EPA-600/E-96-072
June 1996
PROCEEDINGS: THE 1995 SYMPOSIUM ON GREENHOUSE GAS
EMISSIONS AND MITIGATION RESEARCH
Symposium Chairperson:
Michael A. Maxwell (EPA-APPCD)
Prepared bv:
Acurex Environmental Corporation
4915 Prospectus Drive
P.O. Box 13109
Research Triangle Park, NC 27709
EPA Contract No. 68-D2-0063
Work Assignment No. 2/057
EPA Project Officer: Keith J. Fritsky
Air Pollution Prevention and Control Division
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
Prepared for:
U.S. Environmental Protection Agency
Office of Research and Development
Washington, DC 20460

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TECHNICAL REPORT DATA
(Please read IxUructiom on the reverse before camp
1. REPORT NO. 2.
EPA-600/R-96-072


4. TITLE AND SUBTITLE
Proceedings: The 1995 Symposium on Greenhouse Gas
Emissions and Mitigation Research
5. REPORT DATE
June 1996
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Sue Philpott, Compiler
S. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Acurex Environmental Corporation
P. O. Box 13109
Research Triangle Park, North Carolina 27709
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-D2-0063, W. A. 2/057
12. SPONSORING AGENCY NAME AND AOORESS
EPA, Office of Research and Development
Air Pollution Prevention and Control Division
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
Proceedings; 6/27-29/95
14. SPONSORING AGENCY COOE
EPA/600/13
16.supplementary notes AFPCD project officer is Keith J. Fritsky, Mail Drop 63, 919/
541-7979.
is. abstract The report documents the 1995 Symposium on Greenhouse Gas Emissions
and Mitigation Research, sponsored by the U.S. Environmental Protection Agency's
Air Pollution Prevention and Control Division (EPA/APPCD), in Washington, DC, on
June 27-29, 1995. The symposium provided a forum of exchange of up-to-date infor-
mation on emission sources contributing to global climate change and state-of-the-
art mitigation technologies and practices. Presentations related to: activities in
EPA, U.S. Department of Energy (DOE), and Electric Power Research Institute
(EPRl) on greenhouse gas emissions and mitigation research, and APPCD1 s global
emissions and technology databases; carbon dioxide emissions, disposal, and con-
trol; methane emissions and mitigation technologies including coal mines, the nat-
ural gas industry, key agricultural sources, and landfills: renewable energy options
including alternative biomass fuels; and advanced energy systems. The proceedings
contain 44 papers, visuals, and abstracts.
17. KEY WORDS AND DOCUMENT ANALYSIS
i. DESCRIPTORS
b. IOENTIFIERS/OPEN ENDED TERMS
C. COS ATI Ficld/Cioup
Pollution Methane
Emission Coal Mines
Greenhouse Effect Natural Gas
Research Agriculture
Climatic Changes Earth Fills
Carbon Dioxide Biomass
Pollution Control
Stationary Sources
Global Climate Change
Renewable Energy
13	B 07 C
14	G 081
04A 21D
14F 02
04B 13 C
07B 08A.06C
18. DISTRIBUTION STATEMENT
Release to Public
19. SECURITY CLASS (This Report J
Unclassified
21. NO. OF PAGES
. , o
20. SECURITY CLASS (This page)
Unclassified
22. PRICE
EPA Form 2220-1 (3-73)

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FOREWORD
The U.S. Environmental Protection Agency is charged by Congress with pro-
tecting the Nation's land, air, and water resources. Under a mandate of national
environmental laws, the Agency strives to formulate and implement actions lead-
ing to a compatible balance between human activities and the ability of natural
systems to support and nurture life. To meet this mandate, EPA's research
program is providing data and technical support for solving environmental pro-
blems today and building a science knowledge base necessary to manage our eco-
logical resources wisely, understand how pollutants affect our health, and pre-
vent or reduce environmental risks in the future.
The National Risk Management Research Laboratory is the Agency's center for
investigation of technological and management approaches for reducing risks
from threats to human health and the environment. The focus of the Laboratory's
research program is on methods for the prevention and control of pollution to air,
land, water, and subsurface resources; protection of water quality in public water
systems; remediation of contaminated sites and groundwater; and prevention and
control of indoor air pollution. The goal of this research effort is to catalyze
development and implementation of innovative, cost-effective environmental
technologies; develop scientific and engineering information needed by EPA to
support regulatory and policy decisions; and provide technical support and infor-
mation transfer to ensure effective implementation of environmental regulations
and strategies.
This publication has been produced as part of the Laboratory's strategic long-
term research plan. It is published and made available by EPA's Office of Re-
search and Development to assist the user community and to link researchers
with their clients.
E. Timothy Oppelt, Director
National Risk Management Research Laboratory
EPA REVIEW NOTICE
This report has been peer and administratively reviewed by the U.S. Environmental
Protection Agency, and approved for publication. Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.
This document is available to the public through the National Technical Information
Service, Springfield, Virginia 22161.

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ABSTRACT
The report documents results of the 1995 Symposium on Greenhouse Gas
Emissions and Mitigation Research, sponsored by the U.S. Environmental
Protection Agency's Air Pollution Prevention and Control Division (EPA/APPCD),
and held in Washington, D.C. on June 27-29, 1995. The symposium provided a
forum of exchange of up-to-date information on emission sources contributing to
global climate change and state-of-the-art mitigation technologies and practices.
Papers were presented in the following areas: activities in EPA, U.S. Department of
Energy (DOE), and Electric Power Research Institute (EPRI) on greenhouse gas
emissions and. mitigation research, and APPCD's global emissions and technology
databases; carbon dioxide (CO2) emissions, disposal, and control; methane (CH4)
emissions and mitigation technologies including such topics as coal mines, the
natural gas industry, key agricultural sources, and landfills; renewable energy
options including alternative biomass fuels, and advanced energy systems. The
proceedings contain 44 papers, visuals, and abstracts.
ii

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TABLE Or CONTENTS
I'age
SESSION I: OVERVIEW OF NATIONAL AND INTERNATIONAL EFFORTS
Frank T. Princiotta, Chairperson
F.PA—Air Pollution Prevention and Control Division (APPCD)
"Greenhouse Warming: The Uncertainties and the Mitigation Challenge,"
Frank Princiotta 	1-1
"Climate Change Activities in EPA's Office of Policy,
Planning & Evaluation (OPPE),"
Kurt Johnson 	1-33
"Pollution Prevention at a Profit,"
Amy Olson	1-38
"Energy Partnerships for a Strong Economy: A Better Climate for Jobs,"
Arlene Anderson and the Energy Partnerships Quality Team	1-44
"Climate Change and the Value of Technological Innovation Under Uncertainty,"
Stephen C. Peck" and Thomas J. Teisbcrg	1-69
"The Global Future: Environment vs. Development"' (Visuals)
John Kadyszewski	1 -81
SESSION II: EMISSIONS FROM ANTHROPOGENIC SOURCES
M.A.K. Khalil, Chairperson
Oregon Graduate Institute
"Global Emissions Inventories/'
Jane Dignon	2-1
"CO2 Emission Calculations and Trends,"
Tom Boden*, Gregg Marland, and Robert .Andres 		2 18
'Denotes Speaker
iii

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Page
"Rice Agriculture: An Important Source of Atmospheric Methane,"
M.A.K. Khalil", M.j. Shearer and R.A. Rasmussen	2-35
"Developing Improved Methane Emission Estimates for Coal Mining Operations,1'
David Kirchgessner*, S.D. Piccot, S.S. Masemore and E.S. Ringier	2-53
"Methods for Estimating Methane Emissions from the Domestic
Natural Gas Industry,"
David Kirchgessner", R.M. Cowgill, M.R. Harrison and L.M. Campbell	2-65
"GioED and GloTech: Global Emissions and Technology Database Software'1
LecL. Beck 	J	2-74
"Overview of EPA's Global Climate Change Research Program
on Waste Management,"
Susan A. Thorneloe", R. Strait, M Doom and B. Eklund	2-85
"Greenhouse Gases from Widely Used Small-Scale Combustion Devices in Developing
Countries: Phases I - II: Sloves in India and China and Phase III: Charcoal Kilns in
Thailand,"
Kirk R. Smith*, Junfeng Zhang and Susan A. Thorneloe	2-100
SESSION III: MITIGATION OF METHANE AND OTHER GREENHOUSE GASES
Rhone Resch, Chairperson
EPA-OAR
"The EPA STAR Program and the Natural Gas Industry,"
Kathleen Hogan 	3-1
"Significant Sources of Methane Emissions in the
Natural Gas Industry,"
Matthew R. Harrison*, R.M. Cowgill and D.A. Kirchgessner	3-14
"Utilization and Control of Landfill Methane by Fuel Cells,"
John C. Trocciola', J.L. Preston and R.J. Spiegel 	3-23
"Methane Recovery from Landfills and an Overview of EPA/APPCD's
Landfill Gas Research Program,"
John G. Pacey", Susan A. Thorneloe, and Michiel Doom	3-27
"Case Studies of Sewage Treatment with Recovery of Energy from Methane,"
William H. Ilahn	3-44
"Denotes Speaker

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Page
"Assessment of CO2 Capture, Utilization, and Disposal,"
Howard J. Herzog 	3-54
'"Front Line' CCb Abatements from the Steel Industry,"
Britt Gilbert 	3 64
' Electrochemical Reduction of CO2 to Fuels,"
Daniel I	DuBois	3-76
"The Carnol Process for CO2 Mitigation from Power Plants and
the Transportation Sector,"
Meyer Steinberg	3-B6
SESSION IV: BIOMASS UTILIZATION
Sivan Kartha, Chairperson
Princeton University
"Demons; ra I ion of a lMWe Biomass Power Plant,"
Patrick Myers*, C.R. Purvis and M. Mazzawi 	—4-1
"Development of a New Generation of Small Scale Biomass-Fueled
Electric Generating Power Plants,"
Joe D. Craig* and Carol R. Purvis 	4-7
"Installation of an Energeo Biomass Power Plant
at a Lumber Company,''
Carol R. Purvis* and Charles F. Sanders	4-17
"An Indirectly Heated Thermochemieal Reactor for Steam
Reforming/Gasification of Biomass and Other Carbonaceous
Materials," (Abstract)
Momtaz Mansour	4-25
"Cost Versus Scale for Advanced Plantation-Based Biomass
Energy Systems in the U.S.,"
Sivan Kartha*, C.I. Marrison and E.D. Larson	4-26
"Greenhouse Gas Implications and Mitigation Opportunities
for Integrated Biomass Systems,"
Jane II. Turnbuir and Ulf Boman	4-50
"Cost of Producing Herbaceous and Woody Biomass Crops in the U.S.,"
Marie E. Walsh	4-59
'Denotes Speaker
v

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Page
"Methanol and Hydrogen from Biomass for Transportation,
with Comparisons to Methanol and Hydrogen from Natural Gas
and Coal,"
Robert H. Williams*, Eric D. Larson, Ryan E. Katofskv, and Jeff Chen	4-69
"Hydrogen from Biomass via Fast Pyrolysis,"
Margaret Mann*, E. Chornet, D. Wang, D. Montane,
S. Czernik, and D, Johnson	4-116
"The Hynol Process,"
Robert H. Borgwardt	4-128
SESSION V: RENEWABLES AMU ADVANCED ENERGY EFFICIENT, END-USE
TECHNOLOGIES
Thomas D. Bath, Chairperson
National Renewable Energy Laboratory (NKEL)
"Greenlifiu.se Gas Mitigation: The Potential for Renewable Energy,"
Thomas D. Bath* and Jack Stone			5-1
"Pollution Prevention by Consumer Choice. The Green Pricing Option/'
Lloyd Wright 	5-10
"Risk, Accounting and Strategic Planning Issues in Integrated Resource Planning
(IRP) Resource Selection,"
Shimon Awerbuch	5-20
"Pollution Mitigation and Photovoltaic Demand-Side Results from the U.S.
Environmental Protection Agency Photovoltaic Demonstrations,"
Edward C. Kem'Jr., Daniel L. Greenberg, and Ronald J. Spiegel 	5-52
"Photovoltaic Energy Impacts on U.S. CO2 Emissions,"
Samuel C. Morris", J. Lee, P.D. Moskowitz, and G. Goldstein 	5-64
"Electric Vehicles: A Source for Energy Security and Clean Air,"
Lawrence G. O'Connell	5-75
"Why Not Plug Your House and Workplace Into Your Fuel Cell Car?," (Visuals)
J. Kelly Kissock* and Robert H. Williams 	5-85
"Free-Piston Stirling Engines for Domestic Cogeneration and Biomass
Energy Conversion,"
William T. Beale 	5-110
'Denotes Speaker
vi

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Ease
"Commercialization of Wind Power and Its Potential Impact on
Greenhouse Gas Emissions,"
Susan Hock*, J,B. Cadogan, J.M. Cohen and I3.L. Johnson 	5-117
"Fuzzy-I.ogic-Bascd Adaptive Control of AC Induction Motors
for Energy Optimization,"
R.J. Spiegel", P.J. Chappell and M.W. Turner 	5-127
"Fuzzy-Logic-Based Adaptive Control of a Variable
Speed Wind Turbine/'
R.J. Spiegel* and B.K. Bose	5-137
"Denotes Speaker
vii

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SESSION I: OVERVIEW OF NATIONAL AND INTERNATIONAL EFFORTS
Frank T. Princiotta, Chairperson
This paper has been reviewed in accordance with (he U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication.
GREENHOUSE WARMING:
THE UNCERTAINTIES AND THE MITIGATION CHALLENGE
Frank T. Princiotta, Director
Air Pollution Prevention and Control Division
National Risk Management Research Laboratory
U.S. Environmental Protection Agency (MD-60)
Research Triangle Park, NC 27711
When considering the issue of greenhouse warming, one must deal with many questions
for which there are high levels of uncertainty. However, there is close to a consensus in the
scientific community that the emissions of greenhouse gases via human activity provide a
significant driving force for wanning over pre-industrial temperature levels.
Such human activity has led to an increased atmospheric concentration of carbon dioxide
(C02), methane (CH4), and chlorofluorocarbons (CFCs), which resist the outward flow of
infrared radiation more effectively than they impede incoming solar radiation. This imbalance
yields the potential for global warming as the atmospheric concentrations of these gases increase.
For example, before the industrial revolution, the concentration of C02 in the atmosphere was
about 280 ppm., and it is now about 360 ppm. Similarly, CH4 atmospheric concentrations have
increased substantially, and they are now more than twice what they were before the industrial
revolution, currently about 1.80 ppm. The impact of human activities is more dramatic with
regard to CFCs. These compounds do not occur naturally; they were not found in the
atmosphere until their initial production several decades ago. Recent data also suggest that
airborne particulates have increased significantly in the post-industrial period and have
contributed to a counteracting cooling impact.
We will attempt to shed light on several of the key issues associated with greenhouse
warming. Using a relatively simple, but instructive, model, and information from a variety of
credible sources, the following issues will be discussed:
What uncertainties are most critical in allowing us to confidently project the
degree of warming expected over the next century?
Given these uncertainties, what are the ranges of warming that appear reasonable?
Which countries and what sectors are most important regarding greenhouse gas
emissions?
Which gases contribute to warming? What is their projected share of such
warming? What is the relative confidence in such impacts?
How effective are various mitigation strategies; what levels of mitigation are
achievable for strategies capping emissions versus a more stringent approach
calling for annual reduction by a given percentage after a certain year? How
important is control of CH4 and of CFC replacements?
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The model (Glowarm 3.0) we have developed to help evaluate these questions is a
spreadsheet (Lotus 1-2-3) model which calculates global concentrations and their associated
global warming contributions for all the major greenhouse gases: C02, CH4, ozone precursors,
nitrous oxide (N20), CFCs, and their substitutes. The model calculates atmospheric
concentrations of greenhouse gases based on projected emissions in 10 year increments. For
C02, look-up tables are used to relate the fraction of CO, remaining in the atmosphere as a
function of time after emission for two alternative C02 life cycles. For the other gases, an
inputcd lifetime value is used. Average global equilibrium temperatures are calculated using
lifetimes and radiative forcing functions described in Intergovernmental Panel on Climate
Change (IPCC), 1990. Realized (or actual) temperature is estimated using an empirical
correlation algorithm we developed based on general-circulation model (GCM) results presented
in IPCC, 1992. This approach uses a correlation which relates the rate of equilibrium warming
over the period between the target year and 1980 to the ratio of actual to equilibrium wanning.
The greater the rate of equilibrium warming, the smaller is the ratio of the actual to equilibrium
ratio.
Figure 1 shows input and output fields for the model. Note that equilibrium and transient
(realized or actual) warming can be calculated for any year (to 2100) for a variety of emission
and control scenarios, two C02 life cycles, an assumed atmospheric sensitivity to a doubling of
C02 concentration, CH4 lifetime, and both sulfate cooling and CFC phaseout assumptions.
Under the same assumptions, the model output temperatures fall generally within 10% of values
calculated by other models (IPCC, 1992, NAS, 1991, Krausc, 1989).
UNCERTAINTIES IMPACTING DEGREE OF WARMING EXPECTED
There are many uncertainties associated with the expected magnitude of global warming.
The following are major uncertainties which will be considered and quantified:
1.	Atmospheric Sensitivity. This critical variable is generally defined as the equilibrium
temperature rise associated with a doubling of C02 concentrations. GCMs arc utilized by
climate modelers to forecast the impact of C02 warming. Unfortunately, the range of
their results is wide and not converging (Dornbusch and Poterba, 1991). The IPCC
(IPCC, 1992) has concluded this range to be between 1.5 and 4.5"C.
2.	CQ^ Life Cycles The Earth's carbon cycle (which involves atmospheric, terrestrial, and
oceanic mechanisms), is complex and not completely understood. Yet, in order to
estimate C02 atmospheric concentrations and subsequent warming, it is necessary to
assume a relationship between C02 remaining in the atmosphere as a function of time
after emission. For this analysis, two C03 life cycles were utilized, one based on IPCC
(1992) and the other described by Walker and Kasting (1991). The Walker model yields
longer atmospheric lifetimes leading to higher CO, concentrations.
3.	Projected Growtli of CO-, Emissions Over Time for a "Business as Usual" Case
Attempting to predict the future is a risky business, at best. Yet, to scope the magnitude
of the warming issue, it is necessary to estimate emissions of greenhouse gases as far in
the future as one wishes to project warming. As we discussed and quantified in a
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previous paper (Princiotta, 1994), the following are key factors which will determine a
given country's emissions of CO,, the most important greenhouse gas:
current emission rate
population growth
growth of economy per capita
growth rate: energy use per economic output
growth rate: carbon emissions per energy use unit
Since future global C02 emissions will be the sum of an individual country's emissions,
all subject to varying factors, listed above, it is clear that even for a "business-as-usual"
or base case there is a large band of uncertainty.
4.	Methane Lifetime. A variety of investigators have provided a range of estimates for the
atmospheric lifetime of CH4. Recent atmospheric data (IPCC, 1992) have indicated an
unexpected deceleration of the increase of CH4 concentration in the atmosphere. We
have analyzed the data and concluded that such behavior seems consistent with a possible
recent decrease in CH4 lifetime (possibly due to an increase in atmospheric hydroxy 1
(OH) concentrations, the primary mechanism for CH4 degradation) and/or a recent
significant slowdown in the increase in CII4 global emissions. The longer the lifetime,
the greater is CH4's contribution to global warming.
5.	Projected Growth of Methane Emissions. There is an incomplete understanding of the
current contributions of the major anthropogenic sources of CH4. They include: landfills,
rice production, coal mines, natural gas production and distribution systems, and the
production of cattle. There is even more uncertainty regarding the likely growth of such
emissions over time as population grows, industrialization accelerates in undeveloped
countries, and agricultural practices change.
6.	Use of High Global Wanning Potential Compounds (e.g. HKC-134a) to Replace CFCs.
As the international community phases out of CFC production, due to concerns
associated with stratospheric ozone depletion, hydrofluorocarbon (HFC)-134a and other
compounds with significant greenhouse warming potential are being utilized as
replacements. The importance of the extent to which compounds such as these are
utilized will be evaluated.
7.	Actual Temperature Response Versus Calculated Equilibrium Warming. GCMs often
calculate projected equilibrium warming rather than transient or actual warming.
Equilibrium warming can be defined as the temperature the Earth would approach if it
were held at a given mix of greenhouse gas concentrations over a long period of time.
Transient (also called realized or actual) temperatures are those that would actually be
experienced at a given point in time, taking into account the thermal inertia of the Earth,
especially its oceans. There is only an incomplete understanding of this thermal inertia
effect and its quantitative impact on actual warming.
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8. Aerosol (Sulfate) Cooling. A recent development (IPCC, 1992) has been the availability
of evidence that emissions of sulfur dioxide (SO-,), other gases and aerosols have
contributed to a significant cooling impact, counteracting greenhouse gas warming.
There is significant uncertainty over the magnitude of the direct impact of such fine
particles and even more uncertainty over their secondary impact on clouds (generally
thought to be significant and in the cooling direction). A related uncertainty is the
relationship of atmospheric particles to their anthropogenic precursor emissions of SO,
and other substances. Yet another aspect of uncertainty is the fact that the atmospheric
lifetime of such particles is quite short, so that, unlike C02, atmospheric concentrations
are much higher over highly industrialized areas compared lo concentrations above the
oceans.
In order to attempt to understand the impact of these variables, we have estimated
warming for five scenarios spanning what we believe are reasonable ranges of values for these
variables. For certain factors, such as atmospheric sensitivity, there is a reasonable consensus
regarding the possible range of values. For other factors, there is no such consensus. It should
be recognized that the credibility of this uncertainty analysis is only as good as the variable
ranges assumed. Table 1 shows the assumed range of values from the "lowest" scenario which
assumes that all of these variables are at values which will yield the lowest degree of warming to
the "highest" case which assumes those values which will yield the highest projected wanning.
These can be characterized as representing best versus worst case scenarios, respectively. In the
middle is the base case which is generally consistent with IPCC (1992)' and represents current
conventional wisdom regarding the most likely scenario.
Figure 2 graphically summarizes the results of Glowarm model calculations for the five
scenarios examined. Also included in this figure is the actual warming estimated in 1980 relative
to the pre-industrial era (NAS, 1991). As indicated, the range of projected global warming varies
from significant to catastrophic. We believe a more likely range of uncertainty is represented
between the low and high scenarios. The predicted warming at 2100 for these cases is 2.1 and
5.7C0, respectively. The magnitude of these values and the difference between them support the
contention that we are dealing with an issue of unprecedented potential impact, but also of
monumental uncertainty. It is noteworthy that, even for the "low" scenario, temperature
increases of 2.1C0 over pre-industrial values (1.6C° over 1980 levels) are projected by 2100.
According to Vostock ice core measurements (Dornbusch and Poterba, 1991), the last time the
Earth experienced such an average temperature was 125,000 years ago.
In order to elucidate the impact of specific variables on warming, additional model runs
were made which evaluated each variable's influence on wanning when its value for the "low"
and "high" scenarios was input with all other variables set at their base level. Figure 3 shows
:Notc that, although the IPCC discussed sulfate cooling as a credible phenomenon, they
did not factor this into their projections of greenhouse warming over time. Also, the current
analysis assumes C02 emissions consistent with IPCC's model IS92f, which assumes emissions
somewhat higher than their base case, lS92a.
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the influence of each variable on realized warming at 2100. As can be seen, atmospheric
sensitivity, CD, emission growth and atmospheric life, and lag time associated with the Earth's
thermal inertia yielded the largest uncertainties. However, other factors, especially sulfate
cooling, were important contributors to uncertainty as well.
It is important to note that uncertainty influences not only the predicted degree of future
warming, but also the effectiveness of a given mitigation strategy. Figure 4 illustrates this point.
Realized warming versus time is plotted for the "low," "high," and base scenarios. In addition,
two stringent mitigation cases are included. Both assume that, by the year 2000, worldwide
mitigation is imposed to decrease emissions of all greenhouse gases by 1% annually. However,
the first mitigation case assumes all of the "high" variables summarized in Table 1. The second,
imposes a mitigation program assuming base (or "most likely") assumptions. The results are
dramatic. They show that, even with a stringent emission reduction program, if the "high" case
values are assumed, warming will be greater for all years before 2100 than for the uncontrolled
base case!
Another series of calculations can shed light on the reasonableness of the five wanning
scenarios. By using the model to back-calculate (i.e., to calculate wanning which would be
expected from the pre-industrialized period to 1980), some indication of scenario credibility can
be deduced. Figure 5 shows calculated warming for the five scenarios. Note that actual
atmospheric concentrations were utilized for this time period, since they are available, so that
atmospheric lifetimes and emission rates are not used by the model. As can be seen, the base
case appears most consistent with the actual warming estimated for the 1800-1980 period. In
fact, the calculated base case warming of about 0.5C° falls right in the middle of the actual
warming of 0.3 to 0.6C° (IPCC, 1992) experienced. However, e%'en on this issue, uncertainty is a
factor. Although most experts agree that such wanning has taken place, some argue that causes
other than greenhouse warming (e.g., natural climate variability) are responsible.
WHICH GASES ARE IMPORTANT?
Let us now examine the important greenhouse gases and their potential warming
contributions. Figure 6 shows the projected contribution by greenhouse gas over the period
1980-2050 for the base scenario. CC>2 and CI14 are clearly the most important contributors to
warming, with CFCs and their substitutes, N,0, and tropospheric ozone2 playing small but
significant roles. Noteworthy, is the projected cooling impact of aerosol sulfates.
However, again, uncertainty is significant this time in determining the relative
contributions of the greenhouse gases. Such uncertainties arc considered in Table 2. For each
greenhouse gas, Table 2 summarizes: atmospheric lifetime, the ratio of current to pre-industrial
atmospheric concentrations, projected contributions to realized warming, and the projected
2This value assumes volatile organic compound (VOC), nitrogen oxide (NOJ, and carbon
monoxide (CO) precursors contribute to ozone (03) formation. However, the small component
of ozone warming associated with CH4 emissions is included in the CH4 value.
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impact of mitigating emissions. Also included is a judgment regarding the relative confidence of
the predicted wanning impacts, along with major uncertainties and the major human sources.
Uncertainty is important for all gases, but especially for aerosols and tropospheric ozone.
When one considers the importance of a given greenhouse gas, it is informative to
evaluate warming prevented for a given mitigation scenario. Figure 7 shows results of model
calculations for the period 1980-2050 comparing equilibrium base scenario wanning to warming
prevented assuming a stringent mitigation program. In this case, a 1% annual reduction in
emissions is assumed for each gas (or its precursor) starting in the year 2000. The main result
here is that short-lived gases such as CH4 and ozone can mitigate a higher fraction of their base
warming. For example, whereas less than half of C02's base warming is mitigated in this case,
about three-quarters of Clip's base warming is mitigated. When viewed from a mitigation (or
warming prevented) viewpoint, CH4 is about half as important as C03; whereas, from an
emission viewpoint, it is less than a third as important.
Figure 8 shows additional model results to help shed light on this point. In this case, the
effect of annual mitigation rate (starting in 2000) on warming mitigated by gas is illustrated. An
interesting observation that can be made is that a stringent 2% per year mitigation program for
CH4 could have almost as much benefit by the year 2050 as capping (0% growth) C02
emissions. Of course, such conclusions are subject to the uncertainties previously discussed.
Such calculations are only as good as the underlying assumptions; they include atmospheric
lifetime and projected emission growth over the period examined.
A closer look at the contributions of chlorofluorocarbons (CFCs), and related compounds
and their substitutes is also informative. Figure 9 shows equilibrium model results for these
compounds for both phaseout and no phaseout cases. It should be noted, that for the CFCs and
carbon tetrachloride (CC14), the model assumed that half of the projected warming would be
counteracted by the cooling associated with the decrease of lower stratospheric ozone associated
with these compounds. As can be seen, the international CFC phaseout program is projected to
essentially eliminate greenhouse warming associated with CFCs by the year 2050. However,
Figure 9 also shows that CFC substitutes such as HFC-134a, a potent greenhouse gas, can be
significant contributors to greenhouse warming, depending, of course, on the degree to which
they are utilized. This particular analysis assumes that 35% of all projected uses of CFC-11,
CFC-12 and CFC-13 in a non-phaseout scenario, would be substituted for by HFC-134a.
WHICH COUNTRIES ARE MAJOR CONTRIBUTORS TO EMISSION OF GREENHOUSE
GASES? WHAT ARE LIKELY TRENDS?
It is useful to look at recent histories of C02 emissions for key countries. Figure 10
derived from NAS, 1991, illustrates growth in C02 emissions from 12 key countries between
I960 and 1988. As indicated, the U.S., USSR (now Russia, Ukraine and other independent
countries), and China are by far the major sources of C02. However, when one considers the
recent (1980-1988) growth rate, China and India are especially significant since this portends
future contributions to C03 emissions. Table 3 summarizes 1988 C02 data (NAS, 1991) for key
countries listed in order of overall emissions, per capita emissions, and per gross national product
1-6

-------
(GNP) emissions. Although, the U.S. leads the world in overall and per capita emissions, China
easily has the largest per GNP emissions.
In order to provide insight into the various sectors contributing to 1990 C02 emissions for
key countries, Figure 11 was generated based on Oak Ridge National Laboratory (ORNL)
calculated data, (Dowden, et al., 1993). This figure illustrates that each country has a distinctive
mix of activities yielding CO? emissions. In the case of the U.S., coal combustion (for electricity
and steam), petroleum for transportation, and natural gas combustion (primarily for power
generation and space heating) arc the three most critical contributors. The pattern is similar in
the former Soviet Union with the major difference in the automobile sector; much less C02 is
generated by a much smaller fleet of vehicles. In China, coal combustion is the dominant source
of C02 emissions, helping to explain why China's C()2 unit of GNP is so high; coal is by far the
most COrrich fuel source per unit of useful output energy. Germany, the fourth most important
source of C02, is also dominated by coal use: in their case, brown coal (lignite) indigenous to
their country. Japan, with few indigenous fossil fuel resources, is heavily dependent on imported
coal and residual oil for power generation. It is interesting to note that India, the second most
populous country in the world and likely a major future contributor, has a pattern similar to.
China, with steam coal the dominant source.
We have already discussed the uncertainties associated with future emissions of CO?.
Such emissions will depend on country-specific factors: population growth, rate of
industrialization, energy use per economic output, and carbon use per energy utilized. Table 4
(Princiotta, 1994) shows a projection of growth of these factors for the developed (OECD) and
relatively undeveloped Asian countries for the period 1990-2025. This projection is derived
from information presented in IPCC. 1992. For the Organization for Economic Cooperation and
Development (OECD) countries, the key driver yielding increased C02 emissions is expected to
be economic growth, whereas population growth is projected to be quite modest. For the Asian
countries, the key driver is likely to be economic growth, with population growth also
significant. For both regions, in the absence of a C02 mitigation program, energy efficiency
gains and a decrease in carbon-intensive energy use are projected to be modest over this time
period.
It is usful to examine the likely results of these drivers on projected emissions of C02
from selected countries. Figures 12 and 13 show such a projection assuming economic,
population, and energy use trends summarized in IPCC, 1992. Projections for the year 2030 and
2100 are combined with actual C02 emission data (NAS, 1991) from the 1960-1988 time period.
These graphics show that the Asian countries, especially China and India, driven by high
projected economic and population, growth, will be the dominant C02 emitters by the middle of
the next century.
Finally, it is instructive to examine CII4 emissions from the important anthropogenic
sources for key countries. Figure 14 summarizes preliminary information from a variety of
sources (Thorneloc, et al., 1993; Lemer, et al., 1988; Safley, et al., 1992; Kirchgessner, et al.,
1993; and Barnes and Edmondson, 1990). Again, each key country has a unique signature
dependent on the size of the economy and the relative importance of: rice production, coal
1-7

-------
mining, natural gas extraction, transmission and distribution; beef production; and the amount of
garbage generated and landfilled. Since rice production is a major CH4 source and China and
India are the world's largest rice producers, this is the major source for these countries. For the
U.S., which leads the world in garbage produced and landfilled, landfill CH4 is the largest
source; beef production, natural gas infrastructure and coal mines are also significant.
WHAT IS AN APPROPRIATE MITIGATION TARGET? HOW MUCH WARMING IS
ACCEPTABLE?
What targets should guide any greenhouse warming mitigation program? In order to
answer this critical question, it is highly desirable to have a good understanding of the effects on
various levels of greenhouse wanning on the environment, the economy, and human settlements.
Unfortunately, again, uncertainty prevails. Unfortunately, our understanding of such potential
impacts ranges from fair (e.g., sea level rise) to poor (e.g., geographical change of
rainfall/evaporation patterns). Therefore, it is exceedingly difficult to set such a target based on
available effects information.
In the absence of definitive effects information, one approach involves selecting an
allowable global temperature increase consistent with our understanding of Earth's climate
history. Krause (1989) summarizes this as:
A 1-1.5C° global average warming would represent a climate not experienced
since the beginning of agricultural civilization (6000 years ago).
A 2-2.5C0 warming represents a climate not experienced since 125,000 years ago
when small human communities existed. Such a climate seemed to partially
disintegrate the West Antarctic shield, raising sea levels 5-7 m.
A 3-4C0 warming has not been experienced since humans appeared on the Earth
(2 million years ago). The last time Earth experienced such a climate was about
3-5 million years ago.
Available limited effects information suggests that climate change to the degree projected
by the base case (2.7C0, from pre-industrial to 2100), could3 have the following impacts
(Krause, 1989 and IPCC, 1990, Stone, 1995):
increased mortality due to spread of infectious diseases, e.g., malaria, and summer
heat stress.
sea levels rising by at least 0.5 to 1.5 m over the next few decades, several meters
in the long term.
Changing ocean currents and precipitation patterns.
More frequent occurrences of weather conditions considered extreme, producing
floods, avalanches, and changes in the availability of run-off water.
Loss of soil moisture due to increased evaporation, with an increase in duration
and frequency of heat waves and droughts.
Reduced precipitation in the mid-latitude continental regions of North America
and Eurasia.
More stagnant air masses for longer time periods.
18

-------
Potential severe impact on agricultural productivity.
Die back of unmanaged forests since they cannot migrate fast enough to keep up
with the wanning trend; this could exacerbate loss of species diversity.
Reduction in stream flows yielding increased pressure on groundwater supplies.
MITIGATION; HOW MUCH AND WHEN TO START?
Figure 15 illustrates the projected results of two hypothetical mitigation scenarios
assuming base case values. If emissions were held constant at year 2000 levels, the rate of
projected warming could be slowed substantially; although significant warming would continue
for the foreseeable future. However, if emissions for all greenhouse gases were reduced 1%
annually, post-1980 warming could be stabilized below about 1C° by the year 2100.
Figure 16 illustrates the impact the year control starts on realized warming projected in
2050 for two mitigation scenarios (1% of annual control and emission cap). As indicated, early
emission control allows for a much larger degree of climate stabilization. These results suggest
that a mitigation program which caps emissions can be equally effective as a more stringent, and
expensive, emission reduction program initiated 10 years later.
SUMMARY AND CONCLUSIONS
A spreadsheet model has been developed to allow for calculations of both equilibrium
and realized greenhouse warming as a function of key variables including: greenhouse
gas emission growth rates, CO, life cycles, CIi4 lifetime, current aerosol cooling, and
CFC phaseout assumptions.
Model calculations for the three most credible cases assuming a varying range of
assumptions yield projected warming at 2100 from a substantial 2.1C° to a potentially
catastrophic 5.7C°. The most likely case yields 2.7C° projected warming from pre-
industrial values. Such uncertainty also impacts the estimates of the effectiveness of a
mitigation program. Model results suggest that, even assuming a stringent mitigation
program, if key uncertainties all align toward maximum greenhouse warming, warming
will be greater than it would be for a business as usual case assuming the mid-range of
the key variables contributing to uncertainty.
Factors contributing most to this uncertainty are: atmospheric sensitivity to a doubling of
C02, C02 emission projections, the C02 life cycle model assumed, and the Earth's
transient response to warming.
3 It is useful to quote directly from the National Academy of Science (NAS, 1991), regarding
such potential impacts: "Several troublesome, possibly dramatic, repercussions of continued
increases in global temperature have been suggested. No credible claim can be made that any of
these events are imminent, but none of them are precluded."
1-9

-------
Utilizing available atmospheric concentrations of the greenhouse gases from the prc-
industrial era to 1980 yields, the model predicts 0.5C" warming, assuming "most likely"
values for the key variables. This agrees well with the range of wanning observed for
this period.
Aerosol/sulfate cooling is an important phenomenon with recent data suggesting cooling
comparable to the wanning associated with CH4, the second most important greenhouse
gas. Again, uncertainty in current and projected cooling is substantial.
CO? is the largest potential contributor of the greenhouse gases, with CH4 the second
most important contributor. Warming associated with tropospheric ozone could be
important, but the underlying science allowing a quantitative judgment is weak.
Mitigating CH4 emissions can achieve substantial benefits, in the near term, in light of its
relatively short atmospheric lifetime. In fact, a 2% per year CH4 mitigation program can
be almost as effective as placing a cap on C02 emissions, assuming mitigation started in
2000 and the target year is 2050.
Although the international phaseout will essentially mitigate greenhouse warming from
CFCs and related compounds by 2050, replacement chemicals such as HFC-134a could
be significant greenhouse gases in this time frame, depending on the extent of use.
The United States, the former Soviet Union, China, Germany, and Japan are the largest
emitters of C02 (in rank order). Each has a distinctive profile with regard to
contributions per fuel-use sector. Developing countries in Asia such as China and India
are expected to have exponential growth in greenhouse gas emissions, driven primarily
by projected economic growth and dependence on coal as a major fossil fuel.
To select a mitigation target, it would be desirable to have a solid understanding of the
likely environmental, economic, and human settlement impacts associated with various
levels of greenhouse warming. Since such information is not available, an alternative
approach is to compare projections of greenhouse warming to geologic histories with
comparable warming and, where possible, deduce possible impacts. Such an analysis
suggests that projected greenhouse warming by (assuming base case variables) 2100
would lead to mean global temperatures not experienced by the Earth in the last 125,000
years. Possible impacts include: seawater rise, changing precipitation patterns, die-back
of indigenous forests, and potential loss of agricultural productivity.
Model analysis shows that the time mitigation is initiated has an important impact on the
degree of mitigation achievable. For example, a program to cap (hold constant)
greenhouse gas emissions can be equally effective as a more stringent mitigation program
initiated 10 years later.
1-10

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References
Barnes, D.W.. and J.A. Edmonds. "An Evaluation of the Relationship Between the Production
and Use of Energy and Atmospheric Methane Emissions." U.S. DOE. Office of Energy
Research. Carbon Dioxide Research Program. Report No. TR047. April 1990.
Bovvden, T.A., et al. "CDIAC Catalog of Numeric Data Packages and Computer Model
Packages." Carbon Dioxide Information Analysis Center. Oak Ridge National Laboratory.
Document No. ORNL/CDIAC-62. May 1993.
Dornbusch, R., and Poterba, J.M. "Global Warming Economic Policy Responses." The MIT
Press, 1991.
Intergovernmental Panel on Climate Change (IPCC), "Scientific Assessment of Climate
Change." June 1990.
Intergovernmental Panel on Climate Change (IPCC), "Climate Change 1992 - Hie
Supplementary Report to the IPCC Scientific Assessment," 1992.
Kirchgessner, D.A., S.D. Piccot, and J.D. Winkler. "Estimate of Global Methane Emissions
from Coal Mines." Chemosphere. Vol. 26, Nos. 1-4, pp. 453-472. 1993.
Krause, F. "Energy Policy in the Greenhouse." International Project for Sustainable Energy
Paths (Il'SEP), EI Cerrito, CA, 1989.
Lerncr, J., E. Matthews, and I. Fung. "Methane Emissions from Animals: A Global High
Resolution Data Base." Global Biogeochemical Cycles, Vol. 2, No. 2, pp. 139-156. 1988
National Academy of Sciences (NAS). "Policy Implications of Greenhouse Warming." National
Academy Press, 1991.
Princiotta, F T. "Greenhouse Warming: The Mitigation Challenge." In Proceedings of the 1992
Greenhouse Gas Emissions and Mitigation Research Symposium, EPA-600/R-94-008 (NTIS
PB94-132180), January 1994.
Safley. L.M., M.E. Casada, J.W. Woodbury, and K.F. Roos. 1992 "Global Methane Emissions
from Livestock and Poultry Manure". U.S. EPAM00/1-91/048.
Thorneloe, S.A., et al. "Waste Management," in Atmospheric Methane: Sources. Sinks, and
Role in Global Change. NA TO ASI Scries.Vol. I 13, Springer-Vcrlag Berlin Heidelberg, 1993.
1-11

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Walker, J.C.G., and Kasting, J.F. "Effects of Fuel and Forest Conservation on Future Level of
Atmospheric Carbon Dioxide." Paleoclimatol., Palaeocol, (Global and Planetary Change
Section). 97 (1992) pp. 151-189. Elsevier Science Publishers.
Stone, R. 'if the Mercury Soars, So May Health Hazards", Science. Vol. 267, Feb. 17, 1995,
pp. 957-958.
1-12

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TABLE 1
Five Scenarios impacting Degree of Global Warming
Variable Impacts on Predicted Warming		Range of Impacts—>Greater Warming
Lowest Low Base Case High Hiqhest
Atmospheric Sensitivity
C02 Life Cycle Model
1.5
IPCC
2
IPCC
2.5
IPCC
3.5
Walker
4.5
Walker
C02 Growth Rate: 1990-2030
1.0%
1.4%
1.85%
2.00%
2.2%
C02 Growth Rate: 2030-2100
0.5%
0.65%
0.78%
1.85%
2.2%
Methane Lifetime, yrs.
CH4 growth Rate: 1990-2030 12030-2100
7
0.67%/0.32%
8
0.77%/.52%
11
i.1~7%/.82%
12
1.27%/ 92%
13
1.37%/1.02%
Penetration of HFC-134a
15%
25%
35%
45%
55%
Actual/Equil. Temp.Ratio @ 0.35 C. deg./yr
0.3
0.4
0.505
0.6
0.7
Current Sulfate Cooling, Deg. C
-2.5
-2
¦1.65
-1
-0.1
Sulfate Cooling Emission Ratio Exponent
1
0.9
0.8
0.7
0.6
Warmina from 1980. Dea. C.fFor warmina from ore-industrial Deriod about 0.5 C. should be added)
;	 Equilibrium Temperature @ 2050
Realized Temperature @ 2050
0.4
1.1
2.3
5.1
7.8
0.4
0.9
1.2
2.6
4.4
Equilibrium Temperature @ 2100
0.9
2.2
4.3
10.3 15.9
Realized Temperature @ 2100
0.8
1.6
2.2
5.2 9.1

-------

rABLE 2. GREENHG3
USE GASES — WHAT IS
KNOWN AND WHA
r ISN'T


CHARACTERISTIC
CARBON DIOXIDE
METHANE
AEROSOLS
HFC-134a
TROPO. OZONE
N20
i. Atnnosphene Life lime (Yrs)
50-100
10-12.5
«1
16
C«t
1S0







?. Current ConcentratiOiV
1.26
2.15
Uncertain
NewCFC Substitute
>1. But Poor Data
108
Pie-Industrial Concentration






(






3. Projected Realized Warrrmg/






By Gas at the year 2100
~u
~0 5
41 5
~0.2
*o.\
~0.1
Most llkety Case: Total Warming * 2 2

Incl. Indirect Effects


(Excludes CH4 source)








4. Impact of 1%/¥r Mitigation:
€C%
31%
-
-
4%
4%
Control starts ?000. the Impact at 2050:






Calculated as % of total mitigation













5. Confidence in Warming Cavitations
Fair/Good
Fair
Poor
Good
Poor
Fair
to? Uems 3. and 4. Abo*e













6. Major Uncertainties
Carbon Cydc Influence on
1. Quantification of Natural and
1. Current extent of Cooling
Extent to vtfiich will
1. Atmospheric Chemistry
Atmospheric Concentration

C02 Atmospheric lifetime
Human Sources and Sinks
2. Relationship of Emissions
Substitute for CFCs
Models Insufficient
Rising Faster Than Known


2. Explanation needed for deceterat-
to Atm. Aerosols

2. Data on Tropo. Ozone
Sources/Sir&s Predict


1#vj growth in Atm. Concentrations
3. Impact on Clotid Formation

Trends Poor






3. Emission data for N0x,






Hydrocarbons and CO






Precursors poor








7. Major Human Sources
Fuel Combustion
Ccal Mining
Fossil Fuel Combustion
Refrigeration Cycles
Mobile Sources: VOCs. NO*
Biomass Burning

. Electric Power
Natural Gas and OU Production and
Biomass Combustion

and CO
Adipii Acid and h#J03 Prod

- Mobta Sources
Transportation


Stationary Cooibus:k>n.
Mobile Sources

• industrial Deforestation
Landfills


NOx and CO
Farming


Rice Padd*s


Biomass Burning: CO and
Stannary Source


Ruminants


VOCs
Combustion


Bicmass Burning & OecomposAon





-------
TABLE 3
C02 Emissions-! 988

C02 per capita

CC)2 pcrGNP

(Million of Tons)

(tons per person)

(Mt C02 per $1000 GNP) I

United States
4804
United States
19
China
6.0
USSR
3982
Canada
17
South Africa !
3.6
China
2236
Czechoslovakia
15
Romania
2.8
Germany
997
Australia
15
Poland
2.7
Japan
989
USSR
14
India
2.5
India
601
Germany
13
Czechoslovakia
1.9
United Kingdom
559
Poland
12
Mexico
1.7
Poland
459 ! United Kingdom
10
USSR
1.5
Canada
438
Romania
10
Korea
1.2
Italy
360
South Africa
8
Canada
1.0
! France
320
Japan
! 8
United States
1.0
j Mexico
307
Italy
i 6
Australia
1.0
! South Africa
284
France
i
6
United Kingdom j
0.8
I Australia
241
Korea
5
Germany
! 0.7
Czechoslovakia
234
Spain
5
Brazil
0.6
Romania
221
; Mexico
4
Spain
I 0.6
Korea
205
China
2
Italy 	
0.4
Brazil
202
Brazil
2
Japan
oi
Spain
j 188
	India
1
France 		
0.3

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TABLE 4
ASSUMED ANNUAL GROWTH FACTORS INFLUENCING C02
EMISSIONS (1990 - 2025)
(Derived from IPCC, 1992)
FACTOR
OECD
ASIA
Growth of Economy Per Capita
2.2%
3.5%
Population Growth Rate
0.3%
1.5%
Growth Rate: Energy Use Per Economic Output
-1.1%
-0.8%
Growth Rate: Carbon Emissions Per Energy
Use Unit
-0.7%
-0.3%
Annual C02 Growth Rate
(Sum of above factors)
+0.7%
+3.9%

-------


mm
mmmmm
MM


1STYR.
1980
199P-293Q,
IPCC-1992}
1
1980 Sulfate Impact
PPM-03/KG:
; END YR:
2050
1.90%
yValker/Kasting Model}!
2
-1.8.5 watts/sq.m
CH4
;IMPACT YR:
2050
2030-2100
C02 Option *
1
Average for North Hemi,
3.50E-15
CONTROL CASE NO:
1
0,760%
OJiTPtp-jBUWM^Ry;

0.8 {S04 effectexpone
NOx
1 =BASE, 2=Control, 7=Cap

CH4 Gwth
Equil.Warming


3.80E-14
START CONTROL
2000
1980-2030
2.32 Deg.Celsius

EQUIL.WARMING
CO
;ANN.EMIS.CONTROL:
1.0%
1.170%


0.54 Deg.Cefsius
6.40E-15
CFC PHASEOU7?
1
2030-2100
Transient Warm ing=


NMHC
(1 =YES,2=NO,3=see B9)

0,820%
1.17 Deg .Celsius

Transient Warming=
3.60E-14
Effect, of CFC Warming
0.5
S02 Gwth


0,48 Dcg.Celsms
Actual/Derwent=
% CFCs to H FC-ma
0.35
1990-2030
CH4 ppm N20ppm
C02ppm
1980
0.3
METHANE LIFETIME'
11
1.20%
3.30 0.350
559
CH4 ppm C02ppm
Transient Response
ATM.SENSmV.2X,degrei
2.50
2030-2100
Rate of Eq.Warm.
0.033
pre-ind. 0.8 280
1


0,35%
(Degree C per Year)

1980 1.65 338
4=slowest,5=slow






1 =base,2=fast






3=fastest
Figure 1: Glowarm Model Input and Output Screen

-------
Projected Realized Warming Versus Time Since 1800
Actual Warming: 1800 to 1980
*	Lowest
~	Low
Most Likely
-B- High
-e- Highest
Figure 2: Projected Realized Warming Versus
Time Since L800

-------
Impact of Variables on Realized Warming
For Year 2100
O

Q
oT
k.
3
4-»
CO
fc.

-------
Projected Realized Global Warming
Three Business as Usual and Two Control Cases
Figure 4; Projected Realized Global Warming for Three Business as Usual
and Two Control Cases

-------
Model Predictions Compared to Actual Warming
For 1800 to 1980
2 5
Highest	High	Bau	Low	Lowest
Scenario
Figure 5: Model Predictions Compared to Actual Warming
for 1800 to 1980

-------
Gas Contributions to Warming
1ST YR:1980; END YR:2050:Uncontrolled Eq.Warming=2.2
Figure 6: Gas Contributions to Warming

-------
WARMING PREVENTED BY:2000 EMISS.CONTROL
PERIOD: 1980-2050;ANN.EMIS.CONTROL:0.010
O
(L)
fi
O)
CD
Q
¦a"
0
c
S
93
D)
E
"E
002
-CH4
03:xCH4CFCs N20 Others Sulfated
~ BASE WARMING
WARM. PREVENTED
Figure 7: Warming Prevented by 2000 Emission Control

-------
-2%
Warming Abated by Gas Vs.Control Rate
1ST YR-.1980; END YR:2050;Uncontrolled Eq.Warming=2.3
mC02
O Methane
A 03 Precursors
B N20
Other
-1% 0% 1% 2%
Annual Mitigation Rate, %
3%
Figure 8: Warming Abated by Gas Vs. Mitigation Rate

-------
Impact of Phasing Out CFCs
1ST YR:1980; END YR:2050:Uncontrolled Eq.Warming=2.3
0.2
0.15
0
2
CD
0)
Q
O 0.1
d>
c
CO
ZJ
D"
Lii
0.05
0
-0.05
CFCJ
CFC-
11
12

¦
fSi
HcEc
ST
-22
M
HFC-1
'WW'
¦M
%
7%
ill
SI
'{@M
Mm

n No Phaseout
m Phaseout
Figure 9: Impact of Phasing Out CFCs

-------
Emissions of C02 by Country
For 12 Largest Emitter# In 1988
t\i
O
o
M
c
£
o
•c

-------
[CQ2 Emissions by Country by Fuel
Brazil Germany India Mexico	UK	USSR
CMna Franc* Japan Poland	USA
¦	Steam Coal
IB) Brown Coal/Lignite
PI Coke Oven Coke
m Residual Fuel Oil
m Gas Oil/Diesel Oil
ES Motor Gasoline
¦	Jet Fuel
¦	Other Oil
¦	Liquified Petroleum Gas
~ Natural Gas
la other
Figure 11: Recent C02 Emissions by Country by Fuel

-------
Projected C02 Emissions for Selected Countries
Actual Values'.1960-1988
100
1950 1970 1980 1988 2030 2100
O United States
¦	USSR
a China
ffl Other Asia
~ Germany
BJapan
¦	Other OECO
a India
a United Kingdom
¦	Middle East
Figure 12: Projected C02 Emissions for
Selected Countries (cumulative bar chart)
1-28

-------
Projected C02 Emissions for Selected Countries
Actual Values for 1960-1988
a United States
*	USSR
*	China
a Other Asia
Germany
=» Japan
*	Other OECD
*	India
*	United Kingdom
o Middle East
2100
Figure 13: Projected C02 Emissions for Selected
Countries (line chart)
1-29

-------
~ RICE
ZJ LANDFILLS
IB ANIMALS
¦ COAL MINES
23 MATURALGAS

-------
Projected Global Warming-Most Likely Case
Base (Uncontrolled), 1% ann.control & emiss.cap
2.5
C_>
	
>	<






J

r


i
i
1






B











¦ Base Case
«¦ 1%control@2000
Cap Emiss,@2000
1980 2000 2020 2040 2060 2080 2100
Year
2120
Figure 15: Projected Global Warming for the Base Case and Two Mitigation Scenarios

-------
Realized Warming Vs. First Year Control
1ST YR:1980; END YR:2050:Uncontrolled Eq.Warming=2.3
1.4
&
o
k.
CD
CD
"U
o
d>
c
	
	i
L


1

/






¦ 1% Control Case
^ 0% Growth(Cap Case)
& No Control
1990 2000 2010 2020 2030 2040
Year Control Starts
Figure 16: Projected Realized Warming vs. First Year Control

-------
This paper hus been reviewed in accordance with the U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication.
Climate Change Activities in EPA's	i-c
Office of Policy, Planning & Evaluation (OPPE)
Kurt Johnson
Climate Change Division
Office of Policy, Planning & Evaluation
U.S. Environmental Protection Agency
401 M Street SW, Mail Code 2122
Washington, DC 20460
OPPE coordinates EPA climate policy and supports the development of U.S. positions on
climate change. OPPE's analytical activities include the following: assessing the potential costs
and benefits of policy options to reduce the risks of global warming, and recommending ways to
reduce greenhouse gas emissions in the most cost-effective way possible; reviewing the
effectiveness of the U.S. Climate Change Action Plan and other countries' climate change plans;
proposing actions that could ensure that the U.S. will meet the Administration's commitment to
reduce greenhouse gas emissions to 1990 levels by the year 2000; preparing studies on the
potential impacts of climate change; and working as part of an inter-agency process to develop
U.S. policy under the Framework Convention on Climate Change. OPPE also administers the
following climate change programs:
Domestic
The State and Local Outreach Program provides technical and limited financial assistance to
States and localities to build expertise, develop action plans, and test innovative measures to
reduce greenhouse gas emissions.
WasteWiSe encourages source reduction and recycling of business waste.
Climate Wise promotes industrial sector improvements in energy efficiency and pollution
prevention.
Transportation Partners develops transportation strategies which reduce greenhouse gas
emissions by slowing growth in vehicle travel.
International
The U.S. Initiative on Joint Implementation encourages the creation of international
partnerships for greenhouse gas reduction projects, such as renewable energy and afforestation.
Country Studies provides technical assistance to developing and transition countries in
conducting climate change studies on sources of greenhouse gas emissions, strategies for limiting
emissions, and climate change impacts.
The Climate Technology Initiative is a linked set of domestic and international measures to
accelerate the development and diffusion of greenhouse gas reduction technologies.
1-33

-------
Climate Change Activities in
EPA's Office of Policy, Planning
& Evaluation
Climate Cfiarige Analysis
ClimalE Change Programs
Kurt Johnson
Climate Change Division
June 27, 1995
Climate Change Analysis
~	Developing U.S. Climate Policy Options
~	Assessing Climate Change Impacts
~	Preparing U.S. GHG Emissions Inventory
Developing U.S. Climate
Policy Options
~	Development of the 1993 U.S. Climate
Change Action Plan
~	Proposing future actions to reduce U.S.
GHG emissions
~	Supporting negotiations under the Climate
Convention
Assessing Climate Change
Impacts
~	Participating in the 1PCC process
~	Developing information about U.S. climate
change impacts:
Human Health	- Water Resources
- 1 nsuraace	- In frastnicture
Forestry	-Ecosystems
Preparing U.S. GHG
Emissions Inventory
~	Establishing methods for quantifying GHG
emissions
~	Developing guidelines for estimating GHG
emissions from facilities, plants, processes
~	Preparing the official U.S. GHG emissions
inventory
Climate Change Programs
~ Domestic
-	Stale and Local
Outreach
-¦ WasfcWiSc
-	CHmafe Wise
-	Transportation Partners
~ International
U.S. Initiative on Joint
Implementation
Country Studies
- Climate Technology
initiative
1-34

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State and Local Outreach
Program
~	Builds state anil local capacity to;
Understand climate change impacts
- Evaluate strategics to reduce G!IG emissions
~	Provides assistance for projects to test
innovative policies
State and Local Outreach
Success:
As part of a State and 1 ,ocal project on
increasing energy efficiency through
lighting equipment standards, Minnesota
estimated that it could reduce annual carbon
emissions by 35,000 tons while saving
almost $2M per year
WasteWile
~	Assists businesses in taking cost-effective
actions to reduce solid waste
~	Promotes waste reduction through:
-	Waste prevention
-	Recycling collection
-	Buying/manufacturing recycled products
WasteWi$e Success:
Target, a nationwide chain of more than 600
retail stores, has eliminated 1.5 million
pounds of packaging waste and saved an
estimated $4,5 million dollars by working
with its vendors to eliminate unnecessary
packaging for clothing
Climate Wise
~	Stimulates industrial sector actions to
reduce GHG emissions
~	Provides information on the full range of
Climate Change Action Plan initiatives to
help industries identity a set of actions that
are most appropriate to them
Climate Wise Success:
~	As a Climate Wise partner, DuPont expects
to save $31 million annually
~	DuPont pledge actions include:
Improvements in manufacturing energy
efficiency
—	Essential elimination ofN.O emissions
-	Reduction ofIIFC-23 and FFC emissions
I -'IS

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Transportation Partners
~	Reduces GHG emissions by slowing growth
in vehicle miles traveled
~	Supports voluntary implementation of
Iransportation strategies that reduce GHG
emissions, improve transportation system
efficiency, and make communities more
livuhle
Transportation Partners
Success:
In Portland, Oregon, Transportation Partners
helped to develop fin analytical tool to
compare the land use, mobility, and air
quality effects of increased mass transit as
an alternative to construction of a new
freewav
U.S. Initiative on Joint
Implementation (USUI)
~	Encourages the development of projects
between two or more countries that reduce,
avoid, or sequester GHG emissions
~	Provides program participants with
technical assistance and public recognition
~	Contributes to formulation of international
joint implementation criteria
Country Studies
Assists developing and transition nations with
climate change studies. Studies include:
Inventories of GHG emissions
-	Evaluations of options to reduce emissions
-	Assessments of climate change impacts and
response options
USUI Success:
A USfJt pilot project in Costa Rica will
develop a privately owned and operated 20
megawatt wind plant. Electricity generated
by 55 U.S.-manufacturcd wind turbines wil
displace electricity currently generated by
the burning of fossil fuel
Country Studies Success:
~	Country Studies provides comprehensive
technical assistance, including training and
guidance documents
~	55 countries are receiving support
~	Building on program results, countries are
preparing national action plans and
technology assessments

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Climate Technology Initiative
~	Seeks to accelerate market penetration of
renewable energy and energy efficiency
technologies
~	Seeks to eliminate barriers including:
-	Lack of information
-	Economies ofscale
-	Lack of finance
Climate Technology Initiative:
Current Plans'
~	Transfer of voluntary programs
~	Country technology studies
~	Network of renewable energy and energy
efficiency centers
~	Innovative market mechanisms
~	Technology prizes
~	Technology demonstrations
~	International finance

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This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication.
POLLUTION PREVENTION AT A PROFIT
Amy C. Olson
United States Environmental Protection Agency
Office of Air and Radiation, Office of Atmospheric Programs,
Atmospheric Pollution Prevention Division
401 M Street, SW (6202J)
Washington. DC 20460
ABSTRACT
Over the past four years, the U.S. EPA's Atmospheric Pollution Prevention Division
(APPD) has been working with over 2,000 organizations to learn numerous ways to save energy
and save money APPD seeks to profitably prevent pollution through new and innovative
voluntary public-private partnership programs. These programs overcome market barriers to
advance energy efficiency Promoting energy-efficient technologies and techniques to prevent
pollution, EPA's Green Lights; ENKRGY STAR Buildings, Homes and Equipment, and methane
reduction and recovery programs have achieved measurable economic and environmental
successes. Working within the framework of President Clinton's Climate Change Action Plan
(CCAP), which responds to the threat of global climate change while strengthening the economy,
APPD provides solutions that create jobs, encourage economic investment, and establish new
product markets.
INTRODUCTION
"We must take the lead in addressing the challenge of global warming that could make
our planet and its climate less hospitable and more hostile, to human life. Today, I
reaffirm my personal, and announce our nation's commitment to reducing our emissions
of greenhouse gases to their 1990 levels by the year 2000. I am instructing my
administration to produce a cost-effective plan... that can continue the trend of reduced
emissions. This must be a clarion call, not for more bureaucracy or regulation or
unnecessary costs, hut insteadfor American ingenuity and creativity, to produce the best
and most energy-efficient technology. "
President Clinton
April 21, 1993
The U.S. EPA's Atmospheric Pollution Prevention Division has responded to President
Clinton's Climate Change Action Plan by implementing creative programs that prevent pollution
profitably. These programs would result in reductions of carbon dioxide, sulfur dioxide, nitrogen
oxides, and other greenhouse and hazardous pollutants, curbing acid rain and smog and helping to
slow global climate change. The CCAP outlines an innovative, interagency strategy to reduce
emissions of greenhouse gases to their 1990 levels by the year 2000. This goal marked the first
step defined by the Framework Convention on Climate Change, the international agreement that
1 -38

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was signed by 161 countries at the Earth Summit in Rio de Janeiro, Brazil. The CCAP includes
47 new and expanded initiatives that address all significant greenhouse gases and sectors of the
economy. The CCAP is expected to provide annual reductions of 108 million metric tons of
carbon equivalent (MMTCE) by the year 2000.
The CCAP responds to the threat of global climate change while also strengthening the
economy. It is a coordinated Federal response that builds on existing policies and programs to
deliver cost-effective emission reductions. Through partnerships between the Federal government
and U.S. businesses and organizations, the Plan improves environmental performance while
creating jobs and contributing to economic growth. Recognizing the significant emissions of
greenhouse gases from energy production, many of the programs encourage businesses to invest
in energy-saving equipment and techniques. By stimulating investment in cost-effective pollution
prevention opportunities, the CCAP increases the long-term profits for businesses and consumers.
Nearly all of EPA's 21 CCAP programs have met or exceeded their 1994 targets and are
on track to achieve their 2000 emission reduction goals. Almost one-half of the emissions
reductions which the U.S. has committed to reduce will be achieved through voluntary programs.
APPD's profitable pollution prevention programs overcome the barriers that prevent profitable
investments in energy efficiency. Working with each sector individually to identify barriers and
define successful strategics, APPD is on target to reduce carbon dioxide emissions by 215
MMTCE by 2000 while producing a $37 billion profit for the economy.
I. OVERVIEW
APPD has been implementing profitable voluntary programs since it launched its flagship
program, Green Lights, in January 1991. The Green Lights program encourages the widespread
use of energy-efficient lighting in commercial and industrial buildings through voluntary
partnerships with corporations, governments, and nonprofit organizations. Building on the
success of Green Lights, APPD has successfully introduced and implemented additional new
pollution prevention programs that enhance market forces to save energy profitably. "A
storehouse of investment opportunities exist for reducing energy use and the pollution it causes in
every sector of the U.S. economy and throughout the world."[1] APPD has developed programs
to take advantage of the cost-effective opportunities to reduce emissions in the following five
major areas: (1) commercial and industrial buildings, (2) residential energy use, (3) energy supply,
(4) industrial and agricultural practices, and (5) chloroflourocarbon (CFC) substitutes
Each APPD program is based on voluntary initiatives to make investments that are both
profitable and maintain or improve quality. As programs are developed, APPD identifies
opportunities for greater efficiency, recognizes the barriers that have prevented or slowed the
process of taking advantage of these opportunities, and formulates practical solutions that
enhance market operation to overcome those barriers. [2] APPD also provides strong technical
support to its partners to help them decide how to accomplish their goals; however, APPD docs
not dictate solutions and never provides subsidies or rebates. APPD works to minimize
bureaucracy, and programs remain flexible to adjust to partner needs and to maximize program
1-39

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effectiveness
This paper provides a brief summary of the APPD programs implemented in commercial
and industrial buildings. The example will illustrate how APPD's programs work and how
participants can benefit. This introduction to the programs also provides a blueprint for future
action. Further details about any of the programs are available from the EPA by calling (202)233-
9190,
COMMERCIAL AND INDUSTRIAL BUILDINGS
Energy used to supply electricity to commercial and industrial buildings produces
approximately 15 percent of all air pollution from utilities in the United States This energy,
which is used to light, heat, air condition, and operate office equipment, costs $71 billion annually.
EPA's ENERGY star and Green Lights programs promote the use of profitable energy-efficient
technologies as a way to increase profits and competitiveness while preventing pollution. These
programs seek to cut building energy use in half while earning rates of return on these energy
efficiency investments of 20 to 40 percent.
The Green Lights program encourages the widespread use of energy efficient lighting.
Lighting accounts for 20 to 25 percent of all electricity sold in the United States, Using available
technology to upgrade lighting systems, this electricity use can be reduced by 50 to 70 percent.
Investments in more efficient and higher quality technologies can earn rates of return of more than
20 percent If Green Lights were fully implemented in all facility space in the U.S., it would save
more than 65 million kilowatts of electricity annually, reducing the national electric bill by $16
billion per year. This would prevent the pollution of 12 percent of U.S. utility emissions of carbon
dioxide, sulfur dioxide, and nitrogen oxides.
Despite the opportunities for profitable investment, most facilities continue to waste
energy by using inefficient systems. Close to one-half of all energy used in buildings could be
eliminated if building owners installed the most profitable technologies. EPA has identified
several major reasons why organizations continue to overlook these investment opportunities.
First, energy efficiency is not a strategic priority for management. Second, despite the
improvements in the technology, a lack of information, training, and education inhibit facility
managers from deploying the most profitable technologies. Another problem is that the energy
users in a building are rarely the people that pay for the energy. Builders, architects, and
engineers need to focus on life cycle costs, not just first costs, when building or remodeling a
building to realize the profitability of energy efficiency.
EPA's programs address these challenges, enhancing market performance and maximizing
pollution prevention. Organizations voluntarily join the Green Lights program by signing a
Memorandum of Understanding with the EPA By signing the Memorandum of Understanding,
senior management makes it clear that energy-efficient lighting is a high priority for the
organization In the agreement, organizations commit to upgrading 90 percent of their space
within a 5 year wherever profitable and wherever lighting quality is maintained or improved. EPA
provides a range of support systems to help Green Lights participants obtain information on
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energy-efficient lighting technology and financing options. Participants also receive public
recognition opportunities for their environmental leadership.
This cost-effective approach to pollution prevention has been extremely successful. The
program currently has approximately 2,000 participants and more than 5 billion square feet of
space committed to the program. Participants include corporations of all sizes; nonprofit
organizations; and federal, state and local government agencies. Program participants have
experienced lighting electricity savings of an average of 47 percent, for a total savings of
approximately $80 million annually. By the year 2000, the program expects to have commitments
from 5,800 participants, representing 15 billion square feet of space. These lighting upgrades will
prevent 41 million metric tons of carbon dioxide emissions while producing $40 billion in
corporate profits and $63 billion in gross savings.
These savings will continue as Green Lights participants are invited to join the ENERGY
STAR Buildings Program Using the same approach, this program involves a multi-stage energy
efficiency building upgrade. Through a step-by-step implementation strategy that takes advantage
of systems interactions and proven technology, ENERGY STAR Buildings partners achieve
additional energy savings while lowering capital expenditures. In addition to publicly recognizing
organizations for their participation and energy savings, EPA provides technical resources to help
plan and implement the upgrades.
This strategy was tested in a demonstration phase before EPA fully launched the ENERGY
STAR Buildings program. The ENERGY STAR Showcase Buildings program involved 24
buildings across the country and verified that the program can successfully maximize energy
savings at a profit for the building owner. Participants saved over 50 cents per square foot and
realized average rates of return of 30 percent or more on their investment in efficiency upgrades.
For example, Montgomery County Government realized a 144 percent rate of return while
reducing energy use by 45 percent annually. Their energy efficiency upgrades led to savings of
$116,000 per year and the prevention of 2.2 million pounds of carbon dioxide released per year.
Although the ENERGY STAR Buildings program was launched in April 1995, it expects to prevent
22 million metric tons of carbon dioxide and save $40 billion by 2000.
Some of the energy savings in the buildings program are achieved in conjunction with the
Energy Star Office Equipment program. Recognizing the need to not only use existing
technologies but continue to develop higher efficiency products, EPA works with manufacturers
to encourage further innovation This program started with the launch of ENERGY STAR
Computers program in June 1992. Computers account for 5 percent of commercial electricity
consumption and are the fastest growing electricity load in the business world. Research has
shown that much of this energy is wasted as computers are left on while not in use.
EPA works with equipment manufacturers and consumers to promote the use of high-
efficiency equipment. Industry-leading manufacturers have signed agreements with EPA to
produce equipment that automatically powers-down to save energy when it is not being used.
This added function is invisible to the user, both in terms of performance and price. APPD works
with manufacturers, retailers, and consumers to create a market for energy-efficient computers,
monitors, printers, fax machines, and copiers. As of 1995, the programs have approximately 90%
i«ii

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of equipment manufacturers nationwide participating in the ENERGY STAR Programs.
Like other energy efficiency investments, EPA ENERGY STAR Office Equipment can save
users money by reducing utility bills. Consumers and businesses can easily recognize the more
efficient products because they carry the ENERGY Starsm logo. The U.S. Government, the
largest buyer of computer equipment in the world, has taken the lead in purchasing ENERGY STAR
computer equipment. A Presidential Executive Order, in effect since October 1993, directs U.S.
agencies to purchase only desktop computers, monitors, and printers that meet EPA ENERGY
STAR guidelines for energy efficiency—provided that they are commercially available and meet the
agencies' performance needs. By the year 2000, purchases of Energy Star equipment will save
the Federal Government an estimated $40 million annually.
CONCLUSION
Green Lights, ENERGY STAR Buildings, and ENERGY STAR Office Equipment address the
largest energy loads in commercial and industrial buildings. Complementing each other, the
programs create a market for energy efficiency by stimulating demand for as well as supply of
high-efficiency equipment. APPD uses similar strategies to reduce (1) residential electricity use;
(2) methane emissions from landfills, coal mines, agricultural practices, and natural gas supply;
and (3) emissions of HFCs, PFCs, and other potent pollutants. These voluntary programs are
expected to save $80 billion in energy bills over the next 20 years while reducing emissions by an
equivalent of 215 million metric tons of carbon dioxide
All of APPD's voluntary programs are on track to achieve theirCCAP emission reduction
goals by 2000. If the plan is fully funded, the U.S. will fulfill its international commitments to
reduce greenhouse gas concentrations to 1990 levels by 2000. The experience gained during
implementation of the voluntary programs proves that "investing in energy efficiency is the single
most cost-effective way to reduce carbon dioxide emissions."[3] Harnessing private initiative, the
U.S. EPA is proving that environmental goals can be successfully achieved while stimulating
economic growth and savings
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REFERENCES
1.	Hoffman, John S. "Pollution prevention as a market-enhancing strategy: A Storehouse of
economical and environmental opportunities." Paper presented at Industrial Ecology
Colloquium, National Academy of Sciences, May 20 and 21, 1991, Pro. Natl. Acad. Set.
USA, Vol.89, February 1992, page 832
2.	The Climate is Right for Action U.S. EPA, Air and Radiation, document number 430-K-
94-004, August, 1994, page 2.
3.	Climate Action Report. Submission of the United States of America under the United
Nations Framework Convention on Climate Change, page 83.
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The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred.
Energy Partnerships For A Strong Economy
A Better Climate For Jobs
Arlene F. Anderson and the Energy Partnerships Quality Team
U.S. Department of Energy
Office Of Energy Efficiency and Renewable Energy
1000 Independence Avenue, S.w.
Washington, D.C. 20585
Abstract
The U.S. Department of Energy's Office of Energy Efficiency and Renewable
Energy has responsibility for implementing many of the actions contained in
the President's Climate Change Action Plan. These programs {Energy
Partnerships For A Strong Economy) are in part programs that are also being
implemented in response to the Energy Policy Act of 1992. With Fiscal Year
1995 funding in hand, DOE and its many partners are saving money and
environmental emissions that would not have been saved had it not been for the
increased emphasis placed on these programs. A sample of DOE's program
accomplishments and a description of the broader context in which they are
implemented follow.
Background
The Climate Change Action Plan (Climate Plan) contains a set of actions
designed to meet the Administration's simultaneous goals of creating jobs,
decreasing residential and commercial energy costs, and fulfilling their
commitment to reduce U.S. greenhouse gas emissions to 1990 levels by the year
200C without harming -economic growth.
Shortly after the Climate Plan'3 release, DOE committed to produce an
implementation strategy for its actions. DOE's Assistant Secretary for Policy,
Planning and Evaluation, Susan Tierney, pledged that this implementation
strategy would contain "milestones and metrics" to enable observers to gauge
whether DOE's Climate Plan strategy was working in each successive year, and
that DOE would not approach the year 2000 without a clear sense of whether the
Climate Plan is achieving the target.
The U.S. Department of Energy, office of Energy Efficiency and Renewable
Energy (EE) has made substantial progress toward implementing the Climate Plan
as it is one of the highest priorities. EE was given direct responsibility for
implementing almost one-half of the Climate Plan actions (21 out of 46 total
actions) and has been working toward implementation since the days when the
Climate Plan was first issued.
Also, EE has made a great deal of progress on Climate Plan programs because it
is poised to do so. The EE mission is to:
Help the Nation accelerate and expand the use of renewable energy and energy
efficient technologies and practices:
To achieve greater energy efficiency and security, environmental health
and economic pi'oductivity;
TO exercise Federal leadership in developing policies, information and
technologies
Through collaboration and partnerships with States, industry and energy
consumers.
Imp 1 amenta t ion St ratecrv
EE has developed an implementation strategy that is extremely comprehensive
and flexible, and allows for examination and adjustment to those portions of
the Climate Plan actions which are more successful than others. EE produced 21
individual implementation plans for each of it's actions. Two other Department
1-44

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of Energy offices have responsibility for three additional actions involving
hydropower, methane research, and fuel cell technology. The Office of Policy,
Planning and Evaluation and the Office of Fossil Energy are planning for
aggressive implementation of these actions.
In order to effectively coordinate development of the implementation plans and
to involve the public in review of these plans, SE created the "Green Room".
The Green Room served as the one place where EE program managers and staff,
collectively referred to as the EE Energy Partnerships Quality Team, gather to
refine implementation plans, respond to public inquiry, and develop measures
of program success. In December, 1994, the physical Green Room space was
replaced by a "Virtual Green Room" where the public may access program
information via the Energy Efficiency and Renewable Energy Network thus
continuing the Green Room's public involvement philosophy after Green Room
planning efforts concluded. The Green Room also served as a pilot project
under the Government Performance and Results Act of 1993. On March 23, 1994
the project was officially dubbed an EE Reinvention Lab for Reinventing
Federal, State, and Local Partnerships. 2
Interagency Cooperation
Energy Partnerships program managers became part of an interagency team
assembled to staff the "White House Conference on Climate Action". This
conference was the second White House sponsored conference designed to foster
interagency cooperation and enlist voluntary participation in Climate Plan
programs. In addition to DOE team members, staff from the Department of
Agri culture, Department of State, Department of Transportation, and the U.S.
Environmental Protection Agency worked together from February 1994 until Earth
Day (April 2.2., 1994) to put together Climate Plan program updates, breakout
sessions, and a major program and technology exhibit for every action
contained in the President's Climate Plan.
Vice President Albert Gore addressed nearly 1,000 conference participants for
an hour during the Conference Plenary Session. Speaking of the Climate Plan,
Vice President Gore stated that "It's a very aggressive attempt to address the
world's most important environmental threat. It has 50 separate programs. It
addresses every sector of the economy. It will improve energy efficiency. It
will save businesses, taxpayers, and consumers money. And it will create
j obs." 3
Guiding Principles
The guiding principles that underlie Energy Partnerships program
implementation have contributed to a flexible and dynamic strategy. KK used
the time period between the release of the Plan (October 1993) and the
beginning of it's Fiscal Year (October 1994) to develop implementation plans
that are well thought out, inclusive of public input, and that achieve
emission reduction goals.
EE's Climate Plan actions are designed to avoid creating new or duplicative
bureaucracies and are based on a set of guiding design principals meant to
ensure chat each program will be cost-effective, measurable, and flexible to
meet the Plan's overall economic and environmental objectives. These
principles include: l) maximizing the use of existing deployment mechanisms,-
2) integrating with on-going programs; 3) extensively involving stakeholders
in program design; 4) tracking and measuring program success; 5} leveraging
additional resources through public-private partnerships; and 6) providing
flexibility for varying geographic and market circumstances.
Individual Energy Efficiency & Renewable Energy Actioris
Several of EE's Energy Partnerships programs are described in the following
text boxes while more detailed Fiscal Year 1995 accomplishments are presented
in the description following the text boxes.
1

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OfflCE OF ENIKGY tfflCICN'CY
AND RENEWABLE ENERGY
REBUILD AMERICA
Goal
Community-wide partnerships to retrofit buildings with highly
leveraged utility industry participation
Strategy
Financial Partnerships
•	financial support from DOE
•	annual cooperative agreements
•	partners match at least 50% to qualify
Funding Use
•	renovation administration
•	technical plans
•	building audits
•	training and communication
Independent Partnership
•	form at any time
•	funded by partners
•	DOE provides technical assistance

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OFFICE OF INPRCY EFFlOfNCY
ASiD tENEVi'Af LC INLRGY
THE AFFORDABLE HOMES PARTNERSHIP
Goals
•	Stimulate homeowner investment in residential energy efficiency
•	Produce homes people can afford, and afford to keep
Strategy
•	Home Energy Rating System
•	Energy Efficient Financing (facilitate over $1 billion in special loans
and mortgages)
•	Education and incentives for homebuilders and rehabilitation
contractors
•	National awareness through work with retailers and manufacturers
(in-store displays, product labeling, media campaigns, and sales
staff training)

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OFFICE or INEECY EfflClEKCY
AND RENEWABLE fcNERGY
TECHNOLOGY INTRODUCTION PARTNERSHIPS
Goal
Increase development and sales of high-efficiency commercial gas
and electric building equipment for water heating, space heating and
cooling, refrigeration, lighting and dish washing
Strategy
• Eliminate market barriers to the manufacture and use of high
efficiency building equipment
Develop partnerships with manufacturers, installers, retailers, and
bulk buyers to cut production costs and increase sales volume

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OFFICE OF INRGY Iff ICIENCT
AND RE^EWABie F.Nf.RCiY
TECHNOLOGY INTRODUCTION
PARTNERSHIPS
Ducting
Potential Partners
Maytag
Whirlpool
Fusion
GE
Western Water Resources
AGCC
\D
Targeted Technologies
Gas Technologies
Laundry Products
Lighting
Retailers
NAESCO
CEE
Hotels/Motels
Manufactured Homes
State Procurements
Public Housing

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OFFICE OF ENfKCY tfFJCifcNCY
ASH) RENtWAKr. FNfRGY
UPGRADE COMMERCIAL AND
RESIDENTIAL BUILDING CODES
Goal
Update commercial and residential energy efficiency measures in
State building codes to lower energy bills, improve housing comfort,
and sustain energy efficiency measures for commercial buildings
Strategy
Section 101 EPAct requires DOE to help States upgrade the
energy efficiency-related provisions of their building codes
•	Co-fund State actions to implement and enforce their code
energy provisions
•	10-20 grants awarded to exemplary States
•	Technical assistance - (testimony, hotline, "setting the
standard" update, software)

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MOTOR CHALLENGE
Goal
To improve industrial energy efficiency, environmental performance,
and productivity by increasing U.S. industry's use of energy-efficient
motor systems
Strategy
•	Showcase Demonstrations
•	Information Clearinghouse & Database
•	Technology Development

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OFHCE Of INERCV EfnCHNCY
AND RENEWABLE ENERGY
MOTOR CHALLENGE SHOWCASE
DEMONSTRATIONS
Industrial Project Teams develop and implement
strategies to improve motor system performance
Partners experience productivity gains
Major downlink to more than 7,000 participants
19 demonstrations selected

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orftCE OF FNIRGY EffKltNCY
AND RINEWABt (
MOTOR CHALLENGE INFORMATION
CLEARINGHOUSE
Technical Assistance
Program Library
Decision Software
Education and Training Seminars
Bulletin Board System
Industry & Association Events
Technology Transfer Activities
National Database - record efficiency improvement,
develop performance benchmarks, and coordinate
voluntary reporting to 1605(b)

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OFFICE Of INIRCY fcfHOENCY
AND RENEWABLE ESIRGY
NICE3
Goals
•	Improve industrial energy efficiency
•	Reduce industry's cost
•	Promote clean production processes
•	Commercialize clean, innovative process or technology
Strategy
•	Industry/State partnerships that demonstrate innovative
approaches
• Matching Grants from DOE to State/Industry partnership (up to
50% of total project cost up to 3 years)

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OFFICE OF ENERCY EFFICIENCY
AND RENE'WARLC ESEKC.Y
NICE3 1995 AWARD WINNERS
ANON, Inc. (California)
MBA Polymers, Inc. (California)
Pacific Clay Brick Products (California)
Louisiana Pacific Corp. (California)
Tri Valley Growers (California)
Sara Lee Knit Products Corp. (North Carolina)
NATVAR Company (North Carolina)
Catalyst and Chemical Services, Inc. (Maryland)
Anthony Industries, Inc. Simplex Products Division (Michigan)
Dana Corporation (Minnesota)
Industrial Gas Technologies Commercialization Center (Ohio)
Air Products and Chemicals, Inc. (Pennsylvania)
Environmental Solutions, Inc. (Virginia)
Quad Graphics, Inc. (Wisconsin)

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OFFICE OF FMtKflY EfflCIENCY
AND ReNCWAOlC INlRCV
NICE3 EXAMPLES
Ultrasonic Products, Inc./ Southern California Edison /
California Department of Water Resources
SCE demonstrated an ultrasonic dishwashing machine
designed by UPI. SCE commissioned a report identifying
impact. New process uses lower water temperature,
requires less water, and reduces dish breakage

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—1
OFHCe OP ENERGY tmCKNCY
AND K[N(WASlf IKEMtf
RENEWABLE ENERGY COMMERCIALIZATION
(COLLABORATES, PARTNERSHIPS &
TECHNOLOGY DEMONSTRATIONS)
Wind
Photovoltaics
Geothermal Heat and Energy
Biomass Power

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OfHf t or £NfK(j"Y fiWClfNCY
AND 8ENEWA&1.E FNI1GY
RENEWABLE ENERGY COMMERCIALIZATION
(COLLABORATES, PARTNERSHIPS &
TECHNOLOGY DEMONSTRATIONS)
Wind
DOE/ERRl Turbine Verification Projects
•	Central and South West Services and Zond Systems
Fort Davis, TX
•	Green Mountain Power, VT
•	Niagra Mohawk, NY
Wind Technology Deployment cost share projects - 8 proposals for
more than 200 MW received
Utility Wind Interest Group
Avian/wind issues analysis and dialog

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OFFICE OF ENERGY EFFICIENCY
AND RENEWABtE ENERGY
RENEWABLE ENERGY COMMERCIALIZATION
(COLLABORATIVES, PARTNERSHIPS &
TECHNOLOGY DEMONSTRATIONS)
Photo voltaics
FY 95 8.5 MW to be awarded (350+ individual systems)
•	residential
•	commercial roof-top
•	building integrated design components
•	grid support
•	distributed generation
More than 90 members of utility. PV group

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OFFtCC OF ENERGY EFflCIENcCY
AND RENEWABLE fNIRGY
RENEWABLE ENERGY COMMERCIALIZATION
(COLLABORATES, PARTNERSHIPS &
TECHNOLOGY DEMONSTRATIONS)
Geothermal Heat Pumps
•	Model utility marketing group
•	National Earth Comfort
•	Annual unit sales of 400,000 by 2000
Geothermal Power
•	Geysers Pipeline Project
•	Ice-Breaker Plant 1/2-2 MW new capacity

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.
RENEWABLE ENERGY COMMERCIALIZATION
(COLLABORATIVES, PARTNERSHIPS &
TECHNOLOGY DEMONSTRATIONS)
Biomass Power
•	DOE rural development and sustainable power promotion 50/50
cost sharing
•	Projects focus on power from energy crops (co-production
considered)
•	Form partnerships with farmers, industry, power producers,
schools, State and local governments
•	As of February 95 over 350 requests for solicitation
•	Applicants proposed over 250,000 acres for biomass feedstock
production
•	Proposed biomass conversion facilities total 21,000 MW by 2000

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Additional EE Energy Partnerships programs that were not described in the
preceding Lexl boxes are presented below along with a description of certain
Fiscal Year 1995 accomplishments.
Climate Challenge
As one of two "Foundation Actions" in the Climate Plan, Climate Challenge is a
joint, voluntary effort of DOE and participating electric utilities to reduce
greenhouse gas emissions. The program provides electric utilities maximum
flexibility to pursue cost-effective, customized strategies to achieve
measurable results in reducing, limiting, avoiding, or offsetting emissions of
carbon dioxide and other greenhouse gases. DOE developed an "Options Workbook"
and has sponsored several technical workshops to assist utilities in selecting
actions to include in their individual program participation accords.
To date, nearly SCO utilities have joined the program and have together
pledged to reduce greenhouse gas emissions in the year 2000 by more than 46
million metric tons of carbon equivalent. In addition, the electric utilities
have sponsored nearly ten industry initiatives aimed at reducing greenhouse
gas emissions.
Promote Integrated Resource Planning
DOE is accelerating the promotion of integrated resource planning (IRP). This
action is founded on the principle that IRP activities implemented by States
and utilities lead to identifying a broader set of resource options. These
options include both supplyside and demand-side resources, which consequently
are expected to lower greenhouse gas emissions. DOE/IRP "core" program
activities have been expanded with increased attention to improving the
information base and planning tools necessary to permit greenhouse gas
imp!Lcations to be factored into resource decision making by utilities and
regulators.
As part of its ongoing program of technical, analysis, the IRP-DSM Program is
providing meaningful support to state utility commissions, state energy
offices, and other customers. Through these activities, the Program is able
to provide objective and highly-sought analysis and assistance to its
customers. This augments their ability to make informed decisions regarding
energy resource selection -- with specific cons* derati on given to addressing
environmental factors, energy efficiency, and renewable energy resources.
Examples of these activities include:
~	Assessing public policy responsibilities in future electric industry
competition
~	DSM resource characterization
~	International Database on Energy Efficiency Programs (IIOEEP)
~	Consideration of environmental externalities in a restructured electric
industry
~	The role of renewable energy in a restructured utility industry
~	Trends in electric utility industry programs for residents of low income
housing
The results of these analysis are being made available directly to IRPDSM
customers from state agenc i es and other organizations to provide them with the
resources they may need in considering energy efficiency and environmental
factors in their resource evaluation and selection processes.
Moreover, the Program performs a variety of outreach services for its
customers through seminars, vouchers, one-on-one assistance, and technical
reports -- that enhance their IRP capabilities. Recently, program customers
from all 50 states were asked to provide input cn the IRP-DSM Program and well
over half indicated that they had made use of Progr-am products and services
and that these services provided important assistance.
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In all, 37 states have formal IRP requirements. Of these, 21 states
incorporate the consideration of environmental impacts within their IRP
processes. As utility industry restructuring continues to take shape, it is
likely that many of these states will continue to pursue the fundamental
objectives of T3P and in particular, consideration of environmental and energy
efficiency impacts.
In 1995, the Program initiated oeverai new activities designed to support
customers in their TR? activities and to adapt the principles of IRP to a
competitive electric industry. Three cf these activities are well underway
and arc currently providing direct assistance to states and targeted,
innovative analysis. Examples these three activities follow:
ADVANCED RESEARCH IN INTEGRATED RESOURCE PLANNING In response to
Title I, Energy Efficiency, Section 111 (Encouragement of Investments in
Conservation and Energy Efficiency by Electric Utilities), Pub. L. 102-
486, The Energy Policy Act of 1992, the IRP-DSM Program recently
solicited proposals for advanced research. This research is exploring
the nature of the utility industry and market transformation, and the
development of new institutions supporting energy efficiency,
environmental quality and fuel diversity. The solicitation called for
innovative research on tcpics such as:
~	New institutions for promoting and enhancing environmental qual ity
as it relates to the electric power industry
~	New i nstitut ions for improving energy efficiency as it relates to
both electricity supply-side and demand-side measures
~	Revisions to electric IRP that match the evolution of the industry
and market
Nearly 50 research proposals were received on a wine variety of topics
nearly half cf which addressed environmental and energy efficiency
issues. The Program is reviewing them and will makes its selections by
the end of fiscal, year 1995.
EDUCATION VOUCHER PROGRAM - The Education Voucher Program was
established to provide states with access to resources for enhancing
their decision making capabilities. The program has been successful in
getting the word out on voucher opportunities and in providing a quick
turnaround response to voucher applications. This has enabled states to
apply vouchers to real-time needs and support current decision making
activities.
The 1995 education voucher program, which began in February 1995 was
recently completed in August 1995. During that time, 335 voucher
applications were received and over 350 vouchers worth approxi mate!y
$250,00 were awarded. Vouchers were used for a variety of purposes
including renewable energy workshops and obtaining technical resources
(software, technical reports) to enhance IRP related decision making.
In many cases, these resources would have been inaccessible to state
aqencies without the IRP-DSM voucher program.
Voucher recipients have been very pleased with the program and have
indicated that it has helped them to incorporate renewable energy and
conservation into resource planning activities and to begin addressing
the manner in which renewable energy/D£M will be treated in a
competitive utility market.
NATIONAL COUNCIL ON COMPETITION IN THE ELECTRIC INDUSTRY - The National
Council was established under the IRP-DSM Program' Climate Plan activity
to assist state, regional, and federal decision makers in making
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informed policy decisions cn electric industry restructuring. It is a
joint council formed with the National Association of Regulatory Utility
Commissioners and the National Conference of State Legislatures. Among
the issues that the National Council is addressing are the impacts of
restructuring on: stranded benefits such as energy efficiency and
renewable energy resources, the consideration of environmental impacts
in energy decision making, and energy services for low income customers.
The National Council has solicited, and received proposals for, highly
focused analysis to address these issues and has issued a series of RFPs
on topics including the potential for stranded benefits under various
electric utility restructuring models.
The National Council has held videoconferences on restructuring issues,
is providing technical advice to states, and is performing a state-by-
state review on the status of competition and restructuring activities.
Together, the National Council activities are providing states with
access to technical analysis and expertise, that would otherwise be
unobtainable, and support them in the process of electric industry
restructuring. It is enabling state-level decision makers to consider
energy efficiency and environmental issues within a restructured utility-
environment .
Expand "Cool Communities11 Program ir. Cities., and ...Federal. Facilities
This Action expands the existing Cool Communities pilot program (founded by
SPA and American Forests) to 2 50 cities and communities and 100 Department of
Defense bases and other Federal facilities. A Cool Communities Consortium-
comprised of government officials, representatives of conservation
organizations, professional and trade associations, and industry sectors, are
working with communities and Federal facilities to reduce residential and
commercial building cooling loads through developing and using light-colored
building and road surface products and strategic tree planting. Utilities are
also encouraged to adopt: th i s shading/cool i no approach as a Demand Side
Management strategy.
After Tucson. Arizona was designated as a Cool Community, the Commanding
General at Davis-Monthan Air Force Base took the initiative to become partners
in the DOE/American Forests collaborative Clean Cities and became the first
Federal facility designated. Andrew Air Force Base has also been designated a
Cool Community, In a recent ceremony, Brigadier General Monroe S. Sams, 89th
Airlift Wing Commander signed an agreement with Neil Sampson from American
Forests committing the Air Force Base to implement strategic tree planting,
and lightening the color of roofs, pavements, and exterior walla to gain
energy efficiency benefits.
Austin, Texas, a current. DOE Clean Cities partner, initiated a program called
"Trees for Znergy" whereby the local electric utility, the local landscaping
industry, and local government: collaborated in providing incentive rebates to
utility rate payers for strategically planting shade tress on house lots.
American Forests ussri DOE's support to leverage local support by visiting with
potential partners and establishing common goals.
Enhance Residential Appliance Standards
Creating higher energy efficiency levels for refrigerators is one element of
the Enhanced Residential Appliance Standards action. Refrigerators and
freezers using 22-30 percent less electricity than those currently
manufactured could be available to American consumers starting in 1998 if a
new, proposed energy conservation standard for these products is adopted.
DOE's proposed standard incorporates most of a 1994 proposal made to the
Department by a coalition of refrigerator manufacturers, electric utilities,

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states and energy conservation advocates. The coalition proposal was made in
response to an advance notice of proposed rulemaking for refrigerator products
published in 1993. The new proposed standard, which covers refrigerators,
refrigerator-freezers and freezers, was published on July 20, 1995, in the
Federal Register as required by the Energy Policy and Conservation Act of
197 5, as amended.
Energy Analysis and Diagnostic Centers (EADCn)
This Action broadens industry's access to energy efficiency and waste
reduction expert, i sr by signi f icant.ly expanding the number of institutions
affiliated with the current Energy Analysis and Diagnostic Center/Industrial
Assessment. Center (EADC/TAC) program. This program uses university-level
engineering faculty to direct students in performing audits of small sized and
medium-sized manufacturing enterprises within a 150 mile radius of the center.
These firms with between 2C and 499 employees, account for approximately 64
percent of energy consumption in the manufacturing sector.
Each fully operational EADC performs approximately 30 energy efficiency audits
annually. The average energy efficiency audit recommends energy savings of 4
billion Btus with an annual cost savings of $40,000. Of these recommenda-
tions, approximately 40 to 50 percent are implemented by the audited firms.
Since its inception in 1976, the program has generated energy savings of
approximately 80 trillion Btus and $438 million with a total program cost to
date of $27.6 million.
The program has also or is developing: a series of collaborative workshops
for industrial and utility clients; "best practice" manuals for facilities
ineligible for direct EADC assistanceone to support plants too small to
justify individual assessment and another to assist staff at. large facilities
for conducting in-house assessments; and an EADC Awards program to recognize
client firms that implement a major portion of their industrial assessment
recommendations.
As part of the program, DOE is providing industrial assessment training and
support for two Mexican institutions, one in Monterray Mexico and one in
Mexico City, to replicate its industrial Assessment Center (IAC) program.
This program uses engineering faculty and students to provide energy
efficiency arid waste assessments for small and medium sized manufacturing
plants.
Expand RD&D for Methane Recovery from Landfills
This action seeks to eliminate key barriers to the economic recovery and
utilization of landfill gas, a renewable energy source. Barriers to recovery
include low methane generation rates; lack of techniques and data on
performance of enhanced generation methods; concerns with air, water, and
solid waste disposal pollution regulations; and low or uncertain return on
investments in energy recovery equipment due to market barriers for
electricity sale. The action results in demonstrating enhanced gas generation,
efficient utilization and recovery techniques, and the environmental
performance of these techniques at: candidate sites.
The Solid Waste Association of North America (SWANA) and DOR'a Methane
Recovery Systems - Landfills program have formed an ongoing cost shared
partnership. This partnership supports a technical advisory group, which
will peer review methods employed in models developed for the purpose of
predicting the generation of methane gas from landfills. The group will also
review, when completed, the Manual of Practice for the operation and
maintenance of landfill gas recovery systems.
?

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Climatewise Recognition Program
An additional "Foundation Action", Climatewise provides recognition, technical
assiaLar.ee, and education for a broad range of greenhouse gas emission
reduction actions, targeted primarily at the industrial sector. CiimateWise
differs from many other Climate Plan act-ions in that it is not: targeted at a
specific technology or end-use, but instead provides industry with the
flexibility to take those actions most suited to its operations. Conceived as
a partnership between DOE and EPA, the program provides industry with an easy
point of access to technical assistance and recognition available through
other Climate Plan technology-specific actions. This program also is designed
to support the Section 160b(b) reporting system created under EPACT, through
tracking companies' greenhouse gas reductions, regardless of whether these
reductions are the result of actions taken in response to other Climate Plan
act ions.
Meeting	U.S 		Commitments
EE has been developing it's ability to measure the success of Climate Plan
actions as progress is observed between now and the year 2000. Program
adjustment is important as EE has a very large and diverse group of actions,
and it is likely that some programs will exceed their target while others may
fall short. EE's implementation framework allows for a shift in resources
toward markets and programs that show greater potential on an annual basis.
This implementation strategy provides additional assurance that the
President's Plan will effectively reduce greenhouse gas emissions, assuming
Congress supports implementation of the Climate Plan as designed.
As Dart of this performance measurement: concept, specific milestones and
metrics are included in each action implementation plan. According to EE's
program manager for evaluation, Darrell Beschen, including 1; )r - v i nf orniati on in
the program design will enable EE in subsequent years to report on progress
being made and on the very specific benefits of EE's actions.
The end goal, which EE is trying to measure from its portion of the Climate
Plan Actions include a $50 billion of private capital investment by the year
2000, greenhouse gas emission reductions of nearly 40 million metric tons of
carbon dioxide equivalent, and energy cost savings of 530 billion by the year
2010. The measures of success EE proposes for it's individual actions include
the long term impacts of the program on the economy (capital investment
generated and energy productivity), energy impacts (energy savings and
renewable production), environmental improvements (the amount of carbon and
waste reduction;, and equity (incidence of cost and benefit, demographic
.impacts and risk) .
EE also will measure short-term progress such as progress toward program
objectives, market penetration and market assessments; client satisfaction,-
changes in public opinion; and cooperation and coordination. As appropriate,
EE proposes to measure new technology developed from R&D; workshop, seminar,
and information and education results; partnerships and replications from
demonstrations; and applications of technical assistance. EE in cooperation
with other Federal agencies has developed a joint tracking system that will
monitor and track a variety of factors to keep the actions on track with
overall Climate Plan objectives.
Changing the Face of America in the 21st Century
Envision an American community in the year 2000. The family home-bought with
an energy efficient mortgage and built to conform to the newest residential
building standards - is safe, comfortable, and cost effective. It is filled with
appliances much more efficient than any available today, such as newly
designed clothes dryers and ultrasonic dishwashers. Using advanced materials
and processes and mare efficient motor sysLems, local industries save energy,
i _Ar\

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prevent pollution, and enhance economic competitiveness.
All this will be accomplished by establishing new public- and private-sector
partnerships through leveraging modest government expenditures to create much
larger private sector investments. These voluntary agreements have the
flexibility needed to achieve the required emission reductions, while avoiding
mandates and regulations and protecting the bottom line for industry. The
President's Climate Plan is the first document that plans to pull energy,
economy, and the environment together-and keep them together tor the next 10
years.
In helping to meet this commitment, EE has a diverse set, of energy efficiency
and energy supply actions that give Americans real choices on how they produce
and use energy. In the commercial sector, the focus is on raising the energy
efficiency of heating and cooling, lighting, and other building systems
through active outreach programs; innovative financing mechanisms for States;
demonstrations of advanced technologies; and education and training efforts.
The residential actions focus on increasing the energy efficiency of both
appliances and buildings. The industrial actions include raising the energy
efficiency of a wide variety of industrial equipment, expanding information
and auditing activities, and reducing or recycling waste. In the utility
sector, EE's actions focus on accelerating the commercialization of renewable
energy technologies and improving the efficiency of electricity transmission
and distribution systems.
EE's actions build on a solid foundation of existing DOE technology research
and development and technology market deployment authorized by the Energy
Policy Act of 1992. As a result, the President's goal for the year 2000 is
taking shape today in businesses and cities across the United States. 5
For more information on DOS's Energy Partnership Programs, contact the Energy
Efficiency and Renewable Energy Clearinghouse at 1-800-353-3732. Program
information may also be accessed via the information superhighway on
http://www.eren.doe.gov.

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Footnotes
1	President William J. Clinton and Vice President Albert Gore, The Climate
Change Action Plan, October 1993, Washington, DC: Office of Environmental
Policy.
2	U.S. Department of Energy, Memorandum from Christine A. Ervin to Archer L.
Durham, Transmittal of FY 1994 Performance Plan for GPRA Pilot Project. March
23, 1994, pp. 1-2.
3	The White House, Office of the Press Secretary, Remarks by the Vice
President at the white House Conference on Climate Action, George Washington
University, Washington, D.C., April 21, 1994. pp.3-4.
4	U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy,
Implementation of the President's Climate Chancre Action Plan. April 1, 1994.
s Coalgate, Barbara, Changing the Face of America in the 21st Century, a draft
editorial produced for use by the DOE Office of Energy Efficiency and
Renewable Energy "Green Room" public outreach effort.
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1-F
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred.
CLIMATE CHANGE AND THE VALUE OP
TECHNOLOGICAL INNOVATION UNDER UNCERTAINTY
Stephen C. Peck and Thoma3 J. Teisberg
Electric Power Research Inatitute
Palo Alto CA 94303
ABSTRACT
In this paper, we use a small-scale "integrated assessment" model to
explore the role of technological innovation in the context of uncertainty
about the costs of climate change and the state of future carbon-free energy
technologies. We find that if future technology is better, optimal emissions
in the future are significantly lower, while optimal emissions in the near
term may be slightly higher. We also find that a 10 percentage point increase
in the probability of even modestly improved technology may be worth $130
billion dollars in present value. These results indicate both that the state
of future technology matters in developing a strategy for addressing climate
change, and that there are potentially large payoffs to actions we might take
to promote improvements in future technology. Developing carbon-free energy
technologies is a key step towards a sustainable development future.
INTRODUCTION
Since the beginning of the industrial revolution, emissions of
greenhouse gases, such as C02, have been accumulating in the earth's
atmosphere at a steady rate. Because these gases enhance the natural heat
trapping ability of the earth's atmosphere, many people fear that the
accumulation of greenhouse gases will cause the earth's climate to change in
undesirable ways. However, there is still great uncertainty about the degree
to which climate may change, and the extent to which the consequences of
climate change will prove harmful.
The time scale of global climate change is unusually long, climate
change is driven by cumulative emissions of C02 and other greenhouse gases
over centuries, and the full climate response to a given level of cumulative
emissions is delayed by at least a few decades, due to the thermal inertia of
the oceans. This slow response of the climate system to greenhouse gas
emissions may provide some policy flexibility in choosing the timing of major
reductions in greenhouse gas emissions. For many plausible scenarios, it may
be reasonable to target major emissions reductions for future years when the
costs of reduction are likely to be lower.
From a time perspective of years to decades, it is important to
anticipate the likely effects of future technological improvements on the need
for future emissions reductions and the costs of those reductions. Moreover,
we should be keenly interested in research and development efforts which
promote technological improvements leading to lower uncontrolled emissions or
less costly emissions reductions.
In this paper, we use a small-scale "integrated assessment" model to
explore the role of technological change in the context of uncertainty about
both the costs of climate change and the state of carbon-free energy
technologies. In this model, the cost of climate change is represented as the
product of possible large warming related welfare losses and the probabilities
of these losses occurring. Thus, uncertainty about the consequences of
climate change is an integral part of the model.
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We use our model to explore technological change issues in two ways.
First, we show the implications for optimal carbon emissions paths of
different technology assumptions and different assumptions about the
probability of climate change losses. Second, we explicitly represent
uncertainty about technological change and explore the possible benefits
arising from increasing the chance of a 20 percent improvement in key
technology parameters of the model.
Not surprisingly, we find that if future technology is better, more
abatement will be optimal in the future. We also find that if future
technology is better, slightly less abatement is optimal in the.near term.
Finally, we find that it is worth approximately $130 billion to have a 10
percentage point increase in the probability of 20 percent improved future
technology; this provides a rough indicator of the gross payoff to research
and development designed to accelerate technological improvement.
THE CETA-R MODEL
CETA-R is a small scale "integrated assessment" model of the climate
change problem, from the perspective of the world as a whole. The model
combines simple representations of the climate system and the economic system,
thereby providing a consistent framework for analyzing alternative policies
that might be adopted to limit or slow climate change. An optimal solution of
the model represents an appropriate balance between the costs of global
warming and the costs of measures that slow this warming.
The following sections briefly describe the economic and climate systems
in CETA-R, how costs of climate change are modelled in CETA-R, and how optimal
emissions policies are determined in the model.1
Economic System
Economic output in CETA-R is a function of inputs of labor, capital,
electric energy, and non-electric energy. Labor input and the initial capital
stock are exogenously specified. Future capital depends on investment
decisions, which are among the key endogenous variables in the model.
Choices about electric and non-electric energy inputs to production are
also key endogenous variables of CETA-R. The amount of energy employed in
producing output, and the energy technologies used, together determine the
costs incurred in energy production and the C02 emissions generated as a
result of energy production.
Besides emissions of C02, we also incorporate exogenously specified
emissions of CH4, N20, and CFCs. Initially, emissions of CH4 and N20 are
assumed to be at levels roughly consistent with IPCC Scenario B projections.
However, since C02 emissions are virtually eliminated by 2200 in all of the
cases we consider, we assume that emissions of the other greenhouse gases are
phased out as well. Thus, emissions of CH4 and N20 are eliminated between
2010 and 2110, and CFC emissions are eliminated immediately.
Climato System
The climate system in CETA and CETA-R contains very simple
representations of the behavior of greenhouse gases in the atmosphere,
equilibrium warming, and the lag of actual warming behind equilibrium warming.
'For a more extended description of CETA-R, see Peck and Teiaberg (1995b).
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We represent the removal of C02 from the atmosphere using the simple C02
impulse response function developed by Maier-Reimer and Hasselmann (1987).2
Behavior of the other exogenous greenhouse gases is represented U3ing a
transition matrix presented in Nordhau3 (1990) that governs the removal or
transformation of these gases over time.
Equilibrium warming from C02 is represented as proportional to the
logarithm of C02 concentration relative to pre-industrial concentration, with
a constant of proportionality that is calibrated to climate sensitivity
results from general circulation model (GCM) equilibrium experiments.'
Equilibrium warming from the other greenhouse gases is a linear function of
the square root of concentration for CH4 and N20, and it is linear in
concentration for CFCs.4
Thermal lag is represented by a simple geometric adjustment process,
which is calibrated to characteristic response times (e-fold times) obtained
in experiments with coupled ocean-atmosphere models.5
Uncertain Losses from Temperature Rise
In CETA-R, the costs of climate change are large welfare losses which
may occur with relatively small probabilities that depend on the extent of
temperature rise.6 To operationalize this approach, we draw upon some expert
survey results reported in Nordhaus (1994). Nordhaus's results provide
estimates of the probabilities of warming-related losses over the next century
or two. .We use these estimates to calibrate loss probability functions which
specify the probabilities of a large welfare loss as a function of temperature
rise, in each 20-year time period of our model.
Nord'naus surveyed about 20 experts in economics and the natural sciences
regarding their subjective probabilities of damage from global warming. Among
other things, the experts were asked to assess the probability of a "'high-
consequence outcome' -- one defined as a lowering of global incomes by 25
percent or more (the economic equivalent of the Great Depression)."7
Nordhaus found that the experts who are natural scientists are much more
pessimistic than the other experts — the natural scientists' probabilities of
^he Maier-Reimer and Hasselmann model represents C02 uptake by the ocean.
We assume that the biosphere is neutral, i.e. it has no net C02 uptake.
3Sulfur aerosols have recently been identified as an important offset to the
warming otherwise expected from C02. We omit this effect because we lack a
simple way to represent it in our model. Since sulfur aerosols have a very short
atmospheric residence time, and since these aerosols are a function of fossil
fuel use, the effect of omitting them from our model is that temperature rise is
overstated during the years before fossil fuel use ends.
¦•Although we treat CFC3 as a greenhouse gas, recent scientific work calls
this assumption into question, since CFCs interact with lower stratospheric ozone
in a way that may largely offset the direct radiative forcing of the CFCs. To
test the practical importance of this effect in our model, we have experimented
with eliminating CFCs altogether, and found no significant effect on optimal
carbon emissions.
assume an e-fold time of 50 years based on Schlesinger and Jiang (1990).
6See Chao (1995) for a steady-state analysis using this kind of approach to
climate change costs.
'Nordhaus (1994), p. 47.
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a high-conaequence event are roughly an order of magnitude greater than the
probabilities of the group as a whole.
Given the great difference of opinion between the natural scientists and
the experts as a whole, we calibrate loss probability functions separately to
match the survey responses of the scientists and the experts as a whole.
These two calibrations provide natural "High and "Low" cases for the coats of
climate change. The resulting calibrated lose probability functions are shown
in Figure 1; these functions give the probability of a 25 percent welfare loss
occurring in a given 20-year model time period, for temperature rises ranging
from .5 degrees C. to 5.5 degrees C.
Determining Optimal Carbon Emissions in the CSTA-R Model
In integrated assessment models, the common approach is to express costs
of climate change as a known function of temperature rise. Then optimal
carbon emissions are determined by choosing energy technology and use patterns
to maximize the present value utility of consumption, taking account of
warming related costs.
The approach in CETA-R is similar, except that climate change losses are
modelled as occurring randomly, with probabilities that depend on temperature
rise, as described in the preceding section. These loss probabilities are
used to express the CETA-R model objective function aa an expected present
value of future utilities of consumption. The CETA-R model is then solved by
choosing energy technology and use patterns which maximize this expected
present value utility of consumption.
SENSITIVITIES
We begin our analysis by exploring the sensitivity of optimal carbon
emission time paths to assumptions about the loss probability function and the
state of technology. We consider two assumptions for the loss probability and
two for the state of technology. Thus, there are four possible scenarios for
which we determine optimal carbon emissions policies.
For our loss probability assumptions, our "High Damage" case uses the
loss probability function calibrated to the scientists' loss estimates. Our
"Low Damage" case uses the loss probability function calibrated to the median
estimates. These assumptions span a wide range of degrees of severity of
climate change.
For our technology assumptions, we treat a set of three technology
parameters as together defining the state of technology. These parameters are
the electric backstop technology cost, the non-electric backstop technology
cost, and the Autonomous Energy Efficiency Improvement (AEEI) rate.
The backstop technologies are admittedly speculative future technologies
that are characterized as providing carbon-free energy in practically
unlimited amounts, but at relatively high cost, and not until some later date.
The electric backstop technology might be photovoltaics or some form of
advanced nuclear power. The non-electric backstop technology might be
hydrogen produced by electrolysis, where the required electricity is obtained
using the electric backstop technology. In the CETA-R base case, the cost of
the electric backstop is 5 cents per KWH (production cost only), and the cost
of the non-electric backstop is about $90 per barrel of oil equivalent.
The AESI is a parameter that governs how much energy inputs may be
reduced over time without reducing output, for given inputs of labor and
capital. In recent years, there has been a trend toward reduced energy inputs
per unit of output, even in the face of flat to declining real energy prices.
We use the AEEI parameter to project this trend into the future. In the CSTA-
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R base case, the AEEI parameter is .68 percent per year, implying that energy
input may fall at this rate without any effect on output, ceteris paribus.8
Our base case values of the electric and non-electric backstop costs and
the AEEI parameters define our "Standard Technology" case. For our "Improved
Technology" case, we reduce the cost of the electric and non-electric backstop
technologies by 20 percent and we raise the Autonomous Energy Efficiency
Improvement rate by 20 percent, starting in 2030.
Figure 2 shows the carbon emissions paths which are optimal for the four
scenarios defined by the High and Low Damage and Standard and improved
Technology assumptions. Although these emissions paths are surprisingly
similar to one another for the first 20 to 40 years, they show great
differences by about 2100. It is also clear from the figure that the damage
assumption has the largest effect on the optimal emissions path, while the
effect of the technology assumption is more modest.
To see what underlies the optimal emissions paths in Figure 2, we next
present a couple of figures which show the energy technologies that are
employed across two of the four scenarios represented in Figure 2. Figure 3,
for example, shows technologies employed in the Low Damage - Standard
Technology case, which is the one with the highest optimal emissions path.
Areas in the figure represent energy production (and consumption) by •
technology used, and the areas cumulate up to the total amount of energy
produced. Following are brief descriptions of each of the areas shown in
Figure 3, beginning at the bottom of the Figure:
(1)	COAL-D, direct use of coal, continues at a low rate throughout the
time horizon shown.
(2)	NE-OG, non-electric oil and gas use, rises to a peak around 2030-
2050, before declining to near zero by 2110. Oil and gas is an
inexpensive technology and relatively low in carbon (compared to coal,
at least); thus it is fully used until the resource base can no longer
support it.
(3)	SYNK, liquid synthetic fuels made from coal, comes on-stream around
2070 to replace the declining production of oil and gas. Synthetic
fuels are very carbon intensive, and their production underlies the
bulge in emissions observed in Figure 2 between 2070 and 2170. In the
Low Damage - Standard Technology case represented in Figure 3, synthetic
fuels are produced until the coal resource base is exhausted, in spite
of the large emissions of carbon that result.
(4)NE-BACK,	the non-electric backstop technology, comes on-stream after
2130 to replace the declining production of synthetic fuels.
(5)	NE-RENEW, non-electric renewables, begin to be used immediately
after their introduction date in 2050.
(6)	E-FOSSIL, electricity produced from fossil fuels, continues until
about 2070.
(7)	E-RENEW, hydroelectric and geothermal electric, is used at capacity
throughout the time horizon shown.
(8)	E-BACK, the electric backstop technology, cornea on-stream around
2050, when it first becomes available. It replaces electricity derived
from fossil fuel technologies.
"This figure is adopted from expert survey results reported in Manne and
Richels (1994).
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Figure 4 shows energy technologies used in the Low Damage - Improved
Technology scenario, which produces the next highest optimal emissions path in
Figure 2. The main difference between Figure 4 and Figure 3 is that synthetic
fuels are phased-out somewhat earlier in Figure 4. This is what accounts for
the somewhat earlier and lower peak in optimal emissions in this scenario.
While we do not show energy use figures for the High Damage cases,
energy use in these cases is similar, except that synthetic fuels use is small
in the High Damage - standard Technology, while it is eliminated entirely in
the High Damage - Improved Technology case.
The preceding examination of energy use across the scenarios represented
in Figure 2 suggests a simple summary interpretation of the optimal emissions
paths in Figure 2. Across all scenarios considered, oil and gas is used in
the first half of the next century; this is what accounts for high degree of
similarity in the optimal emissions paths in this early time frame. After
about 2050, however, there are big differences in the extent to which
synthetic fuels are used. When they are used heavily, as in the Low Damage
scenarios, optimal emissions rise sharply to a new peak around 2110 or 2130;
but when synthetic fuels are used lightly or not at all, as in the High Damage
scenarios, optimal emissions begin to fall after oil and gas use ends.
These sensitivity results indicate that the climate change damage
assumption is the more important determinant of optimal emissions. Still, the
technology cost assumption has an important affect on optimal emissions, even
for the 20 percent technology improvement that we have assumed. While the
effect of technology is small before about 2070, after 2070, optimal emissions
are significantly lower if technology is better.
Since climate change costs depend on cumulative emissions over decades
and climate response 'to emissions is slow, it is reasonable to hypothesize
that lower optimal future emissions would be accompanied by higher optimal
near term emissions. However, the differences in optimal near term emissions
are too small to see clearly in Figure 2. Thus, to test the above hypothesis,
Table 2 shows optimal emissions in 2030 and the difference in emissions due to
improved future technology, for both climate change cost assumptions. The
numbers in the table show that there is an increase in near term emissions
when future technology is better, thus confirming our hypothesis.
Table 2
Optimal Emissions in 2030
and the Increase Due to Improved Future Technology
(Billion tons/yr.)
Future	Low	High
Technology	Damage"	Damage
Improved	10.362	9.821
Standard	10.352	9.775
Increase	.010	.046
The reason that the change in near term optimal emissions in Table 2 is
small is that optimal emissions in the near term are generally insensitive to
underlying assumptions. As we saw earlier, this insensitivity is attributable
to the fact that conventional oil and gas is the key energy technology in this
time frame, and it is optimal to make use of the oil and gas technology,
whether climate change costs are "High" or "Low," as we have defined these
scenarios here.
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UNCERTAINTY AND THE VALUE OF IMPROVED TECHNOLOGY
In this section, we explicitly associate probabilities with the four
climate change and technology scenarios we considered in the preceding
section. We assume that climate change cost and technology are uncertain
parameters through 2010, but that uncertainty about them is resolved after
2010.
Given this specification of uncertainty, CETA-R may be used to determine
optimal emissions under uncertainty through 2010, as well as optimal emissions
after 2010 when uncertainty has been resolved. These optimal emissions paths
will necessarily be the same across scenarios before uncertainty is resolved,
but will generally differ across scenarios starting in 2030 when uncertainty
is assumed to have been resolved.
In addition, given this specification of parameter uncertainty, CETA-R
may be used to explore the present value today of changing the probabilities
of the two technology assumptions. This provides a measure of the gross
benefit of a given increase in the odds of improved future technology, and a
suggestion of the magnitude of the possible payoff from research and
development that improves the odds of better future technology.
We assume that the probability of the Low Damage case is .8, while the
probability of the High Damage case is .2. For the state of technology, we
experiment with a range of probabilities from a "pessimistic" .3 chance of the
Improved Technology case to an "optimistic" .7 chance of Improved Technology
case.
Figures 5 and 6 show the optimal emissions paths obtained from CETA-R
for the pessimistic and optimistic technology assumptions, respectively.
These paths are indistinguishable from one another. This just means that the
optimal emissions policy under uncertainty is virtually the same for the .3,
and .7 chance of Improved Technology;' and of course, once uncertainty has
been resolved, it is to be expected that optimal policies would not depend on
the earlier probabilities.10
The optimal emissions in CETA-R result from energy use choices that
maximize the expected present value of utility, as described earlier. The
maximized expected present value of utility then provides a measure of the
total future benefits obtained when an optimal emissions policy is followed,
given other underlying model assumptions, including the probability of the
improved future technology. Thus, by comparing maximized expected present
value utility for different assumptions about the probability of improved
future technology, we can obtain estimates of the gross benefits that might be
obtained from increasing the probability of improved future technology."
'A careful examination of the underlying numbers reveals that optimal
emissions in 2010 are slightly higher when the probability of improved technology
in the future is higher (70 percent rather than 30 percent). This is consistent
with the results in Table 2, which indicated that when improved future technology
is certain, optimal emissions are higher in the near term.
'"optimal decisions would differ across the cases in Figures 5 artd 6 only to
the extent that decisions made in 2010 under uncertainty had been different
across cases, and these different decisions affected the context of future
decisions, e.g. by changing the remaining oil and gas or coal resource bases.
,:The difference in maximized present value utility must be converted to
dollar units. However, this is easily done using the shadow price associated
with the model constraint that limits consumption to net output available after
investment.
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Table 3 below presents gross benefits obtained when the probability of
improved future technology is progressively increased from .3 to .7. These
gross benefits are roughly independent of the level of the probability, and
equal to about $130 billion for each 10 percentage point increase in the
probability.
Table 3
Gross Benefits from Increased-Probability
of Improved Future Technology
(Billion $)
Gross Benefit of
10 Percentage Pt.
Probability of	Increase in Probability
Improved Technology	of Improved Technology
30%	127
40%	127
50%	129
60%	130
70%
It should be noted that CETA-R adopts a world-wide perspective on the
climate change issue, and that the above benefits of improved future
technology assume that this technology is deployed world-wide, wherever its
deployment is justified. Since it is likely that only twenty percent of total
carbon emissions will come from the OECD countries by early in the twenty-
second century,12 deployment of improved technologies is likely to be
particularly important outside the OECD. This may require that institutions
be developed to encourage the world-wide dissemination of technology
improvements that will be beneficial in addressing the climate change issue.
SUMMARY AND CONCLUSIONS
In this paper, we use a small scale "integrated assessment" model of
climate change to explore the role that technological improvement plays in
addressing climate change. We look at the implications of future technology
improvements for present and future optimal emissions policies, and we
estimate the dollar benefits potentially available from improvements in future
technology.
We find that if future technology ia better, optimal emissions in the
future are significantly lower, while optimal emissions in the near term may
be slightly higher. We also find that a 10 percentage point increase in the
probability of even modestly improved technology may be worth $130 billion
dollars in present value. These results indicate both that the state of
future technology matters in developing a strategy for addressing the climate
change issue, and that there are potentially large payoffs to actions we might
take to nurture improvements in future technology.
However, we note that for the full benefits of technology improvements
to be realized, these improvements must be available anywhere in the world
where they could be advantageously used in reducing greenhouse gas emissions.
,:In Peck and Teisberg (1995), we disaggregate the world into two regions,
the OECD and the rest-of-the-worId (ROW). We find that when world-wide emissions
reach their peak, ROW emissions are four times OECD emissions.
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Thus, it may be important to develop institutions to facilitate world-wide
dissemination of future technology improvements that aid in addressing the
climate change issue.
Finally, we note that lowering the cost of backstop technologies may be
viewed as an important way to facilitate a transition to a sustainable
development path in the future. If the greenhouse risk proves to be low,
these technologies will replace fossil fuels sometime in the twenty-second
century when these limited resources become exhausted. If the greenhouse risk
proves to be high, the backstop technologies may be called into service much
sooner to avoid overuse of the limited C02 absorptive capacity of the earth's
atmosphere.
Disclaimer
This paper does not necessarily represent the position of EPRI or of its
members.
References
Chao, Hung-Po' (1995), "Managing the Risk of Global Climate Catastrophe: An
Uncertainty Analysis," Risk Analysis, forthcoming.
Maier-Reimer, E. and K. Hasselmann (1987), "Transport and Storage of C02 in
tho Ocean — An Inorganic Ocean-Circulation Carbon Cycle Model", Climate
Dynamics. Vol. 2, pp. 63-90.
Manne, Alan S. and Richard G. Richels (1994), "The Costs of Stabilizing Global
C02 Emissions: A Probabilistic Analysis Based on Expert Judgements," The
Energy Journal. Vol. 15, No. 1, pp. 31-56.
Nordhaus, William D. (1990), "Contribution of Different Greenhouse Gases to
Global Warming: A New Technique for Measuring Impact," February 11.
Nordhaus, William D. (1994), "Expert Opinion on Climatic Change," American
Scientist. January-February, pp. 45-51.
Peck, Stephen C. and Thomas J. Teisberg (1995a), "International C02 Emissions
Control: An Analysis Using CETA," Energy Policy, Vol. 23, No. 4.
Peck, Stephen C. and Thomas J. Teisberg (1995b), "Optimal C02 Control Policy
with Stochastic Losses from Temperature Rise," C1imatic Change. forthcoming.
Schlesinger, Michael E. and Xingjian Jiang (1990), "Simple Model
Representation of Atmosphere-Ocean GCM3 and Estimation of the Time Scale of
C02-Induced Climate Change," Journal of Climate, December, pp. 1297-1315.
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Figure 1: Calibrated
Loss Probability Functions
Loss Probability per Period
Temperature Rise (Deg. C.)
—~ Median ^ Scientists'
Figure 2: Optimal Emissions
for Four Scenarios
Billion tons/yr.
Year
Damage/Technology:
Low/Improved - Low/Std. —High/Improved -1Hlgh/Std.
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Figure 3: Energy Use
Low Damage - Std. Technology
EJ/Yr.
Year
HDD COAL-D O NE-OQ CHI SYNF	[_~ NE-BACK
S3 NE-RENEW M E-FOSSIL WS E-RENEW W& E-BACK
Figure 4: Energy Use
Low Damage - Improved Technology
EJ/Yr.
Year
ED COAL-D Em NE-OQ	Em SYNF	~ NE-BACK
US NE-RENEW Wk E-FOSSIL	E-RENEW WM E-BACK
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Figure 5: Optimal Emissions
ProbOmproved Technology) = .3
Billion tons/yr.
Year
Damage/Technology:
	Low/Improved * low/Std.	High/Improved -<=*-Hlgh/Std.
Figure 6: Optimal Emissions
ProbOmproved Technology) = .7
Billion tons/yr.
1990	2030	2070	2110	2150	2190
Year
Damage/Technology:
Low/Improved 1 Low/Std.	High/Improved ~~e— Hlgh/Std.
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The Global Future:
Environment vs. Development
J ohn Kadyszewski
Winrock International
Symposium on Greenhouse Gas
Emissions and Mitigation Research
June 27-29,1995
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Summary
•	Increasing Importance of Developing
Country Emissions
•	Perceived Conflict Between
Environment and Development
•	Emerging Competition for Capital
•	Implications for Technology
Development
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GHG Emissions in-
Developing Countries Will
Surpass the United States,
Europe, anrf Japan Early in
the Next Century
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C02 Emissions 1990
oe
4^
4 5%
lURest of World
M S o v iet Union
S., Europe, and
Japan
16%
123
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C02 Emissions 2010
13%
Rest of World
Former Soviet
Union
U.S, Europe, and
Japan
51%
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China:
1990
"T
:f ~V<*;: JT» '-^
r v<*-#> | Mfc.

2.5 million MT
CO2 Emissions
8 million MT
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Development Needs
•	Growth in Energy Consumption
Essential for Future Development
io
-4
•	Primary Constraint — Lack of Capital
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Per Capita Energy
Consumption 1991
CO
oo
350
300
250
200
150
100
50
0
320
187
Gigajoules
per Capita
m



H . I



ill
23
9
9.5

HH. MH

	wasasnaaesmssAi
U.S. Germany China
India
Central
America
WM
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Per Capita Electricity
Consumption 1990
so
sO
12
10
8
6
4
2
0
11.6
0.54
0.43
0.31
North
America
China Central
America
India
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o
o
Capital Requirements for
New Power Capacity
China — $10 billion per year
India — $12 billion per year
Rest of Asia - $8 billion per year
Latin America - $15 billion per year
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Average Power Sector Lending
Early 1990's -
$4 billion per year combined
from
Asian Development Bank,
Inter American Development
Bank, World Bank
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Economic Priorities
•	Attract Private Capital
•	Minimize Government Liability
•	Minimize Cost Per Unit of Capacity
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Perception:
Restraints on Emissions
Will Make New Sources
I
VG
L»J
of Energy More Expensive
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Competition for Private Capital
•	Many Countries Building
Credit-W orthiness
•	Building Credit-Worthiness
Takes Years
•	Maximum Multinational Leverage
Early in Process
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Private Power Experience
•	USAID/World Bank 1994 Study
•	Eight Projects -- 4700 MW Total
•	Bilateral and Multilateral Support
Extended Maturities 7 Years
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What About New
Technology?
o\
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Market Trend in
United States
•	Power Demand Flat
•	Downward Pressure on Prices
i
vO
•	Market Consolidation Underway
•	Investment in R&D Declining
SS3
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Market Trend in
Developing Economies
Power Demand Growing at
10 Percent Per Year
Local Technology Significantly
Cheaper than Imported Technology
Financing Critical to Technology Choice
Local Firms Developing Capability to
Build Conventional Technology
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Impact on Technology Choice
•	Companies that Bring Financing Hiave
Comparative Advantage
•	Rate of Innovation Declining
•	Opportunities for Multinational
Companies Changing
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Central American Experience
•	Region Rich in Renewable Resources
•	Cost of Electricity from Renewable
Resources Competitive
•	Renewables Harder to Finance
•	Fossil Market Share Growing
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Blending Environment and
Development Objectives
•	Influence Private Capital Lending
•	Create Incentives to Develop "Safe"
and "Clean" Technology
•	Build Local Capacity
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New Priorities of International
Financial Institutions
•	Promote Policy Reform —
Rationalized Pricing,
Regulatory Transparency
O
to
•	Protect Global Environment
•	Support Free Trade
m
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How to Protect
Global Environment
• Use IFI's to Attract Private Capital
to "Clean" and "Safe" Energy
Technology (e.g. Help Extend
Maturities)
03
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SESSION II: EMISSIONS FROM ANTHROPOGENIC SOURCES
M. A. K. Khali 1, Chairperson
2-A
The work described in (his paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred.
GLOBAL EMISSIONS INVENTORIES
Jane Dignon
Global Climate Research Division
Lawrence Livennorc Laboratory
Livermore, CA 94550 U.S.A.
ABSTRACT
Many trace chemical species in the atmosphere are radiatively important and may affect
climate and air quality. Detailed and accurate emissions inventories are essential for understanding
the changing chemical composition of our atmosphere, and to establish compliance with international
agreements. Currently climate and chemistry model predictions are limited by the paucity of quality
emissions data input. This paper is designed to present a compilation of emissions inventories for
radiatively important trace species. It reports the spatial and temporal characteristics of the emissions
along with some interpretive comments.
INTRODUCTION
Anthropogenic and natural factors affect the radiative forcing of the atmosphere. They have
various magnitudes and different signs. The concept of radiative forcing allows us to compare the
potential impacts of various factors. Different chemical species found in the atmosphere can affect
the radiative forcing by acting as greenhouse gases. The amount that any individual chemical can
effect the radiative balance is dependent on their concentration and their residence time in the
atmosphere, i.e. their chemical lifetime. Their chemical concentrations and lifetimes are dependent
on their sources and sinks, and/or the sources and sinks of their chemical precursors.
Carbon dioxide has received most of the attention in regard to the concerns of climate change
and greenhouse effect. Model studies have shown that the sum of the radiative effects from other
greenhouse gases, along with the indirect effects due to chemistry could be comparable to the
projected effects of C02 alone [1], The names, chemical structures, along with the direct and indirect
ways these atmospheric constituents can influence the radiative forcing of the Earth/atmosphere
system are listed in Table 1.
Most of the gases listed in Table 1 are greenhouse gases, or in other words, they are
absorbers of long wave terrestrial radiation. Several of the other gases, e.g. nitrogen oxides, OH and
CO, do not directly affect climate, but are important in relation to climate change because of their
atmospheric chemical processes. They can have a strong influence on the atmospheric radiative
forcing by affecting the concentration and distribution of the greenhouse gases.
Other species can form aerosols in the atmosphere that may affect climate through scattering
of solar radiation and by altering cloud properties. From Table 1 we can see that the atmospheric
concentrations of many of these radiatively important trace species are increasing. Evidence suggests
that surface emissions, primarily from anthropogenic sources, are largely responsible for the
increasing trends, particularly for gases such as CO_„ CH4, CO, N,0, CFCs, and several of the
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halocarbons [2]. The primary goal of this paper is to establish what we know about the emissions
and budgets of the radiatively important atmospheric constituents listed in Table 1.
CARBON DIOXIDE.
Atmospheric carbon dioxide concentrations have been measured at the Mauna Loa
Observatory in Hawaii since 1958. The average annual concentration of C02 at Mauna Loa has risen
from 315.8 ppmv in 1959 to 356.2 ppmv in 1992 [3]. C02 concentration in air bubbles trapped in ice
cores indicate that the preindustrial concentration of C02 was approximately 280 ppmv [4] [5]. Fossil
fuel use and changing land use (i.e., deforestation and biomass burning) are the two types of human
activities responsible for the increasing trends of C02.
Burning of fossil fuels released about 6±.6 Pg of carbon into the atmosphere in 1990 [6][7],
From 1860 fossil fuel emissions have increased from less than 0.1 PgC per yr to greater than 6 PgC
per year presently[8]. Emissions of C02 increased steadily at about 4.5 percent per year from 1945
through 1979, then declined from 1979 to 1983 but have increased since. Marland et al. [6] have
presented inventories of C02 emissions on a country by country basis from 1950 to the present. In
1950 the U.S. was responsible for more that 40 percent of the total global emissions. This share has
steadily declined to less than 25 percent today. Now the U.S., former Soviet Union, and Peoples
Republic of China combined are responsible for about half of the worlds fossil fuel emissions.
Estimates of the net flux of carbon into the atmosphere for the year 1980 from land use range
from 0.4 PgC/yr to 2.5 PgC/yr [2][9][10][11]. Prior to the impact of human activities, natural
vegetation contained roughly 1000 Pg carbon [12]. This has decreased to current levels of about
560 Pg carbon [13]. It is clear that the magnitude of the carbon storage in contemporary landscapes
is less than what was stored in the natural vegetation, however the rate of release and the timing of
the major releases is very uncertain. Houghton and Skole [14] give estimates of carbon releases from
vegetation and soils since 1800. They estimate that carbon storage in vegetation and soil has
decreased by 170 Pg since 1800.
The observed increase in the carbon content of the atmosphere represents only 54 percent
of the total release. Inconsistencies in our understanding of the relationship between observed
increases in atmospheric C02 concentration and past fossil fuel emissions makes it difficult to make
projections of future levels. All evidence indicates, however, that the C02 concentration can rise to
double preindustrial levels within the next 50 years due to continued human activities.
METHANE
Although its atmospheric abundance is less than 0.5 percent that of C02, each molecule of
methane (CH4) is about 21 times more effective at absorbing infra-red radiation than an additional
molecule of C02 [12]. The globally averaged atmospheric concentration of CH4 is about 1.72 ppmv,
with slightly higher concentrations in the Northern Hemisphere (1.76 ppmv) than the Southern
Hemisphere (1.68 ppmv).. Methane concentrations increased at an average of about 1 percent per
year (16 ppbv/yr) over the decade from 1979-1989. Khalil and Shearer [15] have shown that the rate
of growth has actually decreased in the late 1980's and early 1990's with the annual increase more on
the order of 10 ppbv per year. The change in growth rate may indicate that changes have occurred
in the sources and/or sinks over the last few decades. Khalil et al. [16] suggest a decoupling of the
increase of agricultural related sources (rice and animals) with the increase in human population.
Although methane is a naturally occurring greenhouse gas, its concentration is growing as
a result of human activities including rice paddies, animal husbandly, landfills, biomass burning, and
fossil fuel use. Globally CH4 has increased by 7 percent over the decade from 1983. Because methane
concentrations have been measured at global background sites for a number of years, the magnitude
of the individual sources is less well known than the mass of atmospheric increase. The estimated
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sources of methane to the atmosphere are broken down in Table 3 [2][9][17][18][19][20][21][22].
Complete spatially resolved emissions inventories of CH4 are complex because of the large number
of CH4 source types. The best known source is probably emissions from domestic animals for which
populations of animals are kept for commercial reasons. Rice is a large source of methane emissions,
however measurements have shown more than an order of magnitude difference in CH4 fluxes.
Similar differences are found in wetlands and landfills. Carbon isotope measurements indicate that
roughly 20 percent of the total emissions are from fossil fuel use [231. Anthropogenic emissions are
responsible for 60-80 percent of the total current methane source (see Table 3).
Photochemical oxidation with the hydroxyl radical (OH) is the largest sink for atmospheric
CH4. Using current estimates of the global OH concentration the total quantity of CH4 that reacts
with OH is about 445 Tg/yr [20]. Microorganisms in the soil also remove CH4 from the atmosphere.
Microbial oxidation is estimated to remove 30±15 Tg/yr. There is also a relatively small (10±5 Tg/yr)
stratospheric sink.
HALOCARBONS
Halocarbons are of environmental concern because they have both the potential to affect
stratospheric ozone as well as being greenhouse gases. With the exception of some natural emissions
of CH3CI and CH3Br, halocarbons present in the atmosphere are entirely from anthropogenic sources.
Annual production and total sales are available from most of the world and are available from trade
organizations. Release statistics of CFC-113, -114, and -115 have been compiled by Fischer et al.
[24], The spatial distribution of these releases are poorly characterized, because data shipment
information is restricted by corporate confidentiality [25]. A summary of global sources is listed in
Table 4.
Global observation networks have provided regular observations of CFC13, CF2CL, CH3CC13
and CCl,, since 1978 [26], CFC-11 and CFC-12 have the largest atmospheric concentrations of 0.2
and 0.5 ppbv respectively. The tropospheric concentrations of both gases were increasing at about
4 percent per year in the early 1990s but have slowed down to roughly 1-2 percent per year [8]. The
concentration of CFC-113 was increasing at an even faster rate in the early 1990s, increasing at about
10% per year, but has also slowed since then. CH,CC1 and HCFC-22 are increasing by about 2 and
7% per year respectively. CFC-113 and CH3CC13 are used as solvents. HCFC-22 is used in air
conditioning and refrigeration.
All of the fully halogenated chloroflourocarbons have very long atmospheric lifetimes with
CFC-11 at 50 years, CFC-12 at 102 years [17]. These long lifetimes contribute to the sustained
increasing concentrations of these gases. Bromine containing halons, used in fire extinguishing, have
very small concentrations but they are very long lived and are much more effective at destroying
stratospheric ozone. The peak tropospheric concentration of halocarbons is expected to have
occurred in 1994 but stratospheric peak will lag by about 3 to 5 years [ 17]. The atmospheric lifetimes
of HCFCs, HFCs and other halocarbons containing hydrogen tend to be much shorter (less than 15
years) due to their reaction with the hydroxyl radical.
Recent modifications of the Montreal Protocol call for the elimination of the production of
CFCs by 1996 and an eventual a phase out of the production CH3CC13, CC14 and the halons. Some
governments are reluctant to comply claiming it will have detrimental impacts on their economies
[27].
NITROUS OXIDE
Nitrous oxide NzO is a greenhouse gas where one molecule is 200 times more effective at
absorbing in the infra-red than C02 and its atmospheric lifetime is about 120 yrs. N,0 is also
responsible for a significant fraction of the natural destruction of stratospheric ozone. The mean
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atmospheric concentration of N20 in 1990 was about 311 ppbv [20]. According to ice core records,
the atmospheric N20 concentration about 150 years ago was 285 ppbv [28]. Its concentration is
currently increasing at roughly ,2-.3 percent per year.
The various natural and anthropogenic sources of N20 are not well quantified consequently
the cause of the increase is not certain. The main anthropogenic sources are from agriculture
especially development of pasture in tropical regions (~6 TgN/yr), biomass burning (2.5-5.7 TgN/yr),
and a number of industrial processes (0.5 TgN/yr) [29]. Addition of nitrogenous fertilizers adds an
additional 0.03 to 2.0 TgN/yr [30]. Bouwman et al. [31] produced an inventory from natural
terrestrial ecosystems of ~4.4 TgN/yr. A best estimate of the current anthropogenic emission of N20
is 5 to 20 Tg N/yr.
N20 is removed mainly by the photolysis in the stratosphere. Table 5 lists the known budget
of N20. It is very difficult at this time to project future emissions of N20 when such large
uncertainties are associated with the numerous small sources. In order for N20 levels to stabilize near
current levels, anthropogenic sources would need to be reduced by more than 50 percent [20].
NON-METHANE HYDROCARBONS AND VOLATILE ORGANIC COMPOUNDS
Non-methane hydrocarbons (NMHCs) constitute a large class of compounds containing only
carbon and hydrogen. Volatile organic compounds (VOCs) include NMHCs and other organic
compounds containing additional elements such as oxygen. A number of NMHCs and VOCs are
potentially important greenhouse gases however their reactivity is high enough that these gases tend
to have short lifetimes; consequently it is unlikely in the foreseeable future that their concentrations
will be large enough to directly affect climate. The indirect climatic affect of NMHCs and VOCs lie
in their tropospheric chemistry.
The indirect climatic effect of VOCs is most important through their controlling of
tropospheric 03 and OH concentrations. For most VOCs, reactions with the hydroxyl radical provide
the major loss and a significant source of carbon monoxide. In the presence of NOx and sunlight,
NMHCs can result in the production of tropospheric 03. VOCs can also react with NO* and produce
a source of organic nitrogen. Organic nitrogen compounds can act as temporary reservoirs for NOx
allowing nitrogen oxides far greater global transport from their sources; which can again lead to
tropospheric ozone production.
Inventories of VOCs are very complex not only because of the numerous source types but
also because of the large number of species included. Sources of VOCs are associated with both
natural and anthropogenic processes. In addition, because of their generally short lifetimes (order of
hours for biogenic hydrocarbons to several months for ethane), combined with their highly localized
sources, organic compounds are not distributed evenly through space and time. In some areas the
natural sources dominate, while in urban areas anthropogenic emissions control VOC concentrations.
Recent estimates of the total global anthropogenic VOC source is about 100-140 Tg C per year with
25 percent due to road transport, 14 percent from solvent use, 13 percent from fuel production and
34 percent from fuel consumption. The rest is from biomass burning (an important source in
subtropical and tropical regions [32]) and other minor sources [22][30], The annual emissions from
natural sources are an order of magnitude higher at 1150 TgC/yr. Isoprene composes 44 percent of
the total, with monoterpenes at 11 percent, other reactive VOCs at 22.5 percent, and the remainder
is other VOCs [33].
CARBON MONOXIDE
Measurements over the past 25 years have shown CO mixing ratios ranging from 40-200 ppbv
[34], Annual mean CO levels in the high latitudes of the Northern Hemisphere are about a factor of
3 greater than the Southern Hemisphere. Carbon monoxide levels are usually much higher over
2-4

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continental regions than oceans reflecting the input from continental sources. Up until 1990,
Northern Hemisphere concentrations of CO were increasing at roughly 1 percent per year. Recent
data of indicate that global CO levels have fallen sharply since 1990 from 1-7 percent per year
depending on location [35][36]. There is no clear explanation for this rapid decrease, however one
speculation is increasingly effective emissions controls.
Although CO is not important for its direct impact as a greenhouse gas, it is important to
climate through its reactivity in the troposphere. The reaction of CO with OH is the primary sink for
atmospheric OH, which yields an additional source of the greenhouse gas CO,. CO is also a local air
pollutant and can contribute to the formation of infra-red absorbing tropospheric ozone in the
presence of NOx. Soil uptake and stratospheric removal are also minor carbon monoxide sinks.
Based on measured CO distributions and an OH field from model calculations the total global sink
of CO is estimated at 865 TgC/yr [8], Studies of 14CO indicate that the global CO sink may be even
higher [37] [38],
The major sources of CO are anthropogenic, including transport, combustion, industrial
processes, and biomass burning. Oxidation of methane and NMHCs from both natural and
anthropogenic origin are also important. Oceans may also be and important natural source. All of
these sources have a large uncertainties. It is estimated that more than half of the current CO
emissions are anthropogenic if one includes that derived from anthropogenic CH4. The source of CO
from the oxidation of isoprene and other NMHCs is dependent on the uncertainties of the NMHC
inventories. The source of CO from the oxidation of CH4 on the other hand is somewhat more well
characterized because the atmospheric concentration of CH4 is more widely understood.
Emissions of CO from fossil fuel combustion peak between 30 and 60 degrees north
latitude[39]. More than 70 percent of the biomass burning source is emitted in tropical regions [32].
Total anthropogenic sources are about 900 TgC/yr with a large uncertainty range and are listed in
Table 6. On the global scale, inventories of CO have been developed at the 5°x5° scale by Muller
[40], The source from biomass burning has been estimated by Hao el al. [41] on a 5°x5° grid for
tropical regions only, and Erickson [42J has developed a global inventory for the ocean flux of CO
with a resolution of 4.5° latitude by 7.5° longitude.
NITROGEN OXIDES
Nitrogen oxides (NO, + NO = NOx) have historically been considered important due to their
role as primary pollutants in photochemical smog and their contribution to acidic dry and wet
deposition. Though one of the nitrogen oxides, namely NO,, is an important absorber of visible solar
radiation, and could affect the climate directly if tropospheric and/or stratospheric concentrations
were to increase, NOx has little direct impact on die tropospheric radiation balance at present.
Nitrogen oxides do however, have a large indirect effect owing to their importance in tropospheric
chemistry. NOx is a catalyst promoting the formation of tropospheric ozone and controlling the
concentration of OH. Through OH, emissions of NOx influence the lifetimes and therefore the
abundances of many of the greenhouse gases. Nitrogen oxide species are relatively short lived,
however, they can react chemically with NMHCs to produce organic nitrate. The strongly
temperature dependent lifetimes of organic nitrates provide a reservoir for nitrogen oxides which can
be transported long ranges to affect ozone chemistry well downstream from the sources.
NOx is emitted mainly in the form of NO. The major sources of reactive nitrogen are fossil
fuel combustion, biomass burning, lightning discharges, microbial activity in soils and transport from
the stratosphere (see Tabic 7). Fossil fuel combustion is the largest source of NOx and according to
Hameed and Dignon [43] the global emissions from fossil fuel combustion increased from 18 TgN
per year in 1970 to more than 24 TgN/yr in 1986.
Anthropogenic emissions of NO* have uncertainties ranging ±30 percent but in the case of
natural sources, uncertainties may range by more than a factor of 2. NOx produced by lightning is
2-5

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probably the most important natural source in the free troposphere. Price et al. [44] give a range
for the NO* source from lightning of 5 to 25 TgN/yr. Preliminary estimates suggest that in some
geographical regions emissions from soils and lightning are the most significant source [45]. Dignon
et al. [46] have determined an emissions estimate from natural soils at 5 TgN /yr. This is consistent
with the 3.3 to 7.7 TgN/yr range given by Levy et al. [47],
Atmospheric oxidation of N02 to HN02 by OH in the daytime and to N03 by 03 at night are
the most important NOx removal processes. Dry deposition of N02 plays a lesser but significant role.
The tropospheric lifetime of NOx varies from less than a day in the boundary layer to about a week
in the free troposphere. Although the removal processes of NO* are reasonably well defined the
global distribution of NOx is quite uncertain therefore an estimate of ~42 Tg N/yr for the sink of
NOx can be made based on the work of Atherton et al. [48].
Because of the high variability in its tropospheric concentrations, it not possible to establish
a clear trend for NOx from atmospheric observations. The anthropogenic sources, particularly in the
Northern Hemisphere, continue to increase and the concentration of nitrate in Greenland ice cores
exhibits an increase during the last century[49]. There is evidence that tropospheric 03 in the
northern mid-latitudes has increased [23] and much of this increase can be attributed to increased
NOx emissions [50],
OZONE
Unlike the other greenhouse gases listed above, whose radiative effects are largely dependent
on their concentrations, the climatic effect of ozone (03) depends on its distribution throughout the
troposphere and stratosphere. Ozone is the primary absorber of ultra-violet and visible radiation in
the atmosphere and its concentrations determine the amount of ultra-violet radiation that reaches the
Earth's surface. Ozone is also a greenhouse gas with a strong infra-red absorption band at 9.6'pm.
Changes in the ozone distribution can cause radiative forcing by influencing both the solar and
infrared radiation. It is the balance between these radiative processes that determine the net effect
of 03 on the climate.
Approximately 90 percent of the ozone in the atmosphere is contained in the stratosphere.
Natural production of ozone in the stratosphere begins with the photodissociation of the 02 molecule
at ultra-violet wavelengths less than 242 nm. This reaction produces two ground-state oxygen atoms
that can then react with 02 to product 03. Increases in ozone above roughly 30 km tend to decrease
the surface temperature by decreasing the amount of solar radiation that reaches the Earth's surface.
Ozone is also produced in the troposphere as a major component of photochemical smog resulting
from anthropogenic emissions of NOx, CO and hydrocarbons. Increases in ozone concentration
below 30 km, where the infra-red greenhouse effect dominates, tend to increase the surface
temperature.
Measurements of ozone from ground based stations and satellites indicate that the
concentrations of ozone in the stratosphere are decreasing. The most obvious feature is the annual
development of the Antarctic ozone hole which occurs in the Austral spring. The October average
total ozone values over Antarctica are 50-70 percent lower than those observed in the 1960s [17].
The primary destruction of 03 in the stratosphere comes from catalytic mechanisms involving various
free radical species, including oxides of nitrogen, chlorine, bromine, and hydrogen. Nitrogen oxide
species are believed to be responsible for 70 percent of the total ozone destruction. Most of the
nitrogen oxides in the stratosphere are believed to occur naturally; however, increasing anthropogenic
emissions of N,0 at the surface are leading to growing amounts of stratospheric NOx. Levels of
reactive chlorine are increasing in the stratosphere from anthropogenic emissions of halocarbons. The
reactive chlorine catalytic mechanism is particularly efficient at destroying ozone in the stratosphere
and is believed to be the major contributor to the observed ozone depletion [11],
Downward transport of ozone from the stratosphere used to be considered the major source
2-6

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of tropospheric ozone. It is now thought that the net tropospheric photochemical production of
ozone is of a comparable magnitude [23][51]. The formation of tropospheric ozone occurs through
mechanisms where NO reacts with H02, in the presence of hydrocarbons and sunlight. Changes in
tropospheric ozone are highly variable both regionally and vertically, making assessment of global
long-term trends difficult. Ozonesonde balloon measurements indicate that northern mid-latitudes
concentration of ozone in the troposphere have been increasing since 1969 [23] [52], There is also
some evidence that lewis have increased in the NH since the early 1900s [53]. Dignon and Hameed
[50] have shown that most of the observed ozone increase between the years 1966 and 1980 can be
attributed to increasing anthropogenic fluxes of NOx and hydrocarbons.
HYDROXYL RADICAL
The lifetimes of many of the radiatively important trace species depends on the concentration
of hydroxyl radical (OH). Hydroxyl is the major scavenging species for removal of virtually all
greenhouse gases except for CO,. The OH radical responds instantaneously to variations in 03, NOx,
CO, CH4, VOCs and sunlight. The field can vary by orders of magnitude in space and time. It is not
currently possible to measure the global field of OH therefore we are left to rely on numerical models
to estimate the global, seasonal and vertical distribution of OH. Anthropogenic increases of
greenhouse gases are removed by OH have the potential to reduce the global OH concentration,
causing a chemical feedback decreasing the loss rate of greenhouse gases, and resulting in elevation
of greenhouse gas concentrations.
AEROSOLS
Aerosols are suspensions of particles in the atmosphere of the size range 10"3 to 100 ym in
diameter. Their distributions are highly variable regionally in both concentration and chemical
composition. Tropospheric aerosols are formed by dispersal of material from the surface (e.g., soil
and dust), by direct emissions of material into the atmosphere (e.g., smoke) and by chemical reactions
in the atmosphere which convert gases into particles (e.g., sulfur dioxide to sulfate). Stratospheric
aerosols have a longer lifetime than aerosols in the troposphere and therefore are more uniformly
distributed. Large volcanic eruptions such as Mt Pinatubo influence the aerosol content of the
stratosphere.
Addition of anthropogenic aerosols can influence the radiative balance of the Earth in two
ways: (1) directly through absorption and through scattering of solar radiation back to space, and
(2) indirectly by acting as cloud condensation nuclei thus changing the lifetime and radiative
properties of clouds. There are many uncertainties associated with the climatic influence of aerosols
one thing that is known is the direct and indirect effect of aerosols are both strongly influenced by
particle size and composition. Therefore, the radiative effects can not be simply related to the aerosol
mass loading. The radiative effect of anthropogenic aerosols are relatively large compared to their
mass loading because their size distribution (< 1 pm) is in the range that is most radiatively active.
Natural sources of aerosols include sea-salts, resulting from the evaporation of sea-spray
droplets, and volcanic emissions. Soil dust is also a major natural source in arid and semi arid
regions. The diameter of windblown dust ranges from 1 to >100 pm, where the largest particles fall
out very rapidly. The annual emissions amounts to about 1500 Tg/yr, which is of the same order as
sea-salt production (1300 Tg /yr). Table 8 summarizes the annual emissions of aerosol into the
troposphere and stratosphere [17]. Removal of aerosols is mainly achieved by deposition to the
Earth's surface or by volatilization.
Release of sulfur dioxide from fossil fuel combustion and carbonaceous species mainly from
biomass burning are the main anthropogenic sources of aerosols. There is evidence suggesting the
concentration of anthropogenic aerosols have increased downwind of industrial regions and that this
2-7

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increase is very large compared with the natural background. Owing to the effect of size distribution
and chemical composition, anthropogenic aerosol contributes approximately 50% of the global mean
optical depth but only 20% to the mass burden [17).
The impact of aerosol on the optical properties of low level clouds has been demonstrated in
the localized observations of ship tracks[54], but has not been observed globally. There is, however,
some observational evidence that mean sizes of cloud droplets are larger in the Southern Hemisphere
than in the Northern Hemisphere, suggesting that sulfate emissions in the industrialized north may be
having a widespread effect[55],
SUMMARY
Atmospheric chemistry determines the concentrations of most of the important greenhouse
gases except for carbon dioxide. The rate of removal of the greenhouse gases from the atmosphere
is also controlled by atmospheric chemistry. The indirect effects of chemical forcing resulting from
the chemical interactions of other species can also affect the concentrations of radiatively important
gases such as ozone.
In order to establish the contribution of any possible climatic change attributable to individual
greenhouse gases, spatially and temporally resolved estimates of their emissions need to be
established. Unfortunately, for most of the radiatively important species the global magnitudes of
their individual fluxes are not known to better than a factor of two and their spatial distributions are
even more poorly characterized. Efforts to estimate future projections of potential impacts and to
monitor international agreements will require continued research to narrow the uncertainties of
magnitude and geographical distribution of emissions.
ACKNOWLEDGMENTS
This work was partially supported by the Lawrence Livermore National Laboratory Directed
Research and Development Program under the auspices of the U.S. Department of Energy Contract
No. W-7405-Eng-48.
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TABLE 1: RADIATTVELY IMPORTANT TRACE SPECIES
Trace Species
Common Nanie
Troposphcric
Concentrations (ppmv)
Trend in Concentration
(% per year)
Atmospheric
Lifetime (yr)
C02
carbon dioxide
356(1992)
0.4
> 1
ch4
methane
1.71
0.7 to 1
8-10
CO
carbon monoxide
.12 (NTH) .06 (SH)
1 (NH) 0 (SH)
0.3
N.O
nitrous oxide
0.31
0.2 to 0.3
120
NOx [=NO+N02]
nitrogen oxides
1 to 20x10"5
unknown
<;0.02
CFCIj
CFC-11
2.7x10"
2
50
CF,Cl3
CFC-12
5.0x10^
4
102
C2F3C13
CFC-113
8.0x10'5
6
85
CHjCCij
methyl chloroforai
l.exKr1
4
S
CFjClBr
halon-1211
2.5x10"6
6
20
CFjBr
halon-1301
2.0x10"6
15
65
S03
sulfur dioxide
1 to 20x[ 0'5
unknown
0.02
CjHj, etc.
NMHC/VOC
<1
unknown

03
ozone
.02 to .1
+(trop.) -(strat)

OH
hydroxy]
4 to loo* 1a9
unknown


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TABLE 2: ESTIMATED BUDGET OF CARBON DIOXIDE [2][6][7][9],
Sources of C02	Estimated value and range (PgC per year)
Gross ocean release
105
100-110
Gross release from land
110
40-120
Energy
Fossil fuel use
Wood fuel use
6.2
5.5-6.5
Anthropogenic (non-energy)
Land use conversion
Cement manufacture
1.1
0.15
0.-2.3
0.1-0.2
Sinks ofC02
Gross ocean uptake
107.5
102.5-112.5
Net ocean uptake
2
1.2-2.8
Gross plant uptake
no
40-120
Reservoirs of Carbon
Stock in atmosphere (1988)
745

Ocean surface layer
630
570-690
Intermediate and deep ocean
38,000
34,000-42,000
Ocean sediments
100,000.000

Marine biosphere
2

Terrestrial biosphere
560

Soils
1700

Recoverable fossil fuels
Oil and gas
Coal
Oil Shale
250
8000
40000

2-13

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TABLE 3:
ESTIMATED SOURCES AND SINKS OF METHANE [2][9][15][17].
Sources
Best estimate and range (Tg CH4/yr)
Natural


Enteric fermentation (wild)
4
1-7
Wetlands
115
55-155
Lakes
5
1-25
Tundra
4
2-7
Oceans
10
5-50
Termites and other insects
20
10-50
Methane hydrates
5
0-100
Other
40
0-80
Anthropogenic


Natural gas losses
40
25-50
Coalmining
30
15-60
Petroleum industry
15
5-30
Wood fuel
15
5-30
Landfills
40
20-70
Animal waste
25
20-30
Sewage treatment
25
15-80
Entemic fermentation .(domesticated)
81
65-100
Rice Padies
60
20-100
Biomass Burning
40
20-80
Sinks
Reaction with tropospheric OH
445
330-560
Stratospheric removal
10
5-15
Microorganism uptake in soils
30
15-45
2-14

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TABLE 4: ESTIMATE SOURCES OF THE MAJOR HALOCARBONS IN TG PER YEAR [8).
Gas
Procuduction
(Mid- to late-I980s)
Uses

CFC-11
0.33
Refrigeration and air conditioning
8%


Closed-cell foams
36%


Open-cell foams
19%


Aerosol propellants
31%


Other uses
6%
CFC-12
0.44
Refrigeration and air conditioning
49%


Closed-cell foams
8%


Open-cell foams
5%


Aerosol propellants
32%


Other uses
6%
CFC-113
0.19
Aerosol propellants; cleaning agents
98%


Closed-cell foams; refrigerants; heat transfer
2%
CH3CCI3
0.70
Cleaning agents
100%
HCFC-22
0.20
Blowing agents; aerosol propellant
15%


Refrigeration and air conditioning
85%
TABLE 5: ESTLMA'IED SOURCES AND SINKS OF NITROUS OXIDE [20][29][30][31],
Sources
Estimated value and range (Tg N per year)
Natural


Oceans and estuaries
3.
1-5
Natural soils
4.6
3-8
Aquifers
0.8
0.8-2
Anthropogenic


Fossil fuel combustion
0.5
0-3
Biomass Burning
4.0
2.5-5.7
Cultivated soils and pastures
6.0
2.5-10
Industrial processes
0.5
0-1.8
Addition of nitrogenous fertilkers
1.0
0-2
Sinks
Stratospheric photolysis
12
9-17
Removal in soils
<0.1

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TABLE 6: ESTIMATED SOURCES AND SINKS OF CARBON MONOXIDE [8].
Sources
Estimated value and range (Tg C per year)
Natural


Plant emissions
75
60-160
Oxidation of natural hydrocarbons
250
50-500
Oceans
20
10-100
Oxidation of methane
400
260-500
Anthropogenic


Energy use
400
300-550
Agriculture
110
40-170
Biomass burning
350
300-700
Oxidation of man-made hydrocarbons
40
0-80
Sinks
Reaction with OH
865
500-1200
Soil uptake
250
100-390
TABLE 7: ESTIMATED SOURCES AND SINKS OF REACTIVE NITROGEN (NOx) [43][44][46] [47],
Sources	Estimated value and range (Tg N per year)
Natural
Stratospheric oxidation of N20
1.0
0.5-1.5
Lightning
15
5-25
Soil microbial activity
5
3-8
Oceans
0.15
<1
Anthropogenic
Fossil fuel combustion	24	20-25
Biomass burning	8	3-13
Sinks
Wet and dry deposition	42	25-85
2-16

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TABLE 8: ESTIMATED SOURCES OF ATMOSPHERIC AEROSOLS [ 17].
Sources
Estimated value and range (Tg dry mass)
Natural Primary
Soil dust (mineral aerosol)	1,500
Sea salt	1,300
Volcanic dust	33
primary organic aerosols	50
Natural Secondary (from gaseous precursors)
Biogenic sulfates	90
Volcanic S02	12
Biogenic VOCs	55
Nitrates firom NOx	22
Anthropogenic Primary
Industrial dust	100
Soot	10
Biomass burning	80
Anthropogenic Secondary
Sulfates from S02	140
Nitrates from NOx •	40
Biogenic VOCs	10
1,000-3,000
1,000-10,000
4-10,000
26-80
60-110
4-45
40-200
10-40
40-130
5-25
50-140
120-180
20-50
5-25
2-17

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2-B
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred
C02 EMISSION CALCULATIONS AND TRENDS
Thomas A. Boden and Gregg Marland
Environmental Sciences Division
Oak Ridge National Laboratory
Oak Ridge, Tennessee 37830-6335
Robert J. Andres
Institute of Northern Engineering
School of Engineering
University of Alaska-Fairbanks
Fairbanks, Alaska 99775-5900
ABSTRACT
Tin's paper describes the compilation, calculation, and availability of the most comprehensive
C02 emissions database currently available. The database offers global, regional, and national annual
estimates of C02 emissions resulting from fossil-fuel burning, cement manufacturing, and gas flaring
in oil fields for 1950-92. The methods of Marland and Rotty 11,2] are used to derive estimates from
energy data published by the United Nations and the U.S. Department of Energy and cement
production data published by the U.S. Bureau of Mines. This C02 emissions database is useful for
carbon-cycle research, provides estimates of the rate at which fossil-fuel combustion and cement
production have released CO, to the atmosphere, and offers baseline estimates for those countries
compiling CO, emissioas inventories.
According to these estimates, the annual total of CO, emissions from fossil fuel consumption,
cement production, and gas flaring has grown almost fourfold since 1950. The 1992 estimate of 6097
million metric tons of carbon ends a string of 8 consecutive years of growth in global C02 emissions
and represents a 1.2% decline from 1991. The 1991 estimate of 6172 million metric tons of carbon is
the highest CO,-emission estimate since the data record began in 1950. but it includes 130 million
metric tons of C02 emitted to the atmosphere from the Kuwaiti oil-field fires.
. Regionally, a marked decline in C02 emissions continued in 1992 for Eastern Europe, and
Western Europe experienced its first decline in emissions since 1987-88. However, regions where
populations continue to grow—such as Africa, Centrally Planned Asia, Central and South .America, the
Far East, and Oceania—showed increases in C02 emissions. In 1950, North America, Eastern Europe,
and Western Europe (including Germany) accounted for 89.1% of global CO, emissions from fossil-
fuel burning, cement production, and gas flaring, whereas the remaining six regions—Africa, Central
and South America, Centrally Planned Asia, the Far East, the Middle East, and Oceania—accounted
for only 10.9%. Now these six regions contribute 41.1% of the C02 emitted globally.
Nationally, the United States continued as the largest single source of fossil fuel-related C02
emissions, with 1332 million metric tons of carbon emitted in 1992. The top three emitting
countries—the United States, China, and Russia—were responsible for 43.2% of the world's emissions
from fossil fuel burning in 1992. The top 20 emitting countries accounted for -80% of all the world's
emissions.
2-18

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INTRODUCTION
Evidence that the atmospheric CO, concentration has risen during the past several decades is
irrefutable [3,4,5], Most of the observed increase in atmospheric C02 is believed to result from C02
releases from fossil-fuel burning. The United Nations (UN) Framework Convention on Climate
Change (FCCC), signed in Rio de Janeiro in June 1992 [6], reflects global concern over the increasing
C02 concentration and its potential impact on climate. One of the convention's stated objectives was
(lie "stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent
dangerous anthropogenic interference with the climate system." Specifically, the FCCC asked all 154
signing countries to conduct an inventory of their current greenhouse gas emissions, and it set
nonbinding targets for some countries to control emissions by stabilizing them at 1990 levels by the
year 2000. Given the importance of COj as a greenhouse gas, the relationsliip between C02 emissions
and increases in atmospheric C02 levels, and the potential impacts of a greenhouse gas-induced
climate change; it is important that comprehensive C02 emissions records be compiled, maintained,
updated, and documented.
Keeling [7] was the first to establish a systematic method for estimating the amount of C02
emitted from fossil fuels. Keeling used energy data from the UN Department of International
Economic and Social Affairs. Since 1973, both the energy data collection and the procedures for
estimating CO- emissions have been refined and improved [1,2,8]. The distributions, trends, and
patterns of these fossil-fuel CO, emissions have been studied and described [2,9-11].
Another source of CO, is cement manufacturing. Hydraulic cement, particularly Portland
cement, is the most abundant and widely used type of cement Portland cement is a combination of
two types of raw materials: one rich in calcium, such as limestone, chalk, marl, or clam or oyster
shells; the other rich in silica, such as clay or shale [12], Jn a cement kiln, calcium carbonate (CaC03)
is broken down (calcined) into C02 and calcium oxide (CaO) [13]. The CaO is used in manufacturing
cement and the C02 is released to the atmosphere. Previous studies determined the amount of CO,
emitted during cement manufacturing using data published by the UN or the U.S. Bureau of Mines
17.12], Although the amounts of C02 produced from cement manufacturing are far less (-3% of 1992
global C02 emissions) than those from fossil-fuel consumption, the quantities are large enough to
constitute an important source of C02 emissions.
Another source of C02 is the flaring of natural gas, a practice used in oil fields to eliminate
waste gases and vapors. This practice is used for convenience in oil field operations that lack the
ability to adequately handle and recover natural gas while producing oil, and is used as a mechanism
to quickly eliminate excess gases during unexpected equipment failures or plant emergencies. Like
those from cement production, emissions from gas flaring are far less (-1% of 1992 global CO2
emissions) than those from fossil-fuel consumption. For some nations (e.g., Kuwait and Oman),
however, C02 emissions from gas flaring constitute a sizeable portion of their total C02 emissions',
these emissions were particularly high during the 1960s and 1970s, before the Middle Eastern
countries had the infrastructure and impetus to recover natural gas at their oil fields.
CONTENTS OF THE C02 EMISSIONS DATABASE
Each year, the Carbon Dioxide Information Analysis Center (CDIAC) compiles a time series
of CO, emission estimates using the methods of Marland and Rotty [1,2]. The current database
contains annual C02 emission estimates for the period 1950-92 for the globe, 10 regions, arid about
240 countries. The database also contains the data used in calculating these emission estimates: a
large portion of the 1992 UN Energy Statistics (UNSTAT) Database [8], hydraulic cement production
estimates compiled by the U.S. Department of Interior's Bureau of Mines [14], and supplemental data
on gas flaring obtained from the U.S. Department of Energy's Energy Information Administration
(DOE/EIA). In addition, annual per capita rates of carbon emission are included. These emission
2-19

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rates were calculated using population estimates published by the UN Statistical Division.
DATA SOURCES
The primary database used to estimate the amount of C02 emitted to the atmosphere from
fossil-fuel burning, gas flaring, and cement production is the UNSTAT Database. The UNSTAT
Database is a comprehensive collection of international energy data compiled by the United Nations
Statistical Office.1 This database provides data for primary and secondary forms of energy. The data
are reported for almost every nation in the world and are reported by individual fuel types. The
complete UNSTAT Database also contains data on production, consumption, capacity, reserves, losses,
and trade of heat and power, renewable, and nuclear energy commodities; none of wliich are used for
the calculation of C02 emissions. The complete 1992 version of the UNSTAT Database contains
440,623 records with 3,084,361 data values and requires ~13 megabytes of disk space. The energy
statistics in the UNSTAT Database were compiled primarily from annual questionnaires distributed by
the UN Statistical Office and were supplemented by data in official national statistical publications.
Where official data were not available or were inconsistent, estimates were made by the Statistical
Office based on governmental, professional, or commercial materials. These international statistics are
published annually by the UN in the Energy Statistics Yearbook (originally published as World Energy
Supplies in Selected Years, 1929-1950). There is typically a 2-year lag between the publication of the
yearbook and the last year of data (i.e., the 1994 yearbook provides energy statistics through 1992).
The cement manufacturing data used to estimate emissions from hydraulic cement production
were compiled by the U.S. Department of Interior's Bureau of Mines. The cement production
database is a comprehensive collection of international data from 166 countries. These data, like those
in the UNSTAT Database, are reported on an individual country basis. In cement production, CO, is
released through calcination to the armospherc:
A
CaC03	> CaO + CO,
Because cement manufacturing uses essentially 100% of the calcium oxide obtained from burning the
calcium carbonate, the amount of calcium oxide in the finished cement provides a good measure of the
amount of C02 released during production [12],
Gas-flaring CO, emission estimates are derived primarily from flaring estimates provided in
the UNSTAT Database. The UNSTAT Database has an incomplete time series for many countries
including China, France, Norway, Oman, and Russia and little data before 1970. Gas-flaring estimates
provided by DOE/EIA were used to complete or supplement the flaring time series for these countries,
and the resulting database contains estimates of gas flaring from 57 countries.
DATA PROCESSING AND CHECKING
The C02 emissions database is derived from a variety of sources and requires considerable
data processing, selection, and integration (Figure 1). Each of the data sets used for calculating the
CO2 emission estimates is checked carefully. CDIAC works with the UN Statistical Division annually
to quality-assure each new version of the UNSTAT Database. The review process is unable to detect
some kinds of data problems but confirms that the UNSTAT Database meets high standards of data
management and internal coasistency. The following highlights the quality-assurance checks
performed routinely on the entire UNSTAT Database, not just those data used in the C02 emission
1 The complete UNSTAT Database is available from the United Nations Statistical Division, 2 United Nations
Plaza, New York, NY. 10017.
2-20

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calculations.
Compare the New Database to the Previous Version
The 1992 UNSTAT Database, released in May 1994, was checked against the 1991 version to
identify additions, deletions, and changes. In general, the oldest data (i.e., 1950-69) had no changes,
whereas in the newer data (1970-92), there were many (>1000) differences. This reflects the dynamic
nature of the UNSTAT Database and the constant addition, deletion, and revision of data as new
information is obtained. The dynamic nature of the UNSTAT Database also requires that users of the
C02 emissions database replace previous versions of the database in their entirety, instead of simply
appending the most recent years' emission estimates.
Check for Duplicate Entries
The 1992 UNSTAT Database was sorted by country, year, commodity, transaction code,
quantity, and units in a search for duplicate entries. Duplicate entries were deleted from the database.
Check for Questionable Data
Tne UNSTAT data were examined to identify suspect data. The checks that were performed
identified:
o Inappropriate years (outside of the 1950-92 range)
o Invalid country codes (checked agaiast the UN documentation)
o Invalid transaction codes (certain transaction codes are valid for only some commodities)
o Questionable import/export quantities (in relation to production quantities)
o Inappropriate units
o Improper signs (some transactions can be only positive or only negative)
o Gaps or large changes in quantities between adjacent years for the sar.ie country,
commodity, and transaction
These checks have identified many "suspicious values." Some are clearly errors, whereas most suggest
review by the UN Statistical Division and are referred back to them for consideration. Rarely, and
only in the case of unmistakable errors and with the concurrence of the UN Statistical Division do the
authors purge or change values before calculating the C02 emission estimates. Having performed this
exercise for 7 years, and continually refining the quality-assurance process, we now find few
"suspicious values" during the annual quality-assurance exercise.
C02 EMISSION CALCULATIONS
As indicated earlier, data from the UNSTAT Database were the primary data used to calculate
the C02 emission estimates. Fuel production data were used in generating global C02 emission
estimates because these data are more complete than energy consumption data. For regional or
national emission estimates, however, one needs to know the amount of fossil fuels consumed, and not
2-21

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the amount produced, by an individual country in order to calculate the C02 emitted.
The calculation of C02 emissioas from fossil fuels is conceptually very simple [2]. For each
type of fuel, the annual C02 emissions are the product of three terms: the amount of fuel consumed,
the fraction of the fuel that becomes oxidized, and a factor for the carbon content of the fuel [2], That
is,
CO2i = (P.) (FO-, (Q ,	(1)
where subscript i represents a particular fuel commodity, P represents the amount of fuel i that is
consumed each year, FO is the fraction of P that is oxidized, C is the average carbon content for fuel
/, and CO2 is the resulting C02 emissions for fuel i expressed in mass of carbon. For C02 emissions,
fossil fuels can be divided into the usual groups of solid, liquid, and gas fuels. An identical procedure
has been adopted by the Intergovernmental Panel on Climate Change (IPCC) in prescribing a
methodology for countries to use in estimating and reporting greenhouse gas emissions [15].
Global total C02 emission estimates are generated using the above equation where P represents
production data from the UNSTAT Database for all primary solid, liquid, and gas fuels. Because
secondary fuels are derived from primary fuels, they need not be included.
Trade data are required to calculate regional and national C02 emission estimates. For these
calculations, both primary and secondary fuel data are used. Table 1 lists the UNSTAT primary and
secondary fuels used in these C02 emission calculations. Consumption [i.e., P; in eq. (1)] is the sum
of production and imports less exports, "bunkers", and stock changes. This is what the UN calls
"apparent consumption" as it relies on production and trade data rather than end-use consumption data.
That is,
consumption, = productioni + imports, - exports, - bunkers, - changes in stocks,,	(2)
where i is a primary solid, liquid, or gas fuel. Bunkers refer to fuels consumed by ships and
aircraft engaged in international trade. Stock changes refer to changes in stocks at producers,
importers, and/or industrial consumers from the beginning to the end of each year.
Adjustment is made for the fraction of crude oil converted into non-energy products (e.g.,
lubricants, asphalt, naphthas). National totals for emissions from petroleum products are based on
energy uses only and do not include emissions from the oxidation of nonfuel products while the global
totals do include an estimate of emissions from oxidation of the non-energy products.
Once consumption and production values have been calculated, these estimates are multiplied
by a factor that reflects the fraction of each broad fuel category that is oxidized [i.e., FO in Eq. (1)]
and the average carbon content (C) of each fuel category. Table 2 lists the values and units of P, FO,
and C for each fuel category.
CO-, Emissions from Cement Manufacturing
Because cement manufacturing uses essentially 100% of the calcium oxide obtained from
burning the calcium carbonate during calcination, the amount of calcium oxide content in the finished
cement is a good measure of the amount of C02 released during production [12], To determine the
amount of COu released from cement manufacturing, one needs to know how much cement was
manufactured, the average calcium oxide content per unit of cement, and a factor to convert the
calcium oxide content into carbon dioxide. Cement production data published by the U.S. Bureau of
Mines are currently reported in thousand short tons, but before 1970 the data were reported in barrels.
To ensure consistent units throughout the 1950 -92 record, two equations were used to convert cement
production estimates to units of metric tons. Cement production before 1970 was calculated using:

-------
cement production (in metric tons) = 0.17055 x quantity of cement produced (in barrels) , (3)
where 0,17055 is the metric-ton equivalent for a barrel.
After 1969, net cement production was calculated using:
cement production (in metric tons) = 0.90718474 x quantity of cement produced (in short tons) , (4)
where 0.90718474 is the metric-ton equivalent for a short ton. The amount of C02 produced from
cement production was calculated using:
CO, production (in metric tons of C) = 0.136 metric tons of C per metric ton cement
x quantity of cement produced (metric tons)	(5)
This conversion factor was obtained by dividing the molar mass of carbon by the molar mass of
calcium oxide and multiplying this quotient by the average fraction of calcium oxide contained in
cement:
(12.01 g C/mole CaC03 -r 56.08 g CaO/mole CaC03) x 0.635 g CaO/g cement = 0.136 g C/g cement (6)
The consensus that 63.5% of the typical cemer.t in the world is composed of calcium oxide is based on the
opinions of experts consulted in the field, as well as inspection of composition data by type and country [12].
Per Capita CO-. Emission Rates
Using the UN population data, the authors estimate per capita C02 emission rates for individual
countries using the equation:
national per capita C02 emission ¦ year'1 - total national C02 emission estimate. ¦ year
-r national population	(7)
The resulting pier capita estimates are expressed in metric tons of carbon • person1 ¦ year"1.
TRENDS IN C02 EMISSIONS
According to these estimates, the global total of CO, emissions from fossil-fuel consumption,
cement production, and gas flaring has grown almost fourfold since 1950 (Table 3 and Figure 2). The
1992 estimate of 6097 million metric tons of carbon ends a string of 8 consecutive years of growth in
global C02 emissions and represents a 1.2% decline from 1991. The 1991 estimate of 6172 million
metric tons of carbon is the highest Commission estimate since the data record began in 1950, but it
includes 130 million metric tons of COa emitted to the atmosphere from the Kuwaiti oil-field fires.
Globally, liquid and solid fuels accounted for 19% of the emissions from fossil-fuel burning in
1992. Combustion of gas fuels (i.e., natural gas) accounted for -17% (1045 million metric tons C) of
total emissions from fossil fuels in 1992 and reflects a gradually increasing global utilization of natural
gas. Emissions from cement production increased slightly and now account for -3% of total
emissions. Emissions from gas flaring declined 10.5% from 1991 to 1992 to 68 million metric tons C
(just 1% of the global total) and remain well below the levels of llie 1970s. This trend for gas flaring
is not fully clear because of uncertainty about the gas-flaring data for Russia.
Regionally, Eastern Europe continued to have a marked decline in CO^ emissions, North
American emissions increased 1.3% during 1992 after 2 successive years of declining emissions, and
2-23

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Western Europe experienced its first decline since 1987-88 (Figure 3). However, regions where
populations continue to grow—such as Africa, Centrally Planned Asia, Central and South America, the
Far East, and Oceania—showed increases in C07 emissions (Figure 4). In 1950, North America,
Eastern Europe, and Western Europe (including Germany) accounted for 89.1% of global C02
emissions from fossil-fuel burning, cement production, and gas flaring, whereas the remaining six
regions accounted for only 10.9%. Now these six regions—Africa, Central and South America,
Centrally Planned Asia, the Far East, the Middle East, and Oceania—contribute 41.1% of the C02
emitted globally.
The top 20 emitting countries accounted for -80% of all the 1992 world CO2 emissions from
fossil-fuel consumption (Figure 5). The top three countries—the United States, China, and
Russia—were responsible for 43.2% of the world's emissions from fossil fuel burning in 1992. Spain,
the 20th-highest C02-emitting nation, contributed slightly less than 1% to this total. The United States
continued as the largest single source of fossil fuel-related C02 emissions, with 1332 million metric
tons of carbon emitted in 1992. In fact, U.S. emissions are ~45% higher than those of the world's
second largest emitter, China. U.S. emissions in 1992 were nearly twice those of 1950, although the
U.S. share of global emissions declined from 44% to 23% over the same interval because of higher
growth rates in other countries.
LIMITATIONS
Marland and Rotty [2] estimated that the uncertainty on the annual global C02 emission
estimates derived from the United Nations' energy data was -6-10%. The reliability of the C02
estimates presented here is bounded by the accuracy and completeness of the values reported by each
country to the UN Statistical Office. The values published by the UN are consistent with numbers
published elsewhere and represent the best efforts of a staff dedicated to the sole task of bringing
together all the available global energy information. It is not possible to independently verify each
number reported by individual countries to the UN. When incoasistencics arise in the official data, the
UN Statistical Office makes its own estimates based on governmental, professional, or commercial
materials.
C02 emission estimates for some individual countries and regions are less reliable than the
global C02 emission estimates. Global totals depend on only production data with some representation
of fuel chemistry and fractioas of fuels that are oxidized. Regional and national data rely further on
information for additional transactions (e.g.. refinery product mix by country, imports, exports, bunker
loadings). For some countries, it is difficult for die UN to obtain sufficient production, consumption,
and trade data. Also, even though the authors account for all of these mass transfers, we do not
attempt to deal with the different carbon content of various products.
The sum of the C02 emissions for all of the individual countries for a given year, as reported
here, will not equal the global total. There are 3 primary reasons for this. First, the national data rely
on internal data on imports and exports and the reported total (over all countries) of exports does not
exactly equal the reported total for imports. Also, we have used different treatment of nonfuel and
bunker fuel uses in the global and national calculations. Nonfuel uses and bunker fuel usage are
accounted for in the production data used for the global calculations, but are not included in national
estimates. The difference between the sum of the individual countries and the global estimates is
generally less than 5%.
2-24

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AVAILABILITY OF THE C02 EMISSIONS DATABASE
The C02 emission estimates and underlying data are available in machine-readable form, upon
request, from CDIAC without charge. CDIAC will also distribute subsets of the database as needed.
This database may be acquired from CDIAC's anonymous File Transfer Protocol (FTP) area (see FTP
access instructions below), or may be requested on 9-track or 8-mm magnetic tape, or on IBM- or
Mac-formatted floppy diskettes. Requests for 9-track magnetic tapes should include preferred tape
specifications (i.e., 1600 or 6250 BPI, labelled or nonlabellcd, ASCII or EBCDIC character, variable-
or fixed-record lengths). Requests should be addressed to:
Carbon Dioxide Information Analysis Center
World Data Center—A for Atmospheric Trace Gases
Oak Ridge National Laboratory
Post Office Box 2008
Oak Ridge, TN 37830-6335, U.S.A.
Tapes, diskettes, and documentation may also be ordered by telephone, facsimile, or electronic
mail:
Telephone: (423) 574-3645 or (423) 241-4842
Fax: (423) 574-2232
Electronic mail: cdiac@ornl.gov
CDIAC home page on the World Wide Web: http://cdiac.esd.orni.gov/cdiac
The following are FFP access instructions.
FTP access: ftp cdiac.esd.oml.gov (or 128.219.24.36)
Enter "anonymous" as the userid.
Enter your electronic-mail address as the password (e.g., "tab<®ornl.gov").
Change to the directory "/pub/ndp030r6".
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REFERENCES
1.	Marland, G., and R. M. Rotty. 1983. Carbon Dioxide Emissions from Fossil Fuels: A Procedure
for Estimation and Results for 1950-1981, DOE/NBB-0036 TR-003. Carbon Dioxide Research
Division, Office of Energy Research, U.S. Department of Energy, Washington, D.C., U.S.A.
2.	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):232-61.
3.	Keeling, C. D., R. B. Bacastow, A. F. Carter, S. C. Piper, T. P. Whorf, M. Heimann, W. G. Mook,
and H. Rocloffzcn. 1989. A three-dimensional model of atmospheric C02 transport based on
observed winds: 1. Analysis of observational data. In D. H. Peterson (ed.), Aspects of
Climate Variability in the Pacific and Western Americas. Geophysical Monograph
55:165-235.
4.	Keeling, C.D., and T. P. Whorf. 1994, Atmospheric CO, records from sites in the SIO air
sampling network, pp. 16-26, In T. A. Boden, D. P. Kaiser, R. J. Scpanski, and F. W. Stoss
(eds.), Trends '93: A Compendium of Data on Global Change. ORNL/CDIAC-65. Carbon
Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tenn.,
U.S.A.
5.	Conway, T. J., P. P. Tans, L. S. Waterman, K. W. Thoning, D. R. Kitzis, K. A. Masarie, and
N. Zhang. 1994. Evidence for inlenuinual variability of the carbon cycle from the National
Oceanic and Atmospheric Administration/Climate Monitoring and Diagnostics Laboratory
Global Air Sampling Network. Journal of Geophysical Research 99:22831-55.
6.	United Nations. 1992. United Nations Framework Convention on Climate Change. United
Natloas, New York, U.S.A.
7.	Keeling, C. D. 1973. Industrial production of carbon dioxide from fossil fuels and limestone.
Tellus 25:174-98.
8.	United Nations. 1994. 1992 Energy Statistics Yearbook. United Nations Statistical Division,
New York, U.S.A.
9.	Marland, G., and T. Boden. 1993. The magnitude and distribution of fossil-fuel-related carbon
releases, pp. 117-38. In M. Heimann (ed.), The Global Carbon Cycle. Springer-Verlag,
Berlin Heidelberg, Germany.
10.	Marland. G., R. J. Andres, and T. Boden. 1994a. Magnitude and trends of CO, emissions.
pp. 215-26. In C. V. Mathai and G. Stensland (eds.), Global Climate Change Science,
Policy, and Mitigation Strategies, Proceedings of the Air & Waste Management
Association International Specialty Conference, Phoenix, Adz., U.S.A., April 5-8, 1994.
11.	Marland, G., R. J. Andres, and T. Boden. 1994b. Global, regional, and national CO, emissions.
pp. 505-84. In T. A. Boden, D. P. Kaiser, R. J. Sepanski, and F. W. Stoss (eds.).
Trends '93: A Compendium of Data on Global Change. ORNL/CDIAC-65. Carbon
Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge,
Tenn., U.S.A.
2-26

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12.	Griffin, R. C. 1987. C02 release from cement production 1950-1986. Institute for Energy
Analysis, Oak Ridge Associated Universities, Oak Ridge, Tenn., U.S.A.
13.	Helmuth, R. A., F. M. Miiler, T. R. O'Connor, and N. R. Greening. 1979. Encyclopedia of
Chemical Technology, pp. 163-93, Vol. 5. John Wiley and Sons, New York.
14.	Solomon, C. S. 1993. Cement. In Cement Minerals Yearbook-!992. U.S. Department of
Interior, Bureau of Mines. Washington, D.C., U.S.A.
15.	IPCC. 1995. IPCC Guidelines for National Greenhouse Gas Inventories. Vols. 1-3. IPCC.
Bracknell, United Kingdom.
2-27

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TABLES
TABLE 1. LISTING OF THE PRIMARY AND SECONDARY FUELS FROM THE UNITED
NATIONS ENERGY STATISTICS DATABASE USED IN CALCULATING C02 EMISSION
ESTIMATES. THE TWO-LETTER COMMODITY CODE USED BY THE UNITED
NATIONS FOR EACH FUEL TYPE IS SHOWN IN PARENTHESES.
Gas Fuels
Primary gas fuels
Natural gas (NG)
Liquid Fuels
Primary liquid fuels
Crude petroleum (CR)
Natural gas liquids (GL)
Solid Fuels
Primary solid fuels
Coal (CL)
Lignite/brown coal (LB)
Oil shale (OS)
Peat (PT)
Secondary gas fuels
Gasworks gas (GG)
Coke-oven gas (OG)
Refiner,' gas (RG)
Secondary liquid fuels
Aviation gasoline (AV)
Plant condensate (CD)
Gas-diesel oils (DL)
Feedstocks (FS)
Jet fuel (JF)
Kerosene (KR)
Liquefied petroleum gas (LP)
Motor gasoline (MO)
Natural gasoline (NT)
Residual fuel oils (RF)
Secondary nonenergy liquid fuels
Bitumen/asphalt (BT)
Lubricants (LU)
Naphthas (NP)
Petroleum coke (PK)
Other petroleum products (PP)
Petroleum waxes (PW)
White spirit/industrial spirit (WS)
Secondary solid fuels
Lignite (brown coal) briquettes (BB)
Hard coal (patent fuel) briquettes (BC)
Brown coal coke (BK)
Peat briquettes (BP)
Gas coke (GK)

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TABLE 2. FACTORS AND UNITS FOR CALCULATING C02 EMISSIONS FROM FUEL
PRODUCTION AND TRADE DATA [C02, = (P) (FO,) (C,)]
From primary and secondary gas fuel production and trade1
C02s = C02 emissions in 104 metric tons of carbon
P, = annual production or consumption in thousands of 1012 joules
FO, = 0.9 B + 1%
Ct = carbon content in 106 tons per thousand 10n joules = 0.0137 + 2%
From crude oil and natural gas liquids production1
COjj = C02 emissions in 106 metric tons of carbon
P, = annual production or consumption in 106 tons
FO, = 0.918 + 3%
C, = carbon content in tons C per ton fuel = 0.85 + 1%
From primary and secondary liquid fuel production and trade3
COa = C02 emissions in 106 metric tons of carbon
Pi = annual production or consumption in 106 tons
FO, = 0.985 ±3%
C, = carbon content in tons C per ton fuel = 0.85 + 1%
From liquid bunker fuel consumption*
COa = CO, emissions in 106 metric tons of carbon
P( = annual production or consumption in \(f tons
FO, = 1.0 + 3%
C, = carbon content in tons C per ton fuel = 0.855 + 1%
From primary and secondary solid fuel production and trades
COj, = C02 emissions in I06 metric tons of carbon
P, = annual production or consumption in 10s tons coal equivalent5
FO, = 0.982 + 2%
C, = carbon content in tons C per ton coal equivalent = 0.746 + 2%
From natural gas flaring7
CO-, = C02 emissions in 106 metric tons of carbon
Pf = annual production or consumption in 1012 joules
FOf = 1.0+1%
C, = carbon content in tons C per 10n joules = 13.454 + 2%
1 With respect to the above gas-related calculations, the following procedures and assumptions should be noted:
(1)	1/ a solid was produced and then converted to a gas that was subsequently consumed, the assumption was made thai the solid was
produced and consumed, in this situation, none of the gas records were influenced.
(2)	If a solid was produced and then converted to a gas thai was exported, it was assumed that in the producing country a solid was
produced and the gas was exported. As a result, gas consumption for this country could show a negative value (consumption =
production •+ imports - exports: C = <0 + 0) -exports). In the consuming country. gas was imported and consumed.
(3)	An amount of gas equivalent to 98% of the marketed production (net production) was oxidized during a given year.
(4)	Natural gas contains 13.7 metric tons of carbon per lerajoule.
(5)	The units seem contrived but are chosen to accomodate data reported in the primary data sources.
" With respect to the above global liquid-related calculations, the following procedures and assumptions should be noted:
(1)	Crude petroleum, natural gas liquids, and all secondary energy liquids were summed on an equal basia in units. That is, a ton
of any liquid contains the same fraction of carbon.
(2)	When calculating global total C02 emissions from liquids, we have estimated that a quantity of liquids equivalent to 6.7% of liquids
produced are not oxidized each year and another 1,5% passes through burners unoxidized or is otherwise spilled. Hence, 91.8% of
annual liquid production is oxidized each year.
(3)	Liquid fuels contain 85.0% carbon by weight
2-29

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3	With respect to the above national liquid-related calculations, the following procedures and assumptions should be noted:
(1)	Cnide petroleum, natural gas liquids, and all secondary energy liquid] were summed on an equal basis in mass units. That is, a ton
of any liquid coo tains the same fraction of carbon.
(2)	When calculating C02 emissions by country, nonenergy secondary liquids were subtracted at the time of production and additional
transactions (i.e.. imports, exports, changes in stock) were not accounted further. Therefore. COj production is only for energy products
and CO, production from the oxidatioo of nonenergy products is not included.
(3)	When calculating national total COi emissions from liquids, we have estimated that a quantity of liquids equivalent to
1.5% passes through burners unoxidized or is othr.rwi.se spilled.
(4)	Liquid fuels contain 85.0% carbon by weight.
4	With respect to the above bunker liquid-related calculations, the following procedures and assumptions should be noted:
(1)	Crude petroleum, natural gas liquids, and all secondary energy liquids were summed on an equal basis in mass units. That is, a ton
of any liquid contains the same fraction of catbon.
(2)	When calculating national total C02 emissions from liquids, we have estimated that a quantity of liquids equivalent to 1.5% passes
through burners ur-.oxidized or is otherwise spilled.
(3)	Liquid bunker fuels contain 85.5% carbon by weight.
(4)	Emissions from bunker fuels are calculated at the point where final fuel loading occurs but are not included in any national totals.
5	With respect to the above solid-related calculations, the following conversion assumption should be noted:
(1) Where no conversion factor exists in the UN data set for a country/commodity, the following standard factors (kcal/kg) are used:
Coal	7000
Lignite brown coal	2695
Peat	2275
Coke-oven coke	6300
Gas coke	6300
Brown coal coke	4690
Hard coal briqueces	7000
Brown coal briquettes	4690
6	The data for annual fuel production must recognize that all coal is not of the same composition, and thus may have varying energy conUnt
and COj potential. There is a strong correlation between energy content and C content so the C content is quite constant when production is
in units of tons coal equivalent where 1 ton coal equivalent is defined as 29.31 X 10s joules.
7	With respect to tbc above gas flaring-related calculations, the following derivation and assumption should be noted;
(1)	The carbon conversion factor of 13.454 metric tons of C TJ"' is the result of dividing the average carbon content of a cubic meter of
flared natural gas (i.a, 525 g C/in1) by the average heating value of a cubic meter of flared natural gas (i.e., 39.021 Tl/IO' m').
(2)	These calculations assume that flared gas is released lo the atmosphere immediately as CO,, even though it is known that a small
fraction is actually discharged as methane.
2-30

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TABLE 3. GLOBAL ANNUAL C02 EMISSIONS FROM FOSSIL-FUEL BURNING, GAS
FLARING, AND CEMENT PRODUCTION FOR 1950-92
Carbon dioxide emissions (million metric tons of carbon)	Per capita
C02 emissions
Gas (metric tons
Year	Total	Solid	Liquid	Gas	Cement flaring of carbon)
1950
1638
1077
423
97
18
23
0.65
1951
1775
1137
479
115
20
24
0.69
1952
1803
1127
504
124
22
26
0.69
1953
1848
1132
533
131
24
27
0.70
1954
1871
1123
557
138
27
27
0.69
1955
2050
1215
625
150
30
31
0.74
1956
2185
1281
679
161
32
32
0.78
1957
2278
1317
714
178
34
35
0.80
1958
2338
1344
732
192
36
35
0.80
1959
2471
1390
790
214
40
36
0.83
1960
2586
1419
850
235
43
39
0.86
1961
2602
1356
905
254
45
42
0.85
1962
2708
1358
981
277
49
44
0.86
1963
2855
1404
1053
300
51
47
0.89
1964
3016
1442
1138
328
57
51
0.92
1965
3154
1468
1221
351
59
55
0.95
1966
3314
1485
1325
380
63
60
0.97
1967
3420
• 1455
1424
410
65
66
0.98
1968
3596
1456
1552
445
70
73
1.01
1969
3809
1494
1674
487
74
80
1.05
1970
4084
1564
1838
516
78
87
1.10
1971
4235
1564
1946
554
84
88
1.12
1972
4403
1580
2055
583
89
94
1.14
1973
4641
1588
2240
608
95
110
1.18
1974
4649
1585
2244
618
96
107
1.16
1975
4622
1679
2131
623
95
93
1.13
1976
4889
1717
2313
647
103
109
1.18
1977
5028
1780
2389
646
108
104
1.19
1978
5076
1796
2383
674
116
107
1.18
1979
5358
1892
2534
714
119
100
1.23
1980
5290
1949
2407
726
120
89
1.19
1981
5119
1920
2271
736
121
72
1.13
1982
5080
1983
2176
731
121
69
1.10
1983
5070
1989
2161
733
125
63
1.08
1984
5242
2081
2185
791
128
58
1.10
1985
5417
' 2238
2170
822
131
57
1.12
1986
5609
2299
2279
840
137
54
1.14
1987
5736
2350
2289
903
143
51
1.14
1988
5961
2412
2393
946
152
58
1.17
1989
6070
2447
2429
982
156
56
1.17
1990
6099
2389
2431
1008
156
65
1.15
1991
6172
2320
2587
1028
162
76
1.15
1992
6097
2344
2470
1045
171
68
1.12
2-31

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FIGURES
Convert to
energy units
UN
Energy
Statistics
KS-T71}
Solids
Energy
Statistics
OA
Steps
Liquids
Gases
[Extract Production
[and Trade Data
f F
Solids
FF
Liquids
Calculate Net Cons,
ind Net Prod.
Jarbon Conten
% Oxidized
FF
Solids -
Define
[Regions
. FF . j
Liquids
(l^ass)'
Final
Database, .
FF *
Gases
(Energy)
Assign
[Nations
National & Regional
CO2 Emissions
Global
CO2 Emissions
FIGURE 1. DATA PROCESSING AND SELECTION OF THE UNITED NATIONS
ENERGY STATISTICS DATABASE (FF DENOTES FOSSIL FUELS)
2-32

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6400-
Solids 	 .—-

M
-
Liquids 	 /
Gases • — • — • /

U
cS
4800 -
Flaring 	
Cement 	 /

cj
V-.
o

Total 	 /

Ti
C

/

o
3200 -


'u
V
S




'—¦' —:'*•

C
S
1600-
^ 	
-	 	

s




u i ¦ i r i ' i t i
1950 19G0 1970 1980 1990
J
2000


Year

FIGURE 2. GLOBAL C02 EMISSIONS FROM FOSSIL FUEL BURNING, CEMENT
PRODUCTION, AND GAS FLARING FOR 1950-92.
Year
FIGURE 3. REGIONAL C02 EMISSIONS FROM FOSSIL FUEL BURNING, CEMENT
PRODUCTION, AND GAS FLARING FOR 1950-92 FOR NORTH AMERICA, EASTERN
EUROPE, AND WESTERN EUROPE.	2-"? 3

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900 -i
Centrally Planned Asia
O
tn
G
o
£-
CJ

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'I he work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the vievss of the Agency and no official endorsement should be inferred.
RICE AGRICULTURE: AN IMPORTANT SOURCE
OF ATMOSPHERIC METHANE
M.A.K. Khalii., M.J. Shearer and R.A. Rasmussen
Global Change Research Center
and
Department of Environmental Science & Engineering
Oregon Graduate Institute
P.O.Box 91,000
Portland, Oregon 97291 USA
ABSTRACT
In all the global budgets of atmospheric methane, emissions from rice agriculture have been
among the largest single sources. Early estimates were as high as 300 Tg/yr but upon careful
examination of the data', the estimates were reduced to about 100 Tg/yr. In time as direct
flux measurements became available and it was found that there was considerable variability
in the whole season emissions of methane from different types of rice fields. The global
estimates now are even lower at about 60 Tg/yr. Even so, rice fields constitute a major
source of methane. The emissions of methane from rice fields may have been higher at
some earlier time in recent decades than they are now. Because of limitation of land readily
adaptable to rice agriculture, the use of inorganic fertilizers and the short growing cycles
of recent hybrid varieties, future emissions may not increase greatly.
INTRODUCTION
The sources of methane are the most complex and critical element in understanding the
concentrations and trends of atmospheric methane. There are three major sources (>50
Tg/yr; Tg = 1012 g), all biogenic, namely rice agriculture, ruminants (particularly cattle) and
other animals, and the natural wetlands. There is a larger number of moderate sources that
individually appear to be less than ten percent of the total annual emissions (10-50 Tg/yr)
but collectively are a significant fraction of the global budget. These sources include
landfills, coal mines, biomass burning, urban areas, sewage disposal, natural gas leakages,
lakes, oceans, and tundra. Finally there are yet smaller minor sources, including biogas pits,
asphalt, several industrial sources, and possibly many others that have not yet been identified
< 5 Tg/yr). The very small sources are thought to be a small fraction of the annual
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The contents do
not necessarily reflect the views of the Agency and no official endorsement should be inferred.

-------
emissions even when taken together. There is still enough uncertainty in the estimates of
emission rates from individual sources that some may go from moderate to major or vice
versa, but it is very unlikely that there are any unknown major sources. Two recent global
budgets of methane are compared in Table 1.
There are several constraints that work at different levels of the global budget of methane.
For the total emission rates from all sources, there is a constraint imposed by the global
mass balance:
S - dC/dt - C/r	(1)
Here, S (Tg/yr) are the global emissions, r is the average atmospheric lifetime (years) (see
Khalil and Shearer, 1993), and C is the global burden (Tg). dC/dt and C can be determined
quite accurately from atmospheric measurements. The atmospheric lifetime is dominated
by reaction with tropospheric OH, with lesser Temoval by soils and other chemical processes
in the stratosphere.
Long-term changes of the sources tell us which sources have contributed to the doubling of
methane over the past century and indeed whether it is the sources that have caused most
of the global increases of methane or the change of the lifetime in Eqn 1. The probable
changes of emissions from the major sources over the past 100 years can be evaluated based
on available geographical and agricultural data (Chappellaz et al., 1993; Kammen and
Marino, 1993; Shearer and Khalil, 1993). From the turn of the century to the present, cattle
populations increased by a factor of almost 3 and area of rice harvested increased by a
factor or 2. These agricultural sources represent a large role of human activities on the
global methane cycle (see Khalil and Shearer 1993 for details). The increases are so large
that they are bound to have a significant effect on the emissions and hence the atmospheric
concentrations. For example, we estimate that rice agriculture contributes some 330 ppbv
to the present atmospheric burden of CH4 in the atmosphere, and may be responsible for
some 20-30% of the increase of methane during the last century (Khalil and Rasmussen,
1991). The growth of these and other sources suggests that the major increases of methane
over the past 100 to 300 years have been caused by increasing emissions as opposed to being
caused by decreasing OH (see Khalil and Shearer, 1993). It is interesting that the major
sources such as rice fields and cattle have not increased much over the last decade -
certainly not comparable to the rapid rates of increase in the 1950s. This slowdown of
major sources may be affecting atmospheric trends, which also show a deceleration (Khalil
and Rasmussen, 1990, 1993; Steele et al., 1992).
Recent global budgets of methane have generally included emissions of about 100 Tg/yr
from rice agriculture (with a range of 50-300 Tg/yr), constituting about 20% of emissions
from all sources (range 14%-40%) (see Shearer and Khalil, 1993, for a review). We will
examine the emissions from rice fields in more detail in the remainder of this paper.
METHANE EMISSIONS RATES FROM RICE FIELDS
Estimating the flux of methane from rice fields in various parts of the world requires
2-36

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knowledge of two factors: the emission rates and the regional or global extrapolant. The
emission rate or flux depends on different internal and external variables fa). Internal
variables include: soil characteristics; rice variety; and soil microbiology. External factors
include: soil temperature driven by solar radiation; meteorological conditions; water level,
which is affected by rainfall and availability of irrigation; and treatments such as the type
and amount of fertilizers applied. The global flux, FG, is usually calculated by equation (2):
= ^
R
where 0R (g/m2/day) is the measured, seasonally averaged emission rate from a region R;
Ar (m2) is the area of the region, presumably with similar characteristics, so that r. Usually, AR and TR are determined from agricultural statistics and are relatively well
known. Problems with the extrapolation arise in associating a measured flux with an
appropriate area and growing season and in the assumption that the measured flux is
representative of the associated area and season.
This empirical approach requires whole season measurements of CH4 emission rates from
as many regions as possible so that the large variations of emissions from one region to
another can be properly included in the estimate of global or regional emissions.
Alternative approaches to global extrapolation also exist and are based on the knowledge
of the processes or factors that control emission rates. At present there are insufficient data
for such approaches to produce reliable estimates of global or regional emissions.
Flux Measurements.
During the last decade a number of systematic experiments have been reported on methane
emissions from rice fields. Most are based on static chamber methods. While there are
many variants, the method consists of enclosing a small part (0.1 - 100 m2) of the rice fields
within a chamber and taking periodic samples. The samples are analyzed for methane
content usually by gas chromatography using flame ionization detectors (GC/FID).
Methane, emitted from the enclosed area of the rice field, builds up in the chamber. The
rate of accumulation is directly proportional to the flux or the rate of emission from the
area covered by the chamber. The relationship is:
(f) = P. ¥ V. X 10 6	(3)
NA A	dt
where (f> is the flux, p is the density of air (molecules/m3), M is the molecular weight of CH4,
2-37

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V is the volume of the chamber (m3), A is the area covered by the chamber (m2), NAis
Avogadro's number, C is the concentration of methane (ppbv) and dC/dt is in (ppbv/hr).
The most common units for reporting fluxes are mg/m2/hr.
In recent years experiments have been designed to measure the flux throughout the growing
season. The earliest experiments of this type made it clear that there are large systematic
changes in methane emissions during the growing cycle. Such changes are driven by several
factors including the growlh of root mass, maturation process for the plants, availability of
nutrients and fertilization, and the seasonal change of temperature and length of day (Schiitz
et al., 1989; Yagi and Minami, 1990; Khalil et al., 1991).
Direct flux measurements are summarized in Table 2 with a description of the nature of the
experiments. These studies were originally designed to quantify the methane produced by
rice paddies; later, to establish which factors affect methane emissions; and most recently,
to investigate treatments which may reduce methane emissions. This table represents a
summary of all the direct measurements that have been reported in the scientific literature
(of which we are aware). The table contains most of the fundamental information that we
have put into Eqn 2. to estimate regional and global fluxes.
Methodology for estimating emissions
The flux of CH4 from rice fields is usually calculated by estimating the length of the season
of methane emission, the area in rice (wetland), and the seasonal average flux of methane
(mg/m2/hr) (see Equation 2). Each of these main variables is discussed separately
Season Length. The estimate of the season length from the literature may be confused by
whether "season" refers to the season of methane emission, the rice growing season (planting
or transplanting to harvest), the total growing season (the frost free period), or the total
growing period, which in the case of transplanted rice includes the time in the seedling beds.
For the estimates here, the growing seasons in Matthevys et al. (1991) were modified as
follows: growing seasons of 140 to 170 days were reduced by 30 days; growing seasons of 110
to 140 days were reduced by 20 days; and growing seasons of fewer than 110 days were
reduced by 10 days. This adjustment was made to better reflect results of the field
measurements for the period of methane emissions shown in Table 2, and models the period
the rice field was actually flooded and emitting methane.
Methane flax factors. Ideally, each rice growing region should have an average methane flux
factor associated with it which uniquely reflects the soil, climate and cultivation practices of
the area. Practically, estimators must rely on the information that is available and their best
judgement to apply measured fluxes from one region to another where data are not
available. We used averaged fluxes from the studies listed in Table 2 for the major seasonal
divisions of Chinese and Indian rice, for other countries where fluxes have been measured,
and to estimate fluxes for other rice growing countries. Flux rates were reduced by 40% for
areas of rainfed rice, approximately the reduction in flux found by Sass et al. (1992) and
Chen et al. (1993) for their intermittent irrigation regimes.
2-38

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Area planted to rice. Estimates of rice growing area are usually taken from published
agricultural statistics supplied by the United Nations, the International Rice Research
Institute, or the agricultural agencies of individual countries (see, for example: U.N. Food
and Agriculture Organization [FAO] Yearbook; International Rice Research Institute
[IRRI] Yearbook; China Agricultural Yearbook).
We calculated the fraction of the total areas in each province in China and state in India
by taking the average of the areas reported in Matthews et al. (1991), the China Agriculture
Yearbooks (all years), and in Bansil (1984). Since methane is only produced under
anaerobic conditions caused by flooded irrigation, the total areas for each country were
reduced by the percentage of dryland (upland) rice grown. Estimates of the percentages
were taken from tables in De Datta (1975), Huke (1982), Morris et al. (1984), and Grist
(1986). Where there was more than one estimate per country, an average was taken. If
there was no estimate for a particular countiy but there was reason to suppose a significant
percentage of the rice area was in upland rice, as for example in Africa or Central America,
an average was taken of the published estimates for neighboring countries, or the average
for the continent was used (usually for African nations). Areas of rainfed rice, assumed to
have lower fluxes due to intermittent drying, were estimated in the same manner.
REGIONAL AND GLOBAL EMISSIONS OF METHANE FROM RICE
AGRICULTURE
Recent estimates of the global source range from 50 to 100 Tg (1012 grams) per year.
Source estimates by country vary greatly with the assumptions made on the importance of
different factors affecting the methane flux, and the information on the factors currently
available.
Global Emissions. Three recent estimates of the global source of CH, from rice agriculture
are shown in Table 3. (Matthews et al. (1991) assumed a global source of 100 Tg.). The
major difference between these estimates is probably in the way a weighted average flux rate
is calculated. The estimate here takes a seasonally averaged flux, based on the field studies
shown in Table 2, and applies it to the seasonal area in wetland rice culture. The Aselmann
and Crutzen (1989) estimate used temperature adjusted fluxes. The IPCC/OECD estimate
uses the early and late growing season fluxes measured by Schutz et al. (1990) in Hangzhou,
PRC. to calculate a range of global emissions (these methods have since been revised, see
Wassmann et al., 1994).
Regional emissions. Estimates of methane emission by country are shown in Table 4,
comparing the countries of South and East Asia by 4 estimation techniques. These
countries produce about 90% of the estimated CH4 from rice agriculture. The. countries
with the largest methane source from wetland rice paddies are all in Asia. The estimates
from this work, OECD/IPCC, and Matthews et al. are described above. Bachelet and Neue
(1993) calculated a range of 40 to 80 Tg/yr as the rice source for South and East Asia,
making different assumptions about the effects of soil type, rice yield, temperature, and
organic matter incorporated in the soil.
2-39

-------
SUMMARY AND CONCLUSIONS
The anthropogenic sources such as rice agriculture increase or decrease according to
complex economic, social, and technological factors, which make it difficult or perhaps
impossible to predict future emissions. Generally, sources such as rice fields and cattle are
related to human population since a larger population requires more food. This is not the
only connection, however, since emissions are also related to "per capita" demand for the
commodity. The emissions are a product of the per capita emission rate and the population,
but both the per capita emission rate and population change in time. It is likely that
population increases are more predictable than the per capita demand. For instance, if
people are generally undernourished, there would be a demand to grow more rice even if
the population is not increasing. After a certain point, however, as people become richer,
the per capita demand for rice may decline as other foods are substituted. The shifting
nature of the connection between population and agricultural emissions makes population
an unreliable predictor of the future even if it works well to explain the past. For instance,
rice fields and cattle rose steadily in the past, keeping pace with population. During the past
decade, the hectares of rice harvested and the number of cattle are no longer increasing
significantly compared to the previous decade, and yet the population is continuing to rise
at close to the same rates as a decade ago, thus breaking the link between population and
methane emissions. Future emissions from rice agriculture will depend on efforts to
increase production without increasing the area planted, particularly through fertilization,
irrigation and planting high productivity cultivars.
Global estimates of methane emission from rice agriculture are derived by summing up
regional estimates, which are calculated by multiplying flux, area and seasonal factors. Any
part of the equation may introduce uncertainty. TTiere is no way to assess whether a
seasonal average flux measurement is correctly associated with area and growing season
extrapolants, since seasonal fluxes can vary widely even in nearby areas. Global estimates
from three different sources have good general agreement on the latitudinal emissions from
rice agriculture. When the regions of interest are individual countries, different assumptions
lead to a much larger disagreements.
ACKNOWLEDGEMENTS
We thank R.Dalluge and D.Stearns for field and laboratory work. This project was
supported in part by a grant from the Department of Energy (DE-FG06-85ER6031); some
portions were supported.by a sub- contract from ICF to Andarz Co. on EPA # 75-110-01
and additional support was provided by the Biospherics Research Corp. The authors, not
the sponsors, are solely responsible for the opinions and conclusions expressed in this paper.
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2-40

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2-43

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Table 1. Estimates of methane emissions from various sources described in two recent global budgets.
Source
NATO-ARW1 Budget
IPCC2 Budget

Methane (Tg)
Methane (Tg)
Natural Sources


Wetlands
110
115 (100 - 200)
Termites
20 (15 - 35)
40 (10 - 100)
Open oceau
4
10 (5 - 20)
Marine sediments
~* (8 - 65)

Geological
10 (1 - 13)

Wfld fire
5 (2 ¦ 5)

Freshwaters

5 (1 - 25)
CH4 Hydrate Destabilization

5 (0 - 100)
Total
150*
175
Anthropogenic Sources


Rice
65 (55 - 90)
110 (25 - 170)
Animals
79
80 (65 - 100)
Manure
15

Landfills
22
40 (20 - 70)
Wastewater treatment
25 (25 - 80)

Biomass burning
50
40 (20 - 80)
Coal mining
46 (25-50)
35 (19 - 50)
Natural gas
30
45 (25 - 50)
Other anthropogenic
13 (7 - 30)

Low temperature fuels
17

Total
360*
350
Subtotal, |4C Depleted Sources:}:
120*
85
All Sources
510*
525
Sinks


Soils
25
30 (15 - 45)
Reaction with OH in the atmosphere
450
500 (400 - 600)
O('D) and CI in the stratosphere
5

Total
480
530
Atmospheric Increase
30
44
Hounded
A possible range of CH, generated was estimated, but is not included in the total..
i	,4C depleted sources were considered to be the "geological" source, plus emissions from CH4 hydrates,
coal mining, natural gas, other anthropogenic (mainly industrial and transportation fossil fuel
combustion), and low temperature fuel combustion.
1-2 1 Atmospheric Methane: Sources, Sinks, and Role in Global Change, ed. M.A.K. Khalil (1993);2IPCC
Scientific Assessment (1990)
2-44

-------
Table 2. Methane flux measurements from rice paddies.
Study
Location
Rice Cultivar
Soil Type
Treatment
Flu*
mg/mYnr
(Emission
Season (days)
Cicerone et aL, 1983
1982 growing season
California, USA
M101
Vertisol, Capay
Cby
Am. phosphate-Am sulfate + Urea: 113
kg N/ha
10.4
100
Cicerone et aL, 1992
1983 growing season
California, USA
Not given
Capay Silty Clay
preplan:: 36 kg N/ha + topdressing after
planting: 78 kg N/ha
4.0
111
1985 growing season
(Only data from plots witfc rice
plants given here)

Not given
Sacramento Clay
No treatment
2.5 t/lia ground rice straw
5 t/ha ground rice straw
78 kg N/ha (Urea, preplant fertilization)
78 kg N/ha + 2.5 t/ha rice straw
78 kg N/ha + 5 t/ha rice straw
05
6.4
189
0.9
3.0
13.9
128
(approximate)
•Seiler et al., 1984
Andalusia, Spain
Raliffl
Not given
Urea (before seeding)- 160 kgN/ha; Am.
nitrate (at tillering}: 40 kg N7ha
4.0
125
Schiitz et al., 1989
Vercelli, Italy
Roma
Sandy Loam
Unfertilized
11.7
114
Data reported from 1984 to
1986; includes data from
Holzapfel-Pschora and Seiler,
1986.


(60% sand, 25%
silt, 12% clay,
2.5% organic Q
Rice straw: average
5	^/ha
3 t/ha
6	t/ha
12 t/lia
24 t/ha
17.6
24^
9.6
13.5
22.1
18.8
118
105
109
110
113




Compost: 60 t/ha
27.5
113




CaCNj: 200 kg N/ha
12.5
118




Urea: average
200 kg N/ha, raked
100 kg N/ha, raked
200 kg N/ha, incorporated
200 kg N/ha, surface
10.7
9.6
9.6
7.9
15.8
118
118
113
113




Straw + Urea: average
6 t/ha + 200 kg N/ha
12 t/ha + 200 kg N/ha
22.5
20.0
25.0
113
113

-------
Table 2. Methane flux measurements from rice paddies (continued).
Study Locatkn Rice Cultivar
Soil Type
Treatment
Flu*
^Emission



mg/m'/br
Season (days)
SchQtz el al., 1989 Vercelli, Italy Roma
Sandy Loam
Ammonium sulfate: average
8.2

(continued)

200 kg N/ha, raked
6.7
118


200 kg N/ha, incorporated
5.6
109


100 kg N/ha, incorporated
8.8
105


SO kg N/ha, incorporated
7.5
105

•
200 kg N/ha, surface
12.5
113


Straw + CaCNj: average
16.8



2.5 t/ha + 37.5 kg N/ha
11.7
118


5 t/ha * 75 kg N/ha
17.9
118


12 t/ha + 200 kg N/ha
20.6
109
Yagi and Minami 1990 flfciaki Knshihikari
Ryugasaki: Gley soil
Noa-iiitrogen (0:60:30)®
2.8
119
Prefecture, Japan
(Eutric GkysoU)
Mineral (60+30:60:30)
2.9
118


Compost 12 t/ha + Mineral (Ibovc)
3.8
112


Rice straw: 6 t/ha + Mineral (above)
9.6
117

Kawachi; peat soil
Rice straw: 6 t/ha + Mineral



(Dystric Histnsnk)
(60+25:60:60+25)
16.3
115

Mito: humic
Non-nitrogen (0:120:®)+30)
1.4
122

Andosol
Mineral (50+30:120:80+30)
1.2
125


Compost 12 t/ha
1.9
129


Rice straw: 6 t/ha
3.2
128


9 t/ha
4.1
128

Tsukuba: light
Mineral (70+30:100:70+30)
0.2
125

colored Andosol
Rice straw: 6 t/ha + Mineral (above)
0.4
115

(volcanic ash soil)



Wassmanc et aL, 1994 Hangzhou, Late Rice
2.5% organic
1987: no fertilizer
33.7
not given;
P.R. China 1987: T8340
matter, clay: 12%,
1987: 694 kg K^SOJha
36.6
- 100
Flood irrigation, all treatments
79.85E > 0.01 mm
1987: 1024 kg/ha tape seed cake
45.0
(from graphs)


1987: KjS04 + rape seed cake
39.7


-------
Table 2. Methane flux measurements from rice paddies (continued).
Study
Location
Rice Cultivar
Soil Type
Treatment
Flu*
mg/mVhr
~Emission
Season (days)
Wassmann et aL, 1994
(continued)
Flood irrigation, all treatments
Huigzhou,
P.R. China
Late Rice (cont.) 2.5% organic
1988: T8340 matter, clay: 12%,
79.856 > 0.01 mm
1989: T8528
1988: do fertilizer	18.9
1988: 694 kg KjSO^ha	13.1
1988: 1024 kg/hi rape seed cake	12.7
1988: K,S04 + rape seed cake	12,0
1989: no fertilizer	41.8
1989: 694 kg ie,SCVha	35.4
1989: 1042 kg manure/ha	50.6
1989:694 kg fC.SC>, + 1042 kg manure/ha	44,0
Early Rice	2.5% organic
1988: Zbefti-3 matter, clay: 12%,
1989: Zaolian 31 79.8% =¦ 0.01 mm
Flood irrigation all years
not given;
-100
not given;
-90
Khalil et al., 1991
Sichuan, China local and hybrid
"pmple soil"
Organic
366
120
Sass et al., 1990, 1991a
1989 and 1990 (fata averaged
for Lake Charles and Beaumont
fertilized sites.
Texas, USA	Jasmine 85 Lk. Charles clay Urea: 149 kg N/ha
(Typic Pelludert) Rice straw: 12 t/ha + Urea: 102 kg N/ha
8.7
15.2
Beaumont clay	Urea: 190 kg N/ha
(Entic Pelludert) Rice straw: 8 t/ha + Urea: 102 kg N/ha
2.5
5.6
85
86
85
86
Sass et al., 1991b	Texas, USA	Jasmine 85 Verland slty clay AH sites, Urea: 190 kg N/ha
loam (Vertic Planted April 9
Ochraqualf)	Straw: 6 Vha	23.5	85
w/o straw	18.3
Platted May 18
Straw: 6 t/ha	18.3	81
viIa straw	11.8
Planted June 15
Straw: 6 t/ha	12.7	76
w/o straw	12.0

-------
Table 2. Methane flux measurements from rice peddles (continued).
Study
Location
Rice Cultivar
Soil Type
Treatment
Flax
mg/m'/hr
'Emission
Season (days)
Sass et al, 1992
Texas, USA
Jasmine 85
Vertand silty clay
loam
All sites, Urea: 165 kg N/ha total
Normal flood irrigation (control)
Mid season aeration
Multiple leration (3 drained periods)
Lase season flood irrigation
4.4
2.3
0.6
6.3
87
87
87
99
Lindau et al, 1991
Looiaana, USA
Lemont
Crowley silt loam
(Typic Albaqualfs)
All sites: Hood irrigation
No fertilizer
Urea: 100 kg N/ha
Urea: 200 kg N/ha
Urea: 300 kg N/ha
10.2
14.5
15.0
17.9
86
Lindau and BoUich, 1993
Louisiana, USA
Texmont
Crowley silt loam
(Typic Albaqualfs)
Clay: 12%
Silt: 71%
First crop: Hood irrigation, K and
phosphorus 67 kg/ha
Urea: 100 kg N/ha
No Nitrogen
Ratooo crop: Flood irrigation
18.4
13.0
77
73
Urea: 84 kg N/ha	29.7
Urea: 84 kg N/ha * 10 tons/ha rice sJraw 85.0
No fertiliser	12.6
Chen et &1., 1993	Beijing,	Huang jiaguang Sandy Loam 610 kg/ha NH.HCQ, + 15 t/ha horse 14.6	79
P.R. China
Sandy Loam
610 kg/ha NH.HCO, +
15 t/ha
hose
14.6
1.33% organic
manure: IT



matter
900 kg/ha NR,HC03: F


17.5

610 kg/ha NH,HCO, +
15 t/ha
horse


manure: F


35.9

710 kg/ha NH^HCO, +
O
f
horse


manure: F


48.9

610 kg/ha NH«HCO, +
15 t/ha
horse


manure*. D


-0.0

-------
Table 2. Mediane flux measurements from rice paddies (continued).
Study
Location
Rice Cultivar
Soil Type
Treatment
Flux
'Emission





mg/m'/hr
Season (days)
Chen ct al., 1993
Nanjing,
Shanyou 63
"yellow-brown
190 kg/ha Urea + 15 t/ha barnyard
10.8
101
(continued)
P R. China

earth* 2.29%
manure: L





organic matter
45 t/ha barnyard manure: ~
9.5





600 kg/ha Ammonium Sulfate: F
2.6





190 kg/ha Urea + 3 t/ha rapestmw: M
143




.
190 kg/ha Urea + 15 t/ha bom yard






manure: Semi-arid
6.6

Yao and Chen, 1994a
Beijing.
Huang Ting
Aquod, 2.9%
1991: Intermittent Irrigation

94

P.R. China
Guang
oganic matter
NHjHjPO,: 144 + 369 + 150 kg/ha
28.8

Mineral fertilizer was applied



(NH^SCV 144 + 180 + 369 kg/ha
22.6

as base, at tillering and at spike



NH.HCO,: 225 +369 + 240 kg/ha
20.4

formation



(NH^CO: 225 + 369 + 2*5 kg/ha
18.0





1992: Flood Irrigation

103




(NH.^SO,: 144 + 279 + 150 kg/lia
9.6





NH4HCOj: 225 + 369 + 240 kg/ha
235





(KH^CO: 117 + 180 + 120 kg/ha
9.4

Yao and Chen, 1994b
Beijing,
Huang Jing
1.9% organic
All treatments:

94

P.R. China
Guang
matter
NH.HCO,: 225 + 369 + 140 kg/ha






22.5 tons manure/ha, intermittent irrigation
218





Intermittent irrigation
183





Flood irrigation
20.4

His in et aL, 1994 in press
West Java,

Aerie Tropaqualf
All treatments: 7 ton/ha rice straw, 67



Indonesia


kg/ha urea, 100 kg/ha KCl 100 kg/ha





clay: 53.5%
phosphate + 67 kg/ha urea +116 kg/ha





silt; 29.7%
urea




1R-64
sand; 16.7%
Flood irrigation
20.2
91




Inter mitten: irrigation
8.7





Saturated soil
8.2



Cisadane

Flood irrigation
14 2
112




Intermittent irrigation
8.7





Saturated soil
3 2


-------
Table 2. Methane flux measurements from rice paddies (continued).
Study
Location
Rice CuMvar
Soil Type
Treatment
Flux
mg/mJ/hr
®Emissi on
Season (days)
Denier van der Gc® and Ncue,
Los Bancs,
IR72
Andaqueptic
1991 wet season, both treatments: 55 kg

not given
1994
Philippines

Haplaquoll
N/ha Urea, Flood irrigation






Control
1.7
-100



clay. 66%
6.66 tons/ha gypsum (CaSOO
08
(from graphs)



silt 28%






sand: 6%
1992 wet season, both treatments: 30 kg





organic C: 1.97%
N/ha Urea, 2 applications + 20 tons/ha






green manure; Flood irrigation

-105




Control
18.5





6.66 tons/ha gypsum
5.3

Neue et al., 1994
Los Bafios,
Philippines
IR-72
Andaqueptic
Haplaquoll
Texture: Clay
Organic C: 1.57K
Hood irrigation, all treatments
1992 dry season:
87 + 30 + 30 kg N/ha Urea
1992 wet season: both treatments three
applications Urea 30 + 30 + 30 kg N/ha:
Control
Urea + S tons/ha rice straw
8.0
3.6
7.3
104
105
Partial Studies: studies where measurements were not takes for a full season a are not yet repotted in full, and are not comparable to the preceding studies. Ranges of
emissions are shown.
Cicerone and Shetter (1981}
California, USA

1.3-7.8

Khali! et al. (1990)
Sichuan, China

1 -50

Parashar et al. (1991)
New Delhi, Kama],
Dehradun, and
Hyderabad, India

0.07 - 80.0

Yagi et al., (1994): 3-5
Suphan Buri, Thailand
Dry Season
19.5
109
measurements were tufam
Suptaan Buri, Thailand
Rainy Season
32.2
97
during die growing season
Khlong Luang, Thailand
Dry Season
3.8
83

Chai Nat, Thailand
Rainy Season
1.6
94
Simpson et al. (1995)
Los Bancs, Philippines
March 9-24, 1992
28.8

* Number of days that methane was actually emitted from the rice paddies.
5 (NiPjOjiKjO) in kg/ha; rates of mineral fertilizer are expressed as basal + supplementary applications.
1 F: flood irrigation; II: intermittent irrigation; D: dry culture.

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Table 3. Estimates of global methane emissions from rice agriculture.

This Work
Aselmann and Crutzen
IPCC

(1995)
(1989)
(1990)
Tg/year
66
92 (531)
60
Year of Estimate
1990
1985
Hot given
1 Number in parentheses assumes a constant flux of 13 mg/m2/hr
2-51

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Table 4. Estimates of methane emission by country for 1990 using five sets of assumptions.
Country
This Work
Matthews' et
Bachelet and
Bachelet and

al.
Neue*
Neue/Soil5
Bangladesh
4.0
6.7
4.1
4.0
China
23.0
21.6
21.3
14.7
India
15.3
27.6
18.5
17.5
Indonesia
6.2
3.7
4.5
3.5
Japan
0.2
1.1
1.0
0.8
Cambodia
0.9
0.9
0.4
0.4
N. Korea
0.3
0.4
0.5
0.4
S. Korea
1.1
0.6
0.8
0.6
Laos
0.5
0.3
0.1
0.1
Malaysia
0.3
0.3
0.3
0.2
Myanmar
1.1
3.7
0.2
1.4
Nepal
0.2
0.3
0.3
0.2
Pakistan
0.7
1.1
0.8
0.4
Philippines
1.2
1.4
1.2
0.8
Sri Lanka
0.4
0.5
0.4
0.3
Taiwan
0.4
0.5
0.4
0.4
Thailand
4.7
6.9
3.8
2.2
Vietnam
2.6
4.3
2.7
1.8
Totals
63
82
61
50
Estimates made by Bachelet and Neue (1993) using the Matthews et al.
(1991) database and a constant methane flux of 0.5 g/tn2-day.
Estimates made by Bachelet and Neue using International Rice Research
Institute (IRRI) rice yield data, and regional estimates of incorporated
organic matter.
The Bachelet and Neue estimate modified using the FAO soil map, and
authors' best judgement on the methane potential of different soil types.

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2-D
This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication.
DEVELOPING IMPROVED METHANE EMISSION ESTIMATES FOR
COAL MINING OPERATIONS
Stephen D. Piccot, Sushma S. Masemore, Eric S. Ringler
Southern Research Institute
6320 Quadrangle Drive, Suite 100
Research Triangle Park, North Carolina 27709, USA
David A. Kirchgessner
U.S. Environmental Protection Agency
Air Pollution Prevention and Control Division
Research Triangle Park, North Carolina 27711, USA
ABSTRACT
The Environmental Protection Agency's (EPA) Air Pollution Prevention and Control
Division (APPCD) has sponsored research to improve emissions data and establish more
representative emissions inventories for coal mining operations. The focus of this effort has
been on the uncertain sources of emissions including surface mines, post-mining coal handling,
abandoned underground mines, and inactive surface and underground mines. Measurements
data collected at 5 surface mines, 20 abandoned underground mines, and 1 coal handling
facility are presented. The significance of these individual sources, and their emissions
processes, is also examined. Measurements priorities are also discussed.
BACKGROUND AND OBJECTIVES
Methane (CH4) is a radiatively important trace gas that has been estimated to account
for about 18 percent of anthropogenic-induced greenhouse warming [1], [2]. It is widely
recognized that emissions'of CH4 from coal mining operations significantly contribute to global
CH4 emissions. Coal mining is among the top three or four sources thought to be responsible
for the recent buildup of CH4 in the troposphere [3]. Accepted annual emissions estimates
range from a low of 35 teragrams to a high of 64 teragrams. Other key anthropogenic
sources of CH4 include ruminants, rice paddies, landfills, natural gas transmission and
distribution systems, liquid waste treatment systems, biomass burning, and a group of minor
industrial sources (e.g., coke production, fossil fuel combustion, geothermal power production,
fossil fuel refining). Emissions of CH4 from the coal mining industry are from the distinctly
different sources listed below:
2-53

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•	Underground mines (mine ventilation and mine degasification systems)
•	Surface mine's
•	Post-mining coal handling (processing, transport, and storage)
•	Abandoned underground mines
•	Inactive underground and surface mines
Over the past 30 years, there have been several attempts to estimate the global
emissions of CH4 from coal mining operations [4] ¦ [9]. Emissions from active underground coal
mines are significant and reasonably well characterized in these estimates; however, improved
emissions data are needed for surface mining operations, post-mining coal handling, and
abandoned and inactive mines. Current estimates for surface mines and post-mining
operations are based on minimal or no measurement data, and most published emissions
inventories fail to account for abandoned and inactive mine emissions altogether.
Over the past several years, the Environmental Protection Agency's (EPA) Air Pollution
Prevention and Control Division (APPCD) has sponsored research to improve emissions data and
establish more representative emissions inventories for coal mining operations. This research
has focused on developing improved emission factors and coalbed reservoir data bases, and
improving emission inventories for the most uncertain sources including surface mines, post-
mining coal handling, and abandoned/inactive underground mines. Improved emissions
inventories for coal mining will enhance the ability of researchers to assess the significance of
coal mining in global scale emission processes.
APPCD's coal mine emissions research program has focused primarily on assessing the
characteristics of mining operations in the U.S.. but the program focus is being extended to
the execution of global scale assessments. This paper describes APPCD's program to improve
coal mine emissions estimates, and presents updated CH4 emissions estimates for some mining
operations in the U.S. These improved estimates are based on the new measurements and
other data developed by APPCD.
DISCUSSION
Underground Mines
Because emissions from underground mines are relatively well characterized, efforts to
develop improved emissions data for this source have been minimal compared to the other
sources. However, coalbed CH4 gas content data are used extensively in the estimates for
underground mines, surface mines, and post-mining coal handling operations, so work has been
done to develop an improved coalbed CH4 data base. This data base, referred to as the
Refined Gas Content (RGC) data base, was compiled using core measurements and other data
collected and analyzed by the U.S Bureau of Mines (BOM). Raw data for over 1,500 samples
were collected from BOM's files. These data were reviewed and entered into a computer-
based data management system, and adjusted to account for atmospheric pressure,
temperature, coal moisture, and ash content, and then revised to account for inaccuracies in
the estimation of the "lost gas" component. General quality assurance exercises were also
conducted.
Using these data and updated mine shaft and gob well emissions data collected and
compiled by the Mine Safety and Health Administration (MSHA), BOM, and the Department of
2-54

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Energy, APPCD is developing improved emissions functions which relate commonly available
parameters such as seam depth, coal basin location, mining technology, and coal quality.
Surface Mines
During the late 1980's and early 1990's, surface coal mines accounted for about 60
percent of the coal produced in the U.S., and 40 percent of the coal produced throughout
the rest of the world [10], [8]. The lack of emissions measurements and other data for
surface mining operations has introduced significant uncertainty into current global emissions
estimates due to the widespread use of surface mining. For example, in recent global
estimates, the emission rate used to represent surface mines (i.e., about half of the world's
coal production) was based on a "best guess" approach [8]. Clearly, the collection of
additional measurements and other data for surface mines will reduce uncertainties in global
emissions estimates.
Surveys conducted at over 30 surface mine sites in the U.S. demonstrate that
emissions from surface mine sites are highly heterogeneous. Within any given mine, CH4
liberations can vary widely from exposed coal surfaces, interburden material, overburden
material, blasted coal areas, and penetrations made into the seam and into the strata
underlying the coal seam. As a result of this heterogeneity, and because surface mine sites
are extremely large and difficult to access, a remote sensing based measurements
methodology has been used. The measurements methodology is unique, and was developed and
validated [11], [12], The methodology is based on the use of an open-path Fourier Transform
Infrared (FTIR) spectrometer which passes a beam of infrared (IR) radiation through the CH4
plume liberated from surface mine sites. The open-path configuration is capable of
representing emissions from large, diffuse, and heterogeneous sources. The IR spectra are
subjected to spectral analysis to determine the infrared absorbence of individual compounds
passing through the beam. These absorbence values are compared against absorbence values
of known compound concentrations to determine the concentration of the gas measured.
In the methodology, FTIR measurements are conducted in the CH4 plume emanating
from the exposed coal surfaces and elsewhere in an effort to estimate the CH4 emission rate
for the mine. The methodology involves the collection of horizontal wind speed and wind
direction measurements in the vicinity of the plume to track and characterize the plume
dimensions using an appropriate plume dispersion model. For each monitoring event, the path-
integrated CH4 concentration in the plume is measured by the FTIR at about 2 meters above
ground level. Simultaneous with this CH4 measurement, the tracer gas sulfur hexaflouride
(SF5) is released from a single point in known quantities from within the active mine. The
tracer concentration from this release is also measured in the plume using FTIR, and these
tracer concentrations are used to define the tracer and CH4 plume's dispersive properties
and dimensions. With the plume concentration and dimensions estimated, it is then possible to
"back-calculate" the emission rate which produced the observed plume concentrations
measured with FTIR.
Table 1 presents the emission rates measured at five surface coal mines in the U.S.:
four in the Powder River region and one in the Northern Appalachian region. The four Powder
River sites account for almost 35 percent of the total coal produced within that region, but
only three sites include both active and inactive areas. As the data for Mine 4 suggest,
2-55

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inactive areas may be significant contributors to the total emissions from surface mines (this is
a preliminary finding and is still under investigation). Emissions from the Northern Appalachian
mine appear low, but this is likely a result of the primary gassy seam's (the Pittsburgh seam)
not being widely exposed during the testing.
Emissions from inactive surface coal mines have not been included in current inventories
because the activity factor used to estimate emissions (i.e., coal production rate) is zero for
inactive sites. Inactive surface sites generally occur for the same reason "abandoned" sites
do; there is some financial impetus to leave the site accessible for future coal extraction.
Preliminary assessments suggest that in some cases emissions from inactive mines may be
significant, but too little data are available to support conclusions at this time. Large, inactive
areas have been observed at three of the four active surface coal mines studied in the Powder
River Basin, and direct measurements conducted at one site indicate that substantial
quantities of ChU gas are being liberated (see Mine 4 in Table 1).
Coal Handling Operations
CH4 is emitted from active coal mines when coal gas, trapped in fractures in coal seams
and adsorbed onto internal coa! surfaces, is liberated into the mine working areas. After
mined coal leaves the confinement of an active underground or surface coal mine, it typically
proceeds to a series of operations during which additional Cl-I4 that was adsorbed on internal
coal surfaces is released to the atmosphere. Post-mining operations, referred to as coal
handling processes, include all of the treatment that coal undergoes between mining and final
use (most often, combustion). These processes can include transportation, storage, crushing,
classification by size, separation of impurities, and drying.
The best current estimates of CH4 emissions from post-mining activities are based on
assuming that the fraction of the in-situ coalbed CH4 content remaining in the coal after
mining is emitted completely to the atmosphere during post-mining activities. This approach
oversimplifies the emission liberation process because it neglects treatment of residual gas,
which can remain associated with the coal until final combustion. In addition, this fraction has
not actually been measured, but is based on assumptions about the residence time of coal in
mines, and the desorption rates of virgin coal samples (not disturbed and broken samples
emerging from mines). For surface mines, post-mining losses are assumed to be zero while for
underground mines, a range of 25 to 60 percent of the original CH4 content has been used
[13].
Recently, APPCD and SRI scientists examined the CH4 release mechanisms and potential
sources of CH4 emissions at coal handling facilities. Site surveys and measurements were
conducted at three coal handling facilities in the Warrior Basin of Alabama. Based on these
evaluations, it was concluded that improved emissions data are needed, but that direct CH4
emission measurement techniques could not be practically used to quantify emissions from coal
handling facilities. Instead, considering the availability of national coal gas content and other
data sets, it was concluded that manipulation of data on coal desorption rates and post-mine
gas contents held the best promise for developing improved national and global emission
inventories. It was concluded that emission relationships can be developed based on: (1) the
in-situ gas content of the seam being mined, (2) the CH4 content in the coal at the mine
outlet, (3) the time rate of CH4 desorption for coal at the mine outlet, and (4) the average
2-56

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cumulative time the coal is exposed to the atmosphere after mining (route time), CH4 content
and other measurements obtained from representative samples of run-of-mine (ROM) coal
(coal as it leaves the mine and enters the processing plant) are being collected and used to
quantify the amount of desorbable gas present in ROM coal. Relationships between these
measurements and the in-situ coalbed CH4 content for the same coal could provide a basis for
national and global inventories using available in-situ coalbed gas content data bases.
In May 1994, SRI completed a field trial of methods for determining gas contents and
desorption rates for ROM coal samples. The field trial had several objectives. The first was to
identify the most efficient technique for determining the gas content of ROM coal; the BOM's
Modified Direct Method versus on-site crushing and analysis were examined. In addition, since
the Modified Direct Method has traditionally been conducted on virgin coal cores, the second
objective was to assess the method's performance on broken ROM coal samples. The final
objective was to determine the "best fit" desorption rate equation for mine mouth samples.
In the field trial, 29 ROM samples were collected at the outlet of one underground mine
in Walker County, Alabama. These samples were placed in sealed canisters for later desorption
in the laboratory, while an additional 22 samples were processed with on-site crushing. Table
2 summarizes the results. In the table, results are presented in units of standard cubic
meters per tonne, and show the desorbed, residual, and total gas content values (i.e.,
desorbed plus residual) determined by the Modified Direct Method. The total gas determined
by on-site crushing is also shown. Gas volumes are not corrected for oxygen (O2) sorption,
which may decrease the .CH4 volume by 7 to 14 percent, or for the presence of non-methane
compounds (present at low ppm levels). Coal weights are "as mined"; that is, there is no
correction for the moisture and ash content of the coal. This presentation is consistent with
BOM national data sets.
For the field trial site, the mean desorbed gas content for the ROM coal samples is 0.84
±0.05 scm/tonne (27.0 ±1.7 scf/ton), with a mean desorption time of about 70 days.
Uncertainty values are based on a 95 percent confidence interval using the standard t(n-1)
distribution. The mean residual gas content is 0.80 ±0.08 scm/tonne (25.7 +2.5 scf/ton).
The mean sum of desorbed and residual gas content is 1.64 ±0.10 scm/tonne (52.4 ±3.1
scf/ton). The mean total gas content from the immediate crushing measurements is in good
agreement with the Modified Direct Method: 1.64 ±0.21 scm/tonne (52.5 ±6.6 scf/ton).
Because of this good agreement, on-site crushing will be used in future field tests, although
initially, the Modified Direct Method will be used to allow a more complete assessment of the
desorption rates associated with broken ROM coal samples.
The CH4 contents of the ROM coal samples determined for the field trial site were
compared to in-situ gas contents associated with virgin coal samples obtained at the site. A
total of 10 coal cores collected within a 3 mile radius of the active mining area were used in
this comparison. The average desorbable gas content for these 10 cores is 3.34 ±0.81
scm/tonne (107 ±26 scf/ton). Residual gas data were not available for these cores; however,
residual gas contents for Walker County coals in the Mary Lee seam, where this mine is
operating, average about 0.69 ±0.22 scm/tonne (22 ±7 scf/ton). This is consistent with the
residual gas contents determined for the ROM samples. Thus, about 40 percent of the total
gas originally contained in the virgin coal (i.e., 100"[1.64/(3.34*0.69)]} remained in the ROM
coal as it left the mine. More importantly, about 25 percent of the original desorbable gas, or
non-residual component, remained. It is unlikely that all of the residual gas in coal will be
2-57

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released to the atmosphere before final combustion; some will surely remain in the coai and be
burned.
Abandoned and Inactive Underground Mines
Abandoned underground coal mines are treated differently depending on local
regulations and whether the mine is expected to be permanently or temporarily Inactive.
Mines may be completely sealed and closed to the atmosphere by backfilling shafts and slopes,
or left vented with cement caps and vent pipes. Obviously, CH4 emissions are expected only
from vented mines; however, the method of closure is not recorded in the national data bases
and must be obtained from other, usually local, sources. It appears that only a fraction of
abandoned mines arc vented, and that these are often associated with mines that are closed
with the intent of later reopening.
The Mine Safety and Health Administration has cataloged 5,970 underground coal
mines abandoned since the early 1970's. These data show that a substantial number of mines
have been closed within the last 6 years and that peaks in mine closures occurred during
1988 and 1991, and again during 1993 and 1994. Most of these mines are located in the
eastern and central U.S. States containing the largest number of abandoned mines (in
decreasing order) are Kentucky, West Virginia, Virginia, Pennsylvania, and Tennessee. These
five states contain about 95 percent of all abandoned underground coal mines, with 50
percent of all these mines located in eight counties in Kentucky, West Virginia, and Virginia.
Although these few areas contain a large fraction of the total population of abandoned mine
sites in the U.S., other areas contain mines that produce substantial emissions; emissions
measured at one Ohio mine were the highest experienced yet in the project.
The method used to determine the CH4 emission rate at capped and vented mines is
simple. A portable IR analyzer is used to measure the percent CH4, carbon dioxide (CO2}, and
O2 concentrations by volume at tho vent outlet, A propeller anemometer is then used to
measure the exit velocity. This information and the vent diameter yield the emission rate.
Temperature and pressure information is obtained from a local weather station and used to
convert to standard conditions, and to assess the effect of atmospheric conditions on flow
rate. Measurements are mads at all shaft and slope vents to determine the total emission
rate for a mine.
To date, CH4 emissions have been measured at 20 abandoned underground coal mines:
9 in West Virginia, 4 in Kentucky, 2 in Ohio, and 5 in Alabama. Table 3 gives the results of
these measurements. The measured emission rates van/ widely from zero to over 21,240
m3/day (750,000 ft3/day) of pure CH4. A few of the rates measured are comparable to
emissions from active underground coal mines with CH4 emission rates among the highest in the
U.S. On the other hand, many abandoned mines measured were found to liberate iittle or no
gas, and many lie below the water table and, once flooded, cease to emit. Although the data
are not presented here, emissions can also vary significantly over both short and long terms,
and from different vents in the same mine.
An understanding of changes in CH4 emissions over time is important since the emission
rate does not remain constant. The tola! emissions for a mine, as well as the emission rate at
any point in time, are functions of diurnal and, probably, seasonal cycles related to changes in
2-58

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temperature and barometric pressure, as well as longer term changes brought on by
processes such as mine flooding and eventual depletion of the available CH4 in the coal.
Measurements have been repeated at some mines to obtain information on changes in the
emission rate over time. Longer term measurements were made at one mine to study the
effects of changes in temperature and barometric pressure on CH4 emissions. In addition,
data showing changes in the CH4 concentration at a vent outlet were obtained over a period
of more than 18 months after closing.
Data obtained for three inactive underground mines at which no coal was being
produced, but ventilation fans and other support equipment remained in operation, suggest
that emissions from an inactive underground mine can be 50 to 80 percent of the emissions
which occurred when the mine was active.
CONCLUSIONS
Although sufficient data are not available to support the development of an emissions
inventory, the emissions measurements data collected so far can be used, together with DOE
coal production data [10], to focus and prioritize measurements and other research. This
has been done by approximating the national U.S. emissions from each source, and comparing
the relative significance associated with each. Figure 1 shows estimated emissions for the
mining related emission categories examined. As the figure shows, emissions from surface
mines, coal handling, and abandoned mines account for about one-third of the total emission
from coal mining. As expected, underground mines are the most significant followed by coal
handling, surface mines, and abandoned mines. These estimates do not include emissions from
inactive underground coal mines--although they too, appear to be potentially significant.
As this comparison suggests, a continued focus on coal handling emissions is important
and will be given high priority in future measurements activities. Continued measurements at
surface mines are a'so needed, particularly in the Appalachian and Illinois Basins, but a special
emphasis on characterizing inactive surface mine sites is clearly justified by the preliminary
data coilected in the Powder River Basin. Third in priority is identifying and measuring
emissions from abandoned underground mines, and conducting a preliminary evaluation of the
potential emissions associated with inactive underground mines. At this point, the number of
abandoned underground mines has not been determined, but they appear to be geographically
concentrated. A survey of local mining authorities in the five states with 95 percent of the
abandoned mines could yield data on emissions from inactive underground mines.
REFERENCES
1.	Smith, B. and D. Tirpak, 1989. The Potential Effects of Global Climate Change on the
U.S.: Report to Congress, EPA/230-05-89-050, Office of Policy Planning and
Evaluation, Washington, DC, 13 pp.
2.	Khali!, M.A.K. and R.A. Rasmussen, 1993. Decreasing Trend of Methane:
Unpredictability of Future Concentrations, Chemosphere, Vol. 26 (1-4): 803-814.
3.	Cicerone, R.J. and R. Oremland, 1988. Biogeochemical Aspects of Atmospheric
Methane, Global Biogeochemical Cycles, 2:299-327.
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4.	Koyama, T., 1963. Gaseous Metabolism in Lake Sediments and Paddy Soils and the
Production of Atmospheric Methane and Hydrogen, Journal of Geophysical Research,
Vol. 68:3971-3973.
5.	Koyama, T., 1964. Biogeochemical Studies on Lake Sediments and Paddy Soils and the
Production of Hydrogen and Methane, Recent Researches in the Fields of Hydrosphere,
Atmosphere, arid Geochemistry, 143-177.
6.	Hitchcock, D.R. and A.E. Wechsler, 1972. Biological cycling of atmospheric trace gases
(Report No. NASW-2128). National Aeronautic and Space Administration, Washington,
DC, 415 p.
7.	Seiler, W., 1984. Contribution of biological processes to the global budget of CH4 in the
atmosphere. In: M.J. Klug and C.A. Reddy (eds) Current Perspectives in Microbial
Ecology. American Society for Microbiology, Washington, DC.
8.	Boyer, C.M., J.R. Kelafant, V.A. Kuuskraa, K.C, Manger, and D. Kruger, 1993. Methane
Emissions from Coal Mining: Issues and Opportunities for Reduction, EPA-400/9-
90/008, Office of Air and Radiation, Washington, DC.
9.	Kirchgessner, D.A., S.D. Piccot, and J.D. Winkler, 1993. Estimate of Global Methane
Emissions from Coal Mines, Chemosphere, Vol. 26 (1-4): 453-472.
10.	U.S. Department of Energy, 1993. Emissions of Greenhouse Gases in the United States
1985-1990, DOE/EIA-0573, Energy Information Administration (EIA), Washington, DC.
11.	Piccot, S.D., A. Chadha, D A. Kirchgessner, R. Kagann, M. Czerniawski, and T. Minnich,
1991. Measurement of Methane Emissions in the Plume of a Large Surface Coal Mine
Using Open-Path FTIR Spectroscopy, In: Proceedings of the 1991 Air and Waste
Management Association Conference, June 16-21, Vancouver, B.C.
12.	Piccot, S.D., S.S. Masemore, E.S. Ringler, S. Srinivasan, D.A. Kirchgessner, and W.F.
Herget, 1994. Validation of a Method for Estimating Pollution Emission Rates From
Area Sources Using Open-Path FTIR Spectroscopy and Dispersion Modeling Techniques.
Journal of the Air and Waste Management Association March 1994, 44: 271-279.
13.	Hogan, K.B., 1993. Opportunities to Reduce Anthropogenic Methane Emissions in the
United States: Report to Congress, EPA/430-R-93-012, Office of Air and Radiation,
Washington, DC.
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TABLE 1: SUMMARY OF MEASURED EMISSION RATES FOR SURFACE MINES
Mine No.
Location
Coal Production
(million tonnes)'
Methane
Emissions
(million m3/yr)b
Significance Ranking'
(groups of
underground mines)
I
Powder River
•11.8
1.7 (active)
(no inactive)
Top 100-200
2
Powder River
9.0
0.9 (active)
? (inactive)
Top 200 400
3
Powder RLver
15.2
1.6 (active)
? (inactive)
Top 100-200
4
Powder River
12.7
1.8 (active)
11.8 (inactive)
Top 30
5
Northern App.
1.3
0-0.1 (active)
0 (inactive)
low
1 To convert million metric tonnes 10 million tons, multiply by 1.10.
6 To convert million ni'/yr to million f'Vyr, multiply by 55.31.
c About 75 percent of total emissions from (he U.S. coa! mine industry are issociared w:ih shout 400 gassy underground mines.
This ranking i!lusira:es how the emissions from each surface mine compare to the emissions from groups of these 400 mines.
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TABLE 2: INITIAL FIELD TRIAL RESULTS
Sample ID
]| Test Duration
Modified Direct Method (scm/tonnc)
On-site Crushing (scm/toune)
1 (days)
Desorbed Gas
Residual Gas
Des+Res
Des+Res
1
85.0
0.74
1.15
1.89
1.24j
2
53.9
0.53
0,87
1.41

3
63.!
0.71
0.63
1.34
1.17
4
59.0
0.85
0.70
1.56
1.31
5
1 84.9
0.93
0.68
1.61
1.58
,
! 59.0
0.89
0.52
1.41

7
I 64.8
1.10
l.ll
2.21
2.461
8
64.8
0.70
0.S2
1.52
1.39
9
61.6
0.86
0.87
1.73
1.46
10
64.8
0.95
0.70
1.64

11
1 64.2
0.66
0.79
1.44
1.12
12
61.2
0.87
0.98
1.86
1.96
13
84.2
0.95
1.18
2.13
2.17.
14
61.1
1,01
0,65
1.66
2.04 j
15
89.1
1.02



16
I 60.9
0.88
0.53
1.42
1.921
17
! 88.8
0.92
1.20
2.11
2.911
18
60.8
0.90
0.68
1.58
1.51
1 19
84.0
0.91


1.60
j 20
88.9
0.94
061
1.56

21a
88.1
0.82
0.75
1.57
1.341
21tj
88.2
0.82
0.73
1.55
l.34l
22
60.1
0.63
0.93
1.57
1.52
23
83.1
0.95
0.71
1.67
1.601
24
60.0
0.77
0.67
1.44
1.34)
25
56.1
0.96


1
i
26
88.2
0.90
0,83
1.73
2.001
27
56.9
0.50
0.72
1.22

28
88.7
0.83
0,85
1.69
1.041
29 j
88.7
0.73

. 1
Average
41.5
0.34
0.80
1.64
1.64]
Standard Err
0.7
0.02
0.04
0.05
0.10]
Count
30
30
26
26
221
"t-95" value
2,05
2.05
2.06
2.06
2.03
+ \-
1.4
0.05
0.08
0.10
0.21
Percent Error
3.4%
6.2%
9.6%
6,0 %
12.6% 1
Explanations For Missing Data:
Total gas content was not determined for samples 2, 6, 10. 15. 20. 25. and 29 due to time constraints in the field.
Residual or total gas determinations for samples 15, 19, 25 , 27. and 29 invalidaied due to leaks or sample mishandling.
To convert standard cubic meters per tonne to standard cubic feet per ton, multiply by 32.03.
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TABLE 3: ABANDONED MINE MEASUREMENTS RESULTS
Mine No.
Year Closed
Basin
State
Flooding
| 1000scm/day
1
circa 1987
C. Appalachian
WV
Flooded
0.2
2
1992
C. Appalachian
wv
Partial
0.5
2ab
1990
C. Appalachian
wv •
Partial
8.3
3
1990
C. Appalachian
WV
Dry
12.3
4
1988
C. Appalachian
WV
Partial
2.3
5
1982
C. Appalachian
wv
Partial
0.0
6
1985
C. Appalachian
WV
Partial
0.1
7
1985
C. Appalachian
WV
Partial
0.0
8
1980
C, Appalachian
WV
Partial
0.1
9
".982
C. Appalachian
WV
Partial
0.0
10
circa 1973
Illinois
KY
N/Ac
1.1
11
N/A
Illinois
KY
N/A
0.0
12
1980
N. Appalachian
OH
Dry
11.3
13
1990
N. Appalachian
OH
Dry
22.0
14
circa 1975
Black Warrior
AL
N/A
0.1
15
1993
Black Warrior
AL
Partial
3.7
'.5a
1993
Black Warrior
AL
Partial
18.8
15b
1993 '
Black Warrior
AL
Partial
14.6
16
1985
Black Warrior
AL !
Flooded
0.0
17
1982
Black Warrior
AL
Flooded '
0.0
18
1932
j
Black Warrior
AL
Flooded j
0.0
19 i
1977
Illinois
KY
Flooded |
0.0
20 ;
1984 j
Illinois
KY
Flooded
0.0
? To convert standard cubic meters per day to standard cubic feed per day, multiply by 35.31.
Subsequent measurements were taken a( Mines Nos. 2 and 15 anil are presented here.
N/A • information daia not available.
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3.151
Underground Mines
Coal Handling
Surface Mines	Total Emissions
Abandoned Mines

-------
2-E
METHODS FOR ESTIMATING METHANE EMISSIONS
FROM THE DOMESTIC NATURAL GAS INDUSTRY
David A. Kirchgessner
U. S. Environmental Protection Agency
Air Pollution Prevention and Control Division
Research Triangle Park, North Carolina 27711, USA
R. Michael Cowgill, Matthew R. Harrison, Lisa M. Campbell
Radian Corporation
8501 Mopac Boulevard
Austin, Texas 78759, USA
ABSTRACT
Anthropogenic emissions of methane are suspected of making a significant contribution
to the phenomena associated with global climate change. Early, gross estimates based on
scarce data suggested that the global natural gas and coal industries each may contribute
10 to 15 percent of the annual anthropogenic methane inventory. This possibility mace the
importance of improving the industry-specific emissions estimates apparent The data
would be useful in determining where emissions could be most economically reduced if
that approach were deemed prudent; the data would also be useful in evaluating the
advisability of switching from coal to natural gas fuel as a near-term measure for reducing
the impact of greenhouse gas emissions on the atmosphere. The project described has
the goal of estimating methane emissions from the domestic gas industry to within ±0.5
percent of production or ±110 BCF.1 Emission estimates are nearly complete and appear
to be converging on 1.5 to 2.0 percent of production with a 1992 base year.
This paper has been reviewed in accordance with the
U.S. Environmental Protection Agency's peer and administrative review policies
and approved for presentation and publication
1 BCF = Billion Cubic Feet = 109 cubic feet; 1 cubic foot = 0.02832 cubic meter.
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INTRODUCTION'
Until recently, measured concentrations of methane in the atmosphere were increasing at
the rate of approximately 1 percent annually [1] and, although recent observations indicate
that atmospheric methane concentrations in the northern hemisphere are beginning to
level off [2,3], interest in accurately quantifying anthropogenic methane sources has not
diminished appreciably. Older estimates based on sparse, and sometimes anecdotal,
evidence suggested that the coal and natural gas industries each contributes 10 to 15
percent of the global anthropogenic methane inventory. If the early estimates are even
approximately correct then these fossil fuel industries are significant contributors of
greenhouse gas and their emissions need to be quantified. This project will also address
the question of whether switching from coal or oil to gas fuel to reduce carbon dioxide
emissions is desirable. Since natural gas is approximately 90 percent methane, significant
emissions from the industry could reduce or eliminate its other inherent advantages.
The Environmental Protection Agency (EPA) and the Gas Research Institute (GRI) are
cofunding and comanaging a project to quantify methane emissions from the gas industry.
The first phase of the project involved locating and evaluating existing data, identifying data
gaps, and defining the overall problem and objectives of the study. The second phase of
the study identified or developed methods for measuring steady emissions and calculating
unsteady emissions from each sector of the industry. The final phase of the study, which
began in 1992 and will be completed in 1995, involves collecting sufficient data to
determine industry emissions to within ±0.5 percent of production {±110 BCF). This paper
describes the methods employed in the study and provides interim results.
METHODOLOGY
The first phase of the study was conducted independently by EPA and GRI, and identified
a number of problems that needed resolution before a credible estimate of gas industry
emissions could be developed. First, it was recognized that, in many cases, good sampling
techniques were not available and needed to be developed and validated. It was also
necessary to develop defensible techniques for extrapolating measurements from a limited
number of sites within a source category to the entire category for the purpose of making
national estimates. Finally, since some sources emit only intermittently, they do not lend
themselves to any sampling approach over the time period available in this study. Those
sources require a means of calculating their unsteady emissions.
Leaks or other emissions typically regarded as fugitive generally have constant rates and
can bo characterized reasonably well by a single sample. Examples of sources which are
unsteady in nature and need to be calculated are compressor exhaust, pneumatic control
devices, maintenance activities, system upsets, and mishaps.
The accuracy needed for quantifying various source categories was prioritized based on
their estimated contribution to total emissions. Larger categories require a higher degree
of accuracy to most efficiently achieve the overall accuracy target of ±110 BCF. The
program was set up so that, if the accuracy target for each source category was achieved,
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the overall program target would be achieved. In this fashion, once the program was under
way, apportionment of resources became automatic.
The framework for assessing emissions consisted of first identifying all hardware that is an
emissions source, determining how many pieces of each hardware component typically
comprise a piece of equipment such as a separator or compressor, and then determining
how many pieces of equipment are found in each industry sector. The five industry sectors
considered are production, processing, transmission, storage, and distribution.
The approaches taken to measuring steady emissions, calculating unsteady emissions,
and extrapolating results are described below.
Measurement Techniques for Steady Emissions:
Emission factor approach: To determine emissions from a source using this technique, the
individual valves, flanges, seals, and threaded fittings are counted. These counts are then
multiplied by the emission factor, or average emission rate, that has been calculated from
a number of measurements of this type of fitting. Emissions are typically measured by a
bagging technique in which the fitting to be measured is enclosed, uncontaminated gas is
passed through the enclosure, and the concentration of the gas of interest is measured at
the outlet. The emission rate is concentration times flow rate. A shortcoming of this
approach is that it is only reasonably accurate for facilities which are similar. Differences
in facilities such as age, operating pressure ranges, and inspection and maintenance
programs can produce large differences between actual and estimated omissions.
Correlation equation technique: Like the emission factor approach, this technique
determines emissions from different types of sources by evaluating the emissions from
individual fittings. Unlike the emission factor approach this method accounts for site-
specific differences. An organic vapor analyzer (OVA) is used to screen fittings for leaks
and to measure the methane concentration on the fitting at the leak. Tho fitting is then
bagged to determine an emission rate, and a correlation is developed between the OVA
concentration and the emission rate. Emissions from other facilities are then determined
by measuring leaks with the OVA and applying the correlation equation to establish an
emission estimate.
Although this is an EPA approved procedure for measuring emission rates (4), it has been
found to be inadequate due to shortcomings in conventional OVAs. The source of the
problem is that the pump in standard OVAs is too small. As a result small leaks may be
underestimated due to wind, variations in standoff distance of the probe from the leak, and
variations in pipe configurations. This led to variations in the data of up to several orders
of magnitude. Large leaks simply exceed the capacity of the instrument. When this
occurred the leak was bagged to determine the true emission rate. In this fashion it was
found that 70 to 80 percent of emissions occurred at large leaks and were being
undercharacterized.
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To correct this problem a new OVA with a larger pump was built, tested, and found to be
superior to conventional OVAs for this application. When it was used in this project at gas
production facilities and transmission stations, the variability in small leaks was reduced
to 10 to 20 percent and large leaks were shown to be fully characterized.
Leak statistics method: This method is used to evaluate leakage from buried pipelines in
distribution systems and gathering lines in production fields. Emission rates are measured
for a large number of leaks to accurately determine the average leak rate as a function of
pipe material, age, pressure, soil characteristics, and type of inspection and maintenance
program. The leak data recorded by individual gas distribution companies are statistically
analyzed to determine the actual number of leaks per mile.2 Total emissions from the
underground distribution system are calculated by multiplying the appropriate average
emission rate per leak by the number of leaks per mile and the number of miles of pipe in
each category.
Due to the expense and difficulty of mounting such a venture, a cooperative effort with nine
domestic and four foreign gas companies was developed to measure leakage from
distribution systems. Most of the data which are likely to be available within the timeframe
of this study have been received and analyzed. The data suggest that leak rate is a
function of pipe material for both mains and services, but insufficient data are available to
demonstrate a statistical relation between leak rate and age, pressure, or soil
characteristics.
As a separate part of this project, investigations at the University of New Hampshire and
Washington State University have investigated the microbial oxidation of methane as a
function of a variety of soil parameters. They have shown that, for very small leaks where
the residence time of the methane in the soil is high, oxidation can be as high as 90 to 95
percent. A conservative estimate of 20 percent has been used for the larger leaks normally
counted in this study.
Tracer gas technique: This method is applied by releasing a sulfur hexafluoride tracer at
a known rate from the methane source, and measuring the concentrations of both tracer
and methane at a point downwind where the two have mixed. Since downwind
concentrations of methane and tracer are known, and the release rate of the tracer is
known, a simple ratio allows calculation of the methane emission rate. Measurements are
made by Fourier transform infrared spectroscopy and real time samples are collected by
a van moving through the methane plume. This simple ratio technique, which requires
neither meteorological data nor modeling, is believed to be best applied at small sources.
In this study it was used at metering and pressure regulating stations.
91 mile = 1,6 kilometers.
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Calculation Techniques for Unsteady Emissions
Intermittent or unsteady emissions are highly variable over the course of a year. Since, in
a program of this scope, it is not feasible or affordable to measure emissions from any
specific source over an extended period of time, these emissions cannot be quantified by
sampling and must instead be calculated.
Each source of unsteady emissions requires a unique set of data and equations to quantify
its average annual emission rate. In general, all unsteady sources of emissions require the
following information in order to calculate annual emissions:
-	A detailed technical assessment of each source to identify the important parameters
affecting emissions;
-	Data gathered from multiple sites which allows the estimation of methane emitted per
emissions event; and
-	Data gathered from multiple sites which allows an estimate of the frequency of events.
An example of an emissions estimate calculated for an unsteady emission source is the
estimate for vessel blowdown during routine maintenance. In this case, the volume,
pressure, and temperature of gas contained in the vessel before blowdown is calculated
to quantify losses from the blowdown event. Additionally, an average frequency of these
vessel blowdown events is necessary to determine the annual losses *'rom this source of
methane emissions.
Extrapolation Methodology
Data in this project were collected for a limited number of sources and were extrapolated
to produce national estimates by source category. The extrapolation and statistical
sampling techniques employed in this study were selected to achieve a relatively high
degree of precision for the overall study while introducing negligible bias. Some degree of
precision was occasionally sacrificed in the smaller categories of emissions to achieve
relatively high levels of precision in the larger categories because this was the most
efficient and cost effective means of achieving the overall accuracy target for the project.
The extrapolation approach employed a method to scale up the average emissions from
a source, determined by a limited sampling effort, to represent the entire population of
similar sources in the gas industry. The extrapolation approach uses the concept of
emission and activity factors to estimate emissions based on the limited number of
samples. These factors are defined in such a way that their product equals the total
emissions from a source. The product of the emission and activity factors equals the total
annual nationwide emissions from a source in the natural gas industry.
Typically, the emission factor for a source represents the average emission rate per source
and the activity factor represents the total industry population of the source. The emission
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factor is the summation of all measured or calculated emission rates from each of the
sources sampled divided by the number of sources sampled. The activity factor is then the
total number of sources in the entire target population or source category.
Sampling approach: The details of the statistical design for this project will be the subject
of a separate report in the series of reports that will accompany the conclusion of this
project. It is necessary to understand generally how the sampling was done, however, in
order to accept the validity of the extrapolation methodology.
Initially, if existing data were not sufficient, a modest amount of data were collected to
determine if a given source was a major contributor to methane emissions. For each
source category, an initial estimate of the number of sources to be sampled was calculated
based on an estimate of the accuracy target and the estimated standard deviation for the
source category. The accuracy targets are based on the need, ultimately, to estimate the
national emission rate to within 0.5 percent of the national production rate based on a 90
percent confidence limit. Sites were selected in a random fashion from known lists of
facilities, such as GRI and American Gas Association member companies. However, the
companies contacted were not required to participate, and a complete list of all sources
for the U.S. was generally not available; therefore, the final set of companies selected for
sampling was not truly random.
After a limited set of data was collected, the data were screened for bias by evaluating the
relationship between emission rate and parameters that may affect emissions. If a
relationship between emissions and a parameter was found, then the population, or the
number of sources in the industry, was stratified by that parameter. For example, station
type was determined to influence the emission rates from metering and pressure regulating
stations, so the number of stations under each station type in the nation was determined.
Once the strata were identified, the precision of the emission rate extrapolated to a
national basis was evaluated and compared to the accuracy target. Where necessary,
additional data were collected in various strata to improve the precision of the national
estimate of emissions from the source. The number of additional data points needed to
meet the newly calculated accuracy target is computed based on the standard deviation
and a 90 percent confidence interval.
DISCUSSION
Over the history of the project, emissions from the individual industry segments and the
industry as a whole have been recalculated as additional pieces of information have been
received and, in some cases, industry boundaries have been redefined to more closely
approximate conventional practice. Although the estimate for the industry as a whole has
varied over this time, it has always remained within the range of 1.0 to 2.0 percent of
production. The last formal presentation of the project status was in March, 1994 at a
workshop in Prague, Czech Republic. Table 1 shows the emissions by industry sector as
they were presented at that time. Since then, considerable information has been added to
the database in the areas of both emission and activity factors and, while specific
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categories within the industry sectors have both increased and decreased, the overall
industry estimate has shifted upward by a modest amount. This movement is controlled
primarily by increases in emission estimates for production gathering lines and separators,
transmission compressor and metering stations, and in gas storage.
The database will continue to be expanded until the project draws to a close in the fall of
this year. Since the additional data can be expected to change the industry and sector
estimates somewhat, and because the analytical methodology must undergo a final
industry review, a revised table of estimates is not offered at this time.
When this project is completed, the database will be retained so that when significant new
data become available they can be incorporated and more current estimates of industry
emissions can be generated. The most plausible assumption, of course, is that industry
emissions as a function of production will decrease over time. New technology that can
reduce emissions is constantly made available and can be incorporated as worn
equipment is changed out. The gas industry could reasonably be expected to conserve the
finite resource on which its existence depends and will, therefore, probably accept these
technologies. In any case, the capability now exists to render a statistically based estimate
of future industry emissions in a very short time with the addition of any amount of new
data available.
ACKNOWLEDGEMENT
Although this study was largely funded and completely comanaged by EPA and GRI,
portions of the program were funded by the American Petroleum Institute and the
American Gas Foundation. The extensive cooperation of individual companies within the
gas industry was. in large part, responsible for the success of this study. Without their
advice, cooperation, and participation the level of detail achieved would not have been
possible. The author also wishes to acknowledge the contribution by Robert A. Lott of GRI
(comanager of this study) to much of the descriptive material on methodologies appearing
in this paper [5],
REFERENCES
1.	Smith, B. and Tirpak, D., The Potential Effects of Global Climate Change on the U.S.:
Report to Congress. EPA/230-05-89-050, U.S. Environmental Protection Agency, Office
of Policy, Planning and Evaluation, Washington, D.C. 13pp, 1989.
2.	Steele, L., Dlugokencky, E,, Lang, P., Tans, P., Martin, R., and Masarie, K., Slowing
down of the global accumulation of atmospheric methane during the 1980s, Nature. 358,
313-316, 1992.
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3.	Dlugokencky, E., Masarie, K., Lang, P., Tans, P., Steele, L., and Nisbet, E., A dramatic
decrease in the growth rate of atmospheric methane in the northern hemisphere during
1992, Ggopbys,.	Res. Letters. 21, 45-48, 1994.
4.	U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards,
Research Triangle Park, NC, Protocols for Generating Unit-Specific Emission Estimates
for Equipment Leaks of VQC and VHAP. EPA/450/3-88/010 (PB89-138689), October 1988.
5.	Lott, R. A., Estimate of Methane Emissions from U.S. Natural Gas Operations.
Presented at International Workshop on Environmental and Economic Impacts of Natural
Gas Losses, Prague, Czech Republic, March 22-24, 1994.
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TABLE 1; SUMMARY OF METHANE EMISSIONS (BCF/Yr)[5]
Segment
Steady
Unsteady
Total j
Production
39
144
183 !
Processing
2
4
6
Transmission & Storage
22
37
59
Distribution
65
4
69
TOTAL
128
189
317

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This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication.
GloED AND GloTech: GLOBAL EMISSIONS AND TECHNOLOGY
DATABASE SOFTWARE
Lee L. Beck
Air Pollution Prevention and Control Division
U. S. Environmental Protection Agency
Research Triangle Park, NC 27711
ABSTRACT
This paper describes two powerful software packages being developed by the U. S. Environmental Protection
Agency (EPA). One is emissions inventory software called GloED, and the other is a technology software called
GloTech. GloED compiles country and source specific inventories of emissions of greenhouse gases by combining
emission factors and activity data. GloTech computes cost and environmental impacts of technologies and technology
combinations. Both software packages arc very uscr-fricndly, integrate the data with its reference, and rely lieavilv on
graphics to assist the user.
INTRODUCTION
The Air and Energy Engineering Research Laboratory (AEERL) of EPA has developed two powerful software
packages which address global emissions and technology. Both are user-friendly, menu-driven tools which are in late
stages of development and are expected to have wide applicability. The emissions software is called GloED for "G/obal
Emissions Database." It is used for storage and retrieval of emissions factors and activity data on a country-specific
basis. Data can be selected from databases resident within GloED and/or generated by the user. The dam are used to
construct emissions scenarios which contain inventories of emissions for the countries and sources selected. Trie
scenario outputs can be displayed on thematic global maps or other graphic outputs such as bar or pie charts. In
addition, data files can be exported as Lotus 1-2-3, dBase, or ASCII files, and graphics can be saved as a .PCX file or
exported to a printer. The technology software is called GloTech for "G'/obal 7'ec/inology." GloTech enables the user to
select information from databases resident within the software and to change or add data as appropriate. Parameters of
the technologies are automatically grouped and accessed using icons selected by the user of the software. The user Ihcri
links the icons with other process icons as appropriate to assemble a process network. After the assembly is complete,
the software calculates the total cost and environmental impacts such as releases to the air, water, and land. GloTech
was developed with funding assistance from the Department of Defense Strategic Environmental Research and
Development Program (SERDP). Both GloED and GloTech arc user-friendly and allow information to easily be
updated so that current information is always available. To assure a clear data pedigree, reference and note fields are
associated with each piece of information and the user updates the reference as changes are made. This paper describes
the various functions of GloED and GloTech.
GloED and GloTech are complex (but not complicated) software packages. Because of this, it is not possible
to describe all of their utility in a brief technical paper such as this. The primary objective of this paper is to give the
reader a sense of what the capabilities of the software packages are capable of doing. Comprehensive documentation for
GloED has been prepared and is currently being reviewed. It should be available for distribution this summer. It is
anticipated that GloTech documentation should be available by the end of calendar year 1995. In the interim, the audior
is available by telephone at (919) 541-0617 to answer questions regarding either software package.
DESCRIPTION OF GloED
GloED is a tool for generating estimates of global emissions on a country- and source-specific basis. Most
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of the emissions da:a in GloED are the product of two numbers: emission factors and activity data. The emission
factor is the amount of emissions per source (e.g., methane emissions per coal mine). The activity data arc the number
of sources (e.g., the number of mines). The emission factor can vary spatially (e.g., by country), and the activity data
usually do. There is no provision for consideration of emission controls except to the extent that they are integral to
the emission factor. However, the user can construct "controlled" and "uncontrolled" datascts, or datasets with any
other assumptions for that matter. Note fields are provided for documentation of the assumptions. GloED stores
emission factors and activity data separately, each with its own reference, allowing the user to evaluate or change only
one component of the emission estimate.
The user selects one or more data sets and then has the option of narrowing the scope of the inventory by
selecting several countries, source categories, and pollutants that are resident within that data set. The final
compilation of data sets, countries, sources, fuels, and pollutants is called a scenario. GloED then calculates an
emissions inventory based on the scenario compiled by the user. GloED also can accept data provided by user-input.
Consequently, the emissions inventories can be updated as new data become available to the user.
The contents of the emissions inventories can be reported in a variety of ways. A text summary of the
emissions inventory will print a tabular breakdown of the results by country, source category, and/or pollutant.
GloED also can develop a pie chart or bar chart showing the countries with the greatest quantity of estimated
emissions in a form that allows easy comparison among them. Finally, GloED can project the results of an emissions
inventory onto a global map, using different colors to designate the type and distribution of pollutants in the selected
scenario. These output formats can be viewed on the screen, saved to a file, or printed as hard copy. The data also
can be exported to Lotus, dBase, or ASCII.
Each level of the program has a menu that allows the user to select the operations that the program will
perform at that level. The user can select the actions in the menu by clicking a mouse cursor on the desired menu
selection, by navigating the menu with the arrow and tab keys of the computer keyboard, or by typing the first letter
of the selection. The GloED main menu always appears along the top of the screen and is a set of pull-down menus,
which means that the user can "pull down" further options by selecting a menu item. When the user selects a menu
option-either with a mouse or with the cursor keys--GloED will lead the user to the screens that apply to that menu
option. Figure 1 shows some of the primary menu options and the secondary pull-dowr. menus. It is actually a
combination of five separate screens which GloED generates in response to the primary menu choices of Scenario,
Database, Reports, Exports, and Tools. The seven primary menu choices and their general functions are:
•	Scenario--This menu allows the user to Load a previously created scenario. Generate a new
scenario, Combine elements of two or more scenarios, Edit an existing scenario, or Delete a
previously created scenario.
•	Database--This menu allows the user to call up the database Editor to add or modify data, or to
Rebuild the database.
•	Mapping—Allows the user to display the emissions inventory in the form of a thematic map,
•	Reports-Allows the user to generate reports of the results of the inventory calculation in Text
form (as tables) or as graphics (Pie charts or Bar charts).
Exports -- Allows the user to use GloED to automatically generate a Lotus 1-2-3
spreadsheet or a dBase file, or to export the data as an ASCII file.
•	Tools -- This option allows the user to use the Units Converter of GloED as a
stand alone tool, or to access the Lotus Importer.
•	Exit -Allows the user to leave the program.
Mapping
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Once a scenario is defined and an emissions inventory is calculated for it, the user is ready to create a map that
reflects the results of the inventory. The map will appear on the computer's video monitor, and each country is
displayed in a color that corresponds to the scenario output. A legend is provided at the lower part of the map to enable
definition of the quantities associated with the colors. A monochromatic copy of a map of emissions from rice growing
is shown in Figure 2.
A series of buttons appears at the bottom of the map: Zoom, Unzoom, Print, PCX File, Query File, and OK.
The [Zoom] button allows the user to define an area of the map to enlarge. Tne area is defined using the mouse or
cursor keys to form a rectangle around the desired area. [Unzoom] returns the user to the full map. If the user clicks on
the [Query File] button and then moves the cursor within a country's border on the map and clicks again, a box with the
emission data for that country is superimposed on the screen.
The user clicks on the [Print] button to send the map to a printer. A dialog box will appear on the screen and
ask for selection of the available printer output port to which the file is to be sent. It will also request definition of the
type of printer available (either by selecting the name with the mouse or by pressing [ENTER] on the appropriate output
port and printer name). Finally, to save the map as a graphic .PCX file, the user clicks on the [PCX File] button, and a
dialog box appears and requests entry of a valid DOS file name (ending with .PCX) for the map file.
Other Graphical Reports
When the Reports option in the main menu is chosen, the menu that pulls down (see
Figure 1) gives three options: Text, Pie, or Bar. Selecting Pie or Bar in the Reports menu allows the user to have the
graphical report appear on screen, be sent to a printer, or saved on disk as a .PCX file. When the location for the
graphical output is designated, the user can select [OK] and the title screen will appear. In this screen, the user types the
primary title for the graphical report. The user can then press [TAB] or mouse-click on the second title field, and enter
the secondary title for the graph: GloED's default choice for the second field is units. The units of the scenario will be
written to the field unless overridden by the user. Figure 3 is an example of a pie chart and a bar chart. The charts
appear in color in GloED.
To present the results as a table, referred to here as a Text report, the user chooses the Reports option in the
GloED main menu. The user then can select the Generate option in a tertiary menu that will appear at the right of the
pull-down menu. A dialog box, called the GIIG Report Generator, will appear. It allows assignment of totaling
priorities to the pollutants, source categories, and countries that will appear in the tabular report.
When the report has been prepared, the GloED tertiary menu bar can be used to display the report on the
screen, to send it to the printer, or to save it on a disk in ASCII text format If the user chooses the "screen" option, the
report can be read like hard copy. This screen functions very much like the smaller scroll boxes in GloED. It has both
horizontal and vertical scroll bars. Mouse-clicking on the arrows at the ends of the bars moves one line per click in the
direction indicated by the arrow. For larger jumps in the report, the user can slide the narrow bars in the middle of the
scroll bars in the desired direction.
Exports
The Exports menu option is used to save the tabular results of the emissions inventory
to an additional file. When the user selects this option in the Reports pull-down menu, another menir pulls down and
gives the option of saving the report as a Lotus 1-2-3 file, a dBase file, or an ASCII file.
DESCRIPTION OF GloTech
GloTech is the name given to the AEERL Global Technology database software. It was initially conceived as a
companion to the GloED software. The thought was that by linking the two software tools, the user can examine
different technology scenarios and the consequent effects on global emissions. This idea may be implemented in a future
version of the software. However, the current version of GloTech is designed to be a stand-alone tool for assessing the
cost, performance, and environmental impacts of technologies.
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GloTech has many features in common with GloED. It is menu/mouse driven, very user-frieridly and relies
heavily on graphics to guide the user through its functions and to display results. It also has reference and note fields to
assure a clear data pedigree, and the user can use data resident within the software, change ihe default data, or add
his/her own. The major difference from GloED is that GloTech is programmed to run under the Microsoft® Windows®
environment.
Electronic File Cabinet
The heart of GloTech is a utility dubbed the "Electronic File Cabinet." This is a user-addressable aggregation
of files pertinent to a technology, and comprises the "Technologies Database." There arc six "folders" in each file
"drawer:" General, Costs. Releases, Inputs, Outputs, and Properties. Figure 4a shows an open folder for General
information from a coal-fired power plant with 1989 emission controls. The Technology Type field is used for
differentiation within a technology, such as the sulfur content of the fuel, where the difference will result in changes in
the parameters in one or more of the other folders (e.g., Releases). Clicking on this field will bring down a selection of
types of the technology entered in the database. The two icons at the lower right of the folder bring up additional
windows for the reference for the folder and notes. The "Icon" field shows the icon assigned to the file drawer, and the
user can click on this icon to change the icon or :o select an icon to assign to a new file drawer.
The "Releases" folder (shown in Figure 4b) has three icons that are not on the "General" folder. The sigma
icon (also on the inputs and outputs folders) brings up the GloTech Formula Editor which is a unique utility included
with the GloTech software. The Formula Editor shows the algoritlun used to arrive at the number in a selected field
(e.g., lbs. NOx per ton of aluminum). It allows for changes in the algorithm and also allows the user to enter and test an
algorithm. The white sphere icon (also on the inputs and outputs folders) brings up a window for viewing or editing the
properties of an item selected (e.g., type of aluminum alloy production). The bulls eye icon, found only on the
"Releases" folder, brings up the Data Attribute Rating System (DARS). DARS is a system developed by EPA/AEERL
to provide a ranking system for emissions inventories. By assigning a numerical value to components of an emission
factor (e.g., measurement technique used, temporal and spacial specificity) based on defined attributes, DARS generates
a semi-quantitative value that can be used to compare the selected emission factor with others [1],
Process Network Editor
The Process Network Editor (Figure 5) is where process "networks" are assembled and modeled. A process
network is a combination of processes linked together. The user assembles a network by selecting an icon from the
choices in the Technology field. Clicking on the down arrow at the left of the field displays all choices, or the user can
narrow the choices by using the Type Filter to select processes by input or output. Or.cc the desired process is located,
the user uses the mouse to click on the icon, and while holding tlie mouse button down, drags the icon onto the network
editor field which comprises the major part of the window. Once the desired processes are placed onto the network
editor, the user clicks on one a process "node." A node is one of the four red boxes which appear at the top, bottom, left,
and right of the icon after it is dropped onto the field. The first node selected becomes the output node of a process. The
user then clicks on a node of an adjacent process, and that node becomes an input node, as designated by a change in
color to green. Once the I/O pair is selected, a window appears which prompts the user for throughput data, and
whether the process is to be tagged. A tagged process will be identified by a large solid arrow and is the process on
which GloTech will base its model calculations. In the example in Figure 5, steel is the tagged process. Electricity
(generated by two processes: conventional and photovoltaic) and scrap are inputs to the steel production process.
Electricity is also an input to the scrap generating facility, and coal is an input to the conventional power production
plant. The user can go as far back as desired to incorporate processes (by adding icons) which contribute to the tagged
process.
Once the desired network is assembled, the user activates the Process Network Activity Builder and defines the
load value(s) and time step interval(s) for which to run the network model. The load value is the production rate, and the
time step interval is the specified time that the network operates under the defined conditions. Tlx time scries generator
is important in mar.y cases to achieve true life-cycle costs, since production, emission controls, and other parameters
frequently change over the life of the units in the process network. After the load and time intervals are defined, the user
clicks on the Run List button, and GloTech calculates inputs, outputs, releases, and costs for each time step.
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Viewing the results
GloTech technologies or the results of the GloTech network calculations can be viewed in text or graphical
form. To view the data in tabulated form (text), the user clicks on Reports form the main menu. This brings down a
secondary menu for the user to select either Technology or Network. By selecting Network, a window appears where
the user chooses the network to be the subject of the report. The user may choose to print the results at this point.
However, GloTech offers the advantage of ranking networks or technologies. To activate the ranking feature, the user
selects several networks (or technologies) and then selects from a pull-down menu in the Report Generator window
whether to rank the networks (or technologies) by cost, releases, inputs, or outputs. The user then clicks on the Rank
button, and selects whether to generate a screen report to be viewed on the computer monitor, or a report to be sent to a
printer or a file, A file name is requested if a file is to be prepared.
GloTech also offers the added advantage of viewing data in graphical form by using the Process Chart viewer.
This is done by clicking on any process icon (tagged or untagged) in the Process Network Editor field. That process is
then highlighted by the computer, and its name appears on the status line. The user then clicks on the "bar chart" icon in
the Flow Editor "toolbox," which appears whenever the Process Network Editor is activated. This activates the Process
Chart viewer. Figure 6 shows a 3-D Bar which represents air releases from a steel production facility in a network. The
results of time series charts can be viewed in a similar way to show the relative change in, for instance, emissions for the
time steps run.
SUMMARY AND COMMENTS
The EPA/AEERL has developed two powerful software packages. GloED software compiles emissions
inventories from data selected from databases resident within the software or entered by the user. It provides the results
in graphical displays or text. Though it was developed as a repository and compiler of data on greenhouse gases, it is
compatible with any emission dila entered by the user. GloED compiles data on a source and country specific basis.
GloTech is technology evaluation software. It has a technologies database resident within the software. It also
can accept data entered by the user. The technology information is accessed via icons which arc linked together to form
process networks. GloTech can be used to store and rank information on technologies. This makes it a useful too! for
comparing technologies on the basis of cost; environmental releases, or other parameters. GloTech also calculates the
total impacts from a technology network. Because of this unique ability to calculate total impacts, GloTech is useful as a
tool for assessment of life-cycle impacts.
REFERENCES
1. Beck, L.L., R.L. Peer, L. A. Bravo, and Y. Yan. A Data Attribute Rating System. Presented at "The
Emissions Inventory: Applications and Improvement," Sponsored by the Air and Waste Management
Association. November 3, 1994. Publication of proceedings in progress.
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Scenario Database
Mapping
Reports Exports Tools Exit
Methane Emissions from Rice Growing
Tg/yr
O-
<	3.00E-03
<	9.0QE—03
<	2.00E—02
I
<	4.00E—02
<	7.00E—02
<	2.00E—01
< 4.00E—01
C 2
D < 30

Figure 2. Global Map Generated by GIotD.

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Methane Emissions from Rice Growing
To/V*
¦ INDIA
ts china
*i THAILAND
m BANGLADESH
M BURMA
¦ VIETNAM
m INDONESIA
¦I BRAZIL
m *JAPAN
S OTHER
Scenario Database HAppin? | Reports S^pts Tools Exit
Figure 3. GloED Pie and Bar Charts.
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Technologies Database
Figure 4a. "General" Folder
og
to
Figure 4b. "Releases" Folder
Figure 4. File Folders

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GloTech Beta 0.9 Rev. 5
File View Ratabase Reports filoED Tools Windows Help
=« Flow Editor

EjS
3
m
flyH
Figure 5. Process Network Editor

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GloTech Beta 0.9 Rev. 5
File View Database Reports GloED Tools Windows Help
3es" are'chos'en from the list included with GloTech, or from the
ones constructed'by thq user. They are linked using the "Process Network,
Editor." GloTech prompts the user for inputs,, then computes the throuputs,
environmental celea^s^and.costs. ^Dat^can,beTdisptay6d usingnumericaf
or graphiGals^splsys-.* Jidi	^ r-
SQk NQm N3D PM VOC CH< 00 002
Pot1\Hapts
Figure 6. Process Chart Viewer

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This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication.
OVERVIEW OF EPA'S GLOBAL CLIMATE CHANGE
RESEARCH PROGRAM ON WASTE MANAGEMENT
Susan A. Thorneloe
U.S. Environmental Protection Agency
Air Pollution Prevention and Control Division
Research Triangle Park, North Carolina 27711
Randy Strait and Michiel Doom
E. H. Pec'nan & Associates, Inc.
3500 Westgate Drive, Suite 103
Durham, North Carolina 27707
Bart Eklund
Racian Corporation
P. O. Box 201088
Austin, Texas 78720-1088
ABSTRACT
This paper provides an overview of ongoing research at EPA's Air Pollution
Prevention and Control Division (APPCD), the former Air and Energy Engineering
Research Laboratory, on greenhouse gas emissions from waste management.
Sources being evaluated include landfills, open dumps, waste piles, wastewater
(treated and untreated), septic sewage, and agricultural waste. Earlier estimates
have suggested that waste management accounts for -70 teragrams (1012 grams)
per year (Tg/yr) of methane (CH4) globally (NATO, 1993) or 19% of total global CH4
anthropogenic emissions of 360 Tg/yr (IPCC, 1992). However, this estimate ranges
from 54 to 95 Tg/yr and is considered very uncertain due to limitations in available
data for establishing credible emission factors and limitations in country-specific
activity data. Due to landfills and possibly other waste sources being amenable to
cost-effective control, these sources have been given a priority for developing more
reliable estimates and identifying cost-effective opportunities for greenhouse gas
(GHG) reductions. Primarily due to the ability to utilize the CH4 for its energy
potential, this is a relatively cost-effective source of GHG emissions to control (Rubin,
et a!., 1992, Augenstein, 1992). Emission sources that are amenable to control - such
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as landfills - have been given a high priority for clarification (EPA, 1989). The
research described in this paper is funded through the U.S. EPA's Global Climate
Change Research Program. This research is part of a larger EPA research program
to develop more reliable GHG emission estimates for the major sources and to identify
cost-effective opportunities for reducing GHG emissions. This research is being
conducted in support of the goals established at the United Nations Conference on
Environment and Development in 1992 and the Climate Change Action Plan (1993).
INTRODUCTION
The United States and other countries are working to develop more reliable
estimates of GHG emissions as part of the United Nations' Framework Convention on
Climate Change (FCCC) (EPA, 1994). Developing systematic and consistent estimates
of emissions at the national and international levels is a prerequisite for evaluating the
feasibility and cost-effectiveness of mitigation strategies and emission-reduction
technologies. The EPA's Office of Research and Development (ORD) is helping to
support program office needs through the development of emission factors and
methodologies for estimating U.S. and global emissions. The Air Pollution Prevention
and Control Division of the National Risk Management Research Laboratory has
responsibility for this research.
The atmospheric concentration of methane (CH4) has risen substantially during
the past few hundred years. From 1980 until very recently it was rising at between
15 and 18 parts per billion by volume (ppbv) annually, the fastest rate observed to
date (Blake and Rowland, 1988). This CH4 increase has been confirmed by numerous
research groups worldwide (Blake, 1994). The increase is attributed to increased
emissions associated with human activities. Sources include coal mining, natural gas
production and transmission, rice cultivation, inefficient fires or combustion sources
such as cookstoves used in a majority of the world's households, and waste manage-
ment activities including facultative lagoons used in developing countries and sanitary
landfills in use in industrialized countries. Even open dumps have been found to be a
source of CH4 emissions and often are a source of tropospheric ozone precursors
resulting from waste fires.
CH4 buildup, from 1980 to 1990, was calculated to contribute about 20% of
the radiative forcing increase due to the buildup of all GHGs taken together during
that period. Blake has reported that the 10 years of CH4 increase could be
responsible for about 20% of the recent "greenhouse effect" (Blake, 1994). Landfill
gas recovery and abatement has been estimated as one of the lowest cost of
possible options to slow the buildup of radiatively forcing gases in the atmosphere
(Rubin, et al., 1992, Augenstein, 1992). Other sources of waste management offer
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cost-effective opportunities for GHG reductions and are regarded as a priority for
evaluation.
Waste management is a major source of CH4 and a source of other GHGs
including nitrous oxide (N20), carbon dioxide (C02), and tropospheric ozone
precursors. Prior to the initiation of EPA's ORD research program, limited field work
had been conducted to establish the GHG potential for the different waste
management activities. Earlier estimates often relied on optimistic assumptions
regarding the extent of anaerobic decomposition and limited (if any) field data
characterizing the GHG emission potential. The EPA/ORD is conducting field test
measurements for those sources where emissions are considered potentially
significant and appear amenable to cost-effective control.
This paper summarizes the results of work recently completed to estimate CH4
emissions from municipal solid waste (MSW) landfills and open dumps using emissions
test data for landfill gas recovery projects. The paper also summarizes research
where field measurements are being conducted to develop more reliable GHG emission
estimates for wastewater treatment sources. The paper concludes by presenting
EPA/ORD's plans for (1) conducting field measurements for other waste management
sources to develop credible U.S. and global emission estimates for each source, and
2) identifying opportunities for cost-effective reductions of GHG emissions such as the
utilization of the waste CH4 where it is technically and economically feasible.
LANDFILLS
The initial focus of EPA's research program for wasto management was on
MSW landfills and open dumps (Thorneloe, 1993 and 1994). Landfills and open dumps
are major sources of CH4 which is produced via the anaerobic decomposition of
buried waste, with global estimates ranging from 10 to 70 Tg/yr. Global
anthropogenic sources have been estimated to emit 360 Tg/yr (IPCC, 1992), which
suggests that landfills and open dumps account for 3 to 19 % of the total. Previous
U.S. and global estimates of CH4 use first order rate decomposition models, some of
which include optimistic assumptions on the amount of carbon (i.e., 80 to 100%) that
is converted to CH4 in a landfill and emitted to the atmosphere. A major uncertainty
in the estimates is that they do not use field test data for estimating CH4 emissions
from landfills. Consequently, it was difficult to determine which of the previous
estimates more accurately reflect actual emissions from landfills and the potential
amount of CH4 that is amenable to control through utilization or abatement.
To address this concern, EPA/ORD began a research program in 1990, aimed
at using field data from landfill gas recovery projects to develop an empirical model
relating landfill gas flows to waste in place. This research aiso involved identifying key
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variables that affect CH4 generation from buried waste. Landfills with gas recovery
systems, where landfill gas is extracted, collected, and measured by personnel on site,
offered a unique opportunity for studying CH4 emissions and variables that affect CH4
generation. Often reliable data are available documenting the quantity and
composition being collected. Landfill data such as waste composition, quantity, and
age are more difficult to ascertain. A quality assurance plan was developed in
determining how to collect, review, and analyze these data. Results of this research
are documented in a series of peer-reviewed EPA reports (Campbell et al., 1991, Peer
et al., 1992; Doom, Stefanski, and Barlaz, 1994; Doom and Barlaz, 1995), The results
of this research led to the development of an empirical model for estimating CH4
emissions. The model was developed with field test data from 105 landfill gas
recovery projects in the U.S. (Peer et al., 1992; Doom, Stefanski, and Barlaz, 1994;
Doom and Barlaz, 1995). Waste in place data were obtained from a survey of
landfills that EPA conducted in 1986 (EPA, 1988). The survey involved a stratified
random sampling approach to collect waste-in-place data for about 1,100 landfills in
the U.S. Statistical methods were then used to estimate total waste-in-place from
the sample. The total waste-in-place estimate was used in the empirical model to
estimate CH4 emissions for the U.S.
Table 1 provides. EPA/ORD's estimate of CH4 emissions from U.'S. landfills using
an empirical model and estimate of total waste in place. The EPA/ORD's estimate for
1992 ranges from 9 to 18 Tg/yr, with a mid-point of 13 Tg/yr. Annual waste
acceptance rates were used to project emissions to 1990 and 1992.
Table 2 provides a comparison of EPA/ORD's estimate to four other estimates.
The other estimates were developed using first order rate decomposition models to
estimate CH4 emissions. The mid-points of two of the previous estimates ranged
from 5 to 7 Tg/yr higher than the EPA/ORD estimate. The mid-points of the other
two estimates ranged from 3 to 7 Tg/yr lower than the EPA/ORD estimate. The
results of this comparison show that the EPA/ORD estimate lies about half way
between the range of the previous estimates.
The EPA/ORD prepared global estimates (Doom and Barlaz, 1995) using the
empirical model previously described. Country-specific waste generation data were
used where data were available. The global CH4 estimate for 1990 ranges from 19
to 40 Tg/yr, with a mid-point of 30 Tg/yr. Table 3 shows EPA/ORD's global estimate
compared to estimates developed using first order rate decomposition models.
Estimates based on the other methodologies range from 10 to 70 Tg/yr. Two of the
previous estimates have mid-points that are 20 to 32 Tg/yr higher than the EPA/ORD
estimate. One of the previous estimates has a mid-point that is one-half lower than
the EPA/ORD estimate. The United States is the biggest contributor to global CH4
emissions; accounting for about 45% of EPA/ORD's global estimate.
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Many developed countries are initiating incentive programs or are developing
regulatory requirements for MSW landfills that could result in a reduction of ChMrom
landfills. Several countries are adopting source reduction and recycling programs to
reduce the paper fraction in landfills and consequently the CH4 potential. The
Netherlands has adopted a stringent composting program that segregates vegetable
and garden waste from the remaining waste stream. Aiso, more stringent controls
for landfill gas emissions are being considered by many countries. The United
Kingdom, as do several other countries, has an incentive program that encourages
CH4 utilization. The United States has proposed federal regulations for MSW landfills
that, if implemented, are estimated to result In a CH4 reduction of 5 Tg/yr by the year
2000. As different programs are implemented over the next several years EPA/ORD
will have a better understanding of their effect on CH4 emissions from landfills:
The potential CH4 reduction that may result from these incentives and/or
regulatory controls may not be realized if economic development and overall
population growth -¦ especially in developing or newly industrialized countries -- result
in more absolute waste generation. Also, in developing countries, there is a distinct
intent to improve solid waste management methods for sanitation reasons. Better
solid waste management methods in these countries may increase the amount of
waste that will be landfilied (i.e., undergoing anaerobic conditions) and thus increase
CH4 emissions.
Substantial uncertainty in the global estimates results from limitations in data
characterizing: (1) country-specific waste generation; (2) waste management
practices; (3) CH4 potential of the waste in place; and (4) CH4 that is emitted from
waste piles and open dumps. This uncertainty is characterized in the EPA reports
that document the methodology and estimates of U.S. and global CH4 from buried
waste (Doom, Stefanski, and Barlaz, 1994; Doom and Barlaz, 1995). Improvements
in activity data, emission factors, and other information characterizing the emission
potential will be used to update these emission estimates.
WASTEWATER TREATMENT
Current EPA research is directed towards characterizing the emission potential
associated with domestic and industrial wastewater treatment sources. Wastewater
can typically be characterized as domestic, industrial, or a combination of both. This
summer EPA/ORD will be sampling five to seven facilities to characterize the GHG
emission potential from wastewater treatment. These data will be used to develop a
methodology and improved emission estimates for wastewater. This paper provides
an overview of the technical approach that EPA/ORD plans to use for this field test
program.
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The specific objectives of this research include:
•	Developing more accurate global and U.S. estimates for CH4i nonmethane
organic compound (NMOC), N2O, and CO2 emissions from waste
management sources:
•	Identifying strategies and technologies for reducing GHG emissions from
waste management sources; and
•	Evaluating future trends in GHG emissions from waste management
sources.
The emission inventory development methodology will involve identifying representative
emissions sources, developing emission factors, and developing activity data that can
be used with emission factors to extrapolate emissions to an entire source category.
Procedures for reviewing the quality of the emission estimates and assessing the
uncertainty associated with the estimates will be developed. The uncertainty
associated with the emission estimates should account for the cumulative uncertainty
associated with emissipn factors, activity data, and extrapolating emission estimates
from a sample of sources to the entire source category.
The major thrust of this research will be to develop emission factors through a
field testing program and to minimize uncertainties associated with current U.S. and
global estimates. Because it will be impossible to obtain country-specific emission
estimates for every country in the world, it will be necessary to develop
methodologies that will ailow for the extrapolation of emissions from a sample of
sources that are representative of a large population of sources. Therefore, to
ensure the most efficient use of field testing dollars, it will be necessary to develop a
clear understanding of the waste stream characteristics, how they vary worldwide,
and their GHG emission potential. This will be achieved by stratifying a source
category by differences in waste stream characteristics that affect emissions [e.g.,
material inputs, decomposition environments (i.e., anaerobic vs. aerobic), climatic
conditions (e.g., rainfall and temperature), operating conditions, and control level] and
assessing the emission potential associated with the differences in source
characteristics. Decisions will then be made on prioritizing subcategories for
developing emission factors, activity data, and emission estimates.
The current methodology for estimating CH4 emissions from wastewater
developed by EPA/APPCD is documented in Chapter 10 of the Report to Congress
entitled: International Anthropogenic Methane Emissions: Estimates *or 1990 (EPA,
1993b). For industrial estimates, the current methodology involves the use of world
wastewater outflow, a biochemical cxygen demand (BOD) loading factor for
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wastewater, an emission factor (i.e., kg CH4/kg BOD), and an estimate of the fraction
of wastewater that is anaerobically digested. Country-specific estimates are not
provided because country-specific wastewater volumes were not known. However,
the methodology for domestic wastewater allows for country-specific estimates by
use of country population, a per capita BOD factor (i.e., kg BOD/day), an emission
factor (i.e., kg CH4/kg BOD), and an estimate of the fraction of wastewater that is
anaerobically digested. Country-specific BOD estimates were developed from the
literature.
Since completion of the EPA 1993b report, EPA/ORD has developed better
activity data and is scheduling field tests to develop more accurate estimates of
emissions. Measurement of emission rates from many of the waste management
sources presents a unique problem because they are area sources, so emissions
cannot be easily collected through a duct or stack for conducting sampling with
traditional methods. The EPA completed a field test program in 1993 to evaluate the
technical feasibility of the open path monitoring-transect method (OPM-TM) and
Fourier Transform Infrared (FTIR) spectrometry to measure GHG emissions. Based on
the results of these measurements, we plan to use FTIR for developing data at
additional sites.
Figure 1 shows a simplified schematic of the OPM-TM, which is used to measure
emission plumes. The entire gas plume is transected by the sampling axis at a
measured distance downwind of the emission source. The vertical profile can be
determined by several methods, for example by using a tracer gas in conjunction with
FTIR spectrometry measurements. If the total cross-sectional area of the plume is
covered during sampling, the plane of sampling is perpendicular to the prevailing wind,
and the species concentration is constant, then the species concentration in the plume
at the sampling plane is equal to the amount being emitted.
The light beam from the FTIR interacts with the molecules along the entire light
path. The parameter measured by the FTIR is a path integrated concentration and
has units of concentration times distances (e.g., ppm'meters). The FTIR
transmitter/receiver and the retroreflector mark the ends of the path through which
the entire emission plume, or a known fraction of the plume, must pass. This path
length can be as long as 500 meters (250m x 2). The exact path length required to
ensure that the plume is captured Is dependent upon the wind speed, the distance
from the source, and the variability in the wind direction.
Emission rates for specific compounds will be developed from the ambient air
concentration data obtained during the transect sampling. The simplest method of
calculating an emission rate is to use a tracer gas and ratio the measured
concentrations of the tracer gas and the compound of interest and use this as a
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multiplier to the known emission rate of the tracer gas to obtain the emission rate of
the compound of interest. This ratio method is illustrated as:
Q(t)S0Ufce =	Where: Q(t)lracer is known, and
Q(0tracer Xm*	XS0UrCe and Xtracer are measured by FTIR.
This approach is limited by the degree to which the tracer release approximates the
emission source and, in some cases, by differences in atmospheric transport between
the tracer gas and the compound(s) of interest.
The FTIR data will be collected and analyzed in 5-minute samples. A 5-minute
sample consists of approximately 128 independent measurements which will be
averaged to produce the sample value. The infrared spectrum for each sample file will
be time stamped and saved to the computer. The FTIR system Is capable of real
timo quantification of 25 compounds, and additional compounds may be quantified
from the stored data, if needed. Once quantified, the concentration data will be time
stamped and written to a data file.
A meteorological station wiil be used to collect temperature, wind direction, and
wind speed data at 2, 6, and 10 feet above ground surface. These data will be
collected by the computer at 5-minute intervals and written to the concentration data
file described above.
To assist in the interpretation of the data collected from OPM, process
operational data will be collected at each site such as physical and chemical
properties of the waste material [e.g., pH, BOD, chemical oxygen demand (COD),
percentage solids, density]; design parameters (e.g., dimensions, surface area); and
operating parameters (e.g., retention time, flowrates).
Results from the wastewater research should be available by this fall. Technical
reports will be prepared for each set of field measurements. These reports will
describe the sites studied and the experimental approach used, document the results
of the sampling, interpret and discuss the results, document the results of the quality
control checks, and present conclusions. The emission factors that are developed will
be used in the emission estimation methodologies along with activity data to develop
U.S. and global estimates.

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FUTURE RESEARCH
Below is the planned schedule for conducting research on the different waste
management categories.
•	94/95	Wastewater treatment (industrial and domestic)
•	95/96	Septic sewage, untreated wastewater, and agricultural waste
•	96/97	Open dumps, waste piles, and open burning of waste
•	97/98	Landfills (industrial, construction & demolition debris,
codisposal and closed)
•	98/99 MSW Landfills (other GHGs and update of CH4)
•	95/99 Assessment of technical feasibility and cost-effectiveness of
alternative control techniques for each waste category
SUMMARY AND CONCLUSIONS
The EPA is conducting research to develop more reliable estimates for
characterizing the GHG potential from waste management sources. The major thrust
of this research is the development cf improved and/or nonexistent emission factors
through field measurements using OPM. The current effort is on wastewater
treatment, and future years will evaluate the other sources including septic sewage
and untreated waste water, agricultural waste, open dumps, waste piles, open
burning of waste, and landfills (industrial, construction & demolition debris, codisposal
and closed, and MSW). This research will also focus on identifying cost-effective
control options for reducing GHG emissions. The research described in this paper is
furdec through the EPA Office of Research and Development's engineering research
program on Global Climate Change.
REFERENCES
Augenstein, D.C. 1990. Greenhouse Effect Contributions of United States Landfill
Methane. GRCDA 13th Annual Landfill Gas Symposium, Lincolnshire, IL.
Augenstein, D.C. 1992. The Greenhouse Effect and U.S. Landfill Methane. Global
Environmental Change. 2, 317-329.
Bingemer, H.G, and P.J. Crutzen. 1987. The Production of Methane from Solid Wastes.
Journal of Geophysical Research, Vol. 92, No. D2, 2181-2187.
Blake, D.R. and F. S. Rowland. 1988. Worldwide Increase in Tropospheric Methane,
1978 to 1987. Science, 239, p. 1129.
Blake, D.R. and D. C. Augenstein, "Methane's Role in Atmospheric Change," presented
2-93

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at the 17th Annual Landfill Gas Symposium, March 22-24, 1994, Long Beach, CA.
Campbell, D. et al., Analysis of Factors Affecting Methane Gas Recovery from Six
Landfills, EPA-600/2-91-055 (NTIS PB92-101351), September 1991.
Doom M. and M. Barlaz, Estimate of Global Methane Emissions from Landfills and Open
Dumps, EPA-600/R-95-019 (NTIS PB95-177002), February 1995.
Doom M., L. Stefanski, and M. Barlaz, Estimate of Methane Emissions from U.S.
Landfills, EPA-600/R-94-166 (NTIS PB94-213519), September 1994.
IPCC (Intergovernmental Panel on Climate Change). 1992. Climate Change 1992. The
Supplementary Report to the IPCC Scientific Assessment.
IPCC/OECD, Draft Guidelines for National Greenhouse Gas Inventories. 1994.
NATO. Atmospheric Methane: Sources, Sinks, and Role in Global Change. Series I,
Global Environmental Change, Vol. 13, Edited by M. A. K. Khalil. 1993.
OECD (Organization for Economic Cooperation and Development). 1991. Estimation
of Greenhouse Gas Emissions and Sinks. Finai Report from OECD Experts Meeting, 18-
21 February 1991, Paris, France. Prepared for Intergovernmental Panel on Climate
Change. OECD, Paris, France.
Peer, R. et al., Development of an Empirical Model of Methane Emissions from Landfills,
EPA-600/R-92-037 (NTIS PB92-152875), March 1992.
President Clinton and Vice President Gore, "The Climate Change Action Plan." October
1993.
Rubin, E.S., R. N. Cooper, R. A. Frosch, T. H. Lee, G. Marland, A. H. Rosenfeld, and D. D.
Stine. 1992. Realistic mitigation Options for Global Warming. Science, 257, p. 148.
Thomeloe, S.A., "Landfill Gas and Its Influence on Global Climate Change," Presented at
Sardinia '93, Fourth International Landfill Symposium, Cagliari, Italy, October 9-14,
1993.
Thomeloe, S.A., "Emissions and Mitigation at Landfills and other Waste Management
Facilities," In Proceedings: The 1992 Greenhouse Gas Emissions and Mitigation
Research Symposium, EPA-600/R-94-008 (NTIS PB94-132180), pp. 4-46 thru 4-57,
January 1994.
2-94

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U.S. EPA, National Survey of Solid Waste (Municipal) Landfill Facilities. U.S. EPA, Office
of Solid Waste and Emergency Response, Washington, DC. EPA/530-SW-88-034 (NTIS
PB89-118525).
U.S. EPA, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-1993. EPA-230-
R-94-014 (NTIS PB95-138079), September 1994.
U.S. EPA, Anthropogenic Methane Emissions in the United States: Estimates for 1990.
Report to Congress, 1993a.
U.S. EPA, International Anthropogenic Methane Emissions: Estimates for 1990. Report
to Congress. 1993b.
U.S. EPA, Policy Options for Stabilizing Global Climate. Developed by the Office of
Policy, Planning and Evaluation. Draft Report to Congress. PB90-182704 Vol. 1,
Chapters l-VI; PB90-182312, Vol. 2, Chapters VII-IX; and PB90-182494, Executive
Summary, February 1989.
2-95

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TABLE 1. TOTAL METHANE EMISSIONS FROM U.S. LANDFILLS

1986 j 1992
Total Municipal Waste in Place (Tg)
4,720
6,200
Landfill Gas Flow Rate (104 m3/min)
5.3
6.6
Estimated Emissions from Municipal Landfills (Tg/yr)
11.2
14.2
Emissions from Industrial Landfills (Tg/yr)
0.55
0.72
Methane Currently Recovered or Flared (Tg/yr)i
1.22
(1.1)
1.7
(1.5)
Estimated Total U.S. Emissions (Tg/yr)
Lower bound
7
9
Mid-point
11
13
Upper bound
1 5
18
1	Amount of recovered CH4. is adjusted to account for the CH4 that would have been oxidized if
allowed to diffuse through the soil cover. This is estimated to be 10%. The adjusted amount is
in parentheses.
2	Amount of CH4. recovered in 1986 assumed to be 70% of 1992 value.
2-96

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TABLE 2. COMPARISON OF ESTIMATES OF METHANE EMISSIONS
FOR U.S. LANDFILLS
Source
Emissions Estimate (Tg/yr)

Lower
bound
Mid-
point
Upper
bound
Bingemer & Crutzeni
(1987 estimate)
11
(+4)2
16
( + 5)
21
( + 6)
IPCC/'OECD Method3
(1990 estimate)

20
( + 7)

Augenstein4
(1990 estimate)
3
(-5)
6
(-7)
8
(-9)
EPA/OAP, Global Change Divisions
(1990 estimate)
8
(0)
10
(-3)
12
(-5)
EPA/ORD Study«
(1986)
7
11
15
(1990 estimate)
(1990)
8
13
17

(1992)
9
13
18
1	Bingemer, H.G. and P.J. Crutzen. 1987.
2	Except for the Bingemer & Crutzen estimate, values in parentheses show the difference in
the estimates relative to the EPA/ORD estimate for 1990. For the Bingemer & Crutzen
estimate, values in parentheses show the difference in the estimates relative to the EPA/ORD
estimate for 1986 (Doom, Stefanski, and Barlaz, 1994). A plus sign indicates the estimate
is higher than the U.S. estimate; a minus sign indicates the estimate is lower than the U.S.
estimate.
3	Organization for Economic Cooperation and Development (OECD). 1991. February 1991,
Paris, France. Prepared for Intergovernmental Panel on Climate Change. OECD, Paris,
France.
4	Augenstein, D.C. 1990.
5	U.S. EPA, 1993a.
6	Doom, Stefanski, and Barlaz, 1994.

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TABLE 3. GLOBAL ESTIMATES OF METHANE EMISSIONS
FROM LANDFILLS AND OPEN DUMPS
Source
Emissions Estimate (Tg/yr)

Lower
Mid-
Upper

bound
point
bound
Bingemer & Crutzen^
30
50
70

(+11)2
(+20)
(+30)
OECD, 19913

62



(+32)

Richards, 19894
10
15
20

(-9)
(-15)
(-20)
EPA/ORD5
19
30
40
(1990 estimate)



1	Bingemer, H.G. and P.J. Crutzen. 1987.
2	Values in parentheses show the difference in the estimates relative to the EPA/ORD estimate.
A plus sign means the estimate is higher than the U.S. estimate; a minus sign means the
estimate is lower than the U.S. estimate.
3	Uses Intergovernmental Panel on Climate Change (IPCC)/Orcanization for Economic
Cooperation and Development (OECD) methodology with updated country-specific data on
MSW generation rates (iPCC/OECD, 1994).
4	Potential emissions, not corrected for the amount that is flared or utilized.
5	Doom and Barlaz, 1995.
2-98

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FIGURE 1. TRANSECT SAMPLING USING AN OPEN PATH MONITOR
Virtual
Plume
Boundary
Virtual
Point
Source
l
Reflecting
Optic-j-
Plume
Centoriine-
Srte
Operations

FT1R
Virtual
Plume
Boundary
2-99

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This paper has been reviewed in accordance with the U.S. Environmental Protection Agency s peer and
administrative review policies and approved for presentation and publication.
GREENHOUSE GASES FROM
WIDELY USED SMALL-SCALE COMBUSTION DEVICES IN
DEVELOPING COUNTRIES:
PHASES I - II: STOVES IN INDIA AND CHINA AND
PHASE IE: CHARCOAL KILNS IN THAILAND
Kirk R. Smith and Junfeng Zhang
East-West Center, Honolulu, HI 96848
Susan A. Thorneloe
Air Pollution Prevention & Control Division
United States Environmental Protection Agency
Research Triangle Park, NC 27711
ABSTRACT
Small combustion devices such as stoves and charcoal kilns in developing
countries are individually small, but so numerous that, depending on their emission
factors, they could possibly influence global inventories of greenhouse-related gases.
A pilot study in Manila found that such devices do seem to have high enough
emission factors to be of interest, and thus a larger set of studies is being undertaken
in India, China, and Thailand to determine emission factors for a wide range of the
kinds of stove/fuel combinations and charcoal kilns of common use in developing
countries. Briefly described here are the protocols being used in these studies.
INTRODUCTION
Although individually insignificant, household and other small-scale
combustion devices in developing countries are sufficiently numerous to potentially
affect national and global inventories of greenhouse-gas emissions. Few
measurements have been made in developing-country conditions, however.
Consequently, the U.S. EPA funded a pilot study in Manila by the East-West Center,
Oregon Graduate Institute of Science and Technology, and the University of the
Philippines. Results (Smith et al.f 1993) show that the combustion conditions of
household stoves using several common fuels, wood, charcoal, gas, and kerosene,
divert rather a high proportion of fuel carbon into non-carbon-dioxide (CO?)
greenhouse gases (products of incomplete combustion); i.e., carbon monoxide
(CO),me thane (CH4), and total non-methane hydrocarbons (TNMHCs).* If verified,
these results would lead to several counter-intuitive and policy-relevant conclusions,
the most important of which are that:
* Also determined in this pilot study were the emission levels of nitrous oxide (N2O) and over
60 individual hydrocarbons (Smith et at., 1992).
O 1 AA

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• biomass fuel cycles are not necessarily greenhouse-gas neutral
even when the fuel is harvested on a completely renewable basis,
and
- substituting fossil for biomass fuels can sometimes be
recommended as a greenhouse-gas control measure.
The conclusion of the pilot study, therefore, was that this avenue of research has
potentially important policy implications related to the relative greenhouse potential
of biornass-based fuel cycles as well as providing valuable increases in accuracy for
global emission inventories.
Consequently, much larger studies in India and China are now being
conducted. These focus on the 25-30 most common stove/fuel combinations in
each nation. Since these two countries contain two-thirds of all stoves in developing
countries, the stoves in this study represent a large fraction of the combinations in
use worldwide. Monitored are approximately 70 gaseous species as well as the
composition of emitted particulates, remaining ash, and the original fuel with the
purpose of elucidating the entire carbon balance for each stove/fuel combination. A
secondary benefit of this work is that it will enable a more detailed analysis of the
energy and health aspects of these fuel cycles and their trade-offs by use of the
Triple Carbon Balance (TCB) analysis method developed as part of this research (Smith
and Thorneloe, 1992; Smith, 1995).
Preliminary TCB analysis of the charcoal fuel cycle indicates that the.
greenhouse-gas emissions from traditionally inefficient charcoal making may be
quite high in developing countries (Smith and Thorneloe, 1992). No systematic
measurements seem to be available in the literature, however. This project,
therefore, will monitor emissions from traditional and modern charcoal kilns in the
three major charcoal-using parts of the developing world: Southeast Asia, Africa, and
Brazil. If borne out by actual measurements, these high emissions would have
immediate policy relevance in international greenhouse gas negotiations and
remediation project planning.
SAMPLING PROTOCOL FOR COOKSTOVE EMISSIONS
Field measurements of cookstove emissions are being carried out in China and
India. Tested fuels include those in common use in developing countries; e.g., crop
residues, animal dung, wood, charcoal, coal, kerosene, liquefied petroleum gas (LPG),
biogas, coal gas, and natural gas. As shown in Tables 1 and 2, 25 fuel/stove
combinations are being measured in China and 30 in India. Most fuel/stove
combinations are being tested in a simulated village house constructed in each
country. For massive stoves and stoves using piped gas fuels, however, the tests are
done in actual homes. In contrast to India, where only one coal/stove combination
was tested, coal is a major fuel used for household cooking and heating in China.
Thus, coal burning tests (several coal/stove combinations were selected) account for
a much larger portion in experiments conducted in China.
2-101

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Since it is known that emissions from most solid fuels can vary during the
burning process (Cooper and Malek, 1982), integrated sampling is needed to cover a
whole burn cycle (from fire start to fire extinction) in order to obtain emission data
that can represent the real burning situation. In addition, as with many household
appliances, it is necessary to choose a particular use cycle for fair comparison
among different stoves. Here is used the "water boiling test" procedure developed as
a standard international method to compare the fuel efficiencies of different stoves
(VITA, 1985). This procedure has the added advantage of enabling the simultaneous
measurement of emissions and efficiency, thus facilitating future calculations of the
impact of changes in one or the other.
Except for coal burning, the burn cycles ranged from 30 to 45 minutes for
most fuel/stove combinations. Coal burning, as practiced in China, needs a longer
cycle (up to 6 hours). A pot containing a known amount of water is placed on a tested
stove during the entire burn cycle. Information on parameters (e.g., water
temperature, amount of vapor generated, amount of fuel burned) necessary to
evaluate the thermal performance is collected, along with information about the
carbon and energy contents of fuel and ash.
A typical sampling configuration includes a sampling probe, filter holder,
pump, and Tedlar bag. For stoves having a flue, the probe is inserted in the flue (see
Figure 1). For those having no flue, the stoves are placed under a hood built for this
purpose, and the probe is placed inside the hood exhaust duct (see Figure 2). Filters
employed to collect total suspended particles (TSP) are 37 mm diameter quartz fiber
filters (Paliflex Products Co., Putnam, CT, U.S.A.). The flow rate of the sampling pump
is adjusted to fill one or two 80-liter Tedlar bags throughout a burn cycle.
Quartz fiber filters are heated to 800°C for 2 hours and then placed in a
desiccator for at least 24 hours before weighing. The filter then is carefully placed in
the filter holder in the laboratory. After sampling, the filter is taken out of the holder
and placed in a petri dish. Each filter sample (contained in a petri dish) is placed in a
desiccator for at least 24 hours before it is weighed. The net weight increase of the
filter after sampling is TSP mass collected on the filter. One filter from each
stove/fuel combination is analyzed for carbon content.
All sampling pumps (SKC Universal Flow Sample Pump, SKC West Inc.,
Fullerton, CA, U.S.A.) used are oil-free. Tedlar bags are flushed at least three times
with clean air before use. After sampling, a filled bag is sealed and well shaken
before samples are taken out of the bag. Glass syringes are used to take samples out
of the Tedlar bag, either directly injecting samples into a gas chromatograph (GC) for
analysis or for transfer into smaller air sampling bags. In addition, stainless-steel
canisters are used to sample a subsample of the Tedlar bags. The procedure is to fill
an evacuated 850 ml canister to 2 atmospheres using a battery-operated pump, a
process taking about 2 minutes (see Figure 3 for details).
A pilot phase study has been carried out in each country to determine burn
cycles, to test protocols of sample collection and analysis, and to measure
background levels of pollutants of concern. Main phase experiments started after
satisfactory conclusions were obtained from the pilot phase study. During the main
phase, three burn tests are conducted for each fuel/stove combination. Local GC
analyses are performed for all three tests, but only one canister sample is collected
for each fuel/stove combination. Once for each fuel, the canisters are collected in
2-102

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duplicate: the second is filled through a small Ascarite trap to reduce N20 artifacts in
the canister.
At least one background indoor air sample is taken for each fuel/stove
combination, and several outdoor (ambient) air samples are collected as well.
SAMPLING PROTOCOL FOR CHARCOAL KILN EMISSIONS
Five types of charcoal kilns have been selected in Thailand: Mud Beehive (900
kg wood, firing time = 72 hours); Brick Beehive (900 kg, 72 h); Single Metal Drum (100
kg, 4h); Ricehusk Mound (200 kg, 3 h); and Earth Mound (200 kg/10 h). The last two
have no chimneys (Chomcham, 1984). For all kilns, a 3 meter by 3 meter hood is
suspended overhead such that all emissions (from firing port, chimneys, cracks, etc.)
can be drawn through a duct by a blower system. The sampling probe is placed in the
duct, through which the airflow will be maintained at a constant rate during the entire
measurement period. The probe sampling flowrate itself is much lower than that for
cookstoves, because the firing times are so much longer than the cooking cycle.
Even so, several large Tedlar bags are filled during the runs with the longer-firing kilns.
A portion is drawn from each of the separate bags to a common mixing bag according
to the duration of sampling each of rhe separate bags represents. GC samples are
drawn from the common mixing bag.
Three runs are to be conducted for each kiln. Local GC analyses are planned
for every rum A pair of canister samples (one with and one without an Ascarite trap)
are collected once for each type of kiln. Ambient air samples are to be taken before
and during kiln operation.
For comparison, an advanced high-efficiency charcoal kiln of the Hawaii
Natural Energy Institute (University of Hawaii) is to be monitored using the same test
protocol.
ANALYTICAL METHODS
In all three countries. GCs are set up to analyze samples taken from. Tedlar
bags for C02, CO, CH4, and TNMHCs. A system of GC/flame ionization detecter
(FID)/methanizer is employed for analysis of CO, CO?, and CH4. In this system, a
Carbonsphere-packed column is used to separate these three compounds. The
separated CO and CO2 are converted by the rnethanizer to CH4 which is then
determined by the FID. TNMHCs are measured indirectly by subtracting CH4 from the
total hydrocarbon (THC). Using a blank column, a GC/'FID system measured THC (the
air peak is subtracted).
The filled canisters are returned to Oregon Graduate Institute of Science and
Technology (OGIST) to be analyzed for CO?, CO, CK4, TNMHCs, and hydrocarbon
speciatlon. The GC/FID/methanizer method is employed to analyze C02, CO, and
CH4 while hydrocarbon speciation is achieved by using the procedure established as
a method that uses GC to separate hydrocarbon species and uses FID to identify the
compounds. The Ascarite canisters are analyzed for N20 using GC/electron capture
detector (ECD) (Rasmussen and Khalil, i960 ; Riggm et ai.. (Method iO-u), 1988,
Rasmussen et ai., 1982).

-------
Fuel and ash analyses {calorific values, carbon contents, sulfur contents,
moisture contents, ash, etc.) are completed locally by standard fuel analysis
methods. Carbon contents of TSP collected on quartz fiber filters are measured by
destructive thermal carbon analysis.
QUALITY ASSURANCE
The same sampling sheets and data input methods are used in China and India
to reduce the confusion when handling and transferring data. Similar sampling and
analytical procedures are followed by both laboratories.
In the pilot study in each country, trial runs are conducted until a satisfactory
analytical precision is obtained. During the main phase experiments, at least one set
of parallel (side-by-side) sampling is conducted for each fuel type. For GC analysis,
two or more injections are made for each sample (relative standard deviation < 10%).
Calibration curves for all measured compounds are made daily and have linear
regressions R2>0.99.
Cross laboratory checks are also conducted. One of the same type of
fuel/stove combination is tested both in China and in India. Results obtained by local
GC analyses are compared with results of canister samples analyzed by OGIST.
Although laboratories of the four institutions used their own locally made calibration
standards on a daily operation basis, each of the four laboratories is provided with a
calibration mixture of CO2, CO, and CH4 from the same source (Scott Specialty Gases,
Inc., Plumsteadville, PA, U.S.A.). Thus, the locally made standards are calibrated with a
common standard, and all calculations are corrected based upon the common
standard if there is any difference between a local standard and the common
standard.
KEY PARTICIPANTS
Kirk R. Smith and Junfeng Zhang, East-West Center, Honolulu, HI, U.S.A.; V.V.N. Kishore
and team, Tata Energy Research Institute (TERI), Delhi, India; Y. Ma and team, Institute
for Techno-Economic and Energy Systems Analysis (ITEESA), Tsinghua University,
Beijing, China; Pojanie Khummongkol, King Mongkut's Institute of Technology,
Bangkok, Thailand; P.N. Winai, Charcoal Research Center, Saraburi, Thailand; M.A.K.
Khalil and R. Rasmussen, Oregon Graduate Institute of Science and Technology
(OGIST), Beaverton, OR, U.S.A.
REFERENCES
CHOMCHARN, A. (1984). Charcoal Production Improvement for Rural Development in
Thailand. Royal Forest Department, Bangkok.
COOPER, J.A. and MALEK, D., editors (1982). Residential Solid Fuels: Environmental
Impacts and Solutions. Oregon Graduate Center, Beaverton, OR.
RASMUSSEN, R.A. and KHALIL, M.A.K. (1980). "Atmospheric halocarbons:
Measurements and analyses of selected trace gases." In: Proceedings of the NATO
Advanced Study Institute on Atmospheric Ozone: Its Variation and Human
Influences. A.C. Aiken, Editor. U.S. Dept. of Transportation, Washington, DC, pp
209-231.
2-104

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RASMUSSEN, R.A., and KHALtL,M.A.K. (1981). "Atmospheric methane:Trends and
seasonal cycles." J. Geophysical Res. 86: 5172-5178.
RASMUSSEN, R.A. KHALIL, M.A.K. and CHANG, J.S.(1982). "Atmospheric trace gases
over China." Environmental Science and Technology 16: 124-126.
RIGGIN, R.M., WINBERRY, W.T., and MURPHY, N.T. (1988): "Compendium of Methods for
the Determination of Toxic Organic Compounds in Ambient Air, EPA/600/4-89-017
(NTIS PB90-116989), 605 pp, June.
SMITH, K.R. (1995). "Health, Energy, and Greenhouse-Gas Impacts of Biomass
Combustion in Household Stoves," Energy for Sustainable Development 1 (4), in
press.
SMITH, K.R. and THORNELOE.S.A. (1992). "Household Fuels in Developing Countries:
Global Warming, Health, and Energy Implications," Paper 5E, In Proceedings: the 1992
Greenhouse Gas Emissions and Mitigation Research Symposium, EPA-600/R-94-008
(NTIS PB94-132180), pp 5-61-5-80, January.
SMITH,K.R..RASMUSSEN, R.A., MANEGDEG, F., and APTE, M. (1992). "Greenhouse
Gases from Small-Scale Combustion in Developing Countries: A Pilot Study in Manila,"
EPA/600/R-92-005 (NTIS PB92-139369), 73 pp, January.
SMITH, K.R., KHALIL, M.A.K., RASMUSSEN,R.A., THORNELOE, S.A., MANEGDEG, F., and
ATPE., M. (1993). "Greenhouse gases from biomass and fossil fuel stoves in developing
countries: a Manila pilot study." Chemosphere 26: 479-505,
VITA, (1985). Testing the Efficiency of Wood-burning Cookstoves: International
Standards, Volunteers in Technical Assistance, Inc., Arlington, VA.
2-105

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TABLE 1. FUEL/STOVE COMBINATIONS TESTED IN CHINA

Fuel
Stove*
Does stove have a flue?
1
Kerosene
Wick
No
2
Kerosene
Pressure
No
3
Coal gas
Traditional
No
4
Coal gas
Infrared headed
No
5
Natural gas
Traditional
No
6
Natural gas
Infrared headed
No
7
IPG
Traditional
No
8
LPG
Infrared headed
No
9
Honeycomb coal
Metal
No
10
Honeycomb cool
Metal
Yes
11
Honeycomb cOal
Improved metal
No
12
Unprocessed coal
Traditional brick w/fan
Yes
13
Unprocessed coal
Metal
Yes
14
Washed coal
Metal
Yes
15
Coal briquette
Metal
N'o
16
Coal briquette
Metal
Yes
17
Wheat residue
Traditional brick
Yes
18
Wheat residue
Improved metal
Yes
19
Maize residue
Traditional brick
Yes
20
Maize residue
Improved metal
Yes
21
Wood 1
Traditional brick
Yes
22
Wood 1
Improved metal
Yes
23
Wood 1
Indian improved metal
No
24
Wood 2
Traditional brick
Yes
25
Wood 2
Indian improved metal
No
Total
12 types
16 types

"In several cases, the stoves marked "traditional" are traditional for each particular fuel.
2-106

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TABLE 2.
FUEL/STOW COMBINATIONS TESTED IN INDIA

Fuel
Stove
Does stove have a flue?
1
Wood 1
Traditional mud
No
2
Wood 1
Improved
No
3
Wood 1
Improved
Yes
4
Wood 1
Mud with ceramic coating
Yes
5
Wood 2
Traditional mud
No
6
Wood 2
Improved
No
7
Wood 2
Improved
Yes
8
Wood 2
Mud with ceramic coating
Yes
9
Wood I
Three-rock stove
No
10
Crop residue 1
Traditional mud
No
11
Crop residue 1
Improved
No
12
Crop residue 1
Improved
Yes
13
Crop residue 1
Mud with ceramic coating
Yes
14
Crop residue 2
Traditional mud
No
15
Crop residue 2
Improved
No
16
Crop residue 2
Improved
Yes
17
Crop residue 2
Mud with ceramic coating
Yes
18
Dung cake
Traditional mud
No
19
Dung cake
Improved
No
20
Dung cake
Improved
Yes
21
Dung cake
Mud with ceramic coating
Yes
22
Root
Traditional mud
No
23
Root
Improved
No
24
Root
Improved
Yes
25
Kerosene
Wick
No
26
Kerosene
Pressure
No
27
Charcoal
Charcoal stove
No
28
Coal briquette
Metal
No
29
LPG
Traditional
No
30
Biogas
Traditional
No
Total
11 types
11 types

*ln several cases, the stoves marked "traditional" are traditional for each particular fuel.
2-107

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FIGURE 1. SAMPLING FROM STOVI WITH fLUE
Scpturn:
,— j>Tlnjs
/ Mrt^ing
n /'*
uE
T«Oen hjfcn? .
y 1
Twfar b«9
(SC liKS)
["Pursp i
J"''
Can&ef
wrrpUrg
J?LO
FIGURE 2. SAMPLING FROM STOVE WITHOUT FLUE
^4
""v v -j
j\ -¦ J T#!©*	•
/ 1; £• \
Septvm.
syriig* —-j
wrrpirg /

i
_l
T<*Jterbag
<90
I
J~\
Camstor
\
pIG1.?KE i. CANISTER SAMPLING FROM A Fill FD 7EDIAR BAC
SeCturrt
syringe sar*p
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SESSION III: MITIGATION OF METHANE AND OTHER GREENHOUSE GASES	3_A
Rhone Resch, Chairperson
This paper has been reviewed in accordance, with (he U.S. Environmental Protection Agency- $ peer and
administrative review policies and approved for presentation arid publication.
Tf IE CPA STAR PROGRAM AND THE NATURAL GAS INDUSTRY
Kathleen Hogan
Chief, Methane and Utilities Branch, US EPA
Mail Code 6202J
401 M Street, SW
Washington, DC 20460
ABSTRACT
This paper describes the Natural Gas STAR Program, a cooperative, voluntary program
between the Natural Gas Industry and the U.S. Environmental Protection Agency (EPA) to implement
pollution prevention techniques in a cost effective manner. Specifically the STAR Program
encourages natural gas companies to adopt cost effective practices and technologies that reduce
emissions of methane - the primary component of natural gas. Methane is a potent greenhouse gas -
20 times more effective than CO, at trapping heat in the atmosphere.
In addition to reducing the threat of global warming, companies that participate in the Natural
Gas STAR Program also save money by reducing leaks and losses of the product they sell. In 1993,
the first partial year of the program, transmission and distribution partners saved 1.3 billion cubic feet
of natural gas worth almost $3 million. The 1994 program results are expected to generate even
greater savings.
INTRODUCTION
The U.S. natural gas system is a large and complex network of pipelines and facilities
involving a wide array of activities, from gas production, processing and transmission to distribution
to residential, commercial and industrial customers. Over a million miles of pipeline and thousands
of facilities are operated and maintained on an ongoing basis to supply and distribute natural gas. As
the principal component of natural gas, methane is emitted from a wide variety of components,
processes, and activities that make up the U.S. natural gas system. Because methane is such a potent
greenhouse gas (20 times more effective at trapping heat than C02) EPA decided to look at pollution
prevention opportunities within the natural gas industry as a method of reducing these emissions. In
the spring of 1993, the EPA launched the Natural Gas STAR Program
In 1993, in response to global concern about greenhouse gases emissions, the U.S. developed
the Climate Change Action Plan. The Action Plan outlines a series of activities that the U.S. will
undertake to reduce greenhouse gas emissions to 1990 levels by the year 2000. The plan includes
expansion of the Natural Gas STAR Program to additional transmission and distribution companies
and development of a new program for natural gas producers.
To date, the STAR Program includes 39 transmission and distribution partners representing
55% of all transmission company pipeline mileage and 25% of distribution company pipeline
mileage. The Producer Program, launched in March, 1995, includes 7 Charter Program Partners
representing 20% of all natural gas produced in the U.S. When fully implemented by the year 2,000
Natural Gas STAR Partners are expected to recover more than 35 billion cubic feet (bef) of natural gas
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worth over $70 million. Savings of this magnitude constitute enough fuel to heat almost 500,000
homes.
OVERVIEW OF THE NATURAL CAS STAR PROGRAM
As the principal component of natural gas, methane is emitted from a wide variety of
components, processes, and activities that make up the U.S. natural gas system. During the initial
planning stages of the Natural Cas STAR Program it became evident that sound analysis would form
the foundation for successful implementation of the program. The first steps in creating the program,
therefore, were to identify both the sources of emissions and opportunities for reducing these
emissions.
The development of the Natural Cas STAR Program consisted of three separate steps: identify
sources of emissions, select effective options for reducing emissions; and implement the program.
The first step in developing the Natural Cas STAR Program took place in 1992 and consisted of
identifying all emission sources and corresponding volumes. Results of this analysis were published
in the first of a series of Reports to Congress titled "Anthropogenic Methane Emissions in the United
States: Estimates for 1990" (USEPA 1993a).
Table 1
1990 Emissions and Major Features of the U.S. Natural Gas System
Stage
Cas Volume*
(Tcf)
Infrastructure1
(1990)
1990 Emissions'1
Wyr)
Production
Cress Production
Marketed Production
Dry Cas Production
21.5
18.6
17.8
269,790 gas wells
44,965 treatment facilities
288,165 oil wells
54,250 heaters'
180,65.3 separators'
19,776 gas dehydrators1
89,500 miles of gathering pipeline
0.69-1.82
Processing
Volume Processed
14.6
734 gas processing plants
6,603 gas dehydrators'
0 0-1 - 0.2 7
Storage
Addition?
Withdrawals
2.5
1.9
397 storage pools with a capacity of
7.8 Tcf
0.01 - 0.06
T ransmission
Cas Transported
20.9
280,100 miies of pipeline
6,097 gas dehya'ratorsc
0.59-2.06
Distribution
Cas Delivered
16.8
836,700 miles of main pipes
474,038 mites of service pipes
3,713 gate stationsb
0.17-0.75 I
Compressor Engine Exhaust
from all 5 Stages
Pipeline fuel
Production Stage
Processing Stage |
pop
K> *vj
16.5 million horsepower
0.27-0.64
Total Emissions
2.18-4.26
a Sources volume and inrrasljuciure data are DOL* 0291) And AGA (1991bi unless rioted otherwise,
b USFPA<1903}.
c Co*v<;til <19S2>.
rl Hie! uwi Uy c©rrcx«*of engines u«od in rh© tranimrwion, storage, And diitrihutien stage* {USEPA 199)).
f> hw-i it-.* lor cornpf«sor engines used in the* production stage (J. ^SrPA 1993).
f Fuel us* for cooipr^v* erginr? uted in the rvorf^ing M-ige (USFPA 199)).
Trf - trillion cubic feci.
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STEP 1: IDENTIFYING EMISSION SOURCES
Fugitive emissions or leaks across all stages of gas production, transmission and distribution
are estimated to be the largest individual source of emissions, accounting for about 38 percent of the
total. These emissions originate throughout the entire system and include leaks at compressor
stations, gate stations and from leaky distribution pipe. Emissions associated with pneumatic devices
are the second largest individual source, accounting for approximately 20 percent of the total
estimated emissions. Pneumatic devices, used primarily in the production and transmission stages to
regulate and control gas pressure and flow, are designed to release small amounts of gas as part of
their normal function. Engine exhaust is the third largest source accounting for about 14% of total
methane emissions. As part of their normal operation, gas fired reciprocating and turbine engines
emit methane in their exhaust gas. logethcr, fugitive emissions, pneumatic devices and engine
exhaust account for nearly 75 percent of total estimated emissions and are considered to result from
normal operations in the gas sector. Emissions from routine maintenance activities and system upsets
are estimated to be relatively minor.
NORMAL OPERATIONS
Pneumatic Devices
Pneumatic devices are commonly used to regulate and control gas pressures and flows
throughout the natural gas system. These devices rely on pressurized gas as an energy source for their
operation. For example, the pressurized gas may be used to maintain the position of an actuator. In
most cases, the natural gas stream itself is a suitable supply of pressurized gas. Emissions from a
pneumatic device result when the device is designed to release the pressurized gas it uses to the
atmosphere.
Emissions from pneumatics are a function of the design and size of the device, the frequency
of its operation, and its age and state of repair. Emissions estimates for field production, processing,
and injection/withdrawal facilities were taken from Tilkicioglu (1CJ90) and Radian (1992a). Emissions
from pneumatic devices on transmission systems were estimated using measured rates from the PG&E
(1990) and SOCAI (1992) unaccounted-for-gas studies. Sample bleed rates for high bleed pneumatics
range from .1 to .6 cubic feet/minute for valve actuators and positioners. Distribution systems were
assumed to have negligible emissions in this category.
Reciprocating Engmes
Reciprocating engines and turbines are used throughout the natural gas system to compress
gas, generate electricity and perform other functions (such as pump water). The exhaust from these
engines is known to contain methane.
Total compressor engine exhaust is calculated separately for all stages by multiplying the
emissions factors for reciprocating engines and turbines by the corresponding estimates of annual fuel
use. Tilkicioglu (1990) reports an emissions factor of 508 kg of methane per million of cubic feet
(MMcf) of fuel used in reciprocating compressor engines (1,120 pounds per MMcf). EPA (1985)
reports a methane emissions factor of approximately 587 kg/MMcf.[1] Additional studies indicate that
emissions are on the order of 513 kg/MMcf when the available data from individual compressors are
weighted by actual fuel usage (Campbell, 1991). Therefore, a representative emissions factor of 510
kg/MMcf is adopted here for estimating these emissions.
Turbine engines exhaust much less methane per MMcf of fuel used than reciprocating
engines. Tilkicioglu uses an emissions factor of 11.8 kg/MMcf (26 pounds/MMcf). EPA (1985) reports


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a value of 9.7 kg/MMcf and Campbell (1991) reports a value of 6.1 kg/MMcf. Tor this study, an
emissions factor of 9.0 kg/MMcf is used, which is roughly the average of these reported values.
Engine Starts and Stops
In the process of starting and stopping reciprocating engines and turbines, natural gas is
generally vented from the equipment. The quantity of gas vented is a function of the internal volume
of the engine and the number of starts and stops conducted annually. Generally, turbines are
operated almost continuously, so that very few starts and stops are conducted. Also, in some cases
pressurized air is used to assist in starting turbines, so that less gas is vented during engine starts in
these cases.
Fquipment Venting
Glycol dehydrators are the principal source of equipment venting emissions. These
dehydrators are used to remove wafer from natural gas through continuous glycol absorption. Other
compounds in the gas are also absorbed including methane. The water-rich glycol is regenerated
with heat, which drives the water out of the glycol. The methane present in the glycol is driven out
with the water in this process and is vented to the atmosphere. Estimates of emissions resulting from
the venting of glycol dehydrators for production, processing and transmission were taken from Radian
(1992a).
Fugitive Emissions
Fugitive emissions occur in all stages of the natural gas industry. Fugitive emissions in above-
ground facilities such as at well-site equipment, compressor stations and gate stations, are primarily a
function of the number of components (e.g., connections and valves) installed and are estimated by:
•	multiplying emissions factors by the number of installed components at model facilities; and
•	scaling the model facility estimates to the industry as a whole.
Fugitive emissions also result from small chronic leaks in buried pipelines due to corrosion of
leaking pipe joints.
ROUTINE MAINTENANCE AND SYSTEM UPSETS
Emissions from routine maintenance include emissions from maintenance of gathering
pipelines, well workovers, orifice fittings, station blowdowns, transmission station shutdowns,
pipeline repair, and compressor blowdowns. For each of these, emissions result when facilities or
equipment are vented to the atmosphere.
In general, routine maintenance emissions are estimated by multiplying the frequency with
which the maintenance activity is performed by the quantity released per activity. The frequency
with which activities are performed was estimated based on interviews with station operators and
operational records reviewed at the model facilities. While some practices vary across facilities, most
maintenance activities are fairly standard. Therefore, the frequency estimates are believed to be
reliable even though only a small number of model facilities was examined.
Methane emissions from system upsets include emergency blowdowns, station shutdowns,
and accidental pipeline ruptures or "dig-ins." Information used to calculate these emissions include
interviews with plant operators and facility logs. Because upsets are unplanned, these estimates are
more uncertain than regula'ly scheduled routine maintenance emissions or normal operations

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emissions. In general, the volume emitted is calculated from the number of annual upsets and the
volume of vented facilities and equipment.
Because transmission systems are generally well marked, dig-ins are infrequent and do not
contribute significantly to emissions. While emissions from system upsets in distributions systems are
generally considered small, dig-ins are the primary source of these emissions.
STEP 2: COST-EFFECTIVE ANALYSIS
The second step in developing the Natural Gas STAR Program was to identify trie technologies
and processes that are cost effective for reducing emissions. To accomplish this task, EPA studied the
existing list of emission sources and looked at a variety of factors to determine the cost-effectiveness
of various emissions reduction strategies. These results were published in a second FPA Report to
Congress, titled "Opportunities to Reduce Anthropogenic Methane Emissions in the United States*
USEPA (1993b). In the transmission and distribution sector directed inspection and maintenance
programs at compressor and gate stations, replacing high-bleed pneumatics, and installing turbines in
place of reciprocating engines are cost effective for reducing methane emissions. These activities,
along with the rehabilitation of leaking distribution pipe, form the core best management practices in
the transmission and distribution sector's Natural Gas STAR Program. In the production sector,
replacement of high-bleed pneumatics and installing flash tank separators on glycol dehydrators are
cost effective solutions and make up the best management practices for the production sector.
The following analysis focused on eight options for reducing emissions in the three stages of
the natural gas system that account for the majority of emissions: production, transmission, and
distribution. Table 2 summarizes the options, including the extent to which each can reduce
emissions. Information on the costs of implementing the option, the anticipated reductions in
methane emissions to the atmosphere, and the associated potential gas savings are identified for each
option in the following section. In addition to reducing methane emissions, these options also result
in other benefits such as improved system safety and reduced emissions of volatile organic
compounds (VOCs), which contribute to tropospheric ozone formation, and in some cases are human
health hazards.
Table 2
Summary of Major Options for Reducing Methane Emissions from the Natural Gas Industry


1990
2000
2010
Option
Stage
Emissions
(Tg/yr)
Emissions
(Tgiyt)
Potential Reductions
(Tg/yr)
Emissions
(Tg/yr)
Potential Reduction
(Tg/yr)


Technically
Feasible
Profitable
Technically
Feasible
Profitable
Replace
High-Bteed
Pneumatic
Devices
Production
0.37
0.44
0.24
0.24
0.45
0.25
0.25
Recover
Fmissinns
from De hy-
dra tor Vents
Production
0.11
0.13
0.12
0.12
0.13
0.12
0.12
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Option
Stage
1990
2000
2010
Emissions
(Tg/yri
Emissions
CTg/yr)
Potential Reductions
Cffi/yr)
Emissions
CTg/yr)
Potential Reduction
CTg/yr)
Technically
Feasible
Profitable
Technically
Feasible
Profitable
Directed l/M
Programs at
Gas Well
sites
Production
0.23
0.27
0.19
000
0.28
0.20
0.00
Dirertpd l/M
Programs at
Compressor
Stations
Transmission
0.33
0.34
0.24
0.24
0.36
0.25
0.25
Replace
High-Bleed
Pneumatic
Devices
0.20
0.21
0.12
0.12
0.22
0.12
0.12
Recover Gas
Vented
During
Pipeline
(Slowdowns
0.22
0.24
0.02
0.00
0.25
0.02
0.00
Directed l/M
Programs at
Gate Stations
Distribution
0.12
0.14
0.10
0.10
0.16
0.11
0.11
Use Turbines
Instead of
Reciproratin
g Engines on
Transmission
Pipelines
Engine
Exhaust
(Transmission)
0.18
0.22
0.07
0.00
0.23
0.13
0.00
Subtotal
1.76
1.99
1.10
0.82
2.08
1.20
0.86
Emissions
from Other
Gas System
Sources
All
1.21
1.39
-
-
1.42
-
-
Total
2.97
3.38
1.10
0.82
3.50
1.20
0.86
PRODUCTION FACILITY OPTIONS
There are two cost-effective major options for reducing methane emissions from natural gas
production facilities:
•	Replacing high-bleed pneumatic devices;
•	Installing flash tank separators on dehydrators.
Other options, such as Inspection and Maintenance Program at natural gas wells may be cost-
effective over time.

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Replacing "High-Bleed" Pneumatics.
Natural gas-operated or pneumatic devices are used throughout production facilities on
gathering lines, heaters, separators, and glycol dehydrators to monitor and control the flow of gas.
Pneumatic devices include valve controllers, valve actuators, pressure regulators, and pressure
transmitters.
Pneumatic devices operate by using gas pressure to drive their operating mechanisms.
Because the pressurized gas stream in the pipeline is a convenient source of pressurized gas, most
pneumatic devices use the pipeline as their source of pressurized gas. High-bleed pneumatic devices
are designed to use a significant amount of pressurized gas, which is then emitted. Devices with
emissions or "bleed" rates of 0.1 to 0.5 cubic feet per minute (ft3/min) are considered to be "high
bleed" types (PG&E 1990).
One option for reducing emissions is to use an alternative source of pressurized gas to operate
the device. In circumstances where compressed air is available, this technique is often used as a
means of saving gas. In most situations, however, providing compressed air is not cost effective.
The most cost effective technique for reducing the emissions from high-bleed pneumatic
devices is to replace high-bleed pneumatics with lower bleed designs at the end of their service life
(generally seven years) where technically feasible. A number of designs exist which either bleed
significantly less gas or do not emit gas at all.
The only incremental cost of implementing this option, therefore, is an additional capital
expense of about $167 per device (Radian 1992b). The cost for replacing high-bleed pneumatics wUh
low or no-bleed pneumatics is recovered in less than 3 years.
Not all high-bleed devices can be replaced with lower bleed devices. Because the response
time of the control device is directly related to the rate of venting, there are some situations where a
high-bleed device is necessary for the effective operation of the production unit (Harrison 1992).
Studies conducted by the U.S. gas industry have shown that there are numerous opportunities for
replacing high-bleed devices (PG&E 1990), and it is estimated that 80 percent of the high bleed
devices can be replaced with low bleed devices.
Installing Flash Tank Separators on Dehydrators
Dehydrators are used throughout the production stage to remove water from natural gas in
order to prevent the formation of hydrate slugs in pipelines and to reduce corrosion. Dehydrators
work by bringing the gas into contact with a desiccant, usually glycol, which absorbs the water from
the gas. When the desiccant becomes saturated, it is removed to a regenerating unit, where it is
heated to drive off the absorbed water. The desiccant usually contains quantities of absorbed
methane and VOCs, which are also driven off and subsequently vented to the atmosphere.
In response to state initiatives to reduce air emissions from glycol regeneration at dehydration
units, a variety of techniques have been explored for capturing and combusting the vapors vented
during glycol regeneration. The most cost effective technique identified for most dehydrator designs
is to install a flash tank separator (FTS) on the glycol line between the water absorption step and the
regenerating process. The FTS prevents the light hydrocarbons, including methane, from reaching the
regenerating unit, substantially reducing the volume of light hydrocarbons vented from the
dehydrator.
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The FTS removes methane absorbed in the de&iccant by rapidly reducing the pressure (e.g.,
from 800 to 900 psi, down to 50 to 100 psi), causing most of the dissolved methane to "flash" out of
solution (back into a gaseous state). The methane gas is then recovered from the FTS and used as
boiler fuel in the regenerating unit. The cost of installing a flash-tank separator is recovered in 28
years.
The estimates of the gas saved using an FTS are likely understated because the model facility
used to derive these values was relatively small. Installing an FTS on larger dehydrators results in
significantly larger amounts of gas saved without significantly increasing the installed cost for the
device.
TRANSMISSION FACIIITY OPTIONS
There are four major options for reducing methane emissions from natural gas transmission
systems:
•	Implementing directed inspection and maintenance programs at compressor stations;
•	Replacing high-bleed pneumatic devices;
•	Capturing gas released during pipeline repairs; and
•	Using turbines more frequently for new pipelines.
Directed Inspection and Maintenance Programs at Compressor Stations
This option reduces fugitive emissions from compressor stations by implementing directed l/M
programs at these facilities. Compressor stations, which are used to maintain the gas pressure in high
pressure transmission pipelines, contain a large number of components. Over lime, these
components may develop leaks. In particular, packing seals around the moving parts of compressors
and valves are important sources of fugitive methane emissions (SOCAL 1992).
The most effective approach for reducing these emissions is to implement directed l/M
programs similar to those described for production wellsites. While transmission facilities are already
required by Department of Transportation regulations to be surveyed periodically with Hydrogen
Flame Ionizer instruments to protect public safety, directed l/M programs could identify leaks which
are not a threat to public safety but emit significant quantities of methane to the atmosphere.
Implementing directed l/M programs at compressor stations requires several different costs,
including screening equipment purchase and O&M cost, screening program costs, and repair costs.
l/M programs are estimated to be a profitable option, with an annualized benefit estimated at about
$4,500 per year per gate station.
Replacing "High-Bleed" Pneumatics
As in the production stage, significant quantities of methane are emitted from the normal
operation of high-bleed pneumatic devices at transmission facilities. Replacing these "high-bleed"
pneumatic devices with "low-" or "no-bleed" devices where technically and economically feasible
could reduce methane emissions from this source by an average of 70 percent per device (Radian
1992b).
The only incremental cost of implementing this option is an additional capital expense of
about $167 per device (Radian 1992b). The cost for replacing high-bleed pneumatics with low or no-
bleerl pneumatics is recovered in less than 3 years.

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Capturing Gas Released During Pipeline Repairs
Routine maintenance work on transmission pipelines requires the removal of gas from the
pipeline section under repair to ensure safe welding conditions. In the U.S., this removal of gas is
usually accomplished by closing off a segment of transmission line, allowing local users to draw on
the enclosed volume to reduce the pressure, and venting the remaining gas to the atmosphere. Since
shut-off valves can be up to 15 miles apart, an extensive section of pipe is often vented, and a
significant volume of gas released. Except where there is a very limited time for removing the gas
from the pipeline (e.g., during peak demand conditions), the gas which would otherwise be vented
from the section under repair can be pumped into an adjoining section of pipe using a portable
evacuation compressor (PEQ. This technique can reduce the amount of vented gas by about 80
percent.[1]
PEC units typically consist of a centrifugal compressor driven by a natural gas powered
turbine. These components, along with auxiliary equipment such as coolers, scrubbers, and electric
generators, are mounted on a standard trailer. A support truck carries the necessary pipe and fittings
to tie-in the compressor unit to the pipeline. Through a series of adapters, such a unit can be coupled
to pipelines with diameters ranging from 10 to 42 inches, A 3 to 4 person crew is needed to
transport, set-up, and operate the unit. A typical operation, evacuating a 20 mile section of 30 inch
pipeline at 800 psi down to a pressure of 160 psi, takes approximately 10 hours. Setup and
disassembly usually requires four hours.
PFCs could recover about 80 percent of the gas emitted per blowdown, for a maximum
recovery of about 9.3 bcf per year. At a price of $2.01/Mcf (DOE 1992), the maximum value of the
saved gas would be approximately $18.8 million per year. The costs associated with a PFC are
substantial. A typical PEC unit costs $5 million to purchase and mount. Operation and maintenance
costs for the fuel and labor are typically $7,800 per blowdown (Radian 1992b).
Greater Use of Turbines in New Pipelines and When Retiring Reciprocators
The compressors used to maintain gas pressure in the natural gas system are driven either by
reciprocating engines or turbines. Currently, reciprocating engines provide 69 percent of the total
16.5 million hp in the transmission, storage, and distribution stages of the U.S. natural gas industry,
and turbines provide the remaining 3 I percent (Jones 1992), About 83 percent of this compressor
horsepower (13.7 million hp) is used in the transmission system, with the rest used at storage facilities
and in distribution networks (AGA 1991b).
Reciprocating engines are a significant source of methane emissions, which result from
incomplete combustion of the natural gas used to fuel the engine. Alternatively, the emissions rate
for turbines is at least an order of magnitude lower than the emissions factor for reciprocating engines.
For example, reciprocating engines emit an average of 500 kg of methane per MMcf of fuel used,
whereas turbines emit an average of only 9 kg of methane per MMcf used (USEPA 1993a). Designing
new transmission pipelines to use turbines as opposed to reciprocating engines and replacing retiring
reciprocating engines with turbines would greatly reduce methane emissions from this source.
The decision to install reciprocating engines or turbines depends on economic considerations,
as well as site-specific and system-wide operational and technical factors. While turbines cannot
replace reciprocating engines in all transmission pipeline applications, using turbines is technically
advantageous in several respects. Turbines are particularly suitable where the transmission system
work load is stable and relatively large. Gas turbines are also environmentally advantageous with
regards to NO, emissions. Despite their many advantages, however, turbines use more fuel than
reciprocators (though emitting less methane per volume of fuel used). In addition, reciprocators
3-9

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operate more effectively at partial loads than turbines, and only reciprocators can develop the high
compression ratios required for some transmission operations (Eberle 1992). Overall, it is estimated
that turbines are technically and operationally suitable candidates for 80 percent of new transmission
pipeline prime mover capacity in the U.S., including both new systems and the replacement of old
units.
The principal benefit of using turbine engines as opposed to reciprocating engines is reduced
emissions of methane and other pollutants. The mafor costs associated with installing and operating
new compressor prime movers are equipment costs, operating and maintenance costs, and fuel costs.
The cost of using turbines is highly site-specific. Based on average values, the analysis shows that the
option is marginally not profitable, with a negative net present value of about $0.2 million, and an
annualized net costs of about $0.01 million.
DISTRIBUTION FACILITY OPTIONS
Methane emissions from natural gas distribution networks can be reduced by implementing
directed inspection and maintenance programs and by rehabilitating leaky pipelines. I he continued
rehabilitation of leaky pipeline is included in the baseline emissions estimates (USFPA 1993a).
Consequently, accelerated replacement would be required to realize incremental emissions
reduction.
Directed Inspection and Maintenance Programs
As with facilities in the production and transmission stages, above ground or "surface"
facilities in distribution networks are important sources of fugitive methane emissions. Gate stations,
where high-pressure gas from transmission companies is received into the distribution network, are
the surface facilities that exhibit the highest levels of fugitive emissions (McManus et al. 1992).
The most effective approach for reducing these emissions is to implement directed inspection
and maintenance (l/'M) programs. While leak surveys of distribution facilities are presently required
by Department of Transportation regulations and state public utility commissions (PUCs),
supplementation with directed l/M programs at gate stations may greatly reduce fugitive methane
emissions to the atmosphere.
In general, implementing directed inspection and maintenance programs at compressor
stations requires several different costs, including screening equipment purchase and O&M cost,
screening program costs, and repair costs. I/M programs are estimated to be a profitable option, with
an annualized benefit estimated at about $1,700 per year per gate station.
Rehabilitating "Leaky" Pipe
Leaks in underground piping in distribution networks are an important source of fugitive
methane emissions. These pipes are usually constructed of steel, plastic, cast iron, or copper. Leaks
occur as a result of corrosion, joint failures (seal deterioration; pipe movement), and fractures (third-
party damage; subsidence; road traffic). Despite a wide range of measures to prevent leakage,
fugitive emissions generally occur.
Fypically, plastic pipe leaks less than steel, which leaks less than other materials such as cast
iron and copper. Rehabilitating the leakiest pipe materials in distribution networks, where
appropriate, could reduce fugitive emissions from these sections of the network by 85 percent or
more.
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Rehabilitation usually takes the form of either complete replacement with plastic pipe (or
sometimes other materials), or the insertion of new pipe material inside of the old one. Because the
cost of rehabilitating pipeline often greatly exceeds the value of avoided maintenance requirements
and gas savings, distribution firms justify their current extensive rehabilitation programs principally on
the basis of reducing safety hazards to the public.
The primary economic benefit of rehabilitating distribution pipeline is the reduction in
maintenance costs. Radian (1992b) estimated the cost savings at about $4.60 per foot of pipeline per
year. The costs associated with pipe rehabilitation vary depending on the technique employed and
the surface conditions encountered. Pipe replacement usually requires excavation, which can be
quite expensive in urban areas. Pipe rehabilitation, by inserting replacement pipe directly into the
leaky existing pipe, avoids expensive excavation but requires extensive coordination and greater
attention to timing. Depending on the method, rehabilitation costs (capital plus labor) using plastic
can range from $80 to $200 or more per foot of distribution pipe (Radian 1992b).
The baseline methane emission estimates for 2000 and 2010 include the continuation of
recent trends in distribution pipeline rehabilitation (USEPA 1993a). These trends include the
rehabilitation of one mile of existing pipe for every two miles of new pipe installed (Watts 1990).
Accelerating pipeline rehabilitation beyond this level would reduce emissions from the projected
baseline levels.
Emerging Technologies and Practices
A number of new or improved technologies and practices for reducing methane emissions are
being developed. These emerging technologies address emissions from each stage of the U.S. gas
system. In many cases, these technologies are already being field tested, or are in limited use, and it
is expected that they will be used more extensively in the near future. Some of the technologies most
likely to have an impact on efforts to reduce emissions include:
•	Installing catalytic converters on reciprocating engines;
•	Using "smart" regulators in distribution systems;
•	Using metallic coated seals;
•	Using sealant and cleaner injections in valves; and
•	Using composite wraps for pipeline repair.
STEP3: PROGRAM IMPLEMENTATION
The design of the Natural Gas STAR Program was modeled on EPA's Green Lights Program, a
voluntary pollution prevention program that encourages companies to install energy efficient lighting.
Like Green Lights, the Natural Gas STAR Program is structured around a memorandum of
understanding (MOU) which specifies cost effective best management practices for each sector. The
MOU, which was developed with input from industry, outlines the responsibilities of both the partner
and EPA. The Natural Gas STAR Program was launched in March, 1993 and initially focused on the
transmission and distribution sectors. The program was expanded to include the production sector in
March, 1995.
Both the transmission and distribution program and the producers program are structured in
the same manner. This structure asks companies to join the Natural Gas STAR Program by voluntarily
signing a "Memorandum of Understanding" (MOU) with EPA and by agreeing to review and
implement appropriate "best management practices" when they are cost effective to the partner. The
Partners then submit an implementation plan to EPA and have three years to implement the program
3-11

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as specified in their plan. Partners can also receive recognition for methane emission reductions
implemented prior to joining Natural Gas STAR. Companies are asked to designate a Natural Gas
STAR implementation manager to oversee the program, document progress, and work with EPA to
publicize successes. The program is structured to minimize additional administrative burdens.
EPA, in turn, agrees to provide technical support for its partners by assisting with
implementation of the program through workshops and training courses, analyzing emerging
technologies and practices in cooperation with the gas industry, and removing regulatory barriers. In
addition, EPA provides opportunities for public recognition through news articles and press releases,
marketing materials, and awards for environmental and technical leadership.
END NOTES
1. Most units in operation have a compression ratio of 5:1, which limits the amount of gas that can be
captured to around 80 percent. That is, the pressure in the evacuated section can only be reduced to
1/5 of that in the adjoining section, leaving the remaining 20 percent of the gas to be vented prior to
maintenance.
REFERENCES
AGA (American Gas Association). 1991a. The Gas Energy Supply Outlook, 1991-2010, AGA;
Arlington, VA.
AGA (American Gas Association). 1991b. Gas facts - 1990 Data, AGA; Arlington, VA.
Campbell, L. 1991. "Methane Emissions from Reciprocating Engines/Gas Turbines Used in Gas
Industry," presented to the Advisory Committee on Methane Emissions from the Natural Gas
Industry, sponsored by the U.S. Environmental Protection Agency and the Gas Research
Institute, San Antonio, Texas, August 8, 1991.
DOE (U.S. Department of Energy). 1992. Natural Cas Monthly (April 1992); US DOE; Washington,
DC.
Eberle, Arthur. 1992. Columbia Gas; personal communication - 7/29/92.
Harrison, Matthew. 1992. Radian Corporation, telephone conversation on 8/12/92.
Jones, Donna Lee. 1992. "National Estimates of Methane Emissions from Compressors in the U.S.
Natural Gas Industry," 1992 AWMA Paper, Kansas City, MO.
McManus, J.B., et al. 1992. Methane Emissions from Natural Cas Distribution Systems, Final Report
prepared for the U.S. Environmental Protection Agency Global Change Division and the Gas
Research Institute Environmental and Safety Research Department.
PG&E (Pacific Gas and Electric). 1990. Unaccounted for Cas Project Summary Volume, PG&E
Research and Development; San Ramon, CA; GRI-90/0067.1.
Radian. 1992a. Estimate of U.S. Methane Emissions - Production Segment (Draft Peer Review
Report), Radian; Austin, TX.

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Radian. 1992b. U.S. Natural Gas Industry Methane Emissions Mitigation and Cost Benefit Analysis,
Radian, Austin, TX.
SOCAI (Southern California Gas Company). 1992. Unaccounted for Gas Project Summary Volume
(in preparation), SOCAL Research and Development; Los Angeles, CA.
Tilkicioglu, B,H. 1990. Annual Methane Emissions Estimates of the Natural Gas Systems in the U.S. -
Phase II, Pipeline Systems, Inc.
USEPA (U.S. Environmental Protection Agency). 1983. Equipment Leaks ofVOC in Natural Gas
Production Industry, USEPA; Research Triangle Park, NC.
USEPA (Environmental Protection Agency). 1985. Compilation of Air Pollutant Emission Factors
Volume I: Stationary Point and Area Sources, Office oi Air and Radiation, Research Triangle
Park, North Carolina, AP-42, September 1985.
USEPA (U.S. Environmental Protection Agency). 1993a, Anthropogenic Methane Emissions in the
United States, Report to the Congress, prepared by the Global Change Division, Office of Air
and Radiation, EPA, Washington, D.C.
USEPA (U.S. Environmental Protection Agency). 1993b. Opportunities to Reduce Anthropogenic
Methane Emissions in the United States, Report to the Congress, prepared by the Global
Change Division, Office of Air and Radiation, EPA, Washington, D.C.
Watts, J, 1990. "25th Distribution Piping Report," Pipeline & Gas Journal, Dec., 1990; pp. 14-15.
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3 B
SIGNIFICANT SOURCES OF METHANE EMISSIONS
IN THE NATURAL GAS INDUSTRY
R. Michael Cowgill
Matthew R. Harrison
Radian Corporation
8501 Mopac Blvd.
Austin, TX 78720
David A. Kirchgessner
U.S. Environmental Protection Agency
Air Pollution Prevention & Control Division
MD-63
Research Triangle Park, NC 27711
ABSTRACT
Methane, the major constituent of natural gas, is a potent greenhouse gas believed to
contribute to the effect of global warming when released to the atmosphere. Reducing methane
emissions would lessen this effect, as well as save money and increase energy efficiency by
decreasing the amount of gas product lost. This project quantified methane emissions from the
natural gas industry. Major sources of methane emissions are summarized and emission
estimation methods are described.
INTRODUCTION
The U.S. Environmental Protection Agency (EPA) cofunded a project to quantify methane
(CH4) emissions from the U.S. natural gas industry [1]. Methane, the major constituent of natural
gas, is a potent greenhouse gas believed to contribute to global warming when released to the
atmosphere. Reducing emissions from natural gas systems would lessen the greenhouse gas
effect attributable to atmospheric CH4. Further, emissions reductions of natural gas, a marketable
resource, could save money and increase energy efficiency.
This paper summarizes the major sources of CH4 being emitted to the atmosphere for all
segments of the U.S. gas industry: production, processing, transmission, storage, and
distribution. A description of how those emissions were determined is also included.
METHANE EMISSION STUDY
The objective of this comprehensive multi-phase study was to quantify CH4 emissions
from the gas industry, from tho wellhead to, and including, the customer's meter, with an overall
accuracy goal of ± 110 BCF1 or approximately ± 0.5 percent of gross annual U.S. natural gas
production based on a 90 percent level of confidence.
During Phase 1 of the program, CH4 emissions from each identified source in the gas
industry were quantified on the basis of available data and engineering judgment. These initial
estimates were used to set priorities for collecting data according to a source's relative importance
in contributing to emissions.
This paper has been reviewed in accordance with the
U. S. Environmental Protection Agency's peer and administrative review policies
and approved for presentation and publication.
1BCF = Billion Cubic Feet = 10° cubic feet; 1 cubic foot = 0.02832 cubic meter.
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In Phase 2 of the program, methods wcro developed to measure the emissions from some
sources in the gas industry and to calculate emissions from the remaining sources. These
methods were validated by tests designed to quantify the accuracy of the measurement
approach (i.e., proof of concept tests), and by industry review of the calculation approaches.
Because omissions could not be measured or calculated from every source {e.g., every glycol
dehydrator or every compressor engine) in the natural gas industry, part of the Phase 2 program
focused on developing defensible techniques for extrapolating the limited data collected for a
specific source in the gas industry to similar sources nationwide.
Phase 3, therefore, focused on collecting the data needed to define emissions from all
sources and on extrapolating from these data to estimate natural gas industry CH4 emissions
nationwide. Additional data collected in Phase 3 of the program concentrated on high-priority
sources. An advisory committee consisting of industiy representatives, project sponsors, and
other interested parties from both government and private sectors, provided guidance and peer
review for all phases of the program.
Industry Characterization
In general, the first step in estimating CH4 emissions from the U.S. natural gas industry
was to recognize, delineate, and characterize each emission source within the industry. The
industry was divided into its principal market segments: production, processing, transmission,
storage, and distribution. Within each segment, the process facilities were identified, and within
each facility, tho individual pieces of equipment and components contributing CH4 emissions (the
source categories) were noted. This method, which ensured that no sources were overlooked or
double counted, produced a manageable framework within which the study was conducted.
Table 1 shows industry market segments, major facilities within those segments, and major
equipment within the facilities After the major equipment (source categories) in each industry
market segment was identified, all possible emissions from each source were identified by
examining the operating modes of the equipment that could result in emissions.
Operating Mode
The sources of CH4 emissions are directly related to the operating mode of the equipment.
Since more than one emission source can be associated with a particular piece of equipment, it is
important to identify the various operating modes to Identify all possible emissions from each
source. In general, the various operating modes are:
•	Startup,
Normal Operation,
•	Maintenance,
•	Upsets, and
•	Mishaps.
Startup operations, such as purging a newly constructed plant, can involve releasing
natural gas directly to the atmosphere. Emissions associated with normal operations include
emissions from process vents, fugitive emissions from packed or sealed surfaces or underground
pipeline leaks, and emissions from gas-operated pneumatic devices. Maintenance operations
Involve blowing down vessels before the equipment is maintained. Process upsets usually
involve releasing natural gas to the atmosphere or to a combustion device, such as a flare, during
overpressure or emergency shutdown conditions. Mishaps include accidental occurrences that
result in emissions such as "dig-ins" (external damage from digging equipment). The study has
shown that emissions from this category (mishaps) are negligible, except for third-party damage
to distribution pipelines ("dig-ins").
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Emission Types
Each source in the natural gas industry has one or more of three general types of
emissions: (1) fugitive emissions, (2) vented emissions, and (3) combusted emissions. Fugitive
emissions are unintentional leaks emitted from sealed surfaces such as packings and gaskets, as
well as leaks from underground pipelines (resulting from corrosion, faulty connections, etc.).
Vented emissions are intentional releases to the atmosphere. Examples of vented emissions aro
emissions from continuous process vents, such as dehydrator reboiler vents; emissions occurring
during maintenance practices, such as blowdowns; and small individual sources, such as gas-
operated pneumatic device vents. Combusted emissions are exhaust emissions from internal
combustion sources {e.g., compressor engines) or from burners and flares. Table 2 shows
examples of emission sources characterized by the operating mode and emission type.
Emission Estimation Techniques
After all potential sources of CH4 emissions in the industry were identified and
characterized, the emissions were quantified. The quantification technique depended on the
variability of the emission rate with time. Some emissions from natural gas industry sources are
continuous and steady and can be more easily measured. "Steady" is a relative term defined by
the time period of data needed for the study. For this study, an annual value of CH4 emissions
was needed. Because it was not practical to measure emissions all year for every source, it was
important that a single measurement be representative of the annual emissions.
Measurement Techniques for Steady Emissions
The techniques used in the study for measuring steady emissions are briefly described in
the following paragraphs. .
Methods for Measuring Fugitive Emissions
Emission factors for estimating fugitive emissions were based on measurements of
emissions from individual sealed surfaces (components) associated with the equipment, such as
valve packing, flange gaskets, screwed fittings, and compressor/pump seals. Emissions from a
large number of components were measured, and an average emission rale per component was
determined for each component type. Emissions from an equipment source, such as a
compressor, or a facility, such as a compressor station, were then calculated by multiplying the
number of components associated with that equipment or facility with the average emission rate
per component.
Emissions from individual components were measured using one of several methods:
•	A high-flow organic vapor analyzer that captures the entire leak and measures the
CH4 concentration and flow rate. The emissions rate is determined from the
product of the concentration and flow rate.
•	A total enclosure technique called bagging. Uncontaminated air is blown through a
plastic bag enclosing the component: the flow rate and outlet concentration are
measured by an organic vapor analyzer, and the leak rate is determined from the
product of the concentration and flow rate.
•	A screening technique where the CH4 concentration is measured by passing a
standard organic vapor analyzer around tho soaled surface. The concentration in
air is measured and then related to an emission rate by a correlation equation. The
correlation equations were developed in other studies relating bagged emissions to
screening values.
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Tracer Gas Method
The tracer gas method of measuring CH4 emissions consists of releasing tracer gas (at a
known constant rate) near the emission source and measuring the downwind concentration of
tracer gas and CH4. Assuming that the CH4 and tracer gas mix completely, and assuming
identical dispersion, the ratio of the downwind concentrations is equal to the ratio of the release
rates. The emission rate of CH4 can then be determined on the basis of the downwind
concentrations of CH4 and tracer gas and the known release rate of the tracer. This method was
used primarily to measure emissions from meters and pressure regulating stations.
Leak Statistics Method
The leak statistics method is used to quantify the CH4 emissions from underground mains
and services in distribution systems. Emission rates are measured for a large number of leaks to
accurately determine the average emission rate per leak as a function of pipe material, age,
pressure, and soil characteristics. The leak statistics program was conducted as a cooperative
program between industry and the project sponsors. The industry participants used specially
designed equipment to measure the leak rates from underground distribution mains and services.
A pipe segment containing the leak is isolated, the isolated segment is repressurized, and the
volumetric flow required to maintain normal operating pressure in the isolated segment is
measured. The leak statistics method combines the measured leak rate per leak with the historical
leak records of the rate per mile. The emissions are determined by multiplying the leak rate per
leak by the leaks per mile and number of miles of pipe.
Calculation Approach for Unsteady Emissions
Emissions that are-intermittent or unsteady have highly variable emission rates during a
year-long period. Because it would not be practical to collect data continuously for a year for
each source, emissions from these sources were calculated rather than measured.
Data must be gathered from each unsteady source of emissions, and a unique set of
equations must be developed to quantify the average annual emissions. In general, all unsteady
sources of emissions require the following information to quantify annual emissions:
•	A detailed technical characterization of the source, identifying the important
parameters affecting emissions;
•	Data gathered from multiple sites that allow the CH4 emitted per "emissions event"
to be estimated; and
•	Data gathered from multiple sites that allow the frequency of "emission events" to
be estimated.
An example of an emissions estimate calculated for an unsteady emission source is the
estimate for vessel blowdown for routine maintenance. In this case, the volume, pressure, and
temperature of gas contained in the vessel before blowdown are "calculated" to quantify the
losses from the blowdown event. Also, an average frequency of these vessel blowdown
events is needed to determine the annual losses from this source of CH4 emissions.
Emissions from some unsteady emission sources have been quantified in other studies
by measuring the emissions per event. Therefore, the emissions data from these separate
studies were combined with site data collected in the present study to quantify the number of
events per year and estimate the annual emissions from these sources.
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General Extrapolation Methodology
Data for the project were collected from a limited number of sources and then extrapolated
to obtain nationwide estimates for similar sources throughout the industry. The extrapolation
techniques were developed so that the emissions from each source could be estimated with a
relatively high level of precision and negligible bias. The extrapolation approach uses omission
and activity factors (EF and AF) to estimate emissions on the basis of a limited number of
samples. These factors are defined in such a way that their product equals the total emissions
from a source:
EF * AF = National Emissions
Typically, the EF for a source represents the average emissions for that source; the AF
represents the total industry population of the source. The sampling approach used affects the
accuracy of the extrapolation method.
Results
This program is in its final review phase. Interim reviews resulted in the industry agreeing
to provide additional data and a redefinition of which oil/gas production facilities are included in the
scope. This redefinition and data collection are ongoing, and the numbers below do not reflect the
new data. However, the general significance of the largest sources will not be affected by the
revisions. The largest U.S. CH4 emissions sources [1] (approximately 86% of the total) and how
the estimates were made are described below and summarized in Table 3.
1.	Compressor Fugitives
Fugitive emissions refer to nearly continuous emissions from sealed and packed surfaces,
such as flange gaskets, valve stem packing, pump and compressor seals, pressure relief valve
(safety valve) seats, and ordinary valve seats on closed valves where the other side of the
valve is open to the atmosphere. Fugitives are sometimes called "leaks."
Compressor fugitives refer to the components directly associated with the compressor
that can leak. Included are the individual suction and discharge lines leading to the compressor
unit, the compressor itself, and the fuel gas system directly mounted on the compressor. Many of
the leak rates on compressors are higher than elsewhere due to compressor vibration. Examples
are the compressor pressure relief valve and the components of the fuel system. Also, some
unique components on compressors have very high emission rates. These components are the
compressor blowdown valve, the compressor suction and discharge valves, the starter gas
valve, and the compressor seals. The compressor blowdown valve and the suction/discharge
valves can leak through the valve seat to the atmosphere under certain compressor operations.
Compressor fugitives were measured in different campaigns at production sites, gas
plants, and compressor stations. Most efforts used screening by Foxboro organic vapor
analyzers backed up by bagging tests. Recent measurements on compressor stations have
accomplished screening with a new high flow rate vapor analyzer.
2.	Other Fugitives (non-compressor)
Other fugitives refer to all of the fugitive leak sources on all piping and vessel components
that are not directly on the compressor. At a compressor station, this includes most of the items
outside of the compressor building, except for the compressor piping manifold. Other fugitives,
therefore, include all of the station piping and vessels and even the parts of the fuel gas system
outside of the compressor building.
Most "other fugitives" were measured by organic vapor analyzers for screening with
bagging tests. Recent transmission compressor station site measurements were also screened
by the new high flow rate vapor analyzer.
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3. Compressor Exhaust
Compressor exhaust emissions are the uncombusted CH4 in the engine exhaust that
result from the inefficiency of the engine. These emissions are relatively small on a per unit of fuel
basis for turbines, but fairly large for reciprocating engines.
Compressor exhaust was measured by stack sampling and gas chromatograph analysis
[2]-
4.	Pneumatics
Pneumatic devices, as defined by this paper, are those gas-powered control devices that
operate valves. The pneumatic device is the controller and actuator for the valve. There are
pneumatic devices operating throttling control valves that regulate liquid level, flow, and pressure.
There are also pneumatic actuators on large compressor or pipeline isolation valves. The
pneumatic device, if powered by natural gas, can emit gas to the atmosphere during operation.
Pneumatic device emissions were estimated using engineering estimates based upon
technical characterizations, stroke frequency measurements, and manufacturer data. Bagging (total
enclosure) measurements were also used from a Canadian Petroleum Association study [3],
Tracer measurements of distribution meter and pressure regulating stations also primarily
measured pneumatic emissions.
5.	Blowdowrts
"Blow" and "purge".are terms that have different definitions in various segments of the
industry. In this paper, blow (also called "blowdown") emissions refer to the direct venting to the
atmosphere of the gas contained inside a pressure vessel, pipeline, or other equipment. Purge is
the process of clearing air from equipment by displacing it with gas; in the process, some purge
gas leaves with the air being cleared.
There are two major sources of "blow and purge" emissions from the natural gas industry:
1) maintenance blowdown/purgo, and 2) emergency/upset conditions. The first source is the
intentional release (blowdown) of gas to the atmosphoro in order to provide a safer working
environment for maintenance activities, or to restore an oxygen-free natural gas environment after
maintenance activities are finished (purge). The second source of blowdown results from
emergency conditions or upset conditions which require gas depressuring.
Other minor sources of blow and purge are not due to maintenance or upsets. Examples
are compressor start gas, sampling gas, and drip gas. These sources are vented to the
atmosphere as part of the normal operation of a gas facility. The company may or may not
include these in its definition of blow and purge gas.
Blowdown emissions were estimated using site estimates of frequency and site
observations of actual volumes and pressures. Company data on blowdown volumes were
often used directly.
6.	Underground Pipeline Leaks
Pipeline leaks refer to the buried portions of gathering, transmission, and distribution
pipelines, mains, and services. The emissions occur through defects and holes in the pipe wall
and joints.
Pipeline leaks were estimated using measured leak rates for distribution (from a detailed
leak isolation and measurement campaign) combined with company or nationally tracked data on
leak frequency.
7.	Dehydrator Vents
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Dehydrator vonts refer to CH4 that is emitted from the regenerator stack of the glycol
dehydrator unit Glycol dohydrators remove water from the natural gas stream, but they absorb
other material as well. Methane is absorbed into the glycol and driven off in the atmospheric
regenerator. Other supporting equipment, such as Kimray pumps and stripping gas lines, may
also put additional CH4 into the glycol and the reboiler.
Dehydrator vent emissions were estimated using chemical equilibrium models for
dehydrators combined with field data on dehydrator characteristics. Some field stack samples and
gas chromatograph analyses were also used.
SUMMARY
While not exhaustive, this paper has attempted to provide the reader with an overview of
how gas industry CH4 emissions have been quantified in this very comprehensive study.
Further, we have provided a list of the largest U.S. CH4 emissions sources identified in the study.
REFERENCES:
1.	"Estimate of Methane Emissions From U.S. Natural Gas Operations," Robert A. Lott, Gas
Research Institute, Presented to the International Workshop on Environmental and
Economic Impacts of Natural Gas Losses, Prague, Czech Republic, March 1994.
2.	"Compilation of Emissions Data for Stationary Reciprocating Gas Emissions Data for
Stationary Reciprocating Gas Engines and Gas Turbines in Use by the Natural Gas
Pipeline Transmission Industry," Charles M. Urban, Southwest Research Institute, May
1988.
3.	Canadian Petroleum Association, "A Detailed Inventory of CH4 and VOC Emissions From
Upstream Oil and Gas Operations in Alberta," March 1992.
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TABLE 1: INDUSTRY CHARACTERIZATIONS
Segment
Facilities
Equipment at the Facility
Production
Well Sites, Central
Gathering Facilities
Well Heads, Separators, Pneumatic Devices,
Chemical Injection Pumps, Dehydrators,
Compressors, Meters, Pipelines
Processing
Gas Plants
Vessels, Dehydrators, Compressors, Acid
Gas Removal (AGR) Units
Transmission
Transmission Pipelines,
Compressor Stations,
Meter and Pressure
Regulating Stations
Vessels, Compressors, Pipelines, Meter and
Pressure Regulating Stations, Pneumatic
Devices
Storage
Underground Injection/
Withdrawal Facilities, and
Liquefied Natural Gas
(LNG) Facilities
Well Heads, Vessels, Compressors,
Dehydrators, Pneumatic Devices
Distribution
Mains (pipelines),
Services (pipelines), Meter
and Pressure Regulating
Stations
Pipelines, Meter and Pressure Regulating
Stations, Pneumatic Devices
TABLE 2: EMISSION CHARACTERIZATIONS
Emission
Type
Specific Source Examples
Operating Mode
Steady or
Unsteady
Fugitive
Packed or Sealed Surfaces,
Leaks (holes In gathering &
distribution pipes), Leaks (holes
in transmission pipes)
Normal Operations,
Normal Operations,
Upsets
Steady, Steady,
Unsteady
Vented
Dehydrator Vents, Pipeline
Purge, Pneumatic Devices,
Compressor Starts, Equipment
Blowdown, Chemical Injection
Pump Vents, Pressure Relief
Valve Lift
Normal Operations,
Maintenance, Normal
Operations, Normal
Operations,
Maintenance, Normal
Operations, Upsets
Steady,
Unsteady,
Unsteady,
Unsteady,
Unsteady,
Unsteady,
Unsteady
Combusted
Compressor Exhaust, Flaring,
Burners
Normal Operations,
Upsets/ Maintenance,
Normal Operations
Unsteady,
Unsteady,
Unsteady
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TABLE 3: U.S. NATURAL GAS INDUSTRY LARGEST
CH4 EMISSIONS SOURCES
Source
% of Total
Compressor Fugitive Emissions
27
Compressor Exhaust
7.4
Other Fugitive Emissions (non-compressor) Production,
Processing, Transmission, Distribution Customer
Meters
8.6
Pneumatics [Includes all meter and pressure regulating
distribution (city gate) emissions]
12.5
Blowdowns
9.8
Underground Pipeline Leaks
17.4
Dehydrator Vents
3.3
TOTAL
86
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3-C
This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication.
UTILIZATION AND CONTROL OF LANDFILL METHANE BY FUEL CELLS
J. L. PRESTON AND J. C. TROCCIOLA
International Fuel Cells Corporation
195 Governors Highway
South Windsor, CT 06074 (USA)
R. J. SPIEGEL
U.S. Environmental Protection Agency
Air Pollution Prevention and Control Division
Research Triangle Park, NC 27711 (USA)
ABSTRACT
The U.S. Environmental Protection Agency (F.PA) has conducted a program to control methane emissions from
landfills using a fuel cell. The fuel cell would reduce air emissions affecting global warming, acid rain, and other
health and environmental issues. By producing useable energy, it would also reduce our dependency on foreign oil.
This paper discusses the Phase II and Phase III results of the U.S. EPA program underway at International Fuel Cells
Corporation. In this program, (wo critical issues were addressed: (i) a landfill gas cleanup method that would remove
contaminants from die gas sufficiently for fuel cell operation, and (ii) successful operation of a commercial fuel cell
power plant on the lower-heating value waste methane gas.
PROGRAM DESCRIPTION
International Fuel Cells Corporation (LFC) was awarded a contract by the U.S. EPA to demonstrate methane (CH4.)
control with energy recovery from landfill gas using a commercial phosphoric acid fuel cell. IPC has conducted a
three-phase program to show that this concept is environmentally feasible in commercial operation. Work was initi-
ated in January 1991 on Phase I that consisted primarily or a conceptual design, cost, and evaluation study.[l] The
Phase II work addressed the issue of contaminant removal from the gas. This consisted of the construction and testing
of a landfill gas cleanup module designed to remove contaminants fiorn the gas. Phase III of this program has just
completed testing of a PC25 fuel cell at an existing landfill gas-to-energy facility owned by Pacific Energy Corpora-
tion in Sun Valley, CA.
LANDFILL GAS CLEANUP
The major element of Phase II was the construction and testing of a gas cleanup system at the Penrose Landfill
in Los Angeles (Sun Valley). California site. Landfill gases consist primarily of carbon dioxide (CO2,) CH,|, nitrogen
(N2,) plus trace amounts of hydrogen sulfide, organic sulfur, organic halides, and non-methane hydrocarbons. The
specific contaminants in the landfill gas of concern to the fuel cell arc sulfur and halides. Both of these ingredients
can "poison" and therefore reduce the life of the power plant's fuel processor. The fuel processor is the unit which
converts CII4 in the landfill gas stream into hydrogen (lb) and CO2 in an endothermic reaction over a catalyst bed.
The catalyst in this bed can react with the halides and sulfides and lose its activity; i.e., poison irreversibly.
The system designed to remove fuel cell contaminants is shown in figure 1, This system is known as the Gas
Prctreatmcnt Unit (GPU). HiS is first removed by adsorption on a packed bed. The material which performs this
function is a specially treated carbon-activated to catalyze the conversion of I hS into elemental sulfur which is depos-
ited on the bed. This conversion to sulfur (i.e., the Claus Reaction) is:
H2S + 1/2 02 		 H-;0 1 s
"111is bed is not regenerable 011 site, but must be removed to anothei site if regeneration is desired.
The first stage cooler removes water, some heavy hydrocarbons, and sulfides which are discharged as condensate
to the Penrose plant's existing water condensate pretreatrnent system. Since the demonstration landfill GPU operates
on a small slipstream from the Penrose site compressor and gas cooler, some of the water and heavy hydrocarbon
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species are removed prior to the GPU. Most of the contaminant halogen and sulfur species are lighter and remain in
the landfill gas to be treated in the pietreatment unit. All remaining water in the landfill gas, as well as some sulfur
and halogen compounds, are removed in a rcgencrable dryer bed which has a high capacity for adsorbing the remaining
water vapor in the landfill gas. There are two dryer beds so that one is always operational while the other is being
regenerated. Trie dry landfill gas is then fed to the second stage cooler. This cooler can be'operated as low as -32°C
and potentially can condense out additional hydrocarbons if present at high enough concentrations. In addition the
second stage cooler reduces the temperature of the carbon bed, therefore enhancing its adsorption performance/?.]
The downstream hydrocarbon adsorption unit whose temperature is controlled by the second stage cooler, is conserva-
tively sized to remove all heavy hydrocarbon, sulfur, and halogen contaminant species in the landfill gas. This unit
consists of two beds of activated carbon so that one is always operational while the other is being regenerated. Both
the regenerate dryer and hydrocarbon removal beds operate on a nominal 16 hour cycle of each set of beds operating
in the adsorption mode for 8 hours and regeneration mode for 8 hours. The gas then passes through a particulate filter
and is warmed indirectly by an ambient air finned tube heat exchanger to ensure a fuel inlet above 0°C before being
ted to the fuel cell unit.
The GPU was constructed by IFC at its facility in South Windsor, CT Construction of the unit was completed
in February 1993. Upon completion of construction, the unit was evaluated at the South Windsor facility, using N2
as the test gas. The unit successfully completed she 16 hour control test verifying that rated flows, pressure, and tem-
perature were achieved. After the test, the unit was shipped to the landfill site located in Los Angeles, CA, where it
was installed in April 1993. Figure 2 is a photograph of the unit installed at the site.
The GPU has been successfully tested at the Penrose landfill site in Los Angeles (Sun Valley). CA. The GPU
successfully removed the sulfur and halogen compounds contained in the landfill gas to a level significantly below
the specified value for use with the phosphoric acid fuel cell and to date has operated for over 2000 hours.
Tabic I compares the measured sulfur and halide contents of the gas produced by the GPU to the specification
value. The data verify that the GPU reduces the sulfur and halide contents of landfill gas to a concentration lower than
required by the fuel eel! power p.lant. The exceptionally low GPU exit contaminant levels indicate that the low temper-
ature cooler is not esseniial, even though the reduced temperature in the activated carbon bed increases capacity for
sullur and halogen compounds. For system simplification in the future, it may be beneficial to eliminate the low tem-
perature cooler, and simplify the refrigeration system, in exchange tor increasing the activated carbon bed value slight-
ly. Based on the favorable results of the GPU testing, the EPA directed IFC to proceed into Phase III of this program
which entails characterizing the performance; i.e., emissions, efficiency, and power output of the commercial phos-
phoric acid fuel cell power plant when operating on landfill gas which has been purified by the GPU.
FUEL CELL TESTING
The power plant utilized in this program is a commercial PC25 200 kW phosphoric acid fuel cell. 'Die power
plant was shipped and installed at the Penrose landfill during 1994 (Figure 3). The unit was started on natural gas prior
10 iis modification Ibr operation on landfill gas. This testing was conducted to establish a baseline performance level.
Upon completion of the natural gas testing, the unit was shut down, modified for low Btu gas and subsequently con-
nected to the GPU for testing on landfill gas. All power produced by the unit was fed into the electrical grid tor sale
to the local electrical utility, the Los Angeles Department of Water and Power (LADWPj. This fuel cell is the first
ever connected to the l.ADWP's grid utility system. Hie revenue produced by the sale of this electricity was used
10 heb offset program costs.
Emission testing of the power plant effluent was conducted by TRC Environmental during February of 1995.
Using EPA Methods 6c. 7e, and 10, respectively, emission levels of sulfur dioxide (SO?) were undetectable at a detec-
tion limit of 0.23 ppm, while nitrogen oxides averaged 0.12 ppm and carbon monoxide (CO) averaged 0,77 ppm. All
data are dry measurements corrected to 15 % oxygen (Cb). These emission levels verify that fuel cells can operate
on landfill gas while maintaining the low emission levels characteristic of this commercial fuel cell power plant. Addi-
tional peifoiinanct* data will be contained in the Phase III final report.
An exciting dimension of the PC25 operating on landfill gas is that, unlike internal combustion engines and tur-
bines, the unit has significant siting characteristics due to its demonstrated low levels of emissions, noise, and vibra-
tion. It can be located remote from the landfill using gas piped from the site. In this way, its thermal energy, as well
as its power, can be put to constructive use at a customer's building. In addition, by siting at the building the economics
improve significantly since the power plant displaces commercial electricity which has a much higher cost than the
revenue which would lie received if the fuel cell were sited at a landfill and received a uiilitics "avoided" cost. Utilis-
ing die fuel cell's thermal energy can result in an overall efficiency [i.e., (Electrical Unergy plus Thermal EnergyVEn-
ergy Content of Gas Consumed)J of 80 %. This high efficiency conserves natural resources and reduces the amount
of CO2 emitted to die atmosphere. It also improves the economics, since heat may be sold to the building owner.
3-24
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SUMMARY
Methane emissions from landfills and other sites are potential contributors to global wanning. Conventional
methods to mitigate these emissions, such as flaring, produce other greenhouse gases such as CO2- By operating a
fuel cell at a landfill site, CH4 is destroyed with universal secondary emissions (CO, SO?, NOx) while efficiently gener-
ating electric powei and lowering total CO2 emissions. In order to operate a fuel cell on landfill gas, the gas must be
"cleaned up" or purified. A landfill gas cleanup prclrcatincnt module was designed, constructed, and tested at a landfill
site. Results indicate that the unit removed all impurities detrimental to the fuel cell. The gas cleanup pretreatment
module was subsequently connected to a commercial fuel cell power plant. The cleanup system/fuel cell power plant
system produced electrical power with low levels of air pollution.
ACKNOWLEDGEMENTS
This materia] has been funded by the U.S. Environmental Protection Agency (EPA) under contract 68-D1-0008
to International Fuel Cells Corporation, This paper lias been subjected to the Agency's review and been approved for
publication. Mention of trade names or commercial products does not constitute endorsement or recommendation
for use.
REFERENCES
[1] Sandelli, G. J. "'Demonstration of Fuel Cells to Recover Energy From Landfill Gas Phase I Final Report: Conceptu-
al Study"; EPA-600-R-92-007; (NI'IS PB92-137520), January 1992.
12] Graham, J. R. and Ramaratnan, M. "Recover)' of VOC's Using Activated Carbon"; Chemical Engineering,
Vol. 100, No. 2, p. 6-12, February 1993.
TABLE I. GPU SULFUR AND HALIDE CONTAMINANT REMOVAL PERFORMANCE

VS SPECIFICATION (ppmV)


GPU Inlet
GPU Exit
Specified Value
Total Sulfur (as II2S)'
117
< 0.047
< 3
Total Halides (as Chloride)2
47
< 0.032
< 3
' Measured by (Jas Chromatography:t tome Photometric Delineation by Et'A Methods IS. Iti, ami

2 Measured by Gas Chrommngmnhy'
Vf/M 1 Spectrometry hy EPA Method TO-14

FIGURE 1: LANDFILL GAS PRETREATMENT SYSTEM
HsS
ADSORBER
-N
-7
COOLER
CONDENSER
3
OFSICCANTS

LOW
TEMPERATURE
COOLER
CONDENSER
3



ACTIVATED

PARTICULATE
CAnBON
/
HLfbH
CONDENSATION
OF V^ATER AND
HYDROCAR
SONS
ADSORPTION
OP WATER
250^0
REGENERATION
ADSORPTION
HYDROCARBONS INCLUDING ORGANIC
SUtrtlR AND HALOGEN COMPOUNDS
26Q8C
REGENERATION
—X CLEAN
1	I Mi
TO
r uo_
CELL
REGENERATION
lt.6 liters/sec
~
TO
TO
FLAR5

H/C
Of: SORPTION




HP2S501
R951104
3-25
[IP 296

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F1GUKL 2: GPU INSTALLATION AT PACIFIC ENERGY LANDFILL
Reproduced from
best available copy.™
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This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication.
METHANE RECOVERY FROM LANDFILLS .AND AN
OVERVIEW OF EPA/APPCD'S LANDFILL GAS RESEARCH PROGRAM
Susan A. Thorneloe
U.S. Environmental Protection Agency
Air Pollution Prevention and Control Division
Research Triangle Park, North Carolina 27711
John G. Pacey
Chairman-SWANA's Landfill Gas Recovery and Utilization Committee
Emcon Associates
San Jose, California 94402
Michiel Doorn
E. H. Pechan & Associates, Inc.
3500 Westgate Drive, Suite 103
Durham, North Carolina 27707
ABSTRACT
Clean Air Act (CAA) regulations for new and existing municipal solid waste
(MSW) landfills which were proposed in May 1991 are scheduled to be promulgated in
August 1995. These regulations are expected to require up to 400 landfills to install
and maintain a landfill gas (LFG) extraction and control Facility to reduce landfill air
emissions. These emissions include nonmethane organic compounds (NMOCs)
which contribute to tropospheric ozone, methane which is a potent greenhouse gas,
and toxic compounds which are of concern to public health (U.S. EPA, 1991 and
Najarian, 1994 and 1995). In addition, landfills that are subject to New Source Review
may also be considered for controls to reduce landfill air emissions. Control options
include flaring the gas or combustion with energy recovery which include (1) direct
use of the gas as medium heating value fuel, (2) generation of electricity using
reciprocating internal combustion (IC) engines, gas or steam turbines, or fuel cells,
and (3) upgrading the gas to pipeline quality or to produce vehicular fuel. Many landfill
owners will be evaluating their options for controlling landfill air emissions and will be
considering if it is practical and economical to minimize potential control costs
through the development of a LFG utUization project.
This paper summarizes ongoing research at EPA's Air Pollution Prevention and
Control Division (the former Air and Energy Engineering Research Laboratory) on LFG
utilization. Research was conducted to identify the technical issues and solutions
through interviews conducted with industry experts in the U.S., Europe, and Australia.
The U.S. developers and operators who were interviewed represent over 70% of the
projects in the U.S. Technical issues associated with the use of LFG as compared to

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natural gas -- which is the primary fuel used for energy conversion equipment such as
IC engines, gas turbines, and fuel cells - can result due to chlorinated and toxic
compounds, particulate, and reduced heating value when compared to natural gas
[18.6 vs. 37.2x106 j/m3 (500 vs. 1000 Btu/scf)]. A recent database of l.FG-to-energy
projects that has been developed through a collaborative program between
EPA/APPC.D and the Solid Waste Association of North America (SWANA), indicates
that, as of December 1994, there arc 137 LFG-to-cncrgy projects in the U.S. and 9 in
Canada. This paper will summarize statistics and industry trends resulting from this
database, and discusses the nontechnical and technical issues and solutions. Other
EPA/APPCD research that will be discussed in this paper is a recent overview of
emerging technologies for LFG utilization and research regarding the demonstration
of fuel cells for LFG utilization.
The research described is funded through the U.S. EPA's Global Climate
Change Research Program. This research is part of a larger EPA research program to
develop more reliable emission estimates for the major sources of greenhouse gas
emissions and to identify cost-cffective opportunities for reducing greenhouse gas
emissions. This research is being conducted in support of the goals established at
the United Nations Conference on Environment and Development in 1992 and the
Climate Change Action Plan (1993).
INTRODUCTION
The EPA/AJPPCD'has estimated that U.S. landfills containing municipal solid
waste (MSW), industrial waste, and construction and demolition debris waste
contribute 9 to 18 teragrams (Tg) per year of methane with an average of 13 Tg
(Doom, Stefanski, and Barlaz, 1994). Global sources of methane emissions from
landfills and open dumps have been estimated by EPA/APPCD to range from 19 to 40
Tg/yr with an average of 30 Tg/yr (Doom and Barlaz, 1995). Global anthropogenic
sources emit 360 Tg/yr (IPCC, 1992), which suggests that landfills and open dumps
account for 5 to 11% of the total (Thorneloe, 1993). The soon-to-be-promulgated
Clean Air Act (CAA) regulations are estimated to result in a reduction of 5 Tg/yr of
methane or 39% of the baseline emissions attributed to MSW landfills. Many other
countries arc also looking at regulatory controls or incentives to encourage control of
LFG emissions as part of the goals set in 1992 to stabilize greenhouse gas (GIIG)
emissions to 1990 levels by the year 2000. EPA/APPCD is conducting research to: (1)
develop more reliable estimates of landfill emissions including methane and NMOCs,
(2) develop emission methodologies for estimating landfill emissions, (3) evaluate
existing and innovative and/or emerging technologies for LFG pretreatment and
utilization, (4) develop technology transfer information to assist landfill
owners/operators who are considering control options, and (5) research and
demonstration of innovative technologies for LFG such as the use of fuel cells. In
addition, APPCD in conjunction with SWANA has developed a more reliable database
of LFG-to-energy projects in North America (Thorneloe and Pacey, 1994). This paper
provides a brief summary of this research.
The EPA's Office of Air Quality Planning and Standards has estimated that 400
landfills will be affected by CAA regulations that are scheduled for promulgation in
August 1995. These rules include New Source Performance Standards and Emission
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Guidelines that will require landfill owners/operators to install LFG extraction and
control systems over the next 2 to 5 years. Landfills that are anticipated to be
targeted by the rule are those sites that contain 2.5 million tons (2.25 million tonnes)
of waste or more and that have a mass emission rate of SO Mg/yr of NMOCs (Najarian,
1995). Control systems may be flares or may include energy recovery such as:
•	Direct use as medium heat-value fuel; e.g., in boilers and brick or cement
kilns,
•	Generation of electricity using reciprocating internal combustion (IC)
engines, gas turbines, or steam turbines, and
•	Upgrading the gas for use as pipeline quality gas or as vehicular fuel.
A LFG-to-energy project provides an opportunity to offset potential control costs, but
many factors need to be considered in determining if it is practical or economical. In
addition, many factors need to be considered when designing and operating these
systems.
APPCD interviewed major developers and operators to gain insight on the
philosophies that lead to successful projects. The findings from this research were
recently published (Doom, Pacey, and Augenstein, 1995) and indicate that there are a
variety of views with varying trade-offs regarding issues such as the extent of gas
cleanup and frequency of energy-equipment overhauls. This report was a follow-up
to research conducted in 1991 and 1992 which reviewed Ihe state of technology of
LFG applications, provided detailed case studies of 6 sites and information on over 50
projects, and reviewed the major capital and operating costs (Augenstein and Pacey,
1992, Thorneloe, 1994). In addition, information on the nontechnical barriers has also
been documented through interviews conducted with industry and regulatory experts
(Thorneloe, 1992a and Doom, Pacey, and Augenstein, 1995). Recently completed
research included a review of emerging technologies including up-to-date
information on fuel cell technology and processes for producing methanol from
landfill gas. A series of technical reports have been developed which are
summarized in this paper. This information is to help those that are making decisions
regarding whether to develop a LFG-to-energy project.
NONTECHNICAL ISSUES AND TRENDS
The LFG industry is almost 20 years old. The first commercial LFG energy
conversion project was initiated in 1974 and was placed on-line at Palos Verdes
landfill, Rolling Hills, California, in 1975. It converted LFG to pipeline quality gas that
was sold to the Southern California Gas Company. Several additional LFG-to-pipeline-
quality projects were brought on-line in the late 1970s, including Mountain View
(1978) and Monterey Park (1979), both in California. Direct-firing-boiler projects were
brought on-line in the late 1970s and early 1980s. The first LFG-to-electricity project
occurred at Brattleboro, Vermont, in 1982, and electrical projects have dominated
ever since. Currently there arc 137 LFG utilization projects in the U.S. and 9 in
Canada. Most projects are in California and the Northeast.
In general, we found that most of the developers favored incentives that help
to overcome unfavorable economics which are primarily due to low fossil fuel cost.
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Over the last decade, energy prices have neither been adequate nor sufficiently
stable to support new projects. States that have provided incentives have helped to
encourage new projects. For example, in 1981 California offered what is known as
Standard Offer #4 (i.e., SO4) which provided a price favored contract that utilities must
offer. The last project under SO4 was started in 1990. Several of these contracts
have expired, and some projects have had to close down when the pricing structure
reverted to the avoided cost price basis (of the utility). New Jersey, New York, and
Pennsylvania adopted a Pioneer Floor Rate of $0.06 per kilowatt-hour (kWh) in the mid-
1980s; however, this was canceled several years ago. Illinois, Michigan, and
Wisconsin have offered energy price incentives to limited LFG projects, thereby
encouraging project development. In the recently completed report (Doom, Pacey,
and Augenstein, 1995), figures are provided showing the distribution of projects in
the U.S. and the number of projects by state, electrical output, and the type of
generating equipment. As a result of the potential CAA regulations requiring 400
sites to install LFG extraction and control systems and efforts by EPA's Outreach
Program to encourage states and utilities to encourage LFG utilization, an increase in
the number of new projects is expected.
Nontechnical issues also exist in other countries, and a recent paper by the
International Energy Agency indicated that for projects to be successful there needs
to be a recognition of the potential for LFG-to-energy utilization and the
environmental benefits resulting from these projects which include the conservation
of fossil fuel (Meadows and Maunder, 1995). Nontechnical issues include, but are
not limited to: 1) energy conversion (i.e., direct gas use, electricity generation,
upgrading gas to pipeline quality), 2) project economics (financing, return on
investment, profit, cost/benefit, etc.), 3) barriers and incentives, and 4) organizational
structure (Thorneloe, 1992b). These issues are discussed below.
Energy Conversion
Generally, direct firing (i.e., boiler or kiln), immediately adjacent to the landfill,
is the most cost effective type of project. However, there are not always boilers near
landfills and with continuous fuel demands (i.e., 24 hours a day, 7 days a week). Also,
larger landfills produce quantities of gas that require several nearby gas customers
requiring continuous demand for fuel in order for all of the gas to be utilized. In the
U.S., 33 projects out of 137 (i.e., 24%) are direct gas use. Reciprocating IC engines are
the most widely used option with 73 projects or 53% of the LFG-to-energy projects in
the U.S. The recent trend towards the use of low-pressure engines eliminates the
need for high pressure compressor which reduces by-product emissions and
parasitic loading. Projects that upgrade gas to pipeline quality have not always been
economically viable over the past decade although there is an interest in vehicle fuel
projects. The major trend of the last decade has been significant growth in the use
of reciprocating IC engines for LFG-to-energy applications (Figure 1).
Figures I through 4 demonstrate the trend in number and type of energy
conversion projects, major manufacturer's equipment selected for the electricity
conversion projects (the principal energy conversion choice of the small to medium
size landfills), and major developers.
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Project Economics
A new point of view on project economics is that the landfill owner shares the
cost of developing the project with the LFG developer who helps offset the regulatory
control costs. In the past the developer was responsible for all costs and LFG-to-
energy projects were considered as a pollution source rather than pollution
prevention. The EPA does consider LFG-to energy projects as pollution prevention
and therefore offsets can be considered by states in permitting projects in
nonattainment areas. Historically, developers were responsible for all costs for a new
project including permitting, legal fees and administrative, engineering, gas extraction
wells, blower (or compressor), energy equipment, and royalties. The CAA
requirements will result in up to 400 sites to extract, collect, and combust I.FG
emissions. Although the cost of energy is low resulting in less revenue for new
projects, an increase in new projects is anticipated. Also there seems to be a
recognition of the pollution prevention benefits such as the offset of fossil fuel
emissions and the conservation of fossil fuel. Many communities are recognizing
that potential control costs can be offset and are working with developers to develop
mutually beneficial projects.
Financing is frequently an issue with LFG project development. As always in a
free market the lender wants security, and the developer wants profit. The lending
rate is a function of many tilings, but risk is high on the list of concerns by today's
financial institutions, and LFG projects receive close scrutiny by today's lenders. The
amount of LFG over a period of 15 years or more can be estimated more reliably now
than 20 years ago. However, often the kind of information that one needs, such as
the amount of waste in a landfill, waste composition, acceptance rate over time, and
age of waste in different areas of landfill, is not readily available or not reliable. For
those, and many more reasons, estimates of LFG generation are generally expressed
in a range. Financial institutions want reliable estimates of LFG potential to projected
rates of return. However, a 20 to 30% difference may be the difference in profit or
loss, and modeling LFG potential is often much less certain. Probably the main reason
for projects to shut down has been inadequate gas quantities to support the energy
equipment. Many developers are going to modular skid-mounted systems so that
equipment can be readily transferred to match gas availability. Many financial
institutions consider LFG-to-energy projects somewhat as a high risk. However, as
the environmental externalities are considered, the number of LFG-to-energy projects
are likely to increase in the future. On occasion the equipment manufacturer/sup-
plier will assist in the project; utility subsidiary companies have assisted in financing
and project development. Several non-regulated utility subsidiaries are currently
active in LFG project development.
Barriers and Incentives
The soon-to-be-final CAA regulations for new and existing MSW landfills should
help to encourage new LFG-to-encrgy projects. In addition, EPA's Landfill Methane
Outreach Program was initiated to encourage new projects by working with states and
utilities. EPA/APPCD research has been directed to provide information of benefit to
landfill owners/operators and to encourage innovative technologies.
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Potential barriers to the development of new projects and the expansion of
existing projects include:
•	unfavorable economics due to low energy costs and high debt service rates for
LTG-to-energy projects that generate electricity or pipeline quality gas,
•	a limited and unstable market place,
•	increased requirements for by-product emissions (e.g., nitrogen oxides and
carbon monoxide) for projects located in nonattainment regions (New Source
Review does consider these projects to be pollution prevention projects and
provides opportunity for slates to consider offsets for these projects. A
methodology has been developed by EPA/APPCD that will allow for
quantification of these pollution prevention benefits. This report is expected
to be released soon.)
•	difficulties in obtaining "attractive" power contracts with local utilities who are
often primarily interested in purchasing low-cost power without considering
environmental externalities (e.g., offsets from power plants using fossil fuel)
[several developers indicated that they were finding it increasingly challenging
to obtain project revenues that cover operating and maintenance, debt service,
royalty payments, and acceptable rate of return], and
•	taxation by some states, such as California and Michigan, on I.FG extraction and
energy conversion facilities.
Energy costs have varied over time and are different across North America.
They vary because LFG'has competitive energy forms and pricing, and the same
energy form has its own pricing that varies widely according to geographic location.
LFG has to compete with coal, oil, natural gas, etc.
For the most part, LFG users must be near the landfill, as it is costly to install
pipelines for transport offsite. This is what makes electricity production the most
favored of LFG-to-energy conversion projects: electricity distribution lines are usually
near the landfill. The pricing structure should be reasonably stable and sufficient to
support project economics which include costs, debt service, royalty payments to
the landfill owner, and an acceptable rate of return to the developers/investors for
privately owned projects (McGuigan et al., 199S).
Many developers who were interviewed reported difficulties in the planning
process, interaction with state and local air agencies, and a variety of state and
federal regulations. Often permits must be obtained from several agencies including
permits for safety, solid waste, water, and air. Industry has claimed that often the
rules are conflicting and that pollution prevention benefits are not considered (Wong,
1992). Recent steps taken by EPA to consolidate regulatory requirements into one
permit will hopefully prevent some of these difficulties in the future.
Factors that help to encourage such projects in the U.S. include: 1) Production
Tax Credits (PTCs); 2) favorable utility contracts for electricity projects; 3) tax
exemptions for LFG extraction and energy conversion facilities; 4) Renewable Energy
Production Incentives in the Energy Policy Act of 1992; and 5) future availability of
retail electricity wheeling.
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PTCs are available to a tax paying entity that has the right to sell the LFG and
does sell it to an energy user who purchases the LFG and converts it to energy.
These PTCs are currently worth about 1.3 cents/kWh sold and are equivalent to a
dollar for dollar tax value. The PTC benefit Is scheduled to phase out in the year 2002
or 2007, depending on the date of extraction system startup for projects installed
prior to the end of 1996. Congress will have to decide if these extensions are to be
continued.
States can help to encourage projects by requiring utilities to pay incentive
rates to LFG projects and by mandating a certain level of capacity be derived from
LFG projects. States can also exclude the LFG-related energy conversion systems
from state taxation. Some utilities are encouraging LFG energy conversion projects by
participating in their developmenl and are joining in ventures to encourage LFG
development.
Organizational Structure
There are many variations in the position the owner/operator takes in regard to
development of an energy conversion project on a site. It is important to recognize
that many successful energy recovery projects appear to embody the following key
elements:
•	they are run by experienced professional management,
•	they are adequately financed so that labor, inventory, and supplies are on
hand as needed,
•	they have an excess LFG gas supply and a favorable market place,
•	the landfill is active and remains so for 5 to 10 more years, and
•	the project is staffed by experienced personnel, and there is backup for
servicing of the LFG extraction and energy conversion systems.
Some companies provide turnkey design/construction for energy conversion
units and will provide the operating and maintenance (O&M) activity as well; some
provide the same turnkey sendee for the extraction systems. The service industry is
expected to increase in response to potential CAA regulatory requirements. The EPA
report (Doorn, Pacey, and Augenstein, 1995) lists the companies that provide
different services related to LFG-to-energy project development, construction, and
O&M.
TECHNICAL ISSUES
LFG compared to natural gas is considered "dirty and wet." LFG trace gases are
primarily NMOCs and are thought to originate from volatile materials discarded in
refuse. Most NMOCs are harmless In energy uses, but potential problems are caused
by halocarbons, including the chlorofluorocarbons widely used in the past in
refrigeration equipment and as aerosol propellants, and other solvents such as dry
cleaning fluids. By-products from the combustion of halocarbons are readily reactive
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with, for example, metal in IC engines. Other NMOCs (such as organic acids) can also
present corrosion problems.
Particulate Matter and Deposits
Landfills contain soil and other particulate material which can be drawn into the
LFG stream. ITiis could pose various problems, including deposits in IC engines and
buildups in the oil of IC engines resulting in shortened oil life and increased wear.
Particulates can be removed by gas filtration, but dimethyl siloxane deposits may still
slowly build up in IC engine cylinders or in gas turbines. These deposits can be
effectively averted by gas refrigeration. Siloxane deposits may have the following
severe consequences:
•	Over time they slowly decrease combustion chamber volume, and
increase compression ratio and tendency to detonate.
•	Chips of deposited material may flake off and cause abrasion of parts
such as valve stems and guides.
•	Finally, the deposits are typically hard, so that removal requires power tools.
LFG Energy Content
Compared to natural gas, nonmethane constituents dilute the LFG, reducing its
energy* content per unit volume. One consequent requirement is that the energy
system, including valves, pipes, and fuel metering, must introduce about twice the
gas volume, relative to incoming air, as is required with pipeline gas. LFG displays
temporal variations in volume and energy content. Gas energy content must be
known and monitored so that fuel metering (for example the air/fuel ratio) can be
adjusted. Gas composition may be measured by methods based on principles of
thermal conductivity, infrared absorption, or gas chromatography. Flow is typically
measured by Pitot tube, orifice plate, and turbine flowmeter methods.
TECHNICAL REMEDIES
Material Modifications
For gas pretreatment, simple rules include preventing condensate as much as
possible and avoiding carbon steel where an aqueous phase might occur. When used
in low pressure situations [i.e., less than 70x103 Pa (10 psi)], carbon steel users may
coat the steel with corrosion-resistant plastic or use polyvinyl chloride (PVC) and
polyethylene. Most designs stipulate the use of stainless steel piping between the
blower (or compressor) and the engine. For higher pressure applications, zinc- or
epoxy-coated carbon steel or stainless steel may be used. Alternatively, with
polyethylene pipe and where cleanliness is not an issue, traps may be used. A case
study has been reported (Augenstein and Pacey, 1992).
For energy conversion equipment, material adaptations are most prevalent with
reciprocating IC engines. The parts of engines most frequently susceptible to
corrosion or wear have proven to be exhaust valves, valve guides, and stems. In many
cases these are now chrome plated. Based on reports from those surveyed,
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including both operators and manufacturers, modifications do not appear to be
extensive and are nowadays custom built into engine models that are standard for
natural gas. Turbine and boiler manufacturers indicate that typically no significant
material modifications are made to the "standard" for conventional fuels applications.
Condensate Management
Condensate is the dilute solution (1 to a few percent) of the condensed water
and contaminants found in LFG that may form as a result of decreasing gas
temperature and/or increasing pressure. Condensate generated in field collection
lines must be drained to avoid blockage. Even with appropriate field collection
system drainage, some condensate will typically reach the plant. Further, condensate
can also result within the plant, due to cooling or refrigeration following gas
compression.
To manage condensate in the field, gas pipes and headers are sloped to allow
drainage to a low point, where the liquid is collected in condensate traps. To protect
the motor, blower, or compressor unit from a sudden large charge of condensate
originating in the extraction system, a condensate interceptor tank [3,785 liters (1,000
gallons) or largerl is usually placed inline directly ahead of the blower or compressor.
Management may elect to cool the gas slightly, refrigerate it to slightly above
freezing, or cool it to - 30 or 35°C (- 20 or 30°F). Compression (with aftercooling),
refrigeration, and cooling to - 30 or 35°C can generate progressively large amounts of
condensate as the gas loses its capacity to hold water and other condensibles (which
is the intention). With IC engines, evidence suggests that condensate may produce
deposits and accelerated wear in IC engines, which may be due not only to deposits
but also to the corrosive nature of condensate.
Another approach to condensate management is to avoid its formation. For
instance, after passage through the knockout tank, the gas may be reheated to avoid
further condensation in the gas feed lines prior to the engines. This may be done in
an air exchanger that absorbs heat from the gas leaving the blower. Refrigerating the
incoming gas stream and removing the resulting condensate has been observed to
result in some benefits (reduced engine deposits, increased oil life, and reported
reductions of other problems).
To remove water vapor, a chemical desiccant, such as glycol or silica, may be
used for those processes where LFG is being upgraded for use as pipeline quality gas
or as vehicular fuel. Several more rigorous cleanup methods may also be applied to
remove stubborn contaminants.
Oil Selection and Management (Reriprnralinp IC Fnpiiips)
With conventional fuels, corrosive compounds stem largely from combustion
of the sulfur in the fuel. However, for l.FG-fueled reciprocating IC engines, the
compounds of concern are the halogens which contribute to an acidic environment.
Chemical additives to the oil can largely neutralize these compounds and reduce
corrosion of engine metal that would otherwise occur. Because of the severity of oil
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service in I.FG engines, frequent oil analyses are conducted in which Total Base
Number, nitration, metal content, and various other components are followed to
determine when replacement is warranted. Levels of metal concentrations will
indicate the degree of wear since the previous oil change, and can help to detect
engine problems.
The buildup of deleterious volatile compounds in engine oil may be reduced
by providing positive crankcase ventilation. Another route to reduce buildup of
volatiles in the oil is to increase cooling water temperature, hence block and oil
temperature, so that evaporation is maximized and condensation minimized. This
will also facilitate vaporization of water in the oil. Ongoing research by EPA/APPCD
has developed a case study on lubrication of spark ignition engines at the Stewartby
site in the United Kingdom.
Engine Adjustments (Reciprocating 1C Engines)
On average, LFG contains only half the amount of methane that natural gas has,
necessitating modification of the fuel/air ratio for gas engines originally designed for
natural gas. Controls are recommended to maintain the desired fuel/air ratio at a
relatively constant level, as energy content of the incoming LFG may vary.
Proper spark advance for the mixture and conditions is key to efficient engine
operation. A typical practice with reciprocating IC engines for natural gas is to
advance the spark to a'constant setting or to follow a preset ratio. Sometimes the
spark setting is adjusted based on fuel/air composition which requires appropriate
measurement and feedback. Maximum engine efficiency, whatever the fuel
composition, is normally obtained with maximum advance (as long as detonation is
avoided).
A general control problem in lean-burn reciprocating IC engines, that relates to
both carburation and ignition timing, is that sudden fuel-rich conditions may occur
with swings in LFG energy content. This condition can result in detonation and severe
engine damage. The air supply to lean-burn engines must be pressurized by
turbocharging. The expansion section is susceptible to damage from any deposits
associated with LFG use.
FIELD EXPERIENCE
Boilers
The most common approach to gas cleanup is to apply minimum gas cleanup,
limited to condensate knockout and optional particulate filtration. The design needs
to be adjusted for the lower energy' content of the LFG flow, an approximate doubling
of burner orifice area (at constant fuel delivery pressure).
A LFG-fueled steam boiler, that supplies 53,000 kg/hr (24,000 lb/hr) (at peak
output) of steam to a pharmaceutical plant in Raleigh, NC, is described in the first
EPA/APPCD report on LFG utilization (Augenstein and Pacey, 1992). Minimal gas
cleanup is employed [condensate simply drops out of a low point in the 1210 m (3/4-
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mi) gas pipeline supplying the plant]. The boiler is equipped for multifucl operation,
incorporating a LFG burner ring and separate dedicated oil and pipeline gas burners.
No operating problems, related to LFG use, have been observed, and the boiler has
functioned well to date. Some corrosion of the inner door and external pipe fittings
did occur, but replacement cost is relatively low.
Reciprocating IC Engines
Early in the history of LFG energy (mid-1980s), cleanup of LFG for use in
reciprocating IC engines was often limited to condensate knockout and particulate
filtration. This procedure was reported to be fairly inefficient: some condensate was
actually aspirated into the engine with the LFG fuel, giving (as might be expected) poor
results. Engines were stated to be "corroded out within a few thousand hours." A
variety of design and materials modifications including chromed valves and hardened
piston rings were applied to ameliorate problems. However, in one case, operating
experience improved only when refrigerated gas cleanup was applied. Minimal
cleanup regimens may suffice under certain conditions ; e.g., at the Marina Landfill in
Monterey County, CA, which uses no gas cleanup other than collection of
condensate and minimal filtration (section 5.3 of Augenstein and Pacey, 1992).
Marina recently added an additional engine and modified the pretreatment system to
include particulate filtration, gas cooling, and heating.
Today's engines are relatively low pressure systems requiring low pressure [<
14x103 Pa (< 2 psi>] LFG delivery to the engines. This has eliminated the need for
compressors with their associated high capital cost and maintenance. A major
operator has recently published details of its experience and has provided further
information in response to the survey conducted by EPA/APPCD (Anderson, 1993).
This operator uses lean-burn Caterpillar 3516 IC engines, and the gas processing
sequence is:
•	Knockout tank with top-end mesh pad,
•	Gas supply [~7xl 03 to 50xl0;! Pa (~1 to 7 psi)] to low-pressure engines
with positive displacement Roots blower,
•	Gas cooling to design dewpoint,
•	Fine filtration and condensate removal, and
•	Gas reheat to ~70°C (~20°F) above dewpoint.
On-line time has been between 89 and 95%. Under circumstances where gas
availability is not limiting, 96% on-line time is even better. Top-end overhaul intervals
are of the order of 8,000 hours, which matches Caterpillar's recommended interval.
Oil changes are reported typically at 700 hour intervals.
Currently, five operators use LFG in turbines, mostly Solar Saturn or Centaur
turbines. These are predominantly "standard" units, except that the combustors are
modified to permit necessary entrance of more gas. Turbine materials have not been
modified, compared to their operation on pipeline gas. For all turbines, temperature
control ("temperature topping") is necessary to prevent overheating of the blades and
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to maximize power recovery. For I.FG-fueled turbines, where energy' content may on
occasion vary rapidly, the fuel/air control must react rapidly or temperature will
overshoot. The temperature overshoot will "trip" and automatically shut down the
turbine. To prevent this-which is more an aggravation, than a serious problem-the
turbine is operated at a slightly lower temperature setpoint and efficiency than is
normal with conventional fuels.
A	typical cleanup sequence would be:
¦	Knockout tank,
•	Stainless steel wire mesh pad, or coalescing filter,
•	LFG compression to 1.2x1 OR Pa (175 psig),
•	Separation of oil from compressed gas,
•	Gas cooling by air heat exchange,
•	Condensate removal by filtration,
•	Reheat, and
•	Final filtration.
LFG Purification to Natural Gas (Pipeline) Qualify
The Environmental/Energy Division of Air Products and Chemicals, Inc. is the
principal entity in pipeline gas preparation (although Browning-Ferris Indust ries also
has a plant). The Gemini™ process used by Air Products, in very brief overview,
consists of:
•	Refrigeration to remove condensate,
•	A solid sorbent pretreatment system employing activated carbon, iron
sponge, and other sorbents to take out the contaminants other than carbon
dioxide (CO2), and
•	Pressure-swing absorption CO2 removal.
For both pretreatment and CO2 removal, multiple fixed-bed columns are used
and regenerated in a batchwise-continuous fashion (gas is cleaned up by columns
with fresh sorbent, while other columns are regenerated off-line). Plant personnel
consider this process to have performed satisfactorily. A general consideration with
the above pipeline purification processes is that nitrogen and oxygen must be limited
in the LFG to the plant, since none of the processes listed above can remove them.
EMERGING TECHNOLOGIES
An EPA report has been developed based on EPA research conducted by
APPCD. This report is expected to be available soon. It provides a critical review of
the different technologies that are being demonstrated in field- and/or bench-scale
LFG demonstration projects which include fuel cells, production of compressed
natural gas for vehicle fuel, production of methanol, and production of commercial
C02 and liquefied natural gas. Other potentially applicable technologies that are
discussed include Stirling cycle and organic Rankine cycle. For each technology or
process, the report provides an overview, process description, and information on its
extent of use, performance, potential emission reduction capability, and potential for
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by-product emission, economics, and technical issues. Provided below is a brief
write-up of three technologies that are being field demonstrated in the U.S.
Vehicular Fuel
Vehicle fueling with compressed gas Is of high interest for environmental and
other reasons. Technology for such fueling is well established. It was reported that,
worldwide in 1990, at least 700,000 vehicles, including many passenger cars, were
fueled by natural gas. Using LFG would involve purification and compression for
reduced-volume storage on board vehicles. The vehicles would have to be equipped
with conversion kits, which include safety devices, to manage the high pressures
involved.
The Selcxol Process and Pressure Swing Adsorption arc two technologies with
merit for the LFG industry. Both have been applied to projects with relatively large gas
flows of 85 x 10fi liters (or 3 x 106 scf) per day or more. For smaller projects,
membrane separation appears to be more suited. Membrane separation may be
combined with absorption or other mechanisms. At the Puente Hills landfill of the
Los Angeles County Sanitation District, a membrane separation system and a LFG
fueling facility have been installed. A demonstration project is underway to verify the
operational performance of different vehicles running on LFG that has approximately
97% methane.
Fuel Cells
Fuel cells have been a well established technology for using natural gas to
generate energy for more than 20 years. They are currently being considered for LFG
applications. The EPA initiated a research, development, and demonstration (RD&D)
project in 1991 to evaluate the use of commercially available fuel cells for LFG
applications because of potential environmental and energy efficiency
characteristics which include:
•	higher energy efficiency (-40%) than conventional technologies,
•	minimal by-product emissions which can be a critical
consideration in nitrogen oxides and carbon monoxide
nonattainment regions,
•	ability to operate in remote areas,
•	minimal labor and maintenance,
•	minimal noise impact (i.e., there are no moving parts), and
•	availability to smaller as well as larger landfills (available in 200 kW
modules).
The major technical issue associated with the application of fuel cells to LFG
projects is the gas cleanup system. The gas cleanup system is designed to clean the
gas to 3 ppmv of chlorides and 3 ppmv of sulfur (Sandelli, 1992). The gas cleanup
system has operated over 2,600 hours with no problems and producing gas of quality
at 0.001 ppmv which is much better than the design specifications. The fuel cell
operated for 4 months on LFG and plans are being made to move it to a new site
where fuel cell waste heat and cleanup system gas will be utilized as boiler fuel. In
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addition, plans arc to provide power both on and off grid. As a result of this
demonstration project, Northeast Utilities plans to install 1 MW of fuel cells in the
Hartford, CT landfill. Several other utilities have expressed interest in the fuel cell for
LFG applications.
The major nontechnical issue associated with fuel cells has been capital cost.
The manufacturer of the phosphoric acid fuel cell, International Fuel Cells subsidiary
ONSI, has guaranteed to potential buyers that the capital cost for the new advanced
power module will be $3000/kW for delivery in 1995. The manufacturer also has
plans to reduce the cost to SI 500 per kW by 1998. This should result in making the
fuel cell competitive with conventional technologies in use today. However, as more
fuel cells are utilized, their capital cost is expected to decrease.
Recovery of Waste Heat from LFG Combustion and Leachate Treatment
Another emerging technology is on-site LFG combustion in an evaporation
system to evaporate leachate. Other on-site uses are likely to evolve such as using
small boilers for hot water, steam, and heating, and small IC engines to offset some,
or all, site electricity use, and space heating. These uses will help offset on-site
energy needs, and perhaps an adjacent, or nearby, customer may be found with
similar needs. Landfill owners/operators will be looking for opportunities to defray
costs, particularly since post-closure costs will extend 30 years after actual closure,
and utilization of LFG-to-recovery waste heat and/or leachate can help to offset
costs.
SUMMARY
This paper describes EPA/APPCD's research to develop information to assist
decision- makers in evaluating the technical and nontechnical issues associated with
LFG energy conversion options. The core of this work is a series of extensive
interviews conducted with companies involved in I.FG utilization project
development, operations, and/or management. In addition, summary statistics and
trends are provided from the database created by EPA/SWANA of North American
LFG-to-energy projects. Current and emerging technologies for LFG utilization are
discussed. Potential technical issues and remedies are discussed including material
energy operating modifications, condensate management, and oil selection. Soon-to-
be-final CAA regulations for LFG are expected to result in 400 sites installing LFG
control systems. EPA/APPCD research will assist the landfill owners/operators in
deciding on opportunities to help offsite potential control costs. The research
described in this paper Is funded through the EPA Office of Research and
Development's Engineering Research Program on Global Climate Change.
REFERENCES
Anderson, C., "Selecting Electrical Generating Equipment for Use With Landfill Gas."
Presented at SWANA's 1.6th Annual Landfill Gas Symposium, Louisville, KY, March 23-
25, 1993.
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Augenstein, D. and J. Pacey, Landfill Gas Energy Utilization: Technology Options and
Case Studies, EPA-600/R-92-116 (NTIS PB92-203116), June 1992.
Doom, M„ J. Pacey, and D. Augenstein, Landfill Gas Energy Utilization Experience:
Discussion of Technical and Non-Technical Issues, Solutions, and Trends, EPA-
600/R-95-035 (NTIS PB95-188108), March 1995.
Doom, M. and M. Barlaz, Estimate of Global Methane Emissions from Landfills and
Open Dumps, F.PA-600/R-95-019 (NTIS PB95-177002), February 1995.
Doom, M„ L. Stefanski, and M. Barlaz, Estimate of Methane Emissions from U.S.
Landfills, EPA-600/R-94-166, (NTIS PB94-213519), September 1994.
IPCC. 1992. Climate Change 1992. The Supplementary Report to the IPCC Scientific
Assessment.
Meadows, M. and D. Maunder, Non-Technical Barriers To Energy Recovery From
Landfill Gas. Presented at SWANA's 18th Annual Landfill Gas Symposium, New
Orleans, LA, March 27-30,1995.
McGuigan, M. et al, Barriers to Landfill Gas Utilization in the Northeast. Presented at
SWANA's 18lh Annual Landfill Gas Symposium, March 27-30, 1995.
Najarian, M., F.PA/OAQPS. Briefing Package for DOE - Municipal Solid Waste Landfills -
New Source Performance Standards and Emission Guidelines," March 9, 1994.
Docket # A-88-09,
Najarian, M., FPA/OAQPS. "Planned Changes to the Proposed Municipal Solid Waste
Landfill New Source Performance Standards and Emission Guidelines." Presented at
SWANA's 18th Annual Landfill Gas Symposium, New Orleans, LA, March 27, 1995.
President Clinton and Vice President Gore, "The Climate Change Action Plan,"
October 1993.
Sandelli, G.J., Demonstration of Fuel Cells to Recover Energy from Landfill Gas, Phase I
Final Report: Conceptual Study, EPA-G00-R-92-007 (NTIS PB92-137520), January 1992.
Thorneloe, S.A. and J. Pacey, "Database of North American Landfill Gas to Energy
Projects." Presented at the 17th Annual International Landfill Gas Symposium by the
Solid Waste Association'of North America, Long Beach, CA, March 22-24, 1994.
Thorneloe, S.A., "Landfill Gas and Its Influence on Global Climate Change." Presented
at Sardinia '93, Fourth International Landfill Symposium, Cagliari, Italy, October 9-14,
1993.
Thorneloe, S.A., "Emissions and Mitigation at Landfills and Other Waste Management
Facilities." In Proceedings: The 1992 Greenhouse Gas Emissions and Mitigation
Research Symposium, EPA-600/R-94-008 (NTIS PB94-132108), pp. 4-46 thru 4-57,
January 1994.
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Thorneloe, S.A., "Landfill Gas Utilization - Options, Benefits, and Barriers." Presented
at The Second United States Conference on Municipal Solid Waste Management,
Arlington, VA, June 4, 1992a.
Thorneloe, S. A. "Landfill Gas Recovery /Utilization - Options and Economics."
Presented at the Sixteenth Annual Conference by the Institute of Gas Technology on
Energy from Biomass and Wastes, Orlando, FL, March 2-6, 1992b.
U.S. EPA, Air Emissions from Municipal Solid Waste Landfills - Background Information
for Proposed Standards and Guidelines, EPA-450/3-90-01 la (NTIS PB91-197061),
March 1991.
Wong, P.P., "Alternative Energy & Regulatory Policy: Till Death Do We Part." Presented
at AWMA Conference on "Cooperative Clean Air Technology - Advances through
Government and Industrial Partnership" in Santa Barbara, CA, March 21 - April 1,1992.
FIGURES
FIGURE 1. NUMBER OF PROJECTS BY END USE AND YEAR
Year
FIGURE 2. NET ELECTRICAL OUTPUT IN MW BY YEAR AND
TYPE OF GENERATING EQUIPMENT
400
a 300
3 i" 200
2 5 100
z 0
~ Reciprocating IC Engine
Q Gas Turbine
H Steam Turbine
cvjCD^tintol^oocnov-cMco^
oocDcocooocoaococftocaoa)
Year
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FIGURE 3. NUMBER OF IC ENGINE AND GAS TURBINE
PROJECTS BY MANUFACTURER AND YEAR
oieO'tincDh-ooaoi-cjcO't
00 00 00 c0c0 03 «3000)050)0)0)
Year
H Caterpillar
H Waukesha
n Cooper-Superior
¦ Other Reciprocating
IC Engines
n Gas Turbine
FIGURE 4. NET ELECTRICAL OUTPUT IN MW BY DEVELOPER AND YEAR
Year
h All Others
¦ Waste Management of
North America
n Landfill Energy Systems
~ Energy Tactics,
Inc./Zapco
n Los Angeles County
Sanitation District
LaicJIaw
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3-E
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred.
CASE STUDIES OF SEWAGE TREATMENT
WITH RECOVERY OF ENERGY FROM METHANE
Hahn, William H.
Science Applications International Corporation
1717 Goodridge Drive
McLean, Virginia 22102
ABSTRACT
Energy recovery from biogas generated from wastewater treatment processes is universally cost
effective and has gained widespread acceptance. The technology exists to allow full use of
biogas, and the extra costs of incorporating this energy source into a system are small. The
payback period for installation of biogas energy recovery at plants having anaerobic digesters is
short, typically less than six years. Recovery and use of biogas accomplish energy conservation
and pollution prevention goals, and also cost savings, making this an obvious choice for
application in all treatment plants that employ anaerobic digestion for stabilization of wastewater
biosolids.
Other energy conservation and municipal pollution prevention activities can be integrated with use
of biogas, as demonstrated by the Sunnyvale plant, including collection and use of landfill gas,
recovery of waste heat, water reclamation, and municipal water conservation. Often, wastewater
treatment plants are located near municipal landfills, and could potentially develop the landfill gas
as an additional energy source. Advantages lie not only in the cost savings from energy recovery
from the landfill gas, but also in meeting regulatory and safety concerns posed by landfill gas
emissions.
The examples of the Orange County and Los Angeles plants show that energy conservation not
only conserves natural resources, but can also lead to increased ability to comply with air
emissions regulations. The greenhouse gas carbon dioxide is released by all wastewater treatment
and biosolids management processes. Converting biosolids to fuel achieves substantial benefit
from the wastes before carbon dioxide is ultimately released. In addition, nonrenewable energy
sources such as natural gas are replaced by the renewable energy from wastewater, without
adversely affecting receiving water quality.
Plants can address environmental mandates in an integrated framework based on energy
conservation, through the use of renewable resources. As the case studies prove that activities
that conserve energy also reduce pollution and costs.
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INTRODUCTION
Anaerobic digestion is one of the most widely used processes of wastewater biosolids
stabilization. The process involves bacterial decomposition of the organic constituents of the
biosolids in the absence of oxygen. The products of anaerobic digestion, apart from solids,
include water and a gas composed of methane, carbon dioxide, hydrogen sulfide, and other minor
gaseous compounds. This "biogas11 has a heat value of approximately 550 Btu/ft3, about 60
percent of the heat value of natural gas.
Biogas may be used either offsite or within the plant to improve energy efficiency of wastewater
treatment processes. Both possibilities should be considered when designing new treatment
facilities or upgrading existing ones. Local objectives and conditions, however, will decide the
use made of biogas at a particular plant.
Inpiant uses are those that result in the biogas being consumed completely within the wastewater
treatment plant, either as primary or backup fuel. Uses include fueling boilers in process heating
operations and space heating and cooling, engine-driven machinery, engine generators for
electricity generation, solids incinerators, boilers for pasteurization of digested biosolids, gas fired
biosolids dryers, and generation of electricity by steam turbines and fuel cells.
Use of waste heat recovery increases energy efficiency in the system, and is of particular value
whenever in-plant use involves the operation of equipment not primarily designed to produce heat
(i.e., engines, incinerators, turbines, etc.). As the case histories in this study demonstrate, fuel
energy efficiency can be increased from 30 to 70 percent by recovering heat for process or space
heating/cooling requirements. Recovery of biogas should always be supplemented with waste gas
burners, or flares, to ensure that excess gas is controlled with the smallest environmental impact.
Offsite, biogas can be used to create either energy or chemicals that are sold for use external to
the plant. The case study presented below of Seattle Metro's Renton Reclamation Plant describes
one such use. Generally, however, it is less practical to process biogas for offsite uses if the gas
can be used in the plant.
The five most adaptable inpiant uses for biogas are as a fuel for (1) generating heat for treatment
processes, (2) generating heat for space heating and cooling, (3) powering engines used to drive
equipment directly, (4) powering engines used with generators to drive remote equipment, and (5)
powering engines used with generators to produce general purpose electrical power.
CASE STUDY: COUNTY SANITATION DISTRICTS OF ORANGE COUNTY
The County Sanitation Districts of Orange County (CSDOC) provides wastewater treatment for a
population of about 2.1 million people. CSDOC operates two treatment plants, with a combined
average wastewater flow of about 235 MGD. Each plant uses advanced primary treatment with
ferric chloride and anionic polymer addition in the primary basins. About 50 percent of the plants'
flow receives secondary treatment. The plants discharge to the ocean through a common outfall.
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CSDOC has for years used biogas to heat the digesters and to fuel some engines that run pumps
and blowers. However, the recovery system did not have the capacity to use all the gas produced
by the digesters, and the excess was burned off. In June of 1993 CSDOC put the Central Power
Generation System (Central Gen) on-line. Central Gen incorporates state-of-the-art techniques to
reclaim energy from biogas This system has been installed at both treatment plants. Currently,
CSDOC does not purchase any electricity, as all of its electricity needs are supplied by onsite
manufacture of energy from a combination of biogas and natural gas
Central Gen consists of a total of eight internal combustion engines fueled by both biogas and
natural gas. The engines drive generators to produce electricity that is then used to operate the
treatment plants. These engines were specifically designed to reduce emissions from the engine
exhaust and to use all the gas produced by the digesters. Power output is 5 megawatts at the
Fountain Valley plant (Plant 1) and 7 megawatts at the Huntington Beach plant (Plant 2).
Plant 2 has the greater energy demand (8 megawatts), due mainly to the presence of the outfall
pumping station at this plant. Plant 1 uses about 4 megawatts. At present all biogas from Plant 1
is exported via pipeline to Plant 2 for use, and the Plant 1 Central Gen operates entirely on natural
gas.
Air Emissions Reductions
CSDOC cites concerns with meeting air emissions requirements as one factor driving energy
conservation efforts. Southern California air regulations are among the most stringent in the
country. Both CSDOC and Hyperion are subject to local regulations promulgated by the South
Coast Air Quality Management District (SCAQMD). SCAQMD regulates emissions of sulfur
dioxides from stationary source internal combustion engines, and sets limits on the allowable
content of sulfiir in gaseous fuels.
Substitution of biogas for natural gas has enhanced the CSDOC plants' ability to meet air quality
requirements. Because biogas has a heat value approximately one-half that of natural gas (LHV =
550 for biogas compared to 950 Btu for natural gas), biogas burns more slowly and more
completely. Ferric chloride is added to the digesters to control sulfides and odor, and the gas is
chilled to condense out water vapor. CSDOC specified parameters for the engine generators'
performance in the contract with the supplier. Performance parameters included exhaust
emissions, generator output, and engine fuel consumption. Penalties for noncompliance with
these parameters were specified in the contract.
Financial Benefits
The $65 million cost for Central Gen and all associated projects will be recovered in about seven
years because of the savings achieved by this project.
Before construction of Central Gen, CSDOC calculated the savings resulting from its existing
energy conservation program in fiscal year 1991-1992. During this year the facility reduced
electrical power purchases by biogas fueling of engines, process changes, lighting energy
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conservation, peak load shifting, and reduction of loadings to the secondary process. CSDOC
estimated the total savings from these programs at $4,101,800. Flow decreased by 16 percent
from June 1991 to June 1992 due to the drought, and this contributed about 12 percent of this
savings. Over the approximately 30 years that CSDOC has been using biogas as a fuel,
approximately $2 million per year has been saved.
With Central Gen on-line and able to fiilly use the biogas produced, the calculated savings in
1993-94 are substantial. The plant staff estimates savings totaling 12,630 kilowatts, worth about
$8,850,000.
CASE STUDY: CITY OF LOS ANGELES HYPERION WASTEWATER TREATMENT
PLANT
The Hyperion Wastewater Treatment Plant receives an average daily flow of 320 to 400 MGD
(the lower flows reflecting recent water conservation efforts). Upstream wastewater reclamation
plants discharge biosolids to Hyperion, resulting in an influent wastestream containing 360 to 400
ppm of total suspended solids. About 190 MGD receives secondary treatment by activated
sludge. The facility currently discharges partial secondary-treated wastewater under a consent
decree: however, construction is underway to provide full secondary treatment.
Hyperion operates the Hyperion Energy Recover System (HERS) which generates energy from
biosolids by producing biogas and by combustion of the solids in a Carver-Greenfield process.
The Carver-Greenfield process is not further described here. HERS saves the City a total of
about $12 million in electricity costs per year and produces up to 20 MW.
Biogas provides approximately 80 percent of the energy produced onsite. Hyperion's anaerobic
digesters produce an average 7.5 million cubic feet per day of biogas. Under normal operating
conditions, all of the biogas is captured and used to either generate electricity (via gas or steam
generators) or to make steam for heating purposes in the plant. Hyperion's biogas has a fuel value
of 600-650 Btu/cubic foot. Iron compounds are added upstream of the primary settling basins
and to the digesters to control hydrogen sulfide, at an annual cost of $1.5 million. Even so,
biogas contains 60 to 100 ppm of hydrogen sulfide. The high sulfide content may result from
sulfur bacteria in the collection system acting on the biosolids produced by upstream water
reclamation plants. Increasing the amount of iron added to the process tanks is not economically
feasible, so biogas is usually treated in a Stretford desulfurization unit to produce a product with a
content of less than 40 ppm of hydrogen sulfide. To pass it through the Stretford unit, the gas is
subjected to "intermediate" pressure (40 psi) as it comes off the digesters. The Stretford unit
produces about 50 to 60 pounds of sulfur daily. The annual cost of operating the unit is $20,000.
After desulfurization, the boilers can directly use the biogas as fuel to produce steam for digester
heating and biosolids drying. However, most of the gas is further pressurized, mixed with natural
gas, and used to power three gas turbines, each with a capacity of4,500 kilowatts of electricity.
Waste heat from the turbines is fed to heat recovery boilers to make high pressure steam.
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Generators driven by steam turbines use the steam to produce more electricity. By using this
"combined cycle" approach to produce power from both gas and steam turbines, the plant
increases its net electrical production by 50 percent over that of a conventional "simple cycle"
power plant (a plant that uses only one kind of generator).
The facility currently uses about 600,000 cubic feet per day of natural gas to supplement biogas
production. This figure represents about 8 percent of the total amount of gas burned at Hyperion.
Hyperion currently operates three digesters as two-stage digesters in a series, and has plans to
operate all the digesters in this manner. This mode of operation allows reduction of the retention
time while increasing the destruction of pathogens and production of biogas. The facility has
plans to install egg-shaped digesters as future capacity becomes necessary, as the egg shape will
allow for better mixing and require less cleaning.
Financial Benefits
Over the period 1992 through 1993, monthly electricity purchases ranged from less than zero
(when the facility receives a credit for producing more electricity than can be used onsite) to
about $460,000. As an example, in July 1993 Hyperion consumed an average 389 megawatt
hours daily, and generated an average 365, for a total daily shortfall of 24 megawatt hours. The
total cost for energy during July 1993 was $865,000. To supplement its onsite production and
make up for the shortfall, the facility bought electricity at a total value of $202,000. Thus,
Hyperion generated over 75 percent of the needed energy onsite during this month.
Power generation varies based on needs for equipment maintenance and repair. In three of the 12
months in fiscal year 1992-1993, HERS generated more power than Hyperion consumed.
CASE STUDY: SUNNYVALE WATER POLLUTION CONTROL PLANT
The Sunnyvale Water Pollution Control Plant (WPCP), in California, incorporated use of biogas
in its original plant construction in 1956. Recently, the City has implemented or planned some
unique new methods to increase energy recovery and further the pollution prevention and water
conservation goals of the plant. These innovative energy recovery options include transfer of
suspended solids biomass harvested from the oxidation pond effluent to the digesters to increase
gas production, and plans to extend the energy recovery operation to the use of gas from the
adjacent municipal landfill. Sunnyvale expects to be able to meet 100 percent of the plant's energy
demands through use of a combination of landfill gas and biogas.
The energy recovery system at the WPCP combines the use of biogas as an engine generator fuel
and boiler fuel, and uses heat recovery from engine-cooling and exhaust stack systems to
supplement plant energy requirements.
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Biogas Production and Use
The Sunnyvale wastewater treatment plant was designed to maximize recovery and use of biogas.
This objective has remained an important consideration in each of the subsequent plant
modifications. The 1956 plant included two digesters; in the 1960's three gas-fueled engine-
generators were added to the plant to power recirculating pumps for the oxidation ponds. A
remote power-generating facility was provided because the recirculation pumps are approximately
one mile from the digesters. A full parallel electrical distribution board is present so that any or
all of the plant electrical circuits can selectively use power generated either within the plant or
commercially.
A blend of biogas and natural gas powers three 110 kilowatt "enginators," or engine generators,
which together produce 330 kilowatts of power. Natural gas is purchased from the local supplier
and blended with air to lower the heating value to about 550 Btu, so that it is equivalent to that of
biogas. The biogas piping system joins with the natural gas piping system, and the two gases are
blended to maintain a constant flow to the pump and generator engines.
Recent plant data show that biogas production for the 12 months between December 1991 and
November 1992 averaged 172,000 cubic feet per day. The monthly average biogas production
varied from a low of 126,000 cubic feet per day in July, to a high of235,000 cubic feet per day in
November The blend of biogas and natural gas meets roughly 30 percent of the plant's 1,000
kilowatt energy demand. •
Increases in biogas production since the early 1980's are largely attributable to two activities.
First, Sunnyvale conducted studies that concluded that suspended solids removed from the
oxidation pond effluent by the AFTs could be fed to the digesters. Approximately 30 percent of
the solids removed by the AFTs are directed to the digesters. The City estimates that gas
production will increase a farther 25 percent when all of these solids are sent to the digesters, to
approximately 224,000 cubic feet per day. Expressed in thermal units, estimated future biogas
production is 5.1 million Btu per hour. Sunnyvale found that using alum for coagulation in the
AFTs caused some toxicity inhibition. They substituted polymer for the alum and increased the
gas production The dependability of gas production and the available digester capacity has also
increased.
Waste Heat Recovery
An important design feature of the Sunnyvale plant is the use of waste heat from the gas-fueled
engines to provide both process heat for the digestion and chlorination systems, and space heating
for various buildings at the treatment plant. Currently, waste heat is recovered in three systems:
(1) pump-engine heat recovery, (2) generator-engine heat recovery and (3) stack heat recovery.
These systems may be supplemented as required by the low-pressure, gas-fired steam boiler;
however, typically more heat is obtained from the heat recovery systems than is actually needed in
the plant. Heat from all sources is converted into hot water for use throughout the plant.
Presently, the plant does not use excess heat for cooling needs.
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Landfill Gas Production
The Sunnyvale WPCP is located next to the municipal landfill. The landfill has received its final
load of solid waste, and was closed on October 1, 1993. Landfill gas (LFG) is produced by
bacterial decomposition of the organic portion of refuse in the absence of oxygen. Once begun,
the rate of decomposition reaches a peak within a few years, then gradually declines as the
decomposable organic material is depleted. In inactive landfills such as Sunnyvale, the production
of LFG is dependent on the portion of previously disposed refuse which has yet to be converted
to LFG.
LFG is a mixture of methane and carbon dioxide, with trace contaminants. The concentration of
methane in undiluted LFG has been measured between 55 percent and 65 percent at the
Sunnyvale landfill. Trace contaminants in LFG can affect engines primarily due to the presence of
chlorine (carried in compounds such as trichloroethylene), which produces hydrochloric acid
during fuel combustion. An advantage to LFG as a generator fuel is its much lower hydrogen
sulfide concentration compared with that of biogas. The concentration of hydrogen sulfide in
Sunnyvale's biogas averages 1,270 parts per million, but when blended with LFG will result in a
reduced concentration that should lower emissions and improve equipment longevity.
The proposed energy conservation project will collect LFG and use it together with biogas from
the WPCP anaerobic digesters to fuel engines and generators that supply the WPCP with
electricity. The City expects that 100 percent of the energy demand of the Sunnyvale wastewater
treatment plant, all of the power for the water reclamation facility and some power for the
municipal waste transfer station will be met through use of LFG and biogas. Projected savings in
reduced purchases of electricity are expected to be $826,400 in FY 94-95. Project payback is
anticipated in approximately six years.
CASE STUDY: SEATTLE METRO RENTON WATER RECLAMATION PLANT
Unlike the other wastewater treatment plants in this study, the Seattle Metro East Division
Reclamation Plant at Renton does not use its biogas onsite for heating and/or cooling. Instead,
Metro has worked out relationships with local utilities that have made it more cost- effective to
sell the gas for offsite use and replace its potential in-plant use with electrically operated heat
pumps that remove heat from effluent. The economics that make this feasible depend on the low
prices for electricity in the Seattle area, and grants and other assistance from the electric utility.
The Renton plant treats about 66 MGD of wastewater. The plant is undergoing expansion, due to
be completed in 1996, which will increase its current design capacity of 72 MGD to 108 MGD.
Plant processes consist of primary settling, aeration, secondary settling, chlorination, and
dechlorination, Biosolids are treated in dissolved air flotation thickeners, followed by anaerobic
digestion and belt filtration Effluent is discharged to Puget Sound through a 12-mile effluent
pipeline.
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Energy Recovery from Biogas
The Renton plant's four anaerobic digesters generate 1.2 million standard cubic feet per day of
biogas. The facility scrubs the biogas to remove carbon dioxide, and sells the resulting 99 percent
pure methane to the local gas utility, Metro receives approximately $1,100 per day for the
scrubbed gas. The biogas potential for onsite heating use is replaced with four 600-horsepower
electrically-operated heat pumps. These heat pumps supply 135 degree water to a closed loop
system that meets 90 percent of building heat requirements, and also maintains ten million gallons
of biosolids in four digesters at 96 degrees. The cooler water that has passed through the heat
exchangers is used in the gas scrubber unit to increase its efficiency
The heat pumps produce four times more heat than would be obtained per watt of power
consumed by directly converting electricity to heat (3.4 Btus are obtained per watt hour). Metro
anticipates that the efficiency will decrease when it changes from the current refrigerant (R12) to
a new refrigerant (134A) that does not contain chlorofluorocarbons, because the 134A refrigerant
is not as efficient in heat transfer.
Advantage of Cold Water for Biogas Scrubbing
The carbon dioxide scrubber consists of a vessel into which secondary effluent is injected under
300 psig. Digester gas is fed into the vessel, and during contact between the gas and the effluent,
pressure forces the carbon dioxide into solution in the water. Cleaned methane gas is drawn off.
To achieve maximum efficiency, cooled effluent that has passed through the heat pumps is used in
the scrubber, since cooler water can hold more gas in solution.
The heat pumps drop the temperature of the effluent flowing through them by 10 degrees
Fahrenheit at a flow rate of960 gallons per minute. This chilled water is fed into the digester gas
scrubber. Metro has found that savings can be achieved by operating a heat pump solely to
produce chilled water to ensure that the digester gas is adequately cleaned to specifications.
Without chilled water, summer heat conditions would cause reduced scrubber efficiency resulting
in wasting some gas that does not meet sale specifications.
Financial Benefits
Metro received a $400,000 grant from Puget Sound Power and Light Company to defray nearly
half the $900,000 (1987 dollars) cost of the heat pumps. The capital costs have been recovered
through Metro's sewer rates and bonds.
In 1992, the heat pumps operated for a total of 9,200 hours. The electricity cost (at 2.5 to 3 cents
per kilowatt hour) was approximately $105,000. The cost of maintenance on the four heat pumps
totaled $30,000 for the year. The total heat production was 55 trillion Btus. By selling the
digester gas and replacing its potential onsite heating use with electrically operated heat pumps,
the facility realizes a gain of $275,000.
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Metro's energy conservation activities have positive environmental benefits. By not burning
biogas onsite, Metro avoids creating air emissions from such a process.
CASE STUDY: ANAEROBIC WASTEWATER TREATMENT
Anaerobic wastewater treatment is most often used as a pretreatment process, with effluent being
directed into a conventional aerated treatment process such as activated sludge or trickling
filtration for polishing. This technology is most appropriate for WWTPs receiving less than 1
MGD and for pretreatment of high-strength industrial wastestreams.
In the anaerobic upflow process, wastewater influent is drawn off the inlet of the primary clarifier
and directed into a bioreactor. Wastewater enters near the bottom of the bioreactor and flows
upward through the filter medium. Effluent is discharged near the top of the bioreactor and
sludge can be removed from the bottom. Bacteria on the filter or in the sludge blanket consume
the organic material in the wastewater, producing methane gas that bubbles to the top and is
collected. Bioreactor effluent typically receives additional treatment to meet surface water
discharge standards, although effluent from some industrial facilities that discharge to WWTPs
may not require additional treatment.
In the early 1980's, Anheuser Busch began developmental work on this technology, which was
not widely used then for treatment of food processing wastewater. Brewery wastewater is readily
biodegradable and free of toxics, but its BOD/COD content is very high. In 1991, Anheuser
Busch modified existing aerobic wastewater treatment processes to incorporate the technology at
breweries in Jacksonville, Florida and Baldwinsville, New York. These facilities generate
wastewater with highly variable flow, BOD and solids loadings, pH, and temperature. Therefore,
screening, equalization and pH and temperature control are necessary to reduce the impact on this
process. Ferric chloride is added to the reactors to control odors.
Anaerobic wastewater treatment has many advantages over aerobic treatment. Anheuser Busch
reports a 75 percent reduction in energy consumption with this process on-line. Energy
consumption is reduced because anaerobic treatment requires less energy than aerobic treatment
and produces energy through methane generation.
Methane recovery from gases collected in the bioreactor's vapor space is 70 to 75 percent. This
compares very favorably to methane recovery from anaerobic digesters, which typically produce
only 55 to 60 percent. Anaierobic wastewater treatment produces relatively small amounts of
biosolids, reducing the costs and energy requirements associated with their disposal. Studies have
found that the process produces only about 25 percent of the solids that would be produced by an
activated sludge process.
Anheuser Busch calculates that an anaerobic process treating 100,000 pounds of BOD per day
would produce 40 percent less C02 than an aerobic process. This works out to a reduction of
14,000 tons of C02 per year.
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Finally, Anheuser Busch has shown that treatment costs are considerably lower with the process
Before installing it, the cost to treat this wastestream was $0,076 per pound of BOD. With the
anaerobic process, costs dropped to $0,019 per pound. Costs savings were realized in residuals
handling, reduced need for aerobic treatment, and through biogas recovery. Construction costs
are about half as great.
CASE STUDY: BIOMASS-ENHANCED DIGESTER GAS PRODUCTION
South Bayside System Authority (SBSA), operates a tertiary treatment plant in Redwood City.
In 1986, SBSA began a demonstration program to find out the effects of adding plant scum and
grease trap wastes to one of its two digesters. The scum and grease wastes were added only to
Digester 1, while Digester 2 was maintained as a control. Both digesters continued to receive the
same volumes of solids from the gravity thickener. SBSA kept records on the volume of wastes
received and the amount of gas generated, and also various operating conditions of each digester.
The study found that excellent digester mixing (turnover rate = 8.5 times daily) and long
detention times (40 days) probably contribute to the ability to accept large volumes of grease.
Grease loadings were increased as the demonstration project progressed, reaching 730,215
gallons per year in 1993 for Digester 1. Each gallon of grease introduced to the digester results in
the production of about 20 cubic feet of biogas. When the digesters were cleaned, no significant
difference was found in the contents of the control versus the digester that received grease wastes.
SBSA now accepts grease trap wastes and septic wastes from a large geographic area beyond its
service area. This program provides an environmentally beneficial disposal option for waste
haulers. Instead of conventional disposal into a designated area of the collection system, these
wastes are placed directly into an anaerobic digester. By avoiding the secondary treatment
process, none of the energy inherent in the wastes is lost and there is no chance of adversely
affecting the secondary process.
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3-F
ASSESSMENT OF C02 CAPTURE, UTILIZATION, AND DISPOSAL(l)
Howard J. Herzog
Massachusetts Institute of Technology
Energy Laboratory, Room E40-471
1 Amherst Street
Cambridge, MA 02139
ABSTRACT
The capture and sequestration (via utilization or disposal) of C02 is the only greenhouse
gas mitigation option that will allow use of our large fossil fuel resources without a build-up of
atmospheric C02. This paper assesses the current status and research needs of this mitigation
option as applied to fossil fuel-fired power plants.
INTRODUCTION
Avoidance of C02 emissions through physical capture of C02 from fossil fuel-fired power
plants has been considered as a potential C02 mitigation option since Marchetti first proposed this
idea linked with disposal of the captured C02 in the deep ocean [1], Since then, many
investigators have published studies examining a variety of options for C02 capture from power
plants and its subsequent disposal or use.
Over the past several years, a Massachusetts Institute of Technology (MIT) Energy
Laboratory team has been investigating the feasibility of capturing and sequestering C02 from
fossil fuel power plants [2,3,4,5,6,7], The largest of these projects was a Special Research Grant
from the U.S. Department of Energy (DOE) to identify, assess, and prioritize research needs for
the capture and non-atmospheric sequestration of a significant portion of the C02 emitted from
fossil fuel-fired electric power plants [6], Much of the data presented in this paper was gathered
in conjunction with the above research projects.
Figure 1 shows a number of different options for mitigating potential global warming
and/or the build-up of atmospheric C02 concentration levels. They include improved efficiency,
fuel switching (to natural gas, renewables, or nuclear), reforestation, flue gas clean-up, and geo-
engineering. This paper first reviews the technologies and costs associated with the flue gas
clean-up option. Next, within the context of all the above mitigation options, the necessary
circumstances for wide-spread implementation of C02 capture and sequestration are presented.
''^The work described in this paper was not funded by the U.S. Environmental Protection Agency. The contents do not
necessarily reflect the views of the Agency and no official endorsement should be inferred.
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C02 CAPTURE
The idea of capturing C02 from the flue gas of power plants did not start with concern
about the greenhouse effect. Rather, it gained attention as a possible economic source of C02,
especially for use in enhanced oil recovery (EOR) operations. In general, C02 capture processes
have significant energy requirements, which reduce the plant's conversion efficiency and net
power output, thereby increasing the amount of C02 produced per net kWl\ of electricity
generated. Because of this additional C02 generated during the capture process, analyses of these
processes need to consider the amount of C02 emissions avoided (CO, emissions with capture
compared to a no capture baseline) rather than the total amount of C02 captured.
Retrofit of Existing Fossil Fuel-Fired Power Plants
One approach to C02 capture is to "scrub" the C02 from the stack gases. A variety of
physical and chemical separation processes are candidates for this application. The chemical
solvent monoethanolamine (MEA) has been used for removal of low concentrations of C02 from
other gas streams and appears to be the best available system for retrofit purposes. For a typical
coal-fired plant, MEA capture of COj, including compression and dehydration for transport, is
likely to involve an energy penalty (see Table 1 for definition) of about 35% (assuming the steam
required is cogenerated) and will approximately double the cost of electricity [3,8], For natural
gas-fired plants, some studies suggest an energy penalty of about 10% may be attainable [9], The
MEA plant will approximately double the land area of the original power plant, which may be a
barrier in retrofitting some plants. In general, if the power plant is fueled with coal, the flue gas
will have to be scrubbed to remove the bulk of the SOx from the flue gas before it reaches the
MEA solution. Several commercial C02 recovery plants using MEA scrubbing have been built
and operated in the U.S., with the North American Chemical Plant in Trona, CA being in
operation the longest (since 1978). The Trona plant is based on Kerr-McGee technology, which
is now licensed by ABB Lummus Crest [10]. Another commercial MEA process, originally
developed by Dow, is licensed by Fluor-Daniel [11].
An alternate approach to flue gas scrubbing is to remove nitrogen from the air prior to the
combustion process. In a retrofit, a cryogenic air separation plant, occupying relatively little land,
would be installed next to the power plant to produce a fairly pure oxygen stream for combustion.
The flue gas would then contain C02 and water, with some nitrogen among the trace components.
To maintain thermal conditions in the combustion zone and prevent overheating of the furnace
liner materials, some of the flue gas would be recycled. This technique has been evaluated in a
small industrial stoker-fired boiler at Black Hills Power and Light Company, Rapid City, South
Dakota [12,13] and a 10 million Btu/hr facility in Irvine, California owned by Energy and
Environmental Research Corp [14]. Most power boilers are operated at slight negative pressure
and do not limit air inleakage. Thus, some sealing and conversion to pressurized operation would
be required. Coal handling and insertion would require modifications, and particulate control
would require reevaluation. Trace impurities would end up in the C02 effluent stream and might
be suitable for disposition with the C02. Since mandated S02 and NOx emission controls already
add 10-25% to the cost of producing electricity and consume up to 7% of the plant's electricity
output [15], this could be counted as a credit toward the C02 control costs. The transportation
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and disposal system would have to be tolerant of these acid gases. This technique has energy
penalties of about 30% and would increase electricity cost by about 80% without the acid gas
removal credit and assuming no problems from air inleakage.
Several other methods have been proposed to capture C02 from flue gas, including
cryogenic fractionation, membrane separation, and molecular sieves. As shown in Table 1, the
energy penalty of these processes are higher, and the net C02 reduction is lower, so they are not
likely to be competitive with either the amine scrubbing or the flue gas recycling technologies. A
major reason for their high energy penalties is that all these technologies require flue gas
compression, which is highly energy-intensive.
CO, Capture from Emerging Power Generation Technologies
One emerging power generation technology, integrated gasification - combined cycle
(IGCC) power plants, uses a very different combustion process from today's plants. IGCC plants
first gasify the fuel to produce a pressurized synthesis gas (mainly CO and II2). Next, for C02
capture, after removal of impurities that might foul the catalyst, the synthesis gas is reacted with
steam in a shift reactor to produce C02 and H2. The C02 and H2 are then separated, with the
hydrogen being combusted to produce C02-free energy. The C02 stream is available for use or
disposal. Since C02 is removed at high pressure in an IGCC plant (as opposed to atmospheric
pressure in most existing plants), the energy penalty compared to MEA scrubbing can be greatly
reduced by using a physical absorbent like Selexol. Projected energy penalties from IGCC plants
of 13% [16] and 20% [8] have been reported.
Power technologies are evolving so that within two decades power plants may be
introduced that can use the hydrogen rich fuel gas from the gasifier/shift-reactor/C02-separator in
fuel cells, MHD, or other advanced cycles. These technologies are likely to yield higher energy
efficiencies and further reduce the penalties associated with CO, capture.
C02 SEQUESTRATION
Once the C02 is captured, the problem of sequestering the C02 still remains. One option
is to use the C02. However, for utilization to be a significant sink of power plant CO^ new uses
need to be identified. In the U.S., over 1.6 Gt(1) of C02 is produced each year from power plants,
but the industrial use of C02 is only 40 million tonnes per year, equivalent to about 2% of the C02
produced by the power plants. In terms of potential applications or products, just about any
carbon-bearing chemical can be considered - from polymers and plastics to substitute fuels like
methanol or minerals like soda ash. However, implementing the recycling of C02 has some
serious drawbacks. C02 is in a folly oxidized energy state after the combustion energy has been
utilized. To reduce C02 to carbon requires about 80% of the energy that is generated from
burning a typical coal. Also, many of the potential uses for recycled C02 will tie up the C02 for
only a short period of time before releasing it to the atmosphere.
'''] Gt = 1 gigatonne = 1 billion metric tonnes; I tonne = metric tonne = 1000 kg; note tht 1 Gt of CO, contains
about 0.27 Gt C.
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While some niche utilization of C02 may occur, it seems highly unlikely that utilization
will become a major sequestration option. Therefore, disposal options must be considered.
Potential disposal sites include in the deep ocean or under the ground (in depicted oil and gas
reservoirs, in deep, confined aquifers, or in mined cavities).
OceanDisposalof CO:
The atmosphere and ocean surface continually exchange carbon dioxide, as does the well-
mixed surface layer with the rest of the ocean. However, the rate at which this entire system
comes to equilibrium with respect to C02 concentrations is slow compared to the rate of
anthropogenic C02 generation. In the long-term (i.e. on the order of 1000 years), the
atmosphere/ocean system will come to the same equilibrium regardless of whether the C02 is
initially emitted to the atmosphere or to the ocean. However, the peak of atmospheric C02
concentration, expected to occur in the next couple of centuries could be significantly reduced if
C02 were released into the ocean rather than into the atmosphere. This minimizes any possible
irreversible or runaway effect of global warming on hydrology, ocean circulation, etc. The
magnitude of "peak shaving" is dependent on the fraction of anthropogenic C02 released into the
ocean, and on the release depth. The estimated residence time for a 500 m injection depth is
about 50 years, increasing to several hundred years at a 1000 m injection depth. These estimates
are based in part on the present penetration depths of radioisotopes produced by the nuclear
testing of the early 1960s and the continuous addition of freons (i.e. CFCs) since the 1950s.
C02 can be released in the deep ocean as a gas, solid or liquid. From a processing and
transportation standpoint, the most efficient mode of disposal is the liquid form. This means that
at the power plant, after separation from other combustion gases, the C02 has to be compressed
and liquefied. The liquid C02 can be transported to the disposal site in pipes, barges or tankers.
Close to shore, the most economic mode of transportation is in pipes laid from coastal power
plants or coastal transfer stations to the appropriate release location. In cases where the distance
is too great for economic transport in pipes, the liquid C02 could be transported in barges or
tankers to a floating discharge platform. From the platform, the liquid C02 is transported to the
deep ocean in a vertical or slanted pipe extending from the platform. Below, four possible
methods of C02 injection are discussed.
Very Deep Ocean Injection at Depths Greater than 3700 m. At ocean depths below the
surface layer and above 500 m, released liquid C02 would initially form a gas before being
dissolved into the seawater. At depths greater than 500 m, the released C02 would be a slightly
buoyant dissolving liquid, or form a hydrate; below 3700 m depths, the C02 liquid would be
heavier than the surrounding water and would sink to the bottom as it dissolves and/or forms
hydrates. Because of these facts, some of the early methods for disposing of C02 in the ocean
suggested a C02 pipeline for injection below 3700 m [17], This would ensure that the injected
C02 would not rise and possibly return quickly to the atmosphere. However, present subsea
pipeline technology is limited to depths of around 600 to 650 m. Using advanced technology and
developing robotic installation and maintenance techniques may extend pipeline injection options
to depths of up to 1000 m (or perhaps even 1500 m). Today, the concept of pipeline discharge at
depths of 3700 m or more appears infeasible. However, discharge at that depth through a vertical
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pipe mounted on a floating platform (based on technology routinely used for scientific deep ocean
drilling) may be possible.
Vnconfined Release at Depths of1000-1500 m. It has been shown in recent studies
[3,5] that positively buoyant plumes of either liquid or gaseous C02 discharged from a pipe
through a difliiser (termed unconfined release) can be dissolved in the seawater with a plume
height rise of less than 100 m. This means that the C02 can be injected at any depth below the
well-mixed surface layer without rising immediately to the surface. However, to maximize
residence times, it is probably desirable to inject the C02 below the thermocline. Depths of 1000-
1500 m would balance the desire for long residence times (deeper injection) with the desire for
low costs (shallower injection).
Dense Plume Formation. A method that may combine relatively shallow injection with
long residence times is to form a dense sinking plume of C02-enriched seawater [18]. Seawater
that is saturated with C02 is slightly denser (about 1%) than unsaturated seawater and will also
tend to sink. Therefore, it has been proposed to form these dense plumes at shallow depths
(200-400 m) and let them flow along the sloping ocean floor to deeper depths. However, sinking
dense plumes will entrain surrounding seawater and eventually approach neutral buoyancy. Since
the initial density difference between the dense plume and the ambient seawater is small, a key
research need is to determine how far the plume will sink based on key system parameters (e.g.
slope of ocean floor, initial plume density, etc.). It may be advantageous to release these plumes
at the heads of submarine canyons, where the confined topography would allow the plume to
dominate the environment. Since dense plumes cannot form in unconfined releases, research
needs include identifying methods of dense plume formation as suggested by Adams, et al. [19],
Dry Ice Injection. Solid C02 (dry ice) is denser than seawater by about 50%, so blocks
can be put into the ocean at the surface and allowed to sink to the bottom. Unfortunately,
untreated blocks of dry ice will tend to melt (or sublimate) and dissolve as they sink through the
water column. Large blocks with high volume to surface area may survive long enough to deposit
some residue on the ocean floor. It has also been suggested that the dry ice be coated to reduce
sublimation or formed into aerodynamically favorable shapes like torpedoes. Other hurdles are
that energy requirements for forming dry ice are about twice that for liquefaction (required for the
other schemes outlined above) and the costs in handling solids are generally greater than those
associated with liquids. However, this method may prove to be the only way to get at least a
fraction of the C02 to great depths.
Land Disposal ofC02
An alternative to sequestering C02 in the deep ocean is the long-term storage or
sequestering of C02 in underground repositories. Options include storage in active or depleted oil
and gas reservoirs, in deep, confined aquifers, and in mined salt or rock cavities. The main issues
are the volume available for storage, the long term integrity of the storage, and the costs
associated with C02 transport to the disposal site and the disposal operation itself Storage
integrity is important not only to prevent the unintended return of C02 to the atmosphere, but also
for concerns about public safety and the potential liability should there be a release. C02 gas is
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heavier than air and has the potential to displace air at the surface and cause asphyxiation.
Storage in depleted oil and gas reservoirs. This appears to be the most promising land
disposal option. Because these reservoirs have already demonstrated their ability to contain
pressurized fluids for long periods of time, their storage integrity for C02 is likely to be good. At
the present rate of gas usage, a volume that ideally could accommodate about 50% of the power
plant C02 production rate is being depleted continuously. Further, taking into account our past
oil and gas usage, these reservoirs have an additional C02 storage potential of about 35 billion
tonnes. However, such reservoirs would require that old wells be reopened and completely
redrilled to gain access. The actual amount of their original capacity that can be utilized
effectively for C02 sequestering is uncertain given that changes to the reservoir may have
occurred due to water/brine intrusion or geostructural alterations.
Storage in active oil and gas reservoirs. C02 from natural reservoirs, which is available at
about one-third the cost of C02 capture from power plants, is presently used for enhanced oil
recovery (EOR) in active oil wells. Furthermore, the amount of C02 that can be utilized for EOR
is small compared to total C02 emissions. While the basic technology exists for EOR, some
additional research is required on necessary modifications to EOR operations to achieve the not
always compatible goals of oil recovery and C02 storage. Injection of C02 in active gas fields is
not an attractive option because it will mix with and dilute the natural gas and will return to the
atmosphere when the natural gas is used.
Storage in deep, confined aquifers. C02 might be stored in deep, confined saline aquifers
that are well below those that communicate with surface waters or that are used for drinking
water supply. Here, the definition of "aquifers" is expanded to include any deep formation, with
sufficient permeability and porosity, that is water-saturated. Injection of C02 into such aquifers
would displace water to provide C02 storage volume. There are many uncertainties about the
feasibility of this option. The aquifer should be located under a relatively impermeable geologic
structural cap to isolate it, but should also have good permeability under the cap. The volumetric
sweep efficiency behavior of C02 in such an aquifer is important in determining the displacement
behavior, as effects of gravity segregation and "fingering" may limit the amount of volumetric
storage capacity. Estimates of potential storage capacity for C02 in deep, confined aquifers range
over several orders of magnitude, with the upper estimates indicating very large storage potential.
Storage in mined salt domes or rock caverns. Costs associated with creating storage
volume are a major concern. Unless a major breakthrough in mining costs occurs, the excavated
rock cavern option is too expensive to be practical. Salt domes can be excavated at more
reasonable cost by solution mining, but even these costs are prohibitive. In either case, very large
amounts of rock or brine would have to be excavated, handled, and utilized or disposed of in an
environmentally acceptable manner.
PROJECTED COSTS OF C02 CAPTURE AND DISPOSAL
Figure 2 plots S/tonne C02 avoided for the five capture scenarios, each assuming three
levels of disposal costs: zero, moderate ($15/tonne C02 captured), and high ($50/tonne C02

-------
captured). For reference, the carbon tax currently in force in Norway is also shown ($50/tonne
C02) The two cases based on emerging technology (i.e. IGCC and fuel cells) have the lowest
C02 avoidance costs due both to relatively high efficiency power cycles and high efficiency C02
capture processes.
CONDITIONS NECESSARY TO IMPLEMENT C02 CAPTURE
Before the implementation of C02 capture and sequestration strategies, the following
three criteria will need to be met:
The effects of the build-up of greenhouse gases in the atmosphere are shown to represent
a clear and present danger. The cost estimates and energy penalties for C02 capture and
sequestration are relatively high. For coal-fired power plants, known retrofit technologies,
together with disposal, would more than double the cost of electricity. Advanced power
cycles promise to provide C02 capture that, together with disposal, would increase the cost of
electricity by 50-100%. If a carbon tax on the order of $50/tonne C02 ($183/tonne C) or
more were imposed, it may be cost-effective to capture and sequester the C02 (see Figure 2).
However, before such large carbon taxes would be imposed, global warming must be shown
to represent a clear and present danger.
The "front-line" options are inadequate to eliminate the threat of global warming. Front-
line options include improving energy efficiency (both demand side and supply side), fuel
switching (from coal and oil to natural gas or renewables like solar, geothermal, wind, and
biomass), and reforestation. These are the options that are generally cited as both the most
cost-effective and having positive benefits beyond just reducing the C02 build-up in the
atmosphere. The key question is whether these options can stop the increase of the
atmospheric C02 concentration by themselves. While not an unanimous opinion, many people
believe the answer is no.
The CO2 capture and sequestration option is developed enough to be considered as a
viable "strong-medicine" option. If the first two conditions discussed above are met, the
policy makers will turn to the "strong-medicine" options. These strong medicine options all
have something that tastes bad when they are used, whether it is cost, environmental
concerns, or safety concerns. In addition to C02 capture and sequestration, these options
include adaptation, fuel switching to nuclear, and geo-engineering (eg. screening out sunlight,
cloud seeding, fertilizing the ocean, etc.)
CONCLUSIONS
C02 capture and sequestration should be viewed as an insurance policy. It is the only C02
mitigation option that allows use of our large fossil fuel resources without a build-up of
greenhouse gases in the atmosphere. Since we cannot accurately predict the future, either in
terms of energy supply or the magnitude of the effects of climate change, it is prudent to continue
research in this area. However, large-scale implementation of the C02 capture and sequestration
option does not appear imminent.
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ACKNOWLEDGEMENTS
This paper was based, in part, upon research projects into the capture and sequestration of
C02. I would like to acknowledge my colleagues who participated in these projects, including
Jefferson W, Tester and Elisabeth M. Drake of the MIT Energy Laboratory, E. Eric Adams of the
MIT Parsons Laboratory, and Dan Golomb of the University of Lowell, as well as our sponsors,
the U.S. Department of Energy, the Mitsubishi Research Institute, and the 1EA Greenhouse Gas
R&D Programme.
REFERENCES
1.	Marchetti, C , "On geoengineering and the CO, problem," Climatic Change, 1, pp. 59-68 (1977).
2.	Golomb, D., H. Herzog, J. Tester, D. White and S. Zemba, Feasibility, Modeling and Economics of
Sequestering Power Plant COj Emissions in the Deep Ocean, MIT-EL 89-003, MIT Energy Laboratory,
Cambridge, MA (1989).
3.	I Ierzog, R, D. Golomb and S, Zemba, "Feasibility, modeling and economics of sequestering power plant CO,
emissions in the deep ocean," Env. Prog., 10(10), pp. 64-74 (1991).
4.	Liro, C.R., E.E. Adams and H.J. Herzog, Modeling the Release of C02 in the Deep Ocean, MIT-EL 91 -002,
MIT Energy Laboratory, Cambridge, MA (1991).
5.	Liro, C.R,, E.E, Adams and H. J. Herzog, "Modeling the release of COt in the deep ocean", Energy Corners.
Mgmt, 33(5-8), pp. 667-674 (1992).
6.	Herzog, H., E. Drake, J. Tester and R. Rosenthal, A Research Needs Assessment for the Capture, Utilization,
and Disposal of Carbon Dioxide from Fossil Fuel-Fired Power Plants, DOE/ER-30194, U.S. Department of
Energy, Washington, DC (1993).
7.	Herzog, H.J. and E.M, Drake, Long-Term Advanced Co3 Capture Options, IEA/93/0E6, IEA Greenhouse Gas
R&D Programme, Cheltenham, U.K. (1993).
8.	Booras, G.S. and S C. Smelser, "An engineering and economic evaluation of C02 removal from fossil-luel-fired
power plants," Energy, 16(11/12), pp. 1295-1305(1991).
9.	Suda, T., M. Fujii, K. Yoshida, M. lijima, T. Seto and S. Matsuoka, "Development of flue gas carbon dioxide
recovery technology," Energy Convers. Mgmt, 33(5-8), pp. 317-324 (1992).
10.	Barchas, R. and R. Davis, "The Kerr-McGee/ABB Lummus Crest technology for the recovery of C02 from stack
gases," Energy Comers. Mgmt, 33(5-8), pp. 333-340 (1992).
11.	Sander, M.T. and C.L. Mariz, "The Fluor Daniel Econamine FG Process: past experience and present day
focus," Energy Comers. Mgmt, 33(5-8), pp. 341-348 (1992).
12.	Kumar, R., T. Fuller, R. Kocourek, G. Teats, J. Young, K, Myles and A. Wolsky, Tests to Produce and Recover
Carbon Dioxide by Burning Coal in Oxygen and Recycling Flue Gas, ANL-CNSV-61, Argoruie National
Laboratory, Argoruie, IL (1987).
13.	Spanrow, F.T., AM Wolsky, G.F. Berry, C. Brooks, T.B. Cobb, E.P. Lynch, D.J. Jankowski and E.W.
Walbndge, Carbon Dioxide from Flue Gases for Enhanced Oil Recovery, ANL-CNSV-65, Argoime National
Laboratory, Argonne IL (1988).
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14.	Abele, A.R., G.S. Kindt, W.D. Clark, R. Payne and S.L. Chen, An Experimental Program to Test the Feasibility
of Obtaining Normal Performance from Combustors Using Oxygen and Recycled Gas instead of Air, ANL-
CNSV-TM-204, Argonne National Laboratory, Argonne, IL (1987).
15.	National Acid Precipitation Assessment Program (NAPAP), Technologies and Other Measures for Controlling
Emissions: Performance, Costs and Applicability, Report 25, Government Printing Office, Washington, DC
(1990).
16.	Hendriks, C., K. Blok and W.C. Turkenburg, "Technology and cost of recovering and storing carbon dioxide
from an integrated-gasifier, combined-cycle plant," Energy, 16(11/12), pp. 1277-1293 (1991).
17.	Baes, C.F., Jr., S.E. Brail and D. W. Lee, "The collection, disposal, and storage of carbon dioxide," Interactions
of Energy and Climate, W, Bach, J. Pankrath, and J. Williams, Eds., 2D. Reidel Publishing Co., pp. 495-519
(1980).
18.	Haugen, P.M. and H. Drange, "Sequestration of C02 in the deep ocean by shallow injection," Nature, 357, pp.
318-320(1992).
19.	Adams, M.E., D. 
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FIGURE 1: SPECTRUM OF OPTIONS FOR ATMOSPHERIC CO, REDUCTION
Renewable
Solar, wind,
gaotharmal
FIGURE 2: SUMMARY OF PROJECTED COSTS OF C02 CAPTURE AND DISPOSAL
160
GTCC/MEA FC/MEA	PC/02	IGCC	FC
Moderate Disposal Costs High Disposal Costs Norway Carbon Tax
Zaro Disposal Costs
$15/tonne CQ2 captured $50/tonna CQ2 captured $50/tonne CQ2
Key: GTCC, Gas Turbine Combined Cycle Power Plant; MEA, Monoethanolamine Capture Process;
PC, Pulverized Coal; 02, Air Separation and Flue Gas Recycle Capture Scheme; ICGG, Integrated
Gasification Combined Cycle with C02 capture from the synthesis gas via shift and physical absorpton;
FC - Similar to IGCC, but replacing the gas turbines with fuel cells.
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3-G
"Front-Line" CO2 Abatements from the Steel Industry
Britt R. Gilbert
TORESCO, Ltd.
Our previous speaker, Mr. Herzog, has distinguished between two fundamentally different
types of response to the dangers of C02 buildup in the atmosphere. One type of response
will occur when (and if) society decides that buildup of atmospheric CO2 threatens us.
Should this occur, mandatory C02 mitigation measures will be forced on industry,
transportation, and agriculture, etc. The costs of these measures may be be shocking.
The second type of response is what Mr. Herzog calls "front-line" strategies. I characterize
front-line strategies as an opportunistic mix of early regulatory, technological, and
financial actions that can produce large "greenhouse gas" abatements, but at costs we can
afford to pay even before we are certain of the dangers from those gases. I wish to tell you
about one such "front-line" strategy: Offer the world's steel makers some small, near-term
economic incentives to reduce their C02 emissions. Steelmaking has the potential to
produce huge, early, and relatively easy abatements of CO2.
COi emissions from steelmaking topped 1 billion metric tonnes per year in 1990. Since
then, and purely by accident, the world steel industry has been reducing its CO2 emissions.
Blissfully unaware of the implications for the biosphere and driven only by commercial
motives, the steel industry will continue to lower its emissions of CO2, but at a pace set
purely by the internal economics of steelrmking.
The pace of these CO2 abatements could be accelerated considerably, I believe, by
relatively small external economic forces (and at a small fraction of the costs that Mr.
Herzog projects for future mandatory controls on CO2 from coal powerplants). For policy
makers struggling with the conflicting social and technological choices that confuse the
debate over what to do about "greenhouse" gas emissions, I submit to you that the profit
motive is the simplest of all factors to manipulate for social good. My thesis is that modest
external economic incentives, put into place in the near term, would result in huge CO2
abatements from steelmaking within as little as 20 to 25 years.
In the continuing debate whether wc "Learn, then Act," or "Act, then Learn," the latter
course is a "no-brainer" if the consequences of early action are overwhelmingly beneficial.
The steel industry needs only a small economic incentive, a nudge, to accomplish quickly
The work described in this paper was riot funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the agency and no official endorsement should be
inferred.
3-64

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what it is already accomplishing deliberately, which is the replacement of obsolescent
technology with advanced technology. It doesn't sound exciting, but the potential CO2
reductions will surprise you.
Carbon-intensive Inefficiency
Fundamental technological and economic forces have been rifting and reforming the steel
industry over the last three decades. And the technological fault line runs through the very
heart of the mill, the coke oven and blast furnace that win iron from ore.
The blast furnace and coke oven are the foundation technologies of the steel industry, and
have survived almost unchanged since the 1880s. Today, about two-thirds of the 750
million tonnes of steel produced worldwide is made from ore and carbon in blast furnaces.
Thermo-chemically, however, coke oven/blast furnace smelting attains only about 35%
efficiency in making iron. (Not only is the blast furnace inefficient, but its deadly adjunct,
the coke oven, exhales a blue haze of carcinogenic VOCs. The coke oven is widely
regarded as the worst environmental menace in heavy industry.)
Figure 1 Carbon Balance for Conventional Iron Smelting
Carbon Inputs,
566 kg C
4.6 kg C
28.5 kg C |
^	~
MOLTEN
IRON
1 Tonne
Carbon Outputs
42 kg C in
Molten Iron
599 kg C
557 kg = TOTAL CARBON fleas C in Iron)
2042 kg = TOTAL C02
0 K9 = TOTAL CCE RECOVERED
2042 kg =C02 FROM STACKS
42 kg C
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Carbon Balance for Conventional Steelmaking
Figure 1 tallies carbon inputs and outputs for conventional ironmaking. Carbon inputs are
shown in the upper left corner. Coke "breeze" (fines from the coking process), coal, and
natural gas contribute 599 kg of carbon input The only output of carbon from ironmaking
is the 42 kg dissolved in the hot metal. The balance of 557 kg of carbon is almost entirely
lost to the atmosphere as CO?. In conventional ironmaking, C02 is released from four
main stacks (sinter plant, coke oven, blast furnace, and the boilers for turbo-blower/steam
turbine-generator). It should be noted that the CO2 in these stacks is diluted, dirty, and not
economically recoverable by currently available processes. The missing 557 kg of carbon
has been combusted in the ironmaking process into 2.04 tonnes of C02 per tonne of iron.
Comparison of CO2 Emissions from Various Iron and Steel Processes
Figure 2		fr
2.1
2.0
0.5
CO2
perT.
Fe
0.6
yX4>$-9

1.7
0£
0.3
0.4
oaa-bated tcan
(,UIDHEX8> etc.)
ooa/-Ba»«d Iron Hon from
(with 2nd without blast
C02 33I&9}	furnace
coke overt
comenttoruil
sieetmMng
(BOF)
recycling
steel scrap tn
Btctrtc Arc
Furnacs (EAF)
BAF melting
temp plus
gaa-btoed Iron
EAF
melting
acnpphn
mtWHM
lron(wC02
Batenj
Steelmaking requires one more device, the Basic Oxygen Furnace (BOF) to turn iron into
steel. In the BOF, hot metal from the blast furnace is combined with scrap and reacted with
oxygen to reduce dissolved carbon in the molten steel to 1% or less. This produces another
116 kg of C02, for a total of 2.16 tonnes C02/tonne iron. Owing to the addition of scrap to
the BOF charge, the CG2 released per tonne of steel is about 1.7 tonnes/tonne steel. Figure
2 shows C02 emissions for conventional iron and steel processes at the center.
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Thus, blast furnace ironmaking is a very carbon-intensive process, requiring metallurgical
coke (porous lumps of nearly pure carbon) made via the destructive distillation of coal. To
make one tonne of iron requires half a tonne of coke, which requires three quarters of a
tonne of coal. And all but 1% of that carbon ends up in the atmosphere as CO2. Every
tonne of molten iron made in a blast furnace releases almost 2.2 tonnes of CO2. (In less
efficient mills in India, China, etc., the CO2 releases may be 4 or 5 tonnes per tonne of
iron.)
CO2 emissions aside, the conventional steelmaking paradigm has big problems; pollution
from coke ovens, inefficient use of expensive coke, operating inflexibility, and need for a
$100-150 million re-line every seven years. As a result, in the United States, no new blast
furnaces have been constructed in decades.
As might be expected, the economic and environmental problems of the blast furnace/coke
oven process have spurred development of a new generation of ironmaking technologies,
some of which are now fully commercial, with many more reaching the demonstration
phase. However, the conventional integrated steel industry has never embraced these new
ironmaking technologies. (That task fell to others, as we shall see.) Rather, the integrated
steelmakers have been squeezing small incremental efficiencies out of their existing
furnaces, and holding their collective managerial breath until a new technological
paradigm for steelmaking emerges.
The New Paradigm
In the mid-1960s, entrepreneurs here and abroad started combining a little-regarded
technology, the electric arc furnace (EAF), with the newly developed continuous caster.
This started the "minimill" movement. Minimills recycle scrap by melting it in EAFs, cast
the recycled steel efficiently using continuous casters, and then sell the resulting "long
products" (rebar, I-beams, etc.) into the local structural steel market. By 1985, the
minimills had completely taken over long products from the integrated steelmakers. In
1989, another temblor shook the industry as the perennial "minimill" leader, Nucor,
opened its first mill to make higher value "flat products" The aftershocks are still being
felt. In the last year, sixteen million tonnes of new electric steelmaking capacity has been
announced for the US alone, all of it in flat-rolled products. The new paradigm is coming
into focus.
Figure 3 classifies world steel production by manufacturing process. Note that, by 1980,
scrap-fed electric arc furnace steelmaking had arrested the growth of conventional
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800
700 '
Mm Tonnes
per year
600 ¦
500
400 -
300 ~
200 -
100 -
0
1950 55 60 65 70 75 80 85 90 95" 2000*
steelmaking. And, by 1990, electric steelmaking had begun to force an absolute decline in
the production of conventional steel. By the year 2000, electric steelmakers will produce
a third of all the world's steel, almost all of it from recycled scrap.
Carbon Dioxide Emissions from Electric Steelmaking
Recycling steel scrap into new steel (using EAFs) requires less energy and emits less
carbon dioxide than conventional production of steel from ore. An EAF requires only
about 450 kwh to melt and purify a tonne of scrap into a tonne of steel, and because
production of that electricity emits about 0.3 tons of C02, electric steelmaking releases
only 18% of the 1.7 tons of CQ2 produced by conventional steelmaking. (I have assumed
a generating mix typical of the US, i.e., 55% coal fired, 20% nuclear, with the balance
being hydro/gas/wind,ete.)
Figure 3
World Steel Production by Process
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Figure 2 also shows the CO2 emissions for scrap-based electric steelmaking. Because
electric steelmaking releases less than a fifth as much CCte/tonne as conventional
steelmaking, the rise of the minimills has already made a sizable positive impact on CO2
emissions from the steel industry.
World CO2 Emissions from Steelmaking
Figure 4 shows CQ2 emissions from steelmaking, by manufacturing process. One can see
that by the turn of the century, the world steel industry will have effected a decrease in
C02 emissions of 165 million tonnes per year, in a decade when steel production was
steady. How? Because electric steelmaking was expanding its share while conventional
steelmaking was contracting.
CO2 Emissions from World Steel Production, by Process
Mm Tonnes
per year
1000
CO2 from EAF
1950 55
Figure 4
60
65
70
75
80
85
90
95
2000
Figures 2 and 4 show that, by the year 2000, electric steelmaking will be producing 1/3 of
the world's steel. But, because electric steelmaking produces only about 18% of the CO2 of
conventional steelmaking, it will produce less than 1/8 of the total CO2 emissions. Thus,
3 69

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unwittingly, and driven solely by the internal economics of steelmaking, the world steel
industry will have delivered to the biosphere a yearly 165 million ton abatement in COe
emissions. Will these abatements continue, and, if so, how fast? The key is the narrow
striped band in Figure 3, representing alternative ironmaking technologies.
Alternative Ironmaking Technologies
Despite the fact that steel is the most recyclable of all the metals, scrap alone cannot
economically supply more than about a third to a half of the total required ferrous input to
a growing steel industry. Enormous tonnages of scrap are available, but the contaminants
contained in the poorer grades of scrap limit its usefulness for making high quality steel,
particularly the flat products. The electric steelmakers' growing appetite for high quality,
low-residual scrap has already caused shortages in recent months, a problem that is
expected to worsen as more electric meltshops come onstream. The only alternative to low-
residual scrap is alternative forms of iron made from ore. The availability of virgin iron
units is the key to expanding the share of electric steel production. When cold "merchant"
iron becomes widely available, it will become increasingly difficult to distinguish between
a new flat-products "minimill" and a streamlined "integrated" mill, sporting a new electric
meltshop in place of its-blast furnace, coke battery, and BOF. This convergence is now
underway.
CCte Emissions from Alternative Ironmaking
There are at least twelve alternative ironmaking technologies. Six are in operation at
commercial scale. Perhaps three or four more will attain commercial status within five to
seven years. Call it a total of ten technically viable alternative ironmaking processes. Of
those ten, five are based on natural gas and five are based on coal (carbon).
It is relatively simple to arrive at a CCte emission rate for the gas-based processes. All five
processes (MIDREX®, HYL®, Iron Carbide, FTOR®, and Circored®) employ reformers
to produce a COfUz syngas from methane. And all five employ "near-stoichiometric"
reactors to reduce iron with that syngas. All five have published energy requirements in
the range of 11.3 to 14.0 Mm Btu of natural gas per tonne of reduced iron. This equates to
approximately 0.3 tonnes of CQ2 per tonne of iron, as is shown in Figure 2. (The amount
of retained carbon is a maximum of 6% for Iron Carbide, less for the other processes.)
In contrast, the five coal-based alternative iron technologies differ greatly from each other.
All five processes eliminate the need for coke, but there the similarities end. Fastmet®
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roasts pellets composed of ore and powdered coal over a hearth; SL/RN® roasts coal and
ore in a rotating kiln; HIsmelt® reduces ore in a molten iron bath; COREX® gasifies coal
and reduces iron in separate vessels and dumps the depleted gas overboard. One new
process, Circofer® reduces ore in a "near-stoichiometric" reactor using syngas made from
coal in an integrated gasifier. The energy requirements for the five coal-based processes
range from 11 to 24 Mm Btus per tonne of iron. The two coal-based processes with the
best efficiency are Circofer® and Fastmet®, and both release approximately the same
amount of CCte per tonne of iron. But Circofer® releases pure CCte, whereas Fastmet®
emits its CCte as a component of the hearth stack gas.
Figure 2 shows the CCte released by the two most efficient coal-based ironmaking
processes, Fastmet® and Circofer®. Both processes have an uncontrolled emission rate of
1.1 tonnes of CCte per tonne of iron. But, because CCte released by Circofer® can be
recovered at 99% purity, Figure 2 also shows a lower figure of 0.15 tonnes of CCte per
tonne of iron, which assumes that this pure CCte is sold into the market for bulk CCte for
enhanced oil recovery. The bulk CCte market for oil recovery in the US is roughly 60
million tons per year. The domestic steel industry requires about 50 million tonnes of iron
per year, and the resulting CCte from advanced ironmaking processes like Circofer is
commensurate with the demand of the oil recovery market. (At present this demand is
met by tapping the huge reservoirs of natural CCte under Colorado, New Mexico and
Utah.) If CCte from ironmaking were sold into this market, most of it would become
sequestered for periods of geologic time. Financial incentives targeted at CCte reduction
and/or capture for re-use would tend to swing the technology mix of ironmaking toward
processes like Circofer® and the gas-based reduction processes.
Two Scenarios for the Future of the Steel Industry and its CCte emissions
The capacity to produce alternative iron units is limited today to less than 30 million tonnes
per year. However, there has been a flurry of interest in such projects in recent months.
(Such projects are a necessity if the 17 million tons of new flat-product minimill capacity
in the US is to be supplied.) The emergence of these these new ironmaking technologies
opens the door to a massive technology shift in the steel industry, away from the old coke
oven/blast furnace system and toward advanced electric steelmaking which will use both
recycled scrap and pure iron from the new ironmaking technologies.
Figure 5 is a scenario for steel production through the year 2020 (again by process). This
is the "Slow Technological Change" scenario. This scenario is certainly plausible, absent
outside forces. Steel production increases steadily, but the scrap-based EAF share of
3-71

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Scenario for Future Steel Production with Slow Technological Change
Figure 5
1950 SB
Figure 6
Scenario for CO2 Emissions with Slow Technological Change
CO* from new
ironmaking
technologies
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production remains constant due to the limits on scrap supply. Blast furnace ironmaking
declines under environmental and economic pressure. Alternative ironmaking makes up
the shortfall. Figure 6 shows the CO2 emissions expected from the "Slow Change"
scenario, which decrease by 200 million tonnes over the twenty year period.
Figure 7 is the "Rapid Technological Change" scenario for future steel production. Here,
I assume that some hypothetical economic incentives catalyze the inevitable changeover
from polluting coke ovens and uneconomic blast furnaces to more economic advanced
Scenario for Future Steel Production with Rapid Technological Change
700 -
600 -
500
400
300
200
Electric Arc Furnace
(recycling scrap)
WMW.-X-H-H-i-rt-Xv:	f
v«'444^v»< i
4 , <,
... ,. 	^
1V -y*<\ '*'"2**J? ' : ~
;F.' {/>. ^s\	\	rv:,'',; ?>5X

I Blast Furnace j
& Open Hearth
steelmaking. These incentives might take the form of a rapid depreciation schedule, an
investment tax credit, or payments from selling carbon allowances. Any form of incentive
could work, provided that the credits are tied to CO2 abatement. I estimate that incentives
of $10 per ton of CO2 abatement would be sufficient to drive the rapid changeover from
blast furnace to advanced electric steelmaking.
In Figure 7, the blast furnaces are abandoned within three 7 year reline cycles. (This is not
unthinkable, as a single reline of a blast furnace costs up to $150 million, whereas the total
capital cost of a new electric meltshop, built from scratch costs half that amount.) Again,
in Figure 7, note that the inherent limitations of scrap supply constrain scrap-fed EAFs to
only modest growth. The rapid abandonment of blast furnaces necessitates the rapid
3-73

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growth of new ironmaking technologies to make up the requited iron inputs.
The consequences for CCte emissions in the "Rapid" scenario are shown in Figure 8, and
they are striking.
Scenario for CO& Emissions with Rapid Technological Change
1200 - -
C02from EAF
200
CO! from new
Ironmaking
technologies
Figure 8
In the "Rapid Technological Change" scenario, CO2 abatements, reaching a staggering 665
million tons per year of C02 by the year 2021, because of the much lower C02 emissions
of advanced steelmaking processes vs. conventional steelmaking. (In order to quantify the
C02 for advanced EAF steelmaking using "new technology" iron units, I have chosen a
value of 0.45 tonnes of CQz as the emission rate for the striped section in Figure 8, by
averaging the last two bars in Figure 2. This is optimistic, but achievable with external
incentives.)
At present, the world steel industry is carbon-based, thermo-chemically inefficient, and
huge. But it is becoming less-dependent on carbon, much more efficient, and even huger.
Steelmaking has the potential for greater near-term decreases in CO2 emissions than any
other heavy industry because it is poised at the brink of fundamental technological shifts,
particularly in ironmaking. The internal cycle of that shift is seven years, which is the
duration of a typical blast furnace campaign. Every seven years, every single blast furnace
in the world must either be relined at a cost of $50-150 million, or be abandoned, ft is now
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technically and economically feasible for the steel industry to retire virtually every blast
furnace in the world within three campaigns, and replace them with advanced iron and
steelmaking technologies, producing huge abatements of C02 in the near term.
I believe that the steel industry will eventually achieve COi abatements of this magnitude.
The question is, how fast? If small economic incentives were to accelerate the process by
30 years, a cumulative atmospheric buildup of twenty billion tonnes of C02 might be
avoided.
The steel industry is engaged in a heated internal debate over die future technology path of
iron and steel making. However, in that debate, CO2 emissions are an abstract
consideration, unquantifiable, because they have no monetary value. The "front line"
strategy I propose is to engage government and industry to develop a strategy to monetize
C02 abatements at some very modest cash value, $5 or $10 per tonne. I predict with
confidence that the steel industry, at least, will respond with rapid, significant decreases in
C02 emissions. Thank you.
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The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement shouhl be. inferred.
ELECTROCHEMICAL REDUCTION OF C02 TO FUELS
Daniel L. DuBois,
National Renewable Energy Laboratory
1617 Cole Boulevard
Golden, CO 80401
ABSTRACT
A potentially usefUl approach to liquid fuel synthesis in the future may involve the direct
electrochemical reduction of CO,. This paper describes some of the problems which must be
overcome for this approach to become feasible. Possible energy and C02 sources are discussed
briefly. The major focus of the discussion is on the properties which catalysts for electrochemical
CO, reduction should possess. A brief review of various catalytic systems currently under study in a
number of laboratories is presented to assess the present state of the art and the problems which need
to be overcome.
INTRODUCTION
Nearly all transportation fuels are derived from fossil energy sources. Because of their high
energy density, ease of handling and storage, and availability, liquid fuels have become dominant in
the transportation sector. In light of present concerns regarding greenhouse gases, it is important to
consider a range of options which could provide the liquid transportation fuels that will continue to be
needed in the future without adding to the net C02 burden. In this paper we discuss one such option
and the technical barriers which must be addressed before such a process can become viable.
Nonfossil sources of energy include nuclear power and renewable energy sources such as
biomass, hydroelectric, photovoltaics, wind, and solar thermal and geothermal processes. With the
exception of biomass, which produces plant material, electricity is the major product of each of these
sources of energy. Because of the relatively low efficiency of converting solar energy to biomass and
subsequently to fuels, very large land masses will be required for fuels produced using this route. A
potentially complementary approach is the direct conversion of electricity and low energy substrates
such as water and C02 into fuels, In today's market this is not economically feasible because of cheap
fossil energy. However, if the environmental costs associated with CO, production become too high
in the future, the conversion of electricity to fuels may become a reasonable option.
Although the electrolysis of water to form hydrogen and oxygen has received the most
attention for energy storage and fuel production from electricity, the reduction of C02 to produce
methanol, ethanol, or other hydrocarbon fuels is also attractive. Both water and C02 are relatively
abundant and provide low energy substrates for the generation of fuels. In this paper, we examine
some of the different routes to C02 reduction and some of the difficulties which must be overcome to
make these processes feasible.

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DISCUSSION
Roggv.S.up{>ly
To assess the technical feasibility of electrochemically reducing C02 to a liquid fuel, we shall
consider the energy requirements for a system that is driven by a photovoltaic grid. Assuming an
average incident solar power of 200 W/m2 and a 10% conversion efficiency, Archer and Bolton
estimate that 1% of the U.S. land area would produce 109 metric tons of methanol which is equivalent
to the total energy consumption of the U.S. in 1978 [1], This rate of methanol production corresponds
to 37 mL/mJday or lxlO2 gallons/m2day. These estimates indicate that there is adequate solar energy
available to meet our fiiel needs, but that this energy source will have to be used efficiently. In
addition to electricity from photovoltaic grids, other sources of electricity based on renewable or
nuclear energy could also be utilized.
CQ;Sources
There are several possible sources of COr These include atmospheric CO,, C02 reservoirs
and carbonate mineral deposits, and C02 rejected from power plants and biomass processing. In order
to utilize C02 directly from the atmosphere, a process must be developed which will permit CO. to be
selectively concentrated with high efficiency. Simple thermodynamic considerations based on the
free energy of mixing of gases suggest that the energy required to concentrate C02 from the current
atmospheric pressure (0.27 mmHg, 350 ppm) to one atmosphere (760 mmHg) would require 4.7
kcal/mole or about 3% of the energy required to reduce C02 to methanol (168 kcal/mole) [2],
However, using current "C02 separation technologies, which are inefficient at low pressures, a
significant fraction of the energy required for making fuels will be utilized for C02 recovery. In one
of the more efficient systems proposed for CO, recovery from the atmosphere, it is estimated that
roughly a third of the total energy consumption required for producing methanol from atmospheric
C02 would be required for C02 recovery [3]. Although it is technically feasible to utilize atmospheric
C02 for the direct synthesis of fuels, the development of new methods for C02 separation and
recovery will be required for good overall energy efficiency.
Although natural CO. reservoirs and carbonate mineral deposits provide a high purity source
of C02, they offer no advantage over fossil fuels from a C02 mitigation viewpoint. Both involve
extracting bound carbon from the earth and releasing it into the atmosphere in the form of carbon
dioxide. For this reason, natural C02 reservoirs are not considered an option as a source of C02.
Various combinations of photovoltaics and integrated coal gasification combined cycle
technologies have been considered for producing hydrocarbon fuels from C02 released during power
generation, and under certain conditions this appears to be an attractive alternative [4], In this process
the C02 produced from a fossil fuel source is reduced using hydrogen produced by electrolysis of
water. The direct current electricity used in the electrolysis experiment is in turn generated from a
photovoltaic array. Ultimately however, the goal should be to completely replace fossil fuels, in
which case this source of C02 would not be available.
Another possible source of CO, is biomass. During the conversion of biomass to fuels
approximately 50% of the carbon is rejected into the atmosphere as CO,. While the production of
fuels from biomass is C02 neutral, utilization of the waste C02 by reducing it to a fuel with electricity
generated from a photovoltaic device offers some advantages to both technologies. Due to the higher
solar conversion efficiencies of a photovoltaic system compared to green plants, the land mass-
requirements for producing a given quantity of liquid fuel could be significantly reduced, and the
electricity produced by photovoltaic devices could be stored as a liquid suitable for use by the
transportation industry.
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Finally, consideration should be given to using C02 in a regenerative fashion in fuel cells
based on alcohols or other hydrocarbon fuels. In such a fuel cell the CO, produced during fuel
consumption would be retained, and the fuel would be resynthesized by running the fuel cell in
reverse to reduce C02. Such cells would be similar in operation to rechargeable batteries. Properly
optimized liquid fiiel cells should have higher energy densities than either hydrogen fuel cells or
batteries. The use of C02 in such a cyclic fashion would reduce the need for major C02 sources.
Catalyst Requirements
There are two commonly considered pathways for reducing C02 to fuels. One pathway is the
direct reduction of C02 to a fuel in a single process. The production of methanol and oxygen from
C02, water, and electricity (eq 3) is an example of such a process. The cathodic and anodic half-cell
reactions that occur during the cell reaction are shown in eqs 1 and 2. Another route requires the
electrolysis of water to produce hydrogen (eq 4), which is used to reduce C02 to a fuel (eq 5). Again
the overall process is the production of methanol and oxygen from CO, and water. The first pathway
has the advantage that it should ultimately be simpler, more efficient, and require less capital
investment. The latter route is more technically advanced. Both routes require the use of catalysts to
be efficient. Uncatalyzed electrochemical reduction of CO. requires large overvoltages (nearly 2
volts) and gives a variety of products depending on reaction conditions. Similarly, in the absence of a
catalyst no reaction occurs between C02 and hydrogen. Better catalysts need to be developed for both
processes. Because the author is more familiar with direct electrochemical reduction of C02, the
catalytic requirements for the process shown by eqs 1 -3 will be discussed here. Similar considerations
apply to catalysts being developed for CO, hydrogenation and water electrolysis.
Cathode C02 + 6 H+ + 6 c"	CH3OH + H20 (1)
Anode 3 H20 ==*= 6 H+ + 6 e" + 3/2 02	(2)
Cell C02 1 21120	CII3OII 1 3/2 02	(3)
Electrolysis	H20 - *" H2 + 1/2 02	(4)
Hydrogenation . co? + 3 Ho	CfchOH + H?Q
Process	C02 + 2 H20 =5=^ CH3OH + 3/2 02 (6)
Four properties that are important in assessing the suitability of a catalyst for carrying out a
given reaction are the catalytic rate (current density), catalyst selectivity (current efficiency), catalyst
lifetime (turnover number), and the overpotential which the catalyst requires (energy efficiency). If a
catalysts fails to meet minimum requirements for any of these properties, it will not be suitable for
carrying out the desired reaction.
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The potentials of half-reactions 1 and 2 are +0.03 V and +1.23 V, respectively, versus the
standard hydrogen electrode. Cell reaction 3 requires a minimum potential difference between the
anode and cathode of 1.2 V. If a conversion efficiency of 80% is desired for converting electrical
energy into chemical energy, the applied voltage should not exceed 1.5 V. Factors contributing to the
cell voltage include resistance losses and overpotentials associated with each electrode. To achieve a
cell overvoltage of less than 0.3 V arid allow for resistance losses, the overvoltage for each half-cell
reaction should be less than 0.1 V. Overpotentials can arise from poor electrode kinetics,
concentration gradients, or a poor match between the potential of the reaction being catalyzed and the
redox potential of the catalyst. Most of the catalysts for C02 reduction studied to date have much
larger overpotentials than are desired, and in many instances the true overpotentials are difficult to
assess, because the catalysts operate in nonaqueous solvents. However, a few catalysts for C02
reduction do appear to operate at relatively low overpotentials [5],
The current density of an electrode is another important parameter that needs to be considered
in fuel production schemes using C02 as a substrate. If an average incident solar flux of 200 W/m2 is
assumed, this corresponds to a current density of approximately 15 mA/cm2 assuming a cell potential
of 1.5 V. If the solar to electricity conversion is 10% then a current density 1.5 mA/cm2 would be
produced. Because 200 W/m2 is an average value, maximum current densities that are one to two
orders of magnitude higher, or approximately 0.1 A/cm2, could easily occur. For heterogeneous
catalysts the current density represents a usefiil measure of the catalytic rate. To put homogeneous
catalysts on the same basis, it is reasonable to calculate the catalytic rate required to produce a current
density of 0.1 A'cm2 if a single monolayer of the catalyst were immobilized on the electrode surface.
Eq 7 shows the relationship between the current density (/), the number of electrons involved in the
catalytic process («), Faraday's constant (/•), the surface coverage of the catalyst (T), the concentration
of CO, (C), and the second order rate constant for the catalytic reaction (k) [6], Assuming six
j = nFkT C	(7)
electrons for the reduction of C02 to methanol and values of 0.1 M and 10"'° moles for the
concentration of C02 and the catalyst surface coverage, respectively, requires a second order rate
constant between 104 and 10s M's1 to achieve a current density of 0.1 A/cm2. The rate requirements
for both the heterogeneous and the heterogenized homogeneous catalysts are very rough estimates.
The rates could be lower if the surface area or the surface coverage can be increased without
deleterious effects. The current densities and rates discussed above are not meant to be interpreted as
unambiguous requirements, but they should provide useful goals.
Catalyst stability is often expressed in terms of its turnover number. The turnover number for
a catalyst is the ratio of the number of moles of product formed to moles of catalyst that are
deactivated. There are at least two factors that could dictate the stability required for a catalyst. The
first is the cost of the catalyst. If the catalyst is very expensive it could contribute significantly to the
cost of the fuel produced. Eq 8 shows the relationship between the turnover number (t.n.), the cost of
the catalyst per kg, the cost of the fuel produced per kilogram, the molecular weight of the catalyst,
the molecular weight of the flicl, and the fraction of the fuel cost attributed to the catalyst (f). For
cos t of cat I kg mo! wt of cat 1
/.«.=			—•			•—	(8)
cos? of fuel / kg mol vet of fiiel f
example, if the cost of the catalyst is $1000/kg, the value of the fuel produced is $ I /kg, the molecular
weight of the catalyst is 1000 g/mole, the molecular weight of methanol is 32 g/mole, and the fraction
of the methanol cost which we can afford to spend on the catalyst is 0.01 or 1%, then the turnover
number of the catalyst would have to be 3xl06 or larger. Put another way, if the turnover number of
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our catalyst is 3x10s or greater, then the catalyst will contribute less than 1% to the cost of the
methanol produced.
The availability of the metals required to make the catalyst could also influence how stable
the catalyst must be. For example, if an area equal to 1% of the U.S. land mass (105 km2) were coated
with one monolayer of a catalyst containing a metal with an atomic weight of 100, then 10 metric tons
of metal would be required. To put this in perspective, in 1978 the world production of platinum
group metals was approximately 200 metric tons, of which about half was palladium. In 1980 the
U.S. automotive industry used 5.5 metric tons of palladium and 16 metric tons of platinum [7]. If
catalysts containing precious metals degrade quickly and cannot be recovered, the use of such metals
will not he practical. However, if relatively high turnover numbers can be achieved and the catalyst
can be recovered, then even precious metal catalysts could be considered. For example, if 10 metric
tons of palladium were used each year to produce 10' metric tons of methanol as discussed above, an
effective turnover number of approximately 10* would be required. While this is a large number, it
should be remembered that at a catalytic rate of 104 M'V', a catalyst will turnover approximately 10*
times in one day, A catalyst with a lifetime of 10 days would be adequate if regeneration of the
catalyst is not too difficult.
The last catalytic property to be discussed is current efficiency. Catalysts with low selectivity
produce a variety of products. This product distribution normally requires product separation and
purificatioa A reasonable goal for product selectivity would be a current efficiency of 90% or greater
for the desired product. This means that 90% of the charge passed is used to produce the desired fuel.
This is also important for energy efficiency if products of lower energy value than the fiiel are formed.
In this case, low current efficiency would also result in low energy efficiency.
Several catalytic systems have been reported for the electrochemical reduction of CO.. Of
these systems copper electrodes are among the most interesting. Systematic surveys of a variety of
metal electrodes resulted in the discovery that copper electrodes could reduce C07 to methane [8].
This result is significant because an eight electron reduction is occurring on the electrode surface.
Several studies have been directed at elucidating the mechanism of this reaction, but a complete
mechanistic picture still remains elusive [9-11], However, a detailed mechanistic understanding could
be useful in overcoming some of the technical problems associated with this system. One problem is
that production of methane occurs only when overvoltages of approximately 1 V are applied. Such a
large ovcrvoltage would mean that the maximum energy efficiency for such a system would be about
50%. A second problem is the selectivity of the reduction process. In addition to methane, a variety
of other products are formed including H;, CO, ethylene, and formate. Ideally, a single product is
desired. When multiple products are formed, their separation will fijrther reduce the overall
efficiency. Another problem is the low current density for methane production. Various approaches
have been used to attempt to overcome this difficulty by increasing either the effective CO,
concentration at the electrode surface or by increasing the electrode surface area. These approaches
appear to be promising, and current densities in excess of 0.1 A/cm2 have been achieved [10, 12].
Finally, upon prolonged electrolysis the copper electrodes become inactive. However, recent results
liave demonstrated that this problem can largely be overcome by regenerating the electrode surface
using short excursions of the electrodes to anodic potentials [13]. This is a very interesting and
important result, because it demonstrates that catalyst regeneration can be very simple and effective.
An interesting extension of this work is the study of gas diffusion electrodes constructed with
copper containing perovskites. In this case current efficiencies in excess of 35% were observed for
the formation of ethanol and propanol [10]. This result clearly demonstrates that higher alcohols can
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be obtained by direct electrochemical reduction of CO,. Although this system exhibits many of the
problems observed for copper electrodes, it clearly merits further study.
There are also several homogeneous catalysts that are of interest. These catalysts can be
classified into three main groups based on the ligands bound to the catalytic metal site. These classes
are illustrated by structures 1-3. The first report of transition metal complexes used to reduce CO.
were phthalocyanines adsorbed on carbon electrodes [14]. This work was extended to include a
variety of macrocyclic complexes by Eisenberg and coworkers [15]. Careful mechanistic studies and
structure activity correlations for this class of complexes have been carried out by Cruetz and Fujita
[16]. These studies have significantly enhanced our knowledge of structural influences on the
mechanisms and thermodynamics of CO. binding. One of the most interesting observations for this
class of complexes is that nickel(I) cyclam complexes (where cyclam is 1,4,8,11-
tetraazacyclotetradecane) adsorbed on mercury are very active, stable, and selective for the reduction
of C02 to CO [17]. Even in acidic solutions CO is quantitatively produced. Hydrogen, which is a
thermodynamically more favorable product, is not produced. On the negative side, the overpotential
for C02 reduction is approximately 0.5 V, and the mercury electrode is environmentally undesirable.
However, if the structural features induced by adsorption onto mercury were elucidated, then
elimination of the requirement for mercuty might be feasible.
n+
Nn ,N
/ \ ,

2+
CO	pr2
N, ;,CO
/ s-	^^ r/
M )	T ^Re	R'P— Pd — S
7 '	:;at/ • ^
N N'	l( )!
\ /	L v J J
ft 1 CO
V_V	^ °	"-PR2
The rhenium bipyridine complex, 2, was first shown to catalyze the reduction of C03 to CO
by Lehn and coworkers [18]. Subsequent work by the groups of Lehn [18], Meyer [19], and Tanaka
[20] has expanded the range of catalysts to include rhodium and ruthenium and provided a better
understanding of the different reaction pathways which can lead to the production of formate in
addition to CO. Tanaka and coworkers have also made the observation that certain complexes can
catalyze the reduction of CO, to methanol, a six electron process [20], Although the current efficiency
for methanol production is low, this result is significant because homogeneous catalysts normally
produce either CO or formate, which are two-electron reduction products. The mechanism of
methanol production is not known, but a greater understanding of this system offers the possibility of
developing catalysts capable of selectively reducing C02 to methanol in a single step. Another recent
advance in this area has been the observation that electrodes can be easily modified with low valent
ruthenium Films which are highly active for the reduction of C02 to CO [21], Unfortunately these
films are very sensitive to oxygen. The majority of the studies of these complexes have been carried
out in organic solvents. As a result, the true overpotentials of these systems are difficult to assess.
However, the redox potentials of these complexes would suggest an overpotential of 0.5 V or greater.
Measured rate constants for these systems are on the order of 50 M"V' [19], significantly less than
needed for practical systems.
The final class of catalysts, involving transition metal phosphine complexes such as 3, has
been studied extensively in our group [22], A large number of metal phosphine complexes containing
various combinations of phosphine ligands and metals were investigated, and it was found that
3-81

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palladium complexes containing tridentate phosphine ligands and a weakly coordinating ligand such
as acetonitrile or dimethylformamide were the most effective catalysts. The reaction catalyzed is the
reduction of C02 to CO, and the current efficiency for CO formation can be as high as 99%. The
catalytic rates for complexes such as 3 range from 10 to 300 M 's"1. The latter rate is reasonably high
for homogeneous catalysts, but it is much lower than the desired rate constants of 104-105. The half-
wave potentials for these catalysts are between -0.7 and -1.1 V vs. the standard calomel electrode, but
because these catalysts function best in organic solvents such as dimethylformamide or acetonitrile,
precise overpotentials are difficult to estimate. Another major problem associated with these catalysts
is their low turnover numbers, typically in the range of 10 to 200. The decomposition products for
several of these catalysts have been unambiguously determined by x-ray diffraction techniques and
shown to be Pd(I) dimers. These dimers are readily reoxidized by application of an anodic potential
to regenerate the original catalytic species. This facile regeneration of the catalyst is similar to that
observed for the copper electrodes described above.
A number of kinetic studies of these catalysts have been carried out, and the mechanism by
which these catalysts operate are among the best understood [22, 23], There are two steps in the
catalytic cycle which can be rate determining. At acid concentrations in excess of 0.05 M,
/—">PR2
RP	Pd"S
-pr2
+ C02
0, ,0 '
c
PR2
RPPd's
< /
V-pr2
(9)
2 ~
RP- I'd C
/ /	OH
V.-PR
l-p
RP I'd
<'• /
k-pr2
6
.pr2
= c;
011 -h2o
Oil
2+
/'"">p^
RP—Pd—C-O
< /
X-PR2
(10)
the rate determining step is the reaction of a Pd(I) intermediate with CO, (reaction 9). At low acid
concentrations, the rate determining step is the cleavage of the carbon oxygen bond in a protonated
hydroxy carbonyl intermediate, 6 (reaction 10). These studies suggested that the negative charge
which develops on the oxygen atoms of bound carbon dioxide in intermediates such as 4 could be
stabilized by interaction with a second metal atom and enhance the catalytic rate. The bimetallic
complex 8 was prepared to test this hypothesis. Studies of this complex indicate that the second
palladium atom of the catalyst is involved in activation of C02, and the catalytic rate is greater than
3x 104 [24], Unfortunately the rate of decomposition is also very rapid and the turnover number
for this catalyst is approximately 10. Current research is directed at stabilizing this complex with
respect to its decomposition reaction.
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/--PR2
L-Pd"NCCH3
41
-PR2
NCCH3
PR2
8
SUMMARY AND CONCLUSIONS
Because it is potentially a single step process, the direct electrochemical reduction of C02
represents an attractive route to liquid fuels. In this paper we have tried to outline some of the
requirements that should be considered in such a scheme. There are a number of energy sources that
could be used to supply the electricity needed for such an electrochemical process. One of these,
photovoltaic production of electricity, was briefly discussed. Possible sources of C02 have also been
examined, and the use of waste C02 generated in the production of fuels from biomass appears to be
an attractive source. In addition to electricity and C02, the conversion of CO. to liquid fuels will
require very stable catalysts with low overpotentials, high catalytic rates, and high selectivity. Ideally,
the catalysts should be capable of functioning within 0.1 V of the thermodynamic potential for the
overall energy conversion process to be efficient. Catalysts that are capable of supporting current
densities of at least 0.1 A/cm2 will be required. For homogeneous catalysts this translates into second
order rate constants between 10* and 105	If relatively expensive catalysts are used or catalysts
based on metals of limited supply are used, then turnover numbers on the order of 10* will need to be
achieved. Finally, the current efficiency (the fraction of the current utilized to produce the desired
fuel) will need to exceed 90%. These numbers are necessarily not firm numbers, because situations
can be found in which such stringent conditions might not need to be met. However, they provide
useful goals, and a catalyst possessing all of these characteristics would certainly provide an attractive
pathway for the conversion of C03 and electricity into fuels.
The status of various catalytic processes has been briefly reviewed in light of the requirements
outlined above. At the present time there is no catalyst that possesses all of the necessary properties.
On the other hand a great deal of progress has been made in this area over the past 10 years, and there
is reason for optimism that such catalysts can be developed. If all of the currently available catalysts
are considered, each of the requirements have been met by at least some catalysts. What remains to
be achieved is the incorporation of all of the desirable features into a single catalyst.
The author would like to acknowledge the financial support of the United States Department of
Energy, Basic Energy Sciences Division, Office of Energy Research, and the United States
Department of Energy Biofuels Systems Division as part of the Biofuels Program.
ACKNOWLEDGEMENT
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This paper has been reviewed in accordance with the U.S. Environmental
Protection Agency's peer and administrative review policies and approved
for presentation and publication.
THE CARNOL PROCESS FOR C02 MITIGATION
FROM POWER PLANTS AND THE TRANSPORTATION SECTOR
Meyer Steinberg
Brookhaven National Laboratory
Upton, NY 11973
ABSTRACT
A carbon dioxide (CCb) mitigation process is developed which converts waste CO2. primarily recovered
front coal-fired power plant slack gases with natural gas, to produce methanol (MeOHi as a liquid fuel and coproduct
carbon as a materials commodity. The Carnol process chemistry consists of methane decomposition to produce
hydrogen (II2) which is catalytically reacted with the recovered waste C02 to produce methanol. The carbon is either
stored or sold as a materials commodity. A process design is modelled, and mass and energy balances are presented
as a function of reactor pressure and temperature conditions. The Carnol process is a viable alternative to
sequestering CO2 in the ocean for purposes of reducing CO2 emissions from coal burning power plants. Over 90%
of the C02 from the coal burning plant is used in the process which results in a net CO? emission reduction of over
90% compared to that obtained for conventional methanol production by steam reforming of methane. Methanol, as
an alternative liquid fuel for automotive engines and for fuel cells, achieves additional CO2 emission reduction
benefits. The economics of the process is greatly enhanced when carbon can be sold as a materials commodity.
Improved process design and economics could possibly be achieved by developing a molten metal (tin) methane
decomposition reactor and a liquid phase, slurry catalyst, methanol synthesis reactor directly using the solvent
saturated with CCb scrubbed from the power plant stack gases. The application of COo mitigation technologies,
such as the Carnol process, depends to some extent, on how serious the country and the world takes the global
greenhouse gas warming problem.
I. INTRODUCTION
The evidence for greenhouse gas COj warming causing global climate change is continuing to mount, and
international agreements are being sought to limit CO2 emissions 0). The C02 emissions are primarily due to
fossil fuel combustion (principally coal, oil, and gas) in the industrial, commercial, and transportation sectors.
Although much effort in the U.S. has gone into the science of climate change, relatively little effort has been
expended for technologies that mitigate greenhouse gas emissions. Improvement in efficiency of energy production
and utilization is recognized as a cost effective method for reducing CO2 emission to a limited degree1-2). Fuel
substitution, utilizing more natural gas and oil versus coal, is recognized to further reduce C02 emission. The use
of biomass for energy production is also effective in COi reduction. A more aggressive manner for reducing CO2
emissions is the removal, recovery, and disposal of CO2 from central power plants, which primarily burn coal, A
fair amount of research has gone into the disposal and sequestering of 002 In the ocean and in depleted gas wells<3;.
However, C02 sequestration presents some formidable technical and economic problems. Much less effort has gone
into preeombustion fuel processing to significantly reduce C02 emission. Coal gasification combined cycle is one
limited step in that direction but still requires C02 sequestration ''•*). The concept of extraction and disposal of
carbon from fossil fuels and utilization of the Hi enriched fractions has been introduced with the idea that carbon is
much less difficult to store and sequester than CO.>W. The coprocessing of fossil fuels with biomtLSs by the
Hvdrocarb process^), producing methanol as a liquefied fuel, can achieve zero CO2 emission. The use of methanol
as an efficient automotive fuel can further reduce CO? emission from the transportation sector16). To maximize
methanol production and reduce development effort, the Hynol process which coprocesses biomass with natural gas
has been introduced*7) and avoids carbon sequestration while still obtaining significant COo emission reduction in a
3-S6

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cost effective manner. Fn this paper we describe and develop an alternative process which converts waste COi.
primarily recovered from coal-fired power plant suick gases, with natural gas to pnxiuce methanol as a liquid fuel and
carbon as a storable materials commodity eoproduct.
II. THE CARNOL PROCESS DESCRIPTION
The Carnol process grew out of a preliminary investigation of alternative processes for using CCV*). The
Carnol process relies on two basic chemical reactions: the thermal decomposition of methane and the catalytic
synthesis of methanol from II2 with COo
Thus 1 mole of methanol is produced from the utilization of I mole of CO2 which results in a net zero
CO2 emission when the methanol is burned. It takes 1.5 moles of CII4 to produce 1 mole of methanol or to react
with I mole of CO> by means of H2. The COi mitigation comes about by removing 1 mole of CO2 from power
plant stack gas (primarily coal fired) and producing but not burning the 1,5 moles of carbon per mole of methanol
produced.
Both reactions are known to lake place and have been practiced in different forms on a commercial,scale.
Methane decomposition to form carbon black is known as the Thermal Black process1^). The Ho is not recovered in
this process but is used as 1'uel. l;rom an energy point of view the Thermal Black process as commercially practiced
is very inefficient. A continuous catalytic methane cracking process called Hypro has been operated for Hi
production for hydrocracking oil in a refinery; however, in this case llie carbon was not recovered but was used as
fuel in the process('3».
The catalytic methanol synthesis from CO2 and H2 has also been practiced commercially; however, only 011
a limited scale, mainly because of the lack of cost effective CO2 feedstock^1'). Most methanol produced currently is
made by the catalytic synthesis of" CO and H2 which is produced by the steam reforming of natural gas^12'. There is
no reduction in CO2 emission by the use of the conventional methanol synthesis process using natural gas. In fact
when coal is used to produce the synthesis gas, there is a large increase in C02 emission.
The reasons that the Carnal process can he considered as a technically feasible and potentially cost effective
means for COt emission reduction are:
1.	Much chemical engineering development effort has recently gone into removal and recovery ofC(>2 from
power plant stack gases. Through the use of hindered amine absorption solvents, the energy requirement for
CCb removal and recovery has been significantly reduced'13).
2.	In principle, production by methane decomposition requires the least amount of energy compared to
other means of H2 production, such as steam reforming of methane and electrolysis of water< '^j. It only
takes IK kcal to decompose 1 mole of methane. Thus the production of 1 mole of requires only 5% of
the energy of combustion of natural gas. The kinetics of methane decomposition has been further
studied1'15) and has become better understood. High surface area carbon itself can act as an autocatalyst for
improving rates of decomposition at lower temperatures,.
Methane decomposition:
Methanol synthesis:
3CH4 = 3C + 6H2
2CO? + 61I2 = 2CH;
-------
3.	Much catalyst development work has lately gone ink) the synthesis of methanol from CO? and H2 resulting
in the development of improved catalysts * "»>.
4.	Methanol as an alternative fuel has a number of benefits: (1) it is a liquid fuel which can be used on a large
scale, (2) it can be transported and stored in accordance with the present infrastructure, (3) it can be used in
stationary and automotive engines as a substitute for petroleum based fuel, thus reducing imports and
improving the balance of payments, (4) when used in internal combustion (1C) engines, it is 30% more
efficient than gasoline which results in lower CO2 emission<0 in the transportation sector, and (5) it has
potential as an ideal fuel supply for efficient fuel cell power systems now underdevelopment.
5.	The Carnol process converts CO2 from power plant stacks to another useful fuel product and thus the
carbon from ihe power plant is essentially used twice. Furthermore, the methanol fuel can obtain
additional CO2 reduction when used in the dispersed automotive sector of the economy. COt emission
from automotive engines emits about 30% of the total emission of CO2 in the U.S. which is about the
same quantity of CO? emitted from central power plant stacks.
6.	It is possible to obtain low net CO? emission without the use of biomass. Instead of using waste CO>
from the atmosphere through biomass. Carnol uses waste CO2 directly from coal burning power plant
stacks.
7.	It is possible to consider the large scale application of Carnol because, next to coal, natural gas is
alHindautly available at low cost.
8.	Because llie potential production of carbon from the Carnol process applied to a 600 MW coal-fired plant
can equal the current market for carbon of 2 million tons/year in the U.S.. new markets for low cost carbon
must be made available iis an alternative to sequestering the carbon produced.
Based on thermodynamic principles, a firsi order simplified analysis of Carnol can be made using the
simplified two reactor flow diagram shown in Figure 1 and given in Table l(s>. H2 is used to provide the
endothermic heat of reaction (by indirect heat transfer) for the thermal decomposition of methane so as to obtain zero
CCh emission. The catalytic CO2/H2 reaction for methanol synthesis is exothermic and can produce some process
steam. Table 1 indicates that there is a 61% reduction in methanol yield by the Carnol process compared to the
conventional methanol process by steam reforming of methane using the same simplified procedure. Howevet, the
CO? emission is completely eliminated compared to conventional methanol production. Although (he [hernial
efficiency is 49.7% compared to 81.5%t'2> by the conventional process, there is available a significant quantity of
carbon coproduct which can be sold as a useful material on the commodity market to offset methanol costs in
competing with conventional methanol cost. Thus, thermal efficiency is not the only criterion by which to judge
the Camol process.
III. CARNOL PROCESS DESIGN
A process design and analysis has been made taking into account process temperature and pressure
conditions. A computer simulation program was used to make a detailed mass and energy balance. The assumptions
in the model are:
1.	Close approach to equilibrium is assumed in the methane decomposition reactor (MDR) and the methanol
synthesis reactor (MSR). The equilibrium data for methane decomposition arc graphically shown in Figure
2.
2.	A fluidized bed MDR is assumed using an indirectly heated circulating alumina Meat transport system. The
rate of methane thermal decomposition is adequate, for a reasonable reactor design, at temperatures of ROO'C
and above.1 ^).
3.	The MSR is a conventional Imperial Chemical Industries, Inc. (ICD type gas-phase methanol catalytic
converter operating at 50 atm pressure and 260*C with a 4 to 1 recycle ratio to achieve close 10 100%
conversion of the CO? feed to the MSR system.
3-88

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4.	A multistage compressor increases the pressure of the process gas from the MDR to the MSR. The
compressor is driven by steam generated from the MDR combuslor exhaust gas.
5.	A eondenscr-fractionator separates the product methanol from the water, ami ihe exothermic energy from the
MSR provides ihe steam for the fractionator.
6.	Residual gas from the MSR is recycled to the MDR for either process gas or as fuel in the eombuslur.
7.	CO2 is supplied as gas at 1 aim from the power plant stack gas recovery system.
A number of recycled and heat transfer configurations and process variables were explored. Table 2 gives
the results of 11 computer runs for the process flow sheet configuration shown in Figure 3 (designated as Carnol HI)
varying the MDR pressure and temperature from 1 to 50 atm and the temperature from 800 to 1100'C, respectively.
Increasing temperature in the MDR decreases CO2 emission, and increasing pressure in the MDR increases CO2
emission. Decreasing pressure in the MSR also increases CO? emission. Table 2 indicates that, at 1 atm pressure
in the MDR and temperatures from 800 to 1100CC, the yield (thermal efficiency) of methanol remains at 41.1%
while the CO? emission is reduced by 87% and higher compared to the combustion of methanol produced by the
conventional steam reforming process. From a materials point of view, temperatures on the order of 800 to 900°C
for the MDR arc preferable. The How sheet of Figure 3 is based on an MDR temperature of 8U0'C. A summary of
the mass and energy balances lor Carnol III is given in Table 3 and the stream compositions in Figure 3, The
decrease in thermal efficiency from the simplified analysis of 49.7% reflects the inefficiencies when taking into
account detailed mass and energy balances.
The CO2 feed to the Carnol process is provided by removal and recovery from coal-fired power plant slack
gases by a monoethanolamine (MEA) solvent absorption stripping system. The amine system has been used for
COi removal and recovery from process gases in ammonia and methanol plants in the U.S. for a number of decades.
Recently published papers from Japan<13> have shown that hindered amine solvents and improved absorption column
packing can decrease the pressure drop across the column, and that an integrated system, with the power plant, has
decreased energy requirements so that there is only an 8% loss in power front a coal burning plant when recovering
90% or better of the COj from its stack gases.
IV. PRELIMINARY ECONOMIC ANALYSIS
The assumptions made are:
1.	CO2 is removed and recovered from a 600 MW(e) coal burning plant (40% efficiency) using amine solvent
at 90% CO7 recovery, 90% plant factor, and 10% additional capacity to make up for the loss of power plant
capacity as a result of the removal and recovery of CO2.
215 lb	s /v 8500Btu	hr ton	rt
CO., rate - - 	r x 6 x 10' kW (e) x	x 7884 — x	= 4.34 x 10 T/ yr
2	MMBtu coal	kW(e)	yr 20001b
The Carnol plant capacities arc shown at the bottom of Table 4 and require 400,000 MSC'F/D of natural
gas. The methanol production rate is 8460 T/D or 61,100 bbl/D and the carbon produced is 5800 T/D.
2.	Since, the Carnol plant has two reaction steps (MDR and MSR) and the conventional plant also has two
steps (steam reforming of methane and methanol synthesis), the capital investment is based on an
equivalent conventional methanol world size plant estimated at $ 100,000/ton meihanol/day<'7'. Thus, the
total investment is $100,000 x 8460 T/D = $846x 1(X'. Production cost is estimated based on factors of
capital investment as follows: 19% for financing (depreciation & interest), 1% for labor, 3% for
maintenance, and 2% for power and miscellaneous, resulting in a total of 25% of the capital investment on
an annual basis for Ihe production cost.
3.	Natural gas prices are assumed to vary between $2 and S3/MSCF ($95 to $142/ton). Note that natural gas
prices in the II.S. were as low as S1.50/MSCF ($7 l/ton) in 1994.
4.	The carbon is assumed to be stored at $HVton. Carbon can also result in income since it has a market in
3-89

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tires, pigments, newsprint inks, etc. Depending on grade, carbon can sell for $100 10 $1000/u>n. In Table
4, carbon price balanced production cost a: less than $20/ton.
5,	The cost of CO? to Carnol recovered from the power plant can be a highly variable quantity depending on
whether there is a carbon tax, in which case Carnol can charge the power plant for disposing of the COt.
At full cost recovery, it is estimated that S5/ton would cover the cost of COj recovery, assuming 8%
reduction in power plant output charged at $0 06/kWh(e). O'.hcr COi cost charges were also assumed
varying from zero to 5108/ton as the market income of methanol varied.
6.	The market price of methanol has been historically around S0.45/gal ($ 136/ton) depending on stable natural
gas feed stock costs. Recently, the methanol market price increased to $l,30/gal ($39-1/ton) due to a supply
shortage in its use for production of methyl tertiary butyl ether (MTBIl) mandated as a gasoline oxygenation
agent <1 s). This huge increase in price has a profound effect on the economics of the Carnol process.
However, as soon as new methanol capacity comes or. line in the next several years, it is expected that the
price will drop back to historical levelsC*-1. At $0.45/gal. methanol production cost competes with
gasoline at S0.69/gal production cost based 011 a 30% improvement in IC engine efficiency (1.54 gaJ
methanol is equivalent to I gal gasoline)'6). No credit is taken in this paper for the use of methanol as a
transportation fuel which would result in an additional 33% reduction in CO; emission compared to
gasoline.
In Table 4, production cost factors were equated to income factors and the CO;> credit was determined in the
last column and evaluated as the figure of merit for the process. The conclusions drawn from this analysis are:
1.	When operating the MDR at 900"C and above and the MSR at 50 atm, the COi emission reduction is
greater than 90% compared to CO2 emission from methanol production by the conventional process.
2.	With no cost for feedstock COi to Carnol, naturai gas at $2/MSCF. no credit for carbon, and methanol at
$0.45/gallon, the cos: of reducing CO2 emission is S25/ton (listed as negative credit). This is less than the
average International Energy Agency (IEA) estimate for removal, recovery, and sequestering C(>2 in the
ocean at $37/ton neglecting transportation (pipelining) costs to the ocean. At S3/MSCF lor natural gas.
the CO; reduction cost using Carnol increases 10 $55/to:» which is the upper limit for ocean disposal of
CO-; neglecting pipelining to the ocean.
3.	By selling the carbon as a commodity at S58 and Si26/ton when natural gas costs $2 and S3/MSCF,
respectively, the CO? reduction cost is reduced to zero. Since the carbon is very pure, this carbon price of
$0.06/lb or less would have an easy market to compete with current prices of carbon black of up ro
$0.5()/lb. The U.S. market lor tire carbon amounts to 2 x 106 tons/yr and there are other uses for carbon at
a low cost price, for example as a filler in construction materials.
4.	If the power plant wants to recover its cost for recovering CO2 up to as high as JlO/ton, at a natural gas
cost of S3/MSCF, carbon produced by Carnol would have to sell for $ 170/ton ($0.085/lb) lo achieve zero
CO? reduction cost, which is still a very reasonable, possibility.
5.	If tlit- methanol can continue to demand Sl.30/gal, or almost 3 times the historical price, at $3/M.SCF for
natural gas and a CO-i feedstock cost charged by the power plant of $5/lon (recoverable cost), assuming no
carbon sales, a CO? credit of $i 03/ton for reducing COi emission can be realized On the other hand, if the
COt credit for reducing emissions is reduced to zero, the power plant could charge as much as S108/ton lor
feeding its CO; to (he Carnol plant. Obviously the charges and profits could be negotiated between the
power plant and the Carnol plant.
V. ADVANCED CARNOL VI PROCESS
Two recent developments have been uncovered that could significantly improve the basic Carnol process.
One is methane decomposition and the other is methanol synthesis.
3-90

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1.	The design of an efficient MDR can be difficult because high temperature energy must be provided to
decompose the methane, and the particulate carbon must be recovered and removed in a continuous manner.
As mentioned earlier, intermittent reheat batch reactors and fluidized bed reactors have their drawbacks.
Recently, we have found that molten metal technology is being applied to decompose liquid and solid
carbonaceous waste material to produce simple gaseous compounds using a molten iron (Fe) bath at
temperatures from MOO to 1650'C
-------
for CO2 from Ihe |iower plant, is 13.0 kg CO^GJ (30.2 lb CO^MMBtu) which represents an 83%
reduction in CO? emission compared to the production of methanol by conventional process; i.e., the steam
reforming of natural gas. When methanol is used in IC engines, an additional 33% reduction in CCh
emission is obtained compared to the use of gasoline as automotive fuel.
VI. CONCLUSION
The Ciirnol process, which produces methanol as a liquid fuel, can effectuate a very significant net decrease
in CO2 emission from coal-fired power plants. The economic value is significantly improved when the coproduct
carbon can be sold as a materials commodity. Two research and development efforts which can significantly improve
the process are (1) developing a molten metal methane decomposition reactor and (2) developing a liquid-phase MEA
slurry catalyst reactor for directly converting CO2 scrubbed from power plaru fuel gas with I It from methane
decomposition to produce methanol as a liquid fuel for the automotive industry. Further development ol the Carnol
process is required to realize the full benefits of the process. Consideration of the applicability of the Carnol process
depends, to some extent, on Isow serious the country and the world take the global greenhouse gas warming problem
and CO2 mitigation technologies.
VII. METRIC CONVERSION FACTORS
Nonmetric
Times
Yields Metric
atni
101,325
Pa
bbl
I5v
I
Btu
1,054
J
cal
4.184
J
gal
3.785
1
lb
0.4536
kg
MSCF
28,320
std m3
Ion
0.9072
tonne
3-92

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REFERENCES
PI W.K. Stevens, 'Scientists Warn of Efiect of Rise in Greenhouse Gases." New Yotk Times, The
Environment. p.C4 (April 11, 1995).
[2]	E. Mills, D. Wilson, T. Johanssen, "Getting Started. No Regrets .Strategics lor Reducing Greenhouse Gas
Emissions," Energy Policy, July/August (1991).
[3]	U.S. Department of Energy, "The Capture, Utilization and Disposal of COz from Fossil Fuel Hi red Power
Plants.1' Vols. I and II, Washington, D.C. (1993).
(4j M. Steinberg, "Biomass and Hydrocarb Technology for Removal of Atmospheric COi.' BNL 14410,
Brookhaven National Laboratory, Upton, NY (March 1990),
[5)	M. Steinberg, Y. Dong, R.H. Rorgwardt," The Coprocessing of Fossil Fuels and Biomass for COi
Emission Reduction in the Transportation Sector," Energy Con vers. Mgmt. 34- No. 9-11, p. 1015-1022
(1993).
[6]	GPA Report, "An Analysis of the Economic and Environmental Effects of Methanol as an Automotive
Fuel," EPA Report No. 0730 (NT1S PB90-225806), Motor Vehicle Emissions Laboratory, Ann Arbor, MI
(September 1989).
[71 M. Steinberg, Y. Dong, "Hynol, an Economic Process for Methanol Production from Biomass and Natural
Gas with Reduced CO2 Emission," BNI.-49733, Brookhaven National Laboratory, Upton. NY (October
1993).
[8] M. Steinberg, Y. Dong, "The Carnol Process for Methanol Production and Utilization with Reduced CCb
Emissions," BNL-60575, Brookhaven National laboratory, Upton, NY (June 1994).
[9J J P. Donnet, A. Voet, Carbon Black, pp. 16-18, Marcel Dekker, New York, NY (1976).
[10]	"Hvpro Process Cleaves Hydrogen from Hydrocarbon." C-hetn. Eng. 69, p. 90-91 (1962).
[11]	Faith. Keyes. Clarke, Industrial Chemicals 4th Edition, p.526, John Wiley and Sons, New York, NY
(1975).
[12]	L.E. Wade ct al., "MethanolKirk Olhrner Encyclopedia of Chemical Technology 15. 3rd Hd., p. 398-
415, WiIey -I nterscicncc and Sons, New York, NY (1981).
[13]	Sudact al., 'Development of Fuel Gas Carbon Dioxide Recovery Technology," Chapter in Carbon Dioxide
Chemistry: Environmental Issues. Ed. by Jon Paul and Claire Marie Pradier, p. 222-35, The Royal Society
of Chemistry, Sweden (1994).
[14]	M. Steinberg, "The Hy-C Process (Thermal Decomposition of Natural Gas) Potentially the Lowest Cost
Source of Hydrogen with the I .east COi Emission." BNL-61364, Brookhaven National laboratory, Upton,
.NY (December 1994).
[15]	A, Kobayashi, M. Steinberg, "The Thermal Decomposition of Methane," BNL-47159, Brookhaven
National Laboratory, Upton, NY (January 1992).
LI6] H. Arakawa et al., "Effective Conversion of CCb to Methanol and Dimethyl Ether by Catalytic
Hydrogenation Over Heterogeneous Catalysts," International Conference on Carbor. Dioxide Utilization, p.
95-102, University of Bari, Italy (Sept. 26-30. 1993).
[17]	J. Korchnak, John Brown Co. A/E Houston. Texas. Personal Communication (1994).
[18]	G. Peaff, "Methanol Transformation to Commodity Status Stretchers Supply," Chcm. & ling. News. p.
13-15 (October 24, 1994).
[19]	P. Nahass, P.A. Moise, C.A. Chanenchuk, "Quantum CEP for Mixed Waste Processing," Molten Metal
Technology, Inc., Waltham, MA (1994).
[20]	S. Lee, Methanol Synthesis Technology, p. 198-224. CRC Press, Inc. Boca Raton, FL (1990).
121] S. Okvama, ' Evaluation of Low Temperature Methanol Synthesis in the Liquid Phase," ACS Division of
Fuel Chemistry. 2005'1 ACS National Meeting 39 No. 4, p. 11 82-6, Washington. D.C. (Aug. 20-25,
1994).
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Table 1
SIMPLIFIED THERMODYNAMIC ANALYSIS OF CARNOL PROCESS
Unit Operations
Reaction
Enthalpy, AH
Decomposition:
MeOH Synthesis:
3CH, - 3 C + 6H2
2COz + 6H2 = 2CH3OH + 2H,0
+ 18 kcal/mol CH4
22 kcal/mol MeOH
Combustion:
H, + Vi02 = H,0
~ 68 kcal/mol H,
Camol Process Analysis
Moles CH< to produce 2 moles MeOH
Moles CH< to produce combustion H2 for heat transfer to CH4
Moles MeOH per total mole CH4
(ligher heat of combustion of MeOH
Higher heat of combustion of CH4
Carnol MeOH thermal efficiency
Carbon produced per mol MeOH
2.00/3.455
3.455/2.0
= 3.000
= 0.455
= 0.579
= 182,000 kcal/Mol
= 212,000 kcal/Mol
= 49.7%
= 1.728
C02 emission=~2 mol C02 (from stack gas) +2 mol C02 from MeOH combustion = 0
Conventional Process Analysis02'
Moles MeOH produced per mol CH4
Thermal efficiency
Moles CO, produced per mol C1I4
Camol process CO? reduction
Yield of Carnol MeOH to conventional
= 0.95
- 81.5%
= 1.05
= 100%
= 61%
3-94

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Table 2
METHANOL PRODUCTION EFFICIENCY AND CO, EMISSION REDUCTION
AS A FUNCTION OF PROCESS REACTOR CONDITIONS
CARNOL III+ PROCESS CONFIGURATION FOR
METHANOL PRODUCTION FROM C02 AND METHANE
Methane Feed = 100 kg
Computer
Run No.
MDR
P atm/T°C**
MSR
P atm/T°C **
CO,
Feed
Stock
kg
MeOH
Thermal
Eff.
%
MeOH
Carbon
Eff.
%
CO,
Emission
lb**
MM Btu**
IIHV MeOH
C02*
Emission
Reduction
1
1/800
50/260
156.6
41.1
50.3
22.7
87.4
5
1/900
50/260
147.1
41.1
50.4
10.2
94.3
6
1/1000
50/260
143.1
41.1
50.4
5.0
98.2
10
1/1100
50/260
142.5
41.5
50.8
2.7
98.5
11
1/800
30/260
163.1
27.7
34.0
33.7
81.3

1/800
30/120
150.1
44.3
54.2
21.1
88.3
3
1/800
6.8/120
163.1
40.7
49.9
23.0
87.3
4
10/900
50/260
133.3
28.8
35.3
99.3
44.8
8
10/900
10/120
133.3
31.5
38.6
90.9
49.5
7
30/100
50/260
122.2
30.3
145
Increase in Emission
9
10/1000
10/260
- NO BALANCE OBTAINED -
*	Emission reduction is compared to production of methanol by conventional steam reforming of natural gas which produces 180 lb
CO,/MM Btu of methanol energy (HHV). Thermal efficiency for a conventional steam reforming plant for methanol production=64% .
*	l atm - 101 kPa, 1 lb = C.454 kg, and 1 Btu = 1.055 kJ.

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Table 3
CARNOL PROCESS III DESIGN
PROCESS SIMULATION - MASS AND ENERGY BALANCES
UNIT	CARNOL III t
H2 - RICH GAS FUEL FOR MDR
MDR
Pressure, atm	1
Temperture, °C	800
CH4 Feedstock, kg	100
Preheat Temp, °C	640
CII4 Fuel for MDR, kg	0
CH4 Conversion, %	91.9
Carbon Produced, kg	68.8
I leat Load, kcal	82,091
Purge Gas for Fuel, kmol	2.4
MSE
Pressure, atm	50
Temp., °C	260
C02 Feedstock, kg	156.6
C02 Conversion, %	90.9
Methanol Produced, kg	100.6
Water Condensed , kg	58.7
Energy for Gas Compression to MSR
Energy, kcal	75,114
1 erlormance
Ratio, MeOH/'CH4, kg/kg	1.01
Carbon Efficiency MeOH, %	50.3
Thermal Efficiency MeOH, %	41.1
Thermal Efficiency C t MeOH, %	81.8
CO, Emission, Ih/'MM Btu	22.7
C02 Emission, kg/GJ	9.8
3-96

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Table 4
PRELIMINARY CARNOL PROCESS ECONOMICS
Costs shown in SlO'/yr and (Unit Costs)
Investabie Capital Cost (IC) = S8.46 x 10'*
PRODUCTION COST FACTORS	=	INCOME FACTORS
0.25 IC
Natural Gas
C Storage
C02 Cost
C Income
MeOH Income
C03 Credit
SI 0
yr
S108
yr
1 S
$10*
yr
' S
V ton)
510s
yr
I ton>
$10'
yr
1 s
\ ton!
ml
yr
$
{gal}
$10'
yr
/ \
$
I !on
[ MSCF /
2.12
2.60
(S2)
0.19
(10)
0
(0)
0
(0)
3.78
(0.45)
-1.10
(-25)
2.12
3.90
(S3)
0.19
(10)
0
(0)
0
(0)
3.78
(0.45)
-2.40
(-55)
2.12
2.60
(S2)
0.19
(10)
0
(0)
1.10
(58)
3.78
(0.45)
0
(0)
2.12
3.90
(S3)
0.19
(10)
0
(0)
2.18
(126)
3.78
(0.45)
0
(0)
2.12
2.60
(52)
0.19
(10)
0.42
(10)
0
(0)
3.78
(0.45)
-1.53
(-35)
2.12
3.90
(S3)
0.19
(10)
0.84
(20)
3.25
(170)
3.78
(0.45)
0
(0)
2.12
3.90
(S3)
0.19
(10)
0.23
(5)
0
(0)
10.95
(130)
+4.47
+103
2.12
3.90
(S3)
0.19
(10)
0.23
(5)
0
(0)
6.48
(0.77)
0
(0)
2.12
3.90
(S3)
0.19
(10)
4.69
(108)
0
(0)
10.95
(1.30)
0
(0)
* Based on the following plant capacities:
JO C05 rate, 90% recovered from a 600 MW(e) net [650 MW(e) gross] coal-fired power plant — 4.34 x 105 T/yr
2)	CH, rate = 2.77 x 106 T/yr = 400,000 MSCF/D
3)	McOH produced = 2.78 x 106 T/yr = 61,100 bbl/D = 8460 T/D
4)	Carbou produced = 1.91 x 106 T/yr = 5800 T/D

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Table 5
METHANOL SYNTHESIS EQUILIBRIUM
Input: Hj 3 moles
C02 1 mole
P (atm)
30
30
50
50
T (°C)
120
260
120
260
CO (mole)
0.0007
0.1365
0.0004
0.1089
CO, (mole)
0.4459
0.7686
0.3285
0.6865
H20 (mole)
0.5541
0.2314
0.6715
0.3135
Hz (mole)
1.3391
2.5787
0.9862
2.2773
MeOH (mole)
0.5534
0.0949
0.6711
0.2046
Total (mole)
2.8932
3.8101
2.6577
3.5908
3-98

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Fig. 1
Simplified Camol Process for Producing Methanol from Natural Gas
and C02 for Zero' C02 Emission
Mass Flows Are In Moles
Flue Gas
0.46 H2C
1.73
Power Plant
Stack Gas
C02
1.00
H20
1.00
Air

-------
Hg. z
I
C
O
ts
cd
LL
X
o
>-
EQUILIBRIUM DATA
CH4 = C + 2H2
200 400 600
800 100Q 1200
TEMPERATURE - deqrees Ceritiarade

-------
Fig. 3
CO2 Mitigation Technology Carnol-lll + Process
Steam
1 atm
"2.8 kmol
Combustor
I
; Alumina or Hex.
MDR
1 atm,800t
640 °C
0
¦0
0.2 kmol
260 °C
	^ Carbon to Storage
68.8 kg
CH4 Feedstock
100 kg, 20°C
2.86 kmol
188°C
Compressor o-
59.5~kmoT~*" 197°C
CO2 Feedstock From
Power Plant Flue Gas
156 6 kg. 20 °C
Cartion Efficiency 50.3%
Thermal Efficiency 41.1%
COz Emission 22.7 lb /MMBtu
Basis 100 kg CH4 Feed
MSR
50 atm, 260 °C
200 °C
"0
138°C
2 6 kmol
—[XI -
59.5 kmol t
Circulator
Condenser
50 atm, 50 °C
Gas Stream
A
B
C
Rate-fonol
12.0
70.4
64.0
Temp-uC
800
260
50
Comp. mol%



CO

3.35
3.68
co2

12.86
14.15
ch4
4.25
17.34
19.08
h2o

4 76
0.14
«2
95.75-
56.67
62.34
MeOH

5.02
0.60
MeOH H?0
101kg 58 7 kg
3-101

-------
Fig. 4
C02 - H20 - Amine Phase Equilibrium
For Liquid Phase Methanol Synthesis
(Taken From Suda et al.,Nov. 1994, Sweden)
3-102

-------
Fig. 5
Carnol VI Process tor CO2 IVIitigation Technology
Combining CO2 Recovery From Power Plants with Liquid Metal Methane Decomposition
and Liquid-Phase Methanol Synthesis
Exhaust Gas
(£0% CO2
Recovery)
PP Flue Gas
MeOK
H20.H2, CW\Ccr£. Recycle
Flue Gas
30 atm
CH
CH<
Nat. Gas
Feedstock
MEA Scrubber
wiiri MeOH Catalyst Slurry
1 atm-40 t
Liquid Phase
Methanol
Converter
30 atm
120°C
MeOH-HzO
Fraciionator
30 atm
?$k- H?/CH4Sep.
Compressor
From 1-10 atm
to 30 atm
Voiter.-Metai Tin
Methane Decomp.
Reactor
1-10 atm
800"C - 900*0
Process Chemistry:
Feedstock
J	|—¦- Product
3/2 CH,, » 3/2 C ~ 3H2
3 m ~ CO? = CH1ON ~ HiO
c	C	1
I i
Flue Prccuct
Gas
Nat. Gas, Decomp.
MeOH Synthesis

-------
Fig. 6
Molten Metal Methane Decomposition Reactor For Carnol VI Process
Basis 1,0 fl-mol CH4 Process Gas
(Numbers shown without units are in moles)
boiler
700"C
Flue Gas
1.58
Gas Comp.
Hj - 2.00 - 90%
CH4-0.??-10%

CH4 1.0 Q-rnol
Feedstock
25"C7 5 aim
Pipeline Gas
Water
Cooled
Conveyor
Carbon
Product
0.15
Flue Gas
50'C
1.58
| H2 - 2.00
I	Compressor
PSA CH4/H2
Separator
and
Compressor
3-104

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SESSION IV: BIOMASS UTILIZATION
Sivan Kartha, Chairperson
4-A
DEMONSTRATION OF A 1 MWc BIOMASS POWER PLANT
Carol R. Purvis
U.S. Environmental Protection Agency
Air Pollution Prevention and Control Division
Research Triangle Park, NC 27711 U.S.A.
Patrick Myers
Research Triangle Institute
Research Triangle Park, NC 27709-2194 U.S.A.
Mounir Mazzawi
Mech-Chem Associates, Inc.
Norfolk, MA 02056 U.S.A.
ABSTRACT
The U.S. Environmental Protection Agency's (EPA's) National Risk Management
Research Laboratory (NRMRL) Air Pollution Prevention and Control Division (APPCD),
formerly EPA's Air and Energy Engineering Research Laboratory (AEERL), is cooperating with
the Research Triangle Institute (RTI) to demonstrate that converting wood energy to electrical
power results in waste utilization, pollution alleviation, and energy conservation.
The project is expected to demonstrate the technical, economic, and environmental
feasibility of an innovative energy conversion technology, producing approximately 1 MWe, at the
Marine Corps Base, Camp Lejeune, NC. Camp 1 .ejeune will supply wood waste for power plant
operation while minimizing transport and maximizing local waste resource utilization. The
technology for the process and the site at Camp Lejeune have been selected, design specifications
are presently underway, and installation, start-up, testing, and demonstration will soon follow.
This paper provides details of the status of this project.
"This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer
and administrative review policies and approved for presentation and publication."
INTRODUCTION
Utilizing biomass as a fuel for power generation will eliminate sulfur dioxide (SO,)
emissions, produce zero net gain of carbon dioxide (C02), reduce air toxic emissions, and help
solve waste disposal problems. Additional benefits from fueling a power generation system with
biomass are savings from avoiding transportation and tipping fees for disposal of biomass residues
4-1

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in a landfill, savings from decreasing or eliminating the purchase of fossil fuels and/or electricity,
possible tax credits, and energy security from using indigenous biomass for fuel. EPA biortiass
energy projects are intended to provide the impetus needed for the development of equipment,
design of systems, creation of markets, and promotion of exportable technologies.
The objective of this project is to demonstrate that an innovative energy conversion
technology fueled with biomass is technically, economically, and environmentally feasible for
Camp Lcjeune and other Department of Defense (DoD) installations, industrial sites, and
developed and developing countries. The approach has been to identify a site, the partners, and
the most viable technology, then design, build, and test the technology. The coordination
between DoD and the partners has been such that the design of the project is in the best interest of
Camp Lejeune. The technical risks have been minimized by the proper selection of technology
based on the available site, size of system, type of fuel, qualifications of operators, and lessons
learned by all cooperators.
Converting wood to power at military installations will result in waste utilization,
alleviation of pollution, and energy conservation. This is a real contribution toward meeting
Federal directives to stabilize C02 emissions at 1990 levels by the year 2000, and to reduce
Federal agencies' energy consumption to 20% below 1991 levels by the year 2000 (Executive
Order 12759). The project also has excellent potential for technology transfer to the commercial
sector and other public agencies which follows a trend of revived commercial interest in wood
energy and growth of independent power production and industry-site power plants.
DEMONSTRATION SITE AND FUEL
Tile Camp Lejeune Energy from Wood (CLEW) project is intended to demonstrate a
biomass-to-cncrgy conversion technology at a scale of approximately 1 MW of electrical output,
on the Marine Corps Base in North Carolina. Camp Lejeune is located in the Coastal Plain of
North Carolina and occupies approximately 153,000 acres (6.2 X 10Rm2). The Base has 45,000
active duty personnel, 4,500 civilian employees, and about 12,000 dependents. The Base utility is
about 30 to 40 MW, with peak summer demand reaching a maximum 70 MW. The 1 acre (4047
m2) site at the Camp Lejeune Piney Green Industrial Area has been selected for the project
facility. The site has easy access to all necessary utilities, is in close proximity to the landfill, and
is secluded from the main section of the Base.
The biomass fuel for the demonstration will be generated by activities on the Base. Over
22,000 tons per year (tpy) (19,958 metric tpy) of combined wood products and tree limbs are
available. Most of the waste is currcnily being landfillcd, and a waste recovery program is sought,
that will be of benefit to the Base. The waste will become the fuel for the demonstration and will
be delivered in chipped or hogged fuel-size to the demonstration site by Base operations. It is
estimated that up to 90% of this waste will be used for the demonstration plant. Fuel preparation
will include metal and other trash removal, and grinder operating conditions for optimum fuel
size.
4-2

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TECHNOLOGY
Mech-Chem Associates, Inc. of Norfolk, MA, in conjunction with Thermal Technologies,
Inc. (TTI) of Omaha, NE, was selected to provide the technology to be demonstrated. The
Mech-Chcm technology consists of an atmospheric fixed-bed down-draft gasifier, gas cleaning
components, and spark-ignited engines.
A down-draft gasifier is used to produce synthetic fuel gas. The synthesis gas exits the
gasifier and flows through a cyclone, heat exchangers, gas/liquid separators, and cartridge filters.
The suction in the system is created by passing the gas through a multistage centrifugal blower.
The blower discharges the gas into a spark-ignited and diesel engine-generator set.
DESIGN
Preliminary design for the system has been completed by Mech-Chem and RTI, and design
review is presently underway. The process flow diagram is shown in Figure 1. Considerations in
designing the overall process for the demonstration include fuel handling, fuel drying, reaction,
gas stream cleanup, fuel sampling, and the engine generator sets. RTI is performing the design on
fuel handling, fuel drying, and fuel sampling, while Mech-Chem is providing the design of the
reactor, gas stream cleanup, and engine generator sets.
The fuel drying for the process will be performed in a deep bed dryer. The chipped wood
fuel will be fed to the dryer by a walking floor trailer at a rate of approximately 2500 Ib/hr (1134
kg/hr). Hot engine exhaust at 400°F (204°C) will be used to dry the wood, and it will be pulled
through the bed at a rate of 5000 SCFM (2.45 m:7sec). The wet fuel at approximately 45%
moisture will be dried in the deep bed dryer to 10% moisture. Tests have been performed by RTI
to confirm the drying rate, retention time, and pressure drop associated with the deep bed dryer.
The hot exhaust will be pulled through the dryer by a 5 HP (3.7 kW) blower, and a cyclone will
separate fines entrained in the air stream leaving the dryer. The fuel will be metered by the dryer
as needed to keep the feed hopper full for the pyrolysis reactor. The fuel will be conveyed from
the hopper to a surge bin which directly feeds the pyrolysis reactor as indicated by the leveling
arm in the reactor.
Pyrolysis reactor PR-20 converts wood chip fuel into a low heat value gas. The wood
chip fuel is fed into the reactor by a surge hopper located at the top of the rector, and preheated
air for combustion is fed from heat exchanger HX-45. The preheated air that enters the reactor
will only partially combust the fuel. The heat from the combustion is transferred to the wood,
driving off the volatile gases by pyrolysis. The result of this pyrolysis is an activated carbon
"char" bed and a low heat value gas. The char is removed from the bottom of the reactor by a
screw conveyor and is collected in carbon hopper CH-40. The activated carbon is potentially a
saleable by-product of the system.
Cyclone CS-50 removes the particulates from the stream initially. The stream is then
cooled to I00°F (38°C) by heat exchangers HX-55 and HX-65, and liquids are separated out by
vertical liquid/gas separators LS-60 and LS-70. The 10 fim cartridge filters F-75 and F-76 further
4-3

-------
remove tars and particulates before the gas reaches blower B-80. The low heat value "syngas" is
pulled through the system by blower B-80. The final stage of gas cooling and cleanup includes
heat exchanger HX-85 and liquid separator LS-90 where the gas is dropped back to 100°F (38°C)
and final liquid separation takes place.
After all tars and particulates are sufficiently removed in the cleanup phase of the process,
the gas is monitored and fed to two engine-generator sets to produce 1 MW of electricity. The
gas is monitored continuously for constituents such as nitrogen, hydrogen, carbon monoxide,
carbon dioxide, and methane. The continuous monitoring of the gas stream will allow for overall
process analysis. The gas is finally fed to the two engines. One engine is a diesel compression
engine and the other a spark-ignited engine. The efficiency and reliability of the two engines will
be compared.
Design Tests
The gasification technology of Mech-Chern Associates is presently in operation at
Ellicottville Energy Plant in Ellicottville, NY. The design of this facility differs from the design of
the CLEW project in three ways: the facility is not operated continuously, it is manually operated,
and it is fueled with sawdust pellets. The CLEW project is to be operated continuously; it is to be
fully automated, utilizing a personal computer; and it is to be fueled with wood chipped with a tub
grinder. Despite the differences between the design of the Ellicottville Energy Plant and the
preliminary design of the CI J;W project, a test operation of the Ellicottville Energy Plant would
aid in the final design phase of the CLEW project.
RTI performed a test of the Ellicottville Energy Plant in June of 1995. Wood for the test
was obtained locally and processed through a tub grinder to match the charateristics of the wood
that will be used to fuel the CLEW project. The main objective of the test was to observe how
Mech-Chern's technology operates with the chipped wood typical of that from Camp Lejeune's
landfill, as opposed to pcllctizcd sawdust. Several modifications to the fuel handling system at the
facility were made due to the larger, less uniform chips, and a gas chromatograph was installed
upstream from the engines to continuously monitor the components of the syngas. However, the
gasification process and cleanup train was operated under normal conditions. The particular
points of interest for observation included the fuel composition and quality, the amount of tars
produced and their composition, the amount of water removed by the liquid separators, the char
quality, the pressure drop through the system, reactor temperatures, and overall system
performance.
PROJECT SCHEDULE
The cooperative agreement between EPA and RTI was signed on July 12, 1994, with a
project period of 3 years. The site was selected in the fall of 1994, and the technology was
selected in the winter of 1994. Agreements between RTI and TTI were signed, and system
design began in the spring of 1995. Site preparation at Camp Lejeune and equipment deliveries to
the site should begin in the summer of 1995. Installation should be completed in the winter of
1995. Testing and demonstration should be completed by summer of 1997.
4-4

-------
ACKNOWLEDGMENTS
This project became a reality due to initial funding from the Department of Defense's
(DoD's) Strategic Environmental Research and Development Program (SERDP), and funding
participation from the EPA's NRMRL, RTI, and North Carolina Department of Commerce's
Energy Division,

-------
FIGURE 1: PROCESS FLOW DIAGRAM
IJYEUIt D**C
WftCC DfWI
31 OQMCnM (GMKW1
is-n
f-n
w-n
fr-tt
«-4*
U-M
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WAT B»»CO (M/M)
UCWO aa*MWRMI
NUT OCCMMCaCR pai/ws)
UCMD S7NWKM
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a*i am
m auMi
hkat Dtcwoan
UCMD XPM7M

BSECM-CHEM
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¦MM*







RESEARCH TRIANGLE INSTT1VTI
IT""







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«¦ » no* h m. i
-« 1 1 TT-584-0IA
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1

-------
4-B
DEVELOPMENT OF A NEW GENERATION OF SMALL SCALE BIOMASS-FUELED
ELECTRIC GENERATING POWER PLANTS
Joe D. Craig
Cratcch, Inc.
P.O. Box 70
Tahoka, Texas 79373
Carol R. Purvis
U.S. Environmental Protection Agency
Air Pollution Prevention and Control Division
Research Triangle Park, North Carolina 27711
ABSTRACT
There exists a need by a large worldwide market for greatly improved small
scale (1 to 20 MWe per unit) biomass-fueled power plants. These power plants will
significantly increase the efficiency of generating electric power from wood and
bagasse as well as convert non-traditional fuel sources such as rice hulls, animal
manure, cotton gin trash, straws, and grasses to electricity. Advancing the technology
of biomass-fueled power plants will greatly expand the use of this environmentally
friendly sustainable 24 hr-per-day source of electrical power for industry and
communities worldwide. This paper briefly describes the status of a biomass-fueled
power plant under development by Cratech, Inc.
"This paper has been reviewed in accordance zvith the U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication."
INTRODUCTION
Responsibly using biomass as a fuel source in any power producing system
places the user in the natural biological cycle; therefore, the user can produce
sustainable power. A well managed and properly designed biomass power system
releases little or no unnatural substances into the environment. As is the case with
many natural biological systems, carbon dioxide will be produced but with zero net
increase in quantity. Advancing the technology of biomass-fueled power plants will
greatly expand the use of this environmentally friendly, sustainable source of electric
power for industry and communities worldwide.
4-7

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Biomass-fueled power plants have been serving industry for many years, and
providing 24 hour-per-day year-round on-site power in many areas of the world.
However, their effidency is low relative to what could be done with new technological
advances, and their use has been limited relative to the biomass resources available for
fuel. Most of these power plants have been placed in service by the wood products
industry where large quantities of fairly clean wood waste are available for use as fuel
to fire boilers. Sugarcane mills have also been fairly large users of biomass, in their
case bagasse, to fire boilers. Most of the bagasse-fueled power plants are very
inefficient at generating electric power which in the past was not of major concern;
however, due to increased demand for electric power in the areas growing sugarcane
and the pressure on mills to increase their energy efficiency, this is no longer
acceptable. Used under sustainable management practices, biomass such as sugarcane
leaves and trash, rice hulls, animal manure, cotton gin trash, cotton stalks, corn stalks,
straws, and grasses are viable sources of biomass for fueling power plants but generally
are not used due to technological limitations. There is great opportunity to increase the
efficiency of generating electrical power from currently used biomass fuel sources and
great opportunity to expand the types of biomass that could be used as fuel for
generating electrical power. Increased efficiency and greater fuel flexibility will allow
users to take advantage of the many benefits of biomass-derived electric power.
Increasing the efficiency of generating electrical power from biomass over that
currently available and increasing the type and amount of biomass fuels suitable for
use in biomass power plants, all at an economically competitive price, will require a
new generation of power plant that exploits recent advancements in several areas of
technology.
A very promising technological path for increasing the efficiency of biomass
power plants and greatly expanding the types of biomass that can be use as fuel is a
properly designed biomass-fueled iniegrated-gasifier gas turbine (BIGGT) power plant.
Figure 1 is a BIGGT power plant block flow diagram. This paper will briefly present
the market requirements, the technology to meet the requirements, a power plant
design, and a projected financial analysis of this type of power plant.
MARKET REQUIREMENTS
There is a need in the worldwide market for biomass power plants with the
following characteristics:
•	Size in units from 1 to 20 MWe.
•	Capable of using a large variety of biomass fuels without extensive
preprocessing.
•	Simple, reliable, durable, and easily maintained.
•	Minimal initial capital cost, low operating cost, and (therefore) minimal cost
of electricity.
•	Ash byproduct, no wastewater to treat.
4-8

-------
•	Exhaust gases meeting all air quality requirements.
•	Readily available and affordable parts and service.
TECHNOLOGY TO MEET THE MARKET REQUIREMENTS
Hie Cratech biomass power plant is being developed to meet these requirements
by integrating a gasifier with a gas turbine engine. The BIGGT system envisioned by
Cratech is shown by the schematic In Figure 2. Strictly from an academic point of view,
this is not the simplest of cycles nor the most efficient; however, given the numerous
tradeoffs that a design engineer must consider while at the same time boldly meeting
the market requirements, the BIGGT power system is considered to have great potential
to succeed in the market.
It is possible that, in the future, integrating a gasifier with a fuel cell can compete
with this system. Fuel cells can approach 50% simple cycle efficiency which is higher
than the simple cycle efficiency of gas turbines especially in small sizes. But the current
cost of fuel cells greatly outweighs their advantage in efficiency. Gas turbine engines
on the other hand have greatly improved in thermal efficiency during the past 15 years,
and their share of the cost of producing electricity is gradually dropping. This trend
will probably continue. Until the cost-to-benefit ratio of the fuel cell is favorable with
that of the gas turbine engine, the more competitive system for serving the biomass
power industry in the foreseeable future is the BIGGT.
POWER PLANT DESIGN
Several technical challenges must be overcome before economical small scale
BIGGT power plants become a commercial reality; however, much progress towards
this goal has been made during the past few years. The following is a brief discussion
of some major features of the Cratech system that are being developed to commercialize
this type of power plant and meet the market requirements. A system schematic is
shown in Figure 2.
This system is the initial feeding point for the biomass. The feed hoppers have
live bottoms capable of feeding most types of biomass. The biomass is fed to a size
reduction hammermill if required. The amount of size reduction should be kept to a
minimum. Size reduction will not be required for such feedstocks as sawdust, rice
hulls, cotton gin trash, nut shells, and bagasse. It would be required for large wood
chips. If moisture content is greater than 20%, drying will be a benefit; otherwise no
drying is required. The biomass is then pneumatically conveyed to the high pressure
feed vessel.
4-9

-------
The components of this system are critical, as they answer the question: How do
you economically feed bulky biomass into a pressure vessel? The major disadvantage
of the BIGGT concept over other biomass-to-electricity generating concepts (that do not
require feeding biomass under pressure) is this problem. A considerable amount of
thought has been put into the design of the biomass pressurization vessel. Its
outstanding features are its small valves for the biomass inlet and outlet and its large
storage volume required to minimize valve cycle times. This component together with
the meter vessel will provide a durable system for accurately and reliably feeding all
types of bulky biomass to the pressurized reactor vessel.
Pressurized Reactor Vessel
A small scale biomass power plant needs to be very fuel flexible because there is
little margin to allow for hardware customization. As a result, the fluidized bed reactor
has been chosen as the heart of the gasification system because it will operate under full
control with almost any type of biomass with minimal preprocessing. There are many
advantages of pressurized gasification, one of them being that the produced fuel gas
can be fed to the gas turbine without further compression.
The gas exiting the reactor is thoroughly cleaned of particles that would be
damaging to the turbine. The BIGGT system removes the particles under hot dry
conditions using a single stage cyclone followed by a hot gas filter vessel. This cleaning
process has three advantages over other types of processes: 1) no heat exchangers are
needed, 2) no scrubbing is required nor wastewater to treat, and 3) the sensible heat of
the gas is retained. The gas cleaning system was tested during phase 1 work and found
to clean the gas such that the particulate concentration of the gas entering the first stage
turbine rotor would be 1 ppm or less with no particle larger than 2.8 um. This meets
gas turbine cleanliness requirements [1,2].
Gas Turbine Engine
The gas turbine engine is ideal for integrating with a pressurized gasification
system. It is a fairly simple heat engine that can burn the type of low heat value gas
that is produced and benefits from enormous development efforts during the past few
years. Its simple cycle efficiency is gradually increasing, and its share of the cost of
electricity is dropping. For stationary power sources now and especially in the future
this is the best choice of the prime mover.
4-10

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CURRENT STATE OF DEVELOPMENT
Cratech is progressing with a three-phase plan to develop this power plant for
commercial use. These phases are:
Phase 1: Feed rate of 0.5 mtph (metric ton per hour) at 2 atmospheres
pressure, including a slipstream flow hot gas cleanup system.
Phase 2: Feed rate of 1 mtph at 10 atmospheres pressure, including a full
flow hot gas cleanup system.
Phase 3: Integrating the phase 2 system with a 1 MWe gas turbine engine
generator set.
Phase 1 of this development program is complete. Figure 3 is a gasifier system
performance chart of a typical phase 1 run. A summary of the phase 1 work has been
reported [3]. Phase 2 is now under way.
FINANCIAL ANALYSIS
The expected cost of power resulting from placing this type of biomass power
plant in service is very difficult to estimate without specifying a site (i.e., generically
sited). Numerous factors come into play at any given site; however, the best way to
present this estimate to a large variety of interested readers is generically sited. Figures
4 and 5 give the basic assumptions, a schematic, and a financial analysis for two power
plant sizes. The smaller power plant might be sited where the biomass is already on-
site. Tliis could be a small industrial facility (perhaps a small rice mill or sawmill) with
a zero or negative value biomass waste stream. The larger power plant would be
suitable as a cogeneration or combined cycle power plant for a sugarcane mill, ethanol
plant, or perhaps even a stand-alone community electric power plant. The financial
assumptions will vary widely. Hie assumptions chosen generally reflect those
expected to be found in the current finance market.
ACKNOWLEDGMENTS
The U.S. Department of Energy's Western Regional Biomass Energy Program
provided funding assistance for the completed Phase 1 development work.
Phase 2 funding assistance is being provided by the U.S. Environmental
Protection Agency's Air Pollution Prevention and Control Division, the U.S.
Department of Defense's Strategic Environmental Research and Development Program
with contract assistance from the Tennessee Valley Authority and The State of Vermont
Department of Public Service.
4-11

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REFERENCES
1.	Brown, M.D., E.G. Baker, and L.K. Mudge. 1986. Evaluation of Processes for
Removal of Particulates, 'l'ars and Oils from Biomass Gasifier Product Gases.
Energy from Biomass and Wastes X, Washington, DC, April 7-10,1986.
2.	Newby, R.A. and R.L. Bannister. Hot Gas Cleaning System for Coal Gasification
Processes, Journal of Engineering for Gas Turbines and Power, April, 1994,
Vol. 116, pp.338.
3.	Craig, j.D. Development of a Small Scale B1GGT Power Plant, Proceedings of the
Sixth National Bioenergy Conference, Reno/Sparks, NV, October 2-6,1994.
FIGURE 1. BIGGT POWER PLANT BLOCK FLOW DIAGRAM
Ash Out
(lo be saved)
Air In Electricity
Steam
4-12

-------
FIGURE 2. CRATECH BIGGT POWER PLANT SCHEMATIC

-------
FIGURE 3. PHASE 1 GASIFICATION SYSTEM PERFORMANCE
(D CD d> ©
Time, hours
CD Reactor Pressure, kPa	(3) Reactor Avg Temp, deg C
(2) Mass Air Flow, kg/min	(§) Biomass Meter, kg/min

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FIGURE 4: FINANCIAL ANALYSIS OF A1 MWe GENERICALLY SITED
BIGGT POWER PLANT
Basic Assumptions
Finance:
Total Investment: $2.19 million
Down Payment: $657,000
Term of Loan: 10 years
Interest Rate: 8.5%
Salvage Value: 20%
(at end of 10 yrs)
Turnkey price not including
taxes or building to house plant
Production Costs:
Biomass Fuel: $0/ton
Hours Operation: 8040 hrs/yr
Part-Time Operator: $10/hr
(one per shift)
Maintenance: $0.01/kWh
Insurance: $30,450/yr
Admin, legal: $5,000/yr
Schematic of Power Plant
Financial Analysis Result
Internal Rale of Return vs $/kWh for Four Values of Steam
ni
O
-	$0.Q(ytdb steam
-	$2.00/k!b Gleam
-	$4.0CVWb steam
-	$G.0CWb steam
0.08
4-15

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FIGURE 5: FINANCIAL ANALYSIS OF A10 MWe GENERICALLY SITED
BIGGT POWER PLANT
Basic Assumptions
Finance:
Total Investment: $16.3 million
Down Payment: $4.9 million
Term of Loan: 10 yrs
Interest Rate: 8.5%
Salvage Value: 20%
(at end of 10 yrs)
Turnkey price not including
taxes or building to house plant
Production Costs
Biomass Fuel: $5/ ton
Operation: 8040 hrs/yr
Operator: $30/hr
(one per shift)
Maintenance: $0.01 /kWh
Insurance: $225,750/yr
Admin, legal: $20,000/yr
Schematic of Power Plant
100 kPa
Financial Analysis Result
Internal Rate of Return vs $/kWh for Four Valves of Steam
~— SO.OOWb steam
¦— $2.CKVMb steam
*—$4.0Gk'b steam
—SaOOMb steam
0.08
4-16

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4-C
INSTALLATION OF AN ENERGEO BIOMASS POWER PLANT
AT A LUMBER COMPANY
Charles F. Sanders
ENERGEO, incorporated
28531 La Maravilla
Laguna Niguel, California 92656
Carol R. Purvis
U.S. Environmental Protection Agency
National Risk Management Research Laboratory, MD-63
Research Triangle Park, North Carolina 27711
ABSTRACT
ENERGEO, inc. is engaged ir. a demonstration test program of
its AGRIPOWER 200 unit fueled with biomass at Sutton Lumber
Company in Tennga, Georgia. The objective of the program is to
evaluate the operating and performance characteristics of the
system using lumber wastes for fuel. The program is scheduled to
accumulate 8000 hours of operation over a period of 1 to 2 years.
The program became a reality due to initial funding from the U.S.
Department of Defense's (DoD's) Strategic Environmental Research
and Development Program (SERDP) and the U.S. Environmental
Protection Agency's <3?A's) Air and Energy Engineering Research
Laboratory (now referred to as National Risk Management Research
Laboratory (NRMRL), Research Triangle Park).
The AGRIPOWER unit operates with an "open" Brayton cycle
using a fluid bed combustor and several heat exchangers to heat
compressed air which in turn drives a turbine/generator (T/G)
sen. The T/G set, which includes the compressor and a
recuperator, is a Solar "Spartan" unit packaged for this
application by Alturdyne, Inc. The combustor utilizes both
in-bed and freeboard combustion zones, and the above-bed zone is
well mixed to provide uniform temperatures.
Design specifications call for consumption of 829 lb/hr (376
kg/hr) of fuel with a lower heating value of 4,270 Btu/lb (9.92
MJ/kg). The net electrical power output will be approximately
2 00 kW-hr/hr. This corresponds to a heat rate of 17,700 Btu/kW-
hr (41.3 MJ/kW-hr). The capital cost of an AGRIPOWER 200 unit
will be approximately $2,25G/kW of capacity.
"Thin paper has been reviewed in accordance with tho U.S. Environmental
Protection Agency's peer and administrative review policies and approved for
presentation and publication. '
4-17

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INTRODUCTION
Around the world, both in developing and developed nations,
there exist areas in which there is little or no electrification.
Often, because of population sparsity or geographical obstacles,
there is little anticipation that these areas will ever have
electric power as part of a distribution system connected to
central power plants. Currently, where electricity is to be
provided, it is, and will be, provided by small diesel generator
sets which are the predominant small units. Unfortunately,
diesel generators consume 0.07 to 0.10 gallon (0.27 to 0.38
liter) of oil per kilowatt-hour generated. Even at subsidized
prices of $1.00/gal ($0.26/liter), the fuel cost alone for
generating electricity amounts to $0.07 to $Q.10/kW-hr generated.
In many locations where diesel oil prices are $2.00 to $4.00/gal
($0.53 to $1.06/liter) the fuel costs alone amount to $0.14 to
$0.40/kW-hr generated. With many of the developing areas
experiencing an imbalance of trade, there is a clear incentive to
develop alternative sources of energy.
Of the choices of renewable energy sources, biomass is one
alternative which offers the possibility of delivering 24 hr/day
electrical service in capacities needed to provide small
communities with the power for domestic, agricultural, and
industrial applications. Power generators which produce 100 to
200 kw-hr/'hr of electricity can provide electrification for
communities of 100 to 300 people. Throughout the world there
exists tremendous quantities of biomass waste, such as wood
waste, rice husks, sugar bagasse, and coconut shells, which is
available as fuel. Using biomass fuel to generate electricity is
environmentally favorable, economically viable, and feasible
within the resources of developing areas.
In response to the need for biomass-fueled electrical
generators, ENERGEO, Inc., of San Mateo, California, has designed
a 200 kW electrical generating system combining two existing and
well founded technologies: gas turbine technology and fluid bed
combustion technology. The system is modular, prefabricated tor
shipment to the site of application, and installed and put in
operation on site in several weeks. The capital cost of the
AGRIPOWER 200 unit is currently $2,25Q/kW of delivered electrical
power f.o.b. manufacturing facilities in California. This cost
may be reduced through manufacturing efficiencies and/or partial
fabrication of the unit in the country of end use.
ENERGEO has received extensive worldwide interest in the
AGRIPOWER 200 unit, including letters of intent to purchase
significant quantities when the operation of the commercial.
version has been demonstrated. In support of the development
and application of small biomass-fueled technologies, and to
foster U.S. exports, a commercial demonstration of ENERGEO's
AGRIPOWER 200 unit was undertaken with funding and participation
from the EPA's NRMRL, DoD's SERDP, the U.S. Department of
Energy's (DOE's) Office of Solar Energy Conversion/Solai" Thermal
4 18

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and Biomass Power, the Tennessee Valley Authority (TVA), and
Sandia National Laboratories.
The demonstration of the AGRIPOWER 200 unit is scheduled to
accumulate 8000 hours of operation over a period of 1 to 2 years
at Sutton Lumber Company in Tennga, Georgia. The objective of
the demonstration project is to evaluate the operating and
performance characteristics of the system using lumber wastes as
fuel. It is hoped that the project will establish the technical
and economic feasibility of the technology and document the
environmental impact. Efficiency and emissions testing will be
performed by independent experts. Additional fuels may be
included in the program at a later date. The supporting agencies
have the option of extending the program for an additional year
and another 7 000 hours on line.
AGRIPOWER TECHNOLOGY
The AGRIPOWER 200 unit is an energy conversion technology
fueled with biomass to produce electricity and heat energy. The
system operates with an "open" Brayton cycle using a fluid bed
combustor and several heat exchangers to heat compressed air
which in turn drives a T/G set. The Solar "Spartan" T/G sec,
including a compressor and a recuperator, is being packaged for
this application by Alturdyne of San Diego, California. The
balance of the system was designed by ENERGEO and fabricated by
PMC Production in Sacramento, California. A turbine combustor
included in the system is used for start-up and may be used to
supplement the biomass fuel for maximum output and/or trim
control of the turbine speed. The electricity generated will be
utilized by the lumber mill with additional electricity supplied
to the grid and sold to the TVA. The system also discharges
clean hot air which can be used for cogeneration.
The process is shown schematically in Figure 1. There are
two primary flow circuits in the process: a compressed air
turbine circuit and a combustion circuit. The compressed air
turbine circuit begins with the intake of ambient air by the
compressor which is powered by direct connection to the turbine.
The air is compressed to several atmospheres and exits through a
recuperator which transfers heat from the turbine exhaust to the
compressed air and improves the efficiency of the system. From
the recuperator, the compressed air passes through a convective
heat exchanger, recovering energy from the furnace flue gases.
Then the compressed air goes to the furnace and receives
additional enexgy via a radiant heat exchanger in the upper part
of the furnace above the fluid bed. From the radiant exchanger
the compressed air returns to the turbine and expands through the
turbine blades to power the compressor and the electrical
generator. The turbine exhaust then passes through the
recuperator and is either discharged to the atmosphere or
utilized for cogeneration. Included as an integral part of the
turbine is a fuel oil combustor which is used for "black" starts
of the system.
4-19

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The combustion circuit uses two fans to supply air to the
fluid bed and the freeboard above the bed. Both air supplies are
preheated by recovering energy from the flue gases. Biomass fuel
is supplied to the furnace by a feed hopper and screw conveyors.
Two screws located in the bottom of the hopper regulate the flow
of fuel to a third screw which injects the fuel above the fluid
bed. The furnace employs both in-bed and freeboard combustion
zones. The freeboard zone is well-mixed to provide uniform
temperatures. The temperatures both in and above the bed are
regulated to limit potential problems associated with the ash.
After giving up energy to the compressed air through the radiant
and convective heat exchangers, the combustion gases pass through
a cyclone for removal of the fly ash. From the cyclone, the flue
gases are used to preheat the combustion air streams via the air
preheaters. An induced draft fan exhausts the flue gases to the
atmosphere and is controlled to maintain a slight negative
pressure in the furnace above the bed.
The motors for the fuel feed screw conveyors and for all
fans are variable speed as part of the system control. Feedback
from the power output by the electrical generator and the inlet,
temperature to the turbine are used to regulate the amount of
fuel supplied to the furnace. Key furnace temperatures are used
to control the combustion air supply. Individual controllers are
utilized for each, principal control loop. The individual
controllers are supervised by a digital computer providing
overall control of the system. If a computer fails, the
individual controllers can operate independently. Under certain
circumstances the computer can override the individual
controllers and control the components directly. While the
control system may appear complex, the interfaces with the
AGRIPOWER unit operators are very simple. Start-up and shutdown
procedures are programmed into the system computer. One of the
issues to be resolved during operation of the AGRIPOWER unit at
Sutton Lumber is the best method for control of the turbine
speed. Several possibilities exist to be evaluated,
DEMONSTRATION PROGRAM
The AGRIPOWER 200 unit to be installed and tested at Sutton
Lumber Company is the basic design intended for distribution to
the market place. Prior to shipment to Sutton Lumber Company,
the unit will be assembled and operated by ENERGEO for "shake
down" in Sacramento, California. At the lumber mill, the unit
will be operated by Sutton personnel as part of their ongoing
power generation from wood wastes. The unit is expected to
operate 24 hr/day in a base-loaded mode. The test will continue
for 8000 operating hours or for 2 years, whichever comes first.
The supporting agencies have the option of extending the test for
another year and an additional 7000 operating hours. Performance
and environmental testing will be conducted by independent
experts. The AGRIPOWER unit is equipped with a number of
pressure and temperature instruments for recording operating data
on a continuous basis. For assistance in evaluation and
4-20

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diagnosis, Sandia National Laboratories will provide additional
instrumentation and data gathering facilities. Through the
continuous data gathering, operating and maintenance logs, and
scheduled tests by the independent experts, the test program will
document the operating and maintenance characteristics, determine
the process performance, and define the potential environmental
effects of the operating unit.
Operating and Maintenance Characteristics
ENERGEO's AGRIPOWER unit is designed for simple operation
and maintenance with a minimum of labor required; an important
part of the program is to verify and improve upon these design
objectives. The operating experiences will be logged throughout
the demonstration program. The condition of equipment, both
internally and externally, will be evaluated by inspection at the
end of the program. Factors of consideration to be determined
include:
•	Operation
-	manpower hours
expenses
-	unexpected events
-	start-ups and shutdowns
•	Maintenance
-	manpower hours
-	expenses
•	Reliability
-	scheduled downtime
-	unscheduled downtime
•	Equipment durability
-	wear/failure
-	corrosion
-	slagging/fouling
•	Instruments and controls
-	equipment/operator interfaces
-	start-up procedures
-	shutdown procedures
-	emergency procedures
-	load following
Process Performance
Design specifications for the Sutton installation call for
consumption of 829 lb/hr (376 kg/hr) of fuel with a lower heating
value of 4,270 Btu/lb (9.92 MJ/kg). The net electrical output
will be approximately 200 kW-hr/hr at the specified maximum
capacity. This corresponds to a heat rate of 17,7 00 Btu/kw-hr
(41.3 MJ/kW-hr). The performance goals call for a capacity
factor of 95% which would yield a total cost (capital and
4-21

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operating expense) of $0.06/kW-hr of electricity generated. The
initial capital cost of an AGRIPOWER system for general
distribution would approximate $2250/kW of installed electrical
capacity. For cogeneralion applications, the 18,000 lb/hr (8163
kg/hr) of turbine exhaust leaving the recuperator still retains a
temperature in excess of 500 °F (260 °C) . When this energy is
used to displace fuel oil for drying, generating steam, or for
other processes, significant savings can be obtained to the
extent that the cost of generating electricity may be totally
of f set,
Important temperatures and pressures will be logged
automatically as part of the AGRIPOWER control system. In
addition, Sandia National Laboratories will provide
instrumentation and data recording capabilities to supplement the
AGRIPOWER equipment. Data capabilities will provide for the
performance evaluation of the system as well as individual
components. Performance parameters of interest include:
•	Energy generated
-	electrical power produced
-	thermal energy discharged
•	Fuel consumption
-	quantaty
-	quality
•	System performance
-	efficiency and heat rate
-	availability and capacity factors
Environmental. Aspects
Atmospheric emissions will be determined by periodic
sampling according to standard EPA test procedures. Emissions of
interest are sulfur dioxide (SOJ , nitrogen oxides (NOx) , carbon
monoxide (CO), and particulates. Biomass fuels sometimes contain
small amounts of sulfur and nitrogen. The wood waste at Sutton
Lumber has been reported to contain 0.04 wt% sulfur and 0.11 wt%
nitrogen, both on a dry basis. The sulfur content yields S02
emissions of 0.36 lb/hr (0.16 kg/hr) or 0.10 lb/106 Btu (0.046
kg/106 kJ) . The combustion temperatures within the AGRIPOWER
combustor are low 'enough to avoid any significant fixation of
atmospheric nitrogen to produce thermal NOx, and essentially all
of the NOx emitted by the unit is anticipated from partial
conversion of the fuel nitrogen. NOx emissions are estimated to
be 0.40 lb/hr (0.18 kg/hr) or 0.124 lb/106 Btu (0.053 kg/106 kJ) .
The combustion in the furnace is well mixed with sufficient
residence time to minimize CO emissions which have been estimated
to be 0.71 lb/hr (0.32 kg/hr) or 0.220 lb/106 Btu (0.094 kg/106
kJ). The ash content of the fuel is 1.0% on a dry basis, and
most of the ash is collected in the cyclone. Particulate
emissions in the flue gas exhausted from the cyclone are
estimated to be 0.46 lb/hr (0.21 kg/hr) or 0.13 lb/1.0f Btu (0.059
4-22

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kg/10h kJ). The fuel is apparently free of any chloride content,
so hydrogen, chloride emissions will be nil.
Ash is discharged from the unit at several points in the
process. A small amount of ash is removed from the bottom of the
furnace as part of the process of purging the fluid bed of tramp
materials. The major portion of ash is collected as fly ash in
the cyclone and discharged from the bottom of the cyclone. The
remaining ash is discharged as particulates in the flue gas. For
each discharge point there is interest in determining the
quantity and composition of ash.
Schedule
The original project plan scheduled the AGRIPOWER unit
shipment; in July 1994 to Sutton Lumber Company for start-up in
August. That schedule has been affected by some contractual and
material supply problems. Currently, the plan calls for
preshipment testing and shipment in August 1995. Start-up is
scheduled for September 1995 with viable operation accomplished
during 1995.
CONCLUSIONS
Direct combustion of biomass currently offers the simplest
and most economical process for recovering energy from biomass
wastes. Throughout the developing areas of the world there
exists a huge potential demand for AGRIPOWER 200 units. ENfclRGEO
has received letters of intent to purchase significant quantities
of the AGRIPOWER 200 units contingent on successful operation of
the demonstration unit. The waste heat from the system can be
used to produce potable water and ice as well as for drying food
and industrial products. Much of the worldwide demand for
AGRIPOWER includes interest in cogeneration for water and ice.
Future plans include design and fabrication of larger units which
will meet some of the greater demands of industrialized
applications. As a proven system, the AGRIPOWER units will fill
a significant worldwide need and contribute to U.S. exports and
trade.
ACKNOWLEDGMENTS
This project 'became a reality due to initial funding from
the DoD's SERDP, and funding and participation from the U.S.
DOE's Office of Solar Energy Conversion/Solar Thermal and Biomass
Power, the EPA's NRMRL, the TVA, Sandia National Laboratories,
ENERGEO, Inc. of San Francisco, California, PMC Production, Inc.
of Sacramento, California, Sutton Lumber Company of Tennga,
Georgia, and International Applied Engineering, Inc. of Atlanta,
Georgia. Mention of trade names or commercial products does not
constitute endorsement or recommendation for use.
4-23

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FIGURE 1: AGRIPOWER PROCESS -- SCHEMATIC

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4-D
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred.
AN INDIRECTLY HEATED THERMOCHEMICAL REACTOR FOR STEAM REFORMING/
GASIFICATION OF BIOMASS AND OTHER CARBONACEOUS MATERIALS
Momtaz Mansonr
Manufacturing and Technology Conversion International, Inc.
P.O.~Box 21
Columbia, MD 21045
Abstract
Manufacturing and Technology Conversion International, Inc. (MTC1) is a process and hardware
oriented energy and environmental technology development company located in Columbia, Maryland with
manufacturing and development facilities in Santa Fe Springs, California and Curtis Bay, Maryland. Based
on the principles and merits of pulse combustion, the Company is developing clean coal burners and fluid-
bed combustors, low NOx combustors, particulate emissions control devices, and now entering the market,
the inclireclly heated steam reformer/gasifier for waste-to-energy conversion and the conversion of coals,
renewables and industrial and municipal wastes including toxins into clean fuel forms for IGCC and
combined-cycle power systems. For the pulp and paper industry the MTCI technology steam
reformer/gasifier can process all kinds of spent liquor for energy and process chemical recovery.
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4-E
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred
C0ST VERSUS SCALE FOR ADVANCED
PLANTATION-BASED BIOMASS ENERGY SYSTEMS IN THE U.S.
Christopher I. Marrison* and Eric D. Larson
Center for Energy and Environmental Studies
School of Engineering and Applied Science
Princeton University, Princeton, NJ 08544
ABSTRACT
A unique feature of biomass energy systems is that the feedstock must be gathered from a wide area
around the energy production facility. For a small-scale facility, transport costs will be relatively low, but
capital cost per unit of output will be high. For a large-scale facility, transport costs will be high, but capital
costs will be relatively low. At some intermediate scale, the total cost of energy should reach a minimum. This
paper examines the effects of scale on the prospective costs of producing electricity and alcohol fuels from
plantation-grown switchgrass in the North Central and Southeast regions of the US,
Site-specific biomass cost-supply curves for the year 2000 and 2020 are developed using projections of
the Oak Ridge National Laboratory for switchgrass yields and costs as a function of land capability class. A
geographic information system (GIS) is used to analyze soil quality distributions and road transport distances.
Conversion technologies considered include one commercial electricity generating technology-the steam
rankine cycle—and one nearing commercial readiness—the gasifier/gas turbine combined cycle. Two alcohol fuels
are considered: methanol via thermochemical gasification and ethanol via enzymatic hydrolysis. Both of these
processes have the potential to be commercially ready early in the next century or sooner. Estimates of installed
capital costs for all of these conversion systems drawn from published and other sources.
In all cases, the minimum cost of electricity (COEJ or alcohol (COA^J is reached at plant capacities
that are larger than conventional wisdom might suggest Up to these capacities, the rate of decrease in unit
capital costs is more rapid than the rate of increase in biomass transportation costs. However, around the
capacity corresponding to COE^ or COA^, there is a wide range over which costs change very little. In
general, higher biomass yields lead to larger capacities at COE^ or COA^ Costs are higher in the NC than
SE region, and (in both regions) costs are lower using year-2020 biomass costs compared to year-2000 costs.
INTRODUCTION
Biomass energy crops are of increasing interest worldwide because of the potential for using them in
advanced electricity and transportation fuel production systems that promise cost-competitiveness with fossil fuel
systems, while substantially reducing emissions of C02 to the atmosphere [Hall, et al., 1991; Turhollow and
Perlack, 1991; Larson et al., 1995]. Also, in industrialized countries like the United States, economically viable
bioenergy systems might help reduce government subsidies paid to farmers. Currently, the government pays
farmers some $1.8 billion/year to keep erodible lands out of production under the Conservation Reserve Program
(CRP). In addition, price-support payments, which many fanners need to maintain profitability,1 were some
$16.1 billion in 1S93 [Flinchbaugh and Edelman, 1994], Perennial energy crops would serve to reduce or
* Present address: Oliver, Wyman & Company, IXC. 666 Fifth Ave., New York, NY 10103 .
! For example, com fanners in Iowa received an average arjiuaJ government payment of $45/acre from 1990 to 1992,
During this same period, the profit per acre (gross income, including government payments, minus total economic costs) was
$51 [Davis, 1994],


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eliminate erosion oil many CRP lands, while providing a revenue source to the farmer. With adequate,
unsubsidized profitability, energy crops might help reduce the present level of price support payments.
A unique feature of biomass energy systems that is the focus of this paper is that the feedstock must be
gathered from a wide area around the energy production facility. For a small-scale facility, transport costs will
be relatively low, but capital cost per unit of output will be high. For a large-scale facility, transport costs will
be high, but capital costs will be relatively low. At some intermediate scale, the total cost of energy should
reach a minimum. This paper examines the effects of scale on the prospective costs of producing electricity and
alcohol fuels from plantation-grown switehgrass in the North Central and Southeast regions of the US.
The components of the total cost of energy supply from biomass are (I) the cost to grow and deliver the
biomass to the conversion facility and (2) the cost of the conversion. A number of studies have examined these
two elements independently. For example, biomass cost-supply curves have been developed for some specific
geographic regions by Graham and Downing [1993], Noon [1994], and English, et al. [1994], among others. A
variety of studies (discussed later) have examined the capital and operating costs for biomass-to-electricity or
biomass-to-fuels conversion systems. There do not appear to have been any previous efforts to marry biomass
supply with biomass conversion studies, as done here, to examine the issue of energy cost versus scale.
BIOMASS COSTS
The starting point for the analysis was the selection of a specific site to provide case-study variations in
soil quality and transportation distances for a typical agricultural area. A four-county area in South Central Iowa
(Appanoose, Lucas, Monroe, and Wayne counties) was chosen, in large part because there is significant interest
in this region in the development of biomass energy production on lands currently under CRP contracts [Cooper,
1993; Brown, 1994], The total area is approximately 5100 km2, over 90% of which is suitable for growing
crops. Some 22% of the area is presently held under CRP contract [DNR, 1994]. Soil type [IGS, 19731 and
road [USGS, 1986] maps of the region were digitized and loaded into a geographic information system (GIS).
(See Marrison [1995] for details of the digitization process.)
The GIS system was used to calculate road transport distances from each acre to a central processing
facility that was assumed to be located near the center of the region,2 As detailed below, the cost of growing
biomass on each acre (dependent primarily on soil typo) was then calculated and added to the transport cost
associated with the distance between that acre and the conversion facility. The characteristics of the Iowa site
(relative soil quality and road layout) were taken to represent typical agricultural areas in the North Central (NC)
region (which includes Iowa) and in the Southeast (SE) region.
Costs of Growing Biomass
Development of energy crops in the US is focussed on short-rotation woody crops for some regions and
on herbaceous crops for others [Hohenstein and Wright, 1994], Switehgrass is a primary candidate energy crop
for the North Central (NQ and Southeast (SE) regions.
Switehgrass yield and cost projections made by analysts at the Oak Ridge National Laboratory [Walsh
and Graham, 1995] provide the basis for biomass production costs presented here. Walsh and Graham give
estimates of per-hectare yields and costs for four regions of the US (Northeast, North Central, Southeast, and
South Central). They identify sub-regions by land capability class (LCC). LCC 1 has few restrictions on use for
crops. LCC2 through LCC4 have variable suitability for crops, and LCC 5 through LCC 8 are generally
unsuited for crop production. Within each LCC, soils are sub-defined by the primary reason for restrictions on
their use as cropland: e - erosion potential; w - excessive water; c -- extreme climate; and s - soil factors
(salinity, shallowness, texture, etc.).
2 The GIS is the MapBox package of Decision Images, Inc. of Princeton, New Jersey (Tomlin, 1990]. Transport distances
for each map unit (acre) arc found by locating the nearest point on the road system, and counting the distance along the road
system tn the conversion facility. The result is a map on wliich every acre has an assigned road transport distance.
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For each sub-class of each LCC, Walsh and Graham estimate the area3 and projected switchgrass
yields. They also give projected plantation establishment costs (incurred in the first year), projected annual
plantation maintenance costs (incurred over ensuing nine years, after which it is assumed the switchgrass would
require replanting), and estimated annual land rents. Tables 1 and 2 give yield and cost estimates, respectively,
for LCC2, LCC3, and LCC4 for the NC and SE regions. Areas classified as LCC1 are not shown, because they
would probably not be used for energy cropping and, in any case, the total LCC1 area is relatively small-about
8% of the total area of the NC and SE regions included in the land capability classifications.
Tables 1 and 2 give two sets of yield and cost estimates-those projected to be achievable in the year
2000 and in 2020. Yields are projected to rise between 2000 and 2020 due primarily to improvements in
switchgrass varieties and farm management practices. Costs per hectare are slightly higher in 2020 than in 2000
due to increased costs for fertilizer and for harvesting the higher yields. For either 2000 or 2020, projected
yields are lower in the NC region than in the SE region, and per-heciare costs are generally higher (due largely
to the higher land rents in the NC region).
As one check on Walsh and Graham's estimates, we examined estimates of switchgrass yields and costs
made by Brown [19941, based on field experiments conducted between 1988 and 1992 in Chariton, Iowa, which
lies within the four-county area selected for the case study analysis here. Soils there are less productive than in
many other parts of Iowa. Brown estimates production costs based on measured test-plot yields and present local
agricultural practices. In this respect, it is more reasonable to compare Brown's estimates with those of Walsh
and Graham for year 2000 than for year 2020. Brown reports a measured average yield during 1988-1992 of
10.5 dry tonnes per ha/yr. Brown estimates establishment-year and subsequent annual maintenance costs to be
$270/ha and $190/ha, respectively, excluding land rent of $202/ha/yr.4 By comparison, Walsh and Graham's
estimates for the North Central region appear conservative.
For the selected site, the available soil map included three qualities of soil: loess, which is generally
very good agricultural land; complex alluvial deposits, which is of intermediate quality for agriculture; and till-
and-outcropping paleosols, which is the least desirable of the three for fanning. We assumed that the yields and
costs of switchgrass from these three soil types are given by area-weighted averages for LCC2, LCC3, and
LCC4, respectively, as estimated by Walsh and Graham (Table 3).
Table 3 provides the inputs for calculating levelized switchgrass production casts per unit of useable
biomass tonnage. The time-averaged tonnage (Table 4) accounts for an assumed zero yield in the establishment
year, two-thirds of the steady-state (Table 3) yield in the next year, followed by eight years at the steady-state
yield. Post harvest losses of 10% fLJMinn, 1994J are also included. The levelized costs in Table 4 assume a
discount rate of 6.5%, as used by Walsh and Graham [1995],
Costs of Transporting Biomass
The standard expression for transport costs takes the form
Cost (in S/tonne) = A + (TC TD)	(1)
where A is a constant fixed costs (e.g. truck loading and unloading), TC is the variable transport cost ($ per
tonne-km), and TD is the transport distance in km.
There are conflicting estimates in the literature for biomass transport costs. Some of the discrepancies
arise because basic underlying assumptions are not made clear. For example, whether the distance to be used in
' Walsh and Graham include in the areas all agricultural cropland (including idled or fallow cropland), area in the
conservation reserve program, and pasfureland with high to medium potential for conversion to cropland. No forest land,
wetlands, or urban areas are included.
4 All costs in this paper are expressed in 1994 S using US GDP deflators [Council of Economic Advisors, 1995],
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an equation of the form shown above is a single or round-trip distance is important. (In this paper, all distances
are one-way distances: TD is the distance from the harvest site to the conversion facility.) In other cases, the
moisture content of the load is not clearly specified. Typical moisture contents for transported biomass are 50%
for wood chips and 10-20% for field-dried svvitchgrass [Miles and Miles, 1980].
Transport cost estimates have been reviewed to establish a baseline relationship for transport costs. In
Eqn. 1, A and TC both affect the transport cost. However, only TC matters in determining the capacity of an
energy conversion facility that minimizes the total energy production cost [Marrison, 1995], so the focus of the
discussion here is on the variable cost parameter, TC. For our subsequent analysis, we use A = S3/dry tonne
and TC = $0.18/dry tonne-km as baseline parameter values for switchgrass bales.5
The variable cost we assumed here is about double that of the widely cited estimate by Bhat, et al.
11992],6 but is supported by other analyses we have reviewed. Johnson [1987] and Lee and Johnson [1988] give
the variable portion of wood chip transportation costs for a variety of different vehicle types (Table 5). The final
column in Table 5 are our estimates (based on their results) of the cost of transporting 15% moisture content
rectangular switchgrass bales. These estimates are based on hourly truck rental rates, truck-load volume
capacities, and the bulk density of switchgrass bales (Table 5). The lowest cost option is the truck with a chip
van: $0.15/t-km (at 15% moisture) or $0.18/dry tonne-km. In another analysis, Bludau [1990] gives transport
cost estimates (based on cost quotations for short-haul freight) that agree well with the low-end estimates of
Johnson.7 For 50% moisture content wood chips the cost in 1994$ per tonne is 2.57 + (0.10-TD), where TD is
in km. For 15% moisture switchgrass bales, the cost is 2.57 + (0.15TD). On a dry basis, the cost is 3.03 +
(0.18-TD). Some transport costs in addition to those cited here are reviewed by Marrison [1995].
Total Costs of Biomass Delivered to the Conversion Facility
Production and transportation costs were summed to get the total cost of biomass delivered to the
conversion facility from each acre of land. Fig, la shows qualitatively the cost distribution. Fig. lb shows costs
against total tonnage of biomass available at that cost or less within the four-county area studied (assuming 94%
of the area is used for switchgrass production, which excludes, primarily, towns and lakes).
For the NC region using yield and cost projections for 2000, biomass costs start at $71/dry tonne, or
S3.9/GJ.8 The maximum production within a transport distance of 32 km (the limit of the four-county area
examined') is 1.7 million dry tonnes/year, with a marginal cost of S79/tonne ($4.3/GJ) and average cost of
$77/tonne (S4.2/GJ). For NC-2020, biomass costs start at $55/dry tonne (J3.0/GJ), and Ihe maximum production
is 2.4 million dry tonnes/year [marginal and average costs of S63/tonne (S3.4/GJ) and $61/tonne ($3.3/GJ)].
Biomass costs are considerably lower in the SE region. For example, using 2020 projections biomass costs start
at $32/dry tonne (S1.7/GJ) and rise to an average cost of $39/dry tonne ($2.1/GJ).
5 Actual transport cost pei tonne of useable biomass al the conversion facility is [3 + 0.18+TDJ/0.9, which accounts for 10%
post-harvest losses [UMinn, 1994], all of which are assumed (conservatively) to occur during storage at the conversion site.
s Bhat et al [1992] indicate that for herbaceous crops, the transportation cost per truck load is $34.08 4- 0,62 d, where d is Lhe
roundtrip distance. They further indicate that one load of switchgrass is 15.5 tonnes of field-dry crops. Assuming a moisture
content of 15%, Bhat's expression for the transport cost per dry tonne becomes 2.6 + 0,094-TD, where TD is the one-way
haul distance in km,
' Bludau's estimates are given originally in 19SS German marks. We converted his estimates to 1994 US dollars using the
average. 1988 exchange rate and the US GDP deflator.
' All fuel energy contents in tliis paper are given on a higher heating value basis. The higher heating value for switchgrass is
assumed to be 18.44 GJ per dry tonne.
' The area analyzed is not circular (sec Fig. 1 a), but the greatest transport distance was limited in the analysis to the minimum
distance between the conversion facility (near the center of the four county area) and the outer border of the area. This defined
a circle with a radius of about 32 km.
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ENERGY CONVERSION TECHNOLOGY COSTS
Several technologies arc commercially available or under development for converting plantation-biomass
into electricity or transportation fuels [Larson. 19931, For electricity production, commercial steam-rankinc cycle
systems are considered here (see EPRI [1992]), together with two varieties of gasificr/gas turbine combined
cycles (BIG/GTCC)--one using low-pressure gasification and one using pressurized gasification [Consonni and
Larson, 1994], BIG/GTCC systems arc not commercially established al present, but are likely to be
commercially ready by the tum of the century. The pressurized BIG/GTCC is more efficient than the low-
pressure version, but is likely to be. more capital intensive below a certain capacity range. Two alcohol
production systems are considered: methanol via theimochemical gasification [Williams el al., 1995] and ethanol
via enzymatic hydrolysis [Wyman et al., 1993], Ft* methanol production, only the initial gasification step is not
commercial, but biomass gasifiers are under active commercial development worldwide. Advanced designs of
enzymatic hydrolysis elhanol production are undergoing pilot-scale testing and development al the unit level in
the USA [Wyman el al, 1993J.
The analysis here requires only overall cost and performance characteristics, so details of the
technologies are not discussed. The performance and cost characteristics assumed here are probably achievable
within about a decade (or sooner) with continued commercialization efforts. Still further advances in the
technologies have been identified and are likely to improve performance and/or lower costs compared to those
assumed here. Uncertainties in the cost estimates among the different technologies are due largely to differences
in the extent of commercial development and scaleup. Cost estimates for electricity technologies (especially the
steam cycle) are more certain than those for the alcohol production systems.
Capital Costs
The total installed capital cost per unit of output capacity for each technology is assumed to vary with
capacity as follows:
UnitCost = C + D-(Capacityf	(2)
where C, D, and E are constants for a given technology, values for which can be determined from available cost
projections. For electricity generation, UnitCost is given in S/kWe. For methanol and ethanol production,
UnitCost is in S/(MJ/hrt,nilF1ll. For all technologies considered, E is a negative number (unit cost falls with
increasing capacity), and thus C corresponds to the unit cost for a very large facility. If the costs for two
facilities with different capacities are available, values for two of the three coefficients in Eqn. 2 can be
determined, once a value for the third coefficient is established.10 Table 6 summarizes all of the capital cost
information used to establish the parameter values lor Eqn. 2. The notes to Table 6 provide details as to sources
of the estimates.
For the electricity producing technologies, the capital costs for the "large" capacity systems (which
establish the values for C) are our estimates based on several considerations. For Ujc. steam-rankinc cycle, C
(51200/kW) is based on an extrapolation to 100 MW of a cost versus capacity relationship given by EPRI
[1992], Also, 51200/kW is 10 to 15% less than the cost given by EPRI [1993] for the least costly 300-MW
coal-fired power plant with flue gas desnlfurization. (FGD would not be needed with biomass.) For the
biomass-gasifier/gas turbine (BIG/GT) systems, ihe values of C (SI200/kW for low-pressure BIG/GT and
$1100/kW for pressurized RIG/GT) were set to force a cross-over in total electricity production costs between
the systems in the 50 to 80 MWt capacity range. Blackadder, el al. [1994] give a detailed analysis suggesting
this cross-over range.
For the methanol and ethanol production facilities, the unit cost at the "large" capacity was set to
achieve a value of E of -0.3, a typical scaling factor for total plant costs for many chemical processes [Holland
10 For example, if a value for C is established, then D - (UniiCost, - C)ICapacitywhere
E = (]og([(//ii'lCo.sr, - C}/\UnitCost2 - C]) j/(loglCapacilyJCapacityJ).
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et al., 1985]. Two seis or cost cstimaLes each for methanol and ethanol are given in Table 6. The set of
estimates shown for only single-capacity methanol or ethanol plants were assumed to best represent likely future
costs. The "earlier design" estimates (also shown in Table 6) were used, together with the selected value of E,
to establish parameter values for Eqn. 2 (see Table 6, note (i)).
The capital cost-capacity relationships for electricity and for alcohol production are plotted in Fig. 2.
These relationships can be considered most accurate for the capacity ranges shown in Table 6 (e.g. between 10
and 50 \TWe for the steam-rankine power plant technology).
To convert capital costs to annualized costs, capital charge rates (CCRs) of 0.101 for electricity and
0.151 for alcohol production plants are assumed. The electricity CCR assumes utility financing for renewable
energy power plants, a 30-year life, 6.2% real pre-tax discount rate, and 38% income tax [EPRI, 1993]. For
alcohol production, the CCR is based oil average financial parameters for major US corporations between 1984
and 1988."
Feedstock Costs and Operating and Maintenance Costs
Fuel/feedstock costs are determined by the efficiencies of the conversion systems. For simplicity,
efficiencies are considered to be fixed with capacity for all except one technology (Table 6). Because the steam-
rankine technology is commercial today, its efficiency at different capacities is well established, and an equation
having the same form as Eqn. 2 was fitted to available performance estimates for use here." For simplicity,
operating and maintenance (O&M) costs per unit of output are also assumed fixed regardless of scale for each
technology (Table 6).
TOTAL COST OF ELECTRICITY AND ALCOHOL FUELS VERSUS PLANT CAPACITY
The total levelized cost per unit of output (kWh for electricity and GJ for alcohol) can now be
calculated by combining the cost of the feedstock with the capital charge anil O&M charges. The levelized cost
of electricity (COE) in $/kWh is:
COE = (Cb-3.6)/(l 8.44-ry 1000) + UnitCos:-CCR/(&76frCF) + OM	(3)
where Cb is the average delivered cost of biomass in $/dry tonne (from Fig. lb), 18.44 GJ/dry tonne is die higher
heating value of swilchgrass, i]c is the electricity generating efficiency (Table 6 for BIG/GT systems and
footnote 12 for steam-rankine systems), UniiCost is the installed capital cost in $/kW (from Fig. 2), CCR is the
capital charge rate (0.101), 8766 is the average number of hours in a year, CF is the capacity factor (assumed to
be 0.75), and OM is the O&M cost (Table 6). The levelized cost of alcohol (COA) in S/GJ is:
COA = (Cyi8.44)/(iy + UnitCosi- CCR • 1000/(8766-CF) + OM	(4)
where elements on the rightliand side are defined as for Eqn. 3, except that T|, is the efficiency of alcohol
production (Table 6), UnitCost is the installed capital cost in $/MJ/hr (Fig. 2), CCR is 0.151, and CF is assumed
to be 0.90.
Electricity Production Costs
Calculated baseline results for the COE versus scale for both the NC and SE regions are shown in Fig.
11	Average financial parameters for major US corporations during 1984-1988 were 9.91% real return on equity, 6.2% real return
on debt, 30% debt fraction, and 44% corporate income tax. The CCR also assumes a 25-year plant life and property rax plus
insurance of 1.5% par year of the initial capital cost
12	For the steam-rankine cycle, n. (%) = 100-10.27 - 0.25-(MW,)tt55J, which assumes 20% efficiency at 10 MW, [F.PRI, 1992]
and 27% efficiency at "large" scale (100 MW, wet wood chip combustion) [EPRI, 1993].
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3a (year 2000) and Fig. 3b (year-2020) for all three electricity technologies. For small capacities, falling unit
capital costs with scale for the conversion systems more than offset increasing biomass costs that arise from
increased transportation costs. The total COE reaches a minimum (COEmJ at the capacity at which the rate of
decrease in unit capital cost equals the rate of increase in the transport costs. At capacities larger than this, there
is a very gradual rise in the COE as the transport costs become increasingly more important.
For a given technology, the considerably lower biomass costs projected for 2020 compared to 2000 or
for the SE compared to the NC region, lead to considerably lower COEmin in 2020 compared to 2000 and in the
SE compared to the NC region, as well as higher installed capacities at which COEmitl are reached (Table 7).
In all cases, the capacity at which the COEmm is achieved is relatively large (e.g. up to 500 MW. for the
steam rankine cycle). However, because of the flatness of the COE curves around their minima, COEmin is
closely approached at much smaller capacities: the capacity at which the COE is within 1% (5%) of COE^ is
about half (one-quarter) of the capacity at COE^ (Table 7).
For the s team-ran lei ne cycle, the capacities for being within 5% of the minimum COE (86-111 MW,) are
larger than existing biomass-fircd stcam-rankine power plants. Most such plants rely on low-cost biomass (e.g.
byproducts of industrial processing), and their scales are set by the availability of feedstock, rather than by the
economics of scale.
The COEmin with BIG/GTCC cycles are approached at much smaller capacities than with the steam-
rankine cycles (COEs within 5% of COE^ at 27-91 MWe~Table 7), because most of the scale economy gains in
capital cost occur at smaller capacities (Fig. 2).
At any scale, the higher efficiency (and lower capital costs) of the B1G/GT systems make them a
significantly less costly source'of electricity than steam-rankine cycles. With the costs in Table 7. BIG/GTs
would be competitive with power from new coal-fired plants: coal-based electricity in 2000 and in 2020 is
projected to cost $0.049/kWh and S0.052/kWh, respectively, in the NC region and S0.047/kWli and S0.049/kWh,
respectively, in the SE region.13 BiG/GICC systems might become competitive in the NC region only when
year-2020 targets are achieved with the system using pressurized gasification. In the SE region, BIG/GTCC
systems would compete in year 2000 as well as 2020.
Alcohol Fuel Production Costs
Calculated baseline results for the cost of methanol and ethanol versus scale for both the NC and SE
regions are shown in Fig. 3c (year-2000) and Fig. 3d (year-2020), Similar patterns are observed as with the
electricity costs, with one major difference: (lie capital costs of the fuel production facilities dominate the total
costs for capacities up to those that can be supported by biomass supplied from the entire selected site (circular
area of about 32 km radius). Even at capacities requiring transport of biomass from the 32-km limit, capital
costs are still falling at a faster rate than biomass transport costs are rising. No absolute minimum is reached
within the limits of the capacity scale shown in Fig. 3c and 3d.
Table 8 gives minimum values of COA and related capacities that are reached within tiie biomass
supply constraints. When biomass costs are relatively lower, plant capacities that give minimum COAs are
" These electricity costs are based on capital and operating costs and performance estimates of the Electric Power Research
Institute for 300 MW, pulverized coal subcritical-steam plants with flue gas destilfurizarion in the East-West Central and Southeast
regions [EPRI, 1993] (corresponding to the NC and SE regions in the analysis in this paper) and on electric utility steam-coal
prices projected by the US Department of Energy for the West-North Central and South Atlantic regions fEIA, 1995]. For the
NC region (in 1994$), the capital cost for the coal facility is $1662/kWc, with fixed and variable O&M costs of $48.8/kW-yr and
50.0021/kWh, and a heat rate of 10.719 MJ/kWh. For the SE region, the corresponding figures are. S1359/k\Ve, $42.0/kW-yr,
$0.0015/kWh, and 10371 MJ/kWh. The DOE projects coal prices in 2000 and 2010, Assuming a continuation of the projected
growth rate between 2000 and 2010 to estimate year 2020 prices, coal prices in the NC region in 2000, 2010, and 2020 would
be $1.14/GJ, J1.27/GJ, and $1,40/GJ, respectively. For the SE region, the corresponding prices would be S1.56/GJ, $1.66/GJ,
and S1.77/GJ.
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larger. Correspondingly, capacities are smaller in the NC region than in the SE region. Methanol production
costs reach 5% of COA^ at capacities of 1322 GJ/hr (169 million gal/yr) and 2018 GJ/hr (258 million gal/yr)
for the NC and SE in 2000, respectively, and 1849 GJ/hr (236 million gal/yr) and 2786 GJ/hr (357 million
gal/yr) in 2020. These capacities are comparable to those of the largest existing industrial biomass processing
facilities or methanol-from-natural gas plants.14
Ethanol production costs approach a minimum at smaller plant capacities than for methanol. Capacities
for a COA within 5% of the minimum range from 650-1470 GJ/hr (66-149 million gal/yr) among all of the cases
considered (Table 8).
The COAmh, for methanol in 2020 ranges from S10.1-12.4/GJ (S0.70-0.85/gallon), with the lower cost in
the SE region (Table 8). The corresponding range for ethanol is $8.6-11.2/GJ ($0.75-0.97/gallon). For
comparison, the average wholesale price of gasoline in 1993 in the US was about $4.5/GJ ($0.6/gallon), and is
projected to rise to about $6.8/GJ in 2010 (S0.9/gal).ls With these costs for gasoline, neither ethanol nor
methanol are competitive on a per-unit of energy basis. However, ethanol and, especially, methanol can be
readily used in fuel cell vehicles (FCVs) that are under intensive development for commercial application early
in the next century [Williams, 1994], With gasoline-equivalent fuel economies16 of methanol-FCVs expected to
be some 2.4 times those for comparable gasoline internal combustion engine vehicles [Ogden et al., 1994],
methanol would be able to compete on a cost-per-vehicle-km basis with gasoline with methanol prices (in $/GJ)
up to 2.4 times those for gasoline.
Sensitivity Analysis
The above results change with changes in inputs, especially those relating to biomass production and
transportation costs. To illustrate some of the effects, the SE region in year-2020 is considered. Four important
input parameters are examined here: (a) planting density, i.e. the fraction of available land at the selected site
that is used for biomass production (baseline value = 0.94); (b) variable transportation cost (S0.1.8/dry tonne-km
baseline); (c) yield (see Table 3); and id) annual land rent (see Table 2).
Reducing the planting density raises transport costs and hence total energy costs for a given capacity. It
also decreases the capacity at which the minimum energy cast is reached. For the baseline case, it was assumed
that all agriculturally-suitable land in the selected area-94% of the area-was available to supply biomass. In
practice, a diversity of crops would be planted. One initial bioenergy-crop strategy that has been proposed for
Iowa [Brown, 1993] and other regions of the US is the use of lands currently under the Conservation Reserve
Program for energy crop production. For the specific four county area considered in our analysis, 22% of
agricultural land is held under CRP contracts. The average for Iowa as a whole is about 8% [Brown, 1993].
With electricity generation, when the planting density is half that for the base case (0.5x0.94 = 0.47),
COE^,, is slightly higher than the baseline value. The capacity that gives COE„.,n drops by 10-15% for BIG/GT
systems and by 30% for steam-rankine systems. When planting density is reduced further to 0.094 (=0.94x0.1),
the COE still does not change dramatically, but the capacity that gives the minimum COE drops by 40-60% for
" The Puenta Arenas facility in Southern Chile is among the largest methanol from-natural gas facilities operating today. Its
capacity is about 300 million gal/yr. The capacities of the largest facilities in the US producing ethanol from corn today are of
this order, and the Inrgtsl elhanol-rrorn-sugarcane factories in Brazil are about half this capacity. The biomass input capacity
of a typical modem large integrated pulp and paper mill today is equivalent to that of a methanol-from-biomass facility that would
have a capacity of about 300 million gal/yr.
15 The 1993 gasoline cost is the 1993 average retail price of S8.64/GJ ($1.14/gal) (across all fuel grades of motor gasoline
and including state and federal taxes) [F.IA, 1995] minus $0.31/gal in state and federal taxes and 50.23/gal in distribution ar.d
filling station costs [Ogden, et al., 1994], The US DOE projects an average retail gasoline price (including taxes) of
S10.85/GJ (S1.43/gal) in 2010.
14 For methanol, Lhe gasoline-equivalent fuel economy (km/liter of gasoline equivalent) is the distance traveled per unit of
methanol (in km/GJ) times 0.0349 GJ/Iiter, the higher heating value of gasoline.
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BIG/GT technology and by over 85% for steam-rankine technology. With cthanol production, larger changes
arise in both the value of COA^ and the capacity at which it is reached. For example, with a density of 0.094,
values of COALlil rise by 30-40% and corresponding capacities fall by more than an order of magnitude. The
very different result for electricity and for alcohol production is due to the greater flatness of the alcohol cost
curves around the minimum.
Raising or lowering the variable transport cost has the predictable effect of raising or lowering COEmlll,
respectively, and decreasing or increasing the corresponding capacity (Table 9).
Changing the yield assumption has a small effect on the capacities at which the minimum COE or COA
are reached, but a much larger impact on the value of COEmill and COA,„b, (Table 9). With higher yield, more
biomass is available within a smaller radius, thereby lowering total production costs and transportation costs per
tonne. Both of these costs impact the value of COEmir or COA^, and increased transportation costs reduce the
capacity required to achieve the minimum costs.
Modified input assumptions which change the unit cost of producing biomass by a fixed amount
(regardless of capacity) shift the COE or COA curves up or down, but will not change the capacity at which
minimum production costs are achieved. One such cost is the land rent. Table 2 gives baseline land rents, and
Table 9 shows the impact of changing these by + $123 per hectare.17
CONCLUSIONS
This paper examined the impact of scale on prospective costs of electricity and alcohol fuels from
plantation-grown biomass in the North Central and Southeast United States. All results are based on assumed
biomass production and conversion technologies, most of which have not yet been commercially demonstrated
and thus involve some uncertainty. The results are informative, nonetheless.
A key conclusion is that for any of the technologies examined, the capacity needed to achieve a
minimum lcvclized energy production cost is larger than prevailing wisdom might suggest, but costs are
relatively insensitive to large changes in the capacity around that value, so that production costs arc not much
different than the costs at much smaller capacities. For example, with pressurized biomass-gasifier/gas turbine
systems, electricity costs are within 5% of the minimum at capacities that are 25%-30% of those at which the
minimum cost is reached.
There arc important distinctions among cost-capacity characteristics of different systems. The cost of
electricity generation (COE) is considerably lower at all scales for gasifier/gas turbine combined cycles
(BIG/GTCCs) than for steam-rankine cycles, and BIG/GTCCs achieve minimum costs at much smaller capacities
than steam-rankine cycles. Assuming year-2020 swilchgrass production systems, the COE for steam-rankine
cycles reaches within 5% of its minimum at 100-110 MW(, BJG/GTCC C'OEs reach 5% of their minimum at
capacities of 30 to 40 MWC with impressurized gasification and at 70 to 90 MW, with pressurized gasification.
The latter technology is the lowest-cost electricity producer at capacities larger than 50 to 75 MW,. Electricity
production costs are considerably lower in the SE region (4.3 to 4.6 c/kWh for BIG/GTCC) than in the NC
region (5.4 to 5.7 c/kWh) due to lower delivered biomass costs.
Projected costs of alcohol production (COA) are lower for ethanol than for methanol by 8-10% in the
North Central region and 15-17% in the Southeast region. Plant capacities that achieve a COA within 5% of the
minimum for methanol are twice those for ethanol. Methanol facilities achieve COAs within 5% of the
11 Land rent represents an opportunity cost arising from choosing to grow energy crops instead of using the land for another
purpose. When reduced by S123/ha, the land rent in the SE region would be negative (see Table 2). A negative land rent
could represent a situation in which a biomass producer is receiving CRP payments while also using Ihe CRP land for
bioenergy production. Biomass crops like switchgrass are perennial, and thus substantially reduce soil erosion compared to
annual row crops. Since erosion control is one objective of the CRP program, the production of energy crops on CRP lands
may not be inconsistent with the goals of the CRP program. A continuation of CRP payments (for a limited period) might
provide an important incentive to induce farmers to grow energy crops.
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minimum when they are comparable iii size, to Ihe largest existing industrial biomass processing facilities (e.g. a
state-of-the-art pulp and paper mill).
Values of COE^ and COA^ change most significantly when assumed yields and/or land rents are
changed, but the corresponding capacities change relatively little. In contrast, values of COE^ and COA^
change relatively little with changes in assumed variable, transport costs and/or planting density, but
corresponding capacities change sigtiificandy.
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Region, Biofuels Feedstock Development Pgm., Oak Ridge National Lab., Oak Ridge, TN, December 1993.
Hall, D.O., Mynick, HJi., and Williams, R.H., "Cooling the Greenhouse with Bioencrgv," Nature, V. 353, Sept.
5. 1991.
Hohenstein, W.G. and Wright, L.L., "Biomass Energy Production in the United States: an Overview," Biomass
and Bioencrgy, 1994, pp. 161-173.
Holland, F.A., Watson, F.A., and Wilkinson, J.K., "Process Economics," Chap. 25, Perry's Chemical Engineers'
Handbook, Ch. 25, 6th cd„ McGraw-Hill, NY, 1984.
IGS (Iowa Geological Survey), "Resource Development Land and Water Use Management, Eleven County Area
South Central Iowa," Iowa City, Iowa, 1973.
Johnson, L.R., "Wood Residue Recovery, Collection and Processing," in Biomass Energy Pjt. Development
Guidebook, for Pacific NW and Alaska Biomass Energy Pgm. by Vranizan et al, DE-AC79-BP61195, 1987.
Larson, E.D, "Technology for Electricity and Fuels from Biomass," Ann Rev. Energy & Env., 1993:567-630.
Larson, E.D., Marrison, C.I., and Williams, R.H., "C02 Mitigation Potential of Biomass Energy Plantations in
Developing Regions," Or. Energy and Env. Studies, Princeton University, Princeton, NJ, April 4, 1995.
Lee, H.W., and Johnson, L.R., "Evaluation of Transport Systems for Forest Biomass," Paper ASAF. #88-5034,
American Society of Agricultural Engineers, Michigan, 1988.
Marrison, C.I, The Effect of Plant Size on the Economics of Producing Energy From Biomass, Working Paper
133, Center for Energy and Environmental Studies, Princeton University, Princeton, NJ, 1995.
Miles, T.R., and Miles, T.R., Jr., "Densification Systems for Agricultural Residues," American Chemical Society
Symposium Series, No 130, 1980.
Noon, C.E., "TVA GIS-Based Biomass Resource Assessment," in Proceedings, First Biomass Conference of (he
Americas, NREL/CP-200-6758, National Renewable Energy Laboratory, Golden, CO, April 1994, pp. 74-78.
Ogden, I.M., Larson, E.T>„ and Delucchi, M.A., "A Technical and Economic Assessment of Renewable
Transportation Fuels and Technologies," prepared for US Congress, Office of Technology Assessment,
Washington, DC, May 27, 1994:
Tomlin, C.D., Geographic Information Systems & Geographic Modeling, Prentice Hall, Engelwood Cliffs, NJ,
1990.
Turhotlow, A.F. and Perlack, R.D., "Emissions of CO, from Energy Crop Production," Biomass and Bioenergy,
1(3), 1991, pp. 129-135.
UMinn (U. of Minnesota), Sustainable Biomass Energy Production, Volume 1, Dedicated Feedstock Energy
Supply, for National Renewable Energy Laboratory, Golden, CO, September 1994.
USGS (United Suites Geological Survey), 1:100000 scale topographic map, a) Appanoose County, b) Lucas
4-36

-------
County, c) Monroe County, d) Wayne County, 1986.
Walsh, M.E., and Graham, R., Biomass Feedstock Supply Analysis: Production Costs, Land Availability, Yields,
Biomass Feedstock Development Pgm., Oak Ridge National Lab.. Oak Ridge, Tenn., 18 January 1995.
Williams, R.H., "Fuel Cells and Their Fuels for Cars," Technology Review, April 1994.
Williams, R.II. and Larson, E.D., "Advanced Gasification-Based Biomass Power Generation," in Renewable
Energy: Sources for Fuels and Electricity, Johansson, Kelly, Reddy, Williams (eds), Island Press, Wash. DC,
1993, pp. 729-785.
Williams, R.H., Larson, E.D., Katoisky, R.E., and Chen, J., "Methanol and Hydrogen from Biomass for
Transportation," Center lor Energy and Environmental Studies, Princeton University, June 1995.
Wyman, C.E., Bain, R.L., Hinman, N.D., and Stevens, D.J., "Ethanol and Methanol from Lignocellulosic
Biomass," in Renewable Energy: Sources for Fuels and Electricity, Johansson, Kelly, Reddy, Williams (eds).
Island Press, Washington, DC, 1993, pp. 865-923.
Table 1. Land areas and projected switchgrass yields in 2000 and 2020 by land capability class (LCC) in
the North Central and Southeast Regions of the US [Walsh and Graham, 19951.

NORTH CENTRAL REGION
SOUTHEAST REGION
Land Capability
Classification*
Areab
(103 ha)
Yield (dry tonnes/ha)
| Area
I (103 ha)
Yield (dry tonnes/ha) j
2000
2020
2000
2020
LCC2c
3379
7.09
10.1
J none
—
—
!| LCC2e
21638
9.29
13.3
2613
13.7
19.5
LCC2s
2769
9.76
13.9
j 806
14.1
20.2
LCC2w
17265
10.1
14.4
1051
13.9
19.8
LCC3c
2
8.33
11.9
none
—
—
LCC3e
15027
9.16
13.1
1 957
12.2
17.4
LCC3s
2011
7.18
10.3
472
13.0
18.5
LCC3w
4761 .
9.65
13.8
1049
13.6
19.4
LCC4e
5171
9.02
12.9
491
11.9
17.0
LCC4s
1452
7.47
10.7
278
12.7
18.1
LCC4w
934 i
6.82
9.76 1
512
12.6
18.1
		!l
(a)	The lowcr-case letters indicates the primary restriction on land management; c = climate, e = erosion, s = soil quality,
and w = wetness.
(b)	The total area considered by Walsh and Graham [1995] includes agricultural cropland (Including idled or fallow
cropland], land ill die conservation reserve program (CRP), and paslnrdand with high to medium potential for conversion to
cropland. Wo forest land, wetlands, or urban areas are included.
4-37

-------
Table 2. Projected costs in 1994 dollars* for switchgrass production in 2000 and 2020 by land capability
class (LCC) in the North Central and Southeast Regions of the US [Walsh, 1995],



NORTH CENTRAL REGION


Land

Year 2000

Year 2020
Capability
Class"
Establishment'
(S/lia)
Maintd
($/ha/yr)
Land
($/ha/yr)
Establishment11
(S/ha)
Maint"
(S/ha/year)
Land
($/ha/yr)
1 LCC2c
326.41
266.71
136
334.55
295.98
136 ;
LCC2c I
327.17
294.90
217
337.20
346.63
217
LCC2s
327.17
294.90
217
337.20
346.63
217
LCC2w
327.17
294.90
217
337.20
346.63
217
LCC3c
130.39
254.71
58
345.32
326.71
58,'
LCC3e
327.17
294.90
217
337.20
346.63
217
i|
LCC3s
326.41
266.71
136 i
334.55
295.98
11
136 ||
LCC3w
327.17
294.90
217 I
337.20
346.63
217
| LCC4c
327.17
294.90
217 1
337.20
346.63
217 ||
! LCC4s
326.41
266.71
136
334.55
295.98
136
I LCC4w I
L. 	 J.
326.41
266.71
136 |
334.55
295.98
136
SOUTHEAST REGION
All LCC
415.28
285.01
71 !
429.30
376.88
71 !
(a) Costs originally given by Walsh and Graham [1995] in 1993 dollars are expressed here in 1994$ using the US GDP
deflator [Council of Economic Advisors, 1995].
(b) The lower-case letters indicates the primary restriction on land management: c - climate, e - erosion, s - soil quality,
and w = wetness.
(v) Excludes laiid rent--total first year cost is tills establishment cost plus one year of land rent. Establishment costs include
variable cash costs: seeds, fertilizer, chemicals, and machinery fuel, lubricants, and repairs; fixed cash costs: general
overhead, taxes and insurance, interest on operating loans and on real estate loans; and costs of farmer-owned resources:
capital replacement, other non-land capital, and labor.
(d) Excludes land rent—total annual maintenance cost is indicated maintenance cost plus land Tent. Maintenance costs include
variable cash costs: fertilizer, harvesting, and machinery fuel, lubricants, and repairs; fixed cash costs: general overhead, taxes
and insurance, interest on operating loans and on real estate loans; and costs of farmer-owned resources: capital replacement,
other non-land capital, and labor.
4-38

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Table 3. Average projected yields and costs (in 1994$) for North Central and Southeast Regions.*
fj
1 Land
i Class
Year 2000
Year 2020
Yield
(dry t/ha/yr)h
First-year
costs ($/ha)
Year 2-10
costs (S/ha/yr)
Yield
(dry l/ha/yry
First-year
costs (Vha)
Year 2-10
costs ($/ha/yr)



NORTH CENTRAL REGION


LCC2
10.4
539.11
504.71
14.8
549.02
554.87
LCC3
10.0
537.68
502.80
14.2
	
547.57
552.58
LCC4
9.2
519.46
478.44
13.1
528.92
523.18



SOUTHEAST REGION


LCC2
152
486.99
356.42
21.7
501.04
448.50 j
LCC3
14.2
486.99
356.42
20.3
501.04
448.50
| LCC4
13.6
486.99
356.42
19.4
501.04
448.50
(a) Average yields and average costs for each land capability class arc calculated as area-weighted averages using the
projected yields and costs by land capability sub-classification. For example, for land capability class 2, the average yield,
YlcC2i is;
^LCC2	f ALocfc*YLCC2e + AlcciS^IXXXm + ^LCC2w"^LCC2w)/Ai.CC!
where Alcaj and Ylcco are the area and yield for LCC2 subclassification, i, and A, tr2 is the total area of LCC2. The
average first year cost, EC,^, 's;
RC; cc2 _ (AI cci,'ECL..(r;c + ALCX7£-ECLCC2c + ALCC2o-ECL£x::4 -h ALCC2w'ECLCC2w)/ALCC2
where EC, m. is the establishment costs plus first-year land rent for LCC2 subclassification, i.
(b) Dry metric tonnes per hectare per year.
4-39

-------
Table 4. Calculated time-averaged delivered biomass and total levelized cost of switchgrass production.
Land
Class
Year 2000
Year 2020
Time-ave. biomass*
(tonnes/ha/yr)
Levelized production
costb ($/dry tonne)
Timc-ave. biomass"
(tonnes/ha/yr)
i
Levelized production j
costb ($/dry tonne) i

NORTH CENTRAL REGION
LCC2
8.1 65.53
11.6
49.93 !
LCC3
7.8
68.04
11.1
51.87 |
I
LCC4
7.2
69.72
10.4
52.85

SOUTHEAST REGION
LCC2
11.9
32.95
16.9
28.12
LCC3
11.1
35.20
15.8
30.04
| LCC4
10.6
36.79
15.1
31.40
(a) This is the average annual useable biomass delivered from a unit area to the conversion facility over a ten year period. It
accounts for no yiekl in the establishment year, two-thirds of the steady-state yield in the next year, the steady state yield for
the eight subsequent years, and 10% post harvest losses:
Time Averaged Biomass = [(0 + 0.667 + 8)Y„^,,-0.9]/10 = 0.78-Y„lrfy
where	are the steady-state yields given in Table 3.
(b) The leveli/ed production cost is calculated from:
($/dry tonne) = ($/dry tonne^^ ^il -L)
where L is the post-harvest loss fraction, which is assumed to be 0.10 [UMinn, 1994], (Tonnage loss occurs during harvest,
in-field storage, transport, and on-site storage, but in calculating transportation costs (see text), we conservatively assume that
ail Josses occur during storage at the conversion facility site, i.e. the lull harvest tonnage must be transported to the facility,
but only 90% is converted to power or fuel at the facility.) The cost before losses is given by:
($/dry tonnaW_. = (E + M-2 fl/(l+i)"l}/(Y„lV(0.667/(l+i) + X [1/(1 hT)))
where E is the first year cost (establishment costs plus land rent) in S/ha and M is the annual cost in years 2 through 10
(maintenance cost plus land rent) and Yrai(%i is the projected steady-state yield (Table 3), and i is the discount rate. A real
discount rate of 6.5% is assumed [Walsh and Graham, 1995].
4-40

-------
Table S. Comparison of wood chip transport vehicles [Johnson, 1987].

Truck Load Limits
Bulk density of | Truck Operating Costs"
load (t/m31 to be
1994$ per tonnc-km'
Vehicle type
Weight
(luniics)
Volume
(m!)
both volume and
weight limited*
(1994S/hr)
(1994$/km)
Wood
chips'*
Switchg.
bales"
Truck with log trailer
22.7
54.2
0.42
60.2
1.38
0.16
0.21
Truck with chip van
22.7
76.4
0.30
60.2
1.38
0.11
0.15
Truck with 30-yard rock trailer
21.8
26.7
r~ —
0.81
60.2
1.38
0.32
0.43
12-yard dump truck
10.9
12.5
0.87
48.1
1.06
0.53
0.71
12 yard dump truck with 10-yard dump trailer
22.7
21.4
1.06
60.2
1.33
0.39
0.51
Dump truck with 30-yard box
10.9
22.9
048
48.1
1.06
0.29
0.38
Truck with solid waste container
11.8
16.8
0.70
54.2
1.24
0.46
0.61
(a,> Calculated from indicated load limits. Since typical bulk densities for most biomass are below these calculated limits, transport vehicle loads will typically be limited by
volume, not weight.
(b)	Based on hourly truck rental rates ana average speeds of 43 kilometers per hour for tractors and 45 kilometers per hour fur trucks. Original data coiiveruid to 1994$
using GDP deflator.
(c)	Includes the cost for the time taken for the return (unladen) journey.
(d)	Johnson indicates 50% moisture content, for wlikh a bulk density of 0.32 luruics/m5 is assumed. (Miles and Miles [1980] indicate a typical range cf bulk densities for
50% moisture content wood chips of 0.29-0.35 tonnes/m3.)
(e,i This is our calculation for 15% moisture content rectangular bales, which we assume have a bulk density of 0.24 tonnes/m5. (Miles and Miles [1980] give a bulk density
of 0,16 t/m3 for a standard rectangular bale of "moist" straw.-. A slightly reinforced baler will achieve 0.24 t/m3, and more expensive balers are able to produce bales at 0.43
t/m3.)

-------
Table 6. Estimates of the unit installed capital costs, conversion efficiencies, and operating and
maintenance costs for systems for electricity or liquid fuels production from biomass at various capacities.
Electricity
production systems
Capacity*
(MWS)
Generating
efficiency (%f
Capital cost
(1994$/kWJ
O&M cost'
(1994$/kWh)

10
20
3510
0.0125
Steam rankinc cycle"1
50
n.r.c
1647
0.0125
large
27
1200
0.0125 j
Biomass-gasifier/gas turbine combined
10
37
2577
0.008
cycle (BIG/GTCC) using ncar-
atmosphcric pressure gasifier and wet
scrubbing cleanup1,1
60
large
37
37
1288
1200
0.008
0.008
Biomass gasifier/gas turbine combined
30
40
1800
0.008
cycle (BIG/GTCC) using pressurized
gasifier and ceramic filter hot gas
60
40
1425
0.008
cleanup"4
large
40
1100
0.008
Alcohol fuel
production systems'
Capacity
(GJ/houry
Production
efficiency (%)
Capital cost
(1994$/MJ/hr)
O&M cost
(1994S/GJ) j
Methanol via indirectly-heated gasifier*
811
60
317
2.61
Methanol via indirectly-heated gasifier,
earlier design estimates1
1049
n.r.
162
n.r.
5245
n.r.
112
n.r.
Ethanol, advanced enzymatic hydrolysis™
1355
50
151
2.18
Ethanol, enzymatic hydrolysis using
j earlier (circa-1990) process design'
590
40
341
2.46
2956
40
230
2.46
(a) "Large" refers lo the capacity at which it is assumed that (he minimum unit installed capital cost Is readied.
(b)	100 times the electricity or fuel production divided by the higher heating value of the input biomass.
(c)	Assumed constant for all capacities.
(d)	From EPRI [1992], except for die capital cost and efficiency or die large-capacity unit. For the latter, see text.
(c) Not required for the analysis in this paper.
(f) The source for the two lowcr-capacity capital cost estimates is a personal communication from H. Lundberg (TPS
Tentiiska Processor, AB, Stockholm, Sweden) in Robert Williams (Center for Energy and Environmental Studies, Princeton
University) on October 29, 1994. TPS Termiska Processer is actively woiking to commercialize biomass-gasifier/gas turbine
combined cycles that would use their near-atmospheric pressure circulating fluidized-bed gasifier system that includes a
secondary tar cracking reactor and wet scrubbing for gas cleanup. For the capital cost at "large" capacity, see discussion in
text. The efficiency is an estimate for a system of about 25 MWC capacity thai would use s General Electric LM2500 gas
turbine fElliott and Booth, 1993],
4-42

-------
(g)	The O&M cost estimate is based on two sources. One is the best "guestimate" of the O&M costs for a commercial, 25-
30 MWt BIG/GT facility in Brazil by industry experts involved in the development of the first commercial-scale BIG/GT
demonstration project (to be built in Brazil). The "guestimate" is 0.5 to 1.0 cents per kWh (private communication from Phil
Elliott, Shell International Petroleum Company, to Robert Williams, Center for Energy and Environmental Studies, Princeton
University, Princeton, New Jersey, Oct. 26, 1994). Williams and Larson [ 1993J give estimates of O&M costs from 0.75 to
0.87 cents/kWh for 100-MWt scale advanced BIG/GT systems.
(h)	The source for the capital cost estimates for the two lower-capacity units is [Consonni and Larson, 1994]. It represents
an estimate of the future commercial-level costs for a system that is being developed toward commercialization by Bioflow, a
Scandinavian joint venture involving Sydkraft, Sweden's second largest electric utility, and Ahlstrom, the Finnish boiler and
gasifier manufacturer. The system includes a circulating fluidized-bed gasifier and a ceramic hot-gas candle filter. For the
capital cost of the large capacity unit, see discussion in text. The indicated efficiency is for a system of about 25 MW,
capacity that would use the General Electric LM2500 gas turbine [Elliott and Booth, 1993].
(i)	Best estimates for methanol and ethanol system capital costs were available only for a single capacity. Hie scaling
exponent, E, in Eqn. 2 was assumed to be -03, a typical value for scaling total plant costs for many chemical processes
[Holland ct al., 19851, and the values for coefficients C and D were established as follows. First, equations of the form of
Eqn. 2 were determined for "earlier designs," for which two different-capacity cost estimates were available. These equations
are: (S/MJ/hr),^ = 31.4 + 1052-(G J/br)'" and (.f/MI/hr)^ = 51.4 + 1963 (GJ/hr)M. The values for C and D in these
equations were multiplied by the ratio of the single-capacity capital cost estimate to the capital cost predicted by the
equations for the "earlier designs" at the same capacity. The resulting equations are given in the caption of Fig. 2.
(j) To convert GJ/hr to liteTs/hr, divide by the appropriate higher heating value: 0,0181 GJ/lit for methanol and 0.0228 GJ/lit
for hydrous ethanol (95% ethanol, 5% water).
(k) From Williams et al., [1995],
(1) From Wyman et al. [1993].
(m) From Odgen, et al. [1994], based on Wyman et aL [1993].
4-43

-------
Table 7. Calculated minimum cost of electricity (COE^,) as a function of installed capacity for the North
Central and Southeast regions. Also shown are the capacities at which COEm,„ is reached and the
capacities at which the COE is within 1% or 5% of COE^,.



1 Installed Capacity (MWC) j
Electricity
i technology
Year
Minimum COE
(1994S/kWh)
For COE =
minimum
For COE within
1% of minimum
For COE within
5% of minimum
NORTH CE>
ITRAL REGION
Steam-rankine
2000
0.090
366
212
86
cycle
2020
0.077
470
227
101
Low-pressure
2000
0.066
114
60
27 1
B1G/GTCC
2020
0.057
127
61
30
' Pressurized
2000
0.062
269
12.3
65
BTG/GTCC
2020
0.054
290
137
72
SOUTHEAST REGION
Steam-rankine
¦ 2000
0.065 424
214
99
cycle
¦





2020
0.060
519
244
111
J .ow-pressure
2000
0.049
130
61
37
B1G/GTCC
2020
0.046
142
64
37
Pressurized
2000
0.046
285
140
85 |
BIG/GTCC
2020
0.043
319
154
91
i
4-44

-------
Table 8. Calculated minimum cost of alcohol (COA^) as a function of installed capacity for the North
Central and Southeast regions. Also shown are the capacities at which COAralri is reached and the
capacities at which the COA is within 1% or 5% of COA^,,.



Installed Capacity (GJ per hour)
Alcohol production
technology
Year
Minimum COA
(1994S/GJ)
For COA =
1 minimum*
For COA within
1% of minimum
For COA within
5% of minimum


NORTH CENTRAL REGION

2000 .
14.2
| > 2700
2373
1322
Methanol
2020
12.4
> 3800
3235
1849

2000
13.1
>2200
1532
652
Etlianol
2020
1
11.2
>3200
2267
952
SOUTHEAST REGION
Methanol
2000
10.9
> 3800
3451
2018
2020 ,
10.1
> 5400
4930
2786
Ethanol
2000
9.4
> 3200
2435
1070
2020
8.6
> 4500
3199
1471
(a) For all cases, the biomass available at the site was exhausted before an absolute minimum COA was reached The
minimum COA values shown here arc the lowest COAs achieved up to this limit in biomass supply.
4-45

-------
Table 9. Results of sensitivity analysis for Southeast Region in 2020 showing impact on minimum energy production cost for each technology and
capacity at which the minimum is reached.
1

ELECTRICITY PRODUCTION
II
ALCOHOL PRODUCTION

Low-Pressore.
BIG/GTCC
Pressuized
BIG/GTCC
Steam-rankine
cycle
Methanol
Ethanol
Parameter
COE_
(c/kWh)
Cap.
(MWJ
COE^
(c/kWh)
Cap.
(MWe) I
COE_
(c/kWh)
Cap.
(MWJ
COAllull
(S/OJ)
Cap. I
(GJ/hr)
COA^
($/GJ)
Cap.
(GJ/hr)
BASE CASE*
4.57
142
4.33
319 "
6.05
520
10.1
> 5500
8.6
>4500
1 Variable transp. = $0.09/t-km
4.48
183
4.23
415
5.85
691
9.8
> 5500
8.3
>4500
Variable transp. = $0.36/t-km
4.71
100
4.50
208
639
304
10.7
> 5500
93
3806
Planting density = 0.5Q-0.94
4.62
127
4.38
277
6.16
362
10.7
> 2700
9.0
>2300
Planting density = G. 10-0.94
4.76
87
4.59
121
6.80
75
13.9
>400
11.2
>300
Yield = +25% (dry l/ha/yr)
4.24
147
4.03
337
5.57
525
93
>7000
7.8
> 5700
Yield = - 25% (dry l/ha/yr)
5.10
123
4.83
301
6.83
447
11.3
>4100
10.0
> 3400
land rent + $123/ha/yr ($50/ac/yr)
5.00
142
4.73
319
6.66
520
13.4
> 3800
12.4
>3200
I and rent - $123/ha/yr ($50/ac/yr)
4.13
142
3.93
319
i 5.43
520
9.4
>5500
i
7.8
>4600
(a) The baseline values of the parameters examined in this table are as follows: variable transportation cost = S0.18/diy tonnc-km; planting density = 0.94; yield = as in
Table 3; land rent = as in Table 2.

-------

BBmBMBBI¦
mHP™"
WMHra
-J3
90
80
70 -
OT -—-r/i
O 0) 50
O C
w £
«»
CD -fl"
> CD
= 2
Q — 20
50 -
iO -
10
2000
^^Marginai cost
/ ^ Ave rag 9 cost
2020
North Centra)
Southeast
2000



2020
0.5 1 1.5 2 2.5 3 3.5
Delivered biomass
(million dry tonnes per year)
(b)
Fig. 1. Levelized total cost of switchgrass delivered to an energy conversion facility from a 5100 knoij four-county area in south central Iowa, as
estimated from a GIS analysis.
(a)	Qualitative results: extent of shading reflects relative cost, taking account of soil productivities and road-transport distances to the facility at a
one-acre resolution. Black areas represent towns, lakes, and other areas where biomass cannot be grown. The conversion facility is assumed to be
on the edge of the centrally located lake. Costs generally rise with radial distance away from the facility. In some places land that is physically
further from the facility but more productive than land closer to the facility gives lower biomass costs.
(b)	Quantitative results: switchgrass cost-supply curve for production systems in 2000 and 2020 in the North Central and Southeast regions of the
USA. Costs rise with tonnage supplied due to increasing transportation distances and/or decreasing soil productivities.

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3500
3000 -
<§ 2500
¦m"
CD
a>
T-
^ 2000
E
> 1500
CO
\ Installed Unit Capital Costs
x
s
s
^ ^ Methanol .. whl sca,c.. -
o
o
0)
LU
1000
500
vSteam-rankine cycle /
Pressurized BIG/GTCC7^
-Unpressurized BIG/GTCC
left scale
300
250
W-
200 O)
CD
0
w
150 o
to
>s
w
100 I
LL
O
.C
o
50 o
<
0 50 100 150 200 250 300 350 400 450 500
Installed Capacity: MW (electricity) or 0.1 *GJ/hour (alcohol)
Fig. 2. Estimated installed capital costs of biomass-fed electricity generation and alcohol fuel production.
The curves plot the following derived relationships:
Steam-rankine cycle, $/kW = 1200 + (22195) MW M3
Pressurized BIG/GTCC, $/kW = 1100 + (110420)-MW"2
Unpressurized BIG/G TCC, $/kVV = 1200 + (47198)MWLJ4
Methanol: S/MJ/hr = 57.7 + (I934) (Gj/hr)"
Ethanol: $/MJ/hr = 28.0 + (1070)-(GJ/hr)'OJ
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(a)
IT
Pressurized BIG/GTCC
Unpressurized BIG/GTCC
Steam-ranklne cycle
i	1	i
50	100	150
Installed Capacity (MWe)
Year 2000
NC SE
200
(b)
IV v


	

	— „

Year 2020
Pressurized BIG/GTCC -
NC .^E.
Unpres3iiri2«J BIG/GTCC
	 	
Steam-rankine cycle
		 —
50	100	ISO
Installed Capacity (MWe)
200
200 400 600 800 1000 1200 1400 1600 1300 20002200
Installed Capacity (GJ/hour)
600 900 1200 1500 1800 2100 2400 2700 3000
Installed Capacity (GJ/hour)
Fig. 3. (a) and (b) Total levelized cost of electricity production as a function of installed capacity for the
selected site in the NC and SE regions in 2000 and 2020. (c) and (d) Total levelized cost of methanol and
ethanol production as a function of capacity.
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4-F
The work described in this paper was not funded by the U.S. Environmentaf Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred.
Greenhouse Gas Implications and Mitigation Opportunities
for Integrated Biomass Systems
Jane Hughes Tumbull
Electric Power Research Institute
3412 Hillview Avenue
Palo Alto, California 94304, USA
Ulf Boman
Vattenfall Utveckling AB
P.O. Box 531. S-162 15
Vallingbv, Sweden
This paper examines the "No net carbon dioxide" theme associated with
development of integrated "closed loop" biomass energy systems. There is no
debate about the efficacy and universality of the biochemistry of
photosynthesis, which undergirds the carbon cycle and puts all plant and
animal forms into something of a overriding symbiotic relationship. Rather
our intent is to consider biomass resource production and use in the context
of the laws of thermodynamics - particularly the first law which states that
energy can neither be created or destroyed.
Background
In the fall of 1993, ten feasibility studies of integrated biomass energy systems
were selected for cofunding by the U.S. Department of Energy through an
initiative process managed by the National Renewable Energy Laboratory
(NREL). The initiative was entitled "Economic Development through
Biomass Systems Integration," and the intent of the studies was to assess the
commercial viability and environmental considerations of a variety of
biomass energy systems which included growing a dedicated feedstock. The
Electric Power Research Institute collaborated with NREL in review of the
proposals and agreed to cofund those studies that involved EPRI member
utilities. For the past 18 months EPRT has been technically and financially
involved in five of the ten projects that received grants.
As of May 15th two of the studies have been completed and are about to be
published. One of these was conducted by Northern States Power Company,
an electric and gas utility serving the North Central region of the nation, with
support from faculty and staff of the University of Minnesota. The other is a
product of the Empire State Biopower Consortium, which was formed in 1993
by Niagara Mohawk Power Company, New York State Electric and Gas and
State University of New York - College of Environmental Studies and .
Forestry. Another study, involving Weyerhaeuser Corporation, Carolina
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Power and Light Company, Amoco, and Stone and Webster Engineering, has
a report in final draft form. The other two have been delayed. This paper
will emphasize the Northern States Power study. It reveals particularly well
the broad range of considerations in integrated biomass system planning that
go into determining the total energy inputs associated with these systems, and
thus the greenhouse gas implications.
Relative Electric Conversion Efficiencies of Biomass and Coal
For many years conventional wisdom has judged the efficiencies of energy
production by the relative efficiencies of whatever process or technology
converted the chemical energy of the fuel into some more immediately
useful form of energy. Most electricity is produced by combustion of carbon-
containing compounds - with carbon dioxide and water formed as the main
byproducts. Therefore, for the electric power industry, Ihe conversion units
are Btu into kWh. (In the rest of the world, the units are MJ into kWh, with
10,000 Btu = 10.5 MJ } At 100 percent efficiency, 3413 Btu (3.58 MJ) would
produce one kWh of electric energy. The assumption is that in the
conversion process all the carbon in the fuel is converted into carbon dioxide,
regardless of the relative efficiencies of the system, and usually the carbon
content of the ash left after combustion of any fuel is less than 5 percent. For
biomass only about 45 to 50 percent of dry weight biomass is carbon, thus the
higher heating value (HHV) is about 8,500 Btu/lb or 20 MJ/kg . In contrast,
coal is 85 to 88 percent carbon and has a higher heating value (HHV) of 12,000
to 14,000 Btu/lb or 30 MJ/kg. A typical baseloaded coal plant has a heat rate of
10,000 Btu/kWh (10,5 MJ/kWh) and thus is about 35 percent efficient. Each
MBtu of fuel burned to produce electricity produces approximately 218
pounds of carbon dioxide. Because of the relatively high moisture content,
heat rates of existing biomass plants in the United States are in the 13,500 to
17,000 Btu/kWh (14 to 18 MJ/kWh) range and efficiencies are lower - between
17 and 25 percent.
A Full Fuel Cycle Approach is Essential
The generation of electricity involves more than the conversion of chemical
energy into electrical. In fact, a whole system includes the energy required to
produce, prepare, and transport the feedstock, besides the energy intrinsic to
the feedstock. Assessments of system implications and efficiencies
increasingly are taking into account the full range of the components of these
systems, with their economic, environmental and energy implications. It is
evident that the choice of a particular method or technology for any one
operation in the system may notably influence other choices and thus the
overall system impacts. A full fuel cycle is comprised of the sum of each of its
component operations and thus reflects the composite of individual
decisions.
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Comprehensive assessments of the full fuel cycles of a large number of
different energy resources are presently being made under the auspices of the
U.S. Department of Energy and the Commission of the European
Communities. These studies are looking at a full range of "damage
functions" or mitigation of "damage functions" related to each of the
resources. ("Damage functions" seems to be a euphemism for externalities.)
In this paper, we are not going to attempt that; rather we shall consider the
individual operations that contribute to the overall energy balance of biomass
power systems. We will take into account significant potential changes in
greenhouse gas emissions associated with different scenarios. We are not yet
at the point of being able to optimize the operational functions of a system to
minimize these emissions. However, we concur with Bernhard
Schlamadinger and Gregg Marland's position that the byproducts of an energy
system also must be included in an assessment of the total energy or carbon
balance, inasmuch as these could store or offset significant amounts of carbon.
Thus, energy system efficiencies (E) should be evaluated in terms of the
summation of the energy inputs as compared with the sum of the energy
outputs.
(E)fficiency = Sum of Inputs
Sum of Outputs
The "Alfagas" Feasibility Study
The Northern States Power Company (NSP) feasibility study looked at a net
75 MW IGT "RenuGas" biomass gasification combined cycle (BGCC) system
using alfalfa stems (18.9 MJ/kg) as feedstock. The alfalfa would be grown on
70,000 hectares of land within 50 miles (80 km) of the conversion facility. The
alfalfa would be grown for four years out of a seven year rotation that would
include corn for two years and soybeans for one year. The alfalfa leaves, 28%
protein, would be converted into a high-value animal and poultry feed
product.
First Things
Before the first field is tilled, consideration has to be given to what will be an
economic transportation distance from field to the power plant. NSP defined
this distance as 50 miles; this means the land requirements for the requisite
feedstock would be 5 percent of the total area. Had they decided on a 30 mile
radius, 20 percent of the total land area would have been required. As alfalfa
harvesting probably would be limited to four summer months, a separate
decision was made to set up 80 regional intermediate storage sites, which
would result in additional equipment, materials handling, costs, and energy
inputs. The alfalfa would be transported from the storage sites to a processing
center next to the power plant for separation of leaves and stems.
Maintaining a steady supply to the center of about 2500 tons each day would
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require 20 trucks operating 16 hours a day, 6 days a week. Transportation is
estimated to require 4700 Btu (7MJ) per ton mile.
The relative proportion of stem and leaf material in alfalfa varies with the
annual cutting schedule as well as with soil and climate. In the first year after
planting, the yield of an alfalfa crop is sub-optimal at best. Thereafter it can be
expected to provide two , three or four cuttings. Four cuts per year produce an
increased percentage of leafy to stem material as well as overall higher yields
than do three or two cuts per year. The system trade-offs here are the higher
market price per ton of the leaves for feed compared with the stems to be used
for fuel, the predisposition toward winter injury associated with crops
harvested into the autumn, and seasonal effects on wildlife protection or
enhancement. From an energy input perspective, the fossil fuel requirement
for four cuts will be double that for two.
Site Preparation
Site preparation decisions include those related to tillage - plowing versus
discing versus no-till. Weed control decisions come next. Weed control can
be done either mechanically or with chemicals. Use of a gallon of diesel fuel
for mechanical control of weeds expends 138,800 Btu, while spraying with a
pound of herbicide reflects input of about a million Btu. Balancing the
options will involve trade-offs in terms of costs and efficacy as well as energy
inputs.
Crop Production = Chemicals = Energy Inputs
"Over the past 60 years, crop yields in the United States have increased by
more than a factor of 3, while at the the same time inputs of fossil fuels into
agricultural production have increased by a factor of 40." ( Pimental and
Dazhang) World-wide, fertilizers and pesticides comprise about 50% of the
total amount of energy used in crops production (Helsel). Nitrogen
fertilizers create the greatest demand for fossil fuel inputs, with eighty percent
of this input being natural gas. Recent findings at the Department of
Agricultural Economics and Rural Sociology at the University of Tennessee
indicate that over the past 25 years, the reduction in energy use in nitrogen
fertilizer production has been about 25 percent, per unit produced, and the
savings associated with phosphate fertilizers is even greater. On the other
hand the energy inputs into the preparation of potassium fertilizers have
increased 10 percent. Noting that the overall energy input for fertilizer
depends on both production inputs and the actual amounts used, they have
concluded that savings in nutrient energy requirements for major U.S. crop
production amounts to about 10 percent over the past 25 years.
At this time, in a conventional corn and soybean rotation, the energy inputs
for nitrogen fertilizer are twice those for the diesel fuel for farm machinery
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used for all operations. On the other hand, as a legume, alfalfa is nitrogen
self-sufficient. When the NSP team analyzed the relative needs for fertilizer
for the proposed seven year rotation of four years of alfalfa, two years of corn
and one year of soybeans, they estimated that nitrogen use would decrease by
about 80 percent as compared with the corn and soybean rotation, though the
potassium requirement would double. Overall, the team determined that the
rotation that included alfalfa for both fuel and feed would require annual
energy inputs of 3.5 MBtu per acre (9 GJ per hectare). This is markedly less
than the annual energy inputs for the conventional corn and soybean
rotation which would be 5.3 MBtu per acre (13 GJ per hectare).
Harvesting and Handling
A forage crop can be harvested with generally available farm equipment,
which is not the case for another important biomass resouce, short-rotation
woody energy crops. In the midwest, both mowers or swathers are used for
harvesting alfalfa, in conjunction with a conditioner that crushes the stems.
Conditioning makes possible field drying to about 20 percent moisture in two
or three days. After that time a baler picks up the dried alfalfa for transport.
Round bales versus square? Large ones versus small? Another decision
point. Round bales are of lower density than square ones and are not as easily
transported; however, round ones also tend to shed rain more readily and
therefore may be less prone to degradation during storage. Work done by Art
Wiselogel of the National Renewable Energy Laboratory indicates that in
general grasses or forage stored outdoors will lose between 10 and 15 percent
of their dry weight over a year's time. This is not a linear function; rather it is
definitely temperature and moisture dependent. Degradation of biomass
materials will be a concern in any environment, aerobic or anaerobic, that
supports bacterial activity.
What about the Co-Product Benefits?
About 50 percent of the alfalfa harvested in the NSP project would not be
intended as power plant fuel, thus it can't be considered in terms of the gross
energy content. Rather, the intrinsic chemical energy of the leaves should be
considered in terms of their feed value. To that end, the comparison is made
with the energy required to produce a similar protein meal from soybeans.
Thus, each pound of alfalfa provides a co-product energy-equivalent output
of 477 Btu.
Energy Balance for the Total System
The NSP project team has concluded that despite the significant energy inputs
needed to produce and deliver an alfalfa biomass energy crop for use as an
energy resource, the system is sound from a systems energy perspective.
Their arithmetic sums to 594 Btu of input for each pound of alfalfa produced,
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transported, dried and fractionated (1394 kj/kg). The feed co-product is
credited with an energy value of 477 Btu/lb, (1110 KJ/kg) and production of
electricity using fuel at 15% moisture in a conversion facility with a heat rate
of 9000 Btu/kWh (1.35 MJ/kWh) equates to another 1433 Btu/lb (3335 kj/kg).
The ratio of energy inputs to outputs is 594/1910 - or 1:3.2
This value for the biomass system should be compared with the ratio of
energy inputs to outputs for coal-fired electricity. The ratio for coal inputs to
outputs has been calculated to be 1:4.4. Thus, in terms of the total energy
going into electric generation systems, coal wins over this dedicated
alfalfa/biomass system. While this may be disappointing for the many
champions of biomass energy, it should not come as a surprise. The work
that was done to store energy as coal was accomplished millions of years ago,
and today we have no way of measuring those long-ago inputs.
The result is very different if we assess the fossil fuel energy balance, rather
than the total energy balance. In this case, we do not include the energy
content of the alfalfa stems (biomass) used directly for electric power
production, and only the fossil fuel needed for production of the biomass fuel
is considered. On the other hand, in the case of coal the fossil energy related
to the mining, transportion, and preparation of the coal for conversion must
be added to the energy of the coal itself.
(E)fficiency = Sum of fossil energy inputs
Sum of fossil energy outputs
At a heat rate of 10,000 Btu/kVVh (10.5 MJ/kWh), the full coal fuel cycle
energy ratio is 1:0.33.
What does this mean in terms of greenhouse gas emissions?
We reiterate that the carbon cycle is not being challenged. For each pound or
kilogram of alfalfa carbon released by combustion in the conversion of
biomass to electricity, a pound or a kilogram of atmospheric or soil carbon has
been fixed photosynthetically within the past twelve months. What we need
to explore beyond just the alfalfa stems used as fuel is the extent to which this
new system may contribute to other sinks for carbon. And there appears to be
only one other likely carbon sink, the soil which is being shifted from a
conventional corn/soybean rotation to this longer term rotation which
includes a four year forage crop. Over the past decade, the importance of soil
sequestration of carbon has begun to be recognized. On a global scale, about
three times as much carbon is present in soil as in vegetation, and about two
times as much is in soil as in the atmosphere. Carbon makes up between 0.6
and 3 percent of topsoil, by weight; this translates into tens to hundreds of
tons per hectare. The extent to which carbon compounds equilibrate in soil
relates to the soil characteristics, the temperature, the depth of plant rootings,
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and the extent of litterfall or applications of mulch. If it is valued and used
sustainably, soil can serve as a powerful tool in the mitigation of greenhouse
gas emissions.
Tn the NSP project, tilling the soil only four years in seven decreases soil
disturbance by about 45 percent. This will be reflected in some increase in the
soil humus reservoir and thus in soil carbon storage. We know that frequent
tillage contributes to the oxidation of available soil carbon and also
encourages loss through erosion of the humus fraction. Topsoils in the U.S.
midwest are estimated to have lost about 40 percent of their organic matter
because of intensive agricultural practices. Still we need to better understand
the effects of fertilization, fire, harvesting, site preparation, and species
conversion - not only on soil carbon, but also on other nutrients. To make a
start in that direction, EPRI is now participating with Oak Ridge National
Laboratory and the Desert Research Institute assessing how harvest practices
will influence the bulk density and total carbon and nitrogen of soils. Other
ongoing work assessing the influence of near-term nitrogen fixation on soil
carbon concentrations, suggests that increased fixed nitrogen is associated
with significantly increased soil carbon.
Conclusion
All the answers regarding the potential for biomass energy are not in, but one
lesson we can draw at this point is: "Beware of Slogans and Simplistic
Answers." To the extent that it is used to offset fossil fuel emissions,
increased development of biomass energy can make an important
contribution to the mitigation of greenhouse gas emissions . However, to the
extent that significant energy is used to produce a energy crop fuel, a "closed
loop" system may not be "No net C02," On the other hand, we still have a
great deal more to learn about the sequestration of carbon in soils. We now
know that the potential for soils to serve as carbon sinks is real, but we are not
ready to say "How?" or "How Much?"
This paper has focused on only one of the attributes of biomass energy
systems. Carbon emission offsets are a measurable benefit of these systems,
but other benefits should not be overlooked. Development of fully
sustainable biomass energy systems would provide notable regional economic
and environmental benefits as well as a renewable, indigenous cost-
competitive energy resource. They are certainly worth pursuing in a wise and
committed fashion.
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May 18th, 1995
EPA Paper for Symposium on Greenhouse Gases
REFERENCES
Bhat, M.G., B.C. English, A.F. Turhollow, H.O. Nyangito. 1994. "Energy in
Synthetic Fertilizers and Pesticides: Revisited," ORNL/Sub/90-99732/2.
Department of Agricultural Economics and Rural Sociology, University of
Tennessee, for Biofuels Feedstock Development Program, Oak Ridge
National Laboratory. 43 p.
Green, M,. 1987. "Energy in Pesticide Manufacture, Distribution, and Use."
Energy in Plant Nutrition and Pest Control ed. Z.R. Helsel, New York:
Elsevier.
Helsel, Z.R. 1987. "Preface to Volume 2." Energy in Plant Nutrition and Pest
Control, ed. Z.R. Helsel. New York: Elsevier.
Johnson, Dale W., 1995. "Effects of Harvesting Intensity on Forest
Productivity and Soil Carbon Storage," Proposal to the US Forest Service.
Lyng, LR, J.H. Cushman, R.J. Nichols, and C.E. Wyman. March 15,1991. "Fuel
Ethanol from Cellulosic Biomass," Science. Volume 251, pp. 1318-1323.
Marland, Gregg and Anthony Turhollow. 1990. "C02 Emissions from
Production and Combusion of Fuel Ethanol from Corn." Oak Ridge National
Laboratory.
Marland, Gregg and Bernhard Schlamadinger. November, 1994. "Biomass
Fuels and Forest Management Strategies: How do We Calculate the
Greenhouse Gas Emissions Benefits?" Oak Ridge National Laboratory, 21 p.
Morris, David and Irshad Ahmed. December 1992. "How Much Energy Does it
Take to Make a Gallon of Ethanol?" Institute for Local Self-Reliance. 7 p.
Overend, Ralph, Biofuels and Municipal Waste Technology Division, 1992.
National Renewable Energy Laboratory, U.S. Department of Energy, "Carbon
Fixation and Storage Using Short Rotation Woody Crops."
Pimentel, D. and W. Dazhong. 1990. "Technological Changes in Energy Use in
U. S. Agricultural Production." The Ecology of Agricultural System ed. C.R.
Carroll, J.H. Vandermeer and P.M. Rosset. New York: Macmillan, pp. 147-163.
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Ranney, J.W., L.L. Wright and C.P. Mitchell. 1991. "Carbon Storage and
recycling in short-rotation energy crops." pp. 39-60 In: Mitchell, C.P. (ed),
Bioenergv and the Greenhouse Effect. Proc. of a Seminar Organized by
International Energy Agnecv/Bioenergy Agreement and National Energy
Administration of Sweden. NUTUK B 1991:1 Stockholm, Sweden. 141 p.
Wiselogel, Arthur. May 15, 1995. Personal communication.
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4-G
COST OF PRODUCING HERBACEOUS AND WOODY BIOMASS CROPS IN THE U.S.
Marie E. Walsh
Biofuels Feedstock Development Program
Oak Ridge National Laboratory
P.O. Box 2008, Building 4500N, MS-6205
Oak Ridge, Tennessee 37831-6205
ABSTRACT
Switchgrass and hybrid poplar are potential renewable sources of liquid fuels, power, and chemicals.
This paper estimates the full economic cost (i.e., variable cash, fixed cash, and opportunity cost of owned
resources) of producing these energy crops in six regions in the United States. Average production costs vary
by region, ranging from $29 to $59/dry ton ($32-65/Mg) for switchgrass bales and $61 to $83/dry ton ($67-
91/Mg) for poplar chips. Within a region, production costs decline substantially as yields increase. Estimated
biomass prices needed to ensure comparable profitability with conventional crops are lower for switchgrass than
for hybrid poplar, and are higher in the Lake States and Corn Belt than for other regions of the U.S.
INTRODUCTION
In the United States, biomass energy systems are increasingly being viewed as means to mitigate
greenhouse gases, decrease dependence on foreign energy supplies, provide alternative environmentally-friendly
crops for agriculture, and enhance rural development opportunities. Urban, industrial, and agricultural wastes
can be used as biomass energy feedstocks, hut supplies at reasonable prices are limited. If biomass energy
systems are to provide a significant portion of the energy used in the U.S., production of crops dedicated to
energy uses will be required. Since 1978, the U.S. Department of Energy has supported biomass energy crop
development through the Biofuels Feedstock Development Program (BFDP) at Oak Ridge National Laboratory
(ORNL). The BFDP is developing herbaceous and short rotation woody crops that can be used to produce
liquid fuels, power, and chemicals.
Successful commercialization of biomass energy systems will require that these systems be
economically competitive with systems currently in use. The feedstock price and cost of converting celiulosic
materials to power, fuel, and chemicals must be competitive with conventional energy sources to be attractive to
utilities and chemical companies. To ensure adequate supplies of biomass feedstocks, these crops must also be
attractive to farmers. Fanners will be asked to convert agricultural cropland from the production of
conventional crops (e.g., corn, soybeans, and wheat) to the production of dedicated energy crops. If this is to
occur, the biomass price offered to farmers must be sufficiently high to ensure a profitability at least equal to
that which the farmer could earn using the land to produce con%'entiona! crops. The cost of producing energy
crops is an important component of the profitability of these crops. This paper will present the estimated cost
of producing herbaceous and short rotation woody crops. Production costs combined with expected biomass
yields are then used to estimate the biomass price needed to ensure comparable profitability with conventional
crops.
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The contents
do not necessarily reflect the view of the Agency and no official endorsement should be inferred.
The work described in this paper was funded by the Biofuels Systems Division, U.S. Department of Energy,
under contract DE-AC05-840R21400 with Lockheed Martin.
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METHODOLOGY AND ASSUMPTIONS
The costs of producing dedicated energy crops have been estimated for six regions of the United States-
-the Lake States (MI,MN,WI); the Corn Beit (IA,IL,IN,MO,OH); Appalachia (KY,NC,TN,VA,WV); the
Southeast (AL.GA.SC); the North Plains (KS,NE,ND,SD); and the South Plains (OK.TX), Energy crops can
be produced in other regions of the U.S.; these regions correspond to the production regions for major U.S.
agricultural crops. Switchgrass and hybrid poplars have been chosen as representative herbaceous and short
rotation woody crops because of their high yield potential and wide geographical distribution, and because the
production methods used to produce them are typical of those that will be used to produce many other potential
energy crops resulting in similar production costs. Other energy crops can be produced, and may be preferable
in some areas.
Switchgrass and hybrid poplars are not currently produced as dedicated energy crops; historical
production cost data is lacking. The production costs must be estimated using reasonable assumptions of the
management practices that will be used to produce these crops. The production cast estimations utilize an
engineering approach. Using engineering data, the hours required for a machine to complete an operation can
be calculated. Combined with the per hour costs of using the machine, the total cost of the operation can be
estimated.
A full economic cost accounting approach is used. This approach assumes that all resources used in
production have value, regardless of ownership status. Thus the estimated production costs include not only the
variable out-of-pocket cash expenses (e.g., seeds, chemicals, fertilizer, fuel, repairs, and hired labor), but fixed
cash costs (e.g., overhead, taxes, interest payments), and the costs of owned resources (e.g., the producer's
own labor, equipment depreciation, land values, the opportunity cost of capital investments) as well. This
approach is conservative, and leads to higher estimated costs than if only variable cash expenses are used. The
approach is most useful for policy analysis, however, even for farmers who base year-to-year planting decisions
on variable costs, a full cost accounting is useful in determining long term survival and expansion potential and
to evaluate quality of life issues.
The estimates assume farmers own all of the equipment needed tn produce energy crops except those
needed to harvest hybrid poplars. Machinery and equipment complements typical of commercial-scale farm
operations in each region are used; size varies by region. Input prices are in 1993 dollars. Costs are estimated
for on-farm production only; no transportation costs are included. Round-trip transportation costs are expected
to be about $7.00 to $10.00 per dry ton ($7.70-11.00/Mg) for hauling distances of less than 50 miles (80 km).
The approach used is, to the greatest extent possible, consistent with that used by the U.S. Department of
Agriculture, Economic Research Service to estimate the costs of producing major field crops [I]. Thus the
production cost estimates are consistent with production cost estimates of major field crops and are readily
comparable.
Site preparation is assumed to consist of moldboard plowing and disking. In some areas, no-till or
conservation-till practices will be employed; estimated cost differences will not be large. Lime, phosphorous,
and potassium are broadcast applied as needed prior to planting. Quantities used for estimation are those
typically used in the region for the production of other crops. Herbicides to control competing grasses and
broadleafs are applied to aid establishment. Weed control is assumed to be necessary only in the establishment
year for switchgrass, but is needed until canopy closure (typically year two) for hybrid poplars and consists of
both chemical and mechanical weed control. The analysis assumes annual applications of nitrogen for
switchgrass and biennial nitrogen applications for hybrid poplar.
Switchgrass stands are assumed to remain in production for 10 years before replanting. Harvesting
occurs in years 2-10 and consists of mowing, raking and round baling. Hybrid poplars are assumed to be
planted at a 6* x 8' (1.8 x 2.4 m) spacing (910 trees/acre, 2248 trees/ha) and are harvested in the seventh year
of production. It is assumed that hybrid poplar harvest is by custom operation, and given the lack of data
available for custom harvest rates for short rotation, intensely managed trees, it was necessary to estimate what
these costs might be. Hybrid poplar harvest is assumed to consist of a felling-bunching operation, skidding to a
landing site, and chipping. Other harvesting options have been proposed (e.g., whole-tree harvesting) which
could potentially result in considerably lower harvesting costs, but these alternatives are not currently
operational. Production cost estimates are adjusted for expected yields. The per dry ton net present value cost
of producing switchgrass bales and hybrid poplar chips is calculated using a 6.5 percent discount rate.
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RESULTS
Production costs vary by region due to differences 111 labor rates, machinery complement, variety
planted, level of chemical and fertilizer inputs used, fixed costs, expected yields, and land rental rates with
yields and rental rates being the most significant factors (Figure 1). Tables 1 and 2 summarize the regional
costs of producing switchgrass bales and hybrid poplar chips respectively, given current expectations of yields.
Switchgrass bale production costs range from approximately $29/dry ton ($32/Nlg) in the Southeast to nearly
S59/dry ton ($65/Mg) in the Lake States given current expected regional yields. Hybrid poplar chip costs range
from $61/dry ton ($67/Mg) in the Southeast to more than $83/dry ton ($91/Mg) in the Corn Belt.
For hybrid poplars, harvesting costs constitute nearly 60 percent of total variable cash costs with
establishment costs accounting for nearly 30 percent. The skidding operation represents nearly half of the
poplar harvesting costs, with chipping representing a fifth of the total harvest cost. Poplar harvesting costs vary
substantially by yield, costing $24, $20, and $18 per dry ton ($26,22, and 20/Mg) for mean annual incremental
yields of 3, 5, and 7 dry ton/acre/year (6.7, 11.2, and 15.7 Mg/ha/yr) respectively.
Large scale production of energy crops will require farmers to convert agricultural land to the
production of these crops. For this to occur, the profit farmers receive from energy crop production mast be
comparable to that which could be obtained producing conventional crops. The biomass price needed to ensure
comparable profitability can be estimated by solving for Pb in equation (1).
Rc = Pb x Yb - Cb	(1)
where Rc is the profitability of conventional crops; Ph is the biomass price; Yb is the biomass yield; and Cb is
the biomass production cost. Figures 2 and 3 summarize the "breakeven" price needed for switchgrass and
hybrid poplar compared to com, soybeans, and wheat. Conventional crop revenues are based on market value
only; commodity program payments for com and wheat are not included.
The estimated production costs are based on expert opinion regarding likely management scenarios
employed and yields expected. Farmers may employ different management strategies and individual farm yields
might differ from expected regional averages. Figures 4 and 5 demonstrate how estimated production costs
might differ un
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TABLE I: THE ESTIMATED COST OF PRODUCING SWITCHGRASS BALES BY REGION
($/ACRB) ($/DRY TON) ($/DRY MG)

LAKE
STATES
CORN BELT
SOUTH-
EAST
APPA-
LACHIA
NORTH
PLAINS
SOUTH
PLAINS
YEAR 1 ($/acre)






Variable Cash Costs
71.15
73.96
116.61
111.56
54.74
90.25
1 Fixed Cash Costs
37.47
37.57
24.05
23.96
27.23
18.61
Owned Resources
20.85
18.24
24.06
23.44
20.70
18.84
SUBTOTAL
129.97
129.77
164.72
158.96
102.67
127.70
YEARS 2-10 (S/acre)






Variable Cash Costs
40.45
46.61
49.97
40.01
34.97
49.33
Fixed Cash Costs
37.17
37.15
22.85
22.67
26.37
17.88
Owned Resources
28.08
33.31
40.23
28.17
32.81
33.82
SUBTOTAL
105.70
116.97
113.05
90.85
94.15
101.03
Land ($/acre)
54.00
86.00
28.00
42.00
36.00
23.00







| EXPECTED YIELDS
| (dry ton/acre/year) (dry Mg/ha/yr)
3.2 (7.2)
4.6 (10.3)
6.0 (13.4)
3.7 (8.3)
3.2 (7.2)
5.0 (11.2)
1






1 NET PRESENT VALUE*
| ($/dry ton) (S/dry Mg)
58.54 (64.39)
51.17 (56.29)
28.33 (31.16)
42.14 (46.35)
47.18 (51.90)
29.33 (32.26)
* Assumes 6.5 percent discount rate

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TABLE 2: THE ESTIMATED COST OF PRODUCING HYBRID POPLAR CHIPS BY REGION
(S/ACRE) ($/DRY TON) (S/DRY MG)

YEAR
1
($/ac)
YEAR
2
($/ac)
YEAR
3
($/ac)
YEAR
4
($/ac)
YEAR
5
($/ac)
YEAR
6
($/ac)
YEAR
7
($/ac)
YIELD
(t/ac/yr)
(Mg/ha/yr)
NPV*
($/ton)
($/Mg)
LAKE
STATES









Variable
299.03
36.67
6.97
25.18
0.00
25.18 •
556.44


Fixed
41.44
36.88
36.36
36.68
36.24
36.68
49.56


Owned
72.31
73.50
62.57
56.34
54.00
56.34
54.00
3.1 (6.9)
72.70
(79.97)
CORN
BELT









Variable
302.76
36.47
6.88
25.15
0.00
25.15
506.44


Fixed
36.24
36.87
36.36
36.68
36.24
36.68
49.56


Owned
103.25
104.22
94.03
88.16
86.00
83.16
86.00
3.1 (6.9)
82.75
(91.03)
SOUTH-
EAST









Variable
317.15
36.54
6.91
25.16
0.00
25.16
506.44


Fixed
27.45
22.58
22.07
22.39
21.95
22.39
35.27


Owned
45.11
46.05
36.96
30.33
28.00
30.13
28.00
3.1 (6.9)
60.57
(66.63)










* Assumes 6.5 percent discount rate

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FIGURE 1: REGIONAL VARIATION IN BIOMASS
PRODUCTION COSTS ($/DRY TON)
REGION
ggg swrrcHGRAss ¦¦ hybrid poplar

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FIGURE 2: BREAKEVEN PRICES FOR
SWITCHGRASS ($/DRY TON)
YIELD (DRY TON)
SOYBEANS-SOUTHEAST —I— CORN-SOUTHEAST	SOYBEANS-CORN BELT
-S- CORN-CORN BELT	WHEAT-CORN BELT tIt WHEAT-SOUTH PLAINS

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FIGURE 3: BREAKEVEN PRICES FOR SRWC
YIELD (DRY TONS)
CORN-CORN BELT	SOYBEANS-CORN BELT WHEAT-CORN BELT
-S- CORN-SOUTHEAST -x- SOYBEANS-SOUTHEAST

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FIGURE 4: IMPACT OF ASSUMPTION CHANGES
ON THE COST OF PRODUCING SWITCHGRASS
HARVEST	—I— LAND	ESTABUSHMENT -S- YIELD

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FIGURE 5: IMPACT OF ASSUMPTION CHANGES
ON THE COST OF PRODUCING SRWC
OS
CO
0	20
PERCENT CHANGE IN ACTIVITY/YIELD
-•-YIELD	LAND RENT	-JK- HARVEST COST -€3- ESTABLISHMENT CO

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4-11
Methanol and Hydrogen from Biomass for Transportation
with Comparisons to Methanol and Hydrogen from Natural Gas and Coal
Robert EL Williams
Eric D. Larson
Ryan E. Katofsky1
Jeff Chen2
Center for Energy and Environmental Studies
Princeton University
Princeton, New Jersey 08540
Presented at the
1995 US EPA Symposium on
Greenhouse Gas Emissions and Mitigation Research
Washington, DC
27-29 June 1995
Present address: Arthur D. Little, Inc., 20 Acorn Park, Cambridge, Massachusetts, 02140-2390.
Present Address: Thermo Fibeitek, Inc., 35 Sword Street, Auburn, Massachusetts, 01501.
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METHANOL AND HYDROGEN FROM BIOMASS FOR TRANSPORTATION, WITH
COMPARISONS TO METHANOL AND HYDROGEN FROM NATURAL GAS AND COAL1
Robert H. Williams
Eric D. Larson
Ryan E. Katofsky2
Jeff Chen
Table of Contents
Abstract		4 - VI
Introduction		4-72
Fuel Cell Vehicles		4 - 72
Biomass-Derived Methanol and Hydrogen for FCVs vs. Alternative
Biofucls Strategies		4-74
Process Technology for Methanol and Hydrogen Production		4 - 77
Biomass Gasifiers		4 - 7fi
Directly-heated gasifiers		4-73
Indirectly-heated gasifiers		4 - 7 9
Process Modeling of Methanol and Hydrogen Production		4 - 81
Efficiencies Fuel Production		4 - 83
Costs of Fuel Production ar.d Use		4 - 84
Costs of producing MeOH		4 - 84
Costs of producing h2.		4 - 87
Consumer costs		4 - 87
Lifecycle CO? Emissions for Alternative Fuel/Vehicle Combinations .4 - 87
Conclusions		4 - 83
'i'ables		4-90
Figures		4-106
References		4 - 113
1	This article is based on a paper of the same title presented at Bio.Resources '94,
Oct.3-7, 1994, Bangalore, India
A shorter veision appears in Energy for Sustainable Development, 1(5), January 1995.
2	Present address: Arthur D. Little Co. 20 Acorn Park, Cambridge, Massachuss«t.f.s,
02140-239G, USA
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The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflact the views of the Agency and no official endorsement should be inferred.
ABSTRACT
Methanol and hydrogen produced from biomass via indirectly heated gasiTiers and their use in
fuel cell vehicles would make it possible for biomass to he used for road transportation, with zero or
near zero local air pollution and very low levels of lifecyclc C02 emissions, if the biomass feedstock is
grown sustainably. Moreover, because this approach to using biomass for transport fuels involves
such an efficient use of land, it offers the potential for making major contributions in reducing
dependence on insecure sources of oil in transportation.
Biomass-derived methanol and hydrogen would be roughly competitive with these fuels
produced at much larger scale (to exploit scale economies) from coal, even with relatively high
biomass feedstock prices. While biomass-derived methanol and hydrogen would not be able to
compete with the production of these fuels from natural gas in the near term, natural gas prices are
expected to rise substantially over the next decade or so. With natural prices expected by the year
2010, biomass would be nearly competitive with natural gas in the production of these fuels. A
carbon tax that would increase the cost of owning and operating fuel cell vehicles on natural gas-
derived fuels by less than 2%. would be adequate to tip the economic balance in favor of biomass.
The production of methanol for export in developing regions could provide sustainable new
income streams for rural areas in developing regions while bringing competition and fuel price
stability to world markets in transport fuels.
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Introduction
Deteriorating urban air quality, growing dependence on insecure energy sources, and global
warming are major challenges forcing reexamination of the petroleum-fueled internal combustion
engine vehicle (ICEV) as the basis for road transportation throughout the world.
Deteriorating urban air quality is the main driver forcing an examination of alternative options
for meeting road transport needs today. To meet air quality goals in the face of continuing growth in
transport fuel demand, tailpipe emission standards have been progressively tightened in many coun-
tries. But tailpipe emission control devices have been getting ever more complicated, expensive, and
difficult to maintain. California regulators have decided that air quality goals for the state cannot be
met simply by requiring further incremental reductions in tailpipe emissions and that more radical
measures are needed; the state has mandated that 2% of new cars must be "zero-emission vehicles" by
1998, rising to 10% by 2003. Twelve eastern states collectively have asked the US Environmental
Protection Agency to impose the California standards on them. In light of increasing air pollution in
megacities like Mexico City and Sao Paulo (UNEP/WHO, 1992), such policies are likely to become
widespread.
The spectre of energy insecurity that haunted energy planning in the 1970s is recmerging.
Energy import dependence is rising (e.g. increasing in the US from 10 to 20% of total demand, 1985-
1993), and the share of world oil production coming from the Middle East is growing (increasing from
18 to 28%, 1985-1993). While soft oil prices may persist for a few years, supplies will eventually
tighten because of rapidly growing transport energy demand in developing countries and limited con-
ventional oil resources outside the Middle East; the US Geological Survey projects that oil production
will decline after the turn of the century in all regioas except the Middle East (Masters, 1990).
For the long run, the. most daunting challenge may be global warming. If society should
decide to respond by trying to stabilize the atmosphere, it will be necessary to reduce carbon dioxide
(COj) emissions from fossil fuel burning by 60% or more (IPCC, 1990).
Methanol (MeOH) and hydrogen (Hj) derived from biomass offer the potential for making
major contributions to transport fuel requirements by addressing competitively all of these challenges,
especially when used in fuel cell vehicles (FCVs).
Fuel Cell Vehicles
In a fuel cell the chemical energy of fuel is converted directly into electricity without first
burning the fuel to generate heat to run a heat engine. The fuel cell offers a quantum leap in energy
efficiency and the virtual elimination of air pollution without the use of emission control devices.
Dramatic technological advances for the proton exchange membrane (PEM) fuel cell in particular have
4-72

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focussed attention on this technology for motor vehicles. The FCV has the potential to compete with
the petroleum-fueled ICEV in cost and performance (ACTD, 1994; Williams, 1993, 1994), while
effectively addressing air quality, energy insecurity, and global warming concerns.
Ballard Power Systems, Inc., of Vancouver, Canada, introduced a prototype PEM fuel cell bus
in 1993 and plans to introduce PEM fuel cell buses on a commercial basis beginning in 1998. In
April 1994 Germany's Daimler Benz introduced a prototype PEM fuel cell light-duty vehicle (a van)
and announced plans to develop the technology for commercial automotive applications. In the US,
the FCV is a leading candidate technology for accelerated development under the "Partnership for a
New Generation of Vehicles," a joint venture launched in September 1993 between the Clinton
Administration and the US automobile industry; the partnership's goal is to develop in a decade
production-ready prototypes of advanced, low-polluting, safc cars that could be run on secure energy
sources, especially rcnewables, that would have up to three times the fuel economy of today's gasoline
ICEVs of comparable performance, and that cost no more to own and operate.
Fuel cells used in vehicles would probably use as fuel either hydrogen3 or a hydrogen carrier
that is converted into H2 onboard the vehicle. Hydrogen FCVs would be about three times as energy-
efficient as comparable ICEVs (measured in km/liter of gasoline-equivalent). Hydrogen could be
carried on the vehicle as liquefied H2, in a metal hydride that releases H2when heated, or as
compressed gas. The latter is the storage option favored at present.4 Alternatively, an H2 carrier
could be delivered to and stored onboard the vehicle, to be converted to H2 just before use. In liquid
form such carriers (e.g. various alcohol and hydrocarbon fuels) are much easier to store and transport
than gaseous H2.
Methanol (MeOH)5 is the preferred liquid carrier at present. Via steam reforming, MeOH can
be converted to a mixture of Hz and C02,6 from which the fuel cell extracts the H2 fuel. Methanol-
3	Hydrogen has a molecular weight of 2.016 kg/kmol, a higher heating value (HHV) of 141.77 MJ/kg, and a
density of 0.0888 kg/m3 at 0.101 MPa and 273 K.
4	The storage challenge posed by gaseous H: for FCV applications is similar to that for ICEVs fueled with
compressed natural gas: while H2 has about 1/3 the heating value of natural gas, the fuel economy of FCVs (in
km/liter of gasoline-equivalent) is about 3 times that for comparable ICEVs.
3 Liquid methanol (CHjOH) has a molecular weight of 32.04 kg/kmol, a higher healing value of 22.67 MJ/kg,
and a density of 797 kg/m3.
6 In a steam reformer a mixture of MeOH and steam (H2Ow) is heated over a catalyst and thereby converted into
a mixture of H2 and carbon monoxide (CO). Then, in "shift reactors," the fuel energy of the CO is "shifted" to
H2via the "water-gas shift" reaction: H20 + CO < > H2 + C02. The resulting mixture of H2 and C02 is delivered
to the anode of the fuel cell. In passing the anode, the fuel cell extracts and consumes most of the H,. The
residual H2 in the anode exhaust is burned to provide heat (through a heat exchanger) for the reformer.
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fueled FCVs would be about 2 1/2 times as energy efficient as comparable ICEVs-somewhat less than
for Refueled FCVs because of energy losses in fuel reforming. Sleam reforming conditions make this
option for use onboard the vehicle more problematic for most other liquid fuels.7 However, partial
oxidation (POX) fuel converters could be used to reform a wide range of liquid hydrocarbons onboard
vehicles. POX reforming entails some efficiency penalty,8 but their use might facilitate the initial
widespread introduction of FCVs by allowing them to operate on conventional hydrocarbon fuels
(gasoline, or diesel), with an eventual transition to more efficient FCVs operating on steam-reformed
methanol or pure hydrogen.
For H2-fueled FCVs local air pollutant emissions from the vehicle would be zero. For MeOH-
fueled FCVs, these emissions would be non-zero but miniscule compared to ICEVs.
Methanol and H2 are made commercially today in relatively small quantities from natural gas,
mainly for chemical and petroleum refining markets. If large-scale fuel markets develop for McOH
and/or H2, natural gas is likely to be the feedstock of choice initially. But when natural gas prices rise
to appropriate levels, biomass- and coal-derived MeOH and Hz will become competitive.
This paper explores the technology, economics, and environmental aspects of producing MeOH
and H2 from biomass for FCV applications, in relation to their production from natural gas and coal. -
But before getting into the details of this analysis, this biofuels strategy is discussed in relation to
alternative biofuels strategies for transportation.
Biomass-Derived Methanol and Hydrogen for FCVs vs. Alternative Biofuels Strategies
Methanol and H2 derived from biomass can be used in ICEVs as well as FCVs, and such
applications might well be pursued before FCVs become widely available. However, these biomass-
derived fuels are far less attractive when used in ICEVs. One reason is that the high efficiency of the
FCV makes it possible for biomass to contribute more than twice as much in displacing petroleum as
with ICEVs, for a given amount of land (Table l)-espec:ally important in light of the fact that land
' For example, to reform ethanol to H2 requires temperatures in excess of 500 °C. The temperature mismatch
between the on-board reformer and a PEM fuel cell, which operates near 100°C, gives rise to efficiency penalties
and operational complexities. In contrast, reforming MeOH is relatively easy, because much lower temperatures
are required (250 °C or less).
" In partial oxidation reforming, fuel is burned at relatively high temperatures in a limited supply of air,
generating a gaseous mixture consisting mainly of Hj, CO, C02, and nitrogen (N^. After partial oxidation, the
CO is combined (in shift reacLors) with H20(|) to form more H2 and C02. The resulting gaseous stream is then
delivered to the anode of the fuel ceil where most of the H2 is extracted for fuel.
Willi partial oxidation fuel converter!;, it is generally difficult to make use of the residua! H2 energy in the
anode exhaust. As a result partial oxidation converters arc less energy-efficient titan steam reformers.
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use constraints will ultimately limit the use of biomass for energy.9 Another is that the use of these
fuels in ICKVs offers limited air quality benefits. With MeOH-fueled ICEVs, CO emissions would be
less and emissions of volatile organic compounds would be less problematic than for gasoline, but
emissions of nitrogen oxides (NOx) would probably not be reduced, and there would probably be some
formaldehyde emissions. Moreover, it is now generally believed that McOH, or any alcohol fuel,
especially when blended with gasoline and used in flexible-fuel ICEVs, offers litde or no air quality
advantage relative to gasoline, other than reduced CO emissions (Calvert et al., 1993). Moreover,
reformulated gasolines can meet or surpass reductions in the emission reactivity of alcohol-gasoline
blends (BEST, 1991). Hydrogen would be a relatively clean fuel for ICEV applications-the only
significant pollutant being NO, produced under lean combustion conditions (desirable to get high fuel
economy); with only one pollutant to worry about, it would be possible, with appropriate control
technology, to reduce its emissioas to very low levels. However, because of the bulk of the storage
system (H2 has a relatively low volumetric energy density) and the relatively low efficiency of ICEVs,
H2-fuelcd ICEVs would have very limited range.
Very little attention has been given to MeOH or H2 derived from biomass for vehicular
applications. The focus of biofuels development has been largely on the production of ethanol via
fermentation from grain, sugar beets, or sugar canc, or the production of rape methyl ester from rape *
seed oil. Such biofiiels have attracted attention largely because the crops involved arc familiar to
farmers, and producing them for energy provides an alternative way for the farmer to make a living.
The largest commercial ethanol programs are in Brazil and the US. In 1989 Brazil produced
from sugar cane 12 billion liters of fuel ethanol, which was used to support 4.2 million cars running
on hydrated ethanol and the remaining 5 million cars on gasohol, a gasoline-ethanol blend (Goldem-
berg et al,, 1993), In 1993 the US produced 4 billion liters of ethanol from maize, for gasohol appli-
cations. In both instances the technologies are presently uneconomic. However, substantial cost
reductions are being made for cane-derived ethanol (Goldemberg et al., 1993), and there are good
prospects for making it competitive at Lhe present world oil price, if electricity is cogeneratcd from
' If biomass is used to provide fuels for fuel cell vehicles, the time when land use constraints will begin limiting
the further expansion of biomass production in providing fuels for transport can be pushed far into the future.
To see this, note that in 1985 there were 389 million automobiles in the world, having an average fuel economy
of 7.42 km/1 (17.5 mpg), and consuming 27 EJ/year of petroleum (Lashoff and Tirpak, 1990). If this many cars
had been methanol-fueled (hydrogen-fueled) FCVs with the fuel economies indicated in Table 1 (note a), primary
biomass requirements would have been 12 EJ/year (9 EJ/year), Producing this much biomass would require
about 40 (30) million hectares of plantations, assuming an average productivity of 15 dry tonnes/hectare/year.
The amount of land worldwide (hat might be dedicated to biomass production for energy is of the order of 500
million hectares (Johansson et al„ 1993).
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canc residues with advanced technology along with ethanol from cane juice (Williams and Larson,
1993). But the prospects arc poor for making ethanol economically from grain (Wvman et al., 1993).
The production of ethanol from grain or sugar beets and the production of rape methyl ester
from rape seed oil also represent inefficient uses of land, with low yields of transport services (vehicle-
km/hectare/year) compared to what is achievable with advanced technologies using woody biomass
feedstocks (Table 1). These options also have marginal energy balances; for the Netherlands (energy
output/fossil fuel input) ratios are 0.9 and 1.2 for ethanol from winter wheat and sugarbeets,
respectively, and 1.8 for rape methyl ester derived from rape seed (Lysen et al., 1992). Greenhouse
performance also tends to be marginal. For maize, the net fuel cycle emissions of C02 are
approximately the same as from gasoline (Ho, 1989; Segal, 19S9); total life cycle GHG emissions may
even be somewhat higher than for reformulated gasoline (DeLuchi, 1991). In the case of rape methyl
ester, life cycle C02 emissions are less than with fossil fuels (Lysen et al„ 1992).
The problems posed by conventional "agro-fuels" have provided the motivation for an R&D
effort aimed at developing enzymatic hydrolysis technology for the production of ethanol from ligno-
cellulosic feedstocks, which can be grown at much lower cost than grain or sugar beets. Moreover,
for a woody feedstock yield of 15 dry tonnes/hcctarc/year, which is generally believed to be
achievable in large-scale production, the ethanol yield could be more than twice that from grain (Table
1). If the US Department of Energy's year-2000 goals for performance and cost are met, ethanol
produced this way would be competitive with gasoline for oil prices less than $25/barreI; energy
balances would also be favorable; life-cycle emissions of C02for ethanol production and use in ICEVs
(in g C/km) would be only about 2% of those from such vehicles operated on reformulated gasoline
(Wyman et al., 1993). A shortcoming of the technology is that, when used in ICEVs, it may not lead
to air quality improvements beyond what can be achieved with reformulated gasoline. (Ethanol offers
less air quality benefits than methanol.) Also, while the yield (useful (ue'/hcctare/ycar) may prove to
be comparable to that for MeOH derived from ligno-ccllulosic feedstocks (Table 1), the lower
efficiency of using ethanol in FCV applications (because fuel conversion would have to be by partial
oxidation instead of steam reforming) restricts its attractiveness vis a vis MeOH.
In the remainder of this report, it is argued that the use of biomass-derived methanol or
hydrogen in fuel cell vehicles offers is a way to use a renewable energy resource as a transportation
fuel, with high efficiency, low emissions of local pollutants and greenhouse gases, and prospectively
compteitive costs.
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Process Technology for Methanol and Hydrogen Production
The production of liquid MeOH or gaseous H2 from biomass, coal or natural gas involves
several similar basic processing steps. With biomass or coal, the feedstock is first gasified (by heating
it to above 700 °C in the presence of little or no oxygen) into a synthesis gas (syngas) consisting of
CO, H2, C02. H20(j), and in some cases methane (CH4) and small quantities of other hydrocarbons.
The syngas exiting the gasifier is cooled and then quenched with a water spray to remove particulates
and other contaminants. Additional cleanup of sulfur (S) compounds (especially important with coal)
is needed to prevent poisoning of downstream catalysts. The syngas then undergoes a series of
chemical reactions that lead to the desired end product. The equipment downstream of the gasifier for
conversion to MeOH or H2 is the same as that used to make MeOH or H2 from natural gas.
All equipment for fuels production from coal is commercially available today. For biomass,
suitable gasification technology is being developed. As a feedstock for gasification, biomass has some
advantages relative to coal: it is more reactive and thus easier to gasify, and most biomass has a
sufficiently low S content that costly S removal systems are not required. On the other hand, while
coal facilities can benefit from economies of scale in capital costs, the higher cost of transporting
biomass (due to its low volurpetric energy density and the low efficiency of photosynthesis) will
constrain biomass facilities to more modest sizes (Larson, 1993).
The processing of natural gas or syngas that contains hydrocarbons begins with reforming the
hydrocarbons, i.e. converting them to CO and H2, usually by reacting the syngas with H2Ow over a
catalyst at close to 900 °C. [Reforming is not needed with some coal and biomass gasifier designs
(discussed below), because no significant quantities of hydrocarbons are present in the syngas.] The
CO:H2 ratio of the gas is next adjusted to the level required for final processing using one or more
shift reactors, wherein H2Ofe; reacts with CO over a catalyst to produce H2 and C02.
For MeOH production (Fig. 1), a single shift reactor operating at 450 to 550 °C produces a
molar II2:CO ratio of about 2. (With natural gas as the feedstock, the high H:C ratio eliminates the
need for the shi ft reactor.) Following the shift, the gas passes through a reactor containing a solvent
that selectively dissolves C02 .and H;Ote) out of the gas. With C02 and 11,0^ removed, the gas stream
is then compressed to about 100 bar and fed to a MeOH synthesis reactor, wherein CO and H2
combine over a catalyst at about 250 °C to form MeOII. Conversion of carbon as CO to carbon as
MeOH is typically in excess of 98%. Water is removed from the MeOH in a final distillation step.
For H2 production (Fig. 1), two shift reactors in series (the first operating at about 450 °C and
the second at about 230 °C) convert to H2 as much of the CO leaving the reformer as possible. The
gas then enters a pressure swing adsorber (PSA), which separates gases by exploiting the ability of
specially designed porous materials to selectively adsorb specific molecules at high pressure and
4-77

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desorb them ac low pressure. The first PSA bed adsorbs C02 and H20, and the second desorbs all
remaining components except H2. Up to 97% of the H2 fed to a PSA can be recovered as final
product with greater than 99.999% purity. The H2 is then compressed for storage or pipeline
transmission.
Biomass gasifiers
Since all process equipment needed to produce MeOH or H2 from biomass is well established
in commercial use, except for the gasifier, the discussion here emphasized the development status and
projected performance of alternative gasifiers. Biomass gasifiers operate by direct or indirect heating.
The former, which involves partial oxidation of the feedstock, is the basic principle used in coal
gasification; the latter is not suitable for most coals due to their low reactivities compared to biomass.
Directly-heated gasifiers. Directly-hcated gasifiers use air or oxygen to burn some of the feedstock in
situ, thereby providing the heat needed to gasify the remaining feedstock. In the production of MeOH
or H2, oxygen is preferred, so as to minimize the gas volumes that must be treated downstream. (The
presence of N2 also reduccs-the efficiency of H2 separation in the PSA step.) A disadvantage of 02
use is increased costs. Because of the sensitivity to scale of capital costs for 02 plants, there is a cost
penalty with 02 that is acute at the smaller scales that would characterize biomass facilities.
Fixed-bed, fluidized-bed, and entrained-bed gasifiers were originally developed for coal
(Simbeck et al., 1993; Synthetic Fuels Associates, 1983). High-temperature entrained-bed gasification
of biomass has not been the focus of any hardware development efforts, but there have been various
efforts to adapt fixed and fluidized-bed designs to biomass. A number of atmospheric-pressure
fluidized-bed units are commercially operating with biomass to supply gas for boilers or furnaces
(Larson, 1993). For production of transport fuels from biomass, the fluidized-bed gasifier is likely to
be the technology of choice among directly-heated gasifier designs, some reasons for which are
discussed below.
In a fluidized-bed gasifier the feedstock, typically fed through the sidewall of the reactor,
mixes into a bed of inert heat carrying material, such as sand, that is maintained in a fluidized state by
injection of 02 (and sometimes H20(i)) from below. Fluidized-bed gasifiers have the flexibility to
accept feedstocks with a wide range of sizes and bulk densities. Ash and unreacted char are carried
out of the top of the reactor and separated from the product gas in a cyclone. In a bubbling fluidized-
bed (Fig. 2a), the solids are removed via the cyclone for disposal. In a circulating fluidized-bed (Fig.
2b) the cyclone is an integral part of the gasifier, making it possible to recycle the solids for further
reaction. In both designs, the product gas exits at 900-1000 °C—essentially the same as the
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temperature throughout the bed. The high average bed temperature', facilitates cracking of high
molecular weight hydrocarbons (tars and oils) that could otherwise complicate downstream processing.
Gasifiers operating at elevated pressures are preferred for MeOH and H2 production to reduce
the sizes and unit costs of downstream reactors and the cost of downstream gas compression. Several
pressurized gasifiers are commercially available for coal but not for biomass. However, there are
several ongoing efforts to demonstrate pressurized, directly-heated biomass gasifier technology, so that
the technology is likely to be commercially ready before the end of the decade.
Tne directly-heated fluidized-bed gasification technology selected here for analysis is the
pressurized bubbling fluidized-bed gasifier under development by the Institute of Gas Technology
(IGT). At pilot scale, the IGT gasifier has had perhaps the most extensive operating experience with
biomass of any pressurized bubbling-bed gasifier (Evans et al., 1988). Also, this technology has been
the focus of several previous assessments of MeOH production from biomass (Wyman, et al, 1993;
Stevens, 1991; OPPA, 1990). A scaled-up version of the IGT reactor has now been built in Hawaii,
where it will be operated initially on sugarcane bagasse (100 tonnes/day capacity). Plans are to
subsequently demonstrate (i) the production of electricity by burning the product gas in a gas turbine
and (ii) the production of MeOH (Overend, et al., 1994). For the present analysis, projected
performance characteristics of a commercial-scale IGT gasifier are considered (Table 2).
The present analysis also considers pressurized entrained-bed biomass gasification (specifically,
with the Shell gasifier, which is commercially available for coal). The entrained flow gasifier, the
predominant coal gasification technology, has not been seriously considered for biomass for two
reasons. First, the feedstock must be crushed to a fine size (100-600 microns), which is relatively
easily done with coal, but is energy and capital intensive with biomass. Second, because of its high
reactivity, biomass does not require the same high peak gasification temperatures needed for coal; thus,
the large amount of 02 used to achieve high temperatures (in excess of 1300 °C for coal) and the
attendant removal of ash as molten slag represent unnecessary costs for biomass. This gasifier is
included in the present analysis to underscore the importance of choosing a gasifier (other than this
one) that is well designed to take advantage of the unique properties of the biomass feedstock.
Indirectly-heated gasifiers. Indirectly-heated gasifiers obtain the heal needed to drive the gasification
reactions from heat-exchange tubes or from an inert heat-carrying material like sand. Indirect heating
gives rise to lower reactor temperatures than direct heating, but temperatures are sufficiently high
(700-800 °C) for effective biomass gasification. The indirect heating makes possible the production of
a gas undiluted by N2, without the use of costly 02.
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To characterize MeOH and H, production based cn indirectly-heated gasification, we consider
projected performance characteristics (Table 2) for the Battellc-Columbus Laboratory (BCL) and the
Manufacturing and Technology Conversion International (MTC1) designs. Both have been tested at
pilot scale but need to be demonstrated at larger scale before they can be commercialized.
The BCL gasifier is an atmospheric-pressure twin, fast fluidized-bed unit that resembles fluid
catalytic crackers commonly used in petrochemical refining (Fig. 2c). After drying, biomass is fed to
the gasification bed, wherein pyrolysis (devolatilization) of the biomass occurs. Hie char (solid
carbon) residue of this process is transferred to a separate combustion bed where it bums to heat sand
that is circulated back to the gasification bed to provide the heat to drive the devolatilization.10 The
ash is removed from the combustor. A portion of the product gas is recirculated (after cleaning) to
fluidize the gasification bed. The solids residence time during gasification is short, so that the specific
throughput rate is relatively high (Table 2), which should reduce unit capital costs relative to other
gasifiers with lower throughputs.
To date, the BCL technology has operated at bench-scale, at about 500 kg/hour capacity
(Feldman, et al., 1988; Paisley and Litt, 1993). A 200 k\Vc gas turbine has recently been coupled to
this unit to explore prospects for power generation with the technology. A BCL gasifier with a
capacity of 200 tonne/day of wood chips will be built in the state of Vermont in the US (with 50%
cost sharing of the installation cost by the US Dept. of Energy) for eventual use in power generation
using a gas turbine (Paisley and Overend, 1994). The use of the BCL gasifier for MeOH production
has also been evaluated by researchers at the National Renewable Energy Laboratory (Wyman et al,
1993). The performance characteristics assumed here for the BCL gasifier (Table 2) are based on a
detailed prc-feasibility study for a commercial-scale BCL-gasifier/gas turbine facility (Breault and
Morgan, 1992).
The MTCf gasifier (Fig. 2d) is an atmospheric-pressure lluidizcd-bcd unit with in-bed heat
exchanger tubes (MTCI, 1990; Durai-Swamy ct al., 1991a). Some combustible gas taken from one or
more downstream points in the process is burned in a pulse combustor that feeds the heat exchanger
tubes, providing the heat for gasification. Pulse combustion creates a highly turbulent flow of hot
combustion products in the heat exchanger tubes, leading to heat transfer rates about five times higher
than those for a conventional heat exchanger (Parkinson, 1990). The combustion of gaseous fuel in
the pulse combustor can be augmented by combustion of residual char from the gasifier and tars
10 To increase the gas production per unit of biomass input to the gasification bed, supplemental fuel (biomass or
other fuel) can be added to the combustor. However, the best overall efficiency (counting all energy inputs to
the gasification and combustion beds) is achieved when no supplemental fuel is used (Paisley, 1994a).
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recovered from the quench step.11 Reactor temperatures are typically low (about 700°C) due to the
indirect heating. In work to date, F^O^is injected into the gasificr both to promote gasification
reactions and to fluidize the bed. In future systems, recycled product gas may be substituted for some
of the	because only a small fraction of the presently used is actually consumed in the
gasification reactions.12 The MTCI design produces a gas with an unusually high H2 and relatively
low CH4 content (Table 2).13
Most bicmass-related development work with the MTCI technology has focussed on "unusual"
biomass feedstocks: black liquor, the lignin-rich byproduct of cellulose extraction during chemical pulp
production (Black, 1991); pulp-mill sludge (Durai-Swamy et al., 1991b); and municipal sewage and
solid wastes (Durai-Swamy et al., 1991c). A pilot-scale MTCI black liquor gasifier of 48 tonnes/day
capacity has operated since 1992 in Erode, India, and a similar unit has recently been installed in a
pulp mill in New Bern, North Carolina (Durai-Swamy, 1994). Also, a pilot-scale pulp-mill sludge
gasifier with a capacity of 24 tonnes/day lias been test operated at a paper mill in Ontario, California.
Process Modeling of Methanol and Hydrogen Production
Detailed thermodynamic process models of MeOH and H2 production from biomass, from
natural gas, and from coal were constructed using commercially-available process simulation software
(ASPEN-PLUS). See Katofsky (1993) for details.
Table 2 gives the performance characteristics, based on experimental data, assumed for the
IGT, MTCI, and BCL biomass gasifiers and for the Shell coal gasifier. With die exception of the
Shell gasifier, the use of experimental data is required, because gas compositions cannot be predicted
using ASPEN-PLUS. All chemical reactions within an ASPEN-PLUS model are assumed to reach
equilibrium. In actual biomass gasifiers, the low temperatures and short residence times produce gas
compositions that are far from chemical equilibrium. The Shell gasifier produces a high enough
temperature that chemical equilibrium calculations give a reasonable match to empirical data.
11	The burning of char and tar in the pulse combustor has been proposed (Turdera and Zahradnik, 1992) but not
demonstrated. Here it is assumed to accounL for 15.3% of the total energy released in the pulse combustor.
12	In the present analysis it is assumed that only H20(K) is Che fluidizing agent, since no data are available for
performance with recycled product gas.
13	This allows some significant simplifications in the downstream process design for MeOH or H2 production. In
particular, the low CH4 fraction allows the reforming step to be avoided; CHI, is carried through the process as an
inert gas, is eventually isolated, and then directed to the pulse combustor. The high H2 content permits the shift
reactor to be eliminated (for CHjOH production) or significantly downsized (for H2 produclion).
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Downstream chemical reactors (reformer, shift, MeOH synthesis) were modeled assuming
operating conditions commonly found in commercial processes today. Gas compositions leaving each
reactor were calculated assuming chemical equilibrium. To account for the fact that equilibrium is
never achieved in a real reactor, the temperature selected lor the calculation (called the approach
temperature) in each case differs by a specified amount from the temperature that would be observed
in practical operation.1,1 The equilibrium assumption coupled with the approach temperature concept
is widely used in industrial practice (although is not suitable for biomass gasifier modeling, as
discussed above), as it allows chemical reactors to be accurately modeled without resorting to much
more complex and uncertain methods based on reaction kinetics. The performance levels assumed for
downstream physical separation steps (C02 or H2 removal) were based on vendors' performance
estimates. Typical pressure losses Uirough reactors and heat exchangers were included in the analysis,
as were compressor efficiencies (Katofsky, 1993).
Because a significant amount of heating and cooling of process streams is required between
reactors, how heat exchange is carried out between process streams that need heating and those that
need cooling has a significant effect on overall plant efficiency. To ensure consistent and realistic
modeling of process-to-process heat exchange from one case to another, "pinch" analysis was used
(Katofsky, 1993). Pinch analysis was introduced about a decade ago as a tool to help analyze and
optimize the energy performance of industrial processes (Linnhoff, 1993). Accounting lor practical
inefficiencies of heat transfer, pinch analysis identifies the amount of heat addition and heat rejection
(cooling) needed from external sources, after first systematically matching process streams that need
heating with those that need cooling so as to minimize wastage. In almost all cases considered here,
all of the process heating needs can be met by heat exchange from other, hotter process streams.
Waste heat that remains after this matching is assumed to be used to raise steam for expansion through
a condensing steam turbine to produce electricity for onsite use. Shortfalls in on-site electricity
supply, in heat, and in cooling needs are assumed to be provided from external sources, the energy
requirements for which are accounted in the analysis.
In the case of natural, gas feedstock, the methodology used here gives overall production
efficiencies for MeOH and H2 production that are consistent with estimates for actual commercial
installations at relatively large scale (Moore, 1994)." This lends confidence in the results for
14	The approach temperature for endothcrmic (heat absorbing) reactions, such as steam reforming, is lower than
the temperature that would be observed in a real reactor. For exothermic (heat releasing) reactions, such as
MeOH synthesis, it would be higher than the aciual observed temperature.
15	In smaller facilities, the gains in efficiency that would come from the extensive levels of heat integration
considered here are typically sacrificed to reduce capital costs.
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biomass, for which there is no commercial experience, and for coal, for which there is very limited
experience.
Efficiencies of Fuel Production
Two measures are used here for the energy efficiency of MeOH or H2 production: (i) the
energy ratio (ER), defined as the energy content of the product fuel divided by the energy in the input
feedstock (HHV basis), which takes no account of the energy required to provide electricity or heat
from external sources, and (ii) the thermal efficiency (TE), defined as the energy content of the
product fuel divided by the energy content of all energy inputs to the process, including the feedstock
and additional amounts of feedstock used to generate the electricity and heal requirements not provided
from byproduct process heat or purge gases (see notes (g) and (h) of Table 3). In effect, the TE gives
the energy performance of a facility whose only energy input is the feedstock under consideration.
With biomass, regardless of the gasifier considered, the ERs and TEs for MeOH production
(Table 3) are lower than for H2 production (Table 4). This is also true when the feedstock is natural
gas or coal. The primary reason is that the MeOH synthesis step is more exothermic (heat rejecting)
than the analogous step (shift reaction plus PSA separation) in production (Katofsky, 1993). Also,
all the ERs are higher than the TEs, because external energy inputs are required in all cases.
The efficiencies of MeOH or H2 production from biomass are lower than with natural gas, as
expected, since gasification consumes a non-negligible fraction of the feedstock energy, following
which the syngas is processed in a manner similar to that for natural gas.14 In contrast, the most
efficient biomass-based MeOH production system is about as efficient as when coal is the
feedstock."
The best ER and TE for MeOH or H2 production from biomass arise with the Shell gasifier,
because this produces Lhe largest volume of CO and H2 per unit of biomass input (Table 2). Also, no
energy-consuming reforming step is required because there are no hydrocarbons in the raw gas.
Despite the high efficiencies with this gasifier, the high costs for this option with biomass (discussed
below) make it unattractive relative to alternative options.
14 Our estimate of the TE for CH3OH production from natural gas is slightly higher than other recent estimates
(OPPA, 1989; Wyman et al., 1993), most probably due to our use of pinch analysis to determine external energy
input requirements. Our estimate of the TE for Hj production from natural gas is consistent with present
industrial practice (Moore, 1994).
11 Another analysis (Wyman et al., 1993) of MeOH from coal found an energy ratio of 0.55. This is lower than
the value estimated in the present analysis (0.65), primarily because the Wyman analysis assumed use of a
Texaco coal gasifier, which has a much lower cold gas efficiency than the Shell gasifier (Synthetic Fuels Assoc.,
1983), which is the gasifier assumed here.
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The other directly-heated biomass gasifier, the bubbling fiuidized-bed gasifier, is characterized
by the lowest ERs and TEs of all the options considered, reflecting the relatively large amount of C02
in the product gas (Table 2). Unlike carbon that leaves the gasifier as CO or hydrocarboas, carbon as
C02 is largely unconverted to final product through downstream processing.
The ERs and TEs for the indirectly-heated gasifiers are 5 to 15% higher than for the bubbling
fluidized-bed cases, but less than for the entrained-bed gasifier. Indirectly heated gasifiers produce
considerably less C02 per unit of biomass input than the IGT gasifier, but do produce some
hydrocarbons due to the low operating temperatures (Table 2). With the MTCI gasifier, the
hydrocarbon content is low enough that they can be carried through downstream processing without
using a reformer, as discussed earlier, thereby avoiding reformer efficiency losses. However, the large
steam requirement for fluidizing the gasifier necessitates a large input of fuel gas to the pulse
com bus tor (to heat the fluidizing steam to the gasification temperature), which reduces the energy
ratio. The ER for the MTCI case might be improved by using recycled product gas for fluidization
instead of steam, as discussed earlier.
The efficiency for MeOH production calculated here with the IGT gasifier is consistent with
results of other process studies (OPPA, 1990; Stevens, 1991; Wyman ct al., 1993); Uie efficiency with
the BCL gasifer is lower than estimated in earlier analyses by Katofsky (1993) and by Wyman ct al.
(1993), because improved estimates for the performance of the BCL gasifier have been used here. The
authors are unaware of previous analyses of MeOH production using the MTCI gasifier or of hydrogen
production from biomass using any gasifier.
Costs of Fuel Production and Use
Fuel costs are examined here at the points of production and of sale to final consumers,
measured in $/GJ of fuel, and also in terms of the transportation service provided, measured in
$/vehicle-kilometer (v-km) of driving, for automotive applications. Moreover, two measures are
provided of the cost per unit of service-the fuel cost/v-km, and the total cost/v-km, including the
capital and other operating costs for the vehicle.
Costs of producing MeOH. Estimates of the levelized costs of MsOH produced from biomass, coal
and natural gas are presented in Fig. 3.11 (Table 5 gives details of the cost estimate.) For biomass,
'8 All costs in this paper arc expressed in constant 1991 US dollars using the US GNP deflator (Council of
Economic Advisors, 1994). Cost estimates in Fig. 3 and Tables 5 and 6 assume a real (inflation-corrected)
discount rate of 9.9%/ycar and a real capital charge rate of 15.1%/ycar (based on average financial parameters
for major US corporations from 1984 to 1989).
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the assumed plant capacity is 1650 dry tonnes input/day, corresponding to 3000 tonnes/day of green
biomass (45% moisture).19 For natural gas, the assumed feed rate is 1.64 million Nm3/day-typical
for a large modem natural-gas MeOH plant. For coal, the assumed feed rate is 5000 tonncs/day, so
that the output capacity is about five times as large as for the biomass cases; the larger capacity is
considered because transportation costs for coal are not as scale sensitive as for biomass (due to the
higher volumetric energy density of coal), so that scale economies in the capital cost of the conversion
plant can be exploited with coal.
Installed capital cost estimates (25%) for major unit operations were developed based on
vendor quotes, other studies of MeOH production, and discussions with gasifier developers. Other cost
elements (startup, working capital, maintenance, contingencies, overhead, etc.) are consistent with
those used in other recent studies (Wyman et al., 1993; OPPA, 1990). For simplicity, external
electricity and heat requirements are assumed to be purchased.
The costs presented in Fig. 3 are for "reference case" feedstock costs. The assumed cost of the
biomass feedstock delivered to the conversion facility is S2.0/GJ.20 For natural gas and coal, prices
are assumed to be S4.1/GJ and $1.45/GJ, respectively, which arc likely to be typical lifecycle prices
for industrial customers in the US for the period 2010-2035 (see note (q) of Table 5).21
The lowest costs for MeOH from biomass-$l 1.2-11.5/GJ (see Table 5 and Fig. 3)-are for
indirectly-heated gasifiers. For the Shell gasifier, high capital costs (especially for feedstock
preparation, high-temperature gas cooling, and 02 production), lead to the highest biomass-MeOH
costs. The MeOH cost for the other directly-heated gasifier, the fluidized-bed IGT unit, is also
relatively high due primarily lo the capital costs for 02 production and the lower energy ratio. The
" For comparison, this biomass input capacity is of the same order as that for a modern pulp and paper making
facility or a large canc sugar production facility.
20	In a major US Department of Energy/Department of Agriculture study (Graham ct al., 1995) estimates have
been made of the costs of producing plantation biomass in the US at various levels of supply, with current and
future biomass plantation technology as projected by biocnergy researchers at the Oak Ridge National
Laboratory. A related study carried out by the US Environmental Protection Agency (Tumure et a!., 1995)
estimates biomass prices under the same technical assumptions about yields and costs but also takes into account
the effects of land use competition, which leads to higher land rents and thus higher biomass prices. In the latter
study it is estimated that with current biomass plantation technology (not yet commercial but as demonstrated in
field trials) some 3 EJ/year of plantation biomass could be produced in the US at prices up to S2/GJ, and that the
potential supply at this price would increase to 8 El/year with plantation technology projected for the year 2020.
For developing countries of Africa, Latin America, and Asia, it has been estimated that about 70 EJ per year
could be produced at this price in 2025, assuming that 10% of the area of these regions that is not forest, not
wilderness and not needed for food production in 2025 is available for biomass production (Larson, Marrison,
and Williams, 1995).
21	For comparison, the average industrial prices for natural gas and coal in the US in 1990 were S3.2/GJ and
S1.5/GJ, respectively.
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cost of MeOII from coal is only 10% less than the lowest cost shown for McOH from biomass, even
though the assumed reference feedstock price is 28% less for coal than for biomass, and the capacity
of the coal plant is five times as large as for biomass.
At the average 1990 natural gas price for US industry ($3,2/GJ) the production cost for MeOH
from natural gas would be S8.2/GJ, 27% less than for the least costly biomass case shown in Fig. 3.
However, natural gas prices are expected to rise in most parts of the world. At our reference natural
gas price of S4.1/GJ for the period 2010-2035, McOH from natural gas would be 16% less costly than
from S2.0/GJ biomass.
In some regions (e.g. some developing countries) biomass-derived MeOH would probably be
competitive with MeOH derived from natural gas. For example, it is estimated that 1.7 EJ/year of
biomass (enough to provide 1.0 EJ/year of MeOH) could be produced on 4 million hectares of
plantations in the northest of Brazil at a cost of $1.5/GJ or less/1 Producing McOH there from
biomass at this price and shipping it to Rotterdam would cost the same as MeOH made in Europe
from natural gas costing $5/GJ, 21% above the reference natural gas price.23 Methanol imports of 1
EJ/year would be able to support 60 million fuel cell-powered cars in Europe (about half of the total
number of private cars in the European Union at present).
Producing biomass-derived fuels in excess of domestic energy needs for export markets in
such a fashion could provide sustainably a major source of income for rural areas of developing
countries (Johansson et al., 1993), and competition from such biofuels in world energy markets would
help keep the price of natural gas from rising too much in the long term.
22 Carpcnticri et al. (1993) estimate that 12.6 EJ/year of biomass could be grown at an average productivity of
12.5 tonncs/hcctarc/year on 50.5 million hectares of plantations in the Brazilian northeast, at an average cost of
S1.55/GJ. This total potential production includes 1.7 EJ/year that could be grown at an average productivity of
20.7 tonnes/hcctare/year on the better available lands at a cost of S1.23/GJ. These costs include 85 km of
transport to the conversion facility but do not include the cost of chipping. Chipping costs have been estimated
by Perlack and Wright (1994) to be S5.13/dry tonne or S0.26/GJ of biomass. Thus the total cost of 1.7 EJ/year
of biomass (including chipping.) svouid be S1.5/GJ delivered to the conversion facility.
13 For biomass feedstock costing S1.5/GJ, the plant-gate cost of MeOH would be S10.4/GJ. For delivery to
Rotterdam, the cost of oceanic transport must be added to this production cost. The cost C (in $/GJ) of oceanic
transport of MeOH via large (250,000 dead-weight tons) tankers fueled with fuel oil costing P (S/barrel) for a
round-trip distance of RT nautical miles is given by (USDOE, 1989):
C = 2.03/rr-lO"5 ~ 2.491C-* * l-55-P*riO-7 * 2.59-P10"'.
For transport from the Brazilian northeast to Rotterdam, RT - 12,000 nautical miles. Moreover, the US DOE
projects (ElA, 1995) that the cost of residual fuel oil for transport in 2010 will be S3.24/GJ or S21.5/barrcl.
Thus the transport cost would add S0.30/GJ to the cost of producing MeOH, bringing the total cost or MeOH
produced from biomass in the Brazilian northeast and delivered to Rotterdam to S10.7/GJ—which would be
competitive with MeOH produced in Europe from natural gas priced at S5/GJ.
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Costs of producing H2. Estimates of the levelized costs of H2 produced from biomass, coal and natural
gas, derived in the same manner as for MeOH, arc also shown in Fig. 3. (Table 6 shows details.)
The ranking of production costs for H2 using various biomass gasifiers is the same as for MeOH, but
H2 production costs are as much as 20% less than for MeOH. This is due to significantly lower
hardware costs and to higher efficiency. The difference in hardware costs is attributable to the simpler
technology required: the PSA unit used in H, production costs about as much as the Selexol® unit used
in MeOH production (to remove C02), but replaces both the Selexol® and MeOH synthesis units. The
latter is one of the cosLliest process units at a MeOH production plant.
The estimated cost of producing H- from biomass is less, by a factor of two or more, than the
cost of H, derived electrolytically from water using wind or photovoltaic power sources, assuming that
the long-term cost reduction goals for these power sources can be met (Ogden et al., 1994; Takahashi,
1989).
The natural gas price at which H2 derived from biomass costing $2.Q/GJ (reference feedstock
price) becomes competitive with H2 derived from natural gas is slightly higher than for MeOH ($5.5
vs. S5.4/GJ), whereas the biomass feedstock price at which H? derived from biomass can compete with
H2 derived from coal at its reference price is considerably higher than for MeOH ($2.1 vs. S1.3/GJ).
If global environmental costs associated with fuel production and use (e.g. net C02 release)
were internalized, the economics of biomass-derived MeOH and H2 production would improve relative
to the fossil fuel options, as discussed below.
Consumer costs. The costs seen by the consumer differ from production costs because of the extra
costs of delivering the fuel to the consumer and the characteristics of the vehicle that uses the fuel.
While the cost of producing H2 from biomass or natural gas is about one-quarter less than that
for producing MeOH, the cost of H2 delivered to consumers is only about 6% less than for MeOH,
largely because of the expense of compressing H2 to high pressure at the refueling station (Fig. 4a and
Table 7). But because H2-fueled FCVs would be more energy-efficient than MeOH-fueled FCVs, the
cost of H2 fuel per v-km would be only four-fifths as much as for MeOH (Fig. 4b and Table 7).
Going one step further and considering the total cost of owning and operating the vehicle (in
cenls/km), however, would tip the balance slightly in favor of MeOH, because H2-fueled FCVs would
probably have higher first costs (Fig. 5 and Tabic 9).
Lifeeycle CO, Emissions for Alternative Fuel/Vehicle Combinations
In addition to potential urban air pollution benefits, the use of MeOH or H2 could also lead to
reduced lifeeycle COz emissions (emissions over the entire cycle of fuel production and use) per km of
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vehicle travel, with especially large reductions for FCVs (Fig. 6, with additional details in Tables 8
and 9).
When natural gas is the feedstock, C02 emissions per km of vehicle travel would decrease
relative to a gasoline-fueled ICEV: by 8% for a MeOH-fueled ICEV; by 16% for a H2-fueIed ICEV;
by 56% for a MeOIf-fuelcd FCV; and by 65% for a H2-fueled FCV.
With coal as the feedstock, CO, emissions would increase relative to a gasoline-fueled ICEV
61% and 58% for MeOH and H2 used in ICEVs, respectively, while emissions would decrease 24%
and 34% for MeOH and H2 used in FCVs, respectively.
In the case of biomass grown sustainably, the C02 released in fuel processing and use is offset
by the C02 removed from the atmosphere during photosynthesis. However, since energy inputs
(typically fossil fuel energy) are needed in the growing, harvesting and transport of die biomass, and
in the delivery of the fuel to the end user, total lifecycle emissions, though small compared to fossil
fuel systems, are non-zero. For fuels production based on the BCL gasifier, lifecycle C02 emissions
for FCVs fueled with MeOH24 and H2 are 93% and 85% less, respectively, than for gasoline-fueled
ICEVs, when the external electricity requirements for fuels production are provided by the average
mix of electricity generation.in the US. If instead this electricity were provided by biomass-fueled
power systems (which is the more likely scenario and the one shown in Fig. 6), lifecycle emissions
would be, respectively, 96% and 91% less than for gasoline-fueled ICEVs.15
A carbon tax on net C02 emissions associated with the production and use of automotive fuels
could be used to internalize the costs of global warming. While it is beyond the scope of the present
analysis to estimate the level of tax required to internalize these costs, a useful exercise is to ask what
the tax would have to be to make the cost of fuels derived from biomas equal to the cost of these fuels
derived from natural gas. The results of this exercise are presented in Fig. 7, which shows the cost of
MeOH and H2 production from natural gas, coal, and biomass as a function of the carbon tax on each
of these fuels, assuming reference feedstock prices for natural gas and coal, and biomass feedstock
24	The lifecycle C02 emissions for MeOH produced using the BCL gasifier can also be expressed as 0.089
tonnes of C per tonne of MeOH produced. For comparison, Ellington et al. (1993) recendy estimated that
lifecycle C02 emissions associated with the production cf MeOH from biomass would be 1.24 tonnes of carbon
per tonne of MeOH produced from biomass and used in a vehicle. Ellington et al.'s estimate neglects the
photosynthetic credit associated with biomass grown sustainably. Also, it assumes use of a biomass gasification
technology that is considerably less efficient than (lie gasifiers we have considered here.
25	Lifecycle C02 emissions could be eliminated completely if biofuels were used in place of fossil fuels in the
production of biomass, if the use of artificial nitrogen fertilizers were eliminated (for example by growing
nitrogen-fixing species in plantations), and if ihe downstream compressor work and transport energy requirements
were provided by renewable energy sources.
4-88

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prices of S1.5/GJ and S2.5/GJ as well as the reference feedstock price of $2.0/GJ.26 The carbon taxes
needed to make MeOII and II2 from biomass competitive with these fuels from natural gas are $85/tC
and $95/tC, respectively, for the reference biomass feedstock cost. A carbon tax at such levels seems
substantial, as it would increase the price of the natural gas feedstock by 21-29%. But to the
consumer owning a FCV operated on natural gas-derived fuels, the tax would hardly be noticeable, as
it would increase the cost of owning and operating the vehicle by less than 1.5%. The effect is small
because fuel accounts for a small pan of ihe cost of owning and operating a FCV (Fig. 5). And even
with the tax in place for FCVs, the total cost of owning and operating the FCV would probably be less
than the total cost of owning and operating a comparable gasoline ICEV with or without the carbon
tax (Fig. 5).
Conclusions
Biomass-derivcd methanol and hydrogen offer substantial improvements over conventional
bio'ucls such as ethanol derived from maize, because (i) they can be produced more efficiently from a
given amount of land and with fewer adverse environmental impacts, and (ii) they are well-suited for
use in clean and efficient fuel cell vehicles. Biomass-derived methanol and hydrogen could make
major contributions to energy requirements for road transportation when used in fuel cell vehicles.
Such systems offer attractive economics in the post-2010 time-frame and the potential for very low
emissions of both local air pollutants arid low net C02emissions if the biomass is grown sustairiably.
The development of technologies for producing MeOH and H2 from biomass should be
coordinated with efforts to develop FCVs. The FCV represents an extrordinarily attractive market for
biomass producers, and FCV developers should not hesitate to introduce their new products out of
concern about the availability of fuels suitable for use in FCVs, in light of the prospect of large
potential renewable supplies of cost-compctitivc biomass-derived MeOH and H2.
26 The absolute lifecyclc C02 emissions (indicated in relative terms in Fig. 6) arc: 22,61 kg C/GJ for gasoline;
23.35 and 21.81 kg C/GJ for natural-gas derived MeOH and Hj, respectively; 40.79 and 41.20 kg C/GJ for coal
derived MeOH and H2, respectively; 2.34 and 5.35 kg C/GJ for biomass derived MeOH and H, respectively
(assuming the BCL gasifier with electricity provided by biomass power plants).
4-89

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Table 1. Energy Yield for Alternative Feedstock/Conversion Technologies
Option
Feedstock Yield
(dry tonnes/ha/year)
Tnnspurl Fuel
Yield
(GJ/ha/year)
Transport Services
Yield"
(105 v-kni/ha/year)
Rape Methyl Ester (Netherlands, year 2000)b
3.7 of Rapeseed
47
21 (ICEV)
EthOH from Maize (US)'
7.2 of Maize
76
27 (ICEV)
EthOH from Wheat (Netherlands, year 2000)4
6.6 of Wheat
72
26 (ICEV)
EthOH from Sugar Beets (Netherlands, year 20CO)*
15.1 of Sugar Beets
132
48 (ICEV)'
EthOH from Sugar Cane (Brazil)'
38.5 of Cane Stems
111
40 (ICF.V)
EthOH, Enzymatic Hydrolysis of Wood (present technology)1
15 of Wood
122
44 (ICEV)
EthOH, Enzymatic Hydrolysis of Wood (improved technology)"
15 of Wood
179
64 (ICEV)
McOH, Thormochemical Gasification of Wood1
15 of Wood
177
64/133 (ICEV/FCV)
H2i Thermochemieal Gasification of Wood*
15 of Wood
213
84/189 (ICEV/FCV)
(a)	The fuel economy of the .vehicles used (in liters of gasoline-equivalent per LOO km) are assumed to be: 6.30 for rape methyl
ester (assumed to be the same as for diesel), 7.97 for ethanol, 7.90 for methanol, and 7.31 for hydrogen used in internal
combustion engine vehicles (ICEVs); and 3.81 for methanol and 3.24 for hydrogen used in fuel cell vehicles (FCVs) (DeLuchi,
1991). Note that 1 '.iter of gasoline equivalent = 0.0348 GJ, HHV.
(b)	Per tonne of seed: 370 liters of rape methyl ester plus (not listed) 1.4 tonnes of straw (Lysen el al., 1992).
(c)	For wet milling, assuming ihe US average maize yield, 1989-1992; per tonne of grain: 440 liters of ethanol plus (not listed)
0.35 tonne of stover (out of 1 tonne of total stover, assuming the rest must be left at the site for soil maintenance), 275 kg of
com gluten cattle feed, and 330 kg of C02 (Wyman el al., 1993).
(d)	Per tonne of seed: 455 liters of ethanol plus (not listed) 0.6 tonnes of straw (Lysen et at., 1992).
(e)	Per tonne of sugar beet: 364 liters of ethanol (Lysen et at., 1S92).
(f)	For the average sugar cane yield ir. Brazil in 19S7 (63.3 tonnes of harvested cane stems per hectare, wet weight); per tonne
of wet cane stems: 73 liters of cthajiol (Goldemberg et al., 1993). In addition, (not listed) the dry weight of the attached lops
and leaves amounts to 0.092 tonnes and that for the detached leaves amounts to 0.188 tonnes per tonne of wet stems—altogether
some 1S dry tonnes per hectare per year (Alexander, 1985).
(g)	Per tonne cf feedstock: 338 liters of ethanol plus (not listed) 183 kWh (0.658 GJ) of electricity, present technology; 497 liters
of ethanol plus (not listed) 101 kWh (0,365 GJ) of electricity, improved technology (Wyman el al., 1993).
(h)	For the iixlirectly-heated Baltelle Columbus Laboratory biomass gasificr; per tonne of feedstock: 11,8 GJ of methanol or 14.2
GJ of hydrogen; per tonne of feedstock, external electricity requirements are 107 kWh (0.38 GJ) for methanol or 309 kWh (1.11
GJ) for hydrogen (see Tables 3 and 4).
4-90

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Table 2. Characteristics of biomass gasifiers.
Feedstock
liiomass
Coal

Bubbling
Indirectly-
Indirectly-heated


| Gasifier design
fluid-bed
heated fluid
fast fluidized-
Entraincd-
En trained-

(IGT)'
bed (MTCI)b
bed (BCL)C
bed (She!l)d
bed (Shell)1
Feedstock characteristics





Dry, ash free composition
CHuAmj
CH, 5303as

CH, jjO0i8
CH09;O0 u
HHV (OJ/dry tonne)
19.28
19.40
19.46
19.28
29.69
Initial moisture (%)
45
45
45
45
5
Moisture after drying (%)
15
20
10
11
5
Additional inputs





Gasifier steam (kg/kg dry feed)
C.3
1.37
0.019
0.03
0.03
Gasifier oxygen (kg/kg dry feed)
0.3
0
0
0.45
0.8
Combustor air (kg/kg dry feed)
0
2.52
2.06
0
0
Reactor characteristics





Exit temperature ("C)
982
697
863
1085
1371
Pressure (MPa)
3.45
0.101
0.101
2.43
2.43
Throughput (dry kg/rn^s)
1.9
0.07
4.09
n,a.
n.a.
Solids residence time
minutes
minutes
-1 second
~1 second
-1. second
Product gas characteristics





Yield (kmol/tonne dry feed)
82.0
146.8
45.8
79.3
92.4
Molecular weight (kg/krnol)
22.27
17.65
21.64
20.08
20.49
HHV (MJ/Nm3 raw gas)
8.62
7.52
15.19
9.25
11.53
HHV (MJ/kg raw gas)
8.68
9.55
15.73
10.32
12.61
Composition1, (volume % wet)





h2o
31.8
49.5
19.9
18.4
2.1
h2
20.8
25.3
16.7
30.7
31.8
CO
15.0
11.2
37.1
39.0
64.3
co2
23.9
9.9
8.90
11.8
1.7
ch4
8.2
4.0
12.6
0.1
0
c2+
0.3
0.2
4.8
0
0
Net carbon conversion® (%)
96.2
67.2
75.2
100
>99
Cold gas efficiency11 (%)
82.1
90.0
80.1
85.2
80.3
(a) Institute of Gas Technology (IGT) gasifier data from OPPA (1990). See also Overend, et al. (1994).
(b)	Manufacturing and Technology Conversion International (MTCI) gasifier data from Durai-Swamy et aJ. (1991a).
(c)	Battelle Columbus Laboratory (BCL) gasifer hsat ajid mass balances from Breault and Morgan (1992). Some product gas
is recycled as the fluidizing agent for the gasifier. An earlier analysis of the BCL gasifier by Katofsky (1993), since proven to
be in error, considered the performance of the BCL gasifier at a higher gasification temperature. (The higher temperature was
achieved by supplemental firing of the combustor with some fresh biomass 10 increase the heat production Tate.) Paisley (1994)
indicates that the most efficient operation (highest gas yield) for the BCL gasifier occurs with no supplemental fueling of the
combustor. This is the case considered here.
(d)	Entrair.ed-bed biomass gasification is based on the Shell gasifier, which has never operated with biomass. However, because
of the high operating temperature of entrained beds, this system san be modeled relatively simply assuming chemical equilibrium.
Katofsky (1993) provides details of the performance estimate of this gasifier operating on biomass,
(e)	From Synthetic Fuels Associates (1983).
(0 Small quantities of nitrogen- and sulfur-containing compounds and argon are not shown.
(g) This is the fraction of carbon input as biomass or coai that leaves as synthesis gas.
(ii) Defined as: [the energy content of the product gas (HHV basis)]/(thc energy content of all energy inputs to the gasifier).
4-91

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Table 3. Hent and mass balance result for methanol production from natural gas, biomass, and coal.
Feedstock
Biomass
N. Gas'
Coal

IGT
MTCI
BCL
Shell
steam
Shell
Process
gasifier
gasifier
gasifier
gasifier
reforming
gasifier
Energy Inputs






Feedstock (GJ/GJ methanol product)b
1.77
1.63
1.65
1.48
1.42
1.54
Electricity (kWh/GJ methanol product)






Pumps
1.12
0.01
0.03
0.30
0.08
0.10
Compressors
8.44
35.38
29.72
7.89
13.05
9.37
Lockhopper
1.53
0.00
0.00
1.03
O.CO
0.69
Oxygen*
13.20
0.00
0.00
16.56
0.00
18.92
Total
24.29
35.39
29.74
25,77
13.13
29.08
S Learn (kg/kg dry feed)d
1.02
1.37
0.38
0.92
3.23
1.91
Energy Ratio (ER)'
0.566
0.615
0.606
0.677
0.704
0649
Fraction of Electricity Input From:






Waste heat'
0.615
0.609
0.696
0.309
0.446
0.416 !
Purge gases*
O.COO
0.000
0.000
0.154
0.000
0.248
External sources
0.385
0.391
0.304
0.537
0.554
0.336
Thermal Efficiency*1
0.539
0.568
0.576
0.610
0.674
0.613
(a) Natural gas is assumed to be available at the conversion site at 2.5 MPa and to have the following volumetric composition:
91.7% CH„ 2.8% C2Hs, 0.2% CO;, and 2.3% (N2+Ar).
(b)	Excluding any feedstock burned for electricity production. The heating values of the input feedstocks are as follows. For
biomass (see Table 2) with the IGT-gasifier, 19.28 GJ/dry tnnne; MTCI gasifier, 19.40 GJ/dry tonne; BCL gasifier, 19.46 GJ/'dry
tonne. For nar.1r.1l gas and coal, 39.51 MJ/Nra1 and 29.70 GJ/dry tonne, respectively.
(c)	Production of 99.5% purity O, is assumed to require 480 kWh/:onne, based on 442 kWh/toime for 95% purity (Brown ct al„
1987), plus an additional 9% for 99.5% purity (Klosek et al.. 1986).
(d)	This is the total amount of steam generated for the process, excluding sic am that is used for electricity production.
(c) The energy ratio is defined as: [the energy contort (HHV basis) of the product (methanol or hydrogen)]/(the energy content
of the feedstock input to the process,excluding any additional feed used for electricity production).
(0 Aii waste heat that is available (after meeting as much of the process heating r.eeds as possible) and that is of sufficient
thermodynamic quality is assumed to be used to raise steam at 6.2 MPa and 400 °C. The steam is expanded in a condensing
sream turbine operating with an exhaust pressure cf 0,005 MPa and an iser.tropic efficiency of 75%. A 95% generator efficiency
is assumed. Pinch analysis techniques were used to determine how much of process healing needs could be met with a highly-
integrated process-to-process heat exchange system. (All heating needs could be thus met in the methanol production cases.)
The pinch analysis also provided the magnitudes cf waste heat remaining that was suitable for steam-clectricity generation,
(g)	Purge gases (from the methanol synthesis loop or the PSA loop) are assumed to be used for electricity production with
efficiencies achievable in a gas turbine/steam turbine combined cycle (Katofsky, 1993).
(h)	The thermal efficiency is defined as: [the energy content (HHV basis) of the product (methanol or hydrogcn)]/(the sum of
energy content of all primary-energy inputs to the process). The inputs include the feedstock plus additional feed used to produce
the electricity and heat that must be provided from external sources. No external heat addition is required for any of the methanol
cases. External cooling is required in the fossil fuel cases. Per GJ of methanol product, the cooling energy requirements are
0.260 GJ for natural gas and 0.216 GJ for coal (Katofsky, 1993). We assume "free" external cooling is available, such as river
water, so cooling is not counted in the thermal efficiency. Tie efficiencies assumed for electricity production correspond to
estimates for advanced gas-turbine based power systems using the same feedstock as the methanol plar.t (Katofsky, 1993). For
natural gas (or purge gas), the efficiency (in %) is given by: 39.58 -t- 0.134xMWt, where MW, is the required electrical capacity
in megawatts. For biomass or coal, the efficiency is 37.00 + 0.047xMWt.
4-92

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Table 4. Heat and mass balance results for hydrogen production from natural gas, biomass, and coal.*
Feedstock
liiotnass
N. Gas6
Coal
Process
IGT
gasifier
MTCI
gasificr
BCL
gasifier
Shell
gasil'ier
steam
reforming
Shell
gasificr
Energy Inputs






Feedstock (GJ./GJ hydrogen product)b
lJO
1.32
1.37
1.27
1.11
1.29
Electricity (kWh/GJ hydrogen product)






Pumps
0.99
0.01
0.04
0.29
0.05
0.11
Compressors
7.77
26.21
22.84
6.21
7.69
8.281
Lockhoppcr
130
0.00
0.00
0.88
0.00
0.581
Oxygen*
11.17
0.00
0.00
14.22
0.00
15.871
PSA'
11.88
9.23
8.90
11.62
2.75
11.03
Total
33.11
35.45
31.79
33.23
10.49
35.87
Steam (leg/kg dry feed)d
1.30
1.37
0.95
1.65
2.66
2.99
Energy Ratio (ER)'
0.669
0.759
0.732
0.788
0.897
0.774
Fraction of Electricity Input From:






Waste heat1"
0.109
0.033
0.317
0.032
0.219
0.086
Purge gasesb
0.000
0.000
0.000
0.151
0.000
0.138
External sources
0.891
0.967
0.683
0.817
0.781
0.776
Thermal Efficiency'
0.564
0.611
0.636
0.645
0.844
0.640
(a) fti a" cases the production facility is designed to produce gaseous Jl; at a pressure of 75 bar.
(b)	See note on the item in Table 3 that corresponds to this it*m,
(c)	Electricity use is assumed to be 4.45 kWh/kmole of CO, (ScSomon, 1991).
(d)	This b the total amount of steam generated for the process, excluding steam that is used for electricity production.
(e)	See note (h) to Table 3. External heating is required only for the coal case (0.031 GJ input/'GJ H2), For use in calculating
the thermal efficiency, the efficiency of external heat production is assumed to be 80%. Hxtemal cooling is required per GJ of
product H2 as follows: 0.137 GJ for the MIC I biomass case, 0.014 GJ for the Shell-biomass case, 0.040 GJ for the natural gis
case, and 0.IS? GJ for the coal case (Katofsky, 1993).
4-93

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Tabic 5. Estimated production costs (in 1991$) for methanol from biomass, natural gas, and coal.
FEEDSTOCK -»
BIOMASS
N. GAS
COAL

IGT
MTCI
BCL
Shell
Steam
• Shell
PROCESS
gasificr
gasificr
gasificr
gasificr
reforming
gasificr
Feedstock input capacity






Dry tonnes/day
1650
1650
1650
1650
1224
5000
GJ/hour
1326
1334
1338
1326
2700
6188
Output production capacity'




2012

Tonnes/day
794
868
858
950
4252
GJ/hour
750
820
811
897
1901
4016
Annual feed and output






Feed (106 GJ/year)
10.45
10.52
10.55
10.45
21.29
48.79
Product output (106 GJ/ycar)
5.91
6.47
6.39
7.07
14.99
31.66
Installed Equipment Costs (106 $)






Feed preparation, including drying1'
17.32
13.21
13.17
38.78
0.00
67.96
Gasifier*
29.74
33.72
12.72
29.74
0.00
120.06
High temperature gas cooling*1
0.00
0.00
0.00
39.67
0.00
113.27
Oxygen plant*
21.55
0.00
0.00
28.77
0.00
95.42
Sulfur removal'
0.00
0.00
0.00
0.00
0.00
36.25
Reformer feed compressor8
0.00
15.94
11.88
0.00
0.00
0.00
Reformer11
21.39
0.00
17.20
0.00
50.00
0.00
Shift reactor'
1.98
0.00
2XO
0.00
0.00
0.00
COj removal'
20.20
15.38
14.34
22,05
0.00
59.50
Methanol synthesis & purification11
35.87
38.05
37.75
40.37
66.25
108.54
Steam turbine cogeneration plant1
17.18
22.85
22.12
16.70
17.11
57.67
Utilities/auxiliaries"1
41.31
34.79
32.80
54.02
33.34
164.67
Subtotal
206.55
173.95
163.98
270.09
166.69
823.33
Contingencies"
41,31
34.79
32.80
54.02
33.34
164.67
Owners costs, fees, profits"
20.65
17.39
16.40
27.01
16.67
82.33
Startup"
10.33
8.70
8.20
13.50
8.33
41.17
Total Capital Requirement (106 S)
278.84
234.83
221.37
364.62
225.04
1111.49
Working Capital" (10s 5)
20.65
17.39
16.40
27.01
16.67
82.33
Land" (10s S)
2.08
2.08
2.08
2.08
4.26
7.40
Variable Operating Costs (106 S/ycar)






Feed'1
20.90
21.03
21.10
20.90
87.28
70.74
Catalysts and chemicals'
1.67
0.67
2.24
0.67
2.58
10.87
Purchased energy"
2.77
4.47
2.89
4.90
5.45
15.47
Subtotal
25.33
26.17
26.23
26.46
95.30
97.07
Fixed Operating Costs (106 S/ycar)






Labor'
1.08
1.08
1.08
1.08
1.00
3.14
Maintenance"
6.20
5.22
4.92
8.10
5.00
24.70
General Overhead
4.73
4.10
3.90
5.97
3.90
18.09
Direct Overhead
0.49
0.49
0.49
0.49
0.45
1.41
Subtotal
12.50
10.88
10.39
15.64
10.35
47.34
Total Operating Costs (10* S/year)
37.83
37.06
36.62
42.11
105.65
144.41
PRODUCTION COST (S/GJ of CH,OH)






Capital"
7,50
5.78
5.52
8.19
2.41
5.58
Labor & maintenance
2.40
1.79
1.98
2.31
0.86
1.84
Purchased energy
0.47
0.69
0.45
0.69
0.36
0.49
Feedstock
3.53
3.25
3.30
2.95
5.82
2.23
TOTAL PRODUCTION COST
13.90
11.51
11.24
14.14
9.46
10.14
Natural gas price (S/GJ) for same total cost"
7.23
5.55
5.36
7.40
4.10
4.58
Biomass price (S/GJ) for same total cost as coal* |
-0.12
1.16
1.33
-0,71
n.a.
n.a.
4-94

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Notes to Table 5:
(a)	Based on process energy ratios given in Table 3.
(b)	Feed preparation costs include drying (and pulverizing for the Shell gasificr cases). Costs are scaled from other estimates
according to feed capacity (dry tonne per day, dtpd) raised to the 0.7 power. The other estimates are as follows: for IGT, S18.5
million for 1814 dtpd (OPI'A, 1990); for MTCi, Sl.48 million for 72,5 dipd (MTCF, 1994); for BCL, $7.51 million Tor 740 dtpd
(Ureault and Morgan, 1992); Shell-biomass, $41.44 million for 1814 dtjxl (OPPA, 1990); and for Shell-coal. S94.3 million for
7982 dtpd (OPPA. 1989).
(c)	Gasificr costs arc scaled from other estimates according to feed capacity (dry tor.nc per day, dtpd) raised to the 0.7 power.
The other estimates are as follows: for IGT, $31.78 million for 1814 dtpd (OPPA, 1990); for MTCI, $3.78 million for 72.5 dtpd
(MTCI, 1994), which is for a pressurized icactor (no adjustment is made for the lower pressure unit considered here); for BCL,
$7.25 million for 740 dtpd (Brsault and Morgan, 1992); Shell-coal, $166.6 million for 7982 dtpd (OPPA, 1989). The ShcU-
gasifier with biomass is assumed to cost the same as the IGT gasificr, because both are pressurized and the lower cost associated
with the higher throughput of an cntrained-beri design is assumed to be offset by the higher cost associated with higher
temperature operation.
(d)	For the coal case, the cost of the high-tcmperamre gas cooling system (plus the shift reactor) is scaled from an estimate of
S157.1 million for a plant with a coal feed rate of 7982 dry tonnes per day (OPPA, 1989). A 0.7 power scaling factor is assumed.
For the biomass case, the cost is scaled (using 0.7 factor) from Dial far the coal case according to the heat removal rate in the
gas cooler: 215.6 MW in the coal case and 48.2 MW in the biomass case.
(e)	The cost for oxygen plants (in million 1991S) is assumed to be 0.260x(',0;pd)°'"2, where t02pd is the plant capacity in tonnes
of 99.5% purity oxygen per day. This is based on estimates of the cost of 95% purity oxygen plants sold by the Air Products
Company for use in integrated coal-gasifier/gas turbine facilities (Rrcwn et al., 1987). The plants produce 02 at 3.7 MPa and
include 20 minutes of gaseous oxygen storage. For plant sizes of 1000 tOjpd or larger, the use of dual trains is assumed, each
providing 50% of the capacity. Methanol or hydrogen production requires an 02 purity of 99.5% (or higher). It is assumed that
capital cost increases by 15% to produce O, of 99.5% purity instead of 95% purity (Klosek et al., 1986).
(0 H,S recovery is required with the coal system. This cost has been scaled using a 0.7 power factor according to the feed rate
of dry coal from a baseline cost of S50.3 million for a coal feed rate of 7982 tonnes per day.
(g)	Compressor cost is assumed to be S900 per kW of required capacity. There is no reformer in the MTCI case. The cost here
refers to the cost of the compressor used to raise die pressure of the syngas before it enters the methanol synthesis loop.
(h)	The reformer cost includes costs for boiler fcedwatcr pumps, steam drum, induced-draft and forced-draft fans, all internal heat
exchangers, including exchangers to cool the reformate to ambient temperature, desuliurizing vessels, local piping, controls,
instrumentation, analyzers, initial catalyst charge and water treating equipment. For the natural gas case, the cost is based on
an estimate of Moore (1994). For the other cases, the reformer cost is scaled (using 0.57 power) according to the total heat
exchange duty of the reformer, including all preheating, after-cooling, and steam raising associated with the reformer. The total
duty in the natural gas case is 767,8 MW.
(i)	No shift reactor is required with natural gas or wish the MTCI biomass gasificr. For the Shell gasificr cases with biomass
and with coal, the shift reactor costs are included in the cost of high temperature gas cooling equipment. For the IGT and BCL
gasifier cases, the shift reactor cost is scaled according to the volume How of H, + CO, assuming a baseline cost of S9.02 million
for a flow rate of 8819 kmol/hour and a scaling factor of 0.65 (Moore, 1994).
(j) For Union Carbide's SELEXOL process, leaving approximately 2% C02 in the exit gas. Costs are scaled according to volume
of CO, removal raised to the 0.7 power. The baseline estimate is S14.3 million for 810 kmol/hour or C02 removal Epps (1991).
(k) Estimated cost with the ICI low-pressure methanol synthesis process, including the make up compressor, recycle compressor,
and synthesis loop equipment. A cost estimate of $66.25 million is assumed for a facility with production capacity of 2012
tonnes per day (Moore, 1994). The costs for other capacities have been scaled using a 0.66 power factor (Mansfield, 1991).
(I) The installed cost (in 1991 S/kWt) for a condensing extraction steam turbine cogeneralion system, including a waste heat
boiler, is assumed to be 3785'(M\V>)''1174, where MW, is the electricity generating capacity of the facility. This is based on
estimates of the cost for steam bottoming cycles in the range of 20 to 40 MW, for gas turbine/steam turbine combined cycles
(Tittle et al., 1993).
(m) Assumed to be 25% of the sum of other installed hardware exists (Wyman et a].. 1993; Moore, 1994).
4-95

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(r.) The following percent of installed equipment costs (given by Wyman et a'.., 1993 for methanol production) are adopted here:
contingencies. 20%; owners costs, fees and profit. 10%; working capital, 10%.
(o) Startup costs are assumed to be 5% of installed hardware costs.
(p) The following costs for land, developed from estimates of Wyman et al. (1993), are assumed: for biomass and coal facilities,
land cost (in million 199IS) is 423x(tpd),,u1, where tpd is the dry feed capacity in tonnes per day; for the natural gas case the
land cost (in 1991$) is assumed to be S0.18 per Gl/yr of natural gas feed capacity.
(q) Assuming Icvclizcd costs for delivered feedstocks of S2.0/GJ for biomass chips, S4.1/GJ for natural gas, and $1.45 for coal.
It is expected that the price of plantation bicmass will he no higher than this in many pails of the world by 2010. The assumed
natural gas and coal prices are levelized prices for lite period 2010-2035 based on prices projected for US industrial customers
in 2010 (F.IA, 1995) escalated for 25 years thereafter at rates of 1.0%/year for natural gas and 0.5%/year for coal.
(r) The costs for catalysts and chemicals for the IGT, BCL, and Shell-coal arc those estimated by Wyman et al (1993) scaled
linearly by production rate. The costs for the MTCl and Shcll-biomass cases tire scaled according to the cost estimated by
Wyman et al. for a biomass case using the Koppers-Totzek entrained bed gasifier, which requires no reforming.
(s) Electricity is the only required external energy input. A cost of 5 cents per kWh is assumed. See Table 3 for quantities.
(t) Labor costs arc based on Wyman et al. (1993). For natural gas, Wyman "s estimate is used directly. For solid feedstocks, the
following relationship foT annual labor costs was derived from two BCL cases of different capacities considered by Wyman, et
al: 10sS = 8S9ic(dipd)0?s', where dtpd is the plant feed rate in dry tonnes per day.
(u) Based on Wyman, et al. (1993), maintenance is assumed to be 3% of installed hardware costs, general overhead is 65% of
labor and maintenance, and direct overhead is assumed to be 45% of labor.
(v) Annual capital charge rate of 15.1% is assumed, based on average financial parameters for major US corporations during the
period 1984-1988 (9.91% real rate of return on equity, 6.2% real rate of return on debt, a 30% debt fraction, a 44% corporate
income tax), a property and insurance rate of 1.5% per year, and a 25-year plant life. For land and working capital, the annual
capital charge rate is taken to be 9,91% per year, the corporate discount rate.
(w) This is the price of natural gas at which the total levelized cost of methanol from natural g3S would equal the total levelized
cost of methanol from the alternative feedstock (biomass or coal).
(x) This is the price of biomass al which the total levelized cost of methanol from biomass would equal Die total levclized cost
of methanol from coal, with coal costing S1.45/GJ.
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Tabic 6. Estimated production costs of hydrogen from natural gas, biomass, and coal (in 1991$).
FEEDSTOCK ->
BIOMASS
N. GAS
COAL

IGT
MTCI
ncr.
Shell
Steam
Shc.ll
PROCESS ->
gasifier
gasifier
gasifier
gasifier
reforming
gasifier
Feedstock in input capacity






Dry tonnes/day
1650
1650
1650
1650
1224
5000
GJ/hour
1326
1334
1338
1326
2700
6188
Output production capacity'



1.99
4.62

Million Nm'/day
1.69
1.93
1.87
9.13
GJ/hour
887
1012
979
1044
2422
4790
Annual feed and output






Feed (105 GJ/year)
10.45
10.52
10.55
10.45
21,29
48.79
Product output (103 GJ/year)
6.99
7.98
7.72
8.23
19,09
37.76
Installed Equipment Costs (10' S)






Feed preparation"
17.32
13.21
13.17
38.78
0.00
67.96
Gasifier1
29.74
33.72
12.72
29.74
0.00
120.06
High temperature gas cooling'
0.00
0.00
0.00
39.67
0.00
113.27
Oxygen plant1"
21.55
O.CO
0.00
28.77
0.00
95.42
Sulfur removalb
0.00
o.co
0.00
0.00
0.00
36.25
Reformer feed compressor1
0.00
14.99
11.88
0.00
0.00
0.00
Reformer"1
22.45
0.C0
18.38
0.00
43.91
0.00
Shift reactors'
4.70
5.10
5.01
3.10
9,02
7.28
PSA recycle compressor*
3.66
4.82
2.43
1.61
7.11
16.43
PSA (with C02 removal)'
14,50
16.02
15.63
16.40
30.82
51.39
Hydrogen compressor"1
2.53
5.31
5.82
4.23
9.64
19.22
Steam turbine cogcneration plant
7.84
4.21
15.87
12.04
11.08
37.19
Utilities/auxiliaries'1
31.07
24.35
25,23
43.58
27.90
141.12
Subtotal
155,37
121.74
126,13
217.91
139.48
705.58
Contingencies'1
31.07
24.35
25.23
43.58
27.90
141.12
Owners costs, fees, profits1.
15.54
12.17
12,61
21.79
13.95
70.56
Startup'
7.77
6.09
6,31
10.90
6,97
35.28
Total Capital Requirement (10s S)
209.76
164.35
170,27
294.18
188.30
952.53
Working Capital1" (10s S)
15.54
12.17
12.61
21.79
13.95
70.56
Land" (10* $)
2.08
2.08
2.08
2.08
4.26
7.40
Variable Operating Costs (10' S/ycar)






Feed'1
20.90
21.03
21.10
20.90
87.28
70.74
Catalysts and chemicals'"
1.67
0.67
2.24
0.67
2.58
10.87
Purchased energy8
10.31
13.68
8.38
11.18
7,82
52.55
Subtotal
32.88
35.38
31.71
32.74
97.68
138.80
Fixed Operating Cosisb (10s S/ycar)






Labor
1.08
1.08
1.08
1.08
1.00
3.14
Maintenance
4.66
3.65
3.78
6.54
4.18
21.17
General Overhead
3.73
3.08
3.16
4.95
3.37
15.80
Direct Overhead
0.49
0.49
0.49
0.49
0.45
1.41
Subtotal
9.96
8.30
8.52
13.06
9.00
41.51
Total Operating Costs (105 S/ycar)
42.85
43.68
40.23
45,81
106.68
180.31
PRODUCTION COSTS ($/ GJ of






Capital*1
4.78
3.29
3.52
5.68
1.58
4.01
Labor & maintenance
1.66
1.12
1.39
1.67
0.61
1.51
Purchased energy
1.48
1.71
1.08
1.36
0.41
1.51
Feedstock
2.99
2.64
2.73
2.54
4.57
1.87
TOTAL PRODUCTION COST (S/GJ)
10.91
8.76
8.73
11.24
7.17
8.91
Natural gas price (S/GJ) for same total cost11
7.45
5.52
5.50
7.75
4.10
5,66
Biomass price (S/GJ) for same total cost as coal'
0.66
2.12
2.13
0.16
n.a.
n.a.
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Notes to Table 6:
(a)	Based on die process energy ratios in Table 4.
(b)	The basis for the cost estimate for this item is the same as for CHjOH production—see corresponding note to Table 5,
(e) For the Shell gasifier cases, (his item includes die high temperature gas cooling and the shift reactors, The gas cooling costs
arc the same as for the corresponding methanol production cases, but additional shift reactor capacity is needed for hydrogen
production. Thus, the costs estimated for the methanol case (Table 5) have been increased by an amount representing the added
ccst of the additional shift reactor capacity. The cos: of the additional shift reactor capacity has been estimated by scaling
according to incremental volume flow of H2 + CO using a 0.65 power factor and assuming a baseline cost of S9.02 million for
a flow of 8819 kmol/Iiour (Moore, 1994).
(d)	The reformer cost includes costs for boiler feedwater pumps, steam drum, ir.duced-draft and forced-draft fans, all internal heat
exchangers, including exchangers to cool the rcformate to ambient temperature, desulfurizing vessels, locat piping, controls,
instrumentation, analyzers, initial catalyst charge and water treating equipment. For the natural gas case. The cost is based on
an estimate of Moore (1994). For the other cases, the reformer cost is scaled (using 0.57 power) according to ihc total heat
exchange duly of the reformer, including all preheating, after-cooling, and steam raising associated with the reformer. The total
duty in the natural gas case is 560.13 MW.
(e)	Compressors are assumed to cost $900 per kW of capacity.
(f)	Assuming use of the "Ge'mini-9" pressure swing adsorption system from Air Products, Inc., which removes C02 and H,0 in
a first bed and produces a fuel gas of 99.999% purity H; out of a second bed. The estimated cost for "lie natural gas case is
$30.82 milhon for a hydrogen production rate of 8474 kmol/liour (Moore, 1994). For the other cases, cost arc scaled according
to the hydrogen production rate raised to the 0.7 power. The cost excludes the recycle compressor.
(g)	For external electricity input, a cost of 5 cents per kWh is assumed. External heat input is charged at S4/GJ. Quantities are
given in Table 4.
(h)	This is the price cf natural gas at which the total levelized cost of hydrogen from natural gas would equal the total levclizerl
cost of hydrogen from the alternative feedstock (biomass or coal).
(i)	This is the price of biomass at which the total levelized cost of hydrogen from biomass would equal the total levelized cost
of hydrogen from coal, with coal costing S1.45/GJ.
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Table 7. Summary uf eslimaLed delivered retail fuel prices" (in 1991 $).
Energy carrier
Reform-
ulated
gasoline'
Methanol
Hydrogen
Feedstock
Crude
Biomass®
N. gas
Coal
Biomass*
N. gas
Coal
Feedstock cost (S/GJ)
53.75
($23/bbI)
2.0
4.1
1.45
2.0
4.1
1.45
Cost components for
delivered fuel (S/GJ)







Production"1
6.76
11.24
9.46
10.14
8.73
7.17
8.91
Transport to filling station"
0.99
1.9
1.9
1.9
0.5
0.5
0.5
Filling station cost'
0.61
1.2
1.2
1.2
4.4
4.4
4.4
Delivered retail price (S/GJ)
[5/liter gasoline equivalent']
[5/gallon gasoline equivalent']
8.36
[0.29]
[1.10]
14.34
[0.50]
[1.89]
12.56
[0.44]
[1.66]
13.24
[0.46]
[1.75]
13.63
[0.48]
[1.80]
12.07
[0.42]
[1.59]
13.81
[048]
11.82)
Vehicle type
ICEV
FCV
FCV
Fuel cost per unit of service®
(cents per km)
2.65
1.92
1.69
1.76
1.58
1.38
1.58
(a) Excluding retail fuel taxes.
(b)	Rased oti a projected crude oil price iri die US of S23/barreI in 2010 (EIA, 1995).
(c)	Assumes use of the BCL gasifier for methanol and hydrogen prod action,.
(d)	Production costs for methanol and hydrogen derived frorn biomass, natural gas, and coal are from Tables 5 and 6. For
reformulated gasoline, with 0.132 GJ/gallon, the production cost per gallon is 0.9-($/bbl crude)/42 + 0.25 + 0.15, where 0.9 is
the fraction of a gallon of gzsuline derived from crude oil, 42 is the number of gallons per barrel, S0.25/gallon is the estimated
cost of refining standard formula gasoline and $0. IS/gallon is the additional cost for refining reformulated gasoline (DeLuchi,
1992).
(e)	Sec Ogden, et al. (1994).
(0 The fuel price in S per unit volume of gasoline equivalent is calculated as the S/GJ price limes ihc higher heating value of
gasoline (0.035 GJ/liler or 0.132 GJ/gallon).
(g) This is the fuel price (in S per liter) divided by the gasoline-equivalent fuel economy (in km per liter). The assumed ICEV
is a year-2000 version of the Ford Taurus, having a fuel economy of 11.0 km/liter (25.8 miles per gallon) when operated on
reformulated gasoline. The FCV version of this automobile would have a gasoline-equivalent fuel economy of 26.1 km/1 (61.5
mpg) when operated on methanol and 30.4 km/I (71.6 mpg) when operated on compressed hydrogen (Ogden et al., 1994).
4-99

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Table 8. Technical and cost characteristics of vehicles considered in the analysis*
! Vehicle type ====>
ICEVb
FCV
! Fuel ====>
Ref. gasoline
Methanol
Hydrogen
j Energy storage system
metal tank
metal lank
carbon/aluminum tank"
; Driving range (km)
64 O4
560
400
j Max. power to wheels (kW)°
101
76
76
Vehicle life (km)
193,080
241,350
241,350
Annual vehicle use (km per year/
17,B00
23,800
23,800
Volume of fuel storage and fuel cell system (lit.)6
63
301
310
Weight of complete vehicle (kg)h
1,415
1,328
1,311
Coefficient of drag1
0.28
0.23 I 0.23
Fuel economy (gasoline-equivalent mpg, HHVV
25.8
61.5
71.6
Fuel economy (gasoline-equivalent liters/100 km)
9.1
3.8
3.3
Full retail price of vehicle, incl. taxes (199IS)
17,976
21,709
25,091
Annual vehicle maintenance cost (199IS/yr)
396
389
376
(a) From Ogden, Larson, and DcLuchi (1994), based on DcLuchi (1992) and unpublished updates thereof.
(b)	The gasoline vehicle is a year-2000 version of the 1990 Ford Taurus.
(c)	Carbon wrapped aluminum ultra-high pressure vessel, storing H2 at 550 bar. As storage pressure increases, the bulk of the
storage system decreases but cost increases. This pressure represents a good balancing of these two opposing tendencies.
(d)	The 1990 Ford Taurus has a 16.0-gallon gasoline tank. If in the year 2000 die tank were the same size and ihc vehicle got
about 25 mpg in use, the drvtr.g range would be about 400 miles, or 640 km.
(e)	For the FCVs, the peak power of the motor has been calculated given the peak power of the ICE, the desired high-end
acceleration of the FCV relative tc the high-end acceleration of die ICEV, and the mass, drag, and rolling resistance of the FCV
and ICEV. The ratio of the maximum acceleration of the FCV at 60 mph to the maximum acceleration of the ICEV at 60 mph
is assumed tc be 0.80:1.00. Note, though, that the FCVs would perform better than the ICEVs at low speeds.
(0 It is assumed that the annual use of the FCV is higher than die ICEV because of the lower operating cost (DcLuchi, 1992),
(g)	The volume of the fuel tank plus the fuel cell and methanol reformer.
(h)	Including one passenger and fuel to 40% of vehicle capacity.
(i)Tae	coefficient of drag is assumed to be lower for FCVs than for ICEVs because of the higher value of improving the
efficiency of FCVs, due in turn to the higher cost of fuel storage.
(j) Gasoline-equivalent fuel economy in miles/gallon is calculated as the mile/million-Btu fuel economy of the alternative vehicle
in combined city and highway driving in the year 2000, divided by 125,000 Btu/gallon gasoline (34,830 kJ/liter). HHV indicates
higher heating values for hydrogen and methanol. (On a lower heating value basis, the gasoline-equivalent fuel economy for
hydrogen vehicles is 1.092 times higher than the higher-heating value basis. It is 1.054 times higher for methanol vehicles.)
The mpg fuel economy of the gasoline ICEV has been calculated from a detailed se: of input parameters, including vehicle
weight, powertrain efficiency, aerodynamic drag, the amount of city vs. highway driving, and other factors. The miles/million
Btu fuel economy of the FCEVs were calculated from a detailed set of input parameters, including vehicle weight, powertrain
efficiency, aerodynamic drag, the amount of city vs. highway driving, and other fac:ors. An electric powertrain, consisting of
the motor, controller, and transmission, is at least 6 times more efficient than an ICE powertrain, in combined city/highway
driving (after accounting for regenerative braking). PEM fuel cells are about 45% efficient (after accounting for the energy
consumption of auxiliaries); hence, the fuel cell/electric motor system would be almost 3 times as efficient as the ICE, before
accounting for differences in vehicle weight and aerodynamic drag.
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Table 9. Lifccycle cost of transportation (cents per km, 199IS) for ICEVs arid FCVs.1

Lifccycle Transportation Cost (cents per km)
Break-
even
gasoline
price
(S/gal.)b
Base vehicle,
excluding fuel
storage ar.d fuel cell
Fuel
storage and
fuel cell
Non-fuel
Operating
costs*
Fuel
(excl.
tax)
TOTAL
ICEV fueled with
reformulaled gasoline
11.60
in base cost
6.58
2.65
20.83
n.a.
FCV fueled with

Methanol from






Biomass
9.65
1.88
6.02
1.92
19.47
0.54
Natural gas
9.65
1.88
6.02
1.69
19.24
0.44
Coal
9,65
1.88
6.02
1.76
19.31
0.47
Hydrogen from






Biomass
9.88
2.53
6.01
1.58
20.00
0.76
Natural gas
9.88
2.53
6.01
1.38
19.80
0.67
Coal
9.88
2.53
6.01
1.58
20.00
0.76
(a) All cost components except fuc, are from Ogden, et al (1994). Fuel costs are fro:n Table 7.
(b)	The breakeven gasoline price is the retail price of gasoline excluding taxes (which averaged S0.31/gallon or $0.082/liter in
1991 in the United States) al which the lifccycle consumer cost-per-km of the methanol or hydrogen vehicle would equal that
of the gasoline vehicle. For comparison, the actual pre-tax gasoline price we assumed in our analysis is $I.10/gal'.on (Table 7).
(c)	Includes regular maintenance ar.d repairs, oil consumption, replacement tires, parking and lolls, registration fee, inspection
anc maintenance fee, accessories, and fuel taxes (assumed to be the same, in cents per km, for all cases, based on current US-
average statc-plus-Federal gasoline taxes).
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Tabic 10. Lifccyclc C02 emissions from the production of alternative energy carriers from fossil fuel feedstocks and
their use in alternative automobiles (grams carbon per km of travel).
I
j Energy carrier
Reformulated
gasoline
Methanol
Hydrogen
j
j Feedstock
Crude Oil
Natural Ci3s
Coal
Natural Gas
Coal
Vehicle type*
ICEV
ICEV
FCV
ICEV
FCV
ICEV
FCV
ICEV
FCV
| ACTIVITY
CO, EMISSION'S (GRAMS OF CARBON PER KM OF VEHICLE TRAVEL)"
Gas well CO/
.
1.20
0.57
-
.
0.92
0.38
-
.
Feedstock recovery*
1.77
1.61
0.76
1.14
0.54
1.23
0.51
0.93
0,39
Feed production*
-
1.44
0.68
- ! -
1.10
0.46
-
-
Feedstock transport'
0.81
-
-
0.51 i 0.29
-
-
0.50
0.21
Fuel production*
From feedstock
8.70
9.CO
4.26
60.32
28.54
42.43
17.72
87.21
36.42
External electr.
1.55
3.89
1.84
5.23
2.47
4.27
1.78
14.49
6.05
Fuel transport to
Tefucling station1
0.57
2.18
1.04
1.2.5
059




Compressors at
refueling station'





9.92
4.14
9.92
4.14
End use
58.22
4S.55
22.02
46.55
22.02
-
.
.
.
TOTAL EMISSIONS
Grams C per km
71.61
65.86
31.17
115.08
54.45
59.86
25.CO
113.05
47.21
Relative to
gasoline ICEV
1.00
0.92
0.44
1.61
0.76
0.84
0.35
1.58
0.66
(a)	The gasoline ICEV is a year-2000 version of the 1990 Ford Taurus havcing a fuel economy of 11.0 km/1 (25.8 mpg). The
methanol and hydrogen vehicles would be comparable-duty vehicles. The ICEVs running on methanol and hydrogen would have
fuel economies of 12.4 Jcrr/t (29.1 mpg) and 12.7 km/I (29.9 mpg), respectively. The FCVs cars running on methanol and
hydrogen would have fuel economies of 26.1 km/. (61.5 mpg) and 30.4 km/1 (71.6 mpg), respectively. For details, see Ogdcn
ct al. (1994).
(b)	The following carbon emission rales are assumed in this analysis for fuels (in kg C/GJ): crude oil, 18.73; residua! fuel, 19.42;
gasoline, 18,31; diescl fuel, 18.65; coal, 24.60; natural gas, 13,87; and methanol, 16.41. Carbon emissions from electricity use
are assumed to be 189.72 g C/.kWh, which corresponds to emissions from primary energy sources representing the average mix
of US electric power generating sources (56.34% coal, 9.43% nntural gas, and 3.18% residual fuel), their respective average heat
rates (10.86 MJ/kWh, 10,73 MJ/kWh. and 10.70 MJ/kWh), and transmission and distribution losses of 7.4%. Emissions from
production and delivery of Aids to power plants are also included in the total per-kWh emissions.
(c)	Based on estimated emissions of CO, from natural gas wells of 1,102 gCO^GJ of gas (200 gC/GJ) [Tabic 7, DeLuchi (1991)],
(d)	Estimated energy use during feedstock recovery is as follows, based on Tables 3 and 4 in DeLuchi (1991). Crude oil
recovery: 0.0254 GJ/GJ of gasoline, 13% of which is consumed as crude oil. 14% as diescl fuel, 50% as natural gas, 17% as
electricity, 4% as gasoline, and 10% as residual fuel. For natural gas Tecovcry: 0.0279 GJ/GJ of natural gas. 1% of which is
crude oil, 4% diescl fuel, 92% natural gas, 1% electricity, and 1% gasoline. For coal recovery; 0.0083 GJ/GJ of coat, 5% of
which is crude oil, 48% diesel fuel, 1% natural gas. 37% electricity, 3% gasoline, and 6% coal,
(c) Estimated energy use during feedstock production is as follows, based on Tables 3 and 4 in DeLuclii (1991). Crude oil and
coal; energy requirements arc included in recovery. For natural gas: 0.0245 GJ/GJ of natural gas, 98% of which is natural gas
and 2% is electricity.
(0 Energy requirements by fuel type for crude oil and coal transport arc from Tables 3 and 4 in DeLuchi (1991). Es'.imated
energy use during feedstock transportation is as follows, based on Tables 3 and 4 in DeLuclii (1991). Crude oil: 0.0116 GJ/GJ
of gasoline, 13% of which is crude oil, 7.4% is electricity, and 91.3% is residual fuel. For natural gas, transportation energy use
is zero because the fuel production facilities are assumed to be located at the wellhead. For coal: 0.0075 GJ/GJ cf coal, 1.3%
of which is crude oil, 74.2% of which is dicsel fuel and 25.8% is residual fuel.
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(g)	Energy requirements for fuel production from feedstock nre estimated to be us follows. For gasoline, 0 1847 GJ/GJ of
gasoline, 77% of which is natural gas, 5% is electricity, 1% is residual fuel, and 16% is coal [Tables 3 and 4 in DeLuchi (1991)].
For natural gas and coal, the fraction of feedstock energy not converted to fuel is (I - ER), where ER is the energy ratio given
in Table 3 fcr methanol production and Table 4 for hydrogen production. Tables 3 and 4 also give electricity supplied from
external sources. For methanol these are 7.274 kWh/GJ of methanol with natural gas feed and 9,771 kWh/GJ of methanol with
coal. For hydrogen, these are 8.193 kWh/GJ of hydrogen with natural gas feed and 22.957 kWh/GJ of hydrogen.
(h)	Energy requirements associated with gasoline and methanol delivery to the refueling station are based on Tables 3 and 4 in
Del.uchi (1991). For gasoline, 0.0084 GJ/GJ oT gasoline are needed, of which 6.9% is electricity, 70.5% is diescl fuel, and 22.6%
is residual fuel. For methanol from natural gas. 0.0378 GJ/GJ of methanol ar2 needed, of which 3% is electricity, 26% is diescl
fuel, and 72% is residual fuel. For methanol from coal. 0.019 Gl/GJ arc needed, or which 12% is electricity, 60% is diescl fuel,
and 19% is residual fuel. Transport energy requirements for methanol from natural gas arc higher than for methanol from coal
because Del.ucK assumes that methanol is produced at remote natural gas sites, while methanol from coal is produced much
closer to the point of use. Hydrogen is assumed to be sufficiently compressed at the production facility for pipeline delivery to
the refueling station with no additional energy inputs.
(i)	Wc calculate (using ASPEN PLUS process simulation software) that compression at the refueling station (from 50 to 8400
psia with 85% compressor efficiency) requires 19.06 kWh/GJ of hydrogen.
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Table 11. Lifecycle C02 emissions from the production of methanol and hydrogen from biomnss and their use in alternative
automobiles (grams carbon per km of travel).
Energy carrier
Methanol
Hydrogen
Gasifier type
IGT
kcl
IGT
BCL
Vehicle type*
ICEV
FCV
ICEV
rev
ICEV
FCV
ICEV
FCV
ACTIVITY
CO, EMISSIONS (GRAMS OF CARBO
N PER KM OF VEHICLE TRAVEL)"'
Feedstock Production"
Establishment
0.06
0,03
0.05
0.03
0.05
0.02
0.04
0.02
Fertilizers
1.03
0.51
1.00
0.48
0.89
0,37
0.81
034
Herbicides
0.16
0.08
0.15
0.07
0.13
0.06
0.12
0.05
Equipment
0,07
0.03
0.07
0.03
0.06
0.02
0.05
0.02
Harvesting
3.04
1.44
2.84
1.34
2.50
1.04
2.28
0.95
Hauling
1,00
0.47
0.93
0.44
0.82
0.34
0.75
0.31
Subtotal, feed production
5.39
2.55
5.04
2.38
4.44
1.86
4.06
1.70
Photosynthctic credit'
- 122.03
- 57.74
-113.98
- 53.93
- 100.48 .
- 41.96
- 91.83
- 38.35
Fuel Production'
From feedstock
75.49
35.72
67.43
31.91
100.48
41.96
91.83
38.35
External electricity
from fossil fuels
5.00
2.37
4.84
2.29
15.36
6.41
11.30
4.72
Subtotal, fuel production
.80.49
38.09
72.27
34.20
115.84
48.37
103.14
43.07 '
Fuel transport to refueling
station1
1.25
0.59
1,25
0.59




Compressors at refueling
station"




9.92
4,14
9.92
4.14
End use
46.55
22.02
46.55
22.02
-
-
-
-
TOTAL NET EMISSIONS
Grams C per km
11.64
551 '
11.12 | 5,26
29.72
12.41
25.28
10.56
Relative to gasoline ICEV
0.16
0.077
0.16 | 0.073
0.42
0.17
0.35
0.15
Total net emissions if external electricity for fuel production is generated from biomass1
Grams C per km
6.95
3.29
6.59
3.12
15.29
6.39
14.67
6.13
Relative to gasoline TCEV
0.097
0.0-16
0.092
0.044
0.214
0.089
0.205
0,086
(a) For the fuel economics of the gasoline 1CEV and FCVs considered here see note (a) of Table 10.
(b)	The following carbon emission rates are assumed in this analysis for fuels (in kg C/CJ): crude oil, 1S.73; residual fuel, 19.42;
gasoline, 18.31; diescl fuel, 18.65; coal, 24.60; natural gas, 13.87; methanol. 16.41; and biomnss, 24.50.
(c)	Carbon emissions from electricity use arc assumed to be 189.72 g C/kWh, which corresponds to emissions from primary
energy sources representing the average mix of US electric power generating sources (56.34% coal, 9.43% natural gas, and 3.18%
residual fuel), their respective average heat rates (10.36 MJ/kWh. 10,73 MJ/kWh, and 10.70 MJ/kWh), andT&D losses of 7.4%.
Emissions associated with production and delivery of the fuels to power plants are also included in the total per-kWh emissions.
We have also calculated die carbon emissions associated with electricity production from biomass (instead of fossil fuels). See
note (7) below.
(d)	Assumed biomass yield (U .3 dry tonnes per hectare per year, alter counting harvesting and handling losses) and energy inputs
for short-rotation intensive culture production of hybrid poplar are from Turhollow and Pcrlack (1991). Energy inputs arc as
follows. Plantation establishment requites 14 GJ/ha/yr of dicsel fuel. Fertilizers require 0.24 GJ/lut/yr diescl fuel, 2.810GJ/ha/yr
natural gas, and 25.55 kWh/ha/yr electricity. Pesticides require 0.29 GJ/ha/vr diescl fuel, 0.10 GJ/ha/yT natural gas, and 1.825
4 104

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kWh/ha/yr electricity. Equipment requires 0.17 GJ/ha/yr dicscl fuel. Harvesting requires 7.31 Cl/ha/yr diescl fuel. Hauling
requires 2.4 GJ/ha/yr diesel fuel.
(c) Assumes an uptake of 485.1 kg cf carbon per dry tonne of biomass.
(0 The fraction of biomass feedstock that is not converted to fuel is (1 - ER), where ER are she energy ratios given in Table 3
for methanol production and Table 4 for hydrogen production. Tables 3 ar.d 4 also give electricity supplied from external sources.
For methanol this is 9 35 kWh/GJ of methanol with the IGT gasifier ar.d 9.041 kWh/GJ of methanol with the BCL gasifier. For
hydrogen, this is 29.50 kWli/GJ of hydrogen Tor the IGT gasifier and 21.7i kWh/GJ of hydrogen for the BCL gasifier. This
electricity is assumed to bo provided by the average US electric utility power mix-sec note (c).
(g)	The energy requirements for methanol delivery to the refueling station arc assumed to bo the same as for methanol from coal.
See note (h) in Table 10. Hydrogen is assumed to be sufficiently compressed at the production facility for pipeline delivery to
the refueling station with no additional energy inputs.
(h)	We calculate (using ASPEN PLUS process simulation software) that compression at die refueling station (from 50 to 8400
psia with 85% compressor efficiency) requires 19.06 kWli/GJ of hydrogen.
(i)	The external electricity requirements for fuel production could be met by electricity produced from biomass, rather than from
fossil fuels. The biomass consumption for electricity production is based en a heat rate corresponding to that estimated for a
biomass-gasifier/stoam-injcctcd gas turbine power station. From Figure 5.5 in Katofsky (1993), this heat rate is (in GJ/kWh):
0.0036/(0.3239 + 0.00059*MW(.), where M\Ve is the required electricity production capacity. The external electricity supply
requirements arc given in Tables 3 and 4 for methanol and hydrogen, respectively.
4-105

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Wet Biomass


Drying
and/or sizing
1
'
Gasification
Quench
Gas Cleanup
Steam
Reforming
Shift
Reaction
CO2
Removal

r
Syntf
& Purif
iesis
cation
t
Liquid
Methanol
psah2
Separation
Compression
Gaseous
Hydrogen
Fig. 1. Thermochemical processing steps in the production of methanol (CIi,OH) or hydrogen (Hj)
from biomass. (PSA is pressure swing adsorption.)
4-106

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Gas
-Gas
Biomass
rc\
Steam/Oxygen
(a) bubbling fluidized-bed gasifier
Biomass
r\
rrP\
Steam/Oxygen Ash
(b) circulating fluidized-bed gasi
Product Gas
Flue Gas
rr\
rc\
Steam	Air
(c) indirectly heated gasifier (BCL)
exchange
lubes
Product
Gas
rC\
Steam
(d) indirectly-heated gasifier (MTCI)
Fig. 2. Alternative designs for thermochemical gasification of biomass: two directly-heated gasifiers-a
bubbling fluidized-bed gasifier (a) and a circulating fluidized bed gasifier (b)\ and two indirectly-
heated gasifiers that are being developed in the US. In the twin-fludized bed design (c), pyrolytic
gasification is driven by heat from circulating sand; the sand and char are separated from the product
gas and sent to a char combustor where the sand is heated again. An alternative design (d) uses an in-
bed heat exchanger to provide the heal for pyrolysis and char gasification. In both indirectly-heated
gasifiers steam and (not shown) recirculated product gas, act as fluidizing agents.
4-107

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Shell
MTCi
Shell
BCL SMR
1 I I
Shell MTCI
IGT
BCL She lSMri
Conversion Process

Feedstock
Purchased Energy
Labor & Maintenance
Jff&l Capital
Fig. 3. Estimated total levelized costs (in 1991 USS per GJ) of producing methanol and hydrogen from
biomass (using alternative gasi tiers), natural gas [via steam methane reforming (SMR)], and coal. See
Tables 5 and 6 for details.
4-108

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20
0
g 15
<1)
£ 10
'55

"55
Q
Estimated Delivered Retail Fuel Prices,
Excluding Retail Taxes
Crude Oit
(§1 $3.7S/GJ
i/vyy//-

Biomass
@ S2.0/GJ

Coal
@ $1.4S/GJ

Natural Gas
Gasoline MeOH
H2 MeOH H2
Fuel Type
MeOH
H2
E3 filling Station
El Transport
~ Production
Estimated Fuel Cost per Unit of Service
Oil
Biomass
Coal
Natural Gas
E
XL
©
Q_
C
C)
o
5>
o>
2.5
1.5
0.5
'My//,
////////,
////////¦
fell#
Gasoline
ICEV
MeOH
FCV
H2
FCV
MeOH
FCV
H2
FCV
MeOH
FCV
Fuel and Vehicle Type
H2
FCV
Fig. 4 Costs to consumer for alternative fuels, (a) Estimated retail price (in 1991 US$ per GJ),
excluding retail taxes, of methanol and hydrogen produced from biomass, coal, and natural gas. (b)
Estimated fuel cost to consumer per vehicle-km of transport service. See Table 7 for details.
4-109

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25
B 20
(I)
w 15
10
~ C tax ($95/t)
¦ C tax ($85/t)
Fuel
[U Non-fuel operating costs
ED Fusi storage & fuel cell
0 Base vehicle
Nat. Gas Coal Biomass
Biomass Nat. Gas Cc£
Crude Oil
Feedstock
Fig. 5. Estimated lifecyclc costs (in 1591 US cents per km) for FCVs fueled with methanol and
hydrogen derived from alternative feedstocks, wiih a comparison to the lifccycle costs of an ICEV
fueled by reformulated gasoline. Sec Table 9 for additional details.
Unlike the costs presented in Table 9, a carbon tax has sufficient to equate the lifecyclc costs
for operation with methanol or hydrogen derived from natural gas and biomass has been included.
The tax needed is 585/tC for methanol and S95AC for hydrogen. THis tax would increase the
lifccycle costs for the natural gas FCV cases by less than 1.5%. The effect of die carbon tax for trie
gasoline ICEV is to raise the lifecyclc cost about 3%.
4-110

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LIFECYCLE CARBON DIOXIDE EMISSIONS
FROM ALTERNATIVE ENERGY CARRIERS IN
ALTERNATIVE VEIIICLES
200-
"U
>
150-
(Li
O
o
>
UJ
u
cn
O

g
o
£
Feedstock
Fig. 6. Estimated Iifccycle carbon dioxide emissions from methanol and hydrogen ICEVs and FCVs,
with comparisons to emissions from a gasoline ICEV. See Tables 10 and 11 for details.
4-111

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Assumed carbon tax ($ per tonne carbon)
Fig. 7. The effect of a carbon tax on the cost of transport fuel production for alternative feedstocks.
The costs on the ordinate axis (zero carbon tax) are fuel production costs from Tables 5 and 6 (BCL
case for biomass) for the reference feedstock prices for natural gas, coal, and biomass, as well as
alternative biomass prices of $1.5/GJ and $2.5/GJ. The prices of the alternative fuels with the carbon
tax are calculated by adding to these prices carbon charges for the lifecycle C02 emission parameters
indicated in Tables 10 and 11.

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4-1
The work described in this paper was not funded by the U.S. Environmental Protection Agency The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred.
HYDROGEN FROM BIOMASS VIA FAST PYROLYSIS
E. Chornet, M. Mann, D. Wang, D. Montane, S. Czernik, and D. Johnson
National Renewable Energy T .aboratory
1617 Cole Blvd
Golden, CO 80401
ABSTRACT
The pyrolysis of biomass and steam reforming of the resultant oils is being studied as a strategy for producing
hydrogen. New technologies for the rapid pyrolysis of biomass provide compact and efficient systems to
transform biomass into vapors that are condensed to oils, with yields as high as 75%-80% by weight of the
anhydrous biomass. A process of this nature is potentially cost competitive with conventional means of hydrogen
production. Fast pyrolysis of biomass results in a pvrolytic oil that is a mixture of (a) carbohydrate-derived acids,
aldehydes and polyols, (b) ligriin-derived substituted phenolics, and (c) extractives-derived terpenoids and fatty
acids. The conversion of this pyrolysis oil into H2 and C02 is diermodynamically favored under appropriate steam
reforming conditions.
Experimental work on this project has revolved around srtidying model compounds present within the oil. This
approach was chosen to understand the chemistry of the operation so that catalysis and reforming conditions
could be optimized early on. Microreactor screening results have proven that many of the compounds present
in pyrolysis oils can be steam reformed using commercially available Ni-based catalysts. A mechanistic study
of the catalysis has shown that die reforming process involves gas-phase thermal decomposition of the
oxygenates followed by steam reforming of the intermediate compounds. Initial experiments have shown that
coke formation on the catalyst is difficult to control even with careful choice of temperature profiles and steam-to-
carbon ratios. Recycling the C02 from the PSA unit has been found to shift the equilibrium away from coke to
produce CO and H2, thus offering the possibility of regenerating the catalyst in-situ.
The technical and economic feasibility of producing hydrogen from biomass by last pyrolysis and steam
reforming has been studied in parallel with the laboratory work. Because all necessary experimental data on the
process have not been obtained, the economic assessment performed was preliminary. For many positive biomass
feedstock costs, the selling price of hydrogen produced by reforming the entire biomass pyrolysis oil falls within
the current market price of hydrogen. The economic position of this process depends on whether the pyrolysis
oil can be produced in-house or must be purchased. If an adhesives coproduct can be made, the necessary
hydrogen selling price is competitive with hydrogen produced from conventional processes and is lower than
when no coproduct is produced. Because biomass pyrolysis oil is similar to petroleum crude oil in that many fuels
and chemicals can be derived from it, further coproduct options will be studied according to current economic
and market conditions. The coproduct option was not studied to economically justify producing hydrogen from
a pyrolysis-based process, but is meant to be an example of the opportunities available from biomass pyrolysis
oil once a system of coproducts is developed.
4-116

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INTRODUCTION
The gasification of carbonaceous materials to yield syngas, followed by shift conversion to convert the CO into
II2 and CO2, is a well established process. Currently, hydrogen is commercially produced by catalytically steam
reforming hydrocarbons, particularly natural gas, liquefied petroleum gas, and naphthas. Recent advances in fast
pyrolysis of biomass have prompted us to examine this route as an alternative to gasification and the conventional
hydrogen production routes. The interest lies in converting residual or dedicated biomass to oil in several small
pyrolysis units and transporting the resultant "biocrude" to a large centralized steam reformer to produce
hydrogen.
Pyrolysis differs from gasification in that it is a thermal decomposition process as opposed to a partial oxidation
process. Pyrolysis occurs at liigh temperatures in an inert atmosphere, and the resultant oil can be steam reformed
to produce hydrogen. Fast pyrolysis has not yet been developed to the same stage of commercial demonstration
as gasification, though several pilot plant units have been constructed and operated in recent years (Ensyn-Red
Arrow, Union Fenosa). Pyrolysis is more complex than gasification because it generates a more diversified
product and requires an external heat supply. However, it also has several important advantages. Potentially it
can yield more hydrogen per unit of biomass than a gasification-based process, and fast pyrolysis is carried out
at lower temperatures (450-550°C) than gasification. Further, because pyrolysis oils are easily transportable,
the pyrolysis and catalytic reforming operations can be carried out independently at different locations to
minimize feedstock costs, transportation, and hydrogen distribution. Pyrolysis can also be carried out at a high
temperature (750-850°C), and if steam is added to the reaction chamber, most of the biomass is directly
converted to gases containing a substantial amount of hydrogen. However, as in gasification, this approach also
generates highly refractory polycyclic aromatic tars. Because of that, we favor a two-step approach with pyrolysis
conditions optimized to generate oils free of polycyclic aromatic tars. The second step is the catalytic steam
reforming of the oils to hydrogen.
The oil produced by fast pyrolysis of biomass is comprised of about 85 wt% oxygenated organic compounds and
15 wt% water dispersed in the organic medium (FJliott, 1988). The organic fraction is a mixture of acids,
aldehydes, alcohols, ketones, furans, substituted phenolics, and oligomers derived from the carbohydrate and
lignin fractions of the biomass. Very little ash and residual carbon (i.e., char) are present in the oil when the
appropriate filtration technology is used. Fluid bed fast pyrolysis of poplar can result in a 76 wt% yield of oil
(Piskorz el al, 1988; Radlein el al, 1991). Given that the organic fraction (~R5 wt% of the oil) has an elemental
composition of CH, 3JO0 53, the theoretical maximum yield of hydrogen from pyrolysis oil is 12.6 wt% of the
initial biomass. To address the technical feasibility of converting pyrolysis oil into H2 and CO, via catalytic
steam reforming, we have initiated a research project with the following objectives:
•	Determine, using thermodynamic simulations, the conditions under which the components of the
pyrolytic oils can be steam reformed to H2 and C02
•	Select suitable catalysts to convert the oxygen rich pyrolytic oil into H2 and C02
•	Assess, via bench scale experiments, the yields of H2 (and CO,) as a function of treatment severity,
catalyst type and catalyst time-on-stream
•	Develop a process flow diagram based on the results obtained and carry out economic forecasts as
a function of feedstocks costs, plant configuration, and plant capacity.
In the first year of the project, FY 1994, we addressed the first two objectives (Chomet, et al, 1994). This report
covers the work conducted in FY 1995 and is centered on the mechanistic aspects of the second objective and the
results obtained in the newly constructed bench scale catalytic system. The fourth and fifth objectives are covered
4-117

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as part of a separate effort reported as a distinct paper (Mann, 1995, 1) and summarized here. Further detail on
experimental efforts can be found in a paper by Chomet (1995).
The literature on steam reforming oxygenates is limited to that of simple alcohols (methanol and ethanol) and
oxygenated aromatic compounds (cresols). The extensive literature on steam reforming methane and heavier
hydrocarbon feedstocks suggests that pyrolysis oil, even though a complex mixture, can be steam reformed using
known catalyst preparations. Little is known, however, about the optimal experimental conditions that will lead
to long-term catalyst activity. To address these issues, we need a better understanding of mechanisms of both
the thermal decomposition and catalytic steam reforming reactions shown below:
1.	steam reforming:
CnHm°k +(»k)H2° = nCO +(n+£-k)H2
2.	thermal decomposition (or cracking):
H,0
CnHm°k	> CxHy°z *	C0' CO,,...) + cokt!
Few of the primary pyrolysis products of biomass are thermally stable at the typical temperature of a reformer,
and it is suspected that the catalytic reforming reactions (eq. 1) will be in competition with tliermal decomposition
reactions (eq. 2). Information on the thermal decomposition of model oxygenated compounds in the gas phase
can be found in the literature (Evans and Milne, 1986; Evans and Milne, 1987; Furimsky, I9B3; Rajadurai, 1994;
Schraa et al, 1994; Suryan et al, 1989; Vuori, 1986).
EXPERIMENTAL WORK
We have performed experimental studies on steam reforming reactions of oxygen-containing model compounds
present as major components in the pyrolysis oil. The reaction pathways and relative reactivity of these model
compounds are being examined to determine whether a single catalyst formulation can reform both the complex
and simple oxygenates present in pyrolysis oil while limiting undesirable side reactions that lower hydrogen
yields. Three types of model compounds were examined. Ketones and aldehydes were represented by acetic acid,
acetone, and hydroxyacetaldehyde. The phenolic series included phenol, anisole, o-cresol, resorcinol,
2,6-dimethylphenol, guaiacol, and syringol. The ftiran family of model compounds consisted of fiiran,
2-methylfuran, 2,5-dimethylfuran, 2-furfuraldehyde, furfuryl alcohol, 5-methylfurfural, and
5-hydroxymethylfurfural. In general, the lignin portion of the biomass yields more hydrogen on a weight or mole
basis than the carbohydrate fraction (cellulose and hemicelluiose). Therefore, we expect the oxygenated
aromatics such as furans and phenolics to produce higher yields of hydrogen than anhydrosugars and other
carbohydrate-derived products..
Because there are two undesirable products, CO and CH4, the hydrogen yield obtained will be less than the
stoichiometric maximum according to reactions 1 and 2. The steam reforming of methane is kinetically favored
at higher temperatures. However, this condition also increases the production of CO, which will be converted
to CO; and H2 in a second water-gas shift reactor operating at low temperatures. The formation of coke may
account for a decrease in hydrogen production as well. Some of the oxygenated products derived from the
carbohydrate component of biomass, especially anhydrosugars, are known to dehydrate rapidly to form carbon.
Experiments have been carried out in a vertical, dual bed quartz reactor housed in a tubular furnace with four
independently controlled temperature zones. A molecular beam mass spectrometer (MBMS) was used for real
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time analysis of products. A series of model compounds, pyrolysis vapors and oils, and the major components
of biomass (lignin, cellulose, and hemiceliulose) were steam reformed with the UCIG-90C catalyst Table 1
summarizes some of these results, and shows that complete conversion of all samples was achieved but that in
a few cases, hydrogen yields were far from stoichiometric maximums. In another set of experiments, different
commercially available catalysts were screened for their ability to reform model compounds. All catalysts
performed well, with high conversions (>99%) and H2 yields averaging 89.5% (±5.3%). There was no clear
indication that one catalyst was better than the others within experiment error limits.
Table 1. Catalytic Steam Reforming of Model Compounds, Biomass, and Related Materials"
Sample
MrlHSV
Conversionb
H, yield
CO, yield
methanol
0.015
> 99.95%
95%
93%
acetic acid
0.0081
> 99.95%
86%
90%
HAA (20 wt% in H20)
0.0081
> 99.95%
96%
103%
phenol (20 wt% in MeOH)
0.013
> 99.95%
99%
98%
syringol (20 wt% in MeOH)
0.013
>99.95%
100%
100%
ADP (41 wt% in MeOHf
0.075
99.7%
69%
47%
xylan"
-0.03
> 99.95%
100%
93%
levoglucosand
-0.03
>99.95%
100%
87%
cellulose*1
-0.03
> 99.95%
102%
98%
eellobiose (18 wt% in H,0)
0.0014
> 99.95%
83%
85%
aspen"
~0.0fi
> 99.95%
62%
60%
lignin4
-0.06
> 99.95%
41%
35%
a	Averaged results from triplicates. Reaction conditions werc60rt°C, t=0.25s, S/C=10-13. Catalyst used: UCI G-90C.
b	Limited by the detection capability of the MBMS instrument.. Also see discussion in text,
c	Steam-to-carbon ratio = 4.5.
d	Sample? pyrolyzed in batches of 5-10 nig at 600°C. Residence time before reaching the catalyst bed was about 0.5s.
The effects of different operating conditions on conversion, H2 yield, and catalyst performance were studied using
model compounds. Temperature has the most profound effect on steam reforming reactions. High conversions
(>99.95%) wens obtained for the three small molecules, methanol, acetic acid, and IIAA at 421CC and above.
However, the lignin-derived compound, ADP, was more difficult to reform, and temperatures above 600°C were
required for complete conversion. At temperatures of 421°C, 500°C, and 600°C, conversions were 21%, 81%,
and 99.7%, respectively. These results were compounded by catalyst deactivation as indicated by decreased
hydrogen yields obtained when experiments were repeated using the same catalyst.
Within experimental error limits, varying the residence time from 0.1 to 0.4 s and increasing the steam-to-carbon
ratio from 4.5 to 7.5 did not show significant effects on hydrogen yield at 600°C and M^HSV = 0.075
molj^j-mL,.^^,"1 h"1 (UCI G-90C catalyst). However, methane formation showed significant dependence on
residence time and steam-to-carbon ratio. As the residence time increased from 0.1 to 0.4 s, a decrease in
methane formation was observed with acetic acid and HAA, but both methanol and ADP/MeOH produced more
methane. As expected, less steam also favored the formation of methane. At 700°C, there was no significant
change in hydrogen yield when the steam-to-carbon ratio was increased from 4.5 to 7.5.
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The thermal decomposition reactions of oxygen-containing model compounds were studied. Results suggest that
both thermal decomposition and catalytic reforming reactions take place during steam reforming. Thermal
decomposition of the oxygenates competes with the catalytic steam reforming reactions of both the starting
material and its secondary cracking products in the bed. The thermal cracking reaction may be promoted by the
reactor walls as well as the catalyst support and we found that only a few compounds are stable enough to reach
the catalyst bed without thermal cracking. However, a highly active catalyst, such as the UCI G-90C, can
effectively steam reform all compounds and secondary products into H, and C02. The remaining difficulties are
how to effectively feed the pyrolysis oil into the reactor, and which catalyst will maintain high activity for
extended periods of time; planned future experiments will address these issues.
In addition to experiments conducted in the microscale reactor, tests were also performed in an enhanced and
scaled-up fixed bed steam reforming reactor. These experiments tested the extent of char formation and hydrogen
yield as a function of operating conditions. Two compounds, acetic acid and a 40 syringol:60 methanol (w:w)
mixture, were tested using catalyst UCI G-90C. Some of the results are shown in Table 2. Carbon was formed
on the catalyst bed in all experiments, but the extent of deposition was strongly dependent on the temperature
profile. Around 500°C, only 70% of the carbon in the feed was recovered in the gaseous products. Part of the
char was entrained in the gas stream and collected with water in the condenser. The accumulation of char in the
bed caused the pressure at the reactor entrance to increase continuously during the experiment. In spite of char
formation, however, the catalyst did not lose any activity and the composition of the gas remained unchanged
during the run. The char was reactive enough to be largely gasified by steam when the feed was interrupted.
Increasing the temperature to 600°C at the bed exit improved gas phase carbon recovery to 80% of the feed, and
although char formed at this temperature, it was not entrained in the gas. Char formation was minimal when the
exit temperature was raised to 710°C, and a 98% carbon recovery and constant pressure drop along the catalyst
bed were achieved throughout the 90 minute experiment.
Increasing the stsam-to-carbon ratio to a value of 10 (runs 42 and 43) resulted in a higher carbon conversion and
lower char formation. A further increase to 14.4 (run 44) did not improve the results and resulted in decreased
catalytic activity. Because these three experiments were carried out using the same catalyst bed, this result
suggests that syringol causes significant deactivation of the catalyst. This is consistent with the experience of
sleam reforming naphtha in which the aromatic content of the feed has to be low enough to ensure long term
catalyst survival. Raising the catalyst temperature while maintaining a similar steam-to-carbon ratio to that of
run 38 resulted in a better carbon conversion, however, an increase in pressure drop along the catalyst bed
because of char accumulation was observed (run 46-a).
The accumulated char can be converted to CO by introducing COz into the bed if the temperature is maintained
above 800°C. After 90 minutes of operation (run 46-a), the feed of steam and syringol/methanol solution was
interrupted and 750 seem of C02 were fed to the reactor and the temperature maintained at 830°C in the bed.
After 60 minutes, the char retained on the catalyst surface was completely gasified because no CO was detected
in the outlet gas. When the syringol/methanol mixture was reformed after this gasification experiment, no loss
of catalytic activity from the inital level was observed.
PROCESS CONVERSION EFFICIENCIES
Using an ASPEN Plus™ model of a biomass gasification and reforming process (Mann, 1995,2), the amount
of hydrogen that can be produced from biomass by fast pyrolysis and steam reforming was estimated. Two
methods were used to estimate the efficiency of this process. The first method looks at the ratio of the amount
of hydrogen produced to the stoichiometric maximum amount of hydrogen possible according to the water gas
shift and steam reforming reactions. The second method calculates the ratio of the energy value of the hydrogen
produced and export steam to the energy value of the biomass feed plus purchased electricity. The amount of
4-120

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Tabic 2. Steam Reforming of Model Compounds Using a Commercial Reforming Catalyst (UCIG-90C):
Experimental Conditions, Carbon Balance and Hydrogen Yield
S/C molar Space velocity05	Temp. (°C)	Carbon0' H2 yield mol of gas/LOO mol of carbon feed
Compound	run# ratio Mc,HSV GHSV T-4 T-5 T-6 balance (%) (%)	H2 C02 CO CIL, C,H4
Acetic acid
29
5.9
0.069
2710
476
487
511
73.6
60.8
121.6
60.5
9.2
3.9
0.06

34
5.8
0.069
2721
497
498
520
68.2
57.3
114.7
56.3
9.5
2.3
0.06

25
5.6
0.067
2614
507
535
599
80.1
64.7
129.5
59.9
17.2
2.9
-

26
5.8
0.067
2614
505
533
594
80.8
65.5
131.0
61.0
17.0
2.8
-

24
5.8
0.067
2606
504
547
661
83.9
68.5
137.0
59.0
23.6
1.3
-

27
5.8 •
0.067
2627
508
547
658
87.3
70.5
140.9
60.9
24.9
1.5
-

23
6.0
0.064
2509
510
560
708
88.3
70.9
141.7
59.3
32.4
0.5
-

28
6.0
0.067
2632
510
558
706
88.6
70.9
141.8
58.1
29.9
0.6
-

30
5.7
0.068
2646
548
610
709
91.9
72.0
144.0
58.6
32.8
0.6
-

31
6.1
0.068
2646
555
615
708
94.8
74.8
149.6
59.8
34.4
0.7
-

32
6.0
0.066
2602
608
667
710
97.9
75.6
151.2
58.3
38.9
0.7
-

33
6.0
0.066
2602
617
661
709
97.9
74.0
148.1
56.7
42.5
0.9
-
Syringol and
38
6.1
0.069
2688
609
670
708
94.7
74.6
194.4
52.3
40.3
2.1
_
methanol
42
10.0
0.058
2288
521
617
705
97.5
77.6
202.3
59.0
36.4
2.1
-
mixture
43
10.0
0.059
2313
519
626
703
99.7
79.5
207.4
62.4
35.3
2.0
_
40:60 (w/w)
44
14.4
0.059
2313
513
616
702
96.2
78.2
203.1
61.3
32.6
2.2
0.13

46-a
7.4
0.056
2205
667
755
829
98.5
75.9
197.1
49.3
49.1
0.1
-

46-b
6.9
0.056
2205
667
757
829
98.3
76.5
198.9
49.7
48.5
0.1
-
(l) MC(HSV in	'-h~'); GHSV: methane equivalent gas hourly space velocity in (h*1).
:2) Carbon recovered in the gas-phase products.

-------
hydrogen produced when all of the pyrolysis oil is reformed is 30,415; 304,152; and 1,013,842 standard m3/day
for 27 T/day, 272 T/day, and 907 T/day plants, respectively. Eighty percent less hydrogen is produced in the
phenolic resin coproduct option. The stoichiometric efficiency and energy conversion efficiency of the process
to reform all of the pyrolysis oil obtained from biomass are 55.3% and 86.5%, respectively. For the coproduct
option, these efficiencies are 39.4% and 62.8%. It should be noted that die energy conversion efficiency does not
take into account any of the energy savings that would result in producing phenolic resins from this process
instead of the conventional technology.
ECONOMIC ANALYSIS
The technical and economic feasibility of producing hydrogen from biomass by fast pyrolysis and steam
reforming has been studied in parallel with laboratory efforts. Because all necessary experimental data on the
process have not been obtained, the economic assessment performed was preliminary. Based on feedstock
availability estimates, three plant sizes were studied: 27 T/day, 272 T/day, and 907 T/day. The potential
profitability of the process being studied can be assessed by comparing economic results to hydrogen market
selling prices, currently between $5/GJ and S15/GJ. Results indicate that hydrogen can be produced to compete
with current hydrogen production methods on the large and medium scale. The necessary hydrogen selling price
is highly dependent upon the biomass feedstock cost, and unless very low-cost biomass can be obtained, some
of the scenarios will not produce hydrogen at competitive prices.
Possible sources of error in this analysis are in equipment cost estimation, feedstock and product market
predictions, and invalid economic assumptions. In particular, economic estimates for producing hydrogen from
pyrolysis oil contain a significant amount of error because adequate experimental data are not available.
Furthermore, fast pyrolysis is not fully understood, and the chemistry and yields that can be obtained on a
consistent basis are unknown. The total error can be reduced by looking atTanges of profitability, such as the
range of hydrogen selling price versus a range of biomass feedstock costs. As more information on the
development of biomass-based technologies becomes available, these analyses can be modified to give a more
representative process cost. The material and energy balance results from the ASPEN Plus™ simulation were
used to determine the size and corresponding cost of major pieces of equipment for the gasification-based
process. The estimated capital cost was then scaled to the appropriate size for the pyrolysis-bascd process.
Operating costs for the processes studied include feedstock costs, electricity to run the compressors ($0.05/kWh),
water for steam generation and cooling ($330/m3), and labor. The feedstock cost was assumed to be the cost of
the pyrolysis oil (Gregoire 1992). Economic analyses were conducted for two cases: first, the pyrolysis oil was
assumed to be purchased, and thus includes a rate of return for the producer; second, the pyrolysis oil was
assumed to be produced in-house and thus the cost reflects only that of production. In this make-versus-buy
assessment, the production scenario yields the most profitable results. However, the alternative concept is more
likely for two reasons. Once developed, a regionalized system in which the pyrolysis oil is produced in several
small units will probably involve multiple oil producers. Second, as more feasible coproduct options are
developed, only a portion of the oil will be purchased and used for hydrogen production.
The revenue from steam produced for export is taken as an operating cost credit. The assumption that the steam
will be able to be sold is probably valid for the medium and large plants as they will most likely be located in
more industrialized centers to take advantage of other infrastructure. However, it may be difficult to sell the
steam produced by the small plant, because this size represents small refueling stations located near the demand
4-122

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for hydrogen. In the analysis of the coproduct option, the revenue from selling the P/N fraction is also taken as
a credit. To obtain a conservative result, the selling price of the adhesives coproduct was assumed to be 75% of
the value of phenol.
Tlie capital and operating costs for each of the scenarios studied are shown in Table 3. These costs were
calculated using a feedstock cost of $16.50/T, a representative cost of waste biomass, for the small and medium
size plants and S46.30/T, the expected cost of biomass from a DFSS, for the large plant. For the medium size
plant, operating costs would increase significantly if biomass could only be obtained from a DFSS.
Table 3; Capital (MMS) and Operating Costs (MM$/year) for the Pyrolysis-Based Process

Reforming Entire Oil
Coproduct O
alion
Plant size
sm
mcd
is
sm
med
lg
Operating costs if oil is:
produced in-house
purchased
0.46
1.02
3.31
8.87
18.16
36.56
0.48
1.04
3.49
9.05
18.76
37.18
Fixed
0.16
0.27
0.33
0.16
0.27
0.33
Variable
o.to
1.01
3.37
0.10
1.00
3.32
Byproduct credit (steam) *
-0.10
-0.97
-3.24
-0.08
-0.78
-2.59
Feed if oil is:
produced in-house
purchased
0.30
0.86
3.00
8.56
17.7
36.1
0-30
0.86
3.00
8.56
17.70
36.12
Capital Costs**
3.07
20.2
58.7
2.89
18.2
52.6
* Revenue from adhesives byproduct is not taken as a credit here so that level comparisons can be made.
** Reforming operation only; pyrolysis capital costs are included in the cost of the feed.
The economic feasibility of producing hydrogen by steam reforming oil from fast pyrolysis was studied using the
DCFROR method. This method calculates the internal rate of return (IRR) that will be earned on the initial
capital investment over the life of the project Given this rate and a feedstock cost, the necessary selling price
of the product can be calculated. Often, the IRR is specified as the minimum acceptable rate for an investor to
finance a project; therefore, the perceived risk of the project can be incorporated into the IRR. Because the
process of producing hydrogen from biomass currently carries higher risks than conventional hydrogen-generating
processes, the IRR specified in this study was 15%, while the going rate for conventional processes is between
9% and 12%. All costs and prices are expressed as January 1995 dollars and a 20-year plant life is assumed.
The results of the DCFROR analysis are shown in Figures I through 4. These figures give the biomass feedstock
price that is necessary to compete in the cuirent hydrogen market. A 37% tax rate and a 15% IRR were used to
calculate selling prices. With the market value of hydrogen between $5/GJ and $15/GJ, these figures show that
hydrogen can be produced to compete with current hydrogen production methods on the large and medium scale.
The necessary hydrogen selling price is highly dependent upon the biomass feedstock cost, and unless very low-
cost biomass can be obtained, some of the scenarios will not produce hydrogen at competitive prices. This is
particularly true on the small scale. Many of the processes studied, however, yield competitive hydrogen prices
at reasonable and even high biomass costs.
Figure 1 represents the case of reforming the entire pyrolysis oil (no coproducts} where the feedstock cost was
assumed to be oil purchased from outside suppliers; Figure 2 assumes that the oil was produced in-housc.
Figures 3 and 4 show the necessary hydrogen selling price for the adhesives coproduct option for pyrolysis oil
4-123

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Figure 1: Selling Price of Hydrogen From Steam Reforming
Entire Biomass Pyrolysis Oil, After Tax, 15% IRR
Feedstock Is considered to be purchased
Figure 2: Selling Price of Hydrogen From Steam Reforming
Entire Biomass Pyrolysis Oil, Aftertax, 15% IRR
Hydrogen selling price (S/GJ)
Feedstock Is considered to be produced (n-hou$e

-------
Figure 3: Production Cost of Hydrogen From Steam
Reforming Biomass Pyroiysis Oil and Selling P/N Fraction,
After Tax, 15%!RR
Hydrogen production cost ($/GJ)
Feedstock Is considered to bo purchased
Figure 4: Selling Price of Hydrogen from Steam Reforming
Biomass Pyroiysis Oil and Selling P/N Fraction,
After Tax, 15% IRR
Hydrogen selling price (S/GJ)
4-125
Foodsteck is considered Jo bo produced in-house

-------
that is purchased arid produced, respectively. As expected, the coproduct option is more economically feasible
than reforming all of the pyrolysis oil to produce only hydrogen. Also as expected, the necessary hydrogen selling
price is lower when pyrolysis oil is produced rather than purchased. However, this may not be feasible once a
system to produce various chemicals and fuels from biomass pyrolysis oil is developed. Hydrogen and an
adhesives coproduct can be produced at economically competitive prices for all positive feedstock costs for the
medium and small plants whether the oil is purchased (Figure 3) or produced (Figure 4). At positive feedstock
costs, the hydrogen produced on the small scale can be sold for at least S9/GJ if the pyrolysis oil is purchased,
and at least S3/GJ if the pyrolysis oil is produced in-house.
The most economic size for the processes studied depends upon the feedstock cost. If the medium size plant can
be supplied with waste biomass at a cheaper price (i.e., S16.50/T) than the biomass supplied by a DFSS
(expected to be $46.30/T), the necessary hydrogen selling price from the medium size plant is lower than that
from the large plant. However, if the medium and large plants must both use biomass from a DFSS, the larger
plant is more economically feasible. The medium size plant is more economical than the small plant if biomass
at the same feedstock cost is used in each. Figures 1 through 4 also show that there is a larger economy of scale
realized in going from the small to the medium size plant than in going from the medium to the large size plant
CONCLUSIONS
The added flexibility of pyrolysis offers many opportunities for pyrolysis-based processes to be viable options
for renewable hydrogen production. It can be designed as a regionalized system of pyrolysis units feeding one
centralized reformer or as a combined operation. Additionally, the most economically feasible combination of
coproducts can be used to increase the likelihood of commercialization. Such operations are expected to be
similar to current petroleum refineries in that they would produce a slate of chemicals and fuels.
Although not complete, the experimental work performed to date has provided new insight into hydrogen
production via fast pyrolysis and catalytic steam reforming. Many of the compounds present in pyrolysis oil can
be steam reformed using commercially available Ni-based catalysts. Under the reaction conditions that have been
tested, complete conversion of many of the model compounds has been achieved. However, hydrogen yields for
some of the compounds were not exceptionally high, partly because of problems with sample feeding and the
result of competing reactions. The initial experiments on the bench scale fixed bed tubular reactor suggest that
controlling coke formation is a key aspect of the catalytic steam reforming of oxygenates. The coke formation
is difficult to prevent even by careful choice of the temperature profiles and steam-to-carbon ratio. However, we
have proven that C02 available from the pressure swing adsorption operation can effectively regenerate the
catalyst.
Depending on biomass feedstock costs, the necessary selling price for hydrogen produced by steam reforming
biomass pyrolysis oil falls within the current market values ($5 - SI 5/GJ) for many of the cost scenarios studied.
As expected, the most feasible process is the hydrogen/adhesives coproduct option. Further coproduct options
will be studied to take advantage of the diverse product opportunities of pyrolysis oil. Of the three plant sizes
studied, the 272 T/day plant is the most economic if waste biomass at a low price can be obtained. If biomass
from a DFSS must be used, the 907 T/day plant is more economic. However, if the small plant is the only size
for which cheaper waste biomass can be obtained, local refueling stations, similar to current gasoline stations,
would be feasible. It should be noted that this analysis contains a fairly high degree of process and market
uncertainty which will be reduced as further data become available.
4-126

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Healed Biomass Gasifier." National Renewable Energy Laboratory. Golden, CO. NREL Report TP-431-8143.
(1995,2).
Piskorz, J.; Scott, D.S.; and Radlein, D., "Composition of Oils Obtained by Fast Pyrolysis of Different Woods", in Pyrolysis
Oils from Biomass, E.J, Soltes andT.A. Milne, Eds, American Chemical Society, Washington, D.C. (1988), 167-178.
Radlein, D.; Piskorz, J.; and Scott, D.S., J. Anal. Appl Pyrolysis 19 (1991), 41.
Rajadurai, S., "Pathways for Carboxylic Acid Decomposition on Transition Metal Oxides", Catal. Rev.-Sci. Eng. 36(1994),
385-403.
Schraa, G.-J.; Arends, LW.C.E.; and Mulder, P., "Thermal Decomposition of 23-Diliydro-l ,4-hcn/.c>dioxm and 1,2-
Dimethyoxybenzene," J. Chem. Soc. Perkin Trans. II (1994), 189.
Suryan, MM.; Kafafi, S A.; and Stein, SJ5., "The Thermal Decomposition of Hydroxy- and Methoxy-Substituted Anisoles,"
J. Amer. Chem. Soc. Ill (1989), 1423, and "Dissociation of Substituted Anisoles: Substituent Effects on Bond
Strengths," J. Amer. Chem. Soc. 111 (1989), 4594.
Vuori, A., "Pyrolysis Studies of Some Simple Coal Related Aromatic methyl Ethers," Fuel 65 (1986), 1575-1583.
4-127

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THE HYNOL PROCESS
Robert H. Dorgwardt
Air Pollution Prevention and Control Division
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
ABSTRACT
This paper describes a process currently under evaluation by EPA for production of
transportation fuel from biomass. If biofuel is to significantly impact petroleum displacement
and greenhouse emissions in the transportation sector, maximum yield of fuel energy from the
available biomass supply must be obtained. It will also be necessary to supplement biofuel with
other fuels or leverage its production by use of a cofeedstock. The fuel should also be
compatible with vehicles powered by fuel cells which promise considerable overall future
environmental benefits. Methanol appears to be the best alternative fuel to meet these
requirements, and this investigation is focused on thermocheniical technologies that can increase
methanol yield from biomass by utilizing natural gas as cofeedstock. The process currently under
evaluation produces methanol in three basic steps: hydrogasification of biomass followed by
steam reforming to .synthesis gas and conversion of the synthesis gas to methanol. Hydrogen
derived from the natural gas is recycled to the gasifier to provide part of the thermal energy for
gasification; the remaining energy required for gasification is obtained by heat exchange with the
reformer effluent. This assessment was carried out using the process simulator Aspen Plus. The
assumptions necessary for such simulations are, wherever possible, consistent with those
published elsewhere for other process options. Results indicate that testing iti actual equipment
is needed, with stringent conditions to be met in each process step if the expected efficiency is
to be realized.
This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's
peer and administrative review policies and approved for presentation and publication.
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INTRODUCTION
As reflected by the Alternative Motor Fuels Act of 1988, the Clean Air Act Amendments
of 1990, the National Energy Strategy of 1991, the Energy Policy Act of 1992, and the Climate
Change Action Plan of 1993, a clean alternative transportation fuel is needed to reduce the
environmental, economic, and national security impacts of dependence on petroleum--and the
increasing imported portion thereof. In addition to domestic sources, the desired alternative
should have maximum effect on reducing greenhouse gas emissions from mobile sources which
account for 30 percent of the U.S. total. Methanol is one alternative fuel that has advantages for
achieving these goals because it is relatively inexpensive to produce, has a variety of potential
domestic feedstocks, is very efficient in internal combustion (IC) engines, reduces toxic
emissions, and is compatible with the existing automotive refueling infrastructure.
The cornerstone for achieving these goals is the Partnership for a New Generation of
Vehicles or "clean car initiative" of 1994 which intends to triple the fuel efficiency of current
vehicles. Fuel cells are a leading candidate for this quantum leap in efficiency, and the necessary
technology is being developed for commercial automotive applications by Daimler Benz and by
Ford/DOH. As a liquid, methanol is regarded as the most viable on-board hydrogen source for
fuel cells, and can increase the fuel efficiency by a factor of 2.5 while virtually eliminating toxic
emissions from these vehicles. Conventional technology for methanol production utilizes natural
gas as feedstock which is reacted with steam to form synthesis gas for catalytic conversion to
methanol. Production and-use of methanol by the conventional route results in the emission of
1.74 tons of carbon dioxide (C02) per ton of methanol. By utilizing biomass as feedstock or
cofeedstock, the net emission of CO, can be greatly reduced. If that biomass is produced
domestically, significant economic as well as environmental benefits would accrue. A major
problem that faces the use of biomass to displace petroleum is the limitation imposed by its
availability relative to the amount of fuel energy required by the transportation sector.
Given the constraints on the amount of petroleum that can be displaced by conversion of
biomass (even if all available land suitable for its production were utilized and no competitive
demand for its use were to develop—such as direct combustion to produce electricity), it is
necessary to consider how the available biomass can best be leveraged with another domestic
feedstock to achieve greatest overall displacement of petroleum and concurrent reduction of
greenhouse emissions at lowest cost. Thermochemical conversion of biomass to methanol is
favored by its compatibility with natural gas as a leveraging cofeedstock. There are several
process options by which natural gas can be used for that purpose. The option discussed here
is the "Hynol" process.
THE HYNOL PROCESS
A key mission of KPA's Office of Research and Development is to conduct high-risk,
proof-of-concept R&D to explore promising technologic innovations and to ensure that ideas with
potentially significant environmental benefits are pursued. Of particular importance in this regard
are concepts for which there is no current incentive within the private sector to develop, due to
either lack of current market incentives or absence of regulatory imperatives. This paper reports
the status of EPA's evaluation of a concept patented [I] by Steinberg and Dong In 1994 that
4-129

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produces methanol from biomass and other carbonaceous materials using natural gas as
cofeedstock. In theory, the extra hydrogen provided by natural gas would allow greater
conversion of biomass to alcohol than other processes. The basic flowsheet for the Hynol
process, as presented to the EPA for evaluation, is shown in Figure 1. As shown, the flow sheet
is not thermally integrated and thus does riot include many heat exchangers, heat-recovery steam
generators, drier, distillation column, or condensers that will be necessary for a workable process.
Nor does it include the compressors or air blowers and pumps necessary to overcome the
pressure drops imposed by the various components of the system. The stream compositions
shown assume chemical equilibrium and therefore do not reflect any rate limitations on the actual
conversion achievable in the three reactors. Kach of these factors affects most of the others, and
the net result can be estimated only with the aid of a process simulator. AEERL recently
obtained Aspen Plus for that purpose, and this paper summarizes results of those simulations.
Given the same assumptions as Figure 1, the stream compositions and flow rates are in
satisfactory agreement with Aspen except for the flow rate in the methanol synthesis loop, for
which a value of 272 kmol is obtained instead of the 159 kmol shown. This flow rate represents
a major energy drain and is therefore important.
Biomass Hydrogasification Reactor (HGR)
Although simulation studies are helpful in assessing the basic prospects of a process for
further development, considerable engineering judgment must also be invoked, much of which
is very specific for the unit operations and technologies involved, and a number of such
judgments are necessary in this case. To begin, equilibrium cannot be achieved in any of the
three primary process steps. Of crucial importance is the degree of carbon conversion obtained
in the. first step, hydrogasification of the biomass, which strongly affects methanol yield and cost.
The gasification reactions occurring in the IK>R are:
Because reactions 1 and 3 are unique to this process (which recycles hydrogen derived from the
natural gas), and because of the relatively long residence time of the char in a recirculating
fluidized bed reactor, and the milling effect of the fluidizing medium, a high conversion of
biomass to synthesis gas should be expected.
The operating conditions of Figure 1 impose an equilibrium limit of 87 percent conversion
of the biomass carbon; the rate processes involved with mass transfer in a fluidized bed and
chemical reaction rates of the gasification step will therefore limit the carbon conversion to
substantially less than 87 percent. Consequently it is essential to select conditions that eliminate
equilibrium constraints on biomass conversion. That can be done by increasing the gasifter
temperature above the specified 800"C or by increasing the amount of steam fed to the gasifier.
Increasing the gasifter temperature can be achieved only by raising the temperature of the
primary heat exchanger which, according to Figure 1, is assumed to operate at 888°C (the
temperature necessary to satisfy the energy balance on the gasifier, given the recycle feed rate
of 15.8 kuiols and assuming that the exothermic gasification reaction goes to completion). The
C + 211, = CH4
C + H;0 - CO + H,
C02 + H2 = CO + 11,0
(1)
(2)
(3)
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other alternative, adding additional steam, requires that the heat exchanger temperature be
increased above 888°C for the same reasons. Together, these limitations require that the rate of
the recycle stream fed to the gasifier be increased above 15.8 kmols.
The consequences of increasing the recycle feed to the gasifier are twofold. First, it
reduces the temperature at which the heat exchanger must operate. Second, it increases the
throughput and size of the heat exchanger, the gasifier, and the reformer which directly affect
capital cost. With a gasifier temperature of 800°C, elimination of equilibrium constraints on the
gasifier operating as in Figure 1 will require a minimum recycle feed rate of 20.15 kmols,
including 2.75 kmols of steam. Although these changes increase capital cost, they also increase
methanol yield; higher yield tends to offset the effect of capital cost on production cost. The
degree of carbon conversion attained in the gasifier directly affects the methanol yield of the
process by improving the methanol yield per unit of biomass fed; it also has an indirect effect
of increasing the amount of natural gas that can be fed as cofecdstock, which is a consequence
of the closed-loop configuration of Hynol.
Another consequence of Hynol's closed-loop configuration is its sensitivity to inerts in
the feedstocks. These include nitrogen in the biomass and, more significantly, nitrogen in the
natural gas. Figure I accounts for the former, but not for the latter, which can typically comprise
over 2 mol percent of the natural gas, Inerts accumulate in a closed loop which must therefore
be opened by a purge stream, the flow rate of which increases with total rate of inert inputs.
Although the energy content of the purge stream is recovered as reformer fuel, the methanol yield
of the process is reduced for obvious reasons.
As presently configured, Hynol will utilize an internal cyclone to retain carbon in the
gasifier for a residence time estimated at several hours. The carbon produced is very fragile and
is expected to be reduced rapidly (ca. 10 min) to 100-j.un particles by action of the sand and
alumma used as the fluidizing medium for the biomass The long solids residence lime and small
particle size are expected to contribute to gasification efficiency. Alumina is added to remove
volatile alkalies that otherwise foul equipment downstream. An external thimble type filter will
remove particulate and ash carried over with the gasifier effluent.
Steam Pyrolvsis Reactor (SPR) and Methanol Synthesis Reactor (MSR)
Gases produced by the HGR are reformed to synthesis gas by reaction with steam at
I000°C in the SPR according to the principal reaction:
CH4 + H,0 = CO + 3 H2	(4)
Refinements in the data of Figure I regarding the performance of this step and the subsequent
methanol synthesis step are necessary to obtain a basis for evaluating thermal efficiency and C02
emission of the process. Among them are estimates of the degree to which the equilibrium
stream compositions may be achieved in practice. "Approach to equilibrium" is a temperature
offset that is applied to the equilibrium calculation to account for rate processes that prevent
attainment of true equilibrium within the constraints of reactor residence time. It has minimum
value when the catalyst is new and increases as the catalyst ages: it is determined by experience
4-131

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with a specific system and is therefore unknown for Hynol. The approach to equilibrium in new
conventional catalytic reformers is about 6°C; Katofsky 12] assumes a 10°C value for his
evaluation of the BatteJle-Columbus Laboratory (BCL) system as an average value over a catalyst
lifetime, and that value is taken for these Hynol simulations. Hynol, which operates at a I50°C
higher reforming temperature, can be expected to have a significantly shorter life of the catalyst
and reformer tubes. For this evaluation, the reformer and methanol synthesis reactors are
assumed (consistent with Katofsky) to be -10 and +12°C, respectively.
The flow sheet of Figure I yields methanol containing 27 wt percent water. In order to
reduce the energy requirements for removing that water by distillation and to reduce the
compressor requirements for the gasifier loop, a condenser has been added between the reformer
and methanol converter to remove the H20 component from the synthesis gas which is
catalytically converted to methanol in the MSR by the reaction:
CO + 2H, = CH,OH	(5)
Figure 2 is a thermally integrated flowsheet of the process that takes into account factors
discussed above including approach to equilibrium in each reactor, the pressure drops in each
unit, power consumption, and power generation. It assumes 100 kg dry biomass fed (plus 11 kg
of biomass moisture) and 87 percent carbon conversion with no equilibrium constraint imposed
by the operating conditions of the gasifiei (by adding steam). In accordance with Williams et
al. [3], the natural gas is assumed to contain 2.3 mol percent nitrogen (N2) and 2.8 percent ethane
(C2II0) in addition to methane. Table 1 gives ihe properties of the major streams; Table 2 lists
the power requirements and the power sources. As shown, the process is not expected to be self-
sufficient with regard to electric power requirements when the biomass carbon conversion is 87
percent. The integrated flowsheet contains a hcat-rccovery steam generator that burns the
nnieacted char from the gasifier: the electricity thus produced is significant. Table 2 shows that
the compressor for the methanol synthesis loop (C2, Figure 2) is, by far, the largest power drain.
That is because of the large flow rate of that stream and the high pressure drop across the
methanol reactor, which is taken to be 8 1 arm, in accordance with Katofsky 12], for a
conventional reactor. Because of the relatively low pressure at which Hynol operates, it would
be particularly advantageous to utilize the newer liquid-phase methanol reactor currently being
demonstrated by Air Products Corp. f4] which has a pressure drop of only 2.4 atm. If the liquid
phase methanol reactor is used for Hynol, and assuming that it can attain the same approach to
equilibrium, the total power requirements are reduced from 103.5 kWh per 100 kg dry biomass
feed to 65.4 kWh, and the process becomes a net exporter of electric power rather than an
importer.
THERMAL EFFICIENCY
The following performance parameters are calculated from the data of Table 1:
Energy ratio = GJ methanol/(GJ biomass + GJ natural gas) = 0.667
Thermal efficiency (conventional MSR) = GJ inelhano!/(GJ CH4 t GJ C3Hfi + GJ biomass t GJ
imported electricity/0.3985) = 0.646
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Thermal efficiency (liquid-phase MSR) - (GJ methanol + GJ exported electricity/0.3985)/(GJ CH,
+ GJ C2H6 + GJ bioinass) = 0.680
Corresponding values of energy ratio for other methanol processes are 0.606 and 0.704
for BCL and conventional steam reforming, respectively. Thermal efficiency of those processes
are 0.576 and 0.674, respectively [3].
C02 EMISSION REDUCTION
The objective of I-Iynol is to achieve maximum displacement of gasoline and maximum
reduction of net C02 emission from a vehicle fleet. Assuming initially that the methanol
produced by Hynol is utilized in conventional IC engines, and assuming as a basis 7.156 mols
of methanol produced according to Figure 2, but using liquid-phase methanol unit, the following
reduction of CO, emission would be obtained from a vehicle fleet using that fuel:
Gasoline displaced	= 48.5 gal (184 liters)
C02 emission avoided from gasoline = 436 kg
C02 emission from natural gas used = 287 kg
Net emission reduction	= 149 kg
A net greenhouse gas reduction of 34 percent is therefore expected for conventional
veh:cles. The greatest effect will be achieved when those vehicles are replaced by future cars
powered by fuel cells which, using methanol as hydrogen carrier, are expected to achieve a fuel
efficiency 2.5 limes that of gasoline. In that case, ihe gasoline displaced will be 95 gallons (360
liters) and the greenhouse gas reduction from the vehicle fleet will be 65 percent.
TECHNICAL HURDLES
A critical component of the process is the primary heat exchanger which must raise the
temperature of the recycle stream to 81 l°C entering the gasifier. A high-temperature ceramic
heat exchanger similar to that developed by Hague International and soon to be demonstrated at
the Warren Station of the Pennsylvania Electric Company under the DOE Clean Coal Program
is expected to be applicable to these conditions [5] and should permit an approach within 50"C
of the reformer effluent temperature. In that case, carbon conversions above 90 percent should
be attainable.
A problem inherent with thermochemical biomass-to-methanol processes that has not been
fully addressed by either Hynol or BCL is the fact that the gasifier effluent must be cleaned of
hydrogen sulfide (H2S). Although the sulfur content of biomass is relatively low (0.05 to 0.15
wt percent) the H2S content of the gasifier effluent will be several hundred ppm, much too high
for conventional reformer or methanol converter catalysts which can tolerate no more than 0 I
ppm. Ideally, hot gasifier effluent would go directly to the reformer without cooling.
Desulfurization by conventional methods such as zinc oxide or zinc titanate will require cooling
to 400 or 700"C, respectively. The effectiveness of these sorbents is reduced by high partial
pressures of water vapor which is very high in both Hynol and BCL systems. The intended
approach for Hynol is to attempt to utilize noble metal catalyst in the reformer which is less
4-133

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sensitive to sulfur poisoning, Dcsulfurization will then be carried out after reforming and heat
recovery prior to methanol synthesis which occurs at a lower temperature.
Conventional steam reformers operate with a steam/carbon ratio in the feed stream of 2.5-
3.5; the ratio corresponding to the data of Figure 2 is only 0.75. A high steam/carbon ratio
prevents carbon formation on the reforming catalyst which will reduce its efficiency and
eventually terminate operation. The high hydrogen content of Hynol's reformer feed stream is
expected to reduce the necessary steam rate, but the amount of steam that will be required to
avoid carbon deposition in the reformer tubes is unknown at this point. Additional steam will
increase the reformer heat load, reduce the energy ratio, and increase COz emissions.
This paper stresses the importance of achieving maximum carbon conversion in the
biomass gasification step. This variable directly affects the maximum yield of methanol by the
process; it also indirectly affects the yield by limiting the amount of natural gas that can be fed
as cofeedstock. If, for example, 95 percent carbon conversion is obtained, the methanol yield
could be increased from 7.15 mols (Figure 2) to 7.6 mols; if the conversion is only 72 percent,
the methanol yield will be only 6.25 mols per 100 kg dry biomass fed. Laboratory studies
carried out at Brookhaven for the EPA in 1992 [6] indicate that biomass may attain carbon
conversions in excess of 90 percent in 1 minute when gasified with hydrogen at Hynol
temperature and pressure. That is the reason for expecting that the process may achieve greater
conversions than other gasification processes, given the long solid residence times expected.
Kinetic studies currently .underway at EPA, using a ihermobalance reactor designed by the
Institute of Gas Technology, have not yet been able to confirm the Brookhaven carbon
conversions. Questions about the thermal efficiency, methanol yield, and relative performance
of Hynol can tie answered only with data from tests in a more realistic fluidized bed gasifier.
Construction of a 23 kg/lir (biomass) test facility is expected to begin this year to obtain the.
operational data required for answers to these questions.
ACKNOWLEDGEMENT
Support for this project by the Department of Defense Strategic Environmental Research
and Development Program (SERDP) is gratefully acknowledged.
REFERENCES
1.	Steinberg, M. and Y. Dong "Process and Apparatus for the Production of Methanol from
Condensed Carbonaceous Material," U.S. patent No. 5,344,848 (September 6, 1994).
2.	Katofsky, R.E. "The Production of Fluid Fuels from Biomass," PU/CESS Report No. 279,
Center for Energy and Environmental Studies, Princeton University, Princeton, NJ (June 1993).
3.	Williams, R.H.; Larson, E.D.; Katofsky, R.E.; and J. Chen "Methanol and Hydrogen from
Biomass for Transportation," presented at Bioresonrees '94 Biomass Resources: a means So
sustainable development, Bangalore, India (October 3-7, 1994).
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4.	"Liquid-Phase Methanol Process Development Unit (PDU)--40-Day Run at LaPorte, Texas
(1984)" Report EPRI-AP-4430, Electric Power Research Institute, Palo Alto, CA (January
1986).
5.	Young, S.. Hague International, Kennebunk, Maine, personal communication (April 1995).
6.	Steinberg, M.; Kobayashi, A.; and Y. Dong "Rates of Reaction and Process Design Data for
the Hydrocarb Process," Report EPA-600/R-93-020 (NTIS PB93-155976), U.S. EPA, Air and
Energy Engineering Research Laboratory, Research Triangle Park, NC (January 1993).
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TABLE 1: PRINCIPAL STREAM PROPERTIES OF FIGURE 2
(


Stream coinpositior
, mols



1 Stream
j Nil.
Stream description
Temp.,
°C
Pressure,
atm*
Flow
CO
C02
CH4
H20
H2
N2
C2H6
CH30H
1 1
Dried biomass feed
25
1
111 kg
0
0
0
0.617
0
0
0
0
2
Unreacted carbon
800
29
0.549 inol
(i
O
0
O
0
0
0
0
3
Gasitier effluent
800
29
24.9 mol
2.545
1.165
5.07K
4.334
10 242
1.56
0
0
4.
Steam to reformer
527
28
5.1 mol
0
0
0
5.1
0
0
0
0
5
Natural gas from grid
25
30
109 kg
0
0.0131
6.189
0
0
0.1452
0.1821
0
6
Natural gas to process
180
28
62 3 kg
0
0.0075
3.538
0
0
0.0806
0.1047
0
7
Reformer elfluen;
1000
24.8
46.5 rnol
9.39
0.712
2.44
3.51
28.82
1.64
0
0
8
Feed co methanol loop
50
22 J
43.2 mol
9.39
0.712
2.44
0.20
28.82
18.56
0
0
9
Methanol reactor feed
54
41.2
258 mol
32.51
5.19
27.52
0.24
171.0
o
00
0
2.51
10
From methanol reactor
260
32.5
243 mol
25.36
4.94
27.52
0.49
156.0
18.56
0
9.90
1 i
Methanol loop recycle
49
41.2
214 rnol
23.12
4.48
25.08
0.04
142.2
16.92
0
2.51
12
Methanol product
40

7.181 mo

0
0
0
0.031
0
0
0
7.15
13
Column bottoms
98

0.41 mol
0
0
A
U
0
0
0
0
0.01
14
Purge to reformer
40
30
1.0 mol
0.107
0.021
0.117
2E-4
0.6638
0.079
0
0.0117
15
Steam to gasifier -
236
30.5
2 8 mol

0
0
0
2.8
0
0
0
0 !
16
Recycle to gasifier
8i 1
29.5
22.55 mo

2 :3
0.411
2.311
2 SO
13.10
1.56

0.23
17
Air to reformer furnace
25

32 5 mol
0
0
0
0
0
25.7
0
0
a I aim = 98 kPa

-------
TABLE 2: ELECTRIC POWER CONSUMPTION
Power requirements, kWh	Power produced, kWh
Methanol loop compressor
56.9
HRSG-1, TG-I
6.8
Gasifier loop compressor
24.3
HRSG-1, TG-2
8.0
SPR furnace air blower
11.4
HRSG-2, TG-2
42.4
Drier steam recycle blower
4.5
HRSG-3, TG-2
19.9
HP boiler fcedwater pump
1.9
TG-3
5.6
Lock hopper
1.7


IP boiler fcedwater pump
1.3


Char combustor air blower
1.0


LP boiler feedwater pump
0.4


Cooling water pump
0.1


Total power	103 5	82.7
Steam
Methanol Water
201.4 kg 75 3 Kg
FIGURE 1. BASIC FLOWSHEET OF THE HYNOL PROCESS
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FIGURE 2: THERMALLY INTEGRATED HYNOL FLOWSHEET
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SESSION V: RENEWABLES AND ADVANCED ENERGY EFFICIENT, END-USE
TECHNOLOGIES
5-A
Thomes D. Bath, Chairperson
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should he inferred.
GREENHOUSE GAS MITIGATION: THE POTENTIAL OF RENEWABLE ENERGY
Thomas D Bath and Jack Stone
National Renewable Energy Laboratory
1617 Cote Boulevard
Golden, CO 80401-3393
ABSTRACT
This paper reviews the opportunity for various forms of renewable energy lo reduce
emissions of greenhouse gases (GHG), both domestical ly and internationally. It builds on the
results of earlier work (ca 1990) by several groups intended to explore this potential. Those
earlier studies showed that these technologies could play a significant role in the longer term
(beyond 2010). Key factors influencing current expectations for these technologies arc discussed.
These include technology progress, energy market characteristics, and the influence of energy and
environmental policies. Our general conclusion is that major changes in all these areas are
necessary to reduce domestic and global GHG emissions through the deployment of renewable
technologies.
INTRODUCTION
During 1989-90, a number of studies [1, 2, 3] assessed the opportunity for renewable
technologies to contribute to U.S. energy markets during the coming 20-40 years. These studies
generally agreed that, under accepted market forecasts, if the performance of these technologies
could be improved, they would become substantial contributors in the 2010 2030 time frame
(Figure 1). Although the studies differed in their conclusions about energy efficiency, they
concluded that renewables could contribute 15%-20% of U.S. energy supply by 2010 and about
20%-40% by 2030. A key factor in the future contribution of renewables in these studies was the
projected rate of improvement of renewable technology performance. At least one study [1] saw-
improved performance as resulting from increased funding of research, development and
demonstration (R.D&D) by the federal government. Translating the results of these studies to
GHG gas emissions was not too difficult Most analysts felt that if the United Stales were to
continue economic growth, then a mixture, of increased renewable energy use and improved
energy efficiency would be required to achieve GHG emission goals. America \s Energy Choices
[3] projected a 10% reduction of carbon dioxide (the major GHG) emissions by 2010, roughly
three-fourths due to efficiency improvements and the remainder due to renewable energy
deployment. Here again, the rate of advancement of renewable technology performance was key,
CHANGES SINCE 1990
Given the previous thinking described above, it is worthwhile to review what actually has
happened since then and whether it alters our outlook on the futur e opportunity for renewables lo
5-1

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reduce GHG emissions. Three key factors need discussion: (1) advancement of conventional and
renewable energy technologies, (2) changes in energy policy, and (.1) GHG mitigation policies.
Technology Advancement
Key to the outlook described above was the accelerated advancement of renewable
technologies. The Interlahoratory White Paper [1 ] predicted a correlation between enhanced
R,D&D funding and the improvement of technology performance. Funding enhancement was
provided, and corresponding technology improvement was realized. Two examples are provided:
(1) Wind technology funding outstripped the Intensified R,D&D scenario (Figure 2) and during
the same period, wind energy system costs were lower than predicted for the scenario (Figure 3);
and (2) PV technology funding was less than the Intensified R,D&D scenario (Figure 4), and
actual costs were close to those forecast (Figure 5). During the same period, technologies for
exploration and production of oil and gas, largely funded by the private sector, also made
significant improvement. This is best made visible in Figures 6 and 7, which show the Energy
Information Agency (EIA) price trajectory expectations for world oil prices and U.S. well-head
natural gas prices. Overall, these data suggest a 12- to 15-year slippage for these key energy
prices to increase to a given target level as compared to 1990 forecasts This is largely due to
technology improvement. Thus, although renewable technologies improved as expected, their
competitive position has not done so, because of advancements in technology for oil and gas
exploration and production.
Energy Policy Changes
Passage of the Energy Policy Act of 1992 (EPAct). intended to implement the results of
the National Energy Strategy (NES) [2], instituted several policies intended to drive down the
price of conventional energy. Key among these were the provisions revising the Public Utility
Holding Company Act to encourage price competition for electricity by creating a new class of
suppliers- the exempt wholesale generators (EWGs). Also, the tax provisions of EPAct made
participants in natural gas partnerships exempt from flic Alternate Minimum Tax, increasing
capital available for field development and depressing gas prices. Tax provisions in EPAct
favoring renewables have had little impact because of the general decline in conventional energy
prices.
Greenhouse Gas Mitigation Policies
The voluntary nature of U.S. policies for greenhouse gas mitigation has not created
sweeping change in U.S. energy markets because these markets are increasingly competitive and
driven by price factors. This has made large-scale, tangible progress difficult to achieve both
domestically and in negotiations with other nations.
THE RESULTS
Recent changes in the outlook for U.S. energy markets have created a situation in which
neither energy efficiency nor renewable energy is anticipated to make the contributions that were
5-2

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seen as possible in 1989 90. Table 1 contrasts 1990 forecasts of U.S. energy consumption in
2010 with those made recently by the EI A Only 25% of the projected improvement [2] in energy
efficiency and 30% of the increased contribution by rcnewables [3] are anticipated by the 1995
EIA AnmialEnergy Outlook [4], indicating a overall 20% increase in U.S. carbon emissions due
to combustion of fossil fuels, as compared to 1990 carbon emissions.
Energy is a component of nearly all economic activity. Thus, the lower energy prices
embodied in the 1995 outlook act to reduce the costs of economic output, making U.S. products
more competitive in global markets. This improvement in competitiveness comes at the expense
of a number of risks—strategic and economic, as well as environmental Strategic risks derive
from our increasing dependence on imported petroleum and our resultant vulnerability to
politically motivated price manipulation of world oil prices. Economic risks are driven by
dependence on a less diverse supply of ultimately finite energy resources, particularly for the
production of electricity. Environmental risks derive from the continued use of coal, petroleum,
and natural gas-the apparent economic winners over the coming 15 years. Their use is the source
of a variety of pollutants related to public health concerns as well as carbon dioxide and methane
emissions related to global wanning. Nearly all energy analysts would conclude thai by
emphasizing price factors, U.S. energy policy has not only discounted these strategic, economic,
and environmental threats but, essentially, has made impossible any improvement in GHG
emissions under the present voluntary programs.
FUTURE OPPORTUNITIES
In order to stabilize or reduce greenhouse gas emissions, the United States must consider
policy and economic opportunities that displace overall the use of fossil fijel resources with
energy efficiency and renewable energy There are four categories of actions that can lead to this
outcome: (1) technology policy, (2) economic policies, (3) energy and environmental regulation,
and (4) export opportunities.
Technology Policy
The observed success in improving the performance of renewable (and energy efficiency)
technologies suggests that further investments in advancing these technologies may bear fruit.
Although federal leadership is a necessity here, a careful review of opportunities for advancement,
federal/private role, and contributions to risk reduction should inform investment and policy-
decisions in (his area, rather than the ideologic concerns flavoring the current debate.
Economic Policies
The U.S. energy market is replete with subsidies and tax policies intended to send low
price signals to consumers. The United States should (1) intentionally reduce the fossil energy
subsidies present today because they are far larger than nonfossil incentives and because the price
outlook seems to favor fossil fuels, and (2) the United States, in the context of tax reform, should
consider the taxation of fuel consumption as a revenue source. Figure 8 shows that the United
States is out of step with most developed nations in this regard, weakening the U. S. posture in
GHG mitigation negotiations.
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Energy and Environmental Regulation
Although there are different motives for energy (economic benefit) and environmental
(protection of health and ecosystems) regulation, there seems to be little reason why government
should not seek synergisms in these two arenas, lixamples that come to mind are (1) the perverse
energy and economic motives that drive life extension practices in coal-fired steam electric
facilities, efficiency and reliability disbenefits notwithstanding, and (2) the export of environmental
pollution damages to other states (with less restrictive environmental needs) under the EWG
provisions of EPAct. Many more examples surely exist. Efforts should be made to identify
opportunities for such synergisms.
Export Opportunities
Energy efficiency and renewable energy can be deployed in any location. Their economic
viability depends on the local energy economic situation and the availability of favorable resource
characteristics. When stripped of government subsidies, energy prices in most developing nations
are high compared to those in the United States. This creates an opportunity for their cost-
effective deployment. The major barrier to achieving this goal are the availability of capital and
institutional resistance within these nations. This is an area in which U.S. policies can have high
payout.
CONCLUSIONS
The current (1995) market outlook suggests that renewable energy is likely to play a
reduced role in the mitigation of U.S. GHG emissions as compared to the expectations of 1990.
Major changes in energy policy, technology advancement/export, and environmental policy are
needed if renewables are to play a more significant role.
REFERENCES
1.	Solar Energy Research Institute (SERI), Idaho National Engineering Laboratory (INEL),
Los Alamos National Laboratory (T.ANL), Oak Ridge National Laboratory (ORNI.), and
Sandia National Laboratories (SNL). 1990. The Potential of Renewable Energy, An
Interlaboratory White Paper. Golden, CO: SERI.
2.	Department of Energy, Office of the Secretary. 1991. National Energy Strategy (NES).
WDC: Department of Energy.
3.	The Union of Concerned Scientists , Alliance to Save Energy , American Council for an
Energy-Efficient Economy, and Natural Resources Defense Council, 1991. America's
Energy Choices. WDC: The Union of Concerned Scientists.
4.	Energy Information Administration (EIA). 1994. Annual Energy Outlook 1995, with
Projections to 2010. WDC: National Energy Information Center.
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TABLE 1: FORECAST OF ANNUAL U.S. ENERGY CONSUMPTION AND
CARBON EMISSIONS IN 2010
t*—i—n
\ *4
HMMMI

Total ^ fteftewables , C •
t, {Quadsf ; (Cfcistte) (Gigatonnes)
'gMPW	;••¦»!= :	= -Mzmmmmmimmmmtemk
C
s

3&Mf. <5« ' * £» lli®
110
103
105
83.4
104
10.1
12.1
11.2
14.8
8.9
1.9
1.7
1.73
1.2
1.62
•- '
Reference Levels:
Total Consumption (2010) —110 Q
Base Renewables Contribution (1990) — 6.8 Q
Carbon Emissions (1990) —1.35 GT
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FIGURE 1: U.S. RENEWABLE ENERGY CONTRIBUTION
1990	2000	2010	2020	2030

-------
FIGURE 3: COST OF ELECTRICITY GENERATED BY WIND
20.0
18.0
16.0
14.0
12.0
10.0
8.0
6.0 "
4.0
2.0
1985
~ •
~
DOE (1991)"
1990
" -43usinoss as usual Scenario^
^	-— 		i
Enhanced R&D SceTiario^-^ ¦
	DOE *(1993)	».,>
SERI et al '(1990):
DOE
•(1989)
1995
Goals and
Projections as
Labelled
*DOE Performance
Projected as of the
indicated date
Costs computed tor
standard wind site
with 5.8 m/s average
wind speed
2000
Year
FIGURE 4: PHOTOVOLTAICS
200
150
100
1975
1980
1985	1990
Fiscal Year
1995
2000
Budget Authority
^— R, D&D Intensification
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FIGURE 5: COST OF ENERGY HAS COME DOWN — MEETING RECENT GOALS
AND PROJECTIONS
80 r^r-
70
60
O
CO
o? 50
© m
O O
V)
40 --
30
20
10
Shugar (1995) Cost Data
O
World Bank (1994) Cost Data
o
.SERI (1990)
Projection
13.9
|- 11.9
9.9
7.9
5.9
3.9
1.9
-0.1
1985
1990
1995 2000 2005 2010 2015 2020
FIGURE 6: PRICE TRAJECTORY EXPECTATIONS BY EIA CIRCA 1989,1994,
AND 1995 ($1992)
World Oil Price
$/BBL
50
40 -
30
20
10
		- -
*	•1



¦i&SiS
,00S0f^
1989
mmm m
1994
1995
mm m
1990
1995
2000
2005
2010
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FIGURE 7: PRICE TRAJECTORY EXPECTATIONS BY EIA CIRCA 1989,1994,
AND 1995 ($1992)
Wellhead Natural Gas
$/MCF
4
3
2
1990

1989
1994
1995
t \ # fm
i
W W
% w
1995
2000
2005
2010
FIGURE 8: AVERAGE GASOLINE PRICES AND TAXES IN THE 10 OECD
COUNTRIES THAT CONSUME THE MOST PETROLEUM, 1992
Australia Canada France Germany	Italy	Japan Nelhedands
Country
I Tax Component
*OEGD - Organization lor Economic Cooperation and Development
Span United Kingdom Ihtec Stales
5-9

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5-B
Pollution Prevention by Consumer Choice:
The Green Pricing Option
Lloyd Wright
US Environmental Protection Agency
401 M Street, SW (6204J)
Washington, DC 20460
ABSTRACT
Allowing consumers to choose clean energy resources for their electricity needs may be one
of the most cost-effective options to reduce greenhouse gases. Through a concept known
as green pricing, participating consumers voluntarily pay a small premium to support
renewable energy technologies. Even at fairly low participation rates of one to five percent,
significant pollution reduction benefits are achieved. In addition to delivering greenhouse gas
reductions at less than $50 per metric ton, green pricing can dramatically transform the US
renewable energy market. This market-based approach also helps electric utilities prepare
for a competitive energy "marketplace. And all of this is achieved voluntarily, with no costs to
non-participants, the government, or electric utilities.
INTRODUCTION
Recent efforts to meet US climate stabilization commitments often have been a series of hard
choices. Policy options that reduce the greatest amount of greenhouse gases are often too
costly or politically difficult to Implement. Finding market-based solutions that also produce
effective and certain reductions is not an easy task. As additional reductions are sought for
both the pre- and post-2000 periods, ideal reduction opportunities will become increasingly
rare.
How would one describe the ideal greenhouse gas mitigation option? Such an option would
involve a minimum of cost for both the governmental and private sectors. The necessary
actions would be voluntary for all parties and create no non-participant costs. The option
would be simple and straight-forward to implement without the need of Intervention by
regulators. The results of the option would be easily measureable and verifiable. And
ideally, such an option would spawn other benefits such as additional pollution reduction and
economic development.
Although in a relatively nascent stage, utility "green pricing" programs offer much promise to
fulfill many of these objectives. Green pricing is an optional electric utility service that allows
customers to choose to have their electricity needs met by environmentally-friendlier
resources.1 In general, under these programs utility customers voluntarily pay a premium on
their electricity bills to have the utilities purchase renewable energy resources. In many
This paper has been reviewed in accordance with the US Environmental Protection Agency's
peer and administrative review policies and approved for presentation and publication.
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respects, utility green pricing programs are analogous to consumers purchasing other
environmentally-preferred products such as recycled paper or biodegradable cleaners.
The pollution reduction potential of green pricing programs is significant. If only one percent
of US residential customers participate In such a program, approximately 400,OCX) metric tons
of carbon emissions could be avoided each year. If projections for the commercial sector are
also included, the greenhouse gas mitigation benefits Jump even further. The potential
reduction in other energy-related emissions, such as S02, NOx, particulates, and mercury, is
also significant.
To date, three utilities have launched green pricing programs in hopes of servicing a segment
of their customer base that prefers environmentally-friendlier resources. The Sacramento
Municipal Utility District (SMUD) has initiated its "PV Pioneers" program in which participating
customers receive solar photovoltaic panels on their rooftops. SMUD's program adds 100
new homes to the program each year and includes such participant benefits as a fixed
electricity rate. Another program is that of Traverse City, Michigan. By signing-up over 200
subscribers to its program, this municipal utility was able to install a 500 kW wind turbine.
Public Service Company of Colorado has launched its "Renewable Energy Alternatives
Program' in which 73,000 participating customers contribute an average of $1.73 per month
for renewabies projects.2
Given the early stage of green pricing development, exact estimates of participation levels are
difficult to determine. The consumer willingness-to-pay for green energy services is central to
the continued progress of such programs.3 While some 50 to 80 percent of consumers
express an interest in paying more clean energy resources, actual participation is typically
less than 10 percent.4 However, even at participation levels of one to five percent, significant
pollution reduction levels can be achieved.
HOW GREEN PRICING WORKS
Green pricing efforts have already taken a variety of forms. In general, though, customers
pay a small premium on their monthly bills to support utility purchases of environmentally-
friendlier resources. The premium can be collected through various mechanisms such as:
¦	a fixed monthly fee;
¦	a percentage adder to the total bill; or
¦	a specific cents-per-kWh adder.
A green pricing program proposed by Niagara Mohawk Power Corporation would have
customers pay a fixed $6 per month fee. Of this amount, Niagara Mohawk would use $4 to
purchase renewable resources, $1 for tree planting, and $1 for administrative and marketing
costs. Sacramento Municipal Utility District's PV Pioneers program involves customers
paying a 15% premium to their existing electric bills. Massachusetts Electric Company is
exploring a program in which participants pay an extra 1 cent per kWh to fund renewabies.
Other creative instruments are being tested to determine consumer interest in funding
renewabies. Portland General Electric is developing several opportunities through its "Share
the Wind" program. In conjunction with US Bank, Portland General Electric has explored
offering customers charge cards, certificate of deposits, and debit cards that support
renewabies. US Bank contributes 1 % of every purchase made on a Share the Wind Visa
Card. Also, Portland General Electric is exploring a "penny jay" program in which customers
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can round up their monthly bills and donate the extra pennies to the fund.5
Box 1 Understanding the Cost Calculations
Example values
Utility long term avoided cast
Utility retail rate
Wind energy cost ,
Photovoltaic cost
No. of participating customers
Ave, energy use per residence'
$0.03/kWh
$0.083/KWh*
$G.04/kWh
$0.015/kWh
5,000
9,965 kWh/yr.'
Green pricing programs differ
from other utility renewable
energy efforts since green
pricing only applies to actions
the utility would not ordinarily
undertake. For instance, if a
wind energy project is already
below a utility's 'avoided cost,"
the utility should undertake
the project even without the
green pricing program.
Avoided cost refers to the
costs of generating and
delivering electric power that
will be avoided if a new
demand- or supply-side
resource is added to the
utility's resource mix. When a
renewable energy resource is
added to the utility system, the
utility avoids some fuel,
transmission, maintenance,
and other costs due to
reduced operation of existing
resources.
Green pricing is not a
substitute for actions a utility
would take for purely
economic reasons. Funds
raised through green pricing
are only applied to purchasing
resources that cost above the
utility's avoided cost.
The fact that some utility costs
are avoided when a renewable
resource is added allows .
green pricing programs to
substantially leverage funding.
Instead of needing funds for
the entire cost of the
renewable energy resource,	; :iJ j;Vvi9:::::J!!:¦	:[
only the amount in excess of	aflBHMaaaHaHBBi
the avoided cost is required.
If a utility's avoided cost is $Q.03/kWh for a wind project that has a cost of $0.04/kWh, then
only the difference, $0.Q1/kWh, will be needed from the green pricing program to purchase
this resource. The example in Box 1 illustrates this tremendous leveraging effect.
Funds Available for Renewables
In this example, funds for the renewables are collected as a
10% price premium to the electric bills of participants.
5000 homes x 9965 kWh/yr x (,1 x $.083/kWh) = $4U.000/yr
Cost of Renewable Resources. .
Assuming a portfolio mix of 75% wind and 25% solar
photovoltaics, the renewable energy costs are:
0.75 x $0,04/kWh + 0,25 x $0.15/kWh * $0.0675/kWh
Funds Needed to Purchase Renewable Resources
The funding needed is the difference between the cost of the
resources and the utility's avoided cost:
$0.0675/kWh - $0,03/kWh = $0.038/kWh
Program Administration and Marketing Costs
For purposes of this example, the administrative and
marketing costs are assumed to be $40,000 per year. Actual
costs will vary by program,
Amount of Renewables Purchased
The amount of renewables purchased due to the green
pricing program is:
($414,000 - $40,000] -r $Q.038/kWh - 9.8 million kWh/yr
Assuming typical capacity factors of 30% and 23% for wind
and photovoltaics, respectively, the amount of these
technologies theoretically added to the system is:
.75 x 9,8 mil, kWh/yr + (0.3 x 8,760 hr/yr) = 2,800 kW wind
.25 x 9.8 mil. kWh/yr (o.23 x 8,760 hr/yr) = 1,200 kW solar
* 1993 resid. ave. rate, 1993 Annual Energy Review, EfA,
" 1993 values, Hous&tiold Energy Consumption and Expenditures,
El A, 1995.
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THE POLLUTION REDUCTION POTENTIAL
Green pricing holds a great potential to reduce energy-related emissions and play a
significant role in US commitments to greenhouse gas stabilization. Green pricing programs
reduce emissions cost-effectively, and with all costs voluntarily incurred. The pollution
benefits, though, are not limited to greenhouse gas emissions as green pricing
simultaneously addresses a range of electric utility pollutants.
Greenhouse Gas Mitigation
Relatively small participation rates in green pricing programs are capable of producing
sizeable greenhouse gas reductions. Renewable technologies such as solar, wind, and
geothermal energy produce virtually no greenhouse emissions. Biomass energy produces
no net emissions of COs when crop or wood inputs are replanted. Landfill methane energy
prevents the escape of methane, a greenhouse gas that is 20 to 30 times more potent than
carbon dioxide. With typical project lifetimes of 30 years, these technologies can produce
large, long-term reductions.
Table 1 shows the pollution reduction potential of green pricing for several different pollutants
and program participation levels. The US electric utility sector was responsible for
approximately 489 million metric tons of carbon in 1993.6 Even if only 1 percent of the
residential sector participates, green pricing will reduce greenhouse gas emissions by
400,000 metric tons per year.7 If residential participation reaches 5 percent and commercial
sector participation reaches just 2 percent, the release of 2.7 million metric tons of carbon
can be prevented.
Of course, one of the most critical tests for any greenhouse gas reduction option is the
financial bottom line. How much does it cost? Under normal circumstances, the purchase of
renewable energy technologies for strictly pollution reduction reasons is not the least-cost
option. Assuming these technologies range in cost from $0.04/kWh to $0.15/kWh, this
translates into greenhouse gas reductions at roughly $190 per metric ton to $710 per metric
ton.8 A typical threshold for the cost-effectiveness of greenhouse gas reductions Is
considered to be $50 per metric ton. Thus, the purchase of renewable energy resources
solely for greenhouse gas reduction reasons does not appear to be particularly competitive
with other options such as tree planting.
As noted above, by leveraging the electric utility's avoided cost, green pricing programs
reduce the total funding needed for renewable energy projects. For technology costs of
$0.04/kWh to $0.15/kWh and an assumed avoided cost of $0.03/kWh, this translates Into
greenhouse gas reductions at $48 per metric ton to $571 per metric ton.9 Thus, at the lower
end of this scale, renewable energy becomes a reasonably competitive greenhouse gas
reduction option.
The above cost figures represent total societal costs. In the case of green pricing all costs
are voluntary. Non-participants pay nothing; only those customers who are motivated to do
so pay the monthly premium on their electric bill. Utility revenues and profits are unaffected
by green pricing. Thus, from a utility perspective, green pricing is a no-cost approach to
reducing emissions. Likewise, since green pricing is not tied to any regulatory requirements,
no public funding is required for these programs.
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Green pricing can help electric utilities meet commitments to the Climate Challenge, a
voluntary program in which utilities have agreed to stabilize or sharply reduce greenhouse
gas emissions by the year 2000. Over 487 rural cooperative, public, and investor-owned
utilities have signed onto this program.10 The Climate Challenge was created as an action
item within the "Climate Change Action Plan" which details US plans for meeting the goals of
the Rio Framework Convention on Climate Change. Even at conservative estimates for
participation levels, green pricing programs can offset increased emissions from typical
system growth rates and thus assist in emission stabilization. Section 1605B of the 1992
Energy Policy Act lays the groundwork for a system of recording greenhouse gas reductions.
A methodology and emission reduction forms have been developed by the US Department of
Energy to help document reductions.11 Thus, utilities can go on record today and secure
credit for greenhouse gas reductions in anticipation of an eventual carbon trading market.
As an added benefit, emission reductions from green pricing programs are readily
measureable and verifiable. The megawatt-hours of output are already measured for financial
purposes. This output can then be converted to emission reductions given the emission
levels of the resources that are being offset. Verification of other options such as demand-
side management and/or tree planting options are complicated by the need for metering and
field approximations. For such options the exact amount of energy generation offset or
carbon sequestered Is often only an estimation. Further, the lifetime of a renewable energy
project is fairly well established and can give emission reductions over a long and certain
period of time.
Many applications of renewable energy resources reduce the need for costly electricity
transmission. Photovoltaic panels on the rooftops of green pricing participants are an
example. Approximately seven percent of electricity generated is estimated to be lost in
transmission and distribution.12 Distributed energy systems such as rooftop photovoltaics
not only directly offset energy through generation, but also eliminate the emissions resulting
from the additional generation needed to make up for line loss.
A Multiple Pollutant Solution
Green pricing programs reduce greenhouse gas emissions as well as a range of other
pollutants. Renewable energy technologies avoid emissions of S02, NOx, particulate, and
mercury and other toxics.13 The simultaneous reduction of multiple pollutants gives green
pricing programs an added value to both electric utilities and the public.
Emissions of S02, NOx, particulate, and air toxics have well-documented impacts and costs.
Emissions from fossil fuel generation harm waters and forests, endanger animal species and
ecosystems, accelerate the decay of buildings and monuments, and impair public health. A
recent study by Harvard University's School of Public Health strongly linked such emissions
to higher rates of illness and mortality.14
The electric utility industry incurs costs to meet the minimum emission standards specified in
the Clean Air Act as well as the requirements of State and local jurisdictions. These costs
traditionally have been reflected in the cost of control devices such as scrubbers and/or the
addition of boiler modifications. With the advent of market-based emission trading systems,
the costs of pollutants such as S02 and NOx are becoming directly internalized in utility cost
structures.
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Title IV of the 1990 Clean Air Act Amendments created a new tradeabie commodity, the S02
emission allowance. The tradeabie allowance market was developed as an innovative and
cost-effective approach to reducing national SOz emissions by 10 million tons annually from
1980 levels. Each allowance represents an authorization to emit one ton of S02. By avoiding
the emission of S02 with renewable energy technologies, utilities avoid expending emission
allowances which have a real market value. Congress also set aside a reserve of bonus
allowances to reward early installation of renewable energy and energy efficiency
technologies.15
The reduction of ambient NOx emissions Is perhaps the next major pollutant to be
incorporated into market trading programs. Under Title I of the Clean Air Act, regions that
are in "non-attainment" must take actions to reduce NOx emissions. The South Coast Air
Quality Management District in Southern California has already initiated a trading program to
address NOx emissions. NOx trading is also under consideration by States In the Northeast
Ozone Transport region. In addition, State and regional governments are exploring the use
of NOx trading to address non-attainment areas in Illinois and Texas.
Through these trading regimes, renewable energy systems installed due to green pricing
programs add quantifiable value to an electric utility. A green pricing participation level of
five percent from the residential sector would save utilities $6.4 million per year in S02
allowances.16 The benefits to renewable energy projects from NOx trading is expected to
be even greater than those from S02 trading.17 These savings are not externalities, but
rather real, internalized dollars that directly affect a utility's financial performance. Given the
advent of trading markets, as well as the on-going costs of traditional control technologies,
green pricing programs add substantial value to a utility's environmental efforts. And all of
this is achieved by a mechanism that imposes no cost to the utility.
BENEFITS BEYOND THE ENVIRONMENT
Green pricing's added value to electric utilities and society as a whole does not end with a
cleaner environment. Green pricing may also transform the economics of the renewable
energy industry as well as provide an array of technological and economic benefits to both
electric utilities and society.
Transforming the Renewable Energy Industry
Green pricing has the potential to dramatically transform the renewable energy market. Even
if implemented with only a modest participation rate, green pricing can result in more
renewable energy generation than in all of the Industry's previous history. Table 2 gives a
forecast of the renewable energy industry with and without green pricing for different
participation levels. For the given mix of technologies in Table 2 and a participation rate of
5% from the residential and 2% from the commercial sector, green pricing would increase the
nation's wind energy capacity by over 150 percent and increase solar photovoltaic capacity
by 60 times.
With such a large increase in renewable energy capacity, green pricing will most likely lead
to lower renewable energy prices through increased economies of scale. A circular effect
begins to take shape; as green pricing lowers renewable energy costs, more renewables can
be purchased with the same amount of funding from green pricing programs.
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The New Energy Marketplace
Renewable energy provides the electric utility industry with a number of benefits that may
well be the key to success in a deregulated utility environment. Renewables add diversity to
resource mixes, and thus lessen dependence on resources such as oil and gas. These fossil
resources are subject to large fluctuations in fuel costs and could put a utility at substantial
risk in a deregulated market. Renewables are also often modular in nature; capacity can be
added to a system a few kilowatts or megawatts at a time. Renewable energy is also an
impressive job creator and boon to economic development. Renewable energy has been
found to provide a greater number of jobs, especially skilled jobs, than traditional energy
technologies.18 Green pricing also gives utilities a relatively easy learning experience with
the future energy market. Green pricing allows utilities to become familiar with renewable
energy technologies, including how to operate and maintain the technologies, how to
integrate the technologies into transmission and distribution systems, and how to evaluate
consumer interest.
Utilities can also learn to view electricity not as a commodity but a set of different products
and services that can be sold in a segmented marketplace. Competition in the new energy-
service market means that energy providers will compete not only on price but the "quality" of
the energy as well. Green pricing may be the bridge to link the traditional electric utility of
today with the entrepreneurial energy-service provider of tomorrow. In fact, although full
competition may yet be years away, utilities may not wish to wait too long before entering the
green energy market. Renewable energy manufacturers and developers appear ready to
also enter this new market. Competition, at least In the green energy arena, may come
sooner than originally thought. And market share lost is not always easy to win back.
GREEN PRICING REALITIES
Despite its promise, green pricing is not without its controversies. While green pricing
exhibits many of the traits of an ideal pollution reduction option, both the environmental
community and the energy industry have raised some issues that must be clarified before the
concept is fully embraced.
Concerns of the Environmental Community
For the renewable energy industry, two decades of technology and manufacturing
improvements have resulted in costs that are often directly competitive with traditional
resources. Nevertheless, the industry is burdened with a stigma of being prohibitively
expensive. By putting a "premium" of 5-10% on participating customers, some fear green
pricing will be perpetuating the stigma that renewables are exotic, expensive resources.
However, some market research Indicates that the public is actually pleasantly surprised the
premium is so little. For many, a premium of only 5-10% Is very small price to pay for a
cleaner environment.
The fact that non-participating customers gain the same environmental and technological
benefits as participants reuses concerns over fairness. When the utility purchases renewables
with participant funds, everyone enjoys cleaner air and water as well as a more diversified set
of energy resources. This criticism is valid, but applies to all environmentally-friendlier
products. Everyone reaps the environmental benefits when only a few people use recycled
paper. However, this free-rider effect has not prevented the environmental community from
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embracing such products, In ©very new market, there are always a few consumers who lead
the way for others to follow and benefit. Green pricing is not unique in this regard.
Another concern is that green pricing will discourage other pro-renewabies policies from
going forward. The adoption of green pricing will be used as an excuse not to develop
green RFPs or set-asides, a renewables portfolio standard, or a renewables wire fee. In fact,
green pricing is compatible with all of these policy options. The funding and subsequent
projects resulting from a green pricing program are wholly distinguishable from projects
initiated for other reasons, Certainly the possibility exists for some to claim green pricing is
the only program needed. However, all of these policy options, including green pricing, can
be presented as a synergistic set of programs that together build a strong and sustainable
renewables market. Green pricing should never be a substitute for procurement of cost-
effective renewable resources on behalf of the utility's entire customer base.
Concerns of the Utility Industry
The existence of a green electricity market is by no means a sure thing. Will customers who
show support in marketing surveys really put their money down when it counts? Perhaps the
greatest fear of utility executives is to spend money on marketing a green pricing program
and then not have sufficient participation rates to cover the investment.
To date, the smaller programs at Sacramento Municipal Utility District and Traverse City have
been reasonably successful. Public Service Company of Colorado's program has had a slow
start. As of April 1995, over §270,000 had been spent on promoting the green pricing
program, and only $113,000 had been collected from participants. However, the company
may very well recoup its costs, especially since marketing costs should fall as the program
matures. Markets for other green products have taken time to develop but now thrive. The
effectiveness of utilities in marketing these programs will most likely the deciding factor in the
success of the green pricing concept.
The utility industry is currently in a state of great uncertainty. Deregulation and competitive
issues are being considered in several states. Some utilities may find it preferable to wait
and see how deregulation falls out before undertaking a new initiative like green pricing.
Waiting, though, carries its own risks. As noted earlier, green pricing can help the utility gain
experience with a new service-oriented market. By not taking the first-mover advantage in
niche markets, utilities risk losing the green energy market to new entrants.
CONCLUSION
The pollution reduction potential of green pricing is dramatic, as is its potential for
transforming the renewable energy market. At potentially less than $50 per metric ton of
carbon, green pricing is a competitive greenhouse gas mitigation option. And best of all, this
cost is paid voluntarily with no non-participant costs. Both environmental organizations and
the utility industry have raised some concerns over green pricing, and these concerns should
be considered closely before committing to this path. However, few options for reducing
pollutants and promoting a robust renewables industry possess as many desirable
characteristics as the green pricing option.
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REFERENCES
1.	Moskovta, David, Renewable Energy: Barriers and Opportunities; Walts and Bridges, World Resources
Institute, 1992. Also, Moskovitz, David, Green Pricing: Experience and Lessons Learned, The Regulatory
Assistance Project, Gardiner, ME, 1993,
2.	Chris Henrichs, Public Service Company of Colorado, Presentation at the 1995 Utility Photovoltaic Group
annual meeting, April 11, 1995, San Antonio, TX.
3.	The Regulatory Assistance Project, Green Pricing Newsletter, Number 2, May 1995, Gardiner, ME
4.	Byrnes, Brian, et al„ Shedding Light on the Marketability of Renewables, Paper presented at National
Association of Regulatory Utility Commissioners conference on renewables, May 9, 1995.
5.	Utility Environment Report, PQE, US Bank Offer Credit, Swings Service to Support Wind Projects, March
3, 1995, p. 11.
6.	Energy Information Agency, Emissions of Greenhouse Gases in the United States: 1987-1992, November
1994, p. 12, 33, and 48.
7.	Based upon the technology mi* and cost assumptions presented in the example in Box 1. Actual
emission reductions will depend on the actual values of these variablea
8.	Assumes national average emission levels for C0S; conversion factor of 0,21 MMTC/billion kWh (or
approximately 1.5 lb CO, per kWh). The actual costs for greenhouse gas reduction will depend upon each
utility's own emission rate. Emission rates vary by resource mix and operating efficiencies.
9.	Again, the additional cost needed to fund a renewable energy project based upon a green pricing
program is the difference between the project's cost and the utility's avoided cost for that project. Thus, for the
given example, the funding needed from the green pricing program is $0.01/kWh to $Q.12/kWh. Actual costs will
be slightly higher due to program administration and marketing costs.
10.	Utility Environment Report, 202 Co-ops Pledge to Cut Greenhouse Gases under DOE's Climate
Challenge," May 12, 1995, p. 3.
11.	Energy Information Agency, Voluntary Reporting of Greenhouse Gases, Form nos. EIA-1605 and EIA-
1605EZ. For more information call (202) 586-8425.
12 Y. Bae, 193S Line Loss Study, Portland General Electric Company, Portland, OR, 1988. Actual line loss
varies by time of day and transmission distance.
13.	Solar and wind energy technologies eliminate virtually all air emissions. Geothermal resources release
small levels of pollutants through the extraction process. Bio mass energy systems emit NOx.
14.	Dockery, Douglas W„ et, al„ American Journal of Respiratory and Critical Care Medicine, March 1995.
15.	For more information see: US EPA, Energy Efficiency and Renewable Energy: Opportunities from Title IV
of the Clean Air Act, Document no. EPA 430-R-94-001, February 1994. To obtain a copy, contact the Acid Rain
Hotline at (202) 233-9620.
16.	Assumes a S02 market price of $l50/ton. Also assumes a green pricing program mix and costs as
described In Box 1. The $6.4 million annual savings does not include bonus allowances awarded from the
Conservation and Renewable Energy Reserve; thus, actual savings will be somewhat greater.
17.	One study (South Coast Air Quality Management District, RECLAIM: Socioeconomic and Environmental
Assessment vol. Ill, October 1993) projects a range of $577 to $11,257 per ton of NOx.
18.	Alliance to Save Energy, American Gas Association, and Solar Energy Industries Association, An
Alternative Energy Future, Washington, DC, April 1992.
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TABLE 1 THE POLLUTION REDUCTION POTENTIAL OF GREEN PRICING (Per Year)*
Participation Rate
Carbon,
metric tons
so2,
metric tons
NOx,
metric tons
Particulates
(PM-10), kg
Mercury,
kg
1% of Residential
400,000
8,500
4,700
161
76
1% of Commercial
340,000
7,200
4,000
136
64
5% of Residential
2% of Commercial
2,680,000
56,900
31,500
1,077
508
10% of Residential
5% of Commercial
5,700,000
121,000
67,000
2,290
1,080
* Based upon the calculation procedures presented in Box 1. Actual reductions will depend upon the actual
renewable energy resource mix. National residential electricity sales for 1993 was 994 billion kWh for a total of
96.6 million residences. Pollution reductions based upon the following national average emission factors:
Carbon
(MMTC/	S02	NOx	PM-10	Mercury
bill. kWW	(aimh)	la/kVM	(mq/kWh)	fma/kWh)
0.21	4.5	2.5	0.085	0.04
TABLE 2 THE POTENTIAL IMPACT OF GREEN PRICING ON THE US RENEWABLES
MARKET**
The amount of generation added for a green pricing program mix of 40% wind, 20% biomass, 10%
geothermal, 10% landfill methane, 10% solar thermal, and 10% solar photovoltaics

Added Capacity, I
With Green Pricing
Resource
Present Case,
No Green Pricing
1% Residential
5% Residential
2% Commercial
10% Residential
5% Commercial
Wind
1717 MW
456 MW
2,768 MW
5,780 MW
Biomass
7707 MW
98 MW
594 MW
1,240 MW
Geothermal
2838 MW
40 MW
242 MW
505 MW
Landfill Methane
400 MW
40 MW
242 MW
505 MW
Solar Thermal
369 MW
98 MW
594 MW
1,240 MW
Photovoltaics
14 MW
149 MW
903 MW
1,885 MW
** Capacity factors used for each technology are: Wind, 0,3; biomass, 0.7; geothermal, 0.85; landfill methane,
0.85; solar thermal, 0.35; photovoltaics, 0.23.
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5-C
The work, described in this paper was riot funded by the U.S. Environmental Protection Agency. The
contents do not necessarily reflect the views of the Agency and no official endorsement should be inferred.
RISK, ACCOUNTING AM) STRATEGIC FLAWING ISSUES IN INTEGRATED RESOURCE PUSWIfG (IRP)
RESOURCE SELECTION
Shimon Awerbuch
Independent Economic Consultant
50 Shelley Drive
Nashua, NH 03062
I. WHAT DOES IT TAKE TO IMPROVE IRP?
What docs it take to improve IRP? At least a few will respond to this somewhat
irreverent question by wondering whether IRP needs cmy improvement. However, while
IRP is evolving as the preferred planning methodology for electric utilities, its emphasis
seems to me to be much less on planning and more on engineering-economics oriented
cost analysis.
Engineering economics concepts, which date back to the early part of the century, were
formalized in the post World-War II era [Awerbuch and Preston, 1993J. Although they
ignore financial risk,^ the concepts have provided a practical, accounting-based means to
help engineers value project alternatives. Engineering economics may work quite well
given the following restrictive conditions:
Condition 1: It makes sense to model the asset or project on the basis of its cash
flows: The practice of representing asset by their cash flows— revenues and costs-
- is so widespread that we tend to forget this basic assumption, which probably
does not hold for many new technologies whose benefits cannot be captured using
a traditional accounting-oriented cost model.
This can be illustrated by examining the problem of trying to value a fax machine
solely on the basis of its cash flows. The cash flow changes for this investment-
additional phone charges incurred over the savings in postage and possible clerical
time— are trivial when compared to the non-accounting benefits generated: the
ability to access the information network, to make rapid decisions and to establish
working relationships not otherwise possible. These benefits, for the most part,
^ The term risk is used to mean financial risk (** which reflects business or operating risk-
coupled with financing risk**) as opposed to other potential risks such as environmental
or health hazards, etc.
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have no corresponding accounting entry and are obviously difficult to quantify
which suggests that it makes little sense to attempt to model a fax investment in
terms of direct cash flow benefits.
Condition 2: It makes sense to assume an environment of static technology
coupled with relatively homogeneous technological choices: This condition, which
no longer holds even in the case of electric utilities, has two important implications
for valuing investments. The implication of the homogeneous technology is that
risk is not dependent on technological choice. The implication of technological
stasis is predictable future which means that various strategic and managerial
options have little value.
Since neither of these conditions is easily met in today's technological environment, more
sophisticated methods of capital budgeting or financial economics must be used to value
resource alternatives. Financial economics techniques reflect risk, and can be used to
model certain benefits, such as the creation of strategic options, which cannot be
expressed in terms of the traditional and confining, accounting-based cash flow approach.
The application of traditional engineering economics to the valuation of electric generating
options seems to originate with Paul Jeynes [Kahn 1988, 23 J who was rather careful to
note the principal shortcomings of the approach, i.e.: that it works only where expected
revenues and the firm's rate of return remain unaffected by the technology choice [Jeynes,
1951, 1956], thus implying that all resource options show the same degree of financial
risk. Indeed the assumption of technological homogeneity probably posed little difficulty
in Jeynes' day, given the relatively limited choice of options in the 1950's- oil and coal
fired central station steam. These were homogeneous in the following ways:
i)	They used similar fossil fuel inputs with prices that were (and still are) highly
correlated with each other and with the general level of economic activity, .
ii)	They had a cost mix consisting of similar proportions of capital and operating
costs.
iii)	They had a similar mix of direct and indirect costs.
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iv)	They had similar operating cost (i.e.: 'fixed' and 'variable') structures so that
operating leverage was similar;^
v)	The regulated revenue stream remained unaffected by the technological choice;
only costs differed so that it made sense to model each technology in terms of its
projected revenue requirements.
vi)	Choosing a particular technology did not create the prospect of different
managerial or strategic options for the firm— options that might affect the firm's
competitiveness in the future; for example: the firm's future capabilities were not
significantly enhanced by choosing, say coal over oil-fired steam generation.
vi) The technologies were all equally 'lumpy' and irreversible.
The evidence suggests [Awerbuch 1993(a), p***] that in engineering economics probably
worked quite well in this environment in that the resource decision probably would have
not changed with the use of more sophisticated techniques.
However, today's utility planner faces a broad range of supply and demand-side resource
options which present different cost and risk characteristics. This calls for the use of more
suitable approaches which:
i)	Reflect the changing technology costs over time as technologies mature, or,
must be adapted to .meet new needs.
For example, the relative costs of fossil and solar technologies change drastically
when i) a new need is imposed— e.g. a requirement for zero or low carbon
emissions, or, ii) when changing economic conditions alter the relative costs of
input factors- e.g. labor costs rise over time relative to capital costs without
productivity gains in the operating and maintenance functions.
ii)	Reflect non-accounting costs such as risk, the source of which can be volatile
fuel costs, or the inflexibility and irreversibility of plant investments.
¦2 Operating leverage involves the ratio of fixed and variable costs; for definition see
Brealcy and Myers [1991, 199-200] or Rao [1992, 193-197],
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iii)	Treat resource alternatives as components in a portfolio of generating assets,
measuring the relative cost contribution of each asset against its relative risk
contribution to the entire generating portfolio.
iv)	Recognize the severe limitation of traditional accounting measurement for
decision-making;
v)	Reflect non-accounting benefits including quality, and strategic, managerial and
flexibility options;
This paper treats the above issues in survey fashion, thus providing an overview of the
important issues affecting IRP resource selection. The following sections introduce and
explore i) the need for more effective strategic planning in IRP, ii) the effect of financial
risk on decision making, and iii) limitations of accounting measurement and its effect on
our perception of cost and cost drivers.
H. IRP WITH AN EMPHASIS ON THE 'P'
IRP Focuses on Current Technology Costs Only
IRP procedures are based almost exclusively on cost as currently conceived and
constructed, without reflecting future cost changes in technologies under consideration or
changes in operating conditions. This practice is especially astonishing given the long
planning horizons— typically twenty years or more. An effective planning process must
consider and reflect future changes in technology costs. In part, this involves i) assessing
and valuing contingencies such as carbon taxes and future retrofits ii) using learning
(experience) curves and other tools for to develop a technological assessment for
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relatively mature technologies such as coal or gas turbines as well as newer
solar/renewable options. In either case, using today's costs makes little sense.
Utility resource plans tend to expresses the costs of particular technologies in terms of
their current accounting costs. But IRP represents an inter-temporal investment strategy
and it needs to reflect anticipated future cost changes. Solar/renewable technologies, for
example, are on a declining cost curve and their expected costs will drop over a long
planning horizon, while coal and other fossil technologies are on the mature part of the
technology curve— their real costs are likely to rise with real increases in labor and fiiel,
and with future attempts to adapt them to new needs.
The Era of Technological Chanpe: The Need for Technology Assessment
Qualitative technology assessment can help properly capture the cost of using a particular
technology as the world changes in the future. For example; fossil generation costs are
routinely based on currently constructed accounting costs. While some aspects of these
costs- e.g. fuel or labor outlays— are projected to the future— this does not capture the
true costs that might be encountered in the future, when operating conditions, competitive
pressures and the cost of alternatives may change. There is plenty of evidence to illustrate
this point: we routinely discard computers, copiers and fax machines because they have
gotten too expensive to use, even though the original cost is sunk and we have made no
unanticipated maintenance outlays. In other words, the technologies obsolesced even
though the original cost projections materialized precisely.
However, while the engineering cost projections were on target, relative costs changed as
the result of new operating requirements or new needs to which the technology could not
be easily adapted. We might, for example, discard a paper copier because it does not
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reduce/enlarge or a fax machine because it does not cut the paper. Cutting paper may not
have been important at the time of purchase since even a plain fax reduced operating costs
or enhanced capabilities and competitive advantage. But over time operating conditions
change— e.g., the volume of usage increases. This may change the cost picture so that it
now becomes too expensive to deal with continuous scrolls of paper. In other words, the
technology has become too expensive even though its accounting costs as originally
projected have remained unchanged. This is especially true if competitors have all
switched to the newer, paper cutting technology.
Given technological progress, resource options arc similarly subject to cost changes as
they are adapted to new market, regulatory and operating conditions so that it also might
become too costly to operate a particular option even though costs materialize as
projected. The most obvious changing conditions are:
i) Environmental Regulation:
More stringent emissions requirements or the possibility of carbon taxes might require
sizable retrofits to meet air quality standards, and/or raise the cost of using coal, and
possibly other fossil fuels. Such contingencies are frequently ignored even though they
probably have significant present value costs.
For example, consider the possibility of a $300 million outlay to meet new emissions
requirements in the tenth year of a coal fired project. Such an outlay has a present value
of $100 million— even if the likelihood of this contingency is only 50%. This is significant
relative to the $600 million or so cost of a 500 mWe coal-fired plant, Likewise, the
imposition of a carbon tax similar to that recently considered in Europe [Electrical Week,
October 28, 1991, p. 16] raises the cost of coal by 60% and the cost of the electricity
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generated by 30%- about $,03/kWh- over base case estimates made by NARUC [1991],
Such contingencies are well within the realm of possibility; omitting their valuation from
the planning process represents a significant oversight.-*
ii) The development of new, lower cost technologies:
IRP techniques need to incorporate technology assessment procedures in order evaluate
the efficiencies-- and hence costs— of future vintages of gas turbines, existing and new
solar/renewables, and possibly 'clean coal1 and advanced nuclear reactors. New vintages
of all technologies may have cost structures different than those used in today's screening
analyses. Given the twenty-year IRP horizon it is important to consider the cost offuture
technology vintages and not just the current costs.
For example, S-shaped (logistic curves) coupled with engineering assessments can be used
to help estimate efficiency increases (i.e. reduced heat-rates, improved ramp-up, lower
maintenance requirements) for existing technologies such as gas turbines. Similarly,
experience curves can be used to help estimate manufacturing cost reductions as a
technology matures which, assuming relatively perfect markets, will translate to lower
The carbon tax possibility is valued by discounting the expected outlay at the after-tax
risk-free rate (about 4.0%), under the assumption that the outlay has no systematic risk
(Risk issues are discussed subsequently in this paper). For example: a $500 million outlay
in 10 years, which has a 10% probability of being mandated, generates a present value of
$32 million.
Arguably, such tax measures may be less likely to be implemented during bad economic'
times, but compliance could occur at various times- both good or bad. To the extent
there is a systematic component to such expectations, the discount rate must be adjusted
up which will reduce the present value.
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initial costs per unit of capacity. Experience-curve cost reduction may be especially
significant for new technologies such as photovoltaics.
7 ***Show logistic curve and a set of learning or experience curves. ***
The results of such experience curve analysis can dramatically change estimated costs in a
new tecluiology such as PV if we conceive of the resource as being installed incrementally
over the planning horizon. Using a set of projected experience curves for photovoltaics
devetoped by Williams and Terzian [1993], we obtain a levelized cost for PV-based
electricity that is nearly 50% lower than NARUC's [1991] estimate of $.22/kWh, the
latter being based on current costs.
Estimating future operating costs of emerging renewables, as well as relatively mature coal
and gas technologies requires an assessment which reflects secular factors, in addition to
the current accounting costs. IRP plans which ignore secular factors are crunching
numbers in a vacuum.
iii") Changes in the utility industrial organization over the next twenty years:
Given the pace of regulatory and technological change the possibility of radical
architectural changes [see: Awerbuch and Preston, 1993; Clark? Henderson?] in the
electricity production process must be considered. Again there is ample case evidence to
support the need for considering such factors: e.g.: various economic, technological and
public policy factors converged to reduce railroads from a major industrial force to
bankruptcy in less than 20 years following World War II.'
' The causal factors are readily identifiable with hindsight: America's post-war economic
preeminence raised standards of living thus making autos widely affordable. In addition,
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M Changes in the relative cost of labor and other input factors:
IRP cost estimates typically project labor costs forward using an assumed, and usually
arbitrary, escalation rate. But the use of such rates masks the underlying economic
changes in the relative costs of factor inputs. A more detailed analysis may easily reveal
that, assuming an absence of productivity gains, the substitution of capital for labor may
become increasingly attractive in electricity generation just as it has in manufacturing.
Resource plans which blindly transpose current cost structures to the future will not reveal
these underlying structural changes which can easily swing the balance away from
technologies that currently appear to be low-cost alternatives.
Clearly these and other forces can join to change the initial and operating cost picture for a
given technology. For example, absent significant efficiency gains, a scenario of relatively
undramatic operating cost increases for gas turbines coupled with more stringent
emissions requirements could combine with experience-based cost reductions in PV to
make the latter the low cost choice at some not too distant future time. Such relative cost
changes are obscured when all technologies are evaluated using their currently-
constructed present value costs.
Federal housing and other programs (e.g. water and sewer grants, FHA/VA mortgage
guarantees, etc.) subsidized and encouraged suburbanization. Railroads could not
effectively serve the resulting diffused intra-urban transportation patterns. Finally,'
massive, federally subsidized highway construction reduced the cost of auto and truck
transport reducing the railroads' inter-urban monopoly as well..
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m. REFLECTING FINANCIAL RISK IN IRP
Financial risk, which reflects the variability of annual rates of return to an asset, project or
firm, is commonly included in the valuation of financial assets, and, increasingly, in the
valuation of corporate investment projects. Risk and its analytic treatment is an integral
part of basic finance courses and is treated in detail in all advanced capital budgeting
courses.
The CAPM as a Basis for Estimating Discount Rates:
Risk is fundamental to the estimation of correct discount rates. Contrary to the
engineering economics approach, which uses the firm's weighted average cost of capital
(WACC) as a proxy rate for discounting projected revenue requirements, financial
economics stresses the need to estimate discount rates more precisely, using the capital
asset pricing model (CAPM) or similar approaches.
Such models are sometimes applied rigorously, using econometric techniques to produce
statistically significant discount rates. Where such econometric estimation is not feasible
or not cost-justified, the CAPM can be used more conceptually to produce estimates that
while judgmental, are materially better than using the firm's WACC, which is clearly the
incorrect discount rate for valuing the projected revenue requirements of most utility
investments.
The CAPM is a remarkably elegant model under which the required rate of return or;
discount rate is driven by j) the prevailing riskless interest rate on US government
obligations, and ii) the level of risk inherent in the particular asset, project, or firm. Figure
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1 illustrates. CAPM Risk is measured using the Beta (P), a statistical measure which
relates the degree to which the year-to-year variability of the project returns co-vary with
the returns to a diversified market portfolio, usually represented by the S&P 500 or similar
index. Risk thus has two components: the uttsystemaiic component, reflecting the
project's or cash flow's own random, year-to-year variability, and the systematic
component, which reflects the degree to which that variability moves in unison with other
assets in the economy. This has important implications for understanding such issues as
'technology risk' which is discussed subsequently.^
The beta of the diversified market portfolio is by definition always equal to: (3=1.0. In
Figure 1 this equates to a market-based rate of return or discount of Km = 12%. Assets
that are riskier than a diversified market portfolio will have higher betas. The returns or
net cash flows of riskless government obligations do not vary period to period so that p =
0,0. Asset j in Figure 1 has a systematic risk of Pj with a required return of Kj, below the
market rate and above the riskless rate. Asset net cash flows generally do not have betas
less than 0.0, although project revenue requirements can. For example, pc, is the Beta for
cash flow C. It has a CAPM-derived discount rate of Kc, below the riskless rate [see:
Awerbuch, 1993(a) and Awerbuch and Deehan, 1993],
Fallacy of the WACC:
s The evidence largely suggests that systematic risk drives discount rates, although some
recent evidence (A survey can be found in Fortune [June 1, 1992, p. 23]) suggests that
unsystematic components also play a role. More recent work has again suggested that
systematic risk as measured by the beta is indeed a useful indicator of the required return
(A survey of recent research supporting continued use of the beta is given in The
Economist, [February 6, 1993, p. 81]). The controversy is not crucial to the valuation of
IRP alternatives [Awerbuch and Deehan, 1993].
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The WACC is the marginal cost of the firm's capital, given its current asset portfolio and
capital structure. The WACC is therefore the market-based discount rate for the firm's
net cash flows to investors (interest payments, earnings, depreciation and deferred taxes).
It is not the correct discount rate for the net cash flows of a new project being considered
unless that project's level of systematic risk equals that of the firm's entire pre-existing
portfolio. More importantly, utilities do not evaluate projects based on the net cash flows
or profits, but rather focus on the revenue requirements or costs. The WACC will almost
never be appropriate for discounting project revenue requirements.^
Estimated Busbar Costs Using Basic CAPM Theory
Correct estimates of the present value revenue requirements (PVRR) of a particular IRP
resource alternative can be found by discounting at the correct, market or CAPM based
discount rate. So doing yields resuHs that are strikingly different from the commonly seen
WACC-based PVRR estimates. The procedure for implementing a market-based
approach to estimating PVRR's is conceptually identical to the traditional WACC-based
approach. Revenue requirements for maintenance, fuel outlays, income taxes, etc. are
estimated and then discounted at their appropriate rates.7
6	Booth [1982], ] shows the analytic relationship between the appropriate discount rates
for a project's revenues, costs and net cash flows- the difference between revenues and
costs [also see Awerbuch 1993(a)].
7	It is generally simpler, although not essential, to estimate actual cash outflows as
opposed to revenue requirements; a straightforward conversion exists which will translate
the present value outflows to PVRR's [see: Awerbuch ***Colorado Testimony 1992],
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For convenience it is possible to categorize project costs into homogenous risk groupings
as follows:
i.	Countcr-cvclical Outflows: Fossil fuel outlays have negative betas, i.e. they co-
vary negatively with other assets in the economy [Awerbuch 1993(a) and
Awerbuch and Deehan, 1993] thus requiring a discount rate below the riskless
rate. Discounting projected ftiel outlays at the WACC, (which is much higher)
significantly understates their present value costs, which biases IRP in favor of
fuel-intensive technologies and against capital intensive ones.
ii.	Riskless Outflows: This category includes depreciation and other tax shelters
which accrue to the firm with virtual certainty. Discounting these tax benefits at
the WACC understates their present value which biases IRP against capital
intensive resources which generate higher tax-shield benefits.
iift Debt-Like Outflows: A variety of project costs, such as property taxes and
fixed maintenance present obligations whose risk is similar to the risk of the
interest payments on the firm's long-term-debt. They are hence discounted at the
firm's after-tax marginal cost of debt.®
ivl Pro-Cvclical Outflows: This group includes variable maintenance outlays
whose costs are driven by labor and material prices that vary with the economy.
The WACC serves as a reasonable proxy rate for this category. Econometric
analysis to estimate the beta is possible, though most likely not warranted in most
cases.
Table 1 shows a set of nominal, after-tax, proxy rates of return that based on recent
market conditions, but which may not reflect particular specific circumstances. This
disclaimer notwithstanding, they are undoubtedly superior to using the WACC. The
application of such market-based rates to projected revenue requirements yields results
that are at times significantly different from the commonly seen WACC-based estimates.
Table 2 shows a set of market-based, levelized busbar cost-estimates derived from the
8 The marginal cost of debt reflects the currently prevailing bond yields, not the original
coupon rates of the firm's debt.

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base-case conditions assumed by NARUC [1991] for coal, gas combined-cycle and
photovoltaics.
The market-based results vary materially from the WACC-based estimates, although the
differences are more pronounced in the case of gas which has a strong negative systematic
risk component (Table 2). The estimated market-based range for gas reflects estimated
betas in the West (low estimate) to those in the Northeast (high estimate). The results
suggest that photovoltaic-based electricity is more competitive with gas generation than
previously thought. The market-based costs of coal generation are 9.5 cents/kWh, as
compared to the 7.7 cents estimated using the WACC. This difference is not as significant
because coal prices are nearly riskless, so that the discount rate is not as low (or as far
below the WACC) as it is for gas.
These results all assume that the systematic component of historic fuel-price variability
continues into the future. If forward commodity markets develop more fully for gas, thus
enabling the establishment of hedging strategies, it may be possible for a firm to develop
an options portfolio that delivers gas at a predictable or riskless future price. Under such
circumstances gas will cost more than the consensus price projections made by NARUC.
However, even if we ignore this, and assume simply that NARUC's gas forecast is riskless-
- an unlikely possibility its WACC-based results are still incorrect.
If it indeed makes sense to assume that gas can be obtained with certainty at the projected
price then the correct present value of the projected gas outlays is obtained by discounting
them at the riskless rate, not the WACC. So doing yields a levelized gas estimate of about
13.7 cents/kWh, (Table 2)~ not the much lower WACC-based estimate commonly seen.;
The WACC does not become the correct discount rale when we assume that a particular
cost component is riskless.
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The Two Components Of Risk: Clearing Up The Confusion
There is considerable confusion regarding the correct procedures for handling risk which
stems from a lack of understanding of the role of systematic and unsystematic risk in
project valuation. For example, a recent report by the National Renewable Energy
Laboratory [1993] concludes:
Increasing the discount rate is a poor substitute for explicitly capturing the
uncertainty in the input variables	 its use... is questionable."
This conclusion is inconsistent with finance theory, which provides us with the basic rule
of valuation: expected cash flows are discounted at the market-based (risk-adjusted)
return. Systematic risk is reflected in the discount rate while random or unsystematic risk
is reflected in the proper estimation of expected cash flows,? which at times requires the
use of simulation and decision theory.
Properly estimating the expected cash flow does not eliminate the need for correct
discount rate estimation. The systematic risk captured in the discount rate is in addition
to the need to correctly capture random risk (uncertainty) in the cash flow estimates
themselves-- both are required. For example: an expected fuel-price stream must be
correctly estimated using appropriate econometrics or decision theory. This expected
value must be discounted at a risk-adjusted rate that reflects its systematic variability— the
fact that returns to assets in the economy decrease when fuel prices rise. This systematic
9 The expected result has a strict definition: it is the probability-weighted average of all
possible outcomes. This differs from the modal, 'promised' or most likely outcome.
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fluctuation is the basis for the required rate of return It cannot be captured in the price
projection which is merely the mean or expected value.
Similarly, in the case of PV, an expected useful life must be estimated which reflects the
unsystematic risk of array failure— some will fail before others. The expected costs,
however, (e.g. fixed maintenance) are discounted at the appropriate risk adjusted rate.
Sensitivity analysis and Monte-Carlo simulation, which is increasingly used in IRP, deal
with total risk (i.e systematic plus random). The distinction between total and systematic
risk is fundamental in capital market theory [see: Stewart Myers, 1976].
Total Risk is the variability in year-to-year returns to an asset or cash flow. It is the sum of
systematic and unsystematic risk. The example first used by Stewart Myers illustrates
these concepts:
The owner of a roulette wheel is exposed to considerable business risk— fortunes can be
made or lost by the "house" in any one night. But this business risk is random or
unsystematic and the owner can easily diversify it by owning many roulette wheels so that
on any given night some make money while others lose. Now the owner is exposed only
to the remaining, non-diversifiable, systematic risk: when the economy is good more
tourists show up to play than when the economy is poor. Beta reflects only this
remaining risk, which is almost impossible to diversify since there are few, if any,
investments that provide a counter-cyclical stream of returns.M Since investors can
easily eliminate un-systematic risk through diversification, the market does not
compensate them for accepting such risks.
10 Hedging or defensive stocks- those with betas less than 1.0, perform better in
recessionary times, although the returns are still higher during good economic times.
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But this does not mean that random risk is irrelevant to project valuation— such risk
clearly affects the distribution of expected cash flows-- it simply implies that unsystematic
risk does not affect the discount rate. The value of a one-roulette wheel business is
determined by first estimating expected cash flows, which could be accomplished
analytically, or by a simulation of the wheel to develop a probability distribution of the
possible outcomes, and the expected value. The business will do better in some months
than in others simply because of chance, but these variations are random and unbiased— at
the end of some sufficiently long period of time, say five years, the earnings will quite
closely match the expected value. The cash flow estimates therefore represent an
unbiased expectation of the fiiture.
The discount rate used to value the net cash flows of the roulette-wheel business are
insensitive to these random monthly or yearly fluctuations since owners can readily
diversify them by having many roulette wheels, not necessarily in the same location.
Under such conditions the actual cash flow in every period— say monthly, would be very
close to the expected value, if attendance at the casino remained constant. But
attendance will vary— presumably with economic conditions, so the expected cash flow of
the business will move with economic conditions. This variability cannot be eliminated.
Technology Risk:
Emerging technologies such a photovoltaics are said to pose a so-called technology risk:
the arrays may degrade or may not survive the 30 years or so promised by manufacturers,
It is frequently, and erroneously assumed that this technology risk justifies the use of
higher rates to discount the benefits. But array-failures are random, and by studying past
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performance we can develop an expected array life— the probability-weighted mean of all
the lives examined.^
For example, there is a finite possibility that some proportion of installed PV cells will only
last 15 years. Others may last 35 years. The expected useful life is the weighted average
of the possible outcomes, as opposed to the modal or promised useful life. Clearly the
"technology risk" of PV may suggest an adjustment to the expected cash flow— it may not
last for 30 years as promised. Yet this array life is a random or unsystematic risk. Owning
many arrays diversifies the outcome so that a constant percentage of units fail each year so
that a replacement reserve can provide the needed replacements. As a result the discount
rate remains unaffected.
Yet to some these arguments seem less than satisfactory, leaving the potentially troubling
issue of technology risk unresolved. Their reasoning is that there exists a finite probability
that an array will fail prematurely, and, in the absence of guarantees by the manufacturer,
such a failure poses a significant uncertainty, thus suggesting that the discount rate should
be altered.
But, as we learned from the roulette-wheel case, this risk is easy to diversify-- it is
virtually eliminated in a large installation, of say, hundreds of arrays. Now some relatively
constant percentage of arrays will fail every year, which is not a risk issue-- but involves
properly forecasting reserve requirements to cover replacements.
11 Additional discussion of technology risk as a R&D Risk can be found in Awerbuch and
Preston, [1993]
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For example: suppose arrays are expected to fail at the rate of one failure per 1000
modules per year. If we are considering an installation with 20,000 modules then we
would allow O&M funds sufficient to replace 20 each year. This is not particularly risky—
not because the number of expected failures is small, but rather because the number of
expected failures is relatively constant year-to-year and uncorrelated to economic events.
In other words, we have diversified the technology-failure risk. Indeed this risk is
identical to the risk surrounding the failure of major components for any other teclinology
including gas turbines and nuclear plants. In order to value the investment correctly it is
important only that the expected life used is unbiased (i.e. represents the mean of a normal
distribution).
Having estimated the expected life we can proceed to value the PV installation using
appropriate risk adjusted discount rates. In the case ofPV, the operating risks are quite
minimal since nearly 100% of the costs are sunk. The fixed maintenance costs— virtually
the only operating cost component— are quite predictable so that the operating outlays are
essentially riskless. Moreover, the revenue risks are also random: they follow electric
output which will show small yearly fluctuations as the results of changes in insolation
[Awerbuch, 1991], But this variability is random and unbiased- the sun will insolatc a
certain amount, on average, over a period of several years. The foregoing arguments lead
to the conclusion that PV technology, in its mature state, is essentially riskless for project
valuation purposes.
Portfolio Theory

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Underlying most fundamental IRP resource decisions is a 30-Year fuel price forecast for
gas and coal. But lei's face it— fuel prices are hardly predictable even over short periods,
let alone 30 years. It is therefore important to develop IRP strategies that are less
sensitive to such projections. This is not impossible— consider the fact that many
investors regularly make long-term financial investments for retirement and other
purposes, yet they do not expect their financial advisor to produce a 30-year performance
forecast as the basis for an investment recommendation. So, since commodity fuel
markets are no more predictable than the stock market, why not borrow some of the ideas
that financial investors have developed to mitigate risk and apply them in IRP?
Since fuel prices are similar to stock market returns in the sense that neither is predictable,
it makes sense to examine the mathematical portfolio techniques that have been developed
to maximize return from financial investments.^ Indeed the investor's problem, i.e.:
maximize, return for a given level of risk, is directly analogous to the IRP problem— which
is to minimize cost for a given level of financial risk. However, the IRP problem is
generally defined naively as finding the least cost resource alternative. But the problem is
not a simple as that. If it were, then financial investors would only have to invest in that
single stock which had the highest expected return.
In other words, if financial investors used the ERP approach, they would simply put most
of their money into a single stock— the one with the highest expected return. .Such an
approach quite obviously makes little sense, although tliis was not clearly recognized in
the investment community as recently as a generation ago [Varian 1993, 159], In fact it
was the insight that this approach must be "patently unrealistic" that led to Nobel Laureate
12 Financial investments are quite reversible as compared to resource options and perhaps
this limits these arguments somewhat but the principal points remain.
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Harry Markowitz's development of modern mean-variance portfolio theory [Varian, 1993,
160],
If we apply portfolio theory to the IRP process than the portfolio selection problem is
based on two factors: i) the risk or variability of expected annual costs of a particular
resource option, and ii) the co-variability of those costs with the portfolio of generating
assets. This reduces to valuing a resource not on its stand-alone life cycle costs, but on its'
cost contribution to the generating portfolio relative to its risk contribution. Current IRP
valuations, by contrast, reflect only the life-cycle costs of individual resource options,
ignoring their role in the resource-mix,
The application of mean-variance portfolio techniques can help create a resource-mix that
minimizes cost for given levels of risk, while yielding predictable results over a range of
economic conditions. Interestingly, it turns out that the ideal mix of risky, or fossil based
technologies may be invariant to potentially different risk preferences that may exist in
different jurisdictions.
While considerably more research is required, mean-variance techniques have been applied
to hypothetical generating portfolios consisting of three technology types: coal, gas and a
riskless renewable such as photovoltaics in a fully operational and mature state
[Awerbuch, 1993c], This analysis of a hypothetical generating portfolio yields several
interesting and important preliminary results:
i) Optimal generating portfolios have a mix of risky (fuel-based) and riskless resource
options, just as optimal financial portfolios have a mix of risky securities and
riskless Treasury bills. High-coal (over 70%) utilities should be able to reduce risk
(cost variability) without increasing costs by adding gas and riskless renewables to
the mix.
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ii)	Overall welfare may be enhanced by allowing customers to buy some portion of
their energy from riskless sources under long-term fixed-price contracts. This
provides theoretical support for a somewhat revised set of'green-pricing' concepts
since renewable-based electricity may cost more initially, but would be fixed over
time.
Under this concept ratepayers would in essence hold a 'portfolio' of rate
obligations consisting of; i) a riskless (fixed) obligation on renewable energy
coupled with ii) a risky or variable obligation on conventional fossil-based
electricity. It may be possible for ratepayers to adjust this portfolio over time, as
the outlook or their needs change, (e.g.: some ratepayers may want to increase the
amount of riskless electricity they buy as its cost declines, others may want to take
more risky electricity if they perceive temporary attractive prices. In general risk-
averse ratepayers could choose to purchase more of their electricity from riskless
sources just as many people select fixed-rate mortgages which cost more initially.
iii)	Sensitivity/simulation analyses, which are widely used to simulate the results of
IRP resource-mixes, improperly understate the risk of the conventional fossil fuel-
based portfolio.
THE HOLE OF ACCOUNTING MEASUREMENT IN IRP
Utility Accounting Was Designed for Regulation, Not Decision-Making
IRP resource decisions are made using inadequate, outdated accounting concepts which
have been abandoned by most globally competitive firms. The structure of utility
accounting systems is specifically designed to distinguish between assets and expenses in
order to accurately calculate the utility's rate base, which serves as the foundation for
setting regulated rates [Preston and Awerbuch, 1993], The system is intended for
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regulatory use, to allow utilities to recover their operating costs and earn a return on the
depreciated assets.
1RP, by contrast, seeks to identify least-cost generating alternatives, where cost is defined
as the busbar cost- the familiar '$/kWh' measure— wliich reflects only the direct costs of
generating electricity including: i) direct initial capital outlays, ii) annual fuel expenses;
and iii) annual direct operating costs such as maintenance, property taxes, etc.
Omitted from the busbar cost, and hence ignored in IRP, are a variety of indirect costs
required to generate electricity and get it to the customer's meter. These costs include such
items as i) transmission and distribution, ii) administrative and general (A&G), iii) a variety
of transactions costs reflecting such activities as compliance with clean air requirements,
and, iv) customer costs such as meter reading.
These indirect costs are collected into cost pools which are then allocated to all projects
based on arbitrary formulas. Such procedures represented standard accounting practice
for over a century— when they were conceived a century ago indirect costs were small and
uncontrollable; it would have made little sense to track them explicitly. Recently however,
these procedures have been abandoned in unregulated firms, where they created
impediments to the adoption of new, capital-intensive process technologies such as
computer integrated manufacturing.
The IRP process would therefore be significantly improved if total costs were used in
place of the traditional busbar cost measure but present accounting systems are inadequate
to support such comparisons because most costs are not tracked by technology, and
others, such as overheads, are pooled and arbitrarily allocated on the basis of direct
5-42

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costs.'-* In utilities, arbitrary cost-allocation procedures may also have been appropriate
at one time when technology choices were homogeneous— coal-based generation did not
create materially different overhead requirements than did, say, oil-fired generation.
Utility accounting procedures can thus not distinguish between low-overhead projects
such as PV, and high overhead projects such as, say, coal. The traditional busbar-based
LRP cost comparisons therefore lead to the selection of resource alternatives with low
direct costs, although such technologies often have very high "hidden" or indirect costs
which are not reflected in the IRP process. These include central administration,
transactions, and regulatory costs, none of which are traced directly to specific plant or
technology types. Moreover, ignoring the "hidden" costs leads to improper avoided cost
measures and inefficient decision-making regarding independent (EPP) power purchases.
Because of their exclusive reliance on the busbar cost, IRP procedures are currently biased
in favor of conventional technologies. For example:
1.	A&G costs are commonly added to projects as a percentage of the capital
outlay. Compare a $5Q0/kW gas turbine to a $5,000/kW PV array where both
options generate the same energy annually: if the A&G add-on is 20%, the turbine
will be 'loaded' with $100 in 'overhead', the PV with $1,000. Using conventional
IRP procedures this overhead loading adds a significant S.05/kWh to the 'cost' of
PV electricity, but only one-tenth that amount to the turbine. Ironically, the PV
array will consume virtually no overhead resources as compared to the turbine.
2.	Assume that it is feasible to lease the PV array for a fixed fee, so that monthly
meter-reading and billing is not required. This represents a further, and for small
customers, significant cost reduction.
3.	In a distributed setting the PV may consume no transmission and little
distribution costs. Moreover, it has become clear that PV is cost effective in
^ PV and similar technologies are capital intensive which suggests that under certain
allocation formulas they may absorb an even greater disproportionate share of overhead
; allocations. The irony is that PV and other renewables would be saddled with relatively
high overhead allocations even though their overhead requirements are quite small.
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serving small, remote loads. There may be other types of load requirements which
are also effectively served by PV. A properly constructed cost system, which
traces costs to resource types and to customer-service groups can help identify
these.
In addition to essentially ignoring the role of important indirect costs in the valuation of
1RP resources, reliance on traditional accounting masks the true cost drivers affecting the
production of electricity. This is similar to what happened in manufacturing, where
traditional unit cost accounting measures— e.g. cost/product produced on the assembly
line, masked such cost drivers as low quality and excessive inventories. The introduction
of modern Activity-Based-Costing (ABC) systems began to show, for example, that
overall costs could be reduced by eliminating the costs associated with manufacturing
defective products which then needed to be repaired or re-manufactured. The realization
that quality manufacturing minimizes total costs is partly based on accounting systems that
enabled managers to recognize the true cost drivers.
The outdated accounting systems underlying IRP suggest that the kilowatt-hour produced
is the cost driver. This is most likely not the case, and development of appropriately
conceived ABC systems may identify the true cost drivers— activities such as the
maintenance of excess capacity, compliance with clean-air act, negotiating fuel contracts,
maintaining fuel inventories generator ramp-up and the maintenance of spinning and idle
reserves. These important cost-drivers are not subject to mansgerial control on an
operating basis, rather they are predetermined by a cost chain-reaction set in place in the
IRP process.
Current IRP practices focus only on the busbar cost- the. accounting equivalent of the:
cost of goods sold [Preston and Awerbuch, 1993], The process must in addition reflect
the following for each resource option:
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i)	The likelihood of that option creating excess capacity;
ii)	The corporate resources consumed and transactions costs created by this
option;
iii)	The corporate resources consumed in planning and executing the option— this
is especially significant for large central-station plants such as coal.
IRP envisions that alternatives can simply 'plug into' the corporate infra-structure but this
view is naive. Different technologies consume corporate resources in radically different
degrees. It is imperative that such costs be reflected in the process. So doing may lead to
the realization that total cost is minimized with the generation offewer, smarter, kilowatt-
hours which have greater information content. Indeed this formula worked in
manufacturing. Implementing such decision-making capabilities will require the
establishment of properly conceived ABC systems that track costs to technologies, thereby
enabling estimates of total cost for resource alternatives.
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References
Awerbuch, Shimon, (1993a) "The Role of Risk and Discount Rates in Integrated
Resource Planning" The Electricity Journal, Volume *** No*** , (April).
Awerbuch, Shimon (1993b) "Measuring the Costs of Photovoltaics in an Electrie Utility
Planning Framework," Progress in Photovoltaics: Research and Applications, Volume 1
No. 2, (April); Chichester: John Wiley and Sons.
Awerbuch, Shimon, 1993c, Review of Methodologies to Analyze the Economics of
Competing Energy Technologies: A Framework for Evaluating Photovoltaics, Section
111: The Application Of Mean-Variance Portfolio Theory To The Valuation Of Competing
Energy Technologies; Sandia National Laboratories, Contract #67-4226, (October).
Awerbuch, Shimon (1992a), "Direct Testimony," , Investigation into the Development of
Rules Concerning Integrated Resource Planning, Colorado Public Utility Commission
Docket 91R-642EG, (February).
Awerbuch, Shimon, "Determining a Bid Price for PV-Generated Electricity Under an IPP
Agreement," Report Prepared Under Contract to Sandia National Laboratories, March
1992.
Awerbuch, Shimon (1992) "Depreciation For Regulated Firms Given Technological Pro-
gress and a Multi-Asset Setting," Utilities Policy, Volume 2, No. 3, (July), 228-239.
Awerbuch, Shimon, (1992a) "Depreciation and Profitability Under Rate of Return
Regulation," Journal of Regulatory Economics, Volume 4, (1992) 63-70.
Awerbuch, Shimon and Alistair Preston, (1993) "We Do Not Have the Measurement
Concepts Necessary To Correctly Implement IRP: A Synthesis and Research Agenda,"
Working Draft.
Awerbuch, Shimon and William Deehan, (1993) "Do Consumers Discount The Future
Correctly? A Market-Based Valuation of Residential Fuel Switching," Working Paper.
Booth, Lawrence D., "Correct Procedures for Evaluation of Risky Cash Outflows,"
Journal of Financial and Quantitative Analysis, 27, (June 1982) 287-300.
Brealey, Richard, and Stewart Myers, 1991 Principles of Corporate Finance, McGraw"
Hill.
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**CIark, Kim "Investment in new Technology and Competitive Advantage" in David J.
Teece (Ed.) The Competitive Challenge; Strategies for Industrial innovation and
Renewal, Ballingcr Division —Harper and Row, 1987.
Copeland, Thomas, and Fred Weston, Financial 'Iheory and Corporate Policy, Third
Edition, Addison Wesley, 1988.
Electric Power Research Institute, Capital-Budgeting Notebook, [RP 1920-03, November
1990, 9-13 to 9-22], Palo Alto, CA.
—Evaluating the Effects of Time and Risk on Investment Choices: A Comparison of
Finance Theory and Decision Analysis, [P-5028, January 1987].
—Capital Budgeting for Utilities: The Revenue Requirements Method [EPRI EA4879,
October 1986, Chapter 2].
--Analysis of Risky Investments for Utilities [EA-3214, September 1983].
—"Choice of Discount Rate in Utility Planning: Principals and Pitfalls,"
[EA-2445-LD, June 1982].
* "'~Henderson, Rebecca and Kim B. Clark, "Architectural Innovation: The
Reconfiguration of Existing Product Technologies and Failure of Established Firms,"
Administrative Science quarterly, Volume 35, (1990) pages 9-30.
***Hirsch, Richard Technology and Transformation in the American Electric Utility
Industry, NY Cambridge Univ. Press, 1989.
Kahn, Edward, 1988, Electric Utility Planning and Regulation, DC: American Council
for an Energy Efficient Economy.
Myers, Stewart 1976, "Postscript: Simulation for Risk Analysis," in: Stewart Myers,
(Editor) Modern Developments in Finance, Dryden Press.
NARUC, 1991 "Electric Power Technology: Options for Utility Generation and Storage,"
Prepared by the Staff Technology Subcommittee, Finance and Technology Committee.
National Renewable Energy Laboratories, [1993], Analytic Studies Division:, A Manual
for the Economic Evaluation of Energy Efficiency and Renewable Energy Technologies,
Golden CO.
Preston, Alistair and Awerbuch, (1993) "Activity-Based Cost and IRP," working draft.
Rao, Ramesh, Financial Management: Concepts and Applications, Macmillan, 1992,
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Schnee, *****
Seitz, Neal, Capital Budgeting and Long-Term Financing Decisions, Dryden Press, 1990,
Williams, Robert H. and Gregory Terzian, (1993) "The Direct Economic Benefits of
Accelerated Development of Renewable Energy Technologies: A Case Study of
Photovoltaic power," Draft, Center for Energy and Environmental Studies, Princeton
University (March).
U.S. News & World Report, "The Hidden Picture," April 29, 1991, p, 50.
Varian, Hal, 1993, "A Portfolio of Nobel Laureates, Markowitz, Miller and Sharpe,"
Journal of Economic Perspectives, Volume 7, Number 1, (Winter).
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TABLE 1
Nominal After-Tax Discount Rates For Project Cash Flow Components8
CASH FLOW
•	Counter-Cyclical Risk
Oil and Gas
Coal
•	Debt-Equivalent Cash Flows^
Property Taxes
Insurance
Fixed O & M
Working Capital
•	Riskless Cash Flows
Depreciation Tax Shields
Tax Credits
Beta
-0.5 to-1.25
-0.2 to -0.4
Suggested
Discount Rate
0.05%
2.0%
5.0%
5.0%
5.0%
5.0%
4.0%
4.0%
Estimation
Method
Econometric-CAPM
m	h
By Convention
By Convention
• Pro-Cyclical Risk
O&M (Variable)	--	8.5%c	Judgmental
a.	Using: 4% risk free rate, 12.0% expected market return, 39% combined, federal-state income tax rate;
b.	Based on 8% marginal cost of debt;
c.	Uses the firm's after-tax WACC; Based on 10.4% Pre-Tax WACC with 50% debt and 10% preferred stock.

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Table 2: WACC-based and Market Based Levelized Revenue Requirements®
WACC-Based Estimates Market-Based Estimates0
Resource Option	CCents/kWhl	CCents/kWh')
Coal-Fired Steam
NARUC Base Case	7.75fe	9.5
Carbon Tax Adjustment	9.5	12.8
Gas Combined Cycle
NARUC Base-Case	8.3^	15.0-26.2
Riskless Future Gas Prices	8.3	13.9
Pbotovoltaics
NARUC Base-Case	24.6fr -	20.7.
a.	Based on a 7% riskless rate, a 14% market rate, and a 9% cost of debt,
b.	Technology assumption and costs taken from NARUC [1991];
c.	Source: Awerbuch 1992 [Colorado testimony.* and reply*]

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Figure 1
Using the CAPM to Estimate Discount Rates for Projects and Revenue Requirements
Km - Required Return to Diversified
Market Portfolio
Kj =« Required Return With Beta = Bj	Market Risk-Return Line
Shimon Awerbuch, Ph.D. Nashua, NH 03062
\text\rabago\FIGURE-1 .XLS Chart 1

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5-n
POLLUTION MITIGATION AND PHOTOVOLTAIC DEMAND-SIDE RESULTS FROM THE
U.S. ENVIRONMENTAL PROTECTION AGENCY PHOTOVOLTAIC DEMONSTRATIONS
ABSTRACT
The U.S. Environmental Protection Agency, 21 electric power companies in the
United States, and the Electric Power Research Institute are conducting two
nationwide Photovoltaic (PV) Demand-Side Management (DSM) projects. Ascension
Technology is responsible for system design, balance-of-systems equipment design
and fabrication, installation supervision, field instrumentation, and data acquisition,
monitoring, and evaluation. The principal goal of the two projects is to investigate the
environmental and DSM benefits of distributed, grid-tied PV systems as pollution
mitigating energy replacements for fossil fuels. In 1993-4,11. electric utilities
installed PV systems on homes, schools, hospitals, offices, and light commercial
buildings. In 1994-5, 12 electric utilities are installing PV systems on larger
commercial, educational, and industrial building rooftops.
This paper has been reviewed in accordance
with the U.S. Environmental Protection Agency's peer and
administrative review policies and approved for presentation and publication.
INTRODUCTION
Perhaps the most promising and potentially ubiquitous solar energy application
is based on PV conversion, the direct conversion of sunlight into electricity.
Tremendous opportunities exist for PV technologies to help meet the growing
electric energy needs in the 21st century. Costs have come down dramatically (about
70% per decade) since solar cells were first used in spacecraft applications. The
current cost of energy from PV systems is 30 to 40 cents per kWh, but technology
advances are expected to drop costs to under 10 cents per kWh by the year 2010.
Competition with fossil-fuel-fired power generation is difficult in current bulk power
markets, but PV will almost certainly be cost-effective for interconnection to electric
grids within 15 years.
Edward C. Kern, Jr. and Daniel L Greenberg
Ascension Technology, Inc.
Ronald J. Spiegel
Air Pollution Prevention and Control Division
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
P.O. Box 314
Lincoln Center, MA 01773
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For grid-connected PV systems, the most immediate opportunity is on the
customer-side, or demand-side, of the meter, where the customer's peak demand
can be partially met using PV systems. For example, in some utility service areas
effective summer peaking rates range to over 40 cents per kWh. This implies that
demand-side PV used to reduce peak building loads might be cost-effective al
today's PV prices. Additional PV value can often be found where PV offsets
requirements for new investment in electric transmission and distribution
equipment.
U.S. ENVIRONMEN TAL PROTECTION AGENCY PROJECTS
Because of solar energy's huge potential and clear environmental benefits, the
U.S. Environmental Protection Agency (EPA) initiated its PV demonstration program. A
competitive procurement in fall 1991 led to the selection of Ascension Technology
as prime contractor. The project approach has been to install and monitor solar PV
energy systems at diverse locations spanning the United States.
EPA Project One
In August 1992 EPA awarded Ascension Technology a contract to conduct a PV
DSM project. The goal of the EPA PV project is being accomplished through case
studies of PV systems installed by the project in 17 cities and by comparing PV DSM
system performance with the actual operating characteristics of 11 project
co-sponsor electric power companies: Arizona Public Service, Atlantic City Electric,
City of Austin Electric Department, New England Electric, New York Power Authority,
New York State Electric and Gas, Northeast Utilities, Northern States Power, Pacific Gas
and Electric, Southern California Edison, and Wisconsin Public Service. Each utility has
installed 3.6-, 7.2-, or 10.8-kW rated! PV systems for 101 kWac total project capacity.
EPA Project Two
In September 1993 EPA awarded a second contract to Ascension Technology
to conduct a DSM assessment of PV systems on commercial, institutional, and light
industrial buildings. This contract expands and builds upon the prior project by
broadening the geographical coverage and by refining PV system designs for ease of
installation, system safety, and electrical code compliance. In this project Arizona
Electric Power Cooperative, Atlantic City Electric, Boston Edison, Consolidated Edison
(New York), Duke Power Company (North Carolina), Florida Power Corporation, Idaho
Power Company, Los Angeles Department of Water and Power, Nevada Power
Company, New York State Electric and Gas, Public Service Company of Colorado, and
Public Service Company of Oklahoma are each installing an 18-kW PV system, for a
combined capacity of 216 kWac. Together with EPA Project One, these systems cover
all but one of the North American Electric Reliability Council districts (the East Centred
Reliability Council being the exception). The 12 electric utility co-partners are
working with the Electric Power Research Institute to co-sponsor the project.
iPV systems are typically rated by the amount of power they will produce under bright
sunlight conditions (irradiance on the solar panel equal to 1 kW/m2) with the air
temperature at 20 °C.
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FIELD TESTING DISTRIBUTED PV GENERATION
The EPA project has installed and is monitoring DSM solar PV systems at
locations from northern New York State to Southern California. These systems supply
power directly to the user, where they compete with the retail price of electric
service rather than the bulk power supply cost to utilities. These systems are
monitored for performance and reliability, with data collected to support studies of
air pollution mitigation, utility demand reduction, and DSM impacts.
The EPA PV DSM monitoring began in July 1993. Electric demand and PV
electric supply data are transferred daily by modem from sites across the country to
Ascension Technology's offices in Waltham, MA. Example data for a 3.6-kW system
on an office building in Minnetonka, MK, is shown in Figure 1. Since the building load
is typically greater than the PV power generation, in this chart each has been
normalized for ease in comparing the load shapes. The building load shown has been
normalized by the peak demand that occurred during the day, and the PV generation
has been normalized by the PV system's power rating. (On this day the PV system
achieved 80% of its potential capacity, probably owing to a high, thin cloud cover.)
The contribution of PV generation has ranged from over 100% of average monthly
electricity consumption for a residence in California, to less than \% of consumption
for some of the commercial facilities involved in the project. It should be noted,
however, that the PV systems usually cover under 10% of the useable roof area on the
commercial buildings.'
POTENTIAL ENERGY AND ENVIRONMENTAL BENEFITS
Residential, commercial, and industrial buildings account for 96% of the
electric energy consumed in the United States. Depletable coal, oil, and gas fossil
energy reserves generate 70% of this electricity and represent a significant
contribution to U.S. global warming and environment-degrading gas emissions. Fossil
fuels used for electric power generation are estimated to account for 34% of the
carbon dioxide (CO2), 67% of the sulfur dioxide (S02), and 37% of the nitrogen oxide
(NOx) emissions into the atmosphere from controllable sources [1]. PV generation,
installed where possible in the U.S. inventory of residential, commercial, and
industrial buildings, could produce 20% of the Nation's electricity in an environ-
mentally benign, distributed, and secure way.
The environmental benefits of DSM using PV power supplies are significant.
Determining environmental benefits requires information about the energy produced
by the PV system, the avoided power plant fuel consumption, and stack emissions
from a mix of gas-, oil-, coal-fired generating stations. Hi'A intends to help quantify
these benefits using the measurements from these projects. Assuming a 20% PV
capacity factor and offsetting emissions from electric power generation using today's
mix of power plants, each megawatt of PV generating capacity has the potential to
offset approximately 1,100 metric tons of CO2 emissions annually.

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MONITORED ENERGY AND ENVIRONMENTAL BENEFITS
Two primary data sets are being recorded for each PV system: energy
produced by the PV system and energy demanded by the host building. To verify the
performance of the PV array and the data acquisition system, both a plane-of-array
irradiance pyranometer and a rotating shadowband pyranometer to measure global,
direct, and diffuse irradiance have been installed. This allows for cross-checking
system performance through the use of array and power conditioner simulation
algorithms. It also verifies the translation algorithm from direct normal and diffuse
irradiance to plane-of-array irradiance, an essential tool in the translation of the
results of the project to other potential PV system designs and to sites with similar
solar resource data. Participating utilities provide hourly records indicating which
load-following power plants (marginal or "swing" plants) are operating as well as total
utility system load. They also supply emissions data for their load-following
generating stations. Currently the project tracks CO2, NOx, SO2, and particulate
emissions.
Figure 2 illustrates the aggregate electricity that has been produced by the EPA
Project One systems starting in July 1993. Variations in energy production result from
several factors: the rating of the systems which range from 3.6 to 10.6 kWac-rated,
the date of system installation and start-up, the solar resource available for
conversion to electricity, and the system reliability. The largest systems in
Ashwaubenon (WI), Austin (TX,) Palm Desert (C.A), Pleasantville (NJ), San Ramon (CA),
and Scottsdale (AZ) have demonstrated the greatest energy production. These have
shown comparable generation, but it is interesting to note that the Arizona system is
rated at 7.2 kW while the others are 10.6 kYV. The significantly larger solar resource in
the Southwest caused this effect. The Plattsburg (NY) system is also 10.6 kW, but has
suffered from several power conditioner failures and heavy snow coverage.
Figure 3 presents 12 month generation results from 16 of the 17 systems (the
Barstow, CA, system has not yet operated for a full year) normalized by their
respective kWac ratings at standard operating conditions (I kW/m? irradiance and
ambient temperature of 20°C). Annual generation varies widely from a low of 900
kWh/kW in Plattsburg, NY, to 1845 kWh/kW in Scottsdale, AZ.
Figure 4 presents the building peak demand reductions caused by the
connection of PV system output to the customer's side of the demand meter. For
each site, the height of the bar represents the output of the PV system at the time of
the highest building load recorded during the entire 15-month study period. Note that
these values are expressed as a percent of the rated PV generation capacity (at
standard operating conditions) rather than as a percent of the building peak demand.
In this way the demand reduction value of the PV systems can be determined by
multiplying the rating by the percentage.
In areas of high electric power generation cost, a 1 kW reduction in demand for
a month can be worth up to $10. Since the PV generation is, to a first approximation,
symmetrical about solar noon (1 pm for daylight savings time), the best correlation of
PV generation to building loads occurs when the building load peaks in the early
afternoon. This happens routinely in commercial buildings with peaking
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air-conditioning electrical demand in the midafternoon. Many studies of PV system
worth show this capacity value is about equal to the energy value. With the addition
of energy storage, the capacity worth can be increased to 100% or even more than
the PV array rating, depending on the relative sizing of PV arrays, batteries, and the
dc-to-ac converter.
Figure 5 illustrates the aggregate CO2 emission reduction benefit of PV power
generation. These results are based on performance data from the various PV
systems and C02 emissions data provided by the co-sponsor electric utilities. Figure
6 presents annual offsets for each of the Project One sites, normalized by the
expected kW output of each system under standard operating conditions (units are
therefore kg/kVV of rated PV capacity). The lighter shaded area in the background is
an approximation of the annual CO2 offset per kW for a PV system whose generation
displaced the national average emission rate of 0.6 kg/kWh.2 Annual reductions in
C02 emissions range from 650 to 2,270 kg / kW of PV system rating. The variance
among the results depends on the solar resource factor and the 2 to 1 variation in
CO2 emissions between coal-fired and gas-fired generation.
Similar results for S02 emissions are shown in Figures 7 and 8. Again, the
results vary widely (from 0.2 to 16.3 kg per kW of system rating) because of regional
fuel use and solar resource differences. Where PV displaces coal-fired generation
the environmental benefits are the greatest. The lighter shaded region in the
background indicates an approximation of the average annual S02 offset that would
be produced by a PV system displacing generation by a unit with the national average
SCb emission rate.
Finally, Figures 9 through 12 present our findings for NOx and particulate
emissions. Preliminary indications are that avoided NOx emissions range from 0.12 to
over 8.7 kg annually per kW of PV capacity (for comparison, our estimate of the
national average offset is 2.6 kg/kW). Annual particulate offsets exhibit a similarly
broad range from under 20 g/kW to 600 g/kW (as compared to an average of 0.21
kg/kW).
Data reduction techniques for assessing these avoided emissions are under
development and testing, so it is important to recognize these as preliminary results.
Further, there is considerable room for debate as to the correct algorithm to use for
determining environmental benefits. For example, many of the emission rates used
in this study are for coal plants that are currently being equipped with "end of the
2Average annual emission offsets were derived by applying national average emission
rates to an approximation of average annual generation (kWh/kW) based 011 the
performance of Project One PV systems. Average generation was calculated by
determining average regional generation for PV systems in the Northeast, the Midwest,
and the Southwest, and then calculating the average of the regional averages. National
emission rates, in turn, were derived by dividing total utility emissions for 1993 as
listed in the Energy Information Administration publication Electric Power Annual
1993 by total kWh generation for that year [2J.
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stack" emissions control technology. Future emissions savings from PV will not
materialize if the current high emissions rates are substantially reduced by these and
other measures to improve existing fossil electric power generation stations.
Another consideration is the dispatch order assumed for this study. It has
been assumed that PV represents a small fraction of the electric generation capacity
so that fossil plant unit commitment and dispatch are not affected. Accordingly, we
have assumed that those power plants that are operating under automatic generation
control are the ones whose emissions will be reduced. When PV power achieves a
substantial fraction of its potential, electric power companies should be able to make
accurate short run (e.g., 24-hour) projections of PV generation. At such time, PV will
likely displace intermediate plants with slower response (ramping) characteristics and
potentially greater air emission offsets since these plants tend to be oil- or coal-fired,
whereas load following plants tend to include cleaner gas and hydroelectric stations.
This suggests that the current estimates might imder predict the emissions savings.
Finally, this study is based on the presumption of economic, rather than
environmental,dispatch. If power systems are controlled so as to minimize harmful
emissions from fossil-fuel-fired plants, the emissions reductions from the PV plants'
operations would be reduced.
ACKNOWLEDGMENTS
This project has been funded in part by the Environmental Protection Agency under
contracts 68-D2-0148 and 68-D3-0.144.
REFERENCES
1.	Statistical Abstract of the United States 1992, Table 354, p. 213, U.S. Department
of Commerce, 1992.
2.	Electric Power Annual 1993, DOE/EIA-0348 (1993), U.S. Energy Information
Administration, Washington, D.C., December 1994.
5-5?

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FIGURE 1 NORMALIZED SUMMER PV GENERATION AND
BUILDING DEMAND PROFTI.ES FOR AN OFFICE
BUILDING IN MINNETONKA, MN.
3 am 6 am Sam 12 pm 3 pm 6 pm 9 pm 12 am
I » Measured PV ! Rlrig Lnari —Simulated PV
FIGURE 2 PHOTOVOLTAIC POWER GENERATION FROM TIIE
EPA PROJECT ONE SITES JULY 1993 THROUGH
SEPTEMBER 1994.
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FIGURE 3 ANNUAL GENERATION PER KILOWATT
Annual Generation (kWh/kW)
200Q
1500-
1C00
500
FIGURE 4 FV GENERATION AS A PERCENT OF RATING
DURING BUILDING PEAK LOAD HOUR
100
Percent cf Rating


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FIGURE 5 ESTIMATED REDUCTION IN CO, EMISSIONS BY THE
EPA PROJECT ONE INSTALLATIONS
FIGURE 6 ANNUAL CO, OFFSET
2500
200C
150C
1000
500
Annual Offset (kg/kW)
lUmKiMUUI. IIIIIB		¦mi 					 I «
/O, <0	fo. (0	Q
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FIGURE 7 SO, EMISSION REDUCTIONS FOR THE EPA PROJECT
ONE INSTALLATIONS
FIGURE 8 ANNUAL SO- OFFSETS
^ Annual Offset (kg/kW)
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FIGURE <> N0X EMISSION REDUCTIONS FOR THE EPA
PROJECT ONE INSTALLATIONS
FIGURE 10 ANNUAL NOx OFFSET
Annual Offset (kg/kW)
101			
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FIGURE 11 REDUCTION IN PARTICULATE EMISSIONS FROM
THE EPA PROJECT ONE INSTALLAT IONS
FIGURE 12 ANNUAL PARTICULATE OFFSETS
^ Annual Offset (kg/kW)
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5-E
PHOTOVOLTAIC ENERGY IMPACTS ON U.S. CO2 EMISSIONS1
S C. Morris, J. Lee, P.D. Moskowitz, and G. Goldstein
Brookhaven National Laboratory
Upton, NY 11973
ABSTRACT
The potential role of PV technology in reducing C02 emissions in the United
States was evaluated in an energy-environmental economic systems model. The
model examined the role of PV in a competitive market environment. PV technology is
already competitive with fossil fuel electricity in off-grid applications. It competes
favorably in the U.S. for certain niche markets. Further growth in those markets is
expected as well as expansion into other markets such as peaking power. This
analysis indicated that, given anticipated improvements in cost and efficiency, PV will
compete favorably as a general source of electricity supply to the grid about 2010 in
the southwestern United States and soon thereafter for U.S. average solar conditions.
PV achieves a higher market penetration if constraints on carbon dioxide emissions are
imposed.
INTRODUCTION
Reducing the use of fossil fuels is a key element for the mitigation of greenhouse
gas emissions. Photovoltaic (PV) systems are currently cost-effective for off-grid
markets for electricity, especially in less developed countries. PV offers the opportunity
for holding down carbon emissions in these countries while contributing to ~ rather
than restricting - economic growth. This analysis, however, focuses on the potential
contribution that PV technologies can make to the reduction of carbon emissions from
the United States.
Studies examining issues of global climate change must consider time scales of
a century or more. Studies of specific technological options, however, are limited to a
reasonable range of technological foresight. This analysis considers the period 1990-
2030. It draws on projections from the National Renewable Energy Laboratory (NREL)
to characterize expected advances in PV technology. It uses MARKAL-MACRO, a
well-established energy-environment-economic systems analysis model, to examine
the competition between PV and other technologies available for reducing greenhouse
gas emissions in the energy system.
'For presented at EPA Symposium on Greenhouse Gas Emissions and Mitigation Research, June 22-29,
1995, Washington, D.C. The work described was not funded by the U.S. Environmental Protection
Agency. This work was prepared as an account of work sponsored by the U.S. Department of Energy.
Neither the United States Government nor any agency thereof, nor any of their employees, nor any of
their contractors, subcontractors, or their employees, makes any warranty, express or implied, or
assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any
information, apparatus, product, or process disclosed or represents that its use would not infringe
privately owned rights. The views and opinions of authors expressed herein do not necessarily state or
reflect those of the United States Government or any agency, contractor, or subcontractor thereof.
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OUTLOOK FOR PHOTOVOLTAICS IN THE U.S.
The cost of photovoltaic power has decreased over seven-fold in the past two
decades and is projected to decrease a further four-fold in the next two decades [1].
PV already competes favorably in the U.S. for certain niche markets. These include
accent lighting, security lighting, sensing devices, water pumps, communications and a
growing number of other uses. In the U.S., many of these uses compete directly with
grid-connected service, that is, services could be provided from the grid, but non-grid-
connected PV is chosen because of convenience or to avoid the cost of electric
connections. Current installed capacity in these applications in the U.S. (< 60 MW) is
several times larger than existing U.S. utility applications and is expected to grow at
roughly 10%/year through 2000 [2]. PV is also cost-effective in remote applications
where grid connection is infeasible and the competition is diesel generators. This
market is smaller in the U.S., however, than in other parts of the world.
Near-term utility applications are likely to focus on peaking power and power
conditioning applications. Many utilities, especially in the U.S. Southwest, experience
their peak load coincident with peak solar insolation. This maximizes the value of PV
for peaking power. The modular capability of PV allows utilities to install appropriate
capacity levels in needed locations. Grid-connected demand-side systems are now
being installed on building roofs. Thirty-nine utilities are testing grid-connected PV
systems in the U.S. [3]^ A number of experimental or demonstration installations are
expected over the next five years, adding 20 MW, although there is also a proposal for
a 100 MW facility [4].
Over the longer term (2000 to 2030), if expected improvements in efficiency and
cost materialize, PV may become competitive with fossil fuel plants. If constraints on
environmental emissions become more stringent, PV will have an additional advantage.
A far-term potential application of PV is the production of hydrogen to provide a carbon-
free fuel for heating and motive power. This has been explored and found cost
effective under severe carbon emission constraints in Europe [5]. It was not
considered in the current analysis.
ANALYSIS OF GREENHOUSE GAS MITIGATION WITH MARKAL-MACRO
Model
MARKAL-MACRO is an integrated planning tool for energy-environment-
economic systems analysis [6]. It is being used by many countries as a tool to examine
mitigation strategies for greenhouse gas reduction [7,8,9,10], It is currently being used
by the U.S. Department of Energy as the analytical tool in developing a least-cost
energy strategy for the United States. As part of this application, the technology data in
the model was substantially updated and reviewed [11], The model provides an explicit
representation of the interactions among the energy system, the economy, and the
environment. It allows inclusion of considerable technological detail on energy
technologies.
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The model can choose among a wide range of mitigation options. These include
reducing demands for energy services, investing in energy conservation measures,
investing in higher efficiency supply and end-use devices, switching from coal or oil to
natural gas, switching from fossil fuels to renewable technologies. In addition to PV,
renewable technologies included in the model are wind, solar thermal, biomass fuels,
wave, and ocean thermal gradients. The model is thus able to evaluate the potential of
PV in a competitive environment.
Characterizing PV
For this analysis, the characterization of PV in the model was expanded based
on data provided by the National Renewable Energy Laboratory (NREL) (Table 1).
This consisted of characterizing the capital and operating cost of PV by vintage year.
Between 1995 and 2030, module efficiency was assumed to increase from 7% to 16%
and system cost assumed to decrease from $7,000/kW to $640/kW (based on U.S.
average solar insolation of 1800 kWh/m2-y). NREL market projections suggested the
potential for 200 GWe of PV technology by 2030. This was used as an upper bound in
the model.
Scenarios
Three scenarios were developed for the analysis. The Reference scenario
assumed average U.S. solar insolation and NREL expectations of improvements in PV
technology. The second scenario assumed that, instead of average U.S. solar
insolation, all PV power plants would be built in the U.S. Southwest. Building-based
systems were still built with U.S. average conditions. This is labeled as SW in the
figures. The third scenario was identical to the Southwest scenario, except that
introduction of new vintages of solar technologies was delayed by ten years. It is
labeled as "slow" in the figures. A small capacity of the early PV technology vintages
was forced into the solution by putting a lower bound on its capacity. This represents
the existing niche markets.
Each scenario was run without constraint on carbon emissions and with carbon
emissions in 2010 through 2030 constrained to be 20% less than 1990 levels.
Analysis Approach
The analysis examines three kinds of results. First is the projected investment in
PV technology in the different cases. To what extent does the model find the
technology cost-effective and how rapidly does it bring it into the energy system? How
is PV technology valued relative to its competitors? Second is the implication of
investment in PV on U.S. carbon dioxide emissions. How do these emissions change
in the unconstrained cases? How is the marginal cost of C02 control affected in the
carbon-constrained cases? Third is the implication for the broader economy. This
includes the impact on gross domestic product (GDP) and on the energy intensity of the
economy (primary energy use per unit GDP).
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RESULTS
Photovoltaics: Projected Capacity and Marginal Costs
Projected capacity of PV for the three cases without carbon dioxide constraint is
shown in Figure 1. Not surprisingly, under Southwestern conditions, PV becomes
competitive earlier and stronger. In the "slow" scenario, the delay in achieving cost and
efficiency gains retards the growth of the technology. Marginal costs are given in Table
2. Negative marginal costs (called reduced costs) indicate how much the cost must
decrease for the technology to be cost-effective. In this case, since PV has already
successfully entered the market, it can be interpreted as the added value of PV in the
niche market competing against the grid. Positive marginal costs indicate the relative
value the model places on further increases in the capacity of PV above the bounds set
at the NREL projection levels.
Impact on Energy Costs and Demand for Energy Services
The annualized total cost of the energy system includes energy resource and
fuel costs, investment in supply- and demand-side technology, operating and
maintenance costs. Because of the stronger market penetration of PV in the Southwest
case, total energy costs were slightly lower than in the US case, despite the fact that
since marginal costs of meeting energy demands were lower in the model results, total
demand for energy services increased slightly in the SW case. Although the effects
were in the expected direction, since the change still represented only a small change
in the overall energy system, the sizes of the effects were small (less than 0.2%).
Impact on Fossil Energy Intensity
Energy intensity is the energy use per unit GDP. When concerned with energy
conservation, energy is usually expressed as primary energy per GDP, using a "fossil
equivalent" value for the primary energy of solar and other renewable resources. Since
PV substitutes for fossil fuels, the measure of interest is the primary fossil energy use
per GDP. This measure declines over time for all cases due to substitution of
renewables for fossil fuels and added conservation. The difference between cases
shows the impact of PV technologies (Figure 2).
Carbon Emissions
Figure 3 shows the projected growth in carbon emissions for the three cases
without carbon constraints. The SW case resulted in a 550 million ton decrease in
carbon emissions over the 45 year study period compared to the US case and a 260
million ton decrease compared to the SLOW case. The former indicates the implication
of the higher output per unit cost of PV in the Southwest. The latter indicates the
potential impact on carbon emissions of the projected improvements in PV relative to a
slower schedule of improvements. It understates the impact of improved PV, however,
since higher marginal costs of electricity in the SLOW case lead to a decrease in
demand for energy services with a consequent decrease in GDP. This slow-down of
the economy leads to lower carbon emissions.
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Impact on GDP
Energy is a required element of production. The impact of decreased demand
for energy services under carbon emission constraints is reflected in the economy by a
reduction in the growth rate of GDP. GDP grows at 1.82%/year in the U.S. reference
case. The growth projection slightly increases in the SW case. The impact is less than
0.1 % per year accumulating to about $3 billion out of $11 trillion by 2030. GDP growth
is slightly lower in the slow case than in the SW case, but higher than in the US case.
When the carbon constraint is imposed, GDP growth slows to 1,77%/year. This
decreased growth results in an estimated GDP in 2030 about 2% lower than in the
unconstrained cases.
CONCLUSIONS
PV technology is already competitive for certain niche markets. MARKAL-
MACRO's reduced costs suggested a premium value on these markets of about
$100/kW. Further growth in those markets is expected as well as expansion into other
niches such as peaking power. Decreasing cost and increasing efficiency should
provide greater incentive for expansion of niche markets. Given these improvements,
this analysis indicated that PV will be competitive as a general source of electricity
supply to the grid in the southwestern U.S. about 2010 and shortly thereafter under
average U.S. solar conditions. PV has the potential of displacing 550 million tons of
carbon emissions through 2030 on a strictly economic basis.
NOMENCLATURE
C02
Carbon dioxide
GDP
Gross Domestic Product
MW
Megawatt (one million watts)
NREL
National Renewable Energy Laboratory
PV
Photovoltaics
ACKNOWLEDGMENTS
This work was supported by the Photovoltaics Division, Office of Energy
Efficiency and Renewable Energy, U. S. Department of Energy, Office of We
acknowledge the contribution of Tom Bath, Walter Short, Jeff Williams, and Tom
Ferguson of NREL in providing current projections of PV cost and efficiency and of
discussion of existing and potential niche markets.
REFERENCES
1.	T. Ferguson, 1995. personal communication of data from NREL.
2.	Energy Information Administration, 1995. Annual Energy Outlook 1995 with
Projections to 2010, U.S. Energy Information Administration, Washington, D.C.
3.	T. Ferguson, 1995 personal communication of data from NREL.
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4 Energy Information Administration, ob sit
5.	T. Kram, 1993. National energy options for reducing CO2 emissions, Vol. 1: the
international connection, Netherlands Energy Research Foundation, Petten.
6.	L. D. Hamilton, G. A. Goldstein, J. Lee, A. S. Manne, W. Marcuse, S. C. Morris, and
C-0. Wene. 1992. MARKAL-MACRO: an overview (BNL 48377). Brookhaven National
Laboratory, Upton, NY.
7.	T. Kram, 1993 ob sit.
8.	T. Kram (ed.). 1994. National energy options for reducing CO2 emissions, Volume 2:
country studies, Netherlands Energy Research Foundation, Petten.
9.	M. N. Denisis, GA Goldstein, E.J. Linky, S.C. Morris, and K.J. Simeonova. 1995.
Demand side management & green lights in Bulgaria. The Bulgaria Energy Forum,
Varna, June 21-23.
10.	M. Tichy, K. J. Simeonova, S. C. Morris, and G. A. Goldstein. 1995. Eastern
Europe: a new frontier for MARKAL-MACRO, International Energy Workshop,
Laxenburg, Austria, June 20-22.
11.	S. C. Morris, J. Lee, and G. A. Goldstein. 1995 (forthcoming). U. S. MARKAL-
MACRO Database Documentation. Brookhaven National Laboratory, Upton, NY.
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TABLES
Table 1. CHARACTERISTICS OF PV TECHNOLOGY SYSTEM.

1995
2000
2005
2010
2020
2030
Capital ($/kW)
7000
3500
2000
1000
800
650
O&M (cents/kWh)
3
0.7
0.3
0.2
0.1
0.1
Module efficiency
7%
10%
12%
14%
15%
16%
Personal communication from T. Ferguson, NREL.
TABLE 2. MARGINAL COST OF PV ($/kW)
Case
2000
2010
2020
2030
US
-too.
-100.
+7.
+30.
SW
-20.
+5.
+10.
+20.
US CO2-20%
-80.
-50.
+22.
+60.
SW C02-20%
0.
+30.
+30.
+20..
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FIGURES
Figure 1, Projected Capacity of PV.
Figure 2. Energy Intensity: Fossile Energy Use per Unit GDP.
Figure 3. Annual U.S. Carbon Emissions.
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PV-03B.XLS Chart 1
Figure 1. Projected Capacity of PV
200
180
160
140
120
| 100
80 —
60
40
20
0


2000
2005
2010
2015
2020
- US
' SW
"• Slow
2025	2030

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PV-03B.XLS Chart 3
Figure 2. Energy Intensity: Fossil Energy Use per Unit GDP
US
sw
Slow

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PV-03B.XLS Chart 4
Figure 3. Annual U.S. Carbon Emissions

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ELECTRIC VEHICLES: A SOURCE FOR ENERGY SECURITY AND CLEAN AIR
Lawrence G. O'Connell
Electric Power Research Institute
P.O. Box 10412
Palo Alto, CA 94303
ABSTRACT
Electric vehicles (EVs) can help solve the problems created by the transportation
sector's heavy dependence on petroleum-based fuels. Studies show that using EVs could
significantly decrease emissions that contribute to urban air quality problems. Further, they
emit less carbon dioxide than gasoline-powered vehicles, and therefore could be part of a
greenhouse gas reduction strategy. In addition, because only a small portion of electricity
used in the United States is generated from oil, replacing conventional vehicles with EVs
could help move the nation toward greater energy security. In recognition of these potential
benefits, legislation and .regulations are now encouraging—and even mandating—zero-
emission vehicles, or EVs, production and use. Automakers have responded by starting EV
development programs that promise viable vehicles in time to meet the legislative
requirements. The electric utility industry, in turn, has been laying the foundation for the
infrastructure to support wider use of this beneficial technology.
INTRODUCTION
The U. S. transportation sector is heavily dependent on petroleum. It uses about 37%
of all energy consumed in the United States, more than the industrial, commercial, or
residential sectors. Within the transportation sector, nearly three-quarters of all energy
consumed is used by cars, trucks, and buses—vehicles that rely entirely on oil-derived
gasoline and diesel fuel.'
To sustain its oil addiction, the United States imports over 50% of its oil.' This
dependency on imported fuel has serious consequences. For example, because the
transportation sector cannot readily substitute fuels, changes in the price of oil significantly
impact our economy. The high level of importation also jeopardizes the nation's energy
security and affects our foreign payments balance adversely.
Furthermore, petroleum-based vehicle emissions are the greatest source of the U.S.
air quality problem.3 For instance, ground-level ozone and carbon monoxide (CO)
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The
Contents do not necessarily reflect the views of the Agency and no official endorsement should be
inferred.
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emissions, which threaten human health, are directly linked to motor vehicle use. These
vehicles also emit large quantities of carbon dioxide (CO.), a principal greenhouse gas.
There is, however, one solution to all three energy-related transportation concerns:
electric vehicles (EVs). Electricity used as a transportation fuel offers the opportunity for
fuel diversity, greater energy security, and a more stable economy, as well as high potential
for a cleaner environment. Further, propelled by government legislation and mandates, EV
technology has greatly improved, making EVs a potentially capable and reliable source of
transportation.
THE PROBLEM WITH PETROLEUM
Access to transportation is fundamental to modern society. The economic health of
the United States depends on maintaining the mobility provided by our transportation
system, as past fuel-supply disruption have demonstrated. However, our current
petroleum-reliant forms of transportation can have grave consequences.
Petroleum-powered vehicles consumed about 64% of the petroleum in the United
States in 1993.4 Because over half of our petroleum is imported, dependence on gasoline-
powered vehicles contributes to energy security threats and adversely affects our foreign
trade balance.
As previously mentioned, petroleum-powered transportation contributes
significantly to deteriorating U.S. air quality. Li 1990, highway vehicles were responsible
for 27% of emissions of volatile organic compounds (VOCs, also measured as NMOG, or
non-methane organic gases) and 28% of emissions of nitrogen oxides (NOx). VOCs and
NOx react together with sunlight to form ground-level ozone or smog.r'
Highway vehicles are responsible for emitting 50% of all carbon monoxide (CO) into
the environment.6 And cars and trucks generate about 24% of CO,, a principal gas
associated with greenhouse gas and global warming.7 Despite the mandate in the 1970
Clean Air Act requiring U.S. cities to reduce their ambient levels of ozone and/or CO, at
least 85 cities still do not meet federal standards for ground-level ozone, and more than 37
cities fail to comply with federal CO limits."
WHY SHOULD WE USE EVS?
Clearly, the United States must find an alternative to its reliance on gasoline-
powered vehicles- In searching for a solution, attention is turning to vehicles that run on
alternative fuels—methanol, ethanol, natural gasoline, liquefied petroleum gas (LPG), and
electricity. (Electricity is riot a fuel, but rather an energy source generated from many
different fuels.) Figure 1 shows the results of a study that compared the pollution reduction
potential of EVs used in California with the next cleanest alternative: a vehicle meeting the
California standards for an ultra-low-emissions vehicle (ULEV). As Table 1 demonstrates,
even taking into account the emissions from the power plants that generate their electricity,
EVs are cleaner than even this very clean alternative—and much cleaner than their
conventional gasoline vehicle counterparts.' In general, substituting an EV for a
conventional vehicle reduces VOC and CO bv about 99% and can reduce NOx by about
half."
5-76

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Table 1.
F.V vs. ULEV Passenger Car Emissions in 2011 for Total Electricity Generation
(grams/miles)
	EV Emissions' (All Power Plants)	

ULEV




93 Vehicle
Emission
Emissions in




Emissions
Type
California
LADWP
PG&E
SDG&E
SCE
SCAB1
ROG
0.191
0.0033
0.0038
0.0020
0.0115
1.517
NO,
0.319
0.1328
0.0398
0.0268
0.0590
1.235
CO
1.089
0.0258
0.0462
0.0051
0.0063
0.0321
13.611
PM3
0.018
0.0079
0.0033
0.0064
0.018
' ULKV omission r>«h>s an* averages and iix:''ixlovchido exhaust and e\'apocat;veecnis$:i>'^ fmm KM,UA(' intl HI JKI>K.\ model runsnivJ emissions
associated v/ith turi prtxliutjan, stomp;:, and di'itribution.
7 HV emission rates retWt (virginal povvvrptinr emissii>ns from ELFIN mtxIH mivs 'Ilu-y .iwimeai average IQ-year passenger car aieigy ei'tickmcy of 0.26
kVVh/mile and an
s PM levels exclude tire wear.
4CARB April 19W LUV/ZBV report; ?outh Coast Air Basin (SCAB) phis the fuel production emissions from Table!.
Source: CPRITechnical Brief TB*104068/Mtiy, 1594-
In addition, a United States General Accounting Office (GAO) study showed EVs
emit less C02 than conventional vehicles. Based on a comparison between a conventional
four-passenger vehicle and an equivalent EV, the study predicted that some C02 emissions
reduction will occur. However, this decrease varies from about 28% to 35% depending on
the carbon intensities of the fuel used to generate the electricity."
EV use could also help the United States decrease dependence on imported oil. The
fuels used to create electricity—natural gas, coal, hydropower, and nuclear—almost always
come from domestic or Canadian sources: Currently, oil only accounts for about 4% of
electricity generation. Thus, EVs recharged during utility peak periods would require only
2 barrels of petroleum over 100,000 mile of operation, while a conventional vehicle would
need 94 barrels to cover the same distance (see Figure 1.) In addition, because EVs will
generally be charged overnight during utility off-peak periods, typically even less than 2
barrels will be consumed.
Figure 1.
Electric Vehicles:	
An Antidote to Oil Addiction
Wx** % AV
5-77

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EV LEGISLATION
Government mandates have played a leading role in moving the transportation
sector toward cleaner fuels. Both state and federal governments have created alternative
fuel vehicle (AFV) legislation that often singles out E Vs for special treatment—such as
specific EV tax incentives and credits.
In 1990, California adopted the world's most stringent vehicle emissions standards.
The California Low-Emission Vehicle (LEV) Program, which includes mandates for zero-
emission vehicles (ZEVs), requires the incremental sale of both LEVs and ZEVs. Starting in
model year 1998,2% of all passenger vehicles and light-duty trucks offered for sale in the
state by major auto manufacturers must be ZEVs. The percentage peaks at 10% in 2003.
Among today's options, only electric vehicles meet the ZEV standards.
Ihe 1990 Clean Air Act Amendments (CAAA) included regulations specifically
affecting the AFV market. One such regulation allows individual states to comply with
either the federal emissions standards—which stipulate specific emissions standard for
vehicles—or the standards of the more stringent California LEV program, including the
ZEV portion of the program.
With the approval of EPA, the Ozone Transport Commission (OTC) in the Northeast
collectively chose to adopt the California LEV program. However, EPA allowed the OTC-
member states to eliminate the ZEV portion of the LEV program, and all but New York and
Massachusetts have not yet opted for the ZEV mandate.
The CAAA also established the Clean Fuel Fleet Vehicle (CFFV) program. Beginning
in 1998, fleets in cities that are in serious, severe, or extreme noncompliance areas for
ozone—or in some cases CO—and that do not adopt the I EV program must meet the CFFV
standards. To be defined as a clean fuel vehicle (CFV), a vehicle must not exceed the
following emissions standards:
•	0.075 grams per mile (gpm) NMOG
•	3.4 gpm CO
•	0.2 gpm NOx
The CFFV program targets fleet owners operating more than 10 vehicles capable of being
centrally fueled. Starting in 1998,30% of new light-duty vehicle purchases in such fleets
must be CFFVs, increasing to 70% in 2000 and beyond. Because extra credits are given for
obtaining vehicles that surpass the required emissions standards, an EV would earn the
fleet owner extra credit, which could be banked against future purchases or traded to
another fleet.
The Energy Policy Act (EPACT) of 1992 also contains mandates affecting EV
purchases and development For example, EV buyers can benefit from a tax credit equal to
10% of the EV purchase price, or up to $4,000. The Act also allocates a $100,000 tax
deduction for each clean-fuel refueling facility put in sendee. In addition, EPACT
authorizes three innovative multi-million dollar R&D programs to help further EV
technology.

-------
EPACT also requires fleets owned by alternative-fuel providers and federal and
state fleets to begin buying AFVs. Initially, the largest requirement applies to alternative-
fuel providers, who must ensure that 30% of the new vehicles they purchase in 1996 are
AFVs. That percentage increases incrementally to 90% in 1999 and beyond. Electric utilities,
however, have the option of delaying AFV purchases until January 1,1998, if the utility
intends to use EVs to comply with the regulations—a delay intended to buy time until EVs
become more readily available. In federal fleets, AFVs must equal 25% of new vehicle
purchased in 1996, building up to 75% in 1999 and beyond. And in state fleets, AFVs must
constitute 10% of new vehicles purchased in 1996, increasing to 75% in 2000 and beyond.
Although there is rio specific ZEV requirement included in this program, the sizable EV tax
credit is intended to function as an extra incentive.
THE STATUS OF EV TECHNOLOGY
Today, automotive manufacturers, ranging from the Big Tliree and large foreign
manufacturers like Nissan and Toyota to small independent manufacturers, are fox-using on
developing limited production runs of EVs. Although these EVs currently serve as
prototype vehicles, limited mass production is scheduled for the near future.
In the mid-1980s, the electric utility industry, with assistance from the U.S.
Department of Energy (DOE) launched the first major effort to develop commercial-grade
EV technology. The Electric Power Research Institute (EPRI), the electric utility industry's
R&D organization, in cooperation with General Motors and Canadian manufacturer
Conceptor Industries, Inc., developed an electric van—the G-Van—as a useful vehicle for
urban fleets. This first generation EV continues to be used in numerous utility fleets today.
Its lead-acid battery provides modest performance: a range of up to 60 miles and a top
speed of 52 mph. The G-Van was the first North American-built EV to be certified as
compliant with Federal Motor Vehicles Safety Standards (FMVSS).
In 1993, each of the Big Tliree initiated major new demonstration programs.
Chrysler, in cooperation with EPRI, came out with its TEVan, an EV with the standard
Chrysler minivan design. The TEVan's nickel-based batteries allow the vehicle to achieve a
range from 50 to 80 miles and reach a top speed of 70 mph. Like the G-Van, the TEVan has
been certified for compliance with FMVSS.
GM caught the public's attention with its small electric concept car, the Impact.
Designed from the ground up for performance, the Impact is one of the fastest EVs around.
With maintenance-free sealed lead-acid batteries, it achieves 70-mile range (in the city),
reaches a top speed electrically limited to 75 mph—although it has been run on a track at
over 180 mph—and accelerates from 0 to 60 mph in 8 seconds.
Ford also has its own version of an electric minivan, the Ecostar. Equipped with a
sodium/sulfur battery and Ford's ac powertrain, the vehicle achieves a 100-mile range and
a top speed of 75 mph.
Independent auto manufacturers are big players in the current EV manufacturing
market, as well. Many independent companies are both converting conventional vehicles to
run on electricity and building EVs from the ground up.
As mentioned, foreign automakers such as BMW, Fiat, Mercedes-Benz, Nissan, PSA
Peugeot Citroen, Toyota, and Volvo are also actively involved with EV development
5-79

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programs. Volvo's Environmental Concept Car (ECC) can, for example, run on battery
power as well as in hybrid mode and reach top speeds between 90 and 100 mph. And
Toyota has staffed a new division with 100 engineers whose sole mission is to develop a
1998-modcl EV. Moreover, Japan's Ministry of International Trade and Industry is
developing plans for future EV joint-venture projects with American and European
automakers.
In addition, government and industry representatives are establishing organizations
to expedite EV market advancement. EV California, a collaboration of California state
agencies, local government, and utilities, is working to institute a large-scale EV
demonstration program. The organization's ultimate goal is to place 2,000 EVs in both
public and private fleets by mid to late 1996. Currently, KV California is looking for an
original equipment manufacturer (OEM) to participate in the program. Further, the
organization is seeking financial support to supplement funding now being received from
California air quality management districts and vehicle registration fees.
The electric utility industry created the EV America program to accelerate the
introduction of EVs into the fleet market with plans to place as many as 5,000 EVs into
utility, commercial, government, and transit fleets by the end of 1997. The program
includes technical maintenance support for the vehicles. DOE is a major source of funding
for the EV America program.
Because the battery is the single most critical EV component, in addition to
developing market-ready EVs, automakers, government, utilities, and battery
manufacturers have been working together to produce an advanced EV battery with both
high specific power and energy. The choice of battery affects EV performance, cost, and
ultimately market acceptance. In addition, EV batteries must be inexpensive, easy to
maintain, safe under all conditions, and tolerant of the abuse vehicles typically experience
in daily operation.
In 1991, U.S, automakers, the electric utility industry, EPRI, and DOE formed the
United States Advanced Battery Consortium (USABC), which plans to develop a "mid-
term" battery (100-125 mile range) by 1998 and a "long-term'' battery (200-mile range) for
mass production early in the next decade. Table 2 shows the key projected characteristics of
these batteries.
Table 2
USABC Goals
Specific Power
Specific Energy
Lifetime
Cost
Mid-term goals
150-200 watts
per kilogram
80-100 watt
hours per
kilogram
5 years
$150 or less per
kilowatt hour
Long-term goals
400 watts per
kilogram
200 watts hours
per kilogram
10 years
$100 or less per
kilowatt hour
Source: United Sfates Advanced Battery Consortium, USABC Update, October, 1334.
5 80

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EV MARKET NICHE
EVs not only offer potential to cure oil-depcndcnce and air quality problems, they
are a realistic form of both personal and public transportation, given the driving habits and
patterns of today's motorists- Studies have concluded that
•	Most American's drive less than 100 mile per day1"
•	Half of the vehicles driven in the United States are driven less than that distance 95% of
the year13
•	60% of households with more than one car could easily use a car with a 90-mile range as
on of their vehicles'4
Commuter studies support these findings. In a recent General Motors study, 85% of
commuters surveyed in Los Angeles, Houston, and Boston travel less than 75 miles a day
and 70% claimed to travel less than 50 mile per day—ranges achieved by today's EV.15
Based on the these statistics, an EV could easily replace one of the two cars owned
by over half of all U.S. households for commuting, running errands, and taking short
trips—the start-and-stop driving for which conventional vehicles are least effi cient and
most polluting. Further, because this type of driving mostly occurs in urban areas where
vehicle- related air pollution is at its worst, EVs offer the extra benefit of a cleaner urban
environment.
EVs are also ideal for the fleet market. Today's EV has sufficient range and
performance for many fleet applications. In addition, the way fleet vehicles are used,
garaged, and fueled perfectly match KV capabilities and operating methods. Ultimately,
fleet owners may also gain economic benefits from an electric fleet because EVs offer low
operating costs, can currently provide emission credits and tax breaks, and will likely have
lower maintenance costs.
EV COSTS
Although EV purchase prices are currently higher than those of conventional
vehicles, the premium can be attributed to the limited production of EVs. Once mass
production begins, EVs should cost the same as conventional vehicles. Moreover, due to the
EV's higher fuel efficiency and potentially lower maintenance costs, EV operating costs are
expected to compare well with those for gasoline vehicles, as demonstrated in Table 3.
Further, a light-weight EV designed from the ground up, using state-of-the-art
technology, should achieve a 90-mile range with inexpensive advanced lead-acid batteries,
which will help keep EV retail prices more affordable. Further, as previously stated, an EV
powered by these batteries would be sufficient for 60% of American households' driving
needs.16
5-81

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Table 3.
Operating costs of Electric vs. Gasoline Vehicles Over 10-year Life

Electric Vehicle
Gasoline Vehicle
Fuel Cost
$0.05/kWh*
$1.25/gal
Vehicle Efficiency (4-door
sedan)**
4 miles/kWh (equivalent to
133 mpg)
25 mpg
Fuel Cost per Mile
$0.0125/mile
$0.05/mile
Battery Cost per Mile
$0.0417/mile***
N/A
Total Operating Cost per
Mile
$0.054/mile
$0.05/mile
"National average off-peak rate. In addition io price,, energy security is a benefit of eitcti icily. Nationwide, only 4% of electricity is generated from
petroleum.
^Mei^ured from the wall plug and the gas pump.
**'Assumes a S2..25J batiery wllh a life of 630cycles; 90 mUes/cycle
Scurce: EPR! Technical Brief T3- 1.D4lJ56I
-------
special consumer features to make it easy and convenient to charge EVs at home or at
public HV charging facilities on a daily basis.
• Level 3 is a high-powered technology currently under development that will provide a
charge in 10-15 minutes, making the charging process parallel to refueling a
conventional vehicle.
Recently, electric utilities and automakers have agreed on the electrical specifications of
level 2 for EV charging in the United States. Operating at a rate up to 5 times faster than
Level 1, Level 2 charging is expected to be the consumer' preference at both private and
public facilities. Moreover, recharging an EV at Level 2 away from the home will extend
the daily range of an EV.
CONCLUSION
As demonstrated in this paper, EVs offer the potential to eliminate problems
associated with petroleum dependency. While improving the environment, EVs can help
U.S. energy security and economic vitality. Furthermore, tax deductions and credits offer
extra incentive for EV purchases, and a number of cooperative efforts such as EV America
and the IWC continue to promote the use of EVs and strengthen the EV infrastructure.
An HV niche market is both realistic and near. It will work to reduce the overall cost
of EV technology and help bring EVs to the general consumer market. However, while
progress is continually being made to advance EV technology, technical and financial
barriers still exist. Most-important, battery quality must continue to improve and become
more affordable. Given the current wave of industry advancements, it appears that the
broad national goal of developing a transportation system that protects natural resources
and ensures national economic stability can be achieved. As more and more EVs take to the
roads, their benefits will continue to enhance the quality of life for millions across the
country.
j
REFERENCES
1	Borg, I.Y. and Briggs, C.K.. U.S. Energy Flow - 1993. UCRL-1D 19227-93, Lawrence Livermorc National
Laboratory, October 1994.
2	Information based on 1994 statistics from the American Petroleum Institute Statistics office. Phone
conversation on 4/5/95.
'international Energy Agency. Cars and Climate Change, OECD/IEA, 1993, pg. 29.
1 Borg, I.Y. and Briggs, C.K., op. cit,
' U.S. Environmental Protection Agency. National Air Pollution Estimates, 1940-1990, November 1991.
'Ibid.
5-83

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7 The Alliance to Save Energy. "Carbon Dioxide Emission, by Activity/' Alliance Update, Fall 1991,
Volume II, Number 3.
*	"EPA Areas Designated Nonattainment," Office of Air Quality Planning and Standards EPA, March,
1995.
*	Electric Van and Gasoline. Van Emissions: A Comparison. TB.CU.177.tO.89, Electric Power Research
Institute, 1989.
ICF, Inc. Methodology for Analyzing the Environmental and Economic Effects of Electric Vehicles: An
Illustrative Study, Prepared for the U.S. Environmental Protection Agency, Office of Mobile Sources,
Emission Control Technology Division, September 1991.
11 U.S. General Accounting Office. Electric Vehicles; Likely Consequences of U.S. and other Nations' Programs
and Policies, GAO/PEMD-95-7, December 1994, pg. 108.
" Deshpande, G.D. Development of Driving Schedules for Advanced Vehicle Assessmmt, SAE Technical Paper
Series No. 840360, Society of Automotive Engineers, Warrendale, PA, 1984.
15 Greene, D. Estimating the Daily Vehicle Usage Distributions and the Implications for Limited-Range Vehicles..
Transportation Research - B, Vol. 19B, 1985, pg, 347 - 358.
M Kiselewich, S.J. and Hamilton, W.F. Electrification of Household Travel by Electric and Hybrid Vehicles,
SAE Technical Paper Series No, 820452, Society of Automotive Engineers, Warrendale, PA, 1982.
15 CALSTART Fact Sheets. "Early EV Adopter Profile," CALSTART, 1992.
"Kiselewich, S.J. and Hamilton, W.F., op. cit.
5-84

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The work described in this paper was riot funded by the U.S. Environmental Protection
Agency. The contents do not necessarily reflect the views of the Agency and no official
endorsement should be inferred.
Why Not Plug Your House and Workplace into
Your Fuel Cell Car?
Robert H. Williams
J. Kelly Kissock
Center for Energy and Environmental Studies
School of Engineering and Applied Science
Princeton University
Princeton, New Jersey
Presented at the:
1995 U.S. EPA Symposium on
Greenhouse Gas Emissions and Mitigation Research
Washington, DC
June 27-29, 1995

-------
FROM THE AGE OF COMBUSTION
TO THE AGE OF ELECTROCHEMISTRY
The fuel cell offers:
-	a quantum leap in energy efficiency,
-	zero or near-zero pollution emissions without control
technologies,
-	low maintenance,
-	ability to use a wide range of primary fuels,
-	prospectively competitive costs in mass production.
The fuel cell could:
-	displace the internal combustion engine in transportation,
-	shift the focus of stationary power generation from central
station to distributed applications,
-	greatly reduce the burning of fuels for providing low-
temperature heat in buildings.

-------
Anatomy of a Fuel Cell
Electrolyte ^ H20 & waste heat

-------
SHOULD AUTOMOTIVE FUEL CELLS BE
DESIGNED FOR DUAL USE?
Rationale:
•	A car is operated 3500-5000 hours during its lifetime.
•	PEM fuel cells may last 50,000 to 60,000 hours or more.
•	Installed generating capacity for 120 million cars @ 25kW/car is
3000 GW, equal to the world's (4 x US) stationary generating
capacity.
Proposed strategy:
•	Produce electricity and hot water (@ 85 °C) for low temperature
heat in stationary applications when car is not in use for transport.
•	Cars parked in "docking stations" at home and workplace with
connections for [fuel + cold water in] and [electricity + hot water
out].
•	Buildings interconnected with electric utility-exporting excess
electricity and importing electricity when needed.
•	Buildings equipped with heat storage systems to serve heating
needs while car is being driven.
•	System operated to utilize heat from fuel cell as fully as
practicable.

-------
Problem Statement and Methodology
•	Goal is to determine the per-car net present
value of fuel savings and net avoided capital
costs for building energy equipment that can be
applied to investments for the home and
workplace docking stations and to any required
FCV modifications.
•	Hourly simulation models for the year 2010 of:
-	New Jersey residence and hospital workplace
-	Texas residence and institutional building workplace
•	Assume that the FCV provides building energy:
-	at work from 8 am to 5 pm on weekdays
-	at home from 6 pm to 7 am every day

-------
Energy Price Assumptions
Assumed prices for conventional energy based on US EIA projections for
the Middle Atlantic Region in 2010

Residential
Commercial
Utility
Electricity ($/kWh)
0.112
0.093
-
Natural Gas (S/GJ)
7.50
6.38
4.28*
Coal ($/GJ)
-
-
1.39
*Levelized (2010-2040) price based on a $3.81/GJ natural gas price in 2010 increasing
1 % per year (6% discount rate).
o
Assumed prices for 99.999% pure H2 produced from natural gas by local
utility (Williams, 1995)

Residential
Commercial
Production ($2.38/GJ + 1.115 * Png)
6.42
6.42
Distribution ($/GJ)
2.89
1.91
Total (S/GJ)
9.81
8.78
[All prices in 1993 dollars]

-------
Calculations of Avoided Electricity Costs
Assume electric utility plant mix of:
-	Baseload: coal integrated gasification combined cycle
-	Load following: natural gas combined cycle
-	Peaking: natural gas combustion turbines
Use SUTIL model to calculate avoided generation costs
Assume EPRI Synthetic Utility A (summer peaking)
Assume that the number of fuel cell power units is sufficient
to displace one central station thermal plant
Value of fuel cell generated electricity sold to the utility:
-	Avoided generation cost = 6.3 0/kWh
-	Credit for reduced T&D energy losses = 0.3 0/kWh
-	Credit for deferred T&D investments = 0.4 to 1.8 0/kWh

-------
Fuel Cell Stack Assumptions
Nominal 25 kW (37.5 kW peak) stack
Polarization curve projected by Allison (formerly Gas
Turbine Division of General Motors)
^Ha-utii = 98%
^Ithermal-util = 75%
T00olant,peak = 85 °C
Anode and Cathode Pressures = 2 Bar
Air Stochiometry = 2.0
H2 and exhaust expansion and air compression done
adiabatically at 75% efficiency.
Fixed parasitic load of 500 W
'"'net — '"'gross ^ expH2	expExh ~ ^cmpAir" '"'fix

-------
vO
[Eff (HHV) = V/1.48]
o
>
CO
atodfo.* Stock
(by Allison Gas
Tuftsin^ Dvisor
of GM)
1wi3
(La&orat.-cy CuU
LAN.)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 11 1S 13 1.4
Current Density (amps/cm ) 2

-------
Fuel Cell Thermal Management System
On Car | In Building
vo
Tf2 	O ^
4
<¦
~
\/
-&
VvVW	
4 Qradiator

Qstor™?:


Ts1

-------
Residential Space and Water Heating Loads
•	Assume energy efficient house (Bliss, 1976)
-	UA (including infiltration) = 0.183 kW/C
-	Avg. internal loads = I = 0.427 kW
-	Avg. solar gains = S = 1.10 kW
~ Tinsjde = 22.2 C
-	Toutslde = hourly TMY data (NJ), hourly measured data (TX)
-Tw_main = 10C(NJ), 15C(TX)
-	Thw = 60 C
-	mhw = hourly hot water demand (Perlman and Mills, 1985)
•	Qsh = [ UA(Ti - To) -1 - S ] +
•	Qhw ~ ^hw ^pw ("^"hw""^w-main)
•	Assumed efficiencies for avoided natural gas -
burning equipment: iifurnace = 93%; r|water.heater = 60%

-------
¦ ¦	¦ ¦ I	¦
Residential Space and
Heating System
Water
Warm Ai r
To House
Cold Water
From Main
Warm Water
To House

-------
System Performance
NJ Residence, January
u*
i
-^1
Temp 50
Storage
(C) 40


v*'V**-"Ar
•J-l
&
•;#
•: i?r
\ <•„„ ,**i* '•	' .» w<— ¦< >v-
 | *	•?, V' '	*
¦' -1 }• %;£iir-.T«*fi, :'5
/ '< « %	* *« *c' ?" *	% I it I - * *	<<
:|
a' ' ¦' #
,r •;; i

'k t ' '
i
8 10 12 14 16 18 20 22
Hour of Day
2.5
2.0
1.5
1.0
0.5
0.0
Efc
(kW)
Efc (kW)

-------
System Efficiencies
NJ Residence, January
00
>.
O
C
©
'o
£
m
0.1 h ^
0.0
0

8 10 12 14
Hour of Day
16
18
20
22
Qstor/Qfc
Qstor/Qload
Efc/ H2sup

-------
VD
$/FCV
Present Value of Savings Per FCV
(i=10%, n=10 yrs) TX and NJ Residences
vings
Texas
New Jersey
Net Capital = - Storage with heat exchanger and 5 cm high-density insulation

-------
Hospital Space and Water
Heating Systems
Tf2
XT"
->
¦qq— y
Fuel Celi
Qfo -

N /

wyw
¦-I'Oradiator
Tf2 O ^
~ ~

Fuel Cell
>
Qfc
><

«>—
/Qradiator
Cold Water
From Main
w
Hot Water
To Building

Water
Heater
¦>
~ s
t	Oaux.w
Qaux.h
six
Boiler

¦5^-
Storage Tank
Ts
8h e



-------
January Hospital Loads
750 FCVs day / 250 FCVs night
0 2
6 8 10 12 14 16 18 20 22
Elec Load
Efcvs-Win
Water Load
Heat Load

-------
o
to
kW
2500
2000
1500
1000
500
July Hospital Loads
750 FCVs day / 250 FCVs night
o
6 8 10 12 14 16 18 20 22
Elec Load
Efcvs-Sum
Water Load
Heat Load

-------
Annual Average Energy Flow Diagram
for Hospital (750/250)
O
Q lost (0.02)
H2 Vented
(0.02)
Q in exhaust Q to radiator
(0-11)	(0.03)

-------
o
•p.
Present Value of Savings Per FCV
(i=10%, n=10yrs) Hospital
Net Cap = - Storage w/ 5 cm Polyurethane Insulation - Heat Exchanger
Equipment prices from: Means, 1994; Ross and Williams, 1981

-------
Institutional Building HVAC System
with Absorption Chillers
©
Tf2
Fuel Ceil
Qfc >
-®—. —^

vww
\/Qradlator
Tf2 
-------
Average Hourly Institutional Building Performance
. -?7	-
78 Temp
(C)
0 2 4 6 8 10 12 14 16 18 20 22
Eload

-------

-------
Present Value of Total Dollar
Savings Per FCV
FCVs day/night
Hospital
NJ Residence
Total
750/250
3,458
2,769
6,227
375/125
6,803
2,769
9,572

FCVs day/night
Institutional
TX Residence
Total
1000/100
4,149
3,274
7,693
500/50
6,596
3,274
9,870

-------
Conclusions
Current thrust of PEM fuel cell development is to pursue
alternative paths for vehicular and stationary congeneration
markets:
-	Cost target for vehicular systems is $50 - $100/kW.
-	Cost target for stationary systems is $1000 to $1500/kW.
-	It is generally thought that radically different designs will be
needed for these alternative markets, in terms of membrane
lifetimes, catalyst loading, etc.
The present analysis suggests that there is reason for
giving serious attention to an alternative "dual-use" strategy
in which the same fuel cell serves both markets.
The dual-use strategy would clearly require a fundamental
reorganization of the energy systems.
But a dual-use strategy could lead to savings in
development costs, and perhaps also to reduced costs for
energy systems, while providing near zero emissions
technologies for transportation and power generation.

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FREE-PIS'TON STIRLING ENGINES
FOR DOMESTIC COGENERATION AND BIOMASS ENERGY CONVERSION
W. T. Bcale
Sunpowcr, Inc.
6 Byard Si.
Athens, OH 45701
ABSTRACT
The successful development of long-life free-piston machines for domestic refrigeration has brought into
existence Stirling engine designs which can be configured for electric power generation using biomass or other
sustainable energy sources. This paper describes the design and performance of machines suitable for near-term
commercial production for natural gas and biomass-ftrcd domestic and light industrial cogeneralion at the I to 10
kW power range.
INTRODUCTION
The machine described here is the latest in a series of evolutionary steps toward commercialization of
hermetically scaled free-piston Stirling machines, intended as a means to avoid the well-known Failings of the
conventional crank drive Stirling engine (1) These deficiencies included leakage of working fluids, seal wear and
friction. lubrication contamination of heat exchangers, control complexity and response time, and system
mechanical complexity, mass and cost. The frcc-piston design promised to solve all of these design problems,
while maintaining the Stirling's advantages of high thermal efficiency, clean, steady state combustion, and low
noise.
Tlie enabling dev elopment was, however, not in the Stirling engine application, but the same technology
embodied in linear motion refrigerant compressors and in small Stirling cryocoolers and domestic refrigerator
coolers (2, 3, 4, 5). The long life, hermetic sealing and mechanical simplicity of these applications has led to
demonstration of the validity of the concept by way of commercial prototypes. From this success the viability of
the engine embodiment of the free-piston concept has at last been given strong support.
The effort invested in developing free-piston Stirling thermal devices for applications to solar electricity
generation and for electronics cooling has resulted in the evolution of mechanically simple and efficient, long-lived
configurations ideally suited as energy conversion devices using sustainable energy sources such as biomass. Since
these machines share major components with linear compressors soon to be in large scale production as non-CFC
heat pumps, their costs can be expected to be attractive relative to what would be imposed by lower production
rates for sustainable energy only.
DESCRIPTION OF FREE-PISTON ENGINE
Figure 1 shows a typical layout of the current generation of free-piston Stirling engines. The machine shown is
designed to deliver 2.5 kW. 120 VAC at 60 Hz. The working fluid is hermetically sealed helium at 40 bar.
The work described in this paper was not funded by the U.S. Environmental Protection Agency. The contents do
not necessarily reflect the views of the Agency and no official endorsement should be inferred.
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The thermodynamic cycle used is a harmonic oscillation approximation to the ideal Stirling cy cle of two isotherms
connected by two constant volume temperature changes. The piston oscillation causes lite compression and
expansion processes and the displacer oscillation leading the piston moves the working gas between hot and cold
volumes at either end of the displacer to assure that most of the gas is in the hot space when it is expanding and in
the cold space when i! is being compressed so as to accomplish the desired work cycle. Dynamics of free-piston
Stirling engines are described in Berchowitz and Redlich (6).
The piston and displacer arc tuned as mechanical spring-mass-damper resonators with the desired phase lead of
about 50 degrees of the displacer lo accomplish the desired gas cycle. This simple tuned oscillation eliminates both
the crank mechanism and its associated lubrication and side forces. The piston power is delivered directly to the
magnets which are directly attached to il The resulting permanent magnet alternator produces alternating current
power at any desired voltage and at a design frequency, usually 50 or 60 Hz. The engine operates at very nearly its
design frequency regardless ofloading or amplitude.
Both piston and displacer float on gas bearings in their cylinders and arc resonated by mechanical springs
which are arranged to avoid side loads on the bearings. These planar springs (flat plates with spiral slits) also
serve lo center and support the large radial load1; of the permanent magnets, acting in effect as friction-free
oscillating bearings. The combination of gas bearings to allow wear-free close fits on the pistons and the use of
mechanical springs to give both resonant frequency and axial positioning is uniquely advantageous in that it
confers high mechanical efficiency, very long life, and elimination of bearing and seal drag and wear.
It should be noted that the function of pidance of the closely fit seals is done by the gas bearings, and the
separate function of axial springing and location is performed by the flexures. The flexures provide only rough
radial centering such as required by the alternator magnets, and as a result of this undemanding role, are much
cheaper lo make than flexures which are required lo perform both springing and highly accurate centering of the
pistons to avoid wear and leakage.
The sum result of the non-contact gas bearings, flexures, and magnet suspension is an exceptionally efficient,
quiet and durable machine. Mechanical efficiency of over 90% (defined as shaft power delivered to alternator
divided by gas power delivered to the piston) is routinely achieved, and the alternator electrical energy conversion
efficiency can readily be made to be over 92%, limited only by cost-efficiency compromises typical of electrical
machinery design In comparison, a typical small IC engine dissipates about 25% of its thermodynamic power in
mechanical losses, chiefly ring and piston friction.
An important feature of this class of machines is that they retain their efficiency and other characteristics when
scaled over a range of at least 100 watts to 20 kW, making them useful for applications ranging from self-powered
furnaces requiring a Tew hundred watts lo small business regeneration requiring multiple tens of kilowatts.
OPERATING FEATURES
Starting
The engine is exceptionally easy to start. Since it is an efficient linear oscillator, not a rotator, only a very
slight axial impulse is sufficient to start the build-up of oscillations once a temperature difference lias been
established between heater and cooler, A low voltage pulse across the alternator is a convenient way lo start ihe
engine.
Power Control
The machine in Figure I uses a power control based on a variable spring between piston and displacer. This
spring couples the displacer lo the piston to greater or lesser degree in proportion to its stiffness. If the spring is at
maximum stiffness then the displacer is essentially locked to the piston and little or no power is generated. The
engine power can rise lo maximum in a very few engine cycles if the relative spring stiffness is reduced to zero
Such a variable stiffness spring can be implemented in a number of ways (7), and can be coupled lo desired output
parameters such as voltage or power lo allow fully automatic and rapid response to imposed load The free-piston
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engine with this type of power control can operate, for example, as a constant voltage generator with high
efficiency over a wide range of power. Since the system variation for power control is mainly displacer phase
angle, little system stored energy change is required and response is correspondingly fast. A perfect spring is not
required; any controllable combination of spring and damper between the piston and displacer can effect power
control. Control of displacer spring to casing stillness can also have the same effect and is preferable in some
embodiments.
Burner
Heater liead temperature change is not used for power control, Ideally, for maximum thermal efficiency, the
heater head temperature should be kept as high as is compatible with life requirements. To keep the head
temperature constant, it is necessary to adjust heat flow in proportion to engine power delivered, which requires
variation of fuel atid air flow as the system load changes. Since combustion products are discharged from the
heater head at high temperature, an exhaust gas recuperator is used to heat the incoming combustion air, Most of
the burner can be inexpensively made of ceramic.
In the case or a bioinass-fired system, a burner similar to the one sketched in Figure 2 is being developed This
type of biomass burner and hopper has been found to be able to burn almost any biomass-dcrived fuel. No pre-
treatment of the fuel is needed other tlian reducing it to a size which will fit the top of the tapered hopper. The
reverse taper enables the fuel to fall continuously toward the combustion zone without jamming. Only the primary
and secondary air flow need to be adjusted to vary burner output. The primary air flow determines the rate of fuel-
gas generation, and the secondary air flows in proportion to assure the correct overall fuel-air ratio.
Cooling
The engine is cooled by a conventional water jacket, coolant pump and heat rejector with fan. The rejected heat
could be used for purposes such as space heating or laundry, or, if there is no such demand, simply dissipated to
the environs.
Noise and Vibration
The Stirling engine oscillates sinusoidally at a single frequency and uses steady combustion, which results in
intrinsically low noise relative to an IC engine, fn fact, the only significant source of noise in such a system is not
the Stirling engine, but the auxiliaries such as fans and blowers. Opposed twin configurations further reduce
intrinsic vibration by balancing all primary inertial forces. No additional mechanism is required to assure opposed
motion in twin engines.
Grid Connection
Since the machine is an oscillator and does not have rotational inertia, it can be attached directly to the grid at
full voltage and will run properly synchronized from the first cycle. The starting transient involves only amplitude
increment, not frequency change. 11>c machine can be operated on the grid with any level of heat input, and will
eitlier deliver power or take it from the grid depending on the heater head temperature.
SIGNIFICANCE OF SMALL COGENERATORS
As has been noted by Teagan, et al. (8). the advent of reliable and cost-effective small scale cogenerators could
have a significant effect on the energy efficiency of countries such as in North America and Europe which use a
significant percentage of total energy for space heating. Typically a space heater takes in high quality fuel such as
natural gas. produces nothing but low temperature heat, and cannot recover the large fraction of available energy
in the fiicl burned at high temperature. Thus an opportunity exists for fuel cells or efficient small heat engines to
deliver both available energy and heat from primary sources which now deliver only low grade heat Thus for
example, a converter with a thermal efficiency of 25%, which is reasonable for an engine of the type discussed
here, could deliver a space heating load of about 5 kW while also delivering up to 1.6 kW of electric power, more
than enough to satisfy the normal home steady state requirement of about I kW. Since about 20% of electricity
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generated in (lie U.S. is used in homes, such a cogeneration system could supply about 5% of the nation's electrical
needs, assuming (hat (lie average heating system is operating about 1/4 of the year. This is of course only a crude
order of magnitude estimate for one application, but serves to illustrate thai the potential for small cogenerators is
big if they can be made into acceptable domestic appliances.
In addition to domestic applications, this machine makes available energy recovery in small businesses such as
restaurants, motels, laundries and elsewhere, where the significant heat load is presently discarded and wasted. In
this regard it is important to note that machines of this type can be scaled over a wide range of delivered power,
from hundreds of watts to tens of kilowatts, with little change in overall efficiency.
The biomass application can be similarly beneficial on farms and elsewhere where biomass is abundant and
underutilized. This application may be even more attractive in countries where biomass is a larger fraction of total
energy use than in (lie U.S.
SYSTEM REQUIREMENTS FOR EFFECTIVE APPLICATION
For the promise of small scale cogeneration to be realized, (lie device itself must have at least the following
attributes for wide acceptance as an appliance:
1)	Attractive first cost, life-cycle cost and payback time
2)	Reliability and service requirements equal or better than domestic furnace
3)	Unobtrusive noise and vibration
4)	High overall available energy conversion efficiency
5)	Fast and efficient response to load
6)	High quality 120 V 60 Hz output; low waveform distortion, frequency variation
7)	Capability of operation either on or off grid
8)	Ability to assume essential load in the event of grid outage
9)	Reasonable size and connectabilily
10)	Acceptable emissions
Prototypes of the system described here haw shown promise of meeting all of the above requirements more
satisfactorily than small IC engines, Ihcrmoclcctrics, thcrmophotovoltaics, or fuel cells. Whether this apparent
advantage over fuel cells and the other candidates will be realized in the long run will be determined by the
market.
REFERENCES
1.	Beale, W.T. Free Piston Stirling Engines - Some Model Tests and Simulations. SAE paper No. 690230, Jan.
1969.
2.	Berchowitz, D.M. Free-Piston Rankine Compression and Stirling Cycle Machines for Domestic Refrigeration.
Greenpeace Ozone Safe Cooling Conference. Washington, D.C., October 18-19, 1993.
3.	van der Walt, N R. and linger, R. Linear Compressors: A Maturing Technology. International Appliance
Technical Conference, University of Wisconsin, Madison, Wisconsin, May 9-11, 1994.
4.	Mennink, B.D. and Berchowitz, D.M. Development of an Improved Stirling Cooler for Vacuum Super
Insulated Fridges with Thermal Store and Photovoltaic Power Source for Industrialized and Developing Countries.
International Institute of Refrigeration Conference, "New Applications of Natural Working Fluids in Refrigeration
and Air Conditioning", Proceedings of Congress Centrum Hannover, May 10 - 13, 1994.
5.	Smedley, G.T,, Ross, R.G., Jr., and Berchowitz, D M. Performance Characterization of the Sunpower
Cryocooler, Proceedings of 8th International Ciyocooler Conference, Vail, Colorado, June 28 - 20, 1994.
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6.	Redlich, R.W. and Berchowitz, D.M. Linear Dynamics of Free-Piston Stirling Engines. Proc. Instn. Mech.
Engrs. 199 (A3): 203-213. 1985.
7.	Beale, W.T. Free Piston Stirling Machine Having Variable Spring Between DispJaccr and Piston for Power
Control and Stroke Limiting. U.S. Patent number 5,385,021, Jan. 31, 1995, date filed Aug. 20, 1992.
8.	Teagan, W.P., Wilson, R.P, Mathias. S., and Frant/is, L System and Technology Concept Evaluation for
Small Commercial/Residential Cogeneration Applications GRI 86/0224, Gas Research Institute, Chicago, Illinois
60631. Final Report, November 1984 - September 1986.
FIGURES
FIGURE 1: TYPICAL FREE-PISTON STIRLING ENGINE
FIGURE 2: BIOMASS BURNER
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FIGURE 1: TYPICAL FREE-PISTON STIRLING ENGINE
—¦ FINNED HEAD
\ r— HOT WORKING
\ \ GAS SPACE
\ \ r- REGENERATOR
\	\	\			CB
X \ x
DISPLACER-18 ram STROKE
ALTERNATOR STATOR
I— VARIABLE SPRING for
/ POWER CONTROL
;— PISTON
/ PLANAR SPRINGS
—DISPLACER
/ PLANAR SPRINGS

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FIGURE 2: BIOMASS BURNER
FUEL
HOPPER
4 EXHAUST
1 FAN
AIR
PREHEATER
ALTERNATOR
/ /
"7—7—7	7
/ / / /
P = PRIMARY AIR
S ¦ SECONDARY AIR
V « CONTROL VALVES
F •	FAN
COOLER
WARM AIR
or
WATER

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5-1
COMMERCIALIZATION OF WIND POWER AND ITS POTENTIAL IMPACT ON GREENHOUSE
GAS EMISSIONS
Commercialization and deployment activities associated with wind power
have accelerated recently, both in the U.S. and abroad. The current
installed base of utility-connected wind power is summarized and
derivative calculations of electric generation and associated
displacement of greenhouse gas emissions are made. Technology and
market development trends are reviewed and DOS-sponsored wind
technology development and deployment activities are discussed.
Finally, an overview of competitive market considerations is given,
including an analysis of the projected competitiveness of wind power
compared to gas-fired generation to the year 2005.
INTRODUCTION
Recent deployment related activities under the U.S. Department of Energy
(DOE) wind energy research and development program, as well as in
industry and utility programs, have experienced a significant expansion.
Although uncertainties have increased in the marketplace over just the
past year or two, total wind installations in the U.S. are expected to
at least double or triple by year 2000. Expansion of development into
the midwest is continuing, with the 1994 completion of the 25 MW initial
phase of a 425 MW commitment in the State of Minnesota. Major wind
projects have been announced for California, Texas and Wyoming, as well
as east coast sites in New England and New York. The status of the new
California projects is uncertain because of the recent Federal Energy
Regulatory Commission (FERC) decision rejecting the bidding process that
separated renewables from other sources. New projects are operating on
power sales contracts at the US$0.05/kWh range, operating at higher wind
speed sites. Thus, wind energy has become the renewable electric
technology with the best potential in the near-term, for reducing
greenhouse gas emissions.
Despite these market activities, recent developments in the utility
generation marketplace have created new uncertainties in the prospects
for wind energy deployment. In response, the DOE Wind Energy Program is
continuing broad-based research and technology development but is also
increasing emphasis on advanced turbine development and adding market
mobilization and deployment activities. The Turbine Development Program
has moved to its next phase, Next-Generation Turbine Development,
exploring designs for commercialization in the 1993-2000 time frame. At
Susan Hock
National Renewable Energy Laboratory
National Wind Technology Center
1617 Cole Blvd.
Denver, CO 8C401
John B. Cadogan
U.S. Department of Energy
1000 Independence Ave., S.W.
Washington, DC 20585
Joseph M. Cohen and Bertrand L. Johnson
Princeton Economic Research, Inc.
1700 Rockville Pike, Suite 550
Rockville, MD 20852
ABSTRACT

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the same time, DOE is participating in the task of implementing the
Energy Partnerships for a Strong Economy Program, undertaken in close
collaboration with the utilities, the wind industry, and other key
parties, which will accelerate the deployment of wind technology. Also,
as international markets continue to grow, DOE is responding by
supporting targeted technology and market development activities in
conjunction with U.S. manufacturers. This paper will discuss current
status and trends in wind power commercialization, DOE's efforts to
accelerate those trends, and the resulting potential for greenhouse gas
emissions.
CURRENT STATUS
Market
Domestic
Electricity generation from wind energy is beginning to occur in many
regions of the country as wind moves beyond the 165 0 MW installed in
California. California provided the field experience to demonstrate that
wind energy could mature to the point where the electric utilities could
begin to treat wind as another generating resource. Wind power generated
approximately 3.4 billion kWh in 1994 in the U.S., avoiding nearly four
million tons of C02 emissions, as compared to coal-fired generators.
Emissions for manufacturing and deployment of wind power plants have been
shown to be negligible compared to extraction and combustion of fossil
fuels. As Figure 1 shows, there are good wind resources in 37 States,
roughly evenly distributed throughout the U.S. with the exception of the
southeast where the wind is generally marginal or even low. In many
Great Plains states, sufficient wind resources exist for each state to
supply a large fraction of total national electricity consumption if
resources were ever developed fully. Wind energy development is
compatible with agriculture and ranching because the land required for
turbines, transformers, power lines and controls occupies only 5 percent
of the total land.
The $0.015/kWh Renewable Energy Production Incentive (REPI), a provision
of the Energy Policy Act of 1992 (EPAct) , is in effect for wind
facilities through July 1, 1999. (The size of the REPI may be escalated
annually. It is currently $0.0l6/kWh.) The REPI, effective for the
first ten years of the plant's life, takes the form of a federal tax
credit for investor-owned utilities (ICUs) and independent developers.
As such, the actual percentage of the $0.015/kWh that can be recovered
will vary depending on the tax situation of the individual
developer/owner. In spite of this, the REPI has clearly had an impact
on the timing and extent of wind plant development in the U.S. The
incentive's importance was enhanced by a recent ruling by the Internal
Revenue Service that will allow new wind turbines within an existing wind
farm to qualify for the credit. Additionally, a facility {even composed
of a single turbine) with used parts may qualify for the credit if the
value of its used components is not more than 20% of its total value.
A current impediment to the use of the REPI by some
manufacturers/developers is the fact that, because they are still
relatively small businesses, they may not generate sufficient taxable
income to fully utilize the full $0.C15/kWh tax credit. To overcome
this, the wind industry has advocated modifying the alternative minimum
tax (AMT) law for wind facilities eligible for the REPI by providing a
25 percent credit against the AMT.
< no

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International
In the last five years, the market in Europe has grown mere steadily than
in the U.S. Installed capacity now totals approximately 1700 MW [l].
Commercial activity there has mostly been a result of government market
support and incentive programs. Five countries -- Germany, Denmark,
U.K., The Netherlands, and Spain -- comprised over 90% of the installed
base at the end of 1994. Recently, other countries have begun to install
significant amounts cf wind energy capacity. India dominates the group
with around 300 MW as of the Spring of 1995. From 1987 to 1994, the
number of countries with more than 1 MW of installed capacity jumped from
11 to 27. Over 90 percent of new capacity installed worldwide in 1994,
including in the U.S., was in foreign countries.
Technology
Wind technology has improved dramatically in the last fifteen years.
While the capital costs of wind turbines have dropped by a factor of
three, energy production per unit of rotor area has roughly tripled as
a result of new airfoils, controls and other improvements. Along with
substantial reductions in O&M costs, the result has been a drop in cost
of energy from over $0.10 per kWh in the late 1980s to the $0.05 per kWh
range today in a moderate wind regime, using constant dollars and
assuming investor-owned utility financing for 30 years. For higher wind
speed sites, wind developers have recently contracted for power sales for
between $0.04 and $0.05 per kilowatt-hour, thus establishing wind power
as the lowest cost renewable technology currently available.
TECHNOLOGICAL PATHS TO COMMERCIALIZATION
New turbines from Kenetech, Zond, Advanced Wind Turbines, Inc., FloWind
and others are becoming available, often through support: from the
DOE/National Renewable Energy Laboratory (NREL) Wind Program. Wind
energy appears to offer a good source of jobs for domestic and export
markets. However, because the near-term U.S. market is uncertain and
competition from international manufacturers is intense, the domestic
wind turbine industry faces a challenge to establish sales volume over
the next few years.
DOE Wind Program Technology R&D
In response to these market realities, the DOE Wind Program aims to
accelerate the building of a competitive wind energy industry and a
sustainable market. Increasing competition is driving industry to
improve technology and to innovate, and a sustainable market is necessary
for industry to continue to make R&D advances and refinements in response
to changing market' needs. The DOE Wind Program consists of two key
activities. The first, Applied Research, is an industry coordinated core
research program to establish the technical underpinnings of wind energy,
conducted at the National laboratories and universities. The second,
Utility and Industry Programs, consists primarily of wind turbine
development and deployment activities. These latter activities are
further discussed in the following sections. They both consist of highly
leveraged contracts with competitively selected industry and utility
partners.
Turbine Development Activities
The development of technologically advanced, higher efficiency wind
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turbines is one of the highest priorities of the U.S. wind industry, as
well as the Wind Program. A number of parallel activities are included
in the program. For the 1995/1996 time frame, three near-term improved
turbines have been developed and are being tested with a cost goal of 5
cent per kWh in 13 mph wind regime (wind power class 4) . Currently, two
of these manufacturers have commercial contracts in place, one of which
has already installed turbines. Three additional value engineered
turbines arc under various stages of development and testing with the
same target. One of these is under contract for a windfarm project in
Texas. In addition, six innovative subsystems contracts have been
initiated for components such as variable speed generators for new
industry turbines. A major effort is the next generation turbine
development project targeted at a cost of energy of 4 cents per kWh or
less in the class 4 wind regime. Seven conceptual design contracts have
been signed, with selection of 2 to 3 from the seven contractors for
cost-shared development planned for late in FY 1995. By the 1998 time
period, the 4 cent per kWh target will open up much of the. Great Plains
to wind energy development, and provide major export opportunities as
well.
MARKET PATHS TO COMMERCIALIZATION
Commercialization Trends
Domestic Commercialization
The Wind Program's projection for the year 2000 is 5,000 MW installed in
the United States and 20,000 MW by 2010. Relative to the 1700 MW
installed today, this level of capacity (by 2010) would provide between
I and 2 percent of the nation's electricity generation, in turn
displacing between about 28 and 50 million tons of C02 annually (based on
either displaced gas-fired or coal-fired generation, respectively). Of
course, the fuels displaced and thus the amount of green house gases
avoided depend on the utility generating mix and what units are on
economic dispatch. Methane emissions during natural gas recovery would
also be avoided. Restructuring of the electric utility industry has
slowed deployment of wind from what we projected as recently as two years
ago. Under current market conditions, the Energy Information
Administration projects 1400 MW added before the turn of the century [2] .
EIA projects 10,000 MW of wind by the year 2010.
Figure 2 illustrates where current wind farms are installed and where
future wind farms are planned. The majority of wind farm installations
are in California, but as the map indicates, there is considerable
activity all over the country. In the northwestern region, contracts
have been signed for over 50 KW of wind plants to be on line by 1996. The
northern plains area of the U.S. has extraordinary wind potential.
Minnesota, Iowa, and Wyoming power producers and utilities plan to add
significant amounts of wind power capacity in the near future. Texas
power producers and utilities have been very active with several projects
in various stages of planning including two firm contracts totalling 46
MW expected on line by the end of 1995, and another 40 MW project
expected by the end of 1996 . In the northeast, projects totalling almost
50 MW are planned in Kew York, Vermont, Maine, and Massachusetts.
International Commercialization
International markets appear to be poised for continued acceleration in
wind energy deployment. An additional 2000 to 3500 MW is expected by
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year 20CO [l]. This market is becoming increasingly important for the
U.S. wind energy industry because of the unexpected slower near-terra
growth of the domestic market. By supporting international market
efforts by the U.S industry, the federal government can help ensure the
long- term viability of the domestic industry while increasing the near-
term impact on reducing greenhouse gas emissions and enhancing the
balance of trade.
Technology Acceptance
As the wind industry has matured and garnered more public attention in
the last few years, a generation of utility planners and regulators who
are conversant with wind energy has begun, to develop; wind energy is
becoming a more acceptable technology within the electric industry. The
familiarity has been spurred through the support of such organizations
as the Electric Power Research Institute (EPRI) and the efforts of EPRI
and DOE in fostering such groups as the Utility wind Interest Group
(UWIG}. UWIG serves as a forum for the discussion of such issues as
utility integration of wind plants, and has recently assumed a broader
role as a key link for electric utilities in the voluntary wind
collaborative discussed below.
Current Market Uncertainty
As mentioned at the beginning of this section, several areas of
uncertainty are present in the current outlook for the domestic wind
power market. Several of these uncertainties in wind development relate
to:
•	the low price, perceived availability and desirable
environmental characteristics that favor natural gas for new
generation projects;
•	utility restructuring and its impact on the role of IRP;
•	repeal of Section 210 of PURPA; and
•	establishment of a sustainable wind industry.
DOE Wind Program Deployment and Market Mobilization Activities
The DOE Wind Program, together with the National Wind Coordinating
Committee and other stakeholders are addressing these issues. Key
elements of the Program's deployment activities are:
National Wind Coordinating Committee
The National Wind Coordinating Committee is a voluntary collaborative
composed of stakeholders, including electric utilities, independent power
producers, State and local governments, utility regulators, wind
equipment manufacturers, service providers, and consumer and
environmental groups. (See Figure 3) . The NWCC is functioning as a
voluntary group which: (l) provides a forum for key stakeholder
viewpoints on a market-driven approach to accelerate the use of wind
power, (2) develops consensus on activities, and (3) coordinates activity
implementation. Individuals and businesses can participate in the
collaborative activities through their respective trade organization,
government representative or stakeholder group.
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Wind Energy Deployment Project
As a result of the Program's public/private partnerships, including the
National Wind Coordinating Committee, improvements in cost of energy,
reliability, and buyer confidence are resulting in the successful
penetration of domestic and international bulk power markets. Continued
FY 1995/1996 collaborative activities will result in accelerated
deployment of wind power plants, increased employment, and a strengthened
wind industry infrastructure. A solicitation for 25 MW or larger cost-
shared wind projects has been issued, with the Federal contribution
limited to 20 percent or less. Proposals are now being evaluated.
Turbine Verification Project
DOE and EPRI have developed a cooperative program to help utilities
evaluate a new generation of wind turbines under typical utility
operating environments. This program is known as the Turbine Verification
Project (TVP) and serves to bridge the gap between development and
commercial sales. Central and South West Services, Inc., with a proposed
6 MW project located in Texas, Green Mountain Power Corp., with a
proposed 8 MW project located in Vermont, and Niagara Mohawk Power, with
a 6 MW project in New York have been selected for this program. An
additional solicitation is planned.
MARKET CONSIDERATIONS FOR COMMERCIALIZATION
Wind technology has improved considerably since the early 1980s, and wind
energy developers, manufacturers and electric utilities have a solid base
of experience in the 1650 MW operating in California. As Figure 2 shows,
wind energy is now moving beyond California. Yet, on the basis of
today's natural gas costs, many say it is difficult to see how wind power
can compete, which is true if one focuses only on first year costs.
Just as there are different technological paths to commercial success,
there are also different paths in terms of market conditions necessary
for wind technology to successfully compete. Economic evaluation of wind
applications for bulk utility power (at the level of a wind farm or wind
power plant) requires definition of the markets targeted. Planning
studies distinguish three market applications, two ownership classes
(regulated utility and independent producer or developer) and many
variations, with diverse decision factors within these markets. Each
wind project must stand on its own merits using appropriate decision
factors.
Three' related, yet different applications are:
1)	Wind energy as a fuel saver against existing capacity:
As a high capital cost and low operating cost option, wind energy appears
more favorable if evaluated on a life cycle basis with anticipated fuel
costs increases included in the evaluation. Wind plant financing costs
are minimized if development proceeds through a municipal utility, which
has access to tax-free financing (100% debt). An investor-owned utility
would typically use a 50/50 debt/equity structure with 30 year financing.
2)	Wind as a generation expansion option (fuel saver plus capacity
credit):
Here the competition is a specific new unit or set of units. With
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certain exceptions, electric utilities in the U.S. are not comfortable
with the notion of a statistical capacity credit for wind, although we
expect this to change as utility experience with wind plants increases.
Again, wind energy looks best if evaluated on life cycle cost basis,
which is typically the method used by regulated utilities.
3) A hybrid plant of wind energy with natural gas-fired combustion
turbines or hydro backup as a firm power source in a competitive resource,
acquisition process:
The village power market for non-interconnected installations and
isolated villages all over the world is not considered in this paper,
although it is an important application.
with the exempt wholesale generators (EWG) provision of the Energy Policy
Act, as well as trends in the utility sector, it appears likely that
historical access or preference for renewables that recognizes the social
or environmental values of increasing renewables use will become less
prevalent. In light of this, a hybrid power system of wind with natural
gas, hydrcpower and/or storage may be necessary for wind energy to
compete successfully in an environment in which new generating resources
are acquired competitively and the role of regulatory oversight including
integrated resource planning is lessened.
With this background, 'we would like to show that with advanced technology
installed at. higher wind resource locations, wind energy can be
competitive with natural gas within the next five years on a fuel saver
basis. We believe tfhat wind will be competitive in other market segments
as well.
DOE cost-of-energy (COS) projections for technology available in 1995,
2000 and 2005 are 5.2 cents/kwh, 4 cents/kWh and 3.8 cents/kWh (in
January 19D3 dollars) respectively for a wind power class 4 site (5.8 m/s
annual average at 10 meters) . For Class 5 winds (6.2 m/s) , the wind COE
goals are 4.5 cents/kWh in 1995 and 3.6 cents/kWh in 2000. The DOB
Energy Information Administration projects a national average cost of
natural gas delivered to electric utilities of $2.59 per million Btu (in
1993 dollars) in the year 2000, which is essentially zero change from the
current cost, although costs vary widely in the spot market in some
regions. The EIA cost of gas is projected to rise to $3.73/MMBtu in the
year 2010, an annual rate of 2.2% above inflation from 1993 [2] .
The results of these simple calculations are shown in Table l for three
wind speed classes for the years 1995, 1999 and 2005. As the cost of
wind energy falls, wind should become competitive in broader regions as
larger areas of lower quality resources become economically attractive.
Clearly, at better' wind sites with the Renewable Energy Production
Incentive, wind energy can be competitive against natural gas at prices
above $2.5/MMBtu. However, this analysis includes the following
assumptions and uncertainties:
1) 30 year financing and lifecycle economics typical of an .investor-owned
utility have, been assumed. A large fraction of capacity added from all
sources in the last five years has been independent producer in origin.
Much of the proposed wind capacity would be independent producer also.
Independent producers have shorter time horizons than regulated utilities
and their bid prices might be higher. Moreover, in a competitive
marketplace that emphasizes short-term, least-cost avoided cost, the 30
year financing and life-cycle costing of an investor-owned utility are
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not likely. The Wind Program is working with other renewables programs
and stakeholders to identify options that would allow renewables to
compete in the emerging competitive marketplace.
7) The Renewable Energy Production Incentive has been assumed for the
years 1995 and 1999. It is worth about 1.2 cents/kWh on a lifecycle
basis assuming that the taxpayer has revenues to offset and is not
limited by other tax provisions.
3)	Effects of transmission costs relating to location of the wind
resource have not been included. These costs could be significant but
will be site-specific [3].
4)	There are aspects of potential value from wind energy that are at
present poorly understood but may enhance the competitive stance of wind
projects in the future. For instance the ability to forecast wind for
minutes, hours, or even days ahead would increase the value of wind by
allowing utilities to use it as a dispatchable source of generation.
Better understanding of how to calculate a statistical, capacity credit
for wind generation would also increase its value [4].
5)	Externality benefits associated with emissions reductions are not
included. Such benefits for wind and other renewables as short
construction time (12 months or less), modularity in sizing and reduced
exposure due to fuel 'cost variations are also not evaluated.
Results of this simple case study would not be significantly different
using detailed power system simulations: key parameters are the cost of
the wind plant, its capacity factor and operations and maintenance cost,
the cost of natural gas, expected escalation rate and conversion
efficiency of the marginal source. Avoided emissions depend on the
marginal source as well.
CONCLUSION
Our data indicate over 2700 MW of wind projects announced for
installation in the U.S. before 2005. Although not all of these projects
may be built, additional plants not yet announced will be. developed.
Wind can compete against other forms of generation in the near-term if
the proper set of market and technical requirements are met. The
principal barrier to wind deployment is perceived risk by decision makers
because of lack of experience with this new technology. Under the Energy
Partnership for a Strong Economy Program, the National Wind Coordinating
Committee will address this risk and is expected to play a major role in
jump-starting the appropriate development of wind energy in many regions
of the United States. DOE-sponsored turbine development and deployment
activities, cost-shared with industry and utilities, will also help
accelerate the deployment of wind energy domestically, and in
international markets. Displacement of C02 from projacted installations
in the U.S. alone is estimated at between 28 and 50 million tons annually
by 2010. Wind energy is positioned to play an important role in our
national and global energy and environmental future.
REFERENCES
1. Arthur D. Little, 1994, in "The U.S. Wind Energy Industry, Bringing
State-Of-The Art Technology To The Market place," American Wind
Energy Association, February 1995.
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2.	Energy Information Administration, Annual Energy Outlook 1995,
DOE/EIA-C'383 (95) , pg. 76, January 1995.
3.	Parsons, B., Wan, Y., Elliott, D., "Estimates of Wind Resource Land
Area and Power Potential in Close Proximity to Existing Transmission
Lines," National Renewable Energy Laboratory, Presentation at
WINDPOWER 95 Conference, Washington, D.C., March, 1995.
4.	Milligan, M., Miller, A., Chapman, F.( "Estimating the Economic
Value of Wind Forecasting to Utilities," National Renewable Energy
Laboratory, Presentation at WINDPOWER 95 Conference, Washington,
D.C., March, 1995.
TABLE 1: COST OF ENERGY COMPARISONS FOR WIND AND NATURAL GAS
CAPITAL AND
FUEL COST
INPUTS
LEVELIZED
COST
OF ENERGY
(COE)
Assumptions:
•	Cost are overnight, in 1S93 constant dollars
•	Fuel costs from EIA Annual Energy Outlook 1995
•	Wind cost of energy calculations use utility economics
•	Renewable Energy Production Incentive valid for wind facilities installed by July 1,1999
•	Gas Heat rates based on mix of peak, intermediate and basoload operation

Year
" ' 1955
1999
2Ct)5
Wind Turbine
Costs
Installed Cost ($/kW)
773
755
742
O&M Cost (cents/kWh)
1.2
1.0
0.8
Cap. Factor (Class 4 wind)
23.9%
28.9%
31.4%
Natural Gas
Combined-Cycie
C03tS
First Yr Fuel Cost ($/MMBtu)
2.57
2.S9
	 158
Real Fuel Cost Escalation
-
	""Dm	
3.2%
Level. Fuel Cost ($/MM3tu)
3.46
3.4a
4 55
Var. O&M Cost (cents/kWh)
0.4
0.4
0.4
Heat Rate (Btu/kWh)
9000
8000
7520
.


Year
1995
1999
2005
Wind Turbine COE
Class 4 winds (5.8 m/s at 10m
5.2
4.0
3.8
Class 5 winds (6.2 m/s)
4.5
3.6
3.4
Class 6 winds (6.7 m/s)
4.1
3.5
3.1
Wind Turt ne COE
with 1.2 cent/kWh
Production Incentive
Class 4 winds (5.8 m/s)
4.0
3.0
3.8
Class 5 winds (6 2 m/s)
3.3
2.6
3.4
Class 6 winds (6.7 m/s)
2.9
2.3
3.1
Natural Gas
Ccrnbined-Cycle
COE
Fuel cost and variab e
O&M cost only
3.5
32
3.8
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FIGURE 1: AVERAGE ANNUAL WIND POWER IN THE U.S.
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lti-125 134US
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CiJJC
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14.6-1 S.J
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FIGURE 3: WIND COMMERCIALIZATION COLLABORATIVE
User Sector
•	Utilities
•	IPPa
•	Trade Organizations
•	UWKJ

National Wind Coordinating Committee [
•	A forum for key stakeholder viewpoints
< Concensus on collaborative activities
•	Coordinate implementation	;
Facilitator Sector
•	DOE/Uabs
•	EPRI
•	Environmental Groups
•	State Energy Offices
•	Regulators
•	Financial Community a
Supplier Sector
•	Turbino Manufacturers
•	Project Developers
< Consultant Support
•	AWEA
«
FIGURE 2: SELECTED WIND POWER IN THE U.S.

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AlTftMStn
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7*7 MM
ITHAC»U«
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-------
5-J
FUZZY-LOGIC-BASED ADAPTIVE CONTROL OF AC
INDUCTION MOTORS FOR ENERGY OPTIMIZATION
R. j. Spiegel and P. J. Chappell
U.S. Environmental Protection Agency
Air Pollution Prevention & Control Division
Research Triangle Park, North Carolina 27711
M. W. Turner
Center for Digital Systems Engineering
Research Triangle Institute
Research Triangle Park, NC 27709
ABSTRACT
Fuzzy logic control of alternating-current (AC) induction motors is being
investigated under sponsorship of the U.S. Environmental Protection Agency (EPA)
for energy efficiency optimization and performance enhancement. An energy
optimizing controller utilizing fuzzy logic has been developed to improve the
efficiency of motor/drive combinations running at various load and speed conditions.
The energy optimizer is complemented by a sensorless speed controller which
maintains motor.shaft revolutions per minute (RPM) to produce constant output
power. Efficiency gains of from approximately 1 to 20% are obtained from laboratory
demonstration with commercial motors and drives. Motor shaft RPM is controlled to
within 0.9%.
This paper has been reviewed in accordance with EPA's peer and administrative
review policies and approved for presentation and publication.
INTRODUCTION
The environmental case for improving motor efficiency is clear. Electric
motors use over 60% of the electrical power generated in the U.S. The U.S. population
of approximately 1 billion (109) motors use over 1700 billion kWh per year. Over 140
million new motors are sold each year. A review of the U.S. motor population reveals
that 90% of the motors are less than 1 hp (0.746 kWe) in size, but use less than 10% of
the electricity consumed by motors. More than 80% of the electricity used by motors
is consumed by less than 1% of the motor population, or motors greater than 20 hp
(14.92 kWe). Based on these facts, it is clear that large energy savings from
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improvement in motor efficiency could be achieved from a relatively small motor
population. Each 1% improvement in motor efficiency could result in 17 billion kWh
per year of electrical energy saved, over $1 billion in energy costs saved per year, an
equivalent of 6-10 million tons per year of displaced coal, and approximately 15 to 20
million tons less carbon dioxide released into the atmosphere.
To reduce energy consumption by electrical motors, EPA is pursuing the
development of fuzzy-logic-based energy optimizers for AC induction motors
controlled by Adjustable Speed Drives (ASDs). Conventional ASDs adjust motor
speed by changing the frequency, voltage, and/or current supplied to an AC motor
[1]. However, they do not optimally adjust these parameters to minimize input
power at a given motor speed and load torque. The technical goals of the research
program are: 1) to increase the efficiency of ASD/motor combinations, especially
when operating at off-rated torque/speed conditions; 2) to develop a generic
controller for energy optimization that can be applied to a wide range of motors and
ASDs regardless of their size and application; and 3) to develop a controller for energy
optimization that can eliminate the requirement for tachometer or encoder feedback
and still maintain the stability and response of closed-loop speed control.
CONTROL SYSTEM
Figure 1 is a general block diagram for the AC induction motor electrical
control system, including details of the ASD (rectifier and inverter). The induction
motor is electrically connected to a voltage-fed, pulse-width modulated (PWM),
insulated gate, bipolar transistor (IGBT) inverter. The IGBT rectifier is connected to
the utility grid. The single frequency (60 Hz), single voltage power from the grid is
converted to direct-current (DC) power. The inverter then converts the DC output of
the rectifier to a variable frequency, variable voltage output to control the speed of
the motor. The fuzzy-logic-based controller consists of three main components: a slip
compensator, an energy optimizer, and a speed corrector. This controller becomes
effective at steady state conditions; i.e., when the speed loop error approaches zero.
During nonsteady state conditions (i.e., when the speed or load torque changes), the
motor excitation current is established at the rated value in order to achieve a fast
response.
Slip Compensator
Because of slip, the induction motor operates at a speed lower than the
synchronous speed [2], It is possible to approximately compensate for this slip speed
without measuring the actual rotor speed. Of course, the speed can also be controlled
by a tachometer, but this adds capital and maintenance costs to the control system. To
illustrate the reason to estimate motor slip, consider an example when the
commanded change in the motor's operating frequency is from the rated value (60 I Iz)
to a new value of 30 Hz. The new operating speed of the motor will not be the desired
value of one-half the rated speed. Usually, the new speed will be slightly greater than
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the desired value, and consequently wastes energy because the motor's speed is too
fast. Slip compensation lowers the rotor speed to the correct value by estimating the
motor's slip, thereby saving energy.
During steady-state conditions, the slip compensation control operates first
(before the energy optimizer and the speed corrector). It is a one-time correction for
each commanded change in the motor's operating condition. For many motor loads
such as centrifugal pumps, compressors, and fans, the load-torque varies as the square
of the rotor speed. This fact allows the calculation of the slip for setting the motor
speed to be relatively easy. However, for a constant load-torque case the slip can be
estimated by measuring the DC power (see Figure 1) to the motor and subtracting
losses in the inverter and in the stator of the motor to estimate the air-gap power.
This yields the motor's torque from which the slip can be estimated.
Energy Optimizer
The energy optimizer operates on the basis of on line efficiency optimization
control, where the motor's magnetic airgap flux is decremented in steps until the
measured input power reaches the lowest value. This type of control does not require
knowledge of motor parameters; it is completely insensitive to parameter changes;
and it is universally applicable to any arbitrary motor. The principle of efficiency
optimization control with flux decrementation is explained as follows. The rotor
airgap flux is decreased by reducing the magnetizing component of the stator current
as a result of lowering the stator voltage in steps. This ultimately results in a
corresponding increase in the torque component of the stator current by the action of
the speed corrector so that the developed torque and speed remain constant. As the
airgap flux is decreased in steps, the iron core loss decreases as well. However, due to
the rise in the torque component of the stator current, the copper loss increases. At the
operating point where the core loss decrease is offset by the copper loss increase, the
minimum input power level is reached. The search is continued until the system
reaches this minimum input power point. Any excursion past this point will cause the
controller to return.
Details of the fuzzy-logic-based energy optimizer will not be described here, as
the optimizer has been elaborated on elsewhere [3,4,5]. It suffices to state that in the
implementation of fuzzy control, the input variables are fuzzified by membership
functions; the fuzzy control rules are evaluated by a rule base table; the outputs are
combined by fuzzy composition (i.e., SUP-MIN principle); and then the resultant
defuzzified by a centroid or height method. The advantages of fuzzy control include:
no mathematical model of the motor is required; it can provide adaptive step sizes
leading to fast convergence; and it can accept inaccurate and noisy signals. E:or a
traditional proportional/integral (PI) controller, the control mapping surface is
confined to a plane in three-dimensional control space. Any type of mapping surface
is possible with a fuzzy controller, resulting in a highly flexible structure to achieve
results. To illustrate the basic fuzzy logic control approach, an example fuzzy rule is
proffered:
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If the power increment is negative medium and the last change in
stator voltage is negative, then the new stator voltage increment
is negative medium.
The basic idea is that, if the last control action indicates a decrease in input power,
proceed searching in the same direction with the control magnitude somewhat
proportional to the measured input power change.
Speed Corrector
As staled previously, when the energy optimizer changes the stator voltage,
there will be a corresponding change in rotor speed. Since the energy optimizer
operates under the assumption of constant output torque and speed, any deviation
from this premise is detrimental to the system's performance. To overcome this
problem without the use of a tachometer, a non-feedback (sensorless) speed corrector
has been developed to maintain rotor speed. This type of approach is desirable
because a feedback-based controller (tachometer) requires additional hardware
(sensors, lines, connections, data acquisition, and data processing) that reduce the ease
of installation and increase the cost and maintenance of the overall control approach.
The speed corrector operates on the general objective to keep the speed at the
value produced by the slip compensator. It operates sequentially with the energy
optimizer. First, the speed corrector estimates the rotor speed based on three inputs:
the change in stator voltage, the stator frequency prior to the voltage charge, and the
initial rotor speed. Using this estimate of the present rotor speed, a new value for the
stator frequency is determined by fuzzy-logic-based procedures. The design of the
fuzzy logic speed corrector was aided by the utilization of basic motor simulation
models based on the Steinmetz equivalent circuit [2], In this regard it should be
emphasized that while the design was affected by the motor models, the fuzzv-logic-
based speed corrector is not model dependent.
LABORATORY RESULTS
A precision test facility has been assembled to ascertain efficiency increases due
to performance of the energy optimizing controller. A personal computer (PC)
monitors the data acquisition system and communicates with the ASD to alter the ASD
voltage and frequency output. Various degrees of load on the motor are achieved by
varying the strength of the field in a DC brake dynamometer.
Figures 2 and 3 show experimental results of optimal efficiencies achieved
using the energy optimizer versus efficiencies achieved by the ASD operating alone.
Figure 2 contains results for a Leeson 10 hp (7.46 kW'e) motor and Figure 3 represents
similar data for a Lincoln Hlectric 10 hp (7.46 kWe) "I li-Efficiency" motor. Results are
compiled over a range of load and speed combinations as represented by the percent
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of rated speed and torque. The horizontal axes of Figures 2 and 3 represent the
different speed and torque combinations. Each combination represents the load
produced by a fan or pump running at the given percent speed. In each case the load
is proportional to the square of the speed. Thus, at 40% of rated speed (the leftmost
horizontal point), the torque is 16% of rated torque. The vertical axes represent the
measured efficiency of the motors for each speed/torque condition. The solid curves
represent the efficiencies available using an ASD operating without the energy
optimizer, while the dashed curves show the results achieved using the ASD
controlled by the energy optimizer.
From Figure 2, efficiency gains range from 8% at low speed/torque conditions
(40/"16) to less than 1% at medium speed/torque conditions (70/49). Especially note
that, at the upper range of speed/torque combinations (90/81), efficiency
improvements as high as 2.5% have been achieved. This is very important because,
although the percent gain is less than at the lower speed/torque combinations, the
actual saving in energy is higher as a result of the motor consuming more power the
faster it operates.
Figure 3 contains results for a different motor (Lincoln Electric). First, observe
that these results are somewhat different from the previous case. Efficiency gains as
high as 12% are achieved for low speed/torque conditions, but virtually no
improvement occurs fot' high speed/torque combinations.
The data of Figures 2 and 3 also demonstrate that different motors yield
different results. The differences are considered to be primarily a function of motor
design.
In order to correct for speed change and maintain output torque, a speed
corrector maintains the desired speed without the use of a tachometer. At each step in
the energy optimization process, the speed correcting controller compensates for
changes in speed with changes in input frequency. The accuracy of the fuzzy-logic-
based speed corrector is demonstrated by the results of Figure 4. The percent speed
error (actual speed/desired speed) is plotted as a function of speed/ torque
combinations for a pump or fan. These data show that the accuracy of the speed
corrector is maintained approximately within a ± 0.9% range,
DISCUSSION AND CONCLUSIONS
Energy optimization of motor/drive combinations has been shown to produce
improvements in efficiency over that available from the ASD functioning alone.
Gains as high as 20% improvement in efficiency have been achieved dependent on the
load and motor. Observation of the composition, number, and energy use of the
motor population in the U.S. indicates that this level of efficiency enhancement has
significant potential for energy savings and pollution prevention [6],
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The use of fuzzy logic aided in the development of an energy optimizer for a
tion-linear dynamic physical system by eliminating the requirement for development
of a detailed system model using motor-dependent parameters. Fuzzy logic has
proven easy to implement for motor/drive control. Use of the fuzzy-logic-based
energy optimizer in a simulator which contained the equivalent circuit parameters for
16 different motors has shown that the energy optimizer demonstrates robustness
when faced with changing machine parameters.
In the laboratory test cases, the adaptive control system (slip compensator,
energy optimizer, and speed corrector) was implemented using software running on a
PC to control a modified commercial ASD. Current effort is directed toward
implementing the controller in C language on an Intel 87C196MC programmable
microchip. The microchip controller generates voltage and frequency signals which
control the PWM output to the inverter. Assembly language code is being used to
produce the required PWM signals for the inverter. The microchip controller will be
installed as the primary inverter controller for the ASD operation.
A demonstration of the technology is planned using a large water pump or
boiler draft fan application in 1996.
REFERENCES
1.	Bose, B.K., Power Electronics and AC Drives, Prentice-Hall, Englewood Cliffs,
NJ, 1986.
2.	Krause, Paul C. and Oleg Wasynczuk, Electromechanical Motion Devices,
McGraw-Hill, Inc., New York, 1989.
3.	Cleland, J., et al., "Fuzzy Logic Control of AC Induction Motors," Proceedings
of 1992 IEEE International Conference on Fuzzy Systems, March 1992.
4.	Spiegel, R.J., et a!., "A Fuzzy-Logic-Based Energy Optimizer for AC Motors,"
presented at the 1995 Fuzz-IEEE Conference, Yokohama, Japan, March 20-24,
1995.
5.	McCormick, Ed arid Wayne Turner, "Genetic Design of a Fuzzy Controller for
AC Induction Motors," Intelligent Automation and Soft Computing, Vol. 1,
Proceedings of the 1994 World Automation Congress, pp. 573-576, Mo Jamshidi,
et al., eds.
6.	Baldwin, S.F., "Energy-Efficient Electric Motor Drive Systems," Electricity.
Johansson, Thomas B., Birgit Bodland, and Robert H. Williams, eds., Lund
University Press, Lund, Sweden, 1988.
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FIGURE 1. FUZZY-LOGIC-BASED ENERGY OPTIMIZER FOR
AN AC INDUCTION MOTOR

-------
FIGURE 2. ENERGY OPTIMIZER PERFORMANCE
FOR A LEESON 10 HP MOTOR

-------
FIGURE 3. ENERGY OPTIMIZER PERFORMANCE
FOR A LINCOLN ELECTRIC 10 HP "HI-EFFICIENCY" MOTOR

-------
FIGURE 4. PERCENT CHANGE IN SPEED AFTER EFFICIENCY OPTIMIZATION
FOR PUMP/FAN LOADS USING FUZZY SPEED CONTROLLER
% Rated Speed/% Rated Torque

-------
5-K
FUZZY-LOGIC-BASED ADAPTIVE CONTROL OF A
VARIABLE SPEED WIND TURBINE
R. J. Spiegel
U.S. Environmental Protection Agency
Air Pollution Prevention & Control Division
Research Triangle Park, North Carolina 27711
B. K. Bose
Department of Electrical Engineering
University of Tennessee
Knoxville, Tennessee 37996
ABSTRACT
Fuzzy-logic control of a variable-speed wind turbine is being investigated
under sponsorship of the U.S. Environmental Protection Agency (EPA) for efficiency
optimization and performance enhancement. The control system consists of three
fuzzy-logic controllers: a controller to track the turbine generator speed with wind
velocity to extract the maximum output power; a controller to optimize the generator
airgap magnetic flux for efficiency improvement; and a controller to provide for
robust speed control against wind gusts and turbine oscillatory torque. The paper
describes the control system which has been developed, as well as early stages of
work to validate the design and document the performance obtained.
This paper has been reviewed in accordance with EPA's peer and administrative
review policies and approved for presentation and publication.
INTRODUCTION
It has been conservatively estimated that the U.S. accessible wind resource
could produce more than 10 times the electricity currently consumed [1]. For
example, the Bonneville Power Administration has identified 20 to 60 gigawatts (GW)
of potential wind capacity in eastern Idaho and Montana, alone. Likewise the world
has an enormous resource of wind power: all the electricity needs of the world could
be met with 10% of the raw wind potential [2], Wind energy is the most cost-
competitive renewable energy technology for the bulk power market, with electricity
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production costs in the range of 5c-7
-------
considerations is the control complexity of meeting all of the potential contradictory
demands placed upon, and the large number of variables occurring within, such a
system, including, for example, variations in wind speed and acceleration, wind gusts,
and wind turbulence. Conventional variable-speed control systems can generate
electrical power at a constant frequency in the face of such a plurality of variables, but
generally not in the most efficient manner to produce maximum power output.
This paper describes an adaptive control approach in which fuzzy logic set
theory is utilized in an integrated intelligent controller to improve the output power
and performance of VSWTs. The control strategy has been validated by a computer
study in which the complete VSWT system was simulated by numerical procedures
[3]. Some of the results of the computer simulation study will be presented here. An
experimental study with a 5 hp (3.735 kWe) laboratory drive system is in progress.
TURBINE CHARACTERISTICS
Both horizontal and vertical axis wind turbines are used in wind-powered
electrical generation systems [4], The vertical Darrieus (egg beater) type has the
advantage that it is located on the ground and can accept wind from any direction
without special yaw mechanisms. Its disadvantages are that this turbine is not self -
starting, and large pulsating torques can be can be produced on the output shaft.
Turbines are generally characterized by a figure-of-merit called a power
coefficient which is defined as the ratio of power extracted from the wind to the power
available in it over the area covered by the diameter of the rotor. If the rotor slows
the wind excessively, too much wind will flow around the rotor blades, and if the
rotor does not slow the wind enough, too much energy will pass through unused. An
optimum is achieved when the wind is slowed by approximately two-thirds, resulting
in a theoretical power coefficient of 0.593,
The aerodynamic efficiency of turbines for varying wind speeds can be
maximized by setting the optimum tip speed ratio (ratio of the turbine speed at the
blade tip to the free stream wind speed). Of course, the ideal theoretical power
coefficient of 0.593 can never be reached. Figure 1 contains a typical family of turbine
torque/speed curves for different wind velocities. Also superimposed on these curves
is a set of constant power curves, along with the locus of maximum power output.
The curves reveal that for each particular wind speed there exists a turbine speed to
deliver maximum power output. To generate this maximum power at each wind
speed, the generator load torque must be matched with the turbine output torque.
This requires a controller that can vary the turbine speed to get the maximum power
output at the given wind conditions. Because the torque/speed characteristics of the
wind generation system are analogous to that of a motor/pump or motor/fan system,
the turbine torque (Te) is proportional to the square of the rotor speed (Wr), while the
power output (P0) is proportional to the cube of the rotor speed. Therefore, the
generator output is proportional to the product of torque and speed (P0<=
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yields the constant power hyperbolic curves on Figure 1. Where the constant power
hyperbolic curves intersect (at a constant wind speed), the turbine torque/speed
curves yield the maximum producible power output by the turbine. It is to be rioted
that this value does not occur at the peak of Ihe turbine torque/speed profile.
Because of variable wind speed conditions, including gusts, the turbine
generator will be rarely operated at full (rated) load conditions. This means that, at
any reduced speed, light load, steady state condition, the generator efficiency can be
further improved by reduction of the generator airgap magnetic flux. At light load
conditions, rated flux operation yields excessive core loss and, consequently, low
efficiency of operation. The concurrent reduction of flux and increase of active
current, so that the developed torque matches the load torque, can provide improved
turbine generator efficiency. Thus, once the turbine speed and the developed torque
are both set at optimum values, the generator flux component of current can be
decreased to reduce the airgap flux until the generator produces the maximum output
power. This type of flux minimization approach has been shown to be a promising
technique for extracting maximum efficiency from ac induction motors when the
motors are operated at less than rated speeds and loads [5,6].
CONTROL SYSTEM
Figure 2 is a the general block diagram for the wind turbine electrical control
system, including details of the power electronics converter (rectifier and inverter).
The wind turbine rotor shaft is coupled to the squirrel cage induction generator
through a speed-up gear ratio (not shown). The induction generator is electrically
connected to a voltage-fed, pulse width modulated (PWM), insulated-gate, bipolar
transistor (IGBT) rectifier. The IGBT PWM inverter is connected to the utility grid
power lines. The variable-frequency, variable-voltage power from the generator is
converted to direct current (dc) power by the rectifier. This rectifier also supplies the
excitation needs of the generator. The inverter converts the dc output of the rectifier
to a single frequency (60 Hz), single-voltage ac output to the grid. Active power can
flow in either direction (rectifier-to-inverter or inverter-to-rectifier) as required by the
converter control sequence. The PWM rectifier uses indirect vector [7] control in the
inner current control loop, while direct vector (7] control is used for the PWM
inverter. Advantages of this converter include a grid-side power factor which is unity
with harmonic distortion essentially nonexistent. Additional advantages include
possible continuous power production from nearly zero speed to the highest possible
safe speed; the turbine, if it is of the vertical type, allows the generator to be operated
as a motor to provide starting torque; regenerative braking torque is used to stop the
turbine; the generator airgap flux is controlled for improvement of efficiency; and the
transient response is fast, giving improved system performance.
The dc link voltage (Vcj) at the capacitor is controlled at a desired level to
permit PWM operation of the converter on both sides (rectifier and inverter). This
voltage, if too high, could damage the semiconductor power devices. If the voltage is
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too low, PWM operation may be prevented. A dc link voltage controller regulates the
output power so that the link voltage remains at the desired level.
Figure 2 also shows a flow diagram of the fuzzy-logic-based control system
which is applicable for either a horizontal or vertical axis wind turbine. Conventional
symbols and notations are used whenever possible to define the parameters and
functional blocks associated with the control scheme. The asterisk (*) is used to
designate control variables. The elements Gi, G2, and G3 are gain or compensator
functions and may contain a limiter to restrict the excursion of the respective variable.
The objective of the control approach is to enhance the performance of the VSWT by
maximizing the output power for a given wind speed. This is accomplished by three
fuzzy logic controllers,, FLC-1, FLC-2, and FLC-3, which perform distinct but
coordinated tasks: FLC-1 optimizes output power; FLC-2 optimizes generator
efficiency (controls airgap magnetic flux), and FLC-3 controls speed.
Fuzzy Controller FLC-1
Since the power is given by the product of torque and speed and the turbine
power approximately equals the line power or output power (P0), the turbine
torque/speed curves of Figure 1 can be translated to the output power/generator
speed curves shown in Figure 3. For a particular value of wind velocity (Vw), the
function of fuzzy controller FLC-1 is to change the generator speed until the
maximum output power condition is reached. The operational procedure is
illustrated in Figure 3. For example, for a wind speed of VW4 the output power will be
at point A if the generator speed is Wri. FLC-1 will then alter the speed in steps until
it reaches the speed Wr2 when the output power is maximum at point B. If the wind
velocity increases to VW2, the output power will jump to point D, and then FLC-1 will
bring the operating point to E. If the wind velocity drops to VW3, then point G is
reached, and FLC-1 brings the operating point to H. This procedure is repeated each
lime the wind velocity changes.
The principles of the fuzzy logic aspects of the controller will not be elaborated
on here; further details can be found elsewhere [3], It suffices to state that, with an
incrementation (or decrementation) of output power, the corresponding
incrementation (or decrementation) of speed is estimated by fuzzy logic principles. If
the increment in output power (AP0) is positive with the last increment in speed
(LAWr) positive, the new control increment (AWr) is continued in the same direction.
Conversely, if a positive LAWr causes a negative AP0, the direction of the search is
reversed. The variables APn, AWr, and LAWr are described by fuzzy logic membership
functions and a rule base or set. The advantages of fuzzy control are: the controller
provides an adaptive step size that leads to fast convergence; the controller can accept
inaccurate and noisy signals; the controller does not need any wind velocity
information; and the controller's real time search approach is insensitive to system
parameter variation.
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Fuzzv Controller FLC-2
Since most of the time the generator is operated at speeds and loads below
rated or full scale values, the generator rotor airgap magnetic flux can be reduced
from rated values to reduce the iron core loss and thereby increase the generator
efficiency [6]. The principle of on-line search-based flux programming control by a
second fuzzy controller, FLC-2, is explained as follows. At a certain wind velocity Vw
and at the corresponding optimum speed Wr established by FLC-1 (which operates at
rated airgap magnetic flux), the rotor flux is reduced by decreasing the magnetizing
component of the stator current. This causes increasing torque current by the speed
loop for the same developed torque. As the flux is decreased, the iron loss decreases
with the attendant increase of copper loss. However, the total system (converters and
generator) loss decreases, resulting in an increase of total generated power P0. The
search is continued until the system reaches the maximum power point. Any attempt
to search beyond this point will force the controller to return to the maximum power
point. The principle of fuzzy controller FLC-2 is somewhat similar to that of FLC-1.
The system output power PD is sampled and compared with the previous value to
determine the increment AP0. In addition, the last excitation current decrement is
reviewed. On these bases, the new decrement step for the excitation current is
generated from fuzzy rules through fuzzy inference and defuzzification. The effect of
controller FLC-2 in boosting the power output is shown in Figure 3. The FLC-2
controller operation starts when FLC-1 has completed its search at the rated flux
condition. If wind velocity changes during or at the end of FLC-2, its operation is
abandoned, the rated flux is established, and FLC-1 control is activated.
Fuzzv Controller FLC-3
The speed loop is controlled by the fuzzy controller FLC-3, as indicated in
Figure 2. It basically provides robust speed control against wind turbulence and
turbine oscillatory torque. The disturbance torque on the generator shaft is inversely
modulated with the developed torque to attenuate modulation of output power and
prevent any possible mechanical resonance effect. In addition, the speed control loop
provides a deadbeat type response when an increment of speed is commanded by
FLC-1. The speed loop error and error change signals are converted to per-unit
signals, processed through fuzzy control, and then summed to generate the generator
torque component of the stator current. Note that, while the fuzzy controllers FLC-1
and FLC-2 operate in sequence at steady wind velocities, FLC-3 is always active
during system operation.
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SYSTKM PERFORMANCE
A 5 hp (3.735 kWe) wind generator system with the control approach of Figure
2 was simulated by computer modeling procedures [3] to validate all the control
strategies and then evaluate the performance of the system. The 5 hp (3.735 kWe)
system was used for the simulation studies because the results will be verified by a 5
hp (3.735 kWe) laboratory system. The model for the generator and converter system
contained conduction and switching losses with the respective vector controls. The
fuzzy controllers FLC-1, FLC-2, and FLC-3 were added in sequence and their
membership function and rule tables were iterated extensively until the performance
was optimized.
Figure 4 shows the performance of the control system as a function of time
when all the fuzzy controllers are in operation and the wind velocity is changed in the
fashion presented by the top curve. The ripple on the wind speed curve is the effects
of turbulence. The values for all the plotted variables are normalized or per unit (pu)
quantities. Conversion to actual units is achieved by multiplication by appropriate
scale factors. First, note that turbine speed (second curve), where the speed loop is
controlled by the fuzzy controller FLC-3, is insensitive to wind turbulence effects.
This means that FLC-3 provides robust speed control. The third curve contains the
magnetizing flux current. As indicated by the curve, FLC-2 is activated when steady-
state conditions are reached (little variation in turbine speed) and then the controller
decrements the current to enhance the output power (bottom curve). During periods
of change, the generator is operated at rated flux conditions, indicated by a per-unit
value of 1 for the flux current to achieve a fast transient response. The bottom curve
shows the output power response. As explained earlier, FLC-1 searches for the
optimum generator speed for a particular wind velocity to achieve maximum power
output. The sequence of the operation for FLC-1 and FLC-2 is also indicated on the
figure. FLC-3 continually operates.
Figure 5 shows the steady-state performance of the fuzzy-logic-based VSWT
compared to a single-speed wind turbine generator. The output power for each
turbine system is plotted as a function of wind velocity. It is apparent that significant
power gains are achieved by the fuzzy-logic-based VSWT for both slower and faster
wind speeds. Also observe the output power i>oost achieved by FLC-2. This gain
occurs primarily at slower wind speeds because the generator is operating at light flux
conditions.
CONCLUSIONS
A fuzzy-logic-based VSWT has been computer modeled. The control system
has been designed and analyzed extensively by numerical simulation, with some of
the results presented here. There arc three fuzzy logic controllers in the system. The
controller FLC-1 searches on-line for the optimum generator speed to optimize
aerodynamic efficiency of the wind turbine. A second fuzzy controller FLC-2
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programs the generator flux by an on-line search so as to optimize the
generator/converter system efficiency. A third fuzzy controller FLC-3 performs
robust speed control against turbine oscillatory torque and wind turbulence. This
fuzzy control approach has the advantages that it is parameter insensitive, provides
fast convergence, and accepts noisy and inaccurate signals. The fuzzy algorithms are
universal and can be applied retroactively in any system. System performance, both
in steady state and dynamic conditions, was found to be excellent.
REFERENCES
1.	Lamarre, L., "A Growth Market in Wind Power," EPRI Journal, pp. 4-15,
December, 1992.
2.	McGowan, J.G., "Tilting Towards Windmills," Technology Review, pp. 39-46,
July, 1993.
3.	Bose, B.K., et al., "Fuzzy Logic Based Intelligent Control of a Variable Speed
Gage Machine Wind Generation System," presented at the IEEE Power
Electronics Specialists Conference, Atlanta, GA, June 18-22,1995.
4.	Moretti, P.M., and Divone, L.V., "Modern Windmills," Scientific American, pp.
110-118, June, 1986.
5.	Sousa, G.C.D., et al., "Fuzzy Logic Based On-Line Efficiency Optimization
Control of an Indirect Vector Controlled Induction Motor Drive," IEEE
Industrial Electronics Conf. Rec. (IECON-93), pp. 1168-1174, November, 1993.
6.	Cleland, J., et al., "Fuzzy Logic Control of AC Induction Motors," Proc. of the
1992 IEEE International Conference on Fuzzv Systems," pp. 843-850, San Diego,
CA, March 1992.
7.	Bose, B.K., Power Electronics and AC Drives, Prentice Hall, 1986.
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FIGURE 1. A TYPICAL FAMILY OF TORQUE-SPEED CURVES
FOR A FIXED-PITCH WIND TURBINE
LOCUS OF MAXIMUiV
POWER DELIVERY
TURBINE TORQUE/SPEED
CURVES FOR INCREASING
WIND SPEED
TURBINE ROTATIONAL SPEED
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FIGURE 2. FUZZY-LOGIC-BASED ADAPTIVE CONTROL BLOCK
DIAGRAM FOR A WIND GENERATION SYSTEM
INDUCTION
GENERATOR v
q PWM
'p0 RECTIFIER
PWM
INVERTER
WIND
PWM
GENERATOR
VECTOR
ROTATOR
VECTOR
ROTATOR
'ds-oT
ids = flux current
iqS = torque current
•dso ~ rated flux current
ws = slip frequency
ADAPTIVE
CONTROLLER

P,-,
b2
0

SEARCH
FOR
P0max
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FIGURE 3. ILLUSTRATION OF FLC-1 AND FLC-2 OPERATION
SHOWING THE MAXIMIZING OF OUTPUT OR LINE POWER
AS THE WIND VELOCITY CHANGES
GENERATOR SPEED (cor)
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FIGURE 4. TIME DOMAIN OPERATION OF FLC-1 AND FLC-2:
(A) NORMALIZED WIND VELOCITY, (B) NORMALIZED GENERATOR SPEED,
(Q NORMALIZED FLUX CURRENT, AND (D) NORMALIZED OUTPUT POWER
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FIGURE 5. STEADY-STATE OUTPUT POWER OF THE
FUZ.ZY-1 .OGIC-R ASED VSWT COMPARED TO A SINGLE-SPEED
WIND TURBINE GENERATOR WITH A FIXED SPEED OF 1050 RPM
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