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Note: This page contains sample records for the topic "average household energy" from the National Library of EnergyBeta (NLEBeta).
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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 Vehicles Energy Consumption 1991  

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

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...

2

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

3

Fact #614: March 15, 2010 Average Age of Household Vehicles  

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

The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first...

4

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

5

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  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.  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

6

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  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.  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

7

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

8

Household Vehicles Energy Use Cover Page  

Annual Energy Outlook 2012 (EIA)

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

9

Communications on energy Household energy conservation  

Science Journals Connector (OSTI)

This study assesses the influence of attitudinal and socio-economic factors on household energy conservation actions. A household interview survey in Regina, Saskatchewan found that respondents perceive an energy problem, although no association with energy conservation actions was determined. Two attitudinal and five socio-economic variables influence household energy conservation. Energy and monetary savings are available to households through energy conservation. Public awareness of household energy conservation through the media can reinforce existing energy conservation actions and encourage new actions.

Fred A. Curtis; P. Simpson-Housley; S. Drever

1984-01-01T23:59:59.000Z

10

Household Vehicles Energy Consumption 1991  

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

vehicle aging have an additional but unknown effect on the MPG of individual vehicles. Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 27 Of the...

11

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

12

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

Gasoline and Diesel Fuel Update (EIA)

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

13

Household vehicles energy consumption 1991  

SciTech Connect

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

14

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

15

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

16

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

17

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

18

Household energy consumption and expenditures 1993  

SciTech Connect

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

19

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

20

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.

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

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

22

Household Vehicles Energy Consumption 1991  

Gasoline and Diesel Fuel Update (EIA)

or More...... 23.1 15.2 197 12.3 10.7 13.0 1.3 12.8 13.0| 6.7 | Race of Householder | White... 135.3 89.5 1,429 89.2 73.9 89.2 9.1 87.5 89.1| 2.0...

23

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.

24

Survey of Household Energy Use (SHEU)  

E-Print Network (OSTI)

Survey of Household Energy Use (SHEU) 2003 Detailed Statistical Report #12;To obtain additional copies of this or other free publications on energy efficiency, please contact: Energy Publications Office of Energy Efficiency Natural Resources Canada c/o St. Joseph Communications Order Processing Unit

25

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...

26

Household transitions to energy efficient lighting  

Science Journals Connector (OSTI)

Abstract New energy efficient lighting technologies can significantly reduce household electricity consumption, but adoption has been slow. A unique dataset of German households is used in this paper to examine the factors associated with the replacement of old incandescent lamps (ILs) with new energy efficient compact fluorescent lamps (CFLs) and light emitting diodes (LEDs). The rebound effect of increased lamp luminosity in the transition to energy efficient bulbs is analyzed jointly with the replacement decision to account for household self-selection in bulb-type choice. Results indicate that the EU ban on \\{ILs\\} accelerated the pace of transition to \\{CFLs\\} and LEDs, while storage of bulbs significantly dampened the speed of the transition. Higher lighting needs and bulb attributes like energy efficiency, environmental friendliness, and durability spur IL replacement with \\{CFLs\\} or LEDs. Electricity gains from new energy efficient lighting are mitigated by 23% and 47% increases in luminosity for CFL and LED replacements, respectively. Model results suggest that taking the replacement bulb from storage and higher levels of education dampen the magnitude of these luminosity rebounds in IL to CFL transitions.

Bradford Mills; Joachim Schleich

2014-01-01T23:59:59.000Z

27

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

Neighborhood Program GETS Green Energy Training ServicesGJGEI Green Jobs, Green Energy Initiative CEWO Cleanincome households. The Green Energy Training Services (GETS)

Zimring, Mark

2012-01-01T23:59:59.000Z

28

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

29

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

30

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

31

Barriers to household investment in residential energy conservation: preliminary assessment  

SciTech Connect

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

32

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" 1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Midwest",25.9,2272,1898,1372,912,762,551 "Midwest Divisions and States" "East North Central",17.9,2251,1869,1281,892,741,508 "Illinois",4.8,2186,1911,1451,860,752,571 "Michigan",3.8,1954,1559,962,729,582,359 "Wisconsin",2.3,2605,2091,1258,1105,887,534

33

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

3 Average Square Footage of West Homes, by Housing Characteristics, 2009" 3 Average Square Footage of West Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total West",24.8,1708,1374,800,628,506,294 "West Divisions and States" "Mountain",7.9,1928,1695,1105,723,635,415 "Mountain North",3.9,2107,1858,912,776,684,336 "Colorado",1.9,2082,1832,722,896,788,311 "Idaho, Montana, Utah, Wyoming",2,2130,1883,1093,691,610,354

34

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.

35

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.

1991-12-31T23:59:59.000Z

36

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

37

Household energy consumption and its demand elasticity in Thailand  

Science Journals Connector (OSTI)

This study concentrates on the analysis of energy consumption, expenditure on oil and LPG use in cars and aims to examine the elasticity effect of various types of oil consumption. By using the Deaton's analysis framework, the cross-sectional data of Thai households economic survey 2009 were used. By defining energy goods in the scope of automobile fuel, the results reflect the low importance of high-quality automobile fuel on all income level households. Thai households tend to vary the quality rather than the quantity of thermal energy. All income groups have a tendency to switch to lower quality fuel. Middle and high-middle households (Q3 and Q4) are the income groups with the greatest tendency to switch to lower-quality fuel when a surge in the price of oil price occurs. The poorest households (Q1) are normally insensitive to a change of energy expenditure in terms of quality and quantity. This finding illustrates the LPG price subsidy policy favours middle and high-middle income households. The price elasticity of energy quantity demand is negative in all income levels. High to middle income families are the most sensitive to changes in the price of energy.

Montchai Pinitjitsamut

2012-01-01T23:59:59.000Z

38

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.

39

Water Related Energy Use in Households and Cities - an Australian  

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

Water Related Energy Use in Households and Cities - an Australian Water Related Energy Use in Households and Cities - an Australian Perspective Speaker(s): Steven Kenway Date: May 12, 2011 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Anita Estner James McMahon This presentation covers the content of recent journal papers and reports focused on the water-energy nexus and the related theory of urban metabolism. This includes (i) a review of the water-energy nexus focused on cities (ii) quantifying water-related energy in cities (iii) modeling household water-related energy use including key factors, sensitivity and uncertainty analysis, and (iv) relevance and implications of the urban metabolism theoretical framework. Steven's work focuses on understanding the indirect connections between urban water management, energy use and

40

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

2 Average Square Footage of South Homes, by Housing Characteristics, 2009" 2 Average Square Footage of South Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total South",42.1,1867,1637,1549,732,642,607 "South Divisions and States" "South Atlantic",22.2,1944,1687,1596,771,668,633 "Virginia",3,2227,1977,1802,855,759,692 "Georgia",3.5,2304,1983,1906,855,736,707 "Florida",7,1668,1432,1509,690,593,625 "DC, DE, MD, WV",3.4,2218,1831,1440,864,713,561

Note: This page contains sample records for the topic "average household energy" 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

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

4 Average Square Footage of Single-Family Homes, by Housing Characteristics, 2009" 4 Average Square Footage of Single-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Single-Family",78.6,2422,2002,1522,880,727,553 "Census Region" "Northeast",12.7,2843,2150,1237,1009,763,439 "Midwest",19.2,2721,2249,1664,1019,842,624 "South",29.7,2232,1945,1843,828,722,684 "West",16.9,2100,1712,1009,725,591,348 "Urban and Rural3"

42

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" 0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Northeast",20.8,2121,1663,921,836,656,363 "Northeast Divisions and States" "New England",5.5,2232,1680,625,903,680,253 "Massachusetts",2.5,2076,1556,676,850,637,277 "CT, ME, NH, RI, VT",3,2360,1781,583,946,714,234 "Mid-Atlantic",15.3,2080,1657,1028,813,647,402

43

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

5 Average Square Footage of Multi-Family Homes, by Housing Characteristics, 2009" 5 Average Square Footage of Multi-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Multi-Family",28.1,930,807,535,453,393,261 "Census Region" "Northeast",7.6,991,897,408,471,426,194 "Midwest",5.6,957,857,518,521,466,282 "South",8.4,924,846,819,462,423,410 "West",6.5,843,606,329,374,269,146 "Urban and Rural3" "Urban",26.9,927,803,531,450,390,258

44

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

6 Average Square Footage of Mobile Homes, by Housing Characteristics, 2009" 6 Average Square Footage of Mobile Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Mobile Homes",6.9,1087,985,746,413,375,283 "Census Region" "Northeast",0.5,1030,968,711,524,492,362 "Midwest",1.1,1090,1069,595,400,392,218 "South",3.9,1128,1008,894,423,378,335 "West",1.4,995,867,466,369,322,173 "Urban and Rural3" "Urban",3.5,1002,919,684,396,364,271

45

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

9 Average Square Footage of U.S. Homes, by Housing Characteristics, 2009" 9 Average Square Footage of U.S. Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total",113.6,1971,1644,1230,766,639,478 "Census Region" "Northeast",20.8,2121,1663,921,836,656,363 "Midwest",25.9,2272,1898,1372,912,762,551 "South",42.1,1867,1637,1549,732,642,607 "West",24.8,1708,1374,800,628,506,294 "Urban and Rural3" "Urban",88.1,1857,1546,1148,728,607,450

46

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

47

Delivering Energy Efficiency to Middle Income Single Family Households  

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

Delivering Energy Efficiency to Middle Income Single Family Households Delivering Energy Efficiency to Middle Income Single Family Households Title Delivering Energy Efficiency to Middle Income Single Family Households Publication Type Report Year of Publication 2011 Authors Zimring, Mark, Merrian Borgeson, Ian M. Hoffman, Charles A. Goldman, Elizabeth Stuart, Annika Todd, and Megan A. Billingsley Pagination 102 Date Published 12/2011 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract The question posed in this report is: How can programs motivate these middle income single family households to seek out more comprehensive energy upgrades, and empower them to do so? Research methods included interviews with more than 35 program administrators, policy makers, researchers, and other experts; case studies of programs, based on interviews with staff and a review of program materials and data; and analysis of relevant data sources and existing research on demographics, the financial status of Americans, and the characteristics of middle income American households. While there is no 'silver bullet' to help these households overcome the range of barriers they face, this report describes outreach strategies, innovative program designs, and financing tools that show promise in increasing the attractiveness and accessibility of energy efficiency for this group. These strategies and tools should be seen as models that are currently being honed to build our knowledge and capacity to deliver energy improvements to middle income households. However, the strategies described in this report are probably not sufficient, in the absence of robust policy frameworks, to deliver these improvements at scale. Instead, these strategies must be paired with enabling and complementary policies to reach their full potential.

48

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)

49

Table 5.12. U.S. Average Vehicle-Miles Traveled by Household...  

Annual Energy Outlook 2012 (EIA)

... 30.7 Q 26.3 37.2 Q Q Q Q Q Q Q 20.7 Race of Householder White ... 26.0 23.2 25.2 32.6 19.3 16.4 13.3...

50

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

51

Laser Fusion Energy The High Average Power  

E-Print Network (OSTI)

Laser Fusion Energy and The High Average Power Program John Sethian Naval Research Laboratory Dec for Inertial Fusion Energy with lasers, direct drive targets and solid wall chambers Lasers DPPSL (LLNL) Kr posters Snead Payne #12;Laser(s) Goals 1. Develop technologies that can meet the fusion energy

52

Household Vehicles Energy Use: Latest Data & Trends  

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

E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATIONHOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W INTRODUCTION Author's...

53

Energy demand of German households and saving potential  

Science Journals Connector (OSTI)

The implementation of the principles of sustainable development requires both using potentialities in saving resources and cutting down emissions (efficiency strategies) as well as more conscious patterns of behaviour of the actors involved (sufficiency strategies). Starting from the current situation of annual CO2 emissions of about 10 t and a sustainability goal of 1??2 t CO2 emissions per inhabitant and year, the question arises in how far households can contribute to achieve this goal. Therefore, in this paper, the environmental impacts of the energy demand of German households will be evaluated by means of describing its status quo and there from deriving saving potentials.

Anke Eber; Dominik Most; Otto Rentz; Thomas Lutzkendorf

2008-01-01T23:59:59.000Z

54

Household Vehicles Energy Use: Latest Data & Trends  

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

This page left blank. E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATIONHOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W...

55

Household Vehicles Energy Use: Latest Data & Trends  

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

This page left blank. This page left blank. E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATION/HOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W INTRODUCTION Author's Note Estimates of gallons of fuel consumed, type of fuel used, price paid for fuel, and fuel economy are based on data imputed by EIA, using vehicle characteristics and vehicle-miles traveled data collected during the interview process for the 2001 National Household Travel Survey (NHTS). Rather than obtaining that information directly from fuel purchase diaries, EIA exploited its experience and expertise with modeling techniques for transportation studies, filling missing and uncollected data with information reported to other federal agencies, as described in Appendices

56

Household Vehicles Energy Use: Latest Data & Trends  

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

E E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATION/HOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W INTRODUCTION Author's Note Estimates of gallons of fuel consumed, type of fuel used, price paid for fuel, and fuel economy are based on data imputed by EIA, using vehicle characteristics and vehicle-miles traveled data collected during the interview process for the 2001 National Household Travel Survey (NHTS). Rather than obtaining that information directly from fuel purchase diaries, EIA exploited its experience and expertise with modeling techniques for transportation studies, filling missing and uncollected data with information reported to other federal agencies, as described in Appendices B and C of this report.

57

Household Vehicles Energy Use: Latest Data & Trends  

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

to on-road, in-use fuel economy, EIA has extended this inventory to include the energy used for travel, thereby continuing a data series that was discontinued by EIA in...

58

Lifestyle change and energy use in Japan: Household equipment and energy consumption  

Science Journals Connector (OSTI)

Energy use in the Japanese residential sector has more than doubled (on a per-household basis) during the post-war period. Important factors contributing to the increase include changes in the types of housing built, heating, cooling, water-heating equipment, and other appliances. In this paper, the developments of household equipment and living conditions in Japan are described, from their 1950s state to the present. Trends in energy consumption by fuel types and end uses are reviewed over the same period. The past trends are combined with expectations for future developments in household equipment and quality, as well as with international comparisons of household-energy use, to predict further increases in household-energy consumption. The results indicate the importance of a renewed emphasis on energy efficiency in the residential sector.

Hidetoshi Nakagami

1996-01-01T23:59:59.000Z

59

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

60

Household Vehicles Energy Use: Latest Data & Trends  

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

B B : E S T I M AT I O N M E T H O D O L O G I E S APPENDIX B A P P E N D I X B ESTIMATION METHODOLOGIES INTRODUCTION The National Household Travel Survey (NHTS) is the nation's inventory of local and long distance travel, according to the U.S. Department of Transportation. Between April 2001 and May 2002, roughly 26 thousand households 41 were interviewed about their travel, based on the use of over 53 thousand vehicles. Using confidential data collected during those interviews, coupled with EIA's retail fuel prices, external data sources of test 42 fuel economy, and internal procedures for modifying test fuel economy to on-road, in-use fuel economy, EIA has extended this inventory to include the energy used for travel, thereby continuing a data series that was discontinued by EIA in 1994. This appendix presents the methods used for each eligible sampled

Note: This page contains sample records for the topic "average household energy" 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

Greenhouse Gas Implications of Household Energy Technology in Kenya  

Science Journals Connector (OSTI)

Energy and Resources Group, University of California, Berkeley, California 94720-3050, Risk, Resource, and Environmental Management Division, Resources for the Future, 1616 P Street NW, Washington, D.C. 20036, and Goldman School of Public Policy, University of California, Berkeley, California 94720-7320 ... Household energy policy is further complicated because charcoal markets in many sub-Saharan African countries operate within a complex political economy that can be hard to characterize and still more difficult to regulate. ... While charcoal consumption carries a larger burden of GHG emissions than firewood use, it also has more potential to attract investment in GHG mitigation activities. ...

Rob Bailis; Majid Ezzati; Daniel M. Kammen

2003-04-01T23:59:59.000Z

62

Rural household energy consumption and its implications for eco-environments in NW China: A case study  

Science Journals Connector (OSTI)

Abstract Rural household energy consumption plays an essential role in the daily life of farmers, especially in developing regions. In this paper, we present a study of household energy consumption in terms of energy sources and energy end uses, and analysis of technical and economic issues associated with the use of biomass and renewable energy and the replacement of fossil fuels. Results show that energy from biomass represents the largest share of total energy supply, and that 41.15% of total energy is consumed for home heating and cooking. The average cost of household energy is 1259 RMB ($US193.6) and this expense is no longer subsidized by the government. It takes less than one year to make a solar stove profitable and less than two years to pay back the household cost of biogas digesters. An 8m3 digester can produce as much energy as 500550kg of standard coal or 940kg of firewood, while a solar stove can generate 1.76נ103MJ heat each year. Moreover, it is estimated that in rural China the annual reduction of CO2 and SO2 emissions in 2020, due to the replacement of fossil fuel by biomass, will be 68.86נ106 and 54.37נ104 tons, respectively. Overall, the investigations and analyses have revealed that the structure of rural household energy consumption is undergoing a transformation from traditional low-efficiency biomass domination to integrated consumption of traditional and renewable energies. Renewable energy will significantly contribute to the sustainable development of rural households.

Hewen Niu; Yuanqing He; Umberto Desideri; Peidong Zhang; Hongyi Qin; Shijin Wang

2014-01-01T23:59:59.000Z

63

Household Vehicles Energy Use: Latest Data & Trends  

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

C C : Q U A L I T Y O F T H E D ATA APPENDIX C A P P E N D I X C QUALITY OF THE DATA INTRODUCTION This section discusses several issues relating to the quality of the National Household Travel Survey (NHTS) data and to the interpretation of conclusions based on these data. In particular, the focus of our discussion is on the quality of specific data items, such as the fuel economy and fuel type, that were imputed to the NHTS via a cold-decking imputation procedure. This imputation procedure used vehicle-level information from the NHTSA Corporate Average Fuel Economy files for model year's 1978 through 2001. It is nearly impossible to quantify directly the quality of this imputation procedure because NHTS does not collect the necessary fuel economy information for comparison. At best, we have indirect evidence on the quality of our

64

How Do You Encourage Everyone in Your Household to Save Energy? |  

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

Everyone in Your Household to Save Energy? Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people-be they roommates, spouses, children, or maybe even yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

65

How Do You Encourage Everyone in Your Household to Save Energy? |  

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

Do You Encourage Everyone in Your Household to Save Energy? Do You Encourage Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people-be they roommates, spouses, children, or maybe even yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

66

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

67

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

68

Property:SalinityAverage | Open Energy Information  

Open Energy Info (EERE)

SalinityAverage SalinityAverage Jump to: navigation, search Property Name SalinityAverage Property Type Number Description Mean average of the low and high end measurements of the salinity [ppm] of the fluid. This is a property of type Page. Subproperties This property has the following 1 subproperty: C Coso Geothermal Area Pages using the property "SalinityAverage" Showing 19 pages using this property. A Amedee Geothermal Area + 975 + B Beowawe Hot Springs Geothermal Area + 700 + Blue Mountain Geothermal Area + 4300 + Brady Hot Springs Geothermal Area + 3500 + C Chena Geothermal Area + 325 + D Desert Peak Geothermal Area + 6700 + Dixie Valley Geothermal Area + 2295 + E East Mesa Geothermal Area + 3750 + G Geysers Geothermal Area + 217 + K Kilauea East Rift Geothermal Area + 18750 +

69

Energy Policy 30 (2002) 815826 Evaluating the health benefits of transitions in household energy  

E-Print Network (OSTI)

as the primary source of domestic energy, has put preventive measures to reduce exposure to indoor air pollutionEnergy Policy 30 (2002) 815­826 Evaluating the health benefits of transitions in household energy for the Future, 1616 P Street NW, Washington, DC 20036, USA b Epidemiology and Burden of Disease Unit, Global

Kammen, Daniel M.

70

Drivers of U.S. Household Energy Consumption, 1980-2009  

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

Drivers of U.S. Household Energy Consumption, 1980-2009 February 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy...

71

Modelling useful energy demand system as derived from basic needs in the household sector  

Science Journals Connector (OSTI)

Inter-fuel substitution in the household sector depends on whether their target energy use is similar or not. To account ... for the effect of end-use application on energy demand, the concept of useful energy is...

Zahra A. Barkhordar; Yadollah Saboohi

2014-10-01T23:59:59.000Z

72

Competition Helps Kids Learn About Energy and Save Their Households Some  

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

Competition Helps Kids Learn About Energy and Save Their Households 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 Addthis Students can register now to save energy and win prizes with the Home Energy Challenge. Students can register now to save energy and win prizes with the Home Energy Challenge. Eric Barendsen Energy Technology Program Specialist, Office of Energy Efficiency and Renewable Energy How can I participate? Visit HomeEnergyChallenge.org to register for the competition. Third through eighth grade students and teachers will be excited to hear about a competition starting up for next school year that challenges students to learn about energy, develop techniques for saving energy, and

73

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

74

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

75

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

Gasoline and Diesel Fuel Update (EIA)

... 32.8 17.2 307 13.4 16.1 14.2 2.0 21.3 14.1 Race of Householder White... 149.5 78.3 1,774 77.6...

76

Abstract--Numerous studies have shown that households' consumption is an important part of the total energy consumed  

E-Print Network (OSTI)

appropriate strategies of giving households' effective feedback on their energy consumption. This study, Energy efficiency. I. INTRODUCTION HE energy consumption of households in buildings attracts a lot in the housing sector. Energy consumption in buildings accounts for 39% of Sweden's total final energy

Beigl, Michael

77

Patterns of residential energy demand by type of household: white, black, Hispanic, and low- and nonlow-income  

SciTech Connect

This report compares patterns of residential energy use by white, black, Hispanic, low-income, and nonlow-income households. The observed downward trend in residential energy demand over the period of this study can be attributed primarily to changes in space-heating energy demand. Demand for space-heating energy has experienced a greater decline than energy demand for other end uses for two reasons: (1) it is the largest end use of residential energy, causing public attention to focus on it and on strategies for conserving it; and (2) space-heating expenditures are large relative to other residential energy expenditures. The price elasticity of demand is thus greater, due to the income effect. The relative demand for space-heating energy, when controlled for the effect of climate, declined significantly over the 1978-1982 period for all fuels studied. Income classes do not differ significantly. In contrast, black households were found to use more energy for space heating than white households were found to use, although those observed differences are statistically significant only for houses heated with natural gas. As expected, the average expenditure for space-heating energy increased significantly for dwellings heated by natural gas and fuel oil. No statistically significant increases were found in electricity expenditures for space heating. Electric space heat is, in general, confined to milder regions of the country, where space heating is relatively less essential. As a consequence, we would expect the electricity demand for space heating to be more price-elastic than the demand for other fuels.

Klein, Y.; Anderson, J.; Kaganove, J.; Throgmorton, J.

1984-10-01T23:59:59.000Z

78

Environmental and Resource Economics Household Energy Demand in Urban China: Accounting for regional prices and rapid  

E-Print Network (OSTI)

growth, China's energy consumption is rising at one of the fastest rates in the world, almost 8% per year over the period 2000-2010. Residential energy consumption has grown even faster than the national total . Although household energy consumption per capita is still low compared to the developed countries

79

Reforming Household Energy Markets: Some Welfare Effects in the United Catherine Waddams Price  

E-Print Network (OSTI)

Reforming Household Energy Markets: Some Welfare Effects in the United Kingdom by Catherine Waddams remain vulnerable. The implications of these findings for the future of energy markets both in the UK This paper summarises some early effects of deregulating the UK energy sector, focusing on the effects

Feigon, Brooke

80

Using Circuit-Level Power Measurements in Household Energy Management Systems  

E-Print Network (OSTI)

Using Circuit-Level Power Measurements in Household Energy Management Systems Alan Marchiori and Qi to accurately measure en- ergy usage in the home. Measuring energy usage is not dif- ficult, however we must decide what to measure. Whole- home energy measurement is cheap and easy to setup be- cause only one

Han, Qi "Chee"

Note: This page contains sample records for the topic "average household energy" 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

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

SciTech Connect

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

82

A holographic proof of the averaged null energy condition  

E-Print Network (OSTI)

The averaged null energy conditions (ANEC) states that, along a complete null curve, the negative energy fluctuations of a quantum field must be balanced by positive energy fluctuations. We use the AdS/CFT correspondence to prove the ANEC for a class of strongly coupled conformal field theories in flat spacetime. A violation of the ANEC in the field theory would lead to acausal propagation of signals in the bulk.

William R. Kelly; Aron C. Wall

2014-11-03T23:59:59.000Z

83

High Average Power, High Energy Short Pulse Fiber Laser System  

SciTech Connect

Recently continuous wave fiber laser systems with output powers in excess of 500W with good beam quality have been demonstrated [1]. High energy, ultrafast, chirped pulsed fiber laser systems have achieved record output energies of 1mJ [2]. However, these high-energy systems have not been scaled beyond a few watts of average output power. Fiber laser systems are attractive for many applications because they offer the promise of high efficiency, compact, robust systems that are turn key. Applications such as cutting, drilling and materials processing, front end systems for high energy pulsed lasers (such as petawatts) and laser based sources of high spatial coherence, high flux x-rays all require high energy short pulses and two of the three of these applications also require high average power. The challenge in creating a high energy chirped pulse fiber laser system is to find a way to scale the output energy while avoiding nonlinear effects and maintaining good beam quality in the amplifier fiber. To this end, our 3-year LDRD program sought to demonstrate a high energy, high average power fiber laser system. This work included exploring designs of large mode area optical fiber amplifiers for high energy systems as well as understanding the issues associated chirped pulse amplification in optical fiber amplifier systems.

Messerly, M J

2007-11-13T23:59:59.000Z

84

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

the residential energy efficiency market is a potentialinstitutions (CDFIs) to market energy improvements. Solve aapproach to energy efficiency market development is

Zimring, Mark

2012-01-01T23:59:59.000Z

85

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

the residential energy efficiency market is a potentialinstitutions (CDFIs) to market energy improvements. Solve acan open significant markets for energy improvements among

Zimring, Mark

2014-01-01T23:59:59.000Z

86

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

rentalhousing/Energy_Efficiency_Project/COB_rebates_8.2.11.PDS/rentalhousing/Energy_Efficiency_Project/SmartRegs_Final_s residential energy efficiency loan program November 2010-

Zimring, Mark

2012-01-01T23:59:59.000Z

87

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

Clean Energy Works Oregon Bill Payment History as a ProxyEnergy and Clean Energy Works Oregon (CEWO), also use utility bill repayment history

Zimring, Mark

2012-01-01T23:59:59.000Z

88

Could a Common Household Fungus Reduce Oil Imports? | Department of Energy  

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

Could a Common Household Fungus Reduce Oil Imports? Could a Common Household Fungus Reduce Oil Imports? Could a Common Household Fungus Reduce Oil Imports? June 21, 2011 - 11:37am Addthis A view of Aspergillus niger with the fungus’ DNA highlighted in green | Photo Courtesy of: PNNL. A view of Aspergillus niger with the fungus' DNA highlighted in green | Photo Courtesy of: PNNL. Ben Squires Analyst, Office of Energy Efficiency & Renewable Energy What does this mean for me? The Department's Pacific Northwest National Laboratory (PNNL) are working to harness the natural process that spoils fruits and vegetables as a way to make fuel and other petroleum substitutes from the parts of plants that we can't eat. The genetic bases of the behaviors and abilities of these two industrially relevant fungal strains will allow researchers to exploit

89

Could a Common Household Fungus Reduce Oil Imports? | Department of Energy  

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

a Common Household Fungus Reduce Oil Imports? a Common Household Fungus Reduce Oil Imports? Could a Common Household Fungus Reduce Oil Imports? June 21, 2011 - 11:37am Addthis A view of Aspergillus niger with the fungus’ DNA highlighted in green | Photo Courtesy of: PNNL. A view of Aspergillus niger with the fungus' DNA highlighted in green | Photo Courtesy of: PNNL. Ben Squires Analyst, Office of Energy Efficiency & Renewable Energy What does this mean for me? The Department's Pacific Northwest National Laboratory (PNNL) are working to harness the natural process that spoils fruits and vegetables as a way to make fuel and other petroleum substitutes from the parts of plants that we can't eat. The genetic bases of the behaviors and abilities of these two industrially relevant fungal strains will allow researchers to exploit

90

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

NASCSP). 2009. Weatherization Assistance Program Fundingof Energys Weatherization Assistance Program with State-2009. National Weatherization Assistance Program Training

Zimring, Mark

2012-01-01T23:59:59.000Z

91

Special Topics on Energy Use in Household Transportation  

Annual Energy Outlook 2012 (EIA)

compare your estimate of your car's mpg to the average of everyone else who takes the test. (Released 04112000; Updated Yearly for Fuel Economies and Weekly for Fuel Prices)...

92

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

Vermont Energy Investment Corporation NYSERDA New Yorkfor a case study on New Yorks energy efficiency programNew York, the New York State Energy Research and Development

Zimring, Mark

2012-01-01T23:59:59.000Z

93

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

and Renewable Energy (DOE EERE), Weatherization andand Roya Stanley (DOE EERE) for their support of thisfor Humanity International DOE EERE Department of Energy

Zimring, Mark

2012-01-01T23:59:59.000Z

94

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

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

N April 4, 2012 Extending Efficiency Services to Underserved Households: NYSERDA's Assisted Home Performance with ENERGY STAR Program Since 2001, New York residents have completed over 39,000 energy upgrades through NYSERDA's Home Performance with ENERGY STAR (HPwES) initiative. Approximately one third of these projects have been completed through the Assisted HPwES track, which offers large incentives to middle income

95

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

energy assessments, title searches, and lien recordings. Theassessments, title searches, and lien recordings. Once INHP

Zimring, Mark

2012-01-01T23:59:59.000Z

96

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

Energy Efficiency Programs. March 17, 2011. Available here:Efficiency Programs. March 17, 2011. Available here:

Zimring, Mark

2012-01-01T23:59:59.000Z

97

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

98

The influence of energy audits on the energy efficiency investments of private owner-occupied households in the Netherlands  

Science Journals Connector (OSTI)

Abstract Energy audits are promoted as an effective tool to drive investment in energy efficiency measures in the residential sector. Despite operating in many countries for several decades details of the impact of audits are mixed. The aim of research presented here is to explore the role of audits on investment in energy efficiency measures by private owner-occupied householders in the Netherlands. Results showed that the main influence of the energy audit was to confirm information held by householders. A significant portion of audit recommendations was ignored, the main reason being that householders considered their dwellings to be adequately energy efficient. A comparison of audit recipients to non-recipients showed that audit recipients did not adopt, plan to adopt or invest in more energy efficiency measures than non-recipients. In fact non-recipients adopted more and invested more in measures. It is concluded that energy based renovation is driven by householder perception of comfort and acceptable outlay on energy bills and not necessarily to expert technical tailored information on the potential to reduce CO2 emissions and environmental impact. Results support arguments for minimum energy efficiency standards and performance based incentives.

Lorraine Murphy

2014-01-01T23:59:59.000Z

99

EIA - Appendix B: Estimation Methodologies of Household Vehicles Energy  

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

If you have trouble viewing this page, contact the National Energy Informaiton Center at (202) 586-8800. Return to Energy Information Administration Home Page If you have trouble viewing this page, contact the National Energy Informaiton Center at (202) 586-8800. Return to Energy Information Administration Home Page EIA Home > Transportation Home Page > Appendix B Estimation MethodologiesIntroduction Appendix B Estimation Methodologies Introduction Statistics concerning vehicle miles traveled (VMT), vehicle fuel efficiency (given in terms of miles per gallon (MPG)), vehicle fuel consumption, and vehicle fuel expenditures are presented in this report. The methodology used to estimate these statistics relied on data from the 1993 Residential Energy Consumption Survey (RECS), the 1994 Residential Transportation Energy Consumption Survey (RTECS), the U.S. Environmental Protection Agency (EPA) fuel efficiency test results, the U.S. Bureau of Labor Statistics (BLS) retail pump price series, and the Lundberg Survey, Inc., price series for 1994.

100

Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour  

Science Journals Connector (OSTI)

Abstract Household energy conservation has emerged as a major challenge and opportunity for researchers, practitioners and policymakers. Consumers also seem to be gaining greater awareness of the value and need for sustainable energy practices, particularly amid growing public concerns over greenhouse gas emissions and climate change. Yet even with adequate knowledge of how to save energy and a professed desire to do so, many consumers still fail to take noticeable steps towards energy efficiency and conservation. There is often a sizeable discrepancy between peoples self-reported knowledge, values, attitudes and intentions, and their observable behaviourexamples include the well-known knowledge-action gap and value-action gap. But neither is household energy consumption driven primarily by financial incentives and the rational pursuit of material interests. In fact, people sometimes respond in unexpected and undesirable ways to rewards and sanctions intended to shift consumers costbenefit calculus in favour of sustainable behaviours. Why is this so? Why is household energy consumption and conservation difficult to predict from either core values or material interests? By drawing on critical insights from behavioural economics and psychology, we illuminate the key cognitive biases and motivational factors that may explain why energy-related behaviour so often fails to align with either the personal values or material interests of consumers. Understanding these psychological phenomena can make household and community responses to public policy interventions less surprising, and in parallel, can help us design more cost-effective and mass-scalable behavioural solutions to encourage renewable and sustainable energy use among consumers.

Elisha R. Frederiks; Karen Stenner; Elizabeth V. Hobman

2015-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

102

A comparative multivariate analysis of household energy requirements in Australia, Brazil, Denmark, India and Japan  

Science Journals Connector (OSTI)

In this paper, we appraise sustainable household consumption from a global perspective. Using per capita energy requirements as an indicator of environmental pressure, we focus on the importance of income growth in a cross-country analysis. Our analysis is supported by a detailed within-country analysis encompassing five countries, in which we assess the importance of various socioeconomic-demographic characteristics of household energy requirements. We bring together family expenditure survey data, inputoutput tables, and energy statistics in a multivariate analysis. Instead of a uniform Kuznet's curve, we find that the effect of increasing income varies considerably across countries, even when controlling for socioeconomic and demographic variations. The latter variables show similar influences, but differing importance across countries.

Manfred Lenzen; Mette Wier; Claude Cohen; Hitoshi Hayami; Shonali Pachauri; Roberto Schaeffer

2006-01-01T23:59:59.000Z

103

Household Vehicles Energy Use: Latest Data and Trends  

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.

2005-01-01T23:59:59.000Z

104

Using census aggregates to proxy for household characteristics: an application to vehicle ownership  

E-Print Network (OSTI)

Instead, Asian and Hispanic households were undersampled byhousehold Age of the householder/Average age of residents Hispanichousehold Age of the householder/Average age of residents Hispanic

Adjemian, Michael; Williams, Jeffrey

2009-01-01T23:59:59.000Z

105

HOUSEHOLD SOLAR POWER SYSTEM.  

E-Print Network (OSTI)

?? Photovoltaic power has become one of the most popular research area in new energy field. In this report, the case of household solar power (more)

Jiang, He

2014-01-01T23:59:59.000Z

106

Energy efficiency in Norwegian households - identifying motivators and barriers with a focus group approach  

Science Journals Connector (OSTI)

This paper describes the theoretical background and results of a focus group study on determinants of energy related behaviour in Norwegian households. 70 Norwegians between 18 and 79 years of age participated in eight focus-groups in four Norwegian cities. The aim of the study was to identify behaviours that Norwegians consider relevant with respect to energy use, the main determinants of those behaviours, as well as barriers against and facilitators of energy efficiency. The most important behaviours from the participants' perspectives were heating, water heating, use of white ware and mobility. The main motivators named were minimising behavioural costs, value orientations, perceived consumer efficacy and social norms. The most important barriers were structural misfits, economic, effort, time consumption, low consumer efficacy and lack of relevant and trustworthy information. The most potent facilitators were economic incentives, gains in comfort, reduced effort, tailored practical information, individual feedback and legislative actions.

Christian A. Klöckner; Bertha M. Sopha; Ellen Matthies; Even Bjørnstad

2013-01-01T23:59:59.000Z

107

Understanding household energy consumption patterns: When West Is Best in Metro Manila  

Science Journals Connector (OSTI)

This paper addresses the topic of energy and development through a multi-disciplinary and systemic approach that combines environmental considerations with a social understanding of consumption. The focus is on electricity usage in the home and specifically lighting and cooling. Set in the urban mega-polis of Metro Manila, the Philippines, energy consumption is first placed in its biophysical perspective: the energy sources and electricity grid are presented, in relation to the Philippines as well as the region. The research findings then explore the social and cultural drivers behind household electricity consumption, revealing in several examples the strong influence of globalizationunderstood here as the flow of people, remittances, images and ideas. Policy recommendations are provided, based on the research results, with concluding remarks relevant to other similar contexts.

Marlyne D. Sahakian

2011-01-01T23:59:59.000Z

108

Residential energy consumption across different population groups : comparative analysis for latino and non-latino households in USA.  

SciTech Connect

Residential energy cost is an important part of the household budget and could vary significantly across different population groups in many countries. In the United States, many studies have analyzed household fuel consumption by fuel type, including electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG), and by geographic areas. Past research has also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, our research shows that residential energy demand by fuel type for Latinos, the fastest growing population group, has not been explained by economic and non-economic factors in any statistical model in public domain. The purpose of this paper was to discuss energy demand and expenditure patterns for Latino and non-Latino households in the United States as a case example of analyzing residential energy consumption across different population groups in a country. The linear expenditure system model developed by Stone and Geary is the basis of the statistical model developed to explain fuel consumption and expenditures for Latino households. For comparison, the models are also developed for non-Latino, black, and non-black households. These models estimate energy consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. Significant variations in the patterns of these fuels consumption for Latinos and non-Latinos are highlighted. The model methodology and results of this research should be useful to energy policymakers in government and industry, researches, and academicians who are concerned with economic and energy issues related to various population groups in their country.

Poyer, D. A.; Henderson, L.; Teotia, A. P. S.; Energy Systems; Univ. of Baltimore

1997-01-01T23:59:59.000Z

109

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

E-Print Network (OSTI)

at 215 million Btu. The rate of consumption generally increased until the oil price shocks of the midChanging Trends: A Brief History of the US Household Consumption of Energy, Water, Food, Beverages understand energy conservation policies, we take a brief look at the history in the US of consumption

110

Simulation of household in-home and transportation energy use : an integrated behavioral model for estimating energy consumption at the neighborhood scale  

E-Print Network (OSTI)

Household in-home activities and out-of-home transportation are two major sources of urban energy consumption. In light of China's rapid urbanization and income growth, changing lifestyles and consumer patterns - evident ...

Yu, Feifei, S.M. Massachusetts Institute of Technology

2013-01-01T23:59:59.000Z

111

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

112

Can ambient persuasive technology persuade unconsciously?: using subliminal feedback to influence energy consumption ratings of household appliances  

Science Journals Connector (OSTI)

In this paper we explore a fundamental characteristic of Ambient Persuasive Technology: Can it persuade the user without receiving the user's conscious attention? In a task consisting of 90 trials, participants had to indicate which of three household ... Keywords: ambient persuasive technology, energy conservation behavior, human-technology interaction, persuasion, social feedback, subliminal feedback

Jaap Ham; Cees Midden; Femke Beute

2009-04-01T23:59:59.000Z

113

THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD  

E-Print Network (OSTI)

energy-using devices in the average U.S. household that used over 4,700 kWh of electricity, natural gas.46]. The cost of these devices was also statistically significant. Keywords: electricity use; energy efficiency the Canadian Industrial Energy End Use Data and Analysis (CIEEDAC) for their financial support made possible

114

''Averaged'' statistical thermodynamics, energy equipartition and the third law  

E-Print Network (OSTI)

Arguments are presented that the assumption, implicit to traditional statistical thermodynamics, that at zero temperature all erratic motions cease, should be dispensed with. Assuming instead a random ultrarelativistic unobservable motion, similar to zitterbewegung, it is demonstrated that in an ideal gas of classical particles the energy equipartition fails in a way that complies with the third law of thermodynamics.

Vesselin I. Dimitrov

1997-07-03T23:59:59.000Z

115

ON THE SELF-AVERAGING OF WAVE ENERGY IN RANDOM GUILLAUME BAL  

E-Print Network (OSTI)

ON THE SELF-AVERAGING OF WAVE ENERGY IN RANDOM MEDIA GUILLAUME BAL Abstract. We consider the stabilization (self-averaging) and destabilization of the energy of waves propagating in random media transport equations for arbitrary statistical moments of the wave field is used to show that wave energy

Bal, Guillaume

116

Global Potential of Energy Efficiency Standards and Labeling Programs  

E-Print Network (OSTI)

and Energy Use in Japan: Household Equipment and EnergyHousehold (Electrified), 1999-2000 Average standby power (W/home) Austria Belgium Canada Denmark Finland France Germany Iceland Ireland Italy Japan

McNeil, Michael A

2008-01-01T23:59:59.000Z

117

Best-practice and average practice: technique choice and energy demand in a vintage model  

Science Journals Connector (OSTI)

Comparisons between best-practice use of energy and average practice have become quite popular ... in debates and scenarios about future need for energy, and sometimes fairly strong conclusions are drawn about lo...

Lennart Hjalmarsson; Finn R. Frsund

1992-01-01T23:59:59.000Z

118

Energy Impacts of Effective Range Hood Use for all U.S. Residential Cooking  

E-Print Network (OSTI)

impact on source energy and cost based on state specifichouse average annual energy and cost savings, relative toof household source energy and cost of range hood use in

Logue, Jennifer M

2014-01-01T23:59:59.000Z

119

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.

120

Household environmental monitoring a strategy to help homeowners reduce their environmental impact  

Science Journals Connector (OSTI)

A group of 20 households was established to study whether we can motivate environmentally sustainable behaviour by providing homeowners with a clear picture of their impact, tangible reasons for improvement, and tailored solutions to follow. Reports for each household compared heating fuel, electricity, water, vehicle fuel/waste generation within the group and recommended cost-effective measures to reduce consumption. On average, 26% of the recommended measures were implemented, resulting in an estimated greenhouse gas reduction of about 2 tonnes per household. Wide variations were found between households, demonstrating the potential to reduce environmental impact through lifestyle, conservation, and energy conscious retrofits.

Jane Thompson; Magda Goemans; Peter C. Goemans; Andrzej Wisniowski

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

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

SciTech Connect

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

122

Table 7.5 Average Prices of Selected Purchased Energy Sources, 2002  

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

5 Average Prices of Selected Purchased Energy Sources, 2002;" 5 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate","Natural ","LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

123

Table N8.2. Average Prices of Purchased Energy Sources, 1998  

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

2. Average Prices of Purchased Energy Sources, 1998;" 2. Average Prices of Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Million Btu." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected","Wood and Other","Biomass","Components" ,,,,,,,"Coal Components",,,"Coke",,"Electricity","Components",,,,,,,,,,,,,"Natural Gas","Components",,"Steam","Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues" " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related",," ",," "

124

Table 7.1 Average Prices of Purchased Energy Sources, 2002  

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

Average Prices of Purchased Energy Sources, 2002;" Average Prices of Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Physical Units." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected Wood and Other Biomass Components" ,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues" " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related",," ",," "

125

Table 7.2 Average Prices of Purchased Energy Sources, 2002  

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

2 Average Prices of Purchased Energy Sources, 2002;" 2 Average Prices of Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; " " Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Million Btu." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected Wood and Other Biomass Components" ,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues" " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related",," ",," "

126

Table 7.4 Average Prices of Selected Purchased Energy Sources, 2002  

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

4 Average Prices of Selected Purchased Energy Sources, 2002;" 4 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Physical Units." " ",," "," ",," "," " ,,"Residual","Distillate","Natural ","LPG and",,"RSE" "Economic","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Row" "Characteristic(a)","(kWh)","(gallons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors"

127

"Table E8.1. Average Prices of Selected Purchased Energy Sources, 1998;"  

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

1. Average Prices of Selected Purchased Energy Sources, 1998;" 1. Average Prices of Selected Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Physical Units." " ",," "," ",," "," " ,,"Residual","Distillate",,"LPG and",,"RSE" "Economic","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Row" "Characteristic(a)","(kWh)","(gallons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors"

128

"Table E8.2. Average Prices of Selected Purchased Energy Sources, 1998;"  

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

2. Average Prices of Selected Purchased Energy Sources, 1998;" 2. Average Prices of Selected Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate",,"LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

129

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

130

"Table A25. Average Prices of Selected Purchased Energy Sources by Census"  

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

. Average Prices of Selected Purchased Energy Sources by Census" . Average Prices of Selected Purchased Energy Sources by Census" " Region, Industry Group, and Selected Industries, 1991: Part 1" " (Estimates in Dollars per Physical Unit)" ,,,,," " " "," "," ","Residual","Distillate","Natural Gas(c)"," "," ","RSE" "SIC"," ","Electricity","Fuel Oil","Fuel Oil(b)","(1000","LPG","Coal","Row" "Code(a)","Industry Groups and Industry","(kWh)","(gallon)","(gallon)","cu ft)","(gallon)","(short ton)","Factors"

131

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

132

Interaction between building design, management, household and individual factors in relation to energy use for space heating in apartment buildings  

Science Journals Connector (OSTI)

Abstract In Stockholm, 472 multi-family buildings with 7554 dwellings has been selected by stratified random sampling. Information about building characteristics and property management was gathered from each property owners. Energy use for space heating was collected from the utility company. Perceived thermal comfort, household and personal factors were assessed by a standardized self-administered questionnaire, answered by one adult person in each dwelling, and a proportion of each factor was calculated for each building. Statistical analysis was performed by multiple linear regression models with control for relevant factors all at the same time in the model. Energy use for heating was significantly related to the building age, type of building and ventilation, length of time since the last heating adjustment, ownership form, proportion of females, and proportion of occupants expressing thermal discomfort. How beneficial energy efficiency measures will be may depend on the relationship between energy use and factors related to the building and the property maintenance together with household and personal factors, as all these factors interact with each other. The results show that greater focus should be on real estate management and maintenance and also a need for research with a gender perspective on energy use for space heating.

Karin Engvall; Erik Lampa; Per Levin; Per Wickman; Egil fverholm

2014-01-01T23:59:59.000Z

133

Free Energy Self-Averaging in Protein-Sized Random Heteropolymers  

E-Print Network (OSTI)

Current theories of heteropolymers are inherently macrpscopic, but are applied to folding proteins which are only mesoscopic. In these theories, one computes the averaged free energy over sequences, always assuming that it is self-averaging -- a property well-established only if a system with quenched disorder is macroscopic. By enumerating the states and energies of compact 18, 27, and 36mers on a simplified lattice model with an ensemble of random sequences, we test the validity of the self-averaging approximation. We find that fluctuations in the free energy between sequences are weak, and that self-averaging is a valid approximation at the length scale of real proteins. These results validate certain sequence design methods which can exponentially speed up computational design and greatly simplify experimental realizations.

Jeffrey Chuang; Alexander Yu. Grosberg; Mehran Kardar

2001-02-05T23:59:59.000Z

134

UNCOVERING BASIC WANTS USING THE ROTTERDAM AND AIDS MODELS: THE US HOUSEHOLD ENERGY CONSUMPTION CASE  

E-Print Network (OSTI)

refers to these latent goods as transformed goods or T-goods. Leading researchers have explored this technique of incorporating characteristics. In this study, we revisit this technique by trying to uncover the basic wants behind the demand for gas..., distillate fuel oil, and the liquefied petroleum gases (LPG) by US households. To give some examples, electricity may be used for many basic wants such as lighting, cooking, and cooling. Similarly, without being exhaustive, gas may be used for heating...

Diallo, Ibrahima

2013-05-31T23:59:59.000Z

135

"Table A25 Average Prices of Selected Purchased Energy Sources by Census"  

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

Average Prices of Selected Purchased Energy Sources by Census" Average Prices of Selected Purchased Energy Sources by Census" " Region, Industry Group, and Selected Industries, 1991: Part 2" " (Estimates in Dollars per Million Btu)" ,,,,,,,,"RSE" "SIC"," "," ","Residual","Distillate"," "," "," ","Row" "Code(a)","Industry Groups and Industry","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","LPG","Coal","Factors" ,,"Total United States" ,"RSE Column Factors:",0.7,0.8,1,2.8,1,0.7 20,"Food and Kindred Products",15.789,2.854,6.064,2.697,7.596,1.433,4.5

136

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

0 2005 Average Energy Expenditures per Household Member and per Square Foot, by Weatherization Eligibility (2010) Members Hhold Hhold Total U.S. Households 780 2.6 0.86 Federally...

137

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

E-Print Network (OSTI)

or unusually high heating oil prices in Massachusetts versusgas, and home heating oil prices averaged over the previousgas than in heating oil prices. There is a strong seasonal

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

2005-01-01T23:59:59.000Z

138

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

139

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

140

NYSERDA's Green Jobs-Green New York Program: Extending Energy Efficiency Financing To Underserved Households  

E-Print Network (OSTI)

Financing Home Energy Upgrades in New York Since 2001, New2009. Administered by the New York State Energy Research andA Diverse Energy Upgrade Platform in New York The new GJGNY

Zimring, Mark

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

Energy use of US residential refrigerators and freezers: function derivation based on household and climate characteristics  

E-Print Network (OSTI)

Residential Energy Consumption Survey (RECS), U.S. Energyod for estimating field energy consumption of US residentialconsumption surveydetailed tables. Residential Energy Con- sumption Survey (RECS), U.S.

Greenblatt, Jeffery

2013-01-01T23:59:59.000Z

142

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

E-Print Network (OSTI)

of Cold Weather and High Energy Costs on the Health of Low-and NBER April 2005 Home energy costs comprise a significant1. Introduction Home energy costs comprise a significant

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

2005-01-01T23:59:59.000Z

143

Table 7.2 Average Prices of Purchased Energy Sources, 2010;  

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

Table 7.2 Average Prices of Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Million Btu. Selected Wood and Other Biomass Components Coal Components Coke Electricity Components Natural Gas Components Steam Components Total Wood Residues Bituminous Electricity Diesel Fuel Motor Natural Gas Steam and Wood-Related and Electricity from Sources and Gasoline Pulping Liquor Natural Gas from Sources Steam from Sources Waste Gases Waste Oils Industrial Wood Byproducts and NAICS Coal Subbituminous Coal Petroleum Electricity from Local Other than Distillate Diesel Distillate Residual Blast Coke Oven (excluding or LPG and Natural Gas from Local

144

High-energy average charged multiplicities from nuclei in a Regge-calculus model  

Science Journals Connector (OSTI)

Lehman and Winbow have used a Gribov Reggeon-calculus approach to derive expressions for average charge multiplicities in high-energy scattering off nuclei. They find the multiplicity to be n=bY+f(A), where b is independent of A. We show that a reasonable modification of their model yields n=b?A13Y+g(A), where b? is known. We find that this expression agrees with experimental data on dndY (where Y=lns) better than that of Lehman and Winbow, and agrees as well as the energy flux model of Gottfried.

R. T. Cutler and Dale R. Snider

1976-03-01T23:59:59.000Z

145

Use of energy-averaged cross sections for nuclear spectroscopy: Mg26 states in the continuum  

Science Journals Connector (OSTI)

Energy averaged cross sections for the C12(O18,?)Mg26 reaction were studied. Over 80 states between Ex(Mg26)=5and20 MeV were observed for many bombarding energies in the range E(O18)=46-50 MeV. Broad, noncorrelated structures observed in the excitation functions prevent the application of Hauser-Feshbach analysis for spin spectroscopy to this particular data set. By implication, our results cast doubt on the previously suggested backbend in the Mg26 yrast sequence.

M. M. Coimbra; N. Carlin Filho; A. Szanto de Toledo; P. M. Stwertka; M- G. Herman; N. G. Nicolis; T. M. Cormier

1984-12-01T23:59:59.000Z

146

Drivers of U.S. Household Energy Consumption, 1980-2009  

Reports and Publications (EIA)

In 2012, the residential sector accounted for 21% of total primary energy consumption and about 20% of carbon dioxide emissions in the United States (computed from EIA 2013). Because of the impacts of residential sector energy use on the environment and the economy, this study was undertaken to help provide a better understanding of the factors affecting energy consumption in this sector. The analysis is based on the U.S. Energy Information Administration's (EIA) residential energy consumption surveys (RECS) 1980-2009.

2015-01-01T23:59:59.000Z

147

Hybrid application of biogas and solar resources to fulfill household energy needs: A potentially viable option in rural areas of developing countries  

Science Journals Connector (OSTI)

Abstract The absence of clean cooking facilities and electricity means billions of rural people are deprived of much needed socioeconomic development. Livestock residues (dung) and solar radiation are two renewable energy resources that are abundantly available in rural areas of developing countries. Although it is not feasible for these two resources separately to meet both thermal (cooking) and electricity demands, hybrid applications have not been given due attention. To facilitate integrating these two resources in rural energy planning, and to promote their dissemination through hybrid applications, it is necessary to evaluate their economic merits, and assess their ability to deal with the demands. In this paper, we examine the techno-economic performance of hybrid applications of these two resources by applying a simulation technique using the HOMER tool, and by giving derived cost-saving equations. We also quantify the monetary savings from replacing traditional fuels, and perform a sensitivity analysis on a number of variables (e.g. dung cost, fuelwood cost) to see how they affect the performance of different energy supply alternatives. Furthermore, we examine the practical applicability of the biogas system in the households through a structured survey of 72 ongoing household biogas plants. This study finds that households that have between three and six cattle can potentially meet their cooking and electricity loads through a hybrid implementation of biogas and solar PV (Photovoltaic) system. By replacing conventional fuels households can achieve savings that are more than the total annualized costs incurred for installing new services.

Md. Mizanur Rahman; Mohammad Mahmodul Hasan; Jukka V. Paatero; Risto Lahdelma

2014-01-01T23:59:59.000Z

148

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

149

Retrofitting the domestic built environment: investigating household perspectives towards energy efficiency technologies and behaviour  

E-Print Network (OSTI)

Company Obligation EEPfH Energy Efficiency Partnership for Homes EPC Energy Performance Certificate EPSRC Engineering & Physical Science Research Council ERDF European Regional Development Fund FDR False discovery rate FIT Feed-in Tariff GHG Greenhouse has...

Pelenur, Marcos

2014-03-04T23:59:59.000Z

150

E-Print Network 3.0 - acute household accidental Sample Search...  

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

Evaluating the health benefits of transitions in household energy Summary: ; Household energy; Indoor air pollution; Intervention assessment; Kenya 1. Introduction Acute...

151

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

EnergyEfficiencyPotentialStudy. TechnicalReportEnergyEfficiency PotentialStudy. TechnicalReportEnergyEfficiency RenewableEnergyTechnologies Transportation AssessmentofHouseholdCarbonFootprintReductionPotentialsisthefinalreport

Masanet, Eric

2010-01-01T23:59:59.000Z

152

Table 7.4 Average Prices of Selected Purchased Energy Sources, 2010;  

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

4 Average Prices of Selected Purchased Energy Sources, 2010; 4 Average Prices of Selected Purchased Energy Sources, 2010; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: U.S. Dollars per Physical Units. Residual Distillate LPG and Economic Electricity Fuel Oil Fuel Oil(b) Natural Gas(c) NGL(d) Coal Characteristic(a) (kWh) (gallons) (gallons) (1000 cu ft) (gallons) (short tons) Total United States Value of Shipments and Receipts (million dollars) Under 20 0.093 1.55 2.58 6.64 1.80 78.29 20-49 0.075 1.66 2.45 6.44 1.80 80.13 50-99 0.070 1.64 1.79 6.04 2.19 68.10 100-249 0.061 1.62 2.38 5.51 1.69 100.69 250-499 0.056 1.69 2.41 5.54 1.59 92.51 500 and Over 0.054 1.54 2.35 5.08 1.15 96.25 Total

153

Table 7.1 Average Prices of Purchased Energy Sources, 2010  

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

Average Prices of Purchased Energy Sources, 2010; Average Prices of Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Physical Units. Coal NAICS TOTAL Acetylene Breeze Total Anthracite Code(a) Subsector and Industry (million Btu) (cu ft) (short tons) (short tons) (short tons) Total United States 311 Food 9.12 0.26 0.00 53.43 90.85 3112 Grain and Oilseed Milling 6.30 0.29 0.00 51.34 50.47 311221 Wet Corn Milling 4.87 0.48 0.00 47.74 50.47 31131 Sugar Manufacturing 5.02 0.31 0.00 53.34 236.66 3114 Fruit and Vegetable Preserving and Specialty Foods 9.78 0.27 0.00 90.59 0.00 3115 Dairy Products 11.21 0.10 0.00 103.12 0.00 3116 Animal Slaughtering and Processing

154

Retrofitting the domestic built environment: investigating household perspectives towards energy efficiency technologies and behaviour.  

E-Print Network (OSTI)

??Retrofitting the UK domestic built environment presents an excellent opportunity to improve its energy performance. However, retrofitting homes is a complex challenge conflated by multiple (more)

Pelenur, Marcos

2014-01-01T23:59:59.000Z

155

Automated Demand Response Approaches to Household Energy Management in a Smart Grid Environment.  

E-Print Network (OSTI)

??The advancement of renewable energy technologies and the deregulation of theelectricity market have seen the emergence of Demand response (DR) programs. Demand response is a (more)

Adika, Christopher Otieno

2014-01-01T23:59:59.000Z

156

Household actions can provide a behavioral wedge to rapidly reduce US carbon emissions  

Science Journals Connector (OSTI)

...ineffective in reducing household energy consumption. Mass media...10 years. The changes in household behavior outlined above result...European Union countries and Japan, where the household sector is less energy intensive. Analyses similar...

Thomas Dietz; Gerald T. Gardner; Jonathan Gilligan; Paul C. Stern; Michael P. Vandenbergh

2009-01-01T23:59:59.000Z

157

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

E-Print Network (OSTI)

? scale?. This covers any energy generation that is decentralized. Micro-generation technologies may take the form of solar photovoltaic (PV), micro-wind turbines, micro-hydro or even micro-combined heat and power (CHP). Micro-generation provides energy...

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

2012-01-01T23:59:59.000Z

158

Retailers : a possible stepping stone for promoting energy efficiency in household appliances  

Science Journals Connector (OSTI)

The public support of energy efficiency generally targets manufacturers (support to R&D policies) and consumers (information campaign). This practice leaves out the retailers, who often have an essential role ...

Michel Colombier; Sophie Attali

1999-01-01T23:59:59.000Z

159

A cross-cultural analysis of household energy use behaviour in Japan and Norway  

Science Journals Connector (OSTI)

In this paper we compare and contrast the results of ethnographic investigations of energy use behaviour in Fukuoka, Japan and Oslo, Norway. These studies show significant differences in end use patterns for space heating, lighting and hot water use. We discuss how these patterns are related to cultural and economic factors. Our findings show that while energy intensive space heating and lighting habits have become an integral part of the presentation of the Norwegian home, Japanese space heat and light habits are more disciplined and less culturally significant. In Japan, the bathing routine is extremely important to the Japanese lifestyle and at the same time very energy intensive. Other energy intensive patterns are identified which do not have the same cultural significance, such as lax temperature setback in Norway and dish washing practices in Japan. The policy implications of these findings are discussed.

Harold Wilhite; Hidetoshi Nakagami; Takashi Masuda; Yukiko Yamaga; Hiroshi Haneda

1996-01-01T23:59:59.000Z

160

Control of household refrigerators. Part 2: Alternate control approaches for improving temperature performance and reducing energy use  

SciTech Connect

In Part 1 it was shown that conventional control of household refrigerators is achieved by regulating the distribution of air in the freezer compartment to all other parts of the plant. In Part 2 three alternative approaches to the conventional control of a top-mount refrigerator are presented: variable temperature bandwidths, uncoupled compressor and evaporator fan, and the combination of these two. These allowed the plant to achieve near-ideal control with respect to improved temperature performance in each compartment. Automatic airflow dampers were used with the dual controllers to independently regulate refrigerator compartment temperature. Plant performance was simulated using a model that computes the refrigerant and airflow systems behavior. Together, these alternate configurations and approaches define new control algorithms that reveal the plant's optimal control model for improving performance and energy usage relative to conventional controllers. Results based on model simulations are dependent upon the model's accuracy and validity. However, the model validation studies cited here, though limited in scope, do show agreement between simulation and experimental data for the ambient temperatures and thermal load conditions considered. This suggests that these model results are reasonable, and representative of actual plant behavior under these conditions and configurations for a top-mount style refrigerator plant.

Graviss, K.J.; Collins, R.L.

1999-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

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

162

Fact #747: October 1, 2012 Behind Housing, Transportation is the Top Household Expenditure  

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

Except for housing, transportation was the largest single expenditure for the average American household in 2010. The average household spends more on transportation in a year than on food. Vehicle...

163

The Travel Behavior of Immigrants and Race/Ethnicity Groups: An Analysis of the 2001 National Household Transportation Survey  

E-Print Network (OSTI)

the average household size for Hispanic respondents isper year, while households of black and Hispanic respondentsHispanic versus settled and native born residents. Vehicle ownership is highly correlated with mode choice as households

Handy, Susan L; Tal, Gil

2005-01-01T23:59:59.000Z

164

Proving the achronal averaged null energy condition from the generalized second law  

SciTech Connect

A null line is a complete achronal null geodesic. It is proven that for any quantum fields minimally coupled to semiclassical Einstein gravity, the averaged null energy condition (ANEC) on null lines is a consequence of the generalized second law of thermodynamics for causal horizons. This result is shown to leading order in Planck's constant for perturbations to classical backgrounds satisfying the null energy condition. Auxiliary assumptions include CPT and the existence of a suitable renormalization scheme for the generalized entropy. Although the ANEC can be violated on general geodesics in curved spacetimes, as long as the ANEC holds on null lines there exist theorems showing that semiclassical gravity should satisfy positivity of energy, topological censorship, and should not admit closed timelike curves. It is pointed out that these theorems fail once the linearized graviton field is quantized, because then the renormalized shear-squared term in the Raychaudhuri equation can be negative. A 'shear-inclusive' generalization of the ANEC is proposed to remedy this, and is proven under an additional assumption about perturbations to horizons in classical general relativity.

Wall, Aron C. [Maryland Center for Fundamental Physics, Department of Physics, University of Maryland, College Park, Maryland 20740-4111 (United States)

2010-01-15T23:59:59.000Z

165

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

166

Solar Energy With an average of over 300 sunny days a year, Israel is an ideal labo-  

E-Print Network (OSTI)

35 Solar Energy With an average of over 300 sunny days a year, Israel is an ideal labo- ratory for testing one particularly promising alternative to fossil fuels: solar energy. In contrast to fossil fuels as much energy strikes the earth in the form of solar radiation as is used in a whole year throughout

Maoz, Shahar

167

Linear Relationship Between Weighted-Average Madelung and Density Functional Theory Energies for MgO Nanotubes  

E-Print Network (OSTI)

Energies for MgO Nanotubes Journal: The Journal of Physical Chemistry Manuscript ID: jp-2012-08041d.R1 Constants and Density Functional Theory Energies for MgO Nanotubes Mark D. Baker,*1 A. David Baker2 , Jane-average Madelung constants of MgO nanotubes correlate in an essentially perfectly linear way with cohesive energies

Hanusa, Christopher

168

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

169

EIA - Household Transportation report: Household Vehicles Energy...  

Gasoline and Diesel Fuel Update (EIA)

all comparisons reported in the text are statistically significant, based on a standard test made at the 0.05 significance level. These tests were made using the actual RSE's...

170

E-Print Network 3.0 - average high energy Sample Search Results  

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

are being Summary: and high expectation. Will these developments and other renewable energy conversions one day replace fossil... the energy density of good quality coals is...

171

E-Print Network 3.0 - average beta energy Sample Search Results  

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

Project Summary: part High-energy part Existing (P. Delahaye) 12;Beta Beams in Beam Intensity and Magnet Cycle... dependent energy change (C. Omet) 12;Beta Beams in...

172

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

173

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

174

Households and Pension  

Science Journals Connector (OSTI)

This chapter deals with two economic issues. First, we examine Japans household structure. In the previous chapter ( Chapter 10 ...), we recognized the importance of the ...

Mitsuhiko Iyoda

2010-01-01T23:59:59.000Z

175

Standby electricity consumption and saving potentials of Turkish households  

Science Journals Connector (OSTI)

Abstract The share of the residential sector currently accounts for about 25% of the national electricity consumption in Turkey. Due to increase in household income levels and decrease in the costs of appliances; significant increases in appliance ownerships and residential electricity consumption levels have been observed in recent years. Most domestic appliances continue consuming electricity when they are not performing their primary functions, i.e. at standby mode, which can constitute up 15% of the total household electricity consumption in some countries. Although the demand in Turkish residential electricity consumption is increasing, there are limited studies on the components of the residential electricity consumption and no studies specifically examining the extent and effects of standby electricity consumption using a surveying/measurement methodology. Thus, determining the share of standby electricity consumption in total home electricity use and the ways of reducing it are important issues in residential energy conservation strategies. In this study, surveys and standby power measurements are conducted at 260 households in Ankara, Turkey, to determine the amount, share, and saving potentials of the standby electricity consumption of Turkish homes. The survey is designed to gather information on the appliance properties, lights, electricity consumption behavior, economic and demographics of the occupants, and electricity bills. A total of 1746 appliances with standby power are measured in the surveyed homes. Using the survey and standby power measurements data, the standby, active, and lighting end-use electricity consumptions of the surveyed homes are determined. The average Turkish household standby power and standby electricity consumption are estimated as 22W and 95kWh/yr, respectively. It was also found that the standby electricity consumption constitutes 4% of the total electricity consumption in Turkish homes. Two scenarios are then applied to the surveyed homes to determine the potentials in reducing standby electricity consumption of the households.

Mustafa Cagri Sahin; Merih Aydinalp Koksal

2014-01-01T23:59:59.000Z

176

Energy Information Administration/Short-Term Energy Outlook - February 2005  

Gasoline and Diesel Fuel Update (EIA)

February 2005 February 2005 1 Short-Term Energy Outlook February 2005 Winter Fuels Update (Figure 1) Despite some cold weather during the second half of January, expected average consumer prices for heating fuels this heating season are little changed since the January Outlook, leaving projections for household heating fuel expenditures about the same as previously reported. Heating oil expenditures by typical Northeastern households are expected to average 32 percent above last winter's levels, with residential fuel oil prices averaging $1.82 per gallon for the October-to-March period. Expenditures for propane-heated households are expected to increase about

177

E-Print Network 3.0 - averaged null energy Sample Search Results  

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

, high density integrated circuits with low energy consumption and low electromagnetic interference (EMI... . In this paper, we propose the use of the NULL Convention Logic...

178

"Table A42. Average Prices of Purchased Energy Sources by Census Region,"  

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

1" 1" " (Estimates in Dollars per Physical Units)" ,,,,,"Noncombustible Energy Sources",,,,,,,,,,,,,,,,,,"Combustible Energy Sources" ,,,,,,,,,,,,,,,"Solids",,,,,,,,,,"Gases",,,,,,,,,"Liquids" " "," ",," "," ",,,,," "," "," "," "," "," "," ",,,"Wood","Wood Residues",,,,,,,,,,,,,,,,,,,," " " "," ",,"Electricity","Electricity","Electricity","Steam","Steam","Steam","Industrial",," ","Bituminous and"," ",," ",,,"Harvested","and Byproducts","Wood and",,"Natural Gas",,,,,,,"Total Diesel Fuel",,,,,"Motor Gasoline",,,,," "

179

Using Utility Bills and Average Daily Energy Consumption to Target Commissioning Efforts and Track Building Performance  

E-Print Network (OSTI)

energy. This sort of analysis can be done using relatively simple techniques such as a hand calculation or a spreadsheet and is the type of thing that any facility engineer or operator could handle and would be interested in. Techniques are also discussed...

Sellers, D.

2001-01-01T23:59:59.000Z

180

Fact #615: March 22, 2010 Average Vehicle Trip Length  

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

According to the latest National Household Travel Survey, the average trip length grew to over 10 miles in 2009, just slightly over the 9.9 mile average in 2001. Trips to work in 2009 increased to...

Note: This page contains sample records for the topic "average household energy" 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

Towards sustainable consumption: do green households have smaller ecological footprints?  

Science Journals Connector (OSTI)

The need for households in rich countries to develop more sustainable consumption patterns is high on the political agenda. An increased awareness of environmental issues among the general public is often presented as an important prerequisite for this change. This article describes how the study team compared the ecological footprints of ''green'' and ''ordinary'' households. These footprint calculations are based on a number of consumption categories that have severe environmental consequences, such as energy and material use in the home, and transport. The comparison is based on a survey of 404 households in the city of Stavanger, where 66 respondents were members of the Environmental Home Guard in Norway. The analysis suggests that, even if the green households have a smaller ecological footprint per household member, this is not caused by their participation in the Home Guard. It merely reflects the fact that green households are larger than ordinary households.

Erling Holden

2004-01-01T23:59:59.000Z

182

The Household Pie  

Science Journals Connector (OSTI)

The discussion of theoretical, conceptual, and methodological concerns in the last three chapters has set the stage for an examination of the total effort that households devote to domestic and market activiti...

Sarah Fenstermaker Berk

1985-01-01T23:59:59.000Z

183

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

4 4 2005 Average Household Expenditures as Percent of Annual Income, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Average Annual Expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other categories are calculated from the Consumer Expenditure Survey (CE). RECS assumed total US households to be 111,090,617 in 2005, while the CE data is based on 117,356,000 "consumer units," which the Bureau of Labor Statistics defines to be financially independent persons or groups of people that use their incomes to make joint expenditure decisions, including all members of a

184

Variability of Consumer Impacts from Energy Efficiency Standards  

Science Journals Connector (OSTI)

A typical prospective analysis of the expected impact of energy efficiency standards on consumers is based on average ... been developed to characterize the variability among individual households and to calculat...

James E. McMahon; Xiaomin Liu

2001-01-01T23:59:59.000Z

185

Energy Information Administration/Short-Term Energy Outlook - January 2005  

Gasoline and Diesel Fuel Update (EIA)

January 2005 January 2005 1 Short-Term Energy Outlook January 2005 Winter Fuels Update (Figure 1) Consumer prices for heating fuels are relatively unchanged since the December Outlook, leaving projections for household heating fuel expenditures about the same as previously projected, despite continued warm weather in the middle of the heating season. Heating oil expenditures by typical Northeastern households are expected to average 30 percent above last winter's levels, with residential fuel oil prices averaging $1.82 per gallon for the October-to-March period. Expenditures for propane-heated households are expected to increase about 20 percent this winter.

186

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

187

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

188

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

189

Household portfolios in Japan  

Science Journals Connector (OSTI)

I provide a detailed description and in-depth analysis of household portfolios in Japan. (1) It is shown that the share of equities in financial wealth and the stock market participation of Japanese households decreased throughout the 1990s. (2) Using survey data, age-related variations in the share of stocks in financial wealth are analyzed. The equity share and stock market participation increase with age among young households, peaking when people reach their 50s, and then stabilizing. However, the share of equities conditional on ownership exhibits no significant age-related pattern, implying that age-related patterns are primarily explained by the decision to hold stocks. A similar mechanism operates to that found in previous studies of Western countries. (3) Owner-occupied housing has a significantly positive effect on stock market participation and on the share of stocks in financial wealth.

Tokuo Iwaisako

2009-01-01T23:59:59.000Z

190

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

191

"Keeping Up" or "Keeping Afloat"? : how American households accumulate wealth  

E-Print Network (OSTI)

having a Black or Hispanic household head, and experiencingBlack households, Hispanic households, poor households, etc.that Black- and Hispanic- headed households appear to be at

Lundy, Jeffrey Dalton

2012-01-01T23:59:59.000Z

192

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

1 1 2005 Energy Expenditures per Household, by Housing Type and Square Footage ($2010) Per Household Single-Family 1.16 Detached 1.16 Attached 1.20 Multi-Family 1.66 2 to 4 units 1.90 5 or more units 1.53 Mobile Home 1.76 All Homes 1.12 Note(s): Source(s): 1) Energy expenditures per square foot were 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, Table US-1 part1; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for

193

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

3 3 2005 Average Household Expenditures, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Other expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other categories are calculated from the Consumer Expenditure Survey (CE). RECS assumed total US households to be 111,090,617 in 2005, while the CE data is based on 117,356,000 "consumer units," which the Bureau of Labor Statistics defines to be financially independent persons or groups of people that use their incomes to make joint expenditure decisions, including all members of a

194

The Hawthorne effect and energy awareness  

Science Journals Connector (OSTI)

...rented* Average household size* Average...Indian, Asian, Hispanic, Pacific Islander, other)* Total households (block, tract...American, Asian, Hispanic/Latino, White...answer) *Only households in the treatment...

Daniel Schwartz; Baruch Fischhoff; Tamar Krishnamurti; Fallaw Sowell

2013-01-01T23:59:59.000Z

195

The Smart Thermostat: Using Occupancy Sensors to Save Energy in Homes  

E-Print Network (OSTI)

.8% energy on average, and actually increases energy consumption in 4 of the 8 households. Categories higher energy consumption on average than those with manual con- trols because users program themThe Smart Thermostat: Using Occupancy Sensors to Save Energy in Homes Jiakang Lu, Tamim Sookoor

Whitehouse, Kamin

196

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

E-Print Network (OSTI)

be damaged when corrosive chemicals are put down the drain. Burning hazardous wastes simply distributes themHousehold 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

de Lijser, Peter

197

Non-CFC vacuum alternatives for the energy-efficient insulation of household refrigerators: Design and use  

SciTech Connect

Energy efficiency, environmental issues, and market incentives all encourage government and industry to continue work on thin-profile vacuum insulations for domestic refrigerators and freezers (R/Fs). Vacuum insulations promise significant improvement in thermal savings over current insulations; the technical objective of one design is an R-value of better than 10 (hr-ft{sup 2}-F/Btu) in 0.1 in. thickness. If performance is improved by a factor of 10 over that of CFC-blown insulating foams, the new insulations (made without CFCs or other potentially troublesome fill gases) will change the design and improve the efficiency of refrigerators. Such changes will meet the conservation, regulatory, and market drivers now strong in developed countries and likely to increase in developing countries. Prototypes of various designs have been tested in the laboratory and in factories, and results to date confirm the good thermal performance of these thin-profile alternatives. The next step is to resolve issues of reliability and cost effectiveness. 34 refs., 4 figs.

Potter, T.F.; Benson, D.K.

1991-01-01T23:59:59.000Z

198

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

2 2 Energy Burden Definitions Energy burden is an important statistic for policy makers who are considering the need for energy assistance. Energy burden can be defined broadly as the burden placed on household incomes by the cost of energy, or more simply, the ratio of energy expenditures to household income. However, there are different ways to compute energy burden, and different interpretations and uses of the energy burden statistics. DOE Weatherization primarily uses mean individual burden and mean group burden since these statistics provide data on how an "average" individual household fares against an "average" group of households (that is, how burdens are distributed for the population). DOE Weatherization (and HHS) also uses the median individual burden which shows

199

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

200

Energy data  

Open Energy Info (EERE)

Data.gov Data.gov and Powered by OpenEI.org Data.gov Mashathon 2010: an Energy Mashup A regional mashup of 7 cities with energy information from Data.gov and OpenEI.org Click on a city to view data Census Utility Information Smart Grid Information Incentives Average kWh rate Average household electricity usage Average electricity cost per household Mashup information This mashup was created at the first Data.gov mashathon event, August 24-25, 2010. It was further refined from October 6-8, 2010 by the National Renewable Energy Laboratory. This mashup profiles 7 cities in different parts of the United States that have a population of roughly 600,000 according to the 2000 census data and 2006 census-estimated population. Thanks to: Teammates at the Data.gov Mashathon, including Susan Turnbull, Chris

Note: This page contains sample records for the topic "average household energy" 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) - 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.

202

Income inequality and carbon dioxide emissions: The case of Chinese urban households  

Science Journals Connector (OSTI)

This paper draws on Chinese survey data to investigate variations in carbon dioxide emissions across households with different income levels. Rich households generate more emissions per capita than poor households via both their direct energy consumption and their higher expenditure on goods and services that use energy as an intermediate input. An econometric analysis confirms a positive relationship between emissions and income and establishes a slightly increasing marginal propensity to emit (MPE) over the relevant income range. The redistribution of income from rich to poor households is therefore shown to reduce aggregate household emissions, suggesting that the twin pursuits of reducing inequality and emissions can be achieved in tandem.

Jane Golley; Xin Meng

2012-01-01T23:59:59.000Z

203

Household Vehicles Energy Consumption 1991  

Gasoline and Diesel Fuel Update (EIA)

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...

204

Household Vehicles Energy Consumption 1991  

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

Protection Agency (EPA) certification files (CERT files) containing laboratory test results of MPG. When the vehicle characteristic was missing from the questionnaire, but...

205

Household Vehicles Energy Consumption 1994  

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

Christy Hall 202-586-1068 chall@eia.doe.gov Public Use Data, Computer Nanno Smith 202-586-5841 nsmith@eia.doe.gov Systems Design Detailed Statistical Tables Vicky...

206

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

2 2 2005 Household Energy Expenditures, by Vintage ($2010) | Year | Prior to 1950 887 | 22% 1950 to 1969 771 | 22% 1970 to 1979 736 | 16% 1980 to 1989 741 | 16% 1990 to 1999 752 | 16% 2000 to 2005 777 | 9% | Average 780 | Total 100% Note(s): Source(s): 1.24 2,003 1) Energy expenditures per square foot were 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 for 2005 expenditures; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price inflators.

207

The impact of retirement on household consumption in Japan  

Science Journals Connector (OSTI)

Using monthly data from the Japanese Family Income and Expenditure Survey, we examine the impact of retirement on household consumption. We find little evidence of an immediate change in consumption at retirement, on average, in Japan. However, we find a decrease in consumption at retirement for low income households that is concentrated in food and work-related consumption. The availability of substantial retirement bonuses to a large share of Japanese retirees may help smooth consumption at retirement. We find that those households that are more likely to receive such bonuses experience a short-run consumption increase at retirement. However, among households that are less likely to receive a retirement bonus, we find that consumption decreases at retirement.

Melvin Stephens Jr.; Takashi Unayama

2012-01-01T23:59:59.000Z

208

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

209

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

210

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

211

Asset Pricing with Countercyclical Household Consumption Risk  

E-Print Network (OSTI)

1 Asset Pricing with Countercyclical Household Consumption Risk George M. Constantinides that shocks to household consumption growth are negatively skewed, persistent, and countercyclical and play that drives the conditional cross-sectional moments of household consumption growth. The estimated model

Sadeh, Norman M.

212

average | OpenEI  

Open Energy Info (EERE)

average average Dataset Summary Description This dataset is part of a larger internal dataset at the National Renewable Energy Laboratory (NREL) that explores various characteristics of large solar electric (both PV and CSP) facilities around the United States. This dataset focuses on the land use characteristics for solar facilities that are either under construction or currently in operation. Source Land-Use Requirements for Solar Power Plants in the United States Date Released June 25th, 2013 (7 months ago) Date Updated Unknown Keywords acres area average concentrating solar power csp Density electric hectares km2 land land requirements land use land-use mean photovoltaic photovoltaics PV solar statistics Data application/vnd.openxmlformats-officedocument.spreadsheetml.sheet icon Master Solar Land Use Spreadsheet (xlsx, 1.5 MiB)

213

More efficient household electricity use  

SciTech Connect

The energy efficiency of electric appliances has increased markedly in OECD countries, according to data provided by utilities, appliance associations, appliance manufacturers, and independent analyses of each country we reviewed (US, Sweden, Norway, Holland, Japan, Germany, UK). These improvements have, in part, offset increases in electricity demand due to increasing saturation of appliances. However, we see evidence that the efficiency of new devices has hit a temporary plateau: Appliances sold in 1988, while far more efficient than similar ones sold in the early 1970s, may not be significantly more efficient than those sold in 1987. The reason for this plateau, according to manufacturers we interviewed, is that the simple energy-saving features have been incorporated; more sophisticated efficiency improvements are economically justified by five to ten year paybacks, but unattractive to consumers in most countries who appear to demand paybacks of less than three years. Manufacturers see features other than efficiency --- such as number of storage compartments and automatic ice-makers --- as more likely to boost sales, market share, or profits. If this efficiency plateau'' proves lasting, then electricity use for appliance could begin to grow again as larger and more fancy models appear in households. 38 refs., 10 figs., 1 tab.

Schipper, L.; Hawk, D.V.

1989-12-01T23:59:59.000Z

214

Minority and poor households: patterns of travel and transportation fuel use  

SciTech Connect

This report documents the travel behavior and transportation fuel use of minority and poor households in the US, using information from numerous national-level sources. The resulting data base reveals distinctive patterns of household vehicle availability and use, travel, and fuel use and enables us to relate observed differences between population groups to differences in their demographic characteristics and in the attributes of their household vehicles. When income and residence location are controlled, black (and to a lesser extent, Hispanic and poor) households have fewer vehicles regularly available than do comparable white or nonpoor households; moreover, these vehicles are older and larger and thus have significantly lower fuel economy. The net result is that average black, Hispanic, and poor households travel fewer miles per year but use more fuel than do average white and nonpoor households. Certain other findings - notably, that of significant racial differences in vehicle availability and use by low-income households - challenge the conventional wisdom that such racial variations arise solely because of differences in income and residence location. Results of the study suggest important differences - primarily in the yearly fluctuation of income - between black and white low-income households even when residence location is controlled. These variables are not captured by cross-sectional data sets (either the national surveys used in our analysis or the local data sets that are widely used for urban transportation planning).

Millar, M.; Morrison, R.; Vyas, A.

1986-05-01T23:59:59.000Z

215

U.S. Department of Energy, Energy Information Administration (EIA  

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

9 - Avg VMT by HH Comp EIA","Table A19. U.S. Average Vehicle-Miles Traveled by Household Composition1 (EIA), 2001 9 - Avg VMT by HH Comp EIA","Table A19. U.S. Average Vehicle-Miles Traveled by Household Composition1 (EIA), 2001 (Thousand Miles per Household)" "Std Errors for A19","Relative Standard Errors for Table A19. U.S. Average Vehicle-Miles Traveled by Household Composition1 (EIA), 2001 (Percent)" "N Cells for A19","Number of Sample Cases Contributing to Estimates in Table A19. U.S. Average Vehicle-Miles Traveled by Household Composition1 (EIA), 2001" " Page A-1 of A-N" "Table A19. U.S. Average Vehicle-Miles Traveled by Household Composition1 (EIA), 2001 (Thousand Miles per Household)" "2001 Household Characteristics","Households With Children",,,,"Households Without Children"

216

Average summer electric power bills expected to be lowest in four years  

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

summer electric power bills expected to be lowest in summer electric power bills expected to be lowest in four years The average U.S. household is expected to pay $395 for electricity this summer. That's down 2.5% from last year and the lowest residential summer power bill in four years, according to the new forecast from the U.S. Energy Information Administration. Lower electricity use to meet cooling demand this summer because of forecasted milder temperatures compared with last summer is expected to more than offset higher electricity prices. The result is lower power bills for most U.S. households during the June, July, and August period. However electricity use and prices vary by region. EIA expects residential power bills will be lower in all areas of the country... except for the West South Central region, which includes

217

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

218

Average Residential Price  

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

Data Series: Average Residential Price Residential Price - Local Distribution Companies Residential Price - Marketers Residential % Sold by Local Distribution Companies Average...

219

Energy Use, Information, and Behavior in Small Commercial Buildings  

E-Print Network (OSTI)

of analyzing and interpreting energy data They used ethnographic interviewing methods to evaluate energy feedback in the form of a Home Energy Report providing raw monthly billing data and weather-corrected annual energy consumption data to households. Like... and restaurants. Range shown is one standard deviation. l..ow energy business' is an average value for the lowest 10% of businesses in the sample. 20a Figure 4. Monthly energy consumption. CENTER FOR ENERGY AND ENVIRONMENTAL STUDIES Princeton University ENERGY...

Haberl, J. S.; Kempton, W.; Komor, P.

2009-02-20T23:59:59.000Z

220

Household equipment of Canadians -- features of the 1993 stock and the 1994 and 1995 purchases: Analysis report  

SciTech Connect

This report reviews the results of three surveys that collected information on household equipment: The 1994 and 1995 Household Equipment Surveys and the 1993 Survey of Household Energy Use. The goal of the report is to highlight the features of energy-consuming equipment bought by Canadian households in 1994 and 1995 in comparison to those owned by households in 1993. Results are presented by type of equipment: Refrigerators, stoves, dishwashers, freezers, automatic washers, automatic dryers, air conditioning systems, heating systems, and water heaters. Appendices include information on survey methodology and a copy of the survey questionnaire.

Not Available

1997-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

Short-Term Energy Outlook - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Projected Winter Fuel Expenditures by Fuel and Region Projected Winter Fuel Expenditures by Fuel and Region The average household winter heating fuel expenditures discussed in this STEO provide a broad guide to changes compared with last winter. However, fuel expenditures for individual households are highly dependent on local weather conditions, market size, the size and energy efficiency of individual homes and their heating equipment, and thermostat settings (see Winter Fuels Outlook table). Forecast temperatures are close to last winter nationally, with the Northeast about 3% colder and the West 3% warmer. Natural Gas About one-half of U.S. households use natural gas as their primary heating fuel. EIA expects households heating with natural gas to spend an average of $80 (13%) more this winter than last winter. The increase in natural gas

222

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

223

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

224

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

225

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

226

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

227

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

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

Purchasing a New Energy-Efficient Central Heating System | Department of  

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

Purchasing a New Energy-Efficient Central Heating System Purchasing a New Energy-Efficient Central Heating System Purchasing a New Energy-Efficient Central Heating System October 21, 2008 - 4:00am Addthis John Lippert Energy prices are skyrocketing. According to the Energy Information Administration's October 7, 2008 forecast, heating fuel expenditures for the average household using oil as its primary heating fuel are expected to increase by $449 over last winter. Households using natural gas to heat their homes can expect to pay $155 more this winter, on average, than last year, and those using propane can expect to pay $188 more. Households heating primarily with electricity can expect to pay an average of $89 more. That's a lot of money resulting solely from rising heating expenses. You may long for the "good old days," but when it comes to heating systems,

231

Purchasing a New Energy-Efficient Central Heating System | Department of  

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

Purchasing a New Energy-Efficient Central Heating System Purchasing a New Energy-Efficient Central Heating System Purchasing a New Energy-Efficient Central Heating System October 21, 2008 - 4:00am Addthis John Lippert Energy prices are skyrocketing. According to the Energy Information Administration's October 7, 2008 forecast, heating fuel expenditures for the average household using oil as its primary heating fuel are expected to increase by $449 over last winter. Households using natural gas to heat their homes can expect to pay $155 more this winter, on average, than last year, and those using propane can expect to pay $188 more. Households heating primarily with electricity can expect to pay an average of $89 more. That's a lot of money resulting solely from rising heating expenses. You may long for the "good old days," but when it comes to heating systems,

232

Characteristics RSE Column Factor: Households with Children Households...  

Annual Energy Outlook 2012 (EIA)

... 6.1 0.8 2.7 2.6 Q Q Q Q Q Q Q 23.2 Race of Householder White ... 54.8 14.4 27.6 12.8 83.7 3.2 6.7 7.2...

233

Physical activity of adults in households with and without children  

E-Print Network (OSTI)

whites, fewer Hispanics, and higher household incomes thanWhites, fewer Hispanics, and higher household incomes thanWhites, fewer Hispanics, and higher household incomes than

Candelaria, Jeanette Irene

2010-01-01T23:59:59.000Z

234

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

235

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

236

U.S. Department of Energy, Energy Information Administration (EIA  

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

A2 - Average per Households","Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" A2 - Average per Households","Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "Std Errors for A2","Relative Standard Errors for Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001 (Percent)" "N Cells for A2","Number of Sample Cases Contributing to Estimates in Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" " Page A-1 of A-N" "Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "2001 Household Characteristics","Number of Households with Vehicles (million)","Average per Household with Vehicles"

237

The World Distribution of Household Wealth  

E-Print Network (OSTI)

Japan is not a remote prospect. In summary, it is clear that householdJapan Korea, South New Zealand Norway Spain Sweden Switzerland United Kingdom United States Year Unit share of top 2002 household

DAVIES, JAMES B; Shorrocks, Anthony; Sandstrom, Susanna; WOLFF, EDWARD N

2007-01-01T23:59:59.000Z

238

To appear in the Proceedings of The Second International Conference on Energy Efficiency in Household Appliances, Naples (Italy), September 2000. Also published  

E-Print Network (OSTI)

California homes. Total standby power in the homes ranged from 14­169 W, with an average of 67 W of thousands of appliances, but few measurements of total standby power consumption in individual homes. To our electricity consumption in individual homes and the likely impact of policies aimed at reduction. We report

Kammen, Daniel M.

239

Americans' Average Radiation Exposure  

SciTech Connect

We live with radiation every day. We receive radiation exposures from cosmic rays, from outer space, from radon gas, and from other naturally radioactive elements in the earth. This is called natural background radiation. It includes the radiation we get from plants, animals, and from our own bodies. We also are exposed to man-made sources of radiation, including medical and dental treatments, television sets and emission from coal-fired power plants. Generally, radiation exposures from man-made sources are only a fraction of those received from natural sources. One exception is high exposures used by doctors to treat cancer patients. Each year in the United States, the average dose to people from natural and man-made radiation sources is about 360 millirem. A millirem is an extremely tiny amount of energy absorbed by tissues in the body.

NA

2000-08-11T23:59:59.000Z

240

Short-Term Energy and Winter Fuels Outlook October 2013  

Gasoline and Diesel Fuel Update (EIA)

and Winter Fuels Outlook October 2013 1 and Winter Fuels Outlook October 2013 1 October 2013 Short-Term Energy and Winter Fuels Outlook (STEO) Highlights  EIA projects average U.S. household expenditures for natural gas and propane will increase by 13% and 9%, respectively, this winter heating season (October 1 through March 31) compared with last winter. Projected U.S. household expenditures are 2% higher for electricity and 2% lower for heating oil this winter. Although EIA expects average expenditures for households that heat with natural gas will be significantly higher than last winter, spending for gas heat will still be lower than the previous 5-year average (see EIA Short-Term Energy and Winter Fuels Outlook slideshow).  Brent crude oil spot prices fell from a recent peak of $117 per barrel in early September to

Note: This page contains sample records for the topic "average household energy" 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

Trip rate comparison of workplace and household surveys  

E-Print Network (OSTI)

Available vs. Trip Rate) 14 El Paso Household Survey (Household Income vs. Trip Rate) . 15 El Paso Workplace Survey (Household Income vs. Trip Rate) . 52 52 53 53 54 54 16 BPA Household Survey (Household Size vs. Trip Rate) . . 17 BPA Workplace... Survey (Household Size vs. Trip Rate) . . 56 56 18 BPA Household Survey (No. of Employees vs. Trip Rate) . . 19 BPA Workplace Survey (No. of Employees vs. Trip Rate) . . 20 BPA Household Survey (Vehicles Available vs. Trip Rate) . . 21 BPA Workplace...

Endres, Stephen Michael

2012-06-07T23:59:59.000Z

242

Estimating broad-brush rebound effects for household energy consumption in the EU 28 countries and Norway: some policy implications of Odyssee data  

Science Journals Connector (OSTI)

Abstract Currently there is a strong policy commitment in European Union (EU) and Organisation for Economic Co-operation and Development (OECD) countries to increase the energy efficiency of residential buildings, and it is widely assumed that this will naturally and automatically reduce domestic energy consumption. However, other factors such as fuel prices, wages, attitudes and lifestyles also influence energy consumption. This paper calculates broad-brush rebound effects based on changes in energy efficiency and energy consumption in each of the 28EU countries plus Norway, for the years 20002011. In doing so, it tests how well the assumption of energy efficiency leading to energy reduction stands up to scrutiny in these lands. It uses the EUs Odyssee database for efficiency and consumption figures and a commonly employed econometric definition of the rebound effect as an energy-efficiency elasticity. Most older EU lands show rebound effects in the expected range of 050%. However, the range for newer EU countries is 100550%, suggesting that energy efficiency increases are not a good predictor of energy consumption. A more in-depth look at one country, Germany, suggests these results underestimate the rebound effect significantly. This also identifies research needs for specific energy consumption determinants in each country, to find more precisely what is driving consumption levels.

Ray Galvin

2014-01-01T23:59:59.000Z

243

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

4 4 Weatherization Population Facts - Roughly 25% of Federally eligible households move in and out of poverty "classification" each year. - The average income of Federally eligible households in FY 2005 was $16,264, based on RECS and Bureau of the Census' Current Population Survey (CPS) data. - States target the neediest, especially the elderly, persons with disabilities, and families with children. - Since the inception of the Weatherization Assistance Program in 1976, over 6.3 million households have received weatherization services with DOE and leveraged funding. - In FY 2009, the energy burden on Federally eligible households was about four times the burden on Federally ineligible households (14% versus 4%). Source(s): ORNL, Weatherization Works: Final Report on the National Weatherization Evaluation, Sept. 1994, p. 1 for migrating poor; ORNL, 1996 for targeting; HHS,

244

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

245

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

246

Unimodular Gravity and Averaging  

E-Print Network (OSTI)

The question of the averaging of inhomogeneous spacetimes in cosmology is important for the correct interpretation of cosmological data. In this paper we suggest a conceptually simpler approach to averaging in cosmology based on the averaging of scalars within unimodular gravity. As an illustration, we consider the example of an exact spherically symmetric dust model, and show that within this approach averaging introduces correlations (corrections) to the effective dynamical evolution equation in the form of a spatial curvature term.

A. Coley; J. Brannlund; J. Latta

2011-02-16T23:59:59.000Z

247

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

248

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

249

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

250

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

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

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

253

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

254

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

255

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

256

HFAG Charm Mixing Averages  

E-Print Network (OSTI)

Recently the first evidence for charm mixing has been reported by several experiments. To provide averages of these mixing results and other charm results, a new subgroup of the Heavy Flavor Averaging Group has been formed. We here report on the method and results of averaging the charm mixing results.

B. Aa. Petersen

2007-12-10T23:59:59.000Z

257

U.S. Department of Energy, Energy Information Administration (EIA  

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

2 - Avg VMT by HH Comp ","Table A12. U.S. Average Vehicle-Miles Traveled by Household Composition (NHTS)2, 2001 2 - Avg VMT by HH Comp ","Table A12. U.S. Average Vehicle-Miles Traveled by Household Composition (NHTS)2, 2001 (Thousand Miles per Household)" "Std Errors for A12","Relative Standard Errors for Table A12. U.S. Average Vehicle-Miles Traveled by Household Composition (NHTS)2, 2001 (Percent)" "N Cells for A12","Number of Sample Cases Contributing to Estimates in Table A12. U.S. Average Vehicle-Miles Traveled by Household Composition (NHTS)2, 2001" " Page A-1 of A-N" "Table A12. U.S. Average Vehicle-Miles Traveled by Household Composition (NHTS)2, 2001 (Thousand Miles per Household)" "2001 Household Characteristics","No Children",,"Youngest Child 0-5",,"Youngest Child

258

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

259

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

E-Print Network (OSTI)

from household energy consumption i n Japan increased b y 20is that household energy consumption i n Japan has notfrom a l l households i n Japan, through 2050 (with energy-

2006-01-01T23:59:59.000Z

260

Metering Campaign on All Cooking End-Uses in 100 Households  

Science Journals Connector (OSTI)

This paper presents the findings of an experimental study performed in 100 French households on the end-use power demand and energy consumption of domestic appliances focusing on cooking appliances [1].

Olivier Sidler

2001-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

Chemical Characterization and Source Apportionment of Household Fine Particulate Matter in Rural, Peri-urban, and Urban West Africa  

Science Journals Connector (OSTI)

In addition to households own fuel, HAP in urban households is affected by the extent of biomass use in the neighborhood, and by traffic-related sources. ... The elemental concentrations of the samples were quantified by energy dispersive X-ray fluorescence (ED-XRF) using a Shimadzu EDX-700HS spectrometer (Shimadzu Corp., Japan) at the Institute of Astronomy, Geophysics and Atmospheric Science, University of Sao Paulo, Brazil. ...

Zheng Zhou; Kathie L. Dionisio; Thiago G. Verissimo; Americo S. Kerr; Brent Coull; Stephen Howie; Raphael E. Arku; Petros Koutrakis; John D. Spengler; Kimberly Fornace; Allison F. Hughes; Jose Vallarino; Samuel Agyei-Mensah; Majid Ezzati

2013-12-18T23:59:59.000Z

262

Effects on minority and low-income households of the EPA proposal to reduce leaded gasoline use  

SciTech Connect

To reduce the potentially harmful environmental effects of lead in the environment, the US Environmental Protection Agency (EPA) has proposed a reduction in the amount of lead used in leaded gasoline. This report examines the potential impacts of such action on minority and low-income households in the US. The benefits of the EPA's proposal would presumably accrue primarily to households that contain small children and that are located in the central cities of metropolitan areas. This is because small children (under age seven) are particularly susceptible to the effects of lead and also because the automobile traffic density in central cities is higher than in any other area. Potential costs are examined in terms of households that own vehicles requiring leaded gasoline. Costs could accrue either because of higher gasoline prices due to reduced lead content or because of higher vehicle repair costs for engines that must use leaded gasoline to prevent excessive wear. Because of their location and number, minority and low-income households with small children would benefit more than the average US household. No costs would be incurred by the relatively large segment of minority and low-income households that own no vehicles. However, the Hispanic and other minority (except black) and low-income households that do own vehicles have a greater than average share of vehicles that require leaded gasoline; costs to these households because of the EPA's proposed action would be comparatively high.

Rose, K.; LaBelle, S.; Winter, R.; Klein, Y.

1985-04-01T23:59:59.000Z

263

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

264

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

265

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

266

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

267

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

268

Madelung Fluid Model for The Most Likely Wave Function of a Single Free Particle in Two Dimensional Space with a Given Average Energy  

E-Print Network (OSTI)

We consider spatially two dimensional Madelung fluid whose irrotational motion reduces into the Schr\\"odinger equation for a single free particle. In this respect, we regard the former as a direct generalization of the latter, allowing a rotational quantum flow. We then ask for the most likely wave function possessing a given average energy by maximizing the Shannon information entropy over the quantum probability density. We show that there exists a class of solutions in which the wave function is self-trapped, rotationally symmetric, spatially localized with finite support, and spinning around its center, yet stationary. The stationarity comes from the balance between the attractive quantum force field of a trapping quantum potential generated by quantum probability density and the repulsive centrifugal force of a rotating velocity vector field. We further show that there is a limiting case where the wave function is non-spinning and yet still stationary. This special state turns out to be the lowest stationary state of the ordinary Schr\\"odinger equation for a particle in a cylindrical tube classical potential.

Agung Budiyono; Ken Umeno

2009-02-23T23:59:59.000Z

269

What People Do with Consumption Feedback: A Long-Term Living Lab Study of a Home Energy Management System  

Science Journals Connector (OSTI)

......to seven households over a period...edition of the Energy Efficiency Action Plan...Consumption. Energy Efficiency in Household Appliances...Council on energy efficiency and repealing...Standards-Households in the informations......

Tobias Schwartz; Gunnar Stevens; Timo Jakobi; Sebastian Denef; Leonardo Ramirez; Volker Wulf; Dave Randall

2014-04-01T23:59:59.000Z

270

VOLUME 87, NUMBER 7 P H Y S I C A L R E V I E W L E T T E R S 13 AUGUST 2001 Free Energy Self-Averaging in Protein-Sized Random Heteropolymers  

E-Print Network (OSTI)

-Averaging in Protein-Sized Random Heteropolymers Jeffrey Chuang,1 Alexander Yu. Grosberg,2,3 and Mehran Kardar1,4 1 of heteropolymers are inherently macroscopic, but are applied to mesoscopic proteins. To compute the free energy. By enumerating the states and energies of compact 18, 27, and 36mers on a lattice with an ensemble of random

Chuang, Jeffrey

271

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

272

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

273

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

274

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

275

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

276

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

277

Household Response To Dynamic Pricing Of Electricity: A Survey...  

Open Energy Info (EERE)

Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic...

278

Household Light Makes Global Heat: High Black Carbon Emissions From Kerosene Wick Lamps  

Science Journals Connector (OSTI)

(3) Lighting is another component of this household energy challenge, with millions of households still relying on simple liquid-fueled lamps, but little is known of the associated environmental and health impacts. ... For laboratory tests, CO2 and CO concentrations were measured in real-time with a Li-COR 6252 (Li-COR Biosciences, Lincoln, NE) and Horiba AIA-220 (Horiba, Kyoto, Japan) nondispersive infrared (NDIR) analyzer, respectively. ...

Nicholas L. Lam; Yanju Chen; Cheryl Weyant; Chandra Venkataraman; Pankaj Sadavarte; Michael A. Johnson; Kirk R. Smith; Benjamin T. Brem; Joseph Arineitwe; Justin E. Ellis; Tami C. Bond

2012-11-19T23:59:59.000Z

279

A robust distance measurement and dark energy constraints from the spherically averaged correlation function of Sloan Digital Sky Survey luminous red Galaxies  

Science Journals Connector (OSTI)

......measurement and dark energy constraints...Digital Sky Survey luminous red...Digital Sky Survey (SDSS) data...assuming a dark energy model or a...constraints on the dark energy and cosmological...largest effective survey volume to date......

Chia-Hsun Chuang; Yun Wang; Maddumage Don P. Hemantha

2012-06-21T23:59:59.000Z

280

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

Note: This page contains sample records for the topic "average household energy" 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

Household Vehicles Energy Use: Latest Data & Trends  

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

for a period of 1 year. VMT was calculated using (1) a regression method developed by Oak Ridge National Laboratories, Center for Transportation Analysis (2) two odometer...

282

Household Vehicles Energy Use: Latest Data & Trends  

Annual Energy Outlook 2012 (EIA)

a NHTS sample vehicle having the following attributes: Volkswagen, Sirocco, 1990, Automobile. Toggling of model years, by a single year increase followed by a single year...

283

Household Vehicles Energy Consumption 1994 - Appendix C  

Annual Energy Outlook 2012 (EIA)

Protection Agency (EPA) certification files (CERT files) containing laboratory test results of MPG. When the vehicle characteristic was missing from the questionnaire, but...

284

Household Vehicles Energy Use: Latest Data & Trends  

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

80, 85, 86, 88, and 600 and 10 CFR Part 474. GREET MODEL Of course, there are other conversion factors available, depending on the various fuel-specific factors. For the...

285

Environmental Communication Aimed at Household Energy Conservation  

Science Journals Connector (OSTI)

The first commitment period of the Kyoto Protocol started in 2008. Japan is required to cut down on greenhouse...2) emissions in Japan have been showing a tendency to increase ... report of the Ministry of the En...

Chizuru Nishio

2010-01-01T23:59:59.000Z

286

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

287

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

288

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

289

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

290

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

291

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

292

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

293

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

294

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

295

Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design  

Science Journals Connector (OSTI)

The literature concerning the application of information-feedback methods for saving energy in the home is reviewed. Particular attention is given to electronic feedback via smart meters and displays, or energy-consumption indicators (ECI). Previous studies have not focused on individual appliances, but this paper presents the findings of a UK field study involving 44 households which considered domestic cooking: it compares the effectiveness of providing paper-based energy-use/saving information with electronic feedback of energy-consumption via \\{ECIs\\} designed specifically for this investigation. Twelve Control Group households were monitored for a period of at least 12 months and this revealed an average daily consumption for electric cooking of 1.30kWh. Subsequently across a minimum monitoring period of 2 months, 14 out of 31 households achieved energy savings of greater than 10% and six of these achieved savings of greater than 20%. The average reduction for households employing an ECI was 15%, whereas those given antecedent information alone reduced their electricity consumption, on average, by only 3%. The associated behavioural changes and the importance of providing regular feedback during use are identified. It is recommended that further attention be given to optimising the design and assessing the use of energy-consumption indicators in the home, in order to maximise the associated energy-saving potential.

G. Wood; M. Newborough

2003-01-01T23:59:59.000Z

296

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

297

Energy in american homes: Changes and prospects  

Science Journals Connector (OSTI)

Average energy consumption per U.S. household has fallen by just under 20% in the last ten years. Much of this drop occurred after 1979, when gas and electricity prices as well as oil prices rose in real terms. The response of households to higher prices has involved physical modifications on and in the home and changes in behavior. Many actions have been taken by households, but the most important single factor has been a significant reduction in indoor temperatures. The greater energy efficiency of new homes and appliances has also helped to depress residential energy demand, although improvements have levelled off in the last few years. There are signs that the momentum of energy conservation is less now than it was 2 years ago, but it appears that energy prices will be high enough to discourage households from returning to former energy-using practices. Along with the continued replacement of homes and appliances with more efficient models, and other factors such as the migration to wanner regions and the movement to more apartments and smaller homes, this will probably keep U.S. residential energy consumption at about its present level through the 1980s.

Stephen Meyers; Lee Schipper

1984-01-01T23:59:59.000Z

298

A comparative evaluation of household preferences for solar photovoltaic standalone and mini-grid system: An empirical study in a costal village of Indian Sundarban  

Science Journals Connector (OSTI)

Solar PhotoVoltaic (SPV) based systems have been widely accepted technology for rural electrification in developing countries. The standalone SPV home lighting system has increasingly been popular among rural households, while SPV mini-grid supply system is being promoted for rural electrification schemes. This study uses data from household survey to explore the impact of household characteristics on the preference for electrical energy from SPV systems. Econometric evidence shows heterogeneity in behavioural pattern for these two SPV systems. The flexibility in use and cost of systems might explain this difference. Household characteristics such as monthly household income, household size, occupational status of household head, number of room and type of house significantly influence households decision for SPV standalone home lighting systems. For SPV mini-grid supply households income and monthly expenditure on kerosene are significant predictors. The result reported in this paper might be a valuable input for policy makers to frame right policy mix with regard to provide subsidy on rural electrification programmes.

Amit K. Bhandari; Chinmoy Jana

2010-01-01T23:59:59.000Z

299

Nevada: Kingston Creek Hydro Project Powers 100 Households  

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

Hydropower project produces enough electricity to annually power nearly 100 typical American households.

300

DOE Average Results  

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

DOE DOE Average Results FY 12 DOE Target FY 12 Customer Perspective: Customer Satisfaction: -Timeliness 92 88 -Quality 94 92 Effective Service Partnership: -Extent of Customer Satisfaction with the responsiveness, etc. 90 92 Internal Business Perspective: Acquisition Excellence: -Extent to which internal quality control systems are effective 90 88 Most Effective Use of Contracting Approaches to Maximize Efficiency and Cost Effectiveness: Use of Competition: -% of total $'s obligated on competitive acquisitions >$3000 (Agency Level Only) 94 85 -% of acquisition actions competed for actions > $3000 (Agency Level Only) 65 68 Performance Based Acquisition: - % PBA actions relative to total eligible new acquisition actions (applicable to new actions > $25K) 82

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301

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

7 7 Residential Energy Burdens, by Weatherization Eligibility and Year (1) 1987 Mean Mean Mean Mean Mdn Mean Mean Mdn Mean Group Indvdl Group Indvdl Indvdl Group Indvdl Indvdl Group Total U.S. Households 4.0% 6.8% 3.2% 6.1% 3.5% 2.4% 7.2% 4.4% 3.2% Federally Eligible 13.0% 14.4% 10.1% 12.1% 7.9% 7.7% 13.8% 9.6% 10.0% Federally Ineligible 4.0% 3.5% N.A. 3.0% 2.6% 2.0% 3.6% 3.1% 2.6% Below 125% Poverty Line 13.0% N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. Note(s): Source(s): 1990 FY 2000 (2) FY 2009 (3) 1) Energy burden can be defined broadly as the burden placed on household incomes by the cost of energy, or the ratio of energy expenditures to income for a household. DOE Weatherization primarily uses mean individual burden and mean group burden since these statistics provide data on how an "average" individual household fares against an "average" group of households (that is, how burdens are

302

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)

303

U.S. Department of Energy, Energy Information Administration (EIA  

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

A2 - Average per Households","Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" A2 - Average per Households","Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "Std Errors for A2","Relative Standard Errors for Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001 (Percent)" "N Cells for A2","Number of Sample Cases Contributing to Estimates in Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "A3 - Average per Vehicles","Table A3. U.S. Per Vehicle Average Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "Std Errors for A3","Relative Standard Errors for Table A3. U.S. Per Vehicle Average Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001

304

Green Computing Wanted: Electricity Consumptions in the IT Industry and by Household Computers in Five Major Chinese Cities  

Science Journals Connector (OSTI)

Exhausted energy consumption becomes a world-wide issue nowadays. Computing contributes a large portion of energy consumption. The concept of green computing has been popularized. Along with the rapid development of China, energy issue becomes more and ... Keywords: energy/electricity consumption, IT industry, household computers, energy efficiency, green computing

Luyang Wang; Tao Wang

2011-08-01T23:59:59.000Z

305

Environmental attitudes and household consumption: an ambiguous relationship  

Science Journals Connector (OSTI)

This article analyses the relationship between environmental attitudes and energy use in the home and for transport by Norwegian households. Quantitative surveys were used to find statistical correlations, and qualitative analyses to reveal mechanisms that influence the ability to behave in an environmentally friendly way. Three theses about attitudes, mechanisms and household consumption are presented. Firstly, a desire to project an environmentally friendly image has little influence on energy use in the home and for transport. Secondly, a sense of powerlessness prevents people from translating positive environmental attitudes into low energy use in the home and for everyday transport. Thirdly, a desire to self-indulge prevents people from translating positive environmental attitudes into low energy use for long distance leisure travel. These results have important implications for environmental policy. Public information and awareness campaigns can give consumers information on how to behave in an environmentally responsible way, but tend only to influence categories of consumption with little environmental impact. Structural change can be used to mitigate the effect of the sense of powerlessness and encourage environmentally friendly behaviour, but the desire to self-indulge is much more difficult to deal with.

Erling Holden; Kristin Linnerud

2010-01-01T23:59:59.000Z

306

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

307

Drivers of Future Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

trends - Household income migration urbanization * Policy: China Energy Outlook - Air pollution - Climate change 4 (1) Industrial energy intensity: The energy intensity of...

308

Enhanced naphthenic refrigeration oils for household refrigerator systems  

SciTech Connect

Due to industry concerns about the successful employment of hydrofluorocarbon-immiscible hydrocarbon oils in refrigeration systems, enhanced naphthenic refrigeration oils have been developed. These products have been designed to be more dispersible with hydrofluorocarbon (HFC) refrigerants, such as R-134a, in order to facilitate lubricant return to the compressor and to ensure proper energy efficiency of the system. Bench tests and system performance evaluations indicate the feasibility of these oils for use in household refrigeration applications. Results of these evaluations are compared with those obtained with polyol esters and typical naphthenic mineral oils employed in chlorofluorocarbon (CFC) and hydrochlorofluorocarbon (HCFC) refrigeration applications.

Reyes-Gavilan, J.L.; Flak, G.T.; Tritcak, T.R. [Witco Corp., Oakland, NJ (United States); Barbour, C.B. [Americold, Cullman, AL (United States)

1997-12-31T23:59:59.000Z

309

Household demand and willingness to pay for hybrid vehicles  

Science Journals Connector (OSTI)

Abstract This paper quantitatively evaluates consumers' willingness to pay for hybrid vehicles by estimating the demand of hybrid vehicles in the U.S. market. Using micro-level data on consumer purchases of hybrid and non-hybrid vehicles from National Household Travel Survey 2009, this paper formulates a mixed logit model of consumers' vehicle choices. Parameter estimates are then used to evaluate consumers' willingness to pay for hybrids. Results suggest that households' willingness to pay for hybrids ranges from $963 to $1718 for different income groups, which is significantly lower than the average price premium (over $5000) of hybrid vehicles, even when taking the fuel costs savings of hybrid vehicles into consideration. The differences reveal that although the market has shown increasing interest in hybrid vehicles, consumers' valuation of the hybrid feature is still not high enough to compensate for the price premium when they make new purchases. Policy simulations are conducted to examine the effects of raising federal tax incentives on the purchase of hybrid vehicles.

Yizao Liu

2014-01-01T23:59:59.000Z

310

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas  

Science Journals Connector (OSTI)

In todays world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austins personal-fleet evolution. Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicles emissions, more strongly than they respond to information on fuel cost savings. Twenty five-year simulations of Austins household vehicle fleet suggest that, under all scenarios modeled, Austins vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, \\{PHEVs\\} and Smart Cars are estimated to represent 25% of the fleets VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO2 emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO2 emissions by 30% (relative to trend). Two- and three-vehicle households are simulated to be the highest adopters of \\{HEVs\\} and \\{PHEVs\\} across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austins current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year. In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.

Sashank Musti; Kara M. Kockelman

2011-01-01T23:59:59.000Z

311

Table 5.17. U.S. Number of Households by Vehicle Fuel Expenditures...  

Annual Energy Outlook 2012 (EIA)

5.17. U.S. Number of Households by Vehicle Fuel Expenditures, 1994 (Continued) (Million Households) 1993 Household and 1994 Vehicle Characteristics RSE Column Factor: All...

312

Transferring 2001 National Household Travel Survey  

SciTech Connect

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

313

average air temperature | OpenEI  

Open Energy Info (EERE)

average air temperature average air temperature Dataset Summary Description (Abstract): Air Temperature at 10 m Above The Surface Of The Earth (deg C)NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly & Annual Average (July 1983 - June 2005)Parameter: Air Temperature at 10 m Above The Surface Of The Earth (deg C)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; Source U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE) Date Released March 31st, 2009 (5 years ago) Date Updated April 01st, 2009 (5 years ago) Keywords average air temperature

314

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

315

Opportunities to reduce greenhouse gas emissions from households in Nigeria  

Science Journals Connector (OSTI)

Efforts to mitigate climate threats should not exclude the household as the household is a major driver of greenhouse gas (GHG) emissions through its consumption...2) emissions from kerosene combustion for lighting

O. Adeoti; S. O. Osho

2012-02-01T23:59:59.000Z

316

Household Wealth in a Cross-Country Perspective  

Science Journals Connector (OSTI)

This paper provides a comparative analysis of household wealth in the United States, the United Kingdom, Japan, France, Germany, Spain, and Italy. ... wealth, looking at the instruments in which households invest...

Laura Bartiloro; Massimo Coletta

2012-01-01T23:59:59.000Z

317

Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip  

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

5: March 22, 5: March 22, 2010 Average Vehicle Trip Length to someone by E-mail Share Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Facebook Tweet about Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Twitter Bookmark Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Google Bookmark Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Delicious Rank Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Digg Find More places to share Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on AddThis.com... Fact #615: March 22, 2010 Average Vehicle Trip Length According to the latest National Household Travel Survey, the average trip

318

Control of household refrigerators. Part 1: Modeling temperature control performance  

SciTech Connect

Commercial household refrigerators use simple, cost-effective, temperature controllers to obtain acceptable control. A manually adjusted airflow damper regulates the freezer compartment temperature while a thermostat controls operation of the compressor and evaporator fan to regulate refrigerator compartment temperature. Dual compartment temperature control can be achieved with automatic airflow dampers that function independently of the compressor and evaporator fan thermostat, resulting in improved temperature control quality and energy consumption. Under dual control, freezer temperature is controlled by the thermostat while the damper controls refrigerator temperature by regulating airflow circulation. A simulation model is presented that analyzes a household refrigerator configured with a conventional thermostat and both manual and automatic dampers. The model provides a new paradigm for investigating refrigerator systems and temperature control performance relative to the extensive verification testing that is typically done by manufacturers. The effects of each type of control and damper configuration are compared with respect to energy usage, control quality, and ambient temperature shift criteria. The results indicate that the appropriate control configuration can have significant effects and can improve plant performance.

Graviss, K.J.; Collins, R.L.

1999-07-01T23:59:59.000Z

319

Home Prices and Household Callan Windsor, Jarkko Jskel and  

E-Print Network (OSTI)

Research Discussion Paper Home Prices and Household Spending Callan Windsor, Jarkko Jääskelä. ISSN 1320-7729 (Print) ISSN 1448-5109 (Online) #12;Home Prices and Household Spending Callan Windsor Abstract This paper explores the positive relationship between home prices and household spending

320

Viscosity-average molecular weight  

Science Journals Connector (OSTI)

n .... An averaged molecular weight for high polymers that relates most closely to measurements of dilute-solution viscosities ...

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

Handling Frame Problems When Address-Based Sampling Is Used for In-Person Household Surveys  

Science Journals Connector (OSTI)

......use as the sampling frame for household surveys. This subset includes...However, around 90 percent of households with PO box addresses also have...recent growth, new construction, Hispanic households, non-English-speaking households......

Graham Kalton; Jennifer Kali; Richard Sigman

2014-09-01T23:59:59.000Z

322

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

E-Print Network (OSTI)

Japan by 2020. 12 of 17 Because of their large share in household energyJapan in 2000 which was 4560 kWh/household (IEEJ, 2003). In developed countries, the energy

Zhou, Nan

2010-01-01T23:59:59.000Z

323

E-Print Network 3.0 - assessing household solid Sample Search...  

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

of Groundwater Contamination from Household Wastewater... 12;Glossary Household Wastewater Treatment These terms may help you make more accurate assessments......

324

Greenhouse Gas Emissions from the Consumption of Electric and Electronic Equipment by Norwegian Households  

Science Journals Connector (OSTI)

Greenhouse Gas Emissions from the Consumption of Electric and Electronic Equipment by Norwegian Households ... Conventional wisdom holds that large appliances, in particular washers, dryers, refrigerators and freezers, dominate residential energy consumption apart from heat, hot water and light. ... (16) It excludes lighting, all professional equipment, space heating, hot water, garden or car equipment, fire alarms, and air conditioning. ...

Edgar G. Hertwich; Charlotte Roux

2011-08-30T23:59:59.000Z

325

Stranded Vehicles: How Gasoline Taxes Change the Value of Households' Vehicle Assets  

E-Print Network (OSTI)

Stranded Vehicles: How Gasoline Taxes Change the Value of Households' Vehicle Assets Meghan Busse pollution caused by the burning of fossil fuels. Argu- ments against energy taxes, and gasoline taxes more incidence of the tax. We study the effect of a gasoline tax using changes in vehicle values. We construct

Rothman, Daniel

326

Characterizing probability density distributions for household electricity load profiles from high-resolution electricity use data  

Science Journals Connector (OSTI)

Abstract This paper presents a high-resolution bottom-up model of electricity use in an average household based on fit to probability distributions of a comprehensive high-resolution household electricity use data set for detached houses in Sweden. The distributions used in this paper are the Weibull distribution and the Log-Normal distribution. These fitted distributions are analyzed in terms of relative variation estimates of electricity use and standard deviation. It is concluded that the distributions have a reasonable overall goodness of fit both in terms of electricity use and standard deviation. A KolmogorovSmirnov test of goodness of fit is also provided. In addition to this, the model is extended to multiple households via convolution of individual electricity use profiles. With the use of the central limit theorem this is analytically extended to the general case of a large number of households. Finally a brief comparison with other models of probability distributions is made along with a discussion regarding the model and its applicability.

Joakim Munkhammar; Jesper Rydn; Joakim Widn

2014-01-01T23:59:59.000Z

327

Residential Energy Expenditures for Water Heating (2005) | OpenEI  

Open Energy Info (EERE)

Expenditures for Water Heating (2005) Expenditures for Water Heating (2005) Dataset Summary Description Provides total and average household expenditures on energy for water heating in the United States in 2005. The data was collected as part of the Residential Energy Consumption Survey (RECS). RECS is a national survey that collects residential energy-related data. The survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the United States. Data were obtained from residential energy suppliers for each unit in the sample to produce the data. Source EIA Date Released September 01st, 2008 (6 years ago) Date Updated January 01st, 2009 (6 years ago) Keywords Energy Expenditures Residential Water Heating Data application/vnd.ms-excel icon 2005_Total.Expenditures.for_.Water_.Heating_EIA.Sep_.2008.xls (xls, 70.1 KiB)

328

Table HC1.2.2 Living Space Characteristics by Average Floorspace  

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

2 Living Space Characteristics by Average Floorspace, " 2 Living Space Characteristics by Average Floorspace, " " Per Housing Unit and Per Household Member, 2005" ,,"Average Square Feet" ," Housing Units (millions)" ,,"Per Housing Unit",,,"Per Household Member" "Living Space Characteristics",,"Total1","Heated","Cooled","Total1","Heated","Cooled" "Total",111.1,2033,1618,1031,791,630,401 "Total Floorspace (Square Feet)" "Fewer than 500",3.2,357,336,113,188,177,59 "500 to 999",23.8,733,667,308,343,312,144 "1,000 to 1,499",20.8,1157,1086,625,435,409,235 "1,500 to 1,999",15.4,1592,1441,906,595,539,339 "2,000 to 2,499",12.2,2052,1733,1072,765,646,400

329

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

Program Definitions DOE Weatherization: Department of Energy's Weatherization Assistance Program DOE Weatherization Eligible Households: Households with incomes at or below 125% of the Federal poverty level, which varies by family size; however, a State may instead elect to use the LIHEAP income standard if its State LIHEAP income standard is at least 125% of the Federal poverty level. Data listed in this chapter include previously weatherized units. DOE Weatherization Eligible Households are a subset of Federally Eligible Households. DOE Weatherization Recipient Households: Households that have received weatherization under DOE Weatherization funding. Federally Eligible Households: Households with incomes below the Federal maximum standard of 150% to 200% of the poverty

330

Averaging Hypotheses in Newtonian Cosmology  

E-Print Network (OSTI)

Average properties of general inhomogeneous cosmological models are discussed in the Newtonian framework. It is shown under which circumstances the average flow reduces to a member of the standard Friedmann--Lema\\^\\i tre cosmologies. Possible choices of global boundary conditions of inhomogeneous cosmologies as well as consequences for the interpretation of cosmological parameters are put into perspective.

T. Buchert

1995-12-20T23:59:59.000Z

331

HIGH AVERAGE POWER OPTICAL FEL AMPLIFIERS.  

SciTech Connect

Historically, the first demonstration of the optical FEL was in an amplifier configuration at Stanford University [l]. There were other notable instances of amplifying a seed laser, such as the LLNL PALADIN amplifier [2] and the BNL ATF High-Gain Harmonic Generation FEL [3]. However, for the most part FELs are operated as oscillators or self amplified spontaneous emission devices. Yet, in wavelength regimes where a conventional laser seed can be used, the FEL can be used as an amplifier. One promising application is for very high average power generation, for instance FEL's with average power of 100 kW or more. The high electron beam power, high brightness and high efficiency that can be achieved with photoinjectors and superconducting Energy Recovery Linacs (ERL) combine well with the high-gain FEL amplifier to produce unprecedented average power FELs. This combination has a number of advantages. In particular, we show that for a given FEL power, an FEL amplifier can introduce lower energy spread in the beam as compared to a traditional oscillator. This properly gives the ERL based FEL amplifier a great wall-plug to optical power efficiency advantage. The optics for an amplifier is simple and compact. In addition to the general features of the high average power FEL amplifier, we will look at a 100 kW class FEL amplifier is being designed to operate on the 0.5 ampere Energy Recovery Linac which is under construction at Brookhaven National Laboratory's Collider-Accelerator Department.

BEN-ZVI, ILAN, DAYRAN, D.; LITVINENKO, V.

2005-08-21T23:59:59.000Z

332

An economic assessment of the impact of two crude oil price scenarios on households  

SciTech Connect

The impact of two possible future crude oil price scenarios -- high and low price cases -- is assessed for three population groups: majority (non-Hispanic and nonblack), black, and Hispanic. The two price scenarios were taken from the energy security'' report published by the US Department of Energy in 1987. Effects of the two crude oil price scenarios for the 1986--95 period are measured for energy demand and composition and for share of income spent on energy by the three population groups at both the national and census-region levels. The effects on blacks are marginally more adverse than on majority householders, while effects on Hispanics are about the same as those on the majority. Little change is seen in percentage of income spent on energy over the forecast period. Both Hispanic and black households would spend a larger share of their incomes on energy than would majority households. The relatively adverse effects in the higher price scenario shift from the South and West Census regions to the Northeast and Midwest. 24 refs., 7 figs., 22 tabs.

Poyer, D.A.; Teotia, A.P.S.; Hemphill, R.C.; Hill, L.G.; Marinelli, J.L.; Rose, K.J.; Santini, D.J.

1990-02-01T23:59:59.000Z

333

Economic theory and women's household status: The case of Japan  

Science Journals Connector (OSTI)

Economic development disadvantages wives. Conventional microeconomic theory predicts this. As household incomes rise, wives have incentives to specialize in intangible household production. This may raise total household production according to the theory of comparative advantage, but disproportionately favors husbands in distribution of the gains according to the marginal productivity theory of distribution. Wives may become better off in absolute terms but more dependent financially on their husbands and lose power within the household. Historically, Japanese gender roles became highly specialized and wives legal status declined, although other Meiji-era features protected wives. Policies to improve women's status should address the precise economic problem involved.

Barbara J. Redman

2008-01-01T23:59:59.000Z

334

Confronting earthquake risk in Japanare private households underinsured?  

Science Journals Connector (OSTI)

Despite the fact that Japan is an earthquake-prone country and Japanese ... risk averse, less than half of Japanese households are insured against earthquake risk. Based on...

Franz Waldenberger

2013-03-01T23:59:59.000Z

335

Salmon consumption at the household level in Japan.  

E-Print Network (OSTI)

??The primary purpose of this study is to investigate the salmon demand of Japanese households. The specific goals are to illuminate the substitutional relationship between (more)

Kikuchi, Akihiro

1987-01-01T23:59:59.000Z

336

Consumer perspectives on household hazardous waste management in Japan  

Science Journals Connector (OSTI)

We give an overview of the management systems of household hazardous waste (HHW) in Japan and discuss the management systems and their...

Misuzu Asari; Shin-ichi Sakai

2011-02-01T23:59:59.000Z

337

Tips: Lighting | Department of Energy  

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

Lighting Lighting Tips: Lighting May 4, 2012 - 3:16pm Addthis Lighting Choices Save You Money. Energy-efficient light bulbs are available in a wide variety of sizes and shapes. Lighting Choices Save You Money. Energy-efficient light bulbs are available in a wide variety of sizes and shapes. What does this mean for me? Replacing 15 inefficient incandescent bulbs in your home with energy-saving bulbs could save you about $50 per year. For the greatest savings, replace your old incandescent bulbs with ENERGY STAR-qualified bulbs. An average household dedicates about 10% of its energy budget to lighting. Switching to energy-efficient lighting is one of the fastest ways to cut your energy bills. Timers and motion sensors save you even more money by reducing the amount of time lights are on but not being used.

338

The Newest Addition to the ENERGY STAR Lineup: Water Heaters | Department  

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

The Newest Addition to the ENERGY STAR Lineup: Water Heaters The Newest Addition to the ENERGY STAR Lineup: Water Heaters The Newest Addition to the ENERGY STAR Lineup: Water Heaters February 17, 2009 - 9:48am Addthis Elizabeth Spencer Communicator, National Renewable Energy Laboratory If you've gone shopping for new appliances sometime in the last decade, then you're probably familiar with the ENERGY STAR® label. ENERGY STAR is a partnership between the U.S. Department of Energy and the U.S. Environmental Protection Agency that sets higher-than-average standards for household appliances, electronics, and commercial products. Products that meet these rigorous energy requirements can be designated as ENERGY STAR products. For the average consumer, it basically means that ENERGY STAR products are more energy efficient than their standard counterparts, and therefore will

339

Household Response To Dynamic Pricing Of Electricity: A Survey Of The  

Open Energy Info (EERE)

Household Response To Dynamic Pricing Of Electricity: A Survey Of The Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Focus Area: Crosscutting Topics: Market Analysis Website: www.hks.harvard.edu/hepg/Papers/2009/The%20Power%20of%20Experimentatio Equivalent URI: cleanenergysolutions.org/content/household-response-dynamic-pricing-el Language: English Policies: "Deployment Programs,Regulations,Financial Incentives" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation Regulations: "Mandates/Targets,Cost Recovery/Allocation,Enabling Legislation" is not in the list of possible values (Agriculture Efficiency Requirements, Appliance & Equipment Standards and Required Labeling, Audit Requirements, Building Certification, Building Codes, Cost Recovery/Allocation, Emissions Mitigation Scheme, Emissions Standards, Enabling Legislation, Energy Standards, Feebates, Feed-in Tariffs, Fuel Efficiency Standards, Incandescent Phase-Out, Mandates/Targets, Net Metering & Interconnection, Resource Integration Planning, Safety Standards, Upgrade Requirements, Utility/Electricity Service Costs) for this property.

340

Core Measure Average KTR Results  

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

Measure Measure Average KTR Results FY 12 Target FY 12 DOE M&O CONTRACTOR (KTR) BSC RESULTS FY 2012 Customer Perspective and level of communication provided by the procurement office 95 92 Internal Business Perspective: Assessment (%) of the degree to which the purchasing system is in compliance with stakeholder requirements 97 Local Goals % Delivery on-time (includes JIT, excludes Purchase Cards) 88 84 % of total dollars obligated, on actions > $150K , that were awarded using effective competition 73 Local Goals Rapid Purchasing Techniques: -% of transactions placed by users 77 Local Goals -% of transactions placed through electronic commerce 62 Local Goals Average Cycle Time: -Average cycle time for <= $150K 8 6 to 9 days

Note: This page contains sample records for the topic "average household energy" 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

Northern Virginia Residents Improve Their Homes' Energy With...  

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

Boost The Northern Virginia Home Energy Makeover Contest logo. The Local Energy Alliance Program (LEAP) awarded energy efficiency funding to three households as part of the...

342

Space Heating Scenarios for Ontario: a Demonstration of the Statistics Canada Household Model  

Science Journals Connector (OSTI)

ABSTRACT This paper describes the analytical and simulation capabilities of the currently implemented version of the household model developed by the Structural Analysis Division, Statistics Canada. The household model, as described in A Design Framework for Long Term Energy Economic Analysis of Dwelling Related Demand [1], is a simulation framework and related data base of the Canadian housing stocks, residential construction, and end-use energy consumption in the residential sector. The purpose of the model is to provide an analytical tool for evaluating a variety of residential energy conservation strategies including insulation retrofitting and the introduction of new building standards, the possibilities for fuel substitution afforded by equipment retrofitting, and the impact of new technologies for space conditioning with respect to impacts on residential energy requirements and construction materials over time. The simulation results for Ontario that are presented in the paper are for demonstration purposes only and do not constitute a forecast. The choice of Ontario was arbitrary; similar calculations can be performed for other provinces, for Canada as a whole, and for selected subprovincial regions. At the time of preparation of this paper, the population and household formation block at the national level, the housing stock block, and the space heating part of the space conditioning block are implemented. Therefore simulation results are limited to these areas.

R.H.H. Moll; K.H. Dickinson

1982-01-01T23:59:59.000Z

343

Inefficient subsidy in Nigerian oil sector; implications for revenue generation and household welfare in Nigeria  

Science Journals Connector (OSTI)

Subsidy exists when consumers are assisted by the government to pay less than the prevailing market price of a given commodity. In respect of fuel subsidy, it means that consumers would pay below the market price per litre of petroleum product. This paper is aim at analysing the effects of the increase in energy prices on the social welfare of Nigerian households and comparing the consequences with the condition in which in concurrence with increase in energy prices, the government undertakes transfer payments to Nigerian households in order to protect their social welfare status. An analytical reasoning model was adopted and within the framework of this model the effects of increase in energy price on social welfare is discussed. Decrease in energy subsidies and a shift towards market prices will result in a lower budget deficit for the government and powerfully harness one of the main causes of inflation. However, if the elimination of subsidies be accompanied by transfer payments to households, the result is increase in the government budget deficit which in its turn will enhance inflation thus very negatively affecting social welfare.

Benjamin Anabori Mmadu; David Chuks Akan

2013-01-01T23:59:59.000Z

344

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

CMU CO 2 CO 2 e EIO?LCA GHG GWP HVAC IO IPCC kg14 Supply Chain GHG3: Estimated average GHG emission factors for California

Masanet, Eric

2010-01-01T23:59:59.000Z

345

Intra-Household Inequality in Transitional Russia Ekaterina Kalugina  

E-Print Network (OSTI)

1 Intra-Household Inequality in Transitional Russia Ekaterina Kalugina Natalia Radtchenko Catherine and satisfaction. Using two different subjective questions of the Russian data RLMS (Russia Longitudinal Monitoring and social changes in Russia, we investigate the dynamics of household behavior. Keywords: subjective data

Paris-Sud XI, Université de

346

Controlling Households' Drilling Fever in France: an economic modeling approach  

E-Print Network (OSTI)

to generate environmental benefits through reducing water use, has produced economic incentives for households; France; households; domestic boreholes; tube well; water pricing. Author-produced version Fourth World negative environmental impact of water price increase in the drinking water sector. Using primary data

Boyer, Edmond

347

West Texas Intermediate Spot Average ............................  

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

Crude Oil (dollars per barrel) Crude Oil (dollars per barrel) West Texas Intermediate Spot Average ............................ 102.88 93.42 92.24 87.96 94.34 94.10 105.84 96.30 95.67 95.33 95.67 93.33 94.12 97.64 95.00 Brent Spot Average ........................................................... 118.49 108.42 109.61 110.09 112.49 102.58 110.27 108.29 106.33 105.00 103.00 102.00 111.65 108.41 104.08 Imported Average .............................................................. 108.14 101.18 97.18 97.64 98.71 97.39 103.07 100.03 99.64 99.33 99.69 97.35 101.09 99.85 99.04 Refiner Average Acquisition Cost ...................................... 107.61 101.44 97.38 97.27 101.14 99.45 105.24 100.44 100.15 99.82 100.18 97.83 100.83 101.61 99.50 Liquid Fuels (cents per gallon) Refiner Prices for Resale Gasoline .........................................................................

348

Assimilation and differences between the settlement patterns of individual immigrants and immigrant households  

Science Journals Connector (OSTI)

...delineate directions for future household-scale investigations of...Categorization: Individuals or Households? The concentration on the...individual bodies. Of course, household structure and geographic context...children compared with non-Hispanic white children hinge on such...

Mark Ellis; Richard Wright

2005-01-01T23:59:59.000Z

349

Efficient Use of Commercial Lists in U.S. Household Sampling  

Science Journals Connector (OSTI)

......educational attainment, Hispanic ethnicity, household income, and home tenure...on the two persons in the household as well as the Hispanic ethnicity status of the head of household (assuming that the Hispanic ethnicity status of persons......

Richard Valliant; Frost Hubbard; Sunghee Lee; Chiungwen Chang

2014-06-01T23:59:59.000Z

350

A theoretical and simulation-based examination of household vehicle choice through an adoption perspective  

E-Print Network (OSTI)

=2 Senior h =3 Table 17: Japan household income distributionto 2005 Japan Census (millions of households)). CHAPTER 5.same shifts of household dynamics as Japan (i.e. lower birth

Liu, Jenny Hsing-I

2010-01-01T23:59:59.000Z

351

Current Status and Future Scenarios of Residential Building Energy Consumption in China  

E-Print Network (OSTI)

Japan by 2020. Because of their large share in household energyJapan in 2000 which was 4560 kWh/household (IEEJ, 2003). In developed countries, the energy

Zhou, Nan

2010-01-01T23:59:59.000Z

352

Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"  

E-Print Network (OSTI)

Energy Source Demand per Household Coal, Oil, Gas, Heat, Electricity Total Energy Source Demand Coal, Oil, Gas, Heat, Electricity Demography Japan

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

353

"Table HC7.10 Home Appliances Usage Indicators by Household...  

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

0 Home Appliances Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"...

354

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

E-Print Network (OSTI)

of household refrigerators and freezers 2 . Therefore, thesales of the refrigerators and freezers are about 20.6for household refrigerators and freezers has been updated

Lin, Jiang

2006-01-01T23:59:59.000Z

355

Modeling households decisions on reconstruction of houses damaged by earthquakesJapanese case study  

Science Journals Connector (OSTI)

In this study, households decisions on reconstruction of damaged houses were modeled, using questionnaire data in Japan. Characteristics of households decisions were investigated using parameter estimation resu...

H. Sakakibara; H. Murakami; S. Esaki; D. Mori; H. Nakata

2008-02-01T23:59:59.000Z

356

Analysis of household refrigerators for different testing standards  

SciTech Connect

This study highlights the salient differences among various testing standards for household refrigerator-freezers and proposes a methodology for predicting the performance of a single evaporator-based vapor-compression refrigeration system (either refrigerator or freezer) from one test standard (where the test data are available-the reference case) to another (the alternative case). The standards studied during this investigation include the Australian-New Zealand Standard (ANZS), the International Standard (ISO), the American National Standard (ANSI), the Japanese Industrial Standard (JIS), and the Chinese National Standard (CNS). A simple analysis in conjunction with the BICYCLE model (Bansal and Rice 1993) is used to calculate the energy consumption of two refrigerator cabinets from the reference case to the alternative cases. The proposed analysis includes the effect of door openings (as required by the JIS) as well as defrost heaters. The analytical results are found to agree reasonably well with the experimental observations for translating energy consumption information from one standard to another.

Bansal, P.K. [Univ. of Auckland (New Zealand). Dept. of Mechanical Engineering; McGill, I. [Fischer and Paykel Ltd., Auckland (New Zealand)

1995-08-01T23:59:59.000Z

357

Shared Solar Projects Powering Households Throughout America...  

Office of Environmental Management (EM)

with enough rooftop space, the proper roof tilt, and just the right orientation to the Sun had the option to power their homes with solar. The average cost of solar panels has...

358

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

1 1 Type (1) Single-Family: 55.4 106.6 39.4 80.5% Detached 55.0 108.4 39.8 73.9% Attached 60.5 89.3 36.1 6.6% Multi-Family: 78.3 64.1 29.7 14.9% 2 to 4 units 94.3 85.0 35.2 6.3% 5 or more units 69.8 54.4 26.7 8.6% Mobile Homes 74.6 70.4 28.5 4.6% All Housing Types 58.7 95.0 37.0 100% 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 Housing Type

359

Energy efficiency highlights in transformation period and updating of energy policy of Poland up to 2005  

Science Journals Connector (OSTI)

This paper presents some important macroeconomic components characterising the energy economy in Poland during the transition period 1995-2000. Evaluation of primary energy use in Poland has been made in two separate energy flows firstly, energy in the production sector and secondly, energy consumed by households. The comparison of energy productivity in Poland and the EU in 2000 shows 50% of the EU average when GDP is calculated according to the ''ppp'' methodology, and still around three times smaller when Poland's GDP is expressed applying the official exchange rate. Some issues of energy pricing policy during 1997-2000 are discussed, mainly analysis focused on changes of relative prices of energy used in the industrial sector and in households. The comparison shows that relative prices of natural gas and electricity increased by 30% and district heating by 17% during the analysed period. Some developmental challenges to Polish energy policy guidelines focusing on both the newest macroeconomic data and legal aspects of energy law are also discussed briefly. A short energy forecast overview is presented finally.

Zygmunt Parczewski

2003-01-01T23:59:59.000Z

360

Household electricity consumption and CO2 emissions in the Netherlands: A model-based analysis  

Science Journals Connector (OSTI)

Abstract Twenty percent of the total energy consumption in the Netherlands comes from household electricity consumption. This comes from household electric appliances whose number has grown in recent years. The paper explores the effect of smart meter introduction, appliance efficiency and consumer behaviour on reducing electricity consumption in the Netherlands. It does so by combining two perspectives: a sociotechnical approach and a bottom up simulation approach. The range of scenarios explored through simulation in the paper provides an understanding of the interplay between efficiency, smart meter diffusion and consumer behaviour. The results show their effect on electricity consumption and suggest that further effort is required to control and reduce it. Insights from the paper suggest that future studies should disaggregate with respect to a number of factors.

George Papachristos

2015-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

Variable Average Absolute Percent Differences  

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

Variable Variable Average Absolute Percent Differences Percent of Projections Over- Estimated Gross Domestic Product Real Gross Domestic Product (Average Cumulative Growth)* (Table 2) 1.0 42.6 Petroleum Imported Refiner Acquisition Cost of Crude Oil (Constant $) (Table 3a) 35.2 18.6 Imported Refiner Acquisition Cost of Crude Oil (Nominal $) (Table 3b) 34.7 19.7 Total Petroleum Consumption (Table 4) 6.2 66.5 Crude Oil Production (Table 5) 6.0 59.6 Petroleum Net Imports (Table 6) 13.3 67.0 Natural Gas Natural Gas Wellhead Prices (Constant $) (Table 7a) 30.7 26.1 Natural Gas Wellhead Prices (Nominal $) (Table 7b) 30.0 27.1 Total Natural Gas Consumption (Table 8) 7.8 70.2 Natural Gas Production (Table 9) 7.1 66.0 Natural Gas Net Imports (Table 10) 29.3 69.7 Coal Coal Prices to Electric Generating Plants (Constant $)** (Table 11a)

362

Field usage and its impact on energy consumption of refrigerator/freezers  

SciTech Connect

This study investigated the effect of door openings and kitchen environment on the energy consumption of nine household refrigerator/freezers (R/Fs) in the field. The factors under consideration include fresh food and freezer door openings, length of door openings, ambient kitchen temperature, and kitchen relative humidity (RH). Average daily energy consumption for the nine units ranged from 1.7 to 5.3 kWh/day. Energy consumption was found to correlate with kitchen temperature and the number of door openings. No dependence on kitchen relative humidity was found. In general, the magnitude of the door opening component of energy consumption was higher for the more efficient units.

Gage, C.L. [Environmental Protection Agency, Research Triangle Park, NC (United States). Air Pollution Prevention and Control Div.

1995-12-31T23:59:59.000Z

363

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book (EERE)

0 0 Region (1) Northeast 73.5 122.2 47.7 24% New England 77.0 129.4 55.3 7% Middle Atlantic 72.2 119.7 45.3 17% Midwest 58.9 113.5 46.0 28% East North Central 61.1 117.7 47.3 20% West North Central 54.0 104.1 42.9 8% South 51.5 79.8 31.6 31% South Atlantic 47.4 76.1 30.4 16% East South Central 56.6 87.3 36.1 6% West South Central 56.6 82.4 31.4 9% West 56.6 77.4 28.1 18% Mountain 54.4 89.8 33.7 6% Pacific 58.0 71.8 25.7 11% U.S. Average 58.7 94.9 37.0 100% 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.

364

Abstract Interpretation for Worst and Average Case Analysis  

E-Print Network (OSTI)

energy usage whilst bounding the average number of requests waiting to be served. PRISM is used phase extracts a control flow graph ­ for some classes of language this may already involve an abstract

Di Pierro, Alessandra

365

Table 17. Recoverable Coal Reserves and Average Recovery Percentage...  

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

Recoverable Coal Reserves and Average Recovery Percentage at Producing U.S. Mines by Mine Production Range and Mine Type, 2012 (million short tons) U.S. Energy Information...

366

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

367

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

Annual Energy Outlook 2012 (EIA)

in gallons, of this household's storage tank(s)? Enter the capacity for the two largest tanks (if there is more than one) in the boxes below. If the capacity is not known, write...

368

Table 2. Percent of Households with Vehicles, Selected Survey...  

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

or More","NA","NA",93.75,96.42857143,91.27516779,97.46835443 "Race of Householder1" " White",88.61111111,"NA",91.54929577,91.68704156,90.27093596,92.77845777 " Black...

369

Fact #748: October 8, 2012 Components of Household Expenditures...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

but then declined until about 2004 when gasoline and motor oil expenditures began to rise again. The share of household expenditures on gasoline and oil was exactly the same...

370

Householder Symposium on Numerical Linear Algebra June 1721, 2002  

E-Print Network (OSTI)

for discussions. This year's symposium is held at Peebles Hotel Hydro in the small town of Peebles (populationHouseholder Symposium on Numerical Linear Algebra June 17­21, 2002 Peebles Hotel Hydro, Scotland

Higham, Nicholas J.

371

U.S. Department of Energy, Energy Information Administration (EIA  

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

A9 - Average VMT by Income","Table A9. U.S. Average Vehicle-Miles Traveled by Family Income and Poverty Status, 2001 A9 - Average VMT by Income","Table A9. U.S. Average Vehicle-Miles Traveled by Family Income and Poverty Status, 2001 (Thousand Miles per Household)" "Std Errors for A9","Relative Standard Errors for Table A9. U.S. Average Vehicle-Miles Traveled by Family Income and Poverty Status, 2001 (Percent)" "N Cells for A9","Number of Sample Cases Contributing to Estimates in Table A9. U.S. Average Vehicle-Miles Traveled by Family Income and Poverty Status, 2001" " Page A-1 of A-N" "Table A9. U.S. Average Vehicle-Miles Traveled by Family Income and Poverty Status, 2001 (Thousand Miles per Household)" "2001 Household Characteristics","Total","2001 Family Income",,,,,,,,,,"Income Relative to Poverty Line"

372

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

efficiencymeasuresapplicabletohomeenergy, commercialsectorelectricityandnaturalgas,industrial

Masanet, Eric

2010-01-01T23:59:59.000Z

373

Residential Energy-Efficient Technology Adoption, Energy Conservation, Knowledge, and Attitudes: An Analysis of European Countries  

E-Print Network (OSTI)

,000 households in ten EU countries and Norway. Knowledge of energy consumption and energy-efficient technology1 Residential Energy-Efficient Technology Adoption, Energy Conservation, Knowledge, and Attitudes of measures of household energy use behavior are estimated using a unique dataset of approximately 5

Paris-Sud XI, Université de

374

Energy and Greenhouse Gas Emissions in China: Growth, Transition, and Institutional Change  

E-Print Network (OSTI)

was for 15% of total primary energy consumption to come fromis on domestic primary energy consumption, for most of thisdoes not include primary energy consumption by households

Kahrl, Fredrich James

2011-01-01T23:59:59.000Z

375

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

376

Innovative System and Method for Monitoring Energy Efficiency in Buildings  

Science Journals Connector (OSTI)

Improving energy efficiency (EE) in buildings may significantly reduce...@lisee, for achieving energy efficiency in buildings (households, officies, campus, data centers, etc. ... devices, locally estimating indo...

Grazia Fattoruso; Saverio De Vito; Ciro Di Palma; Girolamo Di Francia

2014-01-01T23:59:59.000Z

377

Report: An Updated Annual Energy Outlook 2009 Reference Case...  

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

666,1876.378052,1886.589233,1896.617065,1906.307617,1915.627686,1924.664062,1933.551636 " Energy Intensity" " (million Btu per household)" " Delivered Energy Consumption",95.737358...

378

Report: An Updated Annual Energy Outlook 2009 Reference Case...  

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

086,1876.765991,1887.016235,1897.062622,1906.736938,1916.007446,1924.966064,1933.756714 " Energy Intensity" " (million Btu per household)" " Delivered Energy Consumption",95.737365...

379

Year Average Transportation Cost of Coal  

Gasoline and Diesel Fuel Update (EIA)

delivered costs of coal, by year and primary transport mode Year Average Transportation Cost of Coal (Dollars per Ton) Average Delivered Cost of Coal (Dollars per Ton)...

380

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

DOE)(2008b). IndustrialAssessmentCentersDatabase. ofEnergysIndustrialAssessmentCenter(IAC) database(

Masanet, Eric

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

Increased energy prices: energy savings and equity aspects. Final report  

SciTech Connect

A mathematical model has been developed which approximates the reduction in a household's total energy consumption in response to higher energy prices and different rebate schemes. This model is based on the assumption that energy consumption is a function of a household's real income, prices of different commodities and energy intensities. The amount of energy saved and the change in real expenditure of a household has been calculated for four tax rates; 50%, 100%, 224% and 400%, and five rebate schemes; one regressive, two progressive, one income distribution preserving and the flat per capita rebate. The results indicate that, for a given tax rate, the choice of rebate scheme does not significantly affect the amount of energy conserved by the households. However, the effect of different rebate schemes on a household's real expenditure could be dramatically different.

Herendeen, R.A.

1983-06-01T23:59:59.000Z

382

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis -- A Reflexively Designed Survey of New-Car-Buying Multi-Vehicle California Households  

E-Print Network (OSTI)

EV,then we expect 13.3 to 15.2% of all light-duty vehicle sales,EV marketpotential for smaller and shorter range velucles represented by our sampleis about 7%of annual, newhght duty vehicle sales.EV body styles" EVs ICEVs Total PAGE 66 THE HOUSEHOLD MA RKET FOR ELECTRIC VEHICLES percent mandatein the year 2003will dependon sales

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

383

Lincoln Electric System (Residential)- Sustainable Energy Program  

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

Lincoln Electric System (LES) offers several rebates to residential customers who are interested in upgrading to energy efficient household equipment. The program includes rebates for insulation...

384

LEDSGP/benefits | Open Energy Information  

Open Energy Info (EERE)

Topics include Housing, Urban Transport, Household Energy in Developing Countries, Health-Care Facilities, and Occupational Health. Health Indicators for Sustainable...

385

Placing barriers to industrial energy efficiency in a social context: a discussion of lifestyle categorisation  

Science Journals Connector (OSTI)

This paper compares how analyses of energy use and efficiency have developed in households and industrial small- and medium-sized enterprises ... earlier studies that use lifestyle categories in examining household

Jenny Palm

2009-08-01T23:59:59.000Z

386

The effects of energy efficiency and environmental labels on appliance choice in SouthKorea  

Science Journals Connector (OSTI)

This paper investigates the effects of energy efficiency and environmental labels on households choice of appliances, using a discrete ... on appliance choice. This paper found that households showed a positive ...

Gicheol Jeong; Yeunjoong Kim

2014-10-01T23:59:59.000Z

387

Average deployments versus missile and defender parameters  

SciTech Connect

This report evaluates the average number of reentry vehicles (RVs) that could be deployed successfully as a function of missile burn time, RV deployment times, and the number of space-based interceptors (SBIs) in defensive constellations. Leakage estimates of boost-phase kinetic-energy defenses as functions of launch parameters and defensive constellation size agree with integral predictions of near-exact calculations for constellation sizing. The calculations discussed here test more detailed aspects of the interaction. They indicate that SBIs can efficiently remove about 50% of the RVs from a heavy missile attack. The next 30% can removed with two-fold less effectiveness. The next 10% could double constellation sizes. 5 refs., 7 figs.

Canavan, G.H.

1991-03-01T23:59:59.000Z

388

Buildings Energy Data Book: 2.6 Residential Home Improvement  

Buildings Energy Data Book (EERE)

7 7 2009 Home Improvement Spending by Household Income ($2010) Income Under $40,000 $40-79,999 $80-119,999 120,000 and Over Note(s): Source(s): 13,005 4,097 16,531 67,731 Home improvements include room additions, remodeling, replacements of household systems and appliances, porches and garages, additions and replacements of roofing, siding, window/doors, insulation, flooring/paneling/ceiling, and disaster repairs. Joint Center for Housing Studies of Harvard University, A New Decade of Growth for Remodeling, 2011, Table A-3, pg. 29; EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for GDP and price deflators. 23,178 6,545 6,841 44,772 14,051 4,299 9,189 39,505 (thousand) (thousand) ($) ($million) 24,675 6,113 5,697 34,825 Number of Homeowners Average Total Homeowners

389

Advances in Household Appliances- A Review  

SciTech Connect

An overview of options and potential barriers and risks for reducing the energy consumption, peak demand, and emissions for seven key energy consuming residential products (refrigerator-freezers, dishwashers, clothes washers, clothes dryers, electric ovens, gas ovens and microwave ovens) is presented. The paper primarily concentrates on the potential energy savings from the use of advanced technologies in appliances for the U.S. market. The significance and usefulness of each technology was evaluated in order to prioritize the R&D needs to improve energy efficiency of appliances in view of energy savings, cost, and complexity. The paper provides a snapshot of the future R&D needs for each of the technologies along with the associated barriers. Although significant energy savings may be achieved, one of the major barriers in most cases is high first cost. One way of addressing this issue and promoting the introduction of new technologies is to level the playing field for all manufacturers by establishing Minimum Energy Performance Standards (MEPS) which are not cost prohibitive and promoting energy efficient products through incentives to both manufacturers and consumers.

Bansal, Pradeep [ORNL; Vineyard, Edward Allan [ORNL; Abdelaziz, Omar [ORNL

2011-01-01T23:59:59.000Z

390

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

392

Comparison of Test Procedures and Energy Efficiency Criteria in Selected International Standards and Labeling Programs for Clothes Washers, Water Dispensers, Vending Machines and CFLs  

E-Print Network (OSTI)

energy labels for household clothes washers include the United States, Canada, Korea, the European Union, Australia and New Zealand, Japan,

Fridley, David

2010-01-01T23:59:59.000Z

393

Determinations and Coverage Rulemakings | Department of Energy  

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

Determinations and Coverage Rulemakings Determinations and Coverage Rulemakings Determinations and Coverage Rulemakings The Energy Policy and Conservation Act (EPCA) (42 U.S.C. 6292(a)) contains a list of 19 consumer products that are considered covered products for which the Secretary of Energy is authorized to establish energy conservation standards. EPCA (42 U.S.C. 6292(a)(20) also allows the Department of Energy (DOE) to classify other types of consumer products as covered products if the DOE determines that: Classifying the products as covered products is necessary or appropriate to carry out the purposes of EPCA; and The average annual per-household energy use by products of such type is likely to exceed 100 kWh per year. (42 U.S.C 6292(b)(1)). (For commercial and industrial equipment, see 42 U.S.C. 6311-6312).

394

Solar: monthly and annual average direct normal (DNI), global horizontal  

Open Energy Info (EERE)

East Asia from NREL East Asia from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

395

Solar: monthly and annual average direct normal (DNI), global horizontal  

Open Energy Info (EERE)

Africa from NREL Africa from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

396

An exploratory study of Spanish households' WEEE disposal behaviour  

Science Journals Connector (OSTI)

This paper presents the findings of an exploratory study based on a survey of 1,537 households in Spain. The questionnaire included 23 key questions regarding the number of appliances in use, previous appliances lifetimes, reasons for buying each new appliance and end-of-life handling of discarded appliances. The distribution of the households along a number of relevant factors was analysed and a prototypical household was identified. A non-parametric analysis of the duration of each type of appliance has also been carried out and it was found that television sets are the most durable of the appliances considered. Survival rates for irons fall more rapidly than for microwaves. Moreover, television sets are the most durable of the appliances considered. Replacement rates of personal computers rapidly increase after approximately six to eight years. Finally, a statistical analysis of the respondents motivations for recycling the appliances considered in this study was carried out.

Ester Gutiérrez; Belarmino Adenso-Díaz; Sebastián Lozano; Plácido Moreno

2011-01-01T23:59:59.000Z

397

Table 2. Percent of Households with Vehicles, Selected Survey Years  

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

Percent of Households with Vehicles, Selected Survey Years " Percent of Households with Vehicles, Selected Survey Years " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",85.5450237,89.00343643,88.75545852,89.42917548,87.25590956,92.08566108 "Household Characteristics" "Census Region and Division" " Northeast",77.22222222,"NA",79.16666667,82.9015544,75.38461538,85.09615385 " New England",88.37209302,"NA",81.81818182,82.9787234,82,88.52459016 " Middle Atlantic ",73.72262774,"NA",78.37837838,82.31292517,74.30555556,83.67346939 " Midwest ",85.51401869,"NA",90.66666667,90.17094017,92.30769231,91.47286822 " East North Central",82,"NA",88.81987578,89.88095238,91.51515152,90.55555556

398

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

most non-Weatherization Assistance Program (WAP) energythe federal Weatherization Assistance Program may have thefrom the Weatherization Assistance Program (WAP) due to the

Zimring, Mark

2014-01-01T23:59:59.000Z

399

Modelling the Energy Demand of Households in a Combined  

E-Print Network (OSTI)

by the European Emissions Trading System (EU ETS) the many drivers and partly mobile emissions sources

Steininger, Karl W.

400

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

system CFL Compact Fluorescent Light Bulb IAQ Indoor Airdiscount compact fluorescent light bulbs (CFLs) or providediscount compact fluorescent light bulbs (CFLs) or provide

Zimring, Mark

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

annual average heating degree days | OpenEI  

Open Energy Info (EERE)

average heating degree days average heating degree days Dataset Summary Description (Abstract): Heating Degree Days below 18° C (degree days)The monthly accumulation of degrees when the daily mean temperature is below 18° C.NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly Average & Annual Sum (July 1983 - June 2005)Parameter: Heating Degree Days Below 18 degrees C (degree days)Internet: http://eosweb.larc.nasa.gov/sse/ Source U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE) Date Released March 31st, 2009 (5 years ago) Date Updated April 01st, 2009 (5 years ago) Keywords annual average heating degree days climate GIS NASA SWERA UNEP Data application/zip icon Download Shapefile (zip, 2.7 MiB)

402

Greenhouse gas emissions from home composting of organic household waste  

SciTech Connect

The emission of greenhouse gases (GHGs) is a potential environmental disadvantage of home composting. Because of a lack of reliable GHG emission data, a comprehensive experimental home composting system was set up. The system consisted of six composting units, and a static flux chamber method was used to measure and quantify the GHG emissions for one year composting of organic household waste (OHW). The average OHW input in the six composting units was 2.6-3.5 kg week{sup -1} and the temperature inside the composting units was in all cases only a few degrees (2-10 {sup o}C) higher than the ambient temperature. The emissions of methane (CH{sub 4}) and nitrous oxide (N{sub 2}O) were quantified as 0.4-4.2 kg CH{sub 4} Mg{sup -1} input wet waste (ww) and 0.30-0.55 kg N{sub 2}O Mg{sup -1} ww, depending on the mixing frequency. This corresponds to emission factors (EFs) (including only CH{sub 4} and N{sub 2}O emissions) of 100-239 kg CO{sub 2}-eq. Mg{sup -1} ww. Composting units exposed to weekly mixing had the highest EFs, whereas the units with no mixing during the entire year had the lowest emissions. In addition to the higher emission from the frequently mixed units, there was also an instant release of CH{sub 4} during mixing which was estimated to 8-12% of the total CH{sub 4} emissions. Experiments with higher loads of OHW (up to 20 kg every fortnight) entailed a higher emission and significantly increased overall EFs (in kg substance per Mg{sup -1} ww). However, the temperature development did not change significantly. The GHG emissions (in kg CO{sub 2}-eq. Mg{sup -1} ww) from home composting of OHW were found to be in the same order of magnitude as for centralised composting plants.

Andersen, J.K., E-mail: jka@env.dtu.d [Department of Environmental Engineering, Technical University of Denmark, DK-2800, Kongens Lyngby (Denmark); Boldrin, A.; Christensen, T.H.; Scheutz, C. [Department of Environmental Engineering, Technical University of Denmark, DK-2800, Kongens Lyngby (Denmark)

2010-12-15T23:59:59.000Z

403

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module 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. Key Assumptions The historical input data used to develop the HEM version for the AEO2003 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 AEO2003 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).

404

Household solid waste characteristics and management in Chittagong, Bangladesh  

SciTech Connect

Solid waste management (SWM) is a multidimensional challenge faced by urban authorities, especially in developing countries like Bangladesh. We investigated per capita waste generation by residents, its composition, and the households' attitudes towards waste management at Rahman Nagar Residential Area, Chittagong, Bangladesh. The study involved a structured questionnaire and encompassed 75 households from five different socioeconomic groups (SEGs): low (LSEG), lower middle (LMSEG), middle (MSEG), upper middle (UMSEG) and high (HSEG). Wastes, collected from all of the groups of households, were segregated and weighed. Waste generation was 1.3 kg/household/day and 0.25 kg/person/day. Household solid waste (HSW) was comprised of nine categories of wastes with vegetable/food waste being the largest component (62%). Vegetable/food waste generation increased from the HSEG (47%) to the LSEG (88%). By weight, 66% of the waste was compostable in nature. The generation of HSW was positively correlated with family size (r{sub xy} = 0.236, p < 0.05), education level (r{sub xy} = 0.244, p < 0.05) and monthly income (r{sub xy} = 0.671, p < 0.01) of the households. Municipal authorities are usually the responsible agencies for solid waste collection and disposal, but the magnitude of the problem is well beyond the ability of any municipal government to tackle. Hence dwellers were found to take the service from the local waste management initiative. Of the respondents, an impressive 44% were willing to pay US$0.3 to US$0.4 per month to waste collectors and it is recommended that service charge be based on the volume of waste generated by households. Almost a quarter (22.7%) of the respondents preferred 12-1 pm as the time period for their waste to be collected. This study adequately shows that household solid waste can be converted from burden to resource through segregation at the source, since people are aware of their role in this direction provided a mechanism to assist them in this pursuit exists and the burden is distributed according to the amount of waste generated.

Sujauddin, Mohammad [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh)], E-mail: mohammad.sujauddin@gmail.com; Huda, S.M.S. [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh); Hoque, A.T.M. Rafiqul [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh); Laboratory of Ecology and Systematics (Plant Ecophysiology Section), Faculty of Science, Biology Division, University of the Ryukyus, Okinawa 903-0213 (Japan)

2008-07-01T23:59:59.000Z

405

Saving Money on Your Energy-Saving Upgrades | Department of Energy  

Energy Savers (EERE)

of the energy-saving household investments that qualify include high-efficiency central air conditioners, heat pumps, furnaces, and boilers that meet the standards listed on the...

406

WEEE and portable batteries in residual household waste: Quantification and characterisation of misplaced waste  

SciTech Connect

Highlights: We analyse 26.1 Mg of residual waste from 3129 Danish households. We quantify and characterise misplaced WEEE and portable batteries. We compare misplaced WEEE and batteries to collection through dedicated schemes. Characterisation showed that primarily small WEEE and light sources are misplaced. Significant amounts of misplaced batteries were discarded as built-in WEEE. - Abstract: A total of 26.1 Mg of residual waste from 3129 households in 12 Danish municipalities was analysed and revealed that 89.6 kg of Waste Electrical and Electronic Equipment (WEEE), 11 kg of batteries, 2.2 kg of toners and 16 kg of cables had been wrongfully discarded. This corresponds to a Danish household discarding 29 g of WEEE (7 items per year), 4 g of batteries (9 batteries per year), 1 g of toners and 7 g of unidentifiable cables on average per week, constituting 0.34% (w/w), 0.04% (w/w), 0.01% (w/w) and 0.09% (w/w), respectively, of residual waste. The study also found that misplaced WEEE and batteries in the residual waste constituted 16% and 39%, respectively, of what is being collected properly through the dedicated special waste collection schemes. This shows that a large amount of batteries are being discarded with the residual waste, whereas WEEE seems to be collected relatively successfully through the dedicated special waste collection schemes. Characterisation of the misplaced batteries showed that 20% (w/w) of the discarded batteries were discarded as part of WEEE (built-in). Primarily alkaline batteries, carbon zinc batteries and alkaline button cell batteries were found to be discarded with the residual household waste. Characterisation of WEEE showed that primarily small WEEE (WEEE directive categories 2, 5a, 6, 7 and 9) and light sources (WEEE directive category 5b) were misplaced. Electric tooth brushes, watches, clocks, headphones, flashlights, bicycle lights, and cables were items most frequently found. It is recommended that these findings are taken into account when designing new or improving existing special waste collection schemes. Improving the collection of WEEE is also recommended as one way to also improve the collection of batteries due to the large fraction of batteries found as built-in. The findings in this study were comparable to other western European studies, suggesting that the recommendations made in this study could apply to other western European countries as well.

Bigum, Marianne, E-mail: mkkb@env.dtu.dk [Technical University of Denmark, Department of Environmental Engineering, Miljvej 113, 2500 Kgs. Lyngby (Denmark); Petersen, Claus, E-mail: claus_petersen@econet.dk [Econet A/S, Strandboulevarden 122, 5, 2100 Kbenhavn (Denmark); Christensen, Thomas H., E-mail: thho@env.dtu.dk [Technical University of Denmark, Department of Environmental Engineering, Miljvej 113, 2500 Kgs. Lyngby (Denmark); Scheutz, Charlotte, E-mail: chas@env.dtu.dk [Technical University of Denmark, Department of Environmental Engineering, Miljvej 113, 2500 Kgs. Lyngby (Denmark)

2013-11-15T23:59:59.000Z

407

U.S. Department of Energy, Energy Information Administration (EIA  

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

A10 - Avg Consumption by Income","Table A10. U.S. Average Vehicle Fuel Consumption by Family Income and Poverty Status, 2001 A10 - Avg Consumption by Income","Table A10. U.S. Average Vehicle Fuel Consumption by Family Income and Poverty Status, 2001 (Gallons per Household) " "Std Errors for A10","Relative Standard Errors for Table A10. U.S. Average Vehicle Fuel Consumption by Family Income and Poverty Status, 2001 (Percent)" "N Cells for A10","Number of Sample Cases Contributing to Estimates in Table A10. U.S. Average Vehicle Fuel Consumption by Family Income and Poverty Status, 2001" " Page A-1 of A-N" "Table A10. U.S. Average Vehicle Fuel Consumption by Family Income and Poverty Status, 2001 (Gallons per Household) " "2001 Household Characteristics","Total","2001 Family Income",,,,,,,,,,"Income Relative to Poverty Line"

408

Estimating the environmental impact of home energy visits and extent of behaviour change  

Science Journals Connector (OSTI)

Abstract The objective of this study was to estimate the environmental impact of a home energy visit programme, known as RE:NEW, that was delivered in London, in the United Kingdom. These home energy visits intended to encourage reductions in household carbon emissions and water consumption through the installation of small energy saving measures (such as radiator panels, in-home energy displays and low-flow shower heads), further significant energy saving measures (loft and cavity wall insulation) and behaviour change advice. The environmental impact of the programme was estimated in terms of carbon emissions abated and on average, for each household in the study, a visit led to an average carbon abatement of 146kgCO2. The majority of this was achieved through the installation of small energy saving measures. The impact of the visits on the installation of significant measures was negligible, as was the impact on behaviour change. Therefore, these visits did not overcome the barriers required to generate behaviour change or the barriers to the installation of more significant energy saving measures. Given this, a number of recommendations are proposed in this paper, which could increase the efficacy of these home energy visits.

Kristy Revell

2014-01-01T23:59:59.000Z

409

Status of not-in-kind refrigeration technologies for household space conditioning, water heating and food refrigeration  

SciTech Connect

This paper presents a review of the next generation not-in-kind technologies to replace conventional vapor compression refrigeration technology for household applications. Such technologies are sought to provide energy savings or other environmental benefits for space conditioning, water heating and refrigeration for domestic use. These alternative technologies include: thermoacoustic refrigeration, thermoelectric refrigeration, thermotunneling, magnetic refrigeration, Stirling cycle refrigeration, pulse tube refrigeration, Malone cycle refrigeration, absorption refrigeration, adsorption refrigeration, and compressor driven metal hydride heat pumps. Furthermore, heat pump water heating and integrated heat pump systems are also discussed due to their significant energy saving potential for water heating and space conditioning in households. The paper provides a snapshot of the future R&D needs for each of the technologies along with the associated barriers. Both thermoelectric and magnetic technologies look relatively attractive due to recent developments in the materials and prototypes being manufactured.

Bansal, Pradeep [ORNL; Vineyard, Edward Allan [ORNL; Abdelaziz, Omar [ORNL

2012-01-01T23:59:59.000Z

410

Minority energy assessment report  

SciTech Connect

The purpose of this research is to project household energy consumption, energy expenditure, and energy expenditure as share of income for five population groups from 1991 to 2009. The approach uses the Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory for the US Department of Energy's Office of Minority Economic Impact. The MEAM provides a framework that can be used to forecast regional energy consumption and energy expenditure for majority, black, Hispanic, poor, and nonpoor households. The forecasts of key macroeconomic and energy variables used as exogenous variables in the MEAM were obtained from the Data Resources, Inc., Macromodel and Energy Model. Generally, the projections of household energy consumption, expenditure, and energy expenditure as share of income vary across population groups and census regions.

Teotia, A.P.S.; Poyer, D.A.; Lampley, L.; Anderson, J.L.

1992-12-01T23:59:59.000Z

411

Stay Warm and Save Money This Winter with Tips from the Energy Department |  

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

Stay Warm and Save Money This Winter with Tips from the Energy Stay Warm and Save Money This Winter with Tips from the Energy Department Stay Warm and Save Money This Winter with Tips from the Energy Department December 19, 2011 - 1:24pm Addthis Department of Energy headquarters during the winter months. | DOE file photo. Department of Energy headquarters during the winter months. | DOE file photo. What does this mean for me? Help your family save money by saving energy with these tips this winter. Click "start now" on Benefits.gov to find out if you're eligible for government assistance, including energy-related costs. Editor's note: This article was originally posted on Benefits.gov. As the days get shorter and temperatures get cooler, those energy bills seem to just keep going up. The average American spends around $2,000 per household on energy costs

412

Stay Warm and Save Money This Winter with Tips from the Energy Department |  

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

Stay Warm and Save Money This Winter with Tips from the Energy Stay Warm and Save Money This Winter with Tips from the Energy Department Stay Warm and Save Money This Winter with Tips from the Energy Department December 19, 2011 - 1:24pm Addthis Department of Energy headquarters during the winter months. | DOE file photo. Department of Energy headquarters during the winter months. | DOE file photo. What does this mean for me? Help your family save money by saving energy with these tips this winter. Click "start now" on Benefits.gov to find out if you're eligible for government assistance, including energy-related costs. Editor's note: This article was originally posted on Benefits.gov. As the days get shorter and temperatures get cooler, those energy bills seem to just keep going up. The average American spends around $2,000 per household on energy costs

413

Household Segmentation in Food Insecurity and Soil Improving Practices in Ghana  

E-Print Network (OSTI)

secure household, and households farming medium quality soil increase the probability of adopting soil improving practices. Application of chemical fertilizers, commercial seeds, and pesticides, along with operating under a seasonal lease tenure...

Nata, Jifar T

2013-08-09T23:59:59.000Z

414

Logistic regression models for predicting trip reporting accuracy in GPS-enhanced household travel surveys  

E-Print Network (OSTI)

This thesis presents a methodology for conducting logistic regression modeling of trip and household information obtained from household travel surveys and vehicle trip information obtained from global positioning systems (GPS) to better understand...

Forrest, Timothy Lee

2007-04-25T23:59:59.000Z

415

Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles  

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

Household vehicle ownership has changed over the last six decades. In 1960, over twenty percent of households did not own a vehicle, but by 2010, that number fell to less than 10%. The number of...

416

Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles  

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

When a household has more than one vehicle, the secondary vehicles travel fewer miles than the primary vehicle. In a two-vehicle household, the second vehicle travels less than half of the miles...

417

A Comparison of Household Budget Allocation Patterns Between Hispanic Americans and Non-Hispanic White Americans  

Science Journals Connector (OSTI)

The budget allocation patterns of Hispanic versus non-Hispanic White households are examined. Annual household expenditure data from 1980 to 1992 are ... Index (1990). The sample includes 588 Hispanic and 8,444 n...

Jessie X. Fan; Virginia Solis Zuiker

1998-06-01T23:59:59.000Z

418

The household production function approach to valuing climate: the case of Japan  

Science Journals Connector (OSTI)

In fact ours is not the first attempt to use the household production function technique empirically to estimate the ... climate and the impact of climate change on households. But our analysis uses repeated cros...

David Maddison; Katrin Rehdanz; Daiju Narita

2013-01-01T23:59:59.000Z

419

Averaged dynamics of ultra-relativisitc charged particles beams  

E-Print Network (OSTI)

In this thesis, we consider the suitability of using the charged cold fluid model in the description of ultra-relativistic beams. The method that we have used is the following. Firstly, the necessary notions of kinetic theory and differential geometry of second order differential equations are explained. Then an averaging procedure is applied to a connection associated with the Lorentz force equation. The result of this averaging is an affine connection on the space-time manifold. The corresponding geodesic equation defines the averaged Lorentz force equation. We prove that for ultra-relativistic beams described by narrow distribution functions, the solutions of both equations are similar. This fact justifies the replacement of the Lorentz force equation by the simpler {\\it averaged Lorentz force equation}. After this, for each of these models we associate the corresponding kinetic model, which are based on the Vlasov equation and {\\it averaged Vlasov equation} respectively. The averaged Vlasov equation is simpler than the original Vlasov equation. This fact allows us to prove that the differential operation defining the averaged charged cold fluid equation is controlled by the {\\it diameter of the distribution function}, by powers of the {\\it energy of the beam} and by the time of evolution $t$. We show that the Vlasov equation and the averaged Vlasov equation have similar solutions, when the initial conditions are the same. Finally, as an application of the {\\it averaged Lorentz force equation} we re-derive the beam dynamics formalism used in accelerator physics from the Jacobi equation of the averaged Lorentz force equation.

Ricardo Gallego Torrom

2012-06-19T23:59:59.000Z

420

Frequency and longitudinal trends of household care product use Rebecca E. Moran a  

E-Print Network (OSTI)

SUPERB Indoor environment d-limonene a b s t r a c t The use of household cleaning products and air, frequencies of use of eight types of household cleaning products and air fresheners and the performance. Introduction Household care products, such as cleaning products and air fresheners, are frequently used

Leistikow, Bruce N.

Note: This page contains sample records for the topic "average household energy" 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

ROBUSTNESS OF ISS SYSTEMS TO INPUTS WITH LIMITED MOVING AVERAGE, WITH APPLICATION TO SPACECRAFT  

E-Print Network (OSTI)

. Cybernetics, O. S. Bragstads plass 2D, NTNU, 7491 Trondheim, NORWAY bUniv. Paris Sud 11 - L2S - EECI - Sup to a class of signals with bounded average-energy, which encompasses the typical disturbances acting on space, energy, average energy, etc.) are typ- ically available. These perturbing signals may have diverse

Boyer, Edmond

422

Potential of Drastic Improvement of Energy Efficiency in Japan  

Science Journals Connector (OSTI)

Introduction of effective policy measures to improve energy efficiency not only for industry sector but for household and commercial sector etc. should be explored...

Seiji Ikkatai; Haruki Tsuchiya

2012-01-01T23:59:59.000Z

423

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...

424

An Analysis of the Price Elasticity of Demand for Household Appliances  

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

Analysis of the Price Elasticity of Demand for Analysis of the Price Elasticity of Demand for Household Appliances Larry Dale and K. Sydny Fujita February 2008 Energy Analysis Department Environmental Energy Technologies Division Lawrence Berkeley National Laboratory University of California Berkeley, CA 94720 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not

425

EREV and BEV Economic Viability vs. Household Retail Electric Pricing Strategies: Two Charges a Day?  

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

EREV and BEV Economic Viability vs. EREV and BEV Economic Viability vs. Household Retail Electric Pricing Strategies: Two Charges a Day? By Dan Santini Argonne National Laboratory dsantini@anl.gov Remarks are attributable only to the author; not to Argonne or U.S. Department of Energy NAATBatt Conference: The Impact of PEVs on T&D Systems: Challenges and Solutions Dec. 7, 2010 The submitted manuscript has been created by Argonne National Laboratory, a U.S. Department of Energy laboratory managed by UChicago Argonne, LLC, under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up, nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly,

426

Residential Clean Energy Grant Program | Department of Energy  

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

Residential Clean Energy Grant Program Residential Clean Energy Grant Program Residential Clean Energy Grant Program < Back Eligibility Residential Savings Category Solar Buying & Making Electricity Heating & Cooling Water Heating Maximum Rebate PV: $1,000 (flat per installation/household incentive) SWH: $500 (flat per installation/household incentive) Program Info Funding Source Strategic Energy Investment Fund (SEIF) Start Date 01/01/2005 Expiration Date When funds are exhausted; annual budget subject to appropriation State Maryland Program Type State Rebate Program Rebate Amount PV: $1,000 (flat per installation/household incentive) SWH: $500 (flat per installation/household incentive) Provider Maryland Energy Administration Maryland's Residential Clean Energy Grant Program, administered by the

427

Solar: monthly and annual average direct normal (DNI), global horizontal  

Open Energy Info (EERE)

South America from NREL South America from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

428

Solar: monthly and annual average direct normal (DNI), global horizontal  

Open Energy Info (EERE)

Central America and the Carribean from NREL Central America and the Carribean from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

429

Recovery and separation of high-value plastics from discarded household appliances  

SciTech Connect

Argonne National Laboratory is conducting research to develop a cost- effective and environmentally acceptable process for the separation of high-value plastics from discarded household appliances. The process under development has separated individual high purity (greater than 99.5%) acrylonitrile-butadiene-styrene (ABS) and high- impact polystyrene (HIPS) from commingled plastics generated by appliance-shredding and metal-recovery operations. The process consists of size-reduction steps for the commingled plastics, followed by a series of gravity-separation techniques to separate plastic materials of different densities. Individual plastics of similar densities, such as ABS and HIPS, are further separated by using a chemical solution. By controlling the surface tension, the density, and the temperature of the chemical solution we are able to selectively float/separate plastics that have different surface energies. This separation technique has proven to be highly effective in recovering high-purity plastics materials from discarded household appliances. A conceptual design of a continuous process to recover high-value plastics from discarded appliances is also discussed. In addition to plastics separation research, Argonne National Laboratory is conducting research to develop cost-effective techniques for improving the mechanical properties of plastics recovered from appliances.

Karvelas, D.E.; Jody, B.J.; Poykala, J.A. Jr.; Daniels, E.J. [Argonne National Lab., IL (United States). Energy Systems Div.; Arman, B. [Argonne National Lab., IL (United States). Energy Systems Div.]|[Praxair, Inc., Tarrytown, NY (United States)

1996-03-01T23:59:59.000Z

430

A multivariate analysis of the energy intensity of sprawl versus compact living in the U.S. for 2003  

E-Print Network (OSTI)

Household energy consumption Sprawl Compact living Energy impact We explore the energy intensity of sprawl versus compact living by analyzing the total energy requirements of U.S. households for the year 2003. The methods used are based on previous studies on energy cost of living. Total energy requirement

Vermont, University of

431

Long-term behaviour of baled household waste  

Science Journals Connector (OSTI)

This study was carried out at the laboratory scale (approximately 15 l) and using real baled waste of industrial dimensions (about 1 m3), in order to assess the long-term behaviour of baled household waste. The laboratory assays were carried out with real household waste which was fractioned on site, reconstituted in the laboratory and then compacted into 15 l airtight containers (unless stated otherwise). These containers were incubated under different experimental conditions at a constant temperature (28C). Three assays were conducted over 34 months and two others over 27 months. For the assays incubated in conditions simulating those of real baled waste (confined medium, with no aeration or water flow), a very low microbial activity was observed. The assay incubated in the same conditions but with slight aeration during the first three months in order to simulate imperfectly airtight wrapping, revealed biodegradation which started in a significant manner after 800 days of incubation. The evolution of two real wrapped bales each containing 900 kg of household waste was monitored over 8 months. These bales were produced industrially, one in July 97 and the other in July 98 at the incinerator plant at Agde (France). The bales were then stored outside at the laboratory location and their evolution was monitored mainly by biogas analysis and temperature measurement. No methane formation was observed, revealing the absence of anaerobic biodegradation, thus confirming the laboratory assays.

Fabian Robles-Mart??nez; Rmy Gourdon

2000-01-01T23:59:59.000Z

432

Regional averaging and scaling in relativistic cosmology  

E-Print Network (OSTI)

Averaged inhomogeneous cosmologies lie at the forefront of interest, since cosmological parameters like the rate of expansion or the mass density are to be considered as volume-averaged quantities and only these can be compared with observations. For this reason the relevant parameters are intrinsically scale-dependent and one wishes to control this dependence without restricting the cosmological model by unphysical assumptions. In the latter respect we contrast our way to approach the averaging problem in relativistic cosmology with shortcomings of averaged Newtonian models. Explicitly, we investigate the scale-dependence of Eulerian volume averages of scalar functions on Riemannian three-manifolds. We propose a complementary view of a Lagrangian smoothing of (tensorial) variables as opposed to their Eulerian averaging on spatial domains. This program is realized with the help of a global Ricci deformation flow for the metric. We explain rigorously the origin of the Ricci flow which, on heuristic grounds, has already been suggested as a possible candidate for smoothing the initial data set for cosmological spacetimes. The smoothing of geometry implies a renormalization of averaged spatial variables. We discuss the results in terms of effective cosmological parameters that would be assigned to the smoothed cosmological spacetime.

Thomas Buchert; Mauro Carfora

2002-10-11T23:59:59.000Z

433

Smart Power Laboratory (Fact Sheet), NREL (National Renewable Energy Laboratory), Energy Systems Integration Facility (ESIF)  

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

Testing of advanced appliances, home automation, Testing of advanced appliances, home automation, HVAC, and energy management systems * Research on various new distribution scenarios such as household DC systems, Residential scale generation and storage integrated with the home energy managements systems * Electric vehicle integration * Hardware-in-the-loop modeling for the characterization of household loads and generation

434

Commercial viability of hybrid vehicles : best household use and cross national considerations.  

SciTech Connect

Japanese automakers have introduced hybrid passenger cars in Japan and will soon do so in the US. In this paper, we report how we used early computer simulation model results to compare the commercial viability of a hypothetical near-term (next decade) hybrid mid-size passenger car configuration under varying fuel price and driving patterns. The fuel prices and driving patterns evaluated are designed to span likely values for major OECD nations. Two types of models are used. One allows the ''design'' of a hybrid to a specified set of performance requirements and the prediction of fuel economy under a number of possible driving patterns (called driving cycles). Another provides an estimate of the incremental cost of the hybrid in comparison to a comparably performing conventional vehicle. In this paper, the models are applied to predict the NPV cost of conventional gasoline-fueled vehicles vs. parallel hybrid vehicles. The parallel hybrids are assumed to (1) be produced at high volume, (2) use nickel metal hydride battery packs, and (3) have high-strength steel bodies. The conventional vehicle also is assumed to have a high-strength steel body. The simulated vehicles are held constant in many respects, including 0-60 time, engine type, aerodynamic drag coefficient, tire rolling resistance, and frontal area. The hybrids analyzed use the minimum size battery pack and motor to meet specified 0-60 times. A key characteristic affecting commercial viability is noted and quantified: that hybrids achieve the most pronounced fuel economy increase (best use) in slow, average-speed, stop-and-go driving, but when households consistently drive these vehicles under these conditions, they tend to travel fewer miles than average vehicles. We find that hours driven is a more valuable measure than miles. Estimates are developed concerning hours of use of household vehicles versus driving cycle, and the pattern of minimum NPV incremental cost (or benefit) of selecting the hybrid over the conventional vehicle at various fuel prices is illustrated. These results are based on data from various OECD motions on fuel price, annual miles of travel per vehicle, and driving cycles assumed to be applicable in those nations. Scatter in results plotted as a function of average speed, related to details of driving cycles and the vehicles selected for analysis, is discussed.

Santini, D. J.; Vyas, A. D.

1999-07-16T23:59:59.000Z

435

Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (  

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

Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (after 24-May 2010 06:00):" Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (after 24-May 2010 06:00):" ,,"Choke","Average","Average","Fluid","Methanol","Water","Oil","Gas","Hyd. Eq.","Gas" ,"Choke","Setting","Upstream","Upstream","Recovery","Recovery","Recovery","Recovery","Recovery","Recovery","Recovery" "Date and Time","Setting","Duration","Pressure","Temp.","Rate","Rate","Rate","Rate","Rate","Rate","Portion" "dd-mmm-yy","(64ths)","(hours)","(psia)","(degF)","(bfpd)","(bfpd)","(bwpd)","(bopd)","(mmcfpd)","(boepd)","(%)"

436

Small Town Energy Program (STEP) Final Report revised  

SciTech Connect

University Park, Maryland (UP) is a small town of 2,540 residents, 919 homes, 2 churches, 1 school, 1 town hall, and 1 breakthrough community energy efficiency initiative: the Small Town Energy Program (STEP). STEP was developed with a mission to create a model community energy transformation program that serves as a roadmap for other small towns across the U.S. STEP first launched in January 2011 in UP and expanded in July 2012 to the neighboring communities of Hyattsville, Riverdale Park, and College Heights Estates, MD. STEP, which concluded in July 2013, was generously supported by a grant from the U.S. Department of Energy (DOE). The STEP model was designed for replication in other resource-constrained small towns similar to University Park - a sector largely neglected to date in federal and state energy efficiency programs. STEP provided a full suite of activities for replication, including: energy audits and retrofits for residential buildings, financial incentives, a community-based social marketing backbone and local community delivery partners. STEP also included the highly innovative use of an Energy Coach who worked one-on-one with clients throughout the program. Please see www.smalltownenergy.org for more information. In less than three years, STEP achieved the following results in University Park: 30% of community households participated voluntarily in STEP; 25% of homes received a Home Performance with ENERGY STAR assessment; 16% of households made energy efficiency improvements to their home; 64% of households proceeded with an upgrade after their assessment; 9 Full Time Equivalent jobs were created or retained, and 39 contractors worked on STEP over the course of the project. Estimated Energy Savings - Program Totals kWh Electricity 204,407 Therms Natural Gas 24,800 Gallons of Oil 2,581 Total Estimated MMBTU Saved (Source Energy) 5,474 Total Estimated Annual Energy Cost Savings $61,343 STEP clients who had a home energy upgrade invested on average $4,500, resulting in a 13% reduction in annual energy use and utility bill savings of $325. Rebates and incentives covered 40%-50% of retrofit cost, resulting in an average simple payback of about 7 years. STEP has created a handbook in which are assembled all the key elements that went into the design and delivery of STEP. The target audiences for the handbook include interested citizens, elected officials and municipal staff who want to establish and run their own efficiency program within a small community or neighborhood, using elements, materials and lessons from STEP.

Wilson, Charles (Chuck) T. [Chuck

2014-01-02T23:59:59.000Z

437

STEO January 2013 - average gasoline prices  

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

gasoline prices are expected to decline over the next two years. The average pump price for regular unleaded gasoline was 3.63 a gallon during 2012. That is expected to fall...

438

Government Energy News  

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

news Office of Energy Efficiency & news Office of Energy Efficiency & Renewable Energy Forrestal Building 1000 Independence Avenue, SW Washington, DC 20585 en U.S. Energy Department, Pay-Television Industry and Energy Efficiency Groups Announce Set-Top Box Energy Conservation Agreement; Will Cut Energy Use for 90 Million U.S. Households, Save Consumers Billions http://energy.gov/articles/us-energy-department-pay-television-industry-and-energy-efficiency-groups-announce-set-top energy-department-pay-television-industry-and-energy-efficiency-groups-announce-set-top" class="title-link">U.S. Energy Department, Pay-Television Industry and Energy Efficiency Groups Announce Set-Top Box Energy Conservation Agreement; Will Cut Energy Use for 90 Million U.S. Households, Save

439

Energy-Efficiency-Related Conference Papers and Workshop Summarys  

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

Home > Households, Buildings & Industry > Energy Efficiency > Home > Households, Buildings & Industry > Energy Efficiency > Conference Papers Conference Papers Page Last Modified: September 2007 The Growth in Electricity Demand in U.S. Households, 1981-2001: Implications for Carbon Emissions Presented at the 25th Annual North American Conference, United States Association for Energy Economics, affiliated with the International Association for Energy Economics, September 18, 2005 Two Decades of U.S. Household Trends in Energy-Intensity Indicators: A Look at the Underlying Factors Presented at the 28th Annual International Association for Energy Economics, International Conference, affiliated with the United States Association for Energy Economics , June 3, 2005 Trends in the Use of Natural Gas in U.S. Households, 1987 to 2001

440

A spatiotemporal auto-regressive moving average model for solar radiation  

E-Print Network (OSTI)

1). Solar radiation, averaged over ten minute intervals, was recorded at each site for two yearsA spatiotemporal auto-regressive moving average model for solar radiation C.A. Glasbey and D, is important in many hydrological, agricultural and energy contexts. To assess solar energy potential, data

Stone, J. V.

Note: This page contains sample records for the topic "average household energy" 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

U.S. Energy Information Administration (EIA) - Source  

Gasoline and Diesel Fuel Update (EIA)

Efficiency Efficiency exec summary Executive Summary With more efficient light-duty vehicles, motor gasoline consumption declines while diesel fuel use grows, even as more natural agas is used in heavy-duty vehicles....Read full section mkt trends Market Trends Energy expenditures decline relative to gross domestic product and gross output...Read full section In the United States, average energy use per person declines from 2010 to 2040...Read full section Residential energy intensity continues to declines across a range of technology assumptions...Read full section Electricity use per household declines from 2011 to 2040 in the Reference case...Read full section Efficiency can offset increases in residential service demand...Read full section Planned expiration of tax credits affects renewable energy use in

442

How Do You Light Your Home Efficiently? | Department of Energy  

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

Light Your Home Efficiently? Light Your Home Efficiently? How Do You Light Your Home Efficiently? July 22, 2009 - 4:30pm Addthis An average household dedicates 11% of its energy budget to lighting. Installing efficient lighting technologies, using task lighting, flipping the switch, and taking advantage of natural daylight can all help you save on your lighting costs. How do you light your home efficiently? Each Thursday, you have the chance to share your thoughts on a question about energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Do You Save Energy in Your Apartment or Rental? How Do You Save Water When Caring for Your Lawn? How Do You Encourage Your Family to Use Less Water

443

U.S. Energy Information Administration (EIA) - Source  

Gasoline and Diesel Fuel Update (EIA)

Efficiency Efficiency exec summary Executive Summary With more efficient light-duty vehicles, motor gasoline consumption declines while diesel fuel use grows, even as more natural agas is used in heavy-duty vehicles....Read full section mkt trends Market Trends Energy expenditures decline relative to gross domestic product and gross output...Read full section In the United States, average energy use per person declines from 2010 to 2040...Read full section Residential energy intensity continues to declines across a range of technology assumptions...Read full section Electricity use per household declines from 2011 to 2040 in the Reference case...Read full section Efficiency can offset increases in residential service demand...Read full section Planned expiration of tax credits affects renewable energy use in

444

A life cycle approach to the management of household food waste - A Swedish full-scale case study  

SciTech Connect

Research Highlights: > The comparison of three different methods for management of household food waste show that anaerobic digestion provides greater environmental benefits in relation to global warming potential, acidification and ozone depilation compared to incineration and composting of food waste. Use of produced biogas as car fuel provides larger environmental benefits compared to a use of biogas for heat and power production. > The use of produced digestate from the anaerobic digestion as substitution for chemical fertilizer on farmland provides avoidance of environmental burdens in the same ratio as the substitution of fossil fuels with produced biogas. > Sensitivity analyses show that results are highly sensitive to assumptions regarding the environmental burdens connected to heat and energy supposedly substituted by the waste treatment. - Abstract: Environmental impacts from incineration, decentralised composting and centralised anaerobic digestion of solid organic household waste are compared using the EASEWASTE LCA-tool. The comparison is based on a full scale case study in southern Sweden and used input-data related to aspects such as source-separation behaviour, transport distances, etc. are site-specific. Results show that biological treatment methods - both anaerobic and aerobic, result in net avoidance of GHG-emissions, but give a larger contribution both to nutrient enrichment and acidification when compared to incineration. Results are to a high degree dependent on energy substitution and emissions during biological processes. It was seen that if it is assumed that produced biogas substitute electricity based on Danish coal power, this is preferable before use of biogas as car fuel. Use of biogas for Danish electricity substitution was also determined to be more beneficial compared to incineration of organic household waste. This is a result mainly of the use of plastic bags in the incineration alternative (compared to paper bags in the anaerobic) and the use of biofertiliser (digestate) from anaerobic treatment as substitution of chemical fertilisers used in an incineration alternative. Net impact related to GWP from the management chain varies from a contribution of 2.6 kg CO{sub 2}-eq/household and year if incineration is utilised, to an avoidance of 5.6 kg CO{sub 2}-eq/household and year if choosing anaerobic digestion and using produced biogas as car fuel. Impacts are often dependent on processes allocated far from the control of local decision-makers, indicating the importance of a holistic approach and extended collaboration between agents in the waste management chain.

Bernstad, A., E-mail: anna.bernstad@chemeng.lth.se [Department of Chemical Engineering, Box 124, Faculty of Engineering (LTH), Lund University, S-221 00 Lund (Sweden); Cour Jansen, J. la [Department of Chemical Engineering, Box 124, Faculty of Engineering (LTH), Lund University, S-221 00 Lund (Sweden)

2011-08-15T23:59:59.000Z

445

Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household  

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

1: January 5, 1: January 5, 2004 Number of Household Vehicles has Grown Significantly to someone by E-mail Share Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Facebook Tweet about Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Twitter Bookmark Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Google Bookmark Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Delicious Rank Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Digg Find More places to share Vehicle Technologies Office: Fact #301:

446

Indoor Secondary Pollutants from Household Product Emissions in the  

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

Indoor Secondary Pollutants from Household Product Emissions in the Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Title Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Publication Type Journal Article LBNL Report Number LBNL-58785 Year of Publication 2006 Authors Destaillats, Hugo, Melissa M. Lunden, Brett C. Singer, Beverly K. Coleman, Alfred T. Hodgson, Charles J. Weschler, and William W. Nazaroff Journal Environmental Science and Technology Volume 40 Start Page Chapter Pagination 4421-4428 Abstract Ozone-driven chemistry is a major source of indoor secondary pollutants of health concern. This study investigates secondary air pollutants formed from reactions between constituents of household products and ozone. Gas-phase product emissions were introduced along with ozone at constant rates into a 198-L Teflon-lined reaction chamber. Gas-phase concentrations of reactive terpenoids and oxidation products were measured. Formaldehyde was a predominant oxidation byproduct for the three studied products, with yields under most conditions of 20-30% with respect to ozone consumed. Acetaldehyde, acetone, glycolaldehyde, formic acid and acetic acid were each also detected for two or three of the products. Immediately upon mixing of reactants, a scanning mobility particle sizer detected particle nucleation events that were followed by a significant degree of ultrafine particle growth. The production of secondary gaseous pollutants and particles depended primarily on the ozone level and was influenced by other parameters such as the air-exchange rate. Hydroxyl radical concentrations in the range 0.04-200 × 105 molecules cm-3 were measured. OH concentrations were observed to vary strongly with residual ozone level in the chamber, which was in the range 1 - 25 ppb, as is consistent with expectations from a simplified kinetic model. In a separate test, we exposed the dry residue of two products to ozone in the chamber and observed the formation of gas-phase and particle-phase secondary oxidation products

447

Polarized electron beams at milliampere average current  

SciTech Connect

This contribution describes some of the challenges associated with developing a polarized electron source capable of uninterrupted days-long operation at milliAmpere average beam current with polarization greater than 80%. Challenges will be presented in the context of assessing the required level of extrapolation beyond the performance of today's CEBAF polarized source operating at ~ 200 uA average current. Estimates of performance at higher current will be based on hours-long demonstrations at 1 and 4 mA. Particular attention will be paid to beam-related lifetime-limiting mechanisms, and strategies to construct a photogun that operate reliably at bias voltage > 350kV.

Poelker, Matthew [JLAB

2013-11-01T23:59:59.000Z

448

Looking for free riding: energy efficiency incentives and Italian homeowners  

Science Journals Connector (OSTI)

We examine the effect of energy efficiency incentives on household energy efficiency home improvements. Starting in February 2007, ... purchase and installation costs of certain types of energy efficiency renovat...

Anna Alberini; Andrea Bigano; Marco Boeri

2014-08-01T23:59:59.000Z

449

Table HC6.10 Home Appliances Usage Indicators by Number of Household...  

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

0 Home Appliances Usage Indicators by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4...

450

Socioeconomic Differences in Household Automobile Ownership Rates: Implications for Evacuation Policy  

E-Print Network (OSTI)

Differences in 10 Household Automobile Ownership Rates:hauseltoldr lacking automobiles were mmit like! ) to be leftWithout 3 Access to an Automobile. Top Ten Metropolitan

Raphael, S; Berube, A; Deakin, Elizabeth

2006-01-01T23:59:59.000Z

451

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

452

Wealth: Determinants of Savings Net Worth and Housing Net Worth of Pre-Retired Households  

Science Journals Connector (OSTI)

The objectives of this study are to determine effects of household members' characteristics, financial resources, and attitude ... Subsamples of White respondents, Black respondents, and Hispanic respondents were...

Satomi Wakita; Vicki Schram Fitzsimmons

2000-12-01T23:59:59.000Z

453

Buildings Energy Data Book  

Buildings Energy Data Book (EERE)

2.1 Residential Sector Energy Consumption 2.1 Residential Sector Energy Consumption 2.2 Residential Sector Characteristics 2.3 Residential Sector Expenditures 2.4 Residential Environmental Data 2.5 Residential Construction and Housing Market 2.6 Residential Home Improvements 2.7 Multi-Family Housing 2.8 Industrialized Housing 2.9 Low-Income Housing 3Commercial Sector 4Federal Sector 5Envelope and Equipment 6Energy Supply 7Laws, Energy Codes, and Standards 8Water 9Market Transformation Glossary Acronyms and Initialisms Technology Descriptions Building Descriptions Other Data Books Biomass Energy Transportation Energy Power Technologies Hydrogen Download the Entire Book Skip down to the tables Chapter 2 focuses on energy use in the U.S. residential buildings sector. Section 2.1 provides data on energy consumption by fuel type and end use, as well as energy consumption intensities for different housing categories. Section 2.2 presents characteristics of average households and changes in the U.S. housing stock over time. Sections 2.3 and 2.4 address energy-related expenditures and residential sector emissions, respectively. Section 2.5 contains statistics on housing construction, existing home sales, and mortgages. Section 2.6 presents data on home improvement spending and trends. Section 2.7 describes the industrialized housing industry, including the top manufacturers of various manufactured home products. Section 2.8 presents information on low-income housing and Federal weatherization programs. The main points from this chapter are summarized below:

454

Ordered Weighted Average Based Fuzzy Rough Sets  

E-Print Network (OSTI)

Ordered Weighted Average Based Fuzzy Rough Sets Chris Cornelis 1 , Nele Verbiest1 , and Richard rough set model, which is based on a similar rationale, our proposal has the ad- vantage a feature selection application confirm the potential of the OWA-based model. Keywords: fuzzy rough sets

Gent, Universiteit

455

2/21/2014 Downsizing Wind Energyfor Your Phone | Glacial EnergyBlog -Commercial Electric Savings, Electric Provider, Electric Supplier http://blog.glacialenergy.com/2014/02/19/downsizing-wind-energy-for-your-phone/ 1/2  

E-Print Network (OSTI)

suppliers selling electricity and natural gas to residential, commercial, industrial, and institutional Energy Saving Tips Events General Electricity green roof Household Tips Life Tips Natural Gas New Announcements Community Electrical Safety Electricity Energy Energy Efficiency Energy Innovations Energy News

Chiao, Jung-Chih

456

Assessment of Supply Chain Energy Efficiency Potentials: A U.S. Case Study  

E-Print Network (OSTI)

use and greenhouse gas (GHG) emissions of a variety of goodsto the supply chain energy and GHG footprints of goods andto estimate achievable household GHG footprint reductions

Masanet, Eric

2010-01-01T23:59:59.000Z

457

Energy Department Awards $92.5 Million to 19 States to Weatherize...  

Office of Environmental Management (EM)

Secretary Alphonso Jackson, and Environmental Protection Agency Administrator Stephen Johnson kicked off the Partnership for Home Energy Efficiency, aimed at reducing household...

458

BC Hydro Brings Energy Savings to Low-Income Families in Canada  

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

The number of British Columbia, Canada, households eligible for Better Buildings Residential Network member BC Hydros Energy Conservation Assistance Program (ECAP) just doubled. British Columbia...

459

SmartTecO: Context-Based Ambient Sensing and Monitoring for Optimizing Energy Consumption  

E-Print Network (OSTI)

, Germany firstname.lastname@kit.edu Naoya Namatame Keio University Tokyo, Japan namachan- tems currently implemented in households and offices. Domestic energy use is commonly invisible

Beigl, Michael

460

Energy-Efficiency Labels and Standards: A Guidebook for Appliances, Equipment, and Lighting - 2nd Edition  

E-Print Network (OSTI)

energy-efficiency standards for household refrigerators are in place in several parts of the world, including North America, Europe, Japan, and

Wiel, Stephen; McMahon, James E.

2005-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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

Energy-efficiency labels and standards: A guidebook for appliances, equipment and lighting  

E-Print Network (OSTI)

energy-efficiency standards for household refrigerators are in place in several parts of the world, including North America, Europe, Japan, and

McMahon, James E.; Wiel, Stephen

2001-01-01T23:59:59.000Z

462

Estimating household fuel oil/kerosine, natural gas, and LPG prices by census region  

SciTech Connect

The purpose of this research is to estimate individual fuel prices within the residential sector. The data from four US Department of Energy, Energy Information Administration, residential energy consumption surveys were used to estimate the models. For a number of important fuel types - fuel oil, natural gas, and liquefied petroleum gas - the estimation presents a problem because these fuels are not used by all households. Estimates obtained by using only data in which observed fuel prices are present would be biased. A correction for this self-selection bias is needed for estimating prices of these fuels. A literature search identified no past studies on application of the selectivity model for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas. This report describes selectivity models that utilize the Dubin/McFadden correction method for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas in the Northeast, Midwest, South, and West census regions. Statistically significant explanatory variables are identified and discussed in each of the models. This new application of the selectivity model should be of interest to energy policy makers, researchers, and academicians.

Poyer, D.A.; Teotia, A.P.S.

1994-08-01T23:59:59.000Z

463

Preliminary assessment of the Louisiana Home Energy Rebate Offer program using IPMVP guidelines  

Science Journals Connector (OSTI)

The Louisiana Home Energy Rebate Offer (HERO) is a residential energy conservation program established in 1999 to provide rebates for qualified applicants to build new homes that are more energy efficient or improve the energy efficiency of existing homes. Energy conservation programs require careful evaluation because of the high cost to implement the measures and the expectation that they will reduce energy use. The purpose of this paper is to demonstrate that residential energy conservation measures in a hot and humid climate can be evaluated using the International Performance Measurement and Verification Protocol (IPMVP), a best practice methodology commonly used in industrial and commercial performance-based contracts, but rarely, if ever, applied to residential programs. Using a random sample of 60 HERO participants, we were able to construct statistically significant electricity consumption baseline models for 90% of households. We determined that more than half of the sample participants consumed more electricity after their efficiency improvement, with an average net household savings of 172kWh/yr, about 1% pre-retrofit consumption. A description of the baseline model construction, preliminary program evaluation, and recommendations are provided. All program conclusions are considered preliminary until a larger and more comprehensive study is conducted.

Mark J. Kaiser; Allan G. Pulsipher

2010-01-01T23:59:59.000Z

464

Home Performance with ENERGY STAR: Utility Bill Analysis on Homes Participating in Austin Energy's Program  

SciTech Connect

Home Performance with ENERGY STAR (HPwES) is a jointly managed program of the U.S. Department of Energy (DOE) and the U.S. Environmental Protection Agency (EPA). This program focuses on improving energy efficiency in existing homes via a whole-house approach to assessing and improving a home's energy performance, and helping to protect the environment. As a local sponsor for HPwES, Austin Energy's HPwES program offers a complete home energy assessment and a list of recommendations for efficiency improvements, along with cost estimates. The owner can choose to implement only one or the complete set of energy conservation measures. Austin Energy facilitates the process by providing economic incentives to the homeowner through its HPwES Loan program and its HPwES Rebate program. In 2005, the total number of participants in both programs was approximately 1,400. Both programs are only available for improvements made by a participating HPwES contractor. The individual household billing data - encompassing more than 7,000 households - provided by Austin Energy provides a rich data set to estimate the impacts of its HPwES program. The length of the billing histories is sufficient to develop PRISM-type models of electricity use based on several years of monthly bills before and after the installation of the conservation measures. Individual household savings were estimated from a restricted version of a PRISM-type regression model where the reference temperature to define cooling (or heating degree days) was estimated along with other parameters. Because the statistical quality of the regression models varies across individual households, three separate samples were used to measure the aggregate results. The samples were distinguished on the basis of the statistical significance of the estimated (normalized) cooling consumption. A normalized measure of cooling consumption was based on average temperatures observed over the most recent nine-year period ending in 2006. This study provided a statistically rigorous approach to incorporating the variability of expected savings across the households in the sample together with the uncertainty inherent in the regression models used to estimate those savings. While the impact of the regression errors was found to be relatively small in these particular samples, this approach may be useful in future studies using individual household billing data. The median percentage savings for the largest sample of 6,000 households in the analysis was 32%, while the mean savings was 28%. Because the number of households in the sample is very large, the standard error associated with the mean percentage savings are very small, less than 1%. A conservative statement of the average savings is that is falls in the range of 25% to 30% with a high level of certainty. This preliminary analysis provides robust estimates of average program savings, but offers no insight into how savings may vary by type of conservation measure or whether savings vary by the amount of cooling electricity used prior to undertaking the measure. Follow-up researchers may want to analyze the impacts of specific ECMs. Households that use electricity for heating might also be separately analyzed. In potential future work several methodological improvements could also be explored. As mentioned in Section 2, there was no formal attempt to clean the data set of outliers and other abnormal patterns of billing data prior to the statistical analysis. The restriction of a constant reference temperature might also be relaxed. This approach may provide evidence as to whether any 'take-back' efforts are present, whereby thermostat settings are lowered during the summer months after the measures are undertaken (reflected in lower reference temperatures in the post-ECM period). A more extended analysis may also justify the investment in and use of the PRISM software package, which may provide more diagnostic measures with respect to the reference temperature. PRISM also appears to contain some built-in capability to detect outliers and other an

Belzer, D.; Mosey, G.; Dagher, L.; Plympton, P.

2008-01-01T23:59:59.000Z

465

Average Rate Speed Scaling Nikhil Bansal1  

E-Print Network (OSTI)

energy. In this setting, the operating system must not only have a job selection policy to determine was deadline feasibility and the objective was to minimize the energy used. More precisely, each job i has of the speed to power function, this even spreading is energy optimal if the instance consists of only one job

Bunde, David

466

Average Rate Speed Scaling Nikhil Bansal  

E-Print Network (OSTI)

energy. In this setting, the operating system must not only have a job selection policy to determine was deadline feasibility and the objective was to minimize the energy used. More precisely, each job i has of the speed to power function, this even spreading is energy optimal if the instance consists of only one job

Bunde, David

467

Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"  

E-Print Network (OSTI)

Total Energy Source Demand Coal, Oil, Gas, Heat, ElectricityEnergy Source Demand per Household Coal, Oil, Gas, Heat,ton of oil equivalent Considerable increases in demand for

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

468

"Table A29. Average Prices of Selected Purchased Energy Sources...  

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

"," "," "," "," "," ","RSE" " "," ","Residual","Distillate","Natural"," "," ","Row" "Economic Characteristics(a)","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","Fac...

469

Table 8. Average Price of U.S. Coal Exports  

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

Average Price of U.S. Coal Exports Average Price of U.S. Coal Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 8. Average Price of U.S. Coal Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Continent and Country of Destination April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change North America Total 78.29 77.25 102.62 77.88 105.14 -25.9 Canada* 81.61 80.70 110.67 81.30 112.16 -27.5 Dominican Republic 78.54 75.09 73.89 75.77 76.61 -1.1 Honduras - 54.58 54.43 54.58 54.43 0.3 Jamaica 480.00 54.43 - 54.72 55.42 -1.3 Mexico 73.45 75.81 94.36 74.35 100.95 -26.3 Other** 80.33 389.30 70.37 82.45 76.10 8.3 South America Total 107.72 108.02 149.99 107.88

470

Table 17. Average Price of U.S. Coke Exports  

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

Average Price of U.S. Coke Exports Average Price of U.S. Coke Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 17. Average Price of U.S. Coke Exports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Continent and Country of Destination April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change North America Total 240.59 241.38 218.40 240.85 225.80 6.7 Canada* 147.49 330.47 243.04 183.08 286.56 -36.1 Mexico 316.57 211.63 189.12 273.97 171.71 59.6 Other** 612.42 485.63 134.48 525.92 135.04 289.5 South America Total 140.65 156.15 322.70 148.29 250.36 -40.8 Other** 140.65 156.15 322.70 148.29 250.36 -40.8 Europe Total 259.26 255.24 - 257.06 427.83 -39.9 Other**

471

Table 22. Average Price of U.S. Coke Imports  

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

Average Price of U.S. Coke Imports Average Price of U.S. Coke Imports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 22. Average Price of U.S. Coke Imports (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Continent and Country of Origin April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change North America Total 263.21 252.66 353.05 261.29 356.01 -26.6 Canada 263.51 252.66 353.05 258.82 356.01 -27.3 Panama 263.09 - - 263.09 - - South America Total 196.86 194.14 175.88 195.94 181.01 8.2 Brazil - - 157.60 - 157.60 - Colombia 196.86 194.14 322.06 195.94 246.68 -20.6 Europe Total 181.55 232.13 385.65 225.53 384.96 -41.4 Czech Republic - 475.91 - 475.91 - - Spain 360.51

472

Sources Of Average Individual Radiation Exposure  

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

Of Average Individual Radiation Exposure Of Average Individual Radiation Exposure Natural background Medical Consumer products Industrial, security, educational and research Occupational 0.311 rem 0.300 rem 0.013 rem 0.0003 rem 0.0005 rem Savannah River Nuclear Solutions, LLC, provides radiological protection services and oversight at the Savannah River Site (SRS). These services include radiation dose measurements for persons who enter areas where they may be exposed to radiation or radioactive material. The results are periodically reported to monitored individuals. The results listed are based on a radiation dose system developed by the International Commission on Radiation Protection. The system uses the terms "effective dose," "equivalent dose" and units of rem. You may be more familiar with the term "millirem" (mrem), which is 1/1000 of a rem.

473

Fat turnover in obese slower than average  

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

9-04 9-04 For immediate release: 09/23/2011 | NR-11-09-04 Fat turnover in obese slower than average Anne M Stark, LLNL, (925) 422-9799, stark8@llnl.gov Printer-friendly This scanning electron micrograph image shows part of a lobule of adipose tissue (body fat). Adipose tissue is specialized connective tissue that functions as the major storage site for fat. Photo courtesy of David Gregory & Debbie Marshall/Wellcome Images LIVERMORE, Calif. -- It may be more difficult for obese people to lose fat because the "turnover" rate is much slower for those overweight than average weight individuals. New research in the Sept. 25 online edition of the journal Nature shows that the turnover (storage and loss rate) of fat in the human body is about 1 1/2 years compared to fat cells, which turnover about every 10 years,

474

Natural Gas Prices: Well Above Recent Averages  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: The recent surge in spot prices at the Henry Hub are well above a typical range for 1998-1999 (in this context, defined as the average, +/- 2 standard deviations). Past price surges have been of short duration. The possibility of a downward price adjustment before the end of next winter is a source of considerable risk for storage operators who acquire gas at recent elevated prices. Storage levels in the Lower 48 States were 7.5 percent below the 5-year average (1995-1999) by mid-August (August 11), although the differential is only 6.4 percent in the East, which depends most heavily on storage to meet peak demand. Low storage levels are attributable, at least in part, to poor price incentives: high current prices combined with only small price

475

Indirect CP violation results and HFAG averages  

E-Print Network (OSTI)

The current status of the search for indirect CP violation in the neutral D meson system at the B-factories and at LHCb is reported. The indirect CP asymmetry search is performed by the measurement of the proper-time asymmetry ($A_{\\Gamma}$) in decays of $D^0-\\bar{D^0}$ mesons to CP eigenstates, $K^-K^+$ and $\\pi^- \\pi^+$, and by $y_{CP}$, the ratio between the effective lifetime measured in decay to a CP eigenstate and that to the mixed eigenstate $K \\pi$. All results are consistent with the no CP violation hypothesis. The latest world averages for mixing and CP asymmetry in the charm sector evaluated by the Heavy Flavour Averaging Group are presented. The no mixing hypothesis is excluded at more than 12 standard deviations. The search for direct and indirect CP violation in the charm sector is consistent with no CP violation at 2.0% confident level.

Silvia Borghi

2013-12-17T23:59:59.000Z

476

Polarized electron beams at milliampere average current  

SciTech Connect

This contribution describes some of the challenges associated with developing a polarized electron source capable of uninterrupted days-long operation at milliAmpere average beam current with polarization greater than 80%. Challenges will be presented in the context of assessing the required level of extrapolation beyond the performance of todays CEBAF polarized source operating at ? 200 uA average current. Estimates of performance at higher current will be based on hours-long demonstrations at 1 and 4 mA. Particular attention will be paid to beam-related lifetime-limiting mechanisms, and strategies to construct a photogun that operate reliably at bias voltage > 350kV.

Poelker, M. [Thomas Jefferson National Accelerator Facility, Newport News, Virginia 23606 (United States)

2013-11-07T23:59:59.000Z

477

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)

478

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

clothes drying, ceiling fans, coffee makers, spas, home security clothes drying, ceiling fans, coffee makers, spas, home security systems, microwave ovens, set-top boxes, home audio equipment, rechargeable electronics, and VCR/DVDs. In addition to the major equipment-driven end-uses, the average energy consumption per household is projected for other electric and nonelectric appliances. The module's output includes number Energy Information Administration/Assumptions to the Annual Energy Outlook 2007 19 Pacific East South Central South Atlantic Middle Atlantic New England West South Central West North Central East North Central Mountain AK WA MT WY ID NV UT CO AZ NM TX OK IA KS MO IL IN KY TN MS AL FL GA SC NC WV PA NJ MD DE NY CT VT ME RI MA NH VA WI MI OH NE SD MN ND AR LA OR CA HI Middle Atlantic New England East North Central West North Central Pacific West South Central East South Central

479

Renewable energy load assessment for Boquillas Del Carmen Coahuila, Mexico  

SciTech Connect

This report outlines the estimates that were made in 1992 of the potential load requirements for Boquillas del Carmen, a small Mexican village on the northern border of the state of Coahuila, Mexico near Big Bend National Park in southern Texas. The study was made to help determine the possibility that village might be electrified by solar or wind energy. Various estimates of are given of the potential load based on estimates ranging from basic use of lights, radio, television, and small household appliances to microwave ovens, refrigerators, and direct evaporative coolers. The low-energy consumption case was estimated to be at 23.0 kWh/month per residence per month, and the high-energy consumption case (with cooling) was 140.7 kWh/month per residence. On average, the typical residence is occupied by five individuals.

Foster, R. [Southwest Technology Development Institute, Las Cruces, NM (United States)

1995-08-01T23:59:59.000Z

480

Yearly-averaged daily usefulness efficiency of heliostat surfaces  

SciTech Connect

An analytical expression for estimating the instantaneous usefulness efficiency of a heliostat surface is obtained. A systematic procedure is then introduced to calculate the usefulness efficiency even when overlapping of blocking and shadowing on a heliostat surface exist. For possible estimation of the reflected energy from a given field, the local yearly-averaged daily usefulness efficiency is calculated. This efficiency is found to depend on site latitude angle, radial distance from the tower measured in tower heights, heliostat position azimuth angle and the radial spacing between heliostats. Charts for the local yearly-averaged daily usefulness efficiency are presented for {phi} = 0, 15, 30, and 45 N. These charts can be used in calculating the reflected radiation from a given cell. Utilization of these charts is demonstrated.

Elsayed, M.M.; Habeebuallah, M.B.; Al-Rabghi, O.M. (King Abdulaziz Univ., Jeddah (Saudi Arabia))

1992-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "average household energy" 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.


481

Using Multiple Household Food Inventories to Measure Food Availability in the Home  

E-Print Network (OSTI)

-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...

Sisk, Cheree L.

2010-10-12T23:59:59.000Z

482

Dimethyl ether (DME) from coal as a household cooking fuel in China  

E-Print Network (OSTI)

technologies. Given China's rich coal resources, the production and use of coal-derived DME as a cooking fuelDimethyl ether (DME) from coal as a household cooking fuel in China Eric D. Larson Princeton gas (LPG) as a household cooking fuel. As such, DME is an attractive fuel for clean cooking. DME can

483

Socioeconomic Differences in Household Automobile Ownership Rates: Implications for Evacuation Policy  

E-Print Network (OSTI)

Socioeconomic Differences in Household Automobile Ownership Rates: Implications for Evacuation's aftermath concerned the size and composition of the area's populations that lacked access to an automobile for all U.S. metropolitan areas that reside in a household without access to an automobile. Finally, we

Sekhon, Jasjeet S.

484

The Driving Internal Beliefs of Household Internet Adoption among Jordanians and the Role of Cultural Values  

Science Journals Connector (OSTI)

The purpose of this study is to develop and validate a comprehensive model for the determinants of household Internet adoption through identifying the driving internal beliefs of individuals and the effect of cultural values on behavioral intention to ... Keywords: Hofstede's Cultural Dimensions, Household Internet Adoption, Internal Beliefs, Micro Cultural Level, Perceived Risks, Technology Acceptance Model

Amin A. Shaqrah; Khaled Saleh Al Omoush; Raed Musbah Alqirem

2011-01-01T23:59:59.000Z

485

Particle and Gas Emissions from a Simulated Coal-Burning Household Fire Pit  

Science Journals Connector (OSTI)

Particle and Gas Emissions from a Simulated Coal-Burning Household Fire Pit ... Chinese anthracite and bituminous coals produce different amounts of emissions when burned in a fire pit that simulates common rural household use of these fuels. ... Here we present emissions from burning 15 different fuels in a laboratory system designed to mimic the fire pits used in Xuan Wei County, China. ...

Linwei Tian; Donald Lucas; Susan L. Fischer; S. C. Lee; S. Katharine Hammond; Catherine P. Koshland

2008-02-21T23:59:59.000Z

486

Journal: Ecological Applications1 Carbon, nitrogen, and phosphorus fluxes in household ecosystems in the3  

E-Print Network (OSTI)

#12;1 Journal: Ecological Applications1 2 Carbon, nitrogen, and phosphorus fluxes in household Resources Center, Saint Paul, MN 551089 3 University of Minnesota, Department of Ecology, Evolution with several29 components of household activities including air and motor vehicle travel, food consumption,30

Minnesota, University of

487

Flame Retardant Transfers from U.S. Households (Dust and Laundry Wastewater) to the Aquatic Environment  

Science Journals Connector (OSTI)

Analytes were ionized by APPI; dopant (acetone) was introduced (150 ?L/min) by a liquid chromatography pump (LC-20AD, Shimadzu Corporation, Kyoto, Japan). ... We collected repeat dust samples from 292 households in the Northern California Childhood Leukemia Study during two sampling rounds (from 2001 to 2007 and during 2010) using household vacuum cleaners and measured 22 PBDEs using high resoln. ...

Erika D. Schreder; Mark J. La Guardia

2014-09-17T23:59:59.000Z

488

Passive sampling methods to determine household and personal care product use  

E-Print Network (OSTI)

Passive sampling methods to determine household and personal care product use DEBORAH H. BENNETTa, cleaning products, passive sampling, SUPERB, longitudinal. Introduction Personal care and household care products, such as cleaning products and pesticides, are frequently used in most house- holds although

Leistikow, Bruce N.

489

Minority energy assessment report. Fall 1992  

SciTech Connect

The purpose of this research is to project household energy consumption, energy expenditure, and energy expenditure as share of income for five population groups from 1991 to 2009. The approach uses the Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory for the US Department of Energy`s Office of Minority Economic Impact. The MEAM provides a framework that can be used to forecast regional energy consumption and energy expenditure for majority, black, Hispanic, poor, and nonpoor households. The forecasts of key macroeconomic and energy variables used as exogenous variables in the MEAM were obtained from the Data Resources, Inc., Macromodel and Energy Model. Generally, the projections of household energy consumption, expenditure, and energy expenditure as share of income vary across population groups and census regions.

Teotia, A.P.S.; Poyer, D.A.; Lampley, L.; Anderson, J.L.

1992-12-01T23:59:59.000Z

490

Modeling household adoption of earthquake hazard adjustments: a longitudinal panel study of Southern California and Western Washington residents  

E-Print Network (OSTI)

This research, aimed at advancing the theory of environmental hazard adjustment processes by contrasting households from three cities in a high seismic hazard area with households from three other cities in a moderate seismic hazard area...

Arlikatti, Sudha S

2006-10-30T23:59:59.000Z

491

2014 Virginia Polytechnic Institute and State University BSE-158NP Household Water Quality in Loudoun County, Virginia  

E-Print Network (OSTI)

2014 Virginia Polytechnic Institute and State University BSE-158NP Household Water Quality in Loudoun County, Virginia OCTOBER 2013 VIRGINIA HOUSEHOLD WATER QUALITY PROGRAM Erin Ling, Water Quality Extension Associate, and Brian Benham, Extension Specialist and Professor

Liskiewicz, Maciej

492

2014 Virginia Polytechnic Institute and State University BSE-151NP Household Water Quality in Albemarle County, Virginia  

E-Print Network (OSTI)

2014 Virginia Polytechnic Institute and State University BSE-151NP Household Water Quality in Albemarle County, Virginia APRIL 2013 VIRGINIA HOUSEHOLD WATER QUALITY PROGRAM Erin Ling, Water Quality Extension Associate, and Brian Benham, Extension Specialist and Professor

Liskiewicz, Maciej