National Library of Energy BETA

Sample records for household characteristics number

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

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

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

  2. 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

  3. 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

  4. 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

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

    SciTech Connect (OSTI)

    Guerin, D.A.

    1988-01-01

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

  6. 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.

  7. 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

  8. 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.....................................................

  9. 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......................

  10. 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

  11. 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.

  12. 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.

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

    Gasoline and Diesel Fuel Update (EIA)

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

  14. 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.

  15. char_household2001.pdf

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

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

  16. Household magnets

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

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

  17. 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

  18. 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

  19. 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

  20. 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

  1. ac_household2001.pdf

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

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

  2. 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

  3. 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.

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

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

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

  5. Table 5.1. U.S. Number of Vehicles, Vehicle-Miles, Motor Fuel...

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

    Table 5.1. U.S. Number of Vehicles, Vehicle-Miles, Motor Fuel Consumption and Expenditures, 1994 (Continued) 1993 Household and 1994 Vehicle Characteristics RSE Column Factor:...

  6. 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 ...

  7. EIA - Household Transportation report: Household Vehicles Energy...

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

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series....

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. ac_household2001.pdf

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

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

  15. 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.

  16. 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...

  17. 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

  18. 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

  19. 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

  20. 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 ...........................................

  1. 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

  2. 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

  3. 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

  4. spaceheat_household2001.pdf

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

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

  5. spaceheat_household2001.pdf

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

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

  6. 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

  7. 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

  8. 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

  9. spaceheat_household2001.pdf

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

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

  10. spaceheat_household2001.pdf

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

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

  11. appl_household2001.pdf

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

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

  12. homeoffice_household2001.pdf

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

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

  13. 1997 Housing Characteristics Tables Housing Unit Tables

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

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

  14. 1997 Housing Characteristics Tables Housing Unit Tables

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

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

  15. housingunit_household2001.pdf

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

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

  16. appl_household2001.pdf

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

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

  17. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

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

  18. 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 ...

  19. 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

  20. 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

  1. 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 ........................

  2. 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

  3. Housing characteristics 1993

    SciTech Connect (OSTI)

    1995-06-01

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

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

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

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

  5. 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...

  6. 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...

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

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

    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. 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.

  9. 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 *...

  10. 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 ...

  11. 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 ...

  12. homeoffice_household2001.pdf

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

    ... 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 ...

  13. char_household2001.pdf

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

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

  14. 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) . . . . . . . . ....

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

    Gasoline and Diesel Fuel Update (EIA)

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

  16. 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

  17. 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

  18. 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

  19. 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

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

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

    Household Expenditures on Transportation, 1984-2010 Fact 748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household ...

  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. 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.

  3. "Utility Characteristics",,,,,,"Number AMR- Automated Meter Reading",,,,,"Number AMI- Advanced Metering Infrastructure",,,,,"Energy Served - AMI (MWh)"

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

    Energy Served - AMI (MWh)" "Year","Month","Utility Number","Utility Name","State","Data

  4. New York Household Travel Patterns: A Comparison Analysis

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim

    2007-05-01

    In 1969, the U. S. Department of Transportation began collecting detailed data on personal travel to address various transportation planning issues. These issues range from assessing transportation investment programs to developing new technologies to alleviate congestion. This 1969 survey was the birth of the Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990 and 1995. Longer-distance travel was collected in 1977 and 1995. In 2001, the survey was renamed to the National Household Travel Survey (NHTS) and collected both daily and longer-distance trips in one survey. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State (NYS), the state procured an additional sample of households in both the 1995 and 2001 surveys. In the 1995 survey, NYS procured an addition sample of more than 9,000 households, increasing the final NY NPTS sample size to a total of 11,004 households. Again in 2001, NYS procured 12,000 additional sample households, increasing the final New York NHTS sample size to a total of 13,423 households with usable data. These additional sample households allowed NYS to address transportation planning issues pertinent to geographic areas significantly smaller than for what the national NPTS and NHTS data are intended. Specifically, these larger sample sizes enable detailed analysis of twelve individual Metropolitan Planning Organizations (MPOs). Furthermore, they allowed NYS to address trends in travel behavior over time. In this report, travel data for the entire NYS were compared to those of the rest of the country with respect to personal travel behavior and key travel determinants. The influence of New York City (NYC) data on the comparisons of the state of New York to the rest of the country was also examined. Moreover, the analysis examined the relationship between population density and travel patterns, and the similarities and differences among New

  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. 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

  7. Transferring 2001 National Household Travel Survey

    SciTech Connect (OSTI)

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

    2007-05-01

    Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle

  8. 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.

  9. 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 ...

  10. 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...

  11. 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 ...

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

    Open Energy Info (EERE)

    Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic...

  13. Microsoft Word - Household Energy Use CA

    Gasoline and Diesel Fuel Update (EIA)

    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

  14. 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

  15. 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.

  16. Household Vehicles Energy Consumption 1991

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

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

  17. Statistical characteristic of the initial exciton number n/sub 0/ and its influence on the results in the exciton model

    SciTech Connect (OSTI)

    MIAO Rong-Zhi; WU Guo-Hua; ZENG Wei-Han; LIU Jian-Ye; YU Chao-Fan; YU Xian

    1985-10-01

    It is assumed that the initial exciton number n/sub 0/ is statistical. The expression of the probability h(n/sub 0/) for any probable n/sub 0/ is given. The theoretical calculation results, including the energy spectra and the double differential cross sections, are obtained by weighted summation of the contributions coming from various probable n/sub 0/. The agreement between experimental data and the theoretical results is quite good.

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

    SciTech Connect (OSTI)

    Dolealov, Markta; Beneov, Libue; Zvodsk, Anita

    2013-09-15

    Highlights: The character of household waste in the three different types of households were assesed. The quantity, density and composition of household waste were determined. The physicochemical characteristics were determined. The changing character of household waste during past 10 years was described. The potential of energy recovery of household waste in Czech republic was assesed. - Abstract: The authors of this paper report on the changing character of household waste, in the Czech Republic between 1999 and 2009 in households differentiated by their heating methods. The data presented are the result of two projects, financed by the Czech Ministry of Environment, which were undertaken during this time period with the aim of focusing on the waste characterisation and complete analysis of the physicochemical properties of the household waste. In the Czech Republic, the composition of household waste varies significantly between different types of households based on the methods of home heating employed. For the purposes of these studies, the types of homes were divided into three categories urban, mixed and rural. Some of the biggest differences were found in the quantities of certain subsample categories, especially fine residue (matter smaller than 20 mm), between urban households with central heating and rural households that primarily employ solid fuel such coal or wood. The use of these solid fuels increases the fraction of the finer categories because of the higher presence of ash. Heating values of the residual household waste from the three categories varied very significantly, ranging from 6.8 MJ/kg to 14.2 MJ/kg in 1999 and from 6.8 MJ/kg to 10.5 MJ/kg in 2009 depending on the type of household and season. The same factors affect moisture of residual household waste which varied from 23.2% to 33.3%. The chemical parameters also varied significantly, especially in the quantities of Tl, As, Cr, Zn, Fe and Mn, which were higher in rural

  19. appl_household2001.pdf

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

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

  20. spaceheat_household2001.pdf

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

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

  1. Request Number:

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

    3023307 Name: Madeleine Brown Organization: nJa Address: --- -------- -------- -- Country: Phone Number: United States Fax Number: n/a E-mail: --- -------- --------_._------ --- Reasonably Describe Records Description: Please send me a copy of the emails and records relating to the decision to allow the underage son of Bill Gates to tour Hanford in June 2010. Please also send the emails and records that justify the Department of Energy to prevent other minors from visiting B Reactor. Optional

  2. Request Number:

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

    1074438 Name: Gayle Cooper Organization: nla Address: _ Country: United States Phone Number: Fax Number: nla E-mail: . ~===--------- Reasonably Describe Records Description: Information pertaining to the Department of Energy's cost estimate for reinstating pension benefit service years to the Enterprise Company (ENCO) employees who are active plan participants in the Hanford Site Pension Plan. This cost estimate was an outcome of the DOE's Worker Town Hall Meetings held on September 17-18, 2009.

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

    Gasoline and Diesel Fuel Update (EIA)

    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

  4. (Document Number)

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

    A TA-53 TOUR FORM/RADIOLOGICAL LOG (Send completed form to MS H831) _____________ _____________________________ _________________________________ Tour Date Purpose of Tour or Tour Title Start Time and Approximate Duration ___________________________ ______________ _______________________ _________________ Tour Point of Contact/Requestor Z# (if applicable) Organization/Phone Number Signature Locations Visited: (Check all that apply, and list any others not shown. Prior approval must be obtained

  5. 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.

  6. 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.

  7. 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.

  8. Quantum random number generator

    DOE Patents [OSTI]

    Pooser, Raphael C.

    2016-05-10

    A quantum random number generator (QRNG) and a photon generator for a QRNG are provided. The photon generator may be operated in a spontaneous mode below a lasing threshold to emit photons. Photons emitted from the photon generator may have at least one random characteristic, which may be monitored by the QRNG to generate a random number. In one embodiment, the photon generator may include a photon emitter and an amplifier coupled to the photon emitter. The amplifier may enable the photon generator to be used in the QRNG without introducing significant bias in the random number and may enable multiplexing of multiple random numbers. The amplifier may also desensitize the photon generator to fluctuations in power supplied thereto while operating in the spontaneous mode. In one embodiment, the photon emitter and amplifier may be a tapered diode amplifier.

  9. Commercial viability of hybrid vehicles : best household use and cross national considerations.

    SciTech Connect (OSTI)

    Santini, D. J.; Vyas, A. D.

    1999-07-16

    Japanese automakers have introduced hybrid passenger cars in Japan and will soon do so in the US. In this paper, we report how we used early computer simulation model results to compare the commercial viability of a hypothetical near-term (next decade) hybrid mid-size passenger car configuration under varying fuel price and driving patterns. The fuel prices and driving patterns evaluated are designed to span likely values for major OECD nations. Two types of models are used. One allows the ''design'' of a hybrid to a specified set of performance requirements and the prediction of fuel economy under a number of possible driving patterns (called driving cycles). Another provides an estimate of the incremental cost of the hybrid in comparison to a comparably performing conventional vehicle. In this paper, the models are applied to predict the NPV cost of conventional gasoline-fueled vehicles vs. parallel hybrid vehicles. The parallel hybrids are assumed to (1) be produced at high volume, (2) use nickel metal hydride battery packs, and (3) have high-strength steel bodies. The conventional vehicle also is assumed to have a high-strength steel body. The simulated vehicles are held constant in many respects, including 0-60 time, engine type, aerodynamic drag coefficient, tire rolling resistance, and frontal area. The hybrids analyzed use the minimum size battery pack and motor to meet specified 0-60 times. A key characteristic affecting commercial viability is noted and quantified: that hybrids achieve the most pronounced fuel economy increase (best use) in slow, average-speed, stop-and-go driving, but when households consistently drive these vehicles under these conditions, they tend to travel fewer miles than average vehicles. We find that hours driven is a more valuable measure than miles. Estimates are developed concerning hours of use of household vehicles versus driving cycle, and the pattern of minimum NPV incremental cost (or benefit) of selecting the hybrid over

  10. Strategies for Collecting Household Energy Data | Department of Energy

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

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data, Call Slides and Discussion Summary, July 19, 2012. Call Slides and Discussion Summary (700.06 KB) More Documents & Publications Homeowner and Contractor Surveys Mastermind: Jim Mikel, Spirit Foundation Generating Energy Efficiency Project Leads and Allocating Leads to Contractors

  11. 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.

  12. 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.

  13. 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.

  14. 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)

  15. Table 5.1. U.S. Number of Vehicles, Vehicle-Miles, Motor Fuel...

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

    Energy Information AdministrationHousehold Vehicles Energy Consumption 1994 43 Table 5.1. U.S. Number of Vehicles, Vehicle-Miles, Motor Fuel Consumption and Expenditures, 1994...

  16. 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.

  17. Table 5.17. U.S. Number of Households by Vehicle Fuel Expenditures...

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

    More ... 8.2 Q 1.7 1.9 1.7 2.6 6.1 2.0 Q Q Q 16.7 Below Poverty Line 100 Percent ... 9.0 2.5 3.6 1.3 1.0 0.6 Q...

  18. Reconstructing householder vectors from Tall-Skinny QR

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

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

    2015-08-05

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

  19. 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.

  20. 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).

  1. 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).

  2. "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" ...

  3. "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" ...

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

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

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

  5. 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

  6. Commercial Buildings Characteristics 1992

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

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

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

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

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

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

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

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

  9. 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...

  10. 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.

  11. 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.

  12. Compendium of Experimental Cetane Numbers

    SciTech Connect (OSTI)

    Yanowitz, J.; Ratcliff, M. A.; McCormick, R. L.; Taylor, J. D.; Murphy, M. J.

    2014-08-01

    This report is an updated version of the 2004 Compendium of Experimental Cetane Number Data and presents a compilation of measured cetane numbers for pure chemical compounds. It includes all available single compound cetane number data found in the scientific literature up until March 2014 as well as a number of unpublished values, most measured over the past decade at the National Renewable Energy Laboratory. This Compendium contains cetane values for 389 pure compounds, including 189 hydrocarbons and 201 oxygenates. More than 250 individual measurements are new to this version of the Compendium. For many compounds, numerous measurements are included, often collected by different researchers using different methods. Cetane number is a relative ranking of a fuel's autoignition characteristics for use in compression ignition engines; it is based on the amount of time between fuel injection and ignition, also known as ignition delay. The cetane number is typically measured either in a single-cylinder engine or a constant volume combustion chamber. Values in the previous Compendium derived from octane numbers have been removed, and replaced with a brief analysis of the correlation between cetane numbers and octane numbers. The discussion on the accuracy and precision of the most commonly used methods for measuring cetane has been expanded and the data has been annotated extensively to provide additional information that will help the reader judge the relative reliability of individual results.

  13. 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.

  14. Shared Solar Projects Powering Households Throughout America | Department

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

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

  15. 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

  16. 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.

  17. Number | Open Energy Information

    Open Energy Info (EERE)

    Property:NumOfPlants Property:NumProdWells Property:NumRepWells Property:Number of Color Cameras Property:Number of Devices Deployed Property:Number of Plants included in...

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

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

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

  19. NSR Key Number Retrieval

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

    NSR Key Number Retrieval Pease enter key in the box Submit

  20. Health Care Buildings : Basic Characteristics Tables

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

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

  1. CBECS Buildings Characteristics --Revised Tables

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

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

  2. 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

  3. "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 ...

  4. 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.

  5. "Utility Characteristics",,,,,,"Number AMR- Automated Meter Reading...

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

    ... 2014,1,12919,"Morenci Water and Electric","AZ","Final",2418,198,".",".... 2014,1,11208,"Los Angeles Department of Water & Power","CA","Final",286199,57380,5758,42...

  6. "Utility Characteristics",,,,,,"Number AMR- Automated Meter Reading...

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

    ... 2015,1,12919,"Morenci Water and Electric","AZ","Preliminary",2282,322,... 2015,1,11208,"Los Angeles Department of Water & Power","CA","Preliminary",308272,60239,5...

  7. New York Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) New York Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New York Number of Natural Gas ...

  8. New Mexico Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Consumers (Number of Elements) New Mexico Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New Mexico Number of Natural ...

  9. North Dakota Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) North Dakota Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers North Dakota Number of Natural ...

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

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

    Energy 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 Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014. Call Slides and Discussion Summary (919.64 KB) More Documents & Publications EcoHouse Program Overview Strengthening Relationships Between Energy Programs and Housing Programs Targeted Marketing and Program

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

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

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

  12. Effect of Income on Appliances in U.S. Households, The

    Reports and Publications (EIA)

    2004-01-01

    Entails how people live, the factors that cause the most differences in home lifestyle, including energy use in geographic location, socioeconomics and household income.

  13. Forum on Enhancing the Delivery of Energy Efficiency to Middle Income Households: Discussion Summary

    SciTech Connect (OSTI)

    none,

    2012-09-20

    Summarizes discussions and recommendations from a forum for practitioners and policymakers aiming to strengthen residential energy efficiency program design and delivery for middle income households.

  14. Report number codes

    SciTech Connect (OSTI)

    Nelson, R.N.

    1985-05-01

    This publication lists all report number codes processed by the Office of Scientific and Technical Information. The report codes are substantially based on the American National Standards Institute, Standard Technical Report Number (STRN)-Format and Creation Z39.23-1983. The Standard Technical Report Number (STRN) provides one of the primary methods of identifying a specific technical report. The STRN consists of two parts: The report code and the sequential number. The report code identifies the issuing organization, a specific program, or a type of document. The sequential number, which is assigned in sequence by each report issuing entity, is not included in this publication. Part I of this compilation is alphabetized by report codes followed by issuing installations. Part II lists the issuing organization followed by the assigned report code(s). In both Parts I and II, the names of issuing organizations appear for the most part in the form used at the time the reports were issued. However, for some of the more prolific installations which have had name changes, all entries have been merged under the current name.

  15. Quantum random number generation

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

    Ma, Xiongfeng; Yuan, Xiao; Cao, Zhu; Zhang, Zhen; Qi, Bing

    2016-06-28

    Here, quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness -- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at amore » high speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.« less

  16. ALARA notes, Number 8

    SciTech Connect (OSTI)

    Khan, T.A.; Baum, J.W.; Beckman, M.C.

    1993-10-01

    This document contains information dealing with the lessons learned from the experience of nuclear plants. In this issue the authors tried to avoid the `tyranny` of numbers and concentrated on the main lessons learned. Topics include: filtration devices for air pollution abatement, crack repair and inspection, and remote handling equipment.

  17. Commercial Buildings Characteristics, 1992

    SciTech Connect (OSTI)

    Not Available

    1994-04-29

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

  18. Document Details Document Number

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

    Document Details Document Number Date of Document Document Title/Description [Links below to each document] D195066340 Not listed. N/A REVISIONS IN STRATIGRAPHIC NOMENCLATURE OF COLUMBIA RIVER BASALT GROUP D196000240 Not listed. N/A EPA DENIAL OF LINER LEACHATE COLLECTION SYSTEM REQUIREMENTS D196005916 Not listed. N/A LATE CENOZOIC STRATIGRAPHY AND TECTONIC EVOLUTION WITHIN SUBSIDING BASIN SOUTH CENTRAL WASHINGTON D196025993 RHO-BWI-ST-14 N/A SUPRABASALT SEDIMENTS OF COLD CREEK SYNCLINE AREA

  19. 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.

  20. Modular redundant number systems

    SciTech Connect (OSTI)

    1998-05-31

    With the increased use of public key cryptography, faster modular multiplication has become an important cryptographic issue. Almost all public key cryptography, including most elliptic curve systems, use modular multiplication. Modular multiplication, particularly for the large public key modulii, is very slow. Increasing the speed of modular multiplication is almost synonymous with increasing the speed of public key cryptography. There are two parts to modular multiplication: multiplication and modular reduction. Though there are fast methods for multiplying and fast methods for doing modular reduction, they do not mix well. Most fast techniques require integers to be in a special form. These special forms are not related and converting from one form to another is more costly than using the standard techniques. To this date it has been better to use the fast modular reduction technique coupled with standard multiplication. Standard modular reduction is much more costly than standard multiplication. Fast modular reduction (Montgomery`s method) reduces the reduction cost to approximately that of a standard multiply. Of the fast multiplication techniques, the redundant number system technique (RNS) is one of the most popular. It is simple, converting a large convolution (multiply) into many smaller independent ones. Not only do redundant number systems increase speed, but the independent parts allow for parallelization. RNS form implies working modulo another constant. Depending on the relationship between these two constants; reduction OR division may be possible, but not both. This paper describes a new technique using ideas from both Montgomery`s method and RNS. It avoids the formula problem and allows fast reduction and multiplication. Since RNS form is used throughout, it also allows the entire process to be parallelized.

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

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

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

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

    SciTech Connect (OSTI)

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

    2015-12-01

    This research is a detailed examination of the travel behaviors and patterns of transit users within New York State (NYS), primarily based on travel data provided by the National Household Travel Survey (NHTS) in 2009 and the associated Add-on sample households purchased by the New York State Department of Transportation (NYSDOT). Other data sources analyzed in this study include: NYS General Transit Feed Specification (GTFS) to assist in analyzing spatial relationships for access to transit and the creation of Transit Shed geographic areas of 1, 2.5, and 5 miles from transit stop locations, LandScan population database to understand transit coverage, and Census Bureau s American Community Survey (ACS) data to examine general transit patterns and trends in NYS over time. The majority of analyses performed in this research aimed at identifying transit trip locations, understanding differences in transit usage by traveler demographics, as well as producing trip/mode-specific summary statistics including travel distance, trip duration, time of trip, and travel purpose of transit trips made by NYS residents, while also analyzing regional differences and unique travel characteristics and patterns. The analysis was divided into two aggregated geographic regions: New York Metropolitan Transportation Council (NYMTC) and NYS minus NYMTC (Rest of NYS). The inclusion of NYMTC in all analysis would likely produce misleading conclusions for other regions in NYS. TRANSIT COVERAGE The NYS transit network has significant coverage in terms of transit stop locations across the state s population. Out of the 19.3 million NYS population in 2011, about 15.3 million (or 79%) resided within the 1-mile transit shed. This NYS population transit coverage increased to 16.9 million (or 88%) when a 2.5-mile transit shed was considered; and raised to 17.7 million (or 92%) when the 5-mile transit shed was applied. KEY FINDINGS Based on 2009 NHTS data, about 40% of NYMTC households used transit

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. Virginia Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  8. Utah Natural Gas Number of Industrial Consumers (Number of Elements...

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

    Industrial Consumers (Number of Elements) Utah Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  9. Wisconsin Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) Wisconsin Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  10. Virginia Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  11. Utah Natural Gas Number of Residential Consumers (Number of Elements...

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

    Residential Consumers (Number of Elements) Utah Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  12. Vermont Natural Gas Number of Residential Consumers (Number of...

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

    Residential Consumers (Number of Elements) Vermont Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  13. Utah Natural Gas Number of Commercial Consumers (Number of Elements...

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

    Commercial Consumers (Number of Elements) Utah Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  14. Virginia Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  15. West Virginia Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) West Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  16. Wisconsin Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Wisconsin Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  17. Vermont Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) Vermont Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  18. West Virginia Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) West Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  19. Washington Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) Washington Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  20. Washington Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Washington Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  1. Washington Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) Washington Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  2. Wisconsin Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) Wisconsin Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  3. Vermont Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Vermont Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  4. West Virginia Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) West Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  5. New York Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) New York Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  6. New Mexico Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Residential Consumers (Number of Elements) New Mexico Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  7. New Jersey Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Residential Consumers (Number of Elements) New Jersey Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  8. New Hampshire Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Consumers (Number of Elements) New Hampshire Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  9. New Hampshire Natural Gas Number of Industrial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Industrial Consumers (Number of Elements) New Hampshire Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  10. New Hampshire Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) New Hampshire Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  11. New Mexico Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) New Mexico Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  12. North Carolina Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) North Carolina Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  13. North Carolina Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) North Carolina Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  14. North Dakota Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) North Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  15. North Dakota Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) North Dakota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  16. North Carolina Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) North Carolina Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

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

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

    5 Household 1 Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005 Year Space ... 3 Fuel Oil 4 LPG 5 Total Electricity 3 Natural Gas Elec- tricity 3 ...

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

    Broader source: Energy.gov [DOE]

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

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

    Broader source: Energy.gov [DOE]

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

  20. 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

  1. 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

  2. Number

    Office of Legacy Management (LM)

    engaged in the production of thorium compounds. The purpose of the trip vas to: l 1. Learn the type of chemical processes employed in the thorium industry (thorium nitrate). 2. ...

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

    SciTech Connect (OSTI)

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

    2005-05-31

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

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

    SciTech Connect (OSTI)

    Figueroa, M.J.; Sathaye, J.

    1993-08-01

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

  5. Alaska Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Alaska Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10 11 8 1990's 8 8 10 11 11 9 202 7 7 9 2000's 9 8 9 9 10 12 11 11 6 3 2010's 3 5 3 3 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Number of Natural

  6. Hawaii Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Hawaii Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 27 26 29 2000's 28 28 29 29 29 28 26 27 27 25 2010's 24 24 22 22 23 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Number of Natural Gas Industrial

  7. 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.

  8. ARM - Measurement - Particle number concentration

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

    number concentration 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 number concentration The number of particles present in any given volume of air. 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

  9. Total Number of Operable Refineries

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

    Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge

  10. 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

  11. 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

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

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

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

  13. 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

  14. 1997 Housing Characteristics Tables Housing Unit Tables

    Gasoline and Diesel Fuel Update (EIA)

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

  16. Nevada Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Nevada Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 93 98 100 1990's 100 113 114 117 119 120 121 93 93 109 2000's 90 90 96 97 179 192 207 220 189 192 2010's 184 177 177 195 218 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016

  17. Maine Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Maine Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 73 73 74 1990's 80 81 80 66 89 74 87 81 110 108 2000's 178 233 66 65 69 69 73 76 82 85 2010's 94 102 108 120 126 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring

  18. Montana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Montana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 435 435 428 1990's 457 452 459 462 453 463 466 462 454 397 2000's 71 73 439 412 593 716 711 693 693 396 2010's 384 381 372 372 369 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  19. Wyoming Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Wyoming Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 190 200 230 1990's 284 228 244 194 135 126 170 194 317 314 2000's 308 295 877 179 121 127 133 133 155 130 2010's 120 123 127 132 131 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  20. Arizona Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Arizona Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 358 344 354 1990's 526 532 532 526 519 530 534 480 514 555 2000's 526 504 488 450 414 425 439 395 383 390 2010's 368 371 379 383 386 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  1. Delaware Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Delaware Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241 233 235 1990's 240 243 248 249 252 253 250 265 257 264 2000's 297 316 182 184 186 179 170 185 165 112 2010's 114 129 134 138 141 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  2. Florida Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Florida Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 575 552 460 1990's 452 377 388 433 481 515 517 561 574 573 2000's 520 518 451 421 398 432 475 467 449 607 2010's 581 630 507 528 520 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  3. Idaho Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Idaho Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 219 132 64 1990's 62 65 66 75 144 167 183 189 203 200 2000's 217 198 194 191 196 195 192 188 199 187 2010's 184 178 179 183 189 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  4. Rhode Island Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Rhode Island Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,158 1,152 1,122 1990's 1,135 1,107 1,096 1,066 1,064 359 363 336 325 302 2000's 317 283 54 236 223 223 245 256 243 260 2010's 249 245 248 271 266 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  5. South Dakota Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) South Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 261 267 270 1990's 275 283 319 355 381 396 444 481 464 445 2000's 416 402 533 526 475 542 528 548 598 598 2010's 580 556 574 566 575 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016

  6. 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.

  7. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  8. Departmental Business Instrument Numbering System

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

    2005-01-27

    The Order prescribes the procedures for assigning identifying numbers to all Department of Energy (DOE) and National Nuclear Security Administration (NNSA) business instruments. Cancels DOE O 540.1. Canceled by DOE O 540.1B.

  9. Departmental Business Instrument Numbering System

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

    2000-12-05

    To prescribe procedures for assigning identifying numbers to all Department of Energy (DOE), including the National Nuclear Security Administration, business instruments. Cancels DOE 1331.2B. Canceled by DOE O 540.1A.

  10. 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).

  11. Nebraska Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Nebraska Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 60,707 61,365 60,377 1990's 60,405 60,947 61,319 60,599 62,045 61,275 61,117 51,661 63,819 53,943 2000's 55,194 55,692 56,560 55,999 57,087 57,389 56,548 55,761 58,160 56,454 2010's 56,246 56,553 56,608 58,005 57,191 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  12. Nebraska Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Nebraska Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 675 684 702 1990's 712 718 696 718 766 2,432 2,234 11,553 10,673 10,342 2000's 10,161 10,504 9,156 9,022 8,463 7,973 7,697 7,668 11,627 7,863 2010's 7,912 7,955 8,160 8,495 8,791 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  13. Nebraska Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Nebraska Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400,218 403,657 406,723 1990's 407,094 413,354 418,611 413,358 428,201 427,720 439,931 444,970 523,790 460,173 2000's 475,673 476,275 487,332 492,451 497,391 501,279 499,504 494,005 512,013 512,551 2010's 510,776 514,481 515,338 527,397 522,408 - = No Data Reported; -- = Not Applicable; NA = Not

  14. Nevada Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Nevada Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 18,294 18,921 19,924 1990's 20,694 22,124 22,799 23,207 24,521 25,593 26,613 27,629 29,030 30,521 2000's 31,789 32,782 33,877 34,590 35,792 37,093 38,546 40,128 41,098 41,303 2010's 40,801 40,944 41,192 41,710 42,338 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  15. Nevada Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Nevada Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 213,422 219,981 236,237 1990's 256,119 283,307 295,714 305,099 336,353 364,112 393,783 426,221 458,737 490,029 2000's 520,233 550,850 580,319 610,756 648,551 688,058 726,772 750,570 758,315 760,391 2010's 764,435 772,880 782,759 794,150 808,970 - = No Data Reported; -- = Not Applicable; NA = Not

  16. Ohio Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Ohio Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 213,601 219,257 225,347 1990's 233,075 236,519 237,861 240,684 245,190 250,223 259,663 254,991 258,076 266,102 2000's 269,561 269,327 271,160 271,203 272,445 277,767 270,552 272,555 272,899 270,596 2010's 268,346 268,647 267,793 269,081 269,758 - = No Data Reported; -- = Not Applicable; NA = Not

  17. Ohio Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Ohio Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 7,929 8,163 8,356 1990's 8,301 8,479 8,573 8,678 8,655 8,650 8,672 7,779 8,112 8,136 2000's 8,267 8,515 8,111 8,098 7,899 8,328 6,929 6,858 6,806 6,712 2010's 6,571 6,482 6,381 6,554 6,526 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  18. Ohio Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Ohio Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,648,972 2,678,838 2,714,839 1990's 2,766,912 2,801,716 2,826,713 2,867,959 2,921,536 2,967,375 2,994,891 3,041,948 3,050,960 3,111,108 2000's 3,178,840 3,195,584 3,208,466 3,225,908 3,250,068 3,272,307 3,263,062 3,273,791 3,262,716 3,253,184 2010's 3,240,619 3,236,160 3,244,274 3,271,074 3,283,869 -

  19. Oklahoma Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Oklahoma Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 87,824 86,666 86,172 1990's 85,790 86,744 87,120 88,181 87,494 88,358 89,852 90,284 89,711 80,986 2000's 80,558 79,045 80,029 79,733 79,512 78,726 78,745 93,991 94,247 94,314 2010's 92,430 93,903 94,537 95,385 96,004 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  20. Oklahoma Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Oklahoma Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,772 2,689 2,877 1990's 2,889 2,840 2,859 2,912 2,853 2,845 2,843 2,531 3,295 3,040 2000's 2,821 3,403 3,438 3,367 3,283 2,855 2,811 2,822 2,920 2,618 2010's 2,731 2,733 2,872 2,958 3,063 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  1. Oklahoma Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Oklahoma Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 809,171 805,107 806,875 1990's 814,296 824,172 832,677 842,130 845,448 856,604 866,531 872,454 877,236 867,922 2000's 859,951 868,314 875,338 876,420 875,271 880,403 879,589 920,616 923,650 924,745 2010's 914,869 922,240 927,346 931,981 937,237 - = No Data Reported; -- = Not Applicable; NA = Not

  2. Oregon Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Oregon Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 40,967 41,998 43,997 1990's 47,175 55,374 50,251 51,910 53,700 55,409 57,613 60,419 63,085 65,034 2000's 66,893 68,098 69,150 74,515 71,762 73,520 74,683 80,998 76,868 76,893 2010's 77,370 77,822 78,237 79,276 80,480 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  3. Oregon Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Oregon Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 676 1,034 738 1990's 699 787 740 696 765 791 799 704 695 718 2000's 717 821 842 926 907 1,118 1,060 1,136 1,075 1,051 2010's 1,053 1,066 1,076 1,085 1,099 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016

  4. Oregon Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Oregon Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 280,670 288,066 302,156 1990's 326,177 376,166 354,256 371,151 391,845 411,465 433,638 456,960 477,796 502,000 2000's 523,952 542,799 563,744 625,398 595,495 626,685 647,635 664,455 674,421 675,582 2010's 682,737 688,681 693,507 700,211 707,010 - = No Data Reported; -- = Not Applicable; NA = Not

  5. Pennsylvania Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Pennsylvania Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 166,901 172,615 178,545 1990's 186,772 191,103 193,863 198,299 206,812 209,245 214,340 215,057 216,519 223,732 2000's 228,037 225,911 226,957 227,708 231,051 233,132 231,540 234,597 233,462 233,334 2010's 233,751 233,588 235,049 237,922 239,681 - = No Data Reported; -- = Not

  6. Pennsylvania Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Pennsylvania Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6,089 6,070 6,023 1990's 6,238 6,344 6,496 6,407 6,388 6,328 6,441 6,492 6,736 7,080 2000's 6,330 6,159 5,880 5,577 5,726 5,577 5,241 4,868 4,772 4,745 2010's 4,624 5,007 5,066 5,024 5,084 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  7. Pennsylvania Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Pennsylvania Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,237,877 2,271,801 2,291,242 1990's 2,311,795 2,333,377 2,363,575 2,386,249 2,393,053 2,413,715 2,431,909 2,452,524 2,493,639 2,486,704 2000's 2,519,794 2,542,724 2,559,024 2,572,584 2,591,458 2,600,574 2,605,782 2,620,755 2,631,340 2,635,886 2010's 2,646,211 2,667,392 2,678,547

  8. Alabama Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Alabama Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 53 54,306 55,400 56,822 1990's 56,903 57,265 58,068 57,827 60,320 60,902 62,064 65,919 76,467 64,185 2000's 66,193 65,794 65,788 65,297 65,223 65,294 66,337 65,879 65,313 67,674 2010's 68,163 67,696 67,252 67,136 67,806 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  9. Alabama Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Alabama Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2 2,313 2,293 2,380 1990's 2,431 2,523 2,509 2,458 2,477 2,491 2,512 2,496 2,464 2,620 2000's 2,792 2,781 2,730 2,743 2,799 2,787 2,735 2,704 2,757 3,057 2010's 3,039 2,988 3,045 3,143 3,244 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  10. Alabama Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Alabama Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 656 662,217 668,432 683,528 1990's 686,149 700,195 711,043 730,114 744,394 751,890 766,322 781,711 788,464 775,311 2000's 805,689 807,770 806,389 809,754 806,660 809,454 808,801 796,476 792,236 785,005 2010's 778,985 772,892 767,396 765,957 769,418 - = No Data Reported; -- = Not Applicable; NA = Not

  11. Indiana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Indiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 116,571 119,458 122,803 1990's 124,919 128,223 129,973 131,925 134,336 137,162 139,097 140,515 141,307 145,631 2000's 148,411 148,830 150,092 151,586 151,943 159,649 154,322 155,885 157,223 155,615 2010's 156,557 161,293 158,213 158,965 159,596 - = No Data Reported; -- = Not Applicable; NA = Not

  12. Indiana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Indiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,497 5,696 6,196 1990's 6,439 6,393 6,358 6,508 6,314 6,250 6,586 6,920 6,635 19,069 2000's 10,866 9,778 10,139 8,913 5,368 5,823 5,350 5,427 5,294 5,190 2010's 5,145 5,338 5,204 5,178 5,098 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  13. Indiana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Indiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,250,476 1,275,401 1,306,747 1990's 1,327,772 1,358,640 1,377,023 1,402,770 1,438,483 1,463,640 1,489,647 1,509,142 1,531,914 1,570,253 2000's 1,604,456 1,613,373 1,657,640 1,644,715 1,588,738 1,707,195 1,661,186 1,677,857 1,678,158 1,662,663 2010's 1,669,026 1,707,148 1,673,132 1,681,841 1,693,267

  14. Iowa Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Iowa Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 80,797 81,294 82,549 1990's 83,047 84,387 85,325 86,452 86,918 88,585 89,663 90,643 91,300 92,306 2000's 93,836 95,485 96,496 96,712 97,274 97,767 97,823 97,979 98,144 98,416 2010's 98,396 98,541 99,113 99,017 99,182 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  15. Iowa Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Iowa Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,033 1,937 1,895 1990's 1,883 1,866 1,835 1,903 1,957 1,957 2,066 1,839 1,862 1,797 2000's 1,831 1,830 1,855 1,791 1,746 1,744 1,670 1,651 1,652 1,626 2010's 1,528 1,465 1,469 1,491 1,572 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  16. Iowa Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Iowa Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 690,532 689,655 701,687 1990's 706,842 716,088 729,081 740,722 750,678 760,848 771,109 780,746 790,162 799,015 2000's 812,323 818,313 824,218 832,230 839,415 850,095 858,915 865,553 872,980 875,781 2010's 879,713 883,733 892,123 895,414 900,420 - = No Data Reported; -- = Not Applicable; NA = Not

  17. Kansas Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Kansas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 82,934 83,810 85,143 1990's 85,539 86,874 86,840 87,735 86,457 88,163 89,168 85,018 89,654 86,003 2000's 87,007 86,592 87,397 88,030 86,640 85,634 85,686 85,376 84,703 84,715 2010's 84,446 84,874 84,673 84,969 85,867 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  18. Kansas Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Kansas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 4,440 4,314 4,366 1990's 4,357 3,445 3,296 4,369 3,560 3,079 2,988 7,014 10,706 5,861 2000's 8,833 9,341 9,891 9,295 8,955 8,300 8,152 8,327 8,098 7,793 2010's 7,664 7,954 7,970 7,877 7,429 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  19. Kansas Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Kansas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 725,676 733,101 731,792 1990's 747,081 753,839 762,545 777,658 773,357 797,524 804,213 811,975 841,843 824,803 2000's 833,662 836,486 843,353 850,464 855,272 856,761 862,203 858,304 853,125 855,454 2010's 853,842 854,730 854,800 858,572 861,092 - = No Data Reported; -- = Not Applicable; NA = Not

  20. Kentucky Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Kentucky Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 63,024 63,971 65,041 1990's 67,086 68,461 69,466 71,998 73,562 74,521 76,079 77,693 80,147 80,283 2000's 81,588 81,795 82,757 84,110 84,493 85,243 85,236 85,210 84,985 83,862 2010's 84,707 84,977 85,129 85,999 85,318 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  1. Kentucky Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Kentucky Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,391 1,436 1,443 1990's 1,544 1,587 1,608 1,585 1,621 1,630 1,633 1,698 1,864 1,813 2000's 1,801 1,701 1,785 1,695 1,672 1,698 1,658 1,599 1,585 1,715 2010's 1,742 1,705 1,720 1,767 1,780 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  2. Kentucky Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Kentucky Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 596,320 606,106 614,058 1990's 624,477 633,942 644,281 654,664 668,774 685,481 696,989 713,509 726,960 735,371 2000's 744,816 749,106 756,234 763,290 767,022 770,080 770,171 771,047 753,531 754,761 2010's 758,129 759,584 757,790 761,575 760,131 - = No Data Reported; -- = Not Applicable; NA = Not

  3. Louisiana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Louisiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 67,382 66,472 64,114 1990's 62,770 61,574 61,030 62,055 62,184 62,930 62,101 62,270 63,029 62,911 2000's 62,710 62,241 62,247 63,512 60,580 58,409 57,097 57,127 57,066 58,396 2010's 58,562 58,749 63,381 59,147 58,611 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  4. Louisiana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Louisiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,617 1,503 1,531 1990's 1,504 1,469 1,452 1,592 1,737 1,383 1,444 1,406 1,380 1,397 2000's 1,318 1,440 1,357 1,291 1,460 1,086 962 945 988 954 2010's 942 920 963 916 883 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  5. Louisiana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Louisiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 952,079 946,970 934,472 1990's 934,007 936,423 940,403 941,294 945,387 957,558 945,967 962,786 962,436 961,925 2000's 964,133 952,753 957,048 958,795 940,400 905,857 868,353 879,612 886,084 889,570 2010's 893,400 897,513 963,688 901,635 899,378 - = No Data Reported; -- = Not Applicable; NA = Not

  6. Maine Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Maine Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,435 3,731 3,986 1990's 4,250 4,455 4,838 4,979 5,297 5,819 6,414 6,606 6,662 6,582 2000's 6,954 6,936 7,375 7,517 7,687 8,178 8,168 8,334 8,491 8,815 2010's 9,084 9,681 10,179 11,415 11,810 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  7. Maine Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Maine Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 12,134 11,933 11,902 1990's 12,000 12,424 13,766 13,880 14,104 14,917 14,982 15,221 15,646 15,247 2000's 17,111 17,302 17,921 18,385 18,707 18,633 18,824 18,921 19,571 20,806 2010's 21,142 22,461 23,555 24,765 27,047 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  8. Maryland Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Maryland Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 51,252 53,045 54,740 1990's 55,576 61,878 62,858 63,767 64,698 66,094 69,991 69,056 67,850 69,301 2000's 70,671 70,691 71,824 72,076 72,809 73,780 74,584 74,856 75,053 75,771 2010's 75,192 75,788 75,799 77,117 77,846 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  9. Maryland Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Maryland Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,222 5,397 5,570 1990's 5,646 520 514 496 516 481 430 479 1,472 536 2000's 329 795 1,434 1,361 1,354 1,325 1,340 1,333 1,225 1,234 2010's 1,255 1,226 1,163 1,173 1,179 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  10. Maryland Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Maryland Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 755,294 760,754 767,219 1990's 774,707 782,373 894,677 807,204 824,137 841,772 871,012 890,195 901,455 939,029 2000's 941,384 959,772 978,319 987,863 1,009,455 1,024,955 1,040,941 1,053,948 1,057,521 1,067,807 2010's 1,071,566 1,077,168 1,078,978 1,099,272 1,101,292 - = No Data Reported; -- = Not

  11. Massachusetts Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Massachusetts Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 84,636 93,005 92,252 1990's 85,775 88,746 85,873 102,187 92,744 104,453 105,889 107,926 108,832 113,177 2000's 117,993 120,984 122,447 123,006 125,107 120,167 126,713 128,965 242,693 153,826 2010's 144,487 138,225 142,825 144,246 139,556 - = No Data Reported; -- = Not Applicable;

  12. Massachusetts Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Massachusetts Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,626 7,199 13,057 1990's 6,539 5,006 8,723 7,283 8,019 10,447 10,952 11,058 11,245 8,027 2000's 8,794 9,750 9,090 11,272 10,949 12,019 12,456 12,678 36,928 19,208 2010's 12,751 10,721 10,840 11,063 10,946 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  13. Massachusetts Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Massachusetts Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,082,777 1,100,635 1,114,920 1990's 1,118,429 1,127,536 1,137,911 1,155,443 1,179,869 1,180,860 1,188,317 1,204,494 1,212,486 1,232,887 2000's 1,278,781 1,283,008 1,295,952 1,324,715 1,306,142 1,297,508 1,348,848 1,361,470 1,236,480 1,370,353 2010's 1,389,592 1,408,314 1,447,947

  14. Michigan Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Michigan Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 178,469 185,961 191,474 1990's 195,766 198,890 201,561 204,453 207,629 211,817 214,843 222,726 224,506 227,159 2000's 230,558 225,109 247,818 246,123 246,991 253,415 254,923 253,139 252,382 252,017 2010's 249,309 249,456 249,994 250,994 253,127 - = No Data Reported; -- = Not Applicable; NA = Not

  15. Michigan Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Michigan Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10,885 11,117 11,452 1990's 11,500 11,446 11,460 11,425 11,308 11,454 11,848 12,233 11,888 14,527 2000's 11,384 11,210 10,468 10,378 10,088 10,049 9,885 9,728 10,563 18,186 2010's 9,332 9,088 8,833 8,497 8,156 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  16. Michigan Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Michigan Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,452,554 2,491,149 2,531,304 1990's 2,573,570 2,609,561 2,640,579 2,677,085 2,717,683 2,767,190 2,812,876 2,859,483 2,903,698 2,949,628 2000's 2,999,737 3,011,205 3,110,743 3,140,021 3,161,370 3,187,583 3,193,920 3,188,152 3,172,623 3,169,026 2010's 3,152,468 3,153,895 3,161,033 3,180,349

  17. Minnesota Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Minnesota Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 88,789 90,256 92,916 1990's 95,474 97,388 99,707 93,062 102,857 103,874 105,531 108,686 110,986 114,127 2000's 116,529 119,007 121,751 123,123 125,133 126,310 129,149 128,367 130,847 131,801 2010's 132,163 132,938 134,394 135,557 136,382 - = No Data Reported; -- = Not Applicable; NA = Not Available;

  18. Minnesota Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Minnesota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,585 2,670 2,638 1990's 2,574 2,486 2,515 2,477 2,592 2,531 2,564 2,233 2,188 2,267 2000's 2,025 1,996 2,029 2,074 2,040 1,432 1,257 1,146 1,131 2,039 2010's 2,106 1,770 1,793 1,870 1,878 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  19. Minnesota Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Minnesota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 872,148 894,380 911,001 1990's 946,107 970,941 998,201 1,074,631 1,049,263 1,080,009 1,103,709 1,134,019 1,161,423 1,190,190 2000's 1,222,397 1,249,748 1,282,751 1,308,143 1,338,061 1,364,237 1,401,362 1,401,623 1,413,162 1,423,703 2010's 1,429,681 1,436,063 1,445,824 1,459,134 1,472,663 - = No

  20. Mississippi Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Mississippi Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 43,362 44,170 44,253 1990's 43,184 43,693 44,313 45,310 43,803 45,444 46,029 47,311 45,345 47,620 2000's 50,913 51,109 50,468 50,928 54,027 54,936 55,741 56,155 55,291 50,713 2010's 50,537 50,636 50,689 50,153 50,238 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  1. Mississippi Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Mississippi Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,312 1,263 1,282 1990's 1,317 1,314 1,327 1,324 1,313 1,298 1,241 1,199 1,165 1,246 2000's 1,199 1,214 1,083 1,161 996 1,205 1,181 1,346 1,132 1,141 2010's 980 982 936 933 943 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  2. Mississippi Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Mississippi Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 370,094 372,238 376,353 1990's 382,251 386,264 392,155 398,472 405,312 415,123 418,442 423,397 415,673 426,352 2000's 434,501 438,069 435,146 438,861 445,212 445,856 437,669 445,043 443,025 437,715 2010's 436,840 442,479 442,840 445,589 444,423 - = No Data Reported; -- = Not

  3. Missouri Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Missouri Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 96,711 97,939 99,721 1990's 105,164 117,675 125,174 125,571 132,378 130,318 133,445 135,553 135,417 133,464 2000's 133,969 135,968 137,924 140,057 141,258 142,148 143,632 142,965 141,529 140,633 2010's 138,670 138,214 144,906 142,495 143,024 - = No Data Reported; -- = Not Applicable; NA = Not

  4. Missouri Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Missouri Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,832 2,880 3,063 1990's 3,140 3,096 2,989 3,040 3,115 3,033 3,408 3,097 3,151 3,152 2000's 3,094 3,085 2,935 3,115 3,600 3,545 3,548 3,511 3,514 3,573 2010's 3,541 3,307 3,692 3,538 3,497 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  5. Missouri Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Missouri Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,180,546 1,194,985 1,208,523 1990's 1,213,305 1,211,342 1,220,203 1,225,921 1,281,007 1,259,102 1,275,465 1,293,032 1,307,563 1,311,865 2000's 1,324,282 1,326,160 1,340,726 1,343,614 1,346,773 1,348,743 1,353,892 1,354,173 1,352,015 1,348,781 2010's 1,348,549 1,342,920 1,389,910 1,357,740

  6. Montana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Montana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 21,382 22,246 22,219 1990's 23,331 23,185 23,610 24,373 25,349 26,329 26,374 27,457 28,065 28,424 2000's 29,215 29,429 30,250 30,814 31,357 31,304 31,817 32,472 33,008 33,731 2010's 34,002 34,305 34,504 34,909 35,205 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  7. Montana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Montana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 167,883 171,785 171,156 1990's 174,384 177,726 182,641 188,879 194,357 203,435 205,199 209,806 218,851 222,114 2000's 224,784 226,171 229,015 232,839 236,511 240,554 245,883 247,035 253,122 255,472 2010's 257,322 259,046 259,957 262,122 265,849 - = No Data Reported; -- = Not Applicable; NA = Not

  8. Wyoming Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Wyoming Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 15,342 15,093 14,012 1990's 13,767 14,931 15,064 15,315 15,348 15,580 17,036 15,907 16,171 16,317 2000's 16,366 16,027 16,170 17,164 17,490 17,904 18,016 18,062 19,286 19,843 2010's 19,977 20,146 20,387 20,617 20,894 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  9. Wyoming Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Wyoming Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 113,175 112,126 113,129 1990's 113,598 113,463 114,793 116,027 117,385 119,544 131,910 125,740 127,324 127,750 2000's 129,274 129,897 133,445 135,441 137,434 140,013 142,385 143,644 152,439 153,062 2010's 153,852 155,181 157,226 158,889 160,896 - = No Data Reported; -- = Not Applicable; NA = Not

  10. Alaska Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Alaska Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 11 11,484 11,649 11,806 1990's 11,921 12,071 12,204 12,359 12,475 12,584 12,732 12,945 13,176 13,409 2000's 13,711 14,002 14,342 14,502 13,999 14,120 14,384 13,408 12,764 13,215 2010's 12,998 13,027 13,133 13,246 13,399 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  11. Alaska Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Alaska Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 66 67,648 68,612 69,540 1990's 70,808 72,565 74,268 75,842 77,670 79,474 81,348 83,596 86,243 88,924 2000's 91,297 93,896 97,077 100,404 104,360 108,401 112,269 115,500 119,039 120,124 2010's 121,166 121,736 122,983 124,411 126,416 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  12. Arizona Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Arizona Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 46 46,702 46,636 46,776 1990's 47,292 53,982 47,781 47,678 48,568 49,145 49,693 50,115 51,712 53,022 2000's 54,056 54,724 56,260 56,082 56,186 56,572 57,091 57,169 57,586 57,191 2010's 56,676 56,547 56,532 56,585 56,649 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  13. Arizona Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Arizona Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 545 567,962 564,195 572,461 1990's 586,866 642,659 604,899 610,337 635,335 661,192 689,597 724,911 764,167 802,469 2000's 846,016 884,789 925,927 957,442 993,885 1,042,662 1,088,574 1,119,266 1,128,264 1,130,047 2010's 1,138,448 1,146,286 1,157,688 1,172,003 1,186,794 - = No Data Reported; -- = Not

  14. Arkansas Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Arkansas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 60 60,355 61,630 61,848 1990's 61,530 61,731 62,221 62,952 63,821 65,490 67,293 68,413 69,974 71,389 2000's 72,933 71,875 71,530 71,016 70,655 69,990 69,475 69,495 69,144 69,043 2010's 67,987 67,815 68,765 68,791 69,011 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  15. Arkansas Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Arkansas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1 1,410 1,151 1,412 1990's 1,396 1,367 1,319 1,364 1,417 1,366 1,488 1,336 1,300 1,393 2000's 1,414 1,122 1,407 1,269 1,223 1,120 1,120 1,055 1,104 1,025 2010's 1,079 1,133 990 1,020 1,009 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  16. Arkansas Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Arkansas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 475 480,839 485,112 491,110 1990's 488,850 495,148 504,722 513,466 521,176 531,182 539,952 544,460 550,017 554,121 2000's 560,055 552,716 553,192 553,211 554,844 555,861 555,905 557,966 556,746 557,355 2010's 549,970 551,795 549,959 549,764 549,034 - = No Data Reported; -- = Not Applicable; NA =

  17. California Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) California Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 413 404,507 407,435 410,231 1990's 415,073 421,278 412,467 411,648 411,140 411,535 408,294 406,803 588,224 416,791 2000's 413,003 416,036 420,690 431,795 432,367 434,899 442,052 446,267 447,160 441,806 2010's 439,572 440,990 442,708 444,342 443,115 - = No Data Reported; -- = Not Applicable; NA =

  18. California Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) California Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 31 44,764 44,680 46,243 1990's 46,048 44,865 40,528 42,748 38,750 38,457 36,613 35,830 36,235 36,435 2000's 35,391 34,893 33,725 34,617 41,487 40,226 38,637 39,134 39,591 38,746 2010's 38,006 37,575 37,686 37,996 37,548 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  19. California Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) California Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 7,626 7,904,858 8,113,034 8,313,776 1990's 8,497,848 8,634,774 8,680,613 8,726,187 8,790,733 8,865,541 8,969,308 9,060,473 9,181,928 9,331,206 2000's 9,370,797 9,603,122 9,726,642 9,803,311 9,957,412 10,124,433 10,329,224 10,439,220 10,515,162 10,510,950 2010's 10,542,584 10,625,190 10,681,916

  20. Colorado Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Colorado Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 108 109,770 110,769 112,004 1990's 112,661 113,945 114,898 115,924 115,994 118,502 121,221 123,580 125,178 129,041 2000's 131,613 134,393 136,489 138,621 138,543 137,513 139,746 141,420 144,719 145,624 2010's 145,460 145,837 145,960 150,145 150,235 - = No Data Reported; -- = Not Applicable; NA = Not

  1. Colorado Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Colorado Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1 896 923 976 1990's 1,018 1,074 1,108 1,032 1,176 1,528 2,099 2,923 3,349 4,727 2000's 4,994 4,729 4,337 4,054 4,175 4,318 4,472 4,592 4,816 5,084 2010's 6,232 6,529 6,906 7,293 7,823 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  2. Colorado Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Colorado Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 925 942,571 955,810 970,512 1990's 983,592 1,002,154 1,022,542 1,044,699 1,073,308 1,108,899 1,147,743 1,183,978 1,223,433 1,265,032 2000's 1,315,619 1,365,413 1,412,923 1,453,974 1,496,876 1,524,813 1,558,911 1,583,945 1,606,602 1,622,434 2010's 1,634,587 1,645,716 1,659,808 1,672,312 1,690,581 -

  3. Connecticut Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Connecticut Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 38 40,886 41,594 43,703 1990's 45,364 45,925 46,859 45,529 45,042 45,935 47,055 48,195 47,110 49,930 2000's 52,384 49,815 49,383 50,691 50,839 52,572 52,982 52,389 53,903 54,510 2010's 54,842 55,028 55,407 55,500 56,591 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  4. Connecticut Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Connecticut Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2 2,709 2,818 2,908 1990's 3,061 2,921 2,923 2,952 3,754 3,705 3,435 3,459 3,441 3,465 2000's 3,683 3,881 3,716 3,625 3,470 3,437 3,393 3,317 3,196 3,138 2010's 3,063 3,062 3,148 4,454 4,217 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  5. Connecticut Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Connecticut Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400 411,349 417,831 424,036 1990's 428,912 430,078 432,244 427,761 428,157 431,909 433,778 436,119 438,716 442,457 2000's 458,388 458,404 462,574 466,913 469,332 475,221 478,849 482,902 487,320 489,349 2010's 490,185 494,970 504,138 513,492 522,658 - = No Data Reported; -- = Not

  6. Delaware Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Delaware Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6 6,180 6,566 7,074 1990's 7,485 7,895 8,173 8,409 8,721 9,133 9,518 9,807 10,081 10,441 2000's 9,639 11,075 11,463 11,682 11,921 12,070 12,345 12,576 12,703 12,839 2010's 12,861 12,931 12,997 13,163 13,352 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  7. Delaware Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Delaware Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 81 82,829 84,328 86,428 1990's 88,894 91,467 94,027 96,914 100,431 103,531 106,548 109,400 112,507 115,961 2000's 117,845 122,829 126,418 129,870 133,197 137,115 141,276 145,010 147,541 149,006 2010's 150,458 152,005 153,307 155,627 158,502 - = No Data Reported; -- = Not Applicable; NA = Not

  8. Florida Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Florida Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 41 42,376 43,178 43,802 1990's 43,674 45,012 45,123 47,344 47,851 46,459 47,578 48,251 46,778 50,052 2000's 50,888 53,118 53,794 55,121 55,324 55,479 55,259 57,320 58,125 59,549 2010's 60,854 61,582 63,477 64,772 67,460 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  9. Florida Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Florida Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 442 444,848 446,690 452,544 1990's 457,648 467,221 471,863 484,816 497,777 512,365 521,674 532,790 542,770 556,628 2000's 571,972 590,221 603,690 617,373 639,014 656,069 673,122 682,996 679,265 674,090 2010's 675,551 679,199 686,994 694,210 703,535 - = No Data Reported; -- = Not Applicable; NA = Not

  10. Georgia Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Georgia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 94 98,809 102,277 106,690 1990's 108,295 109,659 111,423 114,889 117,980 120,122 123,200 123,367 126,050 225,020 2000's 128,275 130,373 128,233 129,867 128,923 128,389 127,843 127,832 126,804 127,347 2010's 124,759 123,454 121,243 126,060 122,573 - = No Data Reported; -- = Not Applicable; NA = Not

  11. Georgia Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Georgia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3 3,034 3,144 3,079 1990's 3,153 3,124 3,186 3,302 3,277 3,261 3,310 3,310 3,262 5,580 2000's 3,294 3,330 3,219 3,326 3,161 3,543 3,053 2,913 2,890 2,254 2010's 2,174 2,184 2,112 2,242 2,481 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  12. Georgia Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Georgia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,190 1,237,201 1,275,128 1,308,972 1990's 1,334,935 1,363,723 1,396,860 1,430,626 1,460,141 1,495,992 1,538,458 1,553,948 1,659,730 1,732,865 2000's 1,680,749 1,737,850 1,735,063 1,747,017 1,752,346 1,773,121 1,726,239 1,793,650 1,791,256 1,744,934 2010's 1,740,587 1,740,006 1,739,543 1,805,425

  13. Hawaii Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Hawaii Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,896 2,852 2,842 1990's 2,837 2,786 2,793 3,222 2,805 2,825 2,823 2,783 2,761 2,763 2000's 2,768 2,777 2,781 2,804 2,578 2,572 2,548 2,547 2,540 2,535 2010's 2,551 2,560 2,545 2,627 2,789 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  14. Hawaii Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Hawaii Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 28,502 28,761 28,970 1990's 29,137 29,701 29,805 29,984 30,614 30,492 31,017 30,990 30,918 30,708 2000's 30,751 30,794 30,731 30,473 26,255 26,219 25,982 25,899 25,632 25,466 2010's 25,389 25,305 25,184 26,374 28,919 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  15. Idaho Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Idaho Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 17,482 18,454 18,813 1990's 19,452 20,328 21,145 21,989 22,999 24,150 25,271 26,436 27,697 28,923 2000's 30,018 30,789 31,547 32,274 33,104 33,362 33,625 33,767 37,320 38,245 2010's 38,506 38,912 39,202 39,722 40,229 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  16. Idaho Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Idaho Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 104,824 111,532 113,898 1990's 113,954 126,282 136,121 148,582 162,971 175,320 187,756 200,165 213,786 227,807 2000's 240,399 251,004 261,219 274,481 288,380 301,357 316,915 323,114 336,191 342,277 2010's 346,602 350,871 353,963 359,889 367,394 - = No Data Reported; -- = Not Applicable; NA = Not

  17. Illinois Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Illinois Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241,367 278,473 252,791 1990's 257,851 261,107 263,988 268,104 262,308 264,756 265,007 268,841 271,585 274,919 2000's 279,179 278,506 279,838 281,877 273,967 276,763 300,606 296,465 298,418 294,226 2010's 291,395 293,213 297,523 282,743 294,391 - = No Data Reported; -- = Not Applicable; NA = Not

  18. Illinois Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Illinois Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 19,460 20,015 25,161 1990's 25,991 26,489 27,178 27,807 25,788 25,929 29,493 28,472 28,063 27,605 2000's 27,348 27,421 27,477 26,698 29,187 29,887 26,109 24,000 23,737 23,857 2010's 25,043 23,722 23,390 23,804 23,829 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  19. Illinois Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Illinois Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,170,364 3,180,199 3,248,117 1990's 3,287,091 3,320,285 3,354,679 3,388,983 3,418,052 3,452,975 3,494,545 3,521,707 3,556,736 3,594,071 2000's 3,631,762 3,670,693 3,688,281 3,702,308 3,754,132 3,975,961 3,812,121 3,845,441 3,869,308 3,839,438 2010's 3,842,206 3,855,942 3,878,806 3,838,120

  20. Rhode Island Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Rhode Island Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 15,128 16,096 16,924 1990's 17,765 18,430 18,607 21,178 21,208 21,472 21,664 21,862 22,136 22,254 2000's 22,592 22,815 23,364 23,270 22,994 23,082 23,150 23,007 23,010 22,988 2010's 23,049 23,177 23,359 23,742 23,934 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  1. Rhode Island Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Rhode Island Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 180,656 185,861 190,796 1990's 195,100 196,438 197,926 198,563 200,959 202,947 204,259 212,777 208,208 211,097 2000's 214,474 216,781 219,769 221,141 223,669 224,320 225,027 223,589 224,103 224,846 2010's 225,204 225,828 228,487 231,763 233,786 - = No Data Reported; -- = Not

  2. South Carolina Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) South Carolina Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 35,414 37,075 38,856 1990's 39,904 39,999 40,968 42,191 45,487 47,293 48,650 50,817 52,237 53,436 2000's 54,794 55,257 55,608 55,909 56,049 56,974 57,452 57,544 56,317 55,850 2010's 55,853 55,846 55,908 55,997 56,172 - = No Data Reported; -- = Not Applicable; NA = Not Available; W

  3. South Carolina Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) South Carolina Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,256 1,273 1,307 1990's 1,384 1,400 1,568 1,625 1,928 1,802 1,759 1,764 1,728 1,768 2000's 1,715 1,702 1,563 1,574 1,528 1,535 1,528 1,472 1,426 1,358 2010's 1,325 1,329 1,435 1,452 1,426 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  4. South Carolina Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) South Carolina Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 302,321 313,831 327,527 1990's 339,486 344,763 357,818 370,411 416,773 412,259 426,088 443,093 460,141 473,799 2000's 489,340 501,161 508,686 516,362 527,008 541,523 554,953 570,213 561,196 565,774 2010's 570,797 576,594 583,633 593,286 604,743 - = No Data Reported; -- = Not

  5. South Dakota Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) South Dakota Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 12,480 12,438 12,771 1990's 13,443 13,692 14,133 16,523 15,539 16,285 16,880 17,432 17,972 18,453 2000's 19,100 19,378 19,794 20,070 20,457 20,771 21,149 21,502 21,819 22,071 2010's 22,267 22,570 22,955 23,214 23,591 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  6. South Dakota Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) South Dakota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 101,468 102,084 103,538 1990's 105,436 107,846 110,291 128,029 119,544 124,152 127,269 130,307 133,095 136,789 2000's 142,075 144,310 147,356 150,725 148,105 157,457 160,481 163,458 165,694 168,096 2010's 169,838 170,877 173,856 176,204 179,042 - = No Data Reported; -- = Not

  7. Tennessee Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Tennessee Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 77,104 81,159 84,040 1990's 88,753 89,863 91,999 94,860 97,943 101,561 103,867 105,925 109,772 112,978 2000's 115,691 118,561 120,130 131,916 125,042 124,755 126,970 126,324 128,007 127,704 2010's 127,914 128,969 130,139 131,091 131,001 - = No Data Reported; -- = Not Applicable; NA = Not Available;

  8. Tennessee Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Tennessee Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,206 2,151 2,555 1990's 2,361 2,369 2,425 2,512 2,440 2,393 2,306 2,382 5,149 2,159 2000's 2,386 2,704 2,657 2,755 2,738 2,498 2,545 2,656 2,650 2,717 2010's 2,702 2,729 2,679 2,581 2,595 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  9. Tennessee Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Tennessee Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 534,882 565,856 599,042 1990's 627,031 661,105 696,140 733,363 768,421 804,724 841,232 867,793 905,757 937,896 2000's 969,537 993,363 1,009,225 1,022,628 1,037,429 1,049,307 1,063,328 1,071,756 1,084,102 1,083,573 2010's 1,085,387 1,089,009 1,084,726 1,094,122 1,106,681 - = No Data Reported; -- =

  10. Texas Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Texas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 294,879 284,013 270,227 1990's 268,181 269,411 292,990 297,516 306,376 325,785 329,287 332,077 320,922 314,598 2000's 315,906 314,858 317,446 320,786 322,242 322,999 329,918 326,812 324,671 313,384 2010's 312,277 314,041 314,811 314,036 317,217 - = No Data Reported; -- = Not Applicable; NA = Not

  11. Texas Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Texas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 4,852 4,427 13,383 1990's 13,659 13,770 5,481 5,823 5,222 9,043 8,796 5,339 5,318 5,655 2000's 11,613 10,047 9,143 9,015 9,359 9,136 8,664 11,063 5,568 8,581 2010's 8,779 8,713 8,953 8,525 8,406 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  12. Texas Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Texas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,155,948 3,166,168 3,201,316 1990's 3,232,849 3,274,482 3,285,025 3,346,809 3,350,314 3,446,120 3,501,853 3,543,027 3,600,505 3,613,864 2000's 3,704,501 3,738,260 3,809,370 3,859,647 3,939,101 3,984,481 4,067,508 4,156,991 4,205,412 4,248,613 2010's 4,288,495 4,326,156 4,370,057 4,424,103 4,469,282 -

  13. Table 4

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

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

  14. Table 4

    Gasoline and Diesel Fuel Update (EIA)

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

  15. 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.

  16. Characteristics of Strong Programs | Department of Energy

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

    Characteristics of Strong Programs Characteristics of Strong Programs Existing financing programs offer a number of important lessons on effective program design. Some characteristics of strong financing programs drawn from past program experience are described below. Engage Contractor Networks The programs with the highest volume of loans have strong contractor networks and regular program communication with those contractors. Significant time and effort are often expended to make sure the

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

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

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

  18. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  19. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  20. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  1. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  2. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  3. 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.

  4. 1999 Commercial Buildings Characteristics

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

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

  5. " Million U.S. Housing Units"

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

    8 Water Heating Characteristics by Number of Household Members, 2005" " Million U.S. ... Members","4 Members","5 or More Members" "Water Heating Characteristics" ...

  6. Evaluation of bulk paint worker exposure to solvents at household hazardous waste collection events

    SciTech Connect (OSTI)

    Cameron, M.

    1995-09-01

    In fiscal year 93/94, over 250 governmental agencies were involved in the collection of household hazardous wastes in the State of California. During that time, over 3,237,000 lbs. of oil based paint were collected in 9,640 drums. Most of this was in lab pack drums, which can only hold up to 20 one gallon cans. Cost for disposal of such drums is approximately $1000. In contrast, during the same year, 1,228,000 lbs. of flammable liquid were collected in 2,098 drums in bulk form. Incineration of bulked flammable liquids is approximately $135 per drum. Clearly, it is most cost effective to bulk flammable liquids at household hazardous waste events. Currently, this is the procedure used at most Temporary Household Hazardous Waste Collection Facilities (THHWCFs). THHWCFs are regulated by the Department of Toxic Substances Control (DTSC) under the new Permit-by Rule Regulations. These regulations specify certain requirements regarding traffic flow, emergency response notifications and prevention of exposure to the public. The regulations require that THHWCF operators bulk wastes only when the public is not present. [22 CCR, section 67450.4 (e) (2) (A)].Santa Clara County Environmental Health Department sponsors local THHWCF`s and does it`s own bulking. In order to save time and money, a variance from the regulation was requested and an employee monitoring program was initiated to determine actual exposure to workers. Results are presented.

  7. 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.

  8. Verification Challenges at Low Numbers

    SciTech Connect (OSTI)

    Benz, Jacob M.; Booker, Paul M.; McDonald, Benjamin S.

    2013-06-01

    Many papers have dealt with the political difficulties and ramifications of deep nuclear arms reductions, and the issues of “Going to Zero”. Political issues include extended deterrence, conventional weapons, ballistic missile defense, and regional and geo-political security issues. At each step on the road to low numbers, the verification required to ensure compliance of all parties will increase significantly. Looking post New START, the next step will likely include warhead limits in the neighborhood of 1000 . Further reductions will include stepping stones at1000 warheads, 100’s of warheads, and then 10’s of warheads before final elimination could be considered of the last few remaining warheads and weapons. This paper will focus on these three threshold reduction levels, 1000, 100’s, 10’s. For each, the issues and challenges will be discussed, potential solutions will be identified, and the verification technologies and chain of custody measures that address these solutions will be surveyed. It is important to note that many of the issues that need to be addressed have no current solution. In these cases, the paper will explore new or novel technologies that could be applied. These technologies will draw from the research and development that is ongoing throughout the national laboratory complex, and will look at technologies utilized in other areas of industry for their application to arms control verification.

  9. 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.

  10. 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.

  11. 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

  12. Picosecond pulses produced by mode locking a Nd:glass laser with Kodak dye number26

    SciTech Connect (OSTI)

    Schiller, N.H.; Foresti, M.; Alfano, R.R.

    1985-05-01

    Kodak dye number26 was used to generate picosecond laser pulses by mode locking a Nd:glass laser. The intensity profiles and characteristics of the pulses were compared with those of pulses emitted using dyes number5 and number9860.

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

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

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

  14. 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.

  15. 1997 Housing Characteristics Tables Home Office Equipment Tables

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

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

  16. Developing and Enhancing Workforce Training Programs: Number...

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

    Developing and Enhancing Workforce Training Programs: Number of Projects by State Developing and Enhancing Workforce Training Programs: Number of Projects by State Map of the ...

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

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

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

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

  4. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires

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

  5. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  6. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  7. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  8. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  9. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  10. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  11. Climate Zone Number 5 | Open Energy Information

    Open Energy Info (EERE)

    Climate Zone Number 5 Jump to: navigation, search A type of climate defined in the ASHRAE 169-2006 standard. Climate Zone Number 5 is defined as Cool- Humid(5A) with IP Units 5400...

  12. ARM - Measurement - Cloud particle number concentration

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

    from you Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud particle number concentration The total number of cloud particles present in any given volume...

  13. Buildings Energy Data Book: 2.2 Residential Sector Characteristics

    Buildings Energy Data Book [EERE]

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

  14. Crude Oil Characteristics Research

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

    SAE Plan June 29, 2015 Page 1 Crude Oil Characteristics Research Sampling, Analysis and Experiment (SAE) Plan The U.S. is experiencing a renaissance in oil and gas production. The ...

  15. ARM - Measurement - Soil characteristics

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

    characteristics 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 : Soil characteristics Includes available water capacity, bulk density, permeability, porosity, rock fragment classification, rock fragment volume, percent clay, percent sand, and texture classification Categories Surface Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer

  16. On the binary expansions of algebraic numbers

    SciTech Connect (OSTI)

    Bailey, David H.; Borwein, Jonathan M.; Crandall, Richard E.; Pomerance, Carl

    2003-07-01

    Employing concepts from additive number theory, together with results on binary evaluations and partial series, we establish bounds on the density of 1's in the binary expansions of real algebraic numbers. A central result is that if a real y has algebraic degree D > 1, then the number {number_sign}(|y|, N) of 1-bits in the expansion of |y| through bit position N satisfies {number_sign}(|y|, N) > CN{sup 1/D} for a positive number C (depending on y) and sufficiently large N. This in itself establishes the transcendency of a class of reals {summation}{sub n{ge}0} 1/2{sup f(n)} where the integer-valued function f grows sufficiently fast; say, faster than any fixed power of n. By these methods we re-establish the transcendency of the Kempner--Mahler number {summation}{sub n{ge}0}1/2{sup 2{sup n}}, yet we can also handle numbers with a substantially denser occurrence of 1's. Though the number z = {summation}{sub n{ge}0}1/2{sup n{sup 2}} has too high a 1's density for application of our central result, we are able to invoke some rather intricate number-theoretical analysis and extended computations to reveal aspects of the binary structure of z{sup 2}.

  17. 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

  18. Utah Natural Gas Number of Gas and Gas Condensate Wells (Number...

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

    Gas and Gas Condensate Wells (Number of Elements) Utah Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 ...

  19. Identification of Export Control Classification Number - ITER

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

    of Export Control Classification Number - ITER (April 2012) As the "Shipper of Record" ... be shipped from the United States to the ITER International Organization in Cadarache, ...

  20. Particle Number & Particulate Mass Emissions Measurements on...

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

    Heavy-duty Engine using the PMP Methodologies Particle Number & Particulate Mass Emissions Measurements on a 'Euro VI' Heavy-duty Engine using the PMP Methodologies Poster ...

  1. Calculating Atomic Number Densities for Uranium

    Energy Science and Technology Software Center (OSTI)

    1993-01-01

    Provides method to calculate atomic number densities of selected uranium compounds and hydrogenous moderators for use in nuclear criticality safety analyses at gaseous diffusion uranium enrichment facilities.

  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. 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).

  4. 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.

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

    SciTech Connect (OSTI)

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

    2014-10-14

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

  6. 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.

  7. Low Mach Number Models in Computational Astrophysics

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

    Ann Almgren Low Mach Number Models in Computational Astrophysics February 4, 2014 Ann Almgren. Berkeley Lab Downloads Almgren-nug2014.pdf | Adobe Acrobat PDF file Low Mach Number Models in Computational Astrophysics - Ann Almgren, Berkeley Lab Last edited: 2016-04-29 11:34:50

  8. Compendium of Experimental Cetane Number Data

    SciTech Connect (OSTI)

    Murphy, M. J.; Taylor, J. D.; McCormick, R. L.

    2004-09-01

    In this report, we present a compilation of reported cetane numbers for pure chemical compounds. The compiled database contains cetane values for 299 pure compounds, including 156 hydrocarbons and 143 oxygenates. Cetane number is a relative ranking of fuels based on the amount of time between fuel injection and ignition. The cetane number is typically measured either in a combustion bomb or in a single-cylinder research engine. This report includes cetane values from several different measurement techniques - each of which has associated uncertainties. Additionally, many of the reported values are determined by measuring blending cetane numbers, which introduces significant error. In many cases, the measurement technique is not reported nor is there any discussion about the purity of the compounds. Nonetheless, the data in this report represent the best pure compound cetane number values available from the literature as of August 2004.

  9. 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.

  10. Survey of lepton number violation via effective operators

    SciTech Connect (OSTI)

    Gouvea, Andre de; Jenkins, James [Northwestern University, Department of Physics and Astronomy, 2145 Sheridan Road, Evanston, Illinois 60208 (United States)

    2008-01-01

    We survey 129 lepton number violating effective operators, consistent with the minimal standard model gauge group and particle content, of mass dimension up to and including 11. Upon requiring that each one radiatively generates the observed neutrino masses, we extract an associated characteristic cutoff energy scale which we use to calculate other observable manifestations of these operators for a number of current and future experimental probes, concentrating on lepton number violating phenomena. These include searches for neutrinoless double-beta decay and rare meson, lepton, and gauge boson decays. We also consider searches at hadron/lepton collider facilities in anticipation of the CERN LHC and the future ILC. We find that some operators are already disfavored by current data, while more are ripe to be probed by next-generation experiments. We also find that our current understanding of lepton mixing disfavors a subset of higher dimensional operators. While neutrinoless double-beta decay is the most promising signature of lepton number violation for the majority of operators, a handful is best probed by other means. We argue that a combination of constraints from various independent experimental sources will help to pinpoint the ''correct'' model of neutrino mass, or at least aid in narrowing down the set of possibilities.

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

    SciTech Connect (OSTI)

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

    2014-12-01

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

  12. Mo Year Report Period: EIA ID NUMBER:

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

    Mo Year Report Period: EIA ID NUMBER: http:www.eia.govsurveyformeia14instructions.pdf Mailing Address: Secure File Transfer option available at: (e.g., PO Box, RR) https:...

  13. 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

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

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

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

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

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

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

  16. Identification of Export Control Classification Number - ITER

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

    of Export Control Classification Number - ITER (April 2012) As the "Shipper of Record" please provide the appropriate Export Control Classification Number (ECCN) for the products (equipment, components and/or materials) and if applicable the nonproprietary associated installation/maintenance documentation that will be shipped from the United States to the ITER International Organization in Cadarache, France or to ITER Members worldwide on behalf of the Company. In rare instances an

  17. Stockpile Stewardship Quarterly Volume 1, Number 4

    National Nuclear Security Administration (NNSA)

    1, Number 4 * February 2012 Message from the Assistant Deputy Administrator for Stockpile Stewardship, Chris Deeney Defense Programs Stockpile Stewardship in Action Volume 1, Number 4 Inside this Issue 2 Applying Advanced Simulation Models to Neutron Tube Ion Extraction 3 Advanced Optical Cavities for Subcritical and Hydrodynamic Experiments 5 Progress Toward Ignition on the National Ignition Facility 7 Commissioning URSA Minor: The First LTD-Based Accelerator for Radiography 8 Publication

  18. LED Color Characteristics

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

    LED Color Characteristics Color quality is an important consideration when evaluating lighting products. This fact sheet reviews the fundamentals regarding light and color, summarizing the most important color issues related to white-light LED systems, including color consistency, stability, tuning, and rendering, as well as chromaticity. LED Emission Attributes Individual LED dies, often referred to as chips, emit light in a narrow range of wavelengths, giving the appearance of a monochromatic

  19. 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.

  20. Approximate resolution of hard numbering problems

    SciTech Connect (OSTI)

    Bailleux, O.; Chabrier, J.J.

    1996-12-31

    We present a new method for estimating the number of solutions of constraint satisfaction problems. We use a stochastic forward checking algorithm for drawing a sample of paths from a search tree. With this sample, we compute two values related to the number of solutions of a CSP instance. First, an unbiased estimate, second, a lower bound with an arbitrary low error probability. We will describe applications to the Boolean Satisfiability problem and the Queens problem. We shall give some experimental results for these problems.

  1. Probing lepton number violation on three frontiers

    SciTech Connect (OSTI)

    Deppisch, Frank F. [Department of Physics and Astronomy, University College London (United Kingdom)

    2013-12-30

    Neutrinoless double beta decay constitutes the main probe for lepton number violation at low energies, motivated by the expected Majorana nature of the light but massive neutrinos. On the other hand, the theoretical interpretation of the (non-)observation of this process is not straightforward as the Majorana neutrinos can destructively interfere in their contribution and many other New Physics mechanisms can additionally mediate the process. We here highlight the potential of combining neutrinoless double beta decay with searches for Tritium decay, cosmological observations and LHC physics to improve the quantitative insight into the neutrino properties and to unravel potential sources of lepton number violation.

  2. WIPP Documents - All documents by number

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

    Note: Documents that do not have document numbers are not included in this listing. Large file size alert This symbol means the document may be a large file size. All documents by number Common document prefixes DOE/CAO DOE/TRU DOE/CBFO DOE/WIPP DOE/EA NM DOE/EIS Other DOE/CAO Back to top DOE/CAO 95-1095, Oct. 1995 Remote Handled Transuranic Waste Study This study was conducted to satisfy the requirements defined by the WIPP Land Withdrawal Act and considered by DOE to be a prudent exercise in

  3. Battling bird flu by the numbers

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

    Battling bird flu by the numbers Battling bird flu by the numbers Lab theorists have developed a mathematical tool that could help health experts and crisis managers determine in real time whether an emerging infectious disease such as avian influenza H5N1 is poised to spread globally. May 27, 2008 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,

  4. Crude Oil Characteristics Research

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

    SAE Plan June 29, 2015 Page 1 Crude Oil Characteristics Research Sampling, Analysis and Experiment (SAE) Plan The U.S. is experiencing a renaissance in oil and gas production. The Energy Information Administration projects that U.S. oil production will reach 9.3 million barrels per day in 2015 - the highest annual average level of oil production since 1972. This domestic energy boom is due primarily to new unconventional production of light sweet crude oil from tight-oil formations like the

  5. The 17 GHz active region number

    SciTech Connect (OSTI)

    Selhorst, C. L.; Pacini, A. A.; Costa, J. E. R.; Gimnez de Castro, C. G.; Valio, A.; Shibasaki, K.

    2014-08-01

    We report the statistics of the number of active regions (NAR) observed at 17 GHz with the Nobeyama Radioheliograph between 1992, near the maximum of cycle 22, and 2013, which also includes the maximum of cycle 24, and we compare with other activity indexes. We find that NAR minima are shorter than those of the sunspot number (SSN) and radio flux at 10.7 cm (F10.7). This shorter NAR minima could reflect the presence of active regions generated by faint magnetic fields or spotless regions, which were a considerable fraction of the counted active regions. The ratio between the solar radio indexes F10.7/NAR shows a similar reduction during the two minima analyzed, which contrasts with the increase of the ratio of both radio indexes in relation to the SSN during the minimum of cycle 23-24. These results indicate that the radio indexes are more sensitive to weaker magnetic fields than those necessary to form sunspots, of the order of 1500 G. The analysis of the monthly averages of the active region brightness temperatures shows that its long-term variation mimics the solar cycle; however, due to the gyro-resonance emission, a great number of intense spikes are observed in the maximum temperature study. The decrease in the number of these spikes is also evident during the current cycle 24, a consequence of the sunspot magnetic field weakening in the last few years.

  6. Pennsylvania Number of Natural Gas Consumers

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

    1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 618 606 604 540 627 666 1967-2014 Industrial Number of Consumers 4,745 4,624 5,007 5,066 5,024 5,084 1987-2014...

  7. Washington Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    059,239 1,067,979 1,079,277 1,088,762 1,102,318 1,118,193 1987-2014 Sales 1,067,979 1,079,277 1,088,762 1,102,318 1,118,193 1997-2014 Commercial Number of Consumers 98,965 99,231...

  8. Kansas Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    855,454 853,842 854,730 854,800 858,572 861,092 1987-2014 Sales 853,842 854,730 854,779 858,546 861,066 1997-2014 Transported 0 0 21 26 26 2004-2014 Commercial Number of Consumers...

  9. Climate Zone Number 1 | Open Energy Information

    Open Energy Info (EERE)

    Zone Number 1 is defined as Very Hot - Humid(1A) with IP Units 9000 < CDD50F and SI Units 5000 < CDD10C Dry(1B) with IP Units 9000 < CDD50F and SI Units 5000 < CDD10C...

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

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

    2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.6 1.2 1.0 1.1 1.1 0.8 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Census Region and Division Northeast ...................................... 20.3 1.5 2.4 2.1 2.8 3.0 8.5 8.8 New

  11. Housing characteristics, 1987: Residential Energy Consumption Survey

    SciTech Connect (OSTI)

    Not Available

    1989-05-26

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

  12. Wafer characteristics via reflectometry

    DOE Patents [OSTI]

    Sopori, Bhushan L.

    2010-10-19

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

  13. Alaska Maximum Number of Active Crews Engaged in Seismic Surveying (Number

    Gasoline and Diesel Fuel Update (EIA)

    of Elements) Seismic Surveying (Number of Elements) Alaska Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 2 3 3 3 1 1 0 0 0 0 2001 0 0 0 0 2 2 0 0 0 0 0 0 2002 2 2 2 2 2 2 2 2 2 2 2 1 2003 0 0 2 2 2 2 2 2

  14. Oklahoma Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    924,745 914,869 922,240 927,346 931,981 937,237 1987-2014 Sales 914,869 922,240 927,346 931,981 937,237 1997-2014 Transported 0 0 0 0 0 1997-2014 Commercial Number of Consumers 94,314 92,430 93,903 94,537 95,385 96,004 1987-2014 Sales 88,217 89,573 90,097 90,861 91,402 1998-2014 Transported 4,213 4,330 4,440 4,524 4,602 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 439 452 430 382 464 489 1967-2014 Industrial Number of Consumers 2,618 2,731 2,733 2,872 2,958 3,063 1987-2014

  15. Sensitivity in risk analyses with uncertain numbers.

    SciTech Connect (OSTI)

    Tucker, W. Troy; Ferson, Scott

    2006-06-01

    Sensitivity analysis is a study of how changes in the inputs to a model influence the results of the model. Many techniques have recently been proposed for use when the model is probabilistic. This report considers the related problem of sensitivity analysis when the model includes uncertain numbers that can involve both aleatory and epistemic uncertainty and the method of calculation is Dempster-Shafer evidence theory or probability bounds analysis. Some traditional methods for sensitivity analysis generalize directly for use with uncertain numbers, but, in some respects, sensitivity analysis for these analyses differs from traditional deterministic or probabilistic sensitivity analyses. A case study of a dike reliability assessment illustrates several methods of sensitivity analysis, including traditional probabilistic assessment, local derivatives, and a ''pinching'' strategy that hypothetically reduces the epistemic uncertainty or aleatory uncertainty, or both, in an input variable to estimate the reduction of uncertainty in the outputs. The prospects for applying the methods to black box models are also considered.

  16. WIPP Site By The Numbers August 2015

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

    0 ft. By the Numbers The Waste Isolation Pilot Plant (WIPP) is a Department of Energy facility designed to safely isolate defense- related transuranic (TRU) waste from people and the environment. WIPP, which began waste disposal operations in 1999, is located 26 miles outside of Carlsbad, New Mexico. Waste temporarily stored at sites around the country is shipped to WIPP and permanently disposed in rooms mined out of an ancient salt formation below the surface. TRU waste destined for WIPP

  17. Stockpile Stewardship Quarterly, Volume 2, Number 1

    National Nuclear Security Administration (NNSA)

    1 * May 2012 Message from the Assistant Deputy Administrator for Stockpile Stewardship, Chris Deeney Defense Programs Stockpile Stewardship in Action Volume 2, Number 1 Inside this Issue 2 LANL and ANL Complete Groundbreaking Shock Experiments at the Advanced Photon Source 3 Characterization of Activity-Size-Distribution of Nuclear Fallout 5 Modeling Mix in High-Energy-Density Plasma 6 Quality Input for Microscopic Fission Theory 8 Fiber Reinforced Composites Under Pressure: A Case Study in

  18. Nevada Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Nevada Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 5 5 4 4 2000's 4 4 4 4 4 4 4 4 0 0 2010's 0 0 0 4 4 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next Release Date: 9/30/2016 Referring Pages: Number of Producing Gas

  19. Table B14. Number of Establishments in Building, Number of Buildings, 1999

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

    4. Number of Establishments in Building, Number of Buildings, 1999" ,"Number of Buildings (thousand)" ,"All Buildings","Number of Establishments in Building" ,,"One","Two to Five","Six to Ten","Eleven to Twenty","More than Twenty","Currently Unoccupied" "All Buildings ................",4657,3528,688,114,48,27,251 "Building Floorspace" "(Square Feet)" "1,001 to 5,000

  20. U.S. Natural Gas Number of Underground Storage Acquifers Capacity (Number

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

    of Elements) Acquifers Capacity (Number of Elements) U.S. Natural Gas Number of Underground Storage Acquifers Capacity (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 49 2000's 49 39 38 43 43 44 44 43 43 43 2010's 43 43 44 47 46 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Number of

  1. Modern technical solutions of gas-fired heating devices of household and communal use and analysis of their testing

    SciTech Connect (OSTI)

    Bodzon, L.; Radwan, W.

    1995-12-31

    A review of technical solutions for gas-fired heating devices for household and communal use in Poland is presented. Based upon the analysis it is stated that the power output of Polish and foreign boilers ranges between 9 and 35 kW. The carbon monoxide content in flue gases reaches (on average) 0.005 vol.%, i.e., it is much lower than the maximum permissible level. Temperature of flue gases (excluding condensation boilers and those with air-tight combustion chamber) ranges between 150 and 200{degrees}C and their heating efficiency reaches 87-93%. The best parameters are given for condensation boilers, however they are still not widespread in Poland for the high cost of the equipment and assembling works. Among the heaters, the most safe are convection devices with closed combustion chamber; their efficiency is also the highest. Thus, it is concluded that a wide spectrum of high efficiency heating devices with good combustion parameters are available. The range of output is sufficient to meet household and communal requirement. They are however - predominantly - units manufactured abroad. It is difficult to formulate the program aimed at the improvement of the technique of heating devices made in Poland, and its implementation is uncertain because the production process is broken up into small handicraft workshops.

  2. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  3. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  4. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 0 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 15.4 11.6 29.7 131 51 99.0 36 1,053 0.41 795 287 Census

  5. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 1 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 14.6 11.0 28.9 116 44 87.9 32 1,032 0.39 781 283 Census

  6. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 2 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 15.5 12.2 30.0 98 40 77.1 27 829 0.34 650 231 Census

  7. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 4 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 17.5 13.8 32.0 91 39 71.9 27 697 0.30 550 203 Census

  8. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 17.4 14.0 33.3 87 37 70.3 27 513 0.22 414 156 Census

  9. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 90 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 16.3 13.5 33.2 77 31 63.9 23 609 0.25 506 181 Census

  10. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 3 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 13.8 11.6 29.8 92 36 77.5 28 604 0.23 506 186 Census

  11. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

    questionnaires 7 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures Total per Floor- per Square per per per Total Total space (1) Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 13.2 11.0 23.2 97 46 81.1 31 694 0.33 578 224 Census

  12. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  13. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  14. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  15. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  16. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  17. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  18. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  19. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  20. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  1. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  2. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  3. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  4. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  5. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  6. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  7. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  8. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  9. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  10. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  11. Residential Buildings Historical Publications reports, data and housing

    Gasoline and Diesel Fuel Update (EIA)

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

  12. R93HC.PDF

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

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

  13. Property:NumberOfLEDSTools | Open Energy Information

    Open Energy Info (EERE)

    Name NumberOfLEDSTools Property Type Number Retrieved from "http:en.openei.orgwindex.php?titleProperty:NumberOfLEDSTools&oldid322418" Feedback Contact needs updating Image...

  14. Property:Number of Plants Included in Planned Estimate | Open...

    Open Energy Info (EERE)

    Number of Plants Included in Planned Estimate Jump to: navigation, search Property Name Number of Plants Included in Planned Estimate Property Type String Description Number of...

  15. Property:Number of Color Cameras | Open Energy Information

    Open Energy Info (EERE)

    Color Cameras Jump to: navigation, search Property Name Number of Color Cameras Property Type Number Pages using the property "Number of Color Cameras" Showing 25 pages using this...

  16. Experimental Stations by Number | Stanford Synchrotron Radiation

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

    Lightsource Experimental Stations by Number Beam Line by Techniques Photon Source Parameters Station Type Techniques Energy Range Contact Person Experimental Station 1-5 X-ray Materials Small-angle X-ray Scattering (SAXS) focused 4600-16000 eV Christopher J. Tassone Tim J. Dunn Experimental Station 2-1 X-ray Powder diffraction Thin film diffraction Focused 5000 - 14500 eV Apurva Mehta Charles Troxel Jr Experimental Station 2-2 X-ray X-ray Absorption Spectroscopy 5000 to 37000 eV Ryan Davis

  17. Health Code Number (HCN) Development Procedure

    SciTech Connect (OSTI)

    Petrocchi, Rocky; Craig, Douglas K.; Bond, Jayne-Anne; Trott, Donna M.; Yu, Xiao-Ying

    2013-09-01

    This report provides the detailed description of health code numbers (HCNs) and the procedure of how each HCN is assigned. It contains many guidelines and rationales of HCNs. HCNs are used in the chemical mixture methodology (CMM), a method recommended by the department of energy (DOE) for assessing health effects as a result of exposures to airborne aerosols in an emergency. The procedure is a useful tool for proficient HCN code developers. Intense training and quality assurance with qualified HCN developers are required before an individual comprehends the procedure to develop HCNs for DOE.

  18. Sensor Characteristics Reference Guide

    SciTech Connect (OSTI)

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

    2013-04-01

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

  19. CBECS Buildings Characteristics --Revised Tables

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

    End-Use Equipment Tables (27 pages, 151 kb) CONTENTS PAGES Table 33. Heating Equipment, Number of Buildings, 1995 Table 34. Heating Equipment, Floorspace, 1995 Table 35. Cooling Equipment,Number of Buildings, 1995 Table 36. Cooling Equipment, Floorspace, 1995 Table 37. Refrigeration Equipment, Number of Buildings and Floorspace, 1995 Table 38. Water-Heating Equipment, Number of Buildings and Floorspace, 1995 Table 39. Lighting Equipment, Number of Buildings, 1995 Table 40. Lighting Equipment,

  20. Nebraska Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Nebraska Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 15 1990's 11 12 22 59 87 87 88 91 95 96 2000's 98 96 106 109 111 114 114 186 322 285 2010's 276 322 270 357 310 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next

  1. Oregon Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Oregon Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 18 1990's 19 16 16 18 19 17 18 17 15 19 2000's 17 20 18 15 15 15 14 18 21 24 2010's 26 24 27 26 28 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next Release Date:

  2. Maryland Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Maryland Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 8 1990's 7 7 9 7 7 7 8 8 8 8 2000's 7 7 5 7 7 7 7 7 7 7 2010's 7 8 9 7 7 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next Release Date: 9/30/2016 Referring Pages:

  3. Missouri Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Missouri Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 4 1990's 8 6 5 8 12 15 24 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 0 53 100 26 28 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next Release Date: 9/30/2016 Referring

  4. U.S. Natural Gas Number of Commercial Consumers - Transported (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Transported (Number of Elements) U.S. Natural Gas Number of Commercial Consumers - Transported (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 220,655 410,695 2000's 433,944 464,412 475,420 489,324 495,586 499,402 539,557 2010's 716,692 763,597 837,652 881,196 885,257 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next

  5. Alaska Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Alaska Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 108 1990's 111 110 112 113 104 100 102 141 148 99 2000's 152 170 165 195 224 227 231 239 261 261 2010's 269 277 185 159 170 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016

  6. Arizona Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Arizona Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3 1990's 5 6 6 6 6 7 7 8 8 8 2000's 9 8 7 9 6 6 7 7 6 6 2010's 5 5 5 5 5 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next Release Date: 9/30/2016 Referring Pages:

  7. Illinois Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Illinois Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241 1990's 356 373 382 385 390 372 370 372 185 300 2000's 280 300 225 240 251 316 316 43 45 51 2010's 50 40 40 34 36 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next

  8. South Dakota Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) South Dakota Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 53 1990's 54 54 38 47 55 56 61 60 59 60 2000's 71 68 69 61 61 69 69 71 71 89 2010's 102 100 95 65 68 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next Release Date:

  9. Tennessee Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Tennessee Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 700 1990's 690 650 600 505 460 420 2000's 380 350 400 430 280 400 330 305 285 310 2010's 230 210 212 1,089 1,024 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next

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

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

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

  11. Michigan Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    3,169,026 3,152,468 3,153,895 3,161,033 3,180,349 3,192,807 1987-2014 Sales 2,952,550 2,946,507 2,939,693 2,950,315 2,985,315 1997-2014 Transported 199,918 207,388 221,340 230,034 207,492 1997-2014 Commercial Number of Consumers 252,017 249,309 249,456 249,994 250,994 253,127 1987-2014 Sales 217,325 213,995 212,411 213,532 219,240 1998-2014 Transported 31,984 35,461 37,583 37,462 33,887 1998-2014 Average Consumption per Consumer (Thousand Cubic Ft.) 649 611 656 578 683 736 1967-2014 Industrial

  12. U.S. Maximum Number of Active Crews Engaged in Seismic Surveying (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) U.S. Maximum Number of Active Crews Engaged in Seismic Surveying (Number of Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 0 0 62 63 59 63 58 61 59 63 62 65 2001 61 61 63 65 64 60 58 56 54 58 59 58 2002 54 57 54 50 51 50 52 50 56 57 50 43 2003 40 41 41 40 38 39 41 43 39 39 38 42 2004 43 45 45 45 44 49 48 49 48 48 49 50 2005 52 53 51 50 55 57 54 55 56 57 57 58 2006 55 57 59 58 58 57

  13. Alaska Maximum Number of Active Crews Engaged in Seismic Surveying (Number

    Gasoline and Diesel Fuel Update (EIA)

    of Elements) Seismic Surveying (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 13 4 23 12

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

    SciTech Connect (OSTI)

    Bernstad, A.; Cour Jansen, J. la

    2012-05-15

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

  15. Property:Other Characteristics | Open Energy Information

    Open Energy Info (EERE)

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

  16. Process for the utilization of household rubbish or garbage and other organic waste products for the production of methane gas

    SciTech Connect (OSTI)

    Hunziker, M.; Schildknecht, A.

    1985-04-16

    Non-organic substances are separated from household garbage and the organic substances are fed in proportioned manner into a mixing tank and converted into slurry by adding liquid. The slurry is crushed for homogenization purposes in a crushing means and passed into a closed holding container. It is then fed over a heat exchanger and heated to 55/sup 0/ to 60/sup 0/ C. The slurry passes into a plurality of reaction vessels in which the methane gas and carbon dioxide are produced. In a separating plant, the mixture of gaseous products is broken down into its components and some of the methane gas is recycled by bubbling it through both the holding tank and the reaction tank, the remainder being stored in gasholders. The organic substances are degraded much more rapidly through increasing the degradation temperature and as a result constructional expenditure can be reduced.

  17. Emissions of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans from the open burning of household waste in barrels

    SciTech Connect (OSTI)

    Lemieux, P.M.; Lutes, C.C.; Abbott, J.A.; Aldous, K.M.

    2000-02-01

    Backyard burning of household waste in barrels is a common waste disposal practice for which pollutant emissions have not been well characterized. This study measured the emissions of several pollutants, including polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDDs/PCDFs), from burning mixtures designed to simulate waste generated by a recycling and a nonrecycling family in a 208-L (55-gal) burn barrel at the EPA's Open Burning Test Facility. This paper focuses on the PCDD/PCDF emissions and discusses the factors influencing PCDD/PCDF formation for different test burns. Four test burns were made in which the amount of waste placed in the barrel varied from 6.4 to 13.6 kg and the amount actually burned varied from 46.6% to 68.1%. Emissions of total PCDDs/PCDFs ranged between 0.0046 and 0.48 mg/kg of waste burned. Emissions are also presented in terms of 2,3,7,8-TCDD toxic equivalents. Emissions of PCDDs/PCDFs appear to correlate with both copper and hydrochloric acid emissions. The results of this study indicate that backyard burning emits more PCDDs/PCDFs on a mass of refuse burned basis than various types of municipal waste combustors (MWCs). Comparison of burn barrel emissions to emissions from a hypothetical modern MWC equipped with high-efficiency flue gas cleaning technology indicates that about 2--40 households burning their trash daily in barrels can produce average PCDD/PCDF emissions comparable to a 182,000 kg/day (200 ton/day) MWC facility. This study provides important data on a potentially significant source of emissions of PCDDs/PCDFs.

  18. CBECS Buildings Characteristics --Revised Tables

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

    Energy Sources and End Use Tables (27 pages, 152 kb) CONTENTS PAGES Table 18. Energy Sources, Number of Buildings, 1995 Table 19. Energy Sources, Floorspace, 1995 Table 20. Energy End Uses, Number of Buildings and Floorspace, 1995 Table 21. Space-Heating Energy Sources, Number of Buildings, 1995 Table 22. Space-Heating Energy Sources, Floorspace, 1995 Table 23. Primary Space-Heating Energy Sources, Number of Buildings, 1995 Table 24. Primary Space-Heating Energy Sources, Floorspace, 1995 Table

  19. Hawaii Number of Natural Gas Consumers

    Gasoline and Diesel Fuel Update (EIA)

    Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2010 0 0 0 0 0 0 0 0 0 0 0 0 2011 0 0 0 0 0 0 0 0 0 0 0 0 2012 0 0 0 0 0 0 0 0 0 0 0 0 2013 1 1 1 1 1 1 1 1 1 1 1 1 2014 1 1 1 1 1 1 1 1 1 1 1 1 2015 0 0 0 0 0 1 1 1 1 1 1 1 2016 1 1 1 1 0 0

    25,466 25,389 25,305 25,184 26,374 28,919 1987-2014 Sales 25,389 25,305 25,184 26,374 28,919 1998-2014 Commercial Number of Consumers 2,535 2,551 2,560 2,545 2,627 2,789 1987-2014 Sales 2,551 2,560 2,545 2,627 2,789 1998-2014 Average Consumption per

  20. New Jersey Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) New Jersey Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 200,387 206,261 212,496 1990's 217,548 215,408 212,726 215,948 219,061 222,632 224,749 226,714 234,459 232,831 2000's 243,541 212,726 214,526 223,564 223,595 226,007 227,819 230,855 229,235 234,125 2010's 234,158 234,721 237,602 236,746 240,083 - = No Data Reported; -- = Not Applicable; NA = Not

  1. New Jersey Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) New Jersey Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6,265 6,123 6,079 1990's 5,976 8,444 11,474 11,224 10,608 10,362 10,139 17,625 16,282 10,089 2000's 9,686 9,247 8,473 9,027 8,947 8,500 8,245 8,036 7,680 7,871 2010's 7,505 7,391 7,290 7,216 7,157 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  2. New York Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) New York Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 23,276 24,654 27,426 1990's 25,008 28,837 28,198 23,833 21,833 22,484 15,300 23,099 5,294 6,136 2000's 6,553 6,501 3,068 2,984 2,963 3,752 3,642 7,484 7,080 6,634 2010's 6,236 6,609 5,910 6,311 6,313 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  3. Ohio Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Ohio Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 34,450 1990's 34,586 34,760 34,784 34,782 34,731 34,520 34,380 34,238 34,098 33,982 2000's 33,897 33,917 34,593 33,828 33,828 33,735 33,945 34,416 34,416 34,963 2010's 34,931 46,717 35,104 32,664 32,967 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  4. Oklahoma Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Oklahoma Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 27,443 1990's 24,547 28,216 28,902 29,118 29,121 29,733 29,733 29,734 30,101 21,790 2000's 21,507 32,672 33,279 34,334 35,612 36,704 38,060 38,364 41,921 43,600 2010's 44,000 41,238 40,000 39,776 40,070 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  5. Pennsylvania Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Pennsylvania Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 30,000 1990's 30,300 31,000 31,000 31,100 31,150 31,025 31,792 32,692 21,576 23,822 2000's 36,000 40,100 40,830 42,437 44,227 46,654 49,750 52,700 55,631 57,356 2010's 44,500 54,347 55,136 53,762 70,400 - = No Data Reported; -- = Not Applicable; NA = Not Available; W

  6. Alabama Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Alabama Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,701 1990's 2,362 3,392 3,350 3,514 3,565 3,526 4,105 4,156 4,171 4,204 2000's 4,359 4,597 4,803 5,157 5,526 5,523 6,227 6,591 6,860 6,913 2010's 7,026 7,063 6,327 6,165 6,118 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure

  7. Indiana Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Indiana Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,310 1990's 1,307 1,334 1,333 1,336 1,348 1,347 1,367 1,458 1,479 1,498 2000's 1,502 1,533 1,545 2,291 2,386 2,321 2,336 2,350 525 563 2010's 620 914 819 921 895 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  8. Kansas Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Kansas Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 13,935 1990's 16,980 17,948 18,400 19,472 19,365 22,020 21,388 21,500 21,000 17,568 2000's 15,206 15,357 16,957 17,387 18,120 18,946 19,713 19,713 17,862 21,243 2010's 22,145 25,758 24,697 23,792 24,354 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  9. Kentucky Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Kentucky Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 11,248 1990's 11,713 12,169 12,483 12,836 13,036 13,311 13,501 13,825 14,381 14,750 2000's 13,487 14,370 14,367 12,900 13,920 14,175 15,892 16,563 16,290 17,152 2010's 17,670 14,632 17,936 19,494 19,256 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  10. Louisiana Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Louisiana Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 16,309 1990's 16,889 15,271 13,512 15,569 12,958 14,169 15,295 14,958 18,399 16,717 2000's 15,700 16,350 17,100 16,939 20,734 18,838 17,459 18,145 19,213 18,860 2010's 19,137 21,235 19,792 19,528 19,251 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  11. Michigan Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Michigan Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,207 1990's 1,438 2,620 3,257 5,500 6,000 5,258 5,826 6,825 7,000 6,750 2000's 7,068 7,425 7,700 8,600 8,500 8,900 9,200 9,712 9,995 10,600 2010's 10,100 11,100 10,900 10,550 10,500 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  12. Mississippi Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Mississippi Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 543 1990's 585 629 507 620 583 535 568 560 527 560 2000's 997 1,143 979 427 1,536 1,676 1,836 2,315 2,343 2,320 2010's 1,979 5,732 1,669 1,967 1,645 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  13. Montana Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Montana Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,700 1990's 2,607 2,802 2,890 3,075 2,940 2,918 2,990 3,071 3,423 3,634 2000's 3,321 4,331 4,544 4,539 4,971 5,751 6,578 6,925 7,095 7,031 2010's 6,059 6,477 6,240 5,754 5,754 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure

  14. Wyoming Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Wyoming Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,431 1990's 2,600 2,821 3,111 3,615 3,942 4,196 4,510 5,160 5,166 4,950 2000's 9,907 13,978 15,608 18,154 20,244 23,734 25,052 27,350 28,969 25,710 2010's 26,124 26,180 22,171 22,358 22,091 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  15. U.S. Natural Gas Number of Industrial Consumers - Sales (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Gas and Gas Condensate Wells (Number of Elements) U.S. Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 262,483 1990's 269,790 276,987 276,014 282,152 291,773 298,541 301,811 310,971 316,929 302,421 2000's 341,678 373,304 387,772 393,327 406,147 425,887 440,516 452,945 476,652 493,100 2010's 487,627 514,637 482,822 484,994 514,786 - = No Data Reported; -- = Not Applicable; NA

  16. U.S. Natural Gas Number of Industrial Consumers - Transported (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Transported (Number of Elements) U.S. Natural Gas Number of Industrial Consumers - Transported (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 49,014 71,281 2000's 75,826 64,052 62,738 62,698 57,672 59,773 58,760 2010's 63,611 64,749 67,551 69,164 69,953 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  17. U.S. Natural Gas Number of Residential Consumers - Sales (Number of

    Gasoline and Diesel Fuel Update (EIA)

    (Number of Elements) U.S. Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 47,710,444 48,474,449 49,309,593 1990's 50,187,178 51,593,206 52,331,397 52,535,411 53,392,557 54,322,179 55,263,673 56,186,958 57,321,746 58,223,229 2000's 59,252,728 60,286,364 61,107,254 61,871,450 62,496,134 63,616,827 64,166,280 64,964,769 65,073,996 65,329,582 2010's 65,542,345 65,940,522 66,375,134 66,812,393

  18. U.S. Natural Gas Number of Residential Consumers - Transported (Number of

    Gasoline and Diesel Fuel Update (EIA)

    Elements) Transported (Number of Elements) U.S. Natural Gas Number of Residential Consumers - Transported (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 252,783 801,264 2,199,519 2000's 2,978,319 3,576,181 3,839,809 4,055,781 3,971,337 3,829,303 4,037,233 2010's 5,274,697 5,531,680 6,364,411 6,934,929 7,005,081 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  19. Arkansas Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) Arkansas Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,830 1990's 2,952 2,780 3,500 3,500 3,500 3,988 4,020 3,700 3,900 3,650 2000's 4,000 4,825 6,755 7,606 3,460 3,462 3,814 4,773 5,592 6,314 2010's 7,397 8,388 8,538 9,843 10,150 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  20. California Natural Gas Number of Gas and Gas Condensate Wells (Number of

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

    Elements) Gas and Gas Condensate Wells (Number of Elements) California Natural Gas Number of Gas and Gas Condensate Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,214 1990's 1,162 1,377 1,126 1,092 1,261 997 978 930 847 1,152 2000's 1,169 1,244 1,232 1,249 1,272 1,356 1,451 1,540 1,645 1,643 2010's 1,580 1,308 1,423 1,335 1,118 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of