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Sample records for average household energy

  1. Fact #614: March 15, 2010 Average Age of Household Vehicles | Department of

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

    Energy 4: March 15, 2010 Average Age of Household Vehicles Fact #614: March 15, 2010 Average Age of Household Vehicles 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 reported in the 1995 survey, have the youngest average age. Average Vehicle Age by Vehicle Type Graph showing the average vehicle age by type (car, van, pickup, SUV, all household

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

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

    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....

  3. 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

  4. 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

  5. Household Vehicles Energy Consumption 1991

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

    or commercial trucks (See Table 1). Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 5 The 1991 RTECS count includes vehicles that were owned or used...

  6. Household Vehicles Energy Consumption 1991

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

    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...

  7. Average household expected to save $675 at the pump in 2015

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

    Average household expected to save $675 at the pump in 2015 Although retail gasoline prices have risen in recent weeks U.S. consumers are still expected to save about $675 per household in motor fuel costs this year. In its new monthly forecast, the U.S. Energy Information Administration says the average pump price for regular grade gasoline in 2015 will be $2.43 per gallon. That's about 93 cents lower than last year's average. The savings for consumers will be even bigger during the

  8. Household Vehicles Energy Consumption 1991

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

    16.8 17.4 18.6 18.9 1.7 2.2 0.6 1.5 Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 15 Vehicle Miles Traveled per Vehicle (Thousand) . . . . . . . . ....

  9. Household Vehicles Energy Use Cover Page

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

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

  10. Strategies for Collecting Household Energy Data | Department...

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

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for ...

  11. Household vehicles energy consumption 1994

    SciTech Connect (OSTI)

    1997-08-01

    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.

  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. Energy Information Administration/Household Vehicles Energy Consumptio...

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

    , Energy Information AdministrationHousehold Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related...

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

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

    National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards (Washington, DC: National Academy of Sciences, 2002), p. 85. 4 8.3 million...

  15. Household energy consumption and expenditures, 1990

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  16. Spacetime averaged null energy condition

    SciTech Connect (OSTI)

    Urban, Douglas; Olum, Ken D.

    2010-06-15

    The averaged null energy condition has known violations for quantum fields in curved space, even when one considers only achronal geodesics. Many such examples involve rapid variation in the stress-energy tensor in the vicinity of the geodesic under consideration, giving rise to the possibility that averaging in additional dimensions would yield a principle universally obeyed by quantum fields. However, after discussing various procedures for additional averaging, including integrating over all dimensions of the manifold, we give here a class of examples that violate any such averaged condition.

  17. Household energy consumption and expenditures 1993

    SciTech Connect (OSTI)

    1995-10-05

    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.

  18. Determinants of Household Use of Selected Energy Star Appliances - Energy

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration Determinants of Household Use of Selected Energy Star Appliances Release date: May 25, 2016 Introduction According to the 2009 Residential Energy Consumption Survey (RECS), household appliances1accounted for 35% of U.S. household energy consumption, up from 24% in 1993. Thus, improvements in the energy performance of residential appliances as well as increases in the use of more efficient appliances can be effective in reducing household energy consumption and

  19. Concentration Averaging | Department of Energy

    Office of Environmental Management (EM)

    Concentration Averaging Concentration Averaging Summary Notes from 3 October 2007 Generic Technical Issue Discussion on Concentration Averaging PDF icon Summary Notes from 3...

  20. Household Vehicles Energy Consumption 1991

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

    more fuel-efficient vehicles, and the implementation of Corporate Average Fuel Economy (CAFE) 6 standards. Figure 13. Average Fuel Efficiency of All Vehicles, by Model Year 6...

  1. Strategies for Collecting Household Energy Data | Department of Energy

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

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data, Call Slides and Discussion Summary, July 19, 2012. Call Slides and Discussion Summary (700.06 KB) More Documents & Publications Homeowner and Contractor Surveys Mastermind: Jim Mikel, Spirit Foundation Generating Energy Efficiency Project Leads and Allocating Leads to Contractors

  2. Household energy consumption and expenditures, 1987

    SciTech Connect (OSTI)

    Not Available

    1989-10-10

    Household Energy Consumption and Expenditures 1987, Part 1: National Data is the second publication in a series from the 1987 Residential Energy Consumption Survey (RECS). It is prepared by the Energy End Use Division (EEUD) of the Office of Energy Markets and End Use (EMEU), Energy Information Administration (EIA). The EIA collects and publishes comprehensive data on energy consumption in occupied housing units in the residential sector through the RECS. 15 figs., 50 tabs.

  3. Household Vehicles Energy Consumption 1991

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

    production vehicles in order to assess compliance with Corporate Average Fuel Economy (CAFE) standards. The EPA Composite MPG is based on the assumption of a "typical" vehicle-use...

  4. Household Vehicles Energy Consumption 1991

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

    selected tabulations were produced using two different software programs, Table Producing Language (TPL) and Statistical Analysis System (SAS). Energy Information Administration...

  5. Household Vehicles Energy Consumption 1991

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

    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...

  6. Household Vehicles Energy Consumption 1991

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

    for 1994, will continue the 3-year cycle. The RTECS, a subsample of the Residential Energy Consumption Survey (RECS), is an integral part of a series of surveys designed by...

  7. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect (OSTI)

    Kwac, J; Flora, J; Rajagopal, R

    2014-01-01

    The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.

  8. Next Generation Household Refrigerator | Department of Energy

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

    Next Generation Household Refrigerator Next Generation Household Refrigerator Embraco's high efficiency, oil-free linear compressor.
    Credit: Whirlpool Embraco's high ...

  9. Household energy consumption and expenditures, 1990. [Contains Glossary

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  10. Household energy consumption and expenditures 1987

    SciTech Connect (OSTI)

    Not Available

    1990-01-22

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

  11. Average U.S. household to spend $710 less on gasoline during 2015

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

    drivers to see big savings at the gasoline pump this summer U.S. consumers are expected to pay the lowest average price for gasoline in six years during this summer's driving season, mostly because of lower crude oil costs. In its new forecast, the U.S. Energy Information Administration said the price for regular gasoline should average $2.45 per gallon this summer. That's down more than a dollar from the $3.59 per gallon seen last summer, and the cheapest average summer pump price since 2009.

  12. Barriers to household investment in residential energy conservation: preliminary assessment

    SciTech Connect (OSTI)

    Hoffman, W.L.

    1982-12-01

    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)

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

    SciTech Connect (OSTI)

    Guerin, D.A.

    1988-01-01

    This study focused on the family household as an organism and on its interaction with the three environments of the human ecosystem (natural, behavioral, and constructed) as these influence energy consumption and energy-consumption change. A secondary statistical analysis of data from the US Department of Energy Residential Energy Consumption Surveys (RECS) was completed. The 1980 and 1983 RECS were used as the data base. Longitudinal data, including household, environmental, and energy-consumption measures, were available for over 800 households. The households were selected from a national sample of owner-occupied housing units surveyed in both years. Results showed a significant( p = <.05) relationship between the dependent-variable energy-consumption change and the predictor variables heating degree days, addition of insulation, addition of a wood-burning stove, year the housing unit was built, and weighted number of appliances. A significant (p = <.05) relationship was found between the criterion variable energy-consumption change and the discriminating variables of age of the head of the household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

  14. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-01-01

    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).

  15. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-12-31

    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).

  16. Household Vehicles Energy Use: Latest Data & Trends

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

    (EERE) program in the U.S. Department of Energy (DOE), Transportation Energy Data Book: Edition 24. Note: * a recession year. Estimates are displayed as rounded values....

  17. Average U.S. household to spend $710 less on gasoline during...

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

    710 in gasoline costs this year compared with what was paid at the pump in 2014. In its new monthly forecast, the U.S. Energy Information Administration said the national ...

  18. Average U.S. household to spend $710 less on gasoline during...

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

    In its new forecast, the U.S. Energy Information Administration said natural gas-fired generation is expected to produce 30% of U.S. electricity this year. That's up from 27% ...

  19. Household Vehicles Energy Consumption 1994 - Appendix C

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

    discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on...

  20. Household Vehicles Energy Use: Latest Data & Trends

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

    E : C H R O N O L O G Y O F W O R L D O I L M A R K E T E V E N T S ENERGY INFORMATION ADMINISTRATIONHOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS 177 APPENDIX E A P P E N D...

  1. Average U.S. household to spend $710 less on gasoline during 2015

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

    natural gas inventories at end of winter higher than last year Despite recent cold temperatures in some parts of the country, U.S. natural gas inventories ended the winter heating season in better shape than last year. In its new forecast, the U.S. Energy Information Administration said natural gas inventories near the end of March were 75% higher compared with the same period in 2014. That sets up adequate supplies for gas-fired power plants this summer to meet electric cooling needs of

  2. Household Vehicles Energy Use: Latest Data & Trends

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

    Federal Highway Administration. Accessed on the world-wide web at http:www.fhwa.dot.govenvironmentcmaqpgsamaq03cmaq1fig3.htm on July 11, 2005. ENERGY INFORMATION...

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

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

    Money | Department of Energy 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

  4. Residential energy use and conservation in Venezuela: Results and implications of a household survey in Caracas

    SciTech Connect (OSTI)

    Figueroa, M.J.; Ketoff, A.; Masera, O.

    1992-10-01

    This document presents the final report of a study of residential energy use in Caracas, the capital of Venezuela. It contains the findings of a household energy-use survey held in Caracas in 1988 and examines options for introducing energy conservation measures in the Venezuelan residential sector. Oil exports form the backbone of the Venezuelan economy. Improving energy efficiency in Venezuela will help free domestic oil resources that can be sold to the rest of the world. Energy conservation will also contribute to a faster recovery of the economy by reducing the need for major investments in new energy facilities, allowing the Venezuelan government to direct its financial investments towards other areas of development. Local environmental benefits will constitute an important additional by-product of implementing energy-efficiency policies in Venezuela. Caracas`s residential sector shows great potential for energy conservation. The sector is characterized by high saturation levels of major appliances, inefficiency of appliances available in the market, and by careless patterns of energy use. Household energy use per capita average 6.5 GJ/per year which is higher than most cities in developing countries; most of this energy is used for cooking. Electricity accounts for 41% of all energy use, while LPG and natural gas constitute the remainder. Specific options for inducing energy conservation and energy efficiency in Caracas`s residential sector include energy-pricing policies, fuel switching, particularly from electricity to gas, improving the energy performance of new appliances and customer information. To ensure the accomplishment of an energy-efficiency strategy, a concerted effort by energy users, manufacturers, utility companies, government agencies, and research institutions will be needed.

  5. Averaged null energy condition violation in a conformally flat spacetime

    SciTech Connect (OSTI)

    Urban, Douglas; Olum, Ken D.

    2010-01-15

    We show that the averaged null energy condition can be violated by a conformally coupled scalar field in a conformally flat spacetime in 3+1 dimensions. The violation is dependent on the quantum state and can be made as large as desired. It does not arise from the presence of anomalies, although anomalous violations are also possible. Since all geodesics in conformally flat spacetimes are achronal, the achronal averaged null energy condition is likewise violated.

  6. Forum on Enhancing the Delivery of Energy Efficiency to Middle Income Households: Discussion Summary

    SciTech Connect (OSTI)

    none,

    2012-09-20

    Summarizes discussions and recommendations from a forum for practitioners and policymakers aiming to strengthen residential energy efficiency program design and delivery for middle income households.

  7. EPA Webinar: Bringing Energy Efficiency and Renewable Housing to Low-Income Households

    Broader source: Energy.gov [DOE]

    Hosted by the U.S. Environmental Protection Agency, this webinar will explore the topic of linking and leveraging energy efficiency and renewable energy programs for limited-income households, including the need to coordinate with other energy assistance programs.

  8. Delivering Energy Efficiency to Middle Income Single Family Households

    SciTech Connect (OSTI)

    none,

    2011-12-01

    Provides state and local policymakers with information on successful approaches to the design and implementation of residential efficiency programs for households ineligible for low-income programs.

  9. Energy-efficient housing alternatives: a predictive model of factors affecting household perceptions

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

    The major purpose of this investigation was to assess the impact of household socio-economic factors, dwelling characteristics, energy conservation behavior, and energy attitudes on the perceptions of energy-efficient housing alternatives. Perceptions of passive solar, active solar, earth sheltered, and retrofitted housing were examined. Data used were from the Southern Regional Research Project, S-141, Housing for Low and Moderate Income Families. Responses from 1804 households living in seven southern states were analyzed. A conceptual model was proposed to test the hypothesized relationships which were examined by path analysis. Perceptions of energy efficient housing alternatives were found to be a function of selected household and dwelling characteristics, energy attitude, household economic factors, and household conservation behavior. Age and education of the respondent, family size, housing-income ratio, utility income ratio, energy attitude, and size of the dwelling unit were found to have direct and indirect effects on perceptions of energy-efficient housing alternatives. Energy conservation behavior made a significant direct impact with behavioral energy conservation changes having the most profound influence. Conservation behavior was influenced by selected household and dwelling characteristics, energy attitude, and household economic factors.

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

    Broader source: Energy.gov [DOE]

    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...

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

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

    5 Household 1 Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005 Year Space ... 3 Fuel Oil 4 LPG 5 Total Electricity 3 Natural Gas Elec- tricity 3 ...

  12. 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 Information Administration | Drivers of U.S. Household Energy Consumption, 1980-2009 i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any

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

    SciTech Connect (OSTI)

    Zimring, Mark; Fuller, Merrian

    2011-01-24

    The New York legislature passed the Green Jobs-Green New York (GJGNY) Act in 2009. Administered by the New York State Energy Research and Development Authority (NYSERDA), GJGNY programs provide New Yorkers with access to free or low-cost energy assessments,1 energy upgrade services,2 low-cost financing, and training for various 'green-collar' careers. Launched in November 2010, GJGNY's residential initiative is notable for its use of novel underwriting criteria to expand access to energy efficiency financing for households seeking to participate in New York's Home Performance with Energy Star (HPwES) program.3 The GJGNY financing program is a valuable test of whether alternatives to credit scores can be used to responsibly expand credit opportunities for households that do not qualify for traditional lending products and, in doing so, enable more households to make energy efficiency upgrades.

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

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

    starting up for next school year that challenges students to learn about energy, develop techniques for saving energy, and help their families save money on their energy bills. ...

  15. Table 5.18. U.S. Average Household and Vehicle Energy Expenditures...

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

    ... 8.5 3,447 0.3 1,676 8.2 3,519 1,827 1,692 8.6 Below Poverty Line 100 Percent ... 14.7 1,600 5.7 935 9.0 2,022...

  16. Special Topics on Energy Use in Household Transportation

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

    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)...

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

    SciTech Connect (OSTI)

    Figueroa, M.J.; Sathaye, J.

    1993-08-01

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

  18. Comparison of energy expenditures by elderly and non-elderly households: 1975 and 1985

    SciTech Connect (OSTI)

    Siler, A.

    1980-05-01

    The relative position of the elderly in the population is examined and their characteristic use of energy in relation to the total population and their non-elderly counterparts is observed. The 1985 projections are based on demographic, economic, and socio-economic, and energy data assumptions contained in the 1978 Annual Report to Congress. The model used for estimating household energy expenditure is MATH/CHRDS - Micro-Analysis of Transfers to Households/Comprehensive Human Resources Data System. Characteristics used include households disposable income, poverty status, location by DOE region and Standard Metropolitan Statistical Area (SMSA), and race and sex of the household head as well as age. Energy use by fuel type will be identified for total home fuels, including electricity, natural gas, bottled gas and fuel oil, and for all fuels, where gasoline use is also included. Throughout the analysis, both income and expenditure-dollar amounts for 1975 and 1985 are expressed in constant 1978 dollars. Two appendices contain statistical information.

  19. Electric Sales, Revenue, and Average Price 2011 - Energy Information

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

    Administration Electricity Glossary › FAQS › Overview Data Electricity Data Browser (interactive query tool with charting & mapping) Summary Sales (consumption), revenue, prices & customers Generation and thermal output Capacity of electric power plants Consumption of fuels used to generate electricity Receipts of fossil-fuels for electricity generation Average cost of fossil-fuels for electricity generation Fossil-fuel stocks for electricity generation Cost, revenue and expense

  20. Household Vehicles Energy Use: Latest Data and Trends

    Reports and Publications (EIA)

    2005-01-01

    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.

  1. Table 7.4 Average Prices of Selected Purchased Energy Sources...

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

    4 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " ...

  2. Energy Conservation Program for Consumer Products: Representative Average Unit Costs of Energy

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

    Energy Conservation Program for Consumer Products: Representative Average Unit Costs of Energy, is a notice issued by the Department of Energy. Though it is not intended or expected, should any discrepancy occur between the document posted here and the document published in the Federal Register, the Federal Register publication controls. This document is being made available through the Internet solely as a means to facilitate the public's access to this document."

  3. A Method for Modeling Household Occupant Behavior to Simulate Residential Energy Consumption

    SciTech Connect (OSTI)

    Johnson, Brandon J; Starke, Michael R; Abdelaziz, Omar; Jackson, Roderick K; Tolbert, Leon M

    2014-01-01

    This paper presents a statistical method for modeling the behavior of household occupants to estimate residential energy consumption. Using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS), actions carried out by survey respondents are categorized into ten distinct activities. These activities are defined to correspond to the major energy consuming loads commonly found within the residential sector. Next, time varying minute resolution Markov chain based statistical models of different occupant types are developed. Using these behavioral models, individual occupants are simulated to show how an occupant interacts with the major residential energy consuming loads throughout the day. From these simulations, the minimum number of occupants, and consequently the minimum number of multiple occupant households, needing to be simulated to produce a statistically accurate representation of aggregate residential behavior can be determined. Finally, future work will involve the use of these occupant models along side residential load models to produce a high-resolution energy consumption profile and estimate the potential for demand response from residential loads.

  4. Household energy conservation attitudes and behaviors in the Northwest: Tracking changes between 1983 and 1985

    SciTech Connect (OSTI)

    Fang, J.M.; Hattrup, M.P.; Nordi, R.T.; Shankle, S.A.; Ivey, D.L.

    1987-05-01

    Pacific Northwest Laboratory (PNL) has analyzed the changes in consumer energy conservation attitudes and behaviors in the Pacific Northwest between 1983 and 1985. The information was collected through stratified random telephone surveys on 2000 and 1058 households, respectively, for 1983 and 1985 in the Bonneville Power Administration (BPA) service area in Idaho, Oregon, Washington and Western Montana. This report covers four topic areas and tests two hypotheses. The topics are as follows: consumer perceptions and attitudes of energy use and conservation in the home; consumer perceptions of energy institutions and other entities; past and intended conservation actions and investments; and segmentation of homeowners into market prospect groups. The hypotheses tested are as follows: (1) There has been no change in the size and psychographic make-up of the original three market segments found in the 1983 survey analysis; and (2) image profiles of institutions with respect to familiarity, overall impression, and believability as sources of energy conservation information remain unchanged since 1983.

  5. Energy Saver Blog | Department of Energy

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

    Home cooling accounts for 6 percent of the average household's energy use. To help you save money by saving energy, our experts are answering your home cooling questions. |...

  6. Survey of Recipients of WAP Services Assessment of Household Budget and Energy Behaviors Pre to Post Weatherization DOE

    SciTech Connect (OSTI)

    Tonn, Bruce Edward; Rose, Erin M.; Hawkins, Beth A.

    2015-10-01

    This report presents results from the national survey of weatherization recipients. This research was one component of the retrospective and Recovery Act evaluations of the U.S. Department of Energy s Weatherization Assistance Program. Survey respondents were randomly selected from a nationally representative sample of weatherization recipients. The respondents and a comparison group were surveyed just prior to receiving their energy audits and then again approximately 18 months post-weatherization. This report focuses on budget issues faced by WAP households pre- and post-weatherization, whether household energy behaviors changed from pre- to post, the effectiveness of approaches to client energy education, and use and knowledge about thermostats.

  7. Cool Ways to Save Energy | Department of Energy

    Energy Savers [EERE]

    accounts for 6 percent of the average household's energy use. To help you save money by saving energy, our experts are answering your home cooling questions. | Photo courtesy ...

  8. "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;" " 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"

  9. 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;" " 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"

  10. 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;" " 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"

  11. 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

  12. 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;" " 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

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

    Gasoline and Diesel Fuel Update (EIA)

    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 ...

  14. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    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

  15. "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" " 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

  16. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book [EERE]

    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 ...

  17. "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;" " 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

  18. 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;" " 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"

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

    SciTech Connect (OSTI)

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

    1998-05-01

    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.

  20. Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data, Call Slides and Discussion Summary, July 19, 2012

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

    19, 2012 Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data Call Slides and Discussion Summary Agenda * Call Logistics and Attendance  Is your program getting household energy data? How? * Program Experience and Lessons:  Janelle Beverly and Jeff Hughes, University of North Carolina Environmental Finance Center (http://www.efc.unc.edu/index.html) * Discussion:  What are successful strategies for obtaining

  1. "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" " 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

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

    SciTech Connect (OSTI)

    Henderson, L.J. ); Poyer, D.A.; Teotia, A.P.S. . Energy Systems Div.)

    1992-09-01

    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.

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

    SciTech Connect (OSTI)

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

    2005-05-31

    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.

  4. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    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

  5. Average Neutron Total Cross Sections in the Unresolved Energy Range From ORELA High Resolutio Transmission Measurements

    SciTech Connect (OSTI)

    Derrien, H

    2004-05-27

    Average values of the neutron total cross sections of {sup 233}U, {sup 235}U, {sup 238}U, and {sup 239}Pu have been obtained in the unresolved resonance energy range from high-resolution transmission measurements performed at ORELA in the past two decades. The cross sections were generated by correcting the effective total cross sections for the self-shielding effects due to the resonance structure of the data. The self-shielding factors were found by calculating the effective and true cross sections with the computer code SAMMY for the same Doppler and resolution conditions as for the transmission measurements, using an appropriate set of resonance parameters. Our results are compared to results of previous measurements and to the current ENDF/B-VI data.

  6. Fact #671: April 18, 2011 Average Truck Speeds | Department of Energy

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

    1: April 18, 2011 Average Truck Speeds Fact #671: April 18, 2011 Average Truck Speeds The Federal Highway Administration studies traffic volume and flow on major truck routes by tracking more than 500,000 trucks. The average speed of trucks on selected interstate highways is between 50 and 60 miles per hour (mph). The average operating speed of trucks is typically below 55 mph in major urban areas, border crossings, and in mountainous terrain. The difference in average speed between peak traffic

  7. Dynamical interpretation of average fission-fragment kinetic energy systematics and nuclear scission

    SciTech Connect (OSTI)

    Nadtochy, P.N. [GSI, Plankstrasse 1, D-64291 Darmstadt (Germany); Omsk State University, Department of Theoretical Physics, Mira Prospect 55-A, RU-644077 Omsk (Russian Federation); Adeev, G.D. [Omsk State University, Department of Theoretical Physics, Mira Prospect 55-A, RU-644077 Omsk (Russian Federation)

    2005-11-01

    A dynamical interpretation of the well-known systematics for average total kinetic energy of fission fragments over a wide range of the Coulomb parameter (600 on the Coulomb parameter. The results of dynamical calculations of within three-dimensional Langevin dynamics show that the mean distance between the centers of mass of nascent fragments at the scission configuration increases linearly with the parameter Z{sup 2}/A{sup 1/3}. This distance changes approximately from 2.35R{sub 0} for {sup 119}Xe to 2.6R{sub 0} for {sup 256}Fm. In spite of this increase in mean distance between future fragments at scission, the linear dependence of on the parameter Z{sup 2}/A{sup 1/3} remains approximately valid over a wide range of the Coulomb parameter Z{sup 2}/A{sup 1/3}.

  8. Fact #615: March 22, 2010 Average Vehicle Trip Length | Department of

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

    Energy 5: March 22, 2010 Average Vehicle Trip Length Fact #615: March 22, 2010 Average Vehicle Trip Length 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 an average of 12.6 miles. The average trip length has been growing each survey year since the lowest average in 1983. Average Vehicle Trip Length, 1969-2009 Graph showing the average vehicle

  9. Assumption to the Annual Energy Outlook 2014 - Residential Demand...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    oil, liquefied petroleum gas, natural gas, kerosene, electricity, wood, geothermal, and solar energy. The module's output includes number of households, equipment stock, average...

  10. Household magnets

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Household magnets Chances are very good that you have experimented with magnets. People have been fascinated with magnetism for thousands of years. As familiar to us as they may be, magnets still have some surprises for us. Here is a small collection of some of our favorite magnet experiments. What happens when we break a magnet in half? Radio Shack sells cheap ceramic magnets in several shapes. Get a ring shaped magnet and break it with pliers or a tap with a hammer. Try to put it back

  11. Fact #565: April 6, 2009 Household Gasoline Expenditures by Income |

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

    Department of Energy 5: April 6, 2009 Household Gasoline Expenditures by Income Fact #565: April 6, 2009 Household Gasoline Expenditures by Income In the annual Consumer Expenditure Survey, household incomes are grouped into five equal parts called quintiles (each quintile is 20%). Households in the second and third quintiles consistently have a higher share of spending on gasoline each year than households in the other quintiles. Household Gasoline Expenditures by Income Quintile Bar graph

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

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

    1" " (Estimates in Dollars per Physical Units)" ,,,,,"Noncombustible Energy Sources",,,,,,,,,,,,,,,,,,"Combustible Energy Sources" ,,,,,,,,,,,,,,,"Solids",,,,,,,,,,"Gases",,,,,,,,,"Liquids" " "," ",," "," ",,,,," "," "," "," "," "," "," ",,,"Wood","Wood Residues",,,,,,,,,,,,,,,,,,,," " "

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

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

    2" " (Estimates in Dollars per Million Btu)" ,,,,,"Noncombustible Energy Sources",,,,,,,,,,,,,,,,,,"Combustible Energy Sources" ,,,,,,,,,,,,,,,"Solids",,,,,,,,,,"Gases",,,,,,,,,"Liquids" " "," ",," "," ",,,,," "," "," "," "," "," "," ",,,"Wood","Wood Residues",,,,,,,,,,,,,,,,,,,," " "

  14. Table 2.4 Household Energy Consumption by Census Region, Selected Years, 1978-2009 (Quadrillion Btu, Except as Noted)

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

    Household 1 Energy Consumption by Census Region, Selected Years, 1978-2009 (Quadrillion Btu, Except as Noted) Census Region 2 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 United States Total (does not include wood) 10.56 9.74 9.32 9.29 8.58 9.04 9.13 9.22 10.01 10.25 9.86 10.55 10.18 Natural Gas 5.58 5.31 4.97 5.27 4.74 4.98 4.83 4.86 5.27 5.28 4.84 4.79 4.69 Electricity 3 2.47 2.42 2.48 2.42 2.35 2.48 2.76 3.03 3.28 3.54 3.89 4.35 4.39 Distillate Fuel Oil and Kerosene 2.19

  15. Energy Intensity Indicators: Residential Source Energy Consumption

    Broader source: Energy.gov [DOE]

    Figure R1 below reports as index numbers over the period 1970 through 2011: 1) the number of U.S. households, 2) the average size of those housing units, 3) residential source energy consumption, 4...

  16. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    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

  17. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    6 Weatherization Costs and Savings - DOE Weatherization program requires that States spend no more than an average of $6,572 per household in PY 2011. All States are using energy audits or priority lists to determine the most cost-effective weatherization measures. - DOE weatherization created an average energy savings of $437 per household, reduced household annual annual consumption by 35% and returned savings of $1.80 per every $1 invested. Source(s): DOE, Weatherization and Intergovernmental

  18. Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    4 1 October 2014 Short-Term Energy and Winter Fuels Outlook (STEO) Highlights  EIA projects average U.S. household expenditures for natural gas, heating oil, electricity, and propane will decrease this winter heating season (October 1 through March 31) compared with last winter, which was 11% colder than the previous 10-year average nationally. Projected average household expenditures for propane and heating oil are 27% and 15% lower, respectively, because of lower heating demand and prices.

  19. Short-Term Energy and Winter Fuels Outlook October 2013

    Gasoline and Diesel Fuel Update (EIA)

    3 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

  20. Question of the Week: What Energy-Saving Improvements are on...

    Energy Savers [EERE]

    This Month on Energy Savers: November 2011 Home cooling accounts for 6 percent of the average household's energy use. To help you save money by saving energy, our experts are ...

  1. ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS

    SciTech Connect (OSTI)

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

    2009-04-15

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

  2. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

  4. Stay Cool for Less Money with a Ceiling Fan | Department of Energy

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Home cooling accounts for 6 percent of the average household's energy use. To help you save money by saving energy, our experts are answering your home cooling questions. | Photo ...

  5. #AskEnergySaver: Home Cooling | Department of Energy

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

    Cooling #AskEnergySaver: Home Cooling July 24, 2014 - 11:13am Addthis Home cooling accounts for 6 percent of the average household's energy use. To help you save money by saving energy, our experts are answering your home cooling questions. | Photo courtesy of ©iStockphoto/JaniceRichard Home cooling accounts for 6 percent of the average household's energy use. To help you save money by saving energy, our experts are answering your home cooling questions. | Photo courtesy of

  6. ,"Housing Units1","Average Square Footage Per Housing Unit",...

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

    ... U.S. Department of Energy's Office of Energy and Efficiency and Renewable Energy (EERE). 5Rented includes households that occupy their primary housing unit without payment of rent. ...

  7. appl_household2001.pdf

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

    Appliances Tables (Million U.S. Households; 60 pages, 240 kb) Contents Pages HC5-1a. Appliances by Climate Zone, Million U.S. Households, 2001 5 HC5-2a. Appliances by Year of Construction, Million U.S. Households, 2001 5 HC5-3a. Appliances by Household Income, Million U.S. Households, 2001 5 HC5-4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 5 HC5-5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 5 HC5-6a. Appliances by Type of Rented

  8. Fact #618: April 12, 2010 Vehicles per Household and Other Demographic

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

    Statistics | Department of Energy 8: April 12, 2010 Vehicles per Household and Other Demographic Statistics Fact #618: April 12, 2010 Vehicles per Household and Other Demographic Statistics Since 1969, the number of vehicles per household has increased by 66% and the number of vehicles per licensed driver has increased by 47%. The number of workers per household has changed the least of the statistics shown here. There has been a decline in the number of persons per household from 1969 to

  9. housingunit_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  10. appl_household2001.pdf

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

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  11. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  12. spaceheat_household2001.pdf

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

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  13. Household Vehicles Energy Consumption 1991

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

    Matching: A model-based procedure used to impute for item nonresponse. This method uses logistic models to compute predicted means that are used to statistically match each...

  14. Household Vehicles Energy Consumption 1991

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

    were imputed as disposed vehicles. To impute vehicle stock changes in the 1991 RTECS, logistic regression equations were used to compute a predicted probability (or propensity)...

  15. Household Vehicles Energy Consumption 1991

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

    a comparison between the 1991 and previous years RTECS designs; (2) the sample design; (3) the data-collection procedures; (4) the Vehicle Identification Number (VIN); (5)...

  16. Household Vehicles Energy Consumption 1994

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

    DC, October 1995), Table DL-1B. 5. "Chained dollars" is a measure used to express real prices. Real prices are those that have been adjusted to remove the effect of changes...

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

    Gasoline and Diesel Fuel Update (EIA)

    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

  18. Energy Information Administration - Energy Efficiency, energy...

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

    Efficiency Energy Efficiency energy consumption savings households, buildings, industry & vehicles The Energy Efficiency Page reflects EIA's information on energy efficiency and...

  19. Neutron resonance averaging

    SciTech Connect (OSTI)

    Chrien, R.E.

    1986-10-01

    The principles of resonance averaging as applied to neutron capture reactions are described. Several illustrations of resonance averaging to problems of nuclear structure and the distribution of radiative strength in nuclei are provided. 30 refs., 12 figs.

  20. 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 Eligible 617 2.7 1.10 Federally Ineligible 844 2.5 0.82 Below 100% Poverty Line 603 2.7 1.14 Source(s): 1,442 EIA, 2005 Residential Energy Consumption Survey: Household Energy Consumption and Expenditures Tables, Oct. 2008, Table US1 part2; EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price

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

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

    Transportation, 1984-2010 | Department of Energy 8: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 Fact #748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household expenditures for transportation was lower in 2010 than it was in 1984, reaching its lowest point in 2009 at 15.5%. In the early to mid-1980s when oil prices were high, gasoline and motor oil made up a larger share of transportation

  2. 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 Commercial Price Commercial Price - Local Distribution Companies Commerical Price - Marketers Commercial % Sold by Local Distribution Companies Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011

  3. Effect of Income on Appliances in U.S. Households, The

    Reports and Publications (EIA)

    2004-01-01

    Entails how people live, the factors that cause the most differences in home lifestyle, including energy use in geographic location, socioeconomics and household income.

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

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

    More Vehicles | Department of Energy 7: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles 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 households with three or more vehicles grew from 2% in 1960 to nearly 20% in 2010. Before 1990,

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

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

    Department of Energy 9: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles 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 that the primary vehicle travels in a day. In a six-vehicle household, the sixth vehicle travels fewer than five miles a day. Daily Vehicle

  6. 15th Annual DOE Small Business Forum and Expo | Department of Energy

    Energy Savers [EERE]

    Cooling #AskEnergySaver: Home Cooling July 24, 2014 - 11:13am Addthis Home cooling accounts for 6 percent of the average household's energy use. To help you save money by saving energy, our experts are answering your home cooling questions. | Photo courtesy of ©iStockphoto/JaniceRichard Home cooling accounts for 6 percent of the average household's energy use. To help you save money by saving energy, our experts are answering your home cooling questions. | Photo courtesy of

  7. ac_household2001.pdf

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

    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

  8. ac_household2001.pdf

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

    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

  9. ac_household2001.pdf

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

    2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.4 1.2 1.7 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 10.7 3.4 7.2 7.1 Air Conditioners Not Used ........................... 2.1 1.1 0.2 0.9 15.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 9.6 3.2

  10. ac_household2001.pdf

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

    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

  11. ac_household2001.pdf

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

    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

  12. ac_household2001.pdf

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

    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

  13. Loan Programs for Low- and Moderate-Income Households | Department of

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

    Energy Programs for Low- and Moderate-Income Households Loan Programs for Low- and Moderate-Income Households Better Buildings Residential Network Multifamily and Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014. Call Slides and Discussion Summary (919.64 KB) More Documents & Publications EcoHouse Program Overview Strengthening Relationships Between Energy Programs and Housing Programs Targeted Marketing and Program

  14. U.S. Energy Information Administration (EIA) - Data

    Gasoline and Diesel Fuel Update (EIA)

    Residential Energy Consumption Survey (RECS) Home energy use & costs Release Date: ... Household characteristics Home energy use & costs Detailed household microdata Commercial ...

  15. homeoffice_household2001.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State ...

  16. char_household2001.pdf

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

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... Income Relative to Poverty Line Below 100 Percent ...... 15.0 13.2 1.8 Q ...

  17. char_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Contact: Stephanie J. Battles, Survey Manager (stephanie.battles@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC2-1a. Household Characteristics by ...

  18. A Glance at China’s Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-01

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

  19. Shared Solar Projects Powering Households Throughout America | Department

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

    of Energy Shared Solar Projects Powering Households Throughout America Shared Solar Projects Powering Households Throughout America January 31, 2014 - 2:30pm Addthis Shared solar projects allow consumers to take advantage of solar energy’s myriad benefits, even though the system is not located on the consumer’s own rooftop. | Photo courtesy of the Vote Solar Initiative Shared solar projects allow consumers to take advantage of solar energy's myriad benefits, even though the system

  20. U.S. Energy Information Administration

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

    Colorado 2014 EIA reports and publications Colorado's average household energy costs ($1,551 per year) are 23% lower than the national average. Colorado was seventh in the nation in crude oil production with 7,785 barrels produced in December 2014. Colorado was ranked sixth in the nation in marketed natural gas production in 2013. Colorado's net electricity generation from solar increased 20% from 2012 to 2013. Colorado energy highlights: U.S. Crude Oil and Natural Gas Proved Reserves, 2013 * In

  1. Ventilation Behavior and Household Characteristics in NewCalifornia Houses

    SciTech Connect (OSTI)

    Price, Phillip N.; Sherman, Max H.

    2006-02-01

    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.

  2. Residential Network Members Impact More Than 42,000 Households | Department

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

    of Energy Impact More Than 42,000 Households Residential Network Members Impact More Than 42,000 Households Photo of a row of townhomes. Eligible Better Buildings Residential Network members reported completing 27,563 home energy upgrades during 2013 as part of the Residential Network's first reporting cycle. In addition, 13 Better Buildings Neighborhood Program partners completed 12,166 home energy upgrades, and six Home Performance with ENERGY STAR® Sponsors completed 2,540 home energy

  3. ac_household2001.pdf

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

    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

  4. ac_household2001.pdf

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

    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

  5. ac_household2001.pdf

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

    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

  6. homeoffice_household2001.pdf

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

    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

  7. homeoffice_household2001.pdf

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

    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

  8. homeoffice_household2001.pdf

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

    2a. Home Office Equipment by West Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Households Using Office Equipment ......................................... 96.2 21.4 6.2 15.2 1.0 Personal Computers 1 ................................. 60.0 14.3 4.0 10.4 3.7 Number of

  9. homeoffice_household2001.pdf

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

    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

  10. homeoffice_household2001.pdf

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

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State income

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

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

    Household Expenditures on Transportation, 1984-2010 Fact 748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household ...

  12. Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics

    SciTech Connect (OSTI)

    Brian C. O'Neill

    2006-08-09

    This report describes results of the research project on "Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics". The overall objective of this project was to improve projections of energy demand and associated greenhouse gas emissions by taking into account demographic factors currently not incorporated in Integrated Assessment Models (IAMs) of global climate change. We proposed to examine the potential magnitude of effects on energy demand of changes in the composition of populations by household characteristics for three countries: the U.S., China, and Indonesia. For each country, we planned to analyze household energy use survey data to estimate relationships between household characteristics and energy use; develop a new set of detailed household projections for each country; and combine these analyses to produce new projections of energy demand illustrating the potential importance of consideration of households.

  13. Buildings and Energy in the 1980s

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

    No. PB83-199554, 220. Residential Energy Consumption Survey: Household Transportation Panel Monthly Gas Purchases and Vehicle and Household Characteristics, 679-981; Order...

  14. Buildings and Energy in the 1980s

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

    conducted in two stages: (1) A Household (RECS)Building (CBECS) Survey and an Energy Suppliers Survey. The HouseholdBuilding Characteristics Survey consists of personal...

  15. Household heating bills expected to be lower this winter

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

    Household heating bills expected to be lower this winter U.S. consumers are expected to pay less this winter on their home heating bills because of lower oil and natural gas prices and projected milder temperatures than last winter. In its new forecast, the U.S. Energy Information Administration said households that rely on heating oil which are mainly located in the Northeast will pay the lowest heating expenditures in 9 years down 25% from last winter as consumers are expected to save about

  16. ac_household2001.pdf

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

    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

  17. homeoffice_household2001.pdf

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

    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

  18. Appliance Commitment for Household Load Scheduling

    SciTech Connect (OSTI)

    Du, Pengwei; Lu, Ning

    2011-06-30

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

  19. appl_household2001.pdf

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

    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

  20. Reynolds-Averaged Navier-Stokes

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Reynolds-Averaged Navier-Stokes simulation of the heave performance of a two-body floating-point absorber wave energy system Yi-Hsiang Yu, Ye Li ⇑ National Wind Technology Center, National Renewable Energy Laboratory (NREL), Golden, CO 80401, USA a r t i c l e i n f o Article history: Received 7 September 2011 Received in revised form 5 August 2012 Accepted 9 October 2012 Available online 17 October 2012 Keywords: Wave energy conversion Heave Computational Fluid Dynamics Reynolds-averaged

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

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

    ... 30.8 25.1 28.9 42.6 27.1 Q Q Q 25.2 31.8 23.3 13.7 Below Poverty Line 100 Percent ... 16.6 15.4 16.2 19.5 12.8 Q...

  2. appl_household2001.pdf

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

    0a. Appliances by Midwest Census Region, Million U.S. Households, 2001 Appliance Types and 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 1.5 Total .............................................................. 107.0 24.5 17.1 7.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 23.8 16.6 7.2 NE 1

  3. appl_household2001.pdf

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

    1a. Appliances by South Census Region, Million U.S. Households, 2001 Appliance Types and 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 1.4 1.5 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 36.2 19.4 6.4 10.3 1.5 1

  4. appl_household2001.pdf

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

    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

  5. appl_household2001.pdf

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

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

  6. appl_household2001.pdf

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

    6a. Appliances by Type of Rented Housing Unit, Million U.S. Households, 2001 Appliance Types and 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 Kitchen Appliances Cooking Appliances Oven ........................................... 33.4 10.1 7.3 14.9 1.1

  7. appl_household2001.pdf

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

    8a. Appliances by Urban/Rural Location, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.9 1.4 1.2 1.3 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 47.5 17.5 19.9 16.8 4.2 1

  8. appl_household2001.pdf

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

    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

  9. homeoffice_household2001.pdf

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

    2001 Home Office Equipment 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 Households Using Office Equipment ......................................... 96.2 6.2 11.4 6.7 5.9 1.7 Personal Computers 1 ................................. 60.0 3.4 7.9 4.1 3.8 4.4 Number of Desktop PCs 1

  10. spaceheat_household2001.pdf

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

    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

  11. spaceheat_household2001.pdf

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

    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

  12. spaceheat_household2001.pdf

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

    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

  13. spaceheat_household2001.pdf

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

    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

  14. spaceheat_household2001.pdf

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

    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

  15. spaceheat_household2001.pdf

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

    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

  16. spaceheat_household2001.pdf

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

    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

  17. Household Vehicles Energy Use: Latest Data & Trends

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

    fuel, diesel motor fuel, electric, and natural gas, excluding propane because NHTSA's CAFE program does not track these vehicles. See Gasoline, Gasohol, Unleaded Gasoline, Leaded...

  18. Household Vehicles Energy Use: Latest Data & Trends

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

    vehicle type, and vehicle model year. "600" - represents a "match" based on EIA expert analysis using subject matter experience, in conjunction with past RTECS. Additionally,...

  19. Household Vehicles Energy Use: Latest Data & Trends

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

    Laboratory (ORNL), Engineering Science Technology Division, Center for Transportation Analysis. For 1,262 vehicles, the work conducted by ORNL did not result in a viable annual VMT...

  20. Household Vehicles Energy Use: Latest Data & Trends

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

    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...

  1. DOE/EIA-032171(84) Energy Information Administration Residential...

    Gasoline and Diesel Fuel Update (EIA)

    it was used to screen households for participation in the Household Transportation Panel. 190 1984 RECS: Consumption and Expenditures, National Data Energy Information...

  2. DOE/EIA-0516(85) Energy Information Administration Manufacturing...

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

    Order No. PB83- 199554HAA Residential Energy Consumption Survey: HouseholdTransportation Panel Monthly Gas Purchases and Vehicle and Household Characteristics, 6179-9181 * Order...

  3. STILE | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    Department of Energy The average American household spends nearly $2,000 per year on energy used in the home, $200 to $400 of which could be paying for wasted energy due to drafts, air leaks around openings, and outdated heating and cooling systems. What statistics fail to convey is the feeling of not wanting to remove your coat when you walk in the door, the dread of stepping onto cold tile in the morning, and your dismay as you crank the thermostat and try not to think of what your next

  4. Property:SalinityAverage | Open Energy Information

    Open Energy Info (EERE)

    + B Beowawe Hot Springs Geothermal Area + 700 + Blue Mountain Geothermal Area + 4,300 + Brady Hot Springs Geothermal Area + 3,500 + Bruchsal Geothermal Area + 100,000 + C Chena...

  5. Junior Energy | Open Energy Information

    Open Energy Info (EERE)

    York Zip: 10003 Product: New York-based organization working with schools to teach children about practical ways to save energy in their own households and neighborhoods....

  6. Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    5 1 October 2015 Short-Term Energy and Winter Fuels Outlook (STEO) Highlights  EIA projects average U.S. household expenditures for natural gas, heating oil, and propane during the upcoming winter heating season (October 1 through March 31) will be 10%, 25%, and 18% lower, respectively, than last winter, because of lower fuel prices and lower heating demand. Forecast lower heating demand and relatively unchanged prices contribute to electricity expenditures that are 3% lower than last winter

  7. appl_household2001.pdf

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

    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

  8. appl_household2001.pdf

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

    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

  9. spaceheat_household2001.pdf

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

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

  10. spaceheat_household2001.pdf

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

    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

  11. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book [EERE]

    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

  12. Fact #616: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose

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

    | Department of Energy 6: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose Fact #616: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose In 2009, getting to and from work accounted for about 27% of household vehicle-miles of travel (VMT). Work-related business was 8.4% of VMT in 2001, but declined to 6.7% in 2009, possibly due to advancements in computing technology making it possible for more business to be handled electronically. VMT for shopping was almost

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

    Gasoline and Diesel Fuel Update (EIA)

    Energy Usage The 1997 Residential Energy Consumption Survey (RECS) collected household energy data for the four most populated States: California, Florida, New York, and Texas. ...

  14. Kingston Creek Hydro Project Powers 100 Households | Department...

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

    Kingston Creek Hydro Project Powers 100 Households Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada ...

  15. Loan Programs for Low- and Moderate-Income Households | Department...

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

    Programs for Low- and Moderate-Income Households Loan Programs for Low- and Moderate-Income Households Better Buildings Residential Network Multifamily and Low-Income Housing Peer ...

  16. 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...

  17. High average power pockels cell

    DOE Patents [OSTI]

    Daly, Thomas P.

    1991-01-01

    A high average power pockels cell is disclosed which reduces the effect of thermally induced strains in high average power laser technology. The pockels cell includes an elongated, substantially rectangular crystalline structure formed from a KDP-type material to eliminate shear strains. The X- and Y-axes are oriented substantially perpendicular to the edges of the crystal cross-section and to the C-axis direction of propagation to eliminate shear strains.

  18. HIGH AVERAGE POWER OPTICAL FEL AMPLIFIERS.

    SciTech Connect (OSTI)

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

    2005-08-21

    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.

  19. Search results | Department of Energy

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

    with household appliances, transportation, and their own bodies. However, the nature of energy, energy transformations, and energy conservation are poorly understood, even...

  20. STEO January 2013 - average gasoline prices

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

    drivers to see lower average gasoline prices in 2013 and 2014 U.S. retail 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 to $3.44 this year and then drop to $3.34 in 2014, according to the new forecast from the U.S. Energy Information Administration. Expected lower crude oil prices.....which accounted for about two-thirds of the price of gasoline in 2012....will

  1. Residential Energy Efficiency Demonstration: Hawaii and Guam Energy Improvement Technology Demonstration Project

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    questionnaires 0 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total 81.6 65.3 142.5 38 17 30.3 11 625 0.29 500 178 Census Region and Division

  2. "Variable","Average Absolute Percent Differences","Percent of...

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

    Annual Energy Outlook Retrospective Review, 2014" "Variable","Average Absolute Percent Differences","Percent of Projections Over- Estimated" "Gross Domestic Product" "Real Gross ...

  3. ,"Housing Units1","Average Square Footage Per Housing Unit",...

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

    ... includes households that occupy their primary housing unit without payment of rent. ... includes households that occupy their primary housing unit without payment of rent. ...

  4. Variable Average Absolute Percent Differences

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

    Variable Average Absolute Percent Differences Percent of Projections Over- Estimated Gross Domestic Product Real Gross Domestic Product (Average Cumulative Growth)* (Table 2) 0.9 45.8 Petroleum Imported Refiner Acquisition Cost of Crude Oil (Constant $) (Table 3a) 37.7 17.3 Imported Refiner Acquisition Cost of Crude Oil (Nominal $) (Table 3b) 36.6 18.7 Total Petroleum Consumption (Table 4) 7.9 70.7 Crude Oil Production (Table 5) 8.1 51.1 Petroleum Net Imports (Table 6) 24.7 73.8 Natural Gas

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

    SciTech Connect (OSTI)

    Lin, Jiang

    2006-07-10

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

  6. Residential energy consumption survey: consumption and expenditures, April 1982-March 1983. Part 1, national data

    SciTech Connect (OSTI)

    Thompson, W.

    1984-11-01

    This report presents data on the US consumption and expenditures for residential use of natural gas, electricity, fuel oil or kerosene, and liquefied petroleum gas (LPG) from April 1982 through March 1983. Data on the consumption of wood for this period are also presented. The consumption and expenditures data are based on actual household bills, obtained, with the permission of the household. from the companies supplying energy to the household. Data on wood consumption are based on respondent recall of the amount of wood burned during the winter and are subject to memory errors and other reporting errors described in the report. These data come from the 1982 Residential Energy Consumption Survey (RECS), the fifth in a series of comparable surveys beginning in 1978. The 1982 survey is the first survey to include, as part of its sample, a portion of the same households interviewed in the 1980 survey. A separate report is planned to report these longitudinal data. This summary gives the highlights of a comparison of the findings for the 5 years of RECS data. The data cover all types of housing units in the 50 states and the District of Columbia including single-family units, apartments, and mobile homes. For households with indirect energy costs, such as costs that are included in the rent or paid by third parties, the sonsumption and expenditures data are estimated and included in the figures reported here. The average household consumption of natural gas, electricity, fuel oil or kerosene, and LPG dropped in 1982 from the previous year, hitting a 5-year low since the first Residential Energy Consumption Survey (RECS) was conducted in 1978. The average consumption was 103 (+-3) million Btu per household in 1982, down from 114 (+-) million Btu in 1981. The weather was the main contributing factor. 8 figures, 46 tables.

  7. GTZ Global Energy Program | Open Energy Information

    Open Energy Info (EERE)

    to households, SME and public utility institutions. Key products include access to modern energy services and promotion of new technologies. References "GTZ projects"...

  8. New applications for high average power beams

    SciTech Connect (OSTI)

    Neau, E.L.; Turman, B.N.; Patterson, E.L.

    1993-08-01

    The technology base formed by the development of high peak power simulators, laser drivers, FEL`s, and ICF drivers from the early 60`s through the late 80`s is being extended to high average power short-pulse machines with the capabilities of supporting new types of manufacturing processes and performing new roles in environmental cleanup applications. This paper discusses a process for identifying and developing possible commercial applications, specifically those requiring very high average power levels of hundreds of kilowatts to perhaps megawatts. The authors discuss specific technology requirements and give examples of application development efforts. The application development work is directed at areas that can possibly benefit from the high specific energies attainable with short pulse machines.

  9. EERE Success Story-Kingston Creek Hydro Project Powers 100 Households |

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

    Department of Energy Kingston Creek Hydro Project Powers 100 Households EERE Success Story-Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada Controls, LLC used a low-interest loan from the Nevada State Office of Energy's Revolving Loan Fund to help construct a hydropower project in the small Nevada town of Kingston. The Kingston Creek Project-benefitting the Young Brothers Ranch-is a 175-kilowatt hydro generation plant

  10. Marginal Energy Prices - RECS97 Update

    Broader source: Energy.gov (indexed) [DOE]

    Marginal Energy Prices - RECS97 Update The original estimation of residential marginal energy prices at the individual household level (as reported in the Marginal Energy Prices ...

  11. Search results | Department of Energy

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

    counted and priced. They measure and evaluate energy use and cost of representative household and school electrical items. http:energy.goveereeducationdownloads...

  12. Home Energy Saver v.2.0

    Energy Science and Technology Software Center (OSTI)

    2008-09-01

    A web-based residential energy calculator. Provides customized estimates of residential energy use, energy bills, and CO2 emissions, based on building description information provided by the user. Energy use is estimated by end-use and device, using engineering models. Space heating and cooling use is based on the DOE-2.1E building simulation model. Other end-uses (water heating, appliances, lighting, and miscellaneous equipment) are based on engineering models developed by LBNL. Users can estimate their household carbon footprint andmore » compare it to average vaules for their neighborhood and other regions, displayed using the Google Maps API. Energy bills can be calculated using either average energy price data or actual utility tariffs (including time-of-use) contained in the LBNL Tariff Analysis Project (TAP). HES includes a link to the TAP energy bill calculator web service. The HES software also includes extensive default input data for required user inputs.« less

  13. Transferring 2001 National Household Travel Survey

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim; Schmoyer, Richard L; Chin, Shih-Miao

    2007-05-01

    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

  14. A Green's function quantum average atom model

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Starrett, Charles Edward

    2015-05-21

    A quantum average atom model is reformulated using Green's functions. This allows integrals along the real energy axis to be deformed into the complex plane. The advantage being that sharp features such as resonances and bound states are broadened by a Lorentzian with a half-width chosen for numerical convenience. An implementation of this method therefore avoids numerically challenging resonance tracking and the search for weakly bound states, without changing the physical content or results of the model. A straightforward implementation results in up to a factor of 5 speed-up relative to an optimized orbital based code.

  15. Lighting Choices to Save You Money | Department of Energy

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

    Lighting Choices to Save You Money Lighting Choices to Save You Money This Energy 101 video explores the different lighting options available to consumers. Light your home using the same amount of light for less money. An average household dedicates about 5% of its energy budget to lighting. Switching to energy-efficient lighting is one of the fastest ways to cut your energy bills. By replacing your home's five most frequently used light fixtures or bulbs with models that have earned the ENERGY

  16. Households to pay more than expected to stay warm this winter

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

    Households to pay more than expected to stay warm this winter Following a colder-than-expected November, U.S. households are forecast to consume more heating fuels than previously expected....resulting in higher heating bills. Homeowners that rely on natural gas will see their total winter expenses rise nearly 13 percent from last winter....while users of electric heat will see a 2.6 percent increase in costs. That's the latest forecast from the U.S. Energy Information Administration. Propane

  17. The changing character of household waste in the Czech Republic between 1999 and 2009 as a function of home heating methods

    SciTech Connect (OSTI)

    Dolealov, Markta; Beneov, Libue; Zvodsk, Anita

    2013-09-15

    Highlights: The character of household waste in the three different types of households were assesed. The quantity, density and composition of household waste were determined. The physicochemical characteristics were determined. The changing character of household waste during past 10 years was described. The potential of energy recovery of household waste in Czech republic was assesed. - Abstract: The authors of this paper report on the changing character of household waste, in the Czech Republic between 1999 and 2009 in households differentiated by their heating methods. The data presented are the result of two projects, financed by the Czech Ministry of Environment, which were undertaken during this time period with the aim of focusing on the waste characterisation and complete analysis of the physicochemical properties of the household waste. In the Czech Republic, the composition of household waste varies significantly between different types of households based on the methods of home heating employed. For the purposes of these studies, the types of homes were divided into three categories urban, mixed and rural. Some of the biggest differences were found in the quantities of certain subsample categories, especially fine residue (matter smaller than 20 mm), between urban households with central heating and rural households that primarily employ solid fuel such coal or wood. The use of these solid fuels increases the fraction of the finer categories because of the higher presence of ash. Heating values of the residual household waste from the three categories varied very significantly, ranging from 6.8 MJ/kg to 14.2 MJ/kg in 1999 and from 6.8 MJ/kg to 10.5 MJ/kg in 2009 depending on the type of household and season. The same factors affect moisture of residual household waste which varied from 23.2% to 33.3%. The chemical parameters also varied significantly, especially in the quantities of Tl, As, Cr, Zn, Fe and Mn, which were higher in rural

  18. Residential Energy Consumption Survey: Housing Characteristics...

    Gasoline and Diesel Fuel Update (EIA)

    either air or liquid as the working fluid. It does not refer :<: passive collection of solar thermal energy. Fuel Oil Paid by Household: The household paid directly to the fuel...

  19. Lincoln Electric System (Residential)- 2015 Sustainable Energy Program

    Broader source: Energy.gov [DOE]

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

  20. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  1. Table HC1.1.2 Housing Unit Characteristics by Average Floorspace, 2005

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

    2 Housing Unit Characteristics by Average Floorspace, 2005 " ,,"Average Square Feet per--" ," Housing Units (millions)" ,,"Housing Unit",,,"Household Member" "Housing Unit Characteristics",,"Total1","Heated","Cooled","Total","Heated","Cooled" "Total",111.1,2171,1618,1031,845,630,401 "Census Region and Division" "Northeast",20.6,2334,1664,562,911,649,220

  2. Accelerating Clean Energy Adoption (Fact Sheet), Weatherization...

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

    Through efforts like the Weatherization Assistance Program (WAP), the State Energy Program ... Other non-energy benefits to ratepayers, households, and communities comprise the ...

  3. 2014 Renewable Energy Markets (REM) Conference

    Broader source: Energy.gov [DOE]

    Renewable Energy Markets (REM) is the clean energy industry's most important annual event focused on the states, businesses, organizations, and households that choose clean, renewable electricity...

  4. IMAT SpA | Open Energy Information

    Open Energy Info (EERE)

    33074 Sector: Renewable Energy, Solar Product: Italy-based company specializing in manufacturing of components for household refrigeration. Their main renewable energy focus is...

  5. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book [EERE]

    9 Northeast Midwest South West National Space Heating 70.3 56.6 20.4 23.8 38.7 Space Cooling 3.6 5.6 13.9 4.0 7.9 Water Heating 21.1 20.4 15.8 21.2 19.0 Refrigerator 5.4 7.0 6.6 5.7 6.3 Other Appliances & Lighting 23.0 25.9 25.0 24.1 24.7 Total (1) 79.9 77.4 95.0 Note(s): Source(s): 2005 Delivered Energy End-Uses for an Average Household, by Region (Million Btu per Household) 122.2 113.5 1) Due to rounding, sums do not add up to totals. EIA, 2005 Residential Energy Consumption Survey, Oct.

  6. Nepal-GTZ Energy Efficiency Program | Open Energy Information

    Open Energy Info (EERE)

    1 GTZ is working with Nepal on integration of EE as part of the national energy strategy, development of EE measures for households. References "GTZ projects" Retrieved...

  7. Pakistan-GTZ Renewable Energy and Energy Efficiency Promotion...

    Open Energy Info (EERE)

    is working with Pakistan on improvement of energy service supply to households and enterprises through RE use and EE. References "GTZ projects" Retrieved from "http:...

  8. Energy Trust of Oregon Inc | Open Energy Information

    Open Energy Info (EERE)

    Product: Gives grants for the implementation of efficiency improvements and renewable energy sources at a household and utility-scale level. Coordinates: 45.511795,...

  9. MEASUREMENT OF THE AVERAGE ENERGY AND MULTIPLICITY OF PROMPT-FISSION-NEUTRONS FROM 238U(n,f) AND 237 Np(n,f) FROM 1 TO 200 MeV.

    SciTech Connect (OSTI)

    TAIEB,J.; GRANIER, T.; ETHVIGNOT, T.; DEVLIN, M.; HAIGHT, R.C.; NELSON, R.O.; ODONNELL, J.M.; ROCHMAN, D.

    2007-06-28

    Taking advantage of the neutron source of the LANCSE, it has been possible to obtain a measure of the velocity distribution and the number of prompt-neutrons emitted in the neutron-induced fission of {sup 238}U and {sup 237}Np over a broad incident neutron energy range. The mean kinetic energy was extracted and is shown as the function of the incident-neutron energy. We confirm here the observation, for both reactions, of a dip around the second chance fission which is explained by the lower kinetic energy of the pre-fission neutrons. Such a observation is reproduced by Los Alamos model as implemented at Bruyeres le Chatel and by the Maslov model. As far as the neutron multiplicity is concerned, a similar dip is observed. However, such a behavior is not present in data measured by other groups.

  10. Search results | Department of Energy

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

    an abstract concept that is very familiar to students from personal experiences with household appliances, transportation, and their own bodies. However, the nature of energy,...

  11. Search results | Department of Energy

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

    Students learn how electrical usage is counted and priced. They measure and evaluate energy use and cost of representative household and school electrical items. http:...

  12. Fact #870: April 27, 2015 Corporate Average Fuel Economy Progress,

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

    1978-2014 - Dataset | Department of Energy 0: April 27, 2015 Corporate Average Fuel Economy Progress, 1978-2014 - Dataset Fact #870: April 27, 2015 Corporate Average Fuel Economy Progress, 1978-2014 - Dataset Excel file and dataset for Corporate Average Fuel Economy Progress, 1978-2014 fotw#870_web.xlsx (17.92 KB) More Documents & Publications Reactor Pressure Vessel Task of Light Water Reactor Sustainability Program: Milestone Report on Materials and Machining of Specimens for the ATR-2

  13. " Million U.S. Housing Units" ,,"2005 Household...

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

    8 Water Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ... to 79,999","80,000 or More" "Water Heating Characteristics" ...

  14. Fact #744: September 10, 2012 Average New Light Vehicle Price Grows Faster

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

    than Average Used Light Vehicle Price | Department of Energy 4: September 10, 2012 Average New Light Vehicle Price Grows Faster than Average Used Light Vehicle Price Fact #744: September 10, 2012 Average New Light Vehicle Price Grows Faster than Average Used Light Vehicle Price In 2011 the average used light vehicle price was 36% higher than in 1990, while the average new light vehicle price was 67% higher than it was in 1990. The average price of a used vehicle had been between $6,000 and

  15. Average and effective Q-values for fission product average (n...

    Office of Scientific and Technical Information (OSTI)

    Average and effective Q-values for fission product average (n,2n) and (n,3n) reaction cross sections Citation Details In-Document Search Title: Average and effective Q-values for ...

  16. Average and effective Q-values for fission product average (n...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Average and effective Q-values for fission product average (n,2n) and (n,3n) reaction cross sections Citation Details In-Document Search Title: Average and ...

  17. ,"Selected National Average Natural Gas Prices"

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

    Selected National Average Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data ...

  18. The New Energy Future in Indian Country: Confronting Climate Change, Creating Jobs, and Conserving Nature

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

    NEW ENERGY FUTURE IN INDIAN COUNTRY: Confr onting Climate Change, Cr eating J obs, and Conser ving Natur e N A T I O N A L W I L D L I F E F E D E R A T I O N 2 0 1 0 * On average, Tribal households pay significantly more in home energy expenses than other Americans. Most utilities are solely owned and operated by non-Tribal entities, so the money paid to energy providers immediately leaves tribal communities. THE NEW ENERGY FUTURE IN INDIAN COUNTRY * The infrastructure and revenue streams

  19. The New Energy Future in Indian Country: Confronting Climate Change, Creating Jobs, and Conserving Nature

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

    THE NEW ENERGY FUTURE IN INDIAN COUNTRY: Confronting Climate Change, Creating Jobs, and Conserving Nature N A T I O N A L W I L D L I F E F E D E R A T I O N 2 0 1 0 * On average, Tribal households pay significantly more in home energy expenses than other Americans. Most utilities are solely owned and operated by non-Tribal entities, so the money paid to energy providers immediately leaves tribal communities. THE NEW ENERGY FUTURE IN INDIAN COUNTRY * The infrastructure and revenue streams

  20. Dynamic Multiscale Averaging (DMA) of Turbulent Flow

    SciTech Connect (OSTI)

    Richard W. Johnson

    2012-09-01

    A new approach called dynamic multiscale averaging (DMA) for computing the effects of turbulent flow is described. The new method encompasses multiple applications of temporal and spatial averaging, that is, multiscale operations. Initially, a direct numerical simulation (DNS) is performed for a relatively short time; it is envisioned that this short time should be long enough to capture several fluctuating time periods of the smallest scales. The flow field variables are subject to running time averaging during the DNS. After the relatively short time, the time-averaged variables are volume averaged onto a coarser grid. Both time and volume averaging of the describing equations generate correlations in the averaged equations. These correlations are computed from the flow field and added as source terms to the computation on the next coarser mesh. They represent coupling between the two adjacent scales. Since they are computed directly from first principles, there is no modeling involved. However, there is approximation involved in the coupling correlations as the flow field has been computed for only a relatively short time. After the time and spatial averaging operations are applied at a given stage, new computations are performed on the next coarser mesh using a larger time step. The process continues until the coarsest scale needed is reached. New correlations are created for each averaging procedure. The number of averaging operations needed is expected to be problem dependent. The new DMA approach is applied to a relatively low Reynolds number flow in a square duct segment. Time-averaged stream-wise velocity and vorticity contours from the DMA approach appear to be very similar to a full DNS for a similar flow reported in the literature. Expected symmetry for the final results is produced for the DMA method. The results obtained indicate that DMA holds significant potential in being able to accurately compute turbulent flow without modeling for practical

  1. Video game console usage and US national energy consumption: Results from a field-metering study

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Desroches, Louis-Benoit; Greenblatt, Jeffery B.; Pratt, Stacy; Willem, Henry; Claybaugh, Erin; Beraki, Bereket; Nagaraju, Mythri; Price, Sarah K.; Young, Scott J.; Donovan, Sally M.; et al

    2014-10-23

    There has been an increased in attention placed on the energy consumption of miscellaneous electronic loads in buildings by energy analysts and policymakers in recent years. The share of electricity consumed by consumer electronics in US households has increased in the last decade. Many devices, however, lack robust energy use data, making energy consumption estimates difficult and uncertain. Video game consoles are high-performance machines present in approximately half of all households and can consume a considerable amount of power. The precise usage of game consoles has significant uncertainty, however, leading to a wide range of recent national energy consumption estimates.more » We present here an analysis based on field-metered usage data, collected as part of a larger field metering study in the USA. This larger study collected data from 880 households in 2012 on a variety of devices, including 113 game consoles (the majority of which are Generation 7 consoles). From our metering, we find that although some consoles are left on nearly 24 h/day, the overall average usage is lower than many other studies have assumed, leading to a US national energy consumption estimate of 7.1 TWh in 2012. Nevertheless, there is an opportunity to reduce energy use with proper game console power management, as a substantial amount of game console usage occurs with the television turned off. The emergence of Generation 8 consoles may increase national energy consumption.« less

  2. Video game console usage and US national energy consumption: Results from a field-metering study

    SciTech Connect (OSTI)

    Desroches, Louis-Benoit; Greenblatt, Jeffery B.; Pratt, Stacy; Willem, Henry; Claybaugh, Erin; Beraki, Bereket; Nagaraju, Mythri; Price, Sarah K.; Young, Scott J.; Donovan, Sally M.; Ganeshalingam, Mohan

    2014-10-23

    There has been an increased in attention placed on the energy consumption of miscellaneous electronic loads in buildings by energy analysts and policymakers in recent years. The share of electricity consumed by consumer electronics in US households has increased in the last decade. Many devices, however, lack robust energy use data, making energy consumption estimates difficult and uncertain. Video game consoles are high-performance machines present in approximately half of all households and can consume a considerable amount of power. The precise usage of game consoles has significant uncertainty, however, leading to a wide range of recent national energy consumption estimates. We present here an analysis based on field-metered usage data, collected as part of a larger field metering study in the USA. This larger study collected data from 880 households in 2012 on a variety of devices, including 113 game consoles (the majority of which are Generation 7 consoles). From our metering, we find that although some consoles are left on nearly 24 h/day, the overall average usage is lower than many other studies have assumed, leading to a US national energy consumption estimate of 7.1 TWh in 2012. Nevertheless, there is an opportunity to reduce energy use with proper game console power management, as a substantial amount of game console usage occurs with the television turned off. The emergence of Generation 8 consoles may increase national energy consumption.

  3. U.S. Department of Energy, Energy Information Administration...

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

    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...

  4. U.S. Department of Energy, Energy Information Administration...

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

    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...

  5. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses. The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  6. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

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

    SciTech Connect (OSTI)

    Herendeen, R.A.

    1983-06-01

    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.

  8. Property-Assessed Clean Energy (PACE) Financing Resources | Department...

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

    ... PACE on community adoption rates of energy efficiency improvements and per household energy consumption, and various program design strategies, and effectiveness of PACE relative ...

  9. U.S. Energy Information Administration (EIA) - Ap

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Consumption & Efficiency view all Residential Energy Consumption Survey Household end ... U. S. States & Countries State Energy Profiles State level data, analysis, and maps ...

  10. Appliance Standby Power and Energy Consumption in South African...

    Open Energy Info (EERE)

    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...