless, their exclusion does slightly bias the estimate downward. There are almost certainly other sources of carbon emissions unknown to the authors of this report. There is no way to estimate the impact of such unknown additional sources.
Estimates of methane emissions are, in general, substantially more uncertain than those for carbon dioxide. Methane emissions are rarely systematically measured. Where systematic measurements have been made, data are restricted to a small portion of the emission sites and a few years. In order to use these data to sufficiently estimate emissions for the full population of emitters, and to develop time-series emissions estimates, scaling mechanisms and sampling techniques must be applied, which will introduce additional error.
Where no systematic measurements have been made, estimation methods rely on a limited set of data applied to a large and diverse group of emitters. However, as additional data comes available each year, uncertainty in emissions estimates declines or, at a minimum, is more clearly delineated. In this year’s report, additional information on emissions from oil and gas operations and municipal wastewater was incorporated into the estimates, significantly reducing uncertainty levels for these sources.
Emissions from coal mines are currently the fourth-largest source of methane emissions in the United States—behind landfills, oil- and gas-related emissions, and domestic livestock—and accounts for approximately 13 percent of national methane emissions. Methane emissions from coal mining have five sources: ventilation systems in underground mines, degasification systems in underground mines, emissions from surface mines, post-mining activities, and emissions from abandoned or closed mines. Only the first four are included in emissions estimates, because data on emissions from abandoned mines are lacking. The uncertainty associated with estimates of emissions from each of the sources included varies considerably and according to the year of the estimate. Based on comparison with other estimates recently published, the overall uncertainty of estimates for emissions from coal mines is probably about 35 percent [200].
Emissions from ventilation systems in the Nation’s gassiest mines are measured on a quarterly basis by the Mine Safety and Health Administration (MSHA). The Bureau of Mines (BOM) has developed a database from MSHA reports for all mines emitting more than 100,000 cubic feet of gas per day. Data on emissions from this source are available for 1985, 1988, 1990, and 1993. Although the measurements themselves should be reasonably accurate, each measurement represents a point in time. Variations in methane emissions across time (e.g., resulting from changes in operating practices) suggest an uncertainty in the range of 10 to 40 percent. The EPA has measured coal mine methane emissions estimates from 1990 through 1994. These estimates exhibit ranges of about 3 to 5 million metric tonnes, giving an uncertainty of 67 percent.
Estimates of emissions from the ventilation systems of nongassy mines are scaled to emissions estimates for 1988 developed by the U.S. Environmental Protection Agency (EPA) [201]. The EPA estimates emissions from nongassy mines at 2 percent of total emissions from the ventilation systems of underground coal mines. Thus, an error as high as 100 percent for this source would add less than 1 percent to the total estimate.
Emissions from degasification systems may be the single largest source of uncertainty in estimates of emissions from coal mines. The estimation method used in this report scales emissions to estimates of emissions for 1988 developed by the EPA. Measurements of emissions were limited to a few mines, with the remainder of the estimate based on known emissions from ventilation systems and estimated recovery efficiencies of degasification systems. The recovery efficiencies have an uncertainty in the neighborhood of 20 percent.
Reliable measurements of emissions from surface mines are available for only five sites. Thus, estimates for this report were based on an emissions range supplied by the Intergovernmental Panel on Climate Change (IPCC) [202]. The range of emissions suggested by the IPCC implies an uncertainty range of plus or minus 75 percent. However, estimates of emissions extrapolated from the five measured sites suggest an uncertainty level of less than 10 percent [203]. Assuming the larger uncertainty level would add only about 10 percent to the overall uncertainty of estimates of emissions from coal mines, because the volume of emissions from surface mines is relatively insignificant.
Emissions from post-mining activities are also estimated on the basis of an emissions range supplied by the IPCC. This emissions range implies an uncertainty in the area of plus or minus 60 percent. However, the magnitude of emissions from this source is similar to that of emissions from surface mines, thus also contributing about 10 percent to the overall uncertainty of coal mine emissions estimates.
The uncertainty associated with emissions estimates from oil and gas operations can be divided
into two
areas: uncertainty associated with estimates for production, transmission, and distribution; and
uncertainty
in estimates of emissions from gas venting.
Estimates of emissions from production, transmission, and distribution of natural gas are
calculated by
extrapolating measured emissions data for a small number of emission sources to the full U.S.
natural gas
system. This is done by using data obtained from a sample of emissions sources to develop
individual
emissions factors for each of the components in the natural gas system, such as engines,
compressors,
pipelines, wellheads, and regulators. Emissions factors are then multiplied by an activity factor
that
represents either the number of units in the source category, or the level of usage for such units.
In previous editions of Emissions of Greenhouse Gases in the United States, the EIA
adopted
emissions factors used in a 1990 report on anthropogenic methane emissions prepared by the
U.S.
Environmental Protection Agency (EPA) [204]. These
factors
were based on very small or nonrepresentative samples. Emissions factors from oil and gas wells
were
based on four model facilities. Emissions factors for distribution pipeline were based on the
distribution
networks of two California utilities that consisted of mostly new, low-leakage plastic pipeline.
Because
much of the Nation’s distribution pipeline continues to be cast iron with a greater
propensity to leak, these
emissions factors biased estimates substantially downward.
For this year’s report, EIA adopted emissions factors from a more recent study funded
jointly by EPA and
the Gas Research Institute (GRI) [205]. The EPA/GRI
study
capitalized on an extended field sampling program and a statistical framework to meet
predetermined
accuracy goals. The more recent study benefitted from data that had not been previously available
on
emissions from pneumatic devices and compressors, the number of metering and regulating
stations, and
emissions from customer meters. The EPA/GRI study also gained from the inclusion of
distribution
systems with cast iron pipe in their measurement samples [206].
Together, these sources produced about 1.5 million metric tons more methane in 1992 than had
been
estimated previously.
While the use of the improved emissions factors from the EPA/GRI report does reduce the
overall
uncertainty of EIA’s emissions estimate from more than 100 percent on the high end of
the range,
significant uncertainty remains. In developing their emissions factors, EPA/GRI did not use
random
sampling or stratified random sampling methods. Instead, sites for measurement were selected at
random
from known lists of facilities, such as GRI or American Gas Association (AGA) member
companies.
Selected companies were not, however, required to participate. Participating companies were
asked to
choose representative sites for sampling rather than one-of-a-kind facilities [207]. Using this sampling technique, the uncertainty of
the point
estimate of 1992 emissions developed for the EPA/GRI report was plus or minus 35 percent.
The EIA developed time-series emissions estimates for the natural gas industry based on the
estimate for
1992 produced by EPA/GRI. As capital stock is replaced or added to the natural gas system,
emissions
factors may change somewhat. Thus, the use of time-series estimates probably adds some error,
though
overall uncertainty should remain below ±50 percent.
Estimates of emissions from venting are also uncertain. The EIA maintains statistics on gas
vented or
flared as reported on a State-by-State basis, but no distinction is made between venting and
flaring in
those statistics. Gas flared releases carbon dioxide rather than methane. This report estimates the
national
share vented on the basis of the estimated share vented for each State.
An additional uncertainty associated with estimates of methane vented is methane vented at
“stripper wells.” Associated natural gas production at oil wells producing less than
10 barrels
per day may be at pressures and volumes too low to be of commercial value. The gas may be
vented or
merely evaporate from storage tanks. Such emissions are not captured in any data series. The
magnitude
of the emissions is impossible to estimate, but “stripper wells” comprise 14 percent
of U.S. oil
production.
Most methane emissions from stationary combustion are the result of wood burning in residential
woodstoves. Because estimates of wood consumption as well as the maintenance and efficiency
of
residential woodstoves are highly uncertain, estimates of emissions from this source may vary by
more
than an order of magnitude.
Methane emissions from mobile combustion may be larger than the estimate offered in this
report, but
it is unlikely that they are significantly smaller. Emissions factors for mobile transportation
assume a
well-maintained fleet. A fleet of inadequately maintained vehicles may have as much as 10 times
the level of
emissions of a fleet of well-maintained or new vehicles. Although much of the U.S. fleet is
well-maintained, a portion is old and/or poorly maintained.
Estimates of methane emissions from landfills were broken into two sources: emissions from
waste
contained in 105 mostly large landfills with gas recovery systems; and emissions from waste
contained
in all other landfills. Uncertainties associated with estimates of emissions for these two sources
differ
substantially.
Emissions for many of the 105 mostly large landfills were estimated for 1992, based on volumes
of gas
recovered multiplied by gas recovery efficiency [208].
Gas
recovery efficiency was estimated, with an associated uncertainty of plus or minus 25 percent.
For years
other than 1992, emissions from this source were estimated using a model of landfill waste
emissions that
is benchmarked to the 1992 data. The model parameters include a low yield and high yield
scenario that
imply an uncertainty of 35 percent.
Emissions from all other landfills were also estimated using an emissions model. This
model’s input
parameters could vary by 30 percent from the mean. A crucial input into the model is amount of
waste
in place. The amount of waste in place was calculated from estimates of waste landfilled annually
between
1960 and 1994 and using a regression equation to backcast waste flows from 1940 to 1960. The
range of
published estimates for years in which multiple sources were available suggests an uncertainty in
the
neighborhood of plus or minus 33 percent, while the error associated with the regression equation
probably adds another 2 to 10 percent additional uncertainty [209].
The ratio of waste in place in the 105 landfills relative to that in all other landfills was assumed
to remain
constant over time. This may be misleading, since the total number of landfills has been
declining, with
greater shares of waste believed to be directed toward larger landfills. Because those landfills
with
measured emissions for 1992 are likely to have higher-than-average emissions per ton of waste,
estimates
may be biased upward in earlier years.
Methane emissions from domestic and commercial wastewater treatment was estimated by
IPCC’s [210] simplified approach, which is based on the
following
assumptions: (1) each person contributes 0.5 kg per day of BOD5 to municipal
wastewater;
(2) 15 percent of this wastewater is treated anaerobically; and (3) anaerobic treatment yields 0.22
kg of
methane per kg of BOD5 treated. These assumptions were developed for developed
countries in general and there is considerable uncertainty regarding their applicability to the
United States.
Per capita organic loadings of municipal wastewater in developed nations ranges from 0.024 to
0.091 kg
BOD5/day. Organic loadings depend on such factors as the amount of kitchen
wastes that
are discharged to sewers and the degree to which industrial wastewaters are discharged to
municipal
wastewater treatment systems. Wastewater treatment methods that are potential sources of
methane
include anaerobic digesters, facultative and anaerobic lagoons, and septic tanks. However,
reliable
information on the quantity of wastewater treated by each of these methods is not available. The
IPCC
emissions factor of 0.22 kg of methane per kg of BOD5 is based on an estimate for
lagoons
in Thailand [211]. The applicability of this factor to
treatment
methods in the United States is uncertain.
A further source of uncertainty is the ultimate fate of methane generated from wastewater in the
United
States. As in the case of landfill methane, wastewater methane generated in sewage treatment
plants may
often be combusted to control odors or emissions of volatile organic compounds. Conceptually,
the
amount of methane combusted should be deducted from estimated emissions. However, the EIA
is not
aware of any information on the amount or extent of combustion of off-gases from sewage
treatment
plants.
Estimates of methane emissions from enteric fermentation in domesticated animals are less
uncertain than
those for other sources of methane emissions. Emissions estimates are a function of an emissions
factor
for each animal group, based on their diet and energy usage multiplied by their population.
Animal
population data have recently been revised by the U.S. Department of Agriculture, and the
magnitude of
revisions shows that population estimates are likely to be accurate within 5 percent. The energy
requirements and diets of cattle—by far the largest source of emissions from enteric
fermentation—have
been carefully studied. There is some uncertainty associated with estimates of the energy
requirements
of other animals, but even if this uncertainty was as high as 50 percent, the impact on the overall
estimate
would be no more than 3 percent.
There is also some uncertainty associated with the average size of cattle, which could affect the
animals’
energy requirements. Cattle sizes have been changing rapidly over the past decade in response to
market
forces. This report uses slaughter weights as a proxy for average animal size, a method that may
be
imperfect. The slaughter sizes vary over time by approximately 33 percent.
The maximum amount of methane that a given amount of an animal’s waste can produce
under optimal
anaerobic conditions can be measured fairly accurately in the laboratory. However, the share of
that
production realized under various waste management regimens is much more uncertain. The
emissions
vary with ambient air temperatures and, depending on the waste management system, may
change by
anywhere from 1 to 60 percent as the temperature changes. For this report, all animal waste was
assumed
to be handled at air temperatures between 59 and 77oF. Overestimating the average
temperature at which waste is handled would bias emissions estimates upward.
Emissions are tied to the amount of waste an animal produces. The amount of waste produced is
a
function of size and diet. Thus, changes in animal sizes, which are difficult to monitor, create
additional
uncertainty. As discussed above, slaughter weights have been used as an imperfect tool for
capturing
changes in animal size. This proxy measure varies by 30 percent over time. Uncertainty in
estimates of
animal populations is on the order of 5 percent or less.
There are large uncertainties associated with the estimate of methane emissions from wetland
rice
cultivation. Emissions estimates are based on several studies of rice paddies in the United States,
which
provide daily emissions rate ranges. Studies have shown large seasonal and time-of-day
variations in
methane flux. Many variables affect methane production in rice fields, including soil
temperature, redox
potential, and acidity; substrate and nutrient availability; addition of chemical and/or organic
fertilizers;
rate of methane oxidation; and rice plant variety. The wide range of emissions provided by
different
researchers suggests an uncertainty of several hundred percent [212].
Estimates of emissions from the burning of crop residues are calculated using the default method
recommended by the IPCC [213]. This method
assumes a carbon
content of about 45 percent of dry matter and that 10 percent of crop residues are burned. The
carbon
content probably is uncertain to plus or minus 10 percent, and the share of crop residues burned
in the
United States is likely to be much smaller than the 10 percent default parameter used. Thus,
estimates are
likely to overstate actual emissions.
Estimates of methane emissions from chemical production are highly uncertain because of the
wide variety
of production processes and inputs. Organic chemical production requires the cracking and
reforming of
hydrocarbon bonds. How the bonds crack and reform depends on several variables, including the
composition of the feedstock, the temperature of the reaction, the catalyst used, and the reaction
vessel.
As a result, the quantities of products and byproducts, including methane, vary. Methane may be
released
through leaks in seals and valves. Therefore, methane emissions are dependent on the operation
and
maintenance practices of the producer.
There is substantial uncertainty associated with estimates of methane emissions from iron and
steel
production, with the plausible range of estimates ranging from 80 percent below the point
estimate
presented in this report, to 100 percent above the point estimate. There are several factors
mitigating
methane emissions from iron and steel production. The pollution controls used on coke ovens to
prevent
emissions of volatile organic compounds usually eliminate methane as well. Exhaust gases from
blast
furnaces that are typically captured and used for fuel contain methane. Because the emissions
factors used
in this report are global emissions factors provided by the IPCC [214] they may not accurately portray the level of
emission controls
found in U.S. plants. Further, the efficacy of these pollution control systems is likely to vary with
operation and maintenance techniques.
Appendix D lists several sources excluded because of excessive
uncertainty or insufficient data. Known
sources excluded from methane emissions estimates are industrial wastewater, abandoned coal
mines,
industrial landfills, and open dumps. There are other sources of methane that have yet to be
identified
and thus are absent from emissions estimates. Excluded sources would invariably add to total
emissions,
but the magnitude of the additions is impossible to estimate.
A number of variables are necessary for accurate calculation of nitrous oxide emissions from the
application of fertilizer. They may include crop type, soil type, nutrient content of the fertilizer,
agricultural management practices, and even climate. In fact, researchers maintain different
opinions about
the effects, if any, of these variables. While it may be possible to quantify some of the variables,
it is
highly unlikely that within the next few years sufficient studies will be conducted to determine a
precise
emissions factor. Therefore, the uncertainty range for the estimate presented in this report is an
order of
magnitude. Additionally, the estimate does not take into account organic fertilizer from human or
farm
animal excreta. Although the data are limited, emissions from this type of fertilizer are generally
greater
than those from mineral fertilizer [215]. In 1994
nitrous oxide
from fertilizer emissions represented approximately 50 percent of U.S. emissions of nitrous
oxides and
over 90 percent of nitrous oxides from agricultural sources.
The accuracy of emissions estimates for crop residue burning is limited, because the practice of
burning
crop residues in the United States has not been quantified. As described in Chapter 4, a default
figure of
10 percent was used in the calculation. This figure is believed to be a maximum representation of
the
practice, and could possibly be as much as an order of magnitude high.
As the result of improved studies, emissions factors recommended by the IPCC are now limited
to one
value for each fuel type, regardless of application. Although the emissions factor for coal is 1.4
kilograms
of nitrous oxide per terajoule of energy input, emissions may range from 0 to 10 kilograms. For
oil, the
recommended emissions factor is 0.6 kilogram, with a possible range of 0 to 2.8 kilograms. The
range is
smallest for natural gas (0 to 1.1 kilograms), with 0.1 kilogram as the suggested factor [216].
The emissions factors were derived from studies of “conventional” combustion
facilities (i.e.,
those equipped with burners and grate combustion, with flame temperatures well beyond
1,000oC). Other types of facilities are used in the United States, adding to the
uncertainty
of estimates presented in this report.
For adipic acid production, emissions estimates are based on three data inputs: production
activity, an
emissions factor, and emissions abatement activity. The primary reasons for uncertainty are that
the
amount of production at plants with emissions abatement is unknown, and the effectiveness of
those
abatement techniques in eliminating nitrous oxide is unknown. Additionally, the emissions factor
for
adipic acid production was determined by stoichiometry. Moreover, plant-specific production
figures must
be estimated by disaggregating total adipic acid production using existing plant capacities.
Therefore, any
national estimate will be an imprecise figure if the conversion of nitric acid to adipic acid is less
than 100
percent efficient.
The emissions factor for nitric acid production is also uncertain. The DuPont data indicate a
range of
emissions from 2 to 9 grams of nitrous oxide per kilogram of acid production. Since the midpoint
of this
range was used in the calculation, estimates may err by as much as 65 percent. As explained in
Chapter
4, applying this emissions factor range to total production also adds uncertainty, because the
emissions
reported at the DuPont plant may not be representative of emissions at all nitric acid production
plants.
The emissions estimates presented in Chapter 6 are taken from data in National Air Pollutant
Emission
Trends, 1900-1994, a report published by the EPA Office of Air Quality Planning and
Standards.
Although true values of criteria pollutant emissions are not known, the EPA states that,
“beginning
with the 1900 to 1992 report, EPA set the primary goal of preparing emission trends that would
also
represent the best available estimates of emissions” [217].
The EPA also explains that one of the difficulties they experience in providing emissions
estimates is
balancing consistency of estimation methods with completeness and accuracy of data. Therefore,
as new
methods and data become available, emissions estimates may be revised.
Estimates of carbon flux from U.S. forests are subject to several potential sources of error.
Uncertainty is
introduced into the estimation method when results of small-scale studies in specific ecosystems
are
applied to different ecosystems or to large areas. This is particularly true for the estimate of soil
carbon
flux, leading EIA to provide low, median, and high estimates for this component ranging from 0
to 127
million metric tons. The estimates of forest carbon flux are also subject to bias from applying
data from
past studies that do not represent all forest conditions, from modeling errors, and from errors in
converting estimates from one reporting unit to another. Forest Service researchers Richard
Birdsey and
Linda Heath (the primary source of data used by EIA in its estimates of aggregate carbon flux)
did not
attempt to estimate the magnitude of these errors, but believe that they are probably small.
In addition, there are two methodological problems common to adding carbon sources and sinks
derived
from land use data to more conventional greenhouse gas emissions:
Oil and Gas Operations
Combustion-Related Emissions
Landfills
Domestic and Commercial Wastewater Treatment
Enteric Fermentation in Domesticated Animals
Solid Waste of Domesticated Animals
Wetland Rice Cultivation
Crop Residue Burning
Chemical Production
Iron and Steel Production
Excluded Sources
Fertilizer
Crop Residue Burning
Stationary Source Combustion
Adipic Acid Production
Nitric Acid Production
Appendix D. Emissions Sources Excluded
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