National Library of Energy BETA

Sample records for unavailable median household

  1. 503 Service Temporarily Unavailable

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

    Service Temporarily Unavailable The server is temporarily unable to service your request due to maintenance downtime or capacity problems. Please try again later. Web Server at cen-efrc.org

  2. 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 ...

  3. Quantifying the Impact of Unavailability in Cyber-Physical Environments

    SciTech Connect (OSTI)

    Aissa, Anis Ben; Abercrombie, Robert K; Sheldon, Federick T.; Mili, Ali

    2014-01-01

    The Supervisory Control and Data Acquisition (SCADA) system discussed in this work manages a distributed control network for the Tunisian Electric & Gas Utility. The network is dispersed over a large geographic area that monitors and controls the flow of electricity/gas from both remote and centralized locations. The availability of the SCADA system in this context is critical to ensuring the uninterrupted delivery of energy, including safety, security, continuity of operations and revenue. Such SCADA systems are the backbone of national critical cyber-physical infrastructures. Herein, we propose adapting the Mean Failure Cost (MFC) metric for quantifying the cost of unavailability. This new metric combines the classic availability formulation with MFC. The resulting metric, so-called Econometric Availability (EA), offers a computational basis to evaluate a system in terms of the gain/loss ($/hour of operation) that affects each stakeholder due to unavailability.

  4. 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

  5. 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

  6. 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....

  7. Emergency diesel generator: Maintenance and failure unavailability, and their risk impacts

    SciTech Connect (OSTI)

    Samanta, P.; Kim, I.; Uryasev, S.; Penoyar, J.; Vesely, W.

    1994-11-01

    Emergency Diesel Generators (EDGs) provide on-site emergency alternating current (ac) electric power for a nuclear plant in the event that all off-site power sources are lost. Existing regulations establish requirements for designing and testing of these on-site power sources to reduce to an acceptable level the probability of losing all ac power sources. Operating experience with EDGs has raised questions about their testing and maintenance to achieve the EDG reliability levels and the total EDG unavailability experienced (fraction of time EDG is out-of-service due to testing, maintenance, and failures). In this report, recent operating experience is used to assess EDG unavailability due to testing, maintenance, and failures during reactor power operation and during plant shutdown. Recent data show an improvement in EDG reliability, but an increase in EDG unavailability due to maintenance, a significant portion of which is due to routinely scheduled maintenances. Probabilistic safety assessments (PSAs) of selected nuclear power plants are used to assess the risk impact of EDG unavailability due to maintenance and failure during power operation, and during different stages of plant shutdown. The results of these risk analyses suggest qualitative insights for scheduling EDG maintenance that will have minimal impact on risk of operating nuclear power plants.

  8. 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

  9. 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 ...

  10. 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 ...

  11. 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 ...

  12. 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 ...

  13. Property:EstimatedCostMedianUSD | Open Energy Information

    Open Energy Info (EERE)

    Name EstimatedCostMedianUSD Property Type Quantity Description the median estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one...

  14. 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...

  15. 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...

  16. Property:EstimatedTimeMedian | Open Energy Information

    Open Energy Info (EERE)

    week,w,Week,Weeks,W,WEEK,WEEKS 12 months,month,m,Month,Months,M,MONTH,MONTHS 1 years,year,y,Year,Years,Y,YEAR,YEARS Pages using the property "EstimatedTimeMedian" Showing 25 pages...

  17. NMDOT Application for Permit to Construct an Access or Median...

    Open Energy Info (EERE)

    Construct an Access or Median Opening on Public Right of Way Jump to: navigation, search OpenEI Reference LibraryAdd to library Legal Document- OtherOther: NMDOT Application for...

  18. 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 ...

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

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

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

  20. 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 *...

  1. 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

  2. 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

  3. 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 ...

  4. 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 ...

  5. 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 ...

  6. 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 ...

  7. 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 ...

  8. 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 ...

  9. 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 ...

  10. 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 ...

  11. 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) . . . . . . . . ....

  12. 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...

  13. 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 ...

  14. 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 ...

  15. 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 ...

  16. 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...

  17. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... definition. 2 Below 150 percent of poverty line or 60 percent of median State ...

  18. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 0.6 0.5 Q 17.4 1 Below 150 percent of poverty line or 60 percent of median State ...

  19. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 1.5 0.5 1.0 14.6 1 Below 150 percent of poverty line or 60 percent of median State ...

  20. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 15.0 1.0 3.4 ... weather station. 2 Below 150 percent of poverty line or 60 percent of median State ...

  1. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 0.7 0.4 0.2 18.4 1 Below 150 percent of poverty line or 60 percent of median State ...

  2. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 15.0 1.4 2.3 ... were conducted. 2 Below 150 percent of poverty line or 60 percent of median State ...

  3. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 0.9 0.5 0.6 13.0 1 Below 150 percent of poverty line or 60 percent of median State ...

  4. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 1.2 0.7 0.5 11.3 1 Below 150 percent of poverty line or 60 percent of median State ...

  5. 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 ...

  6. 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. ...

  7. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 15.0 6.7 2.3 ... 4.9 Q Q 0.2 14.8 1 Below 150 percent of poverty line or 60 percent of median State ...

  8. 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

  9. 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

  10. Table B2. Summary Table: Totals and Medians of Floorspace, Number of Workers,

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

    . Summary Table: Totals and Medians of Floorspace, Number of Workers, Hours of Operation, and Age of Building, 1999" ,"All Buildings (thousand)","Total Floorspace (million square feet)","Total Workers in All Buildings (thousand)","Median Square Feet per Building (thousand)","Median Square Feet per Worker","Median Hours per Week","Median Age of Buildings (years)" "All Buildings

  11. 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.

  12. Digital I&C systems in nuclear power plants. Risk-screening of environmental stressors and a comparison of hardware unavailability with an existing analog system

    SciTech Connect (OSTI)

    Hassan, M.; Vesely, W.E.

    1998-01-01

    In this report, we present a screening study to identify environmental stressors for digital instrumentation and control (I&C) systems in a nuclear power plant (NPP) which can be potentially risk-significant, and compare the hardware unavailability of such a system with that of its existing analog counterpart. The stressors evaluated are temperature, humidity, vibration, radiation, electro-magnetic interference (EMI), and smoke. The results of risk-screening for an example plant, subject to some bounding assumptions and based on relative changes in plant risk (core damage frequency impacts of the stressors), indicate that humidity, EMI from lightning, and smoke can be potentially risk-significant. Risk from other sources of EMI could not be evaluated for a lack of data. Risk from temperature appears to be insignificant as that from the assumed levels of vibrations. A comparison of the hardware unavailability of the existing analog Safety Injection Actuation System (SIAS) in the example plant with that of an assumed digital upgrade of the system indicates that system unavailability may be more sensitive to the level of redundancy in elements of the digital system than to the environmental and operational variations involved. The findings of this study can be used to focus activities relating to the regulatory basis for digital I&C upgrades in NPPs, including identification of dominant stressors, data-gathering, equipment qualification, and requirements to limit the effects of environmental stressors. 30 refs., 8 figs., 26 tabs.

  13. 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...

  14. 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 ...

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

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

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

  16. 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 ...

  17. 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...

  18. ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS

    SciTech Connect (OSTI)

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

    2009-04-15

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

  19. 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.

  20. 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

  1. Fact #597: November 16, 2009 Median Age of Cars and Trucks Rising in 2008

    Broader source: Energy.gov [DOE]

    The median age of cars and trucks in the U.S. continued to grow in 2008. Due to the economic climate and high gasoline prices that summer, consumers held onto their vehicles longer and delayed new...

  2. 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

  3. 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.

  4. 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.

  5. 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.

  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. 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.

  8. 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)

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

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

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

  10. 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.

  11. 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 ...

  12. 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

  13. 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).

  14. 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).

  15. 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.

  16. 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...

  17. 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...

  18. 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 ...

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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 ...

  6. 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...

  7. 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...

  8. 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...

  9. 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 ...

  10. 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...

  11. 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 ...

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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 ...

  19. 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.

  20. 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...

  1. 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...

  2. 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

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

    SciTech Connect (OSTI)

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

    2005-05-31

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

  4. 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.

  5. 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.

  6. "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

  7. 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

  8. 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

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

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

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

  10. "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"

  11. "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"

  12. "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

  13. 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

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

    SciTech Connect (OSTI)

    Siler, A.

    1980-05-01

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

  15. 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.

  16. 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...

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.....................................................

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. " 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"

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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.

  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. 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.

  20. 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).

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  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. 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.

  10. " 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"

  11. " 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"

  12. " 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"

  13. " 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"

  14. " 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"

  15. " 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"

  16. " 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

  17. " 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

  18. " 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"

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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...

  5. 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

  6. 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.

  7. b2.pdf

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

    Median

  8. Next Generation Household Refrigerator

    Broader source: Energy.gov [DOE]

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

  9. http://www.census.gov/

    National Nuclear Security Administration (NNSA)

    People & Households American Community Survey * Estimates * Projections Income | State Median Income * Poverty * Health Insurance International * Genealogy * Census 2000 * More ...

  10. ,"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

  11. ,"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

  12. ,"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

  13. ,"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"

  14. ,"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

  15. ,"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"

  16. ,"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"

  17. ,"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"

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

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

    ... 7.6 2.1 3.3 2.2 11.5 Q Q Q 1.4 6.9 2.8 18.8 Below Poverty Line 100 Percent ... 6.6 1.6 3.6 1.3 5.8 0.3 0.7...

  19. homeoffice_household2001.pdf

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

    more ...... 2.2 0.9 0.5 Q Q Q 0.4 23.9 Have Access to Internet ...... 50.7 9.3 10.1 8.8 6.1 6.7 9.7 5.7 Hours PCs Turned On Each Week Less ...

  20. spaceheat_household2001.pdf

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

    Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With ... Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With ...

  1. ac_household2001.pdf

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

    Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile ... Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile ...

  2. spaceheat_household2001.pdf

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

    Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings ... Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings ...

  3. ac_household2001.pdf

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

    Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings ... Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings ...

  4. spaceheat_household2001.pdf

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

    Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile ... Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile ...

  5. ac_household2001.pdf

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

    Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With ... Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With ...

  6. appl_household2001.pdf

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

    ... Q Q Q Q Q NF Video Cassette Recorders (VCRs) and DVD Players ...... 29.3 9.3 6.4 12.6 1.0 7.2 1 ...... 18.9 5.3 4.0 8.9 0.7 8.3 2 ...

  7. appl_household2001.pdf

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

    ... 11.4 Both ...... 1.9 0.3 0.4 0.5 Q Q 0.4 25.0 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 14.5 16.7 16.7 12.2 12.7 ...

  8. appl_household2001.pdf

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

    ... 0.3 0.4 1.3 13.2 Both ...... 1.9 1.6 Q Q Q 30.6 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 67.8 8.3 14.0 6.0 4.6 1 ...

  9. appl_household2001.pdf

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

    ... 1.9 0.3 0.5 0.3 0.3 0.6 26.4 Video Cassette Recorders (VCRs) and DVD Players ... 1.9 0.3 0.4 0.5 Q Q 0.4 25.0 Video Cassette Recorders (VCRs) and DVD Players ...

  10. appl_household2001.pdf

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

    ... Both ...... 1.9 0.8 0.5 Q Q 27.0 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 34.6 18.4 ...

  11. appl_household2001.pdf

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

    ... Both ...... 1.9 0.5 0.4 Q 19.8 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 22.5 15.6 ...

  12. appl_household2001.pdf

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

    ... 13.7 Both ...... 1.9 0.3 0.5 0.3 0.3 0.6 26.4 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 8.1 25.8 22.1 18.8 21.3 ...

  13. appl_household2001.pdf

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

    ... Both ...... 1.9 0.3 Q 0.2 27.2 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 21.0 6.1 ...

  14. appl_household2001.pdf

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

    ... 12.2 Both ...... 1.9 0.2 Q Q 35.2 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 18.0 13.3 ...

  15. appl_household2001.pdf

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

    ... 2.7 9.7 Both ...... 1.9 Q 0.3 0.6 1.1 Q 0.3 25.6 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 13.9 19.8 25.3 37.0 11.7 ...

  16. appl_household2001.pdf

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

    ... ...... 1.9 0.7 0.4 0.4 0.3 22.1 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 44.9 15.5 ...

  17. appl_household2001.pdf

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

    ... 8.9 Q Q 1.1 14.3 Both ...... 1.7 1.5 Q Q Q 43.3 Video Cassette Recorders (VCRs) and DVD Players ...... 66.7 58.5 1.9 1.4 5.0 7.1 1 ...

  18. appl_household2001.pdf

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

    ... Both ...... 1.9 Q 0.2 Q 0.4 24.5 Video Cassette Recorders (VCRs) and DVD Players ...... 96.1 6.3 11.4 6.7 ...

  19. Household Vehicles Energy Consumption 1991

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

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

  20. Household Vehicles Energy Consumption 1994

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

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

  1. spaceheat_household2001.pdf

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

    ......... 1.9 0.2 Q Q Q 30.7 Other ...... 0.4 Q Q Q Q 46.3 (*) Value rounds to zero in the units displayed. ...

  2. Household Vehicles Energy Consumption 1991

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

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

  3. Household Vehicles Energy Consumption 1991

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

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

  4. homeoffice_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 1.1 1.4 1.2 Total ......

  5. spaceheat_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 1.7 Total ......

  6. Household Vehicles Energy Consumption 1991

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

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

  7. ac_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 HC4-1a. Air Conditioning by Climate ...

  8. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 9.8 2.8 2.1 4.4 0.5 11.6 100 to 150 Percent ...... 5.1 1.4 1.1 2.3 Q 14.2 Above 150 ...

  9. char_household2001.pdf

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

    Income Relative to Poverty Line Below 100 Percent ...... 5.2 3.9 Q Q 1.1 21.9 100 to 150 Percent ...... 6.4 5.2 0.2 Q 0.9 16.5 Above 150 Percent ...

  10. homeoffice_household2001.pdf

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

    ... report, the heating or cooling degree-days are a measure of how cold or how hot a location is over a period of one year, relative to a base temperature of 65 degrees Fahrenheit. ...

  11. ac_household2001.pdf

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

    ... report, the heating or cooling degree-days are a measure of how cold or how hot a location is over a period of one year, relative to a base temperature of 65 degrees Fahrenheit. ...

  12. Household Vehicles Energy Consumption 1991

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

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

  13. Household Vehicles Energy Consumption 1991

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

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

  14. Household Vehicles Energy Consumption 1991

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

    of vehicles in the residential sector. Data are from the 1991 Residential Transportation Energy Consumption Survey. The "Glossary" contains the definitions of terms used in the...

  15. Household Vehicles Energy Consumption 1991

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

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

  16. spaceheat_household2001.pdf

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

    ......... 0.8 Q Q Q 51.7 Heat Pump ......8.0 0.2 Q Q 26.5 Steam or Hot-Water System ...... 4.4 Q Q Q 16.2 For ...

  17. spaceheat_household2001.pdf

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

    8.5 7.3 7.8 8.5 9.2 17.7 6.4 Central Warm-Air Furnace ...... 44.8 8.1 6.6 6.7 6.5 6.9 ... 0.8 1.1 2.2 0.7 0.5 0.9 17.2 Central Warm-Air Furnace ...... 12.6 2.2 4.4 3.1 1.2 0.8 ...

  18. spaceheat_household2001.pdf

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

    59.1 32.3 10.0 13.1 3.6 6.0 Central Warm-Air Furnace ...... 44.8 22.7 ... 6.1 2.7 1.4 0.8 1.2 15.0 Central Warm-Air Furnace ...... 12.6 5.9 ...

  19. City-Level Energy Decision Making: Data Use in Energy Planning...

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

    City to Park City, Utah, including a diverse sample of population size, utility type, region, annual greenhouse gas reduction targets, vehicle use, and median household income. ...

  20. PowerPoint Presentation

    Office of Environmental Management (EM)

    areas, typically have: - low median household incomes - high unemployment - high poverty (see "Designations" section in website's FAQs) 6 www.sba.gov There are 4 kinds of ...

  1. Port Graham Biomass Community Heat Project

    Energy Savers [EERE]

    force; Median household income 18,942 Heat 5-community buildings with cord wood ... Port Graham Community Building Biomass Heat Project 2015 BIA and other studies ...

  2. TITLE

    Office of Legacy Management (LM)

    Pages 12 and 13 are unavailable Appendix B is unavailable

  3. Household Vehicles Energy Use: Latest Data & Trends

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

    C : Q U A L I T Y O F T H E D ATA APPENDIX C A P P E N D I X C QUALITY OF THE DATA INTRODUCTION This section discusses several issues relating to the quality of the National...

  4. Microsoft Word - Household Energy Use CA

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

    US PAC CA 1990-2009 1970-1989 1950-1969 Before 1950 YEAR OF CONSTRUCTION AVERAGE SQUARE FOOTAGE US 1,971 PAC 1,605 CA 1,583 NO. OF TELEVISIONS HAVE A DVR NO. OF REFRIGERATORS 0% ...

  5. Household Vehicles Energy Use: Latest Data & Trends

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

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

  6. Household Vehicles Energy Use: Latest Data & Trends

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

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

  7. 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.

  8. 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...

  9. Household Vehicles Energy Use: Latest Data & Trends

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

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

  10. Shared Solar Projects Powering Households Throughout America...

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

    including shared solar View and download photographs, videos, graphics, and other multimedia related to solar technologies Subscribe to Office of Energy Efficiency and Renewable ...

  11. Household Vehicles Energy Use: Latest Data & Trends

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

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

  12. Household Vehicles Energy Consumption 1994 - Appendix C

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

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

  13. Household Vehicles Energy Use: Latest Data & Trends

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

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

  14. Spatially assisted down-track median filter for GPR image post-processing

    DOE Patents [OSTI]

    Paglieroni, David W; Beer, N Reginald

    2014-10-07

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  15. Radiofrequency Ablation of Large Renal Angiomyolipoma: Median-Term Follow-Up

    SciTech Connect (OSTI)

    Gregory, S. M. Anderson, C. J.; Patel, U.

    2013-06-15

    Purpose. To study the feasibility of percutaneous radiofrequency ablation (RFA) of large angiomyolipomas (AMLs) using saline-cooled electrodes. Materials and Methods. Institutional Review Board approval for the study was received. Four patients (all female, age range 33-67 years) with large AMLs (maximal axis 6.1-32.4 cm) not suitable for embolotherapy or surgery consented to a trial of RFA. Procedures were performed under computerized tomographic guidance using 14G saline-infused electrodes. Two ablations (diameter 4-7 cm) were undertaken in each patient. Variables studied were technical success, treatment safety, alteration of tumor consistency, tumor size, effect on renal function, and medium-term freedom from haemorrhage. Results. All four patients underwent successful RFA without any intraprocedural complications. There has been no haemorrhage, or new renal specific symptom, during a minimum 48-month period, and normal renal function has been normal. On follow-up radiological imaging, the tumors have become fattier with involution of the soft-tissue elements (soft tissue-to-total tumor ratio decreased mean [range] of 0.26 [0.14-0.48] to 0.17 [0.04-0.34] U; p = 0.04 [paired Student t test]). Further evidence of treatment effect was the development of a capsule around the ablation zone, but there was no change in overall tumor volume (mean [range] 1,120 [118-2,845] to 1150 [90-3,013] ml; p = 1 [paired Student t test]). Conclusion. RFA of large AMLs is technically feasible using saline-infused electrodes. The soft-tissue elements decreased in volume; the tumors become fattier; and there has been no renal haemorrhage during a 48-month period.

  16. 1997 Housing Characteristics Tables Home Office Equipment Tables

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

    ... RSE Column Factor: Total 1997 Household Income Below Poverty Line Eli- gible for Fed- eral ... 32.3 39.0 2.7 1 Below 150 percent of poverty line or 60 percent of median State income. ...

  17. DOE_OR_21548_590_R_0.pdf

    Office of Legacy Management (LM)

    Figure 1-1 is unavailable

  18. DOE_OR_21548_667_R_0.pdf

    Office of Legacy Management (LM)

    Pages 44 and 45 are unavailable

  19. Residential Network Members Impact More Than 42,000 Households

    Broader source: Energy.gov [DOE]

    Eligible Better Buildings Residential Network members reported completing 27,563 home energy upgrades during 2013 as part of the Residential Network’s first reporting cycle. In addition, 13 Better...

  20. Household Vehicles Energy Use: Latest Data and Trends

    Reports and Publications (EIA)

    2005-01-01

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

  1. Residential Network Members Impact More Than 42,000 Households...

    Energy Savers [EERE]

    annual electricity savings of more than 5 million kilowatt-hours; estimated natural gas savings of 71,580 British therms; and 653,245 estimated annual cost savings. In New...

  2. Special Topics on Energy Use in Household Transportation

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

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

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

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

    You are not required to respond to this form unless it displays a currently valid OMB control number. You will find the OMB approval number and expiration date at the top left-hand ...

  4. 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 ...

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

    Gasoline and Diesel Fuel Update (EIA)

    ... 9.6 5.0 100 4.4 6.2 4.5 0.8 6.8 4.5 Income Relative to Poverty Line Below 100 Percent... 11.4 6.0 116 5.1 5.6...

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

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

    11.5 0.8 1.0 0.9 0.8 0.7 0.8 0.7 1.6 1.4 0.8 0.5 0.2 0.1 0.7 0.4 Income Relative to Poverty Line Below 100 Percent... 13.3 0.3 0.4 0.4 0.6...

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

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

    ... 6.5 1.5 15.4 957 1,031 Income Relative to Poverty Line Below 100 Percent... 7.9 1.4 14.7 942 937...

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

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

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

  9. Could a Common Household Fungus Reduce Oil Imports?

    Broader source: Energy.gov [DOE]

    Imagine if the same mold that ruins old grapes and onions could double as a key ingredient in the recipe to reduce U.S. dependence on foreign oil. Pacific Northwest National Laboratory are working to harness the natural process that spoils fruits and vegetables as a way to make fuel and other petroleum substitutes.

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

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

    ... in a civil penalty of not more than 2,750 per day for each violation, or a fine of not more than 5,000 per day for each willful violation. The government may bring a civil ...

  11. EIA - Appendix B: Estimation Methodologies of Household Vehicles...

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

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

  12. Survey of mercury, cadmium and lead content of household batteries

    SciTech Connect (OSTI)

    Recknagel, Sebastian; Radant, Hendrik; Kohlmeyer, Regina

    2014-01-15

    Highlights: • A well selected sample of 146 batteries was analysed for its heavy metals content. • A comparison was made between heavy metals contents in batteries in 2006 and 2011. • No significant change after implementation of the new EU Batteries Directive. • Severe differences in heavy metal contents were found in different battery-types. - Abstract: The objective of this work was to provide updated information on the development of the potential impact of heavy metal containing batteries on municipal waste and battery recycling processes following transposition of the new EU Batteries Directive 2006/66/EC. A representative sample of 146 different types of commercially available dry and button cells as well as lithium-ion accumulators for mobile phones were analysed for their mercury (Hg)-, cadmium (Cd)- and lead (Pb)-contents. The methods used for preparing the cells and analysing the heavy metals Hg, Cd, and Pb were either developed during a former study or newly developed. Several batteries contained higher mass fractions of mercury or cadmium than the EU limits. Only half of the batteries with mercury and/or lead fractions above the marking thresholds were labelled. Alkaline–manganese mono-cells and Li-ion accumulators, on average, contained the lowest heavy metal concentrations, while zinc–carbon batteries, on average, contained the highest levels.

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

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

    power producers using more natural gas in 2015 U.S. electric power producers are increasing their use of natural gas and burning less coal for generating electricity. In its new forecast, the U.S. Energy Information Administration said natural gas-fired generation is expected to produce 30% of U.S. electricity this year. That's up from 27% during 2014. More competitively-priced natural gas is expected to cut coal's share of electricity generation from about 39% last year to just under 36% this

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

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

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

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

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

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

  16. Evaluating the biogas potential of the dry fraction from pretreatment of food waste from households

    SciTech Connect (OSTI)

    Murto, Marika; Bjrnsson, Lovisa; Rosqvist, Hkan; Bohn, Irene

    2013-05-15

    Highlights: ? A novel approach for biogas production from a waste fraction that today is incinerated. ? Biogas production is possible in spite of the impurities of the waste. ? Tracer studies are applied in a novel way. ? Structural material is needed to improve the flow pattern of the waste. ? We provide a solution to biological treatment for the complex waste fraction. - Abstract: At the waste handling company NSR, Helsingborg, Sweden, the food waste fraction of source separated municipal solid waste is pretreated to obtain a liquid fraction, which is used for biogas production, and a dry fraction, which is at present incinerated. This pretreatment and separation is performed to remove impurities, however also some of the organic material is removed. The possibility of realising the methane potential of the dry fraction through batch-wise dry anaerobic digestion was investigated. The anaerobic digestion technique used was a two-stage process consisting of a static leach bed reactor and a methane reactor. Treatment of the dry fraction alone and in a mixture with structural material was tested to investigate the effect on the porosity of the leach bed. A tracer experiment was carried out to investigate the liquid flow through the leach beds, and this method proved useful in demonstrating a more homogenous flow through the leach bed when structural material was added. Addition of structural material to the dry fraction was needed to achieve a functional digestion process. A methane yield of 98 m{sup 3}/ton was obtained from the dry fraction mixed with structural material after 76 days of digestion. This was in the same range as obtained in the laboratory scale biochemical methane potential test, showing that it was possible to extract the organic content in the dry fraction in this type of dry digestion system for the production of methane.

  17. 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...

  18. Table 5.2. U.S. per Household Vehicle-Miles Traveled, Vehicle...

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

    75,000 or More ... 8.2 2.3 28.5 1,443 1,692 5.2 Below Poverty Line 100 Percent ... 9.0 1.4 14.7 769 890 7.3 125...

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

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

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

  20. 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...

  1. Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own...

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

    Trends in the United States and its Major Metropolitan Area, 1960-1990, Cambridge, MA, 1994, p. 2-2. 2000 data - U.S. Bureau of the Census, American Fact Finder, ...

  2. Electricity storage for grid-connected household dwellings with PV panels

    SciTech Connect (OSTI)

    Mulder, Grietus; Six, Daan; Ridder, Fjo De

    2010-07-15

    Classically electricity storage for PV panels is mostly designed for stand-alone applications. In contrast, we focus in this article on houses connected to the grid with a small-scale storage to store a part of the solar power for postponed consumption within the day or the next days. In this way the house owner becomes less dependent on the grid and does only pay for the net shortage of his energy production. Local storage solutions pave the way for many new applications like omitting over-voltage of the line and bridging periods of power-line black-out. Since 2009 using self-consumption of PV energy is publicly encouraged in Germany, which can be realised by electric storage. This paper develops methods to determine the optimal storage size for grid-connected dwellings with PV panels. From measurements in houses we were able to establish calculation rules for sizing the storage. Two situations for electricity storage are covered: - the storage system is an optimum to cover most of the electricity needs; - it is an optimum for covering the peak power need of a dwelling. After these calculation rules a second step is needed to determine the size of the real battery. The article treats the aspects that should be taken into consideration before buying a specific battery like lead-acid and lithium-ion batteries. (author)

  3. Householder's Perceptions of Insulation Adequacy and Drafts in the Home in 2001

    Reports and Publications (EIA)

    2004-01-01

    In order to improve the estimation of end-use heating consumption, the Energy Information Administration's (EIA), 2001 Residential Energy Consumption Survey (RECS), for the first time, asked respondents to judge how drafty they perceived their homes to be as a measure of insulation quality.

  4. 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.

  5. Low-cost household paint abatement to reduce children's blood lead levels

    SciTech Connect (OSTI)

    Taha, T.; Kanarek, M.S.; Schultz, B.D.; Murphy, A.

    1999-11-01

    The purpose was to examine the effectiveness of low-cost abatement on children's blood lead levels. Blood lead was analyzed before and after abatement in 37 homes of children under 7 years old with initial blood lead levels of 25--44 {micro}g/dL. Ninety-five percent of homes were built before 1950. Abatement methods used were wet-scraping and repainting deteriorated surfaces and wrapping window wells with aluminum or vinyl. A control group was retrospectively selected. Control children were under 7 years old, had initial blood lead levels of 25--44 {micro}g/dL and a follow-up level at least 28 days afterward, and did not have abatements performed in their homes between blood lead levels. After abatement, statistically significant declines occurred in the intervention children's blood lead levels. The mean decline was 22%, 1 to 6 months after treatment. After adjustment for seasonality and child's age, the mean decline was 6.0 {micro}g/dL, or 18%. The control children's blood levels did not decline significantly. There was a mean decline of 0.25 {micro}g/dL, or 0.39%. After adjustment for seasonality and age, the mean decline for control children was 1.6 {micro}g/dL, or 1.8%. Low-cost abatement and education are effective short-term interim controls.

  6. Table HC6.7 Air-Conditioning Usage Indicators by Number of Household...

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

    ... Type of Glass in Windows Single-pane Glass...... Q N Q Q Q Q Proportion of Windows Replaced All......

  7. Teleseismic-Seismic Monitoring At Valles Caldera - Sulphur Springs...

    Open Energy Info (EERE)

    Basis Full text unavailable. Notes Full text unavailable. References Takeshi Nishimura, Michael Fehler, W. Scott Baldridge, Peter Roberts, Lee Steck (1997) Heterogeneous...

  8. Guam: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    EIA Natural Gas Reserves Unavailable Cubic Meters (cu m) NA 2010 CIA World Factbook Oil Reserves Unavailable Barrels (bbl) NA 2010 CIA World Factbook Energy Maps featuring...

  9. American Samoa: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    EIA Natural Gas Reserves Unavailable Cubic Meters (cu m) NA 2010 CIA World Factbook Oil Reserves Unavailable Barrels (bbl) NA 2010 CIA World Factbook Energy Maps featuring...

  10. Republic of the Congo: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    EIA Natural Gas Reserves Unavailable Cubic Meters (cu m) NA 2010 CIA World Factbook Oil Reserves Unavailable Barrels (bbl) NA 2010 CIA World Factbook Energy Maps featuring...

  11. Slovenia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Slovenia Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code SI 3-letter ISO code SVN Numeric ISO code...

  12. Peru: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Peru Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code PE 3-letter ISO code PER Numeric ISO code...

  13. Guadeloupe: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Guadeloupe Population Unavailable GDP Unavailable Energy Consumption 0.03 Quadrillion Btu 2-letter ISO code GP 3-letter ISO code GLP Numeric ISO...

  14. Australia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Australia Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code AU 3-letter ISO code AUS Numeric ISO code...

  15. Gambia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Gambia Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code GM 3-letter ISO code GMB Numeric ISO code...

  16. Antigua and Barbuda: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Antigua and Barbuda Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code AG 3-letter ISO code ATG Numeric ISO code...

  17. Thailand: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Thailand Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code TH 3-letter ISO code THA Numeric ISO code...

  18. Sierra Leone: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Sierra Leone Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code SL 3-letter ISO code SLE Numeric ISO code...

  19. Djibouti: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Djibouti Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code DJ 3-letter ISO code DJI Numeric ISO code...

  20. Saint Barthlemy: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Saint Barthlemy Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code BL 3-letter ISO code BLM Numeric ISO code...

  1. Taiwan: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Taiwan Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code TW 3-letter ISO code TWN Numeric ISO code...

  2. Georgia (country): Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Georgia Population Unavailable GDP Unavailable Energy Consumption 0.17 Quadrillion Btu 2-letter ISO code GE 3-letter ISO code GEO Numeric ISO...

  3. France: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name France Population Unavailable GDP Unavailable Energy Consumption 11.29 Quadrillion Btu 2-letter ISO code FR 3-letter ISO code FRA Numeric ISO...

  4. Croatia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Croatia Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code HR 3-letter ISO code HRV Numeric ISO code...

  5. Palau: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Palau Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code PW 3-letter ISO code PLW Numeric ISO code...

  6. Uganda: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Uganda Population Unavailable GDP Unavailable Energy Consumption 0.04 Quadrillion Btu 2-letter ISO code UG 3-letter ISO code UGA Numeric ISO...

  7. Ireland: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Ireland Population Unavailable GDP Unavailable Energy Consumption 0.69 Quadrillion Btu 2-letter ISO code IE 3-letter ISO code IRL Numeric ISO...

  8. Cayman Islands: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Cayman Islands Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code KY 3-letter ISO code CYM Numeric ISO code...

  9. Myanmar: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Myanmar Population Unavailable GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code MM 3-letter ISO code MMR Numeric ISO code...

  10. Gambia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    MWhyear NA 2008 NREL Coal Reserves Unavailable Million Short Tons NA 2008 EIA Natural Gas Reserves Unavailable Cubic Meters (cu m) NA 2010 CIA World Factbook Oil Reserves...

  11. Armenia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    ,"inlineLabel":"","visitedicon":"" Country Profile Name Armenia Population Unavailable GDP Unavailable Energy Consumption 0.22 Quadrillion Btu 2-letter ISO code AM 3-letter ISO...

  12. Democratic Republic of Congo: Energy Resources | Open Energy...

    Open Energy Info (EERE)

    MWhyear NA 2008 NREL Coal Reserves Unavailable Million Short Tons NA 2008 EIA Natural Gas Reserves Unavailable Cubic Meters (cu m) NA 2010 CIA World Factbook Oil Reserves...

  13. Yurok Tribe- 2005 Project

    Broader source: Energy.gov [DOE]

    The Yurok Tribe has a great need for improved energy services on the reservation. The members pay $328 per month per household on average for energy, with just a $9,000 median household income. The project will assess the need for energy efficiency services on the reservation, identify available resources, and develop an implementation plan for meeting these needs. With an unemployment rate of 42%, the job training component of this program will benefit the tribe. Past attempts have been made to provide energy efficiency and renewable energy maintenance services on the reservation, but many of these services have not endured because they were not tribe-driven. This project will build tribal expertise, increase awareness, and form collaborative relationships with local energy services.

  14. Project Reports for Yurok Tribe- 2005 Project

    Broader source: Energy.gov [DOE]

    The Yurok Tribe has a great need for improved energy services on the reservation. The members pay $328 per month per household on average for energy, with just a $9,000 median household income. The project will assess the need for energy efficiency services on the reservation, identify available resources, and develop an implementation plan for meeting these needs. With an unemployment rate of 42%, the job training component of this program will benefit the tribe. Past attempts have been made to provide energy efficiency and renewable energy maintenance services on the reservation, but many of these services have not endured because they were not tribe-driven. This project will build tribal expertise, increase awareness, and form collaborative relationships with local energy services.

  15. Electricity Demand of PHEVs Operated by Private Households and Commercial Fleets: Effects of Driving and Charging Behavior

    SciTech Connect (OSTI)

    John Smart; Matthew Shirk; Ken Kurani; Casey Quinn; Jamie Davies

    2010-11-01

    Automotive and energy researchers have made considerable efforts to predict the impact of plug-in hybrid vehicle (PHEV) charging on the electrical grid. This work has been done primarily through computer modeling and simulation. The US Department of Energys (DOE) Advanced Vehicle Testing Activity (AVTA), in partnership with the University of California at Daviss Institute for Transportation Stuides, have been collecting data from a diverse fleet of PHEVs. The AVTA is conducted by the Idaho National Laboratory for DOEs Vehicle Technologies Program. This work provides the opportunity to quantify the petroleum displacement potential of early PHEV models, and also observe, rather than simulate, the charging behavior of vehicle users. This paper presents actual charging behavior and the resulting electricity demand from these PHEVs operating in undirected, real-world conditions. Charging patterns are examined for both commercial-use and personal-use vehicles. Underlying reasons for charging behavior in both groups are also presented.

  16. 1

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

    Why Los Alamos? Quality of life makes town "Best Of" April 3, 2012 Real secrets related to Los Alamos have as much to do with quality of life as prosperity and stability Recognized by Forbes Magazine as the Richest County in the Western United States in 2012, Los Alamos County residents have a median annual household income of $103,643. The Lab is the primary employer of over 7000 scientists, engineers, technicians, and professionals. Unemployment in town is less than 3%, about half

  17. Senegal: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    MWhyear 76 2008 NREL Coal Reserves Unavailable Million Short Tons NA 2008 EIA Natural Gas Reserves Unavailable Cubic Meters (cu m) NA 2010 CIA World Factbook Oil Reserves 0...

  18. Mammoth Pacific Geothermal Development Projects: Units II and...

    Open Energy Info (EERE)

    Projects: Units II and III Abstract Abstract unavailable. Author Environmental Science Associates Published Environmental Impact Report, prepared for Energy Management...

  19. Energy Efficient Home Improvements Loan Program

    Broader source: Energy.gov [DOE]

    Note: This program is currently unavailable. Check the program web site for more information regarding future funding.

  20. Word Pro - Untitled1

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

    Household Energy Consumption Household Energy Consumpton by Census Region, Selected Years, 1978-2009 Household Energy Consumption by Source, 2009 Energy Consumption per ...

  1. dec00

    Gasoline and Diesel Fuel Update (EIA)

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

  2. Table 4

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

    9. Mean Annual Electricity Consumption for Lighting, by Family Income by Number of Household Members, 1993 (Kilowatthours) Number of Household Members Family Income All Households...

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

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

    HC7 Home Office Equipment, Million U.S. Households PDF PDF Household Energy Usage The 1997 Residential Energy Consumption Survey (RECS) collected household energy data for the ...

  4. 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...

  5. Title Slide Examples

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

    5,444 228 Suspended Reports Per Household Measured Savings 208.1 12.0 Per Household Joint Rebate Program Savings 0.5 1.0 Per Household Joint Upstream Savings 43.3 na Per Household...

  6. S:\VM3\RX97\TBL_LIST.WPD

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

    Million U.S. Households; 13 pages, 52 kb) Contents Pages HC2-1a. Household Characteristics by Climate Zone, Million U.S. Households, 1997 2 HC2-2a. Household Characteristics by Year of Construction, Million U.S. Households, 1997 1 HC2-3a. Household Characteristics by Household Income, Million U.S. Households, 1997 1 HC2-4a. Household Characteristics by Type of Housing Unit, Million U.S. Households, 1997 1 HC2-5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S.

  7. S:\VM3\RX97\TBL_LIST.WPD

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

    Percent of U.S. Households; 13 pages, 54 kb) Contents Pages HC2-1b. Household Characteristics by Climate Zone, Percent of U.S. Households, 1997 2 HC2-2b. Household Characteristics by Year of Construction, Percent of U.S. Households, 1997 1 HC2-3b. Household Characteristics by Household Income, Percent of U.S. Households, 1997 1 HC2-4b. Household Characteristics by Type of Housing Unit, Percent of U.S. Households, 1997 1 HC2-5b. Household Characteristics by Type of Owner-Occupied Housing Unit,

  8. Geological History of Lake Lahontan, a Quaternary Lake of Northwestern...

    Open Energy Info (EERE)

    a Quaternary Lake of Northwestern Nevada Abstract Abstract unavailable. Author Israel C. Russell Organization U.S. Geological Survey Published U.S. Government Printing...

  9. NV Energy (Southern)- Residential Energy Efficiency Rebate Program

    Broader source: Energy.gov [DOE]

    Note: As of January 2016, programs for pool pump rebates, refrigerator recycling, and LED lighting discounts are unavailable in NV Energy's southern territory. See website for more information.

  10. Emergency Management Program Inspection Criteria, Approach, and...

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

    ... for use when an event renders the primary facilities and equipment unavailable, and other site- and facility-specific planning and response capabilities needed for a ...

  11. Tectonic analysis of the Rio Grande Rift Zone, central Colorado...

    Open Energy Info (EERE)

    Rift Zone, central ColoradoThesisDissertation Abstract Abstract unavailable. Author D.H. Knepper Organization Colorado School of Mines Published Publisher Not Provided, 1974...

  12. Update on Mammoth Pacific, LP Operations | Open Energy Information

    Open Energy Info (EERE)

    Update on Mammoth Pacific, LP Operations Abstract Abstract unavailable. Author Charlene L. Wardlow Published Publisher Not Provided, 2011 DOI Not Provided Check for DOI...

  13. Hydrology of the Geothermal System in Long Valley Caldera, California...

    Open Energy Info (EERE)

    System in Long Valley Caldera, California Abstract Abstract unavailable. Author Michael L. Sorey Published Unpublished report for the Long Valley Hydrologic Advisory Committee,...

  14. Hydrologic Monitoring Summary Long Valley Caldera, California...

    Open Energy Info (EERE)

    Summary Long Valley Caldera, California Abstract Abstract unavailable. Author Michael L. Sorey Published ORMAT internal report, 2010 DOI Not Provided Check for DOI...

  15. The Thermal Conductivity of Rocks and Its Dependence Upon Temperature...

    Open Energy Info (EERE)

    unavailable. Authors F. Birch and H. Clark Published Journal American Journal of Science, 1940 DOI Not Provided Check for DOI availability: http:crossref.org Online...

  16. Resource Program

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

    600 average megawatts of generation could be available to the region from concentrated solar power plants in Nevada, but facilities to transmit this power are unavailable until...

  17. The Shallow Hydrothermal System of Long Valley Caldera, California...

    Open Energy Info (EERE)

    Abstract Abstract unavailable. Authors Gene A. Suemnicht, Michael L. Sorey, Joseph N. Moore and Robert Sullivan Conference Stanford, CaliforniaThirty-Second Workshop on...

  18. Salt Wells Geothermal Energy Projects Environmental Impact Statement...

    Open Energy Info (EERE)

    Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Salt Wells Geothermal Energy Projects Environmental Impact Statement Abstract Abstract unavailable....

  19. Updating the Classification of Geothermal Resources - Presentation...

    Open Energy Info (EERE)

    - Presentation Abstract Abstract unavailable. Authors Colin F. Williams and Marshall J. Reed and Arlene F. Anderson Conference Thirty-Sixth Workshop on Geothermal Reservoir...

  20. Radioactive Mineral Occurences in Nevada | Open Energy Information

    Open Energy Info (EERE)

    Radioactive Mineral Occurences in Nevada Abstract Abstract unavailable. Author Larry J. Garside Organization Nevada Bureau of Mines and Geology Published Nevada Bureau of...

  1. Low-Pressure Solubility of Gases in Liquid Water | Open Energy...

    Open Energy Info (EERE)

    Water Abstract Abstract unavailable. Authors Emmerich Wilhelm, Rubin Battino and Robert J. Wilcock Published Journal Chemical reviews, 1977 DOI Not Provided Check for DOI...

  2. An active seismic reconnaissance survey of the Mount Princeton...

    Open Energy Info (EERE)

    area, Chaffee County, ColoradoThesisDissertation Abstract Abstract unavailable. Author J.S. Crompton Organization Colorado School of Mines Published Publisher Not Provided, 1976...

  3. Thermal Waters of Nevada | Open Energy Information

    Open Energy Info (EERE)

    to library Report: Thermal Waters of Nevada Abstract Abstract unavailable. Authors Larry J. Garside and John H. Schilling Organization Nevada Bureau of Mines and Geology Published...

  4. Land Use History of Coso Hot Springs, Inyo County California...

    Open Energy Info (EERE)

    County California Abstract Abstract unavailable. Authors Cecil R. Brooks, W. M. Clements, J. A. Kantner and G. Y. Poirier Published Iroquois Research Institute, 1979 DOI Not...

  5. CHP Enabling Resilient Energy Infrastructure

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

    ... Power Outage Cost Estimates Superstorm Sandy o Nearly 20 billion in losses from ... (unavailability of gas in NJ post Sandy) Emergency Preparedness & Planning o ...

  6. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

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

    coke ovens), and rolling mills. 2. 1998 data unavailable due to disclosure avoidance procedures in place at the time. 3. Denominators represent the entire steel industry, not those...

  7. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    coke ovens), and rolling mills. 3. 1998 data unavailable due to disclosure avoidance procedures in place at the time. 4. Denominators represent the value of production for the...

  8. Marshall Islands: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Marshall Islands Population 56,429 GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code MH 3-letter ISO code MHL Numeric ISO code...

  9. San Marino: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name San Marino Population 32,576 GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code SM 3-letter ISO code SMR Numeric ISO code...

  10. Anguilla: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Anguilla Population 13,452 GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code AI 3-letter ISO code AIA Numeric ISO code...

  11. Tuvalu: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Tuvalu Population 10,837 GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code TV 3-letter ISO code TUV Numeric ISO code...

  12. Drilling results from eastern Long Valley Caldera | Open Energy...

    Open Energy Info (EERE)

    Abstract Abstract unavailable. Authors J.L. Smith and R.W. Rex Published American Nuclear Society, 1977 Report Number Energy and Mineral Resource Recovery DOI Not Provided...

  13. Classification of Geothermal Systems: A Possible Scheme | Open...

    Open Energy Info (EERE)

    of Geothermal Systems: A Possible Scheme Abstract Abstract unavailable. Author Subir K. Sanyal Conference Thirtieth Workshop on Geothermal Reservoir Engineering; Stanford,...

  14. This Week In Petroleum Printer-Friendly Version

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

    would not reach consuming countries until December or later. In addition, due to maintenance, some oil production from the United Arab Emirates was unavailable during much of...

  15. Exploration and Development Techniques for Basin and Range Geothermal...

    Open Energy Info (EERE)

    Abstract Abstract unavailable. Authors David D. Blackwell, Mark Leidig, Richard P. Smith, Stuart D. Johnson and Kenneth W. Wisian Conference GRC Annual Meeting; Reno, NV;...

  16. Resurgent cauldrons | Open Energy Information

    Open Energy Info (EERE)

    library Journal Article: Resurgent cauldrons Abstract Abstract unavailable. Authors R L Smith and R A Bailey Published Journal Geological Society of America Memoir 116, 1968 DOI...

  17. Thermally Speciated Mercury in Mineral Exploration | Open Energy...

    Open Energy Info (EERE)

    Speciated Mercury in Mineral Exploration Abstract Abstract unavailable. Author S.C. Smith Conference IGES; Dublin, CA; 20030901 Published IGES, 2003 DOI Not Provided Check...

  18. BLM Approves Salt Wells Geothermal Energy Projects | Open Energy...

    Open Energy Info (EERE)

    Energy Projects Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: BLM Approves Salt Wells Geothermal Energy Projects Abstract Abstract unavailable....

  19. Principal Types of Volcanoes | Open Energy Information

    Open Energy Info (EERE)

    Types of Volcanoes Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Principal Types of Volcanoes Abstract Abstract unavailable. Author John Watson...

  20. Mammoth Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    Article: Mammoth Geothermal Project Abstract Abstract unavailable. Authors Ben Holt and Richard G. Campbell Published Journal Geo-Heat Center Quarterly Bulletin, 1984 DOI Not...

  1. Energy Department Announces National Geothermal Data System to...

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

    The public data platform encompasses thousands of databases, geologic maps, and reports, drawing from millions of digitized records that were previously unavailable-and can aid ...

  2. A Preliminary Study of the Waters of the Jemez Plateau, New Mexico...

    Open Energy Info (EERE)

    of the Jemez Plateau, New Mexico Abstract Abstract unavailable Authors Clyde Kelly and E.V. Anspach Published Journal University of New Mexico Bulletin, Chemistry Series, 1913 DOI...

  3. Research Highlight

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

    which is often limited or unavailable," said Dr. Evgueni Kassianov, PNNL atmospheric scientist and lead author of the paper, which appears in the journal Atmosphere. "Our...

  4. Insights from Smart Meters. Ramp-up, dependability, and short-term persistence of savings from Home Energy Reports

    SciTech Connect (OSTI)

    Todd, Annika; Perry, Michael; Smith, Brian; Sullivan, Michael; Cappers, Peter; Goldman, Charles A.

    2015-04-21

    Smart meters, smart thermostats, and other new technologies provide previously unavailable high-frequency and location-specific energy usage data. Many utilities are now able to capture real-time, customer specific hourly interval usage data for a large proportion of their residential and small commercial customers. These vast, constantly growing streams of rich data (or, “big data”) have the potential to provide novel insights into key policy questions about how people make energy decisions. The richness and granularity of these data enable many types of creative and cutting-edge analytics. Technically sophisticated and rigorous statistical techniques can be used to pull useful insights out of this high-frequency, human-focused data. In this series, we call this “behavior analytics.” This kind of analytics has the potential to provide tremendous value to a wide range of energy programs. For example, disaggregated and heterogeneous information about actual energy use allows energy efficiency (EE) and/or demand response (DR) program implementers to target specific programs to specific households; enables evaluation, measurement and verification (EM&V) of energy efficiency programs to be performed on a much shorter time horizon than was previously possible; and may provide better insights into the energy and peak hour savings associated with EE and DR programs (e.g., behavior-based (BB) programs). The goal of this series is to enable evidence-based and data-driven decision making by policy makers and industry stakeholders, including program planners, program administrators, utilities, state regulatory agencies, and evaluators. We focus on research findings that are immediately relevant.

  5. Insights from Smart Meters: The Potential for Peak-Hour Savings from Behavior-Based Programs

    SciTech Connect (OSTI)

    Todd, Annika; Perry, Michael; Smith, Brian; Sullivan, Michael; Cappers, Peter; Goldman, Charles

    2014-03-25

    The rollout of smart meters in the last several years has opened up new forms of previously unavailable energy data. Many utilities are now able in real-time to capture granular, household level interval usage data at very high-frequency levels for a large proportion of their residential and small commercial customer population. This can be linked to other time and locationspecific information, providing vast, constantly growing streams of rich data (sometimes referred to by the recently popular buzz word, “big data”). Within the energy industry there is increasing interest in tapping into the opportunities that these data can provide. What can we do with all of these data? The richness and granularity of these data enable many types of creative and cutting-edge analytics. Technically sophisticated and rigorous statistical techniques can be used to pull interesting insights out of this highfrequency, human-focused data. We at LBNL are calling this “behavior analytics”. This kind of analytics has the potential to provide tremendous value to a wide range of energy programs. For example, highly disaggregated and heterogeneous information about actual energy use would allow energy efficiency (EE) and/or demand response (DR) program implementers to target specific programs to specific households; would enable evaluation, measurement and verification (EM&V) of energy efficiency programs to be performed on a much shorter time horizon than was previously possible; and would provide better insights in to the energy and peak hour savings associated with specifics types of EE and DR programs (e.g., behavior-based (BB) programs). In this series, “Insights from Smart Meters”, we will present concrete, illustrative examples of the type of value that insights from behavior analytics of these data can provide (as well as pointing out its limitations). We will supply several types of key findings, including: • Novel results, which answer questions the industry previously was unable to answer; • Proof-of-concept analytics tools that can be adapted and used by others; and • Guidelines and protocols that summarize analytical best practices. This report focuses on one example of the kind of value that analysis of this data can provide: insights into whether behavior-based (BB) efficiency programs have the potential to provide peak-hour energy savings.

  6. table4.xls

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

    Household, Selected Survey Years Survey Years Household Composition Households With Children... NA NA 2.0 2.0 2.0 2.2 Age of Oldest Child Under...

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. --No Title--

    Buildings Energy Data Book [EERE]

    2 2005 Residential Delivered Energy Consumption Intensities, by Vintage Per Square Per Household Per Household Percent of Year Built Foot (thousand Btu) (1) (million Btu) Member ...

  13. --No Title--

    Buildings Energy Data Book [EERE]

    1 2005 Residential Delivered Energy Consumption Intensities, by Housing Type Per Square Per Household Per Household Percent of Type Foot (thousand Btu) (1) (million Btu) Members ...

  14. Preliminary Release: August 19, 2011",,,,,,,,,,,,,"Released:...

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

    ... household products that meet strict energy efficiency guidelines earn the Energy Star. ... household products that meet strict energy efficiency guidelines earn the Energy Star. ...

  15. Targeted Marketing and Program Design for Low- and Moderate-Income...

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

    Targeted Marketing and Program Design for Low- and Moderate-Income Households Targeted Marketing and Program Design for Low- and Moderate-Income Households Better Buildings ...

  16. 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 ...

  17. 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...

  18. Microsoft Word - Mont Co Final Report 1-4-13

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

    to reduce energy consumption for low-income households through energy efficient upgrades. ... The Weatherization Program helps eligible low-income households lower their energy costs ...

  19. Table 4

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

    1. Mean Annual Electricity Consumption for Lighting, by Number of Household Members by Number of Rooms, 1993 (Kilowatthours) Number of Rooms Number of Household Members All...

  20. table13.xls

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

    Survey Years (Nominal Dollars) Survey Years Household Composition Households With Children... NA NA 599 708 722 886 Age of Oldest Child Under...

  1. table2.xls

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

    Vehicles, Selected Survey Years Survey Years Household Composition Households With Children... NA NA 91 92 91 93 Age of Oldest Child Under 7...

  2. Fuel Consumption per Vehicle.xls

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

    Selected Survey Years (Gallons) Survey Years Household Composition Households With Children... NA NA 609 597 625 665 Age of Oldest Child Under...

  3. table14.xls

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

    Survey Years (Nominal Dollars) Survey Years Household Composition Households With Children... NA NA 1,198 1,395 1,453 1,903 Age of Oldest...

  4. table5.xls

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

    Selected Survey Years (Billions) Survey Years Household Composition Households With Children... NA NA 674 753 796 1,078 Age of Oldest Child...

  5. Microsoft Word - 20050821_Appendix_A.doc

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

    A9. U.S. Average Vehicle-Miles Traveled by Family Income and Poverty Status, 2001 (Thousand Miles per Household) ENERGY INFORMATION ADMINISTRATION HOUSEHOLD VEHICLES ENERGY USE:...

  6. Microsoft Word - 20050821_Appendix_A.doc

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

    0. U.S. Average Vehicle Fuel Consumption by Family Income and Poverty Status, 2001 (Gallons per Household) ENERGY INFORMATION ADMINISTRATION HOUSEHOLD VEHICLES ENERGY USE: LATEST...

  7. Buildings and Energy in the 1980s

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

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

  8. Slide 1

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

    Need 3 Significant number of low-income customers. * 12% of families below federal poverty level. * 18% of households receive food stamps. * 34% have household incomes income...

  9. BENTON PUD LOW INCOME CONSERVATION PROGRAM

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

    result in a preference being given to households with incomes below 125% of Federal Poverty Guidelines (FPG) Upper low income households with incomes between 125 and 200%...

  10. 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...

  11. Buildings and Energy in the 1980s

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

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

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

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

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

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

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

    ... Below Poverty Line (100 Percent and 125 Percent)-Low income classifications to which certain households are assigned. "Below 100 percent of poverty line includes households with ...

  14. accomplishment reports | netl.doe.gov

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

    Air Conditioning Tables (Million U.S. Households; 24 pages, 138 kb) Contents Pages HC4-1a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 2 HC4-2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 2 HC4-3a. Air Conditioning by Household Income, Million U.S. Households, 2001 2 HC4-4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 2 HC4-5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2

  15. approved_list

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

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

  16. apr01

    Gasoline and Diesel Fuel Update (EIA)

    Air Conditioning Tables (Million U.S. Households; 24 pages, 138 kb) Contents Pages HC4-1a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 2 HC4-2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 2 HC4-3a. Air Conditioning by Household Income, Million U.S. Households, 2001 2 HC4-4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 2 HC4-5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2

  17. S:\VM3\RX97\TBL_LIST.WPD

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

    Space Heating Tables (Percent of U.S. Households; 24 pages, 85 kb) Contents Pages HC3-1b. Space Heating by Climate Zone, Percent of U.S. Households, 1997 2 HC3-2b. Space Heating by Year of Construction, Percent of U.S. Households, 1997 2 HC3-3b. Space Heating by Household Income, Percent of U.S. Households, 1997 2 HC3-4b. Space Heating by Type of Housing Unit, Percent of U.S. Households, 1997 2 HC3-5b. Space Heating by Type of Owner-Occupied Housing Unit, Percent of U.S. Households, 1997 2

  18. S:\VM3\RX97\TBL_LIST.WPD [PFP#201331587]

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

    Million U.S. Households; 24 pages, 78 kb) Contents Pages HC4-1a. Air Conditioning by Climate Zone, Million U.S. Households, 1997 2 HC4-2a. Air Conditioning by Year of Construction, Million U.S. Households, 1997 2 HC4-3a. Air Conditioning by Household Income, Million U.S. Households, 1997 2 HC4-4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 1997 2 HC4-5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 1997 2 HC4-6a. Air Conditioning by

  19. S:\VM3\RX97\TBL_LIST.WPD [PFP#201331587]

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

    Million U.S. Households; 12 pages, 47 kb) Contents Pages HC7-1a. Home Office Equipment by Climate Zone, Million U.S. Households, 1997 1 HC7-2a. Home Office Equipment by Year of Construction, Million U.S. Households, 1997 1 HC7-3a. Home Office Equipment by Household Income, Million U.S. Households, 1997 1 HC7-4a. Home Office Equipment by Type of Housing Unit, Million U.S. Households, 1997 1 HC7-5a. Home Office Equipment by Type of Owner-Occupied Housing Unit, Million U.S. Households, 1997 1

  20. S:\VM3\RX97\TBL_LIST.WPD [PFP#201331587]

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

    Million U.S. Households; 48 pages, 134 kb) Contents Pages HC6-1a. Usage Indicators by Climate Zone, Million U.S. Households, 1997 4 HC6-2a. Usage Indicators by Year of Construction, Million U.S. Households, 1997 4 HC6-3a. Usage Indicators by Household Income, Million U.S. Households, 1997 4 HC6-4a. Usage Indicators by Type of Housing Unit, Million U.S. Households, 1997 4 HC6-5a. Usage Indicators by Type of Owner-Occupied Housing Unit, Million U.S. Households, 1997 4 HC6-6a. Usage Indicators by

  1. Computer usage and national energy consumption: Results from a field-metering study

    SciTech Connect (OSTI)

    Desroches, Louis-Benoit; Fuchs, Heidi; Greenblatt, Jeffery; Pratt, Stacy; Willem, Henry; Claybaugh, Erin; Beraki, Bereket; Nagaraju, Mythri; Price, Sarah; Young, Scott

    2014-12-01

    The electricity consumption of miscellaneous electronic loads (MELs) in the home has grown in recent years, and is expected to continue rising. Consumer electronics, in particular, are characterized by swift technological innovation, with varying impacts on energy use. Desktop and laptop computers make up a significant share of MELs electricity consumption, but their national energy use is difficult to estimate, given uncertainties around shifting user behavior. This report analyzes usage data from 64 computers (45 desktop, 11 laptop, and 8 unknown) collected in 2012 as part of a larger field monitoring effort of 880 households in the San Francisco Bay Area, and compares our results to recent values from the literature. We find that desktop computers are used for an average of 7.3 hours per day (median = 4.2 h/d), while laptops are used for a mean 4.8 hours per day (median = 2.1 h/d). The results for laptops are likely underestimated since they can be charged in other, unmetered outlets. Average unit annual energy consumption (AEC) for desktops is estimated to be 194 kWh/yr (median = 125 kWh/yr), and for laptops 75 kWh/yr (median = 31 kWh/yr). We estimate national annual energy consumption for desktop computers to be 20 TWh. National annual energy use for laptops is estimated to be 11 TWh, markedly higher than previous estimates, likely reflective of laptops drawing more power in On mode in addition to greater market penetration. This result for laptops, however, carries relatively higher uncertainty compared to desktops. Different study methodologies and definitions, changing usage patterns, and uncertainty about how consumers use computers must be considered when interpreting our results with respect to existing analyses. Finally, as energy consumption in On mode is predominant, we outline several energy savings opportunities: improved power management (defaulting to low-power modes after periods of inactivity as well as power scaling), matching the rated power of power supplies to computing needs, and improving the efficiency of individual components.

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

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

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

  3. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  4. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total 83.1 66.1 144.2 37 17 29.1 10 678 0.31 539 192 Census Region and Division

  5. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total 83.7 66.0 142.2 36 16 28.0 10 708 0.33 558 204 Census Region and Division

  6. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total 86.3 67.4 144.3 37 17 28.8 11 808 0.38 632 234 Census Region and Division

  7. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total 90.5 70.4 156.8 39 18 30.5 12 875 0.39 680 262 Census Region and Division

  8. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 97 Average Electricity Residential Buildings Consumption Expenditures Total per Floor- per Square per per per Total Total space (1) Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total 101.4 83.2 168.8 42 21 35.0 13 1,061 0.52 871 337 Census Region and

  9. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2001 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total 107.0 85.2 211.2 46 18 36.0 14 1,178 0.48 938 366 Census Region and Division

  10. Major NERSC Maintenance Tuesday November 11

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

    Major NERSC Maintenance Tuesday November 11 Major NERSC Maintenance Tuesday November 11 October 31, 2014 by Francesca Verdier There will be a major NERSC maintenance on Tuesday, November 11, from 08:00 until 18:00 PST. Several systems and services will be unavailable during this time. Edison, Hopper, Data Transfer nodes, and Science Gateway (data portal) nodes will be unavailable 08:00 - 13:00. Carver/Dirac, PDSF, and Genepool will be unavailable 08:00 - 18:00. HPSS and web servers

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

    SciTech Connect (OSTI)

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

    2008-01-01

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

  12. Alarm guided critical function and success path monitoring

    DOE Patents [OSTI]

    Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

    1994-01-01

    The use of alarm indication on the overview (IPSO) display to initiate diagnosis of challenges to critical functions or unavailability of success paths, and further alarm-based guidance toward ultimate diagnosis.

  13. NV Energy (Northern Nevada)- Residential Energy Efficiency Rebate Program

    Broader source: Energy.gov [DOE]

    Note: NV Energy's Second Refrigerator or Freezer Recycling program is currently unavailable. Check the website or contact the program at recycle@nvenergy.com for updates and more information.

  14. PDSF User Meeting 07-07-15.pptx

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

    July 7 , 2 015 Lisa Gerhardt Utilization --- 2 --- Past Outages * 6315 (12 hour): NX unavailable * 7415 (6 hours): System wide outage due to global common i ssues * 7515 (1...

  15. Radiometric Ages- Compilation 'B', U.S. Geological Survey | Open...

    Open Energy Info (EERE)

    Abstract Abstract unavailable Authors R.F. Marvin and S.W. Dobson Published New Mexico Bureau of Mines and Mineral Resources, 1979 Report Number IsochronWest no. 26 DOI Not...

  16. Denmark: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    MWhyear 143 2008 NREL Coal Reserves Unavailable Million Short Tons NA 2008 EIA Natural Gas Reserves 61,300,000,000 Cubic Meters (cu m) 62 2010 CIA World Factbook Oil Reserves...

  17. Netherlands: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    MWhyear 151 2008 NREL Coal Reserves Unavailable Million Short Tons NA 2008 EIA Natural Gas Reserves 1,416,000,000,000 Cubic Meters (cu m) 24 2010 CIA World Factbook Oil Reserves...

  18. Running on Carver

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

    Running on Carver Running on Carver The Daya Bay software is installed on PDSF on common so is therefore unavailable on Carver. At this point there has been no effort to port the...

  19. Present Day Kinematics of the Eastern California Shear Zone from...

    Open Energy Info (EERE)

    Abstract unavailable. Authors S.C. McClusky, S.C. Bjomstad, B. H. Hager, R. W. King, B. J. Meade, M. M. Miller, F. C. Monastero and B. J. Souter Published Journal Geophysical...

  20. The Magma Energy Program | Open Energy Information

    Open Energy Info (EERE)

    Article: The Magma Energy Program Abstract Abstract unavailable. Authors T.Y. Chu, J.C. Dunn, John T. Finger, John B. Rundle and H.R. Westrich Published Journal Geothermal...

  1. Kenya: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Kenya Population 38,610,097 GDP Unavailable Energy Consumption 0.21 Quadrillion Btu 2-letter ISO code KE 3-letter ISO code KEN Numeric ISO...

  2. Greenland: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Greenland Population 56,968 GDP Unavailable Energy Consumption 0.01 Quadrillion Btu 2-letter ISO code GL 3-letter ISO code GRL Numeric ISO...

  3. United States: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    page. Country Profile Name United States Population 320,206,000 GDP Unavailable Energy Consumption 99.53 Quadrillion Btu 2-letter ISO code US 3-letter ISO code USA Numeric ISO...

  4. Syria: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Syria Population 17,951,639 GDP Unavailable Energy Consumption 0.84 Quadrillion Btu 2-letter ISO code SY 3-letter ISO code SYR Numeric ISO...

  5. South Korea: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name South Korea Population 51,302,044 GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code KR 3-letter ISO code KOR Numeric ISO code...

  6. Somalia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Somalia Population 10,428,043 GDP Unavailable Energy Consumption 0.01 Quadrillion Btu 2-letter ISO code SO 3-letter ISO code SOM Numeric ISO...

  7. Montserrat: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Montserrat Population 4,900 GDP Unavailable Energy Consumption 0.00 Quadrillion Btu 2-letter ISO code MS 3-letter ISO code MSR Numeric ISO...

  8. Nepal: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Nepal Population 26,494,504 GDP Unavailable Energy Consumption 0.08 Quadrillion Btu 2-letter ISO code NP 3-letter ISO code NPL Numeric ISO...

  9. Nauru: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    "","visitedicon":"" Country Profile Name Nauru Population 9,275 GDP Unavailable Energy Consumption 0.00 Quadrillion Btu 2-letter ISO code NR 3-letter ISO code NRU Numeric ISO...

  10. Northern Mariana Islands: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Northern Mariana Islands Population 53,833 GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code MP 3-letter ISO code MNP Numeric ISO code...

  11. Turks and Caicos Islands: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Turks and Caicos Islands Population 31,458 GDP Unavailable Energy Consumption 0.00 Quadrillion Btu 2-letter ISO code TC 3-letter ISO code TCA Numeric ISO...

  12. Portugal: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Portugal Population 10,562,178 GDP Unavailable Energy Consumption 1.06 Quadrillion Btu 2-letter ISO code PT 3-letter ISO code PRT Numeric ISO...

  13. Republic of Macedonia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Republic of Macedonia Population 2,022,547 GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code MK 3-letter ISO code MKD Numeric ISO code...

  14. Slovakia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Slovakia Population 5,397,036 GDP Unavailable Energy Consumption 0.80 Quadrillion Btu 2-letter ISO code SK 3-letter ISO code SVK Numeric ISO...

  15. Bhutan: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Bhutan Population Unavailable GDP 1,488,000,000 Energy Consumption 0.05 Quadrillion Btu 2-letter ISO code BT 3-letter ISO code BTN Numeric ISO...

  16. Saint Helena: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Saint Helena Population 4,255 GDP Unavailable Energy Consumption 0.00 Quadrillion Btu 2-letter ISO code SH 3-letter ISO code SHN Numeric ISO...

  17. Malaysia: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Malaysia Population 28,334,135 GDP Unavailable Energy Consumption 2.45 Quadrillion Btu 2-letter ISO code MY 3-letter ISO code MYS Numeric ISO...

  18. New Zealand: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name New Zealand Population 4,242,048 GDP Unavailable Energy Consumption Quadrillion Btu 2-letter ISO code NZ 3-letter ISO code NZL Numeric ISO code...

  19. Pakistan: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Pakistan Population 196,174,380 GDP Unavailable Energy Consumption 2.48 Quadrillion Btu 2-letter ISO code PK 3-letter ISO code PAK Numeric ISO...

  20. Moldova: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Moldova Population Unavailable GDP 8,738,000,000 Energy Consumption 0.14 Quadrillion Btu 2-letter ISO code MD 3-letter ISO code MDA Numeric ISO...

  1. Bangladesh: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Bangladesh Population 156,594,962 GDP Unavailable Energy Consumption 0.87 Quadrillion Btu 2-letter ISO code BD 3-letter ISO code BGD Numeric ISO...

  2. Bahrain: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Bahrain Population 1,234,571 GDP Unavailable Energy Consumption 0.55 Quadrillion Btu 2-letter ISO code BH 3-letter ISO code BHR Numeric ISO...

  3. Sweden: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Country Profile Name Sweden Population 9,658,301 GDP Unavailable Energy Consumption 2.22 Quadrillion Btu 2-letter ISO code SE 3-letter ISO code SWE Numeric ISO...

  4. Email Announcements Archive

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

    Email Announcements Archive Email Announcements Archive Subject Date Author Edison will be unavailable this Thursday, 172016 8:00-17:00 PST 2016-01-05 15:37:04 Zhengji Zhao...

  5. Chemical Evolution and Chemical State of the Long Valley Magma...

    Open Energy Info (EERE)

    Abstract Abstract unavailable. Author Roy A. Bailey Published U.S. Geological Survey, 1984 Report Number Open File Report 84-939 DOI Not Provided Check for DOI availability:...

  6. Ghana: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    MWhyear 73 2008 NREL Coal Reserves Unavailable Million Short Tons NA 2008 EIA Natural Gas Reserves 22,650,000,000 Cubic Meters (cu m) 76 2010 CIA World Factbook Oil Reserves...

  7. Benin: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    MWhyear 100 2008 NREL Coal Reserves Unavailable Million Short Tons NA 2008 EIA Natural Gas Reserves 1,133,000,000 Cubic Meters (cu m) 97 2010 CIA World Factbook Oil Reserves...

  8. Request to Cancel DOE G 481.1-1, Department of Energy Work for Others Guide

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2015-11-23

    By Cancelling this directive DOE is reducing duplicative publications of program related information and recognizing the effects of DOE/contractor working groups and the use of previously unavailable electronic communication systems.

  9. PDSF Selected Announcements

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

    February 2011 pdsfdtn1 maintenance 3211, 0900-1700 PT February 28, 2011 by Eric Hjort During the maintenance pdsfdtn1 will be down and unavailable. Read the full post eliza5...

  10. Microsoft Word - DOE EISs unavilable Electronically Template

    National Nuclear Security Administration (NNSA)

    DOE, 2001a, is unavailable to the public in an electronic format due to security sensitivity of some of the information within the document. DOE will continue to provide hard ...

  11. Geologic Map of the Jemez Mountains, New Mexico | Open Energy...

    Open Energy Info (EERE)

    MexicoInfo GraphicMapChart Abstract Abstract unavailable Cartographers Robert Leland Smith, Roy A. Bailey and Clarence Samuel Ross Published U.S. Geological Survey, 1970 DOI Not...

  12. Salt Wells, Eight Mile Flat | Open Energy Information

    Open Energy Info (EERE)

    Eight Mile Flat Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Salt Wells, Eight Mile Flat Abstract Abstract unavailable. Author Nevada Bureau...

  13. Web Page Error 404.1 Page Cannot be Found

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

    Us Media Center Contact Us Site Map The page you are looking for cannot be found. The Web site you are looking for is unavailable due to its identification configuration...

  14. Guinea-Bissau: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    0 Area(km) Class 3-7 Wind at 50m 116 1990 NREL Solar Potential 93,662,158 MWhyear 132 2008 NREL Coal Reserves Unavailable Million Short Tons NA 2008 EIA Natural Gas...

  15. 2007 Annual Report | Open Energy Information

    Open Energy Info (EERE)

    7 Annual Report Jump to: navigation, search OpenEI Reference LibraryAdd to library Report: 2007 Annual Report Abstract Abstract unavailable. Author Enel Organization Enel S.p.A....

  16. U-232: Xen p2m_teardown() Bug Lets Local Guest OS Users Deny...

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

    unavailable and may cause the domain 0 kernel to panic. There is no requirement for memory sharing to be in use. Impact: A guest kernel can cause the host to become unresponsive...

  17. DARPA looks beyond GPS for positioning, navigating, and timing

    SciTech Connect (OSTI)

    Kramer, David

    2014-10-01

    Cold-atom interferometry, microelectromechanical systems, signals of opportunity, and atomic clocks are some of the technologies the defense agency is pursuing to provide precise navigation when GPS is unavailable.

  18. PDSF Selected Announcements

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

    42611: eliza18 emergency maintenance 9am-3pm April 25, 2011 by Eric Hjort | 0 Comments The Eliza18 filesystem will be unavailable from 9AM - 3PM tomorrow (0426) for emergency...

  19. Gas Clean-Up for Fuel Cell Applications Workshop Report

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

    ... in pos eum quo con et grid electricity is unavailable and the fuel effciency, reliability and environment friendliness of the fuel cell is of greatest beneft to the client. ...

  20. Table 10.24 Reasons that Made Distillate Fuel Oil Unswitchable, 2006;

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

    4 Reasons that Made Distillate Fuel Oil Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million barrels. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Distillate Fuel Oil Unswitchable Distillate Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry Consumed as a Fue Fuel Oil Fuel Use

  1. Table 10.25 Reasons that Made Residual Fuel Oil Unswitchable, 2006;

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

    5 Reasons that Made Residual Fuel Oil Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million barrels. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Residual Fuel Oil Unswitchable ResiduaCapable of Using Adversely Affects Alternative Environmental Contract Storage for Another Columns F, G, Code(a) Subsector and Industry Consumed as a Fue Fuel Oil Fuel Use

  2. Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable;

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

    0 Reasons that Made Electricity Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million kWh. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Electricity Consumed Unswitchable Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry as a Fuel Electricity Fuel Use Another Fuel the Products

  3. Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable;

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

    1 Reasons that Made Natural Gas Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Billion cubic feet. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Natural Gas Unswitchable Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry Consumed as a FueNatural Gas Fuel Use Another Fuel the

  4. Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable;

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

    2 Reasons that Made Coal Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million short tons. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Coal Consumed Unswitchable Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry as a Fuel Coal Fuel Use Another Fuel the Products Fuel

  5. Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable;

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

    3 Reasons that Made LPG Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million barrels. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS LPG Consumed Unswitchable Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry as a Fuel LPG Fuel Use Another Fuel the Products Fuel

  6. homogeneous charge compression ignition

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

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

  7. how-to-speed-up-traffic

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

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

  8. jan02

    Gasoline and Diesel Fuel Update (EIA)

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

  9. oil1997.xls

    Gasoline and Diesel Fuel Update (EIA)

    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 13.2 11.0 23.2 97 46 81.1 31 694 0.33 578 224 Census Region and Division Northeast 8.2 6.2 14.5 136 57 101.3 40 950 0.40 710 282 New England 3.1

  10. oil2001.xls

    Gasoline and Diesel Fuel Update (EIA)

    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 11.2 9.4 26.0 80 29 67.1 26 723 0.26 607 236 Census Region and Division Northeast 7.1 5.4 16.8 111 36 84.7 33 992 0.32 757 297 New England 2.9 2.5 8.0 110

  11. R93HC.PDF

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

    3. Total Air-Conditioning in U.S. Households, 1993 Housing Unit and Household Characteristics RSE Column Factor: Total Households (millions) Cooled Floorspace (square feet per household) Number of Cooling Degree-Days per Household Air-Conditioner Use in Summer 1993 1 (percent of households) RSE Row Factors 1993 Normal Total Not at All Only a Few Times Quite a Bit All Summer 0.8 0.6 0.6 0.6 3.5 0.9 1.4 1.2 Total .................................................... 66.1 1,416 1,536 1,438 100.0 3.4

  12. S:\VM3\RX97\TBL_LIST.WPD

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

    V 1997 Housing Characteristics Tables Space Heating Tables (Million U.S. Households; 24 pages, 83 kb) Contents Pages HC3-1a. Space Heating by Climate Zone, Million U.S. Households, 1997 2 HC3-2a. Space Heating by Year of Construction, Million U.S. Households, 1997 2 HC3-3a. Space Heating by Household Income, Million U.S. Households, 1997 2 HC3-4a. Space Heating by Type of Housing Unit, Million U.S. Households, 1997 2 HC3-5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S.

  13. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 94.0 74.2 169.2 124 54 98.1 38 1,485 0.65 1,172 450 Census

  14. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 3 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 96.6 76.4 181.2 43 18 34.0 13 1,061 0.45 840 321 Census Region

  15. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 Average Fuel Oil/Kerosene 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 15.4 11.6 29.7 131 51 99.0 36 1,053 0.41 795 287 Census

  16. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 Average Fuel Oil/Kerosene 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 14.6 11.0 28.9 116 44 87.9 32 1,032 0.39 781 283 Census

  17. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 Average Fuel Oil/Kerosene 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 15.5 12.2 30.0 98 40 77.1 27 829 0.34 650 231 Census

  18. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 Average Fuel Oil/Kerosene 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 17.5 13.8 32.0 91 39 71.9 27 697 0.30 550 203 Census

  19. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average Fuel Oil/Kerosene 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 17.4 14.0 33.3 87 37 70.3 27 513 0.22 414 156 Census

  20. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 90 Average Fuel Oil/Kerosene 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 16.3 13.5 33.2 77 31 63.9 23 609 0.25 506 181 Census

  1. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 3 Average Fuel Oil/Kerosene 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 13.8 11.6 29.8 92 36 77.5 28 604 0.23 506 186 Census

  2. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average Fuel Oil/Kerosene 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 13.2 11.0 23.2 97 46 81.1 31 694 0.33 578 224 Census

  3. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires Fuel Oil/Kerosene, 2001 Average Fuel Oil/Kerosene 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 11.2 9.4 26.0 80 29 67.1 26 723 0.26

  4. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 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 7.7 7.4 12.1 47 29 45.6 16 379 0.23 365 125 Census Region and Division

  5. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 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 7.3 7.2 12.2 44 26 42.8 15 389 0.23 382 133 Census Region and Division

  6. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 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 7.3 7.2 11.7 40 25 39.6 14 383 0.23 376 132 Census Region and Division

  7. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 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 7.8 7.7 12.0 41 26 40.1 15 406 0.26 398 146 Census Region and Division

  8. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 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 7.7 7.6 12.3 41 26 41.1 15 369 0.23 366 131 Census Region and Division

  9. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 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 8.2 0.5 13.9 542 20 34.1 12 6,063 0.23 381 134 Census Region and

  10. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 3 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 8.1 7.9 14.9 48 25 46.8 17 481 0.26 470 170 Census Region and Division

  11. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average LPG 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 8.1 8.0 13.9 45 26 44.6 17 508 0.29 500 192 Census Region and

  12. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 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 53.4 41.5 92.8 127 57 98.7 35 578 0.26 450 159 Census Region and

  13. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 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 54.2 41.0 91.8 116 52 87.6 32 658 0.29 498 183 Census Region and

  14. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 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 55.4 41.3 93.2 121 53 89.9 33 722 0.32 537 198 Census Region and

  15. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 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 57.3 42.5 99.4 114 49 84.3 33 615 0.26 456 176 Census Region and

  16. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 Average of Major Energy Sources Residential Buildings Consumption Expenditures Total per per per per Total Total Floorspace per Square per Household per Square per Household Households Number (billion Building Foot Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) (million Btu) (thousand Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 81.6 65.4 142.5 143 65 114.1 41 1,156 0.53 926 330

  17. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 Average of Major Energy Sources 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) (millionBtu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 83.1 66.1 144.2 141 64 111.7 40 1,256 0.58 998 356

  18. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 Average of Major Energy Sources 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 83.8 66.1 142.2 130 60 102.3 37 1,309 0.61 1,033 377

  19. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 Average of Major Energy Sources 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 86.3 67.5 144.4 134 63 104.7 39 1,437 0.67 1,123 417

  20. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average of Major Energy Sources 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 90.5 70.4 156.8 130 58 100.8 39 1,388 0.62 1,080 416

  1. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 Average of Major Energy Sources 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 94.0 74.2 169.2 124 54 98.1 38 1,485 0.65 1,172 450

  2. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 3 Average of Major Energy Sources 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 96.6 76.5 181.2 131 55 103.6 40 1,620 0.68 1,282 491

  3. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average of Major Energy Sources Residential Buildings Consumption Expenditures Total per Floor- per Square per per per Total Total space(2) 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 101.5 83.2 168.8 123 61 101.0 39 1,633 0.80

  4. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2001 Average of Major Energy Sources 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 107.0 85.2 211.3 116 47 92.2 36 1,875 0.76 1,493

  5. 1997 SSRL Accelerator Physics Schedule

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

    Percent of U.S. Households; 13 pages, 48 kb) Contents Pages HC7-1b. Home Office Equipment by Climate Zone, Percent of U.S. Households, 1997 1 HC7-2b. Home Office Equipment by Year of Construction, Percent of U.S. Households, 1997 1 HC7-3b. Home Office Equipment by Household Income, Percent of U.S. Households, 1997 1 HC7-4b. Home Office Equipment by Type of Housing Unit, Percent of U.S. Households, 1997 1 HC7-5b. Home Office Equipment by Type of Owner-Occupied Housing Unit, Percent of U.S.

  6. 1Q97.pdf

    Gasoline and Diesel Fuel Update (EIA)

    Percent of U.S. Households; 13 pages, 48 kb) Contents Pages HC7-1b. Home Office Equipment by Climate Zone, Percent of U.S. Households, 1997 1 HC7-2b. Home Office Equipment by Year of Construction, Percent of U.S. Households, 1997 1 HC7-3b. Home Office Equipment by Household Income, Percent of U.S. Households, 1997 1 HC7-4b. Home Office Equipment by Type of Housing Unit, Percent of U.S. Households, 1997 1 HC7-5b. Home Office Equipment by Type of Owner-Occupied Housing Unit, Percent of U.S.

  7. 1997 Housing Characteristics Tables Home Office Equipment Tables

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

    Percent of U.S. Households; 13 pages, 48 kb) Contents Pages HC7-1b. Home Office Equipment by Climate Zone, Percent of U.S. Households, 1997 1 HC7-2b. Home Office Equipment by Year of Construction, Percent of U.S. Households, 1997 1 HC7-3b. Home Office Equipment by Household Income, Percent of U.S. Households, 1997 1 HC7-4b. Home Office Equipment by Type of Housing Unit, Percent of U.S. Households, 1997 1 HC7-5b. Home Office Equipment by Type of Owner-Occupied Housing Unit, Percent of U.S.

  8. 1997 Housing Characteristics Tables Housing Unit Tables

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

    Million U.S. Households; 45 pages, 128 kb) Contents Pages HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 1997 4 HC1-2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 1997 4 HC1-3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 1997 4 HC1-4a. Housing Unit Characteristics by Type of Housing Unit, Million U.S. Households, 1997 3 HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit,

  9. 1997 Housing Characteristics Tables Housing Unit Tables

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

    Percent of U.S. Households; 45 pages, 121 kb) Contents Pages HC1-1b. Housing Unit Characteristics by Climate Zone, Percent of U.S. Households, 1997 4 HC1-2b. Housing Unit Characteristics by Year of Construction, Percent of U.S. Households, 1997 4 HC1-3b. Housing Unit Characteristics by Household Income, Percent of U.S. Households, 1997 4 HC1-4b. Housing Unit Characteristics by Type of Housing Unit, Percent of U.S. Households, 1997 3 HC1-5b. Housing Unit Characteristics by Type of Owner-Occupied

  10. STEO October 2012 - wood

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

    that households across the U.S. use as a supplemental heating source. Almost half of all rural households use wood this way, in addition to using it for cooking or water heating

  11. Table 4

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

    4. Light Usage by Total Number of Rooms, Percent of U.S. Households, 1993 Total Number of Rooms Housing Unit and Household Characteristics Total 1 or 2 3 to 5 6 to 8 9 or More RSE...

  12. Table 4

    Gasoline and Diesel Fuel Update (EIA)

    3. Light Usage by Total Number of Rooms, Million U.S. Households, 1993 Total Number of Rooms (excluding bathrooms) Housing Unit and Household Characteristics Total 1 or 2 3 to 5 6...

  13. table12.xls

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

    Years (Billion Nominal Dollars) Survey Years Household Composition Households With Children... NA NA 35.9 46.1 46.7 70.7 Age of Oldest Child...

  14. table1.xls

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

    Selected Survey Years (Millions) Survey Years Household Composition Households With Children... NA NA 29.9 33.0 32.1 37.1 Age of Oldest Child...

  15. " East North Central",1296,1220,977,1185,1225,1577

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

    More Persons",1790,1711,1422,1500,1700,2202 "Household Composition" " Households With Children","NA","NA",1198,1395,1453,1903 " Age of Oldest Child" " Under 7 Years","NA","NA",1057...

  16. table8.xls

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

    Survey Years (Billion Gallons) Survey Years Household Composition Households With Children... NA NA 36.4 38.9 40.4 53.1 Age of Oldest Child...

  17. table3.xls

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

    Selected Survey Years (Millions) Survey Years Household Composition Households With Children... NA NA 59.8 65.1 64.6 79.8 Age of Oldest Child...

  18. table7.xls

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

    Selected Survey Years (Thousands) Survey Years Household Composition Households With Children... NA NA 22.5 22.8 24.8 29.2 Age of Oldest Child...

  19. Z

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

    or the population as a whole. Alternative vehicle usage within a household is a real option for those households which have more than one vehicle. The use of large...

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

    Gasoline and Diesel Fuel Update (EIA)

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