Year 2005 UCD— ITS— RR— 05— 10
A Multi- Country Analysis of Lifecycle Emissions from
Transportation Fuels and Motor Vehicles
Mark A. Delucchi
Institute of Transportation Studies ◊ University of California, Davis
One Shields Avenue ◊ Davis, California 95616
PHONE: ( 530) 752- 6548 ◊ FAX: ( 530) 752- 6572
WEB: http:// its. ucdavis. edu/
A MULTI- COUNTRY ANALYSIS OF LIFECYCLE EMISSIONS FROM
TRANSPORTATION FUELS and MOTOR VEHICLES
UCD- ITS- RR- 05- 10
For Nissan Motor Company
Mark A. Delucchi
madelucchi@ ucdavis. edu
www. its. ucdavis. edu/ people/ faculty/ delucchi/
Institute of Transportation Studies
One Shields Avenue
University of California
Davis, California 95616
May 30, 2005
TABLE OF CONTENTS
BACKGROUND AND OVERVIEW OF NISSAN- FUNDED RESEARCH .................................. 1
Background............................................................................................................ 1
Request for proposal from Nissan...................................................................... 1
Products of the Nissan- funded research ........................................................... 1
Overview of this final report ............................................................................... 2
INTRODUCTION TO THE FINAL REPORT............................................................................ 3
OVERVIEW OF THE LIFECYCLE EMISSIONS MODEL ( LEM) .............................................. 4
Introduction ........................................................................................................... 4
A general description of “ lifecycle” emissions analysis.................................. 4
Transportation lifecycles in the LEM ................................................................. 5
Fuel and feedstock combinations for motor vehicles ...................................... 6
Fuel, material, vehicle, and infrastructure lifecycles in the
LEM............................................................................................................... 7
Sources of emissions in LEM lifecycles.............................................................. 8
Pollutant tracked in the LEM .............................................................................. 9
Material commodities in the LEM .................................................................... 10
INPUTS AND OUTPUTS OF THE LEM............................................................................... 11
Major inputs to the LEM: projections of energy use and
emissions.................................................................................................... 11
Overview of major outputs of the LEM........................................................... 11
Emissions per mile from the use of conventional and
alternative transportation fuels for motor vehicles ............................. 13
Emissions per energy unit from the use of electricity, and
from end- use heating ............................................................................... 13
Results by emissions sector or stage of lifecycle ............................................ 13
Analysis of emissions from complete transportation
scenarios..................................................................................................... 15
ANALYSIS OF EMISSIONS FOR COUNTRIES OTHER THAN THE U. S............................... 16
Background.......................................................................................................... 16
Data specific to “ consuming” countries .......................................................... 17
Representation of producing countries ........................................................... 20
COMPARISON OF THE LEM WITH OTHER RECENT LC MODELING
EFFORTS...................................................................................................................... 22
METHODS AND ANALYTICAL ISSUES IN LCA................................................................. 28
General method of estimation of lifecycle- CO 2 emissions
from transportation systems in the LEM .............................................. 28
Overview of basic analytical issues in LCA .................................................... 31
Issues concerning the detail, scope, and structure of the LEM .................... 29
Focus on the question of dynamic versus fixed I- O ratios............................ 32
Applicability of International Organization for
Standardization ( ISO) 14040 standards ................................................. 33
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DISCUSSION OF RESULTS FROM THE LEM........................................................................ 35
Energy efficiency and emissions of vehicles. .................................................. 35
Energy intensity of fuel cycles and kinds of process fuel used.................... 36
Leaks of methane and CO2................................................................................ 36
Leaks of hydrogen............................................................................................... 37
Electricity generation: efficiency and mix of fuels, ........................................ 37
Grams emitted per 106 BTU of fuel delivered to end users,
by stage and feedstock/ fuel combination............................................. 38
Upstream fuel cycle and material lifecycle emissions
expressed relative to end- use emissions. .............................................. 38
Gram- per- mile emissions by vehicle/ fuel/ feedstock
combination, and stage of the fuel cycle. .............................................. 39
Comparison of results with IPCC GWPs versus with CEFs
estimated here ........................................................................................... 39
Comparison of results using IPCC methods for estimating
emissions from land- use changes with results using
our methods............................................................................................... 43
Uncertainty in important parameter values.................................................... 43
REFERENCES..................................................................................................................... 45
TABLE Y- 10B. CALCULATED VEHICLE WEIGHT OF FUEL, FUEL STORAGE, AND ICE
VEHICLES ( U. S. 2010).............................................................................................. 49
TABLE Y- 11. CALCULATED VEHICLE ENERGY USE ( U. S. 2010).............................................. 51
TABLE Y- 12A. CALCULATED EMISSIONS FROM LIGHT- DUTY ICEVS ( G/ MI, EXCEPT
AS NOTED) ( BEST CEFS) ( U. S. 2010) ...................................................................... 54
TABLE Y- 13A. ENERGY INTENSITY: BTUS OF PROCESS ENERGY CONSUMED PER
NET BTU OF FUEL TO END USERS ( U. S. 2010)....................................................... 57
TABLE Y- 13B. ENERGY CONSUPMTION OF FUELCYCLES: BTUS OF PROCESS
ENERGY CONSUMED PER MILE OF TRAVEL BY VEHICLES ( U. S. 2010) ................. 60
TABLE Y- 15A. LEM- CALCULATED EFFICIENCY OF ELECTRICITY GENERATION, BY
FUEL TYPE................................................................................................................. 62
TABLE Y- 15B. SOURCE OF ELECTRICITY, BY TYPE OF GENERATING PLANT, FOR
GENERIC POWER ...................................................................................................... 66
TABLE Y- 16A. CO2- EQUIVALENT EMISSIONS PER UNIT OF ENERGY DELIVERED TO
END USERS, BY STAGE AND FEEDSTOCK/ FUEL COMBINATION ( G/ 106-
BTU): U. S. 2010 AND 2050..................................................................................... 70
TABLE Y- 16B. CO2- EQUIVALENT EMISSIONS PER UNIT OF ENERGY DELIVERED TO
END USERS, BY STAGE AND FEEDSTOCK/ FUEL COMBINATION ( G/ 106-
BTU): JAPAN 2010 AND 2050 ................................................................................. 76
TABLE Y- 16C. CO2- EQUIVALENT EMISSIONS PER UNIT OF ENERGY DELIVERED TO
END USERS, BY STAGE AND FEEDSTOCK/ FUEL COMBINATION ( G/ 106-
BTU): CHINA 2010 AND 2050................................................................................. 82
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TABLE Y- 16D. CO2- EQUIVALENT EMISSIONS PER UNIT OF ENERGY DELIVERED TO
END USERS, BY STAGE AND FEEDSTOCK/ FUEL COMBINATION ( G/ 106-
BTU): GERMANY 2010 AND 2050........................................................................... 88
TABLE Y- 18. TOTAL EMISSIONS OVER THE WHOLE UPSTREAM FUELCYCLE, PER UNIT
OF ENERGY DELIVERED TO END USERS, BY POLLUTANT AND
FEEDSTOCK/ FUEL COMBINATION ( G/ 106- BTU) ( BEST CEFS) ( U. S.
2010) ......................................................................................................................... 96
TABLE Y- 19A. GRAM- PER- MILE EMISSIONS BY VEHICLE/ FUEL/ FEEDSTOCK
COMBINATION, AND STAGE OF THE FUELCYCLE ( BEST CEFS): U. S.
2010 AND 2050......................................................................................................... 99
TABLE Y- 19B. GRAM- PER- MILE EMISSIONS BY VEHICLE/ FUEL/ FEEDSTOCK
COMBINATION, AND STAGE OF THE FUELCYCLE ( BEST CEFS): JAPAN
2010 AND 2050....................................................................................................... 111
TABLE Y- 19C. GRAM- PER- MILE EMISSIONS BY VEHICLE/ FUEL/ FEEDSTOCK
COMBINATION, AND STAGE OF THE FUELCYCLE ( BEST CEFS): CHINA
2010 AND 2050....................................................................................................... 125
TABLE Y- 19D. GRAM- PER- MILE EMISSIONS BY VEHICLE/ FUEL/ FEEDSTOCK
COMBINATION, AND STAGE OF THE FUELCYCLE ( BEST CEFS):
GERMANY 2010 AND 2050.................................................................................... 139
TABLE Y- 25. UPSTREAM FUELCYCLE EMISSIONS AS A PERCENTAGE OFF END- USE
EMISSIONS, BY POLLUTANT AND FEEDSTOCK/ FUEL COMBINATION
( BEST CEFS) ( U. S. 2010) ....................................................................................... 156
TABLE Y- 27. CO 2 - EQUIVALENT EMISSIONS FROM THE LIFEYCLE OF VEHICLE
MATERIALS AND VEHICLE ASSEMBLY ( G/ LB) ( BEST CEFS) ( U. S. 2010)............ 159
TABLE Y- 28. COMPARISON OF LIFECYCLE EMISSIONS WITH LEM CEFS VS. IPCC
GWPS ..................................................................................................................... 161
A. UNITED STATES, YEAR 2010............................................................................. 161
B. JAPAN, YEAR 2010. ............................................................................................ 163
C. CHINA, YEAR 2010............................................................................................ 164
D. GERMANY, YEAR 2010...................................................................................... 165
APPENDIX A: PATHWAY DIAGRAMS .............................................................................. 166
APPENDIX B: DATA FOR JAPAN, CHINA, AND GERMANY....................................... 167
PARAMETER VALUES ...................................................................................................... 168
General................................................................................................................ 168
Motor vehicle fuel use ...................................................................................... 169
Motor vehicle exhaust emissions: light- duty gasoline
vehicles..................................................................................................... 169
Motor vehicle exhaust emissions: heavy- duty diesel vehicles................... 170
Exhaust missions from alternative- fuel vehicles.......................................... 171
Emissions related to the use of lubricating oil by motor
vehicles..................................................................................................... 171
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Emissions of particulate matter from road dust, brake wear,
and tire wear............................................................................................ 171
Motor vehicles ( lifetime to scrappage)........................................................... 172
Upstream liquid- fuel evaporative emissions................................................ 172
Electricity generation and distribution efficiency ........................................ 172
Electricity generation fuel mix ........................................................................ 174
Electricity trade ................................................................................................. 175
Electricity generation emissions ..................................................................... 175
Diesel fuel sulfur content ................................................................................. 177
Other petroleum fuel sulfur content .............................................................. 177
Coal sulfur content............................................................................................ 178
Flows of materials: general.............................................................................. 178
Sources of materials embedded in motor vehicles....................................... 179
Petroleum production and trade .................................................................... 179
Coal production and trade............................................................................... 180
Natural gas production and trade .................................................................. 181
Natural gas losses in distribution ................................................................... 182
Flows of motor vehicles ................................................................................... 182
The nuclear fuelcycle........................................................................................ 184
Crop production and fertilizer use................................................................. 186
Corn- ethanol production ................................................................................. 188
Nitrogen deposition.......................................................................................... 188
REFERENCES.................................................................................................................... 190
Multi- country ( regional or global).................................................................. 190
China................................................................................................................... 196
Germany............................................................................................................. 198
Japan 198
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BACKGROUND AND OVERVIEW OF NISSAN- FUNDED RESEARCH
Background
The task of developing and evaluating strategies to reduce emissions of urban air
pollutants and greenhouse gases is complicated. There are many ways to produce and
use energy, many sources of emissions in an energy lifecycle, and several kinds of
pollutants ( or greenhouse gases) emitted at each source. An evaluation of strategies to
reduce emissions of greenhouse gases must be broad, detailed, and systematic. It must
encompass the full “ lifecycle” of a particular technology or policy, and include all of the
relevant pollutants and their effects. Towards this end, Dr. Mark A. Delucchi of the
Institute of Transportation Studies at the University of California, Davis ( ITS- Davis) has
developed a detailed, comprehensive model of lifecycle emissions of urban air
pollutants and greenhouse gases from the use of variety of transportation modes. The
model is called the Lifecycle Emissions Model, or LEM.
The LEM estimates energy use, criteria pollutant emissions, and CO 2 - equivalent
greenhouse- gas emissions from a variety of transportation and energy lifecycles. It
includes a wide range of modes of passenger and freight transport, electricity
generation, heating, and more. For transport modes, it represents the lifecycle of fuels,
vehicles, materials, and infrastructure. It calculates energy use and all regulated air
pollutants plus so- called greenhouse gases. It includes input data for up to 30 countries,
for the years 1970 to 2050, and is fully specified for the United States. Full
documentation of the LEM is provided in a main report and several appendices,
available at Dr. Delucchi’s website, www. its. ucdavis. edu/ people/ faculty/ delucchi/.
Request for proposal from Nissan
Nissan Motor Company is interested in the lifecycle environmental impacts of
motor vehicles and motor fuels. Towards this end, Nissan has funded ITS- Davis to
further develop and apply the LEM to analyze lifecycle environmental impacts of motor
vehicles and motor fuels. Nissan is especially interested in the longer- term options, such
as hydrogen, and on impacts in countries around the world.
Products of the Nissan- funded research
With Nissan funding ( and co- funding from other sources) ITS- Davis has
completed several major projects and deliverables:
• Major updates and revisions to the LEM. The most significant of these
revisions pertain to CO 2 - equivalency factors, cultivation and land use related to
biofuels, and the lifecycle of materials. The work on CO 2 - equivalency factors is
documented in a revised Appendix D to the LEM main report, the work on the lifecycle
of materials is documented in a revised Appendix H to the LEM main report, and the
work on cultivation and land use is documented in the revised LEM main report and in
a revised Appendix C to the LEM main report. Other recently completed updates and
revisions to the LEM include changes in the presentation of results, changes in macros
that generate key tables, and changes in formatting and layout.
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• Expansion of the LEM to include new pathways. Under this project the LEM
has been expanded to include the complete fuel lifecycle for hydrogen derived from
biomass and hydrogen derived from coal with CO 2 sequestration. These major
expansions are fully incorporated in the revised LEM and are documented in the LEM
main report and in a new Appendix K to the LEM main report.
• Delivery of the LEM to Nissan and provision of technical support to Nissan
staff. At the beginning of this project Nissan was given a copy of the LEM and two days
of intensive training in its use by Dr. Delucchi. With this final report the latest revised
version of the LEM is being delivered to Nissan. Further technical support may be
provided to Nissan staff in the near future.
• New sections in the LEM documentation. Four major new sections providing
general background and methodological overview have been added to the LEM main
report. These are: i) an extensive formal documentation of the general structure of the
LEM; ii) a discussion of analytical and methodological issues in lifecycle analysis; iii) a
review of the substance and applicability of ISO 14040 standards pertaining to LCA;
and iv) the creation of detailed pathways diagrams. All four of these major new sections
are available in the revised LEM main report and also are included in this final report
( see body of final report, below and Appendix A to this report).
• Model runs and final report for Nissan. In addition to the foregoing, ITS- Davis
is providing this final report which provides an overview of the LEM, pathways
diagrams ( Appendix A to this report), presentation of some of the important input
parameters ( Appendix B to this report), extensive tables of results of runs from the
most recent version of the LEM, and a discussion of the results and important
parameters.
Overview of this final report
General. This report provide an overview of basic assumptions and general
results for all of the fuel, feedstock, and light- duty vehicle combinations treated in the
LEM, and somewhat more detailed results and discussions for the longer- term
advanced options, including compressed or liquefied hydrogen from natural gas,
compressed or liquefied hydrogen from water via electrolysis, and liquid biofuels
developed from wood, grass, or corn. It considers fuel- cell electric vehicles ( FCVs) as
well as internal- combustion engine vehicles ( ICEVs).
Target years. The LEM has the capability of modeling lifecycle environmental
impacts in any target year from 1970 to 2050. For this analysis we have estimated results
for the near term ( 2010) and the long term ( 2050). ( We originally proposed to run the
LEM for three dates, 2005, 2020, and 2050, but for three reasons have modeled 2010 and
2050 instead: there is not enough difference between 2005 and 2020 to warrant separate
runs; having three target years instead of two increases the already large number of
results tables by 50%; and Nissan has the LEM and hence the capability to run any year
it is interested in.)
Countries. The LEM also has the capability of modeling lifecycle environmental
impacts in up to 30 countries simultaneously. For this project, we have performed
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lifecycle analysis for Japan, China, the U. S., and Germany, using existing data in the
LEM. ( We originally proposed to run the LEM for Poland, Italy, and the U. K. as well,
but for several reasons we omitted them: the data for these countries are not as good as
the data for China, Japan, and the U. S.; presenting results for three more countries
would greatly multiply the already- large number of results tables; and Nissan has the
LEM and hence the capability to run any country it is interested in.)
Results reported. The LEM produces a wide range of quantitative outputs related
to lifecycle emissions from the use of alternative transportation fuels and modes. For
this report we provide estimates of lifecycle CO 2 - equivalent GHG emissions in grams
per mile, by stage of lifecycle and fuel/ feedstock/ vehicle combination; emissions of
pollutants from the “ upstream” fuel cycle ( i. e., all stages of the fuel lifecycle excluding
end use) in grams per million BTU of fuel, by individual pollutant including CO 2 -
equivalent and fuel/ feedstock combination; and emissions of pollutants from the
vehicle and materials lifecycle, in grams per pound of material, by individual pollutant
( including CO 2 - equivalent) and vehicle type.
We discuss the key assumptions of the analysis and their impacts on the results.
We pay particular attention to inputs and outputs that determine or reveal differences
among countries, including kinds and sources of feedstocks for various fuel production
pathways, differences in technologies, and differences in emissions regulations and fuel
properties.
INTRODUCTION TO THE FINAL REPORT
Highway vehicles are a major source of urban air pollutants and so- called
“ greenhouse gases”. In most cities throughout the world, light- duty gasoline vehicles
are major sources of volatile organic compounds ( VOCs), nitrogen oxides ( NOx), and
toxic air pollutants, and often single largest source of carbon monoxide ( CO). Heavy-duty
diesel vehicles can be significant source of NOx, sulfur oxides ( SOx), and
particulate matter ( PM).
These air- pollutant emissions from highway vehicles lead to serious air quality
problems. Most urban areas routinely violate national ambient air quality standards
and international air- quality guidelines promulgated by the World Health Organization
( WHO), especially for ambient ozone and PM. Clinical and epidemiological studies
have associated ambient levels of PM, O3, and other pollutants with human morbidity
and mortality ( U. S. EPA, 1996a, 1996b; McCubbin and Delucchi, 1999; Rabl and
Spadaro, 2000). In response to these apparently serious health effects, national and
international regulatory agencies throughout the world have promulgated stringent air-quality
and emissions standards.
Motor vehicles also are a major source of carbon dioxide ( CO2), the most
significant of the anthropogenic pollutants that can affect global climate. In the U. S., the
highway- fuel lifecycle contributes about 30% of all CO2 emitted from the use of fossil
fuels ( DeLuchi, 1991). In the OECD ( Organization for Economic Cooperation and
3
Development), the highway- fuel lifecycle contributes about one- quarter of all CO2
emitted from the use of fossil fuels ( DeLuchi, 1991; emissions in Europe are below the
OECD- wide average, and emissions in the U. S. above). Worldwide, the highway fuel-lifecycle
contributes about 20% of total CO2 emissions from the use of fossil fuels – a
lower percentage than in the OECD because outside the OECD relatively few people
own and drive cars.
Many scientists now believe that an increase in the concentration of CO2 and
other “ greenhouse” gases, such as methane and nitrous oxide, will increase the mean
global temperature of the earth. In 1995, an international team of scientists, working as
the Intergovernmental Panel on Climate Change ( IPCC), concluded that “ the balance of
evidence suggests that there is a discernible human influence on global climate” ( IPCC,
1996a, p. 5). According to the IPCC, in the long run this global climate change might
affect agriculture, coastal developments, urban infrastructure, human health, and other
aspects of life on earth ( IPCC, 1996b). The most recent IPCC reports ( IPCC, 2001a,
2001b) have confirmed and expanded upon these findings.
OVERVIEW OF THE LIFECYCLE EMISSIONS MODEL ( LEM)
Introduction
Given the continuing problem of urban air pollution, the growing consensus that
emissions of greenhouse gases will affect global climate, and the expanding role of
transportation in environmental problems, it is useful to have a tool that can evaluate
strategies to reduce emissions of urban air pollutants and greenhouse gases. However,
the task of developing and evaluating such strategies is complicated. There are many
ways to produce and use energy, many sources of emissions in an energy or materials
lifecycle, and several kinds of pollutants emitted at each source. An evaluation of
strategies to reduce emissions of greenhouse gases must be broad, detailed, and
systematic. It must encompass the full “ lifecycle” of a particular technology or policy,
and include all of the relevant pollutants and their effects. Towards this end, Dr.
Delucchi has developed a detailed, comprehensive model of lifecycle emissions of
urban air pollutants and greenhouse gases from the use of variety of transportation
modes.
A general description of “ lifecycle” emissions analysis
The distinguishing feature of a “ lifecycle” emissions analysis is that it estimates
emissions associated with the entire “ lifecycle” of a particular product, as opposed to
emissions from just consumer end use. A “ lifecycle” comprises all of the physical and
economic processes involved directly or indirectly in the “ life” of the product, from the
recovery of raw materials used to make pieces of the product to recycling of the used
product at the end of its life. A lifecycle analysis ( LCA) of emissions formally
characterizes the inputs, outputs, and emissions for each stage of the lifecycle, links the
4
stages together, and aggregates the emission results over all of the linked stages. In
essence, LCAs are input- output ( I- O) analyses with emissions factors.
The basic building block in LCA is a set of energy and material inputs associated
with a particular output of interest for a particular stage in a lifecycle, with emission
factors attached to some of the inputs. A “ lifecycle” is then a particular combination of
I- O building blocks ( or stages) linked together, where the output of one block ( or stage)
is one of the inputs to another stage, and the output of the last stage is the product or
quantity of interest. A “ lifecycle analysis” aggregates the emissions attached to the
inputs over all of the linked stages, to produce an estimate of total emissions per unit of
final product output from the lifecycle.
Consider, for example, this simplified depiction of the lifecycle of gasoline: crude
oil recovery, petroleum refining, and gasoline end use. In the first stage, fuels and
materials are input to the crude- oil recovery process, which results in an output of
crude oil. This crude oil output is input to the next stage, petroleum refining. ( The
petroleum refining stage also has other energy and material inputs.) The output of the
petroleum refining stage is gasoline, which is input to the last stage, end use. At each
stage, emissions are associated with the use of various inputs. Adding up the emissions
associated with all of the inputs for crude oil recovery, petroleum refining, and gasoline
end use gives us a picture of the “ lifecycle” emissions impact of gasoline. Appendix A
provides diagrammatic representations of several “ pathways” in the LEM.
The Lifecycle Emissions Model ( LEM) described here uses LCA to estimate
energy use, criteria air- pollutant emissions, and CO 2 - equivalent greenhouse- gas
emissions from a wide range of energy and material lifecycles. It includes lifecycles for
passenger transport modes, freight transport modes, electricity, materials, heating and
cooling, and more. For transport modes, it represents the lifecycle of fuels, vehicles,
materials, and infrastructure. It calculates energy use and lifecycle emissions of all
regulated air pollutants plus so- called greenhouse gases. It includes input data for up to
30 countries, for the years 1970 to 2050, and is fully specified for the U. S.
The following sections give further details on the general structure of the LEM.
For full documentation, see the series of reports available on the author’s faculty web
page ( Delucchi, 2003).
Transportation lifecycles in the LEM
The LEM calculates lifecycle emissions for the following passenger transportation
modes:
• light- duty passenger cars ( internal- combustion engine vehicles [ ICEVs])
operating on a range of fuel types [ see below]; battery- powered
electric vehicles [ BPEVs]; and fuel- cell electric vehicles, with or without
an auxiliary peak- power unit [ FCVs];
• full- size buses ( ICEVs and FCVs)
5
• mini- buses ( albeit modeled crudely)
• mini- cars ( ICEVs and BPEVs)
• motor scooters ( ICEVs and BPEVs)
• bicycles
• heavy- rail transit ( e. g., subways)
• light- rail transit ( e. g., trolleys)
The LEM also calculates lifecycle emissions for the following freight transport modes:
• medium and heavy- duty trucks
• diesel trains
• tankers, cargo ships, and barges
• pipelines
Fuel and feedstock combinations for motor vehicles
For motor vehicles, the LEM calculates lifecycle emissions for a variety of
combinations of end- use fuel ( e. g., methanol), fuel feedstocks ( e. g., coal), and vehicle
types ( e. g., fuel- cell vehicle). For light- duty vehicles, the fuel and feedstock
combinations included in the LEM are:
6
Fuel -->
↓ Feedstock
Gasoline Diesel Methanol Ethanol Methane
( CNG, LNG)
Propane
( LPG)
Hydrogen
( CH2) ( LH2)
Electric
Petroleum ICEV,
FCV
ICEV ICEV BPEV
Coal ICEV ICEV ICEV,
FCV
FCV BPEV
Natural gas ICEV ICEV,
FCV
ICEV ICEV ICEV,
FCV
BPEV
Wood or grass ICEV,
FCV
ICEV,
FCV
ICEV FCV BPEV
Soybeans ICEV
Corn ICEV
Solar power ICEV,
FCV
BPEV
Nuclear power ICEV,
FCV
BPEV
The LEM has similar but fewer combinations for heavy- duty vehicles ( HDVs),
mini- cars, and motor scooters.
Fuel, material, vehicle, and infrastructure lifecycles in the LEM
The LEM estimates the use of energy, and emissions of greenhouse gases and
urban air pollutants, for the complete lifecycle of fuels, materials, vehicles, and
infrastructure for the transportation modes listed above. These lifecycles are
constructed as follows:
Lifecycle of fuels and electricity:
• end use: the use of a finished fuel product, such as gasoline, electricity,
or heating oil, by consumers.
• dispensing of fuels: pumping of liquid fuels, and compression or
liquefaction of gaseous transportation fuels.
• fuel distribution and storage: the transport of a finished fuel product to
end users and the operation of bulk- service facilities. For example, the
shipment of gasoline by truck to a service station.
• fuel production: the transformation of a primary resource, such as
crude oil or coal, to a finished fuel product or energy carrier, such as
gasoline or electricity. A detailed model of emissions and energy use at
petroleum refineries is included.
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• feedstock transport: the transport of a primary resource to a fuel
production facility. For example, the transport of crude oil from the
wellhead to a petroleum refinery. A complete country- by- country
accounting of imports of crude oil and petroleum products by country
is included in the LEM.
• feedstock production: the production of a primary resource, such as
crude oil, coal, or biomass. Based on primary survey data at energy-mining
and recovery operations, or survey or estimated data for
agricultural operations.
Lifecycle of materials:
• crude- ore recovery and finished- material manufacture: the recovery
and transport of crude ores used to make finished materials and the
manufacture of finished materials from raw materials ( includes
separate characterization of non- energy- related process- area
emissions).
• the transport of finished materials to end users.
Lifecycle of vehicles:
• materials use: see the “ lifecycle of materials”.
• vehicle assembly: assembly and transport of vehicles, trains, etc.
• operation and maintenance: energy use and emissions associated with
motor- vehicle service stations and parts shops, transit stations, and so
on;
• secondary fuel cycle for transport modes: building, servicing, and
providing administrative support for transport and distribution modes
such as large crude- carrying tankers or unit coal trains.
Lifecycle of infrastructure:
• energy use and materials production: the manufacture and transport of
raw and finished materials used in the construction of highways,
railways, etc., as well as energy use and emissions associated with the
construction of the transportation infrastructure. ( Presently these are
represented crudely; future versions of the LEM will have a more
detailed treatment of the infrastructure lifecycle.)
Sources of emissions in LEM lifecycles
8
The LEM characterizes greenhouse gases and criteria pollutants from a variety of
emission sources:
• Combustion of fuels that provide process energy ( for example, the
burning of bunker fuel in the boiler of a super- tanker, or the
combustion of refinery gas in a petroleum refinery);
• Evaporation or leakage of energy feedstocks and finished fuels ( for
example, from the evaporation of hydrocarbons from gasoline storage
terminals);
• Venting, leaking, or flaring of gas mixtures that contain greenhouse
gases ( for example, the venting of coal bed gas from coal mines);
• Fugitive dust emissions ( for example, emissions of re- entrained road
dust from vehicles driving on paved roads);
• Chemical transformations that are not associated with burning process
fuels ( for example, the curing of cement, which produces CO2, or the
denitrification of nitrogenous fertilizers, which produces N2O, or the
scrubbing of sulfur oxides ( SOx) from the flue gas of coal- fired power
plants, which can produce CO2);
• Changes in the carbon content of soils or biomass, or emissions of non-
CO2 greenhouse from soils, due to changes in land use.
Pollutant tracked in the LEM
The LEM estimates emissions of the following pollutants:
• carbon dioxide ( CO2) • total particulate matter ( PM)
• methane ( CH4) • particulate matter less than 10 microns
diameter ( PM10), from combustion
• nitrous oxide ( N2O) • particulate matter less than 10 microns
diameter ( PM10), from dust
• carbon monoxide ( CO) • hydrogen ( H 2 )
• nitrogen oxides ( NOx) • chlorofluorocarbons ( CFC- 12)
• nonmethane organic compounds
( NMOCs), weighted by their ozone-forming
potential
• hydrofluorocarbons ( HFC- 134a)
9
• sulfur dioxide ( SO2) • the CO 2 - equivalent of all of the
pollutants above
Ozone ( O3) is not included in this list because it is not emitted directly from any
source in a fuel cycle, but rather is formed as a result of a complex series of chemical
reactions involving CO, NOx, and NMOCs.
The LEM estimates emissions of each pollutant individually, and also converts
all of the pollutant into CO2- equivalent greenhouse- gas emissions. To calculate total
CO2- equivalent emissions, the model uses CO2- equivalency factors ( CEFs) that convert
mass emissions of all of the non- CO2 gases into the mass amount of CO2 with an
equivalent effect on global climate. These CEFs are conceptually related, broadly, to the
“ Global Warming Potentials” ( GWPs) used by the Intergovernmental Panel on Climate
Change ( IPCC). The CEFs are discussed in Appendix D of Delucchi ( 2003).
Material commodities in the LEM
Finally, the LEM includes the lifecycle of the following materials:
• plain carbon steel • zinc die castings
• high strength steel • powdered metal
components
• stainless steel • other materials ( lead)
• recycled steel • sodium
• iron • sulfur
• advanced composites • titanium
• other plastics • sulfuric acid
• fluids and lubricants • potassium hydroxide
• rubber • nickel and compounds
• virgin aluminum • lithium
• recycled aluminum • cement
• glass • concrete
• copper • limestone
10
• agricultural chemicals
( mainly fertilizers)
Note that recycled steel and recycled aluminum are treated as separate materials
from virgin steel and virgin aluminum. In this way, the full lifecycle of materials,
including recycling, is explicitly represented. Appendix H of Delucchi ( 2003) documents
the methods and data used in to model the lifecycle of materials.
INPUTS AND OUTPUTS OF THE LEM
Major inputs to the LEM: projections of energy use and emissions
The LEM projects energy use and emissions, or changes in energy use and
emissions, for the period 1970 to 2050. The user specifies any target year between 1970
and 2050, and the LEM looks up or calculates energy- use intensities, emission factors, or
other data for the specified year.
There are several kinds of projections in the LEM:
• look- up tables ( usually based on energy- use or emissions projections from the
EIA);
• constant percentage changes per year;
• logistic functions with upper or lower limits; and
• logistic functions with upper and lower limits.
The functional forms of these projections are discussed in more detail in the Main
Report of the model documentation ( Delucchi, 2003).
Overview of major outputs of the LEM
The LEM produces the following tables of results, some of which are discussed in
more detail the following sections:
• Emissions per mile from motor vehicles: CO2- equivalent emissions ( in
g/ mi) by stage of fuel cycle and for the vehicle lifecycle, for all of the
feedstock/ fuel/ vehicle combinations represented in the LEM.
• Emissions from electricity use: CO 2 - equivalent emissions ( in g/ kWh-delivered)
for different sources of electricity generation.
• Emissions from use of heating fuels: CO 2 - equivalent emissions ( in
g/ 106- BTU- heat- delivered) for natural gas, LPG, electricity, and fuel oil.
• Summary of percent change in lifecycle g/ mi emissions from
alternative- fuel vehicles, relative to conventional gasoline LDVs or
diesel HDVs.
11
• BTUs of process and end- use energy per mile of travel by stage of
lifecycle, for different feedstock/ fuel/ vehicle combinations.
• Breakdown of energy use by type of energy ( e. g., diesel fuel, natural
gas, propane), stage of lifecycle, and feedstock/ fuel combination.
• Vehicle characteristics: input data and results regarding vehicle weight
and energy use.
• Emissions from EVs, by region: a macro runs the model for regional
data for EV recharging and prints the g/ mi results for up to six
different regions.
• Emissions by IPCC sector: The g/ mi results for vehicles are mapped
into the IPCC sectors used in GHG accounting ( e. g., “ energy/ road
transport,” “ energy/ industry,” “ land- use/ forestry”).
• Emissions by geographic sector: The g/ mi results for vehicles are
mapped into a geographic framework that distinguishes in- country
from outside- of- country emissions.
• Emissions by individual pollutant: one set of tables reports emissions
of each individual pollutant ( not weighted by CO 2 - equivalency factors)
for each stage of the upstream fuel cycle for each feedstock/ fuel.
Another table does the same for vehicle manufacture and assembly.
• CO 2 - equivalent emissions by pollutant: a tabular summary of the
contribution of each pollutant to upstream fuel cycle CO 2 - equivalent
emissions.
• Emissions from complete transportation scenarios: a table of results
that shows g/ passenger- mi emissions from a user- specified mix of
travel by conventional motor vehicles, alternative- fuel vehicles
( including electric vehicles), mini- cars, scooters, buses, trolleys,
subways, bicycles, and walking.
• Emissions from other countries: the LEM can be programmed to
calculate all results for the characteristics of any of up to 30 different
countries. Separate data files exist within the LEM for each of the
countries.
In the following sections we discusses the major outputs of the LEM in more
detail.
12
Emissions per mile from the use of conventional and alternative transportation fuels
for motor vehicles
The LEM estimates CO2- equivalent emissions per mile for the motor- vehicle
transportation fuel and feedstock combinations shown above. For baseline petroleum
fuels ( gasoline and diesel fuel), the results are reported as grams of individual gases or
CO2- equivalent emissions from each stage of the lifecycle of fuels. The lifecycle of fuels
also include the manufacture and assembly of materials for vehicles, per mile of travel
by the vehicle. For the alternative fuel vehicles, the results are reported in grams/ mile
as for gasoline and diesel vehicles, and also as a percentage change relative to the
petroleum- fuel gram- per- mile baseline.
Emissions per energy unit from the use of electricity, and from end- use heating
The LEM calculates grams of individual gases and grams of CO2- equivalent
emission from the entire fuel cycle, per kWh of electricity delivered to end users. It
analyzes coal, residual fuel oil, natural gas, methanol, nuclear, and hydro power plants,
individually or in any combination. The analysis covers emissions from all stages of the
fuel cycle, from feedstock recovery to scrubbing sulfur from flue gas to transmitting
power via high- voltage lines, which can produce N2O. The estimates of emissions of
NOx and SOx account for the phase- in and effectiveness of emission controls. The
gram/ kWh emissions can be estimated for any power- plant efficiency, fuel mix,
emission- control scenario, and time horizon.
The LEM also estimates lifecycle emissions from the use of NG, LPG, fuel oil,
and electricity for space heating and water heating, in grams CO2- equivalent emissions
per 106 BTU of heat delivered.
Results by emissions sector or stage of lifecycle
The LEM organizes lifecycle emissions in several ways. First, it presents
emissions by stage of the lifecycle:
• vehicle operation ( fuel)
• fuel dispensing
• fuel storage and distribution
• fuel production
• feedstock transport
• feedstock and fertilizer production
• CH4 and CO2 gas leaks and flares
• emissions displaced by coproducts
• vehicle assembly and transport
• materials in vehicles
• lube oil production and use
• refrigerant ( HFC- 134a) use
13
Second, the LEM maps the results calculated by “ stage” of the lifecycle ( e. g.,
petroleum refining) into the emissions sectors used in the IPCC greenhouse- gas emissions-accounting
frameworks. In the following table, the IPCC sectors are underlined, and the
LEM stages that are mapped into each IPCC sector are in italics below the pertinent
IPCC sector:
IPCC energy/ road transport: fuels
LEM: Vehicle operation, fuel Note: This mapping includes credits for plant
uptake of CO2. Changes in soil and plant
carbon are in " Land-use/
forestry/ agriculture".
IPCC energy/ industry: fuels
LEM: Fuel dispensing
LEM: Fuel storage and distribution
LEM: Fuel production
LEM: Feedstock transport
LEM: Feedstock, fertilizer production
LEM: CH4 and CO2 gas leaks, flares Note: related to fuel production and use.
IPCC energy/ industry: materials, vehicles
LEM: Vehicle assembly and transport
LEM: Materials in vehicles
LEM: Lube oil production and use
LEM: Refrigerant ( HFC- 134a)
IPCC land- use/ forestry/ agriculture
LEM: Land use changes, cultivation Note: this does not include any energy- related
emissions ( e. g., from fuel use by tractors).
Not mapped to IPCC sectors:
LEM: Emissions displaced by coproducts
LEM: Road dust, brake dust, tirewear PM
14
Third, the LEM maps the CO2- equivalent emission results into six geographic
sectors:
• the energy/ road transport sector of the designated consuming country
( the country selected for analysis; e. g., the U. S.);
• the energy/ industry sector of the designated consuming country;
• the energy/ industry sector of a selected major exporter ( e. g., Canada) to
the designated consuming country;
• the energy/ industry sector of a second major exporter;
• international transport; and
• the rest of the world.
This mapping reveals how policies in one country affect emissions in other
countries. International transport is a separate source because in the IPCC accounting it
is not assigned to any country.
The mapping into geographic sectors is based on part on the LEM’s
representation of trade between major producing countries and designated consuming
and target countries. Trade between countries is discussed in the section “ Analysis of
emissions from countries other than the U. S.”
Analysis of emissions from complete transportation scenarios
The LEM estimates total average emissions per passenger- mile and per freight
ton- mile from a complete transportation scenario. A complete transportation scenario
includes passenger transport and freight transport by all possible modes, where the
modal shares and other characteristics of the modes are specified by the user.
The passenger travel modes that can be characterized in a transportation scenario
are:
• conventional motor vehicles,
• alternative- fuel vehicles ( including electric battery and fuel- cell vehicles)
• mini- cars ( conventional and alternative- fuel)
• scooters
• buses ( conventional and alternative- fuel)
• trolleys
• subways
• bicycles and walking
15
The freight modes that can be characterized in a complete transportation scenario
are:
• heavy- duty and medium– duty trucks ( conventional and alternative- fuel)
• rail
• cargo ship, tanker, and barge
• pipeline
To create a scenario, the user specifies the distribution of passenger miles of
travel over all passenger transport modes and the distribution of freight ton- miles of
travel over all freight transport modes. The user also specifies the passenger occupancy
and in some cases the energy- use efficiency of each mode. With these data, the LEM
calculates average CO 2 - equivalent lifecycle emissions per passenger mile and freight
ton- mile for the scenario.
ANALYSIS OF EMISSIONS FOR COUNTRIES OTHER THAN THE U. S.
Background
The LEM originally was constructed and specified for the U. S. only. Starting in
the late 1990s it was extensively revised to be able to estimate lifecycle emissions from
the use of energy and materials in countries other than the U. S. Data sets for countries
other than the U. S. were created for the most important parameters in the model. Now,
the LEM can estimate lifecycle emissions from the use of transportation fuels, transport
modes, electricity, and heat in any one of up to 30 countries. The user specifies a
country ( which I will refer to as a “ consuming” or “ target” country), and the LEM looks
up the corresponding data sets and uses them in the active calculations.
In the LEM, the calculation of end- use emissions from transportation, electricity,
and heat involves hundreds of parameters. There are parameters for the inputs and
outputs of fuel- conversion processes ( e. g., crude oil refining to gasoline), the efficiency
of fuel use by motor vehicles ( e. g., fuel economy in urban driving), emissions from
motor vehicles ( e. g., g/ mi of particulate matter), and so on. If one had unlimited time
and resources, one would have country- specific values for every parameter in the
model. For example, there would be a unique set of emission factors for each country,
because combustion technology, regulations, and emission controls vary from country
to country. However, because I do not have unlimited time and resources, I have
developed country specific- values for only the most important parameters. For these
relatively important parameters, the LEM has 30 values or sets of values – one for each
country.
For most parameters, however, the LEM does not have country- specific data sets.
For example, as a general rule, I have assumed that fuel qualities ( apart from sulfur
16
content), CO2- equivalency factors ( similar to IPCC “ Global Warming Potentials”), land-use
impacts ( e. g., changes in carbon storage due to cultivation), and the energy intensity
and emissions of new technologies ( e. g., the energy use of facilities that produce diesel-like
fuel via the Fischer- Tropsch process, or emissions from natural- gas motor vehicles
relative to emissions from gasoline vehicles) are the same in all countries. For these
parameters, the LEM uses either generic technology values ( e. g., the parameters that
specify inputs and outputs for converting natural gas to hydrogen are based on a
generic technological specification, not on country- specific inputs and outputs), or
values specific to the U. S. ( e. g., the travel distances for trucks distributing finished
motor fuels are based on U. S. data, regardless of whether the U. S. data are appropriate
for any particular country). I believe that most of the non- country- specific
technologically generic assumptions are reasonable for all countries. Some of the U . S.-
based assumptions are likely to be inaccurate for other countries, but because most of
these parameters are relatively unimportant ( in the sense that changes in the value of
the parameter have a relatively minor impact on total estimated lifecycle emissions), the
inaccuracies generally are relatively unimportant.
Data specific to “ consuming” countries
The LEM has the following parameters specific to designated target or
“ consuming” countries:
DATA CATEGORY COUNTRY- SPECIFIC PARAMETERS
Motor- vehicle fuel use
( light- duty and heavy-duty
vehicles)
City fuel economy, highway fuel economy, and city-driving
fraction of total VMT, by vehicle type ( light- duty
vehicles, heavy- duty trucks, and buses).
Motor- vehicle emissions
( light- duty and heavy-duty
vehicles)
Emissions by pollutant, model year, and vehicle type
( light- duty vehicles and heavy- duty vehicles) ( exhaust
emissions, evaporative emissions, and road- dust,
brakewear, and tailpipe PM).
Motor scooters Fuel economy and emissions by pollutant, relative to US
values.
Mini cars ( up to 500 kg) Fuel economy and emissions by pollutant, relative to US
values.
Motor vehicles ( all types) Lifetime to scrappage.
Rail transit ( heavy rail and
light rail)
Passenger load/ passenger- capacity factors;
BTUs/ capacity- mile for traction energy; BTUs/ capacity-mile
for station energy; energy for construction relative to
energy for traction.
Evaporative emissions g/ gal emissions from refueling and fuel marketing, in a
base year; annual rate of change of g/ gal emissions
17
Electricity generation and
distribution efficiency
Generation efficiency in a base year, by type of fuel;
percent change in generation efficiency per year, by type
of fuel; electricity distribution efficiency in a base year;
annual percentage change in distribution efficiency
Electricity generation fuel
mix for specific end uses
of electricity
Mix of sources used to generate electricity ( coal, oil, gas
boiler, gas turbine, nuclear, hydro, other), specified
separately for: EV recharging, crop- ethanol production,
biomass- ethanol production, operation of rail transit,
water electrolysis ( for hydrogen production), and generic
power. ( For generic power, data are base year generation
by type in gWh, and percentage change per year in
absolute generation.)
Electricity generation
emissions
Efficiency of emission controls, by pollutant, relative to
US values.
Diesel fuel sulfur Sulfur content ( ppm) for various years between 1970 and
2050, for highway, offroad, and heating fuels.
Other fuel quality Sulfur content of coal and various petroleum products,
relative to that in the U. S..
Material flows Imports of materials by producing region ( the major
material producing and exporting regions of the world)
and by material ( iron, aluminum, plastics, and “ other
materials”); transport distances between producing and
consuming countries; transport modes ( ship or other) by
producing region.
Oil flows Imports of petroleum by producing region ( the major oil
producing and exporting regions of the world) and by
kind of petroleum ( crude oil, light petroleum products,
heavy petroleum products); transport distances between
producing and consuming countries; transport modes
( ship or other) by producing region.
Coal flows Imports of coal by producing region ( the major coal
producing and exporting regions of the world); transport
distances between producing and consuming countries;
transport modes ( ship or other) by producing region.
Natural- gas flows Imports of natural gas by producing region ( the major gas
producing and exporting regions of the world) and
product ( natural gas by pipeline, liquefied natural gas,
and natural- gas- derived liquids); transport distances
between producing and consuming countries; transport
modes ( pipeline or ship) by producing region.
Natural gas losses Leakage from domestic distribution systems ( percent of
18
end use consumption).
Motor- vehicle flows Imports of motor vehicles by producing region ( the
major- vehicle producing and exporting regions of the
world) and type of vehicle ( heavy- duty or light- duty);
transport distances between producing and consuming
countries; transport modes ( ship or other) by producing
region.
Uranium production and
enrichment
Production of uranium by country; imports of enriched
uranium ( as “ separative work units” [ SWUs] by
producing region ( the major SWU- producing- countries of
the world); SWUs per MWh generated; tons of enriched
uranium per GWh generated.
Crop production and
fertilizer use
Harvest yield in base year and annual change in harvest
yield, by crop type; rate of nitrogen loss, by crop type;
fraction of residue burned, by crop type; energy intensity
of N- fertilizer production relative to U. S; distribution of
land types displaced, by crop type.
Corn- ethanol production Total energy requirement ( BTUs- process- fuel/ gal-ethanol);
electricity use ( kWh/ gal); type of process fuel
( coal, oil, gas, biomass).
Nitrogen deposition Distribution of land types affected by deposition, by
country; deposition of N onto agricultural land, by
country.
Multi- modal emissions Parameters for the estimation of emissions per passenger-mi
and emissions per ton- mi ( for use in the analysis of the
impacts of multi- modal transportation policies): vehicle
occupancy by mode ( passenger cars, motor- scooters,
mini- cars, bicycles, minibuses, and buses); passenger-load/
passenger- capacity fractions for rail heavy and light
rail; passenger- miles of travel by mode ( light- duty
vehicles, buses, minibuses, minicars, and motor scooters
[ including a wide range of alternative fuels and electric
vehicles], heavy rail, light rail, bicycling, and walking);
tons and miles of travel by freight mode ( large and
medium diesel, CNG, and ethanol trucks, diesel trains,
cargo ships, tankers, barges, and pipelines).
Appendix B of this report documents some of the country- specific parameter
values.
19
Representation of producing countries
The preceding section describes data sets specific to the target or consuming
countries. Among the country- specific parameters listed in that table are several that
describe imports of fuels or materials for consuming countries. For each consuming
country and fuel or material commodity, the user specifies the fraction imported from
each of the major producing regions of the world. For example, for any consuming
country ( say, Japan), one specifies the amount of crude oil imported from the major
crude- oil producing and exporting regions of the world ( the Persian Gulf, Indonesia,
and so on).
Important energy- use and emissions parameters are specified for each producing
region. For example, the energy intensity of petroleum refining is specified for each
major petroleum- product- exporting region, and venting and flaring of associated gas is
specified for each major crude- oil- producing region. The shipping distance between
producing regions and designated end- use consuming ( target) countries also is
specified. The energy, emissions, and distance parameters for each producing region are
weighted according to the region’s contribution to the total consumption of the
designated or “ target” country.
The LEM represents producing regions and flows between producing regions
and consuming countries for two reasons: 1) to properly represent differences in energy
intensity and emission factors from one region to the next; and 2) to allow users to
separate “ domestic” emissions, associated with the designated consuming country,
from foreign emissions. This second purpose can be useful in national GHG accounting
inventories.
In the LEM, the commodities exported from producing regions to consuming
countries are crude oil, petroleum products, natural gas ( including liquefied natural
gas), natural- gas liquids, coal, uranium, SWUs, vehicles, steel and iron, aluminum,
plastics, and other materials. The producing regions vary by commodity, of course, and
are those that actually account for the bulk of the production of the commodity in the
world today. The following table lists the key producing regions and the commodities
produced in each region.
Producing region or country Commodity produced
U. S. all
Canada all except SWUs
Japan SWUs, MVs, all materials
N. Europe all except MVs, uranium
S. Europe petroleum products, NG, NGTLs, all materials
Former Soviet Union all except MVs
China coal, SWUs
Korea MVs, materials
20
Asian Exporters all except SWUs, uranium, MVs
Venezuela petroleum products, crude oil
North Africa ( Algeria, Libya) petroleum products, crude oil, NG, NGTLs
Nigeria petroleum products, crude oil, NG ( LNG)
Indonesia coal, petroleum products, crude oil, NG, NGTLs
Persian Gulf petroleum products, crude oil, NG, NGTLs
Malaysia NG ( LNG)
Caribbean Basin petroleum products, crude oil, coal, NG ( LNG)
Other all
Mexico crude oil, NG, NGTLs, MVs
France SWUs, MVs
Germany MVs, materials
Other Europe MVs
Australia coal, uranium, NG ( LNG)
Colombia coal
Poland, Czech Republic coal
South Africa coal, uranium
Other Middle East crude oil
Other Africa crude oil
Target developed ( domestic) all
Target LDC ( domestic) all
International transport all except SWUs, uranium
In this table, “ all” commodities are crude oil, petroleum products, natural gas
( NG) including liquefied natural gas ( LNG), natural- gas liquids ( NGTLs), coal,
separative work units ( SWUs; for enriching uranium), uranium, motor vehicles ( MVs),
steel and iron, aluminum, plastics, and other materials, and “ all materials” are steel and
iron, aluminum, plastics, and other materials. Note that the “ target developed” and
“ target LDC” categories are used to account for domestic production in target countries
that are not part of any of the major producing regions.
For each commodity produced and traded in the LEM, there are parameters that
are relevant to the estimation of lifecycle energy use and emissions and specific to each
producing region. The following table shows commodities produced and traded in the
LEM, and the corresponding energy use and emissions parameters specified for the
commodity and producing region:
Commodity produced Energy and emission parameters for producing regions
21
crude oil Amount of oil recovery onshore, offshore, and from
unconventional reserves; energy intensity of oil
recovery for onshore, offshore, and unconventional
production; venting and flaring of associated gas; CO 2
and SO 2 emissions from oil production; emissions
associated with using concrete to plug oil wells.
petroleum products Energy intensity of petroleum refining; mix of fuels
used by petroleum refineries; electricity generation mix
for petroleum refineries; sulfur content of fuels.
natural gas Energy intensity of gas production; energy intensity of
gas transmission; leakage from gas recovery, processing
and transmission; CO 2 and SO 2 emissions from oil
production; emissions associated with using concrete to
plug oil wells.
NGTLs Energy intensity of natural- gas- to- liquids ( NGTL)
production.
coal Energy intensity of coal production; amount of
production from underground and surface mines;
methane emissions from underground and surface
mines; fate of methane emissions from coal mining.
materials Energy intensity of materials production.
vehicles Energy intensity of vehicle assembly; electricity
generation mix for vehicle assembly.
uranium Energy intensity of uranium production.
SWUs SWU production by gas diffusion, centrifuge, and laser-based
technologies; electricity requirements of each
production technology.
The values of these parameters are given and documented in the Main Report of
Delucchi ( 2003).
COMPARISON OF THE LEM WITH OTHER RECENT LC MODELING EFFORTS
The structure and coverage of the LEM can be compared with that of several
other recent transportation fuelcycle or lifecycle modeling efforts:
Project GM - ANL
U. S.
GM – LBST
Europe
MIT 2020 EUCAR LEM
Region North America Europe based on U. S.
data
Europe multi- country
( primary data
for U. S.; other
data for up to
22
30 countries)
Time frame near term
( about 2010)
2010 2020 2010 and
beyond
any year from
1970 to 2050
Transport
modes
LDV ( light-duty
truck)
LDV ( European
mini- van)
LDV ( mid- size
family
passenger car)
LDVs ( compact
5- seat
European
sedan)
LDVs, HDVs,
buses, light- rail
transit, heavy-rail
transit,
minicars,
scooters,
offroad vehicles
Vehicle
drivetrain type
ICEVs, HEVs,
BPEVs, FCEVs
ICEVs, HEVs,
FCEVs
ICEVs, HEVs,
BPEVs, FCEVs
ICEVs, HEVs,
FCEVs
ICEVs, BPEVs,
FCEVs
Motor fuels gasoline, diesel,
naptha, FTD,
CNG,
methanol,
ethanol, CH2,
LH2, electricity
gasoline, diesel,
naptha, FTD,
CNG, LNG,
methanol,
ethanol, CH2,
LH2
gasoline, diesel,
FTD, methanol,
CNG, CH2,
electricity
gasoline, diesel,
FTD, CNG,
ethanol, FAME,
DME, naptha,
methanol, CH2,
LH2
gasoline, diesel,
LPG, FTD,
CNG, LNG,
methanol,
ethanol, CH2,
LH2, electricity
Fuel
Feedstocks
crude oil,
natural gas,
coal, crops,
ligno- cellulosic
biomass,
renewable and
nuclear power
crude oil,
natural gas,
coal, crops,
ligno- cellulosic
biomass, waste,
renewable and
nuclear power
crude oil,
natural gas,
renewable and
nuclear power
crude oil,
natural gas,
coal, nuclear,
wind. sugar
beets, wheat, oil
seeds, wood
crude oil,
natural gas,
coal, crops,
lignocellulosic
biomass,
renewable and
nuclear power
Vehicle
energy- use
modeling,
including
drive cycle
GM simulator,
U. S. combined
city/ highway
driving
GM simulator,
European Drive
Cycle ( urban
and extra- urban
driving)
MIT simulator,
U. S. combined
city/ highway
driving
Advisor ( NREL
simulator),
New European
Drive Cycle
simple model
based on
SIMPLEV- like
simulator, U. S.
combined
city/ highway
driving
Fuel lifecycle GREET model LBST E2 I- O
model and data
base
literature
review
LBST E2 I- O
model and data
base ( review &
update of GM
et al. [ 2002])
detailed
internal model
Vehicle
lifecycle
not included not included detailed
literature
review and
analysis
not included internal model
based on
detailed
literature
review and
analysis
23
GHGs [ CEFs] CO2, CH4, N2O
[ IPCC] ( other
pollutants
included as
non- GHGs)
CO2, CH4, N2O
[ IPCC]
CO2, CH4
[ IPCC]
CO2, CH4, N2O
[ IPCC]
CO2, CH4, N2O,
NOx, VOC, SOx,
PM, CO, H2,
HFCs, CFCs
[ own CEFs, also
IPCC CEFs]
Infrastructure not included not included not included not included crude
representation
Price effects not included not included not included not included a few simple
quasi-elasticities
Reference GM, ANL et al.
( 2001)
GM et al.
( 2002a, 2002b,
2002c)
Weiss et al.
( 2000)
Concawe et al.
( 2004)
Delucchi ( 2003)
Project ADL
AFV LCA
EcoTraffic CMU I- O LCA Japan
CO2 from
AFVs
LEM
Region United States generic, but
weighted
towards
European
conditions
United States Japan multi- country
( primary data
for U. S.; other
data for up to
30 countries)
Time frame 1996 baseline,
future scenarios
between 2010
and 2015
near term near term? any year from
1970 to 2050
Transport
modes
subcompact
cars
LDVs ( generic
small passenger
car)
LDVs ( midsize
sedan)
LDVs ( generic
small passenger
car)
LDVs, HDVs,
buses, light- rail
transit, heavy-rail
transit,
minicars,
scooters,
offroad vehicles
Vehicle
drivetrain type
ICEVs, BPEVs,
FCEVs
ICEVs, HEVs,
FCEVs
ICEVs ICEVs, HEVs,
BPEVs
ICEVs, BPEVs,
FCEVs
Motor fuels gasoline, diesel,
LPG, CNG,
LNG, methanol,
ethanol, CH2,
LH2, electricity
gasoline, diesel,
FTD, CNG,
LNG, methanol,
DME, ethanol,
CH2, LH2
gasoline, diesel,
biodiesel, CNG,
methanol,
ethanol
gasoline, diesel,
electricity
gasoline, diesel,
LPG, FTD,
CNG, LNG,
methanol,
ethanol, CH2,
24
LH2, electricity
Fuel
feedstocks
crude oil,
natural gas,
coal, corn,
ligno- cellulosic
biomass,
renewable and
nuclear power
crude oil,
natural gas,
ligno- cellulosic
biomass, waste
crude oil,
natural gas,
crops, ligno-cellulosic
biomass
crude oil,
natural gas,
coal, renewable
and nuclear
power
crude oil,
natural gas,
coal, crops,
lignocellulosic
biomass,
renewable and
nuclear power
Vehicle
energy- use
modeling,
including
drive cycle
Gasoline fuel
economy
assumed; AFV
efficiency
estimated
relative to this
Advisor ( NREL
simulator),
New European
Drive Cycle
Gasoline fuel
economy
assumed; AFV
efficiency
estimated
relative to this
none; fuel
economy
assumed
simple model
based on
SIMPLEV- like
simulator, U. S.
combined
city/ highway
driving
Fuel lifecycle Arthur D. Little
emissions
model, revised
literature
review
own
calculations
based on other
models ( LEM,
GREET..)
values from
another study
detailed
internal model
Vehicle
lifecycle
not included not included Economic
Input- Output
Life Cycle
Analysis
software
( except end- of-life)
detailed part-by-
part analysis
internal model
based on
detailed
literature
review and
analysis
GHGs [ CEFs] CO2, CH4,
[ partial GWP]
( other
pollutants
included as
non- GHGs)
none ( energy
efficiency study
only)
CO2, CH4, N2O?
[ IPCC] ( other
pollutants
included as
non- GHGs)
CO2 CO2, CH4, N2O,
NOx, VOC, SOx,
PM, CO, H2,
HFCs, CFCs
[ own CEFs, also
IPCC CEFs]
Infra- structure not included not included not included not included crude
representation
Price effects not included not included not included
( fixed- price I- O
model)
not included a few simple
quasi-elasticities
Reference Hackney & de
Neufville ( 2001)
Ahlvik and
Brandberg
( 2001)
MacLean et al.
( 2000)
Tahara et al.
( 2001)
Delucchi ( 2003)
25
The terms in the model comparison table are defined as follows:
Region The countries or regions covered by the analysis.
Time frame The target year of the analysis.
Transport modes The types of passenger transport modes included. LDVs = light-duty
vehicles, HDVs = heavy- duty vehicles.
Vehicle drivetrain
type
ICEVs = internal combustion- engine vehicles, HEVs = hybrid-electric
vehicles ( vehicles with an electric and an ICE drivetrain),
BPEVs = battery- powered electric vehicles ( BPEVs), FCEVs =
fuel- cell powered electric vehicles.
Motor fuels Fuels carried and used by motor vehicles. FTD = Fischer- Tropsch
diesel, CNG = compressed natural gas, LNG = liquefied natural
gas, CH2 = compressed hydrogen, LH2 = liquefied hydrogen,
DME = dimethyl ether, FAME = fatty acid methyl esters.
Fuel feedstocks The feedstocks from which the fuels are made.
Vehicle energy-use
modeling
The models or assumptions used to estimate vehicular energy
use ( which is a key part of fuelcycle CO 2 emissions), and the drive
cycle over which fuel usage is estimated ( if applicable).
Fuel lifecycle The models, assumptions, and data used to estimate emissions
from the lifecycle of fuels.
Vehicle lifecycle The lifecycle of materials and vehicles, apart from vehicle fuel.
The lifecycle includes raw material production and transport,
manufacture of finished materials, assembly of parts and
vehicles, maintenance and repair, and disposal.
GHGs and CEFs The pollutants ( greenhouse gases, or GHGs) that are included in
the analysis of CO 2 - equivalent emissions, and the CO 2 -
equivalency factors ( CEFs) used to convert non- CO 2 GHGs to
equivalent amount of CO 2 ( IPCC = factors approved by the
Intergovernmental Panel on Climate Change [ IPCC]; LEM CEFs
are those derived in Appendix D of Delucchi [ 2003]).
Infrastructure The lifecycle of energy and materials used to make and maintain
infrastructure, such as roads, buildings, equipment, rail lines, and
so on. ( In most cases, emissions and energy use associated with
the construction of infrastructure are small compared with
emissions and energy use from the end use of transportation
26
fuels.)
Price effects This refers to the relationships between prices and equilibrium
final consumption of a commodity ( e. g., crude oil) and an
“ initial” change in supply of or demand for the commodity or its
substitutes, due to the hypothetical introduction of a new
technology or fuel.
Note that the study by EcoTraffic ( Ahlvik and Brandberg, 2001) provides a good
comparison of their work with the GM WTW U. S. ( GM et al., 2001), the MIT 2020
( Weiss et al. 2000), and several other studies.
Among the tools used in the studies in the table above, those used in the GM
WTW studies are most similar to those used in the transportation fuel lifecycles of the
LEM. In particular, the GREET model is similar to the fuel lifecycle parts of the LEM.
( See Wang [ 1999] for documentation of the GREET model.) Even so, there are
significant differences. Generally, the LEM is broader in scope than the GM studies: it
covers more countries, wider time frames, more transport modes, more pollutants,
more aspects of the lifecycle ( such as materials), and more relevant effects ( such as price
effects). One significant exception is that the GM studies, and several other studies
listed in the table above, include one vehicle type ( hybrid EVs) and some fuel pathways
( such as fuels from waste) that are not included in the LEM.
My examination of the available documentation for the GREET model and the
LBST E2 I- O model ( used in the GM WTW European study) indicates that, apart from
the differences noted in the table above, the fuel lifecycle parts of the LEM are in some
cases more detailed than are the GREET and E2 models. For example, the LEM includes
a more detailed carbon tracking ( apportioning carbon between fuel, lubricating oil,
biomass and non- biomass components) than do other models. More significantly, the
LEM has a more comprehensive and detailed treatment of emissions associated with
cultivation, land- use change, the nitrogen cycle, and particulate matter. The LEM also
uses complete, detailed input- output relationships, usually based on primary data
( rather than secondary citation of literature), for most lifecycle stages.
Note that the comparison above covers only major, original, recent analyses of
lifecycle emissions from a wide range of alternative transportation fuels. It does not
include the following:
• older LCAs of alternative transportation fuels ( see DeLuchi [ 1991] for a
discussion of studies done before 1990, and Wang [ 1999] for a discussion of
studies done in the 1990s);
• studies that are entirely derivative;
• studies of a single fuel or narrow range of transportation fuels;
• studies that focus mainly on the lifecycle of the automobile as opposed to
automotive fuels ( e. g., Sullivan et al., 1998; see Appendix H of Delucchi [ 2003]
for more discussion pertinent to these analyses);
27
• LCAs not directly related to transportation ( of which there area great many, for
a wide range of non- transportation products and system, including power
generation, building materials, and more).
It should be emphasized that many of these studies, and particularly some of
those that focus on a single fuel or a narrow range of fuels, are of high quality. I have
omitted them only to keep the comparison manageable. It is also worth noting that
many of the non- transportation LCAs and some of the transportation LCAs follow
guidelines established by the International Organization for Standardization ( ISO). The
general applicability ISO guidelines are discussed briefly in a separate section below.
METHODS AND ANALYTICAL ISSUES IN LCA
General method of estimation of lifecycle- CO2 emissions from transportation
systems in the LEM
As discussed above, basic outputs of the LEM include lifecycle CO 2 - equivalent
emissions per mile of travel by transportation modes or per pound of material
produced ( g/ mi or g/ lb). Appendix H of Delucchi [ 2003] documents the calculation of
g/ lb emissions from the lifecycle of materials. Here I present the basic methods used to
calculate g/ mi emissions from the lifecycle of transportation fuels.
Generally, the LEM calculates grams of CO2- equivalent emissions from stage S
( e. g., oil recovery) of the lifecycle of end- use fuel X ( the fuel of interest; e. g., motor
gasoline), per mile of travel, by multiplying emissions per energy unit of X by energy
use per mile:
GHGMI S, X = GHGBTU S, X ⋅ M X eq. 1a
where:
GHGMIS, X = CO2- equivalent emissions of GHGs from stage S of the lifecycle of
fuel X, in grams per vehicle mile of travel
GHGBTUS, X = CO2- equivalent emissions of GHGs from stage S of the lifecycle of
fuel X, in grams per million BTU of X made available to end users
( discussed below)
MX = fuel X available to the transportation sector, in 106 BTUs per vehicle mile of
travel ( elaborated in the Main Report of Delucchi [ 2003])
Subscript S = stages of the lifecycle ( feedstock recovery, feedstock transport, etc.;
see the list earlier in this report)
Subscript X = fuel ( or commodity) whose lifecycle is being analyzed ( see the
table earlier in this report)
28
Strictly speaking the method of equation 1a applies only to “ upstream” or non-end
use stages of the lifecycle. CO 2 - equivalent emissions from end- use of fuels by
vehicles are calculated with a slightly different method, not presented here.
Emissions over the entire lifecycle of X are simply the sum of g/ mi emissions for
each stage:
GHGMI X = GHGMI S, X
S Σ
eq. 1b
CO 2 - equivalent emissions per energy unit of fuel X delivered to end users – the
parameter GHGBTU – are calculated by multiplying inputs to stage S per unit of final
output of the fuel of interest X by CO 2 - equivalent emissions from the use of the inputs.
Thus, the heart of the LEM is essentially an engineering input- output model with
emission factors. Formally:
GHGBTU S, X = IO I , S, X ⋅ CEEF I
I Σ
eq. 1
where:
IOI, S, X = input of quantity I to stage S of the lifecycle of fuel X per BTU of X
delivered to end users ( the units of the inputs – lbs, BTUs, etc. – vary with
the type of input) ( discussed further below)
CEEF I = CO2- equivalent emissions of GHGs per unit of input I
Subscript I = quantities input to stages of lifecycles ( includes energy
commodities, such as coal, oil, and natural gas; chemicals, and more; see
discussions of specific lifecycles throughout the Main Report of Delucchi
[ 2003])
Input/ output ratios ( parameter IO) are discussed throughout this
documentation. Typically they are not specified as such but rather are the result of
further calculations within the LEM.
CO 2 - equivalent emissions ( CEEF) are calculated as the product of a CO 2 -
equivalency factor ( CEF) and emissions of individual pollutants P, summed over all P:
CEEF I = EF P, I ⋅ CEF P
P Σ
eq. 1d
where:
EFP, I = the emission factor for pollutant P and input I: grams of pollutant P per
unit of input I ( discussed below)
CEF P = CO2- equivalency factor for pollutant P ( discussed in Appendix D of
Delucchi [ 2003])
29
Subscript P = individual pollutants tracked in the LEM ( CH 4 , N 2 O, etc; see the list
earlier in this report)
The emission factors EF generally are calculated directly from primary inputs to
the LEM. These primary emission- factor inputs are taken from a wide variety of
primary sources, such as the EPA’s compilation of emission factors known as AP- 42.
( See the discussion of individual lifecycles in Delucchi [ 2003] for details.) Emissions of
CO 2 are a special case, because these emissions are calculated based on carbon contents
( rather than specified by the user) and because the CEF for CO 2 is 1.0. Formally,
emissions of CO 2 are calculated on the basis of a complete carbon balance for any input
I:
EF CO2, I = CC I − C NONCO2, I ( )⋅ MW CO2
MW C
eq. 1e
where:
CCI = the carbon content of input I ( grams of C per unit of I; these are specified
in DeLuchi [ 1993] and Delucchi [ 2003])
CNONCO2, I = carbon in input I that ends up in any form other than CO2 ( based
on calculations of the carbon content of non- CO 2 gases and other carbon
sinks; most of these further calculations are presented in this
documentation)
MWCO2 / MWC = the ratio of the molecular weight of CO 2 to that of C ( 3.664)
The carbon- balance calculations also properly distinguish biogenic from fossil-fuel
carbon for the purpose of determining “ net” emissions to the atmosphere.
The summary calculations presented above provide a general outline of some of
the main algorithms within the LEM. There are of course many variations on the
methods presented above, considerable further elaborations ( especially in the case of
calculating input/ output ratios), and a number of important cases where entirely
different algorithms are used ( e. g., the calculation of CO 2 - equivalent emissions related
to changes in land- use in the lifecycle of biofuels). Most of these are discussed Delucchi
( 2003). Finally, additional methodological considerations, such as “ own- use” of fuel,
also are discussed in Delucchi ( 2003).
Note on structural circularity. All of the major lifecycle calculations within the
LEM are circular: every lifecycle is related structurally to every other lifecycle. For
example, the calculation of lifecycle emissions associated with the use of coal calls on
the calculation of lifecycle emissions associated with the use of natural gas, but also vice
versa: the natural- gas lifecycle calls on the coal lifecycle. This structural circularity
connects most lifecycles. The model resolves these circularly related equations by
iterative calculations using convergence algorithms internal to the spreadsheet
program. This structural circularity is an proper representation of the real world and is
a methodological advantage of the LEM over models that lack such structure.
30
Overview of basic analytical issues in LCA
As mentioned above, transportation LCAs, and indeed all LCAs as done today,
are essentially linked input- output building blocks with emission factors. From this
simple description we can identify several basic analytical issues in LCA:
i) detail: the appropriate “ grain” or level of detail of the building blocks and
the appropriate number of building blocks ( e. g., in the case of petroleum
refining, should one represent the entire petroleum- refining sector of the
economy, or specific petrochemical processes within refineries);
ii) scope: the boundaries or extensiveness of the system of blocks that
represent the lifecycle ( e. g., in an analysis of transportation fuels, whether
to include materials used in the construction of petroleum refineries);
iii) structure: the mathematical representation of building blocks and the
nature of the I- O relationships between building blocks ( e. g., fixed versus
dynamic I- O ratios for building blocks).
The issues outlined above are widely recognized in the literature on LCA ( see for
example the recent articles by Rebitzer et al. [ 2004] and Pennington et al. [ 2004]). Many
discussions in the literature focus on the trade- off between detail and extensiveness,
typically manifested in the choice between detailed engineering- type process- specific
LCAs of limited extensiveness and extensive economy- wide I- O type analyses of
limited detail. ( For an example of the latter, see Matthews and Small [ 2001].) There has,
however, been virtually no in- depth discussion of the question of fixed versus dynamic
I- O ratios. In a later section of this documentation I will address this issue in some
depth. In the following section I discuss specific issues of detail, scope, and structure in
the LEM.
Issues concerning the detail, scope, and structure of the LEM
An ideal analysis of life cycle emissions and energy use would include all
energy- consuming and pollutant- emitting processes and all pollutants in complete and
correct detail. With respect to this ideal, the LEM falls short in several ways. In addition,
although most parts of the LEM contain reasonably detailed representations, there are a
few important simplifications that can lead to misleading or internally inconsistent
results.
• The LEM does not include at least two major kinds of air pollution: emissions
of particulate matter dust from some sources ( e. g., dust from agricultural operations or
coal mining [ however, dust from roadways is included), and emissions of volatile
organic compounds from biomass ( e. g., terpenes from trees used in short- rotation
intensive cultivation). Inclusion of these sources of pollutant could change the relative
attractiveness of different life cycles.
• Although it includes emissions associated with materials manufacture and
assembly for vehicles, trains, and ships, it does not include emissions associated with
31
materials used for large construction projects such as power plants and refineries. It is
possible, albeit in my view in unlikely, that in some lifecycles this omitted source of
emissions might be unlikely.
• Generally, the model uses average rather than “ marginal” emission- reduction
factors. For example, the model calculates the average emissions for all coal- fired boilers
used in industry, on the basis of the projected extent and effectiveness of emission
controls. It does not distinguish industries or processes in which all boilers will be
controlled from industries or processes in which few boilers will be controlled. This
results in an overestimate of emissions from new sources, which are required to meet
New Source Performance Review Standards, and an underestimation of emissions from
old sources not subject to emission controls.
• A few important parameters are not projected year- by- year through 2050, as
are many unimportant parameters are, but rather are fixed at year 2000 values.
• The calculation of second- order energy use and emissions related to the
manufacture and servicing of transportation modes ( trains, ships, trucks, and pipelines)
also is an input rather than a calculated parameter, and might in fact be inconsistent
with other calculations in the analysis.
• For the most part the LEM assumes fixed rather than dynamic I- O ratios. As
discussed in the next section, I- O ratios generally are not fixed, but rather vary as some
function of the assumed changes in the level of use of the product whose lifecycle is
being modeled (“ the product of interest”). The ultimate driver of the variation in I- O
ratios is changes in the prices of important commodities, changes which are related to
changes in the level of use of the product of interest. Hence, in principle, dynamic I- O
ratios could be represented by the use of price elasticities, which show how the use of
major commodities changes with changes in prices. The LEM uses a few quasi price
elasticities, mainly as regards the marketing of the co- products of some production
processes ( e. g., the marketing of the co- products of corn- to- ethanol conversion).
Focus on the question of dynamic versus fixed I- O ratios
LCAs that I am aware of, including economic I- O LCAs, have assumed fixed I- O
ratios. Many LCAs, and all economic I- O LCAs, acknowledge this assumption, but none
discuss it or justify it any length. In this context, “ fixed” I- O ratios mean that ratios of
input quantities to output quantities, at every stage, from intermediate production to
final demand, do not change as a result of the posited changes in the final output of the
product whose lifecycle is being analyzed. The meaning of this is best illustrated by an
example.
Consider a lifecycle analysis of motor gasoline, in which we wish to estimate the
lifecycle impacts of using more or less motor gasoline than in some baseline. To assume
fixed I- O ratios means, for example, to assume that the ratio of crude oil input to
refinery outputs of each petroleum product, or the ratio of crude oil input to total
power- plant output of electricity, or the ratio of gasoline use to vehicle- miles of travel,
are constant regardless of the level of motor- gasoline use. Given this characterization,
the methodological question can be put succinctly: are these reasonable assumptions?
32
In the real world, I- O ratios are not actually fixed, but rather are a function of
changes in prices – changes which are associated with the change in final output ( of the
product of interest) that is at least implicitly posited in any LCA. Let us focus again on
transportation LCAs. Any action regarding transportation – for example, a vehicle
production mandate by government, a public subsidy to fuels, or a market decision by a
private company to make a new kind of diesel fuel – will affect the prices of globally
important commodities, such as oil, natural gas, or steel. The effects on the prices of
these commodities ultimately will affect emissions, which are what lifecycle emissions
models wish to estimate. As a result, transportation LCAs that assume fixed rather than
dynamic I- O ratios mis- estimate the emissions of interest.
In general, actions may affect prices directly, for example by changing tax rates,
or indirectly, by affecting the supply of or demand for commodities used in
transportation. In an integrated and complex global economy, changes in the prices of
important commodities ultimately will affect production and consumption of all
commodities in all sectors throughout the world. In the final equilibrium of prices and
quantities, there will be a new global pattern of production and consumption. This
pattern will be different from what would have obtained had prices been fixed.
Associated with this new pattern of production and consumption ( arising from
dynamic prices) will be a new pattern of emissions of air pollutants. The difference
between the global emissions pattern associated with the transportation action being
evaluated and the global emissions pattern without the action ( in a world of dynamic
prices) may be said to be the “ emissions impact” of the action being evaluated. This
emissions impact will differ from that obtained when we assume that prices are fixed,
because the pattern of production and consumption assuming fixed prices will differ
from that assuming dynamic prices.
Returning to our gasoline example, any action that affects gasoline use is likely to
affect the price of gasoline and by extension the price of crude oil. In turn, changes in
the price of gasoline will have a direct affect on transportation choices and hence on
transportation- related emissions. Furthermore, changes in the price of crude oil will
affect the consumption not only of crude oil but of the products of, substitutes for and
complements of crude oil and petroleum products as well. These large- scale changes in
prices of major commodities will reverberate throughout the world economy, affecting
the production of important raw materials ( such as ores) and finished products ( such as
metals). These changes in production will result in changes in emissions.
The reasoning outlined above suggests that any real- world action that is the
ostensible object of an LCA ( such as a policy that affects motor- gasoline use) is likely to
affect prices and hence ultimately likely to make the standard assumption of fixed I- O
ratios invalid. ( See Delucchi [ 2002] for further discussion.)
Applicability of International Organization for Standardization ( ISO) 14040
standards
As mentioned above, the International Organization for Standardization ( ISO)
has established guidelines for conducting LCA. The ISO guidelines for LCA are laid
33
out in ISO standards 14040 to 14049 ( see the ISO web site, www. iso. ch/ iso/ en/ iso9000-
14000/ iso14000/ iso14000index. html). The specific standards are:
Title Year Description
ISO 14040: 1997 1997 Environmental management – Life cycle
assessment – Principles and framework. ( General
principles and methodological requirements.)
ISO 14041: 1998 1998 Environmental management – Life cycle
assessment – Goal and scope definition and
inventory analysis.
ISO 14042: 2000 2000 Environmental management – Life cycle
assessment – Life cycle impact assessment.
( Guidance on conducting the actual life- cycle
assessment.)
ISO 14043: 2000 2000 Environmental management – Life cycle
assessment – Life cycle interpretation. ( Guidance
on interpreting the results of the analysis.)
ISO/ Technical report
14047: 1997
Post 2002? Environmental management – Life cycle
assessment – Examples of application of ISO 14042.
ISO/ Technical report
14048: 2002
2002 Environmental management – Life cycle
assessment – Data documentation format.
( Information regarding the formatting of data to
support life cycle assessment.)
ISO/ Technical report
14049: 2000
2000 Environmental management – Life cycle
assessment – Examples of application of ISO 14041
to goal and scope definition and inventory
analysis.
A number of articles and reports discuss ISO 14040 standards or LCA
applications that are consistent with ISO 14040 standards. For example, Rebitzer et al.
( 2004) and Pennington et al. ( 2004) provide recent comprehensive reviews of methods,
data, and applications in LCA, with reference to ISO guidelines. Weidema ( 2001)
discusses the proper handling of joint production ( sometimes known as “ co- product
allocation”) with specific reference to the methods of ISO 14041. There also are many
commercial database and inventory tools that follow ISO 14040 protocols.
ISO guidelines and transportation LCAs. In principle, there are three ways in
which the ISO 14040 guidelines and database tools might be useful in lifecycle of
analyses of CO 2 - equivalent emissions associated with policies directed towards
alternative transportation options. First, they might provide guidance concerning
conceptual and methodological issues, such as those concerning system boundaries and
34
joint production. However, in this respect it appears that the ISO 14040 guidelines and
tools may reflect but usually do not themselves advance the state of the art, and as a
result have no advantage over models, such as the LEM, which have undertaken
original ( albeit limited) explorations of conceptual and methodological issues. For
example, the first version of the LEM ( DeLuchi, 1991, 1993) addressed several
conceptual and methodological issues in fuelcycle analysis independently of and in
some instances prior to treatment by ISO 14040, including: joint production ( also known
as “ co- production;” e. g., the production of ethanol and feed from inputs of corn and
other items); system boundaries ( e. g., whether to include, in analyses of alternative
transportation fuels, inputs and outputs associated with infrastructure, buildings, and
maintenance and repair); “ own- use” ( e. g., the use of diesel fuel by trucks delivering
diesel fuel to service stations in the lifecycle of diesel fuel); and nth- order indirect effects
( e. g., the lifecycle of natural gas used to recover crude oil made into diesel fuel used to
transport coal to power plants that provide electricity to petroleum refineries that make
gasoline).
Second, ISO 14040- based tools and databases might provide input- output or
emission- factor data relevant to transportation LCAs. This indeed can be case, and in
the development of the LEM I have consulted these databases whenever they have been
publicly available ( e. g., National Renewable Energy Laboratory, 2003). However, my
experience has been that those ISO- 14040- based database tools per se, and per force, do
not develop original data from primary sources ( such as actual experiments, or analyses
of primary survey data) but rather rely on data developed by others – including, in
some cases, original estimates developed in the documentation for earlier versions of
the LEM.
Third, the ISO 14040 guidelines can provide a common template for organizing,
presenting, and interpreting LCAs. However, ISO 14040 formats appear to be most
suited to multi- media, multi- pollutant, multi- denominated ( i. e., not reduced to a single
common metric) outputs of industrial processes. By contrast, LCAs of CO 2 - equivalent
emissions from transportation alternatives report single- media, multi- pollutant, single-metric
outputs of public transportation policies. There is no particular advantage to
shoe- horning the outputs of the transportation LCAs into ISO 14040 formats.
In summary, LCAs of CO 2 - equivalent emissions from transportation alternatives
have developed independently of the multi- media, multi- pollutant, multi- metric LCAs
of industrial processes that ISO 14040 targets. Although ISO 14040 guidelines and
databases can inform transportation LCAs, it is at least as likely that the methods and
original data estimates of the more academically advanced transportation models
would inform the more applied, commercial world of ISO 14040.
DISCUSSION OF RESULTS FROM THE LEM
Energy efficiency and emissions of vehicles.
35
Vehicle energy use is one of the most important calculated parameters in the
LEM, because it linearly determines fuel cycle emissions of CO2. In the LEM, the energy
use of a vehicle is determined by the mi/ BTU energy- conversion efficiency of the AFV
engine or powertrain relative to that of the baseline gasoline or diesel vehicle, the
weight of the vehicle, and other parameters. The weight of a vehicle, in turn, is a
function of the driving range, the characteristics of the fuel storage systems, and other
factors. Of these parameters, the energy- conversion efficiency of the powertrain is the
most important because it directly determines vehicle energy use. Driving range and
vehicle weight are less important because they affect vehicle energy use only indirectly.
( Over the typical range of variation of both driving range and fuel- storage
characteristics, the fuel cycle CO2- equivalent emissions vary by only 1- 2%.)
The input parameters for the calculation of vehicle energy use are discussed in
the Main Report of Delucchi ( 2003). The calculated weight results are shown in Table Y-
10b, and the calculated overall efficiency and fuel- use results are shown in Table Y- 11.
Compared with analysis in DeLuchi ( 1991), the efficiency of the EV relative to efficiency
of the baseline gasoline vehicle has increased, and as a result fuel cycle GHG emissions
from EVs are significantly lower.
The calculated g/ mi emissions are shown in Tables Y- 12a. For economy of
presentation, all of these results are shown for the U. S. 2010 case only.
Energy intensity of fuel cycles and kinds of process fuel used
Table Y- 13a presents the new calculated energy intensities by stage of the fuel
cycle, in BTUs of process energy used at each stage per BTU of fuel made available to
end users. ( For economy of presentation, this result is shown for the U. S. in 2010 only.)
The most significant parameters are those relating to the energy requirements of fuel
production ( e. g., methanol production from natural gas); less significant are those
relating to the energy requirements of fuel and feedstock transport.
Table Y- 13b shows BTUs of process energy consumed per vehicle mile of travel.
Variation in the mix of process fuels ( not presented here) typically has only a
minor effect on fuel cycle CO2- equivalent emissions. An example of an exception is
whether coal or natural gas is used to provide process heat at corn- to- ethanol plants.
Leaks of methane and CO2
As discussed in the Main Report of Delucchi ( 2003), the data and methods used
to estimate leaks from natural- gas systems, venting and flaring of gas associated with
oil production, and methane emissions from coal mines have been completely revised.
As a result, calculated venting and flaring emissions from oil wells have increased by a
minor amount, calculated leaks from natural- gas systems have increased substantially,
and calculated emissions from coal mining have decreased substantially, compared
with the results reported in DeLuchi ( 1991). Table 24 in the Main Report ( Delucchi,
2003) shows parameters in the estimation of leaks from coal mining, and Table 28 in the
Main Report shows parameters in the estimation of leaks from NG systems.
36
The increase in the calculated leakage rate from NG systems ( compared with the
value in DeLuchi [ 1991]) increases fuel- cycle emissions by about 7 g/ mi, or 2%. The
decrease in calculated methane emissions from coal mining decreases CO2- equivalent
emissions from the coal- to- electricity fuel cycle by about 2%.
Leaks of hydrogen
The LEM, unlike other lifecycle models, estimates leaks from hydrogen stations,
vehicles, and pipelines, and accounts for the climate effect of hydrogen leaks on
concentrations of methane and tropospheric ozone. The following table shows the CO 2 -
equivalent gram/ mile fuelcycle emissions ( not including emissions from the lifecycle of
materials or vehicles) without and with a CEF for hydrogen, and the resulting
percentage increase in fuelcycle emission, for conditions in the U. S. ( number before the
comma is without CEF for H 2 , number after the comma is with CEF):
Light- duty FCEV
( H 2 / water)
Light- duty FCEV
( H 2 / NG)
Heavy- duty ICE
( H 2 / NG)
Compressed H 2 42.8, 44.5 ( 4.0%) 197, 198 ( 0.4%) 2497, 2507 ( 0.4%)
Liquefied H 2 ( central.) 116.2, 119.2 ( 2.6%) 273, 276 ( 0.9%) 3345, 3375 ( 0.9%)
The increase in the CO 2 - equivalent emissions due to assigning a non- zero CEF to
hydrogen, compared with a CEF of zero, ranges from less than 1% in the case of
vehicles using compressed hydrogen made from natural gas, to 3- 4%, in the case of
vehicles using liquid hydrogen made from electrolysis of water. The use of liquefied
rather than compressed hydrogen results in higher leakage, and hence higher CO 2 -
equivalent emissions, because of boil- off losses associated with liquid- fuel transfers.
The use of hydrogen made from water rather than from natural gas results in higher
hydrogen leakage, and hence higher CO 2 - equivalent emissions, because of the
assumption that there are hydrogen pipelines in the case of hydrogen from water but
not in the case of hydrogen from natural gas.
This analysis has explicit estimates of leakage from vehicular storage and fuel
systems, fuel- cell stacks, fuel dispensing, other liquid- fuel transfers, pipeline
distribution, pipeline transmission, and pipeline compressors. However, there are very
few data on hydrogen leakage rates, and our assumptions may be substantially wrong.
Note, too, that as regards comparing lifecycle GHG emissions from hydrogen fuel- cell
vehicles with lifecycle GHG emissions from fossil- fuel internal- combustion- engine
vehicles, we have not included emissions of hydrogen from the incomplete combustion
of fossil fuels. We do not know the magnitude of this source, and hence do not know
how the omission might affect the comparison.
Electricity generation: efficiency and mix of fuels,
The LEM projects the efficiency of electricity generation and the mix of fuels used
for generic national power. Tables Y- 15a and Y- 15b show the projected efficiencies and
37
fuel mixes. The efficiency of power generation and the mix of fuels used are important
in lifecycles ( such as battery electric vehicles) that have a significant electricity input.
Grams emitted per 106 BTU of fuel delivered to end users, by stage and
feedstock/ fuel combination.
Table Y- 16 shows the calculated CO2- equivalent emissions per unit of energy
delivered to end users, by stage of the fuel cycle and feedstock/ fuel combination. These
results are useful mainly for the purpose of estimating emissions from the “ upstream”
portion of fuel lifecycles ( i. e., the entire lifecycle except end use). For example, one can
use the g/ 106- BTU results for the NG fuel cycle to estimate emissions from the use of
NG for home heating. ( One still must estimate emissions from final end- use combustion
of the gas in the home, of course.) These results are shown for all countries and analysis
years.
Table Y- 18 shows the calculated emissions per unit of energy delivered to end
users, by individual pollutant ( without CO2- equivalency weights) and feedstock/ fuel
combination. For economy of presentation, these results are shown for the U. S. 2010
case only. The importance of upstream emissions of individual pollutants can be
understood better by relating these emissions to end use, which is done in the next
section.
Upstream fuel cycle and material lifecycle emissions expressed relative to end- use
emissions.
One can gain a better understanding of the magnitude of emissions from the
upstream fuelcycle and emissions from the materials lifecycle by expressing them
relative to end- use emissions from vehicles. Thus, Table Y- 25 expresses upstream
emissions of each pollutant as a percentage of end- use vehicular emissions of the
pollutant ( for the U. S. 2010 case) and Table Y- 27 expresses emissions from the materials
lifecycle and vehicle assembly and transport as a percentage of end- use vehicular
emissions ( also for the U. S. 2010 case).
These percentages are interesting in several respects. In all cases, upstream and
materials- lifecycle emissions of CH4 and SOx equal or exceed vehicular emissions,
usually by a wide margin. In most cases, upstream emissions of PM ( BC+ OM) exceed
vehicular emissions. ( A significant exception is that PM emissions from the materials
lifecycle for HDDVs are a small fraction of PM emissions from HDDVs.) This is
significant because all three are potent greenhouse gases, and because on a per- kg basis
SOx and PM are the most damaging of all urban pollutants ( Delucchi, 2000).
Upstream fuelcycle emissions of CO and N2O are relatively minor in the fossil-fuel
lifecycles, but significant in the biofuel lifecycles. In the case of N 2 O, the large
emissions are due to the fixation of N or the use of N fertilizer. Material lifecycle
emissions of CO and N2O are relatively small compared with end- use vehicle
emissions. Upstream and material- lifecycle emissions of NOx and NMOCs generally
are significant fractions of vehicular emissions, and in some fuel cycles ( e. g., ethanol)
38
exceed vehicular emissions. Upstream CO2, NOx, and CO2- equivalent emissions are
large in those fuel cycles in which fuel production is relatively energy intensive ( such as
ethanol, methanol, and hydrogen from natural gas).
My findings with regard to emissions of CO, NO X , CH 4 , and SO 2 from the
“ upstream” ( or well- to- tank) lifecycle of fuels, expressed as a percentage of end- use
( vehicular emissions), are similar to those in Van Mierlo et al. ( 2004). However, Van
Mierlo et al. ( 2004) estimate lower upstream CO 2 and higher upstream NMOC
emissions.
My findings with regards to emissions from the lifecycle of materials used in
vehicles ( Table Y- 27) are similar to those in Maclean and Lave ( 1998) and Tahara et al.
( 2001). For example, Tahara et al. ( 2001) estimate that the lifecycle of automotive
materials emits about 1.6 lbs of CO2 per lb of vehicle, and that assembly emits about 1.0
lbs of CO2 per lb of vehicle. I estimate that the lifecycle of materials emits about 1.5 lbs
of CO2 per lb of vehicle, and that assembly emits about 0.3 lbs of CO2 per lb of vehicle.
It is possible that my estimate of assembly energy do not account adequately for energy
used to assemble parts at establishments not included in the automotive manufacturing
sector.
Gram- per- mile emissions by vehicle/ fuel/ feedstock combination, and stage of the
fuel cycle.
Table Y- 19 presents the final g/ mi results by vehicle/ fuel/ feedstock, and stage
of the fuel cycle. The results are presented for all LDVs, all countries, and all analysis
years.
Comparison of results with IPCC GWPs versus with CEFs estimated here
As indicated by eq. 1d, CO 2 - equivalency factors ( CEFs), which convert gases
other than CO 2 to the amount of CO 2 with some equivalent effect on climate or the
global economy, are an integral part of the calculation of CO 2 - equivalent lifecycle
emissions. Appendix D of the LEM main report documents the development of the
CEFs used in the LEM ( hereinafter referred to as “ LEM CEFs”). As noted in Appendix
D, the LEM CEFs differ in a number of important respects from the widely used CEFs –
called “ Global Warming Potentials,” or GWPs – adopted by the Intergovernmental
Panel on Climate Change ( IPCC). The most important difference is that the IPCC has
not formally estimated CEFs ( qua GWPs) for CO, NMOCs, NO X , SO X , PM and H 2 ( apart
from accounting for the effect of CO and C in NMOCs oxidizing to CO 2 ), whereas we
have ( see Appendix D of the LEM documentation for details):
39
Pollutant Our CEFs ( yr. 2030) IPCC 100- yr. GWPs
NMOC- C 3.664 3.664
NMOC- 0 3 / CH 4 , SOA 3 not estimated
CH 4 14 23
CO 10 1.6
N 2 O 300 296
NO 2 - 4 not estimated
SO 2 - 50 not estimated
PM ( black carbon) 2,770 not estimated
CFC- 12 13,000 8,600
HFC- 134a 1,400 1,300
PM ( organic matter) - 240 not estimated
PM ( dust) - 22 not estimated
H 2 42 not estimated
CF 4 41,000 5,700
C 2 F 6 92,000 11,900
HF 2000 not estimated
In addition, the IPCC GHG accounting methods ignore temporary carbon
sequestration or emission due to changes in land use, whereas we do not. As we discuss
below, the use of IPCC GWPs and methods rather than the LEM CEFs eliminates
significant CO 2 - equivalent emissions related to changes in land use.
How important are the differences between the LEM CEFs and the IPCC GWPs?
In this section, we compare results from the LEM using LEM CEFs with results using
IPCC GWPs, for a selected number of fuel lifecycles.
Results for the U. S. Table Y- 28A presents this comparison for the U. S, for the
year 2010. The table shows the percentage change in the g/ mi emissions going from the
IPCC g/ mi results to the LEM CEF g/ mi results, and two different measures of the
percentage change in emissions relative to gasoline. As one would expect, there are
significant differences in using IPCC GWPs rather than LEM CEFs in those cases where
there are significant differences in emissions of the pollutants for which LEM CEFs
differ significantly from IPCC GWPs – PM, SO 2 , and ( perhaps surprisingly) CO – or else
significant emissions associated with changes in land use ( which are counted in the
LEM CEF case but not in the IPCC GWP case).
Three of the four lifecycles in which the differences between the IPCC- GWP
results and the LEM- CEF results are large – diesel ICEVs, corn ethanol, and cellulosic
ethanol – all involve significant emissions of PM or CO. The significant differences
between the LEM CEF case and the IPCC GWP case for corn ethanol and cellulosic
40
ethanol are due also to the different treatment of emissions related to changes in land
use. This is discussed more in the next section.
The other lifecycle for which LEM CEFs and IPCC GWPs differ significantly is
that of battery EVs using coal- based electricity. In this case, SO 2 emissions make
lifecycle CO 2 - equivalents significantly lower when using LEM CEFs as opposed to IPCC
GWPs because the LEM CEF for SO 2 is negative. In fact, in the case of battery EVs from
coal, pollutant- by- pollutant tests indicate that nearly 100% of the difference between the
results with LEM CEFs and the results with IPCC GWPs is due to SO 2 . PM emissions
don’t matter at all in this case because U. S. power plants are estimated to emit very low
levels of PM in 2010, and because PM from coal boilers – unlike PM from diesel fuel –
contains relatively little black carbon.
The case of diesel ICEVs warrants further comment. In this case, the impact of
switching from LEM CEFs to IPCC GWPs depends almost entirely on emissions of PM
from diesel LDVs relative to emissions of PM from gasoline LDVs. The LEM assumes
that diesel LDV model years prior to 2005 have an order of magnitude larger PM
emissions, but that model years 2005 and later have only twice the PM emissions of
gasoline LDVs. In the cases analyzed here, diesel LDVs are estimated to be model year
2005, and hence to have relatively low PM emissions. Thus, in the cases presented here
the difference between IPCC GWPs and LEM CEFs is only modest, albeit not trivial.
However, if diesel LDV PM emissions are at least an order of magnitude higher than
gasoline LDV PM emissions, then switching from IPCC GWPs to LEM CEFs changes
the results for diesel vehicles from a significant reduction in lifecycle emissions
compared with gasoline to a significant increase. In this case, whether or not one
accounts for the warming impact of PM has a decisive impact on the overall
attractiveness of diesel relative to gasoline. Of course, if one assumes that PM emissions
from diesel LDVs are the same as PM from gasoline LDVs, then the LEM CEFs give
roughly the same results as do the IPCC GWPs.
In all other cases analyzed, with one modest exception, the difference between
using IPCC GWPs and LEM CEFs is relatively small. The modest exception is that in the
case of FCEVs using hydrogen from water, life- cycle emissions are slightly higher with
LEM CEFs than with IPCC GWPs. This is because a water- to- hydrogen system leaks
modest amounts of hydrogen, which has a non- trivial impact on climate that is
accounted for by LEM CEFs but not by IPCC GWPs. ( Impacts of leaks of hydrogen are
discussed further in section “ Leaks of hydrogen” of this report.) However, this
difference in lifecycle emissions does not materially affect the attractiveness of this
hydrogen pathway compared with gasoline, because emissions are much lower than
with gasoline regardless of the CEFs used.
Results for other countries. Parts B, C, and D of Table Y- 28 show the comparison
of LEM CEFs with IPCC GWPs for Japan, China, and Germany, again for the year 2010.
The comparison for Japan is qualitatively similar to the comparison for the U. S. just
discussed. Although there are major differences between total lifecycle emissions in
Japan versus in the U. S., what is of interest here are emissions with LEM CEFs versus
emissions with IPCC GWPs, and those differences vary far less from country to country
41
than do differences in absolute or total emissions. In this respect, only two differences
between the results for Japan and the results for the U. S. are notable. First, there is less
difference between gasoline and battery EVs using coal- based power in Japan than
there is in the U. S, because coal in Japan is assumed to have less sulfur than in the U. S.,
and because coal- fired power plants in Japan are assumed to have tighter SO 2 emission
controls than in the U. S. This results in lower SO 2 emissions in Japan and hence less of
an effect due to the CEF for SO 2 .
Second, hydrogen losses from the water- to- hydrogen system are more
pronounced in Japan than in the U. S., and as a result whether or not one includes a CEF
for hydrogen has a greater impact in Japan than in the U. S. However, the attractiveness
of hydrogen relative to gasoline remains qualitatively the same in both countries
regardless of the CEFs used.
The results for China ( Y- 28C) are interesting in several respects. First, in China
the use of LEM CEFs rather than IPCC GWPs has an especially significant effect on
lifecycle emissions of diesel fuel, cellulosic ethanol, and battery EVs from coal. In the
case of diesel fuel, this is because the projected continued large emissions of PM from
diesel- fuel vehicles in China. In the case of cellulosic ethanol, it is because of significant
emissions related to changes in land use, counted in the LEM CEF case but not the IPCC
GWP case. In the case of battery EVs from coal, it is because of the high level of SO X
emissions from power plants in China, which as mentioned above serve to significantly
decrease lifecycle emissions in the LEM CEF case compared to the IPCC GWP case.
The results for Germany, shown in Table Y- 28D, are sufficiently similar to the
results already shown ( especially to those for the U. S.) that no further discussion is
warranted.
Notes on results for China. Kreucher et al. ( 1998) have estimated emissions of
CO 2 , SO 2 , NO x , CO, THC, and PM from the lifecycle of fuels and vehicles for several
coal- based feedstock/ fuel/ vehicle combinations in China: coal to gasoline or methanol,
coal to electricity, coal or coke- oven gas to methanol, byproducts to methanol, and ( for
comparison) crude oil to gasoline or diesel fuel. For these combinations, they show
upstream fuelcycle emissions of each pollutant assuming state- of- the art emission
factors, and also assuming EPA’s AP- 42 emission factors. We can compare our
estimates of upstream fuelcycle emissions ( in g/ million BTU) with theirs for oil- to-gasoline,
oil- to- diesel, coal- to- methanol, and gas- to- methanol. All of our upstream
emission factors ( all pollutants, all fuelcycles) are higher ( in some cases, several- fold
higher) than the “ state- of- the- art” emission factors of Kreucher et al. ( 1998). Moreover,
our estimates for CO 2 , CO, NO x , and ( we infer) CH 4 in all cases are higher than the “ EPA
AP- 42” emission factors of Kreucher et al. ( 1998). Our estimates of PM emissions lie
between the Kreucher et al. ( 1998) “ state- of- the- art” and “ EPA AP- 42”) cases. We
cannot readily explain the differences between the sets of estimates.
42
Comparison of results using IPCC methods for estimating emissions from land- use
changes with results using our methods.
Our methods for estimating GHG emissions related to land- use changes are
similar to those outlined by the IPCC ( 1997, chapter 5) except for this key difference: we
use a time- varying discount rate with a very long time horizon ( see Appendix D)
whereas the IPCC apparently assumes a zero discount rate but suggests using a 100-
year time horizon ( e. g., IPCC, 1997, pp. 5- 34 and 5- 35). As discussed in Appendix D of
Delucchi ( 2003), the value of the discount rate can have a significant effect on estimated
CEFs. In this section, we will show that value of the discount rate also can have a
significant effect on estimated GHG emissions related to land- use changes.
The Main Report of Delucchi ( 2003) provides a brief discussion of how the
discount rate ( and time horizon) affect GHG emissions related to land- use changes. Our
methods and the IPCC methods both assume that any initial change in land use – say,
the clearing of forest to plant crops – eventually is reversed when the program that gave
rise to the initial change ( planting crops, in our example here) is abandoned. Following
abandonment, the carbon content of the soils and biomass begins a gradual return to
the original values ( in our example, those of a forest). If the discount rate is zero and the
carbon content after reversion is the same as the original carbon content ( and if the
complete reversion occurs within the time horizon – 100 years in the IPCC
recommendations), then the net carbon emission due to the program is zero. However,
if the discount rate is not zero, then the present value of the future carbon gain
following reversion is less than the value of the carbon loss at the start of the program,
resulting in a non- zero net emission due to the program.
As shown in the LEM main report, emissions related to changes in land use can
be significant in biofuel lifecycles. As a result, whether one uses the LEM CEFs ( which
incorporate a non- zero discount rate, and hence count emissions related to land- use
changes) or the IPCC GWPs ( which ignore emissions related to changes in land use) can
have a big impact on absolute and relative emissions in biofuel lifecycles. Indeed, much
of the difference between the LEM CEF results and the IPCC GWP results for biofuel
lifecycles in Tables Y- 28 A, B, C, and D are due to just this difference in the treatment of
emissions related to changes in land use.
Uncertainty in important parameter values
All parameter values are uncertain to some degree. In some cases, the
uncertainty is great enough, and the parameter values important enough, to
significantly affect the certainty of the overall results. The most important uncertainties
in this analysis are:
43
• The CO2- equivalency factors ( CEFs) for all non- CO2 greenhouse gases. The
uncertainty in the CEFs for CH4, N2O, N ( as NOx, or nitrogen in fertilizer), SO2, and
PM can have a significant effect on the overall results. The uncertainty in the CEFs for
CO and NMOCs is less important: varying these CEFs over their likely range of values
does not significantly affect the results. See Appendix D of Delucchi ( 2003) and the
comparison of our CEFs with IPCC GWPs in this report for further discussion.
• Efficiency of end use. In all fuel cycles, the efficiency of energy end use is
important and still uncertain. In particular, in the EV cycle, the major uncertainty
remains the relative energy use of EVs ( both BPEVs and FCEVs) although the new
energy- use model described briefly in Appendix G of Delucchi ( 2003) has helped to
narrow that uncertainty. The effect of the mix of fuels used to generate power is
reasonably well reflected in the regional results.
There also is non- trivial uncertainty in the composition and cycle life of batteries
for EVs. The cycle life is important because the shorter the cycle life ( in miles of travel),
the higher the g/ mi lifetime emissions.
• The evolution of fuel- production technology. Generally, I have assumed that
production processes will continue to get more efficient, and gradually switch from
high- emitting to low- emitting process fuels. Historically there is some justification for
these assumptions. For example, in the 1980s, high fuel prices led to considerable
improvements in the fuel efficiency of corn- to- ethanol conversion processes, and
environmental and other considerations spurred a switch from coal to natural gas. It is
not clear, however, to what extent these trends can be expected to continue. And the
problem of prediction is even more difficult for those technologies, such as wood- to-ethanol,
that are still being developed.
• Emissions related to changes in cultivation and land use. In the biomass fuel
cycles, the most uncertain and important parameters, aside from those mentioned
above, are those that represent which land uses ( e. g., forests, pasture land, or
agricultural land) are replaced by which energy crop systems ( corn, soybeans,
switchgrass, or SRIC trees), and those pertaining to N2O emission related to nitrogen
fertilizer inputs. In some cases ( e. g., the biodiesel fuel cycle), uncertainty regarding N
inputs can have an enormous impact on fuel cycle CO2- equivalent emissions.
• The effect of quantity changes on prices and hence demand and, ultimately,
supply in other markets. In a few instances I account, crudely, for economic effects in
the markets for products related to the co- products of fuel cycles ( e. g., in markets for
electricity affected by the generation of power from excess lignin in biomass- to- ethanol
plants). The values of these parameters are uncertain and can significantly affect
fuelcycle CO 2 - equivalent emissions. ( See the longer discussion above, and the
exploratory discussion in Delucchi [ 2002].)
44
REFERENCES
P. Ahlvik and A. Brandberg, Well to Wheels Efficiency for Alternative Fuels from Natural
Gas or Biomass, Publication 2001: 85, Swedish National Road Administration, October
( 2001).
CONCAWE, EUCAR ( European Council for Automotive Research and Development),
and ECJRC ( European Commission Joint Research Centre), Well- To- Wheels Analysis of
Future Automotive Fuels and Powertrains in the European Context, Well- to- Wheels Report,
Version 1b, January ( 2004). Available on the web at
http:// ies. jrc. cec. eu. int/ Download/ eh.
M. A. Delucchi, A Lifecycle Emissions Model ( LEM): Lifecycle Emissions from Transportation
Fuels, Motor Vehicles, Transportation Modes, Electricity Use, Heating and Cooking Fuels, and
Materials, UCD- ITS- RR- 03- 17, Institute of Transportation Studies, University of
California, Davis, December ( 2003). To be revised June ( 2005). Approx. 370 pp. With
appendices shown below. Available at www. its. ucdavis. edu/ faculty/ delucchi. htm.
Appendix A: Energy use and emissions from the lifecycle of diesel- like fuels
derived from biomass ( 20 pp.)
Appendix B: Data for other countries ( 81 pp.)
Appendix C: Emissions related to cultivation and fertilizer use ( 73 pp.)
Appendix D: CO 2 - equivalency factors ( 115 pp.)
Appendix E: Data on methane emissions from natural gas production, oil
production, and coal mining ( 24 pp.)
Appendix F: Emissions of nitrous oxide and methane from alternative fuels for
motor vehicles and electricity- generating plants in the U. S. ( 74 pp.)
Appendix G: Parameters calculated with the EV and ICEV energy- use and
lifecycle- cost model ( 8 pp.)
Appendix H: The lifecycle of materials ( 103 pp.)
Appendix J: Emission factors for heavy- duty diesel vehicles (~ 25 pp.)
Appendix Y: Some results from the LEM (~ 50 pp.)
Appendix Z: References to the Main Report ( 47 pp.)
M. A. Delucchi, Incorporating the Effect of Price Changes on CO2- Equivalent Emissions from
Alternative- Fuel Lifecycles: Scoping the Issues, for Oak Ridge National Laboratory, Oak
Ridge, Tennessee, June ( 2002).
M. A. Delucchi, “ Environmental Externalities of Motor- Vehicle Use in the U. S.,”
Journal of Transport Economics and Policy 34: 135- 168, May ( 2000).
45
M. A. Delucchi and D. McCubbin, The Contribution of Motor Vehicles and Other Sources to
Ambient Air Pollution, Report # 16 in the series: The Annualized Social Cost of Motor- Vehicle
Use in the United States, based on 1990- 1991 Data , UCD- ITS- RR- 96- 3 ( 16), Institute of
Transportation Studies, University of California, Davis, November ( 1996).
M. A. DeLuchi, Emissions of Greenhouse Gases from the Use of Transportat