Table 12. Cumulative Power Sector and Household Emission Reductions for High & Low

Economic Growth Sensitivities to 2030

Shipment Drop AE099 Low Economic

Growth

AE099 Reference Economic

Growth

AE099 High Economic

Growth

MEF = 1.04 in 2004 & 1.26 in 2007 (PROPOSED MEF)

Carbon(Mt) 93.8 95.1 9.6

NO,, (kt) 292.7 253.5 2485

S02(kt)

________________________ ____________________- _______________________

Table 13. Cumulative Power Sector and Household Emission Reduction with Elasticity

Sensitivities to 2030

Shipment Drop Sensitivity

Price / Income = medium

Price Elasticity = none

Reference Case

Price Elasticity =

medium

Price I Income = none

Sensitivity

Price Elasticity = high

Price I Income = none

MEF = 1.04 in 2004 & 1.26 in 2007 (PROPOSED MEF)

Carbon (Mt) 97.3 95,] 94.4

NO(kt) 256.2 253.5 254.3

S02(kt) 28.7 ] 276

5.2 Water Resources

The measurement of the MEF and the DOE minimum efficiency level do not have as a

condition a set maximum water usage. However, energy savings are often achieved by reducing

the hot water consumption and in some cases the total water consumption for a wash cycle.

Table 14 lists the cumulative reduction in water use through 2020 for each of the efficiency

levels. Water savings are based on the results of a manufacturer questionnaire detailing energy

and water use of clothes washers under the various efficiency standard scenarios.

EA- 19

EE-RM-PET-100 COMMENT 88
Table 14. Cumulative Reduction in Water Use to 2030

MEF

Parameter

0.86 0.908 0.961 1.021 1.089 1.257 1.362 1.485 1.634 1.04 in 2004

1.26 in 2007

TSL 1 TSL 2 TSL 4 TSL 5 TSL 6 TSL 3

(PROPOSED

MEF)

Trillion 0.41 0.41 0.41 0.53 9.09 12.9 12.9 10.9 10.9 11.59

Gallons

The proposed standard would result in significant water savings which amounts to 11.59

trillion gallons through the period 2004 - 2030. This means less water needs to be pumped from

U.S. aquifers and rivers, and less strain on many of the nation's overtaxed water and sewer

systems. The standards will save enough in less use water to supply the needs of 7.3 million

households for 25 years (based on indoor water use). Results of a sensitivity analysis for high

and low economic growth and high and low forecasts of price elasticity (i.e., number of washer

shipments) are shown below in Tables 15 and 16.

Table 15. Cumulative Water Reduction for High & Low Economic Growth Sensitivities

to 2030

Shipment Drop AE099 Low Economic AE099 Reference Economic AE099 High Economic

Growth Growth Growth

MEF = 1.04 in 2004 & 1.26 in 2007 (PROPOSED MEF)

Trillion Gals Water 11.58 11.59 11.59

Table 16. Cumulative Water Reduction with Elasticity Sensitivities to 2030

Shipment Drop Price / Income = medium Reference Case Price Elasticity = high

Price Elasticity = none Price Elasticity = Price I Income = none

medium

Price / Income = none

MEF = 1.04 in 2004 & 1.26 in 2007 (PROPOSED MEF)

Trillion Gals Water 11.8 11.59 11.5

EA-20

EE-RM-PET-100 COMMENT 88
5.3 Wetlands I Endangered and Threatened Species / Cultural Resources

As this action is not a site-specific action, nor would it change land disturbance due to

clothes washer placement, impacts to these resources are not expected. Therefore, this action is

not expected to impact the quality of wetlands, or threatened or endangered species, although

lowered national water use and reduced air pollution could have a positive impact, if any at all.

This action is not expected to impact cultural resources such as historical or archaeological sites.

5.4 Socioeconomic Impacts

Analysis has shown that the possible increase in the first cost of purchasing a more

efficient clothes washer is on average offset by a reduction in the life-cycle cost of owning a

more efficient washer. This is true for every standard level considered. Although the proposed

standard may increase the initial cost of a clothes washer, the proposed standard level has a

decrease in life-cycle cost (due to reduced energy and water costs) for 90% of consumers at the

first stage in 2004 and for 80% of consumers at the second level of the standard becoming

effective in 2007. See chapter 7 and Appendix G of the TSD for details.

5.5 Environmental Justice Impacts

The proposed action, a new minimum efficiency standard for clothes washers, would not

cause any adverse environmental impacts, and therefore would not cause any disproportionately

high and adverse human health or environmental impacts. Positive impacts, such as decreased

air emissions and water conservation, would be equally shared among all populations. However,

the department did conduct a consumer utility analysis that looked at economic impacts to lowincome and elderly populations. For a complete discussion see chapter 8 and Appendix K of the

TSD at the DOE internet site at

http://www.eren.doe.govlbuildings/codes_standards/applbrf/clwasher.html.

5.6 Energy Consumption Impacts

The proposed standard level of a 1.04 MEF in 2004 and a second higher level of 1.26

MEF in 2007 (TSL 3) would result in the energy savings through the year 2030 shown in Table

17, when compared against the no-action alternative.

EA-21

EE-RM-PET-100 COMMENT 88
Table 17. Cumulative Energy Savings for Trial Standard Level 3 (Proposed MEF)

Cumulative Energy Savings in Quads

Total Electric Gas Oil LPG

from 2004

to 2010 0.39 0.23 0.14 0.01 0.01

to 2020 2.51 1.47 0.93 0.06 0.05

To 2030 5.52 3.23 2.05 0.14 0.1

5.7 Summary of Environmental Impacts

This BA provides information on the effects new clothes washer standards would have on

pollutants and other emissions as well as on water use. Analysis of carbon and NO emissions

from the power sector and households indicates that each of the proposed trial standard levels

would have a positive impact on the environment. Cumulative power sector and household

emissions reductions through 2020 for the proposed standards range from 2.5-65 Mt for carbon

and 8.4-210 kt for NOR. Through 2030, the cumulative emissions reductions range from 5.1-135

Mt for carbon and 14.4-364 kt of NOR. The reduction in SO2 emissions ranges from 0.6-15.5 kt

through 2020 and from 1.2-31.4 kt through 2030. The corresponding reduction in water use

through 2030 ranges from 0.4 1-12.94 trillion gallons of water.

The major stakeholders, including manufacturers and energy efficiency advocates, have

jointly submitted a proposed clothes washer efficiency standard to DOE that they both feel is

technically feasible and economically justified. The proposed standard, which is the

Department's proposed action for purposes of this EA, would go into effect in two stages. The

proposed standard level of a 1.04 MEF (Modified Energy Factor) in 2004 and a second higher

level of 1.26 MEF in 2007 would have the following cumulative reductions in emissions. By the

year 2025, the annual reduction in fuel needed to generate electricity will be equivalent to the

amount needed to run five large coal-fired power plants. (This is equivalent to an annual savings

of 0.18 quads of source energy, 0.086 quads of site energy or 24 Tera watt-hours (TWh) of

electricity sales). The proposed standard will save enough electricity to light 16 million U.S.

homes for 25 years, while cutting greenhouse gas emissions by an amount equal to that produced

by three million cars every year. The proposed standard has significant environmental benefits.

Cumulative emissions reductions through 2030 are 95.1 Mt (million metric tons) for carbon,

253.5 kt (thousand metric tons) for NOR, 28.1 kt for SO2. Water use reductions are 11.59 trillion

gallons cumulative to 2030. This means less water needs to be pumped from America's aquifers

and rivers, and less strain on many of the nation's overtaxed water and sewer systems. The

standards will save enough water to supply the indoor water usage needs of 7.3 million

households for 25 years.

EA-22

EE-RM-PET-100 COMMENT 88
REFERENCES

U.S. Department of Energy-Office of Building Research and Standards, Technical

Support Document: Energy Efficiency Standards for Consumer Products: Clothes

Washers, September, 2000. Washington, DC.

2. Title, Code of Federal Regulations, Part 430, Docket No. EE-RM-94-403, RIN 1904-

AA67, Energy Conservation Program for Consumer Products: Clothes Washer Energy

Conservation Standards; Proposed Rule, October 5, 2000, Federal Register.

3. U.S. Department of Energy - Energy Information Administration, Annual Energy Outlook

1999: With Projections Through 2020, December, 1998. Washington, DC. Report No.

DOE/EIA-03 83(99). <http://www.eia.doe.govfoiaf/aeo99/homepage.html>

EA-23

EE-RM-PET-100 COMMENT 88
APPENDIX EA.1. EMISSION FACTORS FOR COMBUSTION FROM NATURAL GAS,

LPG, AND OIL-FIRED RESIDENTIAL WATER HEATERS AND CLOTHES DRYERS

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TABLE OF CONTENTS

EA-1 OVERVIEW EA.1-1

EA-2 EMISSIONS FACTORS BY FUEL TYPE EA.1-2

EA-2.1 All Fuels: Carbon EA.l-2

EA-2.2 Natural Gas EA.l-2

EA-2.2.1 Oxides of Nitrogen EA.1-2

EA-2.2.2 Sulfur Dioxide EA. 1-3

EA-2.3 Fuel Oil #2 EA.1-3

EA-2.3.1 Oxides of Nitrogen EA.1-3

EA-2.3.2 Sulfur Dioxide EA.l-3

EA-2.4 LPG EA.1-4

EA-2.4.1 Oxides of Nitrogen EA.l-4

EA-2.4.2 Sulfur Dioxide EA.1-5

EA-3 SUMMARY EA.1-5

LIST OF TABLES

Table EA- 1.1 Estimated National Average Emission Factors for Household Fuel

Combustion of Natural Gas, Fuel Oil #2, and LPG EA.1-2

EA.1-i

EE-RM-PET-100 COMMENT 88
APPENDIX EA-1. EMISSION FACTORS FOR COMBUSTION FROM NATURAL GAS,

LPG, AND OIL-FIRED RESIDENTIAL WATER HEATERS AND CLOTHES DRYERS

EA-1 OVERVIEW

The modified version of the National Energy Modeling System (NEMS) used for the

appliance energy efficiency standards analysis, called NEMS-BRS, comprehensively considers a

wide range of aspects of energy use.a However, this model does not consider household emissions

of SO2 and NO from the combustion of natural gas, heating fuel oil #2 (i.e., high-sulfur distillate

fuel oil), and liquefied petroleum gas (LPG). Because an efficiency standard could result in changes

in these emissions, the Department has performed some elementary research to determine

appropriate emission factors for carbon, sulfur dioxide (SO2), and oxides of nitrogen (NO) from

household appliances. Specifically, this work focuses on emission rates from the use of water

heaters and clothes dryers and is used to calculate emissions savings from proposed efficiency

standards on clothes washers.

This analysis attempts to verify that the emissions factors from the U.S. Environmental

Protection Agency (EPA) for carbon, SO2, and NO from natural gas, fuel oil, and LPG combustion

are representative of the U.S.' The EPA cautions against the use of these emissions factors as

representative of actual emissions. Rather, they are to be used, and are used here, as general

approximations of national average emissions factors in order to calculate emissions savings that

result from proposed water heater or clothes washer energy-efficiency standards. This analysis

compares EPA's emissions factors with those from other sources and with regional regulations.

Table EA- 1 summarizes the emissions factor estimates for the three fuels of interest. The

values presented here are based on EPA' s assessment of combustion emissions (with the exception

of SO2 from LPG, see discussion below). These emissions estimates represent an approximate

emissions factor for the U.S. as a whole. They are used, together with estimated energy savings, to

calculate end-use site emissions savings. The emissions factors discussed in this analysis are

represented as mass, grams (g) or kilograms (kg), of the specific emission of interest per gigajoule

(GJ) of energy input to the water heater or clothes washer."

There are significant differences in state regulations, making it difficult to generalize about

localized emissions. For residential fuel oil combustion, stricter state standards exist in the

northeastern United States and southern California than elsewhere. State and local agencies like

aFor more information on NEMS, please refer to the U.S. Department of Energy, Energy Information Administration

documentation. A useful summary is National Energy Modeling System. An Overview 1998, DOE/EIA-058 1(98), February

1998. DOE/ETA approves use of the name NEMS to describe only an official version of the model without any modification to

code or data. Because our analysis entails some minor code modifications and the model is run under policy scenarios that are

variations on DOE/ETA assumptions, the name NEMS-BRS refers to the model as used here (BRS is DOE's Building Research

and Standards office, under whose aegis this work has been performed).

b

0.454 kg = 1 pound (lb); 1.055 GJ = 1 million British thermal units (MBtu)

EA. 1-1

EE-RM-PET-100 COMMENT 88
southern California's South Coast Air Quality Management District (SCAQMD), the New Jersey

Department of Environmental Protection, and the New York Department of Environmental

Conservation have established regulations for residential fuel combustion emissions. These

regulations, however, are local to individual counties and do not apply to all regions in the Northeast

or even all of California.

Table EA-1.l Estimated National Average Emission Factors for Household Fuel

Combustion of Natural Gas, Fuel Oil #2, and LPG

___________________

Carbon

(kgIGJ)

SO2

(gIGJ)

NO,

(g/GJ)

Natural Gas 13.8 0 42

HeatingFuelOil#2 18.7 218 61

LPG 16 7.2 66

EA-2 EMISSIONS FACTORS BY FUEL TYPE

EA-2.1 All Fuels: Carbon

NEMS-BRS tracks emissions of carbon as C02, but factors are included here for

completeness. The combustion of natural gas, fuel oil #2, and LPG oxidizes virtually all carbon in

the fuel to CO2. This facilitates estimating carbon emissions factors because the carbon content of

the fuel is the only determinant of emissions. The carbon estimates in Table EA- 1.1 are based on

EPA's assessment of carbon combustion from natural gas, fuel oil #2, and LPG use. Other sources

of information include the U.S. DOE' s Energy Information Administration (EIA), Oregon State

EPA, and the Gas Research Institute (GRJ). All agree to within ± 2.0 % of EPA's assessed estimate

of carbon emissions. EPA's carbon emissions factors for natural gas, fuel oil #2, and LPG

combustion are therefore a reasonable evaluation of nationally averaged carbon emissions rates.

Carbon monoxide (CO) can be formed by incomplete carbon oxidization, causing a severe

health hazard. CO emissions only result from poorly ftmctioning appliances, and since NEMS-BRS

assumes that all water heaters or clothes washers are functioning properly, it is unlikely that these

emissions will change.

EA-2.2 Natural Gas

EA-2.2.1 Oxides of Nitrogen

Emissions of NO that result from the combustion of natural gas from appliances are also

covered by regulations in some jurisdictions. The EPA's estimated NO emissions factor of 42 g/GJ

from gas-fired water heaters or clothes washers is equal to the regulation set by the state of New

York. This is approximately 20% higher than the strict standard set by the South Coast Air Quality

EA. 1-2

EE-RM-PET-100 COMMENT 88
Management District (SCAQMD). The SCAQMD provides extensive research into emissions

factors2 and California regulations tend to influence many other states. New Jersey is the only other

state that is known to have NO emissions regulations for water heaters, with a limit of 86g of

NO/GJ of heat input. The absence of regulations in other states suggests that most have emissions

rates comparable to U.S. EPA's estimated value.

EA-2.2.2 Sulfur Dioxide

SO2 emissions from natural gas combustion are assumed to be zero.

EA-2.3 Fuel Oil #2

EA-2.3.1 Oxides of Nitrogen

N0 formation in combustion processes is significantly more complex than SO2 or CO2. N0

can result from oxidization of N2 in the fuel, but the larger source is N2 in the combustion intake.

This process is sensitive to combustion chemistry, and therefore, quite variable. It also implies that

appliance design can lower N0 emissions. An added difficulty is that the potential hazard of

residential N0 emissions is also hard to quantify. N0 is both an acid precipitation and ozone (03)

precursor, but because residential appliances are a relatively small and dispersed (i.e., hard to

monitor) source, these emissions tend to play a small role in NO control strategies. The 03 hazards

of NO emissions are highly variable both spatially and over time, as weather conditions favor or

disfavor 03 formation. One would, therefore, expect NO emissions rules to vary significantly across

jurisdictions.

The value estimated by EPA of 61 g of NOX/GJ is for distillate oil-fired boilers with a

combustion rate less than 106 GJlhour (or 100 MBtu/hour) of heat input. This combustion type is

characteristic ofresidential water heaters or clothes washers.3 Additional research into specific state

regulations reveals good matches with the U.S. EPA's emissions factor: New Hampshire limits N0

emissions to 60 g/GJ for non-utility boilers and New York and New Jersey regulations cap emissions

at 52 g ofN0/GJ. These state limits confirm that the U.S. s estimate can serve as a reasonable

national average.

EA-2.3.2 Sulfur Dioxide

Emissions of SO2 are a direct function of the sulfur content of the fuel. Assuming complete

combustion of sulfur to SO2 makes it easy to assess and compare emissions across data sources.

Individual state and county regulations limiting the amount of sulfur in residential fuel oil, however,

reveal substantial variability in SO2 emissions factors from the U.S. EPA's estimate of 218g of

SO2IGJ of fuel energy content. This is roughly equivalent to 0.5% sulfur content by weight using

an emissions factor for fuel oil #2 of 43,950 gIGJ weight per unit energy content. A straight

multiplication of the fuel energy content and the percentage of sulfur content in the fuel provide the

emissions factor.

EA. 1-3

EE-RM-PET-100 COMMENT 88
In the state of New York, SO2 emissions limits range from 8 8-659 g/GJ depending on the

county. In New Hampshire, the emissions rate of SO2 from high-sulfur distillate fuel oil combustion

cannot exceed 176 g/GJ. In Maine and Michigan, the regulations are higher than the U.S. EPA's

assessment, limiting SO2 emissions from fuel oil to 500 g of S02/GJ of heat input. Such broad

ranges and varying limits in certain regions are a strong argument for using EPA' s averaged national

value over a regionally weighted average incorporating the various state and county regulations.

Comparing the sulfur content of fuel oil from different refineries also demonstrates regional

variability. Most sources were obtained through online web sites detailing product specifications.

Mobil Corporation's residential heating fuel oil (#2 high-sulfur) for most states contains a maximum

0.5% sulfur by mass (219 g of 502/GJ of heat input), which is very close to EPA's emissions factor.

Mobil also markets fuel with lower sulfur content to some regions in the Northeast. For example,

Mobil's lowest sulfur content residential heating fuel oil contains 0.2% sulfur by weight (88 gIGJ),

as required in New York City, Philadelphia, parts of Delaware, and most of New Jersey. Other

regional regulations adhered to by Mobil are 132 g/GJ for most of Pennsylvania and parts of New

Jersey, a limit of 127 g of S02/GJ of heat input for the state of Illinois, and an SO2 emissions factor

of 145 g/GJ in Massachusetts. The sulfur contents of distillate fuel oil from Chevron, Phillips 66,

and the American Society for Testing and Materials (AS TM) exactly match the U.S. EPA' s estimate,

substantiating the use of the latter for the analysis. Considerable variation does exist among counties

and states, especially in the Northeast. Nonetheless, EPA provides a reasonable estimate of

emissions from residential oil-fired water heaters that is representative of the national average.

EA-2.4 LPG

EA-2.4.1 Oxides of Nitrogen

Although NES results are presented for LPG, EPA estimates emissions for only propane

and butane, fuels within the LPG family of gases. In the United States, the composition of LPG is

typically 90% propane (C3H8) by liquid volume, 5% propylene (C3H6), and 2.5% butane (C4H10).4

This analysis uses the U.S. EPA's propane emissions estimate to verify its comparability with LPG

combustion or determines a more suitable estimate from other sources that best represents LPG

emissions rates.

EPA estimates an emissions factor of 66 g of NOIGJ of energy input from propane-fired

water heaters, which is slightly higher than the natural gas estimate. The University of New

Hampshire's Energy Office estimates an emissions factor of 43 g/GJ from LPG combustion for the

state of New Hampshire. In contrast, the state of New Jersey's EPA establishes an 86 g/GJ

emissions factor. Both sources, therefore, support EPA's national assessment ofNO emissions from

residential propane combustion.

EA.1-4

EE-RM-PET-100 COMMENT 88
EA-2.4.2 Sulfur Dioxide

The sulfur content of LPG is very low5 although a few regulations exist in certain parts of the

country. The U.S. EPA's SO, emissions estimate is derived from the sulfur content of the propane

fuel. With 90% of LPG comprised of propane, the EPA's propane emissions factor is a reasonable

value for LPG emissions rates. Under the New Hampshire Department of Environmental Services

(DES) regulation, the maximum sulfur content allowable is 13.3 g/GJ of SO2 from LPG combustion.

The San Diego County Air Pollution Control District enforces a stricter limit of only 8.8 g of SO2IGJ

of energy input using the U.S. EPA's recommended value. Both the ASTM and Santa Barbara

County Air Pollution Control District specify a sulfur standard of 0.0185% sulfur by weight, which

approximates an emissions factor of 4.0 g of S02/GJ of energy input. This calculation is based on

an LPG weight per unit energy of 21,756 g/GJ. Even lower, Nett Technologies Inc. estimates a

0.0 12% sulfur content by mass LPG average for the United States as well as Canada, which is

approximately 2.6 g of S02/GJ of heat input.

The wide range of emissions factors for SO2 makes it difficult to determine a representative

estimate for the emissions factor and the very small net effect of any energy-efficiency standard

argue against making a significant research effort. The obtained estimates range in magnitude from

approximately 4 to 13 g/GJ of energy input. The statistical average or arithmetic mean of these four

estimates is 7.2 g/GJ, the value provided in Table EA- 1. The averaged emissions factor estimate of

7.2 g/GJ energy input is reasonable to explain three of the five sources presented and suitably

accounts for the average among the two extreme estimates. Table EA- 1 therefore adequately

represents national SO2 emissions from residential LPG combustion.

EA-3 SUMMARY

This investigation of emissions factors from natural gas-, fuel oil-, and LPG-fired residential

water heaters andlor clothes washers indicates that using the values estimated by EPA's AP-42 is

a robust and credible basis for analysis with NES output. This analysis indicates that regulations at

the state and county level, especially in the northeastern region of the United States, are generally

not good estimators of the national average set forth by the EPA AP-42 report. This is especially

true for SO2 emissions factors from fuel oil combustion where individual state and county

regulations are highly variable. Thus, although it is worthwhile examining regional legislation to

support the national average, this analysis demonstrates the complexity that would be required to

establish a weighted regional calculation for each emission. EPA' s own lack of data on the sulfur

content ofLPG made it difficult to derive a nationally representative emissions factor for the country

as a whole. External sources were therefore incorporated in the Table EA- 1 estimate for SO2

emissions from LPG combustion.

EA. 1-5

EE-RM-PET-100 COMMENT 88
REFERENCES

1. U.S. Environmental Protection Agency, Compilation ofAirPollutant Emission Factors, AP42, Fflh Edition, Volume I. Stationary Point and Area Sources, 1998. October.

<http :I/www.epa. gov/ttn/chief/ap42.html>

2. South Coast Air Quality Management District, March, 1995. <http:I/www.aumd.gov/

rules/ri 121.html>

3. New Jersey State Department of Environmental Protection, September 1993.

<http://www.state.ni .us/dep/aim127 19968 .htm#Boilers>

4. United States Hemispheric Clean Cities Program, 1994. <http://www.hemisccities.doe. gov/altfuels/propane.html>

5. U.S. Environmental Protection Agency, Compilation ofA irPollutantEmission Factors, AP42, Fifth Edition, Volume I: Stationary Point and Area Sources, Chapter 1, External

Combustion Sources, 1998. October. <http://www.epa. gov/ttnlchief/ap42c 1 .html>

EA.1-6

EE-RM-PET-100 COMMENT 88
APPENDIX EA.2. UPSTREAM EMISSION FACTORS FROM COAL AND NATURAL

GAS PRODUCTION

....................................

TABLE OF CONTENTS

Table EA-2. 1 Estimated Upstream Emission Factors and Relative Percentages to Direct Power

Plant Combustion Emissions EA.2-2

EA.2-i

EE-RM-PET-100 COMMENT 88
APPENDIX EA-2. UPSTREAM EMISSION FACTORS FROM COAL AND NATURAL

GAS PRODUCTION

Tracking of pollutant emissions by the National Energy Modeling System (NEMS) used for

the appliance energy efficiency standards analysis, called NEMS-BRS, is incomplete, with thorough

treatment of some aspects and scant treatment of others.a The approach is also somewhat different

between emissions. Overall, carbon emissions are well covered because they are estimated based

on elemental carbon released as carbon dioxide (C02) from all hydrocarbon combustion. However,

some energy-use effects of proposed standards are not tracked by NEMS-BRS so their effects on

carbon emissions are not counted. For example, the effect of lower residential electricity

consumption on generation is estimated, but not the second order effect on energy consumed in coal

transportation to power plants.

In other words, the amount of energy used to perform the upstream processes in coal and

natural gas production is not linked to the downstream consumption of these fuels. For this reason,

while total carbon emissions are counted, changes due to proposed standards are not. According to

DeLuchi, the amount of energy used to mine and clean the coal is minimal, amounting to less than

1% of the energy available in the coal. The amount of energy required to transport the coal using

trains, trucks, and pipelines is approximately 0.156 exajoules/annually (EJIa) or 0.148 Quads/a as

estimated for the year 2000.1 Based on the AE099 energy consumption of coal from electric

generation, this corresponds to 0.7% of the total energy required by electric generators. For natural

gas production, the amount of energy used to transport natural gas to the end-use consumer is 3.5%

of the total natural gas produced and made available to end-use customers as estimated for the year

2000. For extraction of crude oil, the relative percentage is only 2.8%. Thus, the upstream losses

are small relative to the total amount of energy embodied in the coal, oil, and natural gas and,

therefore, changes due to proposed standards are also likely to be small.

NEMS-BRS tracks only NO and SO2 emissions from power generation. Sources of these

emissions that may be affected by proposed standards are therefore missed. Two notable sources

of NO and SO2 emissions not considered are household emissions from the combustion of natural

gas, liquefied petroleum gas (LPG), and heating fuel oil and emissions associated with fuel

extraction and delivery to the point of combustion.

This analysis considers two uncounted emissions from coal and natural gas production and

delivery, SO2 and NOR. These emissions include those due to the mining of coal or extraction of

natural gas, the physical processes involved in preparing or cleaning the fossil fuel, and the

transportation of the fuel from the mine to the power plant. Household combustion effects of

aFor more information on NEMS, please refer to the U.S. Department of Energy, Energy Information Administration

documentation. A useful summary is National Energy Modeling System: An Overview 1998, DOE/EIA-0581(98), February

1998. DOE/ETA approves use of the name NEMS to describe only an official version of the model without any modification to

code or data. Because our analysis entails some minor code modifications and the model is run under policy scenarios that are

variations on DOE/EIA assumptions, the name NEMS-BRS refers to the model as used here (BRS is DOE's Building Research

and Standards office, under whose aegis this work has been performed).

EA.2- 1

EE-RM-PET-100 COMMENT 88
proposed standards are explicitly included in the appliance energy-efficiency standards analysis and

the methods used are described in Appendix EA- 1.

Studies addressing upstream emissions are very limited. Thus, the reliability of the exact

measurements can be easily criticized. The values presented here are only intended to provide a

coarse estimate of the magnitude of upstream emissions not accounted for in NEMS-BRS. In

general, emissions from mining, cleaning, or transporting fossil fuels are small compared to the

emissions that result from their combustion.

Upstream emissions estimates for carbon and NO are taken from a thorough study done by

M.A. DeLuchi at Argonne National Laboratory in 1993. DeLuchi provides estimates of full fuelcycle emissions factors for emissions of C02, methane (CH4), carbon monoxide (CO), non-methane

organic compounds (NMOC), and NO from coal and natural gas production. An emission factor

for SO2 is taken from the United States Environmental Protection Agency's (EPA) Compilation of

Air Pollutant Emissions Factors, AP-42.2 This source notes that coal cleaning is the primary source

for upstream SO2 emissions from coal production, so the emission factor for SO2 only reflects the

coal cleaning process. Transportation is not addressed in EPA's study.

Emission factor estimates and corresponding percentage contributions of the upstream

emissions relative to power plant emissions are shown in Table EA-2. 1 for carbon, SO2, and NO

from coal and natural gas production. The relative percentage to power plant emissions is provided

so an estimate of upstream emission savings based on the savings from the power plant could be

easily estimated. The values shown in Table EA-2. 1 represent emissions from upstream processes

as mass (g) of deliverable energy to end-use consumers.

Table EA-2.1 Estimated Upstream Emission Factors and Relative Percentages to Direct Power

Plant Combustion Emissions

Coal Natural Gas

%of %of Emission Emission Combustion Combustion Factor (g/GJ) Factor (g/GJ) Emissions Emissions

Carbon 2222 2.7 5456 11.9

SO2 29.2 0.9 0 0

NO 41.7 5.8 153 40

DeLuchi's analysis reveals that upstream processes in coal production relative to power plant

emissions account for 5.8% of NO and 2.7% of carbon. The AP-42 indicates that less than one

EA.2-2

EE-RM-PET-100 COMMENT 88
percent of SO2 emissions result upstream relative to those from coal power plant emissions.

Upstream coal processes, therefore, account for at most 6% of relative power plant emissions for

carbon, SO2, and NOR.

For natural gas production, the upstream 502 emissions are negligible. The upstream

emissions from NOR, however, are quite significant, accounting for 40.0% of emissions relative to

those from the power plant. Total natural gas combustion NO emissions from the power plant are

only half those from coal, while emissions upstream processes are four times those of coal. Carbon

emissions are nearly 12% of power plant emissions with an emission factor of 5456 gIGJ of

deliverable energy; however, as noted above, changes to these emissions are counted by NEMS.

Relative to the entire fuel cycle, DeLuchi estimates that approximately 8% by mass of all

emissions from coal production are due to mining, preparation, and transport from the mine to the

plant. Transportation emissions include those resulting from the use of fuel by the modes of

transportation used to move the fuel from the site of extraction to fuel production facilities. For

natural gas production, 14% of total emissions are estimated to result from upstream processes.

Based on Table EA-2. 1, this higher loss factor in natural gas production is likely due to the higher

NO contribution.

Thus, emissions factors and their relation to power plant emissions are provided to reveal the

relatively small proportion of energy losses attributable to upstream processes. With the exception

of NO emissions from natural gas production, all emissions are less than 12% of power plant

emissions.

EA.2-3

EE-RM-PET-100 COMMENT 88
REFERENCES

DeLuchi, M. A., Emissions of Greenhouse Gasesfrom the Use of Transportation Fuels and

Electricity, Volume 2: Appendixes A-S, November, 1993, Argonne National Laboratory.

Argonne, IL. Report No. ANL/ESD/TM-22-Vol.2.

2. U.S. Environmental Protection Agency, Compilation ofA ir Pollutant Emission Factors, AP42, F?fth Edition, Volume I. Stationary Point and Area Sources, Chapter 1], Mineral

Products Industry, 1995. November. <http://www.epa. ov/ttnIchief/ap42c 11 .html>

EA.2-4

EE-RM-PET-100 COMMENT 88
APPENDIX EA.3. INTERPOLATION OF UTILITY AND ENVIRONMENTAL

RESULTS FROM NEMS-BRS OUTPUT

TABLE OF CONTENTS

Figure EA-3.1 a An Example of the Interpolation of a Trial Standard Level:

Difference in Coal Capacity .................................. EA.3-4

Figure EA-3.lb Close-Up of the Interpolation of Trial Standard

Level X2 from Xl ......................................... EA.3-5

Figure EA-3.2 Example of Trial Standard Level Xl: Marginal NO Emissions ...... EA.3-6

EA.3-i

EE-RM-PET-100 COMMENT 88
APPENDIX EA-3. INTERPOLATION OF UTILITY AND ENVIRONMENTAL

RESULTS FROM NEMS-BRS OUTPUT

The effects of proposed clothes washer energy efficiency standard levels on electricity and

gas industries have been analysed using a variant of the U. S. DOE/EIA' s National Energy Modelling

System (NEMS), called NEMS-BRS, together with some exogenous calculations.a Because the

relative size of the energy savings being implemented in NEMS-BRS is too small to be seen in the

context of the whole electricity and gas utility sector, NEMS-BRS is not used directly. Rather,

exploratory runs are conducted to estimate marginal effects, which are then used to calculate the

small effects due to each proposed trial standard case.

To run a simulation inNEMS-BRS, the Residential Demand Module clothes washer, clothes

diyer and water heater load is reduced annually according to the energy savings estimated by the

National Energy Savings (NES) model for each trial standard level. These energy savings increase

over time and are distinguished by fuel type (electricity, gas, oil, and LPG). Differences in fuel

usage among U.S. census divisions come from data derived from the Residential Energy

Consumption Survey (RECS).1

The magnitude of the energy decrement that would be required for NEMS-BRS to produce

stable results safely out of the range of numerical noise is greater than even the most stringent

standard under consideration. Therefore, it has been necessary in both the utility and environmental

analyses, to estimate results in the range of the standard levels effects using interpolation.

Interpolated values are derived from a series of higher decrement simulations based on the standard

level. The actual annual savings attributed to each standard level are compared between standard

levels, and those with similar savings patterns over time are grouped. One set of simulations is run

for each of the savings groups. The groups used for the clothes washers analysis are listed below.

The standard level in the first row was the one used to model the others in the same group.

aFor more information on NEMS, please refer to the U.S. Department of Energy, Energy Information Administration

documentation. A useful summary is National Energy Modeling System: An Overview 1998, DOE/EIA-058 1(98), February

1998. DOE/ETA approves use of the name NEMS to describe only an official version of the model without any modification to

code or data. Because our analysis entails some minor code modifications and the model is run under policy scenarios that are

variations on DOE/ETA assumptions, the name NEMS-BRS refers to the model as used here (BRS is DOE's Building Research

and Standards office, under whose aegis this work has been performed).

EA.3- 1

EE-RM-PET-100 COMMENT 88
The MEFs (Modified Energy Factors) in the table below are grouped into four multiplier

categories.

Group 1

(Multipliers 8, 12, 16)

Group 2

(Multipliers 6, 9, 12)

Group 3

(Multipliers 2, 4, 6)

Group 4

(Multiplier 6, 9, 12)

1.089 1.257 1.634 1.04 in yr 2004

& 1.26 in yr 2007

1.021 1.362 1.485

0.96 1

0.908

0.860

To preserve the pattern of energy savings over time for a trial standard, savings in each year

are multiplied by the same factor. This factor varies between groups because the magnitude of the

savings changes. An appropriate set of multipliers were chosen to augment the savings to a

magnitude that produces credible results. Using professional judgement, sets of three multipliers

were selected for each of the patterns shown in the table above. For the 1.634 MEF (50% energy

reduction level), the series consists of simulations of 2, 4, and 6 times the trial standard energy

savings.

The output for electricity generation and capacity by fuel type for each of the iterations (the

2, 4, and 6 times the standard) is then regressed, with the y-intercept forced through the origin

because a zero change must be the case with no standard in place and because the target points of

interpolation are close to the origin (i.e., at low energy decrements). Other trial standards within the

same group are interpolated along this regression line by substituting the x-value in the regression

equation with the ratio of energy savings between standard levels in the peak energy savings year.

Figure EA-3.l a shows an example of the interpolation approach for a trial standard level Xl.

The magnitude of the energy savings multiplier is plotted on the x-axis against the reduction in coal

installed generating capacity for each reported year, as shown by the various plotted lines. In general,

results for the various NEMS-BRS runs are reasonably stable and linear, with the noisy behavior

appearing below the first multiplier of the trial standard level savings decrement.

Figure EA-3. lb shows a close-up of the interpolated points for trial standard level X2 from

standard Xl. The heavy horizontal lines illustrate the calculated values for the difference in coal

capacity in 2020. These regressions appear stable, so estimating results via interpolation toward zero

seems justified. A similar approach was used to find the drop in installed generating capacity from

other fuels and in generation for each fuel type in each reported year.

The estimated reduction in total fuel generation that we report at each trial standard level as

determined by interpolation is then used to determine emissions savings. First, annual marginal

EA.3-2

EE-RM-PET-100 COMMENT 88
3 emissions rates are calculated for each of the simulations in a savings group, based on the actual

output from NEMS-BRS. Marginal emissions rates incorporate both effects of the standards-the

emissions saved by the reduction in total generation and the slight change in the emissions

characteristics of the whole power sector that result from the slight change in dispatch and capacity

expansion plan. The net effect on the entire system is very small and, typically, the overall effect on

emissions can be fully attributed to the decremental generation. The annual marginal emissions rates

at the trial standard level are then extrapolated from these rates (at multipliers of the trial standard

level savings) by taking a simple average.

Figure EA-3.2 shows an example of the extrapolation for NO emissions rates for trial

standard level Xl. In this case, marginal rates for NO emissions are shown for each year. As is

evident in the figure, more stable results are produced at higher levels of demand decrement. At

lower decrement levels (i.e., both on the left-hand side of the figure and in years with small standards

impacts), the emissions rate is quite variable. The dashed plots (years 2003 - 2010) show the earlier

years of the imposed standard-those in which the decrements to demand are smallest (not shown

here). In most cases, these curves are so close to flat that regression of the higher decrement

simulation points produces a curve very close to the simple average of values. The constant

emissions rates at higher decrement levels are therefore assumed to hold in the range of small

decrements commensurate with the various standard levels, and the implied marginal emissions rates

are used to estimate emissions reductions. Total emissions savings in each year are the product of

the annual marginal emissions rate and the reduction in thermal generation for that year (as

calculated by the interpolation method described above). For each of the standard levels, marginal

emissions rates for all years are derived by averaging the marginal rates of the three higher decrement

levels (e.g., 2, 4, and 6 times for 50% energy reduction level).

EA.3-3

EE-RM-PET-100 COMMENT 88
NoStd.Lvi. 6x Std. Lvi. Xl 8x Std. Lvi. Xl lOx Std. Lvi

0

-

-

- -

-6 -_

2010 Regression

- - - 2015 Regression

- - 2020 Regression

Savings Multiplier

xl

Figure EA-3.la An Example of the Interpolation of a Trial Standard Level: Difference in Coal Capacity

EA.3-4

EE-RM-PET-100 COMMENT 88
NoStd.LvI.

02c 050

- -

75 1 0 125 150 175 2

- . - -

-0.5 . -

N

-0.9

-1.0

-1.2

-1.5 - -+2000

---2OO5

--2010

---- 2015

-*--- 2020

-2.0 -

2005 Regression

2010 Regression

- - -2015 Regression

- - 2020 Regression

-2.5

2020

2020

Savings Multiplier

Figure EA-3.lb Close-Up of the Interpolation of Trial Standard Level X2 from Xl

N

N

-

N

N

N

EA.3-5

EE-RM-PET-100 COMMENT 88
8

6

4

2

o 0

z

-4

-6

-8

-10

S

• :::--.. --. .

______ ----=ii

2003

""2004

2005

- - 2006

--*• 2007

"2008

2009

2010

2011

2012

2013

2014

- - 2015

2016

2017

2018

20 19

Std. Lvi. Xl 6x Std. Lvi. Xl 8x Std. Lvi. Xl lOx Std. Lvl.X1

Savings Multiplier

Figure EA-3.2 Example of Trial Standard Level Xl: Marginal NO Emissions

EA.3-6

EE-RM-PET-100 COMMENT 88
REFERENCE

1. U.S. Department of Energy - Energy Information Administration, Residential Energy

Consumption Survey: Household Energy Consumption and Expenditures 1993, October,

1995. Washington, DC. Report No. DOE/EIA-0321(93).

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EE-RM-PET-100 COMMENT 88