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Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

Household Energy Consumption and Expenditures  

Reports and Publications (EIA)

Presents information about household end use consumption of energy and expenditures for that energy. These data were collected in the 2005 Residential Energy Consumption Survey (RECS)

Information Center

2008-09-01T23:59:59.000Z

2

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

DOEEIA-0464(91) Distribution Category UC-950 Household Vehicles Energy Consumption 1991 December 1993 Energy Information Administration Office of Energy Markets and End Use U.S....

3

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

a regular basis at the time of the 1990 RECS personal interviews. Electricity: See Main Heating Fuel. Energy Information AdministrationHousehold Vehicles Energy Consumption 1991...

4

Household Vehicles Energy Consumption 1994  

U.S. Energy Information Administration (EIA) Indexed Site

AdministrationHousehold Vehicles Energy Consumption 1994 110 Electricity: See Main Heating Fuel. Energy Used in the Home: For electricity or natural gas, the quantity is the...

5

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

. . Vehicle Fuel Efficiency and Consumption Fuel consumption is estimated from RTECS data on the vehicle stock (Chapter 2) and miles traveled (Chapter 3), in combination with vehicle fuel efficiency ratings, adjusted to account for individual driving circumstances. The first two sections of this chapter present estimates of household vehicle fuel efficiency and household fuel consumption calculated from these fuel efficiency estimates. These sections also discuss variations in fuel efficiency and consumption based on differences in household and vehicle characteristics. The third section presents EIA estimates of the potential savings from replacing the oldest (and least fuel-efficient) household vehicles with new (and more fuel-efficient) vehicles. The final section of this chapter focuses on households receiving (or eligible to receive) supplemental income under

6

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

3. 3. Vehicle Miles Traveled This chapter presents information on household vehicle usage, as measured by the number of vehicle miles traveled (VMT). VMT is one of the two most important components used in estimating household vehicle fuel consumption. (The other, fuel efficiency, is discussed in Chapter 4). In addition, this chapter examines differences in driving behavior based on the characteristics of the household and the type of vehicle driven. Trends in household driving patterns are also examined using additional information from the Department of Transportation's Nationwide Personal Transportation Survey (NPTS). Household VMT is a measure of the demand for personal transportation. Demand for transportation may be viewed from either an economic or a social perspective. From the economic point-of-view, the use of a household vehicle represents the consumption of one

7

Household Vehicles Energy Consumption 1994  

U.S. Energy Information Administration (EIA) Indexed Site

W as hi ng to n, DC DOEEIA-0464(94) Distribution Category UC-950 Household Vehicles Energy Consumption 1994 August 1997 Energy Information Administration Office of Energy Markets...

8

Household vehicles energy consumption 1994  

SciTech Connect

Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

NONE

1997-08-01T23:59:59.000Z

9

Household vehicles energy consumption 1991  

Science Conference Proceedings (OSTI)

The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted during 1991 and early 1992. The 1991 RTECS represents 94.6 million households, of which 84.6 million own or have access to 151.2 million household motor vehicles in the 50 States and the District of Columbia.

Not Available

1993-12-09T23:59:59.000Z

10

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

Detailed Detailed Tables The following tables present detailed characteristics of vehicles in the residential sector. Data are from the 1991 Residential Transportation Energy Consumption Survey. The "Glossary" contains the definitions of terms used in the tables. Table Organization The "Detailed Tables" section consists of three types of tables: (1) Tables of totals such as number of vehicle miles traveled (VMT) or gallons consumed; (2) Tables of per household statistics such as VMT per household; and (3) Tables of per vehicle statistics such as vehicle fuel consumption per vehicle. The tables have been grouped together by specific topics such as model year data, or family income data to facilitate finding related information. The Quick-Reference Guide to the detailed tables indicates major topics of each table. Row and Column Factors These tables present estimates

11

Household energy consumption and expenditures 1987  

SciTech Connect

This report is the third in the series of reports presenting data from the 1987 Residential Energy Consumption Survey (RECS). The 1987 RECS, seventh in a series of national surveys of households and their energy suppliers, provides baseline information on household energy use in the United States. Data from the seven RECS and its companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are made available to the public in published reports such as this one, and on public use data files. This report presents data for the four Census regions and nine Census divisions on the consumption of and expenditures for electricity, natural gas, fuel oil and kerosene (as a single category), and liquefied petroleum gas (LPG). Data are also presented on consumption of wood at the Census region level. The emphasis in this report is on graphic depiction of the data. Data from previous RECS surveys are provided in the graphics, which indicate the regional trends in consumption, expenditures, and uses of energy. These graphs present data for the United States and each Census division. 12 figs., 71 tabs.

Not Available

1990-01-22T23:59:59.000Z

12

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

1. 1. Introduction The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The Energy Information Administration (EIA) is mandated by Congress to collect, analyze, and disseminate impartial, comprehensive data about energy--how much is produced, who uses it, and the purposes for which it is used. To comply with this mandate, EIA collects energy data from a variety of sources covering a range of topics 1 . Background The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted

13

Elements of consumption: an abstract visualization of household consumption  

Science Conference Proceedings (OSTI)

To promote sustainability consumers must be informed about their consumption behaviours. Ambient displays can be used as an eco-feedback technology to convey household consumption information. Elements of Consumption (EoC) demonstrates this by visualizing ... Keywords: a-life, eco-feedback, household consumption, sustainability

Stephen Makonin; Philippe Pasquier; Lyn Bartram

2011-07-01T23:59:59.000Z

14

Household Vehicles Energy Consumption 1994 - PDF Tables  

U.S. Energy Information Administration (EIA)

Table 1 U.S. Number of Vehicles, Vehicle Miles, Motor Fuel Consumption and Expenditures, 1994 Table 2 U.S. per Household Vehicle Miles Traveled, Vehicle Fuel ...

15

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

. . Trends in Household Vehicle Stock The 1991 RTECS counted more than 150 million vehicles in use by U.S. households. This chapter examines recent trends in the vehicle stock, as measured by the RTECS and other reputable vehicle surveys. It also provides some details on the type and model year of the household vehicle stock, and identifies regional differences in vehicle stock. Because vehicles are continuously being bought and sold, this chapter also reports findings relating to turnover of the vehicle stock in 1991. Finally, it examines the average vehicle stock in 1991 (which takes into account the acquisition and disposal of household vehicles over the course of the year) and identifies variations in the average number of household vehicles based on differences in household characteristics. Number of Household Vehicles Over the past 8 years, the stock of household vehicles has

16

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

Aggregate Aggregate Ratio: See Mean and Ratio Estimate. AMPD: Average miles driven per day. See Appendix B, "Estimation Methodologies." Annual Vehicle Miles Traveled: See Vehicle Miles Traveled. Automobile: Includes standard passenger car, 2-seater car and station wagons; excludes passenger vans, cargo vans, motor homes, pickup trucks, and jeeps or similar vehicles. See Vehicle. Average Household Energy Expenditures: A ratio estimate defined as the total household energy expenditures for all RTECS households divided by the total number of households. See Ratio Estimate, and Combined Household Energy Expenditures. Average Number of Vehicles per Household: The average number of vehicles used by a household for personal transportation during 1991. For this report, the average number of vehicles per household is computed as the ratio of the total number of vehicles to the

17

Household energy consumption and expenditures 1993  

Science Conference Proceedings (OSTI)

This presents information about household end-use consumption of energy and expenditures for that energy. These data were collected in the 1993 Residential Energy Consumption Survey; more than 7,000 households were surveyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information represents all households nationwide (97 million). Key findings: National residential energy consumption was 10.0 quadrillion Btu in 1993, a 9% increase over 1990. Weather has a significant effect on energy consumption. Consumption of electricity for appliances is increasing. Houses that use electricity for space heating have lower overall energy expenditures than households that heat with other fuels. RECS collected data for the 4 most populous states: CA, FL, NY, TX.

NONE

1995-10-05T23:59:59.000Z

18

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

methodology used to estimate these statistics relied on data from the 1990 Residential Energy Consumption Survey (RECS), the 1991 Residential Transportation Energy Consumption...

19

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

Appendix A How the Survey Was Conducted Introduction The Residential Transportation Energy Consumption Survey (RTECS) was designed by the Energy Information Administration (EIA)...

20

Did Household Consumption Become More Volatile?  

E-Print Network (OSTI)

I show that after accounting for predictable variation arising from movements in real interest rates, preferences, income shocks, liquidity constraints and measurement errors, volatility of household consumption in the US increased between 1970 and 2004. For households headed by nonwhite and/or poorly educated individuals, this rise was significantly larger. This stands in sharp contrast with the dramatic fall in instability of the aggregate U.S. economy over the same period. Thus, while aggregate shocks affecting households fell over time, idiosyncratic shocks increased. This finding may lead to significant welfare implications.

Olga Gorbachev

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

C C Quality of the Data Appendix C Quality of the Data Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses under- coverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1991 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1991 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics published in this report such as total

22

Household energy and consumption and expenditures, 1990. Supplement, Regional  

Science Conference Proceedings (OSTI)

The purpose of this supplement to the Household Energy Consumption and Expenditures 1990 report is to provide information on the use of energy in residential housing units, specifically at the four Census regions and nine Census division levels. This report includes household energy consumption, expenditures, and prices for natural gas, electricity, fuel oil, liquefied petroleum gas (LPG), and kerosene as well as household wood consumption. For national-level data, see the main report, Household Energy Consumption and Expenditures 1990.

Not Available

1993-03-02T23:59:59.000Z

23

Essays on the effects of demographics on household consumption.  

E-Print Network (OSTI)

??My dissertation analyses the relationship between households' consumption behavior and changes in family demographic characteristics. The first paper studies consumption over the period of the… (more)

Stepanova, Ekaterina, 1977-

2006-01-01T23:59:59.000Z

24

1997 Residential Energy Consumption and Expenditures per Household ...  

U.S. Energy Information Administration (EIA)

Return to: Residential Home Page . Changes in the 1997 RECS: Housing Unit Type Per Household Member Per Building Increase. Residential Energy Consumption ...

25

Household Energy Consumption and Expenditures 1993 -- Executive ...  

U.S. Energy Information Administration (EIA)

national level data on energy-related issues on households and energy expenditures in the residential sector.

26

Household and environmental characteristics related to household energy-consumption change: A human ecological approach  

Science Conference Proceedings (OSTI)

This study focused on the family household as an organism and on its interaction with the three environments of the human ecosystem (natural, behavioral, and constructed) as these influence energy consumption and energy-consumption change. A secondary statistical analysis of data from the US Department of Energy Residential Energy Consumption Surveys (RECS) was completed. The 1980 and 1983 RECS were used as the data base. Longitudinal data, including household, environmental, and energy-consumption measures, were available for over 800 households. The households were selected from a national sample of owner-occupied housing units surveyed in both years. Results showed a significant( p = household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

Guerin, D.A.

1988-01-01T23:59:59.000Z

27

Energy Consumption of Refrigerators in Ghana - Outcomes of Household...  

NLE Websites -- All DOE Office Websites (Extended Search)

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar HostPoint of...

28

Smoothing consumption across households and time : essays in development economics  

E-Print Network (OSTI)

This thesis studies two strategies that households may use to keep their consumption smooth in the face of fluctuations in income and expenses: credit (borrowing and savings) and insurance (state contingent transfers between ...

Kinnan, Cynthia Georgia

2010-01-01T23:59:59.000Z

29

Residential energy consumption survey. Consumption patterns of household vehicles, supplement: January 1981-September 1981  

Science Conference Proceedings (OSTI)

Information on the fuel consumption characteristics on household vehicles in the 48 contiguous States and the District of Columbia is presented by monthly statistics of fuel consumption, expenditures, miles per gallon, and miles driven.

Not Available

1983-02-01T23:59:59.000Z

30

Projecting household energy consumption within a conditional demand framework  

SciTech Connect

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

31

Projecting household energy consumption within a conditional demand framework  

Science Conference Proceedings (OSTI)

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

32

Appliance Standby Power and Energy Consumption in South African Households  

Open Energy Info (EERE)

Appliance Standby Power and Energy Consumption in South African Households Appliance Standby Power and Energy Consumption in South African Households Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Appliance Standby Power and Energy Consumption in South African Households Focus Area: Appliances & Equipment Topics: Policy Impacts Website: active.cput.ac.za/energy/web/DUE/DOCS/422/Paper%20-%20Shuma-Iwisi%20M. Equivalent URI: cleanenergysolutions.org/content/appliance-standby-power-and-energy-co Language: English Policies: Deployment Programs DeploymentPrograms: Technical Assistance A modified engineering model is proposed to estimate standby power and energy losses in households. The modified model accounts for the randomness of standby power and energy losses due to unpredicted user appliance operational behavior.

33

A Glance at China’s Household Consumption  

SciTech Connect

Known for its scale, China is the most populous country with the world’s third largest economy. In the context of rising living standards, a relatively lower share of household consumption in its GDP, a strong domestic market and globalization, China is witnessing an unavoidable increase in household consumption, related energy consumption and carbon emissions. Chinese policy decision makers and researchers are well aware of these challenges and keen to promote green lifestyles. China has developed a series of energy policies and programs, and launched a wide?range social marketing activities to promote energy conservation.

Shui, Bin

2009-10-22T23:59:59.000Z

34

Energy Information Administration/Household Vehicles Energy Consumption 1994  

U.S. Energy Information Administration (EIA) Indexed Site

, , Energy Information Administration/Household Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related characteristics of highway vehicles available for personal use by members of U.S. households. The data were collected in the 1994 Residential Transportation Energy Consumption Survey, the final cycle in a series of nationwide energy consumption surveys conducted during the 1980's and 1990's by the Energy Information Administrations. Engines Became More Powerful . . . Percent Distribution of Total Residential Vehicle Fleet by Number of Cylinders, 1988 and 1994 Percent Distribution of Vehicle Fleet by Engine Size, 1988 and 1994 Percent Percent 4 cyl Less than 2.50 liters 6 cyl 2.50- 4.49 liters 8 cyl 4.50 liters or greater 20 20 40 40 Vehicle

35

Energy Consumption of Refrigerators in Ghana - Outcomes of Household  

NLE Websites -- All DOE Office Websites (Extended Search)

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Robert Van Buskirk Galen Barbose As part of activities to develop refrigerator efficiency standards regulations in Ghana, a national survey on the energy consumption of refrigerators and refrigerator-freezers has been conducted. The survey covered 1000 households in urban, peri-urban and rural communities in various parts of the country. The survey found that, on average, refrigerators and refrigerator-freezers in Ghana use almost three times what is allowed by minimum efficiency standards in the U.S., and a few refrigerators had energy use at levels almost ten times the U.S.

36

Table CE2-3c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household4,a Physical Units of Space-Heating Consumption per Household,3 Where the Main Space-Heating Fuel Is:

37

Table CE2-7c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

38

Table CE2-12c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

39

Table CE2-4c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

40

Table CE2-7c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3 Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

RECS data show decreased energy consumption per household  

Reports and Publications (EIA)

Total United States energy consumption in homes has remained relatively stable for many years as increased energy efficiency has offset the increase in the number and average size of housing units, according to the newly released data from the Residential Energy Consumption Survey (RECS). The average household consumed 90 million British thermal units (Btu) in 2009 based on RECS. This continues the downward trend in average residential energy consumption of the last 30 years. Despite increases in the number and the average size of homes plus increased use of electronics, improvements in efficiency for space heating, air conditioning, and major appliances have all led to decreased consumption per household. Newer homes also tend to feature better insulation and other characteristics, such as double-pane windows, that improve the building envelope.

2012-06-06T23:59:59.000Z

42

Household Vehicles Energy Consumption 1994 - Appendix C  

U.S. Energy Information Administration (EIA) Indexed Site

Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses undercoverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1994 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1994 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics

43

Household energy and consumption and expenditures, 1990. [Contains Division, Census Region, and Climate Zone maps  

Science Conference Proceedings (OSTI)

The purpose of this supplement to the Household Energy Consumption and Expenditures 1990 report is to provide information on the use of energy in residential housing units, specifically at the four Census regions and nine Census division levels. This report includes household energy consumption, expenditures, and prices for natural gas, electricity, fuel oil, liquefied petroleum gas (LPG), and kerosene as well as household wood consumption. For national-level data, see the main report, Household Energy Consumption and Expenditures 1990.

Not Available

1993-03-02T23:59:59.000Z

44

Table 2. Fuel Oil Consumption and Expeditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Fuel Oil Consumption and Expeditures in U.S. Households ... Space Heating - Main or Secondary ... Forms EIA-457 A-G of the 2001 Residential Energy Consumption

45

Feed the Future Bangladesh: Baseline Integrated Household Survey | Data.gov  

NLE Websites -- All DOE Office Websites (Extended Search)

Feed the Future Bangladesh: Baseline Integrated Household Survey Feed the Future Bangladesh: Baseline Integrated Household Survey Agriculture Community Menu DATA APPS EVENTS DEVELOPER STATISTICS COLLABORATE ABOUT Agriculture You are here Data.gov » Communities » Agriculture » Data Feed the Future Bangladesh: Baseline Integrated Household Survey Dataset Summary Description The Bangladesh Integrated Household Survey dataset is a thorough assessment of current standard of food security in Bangladesh taken from 2011-2012. The dataset includes all baseline household surveys made under the USAID-led Feed the Future initiative, a collaborative effort that supports country-owned processes and plans for improving food security and promoting transparency, and within the Zones of Influence as outlined by the Feed the Future Bangladesh plan .The BIHS sample is statistically representative at the following levels: (a) nationally representative of rural Bangladesh; (b) representative of rural areas of each of the seven administrative divisions of the country; and, (c) representative of the Feed the Future (FTF) zone of influence.

46

Residential energy consumption and expenditure patterns of black and nonblack households in the United States  

Science Conference Proceedings (OSTI)

Residential energy consumption and expenditures by black and nonblack households are presented by Census region and for the nation based on the Energy Information Administration's 1982-83 Residential Energy Consumption Survey (RECS). Black households were found to have significantly lower levels of electricity consumption at both the national and regional level. Natural gas is the dominant space heating fuel used by black households. Natural gas consumption was typically higher for black households. However, when considering natural gas consumption conditional on natural gas space heating no significant differences were found. 10 refs., 1 fig., 8 tabs.

Vyas, A.D.; Poyer, D.A.

1987-01-01T23:59:59.000Z

47

Table 1. Total Energy Consumption in U.S. Households by Origin ...  

U.S. Energy Information Administration (EIA)

Wood (million cords) ..... 21.4 19.8 0.8 0.6 0.3 19.3 Million Btu per Household3 Total Btu Consumption per Household, Fuels Used: Electricity Primary ...

48

Essays on the Consumption and Investment Decisions of Households in the Presence of Housing and Human Capital  

E-Print Network (OSTI)

2 Housing and the Consumption Allocation of Households:of Indivisibility on Housing Consumption Volatility . 2.5and consumption allocation . . . . . . . . . . . . . . .

Betermier, Sebastien

2010-01-01T23:59:59.000Z

49

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Total Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total ... where the end use is electric air-conditioning, ...

50

Table 1. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

This write-up presents 1997 Residential Energy Consumption and Expenditures by Origin of Householder. In 1997, there were 101.5 million residential ho ...

51

Table 3. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

This write-up presents 1997 Residential Energy Consumption and Expenditures by Origin of Householder. In 1997, there were 101.5 million residential ...

52

Analysis of the energy requirement for household consumption.  

E-Print Network (OSTI)

??Humans in households use energy for their activities. This use is both direct, for example electricity and natural gas, but also indirect, for the production,… (more)

Vringer, Kees

2005-01-01T23:59:59.000Z

53

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-01-01T23:59:59.000Z

54

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-06-01T23:59:59.000Z

55

Simulating household activities to lower consumption peaks: demonstration  

Science Conference Proceedings (OSTI)

Energy experts need fine-grained dynamics oriented tools to investigate household activities in order to improve power management in the residential sector. This paper presents the SMACH framework for modelling, simulating and analy- sis of household ... Keywords: agent-based modelling, energy, social simulation

Edouard Amouroux, Francois Sempé, Thomas Huraux, Nicolas Sabouret, Yvon Haradji

2013-05-01T23:59:59.000Z

56

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Table CE1-4c. Total Energy Consumption in U.S. Households by Type of Housing Unit, 1997 ... where the end use is electric air-conditioning, ...

57

Table CE1-1c. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE1-1c. Total Energy Consumption in U.S. Households by Climate Zone, 2001 RSE Column Factor: Total Climate Zone1 RSE Row Factors Fewer than 2,000 CDD and --

58

Table CE1-10c. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE1-10c. Total Energy Consumption in U.S. Households by Midwest Census Region, 2001 RSE Column Factor: Total U.S. Midwest Census Region RSE Row

59

Table 4. LPG Consumption and Expeditures in U.S. Households by End ...  

U.S. Energy Information Administration (EIA)

Table 4. LPG Consumption and Expeditures in U.S. Households by End Uses and Census Region, 2001 RSE Column Factor: Total U.S. Census Region RSE Row

60

Table CE4-7c. Water-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE4-7c. Water-Heating Energy Consumption in U.S. Households by Four Most Populated States, 1997 RSE Column Factor: Total U.S. Four Most Populated States

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Table CE5-2c. Appliances Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE5-2c. Appliances1 Energy Consumption in U.S. Households by Year of Construction, 2001 RSE Column Factor: Total Year of Construction RSE Row

62

Essays on health care consumption and household finance  

E-Print Network (OSTI)

This thesis explores how health insurance affects the decisions that individuals make. The first chapter studies the effect of insurance on health care consumption. Nearly 10 percent of teenagers become ineligible for their ...

Gross, Tal (Tal A.)

2009-01-01T23:59:59.000Z

63

Residential energy consumption and expenditure patterns of low-income households in the United States  

SciTech Connect

The principal objective of this study is to compare poor and non-poor households with respect to energy consumption and expenditures, housing characteristics, and energy-related behavior. We based our study on an analysis of a national data base created by the US Department of Energy, the 1982-1983 Residential Energy Consumption Survey (RECS). RECS includes detailed information on individual households: demographic characteristics, energy-related features of the structure, heating equipment and appliances, recent conservation actions taken by the household, and fuel consumption and costs for April 1982-March 1983. We found a number of statistically significant (at the 0.05 level) differences between the two income groups in terms of demographics, heating/cooling/water heating systems, appliance saturation, the thermal integrity of their home, energy conservation behavior, energy consumption, energy expenditures, and the percentage of income spent on energy costs. For example, the non-poor used 22% more energy and paid 25% more money on utilities than the poor; however, the poor spent 20% more energy per square foot than the non-poor and spent about 25% of their income on energy expenditures, compared to 7% for the non-poor. These differences suggest different approaches that might be taken for targeting energy conservation programs to low-income households. Since the poor's ''energy burden'' is large, informational, technical, and financial assistance to low-income households remains an urgent, national priority. 13 refs., 26 tabs.

Vine, E.L.; Reyes, I.

1987-09-01T23:59:59.000Z

64

The impact of the Persian Gulf crisis on household energy consumption and expenditure patterns  

Science Conference Proceedings (OSTI)

The Iraqi invasion of the Kingdom of Kuwait on August 2, 1990, and the subsequent war between Iraq and an international alliance led by the United States triggered first immediate and then fluctuating world petroleum prices. Increases in petroleum prices and in U.S. petroleum imports resulted in increases in the petroleum prices paid by U.S. residential, commercial, and industrial consumers. The result was an immediate price shock that reverberated throughout the U.S. economy. The differential impact of these price increases and fluctuations on poor and minority households raised immediate, significant, and potentially long-term research, policy, and management issues for a variety of federal, state, and local government agencies, including the U.S. Department of Energy (DOE). Among these issues are (1) the measurement of variations in the impact of petroleum price changes on poor, nonpoor, minority, and majority households; (2) how to use the existing policy resources and policy innovation to mitigate regressive impacts of petroleum price increases on lower-income households; and (3) how to pursue such policy mitigation through government agencies severely circumscribed by tax and expenditure limitations. Few models attempt to assess household energy consumption and energy expenditure under various alternative price scenarios and with respect to the inclusion of differential household choices correlated with such variables as race, ethnicity, income, and geographic location. This paper provides a preliminary analysis of the nature and extent of potential impacts of petroleum price changes attributable to the Persian Gulf War and its aftermath on majority, black, and Hispanic households and on overlapping poor and nonpoor households. At the time this was written, the Persian Gulf War had concluded with Iraq`s total surrender to all of the resolutions and demands of the United Nations and United States.

Henderson, L. [Univ. of Baltimore, MD (United States); Poyer, D.; Teotia, A. [Argonne National Lab., IL (United States)

1994-09-01T23:59:59.000Z

65

Understanding and Improving Household Energy Consumption and Carbon Emissions Policies - A System Dynamics Approach  

E-Print Network (OSTI)

The purpose of this paper is to propose and demonstrate the application of system dynamics modeling approach to analyze and study the behavior the complex interrelationships among the different policies/interventions aimed at reducing household energy consumption and CO2 emissions (HECCE) based on the Climate Change Act of 2008 of the UK government. The paper uses the system dynamics as both the methodology and tool to model the policies/interventions regarding HECCE. The model so developed shows the complex interrelationships among the different policies/interventions variables and presents the basis for simulating the different scenarios of household energy consumption reduction strategies. The paper concludes that the model is capable of adding to the understanding of the complex system under which HECCE operate and improve it accordingly by studying the behavior of each policy/intervention over time. The outcomes of the research will help decision makers draw more realistic policies/interventions for household energy consumption which is critical to the CO2 emissions reductions agenda of the government.

Oladokun, M.; Motawa, I.; Banfill, P.

2012-01-01T23:59:59.000Z

66

Residential energy consumption of low-income and elderly households: how non-discretionary is it  

SciTech Connect

The energy literature is replete with opinions that the poor and elderly have cut their residential energy consumption to a minimum. This paper challenges such conclusions through an analysis of data on a sample of 319 Decatur, Illinois homeowners. The data include utility bill histories and survey information on housing characteristics, energy-related behaviors, attitudes, and socio-economic and demographic characteristics. It shows that residential energy consumption per square foot of living space is significantly higher for the elderly and poor than for other groups of Decatur homeowners. By breaking energy use into seasonal components, the paper estimates consumption for various household uses. This information, combined with the survey data, suggests that both subgroups heat and cool their homes inefficiently, due in part to the conditions of their homes, but also due to energy-related behaviors. The public policy implications of the findings are discussed.

Brown, M.A.; Rollinson, P.A.

1984-01-01T23:59:59.000Z

67

The federal energy policy: An example of its potential impact on energy consumption and expenditures in minority and poor households  

SciTech Connect

This report presents an analysis of the relative impacts of the National Energy Strategy on majority and minority households and on nonpoor and poor households. (Minority households are defined as those headed by black or Hispanic persons; poor households are defined as those having combined household income less than or equal to 125% of the Office of Management and Budget`s poverty-income threshold.) Energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1987 to 2009 are reported. Projected consumptions of electricity and nonelectric energy over this period are also reported for each group. An analysis of how these projected values are affected under different housing growth scenarios is performed. The analysis in this report presents a preliminary set of projections generated under a set of simplifying assumptions. Future analysis will rigorously assess the sensitivity of the projected values to various changes in a number of these assumptions.

Poyer, D.A.

1991-09-01T23:59:59.000Z

68

Changing Trends: A Brief History of the US Household Consumption of Energy, Water, Food, Beverages and Tobacco  

E-Print Network (OSTI)

in household and per capita consumption of energy and water, and also at food, beverages, and tobacco, products invites several questions: Did per capita energy use increase from 1949 to 1973 due to bigger houses US primary energy consumption from 1949 to 2001 (Figure 1). In 1949, U.S. energy use per person stood

Diamond, Richard

69

Household activities through various lenses: crossing surveys, diaries and electric consumption  

E-Print Network (OSTI)

comparison between electricity consumption and behavioralK. 2013. “Domestic energy consumption-What role do comfort,residential electricity consumption” Energy Policy, 42(2012)

Durand-Daubin, Mathieu

2013-01-01T23:59:59.000Z

70

Table 1. Consumption and Expenditures in U.S. Households, 1997  

U.S. Energy Information Administration (EIA)

A household is assigned to a climate zone according to the 30-year average annual degree-days for an appropriate nearby weather station. (5) ...

71

Table CE1-7c. Total Energy Consumption in U.S. Households by Four ...  

U.S. Energy Information Administration (EIA)

Other Appliances and Lighting ... It does include the small number of households where the fuel for central air-conditioning equipment was something other than ...

72

Assessing the Environmental Costs and Benefits of Households Electricity Consumption Management.  

E-Print Network (OSTI)

?? In this study the environmental costs and benefits of smart metering technology systems installed in households in Norway have been assessed. Smart metering technology… (more)

Segtnan, Ida Lund

2011-01-01T23:59:59.000Z

73

Section J: HOUSEHOLD CHARACTERISTICS  

U.S. Energy Information Administration (EIA)

2001 Residential Energy Consumption Survey Form EIA-457A (2001)--Household Questionnaire OMB No.: 1905-0092, Expiring February 29, 2004 42 Section J: HOUSEHOLD ...

74

Do Households Smooth Small Consumption Shocks? Evidence from Anticipated and Unanticipated Variation in Home Energy Costs  

E-Print Network (OSTI)

Erik Hurst. 2004. “Consumption vs. Expenditure. ” National14: Attanasio, Orazio. 1999. “Consumption. ” In J.Taylor andThe Life-Cycle Model of Consumption and Saving. ” Journal of

Cullen, Julie Berry; Friedberg, Leora; Wolfram, Catherine

2005-01-01T23:59:59.000Z

75

Residential energy consumption across different population groups: Comparative analysis for Latino and non-Latino households in U.S.A.  

SciTech Connect

Residential energy cost, an important part of the household budget, varies significantly across different population groups. In the United States, researchers have conducted many studies of household fuel consumption by fuel type -- electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG) -- and by geographic areas. The results of past research have also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, research shows that residential energy demand by fuel type for Latinos, the fastest-growing population group in the United States, has not been explained by economic and noneconomic factors in any available statistical model. This paper presents a discussion of energy demand and expenditure patterns for Latino and non-Latino households in the United States. The statistical model developed to explain fuel consumption and expenditures for Latino households is based on Stone and Geary`s linear expenditure system model. For comparison, the authors also developed models for energy consumption in non-Latino, black, and nonblack households. These models estimate consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. The study revealed significant variations in the patterns of fuel consumption for Latinos and non-Latinos. The model methodology and results of this research should be useful to energy policymakers in government and industry, researchers, and academicians who are concerned with economic and energy issues related to various population groups.

Poyer, D.A.; Teotia, A.P.S. [Argonne National Lab., IL (United States); Henderson, L. [Univ. of Baltimore, MD (United States)

1998-05-01T23:59:59.000Z

76

Leaking electricity: Standby and off-mode power consumption in consumer electronics and household appliances  

Science Conference Proceedings (OSTI)

This report assesses ``leaking`` electricity from consumer electronics and small household appliances when they are in standby mode or turned off, and examines the impacts of these losses. The report identifies trends in relevant product industries and gives technical and policy options for reducing standby and off-mode power loss.

Thorne, J.; Suozzo, M.

1998-12-31T23:59:59.000Z

77

Household activities through various lenses: crossing surveys, diaries and electric consumption  

E-Print Network (OSTI)

changes differ from one appliance to another. Referencespeople activities, appliances use, and electric consumption.of use of the three appliances studied. However, variations

Durand-Daubin, Mathieu

2013-01-01T23:59:59.000Z

78

Household operational energy consumption in urban China : a multilevel analysis on Jinan  

E-Print Network (OSTI)

With decades of economic growth and socio-economic transformation, China's residential sector has seen rapid expansion in energy consumption, and is now the second largest energy consuming sector in the country. Faced with ...

Wang, Dong, M.C.P. Massachusetts Institute of Technology

2012-01-01T23:59:59.000Z

79

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Key Assumptions Key Assumptions The historical input data used to develop the HEM version for the AEO2000 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2000 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and transportation sectors as inputs to the disaggregation algorithm that results in the direct fuel expenditure analysis. Household end-use and personal transportation service consumption are obtained by HEM from the NEMS Residential and Transportation Demand Modules. Household disposable income is adjusted with forecasts of total disposable income from the NEMS Macroeconomic Activity Module.

80

Promoting new patterns in household energy consumption with pervasive learning games  

Science Conference Proceedings (OSTI)

Engaging computer games can be used to change energy consumption patterns in the home. PowerAgent is a pervasive game for Java-enabled mobile phones that is designed to influence everyday activities and use of electricity in the domestic setting. PowerAgent ...

Magnus Bang; Anton Gustafsson; Cecilia Katzeff

2007-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Consumption patterns and household hazardous solid waste generation in an urban settlement in Mexico  

SciTech Connect

Mexico is currently facing a crisis in the waste management field. Some efforts have just commenced in urban and in rural settlements, e.g., conversion of open dumps into landfills, a relatively small composting culture, and implementation of source separation and plastic recycling strategies. Nonetheless, the high heterogeneity of components in the waste, many of these with hazardous properties, present the municipal collection services with serious problems, due to the risks to the health of the workers and to the impacts to the environment as a result of the inadequate disposition of these wastes. A generation study in the domestic sector was undertaken with the aim of finding out the composition and the generation rate of household hazardous waste (HHW) produced at residences. Simultaneously to the generation study, a socioeconomic survey was applied to determine the influence of income level on the production of HHW. Results from the solid waste generation analysis indicated that approximately 1.6% of the waste stream consists of HHW. Correspondingly, it was estimated that in Morelia, a total amount of 442 ton/day of domestic waste are produced, including 7.1 ton of HHW per day. Furthermore, the overall amount of HHW is not directly related to income level, although particular byproducts do correlate. However, an important difference was observed, as the brands and the presentation sizes of goods and products used in each socioeconomic stratum varied.

Delgado Otoniel, Buenrostro [Instituto De Investigaciones Agricolas y Forestales, Universidad Michoacana De San Nicolas De Hidalgo, Av. San Juanito Itzicuaro S/N, Col. San Juanito Itzicuaro, C.P. 58330, Morelia-Aeropuerto, Michoacan (Mexico)], E-mail: otonielb@zeus.umich.mx; Liliana, Marquez-Benavides; Gaona Francelia, Pinette [Instituto De Investigaciones Agricolas y Forestales, Universidad Michoacana De San Nicolas De Hidalgo, Av. San Juanito Itzicuaro S/N, Col. San Juanito Itzicuaro, C.P. 58330, Morelia-Aeropuerto, Michoacan (Mexico)

2008-07-01T23:59:59.000Z

82

EIA Average Energy Consumption 2005  

U.S. Energy Information Administration (EIA)

Table US8. Average Consumption by Fuels Used, 2005 Physical Units per Household Fuels Used (physical units of consumption per household using the fuel)

83

Household Vehicles Energy Consumption  

Reports and Publications (EIA)

This report provides newly available national and regional data and analyzes the nation's energy use by light-duty vehicles. This release represents the analytical component of the report, with a data component having been released in early 2005.

Mark Schipper

2005-11-30T23:59:59.000Z

84

Modelling household electricity consumption.  

E-Print Network (OSTI)

??A number of conclusions are drawn, however given the limited and non-representative na- ture of the data on which the model is calibrated, these can… (more)

de la Rue, Philip Martin

2010-01-01T23:59:59.000Z

85

Assumptions to the Annual Energy Outlook 2001 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Completed Copy in PDF Format Completed Copy in PDF Format Related Links Annual Energy Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Household Expenditures Module Key Assumptions The historical input data used to develop the HEM version for the AEO2001 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2001 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and

86

The 1997 Residential Energy Consumption Survey -- Two Decades  

U.S. Energy Information Administration (EIA)

1997 Residential Energy Consumption Survey presents two decades of changes in energy consumption related Household Characteristics

87

EIA - Household Transportation report: Household Vehicles Energy  

U.S. Energy Information Administration (EIA) Indexed Site

4 4 Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series. Based on the 1994 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use

88

Consumption  

E-Print Network (OSTI)

www.eia.gov Annual Energy Outlook 2013 projections to 2040 • Growth in energy production outstrips consumption growth • Crude oil production rises sharply over the next decade • Motor gasoline consumption reflects more stringent fuel economy standards • The U.S. becomes a net exporter of natural gas in the early 2020s • U.S. energy-related carbon dioxide emissions remain below their 2005 level through 2040

Adam Sieminski Administrator; Adam Sieminski; Adam Sieminski; Adam Sieminski; Adam Sieminski

2013-01-01T23:59:59.000Z

89

Assumptions to the Annual Energy Outlook - Household Expenditures Module  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module Assumption to the Annual Energy Outlook Household Expenditures Module Figure 5. United States Census Divisions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division (see

90

Energy Consumption, Efficiency, Conservation, and Greenhouse Gas Mitigation in Japan's Building Sector  

E-Print Network (OSTI)

comparison o f energy consumption i n housing (1998) (Trends i n household energy consumption (Jyukankyo Research4) Average (N=2976) Energy consumption [GJ / household-year

2006-01-01T23:59:59.000Z

91

Residential Energy Consumption Survey: Consumption and expenditures, April 1984 through March 1985: Part 1, National data  

Science Conference Proceedings (OSTI)

This report presents data collected in the 1984 Residential Energy Consumption Survey (RECS) conducted by the Energy Information Administration (EIA). The 1984 RECS was the sixth national survey of US households and their energy suppliers. The purpose of these surveys is to provide baseline information on how households use energy. Households in all types of housing units - single family homes (including townhouses), apartments, and mobile homes - were chosen to participate. Data from the surveys are available to the public in published reports such as this one and on public-use data tapes. The report presents data on the US consumption and expenditures for residential use of these ''major fuels'' - natural gas, electricity, fuel oil, kerosene, and liquefied petroleum gas (LPG) - from April 1984 through March 1985. These data are presented in tables in the Detailed Statistics section of this report. Except for kerosene and wood fuel, the consumption and expenditures data are based on actual household bills obtained, with the permission of the household, from the companies supplying energy to the household. Purchases of kerosene are based on respondent reports because records of ''cash and carry'' purchases of kerosene for individual households are usually unavailable. Data on the consumption of wood fuel (Table 27) covers the 12-month period ending November 1984 and are based on respondent recall of the amount of wood burned during the 12-month period. Both the kerosene and wood consumption data are subject to memory errors and other reporting errors. This report does not cover household use of motor fuel, which is reported separately.

Not Available

1987-03-04T23:59:59.000Z

92

Energy Spending and Vulnerable Households  

E-Print Network (OSTI)

 off than before. In particular large households with low  incomes seem to have been adversely affected by the new tariff structures since  they have comparably large energy expenditure (Bennet et al., 2002).    5. Vulnerable Households and Energy Spending  The...  tariffs can play an important part in the public debate  on  eradicating  fuel  poverty  and  helping  the  vulnerable  households.  Smart  metering  can  provide  consumers  with  information  on  the  actual  energy  consumption and might  lead  to...

Jamasb, Tooraj; Meier, Helena

2011-01-26T23:59:59.000Z

93

Residential Energy Usage by Origin of Householder  

U.S. Energy Information Administration (EIA)

Home > Energy Users > Residential Home Page > Energy Usage by Origin of Householder. Consumption and Expenditures. NOTE: To View and/or Print PDF's ...

94

Household Vehicles Energy Consumption 1991  

U.S. Energy Information Administration (EIA) Indexed Site

all comparisons reported in the text are statistically significant, based on a standard test made at the 0.05 significance level. No adjustments were made for simultaneous...

95

Table CE2-5.1u. Space-Heating Energy Consumption and Expenditures ...  

U.S. Energy Information Administration (EIA)

Space-Heating Energy Consumption and Expenditures by Household Member and Demographics, 2001 Household ... Total Households Using a Major Space-Heating

96

Household gasoline demand in the United States  

E-Print Network (OSTI)

Continuing rapid growth in U.S. gasoline consumption threatens to exacerbate environmental and congestion problems. We use flexible semiparametric and nonparametric methods to guide analysis of household gasoline consumption, ...

Schmalensee, Richard

1995-01-01T23:59:59.000Z

97

Residential energy consumption survey: housing characteristics 1984  

SciTech Connect

Data collected in the 1984 Residential Energy Consumption Survey (RECS), the sixth national survey of households and their fuel suppliers, provides baseline information on how households use energy. Households living in all types of housing units - single-family homes (including townhouses), apartments, and mobile homes - were chosen to participate. Data from the surveys are available to the public. The housing characteristics this report describes include fuels and the uses they are put to in the home; appliances; square footage of floorspace; heating (and cooling) equipment; thermal characteristics of housing structures; conservation features and measures taken; the consumption of wood; temperatures indoors; and regional weather. These data are tabulated in sets, first showing counts of households and then showing percentages. Results showed: Fewer households are changing their main heating fuel. More households are air conditioned than before. Some 50% of air-conditioned homes now use central systems. The three appliances considered essential are the refrigerator, the range, and the television set. At least 98% of US homes have at least one television set; but automatic dishwashers are still not prevalent. Few households use the budget plans tht are available from their utility companies to ease the payment burden of seasonal surges in fuel bills. The most common type of heating equipment in the United States is the natural-gas forced-air furnace. About 40% ofthose furnaces are at least 15 years old. The oldest water heaters are those that use fuel oil. The most common conservation feature in 1984 is ceiling or attic insulation - 80% of homes report having this item. Relatively few households claimed tax credits in 1984 for energy-conservation improvements.

Not Available

1986-10-08T23:59:59.000Z

98

Residential Energy Consumption Survey Data Tables  

U.S. Energy Information Administration (EIA)

Below are historical data tables from the Residential Energy Consumption Survey (RECS). These tables cover the total number of households ...

99

Whole-house measurements of standby power consumption  

E-Print Network (OSTI)

Whole-House Measurements of Standby Power Consumption" InStudy on Miscellaneous Standby Consumption of HouseholdA. , Murakoshi, C. 1997. Standby Electricity Consumption in

Ross, J.P.; Meier, Alan

2000-01-01T23:59:59.000Z

100

Residential Energy Consumption Survey (RECS) - Analysis ...  

U.S. Energy Information Administration (EIA)

RECS data show decreased energy consumption per household. RECS 2009 — Release date: June 6, 2012. Total United States energy consumption in homes has remained ...

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

The impact of rising energy prices on household energy consumption and expenditure patterns: The Persian Gulf crisis as a case example  

SciTech Connect

The Iraqi invasion of Kuwait and the subsequent war between Iraq and an international alliance led by the United States triggered immediate increases in world oil prices. Increases in world petroleum prices and in US petroleum imports resulted in higher petroleum prices for US customers. In this report, the effects of the Persian Gulf War and its aftermath are used to demonstrate the potential impacts of petroleum price changes on majority, black, and Hispanic households, as well as on poor and nonpoor households. The analysis is done by using the Minority Energy Assessment Model developed by Argonne National Laboratory for the US Department of Energy (DOE). The differential impacts of these price increases and fluctuations on poor and minority households raise significant issues for a variety of government agencies, including DOE. Although the Persian Gulf crisis is now over and world oil prices have returned to their prewar levels, the differential impacts of rising energy prices on poor and minority households as a result of any future crisis in the world oil market remains a significant long-term issue.

Henderson, L.J. (Baltimore Univ., MD (United States)); Poyer, D.A.; Teotia, A.P.S. (Argonne National Lab., IL (United States). Energy Systems Div.)

1992-09-01T23:59:59.000Z

102

Figure 2. Energy Consumption of Vehicles, Selected Survey Years  

U.S. Energy Information Administration (EIA) Indexed Site

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure 2 Figure 2. Energy Consumption of Vehicles, Selected Survey Years...

103

Tanzania Roads Evaluation - Baseline | Data.gov  

NLE Websites -- All DOE Office Websites (Extended Search)

Tanzania Roads Evaluation - Baseline Tanzania Roads Evaluation - Baseline Agriculture Community Menu DATA APPS EVENTS DEVELOPER STATISTICS COLLABORATE ABOUT Agriculture You are here Data.gov » Communities » Agriculture » Data Tanzania Roads Evaluation - Baseline Dataset Summary Description Baseline survey for impact evaluation of MCC's roads improvement investments in Tanzania. The evaluation will examine the project's household- and community-level effects on local standards of living along the roads. For the evaluation of major roads on the mainland, Economic Development Initiatives conducted a survey of 3,000 households in 200 communities in 2009. For the Pemba rural roads evaluation, Economic Development Initiatives conducted a survey on 570 households in the treatment group and 630 households in the comparison group.

104

Development of the Household Sample for Furnace and Boiler Life...  

NLE Websites -- All DOE Office Websites (Extended Search)

households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler...

105

The Other Energy Crisis: Managing Urban Household Energy Use in Senegal  

E-Print Network (OSTI)

for 62 percent of national energy consumption, or over 1 .1energy consumption, and (2) residential, because of the dominant role that households play in national

Leitmann, Josef

1989-01-01T23:59:59.000Z

106

Table WH2. Total Households by Water Heating Fuels Used, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households by Water Heating Fuels Used, 2005 ... 2005 Residential Energy Consumption Survey: Energy Consumption and Expenditures Tables. Table WH2.

107

Answers to Frequently Asked Questions About the Household Bottled ...  

U.S. Energy Information Administration (EIA)

Form EIA-457D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey

108

Table 1. Household Characteristics by Ceiling Fans, 2001  

U.S. Energy Information Administration (EIA)

A reporting of the number of housing units using ceiling fans in U.S. households as reported in the 2001 Residential Energy Consumption Survey

109

Answers to Frequently Asked Questions About the Household ...  

U.S. Energy Information Administration (EIA)

Form EIA-457E (2001) – Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey

110

Microsoft Word - Household Energy Use CA  

U.S. Energy Information Administration (EIA) Indexed Site

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

111

Microsoft Word - Household Energy Use CA  

Gasoline and Diesel Fuel Update (EIA)

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

112

Do Disaster Expectations Explain Household Portfolios?  

E-Print Network (OSTI)

use the American Consumer Expenditure Survey (CEX) for consumption ex- penditure information. The data covers the period between 1983 and 2004. The expenditure information is recorded quarterly with approximately 5000 households in each wave. Every...

Alan, Sule

113

EIA - Household Transportation report: Household Vehicles ...  

U.S. Energy Information Administration (EIA)

This report, Household Vehicles Energy Use: Latest Data & Trends, provides details on the nation's energy use for household passenger travel. A primary purpose of ...

114

Residential Energy Consumption for Water Heating (2005) Provides...  

Open Energy Info (EERE)

Residential Energy Consumption for Water Heating (2005) Provides total and average annual residential energy consumption for water heating in U.S. households in 2005, measured in...

115

Form EIA-457E (2001) -- Household Bottled Gas Usage  

U.S. Energy Information Administration (EIA) Indexed Site

F (2001) -- Household Natural Gas Usage Form F (2001) -- Household Natural Gas Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Natural Gas Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

116

Form EIA-457E (2001) -- Household Bottled Gas Usage  

U.S. Energy Information Administration (EIA) Indexed Site

E (2001) - Household Electricity Usage Form E (2001) - Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Electricity Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

117

THE DEVELOPMENT OF A 1990 INDUSTRIAL ENERGY USE BASELINE  

E-Print Network (OSTI)

to determine total energy consumption for that industry. However, if specific energy intensities per unit consumption, and emissions generated by energy consumption, a comprehensive, baseline data set of industrial branches of Canadian industry, forms the goal of this report. An adequate baseline energy consumption

118

Table AP5. Average Consumption for Home Appliances and Lighting by ...  

U.S. Energy Information Administration (EIA)

Table AP5. Average Consumption for Home Appliances and Lighting by Fuels Used, 2005 Physical Units per Household U.S. Households (millions) Fuels Used

119

Table CE5-5.1u. Appliances Energy Consumption and Expenditures by ...  

U.S. Energy Information Administration (EIA)

Table CE5-5.1u. Appliances1 Energy Consumption and Expenditures by Household Member and Demographics, 2001 Household Demographics RSE Column Factor:

120

Factors influencing county level household fuelwood use  

Science Conference Proceedings (OSTI)

This study explains household fuelwood consumption behavior at the county level by linking it to economic and demographic conditions in counties. Using this link, counties are identified where potential fuelwood use problems and benefits are greatest. A probit equation estimates household probability of wood use (percent woodburners in a county heating degree days, household income, nonwood fuel price, fuelwood price, percent forest land, population density, and fraction of households using various types of heating equipment. A linear-in-parameters equation estimates average wood consumed by a woodburner based on county heating degree days, household income, percent forest land, and price of nonwood fuel divided by fuelwood price. Parameters are estimated using fuelwood use data for individual households from a 1908-81 nationwide survey. The probit equation predicts percentage of wood burns well over a wide range of county conditions. The wood consumption equation overpredicts for counties with high income and high population density (over 6000 persons per square mile). The model shows average woodburning per household over all households decreases with increasing population density, and the influence of county economic characteristics varies with density.

Skog, K.E.

1986-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

US SoAtl GA Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

GA GA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl GA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl GA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl GA Expenditures dollars ELECTRICITY ONLY average per household * Site energy consumption (89.5 million Btu) and energy expenditures per household ($2,067) in Georgia are similar to the U.S. household averages. * Per household electricity consumption in Georgia is among the highest in the country, but similar to other states in the South. * Forty-five percent of homes in Georgia were built since 1990, a characteristic typically associated with lower per household consumption. Georgia homes,

122

US SoAtl GA Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

GA GA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl GA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl GA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl GA Expenditures dollars ELECTRICITY ONLY average per household * Site energy consumption (89.5 million Btu) and energy expenditures per household ($2,067) in Georgia are similar to the U.S. household averages. * Per household electricity consumption in Georgia is among the highest in the country, but similar to other states in the South. * Forty-five percent of homes in Georgia were built since 1990, a characteristic typically associated with lower per household consumption. Georgia homes,

123

Energy and household expenditure patterns  

Science Conference Proceedings (OSTI)

Since households account, either directly or indirectly, for two-thirds of the energy consumed in the US, changes in household activities will affect energy use. Expected changes in prices, personal income, and family spending over the next 20 years are looked at as well as the implications for energy consumption. The analysis shows that direct energy purchases will break with past trends, dropping from 2.6% to 0.2% annual growth for the rest of the century. Growth in spending on energy-using goods is also likely to slow down. The year 2000 will see a marked decrease in the growth of national energy consumption. 58 references, 3 figures, 35 tables.

Lareau, T.J.; Darmstadter, J.

1983-01-01T23:59:59.000Z

124

US ENC IL Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

IL IL Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC IL Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC IL Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC IL Expenditures dollars ELECTRICITY ONLY average per household * Illinois households use 129 million Btu of energy per home, 44% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Illinois households spending 2% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

125

US ENC MI Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

MI MI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC MI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC MI Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC MI Expenditures dollars ELECTRICITY ONLY average per household * Michigan households use 123 million Btu of energy per home, 38% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Michigan households spending 6% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

126

US ENC MI Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

MI MI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC MI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC MI Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC MI Expenditures dollars ELECTRICITY ONLY average per household * Michigan households use 123 million Btu of energy per home, 38% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Michigan households spending 6% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

127

US ENC IL Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

IL IL Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC IL Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC IL Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC IL Expenditures dollars ELECTRICITY ONLY average per household * Illinois households use 129 million Btu of energy per home, 44% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Illinois households spending 2% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

128

Energy Consumption, Efficiency, Conservation, and Greenhouse Gas Mitigation in Japan's Building Sector  

E-Print Network (OSTI)

2004, "Household Energy Consumption Reported o n A National2006, "Household Energy consumption Reported i n a Nationalconsumption for different uses i n housing and energy usage analysis based on national

2006-01-01T23:59:59.000Z

129

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

Household Tables Household Tables (Million U.S. Households; 24 pages, 122 kb) Contents Pages HC2-1a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 2 HC2-2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 2 HC2-3a. Household Characteristics by Household Income, Million U.S. Households, 2001 2 HC2-4a. Household Characteristics by Type of Housing Unit, Million U.S. Households, 2001 2 HC2-5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2 HC2-6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 2 HC2-7a. Household Characteristics by Four Most Populated States, Million U.S. Households, 2001 2

130

Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China  

E-Print Network (OSTI)

appliance, lighting, and heating and cooling usage in theseusage in rural households. Primary Energy Consumption (EJ) Appliance Cooking lighting

Zhou, Nan

2010-01-01T23:59:59.000Z

131

char_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

9a. Household Characteristics by Northeast Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row...

132

Household Vehicles Energy Use: Latest Data and Trends - Table A01  

U.S. Energy Information Administration (EIA)

Table A1. U.S. Number of Vehicles, Vehicles-Miles, Motor Fuel Consumption and Expenditures, 2001: 2001 Household and Vehicle Characteristics

133

Table AP1. Total Households Using Home Appliances and Lighting by ...  

U.S. Energy Information Administration (EIA)

Total Consumption for Home Appliances and Lighting by Fuels Used, 2005 Quadrillion British Thermal Units (Btu) U.S. Households (millions) Electricity

134

Table SH2. Total Households by Space Heating Fuels Used, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households by Space Heating Fuels Used, 2005 ... 2005 Residential Energy Consumption Survey: ... Electricity Natural Gas Fuel Oil Kerosene LPG Other

135

US WSC TX Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

WSC TX WSC TX Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US WSC TX Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US WSC TX Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US WSC TX Expenditures dollars ELECTRICITY ONLY average per household * Texas households consume an average of 77 million Btu per year, about 14% less than the U.S. average. * Average electricity consumption per Texas home is 26% higher than the national average, but similar to the amount used in neighboring states. * The average annual electricity cost per Texas household is $1,801, among the highest in the nation, although similar to other warm weather states like Florida. * Texas homes are typically newer, yet smaller in size, than homes in other parts of

136

US WSC TX Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

WSC TX WSC TX Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US WSC TX Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US WSC TX Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US WSC TX Expenditures dollars ELECTRICITY ONLY average per household * Texas households consume an average of 77 million Btu per year, about 14% less than the U.S. average. * Average electricity consumption per Texas home is 26% higher than the national average, but similar to the amount used in neighboring states. * The average annual electricity cost per Texas household is $1,801, among the highest in the nation, although similar to other warm weather states like Florida. * Texas homes are typically newer, yet smaller in size, than homes in other parts of

137

US ENC WI Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

120 120 US ENC WI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC WI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC WI Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 US ENC WI Expenditures dollars ELECTRICITY ONLY average per household * Wisconsin households use 103 million Btu of energy per home, 15% more than the U.S. average. * Lower electricity and natural gas rates compared to states with a similar climate, such as New York, result in households spending 5% less for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S.

138

US ENC WI Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

120 120 US ENC WI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC WI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC WI Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 US ENC WI Expenditures dollars ELECTRICITY ONLY average per household * Wisconsin households use 103 million Btu of energy per home, 15% more than the U.S. average. * Lower electricity and natural gas rates compared to states with a similar climate, such as New York, result in households spending 5% less for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S.

139

US ESC TN Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

ESC TN ESC TN Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ESC TN Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US ESC TN Site Consumption kilowatthours $0 $400 $800 $1,200 $1,600 US ESC TN Expenditures dollars ELECTRICITY ONLY average per household * Tennessee households consume an average of 79 million Btu per year, about 12% less than the U.S. average. * Average electricity consumption for Tennessee households is 33% higher than the national average and among the highest in the nation, but spending for electricity is closer to average due to relatively low electricity prices. * Tennessee homes are typically newer, yet smaller in size, than homes in other parts of the country.

140

Profiling energy use in households and office spaces  

Science Conference Proceedings (OSTI)

Energy consumption is largely studied in the context of different environments, such as domestic, corporate, industrial, and public sectors. In this paper, we discuss two environments, households and office spaces, where people have an especially ...

Salman Taherian; Marcelo Pias; George Coulouris; Jon Crowcroft

2010-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

SciTech Connect

The term ?household carbon footprint? refers to the total annual carbon emissions associated with household consumption of energy, goods, and services. In this project, Lawrence Berkeley National Laboratory developed a carbon footprint modeling framework that characterizes the key underlying technologies and processes that contribute to household carbon footprints in California and the United States. The approach breaks down the carbon footprint by 35 different household fuel end uses and 32 different supply chain fuel end uses. This level of end use detail allows energy and policy analysts to better understand the underlying technologies and processes contributing to the carbon footprint of California households. The modeling framework was applied to estimate the annual home energy and supply chain carbon footprints of a prototypical California household. A preliminary assessment of parameter uncertainty associated with key model input data was also conducted. To illustrate the policy-relevance of this modeling framework, a case study was conducted that analyzed the achievable carbon footprint reductions associated with the adoption of energy efficient household and supply chain technologies.

Kramer, Klaas Jan; Homan, Greg; Brown, Rich; Worrell, Ernst; Masanet, Eric

2009-04-15T23:59:59.000Z

142

Residential Energy Consumption Survey Results: Total Energy Consumption,  

Open Energy Info (EERE)

Survey Results: Total Energy Consumption, Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005) Dataset Summary Description The Residential Energy Consumption Survey (RECS) is a national survey that collects residential energy-related data. The 2005 survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the U.S. Data were obtained from residential energy suppliers for each unit in the sample to produce the Consumption & Expenditures data. The Consumption & Expenditures and Intensities data is divided into two parts: Part 1 provides energy consumption and expenditures by census region, population density, climate zone, type of housing unit, year of construction and ownership status; Part 2 provides the same data according to household size, income category, race and age. The next update to the RECS survey (2009 data) will be available in 2011.

143

Residential Energy Consumption - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

The Residential Energy Consumption Survey provides national and regional information about U.S. households and their energy usage. The first survey was conducted in 1978.

144

Number, Energy Consumption, and Energy-Related Carbon ...  

U.S. Energy Information Administration (EIA)

Tabulation of changes in the number, energy consumption, and energy-related carbon emissions of U.S. households, 1980-1997.

145

2001 Consumption and Expenditures -- Electric Air-Conditioning ...  

U.S. Energy Information Administration (EIA)

CE3-1c. Electric Air-Conditioning Energy Consumption in U.S. Households by Climate Zone, 2001 : 2: CE3-2c. ...

146

Table US1. Total Energy Consumption, Expenditures, and Intensities ...  

U.S. Energy Information Administration (EIA)

Part 1: Housing Unit Characteristics and Energy Usage Indicators Energy Consumption 2 Energy Expenditures 2 Total U.S. (quadrillion Btu) Per Household (Dollars) Per

147

2003 Commercial Buildings Energy Consumption - What is an RSE  

U.S. Energy Information Administration (EIA) Indexed Site

Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > 2003 Detailed Tables > What is an RSE? What is an RSE? The estimates in the...

148

EIA - Gasoline and Diesel Fuel report: Household Vehicles Energy  

U.S. Energy Information Administration (EIA) Indexed Site

1 1 Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued after EIA's 1994 survey. Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. This report, Household Vehicles Energy Consumption 1991, is based on data from the 1991 Residential Transportation Energy Consumption Survey (RTECS). Focusing on vehicle miles traveled (VMT) and energy enduse consumption and expenditures by households for personal transportation, the 1991 RTECS is

149

US WNC MO Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

WNC MO WNC MO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US WNC MO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 3,000 6,000 9,000 12,000 15,000 US WNC MO Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 US WNC MO Expenditures dollars ELECTRICITY ONLY average per household * Missouri households consume an average of 100 million Btu per year, 12% more than the U.S. average. * Average household energy costs in Missouri are slightly less than the national average, primarily due to historically lower residential electricity prices in the state. * Missouri homes are typically larger than homes in other states and are more likely to be attached or detached single-family housing units.

150

US Mnt(N) CO Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

Mnt(N) CO Mnt(N) CO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(N) CO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US Mnt(N) CO Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US Mnt(N) CO Expenditures dollars ELECTRICITY ONLY average per household * Colorado households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Average household energy costs in Colorado are 23% less than the national average, primarily due to historically lower natural gas prices in the state. * Average electricity consumption per household is lower than most other states, as Colorado residents do not commonly use electricity for main space heating, air

151

US Mnt(N) CO Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

Mnt(N) CO Mnt(N) CO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(N) CO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US Mnt(N) CO Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US Mnt(N) CO Expenditures dollars ELECTRICITY ONLY average per household * Colorado households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Average household energy costs in Colorado are 23% less than the national average, primarily due to historically lower natural gas prices in the state. * Average electricity consumption per household is lower than most other states, as Colorado residents do not commonly use electricity for main space heating, air

152

Householder’s Perceptions of Insulation Adequacy and Drafts in the Home in 2001  

E-Print Network (OSTI)

In order to improve the estimation of end-use heating consumption, the Energy Information Administration's (EIA), 2001 Residential Energy Consumption Survey (RECS), for the first time, asked respondents to judge how drafty they perceived their homes to be as a measure of insulation quality. The analysis of the 2001 RECS data shows that householders in newlyconstructed homes perceived their homes to be better insulated and less drafty than do householders in older homes. Single-family homes are perceived to be better insulated and less drafty than are apartments in buildings with two to four units. Cross-variable comparisons also provide the associations between the level of insulation and winter drafts in the homes with household characteristics and location of the home.

Behjat Hojjati

2004-01-01T23:59:59.000Z

153

Car Sharing within Households  

E-Print Network (OSTI)

The objective of this paper was to analyse two activities: who rents a car and why? Which households share the driving of their cars? In order to do that, the Parc-Auto (Car-Fleet) database, built from annual postal surveys conducted with a panel of 10,000 French households, has been processed. Among approximately one hundred questions in the survey, two key questions have been crossed against many social, economic, demographic, geographic or time variables. KQ1: “During the last 12 months, did you — or another person from your home — rent a car in France for personal purposes? ” KQ2: “Is this car occasionally used by other persons?” Here are the main findings. Renting households are mainly working, high income households, living in the core of big cities, and in particular in Paris. Most of them have two wage-sheets and two cars, one of which is generally a recent, high power, high quality car. Car rental is mainly an occasional practice. Yet for a minority of renters, it is a sustained habit. Households with more licence holders than cars share the most: about three quarters of them share their cars. On the contrary, single driver-single car households have less opportunity to share: only 15 % share. Household car sharing shed light on the gender role within households: while 58 % of the main users of the shared cars are male, 55 % of secondary users are female. Household car sharing is mainly a regular practice. Finally, without diminishing the merits of innovative transport solutions proposed here and there, it is not a waste of time to give some insight on self established behaviour within households. This reveals that complex patterns have been built over time by the people themselves, to cope with diverse situations that cannot be easily handled by straightforward classifications. The car cannot be reduced to a personal object. Household car sharing also carries strong links with the issue of car dependency. Sifting car availability and choice

Francis Papon; Laurent Hivert

2008-01-01T23:59:59.000Z

154

PRELIMINARY DATA Housing Unit and Household Characteristics  

U.S. Energy Information Administration (EIA) Indexed Site

PRELIMINARY DATA Housing Unit and Household Characteristics RSE Column Factor: Total Households (million) Households With Fans (million) Percent of Households With Fans Number of...

155

Econometric analysis of energy use in urban households  

SciTech Connect

This article analyzes the pattern of energy carrier consumption in the residential sector of Bangalore, a major city in south India. A 1,000-household survey was used to study the type of energy carrier used by households in different income groups for different end-uses, such as cooking, water heating, and lighting. The dependence of income on the carrier utilized is established using a carrier dependence index. Using regression analysis, the index analyses the impact of different explanatory variables such as family income, family size, and price of energy carrier on consumption. The results show that income plays an important role not only in the selection of an energy carrier but also on the quantity of consumption per household. Also, a source-service matrix is prepared for Bangalore`s residential sector, which shows the disaggregation of energy consumption by the type of energy carrier and end-use.

Reddy, B.S. [Indira Gandhi Inst. of Development Research, Bombay (India)

1995-05-01T23:59:59.000Z

156

US SoAtl VA Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

SoAtl VA SoAtl VA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl VA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl VA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl VA Expenditures dollars ELECTRICITY ONLY average per household * Virginia households consume an average of 86 million Btu per year, about 4% less than the U.S. average. * Average electricity consumption and costs are higher for Virginia households than the national average, but similar to those in neighboring states where electricity is the most common heating fuel. * Virginia homes are typically newer and larger than homes in other parts of the country. CONSUMPTION BY END USE

157

US SoAtl VA Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

SoAtl VA SoAtl VA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl VA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl VA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl VA Expenditures dollars ELECTRICITY ONLY average per household * Virginia households consume an average of 86 million Btu per year, about 4% less than the U.S. average. * Average electricity consumption and costs are higher for Virginia households than the national average, but similar to those in neighboring states where electricity is the most common heating fuel. * Virginia homes are typically newer and larger than homes in other parts of the country. CONSUMPTION BY END USE

158

US Mnt(S) AZ Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

Mnt(S) AZ Mnt(S) AZ Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(S) AZ Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 3,000 6,000 9,000 12,000 15,000 US Mnt(S) AZ Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US Mnt(S) AZ Expenditures dollars ELECTRICITY ONLY average per household * Arizona households use 66 million Btu of energy per home, 26% less than the U.S. average. * The combination of lower than average site consumption of all energy, but above average electricity which is relatively expensive, results in Arizona households spending 3% less for energy than the U.S. average. * More reliance on air conditioning keeps average site electricity consumption in the state high relative to other parts of the U.S.

159

US MidAtl NJ Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

in New Jersey homes is for space heating. Air conditioning accounts for a larger share of household consumption than other Northeast states, but still only accounts for 3% of the...

160

US MidAtl NJ Site Consumption  

Annual Energy Outlook 2012 (EIA)

than the average U.S. household. * New Jersey homes are 20% larger than the average U.S. home. CONSUMPTION BY END USE Nearly half the energy consumed in New Jersey homes is for...

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

US Mnt(S) AZ Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

Mnt(S) AZ Mnt(S) AZ Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(S) AZ Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 3,000 6,000 9,000 12,000 15,000 US Mnt(S) AZ Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US Mnt(S) AZ Expenditures dollars ELECTRICITY ONLY average per household * Arizona households use 66 million Btu of energy per home, 26% less than the U.S. average. * The combination of lower than average site consumption of all energy, but above average electricity which is relatively expensive, results in Arizona households spending 3% less for energy than the U.S. average. * More reliance on air conditioning keeps average site electricity consumption in the state high relative to other parts of the U.S.

162

Consumption & Efficiency - Data - U.S. Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Consumption & Efficiency Consumption & Efficiency Glossary › FAQS › Overview Data Residential Energy Consumption Survey Data Commercial Energy Consumption Survey Data Manufacturing Energy Consumption Survey Data Vehicle Energy Consumption Survey Data Energy Intensity Consumption Summaries Average cost of fossil-fuels for electricity generation All Consumption & Efficiency Data Reports Analysis & Projections All Sectors Commercial Buildings Efficiency Manufacturing Projections Residential Transportation All Reports Find statistics on energy consumption and efficiency across all fuel sources. + EXPAND ALL Residential Energy Consumption Survey Data Household characteristics Release Date: March 28, 2011 Survey data for occupied primary housing units. Residential Energy Consumption Survey (RECS)

163

2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions  

U.S. Energy Information Administration (EIA) Indexed Site

D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Bottled Gas (LPG or Propane) Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

164

A Framework for Corporate Householding  

E-Print Network (OSTI)

Previous research on corporate household and corporate householding has presented examples, literature review, and working definitions. In this paper, we first improve our ...

Madnick, Stuart

2003-03-21T23:59:59.000Z

165

Baseline data for the residential sector and development of a residential forecasting database  

SciTech Connect

This report describes the Lawrence Berkeley Laboratory (LBL) residential forecasting database. It provides a description of the methodology used to develop the database and describes the data used for heating and cooling end-uses as well as for typical household appliances. This report provides information on end-use unit energy consumption (UEC) values of appliances and equipment historical and current appliance and equipment market shares, appliance and equipment efficiency and sales trends, cost vs efficiency data for appliances and equipment, product lifetime estimates, thermal shell characteristics of buildings, heating and cooling loads, shell measure cost data for new and retrofit buildings, baseline housing stocks, forecasts of housing starts, and forecasts of energy prices and other economic drivers. Model inputs and outputs, as well as all other information in the database, are fully documented with the source and an explanation of how they were derived.

Hanford, J.W.; Koomey, J.G.; Stewart, L.E.; Lecar, M.E.; Brown, R.E.; Johnson, F.X.; Hwang, R.J.; Price, L.K.

1994-05-01T23:59:59.000Z

166

Residential energy-consumption survey: consumption and expenditures, April 1978-March 1979  

SciTech Connect

Tables present data on energy consumption and expenditures for US households during a 12-month period. The total amount of energy consumed by the residential sector from April 1978 through March 1979 is estimated to have been 10,563 trillion Btu with an average household consumption of 138 million Btu. Table 1 summarizes residential energy consumption for all fuels (totals and averages) as wells as total amounts consumed and expenditures for each of the major fuel types (natural gas, electricity, fuel oil, and liquid petroleum gas). Tables 2 and 3 give the number of households and the average energy prices, respectively, for each of the major fuel types. In Tables 4 to 9, totals and averages for both consumption and expenditures are given for each of the major fuels. The consumption of each fuel is given first for all households using the fuel. Then, households are divided into those that use the fuel as their main source of heat and those using the fuel for other purposes. Electricity data (Tables 5 to 7) are further broken down into households that use electricity for air conditioning and those not using it for this purpose. Limited data are also presented on households that use each of the major fuels for heating water. Each of the consumption tables is given for a variety of general household features, including: geographical, structural and physical, and demographic characteristics. Tables 10 to 18 present the same information for the subgroup of households living in single-family owner-occupied detached houses. The third set of tables (19 to 27) is limited to households that paid directly for all of the energy they used. Tables 28 to 36 provide variance estimates for the data.

Not Available

1980-07-01T23:59:59.000Z

167

US NE MA Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

NE MA NE MA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US NE MA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US NE MA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US NE MA Expenditures dollars ELECTRICITY ONLY average per household * Massachusetts households use 109 million Btu of energy per home, 22% more than the U.S. average. * The higher than average site consumption results in households spending 22% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S. However, spending on electricity is closer to the national average due to higher

168

US NE MA Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

NE MA NE MA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US NE MA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US NE MA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US NE MA Expenditures dollars ELECTRICITY ONLY average per household * Massachusetts households use 109 million Btu of energy per home, 22% more than the U.S. average. * The higher than average site consumption results in households spending 22% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S. However, spending on electricity is closer to the national average due to higher

169

Racial and demographic differences in household travel and fuel purchase behavior  

Science Conference Proceedings (OSTI)

Monthly fuel purchase logs from the Residential Energy Consumption Survey's Household Transportation Panel (TP) were analyzed to determine the relationship between various household characteristics and purchase frequency, tank inventories, vehicle-miles traveled, and fuel expenditures. Multiple classification analysis (MCA) was used to relate observed differences in dependent variables to such index-type household characteristics as income and residence location, and sex, race and age of household head. Because it isolates the net effect of each parameter, after accounting for the effects of all other parameters, MCA is particularly appropriate for this type of analysis. Results reveal clear differences in travel and fuel purchase behavior for four distinct groups of vehicle-owning households. Black households tend to own far fewer vehicles with lower fuel economy, to use them more intensively, to purchase fuel more frequently, and to maintain lower fuel inventories than white households. Similarly, poor households own fewer vehicles with lower fuel economy, but they drive them less intensively, purchase fuel more frequently, and maintain lower fuel inventories than nonpoor households. Elderly households also own fewer vehicles with lower fuel economy. But since they drive them much less intensively, their fuel purchases are much less frequent and their fuel inventories are higher than nonelderly households. Female-headed households also own fewer vehicles but with somewhat higher fuel economy. They drive them less intensively, maintain higher fuel inventories, and purchase fuel less frequently than male-headed households. 13 refs., 8 tabs.

Gur, Y.; Millar, M.

1987-01-01T23:59:59.000Z

170

housingunit_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

Housing Unit Tables Housing Unit Tables (Million U.S. Households; 49 pages, 210 kb) Contents Pages HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 5 HC1-2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 2001 4 HC1-3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 4 HC1-4a. Housing Unit Characteristics by Type of Housing Unit, Million U.S. Households, 2001 4 HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 4 HC1-6a. Housing Unit Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 4 HC1-7a. Housing Unit Characteristics by Four Most Populated States, Million U.S. Households, 2001 4

171

usage_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

Usage Indicators Tables Usage Indicators Tables (Million U.S. Households; 60 pages, 247 kb) Contents Pages HC6-1a. Usage Indicators by Climate Zone, Million U.S. Households, 2001 5 HC6-2a. Usage Indicators by Year of Construction, Million U.S. Households, 2001 5 HC6-3a. Usage Indicators by Household Income, Million U.S. Households, 2001 5 HC6-4a. Usage Indicators by Type of Housing Unit, Million U.S. Households, 2001 5 HC6-5a. Usage Indicators by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 5 HC6-6a. Usage Indicators by Type of Rented Housing Unit, Million U.S. Households, 2001 5 HC6-7a. Usage Indicators by Four Most Populated States, Million U.S. Households, 2001 5

172

homeoffice_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

Home Office Equipment Tables Home Office Equipment Tables (Million U.S. Households; 12 pages, 123 kb) Contents Pages HC7-1a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 1 HC7-2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 1 HC7-3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 1 HC7-4a. Home Office Equipment by Type of Housing Unit, Million U.S. Households, 2001 1 HC7-5a. Home Office Equipment by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 1 HC7-6a. Home Office Equipment by Type of Rented Housing Unit, Million U.S. Households, 2001 1 HC7-7a. Home Office Equipment by Four Most Populated States, Million U.S. Households, 2001 1

173

The household energy transition in India and China Shonali Pachauri a,, Leiwen Jiang b  

E-Print Network (OSTI)

household surveys. The two countries differ sharply in several respects. Residential energy consumption of national primary energy consumption statistics shows clearly that both India and China are countries energy consumption remains low in both countries, particularly in India. Average energy use is low

174

Model documentation: household model of energy  

Science Conference Proceedings (OSTI)

The Household Model of Energy is an econometric model, meaning that energy use is determined quantitatively with the use of economic variables such as fuel prices and income. HOME is also primarily a structural model, meaning that energy use is determined as the result of interactions of intermediate components such as the number of households, the end use fuel shares and the energy use per household. HOME forecasts energy consumption in all occupied residential structures (households) in the United States on an annual basis through 1990. The forecasts are made based upon a number of initial conditions in 1980, various estimated elasticities, various parameters and assumptions, and a set of forecasted fuel prices and income. In addition to the structural detail, HOME operates on a more disaggregated level. This includes four end-use services (space heating, water heating, air conditioning, and others), up to seven fuel/technology types (dependent upon the end use service), two housing types, four structure vintages, and four Census regions. When the model is run as a module in IFFS, a sharing scheme further disaggregates the model to 10 Federal regions.

Holte, J.A.

1984-02-01T23:59:59.000Z

175

Residential Energy Consumption Survey: Quality Profile  

SciTech Connect

The Residential Energy Consumption Survey (RECS) is a periodic national survey that provides timely information about energy consumption and expenditures of U.S. households and about energy-related characteristics of housing units. The survey was first conducted in 1978 as the National Interim Energy Consumption Survey (NIECS), and the 1979 survey was called the Household Screener Survey. From 1980 through 1982 RECS was conducted annually. The next RECS was fielded in 1984, and since then, the survey has been undertaken at 3-year intervals. The most recent RECS was conducted in 1993.

NONE

1996-03-01T23:59:59.000Z

176

Household Vehicles Energy Use Cover Page  

U.S. Energy Information Administration (EIA) Indexed Site

Household Vehicles Energy Use Cover Page Glossary Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use Cover Page Contact Us * Feedback *...

177

Table CE3-6.1u. Electric Air-Conditioning Energy Consumption and ...  

U.S. Energy Information Administration (EIA)

Table CE3-6.1u. Electric Air-Conditioning Energy Consumption and Expenditures by Household Member and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

178

Table AC6. Average Consumption for Air-Conditioning by Equipment ...  

U.S. Energy Information Administration (EIA)

Central System 5 Table AC6. Average Consumption for Air-Conditioning by Equipment Type, 2005 Million British Thermal Units (Btu) per Household

179

Table CE4-6.1u. Water-Heating Energy Consumption and Expenditures ...  

U.S. Energy Information Administration (EIA)

Table CE4-6.1u. Water-Heating Energy Consumption and Expenditures by Household Member and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

180

Table WH10. Consumption Intensity by Main Water Heating Fuel Used ...  

U.S. Energy Information Administration (EIA)

Main Water Heating Fuel Used (physical units/number of household members) Electricity Table WH10. Consumption Intensity by Main Water Heating Fuel Used, 2005

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Table AP2. Total Consumption for Home Appliances and Lighting by ...  

U.S. Energy Information Administration (EIA)

Total Consumption for Home Appliances and Lighting by Fuels Used, 2005 Physical Units U.S. Households (millions) Fuels Used (physical units) Electricity (billion kWh)

182

Table SH7. Average Consumption for Space Heating by Main Space ...  

U.S. Energy Information Administration (EIA)

Fuel Oil (gallons) Main Space Heating Fuel Used (physical units of consumption per household using the fuel as a main heating source) Table SH7.

183

Table SH8. Average Consumption for Space Heating by Main Space ...  

U.S. Energy Information Administration (EIA)

Fuel Oil Main Space Heating Fuel Used (million Btu of consumption per household using the fuel as a main heating source) Any Major Fuel 4 Table SH8.

184

Table CE5-6.1u. Appliances Energy Consumption and Expenditures by ...  

U.S. Energy Information Administration (EIA)

Table CE5-6.1u. Appliances1 Energy Consumption and Expenditures by Household Member and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

185

Modelling the Energy Demand of Households in a Combined  

E-Print Network (OSTI)

. Emissions from passenger transport, households'electricity and heat consumption are growing rapidly despite demand analysis for electricity (e.g. Larsen and Nesbakken, 2004; Holtedahl and Joutz, 2004; Hondroyiannis, 2004) and passenger cars (Meyer et al., 2007). Some recent studies cover the whole residential

Steininger, Karl W.

186

Household Hazardous Waste Household hazardous waste is the discarded, unused, or leftover portion of household products  

E-Print Network (OSTI)

Household Hazardous Waste Household hazardous waste is the discarded, unused, or leftover portion of household products containing toxic chemicals. These wastes CANNOT be disposed of in regular garbage. Any should be considered hazardous. You cannot treat hazardous wastes like other kinds of garbage

de Lijser, Peter

187

Table WH6. Average Consumption for Water Heating by Major Fuels ...  

U.S. Energy Information Administration (EIA)

Major Fuels Used 5 (physical units of consumption per household using the fuel as a water heating source) Electricity (kWh) Table WH6. Average Consumption for Water ...

188

Residential energy use and conservation actions: analysis of disaggregate household data  

Science Conference Proceedings (OSTI)

The Energy Information Administration recently published data they collected from the National Interim Energy Consumption Survey (NIECS). NIECS includes detailed information on 4081 individual households: demographic characteristics, energy-related features of the structure, heating equipment and appliances therein, recent conservation actions taken by the household, and fuel consumption and cost for the April 1978 to March 1979 one-year period. This data set provides a new and valuable resource for analysis. The NIECS data on household energy consumption - total energy use, electricity use, and use of the primary space heating fuel, are summarized and analyzed. The regression equations constructed explain roughly half the variation in energy use among households. These equations contain ten or fewer independent variables, the most important of which are fuel price, year house was built, floor area, and heating degree days. Regression equations were developed that estimate the energy saving achieved by each household based on their recent retrofit actions. These equations predict 20 to 40% of the variation among households. Total annual energy use is the most important determinant of retrofit energy saving; other significant variables include age of household head, household income, year house was built, housing tenure, and proxies for the cost of heating and air conditioning the house.

Hirst, E.; Goeltz, R.; Carney, J.

1981-03-01T23:59:59.000Z

189

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

Air Conditioning Tables Air Conditioning Tables (Million U.S. Households; 24 pages, 138 kb) Contents Pages HC4-1a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 2 HC4-2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 2 HC4-3a. Air Conditioning by Household Income, Million U.S. Households, 2001 2 HC4-4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 2 HC4-5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2 HC4-6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 2 HC4-7a. Air Conditioning by Four Most Populated States, Million U.S. Households, 2001 2 HC4-8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 2

190

Appliance Commitment for Household Load Scheduling  

Science Conference Proceedings (OSTI)

This paper presents a novel appliance commitment algorithm that schedules thermostatically-controlled household loads based on price and consumption forecasts considering users comfort settings to meet an optimization objective such as minimum payment or maximum comfort. The formulation of an appliance commitment problem was described in the paper using an electrical water heater load as an example. The thermal dynamics of heating and coasting of the water heater load was modeled by physical models; random hot water consumption was modeled with statistical methods. The models were used to predict the appliance operation over the scheduling time horizon. User comfort was transformed to a set of linear constraints. Then, a novel linear, sequential, optimization process was used to solve the appliance commitment problem. The simulation results demonstrate that the algorithm is fast, robust, and flexible. The algorithm can be used in home/building energy-management systems to help household owners or building managers to automatically create optimal load operation schedules based on different cost and comfort settings and compare cost/benefits among schedules.

Du, Pengwei; Lu, Ning

2011-06-30T23:59:59.000Z

191

Transportation Baseline Report  

Science Conference Proceedings (OSTI)

The National Transportation Program 1999 Transportation Baseline Report presents data that form a baseline to enable analysis and planning for future Department of Energy (DOE) Environmental Management (EM) waste and materials transportation. In addition, this Report provides a summary overview of DOE’s projected quantities of waste and materials for transportation. Data presented in this report were gathered as a part of the IPABS Spring 1999 update of the EM Corporate Database and are current as of July 30, 1999. These data were input and compiled using the Analysis and Visualization System (AVS) which is used to update all stream-level components of the EM Corporate Database, as well as TSD System and programmatic risk (disposition barrier) information. Project (PBS) and site-level IPABS data are being collected through the Interim Data Management System (IDMS). The data are presented in appendices to this report.

Fawcett, Ricky Lee; Kramer, George Leroy Jr.

1999-12-01T23:59:59.000Z

192

Energy Information Administration - Transportation Energy Consumption by  

U.S. Energy Information Administration (EIA) Indexed Site

Energy Consumption Energy Consumption Transportation Energy Consumption Surveys energy used by vehicles EIA conducts numerous energy-related surveys and other information programs. In general, the surveys can be divided into two broad groups: supply surveys, directed to the suppliers and marketers of specific energy sources, that measure the quantities of specific fuels produced for and/or supplied to the market; and consumption surveys, which gather information on the types of energy used by consumer groups along with the consumer characteristics that are associated with energy use. In the transportation sector, EIA's core consumption survey was the Residential Transportation Energy Consumption Survey. RTECS belongs to the consumption group because it collects information directly from the consumer, the household. For roughly a decade, EIA fielded the RTECS--data were first collected in 1983. This survey, fielded for the last time in 1994, was a triennial survey of energy use and expenditures, vehicle miles-traveled (VMT), and vehicle characteristics for household vehicles. For the 1994 survey, a national sample of more than 3,000 households that own or use some 5,500 vehicles provided data.

193

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

3a. Household Characteristics by Household Income, 3a. Household Characteristics by Household Income, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Household Size 1 Person ....................................... 28.2 9.7 -- -- -- 6.5 11.3 5.7 2 Persons ...................................... 35.1 4.3 -- -- -- 2.0 7.8 5.8 3 Persons ...................................... 17.0 -- 3.3 -- -- 2.2 5.2 7.3 4 Persons ...................................... 15.6 -- 2.2 -- -- -- 4.3 8.1 5 Persons ...................................... 7.1

194

US MidAtl PA Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

MidAtl PA MidAtl PA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl PA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl PA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl PA Expenditures dollars ELECTRICITY ONLY average per household * Pennsylvania households consume an average of 96 million Btu per year, 8% more than the U.S. average. Pennsylvania residents also spend 16% more than the average U.S. households for energy consumed in their homes. * Average electricity consumption in Pennsylvania homes is 10,402 kWh per year, which is lower than the national average, but 58% more than New York households and 17% more than New Jersey residents.

195

US MidAtl PA Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

MidAtl PA MidAtl PA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl PA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl PA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl PA Expenditures dollars ELECTRICITY ONLY average per household * Pennsylvania households consume an average of 96 million Btu per year, 8% more than the U.S. average. Pennsylvania residents also spend 16% more than the average U.S. households for energy consumed in their homes. * Average electricity consumption in Pennsylvania homes is 10,402 kWh per year, which is lower than the national average, but 58% more than New York households and 17% more than New Jersey residents.

196

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2a. Household Characteristics by West Census Region, 2a. Household Characteristics by West Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.8 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Household Size 1 Person ...................................................... 28.2 5.6 1.8 3.8 5.4 2 Persons .................................................... 35.1 7.3 1.9 5.5 4.9 3 Persons .................................................... 17.0 3.5 0.9 2.6 7.6 4 Persons .................................................... 15.6 3.5 1.1 2.4 6.4 5 Persons .................................................... 7.1 2.0 0.6 1.4 9.7 6 or More Persons

197

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

0a. Household Characteristics by Midwest Census Region, 0a. Household Characteristics by Midwest Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 24.5 17.1 7.4 NE Household Size 1 Person ...................................................... 28.2 6.7 4.7 2.0 6.2 2 Persons .................................................... 35.1 8.0 5.4 2.6 5.0 3 Persons .................................................... 17.0 3.8 2.7 1.1 7.9 4 Persons .................................................... 15.6 3.5 2.5 1.0 8.1 5 Persons .................................................... 7.1 1.7

198

1 Consumption smoothing: empirical evidence from rural Burkina Faso  

E-Print Network (OSTI)

This paper analyzes the community insurance of individual consumption against income risks in rural Burkina Faso. The study area is characterized by significant income volatility, particularly for poor households, caused by global or idiosyncratic shocks. The average consumption at village or region community level is used to control for global shocks. The differential effect of income instability on consumption insurance of poor households has been identified. We find robust results by using the General Least Square Method, applied to a 2004-2006 panel data from PNGT2. These results indicate partial consumption insurance by the community. Poor household income is more unstable. Its consumption is more linked to its income variation and less assured by its community during important global shocks. Consumption in the cotton basin is more sensitive to the income risk and less insured by the community. Food consumption is more assured. These results reveal an important role of the rural community in risk sharing, principally in situation of absence of formal insurance structures. 1. Background and objectives The rural Burkina Faso is characterized by important income volatility generated by global or idiosyncratic shocks. This volatility would be particularly for the poor. The main income source in this area is agriculture; then, income is dependent on climatic and socio-economic shocks, as in most of the developing countries (Deaton, 1992, 1997). The instability of household income is a risk on their consumption. Some risks are global, affecting all the households and others are idiosyncratic. However, the formal institutional mechanisms of consumption insurance against these risks are not well developed or not effective. The literature indicates that rural households develop various actions of consumption adjustment in case of income risks 1. It is, for example, about storage of agricultural food grains, space diversification of land plots exploited, credit, speculation on assets and family solidarity

Yiriyibin Bambio

2010-01-01T23:59:59.000Z

199

Household Energy Consumption and Expenditures 1993 -- Index Page  

U.S. Energy Information Administration (EIA) Indexed Site

Fax: (202) 586-0018 URL: http:www.eia.govemeurecs1d.html If you are having any technical problems with this site, please contact the EIA Webmaster at wmaster@eia.doe.gov...

200

Extending Efficiency Services to Underserved Households: NYSERDA...  

NLE Websites -- All DOE Office Websites (Extended Search)

Extending Efficiency Services to Underserved Households: NYSERDA's Assisted Home Performance with ENERGY STAR Program Title Extending Efficiency Services to Underserved Households:...

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

U.S. Energy Information Administration (EIA) Indexed Site

1997 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 1997 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables Table Titles (Released: February 2004) Entire Section Percents Tables: HC1 Housing Unit Characteristics, Million U.S. Households PDF PDF NOTE: As of 10/31/01, numbers in the "Housing Units" TABLES section for stub item: "Number of Floors in Apartment Buildings" were REVISED. These numbers will differ from the numbers in the published report. Tables: HC2 Household Characteristics, Million U.S. Households PDF PDF Tables: HC3 Space Heating, Million U.S. Households PDF PDF Tables: HC4 Air-Conditioning, Million U.S. Households PDF PDF Tables: HC5 Appliances, Million U.S. Households PDF PDF

202

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

U.S. Energy Information Administration (EIA) Indexed Site

3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables Topical Sections Entire Section All Detailed Tables PDF Tables: HC1 Household Characteristics, Million U.S. Households Presents data relating to location, type, ownership, age, size, construction, and householder demographic and income characteristics. PDF Tables: HC2 Space Heating, Million U.S. Households Presents data describing the types of heating fuel and equipment used for main and secondary heating purposes. PDF Tables: HC3 Air-Conditioning, Million U.S. Households Presents data describing selected household characteristics including location, number of rooms and area cooled and air-conditioning usage. PDF

203

Survey Consumption  

Gasoline and Diesel Fuel Update (EIA)

fsidentoi fsidentoi Survey Consumption and 'Expenditures, April 1981 March 1982 Energy Information Administration Wasningtoa D '" N """"*"""*"Nlwr. . *'.;***** -. Mik>. I This publication is available from ihe your COr : 20585 Residential Energy Consumption Survey: Consum ption and Expendi tures, April 1981 Through March 1982 Part 2: Regional Data Prepared by: Bruce Egan This report was prepared by the Energy Information Administra tion, the independent statistical

204

Re-baselining Report  

NLE Websites -- All DOE Office Websites (Extended Search)

008 008 DOE/NETL-2008/1308 Re-baselining APS, CS & FC GRPA R&D Goals Impact of Cost Escalation on Power System R&D Goals Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or

205

Modeling energy consumption of residential furnaces and boilers in U.S. homes  

E-Print Network (OSTI)

CONSUMPTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Lutz, James; Dunham-Whitehead, Camilla; Lekov, Alex; McMahon, James

2004-01-01T23:59:59.000Z

206

EIA - Household Transportation report: Household Vehicles Energy Use:  

U.S. Energy Information Administration (EIA) Indexed Site

Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Use: Latest Data & Trends November 2005 Release (Next Update: Discontinued) Based on the 2001 National Household Travel Survey conducted by the U.S. Department of Transportation and augmented by EIA Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses in an effort to maintain consistency with its past residential transportation series, which was discontinued after 1994. This report, Household Vehicles Energy Use: Latest Data & Trends, provides details on the nation's energy use for household passenger travel. A primary purpose of this report is to release the latest consumer-based data

207

Guidance for Developing Baseline and Annual Water Use | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Guidance for Developing Baseline and Annual Water Use Guidance for Developing Baseline and Annual Water Use Guidance for Developing Baseline and Annual Water Use Potable water use intensity is defined as annual potable water use divided by total gross square footage of facility space (gal/ft2). The facility gross square footage is the same value used for energy use intensity reduction goals. Executive Order (E.O.) 13423 requires Federal agencies to develop a potable water use intensity baseline for fiscal year (FY) 2007. Agencies must report total potable water consumption and gross facility square footage against that baseline. To avoid additional reporting requirements, E.O. 13423 does not require agencies to report square footage of irrigated turf or landscape. Potable water used for landscape irrigation must be reported in total potable water

208

Cover Page of Household Vehicles Energy Use: Latest Data & Trends  

U.S. Energy Information Administration (EIA) Indexed Site

Household Vehicles Energy Use Cover Page Cover Page of Household Vehicles Energy Use: Latest Data & Trends...

209

ac_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total...

210

Household savings and portfolio choice  

E-Print Network (OSTI)

This thesis consists of three essays that examine household savings and portfolio choice behavior. Chapter One analyses the effects of employer matching contributions and tax incentives on participation and contribution ...

Klein, Sean Patrick

2010-01-01T23:59:59.000Z

211

Household energy handbook: an interim guide and reference manual. World Bank technical paper  

SciTech Connect

A standard framework for measuring and assessing technical information on the household energy sector in developing countries is needed. The handbook is intended as a first step toward creating such a framework. Chapter I discusses energy terms and principles underlying the energy units, definitions, and calculations presented in the following chapters. Chapter II describes household consumption patterns and their relationship to income, location, and household-size variables. Chapter III evaluates energy end uses and the technologies that provide cooking, lighting, refrigeration, and space-heating services. Chapter IV examines household energy resources and supplies, focusing on traditional biomass fuels. Finally, Chapter V demonstrates simple assessment methods and presents case studies to illustrate how household energy data can be used in different types of assessments.

Leach, G.; Gowen, M.

1987-01-01T23:59:59.000Z

212

Residential energy consumption: An analysis-of-variance study  

SciTech Connect

In this report, tests of statistical significance of five sets of variables with household energy consumption (at the point of end-use) are described. Five models, in sequence, were empirically estimated and tested for statistical significance by using the Residential Energy Consumption Survey of the US Department of Energy, Energy Information Administration. Each model incorporated additional information, embodied in a set of variables not previously specified in the energy demand system. The variable sets were generally labeled as economic variables, weather variables, household-structure variables, end-use variables, and housing-type variables. The tests of statistical significance showed each of the variable sets to be highly significant in explaining the overall variance in energy consumption. The findings imply that the contemporaneous interaction of different types of variables, and not just one exclusive set of variables, determines the level of household energy consumption.

Poyer, D.A.

1992-01-01T23:59:59.000Z

213

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

3a. Air Conditioning by Household Income, 3a. Air Conditioning by Household Income, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.9 1.5 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 12.3 17.4 21.5 31.7 9.6 23.4 3.9 Air Conditioners Not Used ............ 2.1 0.4 0.7 0.5 0.5 0.4 0.9 20.8 Households Using Electric Air-Conditioning 2 .......................... 80.8 11.9 16.7 21.0 31.2 9.1 22.6 3.9 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 .............. 57.5 6.2 10.7 15.2 25.3 4.5 12.4 5.3 Without a Heat Pump .................. 46.2 4.9 9.1 12.1 20.1 3.6 10.4 6.1 With a Heat Pump

214

US MidAtl NY Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

MidAtl NY MidAtl NY Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl NY Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl NY Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl NY Expenditures dollars ELECTRICITY ONLY average per household * New York households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Electricity consumption in New York homes is much lower than the U.S. average, because many households use other fuels for major energy end uses like space heating, water heating, and cooking. Electricity costs are closer to the national average due to higher than average electricity prices in the state.

215

US MidAtl NY Site Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

MidAtl NY MidAtl NY Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl NY Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl NY Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl NY Expenditures dollars ELECTRICITY ONLY average per household * New York households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Electricity consumption in New York homes is much lower than the U.S. average, because many households use other fuels for major energy end uses like space heating, water heating, and cooking. Electricity costs are closer to the national average due to higher than average electricity prices in the state.

216

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

4 4 Ownership (1) Owned 54.9 104.5 40.3 78% Rented 77.4 71.7 28.4 22% Public Housing 75.7 62.7 28.7 2% Not Public Housing 77.7 73.0 28.4 19% 100% Note(s): Source(s): 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008 2005 Residential Delivered Energy Consumption Intensities, by Ownership of Unit Per Square Per Household Per Household Percent of Foot (thousand Btu) (million Btu) Members (million Btu) Total Consumption

217

Household energy use in urban Venezuela: Implications from surveys in Maracaibo, Valencia, Merida, and Barcelona-Puerto La Cruz  

Science Conference Proceedings (OSTI)

This report identifies the most important results of a comparative analysis of household commercial energy use in Venezuelan urban cities. The use of modern fuels is widespread among all cities. Cooking consumes the largest share of urban household energy use. The survey documents no use of biomass and a negligible use of kerosene for cooking. LPG, natural gas, and kerosene are the main fuels available. LPG is the fuel choice of low-income households in all cities except Maracaibo, where 40% of all households use natural gas. Electricity consumption in Venezuela`s urban households is remarkably high compared with the levels used in households in comparable Latin American countries and in households of industrialized nations which confront harsher climatic conditions and, therefore, use electricity for water and space heating. The penetration of appliances in Venezuela`s urban households is very high. The appliances available on the market are inefficient, and there are inefficient patterns of energy use among the population. Climate conditions and the urban built form all play important roles in determining the high level of energy consumption in Venezuelan urban households. It is important to acknowledge the opportunities for introducing energy efficiency and conservation in Venezuela`s residential sector, particularly given current economic and financial constraints, which may hamper the future provision of energy services.

Figueroa, M.J.; Sathaye, J.

1993-08-01T23:59:59.000Z

218

Future Air Conditioning Energy Consumption in Developing Countriesand what can be done about it: The Potential of Efficiency in theResidential Sector  

SciTech Connect

The dynamics of air conditioning are of particular interestto energy analysts, both because of the high energy consumption of thisproduct, but also its disproportionate impact on peak load. This paperaddresses the special role of this end use as a driver of residentialelectricity consumption in rapidly developing economies. Recent historyhas shown that air conditioner ownership can grow grows more rapidly thaneconomic growth in warm-climate countries. In 1990, less than a percentof urban Chinese households owned an air conditioner; by 2003 this numberrose to 62 percent. The evidence suggests a similar explosion of airconditioner use in many other countries is not far behind. Room airconditioner purchases in India are currently growing at 20 percent peryear, with about half of these purchases attributed to the residentialsector. This paper draws on two distinct methodological elements toassess future residential air conditioner 'business as usual' electricityconsumption by country/region and to consider specific alternative 'highefficiency' scenarios. The first component is an econometric ownershipand use model based on household income, climate and demographicparameters. The second combines ownership forecasts and stock accountingwith geographically specific efficiency scenarios within a uniqueanalysis framework (BUENAS) developed by LBNL. The efficiency scenariomodule considers current efficiency baselines, available technologies,and achievable timelines for development of market transformationprograms, such as minimum efficiency performance standards (MEPS) andlabeling programs. The result is a detailed set of consumption andemissions scenarios for residential air conditioning.

McNeil, Michael A.; Letschert, Virginie E.

2007-05-01T23:59:59.000Z

219

Future Air Conditioning Energy Consumption in Developing Countriesand what can be done about it: The Potential of Efficiency in theResidential Sector  

SciTech Connect

The dynamics of air conditioning are of particular interestto energy analysts, both because of the high energy consumption of thisproduct, but also its disproportionate impact on peak load. This paperaddresses the special role of this end use as a driver of residentialelectricity consumption in rapidly developing economies. Recent historyhas shown that air conditioner ownership can grow grows more rapidly thaneconomic growth in warm-climate countries. In 1990, less than a percentof urban Chinese households owned an air conditioner; by 2003 this numberrose to 62 percent. The evidence suggests a similar explosion of airconditioner use in many other countries is not far behind. Room airconditioner purchases in India are currently growing at 20 percent peryear, with about half of these purchases attributed to the residentialsector. This paper draws on two distinct methodological elements toassess future residential air conditioner 'business as usual' electricityconsumption by country/region and to consider specific alternative 'highefficiency' scenarios. The first component is an econometric ownershipand use model based on household income, climate and demographicparameters. The second combines ownership forecasts and stock accountingwith geographically specific efficiency scenarios within a uniqueanalysis framework (BUENAS) developed by LBNL. The efficiency scenariomodule considers current efficiency baselines, available technologies,and achievable timelines for development of market transformationprograms, such as minimum efficiency performance standards (MEPS) andlabeling programs. The result is a detailed set of consumption andemissions scenarios for residential air conditioning.

McNeil, Michael A.; Letschert, Virginie E.

2007-05-01T23:59:59.000Z

220

DOE/EIA-0193/P PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY  

U.S. Energy Information Administration (EIA) Indexed Site

193/P 193/P PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY OFFICE OF THE CONSUMPTION DATA SYSTEM OFFICE OF PROGRAM DEVELOPMENT ENERGY INFORMATION ADMINISTRATION AUGUST 1, 1979 PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY Attached is the first report of the Office of the Consumption Data System, Office of Program Development, Energy Information Administration, presenting preliminary data from the National Interim Energy Consumption Survey (NIECS). The focus of this report is the conservation activities performed by households since January 1977, and the status of households with respect to insulation, storm windows, and other energy conserving characteristics. These tables are from preliminary data files.

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Residential Energy Consumption Survey: housing characteristics, 1982  

Science Conference Proceedings (OSTI)

Data in this report cover fuels and their use in the home, appliances, square footage of floor space, heating equipment, thermal characteristics of the housing unit, conservation activities, wood consumption, indoor temperatures, and weather. The 1982 survey included a number of questions on the reasons households make energy conservation improvements to their homes. Results of these questions are presented. Discussion also highlights data pertaining to: trends in home heating fuels, trends in conservation improvements, and characteristics of households whose energy costs are included in their rent.

Thompson, W.

1984-08-01T23:59:59.000Z

222

Research on Regional Differences of Urban Resident Consumption Structure in China Based on Fuzzy Matter Element Model  

Science Conference Proceedings (OSTI)

Study of residents’ consumption structure plays an important role in macroeconomic policy formulation. Based on per capita annual consumption expenditure of urban households, the fuzzy matter element model is used to evaluate urban resident consumption ... Keywords: comsumption structure, fuzzy matter-element, Euclid approach degree, government consumption expenditure

Hong Li; Bo Zhou

2010-11-01T23:59:59.000Z

223

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

a. Household Characteristics by Climate Zone, a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Household Size 1 Person ....................................... 28.2 2.5 8.1 6.5 4.8 6.2 9.9 2 Persons ...................................... 35.1 3.1 9.4 8.2 6.5 7.9 8.7 3 Persons ...................................... 17.0 1.3 4.3 4.0 3.3 4.1 10.7 4 Persons ...................................... 15.6 1.4 3.9 3.4 3.4 3.5 10.5 5 Persons ......................................

224

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

6a. Household Characteristics by Type of Rented Housing Unit, 6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total Rented Units ........................ 34.3 10.5 7.4 15.2 1.1 6.9 Household Size 1 Person ....................................... 12.3 2.5 2.6 7.0 0.3 10.0 2 Persons ...................................... 9.2 2.5 2.5 4.1 Q 11.8 3 Persons ...................................... 5.4 2.0 1.1 2.0 0.4 13.9 4 Persons ...................................... 3.8 1.6 0.7 1.4 Q 17.7 5 Persons ...................................... 2.0 0.9 0.4 0.6 Q 24.1 6 or More Persons ........................

225

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

5a. Household Characteristics by Type of Owner-Occupied Housing Unit, 5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.3 0.4 2.0 2.9 1.3 Total Owner-Occupied Units ....... 72.7 63.2 2.1 1.8 5.7 6.7 Household Size 1 Person ....................................... 15.8 12.5 0.8 0.9 1.6 10.3 2 Persons ...................................... 25.9 23.4 0.5 0.5 1.5 10.1 3 Persons ...................................... 11.6 9.6 0.5 Q 1.3 12.1 4 Persons ...................................... 11.8 10.9 Q Q 0.7 15.7 5 Persons ...................................... 5.1 4.5 Q Q 0.4 24.2 6 or More Persons

226

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

1a. Household Characteristics by South Census Region, 1a. Household Characteristics by South Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.5 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Household Size 1 Person ...................................................... 28.2 9.9 5.0 1.8 3.1 6.3 2 Persons .................................................... 35.1 13.0 6.7 2.5 3.8 4.2 3 Persons .................................................... 17.0 6.6 3.7 1.2 1.7 8.8 4 Persons .................................................... 15.6 6.0 3.3 0.8 1.9 10.7 5 Persons ....................................................

227

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

8a. Household Characteristics by Urban/Rural Location, 8a. Household Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Household Size 1 Person ...................................................... 28.2 14.6 5.3 4.8 3.6 6.4 2 Persons .................................................... 35.1 15.7 5.7 6.9 6.8 5.4 3 Persons .................................................... 17.0 7.6 2.8 3.5 3.1 7.2 4 Persons .................................................... 15.6 6.8 2.3 4.1 2.4 8.1 5 Persons .................................................... 7.1 3.1 1.3 1.3 1.4 12.3 6 or More Persons

228

homeoffice_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

3a. Home Office Equipment by Household Income, 3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.4 1.9 1.2 1.0 0.6 1.9 0.9 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 47.6 3.0 Households Using Office Equipment .......................... 96.2 13.2 19.8 25.5 37.7 10.7 38.8 3.2 Personal Computers 2 ................... 60.0 3.7 8.7 16.0 31.6 3.7 17.4 4.6 Number of Desktop PCs 1 .................................................. 45.1 2.8 7.1 12.8 22.4 2.8 13.6 5.1 2 or more .................................... 9.1 0.6 0.7 1.7 6.2 0.6 2.2 13.0 Number of Laptop PCs

229

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2a. Household Characteristics by Year of Construction, 2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.0 1.2 1.2 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Household Size 1 Person ....................................... 28.2 2.5 4.5 5.1 4.0 3.7 8.3 7.5 2 Persons ...................................... 35.1 4.8 6.2 6.6 4.5 5.3 7.8 5.8 3 Persons ...................................... 17.0 2.5 3.3 2.9 2.3 1.9 4.1 8.4 4 Persons ...................................... 15.6 3.4 2.8 2.3 1.9 1.8 3.4 9.6 5 Persons ...................................... 7.1 1.6 1.2 1.3 0.6 0.7 1.6 14.3 6 or More Persons

230

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

HOW MANY HYBRID HOUSEHOLDS IN THE CALIFORNIA NEW CAR MARKET?average 2.43 cars per household, then the hybrid householdnumber of multi-car households that fit our hybrid household

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

231

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

U.S. Energy Information Administration (EIA) Indexed Site

2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables + EXPAND ALL Tables HC1: Housing Unit Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Owner-Occupied Housing Unit PDF Four Most Populated States PDF Urban/Rural Location PDF Northeast Census Region PDF Midwest Census Region PDF South Census Region PDF West Census Region PDF Tables HC2: Household Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Housing Unit PDF Type of Owner-Occupied Housing Unit PDF Type of Rented Housing Unit PDF

232

Household energy in South Asia  

Science Conference Proceedings (OSTI)

This research study on the use of energy in South Asis (India, Pakistan, Sri Lanka and Bangladesh) was sponsored by the Food and Agriculture Organization of the UN, the International Bank for Reconstruction and Development (the World Bank), and the Directorate-General for Development of the Commission of the European Communities. The aim of this book is to improve the understanding of household energy and its linkages, by reviewing the data resources on household energy use, supply, prices and other relevant factors that exist in South Asia.

Leach, G.

1987-01-01T23:59:59.000Z

233

Pacific Northwest Residential Energy Consumption Survey : Sample Selection Activities.  

Science Conference Proceedings (OSTI)

The primary purpose of the 1983 Pacific Northwest Residential Energy Consumption Survey is to obtain a comprehensive data base regarding household energy usage patterns incorporating not only general behavioral indicators of usage (e.g., temperature at which the dwelling is maintained at different times of day during the months of the year in which heating systems are activated or conservation measures effected) but also those characteristics lying further beyond the realm of immediate influence of the household dwellers which directly effect energy consumption (e.g., housing and household characteristics including square footage, number of floors or levels, the number and characteristics of the appliances in the household and household demographics/composition). The data base to be assembled as part of this research effort is also to include households' actual level of energy use for two major fuels (i.e., electricity and natural gas) obtained, with the consent of respondents, from their servicing utility(ies). Two samples have been incorporated in the study. The primary sample - the Regional Sample - will generate a large and comprehensive data base from a representative cross-section of individual households in the Pacific Northwest. A second, Supplementary Sample was incorporated in the survey design to ensure that a sufficient number of households not participating in qualified loan or grant programs, but comparable to participant households on a number of key descriptive characteristics, were included in the assessment. Inclusion of such households in the assessment will permit a formal evaluation of the loan/grant programs to be accomplished. Sampling procedures are described thoroughly.

Louis Harris and Associates

1983-08-03T23:59:59.000Z

234

Assumptions to the Annual Energy Outlook 2002 - Household Expenditures...  

Annual Energy Outlook 2012 (EIA)

Expenditures Module The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

235

Table WH1. Total Households Using Water Heating Equipment, 2005 ...  

U.S. Energy Information Administration (EIA)

Table WH1. Total Households Using Water Heating Equipment, 2005 Million U.S. Households Fuels Used (million U.S. households) Number of Water Heaters Used

236

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

3a. Space Heating by Household Income, 3a. Space Heating by Household Income, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Heat Home ..................................... 106.0 18.4 22.7 26.8 38.1 14.6 33.4 3.3 Do Not Heat Home ........................ 1.0 0.3 Q 0.3 0.3 0.3 0.4 23.4 No Heating Equipment .................. 0.5 Q Q Q 0.2 Q Q 35.0 Have Equipment But Do Not Use It ................................ 0.4 Q Q Q Q 0.2 0.3 22.8 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 18.4 22.7

237

appl_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

3a. Appliances by Household Income, 3a. Appliances by Household Income, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.8 1.6 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 18.0 22.0 26.1 35.6 14.4 32.6 3.2 1 ................................................ 95.2 17.3 21.1 24.8 32.0 13.8 31.1 3.4 2 or More .................................. 6.5 0.8 0.9 1.3 3.6 0.6 1.5 13.1 Most Used Oven ........................ 101.7 18.0 22.0 26.1 35.6 14.4 32.6 3.2

238

Private computation of spatial and temporal power consumption with smart meters  

Science Conference Proceedings (OSTI)

Smart metering of utility consumption is rapidly becoming reality for multitudes of people and households. It promises real-time measurement and adjustment of power demand which is expected to result in lower overall energy use and better load balancing. ...

Zekeriya Erkin; Gene Tsudik

2012-06-01T23:59:59.000Z

239

Table CE3-4c. Electric Air-Conditioning Energy Consumption in U.S ...  

U.S. Energy Information Administration (EIA)

Table CE3-4c. Electric Air-Conditioning Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total Type of Housing Unit

240

Table CE3-1c. Electric Air-Conditioning Energy Consumption in U.S ...  

U.S. Energy Information Administration (EIA)

Table CE3-1c. Electric Air-Conditioning Energy Consumption in U.S. Households by Climate Zone, 2001 RSE Column Factor: Total Climate Zone1 RSE Row

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Elasticities of Electricity Demand in Urban Indian Households  

E-Print Network (OSTI)

Energy demand, and in particular electricity demand in India has been growing at a very rapid rate over the last decade. Given, current trends in population growth, industrialisation, urbanisation, modernisation and income growth, electricity consumption is expected to increase substantially in the coming decades as well. Tariff reforms could play a potentially important role as a demand side management tool in India. However, the effects of any price revisions on consumption will depend on the price elasticity of demand for electricity. In the past, electricity demand studies for India published in international journals have been based on aggregate macro data at the country or sub-national / state level. In this paper, price and income elasticities of electricity demand in the residential sector of all urban areas of India are estimated for the first time using disaggregate level survey data for over thirty thousand households. Three electricity demand functions have been estimated using monthly data for the following seasons: winter, monsoon and summer. The results show electricity demand is income and price inelastic in all three seasons, and that household, demographic and geographical variables are important in determining electricity demand, something that is not possible to determine using aggregate macro models alone. Key Words Residential electricity demand, price elasticity, income elasticity Short Title Electricity demand in Indian households Acknowledgements: The authors would like to gratefully acknowledge the National Sample Survey Organisation, Department of Statistics of the Government of India, for making available to us the unit level, household survey data. We would also like to thank Prof. Daniel Spreng for his support of our research. 2 1.

Shonali Pachauri

2002-01-01T23:59:59.000Z

242

324 Building Baseline Radiological Characterization  

SciTech Connect

This report documents the analysis of radiological data collected as part of the characterization study performed in 1998. The study was performed to create a baseline of the radiological conditions in the 324 Building.

R.J. Reeder, J.C. Cooper

2010-06-24T23:59:59.000Z

243

ARM - Baseline Change Request Guidelines  

NLE Websites -- All DOE Office Websites (Extended Search)

DocumentsBaseline Change Request Guidelines DocumentsBaseline Change Request Guidelines Page Contents Introduction Submit a BCR BCR Process Flowchart Baseline Change Request Guidelines Introduction Baseline Change Requests (BCR) are used by the ARM Infrastructure as a process to provide configuration control and for formally requesting and documenting changes within the ARM Infrastructure. Configuration Control: BCRs are required for changes to instruments, data systems, data processes, datastreams, measurement methods, and facilities. They help ensure that all aspects of the ARM Infrastructure are consulted prior to implementing changes. Seemingly minor changes can have significant repercussions throughout the Facility and therefore, NO change to an operational instrument, computer, facility, or other system can or will be

244

A functional analysis of electrical load curve modelling for some households specific electricity end-uses  

E-Print Network (OSTI)

A functional analysis of electrical load curve modelling for some households specific electricity and the way electrical devices are used will evolve significantly. The energy consumption is likely of electrical devices; · integration of decentralized energy production and stocking (PV modules with battery

Paris-Sud XI, Université de

245

PHEV Utility Factors (UFs) Derived from Households' Vehicle Usage Patterns Jamie Davies, Ken Kurani  

E-Print Network (OSTI)

to calculate electrical consumption, emissions, fuel costs, and battery lifetime and degradation. Of particular of Battery Electric Vehicles (BEVs) while allowing consumers to make use of the familiar gasoline refueling, each household starts the day with a fully charged battery and does not recharge throughout the day

California at Davis, University of

246

Energy consumption and usage characteristics from field measurements of residential dishwashers, clothes washers and clothes dryers  

SciTech Connect

The measured energy consumption and usage characteristics for household dishwashers, clothes washers, and clothes dryers for ten townhouses at Twin Rivers, N.J., are presented. Whenever the dishwashers and/or clothes washers were in use, the energy consumption, water consumption, frequency of usage, and water temperature were measured by a data acquisition system. The electrical energy of electric clothes dryers and the gas consumption of gas clothes dryers were measured, as well as their frequency and duration of use, and exhaust temperature. Typical household usage patterns of these major appliances are included.

Chang, Y.L.; Grot, R.A.

1980-10-01T23:59:59.000Z

247

Development of the Household Sample for Furnace and Boiler Life-Cycle Cost  

NLE Websites -- All DOE Office Websites (Extended Search)

Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Analysis Title Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Analysis Publication Type Report LBNL Report Number LBNL-55088 Year of Publication 2005 Authors Whitehead, Camilla Dunham, Victor H. Franco, Alexander B. Lekov, and James D. Lutz Document Number LBNL-55088 Pagination 22 Date Published May 31 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated.The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

248

Psychological strategies to reduce energy consumption: first annual progress report  

SciTech Connect

A multidisciplinary program composed of a mix of physical and social scientists is studying the behavior of occupants as well as the engineering aspects of household energy consumption. A study of the Twin Rivers, New Jersey area examined and tested psychological strategies for helping people achieve significant reductions in their residential energy consumption. The results show that homeowners are motivated by cost and other pressures provided by daily feedback on their actual energy consumption. Four feedback experiments suggest that feedback helps homeowners to reduce their energy consumption, but the optimal nature of the feedback system has yet to be identified. The project also included research on thermostat control and on attitudes.

Seligman, C.; Darley, J.M.; Becker, L.J.

1976-01-01T23:59:59.000Z

249

homeoffice_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

9a. Home Office Equipment by Northeast Census Region, 9a. Home Office Equipment by Northeast Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total .............................................................. 107.0 20.3 14.8 5.4 NE Households Using Office Equipment ......................................... 96.2 17.9 12.8 5.0 1.3 Personal Computers 1 ................................. 60.0 10.9 7.7 3.3 3.1 Number of Desktop PCs 1 ................................................................ 45.1 8.7 6.2 2.5 3.7 2 or more ................................................... 9.1 1.4 0.9 0.5 12.9 Number of Laptop PCs 1 ................................................................

250

homeoffice_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

0a. Home Office Equipment by Midwest Census Region, 0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0 14.1 9.9 4.2 3.7 Number of Desktop PCs 1 ................................................................ 45.1 10.4 7.2 3.2 3.7 2 or more ................................................... 9.1 2.3 1.6 0.7 10.1 Number of Laptop PCs 1 ................................................................

251

char_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2001 2001 Household Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Household Size 1 Person ...................................................... 28.2 2.2 2.4 1.8 1.7 7.3 2 Persons .................................................... 35.1 2.2 4.0 2.4 2.0 6.9 3 Persons .................................................... 17.0 1.1 2.0 1.2 1.2 9.5 4 Persons .................................................... 15.6 0.8 1.9 1.3 0.9 11.2 5 Persons .................................................... 7.1 0.4 1.1 0.4 0.5 19.8 6 or More Persons ....................................... 4.0 0.4 0.9 0.4 0.1 16.4 2001 Household Income Category

252

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

0a. Air Conditioning by Midwest Census Region, 0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 20.2 13.4 6.7 2.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 14.3 9.5 4.8 3.8 Without a Heat Pump ................................ 46.2 13.6 9.0 4.6 3.9 With a Heat Pump .....................................

253

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

8a. Air Conditioning by Urban/Rural Location, 8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 36.8 13.6 18.9 13.6 4.3 Air Conditioners Not Used ........................... 2.1 1.2 0.2 0.4 0.3 21.4 Households Using Electric Air-Conditioning 2 ........................................ 80.8 35.6 13.4 18.6 13.3 4.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 ............................ 57.5 23.6 8.6 15.8 9.4 5.1 Without a Heat Pump ................................ 46.2 19.3 7.4 13.1 6.4 6.3 With a Heat Pump ..................................... 11.3 4.4

254

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

5a. Air Conditioning by Type of Owner-Occupied Housing Unit, 5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 59.5 58.7 6.5 12.4 5.3 5.2 Air Conditioners Not Used ............ 1.2 1.1 Q 0.6 Q 23.3 Households Using Electric Air-Conditioning 1 .......................... 58.2 57.6 6.3 11.8 5.1 5.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 44.7 43.6 3.2 7.1 3.5 7.0 Without a Heat Pump .................. 35.6 35.0 2.4 6.1 2.7 7.7 With a Heat Pump .......................

255

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

6a. Air Conditioning by Type of Rented Housing Unit, 6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.8 0.5 1.4 1.2 1.6 Households With Electric Air-Conditioning Equipment ........ 23.4 58.7 6.5 12.4 5.3 6.1 Air Conditioners Not Used ............ 0.9 1.1 Q 0.6 Q 23.0 Households Using Electric Air-Conditioning 1 .......................... 22.5 57.6 6.3 11.8 5.1 6.2 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 12.7 43.6 3.2 7.1 3.5 8.5 Without a Heat Pump .................. 10.6 35.0 2.4 6.1 2.7 9.3 With a Heat Pump ....................... 2.2 8.6 0.8 1.0

256

Inconsistent pathways of household waste  

Science Conference Proceedings (OSTI)

The aim of this study was to provide policy-makers and waste management planners with information about how recycling programs affect the quantities of specific materials recycled and disposed of. Two questions were addressed: which factors influence household waste generation and pathways? and how reliable are official waste data? Household waste flows were studied in 35 Swedish municipalities, and a wide variation in the amount of waste per capita was observed. When evaluating the effect of different waste collection policies, it was found to be important to identify site-specific factors influencing waste generation. Eleven municipal variables were investigated in an attempt to explain the variation. The amount of household waste per resident was higher in populous municipalities and when net commuting was positive. Property-close collection of dry recyclables led to increased delivery of sorted metal, plastic and paper packaging. No difference was seen in the amount of separated recyclables per capita when weight-based billing for the collection of residual waste was applied, but the amount of residual waste was lower. Sixteen sources of error in official waste statistics were identified and the results of the study emphasize the importance of reliable waste generation and composition data to underpin waste management policies.

Dahlen, Lisa [Division of Waste Science and Technology, Lulea University of Technology, SE, 971 87 Lulea (Sweden)], E-mail: lisa.dahlen@ltu.se; Aberg, Helena [Department of Food, Health and Environment, University of Gothenburg, P.O. Box 12204, SE, 402 42 Gothenburg (Sweden); Lagerkvist, Anders [Division of Waste Science and Technology, Lulea University of Technology, SE, 971 87 Lulea (Sweden); Berg, Per E.O. [HB Anttilator, Stagnellsgatan 3, SE, 652 23, Karlstad (Sweden)

2009-06-15T23:59:59.000Z

257

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

1a. Air Conditioning by South Census Region, 1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 36.9 19.0 6.4 11.5 1.6 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 30.4 16.1 5.0 9.2 2.8 Without a Heat Pump ................................ 46.2 22.1 10.4 3.4 8.3 5.6 With a Heat Pump

258

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

9a. Air Conditioning by Northeast Census Region, 9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...................... 82.9 14.5 11.3 3.2 3.3 Air Conditioners Not Used ........................... 2.1 0.3 0.3 Q 28.3 Households Using Electric Air-Conditioning 1 ........................................ 80.8 14.2 11.1 3.2 3.4 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 5.7 4.9 0.8 8.9 Without a Heat Pump ................................ 46.2 5.2 4.5 0.7 9.2 With a Heat Pump .....................................

259

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2a. Air Conditioning by Year of Construction, 2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.1 1.2 1.1 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 13.6 16.0 14.7 10.4 10.5 17.6 4.7 Air Conditioners Not Used ............ 2.1 Q 0.3 0.5 0.3 0.4 0.5 27.2 Households Using Electric Air-Conditioning 2 .......................... 80.8 13.4 15.8 14.2 10.1 10.2 17.1 4.7 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 .............. 57.5 12.6 13.7 11.0 7.1 6.6 6.4 5.9 Without a Heat Pump .................. 46.2 10.1 10.4 8.0 6.1 5.9 5.7 7.0 With a Heat Pump ....................... 11.3 2.5 3.3

260

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

4a. Air Conditioning by Type of Housing Unit, 4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.6 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 82.9 58.7 6.5 12.4 5.3 4.9 Air Conditioners Not Used ............ 2.1 1.1 Q 0.6 Q 21.8 Households Using Electric Air-Conditioning 1 .......................... 80.8 57.6 6.3 11.8 5.1 4.9 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 57.5 43.6 3.2 7.1 3.5 6.7 Without a Heat Pump .................. 46.2 35.0 2.4 6.1 2.7 7.7 With a Heat Pump ....................... 11.3 8.6 0.8 1.0 0.8 19.7 Room Air-Conditioning

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

The comparative impact of the market penetration of energy-efficient measures: A sensitivity analysis of its impact on minority households  

SciTech Connect

A sensitivity study was made of the potential market penetration of residential energy efficiency as energy service ratio (ESR) improvements occurred in minority households, by age of house. The study followed a Minority Energy Assessment Model analysis of the National Energy Strategy projections of household energy consumption and prices, with majority, black, and Hispanic subgroup divisions. Electricity and total energy consumption and expenditure patterns were evaluated when the households` ESR improvement followed a logistic negative growth (i.e., market penetration) path. Earlier occurrence of ESR improvements meant greater discounted savings over the 22-year period.

Bozinovich, L.V.; Poyer, D.A.; Anderson, J.L.

1993-12-01T23:59:59.000Z

262

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

... per Household3 1997 Cooling Degree-Days per Household Total U.S. Households ..... 1,274 1,166 1,562 1,010 6.6 No/Don’t Use Air-Conditioning ...

263

RESIDENTIAL ENERGY CONSUMPTION SURVEY 1997 CONSUMPTION AND ...  

U.S. Energy Information Administration (EIA)

Residential Sector energy Intensities for 1978-1997 using data from EIA Residential Energy Consumption Survey.

264

Space-Heating energy used by households in the residential sector.  

U.S. Energy Information Administration (EIA) Indexed Site

Detailed Tables Detailed Tables Energy End Uses Ranked by Energy Consumption, 1989 The following 28 tables present detailed data describing the consumption of and expenditures for energy used by households in the residential sector. The data are presented at the national level, Census region and division levels, for climate zones and for the most populous States, as well as for other selected characteristics of households. This section provides assistance in reading the tables by explaining some of the headings for the categories of data. It also explains the use of the row and column factors to compute the relative standard error of the estimates given in the tables. Organization of the Tables The tables cover consumption and expenditures for six topical areas: Major Energy Source

265

Development of the household sample for furnace and boilerlife-cycle cost analysis  

Science Conference Proceedings (OSTI)

Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated. The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

Whitehead, Camilla Dunham; Franco, Victor; Lekov, Alex; Lutz, Jim

2005-05-31T23:59:59.000Z

266

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

What's new in our home energy use? What's new in our home energy use? RECS 2009 - Release date: March 28, 2011 First results from EIA's 2009 Residential Energy Consumption Survey (RECS) The 2009 RECS collected home energy characteristics data from over 12,000 U.S. households. This report highlights findings from the survey, with details presented in the Household Energy Characteristics tables. How we use energy in our homes has changed substantially over the past three decades. Over this period U.S. homes on average have become larger, have fewer occupants, and are more energy-efficient. In 2005, energy use per household was 95 million British thermal units (Btu) of energy compared with 138 million Btu per household in 1978, a drop of 31 percent. Did You Know? Over 50 million U.S. homes have three or more televisions.

267

Trade-Off Between Consumption Growth and Inequality: Theory and Evidence for Germany  

E-Print Network (OSTI)

This paper examines the structure and evolution of consumption inequality. Once heterogeneous agents relate their neighbors ’ consumption to their own, consumption volatility and inequality are affected. The model predicts a positive relationship between the group specific average consumption growth and within-group inequality, which is empirically confirmed using survey data from the German Socio-Economic Panel (GSOEP) covering the period 1984-2005. Age and household size are crucial for within-group inequality, as young and/or small households are more sensitive to income and consumption shocks. The data also shows increases of within-group inequality directly after the reunification and the introduction of the euro. Preliminary! Keywords: consumption inequality, consumption growth, German Socio-Economic Panel,

Runli Xie; Jel Codes E

2009-01-01T23:59:59.000Z

268

Comparative analysis of energy data bases for household residential and transportation energy use  

SciTech Connect

Survey data bases covering household residential and transportation energy use were reviewed from the perspective of energy policy analysts and data base users. Twenty-three surveys, taken from 1972 to 1985, collected information on household energy consumption and expenditures, energy-using capital stock, and conservation activities. Ten of the surveys covered residential energy use only, including that for space heating and cooling, cooking, water heating, and appliances. Six surveys covered energy use only for household travel in personal vehicles. Seven surveys included data on both of these household energy sectors. Complete energy use data for a household in one year can be estimated only for 1983, using two surveys (one residential and one transportation) taken in the same households. The last nine surveys of the 23 were recent (1983--1985). Review of those nine was based on published materials only. The large-scale surveys generally had less-comprehensive data, while the comprehensive surveys were based on small samples. The surveys were timely and useful for analyzing four types of energy policies: economic regulation, environmental regulation, federal energy production, and direct regulation of energy consumption or production. Future surveys of energy use, such as those of residential energy consumption, should try to link their energy-use questions to large surveys, such as the American Housing Survey, to allow more accurate analysis of comparative impacts of energy policies among population categories of interest (e.g., minority/majority, metropolitan/nonmetropolitan area, census regions, and income class). 78 refs., 9 figs., 29 tabs.

Teotia, A.; Klein, Y.; LaBelle, S.

1988-11-01T23:59:59.000Z

269

Patterns of rural household energy use: a study in the White Nile province - the Sudan  

Science Conference Proceedings (OSTI)

The study investigates rural household domestic energy consumption patterns in a semiarid area of the Sudan. It describes the socioeconomic and evironmental context of energy use, provides an estimation of local woody biomass production and evaluates ecological impacts of increased energy demand on the local resource base. It is based on findings derived from field surveys, a systematic questionnaire and participant observations. Findings indicate that households procure traditional fuels by self-collection and purchases. Household members spent on average 20% of their working time gathering fuels. Generally per caput and total annual expenditure and consumption of domestic fuels are determined by household size, physical availability, storage, prices, income, conservation, substitution and competition among fuel resource uses. Households spend on average 16% of their annual income on traditional fuels. Aggregation of fuels on heat equivalent basis and calculation of their contribution shows that on average firewood provides 63%, charcoal 20.7%, dung 10.4%, crop residues 3.4% and kerosene/diesel 2.5% of the total demand for domestic purposes. Estimated total household woodfuel demand exceeds woody biomass available from the local forests. This demand is presently satisfied by a net depletion of the local forests and purchases from other areas. Degradation of the resource base is further exacerbated by development of irrigation along the White Nile River, increasing livestock numbers (overgrazing) and forest clearance for rainfed cultivation. The most promising relevant and appropriate strategies to alleviate rural household domestic energy problems include: conservation of the existing forest, augmentation through village woodlots and community forestry programmes and improvements in end-use (stoves) and conversion (wood to charcoal) technologies.

Abdu, A.S.E.

1985-01-01T23:59:59.000Z

270

Predicting summer energy consumption from homeowners attitudes  

SciTech Connect

Two surveys examined the relationship between homeowners attitudes toward energy use and their actual summer electric consumption. In Survey 1, 56 couples filled out questionnaires concerning their energy attitudes. A factor analysis of their responses revealed four factors: comfort and health concerns, effort to conserve and monetary savings, role of the individual, and legitimacy of the energy crisis. The factors were entered into a multiple regression analysis to predict actual summer electric consumption. The attitudinal factors together significantly accounted for 55% of the variance in summer electric consumption. The comfort and health factor by itself explained 30% of the consumption variance. Survey 2, consisting of 69 couples, was conducted to elaborate the meaning of the factors. The results of the factor analysis of Survey 2 revealed six factors: comfort, health, individual's role, belief in science, legitimacy of the energy crisis, and effort to conserve. An overall regression analysis showed that the factors significantly explained nearly 60% of the summer consumption variance. The comfort factor was again the best predictor of summer electric consumption, accounting for 42% of the variance. It was concluded that attitudes about one's comfort are significantly related to household energy consumption (primarily air conditioning). The implications for energy conservation campaigns were discussed. 10 references, 3 tables.

Seligman, C.; Kriss, M.; Darley, J.M.; Fazio, R.H.; Becker, L.J.; Pryor, J.B.

1979-01-01T23:59:59.000Z

271

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities >Table 7a Glossary U.S. Residential Housing Primary Page Last Revised: July 2009

272

Nationwide Survey on Household Energy Use  

U.S. Energy Information Administration (EIA)

4 ~ Apartment in house or building divided into 2, 3, or 4 apartments ... of your family (living in your household). Include income from all sources--before taxes

273

Alston S. Householder Fellowship | Careers | ORNL  

NLE Websites -- All DOE Office Websites (Extended Search)

in Scientific Computing honors Dr. Alston S. Householder, founding Director of the Mathematics Division (now Computer Science and Mathematics Division) at the Oak Ridge National...

274

Home > Households, Buildings & Industry > Energy Efficiency ...  

U.S. Energy Information Administration (EIA)

Glossary Home > Households, Buildings & Industry > Energy Efficiency > Residential Buildings Energy Intensities > Table 4 Total Square Feet of U.S. Housing Units

275

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities > Table 5c Glossary U.S. Residential Housing Site Page Last Revised: July 2009

276

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities >Table 7b Glossary U.S. Residential Housing Primary Energy Intensity

277

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities > Table 8b Glossary U.S. Residential Buildings Primary Energy Intensity

278

The United States Government Configuration Baseline ...  

Science Conference Proceedings (OSTI)

... ITL). The United States Government Configuration Baseline (USGCB) - Windows Vista Firewall Content. Warning Notice. ...

2013-08-02T23:59:59.000Z

279

The United States Government Configuration Baseline ...  

Science Conference Proceedings (OSTI)

... Laboratory (ITL). The United States Government Configuration Baseline (USGCB) - Windows 7 Content. Warning Notice. Do ...

2013-08-02T23:59:59.000Z

280

homeoffice_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

1a. Home Office Equipment by South Census Region, 1a. Home Office Equipment by South Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ......................................... 96.2 34.6 18.4 6.0 10.1 1.2 Personal Computers 1 ................................. 60.0 20.7 11.7 3.2 5.8 4.0 Number of Desktop PCs 1 ................................................................ 45.1 15.5 8.6 2.6 4.3 4.9 2 or more ................................................... 9.1 3.1 2.0 0.4 0.7 9.6 Number of Laptop PCs

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Electricity Prices for Households - EIA  

Gasoline and Diesel Fuel Update (EIA)

Households for Selected Countries1 Households for Selected Countries1 (U.S. Dollars per Kilowatthour) Country 2001 2002 2003 2004 2005 2006 2007 2008 2009 Argentina NA NA NA NA NA NA 0.023 NA NA Australia 0.091 0.092 0.094 0.098 NA NA NA NA NA Austria 0.144 0.154 0.152 0.163 0.158 0.158 0.178 0.201 NA Barbados NA NA NA NA NA NA NA NA NA Belgium NA NA NA NA NA NA NA NA NA Bolivia NA NA NA NA NA NA NA NA NA Brazil NA NA NA NA NA NA 0.145 0.171 NA Canada 0.067 0.069 0.070 0.071 0.076 0.078 NA NA NA Chile NA NA NA NA NA NA 0.140 0.195 NA China NA NA NA NA NA NA NA NA NA Chinese Taipei (Taiwan) 0.075 0.071 0.074 0.076 0.079 0.079 0.080 0.086 NA Colombia NA NA NA NA NA NA 0.111 0.135 NA

282

homeoffice_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2a. Home Office Equipment by Year of Construction, 2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.4 1.1 1.1 1.2 1.2 1.0 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Households Using Office Equipment .......................... 96.2 14.9 16.7 17.0 12.2 13.0 22.4 4.4 Personal Computers 2 ................... 60.0 11.0 11.6 10.3 7.2 7.8 12.0 5.3 Number of Desktop PCs 1 .................................................. 45.1 8.0 9.0 7.7 5.3 6.1 9.1 5.8 2 or more .................................... 9.1 1.8 1.6 2.0 1.1 1.0 1.6 11.8 Number of Laptop PCs 1 ..................................................

283

ac_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2001 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditioning Equipment ...................... 82.9 4.9 6.0 7.4 6.2 2.4 Air Conditioners Not Used ........................... 2.1 0.1 0.8 Q 0.1 23.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 4.7 5.2 7.4 6.1 2.6 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 1.3 3.9 6.2 5.7 6.7 Without a Heat Pump ................................ 46.2 1.2 3.2 5.5 3.8 8.1 With a Heat Pump ..................................... 11.3 Q 0.8 0.6 1.9 14.7 Room Air-Conditioning ................................ 23.3 3.4 1.2 1.2 0.3 13.6 1 Unit

284

homeoffice_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

a. Home Office Equipment by Climate Zone, a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.2 1.1 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.9 Households Using Office Equipment .......................... 96.2 8.4 26.2 21.1 19.0 21.5 7.8 Personal Computers 2 ................... 60.0 5.7 16.7 13.1 12.1 12.6 7.4 Number of Desktop PCs 1 .................................................. 45.1 4.2 12.8 9.6 8.8 9.6 7.8 2 or more .................................... 9.1 0.8 2.4 2.3 2.0 1.7 12.1 Number of Laptop PCs 1 ..................................................

285

The dubuque electricity portal: evaluation of a city-scale residential electricity consumption feedback system  

Science Conference Proceedings (OSTI)

This paper describes the Dubuque Electricity Portal, a city-scale system aimed at supporting voluntary reductions of electricity consumption. The Portal provided each household with fine-grained feedback on its electricity use, as well as using incentives, ... Keywords: behavior change, consumption feedback systems, ecf, electricity, smart meters, social comparison, sustainability

Thomas Erickson; Ming Li; Younghun Kim; Ajay Deshpande; Sambit Sahu; Tian Chao; Piyawadee Sukaviriya; Milind Naphade

2013-04-01T23:59:59.000Z

286

The dubuque water portal: evaluation of the uptake, use and impact of residential water consumption feedback  

Science Conference Proceedings (OSTI)

The Dubuque Water Portal is a system aimed at supporting voluntary reductions of water consumption that is intended to be deployed city-wide. It provides each household with fine-grained, near real time feedback on their water consumption, as well as ... Keywords: behavior change, games, smart meters, social comparison, sustainability, water, water and energy feedback systems

Thomas Erickson; Mark Podlaseck; Sambit Sahu; Jing D. Dai; Tian Chao; Milind Naphade

2012-05-01T23:59:59.000Z

287

Alternative scenarios of green consumption in Italy: An empirically grounded model  

Science Conference Proceedings (OSTI)

Any transition towards a more environmentally sustainable world will strongly depend on people's willingness to adopt the best available practices. We present here the Consumption Italy (CITA) model, an empirically grounded agent-based model designed ... Keywords: Agent-based-modelling, Carbon footprint, Environmental policies, Household consumption

Giangiacomo Bravo, Elena Vallino, Alessandro K. Cerutti, Maria Beatrice Pairotti

2013-09-01T23:59:59.000Z

288

Operational energy consumption and GHG emissions in residential sector in urban China : an empirical study in Jinan  

E-Print Network (OSTI)

Driven by rapid urbanization and increasing household incomes, residential energy consumption in urban China has been growing steadily in the past decade, posing critical energy and greenhouse gas emission challenges. ...

Zhang, Jiyang, M.C.P. Massachusetts Institute of Technology

2010-01-01T23:59:59.000Z

289

Approaches for Monitoring and Reduction of Energy Consumption in the Home  

E-Print Network (OSTI)

By now, energy consumption in the home or even for single devices has not been monitored widely, except for billing and accounting reasons. Consumers are not able to track individual load profiles, therefore positive or negative trends in consumption were not noticed immediately. This work is based on the importance of direct feedback and its savings potential in terms of energy consumption: If you can’t measure it, you can’t improve it. We compare various monitoring approaches such as metering on device level, smart meters and non intrusive load monitoring of electrical devices. Furthermore, the In a world of highly developed countries and emerging economics, energy supply plays a major role. In a modern household, hardly any device runs without electricity. Load profiles are the overlay of a household’s energy demand. Consumers are not able to keep track of individual energy consumption. The basic idea of this work is: If you

Faculty Of Informatics; Tobias Hochwallner; Lukas Lang

2009-01-01T23:59:59.000Z

290

Characterization of household waste in Greenland  

Science Conference Proceedings (OSTI)

The composition of household waste in Greenland was investigated for the first time. About 2 tonnes of household waste was sampled as every 7th bag collected during 1 week along the scheduled collection routes in Sisimiut, the second largest town in Greenland with about 5400 inhabitants. The collection bags were sorted manually into 10 material fractions. The household waste composition consisted primarily of biowaste (43%) and the combustible fraction (30%), including anything combustible that did not belong to other clean fractions as paper, cardboard and plastic. Paper (8%) (dominated by magazine type paper) and glass (7%) were other important material fractions of the household waste. The remaining approximately 10% constituted of steel (1.5%), aluminum (0.5%), plastic (2.4%), wood (1.0%), non-combustible waste (1.8%) and household hazardous waste (1.2%). The high content of biowaste and the low content of paper make Greenlandic waste much different from Danish household waste. The moisture content, calorific value and chemical composition (55 elements, of which 22 were below detection limits) were determined for each material fraction. These characteristics were similar to what has been found for material fractions in Danish household waste. The chemical composition and the calorific value of the plastic fraction revealed that this fraction was not clean but contained a lot of biowaste. The established waste composition is useful in assessing alternative waste management schemes for household waste in Greenland.

Eisted, Rasmus, E-mail: raei@env.dtu.dk [Department of Environmental Engineering, Technical University of Denmark, Kongens Lyngby (Denmark); Christensen, Thomas H. [Department of Environmental Engineering, Technical University of Denmark, Kongens Lyngby (Denmark)

2011-07-15T23:59:59.000Z

291

Factors of material consumption  

E-Print Network (OSTI)

Historic consumption trends for materials have been studied by many researchers, and, in order to identify the main drivers of consumption, special attention has been given to material intensity, which is the consumption ...

Silva Díaz, Pamela Cristina

2012-01-01T23:59:59.000Z

292

appl_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

9a. Appliances by Northeast Census Region, 9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1 .............................................................. 95.2 18.2 13.3 4.9 1.1 2 or More ................................................. 6.5 1.4 1.1 0.3 11.7 Most Used Oven ...................................... 101.7 19.6 14.5 5.2 1.1 Electric .....................................................

293

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

1a. Space Heating by South Census Region, 1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home ....................................... 1.0 Q Q Q Q 20.1 No Heating Equipment ................................ 0.5 Q Q Q Q 39.8 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q Q 39.0 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0

294

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

9a. Space Heating by Northeast Census Region, 9a. Space Heating by Northeast Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 20.3 14.8 5.4 NE Heat Home .................................................... 106.0 20.1 14.7 5.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.9 No Heating Equipment ................................ 0.5 Q Q Q 39.5 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.7 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 20.1 14.7 5.4 NE Natural Gas .................................................

295

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

0a. Space Heating by Midwest Census Region, 0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No Heating Equipment ................................ 0.5 Q Q Q 39.2 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.4 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 24.5 17.1 7.4 NE Natural Gas

296

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2a. Space Heating by West Census Region, 2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment ................................ 0.5 0.4 Q 0.4 18.1 Have Equipment But Do Not Use It ............................................... 0.4 0.2 Q 0.2 27.5 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 22.6 6.7 15.9 NE Natural Gas .................................................

297

appl_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2a. Appliances by West Census Region, 2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1 .............................................................. 95.2 20.9 6.4 14.5 1.1 2 or More ................................................. 6.5 1.2 0.2 1.0 14.6 Most Used Oven ...................................... 101.7 22.1 6.6 15.5 1.1 Electric .....................................................

298

2 The Financial and Economic Crises: Implications for Consumer Finance and for Households in Michigan  

E-Print Network (OSTI)

IPPSR and MSUE at Michigan State University for financial support. This paper was partially written while a Visiting Scholar at the National Poverty Center at the University of Michigan, and its Michigan is an epicenter of the recent economic and financial crises. Median personal income was 8 percent above the national average at the beginning of the decade and was 8 percent below the national average by the end of it. Between 2008 and 2009, personal income fell for the first time since 1958. Rates of unemployment and foreclosure activity remain high and above the national average. Indeed, the Michigan economy is changing in dramatic and important ways, but there is little information on household responses to this changing environment. How are Michigan households responding to economic and financial shocks? Are they smoothing income, consumption, or both? What mechanisms are they using to achieve these outcomes? On which factors does the degree of adjustment depend? Using data collected from recent household surveys,

Lisa D. Cook; Lisa D. Cook; Ann Marie Schneider; Lauren Meunier; Lisa D. Cook

2010-01-01T23:59:59.000Z

299

Baseline LAW Glass Formulation Testing  

Science Conference Proceedings (OSTI)

The major objective of the baseline glass formulation work was to develop and select glass formulations that are compliant with contractual and processing requirements for each of the LAW waste streams. Other objectives of the work included preparation and characterization of glasses with respect to the properties of interest, optimization of sulfate loading in the glasses, evaluation of ability to achieve waste loading limits, testing to demonstrate compatibility of glass melts with melter materials of construction, development of glass formulations to support ILAW qualification activities, and identification of glass formulation issues with respect to contract specifications and processing requirements.

Kruger, Albert A. [USDOE Office of River Protection, Richland, WA (United States); Mooers, Cavin [The Catholic University of America, Washington, DC (United States). Vitreous State Lab.; Bazemore, Gina [The Catholic University of America, Washington, DC (United States). Vitreous State Lab; Pegg, Ian L. [The Catholic University of America, Washington, DC (United States). Vitreous State Lab; Hight, Kenneth [The Catholic University of America, Washington, DC (United States). Vitreous State Lab; Lai, Shan Tao [The Catholic University of America, Washington, DC (United States). Vitreous State Lab; Buechele, Andrew [The Catholic University of America, Washington, DC (United States). Vitreous State Lab; Rielley, Elizabeth [The Catholic University of America, Washington, DC (United States). Vitreous State Lab; Gan, Hao [The Catholic University of America, Washington, DC (United States). Vitreous State Lab; Muller, Isabelle S. [The Catholic University of America, Washington, DC (United States). Vitreous State Lab; Cecil, Richard [The Catholic University of America, Washington, DC (United States). Vitreous State Lab

2013-06-13T23:59:59.000Z

300

All Consumption Tables  

U.S. Energy Information Administration (EIA)

2010 Consumption Summary Tables. Table C1. Energy Consumption Overview: Estimates by Energy Source and End-Use Sector, 2010 (Trillion Btu) ... Ranked by State, 2010

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Residential Energy Consumption Survey: Consumption and expenditures, April 1984 through March 1985: Part 2, Regional data. [Contains glossary  

SciTech Connect

Included here are data at the Census region and division level on consumption of and expenditures for the major fuels used in residential households - electricity, natural gas, fuel oil/kerosene, and liquefied petroleum gas (LPG). Data are also presented on wood consumption. Section 1 of this report contains data on the average amount of energy consumed per household for space heating in 1984 and the corresponding expenditures. Sections 2 through 7 summarize the energy consumption and expenditure patterns. Appendices A through D contain information on how the survey was conducted, estimates of the size of the housing unit in square feet and the quality of the data. Procedures for calculating relative standard errors (RSE) are located in Appendix C, Quality of the Data. Procedures for estimating the end-use statistics are located in Appendix D. Census and weather maps, and related publications are located in Appendices E through G.

Not Available

1987-05-13T23:59:59.000Z

302

Use of electricity billing data to determine household energy use fingerprints  

Science Conference Proceedings (OSTI)

Ways to analyze billing data are discussed. The starting point for these analyses is a method developed at Princeton University. Their Scorekeeping model permits decomposition of total household energy use into its weather- and nonweather-sensitive elements; the weather-sensitive portion is assumed proportional to heating degree days. The Scorekeeping model also allows one to compute weather-adjusted energy consumption for each household based on its billing data and model parameters; this is the model's estimate of annual consumption under long-run weather conditions. The methods discussed here extend the Scorekeeping results to identify additional characteristics of household energy use. In particular, the methods classify households in terms of the intensity with which the particular fuel is used for space heating (primary heating fuel vs supplemental heating fuel vs no heating at all with the fuel). In addition, households that use the particular fuel for air conditioning are identified. In essence, the billing data and model results are used to determine household energy use fingerprints. The billing data and model results can also be used to identify and correct anomalous bills. The automated method discussed here identifies anomalously high or low utility bills, which are then dropped before re-estimation of the Scorekeeping model parameters. Alternatively, a pair of bills may be combined if one is very high and a temporally adjacent bill is very low. The Scorekeeping model is then re-estimated after the two bills are combined into one. The methods permit careful examination and analysis of changes in energy use from one year to another.

Hirst, E.; Goeltz, R.; White, D.

1984-08-01T23:59:59.000Z

303

Mitigating Carbon Emissions: the Potential of Improving Efficiencyof Household Appliances in China  

SciTech Connect

China is already the second's largest energy consumer in the world after the United States, and its demand for energy is expected to continue to grow rapidly in the foreseeable future, due to its fast economic growth and its low level of energy use per capita. From 2001 to 2005, the growth rate of energy consumption in China has exceeded the growth rate of its economy (NBS, 2006), raising serious concerns about the consequences of such energy use on local environment and global climate. It is widely expected that China is likely to overtake the US in energy consumption and greenhouse gas (GHG) emissions during the first half of the 21st century. Therefore, there is considerable interest in the international community in searching for options that may help China slow down its growth in energy consumption and GHG emissions through improving energy efficiency and adopting more environmentally friendly fuel supplies such as renewable energy. This study examines the energy saving potential of three major residential energy end uses: household refrigeration, air-conditioning, and water heating. China is already the largest consumer market in the world for household appliances, and increasingly the global production base for consumer appliances. Sales of household refrigerators, room air-conditioners, and water heaters are growing rapidly due to rising incomes and booming housing market. At the same time, the energy use of Chinese appliances is relatively inefficient compared to similar products in the developed economies. Therefore, the potential for energy savings through improving appliance efficiency is substantial. This study focuses particularly on the impact of more stringent energy efficiency standards for household appliances, given that such policies are found to be very effective in improving the efficiency of household appliances, and are well established both in China and around world (CLASP, 2006).

Lin, Jiang

2006-07-10T23:59:59.000Z

304

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

affordable, and reliable energy services and products to consumption of energy, goods, and services by  California consumption of energy, goods, and services by  California 

Masanet, Eric

2010-01-01T23:59:59.000Z

305

Probit Model Estimation Revisited: Trinomial Models of Household Car Ownership  

E-Print Network (OSTI)

Household Ownership of Car Davidon, W. C. (1959) VariableStudy Report 9: Models of Car Ownership and License Holding.Trinomial Models of Household Car Ownership. Transportation

Bunch, David S.; Kitamura, Ryuichi

1991-01-01T23:59:59.000Z

306

Modeling patterns of hot water use in households  

E-Print Network (OSTI)

7 No Dishwashers . . . . . . . .to households without dishwashers. no_cw is only applied towasher; the absence of a dishwasher; a household consisting

Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

1996-01-01T23:59:59.000Z

307

Baseline Ozone Results from 1923 to 1955  

Science Conference Proceedings (OSTI)

Baseline total atmospheric ozone values have been derived, using the Chappuis band, from historical data for 11 Smithsonian sites, including both Northern and Southern Hemispheres. The main baselines consist of 1194 and 970 days respectively for ...

Ronald J. Angione; Robert G. Roosen

1983-08-01T23:59:59.000Z

308

Baseline Test Specimen Machining Report  

SciTech Connect

The Next Generation Nuclear Plant (NGNP) Project is tasked with selecting a high temperature gas reactor technology that will be capable of generating electricity and supplying large amounts of process heat. The NGNP is presently being designed as a helium-cooled high temperature gas reactor (HTGR) with a large graphite core. The graphite baseline characterization project is conducting the research and development (R&D) activities deemed necessary to fully qualify nuclear-grade graphite for use in the NGNP reactor. Establishing nonirradiated thermomechanical and thermophysical properties by characterizing lot-to-lot and billet-to-billet variations (for probabilistic baseline data needs) through extensive data collection and statistical analysis is one of the major fundamental objectives of the project. The reactor core will be made up of stacks of graphite moderator blocks. In order to gain a more comprehensive understanding of the varying characteristics in a wide range of suitable graphites, any of which can be classified as “nuclear grade,” an experimental program has been initiated to develop an extensive database of the baseline characteristics of numerous candidate graphites. Various factors known to affect the properties of graphite will be investigated, including specimen size, spatial location within a graphite billet, specimen orientation within a billet (either parallel to [P] or transverse to [T] the long axis of the as-produced billet), and billet-to-billet variations within a lot or across different production lots. Because each data point is based on a certain position within a given billet of graphite, particular attention must be paid to the traceability of each specimen and its spatial location and orientation within each billet. The evaluation of these properties is discussed in the Graphite Technology Development Plan (Windes et. al, 2007). One of the key components in the evaluation of these graphite types will be mechanical testing on specimens drawn from carefully controlled sections of each billet. To this end, this report will discuss the machining of the first set of test specimens that will be evaluated in this program through tensile, compressive, and flexural testing. Validation that the test specimens have been produced to the tolerances required by the applicable ASTM standards, and to the quality control levels required by this program, will demonstrate the viability of sending graphite to selected suppliers that will provide valuable and certifiable data to future data sets that are integral to the NGNP program and beyond.

mark Carroll

2009-08-01T23:59:59.000Z

309

Urban household energy use in Thailand  

SciTech Connect

Changes in household fuel and electricity use that accompany urbanization in Third World countries bear large economic and environmental costs. The processes driving the fuel transition, and the policy mechanisms by which it can be influenced, need to be better understood for the sake of forecasting and planning, especially in the case of electricity demand. This study examines patterns of household fuel use and electrical appliance utilization in Bangkok, Chieng Mai and Ayutthaya, Thailand, based on the results of a household energy survey. Survey data are statistically analyzed using a variety of multiple regression techniques to evaluate the relative influence of various household and fuel characteristics on fuel and appliance choice. Results suggest that changes to the value of women's time in urban households, as women become increasingly active in the labor force, have a major influence on patterns of household energy use. The use of the home for small-scale commercial activities, particularly food preparation, also has a significant influence on fuel choice. In general, household income does not prove to be an important factor in fuel and appliance selection in these cities, although income is closely related to total electricity use. The electricity use of individual household appliances is also analyzed using statistical techniques as well as limited direct metering. The technology of appliance production in Thailand is evaluated through interviews with manufacturers and comparisons of product performance. These data are used to develop policy recommendations for improving the efficiency of electrical appliances in Thailand by relying principally on the dynamism of the consumer goods market, rather than direct regulation. The annual electricity savings from the recommended program for fostering rapid adoption of efficient technologies are estimated to reach 1800 GWh by the year 2005 for urban households alone.

Tyler, S.R.

1992-01-01T23:59:59.000Z

310

Electricity Consumption Electricity Consumption EIA Electricity Consumption Estimates  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Consumption Consumption Electricity Consumption EIA Electricity Consumption Estimates (million kWh) National Petroleum Council Assumption: The definition of electricity con- sumption and sales used in the NPC 1999 study is the equivalent ofwhat EIA calls "sales by utilities" plus "retail wheeling by power marketers." This A nn u al Gro wth total could also be called "sales through the distribution grid," 2o 99 99 to Sales by Utilities -012% #N/A Two other categories of electricity consumption tracked by EIA cover on site Retail Wheeling Sales by generation for host use. The first, "nonutility onsite direct use," covers the Power Marketen 212.25% #N/A traditional generation/cogeneration facilities owned by industrial or large All Sales Through Distribution

311

Consumption Moment Risk Factors and Cross-Section of Long-Run Stock Returns  

E-Print Network (OSTI)

We introduce the multifactor asset pricing model that includes as risk factors the …ve Chen et al. (1986) macroeconomic variables along with the rates of change in the …rst four cross-sectional consumption moments. The empirical evidence on the pricing of the economic state variables is sensitive to the experimental design, whereas we …nd strong evidence that with the limited participation of households in the capital markets the aggregate consumption risk (measured by the rate of change in average consumption) and the background risk in consumption (measured jointly by the rates of change in the higher-order consumption moments) are both signi…cantly priced. JEL classi…cation: G12

Andrei Semenov

2011-01-01T23:59:59.000Z

312

Consumption Technical Notes  

U.S. Energy Information Administration (EIA)

as street lighting and public services; and the Manufacturing Energy Consumption Survey covers only manufacturing establishments,

313

Pinellas Plant Environmental Baseline Report  

Science Conference Proceedings (OSTI)

The Pinellas Plant has been part of the Department of Energy`s (DOE) nuclear weapons complex since the plant opened in 1957. In March 1995, the DOE sold the Pinellas Plant to the Pinellas County Industry Council (PCIC). DOE has leased back a large portion of the plant site to facilitate transition to alternate use and safe shutdown. The current mission is to achieve a safe transition of the facility from defense production and prepare the site for alternative uses as a community resource for economic development. Toward that effort, the Pinellas Plant Environmental Baseline Report (EBR) discusses the current and past environmental conditions of the plant site. Information for the EBR is obtained from plant records. Historical process and chemical usage information for each area is reviewed during area characterizations.

Not Available

1997-06-01T23:59:59.000Z

314

appl_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

a. Appliances by Climate Zone, a. Appliances by Climate Zone, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.1 Total .................................................. 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Kitchen Appliances Cooking Appliances Oven .............................................. 101.7 9.1 27.9 23.1 19.4 22.2 7.8 1 ................................................... 95.2 8.7 26.0 21.6 17.7 21.2 7.9 2 or More ..................................... 6.5 0.4 1.9 1.5 1.7 1.0 14.7 Most Used Oven ........................... 101.7 9.1 27.9 23.1 19.4 22.2

315

appl_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

4a. Appliances by Type of Housing Unit, 4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.6 1.9 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 69.1 9.4 16.7 6.6 4.3 1 ................................................ 95.2 63.7 8.9 16.2 6.3 4.3 2 or More .................................. 6.5 5.4 0.4 0.4 0.2 15.9 Most Used Oven ........................ 101.7 69.1 9.4 16.7 6.6 4.3 Electric ...................................... 63.0 43.3 5.2 10.9 3.6

316

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

8a. Space Heating by Urban/Rural Location, 8a. Space Heating by Urban/Rural Location, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.6 0.9 1.3 1.3 1.2 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.3 Heat Home .................................................... 106.0 49.1 18.0 21.2 17.8 4.3 Do Not Heat Home ....................................... 1.0 0.7 0.1 0.1 0.1 25.8 No Heating Equipment ................................ 0.5 0.4 0.1 Q 0.1 33.2 Have Equipment But Do Not Use It ............................................... 0.4 0.3 Q Q Q 30.2 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 49.1 18.0 21.2 17.8 4.3 Natural Gas

317

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

5a. Space Heating by Type of Owner-Occupied Housing Unit, 5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.4 1.9 3.0 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Heat Home ..................................... 72.4 63.0 2.0 1.7 5.7 6.7 Do Not Heat Home ........................ 0.4 0.2 Q Q Q 46.2 No Heating Equipment .................. 0.3 0.2 Q Q Q 39.0 Have Equipment But Do Not Use It ................................ Q Q Q Q Q NF Main Heating Fuel and Equipment (Have and Use Equipment) ............ 72.4 63.0 2.0 1.7 5.7 6.7 Natural Gas

318

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2a. Space Heating by Year of Construction, 2a. Space Heating by Year of Construction, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.5 1.1 1.1 1.1 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Heat Home ..................................... 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Do Not Heat Home ........................ 1.0 Q Q Q 0.2 0.3 Q 23.2 No Heating Equipment .................. 0.5 Q Q Q 0.2 Q Q 30.3 Have Equipment But Do Not Use It ................................ 0.4 Q Q Q Q Q Q 37.8 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Natural Gas ...................................

319

appl_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

5a. Appliances by Type of Owner-Occupied Housing Unit, 5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.3 0.4 2.1 3.1 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Kitchen Appliances Cooking Appliances Oven ........................................... 68.3 59.1 2.0 1.7 5.4 7.0 1 ................................................ 62.9 54.1 2.0 1.6 5.2 7.1 2 or More .................................. 5.4 5.0 Q Q 0.2 22.1 Most Used Oven ........................ 68.3 59.1 2.0 1.7 5.4 7.0 Electric ......................................

320

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

4a. Space Heating by Type of Housing Unit, 4a. Space Heating by Type of Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.7 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.4 Heat Home ..................................... 106.0 73.4 9.4 16.4 6.8 4.5 Do Not Heat Home ........................ 1.0 0.3 Q 0.6 Q 19.0 No Heating Equipment .................. 0.5 0.2 Q 0.3 Q 24.2 Have Equipment But Do Not Use It ................................ 0.4 Q Q 0.3 Q 28.1 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 73.4 9.4 16.4 6.8 4.5 Natural Gas ...................................

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

appl_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

2a. Appliances by Year of Construction, 2a. Appliances by Year of Construction, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.5 1.2 1.1 1.2 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 1 ................................................ 95.2 13.1 16.3 16.6 12.1 12.7 24.3 4.4 2 or More .................................. 6.5 1.2 0.9 1.1 0.7 1.0 1.6 14.8 Most Used Oven ........................ 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 Electric ......................................

322

spaceheat_household2001.pdf  

U.S. Energy Information Administration (EIA) Indexed Site

6a. Space Heating by Type of Rented Housing Unit, 6a. Space Heating by Type of Rented Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Heat Home ..................................... 33.7 10.4 7.4 14.8 1.1 6.9 Do Not Heat Home ........................ 0.6 Q Q 0.5 Q 21.4 No Heating Equipment .................. 0.2 Q Q Q Q 84.5 Have Equipment But Do Not Use It ................................ 0.4 Q Q 0.3 Q 36.4 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 33.7 10.4 7.4 14.8 1.1 6.9 Natural Gas ...................................

323

A statistical analysis of structural differences in minority household electricity demand  

SciTech Connect

In this paper, the structures for electricity demand in non-Latino Black and White households are compared. Electricity demand will be analyzed within the context of a complete demand system, and statistical tests for structural differences will be systematically conducted in the hope of pinpointing the location of differences within the context of this model. Structural differences in demand are defined as statistically significant differences in a parameter or group of parameters that identify the quantitative relationship between explanatory variables and electricity consumption. Along with population taste differences, which might emanate from historical and cultural population differences, structural differences might also occur because of differences in housing and geographic patterns and as a result of differences in access to markets and information. As a consequence, energy consumption decisions will differ, and the level and composition of energy consumption are likely to vary. In practice, it is nearly impossible to untangle the causes contributing to structural differences, but it is reasonably easy to test for statistical differences. The superficial evidence indicates there is a strong likelihood that structural differences do exist in electricity demand between White and Black households. The null hypothesis, which states that there exist no differences in the structures for electricity demand for Black and White households, is tested.

Poyer, D.A.; Earl, E.

1994-09-01T23:59:59.000Z

324

Energy-related attitude/belief variables in conventional econometric equations: An empirical approach applied to residential energy consumption. Doctoral thesis  

Science Conference Proceedings (OSTI)

The study analyzes a subsample of 523 households from the 1975 Lifestyles and Household Energy Use Survey conducted for the Washington Center for Metropolitan Studies. The study explores the empirical relationship between a set of four Energy-Related Attitude/Belief (ERAB) variables, household electricity and natural gas consumption, and three Energy-Related Discrete Choice (ERDC) variables. Using principal components factor analysis, the ERAB variables were constructed from a portion of the survey responses dealing with what households felt should be done to handle current or future energy shortages. A key finding of the study is that in the context of a conventional econometric specification of electricity and natural gas consumption, ERAB variables are statistically significant, although less significant than conventional explanatory variables for household energy consumption.

Wetzel, B.M.

1988-10-01T23:59:59.000Z

325

U.S. Household Electricity Report  

Reports and Publications (EIA)

Brief analysis reports on the amount of electricity consumed annually by U.S. households for each of several end uses, including space heating and cooling, water heating, lighting, and the operation of more than two dozen appliances.

Barbara Fichman

2005-07-14T23:59:59.000Z

326

Household energy handbook: an interim guide and reference manual. World Bank technical paper. Manuel d'energie domestique: memento et guide interimaire  

Science Conference Proceedings (OSTI)

A standard framework for measuring and assessing technical information on the household energy sources in developing countries is needed. This handbook is intended as a first step toward creating such a framework. Chapter 1 discusses energy terms and principals underlying the energy units, definitions, and calculations presented in the following chapters. Chapter 2 describes household consumption patterns and their relationship to income, location and household use variables. Chapter 3 evaluates energy end-uses and the technologies that provide cooking, lighting, refrigeration, and space heating services. Chapter 4 examines household energy resources and supplies, focusing on traditional biomass fuels. Finally, Chapter 5 demonstrates simple assessment methods and presents case studies to illustrate how household energy data can be used in different types of assessments.

Leach, G.; Gowen, M.

1989-01-01T23:59:59.000Z

327

Fuel Consumption - Energy Information Administration  

U.S. Energy Information Administration (EIA)

The Energy Information Administration, Residential Energy Consumption Survey(RTECS), 1994 Fuel Consumption

328

Baseline Graphite Characterization: First Billet  

SciTech Connect

The Next Generation Nuclear Plant Project Graphite Research and Development program is currently establishing the safe operating envelope of graphite core components for a very high temperature reactor design. To meet this goal, the program is generating the extensive amount of quantitative data necessary for predicting the behavior and operating performance of the available nuclear graphite grades. In order determine the in-service behavior of the graphite for the latest proposed designs, two main programs are underway. The first, the Advanced Graphite Creep (AGC) program, is a set of experiments that are designed to evaluate the irradiated properties and behavior of nuclear grade graphite over a large spectrum of temperatures, neutron fluences, and compressive loads. Despite the aggressive experimental matrix that comprises the set of AGC test runs, a limited amount of data can be generated based upon the availability of space within the Advanced Test Reactor and the geometric constraints placed on the AGC specimens that will be inserted. In order to supplement the AGC data set, the Baseline Graphite Characterization program will endeavor to provide supplemental data that will characterize the inherent property variability in nuclear-grade graphite without the testing constraints of the AGC program. This variability in properties is a natural artifact of graphite due to the geologic raw materials that are utilized in its production. This variability will be quantified not only within a single billet of as-produced graphite, but also from billets within a single lot, billets from different lots of the same grade, and across different billets of the numerous grades of nuclear graphite that are presently available. The thorough understanding of this variability will provide added detail to the irradiated property data, and provide a more thorough understanding of the behavior of graphite that will be used in reactor design and licensing. This report covers the development of the Baseline Graphite Characterization program from a testing and data collection standpoint through the completion of characterization on the first billet of nuclear-grade graphite. This data set is the starting point for all future evaluations and comparisons of material properties.

Mark C. Carroll; Joe Lords; David Rohrbaugh

2010-09-01T23:59:59.000Z

329

TERMS OF REFERENCE Baseline Study of Bari Imam Colony  

E-Print Network (OSTI)

This is the thirteenth year that Plan is operating in Pakistan. It has three program units based in the districts of Chakwal and Vehari in the Province of Punjab and the squatter settlements of Islamabad (the capital city). Plan Pakistan strives to reach out to as many children as possible through program such as Enabling Environment for Good Governance, The Right to Quality Education, Right to an Adequate Standard of Living, Right to health and health services and Mainstreaming Child-Centred Disaster Risk Management. Plan works in partnership first and foremost with children and their families, communities and their organizations, government departments and like-minded development agencies. About the Assignment Plan has intended to minimize the vulnerabilities of children living in Bari Imam Colony, Islamabad. This slum consists of approximately 3,000 households. Based on initial assessment Plan aims to engage local residents to take charge of activities, to generate internal and external resources, to sustain their development and to bring about changes in the quality of life of their children. Plan’s program interventions may bring intended and unintended results in lives of children. To asses the gravity of change a baseline study need to be in place before launching program in Bari Imam Colony. Overall purpose of the assignment Plan Pakistan wants consultant to Review the project document, objectives and indicators and conduct the baseline study of the community in the light of the project document with 95 % confidence interval. Methodology and procedures: The consultant/consulting organization will propose the detailed methodology to implement the said assignment; few key tasks are as under. 1. Review the Project documents and conduct meetings with the relevant Plan staff at Country Office and urban programme unit. 2. Prepare tools for the baseline (sampling methodology, questionnaire, data entry and analysis tool(s), etc.) 3. Pretesting and adjustment of the tools 4. Data collection, cleaning and analysis

unknown authors

2010-01-01T23:59:59.000Z

330

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

EIA household energy use data now includes detail on 16 States EIA household energy use data now includes detail on 16 States RECS 2009 - Release date: March 28, 2011 EIA is releasing new benchmark estimates for home energy use for the year 2009 that include detailed data for 16 States, 12 more than in past EIA residential energy surveys. EIA has conducted the Residential Energy Consumption Survey (RECS) since 1978 to provide data on home energy characteristics, end uses of energy, and expenses for the four Census Regions and nine Divisions. In 1997, EIA produced additional tabulations for the four most populous States (California, New York, Texas, and Florida). A threefold increase in the number of households included in the 2009 RECS offers more accuracy and coverage for understanding energy usage for all estimated States, Regions and Divisions.

331

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

Share of energy used by appliances and consumer electronics increases in Share of energy used by appliances and consumer electronics increases in U.S. homes RECS 2009 - Release date: March 28, 2011 Over the past three decades, the share of residential electricity used by appliances and electronics in U.S. homes has nearly doubled from 17 percent to 31 percent, growing from 1.77 quadrillion Btu (quads) to 3.25 quads. This rise has occurred while Federal energy efficiency standards were enacted on every major appliance, overall household energy consumption actually decreased from 10.58 quads to 10.55 quads, and energy use per household fell 31 percent. Federal energy efficiency standards have greatly reduced consumption for home heating Total energy use in all U.S. homes occupied as primary residences decreased slightly from 10.58 quads in 1978 to 10.55 quads in 2005 as reported by the

332

Do homeowners increase consumption after the last mortgage payment? An alternative test of the permanent income hypothesis  

E-Print Network (OSTI)

The maturity date of a mortgage loan marks the end of monthly mortgage payments for homeowners. In the period after the last payment, homeowners experience an increase in their monthly disposable income that is equal to the average monthly mortgage payment. Our study interprets this event as an anticipated increase in income, and analyzes consumption behavior over the transition period. In particular, we test whether households smooth consumption as predicted by the rational expectation Life-Cycle/Permanent Income Hypothesis (Re-LC/PIH). We find that they do. Households do not alter nondurable goods consumption in the period following the last mortgage payment despite the increase in disposable income.

Brahima Coulibaly; Geng Li

2006-01-01T23:59:59.000Z

333

UK Energy Consumption by Sector The energy consumption data consists...  

Open Energy Info (EERE)

Consumption by Sector The energy consumption data consists of five spreadsheets: "overall data tables" plus energy consumption data for each of the following...

334

Hanford site technical baseline data dictionary  

Science Conference Proceedings (OSTI)

The purpose of this Data Dictionary is to provide information concerning the structure and information contained in the Hanford Site Technical Baseline Database (HSTD).

Baynes, P.A. [Lockheed Martin Hanford Corp., Richland, WA (United States)

1997-04-30T23:59:59.000Z

335

Defining Information System For the Baseline Inventory | Department...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Defining Information System For the Baseline Inventory Defining Information System For the Baseline Inventory Defining Information System For the Baseline Inventory Defining...

336

Estimation of Energy Baseline by Simulation for On-going Commissioning and Energy Saving Retrofit  

E-Print Network (OSTI)

This paper proposes a method of estimating the adjusted energy baseline using simulation models, which can calculate the energy baseline with various conditions, such as conditions of weather, occupancy and equipment operations. Especially, this paper reveals what detailed data the calibration of the model needs and the change of accuracy caused by different calibration data. Using the operational data of a middle-scale office building in Osaka Japan, the simulation accuracies of three models, which are calibrated using monthly energy consumptions of whole building (Level 1), monthly energy consumptions of subsystems (Level 2) and the detailed operational data of equipments (Level 3) respectively, are compared. The result shows that the differences of daily-integrated energy consumptions between measured value and simulated value using the model of Level 1 and 2 are not much different. The model of Level 3 is about 3% more accurate than the model of Level 1 and 2.

Miyata, M.; Yoshida, H.; Asada, M.; Iwata, T.; Tanabe, Y.; Yanagisawa, T.

2006-01-01T23:59:59.000Z

337

Special Topics on Energy Use in Household Transportation  

U.S. Energy Information Administration (EIA) Indexed Site

Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home > Transportation Home Page > Special Topics Special Topics Change in Method for Estimating Fuel Economy for the 1988 and subsequent RTECS (Released 09/12/2000) Can Household Members Accurately Report How Many Miles Their Vehicles Are Driven? (Released 08/03/2000) Calculate your Regional Gasoline Costs of Driving using the “Transportation Calculator” updated for new model years! Choose your car or SUV and see the gasoline part of the cost of driving in various parts of the country using EIA's current weekly prices. This application uses DOE/EPA's Fuel Economy Guide to set the MPG, but you can change it to compare your estimate of your car's mpg to the average of everyone else who takes the test. (Released 04/11/2000; Updated Yearly for Fuel Economies and Weekly for Fuel Prices)

338

Connected Consumption: The hidden networks of consumption  

E-Print Network (OSTI)

In this paper, we present the Connected Consumption Network (CCN) that allows a community of consumers to collaboratively sense the market from a mobile device, enabling more informed financial decisions in geo-local ...

Reed, David P.

339

Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle  

NLE Websites -- All DOE Office Websites (Extended Search)

1: January 8, 1: January 8, 2007 Household Vehicle Trips to someone by E-mail Share Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Facebook Tweet about Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Twitter Bookmark Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Google Bookmark Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Delicious Rank Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Digg Find More places to share Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on AddThis.com... Fact #451: January 8, 2007 Household Vehicle Trips In a day, the average household traveled 32.7 miles in 2001 (the latest

340

Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle  

NLE Websites -- All DOE Office Websites (Extended Search)

2: October 3, 2: October 3, 2005 Household Vehicle Ownership to someone by E-mail Share Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Facebook Tweet about Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Twitter Bookmark Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Google Bookmark Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Delicious Rank Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Digg Find More places to share Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on AddThis.com... Fact #392: October 3, 2005 Household Vehicle Ownership Household vehicle ownership has changed significantly over the last 40

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

CSV File Documentation: Consumption  

Gasoline and Diesel Fuel Update (EIA)

Consumption Consumption The State Energy Data System (SEDS) comma-separated value (CSV) files contain consumption estimates shown in the tables located on the SEDS website. There are four files that contain estimates for all states and years. Consumption in Physical Units contains the consumption estimates in physical units for all states; Consumption in Btu contains the consumption estimates in billion British thermal units (Btu) for all states. There are two data files for thermal conversion factors: the CSV file contains all of the conversion factors used to convert data between physical units and Btu for all states and the United States, and the Excel file shows the state-level conversion factors for coal and natural gas in six Excel spreadsheets. Zip files are also available for the large data files. In addition, there is a CSV file for each state, named

342

Methods to Develop Energy Baselines for California's  

E-Print Network (OSTI)

Methods to Develop Energy Baselines for California's Regions Transportation Energy Research PIER Transportation Research www.energy.ca.gov/research/transportation May 2011 The Issue New methods and baseline impacts of land use policies and infrastructure investments, and guide future land use decisions

343

ELECTRICITY CONSUMPTION TO INFORM DATA-DRIVEN ENERGY EFFICIENCY  

E-Print Network (OSTI)

Abstract. Effective demand-side energy efficiency policies are needed to reduce residential electricity consumption and its harmful effects on the environment. The first step to devise such polices is to quantify the potential for energy efficiency by analyzing the factors that impact consumption. This paper proposes a novel approach to analyze large data sets of residential electricity consumption to derive insights for policy making and energy efficiency programming. In this method, underlying behavioral determinants that impact residential electricity consumption are identified using Factor Analysis. A distinction is made between long-term and short-term determinants of consumption by developing separate models for daily maximum and daily minimum consumption and analyzing their differences. Finally, the set of determinants are ranked by their impact on electricity consumption, using a stepwise regression model. This approach is then applied on a large data set of smart meter data and household information as a case example. The results of the models show that weather, location, floor area, and number of refrigerators are the most significant determinants of daily minimum (or idle) electricity consumption in residential buildings,

Amir Kavousian; Ram Rajagopal; Martin Fischer; Amir Kavousian; Ram Rajagopal; Martin Fischer

2012-01-01T23:59:59.000Z

344

The US Long Baseline Neutrino Experiment Study  

Science Conference Proceedings (OSTI)

The US Long Baseline Neutrino Experiment Study was commissioned jointly by Brookhaven National Laboratory (BNL)and Fermi National Accelerator Laboratory (FNAL) to investigate the potential for future U.S. based long baseline neutrino oscillation experiments using MW class conventional neutrino beams that can be produced at FNAL. The experimental baselines are based on two possible detector locations: 1) off?axis to the existing FNAL NuMI beamline at baselines of 700 to 810 km and 2) NSF's proposed future Deep Underground Science and Engineering Laboratory (DUSEL) at baselines greater than 1000 km. Two detector technologies are considered: a megaton class Water Cherenkov detector deployed deep underground at a DUSEL site

Mary Bishai; US Long Baseline Study Group

2008-01-01T23:59:59.000Z

345

DOE/EIA-0207/3 Residential Energy Consumption Survey: Conservation  

U.S. Energy Information Administration (EIA) Indexed Site

3 3 Residential Energy Consumption Survey: Conservation February 1980 U.S. Department of Energy Energy Information Adminstration Assistant Administrater for Program Development Other NEICS Reports Preliminary Conservation Tables from the National Interim Energy Consumption Survey, August 1979, DOE/EIA-0193/P Characteristics of the Housing Stocks and Households: Preliminary Findings from the National Interim Energy Consumption Survey, October 1979, DOETllA-0199/P The above reports are available from the following address; U.S. Department of Energy Technical Information Center Attn:; EIA Coordinator P.O. Box 62 Oak Ridge, TN 37830 Residential Energy Consumption Survey; Characteristics of the Housing Stock and Households, DOE/EIA-0207/2, GPO Stock No,, 061-003-00093-2; $4.25

346

consumption | OpenEI  

Open Energy Info (EERE)

consumption consumption Dataset Summary Description This dataset is from the report Operational water consumption and withdrawal factors for electricity generating technologies: a review of existing literature (J. Macknick, R. Newmark, G. Heath and K.C. Hallett) and provides estimates of operational water withdrawal and water consumption factors for electricity generating technologies in the United States. Estimates of water factors were collected from published primary literature and were not modified except for unit conversions. Source National Renewable Energy Laboratory Date Released August 28th, 2012 (2 years ago) Date Updated Unknown Keywords coal consumption csp factors geothermal PV renewable energy technologies Water wind withdrawal Data application/vnd.openxmlformats-officedocument.spreadsheetml.sheet icon Operational water consumption and withdrawal factors for electricity generating technologies (xlsx, 32.3 KiB)

347

Analysis of ultimate energy consumption by sector in Islamic republic of Iran  

Science Conference Proceedings (OSTI)

Total ultimate energy consumption in Iran was 1033.32 MBOE in 2006, and increased at an average annual rate of 6% in 1996-2006. Household and commercial sector has been the main consumer sector (418.47 MBOE) and the fastest-growing sector (7.2%) that ... Keywords: Iran, agricultural sector, energy audits, energy consumption, industrial sector, residential and commercial sector, transportation sector

B. Farahmandpour; I. Nasseri; H. Houri Jafari

2008-02-01T23:59:59.000Z

348

Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle  

NLE Websites -- All DOE Office Websites (Extended Search)

5: February 5, 5: February 5, 2007 Household Vehicle Miles to someone by E-mail Share Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Facebook Tweet about Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Twitter Bookmark Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Google Bookmark Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Delicious Rank Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Digg Find More places to share Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on AddThis.com... Fact #455: February 5, 2007 Household Vehicle Miles The graphs below show the average vehicle miles of travel (VMT) - daily

349

Competition Helps Kids Learn About Energy and Save Their Households...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm...

350

Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle  

NLE Websites -- All DOE Office Websites (Extended Search)

3: January 22, 3: January 22, 2007 Household Vehicle Ownership to someone by E-mail Share Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Facebook Tweet about Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Twitter Bookmark Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Google Bookmark Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Delicious Rank Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Digg Find More places to share Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on AddThis.com... Fact #453: January 22, 2007 Household Vehicle Ownership

351

Vehicle Technologies Office: Fact #259: March 17, 2003 Household...  

NLE Websites -- All DOE Office Websites (Extended Search)

9: March 17, 2003 Household Travel by Gender to someone by E-mail Share Vehicle Technologies Office: Fact 259: March 17, 2003 Household Travel by Gender on Facebook Tweet about...

352

Essays on household decision making in developing countries  

E-Print Network (OSTI)

This dissertation contains three essays on household decision making in the areas of education and health in developing countries. The first chapter explores intra-household decision making in the context of conditional ...

Berry, James W. (James Wesley)

2009-01-01T23:59:59.000Z

353

ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR  

NLE Websites -- All DOE Office Websites (Extended Search)

ANALYSIS OF CEE HOUSEHOLD SURVEY ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR ® FOR 2012 TABLE OF CONTENTS Acknowledgements .................................................................................. ii Executive Summary ............................................................................ ES-1 Introduction ............................................................................................... 1 Methodology Overview ............................................................................. 2 Key Findings ............................................................................................. 5 Recognition .................................................................................................................. 5 Understanding ........................................................................................................... 12

354

Baseline Wind Energy Facility | Open Energy Information  

Open Energy Info (EERE)

Baseline Wind Energy Facility Baseline Wind Energy Facility Jump to: navigation, search Name Baseline Wind Energy Facility Facility Baseline Wind Energy Facility Sector Wind energy Facility Type Commercial Scale Wind Facility Status Proposed Owner First Wind Developer First Wind Location Gilliam County OR Coordinates 45.626863°, -120.162885° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":45.626863,"lon":-120.162885,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

355

Baseline Report for the Fort Hood Army Base: Sept. 1, 2002 - Aug. 31, 2003  

E-Print Network (OSTI)

This report presents electricity, natural gas and cooling baselines for the thermal plant, buildings located in the 87000 block, III Corp building and other buildings that were determined to be part of the ESPC project at Ft. Hood. A baseline analysis is also presented for the natural gas consumption for the Ft. Hood Army base. The weather-independent analysis, which utilizes 24-hour profiles that were developed using ASHRAEâ??s 1093-RP diversity factor procedures are presented for data obtained from portable loggers attached to Watt-hour meters in selected buildings as well as data from the Main, West and North Substations.

Haberl, J. S.; Baltazar-Cervantes, J. C.; Liu, Z.; Claridge, D. E.; Turner, W. D.

2003-01-01T23:59:59.000Z

356

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

2 2 Year Built (1) Prior to 1950 74.5 114.9 46.8 24% 1950 to 1969 66.0 96.6 38.1 23% 1970 to 1979 59.4 83.4 33.5 15% 1980 to 1989 51.9 81.4 32.3 14% 1990 to 1999 48.2 94.4 33.7 16% 2000 to 2005 44.7 94.7 34.3 8% Average 58.7 95.0 40.0 Note(s): Source(s): 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008. 2005 Residential Delivered Energy Consumption Intensities, by Vintage Per Square Per Household Per Household

357

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

Appliances ... include the small number of households where the fuel for central air-conditioning equipment was something other than electricity; ...

358

Household carbon dioxide production in relation to the greenhouse effect  

SciTech Connect

A survey of 655 households from eastern suburbs of Melbourne was undertaken to determine householders[prime] attitudes to, and understanding of, the greenhouse effect. Carbon dioxide emissions resulting from car, electricity and gas use were computed and household actions which could reduce CO[sub 2] emissions were addressed. Preliminary analysis of the results indicates that householders in this area are aware of, and concerned about, the greenhouse effect, although their understanding of its causes is often poor. Many appreciate the contribution of cars, but are unclear about the relative importance of other household activities. Carbon dioxide emissions from the three sources examined averaged 21[center dot]2 tonnes/year per household and 7[center dot]4 tonnes/year per person. Electricity was the largest contributor (8[center dot]6 tonnes/year), cars the next largest (7[center dot]7 tonnes/year) and gas third (5[center dot] tonnes/year) per household. Emissions varied considerably from household to household. There was a strong positive correlation between availability of economic resources and household CO[sub 2] output from all sources. Carbon dioxide production, particularly from car use, was greater from households which were most distant from a railway station, and from larger households, and numbers of children in the household had little effect on emissions. There were also some economics of scale for households containing more adults. Understanding the causes of the greenhouse bore little relation to change in CO[sub 2] emissions; being concerned about it was associated with a small reduction; but actual actions to reduce car use and household heating, however motivated, produced significant reductions. 12 refs., 9 figs., 6 tabs.

Stokes, D.; Lindsay, A.; Marinopoulos, J.; Treloar, A.; Wescott, G. (Deakin Univ., Clayton (Australia))

1994-03-01T23:59:59.000Z

359

Mitigating Carbon Emissions: the Potential of Improving Efficiency of Household Appliances in China  

E-Print Network (OSTI)

Efficiency of Household Appliances in China Jiang Lin8 Appliance Market inEfficiency of Household Appliances in China Executive

Lin, Jiang

2006-01-01T23:59:59.000Z

360

Energy Information Administration - Energy Efficiency, energy consumption  

U.S. Energy Information Administration (EIA) Indexed Site

Efficiency Efficiency Energy Efficiency energy consumption savings households, buildings, industry & vehicles The Energy Efficiency Page reflects EIA's information on energy efficiency and related information. This site provides an in depth discussion of the concept of energy efficiency and how it is measured, measurement, summaries of formal user meetings on energy efficiency data and measurement, as well as analysis of greenhouse gas emissions as related to energy use and energy efficiency. At the site you will find links to other sources of information, and via a listserv all interested analysts can share ideas, data, and ask for assistance on methodological problems associated with energy use, energy efficiency, and greenhouse gas issues. Contact: Behjat.Hojjati@eia.doe.gov

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Table A4. Residential sector key indicators and consumption  

Gasoline and Diesel Fuel Update (EIA)

3 3 U.S. Energy Information Administration | Annual Energy Outlook 2013 Reference case Table A4. Residential sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Energy Information Administration / Annual Energy Outlook 2013 Table A4. Residential sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Key indicators and consumption Reference case Annual growth 2011-2040 (percent) 2010 2011 2020 2025 2030 2035 2040 Key indicators Households (millions) Single-family ....................................................... 82.85 83.56 91.25 95.37 99.34 103.03 106.77 0.8% Multifamily ........................................................... 25.78 26.07 29.82 32.05 34.54 37.05 39.53 1.4%

362

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

How does EIA estimate energy consumption and end uses in U.S. homes? How does EIA estimate energy consumption and end uses in U.S. homes? RECS 2009 - Release date: March 28, 2011 EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage patterns, and household demographics. This information is combined with data from energy suppliers to these homes to estimate energy costs and usage for heating, cooling, appliances and other end uses â€" information critical to meeting future energy demand and improving efficiency and building design. RECS uses a multi-stage area probability design to select sample methodology figure A multi-stage area probability design ensures the selection

363

Residential Energy Consumption for Water Heating (2005) | OpenEI  

Open Energy Info (EERE)

for Water Heating (2005) for Water Heating (2005) Dataset Summary Description Provides total and average annual residential energy consumption for water heating in U.S. households in 2005, measured in both physical units and Btus. The data is presented for numerous categories including: Census Region and Climate Zone; Housing Unit Characteristics (type, year of construction, size, income, race, age); and Water Heater and Water-using Appliance Characteristics (size, age, frequency of use, EnergyStar rating). Source EIA Date Released September 01st, 2008 (6 years ago) Date Updated January 01st, 2009 (5 years ago) Keywords Energy Consumption Residential Water Heating Data application/vnd.ms-excel icon 2005_Consumption.for_.Water_.Heating.Phys_.Units_EIA.Sep_.2008.xls (xls, 67.6 KiB)

364

Building and occupant characteristics as determinants of residential energy consumption  

Science Conference Proceedings (OSTI)

The major goals of the research are to gain insight into the probable effects of building energy performance standards on energy consumption; to obtain observations of actual residential energy consumption that could affirm or disaffirm comsumption estimates of the DOE 2.0A simulation model; and to investigate home owner's conservation investments and home purchase decisions. The first chapter covers the investigation of determinants of household energy consumption. The presentation begins with the underlying economic theory and its implications, and continues with a description of the data collection procedures, the formulation of variables, and then of data analysis and findings. In the second chapter the assumptions and limitations of the energy use projections generated by the DOE 2.0A model are discussed. Actual electricity data for the houses are then compared with results of the simulation.

Nieves, L.A.; Nieves, A.L.

1981-10-01T23:59:59.000Z

365

Fort Irwin Integrated Resource Assessment. Volume 2, Baseline detail  

SciTech Connect

This report documents the assessment of baseline energy use at Fort Irwin, a US Army Forces Command facility near Barstow, California. It is a companion report to Volume 1, Executive Summary, and Volume 3, Integrated Resource Assessment. The US Army Forces Command (FORSCOM) has tasked the US Department of Energy (DOE) Federal Energy Management Program (FEMP), supported by the Pacific Northwest Laboratory (PNL), to identify, evaluate, and assist in acquiring all cost-effective energy projects at Fort Irwin. This is part of a model program that PNL has designed to support energy-use decisions in the federal sector. This program (1) identifies and evaluates all cost-effective energy projects; (2) develops a schedule at each installation for project acquisition considering project type, size, timing, and capital requirements, as well as energy and dollar savings; and (3) targets 100% of the financing required to implement energy efficiency projects. PNL applied this model program to Fort Irwin. This analysis examines the characteristics of electric, propane gas, and vehicle fuel use for a typical operating year. It records energy-use intensities for the facilities at Fort Irwin by building type and energy end use. It also breaks down building energy consumption by fuel type, energy end use, and building type. A complete energy consumption reconciliation is presented that accounts for all energy use among buildings, utilities, and applicable losses.

Richman, E.E.; Keller, J.M.; Dittmer, A.L.; Hadley, D.L.

1994-01-01T23:59:59.000Z

366

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

by electric and hybrid vehicles", SAE Technical Papers No.household response to hybrid vehicles. Finally, we suggestas electric or hybrid vehicles. Transitions in choices of

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

367

OpenEI - consumption  

Open Energy Info (EERE)

91/0 en Operational water 91/0 en Operational water consumption and withdrawal factors for electricity generating technologies http://en.openei.org/datasets/node/969 This dataset is from the report Operational water consumption and withdrawal factors for electricity generating technologies: a review of existing literature (J. Macknick, R. Newmark, G. Heath and K.C. Hallett) and provides estimates of operational water withdrawal and water consumption factors for electricity generating technologies in the United States. Estimates of water factors were collected from published primary literature and were not modified except for unit conversions.

License

368

Energy-consumption modelling  

SciTech Connect

A highly sophisticated and accurate approach is described to compute on an hourly or daily basis the energy consumption for space heating by individual buildings, urban sectors, and whole cities. The need for models and specifically weather-sensitive models, composite models, and space-heating models are discussed. Development of the Colorado State University Model, based on heat-transfer equations and on a heuristic, adaptive, self-organizing computation learning approach, is described. Results of modeling energy consumption by the city of Minneapolis and Cheyenne are given. Some data on energy consumption in individual buildings are included.

Reiter, E.R.

1980-01-01T23:59:59.000Z

369

Salton Sea sampling program: baseline studies  

DOE Green Energy (OSTI)

Baseline data are provided on three species of fish from the Salton Sea, California. The fishes considered were the orange mouth corvina (Cynoscion xanthulus), gulf croaker (Bairdiella icistius) and sargo (Anisotremus davidsonii). Morphometric and meristic data are presented as a baseline to aid in the evaluation of any physiological stress the fish may experience as a result of geothermal development. Analyses were made on muscle, liver, and bone of the fishes sampled to provide baseline data on elemental tissue burdens. The elements measured were: As, Br, Ca, Cu, Fe, Ga, K, Mn, Mi, Pb, Rb, Se, Sr, Zn, and Zr. These data are important if an environmentally sound progression of geothermal power production is to occur at the Salton Sea.

Tullis, R.E.; Carter, J.L.; Langlois, G.W.

1981-04-13T23:59:59.000Z

370

Evaluation program effectiveness of household hazardous waste collection: The Seattle-King County experience  

SciTech Connect

The Seattle-King County Hazardous Waste Management Plan provides the framework for an intensive effort to keep Household Hazardous and Small Quantity Generator (SQG) wastes from entering the normal'' municipal waste streams. The Plan sets ambitious goals for diverting thousands of tons of hazardous wastes from being thrown, poured or dumped in the municipal waste stream. During the first five years, over $30 millon will be spent for a variety of HHW and SQG programs. The Plan incorporates a wide range of elements, including education, collection, and compliance components. Many of the hazardous waste education and collection programs have been developed in response to the Plan, so their effectiveness is still undetermined. A key component of the Plan is program evaluation. This report provides descriptions of two evaluation methods used to establish baselines for assessing the effectiveness of the Hazardous Waste Management Plan's programs. Focusing on the Plan's household hazardous waste programs, the findings of the baseline evaluations are discussed and conclusions are made. A general population survey, conducted through telephone interviews, was designed to assess changes in knowledge, attitudes, and behaviors of area residents. Characterization of the solid waste stream was used to identify the hazardous constituents contributed to municipal solid waste by households. Monitoring changes in the amount of hazardous materials present in the waste stream was used to indicate whether or not Program strategies are influencing disposal behaviors. Comparing the data gathered by these two evaluation methods provided a unique opportunity to cross-check the findings and validate that change, if any, has occurred. From the comparisons, the report draws a number of conclusions.

1991-10-01T23:59:59.000Z

371

Residential energy consumption and expenditures by end use for 1978, 1980, and 1981  

Science Conference Proceedings (OSTI)

The end-use estimates of the average household consumption and expenditures are statistical estimates based on the 1978, 1980, and 1981 Residential Enery Consumption Surveys (RECS) conducted by the Energy Information Administration (EIA) rather than on metered observations. The end-use estimates were obtained by developing a set of equations that predict the percentage of energy used for each broad end-use category. The equations were applied separately to each household and to each fuel. The resulting household end-use estimates were averaged to produce estimates of the average end-use consumption and expenditures on a national and regional basis. The accuracy and potential biases of these end-use estimates vary depending on the fuel type, on the year of the survey, and on the type of end use. The figures and tables presented show the amount and the type of energy cosumed, plus the cost of this energy. National averages are given as well as averages for various categories including region, size and age of dwelling, number of heating degree-days, and income. Some of the significant findings; energy trends by end use for all fuels used in the home for 1978, 1980, and 1981; and electricity consumption and expenditures and natural gas consumption and expenditures are discussed.

Johnson, M.

1984-12-01T23:59:59.000Z

372

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

373

Residential Energy Consumption Survey (RECS) - U.S. Energy Information  

Gasoline and Diesel Fuel Update (EIA)

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

374

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

U.S. Energy Information Administration (EIA) Indexed Site

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

375

Household attitudes toward energy conservation in the Pacific Northwest: overview and comparisons  

SciTech Connect

This report presents an overview of a baseline residential energy conservation study for the Pacific Northwest conducted in November 1983 by RMH Research, Inc. It also compares the study results with available data from other surveys. The primary focus of the RMH study is conservation marketing. As such it assesses the attitudes, perceptions, and past conservation actions of the region's residents and provides market segmentation based upon past conservation actions and the propensity to invest in conservation in the future. Excluding renters, who account for about 24% of the region's households, three prospect groups for marketing conservation investments are identified: First Tier Prospects who are very likely to invest in additional conservation measures requiring larger sums of money (estimated at about 547,000 households, or 18 percent of the region's households); Second Tier Prospects who are somewhat likely to invest in full weatherization (estimated at about 22% of the region's households or 695,700); and Non-Prospects who are unlikely to invest in energy conservation in the near future (estimated to be 1,113,400 or 36% of the regional total). A summary comparison of the most important distinguishing attributes of the three prospect groups is presented. Considering the current surplus status of the region's electricity supply situation and the overall strategy in capability building, implications include (1) using public information programs through utilities and the news media to maintain the conservation interests of the first-tier prospects and (2) exploring ways to move the second-tier prospects into the first tier and to reach the so-called non-prospect and rental housing groups.

Fang, J.M.

1985-06-01T23:59:59.000Z

376

Homeowners energy conservation and consumption behavior: wood users and non/low wood users  

SciTech Connect

Relationships among energy expenditure, energy consumption, energy-budget share, energy managerial practices, housing, and household-membership factors for non/low wood-user and high wood-user households were examined to explain substitution of fuelwood for primary fuels. Data were from a nationwide representative sample of 1599 homeowners collected by the Department of Energy in 1982-1983 Residential Energy Conservation Survey. In three multivariate regression models, different dependent variables - energy expenditure, energy consumption, and energy budget share, were used. The same independent variables - housing factors, household energy managerial practices, and household membership factors, were used in the three models. Finally, in a fourth model, discriminant analysis with the dichotomous criterion variable of non/low or high wood users and significant variables from the multivariate regressions models were used to explain 34% of the variance. The amount of space heated, their appliance use, whether they had teenage children, and if they were single-earner households were significant explanatory variables in all four models.

Urich, J.R.

1986-01-01T23:59:59.000Z

377

Model of home heating and calculation of rates of return to household energy conservation investment  

Science Conference Proceedings (OSTI)

This study attempts to find out if households' investments on energy conservation yield expected returns. It first builds a home-heating regression model, then uses the results of the model to calculate the rates of return for households' investments on the energy conservation. The home heating model includes housing characteristics, economic and demographic variables, appliance related variables, and regional dummy variables. Housing characteristic variables are modeled according to the specific physical relationship between the house and its heating requirement. Data from the Residential Energy Consumption Survey (RECS) of 1980-1981 is used for the empirical testing of the model. The model is estimated for single-detached family houses separately for three major home-heating fuel types: electricity, natural gas and fuel oil. Four scenarios are used to calculate rates of return for each household. The results show in the Northern areas the rates of return in most of the cases are a lot higher than market interest rates. In the Western and Southern areas, with few exceptions, the rates of return are lower than market interest rates. The variation of heating degree days and energy prices can affect the rates of return up to 20 percentage points.

Hsueh, L.M.

1984-01-01T23:59:59.000Z

378

Table 1. Consumption and Expenditures in U.S. Households, 1997  

U.S. Energy Information Administration (EIA)

Rural or Open Country ..... 16.5 16.0 30.0 105 56 102 38 1,554 0.83 1,513 564 3.2 Climate Zone(4) Under 2,000 CDD and Over 7,000 HDD ..... 9.3 8.4 17 .9 136 64 123 47 ...

379

Do Households Smooth Small Consumption Shocks? Evidence from Anticipated and Unanticipated Variation in Home Energy Costs  

E-Print Network (OSTI)

natural gas, and home heating oil prices averaged over thein 2000 and 2001. Home heating oil prices show a similarstate. Information on home heating oil prices comes from

Cullen, Julie Berry; Friedberg, Leora; Wolfram, Catherine

2005-01-01T23:59:59.000Z

380

Table 2.5 Household Energy Consumption and Expenditures by End ...  

U.S. Energy Information Administration (EIA)

Appliances, 2 Electronics, and Lighting : Natural Gas: Elec-tricity 3: Fuel Oil 4: LPG 5: Total: Electricity 3: Natural Gas: Elec-tricity 3: Fuel Oil ...

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Table 2.5 Household Energy Consumption and Expenditures by End Use ...  

U.S. Energy Information Administration (EIA)

Air Conditioning: Water Heating: Appliances, 2 Electronics, and Lighting : Natural Gas: Elec-tricity 3: Fuel Oil 4: LPG 5: Total: Electricity 3: Natural Gas: Elec ...

382

Do Households Smooth Small Consumption Shocks? Evidence from Anticipated and Unanticipated Variation in Home Energy Costs  

E-Print Network (OSTI)

the Effects of Electricity Price Changes on Californiahighest for gas and electricity prices and lower for weatherfor unexpected changes in electricity prices, which have a

Cullen, Julie Berry; Friedberg, Leora; Wolfram, Catherine

2005-01-01T23:59:59.000Z

383

Table 4. LPG Consumption and Expenditures in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may not sum to totals.

384

Table 2. Fuel Oil Consumption and Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may ...

385

Table 5. Kerosene Consumption and Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may not sum to totals.

386

Table 1a. Residential Site Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

241. 235. 257. 375. 321. 253. Apartments in Buildings with 2 to 4 Units. 681. 534. 468. 477. 394. 377. 372. 405. 359. 183. 315. 302. Apartments in Buildings with 5 or ...

387

Table 2. Fuel Oil Consumption and Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

1 A small amount of fuel oil used for appliances is included in "Fuel Oil" under "All Uses." NF = No applicable RSE row factor.

388

Table 5. Kerosene Consumption and Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

1 A small amount of kerosene used for water heating and appliances is included in "Kerosene" under "All Uses." (*) ...

389

Table CE5-7c. Appliances Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Other Appliances and Lighting (kWh) ..... 5,412 3,903 3,739 6,722 6,222 4.1 Natural Gas (thousand cf) ..... 9 7 9 11 13 7.1 LPG (gallons ...

390

Table 3. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Fuel Oil (million gallons) ..... 7,273 761 1,598 2,262 2,653 811 2,138 11.5 Kerosene (million gallons ...

391

Do Households Smooth Small Consumption Shocks? Evidence from Anticipated and Unanticipated Variation in Home Energy Costs  

E-Print Network (OSTI)

home energy costs are electricity bills. 76% of energy coststo be paying their electricity bills directly, for instanceof the fact that electricity bills comprise almost three-

Cullen, Julie Berry; Friedberg, Leora; Wolfram, Catherine

2005-01-01T23:59:59.000Z

392

Table 2.5 Household Energy Consumption and Expenditures by End Use ...  

U.S. Energy Information Administration (EIA)

Short-Term Energy Outlook › Annual Energy Outlook ... 1984: 20.66: 4.62: 8.51: 2.00: 35.79: 7.06: 6.63: 6.44: 1.09.58: 14.74: 2.31: 36.36.54: 39.21: 1987: 18.05: 5 ...

393

Table 2.4 Household Energy Consumption by Census Region, Selected ...  

U.S. Energy Information Administration (EIA)

Short-Term Energy Outlook › Annual Energy Outlook ... no data available. - Data for 1978-1984 are for April of year shown through March of following year; data

394

Manufacturing Consumption of Energy 1991  

U.S. Energy Information Administration (EIA) Indexed Site

J Related EIA Publications on Energy Consumption Energy Information AdministrationManufacturing Consumption of Energy 1991 526 Appendix J Related EIA Publications on Energy...

395

Manufacturing Consumption of Energy 1991  

U.S. Energy Information Administration (EIA) Indexed Site

3. Energy Consumption in the Manufacturing Sector, 1991 In 1991, the amount of energy consumed in the manufacturing sector was as follows: * Primary Consumption of Energy for All...

396

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

5HVLGHQWLDO (QHUJ\\ &RQVXPSWLRQ 6XUYH\\V 1997 Consumption and Expenditures Tables Appliances Consumption Tables (17 pages, 60 kb) Contents Pages CE5-1c.

397

Better Buildings Neighborhood Program: Step 4: Establish Baseline...  

NLE Websites -- All DOE Office Websites (Extended Search)

Establish Baseline Quality Workforce Standards to someone by E-mail Share Better Buildings Neighborhood Program: Step 4: Establish Baseline Quality Workforce Standards on Facebook...

398

South Africa - Greenhouse Gas Emission Baselines and Reduction...  

Open Energy Info (EERE)

Africa - Greenhouse Gas Emission Baselines and Reduction Potentials from Buildings Jump to: navigation, search Name South Africa - Greenhouse Gas Emission Baselines and Reduction...

399

Mexico - Greenhouse Gas Emissions Baselines and Reduction Potentials...  

Open Energy Info (EERE)

Greenhouse Gas Emissions Baselines and Reduction Potentials from Buildings Jump to: navigation, search Name Mexico - Greenhouse Gas Emissions Baselines and Reduction Potentials...

400

Atlantic NAD 83 SLA Baseline Points | Data.gov  

NLE Websites -- All DOE Office Websites (Extended Search)

SLA Baseline Points Ocean Data Tools Technical Guide Map Gallery Regional Planning Feedback Ocean You are here Data.gov Communities Ocean Data Atlantic NAD 83 SLA Baseline...

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Cost and Performance Baseline for Fossil Energy Plants  

NLE Websites -- All DOE Office Websites (Extended Search)

Baseline for Fossil Energy Plants Volume I (May 2007) Cost and Performance Baseline for Fossil Energy Plants, Volume I Report Desk Reference Presentation Slides "Gasification Costs...

402

PARS II Process Document - Over Target Baseline (OTB) Reporting...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Over Target Baseline (OTB) Reporting PARS II Process Document - Over Target Baseline (OTB) Reporting This document details the process by which contractors should conduct Over...

403

PARS II Process Document - Over Target Baseline (OTB) Reporting...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

PARS II Process Document - Over Target Baseline (OTB) Reporting PARS II Process Document - Over Target Baseline (OTB) Reporting This document details the process by which...

404

Seismic baseline and induction studies- Roosevelt Hot Springs...  

Open Energy Info (EERE)

Seismic baseline and induction studies- Roosevelt Hot Springs, Utah and Raft River, Idaho Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Report: Seismic baseline and...

405

Building and occupant characteristics as determinants of residential energy consumption  

Science Conference Proceedings (OSTI)

The major goals of the research are to gain insight into the probable effects of building energy performance standards on energy consumption; to obtain observations of actual residential energy consumption that could affirm or disaffirm comsumption estimates of the DOE 2.0A simulation model; and to investigate home owner's conservation investments and home purchase decisions. The first chapter covers the investigation of determinants of household energy consumption. The presentation begins with the underlying economic theory and its implications, and continues with a description of the data collection procedures, the formulation of variables, and then of data analysis and findings. In the second chapter the assumptions and limitations of the energy use projections generated by the DOE 2.0A model are discussed. Actual electricity data for the houses are then compared with results of the simulation. The third chapter contains information regarding households' willingness to make energy conserving investments and their ranking of various conservation features. In the final chapter conclusions and recommendations are presented with an emphasis on the policy implications of this study. (MCW)

Nieves, L.A.; Nieves, A.L.

1981-10-01T23:59:59.000Z

406

Solid Waste Program technical baseline description  

SciTech Connect

The system engineering approach has been taken to describe the technical baseline under which the Solid Waste Program is currently operating. The document contains a mission analysis, function analysis, system definition, documentation requirements, facility and project bases, and uncertainties facing the program.

Carlson, A.B.

1994-07-01T23:59:59.000Z

407

Waste management project technical baseline description  

SciTech Connect

A systems engineering approach has been taken to describe the technical baseline under which the Waste Management Project is currently operating. The document contains a mission analysis, function analysis, requirement analysis, interface definitions, alternative analysis, system definition, documentation requirements, implementation definitions, and discussion of uncertainties facing the Project.

Sederburg, J.P.

1997-08-13T23:59:59.000Z

408

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

3 3 Building Type Pre-1995 1995-2005 Pre-1995 1995-2005 Pre-1995 1995-2005 Single-Family 38.4 44.9 102.7 106.2 38.5 35.5 Detached 37.9 44.7 104.5 107.8 38.8 35.4 Attached 43.8 55.5 86.9 85.1 34.2 37.6 Multi-Family 63.8 58.7 58.3 49.2 27.2 24.3 2 to 4 units 69.0 55.1 70.7 59.4 29.5 25.0 5 or more units 61.5 59.6 53.6 47.2 26.3 24.2 Mobile Homes 82.4 57.1 69.6 74.5 29.7 25.2 Note(s): Source(s): 2005 Residential Delivered Energy Consumption Intensities, by Principal Building Type and Vintage Per Square Foot (thousand Btu) (1) Per Household (million Btu) Per Household Member (million Btu) 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average

409

A comparative analysis of energy demand and expenditures by minority and majority households within the context of a conditional demand system  

SciTech Connect

Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

Poyer, D.A.

1992-08-01T23:59:59.000Z

410

A comparative analysis of energy demand and expenditures by minority and majority households within the context of a conditional demand system  

SciTech Connect

Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

Poyer, D.A.

1992-01-01T23:59:59.000Z

411

Experience with improved charcoal and wood stoves for households and institutions in Kenya  

SciTech Connect

Efforts at promoting more fuel-efficient charcoal stoves to replace traditional charcoal stoves in Kenya offer some lessons for the dissemination of appropriate technologies. This paper looks at the market-based approach which has made the Kenyan charcoal stoves project a success. Trends in woodfuels (wood and charcoal) consumption in Kenya are identified; the traditional technology for charcoal combustion and the upgraded traditional technologies are described; production achievement and the dissemination and promotion strategy used are examined; and a financial and economic analysis is performed with social, health and environmental effects assessed. Other ways to achieve a more favourable balance between woodfuels consumption and supply are then discussed looking at more efficient charcoal kilns and household woodstoves, improved institutional stoves and increased wood production. The replication potential of the Kenya experiment in other countries is also explored. The lessons learnt from the the Kenya experience concern the relationship between technology, choice and delivery systems as they interact with, economic, institutional, and policy factors. In this case, the design work accepted the traditional technology as a starting point which helped ensure widespread acceptance by households. The potential desirability of relying on local artisans to manufacture consumer durables using existing private sector channels to market these goods is also shown. It also highlights the importance of going beyond a laissez-faire approach and supporting training, demonstration, and publicity to faciliate the workings of the private sector. In the Kenyan case, technology choice was relatively unsubsidized and left ot the preferences of consumers.

Hyman, E.L.

1985-01-01T23:59:59.000Z

412

Towards sustainable household energy use in the Netherlands, Int  

E-Print Network (OSTI)

Abstract: Households consume direct energy, using natural gas, heating oil, gasoline and electricity, and consume indirect energy, the energy related to the production of goods and the delivery of services for the households. Past trends and present-day household energy use (direct and indirect) are analysed and described. A comparison of these findings with objectives concerning ecological sustainability demonstrates that present-day household energy use is not sustainable. A scenario towards sustainable household energy use is designed containing far-reaching measures with regard to direct energy use. Scenario evaluation shows a substantial reduction of direct energy use; however, this is not enough to meet the sustainability objectiv es. Based on these results, the possibilities and the limitations are discussed to enable households to make their direct and indirect energy use sustainable on the long run.

Jack Van Der Wal; Henri C. Moll

2001-01-01T23:59:59.000Z

413

DOETEIAO32l/2 Residential Energy Consumption Survey; Consumption  

Gasoline and Diesel Fuel Update (EIA)

sample custom-designed to meet the analytic objectives for surveys of residential energy use; sample as many as 5,500 households; provide 2-day personal training sessions...

414

Office Buildings - Energy Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

Energy Consumption Energy Consumption Office buildings consumed more than 17 percent of the total energy used by the commercial buildings sector (Table 4). At least half of total energy, electricity, and natural gas consumed by office buildings was consumed by administrative or professional office buildings (Figure 2). Table 4. Energy Consumed by Office Buildings for Major Fuels, 2003 All Buildings Total Energy Consumption (trillion Btu) Number of Buildings (thousand) Total Floorspace (million sq. ft.) Sum of Major Fuels Electricity Natural Gas Fuel Oil District Heat All Buildings 4,859 71,658 6,523 3,559 2,100 228 636 All Non-Mall Buildings 4,645 64,783 5,820 3,037 1,928 222 634 All Office Buildings 824 12,208 1,134 719 269 18 128 Type of Office Building

415

A Model of Household Demand for Activity Participation and Mobility  

E-Print Network (OSTI)

household car ownership, car usage, and travel by differentownership demand, and car usage demand. Modal travel demand,mode), car ownership, and car usage for spatial aggregations

Golob, Thomas F.

1996-01-01T23:59:59.000Z

416

Crime and the Nation’s Households, 2000 By  

E-Print Network (OSTI)

experienced 1 or more violent or property crimes in 2000, according to data from the National Crime Victimization Survey (NCVS). About 4.3 million households had members who experienced 1 or more nonfatal violent crimes, including rape, sexual assault, robbery, and aggravated or simple assault. About 14.8 million households experienced 1 or more property crimes — household burglary, motor vehicle theft, or theft. Vandalism, presented for the first time in a Bureau of Justice Statistics (BJS) report, victimized about 6.1 million households. The households that sustained vandalism were counted separately from those experiencing other crimes. Because vandalism is included for the first time, findings are presented in a box on page 4. Beginning in 2001, NCVS victimizations will be measured both with and without vandalism. Measuring the extent to which households are victimized by crime One measure of the impact of crime throughout the Nation is gained through estimating the number and percentage of households victimized Highlights During 2000, 16 % of U.S. households had a member who experienced a crime, with 4 % having a member victimized by violent crime. During 1994, 25 % of households experienced at least one crime; 7 % a violent crime.

Patsy A. Klaus

2002-01-01T23:59:59.000Z

417

Barriers to household investment in residential energy conservation: preliminary assessment  

Science Conference Proceedings (OSTI)

A general assessment of the range of barriers which impede household investments in weatherization and other energy efficiency improvements for their homes is provided. The relationship of similar factors to households' interest in receiving a free energy audits examined. Rates of return that underly household investments in major conservation improvements are assessed. A special analysis of household knowledge of economically attractive investments is provided that compares high payback improvements specified by the energy audit with the list of needed or desirable conservation improvements identified by respondents. (LEW)

Hoffman, W.L.

1982-12-01T23:59:59.000Z

418

Household Responses to the Financial Crisis in Indonesia  

E-Print Network (OSTI)

on farm households in Indonesia and Thailand,” World Bank20. Cameron, Lisa. (1999). “Indonesia: a quarterly review,”The Real Costs of Indonesia's Economic Crisis: Preliminary

Thomas, Duncan; Frankenberg, Elizabeth

2005-01-01T23:59:59.000Z

419

SUPPLEMENTAL ENERGY-RELATED DATA FOR THE 2001 NATIONAL HOUSEHOLD ...  

U.S. Energy Information Administration (EIA)

... vehicle manufacturer, vehicle model, vehicle model year, and vehicle type – several ENERGY INFORMATION ADMINISTRATION/2001 NATIONAL HOUSEHOLD TRAVEL SURVEY K-23 ...

420

U.S. households are incorporating energy–efficient features ...  

U.S. Energy Information Administration (EIA)

... area of increased efficiency: about 60% of households use at least some energy-efficient compact fluorescent (CFL) or light-emitting diode (LED) ...

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Householder's Perceptions of Insulation Adequacy and Drafts in the ...  

U.S. Energy Information Administration (EIA)

The 2001 RECS was the first RECS to request household perceptions regarding the presence of winter drafts in the home. The data presented in this report ...

422

Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing  

Science Conference Proceedings (OSTI)

Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

2011-08-15T23:59:59.000Z

423

In-vessel composting of household wastes  

Science Conference Proceedings (OSTI)

The process of composting has been studied using five different types of reactors, each simulating a different condition for the formation of compost; one of which was designed as a dynamic complete-mix type household compost reactor. A lab-scale study was conducted first using the compost accelerators culture (Trichoderma viridae, Trichoderma harzianum, Trichorus spirallis, Aspergillus sp., Paecilomyces fusisporus, Chaetomium globosum) grown on jowar (Sorghum vulgare) grains as the inoculum mixed with cow-dung slurry, and then by using the mulch/compost formed in the respective reactors as the inoculum. The reactors were loaded with raw as well as cooked vegetable waste for a period of 4 weeks and then the mulch formed was allowed to maturate. The mulch was analysed at various stages for the compost and other environmental parameters. The compost from the designed aerobic reactor provides good humus to build up a poor physical soil and some basic plant nutrients. This proves to be an efficient, eco-friendly, cost-effective, and nuisance-free solution for the management of household solid wastes.

Iyengar, Srinath R. [Civil and Environmental Engineering Department, V.J. Technological Institute, H.R. Mahajani Road, Matunga, Mumbai 400 019 (India)]. E-mail: srinathrangamani@yahoo.com; Bhave, Prashant P. [Civil and Environmental Engineering Department, V.J. Technological Institute, H.R. Mahajani Road, Matunga, Mumbai 400 019 (India)]. E-mail: drppbhave@vsnl.net

2006-07-01T23:59:59.000Z

424

Amtrak fuel consumption study  

Science Conference Proceedings (OSTI)

This report documents a study of fuel consumption on National Railroad Passenger Corporation (Amtrak) trains and is part of an effort to determine effective ways of conserving fuel on the Amtrak system. The study was performed by the Transportation Systems Center (TSC). A series of 26 test runs were conducted on Amtrak trains operating between Boston, Massachusetts, and New Haven, Connecticut, to measure fuel consumption, trip time and other fuel-use-related parameters. The test data were analyzed and compared with results of the TSC Train Performance Simulator replicating the same operations.

Hitz, J.

1981-02-01T23:59:59.000Z

425

Pomona Loop Baseline Performance Testing.PDF  

NLE Websites -- All DOE Office Websites (Extended Search)

Pomona Loop Baseline Performance Testing Summary Pomona Loop Baseline Performance Testing Summary The U.S. Department of Energy's Field Operations Program sponsors the Urban and Freeway Pomona Loop range testing in Southern California. The testing is performed by one of the Program's testing partners, Southern California Edison. The vehicles are tested on local city streets (Urban Loop) and four highways (Freeway Loop). The Urban Loop is 19.3 miles long, ranging in elevation from 900 to 1500 feet, with approximately 50 stop signs and traffic lights. The Freeway Loop is 37.2 miles long, ranging in elevation from 700 to 1150 feet, and consists of four connected freeways shaped like a rectangle. When a vehicle is Pomona Loop tested, eight range tests are performed, with four tests on the Urban Loop and four on the Freeway Loop. The range tests are performed

426

2005 Residential Energy Consumption Survey  

U.S. Energy Information Administration (EIA) Indexed Site

F (2005) - Household Natural Gas Usage Form F (2005) - Household Natural Gas Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Natural Gas Usage Form Service Address: If the customer account number is not shown above, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and provide the requested information for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality and sanctions. Use the enclosed self-addressed envelope and return the completed form to:

427

2005 Residential Energy Consumption Survey  

U.S. Energy Information Administration (EIA) Indexed Site

G (2005) - Household Fuel Oil or Kerosene Usage Form G (2005) - Household Fuel Oil or Kerosene Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Fuel Oil or Kerosene Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality and sanctions.

428

2005 Residential Energy Consumption Survey  

U.S. Energy Information Administration (EIA) Indexed Site

D (2005) - Household Propane (Bottled Gas or LPG) Usage Form D (2005) - Household Propane (Bottled Gas or LPG) Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Propane (Bottled Gas or LPG) Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality

429

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

Table CE5-1e. Appliances1 Energy Expenditures in U.S. Households by Climate Zone, 1997 RSE Column Factor: Total Climate Zone2 RSE Row Factors Fewer than 2,000 CDD and --

430

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

Table CE4-1e. Water-Heating Energy Expenditures in U.S. Households by Climate Zone, 1997 RSE Column Factor: Total Climate Zone1 RSE Row Factors Fewer than 2,000 CDD ...

431

Systematic errors in long baseline oscillation experiments  

Science Conference Proceedings (OSTI)

This article gives a brief overview of long baseline neutrino experiments and their goals, and then describes the different kinds of systematic errors that are encountered in these experiments. Particular attention is paid to the uncertainties that come about because of imperfect knowledge of neutrino cross sections and more generally how neutrinos interact in nuclei. Near detectors are planned for most of these experiments, and the extent to which certain uncertainties can be reduced by the presence of near detectors is also discussed.

Harris, Deborah A.; /Fermilab

2006-02-01T23:59:59.000Z

432

Lifestyle Factors in U.S. Residential Electricity Consumption  

Science Conference Proceedings (OSTI)

A multivariate statistical approach to lifestyle analysis of residential electricity consumption is described and illustrated. Factor analysis of selected variables from the 2005 U.S. Residential Energy Consumption Survey (RECS) identified five lifestyle factors reflecting social and behavioral choices associated with air conditioning, laundry usage, personal computer usage, climate zone of residence, and TV use. These factors were also estimated for 2001 RECS data. Multiple regression analysis using the lifestyle factors yields solutions accounting for approximately 40% of the variance in electricity consumption for both years. By adding the associated household and market characteristics of income, local electricity price and access to natural gas, variance accounted for is increased to approximately 54%. Income contributed only {approx}1% unique variance to the 2005 and 2001 models, indicating that lifestyle factors reflecting social and behavioral choices better account for consumption differences than income. This was not surprising given the 4-fold range of energy use at differing income levels. Geographic segmentation of factor scores is illustrated, and shows distinct clusters of consumption and lifestyle factors, particularly in suburban locations. The implications for tailored policy and planning interventions are discussed in relation to lifestyle issues.

Sanquist, Thomas F.; Orr, Heather M.; Shui, Bin; Bittner, Alvah C.

2012-03-30T23:59:59.000Z

433

Reduced power consumption in  

E-Print Network (OSTI)

and a potential energy savings of over $30 Billion/year. This new approach is demanded by the exponentiallyBenefits Reduced power consumption in IC devices; hence potential energy savings of 300 Billion KWh://www.sia- online.org) CuRIE Interconnect Technology for Improved Energy Efficiency in IC Chips ARPA-E Technology

434

Natural Gas Consumption  

U.S. Energy Information Administration (EIA) Indexed Site

Lease Fuel Consumption Plant Fuel Consumption Pipeline & Distribution Use Volumes Delivered to Consumers Volumes Delivered to Residential Volumes Delivered to Commercial Consumers Volumes Delivered to Industrial Consumers Volumes Delivered to Vehicle Fuel Consumers Volumes Delivered to Electric Power Consumers Period: Monthly Annual Lease Fuel Consumption Plant Fuel Consumption Pipeline & Distribution Use Volumes Delivered to Consumers Volumes Delivered to Residential Volumes Delivered to Commercial Consumers Volumes Delivered to Industrial Consumers Volumes Delivered to Vehicle Fuel Consumers Volumes Delivered to Electric Power Consumers Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 23,103,793 23,277,008 22,910,078 24,086,797 24,477,425 25,533,448 1949-2012 Alabama 418,512 404,157 454,456 534,779 598,514 666,738 1997-2012 Alaska 369,967 341,888 342,261 333,312 335,458 343,110 1997-2012

435

& CONSUMPTION US HYDROPOWER PRODUCTION  

E-Print Network (OSTI)

12% of the nation's electricity. Hydropower produces more than 90,000 megawatts of electricity, which is enough to meet the needs of 28.3 million consumers. Hydropower accounts for over 90% of all electricity the NAO. ENERGY CONSUMPTION AND PRODUCTION IN NORWAY AND THE NAO The demand for heating oil in Norway

436

Reduction of Water Consumption  

E-Print Network (OSTI)

Cooling systems using water evaporation to dissipate waste heat, will require one pound of water per 1,000 Btu. To reduce water consumption, a combination of "DRY" and "WET" cooling elements is the only practical answer. This paper reviews the various options available: WET-DRY towers, or DRY-WET, or combination WET and DRY towers!

Adler, J.

1985-05-01T23:59:59.000Z

437

Crisis and Consumption Smoothing  

Science Conference Proceedings (OSTI)

The dramatic impact of the current crisis on performance of businesses across sectors and economies has been headlining the business press for the past several months. Extant reconciliations of these patterns in the popular press rely on ad hoc reasoning. ... Keywords: consumer behavior, consumption smoothing, crisis, econometrics, marketing strategy

Pushan Dutt; V. Padmanabhan

2011-05-01T23:59:59.000Z

438

Overview of CFC replacement issues for household refrigeration  

Science Conference Proceedings (OSTI)

In 1974, the famous ozone depletion theory of Rowland and Molina claimed that chlorofluorocarbons (CFCs) diffuse into the stratosphere where they are broken down by photolysis to release chlorine atoms that catalytically destroy ozone. Although the understanding of the science is still imperfect, there is little doubt that CFCs play a major role in the Antarctic ozone hole phenomenon and the decline in ozone observed in the rest of the world. Another issue that has become increasingly important is the potential of CFCs to change the earth's temperature and to modify the climate. While the main impact in global warming is made by increased concentrations of carbon dioxide, CFCs and other trace gases also contribute to this effect. In an effort to respond to the global environmental threat, a CFC protocol was adopted during a diplomatic conference in Montreal. This document, known as the Montreal Protocol, was ratified in 1988 and put into effect on January 1, 1989. In accordance with Article 6 of the Montreal Protocol, the countries that signed the agreement shall periodically assess the control measures provided for in the Protocol. As part of that assessment process, household refrigeration was investigated to determine the status of CFC-12 replacements. The conclusion was that much progress has been made towards finding a suitable replacement. Compressors designed for HFC-134a have efficiencies comparable to those for CFC-12 and acceptable reliability tests have been obtained with ester lubricants. In addition, other replacements such as R-152a and refrigerant mixtures exist, but will require more study. Cycle options, such as the Stirling cycle, may be viable, but are further out in the future. The impact of new refrigerants is expected to result in elimination of CFC-12 consumption in developed countries by 1997 and in developing countries by 2005.

Vineyard, E.A. (Oak Ridge National Lab., TN (United States)); Roke, L. (Fisher and Paykel, Auckland (New Zealand)); Hallett, F. (Frigidaire, Washington, DC (United States))

1991-01-01T23:59:59.000Z

439

Overview of CFC replacement issues for household refrigeration  

Science Conference Proceedings (OSTI)

In 1974, the famous ozone depletion theory of Rowland and Molina claimed that chlorofluorocarbons (CFCs) diffuse into the stratosphere where they are broken down by photolysis to release chlorine atoms that catalytically destroy ozone. Although the understanding of the science is still imperfect, there is little doubt that CFCs play a major role in the Antarctic ozone hole phenomenon and the decline in ozone observed in the rest of the world. Another issue that has become increasingly important is the potential of CFCs to change the earth`s temperature and to modify the climate. While the main impact in global warming is made by increased concentrations of carbon dioxide, CFCs and other trace gases also contribute to this effect. In an effort to respond to the global environmental threat, a CFC protocol was adopted during a diplomatic conference in Montreal. This document, known as the Montreal Protocol, was ratified in 1988 and put into effect on January 1, 1989. In accordance with Article 6 of the Montreal Protocol, the countries that signed the agreement shall periodically assess the control measures provided for in the Protocol. As part of that assessment process, household refrigeration was investigated to determine the status of CFC-12 replacements. The conclusion was that much progress has been made towards finding a suitable replacement. Compressors designed for HFC-134a have efficiencies comparable to those for CFC-12 and acceptable reliability tests have been obtained with ester lubricants. In addition, other replacements such as R-152a and refrigerant mixtures exist, but will require more study. Cycle options, such as the Stirling cycle, may be viable, but are further out in the future. The impact of new refrigerants is expected to result in elimination of CFC-12 consumption in developed countries by 1997 and in developing countries by 2005.

Vineyard, E.A. [Oak Ridge National Lab., TN (United States); Roke, L. [Fisher and Paykel, Auckland (New Zealand); Hallett, F. [Frigidaire, Washington, DC (United States)

1991-12-31T23:59:59.000Z

440

Using Multiple Household Food Inventories to Measure Food Availability in the Home  

E-Print Network (OSTI)

The purpose of this study was to determine the feasibility of conducting multiple household food inventories over the course of 30 days to examine weekly food variability. Household food availability influences the foods individuals choose to consume; therefore, by assessing the home food environment a better understanding of what people are eating can be obtained. Methods of measuring home food availability have been developed and tested in recent years; however most of these methods assess food availability on one occasion only. This study aimed to capture "usual" availability by using multiple assessments. After the development and pre-testing of the 171-item home observation guide to determine the presence and amount of food items in the home (refrigerator, freezer, pantry, elsewhere), two trained researchers recruited a convenience sample of 9 households (44.4% minority), administered a baseline questionnaire (personal info, shopping habits, food resources, and food security), and conducted 5 in-home assessments (5-7 day interval) over a 30-day period. Each in-home assessment included shopping and fast food activities since the last assessment and an observational survey of types and amounts of foods present. The final in-home assessment included an audio recorded interview on food habits and beliefs. Complete data were collected from all 9 women (32.8 y +/- 6.0; 3 married; 4 +/- 1.6 adults/children in household; 4 SNAP; 6 food insecure) and their households. Weekly grocery purchases (place, amount, and purpose) use (frequency) varied from once (n=1) to every week (n=5); 4 used fast food 2-3 times/wk for 4 weeks. Quantity and types of fresh and processed fruits and vegetables varied by week and by family. The feasibility of conducting multiple in-home assessments was confirmed with 100% retention from all participants. This methodology is important in that it provided detailed information on intra-monthly variation in food availability. The findings suggest the inadequacy of a single measure to assess food availability in the home.

Sisk, Cheree L.

2009-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

A REVIEW OF ASSUMPTIONS AND ANALYSIS IN EPRI EA-3409, "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPS BEHAVIORAL MODELS"  

E-Print Network (OSTI)

EPRI EA-3409, "Household Appliance Choice: Revision of REEPSEA",3409: "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPSreport EA-3409, "Household Appliance Choice: Revi- sion of

Wood, D.J.

2010-01-01T23:59:59.000Z

442

Residential Energy Consumption Survey (RECS) - U.S. Energy Information  

Gasoline and Diesel Fuel Update (EIA)

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years December 20, 2013 Gas furnace efficiency has large implications for residential natural gas use December 5, 2013 EIA publishes state fact sheets on residential energy consumption and characteristics August 19, 2013 All 48 related articles › Other End Use Surveys Commercial Buildings - CBECS Manufacturing - MECS Transportation About the RECS EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage

443

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

The impact of increasing home size on energy demand The impact of increasing home size on energy demand RECS 2009 - Release date: April 19, 2012 Homes built since 1990 are on average 27% larger than homes built in earlier decades, a significant trend because most energy end-uses are correlated with the size of the home. As square footage increases, the burden on heating and cooling equipment rises, lighting requirements increase, and the likelihood that the household uses more than one refrigerator increases. Square footage typically stays fixed over the life of a home and it is a characteristic that is expensive, even impractical to alter to reduce energy consumption. According to results from EIA's 2009 Residential Energy Consumption Survey (RECS), the stock of homes built in the 1970s and 1980s averages less than

444

Residential energy-consumption survey: housing characteristics, 1981  

SciTech Connect

Data in this report cover fuels and their use in the home, appliances, square footage of floor space, heating equipment, thermal characteristics of the housing unit, conservation activities, and consumption of wood. Collected for the first time are data related to indoor temperatures and the use of air conditioning. A unique feature of the 1981 survey is an increased sampling of low-income households funded by the Social Security Administration to provide them information for the Low-Income Home Energy Assistance Program. Discussion highlights data pertaining to these topics: changes in home heating fuel, secondary heating, indoor temperatures, features of new homes, use of air conditioning, use of solar collectors, and wood consumption.

Thompson, W.

1983-08-01T23:59:59.000Z

445

Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions |  

Open Energy Info (EERE)

Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions Jump to: navigation, search Tool Summary Name: Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions Agency/Company /Organization: World Bank Sector: Energy Topics: Baseline projection, GHG inventory, Pathways analysis Resource Type: Publications, Lessons learned/best practices Website: www.p2pays.org/ref/22/21739.pdf References: Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions[1] Summary "Rigor in baselines It's important to establish the right degree of rigor in baselining. Overly lax baselines will threaten the system's credibility and usefulness, and shift rents from high quality providers to low quality providers of offsets. Overly stringent baselines will discourage valid projects and

446

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households by Household Income, 2001 RSE Column Factor: Total 2001 Household Income Below Poverty

447

Baseline Graphite Initial Mechanical Test Report  

SciTech Connect

The Next Generation Nuclear Plant (NGNP) Project is tasked with selecting a high temperature gas reactor technology that will be capable of generating electricity and supplying large amounts of process heat. The NGNP is presently being designed as a helium-cooled high temperature gas reactor (HTGR) with a large graphite core. The graphite baseline characterization project is conducting the research and development (R&D) activities deemed necessary to fully qualify nuclear-grade graphite for use in the NGNP reactor. One of the major fundamental objectives of the project is establishing nonirradiated thermomechanical and thermophysical properties by characterizing lot-to-lot and billet-to-billet variations (for probabilistic baseline data needs) through extensive data collection and statistical analysis. The reactor core will be made up of stacks of graphite moderator blocks. In order to gain a more comprehensive understanding of the varying characteristics in a wide range of suitable graphites, any of which can be classified as “nuclear grade,” an experimental program has been initiated to develop an extensive database of the baseline characteristics of numerous candidate graphites. Various factors known to affect the properties of graphite will be investigated, including specimen size, spatial location within a graphite billet, specimen orientation within a billet (either parallel to [P] or transverse to [T] the long axis of the as-produced billet), and billet-to-billet variations within a lot or across different production lots. Because each data point is based on a certain position within a given billet of graphite, particular attention must be paid to the traceability of each specimen and its spatial location and orientation within each billet. The evaluation of these properties is discussed in the Graphite Technology Development Plan (Windes et. al 2007). One of the key components in the evaluation of these graphite types will be mechanical testing of specimens drawn from carefully controlled sections of each billet. This report is confirmation that the test procedures are in place and approved, and that mechanical testing of graphite under the Baseline Graphite Characterization program has commenced.

Mark Carroll; Randy Lloyd

2009-09-01T23:59:59.000Z

448

Data Center Power Consumption  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Center Power Consumption Center Power Consumption A new look at a growing problem Fact - Data center power density up 10x in the last 10 years 2.1 kW/rack (1992); 14 kW/rack (2007) Racks are not fully populated due to power/cooling constraints Fact - Increasing processor power Moore's law Fact - Energy cost going up 3 yr. energy cost equivalent to acquisition cost Fact - Iterative power life cycle Takes as much energy to cool computers as it takes to power them. Fact - Over-provisioning Most data centers are over-provisioned with cooling and still have hot spots November 2007 SubZero Engineering An Industry at the Crossroads Conflict between scaling IT demands and energy efficiency Server Efficiency is improving year after year Performance/Watt doubles every 2 years Power Density is Going Up

449

Mexico - Greenhouse Gas Emissions Baselines and Reduction Potentials from  

Open Energy Info (EERE)

Greenhouse Gas Emissions Baselines and Reduction Potentials from Greenhouse Gas Emissions Baselines and Reduction Potentials from Buildings Jump to: navigation, search Name Mexico - Greenhouse Gas Emissions Baselines and Reduction Potentials from Buildings Agency/Company /Organization United Nations Environment Programme Sector Energy Focus Area Buildings Topics Baseline projection, GHG inventory, Pathways analysis, Background analysis Resource Type Publications Website http://www.unep.org/sbci/pdfs/ Country Mexico Central America References Greenhouse Emissions Baselines and Reduction Potentials for Buildings[1] Mexico - Greenhouse Gas Emissions Baselines and Reduction Potentials from Buildings Screenshot "This report represents the first comprehensive description of the factors that determine the present and future impacts of residential and commercial

450

101. Natural Gas Consumption  

Gasoline and Diesel Fuel Update (EIA)

1. Natural Gas Consumption 1. Natural Gas Consumption in the United States, 1930-1996 (Million Cubic Feet) Table Year Lease and Plant Fuel Pipeline Fuel Delivered to Consumers Total Consumption Residential Commercial Industrial Vehicle Fuel Electric Utilities Total 1930 ....................... 648,025 NA 295,700 80,707 721,782 NA 120,290 1,218,479 1,866,504 1931 ....................... 509,077 NA 294,406 86,491 593,644 NA 138,343 1,112,884 1,621,961 1932 ....................... 477,562 NA 298,520 87,367 531,831 NA 107,239 1,024,957 1,502,519 1933 ....................... 442,879 NA 283,197 85,577 590,865 NA 102,601 1,062,240 1,505,119 1934 ....................... 502,352 NA 288,236 91,261 703,053 NA 127,896 1,210,446 1,712,798 1935 ....................... 524,926 NA 313,498 100,187 790,563 NA 125,239 1,329,487 1,854,413 1936 ....................... 557,404 NA 343,346

451

Residential Energy Consumption Survey:  

Gasoline and Diesel Fuel Update (EIA)

E/EIA-0262/2 E/EIA-0262/2 Residential Energy Consumption Survey: 1978-1980 Consumption and Expenditures Part II: Regional Data May 1981 U.S. Department of Energy Energy Information Administration Assistant Administrator for Program Development Office of the Consumption Data System Residential and Commercial Data Systems Division -T8-aa * N uojssaooy 'SOS^-m (£03) ao£ 5925 'uofSfAfQ s^onpojj aa^ndmoo - aojAaag T BU T3gN am rcoj? aig^IT^^ '(adBx Q-naugBH) TOO/T8-JQ/30Q 30^703 OQ ' d jo :moaj ajqBfT^A^ 3J^ sjaodaa aAoqe aqa jo 's-TZTOO-eoo-Tgo 'ON ^ois odo 'g^zo-via/aoQ 'TBST Sujpjjng rXaAang uojidmnsuoo XSaaug sSu-ppjprig ON ^oo^s OdO '^/ZOZO-Via/aOQ *086T aunr '6L6I ?sn§ny og aunf ' jo suja^Bd uoj^dmnsuoo :XaAjng uo^^dmnsuoQ XSaaug OS '9$ '6-ieTOO- 00-T90 OdD 'S/ZOZO-Via/aOa C

452

Econometric model of the joint production and consumption of residential space heat  

Science Conference Proceedings (OSTI)

This study models the production and comsumption of residential space heat, a nonmarket good. Production reflects capital investment decisions of households; consumption reflects final demand decisions given the existing capital stock. In the model, the production relationship is represented by a translog cost equation and an anergy factor share equation. Consumption is represented by a log-linear demand equation. This system of three equations - cost, fuel share, and final demand - is estimated simultaneously. Results are presented for two cross-sections of households surveyed in 1973 and 1981. Estimates of own-price and cross-price elasticities of factor demand are of the correct sign, and less than one in magnitude. The price elasticity of final demand is about -0.4; the income elasticity of final demand is less than 0.1. Short-run and long-run elasticities of demand for energy are about -0.3 and -0.6, respectively. These results suggest that price-induced decreases in the use of energy for space heat are attributable equally to changes in final demand and to energy conservation, the substitution of capital for energy in the production of space heat. The model is used to simulate the behavior of poor and nonpoor households during a period of rising energy prices. This simulation illustrates the greater impact of rising prices on poor households.

Klein, Y.L.

1985-12-01T23:59:59.000Z

453

Document Number Q0029500 Baseline Risk Assessment Update 4.0 Baseline Risk Assessment Update  

Office of Legacy Management (LM)

Baseline Risk Assessment Update Baseline Risk Assessment Update 4.0 Baseline Risk Assessment Update This section updates the human health and the ecological risk assessments that were originally presented in the 1998 RI (DOE 1998a). The impacts on the 1998 risk assessments are summarized in Section 2.9. 4.1 Human Health Risk Assessment Several activities completed since 1998 have contributed to changes in surface water and ground water concentrations. Activities that have impacted, or likely impacted surface water and ground water concentrations are Millsite Excavation (Section 2.1) Remediation of Soil and Sediment Along Montezuma Creek (Section 2.3) Millsite Dewatering and Treatment (Section 2.5) PRB Treatability Study (Section 2.6) Surface water and ground water monitoring data have been used to refine the list of COCs

454

Table AC1. Total Households Using Air-Conditioning Equipment, 2005 ...  

U.S. Energy Information Administration (EIA)

Table AC1. Total Households Using Air-Conditioning Equipment, 2005 Million U.S. Households Type of Air-Conditioning Equipment (millions) Central System

455

Table SH1. Total Households Using a Space Heating Fuel, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households Using a Space Heating Fuel, 2005 Million U.S. Households Using a Non-Major Fuel 5 ... Space Heating (millions) Energy Information Administration

456

Testing Electric Vehicle Demand in `Hybrid Households' Using a Reflexive Survey  

E-Print Network (OSTI)

1994) Demand for Electric Vehicles in Hybrid Households: A nand the Household Electric Vehicle Market: A Constraintsthe mar- ket for electric vehicles in California. Presented

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

457

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

E-Print Network (OSTI)

of Household Income and Appliance Ownership. ECEEE Summerof decreasing prices of appliances, if price data becomesForecasting Household Appliance Ownership in a Growing

Letschert, Virginie

2010-01-01T23:59:59.000Z

458

2009 Energy Consumption Per Person  

Energy.gov (U.S. Department of Energy (DOE))

Per capita energy consumption across all sectors of the economy. Click on a state for more information.

459

Determination of Baselines for Evaluation and Promotion of Energy Efficiency in Wastewater Treatment Facilities  

E-Print Network (OSTI)

Wastewater treatment plants are one of the largest energy consumers managed by the public sector. As plants expand in the future to accommodate population growth, energy requirements will substantially increase. Thus, implementation of energy efficient technologies is crucial in reducing national energy consumption. A detailed understanding of the current industry standards (baselines) is needed to estimate the energy savings potential for advanced state-of-the-art technologies and to provide incentives for application of the new technologies in retrofit and new construction projects. This paper summarizes the process BASE Energy, Inc. (BASE) went through to establish baselines to compare the energy performance of potential energy efficient technologies in the wastewater treatment industry that can be applied to energy efficiency programs available for wastewater treatment plants.

Chow, S. A.; Ganji, A. R.; Fok, S.

2009-05-01T23:59:59.000Z

460

NETL - Bituminous Baseline Performance and Cost Interactive Tool | Open  

Open Energy Info (EERE)

NETL - Bituminous Baseline Performance and Cost Interactive Tool NETL - Bituminous Baseline Performance and Cost Interactive Tool Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Bituminous Baseline Performance and Cost Interactive Tool Agency/Company /Organization: National Energy Technology Laboratory Sector: Energy Topics: Baseline projection, GHG inventory Resource Type: Software/modeling tools Website: www.netl.doe.gov/energy-analyses/refshelf/results.asp?ptype=Models/Too References: Bituminous Baseline Performance and Cost Interactive Tool [1] Bituminous Baseline Performance and Cost Interactive Tool The Bituminous Baseline Performance and Cost Interactive Tool illustrates key data from the Cost and Performance Baseline for Fossil Energy Plants - Bituminous Coal and Natural Gas to Electricity report. The tool provides an

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Grocery 2009 TSD Chicago Baseline | Open Energy Information  

Open Energy Info (EERE)

Type Baseline Model Target Type ASHRAE 90.1 2004 Model Year 2009 IDF file http:apps1.eere.energy.govbuildingsenergyplusmodelsChicago2009TSDGroceryBaseline.idf XML file...

462

Grocery 2009 TSD Miami Baseline | Open Energy Information  

Open Energy Info (EERE)

Type Baseline Model Target Type ASHRAE 90.1 2004 Model Year 2009 IDF file http:apps1.eere.energy.govbuildingsenergyplusmodelsMiami2009TSDGroceryBaseline.idf XML file...

463

Proposed Methodology for LEED Baseline Refrigeration Modeling (Presentation)  

SciTech Connect

This PowerPoint presentation summarizes a proposed methodology for LEED baseline refrigeration modeling. The presentation discusses why refrigeration modeling is important, the inputs of energy models, resources, reference building model cases, baseline model highlights, example savings calculations and results.

Deru, M.

2011-02-01T23:59:59.000Z

464

US Biofuels Baseline and impact of extending the  

E-Print Network (OSTI)

June 2011 US Biofuels Baseline and impact of extending the $0.45 ethanol blenders baseline projections for agricultural and biofuel markets.1 That baseline assumed current biofuel policy for cellulosic biofuels was assumed to expire at the end of 2012. This report compares a slightly modified

Noble, James S.

465

The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures  

SciTech Connect

In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

Eisenberg, Joel Fred [ORNL

2008-06-01T23:59:59.000Z

466

The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures  

SciTech Connect

In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

Eisenberg, Joel Fred [ORNL

2008-06-01T23:59:59.000Z

467

ENERGY CONSUMPTION SURVEY  

U.S. Energy Information Administration (EIA) Indexed Site

5 RESIDENTIAL TRANSPORTATION 5 RESIDENTIAL TRANSPORTATION ENERGY CONSUMPTION SURVEY Prepared for: UNITED STATES DEPARTMENT OF ENERGY ENERGY INFORMATION ADMINISTRATION OFFICE OF ENERGY MARKETS AND END USE ENERGY END USE DIVISION RESIDENTIAL AND COMMERCIAL BRANCH WASHINGTON, DC 20585 Prepared by: THE ORKAND CORPORATION 8484 GEORGIA AVENUE SILVER SPRING, MD 20910 October 1986 Contract Number DE-AC01-84EI19658 TABLE OF CONTENTS FRONT MATTER Index to Program Descriptions........................................... vi List of Exhibits ....................................................... viii Acronyms and Abbreviations ............................................. ix SECTION 1: GENERAL INFORMATION ........................................ 1-1 1.1. Summary ....................................................... 1-1

468

Margins up; consumption down  

SciTech Connect

The results of a survey of dealers in the domestic fuel oil industry are reported. Wholesale prices, reacting to oversupply, decreased as did retail prices; retail prices decreased at a slower rate so profit margins were larger. This trend produced competitive markets as price-cutting became the method for increasing a dealer's share of the profits. Losses to other fuels decreased, when the figures were compared to earlier y; and cash flow was very good for most dealers. In summary, profits per gallon of oil delivered increased, while the consumption of gasoline per customer decreased. 22 tables.

Mantho, M.

1983-09-01T23:59:59.000Z

469

Reducing Greenhouse Emissions and Fuel Consumption  

E-Print Network (OSTI)

the Emissions and Fuel Consumption Impacts of IntelligentTravel Time, Fuel Consumption and Weigh Station Efficiency.EMISSIONS AND FUEL CONSUMPTION - Sustainable Approaches for

Shaheen, Susan; Lipman, Timothy

2007-01-01T23:59:59.000Z

470

Essays on consumption cycles and corporate finance  

E-Print Network (OSTI)

and the consumption cycle . . . . . . . . . . . . .3.1.6 Optimal consumption, expenditures and1.3.2 Optimal nondurable consumption and durable

Issler, Paulo Floriano

2013-01-01T23:59:59.000Z

471

Milk consumption and acne in adolescent girls  

E-Print Network (OSTI)

Milk consumption and acne in adolescent girls Clement Aassociation between milk consumption and occurrence of acneand 'don't drink milk'. Consumption of the specific types of

2006-01-01T23:59:59.000Z

472

A Note on the Consumption Function  

E-Print Network (OSTI)

Zeldes, S. (1989) ‘ Consumption and Liquidity Constraints:A Note on the Consumption Function Douglas G.Steigerwald Consumption Function The international

Steigerwald, Douglas G

2009-01-01T23:59:59.000Z

473

Stock Market and Consumption: Evidence from China  

E-Print Network (OSTI)

A. 1992. Understanding Consumption. Cambridge, UK: CambridgeStock market wealth and consumption. The Journal of Economic139–146. Stock Market and Consumption: Evidence from China

Hau, Leslie C

2011-01-01T23:59:59.000Z

474

Measurement of nicotine in household dust  

Science Conference Proceedings (OSTI)

An analytical method of measuring nicotine in house dust was optimized and associations among three secondhand smoking exposure markers were evaluated, i.e., nicotine concentrations of both house dust and indoor air, and the self-reported number of cigarettes smoked daily in a household. We obtained seven house dust samples from self-reported nonsmoking homes and 30 samples from smoking homes along with the information on indoor air nicotine concentrations and the number of cigarettes smoked daily from an asthma cohort study conducted by the Johns Hopkins Center for Childhood Asthma in the Urban Environment. House dust nicotine was analyzed by isotope dilution gas chromatography-mass spectrometry (GC/MS). Using our optimized method, the median concentration of nicotine in the dust of self-reported nonsmoking homes was 11.7 ng/mg while that of smoking homes was 43.4 ng/mg. We found a substantially positive association (r=0.67, P<0.0001) between house dust nicotine concentrations and the numbers of cigarettes smoked daily. Optimized analytical methods showed a feasibility to detect nicotine in house dust. Our results indicated that the measurement of nicotine in house dust can be used potentially as a marker of longer term SHS exposure.

Kim, Sungroul [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Institute for Global Tobacco Control, 627 N. Washington Street, 2nd Floor Baltimore, MD 21205 (United States); Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)], E-mail: srkim@jhsph.edu; Aung, Ther; Berkeley, Emily [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Diette, Gregory B. [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Department of Medicine, Johns Hopkins University School of Medicine (United States); Breysse, Patrick N. [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)

2008-11-15T23:59:59.000Z

475

Indexes of Consumption and Production  

U.S. Energy Information Administration (EIA) Indexed Site

Figure on manufacturing production indexes and purchased energy consumption Figure on manufacturing production indexes and purchased energy consumption Source: Energy Information Administration and Federal Reserve Board. History of Shipments This chart presents indices of 14 years (1980-1994) of historical data of manufacturing production indexes and Purchased (Offsite-Produced) Energy consumption, using 1992 as the base year (1992 = 100). Indexing both energy consumption and production best illustrates the trends in output and consumption. Taken separately, these two indices track the relative growth rates within the specified industry. Taken together, they reveal trends in energy efficiency. For example, a steady increase in output, coupled with a decline in energy consumption, represents energy efficiency gains. Likewise, steadily rising energy consumption with a corresponding decline in output illustrates energy efficiency losses.

476

U.S. Climate Zones-Households - - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Residential Sector energy Intensities for 1978-1997 using data from EIA Residential Energy Consumption Survey.

477

Feedback as a means of decreasing residential energy consumption. Report PU/CES 34  

SciTech Connect

When residential units are analyzed in human factor terms, it is apparent that the consumption level feedback (typically a bill, calculated once a month, over all appliances) is inadequate to give the resident useful information about his energy consuming actions. The present study tested the hypothesis that providing immediate feedback to homeowners concerning their daily rate of electric usage would be effective in reducing electric consumption. In the studied homes, central air-conditioning is the largest single source of electric power consumption during the summer. Accordingly, it was possible to predict the household's expected electric consumption in terms of the average daily outdoor temperature. Predicted electric consumption was derived from a previous month's modeling period during which a regression line was fitted to predict consumption from average daily temperature, for each home. Feedback was expressed as a percentage of actual consumption over predicted consumption. Feedback was displayed to homeowners four times a week for approximately one month. The results confirmed the prediction. Before feedback began, the feedback and control groups were consuming electricity at approximately equal rates. During the feedback period, the feedback group used 10.5 percent less electricity. The effectiveness of the feedback procedure was explained in terms of its cueing, motivational, and commitment functions.

Seligman, C.; Darley, J.M.

1976-08-01T23:59:59.000Z

478

Household Preferences for Supporting Renewable Energy, and Barriers...  

NLE Websites -- All DOE Office Websites (Extended Search)

Household Preferences for Supporting Renewable Energy, and Barriers to Green Power Demand Speaker(s): Ryan Wiser Date: May 9, 2002 - 12:00pm Location: Bldg. 90 Nearly 40% of the...

479

A Theoretical Basis for Household Energy Conservation UsingProduct...  

NLE Websites -- All DOE Office Websites (Extended Search)

A Theoretical Basis for Household Energy Conservation Using Product-Integrated Feedback Speaker(s): Teddy McCalley Date: October 11, 2002 - 12:00pm Location: Bldg. 90 Seminar Host...

480

Manufacturing Consumption of Energy 1991--Combined Consumption and Fuel  

U.S. Energy Information Administration (EIA) Indexed Site

< < Welcome to the U.S. Energy Information Administration's Manufacturing Web Site. If you are having trouble, call 202-586-8800 for help. Return to Energy Information Administration Home Page. Home > Energy Users > Manufacturing > Consumption and Fuel Switching Manufacturing Consumption of Energy 1991 (Combined Consumption and Fuel Switching) Overview Full Report Tables & Spreadsheets This report presents national-level estimates about energy use and consumption in the manufacturing sector as well as manufacturers' fuel-switching capability. Contact: Stephanie.battle@eia.doe.gov Stephanie Battle Director, Energy Consumption Division Phone: (202) 586-7237 Fax: (202) 586-0018 URL: http://www.eia.gov/emeu/mecs/mecs91/consumption/mecs1a.html File Last Modified: May 25, 1996

Note: This page contains sample records for the topic "baseline household consumption" from the National Library of EnergyBeta (NLEBeta).
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481

Characterizing Household Plug Loads through Self-Administered Load Research  

Science Conference Proceedings (OSTI)

Household miscellaneous loads, which include consumer electronics, are the fastest growing segment of household energy use in the United States. Although the relative energy intensity of applications such as heating and cooling is declining, the DOEAnnual Energy Outlook forecasts that the intensity of residential miscellaneous end uses will increase substantially by 2030. Studies by TIAX and Ecos Consulting reveal that miscellaneous devices8212smaller devices in terms of energy draw but growing in usage8...

2009-12-09T23:59:59.000Z

482

Household waste disposal in Mekelle city, Northern Ethiopia  

SciTech Connect

In many cities of developing countries, such as Mekelle (Ethiopia), waste management is poor and solid wastes are dumped along roadsides and into open areas, endangering health and attracting vermin. The effects of demographic factors, economic and social status, waste and environmental attributes on household solid waste disposal are investigated using data from household survey. Household level data are then analyzed using multinomial logit estimation to determine the factors that affect household waste disposal decision making. Results show that demographic features such as age, education and household size have an insignificant impact over the choice of alternative waste disposal means, whereas the supply of waste facilities significantly affects waste disposal choice. Inadequate supply of waste containers and longer distance to these containers increase the probability of waste dumping in open areas and roadsides relative to the use of communal containers. Higher household income decreases the probability of using open areas and roadsides as waste destinations relative to communal containers. Measures to make the process of waste disposal less costly and ensuring well functioning institutional waste management would improve proper waste disposal.

Tadesse, Tewodros [Agricultural Economics and Rural Policy Group, Wageningen University, Hollandseweg 1 6706 KN Wageningen (Netherlands)], E-mail: tewodroslog@yahoo.com; Ruijs, Arjan [Environmental Economics and Natural Resources Group, Wageningen University, P.O. Box 8130, 6700 EW Wageningen (Netherlands); Hagos, Fitsum [International Water Management Institute (IWMI), Subregional Office for the Nile Basin and East Africa, P.O. Box 5689, Addis Ababa (Ethiopia)

2008-07-01T23:59:59.000Z

483

Ventilation Behavior and Household Characteristics in NewCalifornia Houses  

SciTech Connect

A survey was conducted to determine occupant use of windows and mechanical ventilation devices; barriers that inhibit their use; satisfaction with indoor air quality (IAQ); and the relationship between these factors. A questionnaire was mailed to a stratified random sample of 4,972 single-family detached homes built in 2003, and 1,448 responses were received. A convenience sample of 230 houses known to have mechanical ventilation systems resulted in another 67 completed interviews. Some results are: (1) Many houses are under-ventilated: depending on season, only 10-50% of houses meet the standard recommendation of 0.35 air changes per hour. (2) Local exhaust fans are under-utilized. For instance, about 30% of households rarely or never use their bathroom fan. (3) More than 95% of households report that indoor air quality is ''very'' or ''somewhat'' acceptable, although about 1/3 of households also report dustiness, dry air, or stagnant or humid air. (4) Except households where people cook several hours per week, there is no evidence that households with significant indoor pollutant sources get more ventilation. (5) Except households containing asthmatics, there is no evidence that health issues motivate ventilation behavior. (6) Security and energy saving are the two main reasons people close windows or keep them closed.

Price, Phillip N.; Sherman, Max H.

2006-02-01T23:59:59.000Z

484

Source separation of household waste: A case study in China  

SciTech Connect

A pilot program concerning source separation of household waste was launched in Hangzhou, capital city of Zhejiang province, China. Detailed investigations on the composition and properties of household waste in the experimental communities revealed that high water content and high percentage of food waste are the main limiting factors in the recovery of recyclables, especially paper from household waste, and the main contributors to the high cost and low efficiency of waste disposal. On the basis of the investigation, a novel source separation method, according to which household waste was classified as food waste, dry waste and harmful waste, was proposed and performed in four selected communities. In addition, a corresponding household waste management system that involves all stakeholders, a recovery system and a mechanical dehydration system for food waste were constituted to promote source separation activity. Performances and the questionnaire survey results showed that the active support and investment of a real estate company and a community residential committee play important roles in enhancing public participation and awareness of the importance of waste source separation. In comparison with the conventional mixed collection and transportation system of household waste, the established source separation and management system is cost-effective. It could be extended to the entire city and used by other cities in China as a source of reference.

Zhuang Ying; Wu Songwei; Wang Yunlong [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China); Wu Weixiang [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)], E-mail: weixiang@zju.edu.cn; Chen Yingxu [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)

2008-07-01T23:59:59.000Z

485

Transferring 2001 National Household Travel Survey  

Science Conference Proceedings (OSTI)

Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle Atlantic, and Pacific), MSA size, and the availability of rail. Extrapolating NHTS data within small geographic areas could risk developing and subsequently using unreliable estimates. For example, if a planning agency in City X of State Y estimates travel rates and other travel characteristics based on survey data collected from NHTS sample households that were located in City X of State Y, then the agency could risk developing and using unreliable estimates for their planning process. Typically, this limitation significantly increases as the size of an area decreases. That said, the NHTS contains a wealth of information that could allow statistical inferences about small geographic areas, with a pre-determined level of statistical certainty. The question then becomes whether a method can be developed that integrates the NHTS data and other data to estimate key travel characteristics for small geographic areas such as Census tract and transportation analysis zone, and whether this method can outperform other, competing methods.

Hu, Patricia S [ORNL; Reuscher, Tim [ORNL; Schmoyer, Richard L [ORNL; Chin, Shih-Miao [ORNL

2007-05-01T23:59:59.000Z

486

Electrical appliance energy consumption control methods and ...  

Electrical appliance energy consumption control methods and electrical energy consumption systems are described. In one aspect, an electrical appliance energy ...

487

Map Data: State Consumption | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Consumption Map Data: State Consumption stateconsumptionpc2009.csv More Documents & Publications Map Data: Renewable Production Map Data: State Spending...

488

Consumption & Efficiency - Analysis & Projections - U.S ...  

U.S. Energy Information Administration (EIA)

Today in Energy - Commercial Consumption & Efficiency. Short, timely articles with graphs about recent commercial consumption and efficiency ...

489

LTC vacuum blasting machine (metal): Baseline report  

SciTech Connect

The LTC coating removal technology was tested and is being evaluated at Florida International University (FIU) as a baseline technology. In conjunction with evaluation of efficiency and cost, this report covers the evaluation conducted for safety and health issues. It is a commercially available technology and has been used for various projects at locations throughout the country. The LTC coating removal system consisted of several hand tools, a Roto Peen scaler, and a needlegun. They are designed to remove coatings from steel, concrete, brick, and wood. These hand tools are used with the LTC PTC-6 vacuum system to capture dust and debris as removal of the coating takes place. The safety and health evaluation during the testing demonstration focused on two main areas of exposure: dust and noise. The dust exposure was minimal but noise exposure was significant. Further testing for each exposure is recommended because of the environment where the testing demonstration took place. It is feasible that the dust and noise levels will be higher in an enclosed operating environment of different construction. In addition, other areas of concern found were arm-hand vibration, whole-body vibration, ergonomi