National Library of Energy BETA

Sample records for household characteristics total

  1. 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

  2. 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...

  3. "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

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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

  9. 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 ...

  10. 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...

  11. 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 ...

  12. 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 ...

  13. 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

  14. 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

  15. 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 ...

  16. 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 ...

  17. 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 ...

  18. 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 ...

  19. 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

  20. 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

  1. Total....................................................................

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

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5

  2. Total...........................................................

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

    Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space

  3. Total..........................................................

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

    5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units ...

  4. Total

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

    Cell shipments Total Inventory, start-of-year 328,658 Manufactured during reporting year ... Table 5. Source and disposition of photovoltaic cell shipments, 2013 (peak kilowatts) ...

  5. Total............................................................

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

    Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592

  6. Total..........................................................

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

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500...... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to ...

  7. Total

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

    Product: Total Crude Oil Liquefied Petroleum Gases Propane/Propylene Normal Butane/Butylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending Components Petroleum Products Finished Motor Gasoline Reformulated Gasoline Conventional Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm Sulfur and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Sulfur

  8. 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 ...

  9. Total..........................................................................

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

    . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to

  10. Total..........................................................................

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

    5.6 17.7 7.9 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.5 0.3 Q 500 to 999........................................................... 23.8 3.9 2.4 1.5 1,000 to 1,499..................................................... 20.8 4.4 3.2 1.2 1,500 to 1,999..................................................... 15.4 3.5 2.4 1.1 2,000 to 2,499..................................................... 12.2 3.2 2.1 1.1 2,500 to

  11. Total..........................................................................

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

    0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7

  12. Total..........................................................................

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

    4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to

  13. Total..........................................................................

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

    7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1

  14. Total................................................

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

    .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to

  15. Total..........................................................

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

    .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7

  16. Total...................................................................

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

    Floorspace (Square Feet) Total Floorspace 1 Fewer than 500............................................ 3.2 0.4 Q 0.6 1.7 0.4 500 to 999................................................... 23.8 4.8 1.4 4.2 10.2 3.2 1,000 to 1,499............................................. 20.8 10.6 1.8 1.8 4.0 2.6 1,500 to 1,999............................................. 15.4 12.4 1.5 0.5 0.5 0.4 2,000 to 2,499............................................. 12.2 10.7 1.0 0.2 Q Q 2,500 to

  17. Total.........................................................................

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

    Floorspace (Square Feet) Total Floorspace 2 Fewer than 500.................................................. 3.2 Q 0.8 0.9 0.8 0.5 500 to 999.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3

  18. Total..........................................................................

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

    25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.9 1.0 500 to 999........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1

  19. Total..........................................................................

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

    7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4

  20. Total...........................................................

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

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8

  1. 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 ...

  2. 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 ...

  3. 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 ...

  4. 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

  5. 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.

  6. "Characteristic(a)","Total(b)","Electricity(c)","Fuel Oil","Fuel...

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

    Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,"Total United ... raw" "Natural Gas Liquids '(NGL).'" " (g) 'Other' includes net steam (the sum of ...

  7. 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....

  8. 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

  9. "Characteristic(a)","Total","Fuel Oil","Fuel Oil(b)","Natural...

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

    "Value of Shipments and Receipts" "(million dollars)" " Under 20",8.3,"X",43.6,17.5,52.5,0... " Not Ascertained (f)",0,"X","X","X","X","X","X",0 "Total",0.5,0,40.6,0....

  10. Determination of the toxicity characteristic for metals in soil: A comparison of the toxicity characteristic leaching procedure and total metal determination

    SciTech Connect (OSTI)

    Bass, D.A.; Taylor, J.D.

    1994-12-01

    A comparison is made of the concentrations of metals extracted from soils using the Toxicity Characteristic Leaching Procedure (TCLP) and a total determination method. This information is of interest in two ways. First, it is hoped that a relationship might be established between the amount of each metal determined after extraction by the TCLP and the amount determined using a total determination method. And second, data are also presented which indicate the general extractability of various metals in soil samples using the TCLP. This study looks specifically at inorganic elements (Sb, As, Ba, Cd, Cu, Cr, Pb, Mg, Hg, Se, Ag, Sn, and Zn) in soils from a firing range. Results show that total determination methods for metals can not generally be used for heterogeneous samples, such as soil samples from a firing range. Some correlation between a total determination method and TCLP was observed when Ba and Cd were present in the samples at lower concentrations (less than 80 mg/kg for Ba and less than 25 mg/kg for Cd); however, additional data are necessary to verify this correlation.

  11. 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.

  12. 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.

  13. 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...

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

    SciTech Connect (OSTI)

    Siler, A.

    1980-05-01

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

  15. 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

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

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

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

  17. 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

  18. 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,

  19. 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

  20. 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...

  1. 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.

  2. 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 ...

  3. 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

  4. 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 --

  5. ,"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

  6. ,"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

  7. ,"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

  8. ,"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"

  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. 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...

  14. 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...

  15. Total ionizing dose effect of ?-ray radiation on the switching characteristics and filament stability of HfOx resistive random access memory

    SciTech Connect (OSTI)

    Fang, Runchen; Yu, Shimeng; Gonzalez Velo, Yago; Chen, Wenhao; Holbert, Keith E.; Kozicki, Michael N.; Barnaby, Hugh

    2014-05-05

    The total ionizing dose (TID) effect of gamma-ray (?-ray) irradiation on HfOx based resistive random access memory was investigated by electrical and material characterizations. The memory states can sustain TID level ?5.2 Mrad (HfO{sub 2}) without significant change in the functionality or the switching characteristics under pulse cycling. However, the stability of the filament is weakened after irradiation as memory states are more vulnerable to flipping under the electrical stress. X-ray photoelectron spectroscopy was performed to ascertain the physical mechanism of the stability degradation, which is attributed to the Hf-O bond breaking by the high-energy ?-ray exposure.

  16. 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 ...

  17. 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 ...

  18. Household Vehicles Energy Use Cover Page

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

    Energy Use Cover Page Glossary Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use Cover Page Contact Us * Feedback * PrivacySecurity *...

  19. 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 ...

  20. 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 ...

  1. 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 ...

  2. 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 ...

  3. 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 ...

  4. 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) . . . . . . . . ....

  5. 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...

  6. 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 ...

  7. 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. ...

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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 ......

  14. 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 ......

  15. " 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"

  16. 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

  17. 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 .............................................

  18. 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.

  19. 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...

  20. 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 ...

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

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

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

  2. 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 ...

  3. 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...

  4. Country Total

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

    Country Total Percent of U.S. total China 1,461,074 34 Republic of Korea 172,379 4 Taiwan 688,311 16 All others 1,966,263 46 Total 4,288,027 100 Note: All Others includes Canada, Czech Republic, Federal Republic of Germany, Malaysia, Mexico, Philippines and Singapore Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.' Table 7 . Photovoltaic module import shipments by country, 2013 (peak kilowatts)

  5. 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.

  6. 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 ......................................

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

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

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

  8. 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.

  9. State Total

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

    State Total Percent of U.S. total Alabama 1,652 0.0 Alaska 152 0.0 Arizona 912,975 19.9 Arkansas 2,724 0.1 California 2,239,983 48.8 Colorado 49,903 1.1 Connecticut 33,627 0.7 Delaware 3,080 0.1 District of Columbia 1,746 0.0 Florida 22,061 0.5 Georgia 99,713 2.2 Guam 39 0.0 Hawaii 126,595 2.8 Idaho 1,423 0.0 Illinois 8,176 0.2 Indiana 12,912 0.3 Iowa 4,480 0.1 Kansas 523 0.0 Kentucky 2,356 0.1 Louisiana 27,704 0.6 Maine 993 0.0 Maryland 30,528 0.7 Massachusetts 143,539 3.1 Michigan 3,416 0.1

  10. "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

  11. "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...

  12. Table 6a. Total Electricity Consumption per Effective Occupied...

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

    a. Total Electricity Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Electricity (thousand) Total Electricity Consumption...

  13. 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

  14. 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

  15. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect (OSTI)

    Kwac, J; Flora, J; Rajagopal, R

    2014-01-01

    The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.

  16. Household 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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)

  1. 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.

  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. 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. ...

  4. 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.

  5. 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

  6. 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

  7. Barge Truck Total

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

    Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over...

  8. 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)",...

  9. Table 6b. Relative Standard Errors for Total Electricity Consumption...

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

    b. Relative Standard Errors for Total Electricity Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Electricity (thousand) Total...

  10. Table 5a. Total District Heat Consumption per Effective Occupied...

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

    a. Total District Heat Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using District Heat (thousand) Total District Heat Consumption...

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

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

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

  12. Reconstructing householder vectors from Tall-Skinny QR

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

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

    2015-08-05

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

  13. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-01-01

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

  14. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-12-31

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

  15. Reconstructing householder vectors from Tall-Skinny QR

    SciTech Connect (OSTI)

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

    2015-08-05

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

  16. " 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"

  17. " 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"

  18. " 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"

  19. " 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"

  20. " 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"

  1. " 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"

  2. 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...

  3. 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 ...

  4. 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

  5. ,"Total Natural Gas Consumption

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

    Gas Consumption (billion cubic feet)",,,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  6. 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

  7. 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.....................................................

  8. 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.

  9. 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.

  10. 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.

  11. " 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

  12. ,"Total Fuel Oil Expenditures

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

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

  13. ,"Total Fuel Oil Consumption

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

    0. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for Non-Mall Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  14. ,"Total Fuel Oil Expenditures

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

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

  15. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

  16. ,"Total Fuel Oil Expenditures

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

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

  17. ,"Total Fuel Oil Consumption

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

    A. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  18. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

  19. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings*...

  20. Parallel Total Energy

    Energy Science and Technology Software Center (OSTI)

    2004-10-21

    This is a total energy electronic structure code using Local Density Approximation (LDA) of the density funtional theory. It uses the plane wave as the wave function basis set. It can sue both the norm conserving pseudopotentials and the ultra soft pseudopotentials. It can relax the atomic positions according to the total energy. It is a parallel code using MP1.

  1. 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 ...

  2. 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...

  3. 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...

  4. 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...

  5. 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 ...

  6. 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...

  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. Summary Max Total Units

    Energy Savers [EERE]

    Summary Max Total Units *If All Splits, No Rack Units **If Only FW, AC Splits 1000 52 28 28 2000 87 59 35 3000 61 33 15 4000 61 33 15 Totals 261 153 93 ***Costs $1,957,500.00 $1,147,500.00 $697,500.00 Notes: added several refrigerants removed bins from analysis removed R-22 from list 1000lb, no Glycol, CO2 or ammonia Seawater R-404A only * includes seawater units ** no seawater units included *** Costs = (total units) X (estimate of $7500 per unit) 1000lb, air cooled split systems, fresh water

  9. Country/Continent Total

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

    peak kilowatts) Country/Continent Total Percent of U.S. total Africa 14,279 3.7 Asia/Australia 330,200 86.2 Europe 19,771 5.1 South/Central America 7,748 2.0 Canada 5,507 1.4 Mexico 5,747 1.5 Total 383,252 100.0 Table 8. Destination of photovoltaic module export shipments, 2013 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.'

  10. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other...

  11. ARM - Measurement - Total carbon

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

    carbon ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total carbon The total concentration of carbon in all its organic and non-organic forms. Categories Aerosols, Atmospheric Carbon Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including

  12. "Characteristic(a)","Total","Electricity(b)","Fuel Oil","Fuel...

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

    " 50-99",5.2,8.9,10.2,26.4,6.5,54,4.3,"X",4.2 " 100-249",12.1,17.2,4,20.2,16,40.3,8.1... 50",13.2,8.7,43.2,22.9,16.9,40.6,27.1,"X",66.4 " 50-99",6.1,6.8,29.8,15.2,9.5,12.2,3....

  13. Table 3a. Total Natural Gas Consumption per Effective Occupied...

    Gasoline and Diesel Fuel Update (EIA)

    3a. Natural Gas Consumption per Sq Ft Table 3a. Total Natural Gas Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Natural Gas...

  14. Total DOE/NNSA

    National Nuclear Security Administration (NNSA)

    8 Actuals 2009 Actuals 2010 Actuals 2011 Actuals 2012 Actuals 2013 Actuals 2014 Actuals 2015 Actuals Total DOE/NNSA 4,385 4,151 4,240 4,862 5,154 5,476 7,170 7,593 Total non-NNSA 3,925 4,017 4,005 3,821 3,875 3,974 3,826 3765 Total Facility 8,310 8,168 8,245 8,683 9,029 9,450 10,996 11,358 non-NNSA includes DOE offices and Strategic Parternship Projects (SPP) employees NNSA M&O Employee Reporting

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

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

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

  16. 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.

  17. 21 briefing pages total

    Energy Savers [EERE]

    1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law

  18. 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

  19. Table 4b. Relative Standard Errors for Total Fuel Oil Consumption...

    Gasoline and Diesel Fuel Update (EIA)

    4b. Relative Standard Errors for Total Fuel Oil Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Fuel Oil (thousand) Total Fuel Oil...

  20. Table 4a. Total Fuel Oil Consumption per Effective Occupied Square...

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

    Table 4a. Total Fuel Oil Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Fuel Oil (thousand) Total Fuel Oil Consumption (trillion...

  1. Total Sales of Kerosene

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

    End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 269,010 305,508 187,656 81,102 79,674 137,928 1984-2014 East Coast (PADD 1) 198,762 237,397 142,189 63,075 61,327 106,995 1984-2014 New England (PADD 1A) 56,661 53,363 38,448 15,983 15,991 27,500 1984-2014 Connecticut 8,800 7,437

  2. 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 ...

  3. 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.

  4. 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.

  5. 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.

  6. Determination of Total Petroleum Hydrocarbons (TPH) Using Total Carbon Analysis

    SciTech Connect (OSTI)

    Ekechukwu, A.A.

    2002-05-10

    Several methods have been proposed to replace the Freon(TM)-extraction method to determine total petroleum hydrocarbon (TPH) content. For reasons of cost, sensitivity, precision, or simplicity, none of the replacement methods are feasible for analysis of radioactive samples at our facility. We have developed a method to measure total petroleum hydrocarbon content in aqueous sample matrixes using total organic carbon (total carbon) determination. The total carbon content (TC1) of the sample is measured using a total organic carbon analyzer. The sample is then contacted with a small volume of non-pokar solvent to extract the total petroleum hydrocarbons. The total carbon content of the resultant aqueous phase of the extracted sample (TC2) is measured. Total petroleum hydrocarbon content is calculated (TPH = TC1-TC2). The resultant data are consistent with results obtained using Freon(TM) extraction followed by infrared absorbance.

  7. 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.

  8. 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

  9. 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

  10. 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

  11. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires Natural Gas, 1997 Average Natural Gas Residential Buildings Consumption Expenditures Total per Floor- per Square per per per Total Total space (1) Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 61.9 51.3 106.1 103 50 85.3 32 698 0.34

  12. 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

  13. Total Eolica | Open Energy Information

    Open Energy Info (EERE)

    Eolica Jump to: navigation, search Name: Total Eolica Place: Spain Product: Project developer References: Total Eolica1 This article is a stub. You can help OpenEI by expanding...

  14. 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.

  15. 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.

  16. Total

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

    Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm Sulfur and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Sulfur Distillate Fuel Oil, Greater than 500 ppm ...

  17. Total..............................................

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

    111.1 86.6 2,720 1,970 1,310 1,941 1,475 821 1,059 944 554 Census Region and Division Northeast.................................... 20.6 13.9 3,224 2,173 836 2,219 1,619 583 903 830 Q New England.......................... 5.5 3.6 3,365 2,154 313 2,634 1,826 Q 951 940 Q Middle Atlantic........................ 15.1 10.3 3,167 2,181 1,049 2,188 1,603 582 Q Q Q Midwest...................................... 25.6 21.0 2,823 2,239 1,624 2,356 1,669 1,336 1,081 961 778 East North

  18. Total........................................................

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

    111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351

  19. Total............................................................

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

  20. Total.............................................................

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

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer....................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Most-Used Personal Computer Type of PC Desk-top Model.................................. 58.6 7.6 14.2 13.1 9.2 14.6 5.0 14.5 Laptop Model...................................... 16.9 2.0 3.8 3.3 2.1 5.7 1.3 3.5 Hours Turned on Per Week Less than 2 Hours..............................

  1. Total..............................................................

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

    ,171 1,618 1,031 845 630 401 Census Region and Division Northeast................................................... 20.6 2,334 1,664 562 911 649 220 New England.......................................... 5.5 2,472 1,680 265 1,057 719 113 Middle Atlantic........................................ 15.1 2,284 1,658 670 864 627 254 Midwest...................................................... 25.6 2,421 1,927 1,360 981 781 551 East North Central.................................. 17.7 2,483 1,926 1,269

  2. Total..............................................................

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

    Do Not Have Cooling Equipment................ 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat

  3. Total...............................................................

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

    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 Computer......................... 75.6 13.7 17.5 26.6 17.8 Number of Desktop PCs 1.......................................................... 50.3 9.3 11.9 18.2 11.0 2.......................................................... 16.2 2.9 3.5 5.5 4.4 3 or More............................................. 9.0 1.5 2.1 2.9 2.5 Number of Laptop PCs

  4. Total...............................................................

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

    0.7 21.7 6.9 12.1 Personal Computers Do Not Use a Personal Computer ........... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer......................... 75.6 26.6 14.5 4.1 7.9 Number of Desktop PCs 1.......................................................... 50.3 18.2 10.0 2.9 5.3 2.......................................................... 16.2 5.5 3.0 0.7 1.8 3 or More............................................. 9.0 2.9 1.5 0.5 0.8 Number of Laptop PCs

  5. Total...............................................................

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

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer ........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Number of Desktop PCs 1.......................................................... 50.3 8.3 14.2 11.4 7.2 9.2 5.3 14.2 2.......................................................... 16.2 0.9 2.6 3.7 2.9 6.2 0.8 2.6 3 or More............................................. 9.0 0.4 1.2

  6. Total...............................................................

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

    Do Not Have Cooling Equipment................. 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment.............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment............................... 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Air-Conditioning Equipment 1, 2 Central System............................................ 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat

  7. Total...............................................................

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

    47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer ........... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......................... 75.6 30.3 12.5 18.1 14.7 Number of Desktop PCs 1.......................................................... 50.3 21.1 8.3 10.7 10.1 2.......................................................... 16.2 6.2 2.8 4.1 3.0 3 or More............................................. 9.0 2.9 1.4 3.2 1.6 Number of Laptop PCs

  8. Total................................................................

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

    111.1 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Do Not Have Space Heating Equipment....... 1.2 0.5 0.3 0.2 Q 0.2 0.3 0.6 Have Main Space Heating Equipment.......... 109.8 26.2 28.5 20.4 13.0 21.8 16.3 37.9 Use Main Space Heating Equipment............ 109.1 25.9 28.1 20.3 12.9 21.8 16.0 37.3 Have Equipment But Do Not Use It.............. 0.8 0.3 0.3 Q Q N 0.4 0.6 Main Heating Fuel and Equipment Natural Gas.................................................. 58.2 12.2 14.4 11.3 7.1 13.2 7.6 18.3 Central

  9. Total.................................................................

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

    49.2 15.1 15.6 11.1 7.0 5.2 8.0 Have Cooling Equipment............................... 93.3 31.3 15.1 15.6 11.1 7.0 5.2 8.0 Use Cooling Equipment................................ 91.4 30.4 14.6 15.4 11.1 6.9 5.2 7.9 Have Equipment But Do Not Use it............... 1.9 1.0 0.5 Q Q Q Q Q Do Not Have Cooling Equipment................... 17.8 17.8 N N N N N N Air-Conditioning Equipment 1, 2 Central System............................................. 65.9 3.9 15.1 15.6 11.1 7.0 5.2 8.0 Without a Heat

  10. Total.................................................................

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

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Space Heating Equipment........ 1.2 N Q Q 0.2 0.4 0.2 0.2 Q Have Main Space Heating Equipment........... 109.8 14.7 7.4 12.4 12.2 18.5 18.3 17.1 9.2 Use Main Space Heating Equipment............. 109.1 14.6 7.3 12.4 12.2 18.2 18.2 17.1 9.1 Have Equipment But Do Not Use It............... 0.8 Q Q Q Q 0.3 Q N Q Main Heating Fuel and Equipment Natural Gas................................................... 58.2 9.2 4.9 7.8 7.1 8.8 8.4 7.8 4.2 Central

  11. Total.................................................................

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

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day.............................. 8.2 2.9 2.5 1.3 0.5 1.0 2.4 4.6 2 Times A Day........................................... 24.6 6.5 7.0 4.3 3.2 3.6 4.8 10.3 Once a Day................................................ 42.3 8.8 9.8 8.7 5.1 10.0 5.0 12.9 A Few Times Each Week........................... 27.2 5.6 7.2 4.7 3.3 6.3 3.2 7.5 About Once a Week................................... 3.9 1.1 1.1

  12. Total..................................................................

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

    78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat

  13. Total..................................................................

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

    . 111.1 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Cooling Equipment..................... 17.8 3.9 1.8 2.2 2.1 3.1 2.6 1.7 0.4 Have Cooling Equipment................................. 93.3 10.8 5.6 10.3 10.4 15.8 16.0 15.6 8.8 Use Cooling Equipment.................................. 91.4 10.6 5.5 10.3 10.3 15.3 15.7 15.3 8.6 Have Equipment But Do Not Use it................. 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central

  14. Total...................................................................

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

    15.2 7.8 1.0 1.2 3.3 1.9 For Two Housing Units............................. 0.9 Q N Q 0.6 N Heat Pump.................................................. 9.2 7.4 0.3 Q 0.7 0.5 Portable Electric Heater............................... 1.6 0.8 Q Q Q 0.3 Other Equipment......................................... 1.9 0.7 Q Q 0.7 Q Fuel Oil........................................................... 7.7 5.5 0.4 0.8 0.9 0.2 Steam or Hot Water System........................ 4.7 2.9 Q 0.7 0.8 N For One Housing

  15. Total.......................................................................

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

    0.6 15.1 5.5 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.9 5.3 1.6 Use a Personal Computer................................ 75.6 13.7 9.8 3.9 Number of Desktop PCs 1.................................................................. 50.3 9.3 6.8 2.5 2.................................................................. 16.2 2.9 1.9 1.0 3 or More..................................................... 9.0 1.5 1.1 0.4 Number of Laptop PCs

  16. Total.......................................................................

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

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer ................... 35.5 8.1 5.6 2.5 Use a Personal Computer................................ 75.6 17.5 12.1 5.4 Number of Desktop PCs 1.................................................................. 50.3 11.9 8.4 3.4 2.................................................................. 16.2 3.5 2.2 1.3 3 or More..................................................... 9.0 2.1 1.5 0.6 Number of Laptop PCs

  17. Total.......................................................................

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

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.4 2.2 4.2 Use a Personal Computer................................ 75.6 17.8 5.3 12.5 Number of Desktop PCs 1.................................................................. 50.3 11.0 3.4 7.6 2.................................................................. 16.2 4.4 1.3 3.1 3 or More..................................................... 9.0 2.5 0.7 1.8 Number of Laptop PCs

  18. Total........................................................................

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

    25.6 40.7 24.2 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.7 Have Main Space Heating Equipment.................. 109.8 20.5 25.6 40.3 23.4 Use Main Space Heating Equipment.................... 109.1 20.5 25.6 40.1 22.9 Have Equipment But Do Not Use It...................... 0.8 N N Q 0.6 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 18.4 13.6 14.7 Central Warm-Air Furnace................................ 44.7 6.1

  19. Total........................................................................

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

    15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing

  20. Total........................................................................

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

    5.6 17.7 7.9 Do Not Have Space Heating Equipment............... 1.2 Q Q N Have Main Space Heating Equipment.................. 109.8 25.6 17.7 7.9 Use Main Space Heating Equipment.................... 109.1 25.6 17.7 7.9 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 18.4 13.1 5.3 Central Warm-Air Furnace................................ 44.7 16.2 11.6 4.7 For One Housing

  1. Total........................................................................

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

    0.7 21.7 6.9 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q N Q Have Main Space Heating Equipment.................. 109.8 40.3 21.4 6.9 12.0 Use Main Space Heating Equipment.................... 109.1 40.1 21.2 6.9 12.0 Have Equipment But Do Not Use It...................... 0.8 Q Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 13.6 5.6 2.3 5.7 Central Warm-Air Furnace................................ 44.7 11.0 4.4

  2. Total........................................................................

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

    4.2 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 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One

  3. Total........................................................................

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

    7.1 7.0 8.0 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.2 Have Main Space Heating Equipment.................. 109.8 7.1 6.8 7.9 11.9 Use Main Space Heating Equipment.................... 109.1 7.1 6.6 7.9 11.4 Have Equipment But Do Not Use It...................... 0.8 N Q N 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 3.8 0.4 3.8 8.4 Central Warm-Air Furnace................................ 44.7 1.8 Q 3.1 6.0

  4. Total........................................................................

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

    7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7

  5. Total...........................................................................

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

    0.6 15.1 5.5 Do Not Have Cooling Equipment............................. 17.8 4.0 2.4 1.7 Have Cooling Equipment.......................................... 93.3 16.5 12.8 3.8 Use Cooling Equipment........................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it.......................... 1.9 0.3 Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 5.2 0.8 Without a Heat

  6. Total...........................................................................

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

    4.2 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 Equipment........................................... 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it.......................... 1.9 1.0 Q 0.8 Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat

  7. Total.............................................................................

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

    Do Not Have Cooling Equipment............................... 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................ 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................ 1.9 0.3 Q 0.5 1.0 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 17.3 32.1 10.5 Without a Heat

  8. Total.............................................................................

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.2 1.0 0.2 2 Times A Day...................................................... 24.6 4.0 2.7 1.2 Once a Day........................................................... 42.3 7.9 5.4 2.5 A Few Times Each Week...................................... 27.2 6.0 4.8 1.2 About Once a Week.............................................. 3.9 0.6 0.5 Q Less Than Once a

  9. Total.............................................................................

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.4 1.0 0.4 2 Times A Day...................................................... 24.6 5.8 3.5 2.3 Once a Day........................................................... 42.3 10.7 7.8 2.9 A Few Times Each Week...................................... 27.2 5.6 4.0 1.6 About Once a Week.............................................. 3.9 0.9 0.6 0.3 Less Than Once a

  10. Total.............................................................................

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

    Do Not Have Cooling Equipment............................... 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................ 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................ 1.9 0.5 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 32.1 17.6 5.2 9.3 Without a Heat

  11. Total.............................................................................

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 2.6 0.7 1.9 2 Times A Day...................................................... 24.6 6.6 2.0 4.6 Once a Day........................................................... 42.3 8.8 2.9 5.8 A Few Times Each Week...................................... 27.2 4.7 1.5 3.1 About Once a Week.............................................. 3.9 0.7 Q 0.6 Less Than Once a

  12. Total.............................................................................

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

    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 Equipment............................................. 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it............................ 1.9 1.0 Q 0.8 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat

  13. Total.............................................................................

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

    Do Not Have Cooling Equipment............................... 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................ 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................ 1.9 0.9 0.3 0.3 0.4 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 25.8 10.9 16.6 12.5 Without a Heat

  14. Total..............................................................................

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

    111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer .......................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer....................................... 75.6 4.2 5.0 5.3 9.0 Number of Desktop PCs 1......................................................................... 50.3 3.1 3.4 3.4 5.4 2......................................................................... 16.2 0.7 1.1 1.2 2.2 3 or More............................................................ 9.0 0.3

  15. Total.................................................................................

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

    7.1 7.0 8.0 12.1 Do Not Have Cooling Equipment................................... 17.8 1.8 Q Q 4.9 Have Cooling Equipment................................................ 93.3 5.3 7.0 7.8 7.2 Use Cooling Equipment................................................. 91.4 5.3 7.0 7.7 6.6 Have Equipment But Do Not Use it............................... 1.9 Q N Q 0.6 Air-Conditioning Equipment 1, 2 Central System.............................................................. 65.9 1.1 6.4 6.4 5.4 Without a

  16. Total....................................................................................

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

    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 Computer.............................................. 75.6 13.7 17.5 26.6 17.8 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 10.4 14.1 20.5 13.7 Laptop Model............................................................. 16.9 3.3 3.4 6.1 4.1 Hours Turned on Per Week Less than 2

  17. Total....................................................................................

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

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer.................................. 35.5 8.1 5.6 2.5 Use a Personal Computer.............................................. 75.6 17.5 12.1 5.4 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 14.1 10.0 4.0 Laptop Model............................................................. 16.9 3.4 2.1 1.3 Hours Turned on Per Week Less than 2

  18. Total....................................................................................

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.0 1.6 0.3 1.1 2 Times A Day.............................................................. 24.6 8.3 4.2 1.3 2.7 Once a Day................................................................... 42.3 15.0 8.1 2.7 4.2 A Few Times Each Week............................................. 27.2 10.9 6.0 1.8 3.1 About Once a Week..................................................... 3.9

  19. Total....................................................................................

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

    Personal Computers Do Not Use a Personal Computer.................................. 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer.............................................. 75.6 26.6 14.5 4.1 7.9 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 20.5 11.0 3.4 6.1 Laptop Model............................................................. 16.9 6.1 3.5 0.7 1.9 Hours Turned on Per Week Less than 2

  20. Total....................................................................................

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

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.4 2.2 4.2 Use a Personal Computer.............................................. 75.6 17.8 5.3 12.5 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 13.7 4.2 9.5 Laptop Model............................................................. 16.9 4.1 1.1 3.0 Hours Turned on Per Week Less than 2

  1. Total....................................................................................

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.7 1.6 1.4 1.5 2 Times A Day.............................................................. 24.6 10.8 4.1 4.3 5.5 Once a Day................................................................... 42.3 17.0 7.2 8.7 9.3 A Few Times Each Week............................................. 27.2 11.4 4.7 6.4 4.8 About Once a Week.....................................................

  2. Total....................................................................................

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

    111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer.................................. 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer.............................................. 75.6 30.3 12.5 18.1 14.7 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 22.9 9.8 14.1 11.9 Laptop Model............................................................. 16.9 7.4 2.7 4.0 2.9 Hours Turned on Per Week Less than 2

  3. Total.........................................................................................

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

    ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer...................................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer.................................................. 75.6 4.2 5.0 5.3 9.0 Most-Used Personal Computer Type of PC Desk-top Model............................................................. 58.6 3.2 3.9 4.0 6.7 Laptop Model................................................................. 16.9 1.0 1.1 1.3 2.4 Hours Turned on Per Week Less

  4. Total

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

    Administration, Form EIA-63B, 'Annual Photovoltaic CellModule Shipments Report.'rounding. ... Form EIA-63B, 'Annual Photovoltaic CellModule Shipments Report.' CellModule ...

  5. Total..........................................................

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

    ... 41.8 2,603 2,199 1,654 941 795 598 1-Car Garage...... 9.5 2,064 1,664 1,039 775 624 390 2-Car Garage......

  6. Total..........................................................

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

    ... Type of Glass in Windows Single-pane Glass...... 27.4 ... Q Q N Q N N Proportion of Windows Replaced All......

  7. Total..........................................................

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

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

  8. Total..........................................................

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 25.8 10.9 16.6 12.5 Without a Heat Pump......

  9. Total..........................................................

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 6.0 17.3 32.1 10.5 Without a Heat Pump......

  10. Total..........................................................

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 47.5 4.0 2.8 7.9 3.7 Without a Heat Pump...... 53.5 ...

  11. Total..........................................................

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump......

  12. Total..........................................................

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

    5.6 17.7 7.9 Do Not Have Cooling Equipment...... 17.8 2.1 1.8 0.3 Have Cooling Equipment...... 93.3 23.5 16.0 7.5 Use ...

  13. Total..........................................................

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

    ... 111.1 20.6 15.1 5.5 Do Not Have Cooling Equipment...... 17.8 4.0 2.4 1.7 Have Cooling Equipment...... 93.3 ...

  14. Total..........................................................

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

    33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment...... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment...... 93.3 26.5 6.5 2.5 ...

  15. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  16. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  17. 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 ...

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

    Broader source: Energy.gov [DOE]

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

  19. 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...

  20. 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...

  1. 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

  2. Table 4

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

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

  3. Table 4

    Gasoline and Diesel Fuel Update (EIA)

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

  4. Determination of Total Solids in Biomass and Total Dissolved...

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

    ... The published moisture loss on drying for sodium tartrate is 15.62% (84.38% total solids). 14.6 Sample size: Determined by sample matrix. 14.7 Sample storage: Samples should be ...

  5. TotalView Training 2015

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

    TotalView Training 2015 TotalView Training 2015 NERSC will host an in-depth training course on TotalView, a graphical parallel debugger developed by Rogue Wave Software, on Thursday, March 26, 2015. This will be provided by Rogue Wave Software staff members. The training will include a lecture and demo sessions in the morning, followed by a hands-on parallel debugging session in the afternoon. Location This event will be presented online using WebEx technology and in person at NERSC Oakland

  6. ARM - Measurement - Total cloud water

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

    cloud water ARM Data Discovery Browse Data Comments? We would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total cloud water The...

  7. U.S. Total Exports

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

    CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass, TX El Paso, TX Freeport, TX Hidalgo, TX Laredo, TX McAllen, TX Penitas, TX Rio Bravo, TX Rio Grande, TX Roma, TX Total ...

  8. 2014 Total Electric Industry- Customers

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

    Customers (Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 6,243,013 862,269 28,017 8 ...

  9. "2014 Total Electric Industry- Customers"

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

    Customers" "(Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",6243013,8...

  10. 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 ...

  11. 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.

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

    SciTech Connect (OSTI)

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

    2005-05-31

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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

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

    SciTech Connect (OSTI)

    Figueroa, M.J.; Sathaye, J.

    1993-08-01

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

  2. 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...

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

    SciTech Connect (OSTI)

    Zimring, Mark; Fuller, Merrian

    2011-01-24

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

  4. CATEGORY Total Procurement Total Small Business Small Disadvantaged

    National Nuclear Security Administration (NNSA)

    CATEGORY Total Procurement Total Small Business Small Disadvantaged Business Woman Owned Small Business HubZone Small Business Veteran-Owned Small Business Service Disabled Veteran Owned Small Business FY 2013 Dollars Accomplished $1,049,087,940 $562,676,028 $136,485,766 $106,515,229 $12,080,258 $63,473,852 $28,080,960 FY 2013 % Accomplishment 54.40% 13.00% 10.20% 1.20% 6.60% 2.70% FY 2014 Dollars Accomplished $868,961,755 $443,711,175 $92,478,522 $88,633,031 $29,867,820 $43,719,452 $26,826,374

  5. 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

  6. 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

  7. 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

  8. "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"

  9. "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"

  10. 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

  11. 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.

  12. 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...

  13. Total Adjusted Sales of Kerosene

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

    End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 269,010 305,508 187,656 81,102 79,674 137,928 1984-2014 East Coast (PADD 1) 198,762 237,397 142,189 63,075 61,327 106,995 1984-2014 New England (PADD 1A) 56,661 53,363 38,448 15,983 15,991 27,500 1984-2014 Connecticut 8,800 7,437

  14. Total Imports of Residual Fuel

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

    Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S. Total 7,281 4,217 5,941 6,842 9,010 5,030 1936-2016 PAD District 1 4,571 2,206 2,952 3,174 3,127 2,664 1981-2016 Connecticut 1995-2015 Delaware 678 85 1995-2015 Florida 351 299 932 836 858 649 1995-2016 Georgia 120 295 210 262 1995-2016 Maine 1995-2015 Maryland 1995-2015 Massachusetts 1995-2015 New Hampshire 1995-2015 New Jersey 1,575 400 1,131 1,712 1,283 843 1995-2016 New York 1,475 998 350 322 234 824 1995-2016 North Carolina

  15. 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...

  16. 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

  17. Total-derivative supersymmetry breaking

    SciTech Connect (OSTI)

    Haba, Naoyuki; Uekusa, Nobuhiro

    2010-05-15

    On an interval compactification in supersymmetric theory, boundary conditions for bulk fields must be treated carefully. If they are taken arbitrarily following the requirement that a theory is supersymmetric, the conditions could give redundant constraints on the theory. We construct a supersymmetric action integral on an interval by introducing brane interactions with which total-derivative terms under the supersymmetry transformation become zero due to a cancellation. The variational principle leads equations of motion and also boundary conditions for bulk fields, which determine boundary values of bulk fields. By estimating mass spectrum, spontaneous supersymmetry breaking in this simple setup can be realized in a new framework. This supersymmetry breaking does not induce a massless R axion, which is favorable for phenomenology. It is worth noting that fermions in hyper-multiplet, gauge bosons, and the fifth-dimensional component of gauge bosons can have zero-modes (while the other components are all massive as Kaluza-Klein modes), which fits the gauge-Higgs unification scenarios.

  18. ,"West Virginia Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","West Virginia Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: West Virginia Natural Gas Total Consumption (MMcf)" ...

  19. ,"New Mexico Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","New Mexico Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: New Mexico Natural Gas Total Consumption (MMcf)" ...

  20. ARM - Measurement - Shortwave broadband total downwelling irradiance

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

    Measurement : Shortwave broadband total downwelling irradiance The total diffuse and direct radiant energy that comes from some continuous range of directions, at wavelengths ...

  1. Total Space Heating Water Heating Cook-

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

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing...

  2. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,870 1,276...

  3. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All...

  4. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,602 1,397...

  5. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings ... 2,037...

  6. 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.

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

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

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

  8. 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.

  9. 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,...

  10. Table HC1.2.1. Living Space Characteristics by

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

    1. Living Space Characteristics by" " Total, Heated, and Cooled Floorspace, 2005" ,,,"Total Square Footage" ,"Housing Units",,"Total1",,"Heated",,"Cooled" "Living Space Characteristics","Millions","Percent","Billions","Percent","Billions","Percent","Billions","Percent" "Total",111.1,100,225.8,100,179.8,100,114.5,100 "Total

  11. Total Space Heating Water Heating Cook-

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

    Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 634 578 46 1 Q 116.4 106.3...

  12. Million Cu. Feet Percent of National Total

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

    2 Alaska - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S2. Summary statistics for natural gas - Alaska, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 269 277 185 R 159 170 Production (million cubic feet) Gross Withdrawals From Gas Wells 127,417 112,268

  13. Million Cu. Feet Percent of National Total

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

    6 District of Columbia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells

  14. Million Cu. Feet Percent of National Total

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

    4 Massachusetts - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0

  15. Million Cu. Feet Percent of National Total

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

    50 North Dakota - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S36. Summary statistics for natural gas - North Dakota, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 188 239 211 200 200 Production (million cubic feet) Gross Withdrawals From Gas Wells

  16. Million Cu. Feet Percent of National Total

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

    6 Washington - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S49. Summary statistics for natural gas - Washington, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil

  17. Total System Performance Assessment Peer Review Panel

    Broader source: Energy.gov [DOE]

    Total System Performance Assessment (TSPA) Peer Review Panel for predicting the performance of a repository at Yucca Mountain.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. R93HC.PDF

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

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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires Fuel Oil/Kerosene, 2001 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 11.2 9.4 26.0 80 29 67.1 26 723 0.26

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  9. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 Average of Major Energy Sources Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (millionBtu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 83.1 66.1 144.2 141 64 111.7 40 1,256 0.58 998 356

  10. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 Average of Major Energy Sources Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 83.8 66.1 142.2 130 60 102.3 37 1,309 0.61 1,033 377

  11. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 Average of Major Energy Sources Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 86.3 67.5 144.4 134 63 104.7 39 1,437 0.67 1,123 417

  12. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average of Major Energy Sources Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 90.5 70.4 156.8 130 58 100.8 39 1,388 0.62 1,080 416

  13. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  14. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 3 Average of Major Energy Sources Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 96.6 76.5 181.2 131 55 103.6 40 1,620 0.68 1,282 491

  15. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average of Major Energy Sources Residential Buildings Consumption Expenditures Total per Floor- per Square per per per Total Total space(2) Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 101.5 83.2 168.8 123 61 101.0 39 1,633 0.80

  16. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2001 Average of Major Energy Sources Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 107.0 85.2 211.3 116 47 92.2 36 1,875 0.76 1,493

  17. 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.

  18. 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...

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

    SciTech Connect (OSTI)

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

    1996-03-01

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

  20. 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

  1. Cell Total Activity Final Estimate.xls

    Office of Legacy Management (LM)

    WSSRAP Cell Total Activity Final Estimate (calculated September 2002, Fleming) (Waste streams & occupied cell volumes from spreadsheet titled "cell waste volumes-8.23.02 with ...

  2. Million Cu. Feet Percent of National Total

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

    0 Alabama - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S1. Summary statistics for natural gas - Alabama, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,026 7,063 6,327 R 6,165 6,118 Production (million cubic feet) Gross Withdrawals From Gas Wells

  3. Million Cu. Feet Percent of National Total

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

    0 Colorado - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 28,813 30,101 32,000 R 32,468 38,346 Production (million cubic feet) Gross Withdrawals From Gas

  4. Million Cu. Feet Percent of National Total

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

    8 Florida - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S10. Summary statistics for natural gas - Florida, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 17,182 16,459 19,742

  5. Million Cu. Feet Percent of National Total

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

    4 Hawaii - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S13. Summary statistics for natural gas - Hawaii, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0

  6. Million Cu. Feet Percent of National Total

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

    6 Idaho - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S14. Summary statistics for natural gas - Idaho, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0

  7. Million Cu. Feet Percent of National Total

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

    4 Kansas - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S18. Summary statistics for natural gas - Kansas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 22,145 25,758 24,697 R 23,792 24,354 Production (million cubic feet) Gross Withdrawals From Gas Wells

  8. Million Cu. Feet Percent of National Total

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

    8 Louisiana - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S20. Summary statistics for natural gas - Louisiana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 19,137 21,235 19,792 R 19,528 19,251 Production (million cubic feet) Gross Withdrawals From Gas

  9. Million Cu. Feet Percent of National Total

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

    4 New Mexico - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S33. Summary statistics for natural gas - New Mexico, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,748 32,302 28,206 R 27,073 27,957 Production (million cubic feet) Gross Withdrawals From

  10. Million Cu. Feet Percent of National Total

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

    6 Oregon - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 26 24 27 R 26 28 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,407 1,344 770 770

  11. Million Cu. Feet Percent of National Total

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

    Total Net Movements: - Industrial: Dry Production: Vehicle ... due to independent rounding. Prices are in nominal dollars. ... Annual Consumption per Consumer (thousand cubic feet) ...

  12. Million Cu. Feet Percent of National Total

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

    from Electric Power to Industrial for years 2002 through ... Totals may not add due to independent rounding. Prices are ... Annual Consumption per Consumer (thousand cubic feet) ...

  13. Total Natural Gas Underground Storage Capacity

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

    Storage Capacity Salt Caverns Storage Capacity Aquifers Storage Capacity Depleted Fields Storage Capacity Total Working Gas Capacity Working Gas Capacity of Salt Caverns Working...

  14. ARM - Measurement - Shortwave narrowband total downwelling irradiance

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

    Send Measurement : Shortwave narrowband total downwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 mum, passes ...

  15. ARM - Measurement - Shortwave narrowband total upwelling irradiance

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

    Send Measurement : Shortwave narrowband total upwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 mum, passes ...

  16. ARM - Measurement - Shortwave spectral total downwelling irradiance

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

    Send Measurement : Shortwave spectral total downwelling irradiance The rate at which radiant energy, at specrally-resolved wavelengths between 0.4 and 4 mum, is being emitted ...

  17. 2014 Total Electric Industry- Sales (Megawatthours

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

    EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",47211525,53107038,19107433,557463,119983459 "Connecticut",12777579,12893531,351479...

  18. Total Supplemental Supply of Natural Gas

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

    Product: Total Supplemental Supply Synthetic Propane-Air Refinery Gas Biomass Other Period: Monthly Annual Download Series History Download Series History Definitions, Sources & ...

  19. 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.

  20. 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.

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

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

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

  2. " 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...

  3. " 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...

  4. 2009 Total Energy Production by State | Department of Energy

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

    Total Energy Production by State 2009 Total Energy Production by State 2009 Total Energy Production by State...

  5. 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.

  6. 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.

  7. Million Cu. Feet Percent of National Total

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

    8 Minnesota - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet ... Summary statistics for natural gas - Minnesota, 2010-2014 2010 2011 2012 2013 2014 ...

  8. EQUUS Total Return Inc | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Name: EQUUS Total Return Inc Place: Houston, Texas Product: A business development company and VC investor that trades as a closed-end fund. EQUUS is...

  9. Million Cu. Feet Percent of National Total

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

    Totals may not add due to independent rounding. Prices are ... 250,994 253,127 Industrial 9,332 9,088 8,833 8,497 8,156 Average Annual Consumption per Consumer (thousand cubic ...

  10. Million Cu. Feet Percent of National Total

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

    Notes: Totals may not add due to independent rounding. Prices ... 34,078 34,283 34,339 Industrial 102 94 97 95 92 Average Annual Consumption per Consumer (thousand cubic feet) ...

  11. Million Cu. Feet Percent of National Total

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

    as known volumes of natural gas that were the result of leaks, damage, accidents, migration, andor blow down. Notes: Totals may not add due to independent rounding. Prices are...

  12. TotalView Parallel Debugger at NERSC

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

    The performance of the GUI can be greatly improved if used in conjunction with free NX software. The TotalView documentation web page is a good resource for learning more...

  13. ARM - Measurement - Shortwave broadband total upwelling irradiance

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

    Send Measurement : Shortwave broadband total upwelling irradiance The rate at which radiant energy, at a wavelength between 0.4 and 4 mum, is being emitted upwards into a ...

  14. "2014 Total Electric Industry- Revenue (Thousands Dollars)"

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

    EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",8414175.4,7806276.7,2262752.4,57837.4,18541041.8 "Connecticut",2523348.7,2004629.1...

  15. 2014 Total Electric Industry- Revenue (Thousands Dollars)

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

    Revenue (Thousands Dollars) (Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 8,414,175 ...

  16. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. ... 2,314 764 719 180 4,046 Supplemental Gas Supplies 732 701 660 642 635 Balancing Item ...

  17. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. ... 3,762 7,315 10,303 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item 65,897 -19,970 ...

  18. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. ... 473 526 484 626 1,359 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -6,645 3,976 ...

  19. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S31. ... 35 108 71 124 185 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -1,393 -3,726 ...

  20. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S51. ... 92 87 100 89 138 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -2,885 -12,890 ...

  1. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. ... 76 96 66 131 128 Supplemental Gas Supplies 1 0 * * 6 Balancing Item 3,249 7,362 ...

  2. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S17. ... 1,844 980 2,403 2,701 Supplemental Gas Supplies 2 1 0 0 1 Balancing Item -1,989 -7,914 ...

  3. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. ... 4,404 3,278 5,208 6,218 Supplemental Gas Supplies 457 392 139 255 530 Balancing Item ...

  4. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S41. ... 698 436 457 645 879 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -1,269 1,045 ...

  5. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S47. ... 0 LNG Storage 0 0 0 0 0 Supplemental Gas Supplies 1 2 3 3 5 Balancing Item -453 -1,711 ...

  6. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S30. ... 195 154 146 210 211 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item 17,590 4,622 ...

  7. 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.

  8. Buildings Energy Data Book: 3.2 Commercial Sector Characteristics

    Buildings Energy Data Book [EERE]

    3 Number of Floors and Type of Ownership, as of 2003 (Percent of Total Floorspace) Floors Ownership One 40% Nongovernment Owned 76% Two 25% Owner-Occupied 36% Three 12% Nonowner-Occupied 37% Four to Nine 16% Unoccupied 3% Ten or More 8% Government Owned 24% Total 100% Federal 3% State 5% Local 15% Total 100% Source(s): EIA, Commercial Building Characteristics 2003, June 2006, Table C1

  9. 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.

  10. Total internal reflection laser tools and methods

    DOE Patents [OSTI]

    Zediker, Mark S.; Faircloth, Brian O.; Kolachalam, Sharath K.; Grubb, Daryl L.

    2016-02-02

    There is provided high power laser tools and laser heads that utilize total internal reflection ("TIR") structures to direct the laser beam along a laser beam path within the TIR structure. The TIR structures may be a TIR prism having its hypotenuse as a TIR surface.

  11. Total pressing Indonesian gas development, exports

    SciTech Connect (OSTI)

    Not Available

    1994-01-24

    Total is on track to become Indonesia's leading gas exporter by the turn of the century. Total's aggressive development of its Mahakam Delta acreage in East Kalimantan is intended to keep pace with growing liquefied natural gas demand, mainly from Japan but also increasingly from South Korea and Taiwan. A frantic scramble is under way among natural gas suppliers in the Pacific Rim region, particularly those with current LNG export facilities, to accommodate projections of soaring natural gas demand in the region. Accordingly, Total's Indonesian gas production goal is the centerpiece of a larger strategy to become a major player in the Far East Asia gas scene. Its goals also fall in line with Indonesia's. Facing flat or declining oil production while domestic oil demand continues to soar along with a rapidly growing economy, Indonesia is heeding some studies that project the country could become a net oil importer by the turn of the century. The paper describes Total's Far East strategy, the Mahakam acreage which it operates, the shift to gas development, added discoveries, future development, project spending levels, and LNG export capacity.

  12. 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.

  13. Million U.S. Housing Units Total............................................................................

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

    Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Home Electronics Usage Indicators Detached Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of

  14. 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).

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Frustrated total internal reflection acoustic field sensor

    DOE Patents [OSTI]

    Kallman, Jeffrey S.

    2000-01-01

    A frustrated total internal reflection acoustic field sensor which allows the acquisition of the acoustic field over an entire plane, all at once. The sensor finds use in acoustic holography and acoustic diffraction tomography. For example, the sensor may be produced by a transparent plate with transparent support members tall enough to support one or more flexible membranes at an appropriate height for frustrated total internal reflection to occur. An acoustic wave causes the membrane to deflect away from its quiescent position and thus changes the amount of light that tunnels through the gap formed by the support members and into the membrane, and so changes the amount of light reflected by the membrane. The sensor(s) is illuminated by a uniform tight field, and the reflection from the sensor yields acoustic wave amplitude and phase information which can be picked up electronically or otherwise.

  1. Fractionated total body irradiation for metastatic neuroblastoma

    SciTech Connect (OSTI)

    Kun, L.E.; Casper, J.T.; Kline, R.W.; Piaskowski, V.D.

    1981-11-01

    Twelve patients over one year old with neuroblastoma (NBL) metastatic to bone and bone marrow entered a study of adjuvant low-dose, fractionated total body irradiation (TBI). Six children who achieved a ''complete clinical response'' following chemotherapy (cyclophosphamide and adriamycin) and surgical resection of the abdominal primary received TBI (10 rad/fraction to totals of 100-120 rad/10-12 fx/12-25 days). Two children received concurrent local irradiation for residual abdominal tumor. The intervals from cessation of chemotherapy to documented progression ranged from 2-16 months, not substatially different from patients receiving similar chemotherapy and surgery without TBI. Three additional children with progressive NBL received similar TBI (80-120 rad/8-12 fx) without objective response.

  2. Total Crude Oil and Petroleum Products Exports

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

    Exports Product: Total Crude Oil and Petroleum Products Crude Oil Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Isobutylene Other Liquids Hydrogen/Oxygenates/Renewables/Other Hydrocarbons Oxygenates (excl. Fuel Ethanol) Methyl Tertiary Butyl Ether (MTBE) Other Oxygenates Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Biomass-Based Diesel Unfinished Oils Naphthas and Lighter

  3. 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.

  4. Total Adjusted Sales of Distillate Fuel Oil

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

    End Use: Total Residential Commercial Industrial Oil Company Farm Electric Power Railroad Vessel Bunkering On-Highway Military Off-Highway All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 55,664,448 58,258,830 59,769,444 57,512,994 58,675,008 61,890,990 1984-2014 East Coast (PADD 1) 18,219,180 17,965,794 17,864,868 16,754,388

  5. Total Adjusted Sales of Residual Fuel Oil

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

    End Use: Total Commercial Industrial Oil Company Electric Power Vessel Bunkering Military All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 7,835,436 8,203,062 7,068,306 5,668,530 4,883,466 3,942,750 1984-2014 East Coast (PADD 1) 3,339,162 3,359,265 2,667,576 1,906,700 1,699,418 1,393,068 1984-2014 New England (PADD 1A) 318,184

  6. Total Sales of Distillate Fuel Oil

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

    End Use: Total Residential Commercial Industrial Oil Company Farm Electric Power Railroad Vessel Bunkering On-Highway Military Off-Highway All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 54,100,092 56,093,645 57,082,558 57,020,840 58,107,155 60,827,930 1984-2014 East Coast (PADD 1) 17,821,973 18,136,965 17,757,005 17,382,566

  7. Total Sales of Residual Fuel Oil

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

    End Use: Total Commercial Industrial Oil Company Electric Power Vessel Bunkering Military All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 6,908,028 7,233,765 6,358,120 6,022,115 5,283,350 4,919,255 1984-2014 East Coast (PADD 1) 2,972,575 2,994,245 2,397,932 2,019,294 1,839,237 1,724,167 1984-2014 New England (PADD 1A) 281,895

  8. 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.

  9. 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.

  10. 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.

  11. "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...

  12. "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 ...

  13. State Residential Commercial Industrial Transportation Total

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

    Sales (Megawatthours) (Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 47,211,525 53,107,038 19,107,433 557,463 119,983,459 Connecticut 12,777,579 12,893,531 3,514,798 168,552 29,354,460 Maine 4,660,605 3,984,570 3,357,486 0 12,002,661 Massachusetts 20,071,160 26,076,208 7,960,941 360,983 54,469,292 New Hampshire 4,510,487 4,464,530 1,969,064 0 10,944,081 Rhode Island 3,070,347 3,657,679 887,150 27,928

  14. Total Ore Processing Integration and Management

    SciTech Connect (OSTI)

    Leslie Gertsch; Richard Gertsch

    2006-01-30

    This report outlines the technical progress achieved for project DE-FC26-03NT41785 (Total Ore Processing Integration and Management) during the period 01 July through 30 September of 2005. This ninth quarterly report discusses the activities of the project team during the period 1 July through 30 September 2005. Richard Gertsch's unexpected death due to natural causes while in Minnesota to work on this project has temporarily slowed progress. Statistical analysis of the Minntac Mine data set for late 2004 is continuing. Preliminary results raised several questions that could be amenable to further study. Detailed geotechnical characterization is being applied to improve the predictability of mill and agglomerator performance at Hibtac Mine.

  15. Performance Period Total Fee Paid FY2001

    Office of Environmental Management (EM)

    FY2001 $4,547,400 FY2002 $4,871,000 FY2003 $6,177,902 FY2004 $8,743,007 FY2005 $13,134,189 FY2006 $7,489,704 FY2007 $9,090,924 FY2008 $10,045,072 FY2009 $12,504,247 FY2010 $17,590,414 FY2011 $17,558,710 FY2012 $14,528,770 Cumulative Fee Paid $126,281,339 Cost Plus Award Fee DE-AC29-01AL66444 Washington TRU Solutions LLC Contractor: Contract Number: Contract Type: $8,743,007 Contract Period: $1,813,482,000 Fee Information Maximum Fee $131,691,744 Total Estimated Contract Cost: $4,547,400

  16. Performance Period Total Fee Paid FY2008

    Office of Environmental Management (EM)

    FY2008 $87,580 FY2009 $87,580 FY2010 $171,763 FY2011 $1,339,286 FY 2012 $38,126 FY 2013 $42,265 Cumulative Fee Paid $1,766,600 $42,265 Cost Plus Incentive Fee/Cost Plus Fixed Fee $36,602,425 Contract Period: September 2007 - November 30, 2012 Target Fee $521,595 Total Estimated Contract Cost Contract Type: Maximum Fee $3,129,570 $175,160 $377,516 $1,439,287 Fee Available $175,160 $80,871 Accelerated Remediation Company (aRc) DE-AT30-07CC60013 Contractor: Contract Number: Minimum Fee $2,086,380

  17. 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.

  18. Buildings Energy Data Book: 3.2 Commercial Sector Characteristics

    Buildings Energy Data Book [EERE]

    6 Commercial Building Vintage, as of 2003 1919 or Before 5% 1920 to 1945 10% 1946 to 1959 10% 1960 to 1969 12% 1970 to 1979 17% 1980 to 1989 17% 1990 to 1999 20% 2000 to 2003 9% Total 100% Source(s): Percent of Total Floorspace EIA, 2003 Commercial Buildings Energy Consumption Survey: Building Characteristics Tables, Oct. 2006, Table A1, p. 1-

  19. Total least squares for anomalous change detection

    SciTech Connect (OSTI)

    Theiler, James P; Matsekh, Anna M

    2010-01-01

    A family of difference-based anomalous change detection algorithms is derived from a total least squares (TLSQ) framework. This provides an alternative to the well-known chronochrome algorithm, which is derived from ordinary least squares. In both cases, the most anomalous changes are identified with the pixels that exhibit the largest residuals with respect to the regression of the two images against each other. The family of TLSQ-based anomalous change detectors is shown to be equivalent to the subspace RX formulation for straight anomaly detection, but applied to the stacked space. However, this family is not invariant to linear coordinate transforms. On the other hand, whitened TLSQ is coordinate invariant, and furthermore it is shown to be equivalent to the optimized covariance equalization algorithm. What whitened TLSQ offers, in addition to connecting with a common language the derivations of two of the most popular anomalous change detection algorithms - chronochrome and covariance equalization - is a generalization of these algorithms with the potential for better performance.

  20. 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

  1. Apparatus and method for quantitatively evaluating total fissile and total fertile nuclide content in samples

    DOE Patents [OSTI]

    Caldwell, John T. (Los Alamos, NM); Kunz, Walter E. (Santa Fe, NM); Cates, Michael R. (Oak Ridge, TN); Franks, Larry A. (Santa Barbara, CA)

    1985-01-01

    Simultaneous photon and neutron interrogation of samples for the quantitative determination of total fissile nuclide and total fertile nuclide material present is made possible by the use of an electron accelerator. Prompt and delayed neutrons produced from resulting induced fissions are counted using a single detection system and allow the resolution of the contributions from each interrogating flux leading in turn to the quantitative determination sought. Detection limits for .sup.239 Pu are estimated to be about 3 mg using prompt fission neutrons and about 6 mg using delayed neutrons.

  2. Minnesota Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    Minnesota Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 ... Share of Total U.S. Natural Gas Residential Deliveries Minnesota Share of Total U.S. ...

  3. California Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    California Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 ... Share of Total U.S. Natural Gas Residential Deliveries California Share of Total U.S. ...

  4. Minnesota Natural Gas Total Consumption (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Total Consumption (Million Cubic Feet) Minnesota Natural Gas Total Consumption (Million ... Referring Pages: Natural Gas Consumption Minnesota Natural Gas Consumption by End Use ...

  5. California Natural Gas Total Consumption (Million Cubic Feet...

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

    Total Consumption (Million Cubic Feet) California Natural Gas Total Consumption (Million ... Referring Pages: Natural Gas Consumption California Natural Gas Consumption by End Use ...

  6. Total Crude Oil and Petroleum Products Imports by Processing...

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

    Product: Total Crude Oil and Petroleum Products Crude Oil Total Products Other Liquids Unfinished Oils Naphthas and Lighter Kerosene and Light Gas Oils Heavy Gas Oils Residuum ...

  7. NREL: Building America Total Quality Management - 2015 Peer Review...

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

    NREL: Building America Total Quality Management - 2015 Peer Review NREL: Building America Total Quality Management - 2015 Peer Review Presenter: Stacey Rothgeb, NREL View the ...

  8. ,"Total District Heat Consumption (trillion Btu)",,,,,"District...

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

    Heat Consumption (trillion Btu)",,,,,"District Heat Energy Intensity (thousand Btusquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  9. ,"Total Natural Gas Consumption (trillion Btu)",,,,,"Natural...

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

    Gas Consumption (trillion Btu)",,,,,"Natural Gas Energy Intensity (thousand Btusquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  10. Total Energy Facilities Biomass Facility | Open Energy Information

    Open Energy Info (EERE)

    Energy Facilities Biomass Facility Jump to: navigation, search Name Total Energy Facilities Biomass Facility Facility Total Energy Facilities Sector Biomass Facility Type...

  11. Webtrends Archives by Fiscal Year — EERE Totals

    Broader source: Energy.gov [DOE]

    Historical EERE office total reports include only Webtrends archives by fiscal year. EERE total reports dating after FY11 can be accessed in EERE's Google Analytics account.

  12. Estimation of Anisotoropy from Total Cross Section and Optical...

    Office of Scientific and Technical Information (OSTI)

    Conference: Estimation of Anisotoropy from Total Cross Section and Optical Model Citation Details In-Document Search Title: Estimation of Anisotoropy from Total Cross Section and ...

  13. Total lymphoid irradiation for multiple sclerosis

    SciTech Connect (OSTI)

    Devereux, C.K.; Vidaver, R.; Hafstein, M.P.; Zito, G.; Troiano, R.; Dowling, P.C.; Cook, S.D.

    1988-01-01

    Although chemical immunosuppression has been shown to benefit patients with chronic progressive multiple sclerosis (MS), it appears that chemotherapy has an appreciable oncogenic potential in patients with multiple sclerosis. Accordingly, we developed a modified total lymphoid irradiation (TLI) regimen designed to reduce toxicity and applied it to a randomized double blind trial of TLI or sham irradiation in MS. Standard TLI regimens were modified to reduce dose to 1,980 rad, lowering the superior mantle margin to midway between the thyroid cartilage and angle of the mandible (to avert xerostomia) and the lower margin of the mantle field to the inferior margin of L1 (to reduce gastrointestinal toxicity by dividing abdominal radiation between mantle and inverted Y), limiting spinal cord dose to 1,000 rad by custom-made spine blocks in the mantle and upper 2 cm of inverted Y fields, and also protecting the left kidney even if part of the spleen were shielded. Clinical efficacy was documented by the less frequent functional scale deterioration of 20 TLI treated patients with chronic progressive MS compared to to 20 sham-irradiated progressive MS patients after 12 months (16% versus 55%, p less than 0.03), 18 months (28% versus 63%, p less than 0.03), and 24 months (44% versus 74%, N.S.). Therapeutic benefit during 3 years follow-up was related to the reduction in lymphocyte count 3 months post-irradiation (p less than 0.02). Toxicity was generally mild and transient, with no instance of xerostomia, pericarditis, herpes zoster, or need to terminate treatment in TLI patients. However, menopause was induced in 2 patients and staphylococcal pneumonia in one.

  14. Investigation of lasing characteristics of 1% Nd : YAG laser ceramics

    SciTech Connect (OSTI)

    Vatnik, S M; Osipov, V V; Vedin, I A; Kurbatov, P F

    2013-03-31

    The lasing characteristics of 1 % Nd : YAG laser ceramics synthesised at the Institute of Electrophysics, Ural Branch, Russian Academy of Sciences are studied. CW lasing is obtained in all the samples with the slope and total optical efficiencies of 25 % and 18 %, respectively. Intrinsic absorption and scattering losses in the ceramics are estimated. (extreme light fields and their applications)

  15. " Million U.S. Housing Units"

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

    3 Household 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" "Household Characteristics" "Total",111.1,30,34.8,18.4,15.9,12 "Household Size" "1

  16. 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

  17. 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...

  18. " 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"

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

    SciTech Connect (OSTI)

    Bernstad, A.; Cour Jansen, J. la

    2012-05-15

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

  20. 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%

  1. Time evolution of the total electric-field strength in multimode lasers

    SciTech Connect (OSTI)

    Brunner, W.; Fischer, R.; Paul, H.

    1988-05-01

    Our previous numerical studies of the output characteristics of multimode lasers are extended to include the evolution of the total electric-field strength. The regular or irregular behavior of the system, which becomes manifest in the evolution of the amplitudes and the phases in the different modes, is reflected also in the evolution of the total electric-field strength in a stroboscopic view. (The total electric-field strength, with its high-frequency time dependence suppressed, is considered at times t, t+..delta..t, t+2..delta..t,..., where ..delta..t is a multiple of the round-trip time in the resonator.) Moreover, it is demonstrated that the evolution of the system is very sensitive to slight changes in the initial conditions. This finding supports the view that the irregularity falls in the class of the so-called deterministic chaos.

  2. 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.

  3. New Mexico Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) New Mexico Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  4. Connecticut Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Connecticut Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

  5. Connecticut Natural Gas Total Consumption (Million Cubic Feet...

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

    Total Consumption (Million Cubic Feet) Connecticut Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  6. Maine Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Maine Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's...

  7. Maine Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Maine Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  8. Project Functions and Activities Definitions for Total Project Cost

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

    1997-03-28

    This chapter provides guidelines developed to define the obvious disparity of opinions and practices with regard to what exactly is included in total estimated cost (TEC) and total project cost (TPC).

  9. Total China Investment Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    China Investment Co Ltd Jump to: navigation, search Name: Total (China) Investment Co. Ltd. Place: Beijing, China Zip: 100004 Product: Total has been present in China for about 30...

  10. Virginia Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Virginia Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  11. Washington Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) Washington Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  12. Delaware Total Electric Power Industry Net Generation, by Energy...

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

    ...e","-","-","-","-","-" "Other","-","-",11,6,"-" "Total",7182,8534,7524,4842,5628 " " "s Value is less than 0.5 of the table metric, but value is included in any associated total.

  13. Kansas Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Kansas Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  14. Arizona Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Arizona Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  15. Arizona Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) Arizona Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  16. ,"Total Crude Oil and Petroleum Products Net Receipts by Pipeline...

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

    Data for" ,"Data 1","Total Crude Oil and Petroleum Products Net Receipts by ... PM" "Back to Contents","Data 1: Total Crude Oil and Petroleum Products Net Receipts by ...

  17. NREL: Building America Total Quality Management - 2015 Peer Review |

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

    Department of Energy NREL: Building America Total Quality Management - 2015 Peer Review NREL: Building America Total Quality Management - 2015 Peer Review Presenter: Stacey Rothgeb, NREL View the Presentation PDF icon NREL: Building America Total Quality Management - 2015 Peer Review More Documents & Publications Home Performance with ENERGY STAR - 2014 BTO Peer Review NREL: Building America Total Quality Management - 2015 Peer Review R25 Polyisocyanurate Composite Insulation Material

  18. 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

  19. 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.

  20. 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...

  1. Scaling properties of proton-nucleus total reaction cross sections

    SciTech Connect (OSTI)

    Abu-Ibrahim, Badawy; Kohama, Akihisa

    2010-05-15

    We study the scaling properties of proton-nucleus total reaction cross sections for stable nuclei and propose an approximate expression in proportion to Z{sup 2/3}sigma{sub pp}{sup total}+N{sup 2/3}sigma{sub pn}{sup total}. Based on this expression, we can derive a relation that enables us to predict a total reaction cross section for any stable nucleus within 10% uncertainty at most, using the empirical value of the total reaction cross section of a given nucleus.

  2. 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.

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

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

    b. Household Characteristics by Four Most Populated States, Percent of U.S. Households, 1997 Household Characteristics RSE Column Factor: Total Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.2 1.4 1.4 Total .............................................................. 100.0 100.0 100.0 100.0 100.0 0.0 1997 Household Income Category Less than $5,000 ......................................... 3.7 4.3 2.8 4.8 1.9 16.2 $5,000 to $9,999

  4. CBECS Buildings Characteristics --Revised Tables

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

    Summary Tables (12 pages, 59 kb) CONTENTS PAGES 1. Summary Table: Totals and Means of Floorspace, Number of Workers, and Hours of Operation, 1995 2. Summary Table: Totals and Medians of Floorspace, Number of Workers, Hours of Operation, and Age of Building, 1995 These data are from the 1995 Commercial Buildings Energy Consumption Survey (CBECS), a national probability sample survey of commercial buildings sponsored by the Energy Information Administration, that provides information on the use of

  5. Total dissolved gas prediction and optimization in RiverWare

    SciTech Connect (OSTI)

    Stewart, Kevin M.; Witt, Adam M.; Hadjerioua, Boualem

    2015-09-01

    Management and operation of dams within the Columbia River Basin (CRB) provides the region with irrigation, hydropower production, flood control, navigation, and fish passage. These various system-wide demands can require unique dam operations that may result in both voluntary and involuntary spill, thereby increasing tailrace levels of total dissolved gas (TDG) which can be fatal to fish. Appropriately managing TDG levels within the context of the systematic demands requires a predictive framework robust enough to capture the operationally related effects on TDG levels. Development of the TDG predictive methodology herein attempts to capture the different modes of hydro operation, thereby making it a viable tool to be used in conjunction with a real-time scheduling model such as RiverWare. The end result of the effort will allow hydro operators to minimize system-wide TDG while meeting hydropower operational targets and constraints. The physical parameters such as spill and hydropower flow proportions, accompanied by the characteristics of the dam such as plant head levels and tailrace depths, are used to develop the empirically-based prediction model. In the broader study, two different models are developed a simplified and comprehensive model. The latter model incorporates more specific bubble physics parameters for the prediction of tailrace TDG levels. The former model is presented herein and utilizes an empirically based approach to predict downstream TDG levels based on local saturation depth, spillway and powerhouse flow proportions, and entrainment effects. Representative data collected from each of the hydro projects is used to calibrate and validate model performance and the accuracy of predicted TDG uptake. ORNL, in conjunction with IIHR - Hydroscience & Engineering, The University of Iowa, carried out model adjustments to adequately capture TDG levels with respect to each plant while maintaining a generalized model configuration. Validation results indicate excellent model performance with coefficient of determination values exceeding 92% for all sites. This approach enables model extension to an increasingly wider array of hydropower plants, i.e., with the proper data input, TDG uptake can be calculated independent of actual physical component design. The TDG model is used as a module in the systematic optimization framework of RiverWare, a river and reservoir modeling tool used by federal agencies, public utility districts, and other dam owners and operators to forecast, schedule, and manage hydropower assets. The integration and testing of the TDG module within RiverWare, led by University of Colorado s Center for Advanced Decision Support for Water and Environmental Systems (CADSWES), will allow users to generate optimum system schedules based on the minimization of TDG. Optimization analysis and added value will be quantified as system wide reductions in TDG achieved while meeting existing hydropower constraints. Future work includes the development of a method to predict downstream reservoir forebay TDG levels as a function of upstream reservoir tailrace TDG values based on river hydrodynamics, hydro operations, and reservoir characteristics. Once implemented, a holistic model that predicts both TDG uptake and transport will give hydropower operators valuable insight into how system-wide environmental effects can be mitigated while simultaneously balancing stakeholder interests.

  6. 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

  7. Table HC1.1.4 Housing Unit Characteristics by Average Floorspace--Apartments, 2

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

    4 Housing Unit Characteristics by Average Floorspace--Apartments, 2005" ,,,"Average Square Feet per Apartment in a --" ," Housing Units (millions)" ,,,"2 to 4 Unit Building",,,"5 or More Unit Building" ,,"Apartments (millions)" "Housing Unit Characteristics",,,"Total","Heated","Cooled","Total","Heated","Cooled" "Total",111.1,24.5,1090,902,341,872,780,441

  8. Table HC1.2.4 Living Space Characteristics by Average Floorspace--Apartments, 2

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

    2.4 Living Space Characteristics by Average Floorspace--Apartments, 2005" ,,,"Average Square Feet per Apartment in a --" ," Housing Units (millions)" ,,,"2 to 4 Unit Building",,,"5 or More Unit Building" ,,"Apartments (millions)" "Living Space Characteristics",,,"Total","Heated","Cooled","Total","Heated","Cooled" "Total",111.1,24.5,1090,902,341,872,780,441

  9. "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

  10. "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

  11. "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

  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. Percentage of Total Natural Gas Industrial Deliveries included in Prices

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

    Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010

  14. Percentage of Total Natural Gas Industrial Deliveries included in Prices

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

    City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S.

  15. Percentage of Total Natural Gas Residential Deliveries included in Prices

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

    City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S.

  16. Percentage of Total Natural Gas Commercial Deliveries included in Prices

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

    City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S.

  17. Real-space formulation of the electrostatic potential and total...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Real-space formulation of the electrostatic potential and total energy of solids Citation Details In-Document Search Title: Real-space formulation of the ...

  18. Trends in Commercial Buildings--Total Primary Energy Detail

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

    Energy Consumption and Graph Total Primary Energy Consumption Graph Detail and Data Table 1979 to 1992 primary consumption trend with 95% confidence ranges 1979 to 1992 primary...

  19. Trends in Commercial Buildings--Total Site Energy Detail

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

    Energy Consumption and Graph Total Site Energy Consumption Graph Detail and Data Table 1979 to 1992 site consumption trend with 95% confidence ranges 1979 to 1992 site...

  20. ,"Crude Oil and Petroleum Products Total Stocks Stocks by Type...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks by Type",6,"Monthly","82015","1151956"...