National Library of Energy BETA

Sample records for average household expenditure

  1. 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 ...

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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 ...

  10. Fact #638: August 30, 2010 Average Expenditure for a New Car Declines in

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

    Relation to Family Earnings | Department of Energy 8: August 30, 2010 Average Expenditure for a New Car Declines in Relation to Family Earnings Fact #638: August 30, 2010 Average Expenditure for a New Car Declines in Relation to Family Earnings Although the average expenditure for a new car has increased from 1967 to 2009, family earnings have also been on the rise. For this period, new car expenditures went from $3,216 to $23,186, while median family earnings went from $7,933 to $77,149.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-06-01

    In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

  16. 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

  17. 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...

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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.

  3. Minority Transportation Expenditure Allocation Model

    Energy Science and Technology Software Center (OSTI)

    1993-04-12

    MITRAM (Minority TRansportation expenditure Allocation Model) can project various transportation related attributes of minority (Black and Hispanic) and majority (white) populations. The model projects vehicle ownership, vehicle miles of travel, workers, new car and on-road fleet fuel economy, amount and share of household income spent on gasoline, and household expenditures on public transportation and taxis. MITRAM predicts reactions to sustained fuel price changes for up to 10 years after the change.

  4. 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.

  5. 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.

  6. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    0 2005 Energy End-Use Expenditures for an Average Household, by Region ($2010) Northeast Midwest South West National Space Heating 1,050 721 371 352 575 Air-Conditioning 199 175 456 262 311 Water Heating 373 294 313 318 320 Refrigerators 194 145 146 154 157 Other Appliances and Lighting 827 665 715 716 725 Total (1) 2,554 1,975 1,970 1,655 2,003 Note(s): 1) Due to rounding, end-uses do not sum to totals. Source(s): EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table US-15; EIA,

  7. ,"Total Fuel Oil Expenditures

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

    A. Fuel Oil Expenditures by Census Region for All Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per...

  8. ,"Total Fuel Oil Expenditures

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

    . Fuel Oil Expenditures by Census Region for Non-Mall Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per...

  9. ,"Total Fuel Oil Expenditures

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

    4. Fuel Oil Expenditures by Census Region, 1999" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per Square Foot"...

  10. 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.

  11. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    5 2005 Households and Energy Expenditures, by Income Level ($2010) Energy Expenditures by Household Income Households (millions) Household Less than $10,000 9.9 9% $10,000 to $14,999 8.5 8% $15,000 to $19,999 8.4 8% $20,000 to $29,999 15.1 14% $30,000 to $39,999 13.6 12% $40,000 to $49,999 11.0 10% $50,000 to $74,999 19.8 18% $75,000 to $99,999 10.6 10% $100,000 or more 14.2 13% Total 111.1 100% Note(s): Source(s): 7% 1) See Table 2.3.15 for more on energy burdens. 2) A household is defined as a

  12. 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

  13. 2009 Energy Expenditure Per Person | Department of Energy

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

    Energy Expenditure Per Person 2009 Energy Expenditure Per Person 2009 Energy Expenditure Per Person...

  14. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    9 Average Annual Energy Expenditures per Household, by Year ($2010) Year 1980 1,991 1981 1,981 1982 2,058 1983 2,082 1984 2,067 1985 2,012 1986 1,898 1987 1,846 1988 1,849 1989 1,848 1990 1,785 1991 1,784 1992 1,729 1993 1,797 1994 1,772 1995 1,727 1996 1,800 1997 1,761 1998 1,676 1999 1,659 2000 1,824 2001 1,900 2002 1,830 2003 1,978 2004 2,018 2005 2,175 2006 2,184 2007 2,230 2008 2,347 2009 2,173 2010 2,201 2011 2,185 2012 2,123 2013 2,056 2014 2,032 2015 2,030 2016 2,007 2017 1,992 2018

  15. 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).

  16. 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).

  17. 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....

  18. Buildings Energy Data Book: 3.3 Commercial Sector Expenditures

    Buildings Energy Data Book [EERE]

    0 2003 Energy Expenditures per Square Foot of Commercial Floorspace, by Vintage ($2010) Vintage $/SF Prior to 1960 1.44 1960 to 1969 1.70 1970 to 1979 1.88 1980 to 1989 2.09 1990 to 1999 1.88 2000 to 2003 1.72 Average 1.77 Source(s): EIA, 2003 Commercial Buildings Energy Consumption and Expenditures: Consumption and Expenditures Tables, Table C4; and EIA, Annual Energy Review 2010, Aug. 2011, Appendix D, p. 353 for price deflators

  19. Commercial Buildings Energy Consumption and Expenditures 1992...

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

    1992 Consumption and Expenditures 1992 Consumption & Expenditures Overview Full Report Tables National estimates of electricity, natural gas, fuel oil, and district heat...

  20. Electricity",,,"Electricity Consumption",,,"Electricity Expenditures...

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

    C9. Total Electricity Consumption and Expenditures, 1999" ,"All Buildings Using Electricity",,,"Electricity Consumption",,,"Electricity Expenditures" ,"Number of Buildings...

  1. Electricity",,,"Electricity Consumption",,,"Electricity Expenditures...

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

    DIV. Total Electricity Consumption and Expenditures by Census Division, 1999" ,"All Buildings Using Electricity",,,"Electricity Consumption",,,"Electricity Expenditures" ,"Number...

  2. ,"Fuel Oil Consumption",,,"Fuel Oil Expenditures"

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

    4. Fuel Oil Consumption and Expenditure Intensities for Non-Mall Buildings, 2003" ,"Fuel Oil Consumption",,,"Fuel Oil Expenditures" ,"per Building (gallons)","per Square Foot...

  3. ,"Fuel Oil Consumption",,,"Fuel Oil Expenditures"

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

    2. Fuel Oil Consumption and Expenditure Intensities, 1999" ,"Fuel Oil Consumption",,,"Fuel Oil Expenditures" ,"per Building (gallons)","per Square Foot (gallons)","per Worker...

  4. 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

  5. Buildings Energy Data Book: 1.2 Building Sector Expenditures

    Buildings Energy Data Book [EERE]

    4 FY 2007 Federal Buildings Energy Prices and Expenditures, by Fuel Type ($2010) Fuel Type Electricity (1) Natural Gas Fuel Oil Coal Purchased Steam LPG/Propane Other Average Total Note(s): Source(s): 17.05 6028.63 Prices and expenditures are for Goal-Subject buildings. 1) $0.0776/kWh. 2) Energy used in Goal-Subject buildings in FY 2007 accounted for 33.8% of the total Federal energy bill. DOE/FEMP, Annual Report to Congress on FEMP FY 2007, Jan. 2010, Table A-4, p. 93 for prices and

  6. Table C12. Electricity Expenditures by Census Region, 1999

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

    Electricity Expenditures by Census Region, 1999" ,"Total Electricity Expenditures (million dollars)",,,,"Electricity Expenditures (dollars)" ,,,,,"per kWh",,,,"per Square Foot"...

  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. State Energy Price and Expenditure Estimates

    Reports and Publications (EIA)

    2016-01-01

    Energy price and expenditure estimates in dollars per million Btu and in million dollars, by state, 1970-2014.

  9. 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...

  10. wf01 - Energy_Expenditures.xlsx

    Gasoline and Diesel Fuel Update (EIA)

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

  11. 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 ...

  12. 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 ...

  13. 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 ...

  14. 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 ...

  15. 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.

  16. State energy price and expenditure report 1994

    SciTech Connect (OSTI)

    1997-06-01

    The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the United States. The price and expenditure estimates developed in the State Energy Price and Expenditure Data System (SEPEDS) are provided by energy source and economic sector and are published for the years 1970 through 1994. Consumption estimates used to calculate expenditures and the documentation for those estimates are taken from the State Energy Data Report 1994, Consumption Estimates (SEDR), published in October 1996. Expenditures are calculated by multiplying the price estimates by the consumption estimates, which are adjusted to remove process fuel; intermediate petroleum products; and other consumption that has no direct fuel costs, i.e., hydroelectric, geothermal, wind, solar, and photovoltaic energy sources. Documentation is included describing the development of price estimates, data sources, and calculation methods. 316 tabs.

  17. State energy price and expenditure report 1992

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the United States. The price and expenditure estimates are provided by energy source and economic sector and are published for the years 1970, 1980, and 1985 through 1992. Data for all years, 1970 through 1992, are available on personal computer diskettes.

  18. Expenditures

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

    ,4628,16.42,12.75,16.62,20.42,1.38,1.06,1.35,1.48 "Three ...",2390,3012,2457,1285,15.31,12.75,15.02,20.2,1.15,1.17,1.27,1.43 "Four to Nine...

  19. State energy price and expenditure report 1991

    SciTech Connect (OSTI)

    Not Available

    1993-09-01

    The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the United States. The price and expenditure estimates are provided by energy source and economic sector and are published for the years 1970, 1975, 1980, and 1985 through 1991. Data for all years, 1970 through 1991, are available on personal computer diskettes. Documentation in Appendix A describes how the price estimates are developed, including sources of data, methods of estimation, and conversion factors applied. This report is an update of the State Energy Price and Expenditure Report 1990, published in September 1992.

  20. Commercial Buildings Energy Consumption and Expenditures 1992

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

    Distribution Category UC-950 Commercial Buildings Energy Consumption and Expenditures 1992 April 1995 Energy Information Adminstration Office of Energy Markets and End Use U.S....

  1. Commercial Buildings Energy Consumption and Expenditures 1992

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

    in this report were based on monthly billing records submitted by the buildings' energy suppliers. The section, "Annual Consumption and Expenditures" provide a detailed...

  2. ,"Natural Gas Consumption",,,"Natural Gas Expenditures"

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

    Census Division, 1999" ,"Natural Gas Consumption",,,"Natural Gas Expenditures" ,"per Building (thousand cubic feet)","per Square Foot (cubic feet)","per Worker (thousand cubic...

  3. Commercial Buildings Energy Consumption and Expenditures 1995...

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

    fuel oil, and district heat consumption and expenditures for commercial buildings by building characteristics. Previous Page Arrow Separater Bar File Last Modified: January 29,...

  4. Commercial Buildings Energy Consumption and Expenditures 1992...

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

    Consumption and Expenditures Electricity Consumption Natural Gas Consumption Wood and Solar Energy Consumption Fuel Oil and District Heat Consumption Energy Consumption in...

  5. 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.

  6. 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...

  7. 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...

  8. State energy price and expenditure report 1989

    SciTech Connect (OSTI)

    Not Available

    1991-09-30

    The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates for the 50 States, the District of Columbia, and the United States. The estimates are provided by energy source (e.g., petroleum, natural gas, coal, and electricity) and by major consuming or economic sector. This report is an update of the State Energy Price and Expenditure Report 1988 published in September 1990. Changes from the last report are summarized in a section of the documentation. Energy price and expenditure estimates are published for the years 1970, 1975, 1980, and 1985 through 1989. Documentation follows the tables and describes how the price estimates are developed, including sources of data, methods of estimation, and conversion factors applied. Consumption estimates used to calculate expenditures, and the documentation for those estimates, are from the State Energy Data Report, Consumption Estimates, 1960--1989 (SEDR), published in May 1991. Expenditures are calculated by multiplying the price estimates by the consumption estimates, adjusted to remove process fuel and intermediate product consumption. All expenditures are consumer expenditures, that is, they represent estimates of money directly spent by consumers to purchase energy, generally including taxes. 11 figs., 43 tabs.

  9. Aggregrate consumer expenditures on energy. Final report

    SciTech Connect (OSTI)

    Jorgenson, D.W.

    1984-08-01

    This report presents a new economic model for the allocation of aggregate consumer expenditures on energy in the United States. Our model is based on a theory of consumer behavior involving two stages. In the first stage total expenditures are allocated between and nonenergy commodities. Allocation depends on the price of energy, prices of all nonenergy commodities, and the level of total expenditure. Total energy expenditure in the second stage is allocated among individual types of energy. The second stage allocation depends on the prices of individual types of energy and the level of total energy expenditure. Our econometric model can be applied to the generation of projection of aggregrate energy demand in the United States. Projected future energy prices, the future level and distribution of total energy expenditure, and the future demographic development of the population for projections. The model can also be used to make projections for individual consumer groups within the United States, classified by total energy expenditure and by demographic characteristics. Finally, it can be integrated into a model of energy and nonenergy expenditures to provide a complete model of aggregate consumer behavior. Our econometric model of aggregate consumer behavior can be applied to the generation of projection of demand individual types of energy and for all nonenergy commodities in the United States.

  10. Company Template (Expenditure-Based) | Department of Energy

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

    Company Template (Expenditure-Based) Company Template (Expenditure-Based) Company Exp-based template.doc (182.5 KB) More Documents & Publications Company Template (Fixed Support) Consortium Template (Expenditure-Based) Consortium Support (Fixed Support)

  11. State energy price and expenditure report, 1995

    SciTech Connect (OSTI)

    1998-08-01

    The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the US. The estimates developed in the State Energy Price and Expenditure Data System (SEPEDS) are provided by energy source and economic sector and are published for the years 1970 through 1995. Data for all years are available on a CD-ROM and via Internet. Consumption estimates used to calculate expenditures and the documentation for those estimates are taken from the State Energy Data Report 1995, Consumption Estimates (SEDR), published in December 1997. Expenditures are calculated by multiplying the price estimates by the consumption estimates, which are adjusted to remove process fuel; intermediate petroleum products; and other consumption that has no direct fuel costs, i.e., hydroelectric, geothermal, wind, solar, and photovoltaic energy sources.

  12. Table C10. Electricity Consumption and Expenditure Intensities...

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

    Electricity Consumption and Expenditure Intensities, 1999" ,"Electricity Consumption",,,,,,"Electricity Expenditures" ,"per Building (thousand kWh)","per Square Foot (kWh)","per...

  13. Consortium Template (Expenditure-Based) | Department of Energy

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

    Template (Expenditure-Based) Consortium Template (Expenditure-Based) Consortium Exp-based template.doc (200.5 KB) More Documents & Publications Consortium Support (Fixed Support

  14. Fuel Oil",,,"Fuel Oil Consumption",,"Fuel Oil Expenditures"

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

    1. Total Fuel Oil Consumption and Expenditures, 1999" ,"All Buildings Using Fuel Oil",,,"Fuel Oil Consumption",,"Fuel Oil Expenditures" ,"Number of Buildings (thousand)","Floorspac...

  15. 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

  16. Buildings Energy Data Book: 4.3 Federal Buildings and Facilities Expenditures

    Buildings Energy Data Book [EERE]

    1 FY 2007 Federal Buildings Energy Prices and Expenditures, by Fuel Type ($2010) Fuel Type Electricity 23.68 (1) 4,009 Natural Gas 9.37 1,138 Fuel Oil 15.25 419 Coal 3.62 63 Purchased Steam 24.30 318 LPG/Propane 17.06 44 Other 16.19 37 Average 17.05 Total 6,029 Note(s): Source(s): Average Fuel Prices Total Expenditures ($/million BTU) ($ million) (2) Prices and expenditures are for Goal-Subject buildings. 1) $0.0776/kWh. 2) Energy used in Goal-Subject buildings in FY 2007 accounted for 33.8% of

  17. 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 ...

  18. 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 *...

  19. 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 ...

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. Fact #747: October 1, 2012 Behind Housing, Transportation is the Top

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

    Household Expenditure | Department of Energy 7: October 1, 2012 Behind Housing, Transportation is the Top Household Expenditure Fact #747: October 1, 2012 Behind Housing, Transportation is the Top Household Expenditure Except for housing, transportation was the largest single expenditure for the average American household in 2010. The average household spends more on transportation in a year than on food. Vehicle purchases, along with gasoline and motor oil, make up a large part of vehicle

  7. State energy price and expenditure report 1993

    SciTech Connect (OSTI)

    1995-12-01

    The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 states and the District of Columbia and in aggregate for the US. The five economic sectors used in SEPER correspond to those used in SEDR and are residential, commercial, industrial, transportation, and electric utility. Documentation in appendices describe how the price estimates are developed, provide conversion factors for measures used in the energy analysis, and include a glossary. 65 tabs.

  8. Residential Buildings Historical Publications reports, data and...

    Gasoline and Diesel Fuel Update (EIA)

    0 Average of Major Energy Sources Residential Buildings Consumption Expenditures Total per per per per Total Total Floorspace per Square per Household per Square per Household ...

  9. 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) . . . . . . . . ....

  10. 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 ...

  11. 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 ...

  12. 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 ...

  13. 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...

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

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

    More ... 8.2 Q 1.7 1.9 1.7 2.6 6.1 2.0 Q Q Q 16.7 Below Poverty Line 100 Percent ... 9.0 2.5 3.6 1.3 1.0 0.6 Q...

  15. Fact #638: August 30, 2010 Average Expenditure for a New Car...

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

    33.6% 1975 4,950 13,719 36.1% 1977 5,814 16,009 36.3% 1979 6,847 19,661 34.8% 1981 8,910 22,388 39.8% 1983 10,606 24,580 43.1% 1985 11,838 27,144 43.6% 1987 13,386 ...

  16. 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...

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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...

  7. 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

  8. 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

  9. 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

  10. 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.

  11. 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...

  12. 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

  13. 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 ...

  14. 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% ...

  15. 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

  16. 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

  17. 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

  18. 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 ...........................................

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. State Energy Data System 2014 Price and Expenditure Technical Notes

    Gasoline and Diesel Fuel Update (EIA)

    Price and Expenditure Technical Notes U.S. Energy Information Administration | State Energy Data 2014: Prices and Expenditures 3 Purpose The State Energy Data System (SEDS) was developed and is maintained and operated by the U.S. Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy production, consumption, prices, and expenditures by state that are defined as consistently as possible over time and across sectors. SEDS exists for two

  11. 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.

  12. 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

  13. 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

  14. 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 ........................

  15. 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

  16. 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...

  17. Buildings Energy Data Book: 3.3 Commercial Sector Expenditures

    Buildings Energy Data Book [EERE]

    8 Average Annual Energy Expenditures per Square Foot of Commercial Floorspace, by Year ($2010) Year $/SF 1980 (1) 2.12 1981 2.22 (2) 1982 2.24 1983 2.21 1984 2.25 1985 2.20 1986 2.06 1987 2.00 1988 1.99 1989 2.01 1990 1.98 1991 1.92 1992 1.86 1993 1.96 1994 2.05 1995 2.12 1996 2.10 1997 2.08 1998 1.97 1999 1.88 2000 2.06 2001 2.20 2002 2.04 2003 2.13 2004 2.16 2005 2.30 2006 2.36 2007 2.35 2008 1.71 2009 2.43 2010 2.44 2011 2.44 2012 2.35 2013 2.28 2014 2.27 2015 2.29 2016 2.29 2017 2.28 2018

  18. 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.

  19. 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 ...

  20. 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...

  1. 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 ...

  2. 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...

  3. Using Fuel Oil",,,"Fuel Oil Consumption",,"Fuel Oil Expenditures...

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

    A. Total Fuel Oil Consumption and Expenditures for All Buildings, 2003" ,"All Buildings Using Fuel Oil",,,"Fuel Oil Consumption",,"Fuel Oil Expenditures" ,"Number of Buildings...

  4. Using Fuel Oil",,,"Fuel Oil Consumption",,"Fuel Oil Expenditures...

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

    . Total Fuel Oil Consumption and Expenditures for Non-Mall Buildings, 2003" ,"All Buildings* Using Fuel Oil",,,"Fuel Oil Consumption",,"Fuel Oil Expenditures" ,"Number of Buildings...

  5. 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.

  6. ,"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. ...

  7. Commercial Buildings Energy Consumption and Expenditures 1992...

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

    with the national average of 81 thousand Btu per square foot), while buildings using solar energy or passive solar features used the major energy sources more intensively...

  8. 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

  9. Microsoft Word - Highlights.docx

    Gasoline and Diesel Fuel Update (EIA)

    and Winter Fuels Outlook  EIA projects average household expenditures for heating oil and natural gas will increase by 19 percent and 15 percent, respectively, this winter (October 1 through March 31) compared with last winter. Projected household expenditures are 5 percent higher for electricity and 13 percent higher for propane this winter. Average expenditures for households that heat with heating oil are forecast to be higher than any previous winter on record (see EIA Short-Term Energy

  10. 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

  11. Buildings Energy Data Book: 3.3 Commercial Sector Expenditures

    Buildings Energy Data Book [EERE]

    3.3 Commercial Sector Expenditures March 2012 3.3.3 Commercial Buildings Aggregate Energy Expenditures, by Year and Major Fuel Type ($2010 Billion) (1) Electricity Natural Gas Petroleum (2) Total 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 148.6 37.0 17.0 202.6 148.9 37.2 17.1 203.2 145.9 36.2

  12. 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

  13. Audit of controls over Superconducting Super Collider Laboratory subcontractor expenditures

    SciTech Connect (OSTI)

    Not Available

    1993-10-22

    In January 1989 the Department of Energy contracted with Universities Research Association, Inc. to design, construct, manage, operate, and maintain the Superconducting Super Collider Laboratory. Through Fiscal Year 1992, costs for subcontractor goods and services accounted for about 75 percent of the Superconducting Super Collider Laboratory expenditures. The Office of Inspector General evaluated the adequacy of controls in place to ensure that subcontractor costs were reasonable, as required by the contract. The following conclusions were drawn from the audit. The Superconducting Super Collider Laboratory did not consistently exercise prudent business judgment in making subcontractor expenditures. As a result, $60 million in expenditures already made and $128 million planned with commercial subcontractors were, in the authors opinion, unnecessary, excessive, or represented uncontrolled growth. The audit also found inadequate justifications, accountability, and cost controls over $143 million in expenditures made and $47 million planned with other Department of Energy laboratories. Improvements were needed in subcontract administration and internal controls, including appropriate audit coverage of the subcontracts. In addition, Department of Energy guidance concerning procurement actions between the laboratories needed to be established.

  14. State Energy Data System CSV File Documentation Price and Expenditure Estimates

    Gasoline and Diesel Fuel Update (EIA)

    State Energy Data System CSV File Documentation Price and Expenditure Estimates The State Energy Data System (SEDS) comma-separated value (CSV) fles contain the price and expenditure esti- mates shown in the tables located on the SEDS website. There are three fles that contain estimates for all states and years. Prices contains the price estimates for all states and Expenditures contains the expenditure estimates for all states. The third fle, Adjusted Consumption for Ex- penditure Calculations

  15. 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.

  16. 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.

  17. 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

  18. Distribution piping expenditures of $2. 66 billion seen for 1983

    SciTech Connect (OSTI)

    Watts, J.

    1982-12-01

    Figures for the 1982 results and 1983 projections of expenditures and pipe mileage compiled in a survey of 500 gas distribution utilities in 50 states, including the 300 largest utilities are presented. Maintenance as a percentage of total construction budget has been steady over the past 3 yrs. If housing construction picks up again by mid-year, 1983 could be a good year for gas utilities because of the convenience and cleanliness of gas heating.

  19. Table A39. Total Expenditures for Purchased Electricity and Steam

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

    9. Total Expenditures for Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" ," Electricity",," Steam" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic

  20. Process for the utilization of household rubbish or garbage and other organic waste products for the production of methane gas

    SciTech Connect (OSTI)

    Hunziker, M.; Schildknecht, A.

    1985-04-16

    Non-organic substances are separated from household garbage and the organic substances are fed in proportioned manner into a mixing tank and converted into slurry by adding liquid. The slurry is crushed for homogenization purposes in a crushing means and passed into a closed holding container. It is then fed over a heat exchanger and heated to 55/sup 0/ to 60/sup 0/ C. The slurry passes into a plurality of reaction vessels in which the methane gas and carbon dioxide are produced. In a separating plant, the mixture of gaseous products is broken down into its components and some of the methane gas is recycled by bubbling it through both the holding tank and the reaction tank, the remainder being stored in gasholders. The organic substances are degraded much more rapidly through increasing the degradation temperature and as a result constructional expenditure can be reduced.

  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. 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.

  3. 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.

  4. 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)

  5. " 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" ...

  6. 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 ...

  7. 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 ...

  8. ,"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 ...

  9. Taxation of expenditures required by the Surface Mining Control and Reclamation Act of 1977 (SMCRA)

    SciTech Connect (OSTI)

    McNally, K.J.

    1987-01-01

    There has been disagreement over whether the expenditures made by the mine operator to comply with the Surface Mining Control and Reclamation Act of 1977 are characterized as capital or deductible expenses. An examination of expenditures made by mine operators during the life of a mine illustrates the dichotomy between deductible and capital expenditures in which special rules may override general capitalization rules to allow the mine operator to deduct a capital expenditure. This makes some expenditures difficult to categorize. Citing case law, the author treats expenditures for exploration and mining permits, performance bonds, and liability insurance. A new provision, section 468, allowing the current deduction for future reclamation and closing costs removed the uncertainty created by prior case law.

  10. 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

  11. Table 7.9 Expenditures for Purchased Energy Sources, 2002

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

    9 Expenditures for Purchased Energy Sources, 2002;" " Level: National and Regional Data;" " Row: NAICS Codes; Column: Energy Sources;" " Unit: Million U.S. Dollars." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,,"RSE" "NAICS"," ","

  12. Table 7.9 Expenditures for Purchased Energy Sources, 2010;

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

    9 Expenditures for Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Million U.S. Dollars. NAICS Residual Distillate LPG and Coke Code(a) Subsector and Industry Total Electricity Fuel Oil Fuel Oil(b) Natural Gas(c) NGL(d) Coal and Breeze Other(e) Total United States 311 Food 10,111 5,328 130 431 3,391 150 442 29 210 3112 Grain and Oilseed Milling 2,130 932 2 12 673 Q 294 0 158 311221 Wet Corn Milling 1,002 352 1 5 296 1 239 0 107

  13. Weatherization assistance for low-income households: An evaluation of local program performance

    SciTech Connect (OSTI)

    Schweitzer, M.; Rayner, S.; Wolfe, A.K.; Mason, T.W.; Ragins, B.R.; Cartor, R.A.

    1987-08-01

    The US Department of Energy's Weatherization Assistance Program (WAP) funds local agencies to provide weatherization services to low-income households. This report describes the most salient features of this program, examines relationships between organization and program outcomes, and presents recommendations for the program's further development. Data were collected by written surveys administered to local weatherization agencies, a telephone survey of 38 states and eight DOE support offices, and site visits to selected local agencies. Locally controlled factors found to be significantly related to program performance include the amount of the weatherization director's time spent on program administration, the use of established client selection criteria, the frequency of evaluation of local goal attainment, and the type of weatherization crews used. Factors controlled at the state or federal levels that influence program performance include delays in state reimbursements of local agency expenditures and local flexibility in the choice of weatherization measures. Data-gathering difficulties experienced during this project indicate a need for possible improvements in goal-setting and record-keeping procedures.

  14. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2001 Average LPG 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 U.S. Households 9.4 9.2 19.6 41 19 40.2 16 607 0.29 598 231 Census Region and

  15. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 Average Natural Gas 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 U.S. Households 57.7 44.8 106.3 109 46 84.2 32 609 0.26 472 181 Census Region

  16. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 3 Average Natural Gas 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 U.S. Households 58.7 46.0 111.9 115 47 89.9 34 696 0.29 546 206 Census Region

  17. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires Natural Gas, 1997 Average Natural Gas Residential Buildings Consumption Expenditures Total per Floor- per Square per per per Total Total space (1) 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 U.S. Households 61.9 51.3 106.1 103 50 85.3 32 698 0.34

  18. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2001 Average Natural Gas 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 U.S. Households 66.9 53.8 137.2 90 35 72.4 27 873 0.34 702 265 Census Region

  19. Buildings Energy Data Book: 1.2 Building Sector Expenditures

    Buildings Energy Data Book [EERE]

    3 Buildings Aggregate Energy Expenditures, by Year and Major Fuel Type ($2010 Billion) (1) Residential Buildings Commercial Buildings Total Building Electricity Natural Gas Petroleum (2) Total Electricity Natural Gas Petroleum (3) Total Expenditures 1980 89.1 40.5 28.9 158.5 70.9 20.5 17.2 108.6 267.2 1981 94.9 41.3 27.8 164.0 79.4 21.4 16.5 117.3 281.3 1982 99.9 47.9 24.5 172.3 83.4 25.1 13.7 122.2 294.5 1983 103.6 51.0 21.4 176.1 83.6 26.1 14.6 124.3 300.4 1984 103.3 51.6 23.6 178.5 87.6 25.9

  20. Spacetime Average Density (SAD) cosmological measures

    SciTech Connect (OSTI)

    Page, Don N.

    2014-11-01

    The measure problem of cosmology is how to obtain normalized probabilities of observations from the quantum state of the universe. This is particularly a problem when eternal inflation leads to a universe of unbounded size so that there are apparently infinitely many realizations or occurrences of observations of each of many different kinds or types, making the ratios ambiguous. There is also the danger of domination by Boltzmann Brains. Here two new Spacetime Average Density (SAD) measures are proposed, Maximal Average Density (MAD) and Biased Average Density (BAD), for getting a finite number of observation occurrences by using properties of the Spacetime Average Density (SAD) of observation occurrences to restrict to finite regions of spacetimes that have a preferred beginning or bounce hypersurface. These measures avoid Boltzmann brain domination and appear to give results consistent with other observations that are problematic for other widely used measures, such as the observation of a positive cosmological constant.

  1. Perceptions of risk among households in two Australian coastal communities

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

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall,more » the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.« less

  2. Perceptions of risk among households in two Australian coastal communities

    SciTech Connect (OSTI)

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall, the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.

  3. Reconstructing householder vectors from Tall-Skinny QR

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

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstratemore » the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.« less

  4. Reconstructing householder vectors from Tall-Skinny QR

    SciTech Connect (OSTI)

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstrate the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.

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

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

    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 ...

  6. "Table HC7.5 Space Heating Usage Indicators by Household Income...

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

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  7. "Table HC7.12 Home Electronics Usage Indicators by Household...

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

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

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

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

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  9. US ESC TN Site Consumption

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

    ESC TN Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ESC TN Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US ESC TN Site Consumption kilowatthours $0 $400 $800 $1,200 $1,600 US ESC TN Expenditures dollars ELECTRICITY ONLY average per household * Tennessee households consume an average of 79 million Btu per year, about 12% less than the U.S. average. * Average electricity consumption for Tennessee households is 33%

  10. US Mnt(N) CO Site Consumption

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

    Mnt(N) CO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(N) CO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US Mnt(N) CO Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US Mnt(N) CO Expenditures dollars ELECTRICITY ONLY average per household * Colorado households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Average household energy costs in

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

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

    Percent of Households with Vehicles, Selected Survey Years " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",85.5450237,89.00343643,88.75545852,89.42917548,87.25590956,92.08...

  12. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    3 Residential Aggregate Energy Expenditures, by Year and Major Fuel Type ($2010 Billion) (1) Electricity Total 1980 158.5 1981 164.0 1982 172.3 1983 176.1 1984 178.5 1985 176.8 1986 169.2 1987 167.1 1988 170.1 1989 172.8 1990 168.2 1991 169.9 1992 166.7 1993 175.6 1994 174.9 1995 172.7 1996 181.8 1997 180.0 1998 173.5 1999 174.0 2000 192.8 2001 203.3 2002 192.1 2003 208.8 2004 215.1 2005 236.7 2006 240.0 2007 246.1 2008 259.6 2009 241.6 2010 251.8 2011 251.3 2012 247.1 2013 240.3 2014 239.4 2015

  13. Buildings Energy Data Book: 3.3 Commercial Sector Expenditures

    Buildings Energy Data Book [EERE]

    9 2003 Energy Expenditures per Square Foot of Commercial Floorspace and per Building, by Building Type ($2010) ($2010) Food Service 4.88 27.2 Mercantile 2.23 38.1 Food Sales 4.68 26.0 Education 1.43 36.6 Health Care 2.76 68.0 Service 1.39 9.1 Public Order and Safety 2.07 32.0 Warehouse and Storage 0.80 13.5 Office 2.01 29.8 Religious Worship 0.76 7.8 Public Assembly 1.73 24.6 Vacant 0.34 4.8 Lodging 1.72 61.5 Other 2.99 65.5 Note(s): Source(s): Mall buildings are no longer included in most CBECs

  14. 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

  15. Polarized electron beams at milliampere average current

    SciTech Connect (OSTI)

    Poelker, Matthew

    2013-11-01

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

  16. 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

  17. 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

  18. 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.

  19. ,"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. ...

  20. 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.

  1. 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.

  2. 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

  3. U.S. Energy Information Administration | State Energy Data 2014: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    23 A P P E N D I X A This appendix contains alphabetical listings of the variables used in the price and expenditure module of the State Energy Data System (SEDS). The first list presents the price and expenditure variables, and the second presents the consumption adjustment variables as described in Section 7, "Consumption Adjustments for Calculating Expenditures." Provided for each variable are: a brief description; unit of measure; and the formulas used to create the variable. If a

  4. Table 1. Real Average Transportation and Delivered Costs of Coal...

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

    Real Average Transportation and Delivered Costs of Coal, By Year and Primary Transport Mode" "Year","Average Transportation Cost of Coal (Dollars per Ton)","Average Delivered Cost...

  5. 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.

  6. Buildings Energy Data Book: 1.2 Building Sector Expenditures

    Buildings Energy Data Book [EERE]

    5 2010 Buildings Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal Electricity Total Percent Space Heating (3) 53.7 14.2 0.9 8.0 0.6 23.7 0.1 23.2 100.8 23.4% Space Cooling 0.4 61.3 61.7 14.3% Lighting 59.3 59.3 13.8% Water Heating 18.3 2.6 2.0 4.6 17.8 40.7 9.4% Refrigeration (4) 26.9 26.9 6.2% Electronics (5) 26.1 26.1 6.1% Ventilation (6) 15.9 15.9 3.7% Cooking 4.0 0.8 0.8 8.8 13.6 3.2% Computers 12.1 12.1 2.8% Wet

  7. Buildings Energy Data Book: 1.2 Building Sector Expenditures

    Buildings Energy Data Book [EERE]

    6 2015 Buildings Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Gas Distil. Resid. LPG Oth(2) Total Coal Total Percent Space Heating (3) 49.5 15.9 1.3 8.1 0.7 25.9 0.2 18.7 94.3 22.7% Space Cooling 0.3 48.0 48.3 11.6% Lighting 45.9 45.9 11.0% Water Heating 17.6 2.6 1.5 4.1 18.3 40.0 9.6% Refrigeration (4) 24.9 24.9 6.0% Electronics (5) 19.8 19.8 4.7% Ventilation (6) 15.1 15.1 3.6% Computers 11.6 11.6 2.8% Wet Cleaning (7) 0.6 10.8 11.4 2.7% Cooking 3.9 0.9 0.9 4.4

  8. Buildings Energy Data Book: 1.2 Building Sector Expenditures

    Buildings Energy Data Book [EERE]

    7 2025 Buildings Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal Electricity Total Percent Space Heating (3) 56.7 14.3 1.5 7.8 0.7 24.3 0.2 19.5 100.7 22.0% Space Cooling 0.3 50.5 50.9 11.1% Lighting 45.2 45.2 9.9% Water Heating 21.3 2.3 1.3 3.6 19.6 44.4 9.7% Refrigeration (4) 24.9 24.9 5.4% Electronics (5) 23.2 23.2 5.1% Computers 13.2 13.2 2.9% Wet Clean (6) 0.8 9.8 10.5 2.3% Cooking 4.8 0.8 0.8 4.9 10.5 2.3%

  9. Buildings Energy Data Book: 1.2 Building Sector Expenditures

    Buildings Energy Data Book [EERE]

    8 2035 Buildings Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal Electricity Total Percent Space Heating (3) 63.4 13.0 1.6 7.7 0.8 23.1 0.2 20.6 107.2 20.9% Water Heating 23.8 2.2 1.2 3.4 35.8 63.0 12.3% Space Cooling 0.4 55.7 56.1 10.9% Lighting 47.8 47.8 9.3% Electronics (4) 27.2 27.2 5.3% Refrigeration (5) 27.0 27.0 5.3% Computers 14.8 14.8 2.9% Cooking 5.8 0.8 0.8 5.4 12.1 2.3% Wet Clean (6) 0.9 10.4 11.3 2.2%

  10. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    5 2010 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 38.7 11.2 8.0 19.8 0.0 14.3 72.9 28.9% Space Cooling (3) 0.0 35.4 35.4 14.0% Water Heating (4) 14.3 2.1 2.0 4.0 14.2 32.6 12.9% Lighting 22.6 22.6 9.0% Refrigeration (5) 14.9 14.9 5.9% Electronics (6) 17.8 17.8 7.1% Cooking 2.4 0.8 0.8 6.0 9.2 3.7% Wet Cleaning (7) 0.6 10.7 11.3 4.5% Computers 5.6 5.6 2.2% Other

  11. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    6 2015 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 35.0 13.0 8.1 21.6 0.0 14.0 70.6 29.2% Space Cooling (3) 0.0 33.8 33.8 14.0% Water Heating 13.5 1.9 1.5 3.4 15.8 32.7 13.5% Lighting 17.6 17.6 7.3% Refrigeration (4) 15.0 15.0 6.2% Electronics (5) 10.9 10.9 4.5% Wet Cleaning (6) 0.6 10.8 11.4 4.7% Cooking 2.2 0.9 0.9 3.8 6.8 2.8% Computers 6.3 6.3 2.6% Other (7)

  12. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    7 2025 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 39.7 11.5 7.8 19.9 0.0 15.0 74.5 28.6% Space Cooling (3) 0.0 36.2 36.2 13.9% Water Heating 16.0 1.4 1.3 2.7 17.1 35.9 13.8% Lighting 15.2 15.2 5.8% Refrigeration (4) 15.5 15.5 6.0% Electronics (5) 12.0 12.0 4.6% Wet Cleaning (6) 0.8 9.8 10.5 4.1% Cooking 2.7 0.8 0.8 4.3 7.8 3.0% Computers 7.7 7.7 2.9% Other (7)

  13. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    8 2035 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 44.3 10.3 7.7 18.6 0.0 16.0 79.0 27.4% Space Cooling (3) 0.0 40.6 40.6 14.1% Water Heating 17.6 1.2 1.2 2.3 17.7 37.6 13.0% Lighting 15.5 15.5 5.4% Refrigeration (4) 17.0 17.0 5.9% Electronics (5) 14.2 14.2 4.9% Wet Cleaning (6) 0.9 10.4 11.3 3.9% Cooking 3.2 0.8 0.8 4.8 8.9 3.1% Computers 8.7 8.7 3.0% Other (7)

  14. Buildings Energy Data Book: 3.3 Commercial Sector Expenditures

    Buildings Energy Data Book [EERE]

    4 2010 Commercial Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal (3) Electricity Total Percent Lighting 35.4 35.4 19.7% Space Heating 15.0 2.9 0.9 0.1 3.9 0.1 8.5 27.5 15.3% Space Cooling 0.4 25.0 25.3 14.1% Ventilation 15.9 15.9 8.9% Refrigeration 11.6 11.6 6.5% Water Heating 4.0 0.6 0.6 2.7 7.3 4.1% Electronics 7.8 7.8 4.3% Computers 6.3 6.3 3.5% Cooking 1.6 0.7 2.3 1.3% Other (4) 2.7 0.3 3.3 1.2 4.8 20.4 28.0

  15. Buildings Energy Data Book: 3.3 Commercial Sector Expenditures

    Buildings Energy Data Book [EERE]

    5 2015 Commercial Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal (3) Electricity Total Percent Lighting 28.4 28.4 16.3% Space Heating 14.6 2.9 1.3 0.1 4.3 0.1 4.7 23.7 13.6% Ventilation 15.1 15.1 8.6% Space Cooling 0.3 14.2 14.5 8.3% Refrigeration 9.9 9.9 5.7% Electronics 8.8 8.8 5.1% Water Heating 4.1 0.7 0.7 2.5 7.3 4.2% Computers 5.3 5.3 3.0% Cooking 1.7 0.6 2.3 1.3% Other (4) 2.9 0.3 3.7 1.4 5.4 22.8 31.1 17.8%

  16. Buildings Energy Data Book: 3.3 Commercial Sector Expenditures

    Buildings Energy Data Book [EERE]

    6 2025 Commercial Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal (3) Electricity Total Percent Lighting 30.1 30.1 15.2% Space Heating 17.1 2.8 1.5 0.1 4.4 0.2 4.5 26.1 13.3% Electronics 11.2 11.2 5.7% Space Cooling 0.3 14.3 14.6 7.4% Water Heating 5.2 0.8 0.8 2.5 8.5 4.3% Computers 5.5 5.5 2.8% Refrigeration 9.4 9.4 4.8% Ventilation 16.6 16.6 8.4% Cooking 2.1 0.6 2.7 1.4% Other (4) 4.8 0.3 4.3 1.7 6.3 31.2 42.3 21.5%

  17. Buildings Energy Data Book: 3.3 Commercial Sector Expenditures

    Buildings Energy Data Book [EERE]

    7 2035 Commercial Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal (3) Electricity Total Percent Lighting 32.3 32.3 14.4% Space Heating 19.0 2.7 1.6 0.2 4.5 0.2 4.6 28.2 12.5% Water Heating 6.3 1.0 1.0 18.1 25.4 11.3% Space Cooling 0.4 15.1 15.5 6.9% Electronics 13.0 13.0 5.8% Refrigeration 10.0 10.0 4.4% Computers 6.0 6.0 2.7% Cooking 2.6 0.6 3.2 1.4% Ventilation 2.4 2.4 1.1% Other (4) 9.3 0.4 4.9 2.0 7.2 40.9 57.5

  18. New York City- Property Tax Abatement for Photovoltaic (PV) Equipment Expenditures

    Broader source: Energy.gov [DOE]

    In August 2008 the State of New York enacted legislation allowing a property tax abatement for photovoltaic (PV) system expenditures made on buildings located in cities with a population of 1 mil...

  19. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, J.D.; Liu, Xiaomin; McMahon, J.E.

    1996-11-01

    This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

  20. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

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

    1996-01-01

    This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

  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. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    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

  3. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 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 83.1 66.1 144.2 37 17 29.1 10 678 0.31 539 192 Census Region and Division

  4. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 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 83.7 66.0 142.2 36 16 28.0 10 708 0.33 558 204 Census Region and Division

  5. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 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 86.3 67.4 144.3 37 17 28.8 11 808 0.38 632 234 Census Region and Division

  6. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 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 90.5 70.4 156.8 39 18 30.5 12 875 0.39 680 262 Census Region and Division

  7. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 97 Average Electricity Residential Buildings Consumption Expenditures Total per Floor- per Square per per per Total Total space (1) 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 101.4 83.2 168.8 42 21 35.0 13 1,061 0.52 871 337 Census Region and

  8. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2001 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 107.0 85.2 211.2 46 18 36.0 14 1,178 0.48 938 366 Census Region and Division

  9. Microsoft Word - Highlights Bullets.doc

    Gasoline and Diesel Fuel Update (EIA)

    November 2004 1 Short-Term Energy Outlook November 2004 Winter Fuels Update (Figure 1) Higher oil prices in this Outlook raised our projections for heating oil and propane prices and household heating fuel expenditures this winter. Heating oil expenditures by typical Northeastern households are now expected to average about 37 percent above last winter's levels (compared to our previous projection of a 28-percent increase), with average residential prices averaging $1.88 per gallon for the

  10. 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.

  11. Impacts of different data averaging times on statistical analysis of distributed domestic photovoltaic systems

    SciTech Connect (OSTI)

    Widen, Joakim; Waeckelgaard, Ewa; Paatero, Jukka; Lund, Peter

    2010-03-15

    The trend of increasing application of distributed generation with solar photovoltaics (PV-DG) suggests that a widespread integration in existing low-voltage (LV) grids is possible in the future. With massive integration in LV grids, a major concern is the possible negative impacts of excess power injection from on-site generation. For power-flow simulations of such grid impacts, an important consideration is the time resolution of demand and generation data. This paper investigates the impact of time averaging on high-resolution data series of domestic electricity demand and PV-DG output and on voltages in a simulated LV grid. Effects of 10-minutely and hourly averaging on descriptive statistics and duration curves were determined. Although time averaging has a considerable impact on statistical properties of the demand in individual households, the impact is smaller on aggregate demand, already smoothed from random coincidence, and on PV-DG output. Consequently, the statistical distribution of simulated grid voltages was also robust against time averaging. The overall judgement is that statistical investigation of voltage variations in the presence of PV-DG does not require higher resolution than hourly. (author)

  12. U.S. Energy Information Administration | State Energy Data 2014: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    Purpose The State Energy Data System (SEDS) was developed and is maintained and operated by the U.S. Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy production, consumption, prices, and expenditures by state that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide state energy production, consumption, price, and expenditure estimates to Members of Congress,

  13. Table 2.10 Commercial Buildings Energy Consumption and Expenditure Indicators, Selected Years, 1979-2003

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

    0 Commercial Buildings Energy Consumption and Expenditure Indicators, Selected Years, 1979-2003 Energy Source and Year Building Characteristics Energy Consumption Energy Expenditures Number of Buildings Total Square Feet Square Feet per Building Total Per Building Per Square Foot Per Employee Total Per Building Per Square Foot Per Million Btu Thousands Millions Thousands Trillion Btu Million Btu Thousand Btu Million Btu Million Dollars 1 Thousand Dollars 1 Dollars 1 Dollars 1 Major Sources 2

  14. 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.

  15. 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

  16. New York Household Travel Patterns: A Comparison Analysis

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim

    2007-05-01

    In 1969, the U. S. Department of Transportation began collecting detailed data on personal travel to address various transportation planning issues. These issues range from assessing transportation investment programs to developing new technologies to alleviate congestion. This 1969 survey was the birth of the Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990 and 1995. Longer-distance travel was collected in 1977 and 1995. In 2001, the survey was renamed to the National Household Travel Survey (NHTS) and collected both daily and longer-distance trips in one survey. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State (NYS), the state procured an additional sample of households in both the 1995 and 2001 surveys. In the 1995 survey, NYS procured an addition sample of more than 9,000 households, increasing the final NY NPTS sample size to a total of 11,004 households. Again in 2001, NYS procured 12,000 additional sample households, increasing the final New York NHTS sample size to a total of 13,423 households with usable data. These additional sample households allowed NYS to address transportation planning issues pertinent to geographic areas significantly smaller than for what the national NPTS and NHTS data are intended. Specifically, these larger sample sizes enable detailed analysis of twelve individual Metropolitan Planning Organizations (MPOs). Furthermore, they allowed NYS to address trends in travel behavior over time. In this report, travel data for the entire NYS were compared to those of the rest of the country with respect to personal travel behavior and key travel determinants. The influence of New York City (NYC) data on the comparisons of the state of New York to the rest of the country was also examined. Moreover, the analysis examined the relationship between population density and travel patterns, and the similarities and differences among New

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

    SciTech Connect (OSTI)

    Bigum, Marianne; Petersen, Claus; Scheutz, Charlotte

    2013-11-15

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

  18. Heating oil and propane households bills to be lower this winter...

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

    Heating oil and propane households bills to be lower this winter despite recent cold spell Despite the recent cold weather, households that use heating oil or propane as their main ...

  19. Table HC1-3a. Housing Unit Characteristics by Household Income...

    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 ...

  20. US SoAtl VA Site Consumption

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

    SoAtl VA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl VA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl VA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl VA Expenditures dollars ELECTRICITY ONLY average per household * Virginia households consume an average of 86 million Btu per year, about 4% less than the U.S. average. * Average electricity consumption and costs are

  1. Annual average efficiency of a solar thermochemical reactor....

    Office of Scientific and Technical Information (OSTI)

    Annual average efficiency of a solar thermochemical reactor. Citation Details In-Document Search Title: Annual average efficiency of a solar thermochemical reactor. Abstract not ...

  2. ARM: Temperature Profiles from Raman Lidar at 60-min averaging...

    Office of Scientific and Technical Information (OSTI)

    Citation Details In-Document Search Title: ARM: Temperature Profiles from Raman Lidar at 60-min averaging interval Temperature Profiles from Raman Lidar at 60-min averaging ...

  3. ARM: Temperature Profiles from Raman Lidar at 10-min averaging...

    Office of Scientific and Technical Information (OSTI)

    Temperature Profiles from Raman Lidar at 10-min averaging interval Title: ARM: Temperature Profiles from Raman Lidar at 10-min averaging interval Temperature Profiles from Raman ...

  4. ARM: AOS Wet Nephelometer 1 Minute Averages (Dataset) | Data...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: AOS Wet Nephelometer 1 Minute Averages AOS Wet Nephelometer 1 Minute Averages Authors: Scott Smith ; Cynthia Salwen ; Janek Uin ; Gunnar Senum ; Stephen Springston ; ...

  5. ARM: AOS Dry Nephelometer 1 Minute Averages (Dataset) | Data...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: AOS Dry Nephelometer 1 Minute Averages AOS Dry Nephelometer 1 Minute Averages Authors: Scott Smith ; Cynthia Salwen ; Janek Uin ; Gunnar Senum ; Stephen Springston ; ...

  6. High Average Brightness Photocathode Development for FEL Applications...

    Office of Scientific and Technical Information (OSTI)

    Conference: High Average Brightness Photocathode Development for FEL Applications Citation Details In-Document Search Title: High Average Brightness Photocathode Development for...

  7. 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

  8. 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,

  9. 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

  10. U.S. Energy Information Administration | State Energy Data 2014: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    5 Section 7. Consumption Adjustments for Calculating Expenditures C O N S U M P T I O N A D J U S T M E N T S Expenditures developed in the EIA State Energy Data System (SEDS) are calculated by multiplying the price estimates by the SEDS consumption estimates. The consumption estimates are adjusted to remove process fuel, intermediate petroleum products, electricity exports, and other consumption that has no direct fuel costs, i.e., hydroelectric, geothermal, wind, solar thermal and photovoltaic