DOE/EIA-0555(95)/2

Energy Consumption Series

Measuring Energy Efficiency 

in the United States1 

Economy: A Beginning

Energy Information 

Administration

October 1995
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DOE/EIA-0555(95)/2 

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Energy Consumption Series

Measuring Energy Efficiency in the 

United States' Economy: A Beginning

October 1995

Energy Information Administration

Office of Energy Markets and End Use

U.S. Department of Energy

Washington, DC 20585

This report was prepared by the Energy Information Administration, the independent statistical and analytical 

agency within the Department of Energy. The information contained herein should not be construed as advocating 

or reflecting any policy position of the Department of Energy or any other organization.
Contacts

This publication was prepared by the Energy Information Administration (EIA) under the general direction of W. Calvin 

Kilgore, Director of the Office of Energy Markets and End Use (202) 586-1617. The project was directed by Lynda T. 

Carlson, Director of the Energy End Use and Integrated Statistics Division (EEUISD) (202) 586-1112 and Dwight French, 

Chief of the Transportation and Industrial Branch (202) 586-1114. The FAX number for all EEUISD personnel is (202) 

586-0018. Specific technical information may be obtained from the Product Manager, Stephanie J. Battles (202) 586-7237 

or sbattles@eia.doe.gov.

Detailed technical questions on the related EIA consumption surveys may be referred to the following members of the 

EEUISD:

Residential Energy Consumption Survey Wendel Thompson 202-586-1119

wthompson @ eia.doe.gov

Manufacturing Energy Consumption Survey Mark Schipper 202-586-1136

mschipper@eia.doe.gov

Residential Transportation Energy Consumption Survey Frank Lambrecht 202-586-4962

flambrecht@eia.doe.gov

Commercial Buildings Energy Consumption Survey Martha Johnson 202-586-1135

mjohnson @ eia.doe.gov

The Energy End Use and Integrated Statistics Division would like to thank the following contract employees for their 

extensive assistance: Mindi Farber, Andrea Lachenmayr, and Cindy Magee.

Data in this report are based upon EIA consumption surveys and are in the public domain. Appropriate credit may be 

reproduced without permission. An example of a suggested citation is "U.S. Department of Energy, Energy Information 

Administration, Commercial Buildings Energy Consumption and Expenditures 1992" or "U.S. Department of Energy, 

Energy Information Administration, 1992 Commercial Buildings Energy Consumption Survey."

This report was undertaken as a first step to define and measure energy efficiency. We encourage customer 

comments and participation in this project. Participation from the readers of this report will allow us to 

enhance our methodology and presentation of energy-efficiency indicators. Focus questions are provided on 

the following page to guide you as you review this report.

If you have comments or suggestions or wish to participate in either our in-house workshops or Internet 

workshops, please contact Stephanie J. Battles by phone at (202) 586-7237, by FAX at (202) 586-0018, or 

by e-mail at sbattles@eia.doe.gov. The mailing address is:

El-632, Mail Stop 2G-090 

1000 Independence Avenue, SW 

Washington, DC 20585.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Focus Questions

1. There are two types of energy-efficiency indicators:

a. Aggregate indicators that use data, which are frequently available and are easier to construct 

b. Comprehensive more detailed indicators where the data are not as frequently available and the 

indicators are more complex to construct.

Considering the trade-offs, which type of indicators should EIA present and why?

2. Should EIA aggregate the sectoral coverage or leave the coverage disaggregated; that is, should there be:

a. Buildings sector indicators versus separate residential and commercial sector indicators 

b. Transportation sector indicators versus passenger and freight indicators 

c. Industrial sector indicators versus separate indicators for manufacturing, agriculture, mining, and 

construction?

3. Should EIA deal with the energy losses incurred in the generation, transformation, transmission, and

distribution stages at the entire economy level, sectoral level, or both levels? How should EIA deal with these 

losses? Should only the losses in the electricity generation sector be considered or should the losses be 

considered in the other energy sectors as well?

4. For each sector, should EIA have a single indicator or multiple indicators to illustrate the variability of 

efficiency trends, depending on the approach used?

5. In your estimation, which of the energy-intensity indicators presented in this report are the most robust, valid, 

and reproducible? Please explain.

6. Do you use any other potential energy-intensity indicators that are robust, valid, and reproducible? Please 

describe.

7. With what frequency should EIA publish the chosen indicators of energy efficiency?

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning

Contents

Executive Summary ............................................................................ ix

1. Introduction .................................................................................]

Organization of the Report .................................................................... 1

Meeting Different Customer Interests and Needs .................................................. 2

2. Defining Energy Efficiency and Its Measurement ................................................. 3

Concept of Energy Efficiency .................................................................. 3

Measuring Energy Efficiency ................................................................. 4

Approach Used in this Report ................................................................. 6

3. Residential Sector ............................................................................ 7

Introduction ............................................................................... 7

Major Data Sources ......................................................................... 8

Energy Consumption in the Residential Sector .................................................... 8

Demand Indicators ......................................................................... 11

Energy-Intensity Indicators in the Residential Sector .............................................. 13

Strengths and Limitations of the Energy-Intensity Indicators ........................................ 16

4. Commercial Building Sector .................................................................. 17

Introduction .............................................................................. 17

Major Data Sources ........................................................................ 18

Energy Consumption in the Commercial Building Sector .......................................... 18

Demand Indicators ......................................................................... 20

Energy-Intensity Indicators in the Commercial Building Sector ..................................... 22

Strengths and Limitations of the Energy-Intensity Indicators ........................................ 25

5. Transportation Sector ........................................................................ 27

Introduction .............................................................................. 27

Major Data Sources ........................................................................ 28

Energy Consumption in the Transportation Sector ................................................ 28

U.S. Domestic Passenger Transportation ....................................................... 30

U.S. Domestic Freight Transportation ......................................................... 38

Transportation Energy-Intensity Composite Indicator .............................................. 45

Strengths and Limitations of the Energy-Intensity Indicators ........................................ 46

6. Industrial Sector ............................................................................ 47

Introduction .............................................................................. 47

Major Data Sources ........................................................................ 50

Energy Consumption in the Manufacturing Sector ................................................ 51

Demand Indicators ......................................................................... 53

Energy-Intensity Indicators in the Manufacturing Sector ........................................... 58

Strengths and Limitations of the Energy-Intensity Indicators ........................................ 60

7. United States Economy ....................................................................... 63

Introduction .............................................................................. 63

Primary Energy ............................................................................ 63

Economy-Wide Energy-Intensity Indicator: Methodology .......................................... 64

Energy-Intensity Composite: A Measure of Change in the U.S. Economy .............................. 66

Strengths and Limitations of the Economy-Wide Energy-Intensity Indicators ........................... 69

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
8. Future Directions ............................................................................ 71

Appendix

A. Methodology .............................................................................. 73

Glossary ...................................................................................... 83

General Terminology .......................................................................... 83

Residential Sector ............................................................................ 85

Commercial Building Sector .................................................................... 86

Transportation Sector .......................................................................... 87

Industrial Sector .............................................................................. 89

U.S. Economy ............................................................................... 91

Tables

3.1. Demand Indicators in the Residential Sector, 1984, 1987, and 1990 .................................. 12

3.2. Unadjusted and Weather-Adjusted Residential Site Energy-Intensity Indicators, 1984, 1987, and

 1990 .................................................................................. 14

3.3. Unadjusted and Weather-Adjusted Energy-Intensity Indicator, 1984,1987, and 1990 .................... 15

4.1. U.S. Commercial Total Site Energy Consumption by Principal Building Activity, 1986, 1989, and 1992 ..... 20

4.2. Comparison of Commercial Site Energy-Intensity Indicators, 1986, 1989, and 1992 ..................... 23

4.3. Strengths and Limitations of the Energy-Intensity Indicators ........................................ 25

5.1. Building up a Composite Energy-Intensity Indicator for the Transportation Sector ....................... 45

6.1. Type of Manufacturing Industry Group ......................................................... 49

6.2. Total Inputs of Energy for High Consumers in the Manufacturing Sector, 1985 to 1991 .................. 53

6.3. Energy-Intensity Indicators in the Manufacturing Sector, 1985,1988, and 1991 ........................ 59

6.4. Strengths and Limitations of the Demand Indicators Used in the Energy-Intensity Indicators ............... 61

7.1. Regional Primary Conversion Factors for Electricity, 1984 to 1992 .................................. 67

A.I. Degree-Day Adjusted Residential Site Energy Consumption, South Census Region, 1990 ................ 74

A.2. Calculation of End-Use Energy Consumption in Northeast Office Buildings, 1992 ...................... 75

A.3. Activity Occupancy-Adjusted Total Commercial Floorspace in the Northeast by Principal Building, 1992 ... 75

A.4. Occupancy-Adjusted Total Commercial Site Electricity Consumption in the Northeast, by Principal

 Building Activity, 1992 ................................................................... 76

A.5. Calculating U.S. Domestic Passenger and Freight Air Travel Energy Consumption ...................... 77

A.6. Calculating U.S. Transportation Site Electricity Consumption ....................................... 77

A.7. Capacity Utilization Rate: 26-Year Average and Annual for 1985, 1988, and 1991 by SIC ............... 78

A.8. Value of Production Methodology Example ..................................................... 79

A.9. Example of Calculating Gross Inputs for the Northeast in 1992 ...................................... 80

Illustrations

3.1. Total Site Residential Energy Consumption and Personal Consumption Expenditures Indices, 1980 to 1993 ... 7

3.2. Percent of Total Site Energy Consumption by End Use, 1990 ........................................ 8

3.3. Housing Units in the Residential Sector, 1990 .................................................... 9

3.4. Percent of Total Site Energy Consumption, 1990 .................................................. 9

3.5. Total Site Energy Consumption by Housing Unit Type, 1984,1987, and 1990 ......................... 10

3.6. Change in Total Site Energy Consumption by Type of Housing Unit.................................. 10

3.7. Change in Unadjusted and Weather-Adjusted Site Energy Consumption by Housing Unit Type ............ 11

3.8. Change in Demand Indicators in the Residential Sector ............................................ 11

3.9. Percent of Housing Units At Least 10 Years Old by Census Region, 1984 and 1990 ..................... 12

3.10. Change in Energy-Intensity Indicators for the Residential Sector ..................................... 14

3.11. Change in an Energy-Intensity Indicator by Housing Unit Type, 1984 to 1990 .......................... 16

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Illustrations (Continued)

4.1. Commercial Building Sector Total Energy Consumption and Gross Domestic Purchases Indices, 1978

 to 1992 ................................................................................ 17

4.2. Number of Commercial Buildings by Principal Building Activity, 1992 ............................... 19

4.3. Floorspace in Commercial Buildings by Principal Building Activity, 1992 ............................. 19

4.4. Change in Total Site Energy Consumption in the Commercial Building Sector, 1986 to 1992 .............. 20

4.5. Demand Indicators in the Commercial Building Sector, 1986, 1989, and 1992 ......................... 21

4.6. Change in Demand Indicators for the Commercial Building Sector ................................... 21

4.7. Change in Energy-Intensity Indicators in the Commercial Buildings Sector ............................ 23

4.8. Change in the Energy-Intensity Indicator in the Commercial Building Sector, by Census Region ........... 24

4.9. Change in the Energy-Intensity Indicator for the Northeast by Principal Building Activity ................. 24

5.1. Total Primary Transportation Energy, Gross Domestic Purchases, and Crude Oil Price Indices,

 1977 to 1993 ........................................................................... 27

5.2. Percent of Total Primary Energy Consumption in the Transportation Sector by Mode, 1992 ............... 29

5.3. Total Site Energy Consumption in the Transportation Sector, 1985 to 1991 ............................ 29

5.4. Change in Total Site Energy Consumption in the Transportation Sector, by Transportation Mode .......... 30

5.5. Site Energy Consumption for Passenger Travel by Mode, 1985, 1988, and 1991 ........................ 31

5.6. Change in Site Energy Consumption for Passenger Travel by Passenger Mode, 1985 to 1991 ............. 31

5.7. Demand Indicator, Vehicle-Miles Traveled by Passenger Modes, 1985, 1988, and 1991 ................. 33

5.8. Change in Demand Indicators, Vehicle Miles, by Passenger Mode ................................... 33

5.9. Change in Occupancy by Passenger Mode, 1985 to 1991 .......................................... 34

5.10. Demand Indicator, Passenger-Miles Traveled, by Passenger Mode, 1985, 1988, and 1991 ................ 34

5.11. Change in Demand Indicator Passenger-Miles Traveled, by Passenger Mode ........................... 35

5.12. Energy-Intensity Indicator for Household Vehicles by Vehicle Type and Age, 1985, 1988, and 1991 ........ 35

5.13. Change in the Energy-Intensity Indicator, 1985 to 1991 ............................................ 36

5.14. Characteristics of Household Vehicles, 1985 and 1991 ............................................ 36

5.15. Energy-Intensity Indicator by Passenger Transportation Mode, 1985 to 1991 ........................... 37

5.16. Change in the Energy-Intensity Indicator by Passenger Transportation Mode ........................... 37

5.17. Freight Transportation Site Energy Consumption, By Freight Mode, 1985,1988, and 1991 ............... 39

5.18. Change in Freight Transportation Site Energy Consumption, by Freight Mode .......................... 39

5.19. Domestic Freight Weight and Miles Traveled by Freight Mode, 1985,1988, and 1991 ................... 41

5.20. Change in Ton Miles by Freight Mode ......................................................... 42

5.21. Energy-Intensity Indicator by Freight Mode, 1985, 1988, and 1991 .................................. 43

5.22. Change in the Energy-Intensity Indicator by Freight Mode .......................................... 44

6.1. Output and Energy Consumption Indices for the Industrial Sector, 1977 to 1993 ........................ 47

6.2. U.S. Industrial Total Site Energy Consumption, 1985, 1988, and 1991 ................................ 48

6.3. Industrial Sector Establishments, 1987 ......................................................... 48

6.4. Sector Shares of Site Energy Consumption in the United States, 1991 ................................ 49

6.5. Offsite-Produced Energy Consumed for Heat and Power and Electricity Generation, 1977 to 1991 ......... 52

6.6. Total Inputs of Energy for Heat and Power and Electricity Generation, by Manufacturing Group,

 1985 to 1991 ............................................................................ 53

6.7. Demand Indicators in the Manufacturing Sector, 1985 to 1991 ...................................... 55

6.8. Change in Demand Indicators, 1985 to 1991 .................................................... 55

6.9. Changes in Inventory, U.S. Manufacturing Sector by Manufacturing Group, 1984 to 1991 ................ 56

6.10. Changes in Value of Shipments, Value of Production, and Adjusted Value of Production by

 Manufacturing Group ..................................................................... 57

6.11. Change in Energy-Intensity Indicators for the Manufacturing Sector .................................. 60

7.1. U.S. Economy Indices of Energy-Intensity Indicators, 1977 to 1993 .................................. 64

7.2. Change in U.S. Energy-Intensity Indicators ...................................................... 68

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning vii

Executive Summary

Energy efficiency is a vital component of the Nation's energy strategy. One of the Department of Energy's missions are to 

promote energy efficiency to help the Nation manage its energy resources. The ability to define and measure energy 

efficiency is essential to this objective. In the absence of consistent defensible measures, energy efficiency is a vague, 

subjective concept that engenders directionless speculation and confusion rather than insightful analysis.

The task of defining and measuring energy efficiency and creating statistical measures as descriptors is a daunting one. This 

publication is not a final product, but is EIA's first attempt to define and measure energy efficiency in a systematic and robust 

manner for each of the sectors and the United States' economy as a whole. In this process, EIA has relied on discussions, 

customer reviews, in-house reviews, and seminars that have focused on energy efficiency in each of the sectors. EIA solicits 

the continued participation of its customers in further refining this work.

The term energy intensity is used to describe a statistical ratio estimator of energy use relative to energy service demand. 

This estimator is often used as a measurement indicator of energy efficiency; and in fact, the concepts of intensity and 

efficiency are sometimes used interchangeably. Intensity measures must be based on available data, and so may not reflect 

factors that might, if measurable, allow energy intensity to approximate energy efficiency more precisely; however, trends 

in the energy-intensity indicators are generally suggestive of trends in energy efficiency. Trends in energy intensity can be 

influenced by factors other than energy efficiency. As a practical matter, it is virtually impossible to remove, or even to 

consider, all of the behavioral or structural factors that would be necessary to obtain a pure measurement of energy efficiency, 

however broadly energy efficiency may be defined.

In this report, the focus is on the measurement of energy intensity. Wherever possible, available data are used to remove 

from the energy-intensity indicator influencing factors such as weather, capacity, and inventory changes that are commonly 

viewed as not related to changes in energy efficiency. For each sector, the number of different energy-intensity indicators 

presented is limited by the data available.

Each chapter covering an economic sector contains discussions of:

 Trends in energy consumption for the economic sector and the factors that influence changes in energy consumption

 Description of the data used to develop indicators of energy-intensity

 Demand indicators that influence the amount of energy consumed as well as their changes over time

 Energy-intensity indicators that compute the ratio of energy consumption to a unit of measurement, for example, Btu 

per square foot of floorspace, or Btu per household

 Strengths and limitations of the energy-intensity indicators such as whether data adequately cover the sector, 

whether data are of good quality and timely, or whether demand indicators characterize energy demand for all 

required services.

Each energy-intensity indicator is examined over two intervals of time: one beginning and ending with years of economic 

growth and one beginning with growth and ending with recession or in the case of the commercial building sector, beginning 

with recession and ending with recovery. The following is a summary of findings for each economic sector and the economy 

as a whole. A graphical presentation (Figures ESI a-1) of these findings follows the sector discussions.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning jx
Residential Sector

In the residential sector, four different energy-intensity indicators were developed using data from EIA's Residential Energy 

Consumption Survey (RECS) (Figures ESI a and ESlb). Each of the indicators was adjusted for the influence of weather. 

These adjustments led either to lower reductions in the energy-intensity indicators during the growth/growth interval (1984 

to 1987) or to actual increases in energy-intensity indicators during the growth/recession interval (1987 to 1990). 

Adjustments for the effects of weather appear to be valid. Without these adjustments, efficiency gains in the residential sector 

would be overestimated. Real efficiency gains appeared to have been made in the residential sector, since most intensity 

indicators displayed reductions; however, the magnitude of the gain cannot be determined from available data. Other 

structural influences, such as changes in disposable income and the mix of housing types and energy sources, may play a 

significant role, and the methodology to account for these and other behavioral and structural effects needs to be developed.

Commercial Building Sector

Energy-intensity indicators in the commercial buildings sector increased during the growth/growth interval (1986 to 1989), 

with the exception of the Btu per square-foot-hour indicator. Five energy-intensity indicators were developed, four with data 

from EIA's Commercial Buildings Energy Consumption Survey (CBECS) (Figures ESlc and ESld). All five energyintensity indicators decreased during the recession/recovery interval (1989 to 1992). Adjustments for weather and vacancy 

effects, for the most part, dampened the increases in energy-intensity indicators during the growth/growth interval and 

reduced the decrease in the energy-intensity indicators during the recession/recovery interval.

It is difficult to ascertain if real efficiency gains were made in the commercial buildings sector. Only one energy-intensity 

indicator was consistent over both the growth/growth and recession/recovery intervals, Btu per square-foot-hour. This 

indicator encompasses both the size of the building and hours of usage, two major factors affecting energy usage. This 

indicator does show possible efficiency gains over both time intervals. More work needs to be done to capture other 

structural and behavioral effects that may influence changes in energy usage in this sector.

Transportation Sector

The transportation sector is one of the most difficult and complex sectors in which to determine whether efficiency gains have 

been made. Data are very sparse for this sector. No one survey covers the entire transportation sector in the same way the 

residential or commercial sector is covered, either for passenger transportation or freight. EIA fields the Residential 

Transportation Energy Consumption Survey (RTECS), where the fuel consumption and expenditures are based on estimates 

using vehicle efficiencies from the U.S. Environmental Protection Agency (EPA). RTECS does not collect data to determine 

passenger miles traveled, and it dropped consumption data based on fuel logs in 1985. Other passenger mode and freight 

mode data are collected from other sources such as Transportation Statistics: Annual Report 1994, published by the Bureau 

of Transportation Statistics, and the Transportation Energy Data Book: Edition 14, developed by the Oak Ridge National 

Laboratory for the Department of Energy. The National Personal Transportation Survey is fielded by the U.S. Department 

of Transportation only once every 7 years. Therefore, any energy-intensity indicators developed for the passenger, freight, 

or the transportation sector as a whole, should be viewed with caution.

For the passenger transportation sector, the best energy-intensity indicator seems to be thousand Btu per passenger mile. 

This intensity indicator accounts for the differences in passenger loads between the automobile and mass transit. For all 

passenger transportation modes, the energy-intensity indicator appeared to be on the decline or at least flat over the 

growth/growth interval (1985 to 1988) (Figures ESle and ESlf). Energy-intensity indicator for mass transit seemed to be 

on the rise over the growth/recession interval (1988 to 1991) as passenger loads dipped. In general, the passenger 

transportation sector appears to be less energy intensive, a finding that implies that it may have become more energy efficient 

over both time intervals.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Changes in the energy-intensity indicator, energy per ton mile, for the freight transportation sector produced mixed results 

over the different modes (Figures ESlg and ESlh). It is difficult to determine whether a particular mode in the sector 

became more or less intensive over both time intervals. The growth/growth interval (1985 to 1988) shows a large percent 

increase in the energy-intensity indicator (54.5 percent). This distortion is due to the fact that small package data collection 

for air carriers, such as United Parcel Service, did not begin until 1986. However, for the growth/recession interval (1988 

to 1991), the air-carrier mode seems to have become slightly more energy intensive. Rail is the only mode with energyintensity indicators declining over both intervals, implying decreases in energy-intensity and increases in energy efficiency. 

Again, effects other than efficiency may influence these declines.

Industrial Sector

Even more troublesome data problems exist in the industrial sector. Data for the agriculture, mining, and forestry sectors 

are suitable only for rudimentary analysis, and they are not presented in this publication.

The Manufacturing Energy Consumption Survey (MECS), fielded by EIA, is the most comprehensive source of 

manufacturing energy consumption data, although several other sources exist. Seven different energy-intensity indicators 

are presented for the manufacturing sector as a whole, and for each of three consuming groups: High-Energy Consumers, 

High-Value added Consumers, and Low-Energy Consumers.

Improvements in energy efficiency in the manufacturing sector seemed to be slight, even when the effects of changes in 

inventory and capacity were considered (Figures ESli and ESlj). After adjustments for these two effects, the indicator 

(energy per adjusted value of production) actually increased 5.0 percent over the growth/growth interval (1985 to 1988) and 

fell by 6.6 percent over the growth/recession interval (1988 to 1991), leaving only a 1.6-percent decrease in this energyintensity indicator over both intervals of time.

Economy

An economy-wide energy-intensity indicator that is consistent over all sectors does not exist, except for one that uses an 

economic-demand indicator such as Gross Domestic Purchases, Gross Domestic Product (GDP) or population. In this 

report, the approach was to build a composite indicator from intensity changes and shares for each sector of the economy. 

EIA consumption surveys are fielded in rotating years, e.g., MECS in 1985, CBECS in 1986, and RECS in 1987, and a 

methodology to compensate for this obstacle was developed. Although far from perfect, the composite indicators represent 

a beginning in the development of an economy-wide, energy-intensity indicator.

All three of the composite indicators, as well as the energy per Gross Domestic Purchases presented in Figure 7.1 and 

discussed in Chapter 7, showed little or no reductions in energy intensity over both time intervals, indicating very little 

efficiency gains (Figures ESlk and ES11). One exception was site energy per capita during the growth/growth interval (1985 

to 1988), which increased by 6.1 percent and decreased by only 2.6 percent during the growth/recession interval (1988 to 

1991). Such a finding may indicate the influence of structural and behavioral effects rather than true gains/losses in 

efficiency. More research is needed to refine these composites.

This report is intended to stimulate discussion and invite reader feedback and future participation.

This is indeed a beginning task. EIA, with the assistance of its customers, needs to refine the energy-intensity indicators as 

presented.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning xi
Refining these indicators will require more work, such as:

• Development of indicators of energy-intensity some demand indicators, like floorspace for commercial and 

residential sectors, do not completely capture the energy-demand profile. Other demand indicators or combinations 

of indicators need to be defined.

• Identification and analysis of structural and behavioral effects energy estimates for each sector were adjusted 

for factors such as weather, occupancy, inventory changes, and capacity utilization; however, other effects may 

influence energy efficiency as well. Methodology is needed to adjust for other structural and behavioral effects.

Customer participation in the form of report feedback and workshop participation will assist in obtaining the most feasible 

and robust indicators within the limitation of the data and resources available.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Figure ES1. Energy-Intensity Indicators for the U.S. Economy, by Sector

Residential Sector

a. Change in Energy-Intensity Indicators, 

1984 to 1987

QUnadiusted BBWeather-Adjusted

b. Change in Energy-Intensity Indicators, 

1987 to 1990

OiJr-adj'.iRted WWs^lhs;-A••,'!' >'-

Million Btu/Bi];!d>nij Million Btu'Building

Million Btu/Household

Million Bt.j/'S'.i FMillion Btu/Person Million Blu/Person

-8.0 -6.0 -4.0 -2.0 0 2.0 4.0 6.0 80

Percent Change

-8 o -60 -4.0 -2 o r :• >:• 

Percent Change

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1984,1987, and 1990 Residential Energy 

Consumption Survey; Public- Use Data Rles. «U.S. Department of Commerce, Bureau of the Census, Current Population Reports, p. 

25.

Commercial Building Sector

c. Change in Energy-Intensity Indicators, 

1986 to 1989

OUnadjusted •Adjusted

Million B[j/Building|

Thousand BUK 

Square Foot

Bin/Square F"oi-Hour| 

Thousand Btu'Fmployeej

Thousand Btu. 

1987 Dollar GDP

d. Change in Energy-Intensity Indicators, 

1989 to 1992

Million Btu/Builtiing

Thousand Btu/l 

Sqjare Foot |

Bfu Square Foot-Hour

Thousand Btu/Employee

Thousand Btu/ 

1987 Dollar GDP

-150 -K>0 -5.0 0 50 100 150 20.0 25.0

Percent Change Percent Change

Note: "Adjusted" includes adjustments for weather and vacancy.

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1986,1989, and 1992 Commercial Buildings 

Energy Consumption Surveys, Public-Use Data Files. »U.S. Bureau of Labor Statistics, Employment and Earnings, monthly March 

issues. »U.S. Bureau of the Census, Current Construction Report, series C30 and press release CB-92-14. »U.S. Bureau of Economic 

Analysis, National Income and Product Accounts of the United States, Volume 2,1959-1988; and Survey of Current Business (March 

1993).

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning XIII
Figure ES1. Energy-Intensity Indicators for the U.S. Economy, by Sector (Continued)

Passenger Transportation Sector

e. Change in Energy-Intensity Indicator, by f. Change in Energy-Intensity Indicator, by 

Passenger-Transportation Mode, 1985 to 1988 Passenger-Transportation Mode, 1988 to 1991

Automobiles ! -6.9:

Motorcycles

Light Trucks

General Aviation

Motorcycles 

light T rucks

Mass Transit

Air Carriers

Mass Transit '

-25.0-20.0-15.0-10.0 -5.0 0 5.0 10.0 15.0 20.0 25.0

Percent Change in Energy-Intensity Indicator 

(Thousand Bin per Passenger Mile)

-25.0-20.0-15.0-10.0 -5.0 0 5.0 10.0 15.0 20.0 25.0

Percent Change in Energy-Intensity Indicator 

(Thousand Btu per Passenger Mile)

Notes: "Mass transit includes buses and passenger rail. • Derivation of these numbers are described in the Transportation section 

of Appendix A.

Sources: »U.S. Department of Energy, Oak Ridge National Laboratory (ORNL), Transportation Energy Data Book, Editions 11 and 

14, Table 2.6 and unpublished 1985 data from ORNL. «U.S. Department of Transportation, Bureau of Transportation Statistics, National 

Transportation Statistics, Annual Report (September 1993), Table 6.

Freight Transportation Sector

g. Change in Energy-Intensity Indicator, by 

Freight-Transportation Mode, 1985 to 1988

h. Change in Energy-Intensity Indicator, by 

Freight-Transportation Mode, 1988 to 1991

__i

30.0 -20.0 -10.0 0 10.0 20.0 30.0 40.0 50.0 60.0

Percent Change In Energy-Intensity Indicator 

(Thousand Btu per Ton Mile)

All Modes

Trucks

Air

Marine

Rail

Oil Pipeline 9.5 f—:—' 

I——,— —,--.- — -—,- -r—- --.- _..,_.__.._. ._ r .

-30.0 -20.0 -10.0 0 10.0 20.0 30.0 40.0 50.0 60.0

Percent Change In Energy-Intensity Indicator 

(Thousand Btu per Ton Mile)

Notes: «ln this graph, the share of oil pipeline in total freight consumption was less than 1 percent. "Energy for moving water and 

natural gas is excluded.

Sources: U.S. Department of Energy, Oak Ridge National Laboratory (ORNL), Transportation Energy Data Book, Edition 8, Table 

1.5; Editions 11 and 14, Table 2.6 and unpublished 1985 data from ORNL. »Eno Transportation Foundation, Inc., Transportation in 

America 1994, 12th Edition, p. 44.

XIV

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Figure ES1. Energy-Intensity Indicators for the U.S. Economy, by Sector (Continued)

Manufacturing Sector

I. Change in Energy-Intensity Indicators, 

1985 to 1988

GSAII Manuiactu'iMCi G<oupsCJHi''ih Cnnr.umois

j. Change in Energy-Intensity Indicators, 

1988 to 1991

Energy/Adjusted Value 

of Production J3L'__

Percent Change Percent Ohanqe

Note: The ratio of the energy-intensity indicator represents changes in thousand Btu per 1987 dollars.

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1985,1988, and 1991 Manufacturing Energy 

Consumption Surveys. "U.S. Department of Commerce, Bureau of Economic Analysis, National Income and Wealth Division, "Gross 

Product by Industry," 1947-1991, files released 12/31/93, Table D3, "Gross Output for Double-Deflated Industries, Fixed 1987 Weights;" 

Table C1, "Gross Output by Industry, Fixed 1987 Weights;" and Table D4, "GPO Deflators." 'Federal Reserve Board, Industrial 

Production, provided by Charles Gilbert 10/25/94. «U.S. Department of Commerce, Bureau of the Census, 1985, 1988, and 1991 

Annual Survey of Manufactures, Table 2.

U.S. Economy

k. Change in Energy-Intensity Indicators, 

1985 to 1988

I. Change in Energy-Intensity Indicators, 

1988 to 1991

Percent Change Percent Change

Note: In these figures GDP stands for Gross Domestic Purchases and Gross Domestic Purchases is in constant 1987 dollars.

Sources: "Energy Information Administration, Office of Energy Markets and End Use, Annual Energy Review 1993, Tables 1.5 and 

2.1; 1986, 1989, and 1992 Commercial Buildings Energy Consumption Surveys; 1894, 1987, and 1990 Residential Energy 

Consumption Surveys; 1985,1988, and 1991 Manufacturing Energy Consumption Surveys. »U.S. Department of Commerce, Bureau of 

Economic Analysis, National Trade Data Bank, National Income and Products Accounts, Quality series. «U.S. Department of Energy, 

Oak Ridge National Laboratory, Transportation Energy Data Book, Editions 11 and 14. «U.S. Department of Transportation, Bureau of 

Transportation Statistics, National Transportation Statistics (September 1993), Tables 1,4, and 6. »Eno Transportation Foundation, 

Inc., Transportation in America 1994, pp. 44 and 49.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning XV

1. Introduction

Measuring Energy Efficiency in the United States Economy: A Beginning is a unique publication of the Energy Information 

Administration (EIA). Instead of reporting survey results or summarizing the energy-related characteristics of an economic 

sector or industry, this report presents the first step in a development process, a work in progress that you, our customer, 

can help in improving and refining.

Energy efficiency has recently become the focus of increasing attention as a vital component of the Nation's energy strategy. 

Energy-efficiency improvement is the first objective addressed in the Department of Energy's current mission statement, "To 

achieve efficiency in energy use." Additionally, a major emphasis of the Energy Policy Act of 1992 (EPACT) is on energy 

efficiency. The ability to assess the contribution of energy efficiency towards the country's continuing efforts to manage its 

energy demand requires a consensus on the definition of energy efficiency. Indicators of energy efficiency are needed that 

are precise, valid, reproducible, and as robust as possible for each economic sector, within the limitations of data availability.

Generally, the concept of efficiency improvement is easy to rally behind. Defining and measuring it are more difficult tasks, 

but they must be addressed if efficiency improvement is to be a viable part of our Nation's energy strategy. In meeting its 

customers' needs, EIA is the most logical agency to define and measure energy efficiency. In this publication, EIA begins 

to address these two tasks: (1) obtain a definitional understanding of energy efficiency and (2) develop indicators of energy 

efficiency.

The report is not intended to be a definitive statement on these issues, but rather a means of focusing the thinking of our 

customers and obtaining their input. Even with the assistance from experts in the report preparation, this publication is still 

nothing more than a "straw man." Many questions need to be answered, and you as our customer, if you desire, can become 

one of our valuable expert reviewers. As you read this report, please consider the precision and reproducibility of each 

methodology. Questions located on the page iii, titled "Focus Questions" at the beginning of this report may serve as a study 

guide for you to use as you read this report.

Preparation of this report has involved written reviews and other forms of feedback from offices within EIA—Energy 

Markets and End Use, Integrated Analysis and Forecasting, and Statistical Standards. Additionally, review comments were 

furnished by offices within the Office of the Assistant Secretary for Energy Efficiency and Renewable Energy (EE). Further 

comments were obtained from a series of internal seminars, which also included experts within EIA, the Department of 

Energy, and the National Laboratories.

Further comments on the report's contents will be sought through additional sources such as responses to an "interactive" 

Home Page on the Internet, electronic bulletin board workshops, and a series of 1 -day sector-specific workshops to begin 

winter 1995. The goal of this approach will be to obtain the most robust indicators of energy efficiency that may be used 

over time as the standards in the measurement of energy efficiency for each sector of the U.S. economy. 1 These robust 

indicators will allow EIA and its customers to assess the contribution of energy efficiency toward meeting the country's 

continuing efforts in managing its energy demand.

Organization of the Report

This report addresses the definitional and methodological issues surrounding the measurement of energy efficiency. Since 

energy efficiency can rarely be measured directly, the report focuses on the changes in energy-intensity with various 

techniques in each of the sectors.

'See the box on page ii for further information.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Report Organization

Chapter 2 addresses issues on definition and measurements which relate to energy efficiency. Each of the next four chapters 

covers one of the major sectors of the U.S. economy. In each chapter, an indexed trend in energy consumption is shown 

followed by an organization section and a description of the data used in that chapter. Next, a discussion of energy 

consumption and changes in consumption for the sector is presented. The demand indicators that influence the amount of 

energy consumed are explored as well as their changes over time. The energy-intensity indicators are then presented as well 

as the changes in these indicators over two intervals of time—an interval of economic "growth/growth" and an interval of 

"recession/recovery" or "growth/recession". 2 Each of the chapters ends with a discussion of the strengths and limitations 

of the energy-intensity indicators.

Chapter 7 presents the U.S. economy as a whole. The energy-intensity indicators developed in the sectoral chapters are the 

inputs into an economy-wide energy-intensity indicator. Since the sectoral indicators are unique to each sector, a 

methodology is presented in this chapter to overcome this obstacle. This chapter also addresses the importance of including 

energy generation, transmission, and distribution losses in the economy-wide energy-intensity indicators. Economy-wide 

energy-intensity indicators are developed taking the losses into account.

Meeting Different Customer Interests and Needs

The report is designed to be read and understood by different types of customers. This is accomplished by using three 

methods to provide additional information, shaded boxes with text, methodology appendix, and a glossary. The shaded boxes 

with text, appendix, and the Glossary are designed to give the reader fast access to definitional or technical documentation.

Shaded Box with Text

Shaded boxes with text are placed frequently throughout the report. These boxes provide brief definitions or information 

that assists in a better understanding of the material presented.

Appendix A: Adjustments to the Data Methodology

In many cases the methodology behind the development of the energy-intensity indicators is complex. For this reason, the 

methodology for each indicator, estimates of energy consumption measures, and other technical issues are placed in the 

appendix in the appropriate section. A reference can be found either in the text or in a footnote that directs the reader; e.g., 

see "Primary Conversion Factors for Site Electricity" in the U.S. economy section of Appendix A for the methodology and 

an example.

Glossary

The Glossary, located in the back of this report, is divided into different sections. The first section is an overall general 

section, which includes information that is general in nature, e.g., definition of demand indicator. The next sections are 

sector-specific. The last section includes definitions that pertain to the economy, e.g., Gross Domestic Purchases and Gross 

Domestic Product.

Two intervals of time will allow comparisons during different periods of economic activity. Additionally, the consumption survey data used in 

the development of the energy-intensity indicators were not available for the manufacturing and residential transportation sectors prior to 1985.

Energy Information Administration/Energy Consumption Series 

2 Measuring Energy Efficiency in the United States' Economy: A Beginning
2. Defining Energy Efficiency and Its

Measurement

The vast size and complexity of the U.S. economy makes consistent, meaningful, and understandable measurement of any 

broad-based characteristic a daunting task. Energy efficiency is no exception.

Concept of Energy Efficiency

The words "energy efficient" and "energy efficiency" are in common use qualitatively, but are difficult to define or even to 

conceptualize. An engineer may define energy efficiency in a very restrictive equipment sense, whereas an environmentalist 

may have a more broad view of energy efficiency. An economist, politician, sociologist, etc., may each have a different 

concept of energy efficiency.

This report, puts forth two concepts of energy efficiency, a technical concept and a more broad, subjective concept. Often 

the words "energy efficiency have been used to describe what actually may be conservation. For example, consider an office 

building that post signs, "BE MORE ENERGY EFFICIENT—USE THE STAIRS INSTEAD OF THE ELEVATOR." If 

people heed the sign and take the stairs instead of the elevators, is this an increase in energy efficiency? Less energy is used, 

but services are reduced. Behavior has changed, leading to reductions in energy use. People with a social view of energy 

efficiency might consider the energy savings to be an efficiency gain, while those with a more technical view of efficiency 

would classify the savings as conservation rather than efficiency improvement.

Consider another example: A household undertakes measures Box 2.1. 

such as adding storm doors, high-efficiency light bulbs, and attic 

insulation. At the same time, in the winter the household raises 

the thermostat and leaves the lights on for longer periods, using 

the same amount of energy it used previously. Has this 

household improved its energy-use efficiency? In a very 

restrictive technical sense, yes. The household is receiving 

higher levels of services (warmer interior) for the same energy 

input, and the individual services are being performed with less 

energy intensity (fewer watts per lumen and fewer Btu per 

degree temperature rise). According to an outcome-based 

concept, however, energy efficiency is not affected unless the 

higher temperatures and longer lighting hours meet additional 

household needs. (Box 2.1 a)

a.

Energy-Efficiency Concepts

Increases in energy efficiency take place 

when either energy inputs are reduced for a 

given level of service or there are increased 

or enhanced services for a given amount of 

energy inputs.

b. Energy efficiency is the relative thrift or 

extravagance with which energy inputs are 

used to provide goods or services._____

Box 2.2.____________________

Relationship Between Energy Use and 

Service Output

where:

Energy efficiency in a more subjective sense may refer to the 

relative thrift or extravagance with which energy inputs are used 

to provide services (Box 2.1b). Energy services encompass a 

myriad of activities, such as powering a vehicle or a toaster, 

firing a boiler, cooling an office, or lighting a parking lot. To be 

energy efficient per se is to provide services with an energy 

input that is small relative to a fixed standard or normal input.

The terms "energy efficiency" and "energy efficient" are used in 

conjunction with other terms such as "energy-intensity" or 

"energy intensive" in describing the mathematical relationship

between energy use and service output. Box 2.2 depicts the ______________________________ basic equation relating the energy use and service output ^^^^^^^^^^^^^^^^^^^^^^^^^^^~ 

relationship. The intensity component, the energy use rate, is the commonly used basis for measuring and assessing 

efficiency since measurement of any narrow technological definition of energy efficiency is not feasible (Box 2.3). Intensity 

and efficiency are not related, in an absolute sense, across energy services. Just because more energy is required to heat a 

ton of steel than to cook a hot dog, cooking a hot dog is not a more efficient process—it simply has smaller unit energy 

requirements, i.e., is less energy intensive.

C '-'s =1*s

Cs = Energy consumption of service s, 

I, = Intensity of energy use per service

unit (or demand indicator), and 

Qs = Measure of the total amount

service s provided.________

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
However, to the extent that the intensity measure is Box 2.3. 

perceived as a use rate that reflects efficiency, intensity •^•••• 

is inversely related to efficiency for a given service; that 

is, , the less energy required to perform a given service,, ...... the greater the efficiency. It follows that a decrease in ETM& m*ns^ 1S the ratl° of ener^ consumption to a unit 

energy-intensity over time may correspond to an of measurement (e.g., floorspace, households, number of 

increase in energy efficiency depending on the level of 

other structural and behavioral effects.3

Measuring Energy Efficiency

Change in energy use over time is driven by a combination of efficiency, weather, behavioral, and structural effects that may 

be only partially separable and may differ among energy services. Therefore, the task of measuring and assessing energy 

efficiency and its change over time consists of the following:

• Deciding which effects should be considered as inherent in efficiency measurement and which are due to weather, 

behavioral, and structural changes to be eliminated or, at least, recognized in the measurements

• Creating an appropriate categorization of energy services that provides the best possible framework of efficiency 

measures

• Combining these statistical measures into a meaningful and understandable assessment of energy efficiency and its 

trends.

There are two approaches to address energy-efficiency trends:

• Market Basket. The market-basket approach is based on consistent measures of consumption per service unit for 

a benchmark set of energy services.

• Comprehensive Approach. The comprehensive approach attempts to take all energy use into account.

Market-Basket Approach

This approach is comparable to the procedure for computing the Index of Industrial Production. The approach estimates 

energy-consumption trends for a controlled set of energy services (the market basket) with individual categories of energy 

services controlled relative to their share in the index. This method of indexing is a type of "bottom-up" approach. If a 

market-basket approach is used, the energy service for which efficiency is measured should encompass the broadest range 

of services.4

Limitations of the Market-Basket Approach

The overriding problem may be a lack of efficiency measures for certain classes of services and the nature of the available 

efficiency measures. Some of the measures may be special-purpose, specific to certain brands or population subclasses, 

often derived in test conditions rather than actual use, and produced without a firm plan for periodic updates. With new ways 

of delivering energy services appearing frequently, problems with keeping current can interfere with trend measurements. 

Additionally, there is a problem with consumer product substitution. If prices change, consumers have a tendacy to substitute 

another comparable product.

' Structural and behavioral effects could mitigate any improvements in energy efficiency, resulting in actual increases in the energy-intensity 

indicator.

For further information see "Quantity Index" in the economy section of Appendix A.

Energy Information Administration/Energy Consumption Series 

4 Measuring Energy Efficiency In the United States' Economy: A Beginning
Comprehensive Approach

The comprehensive approach starts the measurement process with the broadest available measures of energy use and demand 

indicators available. Over time, changes in such measures reflect changes in behavior, weather, structure, and energy 

efficiency. In order to be a viable for assessing energy efficiency, structures of energy measures need to be produced that 

it is possible to separate the effects unrelated to energy efficiency. This approach can be thought of as a "top-down" 

approach. It is like peeling away all the effects until energy efficiency is all that remains.

The measurement of the energy efficiency in the U.S. economy or even just sectors of the U.S. economy is beyond the scope 

of currently available data, EIA or otherwise. This being said, the broader measure, energy intensity, which includes both 

the narrowly defined efficiency changes as well as some behavioral and structural changes that cannot be totally separated 

given currently available data, is still of interest. A "good" measure of energy intensity should identify (or remove from the 

measure) as many of the behavioral and structural changes that affect energy intensity, but are generally agreed to be 

unrelated to energy efficiency, as is computationally feasible within budges limitations and data availability.

Limitations of the Comprehensive Approach

Increased service detail provides an increased understanding of and more precise control over the concept of efficiency being 

measured. At the same time that energy intensities associated with energy services are changing, the amount and nature of 

service demands are also changing. Deciding which change should be embodied in measuring energy-efficiency change is 

a critical and potentially controversial subject.

Using energy-intensity as the indicator of energy efficiency and separating those changes that are not changes in energy 

efficiency (e.g., weather) requires service detail in both the numerator (energy consumption) and denominator (demand 

indicator). It is impossible to extricate all weather, structural, arid behavioral changes from efficiency assessment using the 

comprehensive approach. Some economic sectors have poor or nonexistent information on energy use and/or characteristics 

associated with energy use.

Box 2.4. ___________^^^^_^^^^___^^^^^^^_^^^

Energy Consumption

Energy consumption used in the intensity indicator can either be primary energy or site energy.

• Primary energy is the amount of energy delivered to an end user (e.g., residential housing unit) adjusted to 

account for the energy that is lost in the generation, transmission, or distribution of the energy.

• Site Energy is the amount of energy delivered to an end user that is not adjusted to account for the energy 

lost in the generation, transmission, and distribution of the energy.

Demand Indicator

A Demand Indicator is a measure of the number of energy-consuming units, or the amount of service or output, 

for which energy inputs are required.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Approach Used in this Report

This report uses the comprehensive approach. The categorization of energy-using sectors and the discussion of energy 

consumption and demand indicators as they are related to energy intensities will originate largely from EIA's end-use 

consumption surveys. There are many other data sources, originating both within and outside of EIA, that also are used as 

tools for this analysis. Some data, such as information from the Department of Transportation, are of considerable use in 

deriving energy-intensity indicators for particular energy-service categories that are not covered by consumption surveys 

or are covered in insufficient detail.

EIA's consumption surveys are triennial data collections that presently cover four sectors: residential households, residential 

personal-use vehicles, commercial buildings, and manufacturing establishments. They are designed to provide information 

on energy consumption and expenditures and on characteristics of the energy-consuming units that affect energy use.

There are other more rigorous approaches than the one used in this report. The U.S. Department of Energy's Office of Policy 

in April 1995, released the report, Energy Conservation Trends (DOE/PO-0034). This report uses the Divisia approach, 

which mathematically decomposes any time trend as a product of component elements. 5 EIA's consumption surveys are 

relatively new and therefore time trend data based on these surveys are not available at this time. Additionally, formal 

econometrics and statistical analysis were not employed since the time trend data from the surveys were limited and budget 

limitations did not permit a more rigorous approach at this time.

Box 2.5.

Energy Information Administration End-Use Consumption Surveys

Strengths

• Cover broad, well-defined subsets of the U.S. 

economy that are delineated by their energy 

needs and use patterns

• Representative of the entire United States

• Measure actual energy use, rather than examples 

of use under test conditions or other special 

circumstances

Limitations

• Incomplete coverage of the sectors, especially the 

industrial and transportation sectors

• Data collections are every 3 years

• Years for the sector data collections do not overlap

• Lack of energy end-use specific data for several 

sectors

• Measure use of major energy sources for most 

purposes within the sector

• Provide information on the ways in which 

energy is used, characteristics of the users, and 

energy consumption

• Statistical methods have been/are being 

developed to partition energy use from these 

surveys into service categories, e.g., space 

heating.

Lag between data collection and its availability for 

analysis

Precision limitations of energy estimates

Lack direct information on equipment efficiency on 

usage rates.

For additional information comparing the Divisia and other methods, see Boyd G.A., D.A. Hanson, and T. Sterner (October 1988), 

"Decomposition of Changes in Energy Intensity: A Comparison of Divisia Index and Other Methods," Energy Economics, pp. 309-312. Another 

source is Howarth, R.B., L. Schipper, P.A. Duerr, and S. Strom, (April 1991) "Manufacturing Energy Use in Eight OECD Countries," Energy 

Economics,pp. 135-142.

Energy Information Administration/Energy Consumption Series 

6 Measuring Energy Efficiency in the United States' Economy: A Beginning
3. The Residential Sector

Introduction

More than 90 million single-family, multifamily, and mobile home households encompass the residential sector. Households 

use energy to cool and heat their homes, to heat water, and to operate many appliances such as refrigerators, stoves, 

televisions, and hot tubs.

The energy sources utilized by the residential sector include electricity, natural gas, fuel oil, kerosene, liquefied petroleum 

gas (propane), coal, wood, and other renewable sources such as solar energy. 6

Early in the 1980's total energy consumption 

in the residential sector started to decline, 

although personal consumption expenditures 

continued to increase (Figure 3.1). Since this 

slight dip in the early 1980's, energy use has 

remained near its 1980 level to the present 

time, while personal consumption expend 

itures have continued to rise. During this 

time, when personal consumption 

expenditures were increasing, the percent of 

energy in total personal consumption 

expenditures was falling. Additionally, even 

though households were purchasing more 

energy for appliances such as televisions and 

dishwashers, many of the appliances were 

using less energy than older models.

Act (NAECA) of 1987 mandated minimum 

energy efficiency standards for several types 

of household appliances and equipment such 

as refrigerators, freezers, room air 

conditioners, television sets, furnaces, water 

heaters, and heat pumps. This followed the 

earlier voluntary appliance efficiency targets 

of the Energy Policy and Conservation Act 

(EPCA) of 1975 and various State applianceefficiency standards. In response to these 

various standards, manufacturers have 

improved the energy efficiency of household

Figure 3.1. Total Site Residential Energy Consumption and 

Personal Consumption Expenditures Indices, 

1980 to 1993

o

o

o

CO

en

X

0) 

TJc

'1980'1981 '1982 '1984 '1993 '1987 '

Year

Notes: • Personal consumption expenditures used to develop the index are in 

constant 1987 dollars. "These expenditures include all personal expenditures and 

not only those for energy. "Energy sources include: natural gas, electricity, 

liquefied petroleum gas, fuel oil, and kerosene. •Preliminary RECS data used for 

1993.

Sources: "Energy Information Administration, Office of Energy Markets and End 

Use, Annual Energy Review 1993, Tables 2.1 and 5.17; 1980, 1981,1982, 1984, 

1987, and 1990 Residential Energy Consumption Surveys, Public-Use Data Files. 

•U.S. Department of Commerce, Bureau of Economic Analysis, National Trade 

Data Bank, National Income and Product Accounts, Quantity series.

appliances and equipment over the past 20 years.

As, Figure 3.1 shows, an increasing gap has developed between primary and site energy consumed in the residential sector. 

Site electricity consumption as a percent of total site energy has climbed from 27 percent in 1982 to 33 percent in 1993. 7 

Greater usage of electricity, due mainly to more widespread use of electric heat pumps, central air conditioning, and 

appliances, is largely responsible for this widening gap. The losses in the generation, transmission, and distribution of 

electricity are more than twice the amount of electricity delivered to the household. These losses are incorporated into the 

primary energy estimates.

In this chapter, total site energy consumption includes only: natural gas, electricity, liquefied petroleum gas, fuel oil, and kerosene. 

Based on preliminary data from the 1993 Residential Energy Consumption Survey (RECS) since final 1993 RECS data were not available at the 

time of this analysis.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Chapter Organization

In this chapter, the major data source, EIA's Residential Energy Consumption Survey, is described first. This is followed 

by a discussion of energy consumption in the residential sector and the necessity of adjusting consumption for changes in 

weather before any analysis is undertaken. Next, the demand indicators—households, buildings, household members, and 

floorspace—are described along with the trends in these demand indicators. Four energy-intensity indicators are presented, 

followed by a discussion of the strengths and limitations of these energy-intensity indicators.

Major Data Sources 

Energy Information Administration 

Residential Energy Consumption Survey (RECS)

The RECS is conducted every 3 years by the EIA. It is a national sample survey of more than 5,000 residential housing units 

and their energy suppliers. The RECS is the only comprehensive source of national-level data on energy-related information 

such as energy consumption for the residential sector.

The RECS is a national multistage probability sample survey. Housing unit and household characteristics data are collected 

via personal interview with the householder. Householders are asked to sign authorization forms allowing their suppliers 

of energy to release billing information about their households. A mail survey is used to collect this information on energy 

consumption from the energy suppliers. Using the RECS data, end-use estimates for space heat, air conditioning, water 

heating, and appliances are obtained by disaggregations of actual bills using a nonlinear technique. 8

Energy Consumption in the Residential Sector

Background

Figure 3.2. Percent of Total Site Energy Consumption 

by End Use, 1990

Appliances 

(25%)

Residential energy provides numerous services 

associated with household living, including space 

heating and cooling, water heating, cooking, 

refrigeration, lighting, and the powering of a wide 

variety of other appliances. Space heating is the 

dominant energy service. In 1990, 52 percent of 

the total site energy was used to provide space 

heating, followed by 25 percent used for 

appliances (Figure 3.2).

Energy demand is shaped by a variety of factors, 

including type of housing unit, location, and 

climate. The dominant housing type in the 

residential sector by far is the single-family 

detached housing unit. In 1990, 62 percent of the 

94 million housing units were detached singlefamily units (Figure 3.3). Single-family detached 

housing units consumed 72 percent of total site 

energy (Figure 3.4). In fact, single-family 

detached homes are the most energy-intensive 

housing type, consuming 113 million Btu per household compared with an average of 98 million Btu per household for all 

housing types in 1990.

Space Heating 

(52%)

_ Air Conditioning 

(5%)

Water Heating 

(18%)

Note: Energy sources are electricity, natural gas, fuel oil, kerosene, and 

liquefied petroleum gas.

Source: Energy Information Administration, Office of Energy Markets and 

End Use, 1990 Residential Energy Consumption Survey, Public-Use Data Files.

See Household Energy Consumption and Expenditures 1990, Appendix D, "End-Use Estimation Methodology," for details on the procedures 

used to calculate the end-use estimates. This EIA publication also describes the RECS sample design, data collection procedures, and limitations of 

the RECS data.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Location is an important factor in determining Figure 3.3. Housing Units in the Residential Sector, 1990

energy consumption. Different regions of the

country face different weather patterns, building g

codes, energy-related behavior, fuel mixes, and =

equipment needs and suitability. In 1990, the E

Midwest used 31 percent of the total site energy, Q

whereas the West used only 16 percent, half the 3

amount that the Midwest used with only J 16 .E<n

percent fewer households (Figure 3.4). Weather g 

played a large part in this difference. Eighty-five ^ 

percent of the housing units in the Midwest were % 

located where heating-degree-days (HDD)9 for f 

1990 exceeded 5,500. On the other hand, only 24 z 

percent of housing units in the West were located 

where the HDD's for 1990 were more than 5,500.

Single-Family 

Detached

Smgle-F: ami!y Motile Homes 

Attached

Energy consumption in the residential sector is Source: Energy Information Administration, Office of Energy Markets and 

examined for two time intervals, a growth/ growth End Use' 199° Residen«al Ener9V Consumption Survey, Public-Use Data Files. 

interval (1984-1987) and a growth/ recession 

interval (1987-1990). 10

Figure 3.4. Percent of Total Site Energy Consumption, 1990

a. Housing Type b. Census Region

Single-Family (Detached)

(72%) _.--' "

Single-Famly(Attached)

2-4 Units

(10%)

Mobile Home 

5 or More Units MO/V 

(8%)

Note: Energy sources are electricity, natural gas, fuel oil, kerosene, and liquefied petroleum gas.

Source: Energy Information Administration, Office of Energy Markets and End Use, 1990 Residential Energy Consumption Survey, 

Public-Use Data Files.

Energy Trends

Among all households, the growth of total site energy consumption was nearly stable, with a recorded growth of 

approximately 1 percent per time interval (Figure 3.5). However, this pattern of growth was not the same for each of the 

individual housing types. Total site energy consumption grew during the growth/growth interval for each of the housing 

types with the exception of multifamily units (Figure 3.6). This trend continued partially during the growth/recession interval 

and reductions in total site energy consumption were even more pronounced for all households in large multifamily buildings. 

From 1987 to 1990, the number of occupied units in large buildings decreased by about half a million." Attached singlefamily housing units, which had experienced growth in total consumption during the growth/growth interval, actually 

experienced reductions during the growth/recession interval.

See "Heating-Degree-Days" and "Cooling-Degree-Days" in the general terminology section of the Glossary.

'°The word "recession" is used to describe a period of slow or no economic growth. A recession is officially defined as two consecutive quarters of 

falling Gross National Product.

"REGS does not collect data on vacant or seasonal housing units.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
The weather was mild in the years studied (1984, 

1989, and 1990) compared to 30-year averages. 

In 1990, the weather was 14 percent warmer than 

the average. In 1987, the weather was 8 percent 

warmer than the average while in 1984, the 

weather was 2 percent colder than the average. 

When weather effects like these are not 

considered, reductions in total energy 

consumption due to milder weather, could be 

regarded as increases in energy efficiency when 

indeed, they are not.

Total residential site energy increased by 2 

percent from 1984 to 1990, but adjusting for 

weather suggests that if the weather had been 

average, total energy consumption would have 

grown by 9 percent during 1984-1990. 

Comparison of weather-adjusted trends against 

the unadjusted total energy consumption trends 

suggests that the weather-induced "conservation" 

should be removed before any attempt is made to 

develop energy-intensity indicators.

Figure 3.5. Total Site Energy Consumption by Housing 

Unit Type, 1984,1987, and 1990

Single-Family (Detached) 

Single-Family (Attached)

' • •'

I 0.37

Mobile Homes • o 39

5 or More Units

Percent Change

Sources: Energy Information Administration, Office of Energy Markets and 

End Use, 1984,1987, and 1990 Residential Energy Consumption Surveys, 

Public-Use Data Files.

Figure 3.6. Change in Total Site Energy Consumption by Housing Unit Type

a. 1984 to 1987 b. 1987 to 1990

Ait Households! AH Households

irvjif:-Family (Detached)! 

>irvj:e-Fami!y (Attached^

Single-Family (Detached)

i Single-Family (Attached)! 

Mobile Homes

2-4 units

5 or More Units, -2i;>j j 

-10.0 -20.0 -10.0 0 10.0 ?QO 300 -30.0 -20.0 -100 0 100 20.0 30.0

Percent Change Percent Change

Sources: Energy Information Administration, Office of Energy Markets and End Use, 1984,1987, and 1990 Residential Energy 

Consumption Surveys, Public-Use Data Files.

In this chapter, total site energy consumption is weather-adjusted before any attempt is made to present energy-intensity 

indicators. Weather-adjusted total site energy consumption is calculated for each Census region. For 1984, 1987 and 1990, 

space-heating energy consumption is adjusted by a heating-degree day (HDD) factor and the air- conditioning demand is 

adjusted by a cooling-degree day (CDD) factor, to which was added unadjusted demand for all other end uses. The 

methodology used to develop the HDD and CDD factors and adjusted total site energy consumption estimates is presented 

along with examples in the residential section of Appendix A under "Degree-Day-Adjusted Estimates."

As seen in Figure 3.7 covering intervals of growth/growth and growth/recession, if total site energy consumption is not 

adjusted for the mild weather, growth in total site energy consumption is underestimated.

10

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Demand Indicators

The main demand indicators or drivers for energy 

services in the residential sector are the number 

of households, population, buildings, and the 

amount of floorspace (Figure 3.8).

Trends in Demand Indicators 

Households

The housing stock has changed significantly since 

1984. The number of households grew by 4.9 

percent during the growth/growth interval and 3.8 

percent during the growth/recession interval.

Much of this growth was in the South. Figure 3.9 

shows that the greatest percentage of older 

households (at least 10 years old) is largest in the 

Northeast and smallest in the South. The growth 

in the construction of new housing units in the 

South is also one reason for the increase in 

households with air-conditioning. New housing 

units are more apt to have central airconditioning. Between 1984 and 1990, the 

number of air-conditioned households throughout 

the country increased by almost 24 percent (Table 

3.1). Throughout the period, the fuel mix also 

changed in United States households. The 

increased use of the electric heat pump, especially 

in the South, drove the 48 percent increase in the 

use of electricity as the main heating fuel.

Figure 3.7. Change in Unadjusted and Weather-Adjusted 

Site Energy Consumption by Housing Unit 

Type

a. 1984 to 1987

All Households 

Single-Family /Detached) 

Single-Family (AHached) 

Mobile Homes 

2 - 4 Unils

5 or More Units

-30.0 -20.0 -lo.o ;: i-:.o 

Percent Change

b. 1987 to 1990

All Households 

Single-Family (Detached) 

Single-Family (Attached) 

Mobile Homes 

2 - 4 Units 

5 or More Units

-30.0 -20.0 -10.0 0 00 20.0 ••; • Percent Change

Sources: Energy Information Administration, Office of Energy Markets and 

End Use, 1984,1987, and 1990 Residential Energy Consumption Surveys, 

Public-Use Data Files.

Figure 3.8. Change in Demand Indicators in the Residential Sector

a. 1984 to 1987 b. 1987 to 1990

Buildings 

Households 

Square Feet 

Population

; ' . 5 : | 4.3

: ' •'. :'• 4.9

. . : : . : ' : . =. . • •• : : 8.6

|*B

Buildings

Households

Square Feet

Population

0 2.0 4.0 6.0 8.0 10.0 0 2.0 4.0 f.O .-• i "I"

Percent Change Percent Change

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1984,1987, and 1990 Residential Energy 

Consumption Surveys, Public-Use Data Files. »U.S. Department of Commerce, Bureau of the Census, Current Population Reports, p. 

25.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 11
Population

The number of households is growing faster than 

the U.S. population. The population grew by only 

6 percent during 1984-1990, whereas the number 

of households grew by 9 percent. This led to a 

decline in household size from 2.73 members per 

household in 1984 to 2.65 members per 

household in 1990.

Furthermore, in 1990, 25 percent of the 

households had only one member—in 1984 this 

percent was 23.6. 12

Floorspace

Figure 3.9. Percent of Housing Units at Least 10 Years 

Old by Census Region, 1984 and 1990

w

'E

D)

C 'in

O

X

"c

+~c 

o 

tt)

OL

1.0 i——

01984 ; 990

300

600

20 0 (

0 '——

Total residential floorspace increased by 17

percent between 1984 and 1990, much faster than

the growth in the number of households. The size public-UseBat'a Fifes'

of housing units has grown over time from 1,673

square feet per household in 1984 to 1,800 square feet per household in 1990. 13

Midwes! South

Sources: Energy Information Administration, Office of Energy Markets and 

End Use, 1984,1987, and 1990 Residential Energy Consumption Surveys,

Buildings Box 3.1.

The number of residential buildings between 

1984 and 1990 grew faster than the number of 

households (9.8 percent growth for buildings and 

8.9 percent for households), indicating greater 

construction of single-family homes. This was 

the case during the growth/recession interval but 

less strong during the growth/growth interval 

between 1984 and 1987 (Table 3.1). •

Demand Indicators In the Residential Sector

Number of Households 

Number of Household Members 

Number of Buildings 

Amount of Floorspace

Table 3.1. Demand Indicators in the Residential Sector, 1984,1987, and 1990

Demand Indicator

Units

1984 | 1987 | 1990

Million Buildings ..................

Million Households ................

With Air-Conditioning ...............

With Electricity as the Main Heat Source

Single-Family Detached .............

Billion Square Feet.................

Heated ..........................

Cooled ..........................

Million Residents ..................

67.6

86.3

51.4

14.5

53.5

144.4

124.3

89.1

235.8

70.5

90.5

57.5

17.9

55.2

156.9

135.0

104.0

242.3

74.2

94.0

63.6

21.5

58.4

169.2

147.5

118.8

248.7

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1984,1987, and 1990 Residential Energy 

Consumption Surveys, Public-Use Data Files. »U.S. Department of Commerce, Bureau of the Census, Current Population Reports, 

p. 25.

Energy Information Administration, Housing Characteristics 1990, DOE/EIA-0314(90), Table 11; Housing Characteristics 1984, DOE/EIA0314(84), Table 17.

l3Energy Information Administration, Housing Characteristics 1990, DOE/EIA-0314(90), Table 15; Housing Characteristics 1984, DOE/EIA0314(84), Table 20.

Energy Information Administration/Energy Consumption Series 

12 Measuring Energy Efficiency in the United States' Economy: A Beginning
Demand-Indicator Adjustments

Demand indicators in the residential sector are influenced by behavioral and structural effects that can mask the effects of 

energy-efficiency changes. The major behavioral influences on residential energy consumption include changes in family 

size, income, average length of daily occupancy, age of household members, thermostat setting, and the number of employed 

members of household.' 4 Structural changes include household size (floorspace), building age, location (region), and fuel 

mix used.

These behavioral and structural effects must be taken into account in comparisons of energy-intensity indicators over time. 

For example, increases in floorspace per household member (612 square feet per household member in 1984 to 680 square 

feet in 1990) increase the demand for space heating and air conditioning, lighting, and convenience appliances such as 

dishwashers.

A behavioral change affecting energy consumption is the growing number of single-member households. Declines in 

household size also result in more floorspace per person, higher heating demand, and lower water heating demand per 

person. Households with fewer members will often acquire the same number and size of major appliances, and consume 

more energy per household member than a larger household. At the same time, though, single persons may spend less time 

at home than families, resulting in fewer hours demanding energy.

Over the whole population, disposable income per capita has increased. During the growth/growth interval, disposable 

income in constant dollars increased 16 percent whereas during the growth/recession interval, this growth was limited to 

4 percent.' 5 While single-member and two-person households may spend less time at home, thereby using less energy, they 

and larger households may also increase the demand for energy services if disposable incomes have increased. Purchase 

of such energy-using equipment as computers, hot tubs, home theater systems, and swimming pools increase residential 

energy consumption.

Illustrated are only a few of the behavioral and structural influences that affect the demand for energy services in the 

residential sector. The next section presents choices of energy-intensity indicators for the residential sector. The behavioral 

and structural influences described in this section need to be considered when the comparisons of the energy-intensity 

indicators are presented over time.

Energy-Intensity Indicators for the Residential Sector

Energy consumption and the drivers of the Box 3.2.__________________________________

demand for energy in the residential sector Energy-Intensity Indicators for the Residential Sector

the demand indicators, have been presented

in detail. The next step is to construct . Million Btu per Building

energy-intensity indicators for the residential

sector. Box 3.2 lists the indicator choices • Million Btu per Household

presented in this section. Each of the . Thousand Btu per Square Foot

indicators have their own strengths and

limitations, which will be discussed in the • Million Btu per Household Member

next section. Additionally, although the

indicators presented in this chapter are based only on site energy consumption, the indicators may also be presented based

on end-use site energy consumption such as space heating. However, not all of the demand indicators are suitable to use

in the development of end-use intensity indicators. For example, the energy used for space heating may be presented as

space-heating energy per square foot, but it would not make sense to use the square foot demand indicator to develop a

water-heating intensity indicator. A more suitable energy-intensity indicator would be water-heating energy per household

member.

14U.S. Congress, Office of Technology Assessment, Building Energy Efficiency, OTA-E-518, May 1992, p. 20. 

U.S. Department of Commerce, Bureau of Economic Analysis, Survey of Current Business Patterns, August issues.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 13
Table 3.2. Unadjusted and Weather-Adjusted Residential Site Energy-Intensity Indicators, 

1984,1987,and 1990

Energy-Intensity Indicator

Million Btu/Building ..........

Thousand Btu/Square Foot .... 

Million Btu/Person ...........

1984

Unadjusted) Weather Adjusted

134 

105 

63 

38

135 

106 

63 

39

Units

1987

Unadjusted | Weather Adjusted

130 

101 

58 

38

133 

104 

60 

39

1990

Unadjusted) Weather Adjusted

124 

98 

55 

37

133 

105 

59 

40

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1984,1987,1990 Residential Energy 

Consumption Surveys, Public-Use Data Files. »U.S. Department of Commerce, Bureau of the Census, Current Population Reports, 

p.25.

Figure 3.10. Change in Energy-Intensity Indicators for 

the Residential Sector

a. 1984 to 1987

Million Blu/Building

Million Btu/Household

Million Btu/Sq. Ft.

Million Btu/Person

eather Adjusted

-8.0 -6.0 -4.0 -2.0

Percent Change

b. 1987 to 1990

Energy-Intensity Indicator Trends

Table 3.2 shows estimates for the various energyintensity indicators for 3 of the RECS years. Two 

sets of estimates are presented: unadjusted and 

weather-adjusted. Given the variety of indicators 

available, caution is warranted in the 

interpretation of residential energy-intensity 

indicators since the magnitude and direction of 

the energy-intensity indicator changes are 

dependent on the choice of the demand indicator. 

Figure 3.10a shows the changes in these 

indicators over the growth/growth interval. In the 

absence of adjusting consumption for weather 

deviations from the normal average, energyintensity appears to fall during the growth/growth 

interval, and energy efficiency may have 

increased, no matter which indicator is used.

When weather adjustments are made, the 

decreases in energy-intensity are less pronounced. 

The story is slightly different when comparing 

changes in these energy-intensity indicators over 

the growth/recession interval (Figure 3.10b). All 

of the energy-intensity indicators registered a 

decrease in intensity, suggesting an increase in 

energy efficiency. Weather-adjusted energyintensity indicators, with the exception of million 

Btu per square foot, actually registered increases 

in energy- intensity suggesting decreases in 

energy efficiency over the growth/recession 

interval.

Individually, the demand indicator, square feet,

registered the largest percent increase over the

growth/growth interval, partially causing the

energy-intensity indicator, million Btu per square

foot, to register the largest percentage decrease in

energy-intensity. Underlying this was the growth

in the average size of the housing units, a

structural change. Conversely, the smallest decrease in an energy-intensity indicator, million Btu per person, reflected the

fact that the growth in population registered the slowest percent change of all of the demand indicators. When adjustments

were made for weather effects, this intensity indicator actually increased.

Million Btu/Building

Million Btu/Household

Million Btu/Sq. Ft.

Million Btu/Person

ClUnadjusted 

^Weather-Adjusted

6.0 8.0

Percent Change

Sources: "Energy Information Administration, Office of Energy Markets and 

End Use, 1984,1987, and 1990 Residential Energy Consumption Survey, 

Public- Use Data Files. »U.S. Department of Commerce, Bureau of the 

Census, Current Population Report, p. 25.

14

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Some of the decreases in the intensity indicators during both the growth/growth and growth/recession intervals may be a 

reflection of energy-efficiency increases. However, the above discussion gives the reader a clearer understanding of the 

difficulties in trying to assess energy-intensity changes as a reflection of changes in energy efficiency. Efficiency gains or 

reductions are taking place along with structural and behavioral changes. To unbundle the intensity indicators and obtain 

"true" or "pure" energy efficiency is impractical if not impossible. Adjustments such as the degree-day adjustments and 

awareness of the behavioral and structural influences are about the most that may be done, especially in an environment of 

limited data, time, and resources. Standardizations can be done to take care of the structural changes such as: changing 

distribution of the household by household type.

Another aspect in the development of energy-intensity indicators is the ability to make comparisons within a particular 

indicator, such as million Btu per household, but over characteristics such as type of housing unit. These comparisons may 

be more fruitful. The million Btu per household is not a particularly robust indicator in that energy use per household 

incorporates changing household member compositions, size, and housing type distributions. The energy-intensity indicators 

may become more robust if the indicator is decomposed by characteristics, such as housing type.

Table 3.3 does just that for two characteristics, type of housing unit and Census region. One can see the differences in the 

energy-intensity indicator across a particular characteristic, whether the energy-intensity indicator was unadjusted or weather 

adjusted. Taking the characteristic, type of housing unit as an example, will demonstrate the advantages of comparing within 

an energy-intensity indicator and across the characteristic. The more detailed "micro-residential" energy-intensity indicator 

is more robust.

Table 3.3. Unadjusted and Weather-Ad justed Residential Energy-Intensity Indicator, 

1984,1987, and 1990

(Million Btu

Characteristic

3er Household)

Million Btu/Household

1984

Unadjusted Weather Adjusted

1987

Unadjusted Weather Adjusted

1990

Unadjusted | Weather Adjusted

All Households .........

Census Region

Northeast .............

Midwest ..............

South ................

West .................

Type of Housing Unit

Single-Family Detached . . 

Single-Family Attached . . . 

Multifamily (2-4 Units) .... 

Multifamily (5 or More) . . .

105

125

129

85

85

73

117 

112 

97 

71

106

127

130

87

85

74

118 

113 

98 

72

101

124

123

84

78

76

114 

99 

93 

64

104

126

131

84

80

78

118 

101 

96 

66

98

120

122

81

78

78

113 

87 

95

51

105

131

131

87

79

84

122 

93 

102 

53

Sources: Energy Information Administration, Office of Energy Markets and End Use, 1984,1987,1990 Residential Energy 

Consumption Surveys; Public-Use Data Files.

The largest decreases in the intensity indicator, million Btu per household, was in the single-family attached and large 

multifamily housing units (Figure 3.11). Since 1984, the number of occupied large multifamily housing units declined by 

almost a half-million units in 1990 as well as total consumption for all large multifamily units.

After weather adjustments, intensity actually increased during the growth/recession interval in the single-family detached 

and smaller multifamily housing units.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 15
Figure 3.11. Change in an Energy-Intensity Indicator by Housing Unit Type

a. 1984 to 1987 b. 1987 to 1990

^Unadjusted GKWeathei-Adjusted

r~] 5 ,

Mobile Home mm, „ Mobile Home |&ig|@ '

Single-Family (Detached) ( H Single-Family (Detached)

: - u 81 I Single-Family (Attached) in'TflBHBI Single-Family (Attached;

1 -361'"] 

Mullifamily (2-4 Units) , '—$ Multifamily (2-4 Units)

-^81} -213 Multifamily ;5 o- More) ,~MM( • Multifamily (5 or More) ,,,„ K 1^^^ 1:> °

Percent Change in Energy-Intensity indicator Percent Change in Energy-Intensity Indicator 

(Million Btu per Household) (Million Btu per Household)

Note: The percent changes were based on unrounded data.

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1984,1987, and 1990 Residential Energy 

Consumption Surveys, Public-Use Data Files.

Strengths and Limitations of the Energy-Intensity Indicators

Four energy-intensity indicators were presented in this chapter that may be used as the basis for the measurement of energy 

efficiency. All four indicators are imperfect. One imperfection can easily be addressed: the influence of changes in the 

weather. Adjusting the intensities for weather, especially since the recent years have been mild, can explain a considerable 

portion of the reductions in these energy-intensity indicators. Structural and behavioral influences affect all four indicators, 

some more than others. Energy use per person account for population growth but does not address other issues. Energy per 

household does not account for the expansion in household floorspace whereas energy per square foot does. Energy per 

square foot may be appropriate for some end uses, e.g., space-heating energy, but not for others such as water heating energy.

No single energy-intensity indicator for the residential sector stands out as clearly superior to the others. The choice of 

indicator depends on the questions asked and on data and resource availability.

Energy Information Administration/Energy Consumption Series 

16 Measuring Energy Efficiency in the United States' Economy: A Beginning
4. Commercial Building Sector

Introduction

The commercial building sector is extremely difficult to delineate. As generally covered by EIA, and for the purposes of this 

document, the commercial building sector consists of all buildings that meet the definition of a building and for which the 

majority of floorspace is dedicated to activities other than residential or industrial 16 businesses. The vast majority of energy 

use associated with this sector occurs in buildings, to maintain the building environment, and provide building-based 

services. Commercial buildings encompass diverse kinds of structures with equally varied operations. Energy use in the 

commercial building sector is affected bytrie physical characteristics of the buildings, age of the buildings, efficiency of the 

equipment, occupants' energy-related behavior, location, and structural effects. Different principal building activities 17 

demand different energy services and various levels of a particular service. The energy used in commercial buildings range 

from the major energy sources—electricity, natural gas, fuel oil, and district heat—to the minor energy sources: propane, 

coal, and the renewable sources, wood and solar. 18

The energy supply disruptions of 1973 and 

1979, along with a growing concern for the 

environment, led to increased awareness of 

the need to reduce energy consumption. 

Commercial buildings built in the 1980's 

were designed for specific climates, were 

well-insulated, and included more efficient 

space conditioning and lighting systems. 

Nevertheless, an expanding economy and 

increases in energy service demand during the 

1980's caused an increase in energy 

consumption in the commercial building 

sector. During that period energy demand 

grew by 1.0 percent a year. 19

Between 1979 and 1983, the economy was 

growing at approximately the same rate as 

total primary energy consumption (Figure 

4.1). In 1983 total energy consumption and 

Gross Domestic Purchases diverged, 

reflecting the growing concern for the 

environment and the building of more energyefficient buildings. 20

Figure 4.1. Commercial Building Sector Total Energy

Consumption and Gross Domestic Purchases 

Indices, 1978 to 1992

O 

O

II 

o>

X

CD 

T3C

-•-Primary Energy

"1986 '

Year

Notes: «U.S. Gross Domestic Purchases used to develop the index are in 

constant 1987 dollars. «Gross Domestic Purchases includes imports and excludes 

exports.

Sources: 'Energy Information Administration, Office of Energy Markets and End

,_. Use, 1979,1983,1986,1989, and 1992 Commercial Buildings Energy Consumption 

Ihis gap seems to surveys, Public-Use Data Files. «U.S. Department of Commerce, Bureau of 

narrow somewhat in 1989 only to reopen Economic Analysis, National Trade Data Bank, National Income and Product 

when the economy faced a slowdown before Accounts, Quantity series, 

the recession in 1991. Between 1989 and

1992, total site energy consumption remained relatively stable while total primary energy fell slightly, reflecting a possible 

relative decline in electricity consumption. In 1989 electricity consumption was 48 percent of all commercial site energy 

consumption, but in 1992, this percentage fell to 45 percent.

I6 lndustrial businesses include manufacturers; agriculture, forestry, and fisheries; mining; and construction. These are excluded from the 

Commercial Building Sector.

17,,

18.

Principal Building Activities" is defined in the commercial section of the Glossary.

In this chapter, commercial site energy consumption includes only electricity, natural gas, fuel oil (distillate and residual), and district heat (hot

water and steam).

19See ElA's Energy End-Use Intensities in Commercial Buildings (DOE/EIA-0555(94)/2), pp. 1 and 2.

20Gross Domestic Purchases is a measure of U.S. gross domestic purchases of goods and services including imports and excluding exports. 

Whereas Gross Domestic Product (GDP) is a measure of U.S. gross domestic production of goods and services. Gross Domestic Product for only 

services is used later in the chapter. See "Gross Domestic Purchases" and "Gross Domestic Product" in the general terminology section of the 

Glossary.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 17
Chapter Organization

In this chapter, the major data source, EIA's Commercial Buildings Energy Consumption Survey, is described first. A 

discussion of site energy consumption in the commercial building sector follows, along with a discussion of the necessity 

of adjusting energy consumption for weather and vacancy influences. Next, the demand indicators, buildings, floorspace, 

square-foot hours, number of employees, and gross domestic product for services are described along with the trends in and 

adjustments to these demand indicators. Five energy-intensity indicators will be presented followed by a discussion of the 

strengths and limitations of the energy-intensity indicators.

Major Data Sources 

Energy Information Administration

Commercial Buildings Energy Consumption Survey (CBECS)

The CBECS is a national representation probability sample of commercial buildings. For the purposes of this survey, a 

commercial building is defined as one whose principal activity is not residential or industrial. The survey covers all 

commercial buildings over 1,000 square feet. For each of the roughly 6,000 buildings in the sample, the CBECS collects 

data on energy-related characteristics of the building through personal interviews with the buildings' owners or managers, 

and total energy consumption for all end uses from billing data provided by the buildings' energy suppliers.

EIA conducts this national sample survey of commercial buildings and their energy suppliers on a triennial basis. Previous 

surveys were conducted in 1979, 1983, and 1986 under the name Nonresidential Buildings Energy Consumption Survey 

(NBECS). In 1989, the survey name was changed to CBECS and for consistency, all the surveys will be referred to CBECS 

in this chapter. The latest CBECS was in 1992.

Energy Consumption in the Commercial Building Sector 

Background

Energy is used in the commercial building sector to provide services such as lighting, space conditioning, ventilation, water 

heating, refrigeration, powering office equipment, and other uses. The amount of energy used to provide these services 

depends on the activities taking place in the commercial buildings; for example, health care, offices, food service, and so 

forth. EIA classifies commercial buildings by the activity occupying the most floorspace in the building. This classification 

is based on the premise that buildings within the same principal building activity have similar energy consumption patterns 

and that activity classification is useful to examine differences in energy use among various types of buildings.

In 1992,27 percent of the 4.8 million commercial buildings in the United States were mercantile buildings used primarily 

for sale and/or distribution of goods and services. These buildings had 18 percent of the 67.9 billion square feet of 

commercial floorspace and used 15 percent of the 5.8 quadrillion Btu of site commercial energy to provide energy services. 

Office buildings accounted for only 16 percent of all buildings and floorspace, but commanded 22 percent of all the 

commercial site energy used in 1992 (Figures 4.2 and 4.3). 21

In 1989, the largest proportion of the energy used for energy services in commercial buildings was for space heating (35 

percent) followed by lighting (18 percent), water heating (9 percent), office equipment (7 percent), space cooling (5 percent), 

ventilation (5 percent), cooking (5 percent) and refrigeration (3 percent). 22 Some building activities use more of a particular 

energy service than other building activities; for example, office buildings used only 30 percent of the total site energy for 

space heating, but educational buildings used 54 percent of total site energy for space heating.

EIA's Commercial Buildings Energy Consumption and Expenditures 1992 (DOE/EIA-0318(92)) presents a profile of energy consumption and 

expenditures in 1992.

22At the present time, only the 1989 CBECS data have been used to estimate end-use estimates. Engineering estimates were derived for each 

building in the sample. These estimates were then statistically adjusted to match the total energy consumption for each building. This methodology is 

fully developed in Energy End-Use Intensities in Commercial Buildings (DOE/EIA-0555(94)/2), September 1994.

Energy Information Administration/Energy Consumption Series 

18 Measuring Energy Efficiency in the United States' Economy: A Beginning
Additionally, regional differences affect the level of Figure 4.2. Number of Commercial Buildings by

demand for energy services. For example, in 1989 the 

South Census Region, a very warm region, used 8 

percent of its total site energy for space cooling, 

whereas the Northeast, a cooler region, used only 3 

percent of total site energy for space cooling.

Principal Building Activity, 1992

Mercantile

Warehouse

Office

Public Assembly

Food

Vacant

Education

Lodging

Other

200 400 600 800 1.000 1.200 '.400 1 ,GOO 

Number of Buildings (Thousands)

Source: Energy Information Administration, Office of Energy Markets 

and End Use, 1992 Commercial Buildings Energy Consumption Survey, 

Public-Use Data Files.

Figure 4.3. Floorspace in Commercial Buildings 

by Principal Building Activity, 1992

Mercantile 

Office

Warehouse

Education

Public Assembly

Vacant

Other

Lodging

Food

Health Care

——1

Energy Trends

Two intervals of time will be used for trends, similar to 

those used for the residential sector but following the 

years of the CBECS. The first is an interval of 

growth/growth (1986 to 1989) and the second of 

recession/recovery (1989 to 1992). Total site energy 

consumption grew by 16 percent in the first interval 

and by less than 1 percent during the second (Table 4.1 

and Figure 4.4).

During the growth/growth interval, total site energy 

consumption increased for each building type except 

for food and health care, but total site consumption 

would have increased more if vacancy rates had not 

increased. During those years, new commercial 

buildings were constructed at a rapid rate, and the total 

floorspace of vacant buildings doubled, increasing from 

2,090 million square feet in 1986 to 4,161 million 

square feet in 1989.

During the recession/recovery interval, changes in total 

site energy consumption varied by building activity 

(Table 4.1). Floorspace for vacant buildings continued 

to grow, but only by 6 percent. The decline in the rate 

of growth of vacant space was attributed to the decline 

in growth of commercial building construction and 

leasing costs.

Weather affects energy consumption in commercial Source; Energy lnformatjon Administration, Office of Energy Markets

buildings. During the intervals studied, the winters and End Use, 1992 Commercial Buildings Energy Consumption Survey,

were warmer and the summers were hotter than the 30- Public-Use Data Files.

year average. If the weather had been closer to the

average, total site energy consumption would not have increased as much during the growth/growth interval, and would have

grown instead of staying flat during the recession/recovery interval. 23

Total site energy consumption estimates can be adjusted not only for the weather effects, but also for vacancy effects. 

Adjusting estimates to omit vacant buildings, which use little energy, changed the trend in total site energy consumption 

during the intervals under study. During the growth/growth interval, the increase in adjusted consumption was less 

pronounced than the unadjusted trend, and the growth in total site energy consumption during the recession/recovery interval 

was even larger (Table 4.1 and Figure 4.4). 24

Total = 67.9 Billion 

Square Feet

2.0 4.0 6.0 8.0 1C.O 12.0

Floorspace (Billion Square Feet)

14.0

23See "Degree-Day Adjusted Estimates" in the commercial section of Appendix A for the methodology and an example. 

24See "Occupied Commercial Buildings Site Energy Consumption Adjustment" in the commercial section of Appendix A.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 19
Table 4.1. U.S. Commercial Total Site Energy Consumption by Principal Building Activity, 

1986,1989, and 1992

(Million Btu)

Principal Building Activity

All Buildings

Principal Building Activity

Public Assembly ..............

Education ...................

Food .......................

Health Care ..................

Lodging .....................

Office ......................

Vacant .....................

Other .......................

Unadjusted

1986 | 1989 | 1992

4,977 5,788 5,803

394 441 419 

632 704 637 

394 394 584 

456 449 403 

299 425 463 

985 1 ,048 892 

1,008 1,230 1,272 

462 536 590 

91 98 131 

254 464 412

Weather Adjusted

1986

5,057

405 

650 

393 

457 

303 

1,001 

1,029 

470 

93 

255

1989

5,725

433 

689 

393 

450 

421 

1,035 

1,224 

526 

96 

458

| 1992

5,931

429 

647 

594 

416 

471 

905 

1,327 

597 

131 

415

Weather and Vacancy Adjusted

1986

4,757

397 

584 

375 

456 

289 

984 

982 

442

249

| 1989

5,317

419 

518 

378 

449 

393 

1,014 

1,196 

517

433

1992

5,664

415 

600 

587 

414 

459 

892 

1,298 

586

414

-- = Data not available.

Sources: Energy Information Administration, Office of Energy Markets and End Use, 1986,1989,1992 Commercial Buildings Energy 

Consumption Surveys, Public-Use Data Files.

Eliminating effects of extreme weather reduces 

the peaks and fills the valleys. By eliminating 

vacant building energy use, periods of high 

vacancy rates (e.g., 1989) are corrected to reflect 

occupied energy use. For almost all principal 

building activities, these adjustments reduced the 

magnitude of the decrease and augmented the 

increases in site energy consumption.

Demand Indicators

Figure 4.4. Change in Total Site Energy Consumption in 

the Commercial Building Sector, 1986 to 1992

25.0 -i———————————

u 01c a s. 

o

a o

5 

a

20.0 -

15.0

10.0

5.0

O Unadjusted

Adjustments

IWeather HlWeather and Vacancy

1986-1989 1989-1992 1986-1992

In the commercial building sector, some of the

demand indicators for energy services are:

number of buildings, operating hours, number of

workers in a building, and size of a building by

floorspace. The greater the floorspace (measured

in square feet), number of buildings, and

operating hours of buildings, the higher the

energy required for heating, cooling, lighting, and

ventilation and other end uses. Thus, the

increases and decreases in unadjusted total site energy consumption shown in Table 4.1 and Figure 4.4, for instance, reflect

commensurate increases and decreases in many of the commercial demand indicators (Figure 4.5).

Sources: Energy Information Administration, Office of Energy Markets and 

End Use, 1986,1989, and 1992 Commercial Buildings Energy Consumption 

Survey, Public-Use Data Files.

Trends in Demand Indicators

Number of Buildings

The number of commercial buildings increased by 9 percent during the growth/growth interval and by 6 percent during the 

recession/recovery interval (Figure 4.6). During both intervals construction of new buildings decreased dramatically, 

dropping by 25 percent over the growth/growth interval and by 40 percent over the recession/recovery interval.25

Data obtained from EIA's 1986, 1989, and 1992 Commercial Buildings Energy Consumption Surveys. Other undocumented data presented in 

this chapter were also obtained from the respective CBECS.

20

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Total Floorspace

Patterns of growth in total floorspace were similar 

to those for number of buildings during both time 

intervals. Increases in total floorspace for new 

construction also followed the growth in the 

number of buildings over the growth years; 

however, during the recession/recovery interval, 

new total floorspace decreased by 23 percent 

although new construction fell by approximately 

40 percent. In 1986, newly constructed buildings 

averaged 15.8 thousand square feet per building. 

This average did not change in 1989, but in 1992, 

the average square footage of a newly constructed 

building was 19.6 thousand square feet.

Figure 4.5. Demand Indicators in the Commercial 

Building Sector, 1986,1989, and 1992

Buildings 

(Million)

Square Feet 

(Billion)

Square-Foot-Hours 

(Trillion)

Employees 

(Million)

GDP (Services) 

(Trillion 1987 Dollars)

50.0 100.0 150.0 200.0 2;>00 3000

Square-Foot Hours Units

Sources: "Energy Information Administration, Office of Energy Markets and 

End Use, 1986, 1989, and 1992 Commercial Building Energy Consumption 

Surveys, Public-Use Data Files. «U.S. Bureau of Economic Analysis, National 

Income and Product Accounts of the United States, Volume 2,1959-1988; and 

Survey of Current Business, March 1993.

Square-foot hours are a surrogate measure of

economic activity. 26 Square-foot hours grew

rapidly during the growth/growth interval (22

percent). The increase in this indicator may be

attributed to the growth of retail sales in mercantile and service buildings. Retail sales grew by almost 10 percent (constant

1987 dollars) during this time.27 The rate of growth in square-foot hours as well as the rate of growth in retail sales slowed

during the recession/recovery interval, resulting in an increase of only 2 percent for retail sales and 3 percent for square-foot

hours. The percent of all commercial buildings open 48 hours or less per week increased from 40 percent in 1989 to 48

percent in 1992. Conversely, the percent of all commercial buildings open 85 hours or more per week decreased from 20

percent in 1989 to 17 percent in 1992. The reduction in operating hours follows the economic slowdown the country as a

whole was facing during those years.

Figure 4.6. Change in the Demand Indicators for the Commercial Building Sector

a. 1986 to 1989 b. 1989 to 1992

Buildings 

Square Feet 

Square-Foot Hours I 

Employees

J90 a Unadjusted 

asAdjusted

Buildings i 

Square Feet 

Square-Foot Hours,: 

Employees

Gross Domestic Product! 

(services)

9.2 • Adii.sted

-10.0 -5.0 0 5.0 10.0 !.1

Percent Change

Gross Domestic Product 

(services)

-10.0 -5.0 Q 5.0 100 15.0 20.0 25.0

Percent Change

Note: "Adjusted" is an adjustment for vacancies.

Sources: • Energy Information Administration, Office of Energy Markets and End Use, 1986 and 1989 Commercial Buildings Energy 

Consumption Surveys, Public-Use Data Files. »U.S. Bureau of Labor Statistics, Employment and Earnings, monthly March issues. 

•U.S. Bureau of the Census, Current Construction Report, series C30 and press release CB-92-14. «U.S. Bureau of Economic 

Analysis, National Income and Product Accounts of the United States, Volume 2,1959-1988 and Survey of Current Business, March 

1993.

26For each principal building activity, the total building square footage is multiplied by the annual operating hours. The square-foot hours are 

summed over all principal building activities to obtain total square-foot hours.

27 U.S. Department of Commerce, Bureau of Economic Analysis, Survey of Current Business, various March issues.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 21
Number of Employees

The total number of employees fell during the Box 4.1. 

growth years and was flat during the ^••^••' 

recession/recovery interval.

During the growth years, the number of

buildings with fewer than 10 employees grew by

7 percent, whereas the number of buildings with

10 to 19 employees fell by 4 percent. The

commercial building sector, perhaps following

the manufacturing sector, may have downsized.

Investigation into changes in the number of

buildings in each principal building activity type

may be warranted since some principal building ^________________________________

activity types may be more apt to substitute

equipment for employees than others (e.g., increased use of computers in office buildings to increase productivity).

Demand Indicators in the Commercial 

Building Sector

Number of Buildings 

Floorspace 

Square-Foot Hours 

Number of Employees

Gross Domestic Product for Services (Constant 1987 

Dollar)

Gross Domestic Product (Services)

This estimate of economic activity appears to run counter to the results of changes in square-foot hours, a surrogate to 

economic activity. During the growth/growth interval, the growth in Gross Domestic Product (GDP) for services was far 

smaller than the growth in square-foot hours. One possible explanation is that commercial businesses may have kept their 

doors open longer to make the same profit that they made in fewer hours in better economic times.

Demand-Indicator Adjustments

Demand indicators, with the exception of GDP for services, can be adjusted by removing vacant buildings from the estimates 

in the same way as the consumption estimates were adjusted. The effects of these adjustments are depicted in Figure 4.6.

Energy-Intensity Indicators for the Commercial Building Sector

Energy-intensity indicators are used to measure 

the ratio of energy consumption to the demand 

for services using the demand indicators 

described in the previous section. The energyintensity indicators may be applied across the 

entire sector, or conditionally for a specific 

building activity, building age, end use, or other 

limiting characteristics. A commonly used 

energy-intensity indicator for the commercial 

building sector is energy consumption per 

square foot. However, a variety of other popular 

indicators exist (see Box 4.2).

Box 4.2

Energy-Intensity Indicators for the 

Commercial Building Sector

Million Btu per Building 

Thousand Btu per Square Foot 

Btu per Square-Foot-Hour 

Thousand Btu per Employee

Thousand Btu per Dollar of Gross Domestic Product for 

Services (Constant 1987 Dollar)

22

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Trends in Energy-Intensity Indicators

During the growth/growth interval, all the energy-intensity indicators—except thousand Btu per square-foot 

hour28—registered increases in intensity, a trend suggesting that energy efficiency decreased.29 During the recession/recovery 

interval, all of the energy-intensity indicators decreased, suggesting increases in energy efficiency (Figure 4.7). The results 

in the two different intervals suggest that influences other than only changes in energy efficiency may be affecting the results. 

If the time interval chosen were the entire period, 1986 to 1992, the energy-intensity indicators, million Btu per building and 

thousand Btu per square foot, showed no changes (Table 4.2).

Adjusting demand indicators in the development of the energy-intensity indicators begins to remove a few of those influences 

that affect energy-intensity that are not due to changes in energy efficiency (Table 4.2 and Figure 4.7). The adjustments seem 

to put a damping effect on the intensity indicators. The increases in intensity during the growth/growth interval are less 

pronounced, and the decreases during the recession/recovery interval are not as great as the unadjusted estimates.

Table 4.2. Comparison of Commercial Site Energy-Intensity Indicators, 1986,1989, and 1992

Energy-Intensity Indicators

Million Btu/Building .........

Thousand Btu/Square Foot . . . 

Btu/Square-Foot-Hour ......

Thousand Btu/Employee ..... 

Thousand Btu/Dollar GDP . . .

Unadjusted

1,198

86 

24

68 

2,231

1986

Weather and 

Vacancy Adjusted

1,300

92 

25

69 

2,132

Unadjusted

1,278

92 

23

82 

2,534

Units

1989

Weather and 

Vacancy Adjusted

1,358

97 

24

81 

2,328

Unadjusted

1,207

86 

22

82 

2,379

1992

Weather and 

Vacancy Adjusted

1 ^^

93 

23

83 

2,332

Note: Service sector Gross Domestic Product estimates are in 1987 constant dollars.

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1986,1989, and 1992 Commercial Building 

Energy Consumption Surveys, Public-Use Data Files. "U.S. Bureau of Economic Analysis, National Income and Product Accounts of 

the United States, volume 2,1959-1988, and Survey of Current Business, March 1993.

Figure 4.7. Change in Energy-Intensity Indicators in the Commercial Building Sector

a. 1986 to 1989 b. 1989 to 1992

-————-r------———

Million Btu/Building

Thousand Dtu/Square Foot

Btu/Square Foot-Hour

Thousand Btu/Employee

a Unadjusted 

BI Adjusted ;

-* '

Million Btu/Building

Thousand Btu/Square Foot 1

Btu/Square Foot-Hour

Thousand Btu/Employee

a Unadjusted 

• Adjusted

-2.8 [ 

-1.0

Thousand Btu/ 

1987 Dollar GDP

Thousand Btu/ 

1987 Dollar GDP

-10.0 -5.0 0 5.0 10.0 15.0 20.0 25.0

Percent Change Percent Change

Note: ""Adjusted" includes adjustments for weather and vacancy. "Percent changes were based on unrounded data.

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1986 and 1989 Commercial Buildings Energy 

Consumption Surveys, Public-Use Data Files. "U.S. Bureau of Economic Analysis, National Income and Product Accounts of the 

United States, Volume 2, 1959-1988, and Survey of Current Business, March 1993.

28 In the last section it was shown that square-foot hours had increased during the growth/growth interval by approximately 18 to 22 percent 

depending on whether the indicator was adjusted for weather and vacancy. This rate of increased slowed dramatically over the recessionary/ recovery 

interval.

29Given the variety of energy-intensity indicators available, caution is warranted in attempting to compare indicators. The magnitude and direction 

of changes in the energy-intensity indicators are dependent on the choice of demand indicator used in the denominator. Additionally, structural or 

behavioral effects may intensify or diminish changes in energy-intensity.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 23
Examination of estimates of the unadjusted and adjusted energy-intensity indicator (thousand Btu per square-foot-hour) 

across the four Census regions demonstrates regional differences (Figure 4.8). During the interval of growth/growth, the 

Northeast was the only Census region with increases in the intensity indicator, even after adjustments are made. During the 

recession/recovery interval, the Northeast experienced the largest decrease in the intensity indicator (-19.7 percent 

unadjusted and -17.1 percent adjusted). The Northeast was the only Census region to have a negative energy-intensity 

indicator. Most of the large decrease was in the mercantile and warehouse building activities (Figure 4.9).

Figure 4.8. Change in the Energy-Intensity Indicator in the Commercial Building Sector by Census 

Region

a. 1986 to 1989 b. 1989 to 1992

Northeast

Midwest i

South '

West

uJUnadjusted 

a Adjusted Northeast

Midwest

South

West

^Unadjusted 

BMAdjusted

I

-20.0 -15.0 -10.0 -5.0 5.0 10.0 15.0 20.0 -20.0 -15.0 -10.0 -5.0 5.0 10.0 15.0 20.0

Percent Change In Energy-Intensity Indicator 

(Thousand Btu/Square-Foot-Hour)

Percent Change In Energy-Intensity Indicator 

(Thousand Btu/Square-Foot-Hour)

Note: ""Adjusted" includes adjustments for weather and vacancy. • Percent changes were based on unrounded data. 

Sources: Energy Information Administration, Office of Energy Markets and End Use, 1986,1989, and 1992 Commercial Buildings 

Energy Consumption Surveys, Public-Use Data Files.

Figure 4.9. Change in Energy-Intensity for the Northeast by Principal Building Activity

a. 1986 to 1989 b. 1989 to 1992

Assembly

Education

Food

Health Care | 

Lodging 

Mercantile 

Office ; 

WarehouS'

O Unadjusted 

BAdjusted

Assembly

Education

Food

Health Care

Lodging

Mercantile

Office

I

i Warehouse!

UUnadjusted ! 

25.4 HAdjusted |

-80.0 -60.0 -40.0 -20.0 0 20.0 40.0 60.0 80.0

Thousand Btu per Square-Foot-Hour

-80.0 -60.0 -40.0 -20 0 0 20.0 40 0 60 0 80 0

Thousand Btu per Square-Foot-Hour

Note: ""Adjusted" includes adjustments for weather and vacancy. "Percent changes were based on unrounded data. 

Sources: Energy Information Administration, Office of Energy Markets and End Use, 1986,1989, and 1989 Commercial Buildings 

Energy Consumption Surveys, Public-Use Data Files.

In the Northeast, in 1992, the demand for electricity was 38 percent of the demand for all major fuels. In the early 1990's, 

electric utilities aggressively promoted demand-side management (DSM) programs, especially in the Northeast to either 

reduce electricity demand at peak times or throughout the year. According to the electric utilities in the Northeast, 55 percent 

of the commercial buildings participated in some type of DSM. This may have been one of the contributing factors in the 

reduction of the energy-intensity indicator.

24

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Going one step further is an examination of the estimates for an energy-intensity indicator, thousand Btu per square-foothour, by principal building activity in the Northeast. Figure 4.9a shows that lodging, mercantile, health care, and warehouse 

building types displayed increases in the energy-intensity indicator during the growth/growth interval while other activities 

posted reductions. These relationships remained even when the estimates were adjusted for weather and vacancy. 30

Other structural and behavioral effects need to be considered, such as new construction growth and changing business tax 

laws in addition to the weather, vacancy, regional, and economic effects discussed above. Such consideration is necessary 

to separate the effects that are related to energy efficiency from the effects that are unrelated. Standardizing could take place 

by basically keeping a characteristic such as floorspace at a certain level and examining the intensity indicators as if the 

amount of floorspace had remained the same. However, as more standardizations take place, a greater level of detailed data 

will be needed.

Strengths and Limitations of the Energy-Intensity Indicators

The CBECS contains sufficient detail that site energy consumption estimates can be adjusted for some of the major influences 

on changes in energy consumption such as weather and vacancy. The CBECS data, though, are available only every 3 years. 

However, this limitation may not be important because the measurement of energy-intensity may be feasible only every few 

years because of the availability of other data and limited resources.

Table 4.3 presents some of the strengths and limitations of the demand indicators that influence the amount of energy 

consumed in the commercial sector. On needs to remember that the greater the disaggregation of the energy-intensity 

indicator, e.g., a particular energy service such as space heating, the greater are the data needs and the lower the precision 

of the data due to sample-size limitations. The particular use of an indicator, such as for policy program evaluation, may 

dictate the type of indicator and the level of disaggregation needed.

Table 4.3. Strengths and Limitations of the Energy-Intensity Indicators_________________

Energy-Intensity Indicator

Strength of Demand Indicator Used 

in the Energy-Intensity Indicator

Limitation of the Demand Indicator 

Used in the Energy-Intensity Indicator

Energy per Building

Energy per Square Foot

Energy per Square-Foot Hour

Energy per Employee

Energy per GDP Services (1987 Dollars)

• Collected by EIA as part of a detailed 

energy survey

• Vacancy adjustments are possible

• Collected by EIA as part of a detailed 

energy survey

• Demand for major energy services 

such as space conditioning is 

influenced by the amount of 

floorspace

• Vacancy adjustments are possible

• Calculated from EIA CBECS data

• Surrogate for economic activity

• Demand for major energy services 

such as space conditioning is 

influenced by the amount of 

floorspace

• Vacancy adjustments are possible

• Available annually

Data available every 3 years

Data not available for buildings 1,000 

square feet or less

Data available every 3 years

• Does not completely capture the 

operational profile of the building, e.g., 

water heating does not depend on 

floorspace in the building

• Data not available for buildings 1,000 

square feet or less

• Data available every 3 years

• Does not completely capture the 

operational profile of the building, e.g., 

water heating does not depend on 

floorspace in the building

• Data not available for buildings 1,000 

square feet or less

• Not available by detailed characteristics

Capture the operational profile of the 

building for water heating for certain 

building activities, e.g., office buildings

Measure of economic activity « 

Available annually___________

Not available by detailed characteristics

30Adjustments are not uniform over the principal building activities since for each of the building activity types energy demand for different energy 

services and different levels of energy services are not the same.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 25

5. Transportation Sector

Introduction

Energy use in the transportation sector is primarily for passenger travel and freight movements. Passenger travel vehicles 

consist of light-duty vehicles (automobiles, motorcycles, and light trucks) and heavy-duty vehicles (buses, airplanes, boats, 

and trains). The freight modes of transport include truck, air, rail, pipeline, and marine (domestic barge and cargo). Energy 

is also used for military operations and off-highway vehicles used for construction and farming.

Petroleum supplies the vehicles in the transportation sector in the forms of gasoline, diesel fuel, liquefied petroleum gas, jet 

fuel, and residual fuel oil. In 1992, more than 60 percent of petroleum products supplied was gasoline. The transportation 

sector uses very small amounts of other fuels such as natural gas and electricity. 31

In the late 1970's total energy consumption 

(indexed to 1980) grew faster than Gross 

Domestic Purchases (GDP). 32 This pattern 

reversed in the early 1980's and became even 

more pronounced as GDP grew at a faster rate 

than total energy consumption. However, 

total energy consumption increased as well, as 

Figure 5.1 shows. Passenger miles have 

increased 21 percent between 1977 and 1992. 

Populations have increased and people are 

traveling more as the distance between work 

and home has increased. More shipping is 

being done over greater distances. 33

The price of energy during this time was very 

volatile. Between 1977 and 1980, the real 

price of crude oil nearly doubled. It reached 

a peak in 1982 and then dived below the 

prices of the late 1970's.

Chapter Organization

Figure 5.1. Total Primary Transportation Energy, Gross 

Domestic Purchases, and Crude Oil Price 

Indices, 1977 to 1993

160

140 -

120-

8100-

80 -

60 -

40 -

20 -

^Energy Consumption -"-Gross Domestic

T977'1978'1979'1980' 1981' i 982' 198.1'1984'1985' !986 l 198?IW8T i:3P;JTT;»^'n-TTTK •?'•'?•-^

Notes: "Gross Domestic Purchases used to develop the index are in constant 

1987 dollars. "Crude Oil Domestic First Purchase Price Index is in constant 1987 

dollars per barrel, U.S. Average.

Sources: "Energy Information Administration, Office of Energy Markets and End 

Use, Annual Energy Review 1993, Tables 2.1 and 5.17. "U.S. Department of 

Commerce, Bureau of Economic Analysis, National Trade Data Bank, National 

The first presentation will be a detailed Income and Product Accounts, Quantity series.

discussion of the several data sources used for

the analysis in this chapter. This will be followed by a discussion of energy consumption in the transportation sector as a

whole.

The next sections will first discuss U.S. passenger transportation followed by a discussion on U.S. freight transportation the 

topics presented are: energy consumption, demand indicators, and the development of energy-intensity indicators. This 

presentation will be followed by the development of a composite energy-intensity indicator for the entire transportation 

sector. The chapter will end with a discussion of the strengths and limitations of the energy-intensity indicators presented 

in the chapter.

31 As of December 1992, there were 2,240 federal and over 248,000 nonfederal alternative-fuel vehicles. Almost 143 million automobiles and 43 

million light trucks were operated on alternative fuels in the United States in 1991. These 250,240 alternative-fuel vehicles represent less than 0.2 

percent of the passenger vehicles. See Alternatives to Traditional Transportation Fuels: An Overview, DOE/EIA-0585/O (June 1984) for more 

detailed information.

32Gross Domestic Purchases includes imports and excludes exports.

33 For more information, see "Transportation and its Costs" in Transportation Statistics: Annual Report 1994, U.S. Department of Transportation, 

Bureau of Transportation Statistics.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 27
Major Data Sources

U.S. Department of Energy (DOE)

Energy Information Administration

Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national multistage probability 

sample survey conducted on personal vehicles from a subsample of households in the RECS sample from the previous year. 

The first annual RTECS was conducted in 1983 with subsequent surveys conducted in 1985 and triennially thereafter. 

Baseline information about the RTECS household and vehicle stock is collected during the RECS personal interview. Via 

telephone interviews, the data for the following year are collected at two points in time about vehicle stock, vehicle stock 

turnover, new purchases, and vehicle-miles traveled (VMT). A third interview takes place early the following year. The 

RTECS is designed to collect actual VMT for each vehicle in the household by obtaining the odometer reading at two points 

in time. The vehicle characteristic information is collected directly from the respondents and the decoded Vehicle 

Identification Number. Vehicle fuel consumption and expenditures are estimated using vehicle fuel efficiency, presented 

in miles per gallon from the U.S. Environmental Protection Agency and adjusted for in-road degradation, and motor fuel 

prices from the Department of Commerce, Bureau of Labor Statistics, and Lundberg, Inc.

Oak Ridge National Laboratory (ORNL)

Transportation Energy Data Book: Transportation Energy Data Book, Edition 14 and earlier reports. These reports are 

statistical compendiums prepared and published by ORNL under contract with the Office of Transportation Technologies 

in DOE. The data book presents statistics and information from diverse sources that characterize transportation activity and 

presents data on other factors that influence transportation energy use.

U.S. Department of Transportation (DOT)

Bureau of Transportation Statistics

Transportation Statistics: Annual Report 1993 and Transportation Statistics: Annual Report 1994. These two reports 

summarize the state of the transportation system as to : the transportation network, the use of the system, how well it works, 

costs of transportation, safety, and energy and the environment. The data presented are from various agencies, including the 

U.S. Department of Commerce-Bureau of the Census, U.S. Department of Labor-Bureau of Labor Statistics, Eno 

Transportation Foundation, Oak Ridge National Laboratory, and the Department of Transportation-Federal Aviation 

Administration and Federal Highway Administration.

Federal Highway Administration

Nationwide Personal Transportation Survey (NPTS) is a periodic survey of personal travel. The NTPS data are based on 

a nationally representative sample of households from which the amount and nature of personal travel by all modes is 

collected.

Energy Consumption in the Transportation Sector 

Background

In 1992, 27 percent of total primary energy and 37 percent of total site energy was used by the transportation sector. 

Automobiles—both private and business—used 40 percent of the sector's energy, and trucks—light-duty and heavyduty—used 32.7 percent (Figure 5.2).

Energy Information Administration/Energy Consumption Series 

28 Measuring Energy Efficiency in the United States' Economy: A Beginning
In this chapter, only the conventional sources of 

energy used in the transportation sector are 

included in the analysis. These are gasoline, diesel 

fuel oil, jet fuel, residual fuel oil, and natural gas 

and electricity used for pipelines and light rail. 

Other energy sources used in the transportation 

sector are not included in this chapter—methanol, 

ethanol, liquefied petroleum gas, compressed 

natural gas, and other alternative fuels that are 

beginning to contribute to the transportation supply 

mix. The Energy Information Administration is just 

beginning to provide data related to these 

alternative fuels. 34

Choice of fuel varies by transportation mode, e.g., 

automobiles consume gasoline, diesel, and 

alternative fiiels; trucks run on diesel fuel, gasoline, 

and liquefied petroleum gas; aircraft fly with jet fuel 

and aviation gasoline; and marine vessels burn 

distillate and residual fuel oil.

Figure 5.2. Percent of Total Primary Energy

Consumption in the Transportation Sector 

by Transportation Mode, 1992

Off-Highway

Military Operation

Percent of Total Energy

Notes: "Motorcycles account for less than .01 percent of total energy 

consumption in the transportation sector. "Off-Highway includes construction 

and farming. •Electricity losses are included.

Source: U.S. Department of Energy, Oak Ridge National Laboratory, 

Energy Trends Transportation Energy Data Soofc(ORNL-6798), Edition 14, Table 2.9.

Almost 70 percent of the energy used in the F'9ure 5'3' Total Site Ener9Y Consumption in the 

transportation sector is used by passenger modes of Transportation Sector, 1985, 1988, and 1991

travel. The smallest amount is used by the military 

and for off-highway vehicles such as those used in 

construction and farming (Figure 5.3). 35

25.0

The two time intervals used in this chapter are one B 

of growth/growth (1985 to 1988) and one of ? 

growth/recession (1988 to 1991). Site energy | 

consumption grew by 8.4 percent during the •& 

interval of growth/growth, but was essentially flat g 

(actually, 0.4 percent decline), during the interval of 

growth/recession (Figure 5.4).

Although most of the energy used in this sector is 

for passenger travel, the energy used for freight 

transportation grew twice as fast as that for 

passenger travel during the interval of 

growth/growth.

20.0

15.0

10.0

The passenger and freight transportation sectors are 

very different. Each uses different energy sources 

and displays different reactions to price changes. 

The energy efficiency characteristics of each are 

treated separately in the next two sections. 36

Notes: "Other modes include military, off-highway (construction and 

farming), and recreational boats. "The methodologies used to separate air 

passenger and freight and to calculate site electricity for rail and pipeline are 

located in the transportation section in Appendix A.

Sources: "U.S. Department of Energy, Oak Ridge National Laboratory 

(ORNL), Transportation Energy Data Book, Editions 11 and 14 and 

unpublished 1985 data from ORNL. •Department of Transportation, Bureau 

of Transportation Statistics, National Transportation Statistics, September 

1993, Tables 1,4, and 6. *Eno Transportation Foundation Inc., 

Transportation in America 1994, pp. 44 and 49.

34The pilot study of alternative fuel vehicles in Atlanta is the first computer-assisted telephone interview survey of participants in the Clean Cities 

program co-sponsored by the U.S. Department of Energy and the U.S. Environmental Protection Agency.

35In this chapter, passenger vehicles do not include recreational boats. Freight transportation modes do not include foreign air and marine cargo 

movements. Military transportation and other vehicles such as construction and farm vehicles are excluded as well. Marine freight does include 

domestic movements through canals, rivers, the Great Lakes, and along the coasts.

36See Green, David L. And Yuehui Fan, Transportation Energy Efficiency Trends, 1972-1992, Oak Ridge National Laboratory (December 

1994) for a detailed discussion of energy efficiency in the transportation sector.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 29
Figure 5.4. Change in Total Site Energy Consumption in the Transportation Sector, 

by Transportation Mode

a. 1985 to 1988 b. 1988 to 1991

All Modes

Passenger

Freight

Other

40 8.0 12.0

Percent Change

4.0 8.0

Percent Change

Notes: •Other modes include military, off-highway (construction and farming), and recreational boats. »The methodology used to 

separate air passenger and freight is presented in the transportation section in Appendix A.

Sources: »U.S. Department of Energy, Oak Ridge National Laboratory (ORNL), Transportation Energy Data Book, Editions 11 and 

14 and unpublished 1985 data from ORNL. »U.S. Department of Transportation, Bureau of Transportation Statistics, National 

Transportation Statistics, Tables 1,4, and 6 (September 1993). «Eno Transportation Foundation Inc., Transportation in America 1994, 

pp. 44 and 49.

U.S. Domestic Passenger Transportation

Background

When the United States recognized the hazards of its dependency on foreign oil supplies in the aftermath of the first oil 

embargo in 1973, passenger automobile fuel economy averaged only 14 miles per gallon (mpg). Congress responded by 

passing the Energy Policy and Conservation Act of 1975 (Public Law 163), which established Corporate Average Fuel 

Economy (CAFE) standards for each automaker, with domestically produced and imported automobiles counted as separate 

fleets.37 The uniform CAFE standard for automobiles began at 18 mpg with the 1978 model year, increasing to 27.5 mpg 

by 1985. For trucks, the CAFE standard began at 17.2 mpg in 1979, rising to 20.5 mpg by 1987.

Public agreement as to the success of the CAFE standards is still pending. During the time when most of the standards were 

coming into effect, the price of gasoline was sharply increasing. The price increases could have increased the public demand 

for more efficient automobiles. Nevertheless, vehicle fuel efficiencies have increased. Newer automobiles are more efficient 

than older cars, averaging 20.6 to 22.0 mpg for model year 1983 or later compared with 14.1 mpg or less for model year 

1979 or earlier. 38

Passenger Transportation Energy Consumption

Site energy used for domestic passenger travel increased by 6 percent during the growth/growth interval and decreased by 

almost 2 percent during growth/recession interval (Figure 5.4). Automobiles and light trucks are responsible for most of 

the energy consumed in passenger transportation (Figure 5.5). The total site energy used in light trucks grew the most of 

any of the passenger modes during the growth/growth interval (13.2 percent) (Figure 5.6).

Fleet CAFE values are measured as the sales-weighted harmonic mean of individual model fuel economies. These standards are based on tests 

administered by the U.S. Environmental Protection Agency; actual on-road fuel economy is considerably less. CAFE standards for light trucks are 

lower than for passenger cars. See Office of Technology Assessment, Improving Automobile Fuel Economy: New Standards, New Approaches, 

OTA-E-504 (October 1991, for more information.

38'See Chapter 4, "Vehicle Fuel Efficiency and Consumption," in Household Vehicles Energy Consumption 1991 (DOE/EIA-0464(91)) for 

further information.

30

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
All passenger transportation modes except mass Figure 5.5. Site Energy Consumption for Passenger

transit sustained reductions in energy use during 

the growth/recession interval. 39 In fact, mass 

transit energy use, which accounted for no more 

than 1 percent of passenger site energy 

consumption in 1991, increased throughout both 

intervals of time, despite recent survey results 

showing increased preference for personal 

vehicles at the expense of mass transit.40

Travel by Passenger Mode, 

1985,1988, and 1991

Automobiles

002 

Motorcycles o 03

002

Light Trucks

The mode experiencing the smallest decline in General Aviation

site energy consumption during the growth/

recession interval was light trucks. The increased Air carriers

penetration of light trucks with lower fuel

economies than passenger automobiles may be Mass Transit

responsible for this.41

2.00 4.00 6.00

Three modes—general aviation, air carriers, and Quadrillion Btu

motorcycles—exoerienced large oercentaee Notes: • Mass Transit includes buses and passenger rail. .Derivation of motorcyctes—experienced large percentage Jhese numbers are described ,n tne transportation section of Appendix A.

reductions in site energy use during the Sources: U.S. Department of Energy, Oak Ridge Nation Laboratory (ORNL),

growth/recession interval; however, these three Transportation Energy Data Book, Edition 8, Table 1.5, Editions 11 and 14,

modes combined amount to about 10 percent of Table 2-6 ar|d unpublished 1985 data from ORNL.

passenger site transportation energy use. Air

carrier energy use grew by 7 percent during the growth/growth interval, only to shrink by an equivalent amount during the

growth/recession interval.

Figure 5.6. Change in Site Energy Consumption for Passenger Travel, by Passenger Mode

a. 1985 to 1988 b. 1988 to 1991

Automobiles 

Motorcycles 

Light Trucks

General Aviation

Air Carriers

Mass Transit

I 34 

87

- "j 13 - 2 — ]"

] 72

0 0

0 5.0 10.0 15.0 20.0 2.

Automobiles 

Motorcycles 

Light Trucks

General Aviation

Air Carriers

Mass Transit

j.O -2

-LI

-BO j 

-07[j

-I89j . :

-»!—— |

5.0 -20.0 -15.0 -10.0 -5.0

Percent Change 

Note: Mass transit includes buses and passenger rail.

r..c 10.0 i ..:, ID >, as.o 

Percent Change

Sources: »U.S. Department of Energy, Oak Ridge National Laboratory (ORNL), Transportation Energy Data Book, Editions 11 and 

14 and unpublished 1985 data from ORNL. •Department of Transportation, Bureau of Transportation Statistics, National Transportation 

Statistics (September 1993), Tables 1,4, and 6. »Eno Transportation Foundation Inc., Transportation in America 1994, pp. 44 and 49.

39Since rail and bus transit vehicles consume energy whether people board them at full capacity or not, increases in energy use may not necessarily 

signify greater passenger occupancy aboard mass transit.

. Department of Transportation, Federal Highway Administration, Nationwide Personal Transportation Survey: Travel Behavior Issues in 

the 90's.

4l Different CAFE standards apply to trucks and automobiles.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 31
Demand Indicators

A number of possible demand indicators may be considered as drivers of the demand for energy services in the passenger 

transportation sector. None of these indicators is universally applicable to all passenger transport modes:

• Population growth is indicative of the demand for personal or household vehicles, and indirectly for nonresidential 

vehicles to support the economy

• Number of persons working may serve as a good indicator of the demand for business travel, either commuting 

daily by car, bus or rail, or extended business trips by rail or air

• Number of vehicles in each mode is useful for within modes perhaps, but not across modes. It severely restricts 

analysis of high-density vehicles (i.e., buses, trains, and planes carrying more people per vehicle)

• Growth in personal income is an important indicator because in the residential transportation sector, higher incomes 

are more likely to result in the purchase of a second or third car. In 1991, for every additional $16,000 of income, 

vehicle miles traveled increased by approximately 3,000 miles.42

• Number, Frequency, and duration of trips made by passenger vehicles vary significantly. For example, in 1991, 

the average car trip was 9 miles while buses averaged 143 miles and planes 806 miles per trip43

• Fuel cost is considered to be a key determinant of transportation demand—the low price of gasoline, which 

contributes to low overall vehicle operating costs, currently does not appear to be as influential in consumers' choice 

of vehicle purchases in comparison with the 1970's and early 1980's44

• Vehicle-miles traveled mask differences in vehicle occupancy across passenger transport modes and changes in 

occupancy over time—in 1991, automobiles carried on average 1.6 passengers per mile while buses and air carriers 

transported 16.4 and 87.7 passengers, respectively

• Passenger-miles traveled reflects vehicle occupancy within each passenger mode—in 1991 mass transit rail and 

buses traveled more than 12 billion vehicle-miles, compared with 153 billion passenger-miles over the same period.

Trends in Demand Indicators

While the vehicle may be the consuming unit, the energy-service demand is for movement from one point to 

another—distance traveled or a social interpretation would say, 1 trip. Only two of the above indicators include distance, 

Vehicle-Miles Traveled (VMT) and passenger-miles traveled (PMT).

Vehicle-Miles Traveled

VMT grew significantly during 1985-1991 (Figures 5.7 and 5.8), primarily because of the growth in VMT for light-duty 

vehicles (23 percent). Most of this growth took place during the growth/growth interval (Figure 5.8a). Of all of the lightduty vehicles, the light truck experienced the largest growth in VMT, not only for the growth/growth interval, but even larger 

growth during the growth/recession interval.

The mix of light-duty vehicles has changed substantially since 1985. Automobiles, while still dominant, lost a 6-percent 

share among all light-duty vehicles: 72 percent in 1991 compared with 78 percent of all light-duty vehicles in 1985. 

Mini vans, which were just entering the market in 1985, have made substantial market penetration, exceeding 5 million 

vehicles in 1991, or a 3-percent market share. Sport-utility vehicles doubled within these 6 years, from 3.7 million to 7.3 

million vehicles in 1991. Pickup trucks increased in number to almost 26 million vehicles in 1991.

42See EIA's Household Vehicles Energy Consumption 1991, p. 19. (December 1993), (DOE/EIA-0464(91)).

43U.S. Department of Transportation, Bureau of Transportation Statistics, 7990 Nationwide Personal Transportation Survey, Summary of 

Travel Trends, p. 18; Eno Transportation Foundation, Transportation in America 1994, p. 70.

""U.S. Congress, Office of Technology Assessment, Improving Autom 

(Washington, DC: U.S. Government Printing Office, October 1991), p. 2.

""U.S. Congress, Office of Technology Assessment, Improving Automobile Fuel Economy: New Standards, New Approaches, OTA-E-504

Energy Information Administration/Energy Consumption Series 

32 Measuring Energy Efficiency in the United States' Economy: A Beginning
VMT for heavy-duty vehicles showed a 11- Figure 5.7. Demand Indicator, Vehicle-Miles Traveled by 

percent growth during the growth/growth interval Passenger Mode, 1985, 1988, and 1991

and only a 3-percent growth during the 

growth/recession interval. Air carriers 

experienced the largest growth in VMT during 

the first interval (22 percent). « 1,8931

A number effectors are responsible for growth in « 

VMT:

Increasing driving-age population .oco

11985 H1988 CD 199 I

2,016

1,879

1,643mm

Light-Duty Vehicles Heavy-Du^ Vehicles

Growing working population, as more ~ 

women enter the workforce and more m 

families have two income-earners

• Rising real income levels, which make °

airfares and extended trips more affordable Notes: «No change was reported for General Aviation 1985-1988. "Mass

diiorudoic transjt |nc|Udes buses and passenger rail.

Source: U.S. Department of Transportation, Bureau of Transportation

• Rising demand for travel as lifestyles Statistics, National Transportation Statistics, Annual Report (September 1993), 

become more multi-dimensional Tables 5 and 6.

• Increasing average personal trip length (9-percent increase between 1983 and 1990) for almost all purposes45

• Longer commutes as more homes are located outside of central cities.46

• Lower vehicle occupancy, which increases vehicle miles relative to PMT (Figure 5.9).

Figure 5.8. Change in Demand Indicator, Vehicle-Miles Traveled, by Passenger Mode

a. 1985 to 1988 b. 1988 to 1991

I

' Aj! Modes 

j Light-Duty Vehicles

Automobiles 

Motorcycles 

Light Trucks 

! Heavy-Duty Vehicles

• General A^iaton

Heavy-Duty Vehicles ! ______ __ j

...J

30.0 40.0

Percent Change Percent Change

Notes: «No change was reported for General Aviation 1985-1988. «Mass transit includes buses and passenger rail. 

Source: U.S. Department of Transportation, Bureau of Transportation Statistics, National Transportation Statistics, Annual Report, 

September 1993, Tables 5 and 6.

45U.S. Department of Transportation, Federal Highway Administration, Nationwide Personal Transportation Survey: Summary of Travel 

Trends, pp. 33 and 42. The NPTS was conducted in 1983 and 1990.

46This could be mitigated somewhat, by the growth of homes and businesses in the suburbs which would imply shorter commutes.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 33
Passenger-Miles Traveled Figure 5.9. Change in Occupancy by Passenger Mode, 

1985 to 1991

Most of the growth in PMT can be attributed to

light-duty vehicles (Figure 5.10). In 1991, there

were 3.5 trillion passenger miles, of which 2.5 Light-Duty vehicles

trillion were attributed to automobiles. The

number of PMT has continually climbed over

both the growth/growth interval (11.8 percent)

and the growth/recession interval (5.4 percent).

The increasing choice of consumers for light

trucks and air travel is reflected in high increases HeavY-Dutv Vehicles

in PMT by these two modes (Figure 5.11).47

All Modes

Automobiles

Motorcycles 

Light Trucks

PMT by light trucks increased 17 percent during 

the growth/growth interval, almost twice the rate 

of increase for automobile passenger miles. Over 

the next 3 years, light-truck passenger miles grew 

by 6.9 percent, a rate of growth only slightly 

greater than automotive passenger mile growth. 

Passenger demand for automobiles and light 

trucks buoyed an otherwise flat recessionary 

period.

Most of the increases in heavy-duty vehicle use 

took place during the growth/growth interval. 

Passenger demand for air carriers and mass 

transit grew by 20 percent and 17 percent, 

respectively, during these two intervals. PMT by 

these three modes did not increase noticeably 

over the growth/recession interval.

General Aviation

Air Carriers

Mass Transit

-15.0 -10.0 -5.0 0 5.0 10.0 15.0

Percent Change

Notes: Mass transit includes buses and passenger rail. 

Source: U.S. Department of Transportation, Bureau of Transportation 

Statistics, National Transportation Statistics, Annual Report (September 1993), 

Tables 5 and 6.

Figure 5.10. Demand Indicator, Passenger-Miles Traveled 

by Passenger Mode, 1985,1988, and 1991

All Modes

Light-Duty Vehicles

Passenger Transportation 

Energy-Intensity Indicators Heavy-Duty Vehicles

Two energy-intensity indicators are presented in 

this section: VMTandPMT. VMT does not take 

into account the number of passengers in a 

vehicle. Only detailed data on light-duty vehicles 

used by households, are available from the 

RTECS conducted by EIA.

91985 

3.009 •1988

3,192 01991

0 1,000 2,000 3,000 4.000 5,000

Billions of Passenger Miles

Note: Mass transit includes buses and passenger rail. 

Source: U.S. Department of Transportation, Bureau of Transportation 

Statistics, National Transportation Statistics, Annual Report (September 1993), 

Table 6.

PMT accounts for differences in vehicle use and

occupancy. These indicators are presented separately so as not to encourage comparisons. The two different indicators are 

based on two different data sets and vehicle definitions. The RTECS data, the source for VMT, cover only household 

vehicles. The data set used for PMT (DOT) defines vehicles differently, e.g., light trucks are both household and commercial 

vehicles. Additionally, DOT defines light trucks as any 2-axle or 4-tire truck, whereas, EIA's definition is based on weight.

Light trucks include Minivans, sport-utility vehicles, and pickup trucks. See the definition of "Light Truck" in the transportation section of the 

Glossary.

34

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Figure 5.11. Change in Demand Indicator, Passenger-Miles Traveled, by Passenger Mode

a. 1985 to 1988 b. 1988 to 1991

Light-Duty Vehicles [^

Automobiles

Motorcycles

Light Trucks

Heavy-Duty Vehicles

General Aviation

A r Carriers [_

L__ 

Mass Transit HIJ'

All Modes 

Light-Duty Vehicles

Automobiles

Motorcycles j

i Light Trucks |

Heavy-Duty Vehicles j

Genera! Aviation j

Air Carriers 

Mass Transit 

) -15.0 -tOO -5.0

:>'

Zb"

Percent Change Percent Change

Notes: Mass transit includes buses and passenger rail.

Source: "Energy Information Administration, Office of Energy Markets and End Use, 1991 Residential Transportation Energy Survey, 

Public-Use Data Files. »U.S. Department of Transportation, Bureau of Transportation Statistics, National Transportation Statistics, 

Annual Report (September 1993), Table 6.

Trends in Energy-Intensity Indicators

Energy per Vehicle-Mile Traveled

In 1991, the passenger car displayed the lowest energy-intensity indicator of all of the household vehicles, 5.9 thousand Btu 

per VMT. The largest was the large van (9.1 thousand Btu per VMT). In 1991 the sport-utility intensity indicator was 7.9 

thousand Btu per VMT versus 5.9 thousand Btu per VMT for the passenger car (Figure 5.12a). The largest reduction in 

the energy-intensity indicator has been experienced by sport-utility vehicles, a 20-percent reduction in the energy-intensity 

indicator between 1985 and 1991 (Figure 5.13) with most of the reduction between 1985 and 1988, the growth/growth 

interval. However, even with such a large reduction in the intensity indicator, sport-utility vehicles intensity indicator is still 

much higher than the passenger car.

Figure 5.12. Energy-Intensity Indicator for Household Vehicles, by Vehicle Type and Age, 

1985,1988, and 1991

a. Vehicle Type b. Vehicle Age

Passenger Car

Sport-Utility

Large Van

Pickup Truck

0 2.0 4.0 6.0 8.0 10-0 12.0

Thousand Btu per Vehicle Mile

Note: Minivan classification not applicable in 1985.

Sources: Energy Information Administration, Office of Energy Markets and End Use, 1985,1988 and 1991 Residential Transportation 

Energy Consumption Surveys, Public-Use Data Files.

10 or More Years

U1985 

MI1991 ;

----- -—----- - -I

2.0 4.0 6.0 8.0 10.0 12.0

Thousand Btu per Vehicle Mile

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 35
Overtime, each type of passenger vehicle has 

experienced reductions in energy-intensity. In 

fact, vehicle vintage is closely associated with 

household vehicle energy-intensity. Newer 

vehicles were, on average, 12 percent less energy 

intensive per VMT (Figure 5.13) in 1991 then in 

1985. However, the energy-intensity indicator for 

4-6 year-old vehicles in 1991 is no different than 

that of new cars, but substantially better than the 

energy-intensity indicator of 4-6 year-old vehicles 

in 1985 (Figure 5.12). There were 31 percent 

fewer new household vehicles on the road in 

1991, a recession year, than in 1985. Vehicles 

were held longer in 1991 than in 1985. The share 

of vehicles 4 to 6 years old increased from 19.2 

percent in 1985 to 25.8 percent in 1991 (Figure 

5.14).

Figure 5.14 displaying the percent share of 

vehicles by vehicle type and vehicle age, shows a 

reduction in the share of the passenger car and an 

increase in the share of sport-utility, pickup truck, 

and the new Minivan. The gas mileage for these 

vehicles is less than the passenger car, thus 

dampening the reduction in energy-intensity 

indicator for household vehicles as a whole.

Energy per Passenger-Mile Traveled

Among light-duty vehicles, light trucks are the 

most energy intensive, consuming 5.9 thousand 

Btu per PMT in-1991, or two-thirds more energy 

than an automobile, to move one passenger 1 mile 

(Figure 5.15). Among the heavy-duty vehicles, 

general aviation vehicles are the most energy 

intensive, consuming 9.6 thousand Btu per PMT 

in 1991. Smaller general aviation planes 

consumed over two and one-half times more jet 

fuel than commercial air carriers to move one 

passenger 1 mile. Mass transit (buses and rail) 

are the least energy intensive of all modes.

Figure 5.13. Change in the Energy-Intensity Indicator, 

1985 to 1991

a. >i Minivan

J5 Sport-Utility

o

-C Laroe '/an

> Pickup Truck

All 

Nev*

2-3 Years I 

4-6 Years i 

7-9 Years I 

10 or More I

-200 j_

•28 4 [

-35.0 -30.0 -25.0 -200 -5.0

Percent Change in Energy-Intensity Indicator 

(Thousand Btu per Vehicle Mile)

Notes: Mini van classification not applicable in 1985. 'Percent changes are 

based on unrounded numbers.

Sources: Energy Information Administration, Office of Energy Markets and 

End Use, 1985 and 1991 Residential Transportation Energy Consumption 

Surveys, Public-Use Data Files.

Figure 5.14. Characteristics of Household Vehicles, 

1985 and 1991

Passenger Car

Miravar,

Largo '/an 

Pickup Truck

SJ

CD 1985 

BB1991

0 200 400 60.0 800 100.!

Percent Share of Vehicles

Notes: • Mini vans were not available in 1985. «ln 1985 all vans were 

considered large. •Sport-utility In 1991 applies to jeep-like In 1985.

Sources: Energy Information Administration, Office of Energy Markets and 

End Use, 1985 and 1991 Residential Transportation Energy Consumption 

Surveys, Public-Use Data Piles. During the growth/growth interval, all passenger

modes except general aviation reduced their

energy-intensity per PMT. Automobiles reduced

their consumption of motor fuels per passenger mile by almost 6 percent (Figure 5.16). Automobile passenger miles

increased far iaster than automobile energy consumption during the interval, which may be correlated with stock turnovers.

36

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning
Although the energy-intensity indicator for mass 

transit was 8 percent less intensive over the 

growth/growth interval, this intensity indicator 

grew by almost 6 percent over the 

growth/recession interval. Several effects may 

explain these changes. Buses in the United States 

are aging. The federally recommended average of 

12 years for a standard bus and 10 years for a 

medium-duty bus. 48 If age is considered a 

surrogate for physical condition, and if 

deteriorating condition adversely affect intensity 

then the energy-intensity of the aging bus fleet 

will increase. Mainly, though, ridership problems 

are causing these intensity changes. Fewer 

people are using buses for transportation.

Mass transit rail cars and locomotives, stations, 

track, and maintenance facilities are far newer 

than buses. Mass transit travel is most often used 

in the urban areas. Urban areas are most apt to 

have rapid rail systems. As shown in the 1990 

Nationwide Personal Transportation Survey, 

ridership problems face both commuter and 

intercity rail.

Figure 5.15. Energy-Intensity Indicator by Passenger

Transportation Mode, 1985,1988, and 1991

?' ?0 40 C.r 8:.' ';!.'•., • ' t i '" 

Thousand Btu per Ppssfuqf! >v:ii"

Notes: "Mass transit includes buses and passenger rail. • Derivation of 

these estimates are described in the transportation section of Appendix A.

Sources: »U.S. Department of Energy, Oak Ridge National Laboratory 

(ORNL), Transportation Energy Data Book, Editions 11 and 14, Table 2.6 and 

unpublished 1985 data from ORNL. »U.S. Department of Transportation, 

Bureau of Transportation Statistics, National Transportation Statistics, Annual 

Report (September 1993), Table 6.

Figure 5.16. Change in the Energy-Intensity Indicator, by Passenger Transportation Mode

a. 1985101988 b. 1988 to 1991

Petcent Change in Energy-intensity I

(Th'i'js»!i,-< 6t«> fj<»r F'r'Ss^rtQfjr Mi

i cent Change in Erseigy-intensity Indicntoi 

(Thousand Btu per "assenqer ;,We>

Notes: «Mass transit includes buses and passenger rail. • Derivation of these numbers are described in the Transportation section 

of Appendix A.

Source: »U.S. Department of Energy, Oak Ridge National Laboratory (ORNL), Transportation Energy Data Book, Editions 11 and 

14, Table 2.6 and unpublished 1985 data from ORNL. •U.S. Department of Transportation, Bureau of Transportation Statistics, National 

Transportation Statistics, Annual Report (September 1993), Table 6.

The largest reductions in the energy-intensity indicator were registered in air travel. Commercial air carriers reduced the 

energy- intensity of their operations by 11 percent during the growth/growth interval and by another 8 percent during the 

growth/recession interval. This reduction was achieved by increasing passenger miles faster than jet fuel demand during 

the growth/growth interval and by reducing jet fuel demand by 7 percent during the growth/recession interval while moving 

the same number of passenger miles. Flight stage length is a key determinant of energy-intensity.

48U.S. Department of Transportation, Bureau of Transportation Statistics, Transportation Statistics, Annual Report 1994, (January 1994), 

Tables 2-8, p. 30.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 37
Increasing flight stage lengths increase the overall efficiency of the aircraft by: 49

• Reducing the fuel used for taxing, idling, climb-out, and approaches

• Using larger, more efficient aircraft

• Increasing load factors if frequency of service decreases.

Fewer, more efficient aircrafts, with increased passenger loads and traveling over longer distances directly reduces energyintensity.

Between 1988 and 1992, the average flight-stage length has fluctuated between 563.2 miles and 588.4 miles with a slight 

upward trend. 50

U.S. Domestic Freight Transportation 

Background: The Changing Regulatory Environment of Freight Transportation

Rail. Much of the growth in transportation energy consumption between 1973 and 1985 was due to freight energy use. 

Deregulation helped increase the demand for energy from freight carriers.

Rail freight transportation in the United States has a history of regulation and subsidization. Major federal legislation passed 

during the 1970's and 1980's partially deregulated portions of the freight system: The Regional Rail Reorganization Act 

(1973) and Railroad Revitalization and Regulatory Reform Act (1976) provided financial support for bankrupt train 

companies and relaxed some rate regulation by the Interstate Commerce Commission. But the railroads were still considered 

completely regulated until the passage of the Staggers Act in 1980, which removed regulatory control of markets in which 

train companies faced substantial competition, and streamlined regulations relating to company mergers and track 

abandonment.

Trucking. In 1980, only 44 percent of trucking industry movements were regulated,51 essentially that portion of travel under 

Interstate Commerce Commission control. The Motor Carrier Act of 1980 reduced restrictions on entry and expansion in 

the trucking industry and relaxed various regulations. The Surface Transportation Assistance Act (1982) superseded state 

requirements on size and weight limits for trucks." The number of businesses in highway freight transportation appears to 

have grown since partial deregulation in 1980. The Interstate Commerce Commission reports more than 50,000 for-hire 

motor carriers are currently operating. It has been estimated that 74 percent of all intercity freight was carried by regulated 

trucks in 1991."

Other freight modes. Congress deregulated domestic air cargo transport in 1978. However, the authority to block 

discriminatory and preferential rates was retained by the Civil Aeronautics Board until 1984, when the authority was 

transferred to the Department of Transportation. Oil pipelines remain 84 percent regulated by the Federal Energy Regulatory 

Commission. Domestic waterborne cargo is the least regulated portion of the freight industry, with only 8 percent of river 

and canal freight transport regulated in 1991.

49A.B. Rose, Energy-Intensity and Related Parameters of Selected Transportation Modes: Passenger Movements, ORNL-5506 (Oak Ridge, 

TN: Oak Ridge National Laboratory, January 1979), pp. 3 and 4.

50U.S. Department of Transportation, Bureau of Transportation Statistics, Transportation Statistics: Annual Report 1994, pp. 83 and 84.

The percentages are calculated from the portion of freight ton miles carried by the mode. See Eno Transportation Foundation, Transportation in 

America 1994, pp. 17 and 51.

52U.S. Congress, Office of Technology Assessment, Saving Energy in U.S. Transportation, p. 50.

53U.S. Department of Transportation, Bureau of Transportation Statistics, Transportation Statistics: Annual Report 1994, pp. 19 and 20.

Energy Information Administration/Energy Consumption Series 

38 Measuring Energy Efficiency In the United States' Economy: A Beginning
Freight Transportation Energy Consumption

Freight total site energy consumption totaled 5.0 

quadrillion Btu in 1991, representing 

approximately 23 percent of total site 

transportation energy (Figure 5.3). Most of the 

energy was used by trucks, which have access to 

3.9 million miles of roads and streets throughout 

the U.S. highway system (Figure 5.17). For 

nonbulk cargo—mail, perishable foods, packaged 

goods—trucks are the dominant transport mode.54

Figure 5.17. Freight Transportation Site Energy

Consumption by Freight Mode, 1985,1988, 

and 1991

Trucks

Air (Domestic)

The share of energy used by domestic air freight Marine (Domestic)

seems to be growing the most, but data collection

for small package shipments such as Federal

Express, or United Parcel Service did not begin Rai|

until 1986. Therefore, the change in site energy

consumption during the growth/growth interval is

a reflection of this. The growth in site energy

consumption during the growth/recession interval

seems reasonable.

20.0 40.0 60.0 80.0 100.0

Percent of Freight Consumption

Notes: *ln this graph, the share of oil pipeline in total freight consumption 

was less than 1 percent. "Energy for moving water and natural gas Is excluded. 

•Data collection for small package shipments such as Federal Express or 

United Parcel Service did not begin until 1986.

Sources: »U.S. Department of Energy, Oak Ridge National Laboratory 

(ORNL), Transportation Energy Data Book, Edition 8, Table 1.5, Editions 11 

and 14, Table 2.6 and unpublished 1985 data from ORNL.

During the growth/growth interval, site energy 

consumption grew from 3.9 quadrillion Btu to 4.4 

quadrillion Btu (12 percent).55 Most of the 

growth was in the trucking industry (13 percent). 

Domestic marine transportation reduced site 

energy consumption by 19 percent during the interval. Rail energy consumption displayed very little growth (Figure 5.18).

Figure 5.18. Change in Freight Transportation Site Energy Consumption, by Freight Mode 

a. 1985 to 1988 b. 1988 to 1991

All Modes

Trucks

Air (Domestic)

Marine (Domestic!

Oil Pipeline 

Rail

-19.4 f:a;::;;:si!ii:ff:::.;:B:«!SSs!sS

•2.6 H

::R|lilit;Pii| 12.0

Hf|iiNiSi;:i|i3.2

- Withheld

1,3

All Modes

Trucks

Air (Domestic)

Marine (Domestic)

Oil Pipeline 

Rail

-25.0-20.0-15.0-10.0-5.0 0 5.0 10.015.020.025.0

Percent Change

-25.0-20.0-15.0-10.0 -5.0 0 5.0 10.0 15.0 20.0 25.0

Percent Change

Notes: •Percent change in domestic air freight transportation is not shown for 1985 to 1988. •Since data collection for small 

package carriers such as Federal Express did not begin until 1986. *ln this graph, the share of oil pipeline In total freight consumption 

was less than 1 percent. "Energy for moving water and natural gas is excluded. Sources: «U.S. Department of Energy, Oak Ridge National Laboratory (ORNL), Transportation Energy Data Book, Edition 8, Table 

1.5, Editions 11 and 14, Table 2.6 and unpublished 1985 data from ORNL.

54U.S. Department of Transportation, Federal Highway Administration, Highway Statistics 1991, Tables MV-9 and MV-11. 

"Excluding energy for moving water and natural gas.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 39
During the growth/recession interval, site energy consumption fell by almost 8 percent. Over both intervals of time, oil 

pipelines displayed a 3 percent growth in energy consumption.56

The changing structure of the U.S. economy has played a major role in the changing nature of freight transport. The economy 

is providing more higher value-added products that weigh less per dollar of value added than raw materials.57 Air and truck 

carriers are transporting a growing share of these high value added products, at the expense of rail and boat transport. 

Moreover, intermodal freight (carriage on trailers and containers by trains, barges and ships for final delivery by trucks) is 

the fastest growing segment of truck freight.

Freight Transportation Demand Indicators

The freight transportation sector is a very heterogenous sector, making it difficult to find one demand indicator that captures 

changes in demand for all of the various modes.

Using the number of freight vehicles as a demand indicator is inappropriate. Freight vehicles vary by size, weight, speed, 

age, and cost. For example, transport units include a variety of engines or self-propelled vessels (tractor trucks, locomotives, 

towboats, tugs, tankers, ships) and hauled or non-self-propelled vessels (rail cars and barges). In freight handling, one 

engine or self-propelled vessel will drag or push a number of flat hauling vehicles that by themselves do not consume energy.

Employment in rail, marine, truck, or air freight is not a perfect indicator. Employment has stayed constant or fallen since 

1985.58 Freight handling is very labor intensive at the points of origin and destination, but the need for workers during very 

long hauls varies by type of mode. Increasing employment in any particular freight mode would not necessarily be 

considered as the cause of greater energy demands, because the employee is not the consuming unit.

Economic activity is also an imperfect indicator. When the economy is growing, freight revenues increase. The opposite 

is true in times of economic contraction. One way of capturing economic activity is to use the industrial production index 

as a proxy for the demand for freight movements. This index is based on the value of output but freight energy consumption 

is not necessarily a function of the dollar value of manufacturing shipments or value added. Tonnage of freight hauled or 

miles traveled do not necessarily move in tandem with increases in the industrial production index, value of manufacturing 

shipments, or manufacturing value added. Shifts in the product mix that alter the industrial production index, for instance, 

are structural shifts in the manufacturing sector, not the source of efficiency improvements in freight transportation.

The weight of goods moved is more closely associated with the amount of energy consumed than with the value of the 

product transported. If more tons of cargo are moved, independent of the value of the cargo, then more energy is expended. 

Measuring freight movements purely in terms of weight is misleading, given the changing structure of the economy towards 

more lighter, higher value-added products and their domination of freight transport.

The distance the freight travels and the weight of the cargo being hauled measured in miles and tons, respectively, is 

correlated with energy consumption. The demand indicator, ton miles, captures both the weight of the freight and the 

distance it travels. Data available on intercity freight movements most likely underestimates the total amount of miles 

traveled since short hauls within city borders are not included.

Figure 5.19 presents a comparison of the composition of domestic freight by ton-miles traveled and transported for 1985, 

1988, and 1991. In 1991 trucks hauled 42 percent of the weight but only 24 percent of the ton miles. Trucks haul primarily 

lighter, high-value added products shorter distances than other freight modes.

^Pipelines include those moving crude oil, petroleum product, coal slurry, natural gas, and water. This chapter is limited to oil pipelines, since

comparable demand indicator data are not available for natural gas.

"U.S. Congress, Office of Tec 

Printing Office, July 1994), p. 50.

58U.S. Depart 

Table 57, p. 144.

57U.S. Congress, Office of Technology Assessment, Saving Energy in U.S. Transportation, OTA-ETI-589 (Washington DC: U.S. Government

n 

58U.S. Department of Transportation, Bureau of Transportation Statistics, National Transportation Statistics, Annual Report (September 1993),

Energy Information Administration/Energy Consumption Series 

40 Measuring Energy Efficiency In the United States' Economy: A Beginning
Figure 5.19. Domestic Freight Weight and Miles Traveled by Freight Mode, 1985,1988, and 1991

a. Billion Ton-Miles Traveled b. Million Tons of Intercity Freight Moved

Notes: •Figure a: Airmode was 7,9,9 ton miles, respectively, for 1985,1988, and 1991. "Figure b: Air mode was 6,8,7 ton miles, 

respectively, for 1985,1988 and 1991. • Energy for moving water and natural gas is excluded. • Marine ton miles include freight 

transported in rivers, canals, Great Lakes and ocean. • Intercity freight ton miles only are included. "Truck ton miles include both 

Interstate Commerce Commission (ICC) and non-ICC trucks. • Pipeline ton miles represent movement of crude oil and other petroleum 

products (excludes movement of water and natural gas). • Air freight volumes Include Federal Express and UPS small package 

shipments only after 1985 since a data collection for small package shipments such as Federal Express or, United Parcel Service did not 

begin until 1986.

Source: Eno Transportation Foundation, Inc., Transportation In America 1994, 12th Edition, pp. 44 and 46.

The opposite situation faces domestic marine and rail freight modes. In 1991, waterborne carriers haul only 16 percent of 

the total intercity freight but account for almost 25 percent of the ton-miles traveled. Rail freight moves 16 percent of the 

tons but accounts for over 18 percent of the ton-miles traveled. Air freight tons and ton miles are comparable. Air freight 

represents less than 0.1 percent of the tons transported.

Trends in Freight Transportation Demand Indicator

During the growth/growth interval, ton miles grew by almost 9 percent while the growth/recessionary interval basically 

showed no growth. Trucks and rail both registered 15-percent gains in ton miles during the growth years with fewer gains 

during the growth/recession interval (Figure 5.20). Rail relies on coal and farm products for at least half of its business. For 

trucks, no single commodity accounts for more than 16 percent of revenues; agriculture, food, and other manufactured goods 

accounted for 29 percent of the 1991 revenues in the trucking industry.59

During the growth/growth interval, data as mentioned previously, were not collected on the small package carriers until 

1986, but this mode seems to be doing well as ton miles grew by almost 7 percent in the growth/recession interval. Air 

freight focuses on high-value goods with high-time demands, either perishables or high-value technical goods.

The largest reduction in ton miles was experienced by the domestic marine freight mode. Growth in this mode was flat 

during the growth/growth interval and fell by almost 11 percent during the growth/recession interval. Marine transport has 

traditionally hauled lower value-added, heavy cargo. An important factor that may have contributed to a reduction in 

domestic marine ton miles is the rise of imported goods.60 Waterborne carriers rely on petroleum and coal for at least half 

of their revenue.

59U.S. Congress, Office of Technology Assessment, Saving Energy in U.S. Transportation, OTA-ETI-589 (Washington, DC: U.S. Government 

Printing Office, July 1994), pp. 43-46. These pages present a discussion on the types of goods each of the freight modes carry.

^U.S. Congress, Office of Technology Assessment, Saving Energy in U.S. Transportation, OTA-ETI-589 (Washington, DC: U.S. Government 

Printing Office, July 1994), p. 50.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 41
Oil pipeline ton miles track movements in the 

petroleum industry. While domestic crude oil 

production fell 9 percent during the 

growth/growth interval, imports of crude oil grew 

by 60 percent.61 Refinery output increased by 9 

percent during this time.62 Ton miles grew by 7 

percent since most of the refinery output is 

delivered to end users via the product pipeline 

system. During the growth/recession interval, 

domestic crude oil production fell by 9 percent, 

imported crude increased by only 13 percent, and 

refinery output showed very little growth. As a 

result, ton miles decreased by nearly 4 percent.

Freight Transportation EnergyIntensity Indicators

Only one energy-intensity indicator is presented 

for the freight transportation sector, energy per 

ton miles. The heavier the freight, and the more 

miles this freight is carried, the more energy is 

needed. If less energy is used for the same level 

of weight and miles or if more weight is carried' 

and/or more miles are traveled for the same 

amount of energy, then gains in energy efficiency 

may occur depending on the level of any 

structural or behavioral effects that may have 

taken place.

When comparing the energy-intensity indicator 

for freight transportation, energy used for 

nonhauling purposes is included. For freight 

modes, a significant portion of the energy 

expended is attributed to nonhauling purposes, 

e.g., almost half of the energy consumed by 

freight rail is not used to move freight:

Figure 5.20. Change in Ton Miles by Freight Mode

a. 1985 to 1988

All Freight

Trucks

Air (Domestic)

Marine (Domestic)

Oil Pipeline

Rail

-20.0 -10.0 0 10.0 20.0 30.0

Percent Change 

b. 1988 to 1991

40.0 50.0

All Freight

Trucks

Air (Domestic)

Marine (Domestic)

Oil Pipeline

Rail

-20.0 -10.0 0 10.0 20.0 30.0

Percent Change

40.0 50.0

Notes: »ln this graph, the share of oil pipeline In total freight consumption 

was less than 1 percent. "Energy for moving water and natural gas Is excluded. 

•Data collection for small package shipments such as Federal Express or 

United Parcel Service did not begin until 1986.

Source: Eno Transportation Foundation, Inc., Transportation In America 

1994, 12th Edition, p. 44.

• More than 30 percent is used for empty backhaul

• About 4 percent is reported lost or spilled each year

• About 4 percent is consumed in idling

• Ten percent is used by yard locomotives assembling and switching cars.63

U.S. Department of Energy, Energy Information Administration, Office of Energy Markets and End Use, Annual Energy Review 1993, Tables 

5.2 and 5.3, pp. 143 and 145.

62U.S. Department of Energy, Energy Information Administration, Office of Energy Markets and End Use, Annual Energy Review 1993, Table 

5.8, p. 155.

63A.B. Rose, Energy Intensity and Related Parameters of Selected Transportation Modes: Freight Movements, ORNL-5554 (Oak Ridge, TN: 

Oak Ridge National Laboratory, June 1979), pp. S-10 and 5-4.

42

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning
Trends In Freight Transportation Energy-Intensity Indicators

Air freight continues to be the most energyintensive mode of freight transportation (Figure 

5.21). In 1985, air freight required 20 thousand 

Btu to move 1 ton 1 mile. By 1988, during an 

interval of growth/growth, this had climbed to 31 

thousand Btu per ton mile. During the 

growth/recession interval, this grew more slowly 

to 32 thousand Btu per ton mile (Figure 5.21).

Figure 5.21. Energy-Intensity Indicator by Freight Mode, 

1985,1988, and 1991

Trucks

Marine

Rail

Trucks were the second most energy-intensive 

freight mode, requiring 4.8 thousand Btu per ton 

mile in 1985. During the growth/growth interval, 

energy consumption increases were close to that 

of increases in ton miles leading to approximately AII Freight 

a 1 -percent reduction in the energy-intensity 

indicator (Figure 5.22a). During the 

growth/recession interval, energy consumption 

growth fell slightly while ton miles increased by

5,000 10,000 15,000 20,000 25,000

^ ^ Qf Q|| p)pe||ne ,n ^ frelght ^^ was |98S ,nan ,

8.3-percent causing a 7.9-percent decrease in the percent. .Energy for moving water and natural gas Is excluded. -Data

energy-intensity indicator (Figure 5.22b).

Throughout the 1970's and early 1980's, there has

been only modest improvement in truck-fleet

economy, with combination trucks averaging 5.5

mpg and larger single-unit trucks at 7.3 mpg in

1990. Heavy single-unit trucks are twice as energy intensive as light trucks used for passenger travel. On average, a

combination truck requires 3.1 thousand Btu to haul 1 ton of cargo 1 mile in 1991.64

collection for small package shipments such as Federal Express or United 

Parcel Service did not begin until 1986.

Sources: *U.S. Department of Energy, Oak Ridge Nation Laboratory 

(ORNL), Transportation Energy Data Book, Edition 11 and 14, Table 2.6 and 

unpublished 1985 data from ORNL.

Countervailing factors may have yielded small gains in truck fuel economy. Factors that may have contributed to improved 

fuel economy include:

• Increased trip lengths

• Technical improvements in electronic engine controls

• Demand-actuated cooling fans

• Intercoolers

• Low-profile radial tires

• Multiple trailers. 65

The energy-intensity indicator for marine freight transportation decreased by 19 percent during the growth/growth interval, 

only to reverse this improvement during the growth/recession interval with a 14-percent increase in the energy-intensity 

indicator. During the growth/growth interval, much of the decrease resulted from a substantial reduction in consumption 

(19.4 percent) while the energy-intensity increase during the growth/recession interval was due to a large decrease in ton 

miles (10.5 percent). Increased imports reduced the distances that domestic marine freight has to travel. The hauling of raw 

materials and manufactured products, which has traditionally been the domain of rail and marine freight, and any intermodal 

competition has significantly been reduced.

^Department of Transportation, Bureau of Transportation Statistics, Transportation Statistics: Annual Report 1994, p. 153. 

65U.S. Congress, Office of Technology Assessment, Saving Energy in U.S. Transportation, OTA-ETT-589 (Washington, DC: U.S. Government 

Printing Office, July 1994), p. 51.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 43
The following improvements in technology and 

engineering may lead to reductions in the marine 

freight energy-intensity indicator:

• Improved engines, with greater use of fuel 

management computer systems

• Improved matching of barges and tugs

• Improved computer-aided operations

• Improved channels and locks

66 • Use of larger barges and tugs.'

Marine carriers are more energy intensive per ton 

mile than freight-train carriers because the 

density and viscosity of the water are greater than 

those of air. A 10-percent reduction in marine 

operating speeds will yield a 20-percent reduction 

in energy use. 67

The energy-intensity indicator for freight trains 

decreased by 12 percent for each of the two 

intervals, growth/growth and growth/recession. 

In both cases, the decreases in the energyintensity indicator were due to growth in ton 

miles. At the same time, energy consumption 

experienced slow growth (1.3 percent) during the 

growth years and energy consumption fell (7.6 

percent) during the growth/recession interval.

Several rail efficiency improvements may be 

responsible for this reduction:

• Increased average trip length with fewer 

stops and greater sustained speeds

• Improved operations and communi 

cations—routing, scheduling, reduced 

empty car-miles, minimized starts and 

stops, and better matched locomotives and 

loads

Figure 5.22. Change in the Energy-Intensity Indicator, 

by Freight Mode

a. 1985(01988

Trucks

Marine

Rail

Pipeline Oif

-30.0 -20.0 -10.0 10.0 20.0 30.0 40.0 50.0 60.0 700

Percent Change In Energy-Intensity Indicator 

(Thousand Btu per Ton Mile)

b. 1988 to 1991

All

Trucks

Air

Rail

Pipeline Oil

-30.0 -20.0 -10.0 0 100 200 300 40.0 50.0 60.0 70.0

Percent Change In Energy-Intensity Indicator 

(Thousand Btu per Ton Mile)

Notes: «ln this graph, the share of oil pipeline in total freight consumption 

was less than 1 percent. "Energy for moving water and natural gas is excluded. 

•Data collection for small package shipments such as Federal Express or 

United Parcel Service did not begin until 1986.

Sources: »U.S. Department of Energy, Oak Ridge National Laboratory 

(ORNL), Transportation Energy Data Book, Edition 8, Table 1.5, Editions 11 

and 14, Table 2.6 and unpublished 1985 data from ORNL. »Eno 

Transportation Foundation, Inc., Transportation in America 1994, 12th Edition, 

p. 44.

Technical improvements—reduced locomotive idling speeds, improved sizing of auxiliary loads, improved wheel-slip 

detection, greater use of flange lubricators, weight reduction, and aerodynamic improvements.68

66U.S. Congress, Office of Technology Assessment, Saving Energy in U.S. Transportation, OTA-ETI-589 (Washington, DC: U.S. Government 

Printing Office, July 1994), pp. 52 and 53.

67A.B. Rose, Energy Intensity and Related Parameters of Selected Transportation Modes: Freight Movements, ORNL-5554 (Oak Ridge, TN: 

Oak Ridge National Laboratory, June 1979), pp. 4-2 and 4-3.

68U.S. Congress, Office of Technology Assessment, Saving Energy in U.S. Transportation, OTA-ETI-589 (Washington, DC: U.S. Government 

Printing Office, July 1994), p. 52 cites Abacus Technology report without full citation.

44

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning
The oil pipeline energy-intensity indicator decreased during the growth/growth interval (increase in ton miles larger than 

increase in consumption), only to increase during the growth/recession interval (energy consumption increased while ton 

miles fell). In most cases, there are no cheap alternatives to pipeline freight. Consequently, pipelines have encountered 

relatively little competition from other freight modes.

Transportation Energy-Intensity Composite Indicator

It is very difficult to make meaningful comparisons across passenger and freight modes. While both modes are petroleum 

dependent, passenger modes are dominated by gasoline-fueled internal combustion engines, and freight modes are dominated 

by diesel engines. Since there is no common demand indicator that may be used for the entire transportation sector, the 

percent change in the energy-intensity indicators from both passenger and freight travel is used in a transportation sector 

energy-intensity composite indicator. A multiplying factor is used that takes into account the relative share of site energy 

consumption of both passenger and freight modes.69 Two composite energy-intensity indicators are presented. The first 

composite is a "bottom-up" approach that is built up from the individual passenger and freight modes. The second composite 

is a "macro" approach calculated from macro passenger and freight sums.70

Table 5.1 shows the shares of each mode as a percent of total site transportation energy. In both cases, appropriate energy 

shares for the later year in any time interval were used. In this analysis, both composite energy-intensity indicators produce 

similar results, whether the methodology was macro or micro. Over the interval of growth/growth, energy-intensity 

composites show a decrease of 3.4 percent for the macro-transportation composite and 3.6. percent for the microtransportation composite, suggesting that there may be an overall increase in energy efficiency. For the interval of 

growth/recession, the energy-intensity composites also suggesting that there may be an overall increase in energy efficiency, 

keeping in mind possible other structural and behavioral effect that could be affecting the results.

Table 5.1. Building up a Composite Energy-Intensity Indicator for the Transportation Sector

Passenger and Freight Modes

Automobiles ............................

Motorcycles ............................

Light Trucks ............................

General Aviation .........................

Air Carriers ............................

Buses ................................

Passenger Rail .........................

Freight Trucks ..........................

Air Freight" .............................

Marine Freight ..........................

Rail Freight ............................

OH Pipeline .............................

Micro-Transportation Composite ..........

Light-Duty Passenger Vehicles .............

Heavy-Duty Passenger Vehicles ............

Freight Trucks ..........................

Non-Highway Freight .....................

Macro-Transportation Composite .........

I Percent Share of Energy

1988

..... 41.0

..... 0.1

..... 18.8

..... 0.7

..... 6.0

..... 0.7

..... 0.2

..... 15.1

..... 1.3

..... 1.5

..... 2.0

..... 0.1

..... 100.0

..... 60.0

..... 7.6

..... 15.1

..... 4.8

..... 100.0

1991

40.6 

0.1 

18.7 

0.6 

5.6 

0.8 

0.2 

15.2 

1.4 

1.5 

1.8 

0.1 

100.0

59.5 

7.2 

15.2 

4.9 

100.0

Percent Change In Intensity

1985 to 1988

-5.5 

-3.7 

-3.3 

0.7 

-10.9 

-12.4 

-4.9 

-1.4 

54.5 

-19.1 

-11.8 

-8.6 

-3.6

4.2 

-9.7 

-1.4 

1.1 

-3.4

1988 to 1991

-6.9 

-0.3 

-7.1 

-18.9 

-8.1 

9.2 

2.7 

-7.9 

2.1 

13.8 

-11.8 

9.5 

-5.8

-6.9 

-7.1 

-7.9 

2.7 

-5.7

1985 to 1991

-12.0 

-3.9 

-10.1 

-18.4 

-18.1 

-4.4 

-2.3 

-9.1 

57.7 

-7.9 

-22.3 

0.1 

-9.0

-10.8 

-16.1 

-9.1 

3.8 

-8.8

•Air Freight estimate Increased after 1985 because data collection of small packages shipments did not begin until 1986.

Sources: •Department of Energy, Oak Ridge National Laboratory (ORNL), Transportation Energy Data Boole. Editions 11 and 14, 

Table 2.6 and unpublished 1985 data from ORNL. *U.S. Department of Transportation, Bureau of Transportation Statistics, National 

Transportation Statistics, Annual Report (September 1993), Table 6, and earlier publications.

69In Chapter 7, "Economy," the methodology for the economy composite is* presented. The methodology is basically the same as presented here. 

70The more detailed "Micro-Transportation" indicator is the more robust of the two indicators. This is because the more structural and behavioral

effects that could be included before the build up of to the composite, the greater the chance that such effects will be removed.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 45
Strengths and Limitations of the Energy-Intensity Indicators

A strength of the indicators for both passenger and freight transportation modes is that they depend on the energy content 

of the fuel being used. This allows all types of fuel to be evaluated and compared. When alternative fuels develop a 

significant presence in the fuel mix, the analysis used will still apply.

The analysis excluded several modes of both passenger and freight transportation. Off-highway energy use, recreational 

boats, cruise ships, military energy use, natural gas pipelines, and foreign air travel and water cargo were not analyzed 

because of lack of available demand indicators.

Data on the miles traveled and energy used to move passengers and freight are at times imprecise and contradictory. The 

Office of Technology Assessment identified two main reasons for the discrepancies: (1) inconsistent definitions on weight 

class, personal use, intercity movements, and inclusion of government and military vehicles; and (2) inconsistent data 

collection and quality (critical data are extrapolated from limited sample surveys or added from questionable State estimates).

In the study, Transportation Energy Efficiency Trends 1972-1992, limitations of the data are presented including:

• Truck freight ton miles are not reported for all types of trucks

• Pipeline ton miles are not reported annually for natural gas

• Domestic waterborne transport data fluctuate

• Passenger-mile data are interpolated from infrequent surveys.

Data are weak in assessing significant changes in the trucking industry since deregulation. The Motor Freight and 

Warehousing Census tracks trucking performed only by firms engaged in trucking services, excluding the majority of the 

trucking industry: owner-operator trucking, and corporate truck fleets that haul their own goods.71 Since deregulation, 

private fleets provide for-hire services, freight forwarders own their own fleets, and railroads and air carriers increasingly 

own and operate their own trucking fleets.

EIA's definition of light trucks may have affected the estimate of energy usage for this category. The definition of light trucks 

as used by the Eno Transportation Foundation is consistent with the Department of Transportation definition—all 2-axle, 

4-tire single-unit trucks. However, EIA defines light trucks as trucks weighing up to 8,500 pounds. About 99.9 percent 

of the light trucks in the RTECS weighs 8,500 pounds or less. Since some 2-axle 4-tire trucks weigh substantially more than 

8,500 pounds, the energy used for light trucks may have been overestimated.

71 U.S. Department of Transportation, Bureau of Transportation Statistics, Transportation Statistics: Annual Report 1994, p. 61.

Energy Information Administration/Energy Consumption Series 

46 Measuring Energy Efficiency In the United States' Economy: A Beginning
U.S. Energy Information Administration

Transportation Sector Energy-Efficiency Workshop

Workshop Program

nartment of Energy, Washington, D.C. March 19, 19%

8:30 a.m. 

9:00 a.m.

9:05 a.m. 

9:15 a.m. 

9:30-10:30 a.m.

10:30 a.m. 

10:45 a.m.

12.-30-J.-30 p.m. 

1:30-3:00 p.m.

3:00p.m. 

3:15 p.m.

4:15 p.m.

<4:j -t p.m.

Registration

Opening Remarks (Room 6E-069) - Jay Hakes, Administrator, U.S. Energy Information 

Administration

Energy-Efficiency Project - Lyndt T. Carbon, Director, Energy End Use and Integrated 

Statistics Division, U.S. Energy Information Administration

Chapter 5. Transportation Sector Overview and Workshop Format - Stephanie J. Battles, Project Manager, Energy 

End Use and Integrated Statistics Division

I. Expert Reviews (Room 6E-069) - Steve Plotkin, Argonne National Laboratory; K.G. Dulecp, Energy and Environmental 

Analysis, Inc. (Facilitator: Energetics; EIA Observer: Christy Hall)

Break

II. Panel Discussion (Room 6E-069): Energy Efficiency-What is it?; How Should EIA Measure It?; How are the

Measurements Used? - Phillip Patterson, Office of Transportation Technologies, U.S. Department of 

Energy; David Chien, U.S. Energy Information Administration; Joanne Sedor, Bureau of Transportation 

Statistics, U.S. Department of Transportation; Lee Schipper, Lawrence Berkeley National Laboratory 

(Facilitator: Energetics; EIA Observer: Ron Lambrecht)

Lunch Break

Parallel Afternoon Sessions

III A. Nontechnical (Room BE-069): Definition of Energy Efficiency; Usage of Energy 

Efficiency Indicators - Barry McNult, Office of Energy Efficiency and Alternative Fuels Policy, 

U.S. Department of Energy (Facilitator: Energetics; EIA Observer: Leigh Carlcion)

III B. Technical (Room 6E-069): Other Approaches and Techniques - David L. Greenc, Center for

Transportation, Oak Ridge National Laboratory (Facilitator: Energetics; EIA Observer: Ivy Harrison)

Break

IV. Plenary Session (Room 6E-069): What Have We Learned.' - Dwight French, Chief, Transportation and

Industrial Branch, U.S. Energy Information Administration; EIA Observers: Christy Hall, Ron 

Larnbrechl, Leigh Carleton, and Ivy Harrison (Facilitator: Energetics)

Closing Remarks: Where Do We Go from Here? - Lynda T. Carbon, Director, Energy End Use nnd Integrated Statistics 

Division

Adjourn

•p Information, Contact: Stephanie J. Battles, U.S. Energy Information Administration 

Telephone: (202)586-7237 or E-Mail: sbattles@eia.doe.i>ov

Guidelines for Expert Reviewers 

Transportation Sector Energy-Efficiency Workshop

March 19, 1996

General Guidelines:

• Length of Review: 20 minutes 

The Review Should Include But Not Limited To The Following Criteria:

• Identification of strengths

• Identification of technical deficiencies

• Specific remedial suggestions which would bring the measurements into 

compliance with professionally accepted standards

• Specific suggestions to improve usefulness of the energy-efficiency indicators

• Rank ordering of the importance of your suggestions for improvements—both 

technical and usefulness.

Please Send To:

Energetics

501 School Street S.W., 

Washington, D.C., 20024 

ATTN: Andrea Lachenmayr

By March 8. 1996:

• One hard copy of your presentation

• Biographical sketch

• Audio-visual equipment needs

Questions Relating to Your Presentation Contact:

Andrea Lachenmayr (Energetics) 

Telephone: (202) 479-2748

Questions Relating to Other Matters Pertaining to the Workshop Contact:

Stephanie J. Battles (Energy Information Administration) 

Telephone: (202) 586-7237 

E-mail: sbattles@eia.doe.gov

03/OB/ti6 WE!) 100

) Measuring U.S. Energy Efficiency

Steve PlotKn

Argonne National Laboratory

CD My Point of View

* Data User, Policy Analyst

* NOT involved in data collection

Q W/io zs tfie Customer?

* Report doesn't explicitly identify customer

» "One of the Department of Energy's missions is to promote energy 

efficiency to help the Nation manage its energy resources,"

» Presumably, customers are Department of Energy officials

* But report doesn't really talk about customers and their needs

GD Despite This, Does the Report Know its Audience?

* Choices about level of detail appear random

* "Interesting stuff, but why did they choose to tell that to me?"

* Language ranges from nontechnical to "jargon"

CD Is This Subject Important?

* How debate the future without understanding the past?

» What does "understand" mean, and does the repeal help?

» What are the specific impacts of government actions and other factois?

* The report avoids delving into underlying causes

* Why not use the existing literature, e-g. Pisarsld, Grc«n?

Q Some Examples Where "Fleshing Out" Would Be 

Useful

* CAFE standards — did they play any lole in improving fuel economy?

» Is there really any doubt (hey ha d some positive impact on fuel economy?

* EIA could at least separate out the "junk science" from the legitimate analysis

* Role of light trucks on fleet fuel economy

• What types of autos axe replaced?

» Role of technology vs, role of creating new market niches

CD Some Comparisons are Apples and Oranges

* Energy intensity of mass transit buses shouldn't be compared to 

intensity of all automobiles

* "Heavy single-unit trucks are twice as energy intensive as light 

trucks used for passenger travel." Why should we care?

Q Avoiding Naive Comparisons: Energy Intensity of Mass 

Transit Vs. Autos

* Energy used in accessing transit

* Trip Circuity

* Embodied energy
V J ' VI V /

10

11

12

» Travel conditions — mostly city driving, weighted to peaks 

» Not youi average auto drive* (what are you analysing?) 

» Dominance of New Yoik City

CD Measuring Freight Intensity

* One indicator is presented — energy per ton-miles

* Growing importance of high value cargo — less about moving 

"tons" and more about moving "dollars of value."

Q How Should We Deal With Differences Among Data 

Sets?

* Make a determined effort to understand differences, resolve them

* Careful about reporting results that are contradicted in another data set 

» Example: mass transit reported as the least energy intensive mode - but not 

according to the Oak Ridge Transportation Data Book

Q The Flagship Graph Compares Total Primary Transportation 

Energy, Crude Prices, and GDP

«• Does this make sense????

* Never mentioned again

* May be OK for freight

* Personal travel does vary with income, but with lots of other 

things as well

CD Why Did You Choose These Time Periods?

* Short periods don't provide stable trends

* Things change slowly (in all sectors, not just transportation!)
6. The Industrial Sector

Introduction

The industrial sector encompasses more than 3 million establishments engaged in manufacturing, agriculture, forestry, 

fishing, construction, and mining. These industries require energy to light, heat, cool, and ventilate facilities (end uses 

characterized as energy needed for comfort). They also use energy to harvest crop^, process livestock, drill and extract 

minerals, power various manufacturing processes, move equipment and materials, raise steam, and generate electricity. 

Some industries require additional energy fuels for use as raw materials (feedstocks) in their production processes. Many 

industries use byproduct fuels72 to satisfy part or most of their energy requirements. In the more energy-intensive 

manufacturing and nonmanufacturing industries, energy used by processes dwarfs the energy demand for comfort.

The value of industrial output has continued 

to increase, while total energy consumed by 

the industrial sector has fallen. This 

relationship is shown in Figure 6.1, where the 

consumption index for both primary and site 

energy is greater than the output index before 

1980 and less afterward, with the gap 

consistently widening in the late 1980's. New 

energy-efficient technology and the changing 

production mix from the manufacture of 

energy-intensive products to less intensive 

products account for much of this difference.73

In the industrial sector, manufacturing 

establishments consume the majority of the 

energy (Figure 6.2), even though they are far 

outnumbered by nonmanufacturing 

establishments (Figure 6.3).

In this chapter, only the manufacturing sector 

is considered in the development of energyintensity indicators. Data are insufficient to 

permit the development of robust energyefficiency indicators for the nonmanufacturing 

sector.74

Figure 6.1. Output and Energy Consumption Indices for the 

Industrial Sector, 1977 to 1993

160

140 - 

120 -

flOO -

II 

O 80 -

O) t—

X 60 H

13c

40 - 

20 -

0

•*• Industrial Output -"-Primary Consumption -"-Site Consumption

1977 '1978 11979 '1980 '1981 11982 '1983'1984 11965'1986'1987 '1988'5989 '1990 1-991 ' 1992 M993

Note: Gross Product Originating by Industry used to develop the Industrial output 

Index Is In constant 1987 dollars.

Sources: "Energy Information Administration, Office of Energy Markets and End 

Use, Annual Energy Review 1993, Table 2.1. »U.S. Department of Commerce, 

Bureau of Economic Analysis, Survey of Current Business, May 1994, October 

1994, and March 1995.

Historically, data on the manufacturing sector's energy use has also been scarce. This lack of data has made energy-use 

analysis more difficult here than in the other sectors. At the same time, an opportunity is available. A well-conceived 

efficiency analysis could be more important and more beneficial here than any other sector because of the amount of energy 

consumption represented in the sector and the perceived potential for additional efficiency improvements.

72A byproduct fuel is a secondary or additional product resulting from the use of feedstocks or the processing of nonenergy materials.

73 As an interesting note, both primary and site energy were presented in Figure 6.1 to show the effects of a change in the energy mix over time. 

Around 1982, a gap develops between primary and site consumption, reflecting a change in the energy mix to the use of more electricity with its 

inherent losses that occur in the generation and transmission of electricity.

74Agriculture, mining, and construction are represented in the Census Bureau's set of quinquennial economic censuses which provide data on 

expenditures for purchased energy. The 1992 Census reports are not available at the present time. In addition. The Census of Mineral Industries 

collects and publishes data on consumption of purchased energy and consumption of onsite-produced energy. Also, the Annual Farm Costs and 

Returns Survey, conducted by the U.S. Department of Agriculture, is a source of annual data on energy expenditures and respondent-estimated prices 

for certain fuels. These data could only be used for rudimentary analysis.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 47
Industrial energy consumption and associated 

output data are classified by Standard 

Industrial Classification (SIC) in most surveys 

of establishments.75 After the transportation 

sector, the manufacturing sector consumes the 

most energy in the United States. In 1991, 

20.3 quadrillion Btu of energy for all 

purposes including use as feedstocks, or about 

one-third of the total end-use energy was 

consumed in the manufacturing sector (Figure 

6.4).

Of the 20 major industry groups in the 

manufacturing sector, in 1991, 6 groups 

accounted for 88 percent of the consumption 

of energy for all purposes: Food and Kindred 

Products; Paper and Allied Products; 

Chemical and Allied Products; Petroleum and 

Coal Products; Stone, Clay, and Glass 

Products; and Primary Metals. These six 

account for only 40 percent of the output 

value for manufacturing, and as a result, are 

very energy intensive in their production, the 

exception being the Food and Kindred 

Products major group. This SIC industry is a 

high-energy consumer, but not very energy 

intensive as we will see later in this chapter.

Box 6.1.

Standard Industrial Classification (SIC) 

groups establishments according to their 

primary economic activity. Each major 

industrial group is assigned a two-digit 

SIC code. The SIC system, which serves 

as a framework for the collection of 

energy consumption and output data, 

divides manufacturing into 20 major 

industry groups and nonmanufacturing 

into 12 major industry groups. Each 

major industry group is further divided 

into three-digit groups and four-digit 

industries.

Figure 6.2. U.S. Industrial Total Site Energy Consumption, 

1985,1988, and 1991

n ro

3

o

nil 985 MM9S6

Notes: *Total manufacturing estimates Includes raw materials (feedstocks) but 

not by product fuels. • Nonmanufacturing estimates were obtained by subtracting 

MECS estimates from the Industrial estimates presented In the Annual Energy 

Review 1993. »Due to this method, the nonmanufacturing estimates may be too 

low.

Sources: Energy Information Administration, Office of Energy Markets and End 

Use, 1985,1988, and 1991 Manufacturing Energy Consumption Surveys, and 

Annual Energy Review 1993, Table 2.1.

Figure 6.3. Industrial Sector Establishments, 1987

2.500

TBc

(0(/) 3 

O

£

M

C

0)

E

XIra 

LU 

B

JO

£

3

2

1,500

Manufacturing Farms Fisheries Mining ':o'is;ruc!io^

Operation:;

industrial Group

Sources: U.S. Department of Commerce, Bureau of the Census, 1987 

Census of Agriculture, 1987 Census of Mineral Industries, 1987 Census of 

Construction Industries, and 1987 Census of Manufactures.

Chapter Organization

For the purpose of this analysis, the manufacturing sector is divided into three major groups; high-energy consumers; high 

value-added consumers; and low-energy consumers. These are summarized in Table 6.1. The most important group, highenergy users, is presented in detail.

75The Office of Management and Budget derived this hierarchial system. Wherever possible, data presented correspond to the 1987 SIC 

rectification. As a result, 1985 and 1988 data may not be comparable with previously published data.

48

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning
Figure 6.4. Sector Shares of Site Energy Consumption in the United States, 1991

Nonmanutacturing 

(4%)

Manufacturing 

(33%)

Buildings 

(26%)

Transportation 

(37%)

Percent of Total

Notes: «The residential and commercial building sectors are combined into the buildings sector. •Nonmanufacturing estimates were 

obtained by subtracting MECS estimates from the industrial estimates, presented in the Annual Energy Review 1993. »Due to this 

method, the nonmanufacturing estimates may be too low.

Source: Energy Information Administration, Office of Energy Markets and End Use, Annual Energy Review 1993, Tables 2.1 and 2.4.

First, the major data sources are described in detail. As in the previous chapters, the trend in energy consumption in the 

manufacturing sector is shown, followed by a discussion of the demand indicators that influence the amount of energy 

consumed, namely gross output, value of shipments, industrial production, value added, and gross product originating. 

Changes in these indicators will be discussed as well as possible adjustments such as capacity and inventory adjustments. 

The most frequently used energy-intensity indicators will be compared, followed by a comparison of capacity and inventoryadjusted intensity indicators as a form of "closing in on energy-efficiency indicators." Last, the strengths and limitations of 

these energy-intensity indicators will be explored.

Table 6.1. Type of Manufacturing Industry Group

Standard Industrial Code | Major Industry Group Description

High-Energy Consumers

20

26

28

29

32

33

Food and Kindred Product 

Paper and Allied Products 

Chemicals and Allied Products 

Petroleum and Coal Products 

Stone, Clay, and Glass Products 

Primary Metal Industries

The high-energy consumers convert raw materials into 

finished goods primarily by chemical (not physical) 

means. Heat is essential to their production, and steam 

provides much of the heat. Natural gas, byproduct and 

waste fuels are the largest sources of energy for this 

group. All, except Food and Kindred Products, are the 

most energy- intensive industries.___________

High-Value Added Consumers

34

35

36

37

38

39

Fabricated Metal Products 

Industrial Machinery and Equipment 

Electronic and Other Electric Equipment 

Transportation Equipment 

Instruments and Related Products 

Miscellaneous Manufacturing Industries

This group produces high value-added transportation 

vehicles, industrial machinery, electrical equipment, 

instruments, and miscellaneous equipment. The primary 

end uses are motor-driven physical conversion of materials 

(cutting, forming, assembly) and heat treating, drying and 

bonding. Natural gas is the principal energy source.

Low-Energy Consumers

21

22

23

24

25

27

30

31 _______

Tobacco Manufactures

Textile Mill Products

Apparel and Other Textile Products

Lumber and Wood Products

Furniture and Fixtures

Printing and Publishing

Rubber and Miscellaneous Plastics

Leather and Leather Products

This group is the low-energy-consuming sector and 

represents a combination of end-use requirements. Motor 

drive is one of the key end uses.

Source: Energy Information Administration, Office of Energy Markets and End Use, Manufacturing Consumption of Energy 1991, 

DOE/EIA-0512(91).

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 49
Major Data Sources 

U.S. Department of Commerce: Bureau of Census

Census of Manufactures/Annual Survey of Manufactures: Historical and Current Series

The Census of Manufactures (CM) and the Annual Survey of Manufactures (ASM) conducted by the U.S. Department of 

Commerce, Bureau of the Census, provide economic data, such as sales, employment, and expenditures by SIC. The CM 

and ASM collect the same information, and together provide an annual series. The CM is conducted every 5 years, and 

collects the same information from essentially the entire population of manufacturing establishments. The CM does not 

collect data from very small establishments, which are represented instead by administrative records from other sources. 

In the years when the CM is not conducted, the ASM collects the same information from a sample of 45,000 to 55,000 

establishments.

Between 1974 and 1981, the ASM collected data on the amounts of individual fuels and electric energy produced offsite, 

and expenditures for those fuels by SIC. Since 1981, the only energy data provided by the ASM are total expenditures for 

offsite-produced fuels, expenditures for electricity, and the amount of electricity produced offsite. The ASM continues to 

provide information on employment, value of shipments, and other important economic characteristics.

Energy Information Administration

Manufacturing Energy Consumption Survey: Current Triennial Series

The Manufacturing Energy Consumption Survey (MECS), conducted by the Energy Information Administration (EIA), 

provides more detailed energy data than the ASM previously did or currently does. The MECS is the most comprehensive 

source of national-level data on energy-related information for the manufacturing sector. The MECS provided three different 

measures of manufacturing energy consumption. These measures differ in terms of how offsite-produced energy, feedstocks, 

and byproduct energy are accounted for. The MECS measure of offsite-produced energy corresponds to the ASM 

"purchased fuels" definition.

The MECS is a sample of approximately 12,000 (increased to 16,000 for 1991) establishments subsampled from the ASM 

sample. Thus the population represented by the MECS matches that covered by the ASM. However, because the MECS 

is only a sample from the ASM, the MECS estimates do not exactly coincide with the ASM for a given survey year, due to 

sampling variability.

MECS data are available for data years 1985,1988, and 1991. The next MECS will provide data for 1994.

U.S. Federal Reserve Board

Annual Production Indices

The Federal Reserve Board (FRB) produces an annual series of production indices, by two-digit manufacturing SIC. The 

basis of this index is specific to each SIC. In many cases, it is tons of product, indexed to a base year. In other cases, a 

different production measure is used, indexed to the same base year. The FRB production indices are given for 

manufacturing as a whole, and for most two-digit SIC manufacturing groups. For SIC 23 (Apparel) and SIC 39 

(Miscellaneous), however, no FRB production index is defined. 76

See "Industrial Production" in the industrial section of the Glossary for a detailed description of the conversion of this index into constant dollars 

for analysis purposes in this report.

Energy Information Administration/Energy Consumption Series 

50 Measuring Energy Efficiency in the United States' Economy: A Beginning
Other Data Sources

U.S. Department of Labor, Bureau of Labor Statistics, provided the data on the costs of production in the manufacturing 

sector. The U.S. Department of Commerce, Bureau of Economic Analysis, provided the gross product originating data as 

well as the deflators used to obtain constant dollar estimates.77

Energy Consumption in the Manufacturing Sector

Measures of Consumption

Manufacturers use energy sources in two Box 6.2.______________________

major ways. The first use is to produce heat ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

and power and to generate electricity. The Three General Measures of Energy Consumption 

second way in which manufacturers use

energy is as a raw material input to the • Site Consumption of Energy - Used for All Purposes is the

manufacturing process or for some other most comprehensive measure of energy consumption and

purpose usually referred to as nonfuel use. represents the first use of energy sources no matter whether they

Box 6.2 describes the three general are consumed as a fue or as a nonfuel (raw matenal). It does not

c . • , , include byproduct fuels produced onsite from previously- measures of energy consumption used by . r . * r j

EIA. According to the 1991 MECS, the counted energy mputs.

amount of Total Site Consumption of Energy I*., ir * .rr- T* • i j n _• -..,,„ „„ _ . .„. „ • Total Inputs of Energy -It includes all energy sources used to for All Purposes was 20.3 quadrillion Btu. , \. * j j. * i I! •* u.u ,.,,„„„ , .„. ^ „ ,. produce heat and power and to generate electricity whether About two-thirds (13.9 quadrillion Btu) of ^^ ^^ ^ ^^ ft ^^ faw materials

this was used to produce heat and power and

to generate electricity, with about one-third . Offsite-Produced Energy - It includes all energy sources

(6.4) quadrillion Btu being consumed as raw purchased or transferred from offsite to produce heat and power

material. This does not include byproduct md to generate dectricity. M nonfuel uses of energy and al,

fuels produced from previously counted byproduct energy are excluded.

energy inputs. The Total Inputs measure, ••^^^^•I^H^^^MH^^^^M^^^^^MM^^^MMI^H^^^^^^

which does include byproduct fuels, is most

useful in discussions of how energy use in the manufacturing sector compares with energy use in the residential and

commercial sectors. It measures only the energy used for its energy content and not as an input into a manufacturing process.

Therefore, the Total Inputs measure is the measure that will be used in the development of energy-intensity indicators in this

chapter. As in the other end-use sectors, the energy consumption measures used in this analysis do not include the energy

lost in the transmission and generation of electricity. These losses are dealt with in Chapter 7, "The U. S. Economy."

Energy Trends

An ideal trend analysis would include lengthy historical consumption trends for all three measures for the manufacturing 

sector. This is not possible since the first comprehensive data series (MECS) was only first fielded in 1985. There is one 

measure, Offsite-Produced Energy, where trend data can be displayed. The MECS's Offsite-Produced Energy measure can 

be used to continue the data series, "Purchased Fuels and Electric Energy," which was previously collected for EIA by the 

Bureau of Census as a supplement to its Annual Survey of Manufactures.78 Since at least 70 percent of Total Inputs of 

Energy is made of energy sources produced offsite, the Offsite-Produced Energy measure does provide some insight into 

changes in energy consumption in the manufacturing sector from 1977 to 1991.

77These sources of data are described in the industrial section of the Glossary.

78Since the MECS does not collect annual data, EIA developed a method to derive estimates of offsite-produced energy for the missing years 1982- 

84, 1986-87, and 1989-1990. This methodology is developed in Derived Annual Estimates of Manufacturing Energy Consumption 1974-1988 

(DOE/ElA-0555(92)/3).

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 51
As mentioned previously, the 20 SIC's have been 

grouped into three groups: High-Energy 

Consumers, High-Value Added Energy 

Consumers, and Low-Energy Consumers. Figure 

6.5 shows the consumption trends for each of 

these groups from 1977 to 1991 for Off siteProduced Energy. The High-Energy Consumers, 

as a group, reduced energy consumption between 

1979 and 1982, but since then and until recently, 

consumption seemed to have been growing but 

only at a small rate. The High-Value Added and 

Low-Energy Consumers seem to have maintained 

a consistent level of consumption over time. In 

1991, for all manufacturing groups, OffsiteProduced Energy represented an insignificant 2 

percent of the total production costs faced by U.S. 

manufacturers.79

Figure 6.5. Offsite-Produced Energy Consumed for Heat 

and Power and Electricity Generation, 

1977 to 1991

12 -

10 -

CO 8 -

c

o

n

3

o

High Consumers->-High-Value Added-"-Low Consumers

Although this percentage does increase to 3.5 

percent for the High-Energy Consumers, it still is 

a very small portion of all of the costs of 

production that manufacturers face. However, in 

1991, the costs of energy totaled $32.9 billion 

(constant 1987 dollars) for the High-Energy Consumers.

19771 1978' 1979' 19801 1981' 1982' 1983' 19841 19851 19861 198 71 19881 1 983> 1990' 1991

Sources: "Energy Information Administration, Office of Energy Markets and 

End Use, Derived Annual Estimates of Manufacturing Energy Consumption, 

1977-1988 (August 1992), Table 1; and 1989-forward—EIA, Form EIA-846, 

1991 Manufacturing Energy Consumption Survey.

As in the past chapters, the most recent trends of energy consumption in manufacturing are placed into two intervals, 1985 

to 1988 and 1988 to 1991, the intervals of growth/growth and growth/recession. Using these intervals in the analysis in the 

remaining portion of this chapter will allow comparisons of Total Inputs of Energy for heat and power and electricity 

generation (including Offsite-Produced Energy) between the intervals of growth/growth and growth/recession. This will 

allow the usage of the most comprehensive data available, the MECS, in the actual development and discussion of energyintensity indicators in the manufacturing sector.

Total Inputs of Energy for heat, power and electricity generation is shown in Figure 6.6 for each of the three manufacturing 

groups. The High-Energy Consumers consume most of the energy used in the manufacturing sector. All three groups are 

consistent in that during the interval of growth/growth, their energy consumption increased but, during the growth/recession 

interval, it declined (Figure 6.6a). The largest percentage decline of Total Inputs of Energy was experienced by the HighValue Added consumers. These consumers' energy consumption declined by 10.4 percent (0.1 quadrillion Btu). During 

the growth/recession interval, the greatest decrease in energy demand was experienced by firms engaged in producing goods 

that fluctuate with changes in personal income, such as jewelry, bicycles, computers, apparel, and leather.

During this interval, High-Energy Consumers faced a 0.4 quadrillion Btu decline in consumption (2.4 percent decline). This 

group, however, did not experience declines in consumption for each member of the group. Paper and Allied Products and 

Chemical and Allied Products continued to grow after 1988, despite reductions by almost all other industry groups. These 

two industry groups actually experienced increases in energy consumption during the growth/recession interval.

See U.S. Department of Labor, Bureau of Labor Statistics Multifoctor Productivity in U.S. Manufacturing, 1949-1991. Data points in 1985

are based on 1972 SIC; 1988 and 1991 data points are based on 1987 SIC. 

52

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Figure 6.6. Total Inputs of Energy for Heat and Power and Electricity Generation by Manufacturing 

Group, 1985 to 1991

a. Quadrillion Btu b. Percent Change

All Groups

High-Energy Consumers

High-Value AddedM 13

I 1.2

Low-Energy Consumers]! 1.2

3.6 W1985

155 C31988

1E -° W1991

All Groups

High-Energy Consumers

High-Value Added

Low-Energy Consumers

10.0 20.0 30.0 -10.0 0 10.0 20.0 30.0

Sources: Energy Information Administration, Office of Energy Markets and End Use, 1985,1988, and 1991 Manufacturing Energy 

Consumption Surveys.

Chemicals manufacturers exhibited the fastest growth in energy inputs throughout the entire 1985 to 1991. (24 percent) 

(Table 6.2) Petroleum and Coal Products industries were responsible for almost 30 percent of the 1.4 quadrillion Btu 

increase in Total Inputs of Energy despite the extent of the consolidation and plant closings that occurred. During the 1980's, 

mergers and acquisitions contributed to a 15-percent reduction in the total capacity of operable refineries in the United 

States.80 Seventeen less sophisticated refiners (i.e., with older, less energy-intensive capital equipment in place) were put 

out of business in the aftermath of the 1986 oil price crash. Additionally, refiners have increased capacity utilization as 

plants were upgraded to meet additional environmental regulations governing gasoline and diesel fuel.

Table 6.2. Total Inputs of Energy for High Consumers in the Manufacturing Sector, 1985 to 1991

Manufacturing Groups

High Energy Consumers ............................. 1

Food and Kindred Products ............................

Paper and Allied Products ............................. 2

Chemicals and Allied Products ......................... 2

Petroleum and Coal Products .......................... '<.

Stone, Clay and Glass Products ........................

Primary Metal Industries .............................. <

Trillion Btu

985 1988 | 1991

,482 12,950 12,639 

946 996 953 

2,190 2,347 2,472 

2,443 2,862 3,040 

2,593 3,122 2,987 

917 1,000 894 

2,393 2,622 2,292

Percent Change

1985-1988

12.8 

5.2 

7.2 

17.1 

20.4 

9.1 

9.6

1988-1991 | 1985-1991

-2.4 10.1 

-4.2 0.8 

5.3 12.9 

6.2 24.4 

-4.3 15.2 

-10.7 -2.5 

-12.6 -4.2

Note: Total Inputs of Energy do not include energy used as feedstocks.

Sources: Energy Information Administration, Office of Energy Markets and End Use, 1985, 1988, and 1991 Manufacturing Energy 

Consumption Surveys.

Demand Indicators

In the industrial sector, the diversity of processes and ways in which energy is consumed makes it difficult to single out 

characteristics that drive energy consumption activities for all industries. At the two-digit SIC level, there are no consistent 

physical units that can be used to measure demand, e.g., tons could be used in the steel industry, but horsepower may be used 

in another industry. The demand indicators that are presented in detail in this chapter are considered surrogates for 

production. The five different dollar-denominated production surrogates considered as potential demand indicators are: gross 

output, value of shipments, industrial production, value added, and gross product originating (GPO).

'"Calculated from EIA, The U.S. Petroleum Refining Industry in the 1980's, October 1990, Table S7.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 53
All five are presented in constant 1987 

dollars to compensate for inflationinduced price fluctuations. However, 

these measures can still fluctuate due 

to changes in energy prices, cost of 

capital, domestic and international 

taxes, consumer demand, and 

production cycles. Descriptions of the 

demand indicators are presented 

briefly in Box 6.3 and also described 

in the industrial sector section of the 

glossary in this report.

The number of establishments, number 

of workers, and weight of 

manufactured goods could be 

considered as potential demand 

"drivers" or indicators of energy 

consumption in the manufacturing 

sector. These three, though, have 

characteristics that would render them 

unsuitable for usage in the 

development by EIA of indicators of 

energy-intensity in the manufacturing 

sector. The following describes some 

of the reasons why each of the three 

potential demand indicators may not 

be suitable and thus not presented 

further in this chapter:

Box 6.3.

Manufacturing Sector Demand Indicators

• Gross Output - The most comprehensive measure of manufacturing 

production that includes sales or receipts and other operating income 

plus inventory change.

• Value of Shipments - The value of shipments includes the receipts 

for products manufactured, services rendered, and resales of 

products bought and resold without further manufacture.

• Industrial Production - An index calculated by compiling indices 

of physical output weighted by U.S. Census1 value added, and adding 

it to the cost of materials. This is multiplied by the Federal Reserve 

Board's "real value added" to convert industrial production into 

dollars.

• Value Added - A measure of activity derived by subtracting the cost 

of materials, supplies, containers, purchased fuel and electricity, and 

contract work from the value of shipments. In essence, it is the value 

of an establishment's output minus the value of the inputs.

• Gross Product Originating (GPO) - The contribution of each 

industry to gross domestic product (GDP). GPO is equal to an 

industry's gross output minus its intermediate inputs from other 

industries.

(1)

(2)

(3)

Number of Industrial Establishments:

a. Substantial variation in terms of size and equipment in operation 

b. Surveyed by the Bureau of the Census only once every 5 years 

c. Establishment data not used to benchmark MECS

Number of Employees81 :

a. Large variation in plant size and automation

b. No relationship between labor intensity and energy-intensity

Weight of the Manufactured Goods:

a. Data not collected across all industries

b. Would tilt demand towards industries producing heavier materials (e.g., cement and steel) and machinery.

Trends in Demand Indicators

As can be seen in Figure 6.7a, increases in each of the demand indicators occurred during the growth/growth interval of 1985 

to 1988. Earlier, energy consumption also increased during this interval (Figure 6.6).

The demand indicator experiencing the largest increase in the growth/growth interval is the value-added demand indicator 

(34.3 percent). This indicator also is the only demand indicator that did not experience an overall reduction during the 

growth/recession interval of 1988 to 1991 (Figure 6.7b).

Includes production and nonproduction workers.

54

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Figure 6.7. Demand Indicators in the Manufacturing Sector, 1985 to 1991

a. Billion 1987 Dollars b. Percent Change

Gross Output

industrial Production

Value Added

Ciross Product Originating

I 2,306

J 2.574 

I 2,551

l 985

i988 

1991

Gross Output

Value of Shipments -61 [

Industrial Production '

Value Added

Gross Product Originating ;

a 1985-88 

: 1983-91 

11965-9"

0 500 1,000 1.500 2.000 2,500 3,000 -1C.O 0

Note: Confidentiality does not allow EIA to display value of shipments estimates.

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1985,1988, and 1991 Manufacturing Energy 

Consumption Surveys. »U.S. Department of Commerce, Bureau of Economic Analysis, National Income and Wealth Division, "Gross 

Product by Industry, 1947-1991," flies released 12/31/93, and Table D4, "GPO Deflator;" Table D3, "Gross Output for Double-Deflated 

Industries, Fixed 1987 Weights;" Table C1, "Gross Output by Industry, Fixed 1987 Weights." "Federal Reserve Board, Industrial 

Production, provided by Charles Gilbert 10/25/94. »U.S. Department of Commerce, Bureau of the Census, Annual Survey of 

Manufactures, 1985,1988, and 1991, Table 2.

High-Energy Consumers

During the growth/recession interval, the growth in 

the various demand indicators for High- Energy 

Consumers was either minimal or negative (Figure 

6.8a). With the exception of GPO, most of the slow 

or negative growth during the growth/recession 

interval can be attributed to the Stone, Clay and 

Glass Products and the Primary Metals industries. 

However, the Primary Metals industries posted an 

8.7- percent increase in 1988 to 1991 in GPO. The 

Primary Metals industries also posted the largest 

increase in value added during the growth/growth 

interval, 1985 to 1988.

High-Value Added Consumer

The High-Value Added Energy Consumers 

accounted for 47 percent of value added in 1985. 

The share of value added for this group decreased 

to 41 percent by 1991 because industrial machinery 

and electronic products both lost out to costcompetitive imported products.

The High-Value Added Energy Consumers also 

were the largest contributors to industrial 

production and GPO, accounting for 45 percent and 

47 percent, respectively, in 1991. With the 

exception of value added, all of the other demand 

indicators, as shown in Figure 6.8b, decreased 

during the growth/recession interval.

Figure 6.8. Change in Demand Indicators, 1985 to 1991

a. High-Energy Consumer

Gross Output

Value ol Shipments

Industrial Production

Value Added

Gross Product Onginating

| 106

I 11.4

| 106 

I 11 9

m 1985-88

— 1988-91

• 1985-91

-20.0 -10.0 0 10.0 20.0 30.0 400 50.0 60.C 70.0 80.0

Percent Change 

b. High-Value Added Energy Consumer

Gross Output

Value of Shipments

Industrial Production

Value Added

Gross Product Onginating

M1985-88 

Li 1988-91 

• 1985-91

-20.0 -10.0 0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0

Percent Change

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 55
Low-Energy Consumers

The Low-Energy Consumers faced reductions 

in each of the demand indicators, the 

exception being value added (Figure 6.8c). 

These reductions seem to be greater than 

reductions in the other two groups. Most of 

the industry groups within the Low-Energy 

Consumers seemed to have faired poorly 

during the growth/recession interval. One 

apparent exception was the Rubber and 

Miscellaneous Plastics industry, which posted 

increases in all of the demand indicators.

Demand Indicator Adjustments

As is demonstrated in the previous discussion, 

the economic environment may have major 

impacts on the levels of the demand indicators 

that drive energy consumption. These effects 

are, however, structural effects that need to be 

considered when measuring changes in 

energy-intensity indicators in the 

manufacturing sector.

The key drawback for the shipments-based 

demand indicator that it measures the product 

shipped from industries, whether 

manufactured this year or taken from 

inventory. Stock changes can obscure 

production activity in the manufacturing 

sector. Industries that build up stocks will 

underestimate actual production. Similarly, 

for industries depleting their stocks, actual 

production will be overestimated. All 

manufacturers reduced inventory during the 

growth/growth interval and built up some 

inventories during the growth/recession 

interval (Figure 6.9). These movements in 

inventory need to be considered when 

choosing a "best" indicator of energy-intensity 

in the manufacturing sector.

Figure 6.8. Change in Demand Indicators, 1985 to 1991 

(Continued)

c. Low-Energy Consumer

Gross Output

Value of Shipments

Industrial Production

Value Added

Gross Product Originating

-20.0 -10.0 0 10.0 20.0 30.0 40.0 500 60.0 70.0 80.0

Percent Change

Sources: "Energy Information Administration, Office of Energy Markets and End 

Use, 1985,1988, and 1991 Manufacturing Energy Consumption Surveys. »U.S. 

Department of Commerce, Bureau of Economic Analysis, National Income and 

Wealth Division, "Gross Product by Industry, 1947-1991," files released 12/31/93; 

Table D3, "Gross Output for Double-Deflated Industries, Fixed 1987 Weights;" 

Table C1, "Gross Output by Industry, Fixed 1987 Weights" and Table D4, "GPO 

Deflators." "Federal Reserve Board, Industrial Production, provided by Charles 

Gilbert 10/25/94. »U.S. Department of Commerce, Bureau of the Census, Annual 

Survey of Manufactures, 1985,1988, and 1991, Table 2.

Figure 6.9. Changes in Inventory, U.S. Manufacturing 

Sector by Manufacturing Group, 

1984 to 1991

All Manufacturers

High-Energy Consumers

High-Value Added

Low-Energy Consumers

-30.0 -20.0 -10.0 10.0 20.0 30.0

Percent Change

Sources: U.S. Department of Commerce, Bureau of the Census, Annual Survey 

of Manufactures, 1985, 1988, and 1991, Table 2.

The best demand indicator that considers

inventory changes is gross output. The

problem is that, with the exception of value of

shipments demand indicator, gross output and the other demand indicators presented in this chapter have not been corrected

for the SIC reclassification in 1987 from a 1972 base. Using these as demand indicators will not provide as accurate a trend

analysis for the years before 1987. Value of shipments data in MECS have been corrected to SIC 1987 basis in all years,

adjusted by MECS weights and then deflated to constant 1987 dollar.

56 Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Although the value of shipments demand indicator does not take inventory changes into account, it can be revised to reflect 

these changes. 82 Inventory-adjusted value of shipments, also called value of production estimates, act much like weather 

adjusted estimates in the residential and commercial sectors. If stocks are drawn down during the base year (1985), then 

the value of production will be less than the value of shipments for that year.

During the growth/growth interval, as inventories were being drawn down, the percentage increase in the value of shipments 

was more than the percentage increase in the value of production, which reflects the levels of production more accurately 

for all three energy-consuming groups (Figure 6.10a). Without inventory adjustments, decreases in energy-intensity 

indicators and potential increases in energy efficiency during these years might be overestimated.

During the growth/recession interval, inventories increased. The value of shipments was less than the value of production, 

reflecting a lower level of production than actually occurred (Figure 6.1 Ob). Although some of the value of the production 

did not leave the establishments as value of shipments, the actual production of this inventory did take place and energy was 

used in the production process. Decreases in energy-intensity indicators and potential increases in energy efficiency might 

be underestimated if inventory changes are not considered.

Figure 6.10. Changes in Value of Shipments, Value of Production, and Adjusted Value of Production 

by Manufacturing Group

a. 1985 to 1988

All Groups

High-Energy Consumer

High-Value Added

Low-Energy Consumer

lue of Shipments 

of Production 

Adjusted Value of Production

All Groups

High-Energy Consumed

High-Value Added

Low-Energy Consumer

b. 1988 to 1991

-*.ijH "Value of Shipment

-7 2 i I -JVaiue of Produclic

091 niAdjusted v'-?lue of

200 30.0 40.0

Percent Change

50.0 -30.0 -20.0 -10.0 0 10.0 2C.O :iO 0 400 53.0

Percent Change

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1985,1988, and 1991 Manufacturing Energy 

Consumption Surveys. »U.S. Department of Commerce, Bureau of Economic Analysis, National Income and Wealth Division, "Gross 

Product by Industry, 1947-1991," files released 12/31/93, Table D3, "Gross Output for Double-Deflated Industries, Fixed 1987 Weights," 

Table C1, "Gross Output by Industry, Fixed 1987 Weights," and Table D4, GPO Deflators." "Federal Reserve Board, Industrial 

Production, provided by Charles Gilbert 10/25/94. "U.S. Department of Commerce, Bureau of the Census, Annual Survey of 

Manufactures, 1985,1988, and 1991, Table 2.

Capacity-Adjusted Value of Production

Production levels vary in accordance with capacity levels and utilization rates. In some cases, manufacturers predetermine 

the utilization rate to maximize profits or minimize operating losses. The utilization rate takes into account scheduled 

maintenance on plant and facilities, vacation plans, and investment in new capital equipment. Other events, such as 

unscheduled outages, labor strikes or slowdowns, and materials supply bottlenecks, may alter utilization rates. If an 

establishment is not operating at full capacity, energy may still be used but this energy should not be considered when 

attempting to measure changes in energy-intensity. However, at the other end, if an establishment is operating at or near full 

capacity, it may be using all of the equipment it can, including some of the old, inefficient equipment.

l2This methodology is described under "Inventory-Adjusted Value of Shipments" in the industrial section of Appendix A.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 57
Accounting for changes in both inventory and capacity utilization yields a capacity-adjusted value of production demand 

indicator. It is derived by comparing the rate of capacity utilization reported by the Federal Reserve Board for each year and 

the 26-year average (1967-1993) for all major industry groups. 83 Not surprisingly, for most of the major industry groups, 

the average capacity utilization rate is higher than the reported annual rate in 1985 and 1991 (when inventories were being 

drawn down) and the average capacity utilization rate was below the reported annual rate in 1988 (when stocks were built). 

This adjustment smooths the value of production estimates by raising the output in years of low capacity utilization (e.g., 

1985 and 1991) and lowering output in years of high capacity utilization (e.g., 1988). If this adjustment is not applied to 

years of low capacity utilization along with little reduction in the amount of energy consumed for heat and power and 

electricity generation, any measure of energy-intensity would cause its corresponding measurement, energy efficiency, to be 

underestimated. Figure 6.10 shows the resulting percent changes in capacity-adjusted value of production for all the 

consuming groups for both the growth/growth and growth/recession intervals. These are smaller than the percent changes 

in the value of production for both periods. These reflect the adjustments on the value of production estimates upward in 

1985 and 1991 where capacity utilization rates were lower than the 26-year average and adjustments downward in 1988 

when actual capacity utilization rates were higher than the 26-year average.

Energy-Intensity Indicators in the Manufacturing Sector

Energy consumption and the "drivers" of energy Box 6.4

consumption, the demand indicators for the 

manufacturing sector, have been discussed in 

detail. The next step is to construct measures of 

energy-intensity using the two components. The 

ideal would be to be able to measure energy 

efficiency in its purest form. The best that can 

be accomplished is to measure changes in 

energy-intensity, adjust where adjustments are 

possible, and be aware that although reductions 

in energy-intensity may reflect increases in 

energy efficiency, these reflections also contain 

some structural and behavioral influences. A 

general indicator of energy-intensity used in the 

manufacturing sector is energy (thousand Btu) 

per demand indicator (in 1987 dollars). Box 6.4 

lists the various potential indicators of energyintensity in the manufacturing sector. There are choices, though, as to which indicator of energy-intensity to use. Table 6.3 

shows the values of the different choices for energy-intensity indicators. Over all the indicators of intensity, the High-Energy 

Consumers are not only high users of energy, they are the most intensive per dollar of output. One exception is the Food 

and Kindred Products industry group. This industry group is a high user of energy, but not a very intensive user of energy.

The energy-intensity indicators using gross output, value of shipments, value of production, and adjusted value of production 

are comparable while the remaining three indicators measures are roughly twice the value in thousand Btu per dollar. The 

leading difference between gross output and value of shipments is that gross output considers inventory changes while value 

of shipments does not, implying that gross output and value of production are very comparable. One can see the difficulties 

in selecting an energy-intensity measure when measuring the impacts of a particular energy program.

Energy-Intensity Indicators for the

Manufacturing Sector 

(Thousand Btu/1987 Dollar)

Energy / Gross Output

Energy / Industrial Production

Energy / Value Added

Energy / Gross Product Originating

Energy / Value of Shipments

Energy / Value of Production

Energy / Adjusted-Capacity Value of Production

The methodology is presented in the industrial section of Appendix A under "Capacity-Adjusted Value of Production Method."

58 Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Table 6.3. Energy-Intensity Indicators in the Manufacturing Sector, 1985.1988. and 1991

Type of Manufacturing Group

All Industrial Groups

1985

1988

1991

High-Energy Consumers

1985

1988

1991

High-Value Added

1985

1988

1991

Low-Energy Consumers

1985

1988

1991

Energy-Intensity Indicator: Energy/Demand Indicator

(Thousand Btu/Constant 1 987 Dollar)

Demand Indicator

Gross 

Output

5.9

6.0

5.9

12.6

12.9

12.4

1.2

1.3

1.1

1.6

1.8

1.8

Industrial 

Production

12.8

12.7

12.4

31.2

31.8

30.7

2.5

2.4

2.2

3.1

3.5

3.6

Value 

Added

13.9

11.8

10.3

35.7

27.5

24.0

2.5

2.4

2.0

4.9

4.2

3.5

Gross Product 

Originating

16.8

16.8

16.5

44.1

44.0

42.7

3.2

3.1

2.8

3.9

4.6

4.8

Value of 

Shipments

6.1

6.0

6.2

12.3

12.7

12.7

1.3

1.2

1.2

2.5

2.5

2.8

Value of 

Production

6.3

5.9

6.2

12.5

12.7

12.7

1.4

1.2

1.2

2.6

2.5

2.8

Capacity- Adjusted 

Value of Production

6.2

6.1

6.0

12.0

13.0

12.6

1.3

1.2

1.1

2.6

2.5

2.6

Note: Total Input Energy for heat and power and electricity generation is used to compute the intensity indicators.

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1985, 1988, and 1991 Manufacturing 

Energy Consumption Surveys. "Department of Commerce, Bureau of Economic Analysis, National Income and Wealth Division, 

"Gross Product by Industry, 1947-1991," files released 12/31/93; Table D2, "Gross Output for Double-Deflated Industries, Fixed 1987 

Weights," Table C1, "Gross Output by Industry, Fixed 1987 Weights;" Table D4, "GPO Deflators." "Federal Reserve Board, Industrial 

Production, provided by Charles Gilbert 10/25/94. "U.S. Department of Commerce, Bureau of the Census, Annual Survey of 

Manufactures, 1985,1988, and 1991, Table 2.

Energy-Intensity Indicator Trends

Figure 6.11 adds to the choice dilemma when looking at the changes in the various energy-intensity indicators for all 

manufacturing and High-Energy Consumers. The outlier by far is value added. The problem with using an energy-intensity 

indicator based on value added, is that the changes could be a reflection that U.S. manufacturing is responsible for less 

finished goods production as final assembly and processing occurs out of the country. One also has to remember that only 

the energy-intensity indicators using value of shipments has been standardized to the 1987 SIC classification.

Figure 6.11 a shows the changes in the energy-intensity indicators over the growth/growth interval. There seem to be 

conflicting messages, depending on which energy-intensity indicator is used. It does seem though, with the clear exception 

of the intensity indicator using value added, that there have been very slight changes in energy-intensity and thus energyefficiency changes seem to have been minimal for both the manufacturing sector and the high consumers of energy. When 

looking at the interval of growth/recession as shown in Figure 6.1 Ib, the intensity picture changes. It seems that for the most 

part, energy indicators fell implying possible increases in energy efficiency. Again, the reader must be aware that structural 

change could be the influential factor. A huge price increase or other market fluctuation could augment a measure such as 

the value of shipments and make energy-intensity appear reduced. Adjusting for capacity utilization helps strip away certain 

economic effects; however, a dollar-denominated energy-intensity indicator will always be susceptible to such market 

changes.

Other Structural Adjustment Considerations

In addition to the effects economic influences may have on the measurement of energy-intensity, changes in the relative 

market share of major industry groups (in terms of constant dollar value added, value of shipments, etc.) can be used to 

indicate changes in industry structure. EIA has developed a method for examining structural changes by holding the relative 

market share constant (percent share of the value of shipments within each two-digit SIC group) and revising four-digit SIC 

industry data in order to build up a structurally-adjusted intensity measure at the two-digit SIC level. 84

84See Energy Information Administration, "Energy Efficiency in the Manufacturing Sector, Monthly Energy Review, December 1992, for a fuller 

treatment of this topic.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 59
Examination of the components affecting intensity Figure 6.11. Changes in Energy-Intensity Indicators for

measures offers some insight into the structural 

changes of U.S. manufacturing and their impact 

on the efficiency of energy use.

the Manufacturing Sector

a. 1985 to 1988

BSAH Manufacturing Groups dHigh Consumers

If five of the High-Energy Consumers85 are the 

most energy intensive per value of shipments or 

value of production, then reducing their share of 

demand could contribute to an overall reduction 

in energy-intensity for U.S. manufacturing. 

Likewise, the less energy-intensive 

categories—High-Value Added and Low-Energy 

Consumers—could increase their share of 

shipments or production and contribute to 

reduced energy-intensity for the manufacturing 

sector as a whole. For further discussion and 

detailed analysis using this methodology, see 

EIA's publication Changes in Energy-Intensity in 

the Manufacturing Sector 1985 - 1991 

(DOE/EIA-0552(85-91)).

Strengths and Limitations of

the Energy-Intensity

Indicators

In this chapter, energy-intensive indicators were 

developed only for the manufacturing sector. 

Most of the energy used in the industrial sector is 

used in the manufacturing sector. This does not 

lessen the importance attached to the 

development of nonmanufacturing energyintensive indicators. Future work needs to 

incorporate the development of these indicators as 

more data become available or new 

methodologies are developed that will allow the 

use of limited nonmanufacturing data.

The energy-intensity indicators developed in this 

chapter are varied. Each have certain strengths 

and limitations or weaknesses. The demand 

indicators used in the energy-intensity indicators 

are compared in Table 6.4.

Energy/Gross Output

Energy/Value of Shipments

Energy/Industrial Production

Energy/Value Added

Energy/Gross Product Originating

Energy/Value of Production

Energy/Adjusted Value of Production

-30.0 -20.0 -10.0 0 10.0 20.0 30.0

Percent Change 

b. 1988 to 1991

@AII Manufacturing Groups dHigh Consumers

Energy/Gross Output

Energy/Value of Shipments

Energy/Industrial Production

Energy/Value Added

Energy/Gross Product Originating

Energy/Value of Production

Energy/Adjusted Value of Production

-127

-12 9

-1.3 

-3 1 f

•Ml

«L

-30.0 -20.0 -10.0 0 10.0 20.0 30.0

Percent Change

Note: The ratio of the energy-intensity indicator represents changes in 

thousand Btu/1987 dollar.

Sources: 'Energy Information Administration, Office of Energy Markets and 

End Use, 1985,1988, and 1991 Manufacturing Energy Consumption Surveys. 

•U.S. Department of Commerce, Bureau of Economic Analysis, National 

Income and Wealth Division, "Gross Product by Industry," 1947-1991, files 

released 12/31/93, Table D3, "Gross Output for Double-Deflated Industries, 

Fixed 1987 Weights," Table C1, "Gross Output by Industry, Fixed 1987 

Weights and Table D4, "GPO Deflators." "Federal Reserve Board, Industrial 

Production, provided by Charles Gilbert 10/25/94. »U.S. Department of 

Commerce, Bureau of the Census, Annual Survey of Manufactures, 1985, 

1988, and 1991, Table 2.

These are all dollar-denominated surrogates for actual output and as such, a huge price change or other market fluctuation 

could augment or distort the value of shipments and make energy-intensity indicators appear higher or lower than the actual 

change in intensity. Such distortion may cause underestimation and overestimation of energy-efficiency improvements.

The exception is the Food and Kindred Products industry group. Although establishments in this group are high-energy users, they are not 

energy intensive.

60

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Table 6.4. Strengths and Limitations of Demand Indicators Used in the Energy-Intensity Indicators

Energy-Intensity Indicator

(Thousand Btu/1987 Constant Dollar)

Strength of Demand Indicator Used in the 

Energy-Intensity Indicator

Limitation of Demand Indicator Used in 

the Energy-Intensity Indicator

Energy/Gross Output

Energy/Industrial Production

Energy/Value Added

Energy/Gross Product Originating

Energy/Value of Shipments

• Most comprehensive measure of 

production—includes inventory change

• Available annually

• Available annually

• Represents the unique contribution of an 

industry group to the production of finished 

goods

• Available for most nonmanufacturing 

industries

• Published consistently by developed 

countries and used in international 

comparisons

• Includes inventory change

• Available annually

• Provides a better approximation of value 

added

• Consistent 1987 SIC classifications

• Collected by EIA as part of a detailed 

energy survey

• Pre-1987 data are based on the 1972 SIC 

classification

• Establishment data not available

• Pre-1987 data are based on the 1972 SIC 

classification

• Establishment data not available

• Only two-digit SIC classification

• Pre-1987 data are based on the 1972 SIC 

classification

Establishment data not available

Underestimates the contribution of primary 

industries because they do not provide 

high-value components for final goods

• Pre-1987 data are based on the 1972 SIC 

classification

• Establishment data not available

• Data available every 3 years

• Does not consider inventory changes

• Industry value of shipments data are 

confidential

Energy/Value of Production

Energy/Adjusted-Capacity 

Value of Production

Consistent 1987 SIC classifications

Collected by EIA as part of a detailed 

energy survey

Includes adjustments for changes in 

inventory

Consistent 1987 SIC classifications

Collected by EIA as part'of a detailed 

energy survey

Includes adjustments for changes in 

inventory and capacity._______

Data available every 3 years

MECS value of shipments data are 

confidential

• Data available every 3 years

• MECS value of shipments data are 

confidential.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 61

7. United States Economy

Introduction

The information detailed in the past chapters demonstrates the difficulties of developing energy-intensity indicators. For 

sectors such as manufacturing, the choices of energy-intensity indicators are many. For transportation, the choices are few. 

Data are limited in some sectors and abundant in others. As was demonstrated, every sector, especially transportation, has 

complexities.

There are even more complexities across sectors. Energy is consumed differently for different reasons. Structural and 

behavioral effects manifest themselves in different ways. In spite of the difficulties, why is it important to attempt to develop 

an economy-wide energy-intensity indicator?

Environmental concerns and concerns about energy supply require knowledge as to how well we are doing in reducing the 

growth of energy consumption for the Nation as a whole. Basically, households, establishments, etc., change consumption 

patterns that, in turn, affect the amount of energy that flows or is delivered to them. Developing site energy-intensity 

indicators is appropriate at this sectoral level. Primary energy used to generate energy, including all of the losses in 

production, transmission and distribution of energy, must be included in the measurement of changes in energy-intensity for 

the economy as a whole.

Chapter Organization

This chapter first discusses primary or "total embodied" energy in definitional terms. Included is a discussion of the trends 

in energy consumption and the losses associated with energy production, transmission and distribution, and how these losses 

have grown over time. A proposed methodology for the development of economy-wide energy-intensity indicators and the 

limitations of such indicators are presented next. This presentation is followed by the development of economy-wide energyintensity indicators using the methodology, including the development of conversion factors to adjust site energy estimates 

upward to account for losses. Finally, several economy-wide energy-intensity indicators are presented and compared. 86

Primary Energy 

Background

Primary energy includes direct use by end users of fossil fuels (petroleum products, natural gas, and coal) and renewable 

energy (biomass and waste products) and the indirect use of fossil fuels, nuclear, hydropower, geothermal, and other 

renewable inputs in the form of electricity.

Two economy energy-intensity indicators, energy per capita and energy per Gross Domestic Purchases87 are shown in index 

form in terms of primary and site energy (Figure 7.1). Indices of energy per capita rose in the early 1980's and remained 

higher than indices of energy per Gross Domestic Purchases, as economic growth outpaced population growth during the 

sustained economic expansion of the 1980's.

The difference between the estimates of primary energy and site energy has grown overtime (Figure 7.1). The indices using 

primary energy were slightly below their site energy counterparts in the 1970's, but were higher by the mid-1980's. The 

indirect consumption of energy as the inputs into electricity generation has grown over time as electricity consumption to 

end users has grown by 47 percent from 1977 to 1993. 88 This suggests increases in aggregate losses associated with time 

generation, transmission, and the distribution of energy.

86A more detailed but similar approach is described under "Energy-Weighted Index" in the economy section of Appendix A. 

87Gross Domestic Purchases is used instead of Gross Domestic Product since it includes all personal consumption, gross private- domestic 

investment, and government purchases (Federal, State, and local) including imports, but not exports. 

88See Table 8.1 in EIA's Annual Energy Review 1993.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 63
Production, transmission, and distribution Figure 7.1. U.S. Economy Indices of Energy-Intensity 

losses occur among all energy sources, but the Indicators, 1977 to 1993

magnitude differs widely. The next two 1 

sections describe these losses for natural gas 

and electricity. 1

Energy Production Losses

Natural Gas. The energy losses in the 

production of natural gas include losses from 

repressuring gas into the wells, removing 

nonhydrocarbon gasses, venting and flaring 

certain amounts of gas during the extraction 

process, "extraction losses" or the removal of 

liquid constituents from the dry gas. Losses 

also occur in the inter- and intrastate pipeline 

distribution system. Operation of today's 

processing and pipeline systems were 

significantly modernized in the late 1980's 

through utilization of remote-terminal units, 

microwave communications, and 

computerized-control systems. 89 This 

modernization has reduced losses.

° 100 - 

II 

o

CO

O) 90

0)

C 80

70 -

— Primary Energy/Gross Domestic Purchases

—-Primary Energy/Per Capita

••-Net Energy/Gross Domestic Purchases

-*-Net Energy/Per Capita

1977M 978 '1979'1980'1 981 '1982'1983'1 98411985 '1 986 'igST'i

Year

7! 989M990 '1 991T992 M 993

Note: Gross Domestic Purchases used to develop the indices is in constant 

1987 dollars.

Sources: 'Energy Information Administration, Office of Energy Markets and End 

Use, Annual Energy Review 1993, Tables 1 .5 and 2.1 ; »U.S. Department of 

Commerce, Bureau of Economic Analysis, National Trade Data Bank, National 

Income and Products Accounts, Quality Series.

Electricity. Losses in the production of electricity are much higher than those from the production of natural gas. Electricity 

is generated by several different processes, each using different raw resources and each involving different amounts of energy 

losses. Most of the energy losses in the generation of electricity occur when heat is converted into mechanical energy for 

turning electric generators. Other losses include power plant use of electricity and losses due to transmission and distribution 

of electricity from the power plant to the end user. The system losses do change from year to year due to changes in the mix 

of inputs used to generate the electricity: coal, natural gas, petroleum products, hydropower, nuclear power, wind, sunlight, 

and geothermal heat. Therefore, for each year, there is a different multiplication conversion factor.

Economy-Wide Energy-Intensity Indicator: Methodology

As demonstrated in the previous sections, primary energy estimates including losses should be used when developing an 

energy-intensity indicator for the economy as a whole. Additionally, estimating primary energy consumption, sector by 

sector, provides more insight than simply using total primary energy data for the economy as a whole. Regional and sectoral 

differences can help explain changes in energy demand.

Methodology

The first step in the development of economy-wide energy-intensity indicators is to develop energy-consumption estimates 

for each of the sectors. This methodology may be used to develop primary, unadjusted site, or adjusted site economy-wide 

energy-intensity indicators.90

Next, for each sector, develop sector-specific energy-intensity indicators.

Finally, as a last step, add each of the sector energy-intensity indicators together into one economy-wide composite.

''National Petroleum Council, The Potential for Natural Gas in the United States, December 1992, p. 113.

90Adjusted site energy includes adjustments for weather, structural, and behavioral effects where possible. Primary energy estimates can also be 

adjusted, but was not done in this analysis.

64 Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
Changes in energy-intensity overtime could be estimated using the economy-wide indicators. This would provide insight 

into changes in energy efficiency. Three composites can be created, based on primary energy, unadjusted site, and adjustedsite energy.

The next sections discuss each of the individual steps listed above using this methodology to develop such energy-intensity 

composite indicators for the U.S. economy. The section also discusses obstacles associated with the third step of the 

methodology and how they may be overcome.

Step I: Development of Energy Estimates, Primary and Site Adjusted

Primary Energy Estimates. Primary conversion factors are calculated. These vary regionally according to the mix of fuels 

used directly or indirectly for electricity generation. For each of the sectors, these conversion factors convert site-adjusted 

estimates of energy consumption into primary energy estimates.

Adjusted-Site Estimates. Using a sectoral approach site energy is adjusted by weather, behavioral, or other structural 

effects that may increase or reduce actual energy consumption.

In the residential sector, site energy is adjusted by heating and cooling fluctuations relative to a normal 30-year average 

expectation for weather, in order to compare what energy demand might have been had the weather been normal. In this 

way, excess demand could be explained in terms of unusual weather patterns.

In the commercial sector, site energy is adjusted by both weather and occupancy, taking into account the fact that energy 

demand is nominal in a vacant building. By eliminating vacant buildings, commercial energy data more realistically reflects 

actual per building usage.

In the Industrial sector, manufacturing value of shipments is adjusted by inventory changes and capacity utilization. By 

eliminating stock build-ups or depletions in any year, industrial production can be more realistically measured. By 

considering capacity utilization, periods of low or excessive product demand can help explain variations in energy demand.

In the transportation sector, the demand for passenger travel (vehicle miles traveled) is adjusted by occupancy. A vehicle 

traveling 100 miles with four passengers represents twice as much demand as a vehicle traveling 100 miles with two 

passengers.

Using adjusted site energy in the development of energy-intensity indicators as a basis for evaluating changes in energy 

efficiency is only one concept of energy efficiency based on the effects they adjust for.

Step 2: Develop Sector-Specific Energy-Intensity Indicators

Activity in each sector of the economy is measured uniquely. The demand indicators for each sector are parameters that 

influence energy consumption such as: the number of buildings, operating hours, the number of workers in a building, and 

the size of a building as measured by its floorspace. For instance, the residential sector measures its activity in terms of the 

number of households owned and rented, whereas the freight transportation sector measures activity in terms of ton miles 

traveled. There is no demand indicator common to all sectors, so sectoral energy-intensity indicators will be unique to each 

sector.91 This leads to the major obstacle in Step 3—adding unique sectoral-intensity indicators together to obtain an 

economy indicator of energy-intensity.

''Sectors, in this report are defined by the standard energy convention: residential, commercial, industrial, and transportation. This is a different 

accounting framework than reflected in the National Income and Product Accounts and the Input-Output Accounts, where sectors reflect SIC 

categories. Creative use of the Gross Output by SIC sector may provide the common denominator for the residential, commercial, industrial, and 

transportation sectors.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 65
Step 3: Adding the Sectoral Energy-Intensities

The actual sectoral energy-intensity indicators cannot be added together, but an alternative is changes in an economy-wide 

energy-intensity built up from the changes in the sectoral energy-intensity indicators. For any given period of time, an 

economy composite energy-intensity indicator can be developed by weighing each of the sectoral changes in each of the 

indicators by the percent share of total consumption that each sector holds.

Box 7.1 provides an example of the development of such an economy-wide energy-intensity composite. The advantage of 

this methodology is that this single economy-wide energy-intensity indicator reflects the uniqueness of each sector, and can 

be adjusted for some of the weather, structural, and behavioral effects that can affect measures of energy-intensity such as 

those listed in Step 1 above. The next section attempts to develop economy energy-intensity composites using the 

methodology presented in this section.

Box 7.1

Economy Energy-lntensity Composite Example (1980-1990)

Sectors Share of Total Consumption (1990) Change in Intensity (1980-1990)

ResMential .15 -2

Commercial .11 -2

Industrial .37 -4

Transportation .37 -3

Economy Composite (Percent Change) =; multiplicative sum of percent share by percent intensity change 

Composite a .15(-2) + .11 (-2) + .37 (-4) + .37 (-3) = -2.8

Notes: • The example is for illustrative purposes only. •Three composites may be developed using different measures of energy: primary, 

unadjusted site, and adjusted site. •The composite could be developed starting at a lower level than sector, e.g., housing unit, SIC, 

transportation mode, or building activity depending on the available data.

Energy-Intensity Composite: A Measure of Change 

in the U.S. Economy

This section will demonstrate the use of the methodology presented above. An economy energy-intensity composite (hereafter 

called economy composite) will be developed using changes in energy-intensity indicators based on adjusted site energy 

reflecting weather, behavioral, and structural changes. This economy composite will be compared to an economy composite 

developed based on changes in energy-intensity indicators using unadjusted site energy. Although an energy composite will 

be developed based on changes in intensity indicators using primary energy, adjustments to reflect behavioral and structural 

changes will not be developed in this report.

Obstacles to Overcome

Two major obstacles must be overcome in the development of economy composites. The first is the limited availability of 

comprehensive energy consumption data for the two comparison years. This is an obstacle whether the economy composite 

uses changes in intensity-indicators based on primary or site energy (unadjusted or adjusted). The second major obstacle 

is the necessity of developing primary conversion factors. These are needed to convert site energy into primary energy so 

that losses in production, transmission, and distribution can be included in an economy primary energy composite.

Energy Information Administration/Energy Consumption Series 

66 Measuring Energy Efficiency in the United States' Economy: A Beginning
Available Comprehensive Data for Consistent Time Periods

The best consumption data available are from EIA's consumption surveys for the manufacturing, commercial, residential, 

and residential transportation sectors. Transportation sector data are available Oak Ridge National Laboratory for other 

modes of transportation. The major obstacle is time coverage. EIA's consumption surveys do not cover the same years. 

Therefore, the only solution is to create an, e.g., "1985-1988" economy composite instead of a true 1985-1988 economy 

composite. This solution is not perfect, but it is the best solution until further research detects another solution.

Development of Primary Conversion Factors

Information on losses is not available for all energy sources. 92 Primary conversion factors are available or can be developed 

for natural gas and electricity.

Electricity. Electric utilities, and by association, nonutility generators,93 can fully measure their generation and transmission 

and distribution (T&D) losses by fuel input (i.e., fossil fuel, nuclear, hydropower, and geothermal). In the development of 

an economy composite using changes in energy-intensity indicators based on primary energy, annual primary conversion 

factors for electricity by region are developed from the losses. These standard, useful measures of the efficiency of electricity 

generation and T&D are multiplied by regional site electricity requirements for each sector of the economy in order to 

estimate primary electricity consumption. The primary conversion factors developed for electricity vary by year and Census 

region (Table 7.1).94

Table 7.1. Regional Primary Conversion Factors for Electricity, 1984 to 1992

Year

1984

1985

1986

1987

1988

1989

1990

1991

1992

Primary Conversion Factor

Census Region

Northeast

3.241

3.353

3.641

3.649

3.599

3.592

3.618

3.647

3.639

Midwest |

3.390

3.396

3.518

3.513

3.524

3.547

3.535

3.577

3.544

South

3.597

3.632

3.570

3.538

3.518

3.516 •

3.435

3.456

3.452

West

3.692

3.687

3.772

3.731

3.670

3.669

3.678

3.648

3.636

Note: See "Primary Electricity Conversion Factors for Site Electricity" in the U.S. Economy section of Appendix A, "Methodology."

Natural Gas. Natural gas T&D losses are more difficult to measure since they are pipeline specific. Losses on the total 

amount of natural gas passing through the entire system vary with the volume of gas and distance traveled in the pipeline. 

Industry experts within EIA and the American Gas Association came to the conclusion that 1.02 was a reasonable estimate 

to be used as a primary conversion factor in the development of primary energy estimates. This conversion factor for primary 

natural gas used in this chapter is less sophisticated than the one developed for electricity. It is a single multiplier, regardless 

of year or region.

Other Energy Sources. Energy losses in pipeline, marine, and truck transportation as well as in bulk storage and 

distribution facilities have not been quantified for either petroleum or coal products.

92Losses occurring in the extraction and production phases for coal, petroleum, and natural gas are accounted for in mining, which pertains to the 

nonmanufacturing industrial sector. Energy losses at refineries are also generally included in the industrial sector 

93See "Nonutility Generator" in the U.S. Economy section of the Glossary for a description. 

94See "Primary Conversion Factors for Site Electricity" in the U.S. Economy section of Appendix A, "Methodology."

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 67
Development of Primary Energy Estimates

Primary energy can be estimated by summing the site energy consumption for each sector, multiplied by the primary 

conversion factors at the regional level.95 This represents approximately 86 percent of the primary energy reported by EIA 

in Table 2.1 in the Annual Energy Review 1993 (AER 93). The only energy estimates omitted by this method are primary 

energy estimates used in mining, agriculture, forestry, recreational boats, and military transport vehicles. Comparing percent 

changes over time for the derived primary energy and AER93 primary energy consumption data for 1985-1988 and 1988- 

1991 reveals the following:

Derived 

AER93

1985-1988

10.0 percent 

8.4 percent

1988-1991

-1.3 percent 

1.1 percent

Energy-Intensity Indicators for the U.S. Economy: The Economy Composites

For 1985,1988, and 1991 economy composites have been developed using site energy, adjusted site energy, and the primary 

energy estimates described in the last section. Figure 7.2 shows the changes in these composites during both the intervals 

of growth/growth and growth/recession. Additionally, this figure also shows the changes in the two energy-intensity 

indicators depicted earlier in Figure 7.1.

Figure 7.2. Change in U.S. Energy-Intensity Indicators

a. 1985101988 b. 1988to1991

Site Energy/GDP

Primary Energy/GDP

Site Energy/Capita

Primary Energy/Capita

Composite 

(Unadjusted Site)

Composite 

(Unadjusted Primary)

Composite 

(Adjusted Site) _.._.

Site Energy/GDP

Primary Energy/GDP

Site Energy/Capita

Primary Energy/Capita

Composite 

(Unadjusted Site)

Composite 

(Unadjusted Primary)

Composite 

(Adjusted Site)

-6.0 -4.0 -2.0 2.0 4.0 6.0 8.0 -6.0 -4.0 -2.0 2.0 4.0 6.0

Percent Change Percent Change

Note: In these figures GDP stands for Gross Domestic Purchases. Gross Domestic Purchases is in constant 1987 dollars and 

includes imports and not exports.

Sources: "Energy Information Administration, Office of Energy Markets and End Use, Annual Energy Review 1993, Tables 1.5 and 

2.1; 1986,1989, and 1992 Commercial Buildings Energy Consumption Surveys; 1894,1987, and 1990 Residential Energy 

Consumption Surveys; 1985,1988, and 1991 Manufacturing Energy Consumption Surveys. »U.S. Department of Commerce, Bureau of 

Economic Analysis, National Trade Data Bank, National Income and Products Accounts, Quality series. «U.S. Department of Energy, 

Oak Ridge National Laboratory, Transportation Energy Data Book, Editions 11 and 14. »U.S. Department of Transportation, Bureau of 

Transportation Statistics, National Transportation Statistics (September 1993), Tables 1,4, and 6. «Eno Transportation Foundation, 

Inc., Transportation in America 1994, pp. 44 and 49.

The methodology and an example can be found under "Development of Primary Energy Estimates" in the U.S. Economy section of Appendix A.

68 Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning
During both intervals, Gross Domestic Purchases grew faster than primary energy consumption, resulting in declining energy 

per dollar of Gross Domestic Purchases. During periods of economic growth, the primary energy per dollar Gross Domestic 

Purchases ratio overestimates the true reduction in energy-intensity, whereas in periods of recession, the primary energy per 

dollar Gross Domestic Purchases ratio underestimates the reduction in energy-intensity. In the latter case, the energy per 

Gross Domestic Purchases ratio may simply eliminate the impact of weather, behavior, or other structural effects that may 

have occurred during the recession rather than representing true efficiency improvements. 96

Population growth remained very steady, averaging approximately 3 percent over both intervals. The major contraction in 

primary energy growth during the growth/recession interval (down to 1.1 percent from 8.4 percent in the growth/growth 

interval) resulted in very distinct percent changes in primary energy per capita ratios. Another interesting finding is that the 

economy's primary energy composite registers the same percent change as the primary energy per capita ratio during 

recessionary times. This could be interpreted to mean that without strong economic growth, population is the strongest 

variable influencing energy-intensity changes. Population is an important demand indicator in residential and passenger 

transportation energy consumption.

Energy-intensity changes are the smallest economy-wide when examined in terms of primary energy, especially during the 

growth/recession interval, highlighting the effects of increases in electricity consumption by end users.

Site energy-intensity indicators need to be examined without weather, behavior, and other structural effects that camouflage 

the true efficiency improvements in the sectors. In Figure 7.2, note how adjusting for weather in the commercial and 

residential sectors, occupancy in the commercial sector, and inventory changes and capacity in the manufacturing sector 

reduces the magnitude of the change in the energy composites during growth/growth interval and increases it during the 

growth/recession interval.

Strengths and Limitations of the Economy-wide 

Energy-Intensity Indicators

Building a composite from the specific energy-intensity changes in each sector provides far greater insight than energy per 

GDP or energy per capita. A composite using population is inappropriate since not all sector activity responds to changes 

in population; e.g., the industrial sector's output cannot be related directly to population growth. Likewise, it would be 

difficult to build a composite using GDP since the estimation of each sector's contribution to GDP is not an exact science.

Using demand indicators such as ton miles allows each sector to be measured uniquely. A limiting factor is that the 

availability of consumption survey data used to create the composite are available only every 3 years. Additionally, the 

available 3 years are not the same 3 years for each of the surveys. Thus, the composite developed in this chapter is far from 

perfect, but indeed is a "beginning" in the development of energy-intensity indicators for the economy as a whole.

96If Gross Domestic Product was used as the demand indicator instead of Gross Domestic Purchases, the percent changes would not be too 

different. From 1985 to 1988, Site Energy/Gross Domestic Product decreased by 1.1 percent and Primary Energy/Gross Domestic Product decreased 

by 1.6 percent. From 1988 to 1991, Site Energy/Gross Domestic Product decreased by 1.7 percent and Primary Energy/Gross Domestic Product 

decreased by 1.0 percent.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 69

8. Future Directions

The Energy Information Administration presents this publication as a beginning attempt to obtain a consensus on the 

definition of energy efficiency and on the development of energy-intensity indicators that are precise, valid, reproducible, 

and as robust as possible for each economic sector, within the limits of data and resource availability.

Energy efficiency is a vital component of the Nation's energy strategy. One of the Department of Energy's mission objectives 

is to promote energy efficiency to help the Nation manage its energy resources. The ability to define and measure energy 

efficiency is essential to this objective. In the absence of defensible energy efficiency measures, any change in consumption 

might be equated with change in energy efficiency even if such fluctuations are caused by structural or behavioral effects.

The preceding chapters illustrate some of the obstacles to measuring energy efficiency on an economy-wide basis: lack of 

consistent data, difficulties in establishing demand indicators, and absence of clarity in identifying structural and behavioral 

influences on efficiency. However, this initial attempt to establish energy-efficiency measures for each economic sector can 

serve effectively as a "straw man," a way to stimulate discussion and draw in wide participation.

EIA is the logical agency to undertake this task. It has the expertise and the credibility to gather and analyze data, convene 

experts, and develop consensus. However, more work needs to be done by EIA and its customers. Feedback from our 

customers, by mail, telephone, fax, or e-mail is highly welcomed. Future in-house and bulletin board workshops are 

additional avenues for customer participation.97

Please refer to the Contacts Page in the front of this report.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 71

Appendix A

Methodology

Data availability were not consistent over the sectors. The data used for the residential analysis (RECS), for example, were 

sufficient to undertake this analysis. However, other sectors such as the transportation sector had limited data availability. 

Several sources of data had to be used to develop energy-intensity indicators. Also, adjustments were made where possible 

to eliminate influences that were not related to energy efficiency. It was necessary to develop primary energy estimates from 

the energy supply sector. Additionally, a composite was used to create an economy-wide energy-intensity indicator. This 

appendix documents these methodologies and other methodologies that could be used but were not used in this report. It 

provides this documentation individually for each of the following sectors: residential, commercial, transportation, 

manufacturing, and the U.S. economy as a whole. For each sector, the methodologies are presented in alphabetic order for 

ease of location.

Residential Sector

Degree-Day-Adjusted Estimates

A degree-day-adjusted estimate of annual site energy consumption explains what would have been consumed if the weather 

had conformed to normal or the 30-year average. 98 For the residential sector, space heating and cooling are degree-day 

adjusted and added to the other unadjusted end uses, water heating and appliances.

It is calculated by the following method:

• Obtain heating degree-day (HDD) factors—the variation between HDD for a specific year and normal HDD, e.g., 

if HDD equals 5,219 and normal HDD equals 6,043 then the HDD factor equals 6043/5219 = 1.158

• Obtain cooling degree-day (CDD) factors—the variation between CDD for a specific year and normal CDD, e.g., 

if CDD equals 609 and normal CDD equals 630 then the CDD factor equals 630/609 = 1.034

• Adjust the amount of each major fuel used for space heating by multiplying heating consumption by the respective 

HDD

• Adjust the amount of electricity and natural gas used for air-conditioning by the respective CDD factor

• Add these weather-adjusted consumption estimates with the other end-use energy estimates, water heating and 

appliances.

Table A.I presents an example for the South Census region. Degree-day-adjusted total residential energy consumption for 

the United States is the sum of the adjusted energy consumption by type of housing unit over all four Census regions.

Commercial Building Sector 

Degree-Day-Adjusted Estimates

For the commercial buildings sector, space heating, cooling, and ventilation are degree-day adjusted and added to the 

remaining unadjusted end-use consumption.

98Heating degree-days, cooling degree-days, and normal degree-days are defined under "General Terminology" in the Glossary.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 73
Table A.1. Degree-Day-Adjusted Residential Site Energy Consumption, South Census Region, 1990

End-Use Adjustment Mobile Home C

a. Space Heat (Trillion Btu) .................... 45

b. HDD Factor .............................. 1 .251

c, Adjusted Space Heat (Trillion Btu) (a * b) ....... 56

d. Air-Conditioning (Trillion Btu) ................. 15

e. CDD Factor .............................. .928

f. Adjusted Air-Conditioning (Trillion Btu) (d * e) . . . . 14 

g. Appliances (Trillion Btu) ..................... 38

h. Water Heating (Trillion Btu) .................. 18

I. Total Adjusted Consumption (Trillion Btu) 

(c + f + g + h) ........................... 126

Type of Housing Unit

Single-Family Multifamily

)etached Attached 2 to 4 Units 1 5 or More Units

810 34 46 40

1.251 1.251 1.251 1.251

1,014 43 58 50

253 19 19 38

.928 .928 .928 .928

235 18 18 35 

659 38 40 60

337 19 30 46

2,245 118 146 191

Total

975

1.251

1,220

344

.928

319 

835

450

2,824

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1990 Residential Energy Consumption Survey, 

Public-use Data Files. •Normal and annual cooling and heating degree-days provided by the U.S. Department of Commerce, National 

Oceanic and Atmospheric Administration.

End-Use Estimate Calculation. In order to adjust for the influence of weather, end-use estimates were needed for the 

commercial buildings sector. The only CBECS end-use consumption estimates by energy source were available are for the 

1989 CBECS. End-use data were needed for the other CBECS years. It was assumed that the percent shares for the end 

uses by energy source, principal building activity, and Census region were the same for all the CBECS years as they were 

in 1989.

Total energy consumption in each Census region by principal building activity was multiplied by these shares to obtain enduse consumption for the other CBECS years. Table A.2 provides an example for office buildings in the Northeast in 1992. 

As an illustration, the total consumption of electricity in 1992 was 125 trillion Btu. The percent share of electricity used for 

space heating in 1989 was 2.4 percent. One hundred twenty five trillion Btu * .024 = 3 trillion Btu used for electric space 

heat in 1992.

Degree-Day Adjusted Estimate Calculation

The following method is used to calculate the degree-day adjusted estimate:

• Obtain HDD factors—the variation between HDD for a specific year and normal HDD, e.g., if HDD equals 6,193 

and normal HDD equals 6,043 then the HDD factor equals 6,043/6,193 = .976

• Obtain CDD factors—the variation between CDD for a specific year and normal CDD, e.g., if CDD equals 412 and 

normal CDD equals 609 then the CDD factor equals 609/412 = 1.478

• Adjust the amount of each major fuel used for space heating by multiplying heating consumption by the respective 

HDD factor

• Adjust the amount of electricity and natural gas used for air-conditioning by the respective CDD factor

• Adjust the amount of electricity used for ventilation by the respective CDD factor

• Add these weather-adjusted consumption estimates with the remaining end-use energy estimates.

Table A.2 also presents an example of the calculation of the degree-day adjusted consumption estimates. As an illustration, 

an estimated 8 trillion Btu were used by office buildings in the Northeast Census region in 1992 for air- conditioning. The 

CDD factor is 1.478. In 1992,1.478 * 8 = 11 trillion Btu of degree-day adjusted electricity was used for air-conditioning.

All office buildings in the Northeast used 238 trillion Btu of energy in 1992, adjusted for weather effects.

Energy Information Administration/Energy Consumption Series 

74 Measuring Energy Efficiency in the United States' Economy: A Beginning
Degree-day adjusted commercial buildings total energy consumption for the United States is the sum of the adjusted energy 

consumption by principal building type over all four Census regions.

Table A.2. Calculation of End-Use Energy Consumption in Northeast Office Buildings, 1992

Energy Source

End Use

Space 

Heating

AirConditioning Ventilation Other Total

Total 

Consumption, 1992

(Trillion Btu)

Percent Share, 1989

Electricity .........

Natural Gas .......

Fuel Oil ..........

District Heat.......

Estimated End-Use Consumption, 1992 (Trillion Btu) 

Electricity ....................................

Natural Gas ..................................

Fuel Oil .....................................

District Heat..................................

Degree-Day Factors ..........................

Degree-Day Adjusted End-Use Consumption, 1992

2.4

63.6

89.6

65.3

76

3

20

33

20

.976

6.0 

2.0 

0.0 

9.5

11

8

1

0

3

1.48

17.9 

0.0 

0.0 

0.0

22

22

0

0

22

1.48

73.8 100.0

34.4 100.0

10.4 100.0

25.2 100.0

115

92

11

4

8

125

32

37

30

224

125

32

37

30

(Trillion Btu) ...................

Electricity ......................

Natural Gas ....................

Fuel Oil .......................

District Heat ....................

............... 75

............... 20

............... 32

............... 19

16

11

1

0

4

33

33

0

0

0

115

92

11

4

8

238

139

32

36

31

Sources: "Energy Information Administration, Office of Energy Markets and End Use, 1989 and 1992 Commercial Buildings Energy 

Consumption Survey, Public-Use Data Files. •Normal and annual cooling and heating degree-days provided by the U.S. Department of 

Commerce, National Oceanic and Atmospheric Administration.

Occupancy-Adjusted Estimates

Adjustments were made to eliminate vacant or mostly vacant buildings from the estimates for the survey years. Adjustments 

were made to both total site energy consumption and demand indicators for each principal building activity and Census 

region.

Demand Indicator Adjustment. Adjustments were made to the following demand indicators: floorspace, buildings, 

floorspace-hours and employees. Vacant buildings that were classified as vacant as well as those that were more than 50 

percent vacant at least 3 months during the survey year were removed. An example is presented in Table A.3.

Table A.3. Occupancy-Adjusted Total Commercial Floorspace in the Northeast by Principal Building 

Activity, 1992

Total Floorspace J 

Principal Building Activity (Million Square Feet) M

Assembly ......................................... 1,229

Education ......................................... 1 ,968

Food Sales/Service .................................. 565

Health Care (inpatient) ............................... 348

Health Care (outpatient) .............................. 38

Laboratory ......................................... 77

Lodging ........................................... 616

Mercantile/Services .................................. 2,798

Office ............................................ 2,525

Other, excluding Vacant .............................. 496

Public Order/Safety ................................. 269

Vacant ........................................... 08

Warehouse ........................................ 1 ,763

All Buildinas ....................................... 13,400

/lore than 50 percent for 3 

onths During Survey Year Occupied

122 1,107 

239 1 ,729 

68 497 

0 348 

0 38 

0 77 

60 556 

26 2,772 

85 2,440 

9 487 

3 266 

708 0 

92 1 ,672 

1,412 11,988

Source: Energy Information Administration, Office of Energy Markets and End Use, 1992 Commercial Buildings Energy Consumption 

Survey, Public-Use Files.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 75
Occupied Commercial Buildings Total Site Energy Consumption Adjustment. The total site energy consumption is 

adjusted by major fuel for each principal building activity (PBA) in each Census region by removing the site energy used 

in vacant buildings and buildings that were more than 50 percent vacant for at least 3 months (Table A.4).

Occupied and Degree-Day Commercial Buildings Site Energy Consumption Adjustment. This methodology adjusts 

for both vacancy and weather. First, the occupied site energy consumption is determined as explained above. Then the 

occupied site energy consumption is adjusted for weather. An example of this methodology was presented in Table A.2.

Table A.4. Occupancy-Adjusted Total Commercial Site Electricity Consumption in the Northeast, 

by Principal Building Activity, 1992

Principal Building Activity All Bull

Assembly ................................................. 2'

Education ................................................. 4;

Food Sales/Food Service ..................................... 3"

Health Care (Inpatient) ....................................... 2

Health Care (Outpatient) ......................................

Laboratory .................................................

Lodging ................................................... 2

Mercantile/Services .......................................... 7"

Office .................................................... 12

Other ..................................................... 1,

Public Order ............................................... f

Vacant ...................................................

Warehouse ................................................ 3(

Total ..................................................... 41<

Total Site Energy Consumption

(Trillion Btu)

clings | Vacant Buildings Occupied Buildings

1 2 22 

I 4 38 

1 <1 36 

I -- 24 

1 

3 -- 3 

1 20 

T <1 77 

5 3 122 

I <1 12 

3 <1 8 

T 7 0 

3 <1 38 

3 -- 401

-- = No cases. 

Source: Energy Information Administration, Office of Energy Markets and End Use, 1992 Commercial Buildings Energy Consumption 

Survey, Public-Use Data Files.

To determine the U.S. total occupied and degree-day total site energy consumption use the following method:

• Adjust at the PBA level by Census region for vacancy and obtain occupied total site energy consumption by PBA 

within each Census region (Table A.3)

• At the level of Step 1, using 1989 percent shares, obtain the end-use estimates for the occupied buildings (Table A.2)

• At the same level degree-day, adjust the end-use estimates using the appropriate degree-day factor (Table A.2)

• Sum up end-use estimates for each major energy source by PBA in each Census region

• Sum across major energy sources to obtain the total occupancy and degree-day adjusted total site energy consumption 

for each Census region PBA

• Sum across the PBA to obtain the Census region totals

• Sum across the Census regions to obtain U.S. occupancy and degree-day adjusted total site energy consumption.

Transportation Sector

Domestic Air Energy Use for Passenger and Freight: Derivation

The available data for aviation energy demand is for both the passenger and freight transportation sectors combined. In many 

aircraits, freight is carried in the hull of the craft while passengers ride in the cabin. Although the passenger-miles traveled 

by air cannot be separated into passenger and freight components, the revenues (in millions of dollars) received for different 

types of air travel can be separated.

Energy Information Administration/Energy Consumption Series 

76 Measuring Energy Efficiency In the United States' Economy: A Beginning
The relative share of revenue dollars was used to estimate the portion of energy consumed for passenger and freight 

movements by air. Table A.5 presents the methodology.

Table A.5. Calculating U.S. Domestic Passenger and Freight Air Travel Energy Consumption

Indicators

U.S. Domestic Passenger

Revenue per Passenger Mile ....................

Passenger Miles ..............................

Passenger Revenues ..........................

U.S. Domestic Freight

Freight Ton Miles .............................

Freight Revenues .............................

Total Operating Revenues .......................

Air Travel Energy Use ...........................

Air Passenger ................................

Air Freight ...................................

| Units

........... Million

........... Million Dollars

........... Cents

........... Million

........... Million Dollars

........... Million Dollars

........... Trillion Btu

........... Trillion Btu

1985

12.21

277,836

33,924

102.23

6.71

6,860

37,629

1,366

1,231

134

| 1988

1 9 *31

OOA 00 1

41,151

111.31

Q OQ

10,385

50,155

1,609

1,320

289

| 1991

n 99

338,085

AA fiQR

in*3 *^n

Q Qfi

m ^OQ

56,165

1,542

1,227

315

Notes: "Passenger and freight revenues may not add to total operating revenues, due to calculations and differences in data 

sources. *Air passenger energy use calculated as the multiple of its revenue ratio and total air travel energy use, e.g., in 1985 the 

equation is (33,924/37,629)* 1,366 = 1,231. »Air freight energy use calculated as the remainder after air passenger energy use is 

subtracted from total air travel energy use, e.g., in 1985 the equation is (1,366 -1,231) = 134.

Sources: •Department of Transportation, Bureau of Transportation Statistics, National Transportation Statistics (September 1993), 

Tables 1, 4, and 6. »Eno Transportation Foundation Inc., Transportation in America 1994, pp. 44 and 49.

Site Energy Consumption Conversion: Electricity consumption is reported for pipelines and passenger rail in the Oak 

Ridge National Laboratory Transportation Energy Data Book. The primary electricity volumes were converted to site 

electricity by applying conversion factors. See 'Primary Conversion Factors" in the economy section in this appendix. Table 

A.6 presents the methodology.

Table A.6. Calculating U.S. Transportation Site Electricity Consumption

Electricity Variables

Primary Electricity (Trillion Btu) 

Pipeline .................................................

Passenger Rail ...........................................

Electricity Conversion Factor ...............................

Site Electricity (Trillion Btu) 

Pipeline .................................................

Passenger Rail ...........................................

| 1985

............. 239.0

............. 55.4

............. 3.292

............. 72.6

............. 16.8

| 1988

244.8

59.9

3.31 1

73.9

18.1

| 1991

243.4

59.5

3.30

73.8

18.0

Note: Site electricity is calculated as primary electricity divided by the conversion factor, e.g., in 1985 the equation for pipelines is 

(239.0/3.292) = 72.6.

Sources: •Department of Energy, Oak Ridge National Laboratory (ORNL), Transportation Energy Data Book (ORNL-6798), 

Editions 11 and 14, Table 2.6 and unpublished 1985 data from ORNL.

Industrial Sector 

Capacity-Utilization Rate

The capacity-utilization rate equals the seasonally adjusted index of industrial production divided by a capacity index 

(sustainable practical capacity, i.e., the greatest level of output a plant can maintain within a realistic work schedule). The 

Federal Reserve Board weights the capacity indexes by value-added proportions.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 77
Capacity-Adjusted Value of Production Method. This method adjusts the value of shipments for changes in capacity 

after the value of shipments has been adjusted for changes in inventories (value of production). See "Inventory Adjustment" 

in this section of the appendix. The method is as follows:

• Divide the 26-year average capacity-utilization rate (average) by the annual reported rate (t) to calculate factors for 

each major industry group (Table A.7. presents these rates by SIC)

• Multiply this factor by the value of production estimate in constant 1987 dollars.

Constant-dollar Capacity-Adjusted Value of Production t =

Capacity-Utilization Rate ave ^ Constant-dollar Value of Production 

Capacity-Utilization Rate,

Table A.7. Capacity-Utilization Rate: 26-Year Average and Annual for 1985,1988, and 1991. by SIC

SIC

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

Major Industry Group

Food and Kindred Products. .........................

Tobacco Manufactures .............................

Textile Mill Products ...............................

Apparel and Other Textiles Products. ..................

Lumber and Wood Products. ........................

Furniture and Fixtures .............................

Paper and Allied Products ..........................

Printing and Publishing. ............................

Chemicals and Allied Products. ......................

Petroleum and Coal Products. .......................

Rubber and Miscellaneous Plastics ...................

Leather and Leather Products. .......................

Stone, Clay, and Glass Products .....................

Primary Metal Industries. ...........................

Fabricated Metal Products ..........................

Industrial Machinery and Equipment. ..................

Electronic and Other Electric Equipment. ..............

Transportation Equipment ..........................

Instruments and Related Products ....................

Miscellaneous Manufacturing Industries. ...............

Capacity Utilization Rates

1967-1993 | 1985

82.3 81.0

NA NA

86.2 83.0

81.1 80.4

83.1 84.6

81.7 79.8

89.7 89.7

86.5 87.0

80.0 77.1

85.5 78.6

83.6 85.3

81.9 75.6

77.9 75.6

80.1 74.0

77.2 74.9

80.8 73.4

80.4 80.7

74.9 78.8

82.0 83.6

75.6 67.7

1988

81.8

NA

88.7

82.8

89.7

84.2

93.2

89.9

83.9

85.2

87.7

79.5

82.2

87.5

81.1

80.5

83.7

79.4

80.5

79.5

1991

81.4

NA

83.3

77.6

79.3

74.2

88.4

79.7

80.6

86.0

80.3

78.5

73.2

77.9

73.2

72.6

78.0

73.4

77.2

74.6

NA = Not Available.

Sources: »U.S. Department of Treasury, Federal Reserve Board (Table provided by Charles Gilbert, 10/12/94). 'Federal Reserve 

Statistical Release (August 15,1994), Table 3 (average).

Inventory Adjustment

Changes in inventories need to be considered when using a demand indicator such as the value of shipments. If inventories 

are being drawn down, the value of shipments will overestimate the actual value of production. If inventories are being built, 

then the value of shipments will underestimate the value of production.

Inventory-adjusted Value of Shipments or Value of Production. The inventories used in the adjustment are year-end 

inventories at cost or market value, deflated to 1987 constant dollars using value of shipments implicit price deflators 

reported by the U.S. Department of Commerce, Bureau of Economic Analysis. The following steps were followed to adjust 

the value of shipments for the effects of changes in inventories:

• Determine the implicit price deflator by dividing current dollar into constant dollar value of shipments for each major 

industry group in each year

• Multiply this deflator by the year-end inventories of the year preceding and the current year

• Add to the deflated value of shipments the deflated current year inventory and subtract the deflated prior year 

inventory.

Energy Information Administration/Energy Consumption Series 

78 Measuring Energy Efficiency in the United States' Economy: A Beginning
Value of Shipments Deflator t = Constant-dollar Value of Shipments,

Current-dollar Value of Shipments t

Constant-dollar Value of Production t =

Constant-dollar 

Value of Shipments,

(Value of 

Shipments 

Deflator.

* Current-dollar) (Value of *Current-dollar) 

Inventories, - Shipments inventories t., 

Deflator,_!

Table A.8. Value of Production Methodology Example

Calculations [Preceding Year (t-1) [Current Year (t)

a. Value of Shipments (million 1987 dollars) .......................................

b. Value of Shipments (million current dollars) .....................................

c. Implicit Price Deflator (a/b) ..................................................

d. Year-End Inventories (current million dollars) ....................................

e. Year-End Inventories (million 1987 dollars) (c*d) .................................

f. Value of Production (million 1987 dollars) (319,212 + 25,224 - 29,276 - 315,160) .......

307,345

255,723

1.20

24,397

29,276

319,212

303,270

1.05

24,023

25,224

315,160

Note: This example is for illustrative purposes only. Although, MECS-weighted value of shipments data (adjusted to 1987 SIC) were used 

throughout Chapter 6, "Industrial Sector," confidentiality does not permit EIA to release value of shipments data that have been revised by 

MECS weights.

U.S. Economy

Energy-Weighted Index

One way for removing effects such as geography and housing unit type effects is to index from a "two-way" disaggregation 

of characteristics to develop an index for total U.S. housing.

As an example, for the Northeast Census region in the residential sector, start with consumption per household for each of 

the five housing types indexed to 1 in the first year as follows:

Northeast Census Region

Mobile Homes 

Single-Family Detached 

Single-Family Attached 

Multifamily (2-4 Units) 

Multifamily (5 or More Units)

1984

1

1

1

1

1

1987

x

X 

X

X 

X

1990

x

X 

X 

X 

X

Compute an energy-weighted index (preferably Tornqvist index) of the individual energy-intensity indices for 1987 and 1990 

for each of the Census regions. This index will be devoid of mix issues relating to housing type and geography. While there 

will still be other behavioral and/or structural effects in the five disaggregated indices, a layered procedure that moves down 

the chain to include measures that disaggregate end-uses (for example, an index of space-heating consumption per square 

foot, not household, since housing sizes are changing, or an index of water heating per occupant rather than per household, 

since persons per household are changing, etc...) and to exploit all of the detail available from the energy consumption 

surveys is a "good measure" of energy intensity. These effects might be relatively minor over the 3 surveys years being 

compared, but without the calculations such as these, only qualitative judgments as to the potential effects can be made. 

This proposed approach is for all intents and purposes has been used for the transportation and economy composites. Indices 

can be developed for each sector and weighted by shares of total energy consumption in the economy.

Primary Conversion Factors for Total Site Electricity

Primary energy estimates include losses in the generation, transmission, and distribution of electricity. In this report, 

conversion factors are developed to account for these losses. Total site electricity estimates are multiplied by these 

conversion factors to obtain primary electricity estimates.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency in the United States' Economy: A Beginning 79
The methodology for developing the conversion factors and obtaining primary electricity estimates is shown in the following 

steps:

Step 1. Calculate gross inputs:

• Convert utility-site generation by energy source and region in kWh to equivalent gross-generation estimates in kWh 

(including generator or shaft losses) by multiplying site generation by the appropriate gross/site ratio plus the 

transmission and distribution losses estimated at 8 percent by the Department of Energy, Office of Energy 

Management.

• For each year, the gross-generation estimates, by Census region, are multiplied by the appropriate annual heat rate 

for each energy source to obtain gross inputs for electricity generation by utilities such that:

Gross Inputs = (Net Generation * (Gross/Site Ratio + T&D Losses) * Heat Rate) /1000.

Data on energy sources used by nonutilities and net exporters to produce electricity purchased by U.S. utilities are not 

available. Since electricity from these sources is primarily produced from either fossil fuels or hydro resources, the heat rates 

of fossil-fueled steam generators are applied to the purchased energy. Table A.9 presents an example of the calculation of 

gross inputs for the Northeast Census region in 1992.

Table A.9. Example of Calculating Gross Inputs for the Northeast in 1992

Calculation Inputs

a. Site Generation (Billion kWh) ..................

b. Gross/Site Ratio ............................

c. T&D Losses ...............................

d. Heat Rates (Btu/kWh) .......................

e. Gross Inputs (Trillion Blu) (a * (b + c)* d)/1000 ....

Generation Energy Sources

Fossil 

Fuels

218.4 

1.07 

0.08 

10,302 

2,588

Nuclear

144.4 

1.06 

0.08 

10,678 

1,757

Hydropower

30.6 

1.01 

0.08 

10,302 

344

Geothermal

0 

1.06 

0.08 

20,955 

0

Other

0.5 

1.07 

0.08 

10,302 

6

Nonutility 

Purchases

52.5 

1.07 

0.08 

10,302 

622

Net 

Imports

12.1 

1.07 

0.08 

10,302 

143

Note: Fossil fuel heat rate is used also for hydropower, nonutility purchases, net imports, and other.

Sources: 'Energy Information Administration, Office of Coal, Nuclear, Electric, and Alternative Fuels, Electric Power Annual 1993 

(DOE/EIA-0348(93), Tables 13,61 and 62. "Energy Information Administration, Office of Energy Markets and End Use, Monthly 

Energy Review (DOE/EIA-0035(94/08)), Table A8; Production Annuelle Brute et Nette d'Electricity, p.16.

Step 2. Add utility-plant use to electricity sales for each sector."

Step 3. All regional estimates of electricity sales and plant use in kWh are converted to Btu using 3,412 Btu per kWh.

Step 4. Divide gross energy inputs by the total site electricity (sales and plant use) for each Census region to obtain 

conversion factor.

Step 5. Site electricity consumption for each end-use sector and Census region are multiplied by the primary electricity 

conversion factors to obtain the corresponding primary electricity estimates. The data source is the consumption 

survey data as developed in each of the sector chapters.

There are three main advantages to using the method described above:

• Generation, transmission and distribution losses are accounted for

• Includes electricity consumption that was generated by both utilities and nonutilities

• Since the heat rate used varies from year to year and by fuel source, changing efficiencies over time are captured.

"Electricity sales data are obtained from EIA's Electric Power Annual 1993 (DOE/EIA-0348(93), Table 26. Plant use electricity is the 

difference between gross inputs and site electricity.

Energy Information Administration/Energy Consumption Series 

80 Measuring Energy Efficiency in the United States' Economy: A Beginning
Regional Manufacturing Estimates: The 1985 estimate of total inputs for heat, power, and generation was based on 

EIA's revised 13,631 trillion Btu total. This total was distributed regionally by using regional shares based on Table 3 in 

the EIA publication, Manufacturing Energy Consumption Survey: Consumption of Energy, 1985 (DOE/EIA-0512(85).

The analysis of the manufacturing sector used revised 1985 estimates to match the revised 1987 SIC standards. Electricity 

was not considered separately. Therefore, electricity consumption for heat, power, and generation in Btu were calculated 

from the kilowatthour estimates in Table 3 of Manufacturing Energy Consumption Survey: Consumption of Energy, 1985 

and Manufacturing Energy Consumption Survey: Consumption of Energy, 1988 (DOE/EIA-0512(88)) by multiplying the 

estimates by 3,412 Btu per kWh. Natural gas consumption for heat, power, and generation in Btu were calculated from the 

cubic-foot estimates in the same tables. The natural gas estimates for the respective surveys were multiplied by 1,031 

Btu/cubic feet.

Both the 1991 electricity and natural gas estimates in Btu were provided in Table A.4 of Manufacturing Energy 

Consumption Survey: Consumption of Energy, 1991, DOE/EIA-512(91) report.

Regional Passenger Transportation Estimates: Passenger transportation data are not available by Census region. On 

the advice of Oak Ridge National Laboratory, it was decided that since household vehicles account for over 70 percent of 

the total energy for passenger travel, regional shares based on the Residential Transportation Energy Consumption Survey 

(RTECS) would be an adequate proxy for passenger transportation energy estimates. 100

There has been very little change in the RTECS regional distribution across survey years. For 1985,1988, and 1991, the 

total U.S. passenger transportation energy estimates were multiplied by the percent shares by Census region to obtain 

regional energy consumption estimates for passenger travel. The percent shares were based on the 1988 RTECS. The 1988 

shares were: 17 percent for the Northeast; 25.2 percent for the Midwest; 36.0 percent for the South, and 21.8 percent for 

the West.

Regional Freight Transportation Estimates: Freight transportation data are not available by Census region. On the 

advice of Argonne National Laboratory, it was decided that since most of the energy source used for freight transportation 

was fuel oil, EIA data could be used instead of Department of Transportation, Bureau of Transportation Statistics data.

EIA's Petroleum Marketing Division annually surveys State-level distillate fuel oil consumed by trucks, rail, and marine 

vehicles and residual fuel oil consumed by rail and marine vehicles, bench marking to the petroleum product supplied data 

published by EIA's Petroleum Supply Division. The report, Fuel Oil and Kerosene Sales, provides State-level data on the 

number of gallons consumed, which were converted to trillion Btu using Oak Ridge National Laboratory conversion factors, 

in order to derive percent shares.

Since there has been little fluctuation in regional distribution year-to-year, it was determined to apply 1988 regional percent 

shares to all annual estimates. The regional percent shares used were: 12.5 percent for the Northeast; 20.2 percent for the 

Midwest; 42.0 percent for the South, and 25.3 percent for the West.

Quantity Index

A quantity index measures changes in quantity over time. The Index of Industrial Production, developed by the Federal 

Reserve Board, is a quantity index.

The weighted aggregate quantity index is computed similar to the weighted aggregate price index.

The Price Index. The price index is a weighted average of expenditures, as a percentage of expenditures existing in a base 

year. A price index may be calculated for a single good or can be calculated as an aggregated price index for a "basket" of 

several goods. Price indices can be unweighted or weighted. The unweighted aggregated approach is heavily influenced by 

those goods with higher prices which dominate the index. To reduce this sensitivity of the unweighted index, a weighted 

price index is used. Each good in an weighted aggregate price index is be weighted according to its importance.

One way to weight a price index is to use base-year quantities, the Laspeyres price index.

'"Business fleets are operated very differently from household vehicles, but adequate data are not available on fleet vehicles.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 81
Laspeyres price indices are calculated by comparing the current and base year cost of a basket of goods of fixed composition. 

As an example, the "basket" can be several "goods" such as energy, clothing, food, housing, etc. that we find in the "basket" 

used to calculate the Consumer Price Index (CPI) or one "good" such as the major energy sources that is used to calculate 

the energy component of the CPI. The Producer Price Index (PPI) developed and maintained by the Bureau Labor Statistics, 

is also a base-weighted price index.

Laspeyres base-weighted price index (ratio of today's cost using base-year quantities to the base-year cost of the goods) 

equals:

where the base-year quantities of the various goods = q0' , 

the base-year prices of the various goods = p0i , and 

present prices of the various goods = p, 1 .

Quantity Index. Similar to the Laspeyres price index, quantities for each item are measured in the base year „ and year , 

with q0' and q,1, representing these quantities for item I (e.g.,end use or energy source). The quantities are then weighted by 

a fixed price (w,1) such as value added, value of shipments, etc. where the quantity index I equals

In some quantity indexes, the weight for item I is the base-period price (p0').

Energy Information Administration/Energy Consumption Series 

82 Measuring Energy Efficiency in the United States' Economy: A Beginning
Glossary

The Glossary is divided into six distinct sections: General Terminology, Residential Sector, Commercial Buildings Sector, 

Transportation Sector, Industrial Sector, and the U.S. Economy.

General Terminology

Behavioral Change: As it affects energy efficiency, behavioral change is a change in energy-consuming activity originated 

by, and under control of, a person or organization. An example of behavioral change is adjusting a thermostat setting, or 

changing driving habits.

British Thermal Unit (Btu): The quantity of heat needed to raise the temperature of 1 pound of water by 1 degree 

Fahrenheit at or near 39.2 degrees Fahrenheit.

Census Region: A geographic area consisting of several States defined by the U.S. Department of Commerce, Bureau of 

the Census. The four Census regions are:

Northeast: Connecticut, Maine, Massachusetts, New Hampshire, Vermont, Rhode Island, New Jersey, New York, and 

Pennsylvania

Midwest: Illinois, Indiana, Michigan, Ohio, Wisconsin, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, 

and South Dakota

South: Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West 

Virginia, Alabama, Kentucky, Mississippi, Tennessee, Arkansas, Louisiana, Oklahoma, and Texas

West: Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming, Alaska, California, Hawaii, Oregon, 

and Washington

Cooling Degree-Days (CDD): A measure of how hot a location was over a period of time, relative to a base temperature. 

In this report, the base temperature is 65 degrees Fahrenheit; the period of time is 1 year. The CDD for a single day is the 

difference between that day's average temperature and 65 degrees, if the daily average exceeds the base temperature, and 

zero if the daily average is less than or equal to the base temperature. The CDD for a longer period of time is the sum of 

the daily CDD from the days in the period.

Demand Indicator: A measure of the number of energy-consuming units, or the amount of service or output, for which 

energy inputs are required.

Establishment: As defined by the 1987 Standard Industrial Classification Manual,"...an economic unit generally at a single 

physical location, where business is conducted or where services or industrial operations are performed." (See 

Manufacturing Establishment.)

End Use: Any specific activity performed by a sector (residential, commercial, industrial, or transportation) that requires 

energy, e.g., refrigeration, space heating, water heating, manufacturing process, feedstocks, etc.

Energy Efficiency: A value-based, philosophical concept. In this report, two different concepts of energy efficiency are 

discussed, a technical and a more broad, subjective concept. In the technical concept, increases in energy efficiency take 

place when either energy inputs are reduced for a given level of service or there are increased or enhanced services for a 

given amount of energy inputs. In the more subjective concept, energy efficiency is the relative thrift or extravagance with 

which energy inputs are used to provide goods or services.

Energy Intensity: The ratio of energy consumption to a measure of the demand for services (e.g., number of buildings, total 

floorspace, floorspace-hours, number of employees, or constant dollar value of Gross Domestic Product for services).

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 83
Floorspace: The area enclosed by exterior walls of a building, including parking areas, basements, or other floors below 

ground level. It is measured in square feet.

Heated Floorspace: The area within a building, which is space heated. 

Cooled Floorspace: The area within a building, which is air-conditioned.

Gross Domestic Purchases: The total purchases by U.S. residents for all goods and services wherever produced, including 

imports, but excluding exports. The scope of energy expenditures and price is more consistent with that of gross domestic 

purchases than gross domestic product. Gross domestic purchases figures are reported in real 1987 dollars, using the 

implicit price deflator published by the U.S. Department of Commerce, Bureau of Economic Analysis. See Appendix A, 

"Additional Measures of Energy Consumption, Expenditures, and Prices" in State Energy Price and Expenditure Report 

1992 (DOE/EIA-0376(92» for a further treatment of the usage of gross domestic purchases.

Gross Domestic Product (GDP): The total value of goods and services produced by the Nation's economy before deduction 

of depreciation charges and other allowances for capital consumption labor and property located in the United States. It 

includes the total output of goods and services by private consumers and government, gross private domestic capital 

investment, and net foreign trade. GDP figures are reported in real 1987 dollars, using the implicit price deflator published 

by the U.S. Department of Commerce, Bureau of Economic Analysis.

Heating Degree-Days (HDD): A measure of how cold a location was over a period of time, relative to a base temperature. 

In this report, the base temperature is 65 degrees Fahrenheit; the period of time is 1 year. The HDD for a single day is the 

difference between that day's average temperature and 65 degrees, if the daily average is below the base temperature, and 

zero if the daily average exceeds or equals the base temperature. The HDD for a longer period is the sum of daily HDD for 

days in that period.

Normal Cooling Degree-Days: Annual cooling degree-day average over 30 years from 1961 through 1990 as calculated 

by U.S. Department of Commerce, National Oceanic and Atmospheric Administration (NOAA).

Normal Heating Degree-Days: Annual heating degree day average over 30 years from 1961 through 1990 as calculated 

by U.S. Department of Commerce, National Oceanic and Atmospheric Administration (NOAA).

Primary Energy Consumption: Primary energy consumption is the amount of site consumption, plus losses that occur 

in the generation, transmission, and distribution of energy (See Site Energy Consumption.).

Sector: The broadest category for which energy consumption and intensity are considered within the U.S. economy. For 

this report, four major energy-using sectors are considered: residential, commercial buildings, transportation, and industrial.

Site Energy Consumption: The Btu value of energy at the point it enters the home, building, or establishment, sometimes 

referred to as "delivered" energy. (See Primary Energy Consumption.)

Structural Change: As it affects energy efficiency, structural change is a change in the relative levels of energy-consuming 

subsectors within a sector. An example of structural change is change in product or industry mix in the industrial sector.

Energy Information Administration/Energy Consumption Series 

84 Measuring Energy Efficiency In the United States' Economy: A Beginning
Residential Sector

End Use: A function for which energy sources or fuels are used in the household. Any specific activity performed requires 

energy. For the residential sector, the following main energy end-use categories are estimated using RECS data. See 

Appendix D, "End-Use Estimation Methodology," in Household Energy Consumption and Expenditures 1990 (DOE/EIA0321(90)).

Space Heating: The use of mechanical equipment to heat all or part of a building to at least 50 degrees Fahrenheit. 

Includes both the main space-heating and secondary space-heating equipment, but excludes energy used to operate 

appliances that give off heat as a byproduct.

Air-Conditioning or Cooling: Conditioning of room air for human comfort by a refrigeration unit (e.g., air- conditioner 

or heat pump) or by circulating chilled water through a central cooling or district cooling system.

Appliances: Energy-consuming equipment used in the home during the year for purposes other than condition of air 

or centralized water heating. Includes cooking appliances (gas stoves, gas ovens, electric stoves, electric ovens, 

microwave ovens, and propane or gas grills); cooling appliances (evaporative coolers, attic fans, window or ceiling fans, 

portable or table fans); and refrigerators, freezers, clothes washers, electric dishwashers, electric clothes dryers, outdoor 

gas lights, electric dehumidifiers, personal computers, electric pumps for well water, black and white television sets, 

color televisions, water bed heaters, swimming pools, swimming pool heaters, hot tubs, and spas.

Water Heating: The use of energy to heat water for hot running water, as well as the use of energy to heat water on 

stoves and in auxiliary water-heating equipment for bathing, cleaning and other noncooking applications of hot water. 

An automatically controlled, thermally insulated vessel designed for heating water and storing heated water at 

temperatures less than 180 degrees Fahrenheit.

Household: A family, individual, or group of up to nine unrelated persons, occupying the same housing unit. "Occupancy" 

means the housing unit was the person's usual or permanent place of residence at the time of the survey. By definition, the 

number of households is the same as the number of occupied housing units.

Household Member: Any eligible person who belongs to a household. Members include babies, boarders, lodgers, 

employed persons who live in the housing unit, and persons who usually are part of the household but are away traveling 

or in a hospital. Excluded are college students who live elsewhere, members of the armed forces, corrections inmates who 

used to live in the residence, or others who remain away from the residence for extended periods of time.

Housing Unit: A house, apartment, group of rooms, or a single room if it is occupied or intended for occupancy, as separate 

living quarters by a family, individual, or group of one to nine unrelated persons. Prisons and nursing homes are excluded.

Mobile Home: A housing unit built on a movable chassis and moved to the site. It may be placed on a permanent or 

temporary foundation and may contain one or more rooms.

Multifamily (2-4 units): A unit in a building with two to four housing units—a structure that is divided into living 

quarters for two, three, or four families or households and in which one household lives above another.

Multifamily (5+ units): A unit in a building with five or more housing units—a structure that contains living quarters 

for five or more families or households and in which one household lives above another.

Single-Family Attached: A structure that provides living space for one family or household that is not divided into 

multiple housing units and has an independent outside entrance. Townhouses, rowhouses, and duplexes are considered 

single-family attached housing units, as long as there is no household living above another one within the walls that go 

from the basement to the roof to separate the units.

Single-Family Detached: A stand-alone structure that provides living space for one household or family. A 

manufactured house assembled on site is a single-family detached unit, not a mobile home.

Energy Information Administration/Energy Consumption Series 

Measuring Energy Efficiency In the United States' Economy: A Beginning 85
Income Level: The income grouping for the total combined income (before taxes and deductions) of all members of the 

family from all sources, for the 12 months prior to the survey. Sources of income include wages, salaries, tips, commissions, 

interest, dividends, rental income, social security or retirement, pensions, food stamps, Aid to Families with Dependent 

Children, unemployment compensation, and other public assistance. Income from unrelated household members is not 

included.

Main Heating Fuel: The fuel used most for space heating.

New Construction: The amount of square footage constructed in the survey year and two years prior, e.g., 1988-1990 for 

the 1990 Residential Energy Consumption Survey.

Personal Consumption Expenditures: All household expenditures on durable goods such as stoves, and nondurable goods 

such as energy, and on services such as day care.

Residential Building: A structure used primarily as a dwelling for one or more households. A building typically containing 

less than 1,000 square feet of floorspace and intended for human occupancy. More than 50 percent of its floorspace must 

be used for residential activities.

Unadjusted Energy Consumption: Site energy consumption as provided in the RECS Public-Use Files. No adjustments 

were made to account for weather variations, behavioral, or structural effects.

Commercial Building Sector

Air-Condition or Cooling: Conditioning of room air for human comfort by a refrigeration unit (e.g., air-conditioner or heat 

pump) or by circulating chilled water through a central cooling or district cooling system that circulates chilled water.

Commercial Building: A building with more than 50 percent of its floorspace used for commercial activities. Commercial 

building include, but are not limited to, stores, offices, schools, churches, gymnasiums, libraries, museums, hospitals, clinics, 

warehouses, and jails. Government buildings are included except for buildings on sites with restricted access, such as some 

military bases or reservations. A building is an enclosed structure containing over 1,000 square feet of floorspace and 

intended for human occupancy. Agricultural, industrial, and residential buildings are excluded from commercial sector 

surveys.

Employee: A worker in a building during the main shift on a typical workday during the year, including self-employed and 

volunteers. Excluded are customers, patients, and students, unless they are working for the business. Also excluded are 

employees who work out of the office, e.g., salespeople, delivery people, and messengers.

Major Fuels: The energy sources or fuels for which consumption and expenditure data were collected on four CBECS 

surveys. These include electricity, natural gas, fuel oil, and district heat. Propane is excluded from all totals.

New Construction: The amount of square footage constructed in the survey year and 2 years prior, e.g., 1990-1992 for the 

1992 CBECS.

Occupied Floorspace: The area of all commercial buildings excluding those buildings classified as vacant and all other 

buildings that were more than 50 percent vacant during the three months preceding the survey.

Principal Building Activity: The activity or function occupying the most floorspace in the building. The categories were 

designed to group buildings that have similar patterns of energy consumption. While all calculations in this report were 

performed using 13 categories, the results were aggregated into the following 10 categories:

Education: refers to buildings that house academic or technical classroom instruction. Certain buildings in educational 

facilities are excluded from this category, e.g., administration (office), dormitory (lodging), gymnasium (assembly), etc.

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86 Measuring Energy Efficiency in the United States' Economy: A Beginning
Food: refers to buildings used for retail or wholesale of food. Includes establishments that sell food retail or wholesale 

(e.g., grocery stores) and establishments that prepare and sell food and beverages for consumption (e.g., restaurants). 

(Combines Food Sales and Food Service)

Health Care: covers diagnostic and treatment facilities for both inpatient (e.g., hospitals, rehabilitation facility) and 

outpatient (e.g., dental, medical, and mental health clinics) care.

Lodging: includes establishments that offer multiple accommodations for short- or long-term residents (e.g., hotels, 

nursing homes).

Mercantile and Service: refers to buildings used for the sales and displays of goods or services, including automotive, 

retail, laundry, and shopping centers, but excluding food.

Office: refers to buildings used for general office space, professional offices, and administrative offices.

Assembly: signifies buildings used for gathering of people for social, recreational, cultural, or religious activities, 

whether in private or public meeting halls. (Combines assembly with religious buildings.)

Warehouse: describes buildings used to store goods, products, merchandise or raw materials, including both 

refrigerated storage and unrefrigerated warehouses.

Vacant: designates buildings in which more floorspace was vacant than was used for any other single activity.

Other: includes parking garages, public order and safety buildings used in the preservation of law and order or safety, 

laboratories that use equipment for experimental testing or analysis, and Other buildings not elsewhere classified (e.g., 

hangars, public restrooms). (Includes the Public Order and Safety Building category.)

Unadjusted Consumption: Major site fuel consumption as provided in the CBECS Public Use Files, excluding 

consumption of propane and consumption by small floorspace (less than 1,000 square feet) and noncommercial (agriculture, 

industrial, or residential) buildings.

Ventilation: The circulation of air through a building to deliver fresh air to occupants.

Vintage: The year of origin or age since the construction of a commercial unit, as calculated from the CBECS survey year.

Transportation Sector

Air Travel: Include both general aviation and commercial air carriers. General aviation refers to the use of non-commercial 

air carriers for several purposes, including business, flight instruction, and other personal activities. Air carriers include both 

scheduled and non-scheduled flights.

Alternative Fuels: Methanol, denatured ethanol, and other alcohols, mixtures containing 85 percent or more (or such other 

percentage, but not less than 70 percent) by volume of methanol, denatured ethanol, and other alcohols with gasoline or other 

fuels; natural gas; liquefied petroleum gas; hydrogen; coal-derived liquid fuels; fuels (other than alcohol) derived from 

biological materials; and electricity, including electricity from solar energy.

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Automobiles: Includes household, government, and commercial cars. The RTECS includes company vehicles if used for 

personal travel in addition to the business usage and the vehicle is ordinarily kept at home.

Buses: Includes commercial, school, and transit buses. It does not include trolley buses.

Combination Trucks: Consists of a power unit (a truck tractor) and one or more trailing units (a semi-trailer or trailer).

Freight Modes: Includes truck, air, marine, rail, and pipeline freight modes. It does not include gas and water pipeline.

Heavy-Duty Vehicles: Combination of all high passenger occupancy modes of transportation, including buses, trains, 

general aviation, and air carriers.

Light-Duty Vehicles: Include automobiles, motorcycles, and light trucks.

Light Trucks: All single unit two-axle, four-tire trucks, including pickup trucks, sports utility vehicles, vans, motor homes, 

etc. This is the Department of Transportation definition. The Energy Information defined light truck as all trucks weighing 

8,500 pounds or less.

Marine Freight: Freight transported over rivers, canals, the Great Lakes, and domestic ocean waterways.

Other Single-Unit Truck: A motor vehicle consisting primarily of a single motorized device with more than two axles or 

more than four tires.

Passenger-Miles Traveled: The total distance traveled by all passengers. It is calculated as the product of the occupancy 

rate in vehicles and the vehicle miles traveled.

Passenger Modes: Includes Light-Duty Vehicles and Heavy-Duty Vehicles. See Light-Duty Vehicles and Heavy-Duty 

Vehicles in this section of the glossary.

Passenger Rail: Includes short- and long-distance passenger rail, commuter rail, and light and heavy rail. Heavy rail is 

electric transit vehicle with capacity for heavy "volume" traffic. It is more genetically referred to as subway. Light rail is 

a type of electric transit railway with a light-volume capacity, with generic names like "streetcars," "trolley cars," and 

"tramways."

Pipeline Freight: Refers to freight carried through pipelines, including natural gas, crude oil, and petroleum products 

(excluding water). Energy is consumed by various electrical components of the pipeline, including, valves, other, 

appurtenances attaches to the pipe, compressor units, metering stations, regulator stations, delivery stations, holders and 

fabricated assemblies. This report presents only oil pipeline freight.

Rail Freight: Refers to intercity freight movement by trains.

Site Energy Consumption: This includes gasoline, distillate fuel oil, liquefied petroleum gas, jet fuel, residual oil, natural 

gas, and electricity converted to their Btu equivalent. Primary energy consumption also includes electrical losses.

Site Energy Consumption Conversion: Electricity consumption is reported for pipelines and passenger rail in the Oak 

Ridge National Laboratory Transportation Energy Data Book. The primary electricity volumes were converted to site 

electricity applying conversion factors. See Appendix A for the methodology.

Sport-Utility Vehicle: Includes light trucks that are similar to Jeeps. Other common terms for these vehicles are sport, 

special purpose, utility, or off-the-road vehicles. They may have a four- or two-wheel drive.

Ton Miles: The product of the distance freight is hauled, measured in miles, and the weight of the cargo being hauled, 

measured in tons. Thus, moving one ton one mile generates one ton mile.

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Truck Freight: This is freight carried by single-unit, non-two-axle, four-tire trucks (Other single unit trucks) and 

combination trucks.

Two-axle, four-tire trucks: A motor vehicle consisting primarily of single motorized device with two axles and four tires.

Vehicle-Miles Traveled: One vehicle traveling a distance of one mile. Total vehicle miles is the total mileage traveled by 

all vehicles.

Industrial Sector

Byproduct Fuels: Secondary or additional products resulting from the feedstock use of energy or the processing of 

nonenergy materials. For examples, the more common byproducts of coke ovens are coal gas, tar, and a mixture of benzene, 

toluene, and xylene (BTX). Byproduct fuels are produced by the use of both energy and nonenergy raw material input, but 

they appear differently on various measures of energy consumption, depending on which one is being considered. For 

instance, total input for heat, power, and electricity generation include both types of byproduct fuels. In order to avoid double 

counting of primary energy, however, primary energy consumption for all purposes does not include byproduct fuel resulting 

from the use of other energy, but includes those resulting from the use of nonenergy sources as raw material input.

Capacity-Utilization Rate: Equals the seasonally adjusted index of industrial production divided by a capacity index 

(sustainable practical capacity, i.e., the greatest level of output a plant can maintain within a realistic work schedule). The 

Federal Reserve Board weights the capacity indexes by value-added proportions. This methodology is described in 

Appendix A.

Feedstock Energy Consumption: Includes all energy sources consumed as a raw material, and it is definitionally 

equivalent to total primary consumption of energy for nonfiiel purposes described in the Manufacturing Energy Consumption 

Survey (MECS).

Gross Output: Gross output equals shipments, minus cost of resale, plus changes in business inventories, coverage 

adjustment, commodity taxes, and new force account construction (value of construction undertaken with own labor, capital, 

etc.). All components are deflated to 1987 dollars. The Bureau of Economic Analysis considers this to be the most 

comprehensive measure of manufacturing production.

Gross Product Originating (GPO): The attribution of gross domestic product to industries or sectors of origin, as provided 

by the National Income and Product Accounts of the Bureau of Economic Analysis. GPO is compiled by summing income 

components—wages and salaries, capital, profits, etc.—and corresponds in concept to value added. GPO deflators are used 

to convert current dollar-denominated value added into 1987 constant dollars.

High-Energy Consumers: Consists of the major manufacturing groups Food and Kindred Products, Paper and Allied 

Products, Chemicals and Allied Products, Petroleum and Coal Products, Stone, Clay and Glass Products, and Primary Metal 

Industries. These firms convert raw materials into finished goods primarily by chemical (and not by physical) means. Heat 

is essential to their production, and steam provides much of the heat. Natural gas and byproduct and waste fuels are the 

largest sources of energy for this group.

High-Value Added Consumers: Producers of high value-added transportation vehicles, industrial machinery, electrical 

equipment, instruments, and miscellaneous equipment. The primary end uses are motor-driven physical conversion of 

materials (cutting, forming, assembly) and heat treating, drying and bonding. Natural gas is the principal energy source for 

these firms.

Industrial Production: The Federal Reserve Board calculates this index by compiling indices of physical output from a 

variety of agencies and trade groups, weighting each index by the Census' value added, and adding it to the cost of materials. 

When physical measures are not available, the Federal Reserve Board uses the number of production workers or amount 

of electricity consumed as the basis for the index. To convert industrial production into dollars, multiply by the "real value 

added" estimate used by the Federal Reserve Board.

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Industrial Sector: As defined by EIA, Comprises manufacturing industries, which make up the largest part of the sector, 

along with mining, construction, agriculture, fisheries, and forestry. Establishments in the sector range from steel mills and 

small farms to companies assembling electronic components. The SIC codes 20 through 39 are used to classify 

establishments as industrial. A subdivision of U.S. economic activity defined by EIA to include manufacturing, construction, 

mining, agriculture, fishing, and forestry (nonmanufacturing) establishments.

Inventories: Year-end inventories at cost or market value, deflated to 1987 constant dollars using value of shipments 

implicit price deflators reported by Bureau of Economic Analysis.

Low-Energy Consumers: This group is the smallest energy consuming sector and represents a combination of end use 

requirements. Motor drive is one of the key end uses. Included in this group are tobacco firms, textile mills, lumber mills, 

rubber and plastics plants, printing and publishing operations, and furniture, apparel, and leather makers.

Major Industry Groups: Two-digit SIC industries, 1-39.

Manufacturing Establishment: An economic unit at a single physical location where mechanical or chemical 

transformation of materials or substances into new products are performed.

Manufacturing Sector: One of 10 fields of economic activity defined by the Standard Industrial Classification Manual, 

including two-digit SIC industries 20-39. It includes all establishments engaged in the mechanical or chemical 

transformation of materials or substances into new products. The establishments in the manufacturing sector constitute the 

universe for MECS.

Total Consumption of Energy for All Purposes: This measure includes offsite-produced energy, feedstocks energy, and 

onsite byproduct fuels resulting from the use of a nonenergy materials as feedstocks. It excludes electricity losses, as well 

as byproduct fuels resulting from the use of energy sources as raw materials.

Nonmanufacturing: Includes agriculture, construction, mining, and resource extraction.

Offsite-Produced Energy for Heat, Power and Electricity Generation: This measure of energy consumption, which 

is equivalent to purchased energy includes energy produced off-site and consumed onsite. It excludes energy produced and 

consumed onsite, energy used as raw material input, and electricity losses.

Standard Industrial Classification (SIC): A classification scheme developed by the Office of Management and Budget 

that categorizes establishments into groups with similar economic activities.

Total Inputs of Energy for Heat, Power, and Electricity Generation: This measure of energy consumption includes 

offsite-produced energy and byproduct fuels resulting from the use of both energy and nonenergy materials as feedstocks. 

However, it excludes feedstocks and electricity losses. Reported in trillion or quadrillion Btu and referred to as Inputs of 

Energy in this report.

Value Added: For the manufacturing and mining sectors, it is a measure of activity derived by subtracting the cost of 

materials, supplies, containers, purchased fuel and electricity, and contract work from the value of shipments (products 

manufactured or mined plus receipts for services rendered). This calculation is adjusted by adding the value added by 

merchandising (mark-up) and the net change in finished goods and work-in-progress inventories. For industries in which 

value of production is collected instead of value of shipments, value added is adjusted by the change in work-in-progress 

inventories. Deflated to 1987 constant dollars using GPO deflator.

Value of Production: Calculated as the value of shipments plus inventory change during the year (subtract prior year-end 

from current year-end inventories) in constant 1987 dollars.

Value of Shipments: Received or receivable net selling values (exclusive of freight and taxes) of all primary and secondary 

products shipped, as well as all miscellaneous receipts for contract work performed for others, installation and repair, sales 

of scrap, and sales of products bought and resold without further processing. Deflated to constant 1987 dollars using GPO 

deflators.

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90 Measuring Energy Efficiency In the United States' Economy: A Beginning
Structurally-Adjusted Estimates: Aggregate energy-intensity changes in the manufacturing sector, from which energy 

efficiency changes may be inferred, include real efficiency changes, changes due to structural shifts in the economy, and 

interaction effects. Separation of structural effects from manufacturing energy-intensity is achieved by characterizing the 

economy in such a way that changing composition of the manufacturing sector is measured by changes in the relative output 

(or changes in the share of output).

It must be emphasized that the extent to which structural shifts can be eliminated from intensity measurement depends on 

the level of disaggregation. For instance, disaggregation at the four-digit SIC level would yield a better result than that at 

the three-digit SIC level, while disaggregation at the three-digit SIC level would yield a better result than that at the two-digit 

level.

U.S. Economy

Energy Source: Any substance that supplies heat or power, e.g., petroleum, natural gas, coal, renewable energy, and 

electricity, including the use of a fuel as a non-energy feedstock.

Fossil Fuel: Any naturally occurring organic fuel, such as petroleum, coal, and natural gas.

Gross Generation: The total amount of electric energy produced by the generating units at a generating station(s), measured 

at the generator terminals.

Gross Inputs: The heat value (Btu) of the energy sources used to generate electricity, measured at the generator terminals, 

including energy used at the generating station.

Net Generation: Gross generation less megawatt hours consumed out of gross generation for station use or auxiliary 

equipment the electric energy consumed at the generating station for station use.

Nonutility Generator: A corporation, person agency, authority, or other legal entity or instrumentality that owns electric 

generating capacity and is not an electric utility. Include qualifying cogenerators and small power producers, and other 

nonutility power producers without a designated franchised service area.

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