National Library of Energy BETA

Sample records for household characteristics census

  1. Table HC1-10a. Housing Unit Characteristics by Midwest Census Region,

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

    0a. Housing Unit Characteristics by Midwest Census Region, Million U.S. Households, 2001 Housing Unit 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 1.8 Total .............................................................. 107.0 24.5 17.1 7.4 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- NF New England

  2. Table HC1-12a. Housing Unit Characteristics by West Census Region,

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

    2a. Housing Unit Characteristics by West Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- NF New England ............................................. 5.4 --

  3. Table HC1-11a. Housing Unit Characteristics by South Census Region,

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

    1a. Housing Unit Characteristics by South Census Region, Million U.S. Households, 2001 Housing Unit 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 1.4 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- -- NF New England

  4. Table HC1-9a. Housing Unit Characteristics by Northeast Census Region,

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

    9a. Housing Unit Characteristics by Northeast Census Region, Million U.S. Households, 2001 Housing Unit 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 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Census Region and Division Northeast ..................................................... 20.3 20.3 14.8 5.4 NF New England

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

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

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

  6. 1999 Commercial Buildings Characteristics--Census Region

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

    (202) 586-8800. Energy Information Administration Commercial Buildings Energy Consumption Survey Top Return to: "1999 CBECS-Commercial Buildings Characteristics" Specific questions...

  7. ac_household2001.pdf

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

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

  8. 1999 Commercial Building Characteristics--Detailed Tables--Census...

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

    Census Region > Detailed Tables-Census Region Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Census Region Table B3. Census Region, Number of Buildings and Floorspace...

  9. 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.

  10. "Table HC11.1 Housing Unit Characteristics by Northeast Census Region, 2005"

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

    Housing Unit Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units" ,,,"Census Division" ,,"Total Northeast" "Housing Unit Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Urban/Rural Location (as Self-Reported)" "City",47.1,6.9,4.7,2.2 "Town",19,6,4.2,1.9

  11. "Table HC11.11 Home Electronics Characteristics by Northeast Census Region, 2005"

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

    1 Home Electronics Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Home Electronics Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Personal Computers" "Do Not Use a Personal Computer ",35.5,6.9,5.3,1.6 "Use a

  12. "Table HC11.2 Living Space Characteristics by Northeast Census Region, 2005"

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

    2 Living Space Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Living Space Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,0.9,0.5,0.4

  13. "Table HC11.4 Space Heating Characteristics by Northeast Census Region, 2005"

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

    4 Space Heating Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Space Heating Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Do Not Have Space Heating Equipment",1.2,"Q","Q","Q" "Have Main

  14. "Table HC11.6 Air Conditioning Characteristics by Northeast Census Region, 2005"

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

    6 Air Conditioning Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Air Conditioning Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Do Not Have Cooling Equipment",17.8,4,2.4,1.7 "Have Coolling

  15. "Table HC11.8 Water Heating Characteristics by Northeast Census Region, 2005"

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

    8 Water Heating Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Water Heating Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Number of Water Heaters" "1.",106.3,19.6,14.4,5.2 "2 or

  16. "Table HC11.9 Home Appliances Characteristics by Northeast Census Region, 2005"

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

    1.9 Home Appliances Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Home Appliances Characteristics",,,"Middle Atlantic","New England" "Total U.S.",111.1,20.6,15.1,5.5 "Cooking Appliances" "Conventional Ovens" "Use an

  17. "Table HC12.1 Housing Unit Characteristics by Midwest Census Region, 2005"

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

    Housing Unit Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Housing Unit Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Urban/Rural Location (as Self-Reported)" "City",47.1,9.7,7.3,2.4

  18. "Table HC12.11 Home Electronics Characteristics by Midwest Census Region, 2005"

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

    1 Home Electronics Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Home Electronics Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Personal Computers" "Do Not Use a Personal Computer ",35.5,8.1,5.6,2.5 "Use a

  19. "Table HC12.2 Living Space Characteristics by Midwest Census Region, 2005"

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

    2 Living Space Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Living Space Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than

  20. "Table HC12.4 Space Heating Characteristics by Midwest Census Region, 2005"

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

    4 Space Heating Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Space Heating Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Do Not Have Space Heating Equipment",1.2,"Q","Q","N" "Have Main

  1. "Table HC12.6 Air Conditioning Characteristics by Midwest Census Region, 2005"

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

    6 Air Conditioning Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Air Conditioning Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Do Not Have Cooling Equipment",17.8,2.1,1.8,0.3 "Have Cooling

  2. "Table HC12.9 Home Appliances Characteristics by Midwest Census Region, 2005"

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

    2.9 Home Appliances Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Home Appliances Characteristics",,,"East North Central","West North Central" "Total U.S.",111.1,25.6,17.7,7.9 "Cooking Appliances" "Conventional Ovens" "Use an

  3. "Table HC13.1 Housing Unit Characteristics by South Census Region, 2005"

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

    Housing Unit Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Housing Unit Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Urban/Rural Location (as Self-Reported)"

  4. "Table HC13.11 Home Electronics Characteristics by South Census Region, 2005"

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

    1 Home Electronics Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Home Electronics Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Personal Computers" "Do Not Use a Personal Computer

  5. "Table HC13.2 Living Space Characteristics by South Census Region, 2005"

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

    2 Living Space Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Living Space Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than

  6. "Table HC13.4 Space Heating Characteristics by South Census Region, 2005"

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

    4 Space Heating Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Space Heating Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Do Not Have Space Heating

  7. "Table HC13.6 Air Conditioning Characteristics by South Census Region, 2005"

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

    6 Air Conditioning Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Air Conditioning Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Do Not Have Cooling Equipment",17.8,1.4,0.8,0.2,0.3 "Have

  8. "Table HC13.8 Water Heating Characteristics by South Census Region, 2005"

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

    8 Water Heating Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Water Heating Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Number of Water Heaters" "1.",106.3,39,21.1,6.6,11.3 "2

  9. "Table HC13.9 Home Appliances Characteristics by South Census Region, 2005"

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

    3.9 Home Appliances Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Home Appliances Characteristics",,,"South Atlantic","East South Central","West South Central" "Total U.S.",111.1,40.7,21.7,6.9,12.1 "Cooking Appliances" "Conventional Ovens" "Use

  10. "Table HC14.1 Housing Unit Characteristics by West Census Region, 2005"

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

    Housing Unit Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Housing Unit Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Urban/Rural Location (as Self-Reported)" "City",47.1,12.8,3.2,9.6 "Town",19,3,1.1,1.9

  11. "Table HC14.11 Home Electronics Characteristics by West Census Region, 2005"

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

    1 Home Electronics Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Home Electronics Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Personal Computers" "Do Not Use a Personal Computer ",35.5,6.4,2.2,4.2 "Use a Personal

  12. "Table HC14.2 Living Space Characteristics by West Census Region, 2005"

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

    2 Living Space Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Living Space Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,1,0.2,0.8 "500 to

  13. "Table HC14.4 Space Heating Characteristics by West Census Region, 2005"

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

    4 Space Heating Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Space Heating Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Do Not Have Space Heating Equipment",1.2,0.7,"Q",0.7 "Have Main Space Heating Equipment",109.8,23.4,7.5,16

  14. "Table HC14.6 Air Conditioning Characteristics by West Census Region, 2005"

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

    6 Air Conditioning Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Air Conditioning Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Do Not Have Cooling Equipment",17.8,10.3,3.1,7.3 "Have Cooling Equipment",93.3,13.9,4.5,9.4 "Use Cooling

  15. "Table HC14.8 Water Heating Characteristics by West Census Region, 2005"

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

    8 Water Heating Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Water Heating Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Number of Water Heaters" "1.",106.3,23.2,7.1,16.1 "2 or More",3.7,1,0.4,0.6 "Do Not Use Hot

  16. "Table HC14.9 Home Appliances Characteristics by West Census Region, 2005"

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

    4.9 Home Appliances Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Home Appliances Characteristics",,,"Mountain","Pacific" "Total U.S.",111.1,24.2,7.6,16.6 "Cooking Appliances" "Conventional Ovens" "Use an Oven",109.6,23.7,7.5,16.2

  17. 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

  18. ac_household2001.pdf

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

    0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1

  19. ac_household2001.pdf

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

    1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1

  20. 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 ...

  1. "Table HC12.8 Water Heating Characteristics by Midwest Census Region, 2005"

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

    8 Water Heating Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Water Heating Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Number of Water Heaters" "1.",106.3,24.5,17.1,7.4 "2 or More",3.7,0.9,0.5,0.4

  2. Table HC11.1 Housing Unit Characteristics by Northeast Census Region, 2005

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

    1.1 Housing Unit Characteristics by Northeast Census Region, 2005 Total......................................................................... 111.1 20.6 15.1 5.5 Urban/Rural Location (as Self-Reported) City....................................................................... 47.1 6.9 4.7 2.2 Town..................................................................... 19.0 6.0 4.2 1.9 Suburbs................................................................ 22.7 4.4 4.0 0.5

  3. "Table HC10.1 Housing Unit Characteristics by U.S. Census Region, 2005"

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

    0.1 Housing Unit Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Housing Unit Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Census Region and Division" "Northeast",20.6,20.6,"N","N","N" "New

  4. spaceheat_household2001.pdf

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

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

  5. spaceheat_household2001.pdf

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

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

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

    SciTech Connect (OSTI)

    Guerin, D.A.

    1988-01-01

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

  7. "Table HC10.11 Home Electronics Characteristics by U.S. Census Regions, 2005"

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

    1 Home Electronics Characteristics by U.S. Census Regions, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Home Electronics Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Personal Computers" "Do Not Use a Personal Computer ",35.5,6.9,8.1,14.2,6.4 "Use a Personal

  8. "Table HC10.2 Living Space Characteristics by U.S. Census Region, 2005"

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

    2 Living Space Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Living Space Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,0.9,0.5,0.9,1 "500 to 999",23.8,4.6,3.9,9,6.3

  9. "Table HC10.4 Space Heating Characteristics by U.S. Census Region, 2005"

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

    4 Space Heating Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Space Heating Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Do Not Have Space Heating Equipment",1.2,"Q","Q","Q",0.7 "Have Main Space Heating

  10. "Table HC10.6 Air Conditioning Characteristics by U.S. Census Region, 2005"

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

    6 Air Conditioning Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Air Conditioning Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Do Not Have Cooling Equipment",17.8,4,2.1,1.4,10.3 "Have Cooling Equipment",93.3,16.5,23.5,39.3,13.9 "Use Cooling

  11. "Table HC10.8 Water Heating Characteristics by U.S. Census Region, 2005"

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

    8 Water Heating Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Water Heating Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Number of Water Heaters" "1.",106.3,19.6,24.5,39,23.2 "2 or More",3.7,0.3,0.9,1.5,1 "Do Not Use Hot

  12. "Table HC10.9 Home Appliances Characteristics by U.S. Census Regions, 2005"

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

    0.9 Home Appliances Characteristics by U.S. Census Regions, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Home Appliances Characteristics",,"Northeast","Midwest","South","West" "Total U.S.",111.1,20.6,25.6,40.7,24.2 "Cooking Appliances" "Conventional Ovens" "Use an Oven",109.6,20.3,25.3,40.2,23.7

  13. ac_household2001.pdf

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

    Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...

  14. "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

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

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

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

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

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

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

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

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

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

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

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

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

  19. Table A19. Components of Total Electricity Demand by Census...

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

    Components of Total Electricity Demand by Census Region and" " Economic Characteristics of ...ansfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)",...

  20. Table A26. Components of Total Electricity Demand by Census Region, Census Di

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

    Components of Total Electricity Demand by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic

  1. National Solar Jobs Census 2014

    Broader source: Energy.gov [DOE]

    The Solar Foundation’s National Solar Jobs Census 2014 is the fifth annual update of current employment, trends, and projected growth in the U.S. solar industry. Data for Census 2014 is derived...

  2. char_household2001.pdf

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

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

  3. ac_household2001.pdf

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

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

  4. ac_household2001.pdf

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

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

  5. ac_household2001.pdf

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

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

  6. Table A26. Total Quantity of Purchased Energy Sources by Census...

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

    Total Quantity of Purchased Energy Sources by Census Region and" " Economic ... ","(1000","(trillion","Row" "Economic Characteristics(a)","Btu)","kWh)","(1000 ...

  7. Household energy consumption and expenditures 1987

    SciTech Connect (OSTI)

    Not Available

    1990-01-22

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

  8. Household magnets

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

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

  9. ,"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

  10. ,"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"

  11. ,"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"

  12. ,"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"

  13. 2015 National Solar Jobs Census

    Broader source: Energy.gov [DOE]

    The Solar Foundation's National Solar Jobs Census 2015 is the sixth annual edition of current employment, trends, and projected growth in the U.S. solar industry. Given this industry's rapid...

  14. Household energy consumption and expenditures, 1990

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

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

  15. 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.

  16. 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....

  17. National Solar Schools Census 2014

    Broader source: Energy.gov [DOE]

    With support from the SunShot Initiative, TSF’s national solar schools census, “Brighter Future: A Study on Solar in U.S. Schools” serves as a starting point for sharing ideas and best practices between schools experienced with solar energy and those seeking to join their ranks. Each solar school has its own unique story to tell on how their systems were financed and installed and how (and whether) solar has been integrated into class curricula.

  18. Table A28. Components of Onsite Electricity Generation by Census Region, Cens

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

    Components of Onsite Electricity Generation by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" ,,,"Renewables" ,,,"(excluding Wood",,"RSE" " "," "," ","and"," ","Row" "Economic Characteristics(a)","Total","Cogeneration(b)","Other

  19. Table HC1-7a. Housing Unit Characteristics by Four Most Populated States,

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

    7a. Housing Unit Characteristics by Four Most Populated States, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.0 1.0 1.3 1.7 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Census Region and Division Northeast ..................................................... 20.3 7.1 -- -- -- NF New England

  20. Table HC1-8a. Housing Unit Characteristics by Urban/Rural Location,

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

    8a. Housing Unit Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.3 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.2 Census Region and Division Northeast ..................................................... 20.3 7.7 4.5 4.7 3.4 7.4 New England .............................................

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

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

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

  2. homeoffice_household2001.pdf

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

    Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total ......

  3. spaceheat_household2001.pdf

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

    Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total ......

  4. Table HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit,

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

    5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.4 0.4 1.8 2.1 1.4 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Census Region and Division Northeast ......................................

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

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

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

  6. 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...

  7. Commercial Buildings Characteristics 1995 - Index Page

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

    >Commercial Buildings Home > 1995 Characteristics Data 1995 Data Executive Summary Table of Contents Overview to Detailed Tables Detailed Tables 1995 national and Census region...

  8. Try This: Household Magnets

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

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

  9. 1997 Housing Characteristics Tables Housing Unit Tables

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

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

  10. 1997 Housing Characteristics Tables Housing Unit Tables

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

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

  11. Hanford Site Regional Population - 2010 Census

    SciTech Connect (OSTI)

    Hamilton, Erin L.; Snyder, Sandra F.

    2011-08-12

    The U.S. Department of Energy conducts radiological operations in south-central Washington State. Population dose estimates must be performed to provide a measure of the impact from site radiological releases. Results of the U.S. 2010 Census were used to determine counts and distributions for the residential population located within 50-miles of several operating areas of the Hanford Site. Year 2010 was the first census year that a 50-mile population of a Hanford Site operational area exceeded the half-million mark.

  12. usage_household2001.pdf

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

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

  13. housingunit_household2001.pdf

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

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

  14. spaceheat_household2001.pdf

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

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

  15. 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 ...

  16. Housing characteristics 1993

    SciTech Connect (OSTI)

    1995-06-01

    This report, Housing Characteristics 1993, presents statistics about the energy-related characteristics of US households. These data were collected in the 1993 Residential Energy Consumption Survey (RECS) -- the ninth in a series of nationwide energy consumption surveys conducted since 1978 by the Energy Information Administration of the US Department of Energy. Over 7 thousand households were surveyed, representing 97 million households nationwide. A second report, to be released in late 1995, will present statistics on residential energy consumption and expenditures.

  17. 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...

  18. 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...

  19. Wade Hampton Census Area, Alaska: Energy Resources | Open Energy...

    Open Energy Info (EERE)

    Wade Hampton Census Area, Alaska: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 62.1458336, -162.8919191 Show Map Loading map......

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

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

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

  1. Table HC1-1a. Housing Unit Characteristics by Climate Zone,

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

    a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 Housing Unit 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 1.8 1.0 1.1 1.2 1.1 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 8.0 Census Region and Division Northeast

  2. Table HC1-2a. Housing Unit Characteristics by Year of Construction,

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

    2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 2001 Housing Unit 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 1.6 1.2 1.0 1.1 1.1 0.8 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Census Region and Division Northeast ...................................... 20.3 1.5 2.4 2.1 2.8 3.0 8.5 8.8 New

  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.
    Credit: Whirlpool Embraco's high ...

  4. 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 ...

  5. 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 *...

  6. 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 ...

  7. homeoffice_household2001.pdf

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

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

  8. homeoffice_household2001.pdf

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

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

  9. homeoffice_household2001.pdf

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

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

  10. homeoffice_household2001.pdf

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

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

  11. homeoffice_household2001.pdf

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

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

  12. spaceheat_household2001.pdf

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

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

  13. 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) . . . . . . . . ....

  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. Table 38. Coal Stocks at Coke Plants by Census Division

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

    Coal Stocks at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2014 Table 38. Coal Stocks at Coke ...

  16. 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 ...

  17. homeoffice_household2001.pdf

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

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

  18. Microsoft Word - Household Energy Use CA

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

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

  19. 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.

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

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

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

  1. 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...

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

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

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

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

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

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

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

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

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

  5. 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...

  6. 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.

  7. 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.

  8. Table 2: U.S. Geographic Areas and Census Regions | Department of Energy

    Energy Savers [EERE]

    2: U.S. Geographic Areas and Census Regions Table 2: U.S. Geographic Areas and Census Regions PDF icon Table 2: U.S. Geographic Areas and Census Regions More Documents & Publications Memorandum Summarizing Ex Parte Communication An Assessment of Heating Fuels And Electricity Markets During the Winters of 2013-2014 and 2014-2015 Final Report of the Mid-Atlantic Marine Wildlife Surveys, Modeling, and Data

  9. " East North Central",198,216,263,296,335,385

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

    Vehicle-Miles Traveled, Selected Survey Years (Billions) " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",1215,1353,1511,1602,1793,2287 "Household Characteristics" "Census...

  10. " East North Central",627,"NA",550,553,574,585.28553

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

    Fuel Consumption per Vehicle, Selected Survey Years (Gallons) " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",621,611,559,548,578,592 "Household Characteristics" "Census...

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

    SciTech Connect (OSTI)

    Dolealov, Markta; Beneov, Libue; Zvodsk, Anita

    2013-09-15

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

  12. A GSC Global Genome Census (GSC8 Meeting)

    ScienceCinema (OSTI)

    Kyrpides, Nikos [DOE JGI

    2011-04-29

    The Genomic Standards Consortium was formed in September 2005. It is an international, open-membership working body which promotes standardization in the description of genomes and the exchange and integration of genomic data. The 2009 meeting was an activity of a five-year funding "Research Coordination Network" from the National Science Foundation and was organized held at the DOE Joint Genome Institute with organizational support provided by the JGI and by the University of California - San Diego. Nikos Kyrpides of the DOE Joint Genome Institute discusses the notion of a global genome census at the Genomic Standards Consortium's 8th meeting at the DOE JGI in Walnut Creek, Calif. on Sept. 9, 2009.

  13. 1992 National census for district heating, cooling and cogeneration

    SciTech Connect (OSTI)

    Not Available

    1993-07-01

    District energy systems are a major part of the energy use and delivery infrastructure of the United States. With nearly 6,000 operating systems currently in place, district energy represents approximately 800 billion BTU per hour of installed thermal production capacity, and provides over 1.1 quadrillion BTU of energy annually -- about 1.3% of all energy used in the US each year. Delivered through more that 20,000 miles of pipe, this energy is used to heat and cool almost 12 billion square feet of enclosed space in buildings that serve a diverse range of office, education, health care, military, industrial and residential needs. This Census is intended to provide a better understanding of the character and extent of district heating, cooling and cogeneration in the United States. It defines a district energy system as: Any system that provides thermal energy (steam, hot water, or chilled water) for space heating, space cooling, or process uses from a central plant, and that distributes the energy to two or more buildings through a network of pipes. If electricity is produced, the system is a cogenerating facility. The Census was conducted through surveys administered to the memberships of eleven national associations and agencies that collectively represent the great majority of the nation`s district energy system operators. Responses received from these surveys account for about 11% of all district systems in the United States. Data in this report is organized and presented within six user sectors selected to illustrate the significance of district energy in institutional, community and utility settings. Projections estimate the full extent of district energy systems in each sector.

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

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

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

  15. 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

  16. 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.

  17. "Table HC11.13 Lighting Usage Indicators by Northeast Census Region, 2005"

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

    3 Lighting Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Lighting Usage Indicators",,,"Middle Atlantic","New England" "Total U.S. Housing Units",111.1,20.6,15.1,5.5 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between

  18. "Table HC12.13 Lighting Usage Indicators by Midwest Census Region, 2005"

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

    3 Lighting Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Lighting Usage Indicators",,,"East North Central","West North Central" "Total U.S. Housing Units",111.1,25.6,17.7,7.9 "Indoor Lights Turned On During Summer" "Number of Lights Turned On"

  19. "Table HC13.13 Lighting Usage Indicators by South Census Region, 2005"

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

    3 Lighting Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Lighting Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total U.S. Housing Units",111.1,40.7,21.7,6.9,12.1 "Indoor Lights Turned On During Summer" "Number of Lights

  20. "Table HC14.13 Lighting Usage Indicators by West Census Region, 2005"

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

    3 Lighting Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Lighting Usage Indicators",,,"Mountain","Pacific" "Total U.S. Housing Units",111.1,24.2,7.6,16.6 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per

  1. CENSUS OF BLUE STARS IN SDSS DR8

    SciTech Connect (OSTI)

    Scibelli, Samantha; Newberg, Heidi Jo; Carlin, Jeffrey L.; Yanny, Brian

    2015-01-01

    We present a census of the 12,060 spectra of blue objects ((g r){sub 0} < 0.25) in the Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8). As part of the data release, all of the spectra were cross-correlated with 48 template spectra of stars, galaxies, and QSOs to determine the best match. We compared the blue spectra by eye to the templates assigned in SDSS DR8. 10,856 of the objects matched their assigned template, 170 could not be classified due to low signal-to-noise ratio, and 1034 were given new classifications. We identify 7458 DA white dwarfs, 1145 DB white dwarfs, 273 rarer white dwarfs (including carbon, DZ, DQ, and magnetic), 294 subdwarf O stars, 648 subdwarf B stars, 679 blue horizontal branch stars, 1026 blue stragglers, 13 cataclysmic variables, 129 white dwarf-M dwarf binaries, 36 objects with spectra similar to DO white dwarfs, 179, quasi-stellar objects (QSOs), and 10 galaxies. We provide two tables of these objects, sample spectra that match the templates, figures showing all of the spectra that were grouped by eye, and diagnostic plots that show the positions, colors, apparent magnitudes, proper motions, etc., for each classification. Future surveys will be able to use templates similar to stars in each of the classes we identify to automatically classify blue stars, including rare types.

  2. 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.

  3. Household energy consumption and expenditures, 1987

    SciTech Connect (OSTI)

    Not Available

    1989-10-10

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

  4. Solar Census - Perfecting the Art of Automated, Remote Solar Shading Assessments (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2014-04-01

    To validate the work completed by Solar Census as part of the Department of Energy SunShot Incubator 8 award, NREL validated the performanec of the Solar Census Surveyor tool against the industry standard Solmetric SunEye measurements for 4 residential sites in California who experienced light to heavy shading. Using the a two one-sided test (TOST) of statistical equivalence, NREL found that the mean differences between the Solar Census and SunEye mean solar access values for Annual, Summer, and Winter readings fall within the 95% confidence intervals and the confidence intervals themselves fall within the tolerances of +/- 5 SAVs, the Solar Census calculations are statistically equivalent to the SunEye measurements.

  5. A stellar census of the Tucana-Horologium moving group

    SciTech Connect (OSTI)

    Kraus, Adam L.; Shkolnik, Evgenya L.; Allers, Katelyn N.; Liu, Michael C.

    2014-06-01

    We report the selection and spectroscopic confirmation of 129 new late-type (SpT = K3-M6) members of the Tucana-Horologium moving group, a nearby (d ∼ 40 pc), young (τ ∼ 40 Myr) population of comoving stars. We also report observations for 13 of the 17 known Tuc-Hor members in this spectral type range, and that 62 additional candidates are likely to be unassociated field stars; the confirmation frequency for new candidates is therefore 129/191 = 67%. We have used radial velocities, Hα emission, and Li{sub 6708} absorption to distinguish between contaminants and bona fide members. Our expanded census of Tuc-Hor increases the known population by a factor of ∼3 in total and by a factor of ∼8 for members with SpT ≥ K3, but even so, the K-M dwarf population of Tuc-Hor is still markedly incomplete. Our expanded census allows for a much more detailed study of Tuc-Hor than was previously feasible. The spatial distribution of members appears to trace a two-dimensional sheet, with a broad distribution in X and Y, but a very narrow distribution (±5 pc) in Z. The corresponding velocity distribution is very small, with a scatter of ±1.1 km s{sup –1} about the mean UVW velocity for stars spanning the entire 50 pc extent of Tuc-Hor. We also show that the isochronal age (τ ∼ 20-30 Myr) and the lithium depletion boundary age (τ ∼ 40 Myr) disagree, following the trend in other pre-main-sequence populations for isochrones to yield systematically younger ages. The Hα emission line strength follows a trend of increasing equivalent width with later spectral type, as is seen for young clusters. We find that moving group members have been depleted of measurable lithium for spectral types of K7.0-M4.5. None of our targets have significant infrared excesses in the WISE W3 band, yielding an upper limit on warm debris disks of F < 0.7%. Finally, our purely kinematic and color-magnitude selection procedure allows us to test the efficiency and completeness for activity-based selection of young stars. We find that 60% of K-M dwarfs in Tuc-Hor do not have ROSAT counterparts and would have been omitted in X-ray-selected samples. In contrast, GALEX UV-selected samples using a previously suggested criterion for youth achieve completeness of 77% and purity of 78%, and we suggest new SpT-dependent selection criteria that will yield >95% completeness for τ ∼ 40 Myr populations with GALEX data available.

  6. 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.

  7. 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)

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

    Broader source: Energy.gov [DOE]

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

  9. 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.

  10. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2001 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 9.4 9.2 19.6 41 19 40.2 16 607 0.29 598 231 Census Region and

  11. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 57.7 44.8 106.3 109 46 84.2 32 609 0.26 472 181 Census Region

  12. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 3 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 58.7 46.0 111.9 115 47 89.9 34 696 0.29 546 206 Census Region

  13. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2001 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 66.9 53.8 137.2 90 35 72.4 27 873 0.34 702 265 Census Region

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

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

    per Household and Other Demographic Statistics Fact 618: April 12, 2010 Vehicles per Household and Other Demographic Statistics Since 1969, the number of vehicles per ...

  15. 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

  16. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-01-01

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  17. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-12-31

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  18. 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.

  19. Travel Patterns And Characteristics Of Transit Users In New York State

    SciTech Connect (OSTI)

    Hwang, Ho-Ling; Wilson, Daniel W.; Reuscher, Tim; Chin, Shih-Miao; Taylor, Rob D.

    2015-12-01

    This research is a detailed examination of the travel behaviors and patterns of transit users within New York State (NYS), primarily based on travel data provided by the National Household Travel Survey (NHTS) in 2009 and the associated Add-on sample households purchased by the New York State Department of Transportation (NYSDOT). Other data sources analyzed in this study include: NYS General Transit Feed Specification (GTFS) to assist in analyzing spatial relationships for access to transit and the creation of Transit Shed geographic areas of 1, 2.5, and 5 miles from transit stop locations, LandScan population database to understand transit coverage, and Census Bureau s American Community Survey (ACS) data to examine general transit patterns and trends in NYS over time. The majority of analyses performed in this research aimed at identifying transit trip locations, understanding differences in transit usage by traveler demographics, as well as producing trip/mode-specific summary statistics including travel distance, trip duration, time of trip, and travel purpose of transit trips made by NYS residents, while also analyzing regional differences and unique travel characteristics and patterns. The analysis was divided into two aggregated geographic regions: New York Metropolitan Transportation Council (NYMTC) and NYS minus NYMTC (Rest of NYS). The inclusion of NYMTC in all analysis would likely produce misleading conclusions for other regions in NYS. TRANSIT COVERAGE The NYS transit network has significant coverage in terms of transit stop locations across the state s population. Out of the 19.3 million NYS population in 2011, about 15.3 million (or 79%) resided within the 1-mile transit shed. This NYS population transit coverage increased to 16.9 million (or 88%) when a 2.5-mile transit shed was considered; and raised to 17.7 million (or 92%) when the 5-mile transit shed was applied. KEY FINDINGS Based on 2009 NHTS data, about 40% of NYMTC households used transit as their means of transportation on any typical day; while only 4% of households located elsewhere in NYS did the same. Regardless of geographic regions, 45% of the transit users came from households with income under $40,000, while 20% of transit users were from the top income group of $100,000 plus households. Travel made by NYMTC transit users were nearly twice as likely to be for work trips as compared to their counterpart non-transit users. Transit users in NYS generally made more trips but with shorter distances; they also drove less, which resulted in fewer miles. Furthermore, NYS transit users spent more time on each trip than their counterpart non-transit users. Because of the intensity of transit network services within NYMTC, 88% of the households reside within the 1-mile transit shed. Outside the NYMTC, however, only 54% of the region s households are located within the same distance. Impact to vehicle ownership was clearly evidenced. Nearly all people from zero-vehicle households in NYMTC lived within a 1-mile radius of transit stops. Elsewhere in NYS, 74% of residents from zero-vehicle households resided within the 1-mile transit shed. Close proximity to transit has a significant impact on increasing transit uses. Transit mode share, as a main mode, was higher for NYS residents that lived within the 1-mile transit shed than others. Based on ACS data, over the period from 2005 to 2013, the total number of NYMTC workers increased more than 9%, while transit commuting grew at a higher rate of more than 15% during the same period. REMARKS Note that transit use in areas outside the NYMTC region generally is not common, resulting in a smaller sample size of transit users in the Rest of NYS region. Caution should be exercised for statistics produced based on small sample sizes that tend to be less precise (i.e., with a larger margin of error). Furthermore, standardized transit network data were not available prior to 2005; comparable analyses using 2001 NHTS therefore was not feasible. As a result, this study focused on examining travel behaviors of transit users using 2009 NHTS data only.

  20. " 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"

  1. " 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"

  2. " 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"

  3. " 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"

  4. " 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"

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

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

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

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

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

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

  7. 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...

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

    Broader source: Energy.gov [DOE]

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

  9. Household heating bills expected to be lower this winter

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

    In its new forecast, the U.S. Energy Information Administration said households that rely on heating oil which are mainly located in the Northeast will pay the lowest heating ...

  10. Determinants of Household Use of Selected Energy Star Appliances

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

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

  11. "Table HC11.10 Home Appliances Usage Indicators by Northeast Census Region, 2005"

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

    0 Home Appliances Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ," U.S. Housing Units (millions) " ,,,"Census Division" ,,"Total Northeast" "Home Appliances Usage Indicators",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A

  12. "Table HC11.12 Home Electronics Usage Indicators by Northeast Census Region, 2005"

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

    2 Home Electronics Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Home Electronics Usage Indicators",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Personal Computers" "Do Not Use a Personal Computer",35.5,6.9,5.3,1.6 "Use a

  13. "Table HC11.5 Space Heating Usage Indicators by Northeast Census Region, 2005"

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

    5 Space Heating Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Space Heating Usage Indicators",,,"Middle Atlantic","New England" "Total U.S. Housing Units",111.1,20.6,15.1,5.5 "Do Not Have Heating Equipment",1.2,"Q","Q","Q"

  14. "Table HC11.7 Air-Conditioning Usage Indicators by Northeast Census Region, 2005"

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

    7 Air-Conditioning Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Air Conditioning Usage Indicators",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Do Not Have Cooling Equipment",17.8,4,2.4,1.7 "Have Cooling

  15. "Table HC12.10 Home Appliances Usage Indicators by Midwest Census Region, 2005"

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

    0 Home Appliances Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Home Appliances Usage Indicators",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A

  16. "Table HC12.12 Home Electronics Usage Indicators by Midwest Census Region, 2005"

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

    2 Home Electronics Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Home Electronics Usage Indicators",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Personal Computers" "Do Not Use a Personal Computer",35.5,8.1,5.6,2.5 "Use

  17. "Table HC12.5 Space Heating Usage Indicators by Midwest Census Region, 2005"

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

    5 Space Heating Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Space Heating Usage Indicators",,,"East North Central","West North Central" "Total U.S. Housing Units",111.1,25.6,17.7,7.9 "Do Not Have Heating Equipment",1.2,"Q","Q","N"

  18. "Table HC12.7 Air-Conditioning Usage Indicators by Midwest Census Region, 2005"

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

    7 Air-Conditioning Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Air Conditioning Usage Indicators",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Do Not Have Cooling Equipment",17.8,2.1,1.8,0.3 "Have Cooling

  19. "Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005"

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

    0 Home Appliances Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Home Appliances Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Cooking Appliances" "Frequency of Hot Meals Cooked"

  20. "Table HC13.12 Home Electronics Usage Indicators by South Census Region, 2005"

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

    2 Home Electronics Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Home Electronics Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Personal Computers" "Do Not Use a Personal

  1. "Table HC13.5 Space Heating Usage Indicators by South Census Region, 2005"

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

    5 Space Heating Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Space Heating Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total U.S. Housing Units",111.1,40.7,21.7,6.9,12.1 "Do Not Have Heating

  2. "Table HC13.7 Air-Conditioning Usage Indicators by South Census Region, 2005"

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

    7 Air-Conditioning Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Air Conditioning Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Do Not Have Cooling Equipment",17.8,1.4,0.8,0.2,0.3 "Have

  3. "Table HC14.10 Home Appliances Usage Indicators by West Census Region, 2005"

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

    0 Home Appliances Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Home Appliances Usage Indicators",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,2.6,0.7,1.9 "2

  4. "Table HC14.12 Home Electronics Usage Indicators by West Census Region, 2005"

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

    2 Home Electronics Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Home Electronics Usage Indicators",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Personal Computers" "Do Not Use a Personal Computer",35.5,6.4,2.2,4.2 "Use a Personal

  5. "Table HC14.5 Space Heating Usage Indicators by West Census Region, 2005"

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

    5 Space Heating Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Space Heating Usage Indicators",,,"Mountain","Pacific" "Total U.S. Housing Units",111.1,24.2,7.6,16.6 "Do Not Have Heating Equipment",1.2,0.7,"Q",0.7 "Have Space Heating

  6. TOWARD A SPECTROSCOPIC CENSUS OF WHITE DWARFS WITHIN 40 pc OF THE SUN

    SciTech Connect (OSTI)

    Limoges, M.-M.; Bergeron, P.; Lepine, S. E-mail: bergeron@astro.umontreal.ca

    2013-05-15

    We present the preliminary results of a survey aimed at significantly increasing the range and completeness of the local census of spectroscopically confirmed white dwarfs. The current census of nearby white dwarfs is reasonably complete only to about 20 pc of the Sun, a volume that includes around 130 white dwarfs, a sample too small for detailed statistical analyses. This census is largely based on follow-up investigations of stars with very large proper motions. We describe here the basis of a method that will lead to a catalog of white dwarfs within 40 pc of the Sun and north of the celestial equator, thus increasing by a factor of eight the extent of the northern sky census. White dwarf candidates are identified from the SUPERBLINK proper motion database, allowing us to investigate stars down to a proper motion limit {mu} > 40 mas yr{sup -1}, while minimizing the kinematic bias for nearby objects. The selection criteria and distance estimates are based on a combination of color-magnitude and reduced proper motion diagrams. Our follow-up spectroscopic observation campaign has so far uncovered 193 new white dwarfs, among which we identify 127 DA (including 9 DA+dM and 4 magnetic), 1 DB, 56 DC, 3 DQ, and 6 DZ stars. We perform a spectroscopic analysis on a subsample of 84 DAs, and provide their atmospheric parameters. In particular, we identify 11 new white dwarfs with spectroscopic distances within 25 pc of the Sun, including five candidates to the D < 20 pc subset.

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

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

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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. A Glance at China’s Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-22

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

  18. New York Household Travel Patterns: A Comparison Analysis

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim

    2007-05-01

    In 1969, the U. S. Department of Transportation began collecting detailed data on personal travel to address various transportation planning issues. These issues range from assessing transportation investment programs to developing new technologies to alleviate congestion. This 1969 survey was the birth of the Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990 and 1995. Longer-distance travel was collected in 1977 and 1995. In 2001, the survey was renamed to the National Household Travel Survey (NHTS) and collected both daily and longer-distance trips in one survey. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State (NYS), the state procured an additional sample of households in both the 1995 and 2001 surveys. In the 1995 survey, NYS procured an addition sample of more than 9,000 households, increasing the final NY NPTS sample size to a total of 11,004 households. Again in 2001, NYS procured 12,000 additional sample households, increasing the final New York NHTS sample size to a total of 13,423 households with usable data. These additional sample households allowed NYS to address transportation planning issues pertinent to geographic areas significantly smaller than for what the national NPTS and NHTS data are intended. Specifically, these larger sample sizes enable detailed analysis of twelve individual Metropolitan Planning Organizations (MPOs). Furthermore, they allowed NYS to address trends in travel behavior over time. In this report, travel data for the entire NYS were compared to those of the rest of the country with respect to personal travel behavior and key travel determinants. The influence of New York City (NYC) data on the comparisons of the state of New York to the rest of the country was also examined. Moreover, the analysis examined the relationship between population density and travel patterns, and the similarities and differences among New York MPOs. The 1995 and 2001 survey data make it possible to examine and identify travel trends over time. This report does not address, however, the causes of the differences and/or trends.

  19. " Million U.S. Housing Units"

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

    3 Household Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Household Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Household Size" "1 Person",30,11.5,6.2,2.1,3.2 "2

  20. " Million U.S. Housing Units"

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

    3 Household Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Household Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Household Size" "1 Person",30,5.5,3.8,1.7 "2 Persons",34.8,6.5,4.8,1.7 "3

  1. " Million U.S. Housing Units"

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

    3 Household Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Household Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Household Size" "1 Person",30,7.3,5,2.3 "2 Persons",34.8,8.4,5.7,2.7 "3

  2. Buildings Energy Data Book: 3.2 Commercial Sector Characteristics

    Buildings Energy Data Book [EERE]

    4 Share of Commercial Floorspace, by Census Region and Vintage, as of 2003 (Percent) Region Prior to 1960 1960 to 1989 1990 to 2003 Total Northeast 9% 8% 3% 20% Midwest 8% 11% 6% 25% South 5% 18% 14% 37% West 3% 9% 5% 18% 100% Source(s): EIA, 2003 Commercial Buildings Energy Consumption Survey: Building Characteristics Tables, Oct. 2006, Table A2, p. 3-4

  3. Table B3. Census Region, Number of Buildings and Floorspace, 1999

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

    . Census Region, Number of Buildings and Floorspace, 1999" ,"Number of Buildings (thousand)",,,,,"Total Floorspace (million square feet)" ,"All Buildings","North- east","Midwest ","South","West","All Buildings","North- east","Midwest","South","West" "All Buildings ................",4657,686,1188,1762,1021,67338,12360,16761,23485,14731 "Building

  4. " by Census Region, Census Division...

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

    ... Products",1907,913,0,0," W "," W ",920,986,13.6 3312," Blast Furnaces and Steel Mills",1824,913,0,0,0," W ",919,905,14.5 3313," Electrometallurgical Products",23,0,0,0,0,0,0,23,62...

  5. " Census Region, Census Division, Industry...

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

    ... Q ",0,43.8 29,"Petroleum and Coal Products",2058,0,0,0,29.2 2911,"Petroleum Refining",1824,0,0,0,29.2 30,"Rubber and Miscellaneous Plastics Products",3350,0," W ",0,20.4 ...

  6. " by Census Region, Census Division...

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

    ... W "," W ",4,14,226,5,4,17.5 ," Recycling of Materials",1263,57,151,996,58,11,46,1...esses",0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 ," Recycling of Materials"," W "," W ",0," W "," W ...

  7. " of Supplier, Census Region, Census...

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

    "Value of Shipments and Receipts" "(million dollars)" " Under 20",121097,429,5068,4183,12.9 " 20-49",121480,613,5931,12800,7.7 " 50-99",110681,1018,9403,15247,7.9 " ...

  8. " by Census Region, Census Division...

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

    1" " (Estimates in Trillion Btu)" ,,,,"Computer Control" ,," "," ","of Processes"," "," ",," "," "," "," " ,," ","Computer Control","or Major",,,"One or More"," ","RSE",," " ...

  9. table6.xls

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

    .4 9.9 10.2 10.6 11.4 12.0 Household Characteristics Census Region and Division Northeast... 9.5 NA 10.3 10.9 11.3 11.9...

  10. " East North Central",9.3,"NA",10.1,10.7,11.6,11.85822

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

    (Thousands) " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",9.4,9.9,10.2,10.6,11.4,12 "Household Characteristics" "Census Region and Division" " Northeast",9.5,"NA",10.3...

  11. " East North Central",21.3,"NA",26,27.6,29,32.4

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

    Number of Vehicles, Selected Survey Years (Millions)" ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",129.3,137.3,147.5,151.2,156.8,191 "Household Characteristics" "Census...

  12. "Table 11. Fuel Economy, Selected Survey Years (Miles Per Gallon...

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

    Fuel Economy, Selected Survey Years (Miles Per Gallon)" ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",15.1,16.1,18.3,19.3,19.8,20.2 "Household Characteristics" "Census...

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

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

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

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

    Broader source: Energy.gov [DOE]

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

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

    Broader source: Energy.gov [DOE]

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

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

    Broader source: Energy.gov [DOE]

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

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

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

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

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

    Broader source: Energy.gov [DOE]

    Since 1969, the number of vehicles per household has increased by 66% and the number of vehicles per licensed driver has increased by 47%. The number of workers per household has changed the least...

  19. "Table HC14.7 Air-Conditioning Usage Indicators by West Census Region, 2005"

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

    7 Air-Conditioning Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Air Conditioning Usage Indicators",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Do Not Have Cooling Equipment",17.8,10.3,3.1,7.3 "Have Cooling Equipment",93.3,13.9,4.5,9.4 "Use Cooling

  20. CBECS Buildings Characteristics --Revised Tables

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

    Geographic Location Tables (24 pages, 136kb) CONTENTS PAGES Table 3. Census Region, Number of Buildings and Floorspace, 1995 Table 4. Census Region and Division, Number of Buildings, 1995 Table 5. Census Region and Division, Floorspace, 1995 Table 6. Climate Zone, Number of Buildings and Floorspace, 1995 Table 7. Metropolitan Status, Number of Buildings and Floorspace, 1995 These data are from the 1995 Commercial Buildings Energy Consumption Survey (CBECS), a national probability sample survey

  1. "Table HC10.10 Home Appliances Usage Indicators by U.S. Census Regions, 2005"

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

    0 Home Appliances Usage Indicators by U.S. Census Regions, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Home Appliances Usage Indicators",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,1.2,1.4,3,2.6 "2 Times A

  2. "Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005"

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

    2 Home Electronics Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Home Electronics Usage Indicators",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Personal Computers" "Do Not Use a Personal Computer",35.5,6.9,8.1,14.2,6.4 "Use a Personal

  3. "Table HC10.13 Lighting Usage Indicators by U.S. Census Region, 2005"

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

    3 Lighting Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Lighting Usage Indicators",,"Northeast","Midwest","South","West" "Total U.S. Housing Units",111.1,20.6,25.6,40.7,24.2 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per

  4. "Table HC10.5 Space Heating Usage Indicators by U.S. Census Region, 2005"

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

    5 Space Heating Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Space Heating Usage Indicators",,"Northeast","Midwest","South","West" "Total U.S. Housing Units",111.1,20.6,25.6,40.7,24.2 "Do Not Have Heating Equipment",1.2,"Q","Q","Q",0.7 "Have Space Heating

  5. "Table HC10.7 Air-Conditioning Usage Indicators by U.S. Census Region, 2005"

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

    7 Air-Conditioning Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Air Conditioning Usage Indicators",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Do Not Have Cooling Equipment",17.8,4,2.1,1.4,10.3 "Have Cooling Equipment",93.3,16.5,23.5,39.3,13.9 "Use Cooling

  6. Buildings Energy Data Book: 2.2 Residential Sector Characteristics

    Buildings Energy Data Book [EERE]

    4 Characteristics of U.S. Housing by Census Division and Region, as of 2005 Census Division Northeast 19% 2,423 1,664 New England 5% 2,552 1,680 Middle Atlantic 14% 2,376 1,658 Midwest 23% 2,566 1,927 East North Central 16% 2,628 1,926 West North Central 7% 2,424 1,930 South 37% 2,295 1,551 South Atlantic 20% 2,370 1,607 East South Central 6% 2,254 1,544 West South Central 11% 2,184 1,455 West 22% 1,963 1,366 Mountain 7% 2,149 1,649 Pacific 15% 1,878 1,238 Total 100% 2,309 1,618 Note(s):

  7. The census of complex organic molecules in the solar-type protostar IRAS16293-2422

    SciTech Connect (OSTI)

    Jaber, Ali A.; Ceccarelli, C.; Kahane, C.; Caux, E.

    2014-08-10

    Complex organic molecules (COMs) are considered to be crucial molecules, since they are connected with organic chemistry, at the basis of terrestrial life. More pragmatically, they are molecules which in principle are difficult to synthesize in harsh interstellar environments and, therefore, are a crucial test for astrochemical models. Current models assume that several COMs are synthesized on lukewarm grain surfaces (≳30-40 K) and released in the gas phase at dust temperatures of ≳100 K. However, recent detections of COMs in ≲20 K gas demonstrate that we still need important pieces to complete the puzzle of COMs formation. Here, we present a complete census of the oxygen- and nitrogen-bearing COMs, previously detected in different Interstellar Medium (ISM) regions, toward the solar-type protostar IRAS16293-2422. The census was obtained from the millimeter-submillimeter unbiased spectral survey TIMASSS. Of the 29 COMs searched for, 6 were detected: methyl cyanide, ketene, acetaldehyde, formamide, dimethyl ether, and methyl formate. Multifrequency analysis of the last five COMs provides clear evidence that they are present in the cold (≲30 K) envelope of IRAS16293-2422, with abundances of 0.03-2 × 10{sup –10}. Our data do not allow us to support the hypothesis that the COMs abundance increases with increasing dust temperature in the cold envelope, as expected if COMs were predominately formed on lukewarm grain surfaces. Finally, when also considering other ISM sources, we find a strong correlation over five orders of magnitude between methyl formate and dimethyl ether, and methyl formate and formamide abundances, which may point to a link between these two couples of species in cold and warm gas.

  8. Table HC1.1.1 Housing Unit Characteristics by

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

    1 Housing Unit Characteristics by" " Total, Heated, and Cooled Floorspace, 2005" ,,,"Total Square Footage" ,"Housing Units",,"Total",,"Heated",,"Cooled" "Housing Unit Characteristics","Millions","Percent","Billions","Percent","Billions","Percent","Billions","Percent" "Total",111.1,100,256.5,100,179.8,100,114.5,100 "Census Region

  9. 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, ...

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

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

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

  11. 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.

  12. 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.

  13. ,"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

  14. ,"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

  15. ,"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

  16. ,"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"

  17. oil1997.xls

    Gasoline and Diesel Fuel Update (EIA)

    Total per Floor- per Square per per per Total Total space (1) Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 13.2 11.0 23.2 97 46 81.1 31 694 0.33 578 224 Census Region and Division Northeast 8.2 6.2 14.5 136 57 101.3 40 950 0.40 710 282 New England 3.1

  18. oil2001.xls

    Gasoline and Diesel Fuel Update (EIA)

    Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 11.2 9.4 26.0 80 29 67.1 26 723 0.26 607 236 Census Region and Division Northeast 7.1 5.4 16.8 111 36 84.7 33 992 0.32 757 297 New England 2.9 2.5 8.0 110

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 7.7 7.4 12.1 47 29 45.6 16 379 0.23 365 125 Census Region and Division

  10. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 7.3 7.2 12.2 44 26 42.8 15 389 0.23 382 133 Census Region and Division

  11. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 7.3 7.2 11.7 40 25 39.6 14 383 0.23 376 132 Census Region and Division

  12. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 7.8 7.7 12.0 41 26 40.1 15 406 0.26 398 146 Census Region and Division

  13. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 7.7 7.6 12.3 41 26 41.1 15 369 0.23 366 131 Census Region and Division

  14. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 8.2 0.5 13.9 542 20 34.1 12 6,063 0.23 381 134 Census Region and

  15. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 3 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 8.1 7.9 14.9 48 25 46.8 17 481 0.26 470 170 Census Region and Division

  16. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average LPG Residential Buildings Consumption Expenditures Total per Floor- per Square per per per Total Total space (1) Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 8.1 8.0 13.9 45 26 44.6 17 508 0.29 500 192 Census Region and

  17. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 53.4 41.5 92.8 127 57 98.7 35 578 0.26 450 159 Census Region and

  18. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 54.2 41.0 91.8 116 52 87.6 32 658 0.29 498 183 Census Region and

  19. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 55.4 41.3 93.2 121 53 89.9 33 722 0.32 537 198 Census Region and

  20. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 57.3 42.5 99.4 114 49 84.3 33 615 0.26 456 176 Census Region and

  1. A HERSCHEL AND APEX CENSUS OF THE REDDEST SOURCES IN ORION: SEARCHING FOR THE YOUNGEST PROTOSTARS

    SciTech Connect (OSTI)

    Stutz, Amelia M.; Robitaille, Thomas; Henning, Thomas; Krause, Oliver; Tobin, John J.; Stanke, Thomas; Megeath, S. Thomas; Fischer, William J.; Ali, Babar; Furlan, Elise; Hartmann, Lee; Osorio, Mayra; Wilson, Thomas L.; Allen, Lori; Manoj, P.

    2013-04-10

    We perform a census of the reddest, and potentially youngest, protostars in the Orion molecular clouds using data obtained with the PACS instrument on board the Herschel Space Observatory and the LABOCA and SABOCA instruments on APEX as part of the Herschel Orion Protostar Survey (HOPS). A total of 55 new protostar candidates are detected at 70 {mu}m and 160 {mu}m that are either too faint (m{sub 24} > 7 mag) to be reliably classified as protostars or undetected in the Spitzer/MIPS 24 {mu}m band. We find that the 11 reddest protostar candidates with log {lambda}F{sub {lambda}}70/{lambda}F{sub {lambda}}24 > 1.65 are free of contamination and can thus be reliably explained as protostars. The remaining 44 sources have less extreme 70/24 colors, fainter 70 {mu}m fluxes, and higher levels of contamination. Taking the previously known sample of Spitzer protostars and the new sample together, we find 18 sources that have log {lambda}F{sub {lambda}}70/{lambda}F{sub {lambda}}24 > 1.65; we name these sources 'PACS Bright Red sources', or PBRs. Our analysis reveals that the PBR sample is composed of Class 0 like sources characterized by very red spectral energy distributions (SEDs; T{sub bol} < 45 K) and large values of sub-millimeter fluxes (L{sub smm}/L{sub bol} > 0.6%). Modified blackbody fits to the SEDs provide lower limits to the envelope masses of 0.2-2 M{sub Sun} and luminosities of 0.7-10 L{sub Sun }. Based on these properties, and a comparison of the SEDs with radiative transfer models of protostars, we conclude that the PBRs are most likely extreme Class 0 objects distinguished by higher than typical envelope densities and hence, high mass infall rates.

  2. Table HC1.2.2 Living Space Characteristics by Average Floorspace

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

    2 Living Space Characteristics by Average Floorspace, " " Per Housing Unit and Per Household Member, 2005" ,,"Average Square Feet" ," Housing Units (millions)" ,,"Per Housing Unit",,,"Per Household Member" "Living Space Characteristics",,"Total1","Heated","Cooled","Total1","Heated","Cooled" "Total",111.1,2033,1618,1031,791,630,401 "Total Floorspace (Square

  3. Word Pro - Untitled1

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

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

  4. 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.

  5. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  6. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  7. Commercial Buildings Characteristics 1992 - Publication and Tables

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

    floorspace by census region, 1992 separater bar To View andor Print Reports (requires Adobe Acrobat Reader) - Download Adobe Acrobat Reader If you experience any difficulties,...

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

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

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

  9. 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.

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

    Broader source: Energy.gov [DOE]

    The overall share of annual household expenditures for transportation was lower in 2010 than it was in 1984, reaching its lowest point in 2009 at 15.5%. In the early to mid-1980s when oil prices...

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

    Broader source: Energy.gov [DOE]

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

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

    Energy Savers [EERE]

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

  13. Buildings Energy Data Book: 2.2 Residential Sector Characteristics

    Buildings Energy Data Book [EERE]

    3 Share of Total U.S. Households, by Census Region, Division, and Vintage, as of 2005 Prior to 1950 to 1970 to 1980 to 1990 to 2000 to Region 1950 1969 1979 1989 1999 2005 Northeast 6.7% 5.2% 2.4% 2.1% 1.3% 0.8% 18.5% New England 2.1% 1.2% 0.5% 0.5% 0.3% 0.3% 4.9% Middle Atlantic 4.6% 4.0% 1.9% 1.6% 1.0% 0.5% 13.6% Midwest 5.7% 5.8% 3.6% 2.5% 3.7% 1.7% 23.0% East North Central 4.3% 3.9% 2.7% 1.8% 2.1% 1.1% 16.0% West North Central 1.4% 1.9% 0.9% 0.7% 1.6% 0.6% 7.1% South 4.0% 6.9% 6.4% 7.5% 7.5%

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

    SciTech Connect (OSTI)

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

    2005-05-31

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

  15. 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.

  16. 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...

  17. 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 ...

  18. 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.

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

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

    Average U.S. household to spend $710 less on gasoline during 2015 Even with the recent increases in gasoline prices, the average U.S. household is still expected save $710 in gasoline costs this year compared with what was paid at the pump in 2014. In its new monthly forecast, the U.S. Energy Information Administration said the national average price for regular gasoline is expected to be $2.39 per gallon this year. That's almost $1 less than the $3.36 average in 2014. Lower crude oil prices

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  6. " Million U.S. Housing Units"

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

    3 Household Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Household Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Household Size" "1 Person",30,5.7,1.5,4.2 "2 Persons",34.8,7.4,2.9,4.5 "3 Persons",18.4,3.9,1.2,2.7

  7. 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.

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

    Broader source: Energy.gov [DOE]

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

  9. "Table HC15.1 Housing Unit Characteristics by Four Most Populated States, 2005"

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

    Housing Unit Characteristics by Four Most Populated States, 2005" " Million Housing Units" ,"U.S. Housing Units (millions)","Four Most Populated States" "Housing Unit Characteristics",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Census Region and Division" "Northeast",20.6,7.1,"N","N","N" "New

  10. 1999 Commercial Buildings Characteristics

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

    Data Reports > 2003 Building Characteristics Overview 1999 Commercial Buildings Energy Consumption SurveyCommercial Buildings Characteristics Released: May 2002 Topics: Energy...

  11. 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

  12. 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.

  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. steoxxxx1

    Gasoline and Diesel Fuel Update (EIA)

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

  15. speakers bureau.indd

    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

  16. file://C:\MyFiles\TeamWorks%20Website\index.htm

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

    0a. Usage Indicators by Midwest Census Region, Million U.S. Households, 2001 ____________________________________________________________________________________________ | | | | | Midwest Census Region | | |___________________________________| | | | | | | | Census Division | | | |_______________________| | | | | | | Total | | East North| West North| Usage Indicators | U.S. | Total | Central | Central | |___________|___________|___________|___________| RSE | | | | | Row RSE Column Factor: | 0.5 |

  17. h:prjq496 ext intext.pdf

    Gasoline and Diesel Fuel Update (EIA)

    0a. Usage Indicators by Midwest Census Region, Million U.S. Households, 2001 ____________________________________________________________________________________________ | | | | | Midwest Census Region | | |___________________________________| | | | | | | | Census Division | | | |_______________________| | | | | | | Total | | East North| West North| Usage Indicators | U.S. | Total | Central | Central | |___________|___________|___________|___________| RSE | | | | | Row RSE Column Factor: | 0.5 |

  18. Longwall census '82

    SciTech Connect (OSTI)

    Sprouls, M.W.

    1982-12-01

    Surveys the number of operating longwall systems in the US in 1982. Active longwall systems totalled 112, with 22 companies operating faces in 11 states. Tables list the number of longwalls for each of the top 12 longwall mining companies, and the number of longwalls in each state. The most sophisticated type of longwall roof supports, shields, now comprise 93 of US longwall installations. The most sophisticated type of cutting machines, the double-ended-rangingdrum shearer (DERS) dominates. The survey also shows a trend for operators to purchase stage loaders with crusher/breakers. The crushers eliminate problems with chunks of material at conveyor transfer points. Concludes that the longwall's future in the US looks bright.

  19. 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.

  20. 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...

  1. Report for Development of a Census Array and Evaluation of the Array to Detect Biothreat Agents and Environmental Samples for DHS

    SciTech Connect (OSTI)

    Jaing, C; Jackson, P

    2011-04-14

    The objective of this project is to provide DHS a comprehensive evaluation of the current genomic technologies including genotyping, Taqman PCR, multiple locus variable tandem repeat analysis (MLVA), microarray and high-throughput DNA sequencing in the analysis of biothreat agents from complex environmental samples. This report focuses on the design, testing and results of samples on the Census Array. We designed a Census/Detection Array to detect all sequenced viruses (including phage), bacteria (eubacteria), and plasmids. Family-specific probes were selected for all sequenced viral and bacterial complete genomes, segments, and plasmids. Probes were designed to tolerate some sequence variation to enable detection of divergent species with homology to sequenced organisms, and to be unique relative to the human genome. A combination of 'detection' probes with high levels of conservation within a family plus 'census' probes targeting strain/isolate specific regions enabled detection and taxonomic classification from the level of family down to the strain. The array has wider coverage of bacterial and viral targets based on more recent sequence data and more probes per target than other microbial detection/discovery arrays in the literature. We tested the array with purified bacterial and viral DNA/RNA samples, artificial mixes of known bacterial/viral samples, spiked DNA against complex background including BW aerosol samples and soil samples, and environmental samples to evaluate the array's sensitivity and forensic capability. The data were analyzed using our novel maximum likelihood software. For most of the organisms tested, we have achieved at least species level discrimination.

  2. ARM - Measurement - Soil characteristics

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

    Measurement : Soil characteristics Includes available water capacity, bulk density, permeability, porosity, rock fragment classification, rock fragment volume, percent clay,...

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

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-06-01

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

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

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

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

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

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

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

  6. 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.

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

    SciTech Connect (OSTI)

    Bigum, Marianne; Petersen, Claus; Scheutz, Charlotte

    2013-11-15

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

  8. 1997 Housing Characteristics Tables Home Office Equipment Tables

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

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

  9. Characteristics of Strong Programs

    Broader source: Energy.gov [DOE]

    Existing financing programs offer a number of important lessons on effective program design. Some characteristics of strong financing programs drawn from past program experience are described below.

  10. Commercial Buildings Characteristics 1992

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

    schedules and the number of workers across all shifts as well as the main shift. * Energy Management Characteristics - Energy management questions were expanded to ask whether or...

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

    SciTech Connect (OSTI)

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

    1996-03-01

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

  12. 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.

  13. " Million U.S. Housing Units"

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

    3 Household Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Household Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Household Size" "1 Person",30,5.5,7.3,11.5,5.7 "2 Persons",34.8,6.5,8.4,12.5,7.4 "3 Persons",18.4,3.4,4.1,7,3.9 "4

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

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

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

  15. 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.

  16. 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.

  17. Commercial Buildings Characteristics, 1992

    SciTech Connect (OSTI)

    Not Available

    1994-04-29

    Commercial Buildings Characteristics 1992 presents statistics about the number, type, and size of commercial buildings in the United States as well as their energy-related characteristics. These data are collected in the Commercial Buildings Energy Consumption Survey (CBECS), a national survey of buildings in the commercial sector. The 1992 CBECS is the fifth in a series conducted since 1979 by the Energy Information Administration. Approximately 6,600 commercial buildings were surveyed, representing the characteristics and energy consumption of 4.8 million commercial buildings and 67.9 billion square feet of commercial floorspace nationwide. Overall, the amount of commercial floorspace in the United States increased an average of 2.4 percent annually between 1989 and 1992, while the number of commercial buildings increased an average of 2.0 percent annually.

  18. 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.

  19. Insights from Smart Meters. Identifying Specific Actions, Behaviors and Characteristics that drive savings in Behavior-Based Programs

    SciTech Connect (OSTI)

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

    2014-12-01

    In this report, we use smart meter data to analyze specific actions, behaviors, and characteristics that drive energy savings in a behavior-based (BB) program. Specifically, we examine a Home Energy Report (HER) program. These programs typically obtain 1% to 3% annual savings, and recent studies have shown hourly savings of between 0.5% and 3%. But what is driving these savings? What types of households tend to be “high-savers”, and what behaviors are they adopting? There are several possibilities: one-time behaviors (e.g., changing thermostat settings); reoccurring habitual behaviors (e.g., turning off lights); and equipment purchase behaviors (e.g., energy efficient appliances), and these may vary across households, regions, and over time.

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

    SciTech Connect (OSTI)

    Lebersorger, S.; Beigl, P.

    2011-09-15

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

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

    SciTech Connect (OSTI)

    Slagstad, Helene; Brattebo, Helge

    2012-07-15

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

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

    SciTech Connect (OSTI)

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

    1987-08-01

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

  3. 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.

  4. 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.

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

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

    b. Housing Unit Characteristics by Four Most Populated States, Percent of U.S. Households, 1997 Housing Unit Characteristics RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.1 1.2 1.7 Total .............................................................. 100.0 100.0 100.0 100.0 100.0 0.0 Census Region and Division Northeast ..................................................... 19.4 100.0 -- -- -- NF New England

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

    SciTech Connect (OSTI)

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

    2012-01-01

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

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

    SciTech Connect (OSTI)

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

    2013-01-15

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

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

    SciTech Connect (OSTI)

    Bernstad, A.; Cour Jansen, J. la

    2011-08-15

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

  9. " Million Housing Units, Final"

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

    4 Structural and Geographic Characteristics of U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" "Structural and Geographic Characteristics",,,,,,"5 or More Members" ,,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "Census Region and Division"

  10. " Million U.S. Housing Units"

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

    Housing Unit Characteristics by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Housing Unit Characteristics" "Total",111.1,30,34.8,18.4,15.9,12 "Census Region and Division" "Northeast",20.6,5.5,6.5,3.4,3,2.1 "New

  11. 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.

  12. Crude Oil Characteristics Research

    Broader source: Energy.gov [DOE]

    The Department of Energy Office of Fossil Energy is continuing to develop a better understanding of scientific questions associated with the production, treatment, and rail transportation of crude oils, including Bakken crude oil. To support this effort, the DOE - in collaboration with the Department of Transportation’s Pipeline and Hazardous Materials Safety Administration (PHMSA) will focus on the portion of the effort described in the Crude Oil Characteristics Sampling, Analysis and Experiment (SAE) Plan. The work contained in this SAE plan is intended to fill knowledge gaps based on recommendations on research needed to improve understanding of transport-critical crude oil and especially tight crude oil properties from the Literature Survey of Crude Oil Properties Relevant to Handling and Fire Safety in Transport recently completed by Sandia National Laboratory.

  13. Wafer characteristics via reflectometry

    DOE Patents [OSTI]

    Sopori, Bhushan L.

    2010-10-19

    Various exemplary methods (800, 900, 1000, 1100) are directed to determining wafer thickness and/or wafer surface characteristics. An exemplary method (900) includes measuring reflectance of a wafer and comparing the measured reflectance to a calculated reflectance or a reflectance stored in a database. Another exemplary method (800) includes positioning a wafer on a reflecting support to extend a reflectance range. An exemplary device (200) has an input (210), analysis modules (222-228) and optionally a database (230). Various exemplary reflectometer chambers (1300, 1400) include radiation sources positioned at a first altitudinal angle (1308, 1408) and at a second altitudinal angle (1312, 1412). An exemplary method includes selecting radiation sources positioned at various altitudinal angles. An exemplary element (1650, 1850) includes a first aperture (1654, 1854) and a second aperture (1658, 1858) that can transmit reflected radiation to a fiber and an imager, respectfully.

  14. Housing characteristics, 1987: Residential Energy Consumption Survey

    SciTech Connect (OSTI)

    Not Available

    1989-05-26

    This report is the first of a series of reports based on data from the 1987 RECS. The 1987 RECS is the seventh in the series of national surveys of households and their energy suppliers. These surveys provide baseline information on how households in the United States use energy. A cross section of housing types such as single-family detached homes, townhouses, large and small apartment buildings, condominiums, and mobile homes were included in the survey. Data from the RECS and a companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are available to the public in published reports such as this one and on public use tapes. 10 figs., 69 tabs.

  15. Sensor Characteristics Reference Guide

    SciTech Connect (OSTI)

    Cree, Johnathan V.; Dansu, A.; Fuhr, P.; Lanzisera, Steven M.; McIntyre, T.; Muehleisen, Ralph T.; Starke, M.; Banerjee, Pranab; Kuruganti, T.; Castello, C.

    2013-04-01

    The Buildings Technologies Office (BTO), within the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), is initiating a new program in Sensor and Controls. The vision of this program is: • Buildings operating automatically and continuously at peak energy efficiency over their lifetimes and interoperating effectively with the electric power grid. • Buildings that are self-configuring, self-commissioning, self-learning, self-diagnosing, self-healing, and self-transacting to enable continuous peak performance. • Lower overall building operating costs and higher asset valuation. The overarching goal is to capture 30% energy savings by enhanced management of energy consuming assets and systems through development of cost-effective sensors and controls. One step in achieving this vision is the publication of this Sensor Characteristics Reference Guide. The purpose of the guide is to inform building owners and operators of the current status, capabilities, and limitations of sensor technologies. It is hoped that this guide will aid in the design and procurement process and result in successful implementation of building sensor and control systems. DOE will also use this guide to identify research priorities, develop future specifications for potential market adoption, and provide market clarity through unbiased information

  16. Word Pro - Untitled1

    Gasoline and Diesel Fuel Update (EIA)

    1 Table 2.4 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 ...

  17. " Electricity Generation by Census Region...

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

    Btu)" " "," "," "," "," "," "," "," ","Waste"," " " "," "," ","Blast"," "," "," "," ... Manmade Fibers",0,0,0,0,0,0,0,0 2824," Organic Fibers, Noncellulosic"," W ",0," W ...

  18. " and Electricity Generation by Census...

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

    Factors:",0.6,0.6,2.2,0.9,0.7,1.8 , 20,"Food and Kindred Products",0,107269,93960,4113,... Factors:",0.7,0.8,1.6,0.9,0.8,1.6 , 20,"Food and Kindred Products",0," W ",0,0," W "," ...

  19. US prep plant census 2008

    SciTech Connect (OSTI)

    Fiscor, S.

    2008-10-15

    Each year Coal Age conducts a fairly comprehensive survey of the industry to produce the US coal preparation plant survey. This year's survey shows how many mergers and acquisitions have given coal operators more coal washing capacity. The plants are tabulated by state, giving basic details including company owner, plant name, raw feed, product ash %, quality, type of plant builder and year built. 1 tab., 1 photo.

  20. CENSUS AND STATISTICAL CHARACTERIZATION OF SOIL AND WATER QUALITY AT ABANDONED AND OTHER CENTRALIZED AND COMMERCIAL DRILLING-FLUID DISPOSAL SITES IN LOUISIANA, NEW MEXICO, OKLAHOMA, AND TEXAS

    SciTech Connect (OSTI)

    Alan R. Dutton; H. Seay Nance

    2003-06-01

    Commercial and centralized drilling-fluid disposal (CCDD) sites receive a portion of spent drilling fluids for disposal from oil and gas exploration and production (E&P) operations. Many older and some abandoned sites may have operated under less stringent regulations than are currently enforced. This study provides a census, compilation, and summary of information on active, inactive, and abandoned CCDD sites in Louisiana, New Mexico, Oklahoma, and Texas, intended as a basis for supporting State-funded assessment and remediation of abandoned sites. Closure of abandoned CCDD sites is within the jurisdiction of State regulatory agencies. Sources of data used in this study on abandoned CCDD sites mainly are permit files at State regulatory agencies. Active and inactive sites were included because data on abandoned sites are sparse. Onsite reserve pits at individual wells for disposal of spent drilling fluid are not part of this study. Of 287 CCDD sites in the four States for which we compiled data, 34 had been abandoned whereas 54 were active and 199 were inactive as of January 2002. Most were disposal-pit facilities; five percent were land treatment facilities. A typical disposal-pit facility has fewer than 3 disposal pits or cells, which have a median size of approximately 2 acres each. Data from well-documented sites may be used to predict some conditions at abandoned sites; older abandoned sites might have outlier concentrations for some metal and organic constituents. Groundwater at a significant number of sites had an average chloride concentration that exceeded nonactionable secondary drinking water standard of 250 mg/L, or a total dissolved solids content of >10,000 mg/L, the limiting definition for underground sources of drinking water source, or both. Background data were lacking, however, so we did not determine whether these concentrations in groundwater reflected site operations. Site remediation has not been found necessary to date for most abandoned CCDD sites; site assessments and remedial feasibility studies are ongoing in each State. Remediation alternatives addressed physical hazards and potential for groundwater transport of dissolved salt and petroleum hydrocarbons that might be leached from wastes. Remediation options included excavation of wastes and contaminated adjacent soils followed by removal to permitted disposal facilities or land farming if sufficient on-site area were available.

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

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

    Million U.S. Households, 1997 Housing Unit Characteristics RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.1 1.2 1.7 Total .............................................................. 101.5 6.8 11.5 7.0 5.9 NF Census Region and Division Northeast ..................................................... 19.7 6.8 -- -- -- NF New England ............................................. 5.3 Q -- -- -- NF Middle Atlantic

  2. CBECS Buildings Characteristics --Revised Tables

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

    Totals and Means of Floorspace, Number of Workers, and Hours of Operation, 1995 Building Characteristics RSE Column Factor: All Buildings (thousand) Total Floorspace (million...

  3. Property:Other Characteristics | Open Energy Information

    Open Energy Info (EERE)

    Characteristics Jump to: navigation, search Property Name Other Characteristics Property Type String Pages using the property "Other Characteristics" Showing 8 pages using this...

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

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

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

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

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

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

  6. 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.

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

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

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

  8. 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.

  9. 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.

  10. Boundary Layer Cloud Turbulence Characteristics

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

    Boundary Layer Cloud Turbulence Characteristics Virendra Ghate Bruce Albrecht Parameter Observational Readiness (/10) Modeling Need (/10) Cloud Boundaries 9 9 Cloud Fraction Variance Skewness Up/Downdraft coverage Dominant Freq. signal Dissipation rate ??? Observation-Modeling Interface

  11. Characteristics RSE Column Factor: Total

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

    and 1994 Vehicle Characteristics RSE Column Factor: Total 1993 Family Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factor: Less than 5,000 5,000...

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

    SciTech Connect (OSTI)

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

    1992-09-01

    The Iraqi invasion of Kuwait and the subsequent war between Iraq and an international alliance led by the United States triggered immediate increases in world oil prices. Increases in world petroleum prices and in US petroleum imports resulted in higher petroleum prices for US customers. In this report, the effects of the Persian Gulf War and its aftermath are used to demonstrate the potential impacts of petroleum price changes on majority, black, and Hispanic households, as well as on poor and nonpoor households. The analysis is done by using the Minority Energy Assessment Model developed by Argonne National Laboratory for the US Department of Energy (DOE). The differential impacts of these price increases and fluctuations on poor and minority households raise significant issues for a variety of government agencies, including DOE. Although the Persian Gulf crisis is now over and world oil prices have returned to their prewar levels, the differential impacts of rising energy prices on poor and minority households as a result of any future crisis in the world oil market remains a significant long-term issue.

  13. 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...

  14. Travel Patterns and Characteristics of Elderly Subpopulation in New York State

    SciTech Connect (OSTI)

    Hwang, Ho-Ling; Wilson, Daniel W.; Reuscher, Tim; Yang, Jianjiang; Taylor, Rob D.; Chin, Shih-Miao

    2015-03-01

    With the increasing demographic shift towards a larger population of elderly (individuals 65 years and older), it is essential for policy makers and planners to have an understanding of transportation issues that affect the elderly. These issues include livability of the community, factors impacting travel behavior and mobility, transportation safety, etc. In this study, Oak Ridge National Laboratory was tasked by the New York State (NYS) Department of Transportation to conduct a detailed examination of travel behaviors, and identify patterns and trends of the elderly within NYS. The National Household Travel Survey (NHTS) was used as the primary data source to analyze subjects and address questions such as: Are there differences in traveler demographics between the elderly population and those of younger age groups who live in various NYS regions; e.g., New York City, other urban areas of NYS, or other parts of the country? How do they compare with the population at large? Are there any regional differences (e.g., urban versus rural)? Gender differences? Do any unique travel characteristics or patterns exist within the elderly group? In addition to analysis of NHTS data, roadway travel safety concerns associated with elderly travelers were also investigated in this study. Specifically, data on accidents involving the elderly (including drivers, passengers, and others) as captured in the Fatal Analysis Reporting System (FARS) database was analyzed to examine elderly driver and elderly pedestrian travel safety issues in NYS. The analyses of these data sets provide a greater understanding of the elderly within NYS and their associated transportation issues. Through this study, various key findings on elderly population size, household characteristics, and travel patterns were produced and are report herein this report.

  15. 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. ...

  16. Agricultural production in the United States by county: a compilation of information from the 1974 census of agriculture for use in terrestrial food-chain transport and assessment models

    SciTech Connect (OSTI)

    Shor, R.W.; Baes, C.F. III; Sharp, R.D.

    1982-01-01

    Terrestrial food-chain models that simulate the transport of environmentally released radionuclides incorporate parameters describing agricultural production and practice. Often a single set of default parameters, such as that listed in USNRC Regulatory Guide 1.109, is used in lieu of site-specific information. However, the geographical diversity of agricultural practice in the United States suggests the limitations of a single set of default parameters for assessment models. This report documents default parameters with a county-wide resolution based on analysis of the 1974 US Census of Agriculture for use in terrestrial food chain models. Data reported by county, together with state-based information from the US Department of Agriculture, Economic and Statistics Service, provided the basis for estimates of model input parameters. This report also describes these data bases, their limitations, and lists default parameters by county. Vegetable production is described for four categories: leafy vegetables; vegetables and fruits exposed to airborne material; vegetables, fruits, and nuts protected from airborne materials; and grains. Livestock feeds were analyzed in categories of hay, silage, pasture, and grains. Pasture consumption was estimated from cattle and sheep inventories, their feed requirements, and reported quantities of harvested forage. The results were compared with assumed yields of the pasture areas reported. In addition, non-vegetable food production estimates including milk, beef, pork, lamb, poultry, eggs, goat milk, and honey are described. The agricultural parameters and land use information - in all 47 items - are tabulated in four appendices for each of the 3067 counties of the US reported to the Census of Agriculture, excluding those in Hawaii and Alaska.

  17. Table A20. Components of Onsite Electricity Generation by...

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

    Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" ,,,,,"RSE" " "," "," "," "," ","Row" "Economic ...

  18. Lands with Wilderness Characteristics | Open Energy Information

    Open Energy Info (EERE)

    with Wilderness Characteristics Jump to: navigation, search Retrieved from "http:en.openei.orgwindex.php?titleLandswithWildernessCharacteristics&oldid647799...

  19. System Design - Lessons Learned, Generic Concepts, Characteristics...

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

    Design - Lessons Learned, Generic Concepts, Characteristics & Impacts System Design - Lessons Learned, Generic Concepts, Characteristics & Impacts Presented at the DOE-DOD ...

  20. Health Care Buildings : Basic Characteristics Tables

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

    Basic Characteristics Tables Buildings and Size Data by Basic Characteristics for Health Care Buildings Number of Buildings (thousand) Percent of Buildings Floorspace (million...

  1. 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.

  2. dec00

    Gasoline and Diesel Fuel Update (EIA)

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

  3. " Million Housing Units, Final"

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

    8 Household Demographics of Homes in Northeast Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Northeast Census Region" ,,,"New England Census Division",,,"Middle Atlantic Census Division" ,"Total U.S.1 (millions)",,"Total New England",,,"Total Middle Atlantic" ,,"Total Northeast",,,"CT, ME, NH, RI, VT" "Household

  4. Next Generation Household Refrigerator

    Broader source: Energy.gov [DOE]

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

  5. natgas1980.xls

    Gasoline and Diesel Fuel Update (EIA)

    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 51.6 39.7 88.5 125 56 96.2 34 497 0.22 383 137 Census Region and Division Northeast 10.9 6.5 18.8 144 50 86.6 31 771 0.27 463 168 New England 1.9 0.9 3.1 162 47 78.9 28 971 0.28 472 169 Middle Atlantic 9.0 5.6 15.7 141 51 88.1 32 739 0.27 461 168 Midwest 15.5 12.4 29.4 164 70 131.6 46 586 0.25 470 165

  6. oil1982.xls

    Gasoline and Diesel Fuel Update (EIA)

    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 Region and Division Northeast 8.8 6.0 17.4 138 48 94.5 34 1,163 0.40 796 283 New England 2.5 1.9 5.9 131 43 101.9 36 1,106 0.36 863 309 Middle Atlantic 6.3 4.1 11.5 142 50 91.5 32 1,191 0.42 769 272 Midwest 2.4 2.1 4.8 74 33 66.2 24 609 0.27 548 202 East

  7. oil1993.xls

    Gasoline and Diesel Fuel Update (EIA)

    (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 Region and Division Northeast 7.9 5.9 17.2 133 45 98.7 36 854 0.29 636 234 New England 2.8 2.4 6.6 125 45 105.6 40 819 0.30 691 262 Middle Atlantic 5.0 3.5 10.6 138 45 94.8 34 878 0.29 605 219 Midwest 2.3 2.2 6.0 60 22 58.4 21 378 0.14 370 132

  8. national-lab-research-network | netl.doe.gov

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

    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 51.6 39.7 88.5 125 56 96.2 34 497 0.22 383 137 Census Region and Division Northeast 10.9 6.5 18.8 144 50 86.6 31 771 0.27 463 168 New England 1.9 0.9 3.1 162 47 78.9 28 971 0.28 472 169 Middle Atlantic 9.0 5.6 15.7 141 51 88.1 32 739 0.27 461 168 Midwest 15.5 12.4 29.4 164 70 131.6 46 586 0.25 470 165

  9. Doppler characteristics of sea clutter.

    SciTech Connect (OSTI)

    Raynal, Ann Marie; Doerry, Armin Walter

    2010-06-01

    Doppler radars can distinguish targets from clutter if the target's velocity along the radar line of sight is beyond that of the clutter. Some targets of interest may have a Doppler shift similar to that of clutter. The nature of sea clutter is different in the clutter and exo-clutter regions. This behavior requires special consideration regarding where a radar can expect to find sea-clutter returns in Doppler space and what detection algorithms are most appropriate to help mitigate false alarms and increase probability of detection of a target. This paper studies the existing state-of-the-art in the understanding of Doppler characteristics of sea clutter and scattering from the ocean to better understand the design and performance choices of a radar in differentiating targets from clutter under prevailing sea conditions.

  10. Tier identification (TID) for tiered memory characteristics

    DOE Patents [OSTI]

    Chang, Jichuan; Lim, Kevin T; Ranganathan, Parthasarathy

    2014-03-25

    A tier identification (TID) is to indicate a characteristic of a memory region associated with a virtual address in a tiered memory system. A thread may be serviced according to a first path based on the TID indicating a first characteristic. The thread may be serviced according to a second path based on the TID indicating a second characteristic.

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

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

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

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

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

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

  13. BIOENERGIZEME INFOGRAPHIC CHALLENGE: Biomass: Types/Characteristics |

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

    Department of Energy Biomass: Types/Characteristics BIOENERGIZEME INFOGRAPHIC CHALLENGE: Biomass: Types/Characteristics BIOENERGIZEME INFOGRAPHIC CHALLENGE: Biomass: Types/Characteristics This infographic was created by students from Albany Academies and Academy of the Holy Names in Albany, NY, as part of the U.S. Department of Energy-BioenergizeME Infographic Challenge. The BioenergizeME Infographic Challenge encourages young people to improve their foundational understanding of bioenergy,

  14. Fracture characteristics and their relationships to producing...

    Open Energy Info (EERE)

    characteristics and their relationships to producing zones in deep wells, Raft River geothermal area Jump to: navigation, search OpenEI Reference LibraryAdd to library Book:...

  15. DERIVATION OF STOCHASTIC ACCELERATION MODEL CHARACTERISTICS FOR...

    Office of Scientific and Technical Information (OSTI)

    FOR SOLAR FLARES FROM RHESSI HARD X-RAY OBSERVATIONS Citation Details In-Document Search Title: DERIVATION OF STOCHASTIC ACCELERATION MODEL CHARACTERISTICS FOR SOLAR FLARES ...

  16. 1999 Commercial Buildings Characteristics--Year Constructed

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

    (202) 586-8800. Energy Information Administration Commercial Buildings Energy Consumption Survey Top Return to: "1999 CBECS-Commercial Buildings Characteristics" Specific questions...

  17. 1999 Commercial Buildings Characteristics--Building Size

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

    (202) 586-8800. Energy Information Administration Commercial Buildings Energy Consumption Survey Top Return to: "1999 CBECS-Commercial Buildings Characteristics" Specific questions...

  18. 1999 Commercial Buildings Characteristics--Disaggregated Principal...

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

    (202) 586-8800. Energy Information Administration Commercial Buildings Energy Consumption Survey Top Return to: "1999 CBECS-Commercial Buildings Characteristics" Specific questions...

  19. Figure 1. Census Regions and Divisions

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

    North Carolina, South Carolina, Tennessee Region 5 Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin Region 6 Arkansas, Louisiana, New Mexico, Oklahoma, Texas Region 7 ...

  20. " Generation by Census Region, Industry Group,...

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

    ... Processes",531,8,19,464,41,13.7 ," Recycling of Materials",1381,59,199,1087,36,5.9 ," ... Catalytic Processes",0,0,0,0,0,"NF" ," Recycling of Materials","W",0,"*","W",1,23 ," ...

  1. " by Type of Supplier, Census Region...

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

    Column Factors:",0.5,1.1,1.2,1.5 , 20,"Food and Kindred Products",0.054,0.075,3.8,2.61... ,"RSE Column Factors:",0.5,1,1.2,1.6 , 20,"Food and Kindred Products",0.072," W ...

  2. " Electricity Generation by Census Region, Industry...

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

    ...,0.6,0.6,1.3,1.3,0.7,1.2,1.2,1.6,1.2 , 20,"Food and Kindred Products",922,172,27,17,512,5,...:",0.7,0.7,1,1.2,0.8,1.2,1.3,1.4,1.1 , 20,"Food and Kindred Products",79,19,7,5,42,1,2,0,3...

  3. " Electricity Generation by Census Region, Industry...

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

    ...,"Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","LPG","(1000","(1000","Other(e)","Row" ...

  4. R93HC.PDF

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

    a. Space Heating by Census Region and Climate Zone, Million U.S. Households, 1993 Space Heating Characteristics RSE Column Factor: Total Census Region Climate Zone RSE Row Factors Northeast Midwest South West Fewer than 2,000 CDD and -- More than 2,000 CDD and Few- er than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Few- er than 4,000 HDD 0.5 0.9 1.1 0.8 0.8 1.6 1.3 1.2 1.2 1.1 Total ................................................. 96.6 19.5 23.3 33.5 20.4 8.7 26.5 22.5

  5. R93HC.PDF

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

    6a. Appliances by Census Region and Climate Zone, Million U.S. Households, 1993 Appliance Types and Characteristics RSE Column Factor: Total Census Region Climate Zone RSE Row Factors Northeast Midwest South West Fewer than 2,000 CDD and -- More than 2,000 CDD and Few- er than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Few- er than 4,000 HDD 0.4 0.9 0.8 0.7 0.8 2.3 1.3 1.3 1.4 1.1 Total ..................................................... 96.6 19.5 23.3 33.5 20.4 8.7

  6. R93HC.PDF

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

    Table 3.7a. Space Heating by Census Region and Climate Zone, Million U.S. Households, 1993 Space Heating Characteristics RSE Column Factor: Total Census Region Climate Zone RSE Row Factors Northeast Midwest South West Fewer than 2,000 CDD and -- More than 2,000 CDD and Few- er than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Few- er than 4,000 HDD 0.5 0.9 1.1 0.8 0.8 1.6 1.3 1.2 1.2 1.1 Total ................................................. 96.6 19.5 23.3 33.5 20.4 8.7

  7. RACORO Forecasting

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

    7a. Space Heating by Census Region and Climate Zone, Million U.S. Households, 1993 Space Heating Characteristics RSE Column Factor: Total Census Region Climate Zone RSE Row Factors Northeast Midwest South West Fewer than 2,000 CDD and -- More than 2,000 CDD and Few- er than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Few- er than 4,000 HDD 0.5 0.9 1.1 0.8 0.8 1.6 1.3 1.2 1.2 1.1 Total ................................................. 96.6 19.5 23.3 33.5 20.4 8.7 26.5

  8. Buildings Energy Data Book: 2.2 Residential Sector Characteristics

    Buildings Energy Data Book [EERE]

    6 Residential Heated Floorspace, as of 2005 (Percent of Total Households) Floorspace (SF) Fewer than 500 6% 500 to 999 26% 1,000 to 1,499 24% 1,500 to 1,999 16% 2,000 to 2,499 9% 2,500 to 2,999 7% 3,000 or more 11% Total 100% Source(s): EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table HC1-3.

  9. 1997 Housing Characteristics Tables Housing Unit Tables

    Gasoline and Diesel Fuel Update (EIA)

    Contact: Robert Latta, Survey Manager (rlatta@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC1-1a. Housing Unit Characteristics by Climate Zone, ...

  10. Principal Characteristics of a Modern Grid

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

    ... Office of Electricity Delivery and Energy Reliability MODERN GRID S T R A T E G Y Characteristics of the Modern Grid It will "Provide power quality for 21 st century needs" Power ...

  11. NREL: Wind Research - Site Wind Resource Characteristics

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

    Site Wind Resource Characteristics A graphic showing the location of National Wind Technology Center and its wind power class 2. Click on the image to view a larger version. ...

  12. LANDS WITH WILDERNESS CHARACTERISTICS, RESOURCE MANAGEMENT PLAN

    Office of Scientific and Technical Information (OSTI)

    CONSTRAINTS, AND LAND EXCHANGES: CROSS-JURISDICTIONAL MANAGEMENT AND IMPACTS ON UNCONVENTIONAL FUEL DEVELOPMENT IN UTAH'S UINTA BASIN (Technical Report) | SciTech Connect LANDS WITH WILDERNESS CHARACTERISTICS, RESOURCE MANAGEMENT PLAN CONSTRAINTS, AND LAND EXCHANGES: CROSS-JURISDICTIONAL MANAGEMENT AND IMPACTS ON UNCONVENTIONAL FUEL DEVELOPMENT IN UTAH'S UINTA BASIN Citation Details In-Document Search Title: LANDS WITH WILDERNESS CHARACTERISTICS, RESOURCE MANAGEMENT PLAN CONSTRAINTS, AND

  13. LANDS WITH WILDERNESS CHARACTERISTICS, RESOURCE MANAGEMENT PLAN

    Office of Scientific and Technical Information (OSTI)

    CONSTRAINTS, AND LAND EXCHANGES: CROSS-JURISDICTIONAL MANAGEMENT AND IMPACTS ON UNCONVENTIONAL FUEL DEVELOPMENT IN UTAH'S UINTA BASIN (Technical Report) | SciTech Connect LANDS WITH WILDERNESS CHARACTERISTICS, RESOURCE MANAGEMENT PLAN CONSTRAINTS, AND LAND EXCHANGES: CROSS-JURISDICTIONAL MANAGEMENT AND IMPACTS ON UNCONVENTIONAL FUEL DEVELOPMENT IN UTAH'S UINTA BASIN Citation Details In-Document Search Title: LANDS WITH WILDERNESS CHARACTERISTICS, RESOURCE MANAGEMENT PLAN CONSTRAINTS, AND

  14. Direct and indirect effect of changes in family structure and lifestyle upon energy consumption, 1950-1080

    SciTech Connect (OSTI)

    Stever, C.J.

    1985-01-01

    This research project examines both the direct and indirect influence of changes in family structure and lifestyle dimensions upon residential energy consumption patterns from 1950 to 1980. These relationships are investigated on a macro level using three national energy surveys administered from 1974 to 1980 and the Census Bureau and other government sources of documenting changes in social characteristics and energy consumption levels over thirty years. Stage I looks at changes in residential consumption from 1950 to 1980 and conservation behavior from 1965 to 1980. The objective of Stage II is to identify those family structure and lifestyle characteristics that constrain conservation measures in which a household engages. Stage III examines the commonly held assumption that investment in conservation equipment will result in reduced consumption. Stage IV explores the potential influence that changes in structural and lifestyle characteristics of householders may have upon average consumption levels from 1950 to 1980. The primary implications of this study are: (1) in order to obtain a complete picture of the current energy situation, it is necessary to examine consumption and conservation behavior both before and after the 1973 oil embargo, and (2) changes in social structural and lifestyle of households over time appear to have contributed as much, if not more, to reduce consumption in the late 1970s as did conscious conservation efforts by householders.

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

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

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

  16. Superconducting wire with improved strain characteristics

    DOE Patents [OSTI]

    Luhman, Thomas; Klamut, Carl J.; Suenaga, Masaki; Welch, David

    1982-01-01

    A superconducting wire comprising a superconducting filament and a beryllium strengthened bronze matrix in which the addition of beryllium to the matrix permits a low volume matrix to exhibit reduced elastic deformation after heat treating which increases the compression of the superconducting filament on cooling and thereby improves the strain characteristics of the wire.

  17. Superconducting wire with improved strain characteristics

    DOE Patents [OSTI]

    Luhman, Thomas; Klamut, Carl J.; Suenaga, Masaki; Welch, David

    1982-01-01

    A superconducting wire comprising a superconducting filament and a beryllium strengthened bronze matrix in which the addition of beryllium to the matrix permits a low volume matrix to exhibit reduced elastic deformation after heat treating which increases the compression of the superconducting filament on cooling and thereby improve the strain characteristics of the wire.

  18. Superconducting wire with improved strain characteristics

    DOE Patents [OSTI]

    Luhman, T.; Klamut, C.J.; Suenaga, M.; Welch, D.

    1979-12-19

    A superconducting wire comprising a superconducting filament and a beryllium strengthened bronze matrix in which the addition of beryllium to the matrix permits a low volume matrix to exhibit reduced elastic deformation after heat treating which increases the compression of the superconducting filament on cooling and thereby improve the strain characteristics of the wire.

  19. Primary Characteristics of Loan Loss Reserve Funds | Department...

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

    Primary Characteristics of Loan Loss Reserve Funds Primary Characteristics of Loan Loss ... Typical residential energy efficiency loans, for example, are in the range of 5,000 to ...

  20. Characteristics of seismic waves from Soviet peaceful nuclear...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Characteristics of seismic waves from Soviet peaceful nuclear explosions in salt Citation Details In-Document Search Title: Characteristics of seismic waves from...

  1. Plant Root Characteristics and Dynamics in Arctic Tundra Ecosystems...

    Office of Scientific and Technical Information (OSTI)

    Dataset: Plant Root Characteristics and Dynamics in Arctic Tundra Ecosystems, 1960-2012 Citation Details In-Document Search Title: Plant Root Characteristics and Dynamics in Arctic...

  2. Gas Electron Multiplier (GEM) Chamber Characteristics Test (Technical...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Gas Electron Multiplier (GEM) Chamber Characteristics Test Citation Details In-Document Search Title: Gas Electron Multiplier (GEM) Chamber Characteristics Test ...

  3. Origins of optical absorption characteristics of Cu2+ complexes...

    Office of Scientific and Technical Information (OSTI)

    Origins of optical absorption characteristics of Cu2+ complexes in solutions Citation Details In-Document Search Title: Origins of optical absorption characteristics of Cu2+ ...

  4. A comparison between characteristics of atmospheric-pressure...

    Office of Scientific and Technical Information (OSTI)

    A comparison between characteristics of atmospheric-pressure plasma jets sustained by ... Title: A comparison between characteristics of atmospheric-pressure plasma jets sustained ...

  5. Spectral characteristics of time resolved magnonic spin Seebeck...

    Office of Scientific and Technical Information (OSTI)

    Spectral characteristics of time resolved magnonic spin Seebeck effect Citation Details In-Document Search Title: Spectral characteristics of time resolved magnonic spin Seebeck ...

  6. Oxidation characteristics of gasoline direct-injection (GDI)...

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

    characteristics of gasoline direct-injection (GDI) engine soot: Catalytic effects of ash and modified kinetic correlation Title Oxidation characteristics of gasoline...

  7. http://2010.census.gov/2010census/data/apportionment-dens-text...

    National Nuclear Security Administration (NNSA)

    ... Density Rank 10 10 10 10 10 10 11 11 11 11 12 Oklahoma Population 1,657,155 2,028,283 2,396,040 2,336,434 2,233,351 2,328,284 2,559,229 3,025,290 3,145,585 3,450,654 3,751,351 ...

  8. Characteristics of potential repository wastes. Volume 1

    SciTech Connect (OSTI)

    Not Available

    1992-07-01

    This document, and its associated appendices and microcomputer (PC) data bases, constitutes the reference OCRWM data base of physical and radiological characteristics data of radioactive wastes. This Characteristics Data Base (CDB) system includes data on spent nuclear fuel and high-level waste (HLW), which clearly require geologic disposal, and other wastes which may require long-term isolation, such as sealed radioisotope sources. The data base system was developed for OCRWM by the CDB Project at Oak Ridge National Laboratory. Various principal or official sources of these data provided primary information to the CDB Project which then used the ORIGEN2 computer code to calculate radiological properties. The data have been qualified by an OCRWM-sponsored peer review as suitable for quality-affecting work meeting the requirements of OCRWM`s Quality Assurance Program. The wastes characterized in this report include: light-water reactor (LWR) spent fuel and immobilized HLW.

  9. Measuring spatial variability in soil characteristics

    DOE Patents [OSTI]

    Hoskinson, Reed L.; Svoboda, John M.; Sawyer, J. Wayne; Hess, John R.; Hess, J. Richard

    2002-01-01

    The present invention provides systems and methods for measuring a load force associated with pulling a farm implement through soil that is used to generate a spatially variable map that represents the spatial variability of the physical characteristics of the soil. An instrumented hitch pin configured to measure a load force is provided that measures the load force generated by a farm implement when the farm implement is connected with a tractor and pulled through or across soil. Each time a load force is measured, a global positioning system identifies the location of the measurement. This data is stored and analyzed to generate a spatially variable map of the soil. This map is representative of the physical characteristics of the soil, which are inferred from the magnitude of the load force.

  10. Forward and reverse characteristics of irradiated MOSFETs

    SciTech Connect (OSTI)

    Paccagnella, A.; Ceschia, M.; Verzellesi, G.; Dalla Betta, G.F.; Soncini, G.; Bellutti, P.; Fuochi, P.G.

    1996-06-01

    pMOSFETs biased with V{sub gs} < V{sub gd} during Co{sup 60} {gamma} irradiation have shown substantial differences between the forward and reverse subthreshold characteristics, induced by a non-uniform charge distribution in the gate oxide. Correspondingly, modest differences have been observed in the over-threshold I-V characteristics. After irradiation, the forward subthreshold curves can shift at higher or lower gate voltages than the reverse ones. The former behavior has been observed in long-channel devices, in agreement with the classical MOS theory and numerical simulations. The latter result has been obtained in short-channel devices, and it has been correlated to a parasitic punch-through conduction mechanism.

  11. Wafer characteristics via reflectometry - Energy Innovation Portal

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

    15,862 Site Map Printable Version Share this resource About Search Categories (15) Advanced Materials Biomass and Biofuels Building Energy Efficiency Electricity Transmission Energy Analysis Energy Storage Geothermal Hydrogen and Fuel Cell Hydropower, Wave and Tidal Industrial Technologies Solar Photovoltaic Solar Thermal Startup America Vehicles and Fuels Wind Energy Partners (27) Visual Patent Search Success Stories Find More Like This Return to Search Wafer characteristics via reflectometry

  12. Wafer characteristics via reflectometry - Energy Innovation Portal

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

    063262 Site Map Printable Version Share this resource About Search Categories (15) Advanced Materials Biomass and Biofuels Building Energy Efficiency Electricity Transmission Energy Analysis Energy Storage Geothermal Hydrogen and Fuel Cell Hydropower, Wave and Tidal Industrial Technologies Solar Photovoltaic Solar Thermal Startup America Vehicles and Fuels Wind Energy Partners (27) Visual Patent Search Success Stories Return to Search Wafer characteristics via reflectometry United States Patent

  13. Buildings Energy Data Book: 2.2 Residential Sector Characteristics

    Buildings Energy Data Book [EERE]

    1 Total Number of Households and Buildings, Floorspace, and Household Size, by Year 1980 80 N.A. 227 2.9 1981 83 N.A. 229 2.8 1982 84 N.A. 232 2.8 1983 85 N.A. 234 2.8 1984 86 N.A. 236 2.7 1985 88 N.A. 238 2.7 1986 89 N.A. 240 2.7 1987 91 N.A. 242 2.7 1988 92 N.A. 244 2.7 1989 93 N.A. 247 2.6 1990 94 N.A. 250 2.6 1991 95 N.A. 253 2.7 1992 96 N.A. 257 2.7 1993 98 N.A. 260 2.7 1994 99 N.A. 263 2.7 1995 100 N.A. 266 2.7 1996 101 N.A. 269 2.7 1997 102 N.A. 273 2.7 1998 104 N.A. 276 2.7 1999 105 N.A.

  14. Building and occupant characteristics as determinants of residential energy consumption

    SciTech Connect (OSTI)

    Nieves, L.A.; Nieves, A.L.

    1981-10-01

    The major goals of the research are to gain insight into the probable effects of building energy performance standards on energy consumption; to obtain observations of actual residential energy consumption that could affirm or disaffirm comsumption estimates of the DOE 2.0A simulation model; and to investigate home owner's conservation investments and home purchase decisions. The first chapter covers the investigation of determinants of household energy consumption. The presentation begins with the underlying economic theory and its implications, and continues with a description of the data collection procedures, the formulation of variables, and then of data analysis and findings. In the second chapter the assumptions and limitations of the energy use projections generated by the DOE 2.0A model are discussed. Actual electricity data for the houses are then compared with results of the simulation. The third chapter contains information regarding households' willingness to make energy conserving investments and their ranking of various conservation features. In the final chapter conclusions and recommendations are presented with an emphasis on the policy implications of this study. (MCW)

  15. Coal-water slurry atomization characteristics

    SciTech Connect (OSTI)

    Caton, J.A.; Kihm, K.D.

    1994-04-01

    The overall objective of this work was to fully characterize the CWS fuel sprays of a medium-speed diesel engine injection system. Specifically, the spray plume penetration as a function of time was determined for a positive-displacement fuel injection system. The penetration was determined as a function of orifice diameter, coal loading, gas density in the engine, and fuel line pressure. Preliminary droplet information also was obtained. The results of this study will assist CWS engine development by providing much needed insight about the fuel spray. In addition, the results will aid the development and use of CWS engine cycle simulations which require information on the fuel spray characteristics.

  16. homeoffice_household2001.pdf

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

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

  17. spaceheat_household2001.pdf

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

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

  18. ac_household2001.pdf

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

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

  19. spaceheat_household2001.pdf

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

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

  20. ac_household2001.pdf

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

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

  1. spaceheat_household2001.pdf

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

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

  2. ac_household2001.pdf

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

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

  3. appl_household2001.pdf

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

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

  4. appl_household2001.pdf

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

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

  5. appl_household2001.pdf

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

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

  6. appl_household2001.pdf

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

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

  7. appl_household2001.pdf

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

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

  8. appl_household2001.pdf

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

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

  9. appl_household2001.pdf

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

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

  10. appl_household2001.pdf

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

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

  11. appl_household2001.pdf

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

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

  12. appl_household2001.pdf

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

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

  13. appl_household2001.pdf

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

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

  14. appl_household2001.pdf

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

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

  15. appl_household2001.pdf

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

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

  16. 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)...

  17. 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...

  18. spaceheat_household2001.pdf

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

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

  19. 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...

  20. 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)...

  1. 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...

  2. ac_household2001.pdf

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

    Contact: Stephanie J. Battles, Survey Manager (stephanie.battles@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC4-1a. Air Conditioning by Climate ...

  3. 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 ...

  4. char_household2001.pdf

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

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

  5. 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 ...

  6. 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 ...

  7. 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 ...

  8. 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 ...

  9. 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 ...

  10. char_household2001.pdf

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

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

  11. char_household2001.pdf

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

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

  12. 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 ...

  13. 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 ...

  14. homeoffice_household2001.pdf

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

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

  15. ac_household2001.pdf

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

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

  16. Household Vehicles Energy Consumption 1991

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

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

  17. 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...

  18. 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...

  19. 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...

  20. spaceheat_household2001.pdf

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

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

  1. spaceheat_household2001.pdf

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

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

  2. spaceheat_household2001.pdf

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

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

  3. Characteristics of transverse waves in chromospheric mottles

    SciTech Connect (OSTI)

    Kuridze, D.; Mathioudakis, M.; Jess, D. B.; Keenan, F. P. [Astrophysics Research Center, School of Mathematics and Physics, Queen's University, Belfast BT7 1NN (United Kingdom); Verth, G.; Erdlyi, R. [Solar Physics and Space Plasma Research Center (SP2RC), University of Sheffield, Hicks Building, Hounsfield Road, Sheffield S3 7RH (United Kingdom); Morton, R. J. [Mathematics and Information Science, Northumbria University, Camden Street, Newcastle Upon Tyne NE1 8ST (United Kingdom); Christian, D. J., E-mail: dkuridze01@qub.ac.uk [Department of Physics and Astronomy, California State University, Northridge, CA 91330 (United States)

    2013-12-10

    Using data obtained by the high temporal and spatial resolution Rapid Oscillations in the Solar Atmosphere instrument on the Dunn Solar Telescope, we investigate at an unprecedented level of detail transverse oscillations in chromospheric fine structures near the solar disk center. The oscillations are interpreted in terms of propagating and standing magnetohydrodynamic kink waves. Wave characteristics including the maximum transverse velocity amplitude and the phase speed are measured as a function of distance along the structure's length. Solar magnetoseismology is applied to these measured parameters to obtain diagnostic information on key plasma parameters (e.g., magnetic field, density, temperature, flow speed) of these localized waveguides. The magnetic field strength of the mottle along the ?2 Mm length is found to decrease by a factor of 12, while the local plasma density scale height is ?280 80 km.

  4. Gas sensor with attenuated drift characteristic

    DOE Patents [OSTI]

    Chen, Ing-Shin [Danbury, CT; Chen, Philip S. H. [Bethel, CT; Neuner, Jeffrey W. [Bethel, CT; Welch, James [Fairfield, CT; Hendrix, Bryan [Danbury, CT; Dimeo, Jr., Frank [Danbury, CT

    2008-05-13

    A sensor with an attenuated drift characteristic, including a layer structure in which a sensing layer has a layer of diffusional barrier material on at least one of its faces. The sensor may for example be constituted as a hydrogen gas sensor including a palladium/yttrium layer structure formed on a micro-hotplate base, with a chromium barrier layer between the yttrium layer and the micro-hotplate, and with a tantalum barrier layer between the yttrium layer and an overlying palladium protective layer. The gas sensor is useful for detection of a target gas in environments susceptible to generation or incursion of such gas, and achieves substantial (e.g., >90%) reduction of signal drift from the gas sensor in extended operation, relative to a corresponding gas sensor lacking the diffusional barrier structure of the invention

  5. " Million Housing Units, Final"

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

    9 Household Demographics of Homes in Midwest Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Midwest Census Region" ,,,"East North Central Census Division",,,,,"West North Central Census Division" ,,,"Total East North Central",,,,,"Total West North Central" ,"Total U.S.1 (millions)" ,,"Total Midwest",,,,," IN, OH",,,"IA, MN, ND, SD" "Household

  6. Buildings Energy Data Book: 2.2 Residential Sector Characteristics

    Buildings Energy Data Book [EERE]

    2 Share of Households, by Housing Type and Type of Ownership, as of 2005 (Percent) Housing Type Owned Rented Total Single-Family: 61.5% 10.3% 71.7% Detached 57.7% 7.2% 64.9% Attached 3.8% 3.1% 6.8% Multi-Family: 3.7% 18.3% 22.0% 2 to 4 units 1.6% 5.3% 6.9% 5 or more units 2.1% 13.0% 15.0% Mobile Homes 5.1% 1.1% 6.2% Total 70.3% 29.6% 100% Source(s): EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table HC3-1 and HC4

  7. Table A27. Quantity of Purchased Electricity, Steam, and Natural...

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

    Type" " of Supplier, Census Region, and Economic Characteristics of the Establishment," ...,"Utility","Transmission","Other","Row" "Economic Characteristics(a)","Supplier(b)","Suppl...

  8. "Table A48. Total Expenditures for Purchased Electricity,...

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

    by Type of Supplier, Census Region, and Economic Characteristics of the" " Establishment, ...,"Utility","Transmission","Other","Row" "Economic Characteristics(a)","Supplier(b)","Suppl...

  9. Table A13. Total Consumption of Offsite-Produced Energy for...

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

    Generation by Census Region and Economic Characteristics of the" " Establishment, ...,"LPG","(1000","(1000","Other(e)","Row" "Economic Characteristics(a)","(trillion ...

  10. "Table A49. Average Prices of Purchased Electricity, Steam...

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

    by Type of Supplier, Census Region, and Economic Characteristics of the" " Establishment, ...,"Utility","Transmission","Other","Row" "Economic Characteristics(a)","Supplier(b)","Suppl...

  11. "Table A15. Selected Energy Operating Ratios for Total Energy...

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

    Generation by Census Region and Economic" " Characteristics of the Establishment, ... Consumption","of Natural Gas","Row" "Economic Characteristics(a)","(million ...

  12. Foaming characteristics of refigerant/lubricant mixtures

    SciTech Connect (OSTI)

    Goswami, D.Y.; Shah, D.O.; Jotshi, C.K.; Bhagwat, S.; Leung, M.; Gregory, A.

    1997-04-01

    The air-conditioning and refrigeration industry has moved to HFC refrigerants which have zero ozone depletion and low global warming potential due to regulations on CFC and HCFC refrigerants and concerns for the environment. The change in refrigerants has prompted the switch from mineral oil and alkylbenzene lubricants to polyolester-based lubricants. This change has also brought about a desire for lubricant, refrigerant and compressor manufacturers to understand the foaming properties of alternative refrigerant/ lubricant mixtures, as well as the mechanisms which affect these properties. The objectives of this investigation are to experimentally determine the foaming absorption and desorption rates of HFC and blended refrigerants in polyolester lubricant and to define the characteristics of the foam formed when the refrigerant leaves the refrigerant/ lubricant mixture after being exposed to a pressure drop. The refrigerants being examined include baseline refrigerants: CFC-12 (R-12) and HCFC-22 (R-22); alternative refrigerants: HFC-32 (R-32), R-125, R-134a, and R-143a; and blended refrigerants: R-404A, R-407C, and R-410A. The baseline refrigerants are tested with ISO 32 (Witco 3GS) and ISO 68 (4GS) mineral oils while the alternative and blended refrigerants are tested with two ISO 68 polyolesters (Witco SL68 and ICI RL68H).

  13. " Million Housing Units, Final"

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

    0 Household Demographics of Homes in South Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"South Census Region" ,,,"South Atlantic Census Division",,,,,,"East South Central Census Division",,,"West South Central Census Division" ,,,,,,,,,"Total East South Central",,,"Total West South Central" ,"Total U.S.1 (millions)",,"Total South Atlantic" ,,"Total

  14. Sooting characteristics of surrogates for jet fuels

    SciTech Connect (OSTI)

    Mensch, Amy; Santoro, Robert J.; Litzinger, Thomas A.; Lee, S.-Y.

    2010-06-15

    Currently, modeling the combustion of aviation fuels, such as JP-8 and JetA, is not feasible due to the complexity and compositional variation of these practical fuels. Surrogate fuel mixtures, composed of a few pure hydrocarbon compounds, are a key step toward modeling the combustion of practical aviation fuels. For the surrogate to simulate the practical fuel, the composition must be designed to reproduce certain pre-designated chemical parameters such as sooting tendency, H/C ratio, autoignition, as well as physical parameters such as boiling range and density. In this study, we focused only on the sooting characteristics based on the Threshold Soot Index (TSI). New measurements of TSI values derived from the smoke point along with other sooting tendency data from the literature have been combined to develop a set of recommended TSI values for pure compounds used to make surrogate mixtures. When formulating the surrogate fuel mixtures, the TSI values of the components are used to predict the TSI of the mixture. To verify the empirical mixture rule for TSI, the TSI values of several binary mixtures of candidate surrogate components were measured. Binary mixtures were also used to derive a TSI for iso-cetane, which had not previously been measured, and to verify the TSI for 1-methylnaphthalene, which had a low smoke point and large relative uncertainty as a pure compound. Lastly, surrogate mixtures containing three components were tested to see how well the measured TSI values matched the predicted values, and to demonstrate that a target value for TSI can be maintained using various components, while also holding the H/C ratio constant. (author)

  15. 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...

  16. 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...

  17. 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...

  18. Effects of Ion Beam on Nanoindentation Characteristics of Glassy Polymeric

    Office of Scientific and Technical Information (OSTI)

    Carbon Surface (Journal Article) | SciTech Connect Effects of Ion Beam on Nanoindentation Characteristics of Glassy Polymeric Carbon Surface Citation Details In-Document Search Title: Effects of Ion Beam on Nanoindentation Characteristics of Glassy Polymeric Carbon Surface Glassy polymeric carbon (GPC) is a useful material for medical applications due to its chemical inertness and biocompatible characteristics. Mitral and aortic and hydrocephalic valves are examples of GPC prosthetic devices

  19. 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

  20. 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

  1. Cluster Analysis of Cloud Regimes and Characteristic Dynamics...

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

    Cluster Analysis of Cloud Regimes and Characteristic Dynamics of Mid-Latitude Synoptic Systems N. D. Gordon and J. R. Norris Scripps Institution of Oceanography University of ...

  2. Current-voltage characteristics of organic heterostructure devices...

    Office of Scientific and Technical Information (OSTI)

    Current-voltage characteristics of organic heterostructure devices with insulating spacer ... Visit OSTI to utilize additional information resources in energy science and technology. A ...

  3. Receiver Operating Characteristic (ROC) Curves: An Analysis Tool...

    Office of Scientific and Technical Information (OSTI)

    for Detection Performance Citation Details In-Document Search Title: Receiver Operating Characteristic (ROC) Curves: An Analysis Tool for Detection Performance You are ...

  4. Differences in the Physical Characteristics of Diesel PM with...

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

    characteristics, carbon state, and surface bound oxygen of soot from biodiesel blends. ... Technologies Trends in Particulate Nanostructure DPF Performance with Biodiesel Blends

  5. Receiver Operating Characteristic (ROC) Curves: An Analysis Tool...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Receiver Operating Characteristic (ROC) Curves: An Analysis Tool for Detection Performance Citation Details In-Document Search Title: Receiver Operating ...

  6. Understanding Fault Characteristics And Sediment Depth For Geothermal...

    Open Energy Info (EERE)

    Understanding Fault Characteristics And Sediment Depth For Geothermal Exploration Using 3D Gravity Inversion In Walker Valley, Nevada Jump to: navigation, search OpenEI Reference...

  7. Characteristics and Effects of Lubricant Additive Chemistry and...

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

    Service Life and Vehicle Fuel Economy Characteristics and Effects of Lubricant Additive Chemistry and Exhaust Conditions on Diesel Particulate Filter Service Life and Vehicle ...

  8. Thermal Hydraulic Characteristics of Fuel Defects in Plate Type...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Thermal Hydraulic Characteristics of Fuel Defects in Plate Type Nuclear Research Reactors Citation Details In-Document Search Title: Thermal Hydraulic ...

  9. Effects of discharge voltage waveform on the discharge characteristics...

    Office of Scientific and Technical Information (OSTI)

    atmospheric plasma jet Citation Details In-Document Search Title: Effects of discharge voltage waveform on the discharge characteristics in a helium atmospheric plasma jet We ...

  10. Thermal Hydraulic Characteristics of Fuel Defects in Plate Type...

    Office of Scientific and Technical Information (OSTI)

    Title: Thermal Hydraulic Characteristics of Fuel Defects in Plate Type Nuclear Research Reactors Turbulent flow coupled with heat transfer is investigated for a High Flux Isotope ...

  11. The Nevada railroad system: Physical, operational, and accident characteristics

    SciTech Connect (OSTI)

    1991-09-01

    This report provides a description of the operational and physical characteristics of the Nevada railroad system. To understand the dynamics of the rail system, one must consider the system`s physical characteristics, routing, uses, interactions with other systems, and unique operational characteristics, if any. This report is presented in two parts. The first part is a narrative description of all mainlines and major branchlines of the Nevada railroad system. Each Nevada rail route is described, including the route`s physical characteristics, traffic type and volume, track conditions, and history. The second part of this study provides a more detailed analysis of Nevada railroad accident characteristics than was presented in the Preliminary Nevada Transportation Accident Characterization Study (DOE, 1990).

  12. Chemical and light-stable isotope characteristics of waters from...

    Open Energy Info (EERE)

    light-stable isotope characteristics of waters from the raft river geothermal area and environs, Cassia County, Idaho, Box Elder county, Utah Jump to: navigation, search OpenEI...

  13. Fact #800: October 21, 2013 Characteristics of New Light Vehicles...

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

    Fact 800: October 21, 2013 Characteristics of New Light Vehicles over Time From model years 1980 to 2012, there have been significant gains in automotive technology. For new light ...

  14. A molecular dynamics investigation of the diffusion characteristics...

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

    137, 83-91 (2011) DOI: 10.1016j.micromeso.2010.08.026 Full-size image (36 K) Abstract: Molecular dynamics (MD) simulations are used to investigate the diffusion characteristics...

  15. Fully Ceramic Microencapsulated Fuels: Characteristics and Potential LWR

    Office of Scientific and Technical Information (OSTI)

    Applications (Conference) | SciTech Connect Fully Ceramic Microencapsulated Fuels: Characteristics and Potential LWR Applications Citation Details In-Document Search Title: Fully Ceramic Microencapsulated Fuels: Characteristics and Potential LWR Applications Authors: Powers, Jeffrey J [1] ; Worrall, Andrew [1] ; Terrani, Kurt A [1] ; Gehin, Jess C [1] ; Snead, Lance Lewis [1] + Show Author Affiliations ORNL Publication Date: 2014-01-01 OSTI Identifier: 1159469 DOE Contract Number:

  16. Integrated MOSFET-Embedded-Cantilever-Based Biosensor Characteristic for

    Office of Scientific and Technical Information (OSTI)

    Detection of Anthrax Simulant (Journal Article) | SciTech Connect Integrated MOSFET-Embedded-Cantilever-Based Biosensor Characteristic for Detection of Anthrax Simulant Citation Details In-Document Search Title: Integrated MOSFET-Embedded-Cantilever-Based Biosensor Characteristic for Detection of Anthrax Simulant In this work, MOSFET-embedded cantilevers are configured as microbial sensors for detection of anthrax simulants, Bacillus thuringiensis. Anthrax simulants attached to the

  17. Measurement Of Gas Electron Multiplier (GEM) Detector Characteristics

    Office of Scientific and Technical Information (OSTI)

    (Journal Article) | SciTech Connect Measurement Of Gas Electron Multiplier (GEM) Detector Characteristics Citation Details In-Document Search Title: Measurement Of Gas Electron Multiplier (GEM) Detector Characteristics The High Energy Physics group of the University of Texas at Arlington has been developing gas electron multiplier detectors to use them as sensitive gap detectors in digital hadron calorimeters for the International Linear Collider, a future high energy particle accelerator.

  18. Statistical characteristics of cloud variability. Part 2: Implication for

    Office of Scientific and Technical Information (OSTI)

    parameterizations of microphysical and radiative transfer processes in climate models (Journal Article) | SciTech Connect Statistical characteristics of cloud variability. Part 2: Implication for parameterizations of microphysical and radiative transfer processes in climate models Citation Details In-Document Search Title: Statistical characteristics of cloud variability. Part 2: Implication for parameterizations of microphysical and radiative transfer processes in climate models The effects

  19. Thermal Hydraulic Characteristics of Fuel Defects in Plate Type Nuclear

    Office of Scientific and Technical Information (OSTI)

    Research Reactors (Technical Report) | SciTech Connect Thermal Hydraulic Characteristics of Fuel Defects in Plate Type Nuclear Research Reactors Citation Details In-Document Search Title: Thermal Hydraulic Characteristics of Fuel Defects in Plate Type Nuclear Research Reactors × You are accessing a document from the Department of Energy's (DOE) SciTech Connect. This site is a product of DOE's Office of Scientific and Technical Information (OSTI) and is provided as a public service. Visit

  20. Physical characteristics of AFEX-pretreated and densified switchgrass,

    Office of Scientific and Technical Information (OSTI)

    prairie cord grass, and corn stover (Journal Article) | SciTech Connect Physical characteristics of AFEX-pretreated and densified switchgrass, prairie cord grass, and corn stover Citation Details In-Document Search This content will become publicly available on May 15, 2017 Title: Physical characteristics of AFEX-pretreated and densified switchgrass, prairie cord grass, and corn stover Authors: Karki, Bishnu ; Muthukumarappan, Kasiviswanathan ; Wang, Yijing ; Dale, Bruce ; Balan, Venkatesh ;