National Library of Energy BETA

Sample records for household size percent

  1. 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...

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

    Office of Energy Efficiency and Renewable Energy (EERE)

    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. Sizing wind/photovoltaic hybrids for households in inner Mongolia

    SciTech Connect (OSTI)

    Barley, C.D.; Lew, D.J.; Flowers, L.T.

    1997-12-31

    Approximately 140,000 wind turbines currently provide electricity to about one-third of the non-grid-connected households in Inner Mongolia. However, these households often suffer from a lack of power during the low-wind summer months. This report describes an analysis of hybrid wind/photovoltaic (PV) systems for such households. The sizing of the major components is based on a subjective trade-off between the cost of the system and the percent unmet load, as determined by the Hybrid2 software in conjunction with a simplified time-series model. Actual resource data (wind speed and solar radiation) from the region are processed so as to best represent the scenarios of interest. Small wind turbines of both Chinese and U.S. manufacture are considered in the designs. The results indicate that combinations of wind and PV are more cost-effective than either one alone, and that the relative amount of PV in the design increases as the acceptable unmet load decreases and as the average wind speed decreases.

  4. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  5. 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

  6. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    0a. Household Characteristics by Midwest Census Region, Million U.S. Households, 2001 Household 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 1.7 Total .............................................................. 107.0 24.5 17.1 7.4 NE Household Size 1 Person ...................................................... 28.2 6.7 4.7 2.0 6.2 2 Persons

  7. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    1a. Household Characteristics by South Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.5 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Household Size 1 Person ...................................................... 28.2 9.9 5.0 1.8 3.1 6.3 2 Persons

  8. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    2a. Household Characteristics by West Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.8 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Household Size 1 Person ...................................................... 28.2 5.6 1.8 3.8 5.4 2 Persons .................................................... 35.1 7.3 1.9 5.5

  9. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    4a. Household Characteristics by Type of Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.4 0.5 1.6 1.4 2.0 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.3 Household Size 1 Person ....................................... 28.2 15.0 3.3 7.9 1.9 5.9 2 Persons

  10. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total Rented Units ........................ 34.3 10.5 7.4 15.2 1.1 6.9 Household Size 1 Person ....................................... 12.3 2.5 2.6 7.0 0.3 10.0 2 Persons

  11. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    8a. Household Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Household Size 1 Person ...................................................... 28.2 14.6 5.3 4.8 3.6 6.4 2 Persons .................................................... 35.1 15.7 5.7

  12. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    3a. Household Characteristics by Household Income, Million U.S. Households, 2001 Household 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 Household Size 1 Person ....................................... 28.2 9.7 --

  13. Household magnets

    U.S. Department of Energy (DOE) all 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

  14. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Household Size 1 Person ....................................... 28.2 2.5 8.1 6.5

  15. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  16. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Household 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 0.3 0.4 2.0 2.9 1.3 Total Owner-Occupied Units ....... 72.7 63.2 2.1 1.8 5.7 6.7 Household Size 1 Person ....................................... 15.8 12.5 0.8 0.9 1.6 10.3 2 Persons

  17. Variable Average Absolute Percent Differences

    U.S. Energy Information Administration (EIA) (indexed site)

    Variable Average Absolute Percent Differences Percent of Projections Over- Estimated Gross Domestic Product Real Gross Domestic Product (Average Cumulative Growth)* (Table 2) 0.9 45.8 Petroleum Imported Refiner Acquisition Cost of Crude Oil (Constant $) (Table 3a) 37.7 17.3 Imported Refiner Acquisition Cost of Crude Oil (Nominal $) (Table 3b) 36.6 18.7 Total Petroleum Consumption (Table 4) 7.9 70.7 Crude Oil Production (Table 5) 8.1 51.1 Petroleum Net Imports (Table 6) 24.7 73.8 Natural Gas

  18. 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....

  19. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    0 New Hampshire - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle ...

  20. Norwich Public Utilities- Zero Percent Financing Program

    Energy.gov [DOE]

    In partnership with several local banks, Norwich Public Utilities (NPU) is offering a zero percent loan to commercial and industrial customers for eligible energy efficiency improvement projects....

  1. Million Cu. Feet Percent of National Total

    Annual Energy Outlook

    Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: ...

  2. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    its Major Metropolitan Area, 1960-1990, Cambridge, MA, 1994, p. 2-2. 2000 data - U.S. Bureau of the Census, American Fact Finder, factfinder.census.gov, Table QT-04, August 2001. ...

  4. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    Table S47. Summary statistics for natural gas - Vermont, 2010-2014 - continued -- Not applicable. < Percentage is less than 0.05 percent. R Revised data. W Withheld. a Pipeline and ...

  5. Try This: Household Magnets

    U.S. Department of Energy (DOE) all 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

  6. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    4 Delaware - Natural Gas 2015 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 S8. Summary statistics for natural gas - Delaware, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 0 0 0 0 0 Gas Wells 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals

  7. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    4 Massachusetts - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 0 0 0 0 0 Gas Wells 0 0 0 0 0 Production (million cubic feet) Gross

  8. District of Columbia Natural Gas Percent Sold to The Commercial...

    U.S. Energy Information Administration (EIA) (indexed site)

    by Local Distribution Companies (Percent) District of Columbia Natural Gas Percent Sold to The Commercial Sectors by Local Distribution Companies (Percent) Decade Year-0 ...

  9. 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 ...

  10. usage_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    Usage Indicators by South Census Region, Million U.S. Households, 2001 5 HC6-12a. Usage Indicators by West Census Region, Million U.S. Households, 2001 5 These data are from the ...

  11. char_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    2001 2 HC2-12a. Household Characteristics by West Census Region, Million U.S. Households, 2001 2 These data are from the 2001 Residential Energy Consumption Survey ...

  12. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    Home Office Equipment by South Census Region, Million U.S. Households, 2001 1 HC7-12a. Home Office Equipment by West Census Region, Million U.S. Households, 2001 1 These data are ...

  13. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    0 Alabama - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 346 367 402 436 414 Gas Wells R 6,243 R 6,203 R 6,174 R 6,117 6,044 Production

  14. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    2 Alaska - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 2,040 1,981 2,006 2,042 2,096 Gas Wells R 274 R 281 R 300 R 338 329 Production

  15. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    0 Colorado - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 5,963 6,456 6,799 7,771 7,733 Gas Wells R 43,792 R 46,141 R 46,883 R 46,876

  16. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    6 District of Columbia - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 0 0 0 0 0 Gas Wells 0 0 0 0 0 Production (million cubic

  17. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    4 Hawaii - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 0 0 0 0 0 Gas Wells 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From

  18. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    6 Idaho - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 0 0 0 0 0 Gas Wells 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From

  19. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    20 Maine - Natural Gas 2015 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 S21. Summary statistics for natural gas - Maine, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 0 0 0 0 0 Gas Wells 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From

  20. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    0 Mississippi - Natural Gas 2015 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 S26. Summary statistics for natural gas - Mississippi, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 561 618 581 540 501 Gas Wells R 1,703 R 1,666 R 1,632 R 1,594 1,560

  1. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    4 Montana - Natural Gas 2015 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 S28. Summary statistics for natural gas - Montana, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 1,956 2,147 2,268 2,377 2,277 Gas Wells R 6,615 R 6,366 R 5,870 R 5,682 5,655

  2. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    4 New Mexico - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 12,887 13,791 14,171 14,814 14,580 Gas Wells R 40,231 R 40,441 R 40,119 R

  3. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    6 New York - Natural Gas 2015 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 S34. Summary statistics for natural gas - New York, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 988 1,170 1,589 1,731 1,697 Gas Wells R 7,372 R 7,731 R 7,553 R 7,619 7,605

  4. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    0 North Dakota - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 5,561 7,379 9,363 11,532 12,799 Gas Wells R 526 R 451 R 423 R 398 462

  5. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    2 Ohio - Natural Gas 2015 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 S37. Summary statistics for natural gas - Ohio, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 6,775 6,745 7,038 7,257 5,941 Gas Wells R 31,966 R 31,647 R 30,804 R 31,060 26,599

  6. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    4 Oklahoma - Natural Gas 2015 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 S38. Summary statistics for natural gas - Oklahoma, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 6,723 7,360 8,744 7,105 8,368 Gas Wells R 51,712 R 51,472 R 50,606 R 50,044

  7. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    6 Oregon - Natural Gas 2015 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, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 0 0 0 0 0 Gas Wells R 28 R 24 R 24 R 12 14 Production (million cubic feet) Gross

  8. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    8 Pennsylvania - Natural Gas 2015 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 S40. Summary statistics for natural gas - Pennsylvania, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 7,046 7,627 7,164 8,481 7,557 Gas Wells R 61,815 R 62,922 R 61,838 R

  9. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    6 Tennessee - Natural Gas 2015 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 S44. Summary statistics for natural gas - Tennessee, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 52 75 NA NA NA Gas Wells R 1,027 R 1,027 1,089 NA NA Production (million cubic

  10. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    8 Texas - Natural Gas 2015 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 S45. Summary statistics for natural gas - Texas, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 85,030 94,203 96,949 104,205 105,159 Gas Wells R 139,368 R 140,087 R 140,964 R 142,292

  11. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    0 Utah - Natural Gas 2015 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 S46. Summary statistics for natural gas - Utah, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 3,119 3,520 3,946 4,249 3,966 Gas Wells R 7,603 R 8,121 R 8,300 R 8,537 8,739 Production

  12. Million Cu. Feet Percent of National Total

    U.S. Energy Information Administration (EIA) (indexed site)

    4 Virginia - Natural Gas 2015 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 S48. Summary statistics for natural gas - Virginia, 2011-2015 2011 2012 2013 2014 2015 Number of Wells Producing Natural Gas at End of Year Oil Wells 2 1 1 2 2 Gas Wells R 7,781 R 7,874 7,956 R 8,061 8,111 Production (million

  13. ac_household2001.pdf

    Annual Energy Outlook

    ... those households were treated as if the fuel was electricity. 3 The 2001 RECS reported ... Notes: * To obtain the RSE percentage for any table cell, multiply the corresponding ...

  14. Household Vehicles Energy Consumption 1991

    U.S. Energy Information Administration (EIA) (indexed site)

    or commercial trucks (See Table 1). Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 5 The 1991 RTECS count includes vehicles that were owned or used...

  15. Household Vehicles Energy Consumption 1991

    U.S. Energy Information Administration (EIA) (indexed site)

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991...

  16. Percent of Commercial Natural Gas Deliveries in California Represented...

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    California Represented by the Price (Percent) Percent of Commercial Natural Gas Deliveries in California Represented by the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep ...

  17. Percent of Industrial Natural Gas Deliveries in New Mexico Represented...

    U.S. Energy Information Administration (EIA) (indexed site)

    Mexico Represented by the Price (Percent) Percent of Industrial Natural Gas Deliveries in New Mexico Represented by the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct ...

  18. Arizona - Natural Gas 2015 Million Cu. Feet Percent...

    Gasoline and Diesel Fuel Update

    4 Arizona - Natural Gas 2015 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: ...

  19. Federal Government Increases Renewable Energy Use Over 1000 Percent...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal Federal Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal...

  20. Household energy use in non-OPEC developing countries

    SciTech Connect (OSTI)

    Fernandez, J.C.

    1980-05-01

    Energy use in the residential sector in India, Brazil, Mexico, the Republic of Korea, the Sudan, Pakistan, Malaysia, and Guatemala is presented. Whenever possible, information is included on the commercial fuels (oil, gas, coal, and electricity) and on what are termed noncommercial fuels (firewood, animal dung, and crop residues). Of special interest are the differences in the consumption patterns of urban and rural areas, and of households at different income levels. Where the data allow, the effect of household size on energy consumption is discussed. Section II is an overview of the data for all eight countries. Section III examines those areas (India, Brazil, Mexico City) for which data exist on the actual quantity of energy consumed by households. Korea, the Sudan, and Pakistan, which collect data on household expenditures on fuels, are discussed in Section IV. The patterns of ownership of energy-using durables in Malaysia and Guatemala are discussed in Section V. (MCW)

  1. Household vehicles energy consumption 1994

    SciTech Connect (OSTI)

    1997-08-01

    Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

  2. 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 ...

  3. 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 *...

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

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    Shared Solar Projects Powering Households Throughout America Shared Solar Projects Powering Households Throughout America January 31, 2014 - 2:30pm Addthis Shared solar projects ...

  5. Next Generation Household Refrigerator | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Next Generation Household Refrigerator Next Generation Household Refrigerator Embraco's high efficiency, oil-free linear compressor.
    Credit: Whirlpool Embraco's high ...

  6. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  7. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    3a. Appliances by Household Income, Million U.S. Households, 2001 Appliance Types and 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 0.5 1.4 1.1 1.0 0.8 1.6 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.2 Kitchen Appliances Cooking Appliances Oven

  8. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  9. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  10. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.4 1.2 1.7 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 10.7 3.4 7.2 7.1 Air Conditioners Not Used ........................... 2.1 1.1 0.2 0.9 15.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 9.6 3.2

  11. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

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

    U.S. Energy Information Administration (EIA) (indexed site)

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

  13. Household Vehicles Energy Consumption 1991

    U.S. Energy Information Administration (EIA) (indexed site)

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

  14. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    3a. Air Conditioning by Household Income, Million U.S. Households, 2001 Air Conditioning 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 0.5 1.4 1.1 1.0 0.9 1.5 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 12.3 17.4 21.5 31.7 9.6 23.4 3.9 Air Conditioners Not Used ............ 2.1 0.4 0.7 0.5 0.5 0.4 0.9 20.8

  15. Household waste disposal in Mekelle city, Northern Ethiopia

    SciTech Connect (OSTI)

    Tadesse, Tewodros Ruijs, Arjan; Hagos, Fitsum

    2008-07-01

    In many cities of developing countries, such as Mekelle (Ethiopia), waste management is poor and solid wastes are dumped along roadsides and into open areas, endangering health and attracting vermin. The effects of demographic factors, economic and social status, waste and environmental attributes on household solid waste disposal are investigated using data from household survey. Household level data are then analyzed using multinomial logit estimation to determine the factors that affect household waste disposal decision making. Results show that demographic features such as age, education and household size have an insignificant impact over the choice of alternative waste disposal means, whereas the supply of waste facilities significantly affects waste disposal choice. Inadequate supply of waste containers and longer distance to these containers increase the probability of waste dumping in open areas and roadsides relative to the use of communal containers. Higher household income decreases the probability of using open areas and roadsides as waste destinations relative to communal containers. Measures to make the process of waste disposal less costly and ensuring well functioning institutional waste management would improve proper waste disposal.

  16. Cover Page of Household Vehicles Energy Use: Latest Data & Trends

    Gasoline and Diesel Fuel Update

    Household Vehicles Energy Use Cover Page Cover Page of Household Vehicles Energy Use: Latest Data & Trends...

  17. Alabama Natural Gas Percentage Total Industrial Deliveries (Percent...

    Gasoline and Diesel Fuel Update

    Industrial Deliveries (Percent) Alabama Natural Gas Percentage Total Industrial Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

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

    Gasoline and Diesel Fuel Update

    % 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...

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

    Annual Energy Outlook

    % 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...

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

    Gasoline and Diesel Fuel Update

    % 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...

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

    Gasoline and Diesel Fuel Update

    % 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...

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

    Annual Energy Outlook

    % 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...

  3. Waste Isolation Pilot Plant Contractor Receives 86 Percent of...

    Office of Environmental Management (EM)

    Waste Isolation Pilot Plant Contractor Receives 86 Percent of Available Fee Waste Isolation Pilot Plant Contractor Receives 86 Percent of Available Fee April 27, 2016 - 12:20pm ...

  4. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  5. 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 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.1 1.2 1.1 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 13.6 16.0 14.7 10.4 10.5 17.6 4.7 Air Conditioners Not Used ............ 2.1 Q 0.3 0.5 0.3 0.4 0.5 27.2 Households Using Electric Air-Conditioning 2

  6. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  7. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  8. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  9. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  10. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  11. 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

  12. ac_household2001.pdf

    Annual Energy Outlook

    RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With ... RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Pays for Electricity ...

  13. char_household2001.pdf

    Annual Energy Outlook

    RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total ... RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Household Owns or ...

  14. Federal Government Increases Renewable Energy Use Over 1000 Percent since

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    1999; Exceeds Goal | Department of Energy Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal Federal Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal November 3, 2005 - 12:35pm Addthis WASHINGTON, DC - The Department of Energy (DOE) announced today that the federal government has exceeded its goal of obtaining 2.5 percent of its electricity needs from renewable energy sources by September 30, 2005. The largest energy

  15. Fact #942: September 12, 2016 Fifteen Percent of Survey Respondents

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Consider Fuel Economy Most Important when Purchasing a Vehicle - Dataset | Department of Energy 2: September 12, 2016 Fifteen Percent of Survey Respondents Consider Fuel Economy Most Important when Purchasing a Vehicle - Dataset Fact #942: September 12, 2016 Fifteen Percent of Survey Respondents Consider Fuel Economy Most Important when Purchasing a Vehicle - Dataset Excel file and dataset for Fifteen Percent of Survey Respondents Consider Fuel Economy Most Important when Purchasing a

  16. Dismantlements of Nuclear Weapons Jump 50 Percent | National...

    National Nuclear Security Administration (NNSA)

    Dismantlements of Nuclear Weapons Jump 50 Percent June 07, 2007 WASHINGTON, D.C. -- Meeting President Bush's directive to reduce the country's nuclear arsenal, the Department of ...

  17. Nuclear Weapons Dismantlement Rate Up 146 Percent | National...

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    Nuclear Weapons Dismantlement Rate Up 146 Percent October 01, 2007 WASHINGTON, D.C. -- The United States significantly increased its rate of dismantled nuclear weapons during ...

  18. Million Cu. Feet Percent of National Total Million Cu. Feet...

    Annual Energy Outlook

    Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: ...

  19. Million Cu. Feet Percent of National Total Million Cu. Feet...

    Annual Energy Outlook

    Feet Percent of National Total Total Net Movements: -1,159,080 - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total ...

  20. Million Cu. Feet Percent of National Total Million Cu. Feet...

    Gasoline and Diesel Fuel Update

    Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: 0 Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: ...

  1. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  2. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  3. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  4. 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...

  5. Nevada Natural Gas % of Total Residential Deliveries (Percent...

    Annual Energy Outlook

    Nevada Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 ... Share of Total U.S. Natural Gas Residential Deliveries Nevada Share of Total U.S. Natural ...

  6. Texas Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update

    Texas Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 ... Share of Total U.S. Natural Gas Residential Deliveries Texas Share of Total U.S. Natural ...

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

    Annual Energy Outlook

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

  8. New York Natural Gas % of Total Residential Deliveries (Percent...

    Annual Energy Outlook

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

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

    Gasoline and Diesel Fuel Update

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

  10. New Jersey Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update

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

  11. BOSS Measures the Universe to One-Percent Accuracy

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    This and future measures at this precision are the key to determining the nature of dark energy. "One-percent accuracy in the scale of the universe is the most precise such ...

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

    Gasoline and Diesel Fuel Update

    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. ...

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

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

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

  14. Fact #942: September 12, 2016 Fifteen Percent of Survey Respondents

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Consider Fuel Economy Most Important when Purchasing a Vehicle | Department of Energy 2: September 12, 2016 Fifteen Percent of Survey Respondents Consider Fuel Economy Most Important when Purchasing a Vehicle Fact #942: September 12, 2016 Fifteen Percent of Survey Respondents Consider Fuel Economy Most Important when Purchasing a Vehicle SUBSCRIBE to the Fact of the Week A 2016 survey of the general population asked "Which one of the following attributes would be most important in your

  15. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  16. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  17. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  18. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  19. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  20. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  1. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  2. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  3. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

    5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.4 1.9 3.0 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Heat Home ..................................... 72.4 63.0 2.0 1.7 5.7 6.7 Do Not Heat Home

  4. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  5. Strategies for Collecting Household Energy Data

    Energy.gov [DOE]

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

  6. 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.

  7. BOSS Measures the Universe to One-Percent Accuracy

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    BOSS Measures the Universe to One-Percent Accuracy BOSS Measures the Universe to One-Percent Accuracy The Baryon Oscillation Spectroscopic Survey makes the most precise calibration yet of the universe's "standard ruler" January 8, 2014 Contact: Paul Preuss, Paul_Preuss@lbl.gov , +1 415-272-3253 BOSS-BAOv1.jpg Baryon acoustic oscillations (gray spheres), which descend from waves of increased density in the very early universe, are where galaxies have a tendency to cluster or align -- an

  8. PERCENT FEDERAL LAND FOR OIL/GAS FIELD OUTLINES

    U.S. Energy Information Administration (EIA) (indexed site)

    PERCENT FEDERAL LAND FOR OIL/GAS FIELD OUTLINES The VBA code below calculates the area percent of a first polygon layer (e.g. oil/gas field outlines) that are within a second polygon layer (e.g. federal land) and writes out the fraction as an attribute for the first polygon layer. If you make buffered well field outline polygons using the VBA code in BUFFERED_WELL_FIELD_OUTLINES.doc, you will have a feature class with the attribute PCTFEDLAND to use as the first polygon layer. If not, add the

  9. Los Alamos reduces water use by 26 percent in 2014

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    Los Alamos reduces water use Los Alamos reduces water use by 26 percent in 2014 The Lab decreased its water usage by 26 percent, with about one-third of the reduction attributable to using reclaimed water to cool a supercomputing center. March 16, 2015 Los Alamos National Laboratory sits on top of a once-remote mesa in northern New Mexico with the Jemez mountains as a backdrop to research and innovation covering multi-disciplines from bioscience, sustainable energy sources, to plasma physics and

  10. U.S. Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    Deliveries (Percent) U.S. 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 Year-9 1990's 100 100 100 100 100 100 100 2000's 100 100 100 100 100 100 100 100 100 100 2010's 100 100 100 100 100 100 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Share of Total U.S. Natural Gas

  11. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  12. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  13. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

  14. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) (indexed site)

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

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

  16. 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.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

  18. 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...

  19. 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 ...

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

    Open Energy Information (Open El) [EERE & EIA]

    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...

  1. Louisiana Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Louisiana 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 Year-9 1990's 1.14 1.09 1.09 1.08 1.06 1.05 0.95 2000's 1.00 1.03 1.01 0.93 0.88 0.85 0.77 0.79 0.76 0.76 2010's 0.95 0.84 0.77 0.79 0.88 0.78 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  2. Maryland Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Maryland 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 Year-9 1990's 1.55 1.58 1.58 1.63 1.56 1.51 1.58 2000's 1.68 1.48 1.64 1.79 1.77 1.78 1.63 1.77 1.66 1.73 2010's 1.75 1.65 1.70 1.70 1.78 1.80 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  3. Massachusetts Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Massachusetts 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 Year-9 1990's 2.45 2.47 2.18 2.18 2.25 2.26 2.24 2000's 2.28 2.24 2.24 2.48 2.32 2.46 2.38 2.44 2.71 2.78 2010's 2.63 2.74 2.78 2.39 2.49 2.75 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  4. Michigan Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Michigan 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 Year-9 1990's 7.46 7.52 7.84 7.62 7.62 7.07 7.42 2000's 7.36 7.20 7.52 7.59 7.44 7.43 7.23 6.95 6.99 6.84 2010's 6.36 6.75 6.67 6.82 6.97 6.77 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  5. Mississippi Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Mississippi 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 Year-9 1990's 0.57 0.56 0.56 0.58 0.55 0.55 0.52 2000's 0.54 0.59 0.54 0.52 0.50 0.51 0.49 0.47 0.49 0.49 2010's 0.57 0.52 0.47 0.51 0.56 0.50 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  6. Missouri Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Missouri 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 Year-9 1990's 2.71 2.53 2.58 2.62 2.56 2.45 2.37 2000's 2.31 2.44 2.34 2.26 2.25 2.21 2.18 2.15 2.33 2.22 2010's 2.25 2.18 2.00 2.17 2.27 2.07 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  7. Montana Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Montana 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 Year-9 1990's 0.41 0.39 0.41 0.42 0.42 0.42 0.42 2000's 0.40 0.42 0.44 0.40 0.41 0.41 0.45 0.42 0.44 0.46 2010's 0.44 0.46 0.46 0.42 0.42 0.41 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  8. Nebraska Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Nebraska 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 Year-9 1990's 0.97 0.92 0.93 0.94 0.95 0.90 0.86 2000's 0.85 0.98 0.90 0.83 0.79 0.79 0.82 0.82 0.87 0.84 2010's 0.84 0.84 0.75 0.84 0.83 0.75 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  9. Alabama Natural Gas % of Total Electric Utility Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    Electric Utility Deliveries (Percent) Alabama Natural Gas % of Total Electric Utility Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 0.17 0.13 0.23 0.23 0.29 0.60 0.53 2000's 0.81 1.29 1.98 1.68 2.14 1.79 2.34 2.57 2.46 3.30 2010's 3.81 4.53 4.40 4.08 4.25 4.12 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  10. Alabama Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Deliveries (Percent) Alabama 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 Year-9 1990's 1.04 1.03 1.02 1.08 0.97 1.03 0.90 2000's 0.95 1.03 0.95 0.92 0.90 0.87 0.87 0.75 0.77 0.75 2010's 0.88 0.78 0.66 0.72 0.77 0.71 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring

  11. Alabama Natural Gas % of Total Vehicle Fuel Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    Vehicle Fuel Deliveries (Percent) Alabama Natural Gas % of Total Vehicle Fuel Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 0.44 0.20 0.15 0.08 0.71 0.57 0.57 2000's 0.57 0.52 0.52 0.52 0.52 0.67 0.47 0.36 0.32 0.29 2010's 0.37 0.64 0.64 0.63 1.07 1.07 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring

  12. Alabama Natural Gas Percentage Total Commercial Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Deliveries (Percent) Alabama Natural Gas Percentage Total Commercial Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 0.90 0.88 0.87 0.92 1.01 0.86 0.91 2000's 0.80 0.87 0.80 0.80 0.85 0.84 0.86 0.78 0.80 0.78 2010's 0.87 0.80 0.74 0.77 0.79 0.78 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  13. Alaska Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Alaska 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 Year-9 1990's 0.28 0.31 0.31 0.31 0.30 0.35 0.37 2000's 0.32 0.35 0.33 0.33 0.37 0.37 0.47 0.42 0.44 0.42 2010's 0.39 0.43 0.52 0.39 0.35 0.40 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  14. Arkansas Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Arkansas 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 Year-9 1990's 0.92 0.86 0.85 0.88 0.85 0.85 0.77 2000's 0.85 0.78 0.80 0.75 0.71 0.70 0.72 0.69 0.73 0.70 2010's 0.76 0.72 0.63 0.71 0.75 0.72 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  15. California Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) California 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 Year-9 1990's 10.11 10.75 9.85 9.03 9.61 12.17 12.03 2000's 10.34 10.75 10.45 9.80 10.52 10.02 11.26 10.43 10.00 10.06 2010's 10.35 10.87 11.52 9.84 7.81 8.70 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next

  16. Colorado Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Colorado 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 Year-9 1990's 2.14 2.05 2.15 2.12 2.32 2.45 2.37 2000's 2.33 2.59 2.64 2.45 2.48 2.57 2.73 2.77 2.74 2.70 2010's 2.74 2.76 2.79 2.76 2.60 2.66 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  17. Wyoming Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Wyoming 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 Year-9 1990's 0.26 0.24 0.25 0.26 0.26 0.28 0.26 2000's 0.24 0.23 0.27 0.24 0.25 0.24 0.27 0.26 0.27 0.26 2010's 0.27 0.28 0.28 0.28 0.26 0.25 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  18. North Dakota Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) North Dakota 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 Year-9 1990's 0.22 0.22 0.23 0.24 0.23 0.22 0.22 2000's 0.22 0.22 0.24 0.23 0.23 0.22 0.22 0.23 0.24 0.24 2010's 0.22 0.23 0.23 0.25 0.25 0.23 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  19. Ohio Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Ohio 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 Year-9 1990's 7.14 7.08 7.38 7.15 7.11 6.56 6.73 2000's 6.88 6.47 6.57 6.75 6.59 6.69 6.23 6.34 6.27 6.12 2010's 5.93 6.07 6.05 6.07 6.30 6.19 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  20. Oregon Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Oregon 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 Year-9 1990's 0.60 0.60 0.58 0.63 0.65 0.76 0.82 2000's 0.78 0.80 0.79 0.73 0.79 0.82 0.94 0.91 0.92 0.94 2010's 0.85 0.99 1.04 0.94 0.81 0.81 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  1. Pennsylvania Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Pennsylvania 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 Year-9 1990's 5.43 5.54 5.40 5.32 5.27 4.82 5.11 2000's 5.26 5.01 4.89 5.22 5.09 5.08 4.71 4.90 4.69 4.76 2010's 4.68 4.66 4.76 4.73 5.01 5.11 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  2. Rhode Island Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Rhode Island 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 Year-9 1990's 0.40 0.36 0.36 0.36 0.36 0.36 0.35 2000's 0.37 0.38 0.36 0.40 0.40 0.40 0.39 0.37 0.36 0.37 2010's 0.35 0.36 0.38 0.37 0.39 0.44 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  3. South Carolina Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) South Carolina 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 Year-9 1990's 0.49 0.48 0.52 0.56 0.52 0.56 0.54 2000's 0.58 0.58 0.56 0.57 0.60 0.59 0.57 0.53 0.55 0.57 2010's 0.68 0.57 0.55 0.58 0.63 0.60 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  4. South Dakota Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) South Dakota 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 Year-9 1990's 0.25 0.25 0.26 0.27 0.27 0.26 0.25 2000's 0.25 0.26 0.26 0.26 0.25 0.25 0.26 0.26 0.28 0.28 2010's 0.27 0.27 0.26 0.28 0.28 0.26 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  5. Tennessee Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Tennessee 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 Year-9 1990's 1.19 1.18 1.24 1.34 1.29 1.31 1.28 2000's 1.37 1.43 1.42 1.37 1.34 1.37 1.40 1.29 1.41 1.38 2010's 1.55 1.43 1.30 1.45 1.54 1.46 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  6. Utah Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Utah 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 Year-9 1990's 1.05 1.01 1.01 1.04 1.17 1.26 1.17 2000's 1.11 1.15 1.21 1.08 1.24 1.20 1.37 1.28 1.35 1.36 2010's 1.38 1.49 1.44 1.44 1.23 1.27 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  7. Vermont Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Vermont 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 Year-9 1990's 0.05 0.05 0.05 0.05 0.05 0.05 0.05 2000's 0.06 0.06 0.06 0.06 0.06 0.06 0.07 0.07 0.06 0.07 2010's 0.06 0.07 0.07 0.07 0.08 0.08 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  8. West Virginia Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) West 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 Year-9 1990's 0.71 0.73 0.73 0.71 0.72 0.66 0.67 2000's 0.63 0.67 0.63 0.63 0.62 0.62 0.60 0.56 0.56 0.55 2010's 0.57 0.53 0.54 0.54 0.56 0.54 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  9. Wisconsin Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Wisconsin 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 Year-9 1990's 2.63 2.64 2.80 2.82 2.73 2.57 2.70 2000's 2.70 2.63 2.81 2.80 2.78 2.72 2.76 2.78 2.87 2.79 2010's 2.58 2.75 2.71 2.92 2.96 2.75 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  10. Connecticut Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % 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 Year-8 Year-9 1990's 0.85 0.86 0.84 0.84 0.81 0.78 0.81 2000's 0.83 0.86 0.82 0.90 0.91 0.92 0.89 0.92 0.88 0.92 2010's 0.89 0.95 0.99 0.96 1.01 1.11 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  11. Delaware Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Delaware 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 Year-9 1990's 0.17 0.18 0.18 0.19 0.18 0.17 0.19 2000's 0.19 0.19 0.20 0.21 0.21 0.21 0.21 0.21 0.20 0.21 2010's 0.21 0.21 0.21 0.21 0.22 0.24 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  12. Florida Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Florida 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 Year-9 1990's 0.28 0.29 0.30 0.31 0.26 0.31 0.29 2000's 0.30 0.33 0.31 0.31 0.33 0.33 0.36 0.32 0.32 0.32 2010's 0.39 0.35 0.35 0.31 0.33 0.33 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  13. Georgia Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Georgia 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 Year-9 1990's 2.33 2.18 2.36 2.42 2.30 2.38 2.09 2000's 2.82 2.51 2.59 2.56 2.60 2.58 2.52 2.37 2.44 2.48 2010's 2.90 2.40 2.35 2.48 2.64 2.56 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  14. Hawaii Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Hawaii 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 Year-9 1990's 0.01 0.01 0.01 0.01 0.01 0.01 0.01 2000's 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 2010's 0.01 0.01 0.01 0.01 0.01 0.01 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  15. Idaho Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Idaho 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 Year-9 1990's 0.25 0.25 0.27 0.29 0.31 0.35 0.38 2000's 0.38 0.40 0.42 0.37 0.42 0.45 0.51 0.50 0.56 0.53 2010's 0.50 0.57 0.58 0.56 0.48 0.51 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  16. Illinois Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Illinois 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 Year-9 1990's 9.99 9.77 10.33 10.28 9.98 9.07 9.42 2000's 9.35 8.95 9.40 9.32 9.11 9.07 9.12 9.17 9.52 9.21 2010's 8.71 8.87 8.70 9.24 9.42 8.70 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  17. Indiana Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Indiana 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 Year-9 1990's 3.31 3.25 3.32 3.43 3.39 3.10 3.21 2000's 3.23 3.09 3.21 3.10 3.05 3.08 2.92 3.02 3.12 2.92 2010's 2.89 2.80 2.78 2.95 3.08 2.89 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  18. Iowa Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Iowa 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 Year-9 1990's 1.68 1.61 1.70 1.68 1.64 1.52 1.51 2000's 1.48 1.49 1.46 1.46 1.40 1.39 1.42 1.43 1.54 1.47 2010's 1.43 1.42 1.35 1.48 1.51 1.36 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  19. Kentucky Natural Gas % of Total Residential Deliveries (Percent)

    U.S. Energy Information Administration (EIA) (indexed site)

    % of Total Residential Deliveries (Percent) Kentucky 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 Year-9 1990's 1.35 1.29 1.36 1.34 1.33 1.23 1.25 2000's 1.29 1.19 1.21 1.22 1.16 1.16 1.08 1.09 1.12 1.08 2010's 1.14 1.08 1.04 1.11 1.13 1.07 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  20. Microsoft Word - Household Energy Use CA

    U.S. Energy Information Administration (EIA) (indexed site)

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

  1. 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.

  2. Transferring 2001 National Household Travel Survey

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim; Schmoyer, Richard L; Chin, Shih-Miao

    2007-05-01

    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.

  3. Percent of Commercial Natural Gas Deliveries in California Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 86.6 77.8 74.5 76.9 48.8 52.1 54.9 50.4 48.7 57.1 2000's 57.1 62.6 68.6 70.3 71.2 68.7 64.7 60.7 56.7 54.9 2010's 54.1 54.3 50.0 49.9 48.4 50.0

  4. Percent of Commercial Natural Gas Deliveries in District of Columbia

    U.S. Energy Information Administration (EIA) (indexed site)

    Represented by the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100.0 97.3 99.0 98.0 90.9 76.8 70.5 54.9 52.3 45.9 2000's 35.6 22.4 23.5 30.5 23.3 100.0 100.0 100.0 100.0 100.0 2010's 100.0 16.9 17.9 19.1 19.9 21.4

  5. Percent of Commercial Natural Gas Deliveries in Louisiana Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100.0 99.1 87.5 98.1 97.9 98.1 98.3 95.9 94.6 93.8 2000's 96.3 96.5 99.0 98.8 98.6 98.6 98.4 98.0 98.4 92.0 2010's 85.9 83.6 78.0 77.7 78.9 79.1

  6. Percent of Commercial Natural Gas Deliveries in Mississippi Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 95.6 95.9 96.4 96.6 96.6 97.0 97.4 94.8 94.8 96.0 2000's 95.6 95.7 96.7 95.9 95.7 95.7 94.9 88.8 90.4 91.0 2010's 90.6 89.8 89.0 89.1 87.5 NA

  7. Percent of Commercial Natural Gas Deliveries in Pennsylvania Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 78.4 77.3 75.8 77.4 74.4 68.4 70.4 63.6 56.8 56.9 2000's 60.5 63.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2010's 100.0 48.5 42.1 40.2 41.4 NA

  8. Percent of Commercial Natural Gas Deliveries in South Carolina Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 97.8 98.2 98.6 99.2 98.5 96.4 99.0 98.8 97.9 97.1 2000's 98.7 97.5 98.5 96.6 96.4 96.2 95.0 94.9 94.9 93.5 2010's 92.7 91.1 90.6 91.7 92.8 91.3

  9. Percent of Commercial Natural Gas Deliveries in Tennessee Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 97.5 95.7 96.4 95.8 94.1 93.8 94.3 92.2 87.3 88.8 2000's 92.5 93.6 90.9 90.5 92.2 92.2 92.0 91.9 91.7 90.2 2010's 90.8 89.9 88.8 90.0 90.7 88.6

  10. Percent of Commercial Natural Gas Deliveries in Washington Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 93.6 92.2 87.3 93.9 95.4 91.8 85.9 84.1 86.8 89.3 2000's 92.7 94.0 89.8 88.0 88.5 88.8 88.9 89.2 89.0 88.7 2010's 87.8 88.4 87.4 86.8 86.0 85.4

  11. Percent of Commercial Natural Gas Deliveries in West Virginia Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 58.1 54.9 56.9 54.3 55.2 51.6 56.3 54.5 49.5 51.8 2000's 56.6 63.9 57.4 60.2 57.1 58.2 56.0 58.6 53.5 53.6 2010's 51.0 49.2 48.9 52.9 56.7 53.3

  12. Percent of Commercial Natural Gas Deliveries in Wisconsin Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 90.7 91.0 91.3 94.4 93.5 92.0 91.6 82.1 74.0 79.0 2000's 78.1 77.2 75.9 79.1 79.7 79.0 76.0 75.5 76.8 76.8 2010's 76.2 76.4 74.4 77.7 77.0 NA

  13. Percent of Industrial Natural Gas Deliveries in Louisiana Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 10.1 9.2 8.5 2000's 10.8 8.3 13.4 13.4 21.6 27.9 28.4 25.9 21.4 18.3 2010's 16.7 13.7 14.7 14.2 11.9 2.0

  14. Percent of Industrial Natural Gas Deliveries in Mississippi Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 39.6 37.6 26.3 2000's 26.9 28.8 25.9 33.7 34.4 25.2 20.0 15.0 12.2 10.1 2010's 9.6 9.7 9.6 10.6 9.9

  15. Percent of Industrial Natural Gas Deliveries in Pennsylvania Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 14.3 13.1 11.8 2000's 11.8 9.9 7.3 6.6 6.4 7.0 5.5 5.4 5.7 4.5 2010's 3.8 2.0 1.3 1.3 1.2 1.0

  16. Percent of Industrial Natural Gas Deliveries in South Carolina Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 86.9 86.7 86.1 2000's 86.5 82.1 87.7 78.5 77.8 77.4 71.4 47.3 47.3 47.6 2010's 46.3 45.4 45.1 45.6 43.6 42.1

  17. Percent of Industrial Natural Gas Deliveries in Tennessee Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 38.3 33.1 34.7 2000's 38.5 36.2 36.0 39.9 40.5 42.4 38.9 38.2 39.9 38.2 2010's 35.7 29.7 29.4 29.7 30.0 29.6

  18. Percent of Industrial Natural Gas Deliveries in Washington Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 23.5 20.1 24.0 2000's 34.5 38.2 27.4 20.1 17.3 15.8 20.2 17.4 12.9 8.7 2010's 8.3 7.5 7.3 6.7 6.5 6.2

  19. Percent of Industrial Natural Gas Deliveries in West Virginia Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 12.2 6.3 10.8 2000's 13.8 16.6 12.7 14.0 13.4 17.0 17.0 16.2 19.0 17.4 2010's 14.7 15.6 16.3 18.0 15.6 NA

  20. Percent of Industrial Natural Gas Deliveries in Wisconsin Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 27.1 22.0 20.2 2000's 22.1 19.5 21.4 20.2 18.8 18.1 18.3 18.5 18.3 18.1 2010's 17.4 17.8 17.6 18.8 19.6 NA

  1. 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.

  2. Table B28. Percent of Floorspace Heated, Number of Buildings and Floorspace, 199

    U.S. Energy Information Administration (EIA) (indexed site)

    8. Percent of Floorspace Heated, Number of Buildings and Floorspace, 1999" ,"Number of Buildings (thousand)",,,,,"Total Floorspace (million square feet)" ,"All Buildings","Not Heated","1 to 50 Percent Heated","51 to 99 Percent Heated","100 Percent Heated","All Buildings","Not Heated","1 to 50 Percent Heated","51 to 99 Percent Heated","100 Percent Heated" "All

  3. Percent of Commercial Natural Gas Deliveries in Connecticut Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100.0 100.0 98.4 90.0 81.6 76.5 74.5 80.4 74.8 85.5 90.8 99.5 1990 100.0 100.0 98.7 95.9 92.3 89.9 87.5 86.9 87.2 91.3 98.3 99.1 1991 99.4 99.4 97.5 92.5 85.9 79.2 76.2 77.1 77.9 85.9 93.0 96.6 1992 97.7 97.2 95.6 94.4 93.6 87.2 95.8 98.8 98.7 97.8 98.2 98.4 1993 97.2 97.7 97.2 98.1 99.4 99.3 88.3 98.4 99.6 100.0 100.0 100.0 1994 89.2 90.7 88.4 88.8 74.2 67.8 62.4 61.1 57.4 68.8 77.9 83.4 1995 86.7 88.1 85.7 81.6

  4. Percent of Commercial Natural Gas Deliveries in District of Columbia

    U.S. Energy Information Administration (EIA) (indexed site)

    Represented by the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1990 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1991 100.0 100.0 100.0 100.0 100.0 92.4 86.7 89.4 90.6 91.1 95.7 99.5 1992 99.6 100.0 100.0 97.4 97.6 100.0 91.4 99.5 99.0 100.0 100.0 100.0 1993 100.0 100.0 100.0 100.0 100.0 99.8 96.8 88.4 90.1 92.6 95.9 97.1 1994 99.8 99.8 100.0 98.8 95.7 94.4 76.6

  5. Percent of Commercial Natural Gas Deliveries in Louisiana Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 1990 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1991 100.0 100.0 100.0 100.0 100.0 98.5 98.6 98.4 98.5 98.4 97.4 97.6 1992 82.3 87.7 88.7 90.6 90.5 90.1 90.6 90.2 91.1 90.6 81.4 86.4 1993 97.4 97.9 98.1 98.6 98.9 98.9 98.8 98.8 98.8 98.2 97.1 97.5 1994 97.7 98.1 98.1 98.0 98.0 97.9 98.4 97.6 98.1 97.9 97.9 97.5 1995 97.8 98.2

  6. Percent of Commercial Natural Gas Deliveries in Massachusetts Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 99.9 1990 100.0 100.0 100.0 100.0 100.0 100.0 100.0 99.8 99.8 99.8 99.7 99.7 1991 99.8 99.8 99.9 99.9 99.9 99.8 99.7 99.6 99.6 99.8 99.9 99.9 1992 99.9 99.9 99.8 99.8 99.7 99.8 99.7 99.6 99.6 99.6 99.7 99.8 1993 98.9 98.7 98.5 97.7 96.5 97.7 96.8 89.2 97.5 96.7 96.9 97.8 1994 75.2 78.4 72.5 69.8 69.8 61.2 67.0 86.0 79.7 90.6 81.2 87.1 1995 87.9 89.4 92.0

  7. Percent of Commercial Natural Gas Deliveries in Mississippi Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1990 97.6 96.0 95.7 95.6 94.5 94.3 93.7 93.5 93.9 94.4 95.2 95.8 1991 96.6 97.0 96.3 95.9 94.5 94.9 94.3 94.6 95.1 94.9 95.5 96.4 1992 96.9 97.3 96.4 96.6 95.2 95.4 95.5 94.8 95.6 95.6 95.9 97.4 1993 97.3 97.3 97.2 97.1 96.1 96.0 96.0 95.7 95.5 95.4 96.1 96.5 1994 97.2 97.6 97.1 96.9 96.1 96.9 97.1 95.1 94.9 94.3 96.2 96.6 1995 96.4 97.4 98.2

  8. Percent of Commercial Natural Gas Deliveries in North Carolina Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 98.7 98.9 94.9 92.4 89.6 87.7 80.1 84.2 84.4 86.3 97.1 98.1 1990 98.6 98.3 98.0 97.0 89.1 86.3 85.3 85.0 84.7 84.0 98.7 99.1 1991 99.3 99.3 99.0 89.0 87.3 86.1 84.4 86.3 85.0 98.0 99.0 99.3 1992 99.3 99.2 99.2 93.1 88.3 85.8 84.3 86.2 89.2 99.9 100.0 100.0 1993 100.0 100.0 100.0 100.0 100.0 95.4 95.4 95.2 99.7 89.7 96.1 100.0 1994 100.0 100.0 100.0 95.3 94.0 92.1 91.8 90.4 88.3 88.0 94.1 99.4 1995 95.7 96.0 94.5

  9. Percent of Commercial Natural Gas Deliveries in Pennsylvania Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 89.4 88.9 88.7 87.4 81.7 76.8 79.6 77.2 76.4 80.3 82.9 85.3 1990 85.9 83.6 80.9 80.0 74.0 70.2 68.5 68.3 67.2 69.6 74.9 79.2 1991 82.2 79.4 78.8 77.7 72.1 72.9 70.6 71.6 72.2 72.9 76.4 76.7 1992 77.1 79.6 76.6 75.1 71.8 73.1 68.1 67.2 69.4 74.0 74.1 79.4 1993 80.5 79.7 79.5 78.2 72.1 72.9 72.9 69.7 70.3 76.5 75.9 77.0 1994 79.0 80.2 77.5 73.9 71.6 70.8 67.1 71.4 67.9 62.7 68.7 72.1 1995 75.1 74.4 74.9 71.4 68.7

  10. Percent of Commercial Natural Gas Deliveries in South Carolina Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 98.5 98.5 98.6 98.3 98.1 98.2 98.1 97.7 97.7 97.8 98.0 97.3 1990 98.6 98.4 98.3 98.1 92.2 97.6 97.6 97.5 97.9 97.3 98.0 98.6 1991 98.7 98.9 98.7 96.9 97.4 97.5 97.3 97.7 97.7 97.4 98.9 98.9 1992 99.1 99.1 98.9 98.6 98.5 95.8 95.5 95.8 97.0 99.7 100.0 100.0 1993 100.0 100.0 100.0 100.0 100.0 100.0 95.1 94.6 100.0 95.3 100.0 100.0 1994 100.0 100.0 100.0 99.7 97.8 98.3 97.0 95.7 95.2 95.6 96.2 99.9 1995 97.8 97.5

  11. Percent of Commercial Natural Gas Deliveries in Tennessee Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 99.1 98.9 98.9 97.5 96.8 95.9 96.7 95.8 96.9 97.1 97.4 99.1 1990 98.9 98.5 98.7 97.9 95.4 95.4 95.1 95.9 95.1 95.5 96.5 97.5 1991 97.9 94.6 93.6 96.0 94.8 94.3 93.8 93.8 94.0 95.3 97.1 97.8 1992 96.6 97.1 96.8 97.2 93.7 95.8 97.3 90.4 91.6 97.3 97.5 97.4 1993 96.6 96.9 96.6 96.5 97.7 91.3 91.6 91.1 91.4 92.3 94.7 98.9 1994 96.7 98.5 97.9 93.0 90.0 89.4 87.2 87.1 89.3 88.4 91.7 94.4 1995 95.5 95.8 93.4 90.8 89.6

  12. Percent of Commercial Natural Gas Deliveries in Washington Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 95.5 94.8 96.9 93.2 93.0 89.7 87.0 92.6 87.3 93.0 93.6 96.5 1990 96.2 95.9 93.2 92.1 90.9 88.9 88.3 88.4 90.1 91.7 95.7 96.5 1991 97.8 94.9 94.3 93.2 91.2 90.5 88.3 87.2 85.6 85.2 88.7 92.1 1992 92.1 89.0 88.7 85.5 83.5 80.7 78.5 80.3 81.6 83.4 86.8 92.3 1993 93.8 93.2 93.9 93.6 90.8 89.8 90.5 90.4 90.6 94.8 97.4 98.0 1994 97.6 97.6 97.6 97.4 92.1 92.1 92.4 91.7 94.4 93.8 94.1 94.7 1995 94.3 94.0 94.2 92.6 91.8

  13. Percent of Commercial Natural Gas Deliveries in Wisconsin Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 94.1 94.2 94.5 94.0 92.6 87.7 86.1 84.2 84.2 84.3 91.1 95.0 1990 91.6 91.5 91.9 91.9 90.3 86.5 83.1 82.4 82.6 87.5 90.1 93.3 1991 93.8 92.3 92.9 91.2 88.8 83.8 80.7 84.7 83.6 86.7 91.5 92.1 1992 92.7 92.1 91.6 90.0 85.8 82.3 83.3 84.1 85.2 90.7 93.4 95.1 1993 95.2 96.0 95.3 93.5 92.1 90.8 89.2 88.5 90.0 92.6 95.2 96.0 1994 97.1 97.6 97.4 96.6 91.8 89.9 83.5 87.1 87.8 90.8 94.4 84.4 1995 93.5 94.0 93.2 92.4 90.0

  14. Percent of Industrial Natural Gas Deliveries in Mississippi Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 28.2 32.5 24.3 32.8 25.6 33.3 27.5 30.2 28.5 21.2 31.3 31.1 2002 27.5 29.8 27.4 27.0 23.9 26.2 24.1 25.8 24.2 23.9 26.3 25.2 2003 32.3 39.3 37.3 34.5 31.8 37.2 34.6 32.3 32.7 28.6 27.0 35.7 2004 39.9 36.9 33.0 32.8 29.8 33.8 32.8 33.7 36.7 31.0 33.7 38.8 2005 26.7 24.2 23.6 24.4 23.7 22.1 23.2 22.8 42.3 24.8 28.8 23.7 2006 24.7 28.1 24.8 23.5 19.5 19.2 18.1 17.2 16.6 17.5 15.6 18.0 2007 18.4 19.6 17.4 15.6 13.4

  15. Percent of Industrial Natural Gas Deliveries in Tennessee Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 48.0 40.7 40.0 33.7 32.1 29.6 33.1 33.6 35.5 29.3 37.7 38.4 2002 36.3 39.0 44.3 34.8 36.6 33.0 32.5 31.8 33.8 35.5 33.9 38.2 2003 36.7 41.2 40.2 37.2 35.5 33.9 38.7 40.5 42.6 44.0 42.1 46.8 2004 44.2 43.4 42.1 40.5 41.0 36.5 36.4 34.6 37.0 38.3 41.5 47.1 2005 39.9 40.5 44.7 47.3 42.5 39.5 39.5 43.3 42.8 41.5 39.7 46.7 2006 40.9 44.6 40.1 37.3 37.4 39.1 35.5 35.5 34.9 38.2 41.6 39.2 2007 38.8 44.2 40.4 35.4 37.8

  16. Percent of Industrial Natural Gas Deliveries in Washington Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 40.1 37.3 39.3 33.9 31.2 31.0 27.1 35.1 34.9 46.1 46.5 46.1 2002 25.9 28.6 29.4 32.8 30.0 24.4 27.5 20.7 24.7 25.4 31.6 26.9 2003 26.3 26.9 25.5 19.5 18.5 15.1 13.6 15.3 17.5 18.9 18.7 22.2 2004 20.9 21.0 21.4 19.1 15.8 16.0 13.2 17.1 15.0 16.2 14.5 15.6 2005 15.1 14.4 15.2 12.9 11.7 11.7 11.0 15.0 15.5 18.8 20.6 25.3 2006 22.9 22.8 22.6 19.7 19.5 17.8 17.2 16.8 17.1 19.2 21.8 22.3 2007 23.5 22.4 23.2 18.7 16.9

  17. Percent of Industrial Natural Gas Deliveries in Wisconsin Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 25.3 26.6 26.1 18.3 12.5 11.2 12.3 12.4 10.9 15.9 19.9 23.0 2002 25.3 23.6 25.8 21.2 18.5 14.3 11.1 13.3 14.7 20.9 24.7 28.9 2003 27.0 27.3 25.9 18.8 15.3 11.7 10.7 11.7 12.2 17.7 21.3 26.2 2004 26.4 24.1 23.9 19.3 13.5 14.1 12.9 10.4 12.4 17.6 19.6 18.6 2005 21.7 20.9 20.8 15.9 13.4 11.2 12.3 13.2 13.9 16.4 21.9 25.1 2006 21.6 21.7 23.0 13.3 14.1 13.5 11.1 12.3 13.3 18.2 22.8 24.2 2007 22.3 23.7 24.1 17.8 13.6

  18. Percent of Commercial Natural Gas Deliveries in West Virginia Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 68.6 69.0 65.3 63.9 55.0 45.3 39.8 39.5 40.5 49.5 58.6 71.5 1990 72.4 67.8 64.6 60.4 53.8 41.6 34.0 37.7 34.7 38.3 56.1 61.2 1991 64.6 65.8 65.4 54.5 42.1 34.1 31.0 33.9 36.5 45.2 55.6 58.0 1992 65.0 65.9 59.9 63.0 54.5 39.3 35.8 33.6 33.4 48.1 56.8 58.9 1993 60.7 61.3 61.7 60.2 47.5 33.6 30.3 30.6 33.0 46.8 54.9 60.1 1994 67.4 65.2 61.9 58.3 47.8 39.6 29.5 34.3 34.2 41.3 47.5 55.7 1995 55.5 59.5 56.1 50.6 42.2

  19. Percent of Industrial Natural Gas Deliveries in Louisiana Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 8.2 7.6 6.3 8.0 7.2 5.9 9.1 9.6 9.0 8.6 10.0 9.1 2002 13.4 13.3 13.0 13.6 14.3 13.5 12.2 13.1 12.9 12.7 13.4 14.8 2003 12.0 13.2 12.0 13.5 13.7 13.7 11.8 12.8 13.4 14.1 16.3 14.3 2004 14.5 15.7 16.4 22.9 22.7 23.7 23.3 22.9 22.8 23.3 25.2 26.0 2005 26.3 25.9 27.3 27.8 28.6 28.2 27.2 28.9 29.0 28.8 28.8 29.0 2006 29.4 28.6 29.2 26.8 28.8 28.3 28.0 29.5 26.3 25.7 28.6 31.5 2007 29.7 31.7 27.3 28.8 29.9 33.6 23.9 23.8

  20. Percent of Industrial Natural Gas Deliveries in Pennsylvania Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 17.0 16.4 11.3 10.2 7.7 5.1 7.3 7.5 8.2 8.8 7.3 8.4 2002 8.8 8.3 7.0 5.9 5.7 5.5 4.8 5.0 7.2 7.5 8.1 11.4 2003 8.5 8.5 8.8 7.3 5.7 5.4 5.2 5.0 5.2 5.5 5.9 6.5 2004 7.7 8.1 7.3 6.8 5.3 4.8 4.8 5.1 5.2 4.7 6.5 8.3 2005 8.8 8.4 8.2 7.0 6.1 5.5 5.9 7.1 5.2 5.2 6.7 8.2 2006 8.2 7.3 7.1 5.3 4.8 4.2 4.1 4.1 6.2 4.2 4.6 5.4 2007 6.7 8.5 8.3 5.9 5.6 3.7 3.3 3.2 4.1 3.1 4.5 6.6 2008 7.7 7.3 7.3 6.9 5.7 4.8 4.4 4.3 3.8 3.9

  1. Percent of Industrial Natural Gas Deliveries in South Carolina Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 91.8 86.4 82.7 82.0 77.6 80.8 80.2 80.2 80.3 79.8 82.4 84.4 2002 89.9 87.6 85.4 88.3 90.4 87.4 90.5 84.4 90.3 90.3 84.3 82.9 2003 79.4 79.6 75.8 79.3 81.8 81.7 78.9 77.3 78.4 77.0 76.5 75.9 2004 76.9 75.6 77.0 79.2 79.0 78.2 78.5 79.0 78.6 78.3 77.2 76.4 2005 78.2 78.8 78.0 77.4 78.1 78.2 78.8 78.7 73.2 76.4 67.9 81.3 2006 80.1 78.6 74.0 80.2 71.2 75.3 75.9 77.2 70.6 74.8 48.6 44.6 2007 48.9 48.4 47.5 46.1 47.5

  2. Percent of Industrial Natural Gas Deliveries in West Virginia Represented

    U.S. Energy Information Administration (EIA) (indexed site)

    by the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 11.2 6.1 6.1 8.6 8.2 7.3 7.7 8.9 5.9 60.8 7.0 62.1 2002 12.1 12.6 11.7 15.0 12.6 12.1 14.7 13.0 16.1 10.7 13.1 10.4 2003 14.3 12.6 20.3 13.9 14.0 14.7 13.6 13.5 14.6 12.9 14.1 10.9 2004 10.7 10.5 11.4 11.5 19.8 15.0 15.7 15.3 14.3 14.8 14.7 12.8 2005 11.4 12.8 12.5 13.7 17.4 21.1 23.5 20.4 22.1 23.0 20.7 18.5 2006 16.3 14.8 17.3 18.6 16.9 20.3 15.7 16.4 19.0 16.7 16.4 16.7 2007 15.2 13.4 15.9 16.3 17.8 18.5 18.5

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

    Energy Savers

    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 ...

  4. Household-level dynamics of food waste production and related beliefs, attitudes, and behaviours in Guelph, Ontario

    SciTech Connect (OSTI)

    Parizeau, Kate; Massow, Mike von; Martin, Ralph

    2015-01-15

    Highlights: • We combined household waste stream weights with survey data. • We examine relationships between waste and food-related practices and beliefs. • Families and large households produced more total waste, but less waste per capita. • Food awareness and waste awareness were related to reduced food waste. • Convenience lifestyles were differentially associated with food waste. - Abstract: It has been estimated that Canadians waste $27 billion of food annually, and that half of that waste occurs at the household level (Gooch et al., 2010). There are social, environmental, and economic implications for this scale of food waste, and source separation of organic waste is an increasingly common municipal intervention. There is relatively little research that assesses the dynamics of household food waste (particularly in Canada). The purpose of this study is to combine observations of organic, recyclable, and garbage waste production rates to survey results of food waste-related beliefs, attitudes, and behaviours at the household level in the mid-sized municipality of Guelph, Ontario. Waste weights and surveys were obtained from 68 households in the summer of 2013. The results of this study indicate multiple relationships between food waste production and household shopping practices, food preparation behaviours, household waste management practices, and food-related attitudes, beliefs, and lifestyles. Notably, we observed that food awareness, waste awareness, family lifestyles, and convenience lifestyles were related to food waste production. We conclude that it is important to understand the diversity of factors that can influence food wasting behaviours at the household level in order to design waste management systems and policies to reduce food waste.

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

    Gasoline and Diesel Fuel Update

    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

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

    SciTech Connect (OSTI)

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

    2014-10-14

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

  7. 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.

  8. 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.

  9. Fact #720: March 26, 2012 Eleven Percent of New Light Trucks...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    0: March 26, 2012 Eleven Percent of New Light Trucks Sold have Gasoline Direct Injection Fact 720: March 26, 2012 Eleven Percent of New Light Trucks Sold have Gasoline Direct Injection ...

  10. Recovery Act Exceeds Major Cleanup Milestone, DOE Complex Now 74 Percent

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Remediated | Department of Energy Recovery Act Exceeds Major Cleanup Milestone, DOE Complex Now 74 Percent Remediated Recovery Act Exceeds Major Cleanup Milestone, DOE Complex Now 74 Percent Remediated The Office of Environmental Management's (EM) American Recovery and Reinvestment Act Program recently achieved 74 percent footprint reduction, exceeding the originally established goal of 40 percent. EM has reduced its pre-Recovery Act footprint of 931 square miles, established in 2009, by 688

  11. Waste Isolation Pilot Plant Contractor Receives 86 Percent of Available Fee

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    | Department of Energy Isolation Pilot Plant Contractor Receives 86 Percent of Available Fee Waste Isolation Pilot Plant Contractor Receives 86 Percent of Available Fee April 27, 2016 - 12:20pm Addthis Nuclear Waste Partnership received about 86 percent of the available fee for the performance period as the Waste Isolation Pilot Plant management and operations contractor. Nuclear Waste Partnership received about 86 percent of the available fee for the performance period as the Waste

  12. 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.

  13. Near Zero Emissions at 50 Percent Thermal Efficiency

    SciTech Connect (OSTI)

    None, None

    2012-12-31

    Detroit Diesel Corporation (DDC) has successfully completed a 10 year DOE sponsored heavy-duty truck engine program, hereafter referred to as the NZ-50 program. This program was split into two major phases. The first phase was called Near-Zero Emission at 50 Percent Thermal Efficiency, and was completed in 2007. The second phase was initiated in 2006, and this phase was named Advancements in Engine Combustion Systems to Enable High-Efficiency Clean Combustion for Heavy-Duty Engines. This phase was completed in September, 2010. The key objectives of the NZ-50 program for this first phase were to: Quantify thermal efficiency degradation associated with reduction of engine-out NOx emissions to the 2007 regulated level of ~1.1 g/hp-hr. Implement an integrated analytical/experimental development plan for improving subsystem and component capabilities in support of emerging engine technologies for emissions and thermal efficiency goals of the program. Test prototype subsystem hardware featuring technology enhancements and demonstrate effective application on a multi-cylinder, production feasible heavy-duty engine test-bed. Optimize subsystem components and engine controls (calibration) to demonstrate thermal efficiency that is in compliance with the DOE 2005 Joule milestone, meaning greater than 45% thermal efficiency at 2007 emission levels. Develop technology roadmap for meeting emission regulations of 2010 and beyond while mitigating the associated degradation in engine fuel consumption. Ultimately, develop technical prime-path for meeting the overall goal of the NZ-50 program, i.e., 50% thermal efficiency at 2010 regulated emissions. These objectives were successfully met during the course of the NZ-50 program. The most noteworthy achievements in this program are summarized as follows: Demonstrated technologies through advanced integrated experiments and analysis to achieve the technical objectives of the NZ-50 program with 50.2% equivalent thermal efficiency under

  14. Sizing a New Water Heater | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Sizing a New Water Heater Sizing a New Water Heater Is your water heater the right size for you house? | Photo credit ENERGY STAR® Is your water heater the right size for you house? | Photo credit ENERGY STAR® A properly sized water heater will meet your household's hot water needs while operating more efficiently. Therefore, before purchasing a water heater, make sure it's the correct size. Here you'll find information about how to size these systems: Tankless or demand-type water heaters

  15. Appliance Commitment for Household Load Scheduling

    SciTech Connect (OSTI)

    Du, Pengwei; Lu, Ning

    2011-06-30

    This paper presents a novel appliance commitment algorithm that schedules thermostatically-controlled household loads based on price and consumption forecasts considering users comfort settings to meet an optimization objective such as minimum payment or maximum comfort. The formulation of an appliance commitment problem was described in the paper using an electrical water heater load as an example. The thermal dynamics of heating and coasting of the water heater load was modeled by physical models; random hot water consumption was modeled with statistical methods. The models were used to predict the appliance operation over the scheduling time horizon. User comfort was transformed to a set of linear constraints. Then, a novel linear, sequential, optimization process was used to solve the appliance commitment problem. The simulation results demonstrate that the algorithm is fast, robust, and flexible. The algorithm can be used in home/building energy-management systems to help household owners or building managers to automatically create optimal load operation schedules based on different cost and comfort settings and compare cost/benefits among schedules.

  16. 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.

  17. 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)

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

    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.

  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. 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.

  1. EECBG 11-002 Clarification of Ten Percent Limitation on Use of...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Efficiency and Conservation Block Grant Program (EECBG), ten percent ... Guidance For Energy Efficiency And Conservation Block Grant Grantees On Financing Programs ...

  2. Fact #924: May 9, 1916 Twenty Percent of New Cars in 2015 Had Turbochargers

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    - Dataset | Department of Energy 4: May 9, 1916 Twenty Percent of New Cars in 2015 Had Turbochargers - Dataset Fact #924: May 9, 1916 Twenty Percent of New Cars in 2015 Had Turbochargers - Dataset Excel file and dataset for Twenty Percent of New Cars in 2015 Had Turbochargers fotw#924_web.xlsx (19.24 KB) More Documents & Publications Fact #923: May 2, 2016 Cylinder Deactivation was Used in More than a Quarter of New Light Trucks Produced in 2015 - Dataset Fact #869: April 20, 2015

  3. U.S. Utility-Scale Solar 60 Percent Towards Cost-Competition Goal |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Utility-Scale Solar 60 Percent Towards Cost-Competition Goal U.S. Utility-Scale Solar 60 Percent Towards Cost-Competition Goal February 12, 2014 - 11:05am Addthis News Media Contact (202) 586-4940 WASHINGTON - The Energy Department announced today that the U.S. solar industry is more than 60 percent of the way to achieving cost-competitive utility-scale solar photovoltaic (PV) electricity - only three years into the Department's decade-long SunShot Initiative. To help

  4. Perceptions of risk among households in two Australian coastal communities

    SciTech Connect (OSTI)

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall, the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.

  5. 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).

  6. 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).

  7. Perceptions of risk among households in two Australian coastal communities

    DOE PAGES-Beta [OSTI]

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall,more » the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.« less

  8. Reconstructing householder vectors from Tall-Skinny QR

    DOE PAGES-Beta [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 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

  9. 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.

  10. 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 ...

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

    U.S. Energy Information Administration (EIA) (indexed site)

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

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

    U.S. Energy Information Administration (EIA) (indexed site)

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

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

  14. Impacts of Increasing Natural Gas Fueled CHP from 20 to 35 Percent...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Impacts of Increasing Natural Gas Fueled CHP from 20 to 35 Percent of Total Electricity Production in Texas, April 2011 Impacts of Increasing Natural Gas Fueled CHP from 20 to 35 ...

  15. If I generate 20 percent of my national electricity from wind...

    Open Energy Information (Open El) [EERE & EIA]

    If I generate 20 percent of my national electricity from wind and solar - what does it do to my GDP and Trade Balance ? Home I think that the economics of fossil fuesl are well...

  16. Fact #924: May 9, 1916 Twenty Percent of New Cars in 2015 Had...

    Energy.gov (indexed) [DOE]

    Twenty Percent of New Cars in 2015 Had Turbochargers File fotw924web.xlsx More Documents & Publications Fact 923: May 2, 2016 Cylinder Deactivation was Used in More than a ...

  17. EECBG 11-002 Clarification of Ten Percent Limitation on Use of...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    EECBG PROGRAM NOTICE 11-002 EFFECTIVE DATE: July 28, 2011 SUBJECT: CLARIFICATION OF TEN PERCENT LIMATION ON USE OF FUNDS FOR ADMINISTRATIVE EXPENSES PURPOSE To provide guidance to...

  18. EECBG 11-002 Clarification of Ten Percent Limitation on Use of Funds for Administrative Expenses

    Energy.gov [DOE]

    U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency and Conservation Block Grant Program (EECBG), ten percent limitation, administrative expenses, the Energy Independence and Security Act of 2007.

  19. Evaluation Prompts ENERGY STAR Program to Replace Web Tool, Saving 90 Percent of Annual Costs

    Energy.gov [DOE]

    This document, from the U.S. Environmental Protection Agency's ENERGY STAR Residential Program, is part of the Case Study Series, highlighting how "Evaluation Prompts ENERGY STAR Program to Replace Web Tool, Saving 90 Percent of Annual Costs."

  20. NREL Study Shows 20 Percent Wind is Possible by 2024 - News Releases | NREL

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    NREL Study Shows 20 Percent Wind is Possible by 2024 Analysis Shows Transmission Upgrades, Offshore Wind, and Operational Changes Needed to Incorporate 20 to 30 Percent Wind January 20, 2010 Today, the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) released the Eastern Wind Integration and Transmission Study (EWITS). This unprecedented two-and-a-half year technical study of future high-penetration wind scenarios was designed to analyze the economic, operational,

  1. NREL Study: Hybrid Delivery Vans Show Nearly 20 Percent Higher Fuel Economy

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    - News Releases | NREL Study: Hybrid Delivery Vans Show Nearly 20 Percent Higher Fuel Economy September 28, 2012 The U.S. Department of Energy's (DOE)'s National Renewable Energy Laboratory (NREL) recently completed a performance evaluation report that showed significant fuel economy benefits of hybrid electric delivery vans compared to similar conventional vans. "During the on-road portion of our study, the hybrid vans demonstrated a 13 to 20 percent higher fuel economy than the

  2. Impacts of Increasing Natural Gas Fueled CHP from 20 to 35 Percent of Total

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Electricity Production in Texas, April 2011 | Department of Energy Impacts of Increasing Natural Gas Fueled CHP from 20 to 35 Percent of Total Electricity Production in Texas, April 2011 Impacts of Increasing Natural Gas Fueled CHP from 20 to 35 Percent of Total Electricity Production in Texas, April 2011 This report is an examination of the possible impacts, implications, and practicality of increasing the amount of electrical energy produced from combined heat and power (CHP) facilities

  3. Better Buildings Challenge Partners Pledge 20 Percent Energy Drop By 2020 |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Challenge Partners Pledge 20 Percent Energy Drop By 2020 Better Buildings Challenge Partners Pledge 20 Percent Energy Drop By 2020 November 9, 2011 - 10:00am Addthis This is the Atlanta Better Buildings Challenge Breakout Session Panel with representatives from the City of Atlanta Office of Sustainability, Southface, the U.S. General Services Administration, and two Atlanta BBC partner organizations. | Photo courtesy of Fred Perry Photography This is the Atlanta Better

  4. Ventilation Behavior and Household Characteristics in NewCalifornia Houses

    SciTech Connect (OSTI)

    Price, Phillip N.; Sherman, Max H.

    2006-02-01

    A survey was conducted to determine occupant use of windows and mechanical ventilation devices; barriers that inhibit their use; satisfaction with indoor air quality (IAQ); and the relationship between these factors. A questionnaire was mailed to a stratified random sample of 4,972 single-family detached homes built in 2003, and 1,448 responses were received. A convenience sample of 230 houses known to have mechanical ventilation systems resulted in another 67 completed interviews. Some results are: (1) Many houses are under-ventilated: depending on season, only 10-50% of houses meet the standard recommendation of 0.35 air changes per hour. (2) Local exhaust fans are under-utilized. For instance, about 30% of households rarely or never use their bathroom fan. (3) More than 95% of households report that indoor air quality is ''very'' or ''somewhat'' acceptable, although about 1/3 of households also report dustiness, dry air, or stagnant or humid air. (4) Except households where people cook several hours per week, there is no evidence that households with significant indoor pollutant sources get more ventilation. (5) Except households containing asthmatics, there is no evidence that health issues motivate ventilation behavior. (6) Security and energy saving are the two main reasons people close windows or keep them closed.

  5. MFT homogeneity study at TNX: Final report on the low weight percent solids concentration

    SciTech Connect (OSTI)

    Jenkins, W.J.

    1993-09-21

    A statistical design and analysis of both elemental analyses and weight percent solids analyses data was utilized to evaluate the MFT homogeneity at low heel levels and low agitator speed at both high and low solids feed concentrations. The homogeneity was also evaluated at both low and high agitator speed at the 6000+ gallons static level. The dynamic level portion of the test simulated feeding the Melter from the MFT to evaluate the uniformity of the solids slurry composition (Frit-PHA-Sludge) entering the melter from the MFT. This final report provides the results and conclusions from the second half of the study, the low weight percent solids concentration portion, as well as a comparison with the results from the first half of the study, the high weight percent solids portion.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

  7. NREL Solar Cell Sets World Efficiency Record at 40.8 Percent - News

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    Releases | NREL NREL Solar Cell Sets World Efficiency Record at 40.8 Percent August 13, 2008 Scientists at the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) have set a world record in solar cell efficiency with a photovoltaic device that converts 40.8 percent of the light that hits it into electricity. This is the highest confirmed efficiency of any photovoltaic device to date. The inverted metamorphic triple-junction solar cell was designed, fabricated and

  8. Fact #763: January 21, 2013 Eighty-four Percent of Scrapped Tires Are

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Recycled | Department of Energy 3: January 21, 2013 Eighty-four Percent of Scrapped Tires Are Recycled Fact #763: January 21, 2013 Eighty-four Percent of Scrapped Tires Are Recycled There were 263 million tires scrapped in 2009 (latest available data) which amounts to more than 4.7 million tons of waste. Fortunately, 84% of that waste was recycled. Most of the recycled tires were used to make fuel for industries such as pulp and paper mills, cement kilns, and electric utilities. Ground

  9. Fact #924: May 9, 1916 Twenty Percent of New Cars in 2015 Had Turbochargers

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    | Department of Energy 4: May 9, 1916 Twenty Percent of New Cars in 2015 Had Turbochargers Fact #924: May 9, 1916 Twenty Percent of New Cars in 2015 Had Turbochargers SUBSCRIBE to the Fact of the Week Turbocharging is not a new technology, but has grown in new light vehicle market share over the last five years. In 2015, more than 20% of new cars and nearly 14% of new light trucks had turbocharged engines (turbos). Turbocharging, often paired with gasoline direct injection (GDI), has allowed

  10. EM's Oak Ridge Cleanup Contractor Earns 93 Percent of Available Fee |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Oak Ridge Cleanup Contractor Earns 93 Percent of Available Fee EM's Oak Ridge Cleanup Contractor Earns 93 Percent of Available Fee July 28, 2016 - 12:45pm Addthis UCOR’s K-27 Building demolition project, pictured here, is ahead of schedule with actual costs projected to be less than planned, according to OREM’s correspondence regarding the contractor’s fee determination. UCOR's K-27 Building demolition project, pictured here, is ahead of schedule with

  11. NNSA hits 21 percent of CFC goal | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    | (NNSA) hits 21 percent of CFC goal Monday, October 27, 2014 - 5:14pm NNSA Blog As of today, NNSA has collected slightly more than 21 percent of its goal of $174,000 for this year's Combined Federal Campaign (CFC). With seven weeks remaining before the campaign closes on Dec. 15, 2014, everyone is encouraged to join those who have become a "Super Hero" and help push NNSA over its goal. Contributions can go to any of more than 20,000 tax-exempt organizations. Each individual can

  12. 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.

  13. How are coastal households responding to climate change?

    DOE PAGES-Beta [OSTI]

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Preston, Benjamin L.; Thomsen, Dana C.; Baum, Scott

    2016-06-13

    In Australia, shared responsibility is a concept advocated to promote collective climate change adaptation by multiple actors and institutions. However, a shared response is often promoted in the absence of information regarding actions currently taken; in particular, there is limited knowledge regarding action occurring at the household scale. To address this gap, we examine household actions taken to address climate change and associated hazards in two Australian coastal communities. Mixed methods research is conducted to answer three questions: (1) what actions are currently taken (mitigation, actions to lobby for change or adaptation to climate impacts)? (2) why are these actionsmore » taken (e.g. are they consistent with capacity, experience, perceptions of risk); and (3) what are the implications for adaptation? We find that households are predominantly mitigating greenhouse gas emissions and that impact orientated adaptive actions are limited. Coping strategies are considered sufficient to mange climate risks, proving a disincentive for additional adaptive action. Influencing factors differ, but generally, risk perception and climate change belief are associated with action. Furthermore, the likelihood of more action is a function of homeownership and a tendency to plan ahead. Addressing factors that support or constrain household adaptive decision-making and action, from the physical (e.g. homeownership) to the social (e.g. skills in planning and a culture of adapting to change) will be critical in increasing household participation in adaptation.« less

  14. EM’s West Valley Cleanup Contactor Receives 85 Percent of Available Fee Award

    Energy.gov [DOE]

    EST VALLEY, N.Y. – EM announced that the contractor at its West Valley Demonstration Project (WVDP) cleanup earned $250,000, or nearly 85 percent of the available fee award of $295,495 for the six-month period ending Feb. 29 this year.

  15. Percent of Commercial Natural Gas Deliveries in Hawaii Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100 100 100 100 100 100 100 100 100 100 2000's 100 100 100 100 100 100 100 100 100 100 2010's

  16. Percent of Commercial Natural Gas Deliveries in Vermont Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100 100 100 100 100 100 100 100 100 100 2000's 100 100 100 100 100 100 100 100 100 100 2010's 100 100 100 100 100 NA

  17. WPN 93-14: 40 Percent Waiver Provisions for Multifamily and Mobile Home Units

    Energy.gov [DOE]

    This program notice provides guidance on multifamily and mobile home units weatherized by states, which adopt the approved 4.0 version of NEAT or other similar approved energy audits and receive a waiver of the 40 percent requirement from DOE.

  18. WPN 94-8: 40 Percent Waiver Provisions for Mobile Home Units

    Energy.gov [DOE]

    This program notice provides clarifying guidance previously issued under Weatherization Program Notice 93-14 on mobile home units weatherized by states which adopt the approved 4.0 version of NEAT or other similar approved energy audits and receive a waiver of the 40 percent requirement from DOE.

  19. Figure 5. Production Schedules at Two Development Rates for the 5 Percent

    U.S. Energy Information Administration (EIA) (indexed site)

    Probability of Recovering 16.0 Billion Barrels 5. Production Schedules at Two Development Rates for the 5 Percent Probability of Recovering 16.0 Billion Barrels of Technically Recoverable Oil from the ANWR Coastal Plain of Alaska fig5.jpg (3770

  20. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, J.D.; Liu, Xiaomin; McMahon, J.E.

    1996-11-01

    This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

  1. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

    1996-01-01

    This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

  2. Household heating bills expected to be lower this winter

    U.S. Energy Information Administration (EIA) (indexed site)

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

  3. A Glance at China’s Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-01

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

  4. Percent of Industrial Natural Gas Deliveries in Vermont Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100.0 100.0 76.6 2000's 83.8 75.4 74.7 78.8 78.3 81.7 78.4 78.0 79.6 77.9 2010's 77.1 80.9

  5. 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.

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

    U.S. Department of Energy (DOE) all webpages (Extended Search)

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

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

    Annual Energy Outlook

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

  8. Household energy conservation attitudes and behaviors in the Northwest: Tracking changes between 1983 and 1985

    SciTech Connect (OSTI)

    Fang, J.M.; Hattrup, M.P.; Nordi, R.T.; Shankle, S.A.; Ivey, D.L.

    1987-05-01

    Pacific Northwest Laboratory (PNL) has analyzed the changes in consumer energy conservation attitudes and behaviors in the Pacific Northwest between 1983 and 1985. The information was collected through stratified random telephone surveys on 2000 and 1058 households, respectively, for 1983 and 1985 in the Bonneville Power Administration (BPA) service area in Idaho, Oregon, Washington and Western Montana. This report covers four topic areas and tests two hypotheses. The topics are as follows: consumer perceptions and attitudes of energy use and conservation in the home; consumer perceptions of energy institutions and other entities; past and intended conservation actions and investments; and segmentation of homeowners into market prospect groups. The hypotheses tested are as follows: (1) There has been no change in the size and psychographic make-up of the original three market segments found in the 1983 survey analysis; and (2) image profiles of institutions with respect to familiarity, overall impression, and believability as sources of energy conservation information remain unchanged since 1983.

  9. Particle and gas emissions from a simulated coal-burning household fire pit

    SciTech Connect (OSTI)

    Linwei Tian; Donald Lucas; Susan L. Fischer; S. C. Lee; S. Katharine Hammond; Catherine P. Koshland

    2008-04-01

    An open fire was assembled with firebricks to simulate the household fire pit used in rural China, and 15 different coals from this area were burned to measure the gaseous and particulate emissions. Particle size distribution was studied with a microorifice uniform-deposit impactor (MOUDI). Over 90% of the particulate mass was attributed to sub-micrometer particles. The carbon balance method was used to calculate the emission factors. Emission factors for four pollutants (particulate matter, CO{sub 2}, total hydrocarbons, and NOx) were 2-4 times higher for bituminous coals than for anthracites. In past inventories of carbonaceous emissions used for climate modeling, these two types of coal were not treated separately. The dramatic emission factor difference between the two types of coal warrants attention in the future development of emission inventories. 25 refs., 8 figs., 1 tab.

  10. New Water Booster Pump System Reduces Energy Consumption by 80 Percent and Increases Reliability

    Office of Energy Efficiency and Renewable Energy (EERE)

    This case study outlines how General Motors (GM) developed a highly efficient pumping system for their Pontiac Operations Complex in Pontiac, Michigan. In short, GM was able to replace five original 60- to 100-hp pumps with three 15-hp pumps whose speed could be adjusted to meet plant requirements. As a result, the company reduced pumping system energy consumption by 80 percent (225,100 kWh per year), saving an annual $11,255 in pumping costs. With a capital investment of $44,966 in the energy efficiency portion of their new system, GM projected a simple payback of 4 years.

  11. Percent of Commercial Natural Gas Deliveries in Alabama Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 79.6 82.7 80.7 80.8 80.3 80.1 81.1 64.7 80.5 70.5 2000's 81.4 82.5 80.5 81.8 82.1 80.5 80.2 79.8 80.2 78.8 2010's 79.3 78.9 76.2 76.6 78.4 77.6

  12. Percent of Commercial Natural Gas Deliveries in Alaska Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100.0 100.0 100.0 100.0 100.0 79.9 63.4 54.5 49.6 55.4 2000's 59.3 60.5 60.0 59.1 55.5 51.2 56.3 76.0 74.9 85.3 2010's 87.7 88.6 94.9 94.5 94.5 98.1

  13. Percent of Commercial Natural Gas Deliveries in Arkansas Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 92.3 91.5 90.7 91.8 95.1 96.0 95.0 94.2 90.8 89.3 2000's 89.9 87.0 80.8 81.9 80.3 74.1 71.7 70.4 64.5 59.4 2010's 55.6 51.5 40.2 43.7 45.5 42.5

  14. Percent of Commercial Natural Gas Deliveries in Colorado Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 97.3 96.0 95.5 95.5 94.8 94.2 93.2 92.8 94.3 97.5 2000's 97.4 95.6 95.3 95.3 94.7 95.2 95.4 95.7 95.2 94.8 2010's 94.6 93.8 92.2 94.7 94.5 NA

  15. Percent of Commercial Natural Gas Deliveries in Delaware Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 98.8 2000's 98.0 98.3 82.8 82.8 81.6 83.3 77.5 74.8 70.6 53.5 2010's 49.8 53.4 43.7 45.0 46.2 45.7

  16. Percent of Commercial Natural Gas Deliveries in Georgia Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 88.4 87.5 88.1 90.5 92.0 93.5 94.1 89.1 83.6 61.0 2000's 17.1 20.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2010's

  17. Percent of Commercial Natural Gas Deliveries in Idaho Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 87.9 87.6 85.7 86.8 85.9 86.0 86.6 86.1 86.4 85.9 2000's 86.3 86.3 85.9 85.2 85.7 85.6 85.8 84.8 86.0 83.7 2010's 82.0 80.8 77.0 77.4 76.6 74.6

  18. Percent of Commercial Natural Gas Deliveries in Illinois Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 57.6 59.0 57.7 55.3 52.8 50.4 53.9 54.3 47.4 42.8 2000's 41.9 41.1 40.9 43.1 41.2 41.5 39.7 42.2 43.3 41.3 2010's 42.3 38.1 36.8 38.4 38.5 36.1

  19. Percent of Commercial Natural Gas Deliveries in Indiana Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 95.7 94.2 96.8 95.2 92.3 87.8 96.3 89.9 79.2 78.3 2000's 78.0 77.1 78.4 79.8 78.2 82.1 79.4 78.1 77.9 73.9 2010's 72.5 70.2 67.4 68.2 67.6 67.0

  20. Percent of Commercial Natural Gas Deliveries in Iowa Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 97.6 97.7 95.7 94.7 90.4 89.3 87.7 88.2 85.8 83.4 2000's 81.1 82.0 81.4 78.0 78.3 78.3 77.3 77.7 75.8 72.5 2010's 72.0 72.1 72.2 72.5 74.4 NA

  1. Percent of Commercial Natural Gas Deliveries in Kentucky Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 95.0 94.0 93.1 92.6 91.4 89.2 90.8 90.0 87.4 87.9 2000's 85.6 81.8 78.9 79.2 78.7 79.7 81.3 81.7 82.0 80.1 2010's 80.5 79.2 77.4 78.8 80.5 79.2

  2. Percent of Commercial Natural Gas Deliveries in Maryland Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 95.6 96.6 96.0 96.6 97.1 96.9 91.9 67.1 36.6 33.4 2000's 39.1 32.6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2010's 100.0 27.3 24.7 26.2 27.3 27

  3. Percent of Commercial Natural Gas Deliveries in Missouri Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 86.0 85.9 85.5 84.6 83.3 83.3 82.2 79.9 78.3 78.6 2000's 80.0 80.8 80.0 80.5 77.4 77.1 76.4 76.9 77.5 76.7 2010's 76.5 73.1 69.2 72.3 70.5 71

  4. Percent of Commercial Natural Gas Deliveries in Montana Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 97.9 97.5 95.4 93.2 91.8 91.6 91.5 91.5 77.2 79.8 2000's 73.5 76.1 75.1 68.8 76.0 77.4 76.9 78.5 79.6 49.2 2010's 54.6 53.3 52.8 53.3 53.5 NA

  5. Percent of Commercial Natural Gas Deliveries in Nebraska Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 93.9 91.8 88.2 91.0 80.2 77.1 70.0 74.2 72.5 66.6 2000's 61.1 63.7 63.7 65.4 63.5 64.5 65.1 63.9 57.5 61.3 2010's 60.6 60.6 55.8 57.3 56.4 56.1

  6. Percent of Commercial Natural Gas Deliveries in New Jersey Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 94.8 93.9 92.4 91.6 91.6 86.3 73.3 56.2 60.5 56.0 2000's 56.9 57.5 49.1 50.7 48.1 51.6 46.9 44.2 42.1 38.3 2010's 36.1 32.6 30.8 35.2 32.0

  7. Percent of Commercial Natural Gas Deliveries in New Mexico Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 83.1 77.7 70.0 62.5 62.4 60.3 64.7 71.0 67.0 63.0 2000's 62.2 67.3 72.5 70.3 69.0 69.0 65.0 64.2 62.6 58.2 2010's 60.7 59.8 57.0 57.0 54.4 NA

  8. Percent of Commercial Natural Gas Deliveries in North Dakota Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 74.8 70.0 68.9 72.7 79.6 80.9 88.0 88.9 83.8 88.2 2000's 89.5 90.1 91.6 94.4 92.6 92.9 93.0 93.3 93.4 92.9 2010's 92.6 92.8 91.9 92.6 93.1 93.0

  9. Percent of Commercial Natural Gas Deliveries in Ohio Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 87.3 86.7 85.6 84.6 81.5 76.3 71.8 65.5 55.0 46.4 2000's 45.2 41.8 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2010's

  10. Percent of Commercial Natural Gas Deliveries in Oregon Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 97.7 97.9 97.8 97.9 98.1 98.1 98.3 98.5 99.0 98.8 2000's 98.8 99.3 98.7 98.4 98.6 98.6 98.5 98.5 98.5 98.4 2010's 97.4 97.4 96.9 96.6 96.0 NA

  11. Percent of Commercial Natural Gas Deliveries in Rhode Island Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 95.9 100.0 100.0 100.0 100.0 100.0 91.8 80.5 59.2 53.2 2000's 53.2 58.0 65.9 72.1 73.3 74.3 73.1 66.5 66.2 68.0 2010's 61.2 56.9 55.4 54.5 52.2 53.9

  12. Percent of Commercial Natural Gas Deliveries in South Dakota Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 86.4 81.8 82.4 83.9 89.1 86.9 82.7 83.3 84.2 81.2 2000's 83.1 84.2 83.1 82.3 82.3 83.5 82.1 81.2 83.0 82.2 2010's 80.9 81.7 81.6 81.6 81.6 81.0

  13. Percent of Commercial Natural Gas Deliveries in Texas Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 89.8 89.3 79.7 83.8 82.4 68.6 83.5 61.4 81.0 77.3 2000's 79.0 88.4 71.8 73.7 74.6 79.5 82.0 81.9 82.5 78.3 2010's 76.4 73.4 72.4 72.8 72.6 NA

  14. Percent of Commercial Natural Gas Deliveries in Utah Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100.0 100.0 100.0 100.0 83.3 81.8 81.9 83.2 82.5 82.9 2000's 83.9 84.4 83.7 84.4 84.4 86.8 86.8 86.9 86.4 85.6 2010's 86.2 86.7 83.9 81.8 78.3 77.0

  15. Percent of Commercial Natural Gas Deliveries in Virginia Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 93.2 93.6 90.7 88.8 86.7 84.1 85.3 77.9 72.1 67.4 2000's 66.4 65.8 61.4 65.7 63.6 100.0 100.0 100.0 100.0 100.0 2010's 100.0 54.1 52.1 54.6 55.8 54.2

  16. Percent of Commercial Natural Gas Deliveries in Wyoming Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 99.8 99.0 98.0 98.0 96.1 93.6 85.9 84.1 90.5 89.1 2000's 90.0 86.5 48.7 51.7 51.4 49.3 47.8 49.3 65.6 65.5 2010's 65.3 64.0 62.6 62.9 60.8

  17. Percent of Industrial Natural Gas Deliveries in Georgia Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 26.7 25.3 23.9 2000's 20.2 19.9 19.2 15.9 16.4 17.1 17.0 17.2 16.1 17.6 2010's 18.2 18.2 20.0 18.9 20.0 NA

  18. Percent of Industrial Natural Gas Deliveries in Idaho Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2.0 2.5 2.7 2000's 2.7 2.2 2.0 2.1 2.4 2.3 2.1 2.0 1.9 1.7 2010's 1.8 2.0 1.9 2.5 2.8 2.4

  19. Percent of Industrial Natural Gas Deliveries in Illinois Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 11.5 9.3 9.1 2000's 9.0 9.9 9.3 9.9 9.0 9.5 8.7 9.5 9.4 7.7 2010's 7.4 6.3 6.0 6.8 6.4 5.9

  20. Percent of Industrial Natural Gas Deliveries in Indiana Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 16.0 9.3 5.8 2000's 10.3 7.7 8.6 9.0 8.3 7.9 7.2 7.4 6.7 7.0 2010's 5.6 3.5 1.9 2.0 2.1 1.9

  1. Percent of Industrial Natural Gas Deliveries in Iowa Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 8.7 6.8 7.4 2000's 7.0 7.5 7.6 7.9 8.4 9.8 8.5 6.5 6.6 6.4 2010's 5.8 5.5 5.2 5.6 4.8 NA

  2. Percent of Industrial Natural Gas Deliveries in Kentucky Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 19.2 17.8 17.5 2000's 19.0 18.7 17.7 18.8 16.9 16.9 15.8 16.6 17.5 18.1 2010's 17.9 17.6 17.8 18.3 17.2 16.0

  3. Percent of Industrial Natural Gas Deliveries in Maryland Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 7.4 7.0 6.5 2000's 6.1 8.5 8.0 10.0 8.2 8.2 6.7 7.8 6.3 5.3 2010's 5.3 5.5 5.1 6.8 7.3

  4. Percent of Industrial Natural Gas Deliveries in Michigan Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 12.5 10.8 11.1 2000's 10.2 11.3 10.2 10.9 10.7 10.1 10.2 12.6 12.5 11.8 2010's 8.8 9.3 7.4 7.4 7.6 NA

  5. Percent of Industrial Natural Gas Deliveries in Missouri Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 21.5 18.2 18.5 2000's 16.8 16.5 16.0 14.8 13.8 14.2 13.2 12.8 13.9 13.2 2010's 13.1 13.4 12.5 13.9 14.0 12.3

  6. Percent of Industrial Natural Gas Deliveries in Montana Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 3.1 1.5 1.7 2000's 1.9 2.2 2.1 1.8 1.6 1.8 0.7 0.8 1.0 1.1 2010's 1.5 1.3 1.0 1.2 1.4

  7. Percent of Industrial Natural Gas Deliveries in Nebraska Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 27.0 12.7 14.2 2000's 15.4 18.0 15.7 16.5 16.5 16.3 11.6 9.7 10.2 8.9 2010's 8.2 7.6 6.8 7.8 7.4 7.1

  8. Percent of Industrial Natural Gas Deliveries in New Jersey Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 49.3 49.5 47.9 2000's 23.5 21.6 20.8 19.5 16.4 19.9 19.5 20.6 11.0 9.0 2010's 8.4 8.2 6.5 6.1 6.6

  9. Percent of Industrial Natural Gas Deliveries in New Mexico Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 9.5 9.8 16.4 2000's 16.5 10.1 15.6 12.3 11.2 8.4 11.6 10.6 10.0 11.9 2010's 12.4 10.2 7.9 8.0 7.5 6.4

  10. Percent of Industrial Natural Gas Deliveries in North Dakota Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 18.5 14.6 14.9 2000's 13.9 9.8 9.2 45.9 51.1 27.5 42.3 48.1 46.2 34.8 2010's 29.7 37.4 34.7 37.9 34.7 39.6

  11. Percent of Industrial Natural Gas Deliveries in Ohio Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 5.7 4.3 4.1 2000's 5.3 6.5 4.0 3.9 3.5 3.6 3.0 2.7 2.7 2.8 2010's 2.1 2.0 1.6 2.2 2.0 NA

  12. Percent of Industrial Natural Gas Deliveries in Oregon Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 16.3 14.3 13.6 2000's 17.7 21.5 14.4 17.5 24.9 33.2 26.6 21.8 20.1 18.9 2010's 17.1 17.1 16.7 16.9 17.2 16.6

  13. Percent of Industrial Natural Gas Deliveries in Rhode Island Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 17.4 7.4 6.5 2000's 34.0 27.3 27.3 18.9 15.7 15.3 13.6 11.6 11.7 9.2 2010's 6.5 6.0 6.3 9.0 8.1 5

  14. Percent of Industrial Natural Gas Deliveries in South Dakota Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 24.1 35.6 37.0 2000's 41.9 42.1 19.4 25.5 28.2 30.2 33.6 17.8 16.9 14.4 2010's 10.4 4.7 4.3 5.2 4.6 4.1

  15. Percent of Industrial Natural Gas Deliveries in Texas Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 17.2 14.1 23.7 2000's 29.6 35.0 43.0 43.9 48.8 54.6 55.4 54.7 50.4 47.2 2010's 48.6 39.0 39.4 41.7 40.3 40.7

  16. Percent of Industrial Natural Gas Deliveries in Utah Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 8.9 8.6 9.5 2000's 10.0 10.4 13.6 13.6 19.8 19.5 20.1 14.1 12.7 12.2 2010's 12.1 12.7 11.0 11.1 10.5 8.6

  17. Percent of Industrial Natural Gas Deliveries in Virginia Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 13.0 12.8 12.1 2000's 17.6 17.3 15.3 17.3 16.0 17.1 13.9 14.1 17.3 15.8 2010's 15.3 13.6 10.9 10.3 11.1 NA

  18. Percent of Industrial Natural Gas Deliveries in Wyoming Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2.5 2.0 2.9 2000's 2.6 2.5 2.9 1.8 2.1 3.7 3.5 3.0 3.2 3.1 2010's 1.1 1.0 0.9 1.2 1.3

  19. Method to produce alumina aerogels having porosities greater than 80 percent

    DOE Patents [OSTI]

    Poco, John F.; Hrubesh, Lawrence W.

    2003-09-16

    A two-step method for producing monolithic alumina aerogels having porosities of greater than 80 percent. Very strong, very low density alumina aerogel monoliths are prepared using the two-step sol-gel process. The method of preparing pure alumina aerogel modifies the prior known sol method by combining the use of substoichiometric water for hydrolysis, the use of acetic acid to control hydrolysis/condensation, and high temperature supercritical drying, all of which contribute to the formation of a polycrystalline aerogel microstructure. This structure provides exceptional mechanical properties of the alumina aerogel, as well as enhanced thermal resistance and high temperature stability.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

  1. Percent of Commercial Natural Gas Deliveries in Hawaii Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100 100 100 100 100 100 100 100 100 100 100 100 1990 100 100 100 100 100 100 100 100 100 100 100 100 1991 100 100 100 100 100 100 100 100 100 100 100 100 1992 100 100 100 100 100 100 100 100 100 100 100 100 1993 100 100 100 100 100 100 100 100 100 100 100 100 1994 100 100 100 100 100 100 100 100 100 100 100 100 1995 100 100 100 100 100 100 100 100 100 100 100 100 1996 100 100 100 100 100 100 100 100 100 100 100 100

  2. Percent of Commercial Natural Gas Deliveries in Vermont Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100 100 100 100 100 100 100 100 100 100 100 100 1990 100 100 100 100 100 100 100 100 100 100 100 100 1991 100 100 100 100 100 100 100 100 100 100 100 100 1992 100 100 100 100 100 100 100 100 100 100 100 100 1993 100 100 100 100 100 100 100 100 100 100 100 100 1994 100 100 100 100 100 100 100 100 100 100 100 100 1995 100 100 100 100 100 100 100 100 100 100 100 100 1996 100 100 100 100 100 100 100 100 100 100 100 100

  3. Percent of Commercial Natural Gas Deliveries in U.S. Total Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 93.1 90.8 89.1 1990's 86.6 85.1 83.2 83.9 79.3 76.7 77.6 70.8 67.0 66.1 2000's 63.9 66.0 77.4 78.2 78.0 82.1 80.8 80.4 79.7 77.8 2010's 77.5 67.3 65.2 65.8 65.8 65.9

  4. Percent of Industrial Natural Gas Deliveries in Hawaii Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 100 100 100 100 100 100 100 100 100 100 100 100 2002 100 100 100 100 100 100 100 100 100 100 100 100 2003 100 100 100 100 100 100 100 100 100 100 100 100 2004 100 100 100 100 100 100 100 100 100 100 100 100 2005 100 100 100 100 100 100 100 100 100 100 100 100 2006 100 100 100 100 100 100 100 100 100 100 100 100 2007 100 100 100 100 100 100 100 100 100 100 100 100 2008 100 100 100 100 100 100 100 100 100 100 100 100

  5. "Table HC15.3 Household Characteristics by Four Most Populated...

    U.S. Energy Information Administration (EIA) (indexed site)

    "Income Relative to Poverty Line" "Below 100 Percent",16.6,1.5,1,1.5,... " 1. Below 150 percent of poverty line or 60 percent of median State ...

  6. Hopper Job Size Charts

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    Job Size Charts Hopper Job Size Charts Fractional Jobs The following charts show the fraction of hours used on Hopper in each of five job-core-size bins: 2014 Usage by Job Size Chart 2013 2012 2011 Large Jobs The following charts show the fraction of hours used on Hopper by jobs using greater than 16,384 cores: 2014 2013 2012 Usage by Job Size Chart 2011 Last edited: 2016-05-02 09:20:42

  7. Possibility of using cylindrical ionization chambers for percent depth-dose measurements in clinical electron beams

    SciTech Connect (OSTI)

    Ono, Takeshi; Araki, Fujio; Yoshiyama, Fumiaki

    2011-08-15

    Purpose: This study investigated the possibility of using cylindrical ionization chambers for percent depth-dose (PDD) measurements in high-energy clinical electron beams. Methods: The cavity correction factor, P{sub cav}, for cylindrical chambers with various diameters was calculated as a function of depth from the surface to R{sub 50}, in the energy range of 6-18 MeV electrons with the EGSnrc C ++ -based user-code CAVITY. The results were compared with those for IBA NACP-02 and PTW Roos parallel-plate ionization chambers. The effective point of measurement (EPOM) for the cylindrical chamber and the parallel-plate chamber was positioned according to the IAEA TRS-398 code of practice. The overall correction factor, P{sub Q}, and the percent depth-ionization (PDI) curve for a PTW30013 Farmer-type chamber were also compared with those of NACP-02 and Roos chambers. Results: The P{sub cav} values at depths between the surface and R{sub 50} for cylindrical chambers were all lower than those with parallel-plate chambers. However, the variation in depth for cylindrical chambers equal to or less than 4 mm in diameter was equivalent to or smaller than that for parallel-plate chambers. The P{sub Q} values for the PTW30013 chamber mainly depended on P{sub cav}, and for parallel-plate chambers depended on the wall correction factor, P{sub wall}, rather than P{sub cav}. P{sub Q} at depths from the surface to R{sub 50} for the PTW30013 chamber was consequently a lower value than that with parallel-plate chambers. However, the variation in depth was equivalent to that of parallel-plate chambers at electron energies equal to or greater than 9 MeV. The shift to match calculated PDI curves for the PTW30013 chamber and water (perturbation free) varied from 0.65 to 0 mm between 6 and 18 MeV beams. Similarly, the shifts for NACP-02 and Roos chambers were 0.5-0.6 mm and 0.2-0.3 mm, respectively, and were nearly independent of electron energy. Conclusions: Calculated PDI curves for PTW

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

    Gasoline and Diesel Fuel Update

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

  9. Edison Job Size Charts

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    Reports » Edison Job Size Charts Edison Job Size Charts Fraction of Hours Used per Job Size Note: Interactive charts with current and past Cori and Edison data are now available on MyNERSC This chart shows the fraction of hours used on Edison in each of 5 job-core-size bins. 2015 Usage by Job Size Chart 2014 Fraction of Hours Used by Big Jobs This chart shows the fraction of hours used on Edison by jobs using 16,384 or more cores. 2015 Usage by Job Size Chart 2014 Last edited: 2016-04-21

  10. Percent of Commercial Natural Gas Deliveries in Alaska Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1990 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1991 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1992 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1993 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1994 100.0 100.0 100.0 100.0 100.0 100.0

  11. Percent of Commercial Natural Gas Deliveries in Delaware Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1990 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1991 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1992 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1993 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1994 100.0 100.0 100.0 100.0 100.0 100.0

  12. Percent of Commercial Natural Gas Deliveries in Maine Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1990 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1991 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1992 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1993 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1994 100.0 100.0 100.0 100.0 100.0 100.0

  13. Percent of Commercial Natural Gas Deliveries in New Jersey Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 99.0 98.9 98.7 98.3 96.2 94.7 94.2 93.4 93.5 94.7 99.0 99.7 1990 99.6 99.3 96.6 94.4 94.3 93.2 89.3 86.4 87.1 86.2 91.7 96.5 1991 98.1 96.5 95.8 91.8 92.3 89.1 89.5 80.6 89.2 90.0 93.2 97.0 1992 96.9 95.7 92.1 87.7 94.1 91.3 88.6 80.7 80.7 86.4 94.8 96.9 1993 93.6 94.0 93.7 91.2 88.5 86.4 87.1 79.8 84.6 90.0 92.4 93.8 1994 94.9 96.2 96.3 89.8 87.4 85.1 81.4 82.2 83.6 88.0 89.6 92.1 1995 93.7 92.4 91.3 87.4 84.5

  14. Percent of Commercial Natural Gas Deliveries in North Dakota Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 81.7 84.8 84.0 83.9 80.6 74.8 69.2 64.9 71.4 70.9 74.8 81.6 1990 83.9 82.5 78.4 76.0 75.4 69.7 54.3 53.3 57.4 58.4 69.8 75.8 1991 79.4 79.9 74.9 71.7 70.6 59.0 49.6 47.6 49.6 48.7 67.6 70.1 1992 71.7 73.7 72.0 71.6 73.6 63.8 61.6 58.8 57.2 56.8 67.3 68.9 1993 77.1 73.8 77.4 76.8 73.3 62.6 58.1 54.0 53.5 56.0 74.2 78.9 1994 82.6 86.8 83.1 82.1 78.4 69.7 66.2 63.2 61.8 64.0 82.2 76.9 1995 84.3 85.9 84.3 83.2 80.0

  15. Percent of Commercial Natural Gas Deliveries in Rhode Island Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100.0 100.0 100.0 87.1 83.9 47.7 48.9 40.4 44.6 82.7 100.0 100.0 1990 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 75.5 80.2 97.3 91.1 1991 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1992 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1993 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1994 100.0 100.0 100.0 100.0 100.0 100.0 100.0

  16. Percent of Commercial Natural Gas Deliveries in South Dakota Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 92.8 93.1 92.8 92.1 92.5 91.6 90.2 89.4 90.0 89.6 91.1 92.0 1990 90.7 90.1 90.2 88.0 78.4 83.0 81.9 82.4 82.0 77.7 82.0 86.3 1991 84.8 83.0 80.5 83.4 79.5 74.9 74.3 74.3 74.5 76.7 83.4 85.2 1992 87.0 83.3 85.6 83.1 80.7 73.5 72.3 74.6 78.0 76.5 81.8 84.7 1993 86.5 83.9 84.4 81.2 76.4 73.3 74.9 72.9 75.8 78.7 90.0 91.2 1994 92.9 92.3 92.6 88.4 84.7 74.7 72.7 82.0 79.0 83.4 88.4 92.1 1995 92.1 90.8 89.7 87.2 82.8

  17. Percent of Commercial Natural Gas Deliveries in Utah Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1990 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1991 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1992 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1993 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1994 83.8 85.2 82.9 82.4 77.7 77.9 76.4

  18. Percent of Commercial Natural Gas Deliveries in Wyoming Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 99.8 99.6 99.7 99.7 1990 99.7 99.7 99.7 99.8 99.7 99.7 99.6 99.6 99.5 99.5 99.7 99.7 1991 99.9 99.9 99.4 98.9 99.0 98.2 97.4 98.3 97.2 98.4 98.6 98.5 1992 98.6 98.1 97.8 98.4 97.9 97.2 96.5 97.1 97.4 97.2 98.2 98.3 1993 98.8 98.2 98.4 98.1 98.2 96.9 97.1 96.5 95.0 97.1 97.2 99.0 1994 98.1 96.0 96.9 97.3 95.2 91.7 93.4 92.1 93.5 95.6 96.1 96.8 1995 88.4 98.2 93.6 92.4 89.2

  19. Percent of Commercial Natural Gas Deliveries in U.S. Total Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1983 NA NA NA NA NA NA NA NA NA NA NA NA 1984 NA NA NA NA NA NA NA NA NA NA NA NA 1985 NA NA NA NA NA NA NA NA NA NA NA NA 1986 NA NA NA NA NA NA NA NA NA NA NA NA 1987 NA NA NA NA NA NA NA NA NA NA NA NA 1988 93.8 93.3 92.5 91.7 89.4 87.5 86.3 87.2 87.6 87.4 88.7 89.7 1989 91.0 91.2 90.8 89.2 88.2 86.1 85.1 85.1 84.6 85.2 87.7 90.7 1990 90.8 88.8 88.3 86.9 85.5 83.8 81.8 81.7 80.3 81.2 84.7 87.9 1991 89.4 88.5 87.8

  20. Percent of Industrial Natural Gas Deliveries in U.S. Total Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 23.5 23.2 22.0 21.0 19.5 19.2 20.2 19.6 19.8 20.3 20.2 20.7 2002 20.3 20.5 20.2 26.3 23.9 25.5 24.0 22.5 22.5 21.7 21.8 23.1 2003 21.4 22.1 21.3 20.9 20.3 19.1 24.7 22.9 22.9 23.3 22.7 23.5 2004 23.1 23.6 22.8 23.3 23.4 25.0 24.9 24.0 22.8 22.6 23.5 24.5 2005 24.8 24.3 24.6 23.9 24.2 23.7 24.5 24.6 23.2 23.2 23.4 23.7 2006 23.7 23.7 23.8 23.5 23.8 23.3 23.6 23.7 22.0 22.9 23.0 23.4 2007 22.7 23.0 22.4 22.3 23.2

  1. Percent of Industrial Natural Gas Deliveries in New Jersey Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 29.3 31.1 27.6 21.9 21.2 19.6 18.6 15.6 18.5 16.8 15.6 21.1 2002 23.5 22.2 23.5 21.5 18.7 18.3 17.4 16.9 18.0 18.5 22.1 26.0 2003 21.1 23.1 26.0 26.8 23.9 18.0 15.3 17.3 13.3 14.9 13.0 18.4 2004 19.5 22.5 18.1 16.6 15.0 13.7 11.6 15.1 13.6 13.6 15.4 18.5 2005 22.4 22.7 21.9 17.6 15.7 15.4 17.7 20.4 16.9 19.4 20.1 25.4 2006 23.6 22.4 21.6 19.0 17.0 16.3 18.5 19.1 15.6 16.6 19.9 21.8 2007 21.5 23.6 20.8 23.0 17.1

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

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

    Reports and Publications

    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. Percent of Commercial Natural Gas Deliveries in Alabama Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 84.0 82.5 89.4 90.6 83.8 86.2 55.5 83.6 78.9 84.4 78.4 85.7 1990 86.9 82.1 80.0 76.8 74.9 79.8 76.8 73.3 76.5 78.0 69.7 81.4 1991 82.2 87.0 87.9 83.2 84.0 85.4 85.7 81.3 75.8 74.4 75.5 81.7 1992 83.7 86.8 84.0 83.2 79.0 77.6 75.3 74.7 74.4 73.2 74.2 80.6 1993 84.1 85.3 85.8 84.0 79.8 76.8 75.9 74.0 74.4 71.3 74.7 79.3 1994 86.1 87.7 84.1 83.1 78.0 76.5 74.8 71.8 64.7 70.0 73.6 76.7 1995 82.5 85.7 85.8 81.4 77.5 75.7

  6. Percent of Commercial Natural Gas Deliveries in Arkansas Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 95.3 95.6 95.9 94.3 91.3 91.5 87.2 86.2 88.2 87.5 90.7 93.4 1990 95.8 94.8 93.7 93.2 90.7 88.8 88.4 86.9 87.4 86.8 90.6 91.5 1991 93.8 94.7 96.1 91.0 87.7 85.1 84.8 85.5 85.9 86.5 90.5 92.3 1992 93.0 94.7 91.3 92.7 88.4 87.0 85.9 85.4 86.4 87.6 88.7 90.8 1993 92.5 93.0 92.8 91.8 87.6 84.2 85.9 84.7 85.7 87.8 92.7 98.7 1994 93.9 95.9 95.4 94.8 91.2 91.7 94.2 94.3 96.6 95.3 96.4 97.4 1995 97.2 98.0 96.3 95.1 93.3 93.1

  7. Percent of Commercial Natural Gas Deliveries in Colorado Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 98.0 98.1 98.3 97.8 97.3 97.3 95.0 91.8 95.8 95.6 96.9 97.2 1990 98.1 98.0 97.9 97.6 97.3 97.4 94.7 94.5 95.5 94.6 97.0 97.0 1991 96.8 97.1 96.1 96.2 96.9 97.2 93.7 93.9 93.6 92.3 94.7 96.3 1992 96.7 96.7 95.9 95.7 95.1 96.0 94.2 93.3 93.6 91.2 93.7 96.2 1993 96.6 96.4 96.5 95.8 95.2 95.5 93.0 93.1 95.2 90.6 94.1 95.9 1994 95.9 96.1 95.7 94.9 95.3 94.3 91.2 91.7 93.1 91.5 93.2 95.5 1995 95.9 96.0 95.1 94.3 95.1 95.5

  8. Percent of Commercial Natural Gas Deliveries in Georgia Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 96.6 93.6 89.7 88.2 85.3 81.7 80.7 80.2 83.0 86.4 89.4 96.8 1990 96.5 90.3 88.7 86.9 82.0 80.9 80.1 82.5 78.9 84.3 87.9 94.1 1991 92.1 90.7 88.8 84.7 81.6 79.7 79.6 80.3 78.8 82.8 90.7 92.5 1992 90.8 90.6 89.3 88.2 85.0 82.7 79.7 83.3 83.4 84.6 87.9 92.9 1993 91.5 92.9 94.6 90.9 86.5 83.0 85.4 84.9 85.6 86.0 91.2 93.0 1994 97.0 94.9 92.4 90.3 89.3 86.8 87.9 89.0 86.1 88.6 91.6 92.6 1995 96.1 97.1 93.3 90.7 89.7 88.4

  9. Percent of Commercial Natural Gas Deliveries in Idaho Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 88.9 90.2 90.6 89.0 82.8 85.9 86.8 83.0 84.1 79.3 84.6 87.4 1990 91.5 90.4 89.7 87.7 85.8 88.1 86.1 85.2 85.0 79.3 86.3 86.4 1991 91.0 91.7 88.5 87.4 87.4 86.8 84.7 84.0 82.9 73.6 85.1 87.5 1992 89.4 89.0 87.1 85.2 83.1 80.2 81.0 82.4 80.2 77.9 82.2 88.3 1993 89.4 89.9 91.0 87.9 87.4 82.3 82.8 81.3 79.2 77.7 81.5 87.8 1994 87.8 88.6 88.1 85.9 83.2 82.7 84.2 80.1 80.6 79.4 84.1 87.6 1995 89.7 89.1 86.5 85.5 86.0 85.3

  10. Percent of Commercial Natural Gas Deliveries in Illinois Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 71.8 73.5 69.8 69.6 67.5 59.7 50.2 47.4 62.4 64.5 68.9 74.5 1990 65.6 65.7 60.2 55.3 52.9 40.6 40.7 41.8 44.5 54.6 52.2 63.6 1991 66.1 62.7 61.0 56.7 49.1 45.4 39.4 43.5 55.0 54.8 60.4 60.3 1992 63.0 58.2 59.5 57.5 53.0 43.4 44.4 49.2 47.0 55.5 60.5 59.9 1993 61.0 58.4 58.3 56.3 51.5 43.4 42.9 38.3 50.0 50.2 53.7 56.0 1994 59.1 59.9 58.0 49.9 46.5 37.8 36.1 36.3 39.7 47.5 49.9 52.0 1995 54.8 53.2 52.9 49.3 40.2 42.9

  11. Percent of Commercial Natural Gas Deliveries in Indiana Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 94.1 93.9 94.3 92.6 92.6 97.2 96.7 96.8 89.1 91.9 97.7 98.9 1990 99.2 98.5 93.4 90.1 92.1 90.6 92.2 89.7 88.4 91.8 98.4 98.6 1991 94.2 93.3 93.2 93.2 92.6 89.2 89.9 89.6 92.6 98.5 97.9 95.4 1992 93.6 92.4 98.6 99.1 99.7 99.9 92.8 99.6 91.9 99.8 99.9 98.0 1993 94.5 94.1 99.6 99.5 100.0 91.9 90.4 91.1 92.9 90.7 92.2 96.1 1994 94.1 97.5 93.7 91.5 88.4 85.6 84.6 85.9 84.3 86.7 91.3 91.4 1995 89.7 89.9 89.5 87.0 83.4 76.1

  12. Percent of Commercial Natural Gas Deliveries in Iowa Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 98.4 98.4 98.5 98.0 97.0 96.3 95.4 95.0 95.2 96.6 97.6 98.3 1990 98.5 98.2 98.1 97.8 97.3 96.3 95.3 95.6 92.3 95.5 97.5 97.7 1991 98.4 98.4 98.2 97.3 96.7 95.7 94.9 91.5 96.0 96.3 98.5 98.0 1992 97.6 97.4 96.5 96.2 94.3 93.2 91.3 90.6 88.7 91.0 96.1 96.7 1993 96.6 96.6 95.8 96.4 92.9 90.8 90.2 88.3 88.9 92.8 95.2 93.2 1994 92.9 94.3 91.2 90.5 87.9 84.1 81.3 80.0 80.5 86.0 90.4 91.0 1995 91.7 92.0 91.1 88.8 86.1 81.9

  13. Percent of Commercial Natural Gas Deliveries in Kansas Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 94.8 94.4 94.1 94.6 92.9 89.2 93.7 94.7 91.8 88.9 88.2 92.9 1990 92.7 90.8 90.6 92.6 91.6 93.1 94.3 94.0 93.3 87.0 88.0 89.4 1991 92.5 91.6 87.9 91.2 88.5 87.1 91.3 89.7 86.9 82.0 87.7 85.3 1992 82.9 83.8 83.9 86.8 88.8 86.8 88.4 88.9 86.9 81.1 78.0 82.7 1993 84.3 83.1 86.1 84.4 85.3 83.0 84.4 86.3 81.3 72.2 75.5 79.9 1994 82.2 85.6 82.3 75.3 69.9 70.4 70.9 71.5 71.9 77.1 83.9 79.5 1995 87.8 73.6 83.2 69.5 62.9 64.8

  14. Percent of Commercial Natural Gas Deliveries in Kentucky Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 97.1 96.6 96.4 94.9 91.0 89.2 89.5 88.2 89.8 90.7 94.4 97.0 1990 97.2 96.9 96.3 94.8 91.6 91.6 89.5 89.5 89.1 93.3 95.0 96.2 1991 97.1 95.7 94.7 89.8 86.4 85.5 87.5 88.0 91.1 91.5 95.7 95.5 1992 95.4 94.2 93.6 91.9 87.9 86.9 86.7 87.4 87.9 93.0 94.6 94.9 1993 91.6 91.6 95.3 93.5 92.4 93.5 89.9 81.6 88.1 88.5 94.5 95.4 1994 93.6 95.9 94.6 92.1 88.2 85.4 83.0 83.5 83.4 87.6 87.9 89.9 1995 90.8 91.2 89.9 86.3 87.4 80.6

  15. Percent of Commercial Natural Gas Deliveries in Maryland Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 97.1 96.6 97.1 96.7 95.9 95.1 94.3 94.7 94.1 94.2 94.6 96.8 1990 97.6 97.1 96.0 95.7 94.3 94.5 93.6 93.1 92.6 93.3 94.7 95.6 1991 97.3 97.5 97.1 96.6 95.9 94.8 94.5 94.7 94.1 95.8 96.5 97.4 1992 97.2 97.2 96.3 95.6 94.1 92.8 93.1 92.7 94.1 95.0 97.0 97.4 1993 97.3 97.4 96.5 96.3 94.6 96.2 95.0 93.4 93.4 95.4 97.1 98.1 1994 98.1 98.3 98.2 95.8 95.8 95.4 95.2 94.1 95.2 96.2 96.5 97.8 1995 97.9 98.5 97.8 96.7 95.9 96.2

  16. Percent of Commercial Natural Gas Deliveries in Michigan Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 75.8 74.5 76.0 71.7 64.9 47.6 51.7 50.8 57.5 64.4 69.5 73.5 1990 73.1 74.0 74.5 72.3 67.4 58.1 49.6 51.5 52.2 62.1 70.1 74.6 1991 73.0 72.2 72.4 67.3 62.1 51.2 44.3 41.2 47.5 60.1 87.2 70.0 1992 73.7 74.5 71.4 70.5 66.6 55.5 48.5 51.6 49.9 61.1 68.6 73.1 1993 74.5 72.3 72.6 68.0 63.7 51.6 50.5 54.4 50.9 63.1 68.1 73.1 1994 73.7 71.6 70.8 66.3 60.1 45.7 41.7 42.3 45.4 55.4 63.4 69.8 1995 72.5 72.2 71.2 68.0 61.5 45.8

  17. Percent of Commercial Natural Gas Deliveries in Missouri Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 94.4 93.9 94.4 93.2 90.7 85.8 86.1 90.5 86.9 88.8 90.3 92.3 1990 93.7 90.7 89.2 88.2 82.5 77.4 70.9 70.8 72.6 74.8 83.8 85.9 1991 90.8 91.1 89.1 82.1 79.0 75.4 71.1 72.2 75.1 75.6 85.9 88.5 1992 89.7 90.1 89.1 88.1 82.7 80.6 71.9 75.8 74.5 76.1 81.0 87.2 1993 87.5 89.2 89.8 88.1 78.0 74.7 72.2 69.2 74.3 73.4 82.3 85.9 1994 88.8 87.2 87.6 85.1 79.0 75.0 70.2 70.0 68.2 70.2 77.0 82.0 1995 87.0 88.9 87.2 83.3 80.9 75.0

  18. Percent of Commercial Natural Gas Deliveries in Montana Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 98.3 98.9 98.8 98.6 97.4 96.8 96.4 96.3 96.3 97.5 97.9 98.1 1990 97.9 97.8 97.6 98.6 96.9 98.4 96.3 95.8 93.3 96.9 97.6 99.6 1991 98.5 98.1 98.0 97.7 97.8 96.9 95.8 95.8 95.8 96.3 96.5 97.2 1992 97.1 98.0 96.7 96.5 96.6 94.9 95.4 96.8 90.6 92.0 92.8 94.6 1993 95.4 94.0 94.9 93.9 94.9 91.1 91.2 91.2 87.5 88.8 91.5 93.5 1994 92.7 93.0 92.7 91.8 91.9 89.6 88.7 87.8 87.5 89.0 91.2 93.1 1995 93.0 92.5 92.5 91.9 92.0 90.1

  19. Percent of Commercial Natural Gas Deliveries in Nebraska Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 96.8 96.5 97.1 99.8 99.7 99.8 99.9 99.9 99.7 98.8 98.1 98.5 1990 95.6 95.3 94.1 93.2 92.3 89.6 96.9 94.2 93.0 90.2 89.9 93.5 1991 93.6 93.3 91.8 87.9 85.4 88.2 96.4 95.2 85.8 86.1 90.5 91.4 1992 91.7 91.6 89.9 90.9 88.7 81.7 85.6 83.6 80.5 84.5 87.1 90.9 1993 94.1 94.7 94.5 93.4 89.5 88.4 88.1 87.8 82.9 85.2 84.8 92.0 1994 88.2 88.9 85.8 82.3 79.2 72.9 75.9 77.8 65.1 62.2 73.5 80.7 1995 81.4 80.6 79.2 79.8 76.0 71.8

  20. Percent of Commercial Natural Gas Deliveries in Nevada Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 98.0 98.1 96.9 95.0 94.2 94.3 92.7 91.7 91.2 96.2 97.2 98.8 1990 99.1 99.4 97.7 97.0 96.4 96.7 95.7 95.0 95.1 96.8 98.4 99.1 1991 99.4 99.4 94.3 92.2 90.6 87.2 84.0 85.2 79.5 84.3 82.2 89.0 1992 90.6 89.5 88.3 87.2 83.7 84.0 84.8 81.4 82.7 88.9 88.5 95.4 1993 97.0 96.0 94.3 91.0 92.5 90.6 89.7 86.7 89.6 89.7 90.9 93.5 1994 93.8 89.3 86.1 81.3 80.1 79.6 76.4 74.5 76.4 73.9 76.7 81.4 1995 81.5 83.2 77.4 78.9 77.1 76.5

  1. Percent of Commercial Natural Gas Deliveries in New York Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 90.4 90.1 89.3 85.0 85.4 81.3 78.6 78.2 73.6 74.8 82.4 89.7 1990 90.5 92.3 85.6 85.3 78.9 77.8 80.2 80.1 76.5 75.8 80.7 81.5 1991 86.2 85.4 84.4 81.0 75.8 72.8 76.8 75.1 73.1 75.0 79.5 81.1 1992 81.0 78.9 79.5 77.3 72.4 70.9 72.9 69.3 69.3 76.0 82.6 81.5 1993 81.4 81.5 82.3 77.8 71.3 66.2 69.1 72.1 72.8 74.1 77.9 77.2 1994 83.7 83.4 83.3 77.7 73.4 73.2 74.7 73.4 75.1 76.4 78.0 81.9 1995 80.8 82.8 79.3 76.3 71.7 66.5

  2. Percent of Commercial Natural Gas Deliveries in Ohio Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 87.4 88.1 87.1 86.0 81.2 74.4 75.5 75.0 78.9 85.1 87.8 90.3 1990 89.9 89.2 89.9 86.4 82.4 78.5 77.0 75.6 77.7 83.0 87.9 91.4 1991 91.6 90.0 87.2 83.6 78.6 74.7 75.5 73.7 75.6 82.6 87.8 89.8 1992 89.1 88.0 88.4 85.7 78.9 73.9 72.0 73.5 73.1 84.2 85.7 88.5 1993 89.4 87.0 86.9 83.8 76.1 73.9 74.6 69.4 72.6 82.8 84.5 86.3 1994 87.4 86.5 84.9 78.4 75.9 70.5 66.7 67.5 66.5 75.1 78.7 81.5 1995 81.0 80.0 78.6 76.8 67.8 61.4

  3. Percent of Commercial Natural Gas Deliveries in Oklahoma Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 89.7 90.2 91.7 87.9 89.1 86.6 86.7 85.0 86.8 86.5 89.1 91.2 1990 94.8 93.2 92.0 93.2 92.6 90.6 89.1 89.5 88.5 87.8 89.9 90.6 1991 94.6 95.1 92.9 91.4 90.3 88.7 87.1 85.6 86.8 81.2 87.6 90.6 1992 91.6 92.3 87.7 90.9 85.4 84.1 80.2 85.7 84.3 85.3 86.9 88.1 1993 91.8 92.0 91.7 90.9 89.1 83.1 80.5 82.2 83.4 83.1 91.5 91.9 1994 90.7 93.8 93.1 89.6 88.0 81.3 74.6 73.8 76.1 78.1 85.0 91.2 1995 90.7 89.8 89.7 85.3 84.9 79.3

  4. Percent of Commercial Natural Gas Deliveries in Oregon Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 99.1 99.2 98.7 98.3 97.6 97.6 97.0 97.2 97.4 96.7 97.3 98.0 1990 98.2 98.6 98.4 97.4 97.4 97.5 96.6 96.6 96.9 95.6 96.5 98.1 1991 98.7 98.3 97.8 97.7 97.5 98.0 97.3 97.2 97.2 95.9 97.6 98.0 1992 98.6 98.4 97.4 97.7 97.7 97.8 97.9 96.7 97.8 94.6 97.4 98.4 1993 98.6 99.0 98.5 98.0 97.6 97.8 97.6 97.5 97.3 93.6 96.5 98.2 1994 98.5 98.6 98.3 97.4 97.6 97.7 98.1 97.7 97.9 97.0 97.8 98.6 1995 98.5 98.5 98.2 98.2 97.9 97.8

  5. Percent of Commercial Natural Gas Deliveries in Texas Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 87.2 92.4 93.7 92.5 90.6 89.6 93.3 91.2 83.1 87.3 87.9 93.2 1990 91.1 90.1 83.9 90.5 90.3 92.3 90.3 90.7 89.1 87.4 88.0 91.5 1991 92.1 91.3 91.8 92.1 87.7 91.4 91.1 90.4 87.3 80.7 84.8 87.6 1992 86.9 85.6 83.4 83.6 79.5 77.8 77.0 75.9 71.9 72.4 75.3 78.6 1993 85.5 86.7 85.6 85.2 80.1 81.0 82.7 85.1 80.7 81.1 84.2 84.0 1994 82.1 81.6 84.0 83.6 73.8 81.6 88.8 82.6 83.3 75.1 78.9 89.0 1995 72.8 71.3 73.6 70.2 55.0 72.7

  6. Percent of Commercial Natural Gas Deliveries in Virginia Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1989 98.3 98.4 98.1 97.1 96.4 96.4 93.9 94.1 95.4 93.3 96.4 97.9 1990 97.2 95.9 90.6 86.6 94.2 93.9 94.1 91.9 92.0 92.9 92.5 93.7 1991 95.9 96.9 95.2 93.6 91.8 90.8 91.3 89.5 90.2 92.6 90.9 93.5 1992 94.6 93.3 93.7 91.7 88.9 88.4 86.9 85.9 83.8 89.9 86.6 90.3 1993 90.2 91.8 89.8 87.6 90.1 87.6 85.4 77.2 85.9 79.8 88.8 93.2 1994 95.2 97.2 92.5 82.7 85.1 76.7 82.4 72.9 72.9 76.1 79.4 86.1 1995 90.8 90.0 88.7 77.6 76.2 74.7

  7. Percent of Industrial Natural Gas Deliveries in Alabama Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 26.4 25.4 21.7 22.1 19.5 21.1 21.0 21.8 21.4 20.8 22.1 21.9 2002 24.1 22.3 22.5 20.1 18.3 19.6 20.7 21.4 20.0 21.4 24.2 23.5 2003 22.3 22.2 23.9 21.3 20.5 20.8 21.8 18.1 19.7 19.6 21.6 22.3 2004 22.6 23.2 21.9 19.9 20.2 20.8 19.1 19.9 19.1 19.7 20.2 21.8 2005 22.9 23.8 21.3 23.1 23.1 22.6 24.8 22.8 26.3 23.5 23.2 26.2 2006 22.8 23.1 22.4 24.1 23.9 22.2 22.5 23.0 23.4 24.5 24.6 25.6 2007 24.1 24.8 24.4 23.9 24.8 23.9

  8. Percent of Industrial Natural Gas Deliveries in Georgia Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 28.1 24.7 21.2 18.5 19.8 19.2 17.1 18.0 16.4 17.5 19.5 19.7 2002 20.2 20.6 21.4 19.5 18.0 19.2 17.7 17.9 18.5 18.2 19.4 19.5 2003 16.7 19.1 17.2 16.0 16.8 14.4 12.6 13.4 14.2 15.3 16.5 18.0 2004 18.2 17.2 17.4 15.5 14.9 15.8 15.9 15.1 15.6 13.9 14.0 22.4 2005 19.9 18.4 15.9 17.9 13.7 14.6 12.9 15.6 19.7 18.7 19.4 18.3 2006 18.3 25.0 17.2 12.5 12.7 16.7 15.2 16.2 15.7 18.0 17.8 17.0 2007 17.2 19.3 17.9 18.7 16.7 16.6

  9. Percent of Industrial Natural Gas Deliveries in Idaho Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 3.3 3.2 2.5 2.2 1.9 1.6 1.5 1.8 1.6 1.5 1.8 2.3 2002 2.7 2.9 2.7 2.5 0.9 1.9 1.8 2.0 1.4 1.6 1.3 2.3 2003 2.2 2.5 2.1 1.8 1.7 1.6 2.0 2.2 1.8 2.0 2.4 3.1 2004 3.2 2.9 2.8 2.0 2.1 2.0 1.9 1.9 1.6 1.5 2.5 3.2 2005 3.0 2.7 2.7 2.4 1.8 1.7 1.6 1.6 2.0 1.7 2.4 3.0 2006 2.5 2.6 2.3 2.0 1.8 1.5 1.6 1.6 1.5 2.0 2.3 2.6 2007 2.3 2.1 1.7 1.8 1.7 1.9 1.7 1.5 1.7 2.0 2.2 2.4 2008 2.2 2.3 2.4 1.8 1.4 1.7 1.6 1.9 1.4 1.8 2.3 2.1

  10. Percent of Industrial Natural Gas Deliveries in Illinois Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 14.3 14.6 11.7 8.9 7.1 6.7 5.8 6.1 7.5 8.7 10.3 12.1 2002 11.2 11.2 11.1 10.3 7.6 7.2 3.9 5.4 6.6 9.4 10.7 12.6 2003 13.4 13.4 12.9 9.2 7.9 6.9 5.7 7.6 5.3 9.1 10.5 10.6 2004 13.5 12.0 9.7 8.1 5.8 6.1 6.4 5.7 5.0 8.3 10.4 11.5 2005 12.9 11.8 10.7 8.2 6.0 4.7 6.3 6.0 6.8 10.6 11.6 12.5 2006 12.3 11.9 11.1 8.8 7.4 4.9 5.3 6.4 6.6 8.5 7.7 9.6 2007 11.5 12.7 12.8 10.6 10.3 7.8 6.0 5.4 6.4 7.5 7.7 10.4 2008 11.7 12.9 12.9

  11. Percent of Industrial Natural Gas Deliveries in Indiana Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 15.1 14.0 7.1 7.1 4.2 3.7 5.2 1.0 5.5 8.3 6.6 10.2 2002 8.4 8.1 10.1 6.4 5.3 6.2 5.3 5.9 6.6 12.5 12.6 12.4 2003 14.2 12.9 8.9 7.2 7.0 5.9 6.2 5.7 9.3 6.2 11.3 9.3 2004 9.2 8.9 8.9 6.9 6.4 6.2 6.9 6.5 7.3 7.9 10.4 11.6 2005 9.8 7.7 9.6 5.8 6.3 5.5 5.5 6.7 8.2 8.2 10.6 8.9 2006 8.2 9.3 7.4 4.3 7.0 5.0 6.4 5.9 6.3 8.2 8.3 8.4 2007 9.3 9.4 5.8 7.6 6.1 5.5 6.0 5.0 6.9 6.8 9.5 9.1 2008 8.4 7.5 7.0 6.7 5.5 4.5 4.7 4.7 5.3

  12. Percent of Industrial Natural Gas Deliveries in Kentucky Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 27.3 21.8 18.9 13.8 17.8 15.8 17.4 17.4 17.3 19.6 16.5 16.9 2002 16.8 18.2 18.9 17.2 15.5 16.5 18.0 19.1 16.3 18.0 18.8 18.4 2003 20.6 20.1 18.7 19.5 19.2 20.3 16.6 16.0 18.1 18.2 18.1 18.4 2004 18.8 18.3 16.3 16.0 14.6 16.6 16.2 15.2 15.5 15.6 17.5 20.3 2005 16.5 17.5 17.3 16.0 15.8 15.2 16.1 14.9 17.4 17.9 17.2 19.7 2006 15.6 16.9 17.6 14.8 14.9 14.2 16.0 15.7 14.6 15.7 15.5 17.6 2007 16.6 18.1 17.0 17.7 16.1 17.5

  13. Percent of Industrial Natural Gas Deliveries in Maryland Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 15.4 11.4 9.7 7.2 6.7 4.5 9.7 6.3 6.3 7.0 6.6 10.3 2002 10.3 11.3 13.0 5.3 5.8 6.0 4.5 5.8 4.3 6.9 7.1 11.9 2003 10.5 13.2 11.4 9.1 7.8 6.6 6.3 6.2 7.1 12.1 11.9 12.9 2004 11.2 10.7 8.8 9.1 6.4 4.7 5.0 5.6 7.2 7.2 9.4 10.9 2005 11.3 11.5 11.3 9.8 5.5 5.1 4.9 5.3 5.2 6.2 9.4 10.7 2006 8.7 10.4 8.9 6.1 4.5 4.4 3.7 3.9 6.5 5.8 7.7 9.2 2007 13.1 13.7 11.0 9.9 6.1 3.7 4.5 3.8 6.9 3.5 8.4 10.4 2008 9.5 10.4 7.5 6.6 4.7 3.1

  14. Percent of Industrial Natural Gas Deliveries in Michigan Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 18.6 17.2 15.3 13.3 9.0 5.7 5.4 5.8 6.0 7.3 9.9 12.0 2002 14.4 13.3 14.0 11.4 8.1 5.7 4.3 5.2 3.9 6.5 10.9 17.6 2003 15.4 14.6 15.1 11.9 8.7 5.9 6.1 3.8 6.7 6.9 9.6 14.4 2004 14.6 15.9 18.0 11.4 7.4 5.7 5.0 4.9 5.0 6.1 9.2 13.3 2005 14.3 17.0 15.8 10.7 8.1 5.3 4.0 3.8 4.6 7.2 9.8 13.8 2006 15.4 16.4 13.5 10.8 7.3 5.1 3.8 4.5 5.2 7.0 10.6 13.6 2007 14.8 17.3 16.9 13.5 11.5 8.4 6.3 6.0 6.2 7.4 11.4 16.6 2008 16.4 17.4

  15. Percent of Industrial Natural Gas Deliveries in Missouri Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 25.6 17.3 19.1 14.4 11.1 10.2 9.5 8.1 9.5 10.2 12.4 32.9 2002 21.7 26.8 26.8 15.8 10.2 9.8 9.3 9.8 10.9 9.0 14.0 18.7 2003 18.8 21.0 19.0 13.6 12.1 12.4 12.5 8.8 10.3 11.1 13.1 16.8 2004 17.4 20.0 16.1 14.7 11.4 10.1 9.6 9.7 10.5 11.0 12.6 15.4 2005 20.1 18.4 16.4 13.9 11.9 9.6 10.1 9.4 10.5 11.2 13.0 17.9 2006 17.2 17.0 14.8 13.7 10.5 10.2 9.9 9.6 10.2 10.8 13.2 16.7 2007 15.4 18.5 16.7 12.3 10.6 10.1 9.7 8.4 8.7 10.3

  16. Percent of Industrial Natural Gas Deliveries in Montana Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 3.0 3.1 2.8 2.6 2.3 1.9 0.9 0.8 1.0 1.2 1.9 3.0 2002 3.0 2.9 3.6 2.3 2.0 1.2 0.9 0.7 0.8 1.1 2.1 3.4 2003 2.9 2.8 3.3 2.1 1.8 1.0 1.0 0.8 0.8 0.6 1.2 1.6 2004 1.8 2.4 1.9 1.0 1.5 1.4 1.1 0.7 0.8 1.1 1.8 2.4 2005 3.1 2.9 2.2 2.3 1.8 1.4 0.9 0.6 0.7 1.0 1.3 2.3 2006 1.3 1.0 1.1 0.9 0.6 0.4 0.2 0.1 0.2 0.3 0.6 1.0 2007 1.0 1.2 0.9 0.9 0.5 0.4 0.3 0.3 0.4 0.5 0.7 1.0 2008 1.3 1.4 1.8 1.1 0.9 0.5 0.6 0.5 0.5 0.4 0.8 0.9

  17. Percent of Industrial Natural Gas Deliveries in Nebraska Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 25.7 29.6 30.3 21.0 19.7 16.7 8.3 12.9 13.3 18.6 12.0 18.7 2002 22.6 19.5 29.3 17.6 15.0 24.0 7.4 8.4 8.8 16.4 18.9 19.6 2003 20.3 22.7 24.9 19.3 17.1 24.1 8.7 9.7 10.9 15.7 17.7 19.4 2004 19.7 21.4 24.7 19.0 18.3 14.2 9.2 10.6 16.5 18.8 16.0 16.6 2005 24.4 20.0 24.6 18.5 19.0 18.2 10.0 8.6 12.9 15.1 14.2 18.3 2006 13.8 15.1 17.1 13.3 13.0 9.8 8.3 7.7 10.5 11.5 10.2 12.4 2007 12.1 13.0 14.5 11.6 9.7 8.9 7.1 6.4 6.9 9.8

  18. Percent of Industrial Natural Gas Deliveries in North Dakota Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 15.2 13.8 16.8 8.2 5.8 5.5 1.1 4.7 8.0 12.1 13.4 17.9 2002 9.8 10.6 12.6 10.1 7.4 4.8 5.1 5.2 6.7 11.6 14.4 13.2 2003 35.1 44.0 60.0 30.9 17.9 17.7 25.0 32.3 22.3 25.2 44.1 87.2 2004 54.7 46.4 57.3 56.1 36.3 16.0 13.5 58.7 63.2 58.6 55.3 53.4 2005 25.1 17.0 17.7 14.7 9.6 4.4 10.3 15.1 51.6 58.4 45.9 23.2 2006 26.1 18.4 28.8 53.1 58.6 61.2 13.1 13.9 43.4 56.3 52.6 19.1 2007 26.6 28.8 24.7 58.5 61.4 46.9 11.0 38.6

  19. Percent of Industrial Natural Gas Deliveries in Ohio Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 13.1 9.8 10.4 6.2 3.9 3.4 1.5 4.8 1.2 2.9 5.6 6.4 2002 5.4 6.2 5.4 4.8 1.9 1.7 1.6 2.1 2.5 2.3 4.9 6.7 2003 6.3 7.0 5.4 4.0 1.8 2.4 2.0 1.7 1.7 2.4 3.3 4.6 2004 5.1 5.7 4.0 3.8 2.1 2.3 1.7 2.3 2.2 2.7 3.4 4.5 2005 5.7 6.6 4.5 2.6 2.0 1.6 2.1 2.0 1.9 2.6 3.3 4.8 2006 4.6 4.7 4.0 2.7 2.1 2.2 2.2 2.1 2.2 2.2 3.0 3.5 2007 3.9 4.8 3.5 2.6 1.8 1.8 1.9 1.4 1.5 1.2 2.2 3.7 2008 3.9 4.2 3.5 2.5 1.1 1.7 1.9 1.4 1.4 1.6 2.7 4.1

  20. Percent of Industrial Natural Gas Deliveries in Oregon Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 27.2 17.0 18.7 20.3 20.5 20.7 23.5 26.8 24.2 21.1 20.6 21.4 2002 18.9 20.8 20.3 19.3 12.6 11.1 10.1 8.9 10.8 11.5 12.6 12.8 2003 13.8 14.3 13.8 12.7 16.1 16.2 15.5 15.6 19.2 21.1 24.5 25.4 2004 25.1 24.3 24.2 23.3 21.8 22.9 22.6 22.1 23.8 23.5 31.1 33.4 2005 34.3 34.3 32.7 31.0 30.2 30.1 31.4 32.1 33.6 35.0 34.8 38.2 2006 36.0 36.3 35.1 26.5 25.4 24.3 23.2 21.2 21.6 20.5 21.5 24.0 2007 23.6 24.3 22.9 21.8 20.8 21.8

  1. Percent of Industrial Natural Gas Deliveries in Rhode Island Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 41.4 29.5 26.1 37.6 29.0 29.3 26.0 26.2 22.4 26.8 29.3 13.6 2002 27.3 27.3 27.3 27.3 27.3 27.3 27.3 27.3 27.3 27.3 27.3 27.3 2003 15.7 18.9 21.5 19.6 26.7 11.7 16.8 18.8 18.6 22.1 18.5 22.3 2004 13.9 16.7 14.5 16.8 21.1 11.7 16.7 15.3 16.0 19.4 10.5 23.0 2005 17.8 14.7 15.9 11.0 16.3 16.5 12.9 13.8 16.3 13.2 16.5 19.7 2006 18.6 18.7 16.4 15.0 12.5 13.3 8.8 10.5 11.4 12.8 10.5 15.7 2007 13.0 19.0 15.1 12.7 10.1 14.3

  2. Percent of Industrial Natural Gas Deliveries in South Dakota Represented by

    U.S. Energy Information Administration (EIA) (indexed site)

    the Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 51.1 54.8 52.4 50.8 35.1 32.7 28.6 26.5 24.1 33.3 45.5 44.5 2002 16.4 18.6 13.2 18.4 14.1 10.7 9.5 9.0 19.5 27.6 30.6 34.9 2003 26.3 24.4 27.3 26.0 23.9 22.4 24.7 23.3 25.3 24.8 26.8 29.1 2004 29.0 28.5 30.0 24.4 26.1 28.2 22.6 27.6 24.8 27.2 33.3 31.0 2005 28.5 28.0 33.6 26.7 31.6 26.1 28.9 31.7 27.8 30.4 33.3 35.8 2006 38.6 36.4 37.5 31.3 39.2 30.3 27.6 30.1 27.8 31.5 33.7 35.4 2007 33.8 31.8 31.3 15.2 16.2 12.1

  3. Percent of Industrial Natural Gas Deliveries in Texas Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 35.8 35.7 33.7 34.2 32.9 34.2 36.5 34.8 37.5 36.0 35.1 34.5 2002 30.8 32.1 30.6 50.7 45.4 50.5 49.5 46.5 46.3 43.4 43.8 44.8 2003 40.1 39.5 39.1 39.5 39.8 36.1 50.7 46.2 49.0 47.8 47.2 48.2 2004 48.4 49.3 46.7 49.4 49.0 51.9 51.3 49.9 47.4 46.0 46.6 48.9 2005 58.7 57.0 56.9 55.8 55.8 54.9 56.8 55.0 52.5 49.7 51.1 49.5 2006 52.1 52.1 54.8 55.6 55.3 54.7 58.1 57.4 54.1 57.9 56.5 55.6 2007 52.7 51.6 52.4 53.0 54.2 56.0

  4. Percent of Industrial Natural Gas Deliveries in Utah Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 11.9 9.2 10.7 10.1 9.5 9.5 10.1 11.5 9.4 9.2 11.0 13.8 2002 14.0 13.8 12.6 15.8 13.0 13.4 12.1 13.6 13.5 12.8 15.0 13.7 2003 14.5 14.6 13.1 14.9 14.1 13.2 11.8 12.7 13.8 13.9 13.2 13.1 2004 13.8 15.2 13.3 14.6 12.7 12.7 18.4 46.5 26.9 24.3 23.4 23.8 2005 18.4 18.6 18.4 17.7 18.6 21.3 20.0 21.2 21.3 21.5 18.3 19.9 2006 22.3 23.2 22.5 24.0 24.0 24.7 24.2 13.9 13.4 15.3 15.8 16.0 2007 14.4 13.6 14.4 14.6 13.3 12.7 14.5

  5. Percent of Industrial Natural Gas Deliveries in Vermont Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 95.2 80.1 79.2 79.2 69.2 67.8 65.6 67.7 70.7 73.3 76.0 79.0 2002 77.7 78.3 78.6 78.2 72.6 66.8 66.7 65.1 66.8 72.6 76.2 85.5 2003 87.3 100.0 100.0 75.7 74.2 72.4 75.0 67.7 70.4 73.2 77.4 80.1 2004 79.9 84.7 80.7 82.2 78.6 73.8 70.0 68.3 69.2 76.4 82.1 83.7 2005 83.6 86.4 82.6 78.0 74.4 71.5 72.1 83.9 94.3 82.4 75.7 96.4 2006 93.0 87.6 82.4 77.2 73.3 72.9 71.7 69.7 71.5 76.3 75.1 79.5 2007 83.0 84.1 81.8 76.2 72.2 71.7

  6. Percent of Industrial Natural Gas Deliveries in Virginia Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 27.4 24.1 20.8 18.6 13.3 23.5 10.9 12.9 15.0 24.1 11.2 15.4 2002 16.8 19.7 18.3 14.0 14.1 10.8 10.7 11.0 13.2 16.0 19.3 22.9 2003 25.6 22.5 16.5 23.9 12.9 9.1 13.4 19.6 12.6 17.7 17.9 17.0 2004 21.5 18.8 18.7 16.8 14.9 11.2 15.6 14.5 8.9 15.1 16.1 21.1 2005 18.3 21.6 18.1 19.3 15.7 16.6 9.5 11.6 16.0 18.7 21.5 20.0 2006 21.6 17.0 16.0 13.2 13.8 10.4 9.5 8.0 12.7 14.5 16.0 15.7 2007 17.0 20.0 17.1 17.2 15.4 9.5 10.3

  7. Percent of Industrial Natural Gas Deliveries in Wyoming Represented by the

    U.S. Energy Information Administration (EIA) (indexed site)

    Price (Percent) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 3.6 3.9 3.7 2.8 1.9 2.1 1.8 2.0 2.0 2.3 2.2 1.8 2002 3.3 3.6 3.6 3.0 3.6 2.4 2.6 2.8 2.8 3.2 2.1 2.5 2003 2.4 2.4 2.1 1.8 1.4 1.4 1.4 1.3 1.4 1.4 2.2 2.0 2004 2.0 1.9 2.2 1.9 1.9 1.9 2.7 1.7 2.3 2.0 2.3 2.4 2005 2.8 5.0 5.8 4.5 4.1 3.5 2.8 2.5 2.5 2.8 4.2 4.4 2006 4.4 4.5 4.2 3.9 3.3 2.7 2.2 2.3 2.8 3.3 3.8 3.7 2007 4.3 4.1 3.4 3.7 2.8 2.0 1.5 1.7 1.9 2.9 3.3 3.3 2008 3.8 3.7 3.9 3.9 2.9 2.1 2.0 1.7 2.5 3.0 3.6 3.9

  8. 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

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

    Annual Energy Outlook

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

  10. ARM - Measurement - Hydrometeor size

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    size 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 : Hydrometeor size The size of a hydrometeor, measured directly or derived from other measurements. Categories Cloud Properties 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 those

  11. 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).

  12. A material flow analysis on current electrical and electronic waste disposal from Hong Kong households

    SciTech Connect (OSTI)

    Lau, Winifred Ka-Yan; Chung, Shan-Shan; Zhang, Chan

    2013-03-15

    Highlights: ► Most household TWARC waste is sold directly to private e-waste collectors in HK. ► The current e-waste recycling network is popular with HK households. ► About 80% of household generated TWARC is exported overseas each year. ► Over 7000 tonnes/yr of household generated TWARC reach landfills. ► It is necessary to upgrade safety and awareness in HK’s e-waste recycling industry. - Abstract: A material flow study on five types of household electrical and electronic equipment, namely television, washing machine, air conditioner, refrigerator and personal computer (TWARC) was conducted to assist the Government of Hong Kong to establish an e-waste take-back system. This study is the first systematic attempt on identifying key TWARC waste disposal outlets and trade practices of key parties involved in Hong Kong. Results from two questionnaire surveys, on local households and private e-waste traders, were used to establish the material flow of household TWARC waste. The study revealed that the majority of obsolete TWARC were sold by households to private e-waste collectors and that the current e-waste collection network is efficient and popular with local households. However, about 65,000 tonnes/yr or 80% of household generated TWARC waste are being exported overseas by private e-waste traders, with some believed to be imported into developing countries where crude recycling methods are practiced. Should Hong Kong establish a formal recycling network with tight regulatory control on imports and exports, the potential risks of current e-waste recycling practices on e-waste recycling workers, local residents and the environment can be greatly reduced.

  13. Does size matter?

    SciTech Connect (OSTI)

    Carreras, B. A.; Physics Department, College of Natural Science and Mathematics and Geophysical Institute, University of Alaska, Fairbanks, Alaska 99775; Physics Department, Universidad Carlos III de Madrid, Madrid ; Newman, D. E.; Dobson, Ian

    2014-06-15

    Failures of the complex infrastructures society depends on having enormous human and economic cost that poses the question: Are there ways to optimize these systems to reduce the risks of failure? A dynamic model of one such system, the power transmission grid, is used to investigate the risk from failure as a function of the system size. It is found that there appears to be optimal sizes for such networks where the risk of failure is balanced by the benefit given by the size.

  14. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  15. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  16. Household heating bills expected to be higher than last winter, mainly driven by colder weather

    U.S. Energy Information Administration (EIA) (indexed site)

    Household heating bills expected to be higher than last winter, mainly driven by colder weather U.S. households are expected to pay higher heating bills this winter compared to last winter mainly because the weather is forecast to be colder than the relatively mild weather seen last winter and fuel prices are forecast to be higher. In its new forecast, the U.S. Energy Information Administration said households using heating oil will see a 38% jump in their heating fuel expenditures while propane

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

  18. 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

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

    Energy.gov [DOE]

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

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

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

    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.

  2. 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 ...

  3. Residential Network Members Impact More Than 42,000 Households | Department

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    of Energy Impact More Than 42,000 Households Residential Network Members Impact More Than 42,000 Households Photo of a row of townhomes. Eligible Better Buildings Residential Network members reported completing 27,563 home energy upgrades during 2013 as part of the Residential Network's first reporting cycle. In addition, 13 Better Buildings Neighborhood Program partners completed 12,166 home energy upgrades, and six Home Performance with ENERGY STAR® Sponsors completed 2,540 home energy

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    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

  5. A Mixed Nordic Experience: Implementing Competitive Retail Electricity Markets for Household Customers

    SciTech Connect (OSTI)

    Olsen, Ole Jess; Johnsen, Tor Arnt; Lewis, Philip

    2006-11-15

    Although the Nordic countries were among the first to develop competition in the electricity industry, it took a long time to make retail competition work. In Norway and Sweden a considerable number of households are actively using the market but very few households are active in Finland and Denmark. One problem has been institutional barriers involving metering, limited unbundling of distribution and supply, and limited access to reliable information on contracts and prices. (author)

  6. Aerosol mobility size spectrometer

    DOE Patents [OSTI]

    Wang, Jian; Kulkarni, Pramod

    2007-11-20

    A device for measuring aerosol size distribution within a sample containing aerosol particles. The device generally includes a spectrometer housing defining an interior chamber and a camera for recording aerosol size streams exiting the chamber. The housing includes an inlet for introducing a flow medium into the chamber in a flow direction, an aerosol injection port adjacent the inlet for introducing a charged aerosol sample into the chamber, a separation section for applying an electric field to the aerosol sample across the flow direction and an outlet opposite the inlet. In the separation section, the aerosol sample becomes entrained in the flow medium and the aerosol particles within the aerosol sample are separated by size into a plurality of aerosol flow streams under the influence of the electric field. The camera is disposed adjacent the housing outlet for optically detecting a relative position of at least one aerosol flow stream exiting the outlet and for optically detecting the number of aerosol particles within the at least one aerosol flow stream.

  7. Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics

    SciTech Connect (OSTI)

    Brian C. O'Neill

    2006-08-09

    This report describes results of the research project on "Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics". The overall objective of this project was to improve projections of energy demand and associated greenhouse gas emissions by taking into account demographic factors currently not incorporated in Integrated Assessment Models (IAMs) of global climate change. We proposed to examine the potential magnitude of effects on energy demand of changes in the composition of populations by household characteristics for three countries: the U.S., China, and Indonesia. For each country, we planned to analyze household energy use survey data to estimate relationships between household characteristics and energy use; develop a new set of detailed household projections for each country; and combine these analyses to produce new projections of energy demand illustrating the potential importance of consideration of households.

  8. Impact of aerosol size representation on modeling aerosol-cloud interactions: AEROSOL SIZE REPRESENTATION

    DOE PAGES-Beta [OSTI]

    Zhang, Y.; Easter, R. C.; Ghan, S. J.; Abdul-Razzak, H.

    2002-11-07

    We use a 1-D version of a climate-aerosol-chemistry model with both modal and sectional aerosol size representations to evaluate the impact of aerosol size representation on modeling aerosol-cloud interactions in shallow stratiform clouds observed during the 2nd Aerosol Characterization Experiment. Both the modal (with prognostic aerosol number and mass or prognostic aerosol number, surface area and mass, referred to as the Modal-NM and Modal-NSM) and the sectional approaches (with 12 and 36 sections) predict total number and mass for interstitial and activated particles that are generally within several percent of references from a high resolution 108-section approach. The modal approachmore » with prognostic aerosol mass but diagnostic number (referred to as the Modal-M) cannot accurately predict the total particle number and surface areas, with deviations from the references ranging from 7-161%. The particle size distributions are sensitive to size representations, with normalized absolute differences of up to 12% and 37% for the 36- and 12-section approaches, and 30%, 39%, and 179% for the Modal-NSM, Modal-NM, and Modal-M, respectively. For the Modal-NSM and Modal-NM, differences from the references are primarily due to the inherent assumptions and limitations of the modal approach. In particular, they cannot resolve the abrupt size transition between the interstitial and activated aerosol fractions. For the 12- and 36-section approaches, differences are largely due to limitations of the parameterized activation for non-log-normal size distributions, plus the coarse resolution for the 12-section case. Differences are larger both with higher aerosol (i.e., less complete activation) and higher SO2 concentrations (i.e., greater modification of the initial aerosol distribution).« less

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. "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"

  15. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

    SciTech Connect (OSTI)

    Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung; Kao, Shih-Chieh; Tuttle, Mark A; Bhaduri, Budhendra L

    2011-01-01

    The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

  16. 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.

  17. 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.

  18. Thermal performance measurements of a 100 percent polyester MLI (multilayer insulation) system for the Superconducting Super Collider

    SciTech Connect (OSTI)

    Boroski, W.N.; Gonczy, J.D.; Niemann, R.C.

    1989-09-01

    Thermal performance measurements of a 100 percent polyester multilayer insulation (MLI) system for the Superconducting Super Collider (SSC) were conducted in a Heat Leak Test Facility (HLTF) under three experimental test arrangements. Each experiment measured the thermal performance of a 32-layer MLI blanket instrumented with twenty foil sensors to measure interstitial layer temperatures. Heat leak values and sensor temperatures were monitored during transient and steady state conditions under both design and degraded insulating vacuums. Heat leak values were measured using a heatmeter. MLI interstitial layer temperatures were measured using Cryogenic Linear Temperature Sensors (CLTS). Platinum resistors monitored system temperatures. High vacuum was measured using ion gauges; degraded vacuum employed thermocouple gauges. A four-wire system monitored instrumentation sensors and calibration heaters. An on-line computerized data acquisition system recorded and processes data. This paper reports on the instrumentation and experimental preparation used in carrying out these measurements. In complement with this paper is an associate paper bearing the same title head, but with the title extension Part 2: Laboratory results (300K--80K). 13 refs., 7 figs.

  19. Guidance for growth factors, projections, and control strategies for the 15 percent rate-of-progress plans

    SciTech Connect (OSTI)

    Not Available

    1993-03-01

    Section 182(b)(1) of the Clean Air Act (Act) requires all ozone nonattainment areas classified as moderate and above to submit a State Implementation Plan (SIP) revision by November 15, 1993, which describes, in part, how the areas will achieve an actual volatile organic compound (VOC) emissions reduction of at least 15 percent during the first 6 years after enactment of the Clean Air Act Amendments of 1990 (CAAA). In addition, the SIP revision must describe how any growth in emissions from 1990 through 1996 will be fully offset. It is important to note that section 182(b)(1) also requires the SIP for moderate areas to provide for reductions in VOC and nitrogen oxides (NOx) emissions as necessary to attain the national primary ambient air quality standard for ozone by November 15, 1996. The guidance document focuses on the procedures for developing 1996 projected emissions inventories and control measures which moderate and above ozone nonattainment areas must include in their rate-of-progress plans. The document provides technical guidance to support the policy presented in the 'General Preamble: Implementation of Title I of the CAAA of 1990' (57 FR 13498).

  20. Mitigating Carbon Emissions: the Potential of Improving Efficiencyof Household Appliances in China

    SciTech Connect (OSTI)

    Lin, Jiang

    2006-07-10

    China is already the second's largest energy consumer in the world after the United States, and its demand for energy is expected to continue to grow rapidly in the foreseeable future, due to its fast economic growth and its low level of energy use per capita. From 2001 to 2005, the growth rate of energy consumption in China has exceeded the growth rate of its economy (NBS, 2006), raising serious concerns about the consequences of such energy use on local environment and global climate. It is widely expected that China is likely to overtake the US in energy consumption and greenhouse gas (GHG) emissions during the first half of the 21st century. Therefore, there is considerable interest in the international community in searching for options that may help China slow down its growth in energy consumption and GHG emissions through improving energy efficiency and adopting more environmentally friendly fuel supplies such as renewable energy. This study examines the energy saving potential of three major residential energy end uses: household refrigeration, air-conditioning, and water heating. China is already the largest consumer market in the world for household appliances, and increasingly the global production base for consumer appliances. Sales of household refrigerators, room air-conditioners, and water heaters are growing rapidly due to rising incomes and booming housing market. At the same time, the energy use of Chinese appliances is relatively inefficient compared to similar products in the developed economies. Therefore, the potential for energy savings through improving appliance efficiency is substantial. This study focuses particularly on the impact of more stringent energy efficiency standards for household appliances, given that such policies are found to be very effective in improving the efficiency of household appliances, and are well established both in China and around world (CLASP, 2006).

  1. Pore size distribution and accessible pore size distribution...

    Office of Scientific and Technical Information (OSTI)

    both rank and type (expressed as either hydrogen or vitrinite content) in the size range ... Subject: 01 COAL, LIGNITE, AND PEAT; 03 NATURAL GAS; 08 HYDROGEN; AMBIENT TEMPERATURE; ...

  2. ARM - Measurement - Aerosol particle size

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    particle size 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 : Aerosol particle size Linear size (e.g. radius or diameter) of an aerosol particle. Categories Aerosols 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 those recorded for

  3. ARM - Measurement - Cloud droplet size

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    droplet size 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 : Cloud droplet size Linear size (e.g. radius or diameter) of a cloud particle Categories Cloud Properties 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 those recorded for

  4. ARM - Measurement - Particle size distribution

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    size distribution 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 : Particle size distribution The number of particles present in any given volume of air within a specified size range. Categories Aerosols 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

  5. ARM - Measurement - Hydrometeor Size Distribution

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    of hydrometeors observed in a given size range. Categories Atmospheric State, Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  6. Glitter-Sized Solar Photovoltaics

    Office of Energy Efficiency and Renewable Energy (EERE)

    Featured in this photograph are tiny glitter-sized photovoltaic cells, developed by Sandia National Laboratories scientists, that could revolutionize the way solar energy is collected and used....

  7. 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.

  8. 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.

  9. Identification of influencing municipal characteristics regarding household waste generation and their forecasting ability in Biscay

    SciTech Connect (OSTI)

    Oribe-Garcia, Iraia Kamara-Esteban, Oihane; Martin, Cristina; Macarulla-Arenaza, Ana M.; Alonso-Vicario, Ainhoa

    2015-05-15

    Highlights: • We have modelled household waste generation in Biscay municipalities. • We have identified relevant characteristics regarding household waste generation. • Factor models are used in order to identify the best subset of explicative variables. • Biscay’s municipalities are grouped by means of hierarchical clustering. - Abstract: The planning of waste management strategies needs tools to support decisions at all stages of the process. Accurate quantification of the waste to be generated is essential for both the daily management (short-term) and proper design of facilities (long-term). Designing without rigorous knowledge may have serious economic and environmental consequences. The present works aims at identifying relevant socio-economic features of municipalities regarding Household Waste (HW) generation by means of factor models. Factor models face two main drawbacks, data collection and identifying relevant explanatory variables within a heterogeneous group. Grouping similar characteristics observations within a group may favour the deduction of more robust models. The methodology followed has been tested with Biscay Province because it stands out for having very different municipalities ranging from very rural to urban ones. Two main models are developed, one for the overall province and a second one after clustering the municipalities. The results prove that relating municipalities with specific characteristics, improves the results in a very heterogeneous situation. The methodology has identified urban morphology, tourism activity, level of education and economic situation as the most influencing characteristics in HW generation.

  10. Method for sizing hollow microspheres

    DOE Patents [OSTI]

    Farnum, E.H.; Fries, R.J.

    1975-10-29

    Hollow Microspheres may be effectively sized by placing them beneath a screen stack completely immersed in an ultrasonic bath containing a liquid having a density at which the microspheres float and ultrasonically agitating the bath.

  11. Effect of particle size reduction on anaerobic sludge digestion

    SciTech Connect (OSTI)

    Koutsospyros, A.D.

    1990-01-01

    The majority of organic pollutants in primary sludge are suspended in the form of particulate rather than soluble matter. Microbial organisms cannot assimilate this material without initial solubilization. In anaerobic digestion, the initial size breakdown is accomplished by hydrolytic bacteria. The extent of solubilization is limited by the size of particulate matter. Thus, size reduction prior to digestion is a sound alternative. Size reduction pretreatment was achieved by means of ultrasonic waves. Sonication proved an effective method for size reduction of particulate matter in primary sludge. In addition, although the method produced relatively high amounts of finely dispered solids, the filtration properties of resulting sludges were not affected. Chemical characteristics of sludge, important in anaerobic digestion, were not affected, at least within the attempted range of sonication time and amplitude. The effect of size reduction of primary sludge solids was studied under batch and semi-continuous feed conditions. Preliminary batch digestion experiments were conducted in five 1.5 liter reactors that accepted sonicated feeds of varying pretreatment at four different feed loads (3.3-13.3% by volume). The digestion efficiency and gas production were increased by as much as 30 percent as a result of sonication without any deterioration in the filtration properties of the digester effluent. At higher feed loads the digester efficiency dropped drastically and significant deterioration of the effluent filtration properties from all reactors was evident. Semi-continuous runs were conducted in four reactors. Solids retention time (SRT) was varied from 8 to 20 days. Process efficiency and gas production were enhanced as a result of sonication. Process improvement was more evident under short SRT (8-10 days).

  12. 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.

  13. Association of pediatric asthma severity with exposure to common household dust allergens

    SciTech Connect (OSTI)

    Gent, Janneane F.; Belanger, Kathleen; Triche, Elizabeth W.; Beckett, William S.; Leaderer, Brian P.

    2009-08-15

    Background: Reducing exposure to household dust inhalant allergens has been proposed as one strategy to reduce asthma. Objective: To examine the dose-response relationships and health impact of five common household dust allergens on disease severity, quantified using both symptom frequency and medication use, in atopic and non-atopic asthmatic children. Methods: Asthmatic children (N=300) aged 4-12 years were followed for 1 year. Household dust samples from two indoor locations were analyzed for allergens including dust mite (Der p 1, Der f 1), cat (Fel d 1), dog (Can f 1), cockroach (Bla g 1). Daily symptoms and medication use were collected in monthly telephone interviews. Annual disease severity was examined in models including allergens, specific IgE sensitivity and adjusted for age, gender, atopy, ethnicity, and mother's education. Results: Der p 1 house dust mite allergen concentration of 2.0 {mu}g/g or more from the main room and the child's bed was related to increased asthma severity independent of allergic status (respectively, OR 2.93, 95% CI 1.37, 6.30 for 2.0-10.0 {mu}g/g and OR 2.55 95% CI 1.13, 5.73 for {>=}10.0 {mu}g/g). Higher pet allergen levels were associated with greater asthma severity, but only for those sensitized (cat OR 2.41 95% CI 1.19, 4.89; dog OR 2.06 95% CI 1.01, 4.22). Conclusion: Higher levels of Der p 1 and pet allergens were associated with asthma severity, but Der p 1 remained an independent risk factor after accounting for pet allergens and regardless of Der p 1 specific IgE status.

  14. 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.

  15. 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

  16. 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.....................................................

  17. 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

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

    U.S. Energy Information Administration (EIA) (indexed site)

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

  19. 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

  20. 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

  1. Table 5.17. U.S. Number of Households by Vehicle Fuel Expenditures...

    U.S. Energy Information Administration (EIA) (indexed site)

    More ... 8.2 Q 1.7 1.9 1.7 2.6 6.1 2.0 Q Q Q 16.7 Below Poverty Line 100 Percent ... 9.0 2.5 3.6 1.3 1.0 0.6 Q...

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

    U.S. Energy Information Administration (EIA) (indexed site)

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

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

    U.S. Energy Information Administration (EIA) (indexed site)

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

  4. Table 5.18. U.S. Average Household and Vehicle Energy Expenditures...

    U.S. Energy Information Administration (EIA) (indexed site)

    ... 8.5 3,447 0.3 1,676 8.2 3,519 1,827 1,692 8.6 Below Poverty Line 100 Percent ... 14.7 1,600 5.7 935 9.0 2,022...

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

    SciTech Connect (OSTI)

    Doležalová, Markéta; Benešová, Libuše; Závodská, 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

  6. A Method for Modeling Household Occupant Behavior to Simulate Residential Energy Consumption

    SciTech Connect (OSTI)

    Johnson, Brandon J; Starke, Michael R; Abdelaziz, Omar; Jackson, Roderick K; Tolbert, Leon M

    2014-01-01

    This paper presents a statistical method for modeling the behavior of household occupants to estimate residential energy consumption. Using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS), actions carried out by survey respondents are categorized into ten distinct activities. These activities are defined to correspond to the major energy consuming loads commonly found within the residential sector. Next, time varying minute resolution Markov chain based statistical models of different occupant types are developed. Using these behavioral models, individual occupants are simulated to show how an occupant interacts with the major residential energy consuming loads throughout the day. From these simulations, the minimum number of occupants, and consequently the minimum number of multiple occupant households, needing to be simulated to produce a statistically accurate representation of aggregate residential behavior can be determined. Finally, future work will involve the use of these occupant models along side residential load models to produce a high-resolution energy consumption profile and estimate the potential for demand response from residential loads.

  7. Small-particle-size cement

    SciTech Connect (OSTI)

    Ewert, D.P.; Almond, S.W.; Blerhaus, W.M. II )

    1991-05-01

    Successful remedial cementing has historically been difficult in wells with large-interval, multizone, gravel-packed completions. The reason is the inability of conventional oilfield cements to penetrate gravel packs adequately. Small-particle-size cement (SPSC) was developed to penetrate gravel packs and to provide the zonal isolation required. This paper details the laboratory work, job design, and field implementation of this new cement.

  8. Strategy Guideline: HVAC Equipment Sizing

    SciTech Connect (OSTI)

    Burdick, A.

    2012-02-01

    The heating, ventilation, and air conditioning (HVAC) system is arguably the most complex system installed in a house and is a substantial component of the total house energy use. A right-sized HVAC system will provide the desired occupant comfort and will run efficiently. This Strategy Guideline discusses the information needed to initially select the equipment for a properly designed HVAC system. Right-sizing of an HVAC system involves the selection of equipment and the design of the air distribution system to meet the accurate predicted heating and cooling loads of the house. Right-sizing the HVAC system begins with an accurate understanding of the heating and cooling loads on a space; however, a full HVAC design involves more than just the load estimate calculation - the load calculation is the first step of the iterative HVAC design procedure. This guide describes the equipment selection of a split system air conditioner and furnace for an example house in Chicago, IL as well as a heat pump system for an example house in Orlando, Florida. The required heating and cooling load information for the two example houses was developed in the Department of Energy Building America Strategy Guideline: Accurate Heating and Cooling Load Calculations.

  9. 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.

  10. "Variable","Average Absolute Percent Differences","Percent of...

    U.S. Energy Information Administration (EIA) (indexed site)

    ... combined heat and power (CHP) electricity generation in electricity generating plants. Prior to AEO2003, coal price projections reflected data collected, estimated, and reported ...

  11. 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.

  12. 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

  13. 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

  14. A Green Approach to SNF Reprocessing: Are Common Household Reagents the Answer?

    SciTech Connect (OSTI)

    Peper, Shane M.; McNamara, Bruce K.; O'Hara, Matthew J.; Douglas, Matthew

    2008-04-03

    It has been discovered that UO2, the principal component of spent nuclear fuel (SNF), can efficiently be dissolved at room temperature using a combination of common household reagents, namely hydrogen peroxide, baking soda, and ammonia. This rather serendipitous discovery opens up the possibility, for the first time, of considering a non-acidic process for recycling U from SNF. Albeit at the early stages of development, our unconventional dissolution approach possesses many attractive features that could make it a reality in the future. With dissolution byproducts of water and oxygen, our approach poses a minimal threat to the environment. Moreover, the use of common household reagents to afford actinide oxide dissolution suggests a certain degree of economic favorability. With the use of a “closed” digestion vessel as a reaction chamber, our approach has substantial versatility with the option of using either aqueous or gaseous reactant feeds or a combination of both. Our approach distinguishes itself from all existing reprocessing technologies in two important ways. First and foremost, it is an alkaline rather than an acidic process, using mild non-corrosive chemicals under ambient conditions to effect actinide separations. Secondly, it does not dissolve the entire SNF matrix, but rather selectively solubilizes U and other light actinides for subsequent separation, resulting in potentially faster head-end dissolution and fewer downstream separation steps. From a safeguards perspective, the use of oxidizing alkaline solutions to effect actinide separations also potentially offers a degree of inherent proliferation resistance, by allowing the U to be selectively removed from the remaining dissolver solution while keeping Pu grouped with the other minor actinides and fission products. This paper will describe the design and general experimental setup of a “closed” digestion vessel for performing uranium oxide dissolutions under alkaline conditions using

  15. 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.

  16. spaceheat_percent2001.pdf

    Gasoline and Diesel Fuel Update

    ... 1.7 Q 2.3 2.6 1.3 Q 29.9 Steam or Hot-Water System ...... 7.4 8.7 12.5 12.9 1.3 Q ... 7.5 18.6 9.3 14.4 Q Q 16.3 Steam or Hot-Water System ...... 4.1 7.8 5.5 8.7 Q Q 18.1 ...

  17. 5000 groove/mm multilayer-coated blazed grating with 33percent efficiency in the 3rd order in the EUV wavelength range

    SciTech Connect (OSTI)

    Advanced Light Source; Voronov, Dmitriy L.; Anderson, Erik; Cambie, Rossana; Salmassi, Farhad; Gullikson, Eric; Yashchuk, Valeriy; Padmore, Howard; Ahn, Minseung; Chang, Chih-Hao; Heilmann, Ralf; Schattenburg, Mark

    2009-07-07

    We report on recent progress in developing diffraction gratings which can potentially provide extremely high spectral resolution of 105-106 in the EUV and soft x-ray photon energy ranges. Such a grating was fabricated by deposition of a multilayer on a substrate which consists ofa 6-degree blazed grating with a high groove density. The fabrication of the substrate gratings was based on scanning interference lithography and anisotropic wet etch of silicon single crystals. The optimized fabrication process provided precise control of the grating periodicity, and the grating groove profile, together with very short anti-blazed facets, and near atomically smooth surface blazed facets. The blazed grating coated with 20 Mo/Si bilayers demonstrated a diffraction efficiency in the third order as high as 33percent at an incidence angle of 11? and wavelength of 14.18 nm.

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

    SciTech Connect (OSTI)

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

    2012-10-15

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

  19. 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.

  20. 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.

  1. 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.

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

    SciTech Connect (OSTI)

    Slagstad, Helene; Brattebo, Helge

    2013-01-15

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

  3. Reduce Pumping Costs through Optimum Pipe Sizing

    SciTech Connect (OSTI)

    Not Available

    2005-10-01

    BestPractices Program tip sheet discussing pumping system efficiency by reducing pumping costs through optimum pipe sizing.

  4. 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

    2012-07-19

    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.

  5. Source segregation and food waste prevention activities in high-density households in a deprived urban area

    SciTech Connect (OSTI)

    Rispo, A.; Williams, I.D. Shaw, P.J.

    2015-10-15

    Highlights: • Study of waste management in economically and socially deprived high-density housing. • Food waste segregation, prevention and recycling activities investigated. • Study involved a waste audit and household survey of 1034 households. • Populations in such areas are “hard-to-reach”. • Exceptional efforts and additional resources are required to improve performance. - Abstract: A waste audit and a household questionnaire survey were conducted in high-density housing estates in one of the most economically and socially deprived areas of England (Haringey, London). Such areas are under-represented in published research. The study examined source segregation, potential participation in a food waste segregation scheme, and food waste prevention activities in five estates (1034 households). The results showed that: contamination of recyclables containers was low; ca. 28% of the mixed residual waste’s weight was recyclable; food waste comprised a small proportion of the waste from these residents, probably because of their relatively disadvantaged economic circumstances; and the recycling profile reflected an intermittent pattern of behaviour. Although the majority of respondents reported that they would participate in a food waste separation scheme, the response rate was low and many responses of “don’t know” were recorded. Municipalities committed to foster improved diversion from landfill need to recognise that there is no “quick and easy fix”, regardless of local or national aspirations. Lasting and sustained behaviour change requires time and the quality of service provision and associated infrastructure play a fundamental role in facilitating residents to participate effectively in waste management activities that maximise capture of source-segregated materials. Populations in deprived areas that reside in high-rise, high-density dwellings are “hard-to-reach” in terms of participation in recycling schemes and exceptional

  6. 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.

  7. Hazards of explosives dusts: Particle size effects

    SciTech Connect (OSTI)

    Cashdollar, K L; Hertzberg, M; Green, G M

    1992-02-01

    At the request of the Department of Energy, the Bureau of Mines has investigated the hazards of military explosives dispersed as dust clouds in a 20-L test chamber. In this report, the effect of particle size for HMX, HNS, RDX, TATB, and TNT explosives dusts is studied in detail. The explosibility data for these dusts are also compared to those for pure fuel dusts. The data show that all of the sizes of the explosives dusts that were studied were capable of sustaining explosions as dust clouds dispersed in air. The finest sizes (<10 [mu]m) of explosives dusts were less reactive than the intermediate sizes (20 to 60 [mu]m); this is opposite to the particle size effect observed previously for the pure fuel dusts. At the largest sizes studied, the explosives dusts become somewhat less reactive as dispersed dust clouds. The six sizes of the HMX dust were also studied as dust clouds dispersed in nitrogen.

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

    SciTech Connect (OSTI)

    Bernstad, A.; Cour Jansen, J. la

    2011-08-15

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

  9. THE CO2 ABATEMENT POTENTIAL OF CALIFORNIA'S MID-SIZED COMMERCIAL BUILDINGS

    SciTech Connect (OSTI)

    Stadler, Michael; Marnay, Chris; Cardoso, Goncalo; Lipman, Tim; Megel, Olivier; Ganguly, Srirupa; Siddiqui, Afzal; Lai, Judy

    2009-12-31

    The Ernest Orlando Lawrence Berkeley National Laboratory (LBNL) is working with the California Energy Commission (CEC) todetermine the potential role of commercial sector distributed generation (DG) with combined heat and power (CHP) capability deployment in greenhouse gas emissions (GHG) reductions. CHP applications at large industrial sites are well known, and a large share of their potential has already been harvested. In contrast, relatively little attention has been paid to the potential of medium-sized commercial buildings, i.e. ones with peak electric loads ranging from 100 kW to 5 MW. We examine how this sector might implement DG with CHP in cost minimizing microgrids that are able to adopt and operate various energy technologies, such as solar photovoltaics (PV), on-site thermal generation, heat exchangers, solar thermal collectors, absorption chillers, and storage systems. We apply a mixed-integer linear program (MILP) that minimizes a site?s annual energy costs as its objective. Using 138 representative mid-sized commercial sites in California (CA), existing tariffs of three major electricity distribution ultilities, and performance data of available technology in 2020, we find the GHG reduction potential for this CA commercial sector segment, which represents about 35percent of total statewide commercial sector sales. Under the assumptions made, in a reference case, this segment is estimated to be capable of economically installing 1.4 GW of CHP, 35percent of the California Air Resources Board (CARB) statewide 4 GW goal for total incremental CHP deployment by 2020. However, because CARB?s assumed utilization is far higher than is found by the MILP, the adopted CHP only contributes 19percent of the CO2 target. Several sensitivity runs were completed. One applies a simple feed-in tariff similar to net metering, and another includes a generous self-generation incentive program (SGIP) subsidy for fuel cells. The feed-in tariff proves ineffective at

  10. 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.

  11. ARM - Measurement - Aerosol particle size distribution

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    particle size distribution 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 : Aerosol particle size distribution The number of aerosol particles present in any given volume of air within a specificied size range Categories Aerosols Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a

  12. ARM - Measurement - Cloud particle size distribution

    U.S. Department of Energy (DOE) all webpages (Extended Search)

    size distribution 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 : Cloud particle size distribution The number of cloud particles present in any given volume of air within a specified size range, including liquid and ice. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each

  13. " Electricity Generation by Employment Size Categories...

    U.S. Energy Information Administration (EIA) (indexed site)

    Total Consumption of Offsite-Produced Energy for Heat, Power, and" " Electricity Generation by Employment Size Categories, Industry Group, and" " Selected Industries, 1991" " ...

  14. Particle size distribution instrument. Topical report 13

    SciTech Connect (OSTI)

    Okhuysen, W.; Gassaway, J.D.

    1995-04-01

    The development of an instrument to measure the concentration of particles in gas is described in this report. An in situ instrument was designed and constructed which sizes individual particles and counts the number of occurrences for several size classes. Although this instrument was designed to detect the size distribution of slag and seed particles generated at an experimental coal-fired magnetohydrodynamic power facility, it can be used as a nonintrusive diagnostic tool for other hostile industrial processes involving the formation and growth of particulates. Two of the techniques developed are extensions of the widely used crossed beam velocimeter, providing simultaneous measurement of the size distribution and velocity of articles.

  15. Investigation of thermochemical biorefinery sizing and environmental...

    Office of Scientific and Technical Information (OSTI)

    Investigation of thermochemical biorefinery sizing and environmental sustainability impacts for conventional supply system and distributed pre-processing supply system designs...

  16. Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

    SciTech Connect (OSTI)

    Keller, Brad M.; Nathan, Diane L.; Wang Yan; Zheng Yuanjie; Gee, James C.; Conant, Emily F.; Kontos, Despina

    2012-08-15

    Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., 'FOR PROCESSING') and vendor postprocessed (i.e., 'FOR PRESENTATION'), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then

  17. Effective Size Analysis of the Diametral Compression (Brazil) Test Specimen

    SciTech Connect (OSTI)

    Jadaan, Osama M.; Wereszczak, Andrew A

    2009-04-01

    This study considers the finite element analysis (FEA) simulation and Weibull effective size analysis for the diametral compression (DC) or Brazil specimen loaded with three different push-rod geometries. Those geometries are a flat push-rod, a push-rod whose radius of curvature is larger than that for the DC specimen, and a push-rod whose radius of curvature matches that of the DC specimen. Such established effective size analysis recognizes that the tensile strength of structural ceramics is typically one to two orders of magnitude less than its compressive strength. Therefore, because fracture is much more apt to result from a tensile stress than a compressive one, this traditional analysis only considers the first principal tensile stress field in the mechanically loaded ceramic component for the effective size analysis. The effective areas and effective volumes were computed as function of Weibull modulus using the CARES/Life code. Particular attention was devoted to the effect of mesh sensitivity and localized stress concentration. The effect of specimen width on the stress state was also investigated. The effects of push-rod geometry, the use of steel versus WC push-rods, and considering a frictionless versus no-slip interface between push-rod and specimen on the maximum stresses, where those stresses are located, and the effective area and effective volume results are described. Of the three push-rod geometries, it is concluded that the push-rod (made from WC rather than steel) whose radius of curvature matches that of the DC specimen is the most apt to cause fracture initiation within the specimen's bulk rather than at the loading interface. Therefore, its geometry is the most likely to produce a valid diametral compression strength test. However, the DC specimen remains inefficient in terms of its area and volume efficiencies; namely, the tensile strength of only a few percent of the specimen's entire area or volume is sampled. Given the high probability

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

    SciTech Connect (OSTI)

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

    1999-11-01

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

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

    SciTech Connect (OSTI)

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

    2010-07-15

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

  20. Emissions from small-scale energy production using co-combustion of biofuel and the dry fraction of household waste

    SciTech Connect (OSTI)

    Hedman, Bjoern . E-mail: bjorn.hedman@chem.umu.se; Burvall, Jan; Nilsson, Calle; Marklund, Stellan

    2005-07-01

    In sparsely populated rural areas, recycling of household waste might not always be the most environmentally advantageous solution due to the total amount of transport involved. In this study, an alternative approach to recycling has been tested using efficient small-scale biofuel boilers for co-combustion of biofuel and high-energy waste. The dry combustible fraction of source-sorted household waste was mixed with the energy crop reed canary-grass (Phalaris Arundinacea L.), and combusted in both a 5-kW pilot scale reactor and a biofuel boiler with 140-180 kW output capacity, in the form of pellets and briquettes, respectively. The chlorine content of the waste fraction was 0.2%, most of which originated from plastics. The HCl emissions exceeded levels stipulated in new EU-directives, but levels of equal magnitude were also generated from combustion of the pure biofuel. Addition of waste to the biofuel did not give any apparent increase in emissions of organic compounds. Dioxin levels were close to stipulated limits. With further refinement of combustion equipment, small-scale co-combustion systems have the potential to comply with emission regulations.