National Library of Energy BETA

Sample records for household expenditure results

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

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

    Household Gasoline Expenditures by Income Quintile Bar graph showing the household gasoline expenditures by income quintile in the years 1989, 1997, and 2007. For more detailed ...

  4. 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.

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

    Broader source: Energy.gov [DOE]

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

  9. Fact #748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010

    Broader source: Energy.gov [DOE]

    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...

  10. 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.

  11. 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.

  12. Table 2.5 Household Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005

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

    5 Household 1 Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005 Year Space Heating Air Conditioning Water Heating Appliances, 2 Electronics, and Lighting Natural Gas Elec- tricity 3 Fuel Oil 4 LPG 5 Total Electricity 3 Natural Gas Elec- tricity 3 Fuel Oil 4 LPG 5 Total Natural Gas Elec- tricity 3 LPG 5 Total Consumption (quadrillion Btu)<//td> 1978 4.26 0.40 2.05 0.23 6.94 0.31 1.04 0.29 0.14 0.06 1.53 0.28 1.46 0.03 1.77 1980 3.41 .27 1.30 .23 5.21 .36 1.15 .30 .22

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. Microsoft Word - Household Energy Use CA

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

    US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 ... households use 62 million Btu of energy per home, 31% less than the U.S. average. ...

  18. ,"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...

  19. ,"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"...

  20. ,"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...

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

    SciTech Connect (OSTI)

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

    1992-10-01

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

  2. 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

  3. 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.

  4. 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

  5. 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

  6. 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

  7. 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...

  8. 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).

  9. 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).

  10. 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....

  11. ,"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...

  12. ,"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...

  13. 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...

  14. 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...

  15. 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...

  16. 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,

  17. 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.

  18. 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"...

  19. Try This: Household Magnets

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

    Household Magnets 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

  20. usage_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 ...

  1. housingunit_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 ...

  2. 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 ...

  3. ac_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 ...

  4. 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.

  5. 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...

  6. 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.

  7. 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....

  8. 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...

  9. 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...

  10. ,"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...

  11. 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,...

  12. SEDS CSV File Documentation: Price and Expenditure

    Gasoline and Diesel Fuel Update (EIA)

    Price and Expenditure Estimates The State Energy Data System (SEDS) comma-separated value ... SOCCB Commercial photovoltaic and solar thermal energy consumption (excluding ...

  13. 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.

  14. 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.

  15. 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...

  16. 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...

  17. 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.

  18. 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) Microsoft Office document icon Company Exp-based template.doc More Documents & Publications Consortium Template (Expenditure-Based) Company Template (Fixed Support) Consortium Support (Fixed Support)

  19. 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.

  20. 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...

  1. State Energy Data System 2013 Price and Expenditure Technical...

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

    Price and Expenditure Technical Notes U.S. Energy Information Administration | State Energy Data 2013: Prices and Expenditures 3 Purpose The State Energy Data System (SEDS) was ...

  2. 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...

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

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

    Template (Expenditure-Based) Consortium Template (Expenditure-Based) Microsoft Office document icon Consortium Exp-based template.doc More Documents & Publications Consortium ...

  4. 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.

  5. 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 ...

  6. 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 ...

  7. 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 *...

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. ac_household2001.pdf

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

    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 ...

  13. 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 ...

  14. 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 ...

  15. 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 ...

  16. homeoffice_household2001.pdf

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

    107.0 7.1 12.3 7.7 6.3 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  17. homeoffice_household2001.pdf

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

    ......... 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  18. homeoffice_household2001.pdf

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

    107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  19. homeoffice_household2001.pdf

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

    ......... 107.0 23.3 6.7 16.6 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  20. spaceheat_household2001.pdf

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

    ... location is over a period of one year, relative to a base temperature of 65 degrees Fahrenheit. A household is assigned to a climate zone according to the 30-year average annual ...

  1. 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) . . . . . . . . ....

  2. ac_household2001.pdf

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

    2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated ... New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditi...

  3. ac_household2001.pdf

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

    2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to ...

  4. ac_household2001.pdf

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

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

  5. ac_household2001.pdf

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

    8a. Air Conditioning by UrbanRural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total UrbanRural Location 1 RSE Row Factors City ...

  6. 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...

  7. 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...

  8. 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...

  9. 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.

  10. 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

  11. 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

  12. "Table A28. Total Expenditures for Purchased Energy Sources...

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

    Total Expenditures for Purchased Energy Sources by Census Region" " and Economic ... "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity...

  13. wf01 - Energy_Expenditures.xlsx

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

    Heating Oil U.S. Average Consumption (gallons) 576.7 544.8 580.7 471.2 545.5 606.9 609.2 499.1 -18.1 Price (gallon) 2.65 2.85 3.38 3.73 3.87 3.88 3.04 2.07 -31.9 Expenditures () ...

  14. 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

  15. 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

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

    Open Energy Info (EERE)

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

  17. 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 ...

  18. 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 ...

  19. 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...

  20. 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.

  1. 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...

  2. 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...

  3. 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

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

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

    This is equivalent to an average annual growth of 1.1% and 1.8%, respectively. As a result, the aggregate energy intensity per household and per square foot declined by 24.2% and ...

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

    SciTech Connect (OSTI)

    Figueroa, M.J.; Sathaye, J.

    1993-08-01

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

  6. 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

  7. 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

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

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

    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

  9. 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. PDF icon Call Slides and Discussion Summary More Documents & Publications Homeowner and Contractor Surveys Mastermind: Jim Mikel, Spirit Foundation Generating Energy Efficiency Project Leads and Allocating Leads to Contractors

  10. 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.

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

    SciTech Connect (OSTI)

    Dolealov, Markta; Beneov, Libue; Zvodsk, Anita

    2013-09-15

    Highlights: The character of household waste in the three different types of households were assesed. The quantity, density and composition of household waste were determined. The physicochemical characteristics were determined. The changing character of household waste during past 10 years was described. The potential of energy recovery of household waste in Czech republic was assesed. - Abstract: The authors of this paper report on the changing character of household waste, in the Czech Republic between 1999 and 2009 in households differentiated by their heating methods. The data presented are the result of two projects, financed by the Czech Ministry of Environment, which were undertaken during this time period with the aim of focusing on the waste characterisation and complete analysis of the physicochemical properties of the household waste. In the Czech Republic, the composition of household waste varies significantly between different types of households based on the methods of home heating employed. For the purposes of these studies, the types of homes were divided into three categories urban, mixed and rural. Some of the biggest differences were found in the quantities of certain subsample categories, especially fine residue (matter smaller than 20 mm), between urban households with central heating and rural households that primarily employ solid fuel such coal or wood. The use of these solid fuels increases the fraction of the finer categories because of the higher presence of ash. Heating values of the residual household waste from the three categories varied very significantly, ranging from 6.8 MJ/kg to 14.2 MJ/kg in 1999 and from 6.8 MJ/kg to 10.5 MJ/kg in 2009 depending on the type of household and season. The same factors affect moisture of residual household waste which varied from 23.2% to 33.3%. The chemical parameters also varied significantly, especially in the quantities of Tl, As, Cr, Zn, Fe and Mn, which were higher in rural households. Because knowledge about the properties of household waste, as well as its physicochemical characteristics, is very important not only for future waste management, but also for the prediction of the behaviour and influence of the waste on the environment as the country continues to streamline its legislation to the European Unions solid waste mandates, the results of these studies were employed by the Czech Ministry of Environment to optimise the national waste management strategy.

  12. 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.

  13. 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

  14. 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.

  15. 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)

  16. Loan Programs for Low- and Moderate-Income Households

    Broader source: Energy.gov [DOE]

    Better Buildings Residential Network Multifamily and Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014.

  17. 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.

  18. 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.

  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. 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 ...

  1. 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

  2. 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.

  3. 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...

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

    Broader source: Energy.gov [DOE]

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

  5. Household heating bills expected to be lower this winter

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

    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 ...

  6. 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

  7. 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

  8. Fact #638: August 30, 2010 Average Expenditure for a New Car Declines in Relation to Family Earnings

    Broader source: Energy.gov [DOE]

    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...

  9. 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 Atlantic, and Pacific), MSA size, and the availability of rail. Extrapolating NHTS data within small geographic areas could risk developing and subsequently using unreliable estimates. For example, if a planning agency in City X of State Y estimates travel rates and other travel characteristics based on survey data collected from NHTS sample households that were located in City X of State Y, then the agency could risk developing and using unreliable estimates for their planning process. Typically, this limitation significantly increases as the size of an area decreases. That said, the NHTS contains a wealth of information that could allow statistical inferences about small geographic areas, with a pre-determined level of statistical certainty. The question then becomes whether a method can be developed that integrates the NHTS data and other data to estimate key travel characteristics for small geographic areas such as Census tract and transportation analysis zone, and whether this method can outperform other, competing methods.

  10. Determinants of Household Use of Selected Energy Star Appliances

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

    Determinants of Household Use of Selected Energy Star Appliances May 2016 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Determinants of Household Use of Selected Energy Star Appliances i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of

  11. Table 1.6 State-Level Energy Consumption, Expenditure, and Price Estimates, 2010

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

    6 State-Level Energy Consumption, Expenditure, and Price Estimates, 2010 Rank Consumption Consumption per Capita Expenditures 1 Expenditures 1 per Capita Prices 1 Trillion Btu Million Btu Million Dollars 2 Dollars 2 Dollars 2 per Million Btu 1 Texas 11,769.9 Wyoming 948.1 Texas 137,532 Alaska 8,807 Hawaii 30.75 2 California 7,825.7 Alaska 898.5 California 117,003 Louisiana 8,661 District of Columbia 26.19 3 Florida 4,381.9 Louisiana 894.4 New York 61,619 Wyoming 7,904 Connecticut 25.63 4

  12. Characterization of household hazardous waste from Marin County, California, and New Orleans, Louisiana

    SciTech Connect (OSTI)

    Rathje, W.L.; Wilson, D.C.; Lambou, V.W.; Herndon, R.C.

    1987-09-01

    There is a growing concern that certain constituents of common household products, that are discarded in residential garbage, may be potentially harmful to human health and the environment by adversely affecting the quality of ground and surface water. A survey of hazardous wastes in residential garbage from Marin County, California, and New Orleans, Louisiana, was conducted in order to determine the amount and characteristics of such wastes that are entering municipal landfills. The results of the survey indicate that approximately 642 metric tons of hazardous waste are discarded per year for the New Orleans study area and approximately 259 metric tons are discarded per year for the Marin County study area. Even though the percent of hazardous household waste in the garbage discarded in both study areas was less than 1%, it represents a significant quantity of hazardous waste because of the large volume of garbage involved.

  13. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  14. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

    SciTech Connect (OSTI)

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

    2015-10-01

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

  16. 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

  17. 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

  18. 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%

  19. 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%

  20. 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

  1. 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)

  2. 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)

  3. 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)

  4. 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

  5. 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%

  6. 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%

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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...

  12. 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

  13. A Glance at China’s Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-22

    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.

  14. 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 York MPOs. The 1995 and 2001 survey data make it possible to examine and identify travel trends over time. This report does not address, however, the causes of the differences and/or trends.

  15. Evaluation of bulk paint worker exposure to solvents at household hazardous waste collection events

    SciTech Connect (OSTI)

    Cameron, M.

    1995-09-01

    In fiscal year 93/94, over 250 governmental agencies were involved in the collection of household hazardous wastes in the State of California. During that time, over 3,237,000 lbs. of oil based paint were collected in 9,640 drums. Most of this was in lab pack drums, which can only hold up to 20 one gallon cans. Cost for disposal of such drums is approximately $1000. In contrast, during the same year, 1,228,000 lbs. of flammable liquid were collected in 2,098 drums in bulk form. Incineration of bulked flammable liquids is approximately $135 per drum. Clearly, it is most cost effective to bulk flammable liquids at household hazardous waste events. Currently, this is the procedure used at most Temporary Household Hazardous Waste Collection Facilities (THHWCFs). THHWCFs are regulated by the Department of Toxic Substances Control (DTSC) under the new Permit-by Rule Regulations. These regulations specify certain requirements regarding traffic flow, emergency response notifications and prevention of exposure to the public. The regulations require that THHWCF operators bulk wastes only when the public is not present. [22 CCR, section 67450.4 (e) (2) (A)].Santa Clara County Environmental Health Department sponsors local THHWCF`s and does it`s own bulking. In order to save time and money, a variance from the regulation was requested and an employee monitoring program was initiated to determine actual exposure to workers. Results are presented.

  16. Household Vehicles Energy Use: Latest Data & Trends

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

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

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

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

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

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

    Broader source: Energy.gov [DOE]

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

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

    Broader source: Energy.gov [DOE]

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

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

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

    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 ...

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

    Broader source: Energy.gov [DOE]

    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...

  2. 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

  3. Model development for household waste prevention behaviour

    SciTech Connect (OSTI)

    Bortoleto, Ana Paula; Kurisu, Kiyo H.; Hanaki, Keisuke

    2012-12-15

    Highlights: Black-Right-Pointing-Pointer We model waste prevention behaviour using structure equation modelling. Black-Right-Pointing-Pointer We merge attitude-behaviour theories with wider models from environmental psychology. Black-Right-Pointing-Pointer Personal norms and perceived behaviour control are the main behaviour predictors. Black-Right-Pointing-Pointer Environmental concern, moral obligation and inconvenience are the main influence on the behaviour. Black-Right-Pointing-Pointer Waste prevention and recycling are different dimensions of waste management behaviour. - Abstract: Understanding waste prevention behaviour (WPB) could enable local governments and decision makers to design more-effective policies for reducing the amount of waste that is generated. By merging well-known attitude-behaviour theories with elements from wider models from environmental psychology, an extensive cognitive framework that provides new and valuable insights is developed for understanding the involvement of individuals in waste prevention. The results confirm the usefulness of the theory of planned behaviour and of Schwartz's altruistic behaviour model as bases for modelling participation in waste prevention. A more elaborate integrated model of prevention was shown to be necessary for the complete analysis of attitudinal aspects associated with waste prevention. A postal survey of 158 respondents provided empirical support for eight of 12 hypotheses. The proposed structural equation indicates that personal norms and perceived behaviour control are the main predictors and that, unlike the case of recycling, subjective norms have a weak influence on WPB. It also suggests that, since social norms have not presented a direct influence, WPB is likely to be influenced by a concern for the environment and the community as well by perceptions of moral obligation and inconvenience. Results also proved that recycling and waste prevention represent different dimensions of waste management behaviour requiring particular approaches to increase individuals' engagement in future policies.

  4. Effects of the R and D tax credit on energy R and D expenditures: an econometric analysis

    SciTech Connect (OSTI)

    Moe, R.J.; Kee, J.R.; Lackey, K.C.; Cronin, F.J.

    1985-02-01

    Objective of the study was to estimate the effects on industrial energy research and development (R and D) expenditures of the R and D Tax Credit component of the Economic Recovery Tax Act of 1981. Two tasks were performed. The first task was to collect data on industrial R and D expenditures, sales, oil prices, and price deflators. The R and D expenditure data were obtained from the National Science Foundation; other data were collected from Commerce Department and Department of Energy publications. The second task was to perform an econometric analysis of the effects of the tax credit on industrial R and D expenditures. Equations relating: (1) total; and (2) energy-related R and D expenditures to sales, oil prices, and a variable representing the availability of the tax credit were estimated, using data for each of seven manufacturing industries and eleven years. The analysis showed that the tax credit caused real total industrial R and D expenditures to be 9.1% greater than they would have been without the credit, but caused real energy industrial R and D expenditures to be 13.8% less than they would have been without the tax credit.

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

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

    November, U.S. households are forecast to consume more heating fuels than ... That's the latest forecast from the U.S. Energy Information Administration. Propane users ...

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

    Reports and Publications (EIA)

    2004-01-01

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

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

    SciTech Connect (OSTI)

    none,

    2012-09-20

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

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

    SciTech Connect (OSTI)

    Bernstad, A.; Cour Jansen, J. la

    2011-08-15

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

  9. Cost comparison between private and public collection of residual household waste: Multiple case studies in the Flemish region of Belgium

    SciTech Connect (OSTI)

    Jacobsen, R.; Buysse, J.; Gellynck, X.

    2013-01-15

    Highlights: Black-Right-Pointing-Pointer The goal is to compare collection costs for residual household waste. Black-Right-Pointing-Pointer We have clustered all municipalities in order to find mutual comparable pairs. Black-Right-Pointing-Pointer Each pair consists of one private and one public operating waste collection program. Black-Right-Pointing-Pointer All cases show that private service has lower costs than public service. Black-Right-Pointing-Pointer Municipalities were contacted to identify the deeper causes for the waste management program. - Abstract: The rising pressure in terms of cost efficiency on public services pushes governments to transfer part of those services to the private sector. A trend towards more privatizing can be noticed in the collection of municipal household waste. This paper reports the findings of a research project aiming to compare the cost between the service of private and public collection of residual household waste. Multiple case studies of municipalities about the Flemish region of Belgium were conducted. Data concerning the year 2009 were gathered through in-depth interviews in 2010. In total 12 municipalities were investigated, divided into three mutual comparable pairs with a weekly and three mutual comparable pairs with a fortnightly residual waste collection. The results give a rough indication that in all cases the cost of private service is lower than public service in the collection of household waste. Albeit that there is an interest in establishing whether there are differences in the costs and service levels between public and private waste collection services, there are clear difficulties in establishing comparisons that can be made without having to rely on a large number of assumptions and corrections. However, given the cost difference, it remains the responsibility of the municipalities to decide upon the service they offer their citizens, regardless the cost efficiency: public or private.

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

    Buildings Energy Data Book [EERE]

    2 Annual Energy Expenditures per Gross Square Foot of Federal Floorspace Stock, by Year ($2010) FY 1985 2.13 FY 2000 1.36 FY 2001 1.58 FY 2002 1.49 FY 2003 1.45 FY 2004 1.54 FY 2005 1.59 FY 2006 2.01 (1) FY 2007 2.01 Note(s): Source(s): Total Federal buildings and facilities energy expenditures in FY 2006 were $5.79 billion (in $2010). 1) Increase due to change in FEMP categorization of Federal buildings. DOE/FEMP, Annual Report to Congress on FEMP FY 2007, Jan. 2010, Table A-9, p. 97 and Table

  11. Special Inquiry on the Office of the Chief Financial Officer's Information Technology Expenditures, OAS-RA-L-12-01

    Energy Savers [EERE]

    Special Inquiry on the Office of the Chief Financial Officer's Information Technology Expenditures OAS-RA-L-12-01 November 2011 Department of Energy Washington, DC 20585 November 28, 2011 MEMORANDUM FOR THE DEPUTY SECRETARY FROM: Gregory H. Friedman Inspector General SUBJECT: INFORMATION: Special Report on "Inquiry on the Office of the Chief Financial Officer's Information Technology Expenditures" INTRODUCTION The Office of the Chief Financial Officer (OCFO) is responsible for ensuring

  12. Nonresidential buildings energy consumption survey: 1979 consumption and expenditures. Part 2. Steam, fuel oil, LPG, and all fuels

    SciTech Connect (OSTI)

    Patinkin, L.

    1983-12-01

    This report presents data on square footage and on total energy consumption and expenditures for commercial buildings in the contiguous United States. Also included are detailed consumption and expenditures tables for fuel oil or kerosene, liquid petroleum gas (LPG), and purchased steam. Commercial buildings include all nonresidential buildings with the exception of those where industrial activities occupy more of the total square footage than any other type of activity. 7 figures, 23 tables.

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

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

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

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

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

    3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Census Region and Division Northeast

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

    Broader source: Energy.gov [DOE]

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

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

    Broader source: Energy.gov [DOE]

    Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people—be they roommates, spouses, children, or maybe even...

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

    Energy Savers [EERE]

    Money | Department of Energy Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm Addthis Students can register now to save energy and win prizes with the Home Energy Challenge. Students can register now to save energy and win prizes with the Home Energy Challenge. Eric Barendsen Energy Technology Program Specialist, Office of Energy Efficiency and Renewable Energy

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

    SciTech Connect (OSTI)

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

    1999-07-16

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

  19. Energy consumption and expenditure projections by population group on the basis of the annual energy outlook 1999 forecast

    SciTech Connect (OSTI)

    Poyer, D.A.; Balsley, J.H.

    2000-01-07

    This report presents an analysis of the relative impact of the base-case scenario used in Annual Energy Outlook 1999 on different population groups. Projections of energy consumption and expenditures, as well as energy expenditure as a share of income, from 1996 to 2020 are given. The projected consumption of electricty, natural gas, distillate fuel, and liquefied petroleum gas during this period is also reported for each population group. In addition, this report compares the findings of the Annual Energy Outlook 1999 report with the 1998 report. Changes in certain indicators and information affect energy use forecasts, and these effects are analyzed and discussed.

  20. Residential Transportation Historical Data Tables for 1983-2001

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

    per household and per vehicle; fuel consumption; fuel expenditures; and fuel economy. Excel PDF Trends in Households & Vehicles Table 1. Number of Households with Vehicles excel...

  1. Municipal solid waste generation in municipalities: Quantifying impacts of household structure, commercial waste and domestic fuel

    SciTech Connect (OSTI)

    Lebersorger, S.; Beigl, P.

    2011-09-15

    Waste management planning requires reliable data concerning waste generation, influencing factors on waste generation and forecasts of waste quantities based on facts. This paper aims at identifying and quantifying differences between different municipalities' municipal solid waste (MSW) collection quantities based on data from waste management and on socio-economic indicators. A large set of 116 indicators from 542 municipalities in the Province of Styria was investigated. The resulting regression model included municipal tax revenue per capita, household size and the percentage of buildings with solid fuel heating systems. The model explains 74.3% of the MSW variation and the model assumptions are met. Other factors such as tourism, home composting or age distribution of the population did not significantly improve the model. According to the model, 21% of MSW collected in Styria was commercial waste and 18% of the generated MSW was burned in domestic heating systems. While the percentage of commercial waste is consistent with literature data, practically no literature data are available for the quantity of MSW burned, which seems to be overestimated by the model. The resulting regression model was used as basis for a waste prognosis model (Beigl and Lebersorger, in preparation).

  2. Influence of assumptions about household waste composition in waste management LCAs

    SciTech Connect (OSTI)

    Slagstad, Helene, E-mail: helene.slagstad@ntnu.no [Department of Hydraulic and Environmental Engineering, Norwegian University of Science and Technology, N-7491 Trondheim (Norway); Brattebo, Helge [Department of Hydraulic and Environmental Engineering, Norwegian University of Science and Technology, N-7491 Trondheim (Norway)

    2013-01-15

    Highlights: Black-Right-Pointing-Pointer Uncertainty in waste composition of household waste. Black-Right-Pointing-Pointer Systematically changed waste composition in a constructed waste management system. Black-Right-Pointing-Pointer Waste composition important for the results of accounting LCA. Black-Right-Pointing-Pointer Robust results for comparative LCA. - Abstract: This article takes a detailed look at an uncertainty factor in waste management LCA that has not been widely discussed previously, namely the uncertainty in waste composition. Waste composition is influenced by many factors; it can vary from year to year, seasonally, and with location, for example. The data publicly available at a municipal level can be highly aggregated and sometimes incomplete, and performing composition analysis is technically challenging. Uncertainty is therefore always present in waste composition. This article performs uncertainty analysis on a systematically modified waste composition using a constructed waste management system. In addition the environmental impacts of several waste management strategies are compared when applied to five different cities. We thus discuss the effect of uncertainty in both accounting LCA and comparative LCA. We found the waste composition to be important for the total environmental impact of the system, especially for the global warming, nutrient enrichment and human toxicity via water impact categories.

  3. Household mold and dust allergens: Exposure, sensitization and childhood asthma morbidity

    SciTech Connect (OSTI)

    Gent, Janneane F.; Kezik, Julie M.; Hill, Melissa E.; Tsai, Eling; Li, De-Wei; Leaderer, Brian P.

    2012-10-15

    Background: Few studies address concurrent exposures to common household allergens, specific allergen sensitization and childhood asthma morbidity. Objective: To identify levels of allergen exposures that trigger asthma exacerbations in sensitized individuals. Methods: We sampled homes for common indoor allergens (fungi, dust mites (Der p 1, Der f 1), cat (Fel d 1), dog (Can f 1) and cockroach (Bla g 1)) for levels associated with respiratory responses among school-aged children with asthma (N=1233) in a month-long study. Blood samples for allergy testing and samples of airborne fungi and settled dust were collected at enrollment. Symptoms and medication use were recorded on calendars. Combined effects of specific allergen sensitization and level of exposure on wheeze, persistent cough, rescue medication use and a 5-level asthma severity score were examined using ordered logistic regression. Results: Children sensitized and exposed to any Penicillium experienced increased risk of wheeze (odds ratio [OR] 2.12 95% confidence interval [CI] 1.12, 4.04), persistent cough (OR 2.01 95% CI 1.05, 3.85) and higher asthma severity score (OR 1.99 95% CI 1.06, 3.72) compared to those not sensitized or sensitized but unexposed. Children sensitized and exposed to pet allergen were at significantly increased risk of wheeze (by 39% and 53% for Fel d 1>0.12 {mu}g/g and Can f 1>1.2 {mu}g/g, respectively). Increased rescue medication use was significantly associated with sensitization and exposure to Der p 1>0.10 {mu}g/g (by 47%) and Fel d 1>0.12 {mu}g/g (by 32%). Conclusion: Asthmatic children sensitized and exposed to low levels of common household allergens Penicillium, Der p 1, Fel d 1 and Can f 1 are at significant risk for increased morbidity. - Highlights: Black-Right-Pointing-Pointer Few studies address concurrent allergen exposures, sensitization and asthma morbidity. Black-Right-Pointing-Pointer Children with asthma were tested for sensitivity to common indoor allergens. Black-Right-Pointing-Pointer Homes were sampled for these allergens and asthma morbidity monitored during the subsequent month. Black-Right-Pointing-Pointer Children exposed and sensitized to Penicillium, Der p, Fel d, Can f risk increased asthma morbidity. Black-Right-Pointing-Pointer These children might benefit from targeted intervention strategies.

  4. Table 3.5 Consumer Expenditure Estimates for Energy by Source, 1970-2010 (Million Dollars )

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

    Consumer Expenditure Estimates for Energy by Source, 1970-2010 (Million Dollars 1) Year Primary Energy 2 Electric Power Sector 11,12 Retail Electricity 13 Total Energy 10,14 Coal Coal Coke Net Imports 3 Natural Gas 4 Petroleum Nuclear Fuel Biomass 9 Total 10 Distillate Fuel Oil Jet Fuel 5 LPG 6 Motor Gasoline 7 Residual Fuel Oil Other 8 Total 1970 4,630 -75 10,891 6,253 1,441 2,395 31,596 2,046 4,172 47,904 44 438 63,872 -4,357 23,345 82,860 1971 4,902 -40 12,065 6,890 1,582 2,483 33,478 2,933

  5. LCA for household waste management when planning a new urban settlement

    SciTech Connect (OSTI)

    Slagstad, Helene; Brattebo, Helge

    2012-07-15

    Highlights: Black-Right-Pointing-Pointer Household waste management of a new carbon neutral settlement. Black-Right-Pointing-Pointer EASEWASTE as a LCA tool to compare different centralised and decentralised solutions. Black-Right-Pointing-Pointer Environmental benefit or close to zero impact in most of the categories. Black-Right-Pointing-Pointer Paper and metal recycling important for the outcome. Black-Right-Pointing-Pointer Discusses the challenges of waste prevention planning. - Abstract: When planning for a new urban settlement, industrial ecology tools like scenario building and life cycle assessment can be used to assess the environmental quality of different infrastructure solutions. In Trondheim, a new greenfield settlement with carbon-neutral ambitions is being planned and five different scenarios for the waste management system of the new settlement have been compared. The results show small differences among the scenarios, however, some benefits from increased source separation of paper and metal could be found. The settlement should connect to the existing waste management system of the city, and not resort to decentralised waste treatment or recovery methods. However, as this is an urban development project with ambitious goals for lifestyle changes, effort should be put into research and initiatives for proactive waste prevention and reuse issues.

  6. The evolving price of household LED lamps: Recent trends and historical comparisons for the US market

    SciTech Connect (OSTI)

    Gerke, Brian F.; Ngo, Allison T.; Alstone, Andrea L.; Fisseha, Kibret S.

    2014-10-14

    In recent years, household LED light bulbs (LED A lamps) have undergone a dramatic price decline. Since late 2011, we have been collecting data, on a weekly basis, for retail offerings of LED A lamps on the Internet. The resulting data set allows us to track the recent price decline in detail. LED A lamp prices declined roughly exponentially with time in 2011-2014, with decline rates of 28percent to 44percent per year depending on lumen output, and with higher-lumen lamps exhibiting more rapid price declines. By combining the Internet price data with publicly available lamp shipments indices for the US market, it is also possible to correlate LED A lamp prices against cumulative production, yielding an experience curve for LED A lamps. In 2012-2013, LED A lamp prices declined by 20-25percent for each doubling in cumulative shipments. Similar analysis of historical data for other lighting technologies reveals that LED prices have fallen significantly more rapidly with cumulative production than did their technological predecessors, which exhibited a historical decline of 14-15percent per doubling of production.

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

    SciTech Connect (OSTI)

    Zimring, Mark; Fuller, Merrian

    2011-01-24

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

  8. "Table HC15.3 Household Characteristics by Four Most Populated States, 2005"

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

    3 Household Characteristics by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Household Characteristics",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Household Size" "1 Person",30,1.8,1.9,2,3.2 "2 Persons",34.8,2.2,2.3,2.4,3.2 "3 Persons",18.4,1.1,1.3,1.2,1.8

  9. Separate collection of household food waste for anaerobic degradation - Comparison of different techniques from a systems perspective

    SciTech Connect (OSTI)

    Bernstad, A.; Cour Jansen, J. la

    2012-05-15

    Highlight: Black-Right-Pointing-Pointer Four modern and innovative systems for household food waste collection are compared. Black-Right-Pointing-Pointer Direct emissions and resource use were based on full-scale data. Black-Right-Pointing-Pointer Conservation of nutrients/energy content over the system was considered. Black-Right-Pointing-Pointer Systems with high energy/nutrient recovery are most environmentally beneficial. - Abstract: Four systems for household food waste collection are compared in relation the environmental impact categories eutrophication potential, acidification potential, global warming potential as well as energy use. Also, a hotspot analysis is performed in order to suggest improvements in each of the compared collection systems. Separate collection of household food waste in paper bags (with and without drying prior to collection) with use of kitchen grinders and with use of vacuum system in kitchen sinks were compared. In all cases, food waste was used for anaerobic digestion with energy and nutrient recovery in all cases. Compared systems all resulted in net avoidance of assessed environmental impact categories; eutrophication potential (-0.1 to -2.4 kg NO{sub 3}{sup -}eq/ton food waste), acidification potential (-0.4 to -1.0 kg SO{sub 2}{sup -}eq/ton food waste), global warming potential (-790 to -960 kg CO{sub 2}{sup -}eq/ton food waste) and primary energy use (-1.7 to -3.6 GJ/ton food waste). Collection with vacuum system results in the largest net avoidance of primary energy use, while disposal of food waste in paper bags for decentralized drying before collection result in a larger net avoidance of global warming, eutrophication and acidification. However, both these systems not have been taken into use in large scale systems yet and further investigations are needed in order to confirm the outcomes from the comparison. Ranking of scenarios differ largely if considering only emissions in the foreground system, indicating the importance of taking also downstream emissions into consideration when comparing different collection systems. The hot spot identification shows that losses of organic matter in mechanical pretreatment as well as tank connected food waste disposal systems and energy in drying and vacuum systems reply to the largest impact on the results in each system respectively.

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

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

    Average U.S. household to spend $710 less on gasoline during 2015 Even with the recent increases in gasoline prices, the average U.S. household is still expected save $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 average price for regular gasoline is expected to be $2.39 per gallon this year. That's almost $1 less than the $3.36 average in 2014. Lower crude oil prices

  11. 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

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

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

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

  13. "Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005"

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

    0 Home Appliances Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Appliances Usage Indicators"

  14. "Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005"

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

    2 Home Electronics Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Electronics Usage Indicators"

  15. "Table HC7.5 Space Heating Usage Indicators by Household Income, 2005"

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

    5 Space Heating Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Space Heating Usage Indicators" "Total U.S. Housing

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

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

    Drivers of U.S. Household Energy Consumption, 1980-2009 February 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Drivers of U.S. Household Energy Consumption, 1980-2009 i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any

  17. Search results | Department of Energy

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

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

  18. Search results | Department of Energy

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

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

  19. Search results | Department of Energy

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

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

  20. Search results | Department of Energy

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

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

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

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

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

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

    Broader source: Energy.gov [DOE]

    In 2009, getting to and from work accounted for about 27% of household vehicle-miles of travel (VMT). Work-related business was 8.4% of VMT in 2001, but declined to 6.7% in 2009, possibly due to...

  3. Summary of expenditures of rebates from the low-level radioactive waste surcharge escrow account for calendar year 1995

    SciTech Connect (OSTI)

    1996-06-01

    This report is submitted in response to Title 1 of the 1980 Low-Level Radioactive Waste Policy Act, as amended, (the Act). The report summarizes expenditures made by compact regions and unaffiliated states during calendar year 1995 of surcharge rebates from the July 1, 1986, January 1, 1988, and January 1, 1990, milestones, and the January 1, 1993, deadline. Section 5(d)(2)(A) of the Act requires the Department of Energy (DOE) to administer a surcharge escrow account. This account consists of a portion of the surcharge fees paid by generators of low-level radioactive waste in nonsited compact regions (compact regions currently without disposal sites) and nonmember states (states without disposal sites that are not members of compact regions) to the three sited states (states with operating disposal facilities--Nevada, South Carolina, and Washington) for the use of facilities in sited states through the end of 1992. In administering the surcharge escrow account, the Act requires DOE to: (1) Invest the funds in interest-bearing United States Government securities with the highest available yield; (2) Determine eligibility for rebates of the funds by evaluating compact region and state progress toward developing new disposal sites against the milestone requirements set forth in the Act; (3) Disburse the collected rebates and accrued interest to eligible compact regions, states, or generators; (4) Assess compliance of rebate expenditures in accordance with the conditions and limitations prescribed in the Act; and (5) Submit a report annually to Congress summarizing rebate expenditures by state and compact region and assessing the compliance of each such state or compact region with the requirement for expenditure of the rebates as provided in section 5(d)(2)(E) of the Act.

  4. Summary of expenditures of rebates from the DOE low-level radioactive waste surcharge escrow account for calendar year 1986

    SciTech Connect (OSTI)

    Not Available

    1987-06-01

    The Low-Level Radioactive Waste Policy Amendments Act of 1985, Public Law 99-240, requires the Department of Energy (DOE) to manage an escrow account creatd by collection of 25% of the non-penalty surcharge fees paid by the generators in non-sited regions and nonmember states to sited states for disposal of low-level radioactive waste. For the milestone period ending June 30, 1986, a total of $921,807.84, representing surcharge fees collected and interest earned, was in escrow during 1986 for rebate to the nonmember states, non-sited compact regions, and sited states. As of December 31, 1986, $802,194.54 had been rebated from the Escrow Account with an additional $118,517.62 scheduled for rebate in early 1987. The remaining rebate to be disbursed under this milestone is $1,095.68 for the state of Delaware. At the request of the state of Delaware, this rebate amount is being held in the Escrow Account until the state provides specific instructions for its disbursement. Individual rebate expenditure reports were submitted to DOE by all the non-sited compact regions and nonmember states that received rebates in 1986. Only $14.00 of these rebates were expended in 1986. DOE reviewed all of these reports and concluded that the single expenditure complies with the expenditure limitations stated in the Act.

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

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

    RoperASW is a well respected survey research firm. You will return your completed forms to ... The government may bring a civil action to prohibit reporting violations which may result ...

  6. Emissions of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans from the open burning of household waste in barrels

    SciTech Connect (OSTI)

    Lemieux, P.M.; Lutes, C.C.; Abbott, J.A.; Aldous, K.M.

    2000-02-01

    Backyard burning of household waste in barrels is a common waste disposal practice for which pollutant emissions have not been well characterized. This study measured the emissions of several pollutants, including polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDDs/PCDFs), from burning mixtures designed to simulate waste generated by a recycling and a nonrecycling family in a 208-L (55-gal) burn barrel at the EPA's Open Burning Test Facility. This paper focuses on the PCDD/PCDF emissions and discusses the factors influencing PCDD/PCDF formation for different test burns. Four test burns were made in which the amount of waste placed in the barrel varied from 6.4 to 13.6 kg and the amount actually burned varied from 46.6% to 68.1%. Emissions of total PCDDs/PCDFs ranged between 0.0046 and 0.48 mg/kg of waste burned. Emissions are also presented in terms of 2,3,7,8-TCDD toxic equivalents. Emissions of PCDDs/PCDFs appear to correlate with both copper and hydrochloric acid emissions. The results of this study indicate that backyard burning emits more PCDDs/PCDFs on a mass of refuse burned basis than various types of municipal waste combustors (MWCs). Comparison of burn barrel emissions to emissions from a hypothetical modern MWC equipped with high-efficiency flue gas cleaning technology indicates that about 2--40 households burning their trash daily in barrels can produce average PCDD/PCDF emissions comparable to a 182,000 kg/day (200 ton/day) MWC facility. This study provides important data on a potentially significant source of emissions of PCDDs/PCDFs.

  7. Table 2.6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009

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

    6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009 Appliance Year Change 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 1980 to 2009 Total Households (millions) 77 78 82 83 84 86 91 94 97 101 107 111 114 32 Percent of Households<//td> Space Heating - Main Fuel 1 Natural Gas 55 55 55 56 57 55 55 55 53 52 55 52 50 -5 Electricity 2 16 17 18 17 16 17 20 23 26 29 29 30 35 17 Liquefied Petroleum Gases 4 5 5 4 5 5 5 5 5 5 5 5 5 0 Distillate

  8. Communicating Results

    Broader source: Energy.gov [DOE]

    Communicating Results: Provide exam results to participants, as well as information regarding any conditions that may require follow-up medical care with their personal physicians or specialists, and provide information regarding possible compensation for work-related illnesses.

  9. The importance of China's household sector for black carbon emissions - article no. L12708

    SciTech Connect (OSTI)

    Streets, D.G.; Aunan, K.

    2005-06-30

    The combustion of coal and biofuels in Chinese households is a large source of black carbon (BC), representing about 10-15% of total global emissions during the past two decades, depending on the year. How the Chinese household sector develops during the next 50 years will have an important bearing on future aerosol concentrations, because the range of possible outcomes (about 550 Gg yr{sup -1}) is greater than total BC emissions in either the United States or Europe (each about 400-500 Gg yr{sup -1}). In some Intergovernmental Panel on Climate Change scenarios biofuels persist in rural China for at least the next 50 years, whereas in other scenarios a transition to cleaner fuels and technologies effectively mitigates BC emissions. This paper discusses measures and policies that would help this transition and also raises the possibility of including BC emission reductions as a post-Kyoto option for China and other developing countries.

  10. Explosive Results

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

    Explosive National Security Science Latest Issue:April 2016 past issues All Issues » submit Explosive Results Scientists at Los Alamos are solving national security challenges, from the threat of toothpaste-tube bombs on airliners to ensuring the safety of our nuclear stockpile. April 1, 2016 Explosive Results To test whether a travel-toothpaste-tube-sized bomb could bring down an airliner, Los Alamos scientists tried to blow a hole through half-inch-thick aircraft-grade aluminum using an

  11. Household`s choices of efficiency levels for appliances: Using stated- and revealed-preference data to identify the importance of rebates and financing arrangements

    SciTech Connect (OSTI)

    Train, K.; Atherton, T.

    1994-11-01

    We examine customers` choice between standard and high-efficiency equipment, and the impact of utility incentives such as rebates and loans on this decision. Using data from interviews with 400 households, we identify the factors that customers consider in their choice of efficiency level for appliances and the relative importance of these factors. We build a model that describes customers` choices and can be used to predict choices in future situations under changes in the attributes of appliances and in the utility`s DSM and as part of the appliance-choice component of utilities` end-use forecasting systems. As examples, the model is used to predict the impacts of: doubling the size of rebates, replacing rebates with financing programs, and offering loans and rebates as alternative options for customers.

  12. Table HC6.10 Home Appliances Usage Indicators by Number of Household Members, 2005

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

    0 Home Appliances Usage Indicators by Number of Household Members, 2005 Total.............................................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day........................................... 8.2 1.4 1.9 1.4 1.0 2.4 2 Times A Day........................................................ 24.6 4.3 7.6 4.3 4.8 3.7 Once a Day............................................................ 42.3 9.9

  13. Table HC6.11 Home Electronics Characteristics by Number of Household Members, 2005

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

    1 Home Electronics Characteristics by Number of Household Members, 2005 Total...................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer ................... 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer................................ 75.6 13.8 25.4 14.4 13.2 8.8 Number of Desktop PCs 1.................................................................. 50.3 11.9 17.4 8.5 7.3 5.2

  14. Table HC6.12 Home Electronics Usage Indicators by Number of Household Members, 2005

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

    2 Home Electronics Usage Indicators by Number of Household Members, 2005 Total................................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer............................. 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer.......................................... 75.6 13.8 25.4 14.4 13.2 8.8 Most-Used Personal Computer Type of PC Desk-top Model.....................................................

  15. Table HC6.2 Living Space Characteristics by Number of Household Members, 2005

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

    2 Living Space Characteristics by Number of Household Members, 2005 Total...................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500............................................... 3.2 1.7 0.8 0.4 0.3 Q 500 to 999....................................................... 23.8 10.2 6.4 3.4 2.3 1.5 1,000 to 1,499................................................. 20.8 5.5 6.3 3.0 3.3 2.6 1,500 to

  16. Table HC6.9 Home Appliances Characteristics by Number of Household Members, 2005

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

    HC6.9 Home Appliances Characteristics by Number of Household Members, 2005 Total U.S.............................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Conventional Ovens Use an Oven.................................................. 109.6 29.5 34.4 18.2 15.7 11.8 1................................................................. 103.3 28.4 32.0 17.3 14.7 11.0 2 or More.................................................... 6.2 1.1 2.5 1.0 0.9 0.8 Do Not

  17. Assessment of lead contamination in Bahrain environment. I. Analysis of household paint

    SciTech Connect (OSTI)

    Madany, I.M.; Ali, S.M.; Akhter, M.S.

    1987-01-01

    The analysis of lead in household paint collected from various old buildings in Bahrain is reported. The atomic absorption spectrophotometric method, both flame and flameless (graphite furnace) techniques, were used for the analysis. The concentrations of lead in paint were found in the range 200 to 5700 mg/kg, which are low compared to the limit of 0.5% in UK and 0.06% in USA. Nevertheless, these are hazardous. Recommendations are reported in order to avoid paint containing lead. 17 references, 1 table.

  18. 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 findings are taken into account when designing new or improving existing special waste collection schemes. Improving the collection of WEEE is also recommended as one way to also improve the collection of batteries due to the large fraction of batteries found as built-in. The findings in this study were comparable to other western European studies, suggesting that the recommendations made in this study could apply to other western European countries as well.

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

    SciTech Connect (OSTI)

    Karvelas, D.E.; Jody, B.J.; Poykala, J.A. Jr.; Daniels, E.J.; Arman, B. |

    1996-03-01

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

  20. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    3 Household Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Household Characteristics"

  1. Transportation Fact of the Week - 2012 Archive | Department of...

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

    2010 October 15, 2012 748 Components of Household Expenditures on Transportation, 1984-2010 October 8, 2012 747 Behind Housing, Transportation is the Top Household ...

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

    Gasoline and Diesel Fuel Update (EIA)

    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...

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

    Gasoline and Diesel Fuel Update (EIA)

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

  4. Table 3.6 Consumer Expenditure Estimates for Energy by End-Use Sector, 1970-2010 (Million Dollars )

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

    Consumer Expenditure Estimates for Energy by End-Use Sector, 1970-2010 (Million Dollars 1) Year Residential Commercial Industrial Transportation Natural Gas 2 Petroleum Retail Electricity 3 Total 4 Natural Gas 2 Petroleum 5 Retail Electricity 3 Total 6,7 Coal Natural Gas 2 Petroleum 5 Biomass 8 Retail Electricity 3 Total 7,9 Petroleum 5 Total 7,10 1970 5,272 4,186 10,352 20,112 1,844 1,440 7,319 10,678 2,082 2,625 6,069 366 5,624 16,691 35,327 35,379 1971 5,702 4,367 11,589 21,934 2,060 1,574

  5. Table HC6.4 Space Heating Characteristics by Number of Household Members, 2005

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

    4 Space Heating Characteristics by Number of Household Members, 2005 Total..................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Space Heating Equipment............ 1.2 0.3 0.3 Q 0.2 0.2 Have Main Space Heating Equipment............... 109.8 29.7 34.5 18.2 15.6 11.8 Use Main Space Heating Equipment................. 109.1 29.5 34.4 18.1 15.5 11.6 Have Equipment But Do Not Use It................... 0.8 Q Q Q Q Q Main Heating Fuel and

  6. Table HC6.5 Space Heating Usage Indicators by Number of Household Members, 2005

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

    5 Space Heating Usage Indicators by Number of Household Members, 2005 Total U.S. Housing Units.................................. 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Heating Equipment..................... 1.2 0.3 0.3 Q 0.2 0.2 Have Space Heating Equipment....................... 109.8 29.7 34.5 18.2 15.6 11.8 Use Space Heating Equipment........................ 109.1 29.5 34.4 18.1 15.5 11.6 Have But Do Not Use Equipment.................... 0.8 Q Q Q Q Q Space Heating Usage During 2005

  7. An Analysis of the Price Elasticity of Demand for Household Appliances

    SciTech Connect (OSTI)

    Fujita, Kimberly; Dale, Larry; Fujita, K. Sydny

    2008-01-25

    This report summarizes our study of the price elasticity of demand for home appliances, including refrigerators, clothes washers, and dishwashers. In the context of increasingly stringent appliance standards, we are interested in what kind of impact the increased manufacturing costs caused by higher efficiency requirements will have on appliance sales. We begin with a review of existing economics literature describing the impact of economic variables on the sale of durable goods.We then describe the market for home appliances and changes in this market over the past 20 years, performing regression analysis on the shipments of home appliances and relevant economic variables including changes to operating cost and household income. Based on our analysis, we conclude that the demand for home appliances is price inelastic.

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

    SciTech Connect (OSTI)

    Herendeen, R.A.

    1983-06-01

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

  9. S U M M A R I E S U.S. Energy Information Administration | State Energy Data 2013: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    Prices and Expenditures 10 Table E8. Primary Energy, Electricity, and Total Energy Expenditure Estimates, 2013 (Million Dollars) State Primary Energy Electric Power Sector g,h Retail Electricity Total Energy g,i Coal Natural Gas a Petroleum Nuclear Fuel Biomass Total g,h,i Distillate Fuel Oil Jet Fuel b LPG c Motor Gasoline d Residual Fuel Oil Other e Total Wood and Waste f Alabama 1,731.6 3,091.3 4,003.6 294.8 251.9 8,443.0 90.5 682.0 13,765.8 352.0 438.7 19,379.5 -3,125.3 7,901.4 24,155.6

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

    SciTech Connect (OSTI)

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

    1994-08-01

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

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

    SciTech Connect (OSTI)

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

    2012-01-01

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

  12. Loss Aversion and Time-Differentiated Electricity Pricing

    SciTech Connect (OSTI)

    Spurlock, C. Anna

    2015-06-01

    I develop a model of loss aversion over electricity expenditure, from which I derive testable predictions for household electricity consumption while on combination time-of-use (TOU) and critical peak pricing (CPP) plans. Testing these predictions results in evidence consistent with loss aversion: (1) spillover effects - positive expenditure shocks resulted in significantly more peak consumption reduction for several weeks thereafter; and (2) clustering - disproportionate probability of consuming such that expenditure would be equal between the TOUCPP or standard flat-rate pricing structures. This behavior is inconsistent with a purely neoclassical utility model, and has important implications for application of time-differentiated electricity pricing.

  13. Word Pro - Untitled1

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

    Household Energy Consumption and Expenditures Household Energy Consumption by End Use, Selected Years, Household Energy Expenditures, Selected Years, 1978-2005¹ 1978-2005¹ Household Energy Consumption for Space Heating by Fuel 2005 Appliances, Electronics, and Lighting Expenditures, Selected Years, 1978-2005¹ 52 U.S. Energy Information Administration / Annual Energy Review 2011 1 For years not shown, there are no data available. 2 Prices are not adjusted for inflation. See "Nominal

  14. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    1 Home Electronics Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Electronics Characteristics"

  15. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    2 Living Space Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Living Space Characteristics"

  16. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    Housing Unit Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Housing Unit Characteristics"

  17. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    4 Space Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Space Heating Characteristics"

  18. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    6 Air Conditioning Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Air Conditioning Characteristics"

  19. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    7 Air-Conditioning Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Air-Conditioning Usage Indicators"

  20. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    HC7.9 Home Appliances Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Appliances Characteristics" "Total

  1. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    3 Lighting Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Lighting Usage Indicators" "Total U.S. Housing

  2. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    8 Water Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Water Heating Characteristics"

  3. S U M M A R I E S U.S. Energy Information Administration | State Energy Data 2013: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    3 Table E11. Commercial Sector Energy Expenditure Estimates, 2013 (Million Dollars) State Primary Energy Retail Electricity Total Energy f Coal Natural Gas a Petroleum Biomass Total f Distillate Fuel Oil Kerosene LPG b Motor Gasoline c Residual Fuel Oil Total d Wood and Waste e Alabama - 312.8 100.1 0.4 49.0 6.3 - 155.8 4.4 472.9 2,376.6 2,849.5 Alaska 43.7 155.9 184.7 0.9 15.8 15.0 - 216.3 2.7 418.6 440.0 858.6 Arizona - 288.1 146.8 (s) 32.4 17.9 - 197.0 2.7 487.9 2,958.0 3,445.9 Arkansas -

  4. S U M M A R I E S U.S. Energy Information Administration | State Energy Data 2013: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    6 Table E14. Electric Power Sector Energy Expenditure Estimates, 2013 (Million Dollars) State Coal Natural Gas a Petroleum Nuclear Fuel Biomass Electricity Imports c Total Energy d Distillate Fuel Oil Petroleum Coke Residual Fuel Oil Total Wood and Waste b Alabama 1,367.8 1,382.3 14.0 - - 14.0 352.0 9.2 - 3,125.3 Alaska 28.8 160.6 76.8 - 12.2 89.0 - - (s) 278.4 Arizona 934.4 1,034.6 11.3 - - 11.3 302.7 5.5 1.3 2,289.9 Arkansas 771.5 404.1 8.3 - 1.0 9.2 75.7 3.1 - 1,263.7 California 12.1 3,732.2

  5. S U M M A R I E S U.S. Energy Information Administration | State Energy Data 2013: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    4 Table E12. Industrial Sector Energy Expenditure Estimates, 2013 (Million Dollars) State Primary Energy Retail Electricity Total Energy f Coal Natural Gas a Petroleum Biomass Total f Coking Coal Steam Coal Total Distillate Fuel Oil LPG b Motor Gasoline c Residual Fuel Oil Other d Total Wood and Waste e Alabama 208.5 155.3 363.9 850.7 552.4 51.1 70.0 31.4 517.7 1,222.5 387.8 2,824.8 1,992.2 4,817.1 Alaska - 0.1 0.1 8.8 664.5 0.9 40.3 - 11.3 717.1 0.2 726.1 184.0 910.1 Arizona - 12.4 12.4 139.3

  6. S U M M A R I E S U.S. Energy Information Administration | State Energy Data 2013: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    2 Table E10. Residential Sector Energy Expenditure Estimates, 2013 (Million Dollars) State Primary Energy Retail Electricity Total Energy e Coal a Natural Gas b Petroleum Biomass Total e Distillate Fuel Oil Kerosene LPG c Total Wood d Alabama - 542.4 2.3 0.4 137.3 139.9 37.3 719.6 3,532.6 4,252.1 Alaska - 170.1 190.3 0.8 14.4 205.5 17.4 392.9 381.2 774.1 Arizona - 552.5 0.3 (s) 141.1 141.4 23.2 717.2 3,878.0 4,595.1 Arkansas - 366.0 0.6 0.2 151.7 152.5 53.6 572.1 1,746.5 2,318.6 California -

  7. S U M M A R I E S U.S. Energy Information Administration | State Energy Data 2013: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    5 Table E13. Transportation Sector Energy Expenditure Estimates, 2013 (Million Dollars) State Primary Energy Retail Electricity Total Energy Coal Natural Gas Petroleum Total Aviation Gasoline Distillate Fuel Oil Jet Fuel a LPG b Lubricants Motor Gasoline c Residual Fuel Oil Total Alabama - 3.2 8.4 3,334.8 294.8 14.5 155.2 8,366.7 59.2 12,233.7 12,236.9 - 12,236.9 Alaska - 0.2 23.0 988.7 2,397.2 2.0 30.1 1,090.5 - 4,531.5 4,531.7 - 4,531.7 Arizona - 22.7 23.0 3,042.0 472.9 26.2 110.8 8,790.2 -

  8. S U M M A R I E S U.S. Energy Information Administration | State Energy Data 2013: Prices and Expenditures

    Gasoline and Diesel Fuel Update (EIA)

    1 Table E9. Total End-Use Energy Expenditure Estimates, 2013 (Million Dollars) State Primary Energy Retail Electricity Total Energy g Coal Natural Gas a Petroleum Biomass Total g Distillate Fuel Oil Jet Fuel b LPG c Motor Gasoline d Residual Fuel Oil Other e Total Wood and Waste f Alabama 363.9 1,708.9 3,989.6 294.8 251.9 8,443.0 90.5 682.0 13,751.9 429.5 16,254.2 7,901.4 24,155.6 Alaska 43.7 335.0 2,028.1 2,397.2 33.2 1,145.8 - 66.0 5,670.4 20.3 6,069.4 1,005.2 7,074.5 Arizona 12.4 1,002.7

  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. U.S. Residential Miscellaneous Refrigeration Products: Results from Amazon Mechanical Turk Surveys

    SciTech Connect (OSTI)

    Greenblatt, Jeffery B.; Young, Scott J.; Yang, Hung-Chia; Long, Timothy; Beraki, Bereket; Price, Sarah K.; Pratt, Stacy; Willem, Henry; Desroches, Louis-Benoit

    2013-11-14

    Amazon Mechanical Turk was used, for the first time, to collect statistically representative survey data from U.S. households on the presence, number, type and usage of refrigerators, freezers, and various “miscellaneous” refrigeration products (wine/beverage coolers, residential icemakers and non-vapor compression refrigerators and freezers), along with household and demographic information. Such products have been poorly studied to date, with almost no information available about shipments, stocks, capacities, energy use, etc. A total of 9,981 clean survey responses were obtained from five distinct surveys deployed in 2012. General refrigeration product survey responses were weighted to demographics in the U.S. Energy Information Administration’s Residential Energy Consumption Survey 2009 dataset. Miscellaneous refrigeration product survey responses were weighted according to demographics of product ownership found in the general refrigeration product surveys. Model number matching for a portion of miscellaneous refrigeration product responses allowed validation of refrigeration product characteristics, which enabled more accurate estimates of the penetrations of these products in U.S. households. We estimated that there were 12.3±1.0 million wine/beverage coolers, 5.5(–3.5,+3.2) million residential icemakers and 4.4(–2.7,+2.3) million non-vapor compression refrigerators in U.S. households in 2012. (All numerical results are expressed with ranges indicating the 95% confidence interval.) No evidence was found for the existence of non-vapor compression freezers. Moreover, we found that 15% of wine/beverage coolers used vapor compression cooling technology, while 85% used thermoelectric cooling technology, with the vast majority of thermoelectric units having capacities of less than 30 wine bottles (approximately 3.5 cubic feet). No evidence was found for the existence of wine/beverage coolers with absorption cooling technology. Additionally, we estimated that there were 3.6±1.0 million hybrid refrigerator-wine/beverage coolers and 0.9±0.5 million hybrid freezer-wine/beverage coolers in U.S. households. We also obtained estimates of miscellaneous refrigeration product capacities, lifetimes, purchase and installation costs, repair frequencies and costs, and maintenance costs. For wine/beverage coolers, we also obtained information on the penetration of built-in units, AC/DC operating capability, the use of internal lights, and distributions of door opening frequencies. This information is essential to develop detailed estimates of national energy usage and life-cycle costs, and would be helpful in obtaining information on other plug-load appliances. Additional information not highlighted in the main report was presented in Appendices.

  11. 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

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

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

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

  13. User interface in ORACLE for the Worldwide Household Goods Information System for Transportation Modernization (WHIST-MOD)

    SciTech Connect (OSTI)

    James, T. ); Loftis, J. )

    1990-07-01

    The Directorate of Personal Property of the Military Traffic Management Command (MTMC) requested that Oak Ridge National laboratory (ORNL) design a prototype decision support system, the Worldwide Household Goods Information System for Transportation Modernization (WHIST-MOD). This decision support system will automate current tasks and provide analysis tools for evaluating the Personal Property Program, predicting impacts to the program, and planning modifications to the program to meet the evolving needs of military service members and the transportation industry. The system designed by ORNL consists of three application modules: system dictionary applications, data acquisition and administration applications, and user applications. The development of the user applications module is divided into two phases. Round 1 is the data selection front-end interface, and Round 2 is the output or back-end interface. This report describes the prototyped front-end interface for the user application module. It discusses user requirements and the prototype design. The information contained in this report is the product of in-depth interviews with MTMC staff, prototype meetings with the users, and the research and design work conducted at ORNL. 18 figs., 2 tabs.

  14. 2004 User Survey Results

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

    13 | Next 2004 User Survey Results Table of Contents Response Summary Respondent Demographics Overall Satisfaction and Importance All Satisfaction, Importance and Usefulness...

  15. 2006 User Survey Results

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

    to provide overall comments about NERSC: Here are the survey results: Respondent Demographics Overall Satisfaction and Importance All Satisfaction, Importance and Usefulness...

  16. 2005 User Survey Results

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

    10 | Next 2005 User Survey Results Table of Contents Response Summary Respondent Demographics All Satisfaction, Importance and Usefulness Ratings Hardware Resources Software...

  17. 2003 User Survey Results

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

    10 | Next 2003 User Survey Results Table of Contents Response Summary Respondent Demographics Overall Satisfaction and Importance All Satisfaction Topics and Changes from...

  18. Big Problems. Big Results.

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

    metal oxide in groundwater. The results are revealing new insights about microbiological activity and contaminant movement below the ground's surface. PNNL scientists invented...

  19. Summary of expenditures of rebates from the low-level radioactive waste surcharge escrow account for calendar year 1989: Report to Congress in response to Public Law 99-240

    SciTech Connect (OSTI)

    Not Available

    1990-06-01

    This response is submitted in response to the Low-Level Radioactive Waste Policy Amendments Act of 1985 (the Act), Public Law 99-240. The report summarizes expenditures made during the calendar year 1989 of surcharge rebates from the July 1, 1986, milestones. Title I of the Act requires the Department of Energy (DOE) to administer a Surcharge Escrow Account. This account consists of a portion of the surcharge fees paid by generators of low-level radioactive waste in nonsited compacts (regional compacts currently without operating disposal sites) and nonmember States (States without disposal sites that are not members of compacts) to the three States with operating disposal facilities (Nevada, South Carolina, and Washington) (sited States) for using their disposal facilities. In administering the Surcharge Escrow Account, the Act requires DOE to: invest the funds in interest-bearing United States Government securities; determine eligibility of rebates of the funds by evaluating State and compact progress toward developing new disposal sites against milestones set forth in the Act; disburse the collected rebates and interest; assess compliance of rebate expenditures with the limitations prescribed in the Act; and submit a report annually to Congress summarizing rebate expenditures by States and regions. 5 tabs.

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

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

    0 Average Fuel OilKerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per...

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

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

    Natural Gas, 1980 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square...

  2. This Week In Petroleum Printer-Friendly Version

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

    many areas. The largest expenditure decreases are in households using natural gas and propane, projected at 12 and 14 percent, respectively. Projected electricity and heating oil...

  3. Microsoft Word - 20050821_Appendix_A.doc

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

    0. U.S. Number of Vehicles, Vehicle-Kilometers, Motor Fuel Consumption and Expenditures, 2001 ENERGY INFORMATION ADMINISTRATION HOUSEHOLD VEHICLES ENERGY USE: LATEST A N D TRENDS...

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

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

    Consumption & Efficiency view all Residential Energy Consumption Survey Household end use consumption of energy and expenditures Commercial Buildings Energy Consumption Survey ...

  5. Fact #747: October 1, 2012 Behind Housing, Transportation is...

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

    in 2010. The average household spends more on transportation in a year than on food. ... expenditures on housing, transportation, food, personal insurance and pensions, health ...

  6. " East North Central",751,"NA",539,650,639,792.21608

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

    Fuel Expenditures per Vehicle, Selected Survey Years (Nominal Dollars) " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",736,722,550,650,668,787 "Household Characteristics"...

  7. Lubricant return comparison of naphthenic and polyol ester oils in R-134a household refrigeration applications

    SciTech Connect (OSTI)

    Reyes-Gavilan, J.L.; Flak, G.T.; Tritcak, T.R.

    1996-12-31

    This paper presents mineral oils and polyol esters as possible lubricant options for domestic refrigeration applications employing R-134a as the heat exchange fluid. A performance comparison, based on data presented, is made between the mineral oils and polyol esters evaluated. To more closely examine lubricant return with N-70 and R-134a and ensure that the oil is not contributing to any deterioration in efficiency due to its accumulation in evaporators, a special test unit was designed with a difficult oil return configuration and its performance carefully monitored. Oil return with a hydrofluorocarbon-miscible polyol ester, R-133-O was also evaluated in this setup and its performance results compared to those obtained with the naphthenic refrigeration oil.

  8. 1999 User Survey Results

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

    helpful. At times they went beyond the scope of my request which resulted in making my job easier." "Provides reliable machines, which are well-maintained and have scheduling...

  9. Testbed: Published Results

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

    Testbed Results Network R&D Software-Defined Networking (SDN) Experimental Network Testbeds 100G SDN Testbed Dark Fiber Testbed Test Circuit Service Testbed Results Current Testbed Research Previous Testbed Research Performance (perfSONAR) Software & Tools Development Data for Researchers Partnerships Publications Workshops Contact Us Technical Assistance: 1 800-33-ESnet (Inside US) 1 800-333-7638 (Inside US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems:

  10. Recent results from MAC

    SciTech Connect (OSTI)

    MAC Collaboration

    1982-05-01

    Some preliminary results from the MAC detector at PEP are presented. These include measurements of the angular distribution of ..gamma gamma.., ..mu mu.. and tau tau final states, a determination of the tau lifetime, a measurement of R, and a presentation of the inclusive muon p/sub perpendicular/ distribution for hadronic events.

  11. Plans, Implementation, and Results

    Broader source: Energy.gov [DOE]

    The Bioenergy Technologies Office carries out technology research, development, and deployment through an ongoing process of planning and analysis, implementation, and review. This Web page includes links to documents that support and document the program management process, and the results and public benefits that derive from it.

  12. Sandia National Laboratories: Search Results

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

    Search Results Search Results Search Loading

  13. Next Generation Household Refrigerator

    Broader source: Energy.gov [DOE]

    Lead Performer: Oak Ridge National Laboratory - Oak Ridge, TN Partner: Whirlpool - Benton Harbor, MI

  14. SPEAR results, 1981

    SciTech Connect (OSTI)

    Scharre, D.L.

    1981-09-01

    New results from SPEAR on the inclusive photon spectrum at the psi' and on J/psi radiative transitions are presented. Evidence for an eta/sub c/' candidate is observed in the psi' inclusive photon spectrum at a mass M = 3592 +- 5 MeV. A new resonance, the theta(1640) which is observed to decay into eta eta, has been seen in radiative transitions from the J/psi. The spin-parity of the l(1440), previously observed in J/psi radiative transitions and originally identified as the E(1420), has been determined to be 0/sup -/.

  15. Recent BABAR Results

    SciTech Connect (OSTI)

    Eigen, Gerald

    2015-04-29

    We present herein the most recent BABAR results on direct CP asymmetry measurements in B → Xsγ, on partial branching fraction and CP asymmetry measurements in B → Xs+-, on a search for B → π/ηℓ+- decays, on a search for lepton number violation in B+ → X-+ℓ'+ modes and a study of B0 →ωω and B0 → ωφ decays.

  16. Organic Separation Test Results

    SciTech Connect (OSTI)

    Russell, Renee L.; Rinehart, Donald E.; Peterson, Reid A.

    2014-09-22

    Separable organics have been defined as “those organic compounds of very limited solubility in the bulk waste and that can form a separate liquid phase or layer” (Smalley and Nguyen 2013), and result from three main solvent extraction processes: U Plant Uranium Recovery Process, B Plant Waste Fractionation Process, and Plutonium Uranium Extraction (PUREX) Process. The primary organic solvents associated with tank solids are TBP, D2EHPA, and NPH. There is concern that, while this organic material is bound to the sludge particles as it is stored in the tanks, waste feed delivery activities, specifically transfer pump and mixer pump operations, could cause the organics to form a separated layer in the tank farms feed tank. Therefore, Washington River Protection Solutions (WRPS) is experimentally evaluating the potential of organic solvents separating from the tank solids (sludge) during waste feed delivery activities, specifically the waste mixing and transfer processes. Given the Hanford Tank Waste Treatment and Immobilization Plant (WTP) waste acceptance criteria per the Waste Feed Acceptance Criteria document (24590-WTP-RPT-MGT-11-014) that there is to be “no visible layer” of separable organics in the waste feed, this would result in the batch being unacceptable to transfer to WTP. This study is of particular importance to WRPS because of these WTP requirements.

  17. Study of energy tax and rebate schemes: energy conservation and the question of equity

    SciTech Connect (OSTI)

    Fazel Sarjui, F.

    1983-01-01

    Taxing all kinds of primary energy at the wellhead on a $/Btu basis is suggested. This aims at inducing energy conservation throughout the economic system. To reduce the financial pressure of the tax on consumers, especially the poor, tax revenues could be rebated to households. It has been attempted to design an equitable rebate scheme. A mathematical model was developed that approximates the reduction in a household's total energy consumption in response to higher energy prices and different rebate schemes. This model is based on the assumption that energy consumption is a function of a household's real income, prices of different commodities, and energy intensities. The amount of energy saved and the change in real expenditure of a household was calculated for four tax rates; 50%, 100%, 224% and 400%, and five rebate schemes; one regressive, two progressive, one income distribution preserving and the flat per-capita rebate. The results indicate that, for a given tax rate, the choice of rebate scheme does not significantly affect the amount of energy conserved by the households. However, the effectof different rebate schemes on a household's real expenditure could be dramatically different.

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

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

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

    0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Northeast",20.8,2121,1663,921,836,656,363 "Northeast Divisions and

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

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

    1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Midwest",25.9,2272,1898,1372,912,762,551 "Midwest Divisions and

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

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

    2 Average Square Footage of South Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total South",42.1,1867,1637,1549,732,642,607 "South Divisions and

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

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

    3 Average Square Footage of West Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total West",24.8,1708,1374,800,628,506,294 "West Divisions and States"

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

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

    4 Average Square Footage of Single-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Single-Family",78.6,2422,2002,1522,880,727,553 "Census

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

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

    5 Average Square Footage of Multi-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Multi-Family",28.1,930,807,535,453,393,261 "Census Region"

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

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

    6 Average Square Footage of Mobile Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Mobile Homes",6.9,1087,985,746,413,375,283 "Census Region"

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

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

    9 Average Square Footage of U.S. Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total",113.6,1971,1644,1230,766,639,478 "Census Region"

  11. US SoAtl GA Site Consumption

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

    GA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl GA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl GA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl GA Expenditures dollars ELECTRICITY ONLY average per household * Site energy consumption (89.5 million Btu) and energy expenditures per household ($2,067) in Georgia are similar to the U.S. household averages. * Per

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