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Sample records for unavailable median household

  1. 503 Service Temporarily Unavailable

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

    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. 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.

  3. 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....

  4. char_household2001.pdf

    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

  5. 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.

  6. ac_household2001.pdf

    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

  7. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

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

  8. usage_household2001.pdf

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

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

  9. homeoffice_household2001.pdf

    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,

  10. housingunit_household2001.pdf

    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

  11. 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...

  12. appl_household2001.pdf

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

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

  13. 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 ...

  14. 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 ...

  15. char_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    9a. Household Characteristics by Northeast Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.5 Total .............................................................. 107.0 20.3 14.8 5.4 NE Household Size 1 Person ...................................................... 28.2 6.0 4.4 1.6 3.5 2 Persons

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  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. 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 ...

  2. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    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

  3. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    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

  4. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (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 Census Division Mountain Pacific 0.4 1.2 1.7 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 10.7 3.4 7.2 7.1 Air Conditioners Not Used ........................... 2.1 1.1 0.2 0.9 15.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 9.6 3.2

  5. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.6 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 82.9 58.7 6.5 12.4 5.3 4.9 Air Conditioners Not Used ............ 2.1 1.1 Q 0.6 Q 21.8 Households Using Electric Air-Conditioning 1

  6. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 36.8 13.6 18.9 13.6 4.3 Air Conditioners Not Used ........................... 2.1 1.2 0.2 0.4 0.3 21.4 Households Using Electric Air-Conditioning 2 ........................................ 80.8 35.6 13.4

  7. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...................... 82.9 14.5 11.3 3.2 3.3 Air Conditioners Not Used ........................... 2.1 0.3 0.3 Q 28.3 Households Using Electric Air-Conditioning 1

  8. char_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.0 1.2 1.2 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Household Size 1 Person ....................................... 28.2 2.5 4.5 5.1 4.0 3.7 8.3 7.5 2 Persons

  9. Household Vehicles Energy Consumption 1991

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

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

  10. homeoffice_household2001.pdf

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

    3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.4 1.9 1.2 1.0 0.6 1.9 0.9 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 47.6 3.0 Households Using Office Equipment .......................... 96.2 13.2 19.8 25.5 37.7

  11. char_household2001.pdf

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

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

  12. spaceheat_household2001.pdf

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

    5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Owner- Occupied Units Type of...

  13. 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 ...

  14. 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...

  15. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.1 1.2 1.1 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 13.6 16.0 14.7 10.4 10.5 17.6 4.7 Air Conditioners Not Used ............ 2.1 Q 0.3 0.5 0.3 0.4 0.5 27.2 Households Using Electric Air-Conditioning 2

  16. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 59.5 58.7 6.5 12.4 5.3 5.2 Air Conditioners Not Used ............ 1.2 1.1 Q 0.6 Q 23.3 Households Using

  17. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.8 0.5 1.4 1.2 1.6 Households With Electric Air-Conditioning Equipment ........ 23.4 58.7 6.5 12.4 5.3 6.1 Air Conditioners Not Used ............ 0.9 1.1 Q 0.6 Q 23.0 Households Using Electric Air-Conditioning

  18. char_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    2001 Household Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Household Size 1 Person ...................................................... 28.2 2.2 2.4 1.8 1.7 7.3 2 Persons .................................................... 35.1 2.2 4.0 2.4 2.0 6.9 3 Persons

  19. homeoffice_household2001.pdf

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

    0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0

  20. homeoffice_household2001.pdf

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

    1a. Home Office Equipment by South Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ......................................... 96.2 34.6 18.4 6.0 10.1 1.2 Personal Computers 1

  1. homeoffice_household2001.pdf

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

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

  2. homeoffice_household2001.pdf

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

    9a. Home Office Equipment by Northeast Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total .............................................................. 107.0 20.3 14.8 5.4 NE Households Using Office Equipment ......................................... 96.2 17.9 12.8 5.0 1.3 Personal Computers 1 ................................. 60.0 10.9

  3. 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 ...

  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. 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 ...

  6. 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 ...

  7. 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 ...

  8. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 2.1 1.0 0.9 1.5 1.0 Total Households With Air-Conditioning ........................... 82.9 5.4 20.9 20.2 14.2 22.1 8.1 Air Conditioners Not Used ............ 2.1 Q 0.4 0.3 0.8 0.4 23.2

  9. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditioning Equipment ...................... 82.9 4.9 6.0 7.4 6.2 2.4 Air Conditioners Not Used ........................... 2.1 0.1 0.8 Q 0.1 23.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 4.7 5.2 7.4 6.1 2.6 Type of Electric Air-Conditioning Used Central

  10. homeoffice_household2001.pdf

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

    a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.2 1.1 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.9 Households Using Office Equipment .......................... 96.2 8.4 26.2 21.1 19.0

  11. homeoffice_household2001.pdf

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

    2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.4 1.1 1.1 1.2 1.2 1.0 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Households Using Office Equipment .......................... 96.2 14.9 16.7 17.0 12.2 13.0 22.4 4.4 Personal Computers 2

  12. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1

  13. 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 ...

  14. 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

  15. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    0a. Appliances by Midwest Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.5 Total .............................................................. 107.0 24.5 17.1 7.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 23.8 16.6 7.2 NE 1

  16. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    1a. Appliances by South Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.4 1.5 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 36.2 19.4 6.4 10.3 1.5 1

  17. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.6 1.9 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 69.1 9.4 16.7 6.6 4.3 1

  18. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.3 0.4 2.1 3.1 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Kitchen Appliances Cooking Appliances Oven ...........................................

  19. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    6a. Appliances by Type of Rented Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Kitchen Appliances Cooking Appliances Oven ........................................... 33.4 10.1 7.3 14.9 1.1

  20. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

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

  1. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1

  2. homeoffice_household2001.pdf

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

    2001 Home Office Equipment RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Households Using Office Equipment ......................................... 96.2 6.2 11.4 6.7 5.9 1.7 Personal Computers 1 ................................. 60.0 3.4 7.9 4.1 3.8 4.4 Number of Desktop PCs 1

  3. spaceheat_household2001.pdf

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

    0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No

  4. spaceheat_household2001.pdf

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

    1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home

  5. spaceheat_household2001.pdf

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

    2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment

  6. spaceheat_household2001.pdf

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

    6a. Space Heating by Type of Rented Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Heat Home ..................................... 33.7 10.4 7.4 14.8 1.1 6.9 Do Not Heat Home

  7. spaceheat_household2001.pdf

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

    8a. Space Heating by Urban/Rural Location, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.6 0.9 1.3 1.3 1.2 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.3 Heat Home .................................................... 106.0 49.1 18.0 21.2 17.8 4.3 Do Not Heat Home ....................................... 1.0 0.7 0.1 0.1 0.1 25.8 No Heating

  8. spaceheat_household2001.pdf

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

    9a. Space Heating by Northeast Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 20.3 14.8 5.4 NE Heat Home .................................................... 106.0 20.1 14.7 5.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.9 No

  9. 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.

  10. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    a. Appliances by Climate Zone, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.1 Total .................................................. 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Kitchen Appliances Cooking Appliances Oven

  11. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    2a. Appliances by Year of Construction, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.5 1.2 1.1 1.2 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 1

  12. spaceheat_household2001.pdf

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

    a. Space Heating by Climate Zone, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.5 1.6 1.1 1.1 1.1 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 8.2 Heat Home ..................................... 106.0 9.2 28.6 23.9 20.7 23.6 8.2 Do Not

  13. spaceheat_household2001.pdf

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

    2a. Space Heating by Year of Construction, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.5 1.1 1.1 1.1 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Heat Home ..................................... 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Do Not Heat Home ........................

  14. spaceheat_household2001.pdf

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

    4a. Space Heating by Type of Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.7 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.4 Heat Home ..................................... 106.0 73.4 9.4 16.4 6.8 4.5 Do Not Heat Home ........................ 1.0 0.3 Q 0.6 Q 19.0 No

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

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

    Department of Energy 7: November 16, 2009 Median Age of Cars and Trucks Rising in 2008 Fact #597: November 16, 2009 Median Age of Cars and Trucks Rising in 2008 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 purchases of vehicles. The median age of cars was at an all-time high in 2008, while the median age of trucks reached its highest point

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

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

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

  17. 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.

  18. 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...

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

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

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

  20. Microsoft Word - Household Energy Use CA

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

    0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household  California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site

  1. Microsoft Word - Household Energy Use CA

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

    0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household  California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site

  2. 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.

  3. 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.<br /> Credit: Whirlpool Embraco's high efficiency, oil-free linear compressor. Credit: Whirlpool ORNL's Pradeep Bansal examines an Embraco linear compressor, which will be used in a Whirlpool-ORNL project aimed at building a more energy-efficient refrigerator. ORNL's Pradeep Bansal examines an Embraco linear compressor, which will be used in a Whirlpool-ORNL

  4. 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

  5. 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.

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

    Gasoline and Diesel Fuel Update (EIA)

    E (2001) - Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Electricity Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information

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

    Gasoline and Diesel Fuel Update (EIA)

    G (2001) -- Household Fuel Oil or Kerosene Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Fuel Oil or Kerosene Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already

  8. Delivering Energy Efficiency to Middle Income Single Family Households

    SciTech Connect (OSTI)

    none,

    2011-12-01

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

  9. 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)

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

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

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

  11. 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

  12. 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.

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

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

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

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

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

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

  15. 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...

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

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

    F (2001) -- Household Natural Gas Usage Form OMB No. 1905-0092, Expiring February 29, 2004 ... This report is required by law. The timely submission of Form EIA-457F by those required ...

  17. 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.

  18. EERE Success Story—Kingston Creek Hydro Project Powers 100 Households

    Broader source: Energy.gov [DOE]

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

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

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

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

  20. 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.

  1. 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.

  2. Household heating bills expected to be lower this winter

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

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

  3. A Glance at Chinas Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-22

    Known for its scale, China is the most populous country with the worlds 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. Kingston Creek Hydro Project Powers 100 Households | Department of Energy

    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 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 on private land that takes advantage of an

  5. Shared Solar Projects Powering Households Throughout America | Department

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

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

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

    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 ...

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

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

    More Vehicles | Department of Energy 7: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles Household vehicle ownership has changed over the last six decades. In 1960, over twenty percent of households did not own a vehicle, but by 2010, that number fell to less than 10%. The number of households with three or more vehicles grew from 2% in 1960 to nearly 20% in 2010. Before 1990,

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

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

    Department of Energy 9: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles When a household has more than one vehicle, the secondary vehicles travel fewer miles than the primary vehicle. In a two-vehicle household, the second vehicle travels less than half of the miles that the primary vehicle travels in a day. In a six-vehicle household, the sixth vehicle travels fewer than five miles a day. Daily Vehicle

  9. 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.

  10. 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.

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

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

    Energy 4: March 15, 2010 Average Age of Household Vehicles Fact #614: March 15, 2010 Average Age of Household Vehicles The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first reported in the 1995 survey, have the youngest average age. Average Vehicle Age by Vehicle Type Graph showing the average vehicle age by type (car, van, pickup, SUV, all household

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

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

    Energy Multifamily and Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014. PDF icon Call Slides and Discussion Summary More Documents & Publications EcoHouse Program Overview Strengthening Relationships Between Energy Programs and Housing Programs Targeted Marketing and Program Design for Low- and Moderate-Income Households

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

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

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

  14. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  15. 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.

  16. Heating oil and propane households bills to be lower this winter despite recent cold spell

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

    Heating oil and propane households bills to be lower this winter despite recent cold spell Despite the recent cold weather, households that use heating oil or propane as their main space heating fuel are still expected to have lower heating bills compared with last winter. In its new monthly forecast, the U.S. Energy Information Administration said the average household that uses heating oil will spend $1,780 this winter that's about $570 less than last winter. Those savings reflect lower crude

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

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

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

  18. 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.

  19. 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 peoplebe they roommates, spouses, children, or maybe even...

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

    Office of Environmental Management (EM)

    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

  1. 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.

  2. "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

  3. 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.

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

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

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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

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

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration Drivers of U.S. Household Energy Consumption, 1980-2009 Release date: February 3, 2015 Introduction In 2012, the residential sector accounted for 21% of total primary energy consumption and about 20% of carbon dioxide emissions in the United States (computed from EIA 2013). Because of the impacts of residential sector energy use on the environment and the economy, this study was undertaken to help provide a better understanding of the factors affecting energy

  13. 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.

  14. 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.

  15. Household magnets

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

    Now which is stronger, gravity or magnetism? What is going on? How do flexible refrigerator magnets work? Get 2 of these magnets, they are often the size of a business card....

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

  20. Table HC6.7 Air-Conditioning Usage Indicators by Number of Household Members, 2005

    Gasoline and Diesel Fuel Update (EIA)

    7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total........................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Cooling Equipment.......................... 17.8 5.4 5.3 2.7 2.5 2.0 Have Cooling Equipment...................................... 93.3 24.6 29.6 15.7 13.4 10.0 Use Cooling Equipment....................................... 91.4 24.0 29.1 15.5 13.2 9.7 Have Equipment But Do Not Use it......................

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

    Gasoline and Diesel Fuel Update (EIA)

    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

  2. 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.

  3. 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.

  4. 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.

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

    SciTech Connect (OSTI)

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

    2008-01-25

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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

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

    SciTech Connect (OSTI)

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

    1987-08-01

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

  14. 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.

  15. 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.

  16. 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).

  17. 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.

  18. 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.

  19. 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.

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

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

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

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

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

    Family & Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households March 13, 2014 Agenda  Call Logistics and Introductions  Featured Participants  Becca Harmon Murphy (Indianapolis Neighborhood Housing Partnership)  Discussion:  What strategies or approaches has your program used to build interest in your loan programs for moderate- and low-income households? What has worked well, and why do you think it was effective?  What

  2. 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.

  3. " 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"

  4. " 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"

  5. " 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"

  6. " 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"

  7. " 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"

  8. 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.

  9. 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.

  10. 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.

  11. 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...

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

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

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

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

    SciTech Connect (OSTI)

    James, T. ); Loftis, J. )

    1990-07-01

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

  14. b2.pdf

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

    Median

  15. Try This: Household Magnets

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

    Now which is stronger, gravity or magnetism? What is going on? How do flexible refrigerator magnets work? Get two of these magnets, they are often the size of a business card....

  16. Next Generation Household Refrigerator

    Broader source: Energy.gov [DOE]

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

  17. 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 ...

  18. ,"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

  19. ,"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

  20. ,"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

  1. ,"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"

  2. ,"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

  3. ,"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"

  4. ,"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"

  5. ,"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"

  6. Better Buildings Neighborhood Program Low/Moderate Income Peer Exchange Call: Targeted Marketing and Program Design for Low and Moderate Income Households Call Slides and Discussion Summary, October 11, 2011

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

    0, 2011 Better Buildings Neighborhood Program Low/Moderate Income Peer Exchange Call: Targeted Marketing and Program Design for Low and Moderate Income Households Call Slides and Discussion Summary Participating Grant Programs * Austin, TX * Bainbridge Is., WA * Carrboro, NC * Chicago, IL * Connecticut * Phoenix, AZ * Portland, OR * NYSERDA (Long Island, NY) * Michigan * New Hampshire * Indianapolis, IN * San Diego, CA * San Jose, CA * Seattle, WA 8/17/2014 2 Agenda * Call Logistics and

  7. 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...

  8. 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...

  9. 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)...

  10. appl_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.2 1.1 1.4 1.3 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 6.9 11.4 6.7 6.1 1.6 1 .............................................................. 95.2 6.2 10.7 6.3 6.0 2.1 2 or More

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. Household Vehicles Energy Consumption 1991

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

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

  16. Household Vehicles Energy Consumption 1994

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

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

  17. 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...

  18. spaceheat_household2001.pdf

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

    2001 Space Heating Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.5 1.1 1.0 1.2 1.6 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Heat Home .................................................... 106.0 7.1 12.0 7.7 6.2 NE Do Not Heat Home ....................................... 1.0 Q 0.3 Q 0.1 20.7 No Heating Equipment ................................ 0.5 Q 0.1 Q Q 41.3

  19. 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 ...

  20. 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 ...

  1. PowerPoint Presentation

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

    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 ...

  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. 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...

  5. 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.

  6. 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...

  7. 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...

  8. 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,...

  9. 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...

  10. 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....

  11. 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...

  12. 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.

  13. 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.

  14. 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. ...

  15. DOE_OR_21548_590_R_0.pdf

    Office of Legacy Management (LM)

    Figure 1-1 is unavailable

  16. DOE_OR_21548_667_R_0.pdf

    Office of Legacy Management (LM)

    Pages 44 and 45 are unavailable

  17. 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...

  18. 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...

  19. 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...

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

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

    More Documents & Publications EcoHouse Program Overview Strengthening Relationships Between Energy Programs and Housing Programs Targeted Marketing and Program Design for Low- and ...

  1. 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.

  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. 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...

  4. 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...

  5. 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.

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

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

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

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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.

  13. 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, ...

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

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

    The Kingston Creek Project-benefitting the Young Brothers Ranch-is a 175-kilowatt hydro generation plant on private land that takes advantage of an existing stream and power line. ...

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

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

    ... Thermostats" "Reduces Temperature During Day" "Yes",18.6,1.9,3.3,4,3.1,6.2,1.2,3.2 "No",14.5,2.3,3.1,2.5,2.4,4.2,1.3,3.5 "Reduces Temperature at Night" ...

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

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

    ...ff",43.6,6.3,11.7,9.6,6.5,9.5,4.3,11.9 "Manually Put into Sleep Mode",19.4,1.9,3.6,4.4,2.9,6.6,1.2,3.7 "CPU Goes to Sleep When PC is Left On" "Yes",9.1,1,1.8,1.7,1.2,3.3,0.7,1.8 ...

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

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

    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 ...

  18. 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)

  19. 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.

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

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

    Sources: U.S. Department of Transportation, Federal Highway Administration, 1990 Nationwide Personal Transportation Survey: Summary of Travel Trends, FHWA-PL-92-027, Washington, ...

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

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

    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 ...

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

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

    1980-2009 February 2015 Independent Statistics & ... DC 20585 U.S. Energy Information Administration | Drivers ... 9 Total electricity ......

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

    Gasoline and Diesel Fuel Update (EIA)

    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.

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

    Gasoline and Diesel Fuel Update (EIA)

    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

  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. 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.

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  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. 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...

  13. Port Graham Biomass Community Heat Project

    Energy Savers [EERE]

    Sink, Chugachmiut Recipient Principal Investigator For Port Graham Village Council US Department of Energy Office of Indian Energy & Economic Development-May 5, 2015 Port Graham population of 177 (2010 Census) Southern tip of Kenai Peninsula, about 28-miles off the road system from Homer, Alaska, accessible by air or water only Unemployment rate 22%; 44.6% out of labor force; Median household income $18,942 Heat 5-community buildings with cord wood biomass heating system Displace

  14. 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.

  15. 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.

  16. 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.

  17. City-Level Energy Decision Making: Data Use in Energy Planning, Implementation, and Evaluation in U.S. Cities

    Broader source: Energy.gov [DOE]

    The report analyzes and presents information learned from a sample of 20 cities across the United States, from New York 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. The report compares climate, sustainability, and energy plans to better understand where cities are taking energy-related actions and how they are measuring impacts. Some common energy-related goals focus on reducing city-wide carbon emissions, improving energy efficiency across sectors, increasing renewable energy, and increasing biking and walking.

  18. 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...

  19. 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...

  20. 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.

  1. 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...

  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. 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...

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

    Gasoline and Diesel Fuel Update (EIA)

    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.

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

    Gasoline and Diesel Fuel Update (EIA)

    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,

  6. 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,...

  7. 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...

  8. EERE Success Story-Competition Provides Students with Real-World...

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

    The competition's 30 national sponsors also provide expert guidance and mentoring, as well as access to compo-nents and systems that might otherwise be unavailable or too ...

  9. 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...

  10. 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,...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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....

  16. 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;...

  17. 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...

  18. 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...

  19. 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....

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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.

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  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 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...

  18. 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...

  19. 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...

  20. EIA Report 9/16/08 - Hurricane Impacts on U.S. Oil & Natural...

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

    ... However, since compression at the Henry Hub complex remains unavailable, nominations with ... & Energy Reliability STEO Hurricane Analysis (pdf) Hurricane Ikes Path as of 0700 ...

  1. EIA Report 9/18/08 - Hurricane Impacts on U.S. Oil & Natural...

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

    ... Compression at the Henry Hub complex remains unavailable at this time and Sabine advises ... & Energy Reliability STEO Hurricane Analysis (pdf) Hurricane Ikes Path as of 0700 ...

  2. EIA Report 9/17/08 - Hurricane Impacts on U.S. Oil & Natural...

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

    ... Compression at the Henry Hub complex remains unavailable at this time and Sabine advises ... & Energy Reliability STEO Hurricane Analysis (pdf) Hurricane Ikes Path as of 0700 ...

  3. Environmental Assessment of Plug-In Hybrid Electric Vehicles...

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

    ... Power Plant Retirements Slower Normal Faster New Generation Technologies Unavailable: Coal with CCS New Nuclear New Biomass Available: IGCC Coal with CCS New Nuclear New Biomass ...

  4. Energy Department Authorizes Alaska LNG Project, LLC to Export...

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

    North Slope gas has been a stranded resource unavailable to commercial markets. The project proposed by Alaska LNG includes a pipeline intended to make North Slope gas accessible ...

  5. Vendor Information | Y-12 National Security Complex

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

    Database. This database provides buyers an opportunity to search for potential suppliers for upcoming requirements. The Vendor Information Database is currently unavailable....

  6. 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.

  7. 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...

  8. US SoAtl GA Site Consumption

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

    household (2,067) in Georgia are similar to the U.S. household averages. * Per household electricity consumption in Georgia is among the highest in the country, but similar to...

  9. 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...

  10. 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%...

  11. 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:...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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 ...

  19. US SoAtl FL Site Consumption

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

    Half of energy consumed by Florida households is for appliances, electronics, and lighting... conditioning Appliances, electronics, lighting Household Energy Use in Florida A closer ...

  20. 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...

  1. 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...

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

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

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

  3. 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...

  4. " Million U.S. Housing Units" ,,"2005...

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

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

  5. " Million U.S. Housing Units,...

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

    ,"Total U.S.1 (millions)",,,..."Below Poverty Line2" "Structural and Geographic ... the number of households below the poverty line, the annual household income and ...

  6. 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...

  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. spaceheat_percent2001.pdf

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

    Space Heating Tables (Percent of U.S. Households; 24 pages, 133 kb) Contents Pages HC3-1b. Space Heating by Climate Zone, Percent of U.S. Households, 2001 2 HC3-2b. Space Heating by Year of Construction, Percent of U.S. Households, 2001 2 HC3-3b. Space Heating by Household Income, Percent of U.S. Households, 2001 2 HC3-4b. Space Heating by Type of Housing Unit, Percent of U.S. Households, 2001 2 HC3-5b. Space Heating by Type of Owner-Occupied Housing Unit, Percent of U.S. Households, 2001 2

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

  13. 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.

  14. 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

  15. Word Pro - Untitled1

    Gasoline and Diesel Fuel Update (EIA)

    Household Energy Consumption Household Energy Consumpton by Census Region, Selected Years, 1978-2009¹ Household Energy Consumption by Source, 2009 Energy Consumption per Household, Selected Years, 1978-2009¹ Energy Consumption per Household, by Census Region, 2009 50 U.S. Energy Information Administration / Annual Energy Review 2011 1 For years not shown, there are no data available. 2 Liquefied petroleum gases. Notes: * Data include natural gas, electricity, distillate fuel oil, kerosene,

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

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

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

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

  4. 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

  5. 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...

  6. 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...

  7. Fuel Mix and Emissions Disclosure

    Broader source: Energy.gov [DOE]

    Information must be provided to customers and to the Virginia State Corporation Commission (SCC) at least once annually. If any portion of this information is unavailable, the electricity provide...

  8. 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:...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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....

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. Web Page Error 404.1 Page Cannot be Found

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

    ... About ORISE Safety Careers Working with 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 ...

  10. Slide 1

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

    Category C: Make funding unavailable this year, pushing it to future years (e.g., NNSA Pension funds) * Program Office: Program Offices, to track and manage what work is to be done...

  11. 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...

  12. 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.

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Gasoline and Diesel Fuel Update (EIA)

    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

  17. 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

  18. 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

  19. Notices

    National Nuclear Security Administration (NNSA)

    8557 Federal Register / Vol. 69, No. 68 / Thursday, April 8, 2004 / Notices We must acknowledge and confirm these periods of unavailability before granting you an extension. To request this extension or to confirm our acknowledgement of any system unavailability, you may contact either (1) the persons listed elsewhere in this notice under FOR FURTHER INFORMATION CONTACT (see VII. Agency Contacts) or (2) the e-GRANTS help desk at 1-888- 336-8930. You may access the electronic grant application

  20. 1997 Housing Characteristics Tables Home Office Equipment Tables

    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.

  1. 1997 Housing Characteristics Tables Housing Unit Tables

    Gasoline and Diesel Fuel Update (EIA)

    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,

  2. 1997 Housing Characteristics Tables Housing Unit Tables

    Gasoline and Diesel Fuel Update (EIA)

    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

  3. R93HC.PDF

    Gasoline and Diesel Fuel Update (EIA)

    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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  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. S:\VM3\RX97\TBL_LIST.WPD

    Gasoline and Diesel Fuel Update (EIA)

    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.

  18. 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...

  19. 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...

  20. " 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. Energy Consumption and Renewable Energy Development Potential on Indian Lands

    Reports and Publications (EIA)

    2000-01-01

    Includes information on the electricity use and needs of Indian households and tribes, the comparative electricity rates that Indian households are paying, and the potential for renewable resources development of Indian lands.

  7. 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 ...

  8. 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

  9. 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...

  10. 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...

  11. " Million Housing Units, Final...

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

    "Income Relative to Poverty Line2" "Below 100 Percent",16.9,3.7,2.9,0... the number of households below the poverty line, the annual household income and ...

  12. TableHC7.1.xls

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

    ... Housing Units (millions) 2005 Household Income 40,000 to 59,999 Below Poverty Line ... Housing Units (millions) 2005 Household Income 40,000 to 59,999 Below Poverty Line ...

  13. TableHC2.1.xls

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

    ... Housing Units (millions) 2005 Household Income 40,000 to 59,999 Below Poverty Line ... Housing Units (millions) 2005 Household Income 40,000 to 59,999 Below Poverty Line ...

  14. " Million Housing Units, Final...

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

    ,"Total U.S.1 (millions)",,,..."Below Poverty Line2" ,,"Less than 20,000","20,000 to ... the number of households below the poverty line, the annual household income and ...

  15. " Million Housing Units, Final...

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

    "Income Relative to Poverty Line2" "Below 100 Percent",16.9,6.7,10.1,... the number of households below the poverty line, the annual household income and ...

  16. " Million Housing Units, Final...

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

    "Income Relative to Poverty Line2" "Below 100 Percent",16.9,3.1,0.9,0... the number of households below the poverty line, the annual household income and ...

  17. " Million Housing Units, Final...

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

    "Income Relative to Poverty Line2" "Below 100 Percent",16.9,2.9,3.7,7... the number of households below the poverty line, the annual household income and ...

  18. " Million Housing Units, Final...

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

    "Income Relative to Poverty Line3" "Below 100 Percent",16.9,5.4,5.6,2... the number of households below the poverty line, the annual household income and ...

  19. " Million Housing Units, Final...

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

    "Income Relative to Poverty Line2" "Below 100 Percent",16.9,7.2,3.4,0... the number of households below the poverty line, the annual household income and ...

  20. " Million Housing Units, Final"

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

    ,"Total U.S.1 (millions)",,,..."Below Poverty Line2" ,,"Less than 20,000","20,000 to ... the number of households below the poverty line, the annual household income and ...

  1. 1997 Housing Characteristics Tables Housing Unit Tables

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

    ... RSE Column Factor: Total 1997 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 1997 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  2. " Million Housing Units, Final...

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

    "Income Relative to Poverty Line2" "Below 100 Percent",16.9,6.9,0.9,2... the number of households below the poverty line, the annual household income and ...

  3. " Million Housing Units, Final"

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

    "Income Relative to Poverty Line2" "Below 100 Percent",16.9,5,3.9,2.9... the number of households below the poverty line, the annual household income and ...

  4. " Million Housing Units, Final...

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

    "Income Relative to Poverty Line2" "Below 100 Percent",16.9,2.4,1,2.1... the number of households below the poverty line, the annual household income and ...

  5. Residential Energy Consumption Survey (RECS) - Analysis & Projections...

    Gasoline and Diesel Fuel Update (EIA)

    ... Overall, 18 percent of households below the poverty line do not have any air conditioning equipment at all. About a third of households below the poverty line use room air ...

  6. win0102

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

    gas-heated homes, 17 percent for oil-heated households, 23 percent for residences using propane as a main heating fuel, and perhaps 3 to 4 percent for households heating with...

  7. U.S. monthly oil production tops 8 million barrels per day for...

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

    of U.S. households heat with natural gas, while almost 40 percent of households depend on electricity as their primary heating source. Heating oil and propane each heat about 5% of...

  8. Categories of Data

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

    Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > 1995 Detailed Tables > Data Categories Column Categories | Row Categories |...

  9. Overview of Commercial Buildings, 2003 - Full Report

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

    Introduction Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > Overview of Commercial Buildings Print Report: PDF Overview of...

  10. Crafty Gifts for the Energy Conscious

    Broader source: Energy.gov [DOE]

    Check out these homemade gifts that can help your loved ones be energy efficient in their households.

  11. Word Pro - Untitled1

    Gasoline and Diesel Fuel Update (EIA)

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

  12. Untitled Document

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

    1991 Residential Transportation Energy Consumption Survey 1991 Residential Transportation Energy Consumption Survey Executive Summary This report, Household Vehicles Energy...

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

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

    Households | Department of Energy Targeted Marketing and Program Design for Low- and Moderate-Income Households Targeted Marketing and Program Design for Low- and Moderate-Income Households Better Buildings Neighborhood Program Low- / Moderate-Income Peer Exchange Call: Targeted Marketing and Program Design for Low- and Moderate-Income Households, Call Slides and Discussion Summary, October 11, 2011. PDF icon Call Slides and Discussion Summary More Documents & Publications Loan Programs

  14. Service Report Energy Information Administration Office of Energy...

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

    (Millions of Households) ... 43 Table 12. Insulation and Air Infiltration Protection By Year House Was Built and Census Region...

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

    Broader source: Energy.gov [DOE]

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

  16. file://C:\Documents%20and%20Settings\VM3\My%20Documents\hc6-3a_

    Gasoline and Diesel Fuel Update (EIA)

    3a. Usage Indicators by Household Income, Million U.S. Households, 2001 ___________________________________________________________________________________________________________ | | | | | | | 2001 Household Income | | Eli- | | | | | gible | | |___________________________________| | for | | | | | | | | Fed- | | | Less | $15,000| $30,000| $50,000| Below | eral | | | than | to | to | or | Poverty| Assist-| Usage Indicators | Total | $14,999| $29,999| $49,999| More | Line | ance 1 |

  17. Time-Dependent Reliability Analysis

    Energy Science and Technology Software Center (OSTI)

    1999-10-27

    FRANTIC-3 was developed to evaluate system unreliability using time-dependent techniques. The code provides two major options: to evaluate standby system unavailability or, in addition to the unavailability to calculate the total system failure probability by including both the unavailability of the system on demand as well as the probability that it will operate for an arbitrary time period following the demand. The FRANTIC-3 time dependent reliability models provide a large selection of repair and testingmore » policies applicable to standby or continously operating systems consisting of periodically tested, monitored, and non-repairable (non-testable) components. Time-dependent and test frequency dependent failures, as well as demand stress related failure, test-caused degradation and wear-out, test associated human errors, test deficiencies, test override, unscheduled and scheduled maintenance, component renewal and replacement policies, and test strategies can be prescribed. The conditional system unavailabilities associated with the downtimes of the user specified failed component are also evaluated. Optionally, the code can perform a sensitivity study for system unavailability or total failure probability to the failure characteristics of the standby components.« less

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

    Gasoline and Diesel Fuel Update (EIA)

    Percent of U.S. Households; 24 pages, 81 kb) Contents Pages HC4-1b. Air Conditioning by Climate Zone, Percent of U.S. Households, 1997 2 HC4-2b. Air Conditioning by Year of Construction, Percent of U.S. Households, 1997 2 HC4-3b. Air Conditioning by Household Income, Percent of U.S. Households, 1997 2 HC4-4b. Air Conditioning by Type of Housing Unit, Percent of U.S. Households, 1997 2 HC4-5b. Air Conditioning by Type of Owner-Occupied Housing Unit, Percent of U.S. Households, 1997 2 HC4-6b. Air

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

    Gasoline and Diesel Fuel Update (EIA)

    Appliances Tables (Percent of U.S. Households; 48 pages, 144 kb) Contents Pages HC5-1b. Appliances by Climate Zone, Percent of U.S. Households, 1997 4 HC5-2b. Appliances by Year of Construction, Percent of U.S. Households, 1997 4 HC5-3b. Appliances by Household Income, Percent of U.S. Households, 1997 4 HC5-4b. Appliances by Type of Housing Unit, Percent of U.S. Households, 1997 4 HC5-5b. Appliances by Type of Owner-Occupied Housing Unit, Percent of U.S. Households, 1997 4 HC5-6b. Appliances by

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

    Gasoline and Diesel Fuel Update (EIA)

    Percent of U.S. Households; 48 pages, 139 kb) Contents Pages HC6-1b. Usage Indicators by Climate Zone, Percent of U.S. Households, 1997 4 HC6-2b. Usage Indicators by Year of Construction, Percent of U.S. Households, 1997 4 HC6-3b. Usage Indicators by Household Income, Percent of U.S. Households, 1997 4 HC6-4b. Usage Indicators by Type of Housing Unit, Percent of U.S. Households, 1997 4 HC6-5b. Usage Indicators by Type of Owner-Occupied Housing Unit, Percent of U.S. Households, 1997 4 HC6-6b.

  1. 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 on 3/16/2016 8:00am-17:00pm PDT. 2016-03-07 16:18:27 Zhengji Zhao <zzhao_at_lbl.gov> A shorter purging period will be implemented on Edison starting 4/1/2016 2016-03-03 14:39:29 Zhengji Zhao <zzhao_at_lbl.gov> Edison will be unavailable next Wednesday, 2/3/2016 8:00-17:00 PST 2016-01-27 13:47:38 Zhengji Zhao <zzhao_at_lbl.gov> Edison will be unavailable this Thursday, 1/7/2016

  2. Released: June 2006

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

    . Summary Table: Totals and Medians of Floorspace, Number of Workers, and Hours of Operation for Non-Mall Buildings, 2003" ,"Number of 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*

  3. PDSF Selected Announcements

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

    February 2011 pdsfdtn1 maintenance 3/2/11, 0900-1700 PT February 28, 2011 by Eric Hjort During the maintenance pdsfdtn1 will be down and unavailable. Read the full post /eliza5 maintenance 2/23/11, 9am-4pm February 17, 2011 by Eric Hjort The Eliza5 filesystem will be unavailable on Wed, Feb 23, 2011 from 9AM - 4PM for maintenance work. Read the full post /eliza4 emergency maintenance 2/7/11 10am-12noon February 4, 2011 by Eric Hjort There will be an emergency downtime for eliza4 on Monday Feb 7,

  4. Genepool Quarterly Maintenance

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

    Genepool Quarterly Maintenance Genepool Quarterly Maintenance November 7, 2012 by Kirsten Fagnan The Genepool cluster will be offline for maintenance next Tuesday, November 13th from 7:00 am to 7:00 pm (PST). During this time staff will upgrade the Genepool compute nodes to Debian 6. Also, the firmware for /projectb and /house will be updated. /projectb will be unavailable from 7:00 am to 7:00 pm (PST) and /house will be unavailable from 8:00 am to 1:00 pm (PST). Any webservices or workflows

  5. Released: June 2010

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

    2 Relative Standard Errors for Table 10.22;" " Unit: Percents." ,,,,"Reasons that Made Coal Unswitchable" " "," ",,,,,,,,,,,,," " ,,"Total Amount of ","Total Amount of","Equipment is Not","Switching","Unavailable ",,"Long-Term","Unavailable",,"Combinations of " "NAICS"," ","Coal Consumed ","Unswitchable","Capable of

  6. Released: June 2010

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

    3 Relative Standard Errors for Table 10.23;" " Unit: Percents." ,,,,"Reasons that Made LPG Unswitchable" " "," ",,,,,,,,,,,,," " ,,"Total Amount of ","Total Amount of","Equipment is Not","Switching","Unavailable ",,"Long-Term","Unavailable",,"Combinations of " "NAICS"," ","LPG Consumed ","Unswitchable","Capable of

  7. Pollutant Exposures from Natural Gas Cooking Burners: A Simulation-Based Assessment for Southern California

    SciTech Connect (OSTI)

    Logue, Jennifer M.; Klepeis, Neil E.; Lobscheid, Agnes B.; Singer, Brett C.

    2014-06-01

    Residential natural gas cooking burners (NGCBs) can emit substantial quantities of pollutants and they are typically used without venting. The objective of this study is to quantify pollutant concentrations and occupant exposures resulting from NGCB use in California homes. A mass balance model was applied to estimate time-dependent pollutant concentrations throughout homes and the "exposure concentrations" experienced by individual occupants. The model was applied to estimate nitrogen dioxide (NO{sub 2}), carbon monoxide (CO), and formaldehyde (HCHO) concentrations for one week each in summer and winter for a representative sample of Southern California homes. The model simulated pollutant emissions from NGCBs, NO{sub 2} and CO entry from outdoors, dilution throughout the home, and removal by ventilation and deposition. Residence characteristics and outdoor concentrations of CO and NO{sub 2} were obtained from available databases. Ventilation rates, occupancy patterns, and burner use were inferred from household characteristics. Proximity to the burner(s) and the benefits of using venting range hoods were also explored. Replicate model executions using independently generated sets of stochastic variable values yielded estimated pollutant concentration distributions with geometric means varying less than 10%. The simulation model estimates that in homes using NGCBs without coincident use of venting range hoods, 62%, 9%, and 53% of occupants are routinely exposed to NO{sub 2}, CO, and HCHO levels that exceed acute health-based standards and guidelines. NGCB use increased the sample median of the highest simulated 1-hr indoor concentrations by 100, 3000, and 20 ppb for NO{sub 2}, CO, and HCHO, respectively. Reducing pollutant exposures from NGCBs should be a public health priority. Simulation results suggest that regular use of even moderately effective venting range hoods would dramatically reduce the percentage of homes in which concentrations exceed health-based standards.

  8. Indoor Air Quality and Ventilation in Residential Deep Energy Retrofits

    SciTech Connect (OSTI)

    Less, Brennan; Walker, Iain

    2014-06-01

    Because airtightening is a significant part of Deep Energy Retrofits (DERs), concerns about ventilation and Indoor Air Quality (IAQ) have emerged. To investigate this, ventilation and IAQ were assessed in 17 non-smoking California Deep Energy Retrofit homes. Inspections and surveys were used to assess household activities and ventilation systems. Pollutant sampling performed in 12 homes included six-day passive samples of nitrogen dioxide (NO2), formaldehyde and air exchange rate (AER); time-resolved data loggers were used to measure particle counts. Half of the homes provided continuous mechanical ventilation. Despite these homes being twice as airtight (3.0 and 7.6 ACH50, respectively), their median AER was indistinguishable from naturally vented homes (0.36 versus 0.37 hr--1). Numerous problems were found with ventilation systems; however, pollutant levels did not reach levels of concern in most homes. Ambient NO2 standards were exceeded in some gas cooking homes that used legacy ranges with standing pilots, and in Passive House-style homes without range hoods exhausted to outside. Cooking exhaust systems were installed and used inconsistently. The majority of homes reported using low-emitting materials, and formaldehyde levels were approximately half those in conventional new CA homes (19.7 versus 36 ?g/m3), with emissions rates nearly 40percent less (12.3 versus 20.6 ?g/m2/hr.). Presence of air filtration systems led to lower indoor particle number concentrations (PN>0.5: 8.80E+06 PN/m3 versus 2.99E+06; PN>2.5: 5.46E+0.5 PN/m3 versus 2.59E+05). The results indicate that DERs can provide adequate ventilation and IAQ, and that DERs should prioritize source control, particle filtration and well-designed local exhaust systems, while still providing adequate continuous ventilation.

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

    Gasoline and Diesel Fuel Update (EIA)

    3 1 October 2013 Short-Term Energy and Winter Fuels Outlook (STEO) Highlights  EIA projects average U.S. household expenditures for natural gas and propane will increase by 13% and 9%, respectively, this winter heating season (October 1 through March 31) compared with last winter. Projected U.S. household expenditures are 2% higher for electricity and 2% lower for heating oil this winter. Although EIA expects average expenditures for households that heat with natural gas will be significantly

  10. Word Pro - Untitled1

    Gasoline and Diesel Fuel Update (EIA)

    Household End Uses: Fuel Types, Appliances, and Electronics Share of Households With Selected Appliances, 1980 and 2009 Space Heating by Main Fuel, 2009 Share of Households With Selected Electronics, 1997 and 2009 Air-Conditioning Equipment, 1980 and 2009 54 U.S. Energy Information Administration / Annual Energy Review 2011 1 Natural gas and electric. 2 Liquefied petroleum gases. 3 Includes kerosene. 4 Coal, solar, other fuel, or no heating equipment. 5 Video Cassette Recorder. 6 Digital Video

  11. Marginal Energy Prices - RECS97 Update

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

    Marginal Energy Prices - RECS97 Update The original estimation of residential marginal energy prices at the individual household level (as reported in the Marginal Energy Prices Report, http://www.eren.doe.gov/buildings/codes_standards/applbrf/pdfs/marginal_ energy_price.pdf) was based on household energy billing data from EIA's 1993 RECS survey. When the 1997 RECS survey data became available, LBNL updated its estimation of residential marginal energy prices at the individual household level

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

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration (EIA) 3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing characteristics Consumption & expenditures Microdata Methodology Housing Characteristics Tables Topical Sections Entire Section All Detailed Tables PDF Tables: HC1 Household Characteristics, Million U.S. Households Presents data relating to location, type, ownership, age, size, construction, and householder demographic and income characteristics. PDF Tables: HC2 Space Heating, Million

  13. Microsoft Word - Highlights.docx

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

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

  14. 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions

    Gasoline and Diesel Fuel Update (EIA)

    D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Bottled Gas (LPG or Propane) Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S.

  15. 2005 Residential Energy Consumption Survey

    Gasoline and Diesel Fuel Update (EIA)

    D (2005) - Household Propane (Bottled Gas or LPG) Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Propane (Bottled Gas or LPG) Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call

  16. 2005 Residential Energy Consumption Survey

    Gasoline and Diesel Fuel Update (EIA)

    E (2005) - Household Electricity Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Electricity Usage Form Service Address: If the customer account number is not shown above, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and provide the requested information for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask

  17. 2005 Residential Energy Consumption Survey

    Gasoline and Diesel Fuel Update (EIA)

    G (2005) - Household Fuel Oil or Kerosene Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Fuel Oil or Kerosene Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free)

  18. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    3 2005 Average Household Expenditures, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Other expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other categories are calculated from the

  19. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book [EERE]

    4 2005 Average Household Expenditures as Percent of Annual Income, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Average Annual Expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other

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

    Buildings Energy Data Book [EERE]

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